Modelling users' perception of the online real estate platforms in a digitally disruptive environment: An integrated KANO-SISQual approach. (October 2021)

• Record Type: Journal Article
• Authors: Ullah, Fahim; Sepasgozar, Samad M.E.; Shirowzhan, Sara; Davis, Steven
• Is Part Of: Telematics and informatics. Volume 63(2021)
• Publication Date: 2021-10
• Subjects: Real estate online platforms -- Smart real estate -- Users' perception -- KANO Model -- SISQual approach -- Technology acceptance model -- Real estate management; Telecommunication -- Periodicals; Computer networks -- Periodicals; Télécommunications -- Périodiques; Réseaux d'ordinateurs -- Périodiques; 384
• DOI: 10.1016/j.tele.2021.101660
• Languages: English
• ISSNs: 0736-5853

Abstract

Highlights: The reliability, accuracy, and credibility of the REOPs are most important for its users in a DDE. Graphical statistics, attractive website design, immersive and novel content attract REOPs users. Tracing user location, learning tutorials, and hyperlinks discourage REOPs users. Improved service, information, and systems quality can satisfy REOPs users in a DDE. Abstract: Global disruption and innovation are revolutionising many industries and creating a digitally disruptive environment (DDE); real estate is no exception. Real estate online platforms (REOPs) are getting more attention in the era of COVID-19, where the real estate businesses must run online, and the service users are pushed to a forced digital experience adoption. The users or consumers are not satisfied or happy with the current state of REOPs and often regret their decisions due to the poor quality of the web-based information provided on these REOPs. Based on a mixed approach of integrated KANO-SISQual, the current study develops a comprehensive smart real estate technology adoption model (SRETAM) to model the users' perception of the REOPs in DDE. Data is collected through a questionnaire survey from 407 Sydney based REOP users. A total of 31 key factors are identified by reviewing 256 articles vetted by 12 local real estate agents. The results highlight 19 factors to be very important to REOPs users: reliability, the accuracy of the information, and credibility of the online platforms are the top three important factors. The hypotheses' results show that all the SRETAM categories contribute equally to the users' behavioural intention to use the REOPs and the KANO categories are statistically different. For KANO categories, eight attractive features are identified: graphical statistics, familiar web technology, content structure, web design, immersive content, self-efficacy, information novelty, and presence of 3D interactive models. Displaying the users' location, learning tutorials, and hyperlinks to external sources on the web portals dissatisfy REOP users. The factors and their classifications can help the users get more features, verified, and transparent information for making better decisions in the DDE, whereas the REOP can enjoy more business due to increased service consumers. This can lay the foundation for transforming the traditional real estate sector into smart real estate in lines with industry 4.0 requirements in the DDE.