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Smart Digital Marketing Capabilities for Sustainable Property Development: A Case of Malaysia

Author

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  • Sheen Low

    (Department of Construction Management and Property, Faculty of Built Environment, University of New South Wales (UNSW), Kensington, Sydney NSW 2052, Australia)

  • Fahim Ullah

    (Department of Construction Management and Property, Faculty of Built Environment, University of New South Wales (UNSW), Kensington, Sydney NSW 2052, Australia)

  • Sara Shirowzhan

    (Department of Construction Management and Property, Faculty of Built Environment, University of New South Wales (UNSW), Kensington, Sydney NSW 2052, Australia)

  • Samad M. E. Sepasgozar

    (Department of Construction Management and Property, Faculty of Built Environment, University of New South Wales (UNSW), Kensington, Sydney NSW 2052, Australia)

  • Chyi Lin Lee

    (Department of Construction Management and Property, Faculty of Built Environment, University of New South Wales (UNSW), Kensington, Sydney NSW 2052, Australia)

Abstract

Digital tools and marketing have been widely adopted in various industries throughout the world. These tools have enabled companies to obtain real-time customer insights and create and communicate value to customers more effectively. This study aims at understanding the principles and practices of sustainable digital marketing in the Malaysian property development industry by investigating the extent to which digital marketing has been adopted, the impediments to its adoption, and the strategies to improve digital capabilities for the local context. Digital marketing theories, practices, and models from other industries are adopted and applied to the local property development industry to lay the foundation for making it smart and sustainable. This paper proposes a marketing technology acceptance model (MTAM) for digital marketing strategy and capability development. The key factors used in the model are ease of use, perceived usefulness, perceived cost, higher return, efficiency, digital service quality, digital information quality, digital system quality, attitude towards use, and actual use. The model and hypothetical relationships of critical factors are tested using structural modeling, reliability, and validity techniques using a sample of 279 Malaysian property development sector representatives. A quantitative approach is adopted, using an online questionnaire tool to investigate the behavior of respondents on the current digital marketing practices and capabilities of Malaysian property development companies. The results show that the sample property development companies are driven by the benefit of easily obtaining real-time customer information for creating and communicating value to customers more effectively through the company brand. Further strategies, such as creating real-time interactions, creating key performance indicators to measure digital marketing, personalization, and encouraging innovation in digital marketing are most preferred by local professionals. An adoption framework is provided based on the reviewed models and results of the current study to help transform the Malaysian property development sector into a smart and sustainable property development sector by facilitating the adoption of digital technologies. The results, based on real-time data and pertinent strategies for improvement of the local property sector, are expected to pave the way for inducing sustainable digital marketing trends, enhancing capabilities, and uplifting the state of the property development sector in developing countries.

Suggested Citation

  • Sheen Low & Fahim Ullah & Sara Shirowzhan & Samad M. E. Sepasgozar & Chyi Lin Lee, 2020. "Smart Digital Marketing Capabilities for Sustainable Property Development: A Case of Malaysia," Sustainability, MDPI, vol. 12(13), pages 1-40, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:13:p:5402-:d:380160
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    2. Le Tung Bach, 2023. "The behavioral intention to adopt Proptech services in Vietnam real estate market," Papers 2312.06994, arXiv.org.
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    5. Jin, Keyan & Zhong, Ziqi & Zhao, Elena Yifei, 2024. "Sustainable digital marketing under big data: an AI random forest model approach," LSE Research Online Documents on Economics 121402, London School of Economics and Political Science, LSE Library.
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