Configuring the Knowledge Diffusion Policy Portfolio of Higher Education Institutes

Abstract

The research proposes an analytic framework to configure the policy portfolio for diffusing knowledge embedded in higher-education institutes. A modified Delphi method was first proposed to derive the key factors for enabling and enhancing the diffusion mechanism. The influence relationships between these factors were derived using the Decision-Making Trial and Evaluation Laboratory (DEMATEL). The analytic network process (ANP) derived weights associated with the key factors. Finally, the Grey Relational Analysis (GRA) was used to derive the policy instruments based on the Grey Relationships between the key factors and the policy instruments. An empirical study based on Taiwanese highereducation institutes also/then verified the feasibility of the proposed analytic framework. These findings suggest that research and development activities, publications, and networks of academic exchange play primary roles in knowledge diffusion in highereducation institutions. Motivation, human resources, and investment are the most important policy instruments to use for improving knowledge diffusion in the highereducation system.

A Novel Analytic Framework of Technology Mining Using the Main Path Analysis and the Decision-Making Trial and Evaluation Laboratory-Based Analytic Network Process

“…DEMATEL was developed by Gabus and Fontela [50] in the 1970s to construct complex causal relationships among numerous world problems. The graph-theory-based model has been widely used in modelling various decision-making problems, which include the configuration of innovation policy portfolio(s) (e.g., [9]), operations management (e.g., [51,52]), education and learning (e.g., [53][54][55][56]), engineering (e.g., [57]), medical devices (e.g., [58,59]), big data analytics (e.g., [60]) and other social problems (e.g., [61]). Compared with other methods (e.g., the ISM), which can structure decision-making problems based on the existence or non-existence of influence relationships between criteria or aspects, DEMATEL can consider the extent of influences between criteria or aspects.…”

Evaluation and Selection of Materials for Particulate Matter MEMS Sensors by Using Hybrid MCDM Methods

“…Yang et al [67] evaluated the disaster-recovery site for information systems of academic big data. Chen et al [68] configured the knowledge diffusion policy portfolio of higher education institutes by MCDM methods. Huang et al [69] developed a curriculum to enhance the imagination in the technology commercialization process.…”

Strategic mechanisms for stimulating academiaindustry interactions in Rwanda

“…For UIC in particular, governments use policy instruments to create a conducive environment for collaboration through setting up institutional boundary spanning mechanisms, funding research projects that are not financially attractive in short term for firms to be willing to invest their own funds (Sá & Litwin, 2011;Etzkowitz, 2008), and coordinating stakeholders' efforts (Becker, 2016). Furthermore, considering that the first goal of public policy instruments is to stimulate public behavior change (Tummers, 2019), UIC policies can be used to establish incentives for triggering motivation to engage in collaboration (Huang et al, 2017;Bodas Freitas & Verspagen, 2017). This section overviews the extant literature not only on what motivates UIC actors, but also on types of policy instruments, interaction between policies and conceptualization of the effectiveness of public policy portfolio.…”

“…• Performance-based funding of universities and reward systems for researchers • Science parks, spin-offs, and business incubators (Guimón, 2013) Human resource development and management for the acquisition of talented workforce at university or in firms. • Policy aimed at providing a sound research environment or at encouraging brain migration and talent outflow (Huang et al, 2017); (Etzkowitz, 2008) • Policy that seeks to improve the quality of university graduates to better respond to industry needs,…”

“…The chapter contributes to the existing literature on UIC in SSA by using a policy mix analytical model to evaluate the adequacy of public policy portfolio with a focus on how proposed policy actions enhance actors' motivation. We do so by cross-tabulating policy actions identified as relevant to the innovation policy interaction domains (Huang et al, 2017;Borrás & Edquist, 2019) with the benefits expected from UIC. The latter being considered as the foundation of academia and industry staff's motivation to collaborate.…”