Influence of Empathy Response on Brand Advocacy: AI Chatbot in the Banking Industry

Research dataset in the context of our study refers to the collection of quantitative data obtained from an online survey completed by respondents. Specifically, this dataset consists of data from Indonesian bank customers who:

1. Have interacted with AI banking chatbots within the past three months, and
2. Completed the online questionnaire covering the study’s variables.

Below is a general overview of the dataset structure used in this research:

1. Respondent Screening Data
- Have you used an AI banking chatbot in the last 3 months? (Yes/No)

2. AI Chatbot Usage
- Frequency of use (e.g., Daily, Weekly, Monthly, Rarely)
- Reasons for use (e.g., Checking balance, Transaction assistance, Complaints, etc.)
- Types of chatbots used (e.g., Livin’ by Mandiri, Jenius chatbot, etc.)

3. Demographic Data
- Age
- Gender
- Education level
- Occupation

4. Research Variables
- Empathy (9 items from Liu-Thompkins et al., 2022)
a) Perspective taking
b) Empathic concern
c) Emotional contagion

- Flow State (8 items from Hyun et al., 2022)
a) Focus, enjoyment, loss of time perception, and control

- Customer Experience (6 items from Ameen et al., 2021)
a) Convenience, personalization, ease of interaction, etc.

- Customer Satisfaction (6 items from Malik et al., 2021)

- Brand Advocacy (5 items from Kim et al., 2018)

5. Rating Scale
All items were rated using a 5-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree)

Second-order PLS-SEM was used for testing the proposed hypotheses and examining the relationships between multiple variables simultaneously..

Responden Results:
1. Total Respondents = 532
2. Respondents who did not use Chatbot = 169
3. Respondents with Unengaged Responses (STD. DEV < 0.2) = 28
4. Inconsistent Respondents = 23

Final Clean Data = 312