Using fuzzy set qualitative comparative analysis for evaluating the effectiveness of relationship marketing and innovation in 3D printing medical market

Author:

Cheng Cheng-Feng1,Chen Ta-Cheng234

Affiliation:

1. Department of Business Administration, Asia University, Taichung, Taiwan

2. 3D Printing Medical Research Institute, Asia University, Taichung, Taiwan

3. Department of Information Management, National Formosa University, Yunlin, Taiwan

4. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan

Abstract

This study aims to explore the configurations of potential relevant antecedents in 3D printing medical Market for achieving high user satisfaction from both the suppliers’ and users’ perspectives. The important antecedents in this study include relationship marketing, innovation, 3D printing perceived values, and 3D printing perceived risk. Firstly, this study investigates the relationships among potential relevant antecedents and user satisfaction. Furthermore, to explore the gap between users’ evaluation and innovation suppliers’ perception, this study addresses this issue based on both perspectives of suppliers and buyers. To assess the applicability of the proposed model, we employed questionnaires survey and collected primary data from 3D printing suppliers and their customers. Moreover, the fuzzy set qualitative comparative analysis (fsQCA) approach has been applied for evaluating the effectiveness of relationship marketing and innovation in 3D printing medical market. Finally, the numerical results indicate that there is one causal configuration (i.e., 1A) found to be sufficient for high user satisfaction for the perspectives of 3D printing suppliers and three configurations for the perspectives of 3D printing customers. In the perspectives of 3D printing suppliers, the combination of relationship marketing, innovation, and 3D printing perceived value is sufficient conditions causing high user satisfaction. However, there are three causal configurations (i.e., 1B, 2B, and 3B) found to be sufficient for high user satisfaction for the perspectives of 3D printing customers.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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