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The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
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Exploring chatbot trust: Antecedents and behavioural outcomes
Subburaj Alagarsamy1, Sangeeta Mehrolia2
1School of Business, Manipal Academy of Higher Education, Dubai Campus, United Arab Emirates.
Heliyon
|May 19, 2023
Summary
Understanding factors influencing trust in banking chatbots is key for effective marketing strategies. This study reveals key drivers of chatbot trust and its impact on customer behavior in the Indian banking sector.
Area of Science:
- Artificial Intelligence
- Marketing
- Human-Computer Interaction
Background:
- Chatbots are increasingly used in banking services.
- Understanding user trust in chatbots is crucial for service providers.
- Limited research exists on the antecedents and outcomes of trust in banking chatbots in India.
Purpose of the Study:
- To identify the antecedents of trust in banking chatbots.
- To examine the behavioral outcomes of trust in banking chatbots.
- To propose and test a conceptual model of chatbot trust in the Indian banking context.
Main Methods:
- An online questionnaire was distributed to users of four major Indian banking chatbots.
- Data from 435 complete responses were analyzed.
- Hypotheses were tested using statistical analysis to determine variance explained.
Main Results:
- Antecedents (excluding interface, design, and technology fear) explained 38.6% of the variance in banking chatbot trust.
- Chatbot trust explained 9.9% of variance in customer attitude, 11.4% in behavioral intention, and 13.6% in user satisfaction.
- The study identified significant factors influencing chatbot trust and its outcomes.
Conclusions:
- Managers can leverage chatbot trust to enhance customer interaction and brand engagement.
- The findings contribute to AI marketing literature by providing a validated conceptual model.
- Insights are valuable for designing effective marketing strategies for banking chatbots.
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