How to cite this paper
Al-Husamiyah, A & Al-Bashayreh, M. (2022). A comprehensive acceptance model for smart home services.International Journal of Data and Network Science, 6(1), 45-58.
Refrences
Ajzen, I. (1991). The theory of planned behavior. Orgnizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. (2002). Perceived Behavioral Control, Self‐Efficacy, Locus of Control, and the Theory of Planned Behavior. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x
Alaiad, A., & Zhou, L. (2017). Patients’ adoption of WSN-based smart home healthcare systems: An integrated model of facilitators and barriers. IEEE Transactions on Professional Communication, 60(1), 4–23. https://doi.org/10.1109/TPC.2016.2632822
Allison, P. D. (2001). Missing data. Sage.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/0092-0703/88 /1601-0074
Bao, H., Chong, A. Y. L., Ooi, K. B., & Lin, B. (2014). Are Chinese consumers ready to adopt mobile smart home? An empirical analysis. International Journal of Mobile Communications, 12(5), 496–511. https://doi.org/10.1504/IJMC.2014.064595
Bohrnstedt, G. (1970). Reliability and validity assessment in attitude measurement. In G. F. Summers (Ed.), Attitude measurement (pp. 80–99). Rand McNally.
Bollinger, C. R., & Chandra, A. (2005). Iatrogenic specification error: A cautionary tale of cleaning data. Journal of Labor Economics, 23(2), 235–257. https://doi.org/10.1086/428028
Carter, L., & Weerakkody, V. (2008). E-government adoption: A cultural comparison. Information Systems Frontiers, 10(4), 473–482. https://doi.org/10.1007/s10796-008-9103-6
Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research (pp. 295–336). Lawrence Erlbaum Associates.
Coakes, S. J., Steed, L., & Dzidic, P. (2006). SPSS Version 13.0 for Windows: Analysis without Anguish (20th ed.). John Wiley & Sons.
Corrado, C. J., & Su, T. (1996). Skewness and Kurtosis In S&P 500 Index Returns Implied by Option Prices. Journal of Financial Research, 19(2), 175–192. https://doi.org/10.1111/j.1475-6803.1996.tb00592.x
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Dong, X., Chang, Y., Wang, Y., & Yan, J. (2017). Understanding usage of Internet of Things (IOT) systems in China: Cognitive experience and affect experience as moderator. Information Technology & People, 30(1), 117–138. https://doi.org/10.1108/ITP-11-2015-0272
Enders, C. K. (2010). Applied missing data analysis. Guilford Press.
Featherman, M., & Pavloub, P. (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Ghany, M. G., Strader, D. B., Thomas, D. L., & Seeff, L. B. (2009). Diagnosis, management, and treatment of hepatitis C: An update. Hepatology, 49(4), 1335–1374. https://doi.org/10.1002/hep.22759
Gotz, O., Liehr-Gobber, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares (pp. 691–711). Springer.
Gross, C., Siepermann, M., & Lackes, R. (2020). The Acceptance of Smart Home Technology. In R. A. Buchmann, A. Polini, B. Johansson, & D. Karagiannis (Eds.), Perspectives in Business Informatics Research (pp. 3–18). Springer International Publishing.
Guhr, N., Werth, O., Blacha, P. P. H., & Breitner, M. H. (2020). Privacy concerns in the smart home context. SN Applied Sciences, 2(2), 247. https://doi.org/10.1007/s42452-020-2025-8
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis (7th ed.). Prentice Hall.
Hojjati, S., & Khodakarami, M. (2016). Evaluation of factors affecting the adoption of smart buildings using the technology acceptance model. International Journal of Advanced Networking and Applications, 7(6), 2936–2943.
Hsu, C. L., & Lin, J. C. C. (2016). An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives. Computers in Human Behavior, 62, 516–527. https://doi.org/10.1016/j.chb.2016.04.023
Hubert, M., Blut, M., Brock, C., Wenjiao Zhang, R., Koch, V., & Riedl, R. (2019). The influence of acceptance and adoption drivers on smart home usage. European Journal of Marketing, 53(6), 1073–1098. https://doi.org/10.1108/EJM-12-2016-0794
Iacobucci, D. (2018). Marketing research : methodological foundations (12th ed.). CreateSpace.
Kim, C., Mirusmonova, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322. https://doi.org/10.1016/j.chb.2009.10.013
Kim, Y., Park, Y., & Choi, J. (2017). A study on the adoption of IoT smart home service: using Value-based Adoption Model. Total Quality Management and Business Excellence. https://doi.org/10.1080/14783363.2017.1310708
Kwak, S. K., & Kim, J. H. (2017). Statistical data preparation: management of missing values and outliers. Korean Journal of Anesthesiology, 70(4), 407–411. https://doi.org/10.4097/kjae.2017.70.4.407
Lemieux, J., & McAlister, L. (2005). Handling missing values in marketing data: A comparison of techniques. MSI-Working Paper Series, 2(05–107), 41–60.
Marikyan, D., Papagiannidis, S., & Alamanos, E. (2019). A systematic review of the smart home literature: A user perspective. Technological Forecasting and Social Change, 138, 139–154. https://doi.org/10.1016/j.techfore.2018.08.015
Miles, J., & Shevlin, M. (2001). Applying regression and correlation : a guide for students and researchers. Sage Publications.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
Nikou, S. (2019). Factors driving the adoption of smart home technology: An empirical assessment. Telematics and Informatics, 45, 101–283. https://doi.org/10.1016/j.tele.2019.101283
Pal, D., Funilkul, S., Charoenkitkarn, N., & Kanthamanon, P. (2018). Internet-of-Things and Smart Homes for Elderly Healthcare: An End User Perspective. In IEEE Access. https://doi.org/10.1109/ACCESS.2018.2808472
Park, E., Cho, Y., Han, J., & Kwon, S. J. (2017). Comprehensive approaches to user acceptance of Internet of Things in a smart home environment. IEEE Internet of Things Journal, 4(6), 2342–2350. https://doi.org/10.1109/JIOT.2017.2750765
Park, E., Kim, S., Kim, Y., & Kwon, S. J. (2018). Smart home services as the next mainstream of the ICT industry: determinants of the adoption of smart home services. Universal Access in the Information Society, 17(1), 175–190. https://doi.org/10.1007/s10209-017-0533-0
Peter, J. P. (1981). Construct validity: A review of basic issues and marketing practices. Journal of Marketing Research, 18(2), 133–145. https://doi.org/10.2307/3150948
Pirker, C. (2009). Statistical noise or valuable information : the role of extreme cases in marketing research. Gabler Verlag / GWV Fachverlage.
Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5. https://doi.org/10.1108/EUM0000000002542
Ramsey, P. P. H., & Ramsey, P. P. H. (2007). Optimal trimming and outlier elimination. Journal of Modern Applied Statistical Methods, 6(2), 355–360. https://doi.org/10.22237/jmasm/1193889660
Relles, D. A., & Rogers, W. H. (1977). Statisticians are fairly robust estimators of location. Journal of the American Statistical Association, 72(357), 107–111. https://doi.org/10.2307/2286917
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach (7th ed.). John Wiley & Sonsy.
Sequeiros, H., Oliveira, T., & Thomas, M. A. (2021). The Impact of IoT Smart Home Services on Psychological Well-Being. Information Systems Frontiers. https://doi.org/10.1007/s10796-021-10118-8
Sharma, S. (1996). Applied Multivariate Techniques (1st ed.). John Wiley and Sons Inc.
Shin, D. (2010). Analysis of online social networks: a cross-national study. Online Information Review, 34(3), 473–495. https://doi.org/10.1108/14684521011054080
Shuhaiber, A. (2018). The role of perceived control, enjoyment, cost, sustainability and trust on intention to use smart meters: An empirical study using SEM-PLS. Advances in Intelligent Systems and Computing, 746, 789–799. https://doi.org/10.1007/978-3-319-77712-2_74
Shuhaiber, A., & Mashal, I. (2019). Understanding users’ acceptance of smart homes. Technology in Society, 58, 101–110. https://doi.org/10.1016/J.TECHSOC.2019.01.003
Staddon, J., & Chow, R. (2008). Detecting reviewer bias through web-based association mining. 2nd ACM Workshop Information Credibility on the Web, 5–9. https://doi.org/10.1145/1458527.1458532
Stojkoska, B. L. R., & Trivodaliev, K. V. (2017). A review of Internet of Things for smart home: Challenges and solutions. Journal of Cleaner Production, 140, 1454–1464. https://doi.org/10.1016/j.jclepro.2016.10.006
Tomlinson, B. (2010). Greening through IT: Information Technology for Environmental Sustainability. In Environmental Health Perspectives (2nd ed.). MIT Press. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3040630/?report=classic
Tornatzky, L., & Klein, K. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, EM-29(1), 28–45. https://doi.org/10.1109/TEM.1982.6447463
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Walker, D. H. T. (1997). Choosing an appropriate research methodology. Construction Management and Economics, 15(2), 149–159. https://doi.org/10.1080/01446199700000003
Yang, H., Lee, H., & Zo, H. (2017). User acceptance of smart home services: an extension of the theory of planned behavior. Industrial Management & Data Systems, 117(1), 68–89. https://doi.org/10.1108/IMDS-01-2016-0017
Yoon, C., & Kim, S. (2007). Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN. Electronic Commerce Research and Applications, 6(1), 102–112. https://doi.org/10.1016/j.elerap.2006.06.009
Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). South-Western Cengage Learning.
Ajzen, I. (2002). Perceived Behavioral Control, Self‐Efficacy, Locus of Control, and the Theory of Planned Behavior. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x
Alaiad, A., & Zhou, L. (2017). Patients’ adoption of WSN-based smart home healthcare systems: An integrated model of facilitators and barriers. IEEE Transactions on Professional Communication, 60(1), 4–23. https://doi.org/10.1109/TPC.2016.2632822
Allison, P. D. (2001). Missing data. Sage.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/0092-0703/88 /1601-0074
Bao, H., Chong, A. Y. L., Ooi, K. B., & Lin, B. (2014). Are Chinese consumers ready to adopt mobile smart home? An empirical analysis. International Journal of Mobile Communications, 12(5), 496–511. https://doi.org/10.1504/IJMC.2014.064595
Bohrnstedt, G. (1970). Reliability and validity assessment in attitude measurement. In G. F. Summers (Ed.), Attitude measurement (pp. 80–99). Rand McNally.
Bollinger, C. R., & Chandra, A. (2005). Iatrogenic specification error: A cautionary tale of cleaning data. Journal of Labor Economics, 23(2), 235–257. https://doi.org/10.1086/428028
Carter, L., & Weerakkody, V. (2008). E-government adoption: A cultural comparison. Information Systems Frontiers, 10(4), 473–482. https://doi.org/10.1007/s10796-008-9103-6
Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research (pp. 295–336). Lawrence Erlbaum Associates.
Coakes, S. J., Steed, L., & Dzidic, P. (2006). SPSS Version 13.0 for Windows: Analysis without Anguish (20th ed.). John Wiley & Sons.
Corrado, C. J., & Su, T. (1996). Skewness and Kurtosis In S&P 500 Index Returns Implied by Option Prices. Journal of Financial Research, 19(2), 175–192. https://doi.org/10.1111/j.1475-6803.1996.tb00592.x
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Dong, X., Chang, Y., Wang, Y., & Yan, J. (2017). Understanding usage of Internet of Things (IOT) systems in China: Cognitive experience and affect experience as moderator. Information Technology & People, 30(1), 117–138. https://doi.org/10.1108/ITP-11-2015-0272
Enders, C. K. (2010). Applied missing data analysis. Guilford Press.
Featherman, M., & Pavloub, P. (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Ghany, M. G., Strader, D. B., Thomas, D. L., & Seeff, L. B. (2009). Diagnosis, management, and treatment of hepatitis C: An update. Hepatology, 49(4), 1335–1374. https://doi.org/10.1002/hep.22759
Gotz, O., Liehr-Gobber, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares (pp. 691–711). Springer.
Gross, C., Siepermann, M., & Lackes, R. (2020). The Acceptance of Smart Home Technology. In R. A. Buchmann, A. Polini, B. Johansson, & D. Karagiannis (Eds.), Perspectives in Business Informatics Research (pp. 3–18). Springer International Publishing.
Guhr, N., Werth, O., Blacha, P. P. H., & Breitner, M. H. (2020). Privacy concerns in the smart home context. SN Applied Sciences, 2(2), 247. https://doi.org/10.1007/s42452-020-2025-8
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis (7th ed.). Prentice Hall.
Hojjati, S., & Khodakarami, M. (2016). Evaluation of factors affecting the adoption of smart buildings using the technology acceptance model. International Journal of Advanced Networking and Applications, 7(6), 2936–2943.
Hsu, C. L., & Lin, J. C. C. (2016). An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives. Computers in Human Behavior, 62, 516–527. https://doi.org/10.1016/j.chb.2016.04.023
Hubert, M., Blut, M., Brock, C., Wenjiao Zhang, R., Koch, V., & Riedl, R. (2019). The influence of acceptance and adoption drivers on smart home usage. European Journal of Marketing, 53(6), 1073–1098. https://doi.org/10.1108/EJM-12-2016-0794
Iacobucci, D. (2018). Marketing research : methodological foundations (12th ed.). CreateSpace.
Kim, C., Mirusmonova, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322. https://doi.org/10.1016/j.chb.2009.10.013
Kim, Y., Park, Y., & Choi, J. (2017). A study on the adoption of IoT smart home service: using Value-based Adoption Model. Total Quality Management and Business Excellence. https://doi.org/10.1080/14783363.2017.1310708
Kwak, S. K., & Kim, J. H. (2017). Statistical data preparation: management of missing values and outliers. Korean Journal of Anesthesiology, 70(4), 407–411. https://doi.org/10.4097/kjae.2017.70.4.407
Lemieux, J., & McAlister, L. (2005). Handling missing values in marketing data: A comparison of techniques. MSI-Working Paper Series, 2(05–107), 41–60.
Marikyan, D., Papagiannidis, S., & Alamanos, E. (2019). A systematic review of the smart home literature: A user perspective. Technological Forecasting and Social Change, 138, 139–154. https://doi.org/10.1016/j.techfore.2018.08.015
Miles, J., & Shevlin, M. (2001). Applying regression and correlation : a guide for students and researchers. Sage Publications.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
Nikou, S. (2019). Factors driving the adoption of smart home technology: An empirical assessment. Telematics and Informatics, 45, 101–283. https://doi.org/10.1016/j.tele.2019.101283
Pal, D., Funilkul, S., Charoenkitkarn, N., & Kanthamanon, P. (2018). Internet-of-Things and Smart Homes for Elderly Healthcare: An End User Perspective. In IEEE Access. https://doi.org/10.1109/ACCESS.2018.2808472
Park, E., Cho, Y., Han, J., & Kwon, S. J. (2017). Comprehensive approaches to user acceptance of Internet of Things in a smart home environment. IEEE Internet of Things Journal, 4(6), 2342–2350. https://doi.org/10.1109/JIOT.2017.2750765
Park, E., Kim, S., Kim, Y., & Kwon, S. J. (2018). Smart home services as the next mainstream of the ICT industry: determinants of the adoption of smart home services. Universal Access in the Information Society, 17(1), 175–190. https://doi.org/10.1007/s10209-017-0533-0
Peter, J. P. (1981). Construct validity: A review of basic issues and marketing practices. Journal of Marketing Research, 18(2), 133–145. https://doi.org/10.2307/3150948
Pirker, C. (2009). Statistical noise or valuable information : the role of extreme cases in marketing research. Gabler Verlag / GWV Fachverlage.
Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5. https://doi.org/10.1108/EUM0000000002542
Ramsey, P. P. H., & Ramsey, P. P. H. (2007). Optimal trimming and outlier elimination. Journal of Modern Applied Statistical Methods, 6(2), 355–360. https://doi.org/10.22237/jmasm/1193889660
Relles, D. A., & Rogers, W. H. (1977). Statisticians are fairly robust estimators of location. Journal of the American Statistical Association, 72(357), 107–111. https://doi.org/10.2307/2286917
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach (7th ed.). John Wiley & Sonsy.
Sequeiros, H., Oliveira, T., & Thomas, M. A. (2021). The Impact of IoT Smart Home Services on Psychological Well-Being. Information Systems Frontiers. https://doi.org/10.1007/s10796-021-10118-8
Sharma, S. (1996). Applied Multivariate Techniques (1st ed.). John Wiley and Sons Inc.
Shin, D. (2010). Analysis of online social networks: a cross-national study. Online Information Review, 34(3), 473–495. https://doi.org/10.1108/14684521011054080
Shuhaiber, A. (2018). The role of perceived control, enjoyment, cost, sustainability and trust on intention to use smart meters: An empirical study using SEM-PLS. Advances in Intelligent Systems and Computing, 746, 789–799. https://doi.org/10.1007/978-3-319-77712-2_74
Shuhaiber, A., & Mashal, I. (2019). Understanding users’ acceptance of smart homes. Technology in Society, 58, 101–110. https://doi.org/10.1016/J.TECHSOC.2019.01.003
Staddon, J., & Chow, R. (2008). Detecting reviewer bias through web-based association mining. 2nd ACM Workshop Information Credibility on the Web, 5–9. https://doi.org/10.1145/1458527.1458532
Stojkoska, B. L. R., & Trivodaliev, K. V. (2017). A review of Internet of Things for smart home: Challenges and solutions. Journal of Cleaner Production, 140, 1454–1464. https://doi.org/10.1016/j.jclepro.2016.10.006
Tomlinson, B. (2010). Greening through IT: Information Technology for Environmental Sustainability. In Environmental Health Perspectives (2nd ed.). MIT Press. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3040630/?report=classic
Tornatzky, L., & Klein, K. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, EM-29(1), 28–45. https://doi.org/10.1109/TEM.1982.6447463
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Walker, D. H. T. (1997). Choosing an appropriate research methodology. Construction Management and Economics, 15(2), 149–159. https://doi.org/10.1080/01446199700000003
Yang, H., Lee, H., & Zo, H. (2017). User acceptance of smart home services: an extension of the theory of planned behavior. Industrial Management & Data Systems, 117(1), 68–89. https://doi.org/10.1108/IMDS-01-2016-0017
Yoon, C., & Kim, S. (2007). Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN. Electronic Commerce Research and Applications, 6(1), 102–112. https://doi.org/10.1016/j.elerap.2006.06.009
Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). South-Western Cengage Learning.