This paper explores how the anthropomorphic features of service robots influence employee service recovery engagement through the mechanism of responsibility diffusion in service failure contexts, with a particular focus on the moderating role of organizational AI readiness. Grounded in the Computers As Social Actors paradigm, we validated our hypotheses across five studies (N = 1532). This progression included a real-world pre-study, an organizational survey, and two controlled experiments featuring both embodied and virtual robotics. A final video-based experiment was conducted to systematically eliminate alternative accounts, including role ambiguity. The results show that service robot anthropomorphism increases the diffusion of responsibility among collaborating employees, which in turn reduces their subsequent service recovery engagement. However, a high degree of organizational AI readiness can buffer this negative effect. Our study advances the scholarship on human-robot collaboration, offering managers actionable guidance for integrating service robots to boost employee productivity. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)"(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic) (N = 1532) (sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic), (sic)(sic)(sic)(sic)(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Grounded in attribution theory, this study examines how robotic empathy influences customers’ motive attributions and continued usage intention. We conducted a scenario-based experiment (N = 347) and a field survey of hotel guests (N = 216). Across studies, high-empathy responses enhance service enhancement attributions and reduce cost reduction attributions, thereby strengthening continued usage intention. Neuroticism further moderated these attribution processes, such that high-neuroticism consumers were more likely to infer cost reduction motives under low empathy, whereas this tendency weakened when empathy was high. This study answers prior calls for research and provides important practical implications.

Language style matching (LSM), a form of linguistic convergence, enhances communication quality and social identity in interpersonal interactions, but its mechanism in human-chatbot interaction-especially after service failures-remains underexplored. Drawing on Communication Accommodation Theory, this research examines how chatbot LSM affects users' reuse intention in service failure contexts. LSM was operationalized through chatbots' adaptive use of function words (e.g., pronouns, auxiliary verbs) during text-based interactions: measured via the established function-word matching formula (Ireland & Pennebaker, 2010), manipulated by programming the chatbot to align with or diverge from users' function-word patterns, and applied to text-based service recovery scenarios. Four controlled experiments test the mediating role of perceived humanness and the moderating role of service failure severity. Results show that the positive effect of LSM on reuse intention is stronger under minor (vs. major) service failures. This research broadens LSM application to human-chatbot interaction, extends communication accommodation theory to non-human agents, and offers insights for chatbot service design.

This research investigates the interactive influence of live-streaming background design and food processing levels on consumer behavior. Our findings reveal that for minimally processed agricultural products, an origin-based background (e.g., broadcasting directly from a farm) significantly enhances purchase intention compared to a standard studio background. We demonstrate that this effect is driven by a heightened perception of freshness. Conversely, for highly processed agricultural goods, the influence of background type is attenuated. Furthermore, we identify rural sentiment as a critical boundary condition, revealing that the positive effect of origin-based backgrounds is amplified among consumers with stronger emotional ties to rural life. These results offer nuanced insights into how digital broadcasting environments can be strategically aligned with product characteristics to optimize marketing outcomes.

PurposeThis paper aims to investigate how promotion- versus prevention-focused ethical leadership differently influence knowledge sharing. Specifically, it investigates the emotional mechanisms underlying these effects and the moderating role of employees' moral identity.Design/methodology/approachDrawing on affective events theory, this research conducted a scenario-based experiment to investigate how promotion- and prevention-focused ethical leadership elicits employees' emotional responses. The authors then used an experience sampling method study to validate the differential effects of these two forms of ethical leadership on knowledge sharing, while examining the mediating role of employees' emotions and the moderating effect of moral identity.FindingsPromotion-focused ethical leadership enhances employee knowledge sharing by eliciting supervisor-directed, other-praising moral emotions. In contrast, prevention-focused ethical leadership evokes supervisor frustration, which in turn inhibits knowledge sharing. Furthermore, employees' moral identity amplifies both emotional pathways, such that individuals with higher levels of moral identity experience stronger emotional responses in reaction to both types of ethical leadership.Originality/valueThis research offers a fine-grained understanding of the relationship between ethical leadership and knowledge sharing by differentiating between promotion- and prevention-focused ethical leadership. It also introduces emotion-based mechanisms and highlights moral identity as a key boundary condition.

A critical challenge in public management and behavioral decision-making is understanding how to translate consumption stimulus policies into actual consumer action. By applying the Motivation-Opportunity-Ability (MOA) framework, this study aims to systematically examine the behavioral mechanisms that drive how consumers receive and use national subsidies. The results showed that: (1) motivation, opportunity and ability have significant positive effects on the intention to claim the national subsidies, and the perceived benefits and pleasant experience are especially critical; (2) the intention to claim the national subsidies significantly predicts the actual use behavior, which verifies the mechanism effect of the “intention-behavior” path; (3) AI-assisted decision-making and return convenience have a significant positive moderating effect on the “intention-behavior” path; (4) the middle- and low-income groups are more sensitive to the incentive path, showing obvious heterogeneity. Random forest test and hot spot analysis of secondary data are further employed to ensure the robustness of conclusions and provide further insights about the spatial distribution of subsidies. The study not only expands the applicable boundaries of MOA model in the study of policy adoption behavior, but also provides empirical evidence and practical suggestions for optimizing the design of subsidy policy and enhancing the efficiency of policy implementation.

Although research about applying artificial intelligence (AI) to sales has strongly developed recently, new evidence points to consumer concerns about potential misuse or abuse of AI. This research focuses on whether AI-assisted (vs. human) selling influences consumers' evaluation of service quality. We examined the impact of AI-assisted selling on perceived service quality across seven experiments (three in the Web Appendix). Drawing on the persuasion knowledge model, we found that consumers may view AI-assisted selling as a persuasive selling approach, thus reinforcing perceptions of manipulative intent, which, in turn, produces negative evaluations of service quality. Additionally, our findings indicate these adverse effects are more pronounced among consumers with high persuasion knowledge and when salespersons have a high level of expertise. Our research contributes to the growing literature on AI in sales and offers practical insights about how sales managers can use AI to integrate and enhance the consumer experience more effectively.

This paper explores how subjective perceptions of busyness influence consumption choices through distinct psychological mechanisms. Grounded in the need for uniqueness theory, the study employs a mixed-method approach-comprising one survey and three scenario-based experiments-to examine the relationship between perceived busyness and experiential consumption preferences. The core hypothesis was confirmed in Study 1a and 1b: individuals perceiving higher levels of busyness demonstrate a stronger inclination toward experiential rather than material purchases. Study 2 further revealed a mediating mechanism, wherein perceived busyness increases the need for uniqueness, which in turn drives experiential preferences. Study 3 identified consumption context as a key boundary condition: the effect of busyness on uniqueness-driven experiential preference is amplified in solitary consumption contexts but attenuated in joint consumption due to the influence of social norms. By uncovering these psychological processes and situational moderators, this research deepens our understanding of how busyness perceptions shape consumer behavior and offers actionable insights for tailoring precision marketing strategies to time-constrained audiences.

Although the benefits of personal initiative for employees have been widely documented, how colleagues respond to personal initiative remains underexplored. Drawing on attribution theory, our research examines when and how colleagues make different attributions to personal initiative and, in turn, engage in proactive or reactive knowledge sharing. Through a two-wave survey (Study 1), a scenario-based experiment (Study 2), and a quasi-field experiment (Study 3), we find that when cooperative goal interdependence is high, colleagues tend to attribute personal initiative to organizational concern and actively share knowledge. In contrast, when cooperative goal interdependence is low, colleagues are more likely to attribute personal initiative to impression management and share knowledge only when explicitly requested. Our research thus introduces an attribution perspective on the interpersonal effects of proactive behavior and offers valuable guidance for managing proactive behavior in organizations.

Artificial intelligence-based service robot failures (hereafter referred to as robot service failures) are inevitable in service practice, making the mitigation of their adverse effects a critical concern for service managers. The present paper investigates the unique classification of robot service failures with the help of mind perception theory and a consumer-centered perspective. Moreover, we further examine the impact of robot service failures on consumer behavioral responses (i.e., reuse intention), the mediating role of negative emotions, and the moderating effect of service robot anthropomorphism. Using a mixed-methods approach, Study 1, based on robot service failure reviews from Ctrip and word co-occurrence network analysis, reveals a two-dimensional classification of robot service failures: agential failures and experiential failures. Furthermore, leveraging the same dataset, Study 2 calculates negative emotions in the text and uses consumer evaluations as a proxy for reuse intention. The results indicate that agential failures (compared to experiential failures) exert a more significant negative impact on consumers, and this relationship is mediated by negative emotions. Study 3 employs a behavioral experiment to further validate the findings of Study 2 and additionally reveals that service robot anthropomorphism moderates the relationship between service failures, negative emotions, and reuse intention, leading to more adverse consequences for experiential failures. This paper makes a valuable contribution to the emerging literature on robot service failures by exploring the distinctiveness of robot services. To the best of our knowledge, this is the pioneering empirical study that explores the unique dimensions of robot service failures. Practically, the findings provide actionable insights. Understanding the classification of robot service failures, which differs from human service failures, allows for a deeper comprehension of AI-powered services and offers effective intervention strategies for consumer recovery following service failures.

Based on cognitive evaluation theory, we investigate the process of word-of-mouth (WOM) textual consistency's effects on consumers' purchase behavior in the context of positive reviews. Through an empirical analysis of secondhand data and two experimental studies, we draw the following conclusions: (1) WOM textual consistency has a positive effect on consumers' cognitive trust and purchase behavior, and cognitive trust has a positive effect on consumers' purchase behavior; (2) WOM textual consistency affects consumers' purchase behavior through the mediating effect of cognitive trust, and this mediating process is moderated by brand strength; (3) cognitive trust fully mediates the relationship between WOM textual consistency and consumers' purchase behavior only in the context of high brand strength; (4) brand strength also moderates the effects of WOM textual consistency on cognitive trust and purchase behavior. In this study, purchase behavior is operationalized in two ways: as actual sales in the field study and as self-reported purchase intentions in the experimental studies. Findings in this paper not only deepen the relevant research in the field of WOM but also provide valuable references for enterprises' WOM marketing practices.

Proactive customer service performance (PCSP) in the hospitality industry is increasingly being adopted by managers as it transcends traditional responsive service mode. However, existing research has tended to view PCSP in a positive light, leaving its dual nature-encompassing both negative and positive outcomes-relatively underexplored. Through a quantitative survey and a controlled scenario experiment in a restaurant setting, and based on social exchange theory and self-determination theory, this research demonstrates that PCSP boosts satisfaction through perceived service effort but may also lower it by reducing perceived service control. Furthermore, an inverted U-shaped relationship between PCSP and customer satisfaction is identified, with internet exposure playing an important moderating role. These findings provide new insights into the effects of PCSP on customers satisfaction, offering guidance for businesses to effectively implement PCSP.

PurposeDrawing on the job design model and adaptive cost theory, this study investigates the impact of artificial intelligence (AI)-enabled task and knowledge characteristics on knowledge hiding. It also explores the moderating role of mastery climate.Design/methodology/approachThis study collected data from 357 employees in high-tech firms using a two-phase survey to empirically test the proposed hypotheses.FindingsThe results indicate that AI-enabled task characteristics (skill and task variety) and knowledge characteristics (specialization, problem solving and job complexity) drive employees to hide knowledge from colleagues. Furthermore, a mastery climate effectively mitigates the impact of AI-enabled task and knowledge characteristics on knowledge hiding.Originality/valueThis study advances understanding of the relationship between AI and knowledge hiding by shifting attention from employees' psychological reactions to the structural transformation of work, showing how AI-enabled job design reshapes tasks and generates adaptive costs that foster knowledge hiding.

PurposeSales performance is one of the critical roles in boosting firm performance, making motivating salespeople a concern for many managers. However, few existing studies on sales performance improvement from the holistic perspective exist. Based on triadic reciprocal determinism, this paper explores the combinations of the factors that may influence sales performance.Methodology/approachBased on matching questionnaires from 154 salespeople and their supervisors, this paper employs fuzzy set qualitative comparative analysis (fsQCA) to delve into the inherent complexity of factors influencing sales performance.FindingsThe results revealed that a combination of personal (family motivation, challenge stress and hindrance stress), behavioral (adaptive selling behavior) and environmental factors (organizational innovation climate and business environment) determine sales performance. Specifically, three paths lead to high sales performance, and one path leads to non-high sales performance. Significantly, the path with an organizational innovation climate can explain high sales performance more effectively than other paths.Research implicationsThis paper makes a valuable contribution to the literature on B2B sales literature by exploring triadic reciprocal determinism. To the best of our knowledge, this is the first fsQCA attempt to address sales performance based on Chinese samples.Practical implicationsThis paper offers an essential basis for sales managers to plan sales strategies. The sales managers could refer to the three paths leading to high sales performance to achieve sales targets. Further, the one path leading to non-high sales performance should be avoided in strategy decision-making.Originality/value/contributionThe paper examines different approaches to achieving high and non-high sales performance using the fsQCA method, which offers a unique and relevant perspective on B2B sales literature.

Purpose Digitally driven virtual streamers are increasingly utilized in live-streaming commerce, possessing distinct advantages compared to human streamers. However, the applicable scenarios of virtual streamers are still unclear. Focusing on product attribute variances, this paper compares the livestreaming effects of virtual and human streamers to clarify the applicable scenarios for each and assist companies in strategically choosing suitable streamers. Design/methodology/approach We conducted four experiments utilizing both images and video as stimulus materials, and each experiment employed different products. To test the proposed model, a total of 1,068 valid participants were recruited, encompassing a diverse group of individuals, including undergraduates and employed workers. Findings The results indicate no significant difference between virtual and human streamers in increasing consumers’ purchase intention for utilitarian products. In contrast, human streamers are more effective in enhancing consumer purchase intention for hedonic products, with a mediating role of mental imagery quality. Consumers’ implicit personality variances also influence their willingness to accept virtual streamers. Originality/value This paper is the first to compare the effects of virtual and human streamers in promoting different products to enhance our comprehension of virtual streamers. Given the potential risks associated with human streamers, a comprehensive understanding of the role of virtual streamers is imperative for brands when deploying live-streaming commerce activities.

Urbanization has profoundly reshaped the patterns and forms of modern urban landscapes. Understanding how urban transportation and mobility are affected by spatial planning is vital. Urban vibrancy, as a crucial metric for monitoring urban development, contributes to data-driven planning and sustainable growth. However, empirical studies on the relationship between urban vibrancy and the built environment in European cities remain limited, lacking consensus on the contribution of the built environment. This study employs Munich as a case study, utilizing night-time light, housing prices, social media, points of interest (POIs), and NDVI data to measure various aspects of urban vibrancy while constructing a comprehensive assessment framework. Firstly, the spatial distribution patterns and spatial correlation of various types of urban vibrancy are revealed. Concurrently, based on the 5Ds built environment indicator system, the multi-dimensional influence on urban vibrancy is investigated. Subsequently, the Geodetector model explores the heterogeneity between built environment indicators and comprehensive vibrancy along with its economic, social, cultural, and environmental dimensions, elucidating their influence mechanism. The results show the following: (1) The comprehensive vibrancy in Munich exhibits a pronounced uneven distribution, with a higher vibrancy in central and western areas and lower vibrancy in northern and western areas. High-vibrancy areas are concentrated along major roads and metro lines located in commercial and educational centers. (2) Among multiple models, the geographically weighted regression (GWR) model demonstrates the highest explanatory efficacy on the relationship between the built environment and vibrancy. (3) Economic, social, and comprehensive vibrancy are significantly influenced by the built environment, with substantial positive effects from the POI density, building density, and road intersection density, while mixed land use shows little impact. (4) Interactions among built environment factors significantly impact comprehensive vibrancy, with synergistic interactions among the population density, building density, and POI density generating positive effects. These findings provide valuable insights for optimizing the resource allocation and functional layout in Munich, emphasizing the complex spatiotemporal relationship between the built environment and urban vibrancy while offering crucial guidance for planning.

The Yangtze River Delta, one of China's economically developed and densely populated regions, depends significantly on how effectively its land use aligns with its socioeconomic structure for sustainable development. This study integrates the entropy method with a coupled coordination model, applying it in dynamic environments, and expanding its scope within big data to assess the interplay of "Land-Economy-Society-Ecology" across 27 cities in the Yangtze River Delta. The findings reveal that most cities exhibit slight imbalances or are on the brink of imbalance in their "Land-Economy-Society-Ecology" relationships. Moreover, the degree of interdependence varies across cities, with those demonstrating higher integration predominantly clustered around Shanghai. These regional disparities are the primary driver variations of the interrelations in "Land-Economy-Society-Ecology" within the Delta. Additionally, spatial absolute beta convergence was not observed across the Yangtze River Delta, except for Anhui, with Shanghai, Jiangsu, and Zhejiang showed no such convergence. These results underscore the imperative for the Yangtze River Delta to strategically allocate land resources, foster regional resource sharing, and prioritize high-quality economic development to achieve sustainable growth.

Prior research has shown that humor can positively impact service recovery in face-to-face interactions. However, the efficacy of using humor in virtual environments for chatbots to address service failures remains unclear. Through three experiments in different populations, this paper found that using humorous emojis by chatbots can help increase consumers' willingness to continue using chatbots after service failures (i.e., reuse intention) and the underlying mechanism; that is, the level of consumers perceiving the degree of the chatbot's intelligence (i.e., perceived intelligence) partially mediates the relationship between humorous emojis use and consumers' reuse intention. Further, how people form impressions about others based on limited information (i.e., implicit personality) significantly moderates the influence path from humorous emojis use to perceived intelligence, and perceived intelligence is more likely to mediate for people who see challenging situations as opportunities (i.e., incremental theorists). In conclusion, this paper provides empirical evidence supporting the potential benefits of using humorous emojis in chatbot service recovery, and offers guidance to online retailers to leverage digital technology for effective consumer engagement.

Robot service failure and subsequent user behavioral responses have emerged as a prominent scientific issue, warranting attention from multiple disciplines. A review of existing literature is crucial to synthesizing and comprehensively evaluating these studies. To this end, the present study undertook a structured systematic literature review to assess the relevant research on the concepts, dimensions, user response (including cognitional and behavioral), and recovery strategies related to service robot failure. Prior studies have largely followed interpersonal service interaction concepts and have identified several major consequences of service robot failure, including emotional and cognitive responses, negative attitudes, attributions of failure, and related behavioral and action-based responses. Notably, recovery strategies for robot service failure can be categorized into two main types: robot-initiated strategy and human intervention strategy. Further research on robot service failure is recommended in five key areas, including exploring the uniqueness of robot service failure, psychologically investigating user responses to robot failure, identifying novel remedy strategies for robot service failures, evolving the concepts of robot service failure and its remedies, and employing mixed-method and complementary research approaches.