An investigation of customer value and patronage in retailing vending machine sector in vietnam

This study investigated the relationship between Customer value and Retailing vending machine patronage, and examines the relationships of antecedents including Customization, Functional

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business -

NGO TRONG TRUNG

AN INVESTIGATION OF CUSTOMER VALUE AND PATRONAGE IN RETAILING VENDING MACHINE

SECTOR IN VIETNAM

MASTER OF BUSINESS (Honours)

Ho Chi Minh City – Year 2014

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business -

NGO TRONG TRUNG

AN INVESTIGATION OF CUSTOMER VALUE AND PATRONAGE IN RETAILING VENDING MACHINE

ACKNOWLEDGEMENT

I would like to thank my supervisor, Dr Hanh Nguyen for her encouragement and guidance throughout the process of conducting this thesis I would also like to thank other members of my advisor committee, Dr Tho Nguyen, Dr Nguyen, Dr Quan, Dr Phong, and

Dr Thao for helping me to understand the process and theoretical foundations of the

research

Many others also deserve my gratitude Among them, Mr Doanh, Mr Tuan, Ms Kim Yen, Master Mai Thien Tam, Ms Nguyet Anh, Mr Huy, Master Nguyen Thi Nguyet and Master Nguyen Huy Khai, helped me to obtain final questionnaire being suitable in the context of Vietnam My colleagues, friends and all of respondents supported to conduct the questionnaire at the best reliability

Finally, I would like to express my gratitude to my family for their love and support, and they are always there when I need them Without their emotional and financial support, this study would not be completed

ABSTRACT

Although Vending machine was predicted would become one of the most important non-store marketing channels, many retailers using vending machine have a difficult time in developing business in Vietnam If vending machine-retailers want to attract more and more shoppers, they need to know what evaluative criteria consumers use when selecting a

vending machine-retailer The past researches demonstrated that Customer value and Retail patronage could enhance retail performance This study investigated the relationship

between Customer value and Retailing vending machine patronage, and examines the

relationships of antecedents including Customization, Functionality and Perceived Risk with Customer Value By utilizing literature review, a research model was proposed to identify the relationships above Additionally, a convenient sample of 247 respondents in Ho Chi Minh City was surveyed to test the theoretical model Structure Equation Modeling (SEM) was used to analyzed the data The final result indicated that Customization and

Functionality are positively related to Customer value, but perceived risk was not supported Customer value is positively related to retailing vending machine patronage

TABLE OF CONTENTS

ACKNOWLEDGEMENT i

ABSTRACT ii

TABLE OF CONTENTS iii

LIST OF TABLES v

LIST OF FIGURES vi

CHAPTER 1: INTRODUCTION 1

1.1 Research background 1

1.2 Research Problem 2

1.3 Research Objective 3

1.4 Significance of the Study 3

1.5 Research methodology and scope 3

1.6 The structure of the study 4

CHAPTER 2: LITERATURE REVIEW AND HYPOTHESES 6

2.1 Vending machine 6

2.2 Customer value 7

2.3 Customization and Functionality 8

2.4 Perceived risk 9

2.5 Customer value and retail patronage 10

2.6 Research model 11

CHAPTER 3: METHODOLOGY 13

3.1 Research process 13

3.1.1 Qualitative research 13

3.1.2 Quantitative research 13

3.2 Research design 17

3.3 Measurements of constructs 18

3.4 Data analysis method 21

3.4.1 Descriptive Statistics 21

3.4.1.1 Test of Skewness 22

3.4.1.2 Test of Kurtosis 22

3.4.2 Confirmatory factors Analysis (CFA) 22

3.4.2.1 Reliability testing 22

3.4.2.2 Convergent validity 22

3.4.2.3 Discriminant validity 23

3.4.3 Structure Equation Modeling (SEM) 23

3.4.4 Bootstrap 23

CHAPTER 4: DATA ANALYSIS AND RESULTS 25

4.1 Sample characteristic 25

4.2 Descriptive statistics 26

4.3 Confirmatory Factor Analysis (CFA) 28

4.4 Structural Equation Modeling (SEM) 38

4.5 Bootstrap analysis 40

4.6 Explanation for finding result of hypotheses 41

CHAPTER 5: CONCLUSION, IMPLICATIONS AND LIMITATION 46

5.1 Conclusion 46

5.2 Implications 47

5.3 Limitation 48

REFERENCES 50

APPENDIX 58

LIST OF TABLES

Table 3.1: The result of collected data 15

Table 3.2: Measurement scales 19

Table 4.1: Sample Characteristic 26

Table 4.2: The result of Skewness and Kurtosis testing 27

Table 4.3: Correlations of components 32

Table 4.4: The result of correlation test 32

Table 4.5: Summary of measurement validation 34

Table 4.6: Correlation of Constructs 36

Table 4.7: Chi-square difference test 37

Table 4.8: Hypotheses Unstandardized Structural Paths 40

Table 4.9: Summary of hypotheses testing result 40

Table 4.10: The result of bootstrap analysis 41

LIST OF FIGURES

Figure 1: Conceptual Model 12

Figure 3: CFA of first-order constructs 29

Figure 4: CFA of second-order construct 31

Figure 5: CFA final 33

Figure 6: Customer value versus retailing vending machine patronage 37

Figure 7: SEM model 39

Figure 8: Structural results (Standardized estimates) 44

CHAPTER 1: INTRODUCTION 1.1 Research background

More than three decades ago, Quelch and Takeuchi (1981) predicted that vending machine would become one of the most important non-store marketing channels Reality, their prediction has surely materialized Most of countries all over the world used vending machine as retail business There are more than seven millions vending machines in

operation in U.S (Leaner 2002), Japan has become a vending-machine-country and Vietnam also has the first vending machines in 2000s

Vending machine offers consumer a variety of products including food, snack,

beverages, newspaper, cosmetic, CDs, cigarettes and so on Lee (2013) argued that as more people has joined workforce during the past several decades and their busy social life

increasingly places more value on time and convenience, vending machine had become an indispensable part of many people daily’s lives

In Vietnam, vending machine was deployed in early 2000s when the Vietnam’s Government issued the coins and experts believe that they will be potential market in the future (Kieu Giang, 2004) However, vending machine sector developed slowly during past time There were many investors failed in applying Vending machine for retail business The first main reason can explain for this is technology Most of vending machine at that time integrated used-coin technology, but Vietnam people do not have habit keeping the coin available or do not like to use coin in transaction This leads used-coin vending

machine to be inconvenient for customer to reach and purchase by vending machine;

secondly, retailers using vending machines cannot find the suitable locations to install vending machine, especially two biggest cities in Vietnam: Ho Chi Minh City and Hanoi City for sidewalk and public areas are quite narrow As a result, vending machine cannot operate at the best; finally, most of the companies invested vending machine sector at that time, were small and not enough ability to invest new modern vending machines, while the companies having enough potential did not want to joint into this industry to push the

vending machine sector in Vietnam (Hong Phuc, 2005)

Fortunately, the business environment has changed in recent years leading to many good signs from vending machine sector First of all, technology is improved, current

vending machine can accept both the cash and coin, even consumer can use credit card to purchase some product sold by vending machine This makes vending machine to be more convenient for customer On the other hand, some big brand names in Vietnam: Pepsi, Coca Cola, begin to use vending machine to sell their product at public areas such as hospital, park, railway station, bus station and airport All above things have prompted vending machine sector grow quicker and quicker

Based on those, author will conduct a study to investigate about relevant knowledge

of vending machine sector in Vietnam

1.2 Research Problem

Given the ever increasing presence and the pervasiveness of vending machines in lives of consumers, it is surprising that there have been to date no studies in marketing and consumer behavior literature that shed light on consumers’ usage behavior with vending machines services in Vietnam Furthermore, most research has focused on purchase

intention, which is customer acquisition oriented, little research has examined consumers’ patronage behavior, which is customer retention oriented However, customer retention is more important than customer acquisition, and building customer value is the key to

retaining customers (Weinstein, 2002)

On the other hand, Customer value has emerged as a crucial instrument for analyzing service quality, customer satisfaction, and consumer behavior (Yieh, Chen, and Wei, 2012)

It is not only the antecedent of attitude, intention, and behavior (Gounaris et al 2007;

Parasuraman and Grewal 2000; Yang and Peterson 2004) but also a critical factor

influencing customer retention and purchase intention (Chang and Wildt, 1994) In addition, customer value is a strategic weapon in attracting and retaining customers and has become one of the most significant factors in the success in service providers (Gale 1994;

Parasuraman 1997) Therefore, many previous studies examine relationship between

Customer value and consumer’s purchasing intention or satisfaction, but little of studies research about influence of Customer value on Patronage behavior

Thus, in order to fulfill this gap, an investigation of Customer Value and Patronage behavior in retailing vending machine sector is examined, and in an effort to indentify the key factors impacting on customer value in vending machine sector in Vietnam, this study considers the concepts of Functionality, Customization, and Perceived Risk as antecedents

of Customer value

1.3 Research Objective

To examine customer value in vending machine situation, it is necessary to focus on identifying key factors affected customer value in using vending machine These factors are perceived risk, functionality and customization Each of these can either positively or

negatively influence customer value in vending machine sector Knowledge about the effect

of customer value on consumers’ vending machine patronage behavior provides helpful implications to marketers in executing marketing and business strategy and customer

relationship management Therefore, the overall purpose of this current study is to examine how customer value affects consumers’ retailing vending machine patronage in Vietnam Particularly, this study investigates:

1 The impact of Customization of vending machine on Customer Value

2 The impact of Functionality of vending machine on Customer Value

3 The impact of Perceived Risk of using vending machine on Customer Value

4 The impact of Customer value on retailing vending machine patronage

1.4 Significance of the Study

The study will provide helpful implications for marketers in executing marketing and business strategy in Vending machine sector in particular and in retail business in general

1.5 Research methodology and scope

The research conducted on consumer in Ho Chi Minh City is one of the biggest cities

in Vietnam, where it centralizes all trading activities, people can reach new technologies in business activities soonest, and the author can collect data from people from different

provinces and social levels in our country

The main purpose of this research is perceived customer value of consumer in using vending machine Therefore, it’s necessary to only focus on the respondents had used the

vending machine for purchasing prior There are three kinds of vending machine which respondents can use in Ho Chi Minh are Vending massage chair, vending soft drink

machine, and vending exchange coin machine Thus, only respondents had used one of threes kinds of vending machine mentioned above, are chosen to conduct the questionnaires for main survey

The Author applies data analysis tool including Microsoft Excel and SPSS, to handle the collected data and to conduct the research The Author also uses Amos 22 software to run Confirmation Factor Analysis (CFA) and Structural Equation Modeling (SEM), and to check relationships between exogenous variables and endogenous variables in the proposed research model

1.6 The structure of the study

This paper is structured into five chapters Specifically, the contents of each chapter will be presented as follow:

Chapter 1: Introduction

In this part, research background, research problem, research objective, significant of study, research scope and methodology, and structure of study will be presented

subsequently

Chapter 2: Literature review and Hypotheses

In this chapter, the definitions of each concept and an extensive literature review will

be presented Then hypotheses are also developed throughout the previous literatures and finally, the research model will be proposed

Chapter 3: Research Methodology

This chapter mentions about the research design, measurement of constructs,

illustrate the process of conducting the research, and then, data analysis method is also presented to lay the foundation of chapter 4

Chapter 4: Data Analysis and Result

This chapter includes Sample characteristic, descriptive statistic, CFA, SEM and discussion of result

Chapter 5: Conclusion

This chapter includes conclusion, Implications and limitation

CHAPTER 2: LITERATURE REVIEW AND HYPOTHESES

In this chapter, author presented an extensive literature review, proposed hypothesis and research model An literature review focused on knowledge of vending machine, theory related to customer value, retail patronage and relationship of constructs be mentioned by others researches Then, hypotheses were also argued and developed particularly by

previous studies to build a research model in this chapter

2.1 Vending machine

According to Meuter et al (2000), Self-service Technology (SST) was the innovative channel of marketplace transactions that was completely different from traditional channel Particularly, interpersonal contact was not required between customer and service providers, customer have to perform entire service by themselves without direct support of employees (Bitner et al., 2002) The types of SSTs deployed by service providers include self-service gas stations, launderettes, and vending machines (Bateson, 1985);self- health diagnosis, ATMs, Online Banking and buffet restaurant (Meuter et al., 2000); and in this study, author only focus on one of types of SSTs is vending machine

Vending machine is a machine which dispenses items such as snacks, beverages, alcohol, cigarettes, consumer products, after the customer insert the currency or credit card into the machine For marketers, vending machine supported to increase the reach and intensity of their retail distributor network They usually were placed outdoors and in

unattended environments such as large retail stores, hospital, gasoline station, offices,

railway station, airport, shopping malls (Lee, 2003) For customer, vending machines

offered the convenience, time saving benefit and 24-hours availability and reasonably fresh and ready to serve products (Quelch and Tekeuchi, 1981)

As mentioned above, Vending machine was one of types of SSTs; it therefore

inherited adequately SSTs’ characteristics in the past researches For instance, a self-service model predicting customer acceptance of SST was proposed by Globerson and Maggard (1991) that based on seven factors: convenience, time saving, self-control, money saved, self-image, perceived risk and self-fulfillment; Meuter et al (2000) also proposed ease of use, the ability to avoid interference from service people, time saving, convenience, and

financial saving as the factors impacting the adoption of SST, and ease of use was the most important factor; service quality of SSTs included seven dimensions: Functionality,

Convenience, Enjoyment, Privacy, Assurance, Design, and Customization, in where,

Functionality represents responsiveness, reliability and ease of use of SSTs, and

Customization referred to extent of an SST can be altered to meet individual customer preferences and transaction histories (Lin and Hsieh, 2011) On the other hand, Ho and Ko (2008) proved that SST characteristics have positive effect on Customer Value Therefore, based on the literature regarding to Vending machine, the current study examines perceived risk, functionality and customization to determine customer value of vending machine sector

2.2 Customer value

The concept of value has been applied in various fields of study, such as economics, social science, accounting, finance, strategy, product management, information system, and marketing (Huber et al., 2001; Ulaga and Chacour, 2001) Customers acknowledged service value through desired purpose or goal achieved (Overby, 2005) Thus, in-depth

understanding of customer value construct was highly important

The concept of customer value was often perceived as an ambiguous and

multifaceted word (Parasuraman, 1997) Many authors had acknowledged the difficulties involved in defining customer value (e.g Piercy and Morgan, 1997; Woodruff, 1997) Therefore, many definition of customer value were proposed by many authors For instance, Holbrook (1994) defined customer value as “an interactive relativistic preference

experience” (p.5), and Woodruff (1997) expanded the concept of customer value as “a customer’s perceived preference for and evaluation of those product attributes, attribute performance, and consequences arising from use that facilitate (or block) achieving the customer’s goal and purposes in use situation”(p.142) Customer value was also defined by Chen and Dubinsky (2003) as “a consumer’s perception of the net benefits gained in

exchange for the cost incurred in obtaining the desired benefits” (p.326) However, there was a general agreement in the literature that customer value was determined by

“customers’ perception not by suppliers” assumptions or intentions (Anderson and Narus,

1998; Woodruff and Gardial, 1996; Zeithaml, 1988); as Doyle (1989, p.83) put it: value is

“not what the producer puts in, but what the customers get out” Based on those, in this study, author used the common definition of customer value proposed by Hanny and Felix (2009), is as “tradeoff between total perceived benefit and total perceived scarify” (p.480)

Sheth et al (1991) argued that customer value was determined by five factors:

functional value, epistemic value, social value, emotional value and conditional value Functional performance, economic utility, and benefit associated with possessing the service express functional value It is a concept of economic benefits of the trade-off between

quality and price and is presumed to be the primary driver of customer choice (Sheth et al., 1991; Sweeney and Soutal, 2001) Customer’s feelings, for instance, love or hate,

comfortable or uncomfortable, happy or sad, etc when they experienced an organization’s product or service represent emotional value Epistemic value is the capacity of services or products to provide novelty or curiosity and satisfy a desire for knowledge (Sheth et al., 1991) Social value is limited to specific social groups (e.g., cultural-ethnic groups) Finally, conditional value relate to special cases, such as an illness or some specific social situation (Sheth et al., 1991; Sweeney and Soutal, 2001)

2.3 Customization and Functionality

The term of customization was defined as “Tailoring the product to the special and unique needs of the customer Each buyer is potentially a unique segment" (Bennett, 1988,

p 51) or "to build, fit, or alter according to individual specifications" (p 281) by Webster (1973) Customization was one of the important factors which marketers paid more

attention to satisfy their each of specific customer segments Terptra (1981) first brought the idea of product customization to the academician’s attention He also stated that “the idea of product "appropriateness" was a legitimate one” (p.54) There were many different cultures and traditions all over the world Each of them had different style of behavior and style leading to each of people’s demand in different cultures was completely different By this, understanding clearly specific customer’s demand was the key supported marketers to

design product or service meeting well for their own customer’s demand

In marketing context, the functionality was defined as “what product does for the buyers and users; utility it offers the user; what he or she can do with it” (Yellow pencil, 2006) Functionality referred to the ability of product or service to facilitate performance and the accomplishment of service customer goal It also was considered to be particular importance because physical settings of vending machine were purposeful environment that exists to fulfill specific needs of customers

On the other hand, functionality and customization are two of dimensions of service quality construct (Lin & Hsieh, 2011) Service, by providing additional value for customers, leads to increased customer satisfaction, though the relationship between service and

satisfaction can be non-linear (Anderson and Mittal, 2000) In addition, service quality is thought to lead to increases in firm profitability and market value through the service–profit chain (Heskett et al 1994) That’s the main reason why service quality has long been

recognized as a key factor for creating customer value Based on literatures above, the following hypotheses were proposed:

H1 Customization of vending machine is positively related to customer value

H2 Functionality of vending machine is positively related to customer value

2.4 Perceived risk

Risk was defined as term of uncertainly and consequences associated with

consumer’s action (Bauer, 1960) Base on this, many studies had adopted this definition to define the construct of perceived risk, such as Cunningham (1967) argued that “perceived risk as a consumer’s perception of the uncertainty and adverse consequences associated with buying a product or service” (p 91) or Dowling and Staelin (1994) understood that

“perceived risk is determined by the distinction between inherent risk and handle risk” (p.121) In general, perceived risk referred that consumer purchase behavior may cause some unexpected results and these results may cause unpleasant experience (Bauer, 1960) Imaging that, customers always had their purchase goal each time when they wanted to buy something (product or service) However, in some cases, customers did not know which purchase decision was the best choice could meet their goal at the best As a result, it would cause unfavorable results and shape a risk consciousness (Cox, 1967)

Perceived risk was a multi-dimension construct including losses and risk factors, which together, explain overall risk related to purchase or use a product or service The identified dimensions were financial, function, psychological, social, time, and physical (Roselius, 1971) In this study, four dimensions chosen to explain the risk in using vending machine were psychological, social, privacy, and time wasting

Perceived risk was one of the factors to influence customer value Sweeny, Soutar, and Johnson (1999) said that customer value mean a tradeoff between benefits and sacrifices

of product or service from consumer’s point of view Therefore, customer value was

affected by sacrifices and sacrifices equal to perceived risk On the other hand, many studies proved that perceived risk could reduce the customer value (Agarwal and Teas, 2001; Chen and Dubinsky, 2003) Based on that, the present study proposed the following hypothesis: H3: Perceived risk of vending machine users is negatively related to customer value

2.5 Customer value and retail patronage

Retail patronage behavior was studied in many empirical researches (Lee, H.Y., Fairhurst, A.E., & Lee, M.Y., 2009) Lee et al, (2009) also argued that retail patronage behavior can explain the mechanism of store choice As a result, it has been a critical issue for academicians and retail managers However, because of the dynamic nature of patronage behavior, a comprehensive picture of retail patronage behavior is a complicated model Laaksomen (1993) defines patronage as “all the possible inner features of dynamism around the shopping behavior phenomenon in terms of store choice” (p.9) Thus, retail patronage was focused on the identification of relevant attributes by one key research stream Firstly, according to Hartley (1980), understanding consumer’s patronage motives can reinforce the basic determinants for consumer buying behavior Hartley (1980) also defined patronage motives as the reasons why customers choose in many different stores and proposed that

“customer considered about patronage factors which indicated the reasons why they shop stores The patronage factors consist of: Convenience _ Location, hour working, shopping ease; Assortment of merchandise _ Variety or limited; Quality and fashion level of goods _ High quality and fashion; Prices _ Lower price; Service _ Credit Card, delivery, return-goods, and knowledgeable sales staff; Excitement _ promotional effort, use of celebrities

and fashion show” (p.77) Secondly, Morgenstein and Strongin (1992) stated that patronage motives as “the reasons why customer choose one place to shop rather than other and

include special brand, attractive facilities, personal service, conveniences, goods value, attentive salespeople, and a good store image” (p 124) Finally, Pan and Zinkhan (2006) categorized a large number of determinants of retail patronage that were frequently

examined in prior studies into three factors: product-relevant factors, market-relevant

factors, and personal factors Product-relevant factors is related to function of product and attributes (product quality, assortment, and price); market-relevant factors pertained to service offered by store with respect to convenience, service quality, store image and

atmosphere, and salespeople; and personal factors refer to consumer characteristic (e.g age, gender, income, and so on)

According to Lee et al (2009), three groups of determinants including product

quality, service quality, and assortment had the strongest influence to consumers’ decision

to patronize a particular store This finding presented clearly the importance of service quality as a key to achieve retail patronage Furthermore, Yieh & Wei (2012) also stated that customer value was a crucial instrument for analyzing service quality Therefore, the

following hypothesis is suggested:

H4 Customer value is positively related to retailing vending machine patronage

2.6 Research model

Based on the literature review and the hypotheses developed, the following research model was proposed

Figure 1: Conceptual Model

Summary

Theoretical background and definitions of each concept in the research model is presented in this chapter Based on the literature review, the relationships of concepts are argued, thus, functionality, Customization and perceived risk are antecedents impacting customer value, and Customer value influence to retail patronage There are four hypotheses

in research model

respondents in Ho Chi Minh City After the preliminary questionnaire had been translated into Vietnamese, the researcher interviewed deeply with 8 people who used the vending machine prior to answer the questionnaire to obtain correct items in the context of

Vietnamese consumers, check the meaning of words in original measurement scales and modify them to be more suitable and easier to understand This step is very important due to there are many differences between meaning in English and Vietnamese, as well as English level of translator, made misunderstanding or not convey enough the meaning of the

original scales After finish this step, most of measurement scales would be refined to be

easy to understand and to be meaningful in context of the study

3.1.2 Quantitative research

After qualitative research, a refined questionnaire was completed to be more

appropriate with Vietnam market, especially Ho Chi Minh City market Consumers in Ho Chi Minh City would be chosen to interview for main survey in this study for using

convenient sample The process of quantitative research was conducted by the following steps:

Step 1: Composing the questionnaire for the research

Questionnaire was designed in English, and then the author translated into

Vietnamese for delivering to respondents (See Appendix A and B)

Step 2: Defining sample size of the research

According to Hair et al (2010) the sample size should be 100 or greater and

minimum sample equal five observations for each item The proposed research model has five factors with 48 scales Therefore, the minimum sample size should be: 48*5 = 240 observations

On the other hand, to test the theoretical and model and hypotheses by Structure Equation Model (SEM) method, the minimum required sample should be 200 observations

The current study used the sample size at 247 observations, so it’s appropriated for CFA and SEM analysis compare to mentioned general rules above After that, author used convenience sampling method to conduct sampling All respondents were asked whether they have ever used vending machine before answering the questionnaire

Step 3: Delivering the questionnaire to the interviewees

The questionnaire is sent to interviewees as two ways First, the respondents would

be received hard copies to answer the questions by author at Universities, Companies and Organizations in HCM City Second, to be more convenient for respondents, the

questionnaires were also broadcasted via internet by Google Docs Thus, a survey link was sent to respondents via email address, Facebook page and Yahoo messenger To answer the questionnaire, respondents click on the link, type their answer and choose the answer they agree or disagree as the 5-points Linkers type and submit the link to researcher To make sure that, all of respondents can understand clearly about vending machine at beginning of interviews, a short description of vending machine was presented for reference purpose Additionally, some real pictures of vending machine on market were also added in

Introduction part to make respondents easy to image

Data were collected during one month To achieve total of 247 samples, the author issued 250 questionnaires in hard copy and sent 200 emails to respondents Firstly, 250 hard copies were delivered author’s colleagues at the work place, author’s friends working in Ho Chi Minh City, students at University of Economic Ho Chi Minh city, and the number of customers who have just used vending massage chairs or vending soft-drink machine or vending coin exchange machine at Trade center, Hospital, Game Zone and Cinema The

result is, author received 176 answers in hard copy from respondents Secondly, 158

feedbacks were sent to author by partners, current customers who author usually gets in touch, classmates at Master of Business Administration program at ISB School and some friends on Facebook and Yahoo Messenger Finally, 176 answers in hard copy and 158 feedbacks via online channel were delivered author Totally, the author received 334

answers from respondents

Step 4: Checking the answers, coding and input data

After checking the answer, the error answers which were missed answers or answer with only one value such as “1”, “2”,“3”, “4” and “5”, or were checked as zigzag line, were removed out of final data to analyze Besides, author also eliminated the answers which respondents chose answer was “no” when they were asked: “Have you ever used Vending machine?” As a result, 87 responses of total of 334 ones were eliminated; total included 247 answers in final The final sample is suitable to the requirement of minimum sample size:

240 observations The following table summarized collected data from the survey

Table 3.1: The result of collected data

Number of questionnaire were delivered

Number of questionnaire were returned

Percentage

Total of sample used for the main survey

Based on the result shown in table 2, the percentage of number of returned

questionnaire in hard copy is more than ones in online channel, and total of sample used for the main survey in hard copy is also more than that of online channel The reason is laying the way author choose the sample For hard copy, respondents were asked whether they had ever used vending machine, and author only delivered questionnaire to respondents

answered “yes” Therefore, most of returned questionnaires in hard copy were not removed out of the final sample by this reason On the other hand, because author joined with

respondents when they answered the hard copy questionnaire, so they conducted strictly and

honestly While conducting the survey throughout online channel, some respondents could answer that they have never used vending machine to stop the survey although they used to purchase something by vending machine in real Furthermore, respondents trended to click randomly answers to finish the questionnaire as soon as possible, and the most popular way was clicking all answers as the same such as only “3” or “1” As the result, these

questionnaires were removed for data analysis

Data from hard copy questionnaires were typed and the answers were submitted via Google Docs tool were also copied and pasted in Excel File together After that, data were reviewed for completion, coded and input raw data in IBM SPSS Statistic Version 16 with the scales as mentioned in measurement scales part

Figure 2: Research process

3.2 Research design

This study aimed to investigate how customer value influences on customer’s

retailing patronage behavior and the antecedents (customization, functionality and perceived risk) of customer value in vending machine sector in Vietnam Therefore, a research model

was proposed as Figure 1 This research used primary data that collected from participants

who were required to have used Vending machine services prior to completing the survey

Particularly, data was collected from customers who used Vending massage chairs, vending coin exchange machine and soft-drink vending machines at Trade center, Supermarket, Mall, Hospital, Cineplex, and Game Zone in Ho Chi Minh City

3.3 Measurements of constructs

Established scales were used, or adapted for use, where possible to measure each of investigated constructs All items were measured on 5-point Linkers-type Where necessary, the survey questions were slightly adapted to reflect the industries investigated

Four first order constructs (functionality, customization, perceived risk and retailing vending machine patronage) and one second order construct (customer value) were used in this study

Customer value of each respondent was measured by Lin & Huang (2012) and

Sweeny & Soutar (2001) Customer value was a second order construct comprising five components: functional value, emotional value, social value, and epistemic value

Functional value was measured by ten items, expressing functional performance, economic utility, and benefits associated with using vending machine Emotional value was measured

by five items, addressing degree of customer’s feeling when they use vending machine to purchase products or services While epistemic value was measured by five items assessing respondents’ level of curiosity and desire for knowledge with vending machine Finally, Social value and conditional value were measured by four and five items to ask respondents about culture-ethnic group and value related to special cases such as promotion, discount, and environment pollution

Measurement of Functionality and Customization of vending machine were based on Lin and Hsieh (2011) scales Functionality was measured by five items to assess

respondents’ perception of responsiveness, reliability, and ease of use Customization

measured by asking respondents about degree of understanding specific needs,

personalization of vending machine

Perceived risk was measured by using eight-item perceived risk scale adapted from Rafale et al (2012), to assess four dimensions chosen to explain the risk in using vending machine were psychological, social, privacy, and time wasting

Retailing vending machine patronage construct was measured by five items adapted from Hoizer and Stem (1985) scale embodying degree of respondents’ choice between purchasing by vending machine and other retail channels

The detailed list of scale items was presented as the following table

Table 3.2: Measurement scales

point

Reference

Functionality I can get my service done with the vending

machine in a short time

Strongly disagree /strongly agree

Lin & Hsieh (2011)

The service process of the vending machine is clear

Using the vending machine requires little effort

I can get my service done smoothly with the vending machine

Each service item/function of the vending machine is error-free

Customization The vending machine understands my specific

disagree /strongly agree

The vending machine has my best interests at heart

The vending machine has feartures that are personalized for me

The vending machine service is well made

The vending machine service has an acceptable standard of quality

The vending machine service would perform consistently

The vending machine service has poor workmanship.(R)

The vending machine service would last a long time

The vending machine service is reasonably priced

The vending machine service offers value for money

The vending machine service is good product for the price

The vending machine service would be economical

Emotional Value

Vending machine service is one that I would enjoy

Strongly disagree /strongly Vending machine service make me want to use

it agree Vending machine service is one that I would

feel relaxed about using it Using Vending machine service would give me pleasure

Using vending machine would make me feel good

Epistemic Value

Lin & Huang, (2012)

Before using the vending machine, I would obtain substantial information about the different makes and models of vending machine Strongly

disagree /strongly agree

I would acquire a great deal of information about the different makes and models before using vending machine

I am willing to seek out novel information

I like to search for the new and different

Using vending machine would help me to feel acceptable

Vending machine service would help me make a good impression on other people

Using Vending machine service would give its users the social approval

Conditional Value

Lin & Huang, (2012)

I would use vending machine instead of conventional stores under worsening environmental conditions

Strongly disagree /strongly agree

I would use vending machine instead of conventional stores when there is a subsidy for using vending machine

I would use vending machine instead of conventional stores when there are discount rates for using vending machine or promotional activity

I would using vending machine instead of conventional stores when vending machine are available

Because I am more familiar with vending machine, I prefer shopping by vending machine than other retail channels

I shop by vending machine even when the selection/variety of goods is poor

Perceived Risk By using Vending Machine, it is highly likely

that my personal information will be used by other people

Strongly disagree /strongly agree

Rafale et al (2012)

Using the vending machine endanger my privacy because of wrongful use of my personal details

Sometimes, I experience unnecessary stress while using the vending machine

Sometime, when I am using machine I feel anxious

I am concerned about wasting too much time using the vending machine

I am concerned about having to waste time on tasks related to using the vending machine Using vending machine can worsen the image other people have of me

Using vending machine makes some people whose opinion I value think that I am not acting correctly

3.4 Data analysis method

Firstly, SPSS version 16 and Microsoft Excel 2007 were used for sample description Secondly, Descriptive Statistics had been also used to check collected data before author proceeded to analyze main indices Then, Reliability and validity of measurement scale were assessed by using Confirmatory Factor analysis Finally, Structure Equation Modeling was used to test the structure model

3.4.1 Descriptive Statistics

According to Loether and McTavish, “Descriptive Statistics are used to help the researchers and consumers of research reports understand more about the research data They assist with understanding how the data are distributed across the possible range of value; with knowing whether or not the shape of variable is normal; and with understand whether one’s subjects tend to clump together in one spot on the distribution or if they are widely scattered through out the possible range of value” (as cited in Marry, L M, 2003, p.35) A wide variety of descriptive statistics is used in research (Marry, L.M, 2003), but in this study we used measures of shape to check distribution of variables Thus, Marry, L.M, (2003) also argued that “the shape for variables that is the most useful for most of data

analyzing testing is normal distribution, often called the bell-shape curve” (p.111) In this study, to test normality of the shape of distribution, two descriptive statistics: Skewness and Kurtosis were used

3.4.1.1 Test of Skewness

Glass & Hopkin (1996) stated that “skew measures whether the two halves of the distribution are symmetrical” and “a normal distribution is presented by a value that ranges from ±2 Values much lower than -2 or higher than +2, denote a skewed rather than normal distribution” (as cited in Mary, L.M, 2003, p.111)

3.4.1.2 Test of Kurtosis

Similarly, Mary, L.M (2003) also mentioned that “a distribution should be nicely and evenly rounded _ neither too peak like a pencil peak up on the graph, nor too flat, like a low hill And the Kurtosis statistic in SPSS must be between ±2” (p.112)

3.4.2 Confirmatory factors Analysis (CFA)

James et al, (2006) stated that “Confirmatory factor analysis (CFA) is a confirmatory technique – it is theory driven Therefore, planning of the analysis is driven by theoretical relationships among the observed and unobserved variables When a CFA is conducted, a hypothesized model is used to estimate a population covariance matrix that is compared with the observed covariance matrix” (p.323) CFA is used to test reliability and validity of measurement prior to testing a structure model (James et al, 2006)

3.4.2.1 Reliability testing

The composite reliability is used to test the reliability of measurement scales

According to Hair et al (2010), the composite reliability estimates the extent to which a set

of latent construct indicators share in their measurement of a construct Composite

reliability should exceed 0.7 (as cited in Shu-Hsun and Ying-Kin, 2008)

3.4.2.3 Discriminant validity

Based on the result of correlations of constructs, and Chi-square different test,

discriminant validity of measurement scales is test Chi-square different test “allows

researchers to compare two models, one in which the construct are correlated, and one in which they are not When the test is significant the constructs presents discriminant

validity” (as cited in Zait and Bertea 2011, p.218)

3.4.3 Structure Equation Modeling (SEM)

James et al, (2006) liked to think that “SEM as CFA and multiple regressions

because SEM is more confirmatory technique, but it also is used for exploration purpose” (p.325) To determine how well a proposed model fits the sample data and demonstrates which one the most superior fit, a group of fit indices including Chi-Square test, RMR and SRMR, CFI and RMSEA, is used to assess the degree of model fit In where,

According to Hu and Bentler (1999), “Chi-Square value is the traditional measure for evaluating overall model fit, and assesses the magnitude of discrepancy between the sample and fitted covariances matrices”

“RMSEA tells us how well model, with unknown but optimally chosen parameters estimates would fit the populations’ covariance matrix” (Diamantopoulos and Siguaw,

2000, p 85)

“The RMR and SRMR are the square root of the different between the residuals of the sample covariance matrix and the hypothesized covariance model” (Hooper et al, 2008, p.54)

“CFI_ Comparative fix index, assumes that all latent variables are uncorrelated (null/independent model) and compares the sample covariance matrix with this null model” (Hooper at al, 2008, p.55) According to Hu and Bentler (1999), value for this statistic should be greater than 0.9 in order to ensure that misspecified models are not accepted

3.4.4 Bootstrap

To evaluate reliability of the estimates in quantitative research by sampling method, authors divided big sample into two parts First one is used to calculate parameters of the research model; other is used to re-assess the result above Another way, authors have to re-

sampling to test Two these ways require to spend more time and expense on collecting data and are not effective in practice, especially in SEM method required a large sample In case

of this, bootstrap is the most suitable method to replace for two methods above According

to Hilmer (2001),

“The goal of bootstrap is to use the sample data to mimic the overall population distribution by re-sampling from the data to calculate an estimates sampling distribution For an initial sample data set of size n, this is accomplished by drawing a random sample of size n with replacement from the initial sample data set, calculating the parameter of interest for the sample drawn, and repeating the process many times The bootstrap estimator is then the average cross all of the parameter estimates from the different bootstrap sample This intuition behind methodology is that the distribution of the parameter estimates from the bootstrap sample mimics the traditional sampling distribution parameter estimates for samples drawn from the population distribution Hence, the bootstrap technique allows the researcher to generate an estimated sampling distribution in cases in which she/he only has assess to a single sample rather than the entire population” (p.6-p.7)

Summary

This chapter presented four main contents including: research design, measurement scales of contrasts, research process and data analysis method Qualitative research and quantitative research are two periods of search process First, Qualitative research is

conducted in-dept interview with eight respondents to check if meaning of scales in

Vietnamese translated from scales in original English version is easy to understand and suitable with context of research Second, Quantitative research, author organized in to four steps, including: Composing the questionnaire, defining the sample size, delivery the

questionnaire to respondents, and receiving, checking and coding data for input into SPSS software the answers from respondents Total of sample used for final analysis is 247

Finally, data analysis method was also presented in this chapter The next chapter will

present the data analysis and result of main survey

CHAPTER 4: DATA ANALYSIS AND RESULTS

The research result was reported in this chapter Firstly, sample characteristic was presented Next, descriptive statistics including Skewness and Kurtosis were conducted to check distribution variables Furthermore, reliability and validity of scales were also

checked by running Confirmatory Factor Analysis Finally, SEM model was used to test research model

4.1 Sample characteristic

There were 39.9% male and 60.7% female valid subjects included in the total data sample Among these, 26-35 years-old accounted for 45.7%, 18-25 years-old accounted for 38.9%, 36-45 years-old accounted for 12.9%, and 46-60 years-old accounted for 2% Only 0.5% of valid sample was 10-17 years-old Regarding to education, people had

college/university degrees occupied 68.8%, MBA occupied 21.5%, high school was about 8.9% and under high school was only 0.8% In terms of occupation, most of respondents were office staff accounted for 66%, manager/businessmen was about 11.3%, retirement accounted for 10.6%, student occupied 10.1%, and the remainder working as worker Finally, in terms of income, ranking from less than five millions to more than 15 millions, the largest income group was from five millions to less than 10 millions, accounted for 47%, the second was less than five millions (occupied 19%), the third was from 10 millions

to less than 15 million (occupied 17.4%), and more than 15 millions accounted for 16.6% All respondents confirmed that they had used the vending machine before they proceed to answer the questionnaire

Table 4.1: Sample Characteristic

18-25 26-35 36-45 46-60

2

0

Education Under high school

High school College/University MBA

Occupation Official Staff

Student Worker Manager/Businessmen Retirement

2 11.3 10.6

4.2 Descriptive statistics

As author mentioned in Chapter 3, the normal distribution is presented when

Skewness and Kurtosis statistic must be between ±2 Therefore, the Skewness and Kurtosis value of any item are much lower than -2 or higher than +2, will be eliminated measurement

scales before running CFA The result of Skewness and Kurtosis were summarized in below table

Table 4.2: The result of Skewness and Kurtosis testing

Descriptive Statistics

N Minimum Maximum Mean

Std

Deviation Skewness Kurtosis

Statistic Statistic Statistic Statistic Statistic Statistic

Std

Error Statistic

Std Error

4.3 Confirmatory Factor Analysis (CFA)

The research model had four first-order constructs consisted of Functionality,

Customization, Perceived Risk and Retailing Vending Machine Patronage, and one order construct were Customer Value having five components: Functional Value, Emotional

second-assess the measurement models of each construct And, then the final measurement model would be conducted to test reliability and validity, before structure equation modeling was used to test the theoretical model and hypotheses

For first order constructs, the author run CFA separately for each construct as the following figure:

Figure 3: CFA of first-order constructs

The result indicated that the CFA models of Customization (P = 0.000 (< 0.05), CMIN/df = 1.368, RMR = 0.033, CFI = 0.998, RMSEA = 0.039), Functionality ( P = 0.000 (< 0.05), CMIN/df = 1.557, RMR = 0.024, CFI = 0.994, RMSEA = 0.048), Perceived Risk (P = 0.000 (< 0.05), CMIN/df = 2.558, RMR = 0.059, CFI = 0.973, RMSEA = 0.08) and Retailing Vending Machine Patronage (P = 0.000 (< 0.05), CMIN/df = 1.578, RMR =