Electronic Commerce Research and Applications最新文献

This study investigates the impact of macro-level dynamics, such as the COVID-19 pandemic, on customer point-usage behavior in e-commerce, focusing on how global crises alter consumer spending and loyalty program engagement. Using big data from SPK, an F&B holding company, and employing binary logit and panel regression models, this study highlights significant shifts in post-pandemic customer behavior. The findings reveal that both customers with low and high usage levels decreased their spending, transaction frequency, and point accumulation. However, the former showed an increased propensity to use points for purchases, with heightened redemption rates and average points used per transaction, whereas the latter exhibited a decline in these areas. These results underscore the importance of understanding customer-specific responses to economic crises for designing effective loyalty program strategies in e-commerce, and offer valuable insights for the development of promotional strategies and theories in this domain.

Online car-hailing service is practicing the concept of sharing, bringing new energy and convenience to the transportation market. However, with its rapid development, service issues have become increasingly prominent, and improving service quality is the key to the sustainable growth of the online ride-hailing industry. Microblog, as a major online platform for gathering public views, have become one of the significant media for publishing and disseminating information nowadays, which also contains numerous views of online taxi users on online taxi services. Aiming at the deficiency of online car-hailing service under microblog public opinion, this paper integrates Service Profit Chain (SPC) and Process Chain Network (PCN) from the perspective of service management. Firstly, a crawler program is used to collect the Internet Word of Mouth data related to online taxi. Then, a BERT text classification model is constructed to roughly classify the data, and the accuracy of this model is tested to 94.54 %. Afterwards, layer segmentation is implemented based on SPC and CatBoost. Besides, a series of problems in the current online taxi service, such as poor attitude of drivers, unsafe driving, and inefficient communication with the customer service staff, have been identified by using sentiment analysis and frequent mining methods. Finally, PCN analysis is used to optimize the online taxi service, proposing strategies such as setting a reservation reminder function, building a dynamic feedback mechanism, and establishing a contact point for lost and found items. The new SPC-PCN online taxi service system constructed in this paper is vital for service quality optimization, and can also promote the sustainable growth of the online taxi market.

Although information transparency and exposure have proven to be important factors in influencing sales, it needs to be further explored whether they always have a boosting effect on sales. This research collected sales data from an e-commerce platform in China to measure the impact of green information transparency and exposure on online sales of organic food, while an eye-tracking experiment was conducted for variable construction. Results show that both green information transparency and exposure can significantly promote online sales of organic food, but the promotion effect varies by sales volume level. In addition, a new finding is that increasing either the green information transparency or exposure will better promote sales than both increasing them. The research emphasizes the value of making trade-offs between green information transparency and exposure in promoting sales. In other words, in order to increase sales as much as possible, stakeholders need to consider more publicly transparent green information or more frequent exposure of green information depending on the level of sales.

Livestream commerce is a form of social commerce that leverages advanced technology for interactivity. Although research is complex due to vast geographical and platform diversity, this domain is ideal for applying affordance theory. We systematically analyze 62 livestreaming and social commerce research papers that have used affordance theory. Our three-step methodology includes performance analysis to identify prolific authors and collaborative patterns; thematic analysis to uncover methodological approaches, contextual themes and focal points of investigation; and science mapping to identify thematic evolution and research frontiers. Through our integrated perspective on affordance theory in social and livestream commerce, we present a typology of key affordances, review prominent works, categorize clusters and topics and identify four research frontiers. We propose an integrated model to explore potential avenues for research on consumer behaviours, holistically integrating actors, context, platform diversity and affordances, and addressing methodological challenges, including use of visual methodologies to investigate real-time interactions.

Conversational agents are increasingly handling a significant volume of service interactions and are projected to handle up to 95% of customer service interactions. However, like any service provider, conversational agents are not immune to service failures, which can result in negative customer experiences. Within the context of interactions between conversational agents and consumers, the informal linguistic strategies employed by conversational agents have been recognized as vital in recovering customer satisfaction after service failures. Nevertheless, research on how these linguistic strategies impact customer responses following service failures is still in its early stages. This study delves into the informal language styles used by conversational agents after service failures, examining the comparative effects of cute language styles (as informal language styles) and literal language styles (as formal language styles) on service recovery. Drawing upon the mind perception theory and the stimulus–organism–response (SOR) model, this research also unveils the underlying dynamics of whimsical and kindchenschema cuteness on customers’ forgiveness, along with literal language styles, in the context of service recovery. Furthermore, this study investigates the moderating influence of exchange and communal relationships, taking into account the boundary effects of relationship norms. To explore these hypotheses, three experiments were conducted. The findings of this research offer valuable theoretical insights and practical implications for designing linguistic strategies employed by conversational agents.

The popularity of live streaming is driving the emergence of a new business model, known as live streaming commerce (LSC). The live chat service serves as a key indicator of viewer engagement in LSC shows, differentiating LSC significantly from traditional e-commerce. In this paper, we collect a rich live streaming dataset and identify two categories of social interactions behind live chat: transaction-oriented and relationship-oriented. Broadcasters and viewers in the transaction-oriented category focus on products and transactions and tend to communicate with non-emotional words in live chats. In contrast, broadcasters and viewers might treat each other as friends and are more likely to post emotional words in the relationship-oriented category. Our econometric model shows a curvilinear association between relationship-oriented social interactions and viewer purchase behaviors. The empirical analysis indicates that to achieve higher sales, LSC broadcasters should make relationship-oriented social interactions in live chat account for 58.64% of the probabilities. We discuss the implications of heterogeneous social interaction strategies across different broadcasters.

Many firms have introduced membership programs as an important customer service initiative. However, little research has focused on how to enforce e-commerce retailing through membership service sharing. To explore the value of membership service sharing in e-commerce retailing, we build a game-theoretical model in which the brand decides whether to enable e-commerce retailing through online direct selling, and then all participants determine whether to engage in membership program sharing. Our findings show that in the case with a low consumer acceptance to the e-commerce channel, the brand will enter the downstream market if the entry cost and product cost are low, or the entry cost is low and the unit cost of the product is very high. One of the interesting findings is that the brand might fall into the encroachment trap when the product cost is moderate. Meanwhile, improving consumer acceptance of the e-commerce channel or the ratio of point exchange are effective ways to escape this trap. Moreover, when consumers are more willing to accept the e-commerce channel, the brand will adopt an e-commerce retailing strategy if the entry cost is low. Also surprisingly, our study shows that the brand would be better off from membership service sharing if the product cost is moderate, or very high, while the retailer would be worse off. Furthermore, when the unit cost of the product is moderate, membership program sharing has a remarkable impact on the brand’s retailing strategy. In addition, we also make some extensions to verify the robustness of the core model.

This study, guided by the elaboration likelihood model, explores the impact of user-generated content features, including argument quality and source credibility, on perceived usefulness. Analyzing social media posts in finance and health, the study’s econometric analysis reveals that these features influence perceived usefulness through central and peripheral cues. Newly identified features, domain relevance, and domain specificity are significantly associated with perceived usefulness. Specifically, domain relevance positively impacts perceived usefulness, while a U-shaped relationship exists for domain specificity. Subsequently, the study discusses the implications for user-generated content and management practices.

Reward-based crowdfunding has become a widely adopted financing mechanism in the creative economy, particularly for IP derivative products, resulting in a typical crowdfunding supply chain comprising an IP owner, a crowdfunding platform, and a manufacturer. Our study aims to build a theoretical model to explore the strategic issue regarding how to design the decision structure of crowdfunding supply chains with IP derivative products. Our analytic results reveal that when the product quality remains consistent across decision structures, the IP owner prefers the self-operation structure (i.e., structure O) if the quality level is either low or high; otherwise, the authorization structures are preferred. When the platform’s commission rate is relatively low, authorizing the manufacturer (i.e., structure M) outperforms authorizing the platform (i.e., structure T), which is counter-intuitive. However, structure O always achieves the highest funding amount and can lead to a tripartite win–win situation under certain conditions. When the quality level is determined endogenously by the creator, in addition to structure O, structure T can also achieve the highest funding target and lead to a tripartite win–win situation in some cases by regulating the quality level. Notably, due to the double marginalization effect, structure M always leads to a sub-optimal outcome for the manufacturer regardless of whether the quality is constant or endogenous.