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Scholars and practitioners alike wish to understand what makes workplace conflict beneficial or injurious to, for example, performance and satisfaction. The authors focus on parties’ personal experience of the conflict, which is complementary to studying conflict issues (i.e. task- or relationship-related conflict). Although many authors discuss the personal experience of conflict, which the authors will refer to as conflict personalization, different definitions are used, leading to conceptual vagueness. Therefore, the purpose of this paper is to develop an integrative definition of the concept of conflict personalization.

The authors conducted a systematic literature review to collect definitions and conceptualizations from 41 publications. The subsequent thematic analysis revealed four building blocks that were used to develop an integrative definition of conflict personalization.

The authors developed the following definition: Conflict personalization is the negative affective as well as cognitive reaction to the self being threatened and/or in danger as a result of a social interaction about perceived incompatibilities.

The integrative definition of this study enables the development of a measurement instrument to assess personalization during workplace conflict, paving the way for developing effective research-based interventions.

Conceptual vagueness hampers theoretical development, empirical research and the development of effective interventions. Although the importance of conflict personalization is mentioned within the field of workplace conflict, it has not been empirically studied yet. This paper can serve as the basis for future research in which conflict issue and personal experience are separated.

The increasing financial burden and complexity of health-care services, exacerbated by factors such as an ageing population and the rise of chronic conditions, necessitate comprehensive and integrated care approaches. While co-created service design has proven valuable in transforming some service industries, its application to the health-care industry is not well understood. This study aims to examine how health consumers are involved in health-care service co-creation.

The study searched 11 electronic databases for peer-reviewed articles published between 2010 and 2019. Additionally, hand searches of reference lists from included studies, Google^© citation searches and searches for grey literature were conducted. The Whittemore and Knafl integrative framework guided the systematic review, and Callahan’s 6 Ws framework was used to extract data from the included articles, facilitating comparisons.

The authors identified 21 articles, mainly from the UK, North America and Australia. Despite the need for more research, findings reveal limited and geographically narrow empirical studies with restricted theory and method applications. From these findings, the authors constructed a conceptual model to enhance nuanced understanding.

This study offers four contributions. First, it introduces the Health Service Design Transformation Model for Comprehensive Consumer Co-Creation, illustrating health consumers’ multifaceted roles in shaping services. Second, consumer vulnerabilities in co-creating services are identified, linked to diverse consumer groups, power dynamics and decision complexity. Third, this study suggests broadening participant inclusion may enhance consumer-centricity, inclusivity and innovation in service design. Finally, the research agenda explores consumer experiences, organizational dynamics, value outcomes and co-creation theory for health-care service advancement.

From a psychosocial perspective, this study aims to understand the impact of psychosocial safety climate (PSC) on the intent to stay of construction workers and provides practical recommendations for construction enterprises to retain construction workers.

This study proposes the conceptual framework explained by the conservation of resources (COR) theory and develops a mediation model of “PSC – job satisfaction – intent to stay” within the framework supported by the stimulus–organism–response (SOR) model. Then, a questionnaire survey of 489 construction workers in Guangzhou was conducted and structural equation modeling (SEM) analysis was performed on the data collected.

Results show that PSC has a significant and positive effect on job satisfaction and intent to stay. In addition, job satisfaction partially mediates the effect of PSC on intent to stay. Hence, the theoretical model of “PSC – job satisfaction – intent to stay” has been empirically tested and supported.

This study is the first to investigate the effect of PSC on intent to stay and enriches the research on the retention of construction workers. The COR theory explains well the mechanism of PSC influence on intent to stay, thus expanding its application to the construction field. Moreover, this study provides practical recommendations for construction enterprises to retain workers so as to build a stable and productive workforce.

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.