Hybridization of metaheuristics and NLP approach to examine public opinion towards virtual voice assistants | Annals … – Springer

• Acikgoz, F., & Vega, R. P. (2021). The role of privacy cynicism in consumer habits with voice assistants: A technology acceptance model perspective, 38(12), 1138–1152. https://doi.org/10.1080/10447318.2021.1987677

• Acikgoz, F., Perez-Vega, R., Okumus, F., & Stylos, N. (2023). Consumer engagement with AI-powered voice assistants: A behavioral reasoning perspective. Psychology & Marketing, 40(11), 2226–2243. https://doi.org/10.1002/MAR.21873

  Article  Google Scholar 

• Adnan Ikram, R. M., Jaafari, A., Milan, S. G., Kisi, O., Heddam, S., & Zounemat-Kermani, M. (2022). Hybridized adaptive neuro-fuzzy inference system with metaheuristic algorithms for modeling monthly pan evaporation. Water 2022, 14(21), 3549. https://doi.org/10.3390/W14213549. 14.

  Article  Google Scholar 

• Agarwal, P., Swami, S., & Malhotra, S. K. (2022). Artificial intelligence adoption in the Post COVID-19 new-normal and role of smart technologies in transforming business: a review. Journal of Science and Technology Policy Management, ahead-of-print(ahead-of-print).https://doi.org/10.1108/JSTPM-08-2021-0122/FULL/XML

• Agerri, R., Artola, X., Beloki, Z., Rigau, G., & Soroa, A. (2015). Big data for natural language processing: A streaming approach. Knowledge-Based Systems, 79, 36–42. https://doi.org/10.1016/J.KNOSYS.2014.11.007

  Article  Google Scholar 

• Ahmed, A., Hassan, A., Aziz, S., Abd-alrazaq, A. A., Ali, N., Alzubaidi, M., Al-Thani, D., Elhusein, B., Siddig, M. A., Ahmed, M., & Househ, M. (2023). Chatbot features for anxiety and depression: A scoping review. Health Informatics Journal, 29(1). https://doi.org/10.1177/14604582221146719/ASSET/IMAGES/LARGE/10.1177_14604582221146719-FIG1.JPEG

• Al-Betar, M. A., Awadallah, M. A., Doush, I. A., Alomari, O. A., Abasi, A. K., Makhadmeh, S. N., & Alyasseri, Z. A. A. (2023). Boosting the training of neural networks through hybrid metaheuristics. Cluster Computing, 26(3), 1821–1843. https://doi.org/10.1007/S10586-022-03708-X/METRICS

  Article  Google Scholar 

• Al-Makhmari, L., Al-Bulushi, A., Al-Habsi, S., Al-Azri, O., & Tarhini, A. (2023). Determinants of consumers’ acceptance of voice assistance technology: Integrating the service robot acceptance model and unified theory of acceptance and use of technology: Research-in-progress. Lecture Notes in Networks and Systems, 550 LNNS, 603–612. https://doi.org/10.1007/978-3-031-16865-9_48/COVER

  Article  Google Scholar 

• Alimamy, S., & Kuhail, M. A. (2023). I will be with you Alexa! The impact of intelligent virtual assistant’s authenticity and personalization on user reusage intentions. Computers in Human Behavior, 143, 107711. https://doi.org/10.1016/J.CHB.2023.107711

  Article  Google Scholar 

• Ammari, T., Kaye, J., Tsai, J. Y., & Bentley, F. (2019a). Music, search, and IoT. ACM Transactions on Computer-Human Interaction (TOCHI), 26(3). https://doi.org/10.1145/3311956

• Ammari, T., Kaye, J., Tsai, J. Y., & Bentley, F. (2019b). Music, search, and IoT: How people (really) use voice assistants. ACM Transactions on Computer-Human Interaction, 26(3). https://doi.org/10.1145/3311956

• Aw, E. C. X., Tan, G. W. H., Cham, T. H., Raman, R., & Ooi, K. B. (2022). Alexa, what’s on my shopping list? Transforming customer experience with digital voice assistants. Technological Forecasting and Social Change, 180, 121711. https://doi.org/10.1016/J.TECHFORE.2022.121711

  Article  Google Scholar 

• Balakrishnan, J., & Dwivedi, Y. K. (2021). Conversational commerce: entering the next stage of AI-powered digital assistants. Annals of Operations Research 2021, 1–35. https://doi.org/10.1007/S10479-021-04049-5

• Balakrishnan, J., Dwivedi, Y. K., Hughes, L., & Boy, F. (2021). Enablers and inhibitors of AI-Powered voice assistants: A dual-factor approach by integrating the status quo bias and technology acceptance model. Information Systems Frontiers 2021, 1, 1–22. https://doi.org/10.1007/S10796-021-10203-Y

  Article  Google Scholar 

• BentleyFrank, L. C., SilvermanMax, WirasingheRushani, W. B., & LottridgeDanielle. (2018). &. Understanding the long-term use of smart speaker assistants. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(3), 1–24. https://doi.org/10.1145/3264901

• Bhattacharya, S., Sarkar, D., Kole, D. K., & Jana, P. (2022). Recent trends in recommendation systems and sentiment analysis. Advanced Data Mining Tools and Methods for Social Computing, 163–175. https://doi.org/10.1016/B978-0-32-385708-6.00016-3

• Bolton, R. N., McColl-Kennedy, J. R., Cheung, L., Gallan, A., Orsingher, C., Witell, L., & Zaki, M. (2018). Customer experience challenges: Bringing together digital, physical and social realms. Journal of Service Management, 29(5), 776–808. https://doi.org/10.1108/JOSM-04-2018-0113/FULL/XML

  Article  Google Scholar 

• Cai, R., Cain, L. N., & Jeon, H. (2022). Customers’ perceptions of hotel AI-enabled voice assistants: Does brand matter? International Journal of Contemporary Hospitality Management, 34(8), 2807–2831. https://doi.org/10.1108/IJCHM-10-2021-1313/FULL/XML

  Article  Google Scholar 

• Calvaresi, D., Carli, R., Piguet, J. G., Contreras, V. H., Luzzani, G., Najjar, A., Calbimonte, J. P., Schumacher, & Michael (2022). Ethical and legal considerations for nutrition virtual coaches. AI and Ethics 2022 3:4, 3(4), 1313–1340. https://doi.org/10.1007/S43681-022-00237-6

• Carpita, M., Pasca, P., Arima, S., & Ciavolino, E. (2023). Clustering of variables methods and measurement models for soccer players’ performances. Annals of Operations Research, 325(1), 37–56. https://doi.org/10.1007/S10479-023-05185-W/TABLES/6

  Article  Google Scholar 

• Chan, S., Li, L., Torous, J., Gratzer, D., & Yellowlees, P. M. (2019). Review and implementation of self-help and automated tools in Mental Health Care. The Psychiatric Clinics of North America, 42(4), 597–609. https://doi.org/10.1016/J.PSC.2019.07.001

  Article  Google Scholar 

• Chen, J., Xu, F., Dong, S., Sun, W., & Zhang, K. (2022). Authorisation inconsistency in IoT third-party integration. IET Information Security, 16(2), 133–143. https://doi.org/10.1049/ISE2.12043

  Article  Google Scholar 

• Cheng, K., Li, Z., Li, C., Xie, R., Guo, Q., He, Y., & Wu, H. (2023). The potential of GPT-4 as an AI-Powered virtual assistant for surgeons specialized in joint arthroplasty. Annals of Biomedical Engineering, 51(7), 1366–1370. https://doi.org/10.1007/S10439-023-03207-Z/METRICS

  Article  Google Scholar 

• Cho, E. (2019). Hey Google, can i ask you something in private? Conference on Human Factors in Computing Systems – Proceedings. https://doi.org/10.1145/3290605.3300488. The effects of modality and device in sensitive health information acquisition from voice assistants.

  Article  Google Scholar 

• Chung, H., Iorga, M., Voas, J., & Lee, S. (2017). Alexa, can i trust you? Computer, 50(9), 100–104. https://doi.org/10.1109/MC.2017.3571053

  Article  Google Scholar 

• Colabianchi, S., Tedeschi, A., & Costantino, F. (2023). Human-technology integration with industrial conversational agents: A conceptual architecture and a taxonomy for manufacturing. Journal of Industrial Information Integration, 35, 100510. https://doi.org/10.1016/J.JII.2023.100510

  Article  Google Scholar 

• Comai, S., Mundstock Freitas, G. V., Xu, K., Conte, M., Colombo, A., Pöyhönen, S., Ajovalasit, M., & Salice, F. (2023). Enhancing unobtrusive home technology systems with a virtual assistant for mood and social monitoring. Lecture Notes in Networks and Systems, 835 LNNS, 81–93. https://doi.org/10.1007/978-3-031-48306-6_8/COVER

  Article  Google Scholar 

• COVID-19 and (2020). the secret virtual assistants: the social weapons for a state of emergency. Emerald Open Research, 1(2). https://doi.org/10.1108/EOR-02-2023-0005

• Eagle, T., Blau, C., Bales, S., Desai, N., Whittaker, S., Li, V., Kocaballi, B., Laranjo, L., Clark, L., Moore, R. J., Kocielnik, R., Vera Liao, Q., Bickmore, T. W., Li, V., & Whittaker, S. (2022). I don’t know what you mean by `I am anxious’’: A new method for evaluating conversational agent responses to standardized mental health inputs for anxiety and depression. ACM Transactions on Interactive Intelligent Systems (TiiS), 12(2), 12. https://doi.org/10.1145/3488057

  Article  Google Scholar 

• Eshkiti, A., · Sabouhi, Fatemeh, Bozorgi-Amiri, A., & Sabouhi, F. (2023). A data-driven optimization model to response to COVID-19 pandemic: A case study. Annals of Operations Research, 2023, 1–50. https://doi.org/10.1007/S10479-023-05320-7

• Ezenyilimba, A., Wong, M., Hehr, A., Demir, M., Wolff, A., Chiou, E., & Cooke, N. (2023). Impact of transparency and explanations on trust and situation awareness in human–robot teams. Journal of Cognitive Engineering and Decision Making, 17(1), 75–93. https://doi.org/10.1177/15553434221136358/ASSET/IMAGES/10.1177_15553434221136358-IMG18.PNG

  Article  Google Scholar 

• Facebook, M. A. U. (2024). worldwide 2023| Statista. (n.d.). Retrieved January 4, from https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/

• Fakhimi, A., Garry, T., & Biggemann, S. (2023). The effects of anthropomorphised virtual conversational assistants on consumer engagement and trust during service encounters. Australasian Marketing Journal, 31(4), 314–324. https://doi.org/10.1177/14413582231181140/ASSET/IMAGES/LARGE/10.1177_14413582231181140-FIG1.JPEG

  Article  Google Scholar 

• Fernandes, T., & Oliveira, E. (2021a). Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption. Journal of Business Research, 122, 180–191. https://doi.org/10.1016/J.JBUSRES.2020.08.058

  Article  Google Scholar 

• Fernandes, T., & Oliveira, E. (2021b). Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption. Journal of Business Research, 122, 180–191. https://doi.org/10.1016/J.JBUSRES.2020.08.058

  Article  Google Scholar 

• Ganguly, S., Mudi, J., Si, T., & Mukherjee, V. (2023). A novel framework for interconnected hybrid power system design using hybridization of metaheuristic algorithms and fuzzy inference. International Journal of Modelling and Simulation, 1–22. https://doi.org/10.1080/02286203.2023.2281181

• Ghobakhloo, M. (2018). The future of manufacturing industry: A strategic roadmap toward industry 4.0. Journal of Manufacturing Technology Management, 29(6), 910–936. https://doi.org/10.1108/JMTM-02-2018-0057/FULL/XML

  Article  Google Scholar 

• Günay, A., Töre Yargın, G., Süner-Pla-Cerdà, S., & Kulaksız, M. (2023). How should my family assistant be?’: Initial perceptions about prospective and anticipated use of in-home virtual assistants in an emerging context. Behaviour & Information Technology, 42(7), 961–984. https://doi.org/10.1080/0144929X.2022.2054357

  Article  Google Scholar 

• Ha, Q. A., Chen, J. V., Uy, H. U., & Capistrano, E. P. (2020). Exploring the Privacy concerns in using intelligent virtual assistants under perspectives of information sensitivity and anthropomorphism. https://doi.org/10.1080/10447318.2020.1834728, 2020.1834728, 37(6), 512–527. https://doi.org/10.1080/10447318.2020.1834728

• Haddad, H., Taghizadeh-Yazdi, M., M., & Zandieh, M. (2022). A Bi-level optimization stochastic approach for a real unit commitment and economic dispatch a case study in Iran. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.4170511

  Article  Google Scholar 

• Haghighat, P., Nguyen, T., Valizadeh, M., Arvan, M., Parde, N., Kim, M., & Jeong, H. (2023). Effects of an intelligent virtual assistant on office task performance and workload in a noisy environment. Applied Ergonomics, 109, 103969. https://doi.org/10.1016/J.APERGO.2023.103969

  Article  Google Scholar 

• Hosseini-Motlagh, S. M., Samani, M. R. G., & Karimi, B. (2023). Resilient and social health service network design to reduce the effect of COVID-19 outbreak. Annals of Operations Research, 1–73. https://doi.org/10.1007/S10479-023-05363-W/FIGURES/3

• Houssein, E. H., Gad, A. G., Hussain, K., & Suganthan, P. N. (2021). Major advances in particle swarm optimization: Theory, analysis, and application. Swarm and Evolutionary Computation, 63, 100868. https://doi.org/10.1016/J.SWEVO.2021.100868

  Article  Google Scholar 

• Hoy, M. B. (2018a). Alexa, Siri, Cortana, and More: An Introduction to voice assistants. Https://Doi.Org/10.1080/02763869.2018.1404391, 2018.1404391, 37(1), 81–88. https://doi.org/10.1080/02763869.2018.1404391

• Hoy, M. B. (2018b). Alexa, Siri, Cortana, and more: An introduction to voice assistants. Medical Reference Services Quarterly, 37(1), 81–88. https://doi.org/10.1080/02763869.2018.1404391

  Article  Google Scholar 

• Huang, Y. C. (2023). Integrated concepts of the UTAUT and TPB in virtual reality behavioral intention. Journal of Retailing and Consumer Services, 70, 103127. https://doi.org/10.1016/J.JRETCONSER.2022.103127

  Article  Google Scholar 

• Huang, S., Kang, Z., Xu, Z., & Liu, Q. (2021). Robust deep k-means: An effective and simple method for data clustering. Pattern Recognition, 117, 107996. https://doi.org/10.1016/J.PATCOG.2021.107996

  Article  Google Scholar 

• Huh, J., Kim, H. Y., & Lee, G. (2023). Oh, happy day! Examining the role of AI-powered voice assistants as a positive technology in the formation of brand loyalty. Journal of Research in Interactive Marketing, ahead-of-print(ahead-of-print). https://doi.org/10.1108/JRIM-10-2022-0328/FULL/XML

• Instagram users worldwide 2025| Statista. (n.d.). Retrieved June 8, (2023). from https://www.statista.com/statistics/183585/instagram-number-of-global-users/

• Jain, S., Basu, S., Dwivedi, Y. K., & Kaur, S. (2022). Interactive voice assistants– does brand credibility assuage privacy risks? Journal of Business Research, 139, 701–717. https://doi.org/10.1016/J.JBUSRES.2021.10.007

  Article  Google Scholar 

• Jelodar, H., Wang, Y., Yuan, C., Feng, X., Jiang, X., Li, Y., & Zhao, L. (2019). Latent dirichlet allocation (LDA) and topic modeling: Models, applications, a survey. Multimedia Tools and Applications, 78(11), 15169–15211. https://doi.org/10.1007/S11042-018-6894-4/METRICS

  Article  Google Scholar 

• Kamoonpuri, S. Z., & Sengar, A. (2023). Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail. Journal of Retailing and Consumer Services, 72, 103258. https://doi.org/10.1016/J.JRETCONSER.2023.103258

  Article  Google Scholar 

• Kannampallil, T., Ronneberg, C. R., Wittels, N. E., Kumar, V., Lv, N., Smyth, J. M., Gerber, B. S., Kringle, E. A., Johnson, J. A., Yu, P., Steinman, L. E., Ajilore, O. A., & Ma, J. (2022). Design and formative evaluation of a virtual voice-based coach for problem-solving treatment: Observational study. JMIR Form Res 2022;6(8):E38092 Https://Formative.Jmir.Org/2022/8/E38092, 6(8), e38092. https://doi.org/10.2196/38092

• Kannampallil, T., Ajilore, O. A., Lv, N., Smyth, J. M., Wittels, N. E., Ronneberg, C. R., Kumar, V., Xiao, L., Dosala, S., Barve, A., Zhang, A., Tan, K. C., Cao, K. K., Patel, C. R., Gerber, B. S., Johnson, J. A., Kringle, E. A., & Ma, J. (2023). Effects of a virtual voice-based coach delivering problem-solving treatment on emotional distress and brain function: A pilot RCT in depression and anxiety. Translational Psychiatry 2023, 13:1(1), 1–8. https://doi.org/10.1038/s41398-023-02462-x. 13.

  Article  Google Scholar 

• Kao, W. K., & Huang, Y. S. (2023). (Sandy). Service robots in full- and limited-service restaurants: Extending technology acceptance model. Journal of Hospitality and Tourism Management, 54, 10–21. https://doi.org/10.1016/J.JHTM.2022.11.006

• Kassaymeh, S., Al-Laham, M., Al-Betar, M. A., Alweshah, M., Abdullah, S., & Makhadmeh, S. N. (2022). Backpropagation neural Network optimization and software defect estimation modelling using a hybrid salp swarm optimizer-based simulated annealing algorithm. Knowledge-Based Systems, 244, 108511. https://doi.org/10.1016/J.KNOSYS.2022.108511

  Article  Google Scholar 

• Katarya, R., & Verma, O. P. (2017). An effective collaborative movie recommender system with cuckoo search. Egyptian Informatics Journal, 18(2), 105–112. https://doi.org/10.1016/J.EIJ.2016.10.002

  Article  Google Scholar 

• Kim, S., & Choudhury, A. (2021). Exploring older adults’ perception and use of smart speaker-based voice assistants: A longitudinal study. Computers in Human Behavior, 124, 106914. https://doi.org/10.1016/J.CHB.2021.106914

  Article  Google Scholar 

• Kirankaya, C., & Aykut, L. G. (2022). Training of artificial neural networks with the multi-population based artifical bee colony algorithm. Network: Computation in Neural Systems, 33(1–2), 124–142. https://doi.org/10.1080/0954898X.2022.2062472

  Article  Google Scholar 

• Klein, A. M., Kölln, K., Deutschländer, J., & Rauschenberger, M. (2023). Design and evaluation of voice user interfaces: What should one consider? Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14052 LNCS, 167–190. https://doi.org/10.1007/978-3-031-35921-7_12/COVER

• Lau, J., Zimmerman, B., & Schaub, F. (2018). Alexa, are you listening? Proceedings of the ACM on Human-Computer Interaction, 2(CSCW). https://doi.org/10.1145/3274371

• Li, Y., Chu, X., Tian, D., Feng, J., & Mu, W. (2021). Customer segmentation using K-means clustering and the adaptive particle swarm optimization algorithm. Applied Soft Computing, 113, 107924. https://doi.org/10.1016/J.ASOC.2021.107924

  Article  Google Scholar 

• Lopez, A., & Garza, R. (2023). Consumer bias against evaluations received by artificial intelligence: The mediation effect of lack of transparency anxiety. Journal of Research in Interactive Marketing, 17(6), 831–847. https://doi.org/10.1108/JRIM-07-2021-0192/FULL/PDF

  Article  Google Scholar 

• López, G., Quesada, L., & Guerrero, L. A. (2018). Alexa vs. siri vs. cortana vs. google assistant: A comparison of Speech-based natural user interfaces. Advances in Intelligent Systems and Computing, 592, 241–250. https://doi.org/10.1007/978-3-319-60366-7_23/COVER

  Article  Google Scholar 

• Maduku, D. K., Mpinganjira, M., Rana, N. P., Thusi, P., Ledikwe, A., & Mkhize, N. H. (2023). boy. Assessing customer passion, commitment, and word-of-mouth intentions in digital assistant usage: The moderating role of technology anxiety. Journal of Retailing and Consumer Services, 71, 103208. https://doi.org/10.1016/J.JRETCONSER.2022.103208

• Mareli, M., & Twala, B. (2018). An adaptive cuckoo search algorithm for optimisation. Applied Computing and Informatics, 14(2), 107–115. https://doi.org/10.1016/J.ACI.2017.09.001

  Article  Google Scholar 

• McLean, G., & Osei-Frimpong, K. (2019a). Hey Alexa… examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in Human Behavior, 99, 28–37. https://doi.org/10.1016/J.CHB.2019.05.009

  Article  Google Scholar 

• McLean, G., & Osei-Frimpong, K. (2019b). Hey Alexa… examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in Human Behavior, 99, 28–37. https://doi.org/10.1016/J.CHB.2019.05.009

  Article  Google Scholar 

• McLean, G., Osei-Frimpong, K., & Barhorst, J. (2021). Alexa, do voice assistants influence consumer brand engagement?– examining the role of AI powered voice assistants in influencing consumer brand engagement. Journal of Business Research, 124, 312–328. https://doi.org/10.1016/J.JBUSRES.2020.11.045

  Article  Google Scholar 

• Meidani, K., Mirjalili, S., & Barati Farimani, A. (2022a). MAB-OS: Multi-armed bandits metaheuristic optimizer selection. Applied Soft Computing, 128, 109452. https://doi.org/10.1016/J.ASOC.2022.109452

  Article  Google Scholar 

• Meidani, K., Mirjalili, S., & Barati Farimani, A. (2022b). Online metaheuristic algorithm selection. Expert Systems with Applications, 201, 117058. https://doi.org/10.1016/J.ESWA.2022.117058

  Article  Google Scholar 

• Mishra, A., Shukla, A., & Sharma, S. K. (2022). Psychological determinants of users’ adoption and word-of-mouth recommendations of smart voice assistants. International Journal of Information Management, 67, 102413. https://doi.org/10.1016/J.IJINFOMGT.2021.102413

  Article  Google Scholar 

• Mohammadi, A., Sheikholeslam, F., & Mirjalili, S. (2022). Nature-inspired metaheuristic search algorithms for optimizing benchmark problems: Inclined planes system optimization to state-of-the-art methods. Archives of Computational Methods in Engineering 2022, 30:1(1), 331–389. https://doi.org/10.1007/S11831-022-09800-0. 30.

  Article  Google Scholar 

• Mounika, V., Yuan, X., & Bandaru, K. (2019). Analyzing CVE database using unsupervised topic modelling. Proceedings– 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019, 72–77. https://doi.org/10.1109/CSCI49370.2019.00019

• Mowlaei, M. E., Abadeh, S., M., & Keshavarz, H. (2020). Aspect-based sentiment analysis using adaptive aspect-based lexicons. Expert Systems with Applications, 148, 113234. https://doi.org/10.1016/J.ESWA.2020.113234

  Article  Google Scholar 

• Naseem, U., Razzak, I., Musial, K., & Imran, M. (2020). Transformer based deep intelligent contextual embedding for twitter sentiment analysis. Future Generation Computer Systems, 113, 58–69. https://doi.org/10.1016/J.FUTURE.2020.06.050

  Article  Google Scholar 

• Novrianda, D., Herini, E. S., Haryanti, F., Supriyadi, E., & Lazuardi, L. (2023). Chemo assist for children mobile health application to manage chemotherapy-related symptoms in acute leukemia in Indonesia: A user-centered design approach. BMC Pediatrics, 23(1), 1–16. https://doi.org/10.1186/S12887-023-04076-0/TABLES/9

  Article  Google Scholar 

• Ogonji, M. M., Okeyo, G., & Wafula, J. M. (2020). A survey on privacy and security of internet of things. Computer Science Review, 38, 100312. https://doi.org/10.1016/J.COSREV.2020.100312

  Article  Google Scholar 

• Okwu, M. O., & Tartibu, L. K. (2021). Particle swarm optimisation. Studies in Computational Intelligence, 927, 5–13. https://doi.org/10.1007/978-3-030-61111-8_2/COVER

  Article  Google Scholar 

• Oranç, C., & Ruggeri, A. (2021). Alexa, let me ask you something different children’s adaptive information search with voice assistants. Human Behavior and Emerging Technologies, 3(4), 595–605. https://doi.org/10.1002/HBE2.270

  Article  Google Scholar 

• Ossadnik, J., Muehlfeld, K., & Goerke, L. (2023). Man or machine– or something in between? Social responses to voice assistants at work and their effects on job satisfaction. Computers in Human Behavior, 149, 107919. https://doi.org/10.1016/J.CHB.2023.107919

  Article  Google Scholar 

• Paul, M., Maglaras, L., Ferrag, M. A., & Almomani, I. (2023). Digitization of healthcare sector: A study on privacy and security concerns. ICT Express. https://doi.org/10.1016/J.ICTE.2023.02.007

  Article  Google Scholar 

• Piñeiro-Martín, A., García-Mateo, C., Docío-Fernández, L., & López-Pérez, M. (2023). del C. Ethical challenges in the development of virtual assistants powered by large language models. Electronics 2023, Vol. 12, Page 3170, 12(14), 3170. https://doi.org/10.3390/ELECTRONICS12143170

• Prentice, C., Loureiro, S. M. C., & Guerreiro, J. (2023). Engaging with intelligent voice assistants for wellbeing and brand attachment. Journal of Brand Management, 30(5), 449–460. https://doi.org/10.1057/S41262-023-00321-0/TABLES/6

  Article  Google Scholar 

• Priya, B., & Sharma, V. (2023). Exploring users’ adoption intentions of intelligent virtual assistants in financial services: An anthropomorphic perspectives and socio-psychological perspectives. Computers in Human Behavior, 148, 107912. https://doi.org/10.1016/J.CHB.2023.107912

  Article  Google Scholar 

• Rahimi, A., Hejazi, S. M., Zandieh, M., & Mirmozaffari, M. (2023). A novel hybrid simulated annealing for no-wait open-shop surgical case scheduling problems. Applied System Innovation 2023, 6(1), 15. https://doi.org/10.3390/ASI6010015. 6.

  Article  Google Scholar 

• Rahman, M. S., Halder, S., Uddin, M. A., & Acharjee, U. K. (2021). An efficient hybrid system for anomaly detection in social networks. Cybersecurity, 4(1), 1–11. https://doi.org/10.1186/S42400-021-00074-W/FIGURES/5

  Article  Google Scholar 

• Rzepka, C., Berger, B., & Hess, T. (2020). Why another customer Channel? Consumers’ perceived benefits and costs of Voice Commerce. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-January, 4079–4088. https://doi.org/10.24251/HICSS.2020.499

  Article  Google Scholar 

• Sattarapu, P. K., Wadera, D., Nguyen, N. P., Kaur, J., Kaur, S., & Mogaji, E. (2023). Tomeito or tomahto: Exploring consumer’s accent and their engagement with artificially intelligent interactive voice assistants. Journal of Consumer Behaviour. https://doi.org/10.1002/CB.2195

  Article  Google Scholar 

• Saura, J. R., Ribeiro-Soriano, D., & Zegarra Saldaña, P. (2022). Exploring the challenges of remote work on Twitter users’ sentiments: From digital technology development to a post-pandemic era. Journal of Business Research, 142, 242–254. https://doi.org/10.1016/J.JBUSRES.2021.12.052

  Article  Google Scholar 

• Sayed, A. A., Abdallah, M. M., Zaki, A. M., & Ahmed, A. A. (2020). Big Data analysis using a metaheuristic algorithm: Twitter as case study. Proceedings of 2020 International Conference on Innovative Trends in Communication and Computer Engineering, ITCE 2020, 20–26. https://doi.org/10.1109/ITCE48509.2020.9047790

• Schadelbauer, L., Schlögl, S., & Groth, A. (2023). Linking personality and trust in intelligent virtual assistants. Multimodal Technologies and Interaction 2023, Vol. 7, Page 54, 7(6), 54. https://doi.org/10.3390/MTI7060054

• Schultz, C. K. N. (2023). Creating the ‘virtual’ witness: The limits of empathy. Museum Management and Curatorship, 38(1), 2–17. https://doi.org/10.1080/09647775.2021.1954980

  Article  Google Scholar 

• Seymour, W., & Such, J. (2023). Ignorance is bliss? The effect of explanations on perceptions of voice assistants. Proceedings of the ACM on Human-Computer Interaction, 7(CSCW1). https://doi.org/10.1145/3579497

• Seymour, W., & Van Kleek, M. (2021). Exploring interactions between trust, anthropomorphism, and relationship development in voice assistants. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2). https://doi.org/10.1145/3479515

• Shami, T. M., El-Saleh, A. A., Alswaitti, M., Al-Tashi, Q., Summakieh, M. A., & Mirjalili, S. (2022). Particle swarm optimization: A comprehensive survey. Ieee Access: Practical Innovations, Open Solutions, 10, 10031–10061. https://doi.org/10.1109/ACCESS.2022.3142859

  Article  Google Scholar 

• Shehab, M., Abu-Hashem, M. A., Shambour, M. K. Y., Alsalibi, A. I., Alomari, O. A., Gupta, J. N. D., Alsoud, A. R., Abuhaija, B., & Abualigah, L. (2022). A comprehensive review of bat inspired algorithm: variants, applications, and hybridization. Archives of Computational Methods in Engineering 2022 30:2, 30(2), 765–797. https://doi.org/10.1007/S11831-022-09817-5

• Shokouhifar, M., Sohrabi, M., Rabbani, M., Molana, M., & Werner, F. (2022). Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm. https://doi.org/10.20944/PREPRINTS202212.0432.V1

• Silva, A., Schrum, M., Hedlund-Botti, E., Gopalan, N., & Gombolay, M. (2023). Explainable artificial intelligence: Evaluating the objective and subjective impacts of xAI on human-agent interaction. International Journal of Human–Computer Interaction, 39(7), 1390–1404. https://doi.org/10.1080/10447318.2022.2101698

  Article  Google Scholar 

• Singh, N., Singh, S. B., & Houssein, E. H. (2022). Hybridizing salp swarm algorithm with particle swarm optimization algorithm for recent optimization functions. Evolutionary Intelligence, 15(1), 23–56. https://doi.org/10.1007/S12065-020-00486-6/METRICS

  Article  Google Scholar 

• Sohrabi, M., Zandieh, M., & Shokouhifar, M. (2023). Sustainable inventory management in blood banks considering health equity using a combined metaheuristic-based robust fuzzy stochastic programming. Socio-Economic Planning Sciences, 86, 101462. https://doi.org/10.1016/J.SEPS.2022.101462

  Article  Google Scholar 

• Song, X., Zhang, Y., Gong, D., & Sun, X. (2021). Feature selection using bare-bones particle swarm optimization with mutual information. Pattern Recognition, 112, 107804. https://doi.org/10.1016/J.PATCOG.2020.107804

  Article  Google Scholar 

• Striegl, J., Gotthardt, M., Loitsch, C., & Weber, G. (2022). Investigating the usability of voice assistant-based CBT for age-related depression. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13341 LNCS, 432–441. https://doi.org/10.1007/978-3-031-08648-9_50/TABLES/1

• Sylvain, F., & Chaniaud, N. (2023). Multi-user centered design: Acceptance, user experience, user research and user testing. Theoretical Issues in Ergonomics Science. https://doi.org/10.1080/1463922X.2023.2166623

  Article  Google Scholar 

• Tian, S., Yang, W., Grange, J. M., Le, Wang, P., Huang, W., & Ye, Z. (2019). Smart healthcare: Making medical care more intelligent. Global Health Journal, 3(3), 62–65. https://doi.org/10.1016/J.GLOHJ.2019.07.001

  Article  Google Scholar 

• Vernuccio, M., Patrizi, M., & Pastore, A. (2023). Delving into brand anthropomorphisation strategies in the experiential context of name-brand voice assistants. Journal of Consumer Behaviour, 22(5), 1074–1083. https://doi.org/10.1002/CB.1984

  Article  Google Scholar 

• Wald, R., Piotrowski, J. T., Araujo, T., & van Oosten, J. M. F. (2023). Virtual assistants in the family home. Understanding parents’ motivations to use virtual assistants with their child(dren). Computers in Human Behavior, 139, 107526. https://doi.org/10.1016/J.CHB.2022.107526

  Article  Google Scholar 

• Wang, L., Cao, Q., Zhang, Z., Mirjalili, S., & Zhao, W. (2022). Artificial rabbits optimization: A new bio-inspired meta-heuristic algorithm for solving engineering optimization problems. Engineering Applications of Artificial Intelligence, 114, 105082. https://doi.org/10.1016/J.ENGAPPAI.2022.105082

  Article  Google Scholar 

• Whang, C., & Im, H. (2021). I like your suggestion! The role of humanlikeness and parasocial relationship on the website versus voice shopper’s perception of recommendations. Psychology & Marketing, 38(4), 581–595. https://doi.org/10.1002/MAR.21437

  Article  Google Scholar 

• X/Twitter: number of users worldwide 2024| Statista. (n.d.). Retrieved January 4, (2024). from https://www.statista.com/statistics/303681/twitter-users-worldwide/

• Xiang, Z., Schwartz, Z., Gerdes, J. H., & Uysal, M. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management, 44, 120–130. https://doi.org/10.1016/J.IJHM.2014.10.013

  Article  Google Scholar 

• Xiaoqiong, W., & Zhang, Y. E. (2020). Image segmentation algorithm based on dynamic particle swarm optimization and K-means clustering. International Journal of Computers and Applications, 42(7), 649–654. https://doi.org/10.1080/1206212X.2018.1521090

  Article  Google Scholar 

• Yi, P., & Zubiaga, A. (2023). Session-based cyberbullying detection in social media: A survey. Online Social Networks and Media, 36, 100250. https://doi.org/10.1016/J.OSNEM.2023.100250

  Article  Google Scholar 

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