Performance drivers of the R&D activities in the chemical sector in Spain: a balanced scorecard approach

ABSTRACT

We have studied the drivers of the performance of the Research and Development (R&D) activities in the chemical sector in Spain. For this purpose, we have validated a Balanced Scorecard (BSC) framework for R&D and analysed the relationships between the Resources and Internal Processes and the Commercial and Financial results of the R&D activities. The study has been undertaken using data gathered from a total of 95 companies in the chemical sector in Spain. We employ the methodology of structural equations and specifically the Partial Least Squares (PLS) technique. We have located the drivers that exert the most effect on each of the dimensions (Resources, Internal Processes, Innovation) that form the BSC for R&D and therefore ultimately affect the performance of the company as a whole (Commercial and Financial Results).

KEYWORDS:

• R&D
• performance drivers
• Spanish chemical sector
• innovation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The calculation of the sampling error for finite populations is obtained from the following expression:

$e=\sqrt{(N-n)\cdot K^2\cdot p\cdot q/N\cdot n}$, where N = Population size; n = Sample size; p = is the (estimated) proportion of the population which has the attribute in question; q = (1−p); p = q = 50%; K (Confidence interval 95%) = 1.96.

2 The model is used for the purpose of predicting which dimensions and items influence the performance of R&D activities, hence endogeneity issues are not analysed, as argued by Hult et al. (2018) whereby when the model is used for predictive purposes, controlling endogeneity is not very useful because it can make the model lose predictive value.

3 For the constructs Performance of the technology and Innovation, we are unable to analyse the reliability, since the constructs are formative. In this case, the weightings are analysed and the absence of collinearity between the items is presented (see Table 3).

4 This product has to have a minimum value of 1.5% for an exogenous construct to be considered a predictor of a dependent construct.

Additional information

Funding

This work has been co-financed by the 2014-2020 ERDF Operational Programme and by the Department of Economy, Knowledge, Business and University of the Regional Government of Andalusia. Project reference: FEDER-UCA18-103353. Title: Circular Economy and Efficiency: Towards new economics models.

Notes on contributors

Daniel Revuelta-Bordoy

Daniel Revuelta-Bordoy is a researcher who is focused on Chemical R&D innovation and Partial Least Squares. He is the owner of College and a PhD at the University of Cádiz, Spain. His research focuses on the development of models of measurement using the methodology of validation of scales and the application of structural equations. His doctoral thesis focused on validating a Balanced Scorecard for the R & D form empirical part of competitive research projects.

Jaime Sánchez-Ortiz

Jaime Sánchez-Ortiz is a researcher who is focused on environmental efficiency on Chemical companies, Data Envelopment Analysis and Partial Least Squares. He is a researcher in the Department of Business Organization from University of Cádiz.

Teresa García-Valderrama

Teresa Garcia Valderrama is a researcher who is focused on Chemical R&D innovation, Data Envelopment Analysis and Partial Least Squares. She is Professor of the University of Cádiz, Spain. She has worked on issues related with the efficiency and performance of R & D in companies and has focused his research on the use of the Data Envelopment Analysis applied to R & D activities and the measure of efficiency in the Public Sector. She is currently Vice chancellors for Social responsibility of the University of Cádiz. She is the principal investigator of national and international competitive research projects.