IDEAS home Printed from https://ideas.repec.org/a/spr/snbeco/v2y2022i3d10.1007_s43546-021-00191-1.html
   My bibliography  Save this article

Intelligent buildings with IoT systems using ML and HITL for indoor environmental control: an investigation of occupants’ adoption intent

Author

Listed:
  • Arunvel Thangamani

    (Indian Institute of Technology Madras)

  • L. S. Ganesh

    (Indian Institute of Technology Madras)

  • Anand Tanikella

    (Saint Gobain Research)

  • Meher Prasad Anumolu

    (Indian Institute of Technology Madras)

Abstract

Office spaces in Intelligent Buildings are equipped with Building Management Systems (BMSs) that use Internet of Things (IoT) with Machine Learning (ML) for saving energy while improving comfort for occupants. The Human-In-The-Loop (HITL) approach in such IoT-based systems has made it possible to empower occupants to set local zone comfort, and use personalized controls, such as blasts of cold or hot air, and lighting settings. However, prior literature shows that occupants engaging with such IoT-based indoor environmental control systems are uncertain and might pose challenges in commercial buildings. This paper discusses an investigation of factors that influence the intent of occupants to adopt such IoT systems that leverage ML and HITL for indoor environmental control. Customizing and extending the Technology Acceptance Model, this research incorporates additional constructs, namely trust, invasiveness, and energy savings propensity, to examine occupants’ intention to accept and engage with IoT-based BMSs quantitatively using multiple regression. The results suggest that perceived benefits, namely comfort, productivity and wellbeing, along with the perceived ease-of-use aspects, namely ease of zone movement, and convenience to access BMS, significantly influence adoption intent. The perceived risks, namely security, privacy and intrusiveness, are not statistically significant. Further, propensity to save energy negatively influences the relationship between perceived benefits and adoption intent. Based on the results of this study, IoT firms can identify potential early adopters of such IoT systems and services in office spaces, carve out value proposition elements, and take strategic decisions.

Suggested Citation

  • Arunvel Thangamani & L. S. Ganesh & Anand Tanikella & Meher Prasad Anumolu, 2022. "Intelligent buildings with IoT systems using ML and HITL for indoor environmental control: an investigation of occupants’ adoption intent," SN Business & Economics, Springer, vol. 2(3), pages 1-38, March.
    • Handle: RePEc:spr:snbeco:v:2:y:2022:i:3:d:10.1007_s43546-021-00191-1
    DOI: 10.1007/s43546-021-00191-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43546-021-00191-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s43546-021-00191-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rashiqa Abdul Salam & Khuram Pervez Amber & Naeem Iqbal Ratyal & Mehboob Alam & Naveed Akram & Carlos Quiterio Gómez Muñoz & Fausto Pedro García Márquez, 2020. "An Overview on Energy and Development of Energy Integration in Major South Asian Countries: The Building Sector," Energies, MDPI, vol. 13(21), pages 1-37, November.
    2. Kieran Mathieson, 1991. "Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior," Information Systems Research, INFORMS, vol. 2(3), pages 173-191, September.
    3. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    4. Mital, Monika & Chang, Victor & Choudhary, Praveen & Papa, Armando & Pani, Ashis K., 2018. "Adoption of Internet of Things in India: A test of competing models using a structured equation modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 339-346.
    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. Cristopher Siegfried Kopplin, 2021. "Two heads are better than one: matchmaking tools in coworking spaces," Review of Managerial Science, Springer, vol. 15(4), pages 1045-1069, May.
    2. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    3. Nistor, Cristian, 2013. "A conceptual model for the use of social media in companies," MPRA Paper 44224, University Library of Munich, Germany.
    4. Francisco Rejón-Guardia & Juán Sánchez-Fernández & Francisco Muñoz-Leiva, 2011. "Motivational Factors that influence the Acceptance of Microblogging Social Networks: The µBAM Model," FEG Working Paper Series 06/11, Faculty of Economics and Business (University of Granada).
    5. Kawsar Ahmad & Arifuzzaman Arifuzzaman & Abdullah Al Mamun & Junayed Md Khaled Bin Oalid, 2021. "Impact of consumer’s security, benefits and usefulness towards cashless transaction within Malaysian university student," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(2), pages 238-250, March.
    6. Xuechao Sui & Xianhui Geng, 2021. "Continuous usage intention to e-transaction cards in wholesale markets of agriproducts: empirical evidence from China," Future Business Journal, Springer, vol. 7(1), pages 1-13, December.
    7. Muhammad Ali & Syed Ali Raza & Chin-Hong Puah & Mohd Zaini Abd Karim, 2017. "Islamic home financing in Pakistan: a SEM-based approach using modified TPB model," Housing Studies, Taylor & Francis Journals, vol. 32(8), pages 1156-1177, November.
    8. Rahman Ummeh Habiba Faria Benteh & Zafar Muhammad Khubaib, 2020. "Factors Influencing Uber Adoption In Bangladesh And Pakistan," Open Economics, De Gruyter, vol. 3(1), pages 86-97, January.
    9. Müller-Seitz, Gordon & Dautzenberg, Kirsti & Creusen, Utho & Stromereder, Christine, 2009. "Customer acceptance of RFID technology: Evidence from the German electronic retail sector," Journal of Retailing and Consumer Services, Elsevier, vol. 16(1), pages 31-39.
    10. 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).
    11. Minseok Choi & Kyeongseok Han & Jeongil Choi, 2015. "The effects of product attributes and service quality of transportation card solutions on service user’s continuance and word-of-mouth intention," Service Business, Springer;Pan-Pacific Business Association, vol. 9(3), pages 463-490, September.
    12. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    13. Gao, Tao (Tony) & Rohm, Andrew J. & Sultan, Fareena & Pagani, Margherita, 2013. "Consumers un-tethered: A three-market empirical study of consumers' mobile marketing acceptance," Journal of Business Research, Elsevier, vol. 66(12), pages 2536-2544.
    14. Johannes Putzke & Detlef Schoder & Kai Fischbach, 2010. "Adoption of Mass-Customized Newspapers: An Augmented Technology Acceptance Perspective," Journal of Media Economics, Taylor & Francis Journals, vol. 23(3), pages 143-164.
    15. El Barachi, May & Salim, Taghreed Abu & Nyadzayo, Munyaradzi W. & Mathew, Sujith & Badewi, Amgad & Amankwah-Amoah, Joseph, 2022. "The relationship between citizen readiness and the intention to continuously use smart city services: Mediating effects of satisfaction and discomfort," Technology in Society, Elsevier, vol. 71(C).
    16. Banu Demirel & Ayça Kübra Hızarcı Payne, 2018. "Social Innovation Adoption Behavior: The Case of Zumbara," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 1-19, April.
    17. Yoon, Jeewhan & Vonortas, Nicholas S. & Han, SungWon, 2020. "Do-It-Yourself laboratories and attitude toward use: The effects of self-efficacy and the perception of security and privacy," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    18. Kamrath, Carolin & Rajendran, Srinivasulu & Nenguwo, Ngoni & Afari-Sefa, Victor & Broring, Stefanie, 2018. "Adoption behavior of market traders: an analysis based on Technology Acceptance Model and Theory of Planned Behavior," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(6), July.
    19. Taneja, Shilpa & Ali, Liaqat, 2021. "Determinants of customers’ intentions towards environmentally sustainable banking: Testing the structural model," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    20. Lombardi, Alessia & Carfora, Valentina & Cicia, Gianni & Del Giudice, Teresa & Lombardi, Pasquale & Panico, Teresa, 2017. "Exploring Willingness to Pay for QR Code Labeled Extra-Virgin Olive Oil: An Application of the Theory of Planned Behavior," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 8(01), pages 1-18, January.

    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:spr:snbeco:v:2:y:2022:i:3:d:10.1007_s43546-021-00191-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.