نشریه مدیریت صنعتی
سال دهم شماره 28 (بهار 1397)

The general concern about supplying food is one of the important issues before an earthquake happens. This research aims to present a conceptual model for “humanitarian supply chain practices to supply food before an earthquake” and prioritizing its practices. This research is applied in nature and it is descriptive regarding the tools and instruments of data collection. After reviewing the related literature and interviewing some experts, 7 criteria and 19 sub-criteria were identified. Then the questionnaire was distributed among the related managers, experts, and academics and 281 questionnaires were completed and gathered. This measuring model was tested according to Structuring Equation Modeling. Furthermore, Fuzzy AHP was used to weight the importance of each practice and its dimensions. Our findings showed that “Monitoring”, “Education”, and “Readiness for logistics and distribution” are the most important dimensions of our conceptual model. So, we used one sample t-test to measure the performance of each practice. Finally, importance-performance matrix was used for prioritizing the practices. We hope that our results will be a good guidance for managers and decision makers of humanitarian supply chain for better understanding of food supplying practices before an earthquake.

One of the common methods for the assessment of an organization's efficiency is comparison with other competitors. However, some researchers have studied the efficiency of a unit within itself during different periods of time and it is used to investigate the performance trend of the unit during previous times. The purpose of this research is to forecast the performance of a unit using the previous time series of its performance. This research conducts comparison and efficiency analysis of a unit during different time periods using SBM and DEA models. And then, the outcome is considered as the training elements of an ANN, so efficiency of future time steps can be estimated for that unit. An industrial unit in Steel industry was studied in this research and its decreasing performance trend during ten years has been presented after efficiency measurements. Implementing different structures of ANNs, finally, we found out that a recurrent neural network with 10 neurons in a hidden layer and Bayesian Regularization algorithm had the best performance for future forecasting of efficiency. The most important achievement of this study is efficiency forecasting for organizations' future using the existing data with regards to the influences of previous time steps on current efficiency by a nonlinear approach. It would lead to providing a clear image of the organization's future as represented for the case of this paper.

The main issue for banks is how much and how to invest in a variety of innovative activities. Innovative activities in banks are carried out in two paradoxical exploratory and exploitative poles. To answer such questions, a longitudinal multiple case study method was used. To do so, 4 banks were selected as the cases for this study and were analyzed in-depth between 2006 and 2017. At first, the tensions of exploratory and exploitative innovation approaches were identified in these banks. Then, the required strategies to respond to these tensions were extracted in these banks. Banks strategies of response were extracted within 17 themes and were classified into the following 4 categories (dimensions): selection, separation, balance, and transcendence.

Effective design of supply chain networks is necessary for micro-economic development. The aim of this study is to design green closed-loop supply chain network with financial decisions considering economic and environmental dimensions of development. Such decisions consist of non-supply chain investments and available loans. Uncertainty of demand and investments related to other investments (ROI) are taken into account, too. Proposed model is multi-product, multi-objective, multi-period, stochastic and closed-loop which is modeled as a mixed integer linear programming problem. A scenario path model is applied in order to deal with the uncertainties. The results approved the effectiveness of considering financial decisions. By increasing the number of available loans, the level of the service delivered to the whole system will increase accompanied by a decreasing inclination. Obtained results are based on a case study in plastic recycling industry. Simultaneous consideration of financial decisions and uncertainty in supply chain network design can lead to an improvement in the profit of the supply chain.

Organizational ambidexterity refers to an organization’s capacity to pursue two distinct goals at the same time, and is known as an important criterion in achieving competitive advantage. So far, many studies have been documented on the concept of organizational ambidexterityand its impact on performance. Nevertheless, few studies have examined its dual dimensions. Evidences suggest that ambidexterity has been positively correlated with performance, and for an organization, it is a valuable tool for continuously improvement in the performance. In this study, ambidexterity has been considered as a construct with two dimensions of balance and combination, and attempt has been made to measure the relationship between this two dimensions and the performance in banking industry. To do so, initially, reviewing the literature, the conceptual model of this study was extracted, and then in order to analyze the research model and hypotheses, we examined 161 bank branches. The structural equation modeling based on partial least squares (PLS) was used to analyze the data. The data analysis suggested a significantly positive impact of ambidexterity on performance which means if the organizations achieve high level of exploitation and exploration, the performance will improve. In this study, the increase in the combined amount of two exploitation and exploration activities or on the absolute value of the difference between these two activities was pointed out and according to the two aforementioned viewpoints, the role of ambidexterity on the performance was investigated. The contradictory results of the research in the two balanced and combined approaches indicated that it is not the balance between the two dimensions of exploitation and exploration that has a positive effect on performance and any increase in each of these two dimensions can lead to the improvement of the performance.

Current dynamic and complicated environment has made organizations and industries compete at an international level. If a world-class level production is pursued, they have to manufacture their products in a world-class level. To meet the world-class production indicators and remain competitive, they need to be more integrated at the level of organization, partners and supply chain. The present study aims to investigate the relationship between supply chain integration (SCI) and world class manufacturing (WCM). This study uses a descriptive-correlative method and its research population covers Electronic Domestic Appliance Industry companies. The samples in this research were selected using simple random sampling method. Fuzzy Delphi method was used to identify the dimensions and indicators of production in the world class level and to collect data, a researcher-made questionnaire was used. AMOS software was used to test the hypotheses through a statistical test of Structural Equation Modeling (SEM). The results showed that three dimensions of SCI namely, internal integration, supplier and customer have significantly positive impacts on obtaining products in world class level. The impact of customer integrity on delivery was not confirmed while high level of integral integrity is claimed to have more effects on cost and on-time delivery rather than other integration dimensions of supply chain integration. As the results showed, the companies in the industry are required to take actions on integrating supply chain comprising internal, supplier and customer integration in order to obtain WCM dimensions such as cost, innovation, quality, delivery, flexibility and services. Also result of. This paper helps managers to distinguish the effects of the different dimensions of SCI on obtaining WCM.

Inventory control and orders planning are among the key issues in developing the economic policies of industrial units, which requires attention to the factors and conditions governing the organization and the market. In this context, an optimal balance among inventories, ordering costs and maintenance costs can have a crucial role in preventing the loss of capital and shortages in the inventories. The purpose of this paper is to control the inventory in multi-item systems under the conditions of probabilistic demand and warehouse limit. The problem is studied by replacing the scheduling horizons with short-term periods in the general model of periodic orders which has solved the problem using the Particles swarm optimization algorithm. The results illustrated the connection of the inventory amount at two times of t-1 & t. The model's advantage is the dynamics of the general model of orders, especially in conditions of uncertainty in the business environment due to dramatic changes in the market conditions that are close to each other. This can make the general model of orders more dynamic and reflect the real conditions better and it can help managers determine the economic value at different times which is of high importance considering the limitations of definitive inventory control formulas. The model has been implemented on four different products in Novin Gateh Co. Since in manufacturing organizations, due to the presence of raw materials, particles, and inventories in the process, the role of inventory control is more evident, the proposed model can be used to create a reliable stream of items and inventory of the organization taking into account the elements of time, location, quantity, quality and costs.

The main objective of this paper is to solve theeconomic order quantity problem, which is formulated as a hybrid posynomial geometric programming, using a rule-based decision support system. Avoiding the complexities of the optimization process problems and using the optimum knowledge to build an inference system, which is easier to understand for the decision makers, are the main features of this article. The main approach taken in this paper is to use uncertain decision variables, extracting the optimal knowledge through the hybrid optimization problem and applying this knowledge to design a hybrid inference system. The developed hybrid inference system was applied to 100 random problems and inferred values of the objective function as well as decision variables were compared to the obtained optimum values. Alike decision variables, more than 97% of the deviations between inferred and optimum values for objective function are less than 2%. These results indicated that the developed hybrid inference system is highly efficient to be implemented as an optimized decision support system and its results are quite reliable. Unlike other works in the literature, in this paper, the optimization problem is not replaced with a rule-base which is presented by group of experts. But, an approach is provided to build the optimal rule-based decision support system in which the optimum knowledge is obtained through an optimization problem. This approach will provide decision makers with all optimal decisions that may be needed in the future by replacing the optimal deterministic values for decision variables with the optimal hybrid distribution.