Journal of Theoretical and Applied Electronic Commerce Research

In today’s world, crowdsourcing is regarded as an effective strategy to deal with a high volume of small issues whose solutions can have their own complexities in systems. Moreover, requesters are currently providing hundreds of thousands of tasks in online job markets and workers need to perform these tasks to earn money. Thus far, various aspects of crowdsourcing including budget management, mechanism design for price management, forcing workers to behave truthfully in bidding prices, or maximized gains of crowdsourcing have been considered in different studies. One of the main existing challenges in crowdsourcing is how to ensure truthful reporting is provided by contributing workers. Since the amount of pay to workers is directly correlated with the number of tasks performed by them over a period of time, it can be predicted that strong incentives encourage them to carry out more tasks by giving untruthful answers (providing the first possible answer without examining it) in order to increase the amount of pay. However, crowdsourcing requesters need to obtain truthful reporting as an output of tasks assigned to workers. In this study, a mechanism was developed whose implementation in crowdsourcing could ensure truthful reporting by workers. The mechanism provided in this study was evaluated as more budget feasible and it was also fairer for requesters and workers due to its well-defined procedure. Full article

Drawing on expectation disconfirmation theory, this study explores the dyadic nature of omni-channel consistency on customer experience. Specifically, we propose a conceptual model that focuses on a brand’s offline channel customer experience relative to that of its online channel, and test the influences of customer experience (in)consistency on customer satisfaction, which then improves repurchase intention and word-of-mouth. The results of polynomial regressions on 265 survey respondents indicate that given omni-channel customer experience inconsistency, customers prefer consistent online and offline experiences. For omni-channel consistency at lower levels of customer experience quality, customers prefer consistency at higher levels of quality. For omni-channel inconsistency where offline customer experience quality is lower than that online, customers prefer omni-channel inconsistency, where offline customer experience quality is higher than that online. These findings produce not only theoretical contributions but also insightful suggestions for how customer experience can be taken into consideration in the promotion of a brand’s omni-channel service success. Full article

The vigorous development of e-commerce has led to online retailers or platforms increasing the capacity of online shopping carts. A large number of products are added to the online shopping cart, but they are not “emptied.” The resulting behavior of products being stuck in the shopping cart is called the “shopping cart abandonment behavior.” Previous literature has focused on the large number of antecedent variables that affect shopping cart abandonment behavior in the pre-decision stage of online shopping. This previous research has studied how to reduce shopping cart abandonment behavior from the perspective of consumers. By focusing on the post-decision-making stage of shopping, this research proposes to sort the products in a chronological order (ascending and descending order) after the products are added to the shopping cart and reduce shopping cart abandonment behavior through the intermediary of forgetfulness and choice overload. We use an exploratory study and two laboratory experiments to reveal the above intermediary mechanism. Our results show that online shopping cart abandonment generally occurs in shopping carts on all major platforms. Forgetting and shopping cart page rendering may be the reasons that lead to shopping cart abandonment behavior. In the case of targeted tasks, ascending order has a significant impact on abandonment behavior, choice overload mediated this effect. Full article

This study examined social media’s role in various levels of research, development, and performance within enterprises in Kuwait. The research incorporated four inductive case analyses in various sectors. The case studies epitomize the supply chain of Kuwaiti enterprises, including small and medium-sized enterprises (SMEs). Media richness theory and social exchange effectuation theory were utilized to create an effective theory and a theoretical framework. This study collected data via a questionnaire completed by 100 managers employed by Kuwaiti SMEs specialized in the food sector and interviews with eight managers. Numerical data were analyzed via SPSS software, while textual data were analyzed by applying thematic analysis. The results of this study suggest that Kuwaiti companies should adopt social media platforms and other novel, innovative outlets to publicize their organizations and maximize performance. Social media richness and openness tend to determine the supplier selection process in most Kuwaiti enterprises, leading to positive transactional and social impacts on entrepreneurship. Full article

Retailers have little control over what their customers say about their products and services online. Review platforms (e.g., Yelp and Travelocity) are rife with negativity, from both real customers with bad experiences and from fake reviews created by competitors. These negative reviews have been shown to influence the purchasing behavior of future consumers. Many platforms do afford companies some control by including them in the online conversation about their products or services. Crafting a response to a poor review which appeals to future consumers may mitigate some of the negative outcomes associated with that review. This study advances our knowledge of responding to negative reviews by adding to the growing body of research, using a simulation-based experiment to test the influence of three elements of a review response on purchase intention (i.e., an apology, an explanation and a pledge to correct the problem identified in the review). In doing so, the data show that purchase intention increases only when a response contains all three elements. Implications for e-commerce researchers and review platform developers are discussed. Full article

The startup business ecosystem in India has experienced exponential growth. The amount of investment in Indian startups in the last decade demonstrates the strong interest of the technology industry to these business models based on innovation. In this context, the present study aims to identify investment opportunities for investors in Indian startups by identifying key indicators that characterize the startup ecosystem in India. To this end, a three steps data mining method is developed using data mining techniques. First, a sentiment analysis (SA), a machine learning approach that classifies the topics into groups expressing feelings, is applied to a dataset. Next, we develop a Latent Dirichlet Allocation (LDA) model, a topic-modeling technique that divides the sample of n = 14.531 tweets from Twitter into topics, using user-generated content (UGC) as data. Finally, in order to identify the characteristics of each topic we apply textual analysis (TA) to identify key indicators. The originality of the present study lies in the methodological process used for data analysis. Our results also contribute to the literature on startups. The results demonstrate that the Indian startup ecosystem is influenced by areas such as fintech, innovation, crowdfunding, hardware, funds, competition, artificial intelligence, augmented reality and electronic commerce. Of note, in view of the exploratory approach of the present study, the results and implications should be taken as descriptive, rather than determining for future investments in the Indian startup ecosystem. Full article

This study investigated the effect of perceived technology quality and personalization quality on behavioral intentions, mediated by perceived empathy in using an artificial intelligence (AI) recommendation service. The study was based on a theoretical model of artificial intelligent device use acceptance. We also tested the moderating effect of individuals’ need for cognition, influencing empathy. Data collection was conducted through an online survey using a nationally recognized consumer research panel service in Korea. The participants were asked to respond to their preferences and needs on sneakers; then, they randomly experienced the AI (versus human expert) recommendation service that offers a recommended product. A total of 200 data were analyzed using SPSS 21.0 for descriptive statistics, reliability analysis, and PROCESS analysis, and AMOS 21.0 for confirmatory factor analysis and structural equation modeling (SEM). Results revealed that, compared with the human (expert) recommendation service, the AI recommendation service increased perceived technology quality, which increased personalization quality. Technology and personalization quality had a positive influence on behavioral intentions, mediated by perceived empathy. In addition, when individuals had a high level of need for cognition, the effect of personalization quality on empathy was stronger. However, individuals with a low level of need for cognition perceived greater empathy, as technology quality increased. The findings of the current study improve understanding of how consumers accept AI technology-driven services in the online shopping context. Full article

FinTech platforms are one of the most important elements in the rapidly digitized world’s economy. This study investigates the factors that affected individuals’ acceptance of FinTech services, especially on internet wealth management platforms. The current research extends the unified theory of acceptance and use of technology (UTAUT) published by MIS Quarterly with integrated financial consumption attributes (i.e., perceived value and perceived risk) alongside the core construct of UTAUT. Data were collected from an established survey company. The empirical results indicate that perceived value, perceived risk, and social influence are strongly related to individuals’ FinTech adoption intention, whereas performance expectancy, effort expectancy, and perceived risk affect individuals’ perceived value, which in turn influences adoption intention. The proposed FinTech adoption model could contribute to information technology (IT) adoption research by extending the UTAUT in which individuals’ performance expectancy and effort expectancy affect their adoption intention indirectly through perceived value. Finally, the implications of the proposed new model for future research and FinTech practice are discussed. Full article

High-tech internationalization touches on two aspects impacting entrepreneurship: openness of the economy and its level of innovativeness. Both of them might positively or negatively affect the process of new company creations, as suggested by the concept of entrepreneurial regime with creative destruction or by the concept of routinized regime with creative accumulation. The aim of the article is to assess the impact of high-tech internationalization on the start-up process of new company creation. Cluster analysis and panel modeling for European Union countries in 2009–2018 were conducted. The research results distinguish clusters of European Union countries with a different level of high-tech internationalization. The impact of high-tech internationalization on start-up rates is significant in the case of both clusters; however, it is stronger in the cluster of countries with a relatively higher level of high-tech international openness. The high-tech intra-EU import and extra-EU high-tech export negatively affect the rate of new enterprise creation in both clusters. Additionally, extra-EU import in clusters with a relatively higher level of high-tech internationalization also negatively impacts start-up rates. The only aspect supporting the start-up process is the level of intra-EU export in clusters with higher levels of high-tech internationalization. The results suggest that in European Union countries, creative accumulation is the dominant phenomenon. Full article

Web 2.0 technology enables customers to share electronic word of mouth (eWOM) about their experiences. eWOM offers great market insights to the organization, and important for organization’s success. eWOM monitoring and management is one of the major contemporary challenges for the organization, because of high volume and frequency of the content. It is nearly impossible for an organization to manually monitor content generated by each user. In this paper, we propose sentiment analysis as an alternative method for analysis of emotions and behavioral intentions in real-time data. Sentiment analysis is performed on women’s e-clothing reviews collected from the Kaggle data repository. The dataset consists of 23,486 reviews, comprising ten feature variables. This study applied artificial neural network techniques to determine polarity of the data in terms of positive or negative. Sentiment analysis was performed by using two artificial neural networks, Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM), to classify the review as recommended (positive) or not recommended (negative). The proposed models have been evaluated on these performance measuring parameters: accuracy, recall, specificity, F1-score and roc-curve. The LSTM method outperformed CNN and achieved classification accuracy of 91.69%, specificity 92.81%, sensitivity 76.95%, and 56.67% F1-score. Based on results of this study, LSTM technique is highly recommended for the sentiment analysis of unstructured text-based user-generated content. Full article

Financial innovation and advances in payment systems are important not only to boost remittances but also to foster the successful development of electronic businesses around the world. As such, many leading companies in electronic commerce are putting a great deal of effort into the development of their payment system to attract more users and compete with other leading companies in the market. WeChat is a social communication tool that introduced a payment function widely adopted as a third-party payment in China nowadays. The purpose of this study was to adopt WeChat as a case study to identify the influential factors that impact consumers’ intention to adopt it as digital payment. We identified several core influential factors including service quality, perceived risk, perceived security, perceived ease of use, social influence, compatibility, and age. Qualitative and quantitative analyses were performed to investigate how influential factors affect the adoption of this third-party digital payment platform. The results revealed that all identified factors have a significant influence on consumer’s intention to use digital payment, except age. This study also provided useful advice for digital payment improvement and recommendations to enhance digital payment for the success of electronic business operations. The paper provides new insight into the factors influencing consumers’ intention to use mobile digital payment. Full article

This study was set out to chiefly examine the influence of psychological traits—need of achievement (“N of Ach”) and risk-taking propensity (RTP)—on perceived usefulness (PUF) and perceived ease of use (PercEU), as well as their effects on the intention to use e-commerce among rural micro-entrepreneurs. This study exploited the psychological traits theories and the technology acceptance model (TAM) by utilizing samples represented by rural micro-entrepreneurs. The results of the study found that the N of Ach and RTP significantly influence PUF and PercEU. The two original TAM constructs and PercEU have significant relationships with PUF and intention. At the same time, it was also found that there exists a significant relationship between PUF and intention. This study therefore serves to fill the gaps where N of Ach and RTP of rural micro-entrepreneurs are seldom tested to examine the effects of perceptions of benefits and ease of use on the adoption of e-commerce. On top of that, this study provides vital input to policy makers and stakeholders of rural development in their efforts to increase the adoption of e-commerce among rural micro-entrepreneurs. Full article

The concept of value co-creation brings about changes in tourists’ roles from value receivers to producers. Most existing studies take value co-creation behavior as a single dimension, ignoring the role switching of tourists. Starting from the precise constitution of value co-creation behavior, this paper, utilizing the method of structural equation modeling (SEM), discusses the mechanism of the effects of tourist participation behavior and citizenship behavior on destination loyalty through each sub-dimension of perceived value. The results showed the following: (1) The participation behavior (in-role) and citizenship behavior (extra-role) of tourists affect different value dimensions. (2) The value co-created by tourists presents a hierarchical state from the primary to the higher level. Among the types of value, novelty and social value belong to the primary level while quality, economic, knowledge, and emotional value belong to the higher level. (3) Destination loyalty is driven not only by tourist behavior (in-role) but also by citizenship behavior (extra-role). Based on the perspective of role switching, this paper establishes the theoretical framework of role switching in the era of value co-creation and proposes some strategic suggestions for marketing transformation. Full article

Recently, the showroom model has developed fast for allowing consumers to evaluate a product offline and then buy it online. This paper aims at exploring the optimal information acquisition strategy and its incentive contracts in an e-commerce supply chain with two competing e-tailers and an offline showroom. Based on signaling game theory, we build a mathematical model by considering the impact of experience service and competition intensity on consumers’ demand. We find that, on the one hand, information acquisition promotes supply chain members to obtain demand information directly or indirectly, which leads to forecast revenue. On the other hand, information acquisition promotes supply chain members to distort optimal decisions, which results in signal cost. The optimal information acquisition strategy depends on the joint impact of forecast revenue, signal cost and demand forecast cost. Notably, in some conditions, the offline showroom will not acquire demand information even when its cost is equal to zero. We also design two different information acquisition incentive contracts to obtain Pareto improvement for all supply chain members. Full article

With the explosive growth of information and the increase of people’s fragmented time, the knowledge payment industry’s market size is growing. However, the heterogeneity between online knowledge payment behavior and traditional consumption gradually comes to the fore. It is of great practical significance to analyze the factors influencing users’ online knowledge payment behavior and clarify users’ online knowledge payment mechanism. Based on UTAUT theory, this study uses statistics, structural equation modeling, and mediating effect analysis to construct a theoretical model of the influencing factors of users’ payment behavior of knowledge payment platform from the user level, knowledge-provider level, and platform level. The findings show that content quality, peer influence, KOL influence, perceived interaction, effort expectation, and perceived trust significantly affect users’ willingness-to-pay and have an indirect effect on users’ paying behavior through their willingness-to-pay. Perceived cost, perceived interaction, content quality, peer influence, performance expectation, and effort expectation directly and significantly affect user paying behavior. By regulating the above elements, the improvement of customer attraction ability of online knowledge platforms can be realized. Full article

In recent years, the study of online consumption behavior has gradually formed its research system and analysis model based on the inheritance of traditional research paradigms, focusing on the inner mechanism of consumption models explained by consumption activities. Online consumption is based on the research scenario of social e-commerce and forms a broad research network through the extension of consumer objects, consumer psychology, and consumer concepts. Although the theoretical constructs of online consumer behavior continue to improve, the relevant studies still do not fully grasp the research frontiers due to the lagging research nature. In the context of Web 2.0, it is impossible to run through the latest developments in online consumption research. Moreover, the study of online consumer behavior has shown a trend of diversification and multiple schools of thought, and a research jungle has emerged, which in essence is the perfection and new height of the study of consumerism. This paper analyses the origins, frontiers, and prospects of online consumer behavior research to clarify the formation principles, development paths, and future directions of the online consumer behavior research jungle. Ultimately based on the economic changes in the post-pandemic context, this paper integrates and proposes an evolving mechanism for studying online consumption behavior, intending to achieve a peek into and reveal the jungle of online consumption research. Full article

In online purchasing, customers may return products due to dissatisfaction with the quality of the product, and receive a refund based on the return policy, which is determined by online distributors. Online distributors can offer generous policies to attract more customers, but at the cost of reducing total profits. In this paper, the effect of the pricing and quality of complementary products (products sold together with other items) in online selling under the return policy is investigated. For this purpose, a mathematical model is developed to obtain optimal values for selling price, refund amount, and quality of products. Based on analytical results, a solution algorithm is proposed to solve the numerical examples and perform sensitivity analysis. Findings reveal that, while increasing the sensitivity of demand with respect to the refund amount, the price, quality, and refund on returned products should be increased. In addition, the online distributor should increase the quality of products when customers are more sensitive to the quality of products. Among other results, the selling price is shown to be negatively affected by demand elasticity with respect to price. In this situation, the online distributor should reduce the quality level and the refund amount for returned products to avoid a sharp decline in profit. In addition, when the quality cost is high, the price and quality should be decreased and the refund amount unchanged. Full article

The spread of social networks and the high level of penetration of digital content and mobile devices have created a society in which consumers expect constant communication from companies. In addition, communication on social media is often accompanied by the hope of being able to interact on an equal footing. In this way, companies hope that the use of social networks will not only increase sales, but also increase attention, brand page traffic, and customer loyalty. The purpose of this study was to provide the grounds for identifying the correlations between the interactive potential of social media based on dialogue-oriented communication and the quality of relationships with online customers. To achieve this goal, an online questionnaire was used in which 604 respondents from Romania participated (204 social media managers and 400 online customers). The results of the study showed that it is particularly important for companies to understand the role of interactive communication in social media and to thus build a bridge between the orientation of communication towards dialogue and relationships with online customers. It was found that the correct use of social networks could also support the achievement of public relation (PR) objectives. In addition, this study has implications for the development of customer-oriented online communication strategies by Romanian companies. Full article

To maintain the sustainable development of a platform’s economy, e-commerce platforms put forward various subsidy programs to retailers selling on them during COVID-19. This paper investigates an e-commerce platform’s decision on subsidizing a retailer selling on it with logistics constraints during an epidemic scenario, with a focus on the role of power structure and altruistic preference. By constructing two Stackelberg game models, the research obtains the optimal subsidy under two power structures (i.e., the dominant platform and the weaker platform), respectively. The comparison between them shows that the conditions of the dominant platform giving subsidies (both altruistic preference and logistics constraints should be higher enough) are stricter than the weaker platform. Considering the same altruistic preference and logistics constraints, the optimal subsidy provided by the weaker platform should always be not less than the dominant platform. However, the weaker platform, surprisingly, can get more utility by lowering its altruistic preference voluntarily when the commission fee is low. No matter what the power structure is, the optimal subsidy increases with the logistics service coefficient and altruistic preference, and the dominant member’s profit/utility is not less than the weaker one, which confirms “the first mover advantage”. Finally, more managerial implications to the platform-retailer systems are discussed. Full article