DIMENSIONS OF CUSTOMER SERVICE QUALITY - AN EMPIRICAL STUDY OF DOMESTIC AIRLINE INDUSTRY IN INDIA
ABSTRACT OF THE THESIS SUBMITTED FOR THE AWARD OF THE DEGREE OF Ph. D. (BUSINESS ADMINISTRATION)
BY . VIPPAN RAJ DUTTT
Under the Supervision of Dr. Mohammed Naved Khan' ; Dr. S C Bansal Senior Lecturer ' , » Associate Professor Department of Business Administration Indian Institute of Management Faculty of Mgt. Studies & Research Lucknow Aligarh Muslim University, Allgarh (India) (India) (Internal Advisor) (External Advisor)
DEPARTMENT OF BUSINESS ADMINISTRATION FACULTY OF MANAGEMENT STUDIES & RESEARCH ALIGARH MUSLIM UNIVERSITY ALIGARH (INDIA) 2008 ABSTRACT
Introduction
Civil Aviation represents one of the biggest industries worldwide with global airline revenues exceeding US$ 485 billion in 2007 (lATA, 2008b). The industry has moved towards liberalisation in the ownership of national carriers, capacity sharing, price controls and market access, leading to greater competition among airlines. In the de-regulated environment, the customer has many choices, if the first airline does not measure up-to the desired standards of service. Focus on service quality is the need of the hour if the airlines aspire to improve market share and further enhance financial perforniance in domestic and international markets.
The airline industry has been a pioneer in the innovative use of Information Technology (IT) (Ghobrial & Trusilov, 2005). E-commerce and IT are changing the nature of the airline business. The dramatic growth of web and self-service technologies facilitate simplified passenger travel involving e-ticketing, automated check-in, common-user self-service kiosks and other passenger, services (Shon, Chen & Chang, 2003). Growth in the air traffic in recent years is due to the spread of low cost service. The Full Service Carriers (FSCs) are facing strong competition from Low Cost Carriers (LCCs). Successful LCCs undermine the economics of FSCs by capturing a growing market share and forcing the latter to drop their fares (Doganis, 2006).
The value proposition for passengers is changing. Travelers expect convenience and connectivity. Simplifying the business and focusing on value is critical. This is leading the way in the air transports industry's evolution towards a low cost industry and will enhance the passengers' travel experience.
Civil Aviation Industry in India
Air transport has a significant role to play in a vast country like India with major industrial and commercial centres located far apart. The domestic civil aviation activities in India can be broadly classified into three categories - regulatory-cum- developmental, infrastructural and air transport services (Planning Commission, 2001). The Ministry of Civil Aviation (MoCA) and its bodies, namely, Directorate General of Civil Aviation (DGCA) and Bureau of Civil Aviation Security (BCAS) look after regulatory and developmental aspect of civil aviation in India. Airport Authority of India (AAI) is responsible for providing infrastructural facilities. Air transport services are provided by scheduled airlines in public and private sector.
In the public sector, Indian Airlines and Alliance Air provide passenger transport and cargo handling services in the country. In the private sector, there are eight scheduled airlines (passenger), namely, Jet Airways, Air Sahara (now JetLite), Deccan Aviaition, Spice Jet, Go Airways, Kingfisher Airlines, Paramount Airways and Indigo operating on the domestic sector providing passengers with a wide choice. Presently, Indian Airlines, Jet Airways and Kingfisher are fiill service carriers, whereas JetLite (erstwhile Air Sahara), Deccan, Spicejet, Paramount, IndiGo and Go Air fall in the category of low cost carriers. Table 1 gives the profile of domestic airlines operating in India.
The civil aviation sector in the country has witnessed a boom largely due to the open sky policy of increased liberalization in both domestic and intemational "sectors. Domestic airlines carried a total of 43.2 million passengers during 2007 compared to 32.7 million in the preceding year, resulting in growth of about 33 per cent (Sinha, 2008). Moreover, the scheduled domestic air services are now available at about 82 airports as against 75 in 2006 (MoCA, 2007a).
Phenomenal growth in the airline sector in India throws up exciting opportunities and, at the same time, poses its own challenges. According to lATA, Indian carriers could post US$ 1.5 billion in losses in 2008 (Bisignani, 2008b). The global crisis resulting from high oil prices and declining traffic is hitting India hard. Consolidation and restructuring are the way to go for Indian carriers to beat losses and stay afloat.
Review of Literature
Much of the research in services marketing centers on understanding services and service quality from customer's point of view (Brown & Bitner, 2006). The conceptualization of service quality, its relationship to satisfaction and measurement methods has been the central theme of literature on the subject. 4' _ Si .- o 4 0-3 Ci ft
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•4«: o ** "I o ^ ri W 5 ^. M o tx 01) _^ _ 3 •c -< = a •St S a 4, <^ ©•2 |i OL' Parasuraman, Zeithaml & Berry (1988) provided the notion of 'gaps' between the expectations of service and subsequent perceptions of what is delivered. These gaps are located throughout the organization between frontline staff, customers and managers.
The identification often dimensions of service quality by these researchers, and later refined to five - Reliability, Assurance, Tangibles, Empathy and Responsiveness (RATER) - has dominated the literature in the field of service quality. Much of the research in this area, since introduction of SERVQUAL in 1988, has been concerned with validating or challenging the construct. The development of SERVQUAL by Parasuraman et al. (1988) as a generaiisable measure of service quality was a seminal contribution that has been adapted and widely used across service industries - Airline (Sultan & Simpson, 2000), Banking (Aga & Safakli, 2007), Education (Arambewela & Hall, 2006), Health (Mostafa, 2005), Hotel (Juwaheer, 2004), Information System & E-Commerce (vanRiel & Semeijn, 2003), Internal Marketing ((Frost & Kumar, 2000), Public Services (Donnelly, Kerr, Rimmer & Shiu, 2006), Retail (Zhao, Bai & Hui, 2002), Tourism & Hospitality (Home, Peter & Pikkemaat, 2005), and Transportation (Cavana, Corbett & Lo, 2007) -around the world.
Conceptual models in service quality enable management to identify quality problems and thus help in planning for the launch of a quality improvement program thereby improving the efficiency, profitability and overall performance. The study examines eight different service quality models reported in the literature: 1. The Disconfirmation Model of Service Quality 2. Nordic Service Quality Model 3. Kano' s Model of Customer Satisfaction 4. The Gaps Model of Service Quality 5. Performance Only Model of Service Quality 6. Six-Sigma Model of Service Quality 7. Internal Service Quality Model 8. Customer Equity Framework
Researchers have examined the service quality of airline industry post deregulation in US, Europe and Asia. These papers focus primarily on measuring the performance of airlines using SERVQUAL instrument and relevance of SERVQUAL and SERVPERF scales to airline industry. Researchers have also
triBSfe employed Structural Equation Modelling (SEM) to investigate the effects of individual dimensions of airline service quality (Park, Robertson & Wu, 2005, 2006).
Research has been carried out to study impact of IT in enhancing customer experience (Baker, 2007). Usage of technology in the area of reservation, baggage handling, customer relationship, frequent flyer is covered extensively. New technology interface like internet, RFID, self service have added value to the passenger services (Wyld, Jones and Totten, 2005; Karp, 2007).
Impact of LCC worldwide on the efficiency, competition and industry structure has been covered in detail in literature reviewed (Doganis, 2006; Hunter, 2006). Of late, LCCs are moving away from original low cost model to differentiate from competition and provide higher value to the passenger (Sobie, 2007).
In India, the aviation sector, from research point of view is largely unexplored. There are not many studies on domestic civil aviation in India. Though some studies have been conducted in recent years, including those by the researcher (Naresh Chandra Committee Report, 2003; Sarkar & Baisya, 2005; Khart, Dutt & Bansal, 2007a, 2007c; Bansal, Khan & Dutt, 2008a), the impact of liberalisation in domestic aviation sector needs to be further explored.
Need for the Study
This study is an in-depth empirical investigation that seeks to establish a method to predict service quality in domestic airline industry in India. The motivation for this work was provided by a lack of any useful instrument to predict and evaluate service quality with specific reference to airline industry in India. It also attempts to measure the gap between expectations and perceptions of the passengers so that strategies can be implemented to improve the quality of service and increase airlines profitability and market share.
Some of the key questions facing airline marketers are (i) identification of attributes that influence customers' choice in airlines, (ii) methodology adopted by the customers to rate the airlines on various parameters, (iii) importance of service quality in purchase intentions, and (iv) system of assessing the satisfaction of an airlme customer. This assessment is crucial because it has major implication for business performance. The findings of the study, it is expected, will help domestic
5 airlines to re-look their customer service measurement systems and mark relative importance of various attributes vis-a-vis various customer segments. It shall also help in carrying out a comparative analysis of the performance of the domestic airlines on the identified service attributes.
Although, airlines have extensively deployed IT to improve their service profile, yet there is a need to evolve a model of service parameters that airlines could adopt in order to leverage IT to their advantage. The research also tries to measure the impact of IT in airline service delivery in Indian scenario.
LCCs are a new phenomenon in India, and they are making attempts to deploy effective low cost solutions extensively for providing service to the passengers. The present work attempts to study their performance from the customer's perspective. The study will also attempt to find out the level of acceptability of low cost business model amongst the airline passengers in India.
Scope of the Study The study covers the following four categories of airlines: • Full Service Carriers - Public Sector, which includes Air India (Domestic) (erstwhile Indian Airlines and Alliance Air). • Full Service Carriers - Private Sector, which includes Jet Airways, Jetlite (erstwhile Air Sahara now taken over by Jet Airways) and Kingfisher Airlines. • Low Cost Carriers which include Deccan (now taken over by Kingfisher Airlines), Spicejet, Paramount, IndiGo and Go Air • International Carriers operating to / from India, which include Cathay Pacific, Emirates, Gulf Airways, Singapore Airlines, Thai Airways, Air Lanka, British Airways, Air India and Korean Airlines.
Research Objectives
The broad objectives of the study can be grouped into four categories:
I: Developing an instrument for measuring service quality > Investigate the extent of applicability of the SERVQUAL instrument to the airline industry in India > Compare service expectations; perceptions and the gaps using tlie SERVQUAL scale > If required, to develop a reliable and valid instrument for measuring various dimensions of service quality in airline industry
II: Investigating service quality in domestic airline industry > Understanding the dimension of services valued by the passengers > To assess satisfaction level of customers on various dimensions of services > Compare the quality of services being offered by various airlines
III: Investigating acceptability of Low Cost Model > To map out the preference of airline passengers for the Low Cost Model iV: Assessing role of IT in airline service delivery > To generate a profile of IT based services being offered by three categories of airlines (i.e. FSC - Public, FSC - Private and LCC) > To map out the passenger preferences for the IT based services > To study the impact of IT on various dimensions of customer service quality
Research Hypotheses
Based on extant literature and objectives of the study, hypotheses were framed and they have been placed under three groups. The first group of hypotheses (HI to HI 0) were developed to measure the overall difference in expectations and perceptions of passengers towards service quality provided by the airlines. The second group of hypotheses (HI 1 to HI4) are related to the impact of IT on passenger services. The third and the last group of hypotheses (HI 5 to HIS) are related to the acceptability of low cost no frills model in India.
Group I: Hypotheses related to service quality in airline industry Hoi: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis 'Tangibility - Support Services' among different categories of airlines. H02: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis 'Tangibility - Additional Support Services' among different categories of airlines. Hoa: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis 'Tangibility - Flight' among different categories of airlines. H04: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis Reliability among different categories of airlines. H05: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis Empathy among different categories of airlines. H06: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis Responsiveness among different categories of airlines. Ho?: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis Assurance among different categories of airlines. Ho8". Significant differences do not exist in the mean scores of the customers' expected service quality among different categories of airlines. H09: Significant differences do not exist in the mean scores of the customers' perceived service quality among different categories of airlines. Hio: Significant differences do not exist in the mean scores of the customers' perceived and expected service quality among different categories of airlines.
Group II: Hypotheses related to Information Technology and service delivery Hii: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines for improvement in satisfaction levels vis-a-vis Flight Support Services (FSS) due to use of IT. H12: Significant differences do not exist in the mean scores of perceptions of passerigers of different categories of airlines for improvement in satisfaction levels vis-a-vis In-Flight Services (IFS) due to use of IT. H13: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding improvement in satisfacfion levels vis-a-vis Customer Support Services (CSS) due to use of IT. Hi4: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding IT adding benefits to customer services.
Group III: Hypotheses related to Low Cost No Frills Model His: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding acceptability of reduction in Flight Support Services (FSS) if it leads to reduction in price of ticket. Hie: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding acceptability of reduction in In-Flight Services (FSS) if it leads to reduction in price of Ticket. H17: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding acceptability of reduction in Customer Support Services (FSS) if it leads to reduction in price of Ticket. His: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding acceptability of Low Cost Model.
One way Analysis of Variance (ANOVA) was used for testing the hypotheses. All of the evaluation uses a significance level of a =0.05.
Research Instrument
The research instrument was designed to measure three key issues:
> Service quality in airline industry, > Impact ofIT in service delivery, and > Acceptability of low-cost no-frills airline service model in India.
Service quality was measured using 6 service quality dimensions and 30 measurement items. The questionnaire for passenger and airline staff is primarily based on SERVQUAL model. Table 2 outlines the airline service quality dimensions explored in the study.
Tangibility dimension was modified to reflect unique characteristics of airline service industry and was divided into two sub-dimensions: > Tangibility - Support Services containing 5 items, and > Tangibility - Flight containing 7 items
Satisfaction and Loyalty were measured using two items each. The instrument utilized a 7-point Likert scale anchored with end points labelled as strongly agree (7) and strongly disagree (1).
Table 2: Airline Service Quality - Operationalization of Variables DimensionA^ariable Service Quality Construct / Parameters Parameter Reference (Questionnaire) Tangibility - Visually Appealing Physical Facilities GBl/GPl/GGl Support Services Vast Sales and Support Network GE2/GP2/GG2 (TSS) Vast Network of Destinations GE3/ GP3/ GG3 Economical Airfare and Discount Schemes GE4/ GP4/ GG4 Web-site and Call Center usage GE5/GP5/GG5 Tangibility - Flight Modem Aircraft with up-to-date Facilities GE6/ GP6/ GG6 (TF) Neat Well Dressed and Visually Appealing Staff GE7/ GP7/ GG7 Seat in Flight of Choice GE8/ GP8/ GG8 Hassle freeCheck-i n and Boarding GE9/ GP9/ GG9 Efficient Baggage Handling Mechanism GEIO/GPIO/GGIO Excellent Quality In-Flight Services GEll/GPll/GGll Multiple Meal Options of High Quality GE12/GP12/GG12 Reliability Special Need Customers GE13/GP13/GG13 (REL) Problems due to Critical Incidents GE14/GP14/GG14 Meet Time Commitment GE16/GP16/GG16 Keep Error Free Records GE17/GP17/GG17 Perform Service right the first time GE27/ GP27/ GG27 Responsiveness Prompt Service to Customers GE19/GP19/GG19 (RESP) Always Willing to Help Customers GE20/ GP20/ GG20 Staff Behavior should Instill Confidence GE22/ GP22/ GG22 Keep Customer informed about time of Service GE28/ GP28/ GG28 Staff never too busy to respond to customer's request GE29/ GP29/ GG29 Assurance Safe Planes and Facilities During Journey GE23y GP23/ GG23 (ASS) Consistently Courteous Staff GE24/ GP24/ GG24 Knowledge to Answer Customers' Queries GE25/GP25/GG25 Individual Attention to Customer GE26/GP26/GG26 Empathy Staff gives Personal Attention to Customer GE15/GP15/GG15 (EMP) Customer's Best Interest at Heart GE18/GP18/GG18 Understand Specific Needs of Customers GE21/GP21/GG21 Convenient Flight Schedules GE30/ GP30/ GG30 Satisfaction Overall Perception that primary airline satisfy GPM (SAT) customer's need GAP between overall Perception and Expectation GGM that primary airline satisfy customer's need Loyalty Continue flying primary airline El (TOY) recommend primary airline to friends and family E2
Key:- GE: General Expectation; GP: General Perception; GG: Gap
Measurement of 'Impact of IT in service delivery' and 'Acceptability of low-cost no-frills airline service model in India' were divided into Flight Support Services,
10 In-Flight Services and Customer Support Services. Table 3 and 4 outlines the dimensions used to study impact of IT in service delivery and acceptability of low- cost no-frills airline service model in India respectively.
Table 3: Role of IT \n Airline Service Delivery - Operationalization of Variables Variable Construct / Parameters Parameter Reference (Questionnaire) Flight Support Reservation and Ticketing CIA Services Check-in and Boarding CIB (IT-FSS) Baggage Handling CIC In Flight Services In-Flight Service and Facilities CID (IT-IFS) Catering / Meals CIE Customer Support Customer Complaint Handling CIF Services Customer Relationship Management CIG (IT-CSS) Frequent Flyer Program cm
Table 4: Low Cost No Frills Model - Operationalization of Variables Variable Construct / Parameters Parameter Reference (Questionnaire) Flight Support Point to Point Service B2 Services More dependency on Internet for ticket sale. B3 (LCC-FSS) Limited Staff & Cabin Crew B4 Increase in Minimum Reporting Time B5 Increase in Baggage Delivery Time B8 In Flight Services Single Class Flight Bl (LCC-IFS) Paid In-Flight Service and Meals B6 In-Flight Advertisements B7 Customer Increase in Customer Complaint Handling B9 Support Services Time (LCC-CSS) No Frequent Flyer Program BIO Company Web Site as main point of contact Bll No Refund Policy B12
Respondents were also asked questions related to demographics such as gender, highest qualification, age group, occupation, annual income bracket and flying experience.
The research instrument was developed in three stages: Stage 1 Identification of constructs and development of draft questionnaire Stage 2 Modification and refining of draft questionnaire Stage 3 Pilot testing
11 Sampling Procedure
Population: The target population for this study was defined as individuals having flown on domestic air carrier at the time the survey was conducted.
Sampling frame: Due to privacy and security concerns, it is practically not possible to obtain list of passengers who have flown via domestic airlines in India. Thus, the sample frame comprised real airline passengers waiting to board their flights at domestic terminals at Indira Gandhi International Airport, Delhi (IGIA); Sardar Vallabhbhai Patel International Airport at Ahmedabad; Chatrapati Shivaji International Airport at Mumbai and Bangalore Airport.
Sampling method: The required data was obtained using intercept technique from real airline passengers waiting to board their flights at aforesaid domestic terminals. It should be noted that the airports covered are the busiest in their respective sectors' and thus expected to provide an unbiased representative sample. The data was collected from March 2006 to Feb 2007.
Sample size: The data analysis technique employed in this research is Structural Equation Modeling (SEM), which is very sensitive to sample size and less stable when estimations are made based on small samples. Thus, it was decided to target a total of around 500 respondents from the four major metros of the country.
Final sample: Total usable passenger responses received were 471. It included 171 FSC - Public, 169 FSC - Private, 80 LCC and 51 Intemational carrier passengers. Of these. New Delhi accounted for around 40%, Mumbai 30%, Bangalore 20% and Ahmedabad 10%. The total usable responses received from airline staff were 63.
' As per Airport Authority of India, domestic passengers handled during 2006-07 at Delhi, Ahmedabad, Mumbai and Bangalore airport were 13.79, 2.09, 14.90 and 6.86 million, respectively.
12 Hypothesized Structural Model
The conceptual model developed by the researcher for the study is depicted below in Exhibit 1:
Exhibit 1: Hypothesized Structural Model
Schema of Analysis
Data analysis starts with profile of the sample. A preliminary screening of the data as well as descriptive and correlation analysis was carried out. Descriptive statistics including minimum, maximum, means, range, standard deviation and variance were obtained for the interval-scaled variables. The multi-item scales were evaluated for reliability, unidimensionality, and validity using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) as per the approach recommended by
13 Anderson and Gerbing (1988). That is, first the measurement model was estimated followed by structural model using LISREL 8.50. Measurement model estimated the unidimensionality, reliability and validity of each construct while structural model involved estimating the relation between independent (exogenous) and dependent (endogenous) variables. Measurement items remaining after these analyses were subjected to different types of construct validity (i.e., convergent and discriminant validity). Once the measurement model was validated, the researcher proceeded to the second step i.e. estimation of the structural relationships between latent variables. It was during this step that the theoretical model was tested. The structural model was analyzed and the standardized path coefficients of the structural model were estimated.
The study also examines consumer expectations versus perceptions. Another interesting aspect of the present study is that it, perhaps for the first time, has attempted to measure airlines' perceptions of consumers' expectations of service delivery. The research also examines the impact of IT on service delivery as also acceptability of low-cost-no-frills model in the Indian context.
For analyzing the measurement model and structural model. Structural Equation Modeling (SEM) capabilities of LISREL 8.50 were used. For proceeding with SEM, use of Maximum Likelihood Estimation (MLE) method was made. A test of association was deployed using Chi-square in SPSS 15.0 to explore if there existed any association between airline category, gender, occupation, age group, flying experience and service provided by various airline categories. Tests of differences (one-way ANOVA in SPSS 15.0) were deployed to find out whether differences existed between airline categories vis-a-vis service quality.
Instrument Refinement, Validity and Reliability
Measurement models were assessed for all six scales of service quality. A principal components factor analysis with promax rotation was conducted on all items and no restrictions were placed on the number of components to be extracted. EPA results showed that out of six constructs, five (Tangibility - Flight, Reliability, Responsiveness, Assurance, and Empathy) were unidimensional while one (Tangibility - Support Service) needed some refinements. Scale purification was carried out vis-a-vis Tangibility - Support Service till factor analysis resulted in a
14 scale that gave unidimensional construct. In all, 3 items were retained for Perception and GAP. Economical airfare / discount schemes and usage of website / call center were dropped from the scale. Cronbach alpha ranged from 0.71 for Perception and 0.67 for GAP. The item-total correlation values, which ranged from 0.43 to 0.64 for Perception and 0.40 to 0.58 for GAP, were also in acceptable range. The scale is therefore reliable. All items leading to these constructs were therefore retained.
Scale refinement was done to obtain better fitting unidimensional scales with the help of CFA. The results show that 5 of the 6 measurement scales were over-identified and did not need any further refinement. The five scales that were over-identified and did not need any modification or refinement were related to Tangibility - Flight (7 items), Reliability (5 items), Responsiveness (5 items), Assurance (7 items) and Empathy (4 items), the scale for Tangibility - Support Service (3 items) - was just- identified (i.e. dF = 0). A Goodness of Fit Index (GFI) of 0.90 or higher for the model suggests that there is no evidence of a lack of unidimensionality.
The items retained in each scale after ensuring unidimensionality were then subject to fiirther tests of reliability and validity. Indicator reliability for most indicators was found to be acceptable (>0.50) in light of the recommended values. Scale reliability was measured in three ways i.e. Cronbach's coefficient alpha, construct reliability and variance extracted measures. All six scales exhibited acceptable scale reliability as assessed by different methods. Various forms of construct validity i.e. convergent and discriminant validity were assessed. Evidences of all forms of validity were found in the study.
Analysis & Findings
The respondents of the study were passenger of domestic airlines. Majority of the respondents were males (85.6%). Professionals and Post Graduates were equally represented in the survey (39 percent) More than half of the respondents (53%) were employed in private sector and 27% in public sector. Majority of private sector passengers flew regularly with private carriers, whereas public sector employees preferred FSC-Public.
In the context of customer service vis-a-vis FSC - Public Sector, FSC - Private Sector, LCC and International Carriers, expectations were significantly high for
15 tangibility - additional support service, reliability and responsiveness. Service quality perceptions were low for tangibility - flight and empathy, especially in case of Low Cost Carriers. While the Gap between perceptions and expectations were observed to be highest for Low Cost Carriers. Overall, reliability of service was an area of concern for passengers across all categories of airlines. There was no difference between customers' expected service quality among different categories of airlines. However, there was difference between customers' perceived service quality. As a result, gap was also observed between customers' perceived and expected service quality among different categories of airlines.
It was evident that Tangibility (Support Service, Additional Support Service and Flight) and Reliability were significant drivers of customer service. Passengers expected airlines to ensure safe journey, offer support to mitigate problems due to critical incidents and particularly meet time commitments.
The results of hypotheses testing using one way ANOVA are presented in Table 5.
Table 5: Results of One Way ANOVA Hyp. Result * Remarks Hoi Rejected Significant differences were observed between customers' perceived and expected service quality (Tangibility - Support Service) across Airline Categories Ho2 Rejected Significant differences were observed between customers' perceived and expected service quality (Tangibility - Additional Support Service) across Airline Categories Ho3 Rejected Significant differences were observed between customers' perceived and expected service quality (Tangibility - Flight) across Airline Categories Ho4 Not No significant differences were observed between customers' Rejected perceived and expected service quality (Reliability) across Airline Categories Ho5 Rejected Significant differences were observed between customers' perceived and expected service quality (Empathy) across Airline Categories Ho6 Rejected Significant differences were observed between customers' perceived and expected service quality (Responsiveness) across Airline Categories Ho7 Rejected Significant differences were observed between customers' perceived and expected service quality (Assurance) across Airline Categories Ho8 Not No significant differences were observed between customers' Rejected expected service quality across Airline Categories Ho9 Rejected Significant differences were observed between customers' perceived service quality across Airline Categories Hio Rejected Significant differences were observed between customers' perceived and expected service quality across Airline Categories ' Results significant atp< 0.05
16 Analysis of data revealed that items for perception and gap loaded on four factors each. Thus, the "classical" five-dimensions of SERVQUAL could not be validated in case of domestic airlines in India.
Hypothesized Airline Service IVIodel
SEM was used to establish the relationship between service quality dimensions (Tangibility - Support Services, Tangibility - Flight, Reliability, Responsiveness, Assurance and Empathy) as exogenous variables and Satisfaiction and Loyalty as endogenous variable for Perception and GAP. Fit indices improved after scale purification. The fit indices for the structural model are given in Table 6. All values were found to be acceptable.
All indices indicate that the model achieved a satisfactory level of overall fit. The model and standardized regression coefficients between the constructs are shown in Exhibit 2 for Perception and Exhibit 3 for GAP.
Table 6: Fit Indices for Airline Service Model - Modified Goodness of Fit Statistics Critical Value Perception GAP Degrees of Freedom (dF) 419 419 Chi-square(/^) 947.237 952.034 Chi-square / dF <3 2.26 2.27 Root Mean Square Error of <0.08 0.0518 0.0520 Approximation (RMSEA) P-Value for Test of Close Fit >0.05 0.246 0.219 (RMSEA < 0.05) HOELTER Index (Critical N) >200 238.035 232.439 Normed Fit Index (NFI) >0.95 0.984 0.981 Non-Normed Fit Index (NNFI) >0.95 0.989 0.987 Comparative Fit Index (CFI) >0.90 0.991 0.989 Root Mean Square Residual (RMR) <0.10 0.0637 0.0806 Standardized RMR <0.08 0.0320 0.0331 Goodness of Fit Index (GFI) >0.90 0.888 0.888 Adjusted Goodness of Fit Index > 0.90- 0.859 0.858 (AGFI)
The relations between independent and dependent variables in the present study, as assessed by SEM, show that there is a significant direct and positive relationship between nearly all independent and dependent variables, thus indicating sufficient criterion validity.
17 Exhibit 2: IVIodified Airline Service Model with Standardised Coefficients - Perception
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0.66— GP30 C:hi-Square=947.24. df=419. P-value=0.00000. R:VISEA=0.052
18 Exhibit 3: IModified Airline Service Model with Standardised Coefficients - GAP 56-^ GGl ]
fo.ie ==^\ 0.12l',.69— GG3 A
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El —0.92
E2 —-5.93
GPM —0.39
GGM —0.11
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0.67* GG30 Chi-Squafe=952.03. df=419. P-\-aiue=0.00000. R:VISEA=0.052
19 Information Technology and Service Delivery
Airlines in India appear to be making sincere attempts at leveraging the power of IT to streamline internal information flows in order to collaborate and enrich customer experience. There is growing realization that the success of airlines will be determined by cost reductions and productivity improvements, and IT is the key to achieving both.
In general, passengers of all categories of airlines agreed that the use of IT in reservation, ticketing and check-in has led to enhanced customer satisfaction. But they were less enthusiastic in the context of use of IT in baggage handling and catering. In comparison to LCC, more passengers of FSC were using Internet to give their feedback to the airline management. Findings suggest that Internet is mainly being used for booking related activities, namely, flight schedule, seat availability, fares, booking and e-ticketing. Interestingly, LCC passengers were active users of Internet, and Internet based auctions of seats were quite popular with them. Further, it was observed that FSC were making greater use of IT for improving customer relations as compared to LCC.
The results of hypotheses testing involving IT usage and improvement in service delivery using one way ANOVA & Chi-square are presented in Table 7.
Table 7: Results of One Way ANOVA Hyp. Result * Remarks H„ Rejected Significant differences were observed between perceptions of passengers of three categories of airlines regarding improvement in satisfaction levels vis-a-vis Flight Support Services (FSS) due to use of IT Hi2 Not No significant differences were observed between perceptions Rejected of passengers of three categories of airlines regarding improvement in satisfaction levels vis-a-vis In - Flight Services (IFS) due to use of IT H,3 Rejected Significant differences were observed between perceptions of passengers of three categories of airlines regarding improvement in satisfaction levels vis-a-vis Customer Support Services (CSS) due to use of IT Hi4 Rejected Significant differences were observed vis-a-vis opinion as to whether use of IT adds to the passenger services across passengers of three categories of airlines * Results significant atp < 0.05
20 Low Cost No Frills Model
Findings demonstrate that the Low Cost Model has high acceptability in the Indian context, hi fact, first time passengers preferred it most. For them price, initially, seems to be the most important criteria as they are not aware of the distinction in quality of service offered by various airlines. The acceptability of LCC Model was found to be lowest for FSC- Private passengers who are primarily price insensitive as they either are business travellers or belong to the sponsored category. It is clear that they are conscious of the service provided during the flight and are willing to pay for quality service.
The results of hypotheses testing involving acceptability of low cost model using one way ANOVA & Chi-square are presented in Table 8.
Table 8: Results of One Way ANOVA Hyp. Result * Remarks Hl5 Rejected Significant differences were observed between passengers of three categories of airlines regarding reduction in Flight Support Services (FSS) if it leads to reduction in price of Ticket. Hi6 Not No significant differences were observed between passengers of Rejected three categories of airlines regarding reduction in In-Flight Services (FSS) if it leads to reduction in price of Ticket. Hi7 Not No significant differences were observed between passengers of Rejected three categories of airlines regarding reduction in Customer Support Services (FSS) if it leads to reduction in price of Ticket. Hi8 Rejected Significant differences were observed vis-a-vis opinion as to whether Low Cost Model is acceptable to passengers of three categories of airlines * Results significant atp<0.05
Managerial Implications of the Research
Based on the findings,Tabl e 9 lists the managerial implications of the present study. Findings suggest that dimensions of Tangibility viz. Support Service, Additional Support Service and Flight were significant drivers of customer service. Airlines should embrace strategies to improve service quality such as meeting passengers' desired service levels, improving the quality of in-flight meal, solving service problems effectively and immediately, making convenient schedules for passengers, and preventing service outages from occurring. If properly handled, these steps will no doubt enhance airline image and result in retaining existing passengers and enticing new passengers.
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S CL Q. Q. 0. CO O a. UJ 2 D. CL Q. 0£. c C C 2 ra o o rsi 0 ID >- o 6 5 = T~ 2 w s (0 re i2 c k c S S q C c o > U) 0 n 0 CM 0 0) q q CM" ra n E (0 0 0 O 'm >- 0 0 c a> 0 o CM 0 E > >- o > c 0 E 1 1 in 1 o re (A = o (0 0 w (0 u E re iq q X) 0 1 1 0i: re0 1 1 o Si u 3 o 0 O 0 re re -J S d T- < -J 1^ in S>- T- <0 T- < UJ OQ >- z >- a. a. z 5 c o 1 0 0 0 •1 . u 3 o "re 2 E = n re u O" —- u 0 0 i > ^ B > 0 >< 0 > {: c! 2 = 0 ^ OH-7 0 re re *; 0 > > <£ = m (0 JC U. Q o .£ >- 0 1- U. il S HL. £(n O o Limitations of the Study Although efforts were made to carry on a research that was theoretically and empirically sound, the study suffers from several limitations: > A general lack of reliable independent statistics on the passenger traffic on routes in India results in a lack of transparency regarding the conduct of airlines and the affect of marketing practices, code-shared flights, interlining and alliances of participants in the market. As a result there are gaps in the research and analysis of developments in the domestic air transport market. > It was observed that there was an apparent reluctance by airlines in general to participate in academic research. One possible reason behind this reluctance appeared to be competition and an apparent 'fear' that such research may 'expose' weaknesses of the organization in general and management in particular. The impact of this limitation was felt more strongly during the survey, resulting in a much lower than expected response rate from airline staff. > There was lack of extensive prior research in this field, particularly in the context of Indian airline industry. This limitation affected the research as there did not appear to be a strong foundation upon which this research could be built. > The study is restricted to specific metros in India. The required data were mainly obtained from airline passengers at domestic terminals at Indira Gandhi International Airport, Delhi (IGIA); Sardar Vallabhbhai Patel International Airport at Ahmedabad; Chatrapati Shivaji International Airport at Mumbai and Bangalore Airport. However, the airports covered were the busiest in their respective sectors and thus expected to provide an unbiased representative sample yet the data might have a slight up-market bias. > The study assumed that the respondents were all individual airline customers whose individual perceptions and expectations relating to service quality controlled the decision regarding primary airline, not taking into account possible impact of company policy or family influence. > Regardless of the attention and effort, the identified variables may have been influenced by the interests and the knowledge limitations of the customers and 24 thus may not be considered to be exhaustive. Additionally collecting respondents' data on expectations and perceptions of service quality at the same time could have compromised the reliability of the data. > The present study has focused on the use of IT by domestic airlines and its effect on customer retention. Although companies have adopted an IT strategy, its implementation may not have been uniform across the airlines covered. > While this research posits a positive relationship between use of IT and passenger satisfaction, there is a need for continuous updation as IT features may have changed since the point of time this study was conducted. > The respondents were asked to fill out a paper-based survey and they were expected to recollect their past experiences vis-a-vis services offered at domestic airline's websites. The quality of responses could be improved if a Web-based survey was administered concurrently to assess respondents' reactions to a particular site's features while they interacted with the site. > Finally, while the sample provided a substantial number of customers in those airlines that facilitated a study of this nature, one cannot generalize the results in other airlines not included within the study. Although this study had a number of constraints, the research was successfully conducted. This success may be attributed to the development and application .of a robust and flexible research design supported by valid and reliable research instruments that enabled the researcher to minimize the effects of the aforementioned limitations. Future Research Directions Based on the study, the following directions for future research may be pointed out: > Research may be carried out to unravel the complex mechanism of airline operations and its impact on service delivery. > The model proposed in the present research needs to be further tested utilizing more variables and a larger sample. Future research efforts need to 25 focus on additional decision variables pertaining to prediction of service quality. > Future researchers can expand the scope of study to include smaller cities for data collection and study the difference in GAP between perception and expectation with respect to service quality of metro respondents and smaller city respondents > The study assumed that the respondents were all individual airline customers whose individual perceptions and expectations relating to service quality controlled the decision regarding primary airline, not taking into account possible impact of company policy or family influence. Future studies may also consider these factors in their analysis. > IT implementation in various business scenarios merits further investigation. > The highly competitive nature of the industry and the pace of changes necessitate regular research in this area so that the stakeholders can feel the pulse of the market. Therefore regular research may be necessary to incorporate other new 'service dimensions' not included in this study. > Future research may compare the difference between web based responses and paper based responses toward service quality. > Further research might prove valuable in confirming the full impact of gender, income, and education on service expectations and perceptions. Extension studies need to be carried out to unravel the relationship of demographic variables with service expectations and perceptions. > This research needs to be replicated to verify as to what extent the results can be transposed to other regions of the world. 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Total Quality Management, 13(2), 241-254. 28 DIMENSIONS OF CUSTOMER SERVICE QUALITY - AN EMPIRICAL STUDY OF DOMESTIC AIRLINE INDUSTRY IN INDIA THESIS SUBMITTED FOR THE AWARD OF THE DEGREE OF Ph. D. (BUSINESS ADMINISTRATION) BY VIPPAN RAJ DUTT Under the Supervision of Dr. Mohammed Naved Khan Dr. S C Bansal Senior Lecturer Associate Professor Department of Business Administration Indian Institute of Management Faculty of Mgt. Studies & Research Lucknow Aligarh Muslim University, Aligarh (India) i India) (Internal Advisor) (External Advisor) DEPARTMENT OF BUSINESS ADMINISTRATION FACULTY OF MANAGEMENT STUDIES & RESEARCH ALIGARH MUSLIM UNIVERSITY ALIGARH (INDIA) 2008 T8788 DECLARATION I do hereby declare that the thesis titled "Dimensions of Customer Service Quality - An Empirical Study Of Domestic Airline Industry In India" submitted to the Faculty of Management Studies and Research, Aligarh Muslim University, Aligarh for the award of the degree of PhD in Business Administration is a record of original work done by me during May 2005 to October 2008 under the supervision and guidance of Dr. Mohammed .Naved Khan, Senior Lecturer, Department of Business Administration, Faculty of Management'Studies & Research, Aligarh Muslim University, Aligarh (Internal Advisor) and" Dr. S. C. Bansal, Associate Professor, Indian Institute of Management, Lucknow (External Advisor) and it has not previously formed the basis for the, award • of any Degree / Diploma / Associateship / Fellowship or similar title to any candidate of any university in India or abroad. (Vippan Raj Dutt) Research Scholar Department of Business Administration Faculty of Management Studies and Research Aligarh Muslim University, Aligarh, India Email: [email protected] CERTIFICATE This is to certify that the thesis entitled "DIMENSIONS OF CUSTOMER SERVICE QUALITY - AN EMPIRICAL STUDY OF DOMESTIC AIRLINE INDUSTRY IN INDIA" submitted to the Faculty of Management Studies and Research, Aligarh Muslim University, Aligarh, India, in partial fulfillment of the requirements for the award of the degree of PhD in Business Administration is a record of original work done by Mr. Vippan Raj Dutt during the period of his study in the Department of Business Administration, Faculty of Management Studies and Research, Aligarh Muslim University under my supervision and guidance and the thesis has not formed the basis for the award of any Degree / Diploma / Associateship / Fellowship or similar title to any candidate of any university. Place : Aligarh (Dr. Mohammed Naved Khan) Date : 11* October, 2008 Internal Advisor Indian InstUiUe of Management Lmkmw (Noida Campm) B-l, Sector-62, Naida - 201 307 (IJ.P.) TTTim : 91-0120.25Cfl740, 2401500 Tel. : S1-0320-250J740,2401500 ->5fS^ CERTIFICATE This is to certify that the thesis entitled "DIMENSIONS OF CUSTOMER SERVICE QUALITY - AN EMPIRICAL STUDY OF DOMESTIC AIRLINE INDUSTRY IN INDIA" submitted to the Facuhy of Management Studies and Research, Aligarh MusUm University, AHgarh, India, in partial fulfillment of the requirements for the award of the degree of PhD in Business Administration is a record of original work done by Mr. Vippan Raj Dutt during the period of his study in the Department of Business Administration, Faculty of Management Studies and Research, Aligarh Muslim University under my supervision and guidance and the thesis has not formed the basis for the award of any Degree / Diploma / Associateship / Fellowship or similar title to any candidate of any university. t^V Icy Place : Lucknow (Dr. S. 0. Bansal) Date : 1T,th" October, 2008 External Advisor *fR#l M^i W'W\ Indian Imtimte tff Mmmgemmt m'a-'Vf!. 3fli5 ?ft(linj?^3 5rS^!vB-22& 013 (go?!::) mm i^i.A^KtlsNajlsr. Oil Saapuf Road, Luckiioiy-226 OlSiUR) INDIA ACKNOWLEDGEMENTS I thank the ALMIGHTY GOD for giving me the courage and perseverance to pursue this study and bring it to its logical conclusion. At the very outset, I wish to record my deep gratitude to Management of Air India (Domestic) (erstwhile Indian Airlines) for giving me permission to pursue this course. I am also thankful to Aligarh Muslim University and All India Management Association (AIMA) for accepting my candidature for this programme. I convey my profound gratefulness to my Internal Advisor Dr. Mohammed Naved Khan, Senior Lecturer, Department of Business Administration, Faculty of Management Studies and Research, Aligarh Muslim University, Aligarh, for his expert professional guidance at all the times all through this research study, without which, completion of this work would have been a very difficult task. I am indeed indebted to him for the valuable time spared by him. This work could not have been brought to its logical conclusion without the support of my External Advisor Dr. S C Bansal, Associate Professor, Indian Institute of Management, Lucknow. I shall always remain indebted to him for his critical inputs as also in giving much required directions for timely completion of this study. I wish to thank Prof. Javaid Akhtar, Dean, Faculty of Management Studies and Research, Aligarh Muslim University, Aligarh, for his help and unstinted support throughout the course of this research. I am also grateful to Prof. Kaleem Mohammed Khan, Dr. Parvaiz Talib, Mr. Asad Rahman and Mr Asif Akhtar for their constant encouragement and concern for the completion of this work. I wish to convey my sincere thanks to Ms Feza Tabassum Azmi for her valuable suggestions and support during the course of this work. IV I am thankful to all other teaching and non-teaching staff at the Department of Business Administration, Aligarh Muslim University, Aligarh, India, for always being very helpful. I would like to express my gratitude to our Department Head in Air India (Domestic), Mrs Anjana Maheshwari, for her encouragement and support during the course of this study. I also acknowledge with thanks the support from Shri V. Viswanathan, GM-IT, Shri N. C. Jain and Shri Vidor Cyan, DGM - IT, Air India (Domestic), colleagues, friends, well wishers, library managers and support staff for the assistance and information provided by them. I would like to take this opportunity to thank Dr. Sujitha Khemka (Asst. Prof- Marketing, Apeejay School of Management, New Delhi), Ms Shamseen Raza Rizvi, Mr Kamal Alil, Mr Rakesh Mudgal and Mr K.R. Adhia, my fellow Research Scholars, for their help and cooperation in the completion of this research work. I am also thankful to Prof. Ravi Shankar, IIT - Delhi, Dr Danish Hashim, Dr Daud S. Farooquie and Dr Ramesh Solanki for their valuable contribution. I am thankful to Aligarh Muslim University, All India Management Association (AIMA), Management Development Institute (MDI), Indian Institute of Management, Lucknow, Indian Institute of Management, Ahmedabad, Indian Institute of Management, Bangalore and Air India (Domestic) for permitting me to use their library facility during the research. I also wish to place on record my gratitude for Indian Institute of Management, Ahmedabad, Waljat College of Applied Science, Oman, Management Development Institute, Indian Institute of Science, Bangalore, Entrepreneur Development Institute of India and Economic and Political Weekly (EPW) for giving me an opportunity to interact with other researchers and management practitioners and clearing my doubts. I am also thankful to the anonymous reviewers of the research papers based on the present work for providing inputs that helped me in refining the present work. I also express my sincere thanks to all the respondents of the study for providing their vital inputs. I also wish to place on record my gratitude for the anonymous reviewers of the research papers based on the present work for providing inputs that helped me in refining the present work. I would also like to express my gratefulness to my father Shri Munishwar Dutt and mother, Mrs Savitri Devi, brother Dharam Veer, sisters - Mohini and Rajni, nephew Anuvesh and my wife Ashima who supported me during difficult moments and encouraged me at all the times to complete the study. In fact, they have been the main motivators for this research. My children's - Dhananjay and Laakshi - keenness in seeing me finish this job played a very important role in the successfiil completion of the study. At last, I am grateful to all the other individuals, not mentioned above, that were only too willing to provide assistance, information and suggestions that have contributed to my understanding of the issues that were covered by this study, and guided me in my research. Vippan Raj Dutt VI PREFACE Civil Aviation is a catalyst for economic development and trade in an increasingly globalized world where people and goods can move around the world farther, faster and cheaper than ever. Airports link the movement of passengers and goods to national economies; serve as primary hubs for the tourism industry as a key logistical center for international trade, and as an ideal location for commercial and industrial development. While the growth rate of the civil aviation sector has slowed down in the mature international markets, it is increasing at a brisk pace in India. This growth is fuelled by the liberalisation of the industry, increase in investments, emergence of Low Cost Carriers (LCCs), positive impetus by regulatory authorities and improvement in the standards of living in the region. Leading players in the Indian aviation industry include Air India, Air India (Domestic) (erstwhile Indian Airlines), Jet Airways, Jet Lite (erstwhile Sahara Airlines), Kingfisher, Deccan, Spicejet, Paramount, Indigo and Go Air. With the entry of LCCs, the airline industry in India is, in fact, presently witnessing the second phase of liberalisation. The boom in Indian civil aviation sector has redefined the way people travel in India. As airfares drop, an increasing number of middle-income travellers prefer to travel by air. But the airline industry in India is currently encountering problems related to air traffic management, inadequate infrastructure, cockpit crew shortage, safety issues, rising fiiel cost, environmental degradation and low levels of customer satisfaction. The profit margins of network airiines have hit rock bottom owing to low-fare competition, increasing security related costs, and shifts in air travel choice behaviour. In the airiine industry, the winds of competition have changed the rules of the game. The pressure to provide better customer services has never been greater. Yet the challenge to reduce operating costs is equally strong. Automation of services can play a key role in attaining these goals, and today, many innovative solutions are being deployed. Rapid advances in the sphere of Information Technology (IT) have permeated every aspect of passenger services in airiine industry. There are several vn software solutions available to improve the passenger's journey, streamline and integrate airline and airport operations, as also track baggage and cargo. The objective of all such solutions is to deliver the highest quality of customized services to the passengers at affordable costs. The study attempts to develop a reliable and valid instrument for measuring service quality dimensions and to examine the customer's perceptions and expectations of service quality in domestic airline industry with special reference to LCCs. The present work also attempts to assess the utility of IT in passenger services by studying the performance of airlines from the customer's perspective. This can also help in evolving a model of service parameters that airlines could adopt in order to leverage IT to their advantage. It also attempts to evolve a model of customer service as applicable to various customer segments. Demographics like age, gender and level of income were also considered in the comparative analysis. The research questions and the derived hypotheses were examined comparing expectations; perceptions and the gap between them. The different demographics, between passengers on domestic flight were considered. This study also discusses various types of technologies that have been successfully deployed for providing better service to the passengers by airline industry in India. It covers issues such as internet-based reservation systems, electronic ticketing, automated check-in, baggage handling, meals, enterprise-wide customer relationship solutions and frequent flyerprogrammes . An attempt has been made to identify and analyze these dimensions in order of their importance and application in enhancing customer satisfaction levels in the airline industry. Further, a comparative analysis has been also been carried out of how different service providers in aviation industry are using internet to provide upgraded services to the passengers thereby leading to enhanced customer satisfaction and improvement in overall efficiencies. The study is organized into a total of six chapters to order the study to sequentially flow to conclusion. They?/**/ chapter provides background and justification for the study, and highlights gap in literature on predicting customer retention as a result of service quality. It vni discusses the need for the study in the context of airline industry in India; research objectives, and hypotheses framed for the study. The second chapter presents a review of the history of aviation in India from it early beginnings do^\^l to current times to include the unique nature of the Indian aviation industry. Current aviation scenario, growth, challenges and opportunities were covered in detail. This was deemed necessary in order to inform the audience about the unique nature of the Indian aviation sector and impact of liberalization on it. The third chapter deals with review of the literature in the area of service quality. Additionally, it thoroughly examines the distinct role of services marketing, relationship between customer satisfaction and service quality, a definition, measurement, and dimensions of service quality. Further it focuses on the literature dealing with service quality in airline industry, impact of IT on service delivery and low-cost no-frills model. The fourth chapter was utilized to discuss the research methods, techniques, and procedures utilized to carry out the research. The chapter then turns to the need to have the ability to measure service quality for customer retention. Instrument was developed to measure perceived quality in airlines, role of information technology in service delivery and impact of low cost model. Using a group of domestic airlines and a sample of their customer base, an examination of service quality gaps utilizing a modification of the well-regarded SERVQUAL instrument follows. Hypothsised service quality model for airline industry is also discussed. It concludes with the limitations of the research. The fifth chapter presents the research findings. It discusses the hypothesized research model and also examines consumer expectations versus perceptions. The chapter also highlights the impact of IT on service delivery and delves into issues related to acceptability of low-cost-no-frills model in India. This sixth md final chapter brings out the study's contribution to knowledge in several areas of service quality delivery in the context of airline industry in India. It also provides details on managerial implications of the study. The study then concludes by suggesting the audience about the fiiturecours e for further research. IX LIST OF PUBLICATIONS BASED ON PRESENT STUDY Issue/ 1 SNo Title of Paper Journal / Organization (s) Proceedings Date Return on Proceedings of Zyman Institute of Marketing "International Brand Science, Emory January 1 Investment: A Case Conference on University, USA, in 5-6, Study of Domestic Return on association with Indian 2006 Airline Industry in Marketing Institute of Management India Investment" (IIM) Ahmedabad, India Passenger Services Proceedings of and Stress in "National Department of Business Employees: Case Conference on Administration, Aligarh February Study of a Domestic 2. Stress Muslim University, 25-26, Airline in India Management: Aligarh, India 2006 Imperatives for Organizational Performance" Role of IT in Proceedings of Waljat College of Enhancing Service "International Applied Science, Quality: An Conference on Muscat, Oman, in September 3. Empirical Study of Service Industry: association with Birla 13-14, Domestic Airlines in Challenges and Institute of Technology 2006 India Opportunities" International Center, Muscat, Oman Aviation Proceedings of Amity Business School, Marketplace and "National Manesar, India Innovative Business Seminar on 4. Solutions: Evidences Business 8 - 9,2006 From Low Cost Strategies in the Carriers in India Borderless World" Entrepreneurial Proceedings of Management Challenges and "Global Development Institute, Acceptability of Conference on Job Gurgaon, India, in Low Cost Business And Wealth association with School October Model: A Case Creation Through of Public Policy, George 5. 26-28 Study of Civil Entrepreneurship" Mason University, 2006 Aviation Industry in Virginia, U.S.A and India Max Planck Institute of Economics, Jena, Germany. Customer Proceedings of Indian Institute of Perceptions and "Conference on Management, Expectations of Research in Ahmedabad, India January 6. Service Quality: A Marketing" 5 - 7,2007 Case Study of Domestic Airline Industry in India Journal / SNo Title of Paper Organization 1 Issue/ Proceedings Date Entrepreneurial Proceedings of Entrepreneur Trends in "Seventh Biennial Development Institute of Liberalised Civil Conference on The India, Ahmedabad, India March 7. Aviation Sector in New Frontiers of 21-23, India: Paradigm Entrepreneurship" 2007 Shifts Beyond 1990s Customer Proceedings of Balamand University, Perceptions, "International Tripoli, Lebanon, in Expectations and Colloquium on academic partnership with November Gaps in Service Business and Suan Dusit Rajabhat 8. 19-22, Quality: Management University, Bangkok, 2007 An Empirical Study (ICBM) 2007" Thailand. of Civil Aviation ISBN 978-1- Industry in India 60530-424-3 Economic Economic and Economic and Political Liberalisation and Political Weekly Weekly, Mumbai, India 43 (34), 9. Civil Aviation 2008 Industry Information IIM-B Indian Institute of Technology and Management Management, Service Delivery: Review (IMR) Bangalore, India 10. Submitted An Empirical Study of Domestic Airlines in India Mapping the Chapter in edited Rajiv Academy for Entrepreneurial book on Technology & Communi 11. Trends: Evidences Entrepreneurship, Management, Mathura, cated from Civil Aviation Macmillan India Sector in India Publication XI LIST OF EXHIBITS PAGE NO. CHAPTER 1: INTRODUCTION Exhibit 1.1 Customer Service Delivery in Airline Industry 5 Exhibit 1.2 IT Usage in Airline Service Delivery 8 Exhibit 1.3 Research Framework of the Study 13 CHAPTER 2: CIVIL AVIATION IN INDIA Exhibit 2.1: Institutional Framework 21 Exhibit 2.2: Domestic Passenger Traffic (1996 - 2007) 27 Exhibit 2.3: Comparative Cost Structure of FSCs and LCCs 34 in India CHAPTER 3: REVIEW OF LITERATURE Exhibit 3.1 Determinants of Zone of Tolerance 54 Exhibit 3.2 Gronroos Quality Model 56 Exhibit 3.3 The Kano Model 58 Exhibit 3.4 Conceptual Model of Service Quality 60 Exhibit 3.5 Internal Service Quality Model 63 Exhibit 3.6: Customer Equity Framework 64 CHAPTER 4: RESEARCH METHODOLOGY Exhibit 4.1 Research Design of the Study 86 Exhibit 4.2 Steps in Questionnaire Design Process 88 Exhibit 4.3 Hypothesised Measurement Model 107 Exhibit 4.4 Six-steps Process of Structural Equation Modeling 109 Exhibit 4.5 Hypothesised Structural Model 110 Xll CHAPTER 5: ANALYSIS AND FINDINGS Exhibit 5.1: CF A 6 Factor Model - Perception 13 6 Exhibit 5.2: CFA 6 Factor Model - GAP 137 Exhibit 5.3: Airline Service Model with Standardised Coefficients - 139 Perception Exhibit 5.4: Airline Service Model with Standardised Coefficients - 140 GAP Exhibit 5.5: Modified Airline Service Model with Standardised 144 Coefficients - Perception Exhibit 5.6: Modified Airline Service Model with Standardised 145 Coefficients - GAP Exhibit 5.7: CFA 3 Factor Model - IT and Service Delivery 157 Exhibit 5.8: CFA 3 Factor Model - Low Cost No Frills Model 169 Xlll LIST OF TABLES PAGE NO. CHAPTER 1: INTRODUCTION Table 1.1: Global Aviation Industry - Financial Forecast 2 CHAPTER 2: CIVIL AVIATION IN INDIA Table 2.1: Profile of Players in the Civil Aviation Sector in India 24 Table 2.2: Detailed Financial Results of Scheduled Domestic 31 Airlines (2006-07) CHAPTER 3: REVIEW OF LITERATURE Table 3.1: Chronology of Service Quality Research 47 - 49 Table 3.2: Definition of Modified SERVQUAL Dimensions 66 CHAPTER 4: RESEARCH METHODOLOGY Table 4.1: Airline Service Quality - Operationalization of Variables 89-90 Table 4.2: Role ofIT in Airline Service Delivery- 91 Operationalization of Variables Table 4.3: Low Cost No Frills Model - Operationalization of 92 Variables Table 4.4: Pilot Study - Factor Analysis on Perception and Gap 96 Table 4.5: Pilot Study - Reliability of SERVQUAL Dimensions: 97 Cronbach's Alpha Table 4.6: Summary ofEFA and CFA for Scale Assessment 101 and Validation CHAPTER 5: ANALYSIS AND FINDINGS Table 5.1: Descriptive Statistics - Service Quality in Airline 115 Industry - Perception Table 5.2: Descriptive Statistics - Service Quality in Airline 116 Industry - GAP Table 5.3: Descriptive Statistics - IT and Service Delivery 117 Table 5.4: Descriptive Statistics - Low Cost No Frills Model 117 XIV Table 5.5: Demographic Profile - Passenger 118 Table 5.6: Demographic Profile - Airline Staff 120 Table 5.7: EFA and Reliability Test Results - Original 121 Instrument - Perception Table 5.8: EFA and Reliability Test Results - Original 122 Instrument - GAP Table 5.9: EFA and Reliability Test Results - Modified 123 Instrument - Perception Table 5.10 : EFA and Reliability Test Results - Modified 124 Instrument - GAP Table 5.11 : Factor Correlation Matrix - Modified Instrument 125 Table 5.12 : Result of Factor Analysis (Combined) 126 Table 5.13 : CFA Results - Modified Instrument - Perception 128-129 Table 5.14 : CFA Results - Modified Instrument - GAP 130-131 Table 5.15 : Assessment of Discriminant Validity - Perception 133 Table 5.16 Assessment of Discriminant Validity - GAP 134 Table 5.17 CFA Summary - Perception and Gap 135 Table 5.18 Fit Indices for Airline Service Model - Original 138 Table 5.19 Modification Indices for the Theoretical Model 141 Table 5.20: Fit Indices for Airline Service Model - Modified 143 Table 5.21: Parameter Estimates for Modified Model 147 Table 5.22: Performance of Airlines on Service Parameters 152 Table 5.23: Service Quality in Airline Industry - Results of One 155-156 WayANOVA Table 5.24: CFA Summary - Role of IT in Service Delivery 158 Table 5.25: Chi-Square Test: Impact of IT on Passenger 158 Services Table 5.26: Impact of IT on Airline Services: Passenger 159 Perceptions Table 5.27: Information Provided on Websites of Airlines Under 165 Study Table 5.28: Utility of Services Available on Websites of Airlines 166 Under Study: Passenger Perceptions Table 5.29: IT and Service Delivery - Results of One Way 168 ANOVA Table 5.30: Summary of CFA Indices - Low Cost No Frills Model 170 XV Table 5.31: Chi-Square Test: Acceptability of Low Cost No Frills 171 Model Table 5.32: Acceptability ofLow Cost No Frills Model 172 (Perceptions) Table 5.33: Acceptability of Low Cost No Frills Model - Results of 174 One Way ANOVA CHAPTER 6: CONCLUSIONS, MANAGERIAL IMPLICATIONS AND DIRECTIONS FOR FUTURE RESEARCH Table 6.1: Focus Areas for Managerial Intervention 181-182 Table 6.2: Passenger Profile and Satisfaction vis-a-vis IT 184 Deployment Table 6.3: Passenger Profile and Satisfaction vis-a-vis Low Cost 185 No Frills Model XVI LIST OF ABBREVIATIONS AAI Airports Authority of India AGFI Adjusted Goodness of Fit Index AI Air India AI (Domestic) Air India (Domestic) (erstwhile Indian Airlines) ANOVA Analysis of Variance AQR Airline Quality Rating ATA Air Transport Association ATC Air Traffic Control ATF Aviation Turbine Fuel B2C Business To Consumer BCAS Bureau of Civil Aviation Security CAGR Compounded Annual Growth Rate CAPA Centre for Asia Pacific Aviation CFA Confirmatory Factor Analysis CFI Comparative Fit Index CLV Customer Life-Time Value CRM Customer Relationship Management CRS Computer Reservation System CSS Customer Support Services dF Degrees of Freedom DGCA Directorate General of Civil Aviation EU European Union EFA Exploratory Factor Analysis FAQ Frequently Asked Questions FDI Foreign Direct Investment FFP Frequent Flyer Programme FIA Federation of India Airlines FSC Full Service Carrier FSS Flight Support Services GAP Perception - Expectation GDP Gross Domestic Product xvn GDS Global Distribution System GFI Goodness of Fit Index lA Indian Airlines lATA International Air Transport Association ICAO International Civil Aviation Organisation ICT Information and Communication Technology IPS In-Flight Services IGIA Indira Gandhi International Airport, Delhi IT Information Technology LCC Low Cost Carrier M&A Merger & Acquisition MoCA Ministry of Civil Aviation MRO Maintenance, Repair & Overhaul NACIL National Aviation Company of India Limited NACIL (I) National Aviation Company of India Limited (erstwhile Indian Airlines) NCAER National Council for Applied Economic Research NFI Normed Fit Index NNFI Non-Normed Fit Index PNR Passenger Name Record PSF Passenger Service Fee PTI Press Trust of India RFID Radio Frequency Identification RMR Root Mean Square Residual RMSEA Root Mean Square Error of Approximation ROI Return on Investment SEM Structural Equation Modelling USD United States of America Dollar XVlll TABLE OF CONTENTS PAGE NO. DECLARATION i CERTIFICATE - INTERNAL ADVISOR li CERTIFICATE - EXTERNAL ADVISOR lil ACKNOWLEDGEMENTS iv - vl PREFACE vil - ix LIST OF PUBLICATIONS BASED ON PRESENT STUDY x - xl LIST OF EXHIBITS xii - xili LIST OF TABLES xlv - xvi LIST OF ABBREVIATIONS xvli - xviii CHAPTER 1: INTRODUCTION 1-15 1.1 Background of the Study 1 1.2 Airline Service Industry: An Overview 3 1.3 Need for the Study 7 1.4 Obj ectives of the Study 10 1.5 Research Framework 12 1.6 Organisation of the Study 15 CHAPTER 2: CIVIL AVIATION IN INDIA 16-41 2.1 Historical Background 16 2.1.1 Phase I (Pre Nationalisation) 16 2.1.2 Phase II (Nationalisation of Civil Aviation) 17 2.1.3 Phase III (Liberalisation of Civil Aviation) 19 2.2 Air Transport Service 20 2.2.1 Institutional Framework 20 2.2.2 Full Service Carriers 23 2.2.3 Low Cost Carriers 25 2.3 Growth of Civil Aviation Industry in India 26 2.4 Quality of Customer Service in Airlines of India 27 2.5 Challenges 30 2.6 Opportunities 36 XIX 2.7 Future Prospects 40 2.8 Chapter Summary 41 CHAPTER 3: REVIEW OF LITERATURE 42- 81 3.1 Concept of Service: An Overview 42 3.1.1 Characteristics of Services 43 3.2 Understanding Service Quality 46 3.3 Service Quality and Customer Satisfaction 52 3.4 Models of Service Quality 53 3.4.1 SQM 1. The Disconfirmation Model of Service Quality 54 3.4.2 SQM2. Nordic Service Quality Model 55 3.4.3 SQM 3. Kano's Model of Customer Satisfaction 56 3.4.4 SQM 4. The Gaps Model of Service Quality 58 3.4.5 SQM 5. Performance Only Model of Service Quality 60 3.4.6 SQM 6. Six-SigmaModel of Service Quality 61 3.4.7 SQM 7. Internal Service Quality Model 62 3.4.8 SQM 8. Customer Equity Framework 63 3.5 Dimensions of Service Quality 65 3.6 Service Quality in Airline Industry 67 3.7 Role ofIT in Service Delivery 72 3.8 Low Cost No Frills Model of Customer Service 76 3.9 Recent Studies on Civil Aviation in India 78 3.10 Research Gap 80 3.11 Chapter Summary 81 CHAPTER 4: RESEARCH METHODOLOGY 82 - 112 4.1 Research Objectives 82 4.2 Research Hypotheses 83 4.3 Research Design 86 4.4 Questionnaire Development and Administration 86 4.4.1 Specification of the Information Needed 87 4.4.2 Selection of Survey Method 92 4.4.3 Measurement Scales 93 4.4.4 Question Content and Wording 93 XX 4.4.5 Response Format 93 4.4.6 Sequence of Questions 94 4.4.7 Pilot Study 95 4.4.8 Administration of Final Questionnaire 97 4.5 Assessment, Refinement and Validation of Measurement Scales 99 4.5.1 Exploratory and Confirmatory Factor Analyses 101 4.5.2 Assessment of Measurement Scales Using EFA 101 4.5.3 Assessment of Measurement Scales Using CFA 103 4.6 Data Analysis Strategy 105 4.7 Hypothesized Research Model 106 4.7.1 Hypothesized Measurement Model 106 4.7.2 Hypothesized Structural Model 108 4.8 Limitations of the Study 110 4.9 Chapter Summary 112 CHAPTER 5: ANALYSIS AND FINDINGS 113-175 5.1 Preliminary Examination of Data 113 5.1.1 Descriptive Analysis 114 5.2 Demographic Profile of the Sample 117 5.3 Instrument Validity and Reliability 119 5.3.1 Phase 1 - Preliminary Assessment (Using EFA) 119 5.3.2 Phase 2 - Confirmatory Assessment (Using CFA) 127 5.4 Hypothesized Airline Service Model 138 5.4.1 Original Model 138 5.4.2 Assessment ofModel Fit and Model Modification 141 5.4.3 Modified Airline Service Model 143 5.4.4 Model Analysis 146 5.5 Measures of Service Quality in Airline Industry 148 5.5.1 Tangibility - Support Services 148 5.5.2 Tangibility - Additional Support Services 148 5.5.3 Tangibility-Flight 148 5.5.4 Reliability 149 5.5.5 Empathy 150 5.5.6 Responsiveness 150 XXI 5.5.7 Assurance 151 5.5.8 Reasons for Gap between Expectation and Perception 153 5.5.9 Results of Hypotheses Testing 15 4 5.6 RoleoflnformationTechnology in Service Delivery 157 5.6.1 Assessment of Measurement Scales Using CFA 157 5.6.2 Measuring Impact of IT on Passenger Services 158 5.6.3 Adoption of Internet Technologies 164 5.6.4 Results of Hypotheses Testing 166 5.7 Low Cost No Frills Model 169 5.7.1 Assessment ofMeasurement Scales Using CFA 169 5.7.2 Acceptability ofLow Cost No Frills Model 170 5.7.3 Results of Hypotheses Testing 173 5.8 Chapter Summary 175 CHAPTER 6: CONCLUSIONS, MANAGERIAL 176-186 IMPLICATIONS AND DIRECTIONS FOR FUTURE RESEARCH 6.1 Conclusions 176 6.1.1 Service Quality in Airline Industry 176 6.1.2 Role of Information Technology in Service Delivery 177 6.1.3 Low Cost No Frills Model 178 6.2 Managerial Implications of the Research 178 6.2.1 Implication Related to Service Quality 179 6.2.2 Implications Related to Role of IT in Service Delivery 183 6.2.3 Implications Related to Low Cost No Frills Model 183 6.3 Directions for Future Research 186 REFERENCES 187-214 Appendix -1 : Airline Passenger Questionnaire 215-218 Appendix - 2 : Airline Staff Questionnaire 219 - 222 Appendix - 3 : Airline Service Quality Audit Questionnaire 223 - 224 Appendix - 4 : Structural Equation Modeling Definitions 225 - 226 xxu CHAPTER 1: INTRODUCTION 1.1 Background of the Study 1.2 Airline Service Industry: An Overview 1.3 Need for the Study 1.4 Objectives of the Study 1.5 Research Framework 1.6 Organisation of the Study CHAPTER 1: INTRODUCTION Chapter Overview This chapter introduces the importance of civil aviation worldwide and traces its growth. It outlines the service delivery mechanism and usage of IT in airline service delivery. It discusses the rationale behind the present research and gives an overview of the objectives of the work and also explains the need for a study of domestic airlines in India. In the end, the chapter provides a bird's-eye view of the study framework. 1.1 Background of the Study Civil aviation has emerged as a major contributor to human and economic progress in most of the developed as well as emerging economies (Sidhu, 1998). According to International Air Transport Association (lATA) (2008b), airline industry represents one of the biggest industries worldwide with global airline revenues exceeding US$ 485 billion in 2007. Its contribution ranges from ensuring connectivity to far-flung areas to facilitating export revenues to growth in tourism. It is estimated that every $100 spent on air transport produces benefits worth $325 to the economy and 100 additional jobs in air transport result in 610 new other jobs (Kamath, 2007). It increases economic efficiency by providing a faster means of distributing goods and services throughout the world. Globally, airlines transport 2.3 billion passengers. According to Bisignani (2008a), approximately US$3.5 trillion worth of business and 32 million jobs depends on airline industry success. Civil aviation industry has been swept by a wave of liberalisation throughout the world (Chan, 2000b; InterW5'I^5'-ga, 2006). The aviation industry has moved towards liberalisation in the ownership of national carriers, capacity sharing, price controls and market access, leading to greater competition among airlines. Open sky policy is being followed in increasing number of countries. Airline alliances are being forged for enhanced networking of destinations and code sharing among airlines is becoming common practice these days. With facilities for easy entry, exit 1 and freedom over fare structure, domestic private operators are competing with national carriers. Airports, apart from providing range of facilities to airlines, are evolving into multifaceted hubs containing hotels, conference centres, duty free shops, and shopping malls. lATA forecasts that, in 2011, the air transport industry will handle 2.75 billion passengers (620 million more passengers than in 2006) and 36 million toimes of international freight (7.5 million tonnes more than in 2006). Liberalisation, availability of more fuel efficient and longer-range aircraft that are better able to serve thinner routes, greater choice and lower fares will be key factors influencing an increase in passenger demand over the forecast period (lATA, 2007). Table 1.1 presents salient financial forecasts of global aviation industry. Table 1.1: Global Aviation Industry - Financial Forecast Parameters 2006 2007 2008 2009 (Forecasts) (Forecasts) Passengers flown (billion) 2.124 2.260 2.321 2.379 Freight carried (million tons) 39.8 41.6 42.4 43.4 Growth rates (Percent) Passenger 5.9 5.9 3.2 3.0 Cargo 3.9 4.0 1.8 2.5 Yield growth (inflation/ 0.5 -3.2 -3.2 1.8 xchange rate adjusted) Expenses (US$ bilUon) 440 468 520 555 Fuel 111 136 186 223 Fuel as percent of expenses 26 29 36 40 Average crude oil price per 65.1 73.0 113.0 110.0 barrel (US$) Revenues (US$ billion) 452 485 520 557 Operating Profit (US$ bilHon) 12.9 16.3 0.3 2.6 Net Profit / Loss (billion US$) -0.5 5.6 -5.2 -4.1 Net margin -0.1 LI -LO -0.7 Source: lA TA (2008b), lA TA Industry Financial Forecast - September 2008. Retrieved September 15, 2008, from www.iata.ors/NR/rdonlvres/25AF6DD6-A677-4C7F-86FB-7ECE56DA702C/0/ I A TAEconomic BriefinsFinancialForecast Ausust08.pdf: Bisignani, G. (2008a, 2 June). State of the Air Transport Industry - 64th Annual General Meeting. Retrieved June 15, 2008 from www.iata.org/pressroom/speeches/2008-06-02-01.htm. lATA has revised its forecast for 2008 in September' 08 (lATA, 2008b) over its previous forecast of March' 08 (lATA, 2008a). The airline industry is projected to lose US$5.2 billion in 2008 because of hikes in oil prices, in contrast to earlier forecast of a collective industry profit of US$4.5 billion. The forecast uses oil price of US$113 per barrel of crude, up from US$86 per barrel used in the March forecast. For every dollar increase in fuel price, costs go up by US$1.6 billion. If the oil stays at US$135 for the rest of the year, losses will be much worse at US$6.1 billion (Bisignani, 2008a). Even with significant further efficiency improvements by airlines, there will be little chance of offsetting the damage to profitability from the headwinds of US recession and record fuel prices (lATA, 2008c). Aviation industry had not been doing very well in the recent past due to overall global recession. At present, the major airlines are finding themselves grounded in the struggle for survival. Twenty four airlines went bust in the last six months (Jan to June 2008). In the de-regulated environment, the customer has many choices, if the first airline does not measure up-to the desired standards of service. The condition is manifesting itself not only worldwide, but also in Indian aviation industry. Civil aviation industry in India is likely to end the current financial year with a loss of Rs 80 billion (Bansal, Khan & Dutt, 2008). Higher Aviation Turbine Fuel (ATF) prices are largely responsible for heavy losses of airlines in India. In order to win this battle, airlines are coming out with various schemes, which include measures like cutting down prices, introduction of apex fares, auction of seats, frequent flier programme, marketing initiatives, airport lounges, holiday packages and customer relationship management. 1.2 Airline Service Industry: An Overview Service Quality in Airline Industry: In the airline business, service quality indicates that all passengers are entitled to receive any or all relevant information to their trip. For example, passengers should be informed immediately of any changes to scheduled flight times or route diversions, or, when consumers book their flights, regardless of the medium used to facilitate the transaction, they should be entitled to full disclosure from the airline with respect to fare information, including extras such as departure taxes, reserve seat charges, and temporary surcharges. Airlines should be committed to providing quality onboard services to passengers. Quality service requires, among other things, the availability of sanitary washroom facilities, the best possible onboard air quality, and the provision of food and non-alcoholic beverages during long flights and/or extended delays. In total, number of different articles used for passenger services during the flight (onboard or inflight service) can reach 1,000 depending on degree of sophistication of passenger service of the airline (Hovora,2001). Focus on ser\ice quality is the need of the hour if the airlines aspire to improve market share and further enhance financial performance in domestic and international segments. Airlines need to better understand the factors likely to have a bearing on the service quality offered by their organization, e.g. expectations and perceptions of airline passengers vis-a-vis service quality. Exhibit 1.1 outlines airline service delivery mechanism. lATA's Passenger Service Conference Resolution Manual contains the standard practices that have been universally agreed upon by airlines to process passengers and baggage in the international interline envirormient (lATA 2008d). It includes procedures for reservations, passenger and baggage check-in and ticket issuance; specifications for baggage tag and ticketing and various multilateral interline agreements; and other passenger traffic-related regulations. lATA also has a set of Recommended Practices and Resolutions that relate to consumers' protection and competition issues (Nikomborirak, 2005). At the 56 I ATA Annual General Meeting, I ATA airlines endorsed a global Customer Service Framework (lATA 2000). lATA adopted a resolution on customer service, which endorsed the lATA Customer Service Framework as a guide for airlines in developing their customer service commitments and plans (Flug Revue, 2000). There are specific guidelines for accommodating special need passengers. It also expects passengers to play a role in safe and efficient operation of the air transport system. The member airlines are committed to provide a high level of service to their customers. The International Civil Aviation Organisation (ICAO) has developed guidance material on consumer interests in areas such as conditions of carriage, fare guarantee, baggage handling, tariff disclosure, denied boarding and a code of conduct for the regulation and operation of the Computer Reservation System (CRS) (ICAO, 2003). But some countries legislate certain aspects of the conditions of carriage in order to ensure passengers' rights. es g «s » ri aj III. H Hi i» « 4; •<< w £1!/i a 1a H o ^ N iliiii Z .2 en 9 B % "i o .5?'2 4 -3 & i-i O •£ S I/) Sllllll Ml U ««• d "" w 111 ..I d '-^ a 1^ I/) a 0 OJ 01 o . I u P •43 9i •s •^ Ml ^ c a « »M^l (S vrr ta: *I'.' •§ The US initial approach to regulation relied mainly on voluntary self-regulation by trade associations. The experience of the US seems to indicate that a purely voluntary scheme has its limitations in the absence of an effective monitoring scheme and the force of law that stands behind it (Nikomborirak, 2005). In June 1999, the Air Transport Association (ATA), working with Congress and the Department of Transport (DoT), developed the 'Airline Customer Service Commitment' (Mead, 2000). The introduction of the Airline Customer Service Improvement Act, 2001, requires that all ATA member airlines incorporate the Customer Service Commitment in their contracts of carriage. ATA members are committed to provide the highest possible level of service to the customers (ATA, 2007). It also requires disclosure of the on-time performance and cancellation rate for chronically delayed or cancelled flights when a customer makes a reservation. As such, the customer can hold the carrier legally liable for breach of contract in case of non-compliance. Information Technology and Service Delivery: The travel industry has been a pioneer in the innovative use of Information Technology (IT) (Feldman, 2001; Gareiss, 2001, 2003; Kelemen, 2003; Kuhlmann, 2003; Botha, 2004; Ghobrial & Trusilov, 2005). The airline industry is embracing cutting edge technology to gain competitive edge (Jiang & Doukas, 2003; Baker, 2007). e-Commerce and IT, which are closely interwined, are changing the nature of the airline business and will increasingly be fundamental to every aspect of airline operation (Doganis, 2006). O'Toole & Pilling (2004) predicts that air travel could become world's first web- enabled industry as online sales, e-tickets and range of new technologies gain ground with increasing speed. The dramatic growth of web and self-service technologies permit customers and airlines to bypass the complexity and cost of old legacy systems (Mclvor, O'Reilly & Ponsonby, 2003; Shon, Chen & Chang, 2003). It will facilitate the introduction of simplified passenger travel involving e-ticketing, automated check-in, common-user self-service kiosks and so on. Use of technology has also led to improvement in supply chain management and procurement. Exhibit 1.2 details the use of IT in airline industry. Low Cost No Frills Model: Growth in the air traffic in recent years is due to the spread of low cost service. The mainline carriers / Full Service Carriers (FSC) are facing strong competition from Low Cost Carriers (LCC). LCC like Southwest Airlines and Jetblue Airways have received high service quality ranking by Bowen and Headley (2007). Airline Quality Rating system is based on weighted average of on-time arrivals, involuntary denied boardings, mishandled baggage, and a combination of 12 customer complaint categories with on-time performance receiving a higher coefficient. Better LCC performance is due to fewer flight cancellations and higher on-time arrival rates (Sayanak, 2003). Successful low cost carriers undermine the economics of full service carriers by capturing a growing market share and forcing the latter to drop their fares (Doganis, 2006). The value proposition for passengers is changing. Despite the variety of forces that will shape the future of the industry, customer choice, preference and demand will remain the main driving force behind these changes (Marshall, 2000). Travelers expect convenience and connectivity. They are willing to pay for value, but they are not prepared to pay for the complexity of the industry systems that have evolved over time. Simplifying the business and focusing on value is critical. This is leading the way in the air transports industry's evolution towards a low cost industry and will enhance the passengers' travel experience. 1.3 Need for the Study This study is an in-depth empirical investigation that seeks to establish a method to predict service quality in domestic airline industry in India. The motivation for this work was provided by a lack of any useful instrument to predict and evaluate service quality in airlines to aid the retention of customers. While the literature is replete with empirical studies on service quality, customer loyalty, customer retention, and customer relationships in general, there is a scarcity of such works relating specifically to airline industry in India. ^ •3 o; 1 O) fi s c qj u fl^ ^ (a 2 M •E g i- g i o % C S S S S DC ID ^ <2; •o 5 ^ S ? -a cr 5 o 0 s 1a^ Z a 0 -K t; o* BO > « OO ^ A ^ -< « (/) ,=• .^^ - 3 O ij (i( '5 •< w a 3 u • • » S . » < I a ^ a .= & •K B « •-S\ 0> ) J**' « fljT S eV)* * a ™ 1- *; - a a W (s 0) O O 0 .3 T.a 1 2 O ! c 4-* 1 o a I . w ^i c I V *2 *" U O s "E o 1^3 f! 0) t |l Ml (U ou 15 (0 I « « a (/) 5**^ 0) fi< (/) U (0 CM a *-*B C S DQco 0 n iio ? "a a ?* Of =0 d fe/i E a »-( « -^ M .3 BO S ^ -^ o a IS .H B«!« UJ I ^ 2 .3 ^ 1 , 1 or KS ct; M 0 M H s 0 O 1-1 IL > H t. < h } \A O Q: 7, f) ^-s m LU 0 (/} 0 M Z 1- W fa s The main purpose of this study is to contribute to the body of knowledge available on quality of customer service in domestic airlines of India. It also measures the gap between expectations and perceptions of the passengers so that strategies can be implemented to improve the quality of service and increase airlines profitability and market share. As airline customers become more knowledgeable and therefore more demanding, and as competition between airlines for domestic and international customers increases, airlines are forced to provide an ever-improving quality of service on one hand, and maintain an economical cost structure in order to survive on the other. This creates a need to determine appropriate measures so that valid and reliable evaluation of existing as well as planned improvement in quality of service could be conducted. Some of the key questions facing airline marketeers are (i) identification of attributes that influence customers' choice in airlines, (ii) methodology adopted by the customers to rate the airlines on various parameters, (iii) importance of service quality in purchase intentions, and (iv) system of assessing the satisfaction of an airline customer. This assessment is crucial because it has major implication for business performance. This study will help domestic airlines to re-look their customer service measurement systems and mark relative importance of various attributes. It shall also help in carrying out a comparative analysis of the performance of the domestic airlines on the identified service attributes. Airlines need to segregate their customer segment. The profile of various customer segments shall help airlines assess the dimensions of service, which are valued by them, why and how they make their choices and what airlines can do to improve customer satisfaction for higher market share. A clear understanding of this shall improve satisfaction of customers belonging to different segments. This analysis shall ensure that airlines maintain and enhance their market share. Many instruments evaluating service quality have been used in various service industries with varying degrees of success. These include SERVQUAL, SERVPERF, weighted-SERVQUAL, weighted-SERVPERF and INTER- SERVQUAL There is a need to determine the extent of applicability of and required modification to such instruments when used in the domestic airline industry. The applicability of such instruments is likely to be influenced by the characteristics and environment of the airline customers. This work investigates the 9 applicability of SERVQUAL to the measurement of the quality of service of domestic airlines in India and introduces the necessary modifications. The results of this study could be implemented by Indian airlines as part of efforts to improve quality of service and maintain its competitiveness. Airlines are making attempts to deploy cost effective IT solutions extensively for providing quality service to the passengers. Although, airlines have extensively deployed IT to improve their service profile, yet there is a need to evolve a model of service parameters that airlines could adopt in order to leverage IT to their advantage. The research also tries to measure the impact of IT in airline service delivery in Indian scenario. LCCs are a new phenomenon in India, and they are making attempts to deploy effective low cost solutions extensively for providing service to the passengers. The present work attempts to study the performance of airlines from the customer's perspective. The study will also attempt to find out the level of acceptability of low cost business model amongst the Indian airline passengers. 1.4 Objectives of the Study As discussed above, the study attempts to develop a reliable and valid instrument for measuring service quality dimensions and to examine the customer's perceptions and expectations of service quality in domestic airline industry with special reference to LCCs. The present work also attempts to assess the utility of IT in passenger services by studying the performance of airlines from the customer's perspective. This can also help in evolving a model of service parameters that airlines could adopt in order to leverage IT to their advantage. It also attempts to evolve a model of customer service as applicable to various customer segments. The broad objectives of the study can be grouped into four categories: I: Developing an instrument for measuring service quality a. Investigate the extent of applicability of the SERVQUAL instrument to the airline industry in India b. Compare service expectations; perceptions and the gaps using the SERVQUAL scale 10 c. If required, to develop a reliable and valid instrument for measuring various dimensions of service quality in airline industry II: Investigating service quality in domestic airline industry a. Understanding the dimension of services valued by the passengers b. To assess satisfaction level of customers on various dimensions of services c. Compare the quality of services being offered by various airlines III: Investigating acceptability of Low Cost Model a. To map out the preference of airline passengers for the Low Cost Model IV: Assessing role of IT in airline service delivery a. To generate a profile of IT based services being offered by three categories of airlines (i.e. FSC - Public, FSC - Private and LCC) b. To map out the passenger preferences for the IT based services c. To study the impact of IT on various dimensions of customer service quality Based on extant literature and objectives of the study, hypotheses were framed and they have been placed under three groups. ThQ first group of hypotheses (Hi to Hio) were developed to measure the overall difference in expectations and perceptions of passengers towards service quality provided by the airlines. The second group of hypotheses (Hn to Hi4) are related to the impact of IT on passenger services. The third and the last group of hypotheses (H15 to Hig) are related to the acceptability of low cost no frills model in India. The research also provides a comparative analysis of the performance of scheduled air transport operators in terms of operating traffic statistics, fleet strength, load factor, cargo carried, financialperformanc e and marketing initiatives. Further, in the light of the findings, an attempt has been made to suggest the possibility of outsourcing some of the non-core service processes by the domestic airlines in the country. 11 1.5 Research Framework Exhibit 1.3 presents the broad research framework followed in this study. Literature review was carried out in the area of service quality with special emphasis on service quality in airline industry, role of IT in service delivery and low cost no frills model of customer service in airline industry. Based on the literature review, gaps in the research area were identified. Literature review led to the formation of research objectives and hypotheses. Research constructs were identified and research instrument for passenger, airline staff and quality service audit were developed. Modified version of service quality measurement tool SERVQUAL (Parasuraman, Zeithaml and Berry, 1988) was employed to assess customer expectations and perceptions of service quality in domestic airline industry in India. SERVPERF study has been simultaneously carried out to provide further insight. Combination of SERVQUAL and SERVPERF instrument makes this work unique in Indian context. The survey instrument used in the study contained questions pertaining to expectation and perception rating for each driver. The questionnaires are primarily based on 22 items of SERVQUAL model. Modified instrument consists of 30 items divided along the 6 dimensions, with a seven-point likert scale accompanying each statement to test the strength of relations. Tangible dimension was modified to reflect unique characteristics of airline service industry and was divided into two sub-dimensions: 1 Tangible - Support Services containing 5 items, and 2 Tangible - Flight containing 7 items The research instrument also contained questions pertaining to 1 Usage of IT and customer rating for each IT driver, and, 2 Acceptability of Low Cost Model being provided by new airlines. In addition, the research instrument also had questions related to demographics. To check for suitability of the research instrument, a two stage pilot study was carried out. Later the instrument was tested for validity and reliability. To meet the objectives of the study, data were collected from the passengers and staff of domestic airiines (Appendix 1,2 and 3). In depth interviews were arranged 12 « a -«,s CM ^ J3 u u o L< «M « 1/1 o 05 •M Vu hu. L. a Q b >» •D i k 3 *>> V) 0) o ^ v: I- cs n o •C .2 ^ -w 6X « EI e — n es O- m JZ SI o ffi i k (A CO 1/1 fl • oH4 M lU s Su3 © u 1 k 1 e _o ^ (R _N d-i a* e O • im "rt W) ftJD B s .S fl •t^ -4a^ % The scope of the study included the following four categories of airlines: > Full Service Carriers - Public Sector, which includes Air India (Domestic) (erstwhile Indian Airlines and Alliance Air). > Full Service Carriers - Private Sector, which includes Jet Airways, Jetlite (erstwhile Air Sahara now taken over by Jet Airways) and Kingfisher Airlines. > Low Cost Carriers which include Deccan (now taken over by Kingfisher Airlines), Spicejet, Paramount, IndiGo and Go Air > International Carriers operating to / from India, which include Cathay Pacific, Emirates, Gulf Airways, Singapore Airlines, Thai Airways, Air Lanka, British Airways, Air India and Korean Airlines.After data collection, questionnaires were checked and edited to ensure completeness before data entry and analysis. Data analysis and interpretation involved use of MS-Excel 2000 spreadsheet program; SPSS 15.0 Statistical Analysis Software; and LISREL 8.5 Structural equation modelling software. Appropriate statistical tools like Exploratory Factor Analysis (EFA), Kaiser-Meyer-Olkin (KMO) and Bartlett's test of sphericity, Confirmatory factor Analysis (CFA), Cronbach's reliability test, cross tabulation, Levene test of Homogeneity of Variance and one-way ANOVA have been applied on the collected data. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to assess and refine the measurement scales in terms of unidimensionality, reliability and validity. Chi-square test was carried out to measure goodness of fit and relationship between respondents of different airline categories and their perception of airline service. Hypotheses were tested and conclusions derived. Managerial implications and directions for future research were discussed. 14 The final stage involved presentation of modified service quality model for airline industry. 1.6 Organisation of the Study Chapter 1, the current chapter, offers an overview of the study. It includes need for the study, broad research objectives and research framework. Customer service in the context of airline industry has also been discussed. Chapter 2 gives an overview of civil aviation environment in India. It also presents the impact of liberalisation focussing on the issues as well as opportunities. Future outlook of civil aviation in India is also covered in this chapter. Chapter 3 provides a review of extant literature relevant to the research problem. The body of literature, as a whole, provides rationale for the scope and the conceptual framework of this study. Chapter 4 discusses the research methodology adopted for the work. Research design, instrument development and pre-testing, survey method, and statistical tools employed in data analysis are also described. It also contains the conceptual research model that has been tested and refined using Structural Equation Modelling tool LISREL 8.5 in subsequent chapter. Further, limitations of the study are also presented. In chapter 5, hypotheses considered for the study have been tested. Reliability and validity measures of the constructs using EFA and CFA are also presented. Assessment and modification of the hypothesised theoretical model described in chapter 4 is carried out. A multivariate model relating the customer service index and relevant variables developed for the study too is discussed. Usage of IT and acceptability of Low Cost No Frill model by the passengers is also covered in this chapter. In the last chapter, i.e. chapter 6, the conclusions are drawn. The managerial implications of the research have also been outlined. It is followed by suggested directions for further research. 15 CHAPTER 2: CIVIL AVIATION IN INDIA 2.1 Historical Background 2.1.1 Phase 1 (Pre Nationalisation) 2.1.2 Phase II (Nationalisation of Civil Aviation) 2.1.3 Phase III (Liberalisation of Civil Aviation) 2.2 Air Transport Service 2.2.1 Institutional Framework 2.2.2 Full Service Carriers 2.2.3 Low Cost Carriers 2.3 Growth of Civil Aviation Industry in India 2.4 Quality of Customer Service in Airlines of India 2.5 Challenges 2.6 Opportunities 2.7 Future Prospects 2.8 Chapter Summary CHAPTER 2: CIVIL AVIATION IN INDIA Chapter Overview This chapter presents the current status of civil aviation industry in India. It also discusses various challenges and opportunities emerging due to economic liberalization in the country. Section 1 gives the historical background of civil aviation in India. Section 2 presents the institutional framework, its players and types of air sei^vices. Growth of civil aviation industry in India has been discussed in Section 3. Quality of customer service in airlines of India is discussed in Section 4. Section 5 highlights some of the important challenges posed by the liberalized economy. Section 6 focuses on the opportunities that can be exploited by the domestic civil aviation carriers. Finally, section 7 draws main conclusions and presents future prospects. 2.1 Historical Bacl This section delves into the past of the air sector in India and discusses its evolution. It studies India's experience, and how entrepreneurship, regulation and economic thought have played a role in its development. 2.1.1 Phase I (Pre Nationalisation) Backed by individual initiative, aviation had an impressive begiiming in India in the first few decades of the last century (Bhandari, 2002). In 1910, the government passed the Indian Airships Act (later amended to Aircraft Act) following private attempts at air travel for personal interest and sport. The Indian Air Board, an advisory set up of senior officials of Government of India was formed in 1918 to advise on ways of assisting and encouraging civil aviation. In 1926, the board submitted memorandum titled "The Past History and Future Development of Civil Aviation in India" (Sen, 1998). The recommendations of the memorandum led to the formation of a separate Department of Civil Aviation and Lt Col Shelmerdine was appointed first Director General of Civil Aviation in 1927. 16 The 1930s, saw an increase in number of aircraft, routes, frequencies of air transport in India. In October 1932, TATA Airlines started operations of its Karachi - Ahmedabad - Bombay - Bellary - Madras service. In Dec, 1933, this was followed by Indian National Airways, a Delhi based company, which operated mail and freight service between Calcutta - Rangoon - Dacca. 'Air Services of India' started passenger services between Bombay - Kathiawar - Kolhapur in 1937. The operations were not profitable and the services were discontinued in two years. By 1939 all parts of the country were connected by regular air services. In July 1946, Tata Airlines was renamed as Air India and converted to a public company. In early 1948, a joint sector company, Air India International Limited., was established by the Government of India and Air India to operate on international routes. The Second World War led to an unparalleled boost to civil aviation. Established air carriers increased the number and size of aircraft they were flying. Many new airlines also entered the industry. This led to a high degree of competition between the airlines and prices crashed reducing the profitability of airlines. However, it continued to be a highly dynamic industry. While the route mileage, miles flown and traffic carried had shown a phenomenal growth, the industry as a whole was operating at a heavy loss. The soaring prices of aviation fiiel, mounting salary bills and disproportionately large fleets took a heavy toll of the then airlines. The government in February 1950 appointed an Air Traffic Enquiry Committee to look into the problems faced by the airlines. The Committee recommended that some of the airlines should be merged. The Government set legislation to nationalize the air transport industry. The Air Corporation Act received Presidential assent on May 28, 1953 and accordingly, two autonomous corporations - Indian Airlines Corporation and Air India International Corporation (the word 'International' was dropped in 1962) - were created on August 1,1953. 2.1.2 Phase II (Nationalisation of Civil Aviation) After nationalisation of the industry in 1953, Indian Airlines Corporation took over the domestic operations, while Air India International Corporation started operations in international sectors except for some routes to the neighbouring countries which were given to Indian Airlines. 17 The eight former independent companies became 'Lines' of Indian Airlines Corporation (IAC): Air India, Air Services of India, Airways (India), Bharat Airways, Deccan Airways, Himalayan Aviation, Indian National Airways and Kalinga Airlines. This gave rise to the problem of integration and rationalisation. Indian Airlines Corporation inherited a fleet of 99 aircraft including 74 Douglas DC- 3 Dakotas, 12 Vickers Vikings, 3 Douglas DC-4s and various smaller types from the eight airlines that made it up. Vickers Viscounts (Ten Nos) were introduced in 1957 with Fokker F27 Friendships (Ten Nos) being delivered from 1961. The 1960s also saw fourteen HS 748s (Avros), manufactured in India by Hindustan Aeronautics Limited, join the fleet. The jet age began for lAC with the introduction of the three pure-jet Sud Aviation Caravelle airhner in 1964, followed by seven Boeing 737- 200s in the early 1970s. In the 22 years since the Corporation was formed, technological development and the growing traffic on the trunk routes have seen the Dakota and the Viking give way to the Viscount, the Viscount to the Caravelle and the gradual supersession of the Caravelle by the Boeing 737-200. Each successive aircraft type has been larger, faster and more economical to operate than the one it replaced (lAC Annual Report 1974-75). April 1976 saw the first three Airbus A300 wide-body jets being introduced. By 1990, Airbus A320s the first fly-by-wireplan e was introduced in lAC fleet. In 1954, Air India International took delivery of its first L-1049 Super Constellations and inaugurated services to Singapore, Bangkok, Hong Kong and Tokyo. It entered the jet age in 1960 when its first Boeing 707, named Nandadevi and registered VT-DJJ, was delivered. Jet services to New York via London were inaugurated that same year in May 1960. On 8 June 1962 the airline's name was officially truncated to Air India. On 11 June 1962 Air India became the world's first all-jet airline. In 1970, Air India moved its offices to downtown Bombay. The next year, the airline took delivery of its first Boeing 747 named Emperor Ashoka and registered VT-EBD. This coincided with the introduction of the 'Palace In The Sky' livery and branding. A distinctive feature of this livery is the paintwork around each aircraft window, in the cusped arch style of windows in Indian palaces. In 1986 Air India took delivery of the Airbus A310. The airline is the largest operator of this type in passenger service. In 1988, Air India also took delivery of two Boeing 747- 300s in mixed passenger-cargo configurafion. In 1993, Air India took delivery of the 18 flagship of its fleet when the first Boeing 747-400 named Konark and registered VT- ESM made history by operating the first non-stop flight between New York and Delhi. Vayudoot started operating as a feederline in January 1981 as a subsidiary of Air India and Indian Airlines. This airline was originally conceived to serve the north east region of India where the surface transport facilities were inadequate and surface routes were circuituous. Subsequently, the services of Vayudoot had been extended to other regions also, charting 100 stations in the country. This had adversely affected its financial performance. After a review, the number of stations on the operational network was brought down to 48 on 31st March 1991. Its operations were restricted to North-Eastem region and other inaccessible areas. Vayudoot had a fleet of eight Domier aircraft, eight Avro and one Fokker aircraft. Vayudoot's financial performance was not satisfactory which finally led to its dissolution and merger of its assets into Indian Airlines. 2.1.3 Phase III (Liberalisation of Civil Aviation) The third phase of Indian aviation began in the year 1986 with granting of permission to private sector players to operate as air taxi operators. The private players allowed to operate as air taxi operators included Air Sahara, Jet Airways, Damania Airways, East West Airlines, Modiluft and NEPC Airways. In 1994, government of India repealed the Air Corporation Act thereby granting scheduled carrier status to six private air taxi operators. However, not many operators were able to continue their business and by 1997 only two private operators - Jet Airways and Air Sahara - continued to operate. Six private airlines - East-West, Modi-Luft, NEPC, Damania, Gujarat Airways and Span Air - were closed and according to an estimate, the capital losses involved in these closures were to the tune of Rs 10 billion (Shah, 2007). The duopoly of Jet Airways and Air Sahara as private carrier was challenged in 2003 by Deccan whose operations in scheduled services began in August. Deccan gave India its first Low Cost Carrier (LCC) or no frills Airline. This marked as a turning point in the history of Indian aviation sector as it marked a shift from the regular economy fares & business fares to the era of check fares such as web fares, 19 APEX fares, internet auctions, special discounts, corporate plans, last day fares, promotional fares. This has led to tremendous growth in air traffic (Seshadri & Henry, 2005). Spurred by the initial success of LCC Model, other airlines entered the sector and opted for No-Frill Model. Since then 5 other airlines namely Spice jet. Kingfisher, Indigo, Paramount, Go Air have begun operations in India. Licenses have been issued to new carriers such as Star Airlines; Skylark; Magic Air ; Air One and many more in the pipeline. Yet another milestone in the history of the Indian Aviation sector came in the year 2007 which is the year of mergers in the Indian Skies. The year has witnessed a series of merger and acquisition of airlines namely: Indian-Air India; the Jet-Sahara Deal; the Kingfisher-Deccan Deal (Bansal, Khan & Dutt, 2008a). These players post consolidations have claim over 80% of the market share. Pandey (2007) feels that consolidation in the Indian airline industry may lead to a monopolistic scenario. A policy adjustment is required to ensure that aviation market remains competitive. 2.2 Air Transport Service India has an eminent position in the civil aviation sector with a large fleet of aircrafts. In all, 14 airlines are operating scheduled air services to and through India and 76 non-scheduled operators are flying over Indian territory. There are over 450 airports and 806 registered aircrafts in the country. There are also 76 non-scheduled air transport operators (DGCA, 2008). Air transport has a significant role to play in a vast country like India with major industrial and commercial centres located far apart (Puri, 2003). The civil aviation sector has significantly changed during this period making earlier projections totally obsolete for the current economic scenario. 2.2.1 Institutional Framework The domestic civil aviation activities in India can be broadly classified into three categories - regulatory-cum-developmental, infrastructural and air transport services (Planning Commission, 2001). Exhibit 2.1 presents the institutional framework of Indian aviation industry. 20 Exhibit 2.1: Institutional Framework Regulatory cum Developmental O Ministry of Civil Aviation 0 Directorate General of Civil Aviation 0 Bureau of Civil Aviation Security Customer Service Air Transport Service Infrastructure 0 Full Service Carrier • Public Sector 0 Airport Authority of India • Private Sector 0 Low Cost Carrier Source: Prepared by the Researcher The Ministry of Civil Aviation (MoCA) and its bodies, namely, Directorate General of Civil Aviation (DGCA) and Bureau of Civil Aviation Security (BCAS) look after regulatory and developmental aspect of civil aviation in India. MoCA is the nodal agency responsible for formulation of national policies, schemes and programmes for development and regulation of civil aviation sector. It's mission is to maintain a competitive civil aviation environment, which ensures safety and security in accordance with international standards, promotes efficient, cost-effective and orderly growth of air transport and contributes to social and economic development of the country (MoCA, 2000). It's function extends to overseeing airport facilities, air traffic services and carriage of both passengers / goods by air. Government has laid down Route Dispersal Guidelines (RDG) in 1994 with a view to achieve better regulation of air transport services taking into account the need for air transport services of different regions of the country (Planning Commission, 2006a). According to the RDG, all scheduled operators are required to deploy in the North Eastern region, Jammu & Kashmir, Andaman & Nicobar Islands and Lakshadweep (Category-II routes) at least 10% of their deployed capacity on trunk 21 routes (Category-I routes). Further, at least 10% of the capacity thus required to be deployed on Category-II routes, is required to be deployed for connectivity exclusively within these regions. 50% of the capacity deployed on Category-I routes is to be deployed on routes other than Category-I and Category-II routes i.e. Category-Ill routes. All airlines are free to operate anywhere in the country subject to compliance with the RDG. In view of the vital changes that have taken place in civil aviation sector since the policy was laid down, it is desirable to review the RDG to bring them in line with these developments (Planning Commission, 2006b). The Airports Authority of India (AAI) was formed on 1st April 1995 by merging the International Airports Authority of India and the National Airports Authority with a view to accelerate the integrated development, expansion and modernization of the operational, terminal and cargo facilities at the airports in the country conforming to international standards. AAI manages 126 airports, which include 11 international airports, 89 domestic airports and 26 civil enclaves at defence airfields. It provides air navigation services covering more than 2.8 million square nautical miles of airspace. AAI, during Apr 2007- Mar 2008 handled about 1.31 million aircraft movements (1.06 million domestic and 0.25 million international); 116.87 million passengers (87.06 million domestic and 29.81 million international) and 1.71 million tormes of cargo (0.57 million domestic and 1.15 million international) (Airport Authority of India 2008). The Air Transport Companies are both in the public sector and in the private sector. In the public sector, Indian Airlines and Alliance Air provide passenger transport and cargo handling services in the country. In the private sector, there are eight scheduled airlines (passenger), namely. Jet Airways, Air Sahara (now JetLite), Deccan Aviation, Spice Jet, Go Airways, Kingfisher Airlines, Paramount Airways and Indigo operating on the domestic sector providing passengers with a wide choice. In addition to the above mentioned scheduled airlines, there are at present 46 companies holding non-scheduled air transport operators permit. Indian Airlines has also been operating to the neighbouring countries in South East Asia and the Middle East. The private scheduled airlines Jet Airways and Air Sahara have been operating on international sectors to Colombo, Kathmandu, Singapore and UK. Presently, Indian Airlines, Jet Airways and Kingfisher are the Full Service Carriers (FSC), whereas JetLite (erstwhile Air Sahara), Deccan, Spicejet, Paramount, IndiGo 22 and Go Air fall in the category of Low Cost Carriers (LCC). Table 2.1 gives the profile of domestic airlines operating in India. 2.2.2 Full Service Carriers National Aviation Company of India Limited (NACIL) is a 100 percent government owned company, incorporated in March, 2007 and started its operations in August, 2007 following the merger of Air India Limited and Indian Airlines Limited. It operates under the brand name "Air India" and its logo remains the Maharaja. The company has employee strength of about 33,000, turnover of more than Rs 150 billion and operates 140 aircraft, making it one of the largest airlines operating in Asia. The company is in the process of major expansion and adding 111 state-of-the-art aircraft to its fleet. Air India covers more than 100 domestic and international destinations. Air India (Domestic) (erstwhile Indian Airlines together with its fully owned subsidiary Alliance Air) has a fleet of 96 aircraft (3 wide bodied airbus A300s, 48 fly-by-wire airbus A320s, 12 Airbus A319s, 2 Airbus A330, 9 Airbus A321, 11 Boeing 737s, 2 Domier Do-228 aircraft 7 ATR-42 and 2 CRJ 700. It has already placed order for 43 new aircraft (i.e. 19 A319s, 4 A320s & 21 A321s) and aircrafts are being delivered on regular basis. The Airlines' network spans from Kuwait in the west to Singapore in the East and covers 79 destinations - 61 within India and 18 abroad. Indian Airlines flight operations centre around its four main hubs the main metro cities of Delhi, Mumbai, Calcutta and Chennai. Together with its subsidiary Alliance Air India (Domestic) carried a total of over 8.1 million passengers in 2007. Jet Airways, which commenced operations on May 5, 1993, has established its position as a market leader within a short span of 14 years. Jet Airways currently operates a fleet of 87 aircraft, which includes 10 Boeing 777-300 ER aircraft, 11 Airbus A330 aircraft, 55 classic and next generation Boeing 737-400/700/800/900 aircraft and 11 modem ATR 72 turboprop aircraft. With an average fleet age of 4.3 years, the airline has one of the youngest aircraft fleets in the world. Jet Airways 23 il O P- + y* W a p O ?; (3 n ? 1^ S s.- n Ui c t i o a> (0 c _o 10 S s < ^- •ao OJ? tt "> 'A '<-' o •J _c M ^j k. Ei > ra ^ o to 0) 6* o •? m • 4> Q (Q I- w -1 ^ r. o •-I S o u I I 1> aS: operates over 395 flights daily. Flights to 63 destinations span the length and breadth of India and beyond, including Colombo, Kathmandu, Dhaka, Bahrain, Dhaka, Singapore, Kuala Lumpur, Bangkok, London, Brussels, New York, Newark, Hong Kong, Shanghai, San Francisco and Abu Dhabi. The airline plans to extend its international operations to other cities in North America, Europe, Africa and Asia in phases with the introduction of additional wide-body aircraft into its fleet. Kingfisher Airlines is part of The UB Group which is one of India's largest conglomerates with diverse interests and a global presence. Kingfisher Airlines now has 254 departures a day and flies to 43 destinations with a fleet of 43 brand new aircraft. With the merger of Kingfisher Airlines and Deccan, the airline covers all segments of air travel from value fares to premium fares and offers the most flights by any single airline network in India. The combined entity now connects 64 cities in India with 424 daily departures across India. 2.2.3 Low Cost Carriers Deccan is a part of The UB Group owned Kingfisher Airlines. Deccan presently flies to 64 destinations nation wide with a fleeto f 41 brand new aircraft and operates over 250 flightsdaily . JetLite (India) Limited is a wholly owned subsidiary of Jet Airways India Limited. It was formed in April 2007 when Jet Airways acquired ailing rival Air Sahara for Rs 14 billion. A value based airline, it provides connection to 32 cities including two international cities with 141 daily flights. Positioned as a Value based Airline, JetLite offers value for money fares, in flight meals at no extra cost, in flight shopping, frequent fliermile s as a partner airline to Jet Privilege and much more. Spicejet follows a typical Low Cost Carrier (LCC) business model and the company operates 18 Boeing 737 - 800 aircraft to 17 destinations. In the last three years, airline has flown over 8.1 million passengers and presently has over 10% market share. Launched in October 2005, Paramount Airways is a premium service scheduled airline operating in South India connecting Chennai, Madurai, Coimbatore, Bangalore, Hyderabad, Vizag, Kochi and Trivandrum. With 52 daily flights to ten 25 destinations across Southern India, the airiines has the maximum daily frequency of flights in all the sectors it flies. Currently airline has five aircrafts. With a fleet induction of seven more aircraft in 2008, the airline would add on another 15 more by end 2009, taking the total fleet strength to 27. Airline plans to have a fleet of 40 aircraft by end 2010 with maximum connectivity in South, West and Northern markets. Started just two years ago as India's first all Business Class service airline, the company has done exceedingly well notching up a market share of 26% in the Southern sector. Go Airlines (India) Private Limited is the aviation foray of the Wadia Group, The airline operates its services under the brand GoAir. GoAir launched its operations in November 2005. GoAir, a low-fare carrier launched with the objective of commoditising air travel, offers airline seats at marginal premium to train fares across India. The airline currently operates across 9 destinations through 80 daily flights. The airline uses the state-of-the-art Airbus A3 20 aircraft fleet. GoAir plans to increase its fleet size to 18 by March 2009 and 34 to March 2011 to induct new routes while efficiently servicing existing ones. IndiGo Airline currently operates 19 aircraft with 118 daily flights connecting 17 destinations, including Agartala, Ahmedabad, Bangalore, Bhubaneshwar, Chennai, Delhi, Goa, Guwahati, Hyderabad, Imphal, Jaipur, Kochi, Kolkata, Mumbai, Nagpur, Pune and Vadodara. IndiGo plans to serve approximately 30 Indian cities by 2010, with a fleeto f approximately 40 A320s. 2.3 Growth of Civil Aviation Industry in India The civil aviation sector in the country has witnessed a boom as passenger traffic and cargo movement have both registered exponential growth (MoCA, 2007b). This change has been largely due to the open sky policy of increased liberalization in both domestic and international sectors. The year 2007 especially witnessed remarkable growth in air passenger traffic. Domestic airlines carried a total of 43.2 million passengers during 2007 compared to 32.7 million in the preceding year, resulting in grov^h of about 33 per cent (Sinha, 2008). Moreover, the scheduled domestic air services are now available at about 82 airports as against 75 in 2006 (MoCA, 2007a). 26 With less than 1 percent of its population currently traveling by air, India's growth potential in this sector appears to be phenomenal. Within a period of 15 years, the number of carriers has grown from 2 to more than 10. Over 135 aircraft have been added in the past two years (CAPA, 2007a). Exhibit 2.2 details the growth of domestic passenger traffic during the last 10 years. Exhibit 2.2: Domestic Passenger Traffic (1996 - 2007) Domestic Passenger Traffic cxn^V cvJ>' oJ"K cJ^" <^r^ oS^^ <#J>' d?n^> cJ^' CN.^ c<.V^ cvJ>' cVJ" r^.^^ r^r ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ Year •NATDNALCARRERS •PRIVATE CARRIERS •TOTAL Source: Bansal, S. C, Khan, M. N., & Dutt, V. R. (2008a). Economic liberalisation and civil aviation industry. Economic & Political Weekly, 43(34), 71-76 2.4 Quality of Customer Service in Airlines of India Air India has been awarded the 5th "Mera Brand Award" after it was voted the "Most Preferred Domestic Airline" in the country at the Consumer World Awards ceremony in New Delhi on March 19, 2008. Air India won the Reader's Digest Trusted Brand Gold Award 2008 in the Airline category. Jet Airways has won numerous awards for service excellence, including "Indian Domestic Airline with Spectacular Growth" and "India's Most Popular Domestic Airline" by SATTE (South Asia Travel and Tourism Exchange) in April 2006. Jet Privilege - Jet Airways' Frequent Flyer programme for the third year in succession was conferred the Freddie Award, this time in the highly coveted category of 27 "Programme of the Year" for Japan, Australia, Asia and Pacific regions. At the 19th Annual Freddie Awards ceremony, Jet Privilege is the only programme to be featured in the 'TOP 5' in all the 9 categories of the Freddie awards. At the core of Jet Airways quality systems are well-defined processes (Indian Management, 2004). The Chairman of Jet Airways, Naresh Goyal, was honoured with the 'Business Person of the Year' award at UK Trade and Investment India Business Awards 2008 for his significant contribution to India-UK business relations and for making the UK a strategic and pivotal destination in Jet Airways' aggressive international expansion plans. With the merger of Kingfisher Airlines and Deccan, the airline covers all segments of air travel from low fares to premium fares and offers the maximum number of flights offered by any single airline network in India. While Kingfisher serves the luxury segment, Deccan caters to the broadest spectrum of travelers in India and offers value added services at the most competitive fares. The result is a world-class airline promising efficient service, the highest standards of safety and on time performance. Kingfisher Airlines has recently been conferred the '5 - Star Airline Status', the most recognized and prestigious award that honours airline Product and Service Quality Excellence, by Skytrax, the world's leading, independent travel forum and air travel information organization. Kingfisher Airlines is India's first and only 5-Star airline and the only one to offer a premium first class service on domestic routes. Besides being the first and the only airline to offer in-flight entertainment on every seat in the domestic skies. Kingfisher Airlines is the only one to offer LIVE TV with 16 channels of live & exciting content. Kingfisher Airlines has received 30 awards for innovation, customer responsiveness and was voted the -Best New Airline of the Year- within months of its launch. Deccan has been adjudged the Best Domestic Low Cost carrier 2007 for the second year in a row by Galileo Express TravelWorld Awards. SpiceJet was recognized as the Best Low Cost Airline for 2007 by TAFI (Travel Agents Federation of India), awarded at Kota Kinabalu, Malaysia. A public opinion survey by Outlook Traveler, a leading travel magazine (2008 Feb), has ranked SpiceJet as the best airline for its services, efficiency, connectivity and value for money over other low cost carriers. With a Technical Dispatch Reliability of 99.6%- better than the world average and with On Time Performance of over 80% - it has become the low - cost airline of 28 choice for all. Over 40 % of its passengers are business travellers, 45% are repeat travelers and over 90% of the passengers have recommended the airline by word of mouth. Paramount Airways is the first premium service, all business class airline. The top quality service includes state-of-the-art Embraer aircraft, luxurious recline window or aisle seating, airport valet service, round-the-clock lounge access, gourmet meals and personalized in-flight attention. Paramount Airways, the leading airline in South India has been awarded "The Century International Quality Era" in the gold category at the International Quality Convention in Geneva Switzerland in March 2008. This international award has been given to Paramoimt for furthering our reputation and position by implementing customer service excellence through quality and iimovation. In 2007, the airline won the prestigious "International Arch of Europe Award" for technology and innovation and the 'Award of Excellence' conferred by the Institute of Economic Studies. GoAir is positioned as 'the Smart People's Airline'. It's captivating theme, 'Fly Smart' is aimed at offering passengers a consistent, quality-assured and time- efficient service through 'pocket-friendly' fares. GoAir is based on 'punctuality, affordability and convenience' business model. The airline has a strategic tie-up with Singapore Airlines Engineering Company (SIAEC), one of the Best engineering companies in the world, for the maintenance and engineering requirements of its aircraft. The airline has also partnered with Radixx International, a leading technology provider of automated aviation and travel related software solutions, for the use of its Air Enterprise. The adoption of such technology solutions enables GoAir to achieve superior process efficiency, thereby helping transfer a greater portion of time savings to its passengers. In March 2008, GoAir has won the PATWA award for "Best Domestic Airline For Excellence in Quality and Efficient Service" at Global Tourism Event - ITB, Berlin, in a very stiff competition amongst airlines of Asia Pacific Region. This is the second consecutive year that GoAir has been awarded this prestigious award. Indigo airline was awarded "Best Low-Fare Carrier in India for the year 2007" by the Air Passengers Association of India (APAI). 29 2.5 Challenges The global crisis resulting from high oil prices and declining traffic has hit India hard. Growth has slowed from 33% in 2007 to 7.5% for the first six months of this year (2008). Indian carriers are likely to post US$ 1.5 billion in losses in 2008, the largest outside the US (Concil, 2008; Bisignani, 2008b). Jet airway's per-day losses are said to be Rs 90 million to Kingfisher's Rs 50 million and the merged carrier Air India's Rs 100 million (Pinto 2008). Spicejet is projecting a loss of upto Rs 1 billion in 2008. Wilbur Ross, the US billionaire, has picked up strategic stake in Spicejet by investing 3.45 billion rupees (£40 million) into Spice Jet. Even the Wadia Group firm GoAir plans to offload 26 percent stake in the low-cost carrier. Domestic airlines have lost around Rs 35 billion in 2006-07 (DGCA, 2008). Table 2.2 gives the detailed financial results of scheduled domestic airlines during 2006-07. Phenomenal growth in the airline sector in India has no doubt thrown up exciting opportunities and, at the same time, challenges too. Aviation infrastructure in major cities is already witnessing excessive pressure, particularly during peak hours. Furthermore, there are some other issues that need to be addressed by the stakeholders in the industry if they wish to improve the situation. Some of these challenges are given below: Declining yields: LCCs and other new entrants command about two-fifths of the market share. During a time of escalating costs, legacy carriers are forced to match LCC fares. More players are being attracted owing to growth prospects which imply more competition at lower fares. Thus, to survive and grow, airlines have to build on their cost efficiencies and other economies. Distribution cost one of the key 'controllable' expenditures in an air carrier's cost structure; thus an effective and efficient distribution mechanism goes a long way in making an airline successful (Ramachandran, 2005). The proposed entry of at least four regional aviation start ups - Air Dravida, Star Aviation, MDLR Airlines and Trans India - could cause further headaches and even delay the break-even for existing airlines. Gaps in Infrastructure: The fast pace of growth of Indian airline industry has created a huge vacuum in the infrastructure required to support this increase in number of passengers, aircraft and flights.Infrastructur e is the weak link in the chain (Pitalwalla, 2006). India's airports are expensive and overcrowded with low service 30 .r-~^ O o o © ^" O © a e o loHHo i o e o o e e o o o o o o o 0 t/) VO 00 r-; fH q OV M t») I-; «»J rj 03 NO Ol 00 M fi »H 1«H • r-i »^ « \Q d 0\ VJ •* 09 ri « m ri in 1-^ l~- fK d NO (^ d •* ri > Higher fuel consumption due to long holding times - on ground as well as in air > Lower utilisation of aircraft resulting from slot constraints and air traffic congestion > Sub-optimal route network strategies because of insufficient night parking stands at major airports, and > Lack of advanced navigational aids like Approach Lighting System (ALS) at the airports While a beginning has no doubt been made in the context of upgrading of existing infrastructure, the results, at current sluggish pace, may be visible after a few years. High Input Costs: Higher Aviation Turbine Fuel (ATF) prices are largely responsible for the red ink on the books of airlines in India. ATF, which used to constitute around 40 percent of the operating cost for airlines, now accounts for up to 50 percent after the prices of ftiel have tripled during the last three years (Pinto, 2008). ATF prices have gone up from Rs 26,000 per kilolitre in 2005 to more than Rs 70,000 in June 2008 (Bansal, Khan & Dutt, 2008a). Airlines have been regularly topping the base fares by fuel surcharge and congestion fee, which have increased to Rs 2,400 for distances below 750 km and Rs 3,150 for longer flights. It is likely to increase fiirthero n account of increase in jet fuel charges by the oil companies. Aviation Turbine Fuel (ATF) prices continue to be abnormally high in India compared to those charged globally. In fact, ftiel costs in India are about 65 percent higher than international standards (CAPA, 2007a). ATF cost / kilolitre is USD 755 in Delhi and USD 780 in Mumbai as against USD 455 in Singapore and USD 497 in Dubai (Trivedi, 2007). High basic rates are aggravated by heavy taxes imposed by State Governments. These prices are around 40 percent higher than international prices due to higher base price and taxes. Sales tax on ATF varies from 20 to 30 32 percent in most states, while excise and customs duties on the fuel are 8 percent and 5 percent respectively. Taking note, Central Government has announced a cut of 5 percent in customs duty on ATF, resulting in 4.3 percent reduction in fuel price by State-run oil companies. To ease the burden, soon the State Governments too plan to discuss the issue of reduction in sales tax after getting full details of price fixation of ATF from the civil aviation ministry. Consequently, the Indian aviation industry has all along been lobbying hard for a better deal in terms of lower ATF prices matching international levels. To make the matter worst, there is unfair discrimination between turboprops and regional jets with latter being charged higher sales tax for their fuel needs compared to the former. The fact that fiiel costs constitute a significant part (35 - 50%) of the total operating costs of airlines necessitates the need of utilizing the derivatives to fix their costs allowing them to stay competitive and yet remain healthy (Shunmugam, 2008). Other reasons for high input costs are increased maintenance charges, high aircraft lease rentals, and high manpower costs due to shortage of skilled technical personnel. Exhibit 2.3 gives the comparative input costs for FSCs and LCCs in India. As a result of price increase, passenger load has fallen to an average of 55 to 60 percent per flight from last year's (2007) peak of 70 to 75 percent. A drop of 15 percent is expected in domestic business traveler, who constitutes approximately 60 percent of Rs 18,000 crore domestic air travel market. International monitors have reduced the forecast for Indian market as a result of the slowdown in the aviation sector. Signals related to cash-flow problems and the capital crunch owing to rising operational costs and subsequent falling demand are already emanating fi-om the industry. Lack of Skilled and Qualified Personnel: There is a severe lack of skilled and qualified personnel right across the sector, even at today's air traffic levels. The shortage is particularly noticeable in case of pilots, licensed engineers, air traffic controllers, cabin crew and other skilled staff required to manage passengers, baggage and cargo. This will only be exacerbated by the growth in the industry. 33 }5 ?: «8 a '•B c (0 O O _J "O c I (0 o(0 v> u. I 3 U I 3 •^ •> m (0 (0 o o > re s ki re Q. E o o t •a CO ;^ UJ s; « Si 3 Excess Capacity: The industry currently has an overcapacity of about 20 percent. Airlines have not just started cutting down their route expansion plans but are also canceling flights on certain low-traffic routes. South India is facing most of the cancellations because the new airports at Hyderabad and Bangalore require quite a bit of city travel. Passengers are not willing to travel these distances for short distance flights. Faced with these bleak prospects, airlines are even canceling or cutting deliveries of new aircraft due this year or sub-leasing them to other global carriers. In the backdrop of high jet fiiel costs and excess capacity in the market, most of the full service carriers are significantly cutting costs by slashing employee allowances, reducing in-flight catering expenses on short-haul flights, cutting maintenance costs, restructuring their processes and increasing dependency on internet as a sales channel, whereas low-cost airlines are increasingly adopting additional types of sales and services like sharing ticket reservation systems or entering into code-share agreements so as to improve passenger load. Jet Airways has signed a two-year contract with Shell-MRPL (Mangalore Refinery and Petrochemicals Limited) joint venture for supply of ATF, while Kingfisher is exploring the option of directly importing ATF. Airlines are also talking about collaborating for operational synergies. Air India, Jet Airways and Kingfisher Airlines plan to save around Rs 10 billion by moving towards a zero-commission structure for travel agents. If the current aviation scenario persists, domestic carriers may move towards second round of mergers and acquisitions as smaller low-cost airlines, hurt by rising fuel prices and decreasing passenger load seek a graceful exit. Perhaps consolidation and restructuring are the way to go for Indian carriers to beat losses and stay afloat. To make their voice heard, at the start of 2007, domestic airlines formed an umbrella organisation under the banner Federation of India Airlines (FIA) (Pandit, 2007). It aims to look at common issues affecting all the airlines, undertake research, bring out reports and publish papers to convince and support the Government in making informed decisions. 35 A concerted implementation of the above measures would go a long way in overcoming the challenges mentioned above and lowering costs for the commercial aviation, thereby making air transport more affordable and its use more widespread. 2.6 Opportunities There is no doubt that the future of Indian aviation sector appears to be bright with huge potential for growth. Estimates suggest that every $100 spent on air transport produces benefits worth $325 to the economy and 100 additional jobs in air transport resuh in 610 new other jobs (Brady, 2007). It is expected that 4 million aviation jobs will be created in the next 10 years (PTI, 2007a). Some of the emerging opportunities for different stakeholders in the aviation industry are discussed below. Large and growing potential market: India is the fourth largest and second fastest growing economy in the world registering a GDP growth of 9.2 percent in Q3 (2006). The disposable income of India's 300 million middle class is expected to increase at an average of 8.5 percent per annum till 2015. Domestic tourism market is already 390 million strong, growing at around 13 percent with foreign tourists touching 4.43 million mark and trends suggesting a growth of around 13 percent. All of these factors present a huge market which can be tapped by the players in the civil aviation industry. Beginning has already been made by different airlines by offering a number of attractive packages. Air Cargo: Freight carriage in India is currently at around 4,200 tons per day with Compounded Annual Growth Rate (CAGR) of 15 percent over the past 2 years. It has been fuelled by a fast growing economy with strong industrial base. The air cargo demand is forecast to grow at 11.4 percent per annum till 2011-12. To support the growth in the cargo sector, the MoCA is proposing exclusive cargo airports, which may be privately owned. The MoCA has also raised FDI from 49 per cent to 74 per cent in the cargo sector to facilitate building of cargo airports at various business centres across the country. Currently Blue Dart, owned by DHL Express, is the main player in the market. It currently has six aircraft: four Boeing 737 and two Boeing 757 freighters, providing a network payload of 250 tones across 60 route connections each night. Air India Cargo, a wholly-owned subsidiary of NACIL, plans to lease freighter aircraft and 36 increase its revenue by 10 per cent to around Rs 9 billion by 2008-09. According to Chairman of Jet Airways, Mr Naresh Goyal, Jet Airways also plans to launch a cargo airliner in 2008 (Choudhury, 2007). Infrastructure to Support the Indian Civil Aviation Industry: The growth in domestic aviation sector has necessitated infrastructure upgrade. Approximately $110 billion will be invested in the Indian Civil Aviation industry by 2020 - $80 billion on aircraft and $30 billion on infrastructure (Chawla, 2007). Development of airport infrastructure is being undertaken through the Public-Private-Partnership (PPP) route in major metro cities like Delhi, Mumbai, Bangalore and Hyderabad while modernization of Kolkata and Chennai airports is being undertaken by the AAI (Pilling, 2005; MoCA, 2007b). The aim of the government is to transform these airports into world-class facilities without any delay through this hybrid mechanism. AAI has also undertaken an ambitious project to modernize 35 non- metro airports. It is expected that terminal buildings and associated side works in 24 airports will be completed by March 2009 whereas in the remaining 11 airports, it would be completed by March, 2010 (MoCA, 2007b). The Government is upgrading the Civil Navigation System (CNS) and Air Traffic Management (ATM) infrastructure to ease congestion at the existing airports. The aim is to improve management of the sky and reduce flying times, allowing more flights to take off and land at the airports. Maintenance, Repair and Overhaul (MRO): At present, there is no large MRO centre in India. Even within 5-hour fly zone from India, this facility does not exist. D checks' are done overseas mainly in Dubai and Singapore. Huge investment is required to ensure servicing and maintenance of increasing fleets. There is a growing demand for airframe, engine and component overhaul facilities. Thus, there exists an opportunity for entrepreneurs to tap the MRO business. India offers substantially lower labor cost - 60 percent lower than Western Europe and USA. The MRO facilities, once established in India, can tap the international market as well due to competitive rates for labour and other facilities. The Government too has recognized the potential and has permitted 49 percent FDI in MRO business. Some positive developments in this segment have already taken place. Gulf Aircraft Maintenance Company (GAMCO) has signed a maintenance support agreement for 37 10 Kingfisher Airlines Airbus A320 aircraft. NACIL has a tie-up with CFM, a joint venture between Snecma (SAFRAN Group) and GE Aviation to establish a joint venture MRO facility in India for CFM56 engines. KLM has agreements with other airline companies such as Spicejet, Jet Airways and JetLite for MRO services. Kingfisher Airlines, GMR Group; Lufthansa Technik AG, Germany; Jupiter Aviation (in consortium with European Aeronautic Defence & Space); and NACIL are also planning to set up comprehensive MRO facilities in India. Ground Handling: Ground handling work entails two basic activities — (i) passenger handling at the landside and ramp, including loading and unloading of aircraft, and (ii) aircraft handling. Currently, all airlines do their ovm ground management, which involves handling of passengers and baggage at the airport and loading or unloading of aircraft. The DGCA has notified that starting from January 1, 2009, only three designated agencies would be allowed to carry out ground handling ftanctions at six metro airports in the country: 1. The airport operator itself or its Joint Venture (JV) partner, 2. Subsidiary companies of the national carrier Air India or its joint ventures specialised in ground handling services. 3. Any other ground handling service providers selected through competitive bidding on revenue sharing basis by the airport operator. After implementation of the aforesaid policy, functions such as loading, unloading and delivery of baggage from the aircraft; cabin cleaning; transportation of passengers from terminal to tarmac and vice-versa would go out of the private airlines' purview. For all other airports in the country, airline operators, in addition to the three designated agencies, would be allowed to undertake self-handling. The Government, however, has not allowed foreign airlines to undertake self-handling. India's ground handling market is estimated to be Rs.ll billion (USD 247.8 thousand) per annum. NACIL presently enjoys 55-percent market share in the Indian ground handling business (Zatakia, 2007). It is expected to grow at 15 percent CAGR till 2011-12. Significant opportunities exist for entrepreneurs in the form of third party handling as well as entering into service contracts with private airports / AAI to offer comprehensive ground handling solutions. Air India and Singapore Airport Terminal Services (SATS) have formed a joint venture AISATS to provide 38 ground handling services to domestic and international carriers at Bangalore and Hyderabad International Airports. Training: Airlines in India will, in near future, need trained pilots, engineers, cabin crew and other ground handling staff. There is projected requirement for 3,600 additional pilots in the short-to-medium term. Entrepreneurs can capitalize on the emerging demand for (i) training establishments for cabin crew, engineers and other staff and (ii) flight simulators for training pilots. At present, there are 39 flying schools in India which are authorised to train for various licences such as Private Pilot Licence and Commercial Pilot Licence. 28 of these institutions are controlled by State Governments. The remaining 11 are operated by private entrepreneurs. These schools produce about 150 commercial pilots each year. DGCA has received 37 proposals to set up new flying training institutes in India. Existing players have already taken some steps to tap this potential. NACIL has a Central Training Establishment at Hyderabad, and Jet Airways has pilot training centre at Mumbai. Budget-carrier Deccan has tied up with Frankfmn Institute of Air Hostess Training as an exclusive cabin crew partner. Kingfisher Training Academy is laimching 12 new centres by February 2008 to meet the acute shortage of manpower in the airlines and hospitality sectors. Leveraging the Internet: Increasing number of passengers are booking their tickets directly on the airlines' websites. Traditional sales channels with paper tickets cost airlines around 10 percent of ticket price. On the other hand, e-ticket sale from own website costs an airline only 3 percent of ticket price. For every direct booking on their website, airlines save an estimated USD 4 plus 5 percent agency commission (Trivedi, 2007). Airlines can also turn their websites into one stop shops for all travel related services, generating additional revenue. Access to new markets: The existing civil aviation policy allows overseas flights only to those domestic airlines that have at least five years' experience in the domestic market. It is also necessary to have a minimum fleet of 20 aircraft to be eligible to fly overseas. Consequently, at present NACIL, Jet and JetLite have the permission to fly abroad. Deccan is expected to join soon as it completes its five years of commercial operations on August 26, 2008. The Ministry of Civil Aviation 39 has given its traffic rights approval to Jet Airways on the India-Gulf/Middle East routes with effect from 1st January 2008. Jet Airways has already launched flights to Kuwait, Muscat, Doha and Bahrain, becoming India's first private air carrier to flyt o the Gulf It has also started flight on Mumbai-Shanghai route. Jet is keen on making Shanghai its hub to facilitate operations in the Asia-Pacific region. Thus, these airlines will have access to new revenue streams and that may help even out the seasonality factor in their domestic operations. It will also spread the risk of downturn in a single market. However, the above opportunities will pose a challenge to the some of the existing players as the risk - cycle of increased competition, low yields, and growth will be transferred to the international arena leading perhaps to more cut-throat competition. 2.7 Future Prospects India's aviation sector is a sunrise industry and will require an investment of over USD 120 billion over the next ten years (lonides, 2007). Two-thirds of this amount is likely to. be absorbed by aircraft purchases and the remaining would be used for developing infrastructure. The number of civilian aircraft in the country is estimated to swell from 350 to 1000 by 2020. Domestic passengers for the industry are forecasted to rise from 35 miUion currently to 182 million by 2020. As the competition gets fiercer, fares would be ftirther reduced and new routes would be added to the existing itinerary. Airfares on metro-to-metro routes are expected to come down, largely due to the competition driven by the IPO-powered aircraft acquisition spree. Non-metros may not experience significant reduction in fares. A booming market always attracts new players. Indians have emerged as big buyers at the Paris Air Show in 2005 with orders for 160 aircraft, worth USD 13 billion (Spaeth, 2005). In fact, domestic operators have plans to acquire 434 new carriers. The MoCA has recently announced new guidelines for airlines planning to start regional operations between smaller cities or connecting towns and India's large cities with small planes that can seat up to 100 passengers. Four companies - M/s MDLR Airlines Private Limited and M/s Jagson Airlines for Northern Region, M/s Star Aviation for Southern Region and M/s Zav Airways for North-East - have been 40 shortlisted by the Ministry for awarding license to start regional services (MoCA, 2008). Thus, this sector is bound to witness more action in the near future. 2.8 jChapter Summary Indian aviation market is growing at a scorching pace. Private airlines have changed the rules of the game in the Indian civil aviation sector in recent years. The entry of budget airlines like Deccan, introduction of cheap airfares by other domestic carriers, rising levels of income and growing aspirations of people have created a new paradigm: air travel is no longer reserved for the elite. The guidelines that regulate the sector are under constant review. Gradually, the bureaucratic hurdles are being removed allowing Indian airlines to compete internationally in in-flight entertainment, cuisine, comforts and other services. These reforms along with boom in the Indian economy have led to the high level of growth in the industry (Bansal, Khan & Dutt, 2008a). Despite a growing market, ironically, airlines in India are fighting for survival. CAPA projects combined losses of US 400-500 million for financial year 2008-09 (CAPA, 2008). A host of initiatives are required to tide over the current situation. For service providers, there is a pressing need to control costs and improve quality of service. The government needs to liberalise rules and regulations governing civil aviation, without compromising on safety and security. It may reduce ATF prices, adjust tax rates, revise lease rentals, and speed up development of infrastructure to match growing demand. The airlines as well as entrepreneurs may jointly develop a large pool of skilled/technical manpower and attract more professionals to manage the aviation industry. Overall, the current state of Indian aviation industry portrays mixed shades. On the one hand, a significant enthusiasm in the aviation sector is primarily attributed to the increased number of private players and emergence of competitive environment. On the other hand, it is also evident that there is a need to strengthen infrastructure network by speedily implementing the proposed projects. 41 CHAPTER 3: REVIEW OF LITERATURE 3.1 Concept of Service: An Overview 3.1.1 Characteristics of Services 3.2 Understanding Service Quality 3.3 Service Quality and Customer Satisfaction 3.4 Models of Service Quality 3.4.1 SQM1. The Disconfirmation Model Of Service Quality 3.4.2 SQM2. Nordic Service Quality Model 3.4.3 SQM 3. Kano's Model Of Customer Satisfaction 3.4.4 SQM 4. The Gaps Model Of Service Quality 3.4.5 SQM 5. Performance Only Model Of Service Quality 3.4.6 SQM 6. Six-Sigma Model Of Service Quality 3.4.7 SQM 7. Internal Service Quality Model 3.4.8 SQM 8. Customer Equity Framework 3.5 Dimensions of Service Quality 3.6 Service Quality in Airline Industry 3.7 Role of IT in Service Delivery 3.8 Low Cost No Frills Model of Customer Service 3.9 Recent Studies on Civil Aviation in India 3.10 Research Gap 3.11 Chapter Summary CHAPTER 3: REVIEW OF LITERATURE Chapter Overview The goal of this chapter is to provide a review of the extant literature relating primarily to service quality in the context of airline industry. Based on this literature survey, an attempt has also been made to establish the research gaps, which provided the basic framework on which the conceptual model of present research is based. The literature on services marketing has been examined from a purely historical perspective to determine its impact on the field of service quality. Then, a brief review of the relationship between customer satisfaction and service quality precedes the literature review defining service quality, and issues in measurement of service quality. Various models of sei^vice quality developed over time have also been discussed. The study of the literature also focuses on the importance of service quality measurement in airlines, service as an attribute in airline selection, impact of service quality on airline profitability, and the validity of scales like SERVQUAL in airline applications. LCC model of service delivery and role of IT in airline service delivery too has been examined. The chapter concludes by focusing on the recent studies on civil aviation in India and a summary of the research issues. 3.1 Concept of Service: An Overview Service, in general, refers to efforts, deeds or processes consisting of a series of activities performed by the service provider, quite often in close co-operation and interaction with the customer. However, the services marketing literature contains many definitions of services. Gronroos (2007) defines service as a process consisting of a series of more or less intangible activities that normally, but not necessarily always, take place in interactions between the customer and service employees and / or physical resources or goods and / or systems of the service provider, which are provided as solutions to customer problems. Bateson (1992) 42 argued that goods/service dichotomy is a subtly changing spectrum, with firms moving their position within this spectrum over time. Zeithaml and Bitner (2003) holds that services include all economic activities whose output is not a physical product or construction, is generally consumed at the time it is produced and provides added value in forms (such as convenience, amusement, timeliness, comfort or health) that are essentially intangible. Vargo and Lusch (2004) defined service as the application of specialized competences (operant resources - knowledge and skills), through deeds, processes and performances for the benefit of another entity or the entity itself. Kotler & Keller (2006) defines services as any act or performance that one party can offer to another that is essentially intangible and does not result in the ownership of anything. Its production may or may not be tied to a physical product. Kasper, Helsdingen and Gabbott (2006) observed that services are originally intangible and relatively quickly perishable activities whose buying, which does not always lead to material possession, takes place in an interactive process aimed at creating customer satisfaction. 3.1.1 Characteristics of Services Services have five important characteristics - intangibility, inseperability, heterogeneity, inability to own and perishability. Each characteristic poses problems and requires strategies to deal with those problems (Shanker, 2002). Intangibility is one of the most important characteristics of services i.e. they do not have a physical dimension. Often services are described using tangible nouns but this obscures the fundamental nature of the service which remains intangible e.g. 'airline' means air transportation, 'hotel' means lodging rental. Berry (1980) describes a good as an object, a device, a thing in contrast to a service which is a deed, a performance, an effort. He argued that even though the performance of most services is supported by tangibles, the essence of what is purchased is a performance. The implication of this argument is that consumers cannot see, touch, hear, taste or smell a service; they can only experience the performance of it (Carman and Uhl, 1973; Sasser, Olsen & Wyckoff, 1978). This makes the perception of service a highly subjective and abstract concept. 43 The second characteristic of services is the inseparability of the production and consumption aspects of the transaction. The service is a performance, in real time, in which the purchaser cooperates with the provider. The inseperability of the role of service provider and consumer also relates to the lack of standardization since the service provider can alter both - the way in which service is delivered, as well as what is delivered - which has important implications for both the management and the evaluation of the service product. The heterogeneity of services refers to the fact that services are delivered by individuals and therefore each service encounter will be different by virtue of the participants or time of performance. As a consequence, each purchaser is likely to receive a different service experience. The perishability of service describes the real time nature of the product. Services cannot be stored unlike goods, and the absence of the ability to build and maintain stocks of the product means that fluctuations in demand cannot be accommodated in the same way as goods. The time of service delivery is critical to its performance and therefore consumers' experience (Kasper et al, 2006). The purchaser only has temporary access or use of service. What is owned is the benefit of the service, not the service itself, e.g. in terms of a holiday the purchaser has the benefit of the flight, hotel and beach but does not own them. The absence of ownership stresses the finite nature of services for purchasers, there is no enduring involvement in the product, only in the benefit. The impact of service characteristics on the service quality is given below (Kasper et al, 2006): ^- Inability to own a service prevents prior determination of service quality that will be provided. ^ Intangibility prevents customer from being able to make comprehensive assessment of service before, during or after delivery. According to Trifa & McQuilken (2001), customer expectations for service quality do not vary with the level of intangibility of the service. > Customer's involvement in delivery process (inseperability) impacts both real 44 and perceived quality. As a general rule, more interaction between customers and the service organization improves quality, but this is dependent upon a range of issues such as clear communications, responsiveness to requests. Companies must learn to manage the interference of customers with their operations to deliver consistent quality at sustainable cost (Frei, 2006). ^ Heterogeneity (variability) makes the definition and implementation of precise quality standards very difficult to achieve. The organizations should ensure that delivery falls within a boundary, i.e. there is a minimum level guaranteed and a maximum level manageable. ^ Perishability of service may restrict its supply thereby putting staff under pressure. The fluctuations in supply, demand, as well as urgency will impact upon service quality. Potential benefits of high quality service includes (Kasper et al, 2006): ^ Creating competitive advantage by insulating customers from competitors ^ Lowering customer recruitment costs ^ Promoting positive word of mouth as customer talk about the service to others. ^ Improved financialperformanc e ^ Reduced staff turnover Based on the above discussion, the following managerial implications of service quality can be delineated: ^ Collecting feedback from a high proportion of dissatisfied customers, who do not complain but also never use the service again. y Quality costs money and there is a need to measure Return on Quality (ROQ) using measurable performance of service quality improvements relative to the investment made. ^ Segmentation approach is too broad and the expectation variation within each segment too wide. There is need to identify neglected areas of service, which provide opportunities to positively surprise customers, thereby maintaining interest. 45 ^ Competitor intelligence needs to be supplemented with customer research to provide quality service to the customers. > There needs to be trade-off between human and technology for providing service. The decision about the human technology mix must be dependent upon customers' reaction and the service dimensions they value. 3.2 Understanding Service Quality Service marketing has emerged slowly as a sub-discipline of marketing. Fisk, Brown and Bitner (1993) labeled the pre-1980s as the "crawling out" period for services marketing. Earlier scholars sought to delineate services from goods and to understand management of the marketing of intangibles (Vargo et al., 2004). The service marketing literature has now reached maturity stage (Gabbott & Hogg, 1998; Furrer & Sollberger, 2004) Much of the research in services marketing centers on understanding services and service quality from customer's point of view (Brown & Bitner, 2006). The use of service quality as a competitive edge has been extensively addressed in marketing literature (Shostack, 1977; Lovelock, 1983; Gronroos, 1978, 2006; Parasuraman, Zeithaml & Berry, 1985, 1988, 1991, 1994A, 1994B; Bitner, Booms & Tetreault, 1990; Rust, Zahorik & Keiningham, 1995; Rust & Chung, 2006; Kasper et al., 2006). In this context, Table 3.1 gives a historical background of evolution of service quality research. 46 00 00 c c o a (D c •S re u 3 3 O CQ 3 U.3 Q. o "is g w 2 W 2 00 n 00 00 0) 0\ OS 0^ as >- JO, c "2 0) ca c ^'1 u re o 11 •2 ? <« •^ (0 > o a§: § c t*^ 00 (<-( an 00 Ct- 00 V- 00 C! O bO o c o — i= o _g O _C ea 0) ea a) M > ca ;3 ca (11 I: ta ca S £ mi ^ S3 T3 U E ^ •S c3a ca c 1 N u b ca ra ca b 6 0) O- 'I 3 ca it k^ ca N CO N ca U H U H ON Service quality has been at the centre of any discussion about service marketing management. The conceptualization of service quality, its relationship to satisfaction and measurement methods has been the central theme of literature on the subject. The pressures driving successful organizations toward top quality service make the measurement of service quality and its subsequent management of overall importance (Robledo, 2001; Harmon, Hensel & Lukes, 2006). Whilst there is general agreement that the evaluation of services is more subjective than tangible goods and, therefore, an understanding of consumers is central to understanding service quality, there has been less agreement about how to operationalise service quality as a construct. In fact, service quality remains illusive, difficult to define and measure (Cronin, Brady & Hult, 2000). Rathmell (1966) initiated early debate over the definition and classification of services. He dealt with issues relating to difficulty in conceptualizing products comprising both goods and services, and the nature of service satisfaction and the goods - service continuum. Shostack (1977) attempted to differentiate services from the dominance of the product orientation. He suggested how marketers need to compensate for the problems presented by managing peripheral cues. Lovelock (1983) recognized the diversity between services and approaches the problem inductively by trying to establish commonalities across service products. Zeithaml, Parasuraman & Berry (1985) reports that discrepancy exists between the problems and strategies cited in the services marketing literature and those reported by actual service suppliers. Service marketing literature needs to recognize and analyze additional problem areas that may be particularly troublesome to service firms. By concentrating upon the nature of the service act, the type of relationship, degree of customization, nature of demand and supply and finally delivery. Lovelock (1983) explored a series of sub-questions through 'insights and implications' structure. Wliile Gronroos (1978) provided insights from services companies as to how the marketing mix is planned and applied bearing in mind the characteristics of the service product. The article presented three dimensions - importance of accessibility, the human element in service delivery and the provision of auxiliary (or augmented) service offerings - which the author believes are central to the development of contextualized marketing mix. Zeithaml (1981) attempted to explain 50 some inherent differences in how consumers use and evaluate services as opposed to physical products. He argued that characteristics of services suggest that they are high in experience and credence qualities but low in search qualities representing an increased difficulty for consumers in evaluation. Parasuraman et al. (1988) provided the notion of 'gaps' between the expectations of service and subsequent perceptions of what is delivered. They opined that these gaps are located throughout the organization between frontline staff, customers and managers. The identification often dimensions of service quality, identified by these researchers, and later refined to five - reliability, assurance, tangibles, empathy and responsiveness (RATER) - has dominated the literature in the field of service quality. Much of the research in this area, since introduction of SERVQUAL in 1988, has been concerned with validating or challenging the construct. Cronin et al., (1992) argues the performance based measures and presents another scale i.e. SERVPERF scale. Teas (1993) questioned the conceptual and operational validity of the perceptions minus expectations framework which were responded by Parasuraman et al. (1994b). While, Buttle's (1996) review of SERVQUAL concentrates on systematically examining the theoretical, operational and statistical criticisms of the SERVQUAL scale and raises a number of directions for future research in the area of service quality measurement. Another thought is that of Service Dominant Logic (Vargo et al, 2004; Lusch and Vargo, 2006) that places activities driven by specialized knowledge and skills, rather than units of output, at the center of exchange processes. The logic specifies that it is service that is exchanged for service. The following eight Foundational Premises (FP) summarize S-D logic: FPL The application of specialized skill(s) and knowledge is the fundamental unit of exchange (Service is exchanged for service) FP2. Indirect exchange masks the fundamental unit of exchange FP3. Goods are distribution mechanisms for service provision FP4. Knowledge is the fundamental source of competitive advantage FP5. All economies are service economies FP6. The customer is always a co-creator of value FP7. The enterprise can only make value propositions 51 FP8. A service - centered view is customer oriented and relational It can be seen that service quality has become a major area of attention to practitioners, managers and researchers owing to its impact on business performance, customer satisfaction, loyalty and profitability (Cronin et al., 1992, Seth et al, 2005). 3.3 Service Quality and Customer Satisfaction Customers have a difficult time in attempting to determine service quality based upon objectivity and as a result need some structured effort on the part of the service provider to plan the service function (Shostack, 1985). Boulding, Kalra, Staelin & ZeithamI, (1993) noted that service quality and customer satisfaction were treated as one and the same by the business press. They indicated that this should be a dynamic process model to examine the subject from expectations to behavioral intentions. Ueltschy, Laroche, Tamilia & Yannopoulos (2004) found that some measures of satisfaction and service quality are non-equivalent across cultures. There has been a substantial amount of posturing in the literature as to whether both constructs (satisfaction/dissatisfaction and service quality) are truly attitudes. Bitner (1990) viewed satisfaction/dissatisfaction as an episodic, transaction-specific measure. Bitner and Hubbert (1994) subsequently raised the question whether or not service quality and customer satisfaction is distinguishable from the customer's perspective. However, studies by Cronin et al. (1992) treat satisfaction/ dissatisfaction as a cumulative rather than a discrete measure. It became obvious that satisfaction/dissatisfaction had to be separated into two distinct types based on a given service encounter or a total service experience. Parasuraman et al. (1988) described service quality as "similar in many ways to an attitude" developed over all encounters with the service providing firm. Cronin et al. (1992) found that there is a major problem when service quality is not termed an attitude. They saw a significant problem when the disconfirmation paradigm is used to measure perceptions in service quality, and it has also been used to distinguish customer satisfaction from service quality. This was identified as an inconsistent 52 approach with the differentiation noted between these constructs in the satisfaction and attitude literature. A set of definitions to clarify the different types of evaluation methods was proposed by Bitner et al. (1994). They noted and established conceptual links between satisfaction in single service encounter, satisfaction with the entire service experience, and service quality. Consistently good service mitigates one single episode of poor service, and as a result would not significantly impact overall satisfaction. Conversely, negative infoimation from some credible source may cause the customer to evaluate service quality less favorably, even though the past experiences have been very satisfying. Anderson, Fomell & Lehmann (1994) investigated the relationship between customer satisfaction, market share and profitability and found that market's expectations of the quality of a firm's output positively affects customers' overall satisfaction with the firm, which leads to economic benefits. From these studies, it is implied that service quality is an input and customer satisfaction is an output. It is reasonable to conclude that there is a consensus among the various researchers that while sersdce quality and customer satisfaction are two different constructs they can still have common indicators. Likewise, there is agreement in the research literature that both service quality and customer satisfaction have an influence on customer loyalty(Bloemer, Ruyter & Wetzels, 1999). 3.4 Models of Service Quality A conceptual model is a simplified description of the relationship that exist between latent and observed variables. It is envisaged that conceptual models in service quality enable management to identify quality problems and thus help in planning for the launch of a quality improvement program thereby improving the efficiency, profitability and overall performance (Garver, 2003; Seth et al, 2005). The study examines eight different service quality models reported in the literature. The critical review of the different service quality models (SQM) is intended to derive linkage between them and highlight the area for further research. 53 3.4.1 SQM 1. The Disconfirmation Model of Service Quality The model is based on the early studies of Oliver (1997) and Olshavsky and Miller (1972). It provides a customer referenced method for assessing service quality. In this model quality is implied if the customers' expectations of the service experience beforehand are exceeded by the service when it is delivered. Expectations and subsequent performance are fundamental to conceptualization of service quality. Customer's service expectations exist at two different levels: a desired level and an adequate level. The difference between the desired and adequate service level is zone of tolerance. Considerable variation in customers' tolerance zones are found between various services, between various service attributes and also between events. The formation of expectations (Exhibit 3.1) involves individual expectation drivers (enduring service intensifiers, transitory service intensifiers and situational factors) and environmental expectation drivers (explicit service promises, implicit service promises and social information sources). The formation of expectations is particularly complex and almost impossible to manage from the organisation's perspectives. Exhibit 3.1 Determinants of Zone of Tolerance Individual Environmental expectation drivers expectation drivers Enduring service Explicit service intensifiers Desired promises '——r Service < Transitory service Zone of Implicit service intensifiers Tolerance promises • Adequate Situational Service Social informatioi factors sources Source: Rasper, H., Helsdingen, P. V. & Gabbott, M. (2006). Services marketing management -A strategic perspective (f' ed.). England: John Wiley & Sons. The second part of the disconfirmation approach is making an assessment of what is actually received or experienced. The problem with performance from the customer's point of view is that it all depends upon the individual's perception. Individuals react differently to different things according to their needs, their personality and their perception of events. 54 A customer derived quality assessment will depend upon a comparison of expectations relative to performance. When expectations are exceeded (E < P), the outcome is beyond satisfaction and closer to customer delight. Perceived service quality is high. When expectations are not met (E > P), perceived service quality is low and the organization would expect to have a dissatisfied customer. When expectations are met (E = P), the customer will assess the quality of service based on the level of expectation. Expectation contains both adequate and desired components. Adequate expectations, if confirmed through experience, don't mean satisfaction, just confirmation. By contrast, desired expectations, if disappointed, means dissatisfaction. Hence the poor service expected and poor service delivered does not necessarily mean satisfaction. Disconfirmation has had a huge impact upon service quality and has been subject to a series of refinements. j^\s\\^ Azad / ,7,7 ""-.^ -,., \ Ate. No '- 'i - 3.4.2 SQM2. Nordic Service Quality Model ^ ^^ - -^ .^-^ ^/ Gronroos (1978) identified that services are not one big amorphous event but comprise of different components - technical quality and functional quality - which interact to determine overall quality. Technical quality refers to a dimension, which describes what the customer gets as the outcome of their interaction with the organization. For instance, a hotel service provides a room and a bed, an airline provides transportation to a destination. Quality of service varies according to the outcome received. Functional quality refers to a dimension, which describes the process by which the technical quality is delivered to the customer. This includes the demeanour of the service provider, the environment in which it is delivered and the behaviour of other customers. An acceptable technical quality is a pre-requisite for a successful functional quality. On the other hand, temporary problems with the technical quality may be excused if the functional quality is good enough (Gronroos, 1982). According to Kang (2006), 55 a two component model yields better fit than a model concentrating on functional quality alone. Exhibit 3.2: Gronroos Quality Model Expected Perceived service Perceived service quality service Service Image Technical Customer solutions contacts Appearance Know-how Technical Behaviour Functional Internal Quality Machines Quality Attitudes relations Service Computer Accessibility systems orientation Source: Gronroos, C. (1984). A Service quality model and its marketing implications, European Journal of Marketing. 18(4) 36-44. 3.4.3 SQM 3. Kano's Model of Customer Satisfaction It provides a useful structure for critical analysis of the proposed features of the product. According to this model quality elements can be classified into three categories, namely Must-be, One-dimensional ,and Attractive needs, depending on their ability to create customer satisfaction or dissatisfaction. The Must-Be or Basic Requirements (Needs): For these needs, customers will be extremely dissatisfied if these requirements are not fulfilled. However, customer satisfaction does not rise above natural even with a high performance. Fulfilling the must-be needs will only lead to "not dissatisfied". In other words, customer takes these requirements for granted and regards them as prerequisites. For example, in an organisation when average punctuality exceeds a certain level there is no increase in customer satisfaction. But if punctuality does not meet customers' expectation it causes a high level of dissatisfaction. The One-Dimensional Requirements (Needs): For these needs, customer satisfaction is proportional to the level of fulfillment- the higher the level of 56 fulfillment, the higher the customer's satisfaction. In other words, customer satisfaction is a linear function of the performance of the product/service attribute. For example, larger sale discounts normally result in higher customer satisfaction, which also explains why low fares provided by low cost carriers are so popular. The Attractive or Excitement Requirements (Needs): These needs are not explicitly expressed or expected by customers. Fulfilling these requirements leads to more than proportional satisfaction. Yet there is not a corresponding decrease in customer satisfaction if theses needs are not met. For example, Kingfisher Airlines offer pick-up and drop facility to business travels who otherwise have to make alternate travel arrangements. Yet the absence of this service will not necessarily resuh in customer dissatisfaction or loss of passengers. The most important contribution of Kano model is that it allowed us to see how it may not be enough to merely satisfy customers by meeting their basic and one- dimensional needs. In a highly competitive marketplace, organizations need to adopt strategies and to create product attributes targeted specifically at existing customers and over-satisfying them (Tan and Pawitra, 2001). The other implication of Kano model discussed by Shen, Tan & Xie, (2000) is the importance of timely and continual development, and introduction of products with iimovative and novel attributes. Kano's model posited that attributes that had once been attractive, over time, become one-dimensional. With fiirther time, they are taken for granted and fall into the category of meeting only the basic needs. According to Matzler & Hinterhuber (1998), the other potential benefit of Kano's model is that it provides valuable guidance in the trade-off situation. If two product attributes cannot be promoted simultaneously due to technical or financial reasons, the attribute that has greater influence on customer satisfaction can be determined. Positioning of service elements, which distinguishes the different types of service elements, can be used as one tool in designing the most effective customer strategy (Huiskonen and Pirttila, 1998). Yueh - Ling, Chao-Che & Pei-Chi (2007) has applied Kano's model to Taiwanese airline industry in order to better understand airline service quality and strategy 57 planning, Kano's model is used to analyze what drives passengers' satisfaction and dissatisfaction in the airline industry. Exhibit 3.3: The Kano Model Customer Delight Satisfaction Excitement needs. Or OeHpters Immediate *'performance" iiee _^_^_ Degree of Poor Good "^ implementalion Not unhappy "Basic" needs, or "hygieno" factors Disappointed Source: Yueh-Ling, Chao-Che & Pei-Chi (2007). Capturing passengers' voices: The application of Kano's model in the airline industry, 2007 International Conference on Logistics, Shipping and Port Management Retrieved September 5, 2007 from www.knu.edu.tw/knul/web/teach/tan/2007ILSC/index.files/files/2B-4.pdf 3.4.4 SQIVI4. The Gaps IVIodel of Service Quality When providers fairly address the people, outputs and processes in service transactions, expectations are more likely to be met. Disappointment and disconfirmation resulting from gaps in performance expectations can lead to non- attritive defection and lost profits (Severt, 2002). Parasuraman et al. (1985) developed a miodel which depicts how various gaps in the service process may affect the customer's assessment of the quality of the service. The model takes into account disconfirmation and different service attributes and links them together with management activity through a gap framework. The foundation of the model (see Exhibit 3.5) is a set of four gaps which are the major contributors to the service quality gap which customers may perceive: Gap 1 (Consumer Expectation - Management Perception Gap): In formulating its service delivery policy, management does not correctly perceive or interpret consumer expectation (Libonati, 1992). 58 Gap 2 (Management Perception - Service Quality Specification Gap): Management does not correctly translate the service policy into rules and guidelines for employees. Gap 3 (Service Quality specification - service delivery Gap): Employees do not correctly translate rules and guidelines into action. Gap 4 (Service Delivery - External Communications Gap): External communications - promises made to customers - do not match the actual service delivery. These four gaps emerge from an executive perspective on a service organization's design, marketing and delivery of services. These gaps are located throughout the organization between frontline staff, customers and managers. They, in turn, contribute to another gap, i.e. gap 5, which is the discrepancy between customers' expected services and the perceived service actually delivered. This gap is a function of the other four gaps: i.e. Gap 5 = f (gaps 1, 2, 3, 4). It is this gap that Parasuraman et al. (1985) sought to measure using the SERVQUAL instrument. It consists of 22 items divided along the 5 dimensions, with a seven-point scale accompanying each statement to test the strength of relations. These 22 items are used to represent five dimensions viz. reliability, responsiveness, tangibles, assurance and empathy (RATER). The instrument empirically relies on the difference in scores between expectations and perceived performance. Mathematically, the same may be expressed as: SQi = Y.^ij-Eij) where, SQi == Perceived service quality of individual 'i' k=Number of service attributes / items P=Service quality perception of individual 'i' for service attribute 'j' E=Service quality expectation of individual 'i' for service attribute 'j' 59 Exhibit 3.4: Conceptual Model of Service Quality Word of Personal Needs Past Mouth Experience ' Expected » Service Gap 5 f Perceived Service Consumer i i Marketer Service External Delivery Communication Gap 4 to Consumers i Gap 3 Gapl Translation of Perceptions into Service \Gap2 ' Management • Perceptions of Consumer Expectations 1 Source: Zeithaml, V. A., Berry, L. L, Parasuratnan, A. (1988). Communication and control processes in the delivery of service quality. Journal of Marketing, 52(2), 35-48. 3.4.5 SQM 5. Performance only Model of Service Quality A variant of SERVQUAL scale, SERVPERF scale contains perceived performance component only. A higher perceived performance implies higher service quality. Cronin et al. (1992) investigated the conceptualization and measurement of service quality and its relationship with consumer satisfaction and purchase intentions. They compared computed difference scores with perception to conclude that perceptions 60 only are better predictor of service quality. In an equation form, it can be expressed as follows: where, SQj = Perceived service quality of individual 'i' k=Number of service attributes / items P=Service quality perception of individual 'i' for service attribute 'j' 3.4.6 SQM 6. Six-Sigma Model of Service Quality Six Sigma is a sophisticated quality program created by Motorola in the 1980's and popularized by the success of General Electric. The initiative is a highly involved measurement device of production defects per one million operations. While it was originally intended to serve as a manufacturing process, several top companies have transitioned its role to focus on virtually all service-related transactions. It is an organizational change model driven by customer demand. Often referred to as "transactional Six Sigma," the methodology is proving to be a useful tool in environments that focus more on people and less on product. Using Six Sigma's defme-measure-analyze-improve-control method, a service company can implement quality: Define. Because Six Sigma is aimed at reducing defects, the first step is to figure out what a defect would be. For example, the company may decide that leaving streaks on the windows is a defect because it is a source of customer dissatisfaction. Measure. The next step is to collect data to find out why, how, and how often this defect occurs. This might include a process flow map of where employees start and finish the job. Other metrics may include recording what products and tools the employees use to carry out the job. 61 Analyze. After the data is measured, the company's Six Sigma team reaHzes that a particular employee is better at a particular job than the other employees. Improve. The team implements that employee's process as a standard way of carrying out the job. Control. The company teaches new employees the correct technique to wash the windows. Over time, there's significant improvement in customer satisfaction and increased business. It may have taken the Six Sigma team one or two brainstorming sessions to clearly define its process, but the DMIAC model remains the same for service industry as it is for manufacturing industry. 3.4.7 SQM7. Internal Service Quality Model Customer service quality evaluations are based almost entirely upon the behaviour of front-line employees (Farrell, Souchon & Durden, 2001) The model, based on GAP model (Parasuraman et al, 1985) evaluates the dimensions and their relationships that determine service quality among internal customers (front-line staff) and internal suppliers (support staff) within a large service organization (Frost and Kumar, 2000). Internal gap 1 shows the difference in support staffs perception of iront-line staffs expectation. Internal gap 2 is the significant difference between service quality specifications and the service actually delivered resulting in an internal service performance gap. Internal gap 3 focuses on front-line staff and measures the difference between front-line staffs expectations and perceptions of support staffs service quality. 62 Exhibit 3.5 internal Service Quality Model Expected Service Internal Gap 3 Perceived Service Front line Staff ti Support Staff Service Delivery iniernai Gapl ik Internal Gap 2 Support Staff Translation of Perceptions of Perceptions into Front-line Service Quality Expectations Specifications Source: Frost, F.A. & Kumar, M. (2000). Intservqual - An internal adaptation of the gap model in a large service organisation. Journal Of Services Marketing, 14(5), 358-377. 3.4.8 SQM 8. Customer Equity Framework The model provides an information-based, customer-driven, competitor-cognizant, and financially accountable strategic approach to maximizing the firm's long-term profitability. Customer equity projections are built fi"om a new model of Customer Life-Time Value (CLV)—which permits the modeling of competitive effects and brand switching patterns. Customer equity is the total of the discounted customer lifetime values summed over all the firm's current and potential customers (Blattberg & Deighton, 1996; Rust, Zeithaml & Lemon, 2004; Rust et al. 2004; Rust, Lemon & Zeithaml, 2006). The ultimate goal of the customer equity model is to link marketing actions to the firm's financial return, making marketing a financially accountable investment. Customers' lifetime values to the firm mediate the relationship between strategic actions and Return on Investment (ROI). The chain of effects behind this approach (Exhibit 3.3) is the following: 1. Marketing investments produce improvements in drivers of customer equity (value equity, brand equity and relationship equity). 63 Exhibit 3.6: Customer Equity Framework Marketing Investment Driver Improvernent(s) Improved Customer Perceptions Increased Increased Customer Customer Attraction Retention Cost of Marketing Investment Increased CLV Increased Customer Return on Marketing Source: Rust, R.T., Lemon. KM & Zeithaml, V.A. (2004). Return on Marketing: Using customer equity to focus marketing strategy, Journal of Marketing, 68,109-127. 2. Improvements in these drivers lead to improvement in customers' perceptions and enhance customer attraction and retention, 3. Attraction of new customers and retention of current customers increase customer equity, and 4. Increased customer equity, relative to cost of marketing actions, results in favorable returns on investment. The review of these eight service quality models highlighted various issues, debates, strengths and weaknesses pertaining to the model. General service quality models .t1 have been developed based on different types of service encounters. The models have been refined based on nev/ situations or new models have evolved out of weaknesses / learning from the existing models. None of the models currently satisfies the set framework (Seth et al, 2005), thus highlighting the need for further research. 3.5 Dimensions of Service Quality After a thorough examination of the research in the areas of service quality and customer satisfaction, it would be appropriate to examine the variables that impact the measurement of service quality. The literature review points to SERVQUAL developed by Parasuraman et al. (1988) as the primary measuring device that can be modified to predict customer perceptions against expectations and the comparison of those perceptions and expectations against the service provider perceptions of what it will require to satisfy the customers' service needs. Based upon SERVQUAL as a measurement device, the Chapter looks at the dimensions in measuring service quality, the SERVQUAL model, the use of the SERVQUAL model to evaluate service quality, and the validity of SERVQUAL in the measurement of service quality. Service quality dimensions are those attributes which contribute to consumer expectations and perceptions of service quality. These are the attributes of the service that are important to the customer and contribute significantly to their quality assessment. Knowledge of these dimensions and, possibly, the ability to measure them can help to yield an insight into more effective ways of improving service quality. In the initial research relating to SERVQUAL, Parasuraman et al. (1985) established ten dimensions for measuring service quality. Those original dimensions were tangibles, reliability, responsiveness, competence, courtesy, credibility, security, access, communication, and understanding the customer. This ten-dimension breakthrough approach to measuring service quality was criticized by Cronin et al. (1992) who not only disagreed with the measurement issue, but also criticized the conceptualization of SERVQUAL. They opined that the perceptions aspect of 65 SERVQUAL was a much better measurement device than SERVQUAL itself. Parasuraman, et al. (1991) revised their SERVQUAL instrument by conducting a new study, which in its refined form changed some scale measurement elements and changed wording relating to those scales. They provided a direct measurement relating to the importance of each dimension reported by the respondents. After substantial research and an evaluation of various critical reviews of SERVQUAL, the modified dimensions as defined in Table 3.2 are tangibles, reliability, responsiveness, assurance, and empathy (Parasuraman et al, 1988 and 1994a; Sachdev & Verma, 2004; Shahin, 2005). Table 3.2 Definition of Modified SERVQUAL Dimensions Dimension Deflnition Tangibles Appearance of physical facilities, equipment, personnel, and communication materials. Reliability Ability to perform the promised service dependably and accurately. Responsiveness Willingness to help customers and provide prompt service. Assurance Knowledge and courtesy of employees and their ability to convey trust and confidence. Empathy Caring, individualized attention the firm provides its customers. Source: Zeithaml, V. A., Berry, L. L, Parasuraman, A. (1988). Communication and control processes in the delivery of service quality. Journal of Marketing, 52(2), 35-48. The instrument has been further developed and promoted through a series of publicafions (Parasuraman et al, 1988; 1991, 1994a, 1994b; Zeithaml et al, 2003). Much of the research in this area since then has been concerned with validating or challenging the construct (Cronin et al, 1992; Babakus & Boiler, 1992; Teas, 1993; Smith, 1995; Buttle, 1996; Genestre & Herbig, 1996; Asubonteng McCleary & Swan, 1996; Nel, Pitt & Berthon, 1997; Llosa, Chandon & Orsingher, 1998; Hussey, 1999; Brady, Cronin & Brand, 2002; Myerscough, 2002; Nyeck, Morales, Ladhari & Pons, 2002; Lai, Hutchinson, Li & Bai, 2007) and suitability of SERVQUAL vs SERVPERF scale (Cronin et al, 1994; Elliot, 1994; Jain & Gupta, 2004; Johns, Avci & Karatepe, 2004). Carrillat, Jaramillo and Mulki (2007), in a meta-analytic investigation of 17 years of research across five continents, conclude that SERVQUAL and SERVPERF are equally valid predictors of overall service quality. Adapting SERVQUAL scale to measurement context improves its predictive validity (Prayag, 2007). 66 The five dimensions of service quality have dominated the Hterature in the field of service quality. There are now over 5500 research articles on this model (Kasper et al, 2006). According to EBSCO database (24 August' 08), SERVQUAL as a keyword is appearing in 114 publications. The development of SERVQUAL by Parasuraman et al. (1988) as a generalisable measure of service quality was a seminal contribution that has been adapted and widely used across industries around the world (Dabholkar et a/., 1996). Major published studies include Banking (Lassar, Manolis & Winsor, 2000; Arasli, Katircioglu & Mehtap-Smadi, 2005; Bexley, 2005; Mukherjee & Nath, 2005; Baumann, Burton, Elliott & Kehr, 2007; Aga & Safakli, 2007), Education (Arambewela «& Hall, 2006; Smith, G., Smith, A. & Clarke, 2007), Health (Lam, 1997; Desombre & Eccles, 1998; Kilboume, Duffy, J.A., Duffy, M. and Giarchi, 2004; Pakdil & Harwood, 2005; Jabnoun & Rasasi, 2005; Mostafa, 2005), Hotel (Ingram & Daskalakis, 1999; Winsted, 2000; Antony, J., Antony, F.J. & Ghosh, 2004; Juwaheer, 2004), Information System & E- Commerce (vanDyke, Kappelman & Prybutok, 1997; Cook & Thompson, 2000; Jiang, Klein & Carr, 2002; Kang & Bradley, 2002; vanRiel & Semeijn, 2003), Internal Marketing (Frost & Kumar, 2000, 2001; Straughan & Cooper, 2002), Public Services (Orwig, Pearson & Cochiran, 1997; Donnelly & Shiu, 1999; Wisniewski, 2001; Brysland & Curry, 2001; Donnelly, Kerr, Rimmer & Shiu, 2006), Retail (Carman, 1990; Finn, Lamb & Charles, 1991; Dabholkar et al, 1996; Zhao, Bai & Hui, 2002) and Tourism & Hospitality (Saleh & Ryan, 1991; Pick & Ritchie, 1991; Augustyn & Ho, 1998; Ryan & Cessford, 2003; Kouthouris & Alexandris, 2005; Home, Peter & Pikkemaat, 2005), Transportation (Crosby & LeMay, 1998; Mehta & Durvasula, 1998; Durvasula, Lysonski & Mehta, 1999; Shainesh & Mathur, 2000; Cavana, Corbett & Lo, 2007). 3.6 Service Quality in Airline Industry The airline industry is inherently unstable (Doganis, 2006) and highly competitive, where all airlines have comparable fares and matching frequent flyer programs. In such a scenario, service quality is a significant driver of passenger satisfaction, loyalty and choice of airline (Sultim and Simpson, 2000; Zins, 2001; Chang et al, 2002; Gilbert & Wong, 2003; Rust, Lemon 8c Zeithaml, 2006). 67 Continued liberalisation and 'open skies', the impact of global alliances, new low- cost, no-frills carriers, on-line ticket selling, and privatisation of state-owned airlines are some of the crucial developments that have been impacting on airline business at a time of continually falling average fares and yields (Teodorovic, Popovic, Pavkovic & Kikuchi, 2002; Morrish & Hamilton, 2002; latrou &, Alamdari, 2005). Increasing competition from low cost, low fare carriers is one of the fundamental challenges being faced by the traditional full service carriers (Chen, Gupta & Rom, 1994; Cerasani, 2002; Gillen & Morrison, 2002; Sayanak, 2003; Franke 2004; Cary, 2004; O'Connell & Williams, 2005; Harrington, Lawton & Rajwani, 2005; Pant, 2006) and it has also led to reduction in average quality of service provided to the customer (Trapani & Olson, 1982; Bhatt, 1997; Chan, 2000a; Butler, 2001; Servitopoulos, 2002; Mazzeo, 2003; Morrison, 2004; Manuela, 2007). Airline industry faces service quality failures on regular basis (Bamford & Xystouri, 2005; Waguespack, 2007) and passenger hardships have increased after September 11, 2001 terrorist attacks (Leone & Liu, 2003; Gkritza, Niemeier & Mannering, 2006). Airlines need to have valid and reliable measures for a better understanding of the variables likely to impact the perception of service quality being offered by them. They need to measure not only customer perceptions but also expectations of airline passengers. If significant variations are found in the perceptions of airline passengers' vis-a-vis service quality on the different flights, changes in the marketing mix need to be implemented to improve the perception of quality. Benchmarking is the most used performance improvement technique for airlines (Fry, Humphreys & Francis, 2005). Several papers (Gourdin & Kloppenborg, 1991; Ostrowski, O'Brien & Gordon, 1993; Young, Cunningham, & Moonkyu, 1994; Truitt & Haynes, 1994; Bejou & Palmer, 1998; Gustafsson, Ekdahl & Edvardsson, 1999; Sultan et ai, 2000; Chang et al., 2002; Tsaur, Chang & Yena, 2002; Gilbert et al, 2003; Alter, 2003; Kozak, Karatepe & Avci, 2003; Boland, Morrison & O'Neill, 2003; Natalisa & Subroto, 2003; Scheraga, 2004; Karankitikom, 2004; Heracleous, Wirtz, & Johnston, 2004; Bel, 2005; Ling, Lin & Lu, 2005; Gursoy, Chen & Kim, 2005; Knibb, 2005; Rhoades & Waguespack, 2005; Anitsal & Paige, 2006; Hunter, 2006; Pham, 2006; Pham & Simpson, 2006; Park, Robertson & Wu, 2005, 2006; Sim, Koh & Shetty, 6^ 2006; Venkatesh & Nargundkar, 2006; Chitnis, 2007; Pakdil & Aydin, 2007; Liou & Tzeng, 2007; Khan, Dutt & Bansal, 2007a & 2007c) have been written during the past few years examining the service quality of airUne industry. These papers focus primarily on measuring the performance of airlines using SERVQUAL instrument Chang, Lim, Jean, Ji & Seo (2002) carried out comparative study of relevance of SERVQUAL and SERVPERF scales to airline industry. In their opinion, SERVQUAL model is more appropriate for airline service industry than SERVPERF. Cunningham, Young & Lee (2002) compares U.S. and Korean customers in terms of their perceptions of airline service quality based on SERVPERF, as well as their perceptions of risks involved in the airline choice. Chenet, Tynan and Money (2000) proposes an alternative model, which shows that service performance gap is influenced both directly and indirectly by a number of critical factors including trust, commitment and co-operation. Air Travel Consumer Report (ATSR), published monthly by US Government of Transportation, provides statistics for on-time performance, mishandled baggage, denied boiardings, customer complaints and cancellation by US airlines (Rhoades et al, 2008). Airline Quality Rating (AQR), that takes in to account 12 customer complaint categories, is being published annually in US since 1991 (Headley and Bowen, 1997; Bowen et al., 2007). Considerable difference due to contextual factors exists in the performance levels between airlines (Williams, 2005). Gardner (2004) carried out a dimensional analysis of airline quality based on on-time arrivals, denied boardings, mishandled baggage and customer complaints, which is in conflict with the results of AQR 2004. Kim & Prideaux (2003) examines cross cultural differences in satisfaction among airline passengers from flight attendants' perspective. Westwood, Pritchard & Morgan (2000) concludes that airline industry needs to address its currently male- oriented service attitudes and facility provision if it is to more effectively cater for businesswomen. Lillis & Abemethy (2002) develops a framework for identifying the primary drivers of the costs of being customer responsive. It aims to develop an understanding of the causal drivers of the costs of responsiveness. 69 Post-deregulation, marketing practice is competitively evolving as airlines seek to be more effective, efficient and profitable (Glisson, Cunningham, Harris & Lorenzo- Aiss, 1996; Driver, 1999, 2001). Frequent Flyer Program (FFP) is an effective marketing technique in the airline industry with positive implications for the financial performance of the carriers involved and their strategic alliance partners (Sharp, B. & Sharp, A., 1997; Yang & Liu, 2003; Suzuki, 2003; Goel, 2003). A judicious blending of conventional marketing and superior customer service is the best recipe for sustained market success (Parasuraman 2000; Santala & Parvinen, 2007). Strategic alliances among airlines are common in the aviation industry and are seen as a response of airlines to changing economic and regulatory conditions (Albers, Koch & Ruff, 2005). There are five key consumer benefits of global alliances to consumers: wider network access; seamless travel; extended lounge access; transferable priority status; and enhanced FFP benefits (Goh & Uncles, 2003). These benefits are seen as highly attractive for business and executive air travellers. Researchers have employed Structural Equation Modelling (SEM) to investigate the effects of individual dimensions of airline service quality (Cezard, 1999; Pong & Yee, 2001; Kalamas, Laroche & Cezard, 2002; Saurina & Coenders, 2002; Park et al, 2005, 2006; Ling et al, 2005; Cassab & MacLachlan, 2006). Chang & Yeh (2001) suggested a multiattribute decision making model to measure and compare overall competitiveness of airlines on five dimensions and their associated objective performance measures. Danaher (1997) employed a method based on conjoint analysis to determine the relative importance of service attributes measured in airline customer satisfaction surveys. Some other recent studies carried out across the world on airline service quality are given below: United States: Deregulation of LFS airline industry has led to changes in route structures, airfares, service quality and barriers to entry (Bhat, 1995; Anderson & John, 1999; Rhoades & Waguespack, 1999; Burghouwt & Hakfoort, 2001; Schnell, 2004). There is a general consensus that levels of service quality have declined significantly since deregulation (Servitopoulos, 2002; Rhoades & Waguespack, 2008). Cerasani (2002) explored the market structure of the US airline industry and 70 the barriers to entry that a new carrier must overcome in order to enter the industry. It then examined the possible entry strategies of a new carrier with a specific emphasis on Southwest AirHnes. Lee & Luengo-Prado (2004) investigates the difference in service quaUty among two major US full service carriers. Madanoglu, Chang & Chu (2004) carried out an Economic Value Analysis (EVA) to demonstrate that during the period 1990 - 1999, airline industry failed to benefit from prospering US economy. EVA is a residual income that subtracts the cost of capital from the operating profits generated by a business (Banerjee, 2000). Sayanak (2003) has examined the performance of low cost carriers in comparison with the other major carriers in USA. It uses economic variables, airport characteristics, weather variables and logistic variables to determine the effects on on-time performance of LCCs and major carriers. It concludes that better LCC performance is due to fewer flight cancellations and higher on-time arrival rates. Europe: Travis (2001) explained the liberalisation of European air transport (United Kingdom, France, Germany, and the European Commission) based on game theory, in combination with process tracing. It found that legal framework was vital to the process of integration. European airlines face greater competition from alternative transportation, notably the high speed train due to shorter distance between major agglomerations (Giaume & Guillou, 2004; Eisenkopf, 2005). Huettinger (2006) provides the operating strategy of Air Baltic and its relation towards the extension policy of Scandinavian Airlines. Jarach (2004) analyze the new market scenario for European Airline Industry in face of macro-economic turmoil like September 11, 2001, consequent economic recession, terrorism, SARS and industry-related changes like growth of LCCs. Piga, Filippi & Bachis (2001) assess the effectiveness of European LCCs distribution strategies. These LCCs are limited to a market, blocked by fewer routes and lower traffic than their U.S. counterparts (Binggeli & Pompeo, 2002). Atalik (2007) identifies five categories of complaints - availability of free tickets and upgrades, staff behaviour, card ownership issues, priority issues and lack of alliances with other airlines - made by the Turkish frequent flyers. Tieman, Rhoades & Waguespack (2008) compares consumer perceptions of airline service quality indicators - on time flight arrivals, baggage reports and flight cancellations - 71 with data reported by Department of Transportation, in the USA and the Association of European Airlines AirUnes (AEA) in the EU. Asia: Asian airUnes have embraced initiatives of total quality management (Chia & Phau, 1999). Singapore Airlines is consistently recognized as the world's best, and also one of the most profitable airline (Strategic Direction, 2003, 2004; Wirtz & Johnston, 2003, 2004). Singapore Airlines has won 2007 & 2008 Airline of the Year title awarded by Skytrax (Miller, 2008). Ahmed, Zairi & Almarri (2006) carried out the SWOT analysis of Air China and identifies the factors that play key role in implementing TQM successfully in Air China. Alam & Karim (1998) develops models for predicting air travel demand in Bangladesh. Zaid (1995) describes the various methods in place by Malaysia Airlines to get feedback - how service quality is measured and monitored - in order to ensure that quality is maintained. Oyewole, Sankaran & Choudhury (2007) found that ICT, reservation procedures, in-flight services, company image and customer complaint handling influence customer satisfaction in Malaysian setting. Yi (2006) predicts that Asian LCCs are unlikely to pose a serious competitive threat to existing FSCs that cater mainly to long-haul routes and a different set of clientele. Africa: Vermooten (2005) deals with the specific commercial practices adopted by airlines in the deregulated South African domestic air transport market for passengers as well as the use of a combination of commercial practices in a predatory manner. 3.7 Role of IT in Service Delivery Information and Communication Technology (ICT) have revolutionised the entire business world. Airlines have been early adopters of ICT and have a long history of technological innovation (Lewis, Semeijn & Talalayevsky, 1998; Feldman, 2001; Gareiss, 2001, 2003; Kelemen, 2003; Botha, 2004; Buhalis, 2004; Ghobrial et al, 2005). Computer Reservation Systems (CRS) or Global Distribution Systems (GDS) have been among the first international inter-organisational systems (Werthner & Klein, 1999). Commercial airlines began using CRS technology in the mid-1970's. 72 Starting from an electromechanical base, the airline reservation systems evolved along with the computer and air transport industries (Copeland & McKenney, 1988). CRS technology has had a dramatic economic impact on the airline industry (Locke, 1989). Airlines have appropriated the benefits of computerized reservation systems, turning them into highly specialized assets for further travel related innovation (Duliba, Kauffman and Lucas, 2001). Airline ticket reservations can now be made and paid for either through internet or even mobile phones. Airlines are offering check-in via mobile phones; deploying IT based solutions to streamline baggage and airport management services, and in-flight e-mail services (Sheng, Nah and Siau, 2005; Baker, 2007). According to SITA (2008) survey, airlines expect mobile check-in to be used by 10% of passengers by 2009. The travel industry as a whole has been in a constant state of change from the mid- nineties through 2002. This flux has been accelerated due to the tragedy associated with September 11, 2001, economic disruption, and the ever-increasing influence of the Internet (Smith and Rupp, 2004). There appears to be a trend towards the extension and consolidation of strategic alliances, structural and operational reorganization, and the application of new technologies (Czipura & Jolly, 2007; Sadi and Henderson, 2000). Cost pressures, changing customer demands and new technology are heralding a new era in airline ticketing. Travel agents, who currently account for 80 to 85 percent of all ticket sales, have most to lose given their market dominance and reliance on ticket sales for much of their revenue. Airlines, on the other hand, have much to gain if they can lower their distribution costs (Grant, 1996). Many carriers are still learning how to correctly blend the online sale channel to find the best recipe for extracting high volumes and more profit as the rules of the distribution game change (Airline Business, 2008) Electronic ticketing offers the opportunity to realise significant savings in ticket distribution costs, revenue accounting and billing processes, and in the reduction of handling costs associated with paper tickets (STTB, 2004). Price wars represent one of the most severe forms of competitive interplay in the market place (Heil & Helsen, 2001). In recent years, there has been an increasing adoption of dynamic pricing policies in airline industry (Klein & Loebbecke, 2003). This trend is mainly due to increased availability of demand data, ease of changing 73 prices due to new technologies, and availability of decision-support tools for analyzing demand data and for dynamic pricing (Murali, 2008). Web-based pricing mechanisms aims at developing pricing strategies that reflect the competitive envirormient of the online market space, giving customers access to lower prices (Elmaghraby and Keskinocak, 2003). Travel and tourism comprise the leading application field in business-to-consumer (B2C) e-commerce, representing approximately half of the total worldwide B2C turnover (Fodor and Werthner, 2004). 0'Toole (2004) predicts that air travel could become world's first web-enabled industry as online sales, e-tickets and range of new technologies gain acceptance with increasing speed. Electronic tickets, smart cards, online prepayments, and other technological advances make advance selling possible for airline industry (Jinhong and Shugan, 2001). These technologies lower the cost of making complex transactions at a greater distance from the seller's site. As the number of internet users swells, the question arises as to how airlines can deal with the challenges of mastering the deployment of e-commerce and related business processes and technologies in their expansion effort (Verton, 2003; Hanke and Teo, 2003). The advanced Technology innovation on convergence of IT and Communication systems provide services for efficient administration, safe and secured air traffic management for better customer satisfaction (Ramalingam, 2002). The airline industry has been embracing cutting edge technologies to gain competitive edge (Jiang et al, 2003; Parker, 2003; Baker, 2007). Airline staff can gather information about ticketing, flight scheduling, and luggage using wireless devices (Malladi and Agrawal, 2002). These emerging teclinologies have been changing the relationship between airlines and customers, airlines themselves and between airlines and their suppliers (Doganis, 2006). The whole process of doing business is being metamorphosed. In India alone the online travel market is expected to grow an average of 46% a year from 2007 to 2011 (Violante, 2008). Kingfisher Airlines has deployed entire suite of Sabre Airline Solution consisting of more than twenty enterprise applications to enhance its guest processing functions (Sabre, 2007). 74 Radio Frequency Identification (RFID) in conjunction with smart card technology provides an extremely powerful mechanism for passenger processing enveloping every event from check-in to boarding. Airline baggage tracking system is one of the major commercial applications of RPID technology (Wyld, Jones and Totten, 2005). However, cost of RFID tags is still a major barrier to its implementation (DeVries, 2008). Self-services in customer relationships are becoming increasingly important—a development that has been boosted by customers' increasing and diverse use of the Internet. Self-service kiosks deliver fast and direct services to travellers' right at the point of service and enable passengers with carry-on luggage to reserve tickets, buy tickets and also check-in (Karp, 2007). With e-ticketing, various self service initiatives such as online e-booking, web check-in, kiosk check-in and SMS check-in can be implemented (Talreja, 2007). A recent lATA survey revealed that passengers not only expect but also demand more opportunities to take control of their travel experience (Amoult, 2008). Balancing of high-tech and high-touch are key challenge to self-service systems (Salomann, Kolbe and Brenner, 2006). The dramatic growth of web and self-service technologies are permitting customers and airlines to bypass the complexity and cost of old legacy systems (Mclvor et al, 2003; Shon et al, 2003; Soldt, Bobbink and Ying, 2007). The emergence of technology has led to concern about the future role of travel agents and Global Distribution Systems (Lewis et al, 1998; Soldt et al, 2007). Cost reductions and efficiency improvements are the key driver of IT projects. IT is critical to the profitability of individual airlines and the overall success of the industry. Airlines need to invest smartly in IT by outsourcing utility aspects, such as network, desktop, web hosting and datacentres and to move to flexible, usage-based charging of application service provision delivery (SITA, 2003). Some of the major IT issues being faced by airline industry worldwide are: > The percentage of revenue spent on IT by airlines on a revenue weighted basis has fallen from 3.5 percent in 2001 to around 2 percent in 2007 (Baker, 2007). > Airlines are encountering problems in quantifying the returns on IT investments (Chatfield & Yetton, 2000). 75 > There is lack of payment security, complexity of pricing model and lack of interlining capability (SITA, 2007). > Although the growth of internet based airline reservation services has been rapid, internet sales have experienced slow growth because of barriers such as perceived risk (Cunningham, Gerlach, Harper & Young, 2005). There is no doubt that IT has rapidly evolved from operational resource into a strategic resource capable of changing patterns of competition within industries. IT is inextricably linked with the business and strategy of any airline (Coby, 2007). 3.8 Low Cost No Frills Model of Customer Service The proliferation of Low Cost Carriers (LCC) is the newest trend in the airline industry. Deregulation in the airline sector resulted in increased competition between airlines which produced a number of small-scale, low cost companies, known as Low Cost Carriers. The low cost airline industry has changed the definition of airlines that air travel is a luxury and it is only for the upper segment of the population. Air travel has become increasingly accessible even to the more price- conscious travellers. The emergence of LCC s is a feature of world air transport markets. The first of the LCCs was Southwest Airlines which began operation in 1971. Since deregulation, a number of carriers have attempted to emulate its model with limited success. Development of Southwest, Ryanair, and easy Jet can be regarded as one of the main drivers of airline industry restructuring (Shumsky, 2006). In the Asia Pacific region. Virgin Blue, based in Australia, and AirAsia, based in Malaysia, are among the success stories (Findlay, 2004). The basic features are fleet commonality, high asset utilization, short turnaround times, low distribution costs, point-to-point service, and secondary airport utilization (Jagersma & van Gorp, 2004; Rhoades et al, 2005). The differences between low cost carriers and traditional airlines can be categorized into three groups: service savings, operational savings and overhead savings. Competitive advantage derived from greater aircraft productivity is of paramount importance and is achieved by a combination of innovative measures like single type of airplane - generally new generation Boeing 737s or Airbus A320s, single 76 passenger class, bare minimum passenger services, char'gftig^'assStigers for service items that are non-essential to the provision of air transport (i.e. on-board food, lounge access), yield management, offering low price to operate at higher passenger load factors, simplified routes, emphasizing point-to-point transit instead of transfers at hubs, direct sales of tickets over the Internet thus avoiding fees and commissions paid to travel agents and corporate booking systems, using websites to sell ancillary holiday products, and not offering frequent flyer programmes or interline (baggage check through) facilities for passengers transferring to or from other airlines (Sarkar &'Rajshekhar, 2004; Spiess & Waring, 2005; Patibandla, 2005; Doganis, 2006; Hunter, 2006; Gopinath, 2007). By adopting these low-cost measures LCC have been able to achieve substantial cost saving on short-haul sector over their full service airline competitors. According to Deccan Aviation's Managing Director, Mr Gopinath, cost per kilometre per seat for Deccan is only 4.3 cents whereas its competitors fly at 8-16 cents. Its revenue yield is 5.1 cents. And now, by expanding the network and adding more flights, he plans to reduce costs even further (Narayanamurthi, 2007). In fact, the low cost carriers are having profound effect on the efficiency, competition and industry structure. Some LCCs, like Southwest Airlines and Jetblue Airways have received high service ratings on factors like on-time performance, flight cancellation etc. (ATW, 2006; Bowen et al, 2007). The traditional full service airlines are facing many challenges and an uncertain future. All that is certain is that unless radical changes are made to the way they transact business, full service carriers will be unable to compete with the low-cost model (Hansson, Ringbeck & Franke, 2003; Foran, 2003; Hunter, 2006). There are allegations of FSC resorting to sharp price reduction coupled with aggressive capacity expansion in response to LCC entry (Windle & Dresner, 1995; Ito & Lee, 2004). The established airlines are forced to make the transition to applying differentiation in their pricing policy in order to compete with these newly formed companies as well as with existing competitors (Economist, 2004; Dikolli & Sedatole, 2004; Button, Costa & Cruz, 2007). Stock market's perceive that low cost business model has higher viability as compared to full service business model in the aftermath of September 11, 2001, terrorist attacks (Flouris & Walker, 2005a, 77 2005b). Value for money acts as a significant factor affecting choice of the airline (Proussaloglou & Koppelman, 1999; Hall, Abubakar & Oppenheim, 2001). Over the past few years, there has been a widespread departure from the original low-cost model introduced by Southwest Airlines (Sobie, 2007). Recent trends in the travel industry are driving an evolution of customer relationship management into customer value management (Esse, 2003). As the number of low-cost carriers has grown, these airlines have begun to compete with one another in addition to the traditional carriers. The low-cost carriers tend to follow a differentiation strategy as opposed to cost leadership on which the original low-cost model was based (Baker & Edinburgh, 2006; Pilling, 2008; Field, 2008). Although an increasing number of 'hybrid' low-cost models are achieving low operating costs, offering low fares and returning attractive operating profit margins, there is a case for recommending adherence to the original model to ensure greater profitability (Alamdari & Pagan, 2005). While it is quite clear that for air travel in India country to become as common as is the case in the US, LCCs have to thrive and consolidate, their roadmap appears fraught with a number of factors like high ATP prices, rising labor costs, rapid fleet expansion, and intense price competition among the players. The problem is also compounded by new players entering the industry even before the existing players could stabilise their operations (Gupta, 2006). Navigation charges are 60% higher and fuel sales tax 80% higher than international benchmarks (Thomas, 2005). Industry as a whole has faced losses of upto Rs. 25 billion in 2006-07 (DGCA, 2008). The only solution is enhanced yield management and quicker turnaround times. The greatest saving in operation costs for LCCs is not just by cutting frills like hot meals but by improving efficiencies. 3.9 Recent Studies on Civil Aviation in India Bhatt (1997) analysed the new aviation policy of India in the context of emerging global order in international civil aviation. The focus was on critical issues related to air transport policy in India seen in the global context. Rao & Rao (1997) had examined the route network of Indian Airlines, utilisation of its physical resources. 78 its financial performance and reliability of operations. It also offers suggestions for improving its performance. Sen (1998) studied the growth of civil aviation in India over a period extending from 1910 to 1997. Someshekar & Chandra (1998) developed a technology plan to enable India become a major global player in civil aviation by 2020. The National Council for Applied Economic Research (NCAER) Report (2000) identified the factors restraining the Civil Aviation sector from fully contributing to the growth and progress of the country. According to Saraswati (2001) and Bhandari (2002) regulatory - policy framework has prevented this sector from being transformed into a mass transport system. They suggested minimal intervention of the government to unlock its potential. Naresh Chandra Committee Report, (2003) delineated the problems being faced by airline industry in India and proposed a roadmap for its rapid growth and improvement in services to the passengers. Bansal, Khan & Dutt (2008a), examines the structure of the civil aviation in India and its growth since liberalisation. It highlights developments that have radically changed the face of aviation industry, opportunities and the concomitant challenges. Baisya & Sarkar (2003,2004) and Sarkar & Baisya (2005), while identifying the key attributes that influence customer choice in airline selection, also presented a comparative analysis of the performance of domestic airlines on the attributes. Khan, Dutt & Bansal (2007a, 2007c), in a preliminary study, investigated the service quality provided by different domestic airlines. Bansal, Khan & Dutt (2006) employed the concept of customer lifetime value in measuring marketing ROI for domestic airlines in India. Khan, Dutt & Bansal (2006b) and Bansal, Khan & Dutt (2008b) have also discussed at length the deployment of IT by the airline industry in India for providing upgraded services to the passengers thereby leading to enhanced customer satisfaction and improvement in overall efficiencies. In yet another research. Khan & Dutt (2006) and Khan, Dutt & Bansal (2006a, 2007b) have traced developments in the aviation sector in India with special reference to LCCs and their role in the emerging borderless world. Dutt (2006) has studied the stress among frontline and background staff of a domestic airline, factors leading to stress, its consequences and stress management techniques. 79 Solanki (2002) studied the management of marketing in different domestic airlines. It also studies the impact of open sky policy on air transport and the problems faced by the airlines. O'Connell & Williams (2006) reviews impact of regulatory reforms in supply of domestic air services. The International Air Transport Association (lATA) has identified five challenges for the successful development of air transport in India (1) enhancing safety, (2) urgent infrastructure improvement, (3) reasonable taxation, (4) commercial freedom and (5) Simplifying the Business through effective use of technology (Concil, 2005). 3.10 Research Gap Review of literature reveals that most of the available studies on civil aviation are confined to USA and UK. In India, the aviation sector, from research point of view is largely unexplored. Particularly, there are not many studies on domestic civil aviation in India. As discussed in the preceding section, though some studies have been conducted in recent years, including those by the researcher, the impact of liberalisation in domestic aviation sector needs to be further explored. Very few studies have been undertaken to determine the specific influence(s) of technology on airline industry structure in India. It is in this context that this study reviews the development and the role of information technology (IT) in the airline industry. It then discusses the role of IT in three areas of airline operations: Flight Support Services, In-Flight Services and Customer Support Services. This study discusses comprehensive research, including exploratory research with airline executives and passengers, using qualitative and quantitative methods to examine the use of ICTs in the domestic airline industry in India and to discuss recent developments in the industry. Several airlines have started operation with new business paradigm and it is having huge impact on the structure of domestic airline industry in India. LCCs which are a new phenomenon in India, are miaking attempts to deploy low cost solutions extensively for providing service to the passengers. But, quality expectations of passengers from these carriers had till date not been explored by any researcher. Thus, the present study is an attempt to bridge this gap. The present research also 80 attempts to study the level of acceptability of low cost business model amongst the Indian airline passengers. Even at the macro level, the customer service aspect of Indian airline industry, especially in the liberalised era has also largely remained unexplored. In fact, no attempt has been made to study the performance of FSCs from customer's perspective. Thus, it is expected that the findings of the study will help the airlines, goverrmient and regulating agencies in evaluating the level of existing services being offered by the players as also in deciding on the portfolio of services to be made mandatory in the interest of passengers. 3.11 Chapter Summary The discussion in this chapter started with a brief, historical review of the development of the literature surrounding the role of service marketing and the relationship between service quality and customer satisfaction. A detailed review of how service quality was defined and measured along with an evaluation of the dimensions going into the measurement of service quality. The SERVQUAL Model (Parasuraman, et al., 1985, 1988) has been examined both as an instrument to measure customer perceptions and expectations of service quality in a general industry setting as well as specific to airline industry. The utility of SERVQUAL in measuring service quality gaps was thoroughly reviewed. Validity issues in the area of airline services in general and SERVQUAL scale in particular too have been discussed. Role of IT in service delivery and impact of low cost model have been reviewed. Studies carried out in India and research gaps have been covered. 81 CHAPTER 4: RESEARCH METHODOLOGY 4.1 Research Objectives 4.2 Research Hypotheses 4.3 Research Design 4.4 Questionnaire Development and Administration 4.4.1 Specification of the Information Needed 4.4.2 Selection of Survey Method 4.4.3 Measurement Scales 4.4.4 Question Content and Wording 4.4.5 Response Format 4.4.6 Sequence of Questions 4.4.7 Pilot Study 4.4.8 Administration of Final Questionnaire 4.5 Assessment, Refinement and Validation of Measurement Scales 4.5.1 Exploratory and Confirmatory Factor Analyses 4.5.2 Assessment of Measurement Scales Using EFA 4.5.3 Assessment of Measurement Scales Using CFA 4.6 Data Analysis Strategy 4.7 Hypothesized Research Model 4.7.1 Hypothesized Measurement Model 4.7.2 Hypothesized Structural Model 4.8 Limitations of the Study 4.9 Chapter Summary CHAPTER 4: RESEARCH METHODOLOGY Chapter Overview This chapter highlights the research objectives of the study, hypotheses, research design, questionnaire design, sampling method, data collection and administration. In addition, this chapter delineates the conceptual underpirmings based on which analysis has been performed in the subsequent chapter of the study. Finally, the limitations of the study and assumptions relevant to this research are discussed. 4.1 Research Objectives The study attempts to develop a reliable and valid instrument for measuring service quality dimensions and to examine the customer's perceptions and expectations of service quality in domestic airline industry with special reference to LCCs. The present work also attempts to assess the utility of IT in passenger services by studying the performance of airlines from the customer's perspective. This can also help in evolving a model of service parameters that airlines could adopt in order to leverage IT to their advantage. It also attempts to evolve a model of customer service as applicable to various customer segments. The broad objectives of the study can be grouped into four categories: I: Developing an instrument for measuring service quality > Investigate the extent of applicability of the SERVQUAL instrument to the airline industry in India > Compare service expectations; perceptions and the gaps using the SERVQUAL scale > If required, to develop a reliable and valid instrument for measuring various dimensions of service quality in airline industry II: Investigating service quality in domestic airline industry > Understanding the dimension of services valued by the passengers > To assess satisfaction level of customers on various dimensions of services > Compare the quality of services being offered by various airlines 82 Ill: Investigating acceptability of Low Cost Model > To map out the preference of airline passengers for the Low Cost Model IV: Assessing role of IT in airline service delivery > To generate a profile of IT based services being offered by three categories of airlines (i.e. FSC - Public, FSC - Private and LCC) > To map out the passenger preferences for the IT based services > To study the impact of IT on various dimensions of customer service quality Scope of the Study: The study covers the following four categories of airlines: > Full Service Carriers - Public Sector, which includes Air India (Domestic) (erstwhile Indian Airlines and Alliance Air). > Full Service Carriers - Private Sector, which includes Jet Airways, Jetlite (erstwhile Air Sahara now taken over by Jet Airways) and Kingfisher Airlines. > Low Cost Carriers which include Deccan (now taken over by Kingfisher Airlines), Spicejet, Paramount, IndiGo and Go Air > International Carriers operating to / from India, which include Cathay Pacific, Emirates, Gulf Airways, Singapore Airlines, Thai Airways, Air Lanka, British Airways, Air India and Korean Airlines. 4.2 Research Hypotheses Based on extant literature and objectives of the study, hypotheses were framed and they have been placed under three groups. T]\Q first group of hypotheses (Hi to Hio) were developed to measure the overall difference in expectations and perceptions of passengers towards service quality provided by the airlines. The second group of hypotheses (Hn to Hi4) are related to the impact of IT on passenger services. The third and the last group of hypotheses (H15 to Hig) are related to the acceptability of low cost no frills model in India. One way Analysis of Variance (ANOVA) was used for testing the hypotheses. It involved statistically examining the differences in the mean value of the dependent variables associated with the effect of controlled independent variables (Malhotra 2007). Here independent variable considered was the airline category. The 83 hypotheses were tested at significance level less than 0.05. The null hypotheses considered for the study are listed below: Group I: Hypotheses related to service quality in airline industry Hoi: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis 'Tangibility - Support Services' among different categories of airlines. H02: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis 'Tangibility - Additional Support Services' among different categories of airlines. H03: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis 'Tangibility - Flight' among different categories of airlines. H04: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis Reliability among different categories of airlines. H05: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis Empathy among different categories of airlines. H06: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis Responsiveness among different categories of airlines. H07: Significant differences do not exist in the mean scores of the gap between customers' perceived and expected service quality vis-a-vis Assurance among different categories of airlines. Hog: Significant differences do not exist in the mean scores of the customers' expected service quality among different categories of airlines. H09: Significant differences do not exist in the mean scores of the customers' perceived service quality among different categories of airlines. Hio: Significant differences do not exist in the mean scores of the customers' perceived and expected service quality among different categories of airlines. 84 Group II: Hypotheses related to Information Technology and service delivery Hii: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines for improvement in satisfaction levels vis-a-vis Flight Support Services (FSS) due to use of IT. H12: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines for improvement in satisfaction levels vis-a-vis In-Flight Services (IFS) due to use of IT. H13: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding improvement in satisfaction levels vis-a-vis Customer Support Services (CSS) due to use of IT. H14: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding IT adding benefits to customer services. Group III: Hypotheses related to Low Cost No Frills Model H15: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding acceptability of reduction in Flight Support Services (FSS) if it leads to reduction in price of ticket. H16: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding acceptability of reduction in In-Flight Services (FSS) if it leads to reduction in price of Ticket. H17: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding acceptability of reduction in Customer Support Services (FSS) if it leads to reduction in price of Ticket. Hig: Significant differences do not exist in the mean scores of perceptions of passengers of different categories of airlines regarding acceptability of Low Cost Model. 85 4.3 Research Design A summary of research design used for this study is presented in Exhibit 4.1. Exhibit 4.1 Research Design of the Study Research Design 1 -L t Exploratory Conclusive Research Design Research Design 1 1' Descriptive Causal Research Research 1 f i Cross-Sectional Longitudinal Design Design _l f 1 Single Cross- Multiple Cross- Scctional Design Sectional Design Conclusive Research: Information needed is clearly defined and the research process is formal and structured. Sample is representative and data analysis is quantitative. Descriptive Research: It describes the relation between independent and dependent variable. It has a structured research design conducted normally through surveys. Cross-Sectional Design: Involves the collection of information from any given sample of population elements only once. Note: The shaded boxes suggest the design followed for the present research. Source: Adapted from Malhotra, N.K. (2007). Marketing research - An applied orientation, 5th Edition. Prentice Hall of India. 4.4 Questionnaire Development and Administration Development of research instrument involved identification of constructs, method of survey to be employed, questionnaire design, pretesting of questionnaire and administration of final questionnaire. The broad methodology adopted in developing 86 the survey instrument used in the study is illustrated in Exhibit 4.2. The same is followed by a discussion on the steps involved in the design. 4.4.1 Specification of the Information Needed Service Quality in Airline Industry The objectives of the first stage were two fold: identify the information requirements and determine the source fi^om which the information could be obtained. This stage begins with identifying the information needed to meet the research objectives. As such an exploratory study was carried out. In depth interviews were held with airline passengers, airline staff, and academics connected with the aviation industry to obtain inputs in developing the questionnaires. In addition, the service quality measures were checked against other independent sources of literature related to service quality. From these interviews, feedback was obtained on the variables to that were considered for inclusion in preliminary questioimaires. The above exercise resulted in the identification of 6 service quality dimensions and 30 measurement items suitable for the airline industry pertaining to expectation and perception rating for each driver. The questionnaires developed for the study also incorporates the 22 items of SERVQUAL model (Appendix 1 for passenger and Appendix 2 and 3 for airline staff). But Tangibility dimension was modified to reflect unique characteristics of airline service industry and was divided into two sub-dimensions: a) Tangibility - Support Services containing 5 items, and b) Tangibility - Flight containing 7 items Table 4.1 outlines the airline service quality dimensions explored in the study. 87 Exhibit 4.2: Steps in Questionnaire Design Process Specify Information and Source Selection of Survey Metliod Develop Questionnaire > Measurement Scales > Question Content & Wording > Response Format > Sequence of Questions > Physical Layout Pilot Test 1 (45 Users) Revision in Questionnaire Pilot Test 2 (66 Users) > Factor Analysis > Reliability Finalisation of Questionnaire Questionnaire Distribution and Administration > Population > Sampling Frame > Sampling Method > Sample Size > > Final Sample I Assessment, Refinement and Validation of Measurement Scales Source: Adapted from Malhotra, N.K, (2007), Marketing research - An applied orientation, 5th Edition. Prentice Hall of India; Kassim, KM. (2001). Determinants of customer satisfaction and retention in the cellular phone market of Malaysia, PhD thesis, Southern Cross University, Lisbon; Hamid, N.R.A. (2006). An Assessment of the Internet's Potential in Enhancing Consumer Relationships. Doctoral Thesis, School of Information Systems, Faculty of Business and Law, Victoria University of Technology. Retrieved April IS, 2007, from httv://wallabv.vu.edu.au/adt-WUT/uvloads/approved /adt-VVUT20060919.112900/pubHc/01frontpdf 88 o 1 (N m ^ ^ r^ r-~ Os 0 (N 00 ON in 00 0\ (N (N O o o O o O O o o 5 5 o O 5 o o O 0 0 0 0 O o O o O O o o 0 o o o o o o o O 0 0 0 0 rt (N m ON 0 00 0\ 1-H CN en •rf l/^ ^ t^ 00 O-v o ^ vB c^ c^ ri CN OH PL, PL| PL Pu (N (N O O PL! PL, PL, 5 PL, PL, PL, PL, o o o o o o o O o O 0 0 0 00 ON o 0 o r^ vB t^ oON 0 r5 00 ON w w W 2 (N (N o o o o o o o o O W w W w w pq S fa W w W W fa O o O O o O o o O 0 0 0 0 ;::! 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These touch-points can primarily be divided into Flight Support Services (Reservation and Ticketing; Check-in and Boarding; and Baggage Handling), In-Flight Services (In-FIight Services and Facilities; and Catering / Meals) and Customer Support Services (Customer Complaint Handling; Customer Relationship Management; and Frequent Flyer Programme) (Table 4.2). The quality of service provided by front-line staff members is largely dependent on the assistance of support staff working in the background. Table 4.2: Role of IT in Airline Service Delivery - Operationalization of Variables Variable Definition of Variable Construct / Parameters Parameter Reference Flight Role of IT in providing Reservation and Ticketing CIA Support services to the passenger Check-in and Boarding CIB Services before and after the flight Baggage Handling CIC (IT-FSS) In Flight Role of IT in providing In-Flight Service and CID Services services to the passenger Facilities (IT-IFS) during the flight Catering / Meals CIE Customer Role of IT in building Customer Complaint CIF Support lasting relations with Handling Services customers and handling Customer Relationship CIG (IT-CSS) customer complaints Management 1 1 Frequent Flyer Program | CIH | Source: Prepared by the Researcher Low Cost No Frills Model Low Cost No Frills model works on the principle of offering low fares as a result of planned reduction in services. The reduction in services is primarily related to Flight Support Services (Point-to-Point Service; More dependency on Internet for Ticket sale; Limited staff and cabin crew; Increase in minimum reporting time; and Increase in baggage delivery time), In-Flight Services (Single class flight; Paid in flight service and meals; and In-flight advertisements) and Customer Support Services (Increase in customer complaint handling; No frequent flyer Programme; Company website as main point of contact; and No refund policy) (Table 4.3). 91 Table 4.3: Low Cost No Frills Model - Operationalization of Variables Variable Variable Definition Construct / Parameters Parameter Reference Flight Reduction in Point to Point Service B2 Support services to customer More dependency on Internet for ticket sale. B3 Services before and after the Limited Staff & Cabin Crew B4 (LCC- flight to reduce Increase in Minimum Reporting Time B5 FSS) price of the ticket Increase in Baggage Delivery Time B8 In Flight Reduction in Single Class Flight Bl Services services during the Paid In-Flight Service and Meals B6 (LCC- flight to reduce In-Flight Advertisements B7 IFS) price of the ticket Customer Reduction in Increase in Customer Complaint Handling B9 Support customer relation Time Services services to reduce No Frequent Flyer Program BIO (LCC- price of the ticket Company Web Site as main point of contact Bll CSS) No Refiind Policy B12 Source: Prepared by the Researcher 4.4.2 Selection of Survey Method The decision to choose a survey method may be based on a number of factors which include sampling, type of population, question form, question content, response rate, costs, and duration of data collection (Aaker, Kumar & Day, 2002). Owing to the nature of the study it was decided to personally administer the structured research instrument developed for the study. The language used in the questionnaire was English and no problem was faced in administration as the target population (airline passengers) is well versed with it. Otherwise too, English is widely spoken and understood in India. The main benefits of the method adopted are listed below: > The questions can be answered by circling the proper response format and with an interviewer present respondents could seek clarity on any question (Aaker et al., 2002; Boyd, Westfall & Stasch, 2003). > The respondents are more motivated to respond as they are not obliged to admit their confusion or ignorance to the interviewer (Hayes, 1998; Boyd et al., 2003). > A higher response rate can be assured since the questiormaires are collected immediately once they are completed (Malhotra, 2007). > This method offered highest degree of control over sample selection (Malhotra, 2007). 92 However, it can be very time consuming if a wide geographic region is involved. 4.4.3 Measurement Scales As this study aims to measure consumer perceptions towards the airline service quality, multiple-item scales were deemed appropriate as it is frequently used in marketing research to measure attitudes (Parasuraman et al, 1991). The use of a multi-item scale would ensure that the overall score, which was a composite of several observed scores, was a reliable reflection of the underlying true scores (Hayes, 1998). Three types of measurement scales were used in this research: nominal, ordinal and interval. Nominal scales were used for identification purposes because they have no numeric value (Hayes, 1998) for example, respondents name, their primary airline. On the other hand, ordinal scales were used to rank Internet users' age group and income level. These scales were then assumed to be interval scales, as is commonly practiced in social science research (Perry, 1998; Hayes, 1998). Further, interval scales were used to measure the subjective characteristics of respondents. For example, in this study, respondents were asked about their expectations and perceptions in relation to service quality in airlines. This scale was used due to its strength in arranging the objects in a specified order as well as being able to measure the distance between the differences in response ratings (Malhotra, 2007). 4.4.4 Question Content and Wording The questions were designed to be short, simple and comprehensible. Care was taken to avoid ambiguous, vague, estimation based, generalization type, leading, double barreled and presumptuous questions (Boyd et al., 2003). 4.4.5 Response Format Two types of response format were chosen: dichotomous close-ended and labeled scales. In order to obtain information pertaining to respondents' demographics a dichotomous close-ended question format was used. In addition, so as to obtain respondent's perception towards airline service quality, labeled scale response format was used. Apart from the simplicity in administration, it was easy to code for 93 statistical analysis (Bums & Bush, 2002; Luck & Rubin, 1999). Labeled scale response format is appropriate in marketing research as it allows the respondents to respond to attitudinal questions in varying degrees that describes the dimensions being studied (Aaker et al., 2002; Boyd et al, 2003). The other advantages of this scale are listed below: > It yields higher reliability coefficients with fewer items than the scales developed using other methods (Hayes, 1998) > This scale is widely used in market research and has been extensively tested in both marketing and social science (Garland, 1991). > It offers a high likelihood of responses that accurately reflect respondent opinion under study (Bums et al, 2002; Wong, 1999; Zikmund, 2000). > It helps to increase the spread of variance of responses, which in tum provide stronger measures of association (Aaker et al, 2002; Wong, 1999). In relation to the number of scale points, there is no clear mle indicating an ideal number. However, many researchers acknowledge that opinions can be captured best with five to seven point scale (Aaker et al, 2002; Malhotra, 2007). Keeping the same in mind, a seven-point Likert scale was used in this research. 4.4.6 Sequence of Questions The questionnaire began with less complex and less sensitive questions and progressed to opinion-sought questions. The questionnaire consisted of seven parts. The first part, i.e. section A asked respondent to identify the primary airline. Section B had questions regarding acceptability of Low Cost No Frills Model. The questions in section C inquired respondents regarding their opinion on impact of IT on Service Delivery. Section D consisted of questions on aspects of domestic flight. Section E tried to measure the loyalty of respondent towards primary airline. Section F consisted of demographic information such as gender, age group and income level. Section G solicited respondent's expectation and perception towards service quality in airline industry. 94 4.4.7 Pilot Study The preliminary questionnaire was pre-tested. The aim was to ensure that the questions were eliciting the required responses, identify ambiguous wording or errors before the survey was carried out on a large scale (Zikmund, 2000; Bums et al, 2002; Malhotra, 2007). It should be noted that prior to pre-testing, three marketing professors were asked to review the questions and give their opinions in the quest for content validity. Some overlapping questions were detected and hence were dropped from the list. After the review process, the questionnaire was ready to be pre-tested in an exploratory survey. The exploratory survey started off in October 2005 with the selection of a small group of respondents based on convenience sample which is common for pilot tests (Zikmund, 2000; Boyd et al, 2003). In all 65 questionnaires were distributed to passengers who had flown in domestic airlines to check for clarity of the measurement items. Passengers were asked to complete the questionnaire and also give overall comments about the questionnaire. A total of 45 usable responses were obtained. Based on the feedback, the questionnaire was further revised. The next stage of pre-testing involved a pilot survey in February 2006 on 94 passengers at Delhi airport. The surveys were personally administered and by the end of week two, a total of 76 questionnaires were collected. After screening, 10 of the questiormaires were found to be unusable because of missing values, which resulted in 66 usable samples for analysis. Exploratory factor analysis using Principal Axis factoring and Promax rotation with Kaiser Normalization resulted in seven factors (Table 4.4). The data was tested for reliability and yielded a Cronbach alpha (Cronbach, 1951) score ranging from0.51 7 to 0.956 (Table 4.5). The results of the pilot study suggested that SERVQUAL, in its classical form (Five Dimensions), could not be used meaningfiilly in this study. 95 Table 4.4: Pilot Study - Factor Analys Is on Perception (P) and Gap (G) Service Quality Parameters 1 2 3 4 5 6 7 Visually Appealing Physical Facilities P G Vast Sales and Support Network G P Vast Network of Destinations G P Economical Airfare and Discount Schemes P G Web-site and Call Center usage P G Modem Aircraft with up-to-date Facilities G P Neat Well Dressed and Visually Appealing G Staff P Seat in Flight of Choice P G Hassle free Check-in and Boarding G P Efficient Baggage Handling Mechanism P G Excellent Quality In-Flight Services P G Multiple Meal Options of High Quality G P Special Need Customers G P Problems due to Critical Incidents G P Perform Service right the first time G P Meet Time Commitment G P Keep Error Free Records G P Keep Customer informed about time of P,G Service Prompt Service to Customers P G Always Willing to Help Customers G P Staff never too busy to respond to G P customer's request Staff Behavior should Instill Confidence P,G Safe Planes and Facilities During Journey G P Consistently Courteous Staff G P ICnowledge to Answer Customers' Queries G P Individual Attention to Customer P,G Staff gives Personal Attention to Customer P,G Customer's Best Interest at Heart P,G Understand Specific Needs of Customers P,G Convenient Flight Schedules P G Extraction Method Principal Axis Factoring, Rotation Method Promax with Kaiser Normalization. 96 Table 4.5: Pilot Study - Reliability of SERVQUAL Dimensions: Cronbach's ALPHA Perception Gap Cronbach Inter-Item Cronbach Inter-Item Alpha Correlation Alpha Correlation (Mean) (Mean) Overall (30 Items) 0.956 0.418 0.954 0.408 Tangibility (12 Items) 0.854 0.328 0.836 0.298 Tangibility - Support 0.592 0.225 0.597 0.229 Service (5 Items) Tangibility - Flight 0.837 0.424 0.841 0.449 (7 Items) Service (18 Items) 0.947 0.498 0.953 0.531 Reliability (5 Items) 0.828 0.491 0.849 0.529 Responsiveness 0.895 0.630 0.870 0.572 (5 Items) Assurance (4 Items) 0.833 0.556 0.869 0.624 Empathy (4 Items) 0.747 0.424 0.770 0.455 4.4.8 Administration of Final Questionnaire The sampling process included several steps: definition of the population, establishment of the sampling frame, specification of the sampling method, determination of the sample size and selection of the sample (Malhotra, 2007). Step 1: Population. The target population for this study was defined as individuals having flown at least once on domestic air carrier at the time the survey was conducted. Step 2: Sampling frame. Due to privacy and security concerns, it is practically not possible to obtain list of passengers who have flown via domestic airlines in India. Thus, the sample frame comprised real airline passengers waiting to board their flights at domestic terminals at Indira Gandhi International Airport, Delhi (IGIA); Sardar Vallabhbhai Patel International Airport at Ahmedabad; Chatrapati Shivaji International Airport at Mumbai and Bangalore Airport. Step 3: Sampling method. The required data was obtained using intercept technique from real airline passengers waiting to board their flights at aforesaid domestic terminals. It should be noted that the airports covered are the busiest in 97 their respective sectors and thus expected to provide an unbiased representative sample. The data was collected from March 2006 to Feb 2007. Thus, broadly, the sampling process adopted for this research involved selection of a sufficient number of elements from the population, and based on this subset, attempt has been made to infer regarding the characteristics of the entire population (Hayes, 1998; Zikmund, 2000; Boyd et al, 2003; Levin & Rubin 2006). Step 4: Sample size. Next step involved determining the sample size of this study. The required sample size depends on factors such as the proposed data analysis techniques, financial support and access to sampling frame (Malhotra, 2007). The data analysis technique employed in this research is Structural Equation Modeling (SEM), which is very sensitive to sample size and less stable when estimations are made based on small samples (Tabachnick & Fidell, 2001; Garson 2007). As a general rule of thumb, data from at least 300 cases is deemed comfortable, 500 considered as very good and 1000 as excellent (Comrey & Lee, 1992; Tabachnick et al, 2001; Garson 2007). Thus it was decided to target a total of around 500 respondents from the four major metros of the country. Step 5: Final Sample. In all, 1153 passengers were randomly approached during the months of March 2006 - Feb 2007. Of these, 528 agreed to participate in the study. During editing phase of the questionnaires, it was observed that 57 responses were incomplete in various respects and thus had to be discarded. This resulted in a total of 471 responses. It included 171 FSC - Public, 169 FSC - Private, 80 LCC and 51 International carrier passengers. Of these, New Delhi accounted for around 40%, Mumbai 30%, Bangalore 20% and Ahmedabad 10%. Most of the respondents were Indian. It may be noted that the feedback received is still relevant as the airline scenario has not changed significantly since then. Convenience sampling approach was used to collect the data from airline staff. They were approached individually during their rest periods. Of the 218 questionnaires distributed, 78 were returned. A total of 15 questionnaires were rejected as they were incomplete in various respects. This resulted in 63 usable responses. As per Airport Authority of India, domestic passengers handled during 2006-07 at Delhi, Ahmedabad, Mumbai and Bangalore airport were 13.79, 2.09, 14.90 and 6.86 million, respectively. 98 4.5 Assessment, Refinement and Validation of Measurement Scales Prior to carrying out further analysis, the multi-item scales developed for the study have to be evaluated for their reliability, unidimensionality, and validity (Anderson and Gerbing, 1988; Sureshchandar, Rajendran and Anantharaman, 2002; SSI, 2007a). Before actual evaluation of the scale, it would be proper to understand these concepts from the point of view of present research. Reliability of a scale refers to how consistent or stable the ratings generated by the scale are likely to be (Parasuraman et al, 1991; Malhotra, 2007; Warner, 2008). Internal consistency reliability was used to assess the reliability of the scales. The most commonly used approach to this method is the use of Cronbach alpha (Cronbach, 1951; Warner, 2008). The analysis yields a correlation coefficient that indicates the level of internal consistency. Cronbach's alpha is the average of all possible split-half coefficients resulting from different ways of splitting the scale items (Park et al, 2006; Malhotra, 2007). Cronbach alpha tends to be high if the scale items are highly correlated (Hair, Anderson, Tatham and Black, 1998, Hau, 2005). However, another test that must be undertaken before the reliability test is the test for unidimensionality of a measurement scale. Unidimensionality is defined as the existence of one construct underlying a set of items (Garver and Mentzer, 1999). It is the degree to which a set of items represent one and only one underlying latent construct. The test for unidimensional scales is important before undertaking reliability tests because reliability such as Cronbach alpha does not ensure unidimensionality but instead assumes it exists (Hair et a/., 1998, Hau, 2005). More importantly, achieving unidimensional measurement is a crucial undertaking in theory testing and development. Unidimensionality is necessary for construct validity (Rubio, Weger & Tebb, 2001). It is therefore, necessary to ensure that each set of indicators designed to measure a single construct achieves unidimensionality. Validity of a measurement scale is the extent to which the scale fully captures all aspects of the construct to be measured (Parasuraman et al, 1991; Hayes 1998; Garson 2002). In a general sense, a measurement scale is considered to be valid if it measures what it is intended to measure. Among several types of validation procedures suggested in the literature, three types are considered as being 99 appropriate to the current research. They are content validity, convergent validity, and discriminant validity. Content validity (also known as face validity) is defined as the extent to which the content of a measurement scale appears to tap all relevant facets of the construct it is attempting to measure (Parasuraman et al., 1991; Ding & Hershberger, 2002; Malhotra, 2007; Warner, 2008). It refers to the degree that the construct is represented by items that cover the domain of meaning for the construct (Garver et al., 1999; Malhotra, 2007). Content validity is essentially a subjective agreement among concerned professionals (Parasuraman et al., 1991). Content validity of the scales used in the current research is established by their origins from the extant literature. The new items that are used for the first time have been developed through a careful review of the extant literature on the practical manifestations of the respective construct. Extensive discussions were held with airline executives, passengers and academicians who reviewed the questionnaire and confirmed that it (with minor change in words of few items) had face validity. After evaluation of the questions, they judged that all of these were appropriate for measuring passengers' attitudes about service quality of domestic airlines in India. Convergent validity is a form of construct validity which refers to the degree to which multiple attempts to measure the same concept are in agreement (Garson 2002, 2007; Warner, 2008). It deals with the question "do the items intended to measure a single latent construct statistically converge together" (Garver et al., 1999). Operationally, convergent validity is assessed by the extent to which the latent construct correlates to items designed to measure that same latent construct. Discriminant validity is assessed by the extent to which the items representing a latent construct discriminate that construct fi-omothe r items representing other latent constructs (Garver et al, 1999; Warner, 2008). Discriminant validity is also a form of construct validity but it represents the extent to which measures of different concepts are distinct (Garson, 2007; Malhotra, 2007). Convergent validity and discriminant validity together form the construct validity. 100 4.5.1 Exploratory and Confirmatory Factor Analyses To assess and refine the measurement scales in terms of unidimensionality, reliability and validity, there are two main approaches that are commonly used in the literature (Sureshchandar et al, 2002). They are Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). In EFA, no a priori restrictions are placed on the pattern of relationships between the observed measures and the latent variables, while in CFA, the researcher must specify in advance several key aspects of the factor model such as the number of factors and patterns of indicator-factor loadings (UUman, 2006; Hsu, 2007). EFA is more appropriate for scale development and CFA for scale validation (Hau, 2005). Hurley, Scandura, Schriesheim, Brannick, Seers, Vanderberg & Williams (1997) has presented guidelines for choice between EFA and CFA for conducting the analysis, and for interpreting the results. The current research employed a combination of both EFA and CFA in a two-phase approach. The first phase involved employing EFA for scale assessment and refinement (Table 4.6). The second phase involved employing CFA for scale validation (Fabrigar, Wegener, MacCallum & Strahan, 1999). The reason for applying both EFA and CFA in this research is that it involves the development of new scales to measure several constructs under investigation. Table 4.6: Summary of EFA and CFA for Scale Assessment and Validation Phase Step Factor analysis Type of test 1 EFA for individual scale Unidimensionality, Preliminary Reliability (Cronbach alpha) Assessment 2 EFA for all scales together Convergent validity. Discriminant validity 3 CFA for individual scale Unidimensionality, Convergent validity, Composite reliability Conflrmation 4 CFA for selected pairs of Discriminant validity scales 5 CFA for all scales together Overall measurement model Source: Adapted from Hau, L.N. (2005). Acquiring marketing knowledge througit international joint ventures, Doctoral Thesis, University of Western Sydney. Retrieved April 15,2008, from library.uws.edu.au/adt-NUWS/uploads/approved/adt-NUWS20061010.143634/public/01Front.pdf 4.5.2 Assessment of Measurement Scales Using EFA In the present research, the EFA was performed using SPSS 15.0. The current research employed common factor analysis (principal axis factoring) with eigenvalue > 1 as a criterion for detemining the number of extracted factors. These 101 criteria were selected because the main objective of this step was to identify the latent dimensions represented in the original variables for each construct in the model. Moreover, the oblique rotation (e.g. PROMAX) was chosen because it reflected more accurately the underlying structure of data than that provided by an orthogonal solution such as VARIMAX (Hair et al, 1998; Rubio et al., 2001; Hau, 2005). The analyses were undertaken in two hierarchical steps: 1) First Step: EFA with principal axis factoring, eigenvalue > 1 and PROMAX rotation was applied to each of the constructs under investigation (Conway and Huffcutt, 2003). The main purpose of this step is to see whether the scale for each construct under investigation is unidimensional (i.e. first-orderconstruct ) or multidimensional (i.e. second-order construct). For a scale to be empirically unidimensional, the factor analysis must result in only one factor extracted. This is necessary because all latent constructs in the theoretical framework are operationaiized as unidimensional constructs. Moreover, items with low factor loadings (< 0.50) were eliminated because they do not converge properly with the latent construct they were designed to measure (Hair et al., 1998; Hau, 2005). Then, reliability analysis (Cronbach Alpha) was applied to each set of indicators (i.e. each scale) to assess and refine the measurement items. Items having low item-to-total correlation coefficients (<0.50) were eliminated. Moreover, as a standard for this preliminary assessment, the scale for each construct must achieve a minimum alpha of 0.70 (Hair et al., 1998; Hau, 2005; Garson, 2007). A more precise evaluation of the reliability (i.e. composite reliability) will be estimated later in the application of CFA to measurement scales (Hair ef fl/., 1998). 2) Second Step: Joint EFA with the same setting (i.e. principal axis factoring, eigenvalue > 1 and PROMAX rotation) was performed on all items of all constructs put together to have a preliminary assessment of unidimensionality, and convergent and discriminant validity (Kline, 1998). Given the result of step 1 where each item loaded highly on the factor representing its underlying construct, this joint EFA allowed all items to correlate with every factor without being constrained to correlate only with its underlying factor (Kline, 1998, p.56). Consequently, it allows the investigation of the general correlation pattern of the measurement items (Fabrigar et al., 1999). 102 Based on this general pattern, various assessments can be made. Firstly, if no item loads highly on more than one factor, it is indicative of unidimensionality, i.e. one item measures only one construct (Anderson et al., 1988). Secondly, all items comprising a scale must load highly on one factor representing the underlying construct. High loadings of all items indicate convergent validity, while loading on only one factor indicates unidimensional construct (i.e. first order construct). Thirdly, no factor consists of two sets of items loading highly on it to indicate discriminant validity (Hair et al, 1998; Hau, 2005). 4.5.3 Assessment of Measurement Scales Using CFA Traditional approaches such as Cronbach alpha and EFA are useful for the assessment and refinement of measurement scales. However, they only serve as preliminary tools (Hair et al., 1998). For a confirmative approach, it is necessary to employ Confirmatory factor analysis (CFA) (Hau, 2005). In CFA, the unidimensionality of a scale is judged by the overall fit of the model including the latent construct and its designate items (Hau, 2005). Reliability evaluated in CFA is the composite reliability. Composite reliability is a better indicator than Cronbach alpha because it is free from the assumption of equal item reliabilities (Anderson et al., 1988; Hair et al., 1998). Composite reliability of a scale can be calculated using the following (Hair et al, 1998) expression: 2 Composite Reliability = (^Standardized Loading) 2 [ (XStandardized Loading) + X^j ] The standardized loadings are obtained directly from the program output; and 8J is the measurement error for each indicator. The measurement error is 1.0 minus the square of the indicator's standardized loading. Convergent validity of a measure is the degree to which multiple attempts to measure the same construct are in agreement (Hair et al, 1998). A benchmark value of substantial coefficient of the parameter estimate indicating convergent validity is 0.70 (Hair e/a/., 1998). 103 Convergent validity is achieved if: 1) the model receives a satisfactory level of fit, and 2) the regression coefficients (factor loadings) of all indicators are statistically significant, i.e. greater than twice its standard error (Anderson et al., 1988; Hau, 2005). Across-construct validity is applicable in the current research because all the investigated constructs are unidimensional. In CFA, items from one scale should not load or converge too closely with items from a different scale (Hau, 2005). Across- construct discriminant validity is achieved when the model receives a satisfactory level of fit; and the 95% confidence interval of the correlation does not include unity (Anderson et al, 1988; Hau, 2005). The test of measurement scales using CFA consists of three hierarchical steps as described previously in Table 5.7. This hierarchical procedure is helpful in identifying and eliminating unacceptable items. Otherwise, these items may cause cross-factor loading, or general scattering of discrepancies that may lead to a low overall measurement model fit (Hau, 2005). The steps are listed below: 1) First Step: Each of the 6 scales was subjected to CFA to evaluate unidimensionality, composite reliability, and convergent validity. 2) Second Step: Discriminant validity was evaluated among selected pairs of constructs. These pairs of constructs were tested separately before testing the whole measurement model because they are theoretically related to each other. It is necessary to confirm that the two constructs within each category are distinct to each other. Totally, 6 pairs of constructs were tested for the discriminant validity in this step. 3) Third Step: Full measurement model, including the 6 constructs, all put together was subjected to CFA. The purpose of this test is to evaluate the across-construct discriminant validity and the overall measurement model. In testing this model, partial disaggregation (or item parceling) was employed. The results of each step are presented in next chapter. 104 4.6 Data Analysis Strategy The final step was to select the appropriate statistical tools for analyzing the data. It involved steps such as coding the responses, cleaning, screening the data and selecting the appropriate data analysis strategy (Hau, 2005; Malhotra, 2007). For systematic approach, research elements, namely the research problem, objectives, characteristics of data and the underlying properties of the statistical techniques need to be understood (Malhotra, 2007). To meet the objectives of the study, the following types of analysis were performed: Descriptive analysis refers to the transformation of raw data into a form that would provide information to describe a set of factors in a situation that will make them easy to understand and interpret (Hau, 2005). This analysis gives a meaning to data through frequency distribution, mean, and standard deviation, which are useful to identify differences among groups. Inferential analysis refers to the cause-effect relationships between variables. Inferential statistics used for this research were Correlations, Structural Equation Modeling (SEM) and Analysis of Variance (ANOVA). Correlation analysis was used to test the existence of relationships between variables being studied. To do so, Pearson correlation coefficient was applied. While in order to test research hypotheses, Analysis of Variance (ANOVA) procedure was applied. ANOVA has its strength over other multivariate analysis because it maximizes the differences among group membership of variables as a whole and helps to understand groups' dimensions differences (Hair et al, 1998). The data were analysed using MS-Excel 2000 spreadsheet program; SPSS 15.0 Statistical Analysis Software; and LISREL 8.5 Structural Equation Modelling software. Appropriate statistical tools like Exploratory Factor Analysis (EFA), Kaiser-Meyer-Olkin (KMO) and Bartlett's test of sphericity. Confirmatory factor Analysis (CFA), Cronbach's reliability test, cross tabulation, Levene test of Homogeneity of Variance and one-way ANOVA have been applied on the collected data. Chi-square test was carried out to measure goodness of fit and relationship between respondents of different airline categories and their perception of airline service (Boyd et al, 2003). 105 4.7 Hypothesized Research Model The hypothesized research model for the present study is based on the expectation disconfirmation theory and the SERVQUAL instrument. This model consists of two parts (Lee, 2007): 1) The Measurement model: Defines the constructs or latent variables that the model will use and assigns observed or measurable variables to each and takes the measurement errors into account. 2) The Structural model: Defines the causal relationship between the constructs (latent variables). The model regresses the endogenous (dependent) latent variables with the linear terms of some endogenous and exogenous (independent) latent variables. 4.7.1 Hypothesized IVIeasurement Model The measurement model consists of five (indicators) to measure expectation disconfirmation and overall perceived performance. The most widely used customer perceived service quality model is SERVQUAL model. Thus, the five formative latent constructs (Tangibility, Reliability, Responsiveness, Assurance and Empathy) are based on the five dimensions of the SERVQUAL instrument. Tangibility construct has been modified into Tangibility - Support Services (5 items) and Tangibility - Flight (7 items) to reflect the unique characteristics of airline industry. The measurement model is shown in Exhibit 4.3. 106 Exhibit 4.3: Hypothesized Measurement Model Visually Appealing Physical Facilities Vast Sales and Support Network Vast Network of Destinations Economical Airfare and Discount Schemes Web-site and Call Center usage Modern Aircraft with up-to-date Facilities Neat Well Dressed and Visually Appealing Staff Seat in Flight of Choice Hassle free Check-in and Boarding Efficient Baggage Handling Mechanism Excellent Quality In-Flight Services Multiple Meal Options of High Quality Special Need Customers Problems due to Critical Incidents Meet Time Commitment Keep Error Free Records Perform Service right the first time Prompt Service to Customers Always Willing to Help Customers Staff Behavior should Instill Confidence * Keep Customer informed about time of Service Staff never too busy to respond to customer's request Safe Planes and Facilities During Journey Consistently Courteous Staff Knowledge to Answer Customers' Queries Individual Attention to Customer Staff gives Personal Attention to Customer Customer's Best Interest at Heart Understand Specific Needs of Customers Convenient Flight Schedules 107 4.7.2 Hypothesized Structural Model Structural Equation Modeling (SEM) is widely used in theoretical research in various disciplines (Joreskog & Sorbom, 1982; Garver et al., 1999; Bentler & Yuan, 1999). SEM can be defined as a class of methodologies that seek to represent hypotheses about the means, variances and covariances of observed data in terms of a smaller number of "structural" pairameters defined by a hypothesized underlying model (Kaplan 2000; Glaser, 2002). It is one of the most popular and well-known advanced approaches used in marketing research (Steenkamp and Baumgamer, 2000). It provides researchers with required flexibility. According to (Chin, 1998) it facilitates researchers in: 1. Modeling relationships among multiple predictor and criterion variables 2. Identify unobservable latent constructs 3. Isolate errors in measurements for observed variables, and 4. Statistically test a priori substanitive/ theoretical and measurement assumptions against empirical data. Basically there are six essential steps in building and validating SEM (Hair et al, 1998): The six-step process is illustrated in Exhibit 4.4. 1. Specify theoretically based model and develop a path diagram, 2. Determine linear models - Structural and Measurement model, 3. Select an input matrix and estimate proposed model, 4. Assess the identification of Structural model, 5. Evaluate goodness-of-fit of model, and 6. Interpret and modify the model, if so required 108 Exhibit 4.4: Six-steps Process of Structural Equation Modelling Determine the / Specify lineiir model / select an input / theoretical -W Develop a path h • Sfiuctm-iil and -•/ matrix model l diagi-nm ; measurement / • Estimation modek (Ti m Evaluate fitness |4- Model of model | ideatificaiiou (•5) (4) Source: Adapted from Hair, J.F., Anderson, R.E., Taiham,R.L. and Black, W.C. (1998). Multivariate Data Analysis, 5th edition. New Delhi; Pearson Education; Hamid, N.R.A. (2006). An Assessment of the Internet's Potential in Enhancing Consumer Relationships. Doctoral Thesis, School of Information Systems, Faculty of Business and Law, Victoria University of Technology. Retrieved April 15,2007, from http://wallaby.vu.edu.au/adt-WUT/uploads/approved/adt- VVUT20060919.112900/public/01fronLpdf The structural model, consisting of eight constructs, is shovm in Exhibit 4.5. SEM was applied to measure the relationships between the independent variables and dependent variables simultaneously. Since this study required the models to be tested for the best-fit, SEM seemed to be the appropriate analysis method as it produces more comprehensive overall goodness-of-fit than those found in other traditional methods (Hau, 2005). LISREL version 8.5 was used for SEM as it provides a graphical user interface, which is easy to understand (Hayduk, 1987; Joreskog & Sorbom, 1997; SSI, 2007b). LISREL also enables data to be imported directly from SPSS. The instrument was subsequently modified using modification indices provided by LISREL. 109 Exhibit 4.5: Hypothesized Structural Model Source: Prepared by the Researcher 4.8 Limitations of the Study Although efforts were made to carry on a research that was theoretically and empirically sound, the study suffers from several limitations: > A general lack of reliable independent statistics on the passenger traffic on routes in India results in a lack of transparency regarding the conduct of airlines and the affect of marketing practices, code-shared flights, interlining and alliances of participants in the market. As a result there are gaps in the research and analysis of developments in the domestic air transport market. 110 > It was observed that there was an apparent reluctance by airHnes in general to participate in academic research. One possible reason behind this reluctance appeared to be competition and an apparent 'fear' that such research may 'expose' weaknesses of the organization in general and management in particular. The impact of this limitation was felt more strongly during the survey, resulting in a much lower than expected response rate from airline staff > There was lack of extensive prior research in this field, particularly in the context of Indian airline industry. This limitation affected the research as there did not appear to be a strong foundation upon which this research could be built. > The study is restricted to specific metros in India. The required data were mainly obtained from airline passengers at domestic terminals at Indira Gandhi International Airport, Delhi (IGIA); Sardar Vallabhbhai Patel International Airport at Ahmedabad; Chatrapati Shivaji International Airport at Mumbai and Bangalore Airport. However, the airports covered were the busiest in their respective sectors and thus expected to provide an unbiased representative sample yet the data might have a slight up-market bias. > The study assumed that the respondents were all individual airline customers whose individual perceptions and expectations relating to service quality controlled the decision regarding primary airline, not taking into account possible impact of company policy or family influence. > Regardless of the attention and effort, the identified variables may have been influenced by the interests and the knowledge limitations of the customers and thus may not be considered to be exhaustive. Additionally collecting respondents' data on expectations and perceptions of service quality at the same time could have compromised the reliability of the data. > The present study has focused on the use of IT by domestic airlines and its effect on customer retention. Although companies have adopted an IT strategy, its implementation may not have been uniform across the airlines covered. Ill > While this research posits a positive relationship between use of IT and passenger satisfaction, there is a need for continuous updation as IT features may have changed since the point of time this study was conducted. > The respondents were asked to fill out a paper-based survey and they were expected to recollect their past experiences vis-a-vis services offered at domestic airline's websites. The quality of responses could be improved if a Web-based survey was administered concurrently to assess respondents' reactions to a particular site's features while they interacted with the site. > Finally, while the sample provided a substantial number of customers in those airlines that facilitated a study of this nature, one cannot generalize the results in other airlines not included within the study. Although this study had a number of constraints, the research was successfully conducted. This success may be attributed to the development and application of a robust and flexible research design supported by valid and reliable research instruments that enabled the researcher to minimize the effects of the aforementioned limitations. 4.9 Chapter Summary This chapter illustrates the research design, steps involved in questionnaire design and administration. It also provides an overview of data analysis. The study's methodology, hypotheses, data collection, the pilot study and pilot sample, the assessment of the validity and reliability of the SERVQUAL instrument, sample size determination, the sampling plan, and techniques for data analysis are also described. In all, 471 responses were obtained from airline passengers for this study. Data analysis teclmiques used in evaluating the hypotheses included Pearson correlation, factor analysis, Cronbachs' ALPHA for reliability analysis, Chi Square Statistics and Analysis of Variance (ANOVA). 112 CHAPTER 5: ANALYSIS AND FINDINGS 5.1 Preliminary Examination of Data 5.1.1 Descriptive Analysis 5.2 Demographic Profile of the Sample 5.3 Instrument Validity and Reliability 5.3.1 Phase 1 - Preliminary Assessment (Using EFA) 5.3.2 Phase 2 - Confirmatory Assessment (Using CFA) 5.4 Hypothesized Airline Service Model 5.4.1 Original Model 5.4.2 Assessment of Model Fit and Model Modification 5.4.3 Modified Airline Service Model 5.4.4 Model Analysis 5.5 Measures of Service Quality in Airline Industry 5.5.1 Tangibility - Support Services 5.5.2 Tangibility - Additional Support Services 5.5.3 Tangibility - Flight 5.5.4 Reliability 5.5.5 Empathy 5.5.6 Responsiveness 5.5.7 Assurance 5.5.8 Reasons for Gap Between Expectation and Perception 5.5.9 Results of Hypotheses Testing 5.6 Role of Information Technology in Service Delivery 5.6.1 Assessment of Measurement Scales Using CFA 5.6.2 Measuring Impact of IT on Passenger Services 5.6.3 Adoption of Internet Technologies 5.6.4 Results of Hypotheses Testing 5.7 Low Cost No Frills Model 5.7.1 Assessment of Measurement Scales Using CFA 5.7.2 Acceptability of Low Cost No Frills Model 5.7.3 Results of Hypotheses Testing 5.8 Chapter Summary CHAPTER 5: ANALYSIS AND FINDINGS Chapter Overview In this chapter, analysis and findings are presented. Firstly, a preHminary screening of the data as well as descriptive and correlation analysis are described in section 1. Section 2 presents the profile of respondents. In section 3, evaluation of the multi- item scales for their reliability, unidimensionality, and validity using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) has been carried out. The airline service model derived through Structural Equation Modeling (SEM) technique is described in section 4. While section 5 discusses the analysis vis-a-vis dimensions of service quality in the context of airline industry. It also covers the testing of hypotheses 1 to 10. Section 6 is related to the role of Information Technology in service delivery and hypotheses 11 to 14 have been tested here. Section 7 discusses acceptability of Low Cost No Frills Model in India and tests hypotheses 15 to 18. Section 8 presents summary of this chapter. 5.1 Preliminary Examination of Data This section presents the screening and cleaning of raw data before it was subjected to analysis. Two broad categories of problems are discussed: case-related issues such as the accuracy of the data input, missing observations; and distribution issues such as nomiality (Hair et al, 1998). The database was maintained using SPSS 15. As already discussed, a total of 528 respondents completed the survey. Screening of the data sets was conducted through an examination of basic descriptive statistics and frequency distributions using relevant features in SPSS software. Values that were found to be out of range or improperly coded were detected with straightforward checks (Hau, 2005). A frequency test was run for every variable to detect any illegal and missing responses. Three cases with illegal responses (respondents had interpreted Likert scale opposite) were noted and corrected. However, 57 questionnaires were found to be unusable because of missing responses. Hence, they were discarded resulting in 471 usable responses. 113 5.1.1 Descriptive Analysis Subsequent to data cleaning and screening, descriptive analysis of the data was carried out. Descriptive statistics including minimum, maximum, means, range, standard deviation and variance were obtained for the interval-scaled variables. The first basic assumption about SEM is that all data have a multivariate normal distribution (Hau, 2005). Skewness and Kurtosis were obtained to assess normality. According to Malhotra (2007), skewness refers to the symmetry of a distribution, that is, a variable whose mean is not in the centre of the distribution is regarded as skewed variable. On the other hand, kurtosis relates to the peakedness of a distribution. A distribution is said to be normal when the values of skewness and kurtosis are equal to zero (Malhotra, 2007). Absolute values of univariate skewness indices greater than 3.0 seem to describe extremely skewed data sets and absolute values of the kurtosis index greater than 10.0 may suggest a problem and values greater than 20.0 may indicate a more serious one (Hau, 2005). In this study, all variables were tested for normality using LISREL. Of the 471 observed variables, none had skewness greater than 3.0 and none had kurtosis index greater than 6.0. These figures indicated that the data was distributed normally. Service Quality in Airline Industry The means for Perception ranged from 4.12 to 5.28 i.e. Neither Agree, Nor Disagree to Moderately Agree, whereas means for GAP ranged from -1.80 to -0.53. This implies that perception of the respondents is less than their expectations. However, the scores were tightly packed around the mean (standard deviation 1.25-1.71 for Perception and 1.49 - 2.07 for GAP), indicating that most respondents share similar opinions towards perception and gap. In relation to range, unlike the variance value, a large range for each variable was observed in case of GAP. Respondents had strong opinion regarding meal, network, sales and support staff and service to the customer. In case of Perception and GAP, the data was slightly skewed towards negative (-1.07 to -0.30 for perception and -0.88 to 0.31 for GAP) and the kurtosis ranges from -0.81 to 0.83 for perception and 0.02 to 1.34 for GAP. The details of descriptive statistics are given in Table 5.1 and 5.2 for Perception and GAP respectively. 114 Table 5.1: Descriptive Statistics - Service Quality in Airline Industry - Perception Variables Range Min Max Mean SD. Var Skew Kurt Visually Appealing Physical 6 1 7 5.00 1.31 1.73 -0.62 0.25 Facilities Vast Sales and Support Netiwrk 6 7 5.18 1.25 1.57 -0.82 0.83 Vast Network of Destinations 6 7 5.18 1.41 1.98 -0.73 -0.11 EcQBomical Airfare and Discount 6 i 4.93 1.42 2.03 -0.58 -0.19 Schemes Web-site and Call Center usage 6 7 5.07 1.44 2.08 -0.80 0.24 Modem Aircraft mfh up-to-date 6 1 4.90 lAd 2.12 -0.67 -0.01 Facilities Neat Well Dressed and Visually 6 7 5.27 1.37 1.89 -0.92 0.63 Appealing Staff Seat in Flight of Choice 6 7 4.76 1.52 2.31 -0.65 -0.08 Hassle free Check-in and Boarding 6 7 5.01 1.46 2.14 -0.84 0.19 Efficient Baggage Handling 6 7 4.92 1.51 2.27 -0.83 0.17 Mechanism Excelienf QuaUtj* In-Flight Senices 6 7 4,79 1.44 2.08 -0.56 -0.11 Multiple Meal Options of High 6 7 4.12 1.71 2.91 -0.30 -0.81 QuaUtj- Special Need Customers 6 7 4.93 1.49 2.23 -0.80 0.30 Problems due to Critical Incidents 6 7 4.71 1.48 2.19 -0.59 -0.09 Staff gives Personal Attention to 6 7 4.70 1.44 2.09 -0.63 -0.05 Customer Meet Time Commitment 6 7 4.65 1.45 2.11 -0.58 -0.03 Keep Error Free Records 6 7 5.11 1.40 1.96 -0.75 0.34 Customer's Best Interest at Heart 6 7 4.79 1.38 1.89 -0.67 0.22 Prompt Senice to Customers 6 7 4.88 1.44 2.07 -0.83 0.30 Always Willing to Help Customers 6 7 4.90 1.45 2.12 -0.79 0.22 Understand Specific Needs of 6 7 4.71 1.42 2.02 -0.66 0.21 Customers Staff Behaviour should Instill 6 7 4.84 1.46 2.12 -0.74 0.20 Confidence Safe Planes and Facilities Duiing 6 7 5.28 1.45 2.10 -1.07 0.86 JoHiiie>' Consistently Courteous Staff 6 T/ 5.08 1.43 2.05 -0.94 0.49 Knowledge to Answer Customers' 6 7 4.95 1.43 2.06 -0.92 0.68 Queries ludiridaal Attention to Customer 6 7 4.63 1.41 2.00 -0.61 0.01 Perfoim Senice right the fu'st time 6 7 4.81 1.40 1.95 -0.79 0.29 Keep Customer informed about time 6 7 4.87 1.40 1.96 -0.75 0.31 of Ser%'ice Staff never too busy to respond to 6 / 4.79 1.50 2.24 -0.72 -0.03 customer's request Convenient Flight Schedules 6 7 4.98 1.41 1.98 -0.79 0.28 115 Table 5.2: Descriptive Statistics - Service Quality in Airline Industry - GAP Variables Range Min Max Mean SD. Var Skew Kurt Visually Appealing Physical 10 -6 4 -0.95 1.59 2.52 -0.10 0.49 Facilities Vast Sales and Support Network 11 -6 5 -0.53 1.65 2.72 0.31 1.34 Vast Network of Destinations 11 -6 5 -1.04 1.63 2.66 -0.16 0.70 Economical Airfare and Discount 9 -6 3 -1.52 1.56 2.45 -0.44 0.10 Schemes Web-site and Call Center usage 9 -6 3 -1.32 1.53 2.33 -0.63 0.76 Modern Aircraft with up-to-date 9 -6 3 -1.51 1.64 2.68 -0.38 0.26 Facilities Neat Well Dressed and Visually 9 -6 3 -1.07 1.54 2.38 -0.54 0.74 Appealing Staff Seat in Flight of Choice 9 -6 3 -1.20 1.66 2.77 -0.73 0.61 Hassle free Check-in and Boarding 9 -6 3 -1.43 1.60 2.56 -0.55 0.32 Efficient Baggage Handling 9 -6 3 -1.55 1.67 2.78 -0.73 0.49 Mechanism Excellent Quality' In-Flight Ser\ices 9 -6 3 -1.35 1.62 2.61 -0.53 0.32 Multiple Meal Options of High 12 -6 6 -1.37 2.07 4.31 -0.07 0.02 Quality Special Need Customers 8 -6 2 -1.57 1.61 2.58 -0.70 0.46 Problems due to Critical Incidents 9 -6 3 -1.80 1.63 2.65 -0.50 0.23 Staff gives Personal Attention to 10 -6 4 -1.33 1.58 2.51 -0.64 0.70 Customer Meet Time Commitment 8 -6 2 -1.70 1.65 2.72 -0.38 0.10 Keep Error Free Records 9 -6 3 -1.31 1.49 2.23 -0.68 0.83 Customer's Best Interest at Heart 9 -6 3 -1.47 1.56 2.43 -0.61 0.53 Prompt Senice to Customers 9 -6 3 -1.52 1.57 2.47 -0.68 0.53 Always Willing to Help Customers 8 -6 2 -1.51 1.57 2.48 -0.76 0.52 Understand Specific Needs of 9 -6 3 -1.44 1.53 2.34 -0.78 0.67 Customers Staff Behaviour should Instill 10 -6 4 -1.43 1.60 2.55 -0.64 0.90 Confidence Safe Planes and Facilities During 9 -6 3 -1.25 1.53 2.34 -0.85 1.30 Journey Consistently Courteous Staff 9 -6 3 -1.25 1.60 2.56 -0.72 0.72 Knowledge to Answer Customers' 8 -6 2 -1.34 1.55 2.39 -0.88 0.74 Queries Individual Attention to Customer 9 -6 3 -1.12 1.60 2.57 -0.80 0.65 Perform Service right the first time 9 -6 3 -1.25 1.53 2.35 -0.73 1.04 Keep Customer informed about time 10 -6 4 -1.28 1.58 2.50 -0.61 1.04 of Service Staff never too busy to respond to 9 -6 3 -1.48 1.64 2.68 -0.65 0.45 customer's request 1 Convenient Flight Schedules 10 -6 4 -1.31 1.56 2.43 -0.55 0.85 Information Technology and Service Delivery The means for variables ranged from 1.72 to 2.67 i.e. respondents agree to the fact that IT has led to the improvement in customer satisfaction level. The scores were tightly packed around the mean with standard deviation ranging from 0.72 to 1.12. In case of response to impact of IT in the area of Reservation and Ticketing, high skewness (-2.37) and kurtosis (5.07) was observed. The details of descriptive statistics are given in Table 5.3. 116 Table 5.3: Descriptive Statistics - IT and Service Delivery Variables Range Min Max Mean SD. Var Skew Kurt Reservation and Tickeing 3 0 3 2.67 0.72 0.51 -2.37 5.07 Check-in and Boarding 3 0 3 2.49 0.87 0.76 -1.69 1.87 Baggage Handling 3 0 3 1.92 1.09 1.18 -0.53 -1.07 In-Flight Service and Facilities 3 0 3 1.89 1.07 1.15 -0.47 -1.09 Catering / Meals 3 0 3 1.72 1.09 1.19 -0.27 -1.24 Customer Complaint Handling 3 0 3 2.01 1.12 1.26 -0.74 -0.89 Customer Relationship Management 3 0 3 2.11 1.08 1.16 -0.92 -0.52 Frequent Flyer Program 3 0 3 2.17 1.08 1.17 -0.97 -0.49 Low Cost No Frills Model The means for variables ranged from 1.30 to 2.56. In other words the respondents were not averse to reduction in service if it was accompanied with reduction in price. However, they were averse to 'No Refunds' and increase in service time. The scores were tightly packed around the mean with standard deviation ranging from 0.59 to 0.83. High skewness (1.86) and kurtosis (2.25) was observed in case of 'No Refund policy. The details of descriptive statistics are given in Table 5.4. Table 5.4: Descriptive Statistics -Low Cost No Frills Model Variables Range Min Max Mean SD. Var Skew Kurt Single Class Flight 2 3 2.56 0.68 0.47 -1.28 0.27 Point to Point Sen ice 2 3 2.55 0.69 0.47 -1.21 0.10 Limited Channels of Ticket Sale 2 3 2.50 0.70 0.49 -1.05 -0.24 Limited Staff & Cabin Crew- 2 3 2.22 0.79 0.63 -0.41 -1,29 Increase in Reporting Time 2 3 1.91 0.79 0.63 0.16 -1.39 Paid In-Flight Service & Meals 2 3 2.11 0.82 0.67 -0.21 -1.47 In-Flight Advertisements 2 3 2.09 0.83 0.69 -0.16 -1.54 Increase in Baggage Delivery Time 2 3 1.56 0.76 0.58 0.93 -0.66 Increase in Customer Complaint 2 3 1.57 0.79 0.62 0.93 -0.77 Handling Time No Frequent Fiver Program 2 3 1.93 0.83 0.69 0.14 -1.54 Company Web Site as main Point of 2 3 2.34 0.73 0.54 -0.62 -0.92 Contact No Refund Policy 2 1 3 1.30 0.59 0.35 1.86 2.25 5.2 Demographic Profile of the Sample Frequency distributions containing data about gender, education, age, occupation, income and flying experience were calculated for all the respondents (Table 5.5). The respondents were predominantly male (85.6%). Professionals and Post Graduates were equally represented in the survey (39 percent). Majority of passengers were between 21 to 40 year of age (68.4 percent), while the passengers 117 Table 5.5: Demographic Profile - Passenger Primary Airline Row Total FSC- FSC- LCC INTL (Percent) Public PRIVATE Carriers Gender Male 148 143 70 42 403 (85.6) Female 23 26 10 9 68 (14.4) Highest Graduation or 32 35 27 10 104 (22.1) Qualification Below Post Graduation 67 70 25 22 184 (39.1) Professional 72 64 28 19 183 (38.8) Age Group Less than 21 1 2 5 1 9(1.9) 21 to 40 101 125 61 35 322 (68.4) 41 to 60 66 40 14 14 134(28.4) Above 60 3 2 0 1 6(1.3) Occupation Self Employed 16 15 13 2 46 (9.8) Employed (Private 60 105 53 31 249 (52.8) Sector) Employed (Govt/ 76 33 7 10 126 (26.8) Public Sector Student 13 10 7 5 35 (7.4) Others 6 6 0 3 15 (3.2) Annual Income Less than 0.5 104 75 51 12 242 (51.4) Bracliet Million 0.5-1.0 Million 48 64 22 10 144 (30.5) 1.0-2.0 Million 14 17 5 11 47 (10.0) Above 2.0 Million 5 13 2 18 38 (8.1) Since how long Less than 1 Year 6 6 7 4 23 (4.9) Flying 1-5 Years 62 84 49 9 204 (43.3) 5-10 Years 32 32 11 15 90 (19.1) More than 10 Years 71 47 13 23 154 (32.7) Domestic 1-5 102 92 51 33 278 (59.0) Flights in last 1 6-10 38 34 22 9 103 (21.9) Year 10-20 17 26 5 5 53(11.2) Above 20 14 17 2 4 37 (7.9) Frequent Flyer No 115 109 62 32 318 (67.5) Member Yes 56 60 18 19 153 (32.5) Travel to No 73 73 54 0 200 (42.5) International 98 96 26 51 271 (57.5) Sector Yes Total 171 169 80 51 471 (Percent) (36.3) (35.9) (17.0) (10.8) (100) between the age 41 to 60 year of age were 28.5%. Passengers between 21-40 years preferred private airlines, whereas preference of passengers between 41-60 was more for FSC - Public. More than half of the respondents (53%) were employed in private sector and 27% in public sector. Majority of private sector passengers flew 118 regularly with private carriers, whereas public sector employees preferred FSC - Public. The highest percentage of passenger included in the survey (51.4 %) were having annual income less than INR 0.5 Million, while 30.6 % had annual income between INR 0.5 - 1 Million. Majority of international carrier passengers were having income above INR 2.0 Million. More than 95% of the respondents had flown for more than 1 year. Most of the respondents (59%) had flown upto 5 times during the last one year. Interestingly, 67 percent of the passengers did not express loyalty toward any particular airline. It should be kept in mind that LCCs do not offer loyalty programmes. About 57% of the respondents had flown on international sector. Majority of the airline staff who responded were male (69.8%), having age less than 30 (54%) with qualification upto graduation (54%) and experience of about five years (60.3%) (Please see Table 5.6). Interestingly, senior officials of national carrier Indian Airlines to the rank of General Manager, Director and Deputy Managing Director agreed to provide feedback on passenger service in their airline. This is perhaps indicative of importance being attached to service quality and growing realization that it needs to be monitored with due care. 5.3 Instrument Validity and Reliability 5.3.1 Phase 1 - Preliminary Assessment (Using EFA) Stepl EFA results showed that out of six constructs, five (Tangibility - Flight, Reliability, Responsiveness, Assurance, and Empathy ) were immediately acceptable while one (Tangibility - Support Service) needed some refinements (Table 5.7 for Perception and Table 5.8 for GAP) Using the latent root or eigenvalue greater than 1 criterion, the results show that only one factor was extracted in case of each. The variance explained by the extracted factor ranged from 52.20% to 70.91% for Perception and 47.82% to 65.47% for GAP, while the factor loadings were all in acceptable range. Thus, it would be safe to say that the five constructs viz. Tangibility - Flight, Reliability, Responsiveness, Assurance, and Empathy were unidimensional. 119 Table 5.6: Demograph c Profile -- Airline Staff Primary Airline Row Total FSC- FSC- LCC INTL (Percent) Public PRIVATE Carriers Gender Male 16 15 11 2 44 (69.8) Female 4 7 4 4 19 (30.2) Highest Graduation or 6 11 12 5 34 (54.0) Qualification Below Post Graduation 3 6 3 0 12 (19.0) Professional 11 5 0 1 17 (27.0) Age Group Less than 30 2 15 13 4 34 (54.0) 31 to 40 8 4 1 1 14 (22.2) 41 to 50 4 3 1 1 9(14.3) Above 50 6 0 0 0 6(9.5) Duration in Less Than 1 Year 0 7 4 2 13 (20.6) Present Airline 1 to 5 Years 2 9 11 3 25 (39.7) 5 to 10 Years 1 6 0 0 7(11.1) More than 10 17 0 0 1 18 (28.6) Years Functional Area Passenger Services 7 9 14 2 32 (50.8) In Flight Services 5 10 0 0 15 (23.8) General 8 3 1 4 16 (25.4) Management Level in Junior 4 15 10 5 34 (54.0) Organisation Management Middle 13 7 5 1 26 (41.2) Management Top Management 3 0 0 0 3(4.8) Staff Reporting Less than 5 8 10 7 4 29 (46.0) to You 5 to 10 5 8 3 2 18 (28.6) 11 to 50 4 1 2 0 7(11.1) More than 50 3 3 3 0 9 (14.3) Total 20 22 15 6 63 (Percent) (31.7) (34.9) (23.8) (9.5) (100) After establishing unidimensionality, the reliabiUty of the composite score was assessed. As shown in Table 5.7 and 5.8, the Cronbach alpha in case of the five constructs were above the threshold of 0.70 (range is from 0.83 to 0.92 for Perception and 0.81 to 0.90 for GAP). The item-total correlation values, which ranged from 0.47 to 0.83 for Perception and 0.48 to 0.80 for GAP, were also in acceptable range. All items leading to these constructs were therefore retained. The Tangibility - Support Service scale needed some refinement. The EFA with principal axis factoring, eigenvalue > 1 and PROMAX rotation did not result in one factor for Perception and GAP. Subsequently, EFA was carried out for one factor. 120 yielding a factor with variance 34.01% for Perception and 31.31% for GAP. The Cronbach alpha for Perception was 0.71 and 0.87 for GAP. However, the factor loading coefficients and item-total correlations of five items in the scale were below the acceptable thresholds. Table 5.7: EFA and Reliability Test Results - Original nstrument - Perception Construct / Items Factor Variance Eigen Item-total Cronbach loading Extracted value correlation Alpha Tangibility - Support Service 34.013 1.701 0.713 Visually Appealing Physical Facilities 0.586 0.465 Vast Sales and Support Network 0.714 0.542 Vast Network of Destinations 0.598 0.454 Economical Airfare and Discount Schemes 0.447 0.402 Web-site and Call Center usage 0.538 0.484 Tangibility - Flight 52.198 3.654 0.882 Modern Aircraft with up-to-date Facilities 0.660 0.617 Neat Well Dressed and Visually Appealing 0.685 0.637 Staff Seat in Flight of Choice 0.648 0.602 Hassle free Check-in and Boarding 0.775 0.718 Efficient Baggage Handling Mechanism 0.810 0.747 Excellent Quality In-Flight Services 0.820 0.764 Multiple Meal Options of High Quality 0.634 0.588 Reliability 59.852 2.993 0.881 Special Need Customers 0.719 0.670 Problems due to Critical Incidents 0.813 0.749 Meet Time Commitment 0.832 0.763 Keep Error Free Records 0.738 0.685 Perform Service right the first time 0.761 0.706 Responsiveness 70.908 3.545 0.924 Prompt Service to Customers 0.858 0.817 Always Willing to Help Customers 0.879 0.834 Staff Behaviour should Instill Confidence 0.848 0.807 Keep Customer informed about time of 0.801 0.766 Service Staff never too busy to respond to 0.821 0.784 customer's request Assurance 67.460 2.698 0.889 Safe Planes and Facilities During Journey 0.712 0.671 Consistently Courteous Staff 0.913 0.834 Knowledge to Answer Customers' Queries 0.838 0.774 Individual Attention to Customer 0.810 0.752 Empathy 57.738 2.310 0.831 Staff gives Personal Attention to Customer 0.817 0.719 Customer's Best Interest at Heart 0.813 0.723 Understand Specific Needs of Customers 0.850 0.739 Convenient Flight Schedules 0.508 0.473 121 Table 5.8: EFA and Reliability Test Results - Original Instrument -1SA P Construct / Items Factor Variance Eigen Item-total Cronbach loading Extracted value lorrelation Alpha Tangibility - Support Service 31.311 1.566 0.866 Visually Appealing Physical Facilities 0.507 0.474 Vast Sales and Support Network 0.710 0.478 Vast Network of Destinations 0.586 0.383 Economical Airfare and Discount 0.472 0.447 Schemes Web-site and Call Center usage 0.488 0.491 Tangibility - Flight 47.819 3.347 0.862 Modern Aircraft with up-to-date 0.657 0.610 Facilities Neat Well Dressed and Visually 0.616 0.566 Appealing Staff Seat in Flight of Choice 0.611 0.558 Hassle free Check-in and Boarding 0.747 0.681 Efficient Baggage Handling Mechanism 0.794 0.716 Excellent Quality In-Flight Services 0.784 0.722 Multiple Meal Options of High Quality 0.601 0.552 Reliability 56.772 2.839 0.866 Special Need Customers 0.704 0.650 Problems due to Critical Incidents 0.816 0.743 Meet Time Commitment 0.808 0.734 Keep Error Free Records 0.737 0.678 Perform Service right the first time 0.693 0.640 Responsiveness 65.466 3.273 0.904 Prompt Service to Customers 0.818 0.768 Always Willing to Help Customers 0.853 0.797 Staff Behaviour should Instill Confidence 0.796 0.747 Keep Customer informed about time of 0.769 0.727 Service Staff never too busy to respond to 0.807 0.760 customer's request Assurance 62.727 2.509 0.867 Safe Planes and Facilities During Journey 0.673 0.626 Consistently Courteous Staff 0.866 0.783 Knowledge to Answer Customers' 0.817 0.742 Queries Individual Attention to Customer 0.799 0.728 Empathy 53.019 2.121 0.808 Staff gives Personal Attention to 0.758 0.658 Customer Customer's Best Interest at Heart 0.814 0.699 Understand Specific Needs of Customers 0.781 0.674 1 Convenient Flight Schedules 1 0.523 0.475 Scale purification was carried out vis-a-vis Tangibility - Support Service till factor analysis resulted in a scale that gave unidimensional construct. In all, 3 items were retained for Perception and GAP. Economical airfare / discount schemes and usage of website / call center were dropped from the scale. The revised instrument with 122 scales giving unidimensional constructs is given in Table 5.9 for Perception and Table 5.10 for GAP. Table 5.9: EFA and Reliability Test Results - Modified Instrument - Perception Construct / Items Factor Variance Eigen Item-total Cronbach loading Extracted value correlation Alpha Tangibility - Support Service 49.626 1.489 0.708 Visually Appealing Physical Facilities 0.497 0.427 Vast Sales and Support Network 0.927 0.644 Vast Network of Destinations 0.618 0.510 Tangibility - Flight 52.198 3.654 0.882 Modern Aircraft with up-to-date Facilities 0.660 0.617 Neat Well Dressed and Visually Appealing 0.685 0.637 Staff Seat in Flight of Choice 0.648 0.602 Hassle free Check-in and Boarding 0.775 0.718 Efficient Baggage Handling Mechanism 0.810 0.747 Excellent Quality In-Flight Services 0.820 0.764 Multiple Meal Options of High Quality 0.634 0.588 Reliability 59.852 2.993 0.881 Special Need Customers 0.719 0.670 Problems due to Critical Incidents 0.813 0.749 Meet Time Commitment 0.832 0.763 Keep Error Free Records 0.738 0.685 Perform Service right the first time 0.761 0.706 Responsiveness 70.908 3.545 0.924 Prompt Service to Customers 0.858 0.817 Always Willing to Help Customers 0.879 0.834 Staff Behaviour should Instill Confidence 0.848 0.807 Keep Customer informed about time of 0.801 0.766 Service Staff never too busy to respond to 0.821 0.784 customer's request Assurance 67.460 2.698 0.889 Safe Planes and Facilities During Journey 0.712 0.671 Consistently Courteous Staff 0.913 0.834 Knowledge to Answer Customers' Queries 0.838 0.774 Individual Attention to Customer 0.810 0.752 Empathy 57,738 2.310 0.831 Staff gives Personal Attention to Customer 0.817 0.719 Customer's Best Interest at Heart 0.813 0.723 Understand Specific Needs of Customers 0.850 0.739 Convenient Flight Schedules 0.508 0.473 EFA results showed that only one factor was extracted in case of Perception and GAP. The variance explained by the extracted factor improved to 49.63% for Perception and 43.92% for GAP, while the factor loadings were all in acceptable range and modified scale was now considered unidimensional. Cronbach alpha ranged from 0.71 for Perception and 0.67 for GAP. The item-total 123 correlation values, which ranged from 0.43 to 0.64 for Perception and 0.40 to 0.58 for GAP, were also in acceptable range. The scale was therefore reliable and all items leading to these constructs were retained. Table 5.10: EFA and Reliability Test Results - Modified Instrument -GAP Construct / Items Factor Variance Eigen Item-total Cronbach loading Extracted value correlation Alpha Tangibility - Support Service 43.952 1.319 0.668 Visually Appealing Physical Facilities 0.475 0.398 Vast Sales and Support Network 0.856 0.576 Vast Network of Destinations 0.600 0.478 Tangibility - Flight 47.819 3.347 0.862 Modern Aircraft with up-to-date 0.657 0.610 Facilities Neat Well Dressed and Visually 0.616 0.566 Appealing Staff Seat in Flight of Choice 0.611 0.558 Hassle free Check-in and Boarding 0.747 0.681 Efficient Baggage Handling Mechanism 0.794 0.716 Excellent Quality In-Flight Services 0.784 0.722 Multiple Meal Options of High Quality 0.601 0.552 Reliability 56.772 2.839 0.866 Special Need Customers 0.704 0.650 Problems due to Critical Incidents 0.816 0.743 Meet Time Commitment 0.808 0.734 Keep Error Free Records 0.737 0.678 Perform Service right the first time 0.693 0.640 Responsiveness 65.466 3.273 0.904 Prompt Service to Customers 0.818 0.768 Always Willing to Help Customers 0.853 0.797 Staff Behaviour should Instill Confidence 0.796 0.747 Keep Customer informed about time of 0.769 0.727 Service Staff never too busy to respond to 0.807 0.760 customer's request Assurance 62,727 2.509 0.867 Safe Planes and Facilities During Journey 0.673 0.626 Consistently Courteous Staff 0.866 0.783 Knowledge to Answer Customers' 0.817 0.742 Queries Individual Attention to Customer 0.799 0.728 Empathy 53.019 2.121 0.808 Staff gives Personal Attention to 0.758 0.658 Customer Customer's Best Interest at Heart 0.814 0.699 Understand Specific Needs of Customers 0.781 0.674 Convenient Flight Schedules 0.523 0.475 124 Step 2 After establishing the unidimensionality and reliability of each scale, all 30 items were jointly subjected to a common factor analysis. This approach allows all items to correlate with every factor without being constrained to correlate only with its underlying factor (Hau, 2005). The results of this procedure are shown in Table 5.10. As shown in the table, four factors were extracted which together explain 59.9 percent of the total variance for Perception and 55.2 percent for GAP. The factor loadings of each of the 30 items vary from 0.467 to 0.870 for Perception and 0.471 to 0.834 which are satisfactory. No item loaded highly on more than one factor. Regarding the issue of appropriateness, the result of the Bartlett's Test of Sphericity and KMO measure (Hau, 2005) indicated that the degree of intercorrelations among the items was suitable for EFA procedures (Chi-square = 10713.569, dF = 435 and sig. = 0.000, KMO = 0.969 for Perception and Chi-square = 9253.532, dF = 435 and sig. = 0.000, KMO = 0.965 for GAP). Factor Correlation test was carried out on the four factors. Factor 1 and 2 showed correlation with Factor 4, whereas Factor 3 did not show any correlation with other factors (Table 5.12). Table 5.11: Factor Correlation Matrix - Modified Instrument Perception Factor 1 Factor 2 Factor 3 Factor 4 Factor 1 1.000 Factor 2 0.774 1.000 Perception Factor 3 0.395 0.481 1.000 Factor 4 0.574 0.596 0.349 1.000 GAP Factor 1 Factor 2 Factor 3 Factor 4 Factor 1 1.000 Factor 2 0.757 1.000 GAP Factor 3 0.382 0.475 1.000 Factor 4 0.506 0.596 0.358 1.000 125 1 d 9 f id 6 3 M 1/1 1* 1^ Vi 0 00 1 irj o d 0 d d d 0 d i 0 1—< 10 1^1 p-l i-H 00 r~ » 60 r- r- ITi i d d d d d d 1d 0 d d d d d d d 1d •a !5 o E o i d d o >, d c I i < o 0 0 e u if- ir. nj id d d d d d d Li. ' 1 o d 1^ u 0 01 t r- a 0 0 i 5 r- 00 06 66 ir; w 0 d d d d d 0 0 d 0 d .0 i © 0 i CM «3 in • S 0) u p re (/:• z a It a 5.3.2 Phase 2 - Confirmatory Assessment (Using CFA) Stepl This section presents the results of the CFA applied to each of the 6 scales used in this study (Table 5.13 for Perception and Table 5.14 for GAP). The results show that 5 of the 6 measurement scales are over-identified and do not need any further refinements. The five scales that are over-identified and do not need any modification or refinement were related to Tangibility - Flight (7 items), Reliability (5 items), Responsiveness (5 items). Assurance (7 items) and Empathy (4 items), the scale for Tangibility - Support Service (3 items) - was just-identified (i.e. dF = 0). The standardized regression coefficients of all items ranged from 0.50 to 0.93 for Perception and from 0.47 to 0.86 for GAP. Therefore, it was safe to conclude that the six scales possess convergent validity. The results also show that the composite reliability of these six scales ranged from 0.733 to 0.924 for Percepfion and 0.689 to 0.905 for GAP. It was thus concluded that these scales were satisfactory in terms of reliability. 127 .^^ ro fO FH X fO X 00 t^ 00 O V o d d U Pi M o C/3 o o d NN o^ ON in 00 o\ d d «E^ 0\ 00 3& ON d d c o fS irj a (S tlH • C 1—( © ITi 0) E 3 ** V> o c •Ji:® •ao fS ®,.; «S lH Sw/ hH 00 V) 1^ 00 ON ON (J 9\ ON ON O d d HM^ ^ ^ o 3 t^ X ON 3& ON ON ON d d d c o o c in ON X (S t>H ITi «s o _o 5^3 V) «s V5 a. ^^ *o •* c4 0) ot_ 0) Q. 1 V) «s r^ *•> c 0) E X 2 ^3 3 O O 00 O v3 d 0^ 0) •B 12 b i- i3 o 'O M X ^ fO X X o • 4^ 3 vo X tn o «s «s TH •* f-i «s o NO o 00 00 00 00 00 X X X X X C en d d s d d d d d d SB •- d d d d a. < U CM li. 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O V O 0) tZ3 o cs •** S E < PM v "E En in ,^ o V en B B B B .** v s B « V s SB en B D. s 'a O >; PQ fi S U In the second step, discriminant validity was evaluated among all the fifteen pairs of constructs for Perception and GAP (total 30 tests). These pairs of constructs were tested separately before testing the whole measurement model because they are theoretically related to each other. Scales were tested for discriminant validity using a chi-square difference test (Sureshchander et al, 1996). CFA is run for the selected pairs of scales, keeping the correlation between the two factors as free parameters. Chi-square value (Chi 1) of this model was calculated. In the next step CFA was re-run for the same scales by fixing the correlation between the two as 1 and chi-square value of the second model (Chi 2) was obtained. The chi-square difference test checks for the statistical significance of the statistic (i.e. Chi 1 - Chi 2) at a significant level of 0.01. The two constructs of interest were distinct and hence unique as (Chi 1 - Chi 2) was statistically significant. The above procedure was repeated for all the possible pairs of scales in the instrument. All the thirty tests were statistically significant at the 0.01 level, thus indicating that all the scales were distinct constructs - a strong demonstration of discriminant validity. The results are presented in Table 5.15 for Perception and Table 5.16 for GAP. 132 TS t3 H3 -O ^ T3 '^ "^ "O T3 "O "^ "O "O •o • pa Pri ,p^ •Prt ap^ 'M^ apN • -a ••* •pa -"J • 3 •pa •p^ w '" "^ u R :« t CS CQ A ^ CQ A R 93 R n a "« Pi > > ^^ > > > > > >>>>>> > w ^ b. 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IN 'Prt • PN • M SP^ 'Pm •p^ • PM •p•^M • PN d .2 ^ 2 .& 2 ,£ J2 ,£ d d C3 • Prt • • p4 4 apM M (PM 'Pm •pa J2 o o »£ bC »£ b£ C3 M fiXI t IMD sr UD t «p«< A 0. 0. d d d 1a d d 3 d 13 d ^ ^ 1/1 VL i/> ^ S3 C3 u VI Pi Pi < H « Step - 3 Confirmatory factor analysis was conducted using LISREL 8.5 on all the six constructs to validate the relationship between observed and the latent variables. The results of CFA suggested that the six dimensional conceptualization fitted the data for passengers patronizing domestic airlines (Table 5.17). The overall results appeared to support the scales giving us the various constructs viz. Tangibility Flight, Tangibility Support Service, Reliability, Responsiveness, Assurance and Empathy (Chi-Square=]239.119, dF=335, P-value=0.00, RMSEA=0.0758, NFI=0.976, CFI=0.983 for Perception and Chi-Square=1083.997, dF=335, P-value=0.00, RMSEA=0.0690, NFI-0.975, CFI=0.983). Discriminant validity was evidenced by the inter-construct correlations that were significantly less than one (Anderson etal., 1988). Table 5.17: CFA Summary - Perception and Gap Goodness of Fit Statistics Recommendation Perception GAP (Garson, 2007) Degrees of Freedom 335 335 Normal Theory Weighted Least 1239.119 1083.997 Squares Chi-Square (P = 0.0) Root Mean Square Error of <0.08 0.0758 0.0690 Approximation (RMSEA) Normed Fit Index (NFI) >0.95 0.976 0.975 Non-Normed Fit Index (NNFI) >0.95 0.980 0.981 Comparative Fit Index (CFI) >0.90 0.983 0.983 Root Mean Square Residual <0.10 0.112 0.128 (RMR) Standardized RMR <0.08 0.0560 0.0493 Goodness of Fit Index (GFI) >0.90 0.842 0.859 Adjusted Goodness of Fit Index >0.90 0.808 0.829 (AGFI) The 6 factor model arrived at using CFA for Perception and GAP are given in Exhibit 5.1 and 5.2 respectively. 135 Exhibit 5.1: CFA 6 Factor Model - Perception 0.62-^ GPl 031-*~ GP2 A 0.59-^ GP3 A\ 0.57-^ GP6 0.51-— GP7 y \\ \ \\ 0.59*- GP8 ^\ U^. •' ' A\ 0\79 \ \ \ \\ 0.3(5*- GPIO v\\\ 'A 0.33— GPl 1 \t64\ 2^\ \ ...-^—... ^s^li ^ER TSS)—1 «^ER_REIj—1.000.59^4? ER_RE^)-1.03^.5y.S5 O.St .00 ER A.SS;—I.OQQ.99' - y ^ 0.3 H- &P29 0.72— GP30 Clii-Squafe=1239.12. df^335, ?-value=O.0QOOQ. RMSEA=0.076 Please refer to Table 4.1 for parameter description 136 Exhibit 5.2: CFA 6 Factor (Model - GAP 0.67--| GGl 0.44 -J GG2 0.62-1 GG3 0.58-i GG6 w 0.61-*- GG — \ \\ 0.62-H GG8 \ 1 \ 0. i \ W \\ 0.38-^ GGIO V \\\ .V\ 0.38-H GGll 0.62-^ GG12 0.47— GG13 0.40-— GG14 0.44-^ GGIS 0.40-^ GGl 6 0 78—;^AP_REL'—1.0fli:|,4H 0.450 — GG17 ^'^ ^ ^. /j^p_REs)>-l:09Q.5|l.82 0.38— GGl 8 ,. 0 84/// /"' "~N •7 "^-0.84///&AP_AS^-l-0H.m0 1 0.29— GGl 9 y^-'T'J 1/ ^"•rr--::; 0.99 p_E^i)—1.0/ 0.29— GG20 0.35— GG21 GG22 //o:r7 / 0.49— GG23 -^ '/0.80/ —=//7F' 0.25— GG24 ^/7// / 0.37- // // / 0.38— GG26 //7/ 0.44— GG27 **// / __--_^__ / / / 0.41— GG28 *j I 0.37— GG29 ^/ 0.71— GG30 ^ Clu-Squafe=1084.00. d&^335, P-vakie=0.00000. RMSEA=Q.069 Pleiae refer to Table 4.1 for parameter description 137 5.4 Hypothesized Airline Service IVIodel 5.4.1 Original Model SEM allows researchers to investigate the measurement model and structural model simultaneously (one-step modeling) or separately (two-step modeling). The separate estimation of measurement model and structural model has been found to be the commonly adopted technique (Hau, 2005). The same has been adopted for the current research. The first step, i.e. the estimation of the measurement model, has already been reported in previous section. This section focuses on the second step, i.e. the application of LISREL to test the hypothesized model. LISREL software was used to estimate the theoretical model based (Exhibit 5.3) on the information provided by the covariances matrix of the 28 composite indicators. The estimation method was the Maximum Likelihood (ML) based on the assumption that the observed variables are normally distributed. This assumption has been shown to be met by the data (Descriptive Analysis). All 28 composite indicators had kurtosis values ranging from -1.07 to -0.30, and skewness values ranged from -0.81 to +0.83 (Table 5.1). All indicators were normally distributed as the values were less than 3.0 for skewness and 10.0 for kurtosis (Hau, 2005). The resulting statistical estimates of the model are shown in Table 5.18 Table 5.18: Fit Indices for Airline Service Model - Original Goodness of Fit Statistics Critical Value Perception GAP Degrees of Freedom (dF) 436 436 Chi-square {y2) 1435.692 1368.557 Chi-square / dF <3 3.29 3.14 Root Mean Square Error of <0.08 0.0698 0.0675 Approximation (RMSEA) P-Value for Test of Close Fit (RMSEA >0.05 0.000 0.000 < 0.05) HOELTER Index (Critical N) >200 173.601 179.834 Normed Fit Index (NFI) >0.95 0.978 0.974 Non-Normed Fit Index (NNFI) >0.95 0.982 0.980 Comparative Fit Index (CFI) >0.90 0.985 0.983 Root Mean Square Residual (RMR) <0.10 0.0931 0.112 Standardized RMR <0.08 0.0471 0.0450 Goodness of Fit Index (GFI) >0.90 0.840 0.846 Adjusted Goodness of Fit Index >0.90 0.806 0.814 (AGFI) 138 Exhibit 5.3: Airline Service Model with Standardised Coefficients - Perception +— GPl ?— GP3 5-^ GP6 1— GP7 6— GP12 5-^ GPl 5 5-^ GP14 El --0.94 1^PER_TF)^\ 35,_- 5-- GPl 5 —-7.60 i-^ GP16 'ER_E^I^^. 0.26 />0.83 ER_RELK-—7-0.21 GPM —0.05 ^ 01" 0.86 //^ER_RES?^ / 0.13 GGM -*0.4: 3— GPl 9 /6.86' 'ER AsV^ 6-^ GP20 5-^ GP23 // 7— GP28 I—- GP29 Chi-Sqiiare=1435.69. dt^36. P-value=0.00000. R.MSEA=0.070 Please refer to Table 4.1 for parameter description 139 Exhibit 5.4: Airline Service IVIodel with Standardised Coefficients - GAP Ei *o.9: E2 --6.24 GPM --0.39 GGM --0.10 Clu-Square=1368.56. clM36, P-value=O.O0OOO. RMSE^=0.C67 Please refer to Table 4.1 for parameter description 140 5.4.2 Assessment of Model Fit and Model Modification In addition to the overall fit, it is necessary to identify any areas of misfit in the model (Hau, 2005). In this regard, LISREL yields the modification indices that are helpful for detecting the model misspecification. Modification Index (MI) reflects the extent to which the model is appropriate. For each fixed parameter specified in the model, LISREL provides an MI value. This value represents the expected drop in overall chi-square value if the parameter were to be fi-eely estimated in a subsequent run (Hau, 2005). A substantial MI value is 7.88 which, if adopted, will lead to a significant model improvement (Joreskog and Sorbom, 1993). Table 5.19 shows that there are eight parameters with MI values, that are greater than 7.88. Table 5.19: Modification Indices for the Theoretical Model Parameters Perception GAP M.I.* SDEC# M.I.^ SDEC# Tangibility - <;—s Convenient Flight 47.426 0.395 29.740 0.305 Support Services Schedules Tangibility - Flight Visually Appealing 43.919 0.477 21.702 0.325 Physical Facilities Tangibility - Flight Special Need Passengers 29.752 0.487 38.114 0.515 Tangibility - Flight Safe Planes and Facilities During 22.006 0.328 21.195 0.309 Journey Tangibility - Flight <;=0 Convenient Flight 23.360 0.442 16.211 0.336 Schedules Responsiveness Perform Service right the 0.990 first time 24.140 0.791 50.122 Assurance Visually Appealing 27.445 0.296 14.209 0.206 Physical Facilities Assurance <;:—> Perform Service right 46.619 0.930 60.306 0.953 the first time * M.I. Modification Index # SDEC Completely Standardised Expected Change These are the covariances of a) Tangibility - Support Service and Convenient Flight Schedules b) Tangibility - Flight and Visually Appealing Physical Facilities c) Tangibility - Flight and Special Need Passengers, d) Tangibility - Flight and Safe Planes and Facilities During Journey, e) Tangibility - Flight and Convenient Flight Schedules, f) Responsiveness and Perform Service right the first time, g) Assurance and Visually Appealing Physical Facilities, and h) Assurance and Perform Service right the first time. Model modification to improve its fit is therefore required. 141 Theoretical Considerations Although the statistics indicate the need for model modification, this should only be done with necessary theoretical support (Garver & Mentzer, 1999; Diamantopoulos & Siguaw, 2000). The theoretical justification for the suggested modification is explained as below. There is theoretical relationship between the construct and the dimension. > Tangibility - Flight and Special Need Passengers: These passengers include unaccompanied minors, differently abled individuals, and senior citizens who require special attention during the flight. Therefore, there exists a theoretical relationship between the two. > Tangibility - Flight and Safe Planes and Facilities During Journey: Safe planes and facilities, though covered under assurance were also perceived by the respondents to be related to the Tangibility - flight > Tangibility - Flight and Convenient Flight Schedules: Convenient flight schedule were also perceived to be related to tangibility - flight. > Assurance and Visually Appealing Physical Facilities: Visually appealing physical facilities assure the passenger regarding the quality of the service that is to be provided during the transaction > Assurance and Perform Service right the first time: Performing efficient service gives an assurance to the customer that the service provider is trustworthy. In the light of the above, the paths indicated by the MI are theoretically justiifiable. But, there existed no theoretical relationship between the construct and the dimension in the following cases: > Tangibility - Support Service and Convenient Flight Schedules > Tangibility - Flight and Visually Appealing Physical Facilities: > Responsiveness and Perform Service right the first time Therefore the paths as indicated by the MI were not theoretically justifiable. 142 5.4.3 Modified Airline Service [Model Given the above-mentioned statistical and theoretical considerations, the modified model was formed by adding five relational paths to the original theoretical model. In other words, five regression parameters that are constrained to zero in the original theoretical model were fi"eely estimated. As shown in Table 5.20, all the fit indices of the modified model were better than those of the original model. Thus, it was concluded that the modified model was more closely aligned with the data than the original theoretical model. Table 5.20: Fit Indices for Airline Service Model - Modified Goodness of Fit Statistics Critical Value Perception GAP Degrees of Freedom (dF) 419 419 2 Chi-square(/ ) 947.237 952.034 Chi-square / dF <3 2.26 2.27 Root Mean Square Error of <0.08 0.0518 0.0520 Approximation (RMSEA) P-Value for Test of Close Fit >0.05 0.246 0.219 (RMSEA < 0.05) HOELTER Index (Critical N) >200 238.035 232.439 Normed Fit Index (NFI) >0.95 0.984 0.981 Non-Normed Fit Index (NNFI) >0.95 0.989 0.987 Comparative Fit Index (CFI) >0.90 0.991 0.989 Root Mean Square Residual (RMR) <0.10 0.0637 0.0806 Standardized RMR <0.08 0.0320 0.0331 Goodness of Fit Index (GFI) >0.90 0.888 0.888 Adjusted Goodness of Fit Index >0.90 0.859 0.858 (AGFI) All indices indicate that the model achieved a satisfactory level of overall fit. The model and standardized regression coefficients between the constructs are shown in Exhibit 5.5 for perception and 5.6 for GAP. 143 Exhibit 5.5: IModified Airline Service IVIodel with Standardised Coefficients - Perception 46-^ GPl GP2 (0.22 := 0.13T5.71— GP3 \ >i.55-^ GP6 0.12 / 0.60-^ GPS K' \\'A65 I ^.48— GP9 -0.07).14 = , ^-41- GPIO vN^x|4^ \/I.38-- GPll 0.1 S-6i \ ^- --^ \ 0.63 El —0.94 PER_TF)^\g^ '—.^ 0.25 LOY i- ""-2.9S- 0.S1 \ 11 ^^•'—- \o--^ E2 —-7.89 GPl 6 t^^ Xj/^'^-^-'j^^^-^.-" 37 "'X; 0.45*- GP17 r '^^.-^nMb^^ ^V^<--0.1—-ni'r-^(^3 SAT ) -0.97 GPM —0.05 \y / III -^=r^ •0.13 ' 0.35— GPIS K ./ Wl /^' ' -0.13 0.76 0.16 GGM —0.^ '^ER ASS; -0.0(5 T..30— GP22 .29— GP25 r/Vf ja.32— GP26 'j/ll 0.08 .- j'/7 >l.36— GP27 r/7 0.37-— GP28 0.32— GP29 r/ 0.66-^ GP30 Chi-Sqiuire=947.24. dr=419. P-value=0.00000. R:VISEA=0.052 Please refer to Table 4.1 for parameter description 144 Exhibit 5.6: IVIodified Airline Service IVIodel with Standardised Coefficients - GAP El -^0.92 0.2S LOY E: —-5.93 -0.12 I SAT V 0.7S GPM -^0.39 . •-'^ "\ 0.94 \.^ GGM -^0.11 Chi-Sqiiare=952.03. df=419. P-v-akie=0.00000. RMSEA=0.052 Please refer to Table 4.1 for parameter description 145 5.4.4 Model Analysis The structural equation model followed conventional linkages between service quality constructs, overall satisfaction and loyalty to the airline, i.e. likelihood of future purchase. The model employed maximum likelihood estimation. Two versions of the model were estimated. Version 1 was for perception and version 2 for GAP. The estimated relationships are presented in Table 5.21 The relations between independent and dependent variables in the present study, as assessed by SEM, show that there is a significant direct and positive relationship between nearly all independent and dependent variables, thus indicating sufficient criterion validity. Passengers perceive empathy on the part of airline staff to be having direct impact on satisfaction and loyalty, whereas responsiveness and reliability were perceived to be having a low impact on satisfaction and loyalty. Tangibility-flight and tangibility - support services builds the loyalty, though its impact on satisfaction is low. Interestingly, GAP in the case of tangibility - flight did affect satisfaction though its impact on loyalty was low. GAP in assurance and reliability did affect satisfaction and loyalty. However, GAP in empathy did not impact satisfaction or loyalty. As the parameter estimates in table 5.21 show, and contrary to expectations, satisfaction was having low impact on loyalty. Original model showed positive impact of satisfaction and loyalty. It was also observed that impact of other latent variables on loyalty changed significantly after the model was applied. The high value of standard error in case of loyalty in modified model indicates that the parameter cannot be reasonably determined by the data in hand (Diamantopoulos et al, 2000). This may also be indicative of practical absence of loyalty in the surveyed passengers towards any particular carrier. 146 00 O r—1 (N ON in ON TS a> .S ON 00 O ON 00 00 m >n 00 o ON o 00 NO in 00 o o m d d d d d d d d d d d < 1 1 1 o ON o 00 vo O ON o T-H 00 00 o o O o in q ON q d d d d d d d d d d d d 1 ^ ON ON lO ON o "O "^ •« ON o ON 00 NO o m o m o o q 1—( O d d d d d d d d d d d d 1 a lu 03 d 1 1 a i; a? 0) o o o ON en S CO CO in CM m 0\ in m T3 0) a .2 *2 d d d d d d d d d d d (N 1 1 1 1 0 S m ON 00 in o T-H 00 00 ON 00 o .—1 a q 00 (N in CN (N rn d d d d d d d d d d d V) o > 1 1 1 1 1 0) (0 • MM t^ E 0\ ON o 00 00 ON -* (A (J ON >n o o NO o O ON in q 00 T-H UJ u i_ a> d d d d d d d I—1 in 0) 4-> 0) E o ON 00 >n 00 O ON NO 00 n3 "O -w ON 00 m m in ON 00 a u «s (N o m (N (0 q d d d d d d d d d d d d « .2 S 1 t 1 a s 50 1 Q. 1 t3 * W N (0 1- t u a t: o o •** a U3 a •Sf If] O s .£3 1 1 a a •*-< V 4> .Sf 1/1 .>; 1 J3 'te a a 'A 03 1 a •M a u > o u '5JD o u a a a .a a u a a a « s m 13 a % o H c« 'So on U .2 S •M< H a en s i i :3 « 13 !/3 i H a a a a a a H 03 o o o o o o i i i i i U u u i i ;^ !» !» "3 ;^ •** >> So. o o o O o 03 c The performances of the airhnes on various service parameters were analyzed and the same is presented below: 5.5.1 Tangibility - Support Services The service quality parameters falling under this dimension include 'visually appealing physical facilities', 'vast sales and support network' and 'vast network of destinations'. FSC - Public has the biggest network of destinations. It also has vast sales & support network. FSC - Private have visually appealing physical facilities. Gap was highest in case of LCC for network of destinations. Passengers expected LCCs to fly to more destinations. Airline staff exhibited higher perception of customer's expectation across all the airlines. Passengers have low expectation from international carriers resulting in least Gap. 5.5.2 Tangibility - Additional Support Services The service quality parameters falling under this dimension include 'economical airfare and discount schemes' and 'web-site and call center usage'. LCCs were rated high on economical airfares and use of website/call center. Passengers expected more discount and economical airfares in case of full service carriers. International passengers have low perception regarding quality of additional services being provided by international airlines. There are restrictions on booking through web site using international credit cards. 5.5.3 Tangibility - Flight The service quality parameters falling under this dimension include 'modem aircraft with up-to-date facilities', 'neat well dressed and visually appealing staff, 'seat in flight of choice', 'hassle free check-in and boarding', 'efficient baggage handling mechanism', 'excellent quality in-flight services' and 'multiple meal options of high quality'. Passengers had high perception regarding the quality of in-flight service of private airlines. Gap regarding aircraft quality and facilities available was high in case of FSC - Public as the aircrafts are quite old, especially those being flown by Alliance 148 Air. Passengers were not satisfied with the quaUty of food provided during the flight. Interestingly, the gap was also high for LCC vis-a-vis in-flight meal options, even though the LCC guidelines are quite clear regarding non-supply of meals to the passengers. Passengers were clearly not satisfied with baggage handling procedure of LCCs. FSC - Private and LCC staff was perceived to be neat and good looking. FSC - Private customers expected more from the airlines. They wanted better quality service during check-in and baggage handling. They desired seat of choice and better quality meals during the flight. FSC - Public passengers expected more with respect to in-flight services. International flights were rated high on the in-flight services as they try to meet the expectations of the passengers. But passenger expectations were found to be on the higher side. Thus, correction is required on the part of these airlines if they want to expand their business in India. 5.5.4 Reliability The service quality parameters falling under this dimension include 'special need customers', 'problems due to critical incidents', 'meet time commitment', 'keep error free records' and 'perform service right the first time'. Gap was high in case of reliability of service for LCCs. Respondents were not satisfied with their service in case of special needs, problems due to critical incidents' and their inability in meeting time commitments. The service of FSC - Public was also perceived to be poor during the critical incidents. The general perception was that FSC - Private keep error free records and performed service right the first time. During critical incidents, FSC - Private customers expect airline to provide better service. FSC - Public passengers have higher expectation fi-om the airline to meet time commitment. Private airline's (both FSC and LCC) passengers expect airlines to keep error free records. In this context, it is to be noted that international airlines have very high reliability standards. ' Negative customer encounters, do not proceed normally but create friction, irritation and dissatisfaction. According to Edvardsson (1992), the major critical incidents in the view of business passengers are delays, cancelled flights, delayed or damaged luggage and overbooking. 149 5.5.5 Empathy The service quality parameters falling under this dimension include 'staff gives personal attention to customer', 'customer's best interest at heart', 'understand specific needs of customers' and 'convenient flight schedules'. Gap between passenger's expectation and perception was high for LCC on all the parameters, namely, staff giving personal attention to customer, airline having customer's best interest at heart; staff attending to specific needs of customers, and convenient flight schedules. It is worth mentioning that LCCs started operations in India during the last few years and their fleet size is not big. To extract maximum revenue, they tend to fly aircraft for longer durations leading to inconvenient flight schedules and inconvenience to passenger in case of any snag in aircraft. Overall, the airlines scored low on empathy. FSC - Private passengers expect airline staff to have customer's best interest at heart. Passengers expect FSC to provide more convenient flight schedules. Gap between passenger and airline staff was very high. Thus, it is indicative of the fact that customers expect a higher level of understanding from the staff 5.5.6 Responsiveness The service quality parameters falling under this dimension include 'prompt service to customers', 'always willing to help customers', 'staff behavior should instill confidence', 'keep customer informed about time of service' and 'staff never too busy to respond to customer's request'. LCCs are unable to provide prompt service to customers perhaps due to low staff to passenger ratio owing to rapid expansion in their operations. At Delhi airport, the number of counters available to them are few (and small) leading to congestion and delay in service to customers. Most of the LCC passengers are first time flyers and consequently they have high anxiety regarding when service will be performed. LCCs have not been able to keep pace with their expectations. The perception was that FSC - Private provides prompt service to customers and that their staff was always willing to help customers, and they keep the customer informed about the time of service. 150 Overall, FSC - Private scored high on responsiveness. Passengers expect FSC - Private staff to meet their requirements and provide prompt service. FSC - Private confirmed to international standards on responsiveness. 5.5.7 Assurance The service quality parameters falling under this dimension include 'safe planes and facilities during journey', 'consistently courteous staff, 'knowledge to answer customers' queries' and 'individual attention to customer'. Findings suggest that LCC staff were poorly trained to answer customers' queries. In fact, most of the passenger handling staff was freshly recruited and at times they find it impossible to handle all the passenger queries. They also do no have adequate staff to provide individual attention to customers. The first time flier, who probably is paying beyond his means, expects higher level of personal attention, which, unfortunately for him, is not a part of package. FSC - Private scored high on assurance. FSC - Public and LCC staff was expected to provide more individual attention to the customer. Customer's also expected FSC - Private staff to answer their queries. It was found that passengers rate international airlines high on Assurance dimension. Overall, airline staff was found to be having higher perception of customer's expectation. However, customers expect FSC - Private to provide even higher level of service in case of tangibility - additional support services, tangibility - flight, reliability and responsiveness. It can be noticed that FSC - Private has similar service quality standards as international airlines. Table 5.22 presents a summary of the above findings. 151 r-) o\ f-^v -* M^ o >/-^ t— OO eo r-- r 1 VO in -* r»v r-^ r-- r-n r-- l-~- r-» ea T—t tsa ro r^l i/l VO eo VO ry o f<^ a> m r^n vo (•""- OS vo n VO trt r'S (-rr\^ OO (N •* «—1 •—4 t~. o m n^ w •r\ r— O ro p e^l oq o\ p c»s o o o «d O O s C5 O o o o 1 1 o 1 ^ 1 1 p p ^ p o ^ o 1 1 1 1 "^ 1 1 o \o OO ri Ov C3 Oi O ri CO t-- vO OO r-:l ro O r-- r- ri *ri VO OO c--t OO r-- C^i r«1 VO VO Ov g f^^ ifNl VO VO ir<"i in OS m r-1 60 < vq 5! M ^ Ov n r j p «—* p 1^1 *—• p 1/S iri o iri ed lo in in in 1 vd 1 vi S" •n vd 1 '^ vd 1 vd t vd 1 vd p s CO t— OS 'Cf OO VO VO in tT-i f»-i VO •^ r 1 m r— t-i^ -* OO OS -* 11^ VO ft r^ ^o OS lO Ov *^ •sf Ov 1^ *n Ov VO o VO OO (^ >et o m OO f- ^0 lO C3^ o VO in •-n V—4 1-^ "-1 o o m in OO OS o i-» Ov |v~. •—< I-— ^ Ov OO OO in ^^ >o r-- g o (0 VO •c o «* f»s c^ rri r^ r^ rfS r»s o t-- r«-i r<^ SO ro od OO ^^ 0) lo T—* o\ f«-l -1 m VO l.-~ in I/-V in Ov OV f*l SO r^ NO OS rr-) Pb, (-- r«-i Ov I/-1 p 'O^S C<> ^ 0) 1/S r-" r^ •«t VO ^ cs vq m r-- **^ in m VO in ini VO p HJ f/^' <^1 0) *j^ r^ CO cs OO r—. rs VO PO "<*• VO i:^j OO r-j r-i C3 r~- in in r-- r- o •^-* -* *^ r--. OO m OO *nw| OO fv| VO VO rn VO r-i 1* OO VO f--: r— OS t— vo o t. c f^ fl ^*«—^I (*S Ci f^i n M Os r-J "* IO r~^ o "* p r-1 r-1 r-i O ft fi O r-l r-i o $> •f^ vd o VO vci O vd VO o vd vd o vd vd p vd vd o vd vd p vd vd o 1 ^ E 6^ S^g t ^ f^ Vl '/"I >/~i C5 T—* in O in O Ov l5^ r<^ Ov OS l".< 0) c> »—* ^—1 c> o o ^—# r—- ^ M a. C3 (S a 1 -4MI -4-1 -41^ •1 CM in ^ o 1O The gap between customer's expectation and perception is a result of set of four gaps as identified in the hterature review. An adapted version of service quality audit questionnaire developed by Messinger (2003) consisting of 4 constructs was used to measure the four gaps (Appendix - 3). Gap 1 (Consumer Expectation - Management Perception Gap) The scale consisted of 5 items. Perhaps LCCs do not undertake market research or utilize its findings.Th e regular interaction with customers is also low in their case. FSC - Public, because of its size and legacy procedures, is not able to disseminate information to all levels. The staff too agreed that levels of management inhibit communication with the customers. Gap 2 (Management Perception - Service Quality Specification Gap). The scale consisted of 17 items. FSC - Public scored low on most of the parameters as there are no clear goals for customer service, no mechanism to measure performance against these goals and also there is no incentive to improve service quality. For LCCs, perhaps sales goals are more important than customer service. Gap 3 (Service Quality specification - service delivery Gap). The scale consisted of 16 items. Here also FSC - Public scored low on most of the parameters. The staff is neither empowered to deliver service, nor do they have the decision making freedom. There is also no incentive for better customer service. The airline staff felt that they spent more time resolving problems over which they had little control. Gap 4 (Service Delivery - External Communications Gap). The scale consisted of 5 items. FSC - Public customer service staff did not have feedback on planning and execution of advertising, nor are they aware of the need for external communication to address customers. The staff felt that external communication does not accurately reflect what customers receive in the service encounter. 153 5.5.9 Results of Hypotheses Testing One-way ANOVA test for independent samples was conducted at significance level of 0.05 to test the null hypotheses. To gain deeper insight, the same was checked for different dimensions too i.e. Tangibility - Support Services, Tangibility - Additional Support Service, Tangibility Flight, Reliability, Empathy, Responsiveness and Assurance. It was observed that significant differences did not exist in mean scores for the gap between customers' perceived and expected service quality (Reliability) across Airline Categories (H04) and also there was no significant difference in mean scores for the customers' expected service quality across airline categories (Hog). All other hypotheses were rejected. However, passengers were found to be having significantly higher perception of service quality for FSC - Private as compared to FSC - Public and LCC's. Findings also indicate difference in the gap between customers' perceived and expected service quality among different categories of airlines for all dimensions. Table 5.23 presents the results of ANOVA test. 154 1 T3 ^3 T3 T3 •*-» a< o o o o o •5? '57 Pi o o 00 ON o o o NO o o o o q o d d d > d o 00 (N 00 o 00 CO oo E^ 00 in m < in o > o NO (N o o o O O O z d d d d d < c > > u !» T-H o in •M o o c « 00 O 73 o in ON i o >n ON NO o in o "5 O 00 ON 00 ON 00 o NO m o ON M X/1 ON o rn q o q 00 in 0) o d ON ri 00 ON NO in NO C/5 in" H 00 in in NO in ON I—1 a oo o in m o in in 00 00 NO NO m 00 00 in o (N in ON o o 00 d 1—1 o u (N d 00 NO 00 NO NO ON NO in 1 1 1 1 1 1 1 1 1 1 1 1 1 1 in o 1 c 0\ 0\ ON ON ON 1—1 O o C^ o t^ o l> NO o NO Z >n in in in r^ 00 in < 00 00 00 1—1 00 0) ni o o u o I—H & o > _> _> CD > 3 3 .rH 3 3 WD 1 ;-, a OH 1 cd PL, PH 1 PH PL, PL, PL, -^ « 1 1 1 1 1 1 1 u u U u U U U U u U U U #N U U u u U U u O u U u U 00 00 U 00 00 00 "E 00 PL PL ,—1 PL, T3 T3 t« "2^ T3 *-> o •!-> 73 0) o \-* O 73 o -^ ^ 2 0) O n (U O g g-s S X 9 1- (U 1) " ^ -ra 3 < O (L» >, U Ml TS :J3 •** B< (u S O ^ (U W u rv T3 tiO O .S o ^ a Mr. CO D r/1 H - ^ •-? OJ 73 3 ra 0) t/3 3 i-j 5^ ^^ S^ ,u (D ~ 4-. n C r. (S tJ ^t< g O -C fl ^ S 8 g (U 73 3 TO OS (N (N o C ^-H (^ 00 (N m &£ o r-H o r^ o o • PN 00 o o o o o V d d d d d < > sn O _w 1^ *+* 00 »—1 ^ o ON z sn vo (N (N in 1—1 < i> VO m m 00 ss >> •T) m' (N ^' 10 Xfl d o • in 00 (N 00 < o o o o ;H ;H •-H Is a O > 0) > U 0) 3 3 3 •rH 3 • iH S<5 • p« DC :3 •t-H s 'S :3 s "C 3 'C k4 t3 fa 3 IN Pu OH "aE CL, PM 'B CIH OH C3 OH PL, Cin PLH "E fe i •>s* 1 1 1 1 s 1 1 1 1 s 1 1 s (0 ^ A U U o —1 ^-1u r-H -uH u 3 U U U u u U U U O U u u U u U U —1 :2i oi 00 U 00 &c O 173 00 U C/3 iz) U oo K/l U •51 o0) UH tLH J l-H fe UH J h—1 UH fe hJ fe fe J tlH PLH J l-H 2 y^ ^ *0E) -o ^ ^3 V (0 CO 'co fH « 1H a a O c/5 CO " 2 s g id y K u JH (U ^ e3 ^ KJ 12 G ,. cd -H C CO +j CH r> ^ PA "« U CO 3 •" 1) CO 3 ra U CO C^ ^ fe §-< cSl^^ ^ 2 g^l s !« S 8 c« ^ g (U D ^ S 5.6.1 Assessment of Measurement Scales Using CFA CFA was conducted using LISREL 8.5 to validate the relationship between observed and the latent variables (Exhibit 5.7). Exhibit 5.7: CFA 3 Factor Model - IT and Service Delivery 0.70-*- CIA 0.53H^ CIB 0.56-^ CIC 0.24-'^ CID 0.48-^ CIE 0.42H^ CIF 0.26- CIG 0.66- cm Clu-Squaie=97.63, (lf=17, P-value=0.00000, RMSEA=0.100 Please refer to Table 4.2 for parameter description The three items were assessed by CFA with the sample data and the resuhs showed a saturated model with perfect fit. Finally, the three scales of FSS (3 items), IFS (2 items) and CSS (3 items) were simultaneously assessed by CFA. The overall results appeared to support the scales despite the significant Chi-Square statistics (Chi- Square-97.633, dF=17, P-value=0.00, RMSEA=0.100, NFI=0.946, CFI=0.955). Discriminant validity was evidenced by the inter-construct correlations that were significantly less than one (Anderson et al, 1988). The results of CFA suggested that the three dimensional conceptualization fitted the data for domestic airline passengers (Table 5.24). 157 Table 5.24: CFA Summary - Role of IT in Service Delivery Goodness of Fit Statistics Critical Value Value Degrees of Freedom 17 Normal Theory Weighted Least Squares 97.633 Chi-Square Root Mean Square Error of <0.08 0.100 Approximation (RMSEA) Normed Fit Index (NFI) >0.95 0.946 Non-Normed Fit Index (NNFI) >0.95 0.926 Comparative Fit Index (CFI) >0.90 0.955 Root Mean Square Residual (RMR) <0.10 0.0541 Standardized RMR <0.08 0.0541 Goodness of Fit Index (GFI) >0.90 0.951 Adjusted Goodness of Fit Index (AGFI) >0.90 0.895 5.6.2 Measuring Impact of IT on Passenger Services Chi square statistic was applied to identify the goodness of fit and relationship between the airline categories and impact of IT on Flight Support Services, In-Flight Services and Customer Support Services. Chi square test for goodness of fit was significant for all measures (Table 5.25). This implied that there were significant differences between the category of responses (no improvement, negligible improvement, some improvement and significant improvement) with respect to impact of IT on service parameters. Table 5.25 : Chi-Square Test: Impact of IT on Passenger Services Service Quality Parameters Goodness of Fit Relatedness with Primary Airline Chi- Deg. of Sig. Pearson Deg. of Sig. Square Freedom Value Value Freedom Value FSS Flight Support Services CIA Reservation and Ticketing 727.157 3 0.000 34.518 9 0.000 CIB Check-in and Boarding 487.191 3 0.000 20.760 9 0.014 CIC Baggage Handling 70.325 3 0.000 5.644 9 0.775 IFS In Flight Services CID In-Flight Service and Facilities 59.166 3 0.000 6.853 9 0.652 CIE Catering / Meals 18.299 3 0.000 12.128 9 0.206 CSS Customer Support Services CIF Customer Complaint Handling 130.316 3 0.000 24.641 9 0.003 CIG Cust. Relationship Management 179.743 3 0.000 28.979 9 0.001 cm Frequent Flyer Program 231.038 3 0.000 29.285 9 0.001 02 Overall Impact of IT 134.178 2 0.000 16.662 6 0.011 158 Table 5.26 summarizes the responses received from passengers when they were asked to indicate the improvement in satisfaction levels as a resuh of the use of IT by Primary Airline (airline flown maximum number of times). Control variables - Gender, Frequent Flyer, International Travel exposure and highest qualification - were also used to get further insight into the above relationship. Table 5.26: Impact of IT on Airline Services: Passenger Perceptions Passenger Response FSC- FSC- LCC Internat Total Public Private (percent) ional (percent) (percent) (percent) (percent) No Improvement 2.9 3.6 3.8 3.9 3.4 and Negligible Improvement 3.5 1.2 5.0 17.6 4.5 Ticketing Some Improvement 12.9 10.1 18.8 21.6 13.8 Significant Improvement 80.7 85.2 72.5 56.9 78.3 Check-ia and No Improvement 5.3 6.5 5.0 9.8 6.2 BoardJBg Negligible Improvement 5.3 4.1 7.5 19.6 6.8 Some Improvemeiit 19.3 17.8 25.0 11.8 18.9 Significant Improvement 70.2 71.6 62.5 58.8 68.2 Baggage No Improvement 12.3 14.8 18.8 17.6 14.9 Hasdling Negligible Improvement 18.7 20.1 16.3 21.6 19.1 Some Improvement 24.0 25.4 31.3 23.5 25.7 Significant Improvement 45.0 S9.6 33.8 37.3 40.3 lu-Flght No Improvement 12.9 15.4 18.8 7.8 14.2 Sen ices and Negligible Improvement 21.1 21.3 16.3 27.5 21.0 Facilities Some Improvement 26.9 23.1 28.8 31.4 26.3 Significant Improvement 39.2 40.2 36.3 33.3 38.4 Catering / No Improvement 14.6 17.8 27.5 15.7 18.0 Meals Negligible Improvement 21.6 23.1 18.8 35.3 23.1 Some Improvement 28.7 27.2 28.8 23.5 27.6 Significant Improvement 35.1 32.0 25.0 25.5 31.2 Customer No Improvement 18.1 17.2 17.5 11.8 17.0 Feedback Negligible Improvement 11.7 6.5 13.8 23.5 11.5 Some Improvement 19.3 25.4 31.3 37.3 25.5 Significant Improvement 50.9 50.9 37.5 27.5 46.1 Customer No Improvement 17.5 11.8 15.0 11.8 14.4 RelatioQsfaip Negligible Improvement 9.4 5.9 15.0 15.7 9.8 Management Some Improvement 18.1 26.0 32.5 43.1 26.1 Significant Improvement 55.0 56.2 37.5 29.4 49.7 Frequent No Improvement 15.2 iO.7 18.8 7.8 13.4 Fiver Negligible Improvement 10.5 7.7 21.3 11.8 11.5 Programme Some Improvement 18.1 16.6 26.3 31.4 20.4 Significant Improvement 56.1 65.1 33.8 49.0 54.8 rr Adds to Neither Agree nor 4.7 6.5 17.5 15.7 8.7 Passenger Disagree Senices Agree 45.0 39.6 40.0 35.3 41.2 Stionglv Agiee 50.3 53.8 42.5 49.0 50.1 159 Reservation and Ticketing All domestic airlines are presently using Internet based system as well as call center support for flight reservations and inventory status details. Web sales account for 35 percent of all ticket sales and barriers to wider internet use appear to be diminishing. On an average 72 percent of tickets issued today are e-tickets. This is predicted to reach 86 percent by end of 2009 (Baker, 2007). If the industry adopts 100 percent e- ticketing, it will save upto $3 billion per year (Simhan & Varghese, 2006). Global Distribution System (GDS) such as SABRE and AMADEUS are also used to store and sell inventory internationally. However, there is a risk premium for internet airline reservation services, which affect consumer buying process (Curmingham, Gerlach, Harper & Young, 2005). Significant relationship [%^(9, N=471) = 34.518, p=0.000] was observed between respondents of different airline categories and their perception of impact of IT in the area of reservation and ticketing (Table 5.25). From Table 5.26 it is clear that the use of IT had resulted in significant improvement in satisfaction levels among respondents across all the categories of airlines. An examination of the observed data revealed that frequent flyers and professionals across the airline categories had higher awareness regarding impact of IT on reservation and ticketing. Check-in and Boarding Upon arrival at the airport, passengers are supposed to report at the airline's counter to complete the formalities. Besides normal check-in at the airport or city office, the IT based check-in options available to passenger are web and kiosk check-in, which provide additional flexibility to the passengers. The use of web-check-in has risen from 43 percent in 2006 to 53 percent in 2007. Bar coded boarding passes are being used by 46 percent of airlines and expected to rise to 88 percent by 2008 (Baker, 2007). Significant relafionship [%^(9, N=471) = 20.760, p<0.05] was observed between respondents of different airline categories and their perception of impact of IT in the area of check-in and boarding (Table 5.25). Use of IT in check-in and boarding 160 resulted in improvement in satisfaction levels as per majority of respondents irrespective of the category of the airlines they patronize (Table 5.26). Baggage Handling Passengers need to get their baggage screened at the check-in counter after which they are issued their domestic boarding passes as well as baggage tags for their final destination. An IT based solution - Positive Passenger Bag Match (PPBM) - saves airlines millions of dollars in mishandled baggage costs and improves customer service. New technologies such as RPID tags capable of sending digital information over secure wireless networks are also revolutionizing baggage handling (Wyld et al, 2005). The advanced scanning technology allows the airline staff to keep track of bags that are loaded on the aircraft. So if a bag needs to be located and removed for any reason, retrieval can be done in a matter of minutes. Thus, airlines can avoid long delays searching for unaccompanied baggage. Low overall relationship was observed between respondents of different airline categories and their perception of impact of IT in the area of baggage handling (Table 5.25). From Table 5.26, it is clear that the use of IT in baggage handling had resulted in minor improvement in satisfaction levels among the respondents. Frequent flyers across the airline categories are definitely concerned with baggage handling mechanism of domestic airlines and the role IT can play in tracking baggage during the journey. In-Flight Services and Facilities Now-a-days airlines are offering SMS and e-mail facilities onboard. Sending and receiving SMS, surfing the Web and accessing e-mail will be more widely available in-flight very soon. New aircrafts being procured by domestic airlines are fitted with in-flight video and audio entertainment facilities to improve passenger in-flight experience. While primarily aimed at enhancing passenger services, these technologies, it is expected, will also offer considerable operational and safety benefits to the airlines. 161 Very low overall relationship was observed between respondents of different airline categories and their perception of impact of IT in the area of in-flight services and facilities (Table 5.25). But use of IT in in-flight services and facilities had resulted in minor improvement in satisfaction levels among the respondents (Table 5.26). Catering /Meals Full Service Carriers offer a wide variety in its in-flight meal menus, with a multi- cuisine approach to cater to the preferences of the range of passengers on its network. For catering logistics management, vendors have used internet technologies to extend domestic airline's catering supply applications over an extranet, helping them improve catering management efficiency and reducing costs. Airlines normally order for vegetarian and non-vegetarian meals based on their past experience with some extra tolerance. However in case of special meal requirements like diet, Jain , salt-free, etc airlines pick the information from PNR to make special request to caterers. Low overall relationship was observed between respondents of different airline categories and their perception of impact of IT in the area of catering / meals (Table 5.25). Thus, use of IT in catering/meals has resulted in moderate improvement in satisfaction levels among the respondents. Customer Feedback Relationship exists between respondents of different airline categories and their perception of impact of IT in the area of customer feedback (Table 5.25). Table 5.26 illustrates that the use of IT in getting customer feedback has resulted in improvement in satisfaction levels for FSC-Public and FSC-Private passengers while the LCC passengers were not that satisfied. 2 Jain meal - This meal is for members of the Jain community who are pure vegetarians. It is prepared with a selection of Indian condiments. It contains one or more of these ingredients: fresh fi^it and stem vegetables that grow above the ground. It does not contain: animal products and by products, and any root vegetables such as onions, mushrooms, ginger, garlic, potatoes, carrots, beets, radishes, etc. 162 Customer Relationship Management Airlines are increasingly embracing IT based customer relationship management (CRM) tools for competitive advantage and improving profitability by developing long term relationships with their passengers (Feldman, 2002; Binggelt, Gupta & de Pommes, 2002; Boland et al, 2003; Viaene & Cumps, 2005; Beaujean, Davidson & Madge, 2006; Darby & Simone, 2006; Soldt et al, 2007). By taking steps to implement a truly consumer-centric approach to relationship management, an airline can be better positioned to acquire, develop and retain high-value customers. Significant relationship exists between respondents of different airline categories and their perception of impact of IT in the area of customer relationship management (Table 5.25). From Table 5.26, it is clear that the use of IT in managing customer relationship had resulted in improvement in satisfaction levels for FSC- Public and FSC-Private passengers. But the scenario was just satisfactory for LCC passengers. From the findings it appears that FSC—^both public and private—are making greater use of IT for managing customer relations as compared to LCC and the passengers too are perhaps aware of it. Further, significant relationship exists in the case of males, frequent flyers, domestic travelers, professionally qualified respondents and graduates. Frequent Flyer Programme All FSC in India now offer frequent flyer programmes. Indian Airlines with Alliance Air and Air-India offers Flying Returns, Jet Airways offers Jet Privilege, Air Sahara calls it COSMOS^ and Kingfisher offers King Club. The primary objective is to attempt to promote customer loyalty by offering awards for mileage or points accumulated during flying. LCC generally don't offer any frequent flyer programme as such and thus there is little or no role of IT in their loyalty programme. There was near unanimity between respondents of different airline categories and their perception of impact of IT in the area of frequent flyer programmes (Table 5.25). Use of IT in frequent flyer programmes had resulted in major improvement in 3 Effective 1 July' 2007, all the members of the COSMOS frequent flyer programme have been enrolled into Jet Airways' Jet Privilege programme and all their balance miles have been transferred to their Jet Privilege account. 163 satisfaction levels for FSC-Private passengers, while passengers of FSC-Public and LCC were comparatively less satisfied (Table 5.26). Significant relationship existed in all the categories except for domestic travellers and respondents with post graduate qualifications. Overall Impact of IT on Airline Services Table 5.24 shows a percentage wise breakdown of the distribution of respondents. The greatest number of respondents indicated strong agreement (50.1%) while the lowest number of respondents fell in 'Neither Agree, Nor Disagree' category for primary airline grouping. It is to be noted that none of the respondent disagreed vis a-vis importance of IT in delivering service in airline industry. Though not statistically significant, it is interesting to note that passengers who had LCC as their primary airline were not that favourably disposed toward the contention that IT had added value to passenger services. While majority of respondents (94.8%) who either had FSC-Public or FSC-Private as their primary airline were in agreement that IT has contributed to enhancement in passenger services. 5.6.3 Adoption of Internet Technologies Internet based technologies are now a major enabler for aviation industry in their quest to achieve substantial cost savings, working effectively, efficiently and safely (Kelemen 2003). Website and web based applications are being extensively used to provide customers service at their door-steps. Check-in kiosks, internet and mobile telephones are also gaining in popularity (Smith, Gunther, Rao & Ratliff, 2001; Wei &Ozok 2005; Baker 2007). Airlines are upgrading their websites to make it easier for Internet savvy passengers to pick and choose flights by price and schedule. The objectives are to attract more travelers to the site, cut customer service costs and increase sales (Higgins 2007). Table 5.27 lists the information provided on the website of various airlines that passengers can access without the intervention of airline staffer travel agent. 164 o o O .Sf t/2 CO CO CO 73 73 CO CO CO CO 73 CO •3 fl o o 0) o o •3 Z s o ,g 73 73 CO CO CO CO t/3 CO 73 o o o 73 o .fa (U O o o 'S Z 0^ o 1^ bc z a i •«-• 5 o o . C/1 on 00 CO 73 to CO 73 CO o CO 73 o CO CO ^ Z z N:u; > H •o •*j o 3 73 73 CO 73 CO 73 CO !Z1 CO CO 73 CO 73 CO CO o o 0) (0 0) fU >- Z z T3 (/l • P4 C a M D •M 0) 0) c a a 13 C8 a C/3 C/3 c/a w yj C/3 73 73 CO CO 73 CO 73 CO k u u D U (U a> o QJ u u > > >^ >^ >^ > >^ < u > >- >^ >- ^ >H >H >^ Z z o Q •p4 (A (3 0) 4^ '35 CO CO C/J CO CO 73 CO 73 CO 73 CO CO CO O CO O ^1 bc o o O c a u o 2,2 ;2 z •o >^ 0) G T3 "> /~\ O s k IM "iaS In" o Q. u CO CO 73 CO 73 CO CO CO 73 73 CO CO CO o o (U o 1^ iZ! •M z n CZu2 . OS _ c CO CO CO CO CO CO CO CO 73 73 CO 00 73 (O CO •* o (U U u o 1) (U 0) 0) •^ z id 0) •"^ £ . 10 • P4 OT CO CO CO CO CO CO 73 CO CO 73 CO CO CO CO CO O s 0) 1) U s •« .s >< u .s o CO u d bJ] o d •Pi* o t d •M o • PN 03 b£ 1/1 d S B S U d d S o a o u ;s 4^ « d a o "3 bX) a d (/I o s -^ u u d a" « s G- fa a .d 1 *** bX) v • mm "d o o u d H u Z Table 5.28: Utility of Services Available on Websites of Airlines Under Study: Passenger Perceptions Web Site Usage FSC- FSC- LCC Interna Total Public Private (percent) tional (percent) (percent) (percent) (percent) Schedule 67.3 66.9 52.5 70.6 65.0 Seat Availability 64.3 55.6 52.5 52.9 58.0 Fares 60.8 62.7 70.0 52.9 62.2 On-line BooMng 45.0 47.3 53.8 29.4 45.6 Offers and 35.7 33.7 33.8 52.9 36.5 Promotions Frequent Flyer 24.6 24.3 11.3 47.1 24.6 Details Internet Auctions 14.0 14.2 20.0 7.8 14.4 Complaints / 13.5 10.1 8.8 11.8 11.3 Compliments e-Ticketing 25.1 37.9 41.3 45.1 34.6 Any Other 8.2 5.9 3.8 5.9 6.4 5.6.4 Results of Hypotheses Testing One-way ANOVA procedure at significance level of 0.05 was used to test the null hypotheses Hn, H12, H13 and H14. Null hypotheses Hn, Ho and HH were rejected where as hypotheses H12 could not be rejected. In case of Hn low mean scores were observed for international carriers and LCCs. Perhaps this can be attributed to restrictions on the part of international carriers in allowing passengers utilize the benefits of IT. While in case of LCCs, the lack of proper IT infrastructure appeared to be a major stumbling block. In case of H12, low mean scores were noticeable for all airlines. This could be due to low awareness regarding usage of IT in In-Flight Services like In-Flight Entertainment, role of IT in Catering, Communication etc. across the four categories 166 of airlines. The ANOVA results showed significant differences did not exist in the mean scores of perceptions of passengers of three categories of airlines regarding improvement in satisfaction levels vis-a-vis In-Flight Services due to use of IT. In case of Hi3, LCCs scored low as there is no mechanism to maintain customer loyalty or relationship. This should be interpreted in the light of the fact that LCCs practically do not offer any frequent flyer programmes. As such, they also scored low on Customer Support Services. This can be attributed to greater interest in numbers rather than satisfying and retaining existing customers. In case of HH, one way ANOVA results revealed that there were significant differences in the mean scores between the category of the airline and passenger perception that IT adds to passenger satisfaction (F=2.730, p<.05). Passengers expect higher usage of IT by LCC to cover up for the shortcomings of service in other areas. Mean scores and standard deviations for each group of respondents are given in Table 5.29. 167 1 T3 -o -o -« i< U V ca u u •<-< a ^o ^ « u *••- V CS ••7w» u •••* ^ •u^ z-ru 4> •'u^ d Pi »5 PSi oi t^ 00 m g 1—1 ^-H '^ i» o o o < d > o d d O o> c^ in o < (N '^ t^ m f^ -st; OS C--; r^ CO d ro (N m '^ ^ Tl- M I—' ^ rsi C^ o in o O ti d d d d < a > 4> o > _; '•w >r^ ,-H in o E u V lU V 0) •** •** •** •pu* "« •1u4 -w a u u R (0 u b cs fi « a • M A 1a3 'wm (S ca •D fl o .>, o > _o .^ o _^ o • •« 2 3 3 3 c bX) S u s ;• '-^ s &• s 'hi •44 re TI v PM PH « h PH PH «« In PH PH « h Pk PH « h H 1 1 1 1 d .2 < U hi h. u u u Si i^ U u u U 6> c« CZ5 CZ5 (» U {/J 05 U cc !/> U CNj (£< i^ ^u ;£< 1^ ^ 5u EIH| b h4 b^ (£< hJ 0) o £ re C ° « ^ ^ ao a U ^ w 00 H cd g •-H (U -H 1 U •_3 ti 1^ d) O e tin .^ a 'S '^ P 6fi « c;, U p 00 S t^ o p 00 S c« S^ VH u (u .2 u ci"S > > «^ ?r o =« ^ ^ O O A /-s O +3 w VH ^ ?, Q.'? ^ oD w p "eS > 2 o ^ '^ a •« ,+^ 00 i2 w >> •> E -2 "C _g ^ fl (D S V (U O fcH 00 ^ u =3 --^ .a 2 (u CFA was conducted using LISREL 8.5 to validate the relationship between observed and the latent variables (Exhibit 5.8). Exhibit 5.8: CFA 3 Factor IVIodel - Low Cost No Frills Model 0.98-* Bl 0.98-^ B2 0.99-^ B3 ¥fih)-l^J^ 0.98-^ B4 0.84— B5 0.78— Be 0.69— B' 0.36— B8 0.50— B9 0.99— BIO 0.97— Bll 0.94— B12 CIii-Squaie=179.78, (lf=51, P-vaIue=0.00000, RMSEA=0.073 IL Please refer to Table 4,3 for parameter description The three scales of FSS (5 items), IFS (3 items) and CSS (4 items) were simultaneously assessed by CFA. The overall results appeared to support the scales despite the significant Chi-Square statistics (Chi-Square= 179.779, dF=51, P- value=0.00, RMSEA=0.0733, NFI=0.705, CFI=0.770). Discriminant validity was evidenced by the inter-construct correlations that were significantly less than one (Anderson et al, 1988). The results of CFA suggested that the three dimensional conceptualization fitted the data for domestic airline passengers (Table 5.30). 169 Table 5.30: Summary of CFA Indices- Low Cost No Frills Model Goodness of Fit Statistics Critical Value Value Degrees of Freedom 51 Normal Theory Weighted Least Squares 179.779 Chi-Square Root Mean Square Error of <0.08 0.0733 Approximation (RMSEA) Normed Fit Index (NFI) >0.95 0.705 Non-Normed Fit Index (NNFI) >0.95 0.702 Comparative Fit Index (CFI) >0.90 0.770 Root Mean Square Residual (RMR) <0.10 0.0360 Standardized RMR <0.08 0.0652 Goodness of Fit Index (GFI) >0.90 0.940 Adjusted Goodness of Fit Index (AGFI) >0.90 0.908 5.7.2 Acceptability of Low Cost No Frills Model Chi square test for goodness of fit was significant for all measures (Table 5.31) except no frequent flyer programme. This implied that there were significant differences between the category of responses (Not acceptable, partially acceptable and acceptable) with respect to acceptability of Low Cost No Frills model. Significant relationship existed between respondents of different airline categories and their acceptability of more dependency on Internet for ticket sale, limited staff and cabin crew and no refiind policy (Table 5.31). The observations with respect to Low Cost No Frills Model are listed below: > Majority of passengers across the three categories of airlines approved the idea of single class flight. The concept of point-to-point service was not approved by majority of Legacy - Private carrier passengers. Majority of New and Legacy Carrier passengers approved of Internet as a major charmel for ticket sales, but did not like the idea of cut in staff strength as a consequence of this migration. Such a response may partly be attributed to apprehensions regarding deterioration in service quality on account of reduction in staff strength. > Increase in minimum reporting time was not acceptable to all the passengers. Service against payment, though acceptable to New Carrier passengers, was not a welcome idea. Acceptability of in-flight advertisements was low and the passengers were against any increase in baggage delivery time. 170 Table 5.31: Chi-Square Test: Acceptability of Low Cost No Frills Model Service Quality Goodness of Fit Relatedness with Parameters Primary Airline Chi- dF Sig. Pearson dF Sig. Square Value Value Value FSS Flight Support Services B2 Point to Point Service 233.287 2 0.000 7.100 6 0.312 B3 More dependency on 187.580 2 0.000 16.633 6 0.011 Internet for ticket sale. B4 Limited Staff & Cabin 33.873 2 0.000 14.228 6 0.027 Crew B5 Increase in Minimum 8.038 2 0.018 11.180 6 0.083 Reporting Time B8 Increase in Baggage 159.401 2 0.000 9.091 6 0.169 Delivery Time IFS In Flight Services Bl Single Class Flight 255.299 2 0.000 6.088 6 0.413 B6 Paid In-Flight Service 9.631 2 0.008 7.775 6 0.255 and Meals B7 In-Flight 7.503 2 0.023 7.496 6 0.277 Advertisements CSS Customer Support Services B9 Increase in Customer 174.127 2 0.000 3.337 6 0.765 Complaint Handling Time BIO No Frequent Flyer 5.516 2 0.063 3.139 6 0.791 Program Bll Company Web Site as 80.115 2 0.000 8.077 6 0.233 main point of contact B12 No Refund Policy 417.949 2 0.000 25.550 6 0.000 B13 Overall Model 223.427 2 0.000 11.495 6 0.074 Acceptable > Passengers were not ready to accept increase in complaint handling time as they generally expect prompt response from airlines. New Airline passengers demonstrated highest acceptability regarding company web-site as main point of contact, though they also expect an option of having face to face contact. Passengers are having strong reservations for no refund policy. > Overall passengers had high acceptability towards Low Cost Model. It was found to be highest for New Carrier passengers for whom price is the most important criteria and quality of service provided is not that important. It is lowest for Legacy - Private passengers who are conscious of the service provided during the flight and are willing to pay for quality service. Table 5.32 gives the perception of passengers towards acceptability of Low Cost No Frills model. 171 Table 5.32: Acceptability of Low Cost No Frills Model (Perceptions) Passenger Response FSC- FSC- LCC Interna Total Public Private (percent) tionai (percent) (percent) (percent) (percent) Point to Point Not Acceptable 8.2 13.0 11.3 15.7 IIJ Senlce Partially Acceptable 24.6 20.7 18.8 31.4 22.9 Acceptable 67.3 66.3 70.0 52.9 65.8 More Not Acceptable 17.0 13.0 5.0 3.9 12.1 dependency ou Partially Acceptable 26.9 29.0 21.3 19.6 25.9 Internet for ticket sale. Acceptable 56.1 58.0 73.8 76.5 62.0 Limited Staff & Not Acceptable 24.6 23.1 10.0 35.3 22.7 Cabin Crew Partially Acceptable 33.9 29.0 41.3 27.5 32.7 Acceptable 41.5 47.9 48.8 37.3 44.6 Increase in Not Acceptable 43.3 37.9 23.8 27.5 36.3 Minimum Partially Acceptable 31.6 36.7 43.8 41.2 36.5 Reporting Time Acceptable 25.1 25.4 32.5 31.4 27.2 Increase in Not Acceptable 43.3 37.9 23.8 27.5 36.3 Baggage Partially Acceptable 31.6 36.7 43.8 41.2 36.5 Deliveiy Time Acceptable 25.1 25.4 32.5 31.4 27.2 Single Class Not Acceptable 9.4 11.2 8.8 19.6 11.0 Fliglit Partially Acceptable 23.4 19.5 20.0 23.5 21.4 Acceptable 67.3 69.2 71.3 56.9 67.5 Paid In-Flight Not Acceptable 25.1 29.0 26.3 39.2 28.2 Senice and Partially Acceptable 35.1 30.2 27.5 35.3 32.1 Meals Acceptable 39.8 40.8 46.3 25.5 39.7 lu-Flight Not Acceptable 35.7 29.0 30.0 19.6 30.6 Advertisements PartiaUy Acceptable 26.9 30.2 28.8 43.1 30.1 Acceptable 37.4 40.8 41.3 37.3 39.3 Increase in Not Acceptable 35.7 29.0 30.0 19.6 30.6 Customer Partially Acceptable 26.9 30.2 28.8 43.1 30.1 Complaint Handling Time Acceptable 37.4 40.8 41.3 37.3 39.3 No Frequent Not Acceptable 37.4 42.0 33.8 37.3 38.4 Flyer Program Partially Acceptable 32.7 26.0 35.0 31.4 30.6 Acceptable 29.8 32.0 31.3 31.4 31.0 Company Web Not Acceptable 37.4 42.0 33.8 37.3 38.4 Site as main Partially Acceptable 32.7 26.0 35.0 31.4 30.6 point of contact Acceptable 29.8 32.0 31.3 31.4 31.0 No Refund Not Acceptable 81.9 79.3 81.3 51.0 77.5 Policy Partially Acceptable 11.1 16.0 12.5 31.4 15.3 Acceptable 7.0 4.7 6.3 17.6 7.2 Overall Model Not Acceptable 7.6 13.0 12.5 3.9 10.0 Acceptable Partially Acceptable 19.9 29.0 26.3 31.4 25.5 Acceptable 72.5 58.0 61.3 64.7 64.5 172 5.7.3 Results of Hypotheses Testing One-way ANOVA procedure was performed at significance level of 0.05 to measure the difference in acceptability of Low Cost Model across passengers of three categories of airlines. Mean scores and standard deviations for each group of respondents are given in Table 5.33. Results show a high level of acceptability across for FSC-Public and Inteniational Carrier passenger as they expect lower price for the quality of service provided to them. (F=2.900, p<0.05). Thus, the null hypothesis Hi8 was rejected. It was observed that differences in mean scores were significant for flight support service His (F=4.905, p<0.05). Except for LCCs, passengers of all carriers expressed reservation in reduction in quality of flight support services, especially, increase in reporting time and baggage delivery time. Thus, the null hypothesis His was rejected. In case of Hypotheses Hie and Hi7, significant differences did not exist in the mean scores of the opinion of the respondents across different categories of airlines. Thus these hypotheses could not be rejected. 173 (N o ON ly-l M O r- NO CO o lo fN 00 0 5^ o »—i 00 0 tJH ON fO NO ON ''t '"^ •^ oj < > o VO ON NO z U t^ IT) (N 0 < uo •—' m 0 o o >^ Q> d d (0 c K 0) w u c l-l 'V. _H -s^ NO (N % \D m >A) in O ^o r~; l-H ON •*- o ^ ^ in o i/5 (0 •; 3 (A > 0) V 00 lO 0\ This chapter first carries out the preliminary examination of data using descriptive analysis. Mean, Standard Deviation, Range, Skevraess and Kurtosis measures were analyzed for the sample. It then reports the demographic profile of the respondents - passengers and staff Instrument validity and reliability has been assessed through two steps procedure: preliminary assessment using EFA and confirmatory assessment using CFA. Consumer expectations versus perceptions have been examined. One of the most significant research findings relate to the area of measuring airlines' perceptions of consumers' expectations of service delivery, which had not been previously researched. The issues of impact of IT on service delivery and acceptability of low- cost-no-frills model were also discussed. The chapter brings together the qualitative and quantitative findings and discusses the most significant ones by comparing and contrasting them with the relevant literature. 175 CHAPTER 6: CONCLUSIONS, IMPLICATIONS AND DIRECTIONS FOR FUTURE RESEARCH 6.1 Conclusions 6.1.1 Service Quality in Airline Industry 6.1.2 Role of Information Technology in Service Delivery 6.1.3 Low Cost No Frills Model 6.2 Managerial Implications of the Research 6.2.1 Implication Related to Service Quality 6.2.2 Implications Related to Role of IT in Service Delivery 6.2.3 Implications Related to Low Cost No Frills Model 6.3 Directions for Future Research CHAPTER 6: CONCLUSIONS, IMPLICATIONS AND DIRECTIONS FOR FUTURE RESEARCH Chapter Overview This chapter presents an overview of the study's structure by setting out the salient points of the previous chapters. An attempt has been made by the researcher to summarize the contribution to knowledge that this study has made. Major findings as well as potential managerial implication of the study have also been discussed. In the concluding section, directions for future researchers have also been discussed. 6.1 Conclusions In conclusion, the current research to a considerable extent was able to achieve the stated objectives. The conclusions revolve around three key issues: service quality in airline industry, role of IT in service delivery and acceptability of low-cost no-frills airline service model in India. 6.1.1 Service Quality in Airline industry Analysis of data revealed that items for perception and gap loaded on four factors each. Thus, the "classical" five-dimensions of SERVQUAL could not be validated in case of domestic airlines in India. In the context of customer service vis-a-vis Full Service Carrier - Public Sector, Full Service Carrier - Private Sector, Low Cost Carriers and International Carriers, expectations were significantly high for tangibility - additional support service, reliability and responsiveness. Service quality perceptions were low for tangibility - flight and empathy, especially in case of Low Cost Carriers. While the Gap between perceptions and expectations were observed to be highest for Low Cost Carriers. Overall, reliability of service was an area of concern for passengers across all categories of airlines. ^ 176 ^\\'--" There was no difference between customers' expected service quality among different categories of airlines considered in the study. However, there was difference between customers' perceived service quality. As a result, gap was also observed between customers' perceived and expected service quality among different categories of airlines. It was evident that Tangibility (Support Service, Additional Support Service and Flight) and Reliability were significant drivers of customer service. Passengers expected airlines to ensure safe journey, offer support to mitigate problems due to critical incidents and particularly meet time commitments. 6.1.2 Role of Information Technology in Service Delivery Airlines in India are vying to outclass each other in the sky. They appear to be making sincere attempts at leveraging the power of IT to streamline internal information flows in order to collaborate and enrich customer experience. Increasing use of IT and enterprise applications has no doubt helped these companies offer better services to existing customers and attract new ones to their fold. There is growing realization that the success of airlines will be determined by cost reductions and productivity improvements, and IT is the key to achieving both. In general, passengers of all categories of airlines agreed that the use of IT in reservation, ticketing and check-in has led to enhanced customer satisfaction. But they were less enthusiastic in the context of use of IT in baggage handling and catering. In comparison to LCC, more passengers of FSC were using Internet to give their feedback to the airline management. Findings suggest that Internet is mainly being used for booking related activities, namely, flight schedule, seat availability, fares, booking and e-ticketing. Interestingly, LCC passengers were active users of Internet, and Internet based auctions of seats were quite popular with them. Further, it was observed that FSC were making greater use of IT for improving customer relations as compared to LCC. 177 6.1.3 Low Cost No Frills Model Findings demonstrate that the Low Cost Model has high acceptability in the Indian context. In fact, first time passengers preferred it most. For them price seemed to be the most important criteria as they were not aware of the differences in quality of service offered by various airlines. The acceptability of LCC Model was found to be lowest for FSC- Private passengers who are primarily price insensitive as they either are business travellers or belong to the sponsored category. They seem to be conscious of the service provided during the flight and are not averse to paying a premium for quality service. 6.2 Managerial implications of Research Prior to the present study, there have been only been two recorded studies (Solanki, 2002; Baisya 2004) relating to marketing and service quality in domestic airlines in India. But none of the studies focussed on the reasons for selection of airlines by consumers, rather they sought to identify the needs of the business customers. This study is the first systematic study that has made an attempt to explore the linkage between expectations and perceived performance relating to the importance of service quality in the selection of an airline. Findings of the study provide an insight into decision-making patterns of airline passengers with regard to various facets of service delivery. This study extends the basic understanding on the subject as it involved interaction with airline passengers and airline staff and compared their responses on similar dimensions. In this context, it needs to be pointed out that most of the previous studies made an attempt to address the issue of relationship between customer expectations and customer perceptions of service quality, but the unit delivering the service quality i.e. airline staff was strangely ignored. Thus, the present study is unique as it for the first time offers a peep into the perspective of service provider vis-a-vis customer's perceptions and expectations. 178 6.2.1 Implications Related to Service Quality This study provides practical implications for airline marketing managers. Findings suggest that dimensions of Tangibility viz. Support Service, Additional Support Service and Flight were significant drivers of customer service. Airline marketers should realize that improvements in these three factors would enhance passengers' repurchase intention and their recommendation to other passengers via positive word of mouth. In addition, airlines should embrace strategies to improve service quality such as meeting passengers' desired service levels, improving the quality of in-flight meal, solving service problems effectively and immediately, making convenient schedules for passengers, and preventing service outages from occurring. If properly handled, these steps will no doubt enhance airline image and result in retaining existing passengers and enticing new passengers. Reliability is one of the most important requirements of airline operations (Sultan et al 2000). Even a minor slip in reliability leads to the formation of a negative airline image. Therefore, domestic airlines should strive to keep a good safety record and on time performance in order to attract potential passengers. The study provides justification to the belief that differences exist in consumer perceptions and expectations based on airline categories. As already discussed, previous researchers had used the SERVQUAL model in countries other than India. However, the present study uses it for the firsttim e across airline categories in India. The study provides empirical evidence relating to differences that exist in expectations and perceptions of airline passengers and the same may significantly impact selection of service provider. It is to be noted that passengers have varying expectations and perceptions of service quality depending upon the demographic profile. The study identifies the three major focus areas for managerial intervention. FSC-Public passengers want staff to be more responsive at the time of critical incidents and want airline to procure modem aircrafts and meet time commitment. Interestingly, LCC passengers want airline to provide meals during the flight. International passengers were concerned about the high cost of airfare. Respondents, in general, expressed displeasure over problems due to critical incidents and airlines not meeting time commitment. 179 Senior passengers were found to be particular about airlines performing service right the first time and keeping the customer informed about time of service. New passengers with flying experience less than one year were concerned about the meal options provided by the airlines. Business class passengers desired a confident approach fi-om airline staff. While frequent flyers want improvement in baggage handling mechanism. Overall, passengers expect airlines to concentrate on their service during critical incidents and try to meet time commitment. Considering the excessive traffic at metro airports, meeting time commitment is going to be an issue till the time major airports are renovated. Baggage handling is another area where airlines need to improve. They need to improve reliability of services, responsiveness of staff and tangible support services. Table 6.1 gives top three areas where management needs to put extra efforts in order to meet customer's expectations. The findings exemplify that mere focus on perceived service quality is insufficient to develop long-term loyalty. Mediating effect of customer satisfaction also needs to be looked into. Passengers expect airline to ensure safe journey, and necessary support to mitigate problems due to critical incidents and meet time commitments. Thus, service managers should ensure that the performance on all components of delivered service is perceived as excellent by customers and also sustain high levels of satisfaction. In order to meet this objective, service staff must be well trained for keeping good relationship with customers and for addressing customers' enquires. As suggested from the measure of perceived service quality, besides the quality of interactions between service staff and customers, physical outcomes are also important and need to be well managed. 180 c/3 in E CO CO 0 1) E E E E E E S E crt 4> IZ) 3 CO CO 3 -4-4 .E c E 'E E 3 CO 3 3 E S 'E •4-* [3 0 -4^ [2 3 CO _1U 0 0 •4-» ca ^-» o 3 '0 '0 '0 '0 3 3 '0 <4H 3 0 0 B ,0 •4^ •o 0 >% e c S ,^ o ,0 "O B _o s s 0 R 0 0 .2 "a. a. '3? w 1 1 e .2 CO E >• a u 0 0 •4"4 u •^^ •^^ 0 V) es 5 CO 0 4> u u u Xi •B Ed •*.* b <: 0 CQ OH 0 d^ >> -W 1 u o a B Dll s uoi;Bt lnD30 s ii 0 .S R u en i- .£f a « < U a «: 0 was en tn en E Vi 'u E E |4-* E 0 s (0 3 .^ re en 'S -^^ 2! "(3 B on en en en en en en en 3 en 0 en en -M w 3 •M 4-» 4-4 4-4 4-> 4.H u < C cr 3 3 •3 3 3 3 3 0 3 4J 3 3 (cU (U u s V) !> •a '3 3 •g ^ 3 _-a 12 ."2 12 12 ;o s 2 60 12 2 B .^ o 0 '0 "u 0 '0 '0 '0 4.H "0 0 '0 U '5 'ji 3 ,3 .3 _3 en ,3 _3 _3 ^•M* • c•-1 • —c1 '•-^ • >-cH c • c•« .5 0 *z U-l •^^ R ^o -4-» O "rt •c3 "w .s u. "« 13 3 "« "3 3 13 3 3 3 '•4iJ c en 0 0 ,0 0 0 0 0 , ^ 'iu .y _u _o 2 _o Cd _o ^ PH [4-* '4-» '4-* "3 *4-* *4-» s E 0 'C o u 0 0 0 u 0 0 X3 0 0 CJ •| en Ofi 0 o 1 o o 0 0 0 0 0 0 0 0 cd 0 0 4-4 1 4.H -t-» •*-» 4-* •M 4-» 4-* 4-» • p^ s E c 00 4-» 4> o o 0 (U 0 B 1 B B >- >- 0 1/: 1 i» o B 0 B 0 • P4 B 1 1 o >> u M Examination of the data revealed that men and women differ significantly in terms of perceived usage of IT in domestic airlines. Young passengers expect higher usage of IT. Passengers with less flying experience did not understand and appreciate the benefits of IT in passenger services. Professionals, frequent flyers and international travelers were found to be more aware of usage of IT. Important business issues associated with online sales were lack of payment security, complexity of airline pricing models and infrastructure constraints. Results indicate that domestic airlines are unable to convert site tourists to buyers as only 25 - 40 percent of customers visit the website for e-ticketing. But overall, passenger agreed that service quality in domestic airlines has improved through use of IT. Table 6.2 provides the satisfaction level of passengers with usage of IT in service delivery based on demographic profile. 6.2.3 Implications Related to Low Cost No Frills Model FSC-Public passengers are most receptive to the idea of low cost no frills model as they are not satisfied with the value of service they get in return of the cost of service. Men and women differ significantly in terms of acceptability of low cost model in domestic airlines. Young passengers expect higher quality of service in air and are willing to pay the price for it, whereas senior citizens are fully in favour of getting value for their money. As a respondent advances in age, respect for money increases. There is no considerable difference in the response based on qualification. FSC-Private passengers value the service being offered in-flight and are reluctant to part with the benefits, even if it costs them more. People with high income are not in favour of low-cost no-frills model. Frequent flyers and business class passengers want comfortable journey and feel that low cost model does not meet their requirements. Overall, majority of passengers are in favour of low-cost no frill model. Table 6.3 gives the acceptability of low-cost no-frills model by the passengers based on demographic profile. 183 Table 6.2: Passenger Profile and Satisfaction vis-a-vis IT Deployment Passenger Profile NAND Agree Strongly Agree (percent) (percent) (percent) Airline FSC - Public 4.7 45.0 50.3 Category FSC - Private 6.5 39.6 53.8 LCC 17.5 40.0 42.5 International Carrier 15.7 35.3 49.0 Gender Male 6.9 40.7 52.4 Female 13.6 49.2 37.3 Age Less than 21 50.0 37.5 12.5 Group 21to40 6.3 41.8 51.9 41 to 60 9.2 43.3 47.5 Above 60 20.0 80.0 Highest Graduation or Below 12.8 40.4 46.8 Qualifi Post Graduation 10.5 42.0 47.5 cation Professional 2.4 42.7 54.9 Occupa- Self Employed 13.6 34.1 52.3 Tion Employed (Private Sector) 8.7 38.5 52.8 Employed (Govt/ Pub.Sector) 6.0 46.6 47.4 Students 3.3 56.7 40.0 Others 50.0 50.0 Annual Less than 0.5 Million 9.1 46.5 44.3 Income 0.5-1.0 Million 4.5 38.8 56.7 Bracket 1.0-2.0 Million 11.1 27.8 61.1 Above 2.0 MiUion 10.0 35.0 55.0 Since Less than 1 Year 31.6 36.8 31.6 how long 1 -5 Years 6.7 45.6 47.7 Flying 5-10 Years 12.0 32.0 56.0 More than 10 Years 3.8 42.7 53.4 Domestic 1-5 9.8 44.9 45.3 Flights in 6-10 5.3 41.5 53.2 lastl 10-20 8.3 31.3 60.4 Year Above 20 36.4 63.6 Class of Economy 7.8 42.1 50.1 Travel Business 9.5 38.1 52.4 Frequent No 9.4 44.1 46.5 Flyer Yes 4.5 37.3 58.2 Member Travel to No 10.0 42.0 48.0 Int'l Yes 5.9 41.8 52.3 Sector Overall percentage 7.9 41.9 50.2 NAND: Neither Agree Nor Disagree 184 Table 6.3: Passenger Profile and Satisfaction vis-a-vis Low Cost No Frills Model Passenger Profile No Maybe Yes Airline FSC - Public 7.6 19.9 72.5 Category FSC - Private 13.0 29.0 58.0 LCC 12.5 26.3 61.3 International Carrier 3.9 31.4 64.7 Gender Male 9.7 24.8 65.5 Female 11.8 29.4 58.8 Age Less than 21 22.2 22.2 55.6 Group 21 to 40 10.6 27.6 61.8 41 to 60 8.2 21.6 70.1 Above 60 100.0 Highest Graduation or Below 7.7 26.9 65.4 Qualifi Post Graduation 10.3 27.7 62.0 cation Professional 10.9 22.4 66.7 Occupa- Self Employed 10.9 13.0 76.1 Tion Employed (Private Sector) 11.6 29.3 59.0 Employed (Govt/ Pub.Sector) 9.5 21.4 69.0 Students 2.9 34.3 62.9 Others 13.3 86.7 Annual Less than 0.5 Million 8.7 25.2 66.1 Income 0.5-1.0 Million 11.8 21.5 66.7 Bracket 1.0 - 2.0 Million 8.5 34.0 57.4 Above 2.0 Million 13.2 31.6 55.3 Since Less than 1 Year 8.7 21.7 69.6 how long 1 - 5 Years 10.3 25.0 64.7 Flying 5-10 Years 12.2 25.6 62.2 More than 10 Years 8.4 26.6 64.9 Domestic 1-5 6.8 25.5 67.6 Flights in 6-10 11.7 22.3 66.0 lastl 10-20 17.0 34.0 49.1 Year Above 20 18.9 21.6 59.5 Class of Economy 9.2 25.6 65.2 Travel Business 23.1 23.1 53.8 Frequent No 8.2 26.1 65.7 Flyer Yes 13.7 24.2 62.1 Member Travel to No 8.5 22.0 69.5 Int'l Yes 11.1 28.0 60.9 Sector Overall percentage 10.0 25.5 64.5 185 6.3 Directions for Future Research Based on the study, the following directions for future research may be pointed out: > Research may be carried out to unravel the complex mechanism of airline operations and its impact on service delivery. > The model proposed in the present research needs to be further tested utilizing more variables and a larger sample. Future research efforts need to focus on additional decision variables pertaining to prediction of service quality. > Future researchers can expand the scope of study to include smaller cities for data collection and study the difference in GAP between perception and expectation with respect to service quality of metro respondents and smaller city respondents > The study assumed that the respondents were all individual airline customers whose individual perceptions and expectations relating to service quality controlled the decision regarding primary airline, not taking into account possible impact of company policy or family influence. Future studies may also consider these factors in their analysis. > IT implementation in various business scenarios merits further investigation. > The highly competitive nature of the industry and the pace of changes necessitate regular research in this area so that the stakeholders can feel the pulse of the market. 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Indian Airlines & Alliance Air Jet Airways Sahara Airlines Low Cost Carriers This is the Primary Airline for rest of the questionnaire. B. LCC Model of Customer Service Please indicate (V) your opinion in case the following alteration in services leads to lower prices of tickets:- Customer Services Acceptable Partially Not Acceptable Acceptable Bl Single Class Flight B2 Point to Point Service (Limited Destinations but faster connectivity between stations) B3 More dependency on Internet for ticket sale. Limited number of Travel Agents and Sales Office. B4 Limited Staff & Cabin Crew B5 Increase in Minimum Reporting Time (By 15 Minutes) B6 Paid In-Flight Service and Meals B7 In-Flight Advertisements B8 Increase in Baggage Delivery Time (By 15 Minutes) B9 Increase in Customer Complaint Handling Time BIO No Frequent Flyer Program Bll Company Web Site as main point of contact B12 No Refund Policy B13. Will you continue flying your primary airline if the above alterations are made in customer services: Yes No Maybe B14. Most important reason (Only One) for flying with primary airline :- B15. Private Airlines generally give better service than National Airline :- Strongly Agree Agree Neither Agree nor Disagree Disagree | | Strongly Disagree C. Information Technology Based Service Offerings CI. Please select the improvement in satisfaction level as a result of use of Information Technology by Primary Airline. Customer Services Improvement in Customer Satisfaction Level Yes Some what Negligible No Improvement A Reservation and Ticketing B Check-in and Boarding C Baggage Handling D In-Flight Service and Facilities E Catering / Meals F Customer Complaint Handling G Customer Relationship Management H Frequent Flyer Program C2. Use of IT by Domestic Airlines add to the passenger services :- Strongly Agree Agree Neither Agree nor Disagree Disagree Strongly Disagree 215 C3. Please select the reasons for accessing primary airline's web site / call center. (You may select more than 1 option) Schedule Seat Availability Fares Online Booking Offers and Promotions Frequent Flyer Details Internet Auctions Complaints/Compliments e-Ticketing Any Other D. Domestic Flights Detail Dl. Since how long have you been flying > First Flight 1 - 5 Years 5-10 Years More than 10 Years D2. You mainly classify your air travel in following categories. (You may select more than 1 option): Business Personal Pleasure Emergency D3. Please select the reasons for travel by Air. (You may select more than 1 option) :- To save travel time For fun For comfort while traveling Suits my Image Any other _ D4. Who finances your air travel (You may select more than 1 option) :- Self Your Employer Any Other _ D5. You mainly travel in which class: Business / Club Economy D6. Have you flown to international sector:- Yes No D7. Number of domestic Flights in last 1 year :- 1-5 6 to 10 10 to 20 Above 20 D8. Duration of domestic air travel (most of the times):- Less than 2 Hours 2-5 Hours More than 5 Hours D9. Are you a frequent flyer member of primary airline :- Yes No E. Please indicate (V) your opinion regarding your primary airline on 7 point scale. (1 = Strongly Disagree, 2 = Disagree, 3 = Moderately Disagree, 4 = Neither Agree Nor Disagree, 5 = Moderately Agree, 6=A gree, 7 = Strongly Agree). El You will continue flying your primary airline Dl D2 D3 D4 D5 D6 D7 E2 You will recommend your primary airline to your Dl D2 D3 D4 D5 D6 D7 friends and family F. Demographic Profile Fl, Your Gender : Male Female F2. Your highest qualification : Matriculation or below Graduation Post Graduation Professional F3. Your age group : Less than 2l| I 21 to 40 I I 41 to 60 Above 60 F4. What is your occupation? ' ' Self-Employed (Own Business) Employed (Private Sector) Employed (Govt/Public Sector) Politician Student Any Others F5. What is your annual income bracket (in Rs. }T Less than 5 Lakhs 5 to 10 Lakhs 10 to 20 Lakhs 20 to 50 Lakhs Above 50 Lakhs F6. Your nationality :- Indian SAARC Country (except India) Rest of World 216 G. Please rank your expectations and perceptions about the customer service being provided by primary airline on 7 point scale. (1 = Strongly Disagree, 2 = Disagree, 3 = Moderately Disagree, 4 = Neither Agree Nor Disagree, 5 = Moderately Agree, 6=Agree, 7 = Strongly Agree). EXPECTATIONS PERCEPTIONS Please rank the extent to which you think Domestic Please rank the extent to which you think Airline should possess following features. Primary Airline possess following features. Strongly Strongly Strongly Strongly Disagree N A N D Agree Disagree N A N D Agree Gl Domestic Airline should have visually appealing Primary Airline has visually appealing physical facilities (e.g. Sales Office, Check-in- physical facilities. Counters, Lounges etc.). Dl D2 D3 D4 D5 D6 D7 Dl D2 D3 04 D5 06 D7 G2 Domestic Airline should have vast sales and support Primary Airline has vast sales and support network. network. Dl 02 D3 D4 D5 D6 07 Dl 02 D3 D4 05 D6 07 G3 Domestic Airline should cover vast network of Primary Airline covers vast network of destinations. destinations. Dl D2 D3 D4 D5 D6 D7 Dl D2 D3 D4 05 D6 07 G4 Domestic Airline should provide economical air fare Primary Airline provides economical air fare and discount schemes. and discount schemes. Dl D2 D3 D4 D5 D6 D7 Dl D2 03 D4 D5 06 D7 GS Domestic Airline should also use web-site / call Primary Airline use web-site / call center to center to provide communication and information to provide communication and information to the passengers. the passengers. Dl D2 D3 D4 D5 D6 D7 Dl D2 D3 D4 D5 D6 D7 G6 Domestic Airline should have modem aircraft with Primary Airline has modem aircraft with up- up-to-date facilities (e.g. comfortable seats, safety to-date facilities. features, low noise, lavatories etc.). Dl D2 D3 D4 D5 D6 D7 Dl D2 D3 04 D5 D6 D7 G7 Domestic Airline's staff should be neat well dressed Primary Airline's staff is neat, well dressed and visually appealing. and visually appealing. Dl D2 D3 D4 D5 D6 D7 Dl D2 D3 04 OS D6 07 G8 Domestic Airline should provide seat in flight of Primary Airline provides seat in flight of choice. choice. Dl D2 D3 D4 D5 D6 D7 Dl 02 D3 D4 D5 06 D7 G9 Domestic Airline should provide hassle free check-in Primary Airline provides hassle free check-in and boarding procedure. and boarding procedure. Dl D2 D3 D4 D5 D6 D7 Dl 02 D3 D4 D5 D6 D7 GIO Domestic Airline should provide efficient baggage Primary Airline provides efficient baggage handling mechanism. handling mechanism. Dl D2 D3 D4 D5 D6 D7 Dl D2 D3 D4 D5 06 D7 Gil Domestic Airline should provide excellent quality Primary Airline provides excellent quality in in-flight services (e.g. in-flight announcement, flight services. security advisory, on-board entertainment, passenger service etc.). Dl D2 D3 D4 D5 D6 07 Dl D2 03 D4 D5 D6 07 G12 Domestic Airline should provide multiple meal Primary Airline provides multiple meal options of high quality. options of high quality. Dl 02 D3 D4 D5 D6 D7 Dl D2 D3 D4 05 D6 07 G13 When a customer has a special need (e.g. children, When a customer has a special need. Primary elders and handicapped), Domestic Airline should Airline shows a sincere interest in solving it. show a sincere interest in solving it. Dl D2 D3 D4 D5 06 07 Dl D2 D3 D4 D5 D6 D7 217 EJfiPECTATIONS PERCEPTIONS G14 Domestic Airline should show a sincere effort in Primary Airline shows a sincere effort in solving solving problems to customers due to critical problems to customers due to critical incidents. incidents (e.g. delays, cancelled flights, delayed/damaged baggage, overbookings etc.). Dl 02 03 D4 OS D6 07 Dl D2 D3 04 OS 06 D7 G15 Domestic Airline should have staff who gives Primary Airline's staff gives personal attenfion to customer personal attention. customer. Ol 02 03 04 D5 06 D7 Dl 02 03 04 OS 06 D7 G16 When Domestic Airline promises to do something When Primary Airline promises to do something by a by a certain time, they should do so (e.g. follow certain fime, they do so. schedule, complaint redressal, baggage delivery). 01 02 03 04 OS 06 07 01 02 D3 D4 OS 06 07 G17 Domestic Airline should keep error free records Primary Airline keeps error free records. (e.g. PNR, tickets, frequent flyerdetail s etc.). 01 02 ' 03 04 OS 06 07 01 02 D3 D4 OS 06 07 G18 Domestic Airline should have customer's best Primary Airline has customer's best interest at heart. interest at heart. 01 02 03 04 OS 06 07 01 D2 03 D4 OS D6 07 G19 The staff of Domestic Airline should give prompt The staff of Primary Airline gives prompt service to service to customers. customers. 01 02 03 04 OS 06 07 01 02 03 D4 OS 06 07 G20 The staff of Domestic Airline should always be The staff of Primary Airline is always willing to help the willing to help the customers. customers. 01 02 03 04 OS 06 07 01 02 03 04 OS 06 07 G21 The staff of Domestic Airline should understand The staff of Primary Airline understands the specific the specific needs of the customers. needs of the customers. 01 02 03 D4 OS 06 07 01 D2 D3 04 OS D6 D7 G22 The behaviour of staff of Domestic Airline should The behaviour of staff of Primary Airline instills instill confidence in their customers. confidence in their customers. Dl 02 03 04 OS 06 07 01 02 03 04 OS 06 D7 G23 Customers of Domestic Airline should feel safe Customers of Primary Airline feel safe about the plane about the plane and facilities during the journey. and facilities during the journey. 01 D2 03 04 OS 06 07 01 02 D3 04 OS D6 07 G24 The staff of Domestic Airline should be Primary Airline's staff is consistently courteous with consistently courteous with customers. customers. 01 02 03 04 OS 06 07 Dl 02 03 D4 OS D6 07 G25 The staff of Domestic Airline should have the The staff of Primary Airline has the knowledge to knowledge to answer customers' questions. answer customers' questions. 01 02 03 04 OS 06 07 Dl 02 D3 D4 OS 06 07 G26 Domestic Airline should give each customer Primary Airline gives each customer individual individual attention. attention. 01 D2 03 04 OS 06 07 01 02 03 04 OS 06 07 G27 Domestic Airline should perform the service right Primary Airline performs the service right the firsttime . the first time. 01 02 03 04 OS 06 07 Dl D2 03 D4 OS 06 07 G28 Domestic Airline should keep customers informed Primary Airline keeps customers informed about when about when services will be performed. services will be performed. 01 02 D3 04 OS 06 07 Dl 02 D3 D4 OS 06 07 G29 The staff of Domestic Airline should never be too The staff of Primary Airiine is never too busy to respond busy to respond to customers' request. to customers' request. 01 02 03 04 OS 06 07 01 02 D3 D4 OS 06 07 G30 Domesfic Airline should have convenient flight Primary Airiine has convenient flight schedules. schedules. < , 01 02 03 04 OS 06 07 Dl D2 03 04 OS 06 07 G31 Overall, Domestic Airline should satisfy customer's Overall, Primary Airiine satisfy customers' needs. needs. 01 02 03 04 OS 06 07 01 02 03 D4 OS 06 07 THANK YOU FOR YOUR TIME AND COOPERATION 218 APPENDIX 2: AIRLINE QUESTIONNAIRE Dear Sir or Madam: I am carrying out a doctoral level business administration researcli on Customer Services in Domestic Airlines in India. As a part of this research study, a survey is being conducted to obtain Airline's view on the subject. You can help me by taking a few moments to complete this questionnaire. At no stage will I seek or disclose your identity. Thank you for your assistance. A. Please select the airline, which you are representing: Indian Airlines & Alliance Air Jet Airways Sahara Airlines Low Cost Carriers (Please Specify) B. Please indicate ( V) your opinion in case the following alteration in services leads to lower prices of tickets :- Customer Services Acceptable Partially Not Acceptable Acceptable Bl Single Class Flight B2 Point to Point Service (Limited Destinations but faster connectivity between stations) B3 More dependency on Internet for ticket sale. Limited number of Travel Agents and Sales Office. B4 Limited Staff & Cabin Crew B5 Increase in Minimum Reporting Time (By J 5 Minutes) B6 Paid In-Flight Service and Meals B7 In-Flight Advertisements B8 Increase in Baggage Delivery Time (By 15 Minutes) B9 Increase in Customer Complaint Handling Time BIO No Frequent Flyer Program Bll Company Web Site as main point of contact B12 No Refijnd Policy C. Information Technology Usage CI. Please select the improvement in satisfaction level of customer as a result of use of Information Technology by your airline. Customer Services Improvement in Customer Satisfaction Level Yes Somewhat Negligible No Improvement A Reservation and Ticketing B Check-in and Boarding C Baggage Handling D In-Flight Service and Facilities E Catering / Meals F Customer Complaint Handling G Customer Relationship Management H Frequent Flyer Program C2. Use of IT by Domestic Airlines add to the passenger services :- Strongly Agree Agree Neither Agree nor Disagree Disagree Strongly Disagree C3. What facilities are provided to the passenger at airline's web site (You may select more than I option) Schedule Seat Availability Fares Online Booking Offers and Promotions Frequent Flyer Details Internet Auctions Complaints/Compl iments e-Ticketing Any Other 219 D. Outsourcing of Customer Services Please identify the level of outsourcing in customer services. Also select the improvement in satisfaction level of customer as a result of outsourcing of the service. Customer Services Level of Outsourcing Improvement in Customer Satisfaction Level Full Partially Planning No Yes No Some Not Stage Plans what Applicable Dl Reservation and Ticketing D2 Check-in and Boarding D3 Baggage Handling D4 Cabin Cleanliness D5 Catering D6 Customer Complaint Handling D7 Customer Relationship Management D8 Frequent Flyer Program D9 Company Web Site Maintenance E. Any Other Suggestions / Remarks regarding Customer Service Dimension of your Airline F. Demographic Profile FL Your Gender: Male Female F2. Your highest qualification : Matriculation or below Graduation Post Graduation Professional F3. What age group aie you in ? Less than 30 | | 30 to 40 \ZI] 40 to 50 Above 50 F4. Since how long have you been in the present Airline :- Less than 1 Year | | 1 - 5 Years | | 5-10 Years More than 10 Years F5. What is your functional area :- Passenger Services | | In Flight Services General Management^ Any Other (Please Specify) F6. What is your level in the organisation? Staff rn Officer Junior Management | | Middle Management B Top Management F7. How many staff reports to you :- LessthanS |^ 5-10 • 10-50 I I More than 50 220 G. Please rank your expectations and perceptions about the customer service being provided by your airline on 7 point scale. (1 = Strongly Disagree, 2 = Disagree, 3 = Moderately Disagree, 4 = Neither Agree Nor Disagree, 5 = Moderately Agree, 6=Agree, 7 = Strongly Agree). EXPECTATIONS PERCEPTIONS Please rank the extent to which you think Domestic Please rank the extent to which you think Airline should possess following features. your Airline possess following features. Strongly Strongly Strongly Strongly Disagree N A N D Agree Disagree N A N D Agree Gl Domestic Airline should have visually appealing Your Airline has visually appealing physical physical facilities (e.g. Sales Office, Check-in- facilities. Counters, Lounges etc.). •1 D2 D3 D4 D5 D6 D7 Ol 02 03 04 OS 06 07 G2 Domestic Airline should have vast sales and support Your Airline has vast sales and support network. network. Dl 02 D3 D4 D5 D6 07 Ol 02 03 04 OS 06 07 G3 Domestic Airline should cover vast network of Your Airline covers vast network of destinations. destinations. Ol 02 03 04 OS 06 07 Ol 02 03 04 OS 06 07 G4 Domestic Airline should provide economical air fare Your Airline provides economical air fare and discount schemes. and discount schemes. Ol 02 03 04 OS 06 D7 Ol 02 03 04 OS 06 07 G5 Domestic Airline should also use web-site / call Your Airline use web-site / call center to center to provide communication and information to provide communication and information to the passengers. the passengers.. Ol 02 03 04 OS 06 07 Dl 02 03 04 OS 06 07 G6 Domestic Airline should have modem aircraft with Your Airline has modem aircraft with up-to- up-to-date facilities (e.g. comfortable seats, safety date facilities. features, low noise, lavatories etc.). Ol 02 03 04 OS 06 07 Ol 02 03 04 OS 06 07 G7 Domestic Airline's staff should be neat well dressed Your Airline's staff is neat, well dressed and and visually appealing. visually appealing. Ol D2 03 04 OS 06 07 Ol 02 03 04 OS 06 07 G8 Domestic Airline should provide seat in flight of Your Airline provides seat in flight of choice. choice. Ol 02 03 04 OS 06 07 Ol 02 03 04 OS 06 07 G9 Domestic Airline should provide hassle free check-in Your Airline provides hassle free check-in and boarding procedure. and boarding procedure. Ol D2 03 04 OS 06 07 Ol 02 03 04 OS 06 07 GIO Domestic Airline should provide efficient baggage Your Airline provides efficient baggage handling mechanism. handling mechanism. Ol 02 03 04 OS D6 07 Ol 02 03 04 OS 06 07 Gil Domestic Airline should provide excellent quality Your Airline provides excellent quality in in-flight services (e.g. in-flight announcement, flight services. security advisory, on-board entertainment, passenger service etc.). Ol 02 D3 D4 OS 06 07 Ol D2 03 04 OS 06 07 G12 Domestic Airline should provide multiple meal Your Airline provides multiple meal options options of high quality. of high quality. Ol 02 03 04 OS 06 07 Ol 02 03 04 OS 06 07 G13 When a customer has a special need (e.g. children, When a customer has a special need, your elders and handicapped), Domestic Airline should Airline shows a sincere interest in solving it. show a sincere interest in solving it. Ol 02 03 04 OS D6 07 Dl 02 D3 04 OS 06 D7 221 EXPECTATIONS PERCEPTIONS G14 Domestic Airline should show a sincere effort in solving Your Airline shows a sincere effort in solving problems to customers due to critical incidents (e.g. delays, problems to customers due to critical incidents. cancelled flights, delayed/damaged baggage, overbookings etc.). ai D2 D3 04 as D6 07 Dl 02 D3 04 OS 06 D7 G15 Domestic Airline should have staff who gives customer Your Airline's staff gives personal attention to personal attention. customer. Dl D2 D3 D4 05 06 D7 Ol D2 03 D4 OS D6 07 G16 When Domestic Airline promises to do something by a When your Airline promises to do something certain time, they should do so (e.g. follow schedule, by a certain time, they do so. complaint redressal, baggage delivery). Dl D2 03 D4 OS D6 07 Ol D2 03 D4 DS D6 07 017 Domestic Airline should keep error free records (e.g. PNR, Your Airline keeps error freerecords . tickets, frequent flyer details etc.). Dl D2 D3 D4 D5 D6 D7 Dl D2 03 D4 DS 06 D7 G18 Domestic Airline should have customer's best interest at Your Airline has customer's best interest at heart. heart. Dl D2 03 D4 OS 06 D7 Ol 02 D3 D4 DS D6 07 G19 The staff of Domestic Airline should give prompt service to The staff of your Airline gives prompt service customers. to customers. Dl D2 D3 D4 OS D6 D7 Dl D2 03 D4 OS 06 D7 G20 The staff of Domestic Airline should always be willing to The staff of your Airline is always willing to help the customers. help the customers. Dl D2 03 04 OS D6 D7 Ol D2 D3 04 DS D6 D7 G21 The staff of Domestic Airline should understand the specific The staff of your Airline understands the needs of the customers. specific needs of the customers. Dl D2 D3 D4 D5 D6 D7 Dl D2 03 D4 DS D6 07 G22 The behaviour of staff of Domestic Airline should instill The behaviour of staff of your Airline instills confidence in their customers. confidence in their customers. Dl 02 D3 D4 OS D6 07 Ol D2 03 04 OS D6 07 G23 Customers of Domestic AiHine should feel safe about the Customers of your Airline feel safe about the plane and facilities during the journey. plane and facilities during the journey. Dl D2 D3 D4 OS D6 D7 Dl 02 D3 D4 OS 06 D7 G24 The staff of Domestic Airline should be consistently Your Airline's staff is consistently courteous courteous with customers. with customers. Dl 02 D3 D4 D5 D6 D7 Dl D2 D3 04 OS 06 07 G25 The staff of Domestic Airline should have the knowledge to The staff of your Airline has the knowledge to answer customers' questions. answer customers' questions. Dl D2 D3 D4 OS 06 D7 Ol D2 03 D4 D5 06 D7 G26 Domestic Airline should give each customer individual Your Airline gives each customer individual attention. attention. Dl D2 03 04 D5 D6 D7 Ol D2 03 D4 OS D6 07 G27 Domestic Airlineshould perfomi the service right the first Your Airline performs the service right the first time. time. Dl D2 03 D4 D5 06 D7 Ol D2 D3 04 DS D6 D7 G28 Domestic Airline should keep customers informed about Your Airline keeps customers informed about when services will be performed. when services will be performed. Dl D2 D3 D4 OS 06 07 Dl 02 D3 D4 DS D6 D7 G29 The staff of Domestic Airline should never be too busy to The staff of your Airline is never too busy to respond to customers' request. respond to customers' request. Dl D2 03 D4 DS D6 D7 Dl D2 D3 D4 OS D6 D7 G30 Domestic Airline should have convenient flight schedules. Your Airline has convenient flight schedules. Dl D2 D3 04 D5 06 07 Ol 02 D3 D4 DS 06 07 G31 Overall, Domestic Airline should satisfy customer's needs. Overall, your Airline satisfy customers' needs. Dl 02 D3 D4 05 D6 D7 Dl D2 D3 D4 OS D6 D7 THANK YOU FOR YOUR TIME AND COOPERATION 222 APPENDIX 3: QUALITY SERVICE AUDIT QUESTIONNAIRE Gap 1 (Consumer Expectation - Management Perception Gap) Knowledge of customer's expectations to managers responsible for customer service Al Do you undertake any market research in your company? Yes No No Idea A2 If you have undertaken market research, have you utilized the findings? Yes No Partially No Idea A3 Do your managers regularly interact with customers? Yes No Partially No Idea A4 Do your managers ensure information is given to all employees at all levels? Yes No Partially No Idea A5 Do your levels of management inhibit communication with customers? Yes No Partially No Idea Gap 2 (Management Perception - Service Quality Specification Gap) Suitable and usable service quality standards set by the Company Bl Is service quality viewed as a strategic goal in your company? Yes No Partially No Idea B2 Are resources committed to improve service quality? Yes No Partially No Idea B3 Do internal programs exist to improve service quality? Yes No Partially No Idea B4 Are managers who improve customer service quality more likely to be rewarded than other managers? Yes No Partially No Idea B5 Does the company emphasize sales goals as much or more than it does customer service? Yes No Partially No Idea B6 Are upper and middle managers committed to providing quality customer service? Yes No Partially No Idea B7 Does the company have the capabilities to meet customer requirements for service? Yes No Partially No Idea B8 Can customer expectations be met without hindering financial performance? Yes No Partially No Idea B9 Do existing operating systems enable customer expectations to be met? Yes No Partially No Idea BIO Are resources and personnel available to deliver customers' desired level of service? Yes No Partially No Idea Bl 1 Does management change policies and procedures to meet the needs of customers? Yes No Partially No Idea B12Is automation used to achieve consistency in customer service? Yes No Partially No Idea B13 Are programs in place to improve operating procedures to deliver consistent service? Yes No Partially No Idea B14 Is there a formal process in place to set the quality of service goals for employees? Yes No Partially No Idea B15 Does the company have clear goals for customer service? Yes No Partially No Idea B16 Does the company measure its performance against these goals? Yes No Partially No Idea B17 Are service-quality standards based on customers', not company, standards?_ Yes I No I 1 Partially | | No Idea 223 Gap 3 (Service Quality specification - service delivery Gap) Incentives for employees to meet service quality standards C1 Do your employees have the proper training to perform their jobs adequately? Yes No Partially No Idea C2 Are there differing expectations of service levels between managers and customers? Yes No Partially No Idea C3 Are your employees overwhelmed with the volume of work to be completed to meet customer demands? Yes No Partially No Idea C4 Are your employees expected to cross-sell services in inappropriate situations? For example, is the employee supposed to "sell" other products while providing service? Yes No Partially No Idea C5 Does your company hire qualified people and does management devote sufficient time and resources to hiring and selecting employees? Yes No Partially No Idea C6 Are employees given the tools and equipment needed to perform their jobs and is the technology reliable? Yes No Partially No Idea C7 Do your employees know what aspects of their jobs will be stressed in performance evaluations? Yes No Partially No Idea C8 Are employees evaluated on how well they interact with customers? Yes No Partially No Idea C9 Are employees who serve customers best more likely to be rewarded financially or through career advancement and/or recognition? Yes No Partially No Idea CIO Are your employees empowered to deliver service? Yes No Partially No Idea C11 Do employees spend time resolving problems that they have little control over? Yes No Partially No Idea CI2 Are employees given the fi-ee^om to make decisions to satisfy customers' needs? Yes No Partially No Idea CI 3 Are employees encouraged to learn new ways to better serve their customers? Yes No Partially No Idea CI4 Are employees required to get approval from other departments before delivering service to customers? Yes No Partially No Idea CI 5 Do customer-contact staff cooperate with rather than compete against other employees? Yes No Partially No Idea CI6 Are employees encouraged to work together to provide customer service? Yes No Partially No Idea Gap 4 (Service Delivery - External Communications Gap) Promises in advertising and public relations that match true delivered service quality levels DI Does your company have adequate horizontal communication within and across departments (operations, marketing, and human resources) and branches? Yes No Partially No Idea D2 Do customer contact staff have input in the planning and execution of advertising? Yes No Partially No Idea D3 Are customer contact staff aware of external communications aimed at customers before it "hits the streets"? Yes No Partially No Idea D4 Does the sales force communicate with customer contact staff to discuss the level of service that can be promised to customers? Yes No Partially No Idea D5 Does your company's external communications accurately reflect what customers receive in the service encounter? Yes \~^ I No I I Partially I ~~] No Idea 224 APPENDIX 4: STRUCTURAL EQUATION MODELING DEFINITIONS Structural Equation Modeling (SEM): SEM is a powerful statistical technique that combines the measurement model (confirmatory factor analysis) and the structural model (regression or path analysis) into a simultaneous statistical test. Measurement Model: Measurement model estimates the unidimensionality, reliability and validity of each construct. Structural Model: Structural model involves estimating the relation between independent (exogenous) and dependent (endogenous) variables. LISREL: This is a Windows application for SEM developed by K. Joreskog & D. S6rbom, Scientific Software International Inc (SSI). Maximum Likelihood Estimation method (MLE): There are various methods available in SEM. If the data are continuous and sample size is not very large, then the MLE method is recommended. The ML estimates are obtained by means of an iterative procedure that minimizes a particular fit function by successively improving the parameter estimates. Standardized Residual: A residual is an observed minus a fitted covariance (variance). A standardized residual is a residual divided by its estimated standard error. There are such residuals for every pair of observed variables. Standardized residuals provide a "statistical" metric forjudging the size of a residual. They should have a value of <2.58 Factor structure: It is a term used to collectively refer to the entire set of pattern coefficients (factor loadings) in a model. Item Loadings/Lambdas: The standardized parameter estimates {factor pattern coefficients, validity coefficients or parameter estimates) often referred to as the Lambdas are the loadings associated with the arrows firom latent variables to their respective indicator variables. T-values: They are examined as they are independent of units of measurement. If t- values are all significant at the p<0.05 level, it indicates that each item is significantly related to its specified construct. Communalities: These are the squared factor loadings for a variable. The communality measures the percent of variance in a given variable explained by its latent variable (factor) and may be interpreted as the reliability of the indicator. A recommended value is more than 0.50. Fit Indices Measures of fit are an integral component of structural equation modeling (Kenny & McCoach, 2003; Schreiber et ai, 2006). Fit indexes quantify the degree of correspondence between a hypothesized latent variable model and the data (Hu & Rentier, 1995,1999). 225 The Root Mean Square Error of Approximation (RMSEA): This index measures the discrepancy between the observed and estimated covariance matrices per degree of freedom. The RMSEA measures the discrepancy in terms of the population and not the sample. Thus, the value of this fit index is expected to better approximate or estimate the population and not be affected by sample size. Again, values run on a continuum from 0 to 1, with values falling between 0.06 to 0.08 deemed as acceptable. Chi-square: The chi-square test is a measure of overall fit of the model to the data. If the chi-square value is statistically significant p< .000), it indicates that the model does not fit the data. Goodness-of-fit Index: The Goodness-of-Fit Index (GFI) is another indication of how well the model fits the data. It should be greater than 0.90. To adjust for model parsimony, an Adjusted Goodness-of-Fit Index (AGFI) is calculated which should exceed 0.90. The GFI and AGFI do not depend on sample size explicitly and measure how much better the model fits as compared to no model at all. Normed Fit Index (NFI): It is used to examine the proportion of total variance accounted for by a model. An acceptable value for the NFI is 0.90 Non-Normed Fit Index (NNFI): It compares a proposed model's fit to a nested baseline or null model. Value of 0.90 or greater is acceptable. Parsimony Normed Fit Index (PNFI): It measures how much better the model fits as compared to a baseline model, usually the independence model. It takes parsimony (degrees of freedom) into account. Parsimonious Goodness of Fit Index (PGFI):); It also measures how much better the model fits as compared to a baseline model, usually the independence model. Parsimony Fit Index (PFI): It reflects the amount of covariance explained by a model when its number of parameters is taken into account. That is, if the same amount of construct covariance is explained by two models, the less complex of the two models will have a higher PFI value. PFI values over 0.60 are considered acceptable Comparative Fit Index (CFI): It is as a noncentrality parameter-based index helps to overcome the limitation of sample size effects. This index ranges from 0 to 1, wdth 0.90 or greater representing an acceptable fit. CFI is similar to the NFI, except that it overcomes the difficulties associated with sample size Akaike's Information Criterion (AIC) and CAIC: A number of measures of fit have been proposed that take parsimony (in the sense of as few parameters as possible) as well as fit into account. These approaches try to deal with this problem by constructing a measure which ideally first decreases as parameters are added and then has a turning point such that it takes its smallest value for the best' model and then increases when further parameters are added. The Akaike's Information Criterion (AIC) and CAIC measures belong to this category. Smaller values indicate a better fit of the model. 226 0 q in M « O NO NO r- C-' r--* l/"!" Ol 1 I 0) a K .C '' 1 u o _ o q ^ '<\ iq q iO •* rt m "t •o rn o 1^ r- O t^ N f; 0) e 6 "1 d d ifi r-i N rr, cK •*' ijs in ^ r-^ fi d © t-- •t ^ in V, O vr r< »-H m m ri t NO NO f( ri NO OS Ol o r~o i TH o c- «-r-i , rH 1-4 F-i o OS o t q !>_ ^ t. oj, ""J. lO iH r-^' i-H 1 (0 fl" •<* •+" •*•" •* ^ Si •d »-H ^ m" ri rW »^ 4-1 «-4 ri M 1 3 V) 0) _ rv (N q o o cs o «o r-> 't •* CNl in >0 NO o t r-H q -. 1^ ««H a d ^ d 0\ <^ d r-^ 00 r-' fri d K d iri ri in r-^ '6 NO Q: 1 O M f~- r-< «
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