Evaluating Public Policy Formation and Support Mechanisms for Technological Innovation
Policy evaluation is a complex task. Most approaches now adopt a mixed method approach combining both quantitative and qualitative techniques. A shortcoming of the standard approaches is that they fail to measure or investigate deeper perceptions of the policy. In this paper the usefulness of projective techniques as a tool for policy evaluation is investigated. Projective techniques are widely used in psychology and consumer studies but their usefulness in policy evaluation has still to be assessed. A simple evaluation is done in this paper by reporting on a study of owner-managers of tradeable-services small and medium size enterprises attitudes to government e-business policy. The survey included firms from Northern Ireland, Republic of Ireland and New Zealand. Traditional quantitative and qualitative survey techniques were used, however these failed to produce conclusive evidence. To overcome this limitation two projective techniques—word association and completion tests—were employed as an additional evaluation method. The paper illustrates how the results of projective techniques can be analysed using both context and matrix analysis. Given that the area of e-business is dynamic and fast changing and that SMEs are extremely heterogeneous, it is argued that the application of projective techniques to assess their attitudes and perceptions of government policy is a good test of the usefulness of the method. The results of the projective techniques lead to more insight into the perceptions and attitudes of the owner-managers and provide interesting individual perspectives into the issues. Problems with the method, such as costs, the level of skill needed to apply the technique and generalization are highlighted. The overall conclusions are that projective techniques could provide an interesting additional tool for policy evaluation and that further assessment of its usefulness is needed.
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Volume (Year): 21 (2007)
Issue (Month): 3 ()
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