Search results

The focus on corporate governance has increased after the financial collapses of several banks worldwide, such as Silicon Valley Bank and First Republic Bank in the USA, and the failure of the Lebanese banking sector. This study examines the impact of audit committee (AC) characteristics on financial performance and investigates the moderating effect of ownership concentration (OC) on the associations between AC characteristics and profitability.

The current research is carried out based on 211 Lebanese banks’ annual reports, focusing on the period from 2012 to 2021. The ordinal least squares (OLS) and the hierarchical multiple regression analysis were adopted to test the study’s hypotheses.

The outcomes reveal that AC size, AC frequency of meetings, and banks’ size (control variable) positively affect financial performance; however, OC does not moderate the associations between the AC characteristics and banks’ profitability.

According to the researcher’s knowledge, no prior study has investigated the moderating effect of OC on these associations. Moreover, the current study contributes to the literature that documented mixed and inconsistent results regarding the direct associations between AC characteristics and financial performance.

This study aims to examine the factors that influence the relationship between sustainability and financial performance (FP) of the European listed companies.

This study analyzed data from 795 companies in 21 European countries by applying linear mixed-effects multilevel regressions, a two steps system generalized method of moments and quantile regression models to uncover the links between sustainability and FP.

The past four decades have witnessed abundant research to determine the relationship between corporate sustainability and FP. Thus, conducting further research in 2023 could be seen as “reinventing the wheel.” Yet, earlier research considered firms as isolated entities with sustainability and FP being dependent only on that firm’s actions. By contrast, with the help of network governance theory, this study shows that a firm’s sustainability and FP depend on an interplay among interorganizational actors, such as institutional qualities, macroeconomic factors and an embrace of sustainability. Here, large firms play an essential role. Three significant findings are drawn. First, sustainability performance has a significant impact on FP in the European context. Second, the institutional quality (IQ) of the rule of law and control of corruption plays a crucial role in enhancing sustainability and FP, and finally the interaction of IQ and economic growth helps to increase companies’ market value (Tobin’s Q). The consistent and empirically robust findings offer key lessons to policymakers and practitioners on the interplay among multiple actors in corporate sustainability and FP.

A synergetic multifaced relationship between governmental institutions and corporations is inevitable for ensuring sustainable development. The degree of intimacy in the relationship, of course, will be determined by the macroeconomic environment.

In this research, this study theoretically and empirically identified that corporate sustainability and FP are not solely dependent on corporate operation. Rather, it is transformed, modified and shaped through an interaction of multiple actors’ trajectories in the macro business environment.

In the uncertain business environment, the supply chains are under pressure to balance routine operations and prepare for adverse events. Consequently, this research investigates how artificial intelligence is used to enable resilience among supply chains.

This study first analyzed the relationship among different characteristics of AI-enabled supply chain and how these elements take it towards resilience by collecting the responses from 27 supply chain professionals. Furthermore, to validate the results, an empirical analysis is conducted where the responses from 231 supply chain professionals are collected.

Findings indicate that the disruption impact of an event depends on the degree of transparency kept and provided to all supply chain partners. This is further validated through empirical study, where the impact of transparency facilitates the mass customization of the procurement strategy to Last Mile Delivery to reduce the impact of disruption. Hence, AI facilitates resilience in the supply chain.

This study adds to the domain of supply chain and information systems management by identifying the driving and dependent elements that AI facilitates and further validating the findings and structure of the elements through empirical analysis. The research also provides meaningful implications for theory and practice.

This research paper aims to contribute to the field of innovation performance benchmarking by identifying appropriate benchmarking groups and exploring learning opportunities and integration directions.

The study employs a multi-dimensional innovation-driven clustering methodology to analyze data from the 2019 edition of the Global Innovation Index (GII). Hierarchical and K-means Cluster Analysis techniques are applied using various sets of distance matrices to uncover and analyze distinct innovation patterns.

This study classifies 129 countries into four clusters: Specials, Advanced, Intermediates and Primitives. Each cluster exhibits strengths and weaknesses in terms of innovation performance. Specials excel in the areas of institutions and knowledge commercialization, while the Advanced cluster demonstrates strengths in education and ICT-related services but shows weakness in patent commercialization. Intermediates show strengths in venture-capital and labour productivity but display weaknesses in R&D expenditure and the higher education quality. Primitives exhibit strength in creative activities but suffer from weaknesses in digital skills, education and training. Additionally, the study has identified 35 indicators that have negligible variance contributions across countries.

The study contributes to finding the relevant countries’ grouping for the enhancement of communication, integration and learning. To this end, this study highlights the innovation structural differences among countries and provides tailored innovation policies.

A research line has emerged that is concerned with investigating human factors in information systems and cyber-security in organizations using various behavioural and socio-cognitive theories. This study aims to explore human and contextual factors influencing cyber security behaviour in organizations while drawing implications for cyber-security in higher education institutions.

A systematic literature review has been implemented. The reviewed studies have revealed various human and contextual factors that influence cyber-security behaviour in organizations, notably higher education institutions.

This review study offers practical implications for constructing and keeping a robust cyber-security organizational culture in higher education institutions for the sustainable development goals of cyber-security training and education.

The value of the current review arises in that it presents a comprehensive account of human factors affecting cyber-security in organizations, a topic that is rarely investigated in previous related literature. Furthermore, the current review sheds light on cyber-security in higher education from the weakest link perspective. Simultaneously, the study contributes to relevant literature by gaining insight into human factors and socio-technological controls related to cyber-security in higher education institutions.

This study aims to posit that managerial value would be one of the responsible factors for the difference in corporate social responsibility practice among businesses. It then empirically tested the effect of managerial value, with the moderation of organizational culture, on corporate social responsibility practice.

The authors have devised a “moderated micro-macro model” type of multilevel model, wherein managerial value took the micro (individual level) predictor variable role, stakeholder-based corporate social responsibility practice the macro (organizational level) outcome variable role and organizational culture the macro level moderating variable role. Because they need the attention of inquiry, large manufacturing firms in the Amhara region of Ethiopia, with a sample size of 53, constituted the organizational level units. The recent performance of the firms against corporate social responsibility practice and organizational culture have been judged by 473 randomly chosen employees. Managerial value has been rated by randomly picked managers, numbered 253. Analytically, Croon and van Veldhoven’s multilevel analytical package and Mplus software suited the designed model.

The study has revealed that managerial value, indeed, is a potential positive driver of CSR practice, the two managerial value dimensions demonstrated differential effects on corporate social responsibility practice and only one of the organizational culture dimensions, hierarchical culture, played a moderation role in managerial value – corporate social responsibility practice link.

The model and this empirical test have not been previously verified.

The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of supply chain management (SCM) and logistics, what are the challenges in BDA applications in the field of SCM and logistics and what are the determinants of successful applications of BDA in the field of SCM and logistics.

This paper conducts a systematic literature review (SLR) to analyse the findings of 44 selected papers published in the period from 2016 to 2020, in the area of BDA and its impact on SCM. The designed protocol is composed of 14 steps in total, following Tranfeld (2003). The selected research papers are categorized into four themes.

This paper identifies sets of benefits to be gained from the use of BDA in SCM, including benefits in data analytics capabilities, operational efficiency of logistical operations and supply chain/logistics sustainability and agility. It also documents challenges to be addressed in this application, and determinants of successful implementation.

The scope of the paper is limited to the related literature published until the beginning of Corona Virus (COVID) pandemic. Therefore, it does not cover the literature published since the COVID pandemic.

This paper contributes to the academic research by providing a roadmap for future empirical work into this field of study by summarising the findings of the recent work conducted to investigate the uses of BDA in SCM and logistics. Specifically, this paper culminates in a summary of the most relevant benefits, challenges and determinants discussed in recent research. As the field of BDA remains a newly established field with little practical application in SCM and logistics, this paper contributes by highlighting the most important developments in contemporary literature practical applications.

The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.

Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.

Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.

The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.

This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.

This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.

In the knowledge management (KM) literature, there are umpteen discussions on knowledge sharing; however, the scholarly community still faces a dearth of literature on knowledge hiding behavior (KHB) and its determinants. The current study aims to examine the direct effect of dark triad (DT) personality dimensions (machiavellianism, narcissism and psychopathy) on KHB dimensions (rationalized hiding, evasive hiding and playing dumb). Drawing on social control theory, this study also explores the moderating effect of workplace spirituality (WS) on the direct relationship between DT and KHB.

Using purposive sampling, 281 matched-pair datasets from faculty members working with higher education institutions (HEI) in India have been obtained. The direct relationship has been tested through regression analysis and moderation analysis has been performed using the PROCESS macro for SPSS.

The study has successfully mapped DT dimensions with KHB dimensions, and it is observed that machiavellians mostly use evasive hiding, narcissists believe in rationalized hiding and paying dumb is mostly used by psychopaths. Workplace spirituality (WS) weakens the direct relationship between DT and KHB.

HEIs are advised to foster a climate conducive to WS by getting faculty to realize that their job is something larger than themselves through developing a sense of community among faculty members.

This empirical study extends the KM literature and expands the scope of bridging the gaps on KHB. It is one of the few studies to examine the impact of DT on KHB with WS as a moderator in HEIs.

This study aims to enhance understanding of malnutrition's effect on academic achievement of primary school students.

This is a descriptive, cross-sectional design built on Roy's adaptation model (RAM). This study uses a random cluster sample, consisting of 453 primary school students. Contextual stimuli (mother's educational level, income and child’s breakfast eating) and focal stimuli (wasting, thinness, body mass index and stunting) were examined regarding adaptive responses to student’s academic achievement.

The investigation revealed that Model 1, which took into account factors of age, gender, the frequency of breakfast, income, the number of family members and the education of mothers, explained 12% (R² = 0.12) of the variance in academic achievement. Stuntedness (β = −3.2 and p < 0.01), BMI (β = 0.94 and p < 0.001), family income per month (β = 5.60 and p < 0.001) and mother's education (β = 2.79 and p < 0.001) were the significant predictors in Model 2.

This study provides evidence that malnutrition is associated with ineffective academic achievement. Moreover, variables such as the mother's level of education, family income and the child’s breakfast consumption have a significant impact on academic achievements.

RAM is a useful framework for determining factors affecting people's reactions to difficult circumstances.