Publicações

Introduction – Quantitative models of sustainable consumption typically treat consumption as exogenous, assuming that every green purchase improves environmental outcomes. Behavioral research on moral licensing, however, suggests that purchases perceived as virtuous can license compensatory indulgence that erodes some of the benefit. Recent formal work treats licensing as an environmental rebound mechanism in static consumer models; this study contributes the first dynamic stock-and-flow formalization, developed from a recent conceptual framework of brand-induced moral licensing.

Methods – Four communication pathways (virtue attribution, identity conferral, effort signaling, and absolution framing) feed two moral accounts with opposite mechanics: credits, which deplete when spent, and credentials, which license behavior without being consumed. The model yields closed-form steady states and a licensing-resistance condition on the rebound ratio ρ> (backfire at ρ> 1). Communication parameters were calibrated through a preregistered content analysis of 120 verbatim-archived units from eight sustainable brands, with perfect dual-coder agreement on the reliability subsample; identity internalization was calibrated from a two-country survey of 3,293 adults. The behavioral conversion parameters are literature-anchored or illustrative, so all rebound magnitudes are model-derived, order-of-magnitude results rather than empirical estimates.

Results – Rebound stays far below backfire: steady-state values span 0.01 to 0.19 across archetypes, preserving 81 to 99% of gross benefit, across 8,000 uncertainty samples and under structural variants allowing credential depletion, sign reversal, and alternative licensing functions. Calibration inverts the theorized risk ordering: identity-positioned brands deploy almost no identity-conferring language, decoupling the typology’s conceptual categories from their communication signatures. The model further predicts that 6-month evaluations understate long-run rebound nearly five-fold, implying measurement windows of 1 to 3 years. Absolution framing is absent from the corpus, consistent with the application timeline of Directive (EU) 2024/825; in counterfactual simulation, restoring such claims forfeits up to a third of gross benefit, whereas reducing the growth signal lowers cumulative modeled benefit without reducing rebound.

Discussion – Licensing rebound is projected to be real but bounded; message design, not demarketing, is the effective lever within the modeled mechanism. The model supplies an auditable communication-risk map and the design brief for the longitudinal study the field lacks.

This paper examines the integration of Information and Communication Technologies (ICT) and Artificial Intelligence (AI) into Customer Relationship Management (CRM) and their high value in supporting strategic competitiveness. To examine the links among strategy formulation, ICT, AI, and uncontrollable factors affecting business operations, this study proposes an interpretive model of these relationships, with strategic competitiveness as the dependent variable. Drawing on interviews and real-world data from several SMEs, the research findings indicate that although adopting AI and forecasting practices may pose challenges, mid-level and top managers increasingly recognize the importance of ICT and AI in formulating and implementing competitive strategies that enhance organizational competitiveness. The key results are discussed, and directions for future research are suggested.

Flow experience and gaming addiction are central to understanding player engagement and spending. This study proposes and tests an integrated model linking flow, online gaming addiction, and purchase intention for in-game virtual goods. Data from 483 gamers were analyzed using covariance-based structural equation modeling. Results confirm that flow positively influences purchase intention both directly and indirectly through addiction, which functions as a partial mediator. Multi-group analysis reveals the core model is robust across gender and engagement level, although the indirect pathway via addiction is stronger among experienced players, while light users show greater sensitivity to engagement-driven consumption. These findings clarify how immersive experiences translate into economic behavior, identify vulnerable user segments, and inform game designers, marketers, and policymakers concerned with responsible monetization.

Impulse buying is something most of us have experienced—walking into a store with no plans to shop and walking out with a bag full of clothes. This study looks closely at what drives that kind of spontaneous behavior, focusing specifically on fashion physical retail in Portugal. The researchers surveyed 411 consumers and used a structural model to analyze how different traits and marketing stimuli influence impulse buying. They looked at factors like sensation seeking, self-identity, shopping motivations (both for pleasure and practicality), how involved people are with fashion, how sensitive they are to price, and how much they’re influenced by store promotions and ambiance. A key part of the study is the role of self-control. The findings show that self-control acts as a kind of filter—helping people resist external triggers like sales promotions or appealing store environments. While fashion involvement, hedonic motives, and price sensitivity directly encourage impulse buying, self-control weakens the impact of other factors. In fact, it completely mediates the effects of store ambiance and promotions. This means that those elements only influence buying behavior when someone’s self-control is low. The study offers valuable insights for fashion retailers. Retailers who want to increase sales should focus on creating enjoyable shopping environments and running sales promotions because these strategies work best with customers who have low self-control. The study deepens our comprehension of impulse buying by showing how motivations interact with environments and internal self-regulation.

Grid-impact studies treat battery electric vehicles as loads, and ask when network capacity will be exhausted. This paper reverses the question: how much of the fleet must operate bidirectionally, and with what probability will an achievable participation rate suffice, for the network to remain within its limits? A conceptual framework adds a vehicle-to-grid and vehicle-to-building flexibility term to the balance between available and required power, nests the authors’ earlier deterministic model for twenty municipalities in Northern Portugal as its zero-flexibility special case, derives a closed-form break-even participation rate per municipality and year, and keeps the simultaneity assumption of that model explicit as a coincidence factor. Participation, location, plug-in and export parameters follow beta-PERT distributions calibrated on published trials and surveys, propagated by Monte Carlo simulation without new field data. The framework is an apparent-power balance per municipality, so its outputs are an upper bound on usable flexibility, not a feeder-level feasibility check. An enrolled vehicle provides about 11 kVA of peak relief, over nine tenths from not charging rather than exporting. Under worst-case simultaneity, observed participation rates, if in place from the outset, halve the 2028 shortfall probability but cannot prevent shortfall by 2030; under realistic coincidence the regional network is not constrained and only eight of twenty municipalities remain critical. The network balance is replicable wherever municipal substation data exist; behavioural parameters require local calibration.