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Marketing

The power of AI: enhancing customer loyalty through satisfaction and efficiency

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Article: 2326107 | Received 04 Dec 2023, Accepted 26 Feb 2024, Published online: 25 Mar 2024

Figures & data

Figure 1. Respondent summary. Source: MS Excel.

Figure 1. Respondent summary. Source: MS Excel.

Table 1. Respondent summary.

Table 2. Outer loadings of latent variables.

Table 3. Descriptive statistics, reliability and validity assessment.

Table 4. Heterotrait-monotrait ratio.

Figure 2. Structured model. Source: SMART-PLS calculation.

Figure 2. Structured model. Source: SMART-PLS calculation.

Table 5. Hypothesis testing.

Table 6. Mediation effect hypothesis testing.

Table 7. Coefficient of determination.

Data availability statement

My study involved the collection of data through a self-prepared questionnaire stored in an Excel sheet format. Considering the sensitive nature of the participant information and ethical considerations surrounding confidentiality, we are unable to share the raw dataset publicly. In light of this, we are seeking your valuable guidance on potential alternatives or acceptable practices that would comply with the Taylor & Francis Open Data Policy while maintaining the confidentiality of our participants. My aim to uphold the principles of transparency and reproducibility while respecting ethical boundaries. If there are specific protocols or methods that would better align with the policy while safeguarding participant confidentiality, I would greatly appreciate your expertise and suggestions in this regard.

Your insights and guidance on potential solutions or acceptable practices for sharing data while ensuring participant confidentiality would be immensely helpful for me to adhere to the journal’s policies effectively.