Development of a tool for selecting mobile shopping site: A customer perspective Jen-Her Wu a,*, Yu-Min Wang b,1 a Department of Information Management, Institute of Health Care Management, National Sun Yat-sen University, 70, Lien-Hai Road, Kaohsiung 804, Taiwan b Department of Information Management, National Chi Nan University, 1, University Road, Puli, Nantou Hsien 545, Taiwan Received 1 June 2005; received in revised form 10 August 2005; accepted 10 September 2005 Available online 20 March 2006 Abstract While mobile technologies and applications are rapidly and widely utilized in electronic commerce, it is extremely important to better understand the evaluative criteria from the consumer's viewpoint in mobile shopping (m-shopping) site selection. This paper investigated the consumer-oriented criteria for m-shopping site selection. An initial criteria list was developed based on some previously validated instruments and then tested to prove its reliability and validity. The final criteria list includes three factors: assurance, merchandise, and enabling functions. This list provides multidimensional criteria for m-shopping site selection in business to consumer markets and provides great insight for managing and developing m-shopping sites. 2006 Elsevier B.V. All rights reserved. Keywords: Mobile shopping; Mobile commerce; Mobile shopping site 1. Introduction With the tremendous advances in hand-held computing and communication capabilities, mobile commerce (mcommerce) is expected to be the next big wave in business. A number of m-commerce applications have been developed and are already in use, covering a wide range of business functions from advertising, banking, ticketing, games, to shopping. Today, the world of business is witnessing profound changes under the influence of wireless technology. The opportunity for m-commerce has opened. M-commerce broadly refers to any transactions with monetary value that is conducted over a wireless telecommunication network [1]. Market researchers have predicted that, by the end of the year 2005, nearly 500 million wireless device users will exist, generating more than $200 billion in revenue [27]. Dollars increase in wireless services may soar from $37 billion in 2001 to $74 billion in 2005 [21]. Mobile Internet access will become a primary tool for completing daily information transactions, e.g., e-mail, retail shopping, and receiving the news [8,22]. Among the innovations in m-commerce services for consumers, shopping via the mobile channel could have a great potential and opportunity [16] and would be a major business channel in the coming years [22]. Mobile shopping (mshopping) allows the consumers to order and pay for goods using a mobile phone regardless of time and place. However, m-shopping could disrupt existing retail models and threaten the established orthodoxies of online selling as many as those of entrenched physical retailers [29]. If shops equip with an understanding of what determines, encourages, and promotes m-shopping consumers, steps can be taken to meet the consumer's expectations and thereby increase the consumer and sales growth rate. However, researches addressing the consumer's perception of m-shopping sites are scarce. The main goal of this 1567-4223/$ - see front matter 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.elerap.2005.09.004 * Corresponding author. Tel.: +886 7 525 2000x4722; fax: +886 7 525 4799. E-mail addresses: tw (J.-H. Wu), ymwang@ ncnu.edu.tw (Y.-M. Wang). 1 Tel.: +886 49 2910960x4820; fax: +886 49 2915205. www.elsevier.com/locate/ecra Electronic Commerce Research and Applications 5 (2006) 192-200 paper is to identify consumer evaluative criteria for the selection of m-shopping sites in business to consumer (B2C) markets that are multidimensional nature. The list of consumer evaluative criteria proposed in this study would be valuable to researchers and practitioners interested in implementing and managing m-shopping sites. The remainder of the paper is organized as follows. Section 2 introduces the m-shopping background and briefly reviews prior related research, including the characteristics and scenario for m-shopping and criteria for the electronic store selection. Section 3 presents the initial criteria list for selecting m-shopping sites. Section 4 describes the research methodology and the sampling techniques adopted for this study. Section 5 analyzes and discusses the results. The last section suggests several implications in administrating mshopping sites and identifies future research directions that they suggest. 2. Background and literature review 2.1. Characteristics and scenario for m-shopping There are similarities and differences among physical shopping, web-based shopping (via a PC browser), and m-shopping (via a handset micro-browser). Shopping is a complex consumer behavior composed of rational choices, entertainment and social contacts. In a web-based shopping or m-shopping environment, the familiar layout of a physical store becomes a maze of pull-down menus, product indices, and search features [24]. Although mobile devices are limited in screen size, memory size, and user interaction compared with web-based commerce, the mobility, Net-access convenience, ubiquity, personalization, flexibility, and dissemination are the advantages of mobile devices [24]. Equipped with micro-browser and other mobile applications, the new range of mobile technologies offers the Internet ''in one's pocket''. For this, the consumer possibilities are endless, including banking, booking, buying tickets, shopping and real-time news [30]. As Barnes [1], and Varshney and Vetter [27] contended, a possible scenario for m-shopping is shown in Fig. 1. Using demographic information collected by mobile shops and information on the current location of mobile users, many targeted advertising and shopping information can be performed. For instance, advertising messages can be personalized based on information provided by consulting the users at an earlier stage or from the user's purchasing habit history. Messages sent to a user can also be location-sensitive and inform a user of various on-going specials in surrounding areas. Shopping messages can be sent to all users located within a certain area or sent independently to a user's current location. 2.2. Criteria for the electronic store selection Many researches have been conducted to identify the criteria that consumers may consider when selecting an electronic store (e-store). For instance, Jarvenpaa and Todd [9] reported four factors that consumers found salience as they browsed through selected electronic malls on the World Wide Web: product perceptions, shopping experience, customer service, and perceived consumer risk. Lee [12] pointed out that the spatial and temporal separation among consumers and marketers would increase fears of web retailer opportunism arising from product and identity uncertainty. Lohse and Spiller [14] offered six attribute categories that influenced e-store traffic and sales: merchandise, service, promotion, convenience, checkout, and navigation. In contrast to traditional consumer behavior, Pavlou and Stewart [19] argued that online transactions have some unique dimensions based on consumer-retailer exchange relationships, such as (a) the extensive use of technology for transactions, (b) the distant and impersonal nature of the online environment, and (c) the implicit uncertainty Fig. 1. Scenario for m-shopping. J.-H. Wu, Y.-M. Wang / Electronic Commerce Research and Applications 5 (2006) 192-200 193 of using an open technological infrastructure for transactions [20]. Wolfinbarger and Gilly [28] identified a number of factors that influenced consumer's e-store image: merchandise assortment, service policies, layout, and institutional factors (i.e., reputation). By analyzing physical retail stores, paper catalogs, and online outlets, Lim [13] concluded 16 attributes that were categorized into six factors for e-stores: merchandise, convenience, interactivity, reliability, promotions, and navigation. Research based on web-based environments emphasized the importance of the flow, information availability and display, customer demand, buyer decision support, interactivity, and graphic style in user interface [17,18,25]. Usability, including navigation, ease of use, search functions, overall site design and organization, and order processing were also examined [2,28]. Based on the foregoing review, shopping site selection in an electronic environment can be summarized into five dimensions: merchandise, service, promotion, convenience, and assurance as shown in Table 1. 3. Selection criteria for m-shopping sites A three-phased approach was used in constructing the selection criteria list: Phase 1. Develop an initial measure list by taking results from a literature review and examining m-shopping characteristics and then determining whether it was complete clear by using it in interviews of domain experts of mobile commerce applications. Revise the list accordingly and use it in a pilot test with 30 experienced mobile shoppers. As a result, the initial survey instrument was extensively revised. Phase 2. The new instrument was then tested via a survey. Some tests were conducted to purify the instrument. Exploratory factor analysis (EFA) was then performed to initially estimate the factor structure. Phase 3. A new data set was gathered. The factor structure derived from EFA was tested and modified using the new data set. 3.1. Initial consumer-oriented criteria development This study aims to identify consumer evaluative criteria for the selection of m-shopping sites in B2C markets. To ensure a comprehensive list of criteria was included, a broad range of previous studies from the marketing, physical shopping, web-based shopping, and m-commerce areas were reviewed [1,2,9,12-14,17-20,24,25,27,28]. An initial list of 35 items based on the five consumer criteria dimensions, as indicated in Table 1, were selected and reworded for the m-shopping environment. These included criteria such as a light screen presentation, providing personalized shopping-information, providing more decision support functions to shorten browsing time and uncertainty (e.g., comparing shopping information and a function for a product-information search, recommendation, etc.). A five point Likert-type scale was used to determine individual reactions to the items, where: 1, not important at all; 2, unimportant; 3, moderately; 4, important; and 5, extremely important. Once the initial list was generated, a review process by the domain experts from the mobile service providers (MSPs) was conducted to verify the completeness, wording, and appropriateness of the items and to verify the content validity. The domain experts included three marketing managers and six professionals on mobile commerce applications. First, we explained the research purpose to them. Then, they were asked to provide feedbacks and comments about the measure. The review process was followed by a pilot study that involved sending thirty questionnaires to mobile shoppers that were recommended by the four MSPs in Taiwan. Feedbacks from the pilot study served as the basis for correcting, refining and enhancing the items. Finally, 27 items remained, as shown in Table 2. Table 1 Consumers' shopping site selecting criteria Label Conceptual description Literature support Merchandise Merchandise is either goods or services offered by stores. The dimension includes items about product information, product characteristics, and price [9,13,17,14,28] Service Service is defined as the consumer support offered by stores. The dimension includes sale service for product selection, answers to questions, a feedback mechanism and so forth [9,14,17,25,28] Promotion Promotion is sales, advertising, and appetizer features that attract customers [1,13,14,27,28] Convenience Convenience is consumers' feelings of comfort, fitness, or advantage. The dimension includes easy navigation, friendly user interface, ease of ordering, and response time [2,9,13,14,17,18,24,25,28] Assurance Assurance involves reputation, security, reliability, and privacy [9,13,19,20,28] 194 J.-H. Wu, Y.-M. Wang / Electronic Commerce Research and Applications 5 (2006) 192-200 3.2. Purify measure Subjects for this study were users engaged in m-shopping in Taiwan. The Taiwan Government launched its National Mobile Infrastructure Project in 2002 and claimed that by year 2006 Taiwan would be a mobile island. However, currently, m-shopping in Taiwan is still in the early implementation stage. Only few well-known stores have actually implemented or partially implemented m-shopping. Due to the small amount of m-shopping samples, four main MSPs in Taiwan are good base to distribute questionnaires because they provide the mobile channel and have the transaction records. We endeavored to find a specific local contact person for each targeted MSP that was placed in charge of distributing the questionnaires and the follow-up activities. A questionnaire was mailed to 1100 random customers that possessed mobile phones with micro-browser features, via the marketing departments of four main MSPs in Taiwan. The respondents were asked to assess the importance each of item regarding to selecting an m-shopping site. We received 183 usable responses, for a response rate of 16.6%. We assessed potential non-response bias by comparing the early versus late respondents that were compared on several demographic characteristics as shown in Table 3. The results indicated that there are no statistically significant differences across early and late respondents. These suggested that non-response bias was not a serious concern. Prior to conducting formal data analysis, the internal consistency (a coefficient) was examined to ensure that the measures were unidimensional and to eliminate ''garbage items'' [3]. The results showed that the 27-item instrument had an acceptable reliability of 0.89. Correlations of each item with the sum of scores on all items were computed. Items were eliminated if their correlations with the sum of scores were less than 0.4 [3]. Thus, the item no. 12 was eliminated. The remaining 26 items had a reliability of 0.938. Bartlett's test of sphericity (p = 0.000) indicated that correlations among these items existed. A Kaiser-Meyer-Olkin measure of sampling adequacy yielded a score of 0.92, indicating high shared-variance and relatively low uniqueness. These test results suggested that factor analysis was worth pursuing. 3.3. Exploratory factor analysis EFA was used to validate the various constructs underlying the data set. The principal components and maximum likelihood methods with varimax rotation were used to examine the data. To derive a stable factor structure, two rules were applied to eliminate items: (1) loadings of less than 0.35 on all factors; and (2) loadings greater than 0.35 on two or more factors [23]. Three iterations yielded a stable set of three factors and left 11 items, as shown in Table 4. The first factor drew from items related to assurance. The second contained items related to the merchandise, such as providing products that I need, providing attractive products, providing a function for a productTable 2 Criteria for evaluation and selection of m-shopping sites Items Merchandise 1. It is important to provide products that I need 2. It is important to provide attractive products 3. It is important to provide branded products 4. It is important to provide accurate product information 6. It is important to provide a function for product-information search 7. It is important to provide a function for product preview 16. It is important to provide reasonable product-price Service 11. It is important to provide comparison information about shopping (e.g., comparisons of functions, features and prices among products) 14. It is important to provide on-line help functions (e.g., FAQ) 15. It is important to have a call center 26. It is important to provide good post-purchase service Promotion 5. It is important to provide instant and the latest product news 13. It is important to provide promotional activities Convenience 8. It is important to have an alluring screen presentation 9. It is important to have concise and light screen presentation 10. It is important to have a quick response time 12. It is important to provide personalized shopping-information 20. It is important to have multiple payment alternatives 25. It is important to provide a reasonable delivery time 27. It is important to provide order tracking and status query functions Assurance 17. It is important to have a legal business license 18. It is important to have a good reputation 19. It is important to have well-known popularity 21. It is important to be able to assure transaction security 22. It is important to have a commitment to privacy protection 23. It is important to have a flawed-product return guarantee 24. It is important to have a refund guarantee Table 3 Respondents profile and non-response bias analysis of exploratory survey (N = 183) Demographics Total (%) Early respondents (%) Late respondents (%) P-value Annual income (NT thousand dollars) 300 under 41.8 41.5 42.0 0.626 P300 and <500 39.0 35.4 42.0 p500 and <1000 17.0 20.7 14.0 p1000 2.2 2.4 2.0 gender male 44.0 46.3 0.557 female 56.0 53.7 58.0 age 20 under 1.1 0.0 0.275 p20 <29 47.3 44.6 49.5 p30 <39 42.3 41.0 43.4 p40 9.3 12.0 7.1 j.-h. wu, y.-m. wang> 0.85, RMR < 0.05, AGFI > 0.80, NFI > 0.80, NNFI > 0.80, and CFI and IFI approach 1 [6,7]. The value of CFI and IFI varies between zero and 1.0, with higher values indicating greater model parsimony. As shown in Table 6, the hypothesized model exhibits good levels of fit and thus provides a satisfactory representation of the underlying structure of the measure for mshopping site selection. 4.1.2. Assessment of reliability and validity The reliability and validity of the measurement model were assessed using several tests. On the first-order CFA measurement models, the standard factor loading of an observed variable (item) on its specified latent variable (factor) is the estimate of the observed variable validity. The larger the factor loading, compared with their standard error and expressed by the corresponding t value, the stronger the evidence that the measured variable (factor) represents the underlying construct [5]. In general, if the t values are greater than |1.96| or |2.576|, they are considered significant at the 0.05 and 0.01 levels, respectively [11]. Our examinations of the t values (Fig. 3) indicated that each item exceeded the critical value for the 0.01 significance level. That is, all items were significantly related to their specified constructs, verifying the posited relationships among items and factors. Table 4 Exploratory factor analysis results Items Factor 1 Factor 2 Factor 3 1 0.104 0.830 0.09 2 0.189 0.801 0.148 6 0.198 0.603 0.291 7 0.308 0.558 0.289 11 0.268 0.178 0.728 13 0.010 0.179 0.775 14 0.156 0.187 0.755 21 0.860 0.273 0.010 22 0.872 0.252 0.163 23 0.877 0.192 0.206 24 0.835 0.09 0.235 Eigenvalue 5.008 1.474 1.087 Proportion 45.526 13.404 9.883 Cumulative 45.523 58.930 68.813 a Coefficient 0.922 0.757 0.718 Table 5 Respondents profile of confirmatory survey (N = 180) Annual income (NT thousand dollars) Age 300 under 39.9% 20 under 3.3% P300 and <500 40.4% p20 and <29 42.1% p500 <1000 15.3% p30 <39 45.4% p1000 4.4% p40 9.3% gender male 48.6% female 51.4% 196 j.-h. wu, y.-m. wang>0.85 RMR 0.03 <0.05 AGFI 0.82 >0.80 NFI 0.89 >0.80 NNFI 0.89 >0.80 CFI 0.92 Approaching 1; higher values, IFI 0.92 higher goodness J.-H. Wu, Y.-M. Wang / Electronic Commerce Research and Applications 5 (2006) 192-200 197 the subjects. More specifically, the ''assurance'' factor scores (i.e., items 21, 22, 23, and 24) are higher than the ''merchandise'' and ''enabling function'' factor scores. Since m-shopping occurs at a distance via a limited screen interface rather than face-to-face, the shoppers may perceive that uncertainty, unsafety, and uneasiness are all higher than in the traditional shopping or electronic shopping context. This may imply that security, privacy, product return, and refund guarantees are the important issues for m-shopping site selection. As in electronic commerce [4,26], the ''assurance'' factor strongly influences the decision of whether to adopt m-shopping and select a mobile store. The ''merchandise'' and ''enabling function'' are also important factors to shoppers in choosing an m-shopping site because not all products that consumers need are available in an m-shopping site. This may cause un-satisfaction to the shoppers and suggest that the m-shopping site needs to provide and modify product portfolio to satisfy their buyers' tastes or needs. Further, the features of product description information and product preview are important in m-shopping because consumers cannot touch or feel products. The functions of product search, shopping information comparison, and on-line help in the m-shopping site can enable consumers to reduce search time and cost. These functions can help consumers find the products they seek effectively and efficiently. Promotion is another important issue to motivate site visits and sales to the shoppers, which may involve sales, advertising, and appetizer features that attract shoppers. Good promotion may not only attract customers to revisit but also increase the enjoyment of m-shopping. Fig. 3. Standardized parameter estimates and t-values for the hypothesized model. Table 7 Consumer-perceived importance on the m-shopping site selection Items 1 2 6 7 11 13 14 21 22 23 24 Mean 3.97 4.01 4.27 4.24 4.12 3.88 3.99 4.76 4.74 4.72 4.65 SD 0.92 0.86 0.74 0.76 0.87 0.88 0.86 0.53 0.54 0.57 0.63 198 J.-H. Wu, Y.-M. Wang / Electronic Commerce Research and Applications 5 (2006) 192-200 5. Conclusion and implications With the growing penetration of mobile device usage and the widespread adoption of the Net, stores need to investigate their customers' perceptions and fit their actual needs. This research presents an initial effort in developing a standard criteria list for selecting m-shopping sites from the consumer perspective. The three-factor consumer-oriented criteria further provide great insights for managing and developing m-shopping sites: M-shopping sites should provide the right products (that attract consumers and fit the consumer's needs) and promotion activity. M-shopping sites should provide functions that help consumers search, view, compare, and purchase merchandises easily and securely. M-shopping sites should provide refunds, flawed-product return guarantees and have a commitment to privacy protection. The findings have several implications for practitioners and researchers. Understanding the consumer is critical for successful management and development of m-shopping sites. The criteria list gives practitioners the insight they need to define what is extremely important to their customers. Once the researchers and practitioners know what is important, they can use the criteria list to compare each store's performance on those items. Comparing the m-shopping site with similar competitors' sites generates ideas about how to improve the store's design. Surveys help the practitioners identify which stores may need to improve so they can provide consumers with a better shopping experience. Results of statistical analysis help management decide how and where to better allocate store resources, such as training and technology. This research provides a better understanding of the design space in which the mobile stores operate. While this study has produced some interesting results, they should be interpreted with caution. Although the surveyed buyers represent a wide diversity of subjects, the sample total of 183 and 180 respondents may not be large enough to generalize the entire mobile shopper population. M-shopping is still in its infancy and rare relative to Internet and physical shopping. Thus, this instrument was developed and tested on a consumer sample that possessed mobile phones and had Internet access experience via mobile phones. This study provided a relatively small test of consumer involvement. The disproportionate sample size among the ages could also lower the significance of the study results. There are several directions for follow-up research. 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Q.No.1 Briefly explain Business to Consumer (B2C) in perspective of electronic Commerce (Only from assigned material).