- Email: [email protected]
Chatbot e-service and customer satisfaction regarding luxury brands
Journal of Business Research xxx (xxxx) xxx–xxx
Contents lists available at ScienceDirect
Journal of Business Research journal homepage: www.elsevier.com/locate/jbusres
Chatbot e-service and customer satisfaction regarding luxury brands Minjee Chunga, Eunju Koa, , Heerim Jounga, Sang Jin Kimb ⁎
a b
Department of Clothing and Textiles, Yonsei University, Seoul, Republic of Korea Department of Business Administration, Changwon National University, Changwon-si, Gyeongsangnam-do, Republic of Korea
ARTICLE INFO
ABSTRACT
Keywords: Chatbot Communication Digital marketing Luxury brand Service agents
This study was undertaken to analyze whether luxury fashion retail brands can adhere to their core essence of providing personalized care through e-services rather than through traditional face-to-face interactions, particularly through Chatbot, an emerging digital tool offering convenient, personal, and unique customer assistance. The authors use customer data to test a five-dimension model measuring Chatbot for customer perceptions of interaction, entertainment, trendiness, customization, and problem-solving. The study reveals that Chatbot eservice provides interactive and engaging brand/customer service encounters. Marketers and managers in the luxury context can adopt the instrument to measure whether e-service agents provide desired outcomes and to determine whether they should adopt Chatbot virtual assistance.
1. Introduction As customers spend more time in digital environments, brands are moving into digital services. Technological advances now allow virtual service agents or “e-service agents” to enhance customer experiences and fulfill expectations through real-time interactions (Hagberg, Sundstrom, & Egels-Zandén, 2016). We contribute to the digital service research by studying e-service agents, particularly Chatbot agents, as a novel and entertaining way to satisfy clients, similar to the services of general offline service agents (Lowry, Romano, Jenkins, & Guthrie, 2009) who traditionally determined the success of service exchanges (Bailey & McCollough, 2000), represented the brand (Balmer & Greyser, 2006), enhanced customer/brand relationships (Fionda & Moore, 2009), provided useful information, and gave customers personally engaging and enjoyable overall shopping experiences (Kim, Kang, & Taylor, 2018; Kim & Ko, 2012). Indeed, service agents still influence 87% of in-store purchase decisions, while 77% of consumers tend to purchase from familiar salespersons (Insider-Trends, 2017). Brand managers and marketers strive to provide deep, intense, and tangible experiences that reinforce consumer preferences and awareness of the brand over its competitors (Atwal & Williams, 2009). When interactions with service agents meet customer expectations (Kang, 2006), the result is likely to be customer satisfaction, loyalty, positive word of mouth, favorable purchase intentions, and ultimately, company profits (Reynolds & Beatty, 1999). Agents tend to inform customers about current trends and possibilities for customization; they help solve problems (Locker, 1995), save time, provide accurate information, give
⁎
credible advice, and convey parasocial benefits (Holzwarth, Janiszewski, & Neumann, 2006). Traditional service agent interactions involve direct face-to-face customer/employee interactions, but social networks are now fulfilling customer needs for immediate responses outside the actual facility. Customers who have used both online and offline services are now finding online service to be effective, accessible, and both time and cost-saving (Escobar, 2016). The proliferation of digital services and digital marketing channels has given brands new opportunities to satisfy customers (Calantone, Di Benedetto, & Rubera, 2018; Correa, Hinsley, & De Zuniga, 2010; Perrey & Spillecke, 2011). The luxury sector is following the trend by adopting digital services that offer 24hour customer service through Chatbot, an online chat system (Dhaoui, 2014; Godey et al., 2016; Ko, Phau, & Aiello, 2016). In this study, we analyze how e-service agents can affect communication quality and overall customer satisfaction for high-end SPA and luxury fashion brands that use Chatbot for e-service. The Chatbot concept goes well with luxury retail brand values of providing superior service for consumers who are willing to pay more (Retail Dive, 2017). Chatbot offers a new layer of support to the service quality dimension by assuring that personalized service is available to meet customer needs anytime and anywhere. In addition, Chatbot is designed to drive future luxury brand/consumer relationships. For example, Louis Vuitton offers a Chatbot service that provides information about global offline stores, access to personal service agents regarding product care, and conversational interfaces that show the craftsmanship behind the products (Forbes, 2017a, 2017b, 2017c). Our objectives are
Corresponding author. E-mail address: [email protected] (E. Ko).
https://doi.org/10.1016/j.jbusres.2018.10.004 Received 9 November 2017; Received in revised form 29 September 2018; Accepted 1 October 2018 0148-2963/ © 2018 Elsevier Inc. All rights reserved.
Please cite this article as: Chung, M., Journal of Business Research, https://doi.org/10.1016/j.jbusres.2018.10.004
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
to verify the effect of marketing efforts provided by Chatbot in the luxury retail context. We develop a measurement for examining how information accuracy, information credibility, and communication competence impact customer perceptions in the digital service context. The study provides insights into how e-service agents affect luxury consumer perceptions. In alignment with previous studies, we show that digital service assistance tools can allow positive brand/customer interactions. Luxury fashion retail brands are becoming more aware that they must interact with customers through the digital environment and are adopting Chatbot as a marketing strategy. Thus, it is essential to study Chatbot service in luxury contexts to determine effects on customer satisfaction.
quality and social network service (SNS) activities according to interaction, entertainment, customization, trendiness, innovativeness, and problem-solving dimensions (Kim & Ko, 2012; Kim, Park, Lee, & Choi, 2016; Ladhari, Souiden, & Dufour, 2017). In addition, social media marketing efforts have shown that interaction, entertainment, customization, trendiness, and word-of-mouth can enhance brand equity and increase customer response (Godey et al., 2016; Morra, Gelosa, Ceruti, & Mazzucchelli, 2018). However, research on e-service agents is relatively scant, especially regarding online communication with brands. We aim to fill the gap by examining interaction, entertainment, trendiness, customization, and problem-solving as marketing efforts in the context of e-service agents.
2. Literature review
2.2.1. Interaction Brand associates must be courteous, helpful, and trustworthy if interactions are to be positive (Dabholkar, Thorpe, & Rentz, 1996). Customers consult with salespersons to save time, get advice, feel valued, enjoy interactions, and ease purchasing procedures (Holzwarth et al., 2006). However, technology has enabled brands to use social media for casual interactions that build and strengthen customer relationships and provide information (Kim & Ko, 2010). As a result, customer interactions with virtual service agents are similar to their interactions with real-world human agents for influencing purchase decisions, saving time, gathering advice, or gaining parasocial benefits (Holzwarth et al., 2006).
2.1. E-service agents Service agents are key to solving customer problems (Chakrabarty, Widing, & Brown, 2014) and determining success or failure in evoking purchase behaviors through positive verbal and nonverbal interactions (Bailey & McCollough, 2000; Godes et al., 2005). Honest, friendly, authentic salesperson/customer relationships are essential for ensuring that both customers and service agents have positive experiences (Bailey & McCollough, 2000; Gautam & Sharma, 2017; Reynolds & Beatty, 1999). As companies become globalized in the new era of digital marketing and artificial intelligence, brands are moving to the online world to better connect with audiences, and service agent roles are changing (Bolton et al., 2013). As artificial intelligence improves and digital marketing becomes more essential, companies across diverse insurance, banking, retail, travel, healthcare, and education industries are successfully using robotic virtual characters that assist customers through desktop interfaces (Forbes, 2017a, 2017b, 2017c). Chatbot is an example of a virtual conversational service robot that can provide human–computer interaction (Lee, Oh, & Choi, 2017; Zhang, Liu, Wang, & Zhu, 2017). New technology tools allow companies to simultaneously meet customer expectations, fulfill company goals, and create value (Choi, Ko, & Kim, 2016; Woodside & Ko, 2013). E-service agents are consistently available personal assistants who help build crucial customer relationships, allow more efficient use of customer time, and provide better understandings regarding product performance (Lee & Choi, 2017; Mimoun, Poncin, & Garnier, 2017; Zhang et al., 2017). Moreover, as accuracy improves, users can enjoy intelligent social dialogues with virtual agents (Godey et al., 2016). Thus, fashion brands such as Burberry, Louis Vuitton, Tommy Hilfiger, Levi's, H&M, and eBay are recognizing the bright promise and increasing popularity of e-service agents (Lee & Choi, 2017). (Table 1). For all that the potential to advance related literature and practical use for marketing communication, there is limited research on e-service agents and thus we aim to contribute here by studying e-service agents.
2.2.2. Entertainment Successful companies know the importance of incorporating fun and entertainment into everyday workplace practices and services (Redman & Mathews, 2002). Entertainment is a hedonic way of introducing useful and valid information, increasing value perceptions and intentions to adopt digital tools such as the mobile Internet and social media (Muntinga, Moorman, & Smit, 2011; Nysveen, Pedersen, & Thorbjørnsen, 2005). For example, Burberry produced a video alluding to the Billy Elliot movie to incorporate visual information, increase customer interest, and connect customers with the brand. Consequently, enjoyment, fun, and relaxation determine whether customers will respond positively to virtual service agents (Godey et al., 2016; Muntinga et al., 2011). 2.2.3. Trendiness Many customers want current brand-and product-related information to ensure that products appropriately convey their trendy lifestyles (Muntinga et al., 2011; Zolkepli & Kamarulzaman, 2015). Many use social media to search for new products, to learn about current trends, and to see reviews (Godey et al., 2016). They seek the latest news and search hot discussions to find new products that suit their tastes. Although in-store salespersons were once the main sources of information about fashion trends, technology changes are allowing online and brickand-mortar experiences to work together (Forbes, 2017a, 2017b, 2017c).
2.2. Marketing efforts of e-service agents
2.2.4. Customization Customization is the process of modifying, personalizing, and tailoring products to satisfy individual preferences (Wang & Li, 2012). Customized service meets individual preferences, builds stronger brand affinity, and ensures loyalty (Godey et al., 2016; Perna, Runfola, Temperini, & Gregoni, 2018). Luxury brands particularly provide products and services targeting specific customer needs and wants, rather than trying to appeal to the general public. For instance, Gucci sends personalized online messages to introduce customized products to target customers (LinkedIn, 2012). Now, virtual agents can offer customized assistance through direct chats.
E-service agents can provide essential marketing efforts that influence decision-making processes (Crosby & Johnson, 2002; Gautam & Sharma, 2017). In customer–salesperson interactions, salespersons enhance customer trust by showing empathy and listening to customer concerns (Aggarwal, Castleberry, Ridnour, & Shepherd, 2005). Such marketing efforts are particularly important for fashion brands that must exchange information about tailored fashion trends or customized services (Forbes, 2017a, 2017b, 2017c). E-service agents can reduce the physical and temporal distance from fashion brands by giving customers easy access to product information (Darke, Brady, Benedicktus, & Wilson, 2016; Zhang & Dholakia, 2018). Digitalization studies of e-service agents have measured IT service
2.2.5. Problem-solving Because proper handling often determines perceptions of retail 2
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
Table 1 Chatbot usage by fashion brands. No.
Brand
Interaction & service
Brand characteristic
Agent characteristic
1
Salvatore Ferragamo Burberry
3
Louis Vuitton
- Although other customers enter, the employee assists only one customer at time. She politely asks other customers to wait until she can serve them. - Service in English. - In-store catalogue display. - When service is delayed, the employee asks customers to wait. She then removes her shoes and kneels to continue assisting customers. - A staff member was always near to help the customer - When the interaction concluded, employees provided cards with product and contact information.
Woman Thirties Qualified expert
2
4
Prada
- Good explanation of the material - Detailed product recommendation based on customer preferences - Demonstration of the brand's craftsmanship - Employees interact with customers eye-to-eye - Good explanation of the material - Recommendation based on the profile's preferences - Employees greet customers at the entrance - Employees have good knowledge about the brand - In-store demonstration of the brand's craftsmanship - Good knowledge about the brand and material - Recommendation based on the profile's preferences
- Although the website is available in Korea, brand purchases must be made in-store.
5
Gucci
- Provides fewer personalized services than other luxury stores. - Service in Chinese.
6
Tommy Hilfiger
- Good knowledge about the collection but failed to ask for the customer's preference. - Service in Chinese - No deep knowledge about the collection - No fluency in Korean or English
Woman Twenties, Qualified expert Woman Thirties, Qualified expert Woman Twenties, Non-expert Foreigner
- Store has a VR panel where customers can virtually try on clothes.
Woman Twenties, Non-expert Man Thirties Qualified expert
which then forms purchase intentions (Taylor & Baker, 1994; Wiedmann, Hennigs, & Siebels, 2009). In the case of online customers, satisfaction might be indicated by their choice to continue using particular websites without changing to other retailers.
service, retail brand associates are often trained to immediately and sincerely handle customer problems, complaints, returns, and exchanges (Dabholkar et al., 1996; Kim et al., 2016). Furthermore, customers who have unmet quality expectations can feel anger and even shame in reactions to feeling restrained (Izard, 1977).
3. Hypotheses development
2.3. Communication quality
3.1. Marketing efforts of e-service agents and communication quality
If customers are to perceive that they have experienced quality communication and to respond positively to the information transmitted (Maltz, 2000), the exchange must meet parameters important in human communication (Mohr & Sohi, 1995). We align our assumptions with studies of bot agents such as Twitter to assume that quality communication requires accuracy, credibility, and competence (Edwards, Edwards, Spence, & Shelton, 2014; Zhao & Rosson, 2009). Customers trust the reliability and completeness of communication when it is accurate (Barry & Crant, 2000; Mohr & Sohi, 1995). They perceive that information is credible and persuasive when they have good relationships with communicators (Edwards et al., 2014; Yuan, Kim, & Kim, 2016). That is, customers must perceive that computermediated communicators listen to their concerns, accurately diagnose their issues, and provide the needed information (Clokie & Fourie, 2016; Spitzberg, 2006; Zhao & Rosson, 2009). To ensure their unique market positions, luxury brands must form communication strategies that adhere to their core brand image (Liu, Li, Mizerski, & Soh, 2012). To evoke positive perceptions of intimacy, understanding, and communication quality, interactions must be smooth, accurate, and complete (Emmers-Sommer, 2004; Maltz, 2000; Mohr & Sohi, 1995). Consumers will positively appraise “the believability of a communicator” (O'Keefe, 1990, p. 130–131) if the information is delivered efficiently and appears to be competent, credible (Zhao & Rosson, 2009), and expert (Snavely & McNeill, 2008; Spitzberg, 2006; Webster & Sundaram, 2009). Thus, we examine accuracy, credibility, and communication competence as communication quality properties in the context of online interaction.
To provide accurate, credible, time-saving information and parasocial benefits (Holzwarth et al., 2006), service agents must provide rich, expert, intense, and efficient communication, using few words and symbols (Barry & Crant, 2000). Good service agent/customer communication focuses on customer needs for trendiness, customization, and problem-solving (Locker, 1995). Customer-oriented salespersons can adapt to customer needs and are thus most likely to establish positive customer relationships (Chakrabarty et al., 2014) that reduces uncertainty, allows efficient information search, and provides enjoyment (Haas & Kenning, 2014). Entertainment also encourages further intentions to use technology. That is, customers must derive enjoyment if they are to use virtual service agents and social media for obtaining brand-related information (Muntinga et al., 2011). Similar to service agents, e-service agents are essential for enhancing customer–brand relationships. Brand marketers use online communication to build positive customer relationships, increase profits, and inform customers about products and services (Kim & Ko, 2012). If consumers are to perceive quality communication, their online relationships with service agents must be smooth, satisfying, timely, effective, and accurate (Emmers-Sommer, 2004; Maltz, 2000; Mohr & Sohi, 1995; Vos, 2009). Luxury brands are finding that interactive marketing positively affects customer/brand relationships (Godey et al., 2016). One interactive method is through online social media to reinforce customer relationships (Ko et al., 2016), acquire information, transmit brand personality, and share opinions about new products. To help luxury brands understand which factors are essential for communicating with customers, we focus on luxury brands and posit that e-service agents can perform marketing efforts that are related to communication quality, which requires accuracy, credibility, and competence:
2.4. Satisfaction Customer satisfaction occurs when customers find that products or services meet or exceed their positive expectations (Chiou & Droge, 2006; Santini, Ladeira, & Sampaio, 2018). Luxury branded products particularly evoke expectations that products will perform as promised,
H1. E-service agents can provide marketing efforts that evoke communication accuracy. 3
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
H2. E-service agents can provide marketing efforts that evoke communication credibility.
outcomes.
H3. E-service agents can provide marketing efforts that evoke communication competence.
4.2. Measurement and procedure We gathered 29 items used in previous studies to measure marketing efforts according to interaction, entertainment, trendiness, customization, and problem-solving (Coelho & Henseler, 2012; Kim & Ko, 2012; Lee & Choi, 2017). These items were previously adopted to verify how brands affect customer relationships through virtual environments. To measure communication quality, we developed 14 items from McCroskey and Teven (1999), Mohr and Sohi (1995), and Spitzberg (2006). We measured overall satisfaction using previous constructs (Joosten, Bloemer, & Hillebrand, 2016; Lee & Choi, 2017). All items were measured on a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). We focused on how young consumers residing in South Korea perceive e-service agents for luxury brands. European luxury brands are enjoying increasing popularity among young Korean shoppers, growing as much as 60% in recent years (The Korea Herald, 2018). Luxury products are strong symbols of social status among Korean women. Moreover, customers from ages 20 to 30 seek imported high-end products in accordance with the latest trends (The Korea Bizwire, 2017), especially through online stores (The Korea Herald, 2018). We surveyed 161 Korean students from a large urban university in Korea. Participants were required to have previously interacted with online luxury brand agents, and to have ultimately purchased a luxury product. After we eliminated incomplete surveys, 157 questionnaires remained for analysis. Respondents were 20 to 30 years-old, averaged 29; most (68.8%) were women (n = 108). We designed the questionnaire to gather data about experiences with Chatbot services for the luxury brand Burberry, which actively offers Chatbot as a new service tool. Respondents viewed a screenshot of a conversation between a customer and Chatbot, the brand's service agent. They then answered questions about the Chatbot's marketing efforts, communication quality, and satisfaction.
3.2. Communication quality and satisfaction Customer satisfaction is more likely when salespersons convey trustworthy, relevant, current, and in-depth product information (Jian, Shi, & Dalisay, 2014; Setia, Venkatesh, & Joglekar, 2013), which reduces uncertainty (Adjei, Noble, & Noble, 2010; Hutter, Hautz, Dennhardt, & Füller, 2013; Mohr & Sohi, 1995), evokes positive attitudes toward service agents, motivates psychological connections and satisfaction, and makes consumers willing to purchase and repurchase premium-priced brands (Annie Jin, 2012; McAlexander, Schouten, & Koenig, 2002; Yuan et al., 2016). Twitterbots can be similar to human agents in providing credible communication and customer satisfaction, but they convey information through digital tools and computer-mediated communication (Edwards et al., 2014; Lowry et al., 2009). For example, fashion brands are using Chatbot e-service agents to interact with customers, provide timely answers to customer questions, and deliver wide and deep information to reduce uncertainty and provide customer satisfaction (Chen & Xie, 2008; Mimoun et al., 2017). But Chatbot agents in luxury brands, like human agents, must be accurate, credible, and competent. Thus: H4. Perceived satisfaction.
communication
accuracy
positively
influences
H5. Perceived satisfaction.
communication
credibility
positively
influences
H6. Perceived communication competence positively influences satisfaction. 4. Research method
5. Empirical results
4.1. Conceptual model
Exploratory and confirmatory factor analyses were used to empirically validate the scale. Composite reliability (CR) coefficient and the average variance extracted (AVE) were used to test scale reliability (Table 2). Validity was based on the AVE values. Measures appeared to
Fig. 1 shows the conceptual model designed for this study. In-store communication measurements were applied to the online context to identify how e-service agents' marketing efforts affect communication
Fig. 1. Conceptual model. 4
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
Table 2 Standardized CFA loadings. Items
Standardized regression weight
Cronbach's α
Interaction: composite reliability = 0.828; average variance extracted = 0.548 The service agent has the knowledge to answer customers' questions. The service agent is never too busy to answer customers' requests. The service agent gives customers individual attention. The service agent is consistently courteous with customers.
0.792 0.873 0.743 0.744
0.867
Entertainment: composite reliability = 0.832; average variance extracted = 0.554 It is fun and enjoyable to share a conversation with the service agent. I was absorbed in the conversation with the service agent. The conversation with the service agent was exciting. I enjoy choosing products more if they are recommended by the service agent than if I choose them myself.
0.808 0.756 0.795 0.814
0.872
Trendiness: composite reliability = 0.0847; average variance extracted = 0.582 The service agent gives the newest information. Using the brand's service agent is very trendy. The service agent provides up-to-date contents. It is fashionable to use the brand's service agent.
0.873 0.788 0.869 0.790
0.897
Customization: composite reliability = 0.817; average variance extracted = 0.529 The brand offers products and services that I couldn't find in another company. If I changed companies, the products and services would not be as customized as I have now. I feel that using this Chatbot and transacting with this service agent meets my personal needs. The service agent provides information about products according to my preferences.
0.763 0.824 0.713 0.773
0.850
Problem solving: composite reliability = 0.814; average variance extracted = 0.525 The service agent willingly handles returns and exchanges. When a customer has a problem, the service agent shows a sincere interest in solving it. The conversational agent is able to handle customer complaints directly and immediately. I have confidence that the service agent has the ability to get the job done.
0.786 0.724 0.602 0.698
0.793
Accuracy: composite reliability = 0.917; average variance extracted = 0.687 The communication with the service agent is timely. The communication with the service agent is accurate. The communication with the service agent is adequate. The communication with the service agent is complete. The communication with the service agent is credible.
0.897 0.909 0.882 0.882 0.884
0.95
Credibility: composite reliability = 0.835; average variance extracted = 0.560 The conversational agent is honest. The conversational agent is trustworthy. The conversational agent is honorable. The conversational agent is moral.
0.778 0.680 0.814 0.823
0.859
Communication competence: composite reliability = 0.734; average variance extracted = 0.367 My interactions with the service agent are more productive than face-to-face interactions with in-store agents. Using service agents is more efficient than other forms of communication. Service agents save a tremendous amount of time.
0.633 0.659 0.565
0.758
Satisfaction: composite reliability = 0.858; average variance extracted = 0.503 I am satisfied with the service agent. I am content with the service agent. The service agent did a good job. The service agent did what I expected. I am happy with the service agent. I was satisfied with the experience of talking with the service agent.
0.736 0.754 0.733 0.747 0.720 0.805
0.884
χ2 = 776.559, df = 629 (χ2/df = 1.235, p = .000), IFI = 0.967, TLI = 0.963, CFI = 0.967, RMSEA = 0.039.
Table 3 Results for correlation matrix.
Interaction (IN) Entertainment (EN) Trendiness (TR) Customization (CU) Problem solving (PS) Accuracy (AC) Credibility (CR) Communication competence (CC) Satisfaction (SA) Mean S.D. a b
IN
EN
TR
CU
PS
AC
CR
0.624a 0.716b 0.637 0.591 0.565 0.348 0.764
0.630a 0.643 0.632 0.687 0.351 0.742
0.691a 0.674 0.509 0.354 0.757
0.592a 0.600 0.344 0.767
0.498a 0.325 0.734
0.794a 0.250
0.602a
0.119 0.616 3.10 1.00
0.071 0.515 3.19 1.00
0.115 0.639 3.36 1.13
0.079 0.647 3.12 0.95
0.171 0.776 2.70 0.76
0.323 0.365 2.91 1.36
0.271 0.788 3.08 0.90
AVE (Average Variance Extracted). Correlation between variables. 5
CC
SA
0.385a 0.155 2.30 0.80
0.562a 3.09 0.90
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
communicate with customers. Our study results can be a guideline for fashion brands to ensure appropriate marketing efforts through e-services. Luxury customers expect exclusive experiences. Although offline brand performance is essential, digital contexts can enhance company–customer connections, customer satisfaction, and shopping experiences. To strengthen online communications, fashion brands are advised to provide accurate and reliable information to ensure positive marketing efforts.
be reliable: the reliability coefficient for service agents' marketing efforts was 0.87 for interaction, 0.87 for entertainment, 0.90 for trendiness, 0.85 for customization, and 0.80 for problem-solving. Cronbach's alpha values exceeded 0.7. The average variance extracted exceeded 0.5, confirming validity for all cases except communication competence. Reliability coefficients were: accuracy = 0.95, credibility = 0.86, communication competence = 0.76, satisfaction = 0.88. Table 2 shows the results of confirmatory factor analysis, AVE, and CR. Correlation analysis was then conducted to observe correlations between variables used in further analysis (Table 3). To test the hypotheses, we used structural equation modeling (SEM). The overall fit indices showed an acceptable fit to the data (χ2 = 349.376, df = 224, χ2/df = 1.560) at a significant level (p = .000), and fit indices within accepted standards (IFI = 0.958, TLI = 0.952, CFI = 0.957, RMSEA = 0.060). The path coefficients revealed that marketing efforts positively impacted accuracy (β = 0.374, p < .001) and credibility (β = 0.964, p < .001), but not competence (β = 0.174, n.s.). Accuracy (β = 0.860, p < .05) and credibility (β = 0.938, p < .001) positively affected satisfaction. Competence had no impact on satisfaction. Marketing efforts failed to significantly affect communication competence and thus failed to bring satisfaction. Participants might have perceived that Chatbot service is more competent than offline service. Although they perceived that Chatbot failed to provide diversity of information, efficiency, and time-saving, they perceived accuracy and credibility. Consider that luxury brand customers tend to devote much time and careful consideration to their purchases. Thus the luxury context may cause customers to perceive that saving time minimizes their effort. Fig. 2 is an illustration of the relationship between variables of the research model.
6.1. Implications This study has several theoretical implications. First, the study is one of the earliest to examine digital contexts to show that online service agents provide convenience and quality communication that positively affect customer perceptions of marketing efforts. Despite the rich prior research on service agents, our work on e-service agents is relatively seminal and establishes a basis for further development in associated theories. Second, our empirical approach demonstrates that e-service agent performance can be measured according to interaction, entertainment, trendiness, customization, and problem-solving components of marketing in the digital context. Future research on customer relationships in virtual environments can further develop our findings showing that e-service agent performance enhances communication. Last, the vast, complex, highly competitive luxury brand industry faces shifting consumption patterns. Brands are keeping pace with new opportunities by providing e-service agents, but empirical research has rarely examined whether they provide quality communication. Nevertheless, customers have increasingly positive perceptions and intentions to interact with Twitterbots, perceiving them as competent, time-saving information-gathering tools (Edwards et al., 2014). By showing that e-service agents provide quality communication that positively impacts customer satisfaction, our study enriches the luxury fashion literature. The findings have managerial implications particularly for the luxury retail segment. First, we focused on consumers 20 to 30 yearsold residing in South Korea, a strong segment of luxury consumers, to capture their perceptions of e-service agent services. Our findings show that luxury fashion brands can use Chatbot to develop digital customer
6. Conclusion Technology now allows artificial intelligence to provide marketing efforts through e-service agents, with effects on customer perceptions of communication quality and brand satisfaction. In this study, we show that customer satisfaction with luxury retail brand e-service agents requires perceptions of having received quality communication. We show how digital service assistance tools can help build positive customer relationships even though e-service agents do not fully
Fig. 2. Results for Structural Equation Modeling (SEM). Model Fit: χ2 = 349.376, df = 224 (χ2/df = 1.560, p = .000), IFI = 0.958, TLI = 0.952, CFI = 0.957, RMSEA = 0.060 Note: The path coefficients are standardized path coefficients, ***p < .001, **p < .01, *p < .05. 6
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
assistance tools that increase customer engagement, provide unrestricted availability, offer highly customizable flexibility, and give simple and natural customer experiences. Chatbots can work with other digital tools such as applications to smooth customer communications with luxury brands. Moreover, our results can be applied to other fashion brands such as SPA or Masstige who wish to maintain positive relationships with core customers through e-service agents. Furthermore, fashion brands can use online communication history to derive inspiration for future customized products. Second, customer–service agent communication precedes trust. Our findings indicate that luxury brand marketers should ensure that oneto-one interactions are accurate and credible so that customers will perceive optimized personal service and rapid response. In addition to carefully training employees to be credible brand ambassadors, luxury brands are advised to consider the five quality dimensions—interaction, entertainment, trendiness, customization, and problem-solving—when building programs for e-service agents. Third, e-service agent technology is currently limited in communication subtleties. As part of the luxury experience, luxury brand customers might desire to interact with actual service agents. We recommend that fashion brands offer e-service agents for convenience, while offering offline service agents for richer brand/customer interactions and customer equity.
6.2. Limitations for future research This study has some limitations to be addressed. The stimuli were developed to simulate real experiences with luxury retail brands (Appendix A): participants viewed screenshots of a manipulated Chatbot template used by the luxury brand Burberry. A live feed for participant interaction might have increased study validity. Future studies should further examine perceptions of other interactional Chatbot feeds. Additionally, study participants were 20 to 30 years-old, an age group that tends to have the most interest in technology (Smartinsights, 2017). All participants had previously worked with service agents before purchasing luxury products. Future studies should evaluate whether outcomes differ among age groups that are unfamiliar with Chatbot. Acknowledgements This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (MOE) (NRF2017S1A2A2041810).
Appendix A. Stimuli development for luxury brand chatbot service
Journal of Brand Management, 16(5–6), 338–346. Bailey, J. J., & McCollough, M. A. (2000). Emotional labor and the difficult customer: Coping strategies of service agents and organizational consequences. Journal of Professional Services Marketing, 20(2), 51–72. Balmer, J. M., & Greyser, S. A. (2006). Corporate marketing: Integrating corporate identity, corporate branding, corporate communications, corporate image and corporate reputation. European Journal of Marketing, 40(7/8), 730–741. Barry, B., & Crant, J. M. (2000). Dyadic communication relationships in organizations: An attribution/expectancy approach. Organization Science, 11(6), 648–664. Bolton, R. N., Parasuraman, A., Hoefnagels, A., Migchels, N., Kabadayi, S., Gruber, T., ... Solnet, D. (2013). Understanding generation Y and their use of social media: A review and research agenda. Journal of Service Management, 24(3), 245–267.
References Adjei, M. T., Noble, S. M., & Noble, C. H. (2010). The influence of C2C communications in online brand communities on customer purchase behavior. Journal of the Academy of Marketing Science, 38(5), 634–653. Aggarwal, P., Castleberry, S. B., Ridnour, R., & Shepherd, C. D. (2005). Salesperson empathy and listening: Impact on relationship outcomes. Journal of Marketing Theory and Practice, 13(3), 16–31. Annie Jin, S. A. (2012). The potential of social media for luxury brand management. Marketing Intelligence & Planning, 30(7), 687–699. Atwal, G., & Williams, A. (2009). Luxury brand marketing–The experience is everything!.
7
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al. Calantone, R. J., Di Benedetto, A., & Rubera, G. (2018). Launch activities and timing in new product development. Journal of Global Scholars of Marketing Science, 28(1), 33–41. Chakrabarty, S., Widing, R. E., & Brown, G. (2014). Selling behaviours and sales performance: The moderating and mediating effects of interpersonal mentalizing. Journal of Personal Selling & Sales Management, 34(2), 112–122. Chen, Y., & Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix. Management Science, 54(3), 477–491. Chiou, J. S., & Droge, C. (2006). Service quality, trust, specific asset investment, and expertise: Direct and indirect effects in a satisfaction-loyalty framework. Journal of the Academy of Marketing Science, 34(4), 613–627. Choi, E., Ko, E., & Kim, A. J. (2016). Explaining and predicting purchase intentions following luxury-fashion brand value co-creation encounters. Journal of Business Research, 69(12), 5827–5832. Clokie, T. L., & Fourie, E. (2016). Graduate employability and communication competence: Are undergraduates taught relevant skills? Business and Professional Communication Quarterly, 79(4), 442–463. Coelho, P. S., & Henseler, J. (2012). Creating customer loyalty through service customization. European Journal of Marketing, 46(3/4), 331–356. Correa, T., Hinsley, A. W., & De Zuniga, H. G. (2010). Who interacts on the Web? The intersection of users' personality and social media use. Computers in Human Behavior, 26(2), 247–253. Crosby, L. A., & Johnson, S. L. (2002). Going my way? Marketing Management, 11(4), 10–11. Dabholkar, P. A., Thorpe, D. I., & Rentz, J. O. (1996). A measure of service quality for retail stores: Scale development and validation. Journal of the Academy of Marketing Science, 24(1), 3. Darke, P. R., Brady, M. K., Benedicktus, R. L., & Wilson, A. E. (2016). Feeling close from afar: The role of psychological distance in offsetting distrust in unfamiliar online retailers. Journal of Retailing, 92(3), 287–299. Dhaoui, C. (2014). An empirical study of luxury brand marketing effectiveness and its impact on consumer engagement on Facebook. Journal of Global Fashion Marketing, 5(3), 209–222. Edwards, C., Edwards, A., Spence, P. R., & Shelton, A. K. (2014). Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter. Computers in Human Behavior, 33, 372–376. Emmers-Sommer, T. M. (2004). The effect of communication quality and quantity indicators on intimacy and relational satisfaction. Journal of Social and Personal Relationships, 21(3), 399–411. Escobar, A. (2016). The impact of the digital revolution in the development of market and communication strategies for the luxury sector (fashion luxury). Central European Business Review, 5(2), 17. Fionda, A. M., & Moore, C. M. (2009). The anatomy of the luxury fashion brand. Journal of Brand Management, 16(5–6), 347–363. Forbes (2017a). How Chatbots improve customer experience in every industry: An infograph. https://www.forbes.com/sites/blakemorgan/2017/06/08/how-chatbotsimprove-customer-experience-in-every-industry-an-infograph/#2162528867df/, Accessed date: 15 July 2017. Forbes (2017b). How luxury brands are adapting to an omnichannel world. https://www. forbes.com/sites/forbescommunicationscouncil/2017/06/02/how-luxury-brandsare-adapting-to-an-omnichannel-world/#6b3dadb81958/, Accessed date: 15 July 2017. Forbes (2017c). Louis Vuitton becomes latest luxury brand to launch a Chatbot. https:// www.forbes.com/sites/rachelarthur/2017/12/08/louis-vuitton-becomes-latestluxury-brand-to-launch-a-chatbot/#46b9941afe10/, Accessed date: 30 December 2017. Gautam, V., & Sharma, V. (2017). The mediating role of customer relationship on the social media marketing and purchase intention relationship with special reference to luxury fashion brands. Journal of Promotion Management, 1–17. Godes, D., Mayzlin, D., Chen, Y., Das, S., Dellarocas, C., Pfeiffer, B., ... Verlegh, P. (2005). The firm's management of social interactions. Marketing Letters, 16(3–4), 415–428. Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research, 69(12), 5833–5841. Haas, A., & Kenning, P. (2014). Utilitarian and hedonic motivators of shoppers' decision to consult with salespeople. Journal of Retailing, 90(3), 428–441. Hagberg, J., Sundstrom, M., & Egels-Zandén, N. (2016). The digitalization of retailing: An exploratory framework. International Journal of Retail & Distribution Management, 44(7), 694–712. Holzwarth, M., Janiszewski, C., & Neumann, M. M. (2006). The influence of avatars on online consumer shopping behavior. Journal of Marketing, 70(4), 19–36. Hutter, K., Hautz, J., Dennhardt, S., & Füller, J. (2013). The impact of user interactions in social media on brand awareness and purchase intention: The case of MINI on Facebook. The Journal of Product and Brand Management, 22(5/6), 342–351. Insider-Trends (2017). Retail trends factfile 2017: Physical retail. http://www.insidertrends.com/retail-trends-factfile-2017-physical-retail/, Accessed date: 30 December 2017. Izard, C. E. (1977). Human emotions. New York, NY: Plenum Press. Jian, G., Shi, X., & Dalisay, F. (2014). Leader–member conversational quality: Scale development and validation through three studies. Management Communication Quarterly, 28(3), 375–403. Joosten, H., Bloemer, J., & Hillebrand, B. (2016). Is more customer control of services always better? Journal of Service Management, 27(2), 218–246. Kang, G. D. (2006). The hierarchical structure of service quality: Integration of technical and functional quality. Managing Service Quality: An International Journal, 16(1),
37–50. Kim, A. J., & Ko, E. (2010). Impacts of luxury fashion brand's social media marketing on customer relationship and purchase intention. Journal of Global Fashion Marketing, 1(3), 164–171. Kim, A. J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research, 65(10), 1480–1486. Kim, J., Kang, S., & Taylor, C. R. (2018). Technology driven experiences from mobile direct to virtual reality. Journal of Global Scholars of Marketing Science, 28(1), 96–102. Kim, S., Park, G., Lee, Y., & Choi, S. (2016). Customer emotions and their triggers in luxury retail: Understanding the effects of customer emotions before and after entering a luxury shop. Journal of Business Research, 69(12), 5809–5818. Ko, E., Phau, I., & Aiello, G. (2016). Luxury brand strategies and customer experiences: Contributions to theory and practice. Journal of Business Research, 69(12), 5749–5752. Ladhari, R., Souiden, N., & Dufour, B. (2017). The role of emotions in utilitarian service settings: The effects of emotional satisfaction on product perception and behavioral intentions. Journal of Retailing and Consumer Services, 34, 10–18. Lee, D., Oh, K. J., & Choi, H. J. (2017, February). The Chatbot feels you: A counseling service using emotional response generation. Big data and smart computing (BigComp), 2017 IEEE International Conference on (pp. 437–440). IEEE. Lee, S., & Choi, J. (2017). Enhancing user experience with conversational agent for movie recommendation: Effects of self-disclosure and reciprocity. International Journal of Human-Computer Studies, 103, 95–105. LinkedIn (2012). Gucci – Social media marketing strategies using internet and social networking sites. http://www.slideshare.net/AngelKritiSangar/gucci-socialmediamarketing-strategies-using-internet-social-networking-sites/, Accessed date: 30 December 2017. Liu, F., Li, J., Mizerski, D., & Soh, H. (2012). Self-congruity, brand attitude, and brand loyalty: A study on luxury brands. European Journal of Marketing, 46(7/8), 922–937. Locker, K. O. (1995). Business and administrative communication (3rd ed.). Chicago: Irwin. Lowry, P. B., Romano, N. C., Jenkins, J. L., & Guthrie, R. W. (2009). The CMC interactivity model: How interactivity enhances communication quality and process satisfaction in lean-media groups. Journal of Management Information Systems, 26(1), 155–196. Maltz, E. (2000). Is all communication created equal? An investigation into the effects of communication mode on perceived information quality. Journal of Product Innovation Management, 17(2), 110–127. McAlexander, J. H., Schouten, J. W., & Koenig, H. F. (2002). Building brand community. Journal of Marketing, 66(1), 38–54. McCroskey, J. C., & Teven, J. J. (1999). Goodwill: A reexamination of the construct and its measurement. Communication Monographs, 66(1), 90–103. Mimoun, M. S. B., Poncin, I., & Garnier, M. (2017). Animated conversational agents and econsumer productivity: The roles of agents and individual characteristics. Information & Management, 54(5), 545–559. Mohr, J. J., & Sohi, R. S. (1995). Communication flows in distribution channels: Impact on assessments of communication quality and satisfaction. Journal of Retailing, 71(4), 393–415. Morra, M. C., Gelosa, V., Ceruti, F., & Mazzucchelli, A. (2018). Original or counterfeit luxury fashion brands? The effect of social media on purchase intention. Journal of Global Fashion Marketing, 9(1), 24–39. Muntinga, D. G., Moorman, M., & Smit, E. G. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30(1), 13–46. Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. (2005). Intentions to use mobile services: Antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, 33(3), 330–346. O'Keefe, D. J. (1990). Persuasion: Theory and research. Newbury Park, CA: Sage. Perna, A., Runfola, A., Temperini, V., & Gregori, G. L. (2018). Problematizing customization and IT in the fashion industry: A case study of an Italian shoemaker. Journal of Global Fashion Marketing, 9(1), 73–86. Perrey, J., & Spillecke, D. (2011). Retail marketing and branding: A definitive guide to maximizing ROI. Wiley (Part2, Chapter 9). Redman, T., & Mathews, B. P. (2002). Managing services: Should we be having fun? Service Industries Journal, 22(3), 51–62. Retail Dive (2017). Louis Vuitton joins luxury brand chatbot trend. https://www. retaildive.com/news/louis-vuitton-joins-luxury-brand-chatbot-trend/512680/, Accessed date: 30 December 2017. Reynolds, K. E., & Beatty, S. E. (1999). Customer benefits and company consequences of customer-salesperson relationships in retailing. Journal of Retailing, 75(1), 11–32. Santini, F. D. O., Ladeira, W. J., & Sampaio, C. H. (2018). The role of satisfaction in fashion marketing: a meta-analysis. Journal of Global Fashion Marketing, 9(4), 1–17. Setia, P., Venkatesh, V., & Joglekar, S. (2013). Leveraging digital technologies: How information quality leads to localized capabilities and customer service performance. MIS Quarterly, 37(2), 565–590. Smartinsights (2017). Global social media research summary. http://www.smartinsights. com/social-media-marketing/social-media-strategy/new-global-social-mediaresearch/, Accessed date: 30 December 2017. Snavely, W. B., & McNeill, J. D. (2008). Communicator style and social style: Testing a theoretical interface. Journal of Leadership and Organizational Studies, 14(3), 219–232. Spitzberg, B. H. (2006). Preliminary development of a model and measure of computermediated communication (CMC) competence. Journal of Computer-Mediated Communication, 11(2), 629–666. Taylor, S. A., & Baker, T. L. (1994). An assessment of the relationship between service quality and customer satisfaction in the formation of consumers' purchase intentions. Journal of Retailing, 70(2), 163–178.
8
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al. The Korea Bizwire (2017). Overseas luxury brands booming with Young South Korean consumers. http://koreabizwire.com/overseas-luxury-brands-booming-with-youngsouth-korean-consumers/83334/, Accessed date: 30 December 2017. The Korea Herald (2018). Luxury European brands extend reach to Korean shoppers. http://www.koreaherald.com/view.php?ud=20180201000941/, Accessed date: 30 January 2018. Vos, M. (2009). Communication quality and added value: A measurement instrument for municipalities. Journal of Communication Management, 13(4), 362–377. Wang, W. T., & Li, H. M. (2012). Factors influencing mobile services adoption: A brandequity perspective. Internet Research, 22(2), 142–179. Webster, C., & Sundaram, D. S. (2009). Effect of service provider's communication style on customer satisfaction in professional services setting: The moderating role of criticality and service nature. Journal of Services Marketing, 23(2), 103–113. Wiedmann, K. P., Hennigs, N., & Siebels, A. (2009). Value-based segmentation of luxury
consumption behavior. Psychology and Marketing, 26(7), 625–651. Woodside, A. G., & Ko, E. (2013). Luxury fashion and culture (7th ed.). Emerald Group Publishing (Chapter 1). Yuan, C. L., Kim, J., & Kim, S. J. (2016). Parasocial relationship effects on customer equity in the social media context. Journal of Business Research, 69(9), 3795–3803. Zhang, M., & Dholakia, N. (2018). Conceptual framing of virtuality and virtual consumption research. Journal of Global Scholars of Marketing Science, 28(4), 305–319. Zhang, W., Liu, T., Wang, Y., & Zhu, Q. (2017). Neural personalized response generation as domain adaptation. (arXiv preprint arXiv:1701.02073). Zhao, D., & Rosson, M. B. (2009). How and why people Twitter: the role that microblogging plays in informal communication at work. In May (Ed.). Proceedings of the ACM 2009 international conference on supporting group work (pp. 243–252). ACM. Zolkepli, I. A., & Kamarulzaman, Y. (2015). Social media adoption: The role of media needs and innovation characteristics. Computers in Human Behavior, 43, 189–209.
9
Contents lists available at ScienceDirect
Journal of Business Research journal homepage: www.elsevier.com/locate/jbusres
Chatbot e-service and customer satisfaction regarding luxury brands Minjee Chunga, Eunju Koa, , Heerim Jounga, Sang Jin Kimb ⁎
a b
Department of Clothing and Textiles, Yonsei University, Seoul, Republic of Korea Department of Business Administration, Changwon National University, Changwon-si, Gyeongsangnam-do, Republic of Korea
ARTICLE INFO
ABSTRACT
Keywords: Chatbot Communication Digital marketing Luxury brand Service agents
This study was undertaken to analyze whether luxury fashion retail brands can adhere to their core essence of providing personalized care through e-services rather than through traditional face-to-face interactions, particularly through Chatbot, an emerging digital tool offering convenient, personal, and unique customer assistance. The authors use customer data to test a five-dimension model measuring Chatbot for customer perceptions of interaction, entertainment, trendiness, customization, and problem-solving. The study reveals that Chatbot eservice provides interactive and engaging brand/customer service encounters. Marketers and managers in the luxury context can adopt the instrument to measure whether e-service agents provide desired outcomes and to determine whether they should adopt Chatbot virtual assistance.
1. Introduction As customers spend more time in digital environments, brands are moving into digital services. Technological advances now allow virtual service agents or “e-service agents” to enhance customer experiences and fulfill expectations through real-time interactions (Hagberg, Sundstrom, & Egels-Zandén, 2016). We contribute to the digital service research by studying e-service agents, particularly Chatbot agents, as a novel and entertaining way to satisfy clients, similar to the services of general offline service agents (Lowry, Romano, Jenkins, & Guthrie, 2009) who traditionally determined the success of service exchanges (Bailey & McCollough, 2000), represented the brand (Balmer & Greyser, 2006), enhanced customer/brand relationships (Fionda & Moore, 2009), provided useful information, and gave customers personally engaging and enjoyable overall shopping experiences (Kim, Kang, & Taylor, 2018; Kim & Ko, 2012). Indeed, service agents still influence 87% of in-store purchase decisions, while 77% of consumers tend to purchase from familiar salespersons (Insider-Trends, 2017). Brand managers and marketers strive to provide deep, intense, and tangible experiences that reinforce consumer preferences and awareness of the brand over its competitors (Atwal & Williams, 2009). When interactions with service agents meet customer expectations (Kang, 2006), the result is likely to be customer satisfaction, loyalty, positive word of mouth, favorable purchase intentions, and ultimately, company profits (Reynolds & Beatty, 1999). Agents tend to inform customers about current trends and possibilities for customization; they help solve problems (Locker, 1995), save time, provide accurate information, give
⁎
credible advice, and convey parasocial benefits (Holzwarth, Janiszewski, & Neumann, 2006). Traditional service agent interactions involve direct face-to-face customer/employee interactions, but social networks are now fulfilling customer needs for immediate responses outside the actual facility. Customers who have used both online and offline services are now finding online service to be effective, accessible, and both time and cost-saving (Escobar, 2016). The proliferation of digital services and digital marketing channels has given brands new opportunities to satisfy customers (Calantone, Di Benedetto, & Rubera, 2018; Correa, Hinsley, & De Zuniga, 2010; Perrey & Spillecke, 2011). The luxury sector is following the trend by adopting digital services that offer 24hour customer service through Chatbot, an online chat system (Dhaoui, 2014; Godey et al., 2016; Ko, Phau, & Aiello, 2016). In this study, we analyze how e-service agents can affect communication quality and overall customer satisfaction for high-end SPA and luxury fashion brands that use Chatbot for e-service. The Chatbot concept goes well with luxury retail brand values of providing superior service for consumers who are willing to pay more (Retail Dive, 2017). Chatbot offers a new layer of support to the service quality dimension by assuring that personalized service is available to meet customer needs anytime and anywhere. In addition, Chatbot is designed to drive future luxury brand/consumer relationships. For example, Louis Vuitton offers a Chatbot service that provides information about global offline stores, access to personal service agents regarding product care, and conversational interfaces that show the craftsmanship behind the products (Forbes, 2017a, 2017b, 2017c). Our objectives are
Corresponding author. E-mail address: [email protected] (E. Ko).
https://doi.org/10.1016/j.jbusres.2018.10.004 Received 9 November 2017; Received in revised form 29 September 2018; Accepted 1 October 2018 0148-2963/ © 2018 Elsevier Inc. All rights reserved.
Please cite this article as: Chung, M., Journal of Business Research, https://doi.org/10.1016/j.jbusres.2018.10.004
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
to verify the effect of marketing efforts provided by Chatbot in the luxury retail context. We develop a measurement for examining how information accuracy, information credibility, and communication competence impact customer perceptions in the digital service context. The study provides insights into how e-service agents affect luxury consumer perceptions. In alignment with previous studies, we show that digital service assistance tools can allow positive brand/customer interactions. Luxury fashion retail brands are becoming more aware that they must interact with customers through the digital environment and are adopting Chatbot as a marketing strategy. Thus, it is essential to study Chatbot service in luxury contexts to determine effects on customer satisfaction.
quality and social network service (SNS) activities according to interaction, entertainment, customization, trendiness, innovativeness, and problem-solving dimensions (Kim & Ko, 2012; Kim, Park, Lee, & Choi, 2016; Ladhari, Souiden, & Dufour, 2017). In addition, social media marketing efforts have shown that interaction, entertainment, customization, trendiness, and word-of-mouth can enhance brand equity and increase customer response (Godey et al., 2016; Morra, Gelosa, Ceruti, & Mazzucchelli, 2018). However, research on e-service agents is relatively scant, especially regarding online communication with brands. We aim to fill the gap by examining interaction, entertainment, trendiness, customization, and problem-solving as marketing efforts in the context of e-service agents.
2. Literature review
2.2.1. Interaction Brand associates must be courteous, helpful, and trustworthy if interactions are to be positive (Dabholkar, Thorpe, & Rentz, 1996). Customers consult with salespersons to save time, get advice, feel valued, enjoy interactions, and ease purchasing procedures (Holzwarth et al., 2006). However, technology has enabled brands to use social media for casual interactions that build and strengthen customer relationships and provide information (Kim & Ko, 2010). As a result, customer interactions with virtual service agents are similar to their interactions with real-world human agents for influencing purchase decisions, saving time, gathering advice, or gaining parasocial benefits (Holzwarth et al., 2006).
2.1. E-service agents Service agents are key to solving customer problems (Chakrabarty, Widing, & Brown, 2014) and determining success or failure in evoking purchase behaviors through positive verbal and nonverbal interactions (Bailey & McCollough, 2000; Godes et al., 2005). Honest, friendly, authentic salesperson/customer relationships are essential for ensuring that both customers and service agents have positive experiences (Bailey & McCollough, 2000; Gautam & Sharma, 2017; Reynolds & Beatty, 1999). As companies become globalized in the new era of digital marketing and artificial intelligence, brands are moving to the online world to better connect with audiences, and service agent roles are changing (Bolton et al., 2013). As artificial intelligence improves and digital marketing becomes more essential, companies across diverse insurance, banking, retail, travel, healthcare, and education industries are successfully using robotic virtual characters that assist customers through desktop interfaces (Forbes, 2017a, 2017b, 2017c). Chatbot is an example of a virtual conversational service robot that can provide human–computer interaction (Lee, Oh, & Choi, 2017; Zhang, Liu, Wang, & Zhu, 2017). New technology tools allow companies to simultaneously meet customer expectations, fulfill company goals, and create value (Choi, Ko, & Kim, 2016; Woodside & Ko, 2013). E-service agents are consistently available personal assistants who help build crucial customer relationships, allow more efficient use of customer time, and provide better understandings regarding product performance (Lee & Choi, 2017; Mimoun, Poncin, & Garnier, 2017; Zhang et al., 2017). Moreover, as accuracy improves, users can enjoy intelligent social dialogues with virtual agents (Godey et al., 2016). Thus, fashion brands such as Burberry, Louis Vuitton, Tommy Hilfiger, Levi's, H&M, and eBay are recognizing the bright promise and increasing popularity of e-service agents (Lee & Choi, 2017). (Table 1). For all that the potential to advance related literature and practical use for marketing communication, there is limited research on e-service agents and thus we aim to contribute here by studying e-service agents.
2.2.2. Entertainment Successful companies know the importance of incorporating fun and entertainment into everyday workplace practices and services (Redman & Mathews, 2002). Entertainment is a hedonic way of introducing useful and valid information, increasing value perceptions and intentions to adopt digital tools such as the mobile Internet and social media (Muntinga, Moorman, & Smit, 2011; Nysveen, Pedersen, & Thorbjørnsen, 2005). For example, Burberry produced a video alluding to the Billy Elliot movie to incorporate visual information, increase customer interest, and connect customers with the brand. Consequently, enjoyment, fun, and relaxation determine whether customers will respond positively to virtual service agents (Godey et al., 2016; Muntinga et al., 2011). 2.2.3. Trendiness Many customers want current brand-and product-related information to ensure that products appropriately convey their trendy lifestyles (Muntinga et al., 2011; Zolkepli & Kamarulzaman, 2015). Many use social media to search for new products, to learn about current trends, and to see reviews (Godey et al., 2016). They seek the latest news and search hot discussions to find new products that suit their tastes. Although in-store salespersons were once the main sources of information about fashion trends, technology changes are allowing online and brickand-mortar experiences to work together (Forbes, 2017a, 2017b, 2017c).
2.2. Marketing efforts of e-service agents
2.2.4. Customization Customization is the process of modifying, personalizing, and tailoring products to satisfy individual preferences (Wang & Li, 2012). Customized service meets individual preferences, builds stronger brand affinity, and ensures loyalty (Godey et al., 2016; Perna, Runfola, Temperini, & Gregoni, 2018). Luxury brands particularly provide products and services targeting specific customer needs and wants, rather than trying to appeal to the general public. For instance, Gucci sends personalized online messages to introduce customized products to target customers (LinkedIn, 2012). Now, virtual agents can offer customized assistance through direct chats.
E-service agents can provide essential marketing efforts that influence decision-making processes (Crosby & Johnson, 2002; Gautam & Sharma, 2017). In customer–salesperson interactions, salespersons enhance customer trust by showing empathy and listening to customer concerns (Aggarwal, Castleberry, Ridnour, & Shepherd, 2005). Such marketing efforts are particularly important for fashion brands that must exchange information about tailored fashion trends or customized services (Forbes, 2017a, 2017b, 2017c). E-service agents can reduce the physical and temporal distance from fashion brands by giving customers easy access to product information (Darke, Brady, Benedicktus, & Wilson, 2016; Zhang & Dholakia, 2018). Digitalization studies of e-service agents have measured IT service
2.2.5. Problem-solving Because proper handling often determines perceptions of retail 2
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
Table 1 Chatbot usage by fashion brands. No.
Brand
Interaction & service
Brand characteristic
Agent characteristic
1
Salvatore Ferragamo Burberry
3
Louis Vuitton
- Although other customers enter, the employee assists only one customer at time. She politely asks other customers to wait until she can serve them. - Service in English. - In-store catalogue display. - When service is delayed, the employee asks customers to wait. She then removes her shoes and kneels to continue assisting customers. - A staff member was always near to help the customer - When the interaction concluded, employees provided cards with product and contact information.
Woman Thirties Qualified expert
2
4
Prada
- Good explanation of the material - Detailed product recommendation based on customer preferences - Demonstration of the brand's craftsmanship - Employees interact with customers eye-to-eye - Good explanation of the material - Recommendation based on the profile's preferences - Employees greet customers at the entrance - Employees have good knowledge about the brand - In-store demonstration of the brand's craftsmanship - Good knowledge about the brand and material - Recommendation based on the profile's preferences
- Although the website is available in Korea, brand purchases must be made in-store.
5
Gucci
- Provides fewer personalized services than other luxury stores. - Service in Chinese.
6
Tommy Hilfiger
- Good knowledge about the collection but failed to ask for the customer's preference. - Service in Chinese - No deep knowledge about the collection - No fluency in Korean or English
Woman Twenties, Qualified expert Woman Thirties, Qualified expert Woman Twenties, Non-expert Foreigner
- Store has a VR panel where customers can virtually try on clothes.
Woman Twenties, Non-expert Man Thirties Qualified expert
which then forms purchase intentions (Taylor & Baker, 1994; Wiedmann, Hennigs, & Siebels, 2009). In the case of online customers, satisfaction might be indicated by their choice to continue using particular websites without changing to other retailers.
service, retail brand associates are often trained to immediately and sincerely handle customer problems, complaints, returns, and exchanges (Dabholkar et al., 1996; Kim et al., 2016). Furthermore, customers who have unmet quality expectations can feel anger and even shame in reactions to feeling restrained (Izard, 1977).
3. Hypotheses development
2.3. Communication quality
3.1. Marketing efforts of e-service agents and communication quality
If customers are to perceive that they have experienced quality communication and to respond positively to the information transmitted (Maltz, 2000), the exchange must meet parameters important in human communication (Mohr & Sohi, 1995). We align our assumptions with studies of bot agents such as Twitter to assume that quality communication requires accuracy, credibility, and competence (Edwards, Edwards, Spence, & Shelton, 2014; Zhao & Rosson, 2009). Customers trust the reliability and completeness of communication when it is accurate (Barry & Crant, 2000; Mohr & Sohi, 1995). They perceive that information is credible and persuasive when they have good relationships with communicators (Edwards et al., 2014; Yuan, Kim, & Kim, 2016). That is, customers must perceive that computermediated communicators listen to their concerns, accurately diagnose their issues, and provide the needed information (Clokie & Fourie, 2016; Spitzberg, 2006; Zhao & Rosson, 2009). To ensure their unique market positions, luxury brands must form communication strategies that adhere to their core brand image (Liu, Li, Mizerski, & Soh, 2012). To evoke positive perceptions of intimacy, understanding, and communication quality, interactions must be smooth, accurate, and complete (Emmers-Sommer, 2004; Maltz, 2000; Mohr & Sohi, 1995). Consumers will positively appraise “the believability of a communicator” (O'Keefe, 1990, p. 130–131) if the information is delivered efficiently and appears to be competent, credible (Zhao & Rosson, 2009), and expert (Snavely & McNeill, 2008; Spitzberg, 2006; Webster & Sundaram, 2009). Thus, we examine accuracy, credibility, and communication competence as communication quality properties in the context of online interaction.
To provide accurate, credible, time-saving information and parasocial benefits (Holzwarth et al., 2006), service agents must provide rich, expert, intense, and efficient communication, using few words and symbols (Barry & Crant, 2000). Good service agent/customer communication focuses on customer needs for trendiness, customization, and problem-solving (Locker, 1995). Customer-oriented salespersons can adapt to customer needs and are thus most likely to establish positive customer relationships (Chakrabarty et al., 2014) that reduces uncertainty, allows efficient information search, and provides enjoyment (Haas & Kenning, 2014). Entertainment also encourages further intentions to use technology. That is, customers must derive enjoyment if they are to use virtual service agents and social media for obtaining brand-related information (Muntinga et al., 2011). Similar to service agents, e-service agents are essential for enhancing customer–brand relationships. Brand marketers use online communication to build positive customer relationships, increase profits, and inform customers about products and services (Kim & Ko, 2012). If consumers are to perceive quality communication, their online relationships with service agents must be smooth, satisfying, timely, effective, and accurate (Emmers-Sommer, 2004; Maltz, 2000; Mohr & Sohi, 1995; Vos, 2009). Luxury brands are finding that interactive marketing positively affects customer/brand relationships (Godey et al., 2016). One interactive method is through online social media to reinforce customer relationships (Ko et al., 2016), acquire information, transmit brand personality, and share opinions about new products. To help luxury brands understand which factors are essential for communicating with customers, we focus on luxury brands and posit that e-service agents can perform marketing efforts that are related to communication quality, which requires accuracy, credibility, and competence:
2.4. Satisfaction Customer satisfaction occurs when customers find that products or services meet or exceed their positive expectations (Chiou & Droge, 2006; Santini, Ladeira, & Sampaio, 2018). Luxury branded products particularly evoke expectations that products will perform as promised,
H1. E-service agents can provide marketing efforts that evoke communication accuracy. 3
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
H2. E-service agents can provide marketing efforts that evoke communication credibility.
outcomes.
H3. E-service agents can provide marketing efforts that evoke communication competence.
4.2. Measurement and procedure We gathered 29 items used in previous studies to measure marketing efforts according to interaction, entertainment, trendiness, customization, and problem-solving (Coelho & Henseler, 2012; Kim & Ko, 2012; Lee & Choi, 2017). These items were previously adopted to verify how brands affect customer relationships through virtual environments. To measure communication quality, we developed 14 items from McCroskey and Teven (1999), Mohr and Sohi (1995), and Spitzberg (2006). We measured overall satisfaction using previous constructs (Joosten, Bloemer, & Hillebrand, 2016; Lee & Choi, 2017). All items were measured on a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). We focused on how young consumers residing in South Korea perceive e-service agents for luxury brands. European luxury brands are enjoying increasing popularity among young Korean shoppers, growing as much as 60% in recent years (The Korea Herald, 2018). Luxury products are strong symbols of social status among Korean women. Moreover, customers from ages 20 to 30 seek imported high-end products in accordance with the latest trends (The Korea Bizwire, 2017), especially through online stores (The Korea Herald, 2018). We surveyed 161 Korean students from a large urban university in Korea. Participants were required to have previously interacted with online luxury brand agents, and to have ultimately purchased a luxury product. After we eliminated incomplete surveys, 157 questionnaires remained for analysis. Respondents were 20 to 30 years-old, averaged 29; most (68.8%) were women (n = 108). We designed the questionnaire to gather data about experiences with Chatbot services for the luxury brand Burberry, which actively offers Chatbot as a new service tool. Respondents viewed a screenshot of a conversation between a customer and Chatbot, the brand's service agent. They then answered questions about the Chatbot's marketing efforts, communication quality, and satisfaction.
3.2. Communication quality and satisfaction Customer satisfaction is more likely when salespersons convey trustworthy, relevant, current, and in-depth product information (Jian, Shi, & Dalisay, 2014; Setia, Venkatesh, & Joglekar, 2013), which reduces uncertainty (Adjei, Noble, & Noble, 2010; Hutter, Hautz, Dennhardt, & Füller, 2013; Mohr & Sohi, 1995), evokes positive attitudes toward service agents, motivates psychological connections and satisfaction, and makes consumers willing to purchase and repurchase premium-priced brands (Annie Jin, 2012; McAlexander, Schouten, & Koenig, 2002; Yuan et al., 2016). Twitterbots can be similar to human agents in providing credible communication and customer satisfaction, but they convey information through digital tools and computer-mediated communication (Edwards et al., 2014; Lowry et al., 2009). For example, fashion brands are using Chatbot e-service agents to interact with customers, provide timely answers to customer questions, and deliver wide and deep information to reduce uncertainty and provide customer satisfaction (Chen & Xie, 2008; Mimoun et al., 2017). But Chatbot agents in luxury brands, like human agents, must be accurate, credible, and competent. Thus: H4. Perceived satisfaction.
communication
accuracy
positively
influences
H5. Perceived satisfaction.
communication
credibility
positively
influences
H6. Perceived communication competence positively influences satisfaction. 4. Research method
5. Empirical results
4.1. Conceptual model
Exploratory and confirmatory factor analyses were used to empirically validate the scale. Composite reliability (CR) coefficient and the average variance extracted (AVE) were used to test scale reliability (Table 2). Validity was based on the AVE values. Measures appeared to
Fig. 1 shows the conceptual model designed for this study. In-store communication measurements were applied to the online context to identify how e-service agents' marketing efforts affect communication
Fig. 1. Conceptual model. 4
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
Table 2 Standardized CFA loadings. Items
Standardized regression weight
Cronbach's α
Interaction: composite reliability = 0.828; average variance extracted = 0.548 The service agent has the knowledge to answer customers' questions. The service agent is never too busy to answer customers' requests. The service agent gives customers individual attention. The service agent is consistently courteous with customers.
0.792 0.873 0.743 0.744
0.867
Entertainment: composite reliability = 0.832; average variance extracted = 0.554 It is fun and enjoyable to share a conversation with the service agent. I was absorbed in the conversation with the service agent. The conversation with the service agent was exciting. I enjoy choosing products more if they are recommended by the service agent than if I choose them myself.
0.808 0.756 0.795 0.814
0.872
Trendiness: composite reliability = 0.0847; average variance extracted = 0.582 The service agent gives the newest information. Using the brand's service agent is very trendy. The service agent provides up-to-date contents. It is fashionable to use the brand's service agent.
0.873 0.788 0.869 0.790
0.897
Customization: composite reliability = 0.817; average variance extracted = 0.529 The brand offers products and services that I couldn't find in another company. If I changed companies, the products and services would not be as customized as I have now. I feel that using this Chatbot and transacting with this service agent meets my personal needs. The service agent provides information about products according to my preferences.
0.763 0.824 0.713 0.773
0.850
Problem solving: composite reliability = 0.814; average variance extracted = 0.525 The service agent willingly handles returns and exchanges. When a customer has a problem, the service agent shows a sincere interest in solving it. The conversational agent is able to handle customer complaints directly and immediately. I have confidence that the service agent has the ability to get the job done.
0.786 0.724 0.602 0.698
0.793
Accuracy: composite reliability = 0.917; average variance extracted = 0.687 The communication with the service agent is timely. The communication with the service agent is accurate. The communication with the service agent is adequate. The communication with the service agent is complete. The communication with the service agent is credible.
0.897 0.909 0.882 0.882 0.884
0.95
Credibility: composite reliability = 0.835; average variance extracted = 0.560 The conversational agent is honest. The conversational agent is trustworthy. The conversational agent is honorable. The conversational agent is moral.
0.778 0.680 0.814 0.823
0.859
Communication competence: composite reliability = 0.734; average variance extracted = 0.367 My interactions with the service agent are more productive than face-to-face interactions with in-store agents. Using service agents is more efficient than other forms of communication. Service agents save a tremendous amount of time.
0.633 0.659 0.565
0.758
Satisfaction: composite reliability = 0.858; average variance extracted = 0.503 I am satisfied with the service agent. I am content with the service agent. The service agent did a good job. The service agent did what I expected. I am happy with the service agent. I was satisfied with the experience of talking with the service agent.
0.736 0.754 0.733 0.747 0.720 0.805
0.884
χ2 = 776.559, df = 629 (χ2/df = 1.235, p = .000), IFI = 0.967, TLI = 0.963, CFI = 0.967, RMSEA = 0.039.
Table 3 Results for correlation matrix.
Interaction (IN) Entertainment (EN) Trendiness (TR) Customization (CU) Problem solving (PS) Accuracy (AC) Credibility (CR) Communication competence (CC) Satisfaction (SA) Mean S.D. a b
IN
EN
TR
CU
PS
AC
CR
0.624a 0.716b 0.637 0.591 0.565 0.348 0.764
0.630a 0.643 0.632 0.687 0.351 0.742
0.691a 0.674 0.509 0.354 0.757
0.592a 0.600 0.344 0.767
0.498a 0.325 0.734
0.794a 0.250
0.602a
0.119 0.616 3.10 1.00
0.071 0.515 3.19 1.00
0.115 0.639 3.36 1.13
0.079 0.647 3.12 0.95
0.171 0.776 2.70 0.76
0.323 0.365 2.91 1.36
0.271 0.788 3.08 0.90
AVE (Average Variance Extracted). Correlation between variables. 5
CC
SA
0.385a 0.155 2.30 0.80
0.562a 3.09 0.90
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
communicate with customers. Our study results can be a guideline for fashion brands to ensure appropriate marketing efforts through e-services. Luxury customers expect exclusive experiences. Although offline brand performance is essential, digital contexts can enhance company–customer connections, customer satisfaction, and shopping experiences. To strengthen online communications, fashion brands are advised to provide accurate and reliable information to ensure positive marketing efforts.
be reliable: the reliability coefficient for service agents' marketing efforts was 0.87 for interaction, 0.87 for entertainment, 0.90 for trendiness, 0.85 for customization, and 0.80 for problem-solving. Cronbach's alpha values exceeded 0.7. The average variance extracted exceeded 0.5, confirming validity for all cases except communication competence. Reliability coefficients were: accuracy = 0.95, credibility = 0.86, communication competence = 0.76, satisfaction = 0.88. Table 2 shows the results of confirmatory factor analysis, AVE, and CR. Correlation analysis was then conducted to observe correlations between variables used in further analysis (Table 3). To test the hypotheses, we used structural equation modeling (SEM). The overall fit indices showed an acceptable fit to the data (χ2 = 349.376, df = 224, χ2/df = 1.560) at a significant level (p = .000), and fit indices within accepted standards (IFI = 0.958, TLI = 0.952, CFI = 0.957, RMSEA = 0.060). The path coefficients revealed that marketing efforts positively impacted accuracy (β = 0.374, p < .001) and credibility (β = 0.964, p < .001), but not competence (β = 0.174, n.s.). Accuracy (β = 0.860, p < .05) and credibility (β = 0.938, p < .001) positively affected satisfaction. Competence had no impact on satisfaction. Marketing efforts failed to significantly affect communication competence and thus failed to bring satisfaction. Participants might have perceived that Chatbot service is more competent than offline service. Although they perceived that Chatbot failed to provide diversity of information, efficiency, and time-saving, they perceived accuracy and credibility. Consider that luxury brand customers tend to devote much time and careful consideration to their purchases. Thus the luxury context may cause customers to perceive that saving time minimizes their effort. Fig. 2 is an illustration of the relationship between variables of the research model.
6.1. Implications This study has several theoretical implications. First, the study is one of the earliest to examine digital contexts to show that online service agents provide convenience and quality communication that positively affect customer perceptions of marketing efforts. Despite the rich prior research on service agents, our work on e-service agents is relatively seminal and establishes a basis for further development in associated theories. Second, our empirical approach demonstrates that e-service agent performance can be measured according to interaction, entertainment, trendiness, customization, and problem-solving components of marketing in the digital context. Future research on customer relationships in virtual environments can further develop our findings showing that e-service agent performance enhances communication. Last, the vast, complex, highly competitive luxury brand industry faces shifting consumption patterns. Brands are keeping pace with new opportunities by providing e-service agents, but empirical research has rarely examined whether they provide quality communication. Nevertheless, customers have increasingly positive perceptions and intentions to interact with Twitterbots, perceiving them as competent, time-saving information-gathering tools (Edwards et al., 2014). By showing that e-service agents provide quality communication that positively impacts customer satisfaction, our study enriches the luxury fashion literature. The findings have managerial implications particularly for the luxury retail segment. First, we focused on consumers 20 to 30 yearsold residing in South Korea, a strong segment of luxury consumers, to capture their perceptions of e-service agent services. Our findings show that luxury fashion brands can use Chatbot to develop digital customer
6. Conclusion Technology now allows artificial intelligence to provide marketing efforts through e-service agents, with effects on customer perceptions of communication quality and brand satisfaction. In this study, we show that customer satisfaction with luxury retail brand e-service agents requires perceptions of having received quality communication. We show how digital service assistance tools can help build positive customer relationships even though e-service agents do not fully
Fig. 2. Results for Structural Equation Modeling (SEM). Model Fit: χ2 = 349.376, df = 224 (χ2/df = 1.560, p = .000), IFI = 0.958, TLI = 0.952, CFI = 0.957, RMSEA = 0.060 Note: The path coefficients are standardized path coefficients, ***p < .001, **p < .01, *p < .05. 6
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al.
assistance tools that increase customer engagement, provide unrestricted availability, offer highly customizable flexibility, and give simple and natural customer experiences. Chatbots can work with other digital tools such as applications to smooth customer communications with luxury brands. Moreover, our results can be applied to other fashion brands such as SPA or Masstige who wish to maintain positive relationships with core customers through e-service agents. Furthermore, fashion brands can use online communication history to derive inspiration for future customized products. Second, customer–service agent communication precedes trust. Our findings indicate that luxury brand marketers should ensure that oneto-one interactions are accurate and credible so that customers will perceive optimized personal service and rapid response. In addition to carefully training employees to be credible brand ambassadors, luxury brands are advised to consider the five quality dimensions—interaction, entertainment, trendiness, customization, and problem-solving—when building programs for e-service agents. Third, e-service agent technology is currently limited in communication subtleties. As part of the luxury experience, luxury brand customers might desire to interact with actual service agents. We recommend that fashion brands offer e-service agents for convenience, while offering offline service agents for richer brand/customer interactions and customer equity.
6.2. Limitations for future research This study has some limitations to be addressed. The stimuli were developed to simulate real experiences with luxury retail brands (Appendix A): participants viewed screenshots of a manipulated Chatbot template used by the luxury brand Burberry. A live feed for participant interaction might have increased study validity. Future studies should further examine perceptions of other interactional Chatbot feeds. Additionally, study participants were 20 to 30 years-old, an age group that tends to have the most interest in technology (Smartinsights, 2017). All participants had previously worked with service agents before purchasing luxury products. Future studies should evaluate whether outcomes differ among age groups that are unfamiliar with Chatbot. Acknowledgements This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (MOE) (NRF2017S1A2A2041810).
Appendix A. Stimuli development for luxury brand chatbot service
Journal of Brand Management, 16(5–6), 338–346. Bailey, J. J., & McCollough, M. A. (2000). Emotional labor and the difficult customer: Coping strategies of service agents and organizational consequences. Journal of Professional Services Marketing, 20(2), 51–72. Balmer, J. M., & Greyser, S. A. (2006). Corporate marketing: Integrating corporate identity, corporate branding, corporate communications, corporate image and corporate reputation. European Journal of Marketing, 40(7/8), 730–741. Barry, B., & Crant, J. M. (2000). Dyadic communication relationships in organizations: An attribution/expectancy approach. Organization Science, 11(6), 648–664. Bolton, R. N., Parasuraman, A., Hoefnagels, A., Migchels, N., Kabadayi, S., Gruber, T., ... Solnet, D. (2013). Understanding generation Y and their use of social media: A review and research agenda. Journal of Service Management, 24(3), 245–267.
References Adjei, M. T., Noble, S. M., & Noble, C. H. (2010). The influence of C2C communications in online brand communities on customer purchase behavior. Journal of the Academy of Marketing Science, 38(5), 634–653. Aggarwal, P., Castleberry, S. B., Ridnour, R., & Shepherd, C. D. (2005). Salesperson empathy and listening: Impact on relationship outcomes. Journal of Marketing Theory and Practice, 13(3), 16–31. Annie Jin, S. A. (2012). The potential of social media for luxury brand management. Marketing Intelligence & Planning, 30(7), 687–699. Atwal, G., & Williams, A. (2009). Luxury brand marketing–The experience is everything!.
7
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al. Calantone, R. J., Di Benedetto, A., & Rubera, G. (2018). Launch activities and timing in new product development. Journal of Global Scholars of Marketing Science, 28(1), 33–41. Chakrabarty, S., Widing, R. E., & Brown, G. (2014). Selling behaviours and sales performance: The moderating and mediating effects of interpersonal mentalizing. Journal of Personal Selling & Sales Management, 34(2), 112–122. Chen, Y., & Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix. Management Science, 54(3), 477–491. Chiou, J. S., & Droge, C. (2006). Service quality, trust, specific asset investment, and expertise: Direct and indirect effects in a satisfaction-loyalty framework. Journal of the Academy of Marketing Science, 34(4), 613–627. Choi, E., Ko, E., & Kim, A. J. (2016). Explaining and predicting purchase intentions following luxury-fashion brand value co-creation encounters. Journal of Business Research, 69(12), 5827–5832. Clokie, T. L., & Fourie, E. (2016). Graduate employability and communication competence: Are undergraduates taught relevant skills? Business and Professional Communication Quarterly, 79(4), 442–463. Coelho, P. S., & Henseler, J. (2012). Creating customer loyalty through service customization. European Journal of Marketing, 46(3/4), 331–356. Correa, T., Hinsley, A. W., & De Zuniga, H. G. (2010). Who interacts on the Web? The intersection of users' personality and social media use. Computers in Human Behavior, 26(2), 247–253. Crosby, L. A., & Johnson, S. L. (2002). Going my way? Marketing Management, 11(4), 10–11. Dabholkar, P. A., Thorpe, D. I., & Rentz, J. O. (1996). A measure of service quality for retail stores: Scale development and validation. Journal of the Academy of Marketing Science, 24(1), 3. Darke, P. R., Brady, M. K., Benedicktus, R. L., & Wilson, A. E. (2016). Feeling close from afar: The role of psychological distance in offsetting distrust in unfamiliar online retailers. Journal of Retailing, 92(3), 287–299. Dhaoui, C. (2014). An empirical study of luxury brand marketing effectiveness and its impact on consumer engagement on Facebook. Journal of Global Fashion Marketing, 5(3), 209–222. Edwards, C., Edwards, A., Spence, P. R., & Shelton, A. K. (2014). Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter. Computers in Human Behavior, 33, 372–376. Emmers-Sommer, T. M. (2004). The effect of communication quality and quantity indicators on intimacy and relational satisfaction. Journal of Social and Personal Relationships, 21(3), 399–411. Escobar, A. (2016). The impact of the digital revolution in the development of market and communication strategies for the luxury sector (fashion luxury). Central European Business Review, 5(2), 17. Fionda, A. M., & Moore, C. M. (2009). The anatomy of the luxury fashion brand. Journal of Brand Management, 16(5–6), 347–363. Forbes (2017a). How Chatbots improve customer experience in every industry: An infograph. https://www.forbes.com/sites/blakemorgan/2017/06/08/how-chatbotsimprove-customer-experience-in-every-industry-an-infograph/#2162528867df/, Accessed date: 15 July 2017. Forbes (2017b). How luxury brands are adapting to an omnichannel world. https://www. forbes.com/sites/forbescommunicationscouncil/2017/06/02/how-luxury-brandsare-adapting-to-an-omnichannel-world/#6b3dadb81958/, Accessed date: 15 July 2017. Forbes (2017c). Louis Vuitton becomes latest luxury brand to launch a Chatbot. https:// www.forbes.com/sites/rachelarthur/2017/12/08/louis-vuitton-becomes-latestluxury-brand-to-launch-a-chatbot/#46b9941afe10/, Accessed date: 30 December 2017. Gautam, V., & Sharma, V. (2017). The mediating role of customer relationship on the social media marketing and purchase intention relationship with special reference to luxury fashion brands. Journal of Promotion Management, 1–17. Godes, D., Mayzlin, D., Chen, Y., Das, S., Dellarocas, C., Pfeiffer, B., ... Verlegh, P. (2005). The firm's management of social interactions. Marketing Letters, 16(3–4), 415–428. Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research, 69(12), 5833–5841. Haas, A., & Kenning, P. (2014). Utilitarian and hedonic motivators of shoppers' decision to consult with salespeople. Journal of Retailing, 90(3), 428–441. Hagberg, J., Sundstrom, M., & Egels-Zandén, N. (2016). The digitalization of retailing: An exploratory framework. International Journal of Retail & Distribution Management, 44(7), 694–712. Holzwarth, M., Janiszewski, C., & Neumann, M. M. (2006). The influence of avatars on online consumer shopping behavior. Journal of Marketing, 70(4), 19–36. Hutter, K., Hautz, J., Dennhardt, S., & Füller, J. (2013). The impact of user interactions in social media on brand awareness and purchase intention: The case of MINI on Facebook. The Journal of Product and Brand Management, 22(5/6), 342–351. Insider-Trends (2017). Retail trends factfile 2017: Physical retail. http://www.insidertrends.com/retail-trends-factfile-2017-physical-retail/, Accessed date: 30 December 2017. Izard, C. E. (1977). Human emotions. New York, NY: Plenum Press. Jian, G., Shi, X., & Dalisay, F. (2014). Leader–member conversational quality: Scale development and validation through three studies. Management Communication Quarterly, 28(3), 375–403. Joosten, H., Bloemer, J., & Hillebrand, B. (2016). Is more customer control of services always better? Journal of Service Management, 27(2), 218–246. Kang, G. D. (2006). The hierarchical structure of service quality: Integration of technical and functional quality. Managing Service Quality: An International Journal, 16(1),
37–50. Kim, A. J., & Ko, E. (2010). Impacts of luxury fashion brand's social media marketing on customer relationship and purchase intention. Journal of Global Fashion Marketing, 1(3), 164–171. Kim, A. J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research, 65(10), 1480–1486. Kim, J., Kang, S., & Taylor, C. R. (2018). Technology driven experiences from mobile direct to virtual reality. Journal of Global Scholars of Marketing Science, 28(1), 96–102. Kim, S., Park, G., Lee, Y., & Choi, S. (2016). Customer emotions and their triggers in luxury retail: Understanding the effects of customer emotions before and after entering a luxury shop. Journal of Business Research, 69(12), 5809–5818. Ko, E., Phau, I., & Aiello, G. (2016). Luxury brand strategies and customer experiences: Contributions to theory and practice. Journal of Business Research, 69(12), 5749–5752. Ladhari, R., Souiden, N., & Dufour, B. (2017). The role of emotions in utilitarian service settings: The effects of emotional satisfaction on product perception and behavioral intentions. Journal of Retailing and Consumer Services, 34, 10–18. Lee, D., Oh, K. J., & Choi, H. J. (2017, February). The Chatbot feels you: A counseling service using emotional response generation. Big data and smart computing (BigComp), 2017 IEEE International Conference on (pp. 437–440). IEEE. Lee, S., & Choi, J. (2017). Enhancing user experience with conversational agent for movie recommendation: Effects of self-disclosure and reciprocity. International Journal of Human-Computer Studies, 103, 95–105. LinkedIn (2012). Gucci – Social media marketing strategies using internet and social networking sites. http://www.slideshare.net/AngelKritiSangar/gucci-socialmediamarketing-strategies-using-internet-social-networking-sites/, Accessed date: 30 December 2017. Liu, F., Li, J., Mizerski, D., & Soh, H. (2012). Self-congruity, brand attitude, and brand loyalty: A study on luxury brands. European Journal of Marketing, 46(7/8), 922–937. Locker, K. O. (1995). Business and administrative communication (3rd ed.). Chicago: Irwin. Lowry, P. B., Romano, N. C., Jenkins, J. L., & Guthrie, R. W. (2009). The CMC interactivity model: How interactivity enhances communication quality and process satisfaction in lean-media groups. Journal of Management Information Systems, 26(1), 155–196. Maltz, E. (2000). Is all communication created equal? An investigation into the effects of communication mode on perceived information quality. Journal of Product Innovation Management, 17(2), 110–127. McAlexander, J. H., Schouten, J. W., & Koenig, H. F. (2002). Building brand community. Journal of Marketing, 66(1), 38–54. McCroskey, J. C., & Teven, J. J. (1999). Goodwill: A reexamination of the construct and its measurement. Communication Monographs, 66(1), 90–103. Mimoun, M. S. B., Poncin, I., & Garnier, M. (2017). Animated conversational agents and econsumer productivity: The roles of agents and individual characteristics. Information & Management, 54(5), 545–559. Mohr, J. J., & Sohi, R. S. (1995). Communication flows in distribution channels: Impact on assessments of communication quality and satisfaction. Journal of Retailing, 71(4), 393–415. Morra, M. C., Gelosa, V., Ceruti, F., & Mazzucchelli, A. (2018). Original or counterfeit luxury fashion brands? The effect of social media on purchase intention. Journal of Global Fashion Marketing, 9(1), 24–39. Muntinga, D. G., Moorman, M., & Smit, E. G. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30(1), 13–46. Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. (2005). Intentions to use mobile services: Antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, 33(3), 330–346. O'Keefe, D. J. (1990). Persuasion: Theory and research. Newbury Park, CA: Sage. Perna, A., Runfola, A., Temperini, V., & Gregori, G. L. (2018). Problematizing customization and IT in the fashion industry: A case study of an Italian shoemaker. Journal of Global Fashion Marketing, 9(1), 73–86. Perrey, J., & Spillecke, D. (2011). Retail marketing and branding: A definitive guide to maximizing ROI. Wiley (Part2, Chapter 9). Redman, T., & Mathews, B. P. (2002). Managing services: Should we be having fun? Service Industries Journal, 22(3), 51–62. Retail Dive (2017). Louis Vuitton joins luxury brand chatbot trend. https://www. retaildive.com/news/louis-vuitton-joins-luxury-brand-chatbot-trend/512680/, Accessed date: 30 December 2017. Reynolds, K. E., & Beatty, S. E. (1999). Customer benefits and company consequences of customer-salesperson relationships in retailing. Journal of Retailing, 75(1), 11–32. Santini, F. D. O., Ladeira, W. J., & Sampaio, C. H. (2018). The role of satisfaction in fashion marketing: a meta-analysis. Journal of Global Fashion Marketing, 9(4), 1–17. Setia, P., Venkatesh, V., & Joglekar, S. (2013). Leveraging digital technologies: How information quality leads to localized capabilities and customer service performance. MIS Quarterly, 37(2), 565–590. Smartinsights (2017). Global social media research summary. http://www.smartinsights. com/social-media-marketing/social-media-strategy/new-global-social-mediaresearch/, Accessed date: 30 December 2017. Snavely, W. B., & McNeill, J. D. (2008). Communicator style and social style: Testing a theoretical interface. Journal of Leadership and Organizational Studies, 14(3), 219–232. Spitzberg, B. H. (2006). Preliminary development of a model and measure of computermediated communication (CMC) competence. Journal of Computer-Mediated Communication, 11(2), 629–666. Taylor, S. A., & Baker, T. L. (1994). An assessment of the relationship between service quality and customer satisfaction in the formation of consumers' purchase intentions. Journal of Retailing, 70(2), 163–178.
8
Journal of Business Research xxx (xxxx) xxx–xxx
M. Chung et al. The Korea Bizwire (2017). Overseas luxury brands booming with Young South Korean consumers. http://koreabizwire.com/overseas-luxury-brands-booming-with-youngsouth-korean-consumers/83334/, Accessed date: 30 December 2017. The Korea Herald (2018). Luxury European brands extend reach to Korean shoppers. http://www.koreaherald.com/view.php?ud=20180201000941/, Accessed date: 30 January 2018. Vos, M. (2009). Communication quality and added value: A measurement instrument for municipalities. Journal of Communication Management, 13(4), 362–377. Wang, W. T., & Li, H. M. (2012). Factors influencing mobile services adoption: A brandequity perspective. Internet Research, 22(2), 142–179. Webster, C., & Sundaram, D. S. (2009). Effect of service provider's communication style on customer satisfaction in professional services setting: The moderating role of criticality and service nature. Journal of Services Marketing, 23(2), 103–113. Wiedmann, K. P., Hennigs, N., & Siebels, A. (2009). Value-based segmentation of luxury
consumption behavior. Psychology and Marketing, 26(7), 625–651. Woodside, A. G., & Ko, E. (2013). Luxury fashion and culture (7th ed.). Emerald Group Publishing (Chapter 1). Yuan, C. L., Kim, J., & Kim, S. J. (2016). Parasocial relationship effects on customer equity in the social media context. Journal of Business Research, 69(9), 3795–3803. Zhang, M., & Dholakia, N. (2018). Conceptual framing of virtuality and virtual consumption research. Journal of Global Scholars of Marketing Science, 28(4), 305–319. Zhang, W., Liu, T., Wang, Y., & Zhu, Q. (2017). Neural personalized response generation as domain adaptation. (arXiv preprint arXiv:1701.02073). Zhao, D., & Rosson, M. B. (2009). How and why people Twitter: the role that microblogging plays in informal communication at work. In May (Ed.). Proceedings of the ACM 2009 international conference on supporting group work (pp. 243–252). ACM. Zolkepli, I. A., & Kamarulzaman, Y. (2015). Social media adoption: The role of media needs and innovation characteristics. Computers in Human Behavior, 43, 189–209.
9