Strategic Role of Customer-Centric Culture in Driving Engagement: Insights from Saudi Arabia’s Automotive Sector
Description
his dataset contains responses from 391 participants working in the automotive aftersales sector in Saudi Arabia, collected via a structured questionnaire to examine the relationships between Customer Relationship Management (CRM), Customer-Centric Culture (CCC), Customer Experience (CX), and Customer Engagement (CE). Data Structure and Components Raw Survey Data (Anonymized) Each row represents one respondent. Includes demographic variables (e.g., region, age group, gender, nationality, department, company). Includes 7-point Likert scale responses to multiple items measuring CRM, CCC, CX, and CE, as well as their subdimensions (e.g., Customer Focus, CRM Processes and Structure, Technology-based CRM, Organizational Commitment, Empowered Employees, Metrics & KPIs, Ambient Experience, Cognitive Experience, Pragmatic Experience, Customer Satisfaction, Customer Trust). Cleaned & Coded Dataset Recoded variables for analysis (e.g., numeric scales from 1–7). Removal of incomplete responses and non-relevant entries. Statistical Output Tables Descriptive Statistics: Mean and standard deviation for each indicator. Demographic Summary: Frequency and percentage distributions for all demographic categories. Measurement Model Results: Factor loadings, Cronbach’s alpha (CA), Composite Reliability (CR), and Average Variance Extracted (AVE) for each construct and dimension. Discriminant Validity (Fornell & Larcker) and Heterotrait-Monotrait (HTMT) ratios. Cross-Loadings for each item. Collinearity Assessment and Effect Sizes (f²). Structural Model Results: Path coefficients, R², Q², and q² values. Predictive Relevance statistics.
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Steps to reproduce
This study utilized a quantitative research methodology for the collection of data through an online survey administered via Google Forms. The choice of Google Forms was influenced by its accessibility and user-friendliness, as observed by (Raju & Harinarayana, 2016), This ensured efficient data collection. Following ethical guidelines, the study was approved by the University Ethics Committee of Management and Science University (Approval No. EA-L1-GSM-2024-12-0036) and complied with best practices for online survey research (Buchanan & Hvizdak, 2009). Informed consent in written form was obtained from all participants, with a distinct emphasis placed on the nature of this consent. At the commencement of the survey, participants were formally invited to complete the questionnaire, during which the study’s purpose, their rights, and the restricted utilization of their information exclusively for research purposes were comprehensively elucidated. The written consent assured that participants comprehended their involvement was voluntary and that their privacy and anonymity would be safeguarded throughout the research process, thereby maintaining the ethical integrity of the study. To calculate the necessary sample size, we utilized (Krejcie & Morgan, 1970) widely used sample size calculator, setting a desired precision of 5% and a confidence level of 95%. We assumed a population proportion of 50% due to the lack of specific data on proportions in the target population, and then divided the sample size by the total number of strata for analysis. Data collection took place from August 10 to September 30, 2024, resulting in a final sample of 391 respondents, which exceeded the recommended threshold and ensured sufficient statistical power for subsequent analyses. Stratified sampling was used to effectively tackle the challenges posed by geographical dispersion, dividing the population into strata to ensure comprehensive representation (Aityan, 2022). To further mitigate potential biases, we made a concerted effort to include respondents from various regions across Saudi Arabia, which enhanced the overall representativeness of the sample. This approach, acknowledging the country’s regional diversity and cultural variances (Mazzetto & Vanini, 2023), improves methodological rigor by capturing differences in customer experiences and ensuring fair representation across different areas (Sarker & AL-Muaalemi, 2022).
Institutions
- Management and Science University