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In recent years, counterproductive knowledge behavior (CKB) and its types have received increasing interest in knowledge management as the degree of knowledge sharing and innovation in enterprises continues to increase. A rapidly growing number of studies have shed light on the important antecedents and consequences of employees’ CKB. However, the various labels, conceptualizations and operationalizations of CKB have fragmented this body of research. This study aims to systematically integrate the effects of the six types of organizational characteristics on CKB and further draws more general conclusions based on the results of previous studies.

Based on a survey of 103 effect values responsible for 52 CKB samples, the authors use the ABC theory to explore the effects of the six types of organizational characteristics on CKB. Moderator analysis were performed to resolve inconsistencies in empirical studies and understand the contexts under which CKB has the strongest or weakest effect.

The results showed that task interdependence and a positive organizational atmosphere, in general, negatively affect employees’ CKB in the moderation analysis. In contrast, workplace discomfort, negative organizational atmosphere, internal competition and time pressure positively and partly affect employees’ CKB. The direction and magnitude of these effects were affected by emotional factors, knowledge personnel types and sample sources. Discussing the theoretical, methodological and practical implications of these findings can offer a guiding framework for future research.

Better control of employees’ CKB is not achieved by adjusting organizational characteristics alone but by combining personal characteristics and mood changes with it to balance organizational characteristics and CKB. Furthermore, the large-sample joint study integrated the conceptual definition of CKB. The multivariate data study provided more reliable conclusions and a solid theoretical foundation for CKB research areas.

This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and regulatory adjustments (RAs) in Organization for Economic Cooperation and Development public commercial banks.

Using principal component analysis (PCA) and regression models, the research analyzes a representative data set of these banks.

A significant negative correlation between risk governance characteristics and RAs is found. Sensitivity analysis on the regulatory Tier 1 capital ratio and the total capital ratio indicates mixed outcomes, suggesting a complex relationship that warrants further exploration.

The study’s limited sample size calls for further research to confirm findings and explore risk governance’s impact on banks’ capital structures.

Enhanced risk governance could reduce RAs, influencing banking policy.

The study advocates for improved banking regulatory practices, potentially increasing sector stability and public trust.

This study contributes to understanding risk governance’s role in regulatory compliance, offering insights for policymaking in banking.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

This paper according to the logic of the “digital access divide--digital capability divide--digital outcome divide” aims to systematically discuss the impact of the digital divide on individual happiness in China, accounting for the variations that exist across different groups, as well as the corresponding mechanisms.

This paper presents cross-sectional analyses of the relationship between the digital divide and individual happiness in China. The analyses are based on data from the Chinese General Social Survey 2017, which academic institutions run on the Chinese Mainland. This database contains information on respondents' Internet access, skills and consequences of use, which can measure the digital divide of Chinese individuals at three levels.

First, individual happiness declined when they experienced the digital access divide in China. For the digital capability divide, the lower the usage skills, the more individual happiness declined. When analyzing the digital outcome divide, the greater the negative consequences, the more individual happiness declined. Second, the impacts of digital access, capability and outcome divide vary according to age, gender, education degrees, hukou, region and sub-dimensions. Third, the digital access and capability divide reduce individuals' happiness by lowering their self-rated social and economic status, whereas the digital outcome divide reduce individual happiness by lowering their fairness perception and social trust.

The authors believe that this is the first study to examine the impact and its variations among different groups of the three-level digital divide on individual happiness, as well as its mechanisms.

The purpose of this study was to determine the determinants of financial statement fraud: the perspective of pentagon fraud theory.

This study used quantitative methods with an explanatory research design by applying secondary data on Islamic banking companies listed on the Indonesia Stock Exchange (IDX).

External pressure affects financial statement fraud, ineffective monitoring affects financial statement fraud, external auditor quality affects financial statement fraud, change in auditor affects financial statement fraud, frequent number of CEO’s picture affects financial statement fraud, external pressure affects firm size, ineffective monitoring affects firm size, external auditor quality affects firm size, change in auditor affects firm size, frequent number of CEO’s picture affects firm size, firm size affects financial statement fraud, firm size mediates the relationship between external pressure on financial statement fraud, firm size mediates the relationship between ineffective monitoring on financial statement fraud, firm size mediates the relationship between external auditor quality and financial statement fraud, firm size mediates the relationship between change in auditor and financial statement fraud, firm size mediates the relationship between frequent number of CEO’s picture and financial statement fraud.

The limitations of this research were found during the research process and can be used as input for further research and related parties in conducting the research to obtain better research results. The limitations of this study are as follows: this study only focused on Islamic banking, so it cannot be generalized to other sectors. Besides, this study only tested five independent variables, one dependent variable and one mediating variable.

For external auditors, financial statement fraud by management might be caused by many factors and is a social as well as an economic problem that must be addressed immediately. Therefore, in carrying out the duties and roles as an external auditor, they must have an attitude of independence (not taking sides) in the mental attitude that must be maintained by the auditor related to the assignment. Auditors must have sufficient technical expertise and training as auditors. In carrying out the audit, the auditor should use their professional skills in responding carefully and thoroughly. Moreover, in carrying out audit work, the auditor must have a plan, must know adequate internal control and obtain sufficiently competent audit evidence.

To the best of the authors’ knowledge, very few studies in Indonesia have applied the Beneish model. There is only one study that implemented the Beneish model, and the study examined only a few companies listed on the IDX. The findings of the present study have important implications not only for banks but also for users of financial statement accounts in Indonesia, especially for investors, auditors, regulators, taxation and other state authorities.

Construction sustainability (CS) is a strategic reaction to the sustainability expectations of the construction industry's external stakeholders. The extant literature has viewed the environmental, social and economic dimensions of CS as having independent effects on financial performance. Due to the influence of common stakeholders, however, interactions in these dimensions will be present in their effect on financial performance. Accordingly, this study identifies the mechanisms of the interactions between the three CS dimensions and how they jointly affect financial performance.

Content analysis of GRI reports of 60 large construction organisations, followed by a hierarchical regression analysis was used to identify the interactions between environmental, social and economic CS in their effect on financial performance.

Economic CS was found to indirectly, and not directly, affect financial performance, the effect being mediated by both environmental and social CS. Environmental CS was found to have a strong negative effect on financial performance, whilst social CS was found to have a strongly significant positive effect on financial performance.

The motivation for engaging in CS is that investment in economic CS will have a positive effect on both environmental and social CS outcomes, which, in turn can have a combined effect on financial performance.

This is one of the first studies investigating the effect of interactions between the environmental, social and economic CS dimensions on the financial performance of construction organisations. It is also one of the first studies that applies a sociotechnical framework to this relationship.

Micro, small and medium-sized enterprises (MSMEs) are vital for economic growth in developing countries. Yet, little research has explored the link between Islamic principles and MSME performance, especially in Uganda. This study aims to investigate the relationship between Islamic financial principles and MSMEs’ performance in Makindye Division Kampala – Uganda.

This study used a correlational research design involving 86 respondents from 30 MSMEs between January and May 2023. Data collected through questionnaires was analyzed with Statistical Package for Social Sciences, examining three independent variables: ethicality, Halal investment and prohibition of riba, in relation to MSME performance.

The results revealed significant relationships between these variables and MSME performance. Prohibition of riba (r = 0.296, n = 86, p = 0.006), Halal investments (r = 0.308, n = 86, p = 0.004) and ethical principles (r = 0.283, n = 86, p = 0.008) all exhibited a statistically significant relationship. Regression analysis with R = 0.405, R² = 0.164 and adjusted R² = 0.134 indicated that all hypothesized variables were significant predictors of MSME performance. Based on findings, this study rejected the null hypothesis, confirming a moderately positive and significant relationship between Islamic financial principles and MSME performance.

This study underscores the importance of active involvement from key stakeholders such as the Uganda Halal Bureau, Uganda Muslim Supreme Council, Islamic financial institutions and government agencies in integrating robust support mechanisms for MSMEs into their strategic frameworks. Such efforts could enhance Uganda’s economic landscape, aligning with the experiences of Malaysia and Indonesia in leveraging Islamic principles for economic growth.

In this paper, the relationship of brand logo and purchase intention is investigated along with the mediating role of customer satisfaction, brand preference and brand attitude. The research is conducted on an online passenger transport company called Tapsi.

In this study, we examine the positive effect of brand logo on brand attitude, consumer satisfaction and strengthening the intention to buy and brand preference by customer satisfaction. The statistical population was randomly selected. We design a conceptual model and then prepare a standard online questionnaire and send it to the target groups. Among this, the participants, 59% are women and 41% are men. After collecting the data through the software Smart-PLS3, we start the analysis. According to Cronbach's alpha and AVE, the validity and reliability of the model are confirmed.

The study shows that the brand logo has a positive and direct influence on customer attitude and satisfaction, and customer satisfaction mediates the purchase intention and brand preference. Given that the brand logo describes the company, managers must be very sensitive to design of a proper logo and spend enough time and money on it.

Few studies have examined the effectiveness of the brand logo the present study and the results show that the brand logo and its structures are directly related to brand attitude as a result of consumer satisfaction in all services even transportation services. The first thing consumers see when they first use a company’s services is the company logo. The brand and its logo can change the attitude and decision of the customer. Past studies have also shown that the brand logo can have a direct impact on customer satisfaction and customer preference for the brand. Therefore a model was prepared and the mentioned variables were selected. Brand preference as a mediating variable has a positive role on buying intention. However all relationships and their predictive power have been confirmed.

Air transport accounts for nearly 40% worth of the global trade cargo volume, where more than 50% of the air cargo is carried on passenger flights. Therefore, this paper aims to focus on identifying the influencing factors for both passenger and cargo demand-driven networks to smoothen the global supply chain.

The data for the study was collected through literature reviews and interviews with industry experts. The analytical hierarchy process was used to analyze the expert's opinions on the critical factors affecting air cargo demand growth. Regression analysis was conducted using the selected variables to develop a model to calculate air cargo demand growth.

According to the expert opinion, it was identified that facilities under airport capacities and facilities are mainly affected by the air cargo carried by combi carriers. The model was developed considering the air connectivity index and air cargo demand at destination variables.

The factors identified here are mainly related to the current situation in Sri Lanka. Applying this methodology to other economic zones will add new factors related to their economic contexts and could be generalized as the influencing factors for the growth of air cargo demand by finding more results.

Previous studies have been conducted using different factors and models to forecast air cargo demand, and those did not consider demand from combi and all-cargo carriers together. More than 98% of air cargo trades in Sri Lanka are happening through combi carriers. Hence, Sri Lanka will be a best case study to analyze the behavior of combi carriers.