Search results

The purpose of this study is to examine the impact of corporate governance (CG) on intellectual capital efficiency (ICE) in Islamic banks (IBs) of Organisation of Islamic Cooperation (OIC) countries.

A sample of 129 IBs is drawn from the 29 OIC countries from 2008 to 2017. A two-step system of the generalised method of moments has been employed to account for the unobserved endogeneity and heteroscedasticity issue that arose due to time-variant and time-invariant variables.

The results revealed that CG measures, namely board size, non-executive directors do explain the extent and quality of ICE in the expected direction. In contrast, CEO duality, Shariah board and audit committee are negatively associated with the ICE. Moreover, the authors observed that male CEO in IBs has negative, but foreign ownership has a positive association with ICE in determining the extent of ICE in IBs. This study contributes specifically to the stakeholder theory and the literature of ICE and CG.

The findings of the study provide insight into how a larger board can overcome skill deficiency and how making more investment in ICE would help to enhance productivity. Hence, bank managers, regulators, policymakers and shareholders have strong interest in designing the appropriate CG structure to develop ICE in banks.

This is one of the few studies which provide empirical evidence of CG mechanism to boost the ICE in the perspective of IBs of the OIC countries.

Local Government in Indonesia annually publishes Local Government Financial Statements (LGFS) for helping their stakeholders in making decisions. Audit Opinion of the LGFS for counties and cities in East Java Province during the last 8 years (2006-2013) showed a quite astonishing result. From all of 301 financial statements, only 45 LGFS (14.95%) obtained Unqualified Opinion, other financial statements (256 or 85.05%) received Non-Unqualified Opinion. This study aims to analyze the accounts and problems in the accounts which cause LGFS obtain Non-Unqualified Opinion. Using content analysis with NVIVO10 applications, this study analyzed 256 audit opinions of the LGFS of counties and cities in East Java during 2006-2013 that obtained Non-Unqualified Opinion to identify the accounts and problems in the accounts which cause LGFS obtain Non-Unqualified Opinion. The results showed that the most frequent accounts as an exception in the audit opinion are the accounts on Budget Realization Report (BR) with the frequency of occurrence as much as 6628 times. The Balance Sheet (BS) accounts was at the second place with the total frequency of occurrence 4206 times. And last, there was a Cash Flow Statement (CF) account with the frequency of occurrence as much as 693 times. In BR, the most frequent account which appears as an exception is spending account (as much as 4198 times), while the assets are the most frequent accounts as an exception in the Balance Sheet (as much as 4206 times). The problem with the accounts that often appear as an exception was mainly due to the weakness of the Internal Control System (ICS), followed by non-compliance with the provisions of law and the last problem is in-economies, inefficiency and ineffectiveness.

Purpose – This research study aims to answer the question of how good is the development of the extended regency, and which shows better autonomy of development—before or after expanding. The implications of this study is to answer whether expanding a regent is truly needed to improve the economic development and welfare of the remote regions and their people. This study analyzes the autonomous state of three regencies, North Aceh, Bireuen and Lhokseumawe districts, which have expanded. The analysis takes into consideration the difference in the proportion of their regional revenues, budgeting perfomance, and economic growth as indicators of regional autonomy.

Design/Method/Approach – The data used in this research are secondary data sourced from the budget realization report and the accountability report of North Aceh, Bireuen, and Lhokseumawe districts from 2006 to 2013. The data analysis methods used in this study are the analysis of financial ratios and the comparative mean of one way anova.

Finding – The results showed a significant value or a probability value more than 0.05. Thus, the hypothesis (H1) is rejected, and therefore the hypothesis (H0) is received.

Research Impication – The implication is that there is no difference in the average of regional autonomy of North Aceh Regency, Bireuen, and Lhokseumawe districts as seen from the proportion of local revenue, budgeting perfomance, and regional growth. It means that with regard to financial performance there is no difference in the level of independence in autonomy among the three regions. The proportion of local revenue, financial permormance area, and the development of North Aceh, Bireuen, and Lhokseumawe districts demonstrate no influence on the level of independence in autonomy.

The current study has a two-fold purpose. Firstly, it aims to analyze the extent to which knowledge management (KM) affects the performance of individuals (task and contextual) on the one hand and that of organizations (product or service, perceived and financial) on the other hand. Secondly, it proposes to investigate the mediating effect of motivation and innovation in the relationship between KM and individual and organizational performance.

Partial least squares structural equation modeling (PLS-SEM) was employed in this study, with mediation analysis performed using advanced PLS-SEM techniques. A total of 1,284 respondents from organizations in both the public and private sectors were included in the sample.

The findings emphasize that KM has a more significant direct effect on individual performance compared to organizational performance. Concurrently, in terms of indirect influence, it is found that KM, through motivation and innovation, has a positive and significant effect on both individual and organizational performances, with a higher influence on the organizational one.

The originality of the work can be noted in designing two different structural models to represent the proposed relationships at the individual and organizational levels. These findings could provide organizational decision makers with empirical evidence, helping them (1) internalize the significance of the KM process in organizations as well as its subsequent effects on individual and organizational performance and (2) identify factors that mediate variable relationships.

Digital technology's integration into education has transformed learning frameworks, necessitating the exploration of factors influencing students’ engagement in digital informal settings. This study, grounded in self-determination theory (SDT), proposes a model comprising artificial intelligence (AI) competence, chatbot usage, perceived autonomy (PA), digital informal learning (DIL) and students’ engagement.

The study collected survey data from 409 participants at Saudi Arabian universities, ultimately using 387 valid responses for analysis. This dataset was subjected to a thorough examination to confirm the validity of our proposed model. To decipher the complex interactions within our model, we utilized partial least squares structural equation modeling (PLS-SEM). The study adopted a disjoint two-stage method to formulate a reflective-formative higher-order construct (HOC).

The study's findings showed that cognitive learning (CL), metacognitive learning (MCL) and social and motivational learning (SML) are the essential components of DIL. Significantly, the study determined that AI competence, chatbot usage, PA and DIL markedly affect students’ engagement. Moreover, the R² value of 0.592 for student engagement indicates the model's robustness in explaining 59.2% of the variance, highlighting its effectiveness in identifying key drivers of student engagement in DIL contexts.

This research enhances understanding by detailing the intricate relationships among AI competence, chatbot usage, and students’ engagement in informal digital learning. It extends SDT to emphasize intrinsic motivations and AI capabilities, introducing reflective-formative HOCs for comprehending educational intricacies. It provides practical strategies for enhancing AI abilities and chatbot use in education, promoting personalized, engaging and autonomous digital learning spaces, thereby advancing educational theory and practice.

This paper aims to investigate how organization capital influences different forms of corporate risk. It also explores how the relationship between organization capital and risks varies in the cross-section of firms.

To test the hypothesis, this study employs the ordinary least squares (OLS) regression model using a large sample of the United States (US) data over the 1981–2019 period. It also uses an instrumental variable approach and an errors-in-variables panel regression approach to mitigate endogeneity problems.

The empirical results show that organization capital is positively related to both idiosyncratic risk and total risk but negatively related to systematic risk. The cross-sectional analysis shows that the positive relationship between organization capital and idiosyncratic risk is significantly more pronounced for the subsample of firms with high information asymmetry and human capital. Moreover, the negative relationship between organization capital and systematic risk is significantly more pronounced for firms with greater efficiency and firms facing higher industry- and economy-wide risks.

The findings have important implications for investors and policymakers. For example, since organization capital increases idiosyncratic risk and total risk but reduces systematic risk, investors should take organization capital into account in portfolio formation and risk management. Moreover, the findings lend support to the argument on the recognition of intangible assets in financial statements. In particular, the study suggests that standard-setting bodies should consider corporate reporting frameworks to incorporate the disclosure of intangible assets into financial statements, particularly given the recent surge of corporate intangible assets and their critical impact on corporate risks.

To the best of the authors' knowledge, this is the first study to adopt a large sample to provide systematic evidence on the relationship between organization capital and a wide range of risks at the firm level. The authors show that the effect of organization capital on firm risks differs remarkably depending on the kind of firm risk a particular risk measure captures. This study thus makes an original contribution to resolving competing views on the effect of organization capital on firm risks.

Sports marketing and sponsorship research is located at the intersection of behavioral and design research, which means that it analyzes the current world and shapes a future world. This dual focus poses challenges for formulating and testing theories of sports marketing.

This article develops criteria for categorizing theoretical concepts as either behavioral or formed as different ways of expressing ideas of sports marketing research. It emphasizes the need for clear concept categorization for proper operationalization and applies these criteria to selected theoretical concepts of sports marketing and sponsorship research.

The study defines three criteria to categorize theoretical concepts, namely (1) the guiding idea of research, (2) the role of observed variables, and (3) the relationship among observed variables. Applying these criteria to concepts of sports marketing research manifests the relevance of categorizing theoretical concepts as either behavioral or formed to operationalize concepts correctly.

This study is the first in sports marketing to clearly categorize theoretical concepts as either behavioral or formed, and to formulate guidelines on how to differentiate behavioral concepts from formed concepts.

A significant number of studies have been conducted to analyze and understand the relationship between gas emissions and global temperature using conventional statistical approaches. However, these techniques follow assumptions of probabilistic modeling, where results can be associated with large errors. Furthermore, such traditional techniques cannot be applied to imprecise data. The purpose of this paper is to avoid strict assumptions when studying the complex relationships between variables by using the three innovative, up-to-date, statistical modeling tools: adaptive neuro-fuzzy inference systems (ANFIS), artificial neural networks (ANNs) and fuzzy time series models.

These three approaches enabled us to effectively represent the relationship between global carbon dioxide (CO₂) emissions from the energy sector (oil, gas and coal) and the average global temperature increase. Temperature was used in this study (1900-2012). Investigations were conducted into the predictive power and performance of different fuzzy techniques against conventional methods and among the fuzzy techniques themselves.

A performance comparison of the ANFIS model against conventional techniques showed that the root means square error (RMSE) of ANFIS and conventional techniques were found to be 0.1157 and 0.1915, respectively. On the other hand, the correlation coefficients of ANN and the conventional technique were computed to be 0.93 and 0.69, respectively. Furthermore, the fuzzy-based time series analysis of CO₂ emissions and average global temperature using three fuzzy time series modeling techniques (Singh, Abbasov–Mamedova and NFTS) showed that the RMSE of fuzzy and conventional time series models were 110.51 and 1237.10, respectively.

The paper provides more awareness about fuzzy techniques application in CO₂ emissions studies.

These techniques can be extended to other models to assess the impact of CO₂ emission from other sectors.