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Item type:Publication, Analysis of factors affecting project communications with a hybrid DEMATEL-ISM approach (A case study in Iran)(Elsevier, 2020-08-01)Project management; Communications management; Fuzzy DEMATEL; Interpretive structural modeling (ISM); MICMAC Analysis; Construction engineering; Human resource management; Industry management; Business management; Behavioral psychology; Business One of the main factors in the success of projects is communications management and proper and timely distribution of information among all internal and external project stakeholders. Despite of emphasizing on the importance of project communications in the literature, there are few studies identifying factors influencing project communications. This research aims to address this shortcoming by identifying and determining sequences and relationships factors affecting project communications and their clustering. The informed communication strategy allows managers to structure the information flow in a better and more controlled manner and to avoid the costs caused by lack of effective and timely communication. The present study is conducted to help clarify the views of the organization's managers and project managers on project communications, and to identify factors affecting it and how they effectively communicate to successfully accomplish the projects. First a number of factors influencing project communications are identified on the basis of previous studies and interviews with experts and project managers working in oil, gas and power plant construction megaprojects in Iran. Then, these factors are analyzed by using the combination of fuzzy DEMATEL and Interpretive Structural Modeling (ISM) techniques. The relationships and sequence between the indicators are determined so that it can be effective in project communications planning and project success through providing an insight for senior managers and project managers. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A novel prediction model for educational planning of human resources with data mining approach: a national tax administration case study(Springer Science+Business Media, 2021-08-13)Human resources training is considered an effective solution in empowering human resources. Organizations try to have effective educational planning for this precious resource by identifying shortcomings through a need assessment. This study provides a model based on organizational data analysis to achieve a unique and appropriate training planning for each staff. Therefore, job performance, organizational promotion and lay-off have become the basis for staff training planning. For this purpose, the tax assessor’s information was investigated. Then, the CRISP-DM methodology was selected, and the project was implemented. Furthermore, a decision tree model was selected to extract unknown rules and patterns in the educational decision-making staff; the neural network model was selected as the predictive model to predict the target variables. The results revealed the decision tree for predicting job performance variables and organizational promotion status, and the neural network model was more effective in predicting service lay-off variables.