Perceived service quality discrepancies between telecommunication service provider and customer

    Perceived service quality discrepancies between telecommunication service provider and customer Lin-Kung Chen, Wei-Ning Yang PII: DOI: Reference:

S0920-5489(15)00028-8 doi: 10.1016/j.csi.2015.02.012 CSI 3016

To appear in:

Computer Standards & Interfaces

Received date: Accepted date:

3 October 2013 20 February 2015

Please cite this article as: Lin-Kung Chen, Wei-Ning Yang, Perceived service quality discrepancies between telecommunication service provider and customer, Computer Standards & Interfaces (2015), doi: 10.1016/j.csi.2015.02.012

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ACCEPTED MANUSCRIPT Perceived service quality discrepancies between telecommunication service provider and customer

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Lin-Kung Chen1 and Wei-Ning Yang2 Department of Information Management National Taiwan University of Science and Technology 1 [email protected] and [email protected]

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Abstract

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The efficiency of telecommunication services (TS) has increased their popularity. However, objectively evaluating the quality and the potential of TS is difficult for the TS provider because its milieu differs from that of the customer. This obstructs the progression of TS development and usage. No studies have established a satisfactory model for estimating the discrepancy. This study therefore provides a model for measuring the presence, magnitude, and form of the perception discrepancy regarding TS by applying analytical hierarchy process (AHP) and multivariate analysis

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of variance (MANOVA). This model further explores the conditions under which the perception discrepancy regarding TS occurs and predicts the direction of change. The analytical results reveal that TS providers and customers significantly differ in their preferences for TS, and they also demonstrate that the difference in milieu of the TS providers and customers significantly correlates with the variation in preference. Therefore, this model can help the TS provider and customer gauge the pros and cons of investment in TS and shape corresponding strategy by linking the developed model, short/long-term TS strategies, and business activities related to TS.

Keywords: Telecommunication Service; Perception Discrepancy; Service Quality; IT Construct; Organization Characteristics.

1. Introduction The deployment of fiber to the x (FTTX) and technological advancements in third generation (3G) and upcoming fourth generation (4G) mobile telecommunications have given birth to many new broadband, multimedia, and cloud computing services in the telecommunication service industry (TSI) 1 [1]. Because of the convenience of telecommunication services (TS), many companies in Taiwan are increasing their use of these services for business management and are demanding highly customized services that suit their business workflow [2-3]. Owing to the increasing popularity and the high efficiency of TS, the competitiveness of companies has

1 The definition of TSI includes network operators and service providers but not hardware suppliers and media industry.

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ACCEPTED MANUSCRIPT strengthened and improved.

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Intuitively, after the telecommunication privatization policy was implemented by the Ministry of Transportation & Communications (MOTC) of Taiwan in 1996, the deregulated telecommunications B2B market quickly responded to customer requirements and expectations in order to maximize customer satisfaction. However, the development and usage of TS did not substantially progress [4] because TS providers had difficulty in objectively evaluating the quality and the potential of the designed TS based only on TS customer satisfaction. The reasons are twofold. First, from the TS provider perspective, the TS provider encounters a management dilemma when the Taiwan government attempts to maintain market competition according to the national policy for public resource management. For example, since the service fee of nation-wide

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TS is still regulated and limited by the Taiwan National Communication Committee, it does not reflect the actual market price2. Therefore, unlike conventional services, the development of TS is affected not only by customer satisfaction, but also by government policy. Secondly, from the TS customer perspective, a TS is considered effective if the gap between customer expectations and actual services received is small, and the perception regarding the TS is determined by the IT and organization milieu of the customer [6]. Therefore, customer satisfaction toward the TS quality is a compound effect that varies according to the customer IT construct (e.g., IT infrastructure and training) and organization characteristics (e.g., centralization and formalization). Therefore, the

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different milieus of the TS provider and customer result in different perceptions toward TS. Notably, this phenomenon has been observed not only in Taiwan but also in South Korea and Japan [7-8]. Therefore, according to the above discussion, the quality estimation/evaluation and short/long-term development scheme of the TS should depend not only on customer satisfaction, but also on the gap in perceptions of TS quality between the provider and customer. Hereafter, this perception discrepancy toward TS quality between provider and customer is referred to as PDSQ. Despite the robust theoretical literature, no studies have provided empirical evidence of the presence and magnitude of PDSQ. Some works have analyzed the impact of PDSQ on customer satisfaction without comparing its presence, magnitude, and form between the TS provider and customer [9-12]. Therefore, this study contributes to the literature on electronic commerce measurement and information systems by providing a model to analyze the presence and magnitude of PDSQ, and in what form PDSQ exists using data commonly available in TS industry. The impacts of the IT construct gap (ITG) and organization characteristic difference (OCD) between TS provider and customer on PDSQ are also analyzed to identify the conditions under which PDSQ occurs and to predict the direction of change. The proposed model applies analytical hierarchy process (AHP) to compare the preferences of TS providers and customers regarding TS quality. Multivariate analysis of variance (MANOVA) is used to compare providers and customers in terms of perceived TS quality. The Spearman correlation coefficient is also calculated to determine the relationship between “ITG/OCD” and “the perception variation toward TS quality”. The potential applications of the developed approach include (1) measuring PDSQ, (2) calculating ITG and OCD, 2 The overall revenues for mobile business reported by

Chunghwa Telecom in 2008 declined 1.9% year-over-year due to declining traffic and] price cuts imposed by the National

Communications Commission (NCC) [5].

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ACCEPTED MANUSCRIPT and (3) estimating the relationship between (1) and (2). This measurement can help firms to

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understand their service quality and to evaluate alternative methods for managing customer switching costs, retention, and acquisition by harmonizing the differences in IT/organization milieus between provider and customer, which can improve TS quality. The organization of this paper is as follows. Section 2 discusses the literature on the information technology construct, organization characteristics, perception discrepancy, and telecommunication service industry. Section 3 introduces the hypotheses and methodology of this study. Section 4 presents the questionnaire results, analysis, and findings. Finally, section 5 presents the conclusions and implications of the study.

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2. Background 2.1 Information Technology Construct

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The Information Technology (IT) construct is the amount of investment in IT infrastructure [13-14] and in training [15-16]. Empirical data in many studies indicate that the magnitude of the IT construct in a firm is the crucial factor in the survival and growth of a firm [17-18]. The IT Infrastructure includes computers, communications technology, databases, etc., that

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comprise the IT environment for the software and the hardware requirements of a firm. Two effects of IT infrastructure are under intensive study in the e-commerce literature. The first is reducing the cost of business processes such as electronic data interchange (EDI) and supply chain systems [19], and the second is using information technology to find improved solutions for problems associated with productivity [20-21]. This results in the introduction of new procedures and possible replacement of original procedures. For example, cloud computing requires migration of computing and data from desktop and handhold devices into large data centers, so that services can be executed over the Internet anywhere and anytime, which inevitably changes the business process. Therefore, by evaluating IT infrastructure through the reduced costs and the enhanced productivity, enterprises can realize the performance and the improvement of IT construction on business process. The IT training indicates the learning content that enables employees to understand the means of using IT and to realize the enhanced performance that IT can bring to them [22]. Two dimensions are considered when analyzing how IT training contributes to business effectiveness and efficiency: information technology acceptance [23] and resource-based theories [17]. According to information technology acceptance theory, IT training helps to improve employee attitudes about using the information systems. In the resource-based view, IT training develops the IT human resources (e.g., technical know-how and managerial IT skills) that determine the overall competence of a firm. A firm with strong IT human resource can integrate IT and business processes and can achieve effective cooperation among different business units. By inspecting IT training through the IT acceptance and IT human resource of the employees, enterprises can evaluate the effectiveness and efficiency of IT construction on business process. 3

ACCEPTED MANUSCRIPT 2.2 Organization characteristics

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Organizational characteristics are the formal task and authority relationships that coordinate employee actions and use of resources to achieve organizational goals [24]. Different organizational characteristics also reflect different ways of information processing and organizational practicing. Two dimensions are typically used to represent the attitude and effect of different organizational characteristics on IT usage: centralization and formalization [25-27]. Centralization is the concentration of management power to make decisions and evaluate activities [25]. An organization is highly centralized when the right of the decisions making is retained by managers. Although managers can efficiently coordinate organizational activities,

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opportunities for individual growth and advancement are limited. In contrast, a decentralized organization delegates decisions to frontline employees. Although decentralization can promote flexibility and responsiveness, it increases the difficulty of achieving the long-term business strategy planning and coordination. Formalization is defined as the explicit rules and procedures for performing organizational operations and decision making [24]. In an organization with high formalization, each employee has distinct function/power and clear-cut responsibility, leading that employee behavior can be predicable. Although a highly formalized organization has superior integration and efficiency, it can

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inadvertently impede the spontaneity and flexibility of internal innovation. In an organization with low formalization, the function/power and responsibility are relatively unstructured and undefined, and the employees therefore are more flexible to execute their work. However, as the size and complexity of an organization increases, low formalization can cause inefficient business processes and poor strategic planning.

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2.3 Discrepancy in Perceived Service Quality In this study, service quality is defined as the difference between customer expectations and service performance [28]. Several dimensions of service quality (SERVQUAL) identified in a survey of different industries can be modified for application to different industry conditions and features [29-32]. Therefore, the studies [33-40] regards the dimensions used to evaluate TS can be rearranged by system service quality, information service quality, and customer service quality. System service quality refers to the quality of connectivity, compatibility, and modularity of the hardware and software within an organization; information quality implies the fitness for use of the provided information including the content, accuracy, format, ease of use, and timeliness; customers service quality is the quality of a series of activities designed to assist customers before, during and after a purchase, including the price and technique support. Therefore, the perception discrepancy of service quality (PDSQ) is the gap between “the service quality which provider presume customer to experience” and “the service quality which the customer actually experiences” [41-42]. A high PDSQ means there is a huge difference between “the service quality expected by the provider” and “the service quality experienced by the 4

ACCEPTED MANUSCRIPT customer”. A high PDSQ can cause the provider to misunderstand the causes of the customer

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satisfaction (whether high or low), and leading that the provider makes wrong decision about the future development and wastes huge monetary and time cost which can be avoided. For example, the EEE PC 900A netbook designed by ASUS in 2007 was targeted at schoolchildren in third world countries3. However, this product unexpectedly attracted the interest of business workers as a secondary laptop for travel or business affair because of its low price and light weight 4, which resulted in high PDSQ. Therefore, ASUS misinterpreted the high customer satisfaction as customer interest in a small laptop with robust functionalities. Therefore, ASUS changed the design of the Eee PC to a small laptop with high computational ability and further expanded their product lines. However, the true customer need was simply an “interface” for easy access to data and the Internet

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rather than a powerful and robust laptop. Therefore, the lighter, more portable, and more convenient iPad took market share from the Eee PC in 2009. Afterward, ASUS admitted that Eee PC failed to satisfy the customers and the cost of this failure was 2 years market leading place and countless monetary cost5. The IT construct and organizational characteristics may also be related to PDSQ as do the information quality, system quality, and customer service quality of TS. The gap of IT constructs, e.g., IT infrastructure and IT training, between the provider and customer may affect the perspectives of the provider and customer regarding the philosophies and technologies of TS design

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[43]. In contrast, differences in organizational characteristics, e.g., formalization and centralization, between provider and customer imply incompatible business procedures and, of course, the TS system procedure. These differences may also cause some inconvenience/disutility perceived and experienced by a customer from the original system to the new TS provided by providers [44].

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2.4 The Telecommunication Service Industry A telecommunication service is an offer of service for a fee directly to the public or to a classes of users while telecommunications is the transmission of data selected by the user 6. The TS market is oligopolistic because of the high barriers to entry, such as the enormous cost and license fees of infrastructure construction and the radio spectrum [45]. A TS is an interesting candidate for studying how discrepancies in quality perception affect customer satisfaction for several reasons. First, TSI is a large and significant market because telecommunication service spending comprises the largest ratio of spending on information technology products and services. By year 2011, global TS spending reached $1.7 trillion while global IT spending approximated $3.66 trillion. Therefore, approximately 46.4% of the IT spending is TS spending [46]. Additionally, the penetration rates of mobile and fixed-line broadband TSs in 3 “Asus plans to ship 1 million Eee PCs to schoolchildren in third-world countries.” from news press “The Eee PC is here” (http://news.cnet.com/8301-10784_3-9809393-7.html) 4 The “…8.9" screen does not affect the overall weight of the Eee PC™ 900A, which remains below 1kg – allowing children and women to carry it with ease, but also perhaps as a secondary laptop or a good option for travel…” from the Eee PC product website (http://uk.asus.com/Eee/) 5 Former ASUS CEO Ian Drew stated that ASUS has “failed the consumer because we have imposed constraints on them.” (http://www.gaj-it.com/14190/the-rise-and-fall-of-the-netbook-will-apples-tablet-become-king/) 6 The United State Telecommunications Act of 1996.

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respectively, which demonstrates the growing dependence of Taiwan citizens on telecommunication services [47]. Second, the rapid, complex, and unprecedented progress of telecommunication technology has resulted in continuous development and promotion of new TSs by providers [43]. As a result, TS customers are often forced to learn and integrate these new TSs into their business strategy and workflow in order to strengthen their competition capability. Third, TS customers have highly diverse levels and types of IT adoption/training and organizational structures/procedures [48]. These events motivated this study of the effects of IT and organization on PDSQ. Finally, the oligopolistic TS market in Taiwan cannot quickly respond to the requirements and expectations of customers [4]. This slow interaction process provides an opportunity to observe the changes in the

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perceptions and attitudes of TS providers and customers regarding TS quality. For the same reasons, TS is also an excellent case study to measure the presence, magnitude, and effects of PDSQ.

3.1 Key Constructs and Hypotheses

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3. Hypotheses and Methodology

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This study analyzed the presence, magnitude, and forms of PDSQ by using data obtained from

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TS providers and customers. For this purpose, as mentioned in Section 2, this study defines the provider perception of service quality (PPSQ) as the expected service quality from the provider perspective and defines customer perception of service quality (CPSQ) as the quality and functionality that a customer actually experiences from the acquired service. Therefore, the perception discrepancy of service quality (PDSQ) is the gap between the PPSQ and CPSQ. According to the literature discussed in Section 2.3, the presence and magnitude of PDSQ might be related to the IT construct gap between provider and customer, and they might be also related to the differences in organizational characteristics between the provider and customer. Therefore, this study also defines the IT construct gap (ITG) as the IT construct gap between a provider and a customer in terms of IT infrastructure and training and defines the organization characteristic difference (OCD) as the different degrees of the formalization and centralization between a provider and a customer. By exploring the relationship between ITG and PDSQ and the relationship between OCD and PDSQ, the TS provider can comprehend the conditions under which the PDSQ takes place and predict the direction of the PDSQ changes. Table 1 summarizes these factors along with descriptions and variable names, and Fig. 1 depicts the research framework of this study.

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ACCEPTED MANUSCRIPT Provider IT construct IT Infra.

Provider’s perception of service quality

IT construct gap

IT Training

IT Infra.

H2

Customer IT construct

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Formalization

System service quality

Organization characteristic difference

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H3

Information service quality

H1

Customer service quality

Customer’s perception of service quality

H1: Perceived discrepancy of service quality (PDSQ) does not significantly differ between providers and customers. H2: The IT construct gap between TS provider and customer correlates negatively with PDSQ. H3: The difference in organizational characteristics between the TS provider and customer correlate positively with PDSQ.

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Centralization

Customer service quality

Perception discrepancy of service quality

Provider Organization Char. Centralization

Information service quality

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Figure 1. Research framework

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Table 1. Constructs and Measures Used in this Study

Constructs/ Sub-constructs

Description or Definitions

System service quality

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Service quality

Information service quality

Customer Service quality

The quality of efficiency & effectiveness, functionality, integration, construct cost, and security within an organization. The utility value of the provided information, including the content, accuracy, integrity, usability, and readability. A series of activities for servicing customers before, during and after a purchase, including the after sales service, flexible-price policy, technique support and training.

Code or Measures

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From [40], [49-59] A high value indicates that the customer obtains high connectivity, good compatibility, and excellent modularity of the hardware and software under reasonable monetary cost. From [41], [49], [52-63] A high value indicates that the customer can easily and quickly receive accurate and rich content.

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From [42], [50], [63], [64] A high value indicates that the customer is given a fair price and comprehensive technique support.

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From [19-21] A high value indicates that the firm has suitable computer equipment, an accessible and barrier-free communication environment, and a well-established database.

IT construct

IT infrastructure

The computers, communications technology, database, etc., that comprise the IT environment for the software and hardware requirement of a firm.

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IT training

The learning content that enables employees to understand how to use IT and why it enhances performance.

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From [17], [22-23] A high value indicates that the firm provides comprehensive documents, courses, and training system for its employees to realize the enhanced performance that IT can bring to them.

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From [24] Formalization is high if each employee has a distinct function/power and a clear-cut responsibility, resulting in predicable employee behavior. From [25] A high value indicates that the right to make decisions is retained by managers.

Centralization

The concentration of power to make decisions and evaluate activities.

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Volume of business

The turnover of the company

Respondent characteristics Age of the respondent

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Industry

Respondent years of experience

Job grades

Classifications of jobs held by respondents in their companies

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Years of experience

Education background

Degree and field of study

1= Primary sector of the industry 2= Secondary sector of the industry 3= Tertiary sector of the economy 4= Quaternary sector of the industry 1= NT$10million under 2= NT$11~50 million 3= NT$51million~100 million 4= NT$100 million above

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Customer characteristics The division of business sectors by economic activity [65]

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The explicit rules and procedures for operation and decision making.

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Formalization

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Organization characteristics

The age of the respondent. 1=5 years under 2=6~10 years 3=11~15 years 4=16 years above 1=Chief executives officer 2=Departmental supervisor 3=Project or team manager 4=Skilled workers 1= College of engineering 2= College of management 3= College of social science 4= College of science 5= College of liberal art

First, a simple null hypothesis is introduced to ensure the existence of PDSQ: Hypothesis 1. Perceived discrepancy of service quality (PDSQ) does not significantly differ between providers and customers. After ensuring the existence of PDSQ by rejecting Hypothesis 1, this study distinguishes between the milieu of the provider and that of the customer and how they affect PDSQ. The purpose is two-fold. First, PDSQ is associated with different observable variables (i.e., TS provider and customer), which have different strategic implications. If PDSQ is driven solely by customer characteristics, then the challenge for providers is identifying the customers who are most likely to loyal and those 8

ACCEPTED MANUSCRIPT most likely to be misled by observable attributes or past behaviors. On the other hand, if PDSQ is

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solely due to provider practices, a TS designed by the provider is likely to be affected by non-market forces such as government regulation. Thus, the challenge is how to design their TS offerings and products such that they can balance the nonmarket strategies/issues to maintain customer loyalty in old customers or to develop customer loyalty in new customers. Second, in addition to measuring the presence of PDSQ, the effects of the TS provider and customer attributes on PDSQ should also be measured. Specifically, TS provider and customer attributes should be used to predict PDSQ. The rationale is that the way to estimate PDSQ (in Hypothesis 1) is to compute the PDSQ directly for each provider and customer and to regress them on provider and customer

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characteristics. However, a limitation of this strategy is the inability to predict how PDSQ will evolve by observing the current status of PDSQ. Additionally, it cannot effectively examine customer-specific effects on PDSQ. Therefore, this study developed a model for predicting PDSQ as a function of TS provider and customer attributes, such as the IT construct and organization characteristics. The model also enables conceptualization and prediction of the presence and evolving patterns of PDSQ. Therefore, this empirical analysis attempts to distinguish these effects by statistically controlling for heterogeneity between TS providers and customers. Therefore, this study

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hypothesized that the IT construct gap between TS provider and customer (IT gap or ITG hereafter) affects PDSQ. A large ITG, which results from a TS customer with poor IT infrastructure and insufficient IT training compared to TS provider, may result in customers who are prone to recognize the advantages of TS (i.e., efficiency and effectiveness) but ignore the corresponding “side-effect” (such as the integration/coordination problems) [66-67]. This results from customers with low IT constructs and insufficient IT knowledge to comprehend and predict the effect of introducing such the TS into their company. Therefore, they are inclined to believe and accept the TS service quality would be what the TS provider says. As a result, PDSQ between TS provider and customer is low. In contrast, low ITG may result in high PDSQ. This results from the TS customers with high IT construct comprehend the pros and cons of introducing such IS into their company, and on the other hand, the TS provider who just push the sales cannot know whether their TS is suit for their customer or not. Therefore, they inevitably have a huge TS perception discrepancy. Accordingly, the second hypothesis was formulated as: Hypothesis 2. The IT construct gap between TS provider and customer correlates negatively with PDSQ. By the same arguments as ITG on PDSQ mentioned above, this study also generally expects that organization characteristic difference (OCD) in terms of centralization and formalization between TS provider and customer should have some effect on PDSQ. Organizational characteristics are the implementation, execution, and control of business process. These characteristics also determine the TS design philosophy of TS provider and the behavior pattern of 9

ACCEPTED MANUSCRIPT TS customer when performing their business procedure. Different organization characteristics

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between provider and customer could result in a TS service that does not operate as expected by the TS customer. This arises because the behavioral patterns and business procedures of the employee are shaped to become compatible with the demands of the role requirements of organization. When TS customers become accustomed to the conventional procedure in their organizations, they may become confused when using a TS service developed by the TS provider with quite different organization characteristics. For example, if the provider is an organization with low centralization, the philosophy of delegating authority to subordinates is unintentionally embedded in the designed TS, which depresses the customer in a highly centralized organization since the customer must strictly monitor the efficiency and effectiveness of corporate activities. In contrast, a provider with a

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highly formalized organization would be inclined to design a TS embedded with explicit rules and procedures. From the perspective of a customer with low formalized organization, the explicit rules and procedures result in insufficiency and inflexibility, which leads customers to believe that the quality of a TS designed by the provider is inferior and does not meet their requirements. Thus, the tension and misunderstanding between customers and provider increase. These phenomena may then increase the service perception discrepancy. Thus, the following hypothesis was proposed.

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Hypothesis 3. The difference in organizational characteristics between the TS provider and

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customer correlate positively with PDSQ.

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3.2 Methodology: PDSQ Measurement

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Hypothesis 1 was examined by comparing the preferences of TS provider and customer on attributes of service quality. Without PDSQ, the TS provider and customer would have the same preference on each attributes of service quality based on average quality levels. However, a difference between the preferences of TS provider and customer regarding service quality attributes suggests that they have different perspectives on what TS should be, which results in a PDSQ. Therefore, the two-step process used to measure PDSQ was (1) applying Analytic Hierarchy Process (AHP) to estimate the preference of each criteria from the TS provider perspective and the preference of each criteria from the customer perspective and (2) applying multivariate analysis of variance (MANOVA) to evaluate the variation in the two preferences from the viewpoint of the TS provider and that of the customer. The AHP is a research method to support rational decision making on several qualitative factors, and it makes use of pairwise comparisons, hierarchical structures, and 9-point ratio scaling to apply weights to attributes [68]. Here, the AHP enabled estimation of the preferences for each service quality dimension from the viewpoint of TS provider and customer, respectively. The details of the two-step process are as follows.

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TS quality

Customer service quality

Accuracy

Functionality

Integrity

Flexible-price policy

Integration

Usability

Technique support

Security

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Readability

After-sales service

Training

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Construct cost

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Efficiency & effectiveness

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Level 2

Information service quality

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System service quality

Level 1

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Figure 2. Hierarchical model to assess criteria

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In the first step, two-tier criteria hierarchy is used to apply AHP (Fig. 2). The goal, which is at the top of the control hierarchy, is to assess service quality in TS. Level 1 has three criteria: system

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service quality ( A1,1 ), information service quality ( A1,2 ), and customer service quality ( A1,3 ). Based on the results of expert interviews, several sub-criteria at level 2 are selected using random selection format and simple frequency analysis method. System service quality has five sub-criteria:

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efficiency & effectiveness ( A2,1 ), functionality ( A2,2 ), integration ( A2,3 ), construct cost ( A2,4 ), and security ( A2,5 ); information service quality owns four sub-criteria including accuracy ( A2,6 ), integrity ( A2,7 ), usability ( A2,8 ), and readability ( A2,9 ); customer service quality has four sub-criteria including after sales service ( A2,10 ), flexible-price policy ( A2,11 ), technique support ( A2,12 ), and training ( A2,13 ). The AHP enabled estimation of the preferences of the TS provider regarding service quality, which were A1,p j ( j {1,2,3} ) and A2,p k ( k {1,2,...,13} ) according to the questionnaire results collected from the TS provider. AHP also enabled the calculation of the TS customer preferences regarding service quality were A1,c j ( j {1,2,3} ) and A2,c k ( k {1,2,...,13} ) based on the questionnaire data collected from TS customers. 11

ACCEPTED MANUSCRIPT The second step applies MANOCA to evaluate the similarities in the preferences (i.e., A2,p k and

A2,c k where k {1,2,...,13} ) of the TS provider and the customer. By statistical convention,

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Hypothesis 1 is rejected if the calculated significance value (p-value) is less than 0.05. Otherwise, Hypothesis 1 is accepted. Multivariate analysis of covariance (MANCOVA) was also performed to ensure that the personal characteristics of the respondents would not affect the preference towards the TS. 3.3 Methodology: Drivers of PDSQ

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Hypotheses 2 and 3 were tested by using a two-step process to determine how ITG and OCD affect PDSQ. First, the square root of the sum of the squares (RSS), which is typically used to calculate the aggregate accuracy of a measurement when all measuring items are known, is used to calculate PDSQ, ITG, and OCD. The PDSQ between provider i and customer j ( PDSQi , j ) was obtained by

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( A

PDSQi , j 

p ,i 2,k

 A2,c ,kj )2

(1),

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k 1

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comparing preferences for each service quality criterion between provider i and customer j:

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where A2,p k,i is the preference of provider i regarding the k-th criteria of service quality and A2,c ,kj is the preference of customer j regarding the k-th criteria of the service quality. The ITG between provider i and customer j ( ITGi , j ) can also be calculated by comparing the IT construct between provider i and customer j:

ITGi , j 

H

 ( IC h 1

i h

 IChj )2

(2),

where IChi and IChj are the h-th attribute of IT construct for provider i and j, respectively. The calculation for the OCD between provider i and customer j ( OCDi , j ) resembles that for ITG:

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 (OC

OCDi , j 

g 1

i g

 OCgj )2

(3)

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where OCgi and OCgj are the g-th organization characteristics for provider i and j, respectively.

( ITGi , j  ITG )  ( PDSQi , j  PDSQ )

for all i , j





( ITGi , j  GIT )

( PDSQi , j  PDSQ )

for all i , j

(4)

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for all i , j

(OCDi , j  OCD )  ( PDSQi , j  PDSQ )

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and

R2 

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R1 

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The second step is to use the Spearman correlation coefficient to evaluate how ITG and OCD affect PDSQ. The respective equations for the relationship between ITG and PDSQ (R1) and between OCD and PDSQ (R2) are

for all i , j



(OCDi , j  OCD )



(5),

for all i , j

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for all i , j

( PDSQi , j  PDSQ )

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where PDSQ , ITG , and OCD are the mean values calculated in (1), (2), and (3), respectively. The R value, which ranges from -1 to 1, is the correlation between variables ITG/OCD and PDSQ. An R value of 1 indicates a positive correlation, and an R value of -1 indicates a negative correlation. An R value of 0 indicates that PDSQ and ITG/OCD are not linearly correlated. 3.4 Data: Telecommunication services provider and customer The data used to test Hypothesis 1 regarding the TS provider perspective of service quality were collected from the five TS providers in Taiwan. The five TS providers are Chunghwa Telecom (6,697,428 subscribers, 29.54% of total subscribers), TWM Solution (5,781,758 subscribers, 25.49% of total subscribers), FarEasTone (5,666,932 subscribers, 24.99% of total subscribers), Asia Pacific Telecom (2,860,762 subscribers, 12.62% of total subscribers), and Vibo (1,669,669 subscribers, 7.36% of total subscribers) [69]. Since these TS providers provide similar TS products (i.e., virtual server hosting, audio conference service, micro payment service, etc.) at similar prices, the analysis did not consider the barriers and switching costs for TS customers switching between TS providers. 13

ACCEPTED MANUSCRIPT The data used to analyze the effects of TS customer perceptions on TS service quality were

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collected from TS customers in Taiwan. To ensure consistent data across different industry types, the TS customers are categorized into four Economic sectors: primary (55.55% CPR 7), secondary (73.66% CPR), tertiary (75.39% CPR), and quaternary industry sector (93.48% CPR) [70-71]. The primary industry section includes industries that profit from extraction of natural resources, e.g., farming, mining, and fishing; the secondary industry section are the factories that process products from the primary industries, such as refining metals, producing furniture, and packing farm products; the tertiary industry sector includes services such as teaching, management, etc.; the quaternary industry sector means the research group of science and technology. All collected data were classified into one of these four sectors.

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The same questionnaires were used to collect IT constructs and organization characteristics of TS providers and customers in order to examine Hypotheses 2 and 3. The questionnaires also collect demographic data (years of experience, job grades, education background, and volume of business) from the respondents, which included TS providers and customers to enable use of individual-level control variables and to ensure that the data were demographically consistent. These data had three key limitations. First, the questionnaires are collected from the TS providers and customers in a specific geographic region, i.e., Taiwan. The data may not be uniformly applied without discretion. Second, the questionnaire did not obtain the perspective of the

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TS provider regarding some TS products, i.e., monopolistic TS products (e.g., IPTV) and obsolete TS products (e.g., 2G mobile service). The purpose was to avoid bias since some TS providers do not provide these TS products. The third issue is that data was collected only for work usage but not home usage. Therefore, perceptions of TS service quality were not analyzed in single office/home office (SOHO). The SOHO workers were excluded from analysis because they typically use the same TS products for both work and personal use, which would have introduced errors into the analysis in this study.

4. Results and findings This study explored the relationships among IT construct gap, organization characteristic difference, and perception discrepancy of service quality between TS provider and customer, as shown in Fig. 3. The survey was performed from June, 2012 to February, 2013. The TS customer population included Taiwan firms listed in Taiwan Business Directory published in 2011. A random stratified sampling method was used to select 50 firms in each of the four Economic sectors. The TS provider population included telecommunication service providers in Taiwan. A random stratified sampling method was used to select 25 project leaders/senior software programmers and senior executives (i.e., directors or general managers) to avoid common method variance problems. The surveys were performed in face-to-face interviews and by telephone. Of the 75 questionnaires distributed, 22 responses were invalid. The remaining 53 questionnaires were valid, which resulted

7 CPR: computer penetration ratio

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ACCEPTED MANUSCRIPT in a useable response rate of 70.66%.

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Ⅱ

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IT construct gap

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Ⅲ

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Organization characteristic difference

Perception discrepancy of service quality

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Figure 3. Research model

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Figure 4 shows the three-part questionnaire used for hypothesis testing in this study. The first

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section of the questionnaire was used to collect the respondent characteristics. The second section of the questionnaire was used to perform AHP. The consistency ratio was calculated to ensure consistency in this section. A CR less than 0.1 was considered an indication that the section was trustworthy. The third section of the questionnaire contained Likert-type scales ranging from 1 (completely disagree) to 5 (completely agree). Exploratory factor analysis (EFA) was used to reduce the number of variables regarding the IT construct with the minimum loss of information. Therefore, items with eigenvalues higher than 1 were extracted for analysis, and those with factor loadings higher than 0.7 were retained in order to ensure the convergent validity [72]. To enhance the rigor and simplicity of the measurements, the dimensions of these retained factors were further extracted by principal component factor analysis with varimax rotation method. Cronbach’s alpha values were also calculated to ensure internal consistency of the questionnaires [73]. The reliability and validity of the measurements were ensured by performing the item generation process described in the studies listed in Table 1 in Section 3, in Cron & Sobol [74], and in Sakaguchi & Dibrell [75]. A list of 36 questionnaire items was reviewed by four academic researchers with expertise in survey methodology and telecommunication service. The explanation and corresponding results are given in the subsections below.

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ACCEPTED MANUSCRIPT Ⅰ. Demographics data 1. What is your gender?

Male

Female

2. Age:

Less than 30

31~40

41~50

More than 50

3. Years of experience:

5 years under

6~10 years

11~15 years

16 years above

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Ⅱ. The telecommunication services product quality expectations of cognitive pairwise comparison. 1. Which of these attributes would you think is MORE IMPORTANT? Please compare in pairs the relative importance between two given item.

9:1

8:1

7:1

6:1

5:1

4:1

3:1

2:1

1:1

1:2

accuracy

Ⅲ-A. IT construct

1:4

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1.Companies using digital textbooks training employees.

1:3

Ⅲ-B. Organization characteristic

1:6

1:7

1:8

1:9

B item integrity

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1.Company processes have SOP

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A item

Weak Equal Weak Essential Very Absolute importance importance unimportance unimportance unimportance unimportance

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Absolute Very Essential importance importance importance

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Figure 4. Partial example of the questionnaire

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4.1 Discrepancy in perceived service quality

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Hypothesis 1, i.e., that service perceptions do not significantly differ between TS providers and customers, was tested by the second part of the questionnaire. First, 13 items were used to measure the perception preference of providers and customers regarding TS. A one-way between-group MANOVA was then used to compare the variation in perceptions between TS providers and customers towards TS. Table 2 shows that the multivariate analysis confirmed a statistically significant difference between TS providers and customers toward the TS quality. Table 2(a) and Fig. 5 further reveal the different viewpoints under the restrictive assumption of two criteria for evaluating a TS. As a result, the sets of preferences and perceptions differed between TS providers and customers. Table 2(a) shows that, according to the TS providers, after-sales service, technique support, and effectiveness & efficiency were the key TS quality indicators. In contrast, TS customers indicated that integrity, accuracy, and security indicator were the key TS quality indicators. Notably, Fig. 5 shows that TS providers and customers significantly (above 0.04) differed in the indicators of after-sales service, technique support, construct cost, accuracy, and integrity. The preferences of TS providers regarding after-sales service and technical support were substantially higher than those of TS customers. However, the preferences of TS providers regarding construct cost, accuracy, and integrity were substantially lower than those of TS customers. The hypothesized reasons are the following. The TS provider focuses on of costs and schedules, so the services are designed to highly flexible in order to fit widely varying requirements with minimal modification effort/cost. However, this strategy inevitably requires the provider to improve technical support and after-sales service. It also motivates providers to persuade customers 16

ACCEPTED MANUSCRIPT to upgrade their IT infrastructure to fit the provider TS. However, customers think that accurately

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integrating the TS into customer business procedure is most important and should not be postponed to the after-sales service. Moreover, the TS designed by the provider should also fit the IT infrastructure currently used by the customer rather than requiring an upgrade to hardware/software with enhanced but non-essential capability. Therefore, the strategy to achieve a faster and less costly TS may not always meet customer requirements. This phenomenon is also consistent with the studies in [76-77]. Table 2. Ranking of weighted perceptions: TS customer and TS provider. (a) Preferences towards TS indicators

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Integrity Accuracy Security Construct cost Readability Efficiency & effectiveness Technique support After-sales service Functionality Integration Usability Flexible-price policy Training

Rank 1 2 3 4 5 6 7 8 9 10 11 12 13

TS provider Indicators After-sales service Technique support Efficiency & effectiveness Integrity Training Flexible-price policy Functionality Integration Security Readability Accuracy Construct cost Usability

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Weighted 0.117 0.101 0.093 0.083 0.080 0.077 0.077 0.076 0.073 0.060 0.060 0.052 0.052

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Rank 1 2 3 4 5 6 7 8 9 10 11 12 13

TS customer Indicators

Weighted 0.189 0.174 0.077 0.076 0.072 0.068 0.059 0.059 0.058 0.056 0.053 0.029 0.029

(b) Multivariate test of variance F

Hypothesis df

Error df

Significance

0.582

2.154

13.000

39.000

0.032*

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*p<0.05 (1-tailed)

Value

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Effect Wilks’ Lambda

variation of preference

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After-sales service Technique support

(0.097) (0.054)

Construct cost

(0.048)

Accuracy Integrity

Usability

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(0.035)

Security

(0.031)

Readability

(0.024)

Training

(0.02)

Flexible-price policy

(0.016)

Functionality

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(0.041)

(0.014) (0.001)

Integration

Provider Customer

0.00

0.05

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(0.000)

Efficiency & effectiveness

0.10

0.15

0.20

0.25

Weight

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Figure 5. Preference discrepancy towards TS indicators (The number located at the right-hand of the bar is the difference of weight between customer and provider) This study further controlled the economic sectors of TS customers in order to observe the

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discrepancy in preferences between TS providers and TS customers in different economic sectors. Table 3 shows statically significantly differences between TS providers and customers when controlling the Economic sectors of TS customers. On the other hand, after further controlling for annual income of TS customers, Table 4 also shows that TS providers and customers significantly differed. That is, the discrepancy in TS indicators between TS providers and TS customers occurred regardless of the economic sector or business scale of TS customers.

Category (a) Primary

Effect

Value 0.253

F 2.958

Hypothesis df 13.000

Error df 13.000

Significance 0.030 *

(b) Secondary

Wilks’ Lambda

Variation of preference

Table 3. Multivariate test of variance regarding different economic sectors

0.257

4.217

13.000

19.000

0.002 **

0.324 0.314

2.567 2.526

13.000 13.000

16.000 15.000

0.038 * 0.044 *

(c) Tertiary

(d) Quaternary * p<0.05, **p<0.01 (1-tailed)

Variation of preference

Category (a) ~ NT 10 (b) NT 11 ~NT 50 (c) NT 51 ~NT 100 (d) NT 101~

Effect

Value 0.286

F 3.269

Hypothesis df 13.000

Error df 17.000

Significance 0.012 *

Wilks’ Lambda

Table 4. Multivariate test of variance regarding different annual incomes

0.229

3.896

13.000

15.000

0.007 **

0.316

2.661

13.000

16.000

0.033 *

0.248

3.491

13.000

15.000

0.012 *

* p<0.05, **p<0.01 (1-tailed) NT unit: 1,000,000 New Taiwan dollar. 1 USD = 30.322 NTD (21.6.2013)

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ACCEPTED MANUSCRIPT A MANCOVA was further used to ensure that the personal characteristics of the respondents

F 0.803

Hypothesis df 13.000

Error df 37.000

Significance 0.653

0.716

1.130

13.000

37.000

0.367

0.736

1.021

13.000

37.000

0.453

0.823

0.613

13.000

37.000

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Value 0.780

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Variation of preference

Table 5. Multivariate test of variance Category AGE Years of experience Job grades Education background

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would not affect TS preferences. The control variables included age, years of experience, job grades, and education background. Table 5 shows that respondents with different personal characteristics did not significantly differ in TS preferences.

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Based on the analytical results, Hypothesis 1 was rejected, i.e., service perceptions significantly differed between TS providers and customers. 4.2 Drivers of PDSQ: The IT construct gap

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Hypothesis 2, that the gap in IT construct between TS provider and customer significantly affects PDSQ, was tested by the Ⅲ-A part of the questionnaire. A two-phase procedure was applied,

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and the results were as follows. First, two dimensions with nine items were used to measure the IT construct of TS providers and customers. Table 6(a) shows the results of factor analysis, which revealed two dimensions, IT training (five items, α= 0.88) and IT infrastructure (four items, α= 0.92), which is consistent with the literature review discussed in section 2.1. The items included in the IT training dimension were “Knowledge management mechanism”, “IT consultancy”, “Collaborative training”, “Off-site training”, and “On-site training”. The items in the IT infrastructure were “Software investment”, “Telecommunication technology”, “Personal computer & mobile device investment”, and “Mainframe hardware support”. The Spearman correlation coefficient was then used to measure the relationship between “IT construct gap between TS provider and customer (ITG)” and “perception discrepancy between TS provider and customer toward TS (PDSQ)”. Table 6(b) shows the analytical results, which indicated that ITG has a significant negative effect on PDSQ. Hence, Hypothesis 2 was supported.

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ACCEPTED MANUSCRIPT Table 6. Result for IT construct gap (a) Factor analysis Dimension Items IT infrastructure

Knowledge management mechanism

0.928

0.063

IT consultancy

0.850

Collaborative training

0.845

Off-site training

0.842

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IT training

On-site training Software investment Telecommunication technology

Mainframe hardware support Eigenvalue

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Common of variance (%) Total variance(%)

0.178 0.097

0.812

0.279

0.102

0.924

0.081

0.907

0.210

0.788

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Personal computer & mobile device investment

0.237

0.259

0.736

3.666

2.839

42.154

33.535

42.154

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(b) The influence of IT construct gap on PDSQ

rho-value

p-value

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0.000**

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PDSQ

** p < 0.01 (1-tailed).

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Table 7. The effect of IT construct gap on PDSQ PDSQ Perception discrepancy of

Perception discrepancy of

Perception discrepancy of

system service quality

information service quality

customer service quality

rho value

rho value

rho value

Dimension

ITG

IT infra. gap IT training gap

p-value

p-value

p-value

-0.424

0.000**

-0.494

0.000**

0.305

0.000**

-0.326

0.001**

-0.374

0.000**

0.289

0.000**

**p<0.01 (1-tailed)

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IT construct gap

PDSQ

Perception discrepancy of system service quality

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IT infrastructure gap

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Perception discrepancy of information service quality

－ IT training gap

Perception discrepancy of customer Service quality

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Figure 6. The relationship between IT construct gap and PDSQ

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The effects of two ITG dimensions on three PDSQ dimensions were further explored since the results in Table 6(b) only revealed the compound effect. Figure 6 also presents the relationships between two dimensions of IT construct gap and three dimensions of PDSQ. Table 7 shows that both “the IT infrastructure gap” and “the IT training gap” have significant negative effects on “the perception discrepancy of system service quality” and “the perception discrepancy of information service quality”. The interpretation is that, given that the questionnaires revealed that TS providers have a high IT construct, the lower the IT construct of TS customers, the larger the IT construct gaps. Therefore, “perception discrepancy of system service quality” and “perception discrepancy of information service quality” decrease. The reason is that, once the TS customer IT construct is poor, the TS provider would automatically obtain the expert power8 and TS customer has to obey the authority of TS provider regarding his/her expertise in IT. Specifically, when the TS provider have sufficient IT knowledge which enables him/her to comprehend the situation that the TS customer encounters and provides judgment, the TS customer with low IT construct will likely defer to TS provider. If the TS provider demonstrates his/her experience and achievement in TS and attempts to expand them to the TS customer business procedure, the TS customer tends to respect, trust, and then accept the TS provider’s suggestion/solution and furthermore look to the TS provide for leadership, even the TS customer does not have sufficient IT knowledge to make sure such

8 Expert power is the term widely used in social science to describe power based on credibility or perceived expertise or skills in an area [78].

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ACCEPTED MANUSCRIPT suggestion/solution is suit for his/her business procedure and can be seamlessly integrated into

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his/her original information system. As the result, the TS provider derives expert power from his/her expertise in IT construct, when the TS customer lacks of IT construct and requires such expertise. In contrast, the TS provider cannot obtain expert power when the TS customer IT construct is high and the IT construct gap between TS provider and customer is low. In such circumstance, the TS customer does have sufficient IT knowledge and understand what situation he/her encounters and what TS he/her exactly needs very well. Therefore, the TS customer has the power to disagree with the TS provider regarding the TS especially in terms of system quality and information quality. As a result, “the perception discrepancy of system service quality” and “the perception discrepancy

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of information service quality” inescapably increase. Conversely, “IT infrastructure gap” and “IT training gap” have a significant positive correlation with “the perception discrepancy of customer service quality” as shown in Table 7. This means that, given that the TS providers owns high IT construct based on the questionnaires, the lower IT construct the TS customers own, the insufficient IT knowledge the TS customers have, the larger IT construct gaps are caused, leading that “the perception discrepancy of customer service quality” increase. The reasons for this phenomenon are twofold. First, TS customer service is mostly triggered by the TS customer response. In other words, TS

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customer service is generally provided after the provider receives the complaint from the customer. This gives the TS customer information power9. Once a TS customer does not have insufficient IT knowledge to manage information power, he/she cannot make a rational argument to persuade the TS provider to provide sufficient customer service quality. In this case, the TS provider has the power to contend with the TS customer regarding the TS, especially in terms of customer service quality. The “perception discrepancy in customer service quality” then increases. Second, the TS customer without sufficient IT knowledge tends to ask the TS provider establish a concise and delicate IT risk management10 framework to minimize, monitor, and control the impact of unfortunate events. However, the expert interviews in this study indicated that establishing such framework is difficult for three reasons. First, strategizing and decision making in conventional risk management required statistical analysis of probability based on the prior events. However, as TS evolves with the continuing changes in the technological environment, the designed risk management framework and corresponding measurement may not adequately cope with a potential/unknown new threat11. Second, the IT risk management methodology involves highly subjective valuations of TS customer assets related to TS service, especially for intangible assets such as business processes, information, and intelligent assets. Third, building a system for monitoring deterioration in TS quality and for initiating required action is still a controversial issue both technically and legally. From technical perspective, monitoring TS quality confronts the 9 Information power is the term widely used in social science to describe power based on the potential to manage information including how to how to limit it to the key people, how to organize/interpret it, or even to falsifying it [78]. 10 Risk management is the process of identifying vulnerabilities/threats to information resources and deciding what countermeasures can reduce risk to an acceptable level based on the value of the information resource to the organization [79]. 11 Threat is “a potential cause of an incident, that may result in harm of systems and organization.” [80].

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ACCEPTED MANUSCRIPT scalability problem because the TS traffic traverse along all the routers on the traffic path,

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especially on a global scale TS, rather than merely the two ends of TS provider and customer. From the legislative view, building such a monitoring system is likely to be viewed as an excuse for introducing internet censorship in order to monitor and control the transfer, publication, viewing, and access of information because such a system inevitably infringes upon privacy and eventually affects innocent TS customers with low IT constructs, whose TS traffic may be hijacked without their knowledge. Similar views were also expressed in [81]. A TS customer with a high IT construct, however, can efficiently use information power to persuade the TS provider to provide the required customer service since a TS customer with high IT construct knows what technique supports he/her requires, how to organize and interpret this

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requirement to the key person of the TS provider, and how to persuade him/her to provide such customer service. Therefore, “the perception discrepancy of customer service quality” decreases.

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4.3 Drivers of PDSQ: Differences in organizational characteristics Hypothesis 3, i.e., that differences in organizational characteristics between TS provider and customer significantly affect PDSQ, was tested by the Ⅲ-B part of the questionnaire through a

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First, two dimensions with eleven items were used to capture the organizational characteristics of the TS provider and the TS customer. Table 8(a) presents the factor analysis results. The two dimensions are centralization (six items, α= 0.91) and formalization (five items, α= 0.90), which are consistent with the results of the literature review discussed in section 2.2. Centralization consists of items: “Employee autonomy”, “Chain of command”, “Division of labor and cooperation”, “Participation in the decision making”, “Problem reporting/resolving through one channel”, and “Explicit promotion and rotation system”. Formalization includes “Norm”, “Standard operating procedure”, “Purposely impersonal”, “Stable organization structure”, and “Complex work flow”. Second, Spearman correlation coefficient was also performed to measure the relationship between “the organization characteristic difference between TS provider and customer (OCD)” and “perception discrepancy between TS provider and customer toward TS (PDSQ)”. Table 8(b) shows the analysis results, which indicate that OCD has significant positive effects on PDSQ. Hence, Hypothesis 3 was supported.

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ACCEPTED MANUSCRIPT Table 8. Result for the organization characteristic difference (a) Factor analysis Dimension Items formalization

Employee’s autonomy

0.870

0.037

Chain of command

0.866

Division of labor and cooperation

0.849

Participation in the decision making

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Problem reporting/resolving through one channel Explicit promotion and rotation system Norm

Purposely impersonal Stable organization structure

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Complex work flow Eigenvalue Common of variance (%)

-0.031 -0.067 0.063

0.763

0.159

0.138

0.905

0.007

0.879

0.001

0.876

0.003

0.838

0.002

0.805

4.04

3.70

36.868

34.045

36.868

70.913

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0.001

0.778

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Standard operating procedure

Total variance(%)

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centralization

(b) The influence of organization characteristic difference on PDSQ

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PDSQ rho-value

p-value

0.378

0.000**

The organization characteristic difference

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Table 9. The effect of Diff. of organization characteristics on PDSQ PDSQ Perception discrepancy of

Perception discrepancy of

Perception discrepancy of

system service quality

information service quality

customer service quality

Dimension

OCD

formalization

rho value

p-value

rho value

p-value

rho value

p-value

0.200

0.000**

0.405

0.000**

0.090

0.009**

0.205

0.000**

0.209

0.000**

0.093

0.008**

difference centralization difference **p<0.01 (1-tailed)

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PDSQ

Perception discrepancy of system service quality

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Formalization difference

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＋

+

Perception discrepancy of customer Service quality

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Centralization difference

Perception discrepancy of information service quality

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＋: Positively related －: Negatively related

Figure 7. The relationship between OCD and PDSQ

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This study performed a detailed analysis of the effects of differences in two dimensions of organizational characteristics on three dimensions of PDSQ. Whereas Table 8(b) only shows the compound effect, Table 9 and Fig. 7 show that both “formalization difference” and “centralization difference” significantly and positively affect the perception discrepancy of system service quality, information service quality, and customer service quality. This confirms the assumption in Section 3.1. Notably, the positive effects of “formalization difference” (rho value=0.090) and “centralization difference” (rho value=0.093) on the perception discrepancy of customer service quality are relatively small. The reason is provided as follows. TS providers have evolved into an organization with low centralization to ensure a more responsive and adaptive for the more rapidly changing TS business environment, and they have also developed as a high formalized organization to provide a predicable procedure without losing control of their giant TS cooperation’s activities. As a result, a TS provider with low centralization and high formalization matches the expectations of the TS customer regarding TS customer service quality, i.e., TS customers prefer customer service is highly responsive, adaptive, and predictable [82], which decreases the effect of “organization characteristic difference” on “the perception discrepancy of customer service quality”.

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ACCEPTED MANUSCRIPT 5. Implications and conclusions

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Based on data commonly available in TS industry, this study measured the presence and magnitude of PDSQ. The analytical results revealed statistically significant perception differences between TS providers and customers in terms of TS information quality, system quality, and customer quality regardless of economic sectors or business scale of TS customers. Notably, the perception of TS providers and customers substantially differed in indicators of after-sales service, technique support, construct cost, accuracy, and integrity. The relationships between the ITG/OCD and PDSQ were further investigated. The results show that ITG is negatively correlated with PDSQ mainly due to a firm with high IT construct owns

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high expert power. This leads the firm with low IT construct tends to respect, trust, and accept the suggestion/solution of the firm with high IT construct, and look for leadership in advance. As a result, the higher ITG exists, the lower PDSQ is. On the other hand, the OCD is positively correlated with PDSQ because the more similar organization characteristics the provider and customer have, the more similar business behavior patterns they have, leading they have more similar perception toward the TS quality. Therefore, PDSQ decreases as OCD decreases. The analytical results of this study have several implications for researchers and practitioners. First, this study offers a new and comprehensive view of TS provider/customer perceptions and

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attitudes about TS. This study shows how and why their perceptions toward TS differ and also provides a model for measuring its presence, magnitude, and in what form it exists. This model further explores the conditions under which perceptions differ and their directions of change. Second, the TS provider can apply the proposed model to develop a business strategy based on PDSQ rather than merely relying on the customer satisfaction. By using the model to predict the evolvement of TS, the TS provider can adjust their future TS investment accordingly. The TS provider can also use the model to predict customer decisions after estimating ITG and OCD. Third, TS customers can also use this model to understand the motivations of the TS provider to provide such a TS service to them. That is, the TS customer can analyze and predict the business strategy of the TS provider by this model. Moreover, TS customers can better gauge the pros and cons of TS investment by linking this model, their short/long-term TS strategies, and their business activities relative to TS.

6. References [1] M. Minges, “Is the Internet mobile? Measurements from the Asia-Pacific region,” Telecommunications Policy, vol. 29, no. 2-3, pp. 113-125, 2005. [2] Institute for information industry foreseeing innovative new digiservices, “2011 Taiwan’s Internet and mobile environment,” Institute for information industry, Taiwan (R.O.C.), 2011. [3] D.J. Leea and J.K. Ahnb, “Factors affecting companies’ telecommunication service selection strategy,” Omega, vol. 35, no. 5, pp. 486-493, 2007. 26

ACCEPTED MANUSCRIPT [4] C.C. Kang, “Privatization and production efficiency in Taiwan’s telecommunications industry,”

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Telecommunications Policy, vol. 33, no. 9, pp. 495-505, 2009. [5] Chunghwa Telecom Co., “Chunghwa telecom reports operating results for full year 2008,” news press, 2009. [6] G. A. Jr. Churchill and C. Surprenant, “An investigation into the determinants of customer satisfaction," Journal of Marketing Research, vol. 19, no. 4, pp. 491-504, 1982. [7] Y. Y. Lee, Y. T. Park, and H. S. Oh, “The impact of competition on the efficiency of public enterprise: the case of Korea telecom,” Asia Pacific Journal of Management, vol. 17, no. 3, 423-442, 2000.

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[8] T. Sueyoshi, “Privatization of Nippon telegraph and telephone: was it a good policy decision?” European Journal of Operation Research, vol. 107, no. 1, 45-61, 1998. [9] J. K. Chen and Y.C. Lee, “A new method to identify the category of the quality attribute,” Total Quality Management, vol. 20, no. 10, pp. 1139-1152, 2009. [10] B. W. Cheng and W. H. Chiu, “Two-dimensional quality function deployment: An application for deciding quality strategy using fuzzy logic,” Total Quality Management, vol. 18, no. 4, pp. 451-470, 2007. [11] J. Randy, “Exploring the determinants of cable television subscriber satisfaction,” Journal of

[14]

[15]

[16] [17] [18] [19]

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Highlights  Objectively evaluating the quality and the potential of TS is difficult.  This is due to the perceptions of providers and customers toward TS are different.  This study measures the presence, magnitude, form of the perception discrepancy.  This study shows their different milieus correlate with the perception discrepancy.  This study can help TS providers/customers shape their TS development strategies.

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