Measuring innovation effectiveness: a SEM-based cross-lagged analysis

• Published in: International journal of innovation science Vol. 13; no. 4; pp. 437 - 455
• Main Authors: Arshi, Tahseen Anwer, Rao, Venkoba, Viswanath, Sumithra, Begum, Vazeerjan
• Format: Journal Article
• Language: English
• Published: Brentwood Emerald Publishing Limited 13-10-2021; Emerald Group Publishing Limited
• Subjects: Competitive advantage; Design; Effectiveness; Emerging markets; Impact analysis; Impact prediction; Innovations; Inquiry method; Longitudinal studies; Market entry; Markets; Mathematical models; Multivariate statistical analysis; Product development; Socioeconomic factors; Synergistic effect; Technological change; Measurement; Systematic innovation; Innovation strategy; Innovation types; Organizational readiness
• ISSN: 1757-2223; 1757-2231
• DOI: 10.1108/IJIS-08-2020-0111

Purpose
The study aims to develop measures for innovation effectiveness impacting organizational performance outcomes. Substantial evidence suggests that measuring innovation effectiveness (IE) continues to be challenging because of the use of different measures across innovation’s broad spectrum. The purpose of this study is to overcome it by examining multiple drivers of IE in emerging market economies (EMEs) and predicting their impact on financial and nonfinancial performance outcomes.
Design/methodology/approach
Through a two-wave panel design, firms from India, Oman and the United Arab Emirates participated in the study with a time lapse of 12 months (T1n = 417, T2n = 403). Four cross-lagged competing models are tested for autoregressive, causal, reversed and reciprocal effects using structural equation modeling (SEM).
Findings
The findings show that the synergistic effect of multiple innovation characteristics, such as innovation degree, cost, frequency and speed determines its endogenous effectiveness. The exogenous effectiveness of innovation is further established through its impact on financial and nonfinancial performance outcomes. Furthermore, readiness for innovation (RFI) is a critical factor that moderates the relationship between drivers and IE.
Practical implications
The study’s findings could inform practitioners in emerging market economies about the appropriate measures of IE. It will guide managerial decisions on making an investment, evaluation, accountability and strategic choices related to innovation.
Originality/value
It is one of the first studies that use a time-based lens to examine IE in EMEs. It posits that given the innovation’s complexity, IE needs to be measured at multiple levels. The study explains how evolutionary dynamics in different sociocultural contexts can bring a new perspective into theory of diffusion of innovation. The moderating role of RFI brings new insights into the IE process and emphasizes its importance in objective-driven and performance-focused innovation efforts.