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Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

Knowledge sharing in online health communities (OHCs) disrupts consumers' health information-seeking behavior patterns such as seeking health information and consulting. Based on social exchange theory, this study explores how the two dimensions of experts' free knowledge sharing (general and specific) affect customer transactional and nontransactional engagement behavior and how the quality of experts' free knowledge sharing moderates the above relationships.

We adopted negative binomial regression models using homepage data of 2,982 experts crawled from Haodf.com using Python.

The results show that experts' free general knowledge sharing and free specific knowledge sharing positively facilitate both transactional and nontransactional engagement of consumers. The results also demonstrate that experts' efforts in knowledge-sharing quality weaken the positive effect of their knowledge-sharing quantity on customer engagement.

This study provides new insights into the importance of experts' free knowledge sharing in OHCs. This study also revealed a “trade-off” between experts' knowledge-sharing quality and quantity. These findings could help OHCs managers optimize knowledge-sharing recommendation mechanisms to encourage experts to share more health knowledge voluntarily and improve the efficiency of healthcare information dissemination to promote customer engagement.

This study explores the determinants of police officer support for pre-arrest/booking deflection programs that divert people presenting with substance use and/or mental health disorder symptoms out of the criminal justice system and connect them to supportive services.

This study analyzes responses from 254 surveys fielded to police officers in Delaware. Questionnaires asked about views on leadership, approaches toward crime, training, occupational experience and officer’s personal characteristics. The study applies a new machine learning method called kernel-based regularized least squares (KRLS) for non-linearities and interactions among independent variables. Estimates from a KRLS model are compared with those from an ordinary least square regression (OLS) model.

Support for diversion is positively associated with leadership endorsing diversion and thinking of new ways to solve problems. Tough-on-crime attitudes diminish programmatic support. Tenure becomes less predictive of police attitudes in the KRLS model, suggesting interactions with other factors. The KRLS model explains a larger proportion of the variance in officer attitudes than the traditional OLS model.

The study demonstrates the usefulness of the KRLS method for practitioners and scholars seeking to illuminate patterns in police attitudes. It further underscores the importance of agency leadership in legitimizing deflection as a pathway to addressing behavioral health challenges in communities.

This research examines the relationship between the timeliness in announcing the discovery of a data breach and consumer trust in an e-commerce company, as well as later trust-rebuilding efforts taken by the company to compensate users impacted by the breach.

A survey experiment was used to examine the effect of both trust-reducing events (announced data breaches) and trust-enhancing events (provision of identity theft protection and credit monitoring) on consumer trust. The timeliness of the breach announcement by an e-commerce company was manipulated between two randomly assigned groups of subjects; one group viewed an announcement of the breach immediately upon its discovery, and the other viewed an announcement made two months after the breach was discovered. Consumer trust was measured before the breach, after the breach was announced, and finally, after the announcement of data protection.

The results suggest that companies that delay a data breach announcement are likely to suffer a larger drop in consumer trust than those that immediately disclose the data breach. The results also suggest that trust can be repaired by providing data protection. However, even after providing identity theft protection and credit monitoring, companies that fail to promptly disclose a breach have lower repaired trust than companies that promptly disclose.

This study contributes to the literature on e-commerce trust by examining how a company's forthrightness in reporting a data breach impacts user trust at the time of the disclosure of the data breach and after subsequent efforts to repair trust.

Loneliness and social isolation are risk factors for morbidity and mortality and a growing health concern. Peer support is an intervention that has shown efficacy in the wider health-care arena. However, little is known about its effectiveness when working with adults and adolescents experiencing these issues. The purpose of this study is to conduct a scoping review on loneliness and social isolation in adult and youth populations.

A preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews was conducted. Five databases, Web of Science, Academic Search Complete, Embase, PsycINFO and Scopus were searched for peer-reviewed literature published in English from inception to 2023.

The search yielded 2,402 articles of which (N = 12) met the inclusion criteria for this review. Peer support interventions for loneliness and social isolation are a relatively new topic of interest for academics. However, it is apparent that loneliness and social isolation cut across populations experiencing various health and social issues. More experiential research is needed to evidence the effectiveness of peer support in these areas with both adults and adolescents. Emerging areas of interest include the use of technology to deliver interventions and the use of technology to facilitate peer support implementation with populations difficult to reach.

Peer support may be a promising social intervention to help those experiencing loneliness and social isolation associated with a range of health conditions. However, further research needs to be undertaken in this emerging area of practice.

Loneliness and social isolation are of increasing concern. To the best of the authors’ knowledge, this is the first scoping review conducted in this area

The research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers social identity as a mediating factor into the research framework.

This paper collected users' activity data of 142,191 ideas submitted by 76,647 users from the MIUI community between October 2010 and May 2018 via Python software, and data were processed using Stata 16.0.

The results indicate that knowledge feedback and social feedback positively influence users' knowledge contribution (quantity and quality), respectively. User's cognitive identity positively mediates the relationship between peer feedback and knowledge contribution behavior, affective identity positively mediates the relationship between peer feedback and knowledge contribution behavior, while evaluative identity positively mediates the relationship between peer feedback and knowledge contribution quality, but there is no mediating effect between peer feedback and knowledge contribution quantity.

This study advances knowledge management by highlighting peer feedback on online innovation communities. By demonstrating the significant mediating effect of social identity, this study empirically clarifies the relationships of peer feedback (knowledge feedback and social feedback) to specific dimensions of knowledge contribution, thereby providing managerial guidance to the online innovation community on incentivizing and managing user interaction to foster the innovation development of firms.

The purpose of this study is to address the mixed predictions about the relationship between general skills training and turnover intention of early career graduates by examining the mediating mechanisms of perceived organizational support (POS) and job satisfaction (JS) through which this relationship might be enacted. This study adopts organizational support theory as the guiding theory and examines the concept of POS as critical for predicting and explaining relationships in the conceptual framework.

A quantitative survey method was used on a sample of 147 Chinese early career graduate trainees. Analysis was conducted using partial least square-based structural equation modelling (PLS-SEM).

The main finding is that participation in general skills training (PGST) does not directly impact turnover intention, rather POS is a mechanism through which this negative relationship operates. This study also found significant evidence for serial mediation by POS on PGST and its relationship with turnover intention. Importantly, JS only has an effect on turnover intention when in the presence of serial mediation by POS.

Cross-sectional study of a small survey sample. Nonetheless, the findings have major implications for research theories on the relationship of general skills training with employee turnover.

PGST does not directly impact turnover intention, rather POS is a mechanism through which this negative relationship operates.

This research emphasizes the important role of POS in the relationship between early career graduate trainees’ PGST and their turnover intentions.

This paper explores how financial technology (FinTech) organisations address poverty-related challenges when providing digital financial services. Employing the conceptual foundation of the liability of poorness (i.e. literacy gaps, a scarcity mindset, intense non-business pressures and a lack of financial slack), this paper explores the innovative strategies that FinTechs use to address these liabilities and promote entrepreneurship.

The paper uses detailed case data collected from three FinTech organisations operating in one South Asian country.

FinTech organisations' innovative strategies reflect a combination of “high touch” (human) vs “low touch” (digital) solutions. All the organisations simplified internal systems or procedures to accommodate customers. The degree to which the three organisations adopted each of the identified strategies shows an emerging typology of FinTechs; that is, innovators with high digital interactions, a mix of digital-human interactions and high human interactions.

The paper develops a typology which categorises FinTech innovative strategies. The typology highlights strategies pro-poor FinTechs use and explains the types of entrepreneurial support innovative organisations provide for their customers. Both the typology and the innovative strategies contribute to enhanced financial inclusion and entrepreneurial promotion amongst the poor.

The originality of the paper comes from its focus on FinTechs' innovative pro-poor strategies. Existing studies typically address the technology-side of innovations. In contrast, this paper combines innovative strategies with the liability of poorness to identify issues associated with financial inclusion.

The Metaverse is an immersive virtual world where individuals interact with each other using an avatar. The Metaverse is promised to offer several potentials for different sectors. While the Metaverse promotes innovative interaction between individuals (e.g. learners), there is a scarcity of knowledge on what influences its acceptance and use in higher educational institutions (HEIs), particularly in developing countries. Thus, this paper aims to identify the factors that affect the users' intentions toward Metaverse technology for educational purposes in the HEIs in Jordan.

A study model was created by incorporating variables from the unified theory of acceptance and use of technology (UTAUT) (performance expectancy, PE; effort expectancy, EE; social influence, SI; and facilitating conditions, FC) and information system success (ISS) model (user satisfaction, SAT; system quality, SQ; service quality, SVQ and information quality, IQ) with perceived curiosity (PC) and hedonic gratification (HG) constructs. Both PC and HG were added as context-related factors that could contribute to improving the applicability of UTAUT and ISS to a wide range of technology use contexts. Data were gathered from 441 Jordanian university students using an online questionnaire.

The analysis of the structural model revealed that users' behavioural intentions toward using Metaverse were significantly affected by user satisfaction (SAT), performance expectancy (PE), facilitating conditions (FC) and hedonic gratification (HG). Also, information quality (IQ) and services quality (SVQ) were revealed to have a significant influence on user satisfaction. Likewise, the results illustrated a significant impact of systems quality (SQ), information quality (IQ) and service quality (SVQ) on PE. Lastly, a significant effect of PC on the EE factor was found.

This study will shed light on a number of practical implications for developers, designers, service providers and decision-makers supporting the acceptance and adoption of the Metaverse technology in the educational context. Also, it will contribute to developing the right strategies, and Metaverse content which will draw the attention of learners.

As per the surveyed literature and the researcher's prior knowledge, this is one of the first studies that integrate the UTAUT model, ISS model and two contextual factors (PC and HG) besides testing the proposed model in a developing country (Jordan). This paper is one of the few in which the individuals' acceptance behaviour of Metaverse technology was examined in the HEIs context.

This study investigates whether the underrepresentation of women in executive-level roles within the supply chain management (SCM) field is justified or the result of gender injustices. The analysis examines if there is a gender compensation gap within executive-level SCM roles and whether performance differences or other observable factors explain disparities.

Publicly reported executive compensation and financial data are merged to empirically test if gender differences exist and investigate whether the underrepresentation of women in executive-level SCM roles is unjust.

Women occupy only 6.29% of the positions in the sample of 447 SCM executives. Unlike prior studies, we find that women executives receive higher compensation. The analysis does not identify observable factors explaining the limited inclusion of women in top-level roles, suggesting that gender injustices are prevalent in SCM.

This study only considers observable factors and cannot conclusively determine if discrimination is occurring. The low level of inclusion of women in executive roles suggests that gender injustice is intrinsic within the SCM profession. These findings will hopefully motivate firms to undertake transformative actions that result in outcomes that advance gender equity, ultimately leading to social justice for female SCM executives.

The use of social justice and feminist theories, a focus on SCM roles, and an empirical methodology utilizing objective measures represents a novel approach to investigating gender discrimination in SCM organizations, complementing prior survey-based studies.