Examining satisfaction with the experience during a live chat service encounter-implications for website providers

A Theory-Driven Deep Learning Method for Voice Chat–Based Customer Response Prediction

A Theory-Driven Deep Learning Method for Voice Chat–Based Customer Response Prediction

In this study, we target the task of voice chat–based customer response prediction in an emerging online interaction–based commercial mode, the invite-online-and-experience-in-store mode. Prior research shows that satisfaction, which can be revealed by the discrepancy between prior expectation and actual experience, is a key factor to disentangle customers’ purchase intention, whereas black box deep learning methods empirically promise us with advantageous capabilities in dealing with complex voice data, for example, text and audio information incorporated in voice chat. To this end, we propose a theory-driven deep learning method that enables us to (1) learn customers’ personalized product preferences and dynamic satisfaction in the absence of their profile information, (2) model customers’ actual experiences based on multiview voice chat information in an interlaced way, and (3) enhance the customer response prediction performance of a black box deep learning model with theory-driven dynamic satisfaction. Empirical evaluation results demonstrate the advantageous prediction performance of our proposed method over state-of-the-art deep learning alternatives. Investigation of cumulative satisfaction reveals the collaborative predictive roles of theory-driven dynamic satisfaction and deep representation features for customer response prediction. Explanatory analysis further renders insights into customers’ personalized preferences and dynamic satisfaction for key product attributes.

Investigating the relationships between dialog patterns and user satisfaction in customer service chat systems based on chat log analysis

While previous studies of customer service chat systems (CSCS) understood user satisfaction as individuals’ subjective perceptions and depended heavily on self-report methods for satisfaction measurement, this article presents an obtrusive chat log analysis that followed the established approaches of search log analysis and examined the relationships between dialog patterns and user satisfaction. An 81-day chat log was obtained from a real-world CSCS that involves both a chatbot and human representatives. A total of 75,918 chat sessions/147,972 sub-sessions containing 251,556 user messages and 349,416 system messages were extracted after data processing and analysed in terms of topic, length and path. As found in this study, the users were more likely to get satisfied on low-difficulty topics. The dialog between the CSCS and users was shallow in general. While human representatives’ elaboration contributed to user satisfaction, the chatbot was responsible for damaging user satisfaction. The significance of this study consists not only in providing objective evidence about user satisfaction in online chat but also in generating practical implications for the CSCS to improve user satisfaction.

Understanding customer satisfaction of augmented reality in retail: a human value orientation and consumption value perspective

Purpose

While customer perceived augmented reality (AR) values have generally enhanced customer experience, AR value would be appreciated the most by a consumer segment that remains unexplored. Drawing from human value orientation theory and consumption value theory, this research proposes a new model analysing the effects of human value orientation (openness to change, conservation, self-transcendence, and self-enhancement) on perceived AR values (playful, social, visual appeal, usability) and subsequently the effects on customer satisfaction.

Design/methodology/approach

:The authors employed a two-step online data collection. The first step was to identify those who had used retailers' AR applications, who were then invited to participate in the full survey in the second step. A sample of 253 AR technology users' data was analysed using partial least square and structural equation modelling.

Findings

The results reveal that each human value orientation is associated with its unique perceived AR values and that various perceived AR values influence customer satisfaction differently.

Originality/value

This study shows the pivotal role human value orientation plays in influencing customer perceived AR values and their impacts on customer satisfaction. The findings offer key implications for digital marketing segmentation.

Examining emotions linked to live chat services: The role of e-service quality and impact on word of mouth

The purpose of this article is twofold: (1) to investigate the emotions experienced by banking customers when using live chat services and their impact on positive word-of-mouth intentions; and, (2) to identify which dimensions of e-service quality (accessibility, customer service and support, perceived security/privacy and design) impact these emotions. A survey was conducted with 682 members of a Web-based panel. Findings demonstrate that emotions, both positive and negative, significantly impact word of mouth. Results further reveal that customer service and support followed by design of live chat services mostly influence consumer emotions. On a practical level, the recommendations provided will improve consumer experience and encourage consumers to use live chat services. This is all the more important since such services are now part of the promotion and contribution of a sustainable mode of consumption that is accessible to all.

WeChat mobile-payment-based smart retail customer experience: an integrated framework

The purpose of this paper is to explore the role of WeChat mobile-payment (m-payment)-based smart technologies in improving the retail customer experience and to develop an integrated framework of the smart retail customer experience including antecedents, consequences, and moderators. Based on the stimulus-organism-response (SOR) paradigm, we investigated the relationships among socio-technical stimuli, the smart retail customer experience, and relationship quality. We also developed hypotheses regarding the moderating role of customer lifetime value (CLV), which is considered an important customer characteristic. The proposed framework was empirically tested based on transaction and survey data of 462 WeChat m-payment retail customers. The results showed the following. (1) WeChat m-payment-based smart retail technology can enhance the customer experience by improving customer-perceived relationship orientation, employee-customer interaction, and communication effectiveness. (2) CLV has a positive moderating effect on the relationship between socio-technical stimuli and the customer experience. (3) The customer experience has a positive influence on relationship quality in the retail industry. Retail managers should make full use of smart retail technologies to improve the customer experience. In addition, they should emphasize the increase in CLV, as this increase enhances the positive relationship between socio-technical stimuli and the customer experience, making customer experience management more efficient.

Determinants of Continuance Intention towards Banks’ Chatbot Services in Vietnam: A Necessity for Sustainable Development

To improve customer experience and achieve sustainable development, many industries, especially banking, have leveraged artificial intelligence to implement a chatbot into their customer service. By integrating DeLone and McLean’s information systems success (D&M ISS) model and the expectation confirmation model (ECM) with the factor of trust, the aim of this study was to investigate the determinants of users’ continuance intentions towards chatbot services in the context of banking in Vietnam. A total of 359 questionnaire surveys were collected from a real bank’s chatbot users and analyzed using structural equation modeling. The findings revealed that users’ continuance intentions towards the banks’ chatbot services were influenced by satisfaction, trust, and perceived usefulness, of which trust had the strongest effect. The results also indicate that information quality, system quality, service quality, and confirmation of expectations had significant effects on three drivers of continuance intention in different ways. Our study contributes to the literature by providing a more comprehensive viewpoint to understand the perceptions and reactions of chatbot users in the post-adoption stage. The results of this study also yield several key suggestions for banking service providers on how to increase their customers’ intentions to continue using chatbot services, serving as a basis for long-term and sustainable development strategies in the current digital era.

Social media brand engagement practices

Purpose

The purpose of this paper is to deepen the understanding on social media brand engagement (SMBE) practices by exploring the impact of consumer brand knowledge, perceived social pressure, perceived social relatedness (PSR) and the role of brand trust.

Design/methodology/approach

A model is proposed to suggest the influence of consumer-level antecedents and moderators of SMBE. Following a survey design approach, data collected from 687 respondents on Facebook are examined through structural equation modelling using AMOS 23.0.

Findings

The findings reveal significant relationship between the examined antecedents (brand knowledge, perceived social pressure and brand trust) and SMBE. Examination of the moderation role of PSR revealed significant interaction effects on the relationship between brand knowledge and SMBE, as well as perceived social pressure and SMBE. The findings also suggest a lack of interaction effect of PSR on the relationship between brand trust and SMBE.

Research limitations/implications

This research provides empirical evidence in support of understanding SMBE practices by testing theoretically grounded hypotheses. The study focussed on technologically savvy respondents and only Facebook users in Ghana, which could limit the generalisation of the findings reported.

Practical implications

This study illustrates a need for managers to integrate multi-communication channels to enhance brand interactions and engagements. Firms must also adopt strategies that would enhance the sharing of interesting information about their brands on their social media platforms to attract others through customer networks.

Originality/value

The conceptualization of SMBE in this study zooms out our understanding of online SMBE by examining pertinent variables that drive or moderate consumer participation in SMBE activities. The integration of these variables brings out new empirical understanding and extends our knowledge on SMBE.