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E-commerce companies employ deceptive techniques known as dark patterns (DPs) to manipulate customer decisions on online platforms. DPs are known to annoy and generate negative emotions in the consumers, which might be detrimental to a brand. Consequently, this study examines the influence of DPs on brand experience (BE) and consumer-based brand equity (CBBE) from the lens of stimulus-organism-response theory in an e-commerce organization.

Survey data was obtained from 419 respondents who frequently make transactions on e-commerce platforms. Subsequently, the authors used partial least squares-based structural equation modeling (PLS-SEM) via the R programming language to analyze the relationships.

It was found that DPs negatively impact the BE and CBBE of an e-commerce firm. Furthermore, BE positively impacts CBBE as well as mediates the relationship between DPs and CBBE. Additionally, no significant moderating influence of shopping frequency was discovered for the relation between DPs and BE.

The study investigates the connection between DPs, BE and CBBE in a general e-commerce context. Results may differ across specialized e-commerce sectors.

The study’s insights could motivate e-commerce managers to reevaluate their use of DPs. The study could help online platforms reorganize their business strategies and adopt a customer-centric approach, which might create a long-term positive relationship with customers. The results might spark discussions over redressing customer relations after previous exploitation via DPs.

To the best of the authors’ knowledge, this study is the first to empirically assess the impact of DPs on crucial brand parameters like BE and CBBE.

E-commerce companies use manipulative user interface (UI) designs known as dark patterns to influence customer decisions over internet platforms. Although dark patterns are known to annoy users and erode customer trust, e-commerce companies continue to use them heavily. Therefore, this study identifies and ranks the factors that motivate e-commerce companies to use dark patterns.

Feedback from 17 industry experts was collected, and a novel causal modelling technique known as the Grey Influence Analysis (GINA) was applied to discover the most important motivating factors in the system.

Meeting long-term economic goals, leveraging data from the existing users and meeting short-term marketing goals emerged as the most crucial reasons behind dark pattern usage. These motivational factors indicate that e-commerce companies prioritize profits over sustainability and are coherent with the agency theory of corporate governance.

The motivating factors have been identified considering the overall e-commerce industry. The factors may vary for specialized e-commerce sectors.

The study’s findings could help e-commerce managers adopt a user-centric approach and encourage them to fulfil their motivations behind dark patterns via other ethical strategies. Furthermore, company shareholders and managers could resolve conflicts of interest to avoid dark patterns and adopt a customer-centric approach. The study would also spark discussions on digital ethics and prompt legal authorities to devise policies against dark patterns.

The study demonstrates a systematic methodology for utilizing GINA in various domains. Additionally, it advances the literature on dark patterns and online customer manipulation.

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

Due to the extreme competition in the e-commerce landscape, online companies resort to driving extra profits by manipulating user decisions via manipulative user interfaces and tricks, known as dark patterns. Although many online users are aware of such manipulative tactics, they struggle to combat dark patterns due to certain challenges. Therefore, this study identifies and ranks the most and least significant user challenges in resisting dark patterns in e-commerce.

Initially, the authors identified 11 user challenges against dark patterns in the existing literature. After collecting expert opinions about the challenges from 17 industry professionals, the authors used grey influence analysis (GINA) to identify the most significant challenges.

The study reveals that lack of user awareness, partial control over cognitive biases and user preference for short-term benefits are the most influential challenges. Conversely, the normalization of aggressive marketing, lack of collective user action and legal challenges were found to have minimal influence.

The study’s findings apply to the generic e-commerce industry and may differ in specialized sectors.

The study’s findings could encourage specialized consumer education regarding dark patterns to assist users in minimizing cognitive biases. Based on the insights, e-commerce companies might differentiate themselves by embracing ethical design methods and supporting consumer trust and transparency above manipulative techniques.

The study pioneered the use of GINA to model user challenges in combating dark patterns, providing fresh insights into how these challenges interact and influence user behavior. It is one of the first to show the cascading effects of user challenges in a manipulative e-commerce environment.