Industrial Management Journal
Year:2019 | Volume:11 | Issue:4 |Papers Count:8

Objective: There are many climatic factors affecting the number of patients in hospitals which generally tend to make a Non-optimal use of their facilities and human resources. This research is aimed at discovering hidden knowledge between climatic factors and the number of hospital patients using data mining techniques. Methods: In this study, the relationship between climatic factors and the number of patients in Dr. Sheikh specialized pediatric hospital of Mashhad is investigated by classification based on multidimensional association rule mining. The number of patients in the nephrology, hematology, emergency and PICU department of this hospital have been considered separately, and consequently the relationship between the number of patients and the climatic factors such as air temperature, relative humidity, wind speed, air pressure and air pollution have been analyzed. This research has analyzed data gathered through a 19 month period and has been obtained by referring to the documents. In this research for feature selection, all subsets of climatic factors are searched and the effect of all subsets on the number of patients are evaluated using linear regression. Also for rule mining is used classification based on multidimensional association rule mining which is based on known Apriori algorithm. Results: The results show different patterns that indicate the relationship between the number of patients in the hospital departments with the climatic factors. Conclusion: This study is able to help analyze the relationship between the climatic factors and the number of patients in the hospital. Also, the rules will help managers make optimal planning for hospital resources according to the different number of patients.

Objective: Change is an important part of the business and work process, and in the current competitive environment, an organization can only survive if it has the tools and capabilities needed to model and simulate its business processes to face these changes. The purpose of this paper is to present a hybrid agent-based and discrete-event simulation model for business process management. Methods: Using the proposed model of this paper, the process of credit card was modeled as a case study in accordance with the concepts of business process management, and then, a discrete-event simulation is used at the operational level, and agent-based simulation at the micro level as well as for modeling agents and their behaviors. The research is carried out in one of the Iranian banks. Results: The findings indicate that the current approach has the necessary adaptation to the actual situation. This means that it provides correct and reliable outputs. The research also shows how the combination of discrete-event and agent-based simulation methods can achieve a higher level of detail and complexity in managing business processes. Conclusion: It has been revealed that the proposed hybrid model has a less average relative error compared to single simulation methods, which in fact represents the acceptable performance of the model. Therefore, it can be used to examine different scenarios by applying changes to the input parameters and observing the results.

Objective: In recent years, global concerns about environmental and social issues have made consumers, government organizations, companies and universities more active, and their focus has increasingly been on the design of the supply chain network as the most important part of the supply chain. The main objective of this paper is to present a supply chain modeling model for Hamadan Glass Manufacturing Company considering the dimensions of sustainability. Methods: In this paper, a Fuzzy Multi-objective Mixed Integral Programming is presented to design a closed loop supply chain under uncertainty conditions in order to minimize environmental impacts and maximize social impacts and economic benefits. In this model, both the constraints and the parameters of the problem are fuzzy, which is determined by the Jimenez method, and the algorithms of NSGA-II and MOPSO have been used to solve the model. Results: The proposed model was solved with two multi-objective genetic algorithms and multi-objective particle swarm optimization, and the necessary comparisons were made between the results. Finally, Pareto's solutions were determined. According to the results, the two algorithms differ in the time criterion that the NSGA-II is superior to MOPSO. Also, there are two different algorithms in the MID standard that MOPSO excels over NSGA-II and does not have any significant superiority over the remaining criteria. Conclusion: Based on the results of the research, simultaneous consideration of economic, environmental and social dimensions and uncertainty in some parameters such as demand and returns lead to improved supply chain performance in terms of profitability and customer satisfaction.

Objective: Due to the fact that the banking industry is mixed with information and communication technologies, extensive developments are expected for this industry and its players in such a way that an ambiguous and complicated future is, specially, expected for the electronic banking industry. Also, analysis of the present research on policy making in electronic banking signifies the lack of a policy making model’ s ability to continuously observe the uncertainties in order to set a long-term plan to preserve the future position of this industry. The aim of the present study is presenting a model for policy making in electronic banking under uncertain conditions. Methods: In order to do so, the issue of policy making in electronic banking has been structured using Soft Systems Methodology. The prescriptive methodology has been applied and the outcomes of this research are in such a way that they consider the targeted uncertainties in policy making. Results: The resultant outcome is a two-circle conceptual model, the main circle of which consists of 5 stages; problem defining ecosystem, scenario presentation ecosystem, control before execution, implementation ecosystem, and control after execution, and the outer circle of which has been designed to implement the necessary controls on the stages is mentioned in the central circle. Conclusion: for structuring the issues of policy making of electronic banking, the implementing of aforementioned model and responsibility of the main players in this area including the central bank, the ministry of economy and finance, banks, software producing companies and payment service providers is described.

Objective: According to the capability of analytical network process (ANP) in analysis of different dependencies and feedback relationships among elements of a decision problem, the current research aims to develop an ANP based method for the benchmark classification problems. Since the essential limitation of ANP is the increase of inconsistency in judgment of decision makers along with increase in problem dimensions, genetic algorithm is used to optimize ANP parameters and improve classification accuracy. Methods: Considering the objective, this study is a developmental research and in term of data analysis, it‘ s a quantitative and mathematical modeling one. In this research, first a multi criteria decision making problem is developed based on ANP and in form of a classification problem and then the unknown parameters of a super matrix were calculated by machine learning methods. Next, the most proper values of these parameters which include thresholds of each class and the applied coefficients in the super matrix are estimated based on sample‘ s benchmarks or data. The following processes have been conducted through a genetic algorithm. Finally, in order to validate the proposed method, its performance is compared to some frequently used classification methods in the reviewed literature. Results: The results indicate the very competitive performance of the proposed method compared to known machine learning methods. Conclusion: Multi-criteria Decision Making Methods (MCDM) are usually used for ranking purposes, however little attention has been paid to their high capabilities. In this paper ANP in combination with genetic algorithm demonstrated an efficient and suitable method in the field of data classification.

Objective: Considering the problem of construction projects performance weaknesses, the aim of this study is to provide a contextual-theoretical model of project performance based on trust in the client and contractor relationship that simultaneously describes the characteristics of trust, the factors affecting it and its outcomes in achieving project performance. Methods: This study was a developmental applied research and has been conducted through a qualitative method. On this basis, using the grounded theory strategy, data from the target community of this research, which included informants of clients and contractors of Tehran urban construction projects, were collected and analyzed. Results: Based on textual analysis of the interviews, the six derived categories of trust characteristics were: Other party’ s ability; Integrity; Benevolence; Having the necessary resources of cooperation; Stability and awareness. Meanwhile, the nine derived categories of factors affecting trust were: Project delivery method quality; Project bid document quality; Project contract quality; Project communication system quality; Other party’ s records reliability; Other party’ s certificates and credentials reliability; Emotional bond depth with other Party; Close environmental factors performance; and Distant environmental factors performance. Finally, the single derived category of the outcomes of trust in achieving an acceptable performance in a project is the quality of the relationship between a client and a contractor during project implementation. Conclusion: The contextual-theoretical model of this study has been extracted by establishing links between derived categories which can contribute to project management literature via generating an understanding of the trust process in the context of urban construction projects, and how it is influenced and it affects the project performance.