Abstract:
The theme of research and development (R&D) lies at the heart of any industry that attempts to increase its productivity, and there is no difference concerning those industries cataloged under the commercial agri-food sector. Key performance indicators (KPIs) are recognized as one of the key tools that are heavily used to measure these efforts in research management, through which the right direction of the research agenda of a research institute is evaluated. The dynamics of KPIs in place are, however, slackly deliberated and remain poorly understood, and perhaps, those set up to work toward achieving Sustainable Development Goal (SDG 2) - "Zero Hunger" are not well explored. This study, on this shed of light, aimed to synthesize the literature build-up on performance management of research that was put into a business perspective. A systematic review of the literature was followed in Phase One to identify, collate, and summarize empirical evidence from the extant literature on performance management systems (PMSs) and KPIs. Thirty-two (32) research administrators and practitioners affiliated with prominent research institutes operating in Sri Lanka directing research for commercial agriculture development were approached in Phase Two via in-person in-depth interviews aided by an interview guide comprising 15 probing questions. To assess the perspectives of those officers in the upper echelon, the Thematic Qualitative Models produced by MAXQDA 2022 software were employed. The outcome of the thematic analysis converged those perspectives into five themes: (1) Research commercialization, (2) Research collaboration, (3) Research for society, (4) Institutional management, and (5) Technology-integrated systems. It underscored the organizational benefits gained from well-thought-out PMSs comprised of smart KPIs. Some analysis techniques such as Code-Frequency-Tables, Code-Maps, etc., provided by the software were systematically used to build some frameworks on KPI-key performance drivers (KPD) relationships that facilitate real-time data-driven PMS in driving research business innovations on commercial agriculture.
