Dataset on Customer perception about across cost-leadership and differentiation hypermarkets
Description
Dataset of service quality, servicescape, perceived value, and customer satisfaction across cost-leadership and differentiation hypermarkets in Malaysia. The time frame of data collection consisted of August-October 2025 and incorporated a structured questionnaire (self-administered), which was given at the hypermarket entrances/exits. Out of 480 questionnaires that were sent out, 405 response that was usable were retained (cost-leadership: n = 201; differentiation: n = 204). The data (Raw Data.xlsx) consists of demographic variables (gender, age, race, education, and income) and 37 Likert scale items with a 7-point scale (service quality: 9 items; servicescape: 14 items; perceived value: 4 items; satisfaction: 10 items).
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Steps to reproduce
Data were obtained through a cross-sectional field survey of hypermarket shoppers in Kuala Lumpur, Malaysia, conducted between **August and October 2025**. The study followed a standardized workflow designed to ensure that the dataset can be reproduced in comparable retail settings. First, a structured questionnaire was developed based on established measures for **service quality, servicescape, perceived value, and customer satisfaction** (see Table 2: item codebook). All items were operationalized using a **7-point Likert scale** (1 = strongly disagree to 7 = strongly agree). The instrument also included a demographic section capturing **gender, age, race, education level, and monthly income** (Table 1). The questionnaire was formatted for self-administration and used identical wording and response anchors across respondents. Second, data collection was implemented using **non-probability convenience sampling** at selected hypermarkets. Respondents were approached at store entry/exit points and invited to participate voluntarily. After a brief explanation of the study purpose, participants provided informed consent and completed the questionnaire anonymously. A total of **480** questionnaires were distributed and **405 usable responses** were retained after basic screening for completeness. Respondents were classified into two groups—**cost-leadership (n = 201)** and **differentiation (n = 204)**—based on the strategic orientation of the hypermarket where the survey was administered, enabling group-based comparisons. Third, data were coded and compiled into **Raw Data.xlsx**, where each row represents one respondent and columns represent demographics and item responses (SQ1–SQ9; SS1–SS14; PV1–PV4; SF1–SF10). Descriptive statistics were computed for all items (Table 3). Measurement quality and construct validity were evaluated using **PLS-SEM** in **SmartPLS 4**, including indicator loadings, Cronbach’s alpha, composite reliability, and AVE (Table 4), discriminant validity via **HTMT** (Table 5), and predictive/explanatory metrics (**R² and Q²**) for customer satisfaction (Table 6). This end-to-end protocol—instrument specification, in-store recruitment and anonymous self-completion, dataset coding in spreadsheet format, and validation using SmartPLS—can be replicated by applying the same questionnaire and grouping procedure in other hypermarkets or regions.
Institutions
- Northern University of MalaysiaKedah, Jitra