This study critically reexamines Herbert Marcuse’s concepts—false needs, technological rationality, and repressive desublimation—within digital platform consumption. Although Marcuse never addressed marketing, his critical theory offers a lens for understanding algorithmic desire engineering. The paper reconstructs these concepts, integrating them with surveillance capitalism, algorithmic culture, and platform studies, to assess their explanatory power and limitations. Findings reveal that false needs are now dynamically reproduced through user-algorithm feedback loops (dynamic reproduction). Technological rationality has evolved into “algorithmic rationality” with three features: black-box opacity, real-time adaptability, and gamified surveillance internalization. Six critical gaps are identified: difficulty distinguishing true/false needs, passive subject representation, Eurocentrism, absence of concrete alternatives, neglect of intersectionality (gender/race/ecology), and crisis of ideology critique in black boxes. Despite these, a reconstructed Marcuse remains vital for showing how platform consumption narrows desire horizons. The paper proposes an “algorithmic-multidimensional subject” acknowledging structural domination and micro-agencies, and outlines future research agendas. It concludes that Marcuse’s theory, reflexively updated, provides a normative foundation for challenging algorithmic engineering of desire.

Keywords: False Needs, Algorithmic Rationality, Herbert Marcuse, Platform Consumption, Consumer Behavior


Introduction
Consumer Behavior Encompasses Mental, Social, And Cultural Actions Before, During, And After Purchase (Solomon, 2020). In Contemporary Society, Consumption Is No Longer Merely A Response To Scarcity But A Means Of Constructing Identity, Status, And Social Belonging (Belk, 2014). Commodities Transcend Their Material Function And Become Cultural Signifiers, Making Consumer Behavior A Crucial Subject For Humanistic Inquiry. Although Herbert Marcuse Never Directly Wrote About Marketing, His Concepts—False Needs, Technological Rationality, Repressive Desublimation, And One-Dimensional Man—Offer A Potent Analytical Framework For Understanding How Algorithmic Systems Engineer Desire, Attention, And Identity. The Central Research Question Is: How Can Marcuse’s Key Concepts Be Reconstructed And Integrated With Contemporary Critical Theories To Simultaneously Illuminate Hidden Dimensions Of Domination In Platform Consumption And Expose Fundamental Ruptures Requiring Correction?

Materials And Methods
The Research Employs A Critical-Theoretical Analysis, Synthesizing A Close Re-Reading Of Marcuse’s Original Texts (Marcuse, 1964; Kellner, 1984) With A Wide Range Of Secondary Literature From Consumer Culture Theory (Arnould & Thompson, 2005; Askegaard & Linnet, 2011), Platform Studies (Srnicek, 2017; Seaver, 2019), Surveillance Capitalism (Zuboff, 2019), Critical Algorithm Studies (Bucher, 2018; Pasquale, 2015), And Empirical Findings On Algorithmic Feedback Loops, Gamification, And Digital Surveillance (Matraf & Gawas, 2025; Duan, 2026; Kanbay Et Al., 2026; Liu & Gómez-Cruz, 2025). The Methodological Approach Involves: (1) Reconstructing Five Foundational Marcusean Concepts—Commodity Fetishism, False Needs, Technological Rationality, Repressive Desublimation, And The Great Refusal; (2) Juxtaposing Them With Contemporary Platform Dynamics To Assess Their Explanatory Power; (3) Systematically Identifying Six Fundamental Theoretical Ruptures That Challenge Direct Application; And (4) Proposing A Reconceptualised Framework That Preserves Critical Insight While Addressing Gaps Through Integration With Feminist, Postcolonial, Ecological, And Intersectional Perspectives. This Approach Acknowledges That Consumer Behavior Cannot Be Reduced To Quantitative Indicators But Requires Humanistic Understanding Of Meaning, Culture, And Power (Dilthey, 1989; Nussbaum, 2010).

Discussion And Results
The Analysis Reveals That Marcuse’s Concept Of False Needs Requires Substantial Updating For The Platform Era. False Needs Are No Longer Merely Imposed Externally Through Mass Media But Are Dynamically Reproduced Through Continuous User-Algorithm Feedback Loops. In This Model, The Consumer Simultaneously Serves As The Subject Of Engineered Desire And The Data Source That Refines Its Engineering. Empirical Work By Matraf And Gawas (2025) Shows That Time Spent On Social Media Correlates With Purchase Intention (58.3% Mediation), With Demographic Variables Showing No Significant Effect—Aligning With Marcuse’s Description Of False Needs As Transcending Class Boundaries.
Technological Rationality Has Evolved Into “Algorithmic Rationality,” Distinguished From Its Industrial Predecessor By Three Qualitative Shifts: Fundamental Black-Box Opacity (Algorithms Operate Invisibly Unlike Observable Machinery); Dynamic Real-Time Adaptability (Each User Interaction Redefines The System, Creating Filter Bubbles That Narrow Choice); And Internalization Of Surveillance Through Gamification (Control Becomes Ostensibly Voluntary And Pleasurable, As Seen In Fitness Apps Or Gig Platforms). Furthermore, Algorithmic Rationality Operates Through Hidden Class Segmentation: Affluent Users With Premium Subscriptions Experience Milder Control, While Disadvantaged Classes Face The Most Intense Data Extraction And Desire Manipulation.
The Study Further Identifies Six Critical Gaps In Marcuse’s Framework: (1) Profound Difficulty Distinguishing True From False Needs In Hyper-Personalized Media—However, From Marcuse’s Perspective, This Difficulty Signals The Success Of Domination, Not The Invalidity Of The Distinction; (2) Passive Representation Of The Subject Neglecting “Platform Cynicism” And Micro-Resistance—Yet These Micro-Agencies Often Get Absorbed Into The System, Leading To The Proposal Of An “Algorithmic-Multidimensional Subject” Who Experiences Fleeting Agency Within Structural Domination; (3) Eurocentric Bias Failing To Account For Consumption Patterns In Peripheral Societies Where Commodities Often Represent Basic Subsistence Rather Than Status-Seeking; (4) Absence Of Concrete Institutional Alternatives, Leaving The Great Refusal Abstract And Individualistic; (5) Neglect Of Intersecting Dimensions Of Power—Gender, Race, And Ecology—Which Are Reproduced Through Algorithmic Biases And Ecological Overconsumption; And (6) Crisis Of Ideology Critique Given The Inscrutability Of Algorithmic Black Boxes, Requiring New Methods Like Reverse Engineering And Field Experiments.
Despite These Limitations, A Critically Reconstructed Marcuse Remains Essential For Illuminating How Platform Consumption Narrows The Horizon Of Desire And Precludes Imagining Systemic Alternatives.
Conclusion
This Paper Demonstrates That Marcuse’s Critical Theory, When Reflexively Updated, Provides A Powerful Normative And Analytical Foundation For Understanding And Challenging The Engineering Of Desire In Platform Capitalism. Three Key Conceptual Innovations Are Introduced: (1) “Dynamic Reproduction” Of False Needs Through User-Algorithm Loops; (2) “Algorithmic Rationality” With Black-Box Opacity, Adaptability, And Gamified Surveillance; And (3) The “Algorithmic-Multidimensional Subject” That Acknowledges Both Structural Domination And Micro-Agencies. However, The Six Identified Ruptures Necessitate Bridging Through Methodological Innovation, Comparative Non-Western Research, Institutional Alternatives (Platform Cooperatives, Data Commons), Intersectional-Ecological Integration, And New Methods For Ideology Critique Focusing On Algorithmic Outputs. Future Research Should Develop Multidimensional Empirical Scales For False-Need Measurement, Employ Algorithmic Ethnography, Investigate Platform Cooperatives As Concrete Forms Of The Great Refusal, And Advance Black-Box Bypassing Methods. Ultimately, The Humanities—Philosophy, Social History, And Critical Theory—Are Foundational To Understanding Contemporary Consumption Because Choices, However Free They Appear, Are Normatively Shaped And Systematically Steered. The Path Forward Is Neither Ideological Defense Of Marcuse Nor Simple Rejection, But Critical Reconstruction And Synthesis With Other Theoretical Traditions—A Synthesis That Can Deepen Theoretical Understanding And Open Practical Horizons For Reducing Data Alienation And False Needs.