IDEAS home Printed from https://ideas.repec.org/a/sae/vision/v27y2023i4p431-442.html
   My bibliography  Save this article

A Consumer-Centric Paradigm Shift in Business Environment with the Evolution of the Internet of Things: A Literature Review

Author

Listed:
  • Sudesh Sheoran
  • Sanket Vij

Abstract

This study attempts to study the evolution of the Internet of Things (IoT) and its implications on the business environment in terms of understanding consumer behaviour and enhancing customer satisfaction through a literature review. A literature search is carried out focussing on the application of IoT for capturing consumer behaviour and enhancing customer experience and satisfaction. NVivo is used to identify the themes of the selected studies and cluster them based on the closeness of themes. It is found that the increasing quest for customer centricity and sustainability in an ever-changing technology environment have made businesses realize the potential benefits of IoT in terms of differentiation and competitive advantage. The perceived benefits influence IoT acceptance and customer satisfaction. However, the perceived risk associated with IoT in terms of privacy and security is a significant challenge for businesses. The future of IoT is based on how businesses are going to mitigate this challenge. While most of the studies suggest frameworks concerning IoT adoption and customer satisfaction in particular sectors or products, this study is unique in a way that it summarizes those studies and gives a brief view of IoT adoption to enhance customer satisfaction across different sectors, products and services.

Suggested Citation

  • Sudesh Sheoran & Sanket Vij, 2023. "A Consumer-Centric Paradigm Shift in Business Environment with the Evolution of the Internet of Things: A Literature Review," Vision, , vol. 27(4), pages 431-442, August.
  • Handle: RePEc:sae:vision:v:27:y:2023:i:4:p:431-442
    DOI: 10.1177/09722629211033944
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/09722629211033944
    Download Restriction: no

    File URL: https://libkey.io/10.1177/09722629211033944?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. YU, Jie & Subramanian, Nachiappan & Ning, Kun & Edwards, David, 2015. "Product delivery service provider selection and customer satisfaction in the era of internet of things: A Chinese e-retailers’ perspective," International Journal of Production Economics, Elsevier, vol. 159(C), pages 104-116.
    2. Sang-Oh Shim & KyungBae Park & SungYong Choi, 2017. "Innovative Production Scheduling with Customer Satisfaction Based Measurement for the Sustainability of Manufacturing Firms," Sustainability, MDPI, vol. 9(12), pages 1-12, December.
    3. Zhiting Song & Yanming Sun & Jiafu Wan & Lingli Huang & Jianhua Zhu, 2019. "Smart e-commerce systems: current status and research challenges," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 221-238, June.
    4. Verhoef, Peter C. & Stephen, Andrew T. & Kannan, P.K. & Luo, Xueming & Abhishek, Vibhanshu & Andrews, Michelle & Bart, Yakov & Datta, Hannes & Fong, Nathan & Hoffman, Donna L. & Hu, Mandy Mantian & No, 2017. "Consumer Connectivity in a Complex, Technology-enabled, and Mobile-oriented World with Smart Products," Journal of Interactive Marketing, Elsevier, vol. 40(C), pages 1-8.
    5. Ni Li & Minghui Sun & Zhuming Bi & Zeya Su & Chao Wang, 2014. "A new methodology to support group decision-making for IoT-based emergency response systems," Information Systems Frontiers, Springer, vol. 16(5), pages 953-977, November.
    6. Violeta Sima & Ileana Georgiana Gheorghe & Jonel Subić & Dumitru Nancu, 2020. "Influences of the Industry 4.0 Revolution on the Human Capital Development and Consumer Behavior: A Systematic Review," Sustainability, MDPI, vol. 12(10), pages 1-28, May.
    7. Shin, Jungwoo & Park, Yuri & Lee, Daeho, 2018. "Who will be smart home users? An analysis of adoption and diffusion of smart homes," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 246-253.
    8. Yan, Yuwei & Huang, Chuanchao & Wang, Qian & Hu, Bin, 2020. "Data mining of customer choice behavior in internet of things within relationship network," International Journal of Information Management, Elsevier, vol. 50(C), pages 566-574.
    9. Maria Tsourela & Dafni-Maria Nerantzaki, 2020. "An Internet of Things (IoT) Acceptance Model. Assessing Consumer’s Behavior toward IoT Products and Applications," Future Internet, MDPI, vol. 12(11), pages 1-23, November.
    10. Alaa Shoukry & Fares Aldeek, 2020. "Attributes prediction from IoT consumer reviews in the hotel sectors using conventional neural network: deep learning techniques," Electronic Commerce Research, Springer, vol. 20(2), pages 223-240, June.
    11. Wei Zhou & Selwyn Piramuthu, 2015. "Information Relevance Model of Customized Privacy for IoT," Journal of Business Ethics, Springer, vol. 131(1), pages 19-30, September.
    12. Thomas P. Novak & Donna L. Hoffman, 2019. "Relationship journeys in the internet of things: a new framework for understanding interactions between consumers and smart objects," Journal of the Academy of Marketing Science, Springer, vol. 47(2), pages 216-237, March.
    13. Guoying Lin & Yuyao Yang & Feng Pan & Sijian Zhang & Fen Wang & Shuai Fan, 2019. "An Optimal Energy-Saving Strategy for Home Energy Management Systems with Bounded Customer Rationality," Future Internet, MDPI, vol. 11(4), pages 1-16, April.
    14. Sarah Cheah & Shenghui Wang, 2017. "Big data-driven business model innovation by traditional industries in the Chinese economy," Journal of Chinese Economic and Foreign Trade Studies, Emerald Group Publishing Limited, vol. 10(3), pages 229-251, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Delgosha, Mohammad Soltani & Hajiheydari, Nastaran & Talafidaryani, Mojtaba, 2022. "Discovering IoT implications in business and management: A computational thematic analysis," Technovation, Elsevier, vol. 118(C).
    2. Attié, Elodie & Meyer-Waarden, Lars, 2022. "The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy ca," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Lucia-Palacios, Laura & Pérez-López, Raúl, 2021. "Effects of Home Voice Assistants' Autonomy on Instrusiveness and Usefulness: Direct, Indirect, and Moderating Effects of Interactivity," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 41-54.
    4. Lars Meyer-Waarden & Julien Cloarec, 2022. "“Baby, you can drive my car”: Psychological antecedents that drive consumers’ adoption of AI-powered autonomous vehicles," Post-Print hal-03385891, HAL.
    5. Manis, K.T. & Madhavaram, Sreedhar, 2023. "AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues," Journal of Business Research, Elsevier, vol. 157(C).
    6. Sojung Kim & Henri Christiaans & Joon Sang Baek, 2019. "Smart Homes as Product-Service Systems: Two Focal Areas for Developing Competitive Smart Home Appliances," Service Science, INFORMS, vol. 11(4), pages 292-310, December.
    7. Rust, Roland T., 2020. "The future of marketing," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 15-26.
    8. Elodie Attié & Lars Meyer-Waarden, 2022. "The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy ca," Post-Print hal-04065165, HAL.
    9. Guerreiro, João & Loureiro, Sandra Maria Correia, 2023. "I am attracted to my Cool Smart Assistant! Analyzing Attachment-Aversion in AI-Human Relationships," Journal of Business Research, Elsevier, vol. 161(C).
    10. László SEER, 2020. "Toward A Threshold Model Of Consumer Autonomy For Human-Smart System Interactions: A Qualitative Study," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 15, pages 57-69, June.
    11. Lu, Yang & Papagiannidis, Savvas & Alamanos, Eleftherios, 2018. "Internet of Things: A systematic review of the business literature from the user and organisational perspectives," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 285-297.
    12. Rokonuzzaman, Md & Kim, Kyoungmi (Kate) & Dugar, Kranti Kumar & Fox, Jennine, 2022. "What makes an object smart? Conceptualization, development, and validation of a scale to measure the Smartness of a Thing (SoT)," Journal of Business Research, Elsevier, vol. 141(C), pages 337-354.
    13. Liang, Yongheng & Xu, Qian & Jin, Liyin, 2021. "The effect of smart and connected products on consumer brand choice concentration," Journal of Business Research, Elsevier, vol. 135(C), pages 163-172.
    14. Chiara Bartoli, 2022. "Consumer self-concept and digitalization: what does this mean for brands?," Italian Journal of Marketing, Springer, vol. 2022(4), pages 419-437, December.
    15. Meyer-Waarden, Lars & Cloarec, Julien, 2022. "“Baby, you can drive my car”: Psychological antecedents that drive consumers’ adoption of AI-powered autonomous vehicles," Technovation, Elsevier, vol. 109(C).
    16. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    17. Inyoung Park & Jieon Lee & Jungwoo Nam & Yuri Jo & Daeho Lee, 2022. "Which networking strategy improves ICT startup companies' technical efficiency?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2434-2443, September.
    18. Cai, Ya-Jun & Lo, Chris K.Y., 2020. "Omni-channel management in the new retailing era: A systematic review and future research agenda," International Journal of Production Economics, Elsevier, vol. 229(C).
    19. Yi Sun & Shihui Li & Lingling Yu, 2022. "The dark sides of AI personal assistant: effects of service failure on user continuance intention," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 17-39, March.
    20. Feng, Wei & Sun, Shujun & Yuan, Hang, 2023. "Research on the efficiency of factor allocation in the pilot free trade zones," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 727-745.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:vision:v:27:y:2023:i:4:p:431-442. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.