Key Performance Indicators (KPI) for Researchers at Different Levels & Strategies to Achieve it
-
Published:2023-08-30
Issue:
Volume:
Page:294-325
-
ISSN:2581-6012
-
Container-title:International Journal of Management, Technology, and Social Sciences
-
language:en
-
Short-container-title:IJMTS
Author:
Aithal P. S.1, Aithal Shubhrajyotsna2
Affiliation:
1. Professor, Institute of Management & Commerce, Srinivas University, Mangalore, India 2. Faculty, Institute of Engineering & Technology, Srinivas University, Mangalore, India
Abstract
Purpose: Key Performance Indicators (KPIs) serve as essential tools for academic researchers across various stages of their careers, from PhD research level to the post-doctorate research level, and even for research supervisors. These quantitative and qualitative metrics play a pivotal role in guiding and evaluating research endeavours, fostering accountability, and enhancing the overall quality and impact of academic work. KPIs play a critical role in shaping the trajectory of academic researchers' careers. They provide a structured way to measure and enhance research productivity, impact, and collaboration, thereby contributing to the advancement of knowledge and the overall enrichment of the academic community. It is academically interesting to know KPTs for PhD scholars’ level, post-doctorate scholars level, and research supervisors level. Methodology/Approach: The exploratory research method is adopted to analyze, compare, evaluate, interpret, and create KPIs at different academic research levels. The information is collected from scholarly articles using listed keywords with the help of search engines like Google.com, Google scholar, Organizational websites, and AI machines like ChatGPT and Bard. Using this relevant information, KPIs at different research levels are obtained. These KPIs at different academic research levels are further analysed using ABCD analysis framework. Findings/Result: Many KPIs are identified and listed at PhD scholars’ level, post-doctorate scholars level, and research supervisors level. Using ABCD analysis framework, these KPIs are analysed and evaluated. It is believed that the identified KPIs systematically in this research are going to be guiding policies for academic researchers at PhD scholars level, post-doctorate scholars level, and research supervisors level. Originality/Value: For the first time, the key performance indicators (KPIs) are identified systematically and presented using exploratory research method. It is believed that like in business organizations of other industries, these key indicators are expected to be guiding principles to enhance the academic research productivity of higher education and research institutions at PhD scholars level, post-doctorate scholars level, and research supervisors level. Type of Paper: Explorative Policy Research.
Publisher
Srinivas University
Reference75 articles.
1. Schrage, M., & Kiron, D. (2018). Leading with next-generation key performance indicators. MIT Sloan Management Review. 2018(6), 180-185. 2. Ishaq Bhatti, M., Awan, H. M., & Razaq, Z. (2014). The key performance indicators (KPIs) and their impact on overall organizational performance. Quality & Quantity, 48, 3127-3143. 3. Badawy, M., Abd El-Aziz, A. A., Idress, A. M., Hefny, H., & Hossam, S. (2016). A survey on exploring key performance indicators. Future Computing and Informatics Journal, 1(1-2), 47-52. 4. Velimirović, D., Velimirović, M., & Stanković, R. (2011). Role and importance of key performance indicators measurement. Serbian Journal of Management, 6(1), 63-72. 5. Maté, A., Trujillo, J., & Mylopoulos, J. (2012). Conceptualizing and specifying key performance indicators in business strategy models. In Conceptual Modeling: 31st International Conference ER 2012, Florence, Italy, October 15-18, 2012. Proceedings 31 (pp. 282-291). Springer Berlin Heidelberg.
Cited by
18 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Data-Driven Excellence;Advances in Business Information Systems and Analytics;2024-06-28 2. Tech-Business Analytics in the Circular Economy;International Journal of Management, Technology, and Social Sciences;2024-05-30 3. Tech-Business Analytics in Blue Economy;International Journal of Applied Engineering and Management Letters;2024-05-16 4. A Quantitative ABCD Analysis of Factors Driving Share Price Volatility in the Indian Pharmaceutical Sector;International Journal of Management, Technology, and Social Sciences;2024-04-17 5. Exploring Neuro Management: Bridging Science and Leadership – An Overview;International Journal of Applied Engineering and Management Letters;2024-04-12
|
|