{"title":"End-users’ acceptance of ’X as a Service’: Evidence from agriculture 4.0","authors":"","doi":"10.1016/j.cie.2024.110524","DOIUrl":null,"url":null,"abstract":"<div><p>With the rapid advancement of information technology, a new service model known as X as a Service has emerged. X can represent diverse resources such as platforms, infrastructure, farming, mobility, security, and more, allowing users to meet their needs flexibly and cost-effectively. The successful application of X as a Service heavily depends on end-users’ acceptance. This study explored the motivation factors for X as a Service based on the evidence from adopting Farming as a Service in Agriculture 4.0 among farmers in Northeastern China. We provided a theoretical framework for Farming as a Service adoption behavior, covering factors including personalization, perceived enjoyment, functionality, perceived risk, financial consequences, and perceived network externality. The effectiveness of the research model was assessed and validated through a two-stage procedural approach, utilizing partial least squares structural equation modeling. Results revealed that our proposed acceptance model for Farming as a Service exhibited a good model fit, accounting for 84.4 % of the variance in adoption intentions. Research findings highlighted that perceived network externality and functionality were the most influential factors in determining users’ adoption intentions for Farming as a Service. Conversely, perceived risk emerged as a significant negative factor influencing adoption. Furthermore, financial consequences, perceived enjoyment, and personalization also played crucial roles as determinants of user adoption. These findings offered valuable insights for service providers to improve their products, services, and marketing strategies.</p></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":6.7000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360835224006454","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
With the rapid advancement of information technology, a new service model known as X as a Service has emerged. X can represent diverse resources such as platforms, infrastructure, farming, mobility, security, and more, allowing users to meet their needs flexibly and cost-effectively. The successful application of X as a Service heavily depends on end-users’ acceptance. This study explored the motivation factors for X as a Service based on the evidence from adopting Farming as a Service in Agriculture 4.0 among farmers in Northeastern China. We provided a theoretical framework for Farming as a Service adoption behavior, covering factors including personalization, perceived enjoyment, functionality, perceived risk, financial consequences, and perceived network externality. The effectiveness of the research model was assessed and validated through a two-stage procedural approach, utilizing partial least squares structural equation modeling. Results revealed that our proposed acceptance model for Farming as a Service exhibited a good model fit, accounting for 84.4 % of the variance in adoption intentions. Research findings highlighted that perceived network externality and functionality were the most influential factors in determining users’ adoption intentions for Farming as a Service. Conversely, perceived risk emerged as a significant negative factor influencing adoption. Furthermore, financial consequences, perceived enjoyment, and personalization also played crucial roles as determinants of user adoption. These findings offered valuable insights for service providers to improve their products, services, and marketing strategies.
期刊介绍:
Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.