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To date, to the best of the authors’ knowledge, the use of implicit measures in the service research domain is limited. This paper aims to introduce implicit measures and explain why, or for what purpose, they are worthwhile to consider; how these measures can be used; and when and where implicit measures merit the service researcher’s consideration.

To gain an understanding of how implicit measures could benefit service research, three promising implicit measures are discussed, namely, the implicit association test, the affect misattribution procedure and the propositional evaluation paradigm. More specifically, this paper delves into how implicit measures can support service research, focusing on three focal service topics, namely, technology, affective processes including customer experience and service employees.

This paper demonstrates how implicit measures can investigate paramount service-related subjects. Additionally, it provides essential methodological “need-to-knows” for assessing others’ work with implicit measures and/or for starting your own use of them.

This paper introduces when and why to consider integrating implicit measures in service research, along with a roadmap on how to get started.

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.

Digital innovation requires organizations to reconfigure their information technology infrastructure (ITI) to cultivate creativity and implement fast experimentation. This research inquiries into ITI generativity, an emerging concept demoting a critical ITI capability for organizational digital innovation. More specifically, it conceptualizes ITI generativity across two dimensions—namely, systems and applications infrastructure (SAI) generativity and data analytics infrastructure (DAI) generativity—and examines their respective social and technical antecedents and their impact on digital innovation.

This research formulates a theoretical model to investigate the social and technical antecedents along with innovation outcomes of ITI generativity. To test this model and its associated hypotheses, a survey was administered to IT professionals possessing knowledge of their organization's IT architecture and digital innovation performance. The dataset, comprising responses from 140 organizations, was analyzed using the partial least squares technique.

Results reveal that both dimensions of ITI generativity contribute to digital innovation performance, with the effect of DAI generativity being more pronounced. In addition, SAI and DAI generativities are driven by social and technical factors within an organization. More specifically, SAI generativity is positively associated with the usage of a digital application services platform and IT human resources, whereas DAI generativity is positively linked to the usage of a data analytics services platform, data analytics services usability and data analytics human resources.

This research contributes to the literature on digital innovation by introducing ITI generativity as a crucial ITI capability and deciphering its role in digital innovation. It also offers useful insights and guidance for practitioners on how to build ITIs to achieve better digital innovation performance.

While, supply chain resilience (SCRES) continues to be a dominant topic in both academic and business literature and has gained more attention recently, there is limited knowledge on SCRES capabilities specific to business functions. The purpose of this paper is to identify and investigate capabilities shared between supply, operations and logistics that are most important for SCRES.

To address this gap, the authors followed a multi-method research approach. First, the authors used the grounded theory method to generate a theoretical framework based on interviews with 51 managers from five companies in automotive SCs. Next, the authors empirically validated the framework using a survey of 340 SC professionals from the manufacturing industry.

Five significant capabilities emerged from the qualitative study; all were significant in empirical validation. This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES.

This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES. In addition, the findings of this research help managers better allocate resources among significant capabilities.

The research objective is rooted in the principle of providing new insights and a collective perspective regarded as Supply Chain Quality Management 4.0 (SCQM4.0), an integration of all three concepts – Industrie 4.0, quality management and supply chain management.

A thorough review of historical developments and existing integration trends among Industrie 4.0, quality and supply chain approaches along with future research directions outlined in the main literature, was conducted. This work establishes a knowledge base on research topics, issues of integration and synergies with a concentration on the potential for deeper integration with supply chain operations.

This article not only introduced the term SCQM4.0 and proposed a definition for it, but also contributed a novel conceptual SCQM4.0 framework and evolutionary perspective through the SCQM4.0 maturation model. Stemming from the gaps, opportunities and benefits identified in the literature, the conceptual SCQM4.0 framework builds on the high potential of the SCQM4.0 constructs to achieve successful governance and implementation. Under the SCQM4.0 maturity framework, it provides a clear evolutionary path underpinned by the SCQM4.0 constructs.

In the effort toward a successful SCQM4.0 implementation, the proposed SCQM4.0 maturity frameworks will be a “road map” for businesses to develop fully and actively in supply chain operations, bringing quality products and services for the company. Industry practitioners are encouraged to perform gap analysis and direct the implementation of the strategy to establish an excellent SCQM4.0.

This is one of the pioneering studies integrating all three concepts (Industrie 4.0, quality management and supply chain management), connecting the link and discovering more synergies to support the future development of more holistic management models. SCQM4.0 is expected to expand on the strengths, synergies and established relationships between technologies 4.0, quality and supply chain, contributing toward a pioneering and quality supply chain.

This study aims to investigate and classify the hospital logistics key performance indicators (KPIs) using the context of public hospitals in remote areas.

The public hospitals in northern Thailand were selected for the case study. The questionnaire was developed and used to collect data from hospital logistics experts. Then, the analytic hierarchy process (AHP) method was used to evaluate the hospital logistics KPIs in each dimension.

This research found that the procurement management dimension is ranked highest. Information and technology management is the last rank in the hospital logistics KPIs used for public hospitals in remote areas.

The public hospitals located in northern Thailand were selected for the case study. Fuzzy multi-criteria decision-making methods can be used to reduce the vagueness of the values.

The results from this study can be a guideline for hospitals to improve the efficiency of their logistics operations.

The decision-makers in the hospital can use these results to improve the hospital’s logistics performance in the future, which could help increase the service level and the safety of the patients.

The hospital logistics KPIs were revised, and the crucial KPIs were prioritized for improving the hospital logistics using the AHP method.

In light of the recent changes in the internal audit (IA) landscape, the role of auditors has undergone a significant transformation. This paper aims to investigate the effects of applying Lean Six Sigma (LSS) techniques on the effectiveness and efficiency of IA.

The study used a quantitative approach, surveying Iranian internal auditors with a sample size of 384 participants. Data analysis involved confirmatory factor analysis and structural equation modeling.

The analyses demonstrate a significant association between LSS application and IA effectiveness and efficiency. In addition, an exploratory analysis indicates that the application of LSS techniques by less experienced internal auditors had a reverse effect on IA function quality as a component of IA competency. However, IA motivation factors, including education and position, did not mediate the impact of LSS on IA effectiveness and efficiency.

This study was conducted with Iranian internal auditors, which may limit the generalizability of the findings to other countries. However, the primary academic implication of this research lies in its novel perspective on emphasizing the concept of continuous improvement in IA through the use of LSS techniques. By focusing on the need for internal auditors to add value to the business in new ways, this research contributes to the literature on IA quality.

This study has significant implications for the effective management of IA departments. By promoting the application of LSS techniques in IA, lean auditing is enhanced, and IA can create value by improving the quality of its functions. Moreover, IA regulators can benefit from this study as it emphasizes providing guidance and training on LSS techniques to enhance IA skills.

This research is pioneering in applying LSS methodology to enhance the effectiveness and efficiency of internal auditing. It also considers the integration of lean thinking into current audit practices, making it unique and valuable in internal auditing research.

General Data Protection Regulation (GDPR) of the European Union (EU) was passed to protect data privacy. Though the GDPR intended to address issues related to data privacy in the EU, it created an extra-territorial effect through Articles 3, 45 and 46. Extra-territorial effect refers to the application or the effect of local laws and regulations in another country. Lawmakers around the globe passed or intensified their efforts to pass laws to have personal data privacy covered so that they meet the adequacy requirement under Articles 45–46 of GDPR while providing comprehensive legislation locally. This study aims to analyze the Malaysian and Saudi Arabian legislation on health data privacy and their adequacy in meeting GDPR data privacy protection requirements.

The research used a systematic literature review, legal content analysis and comparative analysis to critically analyze the health data protection in Malaysia and Saudi Arabia in comparison with GDPR and to see the adequacy of health data protection that could meet the requirement of EU data transfer requirement.

The finding suggested that the private sector is better regulated in Malaysia than the public sector. Saudi Arabia has some general laws to cover health data privacy in both public and private sector organizations until the newly passed data protection law is implemented in 2024. The finding also suggested that the Personal Data Protection Act 2010 of Malaysia and the Personal Data Protection Law 2022 of Saudi Arabia could be considered “adequate” under GDPR.

The research would be able to identify the key principles that could identify the adequacy of the laws about health data in Malaysia and Saudi Arabia as there is a dearth of literature in this area. This will help to propose suggestions to improve the laws concerning health data protection so that various stakeholders can benefit from it.

This study draws on Organisation Justice Theory and Social Exchange Theory to examine the effects of the performance appraisal process (PAP) on employee commitment (ECO) via a serial mediation of performance appraisal outcome (PAO) and employee reward (ERE).

Survey data were collected from a sample of 363 academics across UK Higher Education Institutions (HEIs), including post-1992 and pre-1992 universities. We tested our hypotheses using partial least squares structural equation modeling (PLS-SEM) with a bias-corrected bootstrapping method.

The findings show that the PAP positively influences ECO and ERE. PAO and ERE mediate the relationship between the PAP and ECO. However, no significant relationship was found between PAO and ECO.

This study has significant implications for HEIs as it underscores the need for managers to ensure the clarity and accuracy of the PAP and to structure rewards to reflect employees’ efforts, considering they affect ECO.

This study contributes to the current debate on performance appraisal by highlighting the extent to which employees’ commitment to an organisation depends on the PAP, PAO and reward.

This paper aims to examine the relationship between the implementation of soft lean practices and organizational resilience development in the service sector.

A mixed-methods explanatory design that relied on two sequential and complementary phases was adopted. In the first phase, a quantitative analysis was performed based on data collected from practitioners from service organizations, allowing the identification of the significance of this relationship. In the second phase, the authors used semi-structured interviews with experts to qualitatively assess how this relationship occurs.

Findings indicated that soft lean practices are positively associated with organizational resilience, although the extent of their relationships varies depending on the resilience ability under analysis. Interviews with experts also provided specific details on how such relationships occur, adding insights to the numerical results.

This study provides a deeper understanding of the implications of lean management, specifically concerning the support of soft lean practices to develop organizational resilience. Additionally, the identification of this relationship (and how it occurs) allows service organizations to deploy human-related strategies to promote broader adoption of certain soft lean practices. As socio-cultural changes are usually time-consuming, anticipating these organizational resilience needs may result in competitive advantages in the face of disruptive events.