Research Article
BibTex RIS Cite

The impact of interaction, trust, anthropomorphism, and usage level of chatbots on customer satisfaction in online retailing

Year 2024, Volume: 26 Issue: Özel Sayı, 81 - 100, 21.10.2024
https://doi.org/10.33707/akuiibfd.1459114

Abstract

Today, chatbots are becoming increasingly common in online retail environments, causing brands to redesign how they interact with customers and deliver services. It is seen that chatbot services are increasing to create a better customer experience and gain a competitive advantage, especially due to the increase in the young population, busy work schedules, and the rapid spread of online retailing. Although chatbots have many features, especially interaction, the perception of trust and anthropomorphic features, which refer to the attribution of human characteristics to inanimate beings, affect users' satisfaction levels. Accordingly, this study aims to measure the effect of consumer perceptions of interaction, trust, anthropomorphic features, and chatbot usage on customer satisfaction in online retailing. In this context, 396 people were reached by using the convenience sampling method, and the survey technique was used as the data collection method. The data obtained were analyzed in the SPSS 25 program. Although the research findings show that the interaction, trust, and anthropomorphism characteristics and usage levels of chatbots positively affect customer satisfaction, the trust variable provides the strongest effect.

References

  • Acharya, A. S., Prakash, A., Saxena, P., & Nigam, A. (2013). Sampling: Why and how of it. Indian Journal of Medical Specialties, 4(2), 330-333.
  • Aggarwal, P., & McGill, A. L. (2012). When brands seem human, do humans act like brands? Automatic behavioral priming effects of brand anthropomorphism. Journal of Consumer Research, 39(2), 307-323.
  • Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.
  • Akintan, I., Dabiri, M., & Ojenike, J. (2020). An appraisal of after sales service on consumer satisfaction: A study of LG Electronics in Lagos, Nigeria. International Journal of Information, Business and Management, 12(1), 92-112.
  • Antons, D., & Breidbach, C. F. (2018). Big data, big insights? Advancing service innovation and design with machine learning. Journal of Service Research, 21(1), 17-39.
  • Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing Science, 48(1), 79-95.
  • Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183-189.
  • Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020). I, chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473.
  • Bag, S., Gupta, S., Kumar, A., & Sivarajah, U. (2021). An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance. Industrial Marketing Management, 92, 178-189.
  • Balakrishnan, J., & Dwivedi, Y. K. (2021). Conversational commerce: Entering the next stage of AI-powered digital assistants. Annals of Operations Research, 1-35.
  • Barış, A. (2020). A new business marketing tool: Chatbot. GSI Journals Serie B: Advancements in Business and Economics, 3(1), 31-46.
  • Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
  • Barry, B., & Crant, J. M. (2000). Dyadic communication relationships in organizations: An attribution/expectancy approach. Organization Science, 11(6), 648-664.
  • Berger, J., Humphreys, A., Ludwig, S., Moe, W. W., Netzer, O., & Schweidel, D. A. (2020). Uniting the tribes: Using text for marketing insight. Journal of Marketing, 84(1), 1-25.
  • Brennan, K. (2006). The managed teacher: Emotional labour, education, and technology. Educational Insights, 10(2), 55-65.
  • Brill, T. M., Munoz, L., & Miller, R. J. (2022). Siri, Alexa, and other digital assistants: A study of customer satisfaction with artificial intelligence applications. In The Role of Smart Technologies in Decision Making (pp. 35-70). Routledge.
  • Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company.
  • Cevahir, E. (2020). SPSS ile nicel veri analizi rehberi. Kibele Yayınları.
  • Chatterjee, S., Ghosh, S. K., Chaudhuri, R., & Nguyen, B. (2019). Are CRM systems ready for AI integration? A conceptual framework of organizational readiness for effective AI-CRM integration. The Bottom Line, 32(2), 144-157.
  • Chen, H., Chan-Olmsted, S., Kim, J., & Sanabria, I. M. (2022). Consumers’ perception on artificial intelligence applications in marketing communication. Qualitative Market Research: An International Journal, 25(1), 125-142.
  • Cheng, Y., & Jiang, H. (2022). Customer–brand relationship in the era of artificial intelligence: Understanding the role of chatbot marketing efforts. Journal of Product & Brand Management, 31(2), 252-264.
  • Chintagunta, P., Hanssens, D. M., & Hauser, J. R. (2016). Marketing science and big data. Marketing Science, 35(3), 341-342.
  • Chung, M., Ko, E., Joung, H., & Kim, S. J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587-595.
  • Chung, N., & Kwon, S. J. (2009). Effect of trust level on mobile banking satisfaction: A multi-group analysis of information system success instruments. Behaviour & Information Technology, 28(6), 549-562.
  • Chung, T. S., Wedel, M., & Rust, R. T. (2016). Adaptive personalization using social networks. Journal of the Academy of Marketing Science, 44, 66-87.
  • Ciechanowski, L., Przegalinska, A., Magnuski, M., & Gloor, P. (2019). In the shades of the uncanny valley: An experimental study of human–chatbot interaction. Future Generation Computer Systems, 92, 539-548.
  • Colace, F., De Santo, M., Pascale, F., Lemma, S., & Lombardi, M. (2017). BotWheels: a Petri Net based chatbot for recommending tires. DATA, 17, 350-358.
  • Colgate, J. E., Wannasuphoprasit, W., & Peshkin, M. A. (1996). Cobots: Robots for collaboration with human operators. In ASME International Mechanical Engineering Congress and Exposition (Vol. 15281, pp. 433-439). American Society of Mechanical Engineers.
  • Crolic, C., Thomaz, F., Hadi, R., & Stephen, A. T. (2022). Blame the bot: Anthropomorphism and anger in customer–chatbot interactions. Journal of Marketing, 86(1), 132-148.
  • Cyr, D., Hassanein, K., Head, M., & Ivanov, A. (2007). The role of social presence in establishing loyalty in e-service environments. Interacting with Computers, 19(1), 43-56.
  • Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42.
  • de Cosmo, L. M., Piper, L., & Di Vittorio, A. (2021). The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots. Italian Journal of Marketing, 2021(1), 83-102.
  • Dekimpe, M. G. (2020). Retailing and retailing research in the age of big data analytics. International Journal of Research in Marketing, 37(1), 3-14.
  • Deloitte. (2022). E-ticaretin öne çıkan başarısı, tüketici davranışlarında değişim ve dijitalleşme. TÜSİAD. https://tusiad.org/tr/yayinlar/raporlar/item/10915-e-ticaretin-one-cikan-basarisi-tuketici-davranislarinda-degisim-ve-dijitallesme-deloitte-digital
  • de Oliveira Santini, F., Ladeira, W. J., Sampaio, C. H., & Perin, M. G. (2018). Online banking services: A meta-analytic review and assessment of the impact of antecedents and consequents on satisfaction. Journal of Financial Services Marketing, 23, 168-178.
  • Deshpande, I. (2019). What is artificial intelligence and machine learning in marketing?. https://www.spiceworks.com/marketing/ai-in-marketing/articles/what-is-artificial-intelligence-machine-learning-in-marketing/
  • Dzyabura, D., & Hauser, J. R. (2019). Recommending products when consumers learn their preference weights. Marketing Science, 38(3), 417-441.
  • Edwards, C., Edwards, A., Spence, P. R., & Shelton, A. K. (2014). Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter. Computers in Human Behavior, 33, 372-376.
  • Eren, B. A. (2021). Determinants of customer satisfaction in chatbot use: Evidence from a banking application in Turkey. International Journal of Bank Marketing, 39(2), 294-311.
  • Feine, J., Gnewuch, U., Morana, S., & Maedche, A. (2019). A taxonomy of social cues for conversational agents. International Journal of Human-Computer Studies, 132, 138-161.
  • Følstad, A., Nordheim, C. B., & Bjørkli, C. A. (2018). What makes users trust a chatbot for customer service? An exploratory interview study. In Internet Science: 5th International Conference, INSCI 2018, St. Petersburg, Russia, October 24–26, 2018, Proceedings 5 (pp. 194-208). Springer International Publishing.
  • Forbes. (2019). AI stats news: Chatbots increase sales by 67% but 87% of consumers prefer humans. https://www.forbes.com/sites/gilpress/2019/11/25/ai-stats-news-chatbots-increase-sales-by-67-but-87-of-consumers-prefer-humans/?sh=30c6f2fe48a3
  • Gabel, S., Guhl, D., & Klapper, D. (2019). P2V-MAP: Mapping market structures for large retail assortments. Journal of Marketing Research, 56(4), 557-580.
  • Gao, L., & Waechter, K. A. (2017). Examining the role of initial trust in user adoption of mobile payment services: An empirical investigation. Information Systems Frontiers, 19, 525-548.
  • Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study–A case of China. Computers in Human Behavior, 53, 249-262.
  • Giese, J. L., & Cote, J. A. (2000). Defining consumer satisfaction. Academy of Marketing Science Review, 1(1), 1-22.
  • Glavas, C., & Letheren, K. (2017). Embracing the bots: How direct to consumer advertising is about to change forever. The Conversation.
  • Gnewuch, U., Morana, S., & Maedche, A. (2017). Towards designing cooperative and social conversational agents for customer service. ICIS, 1-13.
  • Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in Human Behavior, 97, 304-316.
  • Golzar, J., Noor, S., & Tajik, O. (2022). Convenience sampling. International Journal of Education & Language Studies, 1(2), 72-77.
  • Gürbüz, S., & Şahin, F. (2014). Sosyal bilimlerde araştırma yöntemleri. Ankara: Seçkin Yayıncılık.
  • Gürsoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169.
  • Haugeland, I. K. F., Fornell, C., Følstad, A., Taylor, C., & Bjørkli, C. A. (2022). Understanding the user experience of customer service chatbots: An experimental study of chatbot interaction design. International Journal of Human-Computer Studies, 161.
  • Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.
  • Hill, J., Ford, W. R., & Farreras, I. G. (2015). Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations. Computers in Human Behavior, 49, 245-250.
  • Holzwarth, M., Janiszewski, C., & Neumann, M. M. (2006). The influence of avatars on online consumer shopping behavior. Journal of Marketing, 70(4), 19-36.
  • Hong, N. O., Govindarajan, U. H., Chien, Y. J. C., & Trappey, J. A. (2019). Comprehensive technology function product matrix for intelligent chatbot patent mining. In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) (pp. 1344-1348).
  • Hsiao, K. L., & Chen, C. C. (2022). What drives continuance intention to use a food-ordering chatbot? An examination of trust and satisfaction. Library Hi Tech, 40(4), 929-946.
  • Huang, J., Zhou, M., & Yang, D. (2007). Extracting chatbot knowledge from online discussion forums. IJCAI, 7, 423-428.
  • Huang, M. H., & Rust, R. T. (2020). Engaged to a robot? The role of AI in service. Journal of Service Research, 109467052090226.
  • Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50.
  • Humphreys, A., & Wang, R. J. H. (2018). Automated text analysis for consumer research. Journal of Consumer Research, 44(6), 1274-1306.
  • Illescas-Manzano, M. D., López, N. V., González, N. A., & Cristofol Rodríguez, C. (2021). Implementation of chatbot in online commerce, and open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 125.
  • Jarek, K., & Mazurek, G. (2019). Marketing and artificial intelligence. Central European Business Review, 8(2).
  • Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586.
  • Jiménez-Barreto, J., Rubio, N., & Molinillo, S. (2021). “Find a flight for me, Oscar!” Motivational customer experiences with chatbots. International Journal of Contemporary Hospitality Management, 33(11), 3860-3882.
  • Kallel, A., Ben Dahmane Mouelhi, N., Chaouali, W., & Danks, N. P. (2023). Hey chatbot, why do you treat me like other people? The role of uniqueness neglect in human-chatbot interactions. Journal of Strategic Marketing, 1-17.
  • Klaus, P., & Zaichkowsky, J. (2020). AI voice bots: A services marketing research agenda. Journal of Services Marketing, 34(3), 389-398.
  • Klein, K., & Martinez, L. F. (2023). The impact of anthropomorphism on customer satisfaction in chatbot commerce: An experimental study in the food sector. Electronic Commerce Research, 23, 2789-2825. https://doi.org/10.1007/s10660-022-09562-8
  • Konya-Baumbach, E., Biller, M., & von Janda, S. (2023). Someone out there? A study on the social presence of anthropomorphized chatbots. Computers in Human Behavior, 139.
  • Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61(4), 135-155.
  • Lalicic, L., & Weismayer, C. (2021). Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents. Journal of Business Research, 129, 891-901.
  • Lee, D., Hosanagar, K., & Nair, H. S. (2018). Advertising content and consumer engagement on social media: Evidence from Facebook. Management Science, 64(11), 5105-5131.
  • Lee, S. A., & Oh, H. (2021). Anthropomorphism and its implications for advertising hotel brands. Journal of Business Research, 129, 455-464.
  • Lei, S. I., Shen, H., & Ye, S. (2021). A comparison between chatbot and human service: Customer perception and reuse intention. International Journal of Contemporary Hospitality Management, 33(11), 3977-3995.
  • Letheren, K., Russell-Bennett, R., & Whittaker, L. (2020). Black, white or grey magic? Our future with artificial intelligence. Journal of Marketing Management, 36(3-4), 216-232.
  • Lin, X., Shao, B., & Wang, X. (2022). Employees' perceptions of chatbots in B2B marketing: Affordances vs. disaffordances. Industrial Marketing Management, 101, 45-56.
  • Liu, X., Singh, P. V., & Srinivasan, K. (2016). A structured analysis of unstructured big data by leveraging cloud computing. Marketing Science, 35(3), 363-388.
  • Locke, E. A. (1967). Relationship of success and expectation to affect on goal-seeking tasks. Journal of Personality and Social Psychology, 7, 125-130.
  • Locke, E. A. (1969). What is job satisfaction? Organizational Behavior and Human Performance, 4(4), 309-336.
  • Lu, L., Cai, R., & Gursoy, D. (2019). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 80, 36-51.
  • Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38(6), 937-947.
  • MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York: Lawrence Erlbaum Associates.
  • Malodia, S., Islam, N., Kaur, P., & Dhir, A. (2024). Why do people use artificial intelligence (AI)-enabled voice assistants? IEEE Transactions on Engineering Management, 71, 491-505. https://doi.org/10.1109/TEM.2021.3117884
  • Marinova, D., Singh, S. K., & Singh, J. (2018). Frontline problem-solving effectiveness: A dynamic analysis of verbal and nonverbal cues. Journal of Marketing Research, 55(2), 178-192.
  • Mende, M., Scott, M. L., van Doorn, J., Grewal, D., & Shanks, I. (2019). Service robots rising: How humanoid robots influence service experiences and elicit compensatory consumer responses. Journal of Marketing Research, 56(4), 535-556.
  • Michaud, L. N. (2018). Observations of a new chatbot: Drawing conclusions from early interactions with users. IT Professional, 20(5), 40-47.
  • Mimoun, M. S. B., Poncin, I., & Garnier, M. (2017). Animated conversational agents and e-consumer productivity: The roles of agents and individual characteristics. Information & Management, 54(5), 545-559.
  • Moffett, J. W., Folse, J. A. G., & Palmatier, R. W. (2021). A theory of multiformat communication: Mechanisms, dynamics, and strategies. Journal of the Academy of Marketing Science, 49, 441-461.
  • Mozafari, N., Weiger, W. H., & Hammerschmidt, M. (2022). Trust me, I'm a bot–repercussions of chatbot disclosure in different service frontline settings. Journal of Service Management, 33(2), 221-245.
  • Murtarelli, G., Gregory, A., & Romenti, S. (2021). A conversation-based perspective for shaping ethical human–machine interactions: The particular challenge of chatbots. Journal of Business Research, 129, 927-935.
  • Netzer, O., Lemaire, A., & Herzenstein, M. (2019). When words sweat: Identifying signals for loan default in the text of loan applications. Journal of Marketing Research, 56(6), 960-980.
  • Nguyen, T. (2019). Potential effects of chatbot technology on customer support: A case study.
  • Sharma, S., Durand, R. M., & Gur-Arie, O. (1981). Identification and analysis of moderator variables. Journal of Marketing Research, 18(3), 291-300.
  • Nordheim, C. B., Følstad, A., & Bjørkli, C. A. (2019). An initial model of trust in chatbots for customer service—findings from a questionnaire study. Interacting with Computers, 31(3), 317-335.
  • Overgoor, G., Chica, M., Rand, W., & Weishampel, A. (2019). Letting the computers take over: Using AI to solve marketing problems. California Management Review, 61(4), 156-185.
  • Pallant, J. (2001). SPSS survival manual: A step by step guide to data analysis using SPSS. Open University Press.
  • Pantano, E., & Pizzi, G. (2020). Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis. Journal of Retailing and Consumer Services, 55, 1-9.
  • Parker, C., & Mathews, B. P. (2001). Customer satisfaction: Contrasting academic and consumers’ interpretations. Marketing Intelligence & Planning, 19(1), 38-44.
  • Paschen, J., Kietzmann, J., & Kietzmann, T. C. (2019). Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of Business & Industrial Marketing, 34(7), 1410-1419.
  • Pitt, C. S., Bal, A. S., & Plangger, K. (2020). New approaches to psychographic consumer segmentation: Exploring fine art collectors using artificial intelligence, automated text analysis and correspondence analysis. European Journal of Marketing, 54(2), 305-326.
  • Prakash, A. V., Joshi, A., Nim, S., & Das, S. (2023). Determinants and consequences of trust in AI-based customer service chatbots. The Service Industries Journal, 1-34.
  • Przegalinska, A., Ciechanowski, L., Stroz, A., Gloor, P., & Mazurek, G. (2019). In bot we trust: A new methodology of chatbot performance measures. Business Horizons, 62(6), 785-797.
  • Roller, S., Dinan, E., Goyal, N., Ju, D., Williamson, M., Liu, Y., & Boureau, Y. L. (2020). Recipes for building an open-domain chatbot. arXiv preprint. arXiv:2004.13637.
  • Roy, R., & Naidoo, V. (2021). Enhancing chatbot effectiveness: The role of anthropomorphic conversational styles and time orientation. Journal of Business Research, 126, 23-34.
  • Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach. Pearson Education Limited.
  • Schuetzler, R. M., Grimes, G. M., & Giboney, J. S. (2020). The impact of chatbot conversational skill on engagement and perceived humanness. Journal of Management Information Systems, 37(3), 875-900.
  • Seranmadevi, R., & Kumar, A. (2019). Experiencing the AI emergence in Indian retail–Early adopters approach. Management Science Letters, 9(1), 33-42.
  • Sha, S. N., & Rajeswari, M. (2019). Creating a brand value and consumer satisfaction in E-commerce business using artificial intelligence with the help of VOSAG technology. International Journal of Innovative Technology and Exploring Engineering, 8(8), 1510-1515.
  • Shawar, B. A., & Atwell, E. S. (2005). Using corpora in machine-learning chatbot systems. International Journal of Corpus Linguistics, 10(4), 489-516.
  • Sheehan, B., Jin, H. S., & Gottlieb, U. (2020). Customer service chatbots: Anthropomorphism and adoption. Journal of Business Research, 115, 14-24.
  • Shokouhyar, S., Shokoohyar, S., & Safari, S. (2020). Research on the influence of after-sales service quality factors on customer satisfaction. Journal of Retailing and Consumer Services, 56, 102139.
  • Shrestha, N. (2021). Factor analysis as a tool for survey analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4-11.
  • Siau, K. L., & Yang, Y. (2017). Impact of artificial intelligence, robotics, and machine learning on sales and marketing. MWAIS 2017 Proceedings, 48.
  • Singh, R., Paste, M., Shinde, N., Patel, H., & Mishra, N. (2018). Chatbot using TensorFlow for small businesses. In 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) (pp. 1614-1619).
  • Sivaramakrishnan, S., Wan, F., & Tang, Z. (2007). Giving an “e‐human touch” to e‐tailing: The moderating roles of static information quantity and consumption motive in the effectiveness of an anthropomorphic information agent. Journal of Interactive Marketing, 21(1), 60-75.
  • Sowa, K., Przegalinska, A., & Ciechanowski, L. (2021). Cobots in knowledge work: Human–AI collaboration in managerial professions. Journal of Business Research, 125, 135-142.
  • Söderlund, M., & Oikarinen, E. L. (2021). Service encounters with virtual agents: An examination of perceived humanness as a source of customer satisfaction. European Journal of Marketing, 55(13), 94-121.
  • Stephen, A., & Ahmad, Y. (2017). Recreating intimacy with connected consumers. NIM Marketing Intelligence Review, 9(2), 48-53.
  • Teo, T. S., Srivastava, S. C., & Jiang, L. I. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99-132.
  • Trappey, A. J. C., Trappey, C., Govindarajan, U. H., Sharma, A., & Yeh, L. C. (2018). Conversational service bot specifications for advanced manufacturing applications. In 2018 IEEE International Conference on Advanced Manufacturing (ICAM 2018).
  • Tripathi, S., & Verma, S. (2018). Social media, an emerging platform for relationship building: A study of engagement with non-government organizations in India. International Journal of Nonprofit and Voluntary Sector Marketing, 23(1), e1589.
  • Valls, A., Gibert, K., Orellana, A., & Antón-Clavé, S. (2018). Using ontology-based clustering to understand the push and pull factors for British tourists visiting a Mediterranean coastal destination. Information & Management, 55(2), 145-159.
  • Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002.
  • Wamba, S. F., Bawack, R. E., Guthrie, C., Queiroz, M. M., & Carillo, K. D. A. (2021). Are we preparing for a good AI society? A bibliometric review and research agenda. Technological Forecasting and Social Change, 164, 120482.
  • Wang, L. C., Baker, J., Wagner, J. A., & Wakefield, K. (2007). Can a retail web site be social? Journal of Marketing, 71(3), 143-157.
  • Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97-121.
  • Westbrook, R. A., & Reilly, M. D. (1983). Value-percept disparity: An alternative to the disconfirmation of expectations theory of consumer satisfaction. Advances in Consumer Research, 10(1).
  • Whang, J. B., Song, J. H., Lee, J. H., & Choi, B. (2022). Interacting with chatbots: Message type and consumers' control. Journal of Business Research, 153, 309-318.
  • Wiliam, A., Sasmoko, H., Prabowo, M., Hamsal, E., & Princes, Y. (2019). Analysis of e-service chatbot and satisfaction of banking customers in Indonesia. Asia Proceedings of Social Sciences, 4(3), 72-75.
  • Wilson-Nash, C., Goode, A., & Currie, A. (2020). Introducing the socialbot: A novel touchpoint along the young adult customer journey. European Journal of Marketing, 54(10), 2621-2643.
  • Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world: Service robots in the frontline. Journal of Service Management, 29(5), 907-931.
  • Xu, Y., Niu, N., & Zhao, Z. (2023). Dissecting the mixed effects of human-customer service chatbot interaction on customer satisfaction: An explanation from temporal and conversational cues. Journal of Retailing and Consumer Services, 74, 103417.
  • Yagoda, R. E., & Gillan, D. J. (2012). You want me to trust a ROBOT? The development of a human–robot interaction trust scale. International Journal of Social Robotics, 4, 235-248.
  • Yao, M. (2017). 100 best bots for brands and business. www.topbots.com/100-best-bots-brands-businesses/
  • Yun, J., & Park, J. (2022). The effects of chatbot service recovery with emotion words on customer satisfaction, repurchase intention, and positive word-of-mouth. Frontiers in Psychology, 13, 922503.
  • Zamora, J. (2017). I'm sorry, Dave, I'm afraid I can't do that: Chatbot perception and expectations. In Proceedings of the 5th International Conference on Human Agent Interaction (pp. 253-260).
  • Zarouali, B., Van den Broeck, E., Walrave, M., & Poels, K. (2018). Predicting consumer responses to a chatbot on Facebook. Cyberpsychology, Behavior, and Social Networking, 21(8), 491-497.
  • Zehir, C., Şahin, A., Kitapçı, H., & Özşahin, M. (2011). The effects of brand communication and service quality in building brand loyalty through brand trust: The empirical research on global brands. Procedia-Social and Behavioral Sciences, 24, 1218-1231.

Çevrimiçi perakendecilikte sohbet robotu kullanımında etkileşim, güven antropomorfizm ve kullanım seviyesinin müşteri memnuniyetine etkisi

Year 2024, Volume: 26 Issue: Özel Sayı, 81 - 100, 21.10.2024
https://doi.org/10.33707/akuiibfd.1459114

Abstract

Günümüzde sohbet robotları, çevrimiçi perakende ortamlarında giderek yaygınlaşmakta ve markaların müşterilerle etkileşim kurma ve hizmet sunma biçimlerini yeniden tasarlamalarına neden olmaktadırlar. Özellikle genç nüfus yoğunluğunun artması, yoğun iş temposu ve çevrimiçi perakendeciliğin hızla yayılması gibi nedenlerle daha iyi müşteri deneyimi yaratmak ve rekabet avantajı elde etmek amacıyla sohbet robotu hizmetlerinin giderek arttığı görülmektedir. Sohbet robotlarının çok sayıda özelliği olmasına karşın, özellikle sohbet robotlarıyla kurulan etkileşim, sohbet robotlarına yönelik güven algısı ve cansız varlıklara insani özellikler yüklenmesini ifade eden antropomorfik özellikler, kullanıcıların memnuniyet düzeylerini etkilemektedir. Bu doğrultuda araştırmanın amacı, çevrimiçi perakendecilikte kullanılan sohbet robotlarının etkileşim, güven, kullanım seviyesi ve antropomorfik özelliklere ilişkin tüketici algılarının müşteri memnuniyetine etkisini ölçmektir. Bu kapsamda örnekleme yöntemi olarak kolayda örnekleme yöntemi, veri toplama yöntemi olarak da anket tekniği kullanılarak 396 kişiye ulaşılmıştır. Elde edilen veriler SPSS 25 programında analiz edilmiştir. Araştırma sonucunda, sohbet robotlarının etkileşim, güven, antropomorfizm özellikleri ile kullanım seviyesinin müşteri memnuniyeti üzerinde olumlu bir etkiye sahip olduğunu ancak, en kuvvetli etkinin güven değişkeninden sağlandığı ortaya çıkmıştır.

References

  • Acharya, A. S., Prakash, A., Saxena, P., & Nigam, A. (2013). Sampling: Why and how of it. Indian Journal of Medical Specialties, 4(2), 330-333.
  • Aggarwal, P., & McGill, A. L. (2012). When brands seem human, do humans act like brands? Automatic behavioral priming effects of brand anthropomorphism. Journal of Consumer Research, 39(2), 307-323.
  • Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.
  • Akintan, I., Dabiri, M., & Ojenike, J. (2020). An appraisal of after sales service on consumer satisfaction: A study of LG Electronics in Lagos, Nigeria. International Journal of Information, Business and Management, 12(1), 92-112.
  • Antons, D., & Breidbach, C. F. (2018). Big data, big insights? Advancing service innovation and design with machine learning. Journal of Service Research, 21(1), 17-39.
  • Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing Science, 48(1), 79-95.
  • Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183-189.
  • Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020). I, chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473.
  • Bag, S., Gupta, S., Kumar, A., & Sivarajah, U. (2021). An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance. Industrial Marketing Management, 92, 178-189.
  • Balakrishnan, J., & Dwivedi, Y. K. (2021). Conversational commerce: Entering the next stage of AI-powered digital assistants. Annals of Operations Research, 1-35.
  • Barış, A. (2020). A new business marketing tool: Chatbot. GSI Journals Serie B: Advancements in Business and Economics, 3(1), 31-46.
  • Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
  • Barry, B., & Crant, J. M. (2000). Dyadic communication relationships in organizations: An attribution/expectancy approach. Organization Science, 11(6), 648-664.
  • Berger, J., Humphreys, A., Ludwig, S., Moe, W. W., Netzer, O., & Schweidel, D. A. (2020). Uniting the tribes: Using text for marketing insight. Journal of Marketing, 84(1), 1-25.
  • Brennan, K. (2006). The managed teacher: Emotional labour, education, and technology. Educational Insights, 10(2), 55-65.
  • Brill, T. M., Munoz, L., & Miller, R. J. (2022). Siri, Alexa, and other digital assistants: A study of customer satisfaction with artificial intelligence applications. In The Role of Smart Technologies in Decision Making (pp. 35-70). Routledge.
  • Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company.
  • Cevahir, E. (2020). SPSS ile nicel veri analizi rehberi. Kibele Yayınları.
  • Chatterjee, S., Ghosh, S. K., Chaudhuri, R., & Nguyen, B. (2019). Are CRM systems ready for AI integration? A conceptual framework of organizational readiness for effective AI-CRM integration. The Bottom Line, 32(2), 144-157.
  • Chen, H., Chan-Olmsted, S., Kim, J., & Sanabria, I. M. (2022). Consumers’ perception on artificial intelligence applications in marketing communication. Qualitative Market Research: An International Journal, 25(1), 125-142.
  • Cheng, Y., & Jiang, H. (2022). Customer–brand relationship in the era of artificial intelligence: Understanding the role of chatbot marketing efforts. Journal of Product & Brand Management, 31(2), 252-264.
  • Chintagunta, P., Hanssens, D. M., & Hauser, J. R. (2016). Marketing science and big data. Marketing Science, 35(3), 341-342.
  • Chung, M., Ko, E., Joung, H., & Kim, S. J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587-595.
  • Chung, N., & Kwon, S. J. (2009). Effect of trust level on mobile banking satisfaction: A multi-group analysis of information system success instruments. Behaviour & Information Technology, 28(6), 549-562.
  • Chung, T. S., Wedel, M., & Rust, R. T. (2016). Adaptive personalization using social networks. Journal of the Academy of Marketing Science, 44, 66-87.
  • Ciechanowski, L., Przegalinska, A., Magnuski, M., & Gloor, P. (2019). In the shades of the uncanny valley: An experimental study of human–chatbot interaction. Future Generation Computer Systems, 92, 539-548.
  • Colace, F., De Santo, M., Pascale, F., Lemma, S., & Lombardi, M. (2017). BotWheels: a Petri Net based chatbot for recommending tires. DATA, 17, 350-358.
  • Colgate, J. E., Wannasuphoprasit, W., & Peshkin, M. A. (1996). Cobots: Robots for collaboration with human operators. In ASME International Mechanical Engineering Congress and Exposition (Vol. 15281, pp. 433-439). American Society of Mechanical Engineers.
  • Crolic, C., Thomaz, F., Hadi, R., & Stephen, A. T. (2022). Blame the bot: Anthropomorphism and anger in customer–chatbot interactions. Journal of Marketing, 86(1), 132-148.
  • Cyr, D., Hassanein, K., Head, M., & Ivanov, A. (2007). The role of social presence in establishing loyalty in e-service environments. Interacting with Computers, 19(1), 43-56.
  • Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42.
  • de Cosmo, L. M., Piper, L., & Di Vittorio, A. (2021). The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots. Italian Journal of Marketing, 2021(1), 83-102.
  • Dekimpe, M. G. (2020). Retailing and retailing research in the age of big data analytics. International Journal of Research in Marketing, 37(1), 3-14.
  • Deloitte. (2022). E-ticaretin öne çıkan başarısı, tüketici davranışlarında değişim ve dijitalleşme. TÜSİAD. https://tusiad.org/tr/yayinlar/raporlar/item/10915-e-ticaretin-one-cikan-basarisi-tuketici-davranislarinda-degisim-ve-dijitallesme-deloitte-digital
  • de Oliveira Santini, F., Ladeira, W. J., Sampaio, C. H., & Perin, M. G. (2018). Online banking services: A meta-analytic review and assessment of the impact of antecedents and consequents on satisfaction. Journal of Financial Services Marketing, 23, 168-178.
  • Deshpande, I. (2019). What is artificial intelligence and machine learning in marketing?. https://www.spiceworks.com/marketing/ai-in-marketing/articles/what-is-artificial-intelligence-machine-learning-in-marketing/
  • Dzyabura, D., & Hauser, J. R. (2019). Recommending products when consumers learn their preference weights. Marketing Science, 38(3), 417-441.
  • Edwards, C., Edwards, A., Spence, P. R., & Shelton, A. K. (2014). Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter. Computers in Human Behavior, 33, 372-376.
  • Eren, B. A. (2021). Determinants of customer satisfaction in chatbot use: Evidence from a banking application in Turkey. International Journal of Bank Marketing, 39(2), 294-311.
  • Feine, J., Gnewuch, U., Morana, S., & Maedche, A. (2019). A taxonomy of social cues for conversational agents. International Journal of Human-Computer Studies, 132, 138-161.
  • Følstad, A., Nordheim, C. B., & Bjørkli, C. A. (2018). What makes users trust a chatbot for customer service? An exploratory interview study. In Internet Science: 5th International Conference, INSCI 2018, St. Petersburg, Russia, October 24–26, 2018, Proceedings 5 (pp. 194-208). Springer International Publishing.
  • Forbes. (2019). AI stats news: Chatbots increase sales by 67% but 87% of consumers prefer humans. https://www.forbes.com/sites/gilpress/2019/11/25/ai-stats-news-chatbots-increase-sales-by-67-but-87-of-consumers-prefer-humans/?sh=30c6f2fe48a3
  • Gabel, S., Guhl, D., & Klapper, D. (2019). P2V-MAP: Mapping market structures for large retail assortments. Journal of Marketing Research, 56(4), 557-580.
  • Gao, L., & Waechter, K. A. (2017). Examining the role of initial trust in user adoption of mobile payment services: An empirical investigation. Information Systems Frontiers, 19, 525-548.
  • Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study–A case of China. Computers in Human Behavior, 53, 249-262.
  • Giese, J. L., & Cote, J. A. (2000). Defining consumer satisfaction. Academy of Marketing Science Review, 1(1), 1-22.
  • Glavas, C., & Letheren, K. (2017). Embracing the bots: How direct to consumer advertising is about to change forever. The Conversation.
  • Gnewuch, U., Morana, S., & Maedche, A. (2017). Towards designing cooperative and social conversational agents for customer service. ICIS, 1-13.
  • Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in Human Behavior, 97, 304-316.
  • Golzar, J., Noor, S., & Tajik, O. (2022). Convenience sampling. International Journal of Education & Language Studies, 1(2), 72-77.
  • Gürbüz, S., & Şahin, F. (2014). Sosyal bilimlerde araştırma yöntemleri. Ankara: Seçkin Yayıncılık.
  • Gürsoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169.
  • Haugeland, I. K. F., Fornell, C., Følstad, A., Taylor, C., & Bjørkli, C. A. (2022). Understanding the user experience of customer service chatbots: An experimental study of chatbot interaction design. International Journal of Human-Computer Studies, 161.
  • Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.
  • Hill, J., Ford, W. R., & Farreras, I. G. (2015). Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations. Computers in Human Behavior, 49, 245-250.
  • Holzwarth, M., Janiszewski, C., & Neumann, M. M. (2006). The influence of avatars on online consumer shopping behavior. Journal of Marketing, 70(4), 19-36.
  • Hong, N. O., Govindarajan, U. H., Chien, Y. J. C., & Trappey, J. A. (2019). Comprehensive technology function product matrix for intelligent chatbot patent mining. In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) (pp. 1344-1348).
  • Hsiao, K. L., & Chen, C. C. (2022). What drives continuance intention to use a food-ordering chatbot? An examination of trust and satisfaction. Library Hi Tech, 40(4), 929-946.
  • Huang, J., Zhou, M., & Yang, D. (2007). Extracting chatbot knowledge from online discussion forums. IJCAI, 7, 423-428.
  • Huang, M. H., & Rust, R. T. (2020). Engaged to a robot? The role of AI in service. Journal of Service Research, 109467052090226.
  • Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50.
  • Humphreys, A., & Wang, R. J. H. (2018). Automated text analysis for consumer research. Journal of Consumer Research, 44(6), 1274-1306.
  • Illescas-Manzano, M. D., López, N. V., González, N. A., & Cristofol Rodríguez, C. (2021). Implementation of chatbot in online commerce, and open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 125.
  • Jarek, K., & Mazurek, G. (2019). Marketing and artificial intelligence. Central European Business Review, 8(2).
  • Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586.
  • Jiménez-Barreto, J., Rubio, N., & Molinillo, S. (2021). “Find a flight for me, Oscar!” Motivational customer experiences with chatbots. International Journal of Contemporary Hospitality Management, 33(11), 3860-3882.
  • Kallel, A., Ben Dahmane Mouelhi, N., Chaouali, W., & Danks, N. P. (2023). Hey chatbot, why do you treat me like other people? The role of uniqueness neglect in human-chatbot interactions. Journal of Strategic Marketing, 1-17.
  • Klaus, P., & Zaichkowsky, J. (2020). AI voice bots: A services marketing research agenda. Journal of Services Marketing, 34(3), 389-398.
  • Klein, K., & Martinez, L. F. (2023). The impact of anthropomorphism on customer satisfaction in chatbot commerce: An experimental study in the food sector. Electronic Commerce Research, 23, 2789-2825. https://doi.org/10.1007/s10660-022-09562-8
  • Konya-Baumbach, E., Biller, M., & von Janda, S. (2023). Someone out there? A study on the social presence of anthropomorphized chatbots. Computers in Human Behavior, 139.
  • Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61(4), 135-155.
  • Lalicic, L., & Weismayer, C. (2021). Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents. Journal of Business Research, 129, 891-901.
  • Lee, D., Hosanagar, K., & Nair, H. S. (2018). Advertising content and consumer engagement on social media: Evidence from Facebook. Management Science, 64(11), 5105-5131.
  • Lee, S. A., & Oh, H. (2021). Anthropomorphism and its implications for advertising hotel brands. Journal of Business Research, 129, 455-464.
  • Lei, S. I., Shen, H., & Ye, S. (2021). A comparison between chatbot and human service: Customer perception and reuse intention. International Journal of Contemporary Hospitality Management, 33(11), 3977-3995.
  • Letheren, K., Russell-Bennett, R., & Whittaker, L. (2020). Black, white or grey magic? Our future with artificial intelligence. Journal of Marketing Management, 36(3-4), 216-232.
  • Lin, X., Shao, B., & Wang, X. (2022). Employees' perceptions of chatbots in B2B marketing: Affordances vs. disaffordances. Industrial Marketing Management, 101, 45-56.
  • Liu, X., Singh, P. V., & Srinivasan, K. (2016). A structured analysis of unstructured big data by leveraging cloud computing. Marketing Science, 35(3), 363-388.
  • Locke, E. A. (1967). Relationship of success and expectation to affect on goal-seeking tasks. Journal of Personality and Social Psychology, 7, 125-130.
  • Locke, E. A. (1969). What is job satisfaction? Organizational Behavior and Human Performance, 4(4), 309-336.
  • Lu, L., Cai, R., & Gursoy, D. (2019). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 80, 36-51.
  • Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38(6), 937-947.
  • MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York: Lawrence Erlbaum Associates.
  • Malodia, S., Islam, N., Kaur, P., & Dhir, A. (2024). Why do people use artificial intelligence (AI)-enabled voice assistants? IEEE Transactions on Engineering Management, 71, 491-505. https://doi.org/10.1109/TEM.2021.3117884
  • Marinova, D., Singh, S. K., & Singh, J. (2018). Frontline problem-solving effectiveness: A dynamic analysis of verbal and nonverbal cues. Journal of Marketing Research, 55(2), 178-192.
  • Mende, M., Scott, M. L., van Doorn, J., Grewal, D., & Shanks, I. (2019). Service robots rising: How humanoid robots influence service experiences and elicit compensatory consumer responses. Journal of Marketing Research, 56(4), 535-556.
  • Michaud, L. N. (2018). Observations of a new chatbot: Drawing conclusions from early interactions with users. IT Professional, 20(5), 40-47.
  • Mimoun, M. S. B., Poncin, I., & Garnier, M. (2017). Animated conversational agents and e-consumer productivity: The roles of agents and individual characteristics. Information & Management, 54(5), 545-559.
  • Moffett, J. W., Folse, J. A. G., & Palmatier, R. W. (2021). A theory of multiformat communication: Mechanisms, dynamics, and strategies. Journal of the Academy of Marketing Science, 49, 441-461.
  • Mozafari, N., Weiger, W. H., & Hammerschmidt, M. (2022). Trust me, I'm a bot–repercussions of chatbot disclosure in different service frontline settings. Journal of Service Management, 33(2), 221-245.
  • Murtarelli, G., Gregory, A., & Romenti, S. (2021). A conversation-based perspective for shaping ethical human–machine interactions: The particular challenge of chatbots. Journal of Business Research, 129, 927-935.
  • Netzer, O., Lemaire, A., & Herzenstein, M. (2019). When words sweat: Identifying signals for loan default in the text of loan applications. Journal of Marketing Research, 56(6), 960-980.
  • Nguyen, T. (2019). Potential effects of chatbot technology on customer support: A case study.
  • Sharma, S., Durand, R. M., & Gur-Arie, O. (1981). Identification and analysis of moderator variables. Journal of Marketing Research, 18(3), 291-300.
  • Nordheim, C. B., Følstad, A., & Bjørkli, C. A. (2019). An initial model of trust in chatbots for customer service—findings from a questionnaire study. Interacting with Computers, 31(3), 317-335.
  • Overgoor, G., Chica, M., Rand, W., & Weishampel, A. (2019). Letting the computers take over: Using AI to solve marketing problems. California Management Review, 61(4), 156-185.
  • Pallant, J. (2001). SPSS survival manual: A step by step guide to data analysis using SPSS. Open University Press.
  • Pantano, E., & Pizzi, G. (2020). Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis. Journal of Retailing and Consumer Services, 55, 1-9.
  • Parker, C., & Mathews, B. P. (2001). Customer satisfaction: Contrasting academic and consumers’ interpretations. Marketing Intelligence & Planning, 19(1), 38-44.
  • Paschen, J., Kietzmann, J., & Kietzmann, T. C. (2019). Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of Business & Industrial Marketing, 34(7), 1410-1419.
  • Pitt, C. S., Bal, A. S., & Plangger, K. (2020). New approaches to psychographic consumer segmentation: Exploring fine art collectors using artificial intelligence, automated text analysis and correspondence analysis. European Journal of Marketing, 54(2), 305-326.
  • Prakash, A. V., Joshi, A., Nim, S., & Das, S. (2023). Determinants and consequences of trust in AI-based customer service chatbots. The Service Industries Journal, 1-34.
  • Przegalinska, A., Ciechanowski, L., Stroz, A., Gloor, P., & Mazurek, G. (2019). In bot we trust: A new methodology of chatbot performance measures. Business Horizons, 62(6), 785-797.
  • Roller, S., Dinan, E., Goyal, N., Ju, D., Williamson, M., Liu, Y., & Boureau, Y. L. (2020). Recipes for building an open-domain chatbot. arXiv preprint. arXiv:2004.13637.
  • Roy, R., & Naidoo, V. (2021). Enhancing chatbot effectiveness: The role of anthropomorphic conversational styles and time orientation. Journal of Business Research, 126, 23-34.
  • Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach. Pearson Education Limited.
  • Schuetzler, R. M., Grimes, G. M., & Giboney, J. S. (2020). The impact of chatbot conversational skill on engagement and perceived humanness. Journal of Management Information Systems, 37(3), 875-900.
  • Seranmadevi, R., & Kumar, A. (2019). Experiencing the AI emergence in Indian retail–Early adopters approach. Management Science Letters, 9(1), 33-42.
  • Sha, S. N., & Rajeswari, M. (2019). Creating a brand value and consumer satisfaction in E-commerce business using artificial intelligence with the help of VOSAG technology. International Journal of Innovative Technology and Exploring Engineering, 8(8), 1510-1515.
  • Shawar, B. A., & Atwell, E. S. (2005). Using corpora in machine-learning chatbot systems. International Journal of Corpus Linguistics, 10(4), 489-516.
  • Sheehan, B., Jin, H. S., & Gottlieb, U. (2020). Customer service chatbots: Anthropomorphism and adoption. Journal of Business Research, 115, 14-24.
  • Shokouhyar, S., Shokoohyar, S., & Safari, S. (2020). Research on the influence of after-sales service quality factors on customer satisfaction. Journal of Retailing and Consumer Services, 56, 102139.
  • Shrestha, N. (2021). Factor analysis as a tool for survey analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4-11.
  • Siau, K. L., & Yang, Y. (2017). Impact of artificial intelligence, robotics, and machine learning on sales and marketing. MWAIS 2017 Proceedings, 48.
  • Singh, R., Paste, M., Shinde, N., Patel, H., & Mishra, N. (2018). Chatbot using TensorFlow for small businesses. In 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) (pp. 1614-1619).
  • Sivaramakrishnan, S., Wan, F., & Tang, Z. (2007). Giving an “e‐human touch” to e‐tailing: The moderating roles of static information quantity and consumption motive in the effectiveness of an anthropomorphic information agent. Journal of Interactive Marketing, 21(1), 60-75.
  • Sowa, K., Przegalinska, A., & Ciechanowski, L. (2021). Cobots in knowledge work: Human–AI collaboration in managerial professions. Journal of Business Research, 125, 135-142.
  • Söderlund, M., & Oikarinen, E. L. (2021). Service encounters with virtual agents: An examination of perceived humanness as a source of customer satisfaction. European Journal of Marketing, 55(13), 94-121.
  • Stephen, A., & Ahmad, Y. (2017). Recreating intimacy with connected consumers. NIM Marketing Intelligence Review, 9(2), 48-53.
  • Teo, T. S., Srivastava, S. C., & Jiang, L. I. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99-132.
  • Trappey, A. J. C., Trappey, C., Govindarajan, U. H., Sharma, A., & Yeh, L. C. (2018). Conversational service bot specifications for advanced manufacturing applications. In 2018 IEEE International Conference on Advanced Manufacturing (ICAM 2018).
  • Tripathi, S., & Verma, S. (2018). Social media, an emerging platform for relationship building: A study of engagement with non-government organizations in India. International Journal of Nonprofit and Voluntary Sector Marketing, 23(1), e1589.
  • Valls, A., Gibert, K., Orellana, A., & Antón-Clavé, S. (2018). Using ontology-based clustering to understand the push and pull factors for British tourists visiting a Mediterranean coastal destination. Information & Management, 55(2), 145-159.
  • Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002.
  • Wamba, S. F., Bawack, R. E., Guthrie, C., Queiroz, M. M., & Carillo, K. D. A. (2021). Are we preparing for a good AI society? A bibliometric review and research agenda. Technological Forecasting and Social Change, 164, 120482.
  • Wang, L. C., Baker, J., Wagner, J. A., & Wakefield, K. (2007). Can a retail web site be social? Journal of Marketing, 71(3), 143-157.
  • Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97-121.
  • Westbrook, R. A., & Reilly, M. D. (1983). Value-percept disparity: An alternative to the disconfirmation of expectations theory of consumer satisfaction. Advances in Consumer Research, 10(1).
  • Whang, J. B., Song, J. H., Lee, J. H., & Choi, B. (2022). Interacting with chatbots: Message type and consumers' control. Journal of Business Research, 153, 309-318.
  • Wiliam, A., Sasmoko, H., Prabowo, M., Hamsal, E., & Princes, Y. (2019). Analysis of e-service chatbot and satisfaction of banking customers in Indonesia. Asia Proceedings of Social Sciences, 4(3), 72-75.
  • Wilson-Nash, C., Goode, A., & Currie, A. (2020). Introducing the socialbot: A novel touchpoint along the young adult customer journey. European Journal of Marketing, 54(10), 2621-2643.
  • Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world: Service robots in the frontline. Journal of Service Management, 29(5), 907-931.
  • Xu, Y., Niu, N., & Zhao, Z. (2023). Dissecting the mixed effects of human-customer service chatbot interaction on customer satisfaction: An explanation from temporal and conversational cues. Journal of Retailing and Consumer Services, 74, 103417.
  • Yagoda, R. E., & Gillan, D. J. (2012). You want me to trust a ROBOT? The development of a human–robot interaction trust scale. International Journal of Social Robotics, 4, 235-248.
  • Yao, M. (2017). 100 best bots for brands and business. www.topbots.com/100-best-bots-brands-businesses/
  • Yun, J., & Park, J. (2022). The effects of chatbot service recovery with emotion words on customer satisfaction, repurchase intention, and positive word-of-mouth. Frontiers in Psychology, 13, 922503.
  • Zamora, J. (2017). I'm sorry, Dave, I'm afraid I can't do that: Chatbot perception and expectations. In Proceedings of the 5th International Conference on Human Agent Interaction (pp. 253-260).
  • Zarouali, B., Van den Broeck, E., Walrave, M., & Poels, K. (2018). Predicting consumer responses to a chatbot on Facebook. Cyberpsychology, Behavior, and Social Networking, 21(8), 491-497.
  • Zehir, C., Şahin, A., Kitapçı, H., & Özşahin, M. (2011). The effects of brand communication and service quality in building brand loyalty through brand trust: The empirical research on global brands. Procedia-Social and Behavioral Sciences, 24, 1218-1231.
There are 139 citations in total.

Details

Primary Language Turkish
Subjects Marketing (Other)
Journal Section Research Articles
Authors

Keti Ventura 0000-0002-6422-0518

Tuğberk Karabaşak 0000-0002-0742-0038

Early Pub Date August 16, 2024
Publication Date October 21, 2024
Submission Date March 26, 2024
Acceptance Date July 25, 2024
Published in Issue Year 2024 Volume: 26 Issue: Özel Sayı

Cite

APA Ventura, K., & Karabaşak, T. (2024). Çevrimiçi perakendecilikte sohbet robotu kullanımında etkileşim, güven antropomorfizm ve kullanım seviyesinin müşteri memnuniyetine etkisi. Afyon Kocatepe Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 26(Özel Sayı), 81-100. https://doi.org/10.33707/akuiibfd.1459114

download