فهرست مطالب سهیلا خویشتن دار

In the procurement process, small and medium-sized enterprises (SMEs) are often in a weak position when facing strong suppliers. Adopting a joint procurement strategy that represents the long-term horizontal cooperation of SMEs in a procurement process, can be considered as an attractive and efficient strategy. Therefore, the purpose of this paper is to propose a mathematical model and optimization algorithm for the decisions related to sourcing and inventory management of SME’s procurement alliance.

In the proposed joint procurement model, SMEs are able to obtain quantity discounts and reduce the total purchase cost by aggregating purchase demands to a relatively larger-scale purchase order. Therefore, the model determines order quantity of each SMEs in the procurement alliance from each of the suppliers in order to minimize the cost of procurement, the number of defective purchased materials and the number of delayed materials delivered. In addition, in this model, the constraints of minimum order quantity, inventory capacity and purchase demand are considered. To examine the validity of the model, a real example using the non-dominant sorting genetic algorithm II (NSGA II) has been optimized.

The results of the numerical experiments showed that the joint procurement model and the proposed optimization algorithm are effective and three objectives are significantly improved in the joint procurement scenario comparing with the independent procurement scenario.

In this article, a multi-objective model for supplier selection and order allocation in the joint procurement process of SMEs is presented. In addition, constrained non-dominant sorting genetic algorithm has been developed to optimize this constrained multi-objective model.

Digital entrepreneurship is an entrepreneurial approach that is suitable for the digital age and has become a dominant discourse in the field of entrepreneurship due to its increasing speed. Given the richness of studies and research background on digital entrepreneurship, the use of scientific methods and co-occurrence analysis can provide a comprehensive and pervasive picture of this field. Therefore, this study aims to draw a co-occurrence map of digital entrepreneurship. This applied research uses a scientific approach and analyzes data using co-occurrence analysis. The data was collected from the Science Direct database from 2015 to the end of 2022, and VOSviewer software was used to draw the co-occurrence map. In total, 19 keywords, 4 clusters, and 68 links with a strength of 152 were identified. The concepts of digital entrepreneurship, knowledge management, big data, business intelligence, strategic management, organizational learning, social networks, competitive advantage, and optimization are the most common words in this field. Therefore, art universities can provide a platform for digital entrepreneurship through a strategic approach using big data analysis and activities on social networks. Knowledge management plays a fundamental role in this regard and can guarantee the competitive advantage of universities through digital entrepreneurship

In a context where substantial volumes of hospital waste are generated and disposed of daily, the ineffective sanitary disposal of such waste can lead to environmental risks and higher operational expenses. However, hospitals frequently overlook objective criteria when evaluating and selecting waste disposal firms, relying instead on subjective judgment and past experiences. This research proposes a decision-making framework that presents a hybrid model combining multi-criteria decision-making and linear programming. The primary objective of this study is to propose a safe and efficient method for outsourcing disposing of or recycling hospital waste.

This study presents a framework for decision-making in hospital waste disposal, addressing both single and multiple outsourcing scenarios. Firstly, the literature is reviewed to identify the criteria for evaluating waste disposal firms. The DEMATEL method is employed to explore the cause-and-effect relationships among these criteria, selecting the most significant ones and visualizing their causal relationships in a network format. The analytic network process (ANP) method is then utilized to evaluate and choose the most suitable waste disposal firm in a single outsourcing scenario. Additionally, to mitigate the risks associated with single outsourcing, a linear programming model is introduced for multiple outsourcing. This mathematical model determines the optimal allocation of waste quantities to various waste disposal firms, aiming to maximize the overall amount of waste disposed of by these firms.

Fidings: 

The framework introduced in this study was put into practice to assess and choose hospital waste disposal firms in Tehran. Through a comprehensive literature review, 10 evaluation criteria were identified. Among these, the six most influential criteria were selected using the DEMATEL method, and their causal relationships were depicted in a network. The ANP was employed to assign weights to the evaluation criteria and the candidate firms. The evaluation criteria, in descending order of importance, include qualified human resources, recycling and disposal capacity, experience, cost, collection and transportation infrastructure, and waste disposal and recycling technology. Furthermore, a linear programming model was solved using Lingo software to optimize the allocation of waste among the candidate firms.

The decision-making model presented in this article offers advantages to both hospital officials and urban pollution control officials in the context of outsourcing sanitary waste disposal. The outcomes obtained from implementing the proposed framework demonstrate that decision-making based on this model not only benefits hospitals in selecting a suitable firm but also helps to mitigate conflicts of interest and disagreements between hospitals, sanitary waste disposal firms, and urban pollution control officials.

Rapid growth and innovation in digital technologies has fundamentally changed the competitive landscape and reformulated traditional strategies, processes and structures. In the digital world, almost anything can be done through a computer or smartphone. Digital entrepreneurship has brought many benefits to companies and society by capitalizing on this process. However, the factors that determine the success and development of digital entrepreneurship, as well as how they relate to each other, are still not clear. This study is important because digital environments are increasingly growing in most developing countries such as Iran. Such an environment is seen as an outstanding opportunity to promote digital entrepreneurship. The purpose of this article is to determine the factors that play an effective role in the development of digital entrepreneurship through digital literacy. These factors have been identified by reviewing the literature and articles of foreign publications in this field and categorizing these factors and then presenting a comprehensive model based on the obtained data, which has been used to analyze the data using SMART PLS 3 software. Also, the statistical population in this research is considered to be all graduates of Tabriz art universities and professors of these universities. The results obtained from the data analysis show that digital literacy (communication and collaboration, teaching and learning skills, information and communication technology literacy, digital research and information literacy) is one of the important issues related to the development of digital entrepreneurship.

Today, resilience is a topic that has attracted increasing interest in the business space. Uncertainty about the future, changes, developments and environmental risks have endangered the survival of today's organizations. Managers of most organizations believe that the resilience of businesses plays an important role in enabling them to invest, sell, market, trade, etc. in the future. On the other hand, the lack of a systematic and efficient study and the existence of a model about the resilience of small and medium businesses in internal and external research has become the main problem of the managers of these companies. Therefore, in this research, the factors affecting the resilience of companies have been investigated in order to adopt effective strategies in order to prevent and prevent disruptions and reduce the performance of companies using system dynamics methods. Considering the importance of the development of small and medium-sized companies in the current state of the country from the economic, security, political, health and other situations, it is necessary to prevent financial and functional helplessness and bankruptcy, therefore, the findings of this research include identifying the factors that contribute to the resistance of small and medium-sized companies with Considering environmental drivers and impulses are effective and presenting a conceptual and operational model of organizational resilience. The research method of the current research is practical in terms of its purpose and it is exploratory in terms of data collection, and the type of research data is qualitative and quantitative.

Based on different characteristics and abilities, entrepreneurs have different motivations in the process of new venture creation. This study aimed to recognize the motivational factors that science-based entrepreneurs agree on their importance and follow in new venture creation. Also, different motivational patterns of these entrepreneurs were identified. In this way, this paper applied Q-method and the results of analyzing the Q-sorts of 30 participants, lead to 5 different motivational patterns, including Altruisms, controllers, ambitious, profiteers, and followers. Despite the identified motivational patterns, entrepreneurs were unanimous in the importance of some of the motivational factors. The important factors that participants agreed on them include having an effective communication network with other entrepreneurs, inventors, academician, producers and investors, as well as applying scientific research and commercializing ideas and inventions. On the other hand, insignificant incentives for all participants include having friendly relationships and being disappointed in previous job. By focusing on common motivational factors and tailored for different mental patterns of individuals, science and technology policymakers can make appropriate policies for achieving science-based economy and consider measures to increase the rate of establishment of such firms and their chances of success.

As an environment-friendly and renewable energy source, biomethane plays a significant role in the supply of sustainable energy. To determine location of reactor and allocate feedstocks, to the reactor in a biomethane production system by minimizing the supply chain cost, a mathematical model is studied in this article. Constraints, such as the limited workforce, the reactors’ demand on the residues, and the deterioration of the residues in the hubs are considered. Two evolutionary Algorithm, Genetic and differential evolutionary algorithms for solving mixed integer nonlinear programming model is proposed. The speed of obtaining the solution is the same but differential evolutionary algorithm finds better solutions than Genetic Algorithm when applied to the given problems.

Different inventory control systems try to determine how much and when to order at the least relevant cost while maintaining a desirable service level for customers. In this article, a continuous review stochastic inventory system, with three objectives, is optimized. In this model, contrary to the traditional inventory models, customer serviceis not considered a shortage cost in the objective function. But the frequency of stock out occasions and the number of items stocked out annually are to be minimized. For determining the Pareto optimal set, multi-objective evolutionary algorithms are used. First, NSGA-II, MOGA, VEGA, RWGA are developed. Then some improvements in NSGA-II mechanisms are made and R-NSGA-II is developed. Subsequently, these algorithms are examined for some criteria such as set coverage and spacing, and the best algorithms for each criteria are presented. The Result shows that R-NSGA-II has good scores formost criteria. Afterwards, Pareto optimal set is ranked using the method of global criteria.