With the evolution of Artificial intelligence (AI), emotional artificial intelligence service agents (AISA) have become common in service industry. However, how artificial empathy of AISA contributes to customer acceptance remains an open question. This study draws on Anthropomorphism Theory and Customer AI Experience Theory to examine whether and how artificial empathy has influence on customer acceptance of AISA. Evidence from three experiments (N=1057) designed by the Experimental vignette method (EVM) shows that: (1) artificial empathy including perspective-taking, empathic concern and emotional contagion has a positive impact on customer acceptance of AISA (study 1); (2) customer AI experience (emotional experience quality, social experience activation and social experience quality) mediates the relationship between artificial empathy and customer acceptance of AISA (study 2); (3) artificial empathy for hedonic (vs. utilitarian) services leads to a stronger effect on customer acceptance of AISA (study 3). This paper enriches our understanding of artificial empathy and provides practical guidance for practitioners strategically managing AISA services in AI-enabled marketing interactions.
In recent years, advances in the digital and live streaming economy have led to exponential growth in the number of self-employed streamers who have become an integral part of the self-driven digital labor force. However, previous research on the impact of streamers' work time arrangements on their virtual gifts remains scarce. To fill this gap in the literature, using large-scale data from Kuaishou live streaming platform, we demonstrate that several features of streamers' work time have an important impact on their virtual gifts. Specifically, our results suggest that work time duration and timing improve streamers' virtual gifts; meanwhile, work time tempo has an adverse effect on streamers' earnings. Taken together, our results provide novel and actionable insights for millions of self-employed streamers, agencies, platforms, and policymakers.
Artificial intelligence generated content (AIGC) refers to content produced by artificial intelligence that represents the perspectives of its users, and a new technique of content Generation. Continuous development in deep learning and algorithms have facilitated the adoption of AIGC. This research summarizes literature published under the topic of AIGC using bibliometric analysis method, aims to provide insightful research directions for future studies. 342 documents were collected from Database of Web of science, network visualization analysis among authors and citation analysis over publications are presented to scholars who wish to further research into this area.
The popularity of live streaming is driving the emergence of a new business model, known as live-streaming commerce (LSC). While there are more and more broadcasters in LSC, their behaviors and performance of them are significantly different. To have a better understanding of broadcasters, we employ different machine learning models to identify different portraits in both static and dynamic dimensions. We collect a rich live-streaming dataset from one leading platform in China. Our dataset features information for both broadcasters and viewers, including viewers’ purchasing behaviors, viewers’ records of posting words, broadcasters’ gender, the number of followers for broadcasters, and the live streaming show information, including the start and end time, and the viewers in each live streaming show. The rich textual information in broadcasters’ profile induction provides us a good opportunity to uncover different static portraits and the records in live streaming shows give us a chance to identify different dynamic behavioral portraits for broadcasters.
The popularity of live streaming is driving the emergence of a new business model, known as live-streaming commerce (LSC). Consumers spend more and more time on smartphones, and the emerging business model of live-streaming commerce (LSC) is flourishing in the retail industry. With highly interactive features, LSC social interactions influence viewer purchase behaviors. To examine the interactions between influencers and viewers, we collected a rich dataset from a leading LSC service platform and integrated research models from the natural language process (NLP) field and econometric models.
This study constructs a model to predict ad attitude when AI influencers act as ad endorsers. In the results, search products and rational ad appeal have more positive ad attitude, perceived empathy and perceived expertise as mediator. These three variables can be reinforced by the consistency of ad appeals and product categories.
The rapid development of artificial intelligence technology has accelerated the promotion and application of service robot in the market. Although technology has provided service robot with increasingly autonomous functions, more research is needed on how service robot with different levels of autonomy affects customer satisfaction in the hospitality industry. Guided by affordance theory, the study examines whether service robot operational and decisional autonomy would have effects on customer satisfaction and explored explanatory mechanism. Adopting an experimental vignette method (EVM), the study reveals that direct effect of service robot operational autonomy and indirect effect of decisional autonomy on customer satisfaction, and functional affordance played a positive mediating role in the impact of service robot autonomy on customer satisfaction. This research extends and enriches the relevant literature on human-machine interaction and customer satisfaction research. Further, the study also provides marketing insights for enterprises to improve autonomous robot design and enhance customer relationships.
Marketers and retailers are increasingly interested in grabbing the opportunity to reach the consumer at the right time and place with a smart phone. Depending on Location Based Advertising (LBA) and associated sensors with the IBeacon technology, marketers can determined the consumer’s favorite products through his search history and previous purchase activities furthermore his location in-store. So, marketers and retailers pay more attention to in-store mobile LBA. In this work, the modified LBA in-store framework are constructed. This model proposed that the temporal time, type of information and the variety of receiver of mobile in-store LBA affect the Purchase intention in retail stores.
The performance of an organization largely depends upon the strategy-environment fit (Mintzberg, 1979). The success of business-level strategy is contingent on industry environment characteristics (Pelham, 1999). Under the strategic fit, new ventures need to match their strategies of market, product with external environment. In different contextual situations, a new venture should employ appropriate management practices that positively impact its performance. The strategic fit provides important theoretical foundations for understanding how strategies drive firm performance. Today, technology-based start-up ventures and corporate entrepreneurship both embrace emerging markets and emerging technologies as the core of their competitive advantage (Thukral, Ehr, Walsh, Groen, & Sijde, 2008). For these new ventures, it is important to set up market orientation strategy at the beginning of founding. New ventures need to explore market opportunities and respond to market requirements. Proactive and responsive market orientations are two dimensions of market orientation considering to latent and current market needs ((Narver, Slater, & Maclachlan, 2004)). Current studies acquiescently treat proactive and responsive as two types of market orientations. However, further study need to clarify whether and what extent and under what contextual situations new ventures pursue two dimensions of market orientation strategy. In specifically, does pursuit of a hybrid market orientation lead to superior performance relative to a pure one? What extent should a new venture emphasize relative pure strategy which can help it to fit its strategy with performance objectives? Furthermore, is the market orientation strategy purity equally important in both emerging and established market conditions and industrial technology standards? This paper proposes hypotheses of positive relationship between market orientation strategy purity and new venture performance. And, Market needs has a moderating role on the relationship of MO purity and new venture performance. That is, for emerging market, the MO purity will exert a weaker influence on the new venture performance. Technological uncertainty has a moderating role on the relationship of MO purity and new venture performance. That is, for emerging technology, the MO purity (especially proactive market orientation) will exert a stronger influence on the new venture performance.
Impacts of Relationship value on Loyalty of Online Group-Buying Customer in China With the development of e-commerce industry, online group-buying pattern has been one of the most popular online shopping patterns in China. Although the online group-buying platform has a large number of consumers, the consumer loyalty to specific online group-buying platform is low. For this phenomenon, scholars usually studied from the perspective of factors which influenced consumer behavior intentions. However, few studies focus on the component and measuring of relational benefits in the process of group-buying. Based on the perspective of consumers, this paper studied the relational benefits between consumers and online group-buying platform, and the perceived benefits of consumers who are in different relationship life cycle.This paper used SPSS to test the reliability and validity of data and carried some discussions about research model through factor analysis and regression analysis. The results indicated that relational benefits were significantly related to customer loyalty, that relationship quality and relationship life cycle was considered as mediator and moderator, respectively. Further, we made some management recommendations for operators in the online group-buying platform.