This study explains why Generation Z consumers in Arab markets form intentions to purchase sustainable skincare products and clarifies the psychological mechanism through which green self-identities are converted into intention. Extending the Theory of Planned Behavior with constructs derived from value-belief-norm theorizing (green self-identity and eco-guilt), a Green Influencer Marketing (GIM) construct measured with a validated eight-item scale and modelled as a single reflective composite, appearance-related social media consciousness, and the horizontal-vertical individualism-collectivism framework, the study positions eco-guilt as the mediating mechanism and appearance-related social media consciousness and vertical collectivism as moderating boundary conditions. Data were collected in January 2026 through an online survey of Generation Z consumers in Egypt, Saudi Arabia, the United Arab Emirates, and Qatar; after screening and the exclusion of fifteen underage respondents, 369 adult responses (ages 18 to 29) were analyzed using partial least squares structural equation modeling in SmartPLS 4 with 10,000 percentile bootstrap subsamples. The findings show that the model explains 78.3% of the variance in purchase intention with strong out-of-sample predictive relevance (Q²predict = 0.734). Attitude, eco-guilt, GIM, vertical collectivism, horizontal individualism, and vertical individualism exert significant positive effects, whereas subjective norms exert a significant negative effect and perceived behavioral control and horizontal collectivism are non-significant. Green self-identity influences intention entirely indirectly through eco-guilt (indirect effect = 0.159, 95% CI [0.100, 0.219]), appearance-related social media consciousness attenuates the GIM effect, and vertical collectivism strengthens the identity-intention link. The pattern is consistent with identity-based sustainability dispositions requiring moral-emotional activation and with cultural hierarchy licensing their behavioural expression, although the cross-sectional design does not permit causal inference. Theoretically, the study clarifies the mechanism connecting self-identities to intention and identifies two boundary conditions of digital and cultural origin; practically, it directs sustainable beauty brands toward moral-emotional framing, relational rather than appearance-centric green influencer strategies, and family- and duty-anchored positioning in Arab markets.

Purpose: This study models how open-source large language model (LLM) recommender interaction quality (personalisation and responsiveness) affects Gen Z online purchase decisions through trust, AI familiarity, and privacy concerns using the Stimulus-Organism-Response (SOR) framework. Design/Methodology/Approach: We have conducted a Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis of 570 Gen Z online shoppers from Egypt, Saudi Arabia, Jordan, and Qatar. Findings: Interaction quality improved trust (β=0.2585) and AI familiarity (β=0.2943) while increasing privacy concerns (β=0.5499). Purchase intention was positively influenced by trust (β=0.2848) and privacy concerns (β=0.3583). AI familiarity showed no direct impact (β=0.0477). Model explained 47% variance in purchase intention. Originality/Value: Few studies examined trust-privacy dynamics for open-source LLM recommenders across four economies. Research Implications: SOR theory application reveals trust mediates positively while high interaction quality increases privacy concerns among Gen Z. Practical Implications: Retailers should optimise interaction quality while implementing transparency and user control mechanisms to address heightened privacy concerns. Keywords: Open-Source LLMs; E-Commerce Interaction Quality; Trust-Privacy; SOR Model; Gen Z; Middle East Shopping. Citation: Shaheen, A., Omeish, F., AlGhamdi, D. S., Khataan, A. and Awad, A. (2026): Sustainable E-Commerce in MENA: An SOR Analysis of Gen Z Purchase Intentions through Open-Source LLM (DeepSeek) Interactions, Trust, Familiarity, and Privacy Concerns. World Journal of Entrepreneurship, Management and Sustainable Development (WJEMSD), Vol. 22, Nos 1-2, pp. 133-150.

Building on conservation of resources theory (COR) and dual-process theory (DP), we explore how cognitive overload (CO) negatively affects sustainable consumer choices (SCC) in Pakistan’s digital and retail settings. We postulate decision fatigue (DF) as a mediator through which CO impairs consumers’ ability to sustainably purchase products. Further, we also propose digital nudging intensity (DNI) as a moderating factor. The results of a scenario-based experiment (Study 1) involving 392 consumers from Karachi and Lahore reveal that CO leads to a substantial reduction in sustainable intentions through DF. Study 2, using multiwave survey data of 214 online consumers in Pakistan, verifies the mediation of DF. We also observe that low intensity of digital nudging mitigates the influence of CO and high intensity of digital nudging increases DF, thus negatively affecting sustainable choices. Our work advances sustainable economic decision-making by incorporating psychological limitations with digital nudging and provides practical insight for creating sustainable consumer environments.

This paper discusses the conceptualization and design of an ergonomically adjustable stand-table workstation that meets the needs of the marketer’s particularly Digital marketers. The suggested system will include such advanced features as AI-based data visualization, adjustments that are controlled by a sound sensor, and mood-sensing lights to increase the level of user comfort, productivity, and well-being. The main characteristics are the motorized height adjustment system, the smart posture tracking system, and the cable management system which is optimized. The current study presents useful information on the design of intelligent ergonomic workspaces through the assessment of the technical feasibility, user comfort, and performance of the workstation. The outcomes of the study suggest that the marketers using the recommended workstation can experience reduced physical discomfort, improved ergonomic position, and cognitive performance. Moreover, the integration of artificial intelligence and sensor-based technologies is seamless and, as a result, it becomes possible to create a customized and interactive working environment, which will decrease stress levels and enhance mental well-being.