Exploring factors of service adoption using SERVQUAL paradigm: Its impact on millennials’ adoption of services in the self-drive rental sector

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The self-drive rental sector has witnessed exponential growth in recent years due to rising demand for long and short-distance drives among millennials. This study aims to investigate the quality of services in the self-driving rental sector and its impact on customer adoption or rejection of service in India. The conceptual framework was developed using the SERVQUAL model and other important factors affecting consumers’ service adoption. A quantitative research method was deployed, and data were gathered through a survey method using a structured questionnaire (based on a 5-point Likert scale). The sample size comprised 385 respondents, 23-38 years old millennials (with 69% of males and 31% of females). The population sample was chosen from Delhi, Mumbai, and Bangalore, India. The data were collected in March 2023. The factor and regression analyses were applied along with chi-square and SEM analyses to test the research hypotheses. The results indicated that the absence of low prices (42%), customer assistance (28 %), and security issues is responsible for consumer rejection. The factors leading to dissatisfaction are the absence of consumer schemes and discounts, a lack of staff interaction and assistance, and poor service quality. The brands must focus on the negative impact arising from the absence of these factors and effectively address the areas of improvement to regain customer trust and garner customer loyalty.

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    • Figure 1. Proposed conceptual framework
    • Table 1. Reliability statistics
    • Table 2. KMO and Bartlett’s test for factors leading to consumer satisfaction
    • Table 3. Rotated component matrix for factors leading to consumer satisfaction
    • Table 4. KMO and Bartlett’s test for factors leading to consumer dissatisfaction
    • Table 5. Rotated component matrix for factors leading to consumer dissatisfaction
    • Table 6. Model summary for brand attributes leading to service adoption
    • Table 7. ANOVA for brand attributes leading to service adoption
    • Table 8. Correlations for SEM analysis
    • Data curation
      A. S. Suresh, Laszlo Vasa, Yogesh Mahajan
    • Methodology
      A. S. Suresh
    • Validation
      A. S. Suresh, Vinod Sharma
    • Writing – review & editing
      A. S. Suresh, Vinod Sharma
    • Conceptualization
      Laszlo Vasa, Vinod Sharma
    • Supervision
      Laszlo Vasa, Vinod Sharma, Yogesh Mahajan
    • Writing – original draft
      Laszlo Vasa, Yogesh Mahajan
    • Visualization
      Yogesh Mahajan