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Fairness concerns in the supply chain management have recently caught much attention in the OM research community. The combined effect of fairness and competition on supply chain coordination and the interplay between them, however, have yet to be thoroughly examined.

The authors study a multiplayer supply chain with one supplier and two competing retailers with fairness concerns by a three-player Stackelberg game model. This theoretical study provides equilibrium solutions under different ranges of fairness and competition combinations. Besides theoretical analysis, the authors also conduct standard economic experiments and estimate structural parameters using experimental data.

The authors find that a simple wholesale price can coordinate the whole supply chain with certain conditions of fairness and competition. Moreover, although fairness concerns always decrease the wholesale price and increase retailers' profit share, downstream competition weakens such effects and decreases downstream players' market share. The experiments confirm the existence of fairness concerns and the interaction of competition and fairness, as shown in the theoretical analysis.

A more comprehensive model with both distributional and peer-induced fairness considered could generate better insights in the interactive impact of competition and fairness. Moreover, the authors followed the previous channel competition literature and modeled the demand with linear demand function which makes the game decisions trackable in closed form solution. A more general demand function could result in different solutions and thus new insights.

The authors’ work provides a comprehensive theoretical study of the interaction between fairness concerns and competition and clarifies the in-depth connection between the effects of competition and fairness concerns in the literature.

This paper aims to explore the effect of fairness concerns on supply chain members' optimal decisions and profits, to compare their profits under different policies, and to investigate the impact of each policy on members, consumers, and the environment with fairness concerns.

Considering government policies and fairness concerns in recycling management, this paper develops five recycling and remanufacturing decision models (anarchy policy model, reward-penalty mechanism model, recycling investment subsidies model, government tax model, and fund subsidy system model). In each model, the manufacturer and the online platform form the Stackelberg game. This research further discusses comprehensive environmental benefits and consumer surplus under five scenarios.

First, the fairness concerns of the online platform inhibit the recovery rate and supply chain members' profit while increasing the platform's utility. Second, fairness concerns increase the profit gap between the manufacturer and online platform, and the higher the degree of fairness concerns, the greater the profit gap; however, the four policies reduce the profit gap. Finally, when there are fairness concerns, environmental taxes damage the interests of supply chain members and consumers, but are most beneficial to the environment; recycling investment subsidies are on the contrary; the fund subsidy system depends on the relative size of the treatment fund and the subsidy fund.

This paper provides useful insights on how to regulate government policy to improve supply chain management with fairness concerns.

Reasonable risk sharing is the key to the smooth implementation of infrastructure public-private partnership (PPP) projects and the optimization of benefit distribution among the participants. This study aims to explore the risk redistribution ratio between the government and the private sector under different degree of fairness concern.

Renegotiation is a mechanism to provide flexibility and make up for incompleteness of PPP contracts. However, the threshold value of risk redistribution ratio and negotiation cost are not explicitly considered in previous studies. In addition, these studies do not consider the influence of the fairness concern psychology on the negotiation process. To address these gaps, based on risk-income equilibrium analysis, this paper established the bargaining optimization model of PPP projects renegotiation considering the fairness concerns of the negotiating parties. Furthermore, this study analyzed the influence of fairness concern degree on negotiation thresholds, negotiation results, and negotiation incomes under three scenarios.

The results showed that excessive focus on the fairness of incomes may exclude the risk redistribution ratio that is most beneficial to project incomes from the negotiation threshold. Moreover, the increase in the fairness concerns of negotiating parties can reduce the negotiation success period, but the net income may not necessarily be improved.

The main contribution of this paper is to propose a new risk renegotiation methodology based on the risk-income equilibrium analysis, which is helpful to develop risk management strategies in the construction field. The research results can provide government with reference about renegotiation in decision making and provide theoretical support for the practice of PPP renegotiation.

The development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.

This paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.

Our findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.

Few studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.

This study considers a contracting problem between a fairness concerned entrepreneur (EN) and a fair-neutral venture capitalist (VC) to explore the effects of asymmetry, agency conflicts and fairness concerns.

The authors construct the model by assuming the EN's risk aversion degree is private information, which is more realistic but ignored in most studies. Under the principal–agent framework, the authors solve the VC's optimal contracting models by identifying the ranges of feasible solution, where the optimal solutions of these models are explicit and nicely reconcile the “private equity” puzzle. Moreover, validity of the optimal solutions is verified by numerical simulations.

In accordance with empirical evidence, information asymmetry lowers the optimal equity share that the VC provides to EN but raises EN's profit due to lower effort disutility and information rent. Moreover, the authors find that the fairness concerns is beneficial for the EN, where it not only increases the EN's optimal equity share, but also enhances the certainty equivalence of the EN's utility regarding its profit. Relative to the benchmark model where the EN's risk aversion degree is common knowledge, the EN's efforts recommended by the optimal contract is less sensitive to the EN's fairness concerns degree when the EN does not actually announce its risk aversion degree.

First, the authors incorporate asymmetry to study a two-period contracting problem and explore how it affects the equity shares allocated to the contractual parties. Second, the authors incorporate fairness concerns and analyze its effect regarding the decision-makings and profits.

The purpose of this paper is to investigate how fairness evaluations are constructed in a B2B context.

This paper conducts a field study of Air Greenland and its internal and external customers based on strong structuration theory (Stones, 2005). The authors employ context and conduct analysis to analyze how fairness evaluations emerge across four levels of structuration.

The paper finds that fairness evaluations emerge as a result of the interaction between external institutional pressures, agents' internal structures, and situated reflection and outcomes. The construction of fairness evaluations was embedded in contradictory institutional structures, where groups of actors constructed different evaluations of fair profits, procedures and prices. Actors furthermore worked on changing position-practice relations which shifted relations, external structures and affected outcomes and fairness evaluations.

This paper offers a conceptualization of embedded agency as emerging across the four levels of structuration. This contributes to debates in strong structuration theory through conceptualizing and analyzing how actors may be both be constrained and oriented by structures while reflexively adapting structures across the four levels of structuration. The paper extends extant pricing fairness research by illustrating how actors' construction of fairness flexibly develop fairness evaluations while responding to legitimacy and societal demands, including the needs of particular customer groups.

The purpose of this research is to examine how a change in team dynamics impacts an individual's motivation to engage in helping behavior and operational performance.

An online vignette experiment and a hybrid discrete event and agent-based simulation model are used.

Study findings demonstrate how a non-core worker's perception of team dynamics influence engagement in helping behavior and system performance.

This study provides a further understanding on how team members react to changes in team processes. This study theorizes on how an individual team member responds to fairness concerns. This study also advances our understanding of the critical importance of helping behavior in a retail logistics setting. This research illustrates how the theory of strategic core and procedural justice literature can be adopted to explain team dynamics in supply chain management.

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.

Under the pressure of dynamic business environments, firms in the banking and finance industry are gradually embracing Fintech, such as robo-advisors, as part of their digital transformation process. While robo-advisory services are expected to witness lucrative growth, challenges persist in the current landscape where most consumers are unready to adopt and even resist the new service. The study aims to investigate resistance to robo-advisors through the privacy and justice perspective. The human-like attributes are modeled as the antecedents to perceived justice, followed by the subsequent outcomes of privacy concerns, perceived intrusiveness and resistance.

An online survey was conducted to gather consumer responses about their perceptions of robo-advisors. Two hundred valid questionnaires were collected and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The results revealed that (1) perceived anthropomorphism and perceived autonomy are the positive determinants of perceived justice, (2) perceived justice negatively impacts privacy concerns and perceived intrusiveness and (3) privacy concerns and perceived intrusiveness positively influence resistance to robo-advisors.

The present study contributes to robo-advisory service research by applying a privacy and justice perspective to explain consumer resistance to robo-advisors, thereby complementing past studies that focused on the technology acceptance paradigm. The study also offers practical implications for mitigating resistance to robo-advisors.

This study aims to analyse the ethical implications associated with the development of artificial intelligence (AI) technologies and to examine the potential ethical ramifications of AI technologies.

This study undertakes a thorough examination of existing academic literature pertaining to the ethical considerations surrounding AI. Additionally, it conducts in-depth interviews with individuals to explore the potential benefits and drawbacks of AI technology operating as autonomous ethical agents. A total of 20 semi-structured interviews were conducted, and the data were transcribed using grounded theory methodology.

The study asserts the importance of fostering an ethical environment in the progress of AI and suggests potential avenues for further investigation in the field of AI ethics. The study finds privacy and security, bias and fairness, trust and reliability, transparency and human–AI interactions as major ethical concerns.

The implications of the study are far-reaching and span across various domains, including policy development, design of AI systems, establishment of trust, education and training, public awareness and further research. Notwithstanding the potential biases inherent in purposive sampling, the constantly evolving landscape of AI ethics and the challenge of extrapolating findings to all AI applications and contexts, limitations may still manifest.

The novelty of the study is attributed to its comprehensive methodology, which encompasses a wide range of stakeholder perspectives on the ethical implications of AI in the corporate sector. The ultimate goal is to promote the development of AI systems that exhibit responsibility, transparency and accountability.