Are AI chatbots a cure-all? The relative effectiveness of chatbot ambidexterity in crafting hedonic and cognitive smart experiences

Fan, Hua; Gao, Wei; Han, Bing

doi:10.1016/j.jbusres.2022.113526

Cited by 17 publications

(9 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Furthermore, providing accurate responses (Q14) is supported by evidence in Nicolescu and Tudorache (2022), Haseeb et al (2019), Kwangsawad and Jattamart, (2022). The ease of understanding the chatbot (Q15) is consistent with outcomes reported in Jenneboer et al (2022), Um and Chung (2020), Rese et al (2020), Fan et al (2023). Additionally, receiving positive recommendations from customers (Q20) aligns with the conclusions drawn in Jenneboer et al (2022), Jiang et al (2022).…”

Section: Discussionmentioning

confidence: 54%

“…Previous research has examined the effectiveness of chatbots in customer service across a variety of industries, including retail (Jones and Comfort, 2022;Rese et al, 2020;Tran et al, 2021;Kwangsawad and Jattamart, 2022;Jiang et al, 2022;Tan and Liew, 2022;Fan et al, 2023), healthcare (Mierzwa et al, 2019;Bates, 2019;Vaidyam et al, 2019;Abd-Alrazaq et al, 2020;Almalki and Azeez, 2020;Calvaresi et al, 2021;Rathnayaka et al, 2022;Puspitasari et al, 2022), tourism (Pillai and Sivathanu, 2020;Ivanov, 2020;Zhang et al, 2020;Rafiq et al, 2022;Pereira et al, 2022;Jones and Comfort, 2022) and finance (Adhim and Mulyono, 2023;Hwang and Kim, 2021;OECD, 2021;Alt et al, 2021;Nguyen et al, 2021;Jang et al, 2021;Lappeman et al, 2022). Ho and Chow (2023) measures the effectiveness of AI-Enabled chatbots in Customer Service using AnyLogic Simulation, through scenario analysis provides managerial implications for the average time in the system, response rate, satisfaction level, and cost savings, helping the companies to understand the impact of adopting AI-enabled chatbots in their customer service.…”

Section: Previous Research On the Effectiveness Of Chatbots In Custom...mentioning

confidence: 99%

See 1 more Smart Citation

Are Chatbots the Key to Success in Customer Service for Logistics Companies? A Statistical Study of 10 of the Most Important Companies in South America

De Santis

2024

OSCM: An Int. Journal

View full text Add to dashboard Cite

This article aims to investigate the effectiveness of chatbots in improving customer service for logistics companies, focusing on ten of the most important companies in South America. Data was collected from 1250 chatbot users across these companies and analyzed to determine the relationship between chatbot usage and customer satisfaction. The results indicate that chatbots can effectively improve customer service in the logistics industry, with a significant positive correlation between chatbot usage and customer satisfaction. The study employed multiple regression analysis to identify the most important factors influencing customer satisfaction with chatbots, including the chatbot's capacity to address customer concerns, its familiarity with the company's products and services, its capability to manage issues without requiring human intervention, its usage of correct grammar in its responses, and its general reputation for customer satisfaction. The results of this study have important implications for the logistics industry, as they provide insight into the potential benefits of chatbot technology for enhancing customer service.

show abstract

Section: Discussionmentioning

confidence: 54%

Section: Previous Research On the Effectiveness Of Chatbots In Custom...mentioning

confidence: 99%

Are Chatbots the Key to Success in Customer Service for Logistics Companies? A Statistical Study of 10 of the Most Important Companies in South America

De Santis

2024

OSCM: An Int. Journal

View full text Add to dashboard Cite

show abstract

“…Research concerning technology interactions predominantly asserts that cognitive cues can enhance the chatbot experience (Chen et al, 2021). Fan et al (2023) echoed this by asserting that efficient chatbots can enrich user experience. However, this was not supported during the postpurchase stage.…”

Section: Discussionmentioning

confidence: 99%

Do chatbots establish “humanness” in the customer purchase journey? An investigation through explanatory sequential design

Dwivedi,

Balakrishnan,

Baabdullah

et al. 2023

Psychology and Marketing

View full text Add to dashboard Cite

Chatbots incorporate various behavioral and psychological marketing elements to satisfy customers at various stages of their purchase journey. This research follows the foundations of the Elaboration Likelihood Model (ELM) and examines how cognitive and peripheral cues impact experiential dimensions, leading to chatbot user recommendation intentions. The study introduced warmth and competence as mediating variables in both the purchase and postpurchase stages, utilizing a robust explanatory sequential mixed‐method research design. The researchers tested and validated the proposed conceptual model using a 3 × 3 factorial design, collecting 354 responses in the purchase stage and 286 responses in the postpurchase stage. In the second stage, they conducted in‐depth qualitative interviews (Study 2) to gain further insights into the validity of the experimental research (Study 1). The results obtained from Study 1 revealed that “cognitive cues” and “competence” significantly influence recommendation intentions among chatbot users. On the other hand, “peripheral cues” and warmth significantly contribute to positive experiences encountered during the purchase stage. The researchers further identified 69 thematic codes through exploratory research, providing a deeper understanding of the variables. Theoretically, this study extends the ELM by introducing new dimensions to human‐machine interactions at the heart of digital transformation. From a managerial standpoint, the study emphasizes the significance of adding a “humanness” element in chatbot development to create more engaging and positive customer experiences actively.

show abstract

“…In addition, following previous research (Fan et al, 2023), t‐spooled scores were calculated to test the comparison effects (see Table 5). In terms of their functional elements, DoctorBots' ease of use significantly decreased both NPC (β EOU→NPC = −0.135, 90% BC‐CI = [−0.197, −0.082]) and PVC (β EOU→PVC = −0.172, 90% BC‐CI = [−0.233, −0.120]), and ease of use played a more significant role in alleviating PVC than NPC (t spooled = 19.264), thereby supporting H3a–H3c.…”

Section: Methodsmentioning

confidence: 99%

Reconciling the personalization–privacy paradox via DoctorBots: The roles of service robot acceptance model elements and technology anxiety

Shi,

Lu,

Zhou

2023

J of Consumer Behaviour

View full text Add to dashboard Cite

The role of artificial intelligence (AI)‐based DoctorBots in improving healthcare and the medical industry is expected to increase significantly in the coming decades. However, contrary to the general view that AI can gradually replace human work, user acceptance of DoctorBots has become an obstacle to the development of AI medical diagnosis. Building on the service robot acceptance model (sRAM), this study investigates the potential of the functional, socioemotional, and relational elements of DoctorBots to reconcile the personalization–privacy paradox, thus enhancing user acceptance. Via two scenario‐based experiments with 398 participants, this study reveals that the negative influence of the personalization–privacy paradox on user acceptance is exacerbated when users' technology anxiety is high. In addition, an online survey of 400 DoctorBot users indicates that ease of use, subjective social norms, social presence, and rapport are effective in addressing both nonpersonalization (NPC) and privacy concerns (PVC). These findings suggest that the healthcare industry can leverage DoctorBots to implement self‐diagnosis. Specifically, DoctorBots' functional elements are effective in mitigating users' NPC, and their relational elements are effective in extenuating users' PVC.

show abstract

Are AI chatbots a cure-all? The relative effectiveness of chatbot ambidexterity in crafting hedonic and cognitive smart experiences

Cited by 17 publications

References 50 publications

Are Chatbots the Key to Success in Customer Service for Logistics Companies? A Statistical Study of 10 of the Most Important Companies in South America

Are Chatbots the Key to Success in Customer Service for Logistics Companies? A Statistical Study of 10 of the Most Important Companies in South America

Do chatbots establish “humanness” in the customer purchase journey? An investigation through explanatory sequential design

Reconciling the personalization–privacy paradox via DoctorBots: The roles of service robot acceptance model elements and technology anxiety

Contact Info

Product

Resources

About