IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v66y2022ics0969698922000303.html
   My bibliography  Save this article

(Im)Balanced customer-oriented behaviors and AI chatbots' Efficiency–Flexibility performance: The moderating role of customers’ rational choices

Author

Listed:
  • Fan, Hua
  • Han, Bing
  • Gao, Wei

Abstract

Artificial intelligence (AI) based chatbots are increasingly deployed in frontline encounters, because they combine frontline service efficiency and flexibility. Using a large-scale data set with more than 130,000 man–machine dialogues from an e-bike sharing platform, Study 1 reveals a complex relationship between chatbots' customer-oriented behaviors and their efficiency–flexibility ambidexterity. Chatbots' level of efficiency–flexibility ambidexterity is higher when their functional and relational customer-oriented behaviors are balanced rather than imbalanced (i.e., a negative imbalance effect) and when they are balanced at a higher rather than a lower level (i.e., a positive balance effect). A follow-up experiment, Study 2, and online survey, Study 3, consistently show that the negative imbalance effect is stronger as customers' perceptions of non-personalization costs decrease and privacy concerns increase, while opportunity cost has no significant influence on the negative imbalance effect. However, consistent with rational choice theory, the positive balance effect is stronger as non-personalization costs increase, privacy concerns decrease, and opportunity cost decreases. In addition, Study 1 and 3 consistently show that in alignment with the stimulus–organism–response framework, efficiency–flexibility ambidexterity partially mediates the relationship between chatbots’ (im)balanced customer-oriented behaviors and customer patronage. This study contributes to the literature on frontline ambidexterity by introducing an AI application context and a more nuanced nonlinear view of the antecedents and consequences of frontline ambidexterity.

Suggested Citation

  • Fan, Hua & Han, Bing & Gao, Wei, 2022. "(Im)Balanced customer-oriented behaviors and AI chatbots' Efficiency–Flexibility performance: The moderating role of customers’ rational choices," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    • Handle: RePEc:eee:joreco:v:66:y:2022:i:c:s0969698922000303
    DOI: 10.1016/j.jretconser.2022.102937
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698922000303
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretconser.2022.102937?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gao, Wei & Li, Wenqian & Fan, Hua & Jia, Xingping, 2021. "How customer experience incongruence affects omnichannel customer retention: The moderating role of channel characteristics," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    2. Prentice, Catherine & Nguyen, Mai, 2020. "Engaging and retaining customers with AI and employee service," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    3. Kathleen M. Eisenhardt & Nathan R. Furr & Christopher B. Bingham, 2010. "CROSSROADS---Microfoundations of Performance: Balancing Efficiency and Flexibility in Dynamic Environments," Organization Science, INFORMS, vol. 21(6), pages 1263-1273, December.
    4. Kull, Alexander J. & Romero, Marisabel & Monahan, Lisa, 2021. "How may I help you? Driving brand engagement through the warmth of an initial chatbot message," Journal of Business Research, Elsevier, vol. 135(C), pages 840-850.
    5. Stephen A. Spiller, 2011. "Opportunity Cost Consideration," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 38(4), pages 595-610.
    6. Michael Lubatkin & Zeki Simsek & Yan Ling & John F. Veiga, 2006. "Ambidexterity and Performance in Small-to Medium-Sized Firms : The Pivotal Role of Top Management Team Behavioral Integration," Post-Print hal-02311781, HAL.
    7. Prentice, Catherine & Nguyen, Mai, 2021. "Robotic service quality – Scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    8. Wu, Ing-Long & Chiu, Mai-Lun & Chen, Kuei-Wan, 2020. "Defining the determinants of online impulse buying through a shopping process of integrating perceived risk, expectation-confirmation model, and flow theory issues," International Journal of Information Management, Elsevier, vol. 52(C).
    9. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    10. Pantano, Eleonora & Pizzi, Gabriele, 2020. "Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    11. Paul S. Adler & Barbara Goldoftas & David I. Levine, 1999. "Flexibility Versus Efficiency? A Case Study of Model Changeovers in the Toyota Production System," Organization Science, INFORMS, vol. 10(1), pages 43-68, February.
    12. Bashir, Shahid & Khwaja, Muddasar Ghani & Mahmood, Asif & Turi, Jamshid Ali & Latif, Khawaja Fawad, 2021. "Refining e-shoppers’ perceived risks: Development and validation of new measurement scale," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    13. Pizzi, Gabriele & Scarpi, Daniele, 2020. "Privacy threats with retail technologies: A consumer perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    14. Chen, Qi & Feng, Yuqiang & Liu, Luning & Tian, Xianyun, 2019. "Understanding consumers’ reactance of online personalized advertising: A new scheme of rational choice from a perspective of negative effects," International Journal of Information Management, Elsevier, vol. 44(C), pages 53-64.
    15. Silva, Emmanuel Sirimal & Bonetti, Francesca, 2021. "Digital humans in fashion: Will consumers interact?," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    16. Chinchanachokchai, Sydney & Thontirawong, Pipat & Chinchanachokchai, Punjaporn, 2021. "A tale of two recommender systems: The moderating role of consumer expertise on artificial intelligence based product recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    17. Miao, C. Fred & Wang, Guangping, 2016. "The differential effects of functional vis-à-vis relational customer orientation on salesperson creativity," Journal of Business Research, Elsevier, vol. 69(12), pages 6021-6030.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fan, Hua & Gao, Wei & Han, Bing, 2023. "Are AI chatbots a cure-all? The relative effectiveness of chatbot ambidexterity in crafting hedonic and cognitive smart experiences," Journal of Business Research, Elsevier, vol. 156(C).
    2. Chakraborty, Debarun & Polisetty, Aruna & G, Sowmya & Rana, Nripendra P. & Khorana, Sangeeta, 2024. "Unlocking the potential of AI: Enhancing consumer engagement in the beauty and cosmetic product purchases," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    3. Oliveira, Guilherme Gouvea de & Lizarelli, Fabiane Letícia & Teixeira, Jorge Grenha & Mendes, Glauco Henrique de Sousa, 2023. "Curb your enthusiasm: Examining the customer experience with Alexa and its marketing outcomes," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    4. Gaan, Niharika & Shin, Yuhyung, 2023. "Sales employees’ polychronicity and sales-service ambidexterity: Mediation of work engagement and moderation of store manager support," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    5. Shahzad, Muhammad Farrukh & Xu, Shuo & An, Xin & Javed, Iqra, 2024. "Assessing the impact of AI-chatbot service quality on user e-brand loyalty through chatbot user trust, experience and electronic word of mouth," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    6. Shirie Pui Shan Ho & Matthew Yau Choi Chow, 2024. "The role of artificial intelligence in consumers’ brand preference for retail banks in Hong Kong," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(2), pages 292-305, June.
    7. Swaraj S. Bharti & Kanika Prasad & Shwati Sudha & Vineeta Kumari, 2023. "Customer acceptability towards AI-enabled digital banking: a PLS-SEM approach," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(4), pages 779-793, December.
    8. Hu, Qian & Pan, Zhao, 2023. "Can AI benefit individual resilience? The mediation roles of AI routinization and infusion," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rahman, Muhammad Sabbir & Bag, Surajit & Hossain, Md Afnan & Abdel Fattah, Fadi Abdel Muniem & Gani, Mohammad Osman & Rana, Nripendra P., 2023. "The new wave of AI-powered luxury brands online shopping experience: The role of digital multisensory cues and customers’ engagement," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    2. Subero-Navarro, à urea & Pelegrín-Borondo, Jorge & Reinares-Lara, Eva & Olarte-Pascual, Cristina, 2022. "Proposal for modeling social robot acceptance by retail customers: CAN model + technophobia," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    3. Park, Jungkun & Yun, Jeewoo & Chang, Woondeog, 2024. "Intention to adopt services by AI avatar: A protection motivation theory perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    4. Mile Katic & Renu Agarwal, 2018. "The Flexibility Paradox: Achieving Ambidexterity in High-Variety, Low-Volume Manufacturing," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 19(1), pages 69-86, March.
    5. Carolina Rojas-Córdova & Amanda J. Williamson & Julio A. Pertuze & Gustavo Calvo, 2023. "Why one strategy does not fit all: a systematic review on exploration–exploitation in different organizational archetypes," Review of Managerial Science, Springer, vol. 17(7), pages 2251-2295, October.
    6. Jan Ossenbrink & Joern Hoppmann & Volker H. Hoffmann, 2019. "Hybrid Ambidexterity: How the Environment Shapes Incumbents’ Use of Structural and Contextual Approaches," Organization Science, INFORMS, vol. 30(6), pages 1319-1348, November.
    7. Jiewei Zu & Jianan Wang & Jun Ma, 2022. "Ambidexterity in a Rapidly Changing Environment of China: Top Management Team Decision Making and Sustained Performance," Sustainability, MDPI, vol. 14(7), pages 1-20, March.
    8. Andreea N. Kiss & Dirk Libaers & Pamela S. Barr & Tang Wang & Miles A. Zachary, 2020. "CEO cognitive flexibility, information search, and organizational ambidexterity," Strategic Management Journal, Wiley Blackwell, vol. 41(12), pages 2200-2233, December.
    9. Ferry Koster & Gina van Bree, 2018. "How Managers Evoke Ambidexterity and Collaboration: A Qualitative Study in a Dutch Hospital," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-19, December.
    10. Eliza Nichifor & Adrian Trifan & Elena Mihaela Nechifor, 2021. "Artificial Intelligence in Electronic Commerce: Basic Chatbots and Consumer Journey," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 1-87, February.
    11. Wu, Jie & Wood, Geoffrey & Chen, Xiaoyun & Meyer, Martin & Liu, Zhiyang, 2020. "Strategic ambidexterity and innovation in Chinese multinational vs. indigenous firms: The role of managerial capability," International Business Review, Elsevier, vol. 29(6).
    12. Aitor Goti & Leire Querejeta-Lomas & Aitor Almeida & José Gaviria de la Puerta & Diego López-de-Ipiña, 2023. "Artificial Intelligence in Business-to-Customer Fashion Retail: A Literature Review," Mathematics, MDPI, vol. 11(13), pages 1-32, June.
    13. Swarup Kumar Dutta, 2013. "Ambidexterity as a Mediating Variable in the Relationship between Dynamism in the Environment, Organizational Context and Strategic Renewal," Jindal Journal of Business Research, , vol. 2(1), pages 27-41, June.
    14. Maduku, Daniel K. & Mpinganjira, Mercy & Rana, Nripendra P. & Thusi, Philile & Ledikwe, Aobakwe & Mkhize, Njabulo Happy-boy, 2023. "Assessing customer passion, commitment, and word-of-mouth intentions in digital assistant usage: The moderating role of technology anxiety," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    15. Daniella Laureiro-Martinez, 2014. "Cognitive Control Capabilities, Routinization Propensity, and Decision-Making Performance," Organization Science, INFORMS, vol. 25(4), pages 1111-1133, August.
    16. Yi Zhang & Feng Wei & Constance Van Horne, 2019. "Individual Ambidexterity And Antecedents In A Changing Context," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 23(03), pages 1-25, April.
    17. Juha Uotila, 2018. "Punctuated equilibrium or ambidexterity: dynamics of incremental and radical organizational change over time," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(1), pages 131-148.
    18. Christel Lane & Daniela Lup, 2015. "Cooking under Fire: Managing Multilevel Tensions between Creativity and Innovation in Haute Cuisine," Industry and Innovation, Taylor & Francis Journals, vol. 22(8), pages 654-676, November.
    19. Poushneh, Atieh, 2021. "Humanizing voice assistant: The impact of voice assistant personality on consumers’ attitudes and behaviors," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    20. Cheng, Zhendong & Fan, Wenfang & Shao, Bingjia & Jia, Wenli & Zhang, Yong, 2024. "The impact of intelligent customer service agents’ initial response on consumers’ continuous interaction intention," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:joreco:v:66:y:2022:i:c:s0969698922000303. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.