Data Sheet AIO Millennials and Gen Z

The dataset titled “A Study on the Attitude, Interest, and Opinion (AIO) of Millennials and Generation Z towards Sustainable Food and Personal Care Products” provides a well-structured, anonymised collection of respondent-level data designed to support transparent analysis and future research replication. This data sheet accompanies the manuscript authored by the research team listed in the title page and serves as the empirical backbone of the study’s quantitative assessment.

The dataset contains responses from 400 individuals belonging to Millennial and Generation Z cohorts residing in Tier 1 Indian cities. Each entry represents a unique participant and captures multiple dimensions of sustainability-related consumer behaviour. The data is arranged in a clean, tabular structure, with each column corresponding to a variable and each row representing a respondent. This format enhances usability for statistical analysis, machine learning applications, and behavioural modelling.

The sheet includes multi-item Likert-scale measurements representing three primary psychological constructs: Attitude, Interest, and Opinion toward sustainable food and personal care products. These items assess respondents’ levels of environmental favourability, motivation, perceived relevance, and evaluative beliefs regarding sustainable offerings. The dataset also contains several indicators measuring Sustainable Purchase Intention, enabling users to analyse behavioural outcomes or develop prediction models.

In addition to psychometric items, the dataset incorporates key demographic variables such as age category, gender, educational qualification, employment type, income band, and city of residence. These variables enable deeper segmentation analyses and facilitate examination of demographic variations in sustainability-oriented behaviour. All personal identifiers have been removed to ensure privacy and compliance with ethical data-handling standards.

Data sheet is analysis-ready, featuring clearly labelled variables, consistent coding schemes, and grouped construct items for ease of import into statistical software packages such as SPSS, R, platforms. Variable naming conventions are intuitive, and response scales are standardised to promote seamless computation of composite scores, factor analyses, reliability testing, and structural modelling.

This dataset is a valuable resource for scholars exploring sustainable consumption, behavioural psychology, segmentation of eco-conscious consumers, or comparative analysis across product categories. Its structured format enables replication of the original modelling procedures, but it is equally adaptable for new analytical approaches, including exploratory factor analysis, predictive modelling, or cross-cultural comparisons. The systematic organisation and clarity of documentation ensure that researchers, educators, and practitioners can utilise the dataset effectively and confidently in both academic and applied contexts.