The Role of the Influencer

The credibility of influencers and para-social interaction both relate positively to purchase intention (Sokolova & Kefi, 2020). The authors discuss how these factors relate to social and physical attractiveness, and compatible attitudes, based on four popular beauty influencers in France (Sokolova & Kefi, 2020). They note that compatible attitudes (homophily) relate to para-social interaction but show no evidence of positive relationships.

Killiann and McManus (2015, 539–549), explained how social media fit into a firm’s existing marketing communications strategy. They found that managers segregate social platforms into four categories: relationship management, newsgathering, creativity, and entertainment. As social platforms continue to develop in real estate, niche platforms are emerging. Platforms that were nonexistent two years ago now have millions of users (Killiann & McManus, 2015, 539–549). Real estate brand managers need to be adept at recognizing the strengths of different platforms and using these to further the customer-brand relationship in this very personal space (Killiann & McManus, 2015, 539–549).

Everyday consumer activities, especially online, are affected by corporate power. Search algorithms control accessible information, and bloggers and other opinion leaders influence consumption decisions through recommendations and product tests distributed across social media (Labrecque et al., 2013, 257–269). The concept of influence in social media environments as a type of control was studied by Labrecque et al. (2013, 257–269). These authors explore the intersection of real estate consumer behavior and digital media by clearly defining consumer power and empowerment via the internet and social media. Real estate consumers can change the way they browse online if they feel that giving out personal information might give companies too much power over them. Thus, the rise of the internet and the development of social media are signs of increased consumer power (Labrecque et al., 2013, 257–269). In this technologically advanced world, ordinary consumers can access large stores of information and influence their lives in commercial and other contexts.

Recalling Levitt’s (1960, 24–47) influential article “Business Myopia,” Smith, Drumright, and Gentile (2010, 4–11) see companies focused on the customer and ignore other stakeholders. They define customers and their needs narrowly and are oblivious to decision-making in the broader social context, where there are multiple stakeholders. The authors put forward a vision for marketing management that will broaden marketer views and engage multiple stakeholders in the process of value creation (Smith et al., 2010, 4–11).

The Future of Marketing

The growth of technology will continue to contribute to the theory and practice of marketing (Lee, 2017, 293–303). Big data represents a new technology paradigm for high volume, high velocity, and high variety data that can revolutionize real estate business operation across many industries (Müller et al., 2016, 289–302). At the same time, the incursion of marketing into a wide range of human activity will give rise to ethical issues. For example, access to data in social media; using big data; consumer segmentation; marketing to ethnic groups; and marketing to vulnerable communities (Kitchin, 2014, 1–41).

Finally, social media and big data will continue to play a substantial part in digital marketing to consumers, as marketers endeavor to understand consumer thinking and promote their products and services (Müller et al., 2016, 289–302). Consumers will not adopt an entirely passive role in this. Rather, consumer reaction will influence the feasibility of marketing particular products at specific prices (Lee, 2017, 293–303).

Alalwan et al. (2017, 1177–1190) review themes and trends in social media marketing from 144 articles, covering marketing and social media; electronic word of mouth; CRM; and firm brands and performance. Sources of user information, including user trust, perceived marketer credibility and reliability, along with user-marketer interactivity, are the primary focus of most social media studies (Aytekin & Demírl Demírli, 2017, 17–36). However, the authors comment that users’ perception of online marketing activity and their related behavior are difficult to measure accurately (Kitchin, 2014, 1–41). Therefore, factors influencing user reactions to marketing on social science platforms will remain the focus for future research (Alalwan et al., 2017, 1177–1190).

With the popularity of social media, real estate companies can readily and economically reach consumers. Big data 2.0 is driven by Web 2.0, which developed from the web technologies of the 1990s and social media. In doing so, it created a paradigm shift in organizational collaboration (Alalwan et al., 2017, 1177–1190). Unlike web analytics, which are mainly used for structured data, social media analytics analyze social media behavior. Understanding this behavior helps real estate companies target consumer segments, tailor products and services to consumers, and develop marketing campaigns (Müller et al., 2016, 289–302).

Lee (2017, 293–303) notes that as long as managers can exploit the data, there is potential for real estate companies to create new businesses, improve business operations, and develop new products and services, at the same time as maintaining cost savings and improving product and service quality. Personalized marketing is possible through analysis of shopper preferences. The challenges, however, are data quality and data security, and – from a consumer perspective – privacy (Lee, 2017, 293–303).

Big Data Analytics

The creation of data-driven research is engendering paradigm shifts across various disciplines (Kitchin, 2014, 1–41). Big data is continuously generated, and it produces massive, dynamic flows of diverse, fine-grained, and relational data. Kitchin (2014, 1–41) argues that big data challenges existing definitions of knowledge and social life.

Big data analytics offer a novel and complementary source of data and a methodology for data analysis (Müller et al., 2016, 289–302). However, the skills for data preparation and the use of analytical tools and criteria for cross-instrumental evaluation are necessary for data mining, machine-learning algorithms, neuro-linguistic programming techniques, and graphic visualization for the intuitive understanding of large data sets (Müller et al., 2016, 289–302).

The availability of methodologies impedes our understanding of real estate consumer thinking. However, decision makers must know the rationale behind various methods for examining and assessing markets from the perspective of consumers (Alalwan et al., 2017, 1177–1190). Big data raised the stakes in marketing through greater ability to discriminate among alternative approaches to real estate consumers. Nonetheless, there must be post-positivist insights that complement or overtake decisions indicated by positivist or big data research (Kitchin, 2014, 1–41). Callahan & Elliott (1996, 79–114) studied the metaphors of listening and conversation to the search for proper understanding of the significance of events. They conclude that free narrative is a valuable approach to our everyday understanding and of real-world behavior as clients are involved in discussions that concern their interests (Callahan & Elliott, 1996, 79–114).

Virtual Reality in Marketing

Beginning with science fiction, virtual reality (VR) can take the participant away from reality into another world where different measures of sensation and time are valid. VR has shown promise in various fields, including education, science, and engineering (Flavián et al., 2019, 547–560). In real estate marketing, it can catch the imagination of a client and convey a convincing message. Documenting the construction of a building can be a practical use of VR. That is because it is linked with a subsequent exploration of the significance of the architecture, and the inclusion of stereoscopic elements can form part of augmented reality (Berg & Vance, 2016, 1–17). But the production of thoughtful, impressive VR projects may lie beyond the resources of many marketing units. Brooks (1999, 16–27) describes VR as an encounter where the user is “effectively immersed in a responsive virtual world” with dynamic control over the viewpoint he or she takes within that world.

VR and mixed reality technology are examples of integrating physical and virtual objects at different levels, so that various devices provide hybrid experiences within the customer experience landscape (Flavián et al., 2019, 547–560). However, the boundary between virtual, augmented, and mixed reality technologies has not been established (Brooks, 1999, 16–27). Flavián et al. (2019, 547–560) propose a new taxonomy of technologies that integrate technological, psychological, and behavioral perspectives, which might add meaning to client experiences with VR.

The use of VR in B2B marketing has not been fully explored. The remaining deficits in our knowledge for implementing VR in society affect the post-purchase stage of the supplier-buyer relationship, especially regarding the level of workload stress (Boyd & Koles, 2019, 590–598). VR is also used in psychological therapy. Most research on this subject is related to the phenomenon of presence, and there is a theoretical consideration of the roles for attention as a mental process, and models of the virtual space (Boyd & Koles, 2019, 590–598). More needs to be learned regarding the relation between presence and emotional responses to virtual stimuli, as research on such responses could play an important role in developing new VR applications (Schuemie, 2001, 183–201). Yoon and Vargas (2014, 1043–1045) find that individual behaviors aligned with the predetermined traits of individual avatars in virtual environments could be accentuated with possible antisocial effects.

VR is a set of technologies that enable immersion in a world beyond reality and engagement in encounters that mimic participants’ interpretation of reality (Berg & Vance, 2016, 1–17). Despite their emphasis on the inherent complexity of the underlying technologies involved in VR, Berg and Vance (2016, 1–17) maintain constant attention to the value of the experience (Berg & Vance, 2016, 1–17).

Digital Marketing in Real Estate

The internet is the primary source of information for consumers, and digital marketing has allowed the real estate industry to reach the masses (Despinola, 2018). A study by Bankwest (2018) found that in the last five years, Australian real estate revenue increased by 5.4 percent to USD 16.3 billion. The daily work of a real estate agent depends on advertising and the following specific activities. An agency may use Search Engine Optimization, blogs, keyword research and video marketing; the agency may also use pay per click search engine marketing (SEM) advertisements, Google Adwords, social media Adwords with specific hashtags, or paid listings with real estate aggregators (Benjamin & Benjamin, 2013, 137–148). An agency may use email marketing, automatic messaging tools – Boost or HomeSpotter, for example. It may use Instagram for walk-throughs, open house and new listing photos, and Facebook for Lead Ads, events, testimonials, and industry news (Ullah & Sepasgozar, 2019). It may advertise on leading realty portals to generate verified and qualified leads in Multiple Listing Service (MLS) using an automatic and manual XML (Extensible Markup Language) system (Ullah et al., 2018, 3142).

Some agencies have found that the ROI in digital marketing in real estate has attracted real estate customers and associates through digital platforms (Ullah et al., 2018, 3142). They may find that the language of a marketed property creates an image for interested buyers and that the content of messages should be personalized, relevant, educational, authoritative, and backed by technical knowledge of marketing (Abelson & Chung, 2005, 265–281). An imaginative agent may initiate a virtual tour of a property under construction or use augmented reality to satisfy a client’s interest in a piece of residential real estate.

Digital technology continues to facilitate real estate marketing. To show the strength of this link, it is worthwhile reflecting on our movement away from routine advertising and automatic responses to a more thoughtful and imaginative approach to technology (Ashley & Tuten, 2015, 15–27).

Innovative Technologies

“Innovative technologies” refers to the shift from traditional real estate to “smart real estate” using smartphone technology, websites and social media-based online platforms, and the need for sustainable, user-centered real estate (Ullah, Sepasgozar, & Wang, 2018, 3142). They examine the adoption of disruptive technologies or innovations that create a new market with new values which overtake existing markets (Ullah, Sepasgozar, & Wang, 2018, 3142). The application of technologies showing in Figure 5.1, such as drones, IoT, clouds, software as a service (SaaS), big data, 3D scanning, wearable technologies, VR and augmented reality (AR), AI, and robotics should help real estate consumers gather as much information as possible and prevent regret over purchase decisions (Ullah, Sepasgozar, & Wang, 2018, 3142).

Although Australia is technologically advanced, Ullah, Sepasgozar, and Wang (2018, 3142) rank Australia behind the US and the UK in global technology adoption. The top three countries for technology adoption readiness are Singapore, Finland, and Sweden, respectively (Ullah, Sepasgozar & Wang, 2018, 3142). Among the 139 countries studied, the US ranks the highest on most criteria, followed by the UK and Australia, showing that the US, the UK, and Australia are leveraged to adopt and implement the latest technologies and likely to attract investment in online real estate. Ullah, Sepasgozar and Wang (2018, 3142) see “smart real estate” management as user-centered and sustainable, utilizing innovative technologies to achieve holistic benefits.

Information and Communications Technology (ICT) has already made its mark in the real estate industry, changing the nature of real estate agents’ work (Jones & Benjamin, 2013, 137–148). Social media platforms have also improved client access to real estate information (Ashley & Tuten, 2015, 15–27). Ullah and Sepasgozar (2019) suggest the adoption of new technologies such as 360° cameras for VR or AR (Ullah & Sepasgozar, 2019).

Disruptive Innovation

In Christensen’s (2018, 1043–1078) “disruptive innovation,” simplicity and accessibility enable a new product or idea to form in a complicated, high-cost market that eventually redefines the industry (Christensen et al., 2018, 1043–1078). However, new technologies can have either sustaining or disruptive effects on real estate companies, depending on the company and its fortunes in real estate marketing (Christensen et al., 2018, 1043–1078). The concept of disruptive technologies applies to cases where an innovation occupies a particular niche or proves efficient in such a way that elements in the industry rely on it to the point where existing markets are disrupted (Christensen et al., 2018, 1043–1078). New technologies, if not strategically approached and adequately embedded in the organizational structure, can erode the competitive position of brands and shrink their marketing edge.

Blockchain and the Internet of Things

The adoption of blockchain is an incremental innovation that can lead to substantial changes in real estate marketing. The gains from this technology may significantly reshape existing real estate marketing practices and improve established business processes. Six propositions suggested by Rejeb et al. (2020, 1–12) provide starting points for further research to identify enablers and barriers. They believe that blockchain technology: creates contemporary market structures by fostering disintermediation, helps combat click fraud, helps reinforce real estate consumers’ trust in brands, enhances privacy protection, empowers digital marketing security, and can enable creative loyalty programs. Disadvantages of this technology are that storing transactions is complicated and expensive, and cost and security burdens may outweigh the value of its marketing applications (Rejeb et al., 2020, 1–12). Furthermore, blockchain technology does not have a suitable governance structure, maintenance is expensive, and, where a “proof-of-work consensus protocol” is used, there is high energy consumption (Rejeb et al., 2020, 1–12).

Kibet’s (2019, 327–334) blockchain-based smart contract design aimed to make transactions shorter, more transparent, and more reliable, particularly regarding taxable income, reducing operational costs and obviating the need for middlemen. Nowinski and Kozma (2017) discuss the possible disruption of existing business models. Blockchain offers “data security, transparency and integrity, anti-tampering and anti-forgery, high efficiency, and low cost” (Zhu & Zhou, 2016, 1–11). Thus, it will be useful for data exchange where security is required, and it can work through authenticating traded goods and disintermediation.

IoT will cause real estate issues, especially if a property is already embedded in an arrangement or series of arrangements for internet connection. Yeo et al. (2014, 568–571) propose an “IC design in cloud” as a turnkey infrastructure for IoT development (Yeo et al., 2014, 568–571). IoT is a complex area where change is inevitable, and so are difficulties. It will benefit infrastructure, transport, industry and agriculture, and disability and healthcare, at the same time as challenging existing regulatory frameworks (Yeo et al., 2014, 568–571). Mainwaring (2017, 265–289) uses “provider network” to denote the different private and public sector actors providing “eObjects” and the associated system. At the same time, customers can be individuals, corporate entities, not-for-profit entities, or public agencies (Yeo et al., 2014, 568–571). Equipment, software, or services may be supplied by different entities, privately, or publicly. Manufacturers, assemblers, and distributors, as well as providers of software services and testers, enter the picture from a consumer point of view (Mainwaring, 2017, 265–289). Mainwaring and Hall (2019) cite evidence that IoT will be more vulnerable to interference and remote attacks than conventional connected computers. Harm is likely to emerge when a vulnerability is exploited, allowing access to controls of cars or industrial safety shutdown systems. Cybercrime, privacy, safety, security, and equal treatment are all matters of concern (Mainwaring & Hall, 2019).

With the exponential growth of network size, blockchain’s decentralized, autonomous capacities could solve some key security challenges associated with the cloud (Kshetri, 2017, 68–72). Blockchain can verify its information and transactions, and this can help trace insecurities in supply chains and deal with crises such as locating security and safety vulnerabilities (Kshetri, 2017, 68–72). However, Fernández-Caramés and Fraga-Lamas (2018) point to complex technical challenges related to blockchain and IoT, especially issues of scalability, security, and cryptographic requirements. Interoperability and standardization in the public interest will require compromise by all stakeholders. Decentralized ownership and international jurisdiction are major issues to be solved by research and collaboration with organizations and governments in relation to blockchain and IoT (Fernández-Caramés & Fraga-Lamas, 2018).

Santoro et al. (2017, 347–354) see “new disruptive technologies” in the context of IoT as demanding an internal knowledge management capacity coupled with a capacity for innovation. Amid of the various issues surrounding IoT, Santoro et al. (2017, 347–354) underline the real estate concern that a client who is put through an IoT arrangement for their home will need to ensure that the security and effectiveness of the network is guaranteed by all agencies involved.

Artificial Intelligence

In “Smart Factories,” under the umbrella concept of AI, intelligent robots, tools, IoT, and big data interact to achieve self-optimizing production (Benotsmane et al., 2019, 143–163). Fountaine, McCarthy and Saleh in 2019 wrote an article entitled Building the AI-Powered companies in the Harvard Business Review (Fountaine, McCarthy, & Saleh, 2019, 62–73). They argue that AI may need patient adaptation to succeed, but leaders must first understand AI and then motivate the workforce to change. Rather than being risk-averse, leaders must be experimental and adaptable (Fountaine, McCarthy, & Saleh, 2019, 62–73). Highlighting worker success with a new AI tool is one way to inspire other workers. Several initiatives with different time schedules may be useful: AI-assisted fraud detection, for example, may take several months, while AI-supported customer service may take years (Benotsmane et al., 2019, 143–163). A leader should be able to detect and discourage signs of resistance to AI initiatives. As innovation succeeds, a virtuous circle can spread AI throughout an organization, and individual decision making can flatten organizational hierarchies (Benotsmane et al., 2019, 143–163). In short, there are advantages in collaboration between humans and machines (Fountaine, McCarthy, & Saleh, 2019, 62–73).

In response to the Harvard Business Review article, Latshaw (2019, 72–78) as editor of the Corporate Real Estate Journal points to the enormous flood of data as a cause of company failure in adapting to AI, and not the technology itself. She argues that “AI is not about IT or cybersecurity, and corporate real estate (CRE) is not about real estate” (Latshaw, 2019, 72–78). Rather, AI is about core business strategy and support of the business; and CRE is in the business of customer service. Latshaw (2019, 72–78) quotes Michael Ford, Microsoft General Manager for Global Real Estate and Securities, who says that as “a data-driven culture,” Microsoft’s products and services pervasively utilize technology through “Artificial Intelligence, machine learning, augmented reality, IoT devices and much more.” Latshaw, (2019, 72–78) comments that CEOs who may not have Ford’s qualifications can still engage in data analysis and knowledge management. She notes, CRE already shares in data analytics aimed at transforming the workplace. Latshaw’s (2019, 72–78) suggestions for CEOs may be summarized in terms of alertness to changes in priorities and readiness to be involved in new business activities (Latshaw, 2019, 72–78).

Taffese (2016) explains that the real estate profession is responding to client demand for faster and more accurate property valuations. The author presents two AI valuation methods, Artificial Neural Networks (ANN) and Expert System (ES). Both methods have their advantages and disadvantages and can become a hybrid system. GeoInformation Neural System (GINS) integrates a Geographic Information System (GIS) technique with ANN modeling. ANN system’s reasoning is difficult to ascertain, and results are often tentative. However, a trend toward the use of AI for property valuation has already begun (Taffese, 2016).

Drones and Wearable Technologies

Drones described as “Paparazzi Aloft” capture images not attainable by a land-based camera, while “Panoptic Aloft” drones, which are operated by law enforcement agencies and potentially moral minorities within a community can transmit real-time voice (Clarke, 2014, 286–305). Clarke (2014, 286–305) shares concerns for privacy and individual rights in industry self-regulation of media, but these do not substantively contribute to regulating surveillance activities. For a real estate agency, there are advantages in obtaining drone images of a property, especially in augmented reality. However, given that community reaction to alleged abuse of the personal right to privacy would be very counterproductive, courteous deference to residents’ feelings is advisable.

Wearable wrist displays, wireless headsets, and technical lanyards allow ergonomic interaction in real-time. Przegalinska (2019), looking at the future of wearable technologies, considers the role of the smartphone in the business world. She sees noninvasive, holistic, and assistive devices as even displacing smartphones and tablets to sit unobtrusively on the person with definite economic value to business. One criterion for their future success might be that they enhance the value of concentration on tasks rather than relegating staff to routine but trivial work (Przegalinska, 2019).

Augmented and Virtual Reality; 3D Scanning

Augmented reality (AR) enables access to a space where, through a camera or video, graphic visualization can increase the perception of reality around the operator in real-time (Rocha, 2016). AR combines real and virtual imagery; it is interactive in real-time and takes 3D form (Rocha, 2016). In business terms, augmented reality is considered any product that adds to a view of reality (van Kleef et al., 2010, 1–36).

With the concepts of AR and WR in mind, real estate circles have turned to available technologies – and even emerging technologies – that will be able to provide the content and processing necessary to bring their expectations into forms that appeal to consumers (Rocha, 2016). This is not only to attract sales but also to demonstrate the broader concern of the industry for proper solutions to problems that arise in real estate. When an online US survey conducted in 2017 asked respondents about any the choice of their current home, 51 percent admitted to having regrets (Trulia, 2017). This is not the result that a real estate practitioner wants to hear from clients. They are not only after gains from advertising and routine real estate tours of properties; they want to know that they are trusted for sincerity and expertise as they work on the client’s behalf (Trulia, 2017). Thus, out of a sense of responsibility to the client, attention to existing and developing resources is justified. Mobile AR advertising can also take place in the viewer’s environment, and mixed enhanced reality engages viewers with local information and instructions (Mathew, 2015). Aslan, Çetin, and Özbilgin (2019, 407–414) projecting hardware, software, and advertising opportunities to 2022 in the AR market, see giants such as Apple, Google, and Microsoft using augmented reality to boost traditional business and open doors to new markets.

AR and VR are developing technologies, where concepts run ahead of the actual adequacy of scanning and projection devices. In the case of VR, a practical documentary will not compare to the masterpieces of science fiction cinema (Rocha, 2016). VR, however, can be valuable in tracing the future development of high-rise dwellings through the stages of construction, so the client can see the gain from paying a deposit for an off-the-plan apartment after completion (van Kleef et al., 2010, 1–36). AR adds a designed 3D model or other sensory elements by a mobile device to the real-world (Rauschnabel & Ro, 2016, 123–148). Although it is expensive, a deposit can detect flaws in the way ducts and pipes are laid out in office ceilings. Clients can visualize a project without being on-site (Rauschnabel & Ro, 2016, 123–148). Biljecki et al. (2015, 2842–2889) explain that many 3D city models cannot be listed, not only because of the absence of technical information but because of fuzzy images, ambiguous terminology, and inadequate 3D environmental information. Their descriptive inventory of city models is intended for stakeholders in the geospatial industry, such as companies and national mapping agencies. This may serve as a reminder of the potentially broad nature of research supporting the real estate industry (Biljecki et al., 2015, 2842–2889). Urban planning is another area which touches on the real estate industry. Urban planning involves consultation and interaction, where geo-virtual environment visualization could serve as a spatial planning communication tool (Kibria et al., 2008, 379–395).

In stratified urban architecture, database management systems (DBMS) are important in GIS to ensure the consistency of spatial and alphanumerical data in one integrated environment (Zlatanova, & Stoter, 2006, 155–180). Wang et al. (2014, 453–476) use building information modeling (BIM) with an AR tool to enhance architectural visualization in a building life cycle. The system allows designers to place a virtual building scheme in a physical environment and provides owners and real estate agents with an interactive experience (Wang et al., 2014, 453–476). Felli et al. (2018) introduce 360⁰ cameras and Mobile Laser Measurement systems that record building data during construction that occupants can use later. This study uses smart data collection technologies for an innovative field experiment where 360-degree cameras and mobile laser measurement (MLM) collect data from a case study building. Buyers were shown 3D videos, models, and visualizations of construction quality, workmanship, and defects in real-time to increase their purchase confidence (Felli et al., 2018). Poushneh (2018, 169–176) finds that as well as augmentation quality, customers value being able to control access to their personal information.

Putting augmented or virtual reality applications into practice quickly becomes a matter of finding and utilizing available technologies. Zlatanova et al. (2002, 71–80) notes that various software can cope with the description of spatial objects, complex analysis, and 3D visualization. However, more advanced tools to represent the 3D world are needed, and 3D geographic information system (GIS) warrants more research. They describe software packages and 3D case studies carried out in Oracle and MicroStation, 3D GIS research issues in 3D structure, and 3D topology (Zlatanova et al., 2002, 71–80).

Doctoral research by Kukko (2013) on mobile laser scanning is valuable as a resource on the background and potential of such topographical scanning tools. Urey et al. (2013) explain how the mobile pico-projector equipped with a microelectromechanical (MEMS) scanner can provide a stereoscopic display system with 3D and interactive AR. In addition, handheld and wearable smart devices enable AR hypermedia print advertisements which can superimpose virtual hyperlinked 2D images over traditional print advertisements. Consumer response found this informative and effective (Yaoyuneyong et al., 2016, 16–30).

A System Dynamic Model for Technology Adoption

Ullah and Sepasgozar (2019) present a system dynamic model for technology adoption based on the quality of the systems, information, and service of real estate websites and their perceived ease of use. The model was based on a literature review on real estate management and information systems or websites (Ullah & Sepasgozar, 2019).

The real estate sector comprises 20 percent of the Australian construction industry, and with its IT orientation tends to a high rate of technological adoption (Despinola, 2018). Factors such as website perceived-usefulness, user-satisfaction and behavioral-intention-to-use have been included in a conceptual system dynamic model of customer appeal with various constituents derived from published literature along with suggestions for future improvements (Mahalaxmi & Ranjith, 2016, 332–338). The model may have value for website managers and real estate agents, suggesting new ideas for clients and incorporation of the latest technologies in the business. For example, using 360° cameras for photographs, video, and virtual reality (Ullah & Sepasgozar, 2019). The conceptual model is a growing synthesis of real estate technology adoption and customer perception, which can be validated using real-life data from clients and real estate agents (Ullah & Sepasgozar, 2019).

Wofford and Thrall (1997, 177–201) show how familiarity with GIS and other information technologies influence thinking on real estate issues and assist in real estate problem-solving. Applying this inductive logic to real estate will probably impart professional skills and a definite competence in knowing how and where to apply the range of technological assets available (Wofford & Thrall, 1997, 177–201).