Printer Friendly

Case study methodology of DSS development for BIM software selection in construction industry.


The current architectural, Engineering and Construction (AEC) industry building has been challenged by the industry lead report (i.e. Egan and Latham Reports) to transform from the traditional design practice towards integrated approach in order to enhance the construction project productivity. Accordingly, a few researchers [14,6] highlighted that the construction and design process cannot be avoided to implement information, communication and technology (ICT) tools or approach such as Building Information Modeling (BIM) particularly in a project. Better project outcomes, improve communication and reducing the time needed for the whole construction process are the main advantages of BIM technology [14,5,6,7,21]. As a result, numerous of BIM software available on market in order to caters the demand of BIM need in construction industry. For example, Autodesk Revit Architechture, Graphisoft ArchiCAD, Softtech Spirit, Bentley Hevacomp, Tekla Structures, Autodesk Revit Structure, Graytec Advance Design, StrutureSoft Metal Wood Framer and others. Each of these software offers a different function, features and cost. In addition, the adoption of BIM required a high investment not only on software and hardware, but also on training expenses [17,19]. Therefore the selection of BIM software is a vital process in adoption of BIM system. Selecting of a wrong technology would influence the company investment and also affect the project performance [16]. Thus, it is desire to develop a Decision Support System (DSS) to enhance the selection of BIM software selection. To demonstrate this objective a case study methodology will be adopted. The design, implement and evaluation of the proposed DSS will be depicted through case study.

Considering the development of DSS for enhancing BIM software selection, this paper will discusses the importance of case study research method in the development of DSS for BIM software selection.

Case study methodology allows researchers to conduct an intensive investigation on contemporary real-life phenomenon and also provide a better insight into detail behavior of research problem [22,24]. Case study method is an appropriate research method for exploratory phase, nevertheless survey and histories methods are suitable for descriptive phase [22]. In addition, case study also acts as a guide for the researchers to explain the complexity of real life phenomenon [24].

Yin [22] has provided case study protocol as a guide for researchers. Figure below illustrated the protocol of case study method:

Fig. 1: A case study protocol [22].

Design case study

Conduct case study

Analyze the case study evident

Case study report

Case study design can be divided into two; (1) single case study and (2) multiple case study. Each of them has different pros and cons depending on purpose of study. Next is conducting the case study. In this stage, it more focus on preparation for data collection process particularly "how the user collects data", and "what type of instrument will be use" and "what source of data collection". Then, analyze case study evident. In this stage, it involves method of analysis. Data analysis in case study involve examining, categorizing, tabulating or the other evident to address propose of a study [22]. Lastly is case study report, it is more on to develop conclusion, recommendation and implication of the study.

From literature, a case study method has been proven beneficial in numerous fields as a research method. Our focus will be on software selection problem which is BIM software selection in construction industry. According to literature in software selection substantial work of case study in software selection has been done in past. Table 1 below illustrated some of previous study that utilized case study in software selection problem.

For the purpose of investigate and validate criteria for BIM software selection in real life phenomenon, the utilization of case study is the most appropriate. This is due to the characteristic of case study that also enable researchers to deal with numerous of evident, for example document, software manual, interview and observation [22]. For example, researcher would be able to investigate the real life of BIM software selection criteria from BIM expert through an interview. A part from that, the case study designed most important for design, implement and evaluation of DSS for BIM software selection.

The development of DSS for BIM software selection is closely related to the case study method. The design of this DSS would totally according to the collection data in case study. For instance, this DSS will be developed based on real criteria of BIM software selection that obtain from interview among the BIM expert during the case study at UTHM Multiple purpose Hall. After the DSS has been developed, evaluations of the DSS need to be conduct among the users through the case study. An Evaluation process is significant to test the usability and effectiveness of the DSS in a real life [1,2,3,8]. From literature in DSS, a substantial work of DSS evaluation criteria has been performed in past. Table 2 below outlines some DSS evaluation criteria from the past study.

However, most of the research on construction literature has been neglected the user evaluation toward the system [10,20].

Research framework:

In order to address the objective of study, a framework has been developed. Figure 2 below illustrated the research framework for the development of BIM software selection.

This framework will be dividing into four major phases:

* Phase One: The Literature review and Data collection

* Phase Two: Conceptual decision model development

* Phase Three: Decision Support System development

* Phases Four: An Evaluation of DSS and conclusion

Literature review and data collection:

In this phase, the problem is defined and the scope as well as the boundaries of the study is indentified. Then, an extensive literature review on construction project management has been conducted which is lead to the gap of this study. Most of the literatures in construction were mostly focusing on the procedure of BIM adoption, the beneficial of BIM, and barriers of BIM. However, there is limited study on the significant of BIM software selection. The significant of decision aid in BIM software selection has been discussed in previous section. Thus, this study attempt to develop a DSS for enhances the BIM software selection process.

In order to address this study objective, a real case study will be deploying a real life construction project at one of the pioneer project at Malaysia. Through, this case study, the data collection activity will be conduct. For this study, data will be collect through documented analysis and semi interview from BIM expertise. The adoption of case study methodology in this study will enable us to conduct a dept investigation of BIM software selection in real life situation. For example, the real attribute of BIM software selection in Malaysia.

Conceptual decision model and DSS development:

In this phase, it is more on implementation of data collection output into the development of decision model for BIM software selection. For example, the result of real criteria in BIM software selection will be adopted in decision model. The output of data collection is significant in order to increase the usability and validity of the decision model.

DSS evaluation:

After the development of DSS, an evaluation of DSS will be conduct among the users through the case study. From DSS literature, an evaluation of DSS is significant in order to measure the effectiveness of DSS in real life situation. A questionnaire that contains evaluation criteria of DSS will be distributed among the users. See the example of questionnaire in appendix A.

Conclusion and Finding:

After all the activity above been conducted, it would lead to the conclusion and findings of this study.

Discussion and Conclusions:

The adoption of BIM has been proven beneficial to the AEC industry in term of increase the quality of construction project, encourage collaboration and saving times. Due to this situation, there are numerous of BIM software available in market. In addition, the adoption of BIM is not low-cost; it required a high investment in term of software, hardware and training expenses. Thus, there is a need of decision aid in selection of BIM software selection. Thus this study attempt to develop DSS for enhances the BIM software selection process.

This paper introduces research framework thorough case study methodology in order to develop a DSS for BIM software selection. A real project that utilized BIM will be adopted as case study for this study. This is due to the characteristic of case study methodology, that suite the purpose of this study. In BIM software selection, a case study methodology is significant in order to develop a DSS and DSS evaluation (measurement of validity and usability). Once a set of criteria for BIM software selection has been indentify from BIM expert through case study, it will be use in the development of decision model and the propose DSS. This approach is anticipated to increase the effectiveness and validity of the DSS development for BIM software selection.


The authors gratefully acknowledge the support by the Ministry of Education Malaysia for providing the funding under Research Acculturation Grant Scheme (RAGS). Many of the parts of this paper were originally written in the parts of student's postgraduate thesis. We also thank the contribution by other member in our Construction Innovation Research Cluster from Universiti Utara Malaysia (UUM).


[1.] Bharati, P., A. Chaudhury, 2004. An empirical investigation of decision-making satisfaction in web-based decision support systems. Decision Support Systems, 37(2): 187-197. doi:10.1016/S0167-9236(03)00006-X.

[2.] Bidgoli, H., 1989. DSS products evaluation: An intergrated framework. Journal of System Management, 40(11): 27-34.

[3.] Borenstein, D., 1998. Towards a practical method to validate decision support systems. Decision Support Systems, 23(3): 227-239. doi:10.1016/S0167-9236(98)00046-3.

[4.] Cebeci, U., 2009. Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Systems with Applications, 36(5): 8900-8909. doi:10.1016/j.eswa.2008.11.046.

[5.] Chelson, D.E., 2010. The effect of building information modelling on construction site productivity. University of Maryand.

[6.] Eastman, C., P. Teicholz, R. Sacks, K. Liston, 2011. BIM Handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors. Hoboken, NJ, USA: John Wiley & Sons, Inc.

[7.] Hergunsel, M.F., 2011. Benefit of Building Information Modelling for construction managers and BIM based scheduling. Worcester Polytechnic Institute.

[8.] Hung, S.Y., Y.C. Ku, T.P. Liang, C.J. Lee, 2007. Regret avoidance as a measure of DSS success: An exploratory study. Decision Support Systems, 42(4): 2093-2106. doi:10.1016/j.dss.2006.05.006.

[9.] Kontio, J., 1996. A case study in applying a systematic method for COTS selection. Proceedings of IEEE 18th International Conference on Software Engineering, 201-209. doi:10.1109/ICSE.1996.493416

[10.] Kumaraswamy, M.M., S.M. Dissanayaka, 2001. Developing a decision support system for building project procurement. Building and Environment, 36(3): 337-349. doi:10.1016/S0360-1323(00)00011-1.

[11.] Lai, V.S., R.P. Trueblood, B.K. Wong, 1999. Software selection: a case study of the application of the analytical hierarchical process to the selection of a multimedia authoring system. Information & Management, 36(4): 221-232. doi:10.1016/S0378-7206(99)00021-X.

[12.] Lu, H., H. Yu, S.S.K. Lu, 2001. The effects of cognitive style and model type on DSS acceptance : An empirical study, 131.

[13.] Mulebeke, J.A.W., L. Zheng, 2006. Analytical network process for software selection in product development: A case study. Journal of Engineering and Technology Management, 23(4): 337-352. doi:10.1016/j.jengtecman.2006.08.004.

[14.] Nawi, M.N.M., A. Lee, M.N.A. Azman and K.A.M. Kamar, "Fragmentation Issue in Malaysian Industrialised Building System (IBS) Projects Critical Success Factors for Improving Team Integration in IBS Construction Projects," Journal of Engineering Science and Technology, 9 (1): 97-106.

[15.] Nawi, M.N.M., A.T. Haron, M.F. Omar and S.H. Ibrahim, 2013. Building Information Modelling (BIM): An integrated Practice in Malaysian Industrialised Building System (IBS) Perspective. Proceeding of The 3rd International Building Control Conference, 230-237.

[16.] Omar, M.F., M.N.M. Nawi, A.T. Nursal, 2013. Aiding Decisions for Selecting Appropriate BIM Software in Construction Industry. Proceeding of The 3rd International Building Control Conference, 46-51.

[17.] Olatunji, O.A., 2011. Modelling the costs of corporate implementation of building information modelling. Journal of Financial Management of Property and Construction, 16(3): 211-231. doi:10.1108/13664381111179206.

[18.] Otamendi, J., J.M. Pastor, A. Garci'a, 2008. Selection of the simulation software for the management of the operations at an international airport. Simulation Modelling Practice and Theory, 16(8): 1103-1112. doi:10.1016/j.simpat.2008.04.022.

[19.] Pena, G., 2011. The evaluation of trainning needs for Building Information Modelling. University of Texas.

[20.] Shen, Y.C., D.A. Grivas, 1996. Decision-Support System For Infrastructure Preservation, 40-49.

[21.] Wong, K., Q. Fan, 2013. Building information modelling (BIM) for sustainable building design. Facilities, 31(3): 138-157. doi:10.1108/02632771311299412.

[22.] Yin, R.K., 2003. Robert K. Yin-Case Study Research_Design and Methods, Third Edition, Applied Social Research Methods Series, 5.pdf.

[23.] Zahrizan, Z., N.M. Ali, A.T. Haron, A. Marshall-ponting and Z. Abd, 2013. "Exploring the adoption of Building Information Modelling (BIM) in the Malaysian Construction Industry : Qualitative approach," pp: 384-395.

[24.] Zainal, Z., 2007. Case study as a research method.

[25.] Ziaee, M., M. Fathian, S.J. Sadjadi, 2006. A modular approach to ERP system selection: A case study. Information Management & Computer Security, 14(5): 485-495. doi:10.1108/09685220610717772.

(1) Ahmad Taufik Nursal, (2) Mohd Faizal Omar Mohd, (3) Mohd Nasrun Mohd Nawi

(1,2) Department of Decision Science, School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

(3) School of Technology Management and Logistics, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

Received: 23 January 2014 ; Received: 19 April 2014; Accepted: 26 April 2014; Available online: 15 May 2014

Published Online 2014 May 15.

Corresponding Author: Ahmad Taufik Nursal, Department of Decision Science, School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.

Table 1: Application of Case study method in software selection.

Problem Description                 Authors

Selection of multimedia             (Lai, Trueblood, & Wong, 1999)
authorizing system (MAS)

Selection of ERP systems in         (Cebeci, 2009)
Textile industry

Selection of simulation software    (Otamendi, Pastor, & Garci'a,

A modular approach of to ERP        (Ziaee, Fathian, & Sadjadi, 2006)
system selection

Systematic method for Commercial-   (Kontio, 1996)
Off-The-Shelf (COTS)

Software selection in product       (Mulebeke & Zheng, 2006)

Table 2: DSS evaluation criteria.

Authors                       Criteria

(Bharati & Chaudhury, 2004)   i. System Quality:

                                * System reliability
                                * Convenient to access
                                * System ease for use
                                * System flexibility

                              ii. Information quality:

                                * Information accuracy
                                * Information completeness
                                * Information relevant
                                * Information content needs
                                * Information timeliness

                              iii. Information presentation:

                                * Presentation Graphics
                                * Presentation color
                                * Presentation style
                                * Navigationally efficient

                              iv. Decision Making Satisfaction

                                * Decision Confident
                                * Decision Effectiveness

(Lu, Yu, & Lu, 2001)          i.   Perceive ease of use
                              ii.  Perceive usefulness
                              ii.  Preference
                              v.   Willingnes

                              i.   Decision performance
(Hung et al., 2007)           i.   User satisfaction
                              ii.  User regret

                              i.   Graphical modeling
                              i.   Integration of modules
                              ii.  Presentation result
(Borenstein, 1998)            iv.  Manufacturing terminology
                              v.   Logical description
                              vi.  Global Efficiency
                              vii. Program consistency
COPYRIGHT 2014 American-Eurasian Network for Scientific Information
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2014 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:Research Article
Author:Nursal, Ahmad Taufik; Omar, Faizal; Nawi, Nasrun
Publication:American-Eurasian Journal of Sustainable Agriculture
Article Type:Report
Geographic Code:9MALA
Date:Mar 1, 2014
Previous Article:Effect of nutrient solution and foliar spray on the growth and tubers content of N,P,K (Riviera cv.) grown hydroponically.
Next Article:Integrated business model for improving integration IBS project team in Malaysian construction industry.

Terms of use | Privacy policy | Copyright © 2020 Farlex, Inc. | Feedback | For webmasters