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Bigelow, B F, Bilbo, D, Ritter, L, Mathew, M and Elliott, J W (2016) An evaluation of factors for retaining female students in construction management programs. International Journal of Construction Education and Research, 12(01), 18-36.
El-Mashaleh, M S, Hyari, K H, Bdour, A N and Rababeh, S M (2016) A multi-attribute decision-making model for construction enterprise resource planning system selection. International Journal of Construction Education and Research, 12(01), 66-79.
- Type: Journal Article
- Keywords: enterprise resource planning; information technology; decision support system; data envelopment analysis; decision making; construction
- ISBN/ISSN: 1557-8771
- URL: https://doi.org/10.1080/15578771.2015.1015755
- Abstract:
Enterprise resource planning (ERP) systems are increasingly becoming essential business technologies. Selection of the optimal ERP system among numerous alternatives is regarded as a major challenge for the decision-maker. This choice is complicated by multiple attributes that the decision-maker needs to consider when evaluating different ERP options. The purpose of this article is to propose a multi-attribute decision-making model for ERP system selection based on data envelopment analysis (DEA). The strengths of the proposed DEA model include the input-output framework, which allows decision-makers to incorporate multiple attributes when evaluating different ERP options. These attributes are not required to be congruent. They can be measured by such criteria as monetary sums, time, or subjective score. Additionally, DEA can accommodate a large number of options (i.e., ERP systems) and variables (i.e., attributes). The proposed approach was utilized by a construction contractor to select the optimal ERP option out of eleven alternatives. During the evaluation process, the decision-maker incorporated six attributes to make the decision. These considered attributes are total cost, implementation schedule, functionality, user friendliness, customization capability, and service and support quality. Sensitivity analysis proved that the proposed model is stable and robust.; Enterprise resource planning (ERP) systems are increasingly becoming essential business technologies. Selection of the optimal ERP system among numerous alternatives is regarded as a major challenge for the decision-maker. This choice is complicated by multiple attributes that the decision-maker needs to consider when evaluating different ERP options. The purpose of this article is to propose a multi-attribute decision-making model for ERP system selection based on data envelopment analysis (DEA). The strengths of the proposed DEA model include the input-output framework, which allows decision-makers to incorporate multiple attributes when evaluating different ERP options. These attributes are not required to be congruent. They can be measured by such criteria as monetary sums, time, or subjective score. Additionally, DEA can accommodate a large number of options (i.e., ERP systems) and variables (i.e., attributes). The proposed approach was utilized by a construction contractor to select the optimal ERP option out of eleven alternatives. During the evaluation process, the decision-maker incorporated six attributes to make the decision. These considered attributes are total cost, implementation schedule, functionality, user friendliness, customization capability, and service and support quality. Sensitivity analysis proved that the proposed model is stable and robust.;
Elliott, J W, Thevenin, M K and Lopez del Puerto, C (2016) Role of gender and industry experience in construction management student self-efficacy, motivation, and planned behavior. International Journal of Construction Education and Research, 12(01), 3-17.
Glick, S, Folkestad, J and Banning, J (2016) Construction management dissertation abstracts: A bounded qualitative meta-study. International Journal of Construction Education and Research, 12(01), 54-65.
Wao, J O, Ries, R, Flood, I, Lavy, S and Ozbek, M E (2016) Relationship between admission gre scores and graduation gpa scores of construction management graduate students. International Journal of Construction Education and Research, 12(01), 37-53.