MEASURING GREENWASHING: DEVELOPING AND VALIDATING CONSTRUCTS
Description
This dataset, titled MEASURING GREENWASHING: DEVELOPING AND VALIDATING CONSTRUCTS, was collected as part of a study aimed at understanding greenwashing practices within organisations. The survey assesses organisational behaviours across multiple constructs of greenwashing, including Misleading Environmental Claims, Selective Disclosure, Symbolic Corporate Environmentalism, ESG Metric Manipulation, Green Trust, Digital Greenwashing, Corporate Reputation and Consumer Trust, and Investor Decision-Making. The dataset includes responses from 320 participants representing diverse organizational roles and demographics. For each construct, participants rated their agreement with statements on a 1–5 Likert scale, where 1 indicates "Strongly Disagree" and 5 indicates "Strongly Agree." This dataset provides valuable insights into how greenwashing practices impact stakeholder trust and perceptions, serving as a foundation for validating measurement constructs for greenwashing in organizational contexts.
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Steps to reproduce
Step 1: Define Constructs and Survey Questions Identify Constructs: Choose constructs that align with your research focus. For greenwashing, relevant constructs might include Misleading Environmental Claims, Selective Disclosure, Symbolic Corporate Environmentalism, etc. Develop Questions: Formulate 5-10 Likert-scale questions per construct (e.g., 1 = Strongly Disagree to 5 = Strongly Agree) that align clearly with each construct's definition. Pilot Test: Run a small pilot survey to ensure clarity and validity of the questions, revising as needed based on feedback. Step 2: Define Demographics Select Demographic Categories: Identify key demographics like Number of Employees, Sales Volume, Job Title, and Years at the Organization. These will provide context for your findings. Establish Proportions: Set realistic distribution goals (e.g., 50–250 employees = 30%) based on industry or population data to ensure the sample reflects your target population. Step 3: Design and Distribute the Survey Choose a Survey Platform: Use a tool like Qualtrics, SurveyMonkey, or Google Forms that supports Likert scales and demographic filters. Recruit Participants: Reach a representative sample via professional networks, online platforms, or industry associations, aiming for at least 300 respondents for statistical power. Screen for Relevance: Use screening questions to ensure participants meet specific criteria, such as being in a managerial position. Step 4: Collect and Organize Data Download Responses: After collecting data, download the responses in a CSV or Excel format. Clean Data: Review for completeness and remove low-quality responses (e.g., incomplete surveys). Code Demographics: Convert demographic responses into coded categories (e.g., "50–250" as 1, "251–500" as 2) to simplify analysis. Step 5: Analyze Data and Validate Constructs Validate Constructs: Perform factor analysis to confirm that items align with the intended constructs. Revise or remove items that don’t load well onto factors. Check Reliability: Calculate Cronbach’s alpha to assess the internal consistency of each construct. Score Constructs: Create scores by averaging responses for each construct as needed. Step 6: Document and Report Describe the Dataset: Document details about constructs, questions, demographics, and methods. Include demographic breakdowns and key characteristics. Save and Share Data: Securely store the dataset and, if relevant, share it with other researchers following ethical guidelines.