Search Results (30)

Conversational AI agents are now a routine touchpoint in e-commerce customer service, and AI empathy has emerged as the headline humanization strategy for repairing relational damage during service failures. A growing evidence base reports that empathic AI often backfires, because consumers cannot reconcile felt warmth with their lay model of what an artificial agent is. This research asks under what conditions AI empathy can be made credible to consumers. We propose that mechanistic interpretability, operationalized in the present studies as a consumer-facing visualization of an AI agent’s internal emotion-vector activations designed in the style of mechanistic-interpretability research, operates as a costly authenticity signal that rehabilitates empathic AI by enabling an attributional shift along the experience dimension of mind perception. Signaling Theory carries the antecedent stage of the causal chain, where mechanistic interpretability serves as a verifiable cue of computational authenticity. Mind Perception Theory carries the downstream stage, where the authenticated empathy is converted into consumer-brand intimacy. Two between-subjects experiments preceded by a feasibility pilot tested the account on Mainland Chinese consumers recruited via the Credamo online panel. Study 1 used a single-factor design contrasting high versus low AI empathy. Study 2 used a two (AI empathy) by two (mechanistic interpretability) full factorial. Study 1 showed a pattern consistent with high (versus low) AI empathy lowering brand intimacy through reduced perceived authenticity. Study 2 replicated the AI-empathy backfire when interpretability was absent, reversed the sign of the AI-empathy slope on the perceived-authenticity mediator when interpretability was present, and neutralized the negative conditional indirect effect on brand intimacy through perceived authenticity. The findings introduce mechanistic interpretability to consumer-marketing scholarship as a manipulable signaling channel, document a structural reversal in the mediator-stage slope coupled with neutralization of the indirect effect on the relational outcome, and prescribe pairing empathic AI phrasing with mechanistic-transparency design rather than deploying empathy without an accompanying transparency cue. Full article

The shift toward Smart Cities heavily relies on adopting energy-efficiency strategies to meet ambitious decarbonization targets. However, the rebound effect, where improvements in technical efficiency are partly offset by increased energy consumption, often reduces the expected environmental and economic benefits. Traditional Marginal Abatement Cost Curves (MACC) often ignore this behavioral feedback, which can lead to an overestimation of mitigation potential. This paper introduces a data-driven probabilistic framework for assessing the influence of the rebound effect on a portfolio of urban mitigation strategies by integrating behavioral feedback into a bottom-up MACC. By combining Monte Carlo (MC) simulations to address parametric uncertainty with Bayesian Networks (BN) for conditional inference, the robustness of nine strategies is examined across residential, commercial, and transportation sectors. The results demonstrate that even a moderate rebound effect ($\eta =0.5$) causes a $10.09\%$ decrease in total net abatement, dropping from 24.86 to 22.35 tCO₂e, and significantly raises costs. Notably, the number of strictly cost-effective strategies ($MAC<0$) decreases from six to three, highlighting the fragility of certain “win–win” measures. This framework introduces the concepts of Financial Backfire Probability (FBP) and Environmental Backfire Probability (EBP) as new metrics for urban planning. These findings emphasize that rebound tolerance is a critical factor in climate policy, indicating that additional measures, such as Internet of Things (IoT)-based monitoring and demand-side management, may be necessary to prevent performance erosion amid behavioral uncertainty. Full article

This study merged archival data from three separate experiments to investigate the typology of individuals who benefit most and least from gratitude letter writing interventions (N = 487). First, k-means clustering of pre- to post-intervention changes in affect revealed three distinct groups: Buffered, Mixed Feelings, and Backfired. The Buffered cluster comprised individuals who, on average, experienced decreases in negative affect (e.g., less frustration) but no changes in positive emotions (e.g., joyful). The Mixed Feelings cluster experienced increases in positive affect, alongside self-conscious emotions, particularly indebtedness, which became more closely aligned with uplifting emotional states following the intervention. The Backfired cluster experienced decreases in positive feelings and increases in negative affect. Next, differences in individual characteristics across clusters indicated that those in the Buffered cluster were relatively more neurotic, had higher baseline negative feelings, and lower trait gratitude. Individuals in the Mixed Feelings cluster tended to be more dispositionally grateful and seemed to invest more effort into the activity. Finally, individuals in the Backfired cluster were also relatively more grateful and had higher baseline positive affect. These findings contribute to understanding individual differences in the effectiveness of gratitude letter interventions and highlight opportunities to tailor such activities to promote personal growth. Full article

This study examines how structured interventions influence team creativity on a metaverse-based collaboration platform. Using B.sket, a custom virtual workspace, we tested two interventions during an online brainstorming task: (1) real-time participation feedback delivered as a communication barcode showing each member’s speaking time and sequence (an informational cue), and (2) a group norm communication encouraging equal participation (a social-normative cue). Eighty-one university students in South Korea, recruited through online advertisements using a convenience sampling method, participated in a 2 (group norm prompt: provided vs. not) × 2 (participation feedback: provided vs. not) between-subject factorial design. Team creativity was evaluated by fluency, flexibility, and originality. Results revealed that, contrary to expectations, participation feedback significantly reduced idea fluency and showed marginally negative effects on flexibility and originality. The group norm prompt produced no significant improvements in creativity. We speculate that these findings can be explained by self-determination theory and ego depletion theory, such that real-time participation feedback may undermine individuals’ sense of autonomy and induce cognitive distraction, thereby reducing creative performance. We discuss practical implications that team process interventions for promoting equal participation should be designed carefully to avoid these unexpected consequences. Full article

Parental educational anxiety poses a significant risk to children’s academic development. This two-stage study first establishes Parental Mathematics Education Anxiety (PMEA) as a unique construct and then examines the complex effects of a positive suggestion intervention. Study 1, a questionnaire-based investigation, revealed that PMEA is a significant and independent negative predictor of children’s mathematics achievement, distinct from parents’ general state anxiety or their own mathematics anxiety. It also identified socioeconomic factors, such as family income and parental education, as key drivers of PMEA. Study 2 employed an experimental design to test an intervention, revealing that the effectiveness of positive suggestions is not universal but is significantly moderated by the three-way interaction of PMEA level, child type (with/without math learning difficulties), and suggestion frequency. Notably, for non-math-difficult children, frequent positive suggestions from high-anxiety parents were found to be potentially detrimental (a “backfire effect”), whereas for math-difficult children in high-anxiety homes, a higher frequency of suggestion was necessary to yield benefits. These findings deepen the understanding of PMEA’s mechanisms and underscore the necessity of moving beyond one-size-fits-all approaches toward differentiated, context-aware intervention strategies in family education. Full article

This research examines how leader–member exchange ambivalence (LMXA) affects employee emotional exhaustion. It investigates the mediating role of workplace sense of control and the moderating effects of interactional justice. Based on Fairness Heuristic Theory, this research proposes that high organizational justice amplifies rather than buffers LMXA’s detrimental effects due to violated fairness expectations. Data from 511 Chinese employees were collected through a two-phase survey and analyzed using moderated mediation analysis. Results show that LMXA positively relates to emotional exhaustion through reduced workplace sense of control, and interactional justice strengthens this indirect effect. The negative impact of LMXA on workplace sense of control increases when justice levels are high, consequently increasing emotional exhaustion. These findings reveal a paradoxical effect of organizational justice, challenging assumptions about its universally positive function. This research contributes by demonstrating that fair organizational systems could backfire when combined with inconsistent leadership. The findings provide insights into how employees manage relational uncertainty and highlight the importance of leadership consistency in organizations. Full article

Personalized marketing presents a powerful but delicate strategy, as its benefits can be negated by rising consumer privacy concerns. To illuminate this tension, this study investigates what causes personalization to fail, focusing on the interaction between the level of message personalization and situationally activated privacy concerns. We conducted a 3 (Message Personalization: Low, Medium, High) × 2 (Situational Privacy Concern: Low, High) between-subjects experiment with 360 participants. These personalization levels were designed as an ecologically valid “intrusiveness ladder,” moving from a generic message to one using contextual data and to one using personally identifiable information (PII). Situational privacy concern was experimentally induced using a news article prime, after which participants were exposed to one of the marketing messages. The results revealed a significant interaction effect that demonstrates a critical “tipping point.” In the low privacy concern condition, increasing personalization boosted purchase intention. Conversely, when privacy concerns were activated, a ‘backfire effect’ occurred: highly intrusive, PII-based personalization was no more effective than a generic message and was significantly less effective than moderate, contextual personalization. Our findings provide causal evidence for the moderating role of situational privacy concern, demonstrating that activating this state is a key condition that triggers a non-linear consumer response. Practitioners must calibrate the level of data intrusiveness, as the most aggressive tactics can be counterproductive when consumer privacy sensitivities are high. Full article

The rapid development of online media has significantly facilitated the public’s information consumption, knowledge acquisition, and opinion exchange. However, it has also led to more violent conflicts in online discussions. Therefore, controversy detection becomes important for computational and social sciences. Previous research on detection methods has primarily focused on larger datasets and more complex computational models but has rarely examined the underlying mechanisms of conflict, particularly the psychological motivations behind them. In this paper, we propose a lightweight and language-independent method for controversy detection by introducing two novel psychological features: ascending gradient (AG) and tier ascending gradient (TAG). These features capture psychological signals in user interactions—specifically, the patterns where controversial comments generate disproportionate replies or replies outperform parent comments in likes. We develop these features based on the theory of the backfire effect in ideological conflict and demonstrate their consistent effectiveness across models and platforms. Compared with structural, interaction, and text-based features, AG and TAG show higher importance scores and better generalizability. Extensive experiments on Chinese and English platforms (Reddit, Toutiao, and Sina) confirm the robustness of our features across languages and algorithms. Moreover, the features exhibit strong performance even when applied to early-stage data or limited “one-page” scenarios, supporting their utility for early controversy detection. Our work highlights a new psychological perspective on conflict behavior in online discussions and bridges behavioral patterns and computational modeling. Full article

Background/Objectives: The effectiveness of eco-labels in encouraging more sustainable food choices varies across studies. We investigate whether consumers’ characteristics may explain this heterogeneity in the context of carbon footprint labeling by studying the moderating role of sociodemographic factors (age, gender, ethnicity, occupation), socioeconomic status (education and subjective socioeconomic position), place of residence (rural to urban), and political ideology. Methods: We manipulated the proportion of carbon-labeled products in two incentive-compatible and pre-registered choice experiments. The first (n = 715) asked consumers to shop for instant meal products in an online grocery store containing a food category’s complete product assortment. The second (n = 1233) forced consumers to make tradeoffs between product preferences and carbon emissions in two consecutive food choices for cut fruit products, one without and another with carbon labels. To capture potential lasting effects, we collected purchase intention data from the same respondents several months after the labeling exposure in both studies. Results: Across both studies, increasing the proportion of products with a carbon label led liberals and centrists to choose lower-emission foods but had minimal or no impact on conservatives (although it never backfired). None of the other individual characteristics moderated the effects of labeling after controlling for political ideology. However, a young age, a low subjective socioeconomic position, and an urban residence indirectly improved responsiveness to labeling by predicting a more liberal political ideology. The labeling effects observed for liberals persisted for four months but not longer. Conclusions: These findings demonstrate the critical moderating role of political ideology and provide actionable insights to improve the targeting and design of sustainability interventions. Full article

The present paper discusses the effects of social identity and self-determination theory and highlights their relevance for welfare conditionality with respect to individual behaviour and well-being. While welfare conditionality may provide economic incentives for certain desired behaviours, e.g., active job search, it is argued that their impact on the claimants’ social self-construal and identity may offset potentially positive effects and increase, for example, social segregation. Taking the integration of immigrants, one of the biggest contemporary challenges for many societies, as a leading example, possible negative effects of welfare conditionality are highlighted and contrasted with the imposed economic incentives. Weighing benefits and potential risks, it is argued that the excessive use of welfare conditionality is likely to backfire in the long run and that this should be taken into account by policy makers. Moreover, it is argued how similar effects can be expected to arise also in different contexts such as the support of child parenting by singles. Full article

Direct-injection technology applied in hydrogen internal combustion engines can effectively prevent backfire, thereby improving the engine performance. Nonetheless, optimizing the injection strategy is highly intricate, requiring a comprehensive understanding of the hydrogen–air mixture formation process inside the cylinder. In this study, a simulation of hydrogen–air mixture formation was systematically conducted in a hydrogen direct-injection internal combustion engine using three-dimensional computational fluid dynamics (CFD) software. Under rated conditions, the influence of the nozzle hole number, injection direction, injection timing, and combustion chamber geometry on the mixture formation was analyzed from the perspectives of flow state and mass transfer. The results indicate that more nozzle holes would lead to more significant non-uniformity of the mixture, mainly due to the Coanda effect. The normalized standard deviation (NSD) of a six-hole nozzle design is 0.3495, which is higher than the NSD of all the single-hole nozzle conditions. By changing the hydrogen injection timing from −144 °CA to −136 °CA, the non-uniformity coefficient of the mixture is little affected, while notable differences in the distribution of the mixture are observed. The appropriate injection directions and optimized combustion chamber geometries could also help to effectively organize the in-cylinder flow, significantly improving the uniformity of the in-cylinder mixture and reducing the likelihood of abnormal combustion events. Full article

Hydrogen fuel is gaining particular attention in internal combustion engines. In addition to zero-carbon emissions, major advantages relate to its combustion characteristics, which allow a significant increase in thermal efficiency under ultra-lean operation and with very low NOx levels. The ignition system is one of the main technology enablers, as it determines the capability to control ultra-lean operations, avoid backfire phenomena, and/or reduce the risks of abnormal combustions. The latter results from hydrogen’s low ignition energy and it is associated with factors like high-temperature residuals, hot spots, and irregular spark plug discharge. The ACIS gen 2-Barrier Discharge Igniter excels in accelerating the initial flame growth speed by the generation of non-equilibrium low-temperature plasma, a strong ignition promoter for the combined action of kinetic and thermal effects. Moreover, its volumetric discharge facilitates combustion initiation on a wide region, in contrast to the localized ignition of traditional spark systems. In this work we present for the first time, to the best of our knowledge, experimental results showing the performance of a hydrogen engine with a low-temperature plasma discharge. Tests were conducted on a single-cylinder research engine, achieving ultra-lean conditions with cycle-to-cycle variability results below 2.5%. The analysis indicates that the H2-BDI combined solution is capable of accelerating the evolution of the flame front compared to traditional spark plugs, leading to a significant reduction in the cycle-to-cycle variability. A meticulous adjustment of the BDI control parameters further enhances igniter performance and contributes to a deeper understanding of the innovative approach proposed in this study. Full article

We propose a quantum-mechanical model that represents a human system of beliefs as the quantised energy levels of a physical system. This model represents a novel perspective on opinion dynamics, recreating a broad range of experimental and real-world data that exhibit an asymmetry of opinion radicalisation. In particular, the model demonstrates the phenomena of pronounced conservatism versus mild liberalism when individuals are exposed to opposing views, mirroring recent findings on opinion polarisation via social media exposure. Advancing this model, we establish a robust framework that integrates elements from physics, psychology, behavioural science, decision-making theory, and philosophy. We also emphasise the inherent advantages of the quantum approach over traditional models, suggesting a number of new directions for future research work on quantum-mechanical models of human cognition and decision-making. Full article

This paper presents novel approaches for reducing the mass of the classical short backfire (SBF) antenna by using additive manufacturing and structural perforations. We first investigated techniques to create a 3D-printed structure with a conductive coating material. This approach resulted in a significant mass reduction (70%) compared with the conventional metallic structure. We performed parametric simulation studies to investigate the effects of the manufacturing process and showed that there was practically no difference in the performance. The largest source of error was the surface roughness and the conductivity of the metal paint. In a second design, we created perforations in the structure to further reduce the mass. We performed parametric studies to optimize mass reduction and to characterize the effects of the perforations and the surface roughness introduced during the 3D-printing process on the antenna. Antenna prototypes were fabricated and tested. The masses of the perforated 3D printed antenna were approximately 30% and 20% of the original aluminum design, respectively (70% and 80% reductions in mass, respectively). The good agreement among the original design, simulation, and measurements demonstrated the effectiveness of the approach. Full article

Hydrogen is an effective route for achieving zero carbon dioxide emissions, with a contained cost compared to electric powertrains. When considering the conversion of spark ignition (SI) engines to H₂ fueling, relatively minor changes are required in terms of added components. This study looks at the possibility of converting a small-size passenger car powered by a turbocharged SI unit. The initial evaluation of range and peak power showed that overall, the concept is feasible and directly comparable to the electric version of the vehicle in terms of powertrain performance. Injection phasing effects and cylinder imbalance were found to be potential issues. Therefore, the present work applied an 0D/1D simulation for investigating the effects of hydrogen fueling with respect to the likelihood of backfire. A range of engine speeds and load settings were scrutinized for evaluating the possibility of achieving the minimal risk of abnormal combustion due to pre-ignition. Ensuring the correct flow was predicted to be essential, especially at high loads and engine speeds. Fuel delivery phasing with respect to valve intake and closing events was also found to be a major factor that influenced not only backfire occurrence but conversion efficiency as well. Interactions with the electronic control unit were also evaluated, and additional requirements compared to standard conversion kits for LPG or CNG fueling were identified. Full article