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This paper aims to explore the significance of resource sharing in business to capture new market opportunities and securing competitive advantages. Firms enter strategic alliances (SAs), especially for designing new products and to overcome challenges in today’s fast changing environment. Research projects have dealt with the creation of SAs, however without concrete referencing the impact on selected supply chain resources. Furthermore, academia rather focused on elaborating the advantages and disadvantages of SAs and how this affects structural changes in the organization than examining the effects on supply chain complexity and performance.

The authors collected and triangulated a multi-industry data set containing primary data coming from more than 200 experts in the field of supply chain management along and secondary data coming from Refinitiv’s joint ventures (JVs) and SA database and IR solutions’ database for annual reports. The data is evaluated in three empirical settings using binomial testing and structural equation modeling.

The results show that nonequity SAs and JVs have varying degrees of impact on supply chain resources due to differences in the scope of the partnership. This has a negative impact on the complexity of the supply chain, with the creation of a JV leading to greater complexity than the creation of a nonequity SA. Furthermore, the findings prove that complexity negatively impacts overall supply chain performance. In addition, this study elaborates that increased management capabilities are needed to exploit the potentials of SAs and sheds light on hurdles that must be overcome within the supply network when forming a partnership. Finally, the authors give practical implications on how organizations can cope with increasing complexity to lower the risk of poor supply chain performance.

This study investigates occurring challenges when establishing nonequity SAs or JVs and how this affects their supply chain by examining supply networks in terms of complexity and performance.

Food manufacturing companies which are essential for national economies, need to attach importance to the adoption of both the lean manufacturing (LM) operational excellence methodology and the Industry I4.0 (I4.0) technologies that empower LM to achieve operational improvement. This study aims to focus on the Greek food manufacturing companies and determine the degree of implementation of LM practices and I4.0 technologies and the impact of I4.0 on LM.

A survey was conducted based on a structured questionnaire which included items reflecting LM practices and I4.0 technologies. A sample of Greek food manufacturing companies were approached and 102 of them fully completed the questionnaire. Descriptive statistics were applied to determine the degree of implementation of LM practices and I4.0 technologies, while the impact of I4.0 on LM was determined through the linear regression analysis.

The degree of implementation of LM practices in the responding food manufacturing companies is high, while the degree of implementation of I4.0 technologies is low to medium. The findings also support a significant and positive impact of I4.0 on LM.

The small size of the sample of the responding Greek food manufacturing companies, the subjective character of the data collected and the cross-sectional nature of the study, constitute the main limitations of the study. Based on these limitations, further studies can be designed.

The present study findings can guide the managers of the food manufacturing companies to further increase the degree of implementation of LM practices through adopting I4.0 technologies. Therefore, they can improve quality, eliminate waste, survive and be more competitive in the current difficult business environment. Academics can also benefit from the present study, given that it provides the LM practices and I4.0 technologies that can be further tested and validated in the food sector.

To the best of the authors’ knowledge, this is the first study that focuses on LM and I4.0 in the Greek food manufacturing companies operating in a business environment where the crises of finance, energy and the Covid-19 pandemic dominate.

While the COVID-19 pandemic has impacted the construction industry, it is still unclear from prior studies about adequately positioning the quality assurance (QA) for the post-pandemic era and future pandemics, especially cross-border construction logistics and supply chain (Cb-CLSC). Thus, this study aims to develop a managerial framework to position the QA of Cb-CLSC during pandemics and post-pandemics by taking lessons from how COVID-19 has impacted the existing QA systems and has been managed successfully.

This is achieved pragmatically through an embedded mixed-method design involving a literature review, survey and interview from experts within the Hong Kong SAR–Mainland China links, typically known as the world’s factory. The design is further integrated with the partial least squares structural equation modelling (PLS-SEM) approach.

The study revealed 10 critical managerial practices (MPs) to position the QA to be adequate for the post-pandemic and during future pandemics, with the top three including “strict observance of government regulations (MP1)”, “planning ahead the period of quality assurance with the quarantine days in host countries (MP6)” and “modification of contract to cater for uncertainties (MP4)”. This attained a relatively good percentage agreement of 53% between the industry and academia. However, the top four MPs regarded as very effective include “implementing digital collaborative inspections with subcontractors and trades (MP8)”, “implementing a digital centralized document and issue management system (MP7)”, “strict observance to government regulations, including vaccination of workers, social distancing, use of prescribed nose masks, etc. (MP1)” and “planning ahead the period of quality assurance with the quarantine days in host countries (MP6)”. Two underlying components of the MPs were revealed as policy-process (PP)-related practices and people-technology-process (PTP)-related practices, and these can be modelled into a managerial framework capable of effectively positioning the QA to be adequate during pandemics through to the post-pandemic era.

The findings of this study depicted significant theoretical and practical contributions to the proactive management of QA activities during pandemics through to the post-pandemic era. It could empower organisations to pay attention to smartly and innovatively balancing people, processes, pandemic policy and technology to inform decisions to effectively position the QA for the post-pandemic era and survive the risks of future pandemics.

The study contributes to the body of knowledge in that it develops a managerial framework to position the QA of Cb-CLSC during pandemics and post-pandemics by taking lessons from how COVID-19 has impacted the existing QA systems and has been managed successfully. It is original research with invaluable primary data in the form of surveys and interviews from experts within the Hong Kong SAR–Mainland China links, typically known as the world’s factory.

Gazelle companies are characterized by rapid growth in a short time. Identifying the determinants of this exponential expansion is important as these firms have a significant impact on the economy. They generate increased employment and investment by investors interested in new opportunities. Previous studies have failed to reach a consensus about what fosters high growth in gazelle companies as each firm’s geographical, political and economic context is different. The present research uses cognitive mapping and interpretive structural modeling (ISM) to overcome the limitations of prior investigations and identify factors that can potentially accelerate growth in gazelle companies.

Two sessions were held with an expert panel with knowledge about and experience with these firms. In the first session, data were collected to create a group cognitive map, while the second meeting comprised ISM-based analyses of the high-growth determinants identified and the causal relationships between them. A final consolidation session was held to discuss the results with two members of the Committee for Central Region Coordination and Development (i.e. Comissão de Coordenação e Desenvolvimento Regional do Centro – a public entity that grants gazelle awards in Portugal).

The analysis system created was tested, and the results demonstrate that the dual methodology used can increase our understanding of the dynamics of high-growth determinants and lead to more informed and potentially better evaluations of gazelle companies. Indeed, once high-growth determinants in gazelle companies are understood, this information can help other firms implement the same business model to achieve similarly rapid growth. The strengths and shortcomings of this new structured analysis model are also analyzed.

The authors know of no prior work reporting the integrated use of cognitive mapping and ISM in this study context.

While COVID-19 mitigation measures (CMMs) aided in steady recovery during the pandemic, they also impeded movement across economies/borders, affecting quality assurance (QA) of Cross-border Construction Logistics and Supply Chain (Cb-CLSC). However, prior studies on the pandemic in the construction project industry have not revealed how CMMs have impacted QA. Thus, this study aims to evaluate the impact of the CMMs on the QA of Cb-CLSC.

This is achieved by adopting an embedded mixed-method approach involving a desk literature review and engaging 150 experts from different economies across the globe using expert surveys, and results verified via semi-structured expert interviews. Structural equation modelling-based multiple regression analysis (SEM-MRA) was integrated to examine the impact of the CMMs on the QA, along with descriptive and content analysis.

The study confirmed that CMMs have not only impacted the QA negatively but also influenced the positioning of the QA for the post-pandemic era and probably to survive the risks of future pandemics. Among all the identified CMMs, the top three critical measures include “lockdown (CMM2)”, “use of personal protective equipment, such as nose masks, disinfects, etc. (CMM5)”, and “electronic/virtual meetings (CMM7)”. However, CMM5 possesses the highest contributory power to form CMM in impacting the QA, and this can be regarded as largely positive by strengthening health and safety management systems. Its negative impact lies with the project cost increment and the inconveniences of using nose and face masks.

This study provides a better understanding to construction practitioners and policy makers on how the pandemic policies, i.e. CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics.

The study contributes to knowledge in that it provides a better understanding of how the pandemic policies, such as CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics. This area of study has been given limited attention among prior studies during the pandemic.

This study aims to address this unexplored influence of international assignment types on the development, transfer and utilization of career capital by assigned repatriates from host to home country. In response to existing literature gap, it aligns with the need for qualitative case studies that delve into threats to the self-reinforcement of repatriates' career capital.

By mean of a qualitative case study, this paper deepens understanding of linkages and processes in career capital development and clarify the interplay between individual interpretations of career actions and the organizational context in which they unfold. Nineteen qualitative interviews with assigned repatriates explored the impact of exposure to new career contexts.

This study provides valuable insights into the complex dynamics of career capital development and transfer during international assignments. It elucidates the impact of career context on assigned repatriates' career capital, emphasizing challenges in career capital generation, dispersion and absorption within multinational enterprises. It contributes to understanding the complexities of (new) managerial capacity development by revealing varied effects that international assignments can exert on individuals' immediate competencies and career capital.

If the assigned expatriate/repatriate’s understanding of the firm’s assignment motive, and their own motive (understanding/reason) for the assignment corresponds then expectations of outcomes can be better managed. Organizations otherwise run the risk of perpetuating inequities in the career development opportunities of employees.

Studies on career capital emphasize its qualities or examine different globally mobile employee types. Yet there's a gap in understanding how the type of assignment impacts career capital development, transfer and utilization. This research fills this void by investigating the international transfer of career capital from host to home country specifically for assigned repatriates.

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.

Studies have so far focused on learning in organizations, factors affecting learning, learning effectiveness and so on but the concept of learning in a hybrid work arrangement is yet unexplored. The purpose of this study is to measure the perception of faculty members in higher education institutions towards learning in a hybrid work arrangement and also to measure the differences of perception towards hybrid work arrangement based on employees’ gender and organization type.

The data was collected from a sample of 390 faculty members composing of Assistant Professors, Associate Professors and Professors, purposely chosen from two of the premier higher education institutions (one private and one public) located in Punjab, India. A self-structured questionnaire was administered to the faculty members who are working on a regular basis and have minimum of two years of work experience with the chosen university. For analysing the collected data exploratory factor analysis and other descriptive statistics have been applied.

The findings of the survey show that in terms of gender differences, it is the female employees who are more satisfied with different aspects of hybrid/remote work arrangement as compared to male employees. In regard to organizational differences in the perception towards learning in a hybrid work arrangement it is found that public university employees have a more positive attitude so far as individual factors are concerned, but in terms of organizational factors, it is the private university that is scoring better than the public university.

The study is limited to only two higher education institutions, and its findings to be applicable in all higher education institutions, further studies may be required on a larger canvas. Future studies may be undertaken using advanced statistical tools like structural equation modelling to explore various variables associated with learning in a hybrid work arrangement.

Applicability of hybrid work arrangement is very high in higher education institutions and to the best of the authors’ knowledge, this is the first study which adds to the literature on perception of employees towards organizational learning in a hybrid work arrangement.

The implementation of control systems allows marketing managers to improve operational decisions and organizational results. This paper aims to identify the relationship between control combinations and organizational results and analyze the relationships between the variables attributed to the marketing managers and with marketing control combinations. Decisions involving marketing control combine formal and informal mechanisms and generate control systems that have a favorable relationship with organizational results.

The paper is based on 301 cross-sectional surveys among marketing managers. The classification procedure based on metric distance was implemented to identify the marketing control combinations. A hierarchical cluster analysis was carried out with perceptions about formal and informal control, to validate the control combination classifications. Finally, a discriminant analysis and ANOVA test were carried out for exploring factors associated with the managers. The data analysis was supported by IBM SPSS Statistics 24 software.

The authors found evidence that, when managers perceive high-control systems, the perception of non-financial and financial results is always better, but the presence of high-clan control also returns optimal results. In addition, the manager's satisfaction levels and work motivation are higher with high control systems than with other control systems.

This study contributes to the existing knowledge by providing a broader empirical basis to extend conceptual frameworks about marketing control combinations that emerge in practice.

企業設置營銷控制系統來進行營銷控制,這可讓市場經理能改善其營運決策和組織成果。本文擬確定控制合併與組織成果的關係;本文亦擬分析涉及市場經理的變數與營銷控制合併的關係。涉及營銷控制的決策會結合正式和非正式的機制,而這些決策會帶來與組織成果有良性關係的控制系統。

本研究乃基於對市場經理進行的301項橫斷調查。研究人員實施基於度量距離的分類程式,來確定營銷控制合併;為了證實有關的控制合併分類是正確的,研究人員就對正式控制和非正式控制的觀感和看法、進行了階層式分群法分析;最後,研究人員進行了判別分析和變異數分析 (ANOVA), 以探索與經理有關聯的因素。有關的數據分析得到IBM公司的SPSS (統計產品與服務解決方案) Statistics 24 (統計軟體) 的支持。

我們證實了、若主管感知高控制的系統,其對非財務結果和財務結果的看法必會較好的,但高社群控制亦會帶來最佳的結果。我們亦證實了高控制系統,較其它控制系統,更能提高主管的滿意程度和工作動機。

本研究提供了一個更廣闊的經驗基礎,以擴展涉及在實踐中出現的營銷控制合併的概念框架,就此,本研究豐富了這方面的知識。

Organizations widely adopt knowledge management (KM) to develop and promote technologies and improve business effectiveness. Analytics can aid in KM, further augmenting company performance and decision-making. There has been significant research in the domain of analytics in KM in the past decade. Therefore, this paper aims to examine the current body of literature on the adoption of analytics in KM by offering prominent themes and laying out a research path for future research endeavors in the field of KM analytics.

A comprehensive analysis was conducted on a collection of 123 articles sourced from the Scopus database. The research has used a Latent Dirichlet Allocation methodology for topic modeling and content analysis to discover prominent themes in the literature.

The KM analytics literature is categorized into three clusters of research – KM analytics for optimizing business processes, KM analytics in the industrial context and KM analytics and social media.

Systematizing the literature on KM and analytics has received very minimal attention. The KM analytics view has been examined using complementary topic modeling techniques, including machine-based algorithms, to enable a more reliable, systematic, thorough and objective mapping of this developing field of research.