Hadi Shirouyehzad; Arash Shahin; Mina Dayani
Volume 2, Issue 1 , March 2015, Pages 1-14
Abstract
Agile project management concept was introduced in the 21st century for the first time to provide continuous and timely software to provide value to the shareholders. This method is also useful for a variety of projects to respond to environmental changes. As a dynamic business area, always there is ...
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Agile project management concept was introduced in the 21st century for the first time to provide continuous and timely software to provide value to the shareholders. This method is also useful for a variety of projects to respond to environmental changes. As a dynamic business area, always there is a balance between the current and desired status of project-based organizations for which the study of the agile gap is important. In addition, there is no exact definition for desired status. Therefore, studying perception and expectation of contractors and employers is playing a main role for agile project management analysis. In this paper, data envelopment analysis has been applied to identify the most critical agile project management dimensions, based on the difference between contractors’ and employers’ perceptions and expectations. The case study includes six projects in Foolad technique Co. , the results showed that the following criteria are in critical condition in Foolad Technique Company: "team capabilities", " Customer Involvement", " Delivery Strategy" and "organizational environment"
Farzad Movahedi Sobhani; Tahereh Madadi
Volume 2, Issue 1 , March 2015, Pages 15-33
Abstract
The main purpose of this paper is to investigate the suitability of diverse data mining techniques for construction delay analysis. Data of this research obtained from 120 Iranian construction projects. The analysis consists of developing and evaluating various data mining models for factor selection, ...
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The main purpose of this paper is to investigate the suitability of diverse data mining techniques for construction delay analysis. Data of this research obtained from 120 Iranian construction projects. The analysis consists of developing and evaluating various data mining models for factor selection, delay classification, and delay prediction. The results of this research indicate that with respect to accuracy and correlation indexes, genetic algorithm with K-NN learning model is the most suitable model for factor selection. By conducting the genetic algorithm, eight significant variables causing construction delay are identified as: Changes in project manager, Difficulties in financing project by owner, Number of employees, Project duration, Unforeseen events, Project Location, Number of equipment, How to get the project. This research also revealed that in the case of delay classification and prediction, respectively, bagging decision tree and bagging neural network has the least amount of error in comparison with other techniques. In addition, to compare the diversity of data mining methods, the optimized parameter vectors of the selected models were also identified.
Alireza Niazi; Mehrdad Nikbakht
Volume 2, Issue 1 , March 2015, Pages 34-51
Abstract
In recent years, Green Supply Chain Management (GSCM) has implemented by the most of industries. With various barriers to implement GSCM, they couldn’t improve performance of the process and products according to the requirements of the environmental regulations. The paper aims to identify and ...
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In recent years, Green Supply Chain Management (GSCM) has implemented by the most of industries. With various barriers to implement GSCM, they couldn’t improve performance of the process and products according to the requirements of the environmental regulations. The paper aims to identify and prioritize of barriers GSCM implementation in petrochemical industry. The GSCM barriers are identified by extraction from the literature and interviews with experts. The statistical population includes the personnel in a petrochemical company of South Pars in Persian Gulf. The paper uses Shapiro-Wilk test for the research variables normality check, and structural equations modeling technique for investigation of the relationships between the variables. Analytical Hierarchy Process (AHP) is used to give priorities for the barriers of the GSCM implementation. The identified barriers have significant impact on GSCM implementation. The regulations and laws, competitive market, technological infrastructure, and lack of top management commitment are finally identified the most important barriers on supply chain management implementation.
Hadi Shirouyehzad; Hananeh Shirvani; Mohammad Reza Vasili
Volume 2, Issue 1 , March 2015, Pages 52-63
Abstract
Nowadays, knowledge management has become a key element of knowledge-based organizations activities. These companies attempt to effectively and efficiently use of their intellectual investments and knowledge resources in order to achieve strategic objectives executing various knowledge management projects. ...
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Nowadays, knowledge management has become a key element of knowledge-based organizations activities. These companies attempt to effectively and efficiently use of their intellectual investments and knowledge resources in order to achieve strategic objectives executing various knowledge management projects. This research is done to Prioritize organizations based on knowledge management processes. Therefore, in first step, the general model of knowledge comprised 4 processes of knowledge creation, knowledge storage, knowledge sharing and application of knowledge, are selected and they were weighted by the experts regards. The statistical population of this research was the chief and middle managers of the companies and a questionnaire was used to collect information. Then Fuzzy TOPSIS, one of multi criteria decision making algorithms was applied to Prioritize automotive part manufacturing companies. The results of prioritizing the organizations through Fuzzy TOPSIS model revealed that PeymanSanat company has the first rank in the field of knowledge management processes with the similarity indicator of 0.5975, and sensitivity analysis revealed the knowledge preservation and knowledge creation are the most effective factors.
Payam Khosravi; Mehdi Alinaghian; Seyed Mojtaba Sajadi; Erfan Babaee Tirkolaee
Volume 2, Issue 1 , March 2015, Pages 64-76
Abstract
Waste collection is a highly visible municipal service that involves large expenditures and difficult operational problems. In addition, it is expensive to operate in terms of investment costs (i.e. vehicles fleet), operational costs (i.e. fuel and maintenances) so that generating small improvements ...
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Waste collection is a highly visible municipal service that involves large expenditures and difficult operational problems. In addition, it is expensive to operate in terms of investment costs (i.e. vehicles fleet), operational costs (i.e. fuel and maintenances) so that generating small improvements in this area can lead to huge savings in municipal expenditures. Among the issues raised in the process of decisions making by managers and associated policy makers, one can point to determining the optimal weekly policies of waste collection. In this paper, the periodic capacitated arc routing problem (PCARP)in mobile disposal sites is described and the authors seek to determine the optimal routes of required edges (streets or alleys) per week, number and location of mobile disposal sites, and the number of required vehicles. We present two simulated annealing algorithms, which are different in cooling schedule and number of iterations of each temperature. To evaluate the performance of these algorithms on small-sized problems, the solver “CPLEX"in application “GAMS” is used. The experimental results show that the presented algorithms have appropriate performance and a reasonable time range.
