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Critical Analysis of the Impacts of Online Service Failure and its Recovery Solution on the Buying Behaviour of Customers in Restaurant Industry: A Case Study of Domino’s Pizza, UK

Harvard, 12000 Words

Abstract

 

The aim of the research is to critically analyse the impacts of online service failure and its recovery solution on the buying behaviour of Domino’s Pizza customers. Research objectives are focussed to explain the impact of online service failure and assess the effectiveness of recovery solution of online service failure in Domino’s Pizza, UK. Another objective is to understand the reasons of increasing numbers of online service failure and explore the influences of recovery strategies of online service failure that can create impact on the buying behaviour of customers. The methodology of this research is mixed because both quantitative and qualitative research methods are applied. Primary and secondary data is used to understand the impact of online service failure in Domino’s Pizza. Both qualitative and quantitative data is collected from the target population of the research so that we can investigate the impact of recovery solutions on buying behaviour of the customers of Domino’s Pizza, UK. Questionnaire survey and qualitative interview are the tools of collecting primary data in this research. Thematic method of data analysis of applied and deductive research approach is used to conduct the research. SPSS and MS Excel are applied to present statistical analysis of the collected data so that we can emphasise on the influences of recovery strategies of online service failure and how they affect on buying behaviour of the customers in restaurant industry. The sample size is 105 and purposive sampling technique is applied to choose the samples. The findings imply that online service failure has negative impact on the business performance of Domino’s Pizza. The customer rate can be decreased because of online service failure. It is also found that customer dissatisfaction and customer turnover are two major consequences of online service failure. The research highlights on the necessity of recovery strategies of online services failure that can help to gain attention of the customers and enhances the opportunity for CRM. The impact of recovery solutions are useful to affect on buying behaviour of the customers. The recruitment of skilled IT experts, improving the role of data analysts, developing quick recovery solution and introducing technical support team to reduce online service failure are the major recommendations made in this research.

 

Table of Contents

 

Acknowledgement ii

Declaration iii

Abstract iv

Chapter – 1: Introduction 1

1.1 Introduction 1

1.2 Background of the Research 2

1.3 Rationale of the Research 3

1.4 Problem Statement 3

1.5 Research Aim and Objectives 4

1.6 Research Questions 5

1.7 Structure of the Research 5

1.8 Conclusion 6

Chapter – 2: Literature Review 6

2.1 Introduction 6

2.2 Online Service failure 6

2.2.1 Effect of Online Service Failure on Online Purchase of Customers 7

2.1        Technology impacts on business 8

Figure 2.1: Technology based Business Innovation 9

2.3 Recovery System of Online Service Failure 10

2.3.1 Recruitment of IT Experts for Recovery of Online Service Failure 10

2.3.2 Quick Recovery of Online Service Failure 11

2.3.3 Online Service Failure and Customer Dissatisfaction 11

2.4 Recovery Solution of Online Service Failure 12

2.4.1 Recovery Solution of Online Service Failure protects Customer Switching 13

2.5 Buying Behaviour 13

2.5.1 Impact of Recovery Solution of Online Service Failure on Buying Behaviour 14

2.6 Conceptual Framework 15

Figure 2.1: Conceptual Framework of the Study 15

2.7 Conclusion 16

Chapter – 3: Research Methodology 17

3.1 Introduction 17

3.2 Research Philosophy 17

3.3 Research Approach 18

3.4 Research Strategy 19

3.5 Type of Research Investigation 19

3.6 Research Methods 20

3.6.1 Quantitative Research Method 20

3.6.2 Qualitative Research Method 20

3.6.3 Mixed Research Method 20

3.7 Techniques of Data Collection 21

3.7.1 Secondary Data 21

3.7.2 Primary Data 21

3.7.3 Tools of Collecting Data 21

3.8 Sampling Technique, Population and Sample Size 21

3.9 Data Analysis Methods 22

3.10 Ethical Considerations 22

3.11 Limitations of Methodology 23

3.12 Conclusion 23

Chapter – 4: Analysis and Findings 23

4.1 Introduction 23

4.2 Analysis of Questionnaire Survey 24

Table 4.1: Analysis of age of the samples 24

Figure 4.1: Analysis of age of the samples 25

Table 4.2: Analysis of gender of the samples 25

Figure 4.2: Analysis of gender of the samples 26

Table 4.3: Analysis of educational level of the samples 26

Figure 4.3: Analysis of educational level of the samples 27

Table 4.4: Domino’s Pizza faces virus and bug problem in online retailing services that lead to customer dissatisfaction 27

Figure 4.4: Domino’s Pizza faces virus and bug problem in online retailing services that lead to customer dissatisfaction 28

Table 4.5: System error and technical errors cause online service failure in Domino’s Pizza that decreasing the sales of the company 28

Figure 4.5: System error and technical errors cause online service failure in Domino’s Pizza that decreasing the sales of the company 29

Table 4.6: Slow and inaccurate home delivery services cause online service failure in Domino’s Pizza that causes customer turnover 29

Figure 4.6: Slow and inaccurate home delivery services cause online service failure in Domino’s Pizza that causes customer turnover 30

Table 4.7: Domino’s Pizza implements recovery solution to improve technical support and operating system of online retailing 30

Figure 4.7: Domino’s Pizza implements recovery solution to improve technical support and operating system of online retailing 31

Table 4.8: Less system failure and flexible order entry are two benefits of recovery solution of online service failure 31

Figure 4.8: Less system failure and flexible order entry are two benefits of recovery solution of online service failure 32

Table 4.9: Domino’s Pizza enhances the opportunity for customer relationship management through the efficacy of recovery solutions 32

Figure 4.9: Domino’s Pizza enhances the opportunity for customer relationship management through the efficacy of recovery solutions 33

Table 4.10: Poor data analysts are the major cause of increasing number of online service failure in Domino’s Pizza 33

Figure 4.10: Poor data analysts are the major cause of increasing number of online service failure in Domino’s Pizza 34

Table 4.11: Lack of skilled IT experts is considered to be a reason of increased number of online service failure 34

Figure 4.11: Lack of skilled IT experts is considered to be a reason of increased number of online service failure 35

Table 4.12: Domino’s Pizza fails to ensure quick recovery of online service problems that increase the number of online service failure 35

Figure 4.12: Domino’s Pizza fails to ensure quick recovery of online service problems that increase the number of online service failure 36

Table 4.13: Recovery strategies of online service failure affect positively on consumer loyalty 36

Figure 4.13: Recovery strategies of online service failure affect positively on consumer loyalty 37

Table 4.14: Recovery strategy of online service failure in Domino’s Pizza motivates buying behaviour of the customers positively 37

Figure 4.14: Recovery strategy of online service failure in Domino’s Pizza motivates buying behaviour of the customers positively 38

Table 4.15: Recovery strategies of online service failure help to gain customer attention and reduce customer switching 38

Figure 4.15: Recovery strategies of online service failure help to gain customer attention and reduce customer switching 39

Table 4.16: Recruitment of IT experts is required in Domino’s Pizza to recover online service failure quickly 39

Figure 4.16: Recruitment of IT experts is required in Domino’s Pizza to recover online service failure quickly 40

Table 4.17: Feedback response and customer complaints can be reviewed quickly to recover online service failure 40

Figure 4.17: Feedback response and customer complaints can be reviewed quickly to recover online service failure 41

Table 4.18: Domino’s Pizza can introduce innovation and quick recovery solutions in online retailing to attract more customers 41

Figure 4.18: Domino’s Pizza can introduce innovation in online retailing and quick recovery solutions to attract more customers 42

4.3 T-Test Result of Questionnaire Survey 42

Table 4.19: Average response of questionnaire survey 42

Table 4.20: T-test result and statistics of questionnaire survey 43

4.4 Findings of Qualitative Interviews 43

4.5 Conclusion 45

Chapter – 5: Conclusion and Recommendations 45

5.1 Conclusion 45

5.2 Summary of the Research Objectives 46

5.3 Recommendations 48

5.4 Limitations and Future Research Scopes 49

References 50

  1. Farrell, S. (2015) The rise and rise of Domino’s Pizza [ONLINE] Retrieved from: http://www.theguardian.com/business/2014/jan/08/dominos-pizza-sales-up [Accessed on: 08 May, 2015] 51

Appendix – A 55

Appendix – B 59

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

List of figures

Figure 2.1: Conceptual Framework of the Study. 13

 

Figure 4.1: Analysis of age of the samples. 22

Figure 4.2: Analysis of gender of the samples. 23

Figure 4.3: Analysis of educational level of the samples. 24

 

Figure 4.4: Domino’s Pizza faces virus and bug problem in online retailing services that lead to customer dissatisfaction. 25

Figure 4.5: System error and technical errors cause online service failure in Domino’s Pizza that decreasing the sales of the company. 26

Figure 4.6: Slow and inaccurate home delivery services cause online service failure in Domino’s Pizza that causes customer turnover 27

 

Figure 4.7: Domino’s Pizza implements recovery solution to improve technical support and operating system of online retailing. 28

Figure 4.8: Less system failure and flexible order entry are two benefits of recovery solution of online service failure. 29

Figure 4.9: Domino’s Pizza enhances the opportunity for customer relationship management through the efficacy of recovery solutions. 30

 

Figure 4.10: Poor data analysts are the major cause of increasing number of online service failure in Domino’s Pizza. 31

Figure 4.11: Lack of skilled IT experts is considered to be a reason of increased number of online service failure. 32

Figure 4.12: Domino’s Pizza fails to ensure quick recovery of online service problems that increase the number of online service failure. 33

 

Figure 4.13: Recovery strategies of online service failure affect positively on consumer loyalty. 34

Figure 4.14: Recovery strategy of online service failure in Domino’s Pizza motivates buying behaviour of the customers positively. 35

Figure 4.15: Recovery strategies of online service failure help to gain customer attention and reduce customer switching. 36

Figure 4.16: Recruitment of IT experts is required in Domino’s Pizza to recover online service failure quickly. 37

Figure 4.17: Feedback response and customer complaints can be reviewed quickly to recover online service failure. 38

Figure 4.18: Domino’s Pizza can introduce innovation in online retailing and quick recovery solutions to attract more customers. 39

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

List of Tables

Table 4.1: Analysis of age of the samples. 22

Table 4.2: Analysis of gender of the samples. 23

Table 4.3: Analysis of educational level of the samples. 24

 

Table 4.4: Domino’s Pizza faces virus and bug problem in online retailing services that lead to customer dissatisfaction. 25

Table 4.5: System error and technical errors cause online service failure in Domino’s Pizza that decreasing the sales of the company. 26

Table 4.6: Slow and inaccurate home delivery services cause online service failure in Domino’s Pizza that causes customer turnover 27

 

Table 4.7: Domino’s Pizza implements recovery solution to improve technical support and operating system of online retailing. 28

Table 4.8: Less system failure and flexible order entry are two benefits of recovery solution of online service failure. 29

Table 4.9: Domino’s Pizza enhances the opportunity for customer relationship management through the efficacy of recovery solutions. 30

 

Table 4.10: Poor data analysts are the major cause of increasing number of online service failure in Domino’s Pizza. 31

Table 4.11: Lack of skilled IT experts is considered to be a reason of increased number of online service failure. 32

Table 4.12: Domino’s Pizza fails to ensure quick recovery of online service problems that increase the number of online service failure. 33

 

Table 4.13: Recovery strategies of online service failure affect positively on consumer loyalty. 34

Table 4.14: Recovery strategy of online service failure in Domino’s Pizza motivates buying behaviour of the customers positively. 35

Table 4.15: Recovery strategies of online service failure help to gain customer attention and reduce customer switching  36

 

Table 4.16: Recruitment of IT experts is required in Domino’s Pizza to recover online service failure quickly. 37

Table 4.17: Feedback response and customer complaints can be reviewed quickly to recover online service failure. 38

Table 4.18: Domino’s Pizza can introduce innovation and quick recovery solutions in online retailing to attract more customers. 39

 

Table 4.19: Average response of questionnaire survey. 40

Table 4.20: T-test result and statistics of questionnaire survey. 40