Need for Service. How the importance of artificial intelligence interactions and human interactions are influencing customer service and loyalty.

Transcription

1 Need for Service. How the importance of artificial intelligence interactions and human interactions are influencing customer service and loyalty. Elizabeth Manser Payne, ABD Doctoral Student in Marketing University of Wisconsin-Whitewater Whitewater, Wisconsin (corresponding author) James Peltier, Ph.D. Department Chair, Arno Kleimenhagen Professor of Sales and Marketing University of Wisconsin-Whitewater Whitewater, Wisconsin

2 EXTENDED ABSTRACT Technology is reshaping the degree to which service firms depend on employees to interact with their customers (Kim et. Al, 2009; Parasuraman, 2000). Advances in artificial intelligence (AI) can now mimic responses and actions that has been historically been made only by humans (Russell & Norvig, 1995). With the application of artificial intelligence to customer service, customers are often clouded whether they are interacting with a real person, machine or both. Despite the increasing use of AI for interacting with customers, questions still remain concerning AI s impact on customer satisfaction and loyalty. AI is rapidly becoming a customer relationship management (CRM) tool (Roussinov & Khao, 2004). Artificial intelligence can discover trends and relationships in the databases to deliver a more robust understanding of the customer, thus giving the firm a strategic competitive advantage (Nemati & Barko, 2002). For example, chatbots are AI software programs that are integrated into CRM applications and are designed to interact with customers on routine transactions by simulating conversation either in an auditory or textual format. Additionally, chatbots are widely implemented in call centers (Korzeniowski, 2017), thus reducing HR costs by lowering the number of employees needed to staff customer service positions (Klie, 2016). Artificial intelligence is an advanced computer system that can learn, solve problems, and make rational decisions (Russell & Norvig, 1995). Interactions with AI gives customers the option to conceivably attain the same type of services that can also be achieved with human interaction. From the customer s point of view, the major distinction is then limited to how the service was obtained. To benchmark a successful AI interaction, we can then measure AI performance to similar human interaction transactions.

3 Previous research on customer-employee interactions have been well-researched and have been found to positively impact loyalty and customer satisfaction (Brakus, 2005; Bove & Johnson, 2006; Brock et al., 2016). Brexendorf et al. (2010) suggest that positive experiences with sales people will ultimately lead to positive brand-related outcomes, such as brand loyalty and positive intentions to remain committed to the brand. On the other hand, the perceived importance for artificial intelligence interaction still requires attention by researchers as we still do not understand how the importance of AI interactions will impact customer satisfaction or loyalty. Marketing literature has been noticeably quiet on the emerging AI field and has lagged behind practitioners who have already launched significant AI investments to interact with their customers. This has created a gap in marketing literature that this paper seeks to address. Motivated by the issues discussed above, this paper develops and outlines a conceptual NfS framework (See Figure 1) to advance the study of artificial intelligence in customer service and consumer behavior literature. The authors are in the beginning stages of developing hypotheses to empirically test the relationship developed in the conceptual model. This study contributes to literature by providing a framework for discussing artificial intelligence in customer service. The new conceptual model outlines the relationship between the antecedents and consequences of the need for service (NfS) construct with its two dimensions of perceived importance for human interactions and perceived importance for artificial intelligence interactions. Future researchers can manipulate the framework to conduct industry-specific research or add moderating variables, such as mobile banking channels to better understand the consequences of perceived importance for human and AI interactions. The overall model can assist practitioners in determining the customer service value of artificial intelligence by examining its ability to influence customer satisfaction and loyalty.

4 References Brakus, J. J., Schmitt, B. H., & Zarantonello, L. (2009). Brand experience: What is it? how is it measured? does it affect loyalty? Journal of Marketing, 73(3), 52. Brexendorf, T. O., Mühlmeier, S., Tomczak, T., & Eisend, M. (2010). The impact of sales encounters on brand loyalty. Journal of Business Research, 63(11), Bock, D. E., Mangus, S. M., & Folse, J. A. G. (2016). The road to customer loyalty paved with service customization. Journal of Business Research, 69(10), Bove, L. L., & Johnson, L. W. (2000). A customer-service worker relationship model. International Journal of Service Industry Management, 11(5), Kim, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), Klie, L. (2016). Digital assistants gain enterprise acceptance. Customer Relationship Management, 20, 12. Korzeniowski, P. (2017). Bots should be in your contact center's future. Customer Relationship Management, 21, Nemati, H. R., & Barko, C. D. (2002). Enhancing enterprise decisions through organizational data mining. The Journal of Computer Information Systems, 42(4),

5 Parasuraman, A. (2000). Technology readiness index (TRI): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research: JSR, 2(4), Roussinov, D., & J, L. Zhao. (2004). Text clustering and summary techniques for CRM message management. Journal of Enterprise Information Management, 17(6), Russell, S., Norvig, P., & Intelligence, A. (1995). A modern approach. Artificial Intelligence. Prentice-Hall, Englewood Cliffs, 25, 27.