What Drives IoT-Based Smart Pet Appliances Usage Intention? The Perspective of the Unified Theory of Acceptance and Use of Technology Model.
DOI:
https://doi.org/10.9781/ijimai.2024.03.001Keywords:
Brand Trust, Internet of things, Perceived Value, Perceived Enjoyment, Smart Pet Appliances, Unified Theory of Acceptance and Use of Technology, Use IntentionAbstract
The advancement of IOT (Internet of Things) has facilitated the development of smart pet appliances, and the market for these products has growing rapidly, this study seeks to identify key factors for pet owner adoption of “smart” pet appliances. The Unified Theory of Acceptance and Use of Technology (UTAUT) a wellestablished model in the field of IOT research is used as the main framework, integrating brand trust, perceived value and perceived enjoyment as the basis for hypothesis formulation and testing based on data collected through questionnaires distributed through online social platforms. Reliability analysis, validity analysis and structural equation model analysis were carried out through confirmatory factor analysis to test the variables and research hypotheses. Results for the UTAUT indicate that effort expectancy has a direct impact on performance expectancy, while performance expectancy, effort expectancy and facilitating condition all have a positive impact on intention. While social influence does not directly or significantly affect use intention, it can indirectly affect intention through perceived value and perceived enjoyment. Brand trust does not have a significant impact on use intention, but can indirectly affect use intention through perceived value. This study further compares user age and number of smart pet home appliances owned to better understand the impact of demographic factors. Findings indicate that, for users under the age of 30, effort expectancy has no significant impact on use intention, while brand trust has no significant impact on perceived value among users over 30. Among the research results based on age as a basis, the impact of hardships in the ethnic group in the age of 30 is not significant, nor do facilitating conditions or perceived value have significant impact on use intention. For users with one smart pet device at home, neither favorable conditions not perceived value have significant impact on use intention, while for users with two smart pet devices, perceived enjoyment does not significantly impact use intention. These finding have potential reference value for future related research in the IOT or smart pet home appliance research field.
Downloads
References
OMDIA. “Omdia report finds purpose-driven smart homes will lead to a market size of $178bn in 2025.” Accessed: Oct. 1, 2022. [Online]. Available: https://omdia.tech.informa.com/pr/2021-sep/omdia-reportfinds-purposedriven-smart-homes-will-lead-to-a-market-size-of-178bnin-2025
LnData-Taiwan. “[Data Feature] Pet Economy Takes Off!” Accessed: Jul. 1, 2023. [Online]. Available: https://lndata-taiwan.medium.com/pettrends-report-2023-13c721720cb8.
Q. Su, Y. Liu, and H. Wu, “Smart Pet Feeding Device Based on Single Chip Microcomputer,” Journal of Physics: Conference Series, vol. 1885, pp. 052032, 2021, doi: 10.1088/17426596/1885/5/052032.
M. I. C. Institute (MIC). “Pet consumer survey 1: 51-55 year olds are the key target market for pet industry, while 26-35 year olds are the biggest users of pet technology products” is a commonly used translation in Taiwan.” Accessed: Jul. 1, 2023. [Online]. Available: https://mic.iii.org.tw/news.aspx?id=574&List=1
PChome Online. “Smart pet care” is becoming a trend! PChome 24h Shopping’s smart pet appliances have seen a whopping 75% surge in performance, and the pet industry is growing against the trend, presenting a great business opportunity for pet lovers.” Accessed: Jul. 1, 2023. [Online]. Available: https://corp.pchome.tw/
W. B. Arfi, I. B. Nasr, T. Khvatova, and Y. B. Zaied, “Understanding acceptance of eHealthcare by IoT natives and IoT immigrants: An integrated model of UTAUT, perceived risk, and financial cost,” Technological Forecasting and Social Change, vol. 163, pp. 120437, 2021, doi: 10.1016/j.techfore.2020.120437
W. Lee and S. Shin, “An empirical study of consumer adoption of Internet of Things services,” International Journal of Engineering and Technology Innovation, vol. 9, no. 1, pp. 1-11, 2019.
A. Abushakra and D. Nikbin, “Extending the UTAUT2 model to understand the entrepreneur acceptance and adopting internet of things (IoT),” in Knowledge Management in Organizations: 14th International Conference, Zamora, Spain, pp. 339-347, 2019.
K. Nikolopoulou, V. Gialamas, and K. Lavidas, “Habit, hedonic motivation, performance expectancy and technological pedagogical knowledge affect teachers’ intention to use mobile internet,” Computers and Education Open, vol. 2, pp. 100041, 2021, doi: 10.1016/j.caeo.2021.100041.
N. Shaw and K. Sergueeva, “The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value,” International journal of information management, vol. 45, pp. 44-55, 2019, doi: 10.1016/j.ijinfomgt.2018.10.024.
K. Pitchayadejanant, “Intention to use of smart phone in Bangkok extended UTAUT model by perceived value,” in Proceedings of the International conference on management, pp. 160-172, 2011.
S. Alwahaishi and V. Snásel, “Acceptance and use of information and communications technology: a UTAUT and flow based theoretical model,” Journal of technology management & innovation, vol. 8, no. 2, pp. 61-73, 2013, doi: 10.4067/S0718-27242013000200005
J. Xie, L. Ye, W. Huang, and M. Ye, “Understanding FinTech platform adoption: impacts of perceived value and perceived risk,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 16, no. 5, pp. 1893-1911, 2021, doi: 10.3390/jtaer16050106.
S. Kim, “Smart pet care system using internet of things,” International Journal of Smart Home, vol. 10, no. 3, pp. 211-218, 2016, doi: 10.14257/ijsh.2016.10.3.21.
K. Jadhav, G. Vaidya, A. Mali, V. Bankar, M. Mhetre, and J. Gaikwad, “IoT based automated fish feeder,” in 2020 International Conference on Industry 4.0 Technology, Pune, India, pp. 90-93, 2020, doi: 10.1109/I4Tech48345.2020.9102682.
M. A. Hidayat and S. Jayakrista, “Smart Pet Feeder on Cat Food Portions Using Mamdani’s Fuzzy Logic Inference System Method,” Journal of Computer Engineering, Electronics and Information Technology, vol. 2, no. 1, pp. 9-20, 2023.
Y. Quiñonez, C. Lizarraga, R. Aguayo, and D. Arredondo, “Communication architecture based on IoT technology to control and monitor pets feeding,” Journal of Universal Computer Science, vol. 27, no. 2, pp. 190-207, 2021, doi: 10.3897/jucs.65094.
P. Aashish. “What Is Pet Tech? - Use Cases, Examples, & Future.Stay Ahead with Feedough.” Accessed: Oct. 1, 2022. [Online]. https://www.feedough.com/pet-tech-definition-use-cases-examples-future/
W. Gu, P. Bao, W. Hao, and J. Kim, “Empirical examination of intention to continue to use smart home services,” Sustainability, vol. 11, no. 19, pp. 5213, 2019, doi: 10.3390/su11195213.
M. Kim and B. R. Choi, “The impact of privacy control on users’ intention to use smart home internet of things (IoT) services,” Asia Marketing Journal, vol. 24, no. 1, pp. 29-38, 2022, doi: 10.53728/2765-6500.1586.
A. Shuhaiber and I. Mashal, “Understanding users’ acceptance of smart homes,” Technology in Society, vol. 58, pp. 101110, 2019.
Y. Chen and M. Elshakankiri, “Implementation of an IoT based pet care system,” in 2020 Fifth International Conference on Fog and Mobile Edge Computing, Paris, France, 2020, pp. 256-262, doi: 10.1109/FMEC49853.2020.9144910.
V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,” MIS quarterly, vol. 27, no. 3, pp. 425-478, 2003, doi: 10.1016/j.techsoc.2019.01.003.
L. Ferreira, T. Oliveira, and C. Neves, “Consumer’s intention to use and recommend smart home technologies: The role of environmental awareness,” Energy, vol. 263, pp. 125814, 2023.
S. F. Hussin, M. F. Abdollah, and I. B. Ahmad, “Acceptance of IoT Technology for Smart Homes: A Systematic Literature Review,” in International Conference on Information Systems and Intelligent Applications, pp. 187-202, 2023, doi: 10.1007/978-3-031-16865-9_16.
W. B. Arfi, I. B. Nasr, G. Kondrateva, and L. Hikkerova, “The role of trust in intention to use the IoT in eHealth: Application of the modified UTAUT in a consumer context,” Technological Forecasting and Social Change, vol. 167, pp. 120688, 2021, doi: 10.1016/j.techfore.2021.120688.
H. J. Kang, J. Han, and G. H. Kwon, “The Acceptance Behavior of Smart Home Health Care Services in South Korea: An Integrated Model of UTAUT and TTF,” International Journal of Environmental Research and Public Health, vol. 19, no. 20, pp. 13279, 2022, doi: 10.3390/ijerph192013279.
H. Sequeiros, T. Oliveira, and M. A. Thomas, “The impact of IoT smart home services on psychological well-being,” Information Systems Frontiers, vol. 24, pp. 1009-1026, 2022, doi: 10.1007/s10796-021-10118-8.
B. A. Akinnuwesi et al., “A modified UTAUT model for the acceptance and use of digital technology for tackling COVID-19,” Sustainable Operations and Computers, vol. 3, pp. 118-135, 2022, doi: 10.1016/j.susoc.2021.12.001.
P. S. Ring and A. H. Van de Ven, “Developmental processes of cooperative interorganizational relationships,” Academy of management review, vol. 19, no. 1, pp. 90-118, 1994, doi: 10.2307/258836.
P. M. Doney and J. P. Cannon, “An examination of the nature of trust in buyer–seller relationships,” Journal of marketing, vol. 61, no. 2, pp. 35-51, 1997, doi: /10.2307/1251829.
M. S. Featherman and P. A. Pavlou, “Predicting e-services adoption: a perceived risk facets perspective,” International journal of humancomputer studies, vol. 59, no. 4, pp. 451-474, 2003, doi: 10.1016/S1071- 5819(03)00111-3.
S. Cannizzaro, R. Procter, S. Ma, and C. Maple, “Trust in the smart home: Findings from a nationally representative survey in the UK,” Plos one, vol. 15, no. 5, pp. e0231615, 2020, doi: 10.1371/journal.pone.0231615.
D. Gefen, “E-commerce: the role of familiarity and trust,” Omega, vol. 28, no. 6, pp. 725-737, 2000, doi: 10.1016/S0305-0483(00)00021-9.
T. T. Luor, H. P. Lu, H. Yu, and Y. Lu, “Exploring the critical quality attributes and models of smart homes,” Maturitas, vol. 82, no. 4, pp. 377- 386, 2015, doi: 10.1016/j.maturitas.2015.07.025.
I. Mashal and A. Shuhaiber, “What makes Jordanian residents buy smart home devices? A factorial investigation using PLS-SEM,” Kybernetes, vol. 48, no. 8, pp. 1681-1698, 2018, doi: 10.1108/K-01-2018-0008.
E. M. Schomakers, H. Biermann, and M. Ziefle, “Users’ preferences for smart home automation–investigating aspects of privacy and trust,” Telematics and Informatics, vol. 64, pp. 101689, 2021, doi: 10.1016/j. tele.2021.101689.
E. J. Johnson and J. W. Payne, “Effort and accuracy in choice,” Management science, vol. 31, no. 4, pp. 395-414, 1985.
V. A. Zeithaml, “Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence,” Journal of marketing, vol. 52, no. 3, pp. 2-22, 1988, doi: 10.2307/1251446.
K. B. Monroe, Pricing: Making profitable decisions, 2nd ed., New York, USA: McGraw-Hill College, 1990.
T. F. Stafford, “Consumption values and the choice of marketing electives: Treating students like customers,” Journal of Marketing Education, vol. 16, no. 2, pp. 26-33, 1994, doi: 10.1177/027347539401600204.
G. LeBlanc and N. Nguyen, “Listening to the customer’s voice: examining perceived service value among business college students,” International Journal of Educational Management, vol. 13, no. 4, pp. 187-198, 1999, doi: 10.1108/09513549910278106.
R. M. Unni, “Value perceptions and retention of textbooks among marketing and other business majors,” Marketing Education Review, vol. 15, no. 2, pp. 71-79, 2005, doi: 10.1080/10528008.2005.11488909.
V. Venkatesh and H. Bala, “Technology acceptance model 3 and a research agenda on interventions,” Decision sciences, vol. 39, no. 2, pp. 273-315, 2008, doi: 10.1111/j.1540-5915.2008.00192.x.
S. T. Park, H. Im, and K.-S. Noh, “A study on factors affecting the adoption of LTE mobile communication service: The case of South Korea,” Wireless Personal Communications, vol. 86, pp. 217-237, 2016 doi: 10.1007/s11277- 015-2802-7.
I. Mashal, A. Shuhaiber, and M. Daoud, “Factors influencing the acceptance of smart homes in Jordan,” International Journal of Electronic Marketing and Retailing, vol. 11, no. 2, pp. 113-142, 2020, doi: 10.1504/ IJEMR.2020.106842.
M. Al Amri and M. A. Almaiah, “Sustainability Model for Predicting Smart Education Technology Adoption Based on Student Perspectives,” International Journal of Advances in Soft Computing & Its Applications, vol. 13, no. 2, pp. 60-77, 2021.
X. Dong, Y. Chang, Y. Wang, and J. Yan, “Understanding usage of Internet of Things (IOT) systems in China: Cognitive experience and affect experience as moderator,” Information Technology & People, vol. 30, no. 1, pp. 117-138, 2017, doi: 10.1108/ITP-11-2015-0272.
D.-H. Shin, “Conceptualizing and measuring quality of experience of the internet of things: Exploring how quality is perceived by users,” Information & Management, vol. 54, no. 8, pp. 998-1011, 2017, doi: 10.1016/j.im.2017.02.006.
A. Shuhaiber, I. Mashal, and O. Alsaryrah, “Smart homes as an IoT application: predicting attitudes and behaviours,” in 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications, pp. 1-7, 2019, doi: 10.1109/AICCSA47632.2019.9035295.
S. Chatterjee, “Factors impacting behavioral intention of users to adopt IoT in India: from security and privacy perspective,” International Journal of Information Security and Privacy, vol. 14, no. 4, pp. 92-112, 2020, doi: 10.4018/IJISP.2020100106.
A. Al-Husamiyah and M. Al-Bashayreh, “A comprehensive acceptance model for smart home services,” International Journal of Data and Network Science, vol. 6, no. 1, pp. 45-58, 2022, doi: 10.5267/j.ijdns.2021.10.005.
T. Kowatsch and W. Maass, “Critical privacy factors of internet of things services: An empirical investigation with domain experts,” in Knowledge and Technologies in Innovative Information Systems: 7th Mediterranean Conference on Information Systems, Guimaraes, Portugal, pp. 200-211, 2012.
F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “User acceptance of computer technology: A comparison of two theoretical models,” Management science, vol. 35, no. 8, pp. 982-1003, 1989.
X. Wang, C. F. Lee, J. Jiang, G. Zhang, and Z. Wei, “Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model,” Behavioral Sciences, vol. 13, no. 3, p. 277, 2023, doi: 10.3390/bs13030277.
T. Coughlan, M. Brown, R. Mortier, R. J. Houghton, M. Goulden, and G. Lawson, “Exploring Acceptance and Consequences of the Internet of Things in the Home,” in 2012 IEEE international conference on green computing and communications, IEEE, pp. 148-155, 2012.
Y. W. Sek, S. H. Lau, K. K. Teoh, C. Y. Law, and S. B. Parumo, “Prediction of user acceptance and adoption of smart phone for learning with technology acceptance model,” Journal of Applied Sciences (Faisalabad), vol. 10, no. 20, pp. 2395-2402, 2010, doi: 10.3923/jas.2010.2395.2402.
T. A. Sykes, V. Venkatesh, and S. Gosain, “Model of acceptance with peer support: A social network perspective to understand employees’ system use,” MIS quarterly, vol. 33, no. 2, pp. 371-393, 2009, doi: 10.2307/20650296.
R. Gatautis and A. Medziausiene, “Factors affecting social commerce acceptance in Lithuania,” Procedia-Social and Behavioral Sciences, vol. 110, pp. 1235-1242, 2014, doi: 10.1016/j.sbspro.2013.12.970.
T. F. Stafford, “Consumption values and the choice of marketing electives: Treating students like customers,” Journal of Marketing Education, vol. 16, no. 2, pp. 26-33, 1994, doi: 10.1177/027347539401600204.
G. LeBlanc and N. Nguyen, “Listening to the customer’s voice: examining perceived service value among business college students,” International Journal of Educational Management, vol. 13, no. 4, pp. 187-198, 1999, doi: 10.1108/09513549910278106.
R. M. Unni, “Value perceptions and retention of textbooks among marketing and other business majors,” Marketing Education Review, vol. 15, no. 2, pp. 71-79, 2005, doi: 10.1080/10528008.2005.11488909.
V. Venkatesh and H. Bala, “Technology acceptance model 3 and a research agenda on interventions,” Decision sciences, vol. 39, no. 2, pp. 273-315, 2008, doi: 10.1111/j.1540-5915.2008.00192.x.
Statista. “Distribution of internet users worldwide as of 2021, by age group.” Accessed: Jul. 1, 2023. [Online]. Available: https://www.statista.com/statistics/272365/age-distribution-of-internet-users-worldwide/
Statista (2023). “Awareness of smart or connected home devices among adults in the United States as of July 2020, by age group.” Accessed: Jul. 1, 2023. [Online]. Available: https://www.statista.com/statistics/1201173/united-states-smart-home-device-awareness-by-age/
DATAREPORTAL (2022). “DIGITAL 2022: GLOBAL OVERVIEW REPORT.” Accessed: Jul. 1, 2023. [Online]. Available: https://datareportal.com/reports/digital-2022-global-overview-report
J. C. Nunnally, Psychometric Theory, 2nd ed., New York, USA: Mcgraw hill book company, 1978. [68] C. Fornell and D. F. Larcker, “Evaluating structural equation models with unobservable variables and measurement error,” Journal of marketing research, vol. 18, no. 1, pp. 39-50, 1981, doi: 10.2307/3151312.
J. Hair, R. E. Anderson, R. L. Tatham, and W. C. Black, Multivariate data analysis with readings, Englewood Cliffs, NJ, USA: Prentice Hall, 1998.
J. Shin, Y. Park, and D. Lee, “Who will be smart home users? An analysis of adoption and diffusion of smart homes,” Technological Forecasting and Social Change, vol. 134, pp. 246-253, 2018, doi: 10.1016/j. techfore.2018.06.029.
C. B. Huat, “Conceptualizing an East Asian popular culture,” Inter-Asia Cultural Studies, vol. 5, no. 2, pp. 200-221, 2004, doi: 10.1080/1464937042000236711.
L. Gao and X. Bai, “A unified perspective on the factors influencing consumer acceptance of internet of things technology,” Asia Pacific Journal of Marketing and Logistics, vol. 26, no. 2, pp. 211-231, 2014, doi: 10.1108/APJML-06-2013-0061.
E. M. Rogers, “A prospective and retrospective look at the diffusion model,” Journal of health communication, vol. 9, no. S1, pp. 13-19, 2004, doi: 10.1080/10810730490271449.
H. W. Kim, H. C. Chan, and S. Gupta, “Value-based adoption of mobile internet: an empirical investigation,” Decision support systems, vol. 43, no. 1, pp. 111-126, 2007, doi: 10.1016/j.dss.2005.05.009.
D. C. Li, “Online social network acceptance: a social perspective,” Internet research, vol. 21, no. 5, pp. 562-580, 2011, doi: 10.1108/10662241111176371.
G. C. Moore and I. Benbasat, “Development of an instrument to measure the perceptions of adopting an information technology innovation,” Information systems research, vol. 2, no. 3, pp. 192-222, 1991, doi: 10.1287/isre.2.3.192.
V. Venkatesh and X. Zhang, “Unified theory of acceptance and use of technology: US vs. China,” Journal of global information technology management, vol. 13, no. 1, pp. 5-27, 2010, doi: 10.1080/1097198X.2010.10856507.
Y. S. Foon and B. C. Y. Fah, “Internet banking adoption in Kuala Lumpur: an application of UTAUT model,” International Journal of Business and Management, vol. 6, no. 4, p. 161, 2011, doi: 10.5539/ijbm.v6n4p161 .
I. Ajzen, “The theory of planned behavior,” Organizational behavior and human decision processes, vol. 50, no. 2, pp. 179-211, 1991, doi: 10.1016/0749-5978(91)90020-T.
S. Taylor and P. Todd, “Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions,” International journal of research in marketing, vol. 12, no. 2, pp. 137-155, 1995, doi: 10.1016/0167-8116(94)00019-K.
J. C. Sweeney and G. N. Soutar, “Consumer perceived value: The development of a multiple item scale,” Journal of retailing, vol. 77, no. 2, pp. 203-220, 2001, doi: 10.1016/S0022-4359(01)00041-0
M. H. Hsu, C. M. Chang, K. K. Chu, and Y. J. Lee, “Determinants of repurchase intention in online group-buying: The perspectives of DeLone & McLean IS success model and trust,” Computers in Human Behavior, vol. 36, pp. 234-245, 2014, doi: 10.1016/j.chb.2014.03.065.
E. Delgado‐Ballester, “Applicability of a brand trust scale across product categories: A multigroup invariance analysis,” European journal of Marketing, vol. 38, no. 5/6, pp. 573-592, 2004, doi: 10.1108/03090560410529222.
Downloads
Published
-
Abstract179
-
PDF50
Submit Article
Information
