Dark Patterns through a Consumer Ethics Lens: Perceived Unethicality, Platform Trust Erosion, and Behavioural Intentions in Digital Markets

Dark patterns are strategies deliberately designed on digital platforms to exploit consumer cognitive limitations and information asymmetry, and are now documented across the majority of major digital platforms globally. However, how consumers morally evaluate these practices and how these evaluations shape trust and behaviour is theoretically underdeveloped. This paper aims to bridge the disciplinary gap between the dark patterns literature, which has concentrated on design classification and prevalence auditing, and the marketing ethics literature, which has not operationalized its well established consumer ethical perception framework to dark patterns. This paper draws from the legacy of unethical marketing, ethics position theory, the persuasion knowledge model and consumer trust theory to propose the Dark Pattern Consumer Ethics Framework (DPCEF) - an integrated theoretical model linking dark pattern perception to consumer trust erosion and behavioural outcomes. The framework proposes Perceived Dark Pattern Unethicality (PDPU) as the formally defined consumer side moral evaluation construct specific to dark patterns, theorises a two stage recognition-evaluation process in which digital literacy moderates the idealism PDPU relationship, and advances consumer platform trust as the mediating mechanism for behavioural outcomes such as negative behavioural intentions and regulatory support response. Finally, seven testable propositions based on theory are proposed. The framework makes a theoretical contribution to consumer ethics by formally integrating two literatures that have evolved in disciplinary isolation, expands the Persuasion Knowledge Model to contexts of digital dark patterns, and introduces regulatory support intention as a new behavioural outcome of perceived marketing unethicality with direct implications for digital consumer protection policy in emerging markets.