Modern Research in Decision Making

Abstract One of the elements of the success of any production organization is the optimization of the product distribution channel. Because it affects all the activities of the organization in order to provide the services needed by the customers. Elements such as inventory, marketing decisions, and pricing are effective in optimizing the distribution channel. Although the investigation of these factors alone leads to optimization, but their simultaneous optimization creates global optimal, which has rarely been addressed in past studies. Therefore, this article seeks to present an integrated model for the simultaneous optimization of supply chain elements in the distribution channel. The proposed model is a bi-objective model in which decisions related to marketing; pricing and inventory control are considered. Two internal and external suppliers have been used. In this study, the first objective function seeks to maximize profit and the second objective function is the utility resulting from customer satisfaction. The presented model has been implemented in the supply chain network of Etka chain stores. Inventory management in distribution centers as well as marketing parameters, including product pricing in channels, choosing the best channel for each product, the amount of sales of each product in each channel and finally the amount of discount for products It has been checked in different channels in the proposed model and then it has been solved by LP metric method by GAMS and NSGA2 algorithm. Which shows that the genetic algorithm of NSGA2 in high dimensions provides the desired results in a more appropriate time.

Abstract The objective of the present research is to present a model of social manufacturing in the furniture industry. This study has been conducted in two phases; in the first qualitative phase, the grounded theory approach was employed to identify influential factors in social manufacturing, and in the second quantitative phase, the structural equation modeling (SEM) approach was utilized to assess conceptual model. Thus, this research is fundamental in purpose and descriptive-exploratory in method. The data collection tool in the qualitative part comprised interviews, with senior managers in the furniture industry constituting the statistical population. Purposeful sampling was employed for participant selection in this qualitative phase. In the quantitative section, a questionnaire served as the data collection instrument, with stratified random sampling as the chosen method. Based on the results of open and axial coding in the qualitative phase, axial codes such as decentralized structure, participatory space, social networks, network-based training, information and communication technologies, and research and development capacities were recognized as necessary infrastructures for social manufacturing. In the following, environmental monitoring, product commercialization, development of collaborative capacities. , intellectual property of ideas, evaluation of idea to product and development of networking are classified as social manufacturing strategies. The results of quantitative section indicated that the most significant strategy for implementing social manufacturing in the furniture industry is the development of networking. Additionally, based on the findings, the most crucial infrastructures for implementing the concept of social manufacturing in the furniture industry is the reinforcement of information and communication technologies.

Abstract Objective: There are many contextual factors influencing strategic innovation, which despite their importance have not been comprehensively investigated, hence the purpose of this study is to identify and conceptualize strategic innovation contexts.
Methodology: This research is developmental-applicative in terms of objective and qualitative-quantitative in terms of approach. In the qualitative part, two meta-composite approaches and case study were used, and in the quantitative part, Dimetal soft modeling was used. The data collection in the meta-combination stage was based on the analysis of the data obtained from the systematic review of studies in the last 24 years (1998 to 2022), the case study stage was an interview with 21 academic and executive experts, and the survey stage was through a questionnaire. Is. For data analysis in the qualitative part, concept analysis, content analysis, and theme analysis, and in the quantitative part, Dimetal technique was used.
Research findings: The results of the research show that the areas of strategic innovation in the football industry were identified in the form of five categories, which include key stakeholders, political-legal factors, technological factors, social-psychological factors, and competition between industry competitors and the business environment. It was categorized.
Research Innovation: The results of this research help managers and those involved in the football industry to make appropriate decisions regarding their clubs by knowing the fields of strategic innovations in the football industry.

Abstract The purpose of this study is to provide operational strategies during the Khoy earthquake in the humanitarian supply chain in order to maintain relief and help the victims and meet their needs quickly.The above research method is qualitative.The present research is applied research in terms of purpose and survey-descriptive in terms of nature.The statistical population of this research is the victims and crisis management experts. In this research, firstly, the needs of victims and the strategies to meet these needs were identified by reviewing the literature and conducting semi-structured interviews.Then, the needs of the victims through BMW and humanitarian supply chain strategies through combined approach of QFD and DEA according to Limitations of cost, time, urgency, effectiveness and ease of implementation were prioritized by distributing questionnaires among them.The final findings of the study showed that the strategy of “creating an accident command and crisis management system to plan, coordinate and assign tasks between organizations and institutions involved in the earthquake crisis in order to enable and expedite rescue operations”and“continuous evaluation for continuous improvement in rescue operations and various measures” were the most important strategy, and the need for "relief for the injured" was the most important need for the injured.Therefore, it is recommended to the authorities in the field of crisis management, by setting up the incident command post and the crisis management system, timely response, speeding up rescue operations, preventing parallel actions, creating unity of action and also regular evaluations cause continuous improvement in the process of rescue operations.

Abstract One of the models that is used to measure the efficiency and decision support is DEA, but considering all the merits, it also has its own limitations, which has led to the idea of combining it with artificial neural networks. ANN is increasingly used in model and data-based approaches to enrich analytical and predictive capabilities and thus improve decision-making. The present research presents a model for evaluating the efficiency of units by integrating neural networks. The studied sector is the active pharmaceutical industry in the Tehran stock market. To create the model, the efficiency of 4 DEA models on a variable scale, including input-oriented and output-oriented BCC model, SBM model and RAM model during the years 2018 to 2022 was calculated in GAMS. The efficiency values of these four models were ANN'S education vector. Also cost, income and profit data from 2018 to 2022 was entered into MATLAB as ANN'S input. To generalize education, the data of 2023 was used. The results showed that the trained efficiency boundary shows a more comprehensive and accurate approximation of efficiency for the ranking of pharmaceutical companies. The results of this research will help pharmaceutical companies in the fields of investment, resource allocation, predicting the results of policies and planning.

Abstract Purpose: This paper aims to present the key research trends in the healthcare supply chain,
critically analyze the research characteristics of these areas, define the main elements of the
healthcare supply chain and the effects of the COVID-19 pandemic on the healthcare supply chain,
and present responses to overcome these impacts based on literature review.
Design/methodology/approach: A systematic literature review is conducted on the healthcare
supply chain research papers covering ten years of research (2010-2020) in peer-reviewed journals
published in English. To achieve this goal, we performed a critical analysis of key research trends
in the healthcare supply chain, assessing the significant characteristics of the articles, such as issue,
solution, research method, outcomes, and concerns,
Findings: We found 13 key research trends in the healthcare supply chain; healthcare supply chain
collaboration, performance measurement, and model/framework were the most significant areas
addressed in the papers reviewed in this study. The reviewed studies did not investigate the
relationship between different entities in the healthcare supply chain in detail, and most had
limitations in generalizing the findings to diverse companies/countries. The primary outcomes of
the assessed studies were cost reductions and performance enhancements.
Originality/value: The analysis of the healthcare supply chain studies in diverse research trends
resulted in insights that help understand concerns in different trends and outcomes of the proposed
solutions. In addition, this study addressed the impact of the COVID-19 pandemic on the
healthcare supply chain and the responses to overcome them in particular.