Explorando os malefícios da sobrecarga cognitiva para as escolhas sustentáveis do consumidor; a fadiga decisória como mediadora e a intensidade dos incentivos digitais internacionais como moderadora
a fadiga decisória como mediadora e a intensidade dos incentivos digitais internacionais como moderadora
DOI:
https://doi.org/10.23925/2179-3565.2026v17i2e76450Palavras-chave:
Sobrecarga cognitiva, Escolhas sustentáveis do consumidor, Fadiga decisória, Nudges digitais, Comércio eletrônicoResumo
Com base na teoria da conservação de recursos (COR) e na teoria do processo dual (DP), exploramos como a sobrecarga cognitiva (CO) afeta negativamente as escolhas sustentáveis do consumidor (SCC) nos contextos digitais e de varejo do Paquistão. Postulamos a fadiga decisória (DF) como mediadora por meio da qual a CO prejudica a capacidade dos consumidores de comprar produtos de forma sustentável. Além disso, também propomos a intensidade dos nudges digitais (DNI) como fator moderador. Os resultados de um experimento baseado em cenários (Estudo 1), envolvendo 392 consumidores de Karachi e Lahore, revelam que a CO leva a uma redução substancial das intenções sustentáveis por meio da DF. O Estudo 2, utilizando dados de levantamento multi-onda de 214 consumidores on-line no Paquistão, confirma a mediação da DF. Observamos também que a baixa intensidade de nudges digitais mitiga a influência da CO, enquanto a alta intensidade de nudges digitais aumenta a DF, afetando negativamente as escolhas sustentáveis. Nosso trabalho avança a tomada de decisão econômica sustentável ao incorporar limitações psicológicas aos nudges digitais e oferece insights práticos para a criação de ambientes de consumo sustentáveis.
Downloads
Referências
Ali, S. M. S. (2025). Cognitive biases in digital decision making: How consumers navigate information overload (Consumer Behavior). Advances in Consumer Research, 2, 168-177.
Aydin, S. (2026). Brand Trust in AI-Driven E-Commerce Personalization: The Well-Being–Privacy Trade-Off. Sustainability, 18(2), 1073.
Balaskas, S., Yfantidou, I., Nikolopoulos, T., & Komis, K. (2025). The Psychology of EdTech nudging: persuasion, cognitive load, and intrinsic motivation. European Journal of Investigation in Health, Psychology and Education, 15(9), 179.
Brislin, R. W. (1986). A culture general assimilator: Preparation for various types of sojourns. International Journal of Intercultural Relations, 10(2), 215-234.
Bettman, J. R., Luce, M. F., & Payne, J. W. (1998). Constructive consumer choice processes. Journal of consumer research, 25(3), 187-217.
Baddeley, A. (1992). Working memory: The interface between memory and cognition. Journal of cognitive neuroscience, 4(3), 281-288.
Chou, C. Y., & Chen, W. J. (2025). Exploring the messenger effect on consumer emotions and attitudes: Promoting socially responsible practices in the cosmetics sector. Electronic Markets, 35(1), 61.
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and instruction, 8(4), 293-332.
Dong, X., Jiang, B., Kassoh, F. S., & Chen, F. (2025). Platform architecture enhances consumer decision certainty in food supply chains: the reference effect and trust transfer mechanism. Frontiers in Sustainable Food Systems, 9, 1550187.
Dhar, R., & Nowlis, S. M. (1999). The effect of time pressure on consumer choice deferral. Journal of Consumer research, 25(4), 369-384.
Fitriani, S. (2025). The Emotional Impact of Influencer Fatigue on Online Shopping Decisions. Journal of Sustainability Industrial Engineering and Management System, 4(1), 315-324.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Hobfoll, S. E. (1989). Conservation of resources: a new attempt at conceptualizing stress. American psychologist, 44(3), 513.
Hobfoll, S. E., Halbesleben, J., Neveu, J. P., & Westman, M. (2018). Conservation of resources in the organizational context: The reality of resources and their consequences. Annual review of organizational psychology and organizational behavior, 5, 103-128.
Jegorow, D. (2025). Digital Fatigue, Sustainability Behaviour, and Energy Awareness Among Generation Z: The Role of Cognitive Resources and Education. Social Sciences, 15(1), 12.
Jangam, S. D. (2025). Mindfulness and Impulsive Buying Behavior Among Gen Z Consumers in Digital Environments: The Role of Social Media Engagement. Available at SSRN 5253588.
Joshi, Y., & Rahman, Z. (2015). Factors affecting green purchase behaviour and future research directions. International Strategic management review, 3(1-2), 128-143.
Jaiswal, R., Gupta, S., & Chen, P. J. (2026). GenAI personalization: antecedents, outcomes, mediators, and moderators. International Journal of Contemporary Hospitality Management, 38(13), 134-158.
Kim, M. (2024). The Effect of Choice Overload on Consumer Emotions, Decision Fatigue, and Purchase Intention: The Moderated Mediation Effect of Word-of-Mouth Credibility. Asia-Pacific Journal of Business Venturing and Entrepreneurship, 19(6), 175-188.
Kaur, T., Dubey, R. K., Das, P., & Mandal, S. (2025). Navigating digital well-being in service encounters: a trait-based analysis of FOMO, JOMO and moderating mechanisms. International Journal of Quality and Service Sciences, 17(4), 498-518.
Khan, S. M. F. A., & Shehawy, Y. M. (2025). Perceived AI Consumer-Driven Decision Integrity: Assessing Mediating Effect of Cognitive Load and Response Bias. Technologies, 13(8), 374.
Kollmuss, A., & Agyeman, J. (2002). Mind the gap: why do people act environmentally and what are the barriers to pro-environmental behavior?. Environmental education research, 8(3), 239-260.
Liang, Y., & Cheng, C. (2025). Greenwashing and Consumer Green Perceived Value: The Mediation Mechanism of Green Consumer Confusion and Green Perceived Risk. Journal of Environmental Management & Tourism, 16(2), 170-185.
Liu, P., Tu, T., & Dong, Q. (2025). Choice overload and experienced utility in the Chinese dairy market: The moderating role of decision styles and the impact of information nudging. Food Quality and Preference, 105635.
Lieder, F., & Griffiths, T. L. (2020). Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources. Behavioral and brain sciences, 43, e1.
Mousa, M. M., Rashed, A. S., Akaileh, M., Zamil, A. M., Ahmed, H. A., & Abdelghani, A. A. (2026). Artificial Intelligence Marketing Technologies and Consumer Purchasing Decisions: The Moderating Role of Virtual Customer Experience and Implications for Sustainable Consumption in Telecommunications Service Environments. Sustainability, 18(6), 2674.
Malhotra, N. K. (1982). Information load and consumer decision making. Journal of consumer research, 419-430.
Masmali, F. H., Khan, S. M. F. A., & Hakim, T. (2025). IoT-Enabled Digital Nudge Architecture for Sustainable Energy Behavior: An SEM-PLS Approach. Technologies, 13(11), 504.
Parvez, T., & Kaushik, H. (2026). Understanding Digital Nudges in E-Commerce: An Interpretative Structural Modeling-Based Analysis of Impulse Buying Behavior. Journal of Emerging Markets and Management, 2(1), 92-108.
Pignatiello, G. A., Martin, R. J., & Hickman Jr, R. L. (2020). Decision fatigue: A conceptual analysis. Journal of health psychology, 25(1), 123-135.
Riandhi, A. N., Arviansyah, M. R., & Sondari, M. C. (2025). AI and consumer behavior: Trends, technologies, and future directions from a scopus-based systematic review. Cogent Business & Management, 12(1), 2544984.
Samara, E., Kilintzis, P., Carayannis, E. G., & Zotas, N. (2025). How startups can decode shifting consumer preferences in the digital era: leveraging behavioral insights for agile business model innovation. Journal of the Knowledge Economy, 1-31.
Sweller, J. (2011). Cognitive load theory. In Psychology of learning and motivation (Vol. 55, pp. 37-76). Academic Press.
Suhluli, S. (2026). Digital Adoption of Generative AI Tools: A Multi-Theory Model Linking Cognitive Load, User Perceptions, and System Attributes. Sustainability, 18(4), 2076.
Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological bulletin, 119(1), 3.
Sunstein, C. R. (2014). Nudging: a very short guide. Journal of consumer policy, 37(4), 583-588.
Shorbaji, M. F., Alalwan, A. A., & Algharabat, R. (2025). AI-enabled mobile food-ordering apps and customer experience: A systematic review and future research agenda. Journal of Theoretical and Applied Electronic Commerce Research, 20(3), 156.
Thaler, R. H., & Sunstein, C. R. (2008). Improving decisions about health, wealth and happiness (Vol. 304). New Haven: Yale University Press.
Verma, T., & Arora, D. S. (2025). Influence Without Intrusion: Decoding the Role of Digital Nudging in Shaping Online Decisions. Electronic Commerce Research, 1-40.
Vohs, K. D., Mead, N. L., & Goode, M. R. (2008). Merely activating the concept of money changes personal and interpersonal behavior. Current Directions in Psychological Science, 17(3), 208-212.
Vermeir, I., & Verbeke, W. (2006). Sustainable food consumption: Exploring the consumer “attitude–behavioral intention” gap. Journal of Agricultural and Environmental ethics, 19(2), 169-194.
Wang, X., & Ren, Y. (2026). The Spillover Effects of E-Commerce Platform Algorithmic Governance: A Focus on Ride-Hailing Drivers’ High-Calorie Food Consumption. Journal of Theoretical and Applied Electronic Commerce Research, 21(2), 66.
Weinmann, M., Schneider, C., & Brocke, J. V. (2016). Digital nudging. Business & Information Systems Engineering, 58(6), 433-436.
White, K., Habib, R., & Hardisty, D. J. (2019). How to SHIFT consumer behaviors to be more sustainable: A literature review and guiding framework. Journal of marketing, 83(3), 22-49.
Wang, W., Chen, Z., & Kuang, J. (2025). Artificial intelligence-driven recommendations and functional food purchases: Understanding consumer decision-making. Foods, 14(6), 976.
Zhou, L., Li, L., Abbasi, A. Z., & Ahmad, W. (2026). Digital financial literacy and quality of life: the moderating role of smartphone addiction and financial stress. The Journal of Risk Finance, 27(1), 1-22.
Zheng, Z., Tan, Q. L., Zheng, X., & Yang, Y. (2025). The Dark Side of AI in Insurance: A Systematic Review of Mechanisms Linking AI Design Features to Consumer Harm. Journal of Consumer Affairs, 59(4), e70034.
Downloads
Publicado
Edição
Seção
Licença
Esta obra está licenciada sob uma licença Creative Commons Atribuição - No comercial - Sin derivaciones 4.0 Internacional
1.O(s) autor(es) autoriza(m) a publicação do artigo na revista;
2.O(s) autor(es) garante(m) que a contribuição é original e inédita e que não está em processo de avaliação em outra(s) revista(s);
3.A revista não se responsabiliza pelas opiniões, ideias e conceitos emitidos nos textos, por serem de inteira responsabilidade de seu(s) autor(es);
4.É reservado aos editores o direito de proceder ajustes textuais e de adequação do artigos às normas da publicação.
1.1 Copyright Statement
This journal is licensed under a Creative Commons Attribution-Non Commercial-No Derivers 4.0 International license.
1. The author (s) authorize the publication of the article in the journal;
2. The author (s) warrant that the contribution is original and unpublished and is not in the process of being evaluated in other journal (s);
3. The journal is not responsible for the opinions, ideas and concepts emitted in the texts, as they are the sole responsibility of its author (s);
4. The editors are entitled to make textual adjustments and to adapt the articles to the standards of publication.
