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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.

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.

This article aims to provide knowledge on the antecedents and consequences of individual proactive behaviour. The proposed research model includes two unexplored antecedents (experienced meaningfulness of work and industry competitive intensity) and one consequence (individual proficiency).

Data were collected from 297 salespeople working at 105 enterprises in a range of industries. Data analysis was performed by applying confirmatory factor analysis and structural equation modelling.

The results show (1) a positive association between industry competitive intensity and salespeople’s experienced meaningfulness of work and their proactivity at work; (2) a positive relationship between salespeople’s proactive behaviour and their individual proficiency and (3) that salespeople’s proactivity mediates the relation between industry competitive intensity and the experienced meaningfulness of work and individual proficiency.

The results suggest that managers could stimulate proactive behaviour by increasing the experienced meaningfulness of work. They also indicate that it is not only individual factors that are relevant in stimulating proactive behaviour at work, as contextual factors (particularly external ones) can also influence individual decisions with regard to engaging or not in proactive behaviour. Our findings regarding the positive relationship between proactivity and proficiency would help managers to encourage salespeople’s proactive behaviour.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

The purpose of this study is to address a significant gap in the understanding of entrepreneurship at the microfoundation level. It focuses on how individual entrepreneurs, specifically Hongbang entrepreneurs in China from 1896 to 1949, shape and transform their contexts. The aim is to provide a deeper understanding of the mechanisms that facilitate entrepreneurial success.

The study adopts a microhistorical approach, investigating the case of Hongbang entrepreneurs in China during 1896-1949. It involves an in-depth examination of historical records to explore the strategic interactions between these entrepreneurs and core stakeholders such as consumers, financial intermediaries, government regulators, and human resources. The research methodology emphasizes a process-oriented view, examining the evolution of personalized networks into extensive connections.

The research reveals that Hongbang entrepreneurs successfully reshaped their unfavorable embedded contexts by strategically collaborating with key stakeholders. They influenced consumer tastes, allied with financial intermediaries, negotiated with governments on regulation policies, and developed human resource stocks. The transformation was facilitated by the evolution of their networks from personalized to extensive connections. These findings highlight the localized strategies such as cronyism in resource acquisition within China’s private property development industry.

This study contributes to the field by offering insights into entrepreneurial contextualization and networking. It sheds light on the complex interplay between entrepreneurs and their contexts, providing a nuanced understanding of localized strategies in the Chinese context. The findings add value to the discourse on entrepreneurship by elucidating the strategic and processual acts through which entrepreneurs engage with stakeholders and reshape their environments.

Conventional wisdom tells us that mediation without ripeness is a fool’s errand (Zartman and Touval, 1985). What, then, is Türkiye’s motivation for mediating the war in Ukraine in lieu of ripeness – and what can its behavior as a mediator tell us about that motivation? In pursuit of this question, this paper inductively analyzes Turkish mediation in the Ukraine war to unpack the relationship between a contextual (ripeness) and actor-level (motivation) variable. Of particular interest is the decision-making and behavior of third parties (like Türkiye in Ukraine) who elect to mediate highly complex conflicts in which ripeness is indiscernible. The purpose of this research is not to propose or test a causal relationship between obscured ripeness and mediation, but rather to examine mediation behavior in situations where ripeness is obscured.

The impact of weaponized information on ripeness and third-party mediation is evaluated through an original, systematic and inductive case study analysis of Turkish mediation in the Russia–Ukraine war. As an intense theater of operations for information warfare for well over a decade, the war in Ukraine serves as an especially apt choice for an analysis of “obscured ripeness.” Likewise, Türkiye’s anomalous position as the only substantive source of mediation in the conflict lends significance to an empirical examination of its motivation and behavior as a mediator.

This research reveals that the pervasive use of weaponized information in the Russia–Ukraine war has distorted and disordered the information environment, thereby obscuring the ability of third parties to determine if the conflict is or could be ripe for mediation. However, the condition of obscured ripeness that prevails in the conflict has not proven a deterrent for mediation by Türkiye, which, as the only mediator in the conflict, has used a transactional approach to mediation motivated by self-regarding interests and animated by a manipulative mediation strategy. In sum, this inductive analysis of Turkish mediation in Ukraine reveals that the use of weaponized information in a conflict indirectly selects on transactional mediation (and mediators). The significance of this finding is magnified by the widespread use of weaponized information in contemporary conflicts as well as the declining frequency of third-party mediation.

There have been few, if any, systematic assessments in Turkish mediation of the Russia–Ukraine war, and none specifically concerned with the effects of weaponized information. Additionally, the paper proposes a typology of mediator motivation that is used to structure that assessment, while also introducing a new concept (“obscured ripeness”) and linking that concept both to the existing literature on ripeness and to the use of weaponized information in contemporary armed conflicts. As such, this manuscript represents an important contribution both to the empirical and theoretical landscape with respect to the study of mediation and international conflict management.

The study compares how work-integrated learning (WIL) placement positioning, duration, assessment strategies and environment at three Southern African universities influence engineering students' academic and employability outcomes.

The study used a qualitative case study approach that drew on the principles of collaborative autoethnography (CAE). The researchers reflected on WIL placement practices, structure, assessment, environment and outcomes at their universities and then analysed the reflections using comparative descriptive techniques.

The study reports no uniformity among the universities in positioning WIL placement in the curriculum. It is done during end-of-year vacations, between the penultimate and final year or in the last year. The study found WIL placement positioning does not influence academic outcomes; however, the influence on employability outcomes needs further investigation. Components of WIL placement assessment are similar, presentations, logbooks and reports. However, there are differences in the weightings of the various assessment components and the contribution of the industry supervisor. There is a growing trend towards placing students within universities to mitigate the challenges of limited opportunities of placements available in the industry. The impact of this also needs to be further investigated. Lastly, there are policy-related challenges in placing international students. Work restrictions on student visas limit international students’ access to WIL placement. Southern African universities need to lobby the waivers to student visa restrictions that limit their participation in WIL programs if there are to succeed in their internationalisation efforts.

The study highlights the gaps in understanding Southern African universities' WIL placement practices, particularly relating to the positioning of WIL placement in the curriculum, the assessment methods used and the theory to work integration and employability outcomes.