Industrial Management Journal
Year:2020 | Volume:12 | Issue:1|Papers Count:7

Objective: Selecting the supplier, allocating the goods to the suppliers, and pricing the goods are the important challenges with which retailers are faced. The present study is aimed at providing a multi-item supplier selection, order allocation, and pricing model with stochastic demand and purchase from the suppliers who provide goods with all-unit discount. Methods: The study has used quantitative modeling by presenting mathematical model. The demand functions are price-based with additive uncertainty. In this study, a mixed nonlinear integer single-objective model was developed. To this end, the response surface methodology was used to estimate the income function and the genetic algorithm was applied to solve the model. Further, the Taguchi method was utilized to set the parameter of the genetic algorithm. For verifying the proposed method, nine problems with different product quantities and levels of variance of stochastic variables of demand were solved. In addition, in order to evaluate the performance of the genetic algorithm, the results of the algorithm in solving problems with small dimensions were compared to the results in solving the model in Lingo software. Results: The results of the study indicated that the difference between the results of genetic algorithm and lingo is not significant. After solving the model for the examples using the proposed method, it was determined that increasing the variance of the random variable of demand results in decreasing the profit level. Conclusion: Considering the supplier selection, order allocation, and pricing issues can help retailers to make better decisions. Furthermore, demand based on the price and various conditions of the discount are assumptions which make the model more practical. The results of solving the model for various examples indicated that increasing uncertainty in demand leads to a decrease in the amount of profit. Moreover, the genetic algorithm is considered as an appropriate alternative to solve a mixed nonlinear integer model of supplier selection, order allocation, and pricing.

Objective: The purpose of the present study is to identify priority indicators-based on the qualitative analysis of the results of the research carried out-and also to provide a framework for measuring the performance of the information security service supply chain. Methods: The methodology of this research is essentially descriptive and qualitative and has been carried out in two stages. In the first phase, 133 papers were reviewed, after evaluation, 28 articles were approved. Then, by using the CASP method, finally, 15 articles on the measurement of the performance of the service chain received the minimum score for conducting a qualitative analysis of the content. By reviewing these articles, a conceptual framework for measuring the performance of the service chain was presented in the form of a "logic model". This model is a tool that illustrates the logic of doing things in the four components of inputs, processes, outputs and outcomes. After verifying the reliability of the results, in the second stage, in order to map the proposed framework into the field of information security services, by referring to ten experts in this field and receiving their views in the three rounds of the Fuzzy Delphi, validation and final modeling of the research was designed. Results: The evaluation of the performance of the information security service supply chain for 19 indicators and 35 effective sub-indicators, under the logic model, were agreed with the coefficient of coordination of Kendal of 0. 742 between experts and specialists. Conclusion: The review of experts' opinions showed that the sub-indicators of knowledge and skills, the provision of new and up-to-dated security technologies and the confidentiality and security of information make the most important and rate of personnel turnover sub-indicator, assessing the least important in the performance evaluation of the information security services supply chain.

Objective: In this study, different ways of delivering goods to customers are created and therefore the vehicle routing decisions are added to this issue. In this case, customers must be divided into clusters and each customer assigned to one means of transportation in order to minimize the cost of orders between customers. In this study, the problem of integrated supply chain scheduling is determined by timely delivery of orders, scheduling orders on a machine in a manufacturing system and batch shipment, allocation to multiple heterogeneous transport modes according to capacity, and finally order delivery. To customers in the time window, it aims to minimize the total cost of distributing orders and the constant and variable costs of fuel and carbon emissions of the vehicle and the total time delay of customer orders. Methods: The problem programming model is a mathematical model of complex nonlinear integer and has been used for solving multi-objective meta-algorithms MOPSO and NSGA-II. Results: The results show that NSGA-II algorithm performs well. Conclusion: This research reduces the costs of production, distribution, inventory maintenance and fuel consumption. It can also help reduce product inventory and maintenance costs.

Objective: The occurrence of natural disasters, such as earthquakes, is sometimes associated with many financial and personal injuries. Proper allocation of each city district to emergency resettlement sites, hospitals and clinics will accelerate the relief process and reduces injuries. The purpose of this research is to present an integer linear mathematical programming model for optimal locating and allocating of emergency resettlement points to city districts. Methods: In this research, the volume of flow between the demand points and emergency resettlement sites, clinics, and hospitals is determined. The objective function of the presented mathematical model is to minimize the mathematical expectation the of total transfer time of people, so that the coefficient of fines is considered for the later transmission of the affected persons to the treatment centers. Due to the accidental nature of natural disasters, uncertainty in this study is seen as a scenario. In this study, the probability of occurrence of different scenarios, the probability of injury in each area in different scenarios, the classification of injured persons, and the limited reception capacity at resettlement and treatment centers are considered. Results: The proposed research model was coded and solved using Bojnord city information. The optimal allocation of each district of Bojnord to temporary hospitals, clinics and resettlement sites has been determined. Conclusion: Although the probability of injury was considered small in different city districts, the hospitals did not have the capacity to repost to the injured persons and it is necessary to use the adjacent city hospital for hospitalization. Locating temporary treatment centers is also needed in areas close to the villages before such events occur.

Objective: Improving sustainability in supply chains is one of the strategic objectives in the current business. Hence, firms have adopted new management strategies to achieve sustainability in their supply chain. Therefore, it is essential to assess the sustainability performance of the newly implemented management strategies. The purpose of this paper is to provide a model for assessing the sustainability performance of LARG supply chain management practices in the automotive supply chain using the dynamics system. Methods: LARG supply chain management practices were identified, by reviewing the literature and interviewing industry experts, prioritized using fuzzy analysis network process, and were eventually presented as an integrated approach to LARG supply chain management practices. Finally, the dynamic system has been used to assess the dynamics of LARG supply chain management practices and their impact on sustainable performance in the supply chain. Results: The research findings show that improved measures in the implementation of total quality management, just in time, flexible transportation lead to a more sustainable supply chain. The results of these measures show sustainability improvement in the supply chain. Conclusion: The results show that a lean strategy is very important for achieving sustainability in the supply chain. The proposed model helps industry managers and decision makers identify the results achieved from implementing LARG supply chain management practices and improving effective practices on sustainability in the supply chain by adopting policies.

Objective: The present study defined the main factors of the stagnation of food and pharmaceutical industrial enterprises with the aim of designing a native model that spatial domainare Kermanshah province. Methods: The Research model was implemented based on the qualitative method of "Grounded Theory". For data gathering, judicial sampling method and snowball technique were used to achieve data theoretical saturation through a profound semistructured interview with 15 experts from differentfields of governmental, academical and private sector. Validity of interviews was confirmed by triangulation method. In order to data analysis, Strauss and Corbin's approach was used. Results: The native model of the stagnation of food and pharmaceutical industrial enterprises is affected by a variety factors which can be categorized in the conditions of causal (weakness of management skills, traditional management of businesses and weakness in organization, weakness in identifying and implementing market management strategies and etc. ), The interference (financial resources; the right understanding of decision-makers and policy-makers; the appropriateness of the supply chain with upstream industries and etc. ) and context (socio-cultural, political, technological and etc. ) and there are several consequences for it at two levels; the macro level and the enterprise level. Conclusion: Identified actions as strategical factors in the model include: challenges in sale, production and supply; weakness in branding; weakness in absorbpation of expert staff; Reducing the competitiveness power of the enterprise; that finally leads to lack of motivation of activists, Reducing sustainable employment, creating a psychological barrier for newcomers at the macro level; and increasing the financial debt, manpower adjustment, reduction in the special value of the brand, decreasing the value of assets and the credibility of the enterprise and the escalation of disputes between key partners at the enterprise level.

Objective: In today's world, global economies face significant shocks and threats, such as financial and economic crises, bankruptcies of the banks and large industries, the spread of infectious diseases, terrorist behavior and the collapse of markets. In recent years, the country has faced extensive and unprecedented sanctions, and other shocks such as natural disasters and the outbreak of corona have damaged the country's economy. Therefore, paying attention to the economic resilience plays an important role in strengthening the country's economy and financial institutions against threats. The capital market, as a source of attracting stray and supportive liquidity for the business environment, plays an important role in preventing the country's economic turmoil. This study aimed to identify and prioritize the factors affecting the resilience of the country's capital market. Methods: The present research is applied in terms of orientation and exploratory in terms of purpose. In order to conduct research in the first stage, by reviewing the literature and interviewing financial experts, the main factors affecting the resilience of the capital market were identified. Subsequently, using the nonparametric test Binominal and Dematel, the main factors were screened and the non-important factors were excluded. Results: The main final factors were: the structure and processes of the organization, attention to learning and training, information sharing, identifying and analyzing impulses, threats and risks ahead, variety of designs and available options, technology acceptance, improvement and development. Conclusion: Subsequently, the sub-factors of each of the main factors were identified. Finally, by using Codas decision-making technique, the priority of sub-factors in each of the main factors was determined.