Determinants of business organization’s adoption of complex innovative product: A case of the intelligent IoT system for hog-raising

• Main Author: CAO, Jingguan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Complex innovative product; relative advantage; compatibility; result demonstrability; trialability; subjective norm; safety; perceived ease of use; perceived usefulness; Management Information Systems; Technology and Innovation
• Online Access: https://ink.library.smu.edu.sg/etd_coll/540; https://ink.library.smu.edu.sg/context/etd_coll/article/1538/viewcontent/GPBA_AY2018_DBA_Cao_Jingguan.pdf
• Institution: Singapore Management University

With the development of science and technology, various opportunities emerged for the application of complex innovative products. However, not all business organizations are willing to adopt complex innovative products although these products can improve efficiency and reduce costs of the organizations, because there are bound to be various problems in the early application of new technologies. Hence, it is important to find the key influencing factors for the acceptance of complex innovative products by business organizations. The Internet of Things (IoT) is a typical complex innovative product, and this dissertation takes the intelligent IoT system for hog-raising as a case to study the determinants of business organization’s adoption of complex innovative products. This dissertation aims to explore the antecedents of hog-raising firms’ adoption of the intelligent IoT system based on the technology acceptance model, innovation diffusion theory, and related literature. I propose that technological factors and social factors will influence the behavioral intention to adopt intelligent IoT systems for hog-raising. In terms of technological factors, I explore the influence of relative advantage, compatibility, result demonstrability, and trialability on the behavioral intention to adopt intelligent IoT systems for hog-raising based on the innovation diffusion theory. In terms of social factors, I investigate the influence of subjective norms and safety on the behavioral intention to adopt intelligent IoT systems for hog-raising. Furthermore, I try to tackle the mechanism behind the relationship based on the technology acceptance model. I argue that relative advantage, compatibility, result demonstrability, and trialability may promote perceived usefulness and further influence the behavioral intention to adopt intelligent IoT systems for hog-raising. Compatibility, result demonstrability, and trialability will promote perceived ease of use and further influence the behavioral intention to use intelligent IoT systems for hog-raising. Using survey data of 266 hog-raising firms in China, this dissertation tests the hypotheses proposed. The results suggest that relative advantage, result demonstrability, and trialability are positively associated with the behavioral intention to use intelligent IoT systems for hog-raising. The relative advantage, result demonstrability, and trialability of intelligent IoT systems for hog-raising will improve users’ perceived usefulness, and further facilitate their adoption intention. The result demonstrability and trialability of intelligent IoT systems for hog-raising will improve users’ ease of use, and further promote their behavioral intention to use the intelligent IoT systems. Furthermore, subjective norm and safety will promote the behavioral intention to use intelligent IoT systems for hog-raising. However, when including social factors, the positive impact of trialability is still significant, however, the positive influence of relative advantage and result demonstrability on the behavioral intention to use intelligent IoT systems for hog-raising becomes not significant anymore. This dissertation contributes to deepening the understanding of the diffusion of the Internet of Things in a special industry, namely, the hog-raising industry, which offer valuable insights into the development and upgrading of other traditional industry. This dissertation also helps to extend the technology acceptance model and innovation diffusion theory by integrating the two theories. Also, this dissertation offers references to promote the adoption of intelligent IoT systems.