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Lean construction (LC) is an innovative approach in the construction industry that has shown significant success in developed countries. Although LC has potential in the construction sector of Pakistan, it has not been extensively explored. This study aims to address this knowledge gap by identifying and predicting current lean practices and assessing the strengths and weaknesses of LC implementation in Pakistan.

Using robust statistical methods to analyze 92 valid responses, the study reveals that approximately 54% of lean practices are currently in use in the construction industry of Pakistan, with a population mean ranging from 52.7% to 55.6%.

Surprisingly, the research identifies instances where some construction firms in Pakistan are implementing LC practices, even though they have only a limited understanding of its underlying principles. Notably, certain subprinciples, such as visual management, top management commitment to change, employee training, process cycle time reduction and production optimization, are less integrated within the construction industry. Exploring the possibility of implementing LC, recommendations for strategies to implement LC in Pakistan are suggested, aligning with the conceptual model proposed by the researchers.

The novelty of this work offers insights that can serve as a comprehensive guide for developing nations. It provides a structured approach to assess and benchmark LC practices, which, in turn, can contribute to a more efficient and effective construction industry. Moreover, the strategies proposed in this research can aid developing countries in the efficient implementation of LC. This will have a positive implication for both economic and developmental outcomes.

This paper aims to examine the impact of the assurance and advisory role of internal audit (ADRIA) on organisational, human and technical proactive measures to enhance cybersecurity (CS).

The questionnaire was used to collect data for 97 internal auditors (IAu) from the Gulf Cooperation Council countries. The authors used partial least squares (PLS) to test the hypotheses.

The results show a positive effect of the ADRIA on each of the organisational proactive measures, human proactive measures and technical proactive measures to enhance CS. The study also found a positive effect of the confirmatory role of IA on both human proactive measures and technical proactive measures to enhance CS. No effect of the confirmatory role of IA on the organisational proactive measures is found.

This study focused on only three proactive measures to enhance CS, and this study was limited to the opinions of IAu. In addition, the study was limited to using regression analysis according to the PLS method.

The results of this study show that managers need to consider the influential role of IA as a value-adding activity in reducing CS risks and activating proactive measures. Also, IAu must expand its capabilities, skills and knowledge in CS auditing to provide a bold view of cyber threats. At the same time, the institutions responsible for preparing IA standards should develop standards and guidelines that help IAu to play assurance and advisory roles.

To the best of the authors’ knowledge, this is the first study of its kind that deals with the impact of the assurance and ADRIA on proactive measures to enhance CS. In addition, the study determines the nature of the advisory role and the assurance role of IA to strengthen CS.

The link between relationship typologies and effectiveness of conflict resolution approaches remains to be tested despite its significance in conflict management in construction project delivery. By using the four relationships attributes based on the group attachment theory, the purpose of the study was to explore the cluster of relationships among project teams and organisations and the performance of conflict management strategies across these clusters in the Ghanaian construction industry.

Using a deductive questionnaire survey in the Ghanaian construction industry, a total of 137 responses were gathered and analyzed using cluster analysis, mean scores and ANOVA to reveal the relationship clusters and performance of conflict management strategies across these clusters.

The results revealed eight relationship clusters that exist among project teams and organisations with distinct influence of roles & tasks function, cognition, emotions and behavior attributes across the relationship clusters. In the aspect of the effectiveness of conflict management strategies, it was noted that the performance of these strategies were significantly different across the groups. For instance, integrating as a conflict management strategy was deemed to be effective in resolving conflict in unitary, adversarial, pluralist, mutuality, collaborative and partnering relationship clusters. In the case of coopetitive and coercive relationships, the performance of integrating as a conflict management strategy was less effective. This study thus has empirically proved that, different relationship clusters of teams and organizations exist within the Ghanaian construction industry, and that they perform different roles & tasks functions, cognition, emotions and behavioural attributes in their formation. Additionally, the performance effectiveness of conflict management strategies differed across the relationship clusters.

By aligning the relationship attributes to the dynamics of relationship clusters experienced in project teams and organisations, relationship quality, suitability and effectiveness of conflict management strategies can be optimized. The findings can inform project teams and stakeholders to develop fit-for-purpose relationship attributes among teams and organisations to enhance team effectiveness, relationship quality and conflict management in the industry.

The objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.

The research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).

Shipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.

These findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

This chapter on anti-racism struggles applies an anti-racist activist framing, both critically examining and recognising the milestones achieved through centuries of pro-justice and anti-racism struggles. It delves into the arduous journey that the global fight for racial equity has undergone and highlights the significant progress as well as setbacks experienced during this lengthy struggle. The earliest history of the fight against racial oppression and domination goes back to anti-slavery and anti-colonial movements. Scholars have analysed the emergence, development and state of global anti-racism struggles in a variety of ways. I approach this subject from a sociological perspective, highlighting the role of social structures, groups and institutions that have contributed to shaping the outcomes of anti-racist initiatives. While recognising the role of individuals and leading political activists, this chapter emphasises anti-racism as a collective social justice struggle. To do this, I explore various local and global anti-racism endeavours and examine how they may influence discussions on race, racism and racial equity and their evolving trajectories across different societies.

Over the last two decades, there has been a significant increase in incivility within the higher education sector, potentially due to mounting pressure and demands on academics, both collectively and individually. The effects on various aspects of academia, such as knowledge and learning, however, remain largely unexplored. The purpose of this research is to fill the gap by performing a theoretical trend analysis and subsequently empirically investigating the impact of workplace incivility on research scholars’ learning engagement and knowledge sharing intentions, including the mediating role of self-esteem.

This study uses a three-stage methodological process: first, a thorough theoretical (bibliographic) analysis of scientific publications, using Biblioshiny, to identify the trends of workplace incivility; second, an empirical, qualitative exploration of the emergent themes and subthemes based on 102 in-depth interviews with research scholars, using NVivo 12 Plus; and third, quantitative testing, using 154 responses and structural equation modeling.

The authors verify a visible negative association between incivility and learning engagement, incivility and knowledge sharing intentions as well as self-esteem’s mediating effect on this relationship. Also, the thematic analysis revealed three distinct themes: the type of incivility; reasons for such incidences; and the impact of such incidences on research scholars.

The research bears implications both to theory and practice. Regarding the former, the gravity and graveness of incivility versus knowledge and learning, within the academic workplace environment, are not simply highlighted, but analyzed and refined, with explicit findings of both scholarly and practicable worth; that also provide solid foundations and avenues for future research.

Further to its primary findings, the research contributes to extant knowledge by elucidating and explicating the topic, both theoretically and empirically, as well as by presenting implications for theory and practice. Regarding practical implications, this research sheds light on how to develop an appropriate organizational culture that facilitates learning engagement and increases knowledge sharing intentions, by nurturing the identified explicit and underlying motivators of civility.

The present work aimed to present the perception of Tunisian professionals towards companies engaged in social responsibility practices and describe the tax evasion strategies of socially responsible Tunisian companies following the coronavirus disease 2019 (COVID-19) pandemic (COVID-19) shock.

A survey was sent to 119 Tunisian tax administration auditors. Data analysis methods principal component analysis (PCA) and regression analysis were used. The data were collected through a questionnaire after the general containment of Tunisia from September 2020 to February 2021. These quantitative data were analysed using processing software (STATA).

Professionals of the tax authorities, particularly those in charge of the audit mission, aim for corporate profitability from the perspective of stakeholders that seek to integrate ethics and social responsibility into companies and consider employee morale a top priority. The results show that highly ethical and socially responsible professionals are far from practising aggressive strategies. Thus, an auditor from the tax administration is far from engaging in social responsibility to justify fraudulent acts. During the COVID-19 period, the role of these professionals was to prevent and detect fraud in the tax sector to fight corruption and investigate taxes based on sound regulations.

The results are consistent with optimal taxation theory, which postulates that a tax system should be chosen to maximise a social welfare function subject to a set of constraints. Professionals seek to make taxation much simpler for taxpayers by providing advice and consultation to manage tax obligations. The minimisation of tax or the play of tax values requires expertise in the field to respect legal constraints. Therefore, these professionals play a crucial role in tax collection, as the professionals' advice and suggestions can influence taxpayers' decision-making.

In recent years, academic researchers, policy makers and the public have become increasingly interested in corporate tax evasion behaviour. At the same time, companies are under increasing pressure to integrate CSR into the companies' decision-making processes, which has led to increased academic interest in CSR. Opportunistic tax minimisation reduces state resources and funds needed for government programmes to improve the social welfare of the entire community. This study represents an overriding concern not only for legal and tax authorities and companies, but also for shareholders and stakeholders.

The authors' study contributes to the existing literature by determining the state of play on corporate social responsibility (CSR) practices amongst Tunisian tax authorities' professionals. In Tunisia, an executive of the tax authorities in charge of the verification mission is required to verify the proper application of the accounting and tax legislation in force, follow up on tax control operations on declared taxes and validate the sincerity of the accounts. This study focussed on the tax evasion of companies engaged in social responsibility practices according to the judgements of Tunisian tax authorities' auditors during the global COVID-19 pandemic.