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The current study probes the multi-dimensional link between total quality management (TQM) and knowledge management (KM) and investigates how different TQM's dimensions impacts KM processes and how this nexus impacts organizational performance (operational and financial performance) by considering KM as an intermediating variable between TQM and organizational performance.

Six TQM practices are taken from “Malcolm Baldrige National Quality Award”, namely leadership, customer focus, strategic planning, human resource management, process management and information and analysis; KM processes include knowledge creation, acquisition, sharing and application and organizational performance comprises operational and financial performance. The researcher put together data from different sized services and manufacturing firms, from small, to medium and large firms located in the United Kingdom (UK).

The results suggested that a positive correlation existed between TQM, KM and organizational performance. KM is also shown to have quite a strong and positive influence on firm operational and financial performance and partially mediates the relationship between TQM and corporate performance. Dimensional analysis indicates that leadership, strategic planning, customer focus and HRM have a significant positive impact on all KM process, while mixed results have been found for process management and information and analysis. The contextual analysis indicates that except for knowledge creation, TQM plays an equally significant role for the majority of manufacturing establishments and services firms.

The present research makes a significant contribution to the scarce literature on the relationship between TQM and KM (mainly at dimensional level), particularly in the context of the UK, and provides a detailed understanding of the relations between different TQM and KM dimensions, and how their relationship impacts on the operational and financial performance of different sizes of manufacturing and services firms.

Highlights

1. Total quality management (TQM) enhances firms' knowledge management (KM) capabilities

2. KM partially mediates the relationship between TQM and firms' performance

3. Leadership, customer focus and process management indicated insignificant impact on knowledge creation

4. TQM and KM are equally important for all sizes manufacturing and services firms

Total quality management (TQM) enhances firms' knowledge management (KM) capabilities

KM partially mediates the relationship between TQM and firms' performance

Leadership, customer focus and process management indicated insignificant impact on knowledge creation

TQM and KM are equally important for all sizes manufacturing and services firms

This study aims to explore COVID-19-related accounting disclosures using sociological disclosure analysis (SDA) within the context of the developing economy of Bangladesh.

COVID-19-related accounting disclosures from listed banks’ annual reports have been examined using three levels of SDA: textual, contextual and sociological interpretations. Data were gathered from the banks’ 2019 and 2020 annual reports. The study uses the legitimacy theory as its theoretical framework.

The research reveals a substantial shift in corporate disclosures due to COVID-19, marked by a significant increase from 2019 to 2020. Despite regulatory and professional directives for COVID-19-specific disclosures, notable non-compliance is evident in subsequent events, going concern, fair value, financial instruments and more. Instead of assessing the implications of COVID-19 and making disclosures, companies used positive, vague and subjective wording to legitimize non-disclosure.

The study’s insights can inform regulators and policymakers in crafting effective guidelines for future crisis-related reporting like COVID-19. The research adds to the literature by methodologically using SDA to explore pandemic-specific disclosures, uncovering the interplay between disclosures, legitimacy and stakeholder engagement.

This study represents a pioneering effort in investigating COVID-19-specific disclosures. Moreover, it uses the SDA methodology along with the legitimacy theory to analyze accounting disclosures associated with COVID-19.

Construction professionals (CPs) are often exposed to various challenges and pressures at work including urgent deadlines, high demands, uncertainty in tasks, and complex problems, which may induce stress and affect performance directly. Mindfulness-based stress reduction (MBSR) training has been used for several years to reduce stress among various types of people, such as nurses, teachers, and family caregivers, but its application to CPs with highly dynamic environment remains uncertain. This study aimed to investigate the impact of MBSR training on the performance of CPs via an intervention study involving two groups (MBSR and control).

Participants in both groups were assessed using a questionnaire survey and a semi-structured interview at the pre- and post-intervention stage. Multiple research methods were used to derive quantitative and qualitative analyses, including factor analysis, independent t-test, Pearson correlation, and contextual analysis.

The findings overall confirm that MBSR has a direct effect on CPs, improving their mindfulness characteristics and enhancing performance by reducing their stress.

A number of practical recommendations are made such as (1) arranging standard eight-week MBSR training for CPs; (2) giving special leave for attending the full mindfulness training; (3) establishing a suitable environment in the office for meditation;(4) allowing CPs an opportunity to pause at difficult moments to create space to respond instead of simply reacting; and (5) expressing love and kindness through gratitude, recognition, and regular feedback.

This research can be considered as valid evidence to convince construction organizations conducting MBSR to the CPs, which is indeed not too remote to enhance their performance as well as the holistic construction performance.

This paper aims to discover and analyze the challenges hampering blockchain technology’s (BT’s) implementation in the Indian health-care sector. A total of 18 challenges have been prioritized and modeled based on an extensive literature search and professional views.

An integrated multi-criteria decision-making approach has been used in two phases. Best worst method (BWM) is used in the first phase to prioritize the challenges with sensitivity analysis to validate the findings and eliminate a few challenges. In the second phase, interpretive structural modeling is applied to the remaining 15 challenges to obtain relative relationships among them with cross-impact matrix multiplication applied to classification analysis for their categorization.

The study’s results reveal that limited knowledge and expertise, cost and risk involved, technical issues, lack of clear regulations, resistance to change and lack of top management support are the top-ranked or high-intensity challenges according to the BWM. Interpretive structural modelling findings suggest that the lack of government initiatives has been driving other challenges with the highest driving power.

This work has been conducted in the Indian context, so careful generalization of the results is needed.

This work will give health-care stakeholders a better perspective regarding blockchain’s adoption. It will help health-care stakeholders, service providers, researchers and policymakers get a glimpse of the strategies for eradicating mentioned challenges. The analysis will help reduce the challenges’ impact on blockchain’s adoption in the Indian health-care sector.

The adoption of BT is a novel concept, especially in developing countries such as India. This is one of the few works addressing the challenges to BT adoption in the Indian health-care sector.

This study aims to focus on the supply chain (SC) cost drivers of healthcare industries in the USA, as SC costs have increased 40% over the last decade. The second-most significant expense, the SC, accounts for 38% of total expenses in a typical hospital, while most other industries can operate within 10% of their operating cost. This makes healthcare centers supply-chain-sensitive organizations with limited facilities for high-quality healthcare services. As the cost drivers of healthcare SC are almost unknown to managers, their jobs become more complex.

Guided by pragmatism and positivism paradigms, a cross-sectional study has been designed using quantitative and deductive approaches. Both primary and secondary data were used. Primary data were collected from health centers across the country, and secondary data were from healthcare-related databases. This study examined the attributes that explain the most significant variation in each contributing factor. With multiple regression analysis for predicting cost and Student's t-tests for the significance of contributing factors, the authors of this study examined different theories, including the market-based view and five-forces, network and transaction cost analysis.

This study revealed that supply, materials and services represent the most significant expenses in primary care. Supply-chain cost breakdown results in four critical factors: facility, inventory, information and transportation.

This study examined the data from primary and secondary care institutions. Tertiary and quaternary care systems were not included. Although tertiary and quaternary care systems represent a small portion of the healthcare system, future research should address the supply chain costs of highly specialized organizations.

This study suggests methods that can help to improve supply chain operations in healthcare organizations worldwide.

This study presents an empirically proven methodology for testing the statistical significance of the primary factors contributing to healthcare supply chain costs. The results of this study may lead to positive policy changes to improve healthcare organizations' efficiency and increase access to high-quality healthcare.

This study analyzes, from the perspective of social exchange theory, the influence of empowering leadership on contextual performance mediated by perceived organizational support (POS) and affective organizational commitment (AOC).

A survey was carried out with 182 employees of the Best Companies to Work in Brazil. Data analysis was performed by structural equation modeling (SEM) and by fuzzy set qualitative comparative analysis (fsQCA).

Results demonstrate that empowering leadership directly influences higher contextual performance and indirectly through the mediation of AOC, but not through POS. Serial mediation confirms that the model's variables self-promote each other to ultimately foster higher performance. Furthermore, all solutions to obtain high contextual performance include empowering leadership in the dimension of trust in the high performance of employees.

The statistical support for the serial mediation indicates that empowering leadership promotes POS, which influences AOC that finally promotes the employee's contextual performance. However, this study's model does not include employees' task performance; our results add to the contextual performance literature.

The study highlights the role of the empowering leadership style in the organizational context, an aspect that deserves attention from the managers and organizations due to its effect on employee performance.

The study adds a new framework to the literature, which can be used by organizations to promote contextual performance. The variables, which include contextual and individual factors, foster the employee's contextual performance in a joint and self-promoting way. Contextual performance exceeds the manager's technical attributions; it covers psychological and discretionary behaviors.

This paper examines the relationship between supply chain network structures and firm financial performance and the moderating role of international relations. In this study, which is grounded in social capital theory and applies the perspective of systemic risk, the authors theorize the effects of supply chain network structures on firm performance.

The authors extracted data from two Chinese databases and constructed a supply chain network of the firms concerned based on nearly 4,300 supply chain relations between 2009 and 2018. The authors adopted the fixed effects model to investigate the relationship between supply chain network structures and firm financial performance.

The econometrics results indicate that network structures, including the degree, centrality, clustering coefficients and structural holes, are significantly related to firm financial performance. A significant and negative relationship exists between international relations and firm financial performance. The authors also find that international relations strongly weaken the relationship between supply chain network structures and firm financial performance.

This study, which collects secondary data from developing countries (e.g. China) and explores the impacts of supply chain network structures on firm stock performance, contributes to the existing literature and provides practical implications.

Contextual cues have become a hot research topic in the field of mobile consumer behavior, owing to the continuous rise of digital marketing. However, the complex online shopping scene makes it challenging to directly identify the association between the characteristics of contextual cues and consumer behavior. Presently, few studies have only systematically extracted and refined the types and characteristics of contextual cues. The purpose of this study is to explore the types and mechanisms of contextual cues in online shopping scenarios.

This study uses the word2vec algorithm, grounded theory and co-occurrence cluster method, along with online shopping word-of-mouth (WOM) text and consumer behavior theory, in order to explore different types of contextual cues and its efficiency from 5,619 comment corpus.

This study puts forward the following conclusions. (1) From the perspective of online shopping, contextual cues comprise aesthetic perception cues, value perception cues, trust-dependent cues, time perception cues, memory attention cues, spatial perception cues, attribute cues and relationship cues. (2) Based on the online shopping scenarios, contextual cues and their interaction effects exert an effect on consumer satisfaction, recommendation, purchase and return behavior.

The study conclusions are helpful to further reveal the deep association between contextual cues and consumer behavior in the process of online shopping, thus providing practical and theoretical enlightenment for enterprises to not only effectively reshape the scene but also promote the consumers' active purchase behavior.

Scholarly communications, particularly, questions and answers (Q&A) present on digital scholarly platforms provide a new avenue to gain knowledge. However, several studies have raised a concern about the content anomalies in these Q&A and suggested a proper validation before utilizing them in scholarly applications such as influence analysis and content-based recommendation systems. The content anomalies are referred as disinformation in this research. The purpose of this research is firstly, to assess scholarly communications in order to identify disinformation and secondly, to help scholarly platforms determine the scholars who probably disseminate such disinformation. These scholars are referred as the probable sources of disinformation.

To identify disinformation, the proposed model deduces (1) content redundancy and contextual redundancy in questions (2) contextual nonrelevance in answers with respect to the questions and (3) quality of answers with respect to the expertise of the answering scholars. Then, the model determines the probable sources of disinformation using the statistical analysis.

The model is evaluated on ResearchGate (RG) data. Results suggest that the model efficiently identifies disinformation from scholarly communications and accurately detects the probable sources of disinformation.

Different platforms with communication portals can use this model as a regulatory mechanism to restrict the prorogation of disinformation. Scholarly platforms can use this model to generate an accurate influence assessment mechanism and also relevant recommendations for their scholars.

The existing studies majorly deal with validating the answers using statistical measures. The proposed model focuses on questions as well as answers and performs a contextual analysis using an advanced word embedding technique.

The purpose of this paper is to expand the use of ethnography to advance research on team science by revealing the barriers to teamwork as manifesting at institutional, cultural, and interpersonal contextual scales. The analysis suggests strategies to enhance team science's collaborative potential.

This paper considers some of the practical and analytical challenges of team science through the use of ethnographic methods. The authors formed a three-person subteam within a larger multisited, federally-funded, interdisciplinary scientific team. The authors conducted six months of participant observation, semi-structured interviews, and a focus group, using iterative deductive and inductive analyses to investigate the larger team's roles, relationships, dynamics, and tensions.

Integrating ethnography into the study of team science can uncover and mitigate barriers faced by teams at three primary levels: (1) academic culture, (2) institutional structures, and (3) interpersonal dynamics. The authors found that these three contextual factors are often taken for granted and hidden in the team science process as well as that they are interactive and influence teams at multiple scales of analysis. These outcomes are closely related to how team science is funded and implemented in academic and institutional settings.

As US federal funding initiatives continue to require scientific collaboration via inter-, multi-, and transdisciplinary research, there is little work done on how teams grapple with the practical tensions of scientific teamwork. This paper identifies and addresses many practical tensions and contextual factors across institutional and organizational structures that affect and challenge the conduct of collaborative scientific teamwork. The authors also argue that ethnography can be a method to challenge myths, understand contextual factors, and improve the goals of team science.