Search results

The purpose of this paper is to examine the effect of corporate governance structure and CEO compensation on the level of tax aggressiveness.

This work analyzes a sample of 471 observations of 100 companies listed on the NASDAQ 100 for the period 2008-2012. It uses a fixed-effect panel model to analyze the effect of different model variables on the tax aggressiveness level.

The main finding of this study is the great influence of corporate governance structure and CEO compensation on reducing tax aggressiveness. Indeed, it finds a significant negative relation between board size, CEO salary, CEO stock options and tax aggressiveness. In addition, the study reveals that there is a direct negative relation between CEO duality, tax fees and tax aggressiveness.

The study was conducted using robust methods to test the effect of corporate governance structure and CEO compensation on tax aggressiveness level. The generalized least squares method was used to fit panel data and overcome heteroscedasticity and autocorrelation problems. The aim of the study was to prove the great effect of both corporate governance structure and CEO compensation on reducing tax aggressiveness. As this study was based on data from American companies, the results cannot be generalized to all contexts.

This paper differs from previous work and tests the effect of corporate governance structure, CEO compensation, CEO characteristics and audit fees on tax aggressiveness. The findings of this study will enrich the literature on tax aggressiveness by suggesting that corporate governance structure and CEO compensation can significantly limit tax aggressiveness behavior. Therefore, shareholders must be aware of these two variables. They need to limit tax aggressiveness behavior, as it is usually accompanied by rent diversion, as reported by Desai and Dharmapala (2006). Therefore, these findings will be helpful to investors, managers and regulators because they have implications for the interactive decision-making process.

The purpose of this paper is to generate a daily operating theater schedule aiming to minimize completion time and maximum overtime while integrating real-life surgeon constraints, such as their role, specialty, qualification and availability.

The paper deals with complete surgery process using multi-objective surgery scheduling approach. Furthermore, the combinatorial nature of the studied problem does not allow to solve it to optimality. Therefore, the authors developed two approaches embedded in a tabu search metaheuristic, namely, weighted sum and e-constraint, to minimize completion time and maximum overtime.

The integration of the upstream and downstream services of an intervention and the consideration of the specific constraints related to surgeons are very essential to obtaining more closed schedules to the realty.

The paper includes implications for the development of efficient schedules for a significant number of operations coming from different specialties throughout its complete surgery process under multi-resource constraints.

The paper can help hospital managers and decision makers to well manage the budget by minimizing the overtime cost and by offering efficient daily operating theater schedule.

The results of the paper will help hospital managers and decision makers to well manage the budget by minimizing the overtime cost and offering efficient daily operating theater schedule.

Waste generation poses a significant environmental challenge in the United Arab Emirates due to the rapid urbanization, population growth and industrialization witnessed in recent decades. As a result, there has been a substantial surge in waste production. To fulfil its sustainability and circular economy aspirations in various economic domains, the UAE must prioritize efficient waste management. The purpose of this study is to assess the environmental and energy efficiency of the UAE’s economic sectors particularly within its vital energy sectors, which encompass crude oil, natural gas and mining, manufacturing and electricity, by gauging their adherence to sustainability and circularity objectives.

The authors used the data envelopment analysis input–output model to identify sectors that exhibit strong performance as well as those that are falling behind.

Based on this study, the agriculture, the crude oil, natural gas and mining sectors and financial services and banking were found to be the most efficient. The results of this study concluded that the UAE is making progress toward achieving its sustainability and circularity objectives; however, the findings suggest that more effort is needed to fully realize these goals.

By identifying high-performing and underperforming sectors, decision-makers can prioritize efforts to enhance sustainability and circularity in area of greatest need in the economy.

Ambulance response time is an important factor in saving lives and is highly linked with the ambulance location problem. The Maximum Expected Covering Location Problem (MEXCLP), introduced by Daskin (1983), is one of the most used ambulance location models that maximize the probability of stratifying demands for emergency medical service (EMS) centers. Due to huge increase in the operational costs of EMS centers, ambulance location models must consider the cost of coverage and the opportunity to use other companies’ private ambulances to answer emergency calls. The paper aims to discuss these issues.

In this paper, the authors propose to extend the MEXCLP to a bi-objective optimization problem where the cost of satisfying emergency calls is minimized.

The proposed model is tested using data retrieved from the Lebanese Red Cross (LRC) in Beirut capital of Lebanon. The reported findings show significant enhancements in the results where the LRC can fully satisfy the perceived demands from all areas in Beirut within 9 min with an affordable cost.

The model is a first attempt to reduce operational costs of EMS centers while constraining the response time to satisfy emergency calls at an acceptable rate.

Operating theaters are considered as the most sensitive health department within hospital centers due to their significant cost/necessity for patients and their economic benefits for hospitals. In this paper, the authors consider patients that may require more than one surgery on the same day in the surgery scheduling problem which is a major technology enhancement in the health industry.

The surgery scheduling includes both the preoperative and the postoperative units of the operative stage. Two objectives are considered in a lexicographic way: the minimization of the makespan while prioritizing the patients having two surgeries and the total completion time to perform. An adapted tabu-search algorithm is used to tackles this NP-hard scheduling problem.

The proposed schedule is more relevant for operating theaters as it integrates all stages of the surgical procedure and considers patients with more than one operation during the same day.

This paper is original as it considers patients who need more than one operation, which responds to real challenge faced by decision-makers' in hospitals. The application of the time lags between stages of the surgical procedure generates a good utilization of the hospital resources and makes the scheduling task more flexible.

This study strives to better understand resistance to chatbots in the banking sector. To achieve this, it proposes a model based on the paradigm of resistance to innovation and the complexity theory. In addition, it explores the role of gender in relation to chatbot resistance.

Data are collected in France using a snowball sampling technique. The sample is composed of 385 participants. FsQCA is used to identify all possible combinations of usage, value, risk, tradition and image barriers, as well as two gender conditions that predict resistance to chatbots.

The results reveal that the sample provides four possible solutions/combinations that may explain resistance to chatbots. These are: (i) a combination of usage, value, risk and tradition barriers, (ii) a combination of value, risk, tradition and image barriers, (iii) a combination of usage, value, risk and image barriers, along with the male gender and (iv) a combination of usage, value, tradition and image barriers, along with the female gender.

This study provides valuable and straightforward theoretical and managerial implications. The proposed solutions suggest a deep understanding of chatbot resistance. Chatbot developers and marketers can highly benefit from these findings to enhance user acceptance.

In this study, barriers are envisioned within the larger context of innovation resistance. The interactions among barriers causing resistance to chatbots are examined through the lens of the complexity theory, while the data analysis employs the fsQCA approach. Furthermore, this study sheds light on the role of gender in explaining chatbot resistance in the banking sector.

We introduce decision support tools aimed at optimizing perishable food supply chain management, effectively balancing conflicting objectives such as the exporter’s product collection cost and the importer’s profit. This involves considering factors like perishability, selling price, discount rate, and order quantity to achieve optimal outcomes.

This study considered a three-echelon supply chain comprising farmers, a single exporter, and a single importer providing a single, random-lifetime, perishable product under deterministic customer demand. The proposed mathematical model derived the optimal order quantity, selling price, and discount rate for the entire supply chain. This integrated optimization model treats both demand and supply sides as a multi-objective problem, employing a nonlinear program and a two-stage capacitated vehicle routing problem formulation. Numerical examples and a case study focusing on Thailand durian supply chain were conducted to illustrate the approach of the proposed model.

Taking into account both the importer’s profit and the exporter’s product collection cost, the proposed integrated supply chain model and tools maximize profitability, minimizes waste, and meets demand by optimizing perishable product collection costs and proposing a discount system for selling prices.

Limited to a single perishable product in a three-echelon international food supply chain. Future research can explore different products and supply chain contexts.

The tools enhance decision-making for supply chain managers, improving efficiency, reducing costs, and enhancing customer satisfaction in the perishable food industry.

The proposed model aids in local workforce management by forecasting required manpower for upcoming seasons. By factoring in product quality and pricing, it ensures customers receive fresh products at fair prices. Furthermore, the near-zero waste concept enhances storage conditions at importers' facilities, contributing to improved environmental hygiene.

The integrated model and decision support tools offer a novel approach to address complexities and conflicting objectives in perishable food supply chains, providing practical insights for researchers and practitioners.

This paper is about customer relationships from the perspective of small suppliers. More precisely, this paper aims to examine the relational implications through a product portfolio model with the main participants of the buying center (buyer/business manager).

The study first uses an in-depth qualitative data analysis to explore how elements of small suppliers’ relationship with such large customer’s main actors are affected by the nature of the product (categorized between strategic, bottleneck and non-critical items). From the results, an empirical model is drawn of small suppliers’ relational strategies in a product-centered and buyer/business manager relationship typology. To analyze the results of the empirical model, a quantitative analysis is performed, using the fuzzy set qualitative comparative analysis approach.

This study contributes to deepen the supplier–customer relationship analysis, from a product-centered and customer dyadic perspective (buyer and customer business manager). The findings highlight three different small suppliers’ relationship strategy with a different level of involvement of the different participants of the buying center.

Few studies so far analyze vertical asymmetric relationships from a triadic perspective composed of the small supplier, the buyer and the business manager – hence, this study contributes to unveiling some of the relationship complexity within a triad of actors and how small suppliers can navigate through this complexity according to their product or service positioning.

The purpose of this paper is to examine the motivations of earnings management and financial aggressiveness levels in the big 100 companies listed on the NASDAQ 100 after the 2007 financial crisis.

This paper uses two samples. The first contains 471 observations of 100 companies listed on the NASDAQ 100 for the period 2008-2012 and is used to examine the motivations of earnings management. The second represents 282 observations of companies listed on the NASDAQ 100 that use financial aggressiveness. The authors use a panel data model to analyze the effects of four explanatory variables (corporate governance structure, CEO compensation, CEO characteristics and audit fees) on both earnings management and financial aggressiveness levels.

The results of the investigation show the significant impact of corporate governance structure, CEO compensation, CEO characteristics and audit fees on reducing the earnings management and financial aggressiveness levels.

The findings can be valuable to both investors and researchers. For researchers, the present work may help in explaining the motivations of earnings management and financial aggressiveness practices used by large American firms after the 2007 US financial crisis. For investors, this study serves to highlight the critical importance of corporate governance, CEO compensation and CEO characteristics in limiting such behaviors. Thus, investors are recommended to account for such variables in order to make effective investment decisions. As an extension to this study, researchers might consider other CEO psychological variables. Other market indices could also be considered in order to generalize and validate the results of the research.

Investors must take into consideration the corporate governance structure and ask for supplementary information about CEO characteristics to ensure better investment decisions.

In this paper, and in contrast to previous research, the authors test the impact of corporate governance structure, CEO compensation, CEO characteristics and audit fees together on the level of both earnings management and financial aggressiveness behavior for large US non-financial firms after the 2007 financial crisis. The authors show that older CEOs use less earnings management and financial aggressiveness. The findings can be valuable to investors, managers and regulators because they have implications for their interactive decision-making process.