Lifecycle Impact Assessment of an Engineering Project Management Process – A SLCA Approach
DOI:
https://doi.org/10.5281/zenodo.14580780Keywords:
Social sustainability, lifecycle assessment, community impact assessment, social impacts, engineering project management, sustainable development, impact assessmentAbstract
Engineering projects are designed to solve societal problems, foster community development, and enhance quality of life. However, these projects often have unintended consequences that affect human life and ecosystems. The management process of these projects significantly influences their social, environmental, and economic impacts. This paper presents a framework for evaluating the lifecycle impacts of engineering project management processes on various stakeholders, including workers, clients, communities, and society at large. The model adopts the UNEP/SETAC guidelines for Social Lifecycle Impact Assessment (SLCA). By identifying potential impacts during the lifecycle stages, project managers can reinforce positive outcomes and mitigate negative effects. Incorporating SLCA in project management is expected to improve overall project value, particularly from a social sustainability perspective
References
Kibert, C. J. Sustainable Construction: Green Building Design and Delivery. Wiley, 2008.
Zhang, X.L., Shen, L. Y., & Wu, Y. Z. Green strategy for gaining competitive advantage.Journal of Cleaner Production, 2011
Hwang, B. G., & Tan, J. S. Green Building Project Management: Obstacles and Solutions.Sustainable Development, 2010.
Eisenberg, D., Done,R., & Ishida, L. Breaking Down the Barriers: Challenges and Solutions to Code Approval of Green Building.Research Report, 2002.
Yudelson, J. The Green Building Revolution. Island Press, 2008.
Agrawal, A., Gans, J., & Goldfarb, A (2017). What to expect from artificial intelligence?MIT Sloan Management Review, 58(3), 22–27.
Akbarighatar, P., Pappas, I., & Vassilakopoulou, P. (2023). A sociotechnical perspectivefor responsible AI maturity models: Findings from a mixed-method literature review.International Journal of Information Management Data Insights, 3(2), Article 100193
Bai, C., Sarkis, J., Yin, F., & Dou, Y. (2020). Sustainable SCF and its relationship tocircular economy-target performance. International Journal of Production Research, 58(19), 5893–5910.
Akter Jahan, S., & Sazu, M. H. [2022]. Rise of mobile banking: a phoenix moment for the financial industry.Management & Datascience, 6[2].
Akter, J. S., & Haque, S. M. [2022]. Innovation Management: Is Big Data Necessarily Better Data. Management ofSustainable Development, 14[2], 27-33.
Haque, S. M., & Akter, J. S. [2022]. Big Data Analytics & Artificial Intelligence In Management Of Healthcare:Impacts & Current State. Management of Sustainable Development. Management of Sustainable Development,,14[1], 36-42.
Isenberg, D. T., Sazu, M. H., & Jahan, S. A. [2022]. How Banks Can Leverage Credit Risk Evaluation to Improve Financial Performance. CECCAR Business Review, 3[9], 62-72.
Jahan, S. A., & Sazu, M. H. [2022]. Role of IoTs and Analytics in Efficient Sustainable Manufacturing of Consumer Electronics. International Journal of Computing Sciences Research, 6.
Jahan, S. A., & Sazu, M. H. [2022]. The Impact of Data Analytics on High Efficiency Supply Chain Management. CECCAR Business Review, 3[7], 62-72.
Jahan, S. A., Isenberg, D. T., & Sazu, M. H. [2022]. How Healthcare Industry can Leverage Big Data Analytics Technology and Tools for Efficient Management. Journal of Quantitative Finance and Economics, 5[1], 149-158.
Sazu, M. H. [2022]. Does Big DataDrive Innovation In E-Commerce: A Global Perspective?. SEISENSE Business Review, 2[1], 55-66.
Sazu, M. H. [2022]. How machine learning can drive high frequency algorithmic trading for technology stocks. .International Journal of Data Science and Advanced Analytics, 4[4], 84-93.
Sazu, M. H., & Jahan, S. A. [2022]. Can big data analytics improve the quality of decision-making in businesses?. Iberoamerican Business Journal, 6[1], 04-27.
Sazu, M. H., & Jahan, S. A. [2022]. Factors Affecting The Adoption OfFinancial Technology Among The Banking Customers In Emerging Economies. Studii Financiare [Financial Studies], 26[2], 39-54.
Sazu, M. H., & Jahan, S. A. [2022]. High efficiency public transportation system: role of big data in making recommendations. Journal of process management and new technologies, 10[3-4], 9-21.
Sazu, M. H., & Jahan, S. A. [2022]. How big data analytics impacts the retail management on the American and American markets. CECCAR Business Review, 3[6], 62-72.
Sazu, M. H., & Jahan, S. A. [2022]. How Big Data Analytics is transforming the finance industry. Bankarstvo,51[2], 147-172.
Sazu, M. H., & Jahan, S. A. [2022]. Impact of big data analytics on business performance. International Research. Journal of Modernization in Engineering Technology and Science, 4[3], 367-378.
Sazu, M. H., & Jahan, S. A. [2022]. Impact of big data analytics on distributed manufacturing: does big data help?. Journal of process management and new technologies, 10[1-2], 70-81.
Sazu, M. H., & Jahan, S. A. [2022]. IMPACT OF BIG DATA ANALYTICS ON GOVERNMENT ORGANIZATIONS TO IMPROVE INNOVATION AND DECISION-MAKING. Management Strategies Journal, 57[3], 34-44.
Sazu, M. H., & Jahan, S. A. [2022]. Impact of blockchain-enabled analytics as a tool to revolutionize the banking industry. Data Science in Finance and Economics, 2[3], 275-293.
Sazu, M. H., & Jahan, S. A. [2022]. The impact of big data analytics on supply chain management practices in fast moving consumer goods industry: evidence from developing countries. International Journal of Business Reflections, 3[1], 112-128.
Sazu, M. H., & Akter Jahan, S. (2022). Impact of big data analytics on government organizations.Management & Datascience,6(2)
Jahan, S. A. (2024). How project management principles can lead to successful project completion inconstruction industry.IPHO-Journal of Advance Research in Business Management and Accounting,2(11), 01-08.
Jahan, S. A. (2024). Integrating Project Management Techniques and Stakeholder Engagement forComprehensive Project Success: A Multi-Domain Analysis.IPHO-Journal of Advance Research in BusinessManagement and Accounting,2(11), 09-17.
Jahan, S. A. (2024). A Unified Approach to Project Management: Integrating Information Views and ICTTools.IPHO-Journal of Advance Research in Business Management and Accounting,2(11), 18-23.
Jahan, S. A. (2024). Utilizing Predictive Analytics and Machine Learning for Enhanced Project RiskManagement and Resource Optimization.IPHO-Journal of Advance Research inBusiness Management andAccounting,2(11), 24-31.
Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R., & Verma, S. (2021). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism:An empirical investigation. Annals of Operations Research, 333(2), 627–652.
Blome, C., Schoenherr, T., & Eckstein, D. (2014). The impact of knowledge transfer andcomplexity on SCF: A knowledge-based view. International Journal of ProductionEconomics, 147, 307–316.
Braunscheidel, M. J., & Suresh, N. C. (2009). The organizational antecedents of a firm’ssupply chain agility for risk mitigation and response. Journal of OperationsManagement, 27(2), 119–140.
Bryant, F.B., & Yarnold, P.R. (1995).Principal-components analysis and exploratory andconfirmatory factor analysis.
C´ardenas, L. J. A., Ramírez, W. F. T., & Rodríguez Molano, J. I. (2018). Model for the incorporation of big data in knowledge management oriented to industry 4.0. In Proceedings of the Data Mining and Big Data: Third International Conference (pp. 683–693). Springer International Publishing. DMBD 2018Proceedings 3.
Can Saglam, Y., Yildiz Çankaya, S., & Sezen, B (2020). Proactive risk mitigation strategiesand supply chain risk management performance: An empirical analysis formanufacturing firms in Turkey. Journal of Manufacturing Technology Management.https://doi.org/10.1108/JMTM-08-2019-0299. ahead-of-print No. ahead-ofprint.
Cichosz, M., Wallenburg, C. M., & Knemeyer, A. M. (2020). Digital transformation at logistics service providers: Barriers, success factors and leading practices. International Journal of Logistics Management, 31(2),209–238.
Chan, A. T., Ngai, E. W., & Moon, K. K. (2017). The effects of strategic and manufacturing flexibilities and supply chain agility on firm performance in the fashion industry.European Journal of Operational Research,259(2), 486–499.
Chandra, C., & Grabis, J. (2009). Role of flexibility in supply chain design andmodeling—Introduction to the special issue. Omega, 37(4), 743–745.
Chaudhuri, A., Ghadge, A., Gaudenzi, B., & Dani, S. (2020). A conceptual framework forimproving effectiveness of risk management in supply networks. International Journalof Logistics Management, 31(1), 77–98.
Cheng, J.H., & Lu, K.L. (2018). The impact of big data analytics use on supply chainperformance—efficiency and adaptability as mediators.
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