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The purpose of the study was to maximize team members' collaboration and develop relationships in a newly formed team to engage with internal and external partners to achieve open innovation (OI) in product development. The authors examine the role of collaborative human resource management (HRM) and relational leadership (RL) in this process.

The study took a two-stage qualitative methodological approach to examine relational leadership as it emerges in a newly formed cross-functional team at a large German fashion house. In stage one, 10 interviews were conducted with members of the new project team over three months and in stage two six external knowledge exchange partners were interviewed.

Collaborative HRM promotes greater social exchange, trust and commitment of team members internal and external to the organization to support the emergence of RL, which is critical for OI. The authors found that collaborative HRM practices such as team-based recruitment, team-based training, team-based performance management with rewards systems and job design support the emergence of RL. Moreover, RL practices such as congruence and commitment towards team goals subsequently promoted the development of knowledge sourcing and sharing (KSS) to support OI.

The study is the first to demonstrate how collaborative HRM enables RL practices to help newly formed teams overcome challenges with achieving KSS to successfully engage with internal and external partners for OI. The authors contribute to HRM theory development of the relationship between HRM and OI by conceptualizing the OI process as a social construction through collaborative HRM and relational leadership.

New product development (NPD) projects are strategically important for firms’ operations but suffer from high failure rates. Leadership is a key factor for project success. However, in contrast to positive project leadership, project managers’ knowledge hiding has received little attention. Drawing on the input-mediator-output (IMO) framework and model of work team resilience, we explored the effect of project managers’ destructive knowledge hiding (i.e. evasive hiding and playing dumb) on project team performance (i.e. efficiency and effectiveness) and the serial indirect effect through team psychological safety and transactive memory systems.

We conducted a time-lagged multiple-sourcing investigation of Chinese high-tech firms and tested the hypotheses using data collected from 105 NPD project teams.

Our findings demonstrated that project managers’ knowledge hiding negatively affects NPD project team performance and indirectly negatively affects transactive memory systems through team psychological safety. Moreover, project managers’ knowledge hiding exerts a negative indirect effect on team performance through team psychological safety and transactive memory systems in serial.

This study contributes to the literature on operations management (OM) by broadening our understanding of the connection between project managers' destructive knowledge hiding and the failure of NPD projects. In providing such insight, it also offers practical guidance for overcoming team-level obstacles arising from project managers' knowledge hiding.

Built asset management processes require a long transition period to collect, edit and update asset conditions information from existing data sets. This paper aims to explore and explain whether and how digital technologies, including asset information model (AIM), Internet of Things (IoT) and blockchain, can enhance asset conditions assessment and lead to better asset management.

Mixed methods are applied to achieve the research objective with a focus in universities. The questionnaire aims to test whether the integration of AIM, IoT and blockchain can enhance asset condition assessment (ACA). Descriptive statistical analysis was applied to the quantitative data. The mean, median, mode, standard deviation, variance, skewness and range of the data group were calculated. Semi-structured interviews were designed to answer how the integration of AIM, IoT and blockchain can enhance the ACA. Quantitative data was analysed to define and explain the essential factors for each sub-hypothesis. Meanwhile, to strengthen the evaluation of the research hypothesis, the researcher also obtained secondary data from the literature review.

The research shows that the integration of AIM, IoT and blockchain strongly influences asset conditions assessment. The integration of AIM, IoT and blockchain can improve the asset monitoring and diagnostics through its life cycle and in different aspects, including financial, physical, functional and sustainability. Moreover, the integration of AIM, IoT and blockchain can enhance cross-functional collaboration to avoid misunderstandings, various barriers and enhance trust, communication and collaboration between the team members. Finally, costs and risk could be reduced, and performance could be increased during the ACA.

The contribution of this study indicated that the integration of AIM, IoT and blockchain application in asset assessment could increase the efficiency, accuracy, stability and flexibility of asset assessment to ensure the reliability of assets and lead to a high-efficiency working environment. More importantly, a key performance indicator for ACA based on the asset information, technology and people experience could be developed gradually.

This study can break the gap between transdisciplinary knowledge to improve the integration of people, technology (AIM, IoT and blockchain) and process value-based ACA in built asset management within universities.

This study aims to offer empirical evidence on how integrated thinking affects the integrated reporting (IR) practice and how integrated thinking originates from board and management involvement, cross-functional integration and integral link between capitals and strategies.

This study is cross-sectional and uses a mixed-method approach. The empirical data for the quantitative approach were collected from the 129 public companies listed on Colombo Stock Exchange in Sri Lanka. The personale responsible for preparing the annual report are selected as the respondents of this study. This study used partial least square modelling to test the hypotheses. The quantitative approach results are triangulated across a qualitative research approach in semi-structural interviews with ten responsible officers of integrated reporting practices.

The central finding of this study is the significant positive relationship between integrated thinking and integrated reporting practice. The qualitative results supported the quantitative findings and show that board and management involvement, cross-functional integration and integral link between capital and strategy enhance the integrated reporting practice. Top management and board management have positive beliefs about the integrated reporting practice; they initiate, encourage, influence, involve and support it. Furthermore, all company departments are involved with the integrated reporting led by the finance department and practice good coordination, communication and collaboration between departments. Moreover, it also evidenced their concern about the linkage between capital and strategy and how they do it in their organisation when practising integrated reporting.

The firms which intend to practice or enhance integrated reporting will be benefited from this study. Hence, this research assists in constructing IT through the direct role of the board and senior leadership, breaking down silos to diffuse IR throughout structures and processes, and concentrating on strategies while managing their capitals and relationships over the long term.

This study provides the initial quantitative empirical evidence on the impact of integrated thinking on integrated reporting practice. To the best of the authors’ knowledge, this study is the first to operationalise both integrated thinking and integrated reporting based on a questionnaire that developed and tested both constructs as higher-order reflective formative and on the relationship between integrated thinking and integrated reporting. The mixed-method approach to examine the relationship between integrated thinking and integrated reporting provides additional insights into the existing literature.

The purpose of this study is to examine tacit knowledge sharing within information systems development (ISD) projects by exploring the combination of social interdependence theory and regulatory focus theory (RFT).

A survey was conducted on 198 ISD professionals to investigate the effect of social interdependence on tacit knowledge sharing. The survey data were analyzed using partial least squares structural equation modeling (PLS-SEM), and the results were discussed.

This study reveals that team members tend to share tacit knowledge in a way characterized by cooperative interdependence, and different patterns of social interdependence have an impact on tacit knowledge sharing. The RFT explains the disparities in attitude toward tacit knowledge sharing. Specifically, individuals with a prevention-focused orientation positively moderate the impact of competitive interdependence on tacit knowledge sharing, while those with a promotion-focused orientation have a negative moderating effect on the effect of competitive interdependence on tacit knowledge sharing. Moreover, promotion-focused individuals negatively moderate the effect of cooperative interdependence on tacit knowledge sharing.

The study identifies important aspects of social interdependence in ISD projects that affect the management of tacit knowledge. Furthermore, the study shows that the influence of cooperative and competitive interdependence on tacit knowledge sharing is moderated by the regulatory focus of an individual, providing new insights into ISD knowledge management.

This study aims to explore the effects of expertise diversity on project efficiency and creativity in health-care project teams.

This study analyzes hierarchical linear models using multi-source data from 50 project teams in a large health-care organization in the USA. This data set includes self-reported survey responses from 274 team members and human resource information for all 515 members across the 50 teams. Expertise diversity is operationalized by professional diversity and positional diversity reflecting two dimensions, domain and level, of the concept of expertise.

This study reveals that professional diversity is negatively related to project efficiency and project creativity, whereas positional diversity is positively related to project efficiency.

Successfully managing a project team of experts within a limited time frame is a challenge for organizations. This study advances the understanding of the double-edged sword effect of expertise diversity on project teams, focusing on professional and positional diversity. It provides important insights for human resource development in terms of the composition of project teams regarding members’ expertise.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.

This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.

Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.

The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.

The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.

The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.

The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.

This study examines the motivational processes of charged behavior and collective efficacy driving interdependence and agency in new product development (NPD) teams and the moderating impact of team risk-taking propensity as affective, cognitive and behavioral social processes support team innovation.

Data were collected from 92 NPD teams engaged in B2C and B2B product and service development. Mediating and moderating effects are examined using partial least squares structural equation modeling, referencing social cognitive and collective agency theories as the research framework.

The analysis validates collective self-efficacy and charged behavior as interdependent motivational–affective processes that align cognitive resources and govern team effort toward innovativeness. Teams' risk-taking propensity regulates behavior, and collective efficacy facilitates self-regulated motivational engagement. Charged behavior cultivates the emotional contagion, team identification, cohesion and adaptation required for team functioning. Team potency fosters cohesiveness, while team learning improves adaptability along the innovation journey. The resulting theory asserts that motivational drivers enhance the interplay between cognitive and behavioral processes.

Managers should consider NPD teams as social systems with a capacity for collective agency nurtured through interdependence, which requires collective efficacy and shared competencies to generate motivational purpose and innovativeness. Managers must remain mindful of teams' risk tolerance as regulating the impact of motivational factors on innovativeness.

This study contributes to research on the motivational–affective drivers of NPD charged behavior and collective efficacy as complementary to cognitive and behavioral processes sustaining team innovativeness.

This paper explores how adaptive organizations, companies capable of continuously adapting their organizational model, dynamically solve the universal problems of organizing.

The authors applied grounded theory to data acquired from six interpretative case studies, collected in two rounds of interviews (15 in total), then completing and validating the study’s evidence through triangulation with several secondary data sources.

In adaptive organizations, polyarchies and intrapreneurial employees are essential to shape the division of labour, leading to high levels of autonomy and empowering individuals and teams, while reducing bureaucracy and hierarchy. In terms of the integration of effort, digital solutions are preferred to social proof in the provision of information, while the authors note that incentives are always geared towards developing strong higher-order dynamic capabilities.

This paper has some limitations that could be addressed in future research, including longitudinal studies to analyse the link between the universal problems of organizing and a company's dynamic capabilities.

Adaptive organizations go beyond tech firms in responding to the universal problems of organizing work by making specific use of digital technologies.

The paper studies how companies should organize themselves so that they continuously adapt to an ever-changing competitive environment.