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Sustainability is a pressing global issue that affects everyone on the planet. This study aims to provide a deeper understanding of the nuanced interplay between mindful organizing (MO), organizational learning capability (OLC), leadership commitment to sustainable development goals (SDGs) and sustainability performance, adopting the theoretical foundation of organizational learning.

The survey data from 728 middle management employees of exporting firms in Pakistan were collected at two points. The mediated moderation analysis was performed through structural equation modeling in AMOS 26.

The results indicate a positive relationship between MO and sustainability performance. The mediating effect of OLC highlights that firms that acquire, assimilate and apply knowledge and insights leverage their MO strategies to improve sustainability performance more effectively. Additionally, the leadership commitment to SDGs amplifies the positive effect of OLC on sustainability performance.

These results have important implications for managers and policymakers who seek to promote sustainability in organizations. The findings suggest that cultivating a mindful organizational culture and investing in learning capability enhance sustainability performance. Exporting firms should develop comprehensive learning programs that embed mindfulness and sustainability into the core of organizational culture. More interdisciplinary research is needed to integrate insights from environmental science, psychology, management and organizational behavior.

This research stands out for its integrative approach, practical relevance, empirical examination of important concepts and alignment with global sustainability goals. Exporting firms must understand how organizational learning capabilities and MO can be harnessed to achieve sustainable outcomes.

This research explains the critical role of technological readiness and green dynamic capabilities in enhancing the sustainability performance of manufacturing firms, which is pivotal for achieving the United Nations’ Sustainable Development Goals. The theoretical framework is grounded in the dynamic capability theory, positing that technological readiness enhances a firm’s green dynamic capabilities, and employee green behavior moderates the effect on the sustainability performance of manufacturing firms.

Quantitative data from 1,660 managerial employees of a diverse sample of manufacturing firms was aggregated at the firm level using interclass correlation and interrater agreement, ensuring robustness using at least two responses per firm. With the final dataset of 418 firms, structural equation modeling was conducted using AMOS26.

The findings reveal that technological readiness positively affects sustainability performance and enhances it through green dynamic capabilities. Furthermore, the study highlights the positive moderating role of employees’ green behavior, amplifying the impact of green dynamic capabilities on sustainability performance.

This research makes a novel contribution to the body of knowledge by integrating dynamic capability theory with empirical evidence on sustainability performance. It represents a significant step toward promoting a more sustainable and responsible future for organizations and society and provides comprehensive insights into the complex interplay of these variables. These insights are crucial for academia, industry practitioners and policymakers striving to foster sustainable practices within the manufacturing sector.

This study investigates the influence of paradoxical leadership on employee transformative learning in higher education institutions (HEIs). Based on paradox theory, this research examines how a paradoxical mindset mediates this relationship and explores the moderating role of employees’ moral values in developing a paradoxical mindset and fostering transformative learning.

The research adopted a quantitative approach. In three phases, data were collected from 411 randomly selected faculty members of HEIs in Pakistan to assess their perceptions of paradoxical leadership, followers’ paradoxical mindset, moral values and transformative learning outcomes. Structural equation modeling was employed for analysis in AMOS26.

The findings reveal paradoxical leadership’s positive and significant impact on transformative learning, mediated by developing a paradoxical mindset. Moral values positively moderate the relationship between paradoxical leadership and developing a paradoxical mindset. However, the moderating effect of moral values on the link between a paradoxical mindset and transformative learning was insignificant.

The study suggests that organizations, particularly HEIs, should cultivate paradoxical leadership to navigate inherent tensions and contradictions, fostering an environment conducive to transformative learning. Developing a paradoxical mindset among employees is crucial for enhancing adaptability and learning, with moral values playing a pivotal role in amplifying the effectiveness of paradoxical leadership.

This study contributes to the literature by providing empirical evidence on the mechanism through which paradoxical leadership influences transformative learning. It extends paradox theory to the context of transformative learning, highlighting the importance of cognitive and ethical dimensions in leadership and learning processes within HEIs.

The COVID-19 impact across major sectors did not exempt the low-cost housing (LCH) sub-sector. This may have increased the existing LCH demand-supply gap, especially in developing countries such as Malaysia. Studies showed that government policy (GP) aids in mitigating COVID-19 impact on goods and services, including housing-related issues. However, there is an academic literature scarcity regarding GP on LCH demand-supply gap during the COVID-19 crisis in Malaysia. Hence, this study aims to investigate the moderating effect of GP on the relationship between LCH demand-supply gap and COVID-19 impact in Malaysia.

The research utilised a quantitative method in collating the data from four major cities in Malaysia. SmartPLS was utilised to analyse the usable 305 questionnaires retrieved from respondents. Structuralist Theory supported the developed framework.

Findings show that GP moderates the relationships between the LCH demand-supply gap and COVID-19 impact on Malaysia's low-income groups' (LIGs) homeownership delivery. It implies that the study's findings provide more understanding of issues influencing LCH demand-supply gap in the COVID-19 era via applying GP to mitigate the gap and improve homeownership for the disadvantaged.

The study intends to stir policymakers toward formulating policies and programmes that will mitigate LCH demand-supply gap during the present and future pandemics.

Besides the theoretical value of the developed model, policymakers can use the study's recommendations to mitigate future LCH demand-supply gaps during pandemics in developing countries using Malaysia as a case study.

Purpose: This study investigates the influence of inflation and oil price fluctuations on stock prices and returns. A thorough bibliometric analysis of research articles published in the last 22 years has been conducted to achieve this objective.

Need for the Study: Inflation and oil prices are critical macroeconomic variables that significantly impact the economy, including the stock market. It is crucial for investors and policymakers to understand the complex relationship between these economic variables and the stock market.

Methodology: The study employed a bibliometric analysis to identify the most influential authors, institutions, and research themes related to the impact of inflation and oil prices on stock prices.

Findings: The study identified that the fluctuations of the stock market are significantly influenced by both inflation and oil prices. This relationship has been extensively studied in the literature, with several key research themes identified. These themes include the effects of inflation and oil prices on various sectors and industries, the role played by monetary and fiscal policy, and the impact of international trade and global economic conditions.

Practical Implications: The insights that have emerged have significant implications for investors and policymakers. It highlights the need for risk management strategies and mitigation of macroeconomic factors’ impact on stock prices.

The goal of this research is to examine the influence of digital leadership (DL) on adaptive capacity (ADC) of small- and medium-sized family businesses (SMFBs). Moreover, the study investigates the mediating influence of the microfoundations of dynamic capabilities represented by sensing capability (SC) and organizational agility (OA), both parallelly and sequentially.

Drawing on the dynamic capabilities view (DCV) and supporting empirical evidence, a conceptual framework is developed along with a set of hypotheses. Using survey data collected from 263 SMFBs in Oman, the hypotheses are tested using structural equation modeling through partial least square-structural equation modeling (PLS-SEM).

The analysis reveals that DL positively influences ADC, SC and OA. Additionally, SC and OA both parallelly mediate the link between DL and ADC. Finally, both SC and OA act as sequential mediators in the relationship between DL and ADC among SMFBs.

For practitioners, the study reveals critical role of DL in strengthening SMFBs. Family business leaders may consider the evidence and invest in leadership development programs to enhance digital competencies, enabling better SC and agility. Policymakers can offer training programs and resources, helping family businesses to build DL and dynamic capabilities essential for thriving in a competitive and evolving business environment.

This study makes four key contributions. First, this study expands the literature at the crossroads of the family business, digitalization, dynamic capabilities and resilience, to investigate the influence of DL on ADC. Second, the role of SC as a mediator in the above relationship, tested in the current study, seems to be overlooked in the empirical literature. Third, the findings demonstrate the mediating role of OA in relationship between DL and ADC. Finally, this appears to be the first study that presents sequential mediating role of SC and OA between DL and ADC, adding a finer-grained understanding of how influence of DL is transmitted to ADC.

Many construction projects exhibit poor performance in terms of fulfilling predetermined schedules and financial objectives. Project control systems (PCSs) have been used to enhance construction project performance; however, a comprehensive framework regarding the key determinants of PCS effectiveness is lacking.

Herein, the determinants for effective PCSs that can improve construction project performance were comprehensively identified by evaluating existing studies. A systematic strategy following the preferred reporting items for systematic reviews and meta-analyses protocol was employed to search for and select relevant studies, followed by a qualitative synthesis.

The significance of incorporating and managing many factors associated with PCS for effective project delivery was elucidated. The study synthesized 12 key determinants and 29 sub-determinants of PCS effectiveness in project delivery and grouped them into organizational, human, technological and operational categories. Out of the four categories examined, operational aspects received the most references, underscoring their critical role in PCS effectiveness, while human-related dimensions received the least amount of attention in the reviewed research, accounting for 4%. This also revealed a significant gap in the research addressing the interactions between all PCS aspects.

Understanding of the variables influencing PCS effectiveness in construction project delivery was enhanced, and a framework for future PCS research in five dominant areas was created.

The purpose of this study is to investigate the impact of Corona Virus Disease 2019 (COVID-19) on the outcome of construction projects and explore the moderating effects of emerging technologies on the relationship between COVID-19 and construction project outcomes.

Data for the study was collected through a Web-based, semistructured questionnaire. The responses of 62 construction practitioners were analyzed using a hierarchical linear regression model. The model consists of 16 independent variables, three control variables (organization size, organization type and project size), one moderator (adoption level of emerging technologies) and three dependent variables (project time, project cost and project quality).

The study confirms the negative significant impact of the COVID-19 pandemic on the performance of construction projects. It also identifies the significant moderating effects of emerging technologies in mitigating the impact of COVID-19 on construction projects. Further, it shows a significant increase in the application of emerging technologies in construction projects during the COVID-19 pandemic. Based on the findings related to the moderating impact of the technology, this study provides a clear set of recommendations for construction firms, public sector and research community in combating the unavoidable situation similar to the COVID-19 pandemic in the future.

To the best of the authors’ knowledge, this is the first study to identify the moderating role of technology on the impact of COVID-19 on the performance of the construction sector in Pakistan. The findings can also be used for the construction sectors of other developing countries.

In the context of the environmental degradation challenge in manufacturing firms, greening the supply chain (SC) is the most widely endorsed method to mitigate the adverse repercussions of climate change. Based on organizational learning and resource dependence theories, the aim of this research is to know how green supply chain external integration (GSCEI) and green supply chain internal integration (GSCII) influence ambidextrous green innovation (AGI). It also examines the mediating roles of green absorptive capacity (GAC) and green knowledge integration capability (GKIC), as well as the moderating role of green technology dynamism (GTD).

To assess the hypothesized model, data were obtained with 386 questionnaires from managers employed in manufacturing firms in Pakistan applying a cross-sectional approach. A partial least square structural equation modeling technique was implemented to evaluate the data.

The results revealed that GSCEI and GSCII substantially impact AGI. Moreover, GAC and GKIC serve as mediators between GSCEI and AGI. GAC and GKIC also intervene in the relationship between GSCII and AGI. GTD was significant as a moderator for the correlation between GSCEI and AGI. However, it does not moderate the relationship between GSCII and AGI.

This research offers significant comprehension and an innovative approach for manufacturing organizations to curb environmental corrosion by stimulating AGI through green SC integration. It suggests to practitioners that integrating internal knowledge with external partners expands communication and collaboration to ensure that resources connected with environmental preservation flow smoothly.

This research is a valuable addition to the field, as it explores for the first time the missing link among the studied constructs. It opened the black box of how knowledge-related capabilities facilitate knowledge resources to elicit AGI, an area that has not yet been explored.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.