Search results

Exploiting an exogenous regulatory shock and a novel measure of asset redeployability, this paper aims to explore the effect of independent directors on asset redeployability. In particular, the authors use an innovative measure of asset redeployability recently developed by Kim and Kung (2016). This novel index has been rapidly adopted in recent literature.

Relying on a quasi-natural experiment, the authors execute a difference-in-difference analysis based on an exogenous regulatory shock to board independence. To mitigate endogeneity and demonstrate causation, the authors also perform propensity score matching, instrumental-variable analysis and Oster’s (2019) approach for testing coefficient stability.

The difference-in-difference estimates show that firms forced to raise board independence have significantly fewer redeployable assets after the shock than those not required to change board composition. This is consistent with the managerial myopia hypothesis. Subject to more intense monitoring, managers behave more myopically, focusing more on assets that are currently useful to the firm and less on redeployability in the future.

The study makes key contributions to the literature. First, the study is the first to examine the effect of board governance on asset redeployability. Second, the authors exploit an innovative index of asset redeployability that has been recently constructed in the literature. Third, by using a natural experiment, the results are much more likely to reflect causality than merely an association.

The purpose of this study is to investigate internal governance mechanisms factors, focusing on Shari’ah-based governance mechanisms that affect the price synchronicity of Islamic banks (IBs).

This study analyzes and compares the effect of Shari’ah and regular governance mechanisms on stock price synchronicity over 2013–2022 using a sample of 51 listed IBs in 13 countries in the Middle East and South Asia region. Using generalized least square method, this paper tests nine hypotheses addressing Shari’ah and regular governance mechanisms.

The findings generally reveal that Shari’ah-based governance mechanisms have a significant impact on the stock price synchronicity of IBs. The main determinants of stock price synchronicity among IBs are SSB size, SSB diversity, SSB members’ qualifications in finance Islamic jurisprudence and SSB interlocks. Shari’ah governance plays a detrimental role in improving the association between bank stock price synchronicity and transparency.

This paper includes three main limitations that may affect the accuracy of the findings. First, this paper relied on publicly available financial statements of IBs online. Hence, the data in this study is from few IBs in each country, which limits the analysis given the reliance is on the best-performing IBs in the country. Second, the results are restricted to the Middle East and South Asia and may not be generalized to other regions. Third, the sample is dominated by Middle East countries (i.e. 37 IBs out of 51).

Both Shari’ah governance and regular governance have an impact on the transparency of IBs. Policymakers or regulators could encourage IBs to embed SSBs into their internal governance structure for the positive impact the SSBs attributes have on stock price synchronicity and transparency.

This research studies IBs, unlike most other works that focus on firms.

We examine the market valuation of targets with multiple large shareholders (MLS) and single large shareholder (SLS) structures, in an international sample of M&A announcement in 19 countries outside North America. We find that the presence and power of MLS in these firms are negatively associated with abnormal returns and first-bid-to-merger-completion returns, suggesting that MLS mitigate agency problems in the target, and hence their acquisition is perceived as “a loss of good governance.” The negative association between MLS targets and returns is stronger in widely held firms suggesting that MLS indeed curb expropriation of minority shareholders. By contrast, when the second largest shareholder in the MLS structure of the target is a family, we find positive cumulative abnormal returns at the merger announcement, suggesting exacerbated agency problems in these firms that should benefit from the “acquisition of good governance.” Our evidence is robust to a battery of tests and to addressing potential endogeneity.

This paper aims to examine the impact of Shari’ah supervisory boards (SSBs) on the performance of Islamic banks (IBs). It also tests whether SSBs’ attributes affect the performance of IBs. Based on a sample of 1,803 Islamic bank-year observations from 82 banks in 15 countries over the period 1993-2014 and controlling for factors known to affect bank performance, this study reveals a robust and significant positive relationship between SSBs and Islamic bank performance. This study also shows that the characteristics of SSBs affect the performance of IBs. This research reveals how SSBs influence the performance of IBs, as well as the processes and roles SSBs use to ensure Shari’ah compliance in business transactions.

The purpose of this study design is to relate SSB presence, size and diversity to financial performance using three techniques. The first technique is a multivariate data analysis that analyzes data arising from more than one variable. The second technique is a clustered regression (clustering by bank), which corrects for serial correlation and produces unbiased t-statistics. Because this sample is drawn from panel data, it is expected serial autocorrelation of the independent variables and error term within banks. In cases where within-company correlation exists, t-statistics based on average regression coefficients from year-by-year regression are upwardly biased and potentially severe (Peterson, 2009). Therefore, this study uses a technique that agrees with Stock and Watson (2002), who show that the standard method of calculating heteroskedasticity-robust standard errors for the fixed-effects estimator generates inconsistent variance estimates. Thus, using the clustered regression is consistent with the fixed-effects estimator. The third technique is a two-stage least-squares regression that helps build an instrumental variable for robustness tests purposes.

The findings suggest that large corporate boards and large SSBs are more efficient in dealing with different monitoring and advisory roles than small SSBs. Consequently, this suggests that increasing the size of corporate boards and SSBs should improve monitoring and advisory functions, management behavior and organizational performance.

It is possible that there is an upper limit to this benefit, however; we do not explore this limit, which therefore provides opportunities for additional research. Because Shari’ah compliance relates only to a rational legal framework of negative screening relegated to interest prohibition and limiting uncertainty. The interest prohibition and limiting uncertainty have not been investigated between the two samples due to data unavailability. In addition, limited accounting-based measures of financial performance may not accurately portray IB performance; hence, an additional market measure is implemented, which is Tobin’s Q.

Ultimately, these findings could help IBs improve their financial results by enhancing their internal and external governance mechanisms (Walsh and Seward, 1990). They provide a basis for developing larger, more diverse SSBs that are more focused on complying with Shari’ah and corporate governance. The results also have significant policy implications for improving firm-level corporate governance versus improving country-level institutional factors. Both views have their advocates. However, it is very difficult to reform the legal system in a short time. Still, this study shows that struggling IBs have a way to improve their corporate governance and simultaneously improve their financing environment.

This research contributes to the literature on the effects of SSBs on IBs’ organizational financial performance, processes and roles. It is the first to examine empirically the underpinnings of how SSBs affect organizational financial performance via agency theory and contingency theory.

This study systematically reviews the existing literature on the application of gamification in logistics and supply chain management (LSCM). This study aims to categorise the literature in various logistics and supply chain domains, to conceptualise the gamification framework pertinent in the context of LSCM and to provide a research agenda for scholars in the area.

The study’s methodology adopts the Preferred Reporting Items for Systematic Review and Meta-Analysis framework to conduct a systematic literature review. Forty relevant papers published from 2012 to 2023 are included in the analysis.

Augmented reality, blockchain, education, sustainability and warehousing have been identified as the key focus areas in which gamification is applied. Furthermore, the paper highlights different research approaches used to study these domains, maps the literature with gamification constructs (affordances, psychological outcomes and behavioural outcomes) and provides potential research avenues for future scholars.

This review offers evidence of the impact of gamification on workforce dynamics, employee motivation, job satisfaction, trust, employee engagement and productivity. The study significantly contributes to the academic community by offering a conceptual framework and meaningful avenues for future researchers.

This research work contributes to the gamification, logistics and supply chain literature by providing a more comprehensive and methodical knowledge of the field. This study adds to the body of knowledge by offering a reference framework for future scholars based on a synthesis of the studies published so far in the area.

Libraries need to develop information processing systems for evaluation, budgeting, planning, and operations. Electronic spreadsheets lend themselves to a variety of applications, but are time‐consuming to create. A model template and macros that can be used in many different types of library data analysis have been developed here. The procedures demonstrated here can build an essential set of tools for meeting fundamental goals of administrative efficiency, effective use of library resources, staff motivation, and rational policy making.

With multiple-related organizations, worldwide infections, deep economic recession and public disorder, and large consumption amount of anti-epidemic resources, the coronavirus disease 2019 (COVID-19) has been defined as a public health emergency of international concern (PHEIC). Nowadays, Wuhan has recovered from the pandemic disaster and reentered normalization. The purposes of this study are to (1) summarize organization collaboration patterns, successful experience and latent defects under across-stage evolution of Wuhan's cooperation governance mode against the pandemic, and on the basis, (2) reveal how the COVID-19 development trends and organizations' collaborative behaviors affected each other.

Detailed content analysis of online news reports covering COVID-19 prevention and control measures on the website of Wuhan Municipal Government was adopted to identify organizations and their mutual collaborative interrelationships. Four complex network (CN) models of organization collaboration representing the outbreak, preliminary control, recession and normalization stages, respectively, were established then. Time-span-based dynamic parameter analyses of the proposed networks, comprising network cohesiveness analysis and node centrality analysis, were undertaken to indicate changes of global and local characteristics in networks.

First, the definite collaborative status of Wuhan Headquarters for Pandemic Prevention and Control (WHPPC) has persisted throughout the period. Medical institutions and some other administrations were the most crucial participants collaborating with the WHPPC. Construction-industry organizations altered pandemic development trends twice to make the situation controllable. Media, large-scale enterprises, etc. set about underscoring themselves contributions since the third stage. Grassroots cadres and healthcare force, small and medium-sized enterprises (SMEs), financial institutions, etc. were essential collaborated objects. Second, four evolution mechanisms of organization collaboration responding to the COVID-19 in Wuhan has been proposed.

First, universality of Wuhan-style governance experience may be affected. Second, the stage-dividing process may not be the most appropriate. Then, data source was single and link characteristics were not considered when modeling.

This study may offer beneficial action guidelines to governmental agencies, the society force, media, construction-industry organizations and the market in other countries or regions suffering from COVID-19. Other organizations involved could also learn from the concluded organizations' contributions and four evolution mechanisms to find improvement directions.

This study adds to the current theoretical knowledge body by verifying the feasibility and effectiveness of investigating cooperation governance in public emergencies from the perspectives of analyzing the across-stage organization collaboration CNs.

Construction projects in Malaysia are often delayed and over budget due to heavy reliance on labor. Linear regression (LR) models have been used in most labor cost (LC) studies, which are less accurate than machine learning (ML) tools. Construction management applications have increasingly used ML tools in recent years and have greatly impacted forecasting. The research aims to identify the most influential LC factors using statistical approaches, collect data and forecast LC models for improved forecasts of LC.

A thorough literature review was completed to identify LC factors. Experienced project managers were administered to rank the factors based on importance and relevance. Then, data were collected for the six highest ranked factors, and five ML models were created. Finally, five categorical indices were used to analyze and measure the effectiveness of models in determining the performance category.

Worker age, construction skills, worker origin, worker training/education, type of work and worker experience were identified as the most influencing factors on LC. SVM provided the best in comparison to other models.

The findings support data-driven regulatory and practice improvements aimed at improving labor issues in Malaysia, with the possibility for replication in other countries facing comparable problems.