Abstract
Intelligent personal assistants (IPA) experience increasing popularity. They are designed to make everyday life easier. But for that purpose they monitor their users. This study investigates how the perceived advantages and disadvantages of using an IPA affect its acceptance. In addition, trust in the IPA and trust in the manufacturer are considered as further influencing factors. The results show that the advantages have a higher impact on acceptance than the disadvantages. The influence of trust in the manufacturer affects both the trust in the IPA and the perceived advantages. Trust in the IPA in turn influences the perceived advantages and disadvantages, and acceptance. In order to increase the perceived advantages, manufacturers should increase the range of functions, particularly in the area of house control, and thus increase the acceptance of IPAs. Another positive effect on acceptance is the reduction of perceived disadvantages by building trust in the IPA and the manufacturer.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Forrester Research: Ownership of smart home devices and smart speakers in the United States from 2015 to 2022 (in million households/units in use). Statista. https://www.statista.com/statistics/794624/us-smart-home-devices-smart-speaker-ownership-forecast/
Gartner: Gartner Says Worldwide Spending on VPA-Enabled Wireless Speakers Will Top $2 Billion by 2020 (2016)
Transparency Market Research: Growing Focus on Strengthening Customer Relations Spurs Adoption of Intelligent Virtual Assistant Technology, Says TMR. Albany, NY (2016)
Augusto, J.C., Nugent, C.D.: Smart homes can be smarter. In: Augusto, J.C., Nugent, C.D. (eds.) Designing Smart Homes. LNCS (LNAI), vol. 4008, pp. 1–15. Springer, Heidelberg (2006). https://doi.org/10.1007/11788485_1
Reis, A., Paulino, D., Paredes, H., Barroso, J.: Using intelligent personal assistants to strengthen the elderlies’ social bonds. In: Antona, M., Stephanidis, C. (eds.) UAHCI 2017. LNCS, vol. 10279, pp. 593–602. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-58700-4_48
Knight, W.: Amazon Working on Making Alexa Recognize Your Emotions. With Google and Apple preparing voice devices for the home, Amazon is teaching Alexa to listen for emotions. https://www.technologyreview.com/s/601654/amazon-working-on-making-alexa-recognize-your-emotions/
Han, S., Yang, H.: Understanding adoption of intelligent personal assistants. Ind. Manag. Data Syst. 118, 618–636 (2018)
Liptak, A.: Amazon’s Alexa started ordering people dollhouses after hearing its name on TV. https://www.theverge.com/2017/1/7/14200210/amazon-alexa-tech-news-anchor-order-dollhouse
Siddike, M.A.K., Kohda, Y.: Towards a framework of trust determinants in people and cognitive assistants interactions. In: Bui, T. (ed.) Proceedings of the 51st Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences (2018)
Kowalczuk, P.: Consumer acceptance of smart speakers: a mixed methods approach. J. Res. Interact. Market. 12, 418–431 (2018)
Orehovački, T., Etinger, D., Babić, S.: The antecedents of intelligent personal assistants adoption. In: Nunes, I.L. (ed.) AHFE 2018. AISC, vol. 781, pp. 76–87. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-94334-3_10
Sano, S., Kaji, N., Sassano, M. (eds.): Prediction of prospective user engagement with intelligent assistants (2016)
Jiang, J., et al.: Automatic online evaluation of intelligent assistants. In: Gangemi, A., Leonardi, S., Panconesi, A. (eds.) Proceedings of the 24th International Conference on World Wide Web - WWW 2015, pp. 506–516. ACM Press, New York (2015)
Kiseleva, J., et al.: Understanding user satisfaction with intelligent assistants. In: Kelly, D., Capra, R., Belkin, N., Teevan, J., Vakkari, P. (eds.) Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval - CHIIR 2016, pp. 121–130. ACM Press, New York (2016)
Davis, F.D.: A technology acceptance model for empirically testing new end-user information systems: theory and results. Massachusetts Institute of Technology (1986)
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989)
Chau, P.Y.K., Hu, P.J.: Examining a model of information technology acceptance by individual professionals: an exploratory study. J. Manag. Inf. Syst. 18, 191–229 (2002)
Mathieson, K.: Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Inf. Syst. Res. 2, 173–191 (1991)
Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage. Sci. 46, 186–204 (2000)
Lee, Y., Kozar, K.A., Larsen, K.R.T.: The technology acceptance model: past, present, and future. Commun. Assoc. Inf. Syst. 12, 752–780 (2003)
Armitage, C.J., Conner, M.: Efficacy of the theory of planned behaviour: a meta-analytic review. Br. J. Soc. Psychol. 40, 471–499 (2001)
Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. Manag. Inf. Syst. Q. 27, 425–478 (2003)
Venkatesh, V., Ramesh, V., Massey, A.P.: Understanding usability in mobile commerce. Commun. ACM 46, 53–56 (2003)
Herzberg, F.: One More Time: How Do You Motivate Employees. Harvard Business Review, Boston (1968)
Hoy, M.B.: Alexa, Siri, Cortana, and more: an introduction to voice assistants. Med. Ref. Serv. Q. 37, 81–88 (2018)
López, G., Quesada, L., Guerrero, L.A.: Alexa vs. Siri vs. Cortana vs. Google assistant: a comparison of speech-based natural user interfaces. In: Nunes, I.L. (ed.) Advances in Human Factors and Systems Interaction, 592, pp. 241–250. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-60366-7_23
Yang, H., Lee, H.: Understanding user behavior of virtual personal assistant devices. Inf. Syst. E-Bus. Manag. 24, 665 (2018)
Chen, C.-F., Xu, X., Arpan, L.: Between the technology acceptance model and sustainable energy technology acceptance model: investigating smart meter acceptance in the United States. Energy Res. Soc. Sci. 25, 93–104 (2017)
Park, C.-K., Kim, H.-J., Kim, Y.-S.: A study of factors enhancing smart grid consumer engagement. Energy Policy 72, 211–218 (2014)
Noyes, J.A.N.: Talking and writing—how natural in human–machine interaction? Int. J. Hum Comput Stud. 55, 503–519 (2001)
Gefen, D., Karahanna, E., Straub, D.W.: Trust and TAM in online shopping: an integrated model. MIS Q. 27, 51–90 (2003)
Reichheld, F.F., Schefter, P.: E-loyalty: your secret weapon on the web. Harvard Bus. Rev. 78, 105–113 (2000)
Mayer, R.C., Davis, J.H., Schoorman, F.D.: An integrative model of organizational trust. Acad. Manag. Rev. (AMR) 20, 709–734 (1995)
McKnight, D.H., Choudhury, V., Kacmar, C.: Developing and validating trust measures for e-commerce: an integrative typology. Inf. Syst. Res. 13, 334–359 (2002)
Rousseau, D.M., Sitkin, S.B., Burt, R.S., Camerer, C.: Not so different after all: a cross-discipline view of trust. Acad. Manag. Rev. (AMR) 23, 393–404 (1998)
Menon, N.M., Konana, P., Browne, G.J., Balasubramanian, S.: Understanding trustworthiness beliefs in electronic brokerage usage. In: Proceedings of the 20th International Conference on Information Systems, pp. 552–555 (1999)
Fung, R., Lee, M.: EC-trust (trust in electronic commerce): exploring the antecedent factors. In: Proceedings of the 5th Americas Conference on Information Systems, pp. 517–519 (1999)
Tan, Y.-H., Thoen, W.: An outline of a trust model for electronic commerce. Appl. Artif. Intell. 14, 849–862 (2000)
Chopra, K., Wallace, W.A.: Trust in electronic environments. In: Proceedings of the 36th Annual Hawaii International Conference on System Sciences, pp. 1–10. IEEE (2003)
Krasnova, H., Spiekermann, S., Koroleva, K., Hildebrand, T.: Online social networks: why we disclose. J. Inf. Technol. 25, 109–125 (2010)
Chin, W.W.: The partial least squares approach to structural equation modeling. In: Modern Methods for Business Research, vol. 295, pp. 295–336 (1998)
Jarvis, C.B., MacKenzie, S.B., Podsakoff, P.M.: A critical review of construct indicators and measurement model misspecification in marketing and consumer research. J. Consum. Res. 30, 199–218 (2003)
Ringle, C.M., Wende, S., Becker, J.-M.: SmartPLS 3. SmartPLS GmbH, Boenningstedt (2015)
Hair, J.F., Hult, G.T.M., Ringle, C., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications, Thousand Oaks (2016)
Chin, W.W.: Commentary: issues and opinion on structural equation modeling. MIS Q. 22, 7–16 (1998)
Huber, F., Herrmann, A., Meyer, F., Vogel, J., Vollhardt, K.: Kausalmodellierung mit Partial Least Squares. Gabler, Wiesbaden (2007)
Cronbach, L.J.: Coefficient alpha and the internal structure of tests. Psychometrika 16, 297–334 (1951)
Nunnally, J.C., Bernstein, I.H., Berge, J.M.T.: Psychometric Theory. MacGrac-Hill, New York (1994)
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E.: Multivariate Data Analysis. Pearson Education, Upper Saddle River (2006)
Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18, 39–50 (1981)
Sarstedt, M., Ringle, C.M., Smith, D., Reams, R., Hair, J.F.: Partial least squares structural equation modeling (PLS-SEM): a useful tool for family business researchers. J. Fam. Bus. Strategy 5, 105–115 (2014)
Diamantopoulos, A., Riefler, P., Roth, K.P.: Advancing formative measurement models. J. Bus. Res. 61, 1203–1218 (2008)
Bollen, K., Lennox, R.: Conventional wisdom on measurement: a structural equation perspective. Psychol. Bull. 110, 305–314 (1991)
Balta-Ozkan, N., Davidson, R., Bicket, M., Whitmarsh, L.: Social barriers to the adoption of smart homes. Energy Policy 63, 363–374 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lackes, R., Siepermann, M., Vetter, G. (2019). Can I Help You? – The Acceptance of Intelligent Personal Assistants. In: Pańkowska, M., Sandkuhl, K. (eds) Perspectives in Business Informatics Research. BIR 2019. Lecture Notes in Business Information Processing, vol 365. Springer, Cham. https://doi.org/10.1007/978-3-030-31143-8_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-31143-8_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31142-1
Online ISBN: 978-3-030-31143-8
eBook Packages: Computer ScienceComputer Science (R0)