Araştırma Makalesi
BibTex RIS Kaynak Göster

ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA

Yıl 2023, Cilt: 6 Sayı: 2, 98 - 127, 31.12.2023
https://doi.org/10.46238/jobda.1299432

Öz

Sohbet robotu yapay zeka uygulamalarından biridir. İşletmeler müşterilerine bilgi vermek, web sitesi içinde yönlendirme yapmak, sorulara anında ve hızlı bir şekilde cevap verebilmek için sohbet robotundan faydalanmaktadırlar. Çalışmanın amacı, endüstriyel pazarda satış çalışanlarının satış faaliyetlerinde sohbet robotlarını kullanımına ilişkin amaç, beklentileri ve elde edilebileceği faydaları ile algılanan engelleri ve endişeleri ortaya koymaktır. Ayrıca sohbet robotlarının müşteri deneyimine sağlayacağı katkıları belirlemektir. Bu doğrultuda 10 satış çalışanı ile derinlemesine görüşmeler yapılmıştır. Görüşmelerin analizinde içerik analizi kullanılmıştır. Çalışma sonuçlarına göre, satış çalışanlarının satış faaliyetlerinde sohbet robotlarını kullanımına ilişkin amaç, beklentileri ve elde edilebileceği faydalar; ürün, lojistik, stok bilgisi sağlaması, departmanlararası veri paylaşması, temel sorularına hızlı cevap vermesi, müşteriyi ilgili kişiye yönlendirmesi, müşteri verilerinin toplanması, rutin işleri takip ederek ziyaret planlaması, şikayet takibi yapması, müşterinin firmaya kaydolmasını kolaylaştırması, farklı dil özelliklerini kullanması, e-postaları analiz ederek önceliklendirmesi ve yanıt verebilmesidir. Satış çalışanları sohbet robotunun doğru şekilde çalışmaması, kişinin izni ve bilgisi olmadan müşteriye yanlış bilgi (randevu, fiyat, temin, stok gibi) paylaşması, müşteri ile sorun yaşaması, talepleri doğru tahmin edememesi konularında endişe duymaktadırlar. Katılımcılar sohbet robotu kullanmalarında algılanan engeller; endüstriyel pazardaki işlerin ve ürünlerin teknik, müşteri kaybetme riskinin yüksek ve maliyetli olması olarak ifade etmişlerdir. Ayrıca sohbet robotunun algılama hatası vermesinin, kullanıcı duygularını anlama zorluğunun, verilen bilginin yetersizliğinin, kullanıcıların eğitim seviyelerinin düşük olmasının kullanım oranını azaltacağını düşünmektedirler.

Kaynakça

  • Accenture Digital, (2017). https://www.accenture.com/_acnmedia/pdf-77/accenture-research-conversational-ai-platforms.pdf. Erişim Tarihi: 12.05.2023
  • Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427-445.
  • 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.
  • Aslam, W., Siddiqui, D. A., Arif, I., & Farhat, K. (2022). Chatbots in the frontline: Drivers of acceptance. Kybernetes,
  • Barış, A. (2020). A new business marketing tool: Chatbot. GSI Journals Serie B: Advancements in Business and Economics, 3(1), 31-46.
  • Behera, R. K., Bala, P. K., & Ray, A. (2021). Cognitive Chatbot for personalised contextual customer service: Behind the scene and beyond the hype. Information Systems Frontiers, 1-21.
  • Bleu, N. (2023). 29 Top Chatbot Statistics For 2023: Usage, Demographics, Trends, https://bloggingwizard.com/chatbot-statistics/
  • Bone, S. A., Fombelle, P. W., Ray, K. R., & Lemon, K. N. (2015). How customer participation in B2B peer-to-peer problem-solving communities influences the need for traditional customer service. Journal of Service Research, 18(1), 23-38.
  • Brandtzaeg, P. B., & Følstad, A. (2017). Why people use chatbots. In International Conference On Internet Science, 377-392.
  • Chalaguine, L. A., Hunter, A., Potts, H., & Hamilton, F. (2019). Impact of argument type and concerns in argumentation with a chatbot. In 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). 1557-1562.
  • Chen, L., Jiang, M., Jia, F., & Liu, G. (2022). Artificial intelligence adoption in business-to-business marketing: Toward a conceptual framework. Journal of Business & Industrial Marketing. 37(5), 1025–1044.
  • Cheng, Y., & Jiang, H. (2020). How do AI-driven chatbots impact user experience? Examining gratifications, perceived privacy risk, satisfaction, loyalty, and continued use. Journal of Broadcasting & Electronic Media, 64(4), 592-614.
  • 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.
  • Chong, T., Yu, T., Keeling, D. I., & de Ruyter, K. (2021). AI-chatbots on the services frontline addressing the challenges and opportunities of agency. Journal of Retailing and Consumer Services, 63, 1-10.
  • 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.
  • Damnjanovic, V. (2019). Entry market strategy for weaver chatbot using the digital B2B model. In 2019 International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI), 40-403.
  • Damnjanovic, V. (2019). Entry market strategy for weaver chatbot using the digital B2B model. In 2019 International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI). 40-403.
  • Dwivedi, Y. K., & Wang, Y. (2022). Guest editorial: Artificial intelligence for B2B marketing: Challenges and opportunities. Industrial Marketing Management, 105, 109-113.
  • Eeuwen, M. V. (2017). Mobile conversational commerce: messenger chatbots as the next interface between businesses and consumers (Master's thesis, University of Twente).
  • Enyinda, C. I., Opute, A. P., Fadahunsi, A., & Mbah, C. H. (2021). Marketing-sales-service interface and social media marketing influence on B2B sales process. Journal of Business & Industrial Marketing, 36(6), 990-1009.
  • Fauser, S., Schmäh, M., Tran, L. C., Le, H. M., Bumiller, J., & Hiller, A. (2022). Will chatbots play a significant role for B2B marketingin the future? Chatbots in B2B businesses. International journal of business and applied social science, 8(12), 6-12.
  • Fernandes, T., & Oliveira, E. (2021). Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption. Journal of Business Research, 122, 180-191.
  • Fischer, H., Seidenstricker, S., Berger, T., & Holopainen, T. (2022). Artificial intelligence in B2B sales: Impact on the sales process. Artificial Intelligence and Social Computing, 28, 135-142.
  • Følstad, A., & Brandtzaeg, P. B. (2020). Users' experiences with chatbots: Findings from a questionnaire study. Quality and User Experience, 5(1), 1-14.
  • Fotheringham, D., & Wiles, M. A. (2022). The effect of implementing chatbot customer service on stock returns: An event study analysis. Journal of the Academy of Marketing Science, 1-21.
  • Gkinko, L., & Elbanna, A. (2023). The appropriation of conversational AI in the workplace: A taxonomy of AI chatbot users. International Journal of Information Management, 69, 1-11.
  • Global Market Insights, I. (2018). Chatbot Market to surpass $1.34bn by 2024: Global Market Insights, Inc. https://www.globenewswire.com/newsrelease/2018/06/13/1520873/0/en/Chatbot-Market-to-surpass-1-34bn-by-2024- Global-Market-Insights-Inc.html. Erişim Tarihi: 12.05.2023
  • Greven, D., Endres, K., Sundralingam, S., & Stich, V. (2023). Implementation-specific Barriers And Measures For Chatbots In B2B Customer Service. In Proceedings of the Conference on Production Systems and Logistics: CPSL. 844-853.
  • Grewal, D., Guha, A., Satornino, C. B., & Schweiger, E. B. (2021). Artificial intelligence: The light and the darkness. Journal of Business Research, 136, 229-236.
  • Griol, D., & Callejas, Z. (2013). An architecture to develop multimodal educative applications with chatbots. International Journal of Advanced Robotic Systems, 10(3), 175.
  • Güler, A., Halıcıoğlu, M. B, Taşğın, S. (2015). Sosyal Bilimlerde Nitel Araştırma, 2. Baskı, Seçkin Yayıncılık, Ankara.
  • Ha, Y., & Lennon, S. J. (2011). Consumer responses to online atmosphere: The moderating role of atmospheric responsiveness. Journal of Global Fashion Marketing, 2(2), 86-94.
  • Hall, K. R., Harrison, D. E., Ajjan, H., & Marshall, G. W. (2022). Understanding salesperson intention to use AI feedback and its influence on business-to-business sales outcomes. Journal of Business & Industrial Marketing, 37(9), 1787-1801.
  • Han, R., Lam, H. K., Zhan, Y., Wang, Y., Dwivedi, Y. K., & Tan, K. H. (2021). Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions. Industrial Management & Data Systems, 121(12), 2467-2497.
  • He, J., & Xin, C. (2021). Developing an AI-Powered Chatbot to Support the Administration of Middle and High School Cybersecurity Camps. Journal of Cybersecurity Education, Research and Practice, 2021(1), 6.
  • Hildebrand, C., & Bergner, A. (2019). AI-Driven Sales Automation: Using Chatbots to Boost Sales. NIM Marketing Intelligence Review, 11(2).
  • Hopping, C. (2018), “80% of customers don’t trust chatbots for aftersales advice”, available at: https://www.itpro.co.uk/machine-learning/30606/80-of-customers-dont-trust-chatbots-for-aftersalesadvice. Erişim Tarihi: 14.05.2023
  • Hsu, C. L., & Lin, J. C. C. (2023). Understanding the user satisfaction and loyalty of customer service chatbots. Journal of Retailing and Consumer Services, 71, 1-10.
  • Huh, J., Whang, C., & Kim, H. Y. (2023). Building trust with voice assistants for apparel shopping: The effects of social role and user autonomy. Journal of Global Fashion Marketing, 14(1), 5-19.
  • 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. Vol. 33(11), 3860-3882.
  • Johari, N. M., & Nohuddin, P. N. (2021). Quality attributes for a good chatbot: a literature review. International Journal of Electrical Engineering and Technology (IJEET), 12(7), 109-119.
  • Kaczorowska-Spychalska, D. (2019). How chatbots influence marketing. Management, 23(1), 251-270. 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.
  • Kalof, L., & Dan, A. (2008). EBOOK: Essentials of Social Research. McGraw-Hill Education (UK). Kaushal, V., Yadav, R. (2022). Exploring B2B Chatbots adoption experiences: Lessons for successful implementation in Businesses. Research Square, 1-31.
  • Kayak. (2017). Mobile travel report. Retrieved fromhttps://www.kayak.es/news/wp-content/uploads/sites/2/2017/05/ES_Report-compressed.pdf. Erişim Tarihi: 14.05.2023
  • Kim, J.M. Han, J. (2022). Impact of the length of stay at hotels on online reviews. International Journal of Contemporary Hospitality Management, 34 (4), 1249-1269.
  • Kim, S. B., Sun, K. A., & Kim, D. Y. (2013). The influence of consumer value-based factors on attitude-behavioral intention in social commerce: The differences between high-and low-technology experience groups. Journal of Travel & Tourism Marketing, 30(1-2), 108-125.
  • Koponen, J. P., & Rytsy, S. (2020). Social presence and e-commerce B2B chat functions. European Journal of Marketing, 54(6), 1205-1224.
  • Koumaras, V., Foteas, A., Papaioannou, A., Kapari, M., Sakkas, C., & Koumaras, H. (2018). 5G performance testing of mobile chatbot applications. In 2018 IEEE 23rd international workshop on computer aided modeling and Design of Communication Links and Networks (CAMAD). 1-6.
  • Kuruca, Y., Üstüner, M., & Şimşek, I. (2022). Dijital pazarlamada yapay zekâ kullanımı: Sohbet robotu (Chatbot). Medya ve Kültür, 2(1), 88-113.
  • Kushwaha, A. K., Kumar, P., & Kar, A. K. (2021). What impacts customer experience for B2B enterprises on using AI-enabled chatbots? Insights from Big data analytics. Industrial Marketing Management, 98, 207-221.
  • Lall´e, S., & Conati, C. (2019). The role of user differences in customization: A case study in personalization for infovis-based content. In In Proceedings of the 24th International Conference on Intelligent User Interfaces. Academic Medicine. 329–339.
  • Lee, D., Oh, K. J., & Choi, H. J. (2017). The chatbot feels you-a counseling service using emotional response generation. In 2017 IEEE international conference on big data and smart computing (BigComp). 437-440.
  • Lee, S. E., Ju, N., & Lee, K. H. (2023). Service chatbot: Co-citation and big data analysis toward a review and research agenda. Technological Forecasting and Social Change, 194, 122722.
  • Li, C. Y., & Zhang, J. T. (2023). Chatbots or me? Consumers’ switching between human agents and conversational agents. Journal of Retailing and Consumer Services, 72, 1-14
  • Li, M., & Wang, R. (2023). Chatbots in e-commerce: The effect of chatbot language style on customers’ continuance usage intention and attitude toward brand. Journal of Retailing and Consumer Services, 71, 1-12.
  • Lin, X., Shao, B., & Wang, X. (2022). Employees' perceptions of chatbots in B2B marketing: Affordances vs. disaffordances. Industrial Marketing Management, 101, 45-56.
  • Liu, Y. L., Hu, B., Yan, W., & Lin, Z. (2023). Can chatbots satisfy me? A mixed-method comparative study of satisfaction with task-oriented chatbots in mainland China and Hong Kong. Computers in Human Behavior, 143, 1-14
  • Lou, C., Kang, H., & Tse, C. H. (2022). Bots vs. humans: how schema congruity, contingency-based interactivity, and sympathy influence consumer perceptions and patronage intentions. International Journal of Advertising, 41(4), 655-684.
  • 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. MacLeod, S. (2018). Qualitative communication research methods. White Press Academics.
  • McLean, G., & Wilson, A. (2016). Evolving the online customer experience… is there a role for online customer support? Computers in human behavior, 60, 602-610.
  • Meshram, S., Naik, N., Megha, V. R., More, T., & Kharche, S. (2021, June). Conversational AI: Chatbots. In 2021 International Conference on Intelligent Technologies (CONIT) 1-6.
  • Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies. Journal of Business Research, 56(11), 899-906.
  • Michiels, E. (2017). Modelling chatbots with a cognitive system allows for a differentiating user experience. Doctoral Consortium and Industry Track Papers, 70–78
  • Mikalef, P., Conboy, K., & Krogstie, J. (2021). Artificial intelligence as an enabler of B2B marketing: A dynamic capabilities micro-foundations approach. Industrial Marketing Management, 98, 80-92.
  • Mostafa, R. B., & Kasamani, T. (2022). Antecedents and consequences of chatbot initial trust. European Journal of Marketing, 56(6), 1748-1771.
  • Mou, Y., & Xu, K. (2017). The media inequality: Comparing the initial human-human and human-AI social interactions. Computers in Human Behavior, 72, 432-440.
  • Murali, S. M., Sandhya, C., Behare, N., Unnikrishnan, A., Rajasekaran, B. (2022). Analysis of Chat bots based Artificial Intelligence (AI) Marketing. Indian Journal of Natural Sciences. 13(73). 45606- 45610
  • Murgai, A. (2018). Transforming digital marketing with artificial intelligence. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(4), 259-262.
  • 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.
  • Nguyen, T. (2019). Potential effects of chatbot technology on customer support: A case study. Master’s Thesis, Aalto University.
  • Noris, A., Nobile, T. H., Kalbaska, N., & Cantoni, L. (2021). Digital fashion: A systematic literature review. A perspective on marketing and communication. Journal of Global Fashion Marketing, 12(1), 32-46.
  • Pappas, I. O., Kourouthanassis, P. E., Giannakos, M. N., & Chrissikopoulos, V. (2014). Shiny happy people buying: the role of emotions on personalized e-shopping. Electronic Markets, 24(3). doi:10.1007/s12525-014-0153-y.
  • Pappas, I., Mikalef, P., Giannakos, M., & Pavlou, P. (2017). Value co-creation and trust in social commerce: An fsQCA approach. In Proceedings of the 25th European Conference on Information Systems (ECIS),Guimarães, Portugal, June 5-10, 2153-2168.
  • Park, N., Jang, K., Cho, S., & Choi, J. (2021). Use of offensive language in human-artificial intelligence chatbot interaction: The effects of ethical ideology, social competence, and perceived humanlikeness. Computers in Human Behavior, 121, 106795.
  • 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.
  • Paschen, J., Wilson, M., & Ferreira, J. J. (2020). Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel. Business Horizons, 63(3), 403-414.
  • Patil, K., & Kulkarni, M. S. (2019). Artificial intelligence in financial services: Customer chatbot advisor adoption. Int. J. Innov. Technol. Explor. Eng, 9(1), 4296-4303.
  • Pillai, R., Ghanghorkar, Y., Sivathanu, B., Algharabat, R. and Rana, N.P. (2023), Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots, Information Technology & People, ahead-of-print No. ahead-of-print.
  • Pizzi, G., Scarpi, D., & Pantano, E. (2021). Artificial intelligence and the new forms of interaction: Who has the control when interacting with a chatbot?. Journal of Business Research, 129, 878-890.
  • 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.
  • Rabetino, R., Ogundipe, S. J. and Kohtamäki, M. (2018). Solution sales process blueprinting, International Journal of Business Environment, 10(2), 132.
  • Ramerman, M. (2020). Five predictions for marketing in 2021. https://tunedupmedia.com/five-predictions-for-marketing -in-2021/. Erişim Tarihi: 26.07.2023
  • Rese, A., Ganster, L., & Baier, D. (2020). Chatbots in retailers’ customer communication: How to measure their acceptance?. Journal of Retailing and Consumer Services, 56, 102176.
  • Riegger, A. S., Klein, J. F., Merfeld, K., & Henkel, S. (2021). Technology-enabled personalization in retail stores: Understanding drivers and barriers. Journal of Business Research, 123, 140-155.
  • Rodríguez Cardona, D., Janssen, A., Guhr, N., Breitner, M. H., & Milde, J. (2021). A matter of trust? Examination of chatbot usage in insurance business. Proceedings of the 54th Hawaii International Conference on System Sciences, 556-565.
  • Ruan, Y., & Mezei, J. (2022). When do AI chatbots lead to higher customer satisfaction than human frontline employees in online shopping assistance? Considering product attribute type. Journal of Retailing and Consumer Services, 68, 1-16.
  • Silva, F. A., Shojaei, A. S., & Barbosa, B. (2023). Chatbot-based services: A study on customers’ reuse ıntention. Journal of Theoretical and Applied Electronic Commerce Research, 18(1), 457-474.
  • Singh, A., Ramasubramanian, K., & Shivam, S. (2019). Building an enterprise chatbot: Work with protected enterprise data using open source frameworks. New York: Apress.
  • Sinisalo, J., Karjaluoto, H. and Saraniemi, S. (2015) Barriers to the use of mobile sales force automation systems: a salesperson’s perspective, Journal of Systems and Information Technology, vol. 17, no. 2, pp. 121–140.
  • Suhaili, S. M., Salim, N., & Jambli, M. N. (2021). Service chatbots: A systematic review. Expert Systems with Applications, 184, 1-20.
  • Sujata, J., Nikita, M., & Shubham, S. (2019). Applications of Chatbots in Marketing: Use Cases, Impacts, Challenges and Drivers. International Journal of Advanced Trends in Computer Science and Engineering, 8(16), 195 – 200.
  • Sundar, S. S., & Kim, J. (2019). Machine heuristic: When we trust computers more than humans with our personal information. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 538, 1–9.
  • Sweezey, M. (2019). Key Chatbot Statistics to Know in 2019, https://www.salesforce.com/blog/chatbot-statistics. Erişim Tarihi: 14.05.2023
  • Tamrakar, M. K., & Badholia, A. (2022, August). Scientific Study of Technological Chatbot Adoption in Customer Service. In 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 1117-1123). IEEE.
  • The Outgrow Blog (2021). https://outgrow.co/blog/vital-chatbot-statistics. Erişim Tarihi: 14.05.2023 Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
  • Verstegen (2022). https://www.chatdesk.com/blog/pros-and-cons-of-chatbots. Erişim Tarihi: 24.07.2023
  • Vladimirovich, K. M. (2020). Future marketing in B2B segment: Integrating Artificial Intelligence into sales management. International Journal of Innovative Technologies in Economy, 4(31).
  • Waghmare, C., & Waghmare, C. (2019). Chatbot Integration. Introducing Azure Bot Service: Building Bots for Business, 111-146.
  • Wang, E. S. T., & Lin, R. L. (2017). Perceived quality factors of location-based apps on trust, perceived privacy risk, and continuous usage intention. Behaviour & Information Technology, 36(1), 2-10.
  • Wang, P., & Shao, J. (2022). Escaping loneliness through tourist-chatbot interactions. In Information and Communication Technologies in Tourism 2022: Proceedings of the ENTER 2022 eTourism Conference, 473-485.
  • 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.
  • White, T. B., Zahay, D. L., Thorbjørnsen, H., & Shavitt, S. (2008). Getting too personal: Reactance to highly personalized email solicitations. Marketing Letters, 19, 39-50.
  • Xing, X., Song, M., Duan, Y., & Mou, J. (2022). Effects of different service failure types and recovery strategies on the consumer response mechanism of chatbots. Technology in Society, 70, 1-12.
  • Xu, X., Wang, X., Li, Y., & Haghighi, M. (2017). Business intelligence in online customer textual reviews: Understanding consumer perceptions and influential factors. International Journal of information management, 37(6), 673-683.
  • Yıldırım, A. ve Şimşek, H. (2018). Sosyal bilimlerde nitel araştırma yöntemleri (10. bs.). Ankara: Seçkin Yayıncılık.
  • Yonatan, R. (2022). Chatbot vs Live Chat: Differences, Pros & Cons For Business. https://getvoip.com/blog/chatbots-vs-live-chat/. Erişim Tarihi: 24.07.2023
  • Yoon, V. Y., Hostler, R. E., Guo, Z., & Guimaraes, T. (2013). Assessing the moderating effect of consumer product knowledge and online shopping experience on using recommendation agents for customer loyalty. Decision Support Systems, 55(4), 883-893.
  • Zacharia, Z. C., Loizou, E., & Papaevripidou, M. (2012). Is physicality an important aspect of learning through science experimentation among kindergarten students?. Early Childhood Research Quarterly, 27(3), 447-457.
  • Zamora, J. (2017). Rise of the chatbots: Finding a place for artificial intelligence in India and US. In Proceedings of the 22nd international conference on intelligent user interfaces companion, 109-112.
  • Zhu, Y., Zhang, J., Wu, J., & Liu, Y. (2022). AI is better when I'm sure: The influence of certainty of needs on consumers' acceptance of AI chatbots. Journal of Business Research, 150, 642-652.
  • Zoltners, A. A., Sinha, P., Sahay, D., Shastri, A., & Lorimer, S. E. (2021). Practical insights for sales force digitalization success. Journal of Personal Selling & Sales Management, 41(2), 87-102.
  • Zumstein, D., & Hundertmark, S. (2017). Communicating and transacting with chatbots: insights from public transport. In Proceedings of the 16th International Conference Applied Computing WWW/Internet. 55-62.

ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA

Yıl 2023, Cilt: 6 Sayı: 2, 98 - 127, 31.12.2023
https://doi.org/10.46238/jobda.1299432

Öz

Sohbet robotu yapay zeka uygulamalarından biridir. İşletmeler müşterilerine bilgi vermek, web sitesi içinde yönlendirme yapmak, sorulara anında ve hızlı bir şekilde cevap verebilmek için sohbet robotundan faydalanmaktadırlar. Çalışmanın amacı, endüstriyel pazarda satış çalışanlarının satış faaliyetlerinde sohbet robotlarını kullanımına ilişkin amaç, beklentileri ve elde edilebileceği faydaları ile algılanan engelleri ve endişeleri ortaya koymaktır. Ayrıca sohbet robotlarının müşteri deneyimine sağlayacağı katkıları belirlemektir. Bu doğrultuda 10 satış çalışanı ile derinlemesine görüşmeler yapılmıştır. Görüşmelerin analizinde içerik analizi kullanılmıştır. Çalışma sonuçlarına göre, satış çalışanlarının satış faaliyetlerinde sohbet robotlarını kullanımına ilişkin amaç, beklentileri ve elde edilebileceği faydalar; ürün, lojistik, stok bilgisi sağlaması, departmanlararası veri paylaşması, temel sorularına hızlı cevap vermesi, müşteriyi ilgili kişiye yönlendirmesi, müşteri verilerinin toplanması, rutin işleri takip ederek ziyaret planlaması, şikayet takibi yapması, müşterinin firmaya kaydolmasını kolaylaştırması, farklı dil özelliklerini kullanması, e-postaları analiz ederek önceliklendirmesi ve yanıt verebilmesidir. Satış çalışanları sohbet robotunun doğru şekilde çalışmaması, kişinin izni ve bilgisi olmadan müşteriye yanlış bilgi (randevu, fiyat, temin, stok gibi) paylaşması, müşteri ile sorun yaşaması, talepleri doğru tahmin edememesi konularında endişe duymaktadırlar. Katılımcılar sohbet robotu kullanmalarında algılanan engeller; endüstriyel pazardaki işlerin ve ürünlerin teknik, müşteri kaybetme riskinin yüksek ve maliyetli olması olarak ifade etmişlerdir. Ayrıca sohbet robotunun algılama hatası vermesinin, kullanıcı duygularını anlama zorluğunun, verilen bilginin yetersizliğinin, kullanıcıların eğitim seviyelerinin düşük olmasının kullanım oranını azaltacağını düşünmektedirler.

Kaynakça

  • Accenture Digital, (2017). https://www.accenture.com/_acnmedia/pdf-77/accenture-research-conversational-ai-platforms.pdf. Erişim Tarihi: 12.05.2023
  • Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427-445.
  • 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.
  • Aslam, W., Siddiqui, D. A., Arif, I., & Farhat, K. (2022). Chatbots in the frontline: Drivers of acceptance. Kybernetes,
  • Barış, A. (2020). A new business marketing tool: Chatbot. GSI Journals Serie B: Advancements in Business and Economics, 3(1), 31-46.
  • Behera, R. K., Bala, P. K., & Ray, A. (2021). Cognitive Chatbot for personalised contextual customer service: Behind the scene and beyond the hype. Information Systems Frontiers, 1-21.
  • Bleu, N. (2023). 29 Top Chatbot Statistics For 2023: Usage, Demographics, Trends, https://bloggingwizard.com/chatbot-statistics/
  • Bone, S. A., Fombelle, P. W., Ray, K. R., & Lemon, K. N. (2015). How customer participation in B2B peer-to-peer problem-solving communities influences the need for traditional customer service. Journal of Service Research, 18(1), 23-38.
  • Brandtzaeg, P. B., & Følstad, A. (2017). Why people use chatbots. In International Conference On Internet Science, 377-392.
  • Chalaguine, L. A., Hunter, A., Potts, H., & Hamilton, F. (2019). Impact of argument type and concerns in argumentation with a chatbot. In 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). 1557-1562.
  • Chen, L., Jiang, M., Jia, F., & Liu, G. (2022). Artificial intelligence adoption in business-to-business marketing: Toward a conceptual framework. Journal of Business & Industrial Marketing. 37(5), 1025–1044.
  • Cheng, Y., & Jiang, H. (2020). How do AI-driven chatbots impact user experience? Examining gratifications, perceived privacy risk, satisfaction, loyalty, and continued use. Journal of Broadcasting & Electronic Media, 64(4), 592-614.
  • 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.
  • Chong, T., Yu, T., Keeling, D. I., & de Ruyter, K. (2021). AI-chatbots on the services frontline addressing the challenges and opportunities of agency. Journal of Retailing and Consumer Services, 63, 1-10.
  • 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.
  • Damnjanovic, V. (2019). Entry market strategy for weaver chatbot using the digital B2B model. In 2019 International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI), 40-403.
  • Damnjanovic, V. (2019). Entry market strategy for weaver chatbot using the digital B2B model. In 2019 International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI). 40-403.
  • Dwivedi, Y. K., & Wang, Y. (2022). Guest editorial: Artificial intelligence for B2B marketing: Challenges and opportunities. Industrial Marketing Management, 105, 109-113.
  • Eeuwen, M. V. (2017). Mobile conversational commerce: messenger chatbots as the next interface between businesses and consumers (Master's thesis, University of Twente).
  • Enyinda, C. I., Opute, A. P., Fadahunsi, A., & Mbah, C. H. (2021). Marketing-sales-service interface and social media marketing influence on B2B sales process. Journal of Business & Industrial Marketing, 36(6), 990-1009.
  • Fauser, S., Schmäh, M., Tran, L. C., Le, H. M., Bumiller, J., & Hiller, A. (2022). Will chatbots play a significant role for B2B marketingin the future? Chatbots in B2B businesses. International journal of business and applied social science, 8(12), 6-12.
  • Fernandes, T., & Oliveira, E. (2021). Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption. Journal of Business Research, 122, 180-191.
  • Fischer, H., Seidenstricker, S., Berger, T., & Holopainen, T. (2022). Artificial intelligence in B2B sales: Impact on the sales process. Artificial Intelligence and Social Computing, 28, 135-142.
  • Følstad, A., & Brandtzaeg, P. B. (2020). Users' experiences with chatbots: Findings from a questionnaire study. Quality and User Experience, 5(1), 1-14.
  • Fotheringham, D., & Wiles, M. A. (2022). The effect of implementing chatbot customer service on stock returns: An event study analysis. Journal of the Academy of Marketing Science, 1-21.
  • Gkinko, L., & Elbanna, A. (2023). The appropriation of conversational AI in the workplace: A taxonomy of AI chatbot users. International Journal of Information Management, 69, 1-11.
  • Global Market Insights, I. (2018). Chatbot Market to surpass $1.34bn by 2024: Global Market Insights, Inc. https://www.globenewswire.com/newsrelease/2018/06/13/1520873/0/en/Chatbot-Market-to-surpass-1-34bn-by-2024- Global-Market-Insights-Inc.html. Erişim Tarihi: 12.05.2023
  • Greven, D., Endres, K., Sundralingam, S., & Stich, V. (2023). Implementation-specific Barriers And Measures For Chatbots In B2B Customer Service. In Proceedings of the Conference on Production Systems and Logistics: CPSL. 844-853.
  • Grewal, D., Guha, A., Satornino, C. B., & Schweiger, E. B. (2021). Artificial intelligence: The light and the darkness. Journal of Business Research, 136, 229-236.
  • Griol, D., & Callejas, Z. (2013). An architecture to develop multimodal educative applications with chatbots. International Journal of Advanced Robotic Systems, 10(3), 175.
  • Güler, A., Halıcıoğlu, M. B, Taşğın, S. (2015). Sosyal Bilimlerde Nitel Araştırma, 2. Baskı, Seçkin Yayıncılık, Ankara.
  • Ha, Y., & Lennon, S. J. (2011). Consumer responses to online atmosphere: The moderating role of atmospheric responsiveness. Journal of Global Fashion Marketing, 2(2), 86-94.
  • Hall, K. R., Harrison, D. E., Ajjan, H., & Marshall, G. W. (2022). Understanding salesperson intention to use AI feedback and its influence on business-to-business sales outcomes. Journal of Business & Industrial Marketing, 37(9), 1787-1801.
  • Han, R., Lam, H. K., Zhan, Y., Wang, Y., Dwivedi, Y. K., & Tan, K. H. (2021). Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions. Industrial Management & Data Systems, 121(12), 2467-2497.
  • He, J., & Xin, C. (2021). Developing an AI-Powered Chatbot to Support the Administration of Middle and High School Cybersecurity Camps. Journal of Cybersecurity Education, Research and Practice, 2021(1), 6.
  • Hildebrand, C., & Bergner, A. (2019). AI-Driven Sales Automation: Using Chatbots to Boost Sales. NIM Marketing Intelligence Review, 11(2).
  • Hopping, C. (2018), “80% of customers don’t trust chatbots for aftersales advice”, available at: https://www.itpro.co.uk/machine-learning/30606/80-of-customers-dont-trust-chatbots-for-aftersalesadvice. Erişim Tarihi: 14.05.2023
  • Hsu, C. L., & Lin, J. C. C. (2023). Understanding the user satisfaction and loyalty of customer service chatbots. Journal of Retailing and Consumer Services, 71, 1-10.
  • Huh, J., Whang, C., & Kim, H. Y. (2023). Building trust with voice assistants for apparel shopping: The effects of social role and user autonomy. Journal of Global Fashion Marketing, 14(1), 5-19.
  • 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. Vol. 33(11), 3860-3882.
  • Johari, N. M., & Nohuddin, P. N. (2021). Quality attributes for a good chatbot: a literature review. International Journal of Electrical Engineering and Technology (IJEET), 12(7), 109-119.
  • Kaczorowska-Spychalska, D. (2019). How chatbots influence marketing. Management, 23(1), 251-270. 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.
  • Kalof, L., & Dan, A. (2008). EBOOK: Essentials of Social Research. McGraw-Hill Education (UK). Kaushal, V., Yadav, R. (2022). Exploring B2B Chatbots adoption experiences: Lessons for successful implementation in Businesses. Research Square, 1-31.
  • Kayak. (2017). Mobile travel report. Retrieved fromhttps://www.kayak.es/news/wp-content/uploads/sites/2/2017/05/ES_Report-compressed.pdf. Erişim Tarihi: 14.05.2023
  • Kim, J.M. Han, J. (2022). Impact of the length of stay at hotels on online reviews. International Journal of Contemporary Hospitality Management, 34 (4), 1249-1269.
  • Kim, S. B., Sun, K. A., & Kim, D. Y. (2013). The influence of consumer value-based factors on attitude-behavioral intention in social commerce: The differences between high-and low-technology experience groups. Journal of Travel & Tourism Marketing, 30(1-2), 108-125.
  • Koponen, J. P., & Rytsy, S. (2020). Social presence and e-commerce B2B chat functions. European Journal of Marketing, 54(6), 1205-1224.
  • Koumaras, V., Foteas, A., Papaioannou, A., Kapari, M., Sakkas, C., & Koumaras, H. (2018). 5G performance testing of mobile chatbot applications. In 2018 IEEE 23rd international workshop on computer aided modeling and Design of Communication Links and Networks (CAMAD). 1-6.
  • Kuruca, Y., Üstüner, M., & Şimşek, I. (2022). Dijital pazarlamada yapay zekâ kullanımı: Sohbet robotu (Chatbot). Medya ve Kültür, 2(1), 88-113.
  • Kushwaha, A. K., Kumar, P., & Kar, A. K. (2021). What impacts customer experience for B2B enterprises on using AI-enabled chatbots? Insights from Big data analytics. Industrial Marketing Management, 98, 207-221.
  • Lall´e, S., & Conati, C. (2019). The role of user differences in customization: A case study in personalization for infovis-based content. In In Proceedings of the 24th International Conference on Intelligent User Interfaces. Academic Medicine. 329–339.
  • Lee, D., Oh, K. J., & Choi, H. J. (2017). The chatbot feels you-a counseling service using emotional response generation. In 2017 IEEE international conference on big data and smart computing (BigComp). 437-440.
  • Lee, S. E., Ju, N., & Lee, K. H. (2023). Service chatbot: Co-citation and big data analysis toward a review and research agenda. Technological Forecasting and Social Change, 194, 122722.
  • Li, C. Y., & Zhang, J. T. (2023). Chatbots or me? Consumers’ switching between human agents and conversational agents. Journal of Retailing and Consumer Services, 72, 1-14
  • Li, M., & Wang, R. (2023). Chatbots in e-commerce: The effect of chatbot language style on customers’ continuance usage intention and attitude toward brand. Journal of Retailing and Consumer Services, 71, 1-12.
  • Lin, X., Shao, B., & Wang, X. (2022). Employees' perceptions of chatbots in B2B marketing: Affordances vs. disaffordances. Industrial Marketing Management, 101, 45-56.
  • Liu, Y. L., Hu, B., Yan, W., & Lin, Z. (2023). Can chatbots satisfy me? A mixed-method comparative study of satisfaction with task-oriented chatbots in mainland China and Hong Kong. Computers in Human Behavior, 143, 1-14
  • Lou, C., Kang, H., & Tse, C. H. (2022). Bots vs. humans: how schema congruity, contingency-based interactivity, and sympathy influence consumer perceptions and patronage intentions. International Journal of Advertising, 41(4), 655-684.
  • 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. MacLeod, S. (2018). Qualitative communication research methods. White Press Academics.
  • McLean, G., & Wilson, A. (2016). Evolving the online customer experience… is there a role for online customer support? Computers in human behavior, 60, 602-610.
  • Meshram, S., Naik, N., Megha, V. R., More, T., & Kharche, S. (2021, June). Conversational AI: Chatbots. In 2021 International Conference on Intelligent Technologies (CONIT) 1-6.
  • Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies. Journal of Business Research, 56(11), 899-906.
  • Michiels, E. (2017). Modelling chatbots with a cognitive system allows for a differentiating user experience. Doctoral Consortium and Industry Track Papers, 70–78
  • Mikalef, P., Conboy, K., & Krogstie, J. (2021). Artificial intelligence as an enabler of B2B marketing: A dynamic capabilities micro-foundations approach. Industrial Marketing Management, 98, 80-92.
  • Mostafa, R. B., & Kasamani, T. (2022). Antecedents and consequences of chatbot initial trust. European Journal of Marketing, 56(6), 1748-1771.
  • Mou, Y., & Xu, K. (2017). The media inequality: Comparing the initial human-human and human-AI social interactions. Computers in Human Behavior, 72, 432-440.
  • Murali, S. M., Sandhya, C., Behare, N., Unnikrishnan, A., Rajasekaran, B. (2022). Analysis of Chat bots based Artificial Intelligence (AI) Marketing. Indian Journal of Natural Sciences. 13(73). 45606- 45610
  • Murgai, A. (2018). Transforming digital marketing with artificial intelligence. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(4), 259-262.
  • 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.
  • Nguyen, T. (2019). Potential effects of chatbot technology on customer support: A case study. Master’s Thesis, Aalto University.
  • Noris, A., Nobile, T. H., Kalbaska, N., & Cantoni, L. (2021). Digital fashion: A systematic literature review. A perspective on marketing and communication. Journal of Global Fashion Marketing, 12(1), 32-46.
  • Pappas, I. O., Kourouthanassis, P. E., Giannakos, M. N., & Chrissikopoulos, V. (2014). Shiny happy people buying: the role of emotions on personalized e-shopping. Electronic Markets, 24(3). doi:10.1007/s12525-014-0153-y.
  • Pappas, I., Mikalef, P., Giannakos, M., & Pavlou, P. (2017). Value co-creation and trust in social commerce: An fsQCA approach. In Proceedings of the 25th European Conference on Information Systems (ECIS),Guimarães, Portugal, June 5-10, 2153-2168.
  • Park, N., Jang, K., Cho, S., & Choi, J. (2021). Use of offensive language in human-artificial intelligence chatbot interaction: The effects of ethical ideology, social competence, and perceived humanlikeness. Computers in Human Behavior, 121, 106795.
  • 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.
  • Paschen, J., Wilson, M., & Ferreira, J. J. (2020). Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel. Business Horizons, 63(3), 403-414.
  • Patil, K., & Kulkarni, M. S. (2019). Artificial intelligence in financial services: Customer chatbot advisor adoption. Int. J. Innov. Technol. Explor. Eng, 9(1), 4296-4303.
  • Pillai, R., Ghanghorkar, Y., Sivathanu, B., Algharabat, R. and Rana, N.P. (2023), Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots, Information Technology & People, ahead-of-print No. ahead-of-print.
  • Pizzi, G., Scarpi, D., & Pantano, E. (2021). Artificial intelligence and the new forms of interaction: Who has the control when interacting with a chatbot?. Journal of Business Research, 129, 878-890.
  • 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.
  • Rabetino, R., Ogundipe, S. J. and Kohtamäki, M. (2018). Solution sales process blueprinting, International Journal of Business Environment, 10(2), 132.
  • Ramerman, M. (2020). Five predictions for marketing in 2021. https://tunedupmedia.com/five-predictions-for-marketing -in-2021/. Erişim Tarihi: 26.07.2023
  • Rese, A., Ganster, L., & Baier, D. (2020). Chatbots in retailers’ customer communication: How to measure their acceptance?. Journal of Retailing and Consumer Services, 56, 102176.
  • Riegger, A. S., Klein, J. F., Merfeld, K., & Henkel, S. (2021). Technology-enabled personalization in retail stores: Understanding drivers and barriers. Journal of Business Research, 123, 140-155.
  • Rodríguez Cardona, D., Janssen, A., Guhr, N., Breitner, M. H., & Milde, J. (2021). A matter of trust? Examination of chatbot usage in insurance business. Proceedings of the 54th Hawaii International Conference on System Sciences, 556-565.
  • Ruan, Y., & Mezei, J. (2022). When do AI chatbots lead to higher customer satisfaction than human frontline employees in online shopping assistance? Considering product attribute type. Journal of Retailing and Consumer Services, 68, 1-16.
  • Silva, F. A., Shojaei, A. S., & Barbosa, B. (2023). Chatbot-based services: A study on customers’ reuse ıntention. Journal of Theoretical and Applied Electronic Commerce Research, 18(1), 457-474.
  • Singh, A., Ramasubramanian, K., & Shivam, S. (2019). Building an enterprise chatbot: Work with protected enterprise data using open source frameworks. New York: Apress.
  • Sinisalo, J., Karjaluoto, H. and Saraniemi, S. (2015) Barriers to the use of mobile sales force automation systems: a salesperson’s perspective, Journal of Systems and Information Technology, vol. 17, no. 2, pp. 121–140.
  • Suhaili, S. M., Salim, N., & Jambli, M. N. (2021). Service chatbots: A systematic review. Expert Systems with Applications, 184, 1-20.
  • Sujata, J., Nikita, M., & Shubham, S. (2019). Applications of Chatbots in Marketing: Use Cases, Impacts, Challenges and Drivers. International Journal of Advanced Trends in Computer Science and Engineering, 8(16), 195 – 200.
  • Sundar, S. S., & Kim, J. (2019). Machine heuristic: When we trust computers more than humans with our personal information. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 538, 1–9.
  • Sweezey, M. (2019). Key Chatbot Statistics to Know in 2019, https://www.salesforce.com/blog/chatbot-statistics. Erişim Tarihi: 14.05.2023
  • Tamrakar, M. K., & Badholia, A. (2022, August). Scientific Study of Technological Chatbot Adoption in Customer Service. In 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 1117-1123). IEEE.
  • The Outgrow Blog (2021). https://outgrow.co/blog/vital-chatbot-statistics. Erişim Tarihi: 14.05.2023 Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
  • Verstegen (2022). https://www.chatdesk.com/blog/pros-and-cons-of-chatbots. Erişim Tarihi: 24.07.2023
  • Vladimirovich, K. M. (2020). Future marketing in B2B segment: Integrating Artificial Intelligence into sales management. International Journal of Innovative Technologies in Economy, 4(31).
  • Waghmare, C., & Waghmare, C. (2019). Chatbot Integration. Introducing Azure Bot Service: Building Bots for Business, 111-146.
  • Wang, E. S. T., & Lin, R. L. (2017). Perceived quality factors of location-based apps on trust, perceived privacy risk, and continuous usage intention. Behaviour & Information Technology, 36(1), 2-10.
  • Wang, P., & Shao, J. (2022). Escaping loneliness through tourist-chatbot interactions. In Information and Communication Technologies in Tourism 2022: Proceedings of the ENTER 2022 eTourism Conference, 473-485.
  • 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.
  • White, T. B., Zahay, D. L., Thorbjørnsen, H., & Shavitt, S. (2008). Getting too personal: Reactance to highly personalized email solicitations. Marketing Letters, 19, 39-50.
  • Xing, X., Song, M., Duan, Y., & Mou, J. (2022). Effects of different service failure types and recovery strategies on the consumer response mechanism of chatbots. Technology in Society, 70, 1-12.
  • Xu, X., Wang, X., Li, Y., & Haghighi, M. (2017). Business intelligence in online customer textual reviews: Understanding consumer perceptions and influential factors. International Journal of information management, 37(6), 673-683.
  • Yıldırım, A. ve Şimşek, H. (2018). Sosyal bilimlerde nitel araştırma yöntemleri (10. bs.). Ankara: Seçkin Yayıncılık.
  • Yonatan, R. (2022). Chatbot vs Live Chat: Differences, Pros & Cons For Business. https://getvoip.com/blog/chatbots-vs-live-chat/. Erişim Tarihi: 24.07.2023
  • Yoon, V. Y., Hostler, R. E., Guo, Z., & Guimaraes, T. (2013). Assessing the moderating effect of consumer product knowledge and online shopping experience on using recommendation agents for customer loyalty. Decision Support Systems, 55(4), 883-893.
  • Zacharia, Z. C., Loizou, E., & Papaevripidou, M. (2012). Is physicality an important aspect of learning through science experimentation among kindergarten students?. Early Childhood Research Quarterly, 27(3), 447-457.
  • Zamora, J. (2017). Rise of the chatbots: Finding a place for artificial intelligence in India and US. In Proceedings of the 22nd international conference on intelligent user interfaces companion, 109-112.
  • Zhu, Y., Zhang, J., Wu, J., & Liu, Y. (2022). AI is better when I'm sure: The influence of certainty of needs on consumers' acceptance of AI chatbots. Journal of Business Research, 150, 642-652.
  • Zoltners, A. A., Sinha, P., Sahay, D., Shastri, A., & Lorimer, S. E. (2021). Practical insights for sales force digitalization success. Journal of Personal Selling & Sales Management, 41(2), 87-102.
  • Zumstein, D., & Hundertmark, S. (2017). Communicating and transacting with chatbots: insights from public transport. In Proceedings of the 16th International Conference Applied Computing WWW/Internet. 55-62.
Toplam 112 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İşletme
Bölüm Özgün Bilimsel Makaleler
Yazarlar

Ezgi Doğan Bu kişi benim 0000-0003-4719-4597

İpek Kazançoğlu 0000-0001-8251-5451

Erken Görünüm Tarihi 30 Kasım 2023
Yayımlanma Tarihi 31 Aralık 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 6 Sayı: 2

Kaynak Göster

APA Doğan, E., & Kazançoğlu, İ. (2023). ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA. Journal of Business in The Digital Age, 6(2), 98-127. https://doi.org/10.46238/jobda.1299432
AMA Doğan E, Kazançoğlu İ. ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA. JOBDA. Aralık 2023;6(2):98-127. doi:10.46238/jobda.1299432
Chicago Doğan, Ezgi, ve İpek Kazançoğlu. “ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA”. Journal of Business in The Digital Age 6, sy. 2 (Aralık 2023): 98-127. https://doi.org/10.46238/jobda.1299432.
EndNote Doğan E, Kazançoğlu İ (01 Aralık 2023) ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA. Journal of Business in The Digital Age 6 2 98–127.
IEEE E. Doğan ve İ. Kazançoğlu, “ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA”, JOBDA, c. 6, sy. 2, ss. 98–127, 2023, doi: 10.46238/jobda.1299432.
ISNAD Doğan, Ezgi - Kazançoğlu, İpek. “ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA”. Journal of Business in The Digital Age 6/2 (Aralık 2023), 98-127. https://doi.org/10.46238/jobda.1299432.
JAMA Doğan E, Kazançoğlu İ. ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA. JOBDA. 2023;6:98–127.
MLA Doğan, Ezgi ve İpek Kazançoğlu. “ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA”. Journal of Business in The Digital Age, c. 6, sy. 2, 2023, ss. 98-127, doi:10.46238/jobda.1299432.
Vancouver Doğan E, Kazançoğlu İ. ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA. JOBDA. 2023;6(2):98-127.

                                                                Creative Commons Lisansı

Bu eser Creative Commons Atıf-AynıLisanslaPaylaş 4.0 Uluslararası Lisansı ile lisanslanmıştır.