An empirical study on customers' behavior of passive and active resistance to innovation. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Wang, Yu; Han, Min; Wang, Yuan; Shafiee, Sara
• Is Part Of: Ekonomska istraživanja. Volume 36:Issue 1(2023)
• Publication Date: 2023-12-31
• Subjects: customers' innovation resistance -- passive innovation resistance -- active innovation resistance -- behavioral reasoning behavior -- innovation adoption intention; O31; O32; O33; Economics -- Research -- Periodicals; Economics -- Research; Electronic journals; 330.072
• DOI: 10.1080/1331677X.2023.2179515
• Languages: English
• ISSNs: 1331-677X

Abstract

Abstract: Previous studies reveal that the failure rate of innovation in enterprises is higher than expected. The reason for innovation failures is due to not only the customers' resistance towards innovation, subsequent changes and ignored factors that promote customer acceptance, but also the other disregarded factors that motivates the resistance towards innovation adaptation. The literature proved the customers' innovation resistance (CIR) consists of two categories. Passive innovation resistance (PIR) described as initial resistance behavior before evaluating the new product; and active innovation resistance (AIR) introduced as the resistant behavior after evaluating innovative products. However, few studies have investigated the simultaneous influence of both PIR and AIR, especially using the empirical methods. The main purposes of this study are (1) to construct a model that reflects on both PIR and AIR as two categories of CIR; (2) to provide empirical evidences to highlight the influences and correlation of PIR and AIR. The method used in this paper is partial least squares path modeling (PLS-PM) method to test our model and the hypotheses. The results from this research mainly indicate that (1) PIR is negatively influenced AIR; (2) PIR (including both cognitive and situational PIR) has negative effect on customers' innovation adoption intention (IAI) while (3) the correlation between AIR and IAI is opposite; (4) the degree of customers' IAI with high-perceived stimulation group and low-perceived stimulation group will reverse according to the changes of PIR and AIR. This paper is helpful for enterprises to improve their innovation success rate by analyzing users' resistance to innovation.