A method for analyzing the effect of implementing an enterprise system based on the complexity of activities

    Chijoo Lee Affiliation
    ; Chiheyon Lee Affiliation
    ; Eul-Bum Lee Affiliation


This paper presents a method for analyzing the effect of implementing an enterprise system (ES) in the construction industry during the ES introduction and planning stages. The effect is a reduction in employees’ work time. The proposed method is based on the 1) level of digitalized and automated activities, the 2) complexity of the activities, and the 3) complexity of the processes in the workflow. The method was applied at a construction company that has no enterprise resource planning (ERP), and the method’s accuracy was evaluated by information technology consultants who have performed planning, construction, and operation in relation to ERP. The result shows that the effect of management business was the largest; most of this effect was on data management and review. After users became familiar with ERP, the reduction in data input time increased. The analysis method takes less time and costs less than using surveys to measure the work time and satisfaction of ES users. It can also identify processes in which the effect increases or decreases, thereby guiding any modifications of the ES before it is introduced.

Keyword : working time, workflow, activity, process, automation and digitalization

How to Cite
Lee, C., Lee, C., & Lee, E.-B. (2018). A method for analyzing the effect of implementing an enterprise system based on the complexity of activities. Journal of Civil Engineering and Management, 24(7), 526-536.
Published in Issue
Nov 13, 2018
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Abdul-Rahman, H.; Wang, C.; Lee, Y. L. 2013. Design and pilot run of fuzzy synthetic model (FSM) for risk evaluation in civil engineering, Journal of Civil Engineering and Management 19(2): 217–238.

Agrell, P. J.; Wikner, J. 1996. A coherent methodology for productivity analysis employing integrated partial efficiency, International Journal of Production Economics 46–47: 401–411.

Ahmad, M. M.; Pinedo Cuenca, R. 2013. Critical success factors for ERP implementation in SMEs, Robotics and Computer-Integrated Manufacturing 29: 104–111.

Anderson, M.; Banker, R. D.; Menon, N. M.; Romero, J. A. 2011. Implementing enterprise resource planning systems: organizational performance and the duration of the implementation, Information Technology and Management 12: 197–212.

Badescu, M.; Garcés-Ayerbe, C. 2009. The impact of information technologies on firm productivity: Empirical evidence from Spain, Technovation 29: 122–129.

Chang, S.-I.; Yen, D. C.; Ng, C. S.-P.; Chang, I.-C.; Yu, S.-Y. 2011. An ERP system performance assessment model development based on the balanced scorecard approach, Information Systems Frontiers 13: 429–450.

Chang, T.-H.; Hsu, S.-C.; Wang, T.-C.; Wu, C.-Y. 2012. Measuring the success possibility of implementing ERP by utilizing the Incomplete Linguistic Preference Relations, Applied Soft Computing 12: 1582–1591.

Chen, Y.; Liang, L.; Yang, F.; Zhu, J. 2006. Evaluation of information technology investment: a data envelopment analysis approach, Computers & Operations Research 33: 1368–1379.

Chou, S.-W.; Chang, Y.-C. 2008. The implementation factors that influence the ERP (enterprise resource planning) benefits, Decision Support Systems 46: 149–157.

Ducq, Y.; Chen, D.; Doumeingts, G. 2012. A contribution of system theory to sustainable enterprise interoperability science base, Computers in Industry 63: 844–857.

Galy, E.; Sauceda, M. J. 2014. Post-implementation practices of ERP systems and their relationship to financial performance, Information & Management 51: 310–319.

Ha, Y. M.; Ahn, H. J. 2014. Factors affecting the performance of Enterprise Resource Planning (ERP) systems in the post-implementation stage, Behaviour & Information Technology 33: 1065–1081.

Hadidi, L.; Assaf, S.; Alkhiami, A. 2017. A systematic approach for ERP implementation in the construction industry, Journal of Civil Engineering and Management 23(5): 594–603.

Hakim, A.; Hakim, H. 2010. A practical model on controlling the ERP implementation risks, Information Systems 35: 204–214.

Hannula, M. 2002. Total productivity measurement based on partial productivity ratios, International Journal of Production Economics 78: 57–67.

Holsapple, C.; Sena, M.; Wagner, W. 2017. The perceived success of ERP systems for decision support, Information Technology and Management.

Holsapple, C. W.; Sena, M. P. 2001. Beyond transactions: the decision support benefits of ERP systems, Journal of Decision Systems 10: 65–85.

Hsu, P.-F.; Yen, H. R.; Chung, J.-C. 2015. Assessing ERP post-implementation success at the individual level: Revisiting the role of service quality, Information & Management 52: 925–942.

Hu, Q.; Quan, J. J. 2005. Evaluating the impact of IT investments on productivity: a causal analysis at industry level, International Journal of Information Management 25: 39–53.

Ibrahim, S. H.; Duraisamy, S.; Sridevi, U. K. 2018. Flexible and reliable ERP project customization framework to improve user satisfaction level, Cluster Computing.

Lee, C.; Lee, C. 2017. Method to reduce the gap between construction and IT companies to improve suitability before selecting an enterprise system, Computers in Industry 85: 23–30.

Lemonakis, C.; Sariannidis, N.; Garefalakis, A.; Adamou, A. 2018. Visualizing operational effects of ERP systems through graphical representations: current trends and perspectives, Annals of Operations Research.

Li, H.-J.; Chang, S.-I.; Yen, D. C. 2017. Investigating CSFs for the life cycle of ERP system from the perspective of IT governance, Computer Standards & Interfaces 50: 269–279.

Livermore, C. R.; Rippa, P. 2011. ERP implementation: A cross-cultural perspective, Journal of Global Information Technology Management 14: 5–26.

Lu, M.; Wong, L.-C. 2007. Comparison of two simulation methodologies in modeling construction systems: Manufacturing-oriented PROMODEL vs. construction-oriented SDESA, Automation in Construction 16: 86–95.

Lu, Z.; Jinghua, H. 2012. The moderating factors in the relationship between ERP investments and firm performance, Journal of Computer Information Systems 53: 75–84.

Mamoghli, S.; Goepp, V.; Botta-Genoulaz, V. 2015. An operational “Risk Factor Driven” approach for the mitigation and monitoring of the “Misalignment Risk” in enterprise resource planning projects, Computers in Industry 70: 1–12.

Nagpal, S.; Kumar, A.; Khatri, S. K. 2017. Modeling interrelationships between CSF in ERP implementations: total ISM and MICMAC approach, International Journal of System Assurance Engineering and Management 8: 782–798.

National IT Industry Promotion Agency. 2008–2016. Yearbook of information society statistics. Ministry of Public Administration and Security.

Ngai, E. W. T.; Law, C. C. H.; Wat, F. K. T. 2008. Examining the critical success factors in the adoption of enterprise resource planning, Computers in Industry 59: 548–564.

Nicolaou, A. I.; Bhattacharya, S. 2006. Organizational performance effects of ERP systems usage: The impact of post-implementation changes, International Journal of Accounting Information Systems 7: 18–35.

Nwankpa, J. K. 2015. ERP system usage and benefit: A model of antecedents and outcomes, Computers in Human Behavior 45: 335–344.

Parhizkar, M.; Comuzzi, M. 2017. Impact analysis of ERP post-implementation modifications: Design, tool support and evaluation, Computers in Industry 84: 25–38.

Parthasarathy, S.; Daneva, M. 2016. An approach to estimation of degree of customization for ERP projects using prioritized requirements, Journal of Systems and Software 117: 471–487.

Parthasarathy, S.; Sharma, S. 2016. Efficiency analysis of ERP packages – A customization perspective, Computers in Industry 82: 19–27.

Parthasarathy, S.; Sharma, S. 2017. Impact of customization over software quality in ERP projects: an empirical study, Software Quality Journal 25: 581–598.

Ram, J.; Corkindale, D.; Wu, M.-L. 2013. Implementation critical success factors (CSFs) for ERP: Do they contribute to implementation success and post-implementation performance?, International Journal of Production Economics 144: 157–174.

Ranjan, S.; Jha, V. K.; Pal, P. 2017. Application of emerging technologies in ERP implementation in Indian manufacturing enterprises: an exploratory analysis of strategic benefits, The International Journal of Advanced Manufacturing Technology 88: 369–380.

Riley, M. J.; Clare-Brown, D. 2001. Comparison of cultures in construction and manufacturing industries, Journal of Management in Engineering 17: 149–158.

Ruivo, P.; Oliveira, T.; Neto, M. 2014. Examine ERP post-implementation stages of use and value: Empirical evidence from Portuguese SMEs, International Journal of Accounting Information Systems 15: 166–184.

Saaty, T. L. 1990. How to make a decision: The analytic hierarchy process, European Journal of Operational Research 48: 9–26.

Shao, B. B. M.; Lin, W. T. 2002. Technical efficiency analysis of information technology investments: a two-stage empirical investigation, Information & Management 39: 391–401.

Soja, P. 2009. Enterprise system implementation issues: learning from field study in Poland, Enterprise Information Systems 3: 173–200.

Subramanian, G. H.; Peslak, A. R. 2010. User perception differences in enterprise resource planning implementations, Journal of Computer Information Systems 50: 130–138.

Sun, H.; Ni, W.; Lam, R. 2015. A step-by-step performance assessment and improvement method for ERP implementation: Action case studies in Chinese companies, Computers in Industry 68: 40–52.

Swierczek, F. W.; Shrestha, P. K. 2003. Information technology and productivity: a comparison of Japanese and Asia-Pacific banks, The Journal of High Technology Management Research 14(2): 269–288.

Usmanij, P. A.; Khosla, R.; Chu, M.-T. 2013. Successful product or successful system? User satisfaction measurement of ERP software, Journal of Intelligent Manufacturing 24: 1131–1144.

Ustundag, A.; Cevikcan, E. 2016. Maximizing the value of residential projects using fuzzy rule based linear programming, Journal of Civil Engineering and Management 22(7): 853–861.

Uwizeyemungu, S.; Raymond, L. 2009. Exploring an alternative method of evaluating the effects of ERP: a multiple case study, Journal of Information Technology 24: 251–268.

Uwizeyemungu, S.; Raymond, L. 2012. Impact of an ERP system’s capabilities upon the realisation of its business value: a resource-based perspective, Information Technology and Management 13: 69–90.

Wei, C.-C. 2008. Evaluating the performance of an ERP system based on the knowledge of ERP implementation objectives, The International Journal of Advanced Manufacturing Technology 39: 168–181.

Xu, J.; Feng, C. 2015. Two-stage based dynamic earth-rock transportation assignment problem under fuzzy random environment to earth-rock dam construction, Journal of Civil Engineering and Management 21(6): 775–797.

Yazdani-Chamzini, A. 2014. Proposing a new methodology based on fuzzy logic for tunnelling risk assessment, Journal of Civil Engineering and Management 20(1): 82–94.

Zhu, Y.; Li, Y.; Wang, W.; Chen, J. 2010. What leads to post-implementation success of ERP? An empirical study of the Chinese retail industry, International Journal of Information Management 30: 265–276.