nach oben

Information Systems Frontiers

Erschienen in:

12.09.2021

Usage Intention of Social Robots for Domestic Purpose: From Security, Privacy, and Legal Perspectives

verfasst von: Sheshadri Chatterjee, Ranjan Chaudhuri, Demetris Vrontis

Erschienen in: Information Systems Frontiers | Ausgabe 1/2024

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Domestic robots, also known as companion robots or social robots, are physical humanoid robots. They connect with online platforms which enhance their functionalities, such as voice and emotion recognition, human facial recognition, along with other Artificial Intelligence (AI) related capabilities make them special. People’s perceptions of robots are changing rapidly. The market for domestic robots is expected to grow exponentially over the next few years. As the use of domestic robots increases, people perceive different kinds of security, privacy, and legal issues with their usage. Few studies have focused on these issues. This study has attempted to understand users’ intention to use robots for household purposes and focuses on their perceptions about security, privacy, and legal issues. Reviewing the literature and the theories helped us to develop the conceptual model. The model has been validated by PLS-SEM technique. The study finds that privacy and security concerns affect households use of domestic robots. The study also finds that few people are aware of legal implications. Also, the study reveals that people expect to get many benefits from using robots for household purposes.

Vorheriger Artikel The Collaborative Interaction with Pokémon-Go Robot uses Augmented Reality technology for Increasing the Intentions of Patronizing Hospitality

Nächster Artikel Knowledge Graph and Deep Learning-based Text-to-GraphQL Model for Intelligent Medical Consultation Chatbot

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

Abba Ari, A. A., Ngangmo, O. K., Titouna, C., Thiare, O., Kolyang, A. M., & Gueroui, A. M. (2020). Enabling privacy and security in Cloud of Things: Architecture, applications, security & privacy challenges. Applied Computing and Informatics, In Press. https://doi.org/10.1016/j.aci.2019.11.005

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–221. https://doi.org/10.1016/0749-5978(91)90020-TCrossRef

Ajzen, I., & Fishbein, M. (2005). The influence of attitudes on behavior. In D. Albarracín, B.T. Johnson, & M. P. Zanna (Eds.), The Handbook of Attitudes (pp. 173–221). Erlbaum

Alaiad, A., & Zhou, L. (2014). The determinants of home healthcare robots adoption: An empirical investigation. International Journal of Medical Informatics, 83(11), 825–840CrossRef

Al-Debei, M. M., & Al-Lozi, E. (2014). Explaining and predicting the adoption intention of mobile data services: a value-based approach. Computers in Human Behavior, 35, 326–338. https://doi.org/10.1016/j.chb.2014.03.011CrossRef

Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396–402. https://doi.org/10.2307/3150783CrossRef

Bartneck, C., Kanda, T., Mubin, O., & Mahmud, A. A. (2009). Does the design of a robot influence its animacy and perceived intelligence? International Journal of Social Robotics, 1(1), 195–204. https://doi.org/10.1007/s12369-009-0013-7CrossRef

Bartneck, C., Nomura, T., Suzuki, T., Kanda, T., & Kennsuke, K. (2005). A cross-cultural study on attitudes towards robots. Paper presented at the International Conference on Human-Computer Interaction, 22–25 July 2005, Las Vegas. https://doi.org/10.13140/RG.2.2.35929.11367

Belanche, D., Casaló, L. V., & Flavián, C. (2012). Integrating trust and personal values into the technology acceptance model: the case of e-government services adoption. Cuadernos de Economía Dirección de la Empresa, 15(4), 192–204. https://doi.org/10.1016/j.cede.2012.04.004CrossRef

Bellotti, V., & Sellen, A. (1993). Design for privacy in ubiquitous computing environments. In G. de Michelis, C. Simone, & K. Schmidt (Eds.), ECSCW’93: Proceedings of the third conference on European Conference on Computer-Supported Cooperative Work September 1993, Milan (pp. 77–92). Springer. https://doi.org/10.1007/978-94-011-2094-4_6

Belyaeva, Z., Shams, S. M. R., Santoro, G., & Grandhi, B. (2020). Unpacking stakeholder relationship management in the public and private sectors: the comparative insights. EuroMed Journal of Business, 15(3), 269–281. https://doi.org/10.1108/EMJB-06-2019-0085CrossRef

Berger, S., Häckel, B., & Häfner, L. (2019). Organizing self-organizing systems: a terminology, taxonomy, and reference model for entities in cyber-physical production systems. Information Systems Frontiers, In Press. https://doi.org/10.1007/s10796-019-09952-8

Bhattacharjee, K. K., Chatterjee, S., Nguyen, B., Ghosh, S. K., & Chaudhuri, S. (2020a). Adoption of artificial intelligence integrated CRM system: an empirical study of Indian organizations. The Bottom Line, In Press. https://doi.org/10.1108/BL-08-2020-0057

Bhattacharya, K., & Chatterjee, S. (2020b). Adoption of artificial intelligence in higher education: a quantitative analysis using structural equation modelling. Education and Information Technologies. In Press. https://doi.org/10.1007/s10639-020-10159-7

Bogue, R. (2017). Domestic robots: Has their time finally come? Industrial Robot, 44(2), 129–136. https://doi.org/10.1108/IR-01-2017-0018CrossRef

Cavallo, F., Limosani, R., Manzi, A., Saffiotti, A., & Dario, P. (2014). Development of a socially believable multi-robot solution from town to home. Cognitive Computation, 6, 954–967CrossRef

Chang, S. J., Witteloostuijn, A. V., & Eden, L. (2010). From the editors: Common method variance in international business research. Journal of International Business Studies, 41(2), 178–184. https://doi.org/10.1057/jibs.2009.88CrossRef

Chatterjee, S. (2019a). Impact of AI regulation on intention to use robots: From citizens and government perspective. International Journal of Intelligent Unmanned Systems, 8(2), 97–114. https://doi.org/10.1108/IJIUS-09-2019-0051CrossRef

Chatterjee, S. (2019b). Influence of IoT policy on Quality of Life: From Government and Citizens’ perspective. International Journal of Electronic Government Research, 15(2), 19–38. https://doi.org/10.4018/IJEGR.2019040102CrossRef

Chatterjee, S., Chaudhuri, R., Vrontis, D., Thrassou, A., & Ghosh, S. (2020a). ICT-enabled CRM system adoption: A dual Indian qualitative case study and conceptual framework development. Journal of Asia Business Studies, In Press. https://doi.org/10.1108/JABS-05-2020-0198

Chatterjee, S., Chaudhuri, R., Vrontis, D., Thrassou, A., Ghosh, S. K., & Chaudhuri, S. (2020b). Social customer relationship management factors and business benefits. International Journal of Organizational Analysis, In Press. https://doi.org/10.1108/IJOA-11-2019-1933

Chatterjee, S., Rana, N. P., & Dwivedi, Y. K. (2021). Assessing consumers’ co-production and future participation on value co‐creation and business benefit: an F-P-C-B model perspective. Information Systems Frontiers, In Press. https://doi.org/10.1007/s10796-021-10104-0

Chen, N. (2018). Are robots replacing routine jobs?, Harvard College Thesis, Applied Mathematics Cambridge, MA. http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA. Accessed 12 Aug 2020.

Chidlow, A., Ghauri, P., Yeniyurt, S., & Cavusgil, S. T. (2015). Establishing rigor in mail survey procedures in international business research. Journal of World Business, 50(1), 26–36. https://doi.org/10.1016/j.jwb.2014.01.004CrossRef

Cuijpers, R. H., Bruna, M. T., Ham, J. R. C., & Torta, E. (2011). Attitude towards robots depends on interaction but not on anticipatory behavior. In B. Mutlu, C. Bartneck, J. Ham, V. Evers, & T. Kanda (Eds.), Social Robots: Proceedings of International Conference on Social Robotics, ICSR 2011, Amsterdam, The Netherlands, Nov. 24–25 (pp. 163–172). Springer-Verlag. https://doi.org/10.1007/978-3-642-25504-5_17

Darling, K. (2012). Extending legal rights to social robots. Paper presented at We Robot Conference, University of Miami, Miami, April 2012. Retrieved from https://doi.org/10.2139/ssrn.20

Dautenhahn, K. (2007). Socially intelligent robots: Dimensions of human-robot interaction. Philosophical Transactions of the Royal Society B: Biological Sciences, 362(1480), 679–704. https://doi.org/10.1098/rstb.2006.2004CrossRef

de Graaf, M. M. A., Ben Allouch, S., & van Dijk, J. A. G. M. (2019). Why would I use this in my home? A model of domestic social robot acceptance. Human-Computer Interaction, 34(2), 115–173. https://doi.org/10.1080/07370024.2017.1312406CrossRef

de Graaf, M. M. A., Allouch, B., & van Dijk, J. A. G. M. S., & (2015). What makes a robot social? A user’s perspective on characteristics for social human–robot interaction. In A. Tapus, E. André, J.-C. Martin, F. Ferland, & M. Ammi (Eds.), Social Robotics: 7th International Conference on Social Robotics, ICSR 2015, Paris, France, October 26–30, Proceedings (pp. 184–193). Springer International Publishing. https://doi.org/10.1007/978-3-319-25554-5_19

Denning, T., Matuszek, C., Koscher, K., Smith, J. R., & Kohno, T. (2009). A spotlight on security and privacy risks with future household robots: Attacks and lessons. In Ubicomp’09 Proceedings of the 11th international conference on Ubiquitous computing. September 2009. (pp. 105–114). https://doi.org/10.1145/1620545.1620564

Dimitropoulos, P., Koronios, K., Thrassou, A., & Vrontis, D. (2019). Cash holdings, corporate performance and viability of Greek SMEs: Implications for stakeholder relationship management. EuroMed Journal of Business, 15(3), 333–348. https://doi.org/10.1108/EMJB-08-2019-0104CrossRef

Dinev, T., Hart, P., & Mullen, M. R. (2008). Internet privacy concerns and beliefs about government surveillance — an empirical investigation. The Journal of Strategic Information Systems, 17(3), 214–233. https://doi.org/10.1016/j.jsis.2007.09.002CrossRef

Ferreira, A., & Franco, M. (2019). The influence of strategic alliances on human capital development: A study applied to technology-based SMEs. EuroMed Journal of Business, 15(1), 65–65. https://doi.org/10.1108/EMJB-04-2019-0052CrossRef

Festa, G., Shams, S. M. R., Metallo, G., & Cuomo, M. T. (2019). Enhancing stakeholder networks in wine tourism – evidence from Italian small municipalities. EuroMed Journal of Business, 15(3), 349–360. https://doi.org/10.1108/EMJB-02-2019-0027CrossRef

Fink, J., Bauwens, V., Kaplan, F., & Dillenbourg, P. (2013). Living with a vacuum cleaning robot: A 6-month ethnographic study. International Journal of Social Robotics, 5(3), 389–408. https://doi.org/10.1007/s12369-013-0190-2CrossRef

Flandorfer, P. (2012). Population ageing and socially assistive robots for elderly persons: the importance of sociodemographic factors for user acceptance. International Journal of Population Research, 12, 1–13. https://doi.org/10.1155/2012/829835CrossRef

Forlizzi, J., DiSalvo, C., & Gemperle, F. (2004). Assistive robotics and an ecology of elders living independently in their homes. Human-Computer Interaction, 19(1/2), 25–59. https://doi.org/10.1207/s15327051hci1901&2_3CrossRef

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/10.1177/002224378101800104CrossRef

Gates, W., & Bill, I. I. I. (2007). A robot in every home. Scientific American, 296(1), 58–65. https://doi.org/10.1038/scientificamerican0208-4spCrossRef

Geisser, S. (1975). The predictive sample reuse method with applications. Journal of the American Statistical Association, 70(350), 320–328. https://doi.org/10.2307/2285815CrossRef

Ghosh, S. K., Chatterjee, S., & Chaudhuri, R. (2019b). Knowledge management improving business process: An interpretative framework for successful implementation of AI-CRM-KM System in organizations. Business Process Management Journal, In Press. https://doi.org/10.1007/s40171-017-0173-5

Ghosh, S. K., Chatterjee, S., Chaudhuri, R., & Chaudhuri, S. (2020). Adoption of AI-integrated CRM system by Indian industry: from security and privacy perspective. Information and Computer Security, In Press. https://doi.org/10.1108/ICS-02-2019-0029

Groom, V., Nass, C., Chen, T., Nielsen, A., Scarborough, J. K., & Robles, E. (2009). Evaluating the effects of behavioral realism in embodied agents. International Journal of Human-Computer Studies, 67(10), 842–849. https://doi.org/10.1016/j.ijhcs.2009.07.001CrossRef

Gupta, M. P., Chatterjee, S., & Kar, A. K. (2018a). Alignment of IT authority and citizens of proposed smart cities in India: System security and privacy perspective. Global Journal of Flexible Systems Management, 19(1), 95–107. https://doi.org/10.1007/s40171-017-0173-5CrossRef

Gupta, M. P., Chatterjee, S., & Kar, A. (2018b). Success of IoT in Smart Cities of India: An empirical analysis. Government Information Quarterly, 35(3), 349–361. https://doi.org/10.1016/j.giq.2018.05.002CrossRef

Hair, J. F., Risher, J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203CrossRef

Harzing, A. W., Brown, M., Köster, K., & Zhao, S. (2012). Response style differences in cross-national research: Dispositional and situational determinants. Management International Review, 52(3), 341–363. https://doi.org/10.1007/s11575-011-0111-2CrossRef

Hassenzahl, M. (2004). The interplay of beauty, goodness, and usability in interactive products. Human-Computer Interaction, 19(4), 319–349. https://doi.org/10.1207/s15327051hci1904_2CrossRef

Heerink, M., Kröse, B., Evers, V., & Wielinga, B. (2010). Assessing acceptance of assistive social agent technology by older adults: The Almere model. International Journal of Social Robotics, 2(4), 361–375. https://doi.org/10.1007/s12369-010-0068-5CrossRef

Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8CrossRef

Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to under parameterized model misspecification. Psychological Methods, 3(4), 424–453. https://doi.org/10.1037/1082-989X.3.4.424CrossRef

Hussain, S., Erdogen, S. Z., & Park, J. H. (2009). Monitoring user activities in smart home environments. Information Systems Frontiers, 11, 539–547. https://doi.org/10.1007/s10796-008-9124-1CrossRef

Iachello, G., & Hong, J. (2007). End-user privacy in human-computer interaction. Foundations and Trends Human-Computer Interaction, 1, 1–137. https://doi.org/10.1561/1100000004CrossRef

Jha, A., & Saha, D. (2021). Mobile Broadband for Inclusive Connectivity: What Deters the High-Capacity Deployment of 4G-LTE Innovation in India? Information Systems Frontiers, In Press. https://doi.org/10.1007/s10796-021-10128-6

Joosse, M., Sardar, A., Lohse, M., & Evers, V. (2013). BEHAVE-II: The revised set of measures to assess users’ attitudinal and behavioral responses to a social robot. International Journal of Social Robotics, 5(3), 379–388. https://doi.org/10.1007/s12369-013-0191-1CrossRef

Kanti, S. G., Chatterjee, S., & Chaudhuri, R. (2020). Knowledge management in improving business process: Aan interpretative framework for successful implementation of AI–CRM–KM system in organizations. Business Process Management Journal. Early cite. https://doi.org/10.1108/BPMJ-05-2019-0183

Kantorovitch, J., Väre, J., Pehkonen, V., Laikari, A., & Seppälä, H. (2014). An assistive household robot – doing more than just cleaning. Journal of Assistive Technologies, 8(2), 64–76CrossRef

Karthick, S., Kumar, S., & Mohan, S. K. (2016). Relative analysis of controller effectiveness for vertical plane control of an autonomous underwater vehicle. In OCEANS 2016-Shanghai, 1–6. IEEE Conference

Khan, G. F., Sarstedt, M., Shiau, W. L., Hair, J. F., Ringle, C. M., & Fritze, M. P. (2019). Methodological research on partial least squares structural equation modeling (PLS-SEM): An analysis based on social network approaches. Internet Research, 29(3), 407–429CrossRef

Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544–564. https://doi.org/10.1016/j.dss.2007.07.001CrossRef

Koops, B.-J., & Leenes., R. (2014). Privacy regulation cannot be hardcoded: A critical comment on the “Privacy by Design” provision in data protection law. International Review of Law, Computers & Technology, 28(1),159–171. https://doi.org/10.1080/13600869.2013.801589

Laufer, R. S., & Wolfe, M. (1977). Privacy as a concept and a social issue: a multidimensional development theory. Journal of Social Issues, 33(3), 23–42. https://doi.org/10.1111/j.1540-4560.1977.tb01880.xCrossRef

Lee, K. M., Jung, Y., Kim, J., & Kim, S. R. (2006a). Are physically embodied social agents better than disembodied social agents? The effects of physical embodiment, tactile interaction, and people’s loneliness in human-robot interaction. International Journal of Human-Computer Studies, 64, 962–973. https://doi.org/10.1016/j.ijhcs.2006.05.002CrossRef

Lee, Y., Lee, J., & Lee, Z. (2006b). Social influence on technology behaviour: Self-identity theory perspective. ACM SIGMIS Database, 37(2/3), 60–75. https://doi.org/10.1145/1161345CrossRef

Lee, K., Lee, K. Y., & Sheehan, L. (2020). Hey Alexa! A magic spell of social glue? Sharing a smart voice assistant speaker and its impact on users’ perception of group harmony. Information Systems Frontiers, 22, 563–583. https://doi.org/10.1007/s10796-019-09975-1CrossRef

Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The technology acceptance model: Past, present and future. Communications of the Association for Information Systems, 12(1), 752–780. https://doi.org/10.17705/1CAIS.01250CrossRef

Leenes, R., & Lucivero, F. (2014). Laws on robots, laws by robots, laws in robots: regulating robot behavior by design. Law Innovation Technology, 6(2), 193–220. https://doi.org/10.5235/17579961.6.2.193CrossRef

Lew, Y. K., Sinkovics, R. R., Yamin, M., & Khan, Z. (2016). Trans-specialization understanding in international technology alliances: The influence of cultural distance. Journal of International Business Studies, 47, 577–594. https://doi.org/10.1057/jibs.2016.10CrossRef

Lindell, M. K., & Whitney, D. J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology, 86(1), 114–121. https://doi.org/10.1037/0021-9010.86.1.114CrossRef

Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modeling (SEM) for building and testing the behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, 57(2), 123–146CrossRef

Majumdar, D., Chatterjee, S., Misra, S., & Damaševičius, R. (2019). Adoption of mobile applications for teaching-learning process in rural girls’ schools in India: an empirical study”, Education and Information Technologies. In Press. https://doi.org/10.1007/s10639-020-10168-6

Market Reports. (2019). Household Robots Market. Markets and Markets. Retrieved from https://www.marketsandmarkets.com/Market-Reports/household-robot-market-253781130.html#:~:text=%5B132%20Pages%20Report%5D%20The%20household,and%20usable%20day%20by%20day. Accessed 16 July 2020

Mellahi, K., & Harris, L. C. (2016). Response rates in business and management research: An overview of current practice and suggestions for future directions. British Journal of Management, 27(2), 426–437. https://doi.org/10.1111/1467-8551.12154CrossRef

Nguyen, B., & Chatterjee, S. (2021). Value co-creation and social media at bottom of pyramid (BOP). The Bottom Line, In Press, https://doi.org/10.1108/BL-11-2020-0070. ISSN: 0888-045X

Pagallo, U. (2016). The impact of domestic robots on privacy and data protection, and the troubles with legal regulation by design. Law, Governance and Technology Series, 24, 387–410. https://doi.org/10.1007/978-94-017-7376-8_14CrossRef

Penco, L., Ivaldi, E., Bruzzi, C., & Musso, E. (2019). Entrepreneurship and the cities in a knowledge-based perspective: evidence from EU. EuroMed Journal of Business, 14(3), 189–208. https://doi.org/10.1007/s11469-019-00095-0CrossRef

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879CrossRef

Porra, J., Lacity, M., & Parks, M. S. (2020). Can computer based human-likeness endanger humanness?” – A philosophical and ethical perspective on digital assistants expressing feelings they can’t have. Information Systems Frontiers, 22, 533–547. https://doi.org/10.1007/s10796-019-09969-zCrossRef

Prabu, J., & Tiwari, A. (2018). Optimization approach for a climbing robot with target tracking in WSNs. Journal of Ocean Engineering and Science, 3(4), 282–287CrossRef

Rana, N. P., Chatterjee, S., & Dwivedi, Y. K. (2020). Social media as a tool of knowledge sharing in academia: an empirical study using valance, instrumentality, and expectancy (VIE) approach. Journal of Knowledge Management, In Press. https://doi.org/10.1108/JKM-04-2020-0252

Robert, L. P., Alahmad, R., Zhang, Q., Kim, S., Esterwood, C., & You, S. (2020). A review of personality in human robot interactions. Foundations & Trends in Information Systems, 4(2), 107–210 [2001.11777v2] A Review of Personality in Human Robot Interactions (arxiv.org)CrossRef

Rodriguez, R. V., Sinha, S., & Tripathi, S. (2020). Impact of Artificial Intelligence on the health protection scheme in India. Public Administration and Policy. Asia-Pacific Journal, 23(3), 273–281. https://doi.org/10.1108/PAP-03-2020-0019CrossRef

Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). The Free Press. ISBN-13: 978-0-7432-2209-9

Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020CrossRef

Salem, M., Eyssel, F., Rohlfing, K., Kopp, S., & Joublin, F. (2013). To err is human (-like): Effects of robot gesture on perceived anthropomorphism and likability. International Journal of Social Robotics, 5(3), 313–323. https://doi.org/10.1007/s12369-013-0196-9CrossRef

Santoro, G., Vrontis, D., Thrassou, A., & Dezi, L. (2018). The Internet of Things: building knowledge management systems for open innovation and knowledge management capacity. Technological Forecasting & Social Change, 136, 347–354. https://doi.org/10.1016/j.techfore.2017.02.034CrossRef

Saunila, M., & Makimattila, M. (2019). A Dynamic Learning Perspective on Innovation Control: Balancing Freedom and Constraint. Chapter 14, 273–291. In the book of D. Vrontis, Y. Weber, A. Thrassou, S. M. R. Shams, & E. Tsoukatos (Eds.), Innovation and Capacity Building: Cross-disciplinary Management Theories for Practical Applications (pp. 273–291). Palgrave Publication. https://doi.org/10.1007/978-3-319-90945-5_14

Scopelliti, M., Giuliani, M. V., & Fornara, F. (2005). Robots in a domestic setting: a psychological approach. University Access Information Society, 4(2), 146–155. https://doi.org/10.1007/s10209-005-0118-1CrossRef

Sebastian, T. (2004). Toward a framework for human-robot interaction. Human-Computer Interaction, 19(1/2), 9–24. https://doi.org/10.1207/s15327051hci1901&2_2CrossRef

Seetharaman, P., Mathew, S. K., & Sein, M. K. (2020). Being (more) human in a digitized world. Information Systems Frontiers, 22, 529–532. https://doi.org/10.1007/s10796-020-10020-9CrossRef

Sharma, S., Ogunlana, K., & Scribner, D. (2018). Modeling human behavior during emergency evacuation using intelligent agents: A multi-agent simulation approach. Information Systems Frontiers, 20, 741–757. https://doi.org/10.1007/s10796-017-9791-xCrossRef

Shiau, W. L., & Chau, P. Y. (2016). Understanding behavioral intention to use a cloud computing classroom: A multiple model comparison approach. Information & Management, 53, 355–365CrossRef

Shin, D. H., & Choo, H. (2011). Modeling the acceptance of socially interactive robotics: Social presence in human-robot interaction. Interaction Studies, 12(3), 430–460. https://doi.org/10.1075/is.12.3.04shiCrossRef

Solove, D. J. (2004). The digital person: Technology and privacy in the information age. NYU Press. The digital person: technology and privacy in the information age. https://www.core.ac.uk. Accessed 31 Jan 2021

Sreenivasulu, N. S., & Chatterjee, S. (2019). Personal data sharing and legal issues of human rights in the era of artificial intelligence: moderating effect of government regulation. International Journal of Electronic Government Research, 15(3), 21–36. https://doi.org/10.4018/IJEGR.2019070102CrossRef

Stone, M. (1974). Cross validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36(2), 111–147. https://doi.org/10.1111/j.2517-6161.1974.tb00994.xCrossRef

Thrassou, A., Santoro, G., Leonidou, E., Vrontis, D., & Christofi, M. (2019). Emotional intelligence and perceived negative emotions in intercultural service encounters: building and utilizing knowledge in the banking sector. European Business Review, Early Cite. https://doi.org/10.1108/EBR-04-2019-0059

Thrassou, A., Vrontis, D., Crescimanno, M., Giacomarra, M., & Galati, A. M. & (2020). The requisite match between internal resources and network ties to cope with knowledge scarcity. Journal of Knowledge Management, Early cite. https://doi.org/10.1108/JKM-06-2019-0291

van der Heijden, H. (2003). Factors influencing the use of websites: The case of a generic portal in the Netherlands. Information & Management, 40(6), 541–549CrossRef

Venkatesh, A. (2008). Digital home technologies and transformation of households. Information Systems Frontiers, 10, 391–395. https://doi.org/10.1007/s10796-008-9097-0CrossRef

Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44, 119–134. https://doi.org/10.1007/s11747-015-0455-4CrossRef

Vrontis, D., Christofi, M., Battisti, E., & Graziano, E. A. (2020). Intellectual capital, knowledge sharing and equity crowdfunding. Journal of Intellectual Capital. https://doi.org/10.1108/JIC-11-2019-0258CrossRef

Vrontis, D., Christofi, M., Pereira, V., Makrides, S. T. A., & Trichina, E. (2021). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. The International Journal of Human Resource Management, In Press. https://doi.org/10.1080/09585192.2020.1871398

Vrontis, D., Thrassou, A., Santoro, G., & Papa, A. (2017). Ambidexterity, external knowledge and performance in knowledge-intensive firms. The Journal of Technology Transfer, 42(2), 374–388. https://doi.org/10.1007/s10961-016-9502-7CrossRef

Wakunuma, K. J., & Stahl, B. C. (2014). Tomorrow’s ethics and today’s response: An investigation into the ways information systems professionals perceive and address emerging ethical issues. Information Systems Frontiers, 16, 383–397. https://doi.org/10.1007/s10796-014-9490-9CrossRef

Willaby, H. W., Costa, D. S. J., Burns, B. D., MacCann, C., & Roberts, R. D. (2015). Testing complex models with small sample sizes: A historical overview and empirical demonstration of what partial least squares (PLS) can offer differential psychology. Personality and Individual Differences, 84, 73–78. https://doi.org/10.1016/j.paid.2014.09.008CrossRef

Wu, S. I. (2003). The relationship between consumer characteristics and attitude toward online shopping. Marketing Intelligence and Planning, 21(1), 37–44CrossRef

Xu, H., Teo, H. H., Tan, B. C. Y., & Agarwal, R. (2009). The role of push–pull technology in privacy calculus: the case of location-based services. Journal of Management Information Systems, 26(3), 135–173. https://doi.org/10.2753/MIS0742-1222260305CrossRef

You, S., & Robert, L. P. (2018). Emotional attachment, performance, and viability in teams collaborating with embodied physical action (EPA) robots. Journal of the Association for Information Systems, 19(5), 377–407CrossRef

Chatterjee, S., Ghosh, S., Chaudhuri, R. and Nguyen, B. (2019a). Are CRM systems ready for AI integration? The Bottom Line, 32(2), 144-157. https://doi.org/10.1108/BL-02-2019-0069

Ghosh, S.K., Chatterjee, S., and Chaudhuri, R. (2019a). Adoption of Ubiquitous Customer Relationship Management (uCRM) in Enterprise: Leadership Support and Technological Competence as Moderators. Journal of Relationship Marketing, 19(2), 75-92. https://doi.org/10.1080/15332667.2019.1664870

Titel: Usage Intention of Social Robots for Domestic Purpose: From Security, Privacy, and Legal Perspectives
verfasst von: Sheshadri Chatterjee
Ranjan Chaudhuri
Demetris Vrontis
Publikationsdatum: 12.09.2021
Verlag: Springer US
Erschienen in: Information Systems Frontiers / Ausgabe 1/2024
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI: https://doi.org/10.1007/s10796-021-10197-7

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 1/2024

An Ostensive Information Architecture to Enhance Semantic Interoperability for Healthcare Information Systems

The Collaborative Interaction with Pokémon-Go Robot uses Augmented Reality technology for Increasing the Intentions of Patronizing Hospitality

Deep Reinforcement Learning-Based Robot Exploration for Constructing Map of Unknown Environment

Scenario-Based Distributionally Robust Unit Commitment Optimization Involving Cooperative Interaction with Robots

Social Robotics Business and Computing

The Mediating Role of Absorptive Capability Between the Effect of Organizational Internalization Through Social Media on Open Inbound Innovation

Premium Partner