Journal of Business Research最新文献

Drawing from AI classification experience and identity-based motivation frameworks, this research explores the impact of AI classification failures on consumers’ self-identification and examines how self-expression plays a crucial role in shaping these effects. Across five studies, this research reveals that AI classification failures can diminish consumers’ self-identification, increasing negative outcomes such as regret, defensive neurophysiological cues, and adverse downstream behaviors for service providers. Consistent with our identity-based account, the findings highlight that the detrimental impact of AI classification failures is more pronounced when consumers are motivated to utilize AI-recommended content for self-expression, and such effects are mitigated when these motives are not salient. This study offers important theoretical and managerial implications for the burgeoning field of service failures by shedding light on the nuanced impact of AI classification failures and their potentially detrimental effects. Finally, it provides managerial recommendations for recovering failures in AI classification experience.

Existing research on optimising marketing resource allocation focuses mainly on the customer rather than the retailer level. However, retailers play an important role in marketing channels, and optimising retailer-level marketing resource allocation poses important decision-making challenges. In this study, we proposed a retailer-level offline marketing resource-optimising allocation model based on retailer segmentation. The model consists of two stages. In the first stage, we built a retailer segmentation index system and introduced a bi-clustering algorithm to segment retailers that can cluster samples and features simultaneously. In the second stage, we proposed a new measurement for the rate of return on the utility of marketing resources and then leveraged the mean–variance model to find optimal marketing resource allocation plans. An empirical study of a famous Chinese alcoholic beverage company demonstrated that the proposed model outperformed four baseline models.

While practitioners question whether employees’ work-related social media use is a blessing or curse, few scholars have studied the content of employees’ social media posts. Moreover, organizations increasingly regulate employees’ online presence through social media governance tools, but research on their effectiveness is lacking. With an online survey among 502 Belgian employees, we quantitatively examined how social media governance affects employees’ online branding behavior. Additionally, we asked participants to share a recent work-related social media post with us, and explain why they posted it. Quantitative findings indicate that employees’ branding behavior on social media is mostly driven by their identification and relationship with their organization. Regarding the influence of social media governance, guidelines and rewards affect branding behavior positively, while a ban and punishments can have a destructive impact through reactance. When we qualitatively zoom in on employees’ work-related posts, these are mainly positive, organization-related and used for organizational promotion.

Despite growing research recognising the role of digital capability in enabling innovation strategy and outcomes, we know little about how firms can effectively adapt to shifts in innovation paradigms caused by digitalisation by leveraging digital platform capability to attain innovation ambidexterity. Drawing on dynamic capability theory (DCT), this study explores the influence of firms’ digital platform capability on innovation ambidexterity by analysing a sample of 312 Chinese manufacturing firms. We find that digital platform capability has a positive effect on innovation ambidexterity via the mediating role of strategic flexibility. Market turbulence positively moderates the relationship between digital platform capability and strategic flexibility. These findings enhance our understanding of the mechanisms by which digital platform capability influences innovation ambidexterity.

With the growing complexity of today’s big data environments, data-driven business model innovation has shown the key features of a complex system, such as dynamics and non-linearity, but relevant research mainly draws a static and linear perspective, which necessitates unveiling data-driven business model innovation as a complex system. To this end, building on complexity theory, this study divides the complex system of data-driven business model innovation into three interdependent subsystems (i.e., big data, business model innovation, and data value). Each subsystem has its more granular components and elements. Then, the system dynamics approach is adopted to clarify the coevolution process and its key influencing factors of data-driven business model innovation. By conducting simulation and sensitivity analysis of key variables, the findings suggest that, like the “flywheel effect”, big data insight, value proposition, customer performance, and firm performance increase with time. Among them, big data insight, value proposition, and customer performance have a basically consistent pace. By contrast, firm performance grows much more slowly at the beginning but has a stronger acceleration in later stages. Besides, improving big data analytics cannot directly increase data value. Only when combined with businesses, it can create marginal benefits, among which business matching is the most salient. This study not only contributes to the advancement of complexity theory and data-driven business model innovation but also deepens business model research through holistic and systematic approaches.

Organizational category research has received increasing attention in the field of management and organization for over 30 years. Although there are extant literature reviews concerning the category research, none of them provides a comprehensive review of organizational category formation in management and organization studies. To address this gap, the study systematically synthesizes and evaluates 345 papers on the organizational category formation from 1989 to 2022 to present state-of-the-art literature and guide future research. First, we identify three stages of the development of organizational category formation literature, and then outline a holistic picture of antecedent, process, and the outcome of organizational category formation in which the underlying research has been investigated to construct a theoretical framework. Finally, the findings also provide concrete guidance for future research endeavors in this area.

In this study, we explore how investors react to incidents of CEO sociopolitical activism. Drawing from the business case logic and political psychology literature, we theorize that the perceived relevance and ideology of CEO comments, as well as the institutional context in which they were made determine investor reactions. Our analysis of 379 CEO comments made between 2007–2020 indicates that investors react positively to CEOs’ political comments and negatively to sociocultural ones. Specifically, political comments are received favorably by investors if they are conservative-leaning, and this is especially true when made by CEOs of firms with greater government dependence or those operating in highly regulated industries. Conversely, investors react negatively to social comments made by CEOs of highly regulated firms. Overall, this study addresses recent calls for research on the expanding role of executives by highlighting the complex reactions CEO sociopolitical activism engenders among capital market stakeholders.

The rise of virtual technology has served as a catalyst for a new influencer model – one with a crafted persona and an animated avatar. These virtual entertainers excel in engaging audiences and have become increasingly popular as a promising industry with many prospective opportunities. However, research within this industry is limited and lacks consistency. This paper aims to establish an emergent theory for the virtual entertainer industry. First, the concept of a virtual entertainer is introduced and defined along with key developments in the evolution of the industry. Using content analysis on 1189 comments and clustering 293 channels with over 180,000 livestreams, the paper identifies 3 key dimensions of virtual entertainers – (1) Organizational Support, (2) Self Expression and (3) Activity; and 5 distinguishing archetypes for virtual entertainers. The performances of these archetypes were compared across multiple success indicators, providing insights for understanding and developing positioning strategies within this growing industry.

Live streaming has been increasingly integrated into e-commerce platforms to sell tourism offerings, yet its value-adding mechanism for enhancing customer shopping experiences remains underexplored. From a value co-creation perspective, this study investigates how customers can co-create value by leveraging the interactive potential in tourism live shopping, and how such customer co-creation behavior can be fostered through the attributes and actions of tourism live streamers, drawing on source credibility and social presence theories. The empirical findings indicate that the credibility traits of tourism live streamers, characterized by trustworthiness, expertise, and attractiveness, are instrumental in fostering customer co-creation behaviors, which can in turn elevate customer perceived value of their tourism live shopping experiences. Additionally, the study reveals that the level of social presence during tourism live shopping sessions may positively moderate the influence of streamer credibility traits on customer co-creation behaviors.