Maghsoud Amiri; Amir Alimi; Seyed Hossein Abtahi
Volume 6, Issue 17 , September 2007, , Pages 135-151
Abstract
Data envelopment analysis model is a model for calculating the efficiency of decision making units (DMUs). In previous models there are some weaknesses that the most important one is changing weights of inputs and outputs in model that lead to evaluate efficiencies of DMUs with different weights. The ...
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Data envelopment analysis model is a model for calculating the efficiency of decision making units (DMUs). In previous models there are some weaknesses that the most important one is changing weights of inputs and outputs in model that lead to evaluate efficiencies of DMUs with different weights. The important subject is that How we should evaluate all of decision making units with one set of weights and optimize their efficiencies simultaneously. This paper aims to present a new model that eliminates the weaknesses of previous models. Odeveloped model is designed based on multi objective decision making models and this model is solved with fuzzy solution method of multi objective decision making models and leads to creating common weights. The main object of research that was better ranking of DMUs rather than basic models have been done by using this model and this is showed with solving the model on an example.
Mohammad Taghi Taghavifard; Amir Mahdi Malek
Volume 9, Issue 22 , September 2011, , Pages 135-165
Abstract
Key Performance Indicators, help an organization to define and measure the progress of organization toward organizational goals. Key Planned Performance Indicators (KPPI) are the tools for measure the progress of organization toward goals and strategic. Since the Decision Makers are concerned with these ...
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Key Performance Indicators, help an organization to define and measure the progress of organization toward organizational goals. Key Planned Performance Indicators (KPPI) are the tools for measure the progress of organization toward goals and strategic. Since the Decision Makers are concerned with these attributes and indices in uncertain environments, selection of these indices is a Multiple-Attribute Decision-Making problem. In the past, several methods such as the linear weighting methods, AHP, TOPSIS, Fuzzy Logic and Mathematical programming have been used to solve the indices selection problem. In this thesis, we give a new grey-based approach to deal with the indices selection problem with regards to organizational strategic plans. Firstly, the weights and ratings of strategic- base attributes for all alternatives are described by linguistic variables that can be expressed in grey numbers. Secondly, using a Grey Possibility Degree (GPD), the ranking order of all alternatives is determined. Finally, an example of indices selection for instruction and research department of IRIB is used to illustrate the proposed approach.
Darush Mohamadi Zanjirani; Majid Esmailian; Saeedeh Jokar
Abstract
Process planning involves determining the most suitable and efficient manufacturing (assembly) processes and their sequence in order to produce a product (part). These processes should be compatible with required attributes in product design documentation. Process planning and scheduling optimization ...
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Process planning involves determining the most suitable and efficient manufacturing (assembly) processes and their sequence in order to produce a product (part). These processes should be compatible with required attributes in product design documentation. Process planning and scheduling optimization is done with Considering qualitative parameters which are affective on job shop and flexible system. Fuzzy Inference System and Meta-heuristic algorithms with multiple objective and goal functions are used to solving problem. Objective functions include minimization of cost and time of processing parts and maximizing the utility of the process design. based on the illustrated numerical example simulated annealing algorithm has better efficiency than imperialist competitive algorithm, particle swarm, bee colony.
Mohammad Valipour Khatir; Zeinolabedin Akbarzadeh
Abstract
Manufacturing strategies as the most common internal controllable capability of companies, play a key role in achieving sustainable competitive advantage. The identification and development of these strategies requires a clear understanding of their role in gaining competitive advantage and their mutual ...
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Manufacturing strategies as the most common internal controllable capability of companies, play a key role in achieving sustainable competitive advantage. The identification and development of these strategies requires a clear understanding of their role in gaining competitive advantage and their mutual effects on each other. In this regard, this paper has presented practical approach to evaluate manufacturing strategies using fuzzy Quality Function Deployment (QFD) and Interpretive Structure Modeling (ISM) techniques. The results of fuzzy QFD show that the studied company has suitable situation in competitive factors contains facilities for sale, the product variety and production technology, while the cost and delivery speed are not desirable. In the following, the ISM technique was used to prioritize the resource allocation in manufacturing strategies; the findings show that human resource empowerment has the highest implementation priority in the Foladin Zob Amol (FZA) company
Mehran Khalaj; Amir Hossine Khalaj; Jalal Talebi
Abstract
Manufacturing systems are always facing different kinds of risk such as failure and interruption risk. Performance risk analysis of manufacturing systems cause errors happening in the prediction of parameters and will also result in wrong decisions where the real and appropriate data is not available. ...
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Manufacturing systems are always facing different kinds of risk such as failure and interruption risk. Performance risk analysis of manufacturing systems cause errors happening in the prediction of parameters and will also result in wrong decisions where the real and appropriate data is not available. In uncertainty condition there is no appropriate data for decision making and in the specific mode of uncertainty the decision maker faces with a lack of information. Risk is a state of uncertainty that the available information from background of system is incomplete. Risks in manufacturing systems are directly related with failure to achieve the reliability of machines. So in this paper the records and the relationship between risk and reliability have been studied, then a model is proposed using Dumpster-Shafer theory to maximize the reliability according to the existing risk. Since the exact calculation of reliability for complex systems and processes is extremely difficult and complicated when the correct data of failure is not available, newly proposed model uses Dumpster-Shafer theory that enjoys all the available data for decision making instead of using the purely qualitative methods. Using this method results in obtain the risk ranges for equipment and machinery. These ranges are drawn in a risk analysis matrix according to the relationship between risk and reliability of machinery and the changes have been determined in order to meet the lower risk. All the proposed methods are examined using the data of a manufacturing company, the concentration of evaluating the reliability is on using the Probability theory in which the failure time is predicted by determining type of component failure distribution while the research provides change in attitude for applying the simultaneous use of possibility and probability theory
Mehdi Seifbarghy; Shima Zangeneh
Abstract
In the classic models of facility location, it is assumed that the selected facilities always work based on the schedule while, in the real world, facilities are always exposed to disruption risk and sometimes these disruptions have long-term effects on the supply chain network and cause a lot of problems. ...
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In the classic models of facility location, it is assumed that the selected facilities always work based on the schedule while, in the real world, facilities are always exposed to disruption risk and sometimes these disruptions have long-term effects on the supply chain network and cause a lot of problems. In this paper, a mixed integer programing (MIP) model presented in order to determine how to serve the customers at the time of disruption in distribution centers in a two-echelon supply chain, including distribution centers and customers. This model selects potential places that minimize traditionally supply chain costs and also the transportation cost after distribution centers disruptions. In fact, the model tries to choose the distribution centers facilities with lowest cost and highest reliability and also allocate them to customers. The problem divided into two sub-problems using Lagrangian relaxation approach. By examining sub-problems optimal conditions, a heuristic solution is used for the first sub-problem and a genetic algorithm is used for the second sub-problem to solve large-scale problems. Finally, numerical examples are presented to examine the performance and efficiency of the proposed model and approach
Maghsoud Amiri; Mahdi Keshavarz Gharabaei
Volume 13, Issue 36 , April 2015, , Pages 143-171
Abstract
Actual scheduling problems may necessitate the decision maker to consider a variety of criteria prior to make any decision. This research considers a single machine scheduling problem, with the objective of minimizing a combination of total tardiness and waiting time variance criteria in which the idle ...
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Actual scheduling problems may necessitate the decision maker to consider a variety of criteria prior to make any decision. This research considers a single machine scheduling problem, with the objective of minimizing a combination of total tardiness and waiting time variance criteria in which the idle time is not allowed. Minimizing total tardiness is always regarded as one of the most important performance criteria in practical systems to avoid penalty costs of tardiness and waiting time variance is an important criterion in establishing Quality of Service (QoS) in many systems. Each of these criteria is known to be NP-hard and therefore the linear combination of them will be NP-hard as well. For this problem, we developed a genetic algorithm by utilizing its general structure. Two types of heuristic and random initial population and two distinct fitness functions are applied to genetic algorithms. The GA is shown experimentally to perform well by testing on various instances.
Maghsoud Amiri
Volume 6, Issue 15 , March 2007, , Pages 143-165
Abstract
After introducing Markowitz mean-variance model, decision makers (DMs) and financial planners paid much attention to the matter of portfolio selection, so that DMs explain purposes and investment requirements in the frame of multi-objective mathematic models which are more consistent with decision making ...
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After introducing Markowitz mean-variance model, decision makers (DMs) and financial planners paid much attention to the matter of portfolio selection, so that DMs explain purposes and investment requirements in the frame of multi-objective mathematic models which are more consistent with decision making realities in optimal portfolio selection. At now there are various methods introduced to optimize such problems. One of the optimization methods is the Compromise Programming (CP) method. In this paper, considering increasing importance of investment in financial portfolios, we propose a new method, called Nadir Compromising Programming (NCP) by expanding a CP-based method for optimization of multi-objective portfolio selection problem. In order to examine NCP performance and operational capability, we implemented a case study by selecting a portfolio with 35 stock indices of Iran stock market. Results of comparing the CP method and proposed method under the same conditions indicate that NCP method results are more consistent with DM purposes.
Mohammad Hoseyn Karimi; Nima Esfandiari; Mahmoud Moradi
Volume 13, Issue 39 , January 2016, , Pages 145-170
Abstract
Many companies are pursuing agile manufacturing in order to reduce costs, improve customer service and attaining competitive advantage. After reviewing theoretical background and literature on agility, this paper presents agility attributes, criteria and enablers. Then a framework developed in order ...
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Many companies are pursuing agile manufacturing in order to reduce costs, improve customer service and attaining competitive advantage. After reviewing theoretical background and literature on agility, this paper presents agility attributes, criteria and enablers. Then a framework developed in order to prioritize and analyze agility indices with considering major competitive advantage. Hybrid Fuzzy Quality Function Deployment (FQFD) and Gap Analysis (GA) approach used to prioritize indices based on experts in an organization. Findings point out that “manufacturing management agility” has lowest maturity among agility enablers that lead this enabler to takes maximum importance. Furthermore, “manufacturing management agility” obtained most weight by FQFD, meaning this enabler has maximum priority and importance for organization. Interestingly, “knowledge management criterion” got first priority among all criteria by regarding maximum gap in gap analysis approach
Hiwa Farughi; Seiran Alaniazar; Seyedhamed Mousavipour; Vahed Moradi
Abstract
Nowadays, most of developed and developing countries, because of both limited resources and growing competitive markets, looking for to diagnose the causes of projects delay and are trying to develop solutions for decreasing amount of delay in next projects. In this paper initially notions related to ...
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Nowadays, most of developed and developing countries, because of both limited resources and growing competitive markets, looking for to diagnose the causes of projects delay and are trying to develop solutions for decreasing amount of delay in next projects. In this paper initially notions related to delay, project risk management, Failure Mode Effects and Analysis (FMEA) method have been reviewed and also construction projects of Kurdistan state organization of schools renovation have been examined. Then a framework based on Fuzzy FMEA and AHP model have been proposed in order to recognize the most important risks and determining the amount of effects of these risks on main objective of projects (i.e. time, cost and quality) and estimating their occurrence probabilities. Meanwhile along with calculating importance coefficient of factors, some ideas to prevent or decrease consequences of these factors have been recommended
supply chain management
Mostafa Ziyaei Hajipirlu; Houshang Taghizadeh; Mortaza Honarmand Azimi
Abstract
The purpose of this study is to design supply chains' upstream structure evaluation model in the automotive industry with spectral clustering based on the theory of complex adaptive systems. In this research, a method for evaluating the intersectionalities related to the structural complexity (horizontal, ...
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The purpose of this study is to design supply chains' upstream structure evaluation model in the automotive industry with spectral clustering based on the theory of complex adaptive systems. In this research, a method for evaluating the intersectionalities related to the structural complexity (horizontal, vertical, and spatial) of supply chains by considering the functional characteristics of its components based on the resilience paradigm is presented. In this regard, a set of algebraic calculations and computational algorithms have been adapted to evaluate the structural design from the perspective of complex components. In the structural design evaluation model through spectral clustering, it is possible to enter information about supply chains in terms of interactions between components in the form of a network as a comprehensive model called similarity graph. According to the field findings, supply chain characteristics in terms of complexity can have interaction with component processing performance. This means that according to the concept of entanglement, the lack of a favorable environmental structure in supply chains can also negatively affect the resilience performance of its components. Findings from the perspective of achieving a supply chain evaluation model as an integrated whole have provided a suitable practical tool for evaluation and pathology of supply chains from the perspective of risk management.
Hamid Shahbandarzadeh; Mohammad Hossein Kabgani
Abstract
This paper focused on locating ATMs problem. At first, this paper aims to identify effective factors in selecting ATMs appropriate locations. After selecting potential locations, optimal locations are determined through mathematical modeling. In this paper, effective factors to determine potential locations ...
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This paper focused on locating ATMs problem. At first, this paper aims to identify effective factors in selecting ATMs appropriate locations. After selecting potential locations, optimal locations are determined through mathematical modeling. In this paper, effective factors to determine potential locations are weighted through Fuzzy AHP. Finally, linear allocation technique with multi-objective approach is used to determine ATMs locations at Bushehr city. After literature review, 46 effective factors are identified and then, based on experts' opinion are categorized in 6 groups of demographic, economic - social factors, competitive – commercial factors, public utility (infrastructure and proximity) factors, investment factors and political - legal factors. Results from Fuzzy AHP show that demographic factors are the most important factors among others. Final results show that each of these six categories, can have different effects on decision makers.
mm uuu
Abstract
Mobile phone towers strength and coverage after happening natural disaster are one of the most important issues in set covering. Every day advances and developments of mobile phone technology have made the telecommunication industry and transferring equipment more important and subscribers and users ...
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Mobile phone towers strength and coverage after happening natural disaster are one of the most important issues in set covering. Every day advances and developments of mobile phone technology have made the telecommunication industry and transferring equipment more important and subscribers and users of the mobile phones and increasing which requires better planning. So, the subject of coverage ability of the cell phone towers is very important. Natural disasters for example earthquake, flood, storm, landslides and activating volcano affect roads, bridges, communication systems, electrical supplying and availability to facilities. Extensive human casualties and huge economic damages are showing prediction necessity and programming for facing these events preventing crisis occurring This paper develops location and strengthening of cell phone towers to maximize service coverage and minimize the loss of communication if natural disaster happens. In addition, proposed model considers backup and emergency coverage. We present a case study of our approach for disaster planning for disaster scenario in a region of Iran. Numerical experiments demonstrate the significance and applicability of the developed model for actual decision-making problem.
Reza Yousefi Zenouz; Akbar Hassanpoor; Parisa Mousavi
Volume 13, Issue 37 , July 2015, , Pages 161-185
Abstract
Risk is inherent and inseparable part of life and business. Always uncertainty condition arising from incomplete information and data or ungovernable variables, associated with opportunities and threats.Nowadays many organizations and companies have relied heavily on information systems and information ...
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Risk is inherent and inseparable part of life and business. Always uncertainty condition arising from incomplete information and data or ungovernable variables, associated with opportunities and threats.Nowadays many organizations and companies have relied heavily on information systems and information security management has transformed to an important organizational topics. And due to the fact that the use of information systems security may be created some risks, an effective risk management process, will result in a successful security program. Risk management includes risk identification process, risk assessment and risk-reduction efforts to acceptable levels. The objective of this research is to prioritize information security risks, in order to provide a mechanism to enhance the security of enterprise information. To this end, a model has been presented for organizational information security risk assessment using the fuzzy AHP and Bayesian networks. In the assessment process, risks impact by fuzzy AHP and risks probability by Bayesian networks have calculated and finally The risks Prioritized. The findings suggest In the case study, the risk of lack of knowledge and lack of proper training in the field of information security, have the highest priority and attention is needed most
amir daneshvar; Mahdi Homayounfar; elham akhavan
Abstract
Data classification is one of the main issues in management science which took into account from different approaches. Artificial intelligence methods are among the most important classification methods, most of them consider total accuracy function in performance evaluation. Since in imbalanced data ...
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Data classification is one of the main issues in management science which took into account from different approaches. Artificial intelligence methods are among the most important classification methods, most of them consider total accuracy function in performance evaluation. Since in imbalanced data sets this function considers the cost of prediction errors as a fix amount, in this research a sensitivity function in used in addition to the accuracy function in order to increase the accuracy in all of the predefined classes. In addition, due to complexity in process of seeking information from decision maker, NSGA II algorithm is used to extract the parameters (Weight vector and cut levels between classes). In each iteration, based on the estimated weight vector and data sets, the algorithm calculate the score of each alternative using Sum Product function and then allocates the alternative to one of the classes, comparing to the estimated cut levels,. Then, using the fitness functions, the estimation class and the actual class will compare by two algorithms and this process will continue since optimizing the parameters. Comparison of the NSGA II and NRGA algorithms show the high efficiency of the proposed algorithm.
Majid Esmaelian; Sayedeh Maryam Abdollahi
Abstract
Course timetabling is an important branch of the general scheduling problem. The course timetabling problem as a step in the course planning process in universities is one of the challenges faced by managers in the field of education. The problem is defined as assigning university courses to specific ...
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Course timetabling is an important branch of the general scheduling problem. The course timetabling problem as a step in the course planning process in universities is one of the challenges faced by managers in the field of education. The problem is defined as assigning university courses to specific periods throughout a week for a given semester while satisfying specific constraints. In this study, we present two novel binary integer linear programming models for the university timetabling problem. Using a GAMS IP Solver, several experiments through each model are solved and the results (the number of the decision variables and solution time) are compared and analyzed. The computational comparison indicates that the second model can be used for modeling large-scaled problems and has less computational and size complexity. Therefore, the second model is applied to optimal scheduling the courses planned for the faculty of administrative science and economics (ASE) at Isfahan University for one semester and the results consist of table of courses planned for teachers, students groups, rooms and workdays are presented
Seyyed Hossein Abtahi; Ahmad Hasani Kakhaki
Volume 4, Issue 12 , March 2006, , Pages 163-182
Abstract
Forecasting is a base of any planning method especially human resource planning. One of the most important problems of organizations is human resource and personnel's problems. Accompanied by advance in the human societies and therefore complication in organizations, these subjects create opportunities ...
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Forecasting is a base of any planning method especially human resource planning. One of the most important problems of organizations is human resource and personnel's problems. Accompanied by advance in the human societies and therefore complication in organizations, these subjects create opportunities and challenges for managers. A proper human resource planning can increase job satisfaction, promote quality and favorites of manpower and decrease staffing cost. Nowadays quantitative and qualities tools and methods are existent that utilize for human resource planning. This article is a research in tree dependent's firm of holding Software Company that applies one of most common method in planning. For estimate human resource needs in future stage, using tree previous year information that confine in six stages and duration of any stage is six month. Markov chain analyze is a method that use for estimate human resource in four job categories. Content scope in this research is human resource issues.
Ali Mohamadi; Payam Shojaei; Hamid Reza Yazdani; Mohammad Reza Sadeghi Moghaddam
Abstract
Regarding to the increasing importance of supply chain risk in the lastdecade in general and projects especially, in this research the dimensions andelements of supply chain risk of projects have been determined. Therefore,Fars Gas Transfer Pipeline projects were considered to discover codes andthemes ...
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Regarding to the increasing importance of supply chain risk in the lastdecade in general and projects especially, in this research the dimensions andelements of supply chain risk of projects have been determined. Therefore,Fars Gas Transfer Pipeline projects were considered to discover codes andthemes according to the phenomena by using Grounded Theory (Corbin andStrauss method). Based on final paradigm model, project supply chain riskmanagement issue was categorized in 6 main dimensions, 19 sub-dimensionsand 57 codes. The results show that supply chain risks as a core phenomenon,consists of environmental risks, organizational risks and network risks. Todo this, we use theoretical sampling and interview with 10 experts from Gasstate company and some suppliers. These interview was deep one becausewe employed open questionnaire. Then by using open encoding, axialencoding and selective encoding, paradigm model was extracted. The mainphenomenon placed the center of model and other themes joined to that
Akram Oveysiomran
Abstract
Input and output selection in Data Envelopment Analysis (DEA) has many important. In this research, inputs and outputs of reginal power companies are selected with artifitial neural network. The application of neural network in the selection of inputs and outputs of reginal power companies is not a precedent ...
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Input and output selection in Data Envelopment Analysis (DEA) has many important. In this research, inputs and outputs of reginal power companies are selected with artifitial neural network. The application of neural network in the selection of inputs and outputs of reginal power companies is not a precedent in the literature and it is considered the main advantage of the proposed method. In order to train two layers MLP neural network, after presenting of error resilience, learning method was used. After neural network training, neural network performance is examined by using the test set. RMSE value for 15 test set equals 0/0269 which reflects the high accuracy of training network. The Sensitivity Analysis of the studied parameters which are the same inputs and outputs of Data Envelopment Analysis, with ten percent increase of parameter, compared to the prior one was carried out and output relative error average for neural network parameters was calculated. Based on the output relative error average, inputs and outputs were determined. By comparing the efficiency scores of regional electricity companies before and after reducing the number of variables, it is noticed that the number of efficient companies during the above four periods decreased from 50 percent to 11 percent. Finally, the neural network application in inputs and outputs selection of the regional electricity companies was unprecedented in the literature and this is the main advantage of this method.
Somayeh Kavianpour; Gavad Rezaeian
Abstract
Appropriate scheduling of shifts for nurses, is a critical issue in hospital management. This study improves the scheduling of shifts for nurses in health services organizations to provide lower cost and also to reduce the computational complexity and finally to realize the outcome of these actions on ...
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Appropriate scheduling of shifts for nurses, is a critical issue in hospital management. This study improves the scheduling of shifts for nurses in health services organizations to provide lower cost and also to reduce the computational complexity and finally to realize the outcome of these actions on job satisfaction and quality of received services. A linear mathematical model is proposed and since this problem is NP-hard, Genetic Algorithm is provided for solving the problem and finally Implemented in Imam Khomeini hospital of Noor city as a real sample. Computational results and performance of the proposed algorithm in terms of solution quality and computational time were analyzed. Accreditation standards for hospitals as well as the Productivity laws are used in the proposed model. Production of timetables by the proposed model, resulting in improved satisfaction levels of nurses and their job performance.
Mohammad Ali Shariat; Soleiman Iranzadeh; Alireza Bafandeh Zendeh
Abstract
The speed of competitiveness and organizational innovation, specifically with respect to corporate sustainability improving functions and environmental stress on manufacturing companies in predicting economic, social, and ecological advantages of their processes and products, significantly increased ...
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The speed of competitiveness and organizational innovation, specifically with respect to corporate sustainability improving functions and environmental stress on manufacturing companies in predicting economic, social, and ecological advantages of their processes and products, significantly increased in the recent decade. This condition faced all manufacturing companies across the world with a new challenge, making them try not only to maintain their current competitive status by developing and implementing sustainable production tools, but also to follow a sustainable progress that considers social, economic, and environmental matters at the same time. This study focused on business sustainability with a new perspective in industrial symbiosis, and tried to develop a sustainable production model through identifying different dimensions of sustainable production from managerial viewpoints of successful manufacturing companies in Semnan Province, Iran. To this end, managers of 33 successful companies across the province with at least five-year continuous work experience were interviewed, using the repertory grid technique. As a result, 33 single individual repertory grids and 175 initial individual constructs of sustainable production were fabricated. Finally, the sustainable collective grid of sustainable production, including 87 secondary constructs within 11 sections were drawn and analyzed through cluster analysis in SPSS. At the end, a sustainable production model with 11 pivots and 87 constructs within 4 sections, along with four production strategies (economic production, lean production, green production, and sustainable production) were proposed
iman ghasemian sahebi; Hamidreza FAllah Lajimi; Alireza Arab
Abstract
Operational strategy is one of the essential tools for operations management in the current competitive environment. The operational strategy focuses on the activities of the operational levels in line with the competitive priorities of the organization. Hence, the present study tries to review and design ...
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Operational strategy is one of the essential tools for operations management in the current competitive environment. The operational strategy focuses on the activities of the operational levels in line with the competitive priorities of the organization. Hence, the present study tries to review and design the most appropriate operational strategies for increasing the efficiency of the Automotive manufacturing industry. However, given that the supply chain of this industry is dependent on the changing and unpredictable environment of the market and environment such as raw materials, suppliers' conditions, government policies and sanctions, and the price fluctuations caused by currency volatility, so the need for operational strategies is felt. Therefore, after determining the annual goals for each output, continuous flow production system was identified as the appropriate system for achieving the desired situation in the studied company. At last, adjustments were provided to improve the company's status in each of the production levers. Output Prioritization and development of the Miltenburg model with the Fuzzy Best-Worst Method took place for the first time According to the experts' opinion, which cost criterion identified as the most important output and the Quality criterion placed at the second level of important; and also Flexibility, performance and delivery criteria placed at the next level of important.
ali shariat nejad; Saba Asgari zahabi
Abstract
Today, with increasing environmental uncertainty, one of the ways to adapt to changes and ensure a permanent job is the tendency towards hybrid entrepreneurship. the present study aimed to survey the impact of hybrid entrepreneurship on career success with the mediating role of diverse career path orientation ...
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Today, with increasing environmental uncertainty, one of the ways to adapt to changes and ensure a permanent job is the tendency towards hybrid entrepreneurship. the present study aimed to survey the impact of hybrid entrepreneurship on career success with the mediating role of diverse career path orientation was conducted. This research is applied research and it is among the descriptive and survey researches. The statistical population of this study is the managers and employees of companies located in industrial states in Lorestan province. Using the Cochran sample calculation formula, the sample size of 350 people was determined and the sample members were selected using the available sampling method. Data collection tools in the present study were standard questionnaires whose validity and reliability were confirmed by content method and Cronbach's alpha and combined reliability. the structural equation modeling approach and PLS software have been used to test the hypotheses. The results of the hypothesis indicate that hybrid entrepreneurship has positive impact on diverse career path orientation and career path success. as a general result, it should be noted that due to the high rate of bankruptcy and loss of jobs, people who work in industrial estates and in professional jobs, can with a hybrid entrepreneurial strategy and direction orientation. A diverse career that leads them to new and entrepreneurial businesses, try your luck at the success of a new career and another business, and take advantage of the benefits of second job, unemployment and state of mind. Unemployment to be safe.
S.jamal’aldin Hosseini; Jalal Rezaeenour; mohammad masoumi; Amir Hosein Akbari
Abstract
One Knowledge Management (KM) as one of the Supply Chain performanceimprovement factors can be strengthened through frameworks like EFQM ExcellenceModel in order to achieve competitive advantage. First, the KM enablers in SC areclassified based on EFQM enabler criteria. Then, the importance of each KM ...
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One Knowledge Management (KM) as one of the Supply Chain performanceimprovement factors can be strengthened through frameworks like EFQM ExcellenceModel in order to achieve competitive advantage. First, the KM enablers in SC areclassified based on EFQM enabler criteria. Then, the importance of each KM enabler isevaluated by fuzzy DEMATEL-ANP. In addition, Analytical Hierarchy Process (AHP) isapplied to evaluate the importance of each KM enabler in knowledge sharing amongsupply chain people. In the research, the multi-objective mixed integer programming isused to optimize knowledge management and select KM strategy in each part of SC.Likewise, it is approved to select suitable members of SC for Research and Development(R&D) unit of SC. Results show that each part of SC should focus on developing someKM enablers, and selection of a suitable strategy. These results also emphasis theeffectiveness of each KM enabler and their development in selecting of suitable membersfor R&D unit of SC.
supply chain management
R. Ghasemy Yaghin; Fateme Darvishi
Abstract
This paper presents a global supplier selection model for the textile and clothing industry using a fuzzy multi-criteria group decision making approach. Then, the order quantity of each supplier is determined by a mathematical programming model. In the first step, a group fuzzy analysis hierarchical ...
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This paper presents a global supplier selection model for the textile and clothing industry using a fuzzy multi-criteria group decision making approach. Then, the order quantity of each supplier is determined by a mathematical programming model. In the first step, a group fuzzy analysis hierarchical process approach is used to obtain the overall weight of the criteria and sub-criteria and then modified VIKOR is developed in order to calculate the vendor rating. In doing so, a modified VIKOR method with fuzzy-random data is extended due to the existence of both qualitative and quantitative criteria. The qualitative criteria are considered by fuzzy linguistic modeling and quantitative criteria from random data are formulated in a stochastic environment (based on historical data of suppliers). In the second step, a nonlinear programming model is developed to to determine the purchasing quantities from suppliers with multi-sourcing strategy. Finally, using a numerical study, the deployment of the above model is done in the clothing industry and crucial parameters are discovered by sensitivity analysis. Our findings indicate the critical role of customer’s demand and assigned capacity of suppliers in procurement plan.
