Mahdi Salehi and Nahid Mohammadi
Investors’ decision-making is based on quantitative and rational analyses, and some other factors deriving from the market expectations are also contribute significantly on the…
Abstract
Purpose
Investors’ decision-making is based on quantitative and rational analyses, and some other factors deriving from the market expectations are also contribute significantly on the shareholders’ response to market interactions. The present study aims to discover whether emotional intelligence and thinking style have a significant effect on the quality of investors’ decision-making.
Design/methodology/approach
To gather data, a questionnaire was designed and developed and distributed among the participants during the first half of 2015. Moreover, the SAS software and the log-linear method was used to test the hypotheses.
Findings
The results show that emotional intelligence, thinking style and quality of decision-making are not dependent and emotional intelligence and thinking style are not interdependent on each other.
Originality/value
The current study used a unique model to test the hypotheses, and the results may be different from those of previous studies.
Details
Keywords
Mina Mikhail, Mohammed El-Beheiry and Nahid Afia
The purpose of this paper is to develop a decision tool that enables supply chain (SC) architects to design resilient SC networks (SCNs). Two resilience design determinants are…
Abstract
Purpose
The purpose of this paper is to develop a decision tool that enables supply chain (SC) architects to design resilient SC networks (SCNs). Two resilience design determinants are considered: SC density and node criticality. The effect of considering these determinants on network structures is highlighted based on the ability to resist disruptions and how SC performance is affected.
Design/methodology/approach
A mixed-integer non-linear programming model is proposed as a proactive strategy to develop resilient structures; design determinants are formulated and considered as constraints. An upper limit is set for each determinant, and resistance capacity and performance of the developed structures are evaluated. These upper limits are then changed until SC performance stabilizes in case of no disruption.
Findings
Resilient SCN structures are achieved at relatively low design determinants levels on the expense of profit and without experiencing shortage in case of no disruption. This reduction in profit can be minimized on setting counter values for the two determinants; relatively higher SC density with lower node criticality or vice versa. At very low SC density levels, the design model will reduce the number of open facilities largely leading to only one facility open at each echelon; therefore, shortage occurs and vulnerability to disruption increases. On the other hand, at high determinants levels, SC vulnerability also increases as a result of having more geographically clustered structures with higher inbound and outbound flows for each facility.
Originality/value
In this paper, a novel proactive decision tool is adopted to design resilient SCNs. Previous literature used metrics for SC density and node criticality to assess resilience; in this research, determinants are incorporated directly as constraints in the design model. Results give insight to SC architects on how to set determinant values to reach resilient structures with minimum performance loss in case of no disruption.
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Keywords
Nahid Dorostkar-Ahmadi, Mohsen Shafiei Nikabadi and Saman babaie-kafaki
The success of any organization in a knowledge-based economy depends on effective knowledge transferring and then proper use of the transferred knowledge. As is known, optimizing…
Abstract
Purpose
The success of any organization in a knowledge-based economy depends on effective knowledge transferring and then proper use of the transferred knowledge. As is known, optimizing the knowledge transferring costs in a product portfolio plays an important role in improving productivity, competitive advantage and profitability of any organization. Therefore, this paper aims to determine an optimal product portfolio by minimizing the konlwedge transferring costs.
Design/methodology/approach
Here, a fuzzy binary linear programming model is used to select an optimal product portfolio. The model is capable of considering the knowledge transferring costs while taking into account the human-hours constraints for each product by a fuzzy approach. Using fuzzy ranking functions, a reasonable solution of the model can be achieved by classical or metaheuristic algorithms.
Findings
Numerical experiments indicate that the proposed fuzzy model is practically effective.
Originality/value
The contributions of this work essentially consist of considering knowledge transferring costs in selecting an optimal product portfolio and using the fuzzy data which make the model more realistic.
Details
Keywords
Ali Rahimian, Keivan Sadeghzadeh, Saeed Reza Mohandes, Igor Martek, Patrick Manu, Maxwell Fordjour Antwi-Afari, Sajjad Mirvalad and Ibrahim Odeh
Following the job demands-resources theory, this study investigates the role of female managers in enhancing employee well-being in terms of psychological health via workplace…
Abstract
Purpose
Following the job demands-resources theory, this study investigates the role of female managers in enhancing employee well-being in terms of psychological health via workplace resources.
Design/methodology/approach
To accomplish this objective, we conducted a comprehensive literature review to identify key IPS. Subsequently, a fuzzy-based algorithm was employed to prioritize these skills. Following this, we developed an algorithm based on Extreme Gradient Boosting (XGBoost) to predict the quality of workers’ IC. The efficacy of the XGBoost model was assessed by applying it to three real-life construction projects.
Findings
Upon application of the model to the case studies, we made the following conclusions: (1) “Leadership Style,” “Listening,” “Team Building” and “Clarifying Expectations” emerged as significant skills and (2) the model accurately predicted workers’ IC quality in over 78% of the cases. This algorithm has the potential to preempt interpersonal conflicts, enhancing job-site productivity, team development and human resources management. Furthermore, it can guide construction managers in designing IPS training programs.
Originality/value
This study contributes to the existing knowledge by addressing the crucial connection between IPS and IC quality in construction projects. Additionally, our novel approach, integrating fuzzy logic and XGBoost, provides a valuable tool for IC prediction. By identifying significant IPS and offering predictive insights, this research facilitates improved communication and collaboration in the construction industry, ultimately enhancing project outcomes.