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This paper explores how blockchain technology can enhance information quality within project management information systems (PMIS), thereby positively affecting knowledge management, learning capabilities and project portfolio success.

We employ a literature review and a theory-based approach to develop a conceptual framework and set of propositions that integrate key principles from blockchain technology, project management and dynamic capabilities theory. Subsequently, a focus group is conducted to refine our propositions, providing insights and examples demonstrating the potential value of blockchain in project management.

The findings suggest that blockchain significantly impacts the information quality within PMIS. This improvement in information quality enhances traceability, reliability and security of project data, facilitating better decision-making and governance. The focus group revealed blockchain’s benefits in managing confidential data and streamlining knowledge sharing processes, ultimately contributing to project portfolio success.

This research offers a novel conceptual framework and original insights into the application of blockchain in project management, particularly within the context of Industry 4.0, paving the way for future research on digital transformation in project management.

The prevalence of independent contractors in the US workforce is growing. This research examines the social environment and career outcomes of labor and employment arbitrators, a unique profession of high-skilled and high-status independent contractors who play a significant role in facilitating organizational justice. Previous research has focused on the employment relationships that independent contractors have with hiring organizations and the characteristics of individuals who become independent contractors; however, little attention has been given to how relational factors influence the career outcomes of high-skilled independent contractors or how such influences differ by gender. Building upon theories of social networks and unequal network returns (UNR), our study investigates the informal social relationships among arbitrators, the association between interpersonal relationship patterns and arbitrators’ career success, and how these associations vary based on gender.

A social network survey is used to collect the social networks, attitudes and fee information of 407 labor and employment arbitrators working in North America. A multi-level regression analysis was used to examine the proposed relationships among social networks, gender and career outcomes of the arbitrators.

We discovered that occupying a central position within advice networks is positively associated with occupational satisfaction. On the other hand, having strong ties is associated with achieving high employment arbitration fees. Notably, we found that the advantages of strong ties for arbitration fees are comparatively weak for female arbitrators relative to their male counterparts.

This research examines the relationship between social networks and career outcomes for independent contractors in the unique context of arbitrators. It further highlights inequalities experienced by female arbitrators in a male-dominated profession where their social networks offer fewer rewards relative to their male counterparts.

A healthcare unit's effectiveness largely depends on how well its interprofessional teams work together. Unfortunately, the strategies used to improve these teams often lack substance. This study analyzed these strategies and found a performance gap.

This study took a unique mixed-method approach, systematically reviewing both qualitative and quantitative studies that identified strategies to enhance interprofessional teams in healthcare units. To gauge the effectiveness of these strategies, the researcher utilized an Importance-Performance Analysis (IPA) in four specialized clinical training centers in Hamadan province, Iran. The analysis of the IPA involved 35 experts from these centers as the statistical population.

Based on a systematic review, there are seven categories: contextual, strategic, communication, organizational, individual, Human Resources Management (HRM), and environmental for promoting interprofessional teams with a total of 36 sub-indicator. Based on the IPA, the HRM aspect shows the most extensive performance gap. The individual and organizational aspects fall under resource wastage, and the environmental aspect is within the indifferent zone. Also, some critical sub-indicators, such as incentives/rewards, roles and responsibilities, financial resources, team-initiated innovation, the culture of respect, partner resources, humility, data availability, set expectations, and team availability, are in the weak areas.

This research has identified critical areas for improvement in promoting teamwork in clinical training centers through a comprehensive gap analysis. It also presents practical policy solutions to address these weak points, providing a clear roadmap for enhancing interprofessional teams in healthcare units.

Improving teamwork in healthcare can be challenging, but it is possible with proper strategies and tools. One of the highlights of the recent study was the combination of systematic review studies with IPA to identify areas for improving interprofessional teamwork in clinical training centers.

This study aims to determine the current state of research on sustainability in the context of human resource management (HRM) practices adopted by small and medium-sized enterprises (SMEs), identify the most important gaps and propose an agenda for future studies.

Through a systematic literature review (SLR), this study comprehensively examines the relevant literature on sustainability-related aspects of HRM in SMEs. It includes descriptive and thematic analyses of 29 research articles published in high-ranked academic journals selected from 506 records retrieved from four major databases (Scopus, Web of Science, ScienceDirect and EBSCOhost).

The findings suggest a growing interest in sustainability-related HRM in SMEs after 2020. Notably, most studies focused on green and social sustainability concerns, with limited attention to the triple bottom line (TBL) perspective. A detailed examination revealed variations among the three streams of research in terms of methodology, location of studies, nature of sustainability-HRM linkage and placement of HRM practices in research models. Despite these differences, positive effects of HRM practices on sustainability integration seem evident, including impacts on employee competences, behaviors and company-level outcomes.

This article is the first to systematically review the literature on the sustainability-HRM nexus specifically for SMEs. It contributes by identifying thematic clusters, methodological trends, contextual aspects and outcomes of sustainability-HRM integration, thereby laying the groundwork for future research.

The paper aims to empirically test a framework to predict the desire and intention to engage with an elective health-care procedure and implement a methodology to test the anticipated positive and negative emotions in hedonic adaptation to an elective procedure.

Two studies in USA and Australia (N = 1,200) confirmed the psychometric properties of the key constructs under the chemical peel condition. Two further studies in the USA and Australia (N = 1,100) explored the research question and hypotheses in the adapted model of goal-directed behaviour under the Botox condition. A survey was self-administered to online panels who had previously engaged in such elective procedures.

The findings highlighted the pragmatic implications for communication and activation strategies to safeguard consumer interests and retain their loyalty.

From the authors’ best understanding, neither a methodology nor a theoretical framework exists to explore hedonic adaptation to recurring engagement with elective health care. A methodology and theoretical framework will highlight the mood states and factors that predict desire and intention to engage. This can advance the research on hedonic adaptation and decision-making and offer pragmatic suggestions for communication and activation strategies to safeguard consumer interests and retain their loyalty.

This paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.

The IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.

Simulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.

This method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.

Unmanned aerial vehicles (UAVs), known for their exceptional flexibility and maneuverability, have become an integral part of mobile edge computing systems in edge networks. This paper aims to minimize system costs within a communication cycle. To this end, this paper has developed a model for task offloading in UAV-assisted edge networks under dynamic channel conditions. This study seeks to efficiently execute task offloading while satisfying UAV energy constraints, and validates the effectiveness of the proposed method through performance comparisons with other similar algorithms.

To address this issue, this paper proposes a task offloading and trajectory optimization algorithm using deep deterministic policy gradient, which jointly optimizes Internet of Things (IoT) device scheduling, power distribution, task offloading and UAV flight trajectory to minimize system costs.

The analysis of simulation results indicates that this algorithm achieves lower redundancy compared to others, along with reductions in task size by 22.8%, flight time by 34.5%, number of IoT devices by 11.8%, UAV computing power by 25.35% and the required cycle for per-bit tasks by 33.6%.

A multi-objective optimization problem is established under dynamic channel conditions, and the effectiveness of this approach is validated.

Social live streaming services (SLSS) have infused gamification into interface design and feature applications. Firms adopt gamification mechanisms to win customer loyalty in the live streaming and SLSS markets. Based on the mechanics-dynamics-aesthetics (MDA) framework and uses and gratifications 2.0 theory (UGT 2.0), this study aims to investigate the effects of game mechanics (mechanics) on enjoyment and user retention (aesthetics) through rewards and social interaction (dynamics) in the context of SLSS.

This study used an online survey via Google Forms, SurveyCake and social media platforms like Facebook, Instagram and Line to collect data from 232 SLSS users in Taiwan. Partial least squares structural equation modeling (PLS-SEM) was adopted to analyze the data.

The results validated the relationships between game mechanics and dynamic elements (rewards and social interaction) that triggered aesthetic elements (enjoyment feelings) among users. In addition, users experienced a sense of enjoyment that led to usage retention when using the gamified SLSS. Further, this study found enjoyment crucial for users to stay interactive with gamified services.

Driven by UGT 2.0, this study closed the gaps by integrating the MDA framework into the SLSS context and better understanding how game mechanics are connected to rewards and social interaction, leading to enjoyment and user retention when using SLSS. This study provides fresh insights into gamification-oriented SLSS practices. It offers significant theoretical and managerial implications and provides guidelines for SLSS platform operators on fostering user retention.

The purpose of this paper is to understand how those involved in executive pay determination in large publicly quoted UK businesses see the role of diversity within remuneration committees (Remcos) as enabling the input of different perspectives, which can enhance their decision-making and potentially improve pay outcomes.

Qualitative, semi-structured interviews were undertaken with 18 high-profile major-enterprise decision-makers and their advisers, i.e. non-executive directors (NEDs) serving Remcos, institutional investors, executive pay consultants and internal human resources (HR) reward specialists, together with data from three focus groups with 10 further reward management practitioners.

Remco members recognise the benefits of social category/demographic diversity but say the likelihood of increasing this is low, given talent pipeline issues. The widening of value diversity is considered problematic for Remcos’ functioning. Informational diversity is used as a proxy for social category/demographic diversity to improve Remcos’ decision-making on executive pay. While the inclusion of members from wider social networks is recognised as potentially bringing a different informational perspective, the social character of Remcos, reflecting their elite nature and experience of wealth, appears ingrained.

Our original contribution is to extend the application of upper echelons theory in the context of Remco decision-making to explain why members do not welcome widening informational diversity by appointing people from different social networks who lack value similarity. Instead, by drawing views from employees, HR acts as a proxy for social network informational diversity. The elite, upper-echelons nature of Remco appointments remains unchanged and team functioning is not disrupted.

The model of pay-for-knowledge incentivizes individuals with financial rewards for sharing their expertise, facilitating a transactional exchange between knowledge providers (sellers) and seekers (buyers). While this model is effective in promoting paid contributions, its influence on free knowledge exchanges remains ambiguous, creating uncertainty about its overall impact on platform knowledge ecosystems. This study aims to explore the mechanim of how knowledge payment influences free knowledge contribution. Based on relational signaling theory, this study posits that a buyer’s payment for knowledge acts as a positive relational signal in the buyer–seller relationship and examines how the signaling effect varies across different social contexts through attribution theory.

This paper empirically tests the hypotheses by analyzing a data set comprising 630 instances from 359 unique knowledge sellers on Zhihu, a prominent knowledge-sharing platform in China. This paper use zero-inflated negative binomial models to conduct this analysis.

The findings reveal that when buyers pay for knowledge, this action positively influences sellers to contribute knowledge for free. However, the strength of this influence is moderated by the platform’s social functions: appreciation feedback tends to weaken this effect, while social network ties enhance it.

Prior research has predominantly focused on the financial incentives of pay-for-knowledge and its spillover effects on unpaid users’ activities. This study shifts the focus to the social dimensions of pay-for-knowledge, arguing that buyer-initiated knowledge payments signal buyers’ commitment to foster reciprocal relationships with sellers. It expands the literature on the relationship between knowledge payment and contribution, moving beyond financial incentives to include social factors, thus enriching our understanding of the interplay between paid and free knowledge activities. Additionally, the empirical evidence supports the efficacy of pay-for-knowledge in promoting both free and paid contributions within knowledge-sharing platforms.