Purpose - This study reestablished the concept of mixed emotions experienced in online and offline shopping environments, and structuralized emotional responses which manifest mixed emotions in each channel, and developed a method of measuring overall mixed emotions in consideration of the asymmetry of emotions. Design/methodology/approach - This study conducted a focus in-depth interview based on phenomenological research and exploratory preliminary survey using questionnaires. In addition, a survey was conducted as a quantitative survey. Findings - Qualitative and quantitative researches were conducted to derive major emotional responses items which manifest mixed emotions in online and offline shopping environments and determine differential emotional structure in each channel. As a result, it was confirmed that mixed emotions consisted of 5 factors in each channel and 21 emotional responses. In addition, a method of measuring overall mixed emotions considering the asymmetric of emotions was developed to prove the difference in behavioral responses. Research implications or Originality - This study is meaningful in that it helps companies efficiently manage and understand customer responses to their products by classifying and systemizing the emotional responses experienced by consumers in online and offline purchase and consumption situations according to the purchase environment.
Purchasing through Internet shopping mall has more uncertainty compared with offline shopping mall. Previous studies have presented that trust plays a role of reducing uncertainty and increasing purchasing intention. In this study, we suggest that third-party assurance and word-of-mouth contribute to the formation of trust. In addition, we also propose that ease of product evaluation plays moderating roles in the relationships between third-party assurance, word-of-mouth and trust. For this study, we collected sample data from two groups consisting of online shoppers purchasing the search goods and experience goods categorized by type of ease of product evaluation. Empirical results show that word-of-mouth and third-party assurance have different effects on trust in two groups. The third-party assurance has a stronger impact on trust in online shopping group of the search goods than in the experience goods, while word-of-mouth in the online community has a stronger impact on trust in online shopping group of the experience goods than in the search goods. We expect that this result will provide researchers and managers who are interested in trust formation factors in online shopping mall with useful theoretical and practical implications.
Journal of the Korean Society of Clothing and Textiles
/
v.35
no.6
/
pp.659-669
/
2011
Consumer responses to 3D online shopping malls are influenced by their attitudes toward technology. This study examines the consumer differentiation according to technology readiness, compares customers with different technology readiness in terms of their perceived telepresence and e-loyalty, and examines the effect of their perceived telepresence on their e-loyalty. Samples from 300 females aged 21 to 39 were used for the final analysis. The results are as follows. First, consumers were classified into three groups, Explorers (N=72), Pioneers (N=105), and Skeptics (N=123), through factor analysis and k-means cluster analysis. Second, the Explorers evaluated the telepresence of the 3D online shopping mall higher than any other group. The Skeptics presented lower e-loyalty and perceived less telepresence in the 3D online shopping mall than the other two groups. Finally, telepresence had a significant influence on e-loyalty, as identified by the regression analysis. This verifies the effectiveness of 3D technology adopted or to be adopted by online shopping malls and demonstrates that 3D shopping malls can be a strategic alternative in the online shopping sector where competition is fierce. The results show that online shopping malls should focus on establishing 3D shopping environments with further effort to utilize the technology.
Recently, the proliferation of mobile devices such as smartphones and tablet personal computers and the development of information communication technologies (ICT) have led to a big trend of a shift from single-channel shopping to multi-channel shopping. With the emergence of a "smart" group of consumers who want to shop in more reasonable and convenient ways, the boundaries apparently dividing online and offline shopping have collapsed and blurred more than ever before. Thus, there is now fierce competition between online and offline channels. Ever since the emergence of online shopping, a major type of multi-channel shopping has been "showrooming," where consumers visit offline stores to examine products before buying them online. However, because of the growing use of smart devices and the counterattack of offline retailers represented by omni-channel marketing strategies, one of the latest huge trends of shopping is "webrooming," where consumers visit online stores to examine products before buying them offline. This has become a threat to online retailers. In this situation, although it is very important to examine the influencing factors for switching from online shopping to webrooming, most prior studies have mainly focused on a single- or multi-channel shopping pattern. Therefore, this study thoroughly investigated the influencing factors on customers switching from online shopping to webrooming in terms of both the "search" and "purchase" processes through the application of a push-pull-mooring (PPM) framework. In order to test the research model, 280 individual samples were gathered from undergraduate and graduate students who had actual experience with webrooming. The results of the structural equation model (SEM) test revealed that the "pull" effect is strongest on the webrooming intention rather than the "push" or "mooring" effects. This proves a significant relationship between "attractiveness of webrooming" and "webrooming intention." In addition, the results showed that both the "perceived risk of online search" and "perceived risk of online purchase" significantly affect "distrust of online shopping." Similarly, both "perceived benefit of multi-channel search" and "perceived benefit of offline purchase" were found to have significant effects on "attractiveness of webrooming" were also found. Furthermore, the results indicated that "online purchase habit" is the only influencing factor that leads to "online shopping lock-in." The theoretical implications of the study are as follows. First, by examining the multi-channel shopping phenomenon from the perspective of "shopping switching" from online shopping to webrooming, this study complements the limits of the "channel switching" perspective, represented by multi-channel freeriding studies that merely focused on customers' channel switching behaviors from one to another. While extant studies with a channel switching perspective have focused on only one type of multi-channel shopping, where consumers just move from one particular channel to different channels, a study with a shopping switching perspective has the advantage of comprehensively investigating how consumers choose and navigate among diverse types of single- or multi-channel shopping alternatives. In this study, only limited shopping switching behavior from online shopping to webrooming was examined; however, the results should explain various phenomena in a more comprehensive manner from the perspective of shopping switching. Second, this study extends the scope of application of the push-pull-mooring framework, which is quite commonly used in marketing research to explain consumers' product switching behaviors. Through the application of this framework, it is hoped that more diverse shopping switching behaviors can be examined in future research. This study can serve a stepping stone for future studies. One of the most important practical implications of the study is that it may help single- and multi-channel retailers develop more specific customer strategies by revealing the influencing factors of webrooming intention from online shopping. For example, online single-channel retailers can ease the distrust of online shopping to prevent consumers from churning by reducing the perceived risk in terms of online search and purchase. On the other hand, offline retailers can develop specific strategies to increase the attractiveness of webrooming by letting customers perceive the benefits of multi-channel search or offline purchase. Although this study focused only on customers switching from online shopping to webrooming, the results can be expanded to various types of shopping switching behaviors embedded in single- and multi-channel shopping environments, such as showrooming and mobile shopping.
The purpose of this study was to examine the effect of interactivity on consumers' mental imagery, attitude toward a product, confidence in evaluation and purchase intention. The proposed model was examined by conducting an experiment using mock apparel websites. A total of 1,009 female college students enrolled at a major midwestern university in the USA participated in the experiment. A structural equation model was used to test the model. The results of the study indicate that interactivity positively influenced mental imagery, attitudes toward a product imagery, and confidence in evaluation. The structural equation model also revealed that mental imagery positively influenced attitude toward a product and confidence in evaluation. Finally, the results show that attitude toward a product and confidence in judgment positively affected purchase intention. The study provides valuable theoretical perspectives which aide in the understanding of the effect of interactivity on consumers' cognitive and behavioral responses, and helps retailers develop effective marketing strategies.
This paper investigates the value of the expectation-confirmation model(ECM) of IT continuance in the internet shopping environments and attempts to expand the ECM with consideration of users diverse internet shopping factors and their preferences. Here, the extended ECM measures the users expectation-confirmation separately at the product, site and service levels, rather than treating it a single construct as measured in the original model. Further, AHP has been used for assessing the relative importance among the shopping factors, and the priority has been used for deriving weighted expectation-confirmation levels in the model. PLS analysis shows that there are significant differences in path coefficients between the ECM and a weighted ECM. This Indicates that users preferences among the diverse shopping factors need to be properly assessed to better understand the relationship between users expectation-confirmation and their continued usage behavior.
This paper seeks to suggest user satisfaction model of digital signage to see how new in-store technology can effectively lead to customers' shopping satisfaction in fashion retails. Authors in particular focus on technological complexity, which is expected to serve a subtle role in using digital signage. This study employed a scenario-based online survey. Interactive digital signage with virtual try-on and video-captures functions was used as stimuli. Data were collected from 320 respondents and 307 useable responses were analyzed to examine a proposed model. Research model compares dual paths of motivators: the extrinsic motivation route that leads from usefulness to shopping outcome satisfaction and intrinsic motivation route that leads from enjoyment to shopping process satisfaction. Technological complexity of digital signage indirectly and negatively influences shopping outcome and process satisfaction, mediated by usefulness and enjoyment, but directly and positively affects shopping process satisfaction. In omni-channel environments, the findings have implications for fashion retail managers in using digital signage to maximize customer satisfaction and to counterbalance the advantages and disadvantages of technological complexity.
While e-commerce market(B2C) grows rapidly, many experts argue that EC(B2C) transactions have not reached its full potential. A notable difference between online and offline consumer markets that is suppressing the growth of EC(B2C) is the decreased presence of human and social elements in the online shopping environments. Generally online shopping lacks human warmth and sociability. In this study, social presence in online shopping mall was proposed as a substitute for face-to-face social interaction in the traditional commerce and author explored what variables affect social presence(human warmth and sociability) on online shopping malls and how human warmth and sociability can influence on online store loyalty. To achieve research objectives, we reviewed literatures related with marketing, psychology and communication research areas. Based on literature review, we proposed a research model on the online shopping mall. To examine the proposed research model, we gathered data by using a self-report questionnaire. Respondents consists of online shoppers with at least five or more times of purchase experience in online shopping malls. Because social presence is a feeling which needs frequent contacts with malls to experience, respondents must have enough purchase experiences. The empirical results are as follows : First, shopping mall's customization efforts influence perceived social presence on the mall significantly. Second, shopping mall's responsiveness influences perceived social presence significantly. Third, perceived activity of community of online shopping mall influences perceived social presence significantly. Mall managers have to activate their customer community to reinforce social presence, resulting in trust building. Finally, perceived social presence influences trust and enjoyment on the mall significantly. And then trust and enjoyment on the mall affect store loyalty significantly. From these findings it can be inferred that perceived social presence appears determinant which is critical to the formation of core variables(trust and loyalty) in existing online shopping papers.
Journal of Information Technology Applications and Management
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v.16
no.1
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pp.51-75
/
2009
This paper develops an integrative model for IT continuance in the internet shopping environments by integrating the expectation-confirmation and the switching cost factors. Using this model, in addition, this study investigates their differential effects on the mediating variables, such as user satisfaction, commitment, and trust which have been identified as antecedents of users' IT continuance intention. Results show that the product and service-related expectation confirmation factors and the relational switching cost factor can have greater impacts on users continuance intention than the web site design factors, and the financial and procedural switching cost factors. In particular, it is interesting to note that relational switching cost can lead users to more commitment, which is revealed as the strongest antecedent of their continuance intention to use a certain shopping site.
In order to buy products through the Internet, consumers dissipate much time and efforts in collecting and comparing product information from various online shopping malls. Consumers can save their efforts by using price comparison sites, but there are some shortcomings in comparison shopping. Firstly, comparison sites do not show the lowest price of some products that are selling in shopping malls. Secondly, the product information provided by comparison sites is sometimes wrong. Thirdly, there are too many results. In order to overcome the shortcomings, we suggested a comparison shopping system based on RSS by using ontology matching. We used the current RSS standard for syntactic interoperability instead of suggesting new standards. Moreover, we used ontology matching for semantic interoperability to compare product information with different ontologies. The suggested ontology matching consists of three steps. The first step is finding exact sense from WordNet for a given product category, and the second step is searching for matching product category candidates from the products of RSS feeds. The final step is calculating similarities of the candidates with the target product category. From the experiments, we could get better recall rates that are suitable for e-commerce environments and the results show that our system is effective in product comparison.
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