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The construction industry is unique but with uncertainties. This is because of the operating environment. This intricacy gives rise to several construction risks and is compounded in developing countries’ turbulent times. If not managed, these risks enhanced in turbulent times could negatively impact the Nigerian construction projects’ cost, time, quality, and performance. Hence, this study investigated the perceived encumbrances facing construction risk management techniques and identified measures to promote sustainable-based construction risk management in turbulent times.

The researchers adopted a qualitative approach and achieved saturation with 28 participants. The participants were government policymakers, quantity surveyors in government ministries/agencies/departments, consultant engineers, consultant architects, consultant and contracting quantity surveyors, and construction contractors knowledgeable about construction risk management. The research employed a thematic analysis for the study’s data.

Findings identified turbulent times related to the industry and major techniques for managing construction project risks in the Nigerian construction industry. It revealed lax adoption and implementation of practices. Also, the study identified major encumbrances facing construction risk and proffered initiatives that would promote sustainable-based construction risk management in turbulent times.

This study investigates encumbrances and suggests measures to promote construction project risk management in turbulent times in Nigeria. Also, the study contributes to the literature’s paucity, uncovering perceived encumbrances and evolving organisations’ management styles to imbed sustainable-based risk management practices by qualitative research design method.

This study aims to investigate the impact of organizational external environmental factors on strategic management accounting (SMA) usage in an emerging economy.

The study collected data from 79 public limited companies listed with the Dhaka Stock Exchange (Bangladesh) through a questionnaire survey. Multiple regression analysis is employed to test the impact of external environmental variables such as perceived environmental uncertainty and intensity of competition on SMA usage.

The study finds a significant positive impact of environmental uncertainty (fluctuation in the external environmental factors) and intensity of competition (domination by few companies) on SMA usage. However, the direction and magnitude of this impact vary considerably for specific groups of SMA practices such as costing, competitor accounting, customer accounting and planning and performance measurement techniques.

This study shows the impact of several facets of environmental uncertainty (i.e. unpredictability, fluctuation, ambiguity, lack of information and uncertainty of the outcome of decision) and intensity of competition (i.e. stressfulness and domination) in the empirical-based SMA research.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).

This paper aims to critically examine the accounting and information systems literature to understand the changes that are occurring in the management accounting profession. The changes the authors are interested in are linked to technology-driven innovations in managerial decision-making and in organizational structures. In addition, the paper highlights research gaps and opportunities for future research.

The authors adopted a grounded theory literature review method (Wolfswinkel et al., 2013) to achieve the study’s aims.

The authors identified four research themes that describe the changes in the management accounting profession due to technology-driven innovations: structured vs unstructured data, human vs algorithm-driven decision-making, delineated vs blurred functional boundaries and hierarchical vs platform-based organizations. The authors also identified tensions mentioned in the literature for each research theme.

Previous studies display a rather narrow focus on the role of digital technologies in accounting work and new competences that management accountants require in the digital era. By contrast, the authors focus on the broader technology-driven shifts in organizational processes and structures, which vastly change how accounting information is collected, processed and analyzed internally to support managerial decision-making. Hence, the paper focuses on how management accountants can adapt and evolve as their organizations transition toward a digital environment.

This paper aims to conduct a bibliometric analysis of studies focusing on green supply chain management (GSCM) within the context of the digital economy.

We utilize the Web of Science database to search and filter relevant documents spanning the years 2003–2022. This extensive dataset enables us to analyze the growth and cutting-edge developments in research pertaining to GSCM in the digital economy.

The paper finds a significant increase in research interest and output, particularly noticeable from 2016 onwards, indicating the growing relevance of integrating GSCM with digital technologies. It is found that the prominent contribution of countries like China, England and the USA, underscoring a strong geographical diversity in research outputs. China leads in the number of publications, which reflects its significant role in shaping the discourse around GSCM in the digital economy. However, when it comes to citations, the USA leads, suggesting a higher impact or quality of research emanating from this region. Collaborative dynamics outlined in the study demonstrate extensive international cooperation, primarily among leading research countries, which is facilitated by shared digital platforms enhancing the research’s reach and impact. The study also highlights a range of emerging themes such as the adoption of blockchain technology, Internet of Things (IoT) and the circular economy within GSCM, indicating dynamic areas for future research.

The findings of this study hold significant practical implications for researchers, practitioners and policymakers. They shed light on the current state of research in GSCM within the digital economy, highlighting areas where further investigation is needed and pointing to the emerging trends in this field. Understanding the distribution of research and influential authors can guide future collaborative efforts and inform decision-making processes in the pursuit of sustainable supply chain practices in the digital era.

This paper contributes to the existing body of knowledge by providing a comprehensive bibliometric analysis of the evolving landscape of GSCM in the digital economy. It offers valuable insights into the growth patterns, key contributors and geographical distribution of research in this domain. This information is crucial for researchers and stakeholders seeking to stay at the forefront of sustainable supply chain practices in an increasingly digital world.

This paper aims to investigate the impact of corporate governance mechanisms and the environmental, social and governance (ESG) disclosure score on bank performance and financial stability. Further, this paper analyses how this relationship varies over the different ownership structures.

The paper uses a sample of 41 Indian banks (including both public sector and private sector banks) over the period ranging from 2008 to 2020. The data is analyzed in both static and dynamic frameworks using panel regression and system generalized methods of moments.

The results indicate that the frequency of board meetings has a negative influence on the performance of the banks. Gender diversity reveals both linear and non-linear relationships with bank performance. In the sample of public sector banks, the board size and promoters’ ownership have a significant negative effect on the bank's performance. In private sector banks, CEO duality adversely affects performance. Further, the results indicate that ESG disclosure score is positively linked with the profitability of banks.

This paper provides a comprehensive analysis of the impact of corporate governance mechanisms and ESG disclosure scores on bank performance and stability in the context of the Indian economy. To the best of the authors’ knowledge, there has been no empirical investigation or study that has been conducted in this respect.

This research addresses the critical challenge of fostering customer loyalty within the highly competitive landscape of the insurance industry. The study investigates the interplay between customer satisfaction, loyalty, and the influence of technology and service quality in the context of insurance services and in periods of crisis.

A quantitative research approach was employed, utilizing a structured questionnaire distributed among diverse insurance customers in Lebanon during crisis conditions. The data were analyzed using SPSS-Amos, incorporating descriptive statistics, correlation analysis, and structural equation modeling (SEM).

This research emphasizes the crucial role of customer satisfaction in fostering loyalty in the insurance sector, especially during crises. High satisfaction levels, influenced by user-friendly online platforms, positively correlate with increased customer loyalty. Technology plays a vital role in maintaining and improving satisfaction, making it a key driver during challenging times. Positive interactions between service quality and satisfaction further highlight the multifaceted impact of technology on shaping customer loyalty.

The research findings provide valuable insights with practical implications for insurers aiming to boost customer loyalty. The study recommends strategic investments in critical areas like claims processing, customer service, communication strategies, digitalization initiatives, and employee training. The study provides insights applicable particularly to insurance companies navigating crisis conditions.

This research contributes both to academic understanding and practical applications by shedding light on the distinctive challenges and opportunities faced by insurers in cultivating customer loyalty within the insurance industry during crisis. The elucidations provided serve as a foundation for developing targeted strategies to address these challenges and to leverage opportunities for enhanced customer loyalty.

In today’s intricate and dynamic construction sector, traditional project management techniques, which view projects in isolation, are no longer sufficient. Project Portfolio Management (PPM) has proven to be an efficient alternative solution for handling multiple construction projects. As such, based on a Machine Learning (ML) approach, this study aims to explore the Critical Success Factors (CSFs) influencing the adoption of PPM, aiming to enhance PPM implementation in construction projects.

A questionnaire based on CSFs gathered from prior studies was developed and validated by experts. Afterward, exploratory data analysis is conducted to understand CSF–PPM relationships. Preprocessing techniques ensure uniformity in variable magnitudes. Lastly, ML techniques, namely Linear Discriminant Analysis (LDA), Logistic Regression (LR) and Extra Trees Classifier (ETC) are developed to model and investigate CSFs' impact on PPM adoption.

The findings pointed out that the ETC model marginally outperforms other ML models with a classification accuracy of 93%. Also, the project size, utilized PPM tool and resource allocation-related factors are the most significant CSFs that influenced the PPM performance by about 48.5%.

This study contributes to the existing body of knowledge by raising awareness among construction companies and other project stakeholders about the pivotal CSFs that must be considered when prioritizing projects and designing an optimal PPM approach.

Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

Enterprise resource planning (ERP) systems that are equipped with numerous features and functionalities help to improve the profitability of construction corporations around the world through enhancing the efficiency of the functions related to cost management. Thus, the purpose of this study was to investigate the applicability of ERP systems for cost management of building construction projects in Sri Lanka.

A qualitative technique was used in this study, which comprised two-round Delphi-based semistructured interviews. Purposive sampling was used to determine the interviewees. Content analysis was used to evaluate the collected data.

The findings of this study identified the ERP system as a strategic tool for gaining a competitive advantage for an organization while confirming 14 uses of ERP systems and 16 stages of the cost management process. Eighteen issues were finalized at the end of the interview rounds while categorizing the suitable ERP applications at each stage of the cost management process.

Even though there are numerous distinct studies conducted on cost management and ERP systems, there has been a lack of studies conducted on the synergy between these two areas that can be adapted for the building projects in the Sri Lankan context. Therefore, the findings of this study can bring a new paradigm to the Sri Lankan construction sector by influencing the adaption of correct ERP systems at numerous project stages by providing a competitive edge.