Search results

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.

The rapid increase in higher education institutions (HEIs) can affect the provision of quality education especially when there are no clear integrated objectives to serve the overall HEI as well as the lack of management related to human resource needs. The quality of HEIs relies on the performance of their employees who are considered as one of the most important resources. Several studies demonstrated that the concept of talent management is not well defined for HEIs and considered it as a new study; however, researchers emphasized on its importance to improve the employees' performance and to achieve sustainable competitive advantages. The main aim of this paper is to propose a faculty equity framework for talent optimization in HEIs to help these institutions to recruit the right people, manage and motivate them to achieve their future goals and serve the best quality.

The faculty equity framework criteria are derived from the standards of national and international quality assurance and accreditation agencies which are grouped into three categories: alignment, capabilities and engagement. These criteria are used to outrank faculties and determine the entrepreneurial champions. As the framework does not require setting weights for these criteria, the authors propose to adapt the ELECTRE IV to outrank faculties.

The proposed framework has given faculty a chance to assimilate the HEI dominant culture and guidance to improve their performance through comparing themselves to entrepreneurial champions who are better aligned, capable and engaged. Also, the framework offers the HEI an opportunity to effectively retain talents and achieve maximized outcomes.

This research provides HEIs with a practical guide on how to enhance practices, policies and strategies regarding their human capital in order to achieve their missions and strategic goals.

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.

Recognizing novel entrepreneurial opportunities arising from a crisis is of paramount importance for firms. Hence, understanding the pivotal factors that facilitate firms in this endeavor holds significant value. This study delves into such factors within a representative empirical context impacted by a crisis, drawing insights from existing literature on opportunity recognition during such tumultuous periods.

The authors conducted a qualitative inspection of 14 Italian firms during the COVID-19 pandemic crisis. The authors collected a rich body of multi-source qualitative data, including 34 interviews (with senior managers and entrepreneurs) and secondary data (press releases, videos, web interviews, newspapers, reports and academic articles) in two phases (March–August 2020 and September–December 2020).

The results suggest the existence of a process model of opportunity recognition during crises based on five entrepreneurial influencing factors (entrepreneurial knowledge, entrepreneurial alertness, entrepreneurial proclivity, entrepreneurial personality and entrepreneurial purpose).

Various scholars have highlighted that, in times of crises, it is not easy and indeed very challenging for entrepreneurs to identify novel entrepreneurial opportunities. However, recent research has shown that crises can also positively impact entrepreneurs and their capacity to identify new entrepreneurial opportunities. Given these findings, not much research has analyzed the process by which entrepreneurs identify novel entrepreneurial opportunities during crises. This study shows that some entrepreneurial influencing factors are very important to identify new entrepreneurial opportunities during crises.