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Original equipment manufacturers and other manufacturing companies rely on the delivery performance of their upstream suppliers to maintain a steady production process. However, supplier capacity uncertainty and delayed delivery often poses a major concern to manufacturers to carry out their production plan as per the desired schedules. The purpose of this paper is to develop a decision model that can improve the delivery performance of suppliers to minimise fluctuations in the supply quantity and the delivery time and thus maximising the performance of the supply chain.

The authors studied a single manufacturer – single supplier supply chain considering supplier uncertain capacity allocation and uncertain time of delivery. Mathematical models are developed to capture expected profit of manufacturer and supplier under this uncertain allocation and delivery behaviour of supplier. A reward–penalty mechanism is proposed to minimise delivery quantity and time of delivery fluctuations from the supplier. Further, an order-fulfilment heuristic based on delivery probability is developed to modify the order quantity which can maximise the probability of a successful deliveries from the supplier.

Analytical results reveal that the proposed reward–penalty mechanism improves the supplier delivery consistency. This consistent delivery performance helps the manufacturer to maintain a steady production schedule and high market share. Modified ordering schedule developed using proposed probability-based heuristic improves the success probability of delivery from the supplier.

Practitioners can benefit from the findings of this study to comprehend how contracts and ordering policy can improve the supplier delivery performance in a manufacturing supply chain.

This paper improves the supplier delivery performance considering both the uncertain capacity allocation and uncertain time of delivery.

A growing body of research finds that gig economy platforms use gamification to enhance managerial control. Focusing on technologically mediated forms of gamification, this literature reveals how platforms mobilize gig workers’ work effort by making the labour process resemble a game. This chapter contends that this tech-centric scholarship fails to fully capture the historical continuities between contemporary and much older occurrences of game-playing at work. Informed by interviews and participatory observations at two food delivery platforms in Amsterdam, I document how these platforms’ piece wage system gives rise to a workplace dynamic in which severely underpaid delivery couriers continuously employ game strategies to maximize their gig income. Reminiscent of observations from the early shop floor ethnographies of the manufacturing industry, I show that the game of gig income maximization operates as an indirect modality of control by (re)aligning the interests of couriers with the interests of capital and by individualizing and depoliticizing couriers’ overall low wage level. I argue that the new, algorithmic technologies expand and intensify the much older forms of gamified control by infusing the organizational activities of shift and task allocation with the logic of the piece wage game and by increasing the possibilities for interaction, direct feedback and immersion. My study contributes to the literature on gamification in the gig economy by interweaving it with the classic observations derived from the manufacturing industry and by developing a conceptualization of gamification in which both capital and labour exercise agency.

This study aims to explain how negative workplace interactions are formed by the application of a performance management system (PMS).

The study draws from unique in-depth interviews with service workers who resigned from an accounting shared service centre (SSC), discussing the reasons behind the resignations. Following an abductive approach, organisational justice theory is used to analyse the service workers' perceptions of negative interactions and to link the negative interactions to the use of the PMS.

The findings suggest that negative workplace interactions are characterised by cost consciousness, inequality and competitiveness. These interactions are attributed to the use of a PMS in the centre and are related to perceptions of distributive, procedural and interactional injustice.

Managers and leaders of shared service–type organisations should not rely on PMSs as an all-encompassing solution; instead, they should acknowledge the fairness of the use of PMSs. Moreover, HR professionals should choose and train employees to apply PMSs fairly. Fairness is important in work allocation, resourcing, monitoring, giving feedback, recognising good performance, promotion and interaction between peers.

This study contributes to the literature by taking an overall perspective on PMSs to analyse and explain the unintended negative consequences of a PMS in a highly scripted and monitored work environment that is usually considered appropriate for such a system's use. Through the analysis, the study highlights pitfalls in the use of a PMS and the importance of interactional injustice not only between but also within organisational levels.

The purpose of this paper is to study the following two issues regarding blockchain crowdsourcing. First, to design smart contracts with lower consumption to meet the needs of blockchain crowdsourcing services and also need to design better interaction modes to further reduce the cost of blockchain crowdsourcing services. Second, to design an effective privacy protection mechanism to protect user privacy while still providing high-quality crowdsourcing services for location-sensitive multiskilled mobile space crowdsourcing scenarios and blockchain exposure issues.

This paper proposes a blockchain-based privacy-preserving crowdsourcing model for multiskill mobile spaces. The model in this paper uses the zero-knowledge proof method to make the requester believe that the user is within a certain location without the user providing specific location information, thereby protecting the user’s location information and other privacy. In addition, through off-chain calculation and on-chain verification methods, gas consumption is also optimized.

This study deployed the model on Ethereum for testing. This study found that the privacy protection is feasible and the gas optimization is obvious.

This study designed a mobile space crowdsourcing based on a zero-knowledge proof privacy protection mechanism and optimized gas consumption.

The question of how work motivation affects team members' tacit and explicit knowledge sharing has long puzzled organizational scholars. In this chapter, the quality of team–member exchange (TMX) is presented as one potential mechanism.

Key variables in the model are intrinsic and extrinsic work motivation, interactional and distributive organizational justice, tacit and explicit knowledge sharing, relationship-oriented and task-oriented TMX, organizational rules, organizational climate for trust. Separate models are developed for intrinsic versus tacit knowledge sharing.

While explicit knowledge sharing depends upon extrinsic factors such as extrinsic work motivation, task oriented TMX, distributive justice perceptions, and organizational rules, tacit knowledge sharing is dependent upon intrinsic factors such as intrinsic work motivation, relationship-oriented TMX, interactive justice perceptions, and perceptions of an organizational climate for trust.

This is the first model to provide a useful framework that should enable scholars to research the factors underlying the relationships between individual employee motivation and both explicit and tacit organizational knowledge sharing.

This paper examines whether target returns act as specific goals that impact risk-taking when individuals make investment decisions.

Using an experimental setting, the authors assign either a low or a high target return to participants and ask them to make independent investment decisions as the risk-free rate fluctuates around their target return and, for some of them, becomes negative.

Building on cumulative prospect theory, the authors find that the prevailing reference point of participants is the target return, regardless of the level of the risk-free rate. This result still holds even when the risk-free rate is negative, suggesting that (1) the target return drives risk-taking more than does a zero-threshold and (2) negative rates are limited as a tool to stimulate appetites for risk. In a follow-up study, the authors show that these conclusions remain valid when the target return is endogenously determined.

The authors' original approach, which pioneers the use of target returns in both the positive and negative interest rate contexts, provides insightful results about the “reach for yield” among regular people.

My way or the highway: A stronger partner in humanitarian relief collaboration often seeks control over its weaker partners by leveraging diverse power tactics that may be non-coercive or coercive in nature. In this backdrop, this research accentuates the perspective of weaker partners to understand how a weaker partner drives collaborative synergy under power tactics. Weaker partner in the collaborative dyad resembles the humanitarian organization (HO) who is less capable in terms of access to resources. This partner is further dependent on the stronger HO's directives to participate in the relief work.

Based on social exchange theory (SET), a collaborative dyad in humanitarian relief work is visualized from the perspectives of power and power disparity. In terms of power, mediated power tactics such as legal, coercive and reward powers are considered. Disparity recognizes the presence of a stronger and a weaker partner. Set also magnifies the insight on conflict and trust that can respectively hamper and improve the synergy between partners. In total, 295 executives representing self-reported weaker HOs are surveyed.

Legal power, as experienced by the weaker partner, bears a positive impact over collaborative performance to improve collaborative synergy. Coercive power shows a negative impact. Reward power again bears a positive impact. Coercion can complicate collaborative synergy by establishing conflicts. Yet, the trust of weaker partner on stronger HO positively moderates the negative impact of conflict over collaborative performance.

This research invokes the view of power disparity to explain synergy in inter-organizational collaboration from the perspective of weaker partners.

We argue that a fundamental issue regarding how to search and how to switch between different cognitive modes lies in the decision rules that influence the dynamics of learning and exploration. We examine the search logics underlying these decision rules and propose conceptual prompts that can be applied mentally or computationally to aid managers’ decision-making.

By applying Multi-Armed Bandit (MAB) modeling to simulate agents’ interaction with dynamic environments, we compared the patterns and performance of selected MAB algorithms under different configurations of environmental conditions.

We develop three conceptual prompts. First, the simple heuristic-based exploration strategy works well in conditions of low environmental variability and few alternatives. Second, an exploration strategy that combines simple and de-biasing heuristics is suitable for most dynamic and complex decision environments. Third, the uncertainty-based exploration strategy is more applicable in the condition of high environmental unpredictability as it can more effectively recognize deviated patterns.

This study contributes to emerging research on using algorithms to develop novel concepts and combining heuristics and algorithmic intelligence in strategic decision-making.

This study offers insights that there are different possibilities for exploration strategies for managers to apply conceptually and that the adaptability of cognitive-distant search may be underestimated in turbulent environments.

Drawing on insights from machine learning and cognitive psychology research, we demonstrate the fitness of different exploration strategies in different dynamic environmental configurations by comparing the different search logics that underlie the three MAB algorithms.