Scielo RSS <![CDATA[Journal of theoretical and applied electronic commerce research]]> https://scielo.conicyt.cl/rss.php?pid=0718-187620200001&lang=pt vol. 15 num. 1 lang. pt <![CDATA[SciELO Logo]]> https://scielo.conicyt.cl/img/en/fbpelogp.gif https://scielo.conicyt.cl <![CDATA[Editorial: How Digital Innovators Achieve Customer Value]]> https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762020000100101&lng=pt&nrm=iso&tlng=pt <![CDATA[Mobile Payment: The Hiding Impact of Learning Costs on User Intentions]]> https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762020000100102&lng=pt&nrm=iso&tlng=pt Abstract: This study analyzes how learning costs for technologies that lack de facto standards, such as mobile payment, affect user intentions. In addition, we evaluate how the negative effect of learning costs is mediated by perceived functional value and facilitating conditions. Data used in this research was obtained from a study among 463 consumers. We find support that negative effects from learning costs are fully mediated by perceived functional value and facilitating conditions. Hence, one important reason of slow user acceptance is that the high diversity mobile payment services, platforms and technologies increases the learning costs of users. The results pose important implications for managers willing to increase the acceptance of mobile payment. <![CDATA[Factors in the Ecosystem of Mobile Payment Affecting its Use: From the Customers' Perspective in Taiwan]]> https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762020000100103&lng=pt&nrm=iso&tlng=pt Abstract: In comparison with the rapid adoption and growth of mobile technologies worldwide, mobile payment services are being adopted at a slower pace than expected. In the literature, most studies about customers’ use of mobile payment have focused mainly on the technological aspects. However, the businesses that provide mobile payment in terms of an ecosystem include various industries. This study integrated and empirically investigated the factors in multi-faceted nature of the mobile payment ecosystems, which influence customers’ acceptance and actual adoption. Although technological and social elements influence customers’ intention to use mobile payment for transactions, this study verified the important connection between cognition (intention to use) and behavior (actual usage). Service quality, service innovation, brand equity, switching costs, and public policy all impact the gap between intention and actual adoption of mobile payment. <![CDATA[Visual Communication and Consumer-Brand Relationship on Social Networking Sites - Uses & Gratifications Theory Perspective]]> https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762020000100104&lng=pt&nrm=iso&tlng=pt Abstract: In the present time of web-based social networking, visual communication assume a key job in business and public communication. Social networking with its astute features has the ability to pull in numerous to interface with others. Visual communication plays key role in engagement behavior on social media further adding to sales. The high quality visual improves visibility in Social Networking Sites and are being selected as organization’s key activity. Thus, the present study proposes a theoretical model of how visual communications through consumer engagement on corporate Social Networking Sites pages influences the consumer-brand relationship. Structural Equation Modelling has been used and validated the effect of visuals with informative, entertaining and remunerative content on consumer engagement further leading to consumer-brand relationship. Uses and Gratifications Theory has been adopted to study the behavioral response of the customers in relation to consumer engagement in social media context. This is a pioneering work to measure the mediation effect of consumer engagement to check the dominance of mediation (consumer engagement) over direct relationship between independent (visual contents) and dependent variable (consumer-brand relationship) on Facebook. In future similar study may be conducted in other social media platforms. <![CDATA[Grey Relational Classification of Consumers' Textual Evaluations in E-Commerce]]> https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762020000100105&lng=pt&nrm=iso&tlng=pt Abstract: Companies have gained important advantages by the development of electronic commerce. Consumer evaluations in electronic environment offer great possibilities for analysis. The fact that the consumer opinions are comprised of textual data, analyzes have complicated and challenging process. In recent years, it is seen that text mining methods are used in analyzes in the literature. However, the evaluations of consumers which are formed by short texts make it necessary to realize the analysis with insufficient data. The weighting methods such as Term Frequency and Term Frequency-Inverse Document Frequency as well as common used classification algorithms such as Na├»ve Bayes and Support Vector Machine have some inadequacies in short text analysis. In this study, a grey relational classification model based on Vector Space Model and Bag of Words has been developed. The model was first applied to the positive-negative categorization of the evaluations, then, applied to the classification of negative evaluations. It was determined that the accuracy level of the model is higher than the classification algorithms commonly used in short text. According to the results of the research, 9637 negative evaluations in 24479 consumer opinion were determined, and 50.4% of the negative evaluations were found to have the most problems related to product. <![CDATA[Exploring Consumers’ Buying Behavior in a Large Online Promotion Activity: The Role of Psychological Distance and Involvement]]> https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762020000100106&lng=pt&nrm=iso&tlng=pt Abstract: As a key marketing tool, online sales promotion has been widely used by online retailers to increase sales of products and brands. Most previous researches on online sales promotion have ignored the effect of consumers’ psychological factors and the heterogeneity of product and consumers. The purpose of this study is to examine the role of psychological distance and involvement on consumers’ buying behavior in large online promotion activities. The research model was examined using empirical analysis of data obtained from consumer surveys after the Double 11 promotion. Our results indicate that temporal distance has positive impact on purchase decision of high involvement products, while having negative impact on purchase decision of low involvement products. Social distance has negative impact on consumers’ purchase decision. Temporal distance is positively associated with consumers’ purchase-decision involvement, and then purchase-decision involvement positively impacts consumers’ total consumption. Social distance has no impact on consumers’ purchase decision involvement. These findings not only advance the understanding of the role of psychological distance and involvement in online sales promotion but also offer implications regarding strategies that online retailers can employ to publish their promotions at different times and encourage consumers more to share promotional information among their friends. <![CDATA[Detection of Auction Fraud in Commercial Sites]]> https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762020000100107&lng=pt&nrm=iso&tlng=pt Abstract: Online auctions have become one of the most convenient ways to commit fraud due to a large amount of money being traded every day. Shill bidding is the predominant form of auction fraud, and it is also the most difficult to detect because it so closely resembles normal bidding behavior. Furthermore, shill bidding does not leave behind any apparent evidence, and it is relatively easy to use to cheat innocent buyers. Our goal is to develop a classification model that is capable of efficiently differentiating between legitimate bidders and shill bidders. For our study, we employ an actual training dataset, but the data are unlabeled. First, we properly label the shill bidding samples by combining a robust hierarchical clustering technique and a semi-automated labeling approach. Since shill bidding datasets are imbalanced, we assess advanced over-sampling, under-sampling and hybrid-sampling methods and compare their performances based on several classification algorithms. The optimal shill bidding classifier displays high detection and low misclassification rates of fraudulent activities. <![CDATA[How to Boost your App Store Rating? An Empirical Assessment of Ratings for Mobile Banking Apps]]> https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-18762020000100108&lng=pt&nrm=iso&tlng=pt Abstract: Smartphones have become the colossal point of attention for both individuals and businesses worldwide resulting into a whole level of new and innovative experience in mobile computing. Mobile applications (mobile app) is an upshot of such innovative mobile computing and produces a noticeable change in the way humans feel and experience. Each and every mobile app has a rating attached to it on App store, which measures the overall feedback of users for a particular mobile app. The present research develops a theoretical research model as a framework to identify the key decision factors influencing Indian users to rate mobile banking apps. A mix method approach consisting of qualitative interviews and a self-administered survey was used to gather information from 343 respondents in Delhi, India. The empirical analysis identifies and ranks six important decision factors: login time, visual design, navigational design, information design, collaboration and service quality, influencing the ratings of a mobile app. This study is one of the very few that has attempted to investigate the relationship between mobile app attributes and user ratings for retail banks and for providing new insights into mobile app attributes of retail banks and their effects on user ratings.