Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/25433
Title: Evaluating the Project Management Methodology Adoption Process in the Sri Lankan Software Industry
Authors: Koggalahewa, Lahiru
Abeysekara, Ruwan
Keywords: process adoption, project management methodology, the software industry
Issue Date: 2022
Publisher: Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka
Citation: Koggalahewa Lahiru; Abeysekara Ruwan (2022), Evaluating the Project Management Methodology Adoption Process in the Sri Lankan Software Industry, International Research Conference on Smart Computing and Systems Engineering (SCSE 2022), Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka. 231-238.
Abstract: Projects are the primary method of implementing change in an organization. Most software firms tend to use a Project Management Methodology (PMM) to deliver the product to the customer. However, there is no rational set of motives to select the desired PMM. Given this context, this study investigates the reasons for the adoption of PMM rather than using an internally defined set of processes. The study also evaluated the factors affecting the selection and implementation of the PMM. The study used multiple case study methods, and data were gathered by conducting six in-depth interviews with experienced management personnel in software organizations. The analysis concludes with a list of PMM adoption motives and how PMM selection, adoption and implementation are carried out in the software industry domain from a strategic point of view. The study investigated organizational transitions and change management from a complex managerial perspective, as well as cultural dimensions and individual and organizational social values. The study fills a gap in the literature. Also, the study derives a proper processual plan for the adoption motives, selection and adoption process of PMM, which should help inform future strategies in this field.
URI: http://repository.kln.ac.lk/handle/123456789/25433
Appears in Collections:Smart Computing and Systems Engineering - 2022 (SCSE 2022)

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