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Consumers have pervasively relied on mobile reviews in digital economy. However, little knowledge exists regarding how customers adopt several mobile reviews to make purchasing decisions. With the assistance of reader-response theory, this study investigates how the consistency of product reviews, in terms of their adherence to both other reviews and the prior experience of the customer, affect perceived quality, confirmation of the customer's expectations, the customer's level of trust in the seller and the consequent purchase intention.

Based on a scenario simulation and an online experiment to collect data, the authors employed AMOS to test the proposed hypotheses using survey data collected from 314 customers in Study 1 and 420 consumers in Study 2.

The results indicate that global consistency positively and significantly contributes to confirmation, perceived quality and trust in sellers while sequential inconsistency positively and significantly influences perceived quality. Meanwhile, purchase intention is positively and significantly promoted by confirmation, perceived quality and trust in sellers, and initial valence has some moderating effects on these relationships.

This study contributes to the understanding of how customers apply product reviews to make purchasing decisions from a new angle. It also elucidates the way in which the perceived consistency of product reviews affects how reviewers are perceived and the consequent effect of these perceptions on a customer's purchase intentions.

Message stream advertising (MSA) has become an increasingly popular option for advertising on mobile social media. However, MSA is often avoided by consumers, and this avoidance deserves more research attention. The purpose of this study is therefore to identify the underlying mechanism and key variables that affect consumer avoidance of MSA in the context of mobile social media.

A face-to-face survey was administered to current mobile users of WeChat (N = 438). Structural equation modeling was conducted to test the relationships in the research model.

Results revealed that mobile consumers employ mechanical avoidance methods (i.e. zipping, muting and zapping) against MSA. The findings also demonstrated that advertising intrusiveness (stimulus) is directly linked to negative emotions, perceived entertainment and sense of control (organism), which, in turn, relate to MSA avoidance (response).

The study contributes to the MSA avoidance literature by using the stimulus-organism-response model to deepen the understanding of consumers' MSA avoidance on mobile social media, and it suggests important managerial implications for advertising practitioners and platform operators.

Wearable health devices (WHDs) have demonstrated significant potential in assisting elderly adults with proactive health management by utilizing sensors to record and monitor various aspects of their health, including physical activity, heart rate, etc. However, limited research has systematically explored older adults’ continued usage intention toward WHD. By utilizing the extended unified theory of acceptance and use of technology (UTAUT2), this paper aims to probe the precursors of elderly adults’ continuance intention to use WHD from an enabler–inhibitor perspective.

The research model was developed based on UTAUT2 and examined utilizing the partial least squares technique (PLS). The research data were collected through in-person meetings with older people (n = 272) in four cities in China.

Results reveal that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic values and perceived complexity are the positive predictors of elderly adults’ continuance intention to use WHDs. Technology-related anxiety and usage cost negatively influence the formation of older people’s continuance intention.

This work is an original empirical investigation that draws on several theories as guiding frameworks. It adds to the existing literature on the usage of wearable technologies and offers insights into how the elderly’s intentions to continue using WHDs can be developed. This study broadens the scope of the UTAUT2 application and presents an alternative theoretical framework that can be utilized in future research on the usage behavior of wearable devices by individuals.

Lead users are essential participants in crowdsourcing innovation events; their continuance intention significantly affects the success of the crowdsourcing innovation community (CIC). Although researchers have acknowledged the influences of network externalities on users' sustained participation in general information systems, limited work has been conducted to probe these relationships in the CIC context; particularly, the predictors of lead users' continued usage intention in such context are still unclear. Hence, this paper aims to explore the precursors of lead users' continuance intention from a network externalities perspective in CIC.

This work ranked users' leading-edge status to recognize lead users in the CIC. And then, the authors proposed a research model based on the network externalities theory, which was examined utilizing the partial least squares (PLS) technique. The research data were collected from an online survey of lead users (n = 229) of a CIC hosted by a China handset manufacturer.

Results revealed that the number of peers, perceived complementarity and perceived compatibility significantly influence lead users' continuance intention through identification and perceived usefulness.

This work contributes to the crowdsourcing innovation research and provides views regarding how lead users' sustained participation can be developed in the CICs. This work also offers an alternative theoretical framework for further research on users' continued intention in open innovation activities.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Social media advertising must engage with consumers, validate their sense of control, and avoid evoking negative emotions.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Drawing on the wisdom of ancient Chinese philosopher Xunzi, this paper aims to present a novel mechanism for governing opportunism, referred to as “cultivational governance.” By examining the role of artificial intelligence (AI) resources possessed by e-commerce platforms, the authors explore how these resources contribute to mitigating seller opportunism. The central hypothesis of this study posits that two distinct types of AI resources, namely, AI technology resources and AI human resources, serve as crucial factors in curbing seller opportunism. Furthermore, the authors propose that platform digital empowerment and value cocreation act as mediating variables linking AI resources to opportunism.

Based on the resource-based view and resource orchestration theory, the authors developed a framework and tested it using survey data from sellers. This framework encompasses five key variables: e-commerce platform’s AI technology resources, AI human resources, platform digital empowerment, value cocreation and seller opportunism. Regression analysis was used for data analysis.

The empirical results validate the effectiveness of cultivational governance mechanisms, as both AI resources effectively suppress seller opportunism through digital empowerment and value cocreation. Specifically, e-commerce platforms’ AI technology resources significantly promote value cocreation and platform digital empowerment, while AI human resources primarily contribute to platform digital empowerment. Although platform digital empowerment encourages value cocreation, its direct impact on reducing seller opportunism was not supported. Notably, value cocreation negatively affects seller opportunism.

The present research mainly contributes to the marketing channel governance literature by introducing a new approach to inhibit opportunism, namely, the cultivational governance mechanism.

This paper aims to provide a comprehensive review of the literature examining the relationship between automation and employment, with a focus on understanding the debates of automation displacement and enablement, and the mediating role of employee augmentation in driving organisational productivity.

A semi-systematic literature review was conducted across the areas of automation, work-design and employee skills over the past 3 years.

The academic literature was found to still be in its infancy, with empirical evidence in an organisational setting scarce. However, research suggests that automation does not cause job displacement or a negative impact on employment. In contrast, data suggest that automation leads to new job creation, task enlargement and skills enhancement. The findings suggest that organisations should employ augmentation alongside automation to drive productivity, in a way that promotes strong work-design, builds trust and leverages human creativity. A further recommendation is made for organisations to focus on continuous upskilling to combat the shortening shelf-life of skills and adapt to the constant change brought around by advances in automation.

Through a synthesis of diverse perspectives and academic evidence, this paper contributes to the nuanced understanding of the complexities surrounding automation and its impact on employment. This literature review underscores the need for organisational strategies that leverage augmentation to harness productivity savings, alongside a renewed focus on widespread employee skills enhancement. In addition to creating new recommendations for practitioners and organisational leaders, this paper also furthers the research agenda through a list of research gaps for scholarly attention.

The purpose of this study is to empirically explore how firms configure centrifugal and centripetal forces in promoting breakthrough innovation (BI), thus improving their strategic performance (SP) in the artificial intelligence (AI) context.

This study applies the centrifugal and centripetal forces model to a survey sample of 285 Chinese AI firms. Fuzzy-set qualitative comparative analysis (fsQCA) and propensity score matching (PSM) are integrated to explore the configurational effects of three centrifugal forces—the autonomy of technical experts, knowledge search and alliance network—and two centripetal forces—strictness of organisational institutions (SOI) and human–human–AI collaboration (HHAC)—on BI, examining whether the configurations that enhance BI can further improve SP.

The results indicate that the strictness of innovation institutions (SII) and strictness of ethical institutions (SEI) are equally important for determining SOI. Three configurations can improve BI when SOI and HHAC are the core conditions; only one of three configurations can further improve SP significantly.

By introducing SOI composed of equally important levels of SII and SEI and HHAC, this research is one of the few empirical studies to explore the mechanisms behind the impact of centrifugal and centripetal forces on BI and SP, which may help researchers and managers address innovation challenges in the AI context.

This study aims to examine how knowledge sharing contributes to organizations’ ambidexterity, their overall performance and the role of knowledge quality in this relationship. Knowledge sharing is conceptualized based on tacit and explicit dimensions, and ambidexterity is viewed as comprising exploitative and explorative capabilities.

This study uses a cross-sectional survey-based research design and structural equation modeling to test the proposed model of knowledge sharing and knowledge quality in organizational ambidexterity and the related hypotheses.

The results indicate that tacit knowledge sharing has a significant, direct impact on the exploitative and explorative capabilities of the organization and indirectly impacts both dimensions of ambidexterity (i.e. exploitative and explorative) through knowledge quality. In contrast, explicit knowledge sharing does not have a significant impact on knowledge quality and affects only the exploitative extent of ambidexterity. Both exploitative and explorative capabilities significantly impact organizational performance.

To the best of the authors’ knowledge, this study is the first study to empirically examine the role of knowledge quality in the context of knowledge sharing for ambidexterity, especially within the context of organizations in the United Arab Emirates.

This study aims to examine the role of big data analytics (BDA) powered by artificial intelligence (AI) in improving sustainable performance (SP) through green supply chain collaboration (GSCC), sustainable manufacturing (SM) and environmental process integration (EPI).

Data was collected from 249 supply chain professionals working at various manufacturing firms, and hypotheses were tested through a quantitative method using PLS-SEM with the help of SmartPLS version 4 to validate the measurement model.

This study identified that BDA-AI significantly and positively affects GSCC, SM and EPI. Similarly, the results showed that GSCC significantly and positively affects SP. At the same time, SM and EPI have an insignificant effect on SP. The GSCC found a significant relationship between BDA-AI and SP for mediation. However, SM and environmental performance integration did not mediate the relationship between BDA and AI and SP.

This research evaluated a second-order model and tested SP in conjunction with the dynamic capability theory in the manufacturing industry of Pakistan. Therefore, this research could be beneficial for researchers, manufacturers and policymakers to attain sustainable goals by implementing the BDA-AI in the supply chain.