Ladislav Pilař

Purpose: This study aims to develop and validate a Digital Conformity Scale (DCS) to understand individuals' conformity to digital norms, addressing the erosion of individuality influenced by pervasive social media exposure. The research explores conformity factors through a meta-analysis and scale development grounded in Social Influence Theory and Banerjee's Herding Behavior Theory. Design/methodology/approach: A meta-analysis was conducted to explore the determinants of conformity in various contexts. After that, data were collected from three diverse groups: 282, 468 and 100, respectively. An exploratory factor analysis (EFA) was performed on a preliminary scale with 50 items. This was followed by a confirmatory factor analysis (CFA) for validation. Finally, the last study assessed digital conformity alongside related constructs for convergent and discriminant validity. Findings: The scale demonstrated good consistency, with EFA indicating four distinct factors. The CFA supported a four-factor model with 25 items, fitting well within the data. Research limitations/implications: Self-report measures may introduce biases and social desirability effects, limiting generalizability. Additionally, the scale's length may burden respondents. Practical implications: The DCS is a valuable tool for understanding digital conformity, promoting well-being and contributing positively to societal welfare. Social implications: Insights from this research can inform guidelines and regulations to encourage responsible digital interaction, contributing to a healthier digital society. Originality/value: The digital era requires rethinking traditional social influence principles, incorporating modern phenomena like trend adoption (TA) and fear of missing out (FoMo). The DCS integrates these characteristics into Social Influence Theory, guiding and navigating the digital landscape and fostering genuine online relationships.

Over the last few decades, the globe has become an eyewitness to several challenges that must be addressed before the bubble bursts. In this regard, environmental sustainability has become a major concern for policy analysts. Leading authorities encourage economies to collaborate and work together for sustainability. In this respect, this study introduces the core environmental determinants, which include income, urbanization, digitalization, natural resources, new businesses and energy transition (ET). To portray the actual situation of Asia-Pacific Economic Cooperation (APEC) economies over the period of 2005–2023, this research utilizes the most prominent estimators and finds reliable outcomes. For instance, income, urbanization, natural resources and business activities can all contribute to environmental deterioration. In contrast, ET significantly reduces pollution. A considerable role of digitalization in sustainability is being observed, and it contributes to environmental quality by 0.185%, 0.069% and 0.005%, correspondingly, under the Cross-Sectional Autoregressive Distributive Lag Model (CS-ARDL), augmented mean group (AMG) and common correlated effect mean group (CCE-MG) estimators. The moderate effect of digitalization reduces emission levels through natural resource conservation, business activities and ET, and the mediating results support the sustainability theme across the selected economies. In a comparative analysis of natural resources, the depletion of forest resources contributes to carbon emissions. Similarly, oil and coal rents describe the adverse but insignificant outcomes for the selected panel. The comparative analysis of the outcomes from natural and mineral resources reveals the superior sustainability performance of mineral resources. The cubic form of income validates the N-shaped environmental Kuznets curve (EKC) hypothesis for the APEC economies. As well, the quadratic form of natural resources and digitalization yields reliable outcomes for a sustainable environment. Ultimately, green initiatives under the environmental sustainability theme are crucial for reducing environmental stress by 2050.

Greenwashing—defined as the strategic misrepresentation of corporate environmental practices—has emerged as a focal point of critical discussion on social media platforms. In this study, discourse related to greenwashing on Twitter was analyzed to uncover key thematic structures, sentiment dynamics, and polarization patterns. A total of 308,075 tweets authored by 148,881 unique users between 1 January 2015 and 31 January 2023 were collected and subjected to topic modelling and sentiment analysis. Ten primary themes were identified: (1) Sustainability and Marketing, (2) Climate Change and Fossil Fuels, (3) International Summits and Activism, (4) The Green Deal, (5) Environmental, Social, and Governance (ESG) Investments, (6) Plastic Waste, (7) Fast Fashion, (8) The Automotive Industry, (9) Deforestation, and (10) Food and Agriculture. Sentiment analysis, conducted using the Valence Aware Dictionary and Sentiment Reasoner (VADER), revealed a predominantly critical tone across the dataset. Negative sentiment was detected in 35.54% of tweets, while only 12.86% conveyed a positive stance; the remaining 51.6% were classified as neutral. These findings underscore the pervasive skepticism towards corporate environmental claims and highlight the perceived dissonance between green marketing narratives and actual corporate behavior. Furthermore, the study illustrates how public sentiment clusters around specific themes, suggesting issue-based polarization in perceptions of environmental credibility. By integrating topic modelling with sentiment polarity analysis, this research offers an empirical framework for evaluating public discourse surrounding greenwashing. The insights derived may inform both corporate sustainability communication strategies and policy interventions aimed at fostering transparency and accountability. Overall, the evidence points to an urgent need for more authentic, verifiable, and ethically aligned environmental messaging to restore public trust in sustainability initiatives.