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Drawing from social exchange theory and a collectivist cultural framework, this study explores the relationship between ethical work climate and organizational citizenship behavior, considering power distance as a potential moderator.

The study used standard scales to obtain data from 244 employees working in various private companies in India. Structural equation modeling was adopted to test the hypotheses using Analysis of Moment Structures (AMOS).

The study results show a significant relationship between ethical climate and organizational citizenship behavior. Ethical work climate influences power distance negatively. However, the results also show that power distance does not serve as a moderator between ethical work climate and organizational citizenship behavior.

Corporate leaders often expect employees to demonstrate organizational citizenship behavior, which is aimed at advancing the organization’s interests and outcomes. This study underscores the necessity for expanding the organizational vision to enhance the ethical work climate. Such an initiative not only promotes improved organizational citizenship behavior but also helps to reduce employees' perceptions of power distance within the organization.

Amid extensive literature rooted in individualistic cultures, our study explores the relationship between ethical work climate and organizational citizenship behavior within a collectivist context. This research uniquely introduces the moderating role of power distance, offering new and distinct insights into this dynamic.

This study introduces a novel approach to preventing construction quality problems by examining the complex interrelations among such issues. Recognizing the overlooked coupling between problems is essential, as it can exacerbate quality issues, triggering chain reactions that compromise project success. The research justifies its focus on these interrelations by highlighting the insufficiency of traditional quality management methods, which often fail to account for interconnected quality problems in the architecture, engineering and construction (AEC) industry.

At the core of this research is the establishment of a knowledge base for construction quality issues, marking a pioneering effort to systematically organize unstructured textual data on construction quality problems and their interconnections. This base serves as a platform for the subsequent application of advanced analytical techniques. Specifically, the study leverages preprocessing, text similarity algorithms and association rule mining to dissect and illuminate the nuanced coupling relationships among construction quality issues, a facet not thoroughly explored in prior research.

The innovative analytical methodology employed here reveals significant insights into the dynamics of construction quality issue coupling. These insights not only deepen the understanding of these complex interactions but also guide the development of targeted intervention strategies. The practical applicability and effectiveness of the proposed approach are demonstrated using selected textual materials as experimental evidence. The findings show that understanding and addressing these couplings can significantly mitigate potential chain reactions of defects, thus enhancing overall project quality.

The originality of this study lies in its threefold contribution: the creation of a dedicated knowledge base for construction quality issues, the application of novel analytical methodologies to decipher coupling relationships and the extension of text analysis techniques to the realm of construction quality problem prevention. Together, these innovations open new avenues for research and practice in construction management, offering a robust framework for the systematic identification and mitigation of quality issues in construction projects.

Globalization and population explosion have worsened postharvest losses (PHL) in developing countries. This study looks to identify numerous controllable variables to reduce these losses and make the fresh produce supply chain more efficient.

The study employs the interpretive structural modelling (ISM) technique to develop a hierarchical model to comprehend the intricate relationships between the variables influencing PHL. These variables are further classified based on the relative levels of importance in terms of their driving and dependence powers.

The findings of this research provide variables for enterprises operating in fresh food supply chains to understand the specific risks that that supply chain faces and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the supply chain to aid implementation of PHL mitigation measures. The study highlights the importance of devising policies, legislation and efforts to regulate and curtail PHL across the global food supply chain.

The efficiency of the food supply chain contributes not only to economic sustainability but also to broader goals such as food security, better utilisation of global resources and sustainability in the supply chain.

It also highlights the significance of well-informed government policies, laws and regulations in successfully controlling and reducing PHL.

This study compares factors contributing to PHL in the fresh produce supply chain and emphasises the stakeholders’ critical role in alleviating these losses. It also highlights the significance of well-informed government policies, laws and regulations in successfully controlling and reducing PHL.

This study investigates how the COVID-19 pandemic, as a unique environmental factor, influences Australian supermarket customers’ satisfaction and behavioural loyalty intentions through contactless self-checkout systems (SCSs). It examines the role of customer perceptions of service quality and vulnerability in shaping these outcomes and explores how customer perceptions of COVID-19 risk moderate these relationships.

Employing the stimulus-organism-response (S-O-R) theoretical framework, this research analyses responses from 428 Australian supermarket customers who use contactless self-checkout systems. The study integrates service quality and customer vulnerability as stimuli, examines their impact on customer satisfaction (the organism) and assesses how these factors influence customers' behavioural loyalty intentions (the response). Additionally, it explores how customer risk perceptions related to COVID-19 act as a moderator within these relationships.

The findings demonstrate that both SCS service quality and customer vulnerability significantly enhance customer satisfaction, positively affecting behavioural loyalty toward the supermarket. Furthermore, the study reveals that higher levels of perceived COVID-19 risk strengthen the impact of customer vulnerability on customer satisfaction and the effect of customer satisfaction on loyalty intentions.

This study contributes to the literature by highlighting the underexplored area of SCS usage and customer perceptions of service quality during an emerging pandemic among Australian consumers. It uniquely combines elements of consumer vulnerability and pandemic-related risk perceptions with traditional service quality metrics to offer new insights into customer behaviour in the retail sector. The study’s insights are valuable for supermarket management and marketing practices, particularly in adapting to and capitalizing on changes in consumer behaviour in response to global crises.

Student engagement is a multifaceted concept that encompasses various dimensions that significantly influence students and their learning journey. This study aims to explore the extent of engagement among management students outside the confines of the classroom, specifically focusing on their engagement with the campus and community and assessing the outcomes resulting from this engagement.

The literature review provided the basis for developing a student engagement framework, focusing on campus and community engagement and their outcomes. Established scales measured these variables through surveys administered to 386 UG and PG management students. In-depth analysis using PLS-SEM technique revealed the interplay of variables, beyond demographic and descriptive examinations.

The study found that campus and community engagement fosters a sense of responsibility. Campus engagement also cultivates long-term loyalty to the institution, while community engagement enhances social consciousness. Additionally, no significant differences in engagement levels were observed based on gender or educational level among management students.

The study faces limitations that need addressing for balanced understanding and future research guidance. Firstly, varying definitions across studies lead to inconsistent outcomes and comparability challenges. Secondly, accurate measurement is difficult due to reliance on self-reporting tools, which are prone to biases. Cultural and contextual differences also limit generalizability, and quantitative data alone may not capture the full picture. In India, identifying specific skills and competencies as engagement outcomes in outcome-based education is challenging, requiring precise variable identification.

The study would contribute to improving the efficacy of efforts beyond the classroom engagement activities as it tests, validates, and projects them as outcome-driven by showcasing learning both as generic competencies in a broad sense and higher-order competencies in particular.

The literature indicates higher education institutes' activities beyond classroom teaching enhance students' campus and community relationships. This study measures these engagements' outcomes and suggests new research dimensions in student engagement.

This paper aims to explore the numerical simulation of MHD flow of Williamson hybrid nanofluid over a porous stretched sheet. Cattaneo–Christov thermal and specie fluxes were used in the model. Partial differential equations are exploit to model the underlying physics of the situation (PDEs).

Using an acceptable similarity functions, these equations were changed into total differential equations (ODEs). The spectral relaxation method (SRM) was used to solve the linked and nonlinear altered ODEs. The Gauss–Seidel procedure is used to figure out how to use Chebyshev pseudospectral techniques in SRM. This is an iterative process.

Increasing the heat relaxation flow increases temperature distributions; increasing the mass relaxation flux increases concentration distributions. A higher value of thermal radiation heat generation and Eckert number was noticed to improve temperature and velocity distributions. Due to the imposed electromagnetic force, a higher magnetic field is detected to cause an elevation in the velocity distribution. Also, a higher thermal radiation is observed to upsurge the velocity in company with temperature distributions.

This research benefits from biomedical engineering, biological sciences, astrophysics and geophysics. The rheological applications of Williamson fluid finds usefulness in biological sciences. The nanoparticles as considered in this study finds applications in the field of biomedical engineering. Also, the application of the imposed electromagnetic field and magnetic field strength is very useful in the area of astrophysics. A good agreement may be found in the literature on this study’s findings.

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.

This research develops a theoretical framework to understand the role of big data analytics capability (BDAC) in enhancing supply chain sustainability and examines the moderating effect of green supply chain management (GSCM) practices on this relationship.

Guided by the dynamic capability view (DCV), we formulated a theoretical model and research hypotheses. We used partial least square-based structural equation modeling (PLS-SEM) to analyze data collected from 159 survey responses from Bangladeshi ready-made garments (RMG).

The statistical analysis revealed that BDAC positively impacts all three dimensions of supply chain sustainability: economic, social and environmental. Additionally, GSCM practices significantly moderate the relationship between BDAC and supply chain sustainability.

This study makes unique contributions to the operations and supply chain management literature by providing empirical evidence and theoretical insights that extend beyond the focus on single sustainability dimensions. The findings offer valuable guidelines for policymakers and managers to enhance supply chain sustainability through BDAC and GSCM practices.

This study advances the current understanding of supply chain sustainability by integrating BDAC with GSCM practices. It is among the first to empirically investigate the combined effects of BDAC on the three dimensions of sustainability – economic, social and environmental – while also exploring the moderating role of GSCM practices. By employing the DCV, this research offers a robust theoretical framework highlighting the dynamic interplay between technological and environmental capabilities in achieving sustainable supply chain performance.

This paper aims to objectively present the research dynamics of China in the field of information behavior and its development trends. Firstly, it incorporates China’s research in the field of information behavior into the global research network of information behavior, analyzing the changes in the status of Chinese scholars and their research institutions in the global research network from 1991 to 2022, the trends in publication volume and the cooperation relationships with other countries. Then, it conducts a detailed analysis of China’s research categories, groups, theoretical models and hot topics in different information contexts in the past five years (2018–2022).

The study retrieved research literature related to information behavior in China from 1991 to 2022 in the Web of Science database. It then utilized a national/institutional cooperation network map to analyze the changes in the status of Chinese scholars/institutions in the global research network during this period, publication volume trends and cooperation relationships with other countries. Furthermore, it employed keyword co-occurrence network maps to analyze the key categories, groups, theories and models of China’s research in different information contexts in the past five years. Based on this, it used keyword clustering network maps to analyze the hot topics of China’s research in different information contexts in the past five years.

(1) China’s research in the field of information behavior started relatively late, but the volume of publications has grown rapidly since 2004, currently ranking second globally in cumulative publication quantity. However, the influence of the literature published by China is limited, and there is a lack of research institutions with global influence. (2) In the last five years, China has conducted extensive research in various information contexts. Among these, most research was conducted in work contexts, followed by healthcare contexts, especially studies related to epidemics. (3) Current research on information behavior in China is characterized by expanded and refined research groups, diversified research categories, continuous expansion and enrichment of research contexts, increased interdisciplinary nature of research and continuous innovation in research methods and theoretical models.

This study, utilizing a scientific knowledge map, elucidates China’s position in global information behavior research, with a specific emphasis on analyzing China’s research hot topics and trends in this field over the past five years. It aims to provide valuable resources for scholars interested in understanding the status of information behavior research in China and to offer some guidance for scholars currently or intending to engage in information behavior research.

This article discusses the underlying teaching framework of relational cultural theory (RCT), as well as additional teaching practices used within a doctoral-level, interdisciplinary social studies course on critical social justice. Areas for future development are identified.

A research-engaged, conceptual report on practice was used to identify and integrate relevant scholarship for the purpose of formulating and analyzing teaching practices for this type of course, and to iteratively identify possible directions for future development.

RCT is a generative, underlying teaching framework for the interdisciplinary social study of critical social justice. Additional teaching practices including a community agreement to guide challenging discussions; participant-led presencing activities at the outset of classes; and, co-creation by participants of the content topics can be fruitfully embedded within RCT. Potential future development could include team-based, community-engaged, experiential term projects aimed at further deepening interdisciplinarity and civic engagement skills.

Practical guidance is provided on the use of RCT, community agreements, co-creation, presencing activities and Indigenous land acknowledgments or contemplations on Indigenous works.

RCT can be used across different educational levels or contexts. Practices of co-creation, presencing and contemplation of Indigenous works are receiving increased consideration in diverse contexts. However, conventional grading procedures can be inconsistent with critical social justice, suggesting the need for research-engaged policy review.

This article responds to recent scholarly calls for discussion of teaching practices in the interdisciplinary, social study of critical social justice in post-secondary education.