Saeed Akbari, Mostafa Khanzadi and Mohammad Reza Gholamian
To address requirements and specifications of construction project, academics need to build a project classification model. In recent years, project success concept, particularly…
Abstract
Purpose
To address requirements and specifications of construction project, academics need to build a project classification model. In recent years, project success concept, particularly on large-scale construction projects, has been a controversial issue, especially in developing countries. Hence, in this paper, after introducing a sustainable success index (SSI), a novel method called “rough set approach” had been adopted to induce decision rules and to classify construction projects. The paper aims to discuss these issues.
Design/methodology/approach
At first, 20 effective success factors and 15 success criteria based on three pillars of sustainability of economy, society and environment had been categorized. The research data used for analysis had been collected from 26 large-scale construction projects in Iran and five other countries. After collecting data collection, observations had been analyzed and 51 decision rules were generated, and the projects were classified. Eventually, in order to evaluate the performance of the generated rules, confusion matrix was applied, and the model was validated.
Findings
The results of the present study show that rough set theory (RST) can be an effective and valuable tool for building expert systems. Practical applications of these results along with limitations and future research are described.
Originality/value
Perhaps for the first time, in the present study, a number of large-scale construction projects are classified based on SSI. Applying RST for building rule-based system and classifying projects in construction project area are novel attempts undertaken in this paper. The rules induced in this study can be applied to develop a sustainable success prediction model in the future studies.
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Morteza Namvar, Mohammad Fathian, Peyman Akhavan and Mohammad Reza Gholamian
This paper aims to empirically explore the effects of intellectual property (IP) on intellectual capital (IC) and firm performance in Iran.
Abstract
Purpose
This paper aims to empirically explore the effects of intellectual property (IP) on intellectual capital (IC) and firm performance in Iran.
Design/methodology/approach
A questionnaire‐oriented survey from senior and top managers in the Iranian computer and electronic industry was utilized for regression analysis.
Findings
The findings indicate that IP significantly influences other dimensions of IC, which consists of human capital (HC), relational capital (RC) and structural capital (SC). The study also provides empirical evidence that gaining firm performance is positively related to these three elements of IC.
Research limitations/implications
First, more advanced statistical techniques with a larger number of respondents could be used to evaluate the regression equations. Second, the companies chosen for the study are from two specific and fairly similar industries in Iran. Thus, the results may not be applicable to other industries in different countries.
Practical implications
With a broad view on IP that considers its creation, protection and utilization too, IP has a central role in knowledge‐based organizations to enhance competitive advantage.
Originality/value
This study builds on and extends the research made by Bollen et al., to link IP and IC to company performance. The paper focuses on the effects of IP on other parts of IC.