Exploring the synergy between R&D and advertising and firm performance: a neural network approach

Purpose: This paper explores the nonlinear interactions of research and development (R&D) and advertising and their synergistic effect on firm performance using Tobin's Q. This study also aims to investigate differential synergy patterns under varying levels of exports with a precision impact on performance. Design/methodology/approach: Unlike a conventional statistical approach, this study uniquely presents a neural network approach to explore the dynamic interplay of strategic factors. A multilayer perceptron neural network (MPNN) is designed to capture complex interaction patterns through a predictive analytic process. Findings: This study finds that the impact of R&D and advertising is positive, with a greater effect on high-export firms. Moreover, the experiment results show that the synergy of R&D and advertising goes beyond the formatted positive/negative frame and actually has a reinforcing effect. Practical implications: This study not only conveys the significant nexus of R&D and advertising for firm performance but also provides industry managers' practical means to assess the joint effect of R&D and advertising on firm performance. The proposed analytic mechanism in particular provides pragmatic decision support to managers in harmonizing their R&D and advertising efforts for a foreseeable impact. Originality/value: This paper presents an innovative analytic process using the MPNN to explore the synergy between R&D and advertising. In addition to offering new perspectives on R&D and advertising, this study presents pragmatic implications for managing those strategic resources to meet performance targets.