An Analysis of the Business Process Reengineering (BPR) Implementation Practices and Their Impact on Customer Satisfaction in the Banking Sector

AJM Volume 4 Issue 1 2019

An Analysis of the Business Process Reengineering (BPR) Implementation Practices and their Impact on Customer Satisfaction in the Banking Sector

Forbes Makudza, Gibson Muridzi & Darlington Chirima Manicaland State University of Applied Sciences, Fernhill, Zimbabwe

Abstract The study analyzed the factors that affect the effective implementation of Business Process Reengineering (BPR) in the banking sector and how that affects customer satisfaction. Guided by a deductive approach, a research conceptual model was developed with four BPR implementation determinants which were measured against Customer Satisfaction. The identified determinants of effective BPR implementation were Change Culture, Information Technology, Employee Commitment and Financial Resources. Statistical hypothesised associations were formulated and literature was analysed to substantiate the validity of the study variables and to paint a clear theoretical gap which the study filled. Data was collected using a self-administered email survey from 11 banks which were in the sampling frame. A quantitative, positivist orientation was followed as the study collected data using a structured questionnaire. The study results depicted the main challenges that were detracting the effective implementation of BPR in traditional banks in Zimbabwe. The study found out that BPR implementation explains Customer Satisfaction by 47%. The banking sector was consequently recommended to enhance an agile culture, reconsider their financial investment policies and revamp their information technology hardware and software so as to enhance agile BPR implementation practices which will improve customer experience and satisfaction. Keywords: Business Process Reengineering, Customer Satisfaction, Change Culture, Financial Resources, Information Technology, Employee Commitment. JEL Classification: M15, M31 Paper Classification: Research Paper

Introduction Increased competition and sophistication of customers require that companies rethink and design processes, procedures, products and services that are cost-efficient and effective with the aid of technology to remain competitive and profitable. Martin (2011) argues that part of the solution lies in redesigning, reconfiguring, automating and standardising processes. Fasna and Gunatilake (2019) opined that the design and implementation of sound business processes are important for business performance given the volatility of the business environment.

ADMAA 64 Amity Journal of Marketing Volume 4 Issue 1 2019 AJM The Zimbabwean banking sector was under threat from upcoming innovative fintech companies and new competitors. Without a good understanding of BPR implementation, banks would not derive the benefits that are earned from effective BPR resulting in loss of both customers and market share to competition and upcoming disruptive banks. For instance, as at 31 December 2018, the total banking institutions in Zimbabwe were 19, yet the total financial services providers under the Reserve Bank of Zimbabwe (RBZ) supervision including banks amounted to 226 (RBZ, 2019). The increase in the number of other financial service providers depict that commercial banks were no longer considered as exclusive suppliers of banking services and products, other players had come into that space, hence, the need to re-engineer and offer competitive services. Oladimeji, Akingunola and Sanusi (2017), indicate that the main problem of BPR does not lie in merely understanding what BPR is all about, but lies on how BPR is implemented. According to Hammer and Champy (2009) as quoted by Osano and Okwena (2015), BPR projects have a failure rate of 70% due to weak implementation. With such a high and alarming failure rate, Guimaraes and Chair add that 65% of managers claim that they were reengineering their processes yet in actual fact, they were not. Surprisingly too, Hussein and Dayekh (2014) found out that out of 36 bank branches considered in their study, only 58.8% of employees were aware of the BPR projects of their bank, the remaining 44.2 were not. These disturbing statistics lead to the questions; what are the factors that can influence the successful implementation of BPR projects and how can they affect customer satisfaction? This study, therefore, aimed to address these.

Objectives of the Study The key research objectives were; i. To identify the determinants of successful BPR implementation. ii. To assess the effect of BPR determinants on BPR implementation. iii. To analyse the impact of BPR implementation on customer satisfaction. Literature Analysis

BPR and its Implementation Hammer and Champy (2009) define BPR as the fundamental rethinking and radical redesign of business processes to achieve dramatic improvements in critical contemporary measures of performance, such as cost, quality, service, and speed. The aspect of radical thinking was also upheld by Mekonnen (2019) who notes that BPR is a radical process of developing a new system from scratch. BPR calls for radicalization of the core business processes to achieve dramatic improvements in business performance (Amanquah & Adjei, 2013). A rather divergent approach was taken by Hussein and Dayekh (2014) who indicated that in BPR there is no need for radical, complete turnaround moves. Rather, companies and banks should consider BPR as an ongoing process not a once-off event. The reasoning of Hussein and Dayekh (2014) was based on the notion that process improvement is continuous, the only time the business stops process improvements is that time when the business collapses. Similarly, Zaini and Saad (2019) view BPR as an approach for improving and controlling already existing business processes, not an abrupt change of complete eradication of a previous system and replacing it with a new, unrelated system.

65 Amity Journal of Marketing ADMAA AJM Volume 4 Issue 1 2019 Ab-llah (2011) also highlighted that BPR is a by-product of business innovation. Therefore, for businesses to remain viable, there is need for continuous improvements. Hence, BPR has a starting point but it does not have an ending point. Guimaraes and Chair (2018) referred to this situation as an infinitive process of BPR. Guimaraes and Chair (2018) suggested that the process is infinite because it evolves as companies do not develop new systems but update existing systems. Hammer and Champy (2009) pointed out that there are three kinds of businesses that undertake re-engineering: those that find themselves in deep trouble, those that are not in trouble but whose management can see trouble coming, and those that are in peak condition and see an opportunity to develop a lead over their competitors. Hammer and Champy’s (2009) rationale was based on the aspect that BPR is implemented to either tap into an existing opportunity or to avoid an impending threat. Osano and Okwena (2015) reiterated that BPR implementation is driven by a business vision that can be broken down into specific business objectives like a reduction of costs, improvement of turnaround time and output quality. Zaini and Saad (2019) also indicated that environmental changes such as customer preference changes and advent of new technology can also drive the implementation of BPR. The need for organisational competitiveness and wining competition may also contribute to the need for BPR implementation (Bradley, Browne, Jackson & Jagdev, 2019).

The Concept of Customer Satisfaction Gronroos (2001) viewed customer satisfaction as a consumer’s fulfillment response. Rogers (2018) adds that customer satisfaction is a judgment that a product or service feature, or the product or service itself, provides a pleasurable level of consumption. The main driving force for customer satisfaction was highlighted by Sidikat (2008) as product or service quality. Therefore, customer satisfaction is an indication that customers are intrigued by the company’s offering. Using the disconfirmation paradigm by Parasuraman, Zeithaml and Malhotra (2005), customer satisfaction can be understood by measuring the difference between customers’ expectations of service and the perception of the service received. If customers’ expectation outweighs perception, it leads to customer dissatisfaction and consumer perception of poor product or service. However, if consumers’ perception of the service rendered outweighs expectations of the service, this leads to customer satisfaction and it is an indication of quality services. Odeny (2016) noted that customer satisfaction is an applied term that determines how products and services supplied by a company meet or surpass customer expectation. It is an evaluation of emotions, reflecting the degree to which the customer believes the service provider evokes positive feelings. Customer satisfaction can therefore reflect the degree to which a consumer believes that the possession or use of a service evokes positive feelings.

Role of BPR Implementation on Customer Satisfaction in the Banking Sector As a business system and process, BPR reforms and transforms business operations to achieve improved performance in the banking sector. According to Amanquah and Adjei (2013), BPR implementation helped the National Commercial Bank of Jamaica to achieve a return on investment (ROI) of more than 500%. Similarly, Amanquah and Adjei (2013) added that BPR enabled GTO Bank Inc. to move its net profit from the red to nearly $500,000. This was accompanied by a 9% increase in gross sales along with a 33% decrease in total operating and administrative costs. Osano and Okwena (2015) contributed that through effective implementation of BPR, companies can become more competitive and gain an edge over their competitors thereby

ADMAA 66 Amity Journal of Marketing Volume 4 Issue 1 2019 AJM satisfying customers. Referencing to the banking sector in Kenya, Osano and Okwena (2015) noted that banks that implemented BPR faster were more responsive to customers and their levels of agility were unmatched to those that took time to change. In essence, the result was the loss of business and market share for Kenyan banks that took time to reengineer. BPR is also a tool that enhances business competitiveness through enhanced customer satisfaction and experience (Riyanto, Primiana, Yunizar & Azis, 2018). Private Banks in Ghana are more active in BPR than government banks. That drove the private banks in Ghana to grow their operations and attract more customers. According to Guimaraes and Chair (2018) the Government of Ghana lost significant market share due to delays in BPR to 21.36% which showed a 6% decline, whilst institutional and individual banks increased their market share to 78.64%. Guimaraes and Chair (2018) attributed the increase in business growth to effective implementation of BPR and the subsequent satisfaction of customers. Acharya (2015) suggested that the Andhra Bank benefited a lot from BPR over the past two decades ending 2015. Acharya (2015) noted that BPR in the Andhra Bank led to the reduction of the processing time in business operations and it strengthened the bank. Over and above, BPR was found to be instrumental as customers and employees favoured its implementation. That led to the double benefits of customer satisfaction and employee satisfaction. BPR is at the centre of the banking sector’s success. Sudha and Kavita (2019) suggested that with the advent of mobile application systems, BPR enhances convenience for customers and offers ubiquitous business environments. This is true even in Zimbabwe where several banks developed mobile banking applications such as the Square mobile application for Steward Bank, the Nedbank Mobile app and the CBZ Touch Mobile Application (Technozim, 2019). Through BPR, banks are now operational on social commerce platforms using web 2.0. For instance, Steward Bank introduced WhatsApp banking through BPR, a platform called Sosholoza Banking (Steward Bank, 2019).

Determinants/ Drivers of BPR Implementation The study analysed various extant literature and theories which relate to BPR implementation determinants. The Resource Based Theory posits that the main determinant of BPR implementation is the availability of resources (Musya, 2013). When the organisation does not have enough resources, BPR implementation will flop. Musya (2013) as quoted by Oladimeji, Akingunola and Sanusi (2017) indicated that businesses must strategically identify and utilize resources of a firm in order to sustain competitive advantage through BPR. Contrary to the resource-based orientation, the theory of BPR Fit suggests that for BPR to be effective, there should be the fit between an organization’s BPR strategy and its determinants which include; structure, technology, culture, management processes, and individual skills and roles (Mulilima, 2018). Conversely, Osano and Okwena (2015) suggest that BPR implementation determinants are four, namely; Management Commitment, Communication of Change, Processes and Systems Management, and Monitoring and Evaluation. These four determinants act as antecedents for BPR performance. Oladimeji et, al. (2017) refined the Osano and Okwena (2015)’ BPR Determinant Model by highlighting some key fundamental aspects of BPR. For instance, Oladimeji et, al. (2017) over- emphasised the role of information technology as a key factor that determines the successful implementation of BPR. This factor was silent in the former model. Oladimeji et, al. (2017) introduced six drivers of BPR effective implementation. These drivers are: information technology, top management commitment to change, employee training, less bureaucratic structure,

67 Amity Journal of Marketing ADMAA AJM Volume 4 Issue 1 2019 change culture and adequate financial resources. According to Oladimeji et, al. (2017), for BPR implementation to be successful, the six drivers are congruential. Oladimeji et, al. (2017) further indicated that failure of BPR implementation can be explained by these determinants.

Study Hypotheses The following were the alternate hypotheses for the study; H1: Change Culture positively impacts BPR implementation. H2: Information Technology positively impacts BPR implementation. H3: Employee Commitment positively impacts BPR implementation. H4: Financial Resources positively impacts BPR implementation. H5: BPR positively impacts customer satisfaction.

The Conceptual Model Using the deductive approach, Figure 1 presents the conceptual model, which was developed by consolidating the determinants of BPR implementation and linking them to customer satisfaction. The Oladimeji et, al. (2017) and Osano and Okwena’s (2015) theories were overarching and support the study model.

Figure 1: The Conceptual Framework for Studying the Association Between BPR Implementation Determinants and Customer Satisfaction. Source: Adapted from Okwena (2015) and Oladimeji et, al. (2017) Change Culture Change culture refers to the responsiveness and readiness of the organisation to move from the status quo to a new disposition (Habib, 2013). Oladimeji et, al. (2017) noted that a collaborative culture is vital for BPR implementation. It starts with top management support and is cascaded downwards to all employees. Culture is how things are done in an organisation, and how things are done affect how BPR is implemented (Sudha & Kavita, 2019). It reflects organisational

ADMAA 68 Amity Journal of Marketing Volume 4 Issue 1 2019 AJM behaviour, attitudes and motives. Organisations with a changing culture are highly adaptive and agile. They are more likely to implement BPR faster, effectively and efficiently as compared to organisations that have a sluggish organisational culture (Habib, 2013). Change culture is determined by top management change leadership, organisational change commitment, organisational involvement and change communication (Oladimeji et, al.,2017). It is hypothesised in the study that if the organisation has a sluggish culture, employee resistance to change is more likely to affect the effectiveness of BPR projects and the pace at which BPR is implemented in the organisation.

Information Technology Information technology refers to the extent to which companies use modern systems (especially computers and telecommunications) for storing, retrieving, and sending information which is necessary for BPR implementation (Martin, 2011). Information technology relates to both hardware and software (Zaini & Saad, 2019). It is hypothesised that where effective information technology is applied, BPR implementation is more likely to be enhanced. Information technology offers facilitating conditions for BPR to take off effectively (Bradley, et al., 2019). The Model of BPR fit places information technology at the centre of all BPR determinants because it intertwines all other determinants of BPR (Mulilima, 2018).

Employee Commitment BPR is implemented by employees of the organisation. The successful implementation of BPR thus largely depends on the commitment of employees towards BPR. Employee commitment is determined by employee training, employee skills, employee motivation and employee confidence (Oladimeji et, al., 2017). The backbone of employee commitment is the ability of the organisation to communicate the BPR change vision and objectives to them timeously (Riyanto, Primiana, Yunizar & Azis, 2018). Employees act as new system users and system developers. Organisations with highly committed employees are more likely to implement BPR faster and effectively than those organisations without such employees (Keya, 2015).

Financial Resources This is a variable for the study that emerged from the Resource Based Theory, and was upheld by Okwena (2015) and Oladimeji et, al. (2017). For organisations to effectively implement BPR, there should be enough financial muscle for it to hire skilled labour, to acquire materials and technologies required as well as to train other employees. If the organisation lacks the financial ability and financial will to fund BPR projects, the BPR initiative is likely to fail. Financial resources are determined by the availability of funds, the timing when funds are availed, the management and evaluation of financial resources (Okwena, 2015; Oladimeji et, al., 2017).

Customer Satisfaction In the conceptual model, customer satisfaction is a judgment that the process of receiving the service or service feature, or service itself, provides a pleasurable level of consumption. The main driving force for customer satisfaction in this study was the process of receiving the service. To that end, customer satisfaction is determined by cycle time, turnaround time, convenience, ubiquity and timeliness of service (Okwena, 2015; Oladimeji et, al., 2017). It is also based on the disconfirmation paradigm whereby the customer measures his perception against the expectation

69 Amity Journal of Marketing ADMAA AJM Volume 4 Issue 1 2019 of the process of receiving a service (Zeithaml, Parasuraman & Berry, 1990). Highly satisfied customers are more likely to be unpaid brand ambassadors of the organisation. Attrition and churning rates are low whilst loyalty and patronage increases.

Methodology Driven by the positivism research philosophy, a structured and quantifiable questionnaire was used to collect data. A deductive approach was adopted by using the business process re-engineering the conceptual model, which had variables and drivers drawn from literature (Okwena, 2015; Oladimeji, et al., 2017). The target population for the study was made up of all registered traditional banks operating in Zimbabwe listed by the Reserve Bank of Zimbabwe (2019). The demarcation of traditional and non-traditional banks was made by the Technozim (2019) on the basis of year of bank establishment in Zimbabwe. Using the Technozim framework of 2019, there were 11 traditional banks in Zimbabwe. The researchers had access to a sampling frame which had electronic email addresses of targeted members. Therefore, simple random sampling was used to sample respondents. Using Outlook Randomization Electronic Emailing (OREE) system, all email addresses were loaded into Outlook and the command function (CFn) was enacted to allow Outlook to populate a survey link to only a number equivalent to the sample size. Using the Morgan Sample Size extract in Saunders, Lewis and Thornhill, (2009), a sample size of 333 respondents was selected. The measurement scales for the study variables (Customer Satisfaction, Change Culture, Information Technology, Employee Commitment and Financial Resources) were adapted from Oladimeji et, al. (2017) and Osano and Okwena (2015). The Cronbach Alpha test statistic shows that all variables had a Cronbach Coefficient of 0.69 and above as shown in Table 1. Table 1: Cronbach Alpha Reliability Test for the BPR Implementation and Customer Satisfaction Variables.

Study Variables Cronbach’s Alpha N of Items Change Culture 0.879 6 Information Technology 0.752 5 Employee Commitment 0.769 5 Financial Resources 0.843 5 BPR Implementation 0.694 4 Customer Satisfaction 0.832 5

Results of the Study The response rate for the study was 62%. The study administered 333 questionnaires yet 207 were returned and validated. Of all respondents, 70% had first degrees whilst over 24% of respondents had a post graduate qualification. Male respondents were 47.8% whilst females were 52.2%, and the age category with many respondents was the ‘26 to 35 years’ category. The study found out that the majority of respondents had stayed with their companies for in excess of 5 years. This shows that they had seen most of the bank processes changing over the years and were better equipped to offer responses to the study. Table 2 presents statistics for the demographic profile.

ADMAA 70 Amity Journal of Marketing Volume 4 Issue 1 2019 AJM Table 2: Demographic Profiles

Gender of Respondents Frequency Percent Valid Percent Cumulative Percent Valid Males 99 47.8 47.8 47.8 Females 108 52.2 52.2 100.0 Total 207 100.0 100.0 Age of Respondents Frequency Percent Valid Percent Cumulative Percent Valid 18 to 15 17 8.2 8.2 8.2 26 to 35 89 43.0 43.0 51.2 36 to 45 81 39.1 39.1 90.3 46 to 55 20 9.7 9.7 100.0 Total 207 100.0 100.0 Respondents’ Level of Education Frequency Percent Valid Percent Cumulative Percent Valid Post graduate degree 50 24.2 24.2 24.2 Degree 145 70.0 70.0 94.2 Diploma 10 4.8 4.8 99.0 High School 2 1.0 1.0 100.0 Total 207 100.0 100.0 In terms of commitment to continuous process changes, banks in the sampling frame were committed. A mean score of 4.03 (standard deviation of 0.910) which equates to the ‘Committed’ category on the measurement scale, indicates that the majority of respondents agreed to the notion that their banks were committed to process changes. However, BPR implementation was sluggish for most traditional banks. A mean score of 2.45 (standard deviation of 0.743), shows that the success story of BPR implementation was not flawless. Figure 2 also indicates lack of agility in BPR implementation

Figure 2. BPR Implementation speed across various banks. The majority of respondents indicated that BPR implementation’s success story was not a desired one. 38.9% likened the swiftness of their BPR process to a sluggish moving tortoise, and a significant 26.1% likened it to an elephant which moves in a relaxed manner. These findings confirmed that BPR practices in traditional banks were slow and dragging. The same notion was

71 Amity Journal of Marketing ADMAA AJM Volume 4 Issue 1 2019 found in a study by Oladimeji et, al. (2017), that BPR implementation is taken to be a responsive strategy, hence it usually takes time for implementation to be effected. The current findings are also aligned with IPC Consultants Survey (2018) findings that the operations and processes of banks in Zimbabwe were not properly adapted to support business process transformations.

BPR Implementation Determinants The first research objective aimed to identify the determinants of successful BPR implementation. Through a deductive approach, the study identified four determinants namely; Change Culture (mean = 3.06), Information Technology (mean = 2.61), Employee Commitment (mean = 4.04) and Financial Resources (mean = 3.23).

The effect of the BPR Determinants on BPR Implementation The second research objective meant to assess the effect of BPR determinants on BPR implementation. This research question was answered with four hypotheses and the analysis was done using stepwise regression statistic shown in Table 3 Table 3: The BPR Implementation Model Summary

Model R R Adjusted Std. Error Change Statistics Square R Square of the R Square F Change df1 df2 Sig. F Estimate Change Change 1 .726a .528 .525 .46944 .528 229.112 1 205 .000 2 .759b .576 .571 .44614 .048 22.967 1 204 .000 3 .773c .598 .592 .43518 .023 11.404 1 203 .001 a. Predictors: (Constant), Employee Commitment b. Predictors: (Constant), Employee Commitment, Change Culture c. Predictors: (Constant), Employee Commitment, Change Culture, Information Technology

Table 3 presents the model summary. Three models are presented with varied r-squared values. Model three which had three independent variables (Employee Commitment, Change Culture, Information Technology) was adopted for analysis because it explains BPR successful implementation by the highest rate of 59% (adjusted r2 = 0.592). The study also found a significant R Squared change of 0.23 from Model 2 to Model 3, this implies that Model 3 is a relatively good model to predict BPR implementation. The inclusion of three independent variables in the model was also found to be statistically significant, p < 0.05. The r2 value seems relatively smaller, however this is ideal, because BPR implementation is also explained by factors other than the ones in the model. The financial resources variable was dropped from the analysis because it was not statistically significant. Model 3 also shows a strong and positive association between BPR determinants and BPR successful implementation, with a correlation coefficient of 0.773. This means that if the variables of the model are enhanced, BPR implementation would be enhanced significantly. Table 4 shows that BPR implementation model 3 was statistically significant. The p-value of the model was 0.000, with an F coefficient of 100.715. The p-value was below the alpha value of 0.05. Therefore, p = 0.000 < 0.05.

ADMAA 72 Amity Journal of Marketing Volume 4 Issue 1 2019 AJM Table 4: Analysis of Variance for the BPR Implementation Model

ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 50.490 1 50.490 229.112 .000b Residual 45.176 205 .220 Total 95.665 206 2 Regression 55.061 2 27.530 138.315 .000c Residual 40.604 204 .199 Total 95.665 206 3 Regression 57.221 3 19.074 100.715 .000d Residual 38.445 203 .189 Total 95.665 206 a. Dependent Variable: BPR Implementation b. Predictors: (Constant), Employee Commitment c. Predictors: (Constant), Employee Commitment, Change Culture d. Predictors: (Constant), Employee Commitment, Change Culture, Information Technology

Table 5 shows the BPR implementation coefficients and the level of significance for each BPR determinant Table 5: The BPR Implementation Coefficients

Standardized Significant/ Model t Sig. Correlations Coefficients Insignificant Beta Zero-order Partial Part 1 (Constant) 2.33 .021 Employee Commitment .726 15.13 .000 .726 .726 .726 2 (Constant) 1.419 .157 Employee Commitment .556 9.594 .000 .726 .558 .438 Change Culture .278 4.792 .000 .620 .318 .219 3 (Constant) 1.082 .281 Employee Commitment .445 6.832 .000 .726 .432 .304 Significant Change Culture .252 4.414 .000 .601 .296 .196 Significant Information Technology .197 3.377 .001 .591 .231 .150 Significant a. Dependent Variable: BPR Implementation

Using Model 3 correlation results (Table 5), all three independent variables had positive associations with BPR Implementation. Employee Commitment had a strong positive correlation coefficient of 0.726, followed by Change Culture (0.601). A moderately strong yet positive association was recorded for Information Technology which recorded a coefficient of 0.591. This can be interpreted to mean that BPR Determinants have a positive moderate to high association with BPR Implementation. This also gives an indication of validity of the study variables. Employee Commitment had a Beta coefficient of 0.445, t value of 6.832 and a statistically significant p value of 0.000. Thus, the study accepted the alternate hypothesis (H3) and concluded that employee commitment positively impacts BPR implementation. Conversely, the decision made meant that the study found out that employees of banks in the sampling frame were more

73 Amity Journal of Marketing ADMAA AJM Volume 4 Issue 1 2019 committed to BPR implementation processes. The study thus noticed a synchronised result with what was known in the literature (Mushaathoni, 2015; Osano & Okwena, 2015; Hussein & Dayekh, 2014). Employee commitment is a vital component in the successful implementation of BPR. Therefore, even though employee commitment was found to be relatively high in this study, there is a continual need to improve and always enhance motivation and commitment of employees so as to enhance and speed up BPR implementation. Change Culture had a Beta coefficient of 0.252 with a t value of 4.414 and a p-value of 0.00. This shows that the association between Change Culture and BPR Implementation was statistically significant but with a relatively low impact. Hence, it was concluded that change culture positively impacts BPR implementation by 25% (H1). Other scholars also found related results. For instance, Guimaraes and Chair (2018) underlined change culture as one of the key success factors of BPR as it minimises resistance to change. Keya (2015) also found related results in his studies in Kenya. Kaya (2015) concluded that a responsive change culture is a significant ingredient of BPR implementation success. Thus, the findings were aligned with literature, and heightened the need for banks to develop an agile change culture which is responsive to process changes. Information Technology explains BPR implementation by 20% (Beta = 0.197, T = 3.377); and the association was found to be statistically significant with a p value of 0.001. The study thus concluded that information technology positively impacts BPR implementation (H2). It means that information technology is a significant determinant of BPR implementation. However, information technology explains only 20% of BPR implementation success, indicating that the information technology of banks in the sampling frame had a weak impact on BPR Implementation. This denotes that there is need to revamp the hardware, software and skills of technicians in the traditional banks. A study by Mushaathoni (2015) found out that without information technology, it may be difficult for organisations to have a competitive edge over their customers. Similarly, Fasna and Gunatilake (2019) found out that information technology which is not suited to support a process-based organisation grows as a barrier at all phases of BPR implementation (pre-implementation, implementation and post-implementation). Therefore, comparing previous studies with the current study shows the need for the banking sector to revamp their information technology, as it acts as the backbone of BPR. The study model also had the fourth determinant, Financial Resources. The study however found out that the variable was not statistically significantly explaining BPR implementation. Therefore, the Financial Resources variable was dropped from analysis using stepwise regression. The insignificant association comes at a time when it is not disputable that financial resources are effective for BPR projects. Hardware, software and employee training all require financial support. That notion was found in a study by Oladimeji et, al. (2017) who note that for organisations to effectively implement BPR there should be enough financial muscle for it to hire skilled labour, to acquire materials and technologies required as well as to train other employees. Similarly, Okwena (2015) concluded that if the organisation lacks the financial ability and financial strong will to fund BPR projects, the BPR initiative is likely to fail. However, the study dropped the role of financial resources since the association was not significant.

The Impact of BPR Implementation on Customer Satisfaction The third and final research objective meant to analyse the impact of BPR implementation on customer satisfaction. Regression test statistic was used to test the association and the results are in Table 6.

ADMAA 74 Amity Journal of Marketing Volume 4 Issue 1 2019 AJM Table 6: The Regression Analysis Model Summary Between BPR Implementation and Customer Satisfaction

Model Summarya Model R R Square Adjusted R Square Std. Error of the Estimate 1 .686a .470 .468 .54968 a. Predictors: (Constant), BPR Implementation

Table 6 shows that BPR implementation in traditional banks explains customer satisfaction by 47% (Adjusted r2 = 0.468). The r value (0.686) of the model also shows a strong positive association between BPR implementation and customer satisfaction. Table 7 indicates the significance level of the association between BPR implementation and customer satisfaction. Table 7 The Customer Satisfaction Coefficients

Coefficientsc Unstandardized Standardized Model Coefficients Coefficients t Sig. B Std. Error Beta 1 (Constant) .589 .164 3.595 .000 BPR .758 .056 .686 13.489 .000 Implementation a. Dependent Variable: Customer Satisfaction

Using results in Table 7, it was concluded that the association between BPR implementation and customer satisfaction was statistically significant with a p-value of 0.000. Therefore, the study concluded that BPR positively impacts customer satisfaction by 47% (H5). These results can be interpreted to mean that if BPR is effectively implemented in banks, customer satisfaction would significantly increase, as attested to by a high correlation coefficient of 0.686. Though the impact of the association was moderately strong, the study noted that the impact could be enhanced by developing a responsive banking process. For a long time now, the role of the customer was at the fore of BPR. A relatively old study by Vakola (1999) showed that customer satisfaction was the main objective of BPR towards the new millennium. Fast forward, Acharya (2015) noted that customers are the ultimate trophy of business competition and that satisfaction of customers enhances performance of business. Zaini and Saad (2019) also concured that effective implementation of BPR helps businesses to run at various locations and enhances the customer experience and satisfaction through fast and effective paperless transactions.

Recommendations The study recommends the erection of an agile culture which embraces process change easily and meets customer needs swiftly. This is essential considering the tumultuous business environment that the banking sector operates in. It is essential to ascertain touch points for process change through an agile culture as this may lead to improved marketing based results like enhanced customer experience, satisfaction and loyalty. Process change culture can be done through redirecting the vision of the company to a more versatile one. Top management may take the lead and promote the marketing philosophy of adapting business processes so as to satisfy customers’ needs and wants. This task is likely to be

75 Amity Journal of Marketing ADMAA AJM Volume 4 Issue 1 2019 easier given that employees were found in this study to be overly committed to BPR projects. The instigation of a leaner, flatter organisational structure is also important in speeding up the process of BPR implementation. This promotes agility towards serving the ever changing preferences of customers. The hardware, software and technicians should be audited to present an up-to-date information technology that supports BPR implementation. Outdated technological practices must be dropped because they derail the pace at which BPR is implemented and that affects the marketing effort of the organisation as customer satisfaction may go down. To do that, the study recommends the benchmarking process against best in-class practices regionally and internationally. This is backed by this study which found out that information technology predicts effective implementation of BPR. Training and retraining empower employees with the knowledge and skills required to effectively implement BPR. This comes following the revelation in this study that employees were both system users and system developers. Thus, training would enhance the level of employee involvement which this study found to be essential towards BPR implementation. BPR implementation was found to be positively predicting customer satisfaction. It is against that background that the researchers recommend the prioritization of BPR projects. Satisfaction of customers guarantees high patronage and market share which are the key benefits in marketing. To enhance satisfaction, the study recommends that companies should promote a change culture, enhance employee commitment and revamp their information technology. These three variables were found to be statistically significant in this study in enhancing BPR implementation which is key for customer satisfaction.

Conclusions The study thus makes the following objective-based conclusions: The first objective of the study was to identify the determinants of successful BPR implementation. The study identified four determinants of successful BPR Implementation, namely; Change Culture, Information Technology, Employee Commitment and Financial Resources. The second objective of the study was to examine the impact of BPR determinants on BPR implementation. The study noted that change culture had a low impact of 25% on BPR implementation. The research study concluded that traditional banks in Zimbabwe had poor Information Technology to drive BPR projects. A weak impact factor of 20% was found regardless of the fact that Information Technology is the lifeblood of BPR. However, if banks improve their Information Technology, Business Process Reengineering implementation would be enhanced as attested to by a moderately strong positive correlation of 0.59. The study concluded that employees of traditional banks in Zimbabwe were very much committed to BPR implementation. BPR implementation can be predicted by employee commitment by 45%, which shows a high impact. However, the study also concluded that there is room to further motivate employees to be more involved because of a strong positive correlation of 0.726. An unexpected conclusion was made regarding the role of financial resources on business process reengineering implementation in banks. At a time when it is common causes that transformation is backed up by financial resources, the study made a conclusion that financial resources do not impact BPR implementation.

ADMAA 76 Amity Journal of Marketing Volume 4 Issue 1 2019 AJM The third objective of the study was to analyse the impact of BPR Implementation on customer satisfaction. It was concluded that the implementation of BPR predicts customer satisfaction by 47%. A high correlation between customer satisfaction and BPR implementation also meant that if BPR is improved, the level of customer satisfaction would also be improved.

Limitations and Areas for Further Research The study encountered a limitation of low response rate from participants. The researcher had to send kind reminders to the participants to enhance response rate. However, regardless of all the effort, the response rate for the study stood low at 62%. Though the response rate was low, yet the sample size was large and that enabled analysis to take place with 207 valid responses. The study zeroed in on business process implementation in the banking sector in Zimbabwe. Other studies may want to further the BPR model which was used in this study by testing it in a different sector, country or region so as to ensure robustness of the model in different situations. Other scholars may also add moderating and mediating variables to the model such as economic factors and facilitating conditions. In essence, the researchers recommend that future studies delve more into how to enhance business process reengineering in a volatile business environment.

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Authors’ Profile Forbes Makudza is an aspiring academic and a promising researcher who is currently serving as a Lecturer of Marketing in the Department of Business Management at Manicaland State University of Applied Sciences, Fernhill, Zimbabwe. His research thrust is premised on digital technologies and how they affect the marketing of goods and services. He is pursuing a Doctor of Philosophy (Ph.D) degree in digital marketing with the University of Zimbabwe, Harare, Zimbabwe. Gibson Muridzi is the Acting Chairperson and Lecturer at Manicaland State University of Applied Sciences, Fernhill, Zimbabwe in the Faculty of Agribusiness and Commerce, Department of Business Management. His research interests are in monitoring and evaluation, e-governance, entrepreneurship and development and leadership. Darlington Chirima is a seasoned strategist, academic and researcher who is attached at Manicaland State University of Applied Sciences, Fernhill, Zimbabwe, where he is working as a Lecturer in the Department of Business Management. His research interests are in corporate strategy, corporate governance, investment and entrepreneurship. He has worked in several Universities in Zimbabwe.

79 Amity Journal of Marketing ADMAA