IMPACT OF E-COMMERCE APPLICATION ON KENYAN TRAVEL AGENCY SUSTAINABILITY
BY
ARNOLD SAWE
UNITED STATES INTERNATIONAL UNIVERSITY-AFRICA
SUMMER 2019
IMPACT OF E-COMMERCE APPLICATION ON KENYAN TRAVEL AGENCY SUSTAINABILITY
BY
ARNOLD SAWE
A Research Project Report Submitted to the Chandaria School of Business in Partial Fulfilment of the Requirements for the Degree of Masters in Business Administration (MBA)
UNITED STATES INTERNATIONAL UNIVERSITY-AFRICA
SUMMER 2019
STUDENT’S DECLARATION
I, the undersigned, declare that this is my original work and has not been submitted to any other college, institution, or university other than the United States International University-Africa in Nairobi for academic credit.
Signed: ______Date: ______Arnold Sawe (ID 631442)
This project has been presented for examination with my approval as the appointed supervisor.
Signed: ______Date: ______Fred Newa
Signed: ______Date: ______Dean, Chandaria School of Business
ii COPYRIGHT
All rights reserved. No part of this project may be reproduced, stored in a retrieval system, or transmitted in any form or by any means: electronic, mechanical, photocopying, recording, or otherwise without prior written consent of the copyright owner.
© Copyright Arnold Sawe 2019
iii ABSTRACT
The purpose of this study was to examine the impact of e-commerce application on Kenyan travel agency sustainability. The study was guided by the following research objectives: to investigate the impact of e-commerce application in the distribution of travel related services, to examine the impact of e-commerce application in building customer loyalty, and to identify the impact of e-commerce application in the diversification of products/services and how they all impact on Kenyan travel agency sustainability.
The study used descriptive research design as it sought to unravel the impact that e- commerce application has on Kenyan travel agency sustainability. Semi-structured questionnaires were administered consisting of both open and close ended questions. The sample was drawn from travel agencies (TAs) located in Nairobi since the county hosted 255 out of the 293 travel agencies that were members of the Kenya Association of Tour Operators (KATO) as per 2018 figures. The focus was on one top management representatives from each travel agency as they are conversant with the day to day running of their organizations and more specifically, the impact of e-commerce adoption. The sample size was 59 respondents from the 293 KATO member travel agencies. The data collected was analyzed using descriptive and inferential statistics with the aid of Statistical Package for Social Sciences (SPSS).
The findings of the study revealed a positive relationship between e-commerce application in the distribution of travel related services and Kenyan travel agency sustainability. It therefore implied that an increase in e-commerce application in the distribution of travel related services will lead to an increase in Kenyan travel agency sustainability. The study also identified a number of efforts to create value between consumers and travel agencies over the internet; this phenomenon has been described as re-intermediation. Re-intermediation efforts as identified in this paper is through the development of global distribution systems (GDS) such as Sabre, Amadeus, Galileo, and Worldspan. In Kenya, re-intermediation is evident through the development of platforms such as ‘SafariBookings.com’ which acts as an online medium for travel agencies to sell their safari packages. These examples demonstrate the online opportunities that Kenyan TAs could use to become sustainable.
iv The findings also showed a positive correlation between e-commerce application in building customer loyalty and Kenyan travel agency sustainability. The positive correlation implied that an increase in e-commerce application in building customer loyalty would lead to an increase in Kenyan travel agency sustainability. These findings concurred with earlier studies which established that e-commerce tools play a vital role in retaining customers. With the use of e-commerce, Kenyan travel agencies will therefore be able to reinforce their competitive advantage aside from expanding across borders.
Lastly, the findings revealed a positive correlation between e-commerce application in product/service diversification and Kenyan travel agency sustainability. Based on this positive correlation, an increase in e-commerce application in product/service diversification would lead to an increase in Kenyan travel agency sustainability. Apart from stressing the importance of e-commerce adoption, this finding concurs with earlier studies which established that TAs stand to benefit from value addition and diversification across markets. The study also noted competition from emerging online travel agencies (OTAs) which are providing differentiated products. To enable TAs to be more competitive, the study suggests differentiation from the OTAs rather than replication.
The study concludes that Kenyan TAs are experiencing both negative and positive effects of e-commerce adoption. The negative effects are the emergence of OTAs which continue to threaten travel agencies’ dominance. The OTAs are gaining traction in the market by providing differentiated products/services and this signifies the important role that differentiation plays in having a competitive edge. On the flipside, the positive effects of e-commerce adoption are the emergence of B2B2C platforms such as ‘SafariBookings.com’ which are complementing the pre-existing platforms such as Amadeus.
The study therefore recommends that TAs should embrace B2B2C platforms as it will enable them to interact with e-customers. With the aid of e-commerce, the TAs will also be able to easily monitor and analyze customer buying habits and differentiate the products/services offered with an aim of ensuring e-customer satisfaction. For future studies, the study recommends conducting a similar study in a different geographical context as the findings may differ. It was further recommended that future studies seek opinions from consumers of travel related products/services.
v ACKNOWLEDGEMENT
I owe my gratitude to the following support systems that have enabled me to undertake this study. First and foremost, the Almighty God for gracing me with life, good health, skills, and a fighting spirit that saw me through the completion of the MBA program. My sincere gratitude and appreciation goes to my supervisor Fred Newa for his suggestions, critiques, comments, and words of encouragement during the formulation and completion of my project. My regards also go to my family members, colleagues, and friends for their moral support throughout my study. Finally, my utmost gratitude and appreciation goes to my loving parents for their continuous encouragement, support, and sacrifices that have made me see through the entire MBA program.
vi DEDICATION
I dedicate this paper to my loving parents, Peter Kipngetich Sawe and Francesca Chelagat Sawe, for giving me all the support and inspiration that I needed.
vii TABLE OF CONTENTS
STUDENT’S DECLARATION ...... ii COPYRIGHT ...... iii ABSTRACT ...... iv ACKNOWLEDGEMENT ...... vi DEDICATION...... vii LIST OF TABLES ...... x LIST OF FIGURES ...... xi LIST OF ABBREVIATIONS AND ACRONYMS ...... xii CHAPTER ONE ...... 1 1.0 INTRODUCTION...... 1 1.1 Background of the Problem ...... 1 1.2 Statement of the Problem ...... 4 1.3 General Objective ...... 6 1.4 Specific Objectives ...... 6 1.5 Significance of the Study ...... 7 1.6 Scope of the Study ...... 7 1.7 Definition of Terms ...... 8 1.8 Chapter Summary ...... 9 CHAPTER TWO ...... 10 2.0 LITERATURE REVIEW ...... 10 2.1 Introduction ...... 10 2.2 The Impact of E-Commerce Application in the Distribution of Travel Related Services ...... 10 2.3 The Impact of E-Commerce Application in Building Customer Loyalty ...... 15 2.4 The Impact of E-Commerce Application in the Diversification of Products/Services ...... 19 2.5 Chapter Summary ...... 24 CHAPTER THREE ...... 25 3.0 RESEARCH METHODOLOGY ...... 25 3.1 Introduction ...... 25 3.2 Research Design ...... 25 3.3 Population and Sampling Design ...... 26
viii 3.4 Data Collection Methods ...... 27 3.5 Research Procedures ...... 27 3.6 Data Analysis Methods ...... 28 3.7 Chapter Summary ...... 29 CHAPTER FOUR ...... 30 4.0 RESULTS AND FINDINGS ...... 30 4.1 Introduction ...... 30 4.2 General Information ...... 30 4.3 E-Commerce Application in Kenyan Travel Agencies ...... 33 4.4 Impact of E-Commerce Application in the Distribution of Travel Related Services on Kenyan Travel Agency Sustainability ...... 36 4.5 Impact of E-Commerce Application in Building Customer Loyalty on Kenyan Travel Agency Sustainability ...... 41 4.6 Impact of E-Commerce Application in the Diversification of Products/Services on Kenyan Travel Agency Sustainability ...... 46 4.7 Multiple Correlation ...... 50 4.8 Multiple Linear Regression ...... 51 4.9 Chapter Summary ...... 53 CHAPTER FIVE ...... 54 5.0 DISCUSSION, CONCLUSIONS, AND RECOMMENDATIONS ...... 54 5.1 Introduction ...... 54 5.2 Summary ...... 54 5.3 Discussion ...... 56 5.4 Conclusions ...... 61 5.5 Recommendations ...... 62 REFERENCES ...... 63 APPENDICES ...... 70 Appendix I: Research Permit ...... 70 Appendix II: Cover Letter ...... 71 Appendix III: Questionnaire ...... 72
ix LIST OF TABLES
Table 4.1: Distribution of Respondents by Gender ...... 30 Table 4.2: Highest Level of Education ...... 31 Table 4.3: Period of Working in the Agency ...... 31 Table 4.4: Current Role in the Agency ...... 32 Table 4.5: Period of Service in the Current Position ...... 32 Table 4.6: Period Which the Agency Has Been in Operation ...... 33 Table 4.7: Extent to Which E-Commerce Enhances Sustainability ...... 33 Table 4.8: Statements on E-Commerce Application in Kenyan Travel Agencies ...... 35 Table 4.9: Extent to Which E-Commerce Application Affects Service Delivery ...... 36 Table 4.10: Types of E-Commerce Intermediaries Used by Kenyan Travel Agencies ..... 36 Table 4.11: Statements on E-Commerce Application in Service Delivery ...... 38 Table 4.12: Correlations...... 39 Table 4.13: Model Summary ...... 39 Table 4.14: ANOVAa ...... 40 Table 4.15: Coefficientsa ...... 41 Table 4.16: Extent to Which E-Commerce Application Has Impacted Customer Loyalty42 Table 4.17: Statements on E-Commerce Application in Building Customer Loyalty ...... 43 Table 4.18: Correlations...... 44 Table 4.19: Model Summary ...... 44 Table 4.20: ANOVAa ...... 45 Table 4.21: Coefficientsa ...... 45 Table 4.22: Extent to Which Product/Service Diversification is Important ...... 46 Table 4.23: Statements on E-Commerce Application in the Diversification of Prod/Serv 47 Table 4.24: Correlations...... 48 Table 4.25: Model Summary ...... 49 Table 4.26: ANOVAa ...... 49 Table 4.27: Coefficientsa ...... 50 Table 4.28: Multiple Correlation ...... 51 Table 4.29: Multiple Linear Regression ...... 52
x LIST OF FIGURES
Figure 2.1: 2016 Internet Penetration in Africa by Internet World Stats (2016)...... 16 Figure 2.2: Categories Suitable for Digital Marketing by Kierzkowski et al. (1996)...... 17
xi LIST OF ABBREVIATIONS AND ACRONYMS
CAK- Communications Authority of Kenya CRM- Customer Relationship Management CRS- Computer Reservation System GDS- Global Distribution Systems IATA- International Air Transport Association ICT- Information and Communication Technology KATO- Kenya Association of Tour Operators KNBS- Kenya National Bureau of Statistics OTA- Online Travel Agency P2P- Peer-to-Peer RM- Relationship Marketing TA- Travel Agency UK- United Kingdom USA- United States of America WWW- World Wide Web
xii CHAPTER ONE
1.0 INTRODUCTION
1.1 Background of the Problem
Arguably, the primary goal of information technology is to transmit large amounts of data between individuals and organizations quickly and accurately (Wienclaw, 2017). Concurrently, with the mass adoption of the internet, this has created a paradigm shift in the way business is conducted. Today, the use of traditional commerce is becoming more unpopular as more businesses continue to integrate e-commerce technologies to their business processes (Mourya & Gupta, 2015).
As stated by Kotler and Keller (2016), e-commerce can be defined as the buying and selling process that is supported by electronic means. With respect to the travel and tourism industry, a study was conducted to examine the impact of e-commerce on the profitability and sustainability of USA based travel agencies (TAs) with respect to size. The findings indicated that larger organizations felt little effect of e-commerce adoption as compared to smaller travel agencies (Elhaj & Barakeh, 2015). The study, however, has geographical delimitations as it was only carried out in the USA.
E-Commerce has positive and negative implications on the brick and mortar travel agencies. For instance, this development has led to internet companies joining in to tap the potential market that e-commerce has created (Smith, 2018). This has been described as disintermediation which is the elimination of intermediaries in the distribution channel (Kibe & Ndivo, 2015). An example of an Online Travel Agency (OTA) is Travelocity which was introduced by Sabre Technology Group in 1996. Travelocity optimized consumer-inventory interaction such as search and customization and this changed the landscape (Granados, Gupta, & Kauffman, 2007). Other examples of OTAs formed later are Expedia, ‘Trip.com’ and ‘Booking.com’ (World Bank Group, 2018). A different study conducted on Australian travel agencies indicates that travel agencies have adopted the use of WWW with most only using a fraction of its business potential (Standing & Vasudavan, 2014). Based on empirical study of OTAs entering the market, the underutilization of e-commerce could be detrimental to the TAs if they don’t adapt.
1 While much of the discussions focus on the demise of the travel agencies, the internet can also be viewed as a catalyst and an opportunity for TAs to re-engineer their role in the distribution chain (Rensburg, 2014). Travel agencies’ role is therefore still important as they act as intermediaries who simplify buyers’ choices. Their ability to organize, collate, and interpret data is still a valued attribute (Khin, 2018). Through re-intermediation, the travel agencies could therefore remain impactful in the business environment. Re- intermediation is defined as the use of internet tools for the development of new intermediaries or development of new methods for existing intermediaries (Smith, 2018).
Re-intermediation is evident through the development of global distribution systems (GDS) such as Sabre, an automated e-commerce system developed by American Airlines in the 1960s. The reservation system was formed to improve efficiency in data processing. At one time, the e-commerce system grew to become the largest real-time data processing system (Granados et al., 2007). Three other examples of GDS that dominate the sector are Amadeus, Galileo, and Worldspan (Kamau, 2015). Locally, travel agencies have started using ‘SafariBookings.com’ which acts as a medium for travel agencies to sell their safari packages online.
According to Mourya and Gupta (2015), e-commerce is classified into six categories with regard to the entities involved in a transaction. They include business to business (B2B), business to customer (B2C), consumer to business (C2B), business to employee (B2E), customer to customer (C2C), business to government (B2G), and government to government (G2G).
B2B e-commerce is carried out between two or more companies within the internet rather than through traditional modes of doing business such as face-to-face and telephones. The transaction could be between a manufacturer and a wholesaler or between a wholesaler and retailer. As stated by Mourya and Gupta (2015), business to business e-commerce accounts for 94% of all e-commerce transactions. B2B electronic markets were developed in the late 1970s so as to facilitate transactions between airlines and travel agencies (Granados et al., 2007).
B2C e-commerce is carried out between a business and the general public. An example of B2C e-commerce is the first internet travel website (Internet Travel Network) which was launched in 1995 (Granados et al., 2007). As observed by Dixit and Sinha (2016), the
2 launch of the website was possible due to the accessibility of the internet in the late 1990s.
Another category is C2B e-commerce which is a form of e-commerce where a consumer originates a transaction with set of requirements and price specifications for a product and/or service. The consumer then reviews the bids from various businesses and selects the most suitable business entity to complete the project.
B2E e-commerce is a form of e-commerce that allows businesses to automate employee related corporate processes. Through the use of an intra-business network, companies are able to provide products and services to their employees. Examples of B2E applications include online supply requests, special employee offers, online insurance policy management and corporate announcement (Mourya & Gupta, 2015).
C2C e-commerce involves a transaction amongst customers who are connected through the internet with the help of an e-commerce platform. Through C2C e-commerce, a customer makes a product listing on the platform and relies on the market maker, who catalogs, sets transaction procedure and optimizes search engines so that the product gets sold (Dixit & Sinha, 2016). Airbnb is a great example of such a platform since it enables individuals to rent out their personal homes/rooms to different people; it is one of the disruptors that have impacted the travel and tourism industry (Sonwabile, 2018).
B2G e-commerce is a fairly new trend in e-commerce. This model is used by government departments to directly reach out to customers by setting-up websites. These websites contain information relating to the different departments. This enables citizens to be informed without the need of going to the various departments to seek information. Mourya and Gupta (2015) argue that the concept of Smart City has evolved from B2G e- commerce. The final e-commerce category as elaborated by Mourya and Gupta (2015) is G2G e-commerce which involves transaction between two governments.
The use of e-commerce in the Kenyan landscape has seen tremendous growth as per a recent research carried out by CAK and KNBS. The joint report indicates that 27% of firms sold their products online (Muli, 2018). Another study conducted through data from aggregation website ‘internetworldStats.org’ indicated that Kenya was leading in Africa in terms of data penetration (Internet World Stats, 2016). Due to these developments, brick and mortar retail giants continue to struggle to stay in business. A recent example is
3 Nakumatt which was once the largest retail chain in east Africa now on its deathbed due to the effect of e-commerce among other factors (Otieno, 2016). With regard to the tourism sector, travel agencies are starting to feel the impact of e- commerce with estimates showing they are losing up to 60% of the market share to self booking portals and shared economies (Muhatia, 2018). This paper therefore provides a study of the travel agency sector within Kenya. The aim is to assess the actual impact of e-commerce application on the industry players.
1.2 Statement of the Problem
Brick and mortar travel agencies are facing a number of effects which are both positive and negative due to the increased use of e-commerce (Smith, 2018). One of the positive impacts as mentioned earlier is the re-intermediation through electronic intermediaries such as Sabre, Amadeus, and ‘SafariBookings.com’. As the Kenyan internet penetration levels keep on increasing, this will influence customer’s decision when it comes to sourcing of goods and services.
Despite the positive implications, e-commerce also has negative implications such as the exposure to fraudsters on the internet. According to a report conducted by Internet Society (2016), lack of trust can have a significant impact on the ability to do business. An example is the requirement to input personal details when conducting online payments; this exposure to fraudsters would make one skeptical especially if there are recurrent fraud cases.
More critically, the increased use of e-commerce could be detrimental to brick and mortar travel agencies who fail to embrace the technology. The implications could be lethal as hotels, traditional partners of travel agencies, are also establishing the use of OTAs that create online presence. According to Standing, Boyer, and Boyer (2014), airlines are encouraging travelers to bypass travel agencies and book their flights directly. The result will be an increase in the number of prospective customers using the OTAs as opposed to brick and mortar travel agencies. Other avenues available are airline direct sales and telephone call centers which enable airline passengers to book their travels directly (Smith, 2018).
4 In a study conducted by Elhaj and Barakeh (2015), the researchers set out to determine the impact of e-commerce on travel agencies in the USA. Due to delimitation of their study, they recommended that future research be replicated in other geographic locations so as to determine the extent to which their findings apply.
In another study conducted in Taiwan to determine the impact of the internet on travel agencies, it was recommended that future studies should research on suppliers’ perceptions of the impact of the internet on the travel and tourism industry (Bennett & Lai, 2005). The study further gave a recommendation that a comparison of different countries would be valuable in assessing the impact of the internet geographically.
To determine the impact of technological advancements on the distribution of travel related services, a study was conducted in Crete, Greece; the findings indicate that the Cretan tourism market players (including the Crete hoteliers and local travel agencies) are trying to support the traditional tour operators. Furthermore, the Cretan tourism market is largely controlled by big traditional tour operators that control the major charter flights. So as to provide a wider generalizability of the results, the study recommended that future research be conducted in different geographic and tourist contexts (Fountoulaki, Jung, & Dieck, 2015).
Pavlovic and Stanić (2015) in their study on the distribution of travel related services in Serbia, identified that people tend to place more trust in traditional agencies when it comes to booking over the internet despite booking via OTAs being cheaper. The research also identified that a large percentage of those who book via traditional agencies prefer agencies they have used before. As mentioned earlier, Kenya is one of the leading courtiers in Africa in terms of data penetration; it was therefore worthwhile to investigate whether customer loyalty in Kenya has been affected by e-commerce application hence making it one of the objectives of this study.
Locally, a survey was conducted on 55 Kenyan travel agencies with an aim of examining the different strategies they adopt in a bid to reposition themselves with respect to the opportunities and threats presented by ICTs. The findings indicate that majority of the TAs used ICTs for more than five years; only about 7% of the TAs sampled had used ICTs for less than five years (Kibe & Ndivo, 2015). In another study conducted by Kamau (2015) on Nairobi based travel agencies, the findings show that the TAs offer amalgamated travel services to different categories of clientele while still incorporating
5 ICTs. With the continuous disruption in the travel and tourism industry due to the internet and its application, it would be worthwhile to investigate how products/services offered in the sector have evolved and its effect on the sustainability of the TAs.
With a focus on e-commerce, this study was therefore conducted to close the gap by investigating, examining, and identifying the impact of e-commerce application in the distribution of travel related services, in building customer loyalty, and in the diversification of products/services respectively, in turn determining their impact on Kenyan travel agency sustainability. The study took into consideration the opinions of specific employees within the organizations as recommended in the previous studies. Employees targeted were top management representatives from each of the agencies sampled. With a focus on Kenya, the study therefore investigated the extent to which e- commerce has impacted travel agencies’ sustainability. It also enabled the researcher to fulfill the requirements for the conferment of Masters Degree at the United States International University-Africa.
1.3 General Objective
The general objective of this study was to investigate the impact of e-commerce application on Kenyan travel agency sustainability.
1.4 Specific Objectives
The objectives underlying this research were:
1.4.1 To investigate the impact of e-commerce application in the distribution of travel related services on Kenyan travel agency sustainability.
1.4.2 To examine the impact of e-commerce application in building customer loyalty on Kenyan travel agency sustainability.
1.4.3 To identify the impact of e-commerce application in the diversification of products/services on Kenyan travel agency sustainability.
6 1.5 Significance of the Study
1.5.1 Kenyan Travel Agencies
The study will be of value to Kenyan travel agencies as well as foreign based travel agencies that seek to enter the Kenyan market. It will also enable the management to have an understanding of the impact that e-commerce has on the organization’s corporate business strategy. In addition, it will also enable them to implement effective competitive strategies so as to keep abreast with the turbulent business environment, more so due to the tremendous growth of e-commerce use.
1.5.2 Other Service Retailers
The study highlights the level of importance of e-commerce adoption for retailers in other industries especially due to the tremendous growth of e-commerce use. This will motivate them to adopt and effectively implement business strategies that are competitive.
1.5.3 Academics/Researchers
The findings of this study will enable academics/researchers to utilize this study’s results as part of secondary data that will be used to enhance future studies in support of adopting information and communication technology. Through the study, academics/researches will also be able to identify gaps in the current research and carry out comprehensive research in those areas.
1.6 Scope of the Study
The study was carried out on select travel agencies that use e-commerce avenues and those that intend to use it in Kenya. The objective of this research was to find out the impact of e-commerce application on Kenyan travel agencies, taking into consideration the distribution of travel related services, customer loyalty, and product/service diversification. The study population comprised 293 members of the Kenya Association of Tour Operators (KATO, 2018). A sample size of 59 was determined from the requirement that for a population of less than 10,000, a sample of between 10-30% of the population is an adequate representation of the target population (Mugenda & Mugenda, 2003). The sample consisted top management representatives drawn from each agency. The scope of the study was restricted to Nairobi as it is the location where majority of
7 Kenyan travel agencies were located; 255 of the 293 travel agencies were located in Nairobi.
1.7 Definition of Terms
1.7.1 E-Commerce
This can be described as carrying out of business primarily over the internet (Khin, 2018).
1.7.2 Distribution Channel
This is the path by which tourism organizations execute the communication and sale of their products and services (Katsoni, 2016).
1.7.3 Diversification
It is the change in characteristics of a company’s product line and/or market (Ansoff, 1948).
1.7.4 Customer Loyalty
This can be described as the customer’s behavior that shows motivation to increase a continuous relationship with a firm (Yang, Chen, & Huang, 2017).
1.7.5 Internet Penetration
Broadly, this is the relationship between the numbers of individual internet users as compared to the demographic data (Ecommerce Foundation, 2016).
1.7.6 Brick and Mortar
This is a form of organization that performs most of its businesses in a storefront (Smith, 2018).
1.7.7 Re-intermediation
The creation of new value between the consumers and the suppliers over the internet (Khin, 2018).
1.7.8 Disintermediation
The removal of intermediaries that formerly linked a company to its customers (Khin, 2018).
8 1.8 Chapter Summary
This chapter introduces the purpose of the study which was the investigation of the impact of e-commerce application on Kenyan travel agency sustainability. It also introduces the research objectives which were to determine the impact of e-commerce application in the distribution of travel related services, in building customer loyalty, and in the diversification of products/services with an aim of determining the extent to which e-commerce has impacted travel agencies’ sustainability in Kenya. The scope of the study was done during a six month period. The study was carried out on Kenyan travel agencies that were using e-commerce and those intending to use e-commerce.
The next chapter is literature review which implements empirical review of studies relating to the identified objectives. Chapter three gives a detailed description of the research design/methodology used in the study with a close look at the data collection methodology used. Chapter four structures the analysis and further interprets the findings. Finally, chapter five reviews the findings that aided in drawing conclusions and providing recommendations.
9 CHAPTER TWO
2.0 LITERATURE REVIEW
2.1 Introduction
This chapter presents the works of other writers who have done research on and/or have published material regarding the topic of study. The basis of this empirical review is to find out e-commerce application’s impact on Kenyan travel agencies in relation to the distribution of travel related services, customer loyalty, and product/service diversification.
2.2 The Impact of E-Commerce Application in the Distribution of Travel Related Services
2.2.1 E-Commerce
E-Commerce is the process of conducting on-line business through transactions such as sales and information exchange (Sprague, 2014). Sprague (2014) further outlines various applications of e-commerce including online retailing, electronic storefronts, electronic markets, and online auctions. According to Nescott, the growth of the internet has significantly changed the way consumers interact with financial providers. Nescott (2012) attributes this growth to the popularity of internet banking as well as the online purchasing of financial products.
As observed by Siaw, Ansah, and Adjei (2015), the travel and tourism industry has been influenced by three major waves of ICT in the past 30 years: the Computer Reservation System (CRS) in the ‘70s, GDS in the ‘80s, and the internet from the mid ‘90s onwards. With the use of ICTs, the three scholars opine that these advancements will impact the whole value chain and affect the process management and service deliverly. According to Rensburg (2014), the growth of the internet has enabled suppliers to become more independent and gradually reduced their dependence on travel agencies, prior to which they served exclusively as intermediaries. As Kamau (2015) observes, airlines and hotels are encouraging their customers to book directly through their own storefronts, mobile applications, and the internet. With these developments, the overarching aim of travel agencies will be to transform their business appropriately in order to gain competitve advantage.
10 2.2.2 Distribution of Travel Related Services
As opined by Wienclaw (2017), businesses that were able to survive beyond the early 2000s were those that adapted the internet as one of the marketing channels. These technological advancements are leading to a change in consumer behavior (Nescott 2012). Through the internet, consumers are able to choose sellers that satisfy their needs. In the travel and tourism industry, there are a number of independent B2B, B2B2C, and C2C platforms. Examples of B2B platforms are GDS such as Sabre and Amadeus (Kamau, 2015). B2B2C examples that are dominating the hotel distribution in the internet are Expedia and Priceline brands such as ‘Booking.com’ (Martin-Fuentes & Mellinas, 2018). There are also a variety of C2C platforms such as Airbnb and CouchSurfing which are disruptors in the travel and tourism industry (Chen, 2018). This change in the distribution of goods and services, due to the internet and its application, has been described as either disintermediation or re-intermediation.
2.2.2.1 Disintermediation
In the travel and tourism industry, the motivating factor for cutting out the middlemen is to link themselves (suppliers) directly to the customer. Airlines have for instance introduced commission caps and increased the use of ICT in a bid to reduce costs and increase efficiency (Kibe & Ndivo, 2015). It is, however, argued that the replacement of physical agencies by virtual ones means that the potential for cost saving as promised by the internet is not being achieved as electronic costs may increase due to increased servicing and multiple channel support.
A significant number of people have, however, shown a propensity to look on the internet and book via traditional means. This can be attributed to the concern over credit card security due to hackers who look for loopholes to steal money in the internet (Mourya & Gupta, 2015). Risks involved in online transactions have, however, been mitigated due to improved security features. In the words of Mourya and Gupta (2015), e-commerce lacks the personal touch. This could be another reason why some people would opt for traditional means as travel related services are regarded as emotion based products that require interaction during the buying process as will be elaborated on in depth in this chapter. Schmidt-rauch and Schwabe (2013) investigated large scale disintermediation in the travel and tourism industry and found that disintermediation could be minimized by
11 concentration on nitche markets, adopting e-commerce, improving online marketing, and implementation of new distribution strategies.
2.2.2.2 Re-intermediation
Due to the development of e-mediaries such as Epedia, Travelocity, and Yahoo Travel, travel agencies need to re-define their role in the distribution chain (Bennett & Lai 2005). According to Kibe and Ndivo (2015), travel agencies need to redefine their roles by creating new values between buyer and seller. Locally in Kenya, we have platforms such as ‘SafariBookings.com’ which enables travel operators to sell packages through their platform. Through these kinds of integrated platforms, an avenue has been created for travel agencies to market and differentiate themselves from online competition by providing value added benefits to their customers (Kibe & Ndivo, 2015). These platforms also have the potential of passing economies of scale directly to the consumer leading to reduced fares as well as the convenience of making reservation anytime be it during the day or at night (Mourya & Gupta, 2015).
There has also been an emergence of airline portals such as Orbitz and Opodo as highlighted by Bennett and Lai (2005). These can also be referred to as Global Distribution Systems (GDS) and are used for reservations, inventory management, and accounting (Standing & Vasudavan, 2014). Other examples as highlighted earlier are Sabre and Galileo (Standing & Vasudavan, 2014). In Kenya, one of the most common GDS used by travel agencies is Amadeus which partnered with Jumia in 2018 in a bid to make travel simple and affordable (Writer, 2018). Still in Kenya, Travelstart in 2015 launched an affiliate platform, ‘neXt’ which offered independent travel consultants a platform to book and manage flights for their clients and issue tickets without requiring an IATA license (StandardMedia, 2015).
2.2.3 Investigating the Impact of E-Commerce Application in the Distribution of Travel Related Services
A number of studies have been done to determine whether travel agencies have been positively or negatively affected by e-commerce. The impact can be classified as either disintermediation or re-intermediation of travel agencies as elaborated on earlier. Much of the discussions from previous studies focus on the demise of travel agencies due to disintermediation albeit e-commerce being viewed as a catalyst and an opportunity for travel agencies to re-engineer their role in the chain of distribution. Embracing e-
12 commerce will thus enable travel agencies to sustain their position in the market (Cheung & Lam, 2009).
Sprague (2014) for instance argues that with the advent of the information age, it has not only revolutionized the way enterprises do businesses with consumers, but also the way they do business with each other. It is therefore unjustified to assume that the advent of e- commerce spelt doom on the travel agencies. More so, many experts have argued that business to business trade will reap the most benefits from the e-commerce trend (Mourya & Gupta, 2015).
A research focusing on 438 Taiwan travel agencies found that the agencies generally regard the internet as an effective tool for their business. The research also found out that the effect of the internet was not significant. Commission cutting by suppliers was, however, a threat but it was thought to be unlikely that disintermediation would occur (Bennett & Lai, 2005).
Contrasting opinions are, however, evident from studies done by other scholars. As observed by Cheung and Lam (2009), the travel agency business has experienced decline as a result of reduced airline fare commissions since 1995. Morosan, Bowen, and Atwood (2014) on the other hand argue that as much as B2B and B2C have digitized, the focus has now shifted to C2C social activities. This is evident in the travel and tourism industry with internet companies such San-Francisco based Airbnb, an online community marketplace, which gives ordinary people an opportunity to host travelers in their homes/facilities, share their experiences with the travelers, and earn an income from the hosting (Airbnb, 2017).
According to Airbnb (2017), an African host typically earns $1,500 yearly with the host community being evenly split at 51% women and 49% men. As stated in a World Bank Group report (2018), P2P platforms such as Airbnb have evolved making them competitive in the accommodation market. This has been seen as a threat to the hotels and tours and travel operators since customers have become exposed to more affordable facilities.
As Gerdeman (2018) states, Airbnb has revolutionized the lodging market by making additional rooms available in countries’ hottest travel spots during the peak season; periods which hotels used to hike room prices so as to earn the biggest margins.
13 Competition between the traditional hotels and Airbnb is thus intensifying. As Airbnb continues to expand its offerings across different cities all over the world, local hotel/tour and travel operators continue to intensify lobbying efforts in local and federal circles for stricter regulations to govern Airbnb.
In Kenya for instance, Airbnb is experiencing pressure from the tourism ministry (Muiruri, 2017). The push is to have Airbnb pay occupancy tax which amounts to 5% from each booking made in the country. In this bid to have e-commerce businesses taxed, the Kenyan government through the Kenya Revenue Authority, recently issued a public notice that would ensure online businesses such as Airbnb are taxed (Kenya Revenue Authority, 2019).
However, as earlier stated in this paper, the internet can be used as an opportunity to re- engineer a company’s role in the distribution chain. Marriot International has for instance responded to the threat of Airbnb with 350 new home sharing properties in Europe. Through its model, travelers will be able to earn and redeem points through Marriot’s award winning loyalty platform (Steinmets, 2018). Other hotels that are expanding beyond what they are known for are Hyatt Hotels and Resorts and Accor Hotels (Moreno de la Santa, 2018).
Based on the above findings it is evident that the travel agencies are experiencing both negative and positive implications of e-commerce adoption. As suggested by Dilts and Prough (2002), travel agencies need to transform their traditional ‘brick and mortar’ services to ‘hybrid click and mortar’ services. Embracing of e-commerce and its application is therefore of importance not only when it comes to booking accommodations but also when it comes to booking flights despite statistics indicating that 90% of the flights market is still offline (Writer, 2018).
In a competitive environment, online capabilities could therefore be extremely helpful in aquiring and retaining customers. Despite its abundant potential, companies may not be undertaking proper marketing actions to create and maintain relationships with customers through the internet.
14 2.3 The Impact of E-Commerce Application in Building Customer Loyalty
2.3.1 Customer Loyalty
As Rahimi, Köseoglu, Ersoy, and Okumus (2017) observe, the concept of marketing has been redefined by the emergence of novel theories such as Relationship Marketing (RM) and Customer Relationship Management (CRM). The four scholars futher described RM as the first customer management theory; it brought companies’ attention to fosussing on long term goals and building long term customer relationships. RM was later replaced by CRM which focusses on attracting, maintaining, and enhancing customer relationships. As the role of the internet became more important, businesses such as travel agencies shifted focus on ways in which they can utilize ICTs to build relations with customers (Rensburg, 2014).
In relation to the travel and tourism industry, ICTs have impacted consumers’ behaviors. Consumers now have more options to search for vacations to meet their budgets. As Dwikesumasari and Ervianty (2017) observed, due to the change in customer behavior, a lot of people have stopped going to traditional travel agencies and have instead opted for OTA applications due to the ease of downloading them from their smartphones. However, Hua et al. (2018) argue that companies in the travel and tourism industry can enhance customer loyalty by responding quickly to customer requests and maintaining a customer preference database. To expound on the same argument, McKinsey consultants Kierzkowski, McQuade, Waitman, and Zeisser (1996) higlight five factors that marketers should address in the digital age: attracting customers to the application, generating interest and participation, retaining users of the application, learn consumer preferences, and customizing the interaction and value delivery. Based on the changes in consumer behavior, examining how customer loyalty has been impacted by e-commerce application in Kenya was therefore of importance to this study.
2.3.2 Examining the Impact of E-Commerce Application in Building Customer Loyalty
Dwikesumasari and Ervianty (2017) conducted a study on respondents aged 17 years and above who had used OTA applications to purchase travel products in order to determine e-customer satisfaction and e-customer loyalty. The findings showed that travel agencies need to capture market loyalty by ensuring there’s e-customer satisfaction through access
15 to travel information, provision of innovative value added services, and development of winning strategies supported by information technology. From a study done earlier, Lehto, Kim, and Morrison (2006) highlight the importance of e-customer satisfaction, the study shows that 95 percent of web users searched the internet to gather travel related information. The study further shows that 93 percent of the web users visited tourism websites when planning vacations.
With regard to customer behavior, Nescott (2012) stated that there is a trend towards individualism which is becoming a social structure of the modern society. In line with the increased individualism, consumers demand a more personalized approach hence the need for individualization of information and services as it satisfies a latent human need as opposed to generic mass medium.
Nescott (2012) further observes a study that examined that the internet usage has increased at a growth rate of 20 percent per year since 1998. Morover, a study conducted in Africa as was earlier highlighted in this paper, established that Kenya was leading in terms of internet penetration in 2016. The 2016 figures indicated that Kenya’s internet penetration rate stood at 70 percent; beating other countries such as Morocco, Nigeria, South Africa, and Egypt just to mention but a few (Internet World Stats, 2016).
Figure 1.1: 2016 Internet Penetration in Africa by Internet World Stats (2016). (Source: https://www.internetworldstats.com Website)
16 It is therefore considered that this increase in internet usage will transform the way business is conducted. Additionally, e-commerce can reinforce a firm’s competitive advantage as it enables expansion across borders. The opening up of new borders as well as the tools that e-commerce provides will therefore play a vital role in retaining customers (Chang, Magobe, & Kim, 2015).
2.3.2.1 Online Behavior Analysis
Figure 2.2: Categories Suitable for Digital Marketing by Kierzkowski et al. (1996). (Source: The McKinsey Quarterly 1996 Number 3)
Kierzkowski et al. (1996) examined interactive marketing’s role in the products/services sectors. They formulated two dimensions as listed below:
a) Fit with Interactive Media b) Potential for Relationship Building
The system has four different quardrants. In the figure above, the co-ordinated system shows the influence of the type and shape of the product offerring and the distribution concept. The upper right quardrant contains emotion based products/services that require interaction during the buying process. This has been described as the domain in which internet was first accepted. Examples as highlighted in the diagram include Travel services, Financial services, Insurance, Music, Books, and Real estate brokerage.
17 Based on the above study, it is evident that the internet and the travel industry are highly compatible. However, Moreno de la Santa (2018) argues that there needs to be a balance between the digital and human touch so as to better customize messaging, products, and services for customers. The manner in which travel related services are communicated is therefore highly important due to its classification as an emotion based product (Nescott, 2012). The internet therefore fulfills this role due to its instantaneous nature and its ability to provide information at a much lower cost than traditional channels; this, however, requires a balance as earlier stated.
As per a study conducted on Australian tour agencies, the findings show that tourist attraction information, fare information, and tour package information are the top three uses of the internet (Standing & Vasudavan, 2014). This study further shows that travel agencies that have embraced the use of the internet emphasize on travel information such as package prices among other travel related information so as to assist the consumers to make decisions. In a different study conducted in Kenya by Kibe and Ndivo (2015), it was observed that Kenyan TAs differentiate themselves from OTAs by offering credit services, face to face communication, and personalized customer care. Based on empirical review, it is, however, evident that customers value online travel due to the exposure to more travel choices, its convinence, as well as its cheaper cost (Rensburg, 2014).
In line with these studies, Mourya and Gupta (2015) highlight several factors that would ensure repeat e-customers: answering emails promptly and personally, avoiding canned responses, and listing of company telephone number(s) and business addresses. Moreover, through e-commerce, companies can easily market their products and services through e-mail, newsletters, websites, blogs, and search engine ads such as Google Ads. This can significantly increase sales if coupled with conventional marketing techniques such as business cards, print advertising, and brochures.
2.3.2.2 Value Chain Analysis and Five Product Levels
Arguably, the main good that flows through e-commerce is information. Porter’s value chain framework (1985) analyzes the value creation on a firm’s primary and support activities as well as their economic implications with a view of increasing value to the customer. Based on the matrix developed by Kierzkowski et al. (1996), travel services and the internet were found to be highly compatible. In addition, due to its classification as an emotional based product, the manner in which travel related information is
18 communicated is therefore important. Since e-commerce has the capability of relaying information instanteneously, e-commerce is considered valuable by the consumer.
Based on Kotler’s five product levels model, consumers attach value to a product progressively in 3 ways: customer need, customer want, and finaly customer demand (Kotler & Keller, 2016). Due to the fact that customers have become more affluent, they now demand quick service delivery (Dwikesumasari & Ervianty, 2017); this is a good indicator as to how valuable e-commerce is to them, as it’s able to facilitate services quickly. The need for quick service delivery is because customers no longer want to wait in line so as to complete a transaction; they can now complete a transaction from start to finish through secure networks simultaneously with other customers (Standing & Vasudavan, 2014). This makes transactions more efficient for the customer.
2.4 The Impact of E-Commerce Application in the Diversification of Products/Services
2.4.1 Product/Service Diversification
Diversification in the tourism sector entails offering varied and customized products as well as flexibility in planning and designing of the destination experience in order to meet the customers’ needs (Weidenfeld, 2018). As opined by Lalitha and Paul (2015), the travel and tourism industry is constantly changing. On this basis, the two authors recommend tailoring of products and services to customers. Unlike conventional brick and mortar travel agencies, OTAs are able to offer a multitude of products. Due to these developments, many Kenyan TAs have employed diversification strategies so as to remain relevant in the market (Kibe & Ndivo, 2015). Weidenfeld (2018), however, asserts that for diversification strategies to succeed, TAs need to identify areas in the market with the best potential and stimulate innovation rather than replication.
According to Ansoff (1948), there are four basic growth strategies that a firm could use. They are: market penetration, market development, product development, and diversification. Ansoff further opines that diversification stands apart from the other three growth strategies. He attributes this to the new skills, techniques, and facilities that are required when implementing diversification strategies as opposed to the other three strategies which usually require the same financial, merchandising, and technical resources. Following this analogy, diversification was a suitable variable to examine in
19 this study due to the nature of ICT advancements that require new skills. There are three types of diversification: vertical diversification, horizontal diversification, and lateral diversification.
Vertical diversification as described by La and Fossen (2001) mostly takes place between hotels and restaurants. The two scholars highlight Marriott and Ritz-Carlton which both merged from restaurants. There have also been attempts to integrate hotels and airline operations but in most cases this has led to disastrous results. An example is the 1970 merger between United Airlines and Western Hotels which was unsuccessful leading to the sale of Westin to Aoki Corporation in 1998 (La & Fossen, 2001). Based on empirical review, this can be greatly attributed to the contrasting forms of organizational cultures between the two.
The second type of diversification is horizontal diversification which occurs when an organization enters a competing or complementary market (Weidenfeld, 2018). This strategy involves acquiring or developing differentiated products to its current ones. According to Oxford Business Group (2016), Kenyan tour operators are seeking to diversify revenue streams through expansion to foreign markets; apart from the key markets which are the UK and USA, there’s a lot of interest in the Asian Markets and Latin America. According to Weidenfeld (2018), this kind of strategy also involves reorienting the market focus in an underexploited area. Based on this explanation, Kenyan travel agencies among other partners have recently embarked on a campaign to market untapped destinations such as western Kenya in a bid to open up tourism opportunities (Ngugi, 2019). This campaign would enable the travel agencies to diversify their product offering to the consumer.
The last diversification strategy is lateral diversification. Unlike vertical and horizontal diversification, lateral diversification does not delimit the field of interest. It therefore involves moving beyond the confines of an industry that a company belongs to (Ansoff, 1948). In the Kenyan tourism sector, there was a recent buyout of local travel agency (Abercrombie & Kent) by Heritage Group S.A. a Swiss company that operates in the cruising and real estate sector (Njanja, 2019). Due to Heritage Group S.A’s investment in a different industry to which it operates in, this can be regarded as lateral diversification.
20 According to Ansoff (1948), choosing among these three diversification strategies will depend on the reasons which prompt diversification. He outlines the following reasons: a vertical move when contributing to the technological progress of the present product line, a horizontal move so as to improve the market coverage, a horizontal move so as to increase the sales volume, a lateral move so as to broaden the technological base of the company and finally a lateral move so as to ensure risk reduction. A good example of a lateral move is Jumia an online shopping company that ventured into the travel agency business in a bid to diversify its portfolio (Weigert, 2018).
2.4.2 Identifying the Impact of E-Commerce Application in the Diversification of Products/Services
With the entry of OTAs such as Airbnb, the customers’ expectations have been set higher due to the world class customer service offered through the digital space. As Moreno de la Santa (2018) observes, Airbnb launched its own tours and activities division in November 2016 so as to position itself as the only brand a consumer will ever need for every part of their travels. The OTAs are therefore evolving to become platforms of experiences. Companies including brick and mortar travel agencies are therefore now subject to these expectations when designing and deploying digital experiences.
In a survey commissioned by Google to determine travel habits of leisure and business travelers residing in America, the findings from the survey indicate that most travelers seek value and frequently engage in comparison shopping. The survey further indicates that a typical travel shopper visits 22 websites before booking a trip (Rensburg, 2014). These findings highlight the importance of travel agencies re-evaluating the value propositions presented to clients so as to outwit competition.
Kibe and Ndivo (2015) in a study conducted in Kenya on TAs established that many of the TAs have employed the following strategies since the advent of the ICTs: going online, focusing more on the clients, increased use of ICT, product diversification, and business differentiation from OTAs.
21 2.4.2.1 Traditional Products/Services
Traditionally, ‘electronic shelf space’ was found either in the travel agencies’ computers or at the suppliers’ reservation centers (Palmer & McCole, 1999). Gao and Rajala (2013) state that a traditional travel agency provides products and services such as airline ticket reservation, hotel reservations, car-hires, cruise lines, and package tours primarily through storefronts. As Rensburg (2014) argues, TAs can still remain relevant by value addition through personalized service, agency expertise, established connections, and ability to negotiate better prices. Rensburg further observes that top TAs are able to acquire perks such as upgraded hotel rooms and amenities, hard to get restaurant reservations, specialized tour guides, as well as access to exclusive destinations and events on behalf of travelers.
Despite TAs being able to survive in the digital age, most of them agree that they need to have the right infrastructure to make customer insight actionable (Moreno de la Santa, 2018).
2.4.2.2 Diversified Products/Services
Due to ICTs' capabilities, travel agencies can now be able to monitor and analyze consumers’ buying habits and interests so as to tailor their offers to suit consumers’ needs and keep an ongoing relationship with them (Mourya & Gupta, 2015). In the opinion of Moreno de la Santa (2018), most travel businesses agree that the industry is ripe for personalization which can be done effectively with the use of rich user data which can be obtained through monitoring and analysis. Moreno de la Santa (2018), however, argues that this artificial intelligence needs to be balanced with human touch.
Lalitha and Paul (2015) opine that it is imperative for TAs to understand how best to tailor products and services to customers’ different needs. Fortunately, another benefit of e-commerce is the revolution of the way goods and services are bought. Through pull- type processing, customers can now tailor-make their travel related products and services to suit their needs (Mourya & Gupta, 2015). Travel companies can therefore receive requests from customers online and tailor-make their requests to the specific needs. The ability of e-commerce to instantaneously relay information will ensure that TAs tailor the travel related products to the customer’s specifications.
22 A challenge is, however, eminent with the emergence of OTAs that joined the fray in 1995 to tap into the lucrative travel and tourism industry (Rensburg, 2014).
2.4.2.3 OTA Products/Services
Due to the capabilities of ICTs, new business models have received increasing attention from scholars in the last 20 years (Pavlovic & Stanić, 2015). These new business models have led to a change in consumption behavior in the travel and tourism industry. These models can be best described by the concept of disruptive innovation whereby products and services are a cheaper and more convenient alternative to the existing products and services in the market (Christensen, Altman, Mcdonald, & Palmer, 2016). As earlier mentioned in detail throughout this paper, Airbnb is an example of an OTA that has disrupted the travel and tourism industry from being a P2P platform that enables individuals to rent out their personal homes/rooms to launching its own tours and activities division in November 2016 (Moreno de la Santa, 2018).
In Africa, Jumia Travel is a great example of an OTA that is reshaping the travel and tourism industry in Africa. According to Weigert (2018), Jumia Travel began its operations in Nigeria in 2013 as an e-travel business experiment and now operates in 10 African countries. Through his study of Jumia Travel in Ivory Coast, Weigert’s comparative analysis showed that while ‘Booking.com’ only listed 210 hotels distributed in 14 localities outside Abidjan, Jumia Travel focused on wider geographical coverage by listing 600 hotels in Ivory Coast in 34 localities. This indicates that Jumia Travel embarked on a horizontal diversification so as to improve market coverage. In a bid to gradually integrate other aspects of travel, Jumia Travel also launched its flight search engine in February of 2017 (Weiger, 2018).
Based on the above examples, it is evident that OTAs are diversifying their product and service offerings even beyond the industries in which they are operating in. Due to the technological advancements, Elhaj and Barakeh (2015) in their study pointed out that TAs could benefit from value addition, diversifying across markets, and customer retention initiatives.
23 2.5 Chapter Summary
This chapter explores the review of literature by various researchers based on the research objectives. The main objective was to investigate the impact of e-commerce application on Kenyan travel agency sustainability. Precisely this literature review was conducted to close the gap by investigating, examining, and identifying the impact of e-commerce application in the distribution of travel related services, in building customer loyalty, and in the diversification of products/services respectively; in turn determining their impact on Kenyan travel agency sustainability. The next chapter discusses the research methodology with a focus on the population and the description of the data collection methods that were used. It also gives details of the research procedures and the data presentation methods that were used.
24 CHAPTER THREE
3.0 RESEARCH METHODOLOGY
3.1 Introduction
In this chapter, the study provides a discussion of the research methodology used when carrying out the study. It also provides the details of the research design, population that was targeted, sampling design for the study, as well as data analysis and data presentation methods used.
3.2 Research Design
According to Cooper and Schindler (2013), a research design is a blueprint that entails the collection, measurement, and analysis of data for a particular project. This study adopted a descriptive research design which entails obtaining data that can be used to determine specific characteristics of a group (Kothari & Garg, 2014). Specifically, this research design entailed gathering of data, after which the data was organized, tabulated, and described.
Through the descriptive research design, the study sought to investigate the impact of e- commerce application on travel agency sustainability with Kenya being the research base. This approach was appropriate because it aims to describe the relationship of the variables that are central to the conceptual framework. The descriptive research design was also preferred because it also helps to answer question such as: the who, what, when, where, and how of a topic (Cooper & Schindler, 2013). The research involved the use of questionnaires for data collection from the sample selected. It was formally structured with clearly and well stated investigative questions that sought to find out pertinent issues related to the study.
The research was a cross-sectional study as it desired to determine whether travel agencies, both those that have adopted e-commerce and those intending to use e- commerce, have been impacted positively or negatively. Through this determination, the research was able to conclude whether or not the travel agencies can become sustainable by embracing e-commerce.
25 3.3 Population and Sampling Design
3.3.1 Population
Cooper and Schindler (2013) describe a population as the total collection of elements from which inferences are made. The focus was on travel agencies that are members of Kenya Association of Tour Operators (KATO). As per 2018 figures, KATO had 293 member agencies (KATO, 2018). This research sampled travel agencies located in Nairobi as 255 out of the 293 travel agencies had offices in Nairobi.
3.3.2 Sampling Design and Sample Size
3.3.2.1 Sampling Frame
A sampling frame is the list of the target population from where the sample size is selected (Kothari & Garg, 2014). A sampling frame includes a numerical identifier for each individual element plus additional information that will aid in identifying the characteristics of the individual which will in turn aid in further analysis. For this study, the sampling frame included top management employees from each travel agency, including their designation.
3.3.2.2 Sampling Technique
According to Neelankavil (2015), a sampling technique is the process of selecting components of the sample that are used to give a representative view of the population. For this study, organizations were selected using simple random sampling technique. This method was suitable because it allowed the researcher to give the population an equal chance of being selected. One top management employee was selected from each agency. This allowed for availability of population elements, greater accuracy, and greater speed of data collection.
3.3.2.3 Sample Size
Ryan (2013) describes a sample size as a subset of the population elements resulting from the sampling strategy. A good sample size will help determine the statistical precision with which population values can be estimated. According to Mugenda and Mugenda (2003), when a population is less than 10,000, a sample size of between 10-30% of the population is adequate. For this study, the sample size was one top management employee from each organization and a total of 59 respondents derived from a population
26 of 293 members of the Kenya Association of Tour Operators (KATO, 2018). The 59 respondents represented approximately 20% of the population. The focus was on Nairobi based travel agencies since 255 out of the 293 KATO members have offices in Nairobi.
3.4 Data Collection Methods
Data collection is the process of obtaining information to a study or enquiry whereas research instruments refer to the tools required to collect data in research (Taylor, Bogdan, & DeVault, 2015). Primary data both quantitative and qualitative in nature were collected for this study. In line with specific research objectives, semi-structured questionnaires were used in data collection from the respondents. The questions were divided into five sections; simplicity and ease were key factors in developing of the questionnaire.
Section A was used to obtain general information about the respondent. Section B sought information on e-commerce application in Kenyan travel agencies. Section C was used to obtain information on e-commerce application in service delivery. Section D was used to generate information on e-commerce application in building customer loyalty. Section E sought to obtain information regarding e-commerce application in the diversification of products/services. The questionnaire had a 5-point likert scale as it attempted to measure latent constructs. The respondents were top management representatives from each of the travel agencies sampled.
3.5 Research Procedures
The research procedure began with a pre-test on five respondents from the target population so as to test the completeness of the questionnaire. According to Mugenda and Mugenda (2003), pre-testing will aid in ascertaining the deficiencies in the design of the questionnaire, allowing errors to be discovered, and also acts as a tool for training a research team before the actual collection of data.
After a successful pre-test, the questionnaires were personally administered to the other respondents after explaining the purpose of the research and how their sincerity will be important to the study. The filled questionnaires were thereafter collected by the researcher who carefully went through it with them to ensure it has all the required
27 information. If need be, clarification on some issues was also done. A drop-off/pick-up method was adopted for instances where the respondents were busy.
3.6 Data Analysis Methods
Data analysis entailed reduction of accumulated data to a manageable size, developing summaries, looking for patterns, and application of statistical techniques (Cooper & Schindler, 2013). So as to attain research quality, quantitative methods of data analysis was used to generate a report which was presented through tabulations.
Before processing the responses, the completed questionnaires were edited for consistency and completeness after which the data was coded so as to enable the grouping of the responses into various categories. With the aid of Statistical Package for Social Science (SPSS), descriptive and inferential analyses were employed. Descriptive analysis included the use of means, frequencies, percentages, and standard deviations which were vital in summarizing and making sense of the data. The inferential analysis entailed the Pearson’s correlation analysis; this measured the strength and direction of the linear relationship between the variables.
Multiple regression was then used to determine the relationship between the dependent variable which is Kenyan travel agency sustainability and the independent variables which are: e-commerce application in the distribution of travel related services, e- commerce application in building customer loyalty, and e-commerce application in product/service diversification.
The multiple regression equation is as follows:
Y = β0 + β1X1 + β2X2 + β3X3 + ε
Whereby:
Y = Kenyan travel agency sustainability;
β0 = Regression constant; β1, β2, and β3 = Coefficients of determination;
X1 = E-Commerce application in the distribution of travel related services;
X2 = E-Commerce application in building customer loyalty;
X3 = E-Commerce application in product/service diversification; and ε = Error term.
28 3.7 Chapter Summary
This chapter describes the research design and methodology which were applied in the study to assess the impact of e-commerce application on Kenyan travel agency sustainability. The next chapter focuses on the research findings in relation to the research objectives.
29 CHAPTER FOUR
4.0 RESULTS AND FINDINGS
4.1 Introduction
The chapter entails the presentation, analysis, and interpretation of the data collected. The quantitative data was analyzed using descriptive and inferential statistics while qualitative data was analyzed using content analysis. Data was presented in frequency distributions, percentages, and frequency tables for ease of understanding and interpreting of the findings.
The research issued a total of 58 questionnaires and a total of 54 respondents completed the questionnaires giving a response rate of 93.1%. The response rate is considered sufficient based on Mugenda and Mugenda (2013) who argued that a response rate of 50% is inadequate, a response rate of 60% being good, while that of 70% and above being excellent for analysis and reporting.
4.2 General Information
4.2.1 Distribution of Respondents by Gender The respondents were requested to indicate their gender. Table 4.1 presents the findings. The findings established that a majority of the respondents (59.3%) were males while 40.7% were female. This illustrates that both gender were equitably involved in the study and therefore the findings of this research did not suffer from gender biasness. Table 4.1: Distribution of Respondents by Gender Gender Frequency Percentage Male 32 59.3 Female 22 40.7 Total 54 100.0
30 4.2.2 Highest Level of Education The respondents were requested to indicate their highest level of education. From the findings, majority of the respondents (37.0%) were Degree holders, 22.2% of the respondents held Masters, 20.4% of the respondents held Higher Diploma, 13.0% of the respondents held PhD while 7.4% of the respondents held a Diploma. This shows that all the participants were well educated to understand and respond to the study’s questions. Table 4.2: Highest Level of Education Highest Level of Education Frequency Percentage Diploma 4 7.4 Higher Diploma 11 20.4 Bachelors 20 37.0 Masters 12 22.2 PhD 7 13.0 Total 54 100.0
4.2.3 Period of Working in the Agency Respondents were required to indicate the period which they had worked with the current agency. The study findings established that 29.6% of the respondents indicated that they had worked with the current agency for a period of 11-15 years, 24.1% indicated to have worked for a period 6 to 10 years, 22.2% indicated to have worked for a period 16-20 years, 13.0% indicated to have worked for a period not exceeding 5 years while 11.1% indicated to have worked for a period more than 20 years. Table 4.3: Period of Working in the Agency Period of Working Frequency Percentage Less than five years 7 13.0 6-10 years 13 24.1 11-15 years 16 29.6 16-20 years 12 22.2 Above 20 years 6 11.1 Total 54 100.0
31 4.2.4 Work Designation Respondents were required to indicate their work designation. From the study findings, most of the respondents (27.8%) indicated that they worked as Head of Marketing, respondents who indicated that they worked as CEO or Head of Operations each represented 22.2% of the sample, 18.5% of the respondents worked as Head of Finance, while 9.3% of the respondents indicated that they worked as Head of ICT. Table 4.4: Current Role in the Agency Current Role Frequency Percentage CEO 12 22.2 Operations Head 12 22.2 Marketing Head 15 27.8 Finance Head 10 18.5 IT Head 5 9.3 Total 54 100.0
4.2.5 Period of Service in the Current Position Participants were required to indicate the period which they had served for in the current position. Results show that 31.5% of the respondents had served for in the current position for a period of 6-10 years, 22.2% of the respondents had served for in the current position for a period 11 to 15 years or 16-20 years, 13.0% of the respondents indicated less than five years while 11.1% indicated more than 20 years. Table 4.5: Period of Service in the Current Position Period of Service Frequency Percentage Less than five years 7 13.0 6-10 years 17 31.5 11-15 years 12 22.2 16-20 years 12 22.2 Above 20 years 6 11.1 Total 54 100.0
32 4.2.6 Period Which the Agency Has Been in Operation Assessment of the period which the agency has been in operation showed that most of the travel agencies (29.6%) have been on operation for a period of 16 to 20 years, 27.8% have been on operation for a period of 11 to 15 years, 24.1% have been on operation for more than 20 years, while 18.5% have been on operation for a period of 6 to 10 years. This indicates that most of the travel agencies had been in operation for a considerable period of time which implies that they were in a position to give credible information relating to mode and nature of their operations. Table 4.6: Period Which the Agency Has Been in Operation Period of Operation Frequency Percentage 6-10 years 10 18.5 11-15 years 15 27.8 16-20 years 16 29.6 Above 20 years 13 24.1 Total 54 100.0
4.3 E-Commerce Application in Kenyan Travel Agencies
4.3.1 Extent to Which E-Commerce Application Enhances Sustainability The study sought to determine the extent to which e-commerce application enhances sustainability. Results obtained showed that majority of the respondents (48.1%) were of the opinion that e-commerce application enhanced sustainability to a great extent, 38.9% of the respondents indicated that e-commerce enhanced sustainability to a very great extent, while 9.3% were neutral. Finally, 3.7% indicated that e-commerce had the least impact in enhancing sustainability. This implies that the adoption and utilisation of e- commerce affects travel agencies’ service delivery to a great extent. Table 4.7: Extent to Which E-Commerce Enhances Sustainability Frequency Percentage Less extent 2 3.7 Neutral 5 9.3 Great extent 26 48.1 Very great extent 21 38.9 Total 54 100.0
33 4.3.2 Statements on E-Commerce Application in Kenyan Travel Agencies The respondents were required to indicate their level of agreement with the following statements relating to e-commerce application in Kenyan travel agencies. The study established that most of the travel agencies have not fully moved to e-commerce business (Mean = 4.39, Std. Dev = 0.49), travel agencies enjoy much lower overheads with the use of e-commerce (Mean = 4.35, Std. Dev = 0.73), most customers are reluctant to provide their personal information over the internet (Mean = 4.28, Std. Dev = 0.49), and that customers don’t experience challenges when making bookings with the travel agencies through e-commerce (Mean = 4.20, Std. Dev = 0.68). These findings go hand in hand with the observation made by Mourya and Gupta (2015) that e-commerce platforms have the potential of passing economies of scale directly to the consumer leading to reduced fares as well as the convenience of making reservation. The findings also concur with the study that established that a lack of trust could significantly affect e-commerce business (Internet Society, 2016). The study further established that e-commerce has forced most of the travel agencies to adopt various strategies to remain competitive (Mean = 4.19, Std. Dev = 0.80), most companies use e-commerce in the travel and tourism industry (Mean = 4.15, Std. Dev = 0.66), and that technical capabilities are limited (Mean = 4.11, Std. Dev = 0.90). These findings concur with the study findings by Cheung and Lam (2009) which established that embracing e-commerce can enable travel agencies to sustain their position in the market.
34 Table 4.8: Statements on E-Commerce Application in Kenyan Travel Agencies N Min Max Mean Std. Dev E-Commerce has forced our travel agency to adopt 54 3.00 5.00 4.19 0.80 various strategies to remain competitive Our travel agency enjoys much lower overheads 54 3.00 5.00 4.35 0.73 with the use of e-commerce Our travel agency has not fully moved to e- 54 4.00 5.00 4.39 0.49 commerce business
Our technical capabilities are limited 54 2.00 5.00 4.11 0.90
Our customers don’t experience challenges when 54 3.00 5.00 4.20 0.68 making bookings with us through e-commerce Customers are reluctant to provide their personal 54 3.00 5.00 4.28 0.49 information over the internet Most companies use e-commerce in the travel and 54 3.00 5.00 4.15 0.66 tourism industry
4.3.3 How E-Commerce Use Impacts Kenyan Travel Agencies It was noted that e-commerce is an effective tool for their businesses. This finding confirmed an earlier observation made by Rensburg (2014) who stated that the internet can be viewed as a catalyst and an opportunity for TAs to re-engineer their role in the distribution chain. Some of the respondents, however, indicated that there is a threat presented by internet companies such as Airbnb and ‘Booking.com’, especially due to their competitive rates as well as the variety of accommodation types offered. This findings concur with Gerdeman (2018) who stated that Airbnb has revolutionized the lodging market by making additional rooms available in countries’ hottest travel spots during the peak seasons at lower rates than hotels. It also confirms that there is a threat to the survival of TAs if they don’t embrace e-commerce.
35 4.4 Impact of E-Commerce Application in the Distribution of Travel Related Services on Kenyan Travel Agency Sustainability
4.4.1 Extent to Which E-Commerce Application Affects Service Delivery The study sought to determine the extent to which e-commerce application affects service delivery. Results obtained show that majority of the respondents (51.9%) were of the opinion that e-commerce application will affect service delivery to a Great extent, 42.6% of the respondents indicated that e-commerce application will affect service delivery to a Very great extent, while 5.6% were Neutral on the effect that e-commerce has on service delivery. This implies that the adoption and utilisation of e-commerce affects travel agencies’ service delivery to a great extent. Table 4.9: Extent to Which E-Commerce Application Affects Service Delivery Frequency Percentage Neutral 3 5.6 Great extent 28 51.9 Very great extent 23 42.6 Total 54 100.0
4.4.2 Types of E-Commerce Intermediaries Used by Kenyan Travel Agencies The study sought to determine the types of e-commerce intermediaries used by Kenyan travel agencies. Results indicated that most of the travel agencies (50%) utilised the ‘SafariBookings.com’ platform, 20% of the travel agencies used Galileo, 40% of the travel agencies used Amadeus, while 12% used Sabre. None used Worldspan and ‘neXt’ systems. Table 4.10: Types of E-Commerce Intermediaries Used by Kenyan Travel Agencies E-Commerce Intermediaries Frequency Percentage Amadeus 22 40 Sabre 7 12 Galileo 11 20 Worldspan 0 0 neXt 0 0 SafariBookings.com 27 50
36 4.4.3 Statements on E-Commerce Application in Service Delivery The respondents were required to indicate their level of agreement with the following statements relating to e-commerce application in service delivery. The study established that most of the travel agencies provided customers with various self-service and delivery options (Mean = 4.31, Std. Dev = 0.47), most of the customers prefer booking directly with the agencies because it’s safer (Mean = 4.24, Std. Dev = 0.55), and that travel agencies’ rates are not as competitive when compared to online travel agencies such as ‘Booking.com’, (Mean = 4.24, Std. Dev = 0.64). These findings go hand in hand with the study findings by Pavlovic and Stanić (2015) which identified that people tend to place more trust in travel agencies when it comes to booking over the internet despite booking via OTAs being a cheaper option.
The study further established that through e-commerce, travel agencies’ market reach has increased (Mean = 4.11, Std. Dev = 0.74), customers have embraced other e-commerce providers (Mean = 4.15, Std. Dev = 0.68), and that e-commerce offers travel services closer to customers (Mean = 4.06, Std. Dev = 0.83). These findings concur with earlier studies’ findings which established that e-commerce has offered organizations and consumers flexibility in turn creating new distribution channels such as B2B, B2B2C, and C2C (Kamau, 2015; Martin-Fuentes & Mellinas, 2018; Chen, 2018). Technical difficulties in terms of reservation and payment was, however, identified as a challenge faced by the travel agencies (Mean = 4.17, Std. Dev = 0.69).
37 Table 4.11: Statements on E-Commerce Application in Service Delivery N Min Max Mean Std. Dev E-Commerce offers our travel services closer to 54 2.00 5.00 4.06 0.83 our customers Through e-commerce, our market reach has 54 3.00 5.00 4.11 0.74 increased Our travel agency provides customers with 54 4.00 5.00 4.31 0.47 various self-service and delivery options Our travel agency rates are not as competitive when compared to online travel agencies such as 54 3.00 5.00 4.24 0.64 ‘Booking.com’ Our customers have embraced other e-commerce 54 3.00 5.00 4.15 0.68 providers Our customers prefer booking through us because 54 3.00 5.00 4.24 0.55 it’s safer Our e-commerce systems suffer technical 54 2.00 5.00 4.17 0.69 difficulties in terms of reservation and payment
4.4.4 Pearson Correlation of E-Commerce Application in the Distribution of Travel Related Services on Kenyan Travel Agency Sustainability The study found a positive correlation between E-Commerce application in the distribution of travel related services (X1) and Kenyan travel agency sustainability (Y) as shown by correlation factor of 0.377; this positive relationship was found to be statistically significant as the significant value was 0.005 which is less than 0.05. These findings concur with the observation made by Wienclaw (2017) that businesses that were able to survive beyond the early 2000s were those that adapted the internet as one of the marketing channels.
38 Table 4.12: Correlations Kenyan travel agency E-Commerce application in sustainability the distribution of travel (Y) related services (X1) Kenyan travel Pearson 1 .377** agency Correlation sustainability Sig. (2-tailed) .005 (Y) N 54 54 E-Commerce Pearson .377** 1 application in the Correlation distribution of Sig. (2-tailed) .005 travel related N 54 54 services (X1)
4.4.5 Regression of E-Commerce Application in the Distribution of Travel Related Services on Kenyan Travel Agency Sustainability The focus of regression test one was to determine the influence of e-commerce application in the distribution of travel related services on Kenyan travel agency sustainability. To test the first regression, the index of Kenyan travel agency sustainability as index of dependent variable was regressed upon the identified sub-measures of e- commerce application in the distribution of travel related services as a composite of the independent variable.
4.4.5.1 Model Summary of E-Commerce Application in the Distribution of Travel Related Services on Kenyan Travel Agency Sustainability The R2 also called the coefficient of multiple determination, is the percent variance of the dependent variable explained uniquely by the independent variable (Cooper & Schindler, 2013). The model had a coefficient of determination (R2) of 0.142 which implied that 14.2% of the variation of Kenyan travel agency sustainability is explained by e-commerce application in the distribution of travel related services. Table 4.13: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .377a .142 .126 7.28132 a. Dependent Variable: Kenyan travel agency sustainability (Y) b. Predictors: (constant), E-Commerce application in the distribution of travel related services (X1)
39 4.4.5.2 ANOVAa From the ANOVA statistics, the study established that the regression model had a significance level of 0.005 which indicated that the data was ideal for making a conclusion on the population parameters as the significance (p-value) was less than 5%. The calculated value was greater than the critical value (8.626 > 2.49) which is an indication that e-commerce application in the distribution of travel related services has a significant impact on Kenyan travel agency sustainability. The significance was less than 0.05 indicating that the model was significant. Table 4.14: ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 457.346 1 457.346 8.626 .005b Residual 2756.917 52 53.018 Total 3214.263 53 a. Dependent Variable: Kenyan travel agency sustainability (Y) b. Predictors: (constant), E-Commerce application in the distribution of travel related services (X1)
4.4.5.3 Coefficientsa From the regression model obtained above, further e-commerce application in the distribution of travel related services while holding the other factors constant would promote Kenyan travel agency sustainability (Y) by a factor of 0.686. The findings concurred with Rensburg (2014) who found a strong positive correlation between the use of online e-commerce platforms and a firm’s competiveness. The scholar further elaborated on the opportunity for travel agencies to re-engineer their role in the distribution chain with the use of the internet. In addition, many experts have argued that B2B trade will reap the most benefits from the e-commerce trend (Mourya & Gupta, 2015). The equation is as follows: Y = 45.409 + 0.686 X1
40 Table 4.15: Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) 45.409 5.512 8.237 .000 E-Commerce application in the distribution of travel .686 .234 .377 2.937 .005 related services (X1) a. Dependent Variable: Kenyan travel agency sustainability (Y)
4.4.6 How E-Commerce Application Impacts on Service Delivery Some of the respondents indicated that e-commerce has enabled suppliers such as airlines and hotels to become more independent and that the suppliers are gradually reducing their dependence on the travel agencies. The results supported findings by Kibe and Ndivo (2015) which indicated that airlines introduced commission caps and increased the use of ICT in a bid to reduce costs and increase efficiency. This finding further highlights the eminent danger that TAs are exposed to if they don’t embrace e-commerce when it comes to booking accommodations and flights.
4.5 Impact of E-Commerce Application in Building Customer Loyalty on Kenyan Travel Agency Sustainability
4.5.1 Extent to Which E-Commerce Application Has Impacted Customer Loyalty The study sought to determine the extent to which e-commerce application has impacted customer loyalty. From the study findings, 37.0% of the respondents indicated to a very great extent, 33.3% of the respondents indicated to a great extent, 24.1 of the respondents were neutral on the effect that e-commerce had on customer loyalty, while 5.6% of the respondents indicated to a less extent. This implies that e-commerce application affects customer loyalty.
41 Table 4.16: Extent to Which E-Commerce Application Has Impacted Customer Loyalty E-Commerce Application on Customer Frequency Percentage Loyalty Less extent 3 5.6 Neutral 13 24.1 Great extent 18 33.3 Very great extent 20 37.0 Total 54 100.0
4.5.2 Statements on E-Commerce Application in Building Customer Loyalty
The respondents were required to indicate their level of agreement with the following statements relating to e-commerce application in building customer loyalty. The study established that travel agencies’ e-commerce systems provide information that meet customer needs (Mean = 4.39, Std. Dev = 0.49), e-commerce shortens the transaction time which improves customer service (Mean = 4.33, Std. Dev = 0.48), e-commerce service enables the delivery of promotional offers (Mean = 4.33, Std. Dev = 0.48), and that customers are involved in updating e-commerce systems (Mean = 4.20, Std. Dev = 0.63). These findings go hand in hand with the study findings by Rensburg (2014) which ellaborated on the important role that the internet plays in building relations with customers. In addition, the findings of this study concur with the study that Hua et al. (2018) conducted which established that companies in the travel and tourism industry can enhance customer loyalty by responding quickly to customer requests and maintaining a customer preference database.
The study further established that travel agencies’ e-commerce service meets customers’ needs (Mean = 4.19, Std. Dev = 0.70), e-commerce systems are effective in providing quality service during and after purchase (Mean = 4.15, Std. Dev = 0.71), e-commerce has enabled travel agencies to customize products and offer them to the mass market (Mean = 4.11, Std. Dev = 0.69), and that through e-commerce, browsers are converted into loyal customers (Mean = 4.00, Std. Dev = 0.75). All of the aforementioned factors further highlight the importance of e-commerce application in ensuring customer loyalty as was evident in the study conducted by McKinsey consultants Kierzkowski et al. (1996). In the study, Kierzkowski et al. higlighted five factors that marketers should
42 address in the digital age: attracting customers to the application, generating interest and participation, retaining users of the application, learn consumer preferences, and customizing the interaction and value delivery. Table 4.17: Statements on E-Commerce Application in Building Customer Loyalty N Min Max Mean Std. Dev
In our travel agency, e-commerce shortens the 54 4 5 4.33 0.48 transaction time which improves customer service
Our e-commerce system provides information 54 4 5 4.39 0.49 that meets customer needs
Through e-commerce, browsers are converted 54 3 5 4 0.75 into loyal customers E-Commerce service enables the delivery of 54 4 5 4.33 0.48 promotional offers In our travel agency, e-commerce has enabled us to customize our products and offer them to the 54 3 5 4.11 0.69 mass market
Our e-commerce service meets our customers’ 54 3 5 4.19 0.7 needs
Our customers are involved in updating e- 54 2 5 4.20 0.63 commerce systems Our e-commerce systems are effective in providing quality service during and after 54 3 5 4.15 0.71 purchase
4.5.3 Pearson Correlations of E-Commerce Application in Building Customer Loyalty on Kenyan Travel Agency Sustainability The table below displays the results of the correlation test analysis between the dependent variable (Kenyan travel agency sustainability) and the independent variable (E- Commerce application in building customer loyalty). The study found a positive correlation between e-commerce application in building customer loyalty (X2) and Kenyan travel agency sustainability (Y) as shown by correlation factor of 0.423; this positive relationship was found to be statistically significant as the significant value was 0.001 which is less than 0.05. The findings concur with the observation made by Dwikesumasari and Ervianty (2017) that a lot of people are now relying on OTA
43 applications as opposed to traditional travel agencies which signals a change in customer behavior. Table 4.18: Correlations Kenyan travel agency E-Commerce sustainability application in building (Y) customer loyalty (X2) Kenyan travel agency Pearson 1 .423** sustainability Correlation (Y) Sig. (2-tailed) .001 N 54 54 E-Commerce application Pearson .423** 1 in building customer Correlation loyalty (X2) Sig. (2-tailed) .001 N 54 54
4.5.4 Regression of E-Commerce Application in Building Customer Loyalty on Kenyan Travel Agency Sustainability The focus of regression test two was to determine the influence of e-commerce application in building customer loyalty on Kenyan travel agency sustainability. To test the first regression, the index of Kenyan travel agency sustainability as index of the dependent variable was regressed upon the identified sub-measures of e-commerce application in building customer loyalty as a composite of the independent variable.
4.5.4.1 Model Summary The model had a coefficient of determination (R2) of 0.179 which implied that 17.9% of the variation of Kenyan travel agency sustainability is explained by e-commerce application in building customer loyalty. Table 4.19: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .423a .179 .163 7.12485 a. Dependent Variable: Kenyan travel agency sustainability (Y) b. Predictors: (constant), E-Commerce application in building customer loyalty (X2) 4.5.4.2 ANOVAa From the ANOVA statistics, the study established that the regression model had a significance level of 0.001 which indicated that the data was ideal for making a conclusion on the population parameters as the significance (p-value) was less than 5%.
44 The calculated value was greater than the critical value (11.318 > 2.49) an indication that e-commerce application in building customer loyalty has a significant impact on Kenyan travel agency sustainability. The significance was less than 0.05 indicating that the model was significant. Table 4.20: ANOVAa Mean Model Sum of Squares df Square F Sig.
1 Regression 574.561 1 574.561 11.318 .001b Residual 2639.702 52 50.763 Total 3214.263 53 a. Dependent Variable: Kenyan travel agency sustainability (Y) b. Predictors: (constant), E-Commerce application in building customer loyalty (X2)
4.5.4.3 Coefficientsa From the regression model obtained above, further e-commerce application in building customer loyalty while holding the other factors constant would promote Kenyan travel agency sustainability (Y) by a factor of 0.726. The findings concurred with the study conducted by Lehto et al. (2006) which showed that 95 percent of web users searched the internet to gather travel related information. The study further showed that 93 percent of the web users visited tourism websites when planning vacations. Travel agencies therefore stand to benefit by utilizing e-commerce avenues. The equation is as follows: Y = 43.557 + 0.726 X2 Table 4.21: Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) 43.557 5.373 8.107 .000 E-Commerce application in .726 .216 .423 3.364 .001 building customer loyalty (X2) a. Dependent Variable: Kenyan travel agency sustainability (Y)
45 4.5.5 How E-Commerce Application Has Impacted Customer Loyalty It was established that a lot of consumers of travel related services have resorted to using OTA applications such as ‘Booking.com’ due to its ease of use. These finding confirm an observation made by Dwikesumasari and Ervianty (2017) that a lot of people have stopped going to traditional travel agencies and have instead opted for OTA applications due to the ease of downloading them from their smartphones.
4.6 Impact of E-Commerce Application in the Diversification of Products/Services on Kenyan Travel Agency Sustainability
4.6.1 Extent to which Product/Service Diversification is Important The study sought to establish the extent to which the travel agencies viewed product/service diversification as important. The findings show that most travel agencies (64.8%) considered product/service diversification of great importance, while 35.2% considered product/service diversification to be of very great importance. Table 4.22: Extent to Which Product/Service Diversification is Important Use of Product/Service Diversification Frequency Percentage Great extent 35 64.8 Very great extent 19 35.2 Total 54 100.0
4.6.2 Statement on E-Commerce Application in the Diversification of Products/Services The respondents were required to indicate their level of agreement with the following statements relating to e-commerce application in the diversification of products/services. From the findings, majority of the respondents agreed that e-commerce use has helped most of the travel agencies to offer competitive products/services (Mean = 4.44, Std. Dev = 0.63), competition from other travel agencies influences adoption of e-commerce (Mean = 4.44, Std. Dev = 0.50), adoption of e-commerce has led to expansion of our market place to national/international markets (Mean = 4.41, Std. Dev = 0.50), degree of adoption of e-commerce influences the competition intensity (Mean = 4.35, Std. Dev = 0.70). These findings go hand in hand with the study findings by Kibe and Ndivo (2015) which established that brick and mortar travel agencies have employed diversification strategies to remain relevant with the increased rivalry from OTAs which offer a
46 multitude of products. Weidenfeld (2018) in his study, however, asserted that for diversification strategies to succeed, TAs need to stimulate innovation rather than replication. The study further established that Competition Authority of Kenya needs to monitor possible anti-competitive behavior as the electronic market place evolves (Mean = 4.11, Std. Dev = 0.66) and that companies’ revenue streams have increased through diversification of products/services (Mean = 4.09, Std. Dev = 0.68). These findings concur with the recent regulation of Kenyan online businesses (Kenya Revenue Authority, 2019). In addition, the findings go hand in hand with recommendations Elhaj and Barakeh (2015) made which pointed out that TAs stand to benefit from diversifying across markets among other initiatives.
Table 4.23: Statements on E-Commerce Application in the Diversification of Products/Services N Min Max Mean Std. Dev Competition from other travel agencies 54 4.00 5.00 4.44 0.50 influences adoption of e-commerce Degree of adoption of e-commerce influences 54 3.00 5.00 4.35 0.70 the competition intensity Competition Authority of Kenya needs to monitor possible anti-competitive behavior as 54 3.00 5.00 4.11 0.66 the electronic market place evolves Adoption of e-commerce has led to expansion of our market place to national/international 54 4.00 5.00 4.41 0.50 markets E-Commerce use has helped our organization 54 3.00 5.00 4.44 0.63 to offer competitive products/services Our revenue streams have increased through 54 3.00 5.00 4.09 0.68 diversification of products/services
4.6.3 Pearson Correlation of E-Commerce Application in Product/Service Diversification on Kenyan Travel Agency Sustainability The table below displays the results of the correlation test analysis between the dependent variable (Kenyan travel agency sustainability) and the independent variable (e-commerce application in product/service diversification). The study found a positive correlation
47 between e-commerce application in product/service diversification (X3) and Kenyan travel agency sustainability as shown by correlation factor of 0.361; this positive relationship was found to be statistically significant as the significant value was 0.007 which is less than 0.05. These findings concur with the study conducted by Lalitha and Paul (2015). The two scholars opined that TAs need to understand how best to tailor products and services to customers’ different needs.
Table 4.24: Correlations Kenyan travel E-Commerce agency application in sustainability product/service (Y) diversification(X3) Kenyan travel agency Pearson Correlation 1 .361** sustainability Sig. (2-tailed) .007 (Y) N 54 54 E-Commerce Pearson Correlation .361** 1 application in Sig. (2-tailed) .007 product/service N 54 54 diversification (X3)
4.6.4 Regression of E-Commerce Application in Product/Service Diversification on Kenyan Travel Agency Sustainability The focus of regression test three was to determine the influence of e-commerce application in product/service diversification on Kenyan travel agency sustainability. To test the first regression, the index of Kenyan travel agency sustainability as index of dependent variable was regressed upon the identified sub-measures of e-commerce application in product/service diversification as a composite of the independent variable.
4.6.4.1 Model Summary The model had a coefficient of determination (R2) of 0.130 which implied that 13.0% of the variation of Kenyan travel agency sustainability is explained by e-commerce application in product/service diversification.
48 Table 4.25: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .361a .130 .114 7.33230 a. Dependent Variable: Kenyan travel agency sustainability (Y) b. Predictors: (constant), E-Commerce application in product/service diversification (X3)
4.6.4.2 ANOVAa From the ANOVA statistics, the study established the regression model had a significance level of 0.007 which indicated that the data was ideal for making a conclusion on the population parameters as the significance (p-value) was less than 5%. The calculated value was greater than the critical value (7.786 > 2.49), an indication that e-commerce application in product/service diversification has a significant impact on Kenyan travel agency sustainability. The significance was less than 0.05 indicating that the model was significant. Table 4.26: ANOVAa Mean Model Sum of Squares Df Square F Sig. 1 Regression 418.606 1 418.606 7.786 .007b Residual 2795.657 52 53.763 Total 3214.263 53 a. Dependent Variable: Kenyan travel agency sustainability (Y) b. Predictors: (constant), E-Commerce application in product/service diversification (X3)
4.6.4.3 Coefficientsa
From the regression model obtained above, further e-commerce application in product/service diversification while holding the other factors constant would promote Kenyan travel agency sustainability (Y) by a factor of 0.679. The findings concurred with Mourya and Gupta (2015) who established that with the use of ICTs capabilities, organizations such as TAs can be able to monitor and analyze consumers’ buying habits and interests so as to tailor their offers to suit consumers’ needs and keep an ongoing relationship with them. The equation is as follows: Y = 45.25 + 0.679 X3
49 Table 4.27: Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) 45.250 5.850 7.735 .000 E-Commerce application in .679 .243 .361 2.790 .007 product/service diversification (X3) a. Dependent Variable: Kenyan travel agency sustainability (Y)
4.6.5 Impact of E-Commerce Application in the Diversification of Products/Services It was established the TAs have been able to personalize products and services to suit customer needs with the use of the rich data collected from the transactions. These finding concurs with a study conducted by Moreno de la Santa (2018) who identified that personalization can be done effectively with the use of rich user data which can be obtained through monitoring and analysis.
4.7 Multiple Correlation
A multiple Pearson’s product-moment correlation coefficient was used to test the direction and magnitude of the relationship between the dependent and independent variables at 95% confidence level. The study found a positive correlation between Kenyan travel agency sustainability and e-commerce application in the distribution of travel related services as shown by correlation factor of 0.377. This positive relationship was found to be statistically significant as the significant value was 0.005 which was less than 0.05. The study also found a positive correlation between Kenyan travel agency sustainability and e-commerce application in building customer loyalty as shown by correlation coefficient of 0.423; the significant value was 0.001 which was less than 0.05. Lastly, the study found a positive correlation between Kenyan travel agency sustainability and e-commerce application in product/service diversification as shown by correlation coefficient of 0.361; the significant value was 0.007 which was less than 0.05.
50 Table 4.28: Multiple Correlation Kenyan travel E-Commerce E-Commerce E- Commerce agency application in application in application in sustainability the distribution building product/service of travel related customer diversification services loyalty
Kenyan Pearson . 1 travel Correlation agency Sig. (2-tailed) sustainability N 54 E-Commerce Pearson .377** 1 application Correlation in the Sig. (2-tailed) distribution of .005 travel related services N 54 54 E- Commerce Pearson .423** 1 .623** application Correlation in building Sig. (2-tailed) .001 0.001 customer loyalty N 54 54 54 E- Commerce Pearson .361** .238 .468* 1 application in Correlation product/service Sig. (2-tailed) .007 0.112 0.023 diversification N 54 54 54 54 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
4.8 Multiple Linear Regression
In this study, a multiple regression analysis was conducted to test the influence among predictor variables. As per the SPSS generated output presented in table below, the equation Y = β0 + β1X1 + β2X2 + β3X3 + ε becomes: Y= 44.421 + 0.686 X1 + 0.726 X2 + 0.679 X3. It was revealed that holding e-commerce application in the distribution of travel related services, e-commerce application in building customer loyalty, and e- commerce application in product/service diversification to a constant zero, Kenyan travel agency sustainability would be at 44.421. From the regression model obtained above, a unit change in e-commerce application in the distribution of travel related services holding the other factors constant would lead to a positive change in sustainability of a Kenyan travel agency by a factor of 0.686. A unit change in e-commerce application in building customer loyalty while holding the other factors constant would lead to a change
51 in sustainability of a Kenyan travel agency by a factor of 0.726. Finally, a unit change in e-commerce application in product/service diversification while holding the other factors constant would positively change performance in the sustainability of a Kenyan travel agency by a factor of 0.679.
The analysis was undertaken at a significance level of 5%. To determine whether the predictor variables were significant, a comparison was done between the obtained probability values and α = 0.05. If the probability values obtained were less than α, the predictor variables were significant otherwise it wasn’t. All the three predictor variables in this study were significant as their probability values were less than α = 0.05. Table 4.29: Multiple Linear Regression Model Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Beta Error (Constant) 44.421 5.457 8.140 .000 E-Commerce application in the distribution of .686 .234 .377 2.937 .005
travel related services (X1) 1 E-Commerce application .726 .216 .423 3.364 .001 in building customer loyalty (X2) E-Commerce application in product/service .679 .243 .361 2.790 .007
diversification (X3) a. Dependent Variable: Kenyan travel agency sustainability (Y)
52 4.9 Chapter Summary
This chapter presents the results and findings from the data collected with an aim of establishing the impact of e-commerce application on Kenyan travel agency sustainability. The study had a sample population of 58 respondents. From the sample, 54 respondents completed the questionnaires giving a response rate of 93.1%. The first section presents general information collected from the respondents. In the subsequent sections, the data is presented in line with the specific objectives of the study. It was noted that the use of e-commerce platforms aided in the distribution of travel related services; it also promoted customer loyalty, and product/service diversification in turn promoting Kenyan travel agency sustainability. Chapter five reviews the findings that aided in drawing conclusions and providing recommendations for future studies.
53 CHAPTER FIVE
5.0 DISCUSSION, CONCLUSIONS, AND RECOMMENDATIONS
5.1 Introduction
This chapter presents discussion, conclusions, and recommendations based on the result findings and this was done by comparing previous literature related to the impact of e- commerce application on travel agency sustainability. It has been organized based on the specific research objectives which sought to investigate, examine, and identify the impact of e-commerce on the distribution of travel related services, customer loyalty, and product/service diversification respectively.
5.2 Summary
The general objective of this study was to establish the impact of e-commerce application on Kenyan travel agency sustainability. The study was guided by three specific objectives which sought to sought to investigate, examine, and identify the impact of e-commerce on the distribution of travel related services, customer loyalty, and product/service diversification respectively all in relation to Kenyan travel agencies.
This study used a descriptive research design and the target population was top management representatives from each travel agency. The basis of concentrating on the top management was because they are more likely to be conversant with the day to day running of their organizations and more specifically, the impact of e-commerce adoption. TAs were selected using simple random sampling technique. This method allowed the researcher to give the population an equal chance of being selected. The top management representatives comprised CEOs, Operations Heads, Marketing Heads, Finance Heads, and IT Heads. The sample size of 59 respondents was arrived at based on the sampling method by Mugenda and Mugenda (2003), which states that a sample of between 10-30% of the population is an adequate representation of the target population.
Primary data was collected through semi-structured questionnaires. The analysis was conducted with the aid of Statistical Package for Social Sciences (SPSS). The data collected was presented in frequency distributions, percentages, and frequency tables for ease of understanding and analysis. Quantitative data was analyzed using descriptive and
54 inferential analysis. The inferential analysis was done using Pearson’s correlation to measure the strength and direction of the relationship between the variables. On the other hand, the qualitative data was analyzed using content analysis.
From Pearson’s correlation analysis to establish the relationship between the e-commerce application in the distribution of travel related services and Kenyan travel agency sustainability, the findings revealed a positive relationship (r = 0.377, p ≤ 0.005). This implied that an increase in e-commerce application in the distribution of travel related services will lead to an increase in Kenyan travel agency sustainability. The research further analyzed the relationship between the dependant variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in the distribution of travel related services). The results showed that the R2 value was 0.142 hence 14.2% of the variation of Kenyan travel agency sustainability is explained by the variation of e-commerce application in the distribution of travel related services. ANOVA analysis results of the regression between the dependent variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in the distribution of travel related services) at 95% confidence level showed that the calculated value was greater than the critical value (8.626 > 2.49). This was an indication that e- commerce application in the distribution of travel related services had a significant impact on Kenyan travel agency sustainability. The regression equation established that taking into account e-commerce application in the distribution of travel related services while holding the other factors constant would lead to the promotion of Kenyan travel agency sustainability (Y) by a factor of 0.686.
Pearson’s correlation analysis also revealed a positive correlation between e-commerce application in building customer loyalty and Kenyan travel agency sustainability (r = 0.423, p ≤ 0.001). Based on this positive correlation, an increase in e-commerce application in building customer loyalty would lead to an increase in Kenyan travel agency sustainability. Further analysis of the relationship between the dependant variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in building customer loyalty) showed that the R2 value was 0.179 hence 17.9% of the variation of Kenyan travel agency sustainability is explained by e-commerce application in building customer loyalty. ANOVA analysis results of the regression between the dependent variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in building customer loyalty) at 95%
55 confidence level showed that the calculated value was greater than the critical value (11.318 > 2.49). This was an indication that e-commerce application in building customer loyalty had a significant impact on Kenyan travel agency sustainability. The regression equation established that taking into account e-commerce application in building customer loyalty while holding the other factors constant would lead to the promotion of Kenyan travel agency sustainability (Y) by a factor of 0.726.
Lastly, Pearson’s correlation revealed a positive correlation between e-commerce application in product/service diversification and Kenyan travel agency sustainability (r = 0.361, p ≤ 0.007). Based on this positive correlation, an increase in e-commerce application in product/service diversification would lead to an increase in Kenyan travel agency sustainability. The research further analyzed the relationship between the dependant variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in the distribution of travel related services). The results showed that the R2 value was 0.130 hence 13.0% of the variation of Kenyan travel agency sustainability is explained by e-commerce application in product/service diversification. ANOVA analysis results of the regression between the dependent variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in product/service diversification) at 95% confidence level showed that the calculated value was greater than the critical value (7.786 > 2.49). This was an indication that e-commerce application in product/service diversification had a significant impact on Kenyan travel agency sustainability. The regression equation established that taking into account e- commerce application in product/service diversification while holding the other factors constant would lead to the promotion of Kenyan travel agency sustainability (Y) by a factor of 0.679.
5.3 Discussion
5.3.1 Impact of E-Commerce Application in the Distribution of Travel Related Services on Kenyan Travel Agency Sustainability The Pearson’s correlation analysis revealed a positive relationship between e-commerce application in the distribution of travel related services and Kenyan travel agency sustainability (r = 0.377, p ≤ 0.005). It therefore implied that an increase in e-commerce application in the distribution of travel related services will lead to an increase in Kenyan travel agency sustainability. Similar findings were recorded by Kibe and Ndivo (2015)
56 who identified that integrated platforms have created an avenue for travel agencies to market and differentiate themselves from online competition by providing value added benefits to their customers.
Further analysis was done to determine the relationship between the dependant variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in the distribution of travel related services). The results showed that the R2 value was 0.142 hence 14.2% of the variation of Kenyan travel agency sustainability is explained by the variation of e-commerce application in the distribution of travel related services. The research that was done on 438 Taiwan travel agencies found that the agencies generally regard the internet as an effective tool for their business (Bennett & Lai, 2005). The TAs were thus enlightened on the importance of embracing the internet and incorporating its tools in the distribution of travel related services so as to ensure sustainability. Rensburg (2014) concurs with these findings by opining that the internet can be viewed as a catalyst and an opportunity for TAs to re-engineer their role in the distribution chain. There are various ways in which TAs can re-engineer their role in the distribution chain as was earlier elaborated in this paper. Re-intermediation is evident through the development of global distribution systems (GDS) such as Sabre, Amadeus, Galileo, and Worldspan (Granados et al., 2007; Kamau, 2015). Most recently, travel agencies in Kenya and Africa as a whole have started using ‘SafariBookings.com’ which acts as a medium for travel agencies to sell their safari packages online. All these examples demonstrate the online opportunities that TAs could use to become sustainable.
The first regression test results established that taking e-commerce application in the distribution of travel related services into account while holding other factors constant would lead to a variation of Kenyan travel agency sustainability by 0.142. This finding concurs with the observation made by Wienclaw (2017) that businesses that were able to survive beyond the early 2000s were those that adapted the internet as one of the marketing channels. In addition, Mourya and Gupta (2015) opine that business to business trade will reap the most benefits from the e-commerce trend. Through the use of e-commerce, the TAs will be able to re-define their role in the distribution chain (Bennett & Lai 2005).
Due to the heightened competition in the travel and tourism industry, online capabilities could therefore be extremely helpful in attracting and retaining customers. As was
57 suggested by Dilts and Prough (2002), travel agencies need to transform their traditional ‘brick and mortar’ services to ‘hybrid click and mortar’ services.
5.3.2 Impact of E-Commerce Application in Building Customer Loyalty on Kenyan Travel Agency Sustainability From Pearson’s correlation analysis, the study found a positive correlation between e- commerce application in building customer loyalty and Kenyan travel agency sustainability (r = 0.423, p ≤ 0.001). This finding implied that an increase in e-commerce application in building customer loyalty would lead to an increase in Kenyan travel agency sustainability. Similar findings were recorded by Hua et al. (2018) who argued that companies in the travel and tourism industry can enhance customer loyalty by responding quickly to customer requests and maintaining a customer preference database. To further elaborate on the same, Kierzkowski et al. (1996) highlighted five factors that should be addressed by marketers in this digital age: attracting customers to the application, generating interest and participation, retaining users of the application, learning the consumers’ preferences, and customizing the interaction and value delivery. A quick response rate and maintaining of a customer preference database can be best achieved with the use of ICTs in turn signifying the importance of embracing e- commerce in order to survive in the industry. In addition, Dwikesumasari and Ervianty (2017) observed that a lot of people have stopped going to traditional TAs and have instead opted for OTA applications. This finding further empasizes the importance of adopting ICTs.
Further analysis of the relationship between the dependant variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in building customer loyalty) was done. The results showed that the R2 value was 0.179 hence 17.9% of the variation of Kenyan travel agency sustainability is explained by e- commerce application in building customer loyalty. This finding concurs with an observation made by Nescott (2012) that internet usage has increased at a growth rate of 20% since 1998. Morover, the study conducted by Lehto et al. (2006) showed that 95% of web users searched the internet to gather travel related information. The study further showed that 93% of the web users visited tourism websites when planning vacations. These findings highlight the importance of e-commerce application in building customer loyalty, especially in this digital age.
58 The second regression test established that taking into account e-commerce application in building customer loyalty while holding the other factors constant would lead to the promotion of Kenyan travel agency sustainability (Y) by a factor of 0.726. These finding concurs with the observation made by Chang et al. (2015) that the tools that e-commerce provides play a vital role in retaining customers. E-Commerce will therefore play an important role in reinforcing a travel agency’s competitive advantage through customer retention. As was earlier stated in this paper, businesses have shifted to CRM which involves attracting, maintaining, and enhancing customer relationships (Rahimi et al., 2017); the best way to do all these tasks is through the utilization of ICTs (Rensburg, 2014).
To further emphasize on the importance of e-commerce application in building customer loyalty, the study conducted by Kierzkowski et al. (1996) established that travel services are classified under emotion based products/services that require interaction during the buying process. In addition, the travel related services are regarded among the products/services where the internet was first accepted. As was earlier highlighted in this paper, the first internet travel website (Internet Travel Network) was launched in 1995 and this was made possible due to the accessibility of the internet in the late 1990s (Granados et al., 2007; Dixit & Sinha, 2016). In order to leverage on the emotion based aspect of travel services and the travel industry’s compatibility with the internet, TAs are best placed to build customer loyalty by balancing between the digital and human touch (Moreno de la Santa, 2018).
5.3.3 Impact of E-Commerce Application in the Diversification of Products/Services on Kenyan Travel Agency Sustainability Lastly, Pearson’s correlation revealed a positive correlation between e-commerce application in product/service diversification and Kenyan travel agency sustainability (r = 0.361, p ≤ 0.007). Based on this positive correlation, an increase in e-commerce application in product/service diversification would lead to an increase in Kenyan travel agency sustainability. This finding confirms the recommendation by Lalitha and Paul (2015), that travel agencies need to tailor products/services to customers’ needs, due to the turbulence in the travel and tourism industry. To further stress on the importance of e- commerce application in the diversification of products/services, Rensburg (2014) highlighted a study commissioned by Google which indicated that most travelers seek value and engage in comparison shopping.
59 Further analysis of the relationship between the dependant variable (Kenyan travel agency sustainability) against the independent variable (e-commerce application in the distribution of travel related services), showed that the R2 value was 0.130 hence 13.0% of the variation of Kenyan travel agency sustainability is explained by e-commerce application in product/service diversification. This finding confirm an observation by Moreno de la Santa (2018) that TAs need to have the right infrastructure in order to make customer insight actionable. In addition, Lalitha and Paul (2015) opined that the TAs need to understand how best to tailor products/services to customers’ different needs. Tailoring of products/services can be effectively done with the use of ICTs.
The third regression equation established that taking into account e-commerce application in product/service diversification while holding the other factors constant would lead to the promotion of Kenyan travel agency sustainability (Y) by a factor of 0.679. This finding further stresses the importance of TAs having the right infrastructure. In addition, it confirms an observation by Elhaj and Barakeh (2015) who found that TAs could benefit from value addition, diversification across markets, and customer retention initiatives. However, Moreno de la Santa (2018) opined that there needs to be a balance of artificial intelligence and human touch.
A challenge is however eminent with the emergence of new business models, more specifically the OTAs, which provide diversified products (Pavlovic & Stanić, 2015). As Rensburg (2014) explained, the emergence of OTAs was in 1995 when they joined the fray to tap into the lucrative travel and tourism industry. An example of an OTA that has been widely mentioned in this paper is Airbnb which is evolving to become a platform of experiences with the launching of its tours and activities division in November 2016. The launch of its new division was in a bid to position itself as the only brand a consumer will ever need, for every part of their travel (Moreno de la Santa, 2018). Moreno de la Santa (2018) further observed that these OTAs offer world class customer service through the digital space which has led to a change in consumption behavior. This trend has been described as individualism whereby consumers demand a more personalized approach (Nescott, 2012).
Due to the change in the behavior of customers, Lalitha and Paul (2015) recommend tailoring the products/services to customers’ needs. Individualization of product/service offering can be easily achieved with the use of ICTs. This will however require TAs to
60 differentiate themselves from the competition. According to Weidenfeld (2018), replication of strategies used by the OTAs will not make the TAs competitive.
5.4 Conclusions
5.4.1 Effect of E-Commerce Application in the Distribution of Travel Related Services on Kenyan Travel Agency Sustainability Kenyan travel agencies are experiencing both negative and positive effects of e- commerce adoption. Negative effects are due to the emergence of OTAs such as ‘Booking.com’ which continues to threaten travel agencies’ dominance. There are, however, positive effects of e-commerce adoption such as the new B2B2C platforms such as ‘SafariBookings.com’ which are now enabling TAs to market their safaris efficiently. These new platforms complement the existing platforms such as Amadeus which have been used by TAs over the years.
5.4.2 Effect of E-Commerce Application in Building Customer Loyalty on Kenyan Travel Agency Sustainability The role of the internet is becoming more important as customers now have more options to search for their travel related services. Travel agencies will therefore need to focus on ways in which they can differentiate themselves from the competition with an aim of ensuring there’s e-customer satisfaction. In addition, retention of customers will require CRM which focuses on attracting, maintaining, and enhancing customer relationships.
5.4.3 Effect of E-Commerce Application in the Diversification of Products/Services on Kenyan Travel Agency Sustainability Kenyan TAs have been able to survive in the digital age, most of them, however, agree that they need to have the right infrastructure to make customer insight actionable. ICTs have for instance led to the development of new business models which have led to a change in consumer behavior. This trend has been described as individualism which is becoming a social structure of the modern society. An example of a new business model, as was highlighted, is Airbnb which is a P2P platform that has enabled individuals to rent out their personal homes/rooms. This has led to diversification of products/services in the market.
61 5.5 Recommendations
5.5.1 Recommendations for Improvement 5.5.1.1 Effect of E-Commerce Application in the Distribution of Travel Related Services on Kenyan Travel Agency Sustainability Kenyan travel agencies need to embrace the new B2B2C platforms that will enable them to interact with e-customers. There has been a rise of such platforms with the most recent being ‘SafariBookings.com’. There are also other platforms such as ‘Safarigo.com’, which despite being in its formative stage, will enable travel agencies to connect with prospective customers in China. The travel agencies therefore need to be on the lookout for new platforms in the market that would enable them to re-engineer their role in the distribution chain.
5.5.2.2 Effect of E-Commerce Application in Building Customer Loyalty on Kenyan Travel Agency Sustainability Kenyan travel agencies need to continuously monitor and analyze consumers’ buying habits and interests so as to tailor offers to suit consumers’ needs while at the same time keeping an ongoing relationship. In addition, Kenyan travel agencies stand a better chance of becoming sustainable if they balance artificial intelligence with human touch based on this study’s findings.
5.5.3.3 Effect of E-Commerce Application in the Diversification of Products/Services on Kenyan Travel Agency Sustainability Kenyan TAs need to be wary of the OTAs while at the same time ensuring that they innovate, rather than replicate the strategies used by their competitors. By identifying the market with the best potential, the TAs also need to tailor the products/services suitable for the market. To effectively tailor the products/services, ICT capabilities can be used to monitor and analyze consumer habits.
5.5.2 Recommendations for Future Studies The study focussed on establishing the impact of e-commerce application on Kenyan travel agency sustainability. A similar study should be conducted in a different geographic context as the findings may differ. In addition, the target respondents of this study were top management executives. There is, however, a need to seek opinions from consumers of travel related products/services.
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69 APPENDICES
Appendix I: Research Permit
70 Appendix II: Cover Letter
Arnold Sawe United States International University-Africa P.O. Box 14634-00800 Nairobi, Kenya +254-728 828 024 Email: [email protected]
Dear Respondent,
I am a Masters in Business Administration (MBA) student at United States International University-Africa. In partial fulfillment of the requirements for the degree, I am carrying out a research project entitled “Impact of E-Commerce Application on Kenyan Travel Agency Sustainability”.
You have been selected as one of the lucky respondents of this study. The results of this study hope to enable travel agencies and players in the service industry in general to come up with effective ways to remain sustainable in the turbulent business environment. Completing the questionnaire will take 15-20 minutes.
I look forward to your acceptance for an honest and objective interview session. The information that you will be giving through this questionnaire is confidential and will only be used for the purpose of this study.
Thank you in advance.
Yours Sincerely,
71 Appendix III: Questionnaire
This questionnaire is divided into five sections. Section A will be used to obtain general information about yourself and the organization you work for. Section B will be used to obtain information on e-commerce application in Kenyan travel agencies. Section C will be used to obtain information on e-commerce application in service delivery. Section D will be used to generate information on e-commerce application in building customer loyalty. Section E will obtain information relating to e-commerce application in the diversification of products/services.
NB: The information obtained will be treated in the strictest confidence.
Your assistance in completing this questionnaire will be highly appreciated.
Section A: General Information
1. What is your gender? 4. What is your current role in the agency?
Male Female CEO Finance Head Operations Head IT Head Marketing Head
2. What is your highest level of education? 5. How long have you served in the current position?
PhD Masters Bachelors Less than 5 years 6-10 years Higher Diploma Diploma 11-15 years 16-20 years Other, please specify: ______ Above 20 years
3. How long have you worked in the agency? 6. How long has the travel agency been in operation?
Less than 5 years 6-10 years Less than 5 years 6-10 years 11-15 years 16-20 years 11-15 years 16-20 years Above 20 years Above 20 years
72 Section B: E-Commerce Application in Kenyan Travel Agencies 7. To what extent does e-commerce enhance sustainability in your organization? Not at all Less extent Neutral Great extent Very great extent
The following statements reflect e-commerce
application in Kenyan travel agencies
Strongly (1) Disagree (2) Disagree (3) Neutral (4) Agree Strongly (5) Agree E-Commerce Opportunities to Agencies 8. E-Commerce has forced our travel agency to adopt various strategies to remain competitive 9. Our travel agency enjoys much lower overheads with the use of e-commerce E-Commerce Challenges to Agencies 10. Our travel agency has not fully moved to e- commerce business 11. Our technical capabilities are limited E-Commerce Opportunities to Customers 12. Our customers don’t experience challenges when making bookings with us through e- commerce E-Commerce Challenges to Customers 13. Customers are reluctant to provide their personal information over the internet E-Commerce Use for Travel Activities in Kenya 14. Few companies use e-commerce in the travel and tourism industry
15. How else does e-commerce use impact Kenyan travel agencies? …………………………………………………………………………………………
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73 Section C: E-Commerce Application in Service Delivery 16. To what extent does e-commerce application affect your service delivery? Not at all Less extent Neutral Great extent Very great extent
17. Which e-commerce intermediaries does your organization use? (tick all applicable) Amadeus Sabre Galileo Worldspan neXt SafariBookings.com Other, please specify: ______
The following statements reflect the impact of (1)
e-commerce application in the distribution of travel related services on Kenyan travel
agency sustainability
Strongly Disagree (2) Disagree (3) Neutral (4) Agree Strongly (5) Agree E-Commerce Opportunities to Agencies 18. E-Commerce offers our travel services closer to our customers 19. Through e-commerce, our market reach has increased 20. Our travel agency provides customers with various self-service and delivery options E-Commerce Challenges to Agencies 21. Our travel agency rates are not as competitive when compared to online travel agencies such as ‘Booking.com’ 22. Our customer s have embraced other e- commerce providers E-Commerce Opportunities to Customers 23. Our customers prefer booking through us because it’s safer E-Commerce Challenges to Customers 24. Our e-commerce systems suffer technical difficulties in terms of reservation and payment
25. How else does e-commerce application impact service delivery? …………………………………………………………………………………………
…………………………………………………………………………………………
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74 Section D: E-Commerce Application in Building Customer Loyalty 26. To what extent does e-commerce application impact customer loyalty? Not at all Less extent Neutral Great extent Very great extent
The following statements reflect the impact of e-commerce application in building customer
loyalty on Kenyan travel agency sustainability
Strongly (1) Disagree (2) Disagree (3) Neutral (4) Agree Strongly (5) Agree E-Commerce and Service Quality 27. In our travel agency, e-commerce shortens the transaction time which improves customer service 28. Our e-commerce system provides information that meets customer needs 29. Through e-commerce, browsers are converted into loyal customers 30. E-Commerce service enables the delivery of promotional offers 31. In our travel agency, e-commerce has enabled us to customize our products and offer them to the mass market E-Commerce and Customer Loyalty 32. Our e-commerce service meets our customers’ needs 33. Our customers are involved in updating e- commerce systems 34. Our e-commerce systems are effective in providing quality service during and after purchase
35. Indicate in other ways how e-commerce application has impacted customer loyalty …………………………………………………………………………………………
…………………………………………………………………………………………
…………………………………………………………………………………………
…………………………………………………………………………………………
…………………………………………………………………………………………
75 Section E: E-Commerce Application in the Diversification of Products/Services 36. To what extent does your organization view product/service diversification as important? Not at all Less extent Neutral Great extent Very great extent
The following statements reflect the impact of e-commerce application in the diversification of products/services on Kenyan travel agency
sustainability
Strongly (1) Disagree (2) Disagree (3) Neutral (4) Agree Strongly (5) Agree E-Commerce Adoption and Competition 37. Competition from other travel agencies influences adoption of e-commerce 38. Degree of adoption of e-commerce influences the competition intensity 39. Competition Authority of Kenya needs to monitor possible anti-competitive behavior as the electronic market place evolves Product/Service Diversification and Its Influence on Business Performance 40. Adoption of e-commerce has led to expansion of our market place to national/international markets 41. E-Commerce use has helped our organization to offer competitive products/services 42. Our revenue streams have increased through diversification of products/services
43. Indicate other ways through which e-commerce application has impacted diversification of products/services …………………………………………………………………………………………
…………………………………………………………………………………………
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…………………………………………………………………………………………
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76