The mediating role of trust in the relationship between key account management programs and commitment, a dealer perspective

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITYNG THE MEDIATING ROLE OF TRUST IN THE RELATIONSHIP BETWEEN KEY ACCOUNT MANAGEMENT PROGRAMS AND COMMITMENT: A DEAL

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY

NG

THE MEDIATING ROLE OF TRUST IN THE

RELATIONSHIP BETWEEN KEY ACCOUNT MANAGEMENT PROGRAMS AND COMMITMENT:

A DEALER PERSPECTIVE

MASTER THESIS

Ho Chi Minh City – 2012

THE MEDIATING ROLE OF TRUST IN THE

RELATIONSHIP BETWEEN KEY ACCOUNT MANAGEMENT PROGRAMS AND COMMITMENT:

A DEALER PERSPECTIVE

MASTER THESIS

In Business Administration

ACKNOWLEDGEMENT

I would like to give my sincere thanks to Dr Nguy n Th Mai Trang, who haddedicatedly instructed me to approach every particular matter from the research methodguidance to intensive support and valuable suggestions for the final completion of thisthesis

I would also like to express my gratefulness to the respected teachers from theUniversity of Economics Ho Chi Minh City for their devotions in training andeducation We inherited much knowledge and experiences thanks to them

I truly appreciate the helps of my colleagues, my friends in eMBA class courseK19, and my partners This research could not be completed successfully if such helps

of knowledge and field work data collection were not supported by them

My special thanks are given to my beloved family and my wife, Phạm Ngọc

P ươ g Trúc who has encouraged me much to complete this thesis

Ho Chi Minh City, October 2012.Nguy n Hải Đô

TABLE OF CONTENT

ACKNOWLEDGEMENT i

TABLE OF CONTENT ii

LIST OF FIGURES v

LIST OF TABLES v

ABSTRACT 1

Chapter 1 2

INTRODUCTION 2

1.1 Research background 2

1.2 Problem statement 3

1.3 Research questions 4

1.4 Research objectives 4

1.5 Research Methodology and Scope 5

1.6 Structure of the research 5

Chapter 2 7

LITERATURE REVIEW 7

2.1 Introduction 7

2.2 High-technology attributes and their effects 8

2.2.1 High technology attributes 8

2.2.2 Effects of high-tech attributes: 10

2.3 Trust 12

2.4 Key Account Management (KAM) programs 12

2.4.1 Responsiveness 13

2.4.2 Information 14

2.4.3 Logistics 15

2.4.4 Tailor-made promotions 16

2.5 Commitment 16

2.6 Conceptual Model 17

2.7 Summary of hypotheses 18

Chapter 3 19

METHODOLOGY 19

3.1 Introduction 19

3.2 Research design 19

3.3 Measurement 19

3.3.1 Independent variables 21

3.3.1.1 Responsiveness 21

3.3.1.2 Information 21

3.3.1.3 Logistics 22

3.3.1.3 Tailor-made promotions 22

3.3.2 Dependent variables 23

3.3.2.1 Trust 23

3.3.2.2 Commitment 24

3.4 Questionnaire translation 24

3.4 Pilot study 25

3.5 Main study 25

3.6 Research sampling 26

3.6.1 Sample size 26

3.6.2 Selecting the samples 26

3.6.3 Collecting data 27

3.7 Statistical tools 28

3.7.1 Cleaning data process 28

3.7.2 Reliability 28

3.7.3 Explanatory Factor Analysis 28

3.7.4 Regression analysis 29

3.8 Conclusion 29

Chapter 4 30

DATA ANALYSIS AND RESULTS 30

4.1 Introduction 30

4.2 Data cleaning 30

4.3 Description of the qualified respondents 30

4.4 Reliability Test of measurement 31

4.5 Exploratory Factor Analysis 32

4.6 Analysis of correlations 37

4.7 Test of Hypotheses 37

4.7.1 Test the appropriateness of model and assumptions for MLR 37

4 7 2 e effects of KAM P o ams’ facto s o t st (H1, H2a, H2b, H3, a d H4) 38 4.7.3 The effect of Trust on Commitment 41

4.8 Conclusions 42

Chapter 5 43

DISCUSSION AND IMPLICATIONS 43

5.1 Findings of the study 43

5.2 Practical implications 46

5.3 Contributions of the study 47

5.4 Limitations and recommendations for future research 48

LIST OF REFERENCES 49

APPENDIX IA: QUESTIONNAIRE (Vietnamese version) 53

APPENDIX IB: Results of the quantitative pilot study 55

APPENDIX II: Descriptive statistics of variables 57

APPE IX III: Meas eme t scales eliabilit of o i i al model’s va iables 58

APPENDIX IV: Measurement scales eliabilit of adj sted model’s ew va iables 61

APPENDIX V: Exploratory Factor Analysis (EFA) 62

APPENDIX VI: Test of MLR assumptions 70

LIST OF FIGURES Figure 2.1: Proposed research model 18

Figure 3.1: The process of the study 20

Figure 4.1: Adjusted research model 36

Figure 4.2: Results of model 1 40

Figure 4.3: Results of model 2 42

LIST OF TABLES Table 3.1: Responsiveness Scale 21

Table 3.2: Information Scale 21

Table 3.3: Logistics Scale 22

Table 3.4: Tailor-made promotions Scale 22

Table 3.5: Tailor-made promotions Scale 23

Table 3.6: Commitment Scale 24

Table 4.1: Characteristics of the samples 31

able 4 2: S mma of C o bac ’s Alp a of meas eme t scales 32

Table 4.3: Rotated Component Matrix 34

able 4 4: S mma of C o bac ’s Alp as wit 2 ew 35

Table 4.5: Correlation matrix 37

Table 4.6: Multiple Linear Regression: Model 1 Summary 39

Table 4.7: Multiple Linear Regression: Model 1 ANOVA 39

Table 4.8: Multiple Linear Regression: Model 1 Coefficients 39

Table 4.9: Multiple Linear Regression: Model 2 Summary 41

Table 4.10: Multiple Linear Regression: Model 2 ANOVA 41

Table 4.11: Multiple Linear Regression: Model 2 Coefficients 41

Table 5.1: The effects of sub-dimensions of Key Account Programs on Trust 45

In a fast-changing environment of high-tech industry in Vietnam, the role of keyaccount management programs has been realized to be truly important as it buildsstrong commitment between suppliers and dealers This study aims at exploring theeffects of ke acco t ma a eme t p o ams’ facto s to t st a d co seq e tl , t st’s effect tocommitment

A survey was conducted with a sample of 202 respondents who are purchasingmanagers, owners and shop/floor managers represents for 8 key accounts in the high-tech industry Exploratory factor analysis and multiple linear regression was employed

to analyze the data

It was found that Marketing and Sales Information, Product Information,Responsiveness and Logistics have positive effects on Trust while Tailor-madePromotions was not significantly related to Trust Finally, Trust has a positive effect onCommitment

The results of this study suggest that suppliers should invest more resources inexchange information with dealers, especially marketing and sales information;responsiveness, logistics and product information are also deserved to invest time andeffort in order to enhance trust and consequently consolidate commitment This studycontributes to the extant literature on key account management programs and is thefirst kind to explore in the high-tech industry in Vietnam

Keywords: Key account management programs, trust, commitment, Vietnam,

high-tech industry

Chapter 1 INTRODUCTION

Key Account Management (KAM) has been received so many interests as most

of sales turnover generated by key customers (Shapiro and Moriarty, 1982; Cespedes,1992) For enterprises who deal in high-tech industry, key accounts play a strategic role

in their short and long run Such strategic customers deserve to be paid more attention

by suppliers Suppliers have the sound reasons to invest more resources in the keyresellers in order to develop a close and valuable relationship, and maintain high trustbetween the dyad These activities are included in a strategic working design calledKey Account Management Program

Literature has shown that a variety of researches investigating the effects of keyaccount management program on trust and consequently on commitment Researches

by Kumar, 1996; Geyskens et al , 1998 showed that building a program like key

account teams will lead to a high level of trust, and then will lead to a long termcommitment between the dyad This will generate a win-win relationship for a longrun

High technology industry is highly dynamic; it changes very fast as the speed oftechnology circle Technological products become obsolete in a very short period,

value of such products decreases day by day Doing business in this industry requireshigh commitment as the environment is ever changing.

Vietnam is a developing and transformational economy Commitment in doingbusiness is a big problem put ahead for such fast changing industry It is argued thatVietnamese businesses just pay more attention on the short term benefits; they canbreak their commitment at ease to achieve their goals Especially, in such a unstableand fast changing environment like high technology, the problem turns out to be quitepopular In order to catch up with the speed of change in the industry, and long for along term and sustainable development, businesses should develop a strategy inbuilding trust and in turn commitment among those by developing strategic programssuch as key account management programs

In a transitio al eco om like Viet am, t e e’s a lack of researches on suchmentioned constructs, the effects of key account management programs on trust and inturn commitment Especially, little attention has been paid in the high-tech industry.The question put forward is whether such constructs affect to the trust andconsequently commitment in the high tech industry, how strong they are and shouldthey deserve to be invested more in order to build a strategy for long term cooperationbetween dyads Empirical research is deserved to be carried out for a brighter view inorder to draw practical implications by investigating the effects of KAM programs ontrust and in turn commitment

1.2 Problem statement

A number of studies have been carried out on the roles of KAM and its effects on trust

and commitment Willem et al (2004) has investigated the roles of KAM programs in

the fast-moving consumer goods industry Faten Baddar Al-Husan and Ross Brennan(2009) have studied the implementation of strategic account management in anemerging economy in the Arab word to reassert the important roles and effects of the

key/strategic account management programs Such mentioned researches and literatureencourages investments in key account management programs to build trust and long-term commitment from customers In a transitional and emerging economy likeVietnam, such researches on key account managements programs has not, to the

a t o ’s best knowledge, received much interests from researchers, especially, in the field of high-tech industry with a fast-changing environment

Therefore, the problem addressed in this study is to investigate the effects of keyaccount management programs on trust and then on commitment from Vietnamesedealers perspective in the high-tech field, such as telecommunications, electricalappliances, and information technology

1.3 Research questions

This research aims at answering the following questions:

- W at’s t e elatio s ip betwee ke acco t ma a eme t p o ams’ facto s on trust andconsequently on commitment?

- What factors should be deserved for investment in order to build long-term win-win business cooperation?

1 The relationship between responsiveness and trust

2 The relationship between information and trust

3 The relationship between logistics and trust

4 The relationship between tailor-made promotions and trust; and

5 The relationship between trust and commitment

This research will investigate such relationships from Vietnamese dealerperspective Consequently, findings will show some facts, and then practicalimplications are proposed.

1.5 Research Methodology and Scope

This research focuses on surveying 8 key accounts (dealers) in high-tech industrylocated in all the provinces of Vietnam where selected dealers have offices andbranches Total correspondents will be targeted at about 210 samples

The research comprises 2 stages: pilot and main study In the first stage aqualitative approach was used to explore whether the scales for measuring theconstructs are suitable or not Then, some amendments had been made where isnecessary

In the second stage, a quantitative approach was employed By interviewingdealers, data were collected for analysis This phase is to test the reliability of themeasurement scales using C o bac ’s alpha coefficient and Exploratory Factor Analysis(EFA) Multiple Linear Regression analysis (MLR) was employed to test the researchmodel and hypotheses SPSS software version 16 was used for data analysis

1.6 Structure of the research

The structure of this research consists of five chapters:

Chapter 4: Data Analysis and Results

This chapter presents the characteristics of research samples and measures concepts ofthe research Descriptive statistics was used to explore the features of explanatoryvariables, as well as the relationship between the variables

Chapter 5: Discussion and Implications

This chapter presents findings of the study, practical implications, contribution of theresearch Some limitations of the research will be mentioned and directions arerecommended for future research

Chapter 2 LITERATURE REVIEW 2.1 Introduction

In this chapter, a review of the literature will be conducted on key accountmanagement, trust and commitment Relationship among those constructs will bereviewed in the shine of prior studies which will incur some relevant theories Thepurpose of reviewing the literature is to clearly define the constructs and to propose aresearch model, then to generate hypotheses which will be tested in the Vietnamesehigh-tec i d st f om deale ’s pe spective

In a modern business society, KAM has proved its emerging importance;literature has developed with different facets of KAM Nevertheless, althoughempirical studies has been carried out, further research recommendations were urged totest deeper in a different extent, particular context Researches on the relationshipbetween trust and commitment have been conducted in the marketing literature

Geykens et al (1998) summarized important findings that trust can be perceived as an

important mediator between the antecedents of commitment and commitment itself(Morgan and Hunt, 1994)

Therefore, the main purpose in this research is to investigate the relationshipsamong KAM factors and trust then commitment in the business dyads especially in thefield of high-tech industry In the following section, a review of the attributes of high-tech industry and its effects would be presented, then a description of the nature of keyaccount management programs, trust and commitment Following this review, a set ofhypotheses is developed After all, some conclusions will be drawn for further testingpurposes

2.2 High-technology attributes and their effects

2.2.1 High technology attributes

As this research focuses on the high-tech field, attributes of high-tech products should

be defined to characterize and distinguish from other product categories From theextant literature of high-technology marketing, five high-tech attributes were derived

In fact, there are several attributes were generated by extant studies; however, thoseattributes are interrelated although appeared in different texts These five attributescovers mostly dimensions referred in the literature It’s c cial to cla if s c att ib tes andeffects of high-tech industry before deeply discuss about the literature review of theconstructs of the research model Due to such attributes and effects, clearer hypothesesshall be derived These five high-tech attributes and their effects are presented in thefollowing section

Short product life cycle High-tech products have shorter life cycle stages in

comparison with ordinary products (Rosenau, 1988) This means such products willincrease sales sharply in a very short period of time and decrease quickly This shows aconstant technological change, and with its continuous changes, its product life cyclewill be very short for a particular product line

Greater risk of discontinuous change in product technology A discontinuous

change is understood as a change that creates a total change in consumption, customerprofiles… If this happens, business competence will be eliminated because current

k owled e is i capable to develop a d ma ket ew p od cts at’s w i -tech

products have greater chances of discontinuity and becomes obsolete in a very shorttime Weiss and Heide, 1993 referred high-tec att ib te as “unpredictability” It’s t eresult of discontinuous innovation in high-tech industry

Indispensability of associated infrastructure Supporting infrastructure is

considered vital element for a success of high-tech product launch In addition, suchinfrastructure should follow the fast changing speed of high-tech products Forexample, MacInnis and Heslop (1990) and Moriatry and Kosnik (1989) consider theexistence of a well-established service network to be a vital component in themarketing mix of high-tech products For example, a mobile phone device should not

be marketed successfully if mobile network is not well established Supportinginfrastructure includes complementary products which facilitate functioning of thehigh-tech product, vital supplies and spares, service people who have qualified skills toset up and fix the product A high-tech product will become useless if thecomplementary products are not compatible and unavailable; such product will notpenetrate into the market well and will not be accepted by end users

Lack of well-established industry standards High-tech products are developed

continuously to meet the changing demands That means such products should satisfythe same needs operate with different standards To generate a standard for be c ma ki ,

it s o ld take a ve lo time It’s a p edictable p ocess A p od ct

currently appears as dominant design, but a newcomer with a revolutionary design willconfound the market and take the dominant position According to Utterback (1994):

“ A dominant design is the one that wins the allegiance of the market place, theone that competitors and innovators should adhere to if they hope to

comma d si ifica t ma ket s a e”

Take the example of Apple with the re-invention of Iphone, it has defeated to some extent the long dominance of Nokia in the mobile phone market

Uncertainty about product functionality A high-tech product has a high

uncertainty in functional variables Moriatry and Kosnik (1989) consider all such

functionality-related ce tai ties de t e eadi “ma ket elated ce tai t ”From the beginning, an end-user finds it hard to match their needs with benefits of p odct’s offe i s Then, to switch a product to another, it takes very high cost A surveyconducted by O2 network operator (O2, 2012) reported that phone calls are not themain function of the smartphones, but internet, social media, music and games areprevailing while it is originally designed for making a call! Mo eove , it’s reallydifficult to oversee the market changes Those contribute to the high uncertainty level

of high-tech product functionality

2.2.2 Effects of high-tech attributes:

Effects due to the shorter product life-cycles In each stage of the product life-cycle,

there are different consumer segments Butaney and Wortzel (1988) affirmed that when

a apid sta e of p od ct life c cle occ s, t e e’s a change in c stome ’s p ofile Fi ms need toadjust their marketing strategy to target their customer segments on the innovationcurve (Moore, 1991) When technology continuously changes and matures, consumerstend to search for a new criterion to evaluate products (Christensen, 1997) Therefore,dealers and retailers, who represent for suppliers in connection with customersegments, continuously change their orientations Shorter product life cycle affects thedyad relationship on pricing, price tends to decline, consequently affects marketingcosts, margin on the dyad This requires tighter cooperation and high trust between thedyad to optimize business performance for both sides

Effects due to the greater risk of discontinuous change in product technology.

High-tech products are characterized by unpredictable and sudden changes, suchchanges are followed by fluctuation on consumption pattern, user profile,complementary products and demand curve (Robertson, 1971) Those require dealers

to improve their expertise to deal with suppliers Otherwise, dealers will be out of date

Furthermore, suppliers will risk losing ma ket’s co fide ce If close coope atio a d trustare not existed, all above bad effects will cause troubles for both sides.

Effects due to the non-existence of industry standards Moriatry and Kosnik

(1989) stated t at it’s eas fo s pplie s a d dist ibutors to persuade customers if t e e’ eexisti i d st ial sta da ds Lack of t ose, c stome s will spe d mo e time

and effort in search process Firms need to spend more resources in customereducation Moreover, purchasing behavior in high-tech products requires complicatedprocess of seeking and analyzing information at every stage That forces dealers tocollect and learn more knowledge to best serve their customers for winning them Ahigh trust and cooperation manner is vital for achieving that

Effects due to the indispensability of supporting infrastructure Supporting

infrastructure development is very important for high-tech products adoption Dealerswith close contacts with customers will grasp the status of supporting infrastructure inthe market Besides, installation and servicing play key roles in high-tech productofferings (Moriatry and Kosnik, 1989; MacInnis and Heslop, 1990) Suppliers withwell-trained service team, together with good cooperation with dealers will support forthe success of marketing high-tech products

Effects due to the uncertainty in product functionality Customers in high-tech

field really concern about the installation and maintenance as technology is veryadvanced, and becomes obsolete quickly Moreover, the switching cost is quite high Insuch uncertainty, to gain confidence in customers, marketing must focus on creatingrelationship rather selling products (McKenna, 1991) This only happens sincesuppliers and dealers work on an united organization Thus, mutual trust is requiredbetween the dyad

2.3 Trust

Trust was defined as honesty or credibility (Geyskens et al., 1998) In the channel

literature, trust was defined:

[ ] t e fi m’s belief t at a ot e compa will pe fo m actio s t at will es lt in positiveoutcomes for the firm, as well as not take unexpected actions that would result

in negative outcomes for the firm (Anderson and Narus, 1990, p 45)

Butler (1991) suggested trust compositions include ten dimensions Those areintegrity, consistency, promise-fulfillment, receptivity, loyalty, fairness, competence,discretion, openness, and availability In this research, a narrower view of trust isconcerned, where trust is near to ethical treatment of suppliers rather than otherdimensions such as competence, openness, and availability This research measures t stclose to i te it a d p omise f lfillme t f om B tle ’s dime sio s

Trust occurs in cognitive and affect-based forms In cognitive form, trustimplies reliable role performance, cultural-ethnic similarity, and professionalcredentials In affect-based form, trust acts as a function of citizenship behavior andinteraction frequency (McAllister, 1995) (as cited in Robert, 2002)

2.4 Key Account Management (KAM) programs

In order to adapt changes in the business environment, suppliers in business to business(B2B) field applied so called Key Account Management (KAM) programs to catch upwit s c dete mi ed facto s i t e c stome s’ b i be avio s a d dema ds These programs wereestablished to take care of significant customers who have st ate ic impo ta ce i s pplies’ b si ess

The literature on KAM has shown on two main factors, one regarded as smallworking individual groups set up to serve a number of important customers (accounts),i.e selling teams (e.g Cespedes, 1992) The studies on selling teams havepredominantly been concerned with what distinguishes successful from unsuccessfulsales teams The other focused on the management concept of key accountmanagement programs, particularly in connection with buyer/seller relationships (e.g.Shapiro and Moriarty, 1982; Pardo, 1997) This means a focus on enhancement of thedyadic business relationships and the effectiveness of the KAM programs from thisperspective (e.g Cespedes, 1992).

Partly adopted from the model of Willem et al (2004), KAM programs consist

of personal and impersonal factors which effect on the dyad relationship Personalfactors comprise similarity in values and responsiveness In this context, similarity invalues is omitted as it is considered such a factor is not an important one contributed toKAM programs in Vietnamese context in the high-tech field, this dimension will betested further in later studies Impersonal factors consist of three sub-factors:information, logistics and tailor-made promotions

2.4.1 Responsiveness

Responsiveness refers to the extent to which suppliers deal with dealers’ problems in

an allowed time frame and effective manner How patient and willing suppliers will actupon dealers’ complai ts

Time of response is widely acknowledged as a competitive advantage by extantliterature, which raises the importance of supplying the right products at the rightquality, price within a minimum lead-time (Stalk, 1988) To achieve responsiveness,particular types of flexibility to the market should be needed; flexibility is defined byOxfo d ictio a as “abilit to adapt” I ma a eme t lite at e, it is viewed as reaction againstuncertainties internally and externally (Gerwin, 1993)

Literature suggests that suppliers who can respond quickly to changes in

customer demands will significantly improve customer satisfaction (Robert et al.,

2002) As a result, trust will be enhanced as relationship quality and loyalty areestablished due to improved satisfaction In such a dynamic and fast –changingenvironment of high-tech industry with its characterized attributes, responsivenessappears to be more significant than any other fields Therefore,

H1: Responsiveness has a positive effect on Trust.

2.4.2 Information

Information refers the extent of information is importantly exchanged between thesupplier and its buyer (Mohr and Spekman, 1994) Information contents are sharedsuch as inventory, planning, capacity and quality, logistics, new product knowledge,etc…

Sharing of information refers to “s a i of mea i f l a d timel i fo matiobetwee fi ms” (A de so a d a s, 1990, p 44) I fo matio s a i is trulyessential for tightening the dyad relationship (Mohr and Nevin, 1990)

Information sharing brings benefits to the buyer-supplier relationship:information is delivered throughout all parties, a closer relationship between buyer andsupplier, new information is executed accurately and timely (Zhou and Benton, 2007)

Narayanan and Raman (2004) found in their studies on information sharing that

in some cases, information is hidden by supplier to benefit themselves, but eventuallygot failure in the whole supply chain Therefore, information sharing should attach withintegrity to build trust between the dyad for a long-term cooperation

Information plays a critical role in business relationship (Cannon and Homburg,2001) (as cited in Tho, 2011) Information support from suppliers can create value forthe dyadic relationships Once information flow is smoothly transferred from suppliers

to c stome s, c stome s ca a ticipate s pplie s’ st ate ic moves a d pote tial c a es

in the industry In the high-tech industry, changes of information happen quickly withhigh speed, an accurate and continuous flow of information exchanged from supplierswill foster the mutual relationship, hence increase trust Thus,

H2: Information has a positive effect on Trust.

2.4.3 Logistics

Logistical considerations appear in orders taking and fulfilling Anderson and Weitz

(1992) ed s pplie s to make eav i vestme t i lo istics so called “idios c atic

which is to evaluate logistics performance and quality levels

Lo istics q alit s o ld be pa tic la ized t o s pplie ’s se vice facto s to

satisf c stome ’s eq i eme ts ose i cl de: se vice polic , delive s stem,people, and internal organization to assure essential functions, long-term supplier-customer relationship

Logistics operations also reflect the performance of delivery Tho (2011) assertsthat delivery performance contributes to the value of dyadic relationship There arethree aspects of delivery performance: on time, flexibility and accuracy (Ulaga andEggert, 2006) (as cited in Tho, 2011)

Logistics, therefore, plays an important role in building trust and commitment betweenthe dyad on a long-term basis Consequently,

H3: Logistics has a positive effect on Trust.

2.4.4 Tailor-made promotions

Tailor-made promotions refer to promotional activities which are tailored orcustomized for dealers to offer an advantage of differentiation from other programs.The promotional mix comprises advertising, direct marketing, personal selling, salespromotions and public relations (Kotler, 2000: 551) Unlike business-to-customerperspective, in this B2B circumstance, those particular promotional activities are tailor-made for dealers

In high-tech industry, promotional activities needed to be tailored case by casefor different key accounts in order for supplier to effectively run the marketingcampaigns Unlike any other types of customers, key accounts play a crucial role insupplie ’s sales st ate , p omotio al activities s o ld ot be mass w ic is mo e suitable fortraditional accounts Therefore,

H4: Tailor-made Promotions have a positive effect on Trust.

2.5 Commitment

Commitme t efe s to “t e adoptio of a lo -term orientation towards the elatio s ip” (A deson and Weitz, 1992, p 19) and goes beyond a simple evaluation of the costs andbenefits associated with the relationship This describes the willingness to make short-term sacrifices to realize long-term benefits

Buchanen (1974) suggests that commitment comprises subjective facets of elatio s ips “apa t f om p el i st me tal wo t ” Fo i sta ce, commitme t ma consist of affective bonds and felt obligations

Trust and commitment are constituted factors to foster business relationships.The effects of those result in different outcomes: positive attitudes towards therelationship, the encouragement of positive behaviors in partners and positive impacts

on partner performance Positive attitudes consist of a imp oveme t i pa t e ’sacquiescence (Morgan and Hunt, 1994), mutual satisfaction and positive attitudes andintentions towards one another (Mohr and Spekman, 1994) Positive behaviors inpartners are showed in improved cooperation, higher risk-taking, and lower tendency toleave and minimized opportunistic behavior (Ghoshal and Moran, 1996).

st a d commitme t ave bee li ked to et e to imp ove t e d ad’s performance bylowering uncertainty, enhance efficiency and positively affect economic performance(Anderson and Narus, 1990; Morgan and Hunt, 1994) In the high-tech industrycharacterized by its distinct attributes and effects, high trust and commitment are bothrequired and linked together Thus,

H5: Trust has a positive effect on Commitment

2.6 Conceptual Model

Based on the literature review, partly adopted the model of Willem et al (2004), a

conceptual model is developed and shown in the Figure 2.1 The model describes therelationships between factors of KAM programs and trust, and consequently oncommitment

Responsiveness

18

H1 (+)

H5 (+)H3 (+) Trust Commitment Logistics

In reviewing of the literature, hypotheses are summarized as follows:

The effects of Key Accounts Management Programs factors on Trust:

H1: Responsiveness has a positive effect on Trust

H2: Information has a positive effect on Trust

H3: Logistics has a positive effect on Trust

H4: Tailor-made Promotions have a positive effect on Trust

The effect of Trust on commitment:

H5: Trust has a positive effect on Commitment.

Chapter 3 METHODOLOGY

3.1 Introduction

Theoretical framework of the research was discussed in the previous chapter In thischapter, research methodology would be introduced, including research design, co stcts’ measurement scales, sampling, statistical tools used to analyze data and test thehypotheses

3.2 Research design

A descriptive method will be used to measure the constructs in the research A surveywill be conducted to collect data for analyzing The process of the study is shown in thefigure 3.1

The study was carried out in 2 phases: a pilot and a main survey Respondents

we e deale s’ purchasing managers, shop/floor managers and owners Product typeswere mobile phones, information technology, and electrical appliances

3.3 Measurement

All the survey questions were adapted and developed from the measurement scales

from the research conducted by Willem et al (2004) The questionnaire comprises 3

sections: the first section consists of 2 questions regarding the specific brand andsupplier whom the respondents had been dealing with, this section was aimed atdirecting the respondents to respond accurately all the questions in the survey; thesecond section consists of 37 items which were used to measure the constructs in theresearch model Those are Responsiveness, Information, Logistics, Tailor-madePromotions, Trust and Commitment Each item was measured on a seven point Likert

Final measurement

scales

Testing researchmodel and hypotheses

Report Writing

Figure 3.1: The process of the study

3.3.1 Independent variables

Independent variable is also considered as predictors This variable will have aninfluence in dependent variable in a positive or negative manner In this study, theindependent variable is key account management programs which comprise

Responsiveness, Information, Logistics, and Tailor-made Promotions

3.3.1.1 Responsiveness

Respo sive ess is t e exte t to w ic s pplie s deal wit deale ’s p oblems timel a deffectively Responsiveness was measured by 6 criteria introduced by Willem et al.(2004):

Table 3.1: Responsiveness Scale

Responsiveness (Cronbach’s alpha = 949)

It is our belief that the service people of firm

x… take our complaints seriously;

respond politely to our complaints;

are sincerely interested in our problems; undertake

accurate actions to solve our problems undertake

actions to solve our problems in time; and respond

quickly to our complaints

3.3.1.2 Information

Information was evaluated based on 8 aspects, this measurement inherited from

Willem et al (2004):

Table 3.2: Information Scale

Information (Cronbach’s alpha = 891)

We receive from the account manager of firm x…

I1 information about their promotional campaigns for their products;

I2 information about the pricing of their products;

I3 information about their product innovations;

I4 information about their new product introductions;

I5 announcement of plans for trade marketing activities;

I6 announcement of plans for consumer marketing activities;

I7 confirmation about their planned marketing activities; and

I8 samples of in-store promotion materials

3.3.1.3 Logistics

Logistics reflects how suppliers take and fulfill orders, the performance of delivery In this study, logistics was measure by 5 items, taken from Willem et al (2004):

Table 3.3: Logistics Scale

Logistics (Cronbach’s alpha = 883)

Firm x delivers us

L1 their products at the agreed time;

L2 exactly what we have ordered;

L3 the orders without much unnecessary delay;

L4 the orders remain adequate even in the case of rising demand as a consequence of

promotional activities; and

L5 enough info matio abo t t e “o de taki ” i case delive p oblems occ

3.3.1.3 Tailor-made promotions

Tailor-made promotions refer to promotional activities which are tailored orcustomized for dealers to offer an advantage of differentiation from other programs.Tailor-made promotions were measured by 7 items, introduced by Willem et al.(2004):

Table 3.4: Tailor-made promotions Scale

Tailor-made promotions (Cronbach’s alpha = 889)

Concerning their promotional activities, firm x has

P1 displays that are easy to set up;

P2 promotional activities that fit the holidays (special days, events);

P3 promotional activities that suit the different seasons;

P4 promotional activities that suit actualities

P5 tailor-made promotions for us;

P6 in-store marketing activities supported by significant advertising campaigns

P7 effective in-store activities

3.3.2 Dependent variables

3.3.2.1 Trust

In this study trust is the dependent variable and plays as a middle role between keyaccount management programs sub-dimensions and commitment Trust is a dependentvariable to key account management programs sub-dimensions, but is also an

dependent variable to commitment In this study, trust was measured by 5 itemsdeveloped by Willem et al (2004):

Table 3.5: Tailor-made promotions Scale

Trust (Cronbach’s alpha = 867)

As a business partner, firm x

is honest;

is a reliable supplier;

treats the information provided by us with

integrity; has a good reputation; and

based upon earlier businesses, we can say that our company has much trust in firm x

Table 3.6: Commitment Scale

Commitment (Cronbach’s alpha = 922)

we are loyal to firm x;

we remain patient when firm x makes mistakes that have negative consequencesfor us;

we expect to keep most of the products from firm x in our

assortment; we expect to adopt new products from firm x;

our relationship with firm x is from our perspective a mutual long-term

commitment; and

we are dedicated to firm x

3.4 Questionnaire translation

The survey questions were translated into Vietnamese simultaneously by a committee

of 2 translators (the author and his sister, an English teacher in an internationallanguage school) This step was carried out to avoid the discrepancies in translationwhich is subjectively affected by the independent translator After counter-reviewingeach version of translation, a group discussion was made to reconcile the meaning ofthe survey questions for a consensus Finally, a draft of Vietnamese questionnaire wasdrawn for a pilot study

The questionnaire was distributed to the respondents on an online survey basis(www.docs.google.com) In the online survey method, the questionnaire was made

virtually as a web-page then the links were sent to the respondents via email or means

In the first step, an exploratory was conducted study to assess the measurementscales An in-depth discussion with 3 dealers (purchasing managers of key accounts inmobile phones sector) was made to clarify and make clear the meaning of surveyquestions and modify the measures This step is critical as measures of constructs wereappropriatel adj sted fo t is st d ’s co text

In the second step, an initial collection of 50 samples was made to test thereliability of the variables in order to refine the measures C o bac ’s alpha reliabilityand exploratory factor analysis (EFA) were employed to assess the scales C o bac ’salphas of all the variables were shown to be higher than 70 Following Nunnally(1978), an alpha of 70 or greater is desirable for each variable to have a level ofinternal consistency The results showed that C o bac ’s alphas of the scales were allhigher than 80 indicating all scales passed the reliability requirements

The results of the quantitative pilot study is shown in the Appendix IB

3.5 Main study

The study was conducted using electronic survey technique, from which questionnaireswere distributed via email as online survey links supported by Google(www.docs.google.com) to a list of respondents who work at selected deale s’ offices

As this study employed EFA to test the research model and hypotheses, it

should be at least 5/1 (observations/items) (Hair et al., 2006) Therefore, this study

aimed at observing around 200-210 samples of respondents

3.6.2 Selecting the samples

A list of 8 key accounts (dealers) were selected to engage in the study through the a t o

’s ca eer relationships, these dealers are big accounts of many high-tech suppliers,dealing in different types of products in the high-tech industry, which are mobilephones sector (i.e Nokia, Sams ,…), electronic appliances and information

technology sector These dealers have a selling chain system and account for a large

po tio of s pplie ’s sales ese deale s have branches and shops stretching along the

country and can be named as Thế Giới i Động, Vi n Thông A, Nguy n Kim, Viettel,Điện Máy Chợ Lớn, Thiê Ho , P ước Lập, FPT Retail.

Respondents were the ones who have a voice in buying decision They werepurchasing managers, owners and had been mostly working in Ho Chi Minh City, therest of respondents who were shop/floor managers had been working in other provinces

of Vietnam This study was conducted to test the hypotheses and research model fromperspective of dealers who have a voice in buying decision process

3.6.3 Collecting data

Based on the principles of choosing the scope and method of sampling, which arelower costs, more accurate results, fast data collection and available population(Donald & Pamela, 2003), a convenient and non-probability sampling was used This isthe most viable method due to limitations in time and costs However, with esea c e ’sexpe ie ces fo ea s i t e i d st , a list of ke acco ts was filte ed to choose the mostappropriate respondents to take part in the survey

The main survey was carried out from August 10, 2012 to September 12, 2012

by the author and some colleagues 250 links and copies of the questionnaire were sent

to the targeted respondents by email The author also asked the respondents torecommend the link to their colleagues at the same level After the questionnaire wassent, the author had reminded the respondents to answer until the targeted number ofresponses was met

After 32 days of conducting fieldwork, 208 responses were collected Thesedata would be gone through a cleaning process and then used for analysis

3.7 Statistical tools

3.7.1 Cleaning data process

Data would be cleaned before analyzing Data cleaning was made to prevent anypossible mistakes which are probably missing data or unreasonable answers (Nguyen,

2011, p.275) Among 44 multiple choice questions presented in the questionnaire, 38questions were quantitative and the rests were social-demographic qualitative Theanswers were reviewed to check if there was any illogical answer that conflicted withthe whole answers As all t e q estio s we e p t as “ eq i ed”, t e e would be no missinganswers in the responses

3.7.2 Reliability

To test the reliability of the measurement scales, C o bac ’s Alpha was used to definewhether the measurements meet the internal consistency Nunally (1978) suggestedthat a scale with Cronbac ’s Alpha is 70 or greater is accepted as internal consistency

3.7.3 Explanatory Factor Analysis

Since the C o bac ’s Alpha was employed to test the reliability of the measurements.Yet the measurement should be proved their validity Two important validities arediscriminant and convergent ones Thus, exploratory factor analysis (EFA) would help

to test those validities EFA is the interdependence technique, meaning that there is nodependent and independent variables, it bases on the interrelationships betweenvariables EFA is used to refine a group of observations into a more meaningful set F(F<k) Items which have loading factors less than 0.5 should be removed (Nguy n,2011) Items w ic ave loadi facto s’ diffe e ce less t a 30 ( iA  iB  3 ) should also bedeleted The eigenvalue was defined to be minimum level at 1

In case after running EFA the number of factors is larger than the number offactors predicted in the theoretical framework, the new factors will be tested again interms of reliability and the research model should be adjusted before testing theresearch model and hypotheses.

Chapter 4 DATA ANALYSIS AND RESULTS

4.1 Introduction

This chapter presents the demographic and statistical analysis of the samples, test ofthe reliability of the measurement scales, Exploratory Factor Analysis, Multiple LinearRegression analysis used to test the hypotheses Tools to be used in the analysis areMicrosoft Excel, SPSS 16.0 software Explanations, answers to the research questionsand other findings of the study will be presented

4.2 Data cleaning

208 copies of responses were received, a check of social demographic questions wasmade and logical checking was also conducted 6 of those appeared to be illogical afterreviewing a reverse-scored question (question 38 in the questionnaire) The remaining

of 202 qualified samples was used for analyzing No missing data was found in thedata table

4.3 Description of the qualified respondents

In 202 qualified samples, 145 samples (71.78%) were male, 57 samples (28.22%) werefemale e e’s o bi diffe e ce i t e t pes of p od ct t at t e espo de ts i volved in, the number

of respondents works in mobile phones sector, IT and electrical appliances is 78(38.61%), 70 (34.65%), and 54 (26.73%) respectively Most of the respondents dealwith distributors (139 samples, 68.81%), the rest worked directly with the brand ownercorporation (63 samples, 31.19%) In respect of education, and level of workingposition, the respondents were almost college and university graduates (146

respondents, 72.28%), just 4 owners took part in the survey, 59 purchasing manager

responded and the rest were shop/floor mangers (68.81%) Most of the respondents

work in the branches (127 samples, 62.9%), the remaining works at the head office

More details on descriptive statistics of variables are available at appendix II

Table 4.1: Characteristics of the samples

Types of products the respondents deal in

Education level of the respondents

4.4 Reliability Test of measurement

Following Nunally (1978), a C o bac ’s Alpha of 70 or greater is desirable for a scale

in terms of internal consistency Reliability test showed that all variables were greater

than 70, thus the measurement scales were reliable

In particular, responsiveness was measured by 6 items (from R1 to R6) had a C

o bac ’s Alpha of 949 Information was measured by 8 items (from I1 to I8) had a C obac ’s Alpha of 891 The C o bac ’s Alpha of Logistics which was measured by 5items (from L1 to L5) was 883 Tailor-made promotion programs were measured by 7items (from P1 to P7) was 889 Trust measured by 5 items (from T1 to T5) had a C obac ’s Alpha of 867 Finally, commitment was measured by 6 items (from C1 to C6)had a C o bac ’s Alpha of 922 Table 4.3 showed a summary of the measurementscales’ C o bac ’s Alphas More details on these scales could be found in the AppendixIII

Table 4.2: Summary of Cronbach’s Alpha of measurement scales

4.5 Exploratory Factor Analysis

After running the test of reliability of the variables, all the retained items then weretested by EFA This stage was carried out to filter and explore the components that canexplain the correlations among variables EFA was run to minimize the number ofvariables from a larger one and enable the new component to explain the mostcharacteristics of the original variables The components extracted could represent for a

discriminant facets of the studied constructs The extracted components then could beused for further analysis as independent variables.

In EFA, the two methods of extraction have commonly been used are principalcomponent analysis and principal factors analysis If the goal of analysis is to detectstructure, it is preferred to use principal factors analysis and if the goal of analysis is toreduce data, it is recommended to use principal components analysis Although, thetwo mentioned methods almost yield similar results (Statsoft, 2008)

In this study, the principal components analysis with Varimax rotation techniquewas used This method appeared to be better as MLR was intended to run at a laterstage, choosing that method could reduce the variables to support for the next step ofregression analysis

EFA results were shown in the table 4.4, from which 5 factors were extractedinstead of 4 factors as predicted in the literature review and research model The 5extracted factors have eigenvalues of greater than 1, and total variance explained of

7 39% All t e facto s’ loadi s we e eate t a KMO a d Ba lett’s est were.817 (p = 000), represented EFA was appropriate and all the measures could be usedfor further analysis However, one item (P4) was discovered to have a loadi facto ’sdifference less than 30 (.572 - 534), then it was deleted