Abstract
To attain project success in R&D (Research & Development) public sector environment, the aspects of an organizational structure play a vital role in the successful implementation of R&D projects. Nevertheless, not meeting proposed timelines and inadequate management of schedules of R&D projects is the intrinsic hurdle in R&D projects. However, the study gauging the impact of organizational structure on the schedule management of R&D projects has never been discussed before. Therefore, this study aims to gauge the effectiveness of organizational structure and schedule management dimensions upon each other by employing predictive modelling technique i.e. ANN (Artificial Neural Network). This study is based on a quantitative approach and the model followed is non-linear regression. A simple random sampling technique is used to collect data from 285 respondents (in two rounds) from various R&D public sector set-ups. The robustness and homogeneity of data is checked by carrying out F and Ttests. Subsequently, data is pre-processed; ANN model is trained and validated by choosing appropriate tuning parameters and quantitative performance measures like RMSE (Root Mean Square Error) and MAPE (Mean Absolute Percentage Error) are analyzed. The results clearly indicated that formalization, decentralization and authority of managers are strongly correlated; differentiation, specialization, coordination mechanism, departmentalization are positively but weakly correlated with some subconstructs and centralization also constitutes positive but weakly correlated among all. The results also imply that decentralized organizational structures are more preferable than centralized structures for the execution of R&D projects when proposed timelines are to be met timely.
Highlights
To attain project success in R&D (Research & Development) public sector environment, the aspects of an OS (Organizational Structure) play a vital role in the successful implementation of R&D projects
The objective of this research is to minimize propose in-advance a predictive model for project/engineering managers and decision makers to opt for the suitable dimensions of OS and SM in interdependent and complex R&D public sector environment for R&D projects’ execution
Environment/Tool Used for this Study: In this study, the software RStudio (Version: 1.0.143.0) is used for data processing that is a powerful and flexible platform for the evaluation of predictive modeling, performance and data analysis
Summary
To attain project success in R&D (Research & Development) public sector environment, the aspects of an OS (Organizational Structure) play a vital role in the successful implementation of R&D projects. It is evident that most of the R&D projects tend to diverge critically from the unit and project costs, performance parameters of the final product and planned schedules i.e. time-to-market. Due to these reasons, customers’ demands and expectations are not fulfilled [7]. An AI (Artificial Intelligence) based mechanism is developed that links the factors of OS to the SM through ANN technique necessary for the prudent execution of R&D projects in public sector environment. Following research questions are formulated for this study: RQ-1: What are the various sub-constructs and dimensions of OS and SM that influence R&D project success?
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