nach oben

Service Business

Erschienen in:

10.11.2022 | Theoretical article

Live support by chatbots with artificial intelligence: A future research agenda

verfasst von: Mark Anthony Camilleri, Ciro Troise

Erschienen in: Service Business | Ausgabe 1/2023

Einloggen

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

search-config

KI-gestützte Suche

Aus

Abstract

This research uses a Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol to investigate the utility of artificially intelligent (AI) conversational chatbots in service business settings. The findings shed light on key theoretical underpinnings focussed on human–computer interactions and clarify the benefits and costs of using responsive chatbot technologies. This contribution implies that, for the time being, works are still in progress for interactive, anthropomorphic chatbots to mimic human customer services agents’ verbal, vocal and visual cues, when they respond to online queries. In conclusion it puts forward plausible research avenues in this promising area of study.

Vorheriger Artikel Applying Industry 4.0 technologies for the sustainability of small service enterprises

Nächster Artikel Perceived value of AI-based recommendations service: the case of voice assistants

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

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

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

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

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

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

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

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Adam M, Wessel M, Benlian A (2021) AI-based chatbots in customer service and their effects on user compliance. Electron Mark 31(2):427–445CrossRef

Adamopoulou E, Moussiades L (2020) Chatbots: history, technology, and applications. Mach Learn Appl. https://doi.org/10.1016/j.mlwa.2020.100006CrossRef

Balakrishnan J, Dwivedi YK (2021) Role of cognitive absorption in building user trust and experience. Psychol Mark 38(4):643–668CrossRef

Becker M, Mahr D, Odekerken-Schröder G (2022) Customer comfort during service robot interactions. Serv Bus. https://doi.org/10.1007/s11628-022-00499-4CrossRef

Belanche D, Casaló LV, Flavián C (2020a) Frontline robots in tourism and hospitality: service enhancement or cost reduction? Electron Mark 31(2):477–492

Belanche D, Casaló LV, Flavian C, Schepers J (2020b) Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success. J Serv Manag 31(2):267–289CrossRef

Belanche D, Casaló LV, Flavián C, Schepers J (2020c) Service robot implementation: a theoretical framework and research agenda. Serv Ind J 40(3–4):203–225CrossRef

Belanche D, Casaló LV, Schepers J, Flavián C (2021) Examining the effects of robots’ physical appearance, warmth, and competence in frontline services: the Humanness-Value-Loyalty model. Psychol Mark 38(12):2357–2376CrossRef

Blut M, Wang C, Wünderlich NV, Brock C (2021) Understanding anthropomorphism in service provision: a meta-analysis of physical robots, chatbots, and other AI. J Acad Mark Sci 49(4):632–658CrossRef

Borau S, Otterbring T, Laporte S, Fosso Wamba S (2021) The most human bot: female gendering increases humanness perceptions of bots and acceptance of AI. Psychol Mark 38(7):1052–1068CrossRef

Brachten F, Kissmer T, Stieglitz S (2021) The acceptance of chatbots in an enterprise context—a survey study. Int J Inf Manag 60:102375. https://doi.org/10.1016/j.ijinfomgt.2021.102375CrossRef

Buhalis D, Cheng ESY (2020) Exploring the use of chatbots in hotels: technology providers’ perspective. In: Inf. and Comm Tech in Tourism. Springer, Cham, pp 231–242

Caldarini G, Jaf S, McGarry K (2022) A literature survey of recent advances in chatbots. Information 13(1):41CrossRef

Camilleri MA (2020) The use of data-driven technologies for customer-centric marketing. Int J Big Data Manag 1(1):50–63CrossRef

Camilleri MA (2021) E-commerce websites, consumer order fulfillment and after-sales service satisfaction: the customer is always right, even after the shopping cart check-out. J Strategy Manag 15(3):377–396CrossRef

Camilleri MA, Kozak M (2022) Interactive engagement through travel and tourism social media groups: a social facilitation theory perspective. Technol Soc 71:102098. https://doi.org/10.1016/j.techsoc.2022.102098CrossRef

Capriotti P, Zeler I, Camilleri MA (2021) Corporate communication through social networks: the identification of the key dimensions for dialogic communication. In: Strat Corp Comm in the Digital Age. Emerald Publishing Limited, Bingley, pp 33–51

Castillo D, Canhoto AI, Said E (2021) The dark side of AI-powered service interactions: exploring the process of co-destruction from the customer perspective. Serv Ind J 41(13–14):900–925CrossRef

Chen JS, Tran-Thien TTY, Florence D (2021) Usability and responsiveness of artificial intelligence chatbot on online customer experience in e-retailing. Int J Retail Distrib Manag 49(11):1512–1531CrossRef

Cheng Y, Jiang H (2020) AI-Powered mental health chatbots: examining users’ motivations, active communicative action and engagement after mass-shooting disasters. J Conting Crisis Manag 28(3):339–354CrossRef

Chong T, Yu T, Keeling DI, de Ruyter K (2021) AI-chatbots on the services frontline addressing the challenges and opportunities of agency. J Retail Consumer Serv 63:102735. https://doi.org/10.1016/j.jretconser.2021.102735CrossRef

Chopra K (2019) Indian shopper motivation to use artificial intelligence: generating Vroom’s expectancy theory of motivation using grounded theory approach. Int J Retail Distrib Manag 47(3):331–347CrossRef

Ciechanowski L, Przegalinska A, Magnuski M, Gloor P (2019) In the shades of the uncanny valley: an experimental study of human–chatbot interaction. Future Gener Comput Syst 92:539–548CrossRef

Crolic C, Thomaz F, Hadi R, Stephen AT (2021) Blame the bot: anthropomorphism and anger in customer-chatbot interactions. J Mark 86(1):132–148CrossRef

De Cicco R, Silva SC, Alparone FR (2020) Millennials’ attitude toward chatbots: an experimental study in a social relationship perspective. Int J Retail Distrib Manag 48(11):1213–1233CrossRef

Dippold D, Lynden J, Shrubsall R, Ingram R (2020) A turn to language: how interactional sociolinguistics informs the redesign of prompt: response chatbot turns. Discourse Context Med 37:100432. https://doi.org/10.1016/j.dcm.2020.100432CrossRef

Eren BA (2021) Determinants of customer satisfaction in chatbot use: evidence from a banking application in Turkey. Int J Bank Mark 39(2):294–311CrossRef

Flavián C, Casaló LV (2021) Artificial intelligence in services: current trends, benefits and challenges. Serv Ind J 41(13–14):853–859CrossRef

Flavián C, Pérez-Rueda A, Belanche D, Casaló LV (2021) Intention to use analytical artificial intelligence (AI) in services—the effect of technology readiness and awareness. J Serv Manag 33(2):293–320CrossRef

Forgas-Coll S, Huertas-Garcia R, Andriella A, Alenyà G (2022) The effects of gender and personality of robot assistants on customers’ acceptance of their service. Serv Bus 16:359–389CrossRef

Grimes GM, Schuetzler RM, Giboney JS (2021) Mental models and expectation violations in conversational AI interactions. Decis Support Syst 144. https://doi.org/10.1016/j.dss.2021.113515

Hajarian M, Camilleri MA, Díaz P, Aedo I (2021) A taxonomy of online marketing methods. In: Strat Corp Comm in the Digital Age. Emerald Publishing Limited, Bingley, pp 235–250

Hildebrand C, Bergner A (2021) Conversational robo advisors as surrogates of trust: onboarding experience, firm perception, and consumer financial decision making. J Acad Mark Sci 49(4):659–676CrossRef

Hoyer WD, Kroschke M, Schmitt B, Kraume K, Shankar V (2020) Transforming the customer experience through new technologies. J Int Mark 51:57–71CrossRef

Huang Y-S, Kao W-K (2021) Chatbot service usage during a pandemic: fear and social distancing. Serv Ind J 41(13–14):964–984CrossRef

Huang JW, Lin CP (2011) To stick or not to stick: The social response theory in the development of continuance intention from organizational cross-level perspective. Comput Hum Behav 27(5):1963–1973CrossRef

Huang MH, Rust RT (2018) Artificial intelligence in service. J Serv Res 21(2):155–172CrossRef

Iovine A, Narducci F, Semeraro G (2020) Conversational Recommender Systems and natural language: a study through the ConveRSE framework. Decis Support Syst 131:113250. https://doi.org/10.1016/j.dss.2020.113250CrossRef

Jiménez-Barreto J, Rubio N, Molinillo S (2021) Find a flight for me, Oscar!” Motivational customer experiences with chatbots. Int J Contemp Hosp Manag 33(11):3860–3882CrossRef

Kasilingam DL (2020) Understanding the attitude and intention to use smartphone chatbots for shopping. Tech Soc 62:101280. https://doi.org/10.1016/j.techsoc.2020.101280CrossRef

Kull AJ, Romero M, Monahan L (2021) How may I help you? Driving brand engagement through the warmth of an initial chatbot message. J Bus Res 135:840–850CrossRef

Kushwaha AK, Kumar P, Kar AK (2021) What impacts customer experience for B2B enterprises on using AI-enabled chatbots? Insights from Big data analytics. Ind Mark Manag 98:207–221CrossRef

Lalicic L, Weismayer C (2021) Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents. J Bus Res 129:891–901CrossRef

Lee SM, Lee D (2020) “Untact”: a new customer service strategy in the digital age. Serv Bus 14(1):1–22CrossRef

Leung XY, Wen H (2020) Chatbot usage in restaurant takeout orders: a comparison study of three ordering methods. J Hosp Tour Manag 45:377–386CrossRef

Lewis SC, Guzman AL, Schmidt TR (2019) Automation, journalism, and human–machine communication: rethinking roles and relationships of humans and machines in news. Dig Journalism 7(4):409–427CrossRef

Li L, Lee KY, Emokpae E, Yang SB (2021) What makes you continuously use chatbot services? Evidence from chinese online travel agencies. Electron Mark 31(3):575–599CrossRef

Lou C, Kang H, Tse CH (2021) Bots vs. humans: how schema congruity, contingency-based interactivity, and sympathy influence consumer perceptions and patronage intentions. Int J Adv 41(4):655–684CrossRef

Lucia-Palacios L, Bordonoba-Juste V, Pérez-López R (2021) Consumer-to-consumer reselling adoption among European countries: differences between old and young millennials. Serv Bus 15(2):253–279CrossRef

Luo X, Tong S, Fang Z, Qu Z (2019) Frontiers: machines vs. humans: the impact of artificial intelligence chatbot disclosure on customer purchases. Mark Sci 38(6):937–947

Matiatou M (2019) Communication technologies in E-tourism: a review of online frameworks. Strat Persp in Dest Mktg. Emerald Publishing Limited, Bingley, pp 174–197

Mero J (2018) The effects of two-way communication and chat service usage on consumer attitudes in the e-commerce retailing sector. Electron Mark 28:205–217

McLean G, Osei-Frimpong K, Wilson A, Pitardi V (2020) How live chat assistants drive travel consumers’ attitudes, trust and purchase intentions: the role of human touch. Int J Contemp Hosp Manag 32(5):1795–1812CrossRef

Melián-González S, Gutiérrez-Taño D, Bulchand-Gidumal J (2021) Predicting the intentions to use chatbots for travel and tourism. Curr Issues Tour 24(2):192–210CrossRef

Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA, PRISMA-P Group (2015) Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev 4(1):1–9CrossRef

Moon Y, Nass C (1996) How “real” are computer personalities? Psychological responses to personality types in human-computer interaction. Comm Res 23(6):651–674

Moriuchi E, Landers VM, Colton D, Hair N (2021) Engagement with chatbots versus augmented reality interactive technology in e-commerce. J Strategy Mark 29(5):375–389CrossRef

Mostafa RB, Kasamani T (2021) Antecedents and consequences of chatbot initial trust. Eur J Mark 56(6):1748–1771CrossRef

Mozafari N, Weiger WH, Hammerschmidt M (2021) Trust me, I’m a bot—repercussions of chatbot disclosure in different service frontline settings. J Serv Manag 33(2):221–245CrossRef

Murtarelli G, Gregory A, Romenti S (2021) A conversation-based perspective for shaping ethical human–machine interactions: the particular challenge of chatbots. J Bus Res 129:927–935CrossRef

Nass C, Moon Y (2000) Machines and mindlessness: social responses to computers. J Soc Issues 56(1):81–103CrossRef

Nass C, Steuer J, Tauber ER (1994) Computers are social actors. In: Proceedings of the SIGCHI Conf on Hum Factors in Comp Syst, pp 72–78

Neuburger L, Beck J, Egger R (2018) The ‘Phygital’ tourist experience: the use of augmented and virtual reality in destination marketing. In Tour Planning and Dest Mktg. Emerald Publishing Limited, Bingley, pp 183–202

Ngai EWT, Lee MCM, Luo M, Chan PSL, Liang T (2021) An intelligent knowledge-based chatbot for customer service. Electron Commun Res Appl 50:101098. https://doi.org/10.1016/j.elerap.2021.101098CrossRef

Nuruzzaman M, Hussain OK (2020) IntelliBot: a dialogue-based chatbot for the insurance industry. Know-Based Syst 196:105810. https://doi.org/10.1016/j.knosys.2020.105810CrossRef

Orden-Mejía M, Huertas A (2021) Analysis of the attributes of smart tourism technologies in destination chatbots that influence tourist satisfaction. Curr Issues Tour 25(17):2854–2869CrossRef

Pantano E, Pizzi G (2020) Forecasting artificial intelligence on online customer assistance: evidence from chatbot patents analysis. J Retail Consumer Serv 55:102096. https://doi.org/10.1016/j.jretconser.2020.102096CrossRef

Pantano E, Scarpi D (2022) I, robot, you, consumer: measuring artificial intelligence types and their effect on consumers emotions in service. J Serv Res 25(4):583–600CrossRef

Paschou T, Rapaccini M, Adrodegari F, Saccani N (2020) Digital servitization in manufacturing: a systematic literature review and research agenda. Ind Mark Manag 89:278–292CrossRef

Pfeuffer N, Benlian A, Gimpel H, Hinz O (2019) Anthropomorphic information systems. Bus Inf Syst Eng 61(4):523–533CrossRef

Pillai R, Sivathanu B (2020) Adoption of AI-based chatbots for hospitality and tourism. Int J Contemp Hosp Manag 32(10):3199–3226CrossRef

Przegalinska A, Ciechanowski L, Stroz A, Gloor P, Mazurek G (2019) In bot we trust: a new methodology of chatbot performance measures. Bus Horiz 62(6):785–797CrossRef

Ranoliya BR, Raghuwanshi N, Singh S (2017) Chatbot for university related FAQs. In: 2017 Int Conf on Adv in Comp, Comm and Inform (ICACCI), pp 1525–1530. IEEE

Rese A, Ganster L, Baier D (2020) Chatbots in retailers’ customer communication: how to measure their acceptance? J Retail Consumer Serv 56:102176. https://doi.org/10.1016/j.jretconser.2020.102176CrossRef

Rha JS, Lee HH (2022) Research trends in digital transformation in the service sector: a review based on network text analysis. Serv Bus 16:77–98CrossRef

Riikkinen M, Saarijärvi H, Sarlin P, Lähteenmäki (2018) Using artificial intelligence to create value in insurance. Int J Bank Mark 36(6):1145–1168

Roy R, Naidoo V (2021) Enhancing chatbot effectiveness: the role of anthropomorphic conversational styles and time orientation. J Bus Res 126:23–34CrossRef

Rutschi C, Dibbern J (2020) Towards a framework of implementing software robots: transforming human-executed Routines into Machines. Database Adv Inf Syst 51(1):104–128CrossRef

Sands S, Ferraro C, Campbell C, Tsao HY (2021) Managing the human–chatbot divide: how service scripts influence service experience. J Serv Manag 32(2):246–264CrossRef

Schanke S, Burtch G, Ray G (2021) Estimating the impact of “humanizing” customer service chatbots. Inf Syst Res 32(3):736–751CrossRef

Schepers J, Belanche D, Casaló LV, Flavián C (2022) How smart should a service robot be? J Serv Res. https://doi.org/10.1177/10946705221107704CrossRef

Schuetzler RM, Grimes GM, Scott Giboney J (2020) The impact of chatbot conversational skill on engagement and perceived humanness. J Manag Inf Syst 37(3):875–900CrossRef

Seering J, Flores JP, Savage S, Hammer J (2018) The social roles of bots: evaluating impact of bots on discussions in online communities. Proc ACM Hum-Comput Interact 2:1–29CrossRef

Selamat MA, Windasari NA (2021) Chatbot for SMEs: integrating customer and business owner perspectives. Tech Soc 66:101685. https://doi.org/10.1016/j.techsoc.2021.101685CrossRef

Sheehan B, Jin HS, Gottlieb U (2020) Customer service chatbots: anthropomorphism and adoption. J Bus Res 115:14–24CrossRef

Shiu-Wan H, Cheng MJ, Chiu PC (2019) Do antecedents of trust and satisfaction promote consumer loyalty in physical and virtual stores? A multi-channel view. Serv Bus 13(1):1–23CrossRef

Shum HY, He X, Li D (2018) From Eliza to XiaoIce: challenges and opportunities with social chatbots. Cornell University, Ithaca

Sidaoui K, Jaakkola M, Burton J (2020) AI feel you: customer experience assessment via chatbot interviews. J Serv Manag 31(4):745–766CrossRef

Stoeckli E, Dremel C, Uebernickel F, Brenner W (2020) How affordances of chatbots cross the chasm between social and traditional enterprise systems. Elect Mark 30(2):369–403CrossRef

Thomaz F, Salge C, Karahanna E, Hulland J (2020) Learning from the Dark Web: LEVERAGING conversational agents in the era of hyper-privacy to enhance marketing. J Acad Mark Sci 48:43–63CrossRef

Tsai WHS, Liu Y, Chuan CH (2021) How chatbots’ social presence communication enhances consumer engagement: the mediating role of parasocial interaction and dialogue. J Res Interact Mark 15(3):460–482CrossRef

Van Pinxteren MME, Pluymaekers M, Lemmink JGAM (2020) Human-like communication in conversational agents: a literature review and research agenda. J Serv Manag 31(2):203–225CrossRef

Wang HS, Yim CKB (2019) Effects of dominance transitions on advice adherence in professional service conversations. J Acad Mark Sci 47(5):919–938CrossRef

Wei W, Liu J, Mao X, Guo G, Zhu F, Zhou P, Hu Y, Feng S (2021) Target-guided emotion-aware chat machine. ACM Trans Inf Syst 39(4):1–24CrossRef

Wilkinson D, Alkan O, Liao QV, Mattetti M, Vejsbjerg I, Knijnenburg BP, Daly E (2021) Why or why not? The effect of justification styles on chatbot recommendations. ACM Trans Inf Syst 39(4):1–21CrossRef

Zhang JJY, Følstad A, Bjørkli CA (2021) Organizational factors affecting successful implementation of chatbots for customer service. J Internet Commun. https://doi.org/10.1080/15332861.2021.1966723CrossRef

Titel: Live support by chatbots with artificial intelligence: A future research agenda
verfasst von: Mark Anthony Camilleri
Ciro Troise
Publikationsdatum: 10.11.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: Service Business / Ausgabe 1/2023
Print ISSN: 1862-8516
Elektronische ISSN: 1862-8508
DOI: https://doi.org/10.1007/s11628-022-00513-9

Springer Professional

Abstract

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

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

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 1/2023

Perceived value of AI-based recommendations﻿ service: the case of voice assistants

Transforming data into information for smart services: integration of morphological analysis and text mining

The relationship between entrepreneurial orientation and success of foodservice business: effects of religion

Barriers and opportunities of digital servitization for SMEs: the effect of smart Product-Service System business models

Is the hotel industry really committed to the environment? Answering using the business models framework

Digital transformation trends in service industries

Perceived value of AI-based recommendations service: the case of voice assistants