The Impact of Market Freedom on the Adoption of Third-party Electronic Marketplaces: A Fuzzy AHP Analysis

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The impact of market freedom on the adoption of third-party electronic

marketplaces: A fuzzy AHP analysis

Hsin-Pin Fu

a,

⁎

, Pei Chao

a,1

, Tien-Hsiang Chang

b,2

, Yu-Shuang Chang

c,3 a

Department of Marketing and Distribution Management, National Kaohsiung First University of Science and Technology, 2, Jhuoyue Rd., Nanzih District, Kaohsiung City, 811, Taiwan, ROC

b

Department of Information Management, National Kaohsiung University of Applied Science, Kaohsiung, Taiwan, ROC, No.415, Jiangong Rd., Sanmin District, Kaohsiung City 80778, Taiwan ROC

c

Foreseeing Innovative New Digiservices (FIND), Advanced e-Commerce Institute (ACI), Institute for Information Industry, Taipei, Taiwan, ROC, 8F., No. 133, Sec. 4, Minsheng E. Rd., Songshan District, Taipei City 105, Taiwan ROC

Received 12 July 2005; received in revised form 2 March 2007; accepted 4 July 2007 Available online 4 September 2007

Abstract

Electronic-marketplace (EM) is an innovative model for interfirm transactions that are undertaken via the Internet. However, in view of higher investment costs and other associated risks, many small and medium-sized enterprises (SMEs), instead of establishing their own EMs, turn to adopt third-party-hosted EMs. In literature, most relevant studies to the adoption of the third-party-hosted EM were conducted on the research contexts of free market. Industries under the protection of government policies may have limited degree of market freedom, different from industries without these protection policies. Thus, this study intends to compare the decision choice of EM adoption between industries with various degree of market freedom. The decision choice of EM adoption consisted of many strategic factors that were constructed in terms of a three-layer hierarchical structure proposed in this paper. A fuzzy analytic hierarchical process (Fuzzy AHP) was utilized to estimate the relative importance of these individual strategic factors involved in the decision-making process of adopting third-party EMs. The research findings indicated there were some similarities and differences in the decision choice between the two industries of interest. The variety of market freedom can account for the differences in the decision choice of EM adoption. In addition to enhancing our understanding of the EM adoption decision of participative companies, the research findings also provide insightful information to third-party EM providers so that they may improve the effectiveness and efficiency of resource allocation.

Keywords: Electronic marketplace; Strategic factors; EM adoption decision; Fuzzy AHP

1. Background and motivations

Electronic-marketplace (EM) is an innovative model for between-organization transactions undertaken via the Internet. Transactions through EMs enable companies to enhance the efficiency of transaction-relevant activities, such as searching for potential trading partners, disseminating necessary

infor-mation about traded-product requirements, negotiating over trading terms, and monitoring product and money flows (Bakos, 1998; Lassen, Kandampully, & Barker, 2002). In the same vein,

Lucking-Reiley and Spulber (2001)argued that the benefits of EM adoption include lowering searching and transaction costs, enhancing efficiency by means of automated transactions, and improving economic gain resulted from the disintermediation effect. Moreover, buyers and sellers from all around the world are able to do business on the EM from which an aggregated result, we believe, is to improve industry-wide efficiency as well. Therefore, the EM can be viewed as a significant innovation that is expected to re-structure the supply chains in

many industries (Gunasekaran, Marri, McGaughey, &

Nebh-wani, 2002; Keskinocak & Tayur, 2001; Sodhi, 2001). As

Industrial Marketing Management 37 (2008) 698–712

⁎ Corresponding author. Tel.: +886 7 6011000x4221. E-mail addresses:hpfu@ccms.nkfust.edu.tw(H.-P. Fu),

peichao@ccms.nkfust.edu.tw(P. Chao),thchang@cc.kuas.edu.tw

(T.-H. Chang),mbaby@iii.org.tw(Y.-S. Chang).

1_{Tel.: +886 7 6011000x4224.} 2_{Tel.: +886 7 3814526x7509.} 3_{Tel.: +886 2 87326222x241.}

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recognizing these merits associated with the adoption of e-marketplace, companies become highly motivated to partici-pate in EMs. However, if participating an EM, companies are still very concerned about some EM-associated risks, such as security problems of the safety and confidentiality of customer data, slow responsiveness to trouble shooting and high switching costs (Ekanayaka, Currie, & Seltsikas, 2003; Tao, 2001). Besides, high investment costs and investment-relevant risks lead most small and medium-sized enterprises (SMEs) to abandon the idea of establishing their own EMs and turn to adopt third-party-hosted EMs. For these companies, the adoption of a third-party hosted EM may be viewed as a proper choice due to gaining a maximum benefit with a minimum associated risk. Hence, we expect a demand for third-party-hosted EMs rapidly increases in the near future.

We may view the third-party EM providers as one of application service providers (ASP). The ASP services, also referred to as an“app-to tap,” provide a centralized repository for software applications that individual participants can “borrow” or “rent” to run on their own desktop computers. This kind system is called a thin client because the applications no longer reside on the participants' systems (Afuah & Tucci,

2003). For participative companies, they may have limited

control over subsequent operations after hooking up with a given application service provider. Moreover, the consequence of these subsequent operations undertaken by the service provider is crucial to these participative companies. By implication, the decision choice of whether to joint a third-part hosted EM becomes very important to prospective companies. Therefore, this paper intends to explore what strategic factors and their individual importance are involved within the decision choices of companies that intend to adopt a third-party EM.

After participating EMs, companies can carry out their transactions via the Internet. The Internet with some essential characteristics (e.g., no limitation of boundary and time) may

allow companies to undertake transactions in a “free” (i.e.,

borderless) market. However, some economic entities around the world are still legislating protection policies for fostering the development of their domestic industries. Under the regulations of the World Trade Organization (WTO), any economic entity that intends to enact the protection policies must sign bilateral government procurement agreements (GPAs) before imple-menting the policies. That is, an economic entity under the WTO's regulations must negotiate with other economic entities to sign GPAs if the entity intends to exclude its certain domestic

industries from free-trade conditions (WTO, 2005). Hence,

companies that have even adopted the EM are still situated in a circumstance of limited market freedom.

Issues relevant to the EM have been received much attention in literature. For example, some studies have concentrated on the business models for EM (Bakos, 1998), whereas others have

discussed about such issues as application models (Grieger,

2003), practical applications (Gottschalk & Abrahamsen,

2002), the hidden motivation of manufacturing industry in

adopting EM (Alba, Lynch, Weitz, & Janiszewski, 1997), the

role of marketplace on the Internet (Bakos, 1998), and the

structure for selecting EM (Stockdale & Standing, 2002). However, these studies have been limited to certain specific issues or concentrated on particular industries. To our best knowledge, no study has been undertaken to compare the decision choice of EM adoption between industries; especially, two industries are characterized with various degrees of market freedom.

As mentioned before, industries under the protection of GPAs have limited market freedom, relative to industries without this regulation. Given the industries with various degrees of market freedom, is there any difference in strategic factors involved in the decision choice of EM adoption? Furthermore, are these involved strategic factors identically important (or weighted) to influence the decision choice? Therefore, the purpose of this paper is to compare the decision choice of EM adoption between industries with various degrees of market freedom, especially in comparing the relative importance of individual strategic factors involved in the EM adoption choices. To find out the relative importance (or weight) of the individual strategic factors is a multicriteria analysis (MCA) problem. Therefore, a fuzzy analytic hierar-chical process (Fuzzy AHP) was utilized to examine the relative weights among the strategic factors within the decision-making process when industries are conditioned on various degrees of market freedom.

The remainder of this paper is organized as follows: first, we review prior studies relevant to strategic factors involved in the decision choice of EM adoption. And then, the characteristics of the two industries under study are described. After that, we discuss the methodological issues related to this study and then undertake empirical analysis. The empirical findings and their managerial implications are reported. Finally, we present the limitations of this study and recommend potential directions for future research.

2. Literature review

EM is an innovative model that allows companies to carry out their transactions via the Internet. To companies, the adoption of EM is expected to shift, at least partially, their existing operation modes into new, inexperienced ones that may not benefit the companies for a certainty. Because of the uncertainties associated with the EM adoption, its decision choice becomes extremely critical to prospective EM adopters. In view of the importance of decision choice of EM adoption, this paper concentrates on what strategic factors are involved and how each strategic factor is weighted in the decision-making process.

In the following, we began with discussing prior studies regarding the strategic factors involved in the decision choice of EM adoption.

2.1. Survey of strategic factors involved in the decision choice The main motivation for companies to adopt an EM is to create the first-mover advantage; that is, by means of the EM adoption, companies are able to establish an advantageous

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competition position before competitors (Bakos, 1997). After adopting an EM, companies are more likely to capture prospective customers for their new products and then

expectedly to gain market shares (Raisch, 2001). To enhance

customer value, companies adopt an EM to serve their existing customers better, especially when their key customers have been accustomed to EM services (Stockdale & Standing, 2002). Similarly, companies are highly motivated to adopt EM if their industry's leading companies have already adopted EM (Stockdale & Standing, 2002). Kaplan and Sawhney (2000)

proposed that a stretch of time saved in gathering a large number of buyers to transact on an EM is the key success factor for the implementation of an EM.

From the perspective of improving efficiency, the adoption of EM allows buyers to reduce purchase prices and undertake transactions with lower costs, and concurrently maintain their flexibility (i.e., switching easily from one supplier to another) (Skjøtt-Larsen, Kotzab, & Grieger, 2003).Detourn, Fischer, and Larson (2000)observed that B-to-B e-commerce contributes to reducing inventory costs, increasing production capacity, enhancing market efficiency, lessening purchase price, and

creating superiority over market intelligence. Hung, Ku, and

Chang (2003)indicated that service charge is the major concern for companies in deciding whether to adopt a third-party application service provider or not.

From the perspective of the completeness of an EM's functions,Skjøtt-Larsen, et al. (2003)observed that the nature of buyer-seller relationships is transformed from‘arms length’ to partnership or strategic alliance. The most noticeable character-istic distinguishing between the former and the latter is inter-firm collaboration.Noekkenved (2000)viewed collaborative relation-ships as relationrelation-ships in which buyers and sellers are‘working jointly’ with each other. In the study ofKumar and Crook (1999), variables to promote inter-firm collaboration include economic incentives, strategic alignment, inter-firm conflicts, and social

issues (such as trust). Rudberg, Klingenberg, and Kronhamn

(2002), furthermore, demonstrated that the function completeness of an EM could facilitate collaborative supply-chain planning.

Agrawal and Pak (2001)also pointed out that the consequential performance of transactions on EM cannot be enhanced until its provider carries out all necessary functions. The more integrity (i.e., completeness) of an EM's functions, the more likelihood of

prospective companies to speed up their EM adoption (Brunn,

Jensen, & Skovgaard, 2002).

From the perspective of infrastructure relevant to EMs, if companies are not willing to set up an EM on their own from scratch, they can employ the services of EM website technicians for various services (e.g., technology implementation, telecom-munication infrastructure, logistics, product-content manage-ment, credit-rating information, business surveillance, pre-shipment inspections, financial payment, etc.) (Hsiao, 2003).

Tan and Wu (2003)concluded that the infrastructure problem is

a major barrier to EM diffusion in China. A study ofKraemer,

Gibbs, and Dedrick (2002), whose research contexts included the USA, France, Denmark, Germany, Japan, Singapore, Taiwan, China, Brazil, and Mexico, emphasized the vital role

of infrastructure in e-commerce adoption. Farhoomand,

Tuu-nainen, and Yee (2000) concluded that the infrastructure problems in Hong Kong and Finland are related to a lack of government support and underdevelopment of regulatory infrastructure. The prospect of e-commerce development in Mainland China was based upon the advancement of regulations

and infrastructure. Kendall, et al. (2001), in an e-commerce

survey of Singapore, mentioned the importance of the receptivity of technological features among EM participants. The technological features, according toTruman (2000), include network security, within-system integration, and the integration of internal data systems with electronic data interchange

systems. Markus and Soh (2002) stated that most Asian

countries do not have viable infrastructures to support EM services, including financial infrastructure, legal and regulatory infrastructure (e.g., taxation), a government's policy promoting the Internet usage, logistics infrastructure, telecommunications infrastructure, appropriate local business practices (e.g., pay-ment), language and education, and industry concentration.

From the perspective of logistics, Gurãl, Ranchhod, and

Hackney (2001) argued that Internet commerce does not eliminate the need for physical logistics systems; on the contrary, Internet commerce increases their importance.Grieger (2003)argued for the concept of value networking, in which the EM is playing an essential role of organizing and managing a complex collection of partnerships among physical logistics service providers.

2.2. Survey of comparison of the decision choice across industries

Many countries have been aware of the consequential impacts of the innovative transaction model. In 2001, the Industrial Development Bureau (IDB) of Taiwan Ministry of Economic Affairs selected nine industries (i.e., steel industry—

STE, information industry— INF, heavy electrical machinery

industry— HEMI, textile industry — TEX, paper industry —

PAP, food industry— FOD, precision machinery industry —

PMI, automobile industry— AUT, medical industry — MED).

And then, IDB funded relevant associations to these individual industries for proposing their industrial plans of the EM development. At the same time, the Taiwan's government also undertook a survey for identifying the strategic factors taken into consideration when these industries were contemplating the adoption of EMs (IDB, 2002).

There were many strategic factors identified in this survey. However, the importance of the individual strategic factors was various among these industries; for example, (i) rolling-out first and gaining market share for the industries of STE, INF and HEMI; (ii) attracting new buyers for the industries of TEX, PAP, FOD and PMI; (iii) increasing product visibility for the TEX industry; (iv) strengthening marketing channels for the TEX industry; (v) strengthening protection of patents and trademarks for the TEX industry; (vi) increasing the ability of the enterprise's resource utilization for the PAP and FOD industries; (vii) strengthening customer service and interaction for the TEX industry; (viii) lowering transaction costs for the industries of TEX, FOD and STE; (ix) strengthening integration

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and collaboration of cross-industry marketing activities for the HEMI and AUT industries; (x) strengthening integration and collaboration of target markets from other industries for the PMI industry; (xi) serving customer's demand better for the industries of PMI, FOD, STE, INF and HEMI; (xii) finding out new suppliers for the industries of PAP, FOD, STE, INF and HEMI; (xiii) receiving trend information about industry development for the industries of TEX, FOD, INF and HEMI; (xiv) emphasizing the degree of compatibility of existing technologies with new ones for the industries of FOD, INF and MED; (xv) ensuring transaction security & trust for the industries of MED, FOD, INF and HEMI; (xvi) developing the degree of intensity of market competitiveness for the MED and INF industries); (xvii) following customer's EM requests for the MED industry; (xviii) expanding organizational scope for the MED industry; (xix) increasing the degree of managerial comprehension and organizational application ability for the INF industry; and (xx) improving the degree of employee's knowledge and capability for the MED and FOD industries. 3. Research settings

Until now, 13 economic entities have signed the GPA and some other ten economic entities (including Taiwan) are within

the negotiation process (WTO, 2005). The heavy electrical

machinery industry (HEMI) is the only Taiwanese industry that comes to the GPA policies and becomes a strategically domestic-protection industry. In 1984, the Ministry of Eco-nomic Affairs of Taiwan began to promote a localization policy to foster the development of HEMI. Under the regulations of this policy, for example, if the state-owned business, Taiwan Power Company (TPC), needed to procure necessary equip-ment, TPC was required to open its tenders only to domestic suppliers whose qualification has been initially certified by the TCC (TPC Certification Committee). According to the statistics

of the Industrial Development Bureau (IDB, 2004), 85% of

sales within a time period between 1999 and 2003 was to domestic markets and only 15% was to foreign markets (see

Table 1), which indicates that the HEMI concentrated mainly on the domestic market as a result of the protection policies. Therefore, the HEMI may be viewed as the industry with less market freedom.

In contrast, the precision machinery industry (PMI) has not been constrained upon the regulations of this localization policy. Although the characteristics of this industry are similar to those of the HEMI (in terms of production procedures, long product lifecycle, high unit price, high capital investment, and high technology intensity), the ratio of domestic to export sales

during the same time stretch (1999–2003) was 30% to 70% (see

Table 1), which indicates the PMI is more export-oriented. Hence, the PMI may be regarded as the industry with more market freedom.

For the research purpose of this paper, we selected the HEMI and the PMI as our research contexts, which, respectively, represent the industries with various degrees of market freedom. 4. Methodology

This paper is to examine the relative weights among the strategic factors within the decision-making process of EM adoption. The phenomenon under study is viewed as a multicriteria-analysis (MCA) problem. To solve this MCA problem, an analytic hierarchical process (AHP) proposed by Saaty (1980) has been widely applied to identify the weight ratios among strategic factors involved in the decision-making process (Radcliffe & Schiederjans, 2003; Moreno-Jiménez & Polasek, 2003).

The basic idea of AHP is to capture experts' knowledge of phenomena under study. However, the conventional AHP may

not be able to truly reflect human cognitive processes —

especially in the situations where problems are not fully defined and/or solving these problems involves uncertain data (so-called

‘fuzzy’ problems). To make up for this shortcoming,Laarhoven

and Pedrycz (1983)therefore introduced the concept of‘fuzzy theory’ to AHP assessments. This so-called ‘fuzzy analytic hierarchical process’ (thereafter ‘fuzzy AHP’) is able to solve

uncertain ‘fuzzy’ problems and to rank excluded factors

according to their weight ratios. Therefore, the fuzzy AHP is utilized in this study.

By integrating relevant studies to Fuzzy AHP analysis in literature, we propose the constituent steps of the Fuzzy AHP. These steps are described, respectively, as follows:

I. Establishing a hierarchy framework

The establishment of a hierarchy framework is based upon the subject matter of interest. Within the hierarchy framework, different criteria may exist. Each criterion may consist of several sub-criteria. By definition, the statements (i.e., description of the subject matter) of sub-criteria should be more specific and more concrete than those of criteria. II. Designing questionnaire

The AHP involves the principles of decomposition, pair-wise comparisons, and priority vector generation and synthesis (Saaty & Bennet, 1977; Saaty, 1980). Therefore, the design of the questionnaire incorporates pair-wise comparisons of factors (i.e., statements) within the hierarchical framework.

III. Establishing fuzzy numbers

Collected through the questionnaire developed at the

Table 1

Import/export data for each industry for the last five years (NT$ billion) Industries Textile Petrochemical PMI Paper Auto HEMI Import value 1999 210 221 144 72 191 40 2000 283 274 156 74 206 34 2001 239 275 105 62 162 27 2002 252 296 123 62 188 28 2003 309 357 147 70 202 30 Export value 1999 443 81 266 12 37 5 2000 501 132 314 14 41 6 2001 442 145 295 14 30 6 2002 422 177 327 16 33 5 2003 408 223 353 19 46 6 Import/export ratio (%) 37:63 65:35 30:70 82:18 84:16 85:15

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previous step, responses of all informants can be formulated as fuzzy numbers.

IV. Constructing fuzzy positive reciprocal matrix

Given the fuzzy numbers, we can construct a n × n fuzzy positive reciprocal matrix.

V. Test consistency

According to the principle suggested by Csutora and

Buckley (2001), let A¯ =⌊a¯ij⌋ be a fuzzy positive reciprocal matrix with aij= (αij/βij,γij/δij). Choose aij∈(βij,γij) and form A =⌊aij⌋. If A is consistent, then A¯ is consistent. Consistency index (CI) and consistency ratio (CR) are calculated as follows:

CI¼ kð max nÞ= n 1ð Þ

CR¼ CI=RIð nÞ 100k

Saaty (1980)suggests that CI≤0.1 is an acceptable range.

λmax is the maximum eigenvector of pair comparative

matrix. n is the number of sub-criteria of the matrix. RIn represents randomized index whose values are shown as

Table 2, according to the study ofAguarón and Moreno-Jiménez (2003).

VI. Eestablishing original matrix (X matrix)

After verifying the consistency of the fuzzy positive recip-rocal matrix, we then begin with establishing original matrix. VII. Undertaking defuzzification

Following the suggestion ofChen and Hwang (1992), we

can obtain the interval of fuzzy weights, (W0l⁎,W1l⁎,

W1u⁎,W0u⁎) by the defuzzification process (α-cut

method) proposed byCsutora and Buckley (2001).

VIII. Undertaking normalization and synthetic analysis Within this step, we normalize the local weights of all factors within the fuzzy weight interval given a criterion (or sub-criterion) and then obtain the global weight of individual factors given the criterion (or sub-criterion). 5. Empirical analysis

By following the steps of Fuzzy AHP discussed above, we analyzed the weights of the strategic factors involved in the EM adoption choice. The analytical steps are described in the following. 5.1. Establishing a hierarchy frameworkt

From a comprehensive literature review, we have identified a number of strategic factors involved in the overall decision-making process of EM adoption. For the purpose of clarification, these strategic factors can be classified into five scopes (i.e., A, B, C, D and E) of the decision-making process (seeFig. 1). Each scope consists of a set of strategic factors. For example, scope A covers internal factors of a participative company. Scope B includes

factors interfaced between the participant and EM provider. Scope C covers factors related to the completeness of functions carried out by the EM provider. Scope D represents factors associated with the interface between the EM provider and the participant's customers. Scope E represents factors of the participant's customers.

The strategic factors within the scopes B, C, and D are more relevant to the research purposes of this paper. Therefore, derived from prior studies in literature, these strategic factors were further organized into a preliminary 3-layer hierarchical structure by which we expect to capture the comprehensive phenomenon of the decision choice of EM adoption. In order to validate the preliminary hierarchical structure, we invited three scholars and eight industrial experts who either had been directly involved in a decision-making process of EM adoption, or had promoted the concept of EM in Taiwan. After a thorough discussion among these members, the validated form of three-layer hierarchical structure was presented, as shown inTable 3, which consists of‘criteria,’ ‘sub-criteria,’ and ‘attribute’ layer. 5.2. Designing questionnaire and data collection

This paper employed questionnaire for data collection. Derived from previous studies in literature, a set of question items (i.e., strategic factors shown inTable 3) was included in the questionnaire of this paper. We used a 9-point rating scale for each of two items (i.e., strategic factors) given one question (shown in Appendix 1). Table 2 Randomized index of RIn N 3 4 5 6 7 8 9 10 11 12 13 14 15 16 RIn 0.52 0.88 1.11 1.25 1.34 1.40 1.45 1.48 1.51 1.53 1.55 1.57 1.58 1.59 5 2 5 2 1 4 2 4 3 5 5 0 3 5

Fig. 1. The scope of decision choice of adopting EM.

Table 3

The three-layer hierarchical structure and its attributes Criteria layer Sub-criteria layer Attribute layer C1:increase

revenues

C1.1:increase sales C1.1.1: increasing new buyers C1.1.2: increasing product visibility C1.1.3: launch of new product C1.2: keep existing

customers

C1.2.1: track customer demand C1.2.2: upgrade customer values C1.2.3: increase communication channels

C1.3: strengthen corporate advantages

C1.3.1: upgrade logistic abilities C1.3.2: strengthen company image C1.3.3: enable strategic alliances C2: lower

costs

C2.1: lower environmental costs

C2.1.1: collecting the competitor information

C2.1.2: receive trend information about industry development

C2.1.3: keep informed of relevant government policies and regulations C2.2: lower

operational costs

C2.2.1: lowering transaction cost C2.2.2: lowering marketing cost C2.2.3: lowering inventory cost C2.3: lower adoption

costs

C2.3.1: completeness of the transaction functions

C2.3.2: number of the participants C2.3.3: safety of transaction C2.3.4: adoption fees

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Hsin-Pin Fu currently serves as a professor of Department of Marketing and Distribution Management at National Kaohsiung First University of Science and Technology. He holds a Ph. D. from Department of Industrial Engineering and Management, National Chiao Tung University, Taiwan. His current research interests are in electronic business and operation management in industrial applications. Mr. Fu has published over 25 articles in International Journal.

Pei Chao is an assistant Professor of Department of Marketing and Distribution Management at National Kaohsiung First University of Science and Technology in Taiwan. He holds a Ph. D. from Boston University, U.S.A. major in Marketing. His research interests include Customer Relationship Management and Relationship Marketing in both business-to-business and business-to-consumer contexts. His recent work has appeared in The Service Industries Journal, Internet Research and Journal of Manufacturing Technol-ogy Management.

Tien-Hsiang Chang is an associate professor at Department of Information Management, National Kaohsiung University of Applied Science, Kaohsiung, Taiwan, ROC. She holds a Ph. D. from Department of Industrial Management, National Taiwan University of Science and Technology. Her current research interests are in operation research, stochastic and information management. Dr. Chang has published over 15 articles in International Journal.

Yu-Shuang Chang currently is project planner of Foreseeing Innovative New Digiservices, Advanced e-Commerce Institute, Institute for Information Industry, Taipei, Taiwan, ROC. She holds a MBA degree from Department of Marketing and Distribution Management at National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan, ROC. Her current research interests are in marketing management and e-business.