Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
10
3
2020
09
22
Designing the Model of Assessing the Risk management of Automaker Companies in Iran:
Grounded Theory
9
28
FA
Ali
Mohaghar
0000-0002-9844-1714
Professor, University of Tehran.
amohaghar@ut.ac.ir
Alireza
Khorasani
Ph.D Student, University of Tehran Alborz Campus.
ar_khorasani@yahoo.com
10.52547/jimp.10.3.9
The purpose of this paper is to present a process model for assessing the risk management of automobile companies, in which it explains why the automaker enters the process of risk management assessment and how this process works. Based on the Grounded theory (GT) approach and the results of 22 in-depth interviews with 18 experts, a exploratory-process model for describing the risk management assessment phenomenon from the viewpoint of the automaker has been addressed. To analyze and integrate the data, the qualitative-inductive method of the GT including open coding steps, axial coding, and selective coding based on Strauss and Corbin's systematic approach were used. Based on this framework, Causal Conditions of the arrival of the automaker to the process of risk management assessment including organizational, national and international factors. The four other categories that describe how risk management is assessed by the automaker are: Intervening factors including the organizational, national and international context, the contingency factors including the nature of the environmental variables, the nature of the customer and the nature of the automaker, the categories of consequences including national results and Organizational result (survival, growth and profitability) and the category of strategy (exposure process) include pre-exposure, exposure and post-exposure stages. <br />
Automaker,Assessment Proccess,Assessment Models,Risk Management,Grounded theory
https://jimp.sbu.ac.ir/article_87545.html
https://jimp.sbu.ac.ir/article_87545_67456b1bef30c098ccafe5e828162774.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
10
3
2020
09
22
An Optimization Model for Closed-Loop Supply Chain Scheduling Problem
29
52
FA
Mohammad
Rostami
Assistant Professor, Shahrood University of Technology.
rostami_m@shahroodut.ac.ir
10.52547/jimp.10.3.29
In today's complex world and in order to increase competitiveness, planners in the manufacturing systems have focused on product distribution and collection of used products. In this paper, the closed-loop supply chain scheduling problem is investigated for the first time. A comprehensive and integrated model is presented for production scheduling, delivering products to retailers using limited-capacity vehicles, and pick-upping end of life products in order to recycle and reuse in supply chain. The aim of this problem is to minimize maximum tardiness. Due to the fact that this problem is NP-hard, a genetic algorithm is presented to solve the large-size instances by obtaining near-optimal solutions. To illustrate the importance of the problem under consideration, a case study of the motor oil supply chain is presented.
Scheduling,Closed-Loop Supply Chain,Maximum Tardiness,Linear Programming Model,Genetic algorithm
https://jimp.sbu.ac.ir/article_87546.html
https://jimp.sbu.ac.ir/article_87546_d3d01dac0bd86b9dc1302724bb6db431.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
10
3
2020
09
22
Evaluation of Organizational Excellence Model for Development and Empowerment of Human Resources (Case Study: Shams Abad Distributed Power Plant)
53
69
FA
Mostafa
Sadeghi Zeydanloo
M.A., Caspian Institute of Higher Education.
mostafacadcam.ms@gmail.com
Seyed Hossein
Seyed Esfahani
Assistant Professor, Caspian Institute of Higher Education.
hoseinse@yahoo.com
10.52547/jimp.10.3.53
The main purpose of this research was to develop and empower the power plant staff (Shams Abad) which was done by power plant specialists in order to grow and improve the organization. and prioritize it using fuzzy model network analysis which can be effective in strategic decision making of the Distributed Power Plant. This study using Delphi questionnaire design and experts' criteria and sub-criteria, we designed Delphi questionnaire and distributed to statistical population. In the next step, the weight of the criteria and sub-criteria screened was determined using fuzzy ANP method. The results showed that strong financial support for the application of new technologies was the highest among the criteria. Out-of-the-box training courses on new technologies and resource utilization skills in device maintenance are ranked second and third, respectively.
Empowering Employees,Human Resources Management,Fuzzy Theory,Analytical Network Process )ANP(,Excellence Model,Delphi Method
https://jimp.sbu.ac.ir/article_87547.html
https://jimp.sbu.ac.ir/article_87547_871254cdb936e7b12731ab221331d43d.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
10
3
2020
09
22
An Enhanced LSTM Method to Improve the Accuracy of the Business Process Prediction
71
97
FA
Mohammad Hasan
Adalat
Department of Computer Engineering, Islamic Azad University Qom, Qom, Iran.
m.adalat@gmail.com
Reza
Azmi
Department of Industrial Engineering, Alzahra University.
azmi.reza@gmail.com
Jafar
Bagherinejad
Department of Computer Engineering, Alzahra University.
jbagheri@alzahra.ac.ir
10.52547/jimp.10.3.71
Prediction of the process behavior plays a key role in business process management. This research benefits from recent development in the field of deep learning to predict the next event in business processes. The proposed method uses Long Short-Term Memory (LSTM) as a promising architecture of recurrent neural networks. This architecture is implemented using a number of configurations with the aim of investigating how each of them affects the performance of the prediction models. In order to build and evaluate our prediction models, we used two publicly available datasets (BPI 2012 and BPI 2017). After developing 300 prediction models, the results indicated that the proposed method outperforms the state-of-the-art methods in terms of precision. The best result in terms of Accuracy (0.907) was achieved through “one-hidden” layer LSTM architecture and by using “Big” configuration in the absence of “feedback”.
Process Management,Prediction Model,Machine Learning,LSTM Architecture
https://jimp.sbu.ac.ir/article_87590.html
https://jimp.sbu.ac.ir/article_87590_34d67a6e96031eaa9980a489cb99f9a5.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
10
3
2020
09
22
Multi-Objective Pharmaceutical Supply Chain Modeling in Disaster (Case Study: Earthquake Crisis in Tehran)
99
123
FA
Fatemeh
Alidoost
M.A., Alborz Campus, University of Tehran.
fatemeh.alidoost@gmail.com
Farzad
Bahrami
f-bahrami@araku.ac.ir
Assistant Professor, Arak University.
f-bahrami@araku.ac.ir
Hossein
Safari
0000-0001-9232-1319
Professor, University of Tehran.
hsafari@ut.ac.ir
10.52547/jimp.10.3.99
Absence of coordination between different sections of pharmaceutical supply chain has been announced as the most important challenge in the medicine industry. These sections are often in conflict and it is possible that their related decisions become suboptimal for the whole supply chain. In this study, a multi-objective mathematical model is offered for pharmaceutical supply chain problem. The model helps make strategic decisions in unexpected disaster occurences such as earthquake and flood. To improve the humanitarian relief in disaster, the model concurrently minimizes the total costs, maximizes the dispersion of distribution centers and minimizes the percentage of drug undersupply as three different objective functions. The model is solved by Torabi-Hassini approach and the performance and importance of objective functions have been compared. In order to verify the proposed model and the relations of different levels of supply chain, Tehran earthquake crisis is considered through different scenarios as the case study. The results illustrate that the highest and lowest demand is in the case of Ray and Mosha fault activation, respectively. Finally, it is shown that increasing the utility of minimizing the percentage of drug undersupply and maximizing dispersion of distribution centers inflicts higher costs on the system.
Pharmaceutical Supply Chain,Disaster,Humanitarian Relief,Multi-Objective Mathematical Modeling,Torabi-Hassini Approach
https://jimp.sbu.ac.ir/article_87598.html
https://jimp.sbu.ac.ir/article_87598_eb5fd762f6b28881135e65ebfb45dca9.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
10
3
2020
09
22
Investigating the Strategic Alignment of Business and Information Technology Using the Luftman Model and ITIL Best Practice
125
141
FA
Mohammad Reza
Taghva
0000-0002-6573-7914
Associate Professor, Allameh Tabataba’i University.
taghva@gmail.com
10.52547/jimp.10.3.125
The aim of this study was to investigate the strategic alignment of business and information technology using Luftman model and ITIL best practice, and since the study of this alignment requires an in-depth study of an industry or an organization, one of the Iranian defensive organizations (in standardization and information technology field) has been selected as the case study. In the first stage, the existence of IT strategy was assessed. Secondly, the degree of alignment of IT strategy with business strategy was assessed. The results showed that the IT strategy in the studied organization is on average 66.26 percent, which indicates the relative and acceptable ability of the organization to define IT strategy. Then, after analyzing the strategic alignment of IT and organization, it was found that the alignment degree of these organizations is generally above average. The results showed the lowest average in the area of business infrastructure and the highest average in the business infrastructure area. It is recommended that similar organizations use the ITIL V4 to assess and align the organization's strategies with the IT strategies.
Business Infrastructure,Information Technology,Information Technology Infrastructure Library,Luftman Model,Strategic Alignment
https://jimp.sbu.ac.ir/article_87596.html
https://jimp.sbu.ac.ir/article_87596_70725cc3465c2421c57b3c0b41c90080.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
10
3
2020
09
22
Location Selection of Solar Power Plants, Wind and Distributed Generation and Degisn of Electrical Distribution Network
143
170
FA
Fereshte
Shahbazi
M.Sc., Iran University of Science and Technology.
fshahbazi146@gmail.com
Hadi
Sahebi
Assistant Professor, Iran University of Science and Technolog.
hadi_sahebi@iust.ac.ir
Ahmad
Makui
0000-0001-6249-530X
Professor, Iran University of Science and Technology.
amakui@iust.ac.ir
10.52547/jimp.10.3.143
Today, the required energy mostly comes from fossil fuels. Due to the limitation of fossil fuel reserves in the world and emissions of pollutants, today's industries have been challenged to replace renewable energy source.Among these renewable energies, solar and wind are important. In this research, firstly, the factors affecting the location of the solar and distributed generation have been investigated and mapping of criteria in the GIS has been prepared.Then, considering the importance of integrating the information, the ANP technique is chosen for weighting the layers and implemented with Super Decision software.Finally, the model of supply chain of the distribution network is proposed with the aim of maximizing the supplier's profit and minimizing the emissions.Zanjan province is considered as the case study for which the model is solved. According to the results, areas of Khodabandeh, Ijrud, and Mahnashan are suitable for the construction of wind power plants and areas of Khodabande and Ijrud are suitable for the construction of solar power plant. Finally, Khodabandeh, Zanjan, and Mahnashan are suitable for construction of the small gas scale plant.
electrical distribution network,location selection,Solar and DG power plants,GIS,ε-Constraint Method
https://jimp.sbu.ac.ir/article_87595.html
https://jimp.sbu.ac.ir/article_87595_fcc65e7f84d6dc80b14188ab2155ec0f.pdf