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The purpose of the present study is to investigate the community’s view of power outages and their effect on sustainable community development. This research has three aims. This project will first investigate how a blackout affects a community’s ability to live sustainably.

A survey questionnaire was developed that included 22 factors from the literature. The questionnaire was distributed to diversified segments of society from different regions of Pakistan and examined critical factors affecting sustainable community development. A total of 349 (77%) responses were received.

The study results confirm that power failure negatively affects the sustainable life of a community. This study found that the reduced production of large manufacturing, decrease leisure and comfort, reduced public administrative efficiency, loss of educational opportunities and increased use of traditional energy sources are the most important factors for sustainable community development. Findings also suggest that policymakers and practitioners in public organizations need to ensure that projects are completed in a timely manner to meet growing community needs.

The purpose of this research is to address knowledge gaps related to power outages and sustainable community development. The major impact of power disruptions on communities was previously disregarded in development discourse. Participants in these discussions recognize communities as genuine stakeholders and acknowledge that power outages can have a substantial impact on their economic and social development. However, previous studies have neglected to address this phenomenon.

The increasing awareness and adoption of technology, particularly artificial intelligence (AI), reshapes industries and daily life, fostering a proactive approach to risk management and leveraging advanced analytics, which may affect the stock price crash risk (SPCR). The main objective of the current study is to explore how AI adoption influences SPCR.

This study employs an Ordinary Least Squares (OLS) fixed-effect regression model to explore the impact of AI on SPCR in Chinese A-share listed companies from 2010 to 2020. Further, number of robustness analysis (2SLS, PSM and Sys-GMM) and channel analysis are used to validate the findings.

The primary findings emphasize that AI adoption significantly reduces SPCR likelihood. Further, channel analysis indicates that AI adoption enhances internal control quality, contributing to a reduction in firm SPCR. Additionally, the observed relationship is notably more pronounced in non-state-owned enterprises (non-SOEs) compared to state-owned enterprises (SOEs). Similarly, this distinction is heightened in nonforeign enterprises (non-FEs) as opposed to foreign enterprises (FEs). The study finding also supports the notion that financial analysts enhance transparency, reducing the SPCR. Moreover, the study results consistently align across different statistical methodologies, including 2SLS, PSM and Sys-GMM, employed to effectively address endogeneity concerns.

Our study stands out for its distinctive focus on the financial implications of AI adoption, particularly how it influences firm-level SPCR, an area that has been overlooked in previous research. Through the lens of information asymmetry theory, agency theory, and the economic implications of integrating AI into financial markets, our study makes a substantial contribution in mitigating SPCR.

This study underscores the pivotal role of AI adoption in influencing stock markets for enterprises in China. Embracing digital strategies, fostering transparency and prioritizing talent development are key for reaping substantial benefits. The study recommends regulatory bodies and service providers to promote AI adoption in strengthening financial supervision and ensure market stability, emphasizing the importance of investing in technologies and advancing talent development.

The purpose of this article is twofold: to identify the characteristics of research on organisation and management in Arab countries and to find out whether research results support the culture‐free hypothesis or not. A thorough search of sixteen journals, research monographs, books and theses produced only 35 empirical studies. Most of these studies were exploratory, descriptive, and used small convenient samples. Although some findings supported the culture‐bound hypothesis, major conceptual and methodological weaknesses in these studies throw doubt upon the validity of their results.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

In the context of an evolving digital-based global economy, this study aims to investige the impact of digital transformation (DT) on a firm’s internal control (IC) quality. It also explores how the personal traits of (CEOs) – such as age, gender and educational background – intersect with DT to shape the IC quality in various types of state-owned enterprises (SOEs).

The study uses the data from China A-shares non-financial enterprises, listed on Shanghai and Shenzhen stock exchanges between 2007 and 2020. Using the fixed effect regression method alongside various statistical techniques, such as propensity score matching, alternative analysis and instrumental variables analysis, yields robust findings. These methods effectively address issues related to functional form misspecification and potential biases from omitted explanatory variables.

The findings reveal a positive impact of DT on firm IC quality, and this impact is more pronounced in firms when the CEO is female, young and possesses a higher level of education. Notably, the study also distinguishes between central and local state-owned enterprises (SOEs), highlighting that DT has a greater influence on IC quality in central SOEs, where CEOs often have higher political ranks and closer to government monitoring. Overall, the findings are robust and consist to alternative variable and other statistical methods.

Following are the significant implications for both academia and business. First, firms that effectively adopt DT to enhance IC not only gain a strategic advantage over competitors but also establish efficient risk management practices and a robust IC system. Second, better IC resulting from DT can enhance investor and stakeholder confidence. This is particularly important for publicly traded companies, where investors and analysts closely scrutinize the robustness of IC systems. Third, DT could result in cost savings over time, as automation and streamlined processes may reduce the need for manual efforts and resource-intensive tasks associated with IC.

The findings are contributed to the literature in multiple ways. It enhances our comprehension of the intricate DT-IC quality relationship, and provides valuable insights into the transformative impact of DT on organizational operations and risk management. It also introduces a novel perspective by investigating how CEOs personal traits intersect with DT to shape IC quality, contributing to upper echelons theory. Furthermore, it expands the discussions on firm ownership by considering the types of SOEs (central vs. local), in the DT-IC quality context.

The purpose of this study is to examine the impact of board diversity (e.g. education, gender, nationality and royal family members) on voluntary corporate social responsibility (CSR) disclosure for a sample of banks listed in the Arabian Gulf Council countries.

The authors use the Global Reporting Initiative guidelines to construct the CSR disclosure index. The empirical analysis is based on the data of banks listed in the Gulf Cooperation Council countries over the period 2011–2019. To tackle the potential issue of endogeneity, the authors apply the system generalized method of moments (GMM) estimation approach to investigate the relationship between board diversity and CSR disclosure index.

The findings of the analysis show that there is a significant relationship between board diversity and the level of voluntary CSR disclosure. Specifically, the authors find that diversity captured by the education level, nationality and the presence of royal family members on board is positively associated with the level of voluntary CSR disclosure while diversity captured by the gender of board members is negatively associated with the level of voluntary CSR disclosure.

The regulators, policymakers, stakeholders and the board of directors become aware of the diversity mechanisms that must be used to promote CSR practices in the banking sector of Arabian Gulf countries.

The authors extend the existing literature by providing empirical evidence on the association between board diversity and voluntary CSR disclosure practices of banks operating in the Arabian Gulf countries. This study also highlights that board gender diversity may have a different impact on voluntary CSR disclosure between developed countries and developing countries. This paper also provides preliminary evidence on the importance of education level, the presence of foreign and royal directors on board to influence CSR practices of banks operating in the Arabian Gulf countries.

Although Islamic banks offer superior financial services than other interest-based conventional banks, they could not expand their share and dominate the markets in several Islamic countries. This problem could be attributed to some causes not addressed. The current study proposes Islamic financial literacy as an important factor that could help aggress this problem. Due to a wide variety of Islamic financial services and the lack of understanding of these services, the banks' small business customers are indifferent between Islamic and interested-based conventional services to finance their business.

This study uses the exploratory technique of multiple correspondence analysis to detect any potential role of Islamic financial literacy in customers' preference for Islamic banks over conventional ones. The potential effect was tested with other essential factors, such as the customers' age, gender, and educational level. This analysis was conducted on a data set from 2061 banks' small businesses customers using the mall-intercept survey method.

The study shows a low level of Islamic financial literacy among Yemeni banks' small business owners' customers. Furthermore, despite integrating some critical factors that could influence the actual bank selection process among Yemini banks' customers, the authors found a decisive potential role of Islamic financial literacy as one of the key determinants of bank selection preferences.

This is the first paper to explore the potential role of Islamic financial literacy on the actual selection between Islamic Banks and their counterparts: the conventional banks in Yemen. The research results could build a more comprehensive theoretical model on Islamic banks' customer behavior.

Purpose: The primary purpose is to discuss the productivity and digitalisation interaction at the theoretical level, analyse the productivity and digitalisation differences between the European Union (EU)-14 and EU-13 countries, and evaluate the digitalisation impact on the manufacturing sector labour productivity of the EU countries.

Need for study: The average added value created per capita in new EU countries (EU-13) is one-third lower than in old EU countries (EU-14). To increase productivity, manufacturing companies must adapt to modern trends and take advantage of industrial digitisation opportunities. Digitisation can improve production efficiency, reduce costs, and improve product quality, allowing continuous monitoring and analysis of production data, enabling informed decisions and faster problem-solving.

Methodology: Analysis of scientific literature, comparing viewpoints, insights, and conclusions. The empirical study includes calculating rates of change of indicators, differences between EU-14 and EU-13, and structural analysis. The impact of digitisation on the productivity of EU countries is studied by creating a correlation matrix and using regression analysis: ordinary least square models.

Findings: EU-13 countries are behind EU-14 in labour productivity and manufacturing digitalisation. Digitalisation positively impacts productivity per employee. A faster increase in digitisation, industrial robot use, and e-commerce sales could significantly increase productivity in EU-13, reducing productivity differences between countries.

Practical implications: This study highlights the need for policy promoting digitisation innovation, particularly in EU-13 countries, to be implemented by both national and EU-based economic development and regional and cohesion institutions.

The purpose of this research is to examine how the implementation of a balanced scorecard (BSC) affects business outcomes in both information technology (IT) and non-IT sectors.

Partial least squares structural equation modeling (PLS-SEM) was used to test the hypothesis. A random sample was used to collect 170 responses from the IT companies and 166 from non-IT companies by using the questionnaire method. The questionnaire was distributed to the top- and middle-level managers in Bangalore city, and we used SmartPLS software to explore the relationship between our research constructs.

The results of this study indicate that a BSC has a significant and positive impact on organizational performance in IT and non-IT sectors. The main distinction in this study is that all BSC perspectives [learning and growth perspective, internal business process (IBP) perspective, customer perspective (CP) and financial perspective (FP)] have a significant, direct and indirect impact on IT companies. On the other hand, solely three BSC perspectives (IBP perspective, CP and FP) have a significant impact on non-IT companies, while learning and growth perspective has an insignificant impact on the FP.

This study provides a critical theoretical and practical contribution of a BSC on business performance in IT and non-IT industries.

India’s rapid economic growth has triggered a significant transformation in its logistics sector, fueled by comprehensive reforms and digital initiatives outlined in the National Logistics Policy. Smart warehouses, equipped with cutting-edge technologies such as IoT, AI and automation, have taken center stage in this evolution. They play a pivotal role in India’s digital journey, revolutionizing supply chains, reducing costs and boosting productivity. This AI-driven transformation, in alignment with the “Digital India” campaign, positions India as a global logistics leader poised for success in the industry 4.0 era. In this context, this study highlights the significance of smart warehouses and their enablers in the broader context of supply chain and logistics.

This paper utilized the ISM technique to suggest a multi-tiered model for smart warehouse ecosystem enablers in India. Enablers are also graphically categorized by their influence and dependence via MICMAC analysis.

The study not only identifies the 17 key enablers fostering a viable ecosystem for smart warehouses in India but also categorizes them as linkage, autonomous, dependent and independent enablers.

This research provides valuable insights for practitioners aiming to enhance technological infrastructure, reduce costs, minimize wastage and enhance productivity. Moreover, it addresses critical academic and research gaps contributing to the advancement of knowledge in this domain, thus paving the way forward for more research and learning in the field of smart warehouses.

The qualitative modeling is done by collecting experts' opinions using the ISM technique solicits substantial value to this research.