I think you need to have two stages. Firstly, you can make interviews in order to understand dimensions related to innovation perception. After you get it, you can create your own scale. Thus, you can make contribution to the literature. Otherwise, Up to me, there will be no contribution to the literature if you just measure perception of innovation.
if you don't find measurements in literature. it will be good contribution to develop your measurements.please read my attached paper to develop construct.
here some procedures, you can follow:
1.Specify domain of the construct:The suggested procedure for scale developing begins with specifying the domain of the construct and underlying the theory of the construct being measured. A theory is essential not only for constructing the scale but also for interpreting the resulting score. Therefore, what is included in the construct and what is excluded should initially be investigated. In this stage, determining the domain is applied by conducting a thorough review of literature in which the variable is used and should present a detailed statement of the reasons and evidence.
2.Generate sample of items:The second step in the procedure for developing better measures is to generate items that capture the domain as specified. Typically, this can be based on exploratory research; including literature searches, interviews, and focus groups. The literature should specify how the variable has been defined previously and how many dimensions or components it has. The individual interviews and focus group discussions can also be used in favour of the item-generation stage. Early stages of item generation focus on developing a set of items that capture each and every one of the dimensions of the construct in this matter. Near the end of the release stage of item development, the focus will shift to editing the item. Each statement should be reviewed so that the formulated words would be as accurate as possible. After the gathered item is edited carefully, the items generated from both interviews and past literature should be submitted to a panel of experts and/or other knowledgeable individuals for judgment. The panel of experts may refine the items and some items may be dropped. Further refinement will also be applied in the actual data.
3.Purify the measures:Although content validity was achieved in the previous stage, the reduced set of items may still be too large to represent a scale. Thus, further reduction techniques are applied in a quantitative manner. Data should be collected on the reduced set of potential scale items from a pre-test sample of respondents. The data were analysed using techniques such as coefficient alpha and factor analysis. The Cronbach’s alpha value is usually used in the early stage to purify the measures. The component is accepted if the Cronbach’s alpha value is greater than the .70 threshold recommended by Nunnally and Bernstein (1994). In order to gain the highest possible reliability coefficient, the components are purified by dropping items with the lowest item-to-total correlation.
4.The continuous improvement cycle in the instrument development process was suggested by Chen and Paulraj (2004). It is similar to the process recommended by Churchill (1979) covering: purify measure by exploratory factor analysis, assess the reliability with new data, and assess construct validity.
this might just be a language thing, but I would start with thinking through what it is that you are actually measuring the perception of, so to speak (especially, but not exclusively if you intend to target social scientists as well).
If you are interested in getting academics' perception of which (other) academics are. then you are to some extent moving into Bourdieu's notion of status in social fields.
if you are interested in how academics perception of what innovation means (a creative idea? something that can be patented? something that will alter our lives and society? something that will make you rich?). then you could have a scale leting them grade what is innovative based on e.g. novelty/creative; practical usefulness; patentability; economic value; potential for future research development.
Thank you for your answer. We think to measure all disciplines' academics.So that, we are trying to look at all dimensions of innovation ( as yo say "novelty/creative; practical usefulness; patentability; economic value; potential for future research development" and etc and the others)
I have listed some sources, my hope is that you find a pattern that will help you elicit the most valid and reliable approaches to innovation surveying. Good luck!
Innovation theory: learning application:
Mytelka, L. K., & Smith, K. (2002). Policy learning and innovation theory: an interactive and co-evolving process. Research policy, 31(8), 1467-1479.
Research/Innovation survey design:
Oerlemans, L. A. G., Buys, A. J., & Pretorius, M. W. (2001, March). Research design for the South African innovation survey 2001. In International Seminar on the Measurement of Innovation Activities (pp. 28-29).
Mairesse, J., & Mohnen, P. (2010). Using innovation surveys for econometric analysis. Handbook of the Economics of Innovation, 2, 1129-1155.
Community Systems Innovation Survey:
Evangelista, R., Iammarino, S., Mastrostefano, V., & Silvani, A. (2002). Looking for regional systems of innovation: evidence from the Italian innovation survey. Regional Studies, 36(2), 173-186.
Survey Debates, Challenges:
Salazar, M., & Holbrook, A. (2004). A debate on innovation surveys. Science and Public Policy, 31(4), 254-266.