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Algorithms are widely used to manage various activities in the gig economy. Online car-hailing platforms, such as Uber and Lyft, are exemplary embodiments of such algorithmic management, where drivers are managed by algorithms for task allocation, work monitoring and performance evaluation. Despite employing substantially, the platforms face the challenge of maintaining and fostering drivers' work engagement. Thus, this study aims to examine how the algorithmic management of online car-hailing platforms affects drivers' work engagement.

Drawing on the transactional theory of stress, the authors examined the effects of algorithmic monitoring and fairness on online car-hailing drivers' work engagement and revealed the mediation effects of challenge-hindrance appraisals. Based on survey data collected from 364 drivers, the authors' hypotheses were examined using partial least squares structural equation modeling (PLS-SEM). The authors also applied path comparison analyses to further compare the effects of algorithmic monitoring and fairness on the two types of appraisals.

This study finds that online car-hailing drivers' challenge-hindrance appraisals mediate the relationship between algorithmic management characteristics and work engagement. Algorithmic monitoring positively affects both challenge and hindrance appraisals in online car-hailing drivers. However, algorithmic fairness promotes challenge appraisal and reduces hindrance appraisal. Consequently, challenge and hindrance appraisals lead to higher and lower work engagement, respectively. Further, the additional path comparison analysis showed that the hindering effect of algorithmic monitoring exceeds its challenging effect, and the challenge-promoting effect of algorithmic fairness is greater than the algorithm's hindrance-reducing effect.

This paper reveals the underlying mechanisms concerning how algorithmic monitoring and fairness affect online car-hailing drivers' work engagement and fills the gap in the research on algorithmic management in the context of online car-hailing platforms. The authors' findings also provide practical guidance for online car-hailing platforms on how to improve the platforms' algorithmic management systems.

In the competitive retailing environment, retailers who provide service experiences that stand out from the competition can gain a competitive advantage. Increasingly, an important aspect of the service experience involves product returns, in particular, the fairness of returns policies and procedures. Previous research studies support that interpersonal justice and informational justice relate positively to consumer attitudes and behaviors. In this paper, the authors examine the relative effects of interpersonal justice and informational justice on return satisfaction, positive word-of-mouth (PWOM) and trust. Additionally, the authors examine the moderating effects of returns process convenience and returns policy restrictiveness as indicators of procedural justice.

A scenario-based experiment methodology was used to test the relationships of interest.

Results support that the effects of interpersonal justice on the outcome variables are stronger than the effects of informational justice. There is also support for a moderating effect of returns process convenience on the relationships between interpersonal justice and each outcome variable, as well as partial support for the moderating effect of returns policy restrictiveness on the relationship between interpersonal justice and PWOM.

The research extends previous work on the effects of justice on customer outcomes. Results support the importance of retailers treating customers with fairness during the returns experience and further support the benefits of providing a convenient returns experience.

Collaborating with consumers during new product development can provide companies with significant benefits and competitive advantages. Although several studies have been conducted on the design of co-innovation platforms, there is still a need for a more comprehensive understanding of the co-innovation phenomenon. To address this gap, this research aims to identify the critical success factors of co-innovation platforms and provide an extensive analysis of the variables that determine their effectiveness.

This study presents a systematic literature review of co-innovation platforms based on an analysis of 89 articles published in 50 scholarly journals in the disciplines of information systems, marketing and business, covering the years from 2006 to 2022.

The review synthesizes the current state of scientific knowledge and groups prior studies thematically as critical success factors of co-innovation platforms. As a result, eight success factors have been identified in terms of quantity and quality of contributions. These factors include product involvement, perceived fairness, sense of community, interactive environment, employee involvement, participant diversity, assessment structure and task design.

The study consolidates existing research about the critical success of co-innovation platforms. It also provides a research framework that incorporates a diverse set of variables that can be used to assess co-innovation performance in future studies.

Organizational justice and its impact on employee commitment have received a lot of attention these days. The objective of this study is to see the effect of job satisfaction as a mediator in the relationship between organizational justice and employee commitment. Also, the role of academic rank as a moderator in the model is probed.

A moderating mediation structural equation model was used for randomly collected cross-section data on 285 employees from public universities in Ethiopia. Necessary condition analysis (NCA) was employed to check the importance of the variables. The Gaussian copula approach was used to check endogeneity in the structural model.

NCA confirms the importance of organizational justice and employee satisfaction as the independent variables. The Gaussian copula approach reveals no endogeneity problems in the structural model. The results supported the partial mediating role of job satisfaction in organizational justice and academic staff’s commitment. Moreover, though staff rank is not a necessary condition, it plays the role of moderator in the relationship between academic staff’s job satisfaction and commitment.

This paper affirms that public institutions must implement fair initiatives and procedures to promote academic staff satisfaction and commitment.

This is the first study to check the job rank as a moderator in the model comprising organization justice, employee commitment and satisfaction. Moreover, application of NCA and Gaussian copula adds to methodological innovation.

The authors analysed fairness as an antecedent of trust to understand how trust building can be actively managed to facilitate collaboration in buyer–supplier relationships.

A case study was employed to buyer–supplier relationships of five organic food companies from three different sectors. The research was developed with data collected in 2022 through qualitative research interviews and analysed using a structured content analysis. A practitioner workshop served to complement findings and confirm the interpretation of data by discussing interview results from a managerial perspective.

A conceptual model based on organisational trust and justice theory was developed to examine causal relations between fairness and trust. Findings show that perceived distributional, procedural and interactional fairness mutually interact with the perceived trustworthiness of business partners and that both contribute to building personal, organisational and institutional trust. Qualitative data support the conceptual model and show that trust is a valuable relational resource that affects relationship quality and the willingness to collaborate and to take risks in times of uncertainty.

High trust levels developed through positive fairness perceptions can lower risk perceptions whilst increasing the willingness to collaborate in supply chain relationships. This can help deal with market uncertainties.

Through the lens of organisational trust and justice theory, this study extends the literature on collaboration in supply chains by including a comprehensive view on the formation of trust in business-to-business (B2B) relationships.

This study aims to conceptualize the relationship of perceived artificial intelligence (AI) credibility with consumer-AI experiences. With the widespread deployment of AI in marketing and services, consumer-AI experiences are common and an emerging research area in marketing. Various factors affecting consumer-AI experiences have been studied, but one crucial factor – perceived AI credibility is relatively underexplored which the authors aim to envision and conceptualize.

This study employs a conceptual development approach to propose relationships among constructs, supported by 34 semi-structured consumer interviews.

This study defines AI credibility using source credibility theory (SCT). The conceptual framework of this study shows how perceived AI credibility positively affects four consumer-AI experiences: (1) data capture, (2) classification, (3) delegation, and (4) social interaction. Perceived justice is proposed to mediate this effect. Improved consumer-AI experiences can elicit favorable consumer outcomes toward AI-enabled offerings, such as the intention to share data, follow recommendations, delegate tasks, and interact more. Individual and contextual moderators limit the positive effect of perceived AI credibility on consumer-AI experiences.

This study contributes to the emerging research on AI credibility and consumer-AI experiences that may improve consumer-AI experiences. This study offers a comprehensive model with consequences, mechanism, and moderators to guide future research.

The authors guide marketers with ways to improve the four consumer-AI experiences by enhancing consumers' perceived AI credibility.

This study uses SCT to define AI credibility and takes a justice theory perspective to develop the conceptual framework.

Justice perceptions describe an individual's evaluation of whether decisions or actions are fair or unfair. These perceptions are important because they affect individual attitudes and behaviors in different situations. Family firms develop and implement governance policies and structures (i.e., governance systems) to diminish the problems that can arise from the overlap between the business, the family, and the ownership systems of a firm. Governance systems help family firms have a clear structure of accountability and a clear understanding of the rights and responsibilities that family and non-family members have toward the family enterprise. Research on governance to date has focused on the practices and policies that exist and their effects on the family firm. However, in the governance context, individual perceptions are important because they are likely to affect the attitudes that family and other members have toward the family enterprise and the likelihood that they will follow the different policies when they are implemented. This chapter takes a receiver perspective to explain how individuals create justice perceptions based on governance mechanisms and the effects of these perceptions. The goal is to understand how we can use this information when developing governance practices in family firms.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

This study aims to examine the perceptions and evaluations of Muslim COVID-19 survivors and health workers regarding the halal, business and ethical attributes of hospitals during their interactions related to COVID-19 treatment.

Descriptive qualitative research with semi-structured online interviews was used to gather insights from COVID-19 survivors and health workers who treated COVID-19 patients. The findings were then compared with existing literature on hospital services and Sharia attributes.

The study found that patients and health-care workers in hospitals are concerned about whether the hospital follows Sharia law, the quality of health-care and hospital services and the ethical conduct of hospital staff. This is especially true during the COVID-19 pandemic, when patients are more anxious about religious conduct and the afterlife.

Hospitals need to address halal attributes in all aspects of their services for Muslim patients and business attributes such as standard health-care quality, service quality and ethical attributes. Participants indicated that when these needs are met, they are more likely to revisit the hospital and recommend it to others.

This study contributes to understanding the expectations of Muslim patients regarding hospital services that meet Islamic ethical and business requirements. Using the COVID-19 pandemic as a case study broadens the understanding of how to better serve Muslim customers.

Based on the social penetration theory and affect theory of social exchange, this study aims to examine the relationship between authentic leadership (AL) and workplace loneliness (WL), as well as the mediating effect of interactional justice (IJ) on this relationship during the COVID-19 pandemic in the US higher education sector.

An online, self-administrated questionnaire was distributed to full-time employees working at higher education institutions in the USA. A total of 464 employees participated in the survey, with structural equation modeling being used to analyze the data.

The outcomes provide evidence that AL is positively related to IJ, whereas the latter is negatively associated with WL. Moreover, IJ fully mediates the relationship between AL and WL. Overall, the findings underline the importance of IJ in affecting employee WL.

The outcomes provide valuable insights for higher education leaders and HR professionals in reducing employee WL. In particular to this end, it is recommended that organizations focus on improving employee IJ and AL perceptions. Furthermore, higher education organizations need to select and promote leaders who exhibit IJ behaviors and AL characteristics. In addition, organizations could offer IJ and AL training to their current leaders.

This study contributes to the limited literature on WL by offering a unique research model that examines IJ as a mediating variable between AL and WL. In addition, it adds to the literature by investigating WL in the context of US higher education sector, which is an understudied area in this research context.