Factors affecting the utilization centerin customer service by firms in vietnam market

Many Vietnamese firms are using the call center as a tool for their customer service channel; however, the benefits that Vietnamese customer orientation firms or broader the orientation

NGUYEN QUOC VIEN

FACTORS AFFECTING THE UTILIZATION OF CALL CENTERIN CUSTOMER SERVICE BY FIRMS

IN VIETNAM MARKET

MASTER OF BUSINESS (Honours)

Ho Chi Minh City - year 2014

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

INTERNATIONAL SCHOOL OF BUSINESS

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NGUYEN QUOC VIEN

FACTORS AFFECTING THE UTILIZATION OF CALL CENTERIN CUSTOMER SERVICE BY FIRMS

IN VIETNAM MARKET

ID: 22110079 MASTER OF BUSINESS (Honours) SUPERVISOR: Dr ĐINH THAI HOANG

Ho Chi Minh City - year 2014

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

INTERNATIONAL SCHOOL OF BUSINESS

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ACKNOWLEDGEMENT

During the process of writing my thesis, I had coped with difficulties and obstacle that

I could not anticipate The pressure of daily work seems to make me give up my study However, thanks to the encouraging of my supervisor, Dr Dinh Thai Hoang, I was received a great will to overcome step by step the difficulties

I own my deepest gratitude to my supervisor, Dr Dinh Thai Hoang, who with his wide research experience, guided me to complete this topic Without his continuous support, encouragement, and enthusiasm, this research would hardly have been completed

I am indebted to Dr Nguyen Dinh Tho for his immeasurable amount of teaching and guidance during the research design course I would like to thank Ms Thai Thi Thu Giang,

my friend at University of Economics Ho Chi Minh City, who introduced me the MBUS course at ISB and encouraged me to go to the end of the course

I also express my warmest gratitude to my professors at ISB, University of Economics

Ho Chi Minh City for their teaching and guidance during my MBUS course I wish to thank warmly my classmates who showed their teamwork spirit and willingness to help each other

to complete our theses

Finally, this thesis is dedicated to my beloved parent and daughter who understand, encourage, and sympathize with me especially in making the convenient environment during

my work of this dissertation

ABSTRACT

This thesis aims to investigate the factors that affect the utilization of call center in customer service by firms in Vietnam, especially in Ho Chi Minh City – a biggest and dynamic center business of Vietnam Many Vietnamese firms are using the call center as a tool for their customer service channel; however, the benefits that Vietnamese customer orientation firms or broader the orientation market firms gain from its customer focus or market focus through call center system either directly or indirectly remain unknown The study uses quantitative research method with the sample size of 230 enterprises including firms are utilizing the call center for their own, firms are using the call center outsourcing service and firms have hotline number to serve their customers The reliability, convergent and discriminant validity of scales was tested by Cronbach’s Alpha coefficient and exploratory factor analysis then regression analysis was done to find out the correlation between the concepts in the theoretical model This study finds that the key concepts in the technology acceptance model (TAM), perceived ease of use of the call center, cannot be used

to predict call center utilization by organizations Other concepts: perceived usefulness of call center, market orientation and service innovation are predictors of call center utilization Learning orientation facilitates market orientation, perceived usefulness and perceived ease

of use of the call center by Vietnamese firms The result of this research assist in identifying keys factors that lead Vietnamese firms to adopt using the call center as a tool to take care, retain their customers and develop market in globalization stage; moreover, this study shows that both large enterprises and SME also gain the benefits from using call center by choosing the right form of call center investment; owning a call center or using call center outsourcing

Keywords: Call center utilization, market orientation, learning orientation, contact

center in Vietnam

CONTENTS

ACKNOWLEDGEMENT .1

ABSTRACT 2

LIST OF TABLES AND FIGURES 5

CHAPTER 1: INTRODUCTION 6

1.1 Contact center introduction 6

1.2 Research background 7

1.3 Research problem 8

1.4 Research objective 9

1.5 Thesis structure 10

CHAPTER 2: LITERATURE REVIEW & HYPOTHESES 11

2.1 Technology Acceptance Model – TAM 11

2.2 TAM and contact center utilization 12

2.3 Market and learning orientations and intention to adopt call center system 15

2.4 Service innovation and call center utilization 18

CHAPTER 3: RESEARCH METHOD 21

3.1 Measurement 21

3.2 Quality study 23

3.3 The sample 24

3.4 Data collection, purifying and coding data 24

CHAPTER 4: DATA ANALYSIS AND RESULTS 26

4.1 Descriptive statistics 26

4.2 Reliability statistic 28

4.2.1 Market Orientation Cronbach’s Alpha 28

a Customer orientation 28

b Competitor orientation 29

4.2.2 Learning orientation Cronbach’s Alpha 31

a Commitment to learning 31

b Shared vision 32

c Open mindedness 33

4.2.3 Perceived usefulness of call center 33

4.2.4 Perceived easy to use call center 34

4.2.5 Service Innovation 35

4.3 Exploratory Factor Analysis (EFA) 36

4.3.1 EFA of Market orientation concept 36

4.3.2 EFA of Learning orientation 37

4.3.3 EFA of Perceived usefulness, Perceived ease of use and Service innovation 39 4.4 Correlations analysis 41

4.5 Regression Analysis 42

4.6 Discussion 50

CHAPTER 5: CONCLUSION 54

5.1 Management implication 55

5.2 Limitation and directions for future research 56

REFERENCE 58

APPENDIX 1: Research process 65

APPENDIX 2: Scale Items 66

APPENDIX 3: Scale Items refinement 69

APPENDIX 4: Factor analysis 72

APPENDIX 5: Regression analysis 75

APPENDIX 6: The result of qualitative survey 77

LIST OF TABLES AND FIGURES

Figure 1: Theory of reasoned action 11

Figure 2: Original technology acceptance model 12

Figure 3: A conceptual model of call center utilization 19

Figure 4: Model regression results 49

Table -5: Cronbach’s Alpha of three components in Market orientation concept 31

Table-10: Cronbach’s Alpha of three components in Learning orientation concept 33

Table-28: Correlations (see appendix 4) 74

Table-45: The summary of verifying hypothesis in conceptual model 49

CHAPTER 1: INTRODUCTION 1.1 Contact center introduction

Nowadays, people regularly receive calls or messages from the customer service center of telecommunication companies, banks, insurance organizations, hospitals, transportation companies, game online companies and consumer firms… or even calls for telesales and telemarketing The question is how they can make a lot of calls; send a hundreds

of messages at the same time to their customers, how they can remember all the customer numbers and detail of each transaction That is a call center; thus, what is the call center?

As defined by North American Quitline Consortium (NAQC), call center is a place where contacts are made and received It is often the “front door” to a business and is the place where most crucial customer interactions take place Therefore, its effective and efficient operation is a key ingredient to the overall success of any organization (NAQC, 2010) There are five main operational functions in any type of call center: workforce management, quality management, technology management, report and communications and financial management

Call centers provide a single contact for customers who may try to reach a company via multiple channels: e-mail, Web chat, fax, and phone, short message service (SMS) or

VoIP (voice over Internet protocol) Call centers, often called contact centers to reflect the

multiple points of access, provide staff with consistent information throughout an integrated

system; the term call center is used interchangeably with contact center These centers

capture data from across the enterprise and consolidate customer-related information into a central database This integration improves the customer's interaction and satisfaction and enhances the efficiency of the business operation (Duane Sharp, 2003)

Large organizations such as telecommunication companies, insurance and financial firms may choose to outsource its call center services, as a professional call center will be able to provide the systems and trained workforce to provide quality service to customers

1.2 Research background

Vietnam's economic growth rate has been among the highest in the Asia Pacific region in recent years 2010, 2011, 2012, 2013 respectively 6.4%, 6.2%, 5.2%, 5.2% Growth in services eased to 5.9%, this sector still made the largest contribution to GDP growth, at 2.5 percentage points (Dominic Mellor, Chu Hong Minh, and Nguyen Luu Thuc Phuong, 2014) With customer service becoming a key focus in Asia Pacific, Vietnam is improving customer relationships for the purpose of greater loyalty, brand recall, and profitability Adopting using the call center or call center service is one of the best ways to improve the customer satisfaction and customer relationship by firms in Vietnam, that’s because there’s a growth in call center in recent years

According to Dao Thi Minh Thao, a research associate in the ICT Practice at Frost & Sullivan APAC, this effort is leading to an impressive growth in Vietnam’s contact center industry that was estimated to be worth $4.2 million in 2011 and is expected to reach $11.4 million in 2018, with a growth rate of 15 percent Most contact center projects in Vietnam are deployed by banks, financial institutions, and telco service providers These sectors require a high level of customer care; large seat numbers are needed to always be available to serve customers She also commented that “for further growth and success, small and middle-sized enterprises (SME) should look forward to more efficient contact center application adoption

to align these trends for the future Emerging global vendors in providing suitable solutions also need to offer more customized solutions and effective marketing activities at more affordable price” (Donna Jeremiah, 2012)

Realizing the potential and advantages of call center, many researches on call center and its effectiveness were taken Most of them focus on the advantages such as customer satisfaction in using and outsourcing call center and service quality in call center operation

In researches indicating the advantages of call center, application of the technologies involved in call center operations can play a key role in accessing more customers, and in providing better quality services especially where additional or extended services become available (Walker and Craig-Lees, 1998) However, call center is a new form of technology

in Vietnam; it has just developed in recent years when firms think of customer There is almost no theoretical research for this type of service technology; thus this is an opportunity for this study

1.3 Research problem

In Vietnam, it’s easy to realize call center is used by most of banks, financial and insurance firms, telecommunication companies, hospitals, transportation companies, game online companies and consumer firms… What are the motivations that lead the firms choosing the call center as tool for customer service channel? The fact is that there is no previous studies mention the evolution of the call center, analyzing the technologies that have contributed to its growth, providing guidelines for the development and implementation of a call center as well as the management of the facility, and the role of human factors that can make a call center a successful operation Especially, there is no empirical research on what factors effecting the utilization of call center in customer service by firms in Vietnam Vietnamese firms just remark the benefits and advantages of using call center through the trend of customer care service what the other big companies did to retain their customers; however, these benefits must be deeply based on the orientation of each organization The question as regards how Vietnamese customer orientation service firm (large or small firm)

or broader how the Vietnamese orientation market firm (large or small firm) benefits from its

customer focus or market focus through call center system either directly or indirectly remain unknown This leads to finding the key factors effecting the call center utilization by firms in Vietnam

According to (Duane Sharp, 2003), call centers are an essential part of any business that deals frequently with customer queries Not only large organizations with huge customer get the benefits from using call center but SME can also get these benefits by choosing outsourcing call center services Building a call center internally may be feasible only for very large enterprises, smaller companies should consider outsourcing their call centers to organizations that specialize in providing these services and already have the latest technologies installed and operating, with trained staff These organizations can often provide excellent customer-oriented services, relieving smaller organizations of the financial, managerial, and human resources issues involved in an internal, corporate call center

1.4 Research objective

Realizing the potential for firms to use the call center as an effectiveness tool and convenient customer service channel to serve their customers better and quickly develop the market and almost no empirical research in call center utilization in Vietnam, this study aim

to fill the gap of lacking the empirical investigation in Vietnam’s call center utilization, reveal the factors that lead firms to adopt using the call center as a part of their business activities specifically in Ho Chi Minh city – a biggest and dynamic business center of Vietnam Since the research involved the new technology factors and IT system integration, the Technology Acceptance Model (TAM) (Davis, 1989) is used to predict information technology usage (Adams et al., 1992; Lucas and Spitler, 1999), this study uses an adapted version of TAM revised by Tho D Nguyen (2007) for internet usage by export firms in transitional markets to explain the extent to which firms in Vietnam market utilize the call

center as tools and customer service channels for their business activities, retain their customers and develop market

1.5 Thesis structure

This thesis is organized in five chapters: chapter 1 mentions the problem research, research objective, research scope and research’s reality meaning; chapter 2 is concerned with literature review and hypotheses; chapter 3 refer to research method; chapter 4 deal with data analysis, results and discussion; chapter 5 talk about conclusion, implications;

limitations and directions for future research

CHAPTER 2: LITERATURE REVIEW& HYPOTHESES

Contact center is a system integrated by telecommunication and information technology It comes out into society to serve the enterprises with large of customers and high density transactions Accepting to invest a new technology depends on many factors especially for business organizations It’s necessary to have a theory that explains why firms adopt to use a new technology system

This chapter firstly introduces Technology Acceptance Model – TAM and other literature review such as market orientation, learning orientation and service innovation then later summarizes several studies related to contact center utilization and propose hypotheses forming the model The end of this chapter is the initial research model for this study

2.1 Technology Acceptance Model - TAM

The technology acceptance model (TAM) was first created by Davis (1989), based on the theory of reasoned action (TRA) (Fishbein & Ajzen, 1975) in psychology research The TRA posits that individual behavior is driven by behavioral intention where behavioral intention is a function of an individual’s attitude toward the behavior and subjective norms surrounding the performance of the behavior In other words, it states that one’s behavior and the intent to behave is a function of one’s attitude toward the behavior and their perceptions about the behavior Therefore, behavior is the function of both attitudes and beliefs TRA is presented in Figure 1 below

Figure 1.Theory of reasoned action

Attitude Toward Act

or Behavior

Subjective Norm

Behavior Behavioral

IntentionNormative Beliefs and

Motivation to Comply

Beliefs and

Evaluation

Meanwhile, TAM proposes that perceived ease of use and perceived usefulness of technology are predictors of user attitude towards using the technology, subsequent behavioral intentions and actual usage Perceived ease of use was also considered to influence perceived usefulness of technology Figure 2 presents original version of TAM (Davis, 1989)

2.2 TAM and contact center utilization

TAM has been applied in numerous studies testing user acceptance of information technology, for example, word processors (Davis et al., 1989), spreadsheet applications (Mathieson, 1991), e-mail (Szajna, 1996), web browser (Morris & Dillon, 1997), telemedicine (Hu et al., 1999), websites (Koufaris, 2002), e-collaboration (Dasgupta, Granger

& Mcgarry, 2002), and blackboard (Landry, Griffeth & Hartman, 2006) In this study, contact center was considered a system that makes use of telecommunication and information technology in accomplishing its mission of providing historical customer’s information and interacting customers through telephone and computer interface

Several other studies have also provided evidence in support of TAM (Igbaria et al., 1995) Moreover, the two main constructs in TAM, perceived usefulness and perceived ease

of use, which have been hypothesized to be fundamental determinants of user acceptance of

IT, can be widely applied (Adams et al., 1992) Perceived usefulness is defined as “the degree

to which a person believes that using a particular system would enhance his or her job performance” and perceived ease of use as “the degree to which a person believes that using a

Perceived Usefulness

Perceived Ease of Use

Attitude Toward Using

External

Variables

Actual System Use

Behavioral Intention to Use

Figure 2.Original technology acceptance model

particular system would be free of effort” (Davis, 1989, p 320) Perceived usefulness and perceived ease of use are key antecedents of the intention to use IT applications Also, several researchers have used perceived usefulness and perceived ease of use, to predict IT usage (Adams et al., 1992; Lucas and Spitler, 1999) It can therefore be concluded that perceived usefulness and perceived ease of use can be used to predict not only the intention to use but also the usage of IT applications (Tho D Nguyen, 2007)

TAM explains IT usage in terms of individual attitudes and intentions, but does not address organizational attitudes and actions directed at desired organizational goals (Tho D Nguyen, 2007).The present research adopts the concepts of perceived usefulness and perceived ease of use applied in the organizational context by Nguyen and Barrett (2006) Specifically, the study explores how firms utilize the call center as a channel of communication to customers Therefore, perceived usefulness of the call center in this context refers to the degree to which a firm believes that utilizing the call center would help

to obtain relevant methods and tools for customer care services Perceived ease of use of the call center in the organizational context is the degree to which the firm believes that utilizing the call center to retain and develop customer relationships by integrating telecommunication and IT system and CRM (customer relationship management) software would be free of effort (Davis, 1989)

Application of the technologies involved in call center operations can play a key role

in accessing more customers, and in providing better quality services especially where additional or extended services become available (Walker and Craig-Lees, 1998) When high-contact (that is, in-person contact) services can be converted into low-contact services, through the use of technology, a number of benefits can result First, and most obviously, customers can avoid attending the “service factory” (Lovelock, 1997) This leads to less cost and greater convenience for the customer Second, the time taken for each transaction should

be lessened due to less need for travel to office-based services; and, once connected to the call center, services should be provided relatively quickly due to the ability of the newer technologies to stream inquiries to unoccupied staff in different call centers, perhaps even in different parts of the country Third, services can be more readily provided in the language of the customer's choice, due to the ability to direct customer calls to specific locations Fourth,

it has been noted that some customers actually rate service quality of call center contact higher than they rate in-person contact (Driver and Johnston, 1998).For service organizations, these new technologies should facilitate greater effectiveness and efficiency (Prabhaker et al., 1997) More customers can be serviced at any one point in time, and, with customers taking

at least part of the responsibility for the streaming of calls (by selecting a preference from a predetermined menu using the telephone keypad), fewer staff are necessary Fewer service centers with less space for customers should be needed leading to a concomitant reduction in management staff and further cost reduction (Alternatively, more, but smaller, in-person service centers with less staff might also be provided.) Accordingly, the firm could perceive the usefulness of the call center, and therefore be likely to utilize it In addition, the firm may believe that it is too difficult to use the call center, even if it believes it will be useful As a result, it can be argued that perceived ease of use is also a potential predictor of call center utilization Moreover, it can be expected that the degree to which the firm perceives that using these call center tools for its purpose is free of effort would, in turn, influence its perception of their usefulness and utilization Consequently:

H1 There is a positive relationship between the perceived usefulness of the call center and call center utilization

H2 There is a positive relationship between the perceived ease of use of the call center and call center utilization

H3 There is a positive relationship between perceived ease of use and perceived usefulness of the call center

Figure 3 depicts the research model employed in the study It is a reduced TAM model, excluding behavioral intention to use and actual system use The external variables constructs are also included in the research model as there are immediate intention to examine antecedents to perceived usefulness and perceived ease of use

2.3 Market and learning orientations and intention to adopt call center system

(Jaworski and Kohli, 1993; Kohli and Jaworski, 1990) define a market orientation as a firm’s organization-wide generation of market intelligence, dissemination of the intelligence across departments, and organization-wide responsiveness to the market intelligence Jaworski and Kohli (1993) and Kohli and Jaworski (1990) state that superior customer value can best be achieved by structuring organizational activities based on customer-focused information generated by and disseminated throughout the organization

As previously mentioned, current models of IT usage explain usage in terms of an individual’s attitudes and intentions, but do not address, in an organizational setting, how an organization’s attitudes and actions lead towards desired organizational goals Though TAM, Theory of Reasoned Action (TRA) (Fishbein and Ajzen, 1975), and Theory of Planned Behavior (TPB) (Ajzen, 1991) provide reasonable predictions of IT usage in personal use settings, their usefulness in explaining implementation within organizational settings has been questioned because of their inability to incorporate the role of organizational characteristics which influence the adoption of an innovation A review of IT implementation research indicates that organizational users’ utilization of IT depends not only on their beliefs, attitudes, and intentions, but also on organization’s strategies, policies and actions (e.g Leonard-Barton and Deschamps, 1988).Consequently, this study explores the effects of

two organizational factors, that is, market orientation and learning orientation on the intention

to adopt the Call center

Market and learning orientations have positive and synergistic effects on organizational behavior (Slater and Narver, 1995) Slater and Narver (1995: 63) argue that ‘‘a market orientation is valuable because it focuses the organization on continuously collecting information about target-customers’ needs and competitors’ capabilities and using this information to create continuously superior customer value’’ Narver and Slater (1990) conceptualize three behavioral components, that is, customer orientation, competitor orientation, and interfunctional coordination Each of these components plays its role in intelligence generation, dissemination, and responsiveness to the collected information This implies that a market-oriented firm is likely to gather more information on markets and environments Market orientation facilitates an organization’s innovativeness (Han et al., 1998; Jaworski and Kohli, 1993).This means that market-oriented firms are more likely to search for innovations including the call center Consequently, market-oriented firms are more likely to recognize the call center as a useful tool to server customer, cross-sell and collect information about markets and competition and are more likely to adopt the call center Accordingly, the following hypotheses, illustrated in Figure 1, are proposed:

H4 Firms with higher levels of market orientation are more likely to have higher levels of perceived usefulness of the call center

H5 Firms with higher levels of market orientation are more likely to have higher levels of intention to adopt the call center

Learning orientation is another organizational factor that influences the propensity of

a firm to create and use knowledge (Sinkula et al., 1997) Learning orientation comprises three components, that is, commitment to learning, open-mindedness, and shared vision Commitment to learning reflects the fundamental value that an organization holds towards

learning which influences whether an organization is likely to promote a learning culture Organizations that are committed to learning value the need to understand the cause and effects of their actions Open-mindedness is linked to the notion of unlearning which refers to the process through which organizations eliminate knowledge Open-mindedness advocates firms reassess their long-held routines, assumptions, and beliefs It is ‘‘an organizational value that may be necessary for unlearning efforts to transpire’’ Shared vision ‘‘provides a focus for learning that fosters energy, commitment, and purpose among organizational members’’ (Sinkula et al., 1997: 309) A learning-oriented firm creates and encourages a learning environment throughout the firm This gives rise to the ability to adopt and implement new ideas, processes or products, that is, to produce innovative capacity for the firm (Hurley and Hult, 1998) Therefore, in learning-oriented firms, members have more opportunities to learn and share knowledge with others including knowledge about and from the call center (KMS – Knowledge Management System) This facilitates the transformation

of knowledge from individual levels to organizational levels (Nonaka and Takeuchi, 1995) Consequently, learning oriented firms are more likely recognize the usefulness of the call center and find it easy to use call center tools for collecting historical customer information Therefore, the following hypotheses, illustrated in Figure 1, are proposed:

H6 Firms with higher levels of learning orientation are more likely to have higher levels of perceived usefulness of the call center

H7 Firms with higher levels of learning orientation are more likely to have higher levels of perceived ease of use of the call center

Learning orientation can help foster market-oriented thoughts and behavior in an organization A key component of learning orientation is an organization’s ability to engage

in adaptive as well as generative learning, in which existing values are questioned, implies how organizations acquire, process and subsequently use market intelligence, that is, their

market orientation (e.g Slater and Narver, 1995) A superior learning environment will leverage the use of all resources, including the behaviors that accompany a market orientation (Baker and Sinkula, 1999) Moreover, firms with a strong learning orientation in markets (where their business values are embedded within a centrally-planned system) are likely to withdraw from their routine ways of doing business which have become embedded in their previous business approach, and are tending to adopt a new way of looking at the market, involving a market oriented approach Accordingly, the following hypothesis, illustrated in Figure 1, is proposed

H8 Firms with higher levels of learning orientation are more likely to have higher levels of market orientation

2.4 Service innovation and call center utilization

Innovation is defined as “adoption of an internally generated or purchased device, system, policy, program, process, product, or service that is new to the adopting organization” (Damanpour, 1991: 556) Service innovation is defined as an ability of firm to generate, adopt or implement new ideas, products, services, techniques, and processes successfully in order to improve existing process and service, as well as creating customer value and increasing marketing profitability (Alegre and Chiva, 2008; Damanpour, 1991; Hult, Hurley and Knight, 2004; Nasution et al., 2011; Slater and Narver, 1995; Tajeddini, 2010) Phokha and Ussahawanitchakit (2010: 7) defined excellence service innovation as “the activities that firms respond to service which distinguishes from competitor by emphasizing the voluntariness to support originality and test new services/product, novelty, technology leadership and R&D in improving new process and willing to responding in order to pay extremely attention to service through rapidly service, and always to be pleased for the on time service” Walker and Ruekert (1987) argue that service innovation can create customer value through high quality of product that generated by good service at the premium prices

Firms with strong innovation capability will have an ability to create and deliver superior customer value which firms can develop and launch new products and services that bring greater customer value, completely and timely understand customer needs and preferences, increase competitive choices, improve service quality, focus on customer needs, and develop powerful customer relationships (Wang et al., 2006) Moreover, service innovation can increase growth in sales revenue, generate new customers, greater market share, more profitability, better returns on investment, and able to reach financial goals (Merrilees, Rundle-Thiele and Lye, 2011) Previous research indicates that service innovation has a positive effect on customer value creation, customer satisfaction, marketing performance, financial performance, and corporate competitive advantage (Chen, Lin and Chang, 2009; Halpern, 2010; Harmancioglu, Grinstein and Goldman, 2010; Jimenez-Jimenez and Sanz-Valle, 2011; Rhee, Park and Lee, 2010; Sadikoglu and Zehir, 2010; Tajeddini, 2010; Wang et al., 2006) This study expects that service innovation will make firms freely to invest IT system such as call center system to satisfy firm’s targets and customer’s needs Therefore, the research relationships are hypothesized as shown below.

H9 Service innovation has a positive influence on call center utilization

H 9

H1

H2 H3

Service innovation Figure 3.A conceptual model of call center utilization

Figure 3 shows a conceptual model that explains the utilization of the call center by Vietnamese firms Together with perceived usefulness and perceived ease of use, market orientation is proposed to be a predictor of call center utilization In addition, learning orientation is expected to have an impact on perceived usefulness, perceived ease of use of the call center and underlie market orientation Finally, service innovation is expected a new factor added into the model studied by Tho (2007) about investigating the factors that affect the intention to adopt the internet by export firms in transitional markets to satisfy contact center utilization

Base on original TAM model and other literatures review, external variables of TAM were replaced by market orientation and learning orientation; attitude toward using, behavioral intention to use and actual system use were reduced an replaced by contact center utilization together with service innovation firmed the conceptual research model in this study In order to examine and measure the relationship between these hypotheses, the next chapter will propose the method of researching to choose the samples, collect the data for measurement

CHAPTER 3: RESEARCH METHOD

Two phases of study were undertaken in this research: a qualitative study and a quantitative study or main survey The qualitative study phase involved a focus group Its purpose was to modify and refine the measures scale The main survey was used to test the measurement and structural models: see Appendix 1 for the research process

3.1 Measurement

Learning orientation (denoted by LEAR_ORI) was measured utilizing the scale developed by Sinkula et al (1997) LEAR_ORI was a second-order construct consisting of three dimensions, i.e commitment to learning, open-mindedness, and shared vision Commitment to learning (denoted by LCOM), was measured by four items addressing the degree that the firm is willing to commit to learning, i.e to promote and nourish a learning culture within the firm Shared vision (LSVI) was measured by four items embodying the focus for learning that fosters energy, commitment, and purpose among every member of the firm Finally, open mindedness (LOPM) was also measured by three items mirroring the unlearning process of the firm Market orientation (MARKET_ORI) was measured based on Narver and Slater’s (1990) scale MARKET_ORI was also a second order construct comprising three components, i.e customer orientation, competitor orientation, and interfunctional coordination Customer orientation (MCUS) was measured by eight items, addressing the firm’s level of commitment to customers Competitor orientation (MCOM) was measured by four items, asking respondents the degree of understanding of and reaction

to competition Interfunctional coordination (MCOI) was measured by five items assessing the level of coordination among functions in the firm

Perceived usefulness (USEFULNESS) and perceived ease to use (EASYTOUSE) of the call center were measured based on the Nguyen and Barrett (2006) scales, a modified version of the Davis (1989) scales PEUS was measured by six items reflecting the level the

firm believes in the usefulness of the call center for obtaining customer relationship and market information PEEU was measured by four items mirroring the degree to which the firm believes that using the call center to obtain relevant information from market through their existing customer database is of ease The measurement for Call Center Utilization (UTILIZATION) should be adapted from Nguyen (2007) The first was a measure of time using telephone and CRM for contacting customers and solving customer problems – that is, for how many hours per day the firm uses the call center to serve their customers, telemarketing for cross-selling and update customers’ information, such as using telephone in call center system, use knowledge management system, searching customer database The second item was about the frequency of using media in call center system such as e-mails, phone, chat, fax… for business purposes This was measured simply by asking respondents how many times per day the firm receives, makes call and sends, receives e-mails related to customers and business activities or retrieve from the electrical reports from their existing call center These two indicators were expected to be closely related This is because, when a firm needs customer’s information, it tries to find it by searching the existing database based

on the phone number with expected to find the right information of customer in order to serve them well Therefore, reflective indicators were used Finally, Service innovation (SERVICE_INNO) is measured by service activities from which firm generates, adopts or implements new ideas, products, services, and processes to respond to customer needs and create customer value It includes five items developed by Scott J Grawe, Haozhe Chen and Patricia J Daugherty (2009) These measures were included in the statements or questionnaire used to interview firms The original statement or questionnaire was in English This English version was translated into Vietnamese because English is not well understood

by managers in this market Back-translation was used to ensure the equivalence of meanings (see Appendix 2 for the scale items) Except for the two items measuring Call Center

Utilization (before qualitative study step this concept has two items), which were measured

by ratio scale expressing the hours using the call center system for business activities, all other items were measured by a five-point Likert scale from 1 = strongly disagree to 5 = strongly agree

3.2 Qualitative study

A focus group was undertaken with ten managers who had responsibility for Call center operation or sales and marketing director in Telecommunication companies, banking, state-owned companies, private companies and multinational organizations in Vietnam and had used the Call Center or hiring the outsourcing call center service for their business activities Although most of the scales have been used widely in the past, this step is important because of the difference in the research area: Using Call Center in customer services A qualitative survey followed to refine the measures It was conducted by making calls to the selected managers group for introduction and invited them to participate in the survey with the list of items in both languages English and Vietnamese enclosed a letter of encouraging them to give their ideas if there is any item should be deleted or added to adapt the reality of call center area sent by email in advanced, then face-to-face interview with them for discussing the necessary for each measurement scale The results indicated that the items should be reduced because some items are not suitable with call center field and the meaning

of several statements is coincided 80% managers of this group agreed to delete three scale items in Market Orientation variable, 70% agreed to delete other three scale items in Learning Orientation variable and totally agreed to refine the items in Call center utilization

by combining the meaning of two items to one item which is enough to clarify this concept (see appendix 6 for the result of qualitative survey).The refined 36 main scale items were used for the main survey to test the models (see Appendix 3 for the list of scale items refined)

at any size or which have the contact center leasing were selected to survey and considered as samples observed Base on the study of Hair, Anderson, Tatham and Black (1998) about Exploratory Factor Analysis (EFA) the sample size is at least 5 times of total observation variable; therefore, in this study the sample size prepared of total main observation variable is

36 and sample size is 36 * 5 =180 A study of Roger (2006) indicated that the minimum sample in practical study is from 150 to 200 samples Relying on the above information, the sample size should be about 200 for this study

3.4 Data collection, purifying and coding data

In order to obtain the sample size of about 200, the 230 questionnaires were sent to the list included 230 firms who had utilized the hotline number, or hiring the call center for their services, or small call center with several agents or large call center for their services and business activities Respondents were senior executives, sales and marketing staffs and technical staffs of the firms The face-to-face interviews were utilized in this research in some cases

About10 per cent of the firms surveyed were stated-owned such as Telecommunication, Power and Banking organizations The limited proprietary was 15 per cent The majority, about 65 percent was joint stock companies such as Telecommunication,

Banking, Services, Financial and Consumer producers The rest 10 per cent was international organization such as Banking, Services, Financial services and Consumer producers

The data collected by directly interview, Google Docs application form and email were input manually in excel file in order to eliminate the missing value as well as identify outliers by intuitive observation The result indicated that there were 26 questionnaires deleted After elimination of outliers and missing values, the data set has 204 observations left, and they were used for the main survey by using the SPSS 20.0 software in the chapter 4

CHAPTER 4: DATA ANALYSIS AND RESULTS

The set of data collected in chapter 3 was input into the application SPSS 20.0 for detail analysis followed the steps below:

The sample collected was distributed depend on gender, age, position, degree and income These factors were descriptive by SPSS software 20.0 The gender of sample included 103 male samples corresponding to 50.5% and 101 female samples corresponding to 49.5% (see the table SEX below)

SEX

Frequency Percent Valid

Percent

Cumulative Percent Valid

Total 204 100.0 100.0

For the age of samples, the table of AGE indicated that there were 50 samples under

25 years old corresponding to 24.5%, 50 samples in the range of 25 to 30 years old corresponding to 24.5%; 58 samples in the range of 31 to 40 years old corresponding to 28.4% and 46 samples over 40 years old corresponding to 22.5%

For the degree of samples, the table of DEGREE indicated that there were 57 samples

at college level corresponding to 27.9%, 67 samples had university degree corresponding to 32.8% and 80 samples had master degree corresponding to 39.2%

The position of samples comprised 72 samples of sales and marketing staffs corresponding to 35.3%, 64 samples of technical staffs corresponding to 31.4% and 68 samples of senior staffs corresponding to 33.3% (see the table of POSITION)

POSITION

Frequency Percent Valid

Percent

Cumulative Percent

The next step of purifying the measures the Cronbach’s Alpha and Exploratory Factor Analysis (EFA) were employed

4.2 Reliability statistic

4.2.1 Market Orientation Cronbach’s Alpha

As mentioned in chapter three, Market orientation was a second order construct comprising three components, i.e customer orientation, competitor orientation, and interfunctional coordination After qualitative study step, customer orientation has six items, competitor orientation has three items and interfunctional coordination has three items Because the Market orientation comprises three different components, the Cronbach’s Alpha must be measured for each component in order to find out its reliability

a Customer orientation

The Cronbach’s Alpha of Customer orientation run by SPSS 20.0 was 0.899 and the detail was shown in table-1 below:

Table-1: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

Scale Variance

if Item Deleted

Corrected Total Correlation

a The value is negative due to a negative average covariance among items

This violates reliability model assumptions You may want to check item codings

According to Nunally & Burnstein (1994), the MARKET_ORI7 was deleted because

of its Corrected Item-Total Correlation was 0.057 very lower than 0.3 and has no descriptive contribution to the concept need to be measured Moreover, the Cronbach's Alpha if this item

deleted was 0.599 higher than the Cronbach's Alpha of 3 items mentioned above Therefore, the poor MARKET_ORI7 item must be deleted in order to have a higher Cronbach’s Alpha, this was proved in second running SPSS shown in table-3.The Cronbach’s Alpha of Competitor orientation now is 0.599, Corrected Item-Total Correlation coefficients of items observed in scale were over 0.4 and there was no case of deleting any variable to make Cronbach’s Alpha of this scale greater than 0.599 Thus, this result was all acceptable for the

next Exploratory Factor Analysis study

Table-3: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

Item-Cronbach's Alpha

if Item Deleted

a The value is negative due to a negative average covariance among items

This violates reliability model assumptions You may want to check item codings

c Interfunctional coordination

The Cronbach’s Alpha of interfunctional coordination component was also measured

in the same way and the outcome was 0.866, total correlation items were higher than 0.3 That is three items in interfunctional coordination correlate each other and contribute to the measurement of interfunctional coordination concept (see table-4)

Table-4: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

Table-5 Scale Cronbach’s Alpha Customer orientation 0.899 Competitor orientation 0.599 Interfunctional coordination 0.866

4.2.2 Learning orientation Cronbach’s Alpha

As mentioned in chapter three, similarity to Market orientation, Learning orientation was also a second order construct comprising three components, i.e commitment to learning, shared vision, and open-mindedness After qualitative study step, commitment to learning has three items left, shared vision has three items and open mindedness has two items Because the Learning orientation comprises three different components, the Cronbach’s Alpha must

be measured for each component in order to find out its reliability

Scale Variance

if Item Deleted

Corrected Total Correlation

Item-Cronbach's Alpha if Item Deleted

a The value is negative due to a negative average covariance among items

This violates reliability model assumptions You may want to check item codings

According to Nunally & Burnstein (1994), the LEARN_ORI3 was deleted because of its Corrected Item-Total Correlation was 0.111 very lower than 0.3 and has no descriptive contribution to the concept need to be measured Moreover, the Cronbach's Alpha if this item deleted was 0.631 higher than the Cronbach's Alpha of 3 items mentioned above Therefore,

the poor LEARN_ORI3 item must be deleted in order to have a higher Cronbach’s Alpha, this was proved in second running SPSS shown in table-7 The Cronbach’s Alpha of Commitment to learning now is 0.631, Corrected Item-Total Correlation coefficients of items observed in scale were over 0.4 and there was no case of deleting any variable to make Cronbach’s Alpha of this scale greater than 0.631 Thus, this result was all acceptable for the

next Exploratory Factor Analysis study

Table-7: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

Item-Cronbach's Alpha

if Item Deleted

a The value is negative due to a negative average covariance among items

This violates reliability model assumptions You may want to check item codings

b Shared vision

The Cronbach’s Alpha of shared vision component was also measured in the same way and the outcome was 0.866, total correlation items were higher than 0.3 That is three items in shared vision correlate each other and contribute to the measurement of shared vision concept (see table-8)

Table-8: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

c Open mindedness

The Cronbach’s Alpha of open mindedness component was also measured by SPSS 20.0 and the outcome was 0.751, total correlation items were higher than 0.3 That is two items in open mindedness correlate each other and contribute to the measurement of shared vision concept (see table-9)

Table-9: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

Item-Cronbach's Alpha

if Item Deleted

a The value is negative due to a negative average covariance among items

This violates reliability model assumptions You may want to check item codings

The Cronbach’s Alpha of three components in Learning orientation concept and Learning variable was summarized in Table-10

Table-10 Scale Cronbach’s Alpha Commitment to learning 0.631

4.2.3 Perceived usefulness of call center

The Cronbach’s Alpha of Perceived usefulness of call center component for the first running SPSS 20.0 was 0.785 and the detail of each item was shown in the table-11 below:

Table-11: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

According to Nunally & Burnstein (1994), the USEFULNESS2 was deleted because

of its Corrected Item-Total Correlation was 0.140 smaller than 0.3 and has no descriptive contribution to the concept need to be measured Moreover, the Cronbach's Alpha if this item deleted was 0.898 higher than the Cronbach's Alpha of 6 items mentioned above

The Cronbach’s Alpha of Perceived usefulness of call center component for the second running SPSS 20.0 was 0.898 higher than the first run 0.785, more reliability and all Corrected Item-Total Correlation was higher than 0.4 The detail of each item was shown in the table-12 below

Table-12: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

4.2.4 Perceived easy to use call center

The Cronbach’s Alpha of Perceived easy to use call center component run by SPSS 20.0 was 0.846 greater than 0.7 and there is no item having the Corrected Item-Total Correlation smaller than 0.4 This Cronbach’s Alpha coefficient was a good measure Nunally

& Burnstein (1994) and the detail of each item was shown in the table-13 below:

Table-13: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

Scale Variance if Item Deleted

Corrected Item-Total Correlation

The Cronbach’s Alpha of Service Innovation component for the second running SPSS 20.0 was 0.790 higher than the first run 0.638, more reliability and all Corrected Item-Total Correlation was higher than 0.4 The detail of each item was shown in the table-15 below

Table-15: Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

4.3 Exploratory Factor Analysis (EFA)

After assessing the reliability of the scale, EFA was employed That the method is chosen to analyze the factors is the Principal Component method with varimax rotation In order to test the convergence of items in measuring a variable and discriminant of variables in the research model, EFA was conducts for all variables including all independent and dependent variables

Before testing the EFA of all variables, the EFA of Market orientation and Learning orientation must be performed in order to test the convergence of Customer orientation, Competitor orientation and Interfunctional coordination in measuring Market orientation variable and Commitment to learning, Shared vision and open mindedness in measuring Learning orientation variable

4.3.1 EFA of Market orientation concept

KMO and Bartlett's test’s results in the factor analysis indicated that the coefficient of KMO is high (equal to 0.828> 0.5) indicating sufficient items for each factor The significance level (Sig.) of 0.000 (<0.05) indicates that the correlation matrix is significantly different from an identity matrix, in which correlations between variables are all zero All of these indicate that EFA is appropriate Table-16 below is a summary of KMO and Bartlett's test’s results

Table-16: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

were71.625% (greater than 50%) as presented in Table-17 (see Appendix 4) This means that there are three factors explain 71.625% the variation of data The result was accepted in this study and used for further study

Rotated component matrix in table-18 indicated that the scale items in market orientation cluster into three groups distinctively defined by high loadings That is all scale items in each concept were converged and appropriate to measure that concept

Table-18: Rotated Component Matrix a

Extraction Method: Principal Component Analysis

Rotation Method: Varimax with Kaiser Normalization

a Rotation converged in 4 iterations

4.3.2 EFA of Learning orientation

KMO and Bartlett's test’s results in the factor analysis indicated that the coefficient of KMO is high (equal to 0.655> 0.5) indicating sufficient items for each factor The significance level (Sig.) of 0.000 (<0.05) indicates that the correlation matrix is significantly different from an identity matrix, in which correlations between variables are all zero All of these indicate that EFA is appropriate Table-19 below is a summary of KMO and Bartlett's test’s results

Table-19: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .655

Rotated component matrix in table-21indicated that the scale items in learning orientation cluster into three groups distinctively defined by high loadings That is all scale items in each concept were converged and appropriate to measure that concept

Table-21: Rotated Component Matrix a

Extraction Method: Principal Component Analysis

Rotation Method: Varimax with Kaiser Normalization

a Rotation converged in 4 iterations