There is an increasing number of academic and regulatory investigations into the behavioral and psychological implications of using Buy Now, Pay Later (BNPL) services due to their rapid growth. There have been extensive investigations into impulse purchases using BNPL services; however, there has been relatively little focus placed upon examining post-purchase regret associated with BNPL service use. The purpose of this paper is to present a systematic review of the extant literature investigating how BNPL service use relates to both impulsive purchasing behavior and post-purchase regret. A total of ten empirical studies were identified through a comprehensive search of the Scopus database according to the PRISMA 2020 guidelines, which were all published between 2018 and 2025. The results indicated that BNPL features, including deferred payments, perceived affordability, and urgency cues, are consistent predictors of both greater impulsive purchasing and lower levels of payment salience. The results of this review, however, reveal that many existing studies have failed to directly measure post-purchase regret and instead rely on proxy indicators, including financial distress, emotional discomfort, and decreased well-being. These findings, therefore, highlight a major theoretical and methodological void in the existing literature. In addition, by providing a synthesis of the current evidence base, this review aims to provide a clearer understanding of how BNPL features influence both consumer decision-making processes and post-purchase emotional responses; additionally, this review highlights the necessity for future research to utilize valid measures of regret, longitudinal designs and ethically informed analytical frameworks when investigating the psychological impacts of adopting BNPL services.

This study examines how consumers respond to personalized advertisements that appear to be derived from prior conversations with generative AI assistants in social commerce settings. Drawing on the Privacy Calculus Theory, Trust Theory, and the Stimulus–Organism–Response framework, the study investigates whether perceived GenAI-based advertising personalization simultaneously creates perceived personalization value and privacy concerns, and how these evaluations shape algorithmic trust and social commerce purchase intention. A scenario-based survey was conducted with 435 social commerce users in Jordan. Respondents evaluated a situation in which a product advertisement appeared to reflect a previous conversation with a generative AI assistant. The data were analyzed using partial least squares structural equation modeling with SmartPLS 4. The findings show that perceived GenAI-based advertising personalization increases both perceived personalization value and privacy concerns. Personalization value strengthens algorithmic trust, whereas privacy concerns weaken it. Algorithmic trust, in turn, strongly enhances social commerce purchase intention. The mediation results show that personalization value and privacy concerns transmit the dual effect of perceived GenAI-based advertising personalization to algorithmic trust. In contrast, algorithmic trust transmits these effects to purchase intention. Perceived transparency disclosure does not significantly reduce privacy concerns, but it strengthens the positive relationship between personalization value and algorithmic trust. This study contributes to digital marketing and social commerce research by showing that GenAI-personalized advertising can be perceived as both useful and intrusive and that perceived transparency disclosure may support trust formation without necessarily eliminating privacy concerns.

This study examines how consumers respond to personalized advertisements that appear to be derived from prior conversations with generative AI assistants in social commerce settings. Drawing on privacy calculus theory, trust theory, and the stimulus–organism–response framework, the study investigates whether GenAI-based advertising personalization simultaneously creates perceived personalization value and privacy concern, and how these evaluations shape algorithmic trust and social commerce purchase intention. A scenario-based survey was conducted with 435 social commerce users in Jordan. Respondents evaluated a situation in which a product advertisement appeared to match a previous conversation with a generative AI assistant. The data were analyzed using partial least squares structural equation modeling with SmartPLS 4. The findings show that perceived GenAI-based advertising personalization increases both perceived personalization value and privacy concern. Personalization value strengthens algorithmic trust, whereas privacy concern weakens it. Algorithmic trust, in turn, strongly enhances social commerce purchase intention. The mediation results confirm that personalization value and privacy concern explain the dual effect of GenAI-based advertising personalization on algorithmic trust. In contrast, algorithmic trust transmits these effects to purchase intention. Transparency disclosure does not significantly reduce privacy concern, but it strengthens the positive relationship between personalization value and algorithmic trust. The study contributes to digital marketing and social commerce research by showing that conversational-AI-derived advertising data can be perceived as both useful and intrusive. That transparency may support trust formation without necessarily eliminating privacy concerns.

The digital advertising sector is plagued by fraud, opacity, and inefficiency, eroding stakeholder trust and economic outcomes. Despite advances in digital marketing technologies, significant gaps remain in combating fraudulent activities and ensuring transparency. Addressing these challenges, this article proposes the AdChain framework, leveraging blockchain technology to revolutionise digital advertising by fostering transparency, reducing fraud, and enhancing operational efficiency. AdChain reconfigures the advertising landscape through a blockchain-based solution that ensures the authenticity and verifiability of ad engagements. By utilising blockchain’s intrinsic attributes, such as decentralisation, immutability, and transparency, AdChain aims to streamline digital advertising practices and restore trust among stakeholders. Using a qualitative approach, the study delineates the AdChain framework’s architecture, emphasising its decentralised nature, immutable records, and transparent processes. These features are designed to mitigate the prevalent issues in digital advertising, providing a more secure and efficient environment for all participants. Our findings indicate that AdChain effectively addresses advertising fraud and enhances the consumer experience by prioritising privacy and data control. This results in substantial economic benefits, optimising advertisers’ return on investment (ROI) and increasing publishers’ revenues. However, realising AdChain’s full potential requires overcoming several obstacles, including technical challenges related to scalability and system integration. Additionally, barriers to widespread adoption, such as regulatory uncertainties and the necessity for industry collaboration and standardisation, must be addressed. Despite these challenges, AdChain presents a promising avenue for transforming digital advertising, offering a robust solution to longstanding issues and paving the way for a more transparent and efficient advertising ecosystem.

A growing number of Buy Now, Pay Later (BNPL) service providers are emerging in digital markets around the globe; however, there is growing academic and regulatory concern about the potential psychological and behavioural impacts of these services on consumers. As part of addressing fears that BNPL services may be contributing to impulse purchases and post-purchase regret, this study provides an integrative and systematic review of empirical research on BNPL use from 2018 to 2025, examining how BNPL services affect impulse purchase behaviour and post-purchase regret. This review utilised PRISMA 2020 guidelines and CASP appraisal and a structured Scopus search, resulting in 10 peer-reviewed studies meeting the inclusion criteria out of the 15,605 initial records. The evidence indicates that BNPL service mechanisms, including instalment framing, urgency cues, and perceived affordability, influence both the reduction of payment salience and increases in impulsive purchasing. There is strong theoretical evidence supporting the role of regret as an emotional outcome related to BNPL. Yet, none of the reviewed studies assessed post-purchase regret using validated psychological tools. Instead, all the reviewed studies assumed that regret was being experienced indirectly through financial stress, compulsive spending and decreased overall well-being, indicating a significant omission in methodology of the BNPL literature. This review developed a conceptual model of psychological processes linking BNPL-induced impulsiveness with regret-related consequences. The results of this study contribute to the development of consumer behaviour theory by defining the missing measurement of regret, identifying the underlying theoretical mechanisms associated with BNPL-driven emotions and providing guidance for future longitudinal, experimental and cross-cultural research. Additionally, the results provide recommendations for protecting consumers, enhancing financial literacy and improving ethical design practices of BNPL product offerings.

Purpose: This paper examines how digital technologies are translated into supply chain performance under disruption and uncertainty. Drawing on the dynamic capabilities view, this study distinguishes digital technologies from supply chain digitalization and conceptualizes supply chain digitalization as the process through which digital resources are embedded into supply chain routines and developed into adaptive supply chain capabilities. Design/methodology/approach: Data were collected from 375 manufacturing organizations in Jordan and analyzed using partial least squares structural equation modeling (PLS-SEM). The model examines the effect of digital technologies on supply chain digitalization, the mediating roles of supply chain resilience, responsiveness and restoration and the moderating role of environmental dynamism. Predictive validity was assessed using PLS-Predict. Findings: The findings show that digital technologies positively influence supply chain digitalization. Supply chain digitalization, in turn, enhances resilience, responsiveness and restoration, which positively affect supply chain performance and mediate the digitalization–performance relationship. Environmental dynamism strengthens the effects of supply chain digitalization on adaptive capabilities and the corresponding indirect effects on performance. The results indicate that digitalization improves performance through capability development, particularly under dynamic operating conditions. Originality/value: The study contributes by distinguishing digital technologies from supply chain digitalization and explaining how digital resources are orchestrated into adaptive supply chain capabilities. It also contributes to benchmarking research by offering a diagnostic framework that helps firms identify where digital technology investments fail to become performance-enhancing capabilities. In addition, it extends supply chain integration, visibility, coordination and information-sharing research by showing how digital resources support resilience, responsiveness and restoration.