Communicating and prioritizing science and technology policy using AHP.

Author:Wu, Yi-Ching

Technology development plays an important role in human civilization, as a critical tool for living, as a source of competition between economies, and as a promoter of economic growth and human welfare. Every government in the world devoted to technology development draws up a national science and technology policy (also called 'S&T policy'). However, S&T policy is difficult to define because technology varies significantly along a continuum, ranging from mono-disciplinary to multidisciplinary commercial innovation (Huang, Shyu, & Tzeng, 2007). Obviously, a substantial proportion of national S&T budgets will go towards satisfying future S&T project requirements and the increasing needs for technology innovation. Decisions about which national S&T policies should be executed first have become increasingly important, but little investigation has been done in how to rank priorities in setting S&T policies, especially as a tool for policy priority making.

The previous studies on S&T policymaking mostly focus on policy participation and policy coordination. OECD (2005a) mentioned the Finnish Science and Technology Policy Council and the Norwegian Innovation Committee have been very influential in directing the process of priority setting but less stakeholder involvement, although there is significant stakeholder involvement in the implementation process and project selection. Thus, policy councils may be a powerful tool for creating a mediated and negotiated outcome during the priority-setting process but may have weaknesses with respect to the ability to develop comprehensive, horizontal policies. Luis (1995) proposed that the Spanish political institutions in charge of coordination were prevented from developing due to conflicts at the managerial level. In particular, the majority of participants at this level continued to work within the old policy paradigm, resulting in a non-transparent approach in which the goals of policymakers and the goals of the general public were not aligned. There is a high probability that these diverse objectives will remain undiscovered and uncorrected if policymaking methodologies cannot facilitate consensus among the various relevant groups (Ryan & Mothibi, 2000). As in all complex decision making processes, selection problems expand from one to several dimensions, making the ultimate goal of identifying a solution fairly complex. Given that the process of making S&T policy decision touches on diverse interests and considerations from many related agencies and groups, it is important to avoid allowing the level of power held by the main interest group to bias decisions concerning the fit between national S&T policy and the particular situation of that country. When policymakers who simply rely on expert analysis and advice face the needs to determine priorities for S&T policies, they cannot create consensus among the various interest groups that attempt to affect S&T policy. Because the national S&T policy position is different for each country, the approach to setting priorities for S&T policies must be adapted to account for local conditions. For instance, Taiwan ranks 7th in the world on the 2004-2008 Economist Intelligence Unit's (EIU) Global Innovation Index, behind Japan, Switzerland, Finland, the US, Sweden, and Germany, and it is the highest ranked of the newly industrialized countries (The Economist, 2009). Taiwan has advantages for the development of knowledge-intensive industries, and its potential is growing rapidly with respect to S&T, which play a key role in leading the transformation of the Taiwanese economy. If Taiwan wishes to become a developed nation, it needs to continually rely on its excellent high-tech infrastructure and R&D personnel, build a knowledge innovation system through cooperation between industry, universities, and research institutes, and provide all citizens with a sustainable and high-quality living environment. Thus, the creation of an integrated S&T policy that unifies different groups is a difficult but important task for Taiwan. In this study, we will take Taiwan S&T policy making as an example and provide a new approach to handle multi-criteria decision making problems of choice and prioritization.

This study applies the analytic hierarchy process (AHP), one of the most widely used methods in resource allocation and organization planning in fields that require multi-criteria decision making (Byun, 2001; Forgionne & Kohli, 2001). The advantages of the AHP method over other multi-criteria methods are its flexibility, its intuitive appeal to decision makers, and its ability to identify inconsistencies (Ramanathan, 2001). In addition, this method decomposes a decision problem into its constituent parts and builds hierarchies of criteria, thereby clarifying the importance of each criterion (Macharis, Springael, De Brucker, & Verbeke, 2004). The AHP method provides a useful mechanism for assessing the consistency of the evaluation measurements and alternatives, and reduces biases in decision making. The AHP method can also achieve remarkable success with respect to the prioritization of S&T policies, particularly for Taiwan, which is attempting to visualize 2015 S&T policy vision--'Innovative Capabilities and Citizens' Quality of Life will Reach the Level of a Developed Nation by 2015.' This method will allow decision makers to evaluate various competing criteria and alternatives for achieving a certain policy vision and goals; furthermore, it will allow decision makers in a group setting to rank order Taiwan S&T policy decisions based on the results of a quantitative analysis. In this study, the Taiwanese case will demonstrate the value of applying the AHP method for S&T policymakers. Moreover, we hope to aggregate different opinions and then use AHP to form a consensus among various groups. The result of the final analysis will be submitted to policymaking agencies for use in determining the direction of S&T development over the course of the next four years, and will be reported in the White Paper on Science and Technology.

In the following section, we first review the modes and obstacles involved in existing policymaking procedures. This review is followed by a discussion of the formulation mechanisms for the Taiwan S&T policy goals and measures. We also provide an overview of the AHP method and the other research methods used in this study. The next section presents the results and discussion of the AHP approach to S&T policy making in Taiwan. Our key findings and conclusions are discussed in the final section of this study.


The modes and obstacles of existing policymaking procedures

Leydesdroff and Gauthier (1996) revealed that the institutionalization of policies varies from one country to the next. Like technological innovation, S&T policy making is not simply the result of the rational process undertaken by bureaucrats and politicians at a given time. In actuality, the definition and implementation of any policy is shaped by the institutional configuration of the state and its prior experience with related policies. The state would be predisposed to favoring existing priorities or to steering the priorities in a particular direction (Georghiou, 1996; Luis, 1995). The causal mechanisms that produce policy decisions are complicated and vary over time (Hart, 2001).

There are significant conceptual, methodological, and implementation challenges associated with achieving an in-depth understanding of policy formulating mechanisms. In general, there are two ways to proceed--a bottom-up method and a top-down method (DSTI, 2006). The bottom-up method is a research activity that is causally linked to societal outcomes through hypothesis development and testing on increasingly more complex and representative systems, which is then combined with socio-econometric modeling (DSTI, 2006). The goal is to produce models that achieve a level of predictive accuracy sufficient to provide at least a partial, practical basis for policy decisions (DSTI, 2006). Sabatier (1986) proposed that bottom-up policy approaches seem more appropriate in situations where there is primary interest in the dynamics of different local situations in which variety prevails. However, it is very difficult to achieve legitimacy and credibility due to their often overly personal or charismatic forms of communication and decision-making (Jamison, 2001). Whether similar analyses could achieve equal utility in the S&T policy domain is a question that deserves consideration. Nonetheless, rather than adopting a pure bottom-up approach, some countries choose to employ a top-down methodology in which expert groups are convened to set ever more narrowly defined goals and objectives in order to achieve greater accountability (Rappert, 1999). The top-down policy approach offers the means of allocating public resources to those areas where they can have the greatest impact and is the most appropriate means of responding to a rapidly changing world (OECD, 2005b). However, a top-down approach to S&T policy has significant negative impacts if it cannot direct S&T policy to create capacity for growth and development throughout its constituent regions. The skills and innovation policies proposed by the UK government in 2003 serve as an example. The UK government expected to transform the country into a high-skill information and knowledge-based economy, but the gap between its perceptions and the reality they face remains very wide (Taylor, 2003). The final failure of this policy was ascribed to the lack of a coherent policy response, industry co-operation, national consensus and a new form of public intervention. At that time, many researchers argued that this approach was too heavily top-down and fragmented in addition to being over-managerial and excessively concerned with the implementation of supply-side measures. In practice, policymaking is required to balance certain...

To continue reading