Human capital in urban management
S.M. Mirbagheri; A. Rafiei Atani; M. Parsanejad
Abstract
BACKGROUND AND OBJECTIVES: Collective decision-making can increase the probability of reaching the correct decision. In Collective decision-making, information, experience, and knowledge are shared, and managers can use the wisdom of their employees with this method. In addition, in Collective decision-making, ...
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BACKGROUND AND OBJECTIVES: Collective decision-making can increase the probability of reaching the correct decision. In Collective decision-making, information, experience, and knowledge are shared, and managers can use the wisdom of their employees with this method. In addition, in Collective decision-making, learning and ideation take place, and employees express their opinions freely and reach a common decision with the help of each other. METHODS: In this study, the concepts related to Collective decision-making are explained using the research background. Then, by using the grounded theory method, the most important questions related to why and how Collective decision-making are answered. To get the opinions of organizational and academic experts in this field, a semi-structured interview was conducted with 54 people who were selected by purposeful sampling. After collecting the data through interviews, the components are coded in an open, axial, and selective. FINDINGS: Through coding, 26 concepts were obtained which were later classified into 5 categories: causal conditions, contextual conditions, intervening conditions, central phenomenon, strategies, and consequences. The findings of this study provide a comprehensive model for the central phenomenon of Collective decision-making.CONCLUSION: The results show that collection alliance, increased awareness and knowledge, growth, and development of members, increased wisdom and collective intelligence, increased members' commitment, increased quality of decision-making, and increased justice are the most important consequences of Collective decision-making. This study is important because it broadens the perspective of managers, and provides a deeper understanding of the nature of Collective decision-making in the organization.
Human capital in urban management
A. Shahrabi Farahani; K. Teymournejad
Abstract
BACKGROUND AND OBJECTIVES: Career management determines the direction of staff's movement in the organizational hierarchy and directs them to perfection. The Objective of this study was to design a model for career management of Tehran Municipality employees. METHODS: The research method was Qualitative-Quantitative ...
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BACKGROUND AND OBJECTIVES: Career management determines the direction of staff's movement in the organizational hierarchy and directs them to perfection. The Objective of this study was to design a model for career management of Tehran Municipality employees. METHODS: The research method was Qualitative-Quantitative and the statistical population of the study was 11 experts in the qualitative section and 660 employees of the organization in the quantitative section. The data collection tool was semi-structured interviews in qualitative section and in quantitative part of the questionnaire was researcher-made. Using the Grounded BACKGROUND AND OBJECTIVES: Career management determines the direction of staff's movement in the organizational hierarchy and directs them to perfection. The Objective of this study was to design a model for career management of Tehran Municipality employees. METHODS: The research method was Qualitative-Quantitative and the statistical population of the study was 11 experts in the qualitative section and 660 employees of the organization in the quantitative section. The data collection tool was semi-structured interviews in qualitative section and in quantitative part of the questionnaire was researcher-made. Using the Grounded Theory and Theoretical Coding, the initial model was presented and the final model of the research was presented using Delphi technique and obtaining the opinions of experts. Exploratory Factor Analysis and Structural Equation Modeling were used to validate the model. FINDING: The final research model was based on 6 categories, 13 factors and 36 concepts: Causal Conditions included individual and organizational factors, Context including hardware and software capabilities, Intervening Conditions including environmental, behavioral and structural barriers, and Strategies including development and current strategies. Consequences of model implementation were classified into three categories: employees, organization and citizens. Among the 36 concepts identified, the highest factor load was related to the concept of job enrichment with a value of 0.882 and the lowest factor load was related to the concept of productivity with a value of 0.712. This model was investigated among the employees and the results of validation confirmed the model. CONCLUSION: By implementing career management, the field of growth and prosperity of employees in the organization is provided and improves the productivity of the organization and customer satisfaction.
M. Shirafkanlamso; P. Mohammadzadeh; D. Behboudi
Abstract
Optimal housing selection is one of the most important challenges in housing demand, which most people, especially housing investors, are facing. Although there is an overall agreement on the importance of the budget role on choosing the house, the model that uniquely measures the role and impact of ...
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Optimal housing selection is one of the most important challenges in housing demand, which most people, especially housing investors, are facing. Although there is an overall agreement on the importance of the budget role on choosing the house, the model that uniquely measures the role and impact of all the factors of investment demand for housing has not been presented and no clear explanation is made. Considering the central role of budget constraints, behavioral and control factors in investment demand, this research carried out in the framework of the qualitative (method of data research method) and quantitative (polynomial logistic method) approach to explaining the mental pattern of investment demand for housing in Tabriz. The data were obtained from semi-structured interviews of 12 experts familiar with the issues of housing capital and distributing a questionnaire among 720 households in Tabriz. The result revealed 250 code, 20 concepts, and 4 categories, based on which the qualitative research model was designed. Also, the results of estimating the logit model using the STATA software indicate that important factors such as welfare and comfort aspects with a coefficient of 0.8292, access to urban services with a coefficient of 0.2287 and proximity to relatives with the coefficient of 0.2199 have had a positive and significant effect on the capital investment demand. But the close proximity of the household header with the coefficient of -0.2014 has a negative impact on the choice of housing capital.