Four Layers Asymmetric Economy Model

4-Layer Asymmetric Economy Model: Rethinking Stratified Productivity and Interconnectivity in Indonesia's Fragmented Economic Landscape

Abstract 

Indonesia's economic landscape presents a unique stratification not adequately captured by conventional dual-economy models. This paper introduces a 4-Layer Asymmetric Economy Model, consisting of (1) traditional cash-based microeconomies, (2) modern industrial sectors, (3) online platform economies, and (4) emerging AI-driven economic systems. These layers operate in parallel, often disconnected, rather than as sequential stages of economic development.

Using a conceptual and semi-empirical approach rooted in classical and contemporary economic sociology---including Lewis's dual economy, Amartya Sen's capability approach, Hernando de Soto's extralegal economy, and sociotechnical system theory---this paper identifies four novel aspects:

1. Segmentasi Non-Linear Ekonomi: Layers coexist with fragmented integration, challenging assumptions of hierarchical transformation.
2. Keadilan Lintas-Lapisan: Economic policies need to ensure fair outcomes across segments without enforcing premature homogenization.
3. AI Invisibility Trap: The rise of algorithmic governance risks marginalizing productive actors invisible to data-driven systems.
4. Stratifikasi Adaptif: Economic actors can move vertically or laterally between layers, driven by crisis response, local innovation, and platform adaptation.
The paper proposes a framework for building a resilient economic structure that absorbs labor, guarantees decent wages, and enables healthy interlayer interactions---without assuming that all units must forcibly "level up." Drawing from case observations in peri-urban Tangerang, we show how small factories and informal vendors remain detached from online and AI economies despite producing for vital supply chains.

We aim to contribute a new theoretical lens that better reflects Indonesia's pluralistic, context-sensitive economic realities, while offering policy implications for inclusive economic planning, digital adaptation, and adaptive workforce strategies.

Theoretical and Empirical Background 

1. Legacy of Dual Economy (Lewis, 1954)

The dual economy model, introduced by W. Arthur Lewis in 1954, serves as a foundational theory for understanding structural economic transitions in developing countries. Lewis proposed a dichotomous structure composed of two coexisting sectors: a traditional, labor-surplus agricultural sector and a modern, capital-intensive industrial sector. The model posits that labor migration from the traditional to the modern sector drives economic growth, facilitated by profit reinvestment in the industrial sector. As industrial productivity rises, surplus labor is gradually absorbed, leading to structural transformation and overall development.

A. Strengths and Contributions

The Lewis model provides a compelling framework for explaining:

The structural segmentation between formal and informal sectors.
Labor underemployment in rural and traditional economies.
The role of capital accumulation and reinvestment as drivers of long-term economic transformation.
Its applicability is particularly visible in economies where informal labor coexists with expanding modern industries, enabling comparative studies on productivity, income disparities, and sectoral labor mobility.

B. Limitations in the Indonesian Context

Despite its historical influence, the dual economy model presents key limitations when applied to contemporary Indonesia:

It assumes a linear and unidirectional transformation, where labor from the traditional sector inevitably moves toward the formal sector.
It fails to account for horizontal economic fragmentation, where multiple sectors (traditional, industrial, digital, and AI-based) coexist in parallel without clear functional integration.
The model overlooks the non-linear dynamics of labor shifts---such as informal actors entering platform economies without moving through formal industries.
For instance, many urban informal workers in Indonesia do not transition into factory or office work but instead jump directly into the third layer (online platforms) or remain entirely detached from both industrial and digital systems. This breaks the Lewis assumption of sequential sectoral absorption.

C. Continued Relevance and the Indonesian Fragmentation

While the dual economy model remains analytically valuable, especially in understanding income inequality and informal sector persistence, its binary framework does not adequately capture the complexity and stratification of Indonesia's economy. The persistence of a large, productive informal sector that neither supplies nor integrates with formal industry challenges the model's core assumption that the informal economy functions merely as a surplus labor reservoir.

Moreover, the emergence of multi-directional flows---e.g., layoffs from modern industry returning to informal or platform-based work---further complicates the picture. In peri-urban areas like Tangerang, for example, small-scale factories operate outside digital and banking ecosystems, contributing significantly to production yet remaining disconnected from formal data and credit systems.

In sum, Indonesia's economic landscape demands a model beyond Lewis's binary---one that reflects fragmented co-existence, partial interconnectivity, and adaptive stratification rather than a singular developmental trajectory.

2. Sociotechnical Systems Theory

Sociotechnical Systems (STS) Theory emerged in the mid-20th century, particularly from the Tavistock Institute's studies on coal mining operations in the UK. It posits that any effective system is a joint optimization of social and technical subsystems, emphasizing the interdependence between human elements (people, institutions, culture) and technological infrastructures (tools, processes, platforms). In the context of economic development, STS theory encourages a holistic approach: technology adoption must be accompanied by corresponding changes in organizational practices, skillsets, and socio-cultural norms to achieve sustainable performance.

A. Key Contribution: Technology as Embedded in Social Context

The STS perspective reframes the economy not merely as a function of production and transaction, but as a complex interplay between:

Technological systems (e.g., digital platforms, AI, automation tools),
Organizational structures (e.g., firms, cooperatives, supply chains),
Socio-cultural dimensions (e.g., norms, trust, labor habits, communication).
This triadic interaction is crucial in understanding why certain innovations succeed or fail. For example, introducing QRIS (Quick Response Code Indonesian Standard) into small warungs does not guarantee usage or inclusion unless vendors possess smartphones, digital literacy, and trust in cashless systems. STS theory thus resists technological determinism and advocates for socio-technical alignment.

B. Indonesian Context: Digital Penetration Without Deep Integration

In Indonesia, STS theory becomes particularly relevant as we observe a paradoxical coexistence: rapid digital technology expansion (e.g., fintech, marketplaces, ride-hailing apps) on one hand, and resilient traditional practices on the other. The availability of technology does not automatically yield interconnection or integration across economic layers.

Key empirical observations include:

Many informal producers (e.g., small home industries, roadside vendors) do not transition into digital supply chains, even when consumer interfaces (like online marketplaces) flourish.
Organizational misalignment: These actors often lack legal status, banking access, or logistical networks required to function in a digital economy.
Social-cognitive gaps: Mistrust of online systems, preference for face-to-face transactions, or fear of being scammed hinder broader participation.
Furthermore, STS helps explain why digitalization can widen fragmentation rather than reduce it. Platforms might create new micro-jobs (e.g., courier, driver) but do so by bypassing traditional employment protections, causing a shift rather than an elevation in labor quality.

C. Implications for Layered Economic Models

STS theory compels us to recognize that introducing technology into an economic ecosystem requires concurrent adaptations in social norms, institutional frameworks, and operational logic. In the proposed 4-layer asymmetric economy model, STS underscores the importance of designing interoperable infrastructures, shared standards, and inclusive digital literacy programs that bridge---rather than bypass---lower economic layers.

Without such alignment, technology risks reinforcing silos, where digital ecosystems become exclusive rather than connective. As such, sociotechnical mediation, not just technological innovation, is essential to creating meaningful economic integration in Indonesia's layered economy.

3. Amartya Sen -- The Capability Approach

Amartya Sen's Capability Approach, developed in the 1980s, represents a paradigm shift in economic and development thinking. Instead of evaluating development solely through income, GDP, or resource access, the capability approach emphasizes the real freedoms individuals have to live the kinds of lives they value. This includes their actual ability to pursue goals, participate in society, and access opportunities---not just the presence of goods or services.

Sen distinguishes between:

Commodities/resources (means),
Functionings (actual doings and beings),
Capabilities (the set of functionings one can choose from).
In short, economic actors should not be judged by what they have, but by what they are effectively able to do.

A. Contribution: Beyond Economic Growth Metrics

The capability approach contributes significantly to layered economic analysis by:

Reframing poverty as deprivation of capabilities, not merely income.
Highlighting how two individuals with the same resources may achieve vastly different outcomes, depending on their environment, education, health, and social context.
Promoting agency over passive welfare---recognizing people as actors, not recipients.
This view critiques economic policies that treat all agents as homogenous or assumes that equal resource distribution yields equal impact. It is particularly relevant when considering economic layers that are structurally excluded from platforms of opportunity.

B. Indonesian Context: High Productivity, Low Capability

In the Indonesian economy---particularly within the first and second layers---there exist millions of economic actors with latent productivity, but severely constrained capabilities:

A tukang kayu in Tangerang may produce furniture with high craftsmanship but has no access to digital marketplaces or design patents.
A small-scale garment home industry may meet export quality standards but lacks supply chain access and financial literacy.
Many warungs and market traders are embedded in hyperlocal economies, where trust and loyalty networks sustain business, but market expansion or modernization is nearly impossible without external intervention.
Even when technology is accessible, many actors lack capability enablers, such as:

Digital training,
Market mapping and networking,
Product innovation support,
Logistical partnerships.
This results in a phenomenon of "productivity without prosperity"---a critical blind spot in many digitalization and industrialization policies.

C. Implications for the 4-Layer Economy

Applying the capability approach to Indonesia's layered economy reveals the necessity of layer-specific capability building, rather than enforcing blanket "upgrading" policies. Rather than pushing small traders to become tech-savvy entrepreneurs overnight, policies should:

Enhance existing strengths (e.g., craftsmanship, community trust, cultural assets),
Provide selective access to market expansion tools,
Invest in intermediary institutions that translate between layers (e.g., cooperatives with digital arms, tech-enabled traditional markets).
This avoids "karbitan" (artificial) economic transitions that overlook the agency and context of grassroots actors. A strong, inclusive economy does not require every actor to enter the digital layer, but rather ensures that each actor has meaningful options to participate and benefit according to their strengths and aspirations.

4. Hernando de Soto -- The Extralegal Economy

Hernando de Soto's work on the extralegal economy, particularly through his influential book "The Mystery of Capital" (2000), challenges mainstream assumptions that informal economies are inherently disorganized or inefficient. Instead, de Soto argues that many informal economic systems---especially in developing countries---are governed by robust but undocumented legal and organizational norms, operating outside the purview of state regulation and official economic metrics.

This perspective shifts the focus from simply formalizing the informal sector, to understanding and recognizing the legitimacy and logic of extralegal systems, many of which are deeply embedded in social networks, customary laws, and localized trust-based arrangements.

A. Core Contribution: Informality as a Parallel Order

De Soto's theory asserts that informal economies are not devoid of structure; they are highly ordered yet extralegal. Key insights include:

Informal entrepreneurs often have property, businesses, and networks, but lack formal recognition (e.g., land titles, business licenses).
This lack of documentation limits their ability to leverage assets for growth (e.g., securing credit, scaling up operations, entering supply chains).
Informality persists not due to laziness or ignorance, but because formal systems are often inaccessible, costly, or unresponsive to local realities.
De Soto's thesis reframes the informal economy as a legitimate economic space that is invisible to formal systems---not because it lacks value, but because it lacks legal legibility.

B. Indonesian Context: Invisible Entrepreneurs in the AI Age

In Indonesia, the extralegal economy is not only large but structurally resilient. From street food vendors to small-scale manufacturing clusters in peri-urban areas like Tangerang or Bekasi, vast segments of the workforce operate in a realm that is:

Productive, yet disconnected from banking systems, taxation frameworks, or business databases;
Relational, relying on community ties, kinship networks, and mutual obligations;
Underrepresented, meaning that even AI-based financial systems or credit-scoring algorithms cannot detect or assess their existence.
This poses a major implication: algorithmic systems trained on formal data inherently exclude these actors. For example:

AI credit models trained on banking transactions will score informal businesses as "non-existent" or "high risk" due to lack of documentation.
Public policy interventions driven by big data may overlook entire communities, leading to skewed targeting and inefficient resource allocation.
As Indonesia increasingly embraces digital government services, AI-driven finance, and algorithmic marketplaces, the extralegal economy becomes even more marginalized by invisibility---not by design, but by default.

C. Implications for the 4-Layer Asymmetric Economy Model

De Soto's insights emphasize that any inclusive economic model must go beyond legal/formal registration and instead:

Design interoperable documentation systems that recognize customary titles, oral contracts, or community-based enterprise records.
Ensure that AI systems and financial algorithms are trained on diversified, context-aware datasets---including proxies for informal economic activity.
Build "formalization bridges", such as cooperative credit unions, digital identity solutions for street vendors, or semi-formal clusters that enable soft entry into Layer 3 (digital platforms) without disrupting Layer 1 dynamics.
The 4-Layer Asymmetric Economy model gains conceptual strength by incorporating extralegal visibility mechanisms, ensuring that digital modernization and AI integration do not unintentionally deepen structural exclusion. Recognizing the extralegal does not mean avoiding modernization---it means building it on a foundation that includes the invisible majority.

5. Adaptive Stratification and the COVID-19 Pandemic

The COVID-19 pandemic brought a sudden and massive disruption to global economic systems, laying bare the flexibility and fragility of socioeconomic stratification---especially in developing economies like Indonesia. Rather than reinforcing a rigid class or layer-based economic order, the pandemic exposed how economic actors dynamically shifted across layers of the economy in response to changing constraints, opportunities, and technologies.

This phenomenon is best captured by the term "adaptive stratification"---a framework that highlights how individuals and enterprises do not exist in static economic categories (e.g., informal vs. formal), but rather exhibit contextual mobility across the multiple layers of the economy based on shocks, digital access, and livelihood strategies.

A. Core Insight: Economic Layers Are Not Fixed Classes

Traditional economic stratification often implies a linear hierarchy---from low-skilled informal work to high-skilled formal employment, from physical to digital economy, from analog to algorithmic. However, the COVID-19 crisis disrupted this view:

Many actors in the Layer 1 and 2 economies (traditional and industrial) adopted digital strategies not as a deliberate upgrade but as a survival mechanism.
The notion of "moving up the economic ladder" gave way to situational diversification and improvisation, where actors operate simultaneously across multiple layers.
This contrasts with theories that view economic modernization as a unidirectional or staged process. The pandemic revealed that actors often jump layers temporarily, or even expand laterally, without abandoning their original economic base.

B. Empirical Examples from the Indonesian Economy

Several real-world adaptations illustrate the concept of adaptive stratification during the pandemic:

Online motorcycle taxi (ojek online) drivers began offering informal delivery services, selling homemade food or groceries via WhatsApp and social media---blending Layer 3 (digital platform) with Layer 1 (informal selling).
Street vendors and food stall operators who previously relied solely on cash transactions adopted QRIS (Quick Response Code Indonesian Standard) and digital wallets such as GoPay and OVO, integrating partially into Layer 4 (AI- and data-driven economy) without fully exiting the cash-based Layer 1.
Small retail shops or warungs with no digital presence began listing their products on Tokopedia, Shopee, or social commerce platforms, often using intermediaries or family members to manage digital interfaces while maintaining physical operations.
These shifts were not permanent transformations, but rather adaptive strategies based on necessity, exposure, and the social context of digital use. Many actors reverted to their previous models after pandemic restrictions eased, while others retained hybrid forms.

C. Implications for the 4-Layer Asymmetric Economy Model

The pandemic underscores a key premise of the 4-layer asymmetric economy model: the layers do not represent linear developmental stages, but coexisting modes of production, transaction, and interaction that individuals and enterprises move between dynamically.

Key takeaways include:

Economic policies must not assume rigid strata, but should be designed to support interlayer mobility---both upward and lateral---especially during periods of crisis.
Technology diffusion policies must account for situational access and usage, not just device ownership or digital literacy in abstract.
Adaptive stratification provides a conceptual framework to design resilience-focused economic strategies, where robustness comes not from full digital migration, but from layer-diversification and flexible adaptation mechanisms.
In essence, the COVID-19 pandemic acts as a real-time stress test of Indonesia's economic layering---validating the necessity of a model that acknowledges fluidity, improvisation, and co-existence, rather than static modernization narratives.

6. Field Study: Preliminary Observations in Tangerang

While macroeconomic theories and digital transformation frameworks often generalize industrial sectors as either formalized or disrupted by technology, field observations in semi-urban industrial clusters like Tangerang reveal a more nuanced reality. This region showcases a distinctive pattern of economic organization that neither fully belongs to the traditional informal sector nor has integrated into the digital or AI-based economic layers.

A. Small-Scale Factories as Hybrid Industrial Actors

In several industrial zones in Tangerang, there exists a dense concentration of small-scale manufacturing units, typically employing fewer than 100 workers. These factories produce a wide variety of essential intermediate goods---ranging from packaging materials and household hardware to textile components and food ingredients. They:

Operate legally but often informally in their financial and digital practices.
Maintain manual record-keeping and cash-based transactions.
Lack integration into digital marketplaces or formal banking analytics, thereby escaping the radar of platform-based economic data systems.
These actors blur the conventional distinction between formal and informal and highlight a unique Layer 2.5, which is industrial in structure but analog in practice.

B. Distribution and Marketing: Interpersonal, Not Digital

Rather than relying on digital platforms or AI-optimized logistics, the distribution systems for these factories' products are heavily relationship-based:

Sales and order-taking are handled by mobile salespersons (sales keliling), family members, or long-term subcontractors.
Product delivery often depends on trusted drivers (sopir langganan) who navigate city routes based on routine, not optimization algorithms.
Marketing relies on repeat orders and word-of-mouth networks, not on SEO, advertising, or digital storefronts.
This system forms a closed economic circuit---efficient in its own way, but invisible to Layers 3 and 4, which operate on data traceability and transaction formalization.

C. Structural Visibility Gap in the AI and Fintech Ecosystem

Despite their importance in real-world supply chains, these small factories are not legible to AI systems, QRIS infrastructures, or digital financial assessments. Their:

Cash-based income is not captured in credit scoring algorithms.
No online presence means they cannot be indexed, recommended, or ranked in marketplace algorithms.
Lack of transaction data makes them inaccessible for fintech products like invoice financing, digital insurance, or adaptive logistics.
This results in a form of "economic invisibility", where vital production units exist materially but not computationally, thus falling outside both digital value chains and policymaking radar.

D. Implications for Layered Economic Modeling

These empirical insights confirm the fragmentation and disconnection that characterize the 4-layer asymmetric economy. Tangerang exemplifies how:

An entire layer of productive actors can remain disconnected from digital infrastructure---not due to lack of potential, but due to mismatched incentives, path dependencies, and ecosystem design.
"Going digital" is not a universal or inevitable transition, but a process mediated by context-specific constraints such as trust networks, supply regularity, and transaction culture.
Economic modeling must therefore incorporate "unseen actors" who operate effectively yet are excluded from digital transformation metrics.
In sum, Tangerang is not an anomaly but a representative node in the Indonesian economic structure. Understanding its micro-level logic is essential for designing layered, inclusive, and non-linear economic development strategies.

1. Introduction

A. The Context of Indonesia's Stratified Economic Landscape

Indonesia's economy presents a nonlinear and stratified structure that resists simplistic categorization into binary frameworks such as formal vs. informal or urban vs. rural. Instead, the Indonesian economic landscape is best understood as a multi-layered asymmetric system, shaped by historical dualities, technological heterogeneity, institutional gaps, and cultural path dependencies. This complexity is both structural and dynamic, yielding economic strata that coexist, compete, and occasionally cooperate---yet often without integration or mutual legibility.

While traditional economic development theory assumes a progressive evolution from informal to formal, or from manual to digital, Indonesia defies this teleology. Its economic architecture can be seen as comprising four distinct layers:

1. Layer 1 -- Traditional Economy: Characterized by cash-based transactions, informal labor arrangements, and physical selling spaces such as roadside stalls, tarp-based markets, and itinerant vendors.
2. Layer 2 -- Industrial-Modern Economy: Consists of factories, offices, and banking institutions---often formalized but not necessarily digitized.
3. Layer 3 -- Digital Platform Economy: Driven by cashless systems, online marketplaces, and app-based logistics and services such as ride-hailing or e-commerce.
4. Layer 4 -- AI-Augmented Economy: Emerging economic activities enabled by artificial intelligence, algorithmic finance, and predictive market behavior---typically accessed only by tech-integrated firms or startup ecosystems.
What makes Indonesia unique is that these layers do not form a neat hierarchy, nor do they always converge over time. Instead, they often remain fragmented horizontally, with limited interoperability across platforms, regulations, and social networks. Moreover, movement between layers is not always desirable or beneficial. A traditional food vendor, for instance, might earn more and experience greater autonomy in Layer 1 than by prematurely transitioning into a digital system that imposes fees, rating pressures, and new risks.

This layered model challenges both policy orthodoxy and digital utopianism. The Indonesian case reveals that economic "upgrading" is not simply about digitization or formalization, but about preserving the productive diversity of each layer while enhancing their interconnectivity without assimilation. More importantly, it raises urgent questions regarding:

Labor absorption and wage sufficiency in each layer.
The visibility of economic actors to state and algorithmic systems.
The risk of algorithmic exclusion, where productive units remain disconnected from platforms that allocate credit, logistics, and attention.
In this context, the Indonesian economy emerges as a living laboratory for understanding layered economic resilience, asymmetric transitions, and the political economy of digital marginality. It calls for an updated theoretical lens---one that respects complexity, multiplicity, and partial integration---not merely linear development.

This paper proposes a conceptual model of the "4-Layer Asymmetric Economy", rooted in this empirical and theoretical tension. It aims to articulate a framework that can serve both as an analytical tool and a developmental vision---where inter-layer interaction is nurtured, not forced; and where visibility, viability, and value are extended to all layers without demanding homogenization.

B. The Paradox of Economic Digitalization: Reinforcing, Not Bridging, Fragmentation

Digitalization is often celebrated as a democratizing force in the economy---promising inclusion, efficiency, and upward mobility. However, in the Indonesian context, the expansion of digital platforms and AI-based systems has not uniformly bridged economic gaps; rather, it has often exacerbated stratification, creating new barriers of access and visibility while reifying older ones. This paradox challenges the dominant policy narrative that assumes technological adoption as an inherently equalizing mechanism.

The irony lies in the selective permeability of digital infrastructure. While QRIS, digital wallets, ride-hailing apps, and online marketplaces have penetrated urban and semi-urban consumer behavior, they remain unevenly adopted across labor-intensive micro-enterprises, small-scale manufacturers, and informal distributors. In many cases, actors in Layer 1 and Layer 2---those engaged in cash-based trade or semi-formal production---lack not only digital literacy or access to smartphones, but also the institutional support and design flexibility to integrate with digital platforms without compromising their autonomy or income.

Moreover, the algorithmic design of digital platforms tends to privilege actors with predictable behavior, verified documentation, and scalable logistics---features that are often absent in informal or locally embedded economic practices. This results in a form of "algorithmic invisibility": productive units that are economically active but digitally unrecognizable. In essence, digitalization creates new fault lines, where inclusion becomes conditional on compatibility with system expectations, not intrinsic economic value.

At the same time, digital transformation in Indonesia has triggered what may be called "platform-induced economic segmentation." Instead of dissolving boundaries between layers, platforms like online marketplaces or app-based delivery systems often reinforce them by:

Filtering users through digital KYC (Know Your Customer) or platform ratings.
Concentrating visibility and rewards on actors already familiar with e-commerce norms.
Embedding feedback loops that marginalize low-frequency or irregular producers and vendors.
This platform logic mirrors broader dynamics of data capitalism, where economic relevance is mediated through data traces, and those who fail to generate data---or the right kind of data---remain excluded from algorithmic recognition and credit scoring.

Consequently, digitalization has not only failed to organically connect the four layers of Indonesia's economy but has, in some instances, intensified the disjunctures between them. The result is a stratified system wherein:

Layer 1 remains materially productive but digitally invisible.
Layer 2 remains structurally embedded but technologically obsolete.
Layer 3 thrives on hyper-visibility and platform incentives.
Layer 4 begins to influence credit allocation, logistics optimization, and even labor sorting---yet based on partial data from only a fraction of the economy.
This paradox compels a rethinking of digital transformation as not merely a technological upgrade, but as a deeply political and relational process---one that can entrench inequality if not deliberately governed. Without addressing the socio-technical disjunctions between these layers, digitalization risks becoming a centrifugal force, pulling economic actors further apart rather than weaving them into a coherent, inclusive system.

C. Research Objective: Proposing the 4-Layer Asymmetric Economy Model

The principal objective of this paper is to articulate and substantiate a novel analytical framework---the 4-Layer Asymmetric Economy Model---which captures the complex co-existence, selective interconnectivity, and dynamic mobility of Indonesia's stratified economic landscape. Specifically, this model aims to:

1. Describe and Differentiate
 -- Precisely delineate the four economic layers---Traditional (Layer 1), Industrial-Modern (Layer 2), Digital Platform (Layer 3), and AI-Augmented (Layer 4)---in terms of their structural characteristics, modes of transaction, and socio-technical configurations.
2. Explain Fragmentation Dynamics
 -- Theorize why and how these layers persist in parallel rather than in a unilinear progression, identifying the socio-technical, institutional, and cultural mechanisms that reinforce horizontal segmentation.
3. Illuminate Novel Aspects of Stratification
 -- Introduce and operationalize four original dimensions of analysis---Non-Linear Segmentation, Cross-Layer Equity, AI-Invisibility Trap, and Adaptive Stratification---to capture phenomena unaddressed by extant theories such as Lewis's dual economy or standard digitalization narratives.
4. Bridge Theory and Practice
 -- Ground the framework in empirical observation (e.g., field data from peri-urban Tangerang) to demonstrate the model's applicability for diagnosing real-world production efficiencies, wage outcomes, and market access bottlenecks across layers.
5. Inform Policy and Strategy
 -- Generate actionable policy guidelines for fostering productive inter-layer linkages---ensuring decent work, fair wages, and accessible markets---without coercive "upgrading" mandates or one-size-fits-all digital interventions.
6. Guide Future Research
 -- Provide a conceptual roadmap for scholars and practitioners to test, refine, and extend the 4-Layer Asymmetric Economy Model in other regional contexts or comparative settings.
By meeting these objectives, the paper will offer a comprehensive lens for understanding and addressing the paradoxes of economic stratification in Indonesia---where productivity, dignity, and inclusion demand a framework that is both layer-sensitive and adaptively integrative.

2. Literature Review

A. Foundational Theories: Lewis, De Soto, Sen, and Sociotechnical Perspectives

The conceptual basis of this paper is situated at the intersection of four major theoretical strands---Lewis's Dual Economy Theory, De Soto's Extralegal Economy, Sen's Capability Approach, and Sociotechnical Systems Theory---each offering distinct yet complementary lenses to analyze the layered economic landscape of contemporary Indonesia.

1. Lewis's Dual Economy Theory (1954)

W. Arthur Lewis's seminal contribution distinguishes between a traditional subsistence sector and a modern capitalist sector, positing that economic development involves the gradual migration of labor from the former to the latter. This model was foundational in development economics, providing a framework to understand structural transformation.

While influential, the Lewis model tends to assume a vertical integration trajectory and fails to account for persistent horizontal fragmentation across coexisting economic layers. In the Indonesian case, the informal sector is not merely a labor surplus reservoir waiting to be absorbed by modern industry; rather, it has become a dynamic and resilient domain, often disconnected from formal industrial and digital systems. Moreover, the Lewis model presumes that technological progress will naturally bridge sectors, an assumption increasingly challenged by platform-induced segmentation and AI-mediated exclusions.

2. De Soto's Theory of the Extralegal Economy (1989)

Hernando de Soto offers a vital corrective by arguing that the informal economy is not disorganized or chaotic but rather structured by informal rules, relational contracts, and extralegal norms. The primary problem, he suggests, is the lack of formal documentation---not the absence of rationality or productivity.

De Soto's insights are highly relevant for understanding Indonesia's first two economic layers, where productive but undocumented micro-enterprises often operate outside the purview of formal financial systems, regulatory databases, or digital platforms. In the context of Layer 4---the AI-augmented economy---De Soto's critique takes on a new dimension: what is undocumented is increasingly not just unbanked but "unseen" by algorithms, leading to data invisibility traps. AI systems that rely on digital traces, legal registration, and structured metadata fail to recognize informal economic actors---even when their output is critical to supply chains.

3. Amartya Sen's Capability Approach (1999)

Sen's framework shifts focus from economic growth metrics to individual and collective capabilities---what people are actually able to do and be. Economic justice, in this view, is defined not by income alone but by access to real opportunities for well-being, choice, and agency.

In Indonesia's stratified economy, many workers and entrepreneurs in Layers 1 and 2 exhibit high productivity and deep local knowledge, yet they lack the technological capabilities and infrastructural access needed to expand markets or stabilize income. Sen's approach thus justifies a development paradigm that enhances agency across all layers, rather than enforcing linear transitions from "low" to "high" technology sectors. It also underscores the need for context-sensitive interventions that prioritize enabling conditions over imposed metrics.

4. Sociotechnical Systems Theory

Sociotechnical theory posits that economic and organizational performance is the result of an interdependent relationship between social systems (people, norms, networks) and technical systems (tools, platforms, infrastructures). Innovations fail when one domain evolves faster than the other.

This framework is critical for interpreting Indonesia's digital transformation. The introduction of Layer 3 (digital platforms) and Layer 4 (AI systems) has not yielded universal inclusion, precisely because social structures---education, trust, transaction norms---have not co-evolved at the same pace. For instance, the mere availability of QRIS does not imply its uptake among warung owners or peddlers whose trust networks rely on cash and face-to-face reciprocity. Similarly, AI-based lending systems fail to accommodate informal creditworthiness embedded in kinship or community dynamics.

Sociotechnical theory enables us to see each economic layer as not merely a "stage of development," but as a configuration of social and technical interdependencies---each with its own internal logic, vulnerabilities, and potential for cross-layer complementarity.

Together, these four theoretical pillars highlight both the promise and the pitfalls of economic transformation. They also reveal the analytical gap this paper seeks to address: the absence of a model that treats multi-layered economies not as transitional anomalies, but as structural realities in need of adaptive and integrative frameworks. This gap gives rise to the 4-Layer Asymmetric Economy Model, introduced in Section 3.

B. Unresolved Gap: Non-linear Horizontal Segmentation in the Economy

While classical and contemporary theories offer insightful frameworks to understand economic stratification, a persistent analytical blind spot remains: non-linear horizontal segmentation that characterizes economies like Indonesia's. Much of the literature continues to frame development in vertical, linear terms---from informal to formal, from rural to urban, from offline to online, or from low-tech to high-tech. These assumptions, while useful in certain contexts, fail to capture the complexity and simultaneity of multiple economic logics coexisting in one national system.

Indonesia presents a case of structural pluralism: four distinct layers of economic activity---traditional cash-based micro-economies (Layer 1), formal-industrial modernity (Layer 2), platform-mediated digital ecosystems (Layer 3), and emergent AI-augmented systems (Layer 4)---not only coexist but often function in parallel rather than in sequence. In many regions, there is no clear "upgrade path" from one layer to another. A street vendor accepting QRIS payments (Layer 1+3) may never enter formal employment (Layer 2), nor will a small family-run factory (Layer 2) be captured by algorithmic market models (Layer 4) without formal data trails.

What remains inadequately theorized is the horizontal disconnect---not between sectors (e.g., agriculture vs. manufacturing), but between layers of economic infrastructure, norms, and technologies. These layers are often marked by incompatibilities in transaction logic, knowledge systems, capital formation, and institutional support. Digitalization, far from integrating these layers, often deepens their asymmetries by privileging visibility, formality, and data-centric models.

Moreover, existing empirical work tends to isolate each layer in disciplinary silos: development economists study Layer 1; industrial economists focus on Layer 2; digital economists on Layer 3; and AI-focused analyses often neglect socioeconomic contexts altogether. Very few studies attempt to model inter-layer dynamics, especially how discontinuities and misalignments across layers affect employment absorption, wage fairness, supply chain resilience, and market access.

This paper aims to fill that gap by proposing a 4-Layer Asymmetric Economy Model that treats each layer as a distinct but interacting subsystem. We argue that economic robustness in such a stratified landscape depends not on universal formalization or linear progression, but on the healthy interconnection of diverse layers, including those that are persistently informal, analog, or relational in nature. Understanding and designing for horizontal asymmetries---rather than erasing or forcing homogenization---may offer a more grounded and effective pathway to inclusive development.

3. Conceptual Framework

A. Definition and Characteristics of Each Layer (1 to 4)

The proposed 4-Layer Asymmetric Economy Model conceptualizes the Indonesian economy as composed of four relatively autonomous but overlapping strata. Each layer represents not merely a stage of development, but a distinct socio-technical-economic regime with its own norms, infrastructures, actors, and logics of operation. Below are the core definitions and characteristics:

Layer 1: Traditional Informal Economy (Cash-Based, Relational, Ground-Level)

Definition: Economic activities that are informal, low-capital, highly relational, and primarily cash-based. This layer includes street vendors, mobile food sellers, market stall operators, and informal service providers who use minimal technology and operate outside formal regulatory systems.

Key Characteristics:

Transactional Medium: Physical cash
Workforce Profile: Low-skilled, often family-run, unregistered
Distribution Logic: Hyper-local and relational (e.g., community trust, informal networks)
Visibility: Largely invisible to formal systems (tax, banking, data)
Strengths: High adaptability, low entry barrier, social embeddedness
Constraints: Lack of protection, credit access, and upward mobility
Layer 2: Modern Industrial-Formal Economy

Definition: This layer includes formally registered businesses and factories, regulated under national labor and tax laws. It encompasses SMEs and large enterprises that operate with standardized procedures, capital investments, and formal employment.

Key Characteristics:

Transactional Medium: Banking and accounting systems
Workforce Profile: Contracted labor, structured management
Distribution Logic: Supply chain--driven (e.g., logistics, distributors, retail)
Visibility: Fully formalized, regulated, and statistically captured
Strengths: Scale efficiency, regulatory legitimacy, access to capital
Constraints: Rigid structures, high compliance cost, slow digital integration
Layer 3: Digital Platform Economy

Definition: Economic actors operating via digital platforms and marketplaces. Includes ride-hailing drivers, online sellers, freelance service providers, and MSMEs using apps like Gojek, Shopee, Tokopedia, and QRIS-enabled payments.

Key Characteristics:

Transactional Medium: Cashless (digital wallets, QR codes, mobile banking)
Workforce Profile: Platform-dependent gig workers, tech-savvy MSMEs
Distribution Logic: Algorithmic intermediation (e.g., customer ratings, search optimization)
Visibility: Data-rich but not always legally formalized
Strengths: Scalability, speed of market access, digital traceability
Constraints: Precarity, platform dependency, data asymmetry
Layer 4: AI-Augmented and Predictive Economy

Definition: The emergent layer driven by artificial intelligence, predictive analytics, and automation. Includes fintech credit scoring, AI-based logistics, autonomous production systems, and algorithmic policy interventions.

Key Characteristics:

Transactional Medium: Data-driven predictions, API-based ecosystems
Workforce Profile: Highly skilled tech professionals; marginalization of analog labor
Distribution Logic: Autonomous or semi-autonomous decision systems (e.g., recommendation engines, predictive pricing)
Visibility: Hyper-visible to systems but selectively inclusive
Strengths: Efficiency, foresight, integration across markets
Constraints: High entry barriers, digital exclusion, systemic opacity
Each layer does not automatically replace or upgrade the previous one; instead, they often coexist in spatial, economic, and relational silos. The strength of the Indonesian economy lies in managing the frictions and potential synergies among these layers---recognizing that not all economic actors aim (or are able) to "move up," and that cross-layer integration must be intentional, context-sensitive, and equity-driven.

B. Interactions Between Layers: Segmentative, Parallel, Non-Hierarchical

The prevailing assumption in many economic development models is that informal or traditional sectors will, over time, "graduate" into more formalized or digital layers---a linear and hierarchical progression. However, empirical realities in Indonesia challenge this model. The 4-Layer Asymmetric Economy Model posits that these layers interact in non-hierarchical, parallel, and segmentative ways.

1. Non-Linear Progression

The four layers do not represent a linear staircase of development from "primitive" to "advanced." Many actors in Layer 1 (traditional economy) remain productive and profitable without ever transitioning to Layer 2 (industrial economy) or Layer 3 (digital platforms). Similarly, actors in Layer 2 may not adopt Layer 4 (AI-based systems) due to high complexity or misalignment with operational needs.

This calls into question development narratives that implicitly regard digitization or formalization as the sole trajectory of progress.

2. Segmentative Structure

Each layer is characterized by a self-sustaining internal logic---regarding labor organization, transactional tools, technological interface, and market relations. These logics do not necessarily intersect or flow naturally into one another. For example:

A small family-run food stall (Layer 1) may continue to thrive in a cash economy despite proximity to Layer 3's cashless customers.
A small factory (Layer 2) may operate with a formal structure but rely entirely on Layer 1's informal logistics and sales agents.
This segmentative reality creates friction and asymmetry in economic policymaking, as efforts to scale up or integrate sectors may overlook the incommensurability of their underlying systems.

3. Parallel and Selective Interaction

While layers can and do interact, the connections are often selective, conditional, and asymmetric. For example:

A Layer 3 merchant selling on Shopee might source goods from a Layer 2 factory, but the factory itself may lack any digital presence.
A Layer 4 fintech application may offer microloans to Layer 1 street vendors using behavioral AI, yet without recognizing the vendor's actual market conditions or social capital.
QRIS adoption by a traditional vendor doesn't imply digital market integration---it may serve only as a payment tool, not a shift in business model.
These parallel flows of value, goods, and information signal that Indonesia's economy is not converging into a single digital economy, but expanding outward into multiple concurrent economies.

4. Implications for Policy and Theory

This segmentative-parallel model demands a departure from monolithic economic strategies such as "digital transformation" or "formalization." Instead, it requires:

Layer-aware interventions that respect the autonomy and logic of each layer;
Bridging infrastructure that enables soft interconnections without forced assimilation;
Recognition of economic plurality as a strength, not a problem to be homogenized.
The Indonesian economy thus functions more like an ecosystem with diverse biomes rather than a factory assembly line. A healthy system is not one where all agents are forced into one model, but one where multiple models coexist, coordinate, and adaptively evolve.

C. Four Novel Contributions of the 4-Layer Asymmetric Economy Model

The proposed 4-Layer Asymmetric Economy Model offers four key areas of novelty that address theoretical, empirical, and policy-level gaps in the current literature on development economics and digital transformation in emerging economies such as Indonesia.

1. Horizontal Stratification Beyond Formal--Informal Binary

Existing Gap: Classical models such as Lewis's dual economy, or de Soto's extralegal frameworks, tend to focus on vertical dichotomies---formal vs informal, documented vs undocumented.
 Novelty: This model introduces horizontal stratification across four overlapping but segmentative layers, where actors in different layers are not distinguished merely by legality/formality, but by mode of operation, transaction system, market orientation, and technological embedding.

Each layer has:

ts own time logic (e.g., daily cashflow vs quarterly reporting)
Its own spatial embeddedness (mobile vendor vs cloud-based seller)
Its own trust mechanism (personal credit vs algorithmic credit scoring)
This nuanced mapping allows for better understanding of frictional zones where digital policies fail to touch informal actors---not due to resistance, but due to systemic misfit.

2. Decentralized and Non-Hierarchical Value Creation

Existing Assumption: Most development frameworks implicitly prioritize upward mobility---"moving up" from Layer 1 to Layer 4 is assumed desirable and linear.
 Novelty: Our model recognizes that value can be generated in all layers, with no single layer inherently superior. For example:

A street vendor (Layer 1) may have higher net cashflow and household impact than a small tech startup (Layer 4).
A factory in Layer 2 may be critical for supply chain resilience, even without digital visibility.
This de-hierarchization of value is especially relevant in the Indonesian context, where Layer 1 and Layer 2 actors may remain persistently productive without transitioning to digital or AI economies. It opens new debates on what counts as 'progress' in a plural economy.

3. Layer-Specific Labor Absorption and Livelihood Dynamics

Existing Blind Spot: Digital economy discourses often celebrate growth, but overlook net labor absorption, wage stability, or social protection.
 Novelty: This model foregrounds how each layer interacts with labor in distinct ways:

Layer 1: High labor absorption, low wage volatility, minimal barriers to entry, but lacks protection.
Layer 2: Moderate wage, medium formality, but vulnerable to shocks due to dependence on export or supply-chain integration.
Layer 3: Gig-based volatility and platform dependency.
Layer 4: Skill-intensive, capital-intensive, low absorption but high productivity per capita.
This classification enables policy focus on layer-sensible employment interventions, rather than assuming digitalization will automatically solve employment issues.

4. Interoperability Without Forced Assimilation

Existing Policy Limitation: Most integration efforts seek to "formalize" or "digitize" informal sectors without understanding their internal logic.
Novelty: This model promotes soft interoperability, i.e., enabling interaction across layers without requiring assimilation into a dominant logic.

For instance:

QRIS can be adopted by a vendor without forcing them to register a legal business entity.
AI credit scoring can be improved by integrating informal transaction records, not erasing them.
This opens the way for multi-systems coordination---an idea more in line with adaptive systems theory than classical linear integration.

Synthesis

The 4-Layer Asymmetric Economy Model reframes Indonesia's economic complexity not as a developmental "problem" but as a systemic ecology of diverse economic practices. Its novelty lies in:

Displacing vertical assumptions with horizontal recognition,
Embracing plural value systems,
Centering labor and livelihoods beyond productivity,
Designing for interoperability over uniformity.
This framework aims to inform both economic theorists and policy architects in rethinking how transformation, inclusion, and productivity are conceptualized and operationalized in stratified emerging economies.

4. Case Observation: Tangerang's Fragmented Factories

A. Description of Small Factories and Local Microeconomy

The city of Tangerang, located within the rapidly urbanizing Jabodetabek metropolitan area, presents a compelling microcosm for observing the disjunctions and asymmetries of Indonesia's layered economy. Despite its proximity to major industrial hubs and international supply chains, a significant portion of Tangerang's productive sector remains anchored in small-scale manufacturing, often operating below the radar of formal economic metrics.

Key Characteristics of Small Factories in Tangerang:

1. Scale and Structure
The majority of observed manufacturing units operate with fewer than 100 workers.
Production spaces are often residential or semi-residential in nature, with makeshift factory setups in converted homes, warehouses, or alley-based workshops.
Legal status is frequently informal or semi-formal---registered only at local neighborhood or sub-district level, lacking full compliance with provincial or national industrial permits.
2. Product Types
These factories produce a wide range of goods, including plastic packaging, spare parts, construction materials, household goods, and garment subcomponents.
Products are often critical support nodes in larger supply chains (e.g., food packaging, footwear accessories), yet their contribution is invisible to most AI-based supply chain optimization systems or national productivity statistics.
3. Operational Modality
Business operations are family-based or kinship-centered, often relying on social trust rather than contracts.
Capital flow is predominantly cash-based, with limited access to formal credit or insurance.
Inventory and logistics are managed through driver-based distribution, informal sales networks, and manual accounting, bypassing Layers 3 and 4 entirely.
4. Market Orientation and Sales
These factories typically do not engage with online marketplaces such as Tokopedia, Shopee, or B2B procurement platforms.
Sales are handled via offline business relationships, often forged over years with other local or regional SMEs.
Most owners and operators have little incentive or capacity to digitalize, despite being productive and integrated in real terms.
5. Technological Interface
Basic production equipment is used, often without digital control systems.
There is no integration with IoT, ERP, or AI-based systems. Even basic QRIS payment tools are rare.
Any form of digital technology adoption (e.g., using WhatsApp for orders, or mobile banking for suppliers) is often done personally, not institutionally.

Implication in the 4-Layer Model Context

In terms of the proposed 4-Layer Asymmetric Economy Model, these factories straddle Layer 1 and Layer 2. They operate with the labor intensity and cash modality of Layer 1, yet are involved in product manufacturing and distribution usually attributed to Layer 2.

However, their absence from Layer 3 (digital marketplaces) and Layer 4 (AI integration) means:

They are structurally disconnected from national narratives of digital transformation.
Their role is underrepresented in productivity discourse.
They are vulnerable to exclusion in policy designs based on algorithmic data visibility.
Conclusion

Tangerang's fragmented factories challenge the notion that industrialization and digitalization naturally evolve in tandem. These units sustain local employment, produce critical goods, and demonstrate economic resilience, but remain outside dominant digital-economic frameworks. They exemplify the layer disconnection and asymmetric visibility that the 4-Layer Economy Model seeks to explain and reformulate.

B. Disconnection from Layer 3 and 4: Platform Economy and AI Integration

The small-scale factories of Tangerang offer an illustrative case of a structural disconnect from the upper layers of Indonesia's evolving digital economy---specifically Layer 3 (Digital Market Platforms) and Layer 4 (AI-Driven Economic Systems). While productive and locally embedded, these enterprises operate in a parallel modality, largely insulated from the technological infrastructures that are driving economic narratives and policies at the national level.

1. Absence from Layer 3: Digital Platform Economy

Lack of E-commerce Engagement
 Despite being producers of physical goods, most of these factories do not sell through online marketplaces such as Tokopedia, Bukalapak, or Shopee.
Their clients are typically offline B2B buyers, repeat customers, or personal contacts.
Payment Systems
Cash transactions remain dominant. QRIS, e-wallets, and digital invoicing are rare or used only personally (e.g., by owner for personal expenses), not as business infrastructure.
This effectively limits their data traceability, which is a prerequisite for inclusion in digital economic planning.
Logistics Disjunction
Distribution relies on manual routing, freelance drivers, or personal delivery rather than being integrated into smart logistics platforms like Gojek/Grab/Kurir API systems.
This further widens the gap from marketplace visibility and real-time supply chain feedback systems.
2. Absence from Layer 4: AI-Integrated Economy

No Formal Digital Footprint
These businesses often do not register on AI-based credit scoring systems, supply-chain optimization algorithms, or business intelligence platforms.
From an AI system's perspective, they don't exist---they are data-invisible.
Limited Data Generation
Without digitized accounting, sales, logistics, or HR systems, there is minimal structured data that can be mined or modeled for optimization, investment decisions, or inclusion in productivity metrics.
No Algorithmic Interaction
Unlike digital-native enterprises whose operations are intertwined with algorithms (e.g., ride-hailing demand prediction, dynamic pricing, platform ranking), these factories are not participants in algorithmic economies.
As a result, their operations are excluded from AI-enhanced opportunity structures, such as automated procurement, AI-based product recommendation, or targeted policy interventions.

Systemic Implication

This disconnection is not merely a technological lag, but a reflection of institutional and epistemological exclusion:

Economic actors who are not legible to the datafied economy are structurally under-served.
Policies based on digital data may systematically overlook productive sectors that are non-digital, leading to misallocation of subsidies, credit, and development programs.

Reframing the Narrative

Contrary to conventional development models that push for vertical "graduation" from informal to formal, or analog to digital, the 4-Layer Asymmetric Economy Model emphasizes the need for:

Horizontal interconnectivity, not forced linearity.
Digital intermediation mechanisms that can make such Layer 1--2 actors visible and valuable without full absorption into platform or AI logic.
Pluralistic economic legitimacy, where different modalities of productivity are acknowledged and supported based on outcome, not merely digital traceability.

C. Effects on Productivity, Wages, and Market Access

The disconnection from Layer 3 and 4 in Tangerang's micro-factory ecosystem creates a distinct set of economic consequences that constrain upward mobility and system-wide efficiency. Despite the high activity level in terms of labor input and output volume, these actors remain sub-optimally positioned in the broader value chain. This manifests in three interrelated outcomes: limited productivity gains, wage stagnation, and market isolation.

1. Stagnant or Sub-optimal Productivity

No Automation or AI Integration
The absence of connection to digital platforms and AI tools results in minimal productivity scaling. Most processes are manual and labor-intensive, and any efficiency improvement relies on experience or improvisation, not systemic optimization.
Inaccessibility of Technology Transfer
New production technologies---such as predictive maintenance, digital inventory systems, or AI-aided quality control---do not reach these factories, due to both cost and lack of exposure. This entrenches a low-tech trap, where labor output is capped and learning curves flatten early.
No Feedback Loops from Market Data
Because they are disconnected from customer-facing platforms, market feedback and trend data are inaccessible. Factories often produce based on historical demand or verbal contracts, not real-time analytics, which limits innovation and responsiveness.
2. Wage Constraints and Precarity

Low Value Capture
Despite producing critical intermediate goods (e.g., parts, raw textiles, packaging), the lack of formal contracts and branding results in low bargaining power. Hence, the value-added is not retained locally, and wages remain at or below subsistence level.
No Performance-based Scaling
Without integration into a measurable system (as seen in Layer 3 & 4 economies), labor is not tied to quantifiable performance. There is no mechanism for wage incentives, productivity bonuses, or profit-sharing.
High Labor Intensity without Social Protection
Informal labor structures dominate. Workers in these factories often lack health insurance, pension contributions, or union representation, leading to heightened economic vulnerability.
3. Constrained Market Access and Revenue Volatility

Geographically Narrow Markets
Distribution is hyper-local or dependent on traditional wholesale buyers. There is no long-tail market access, unlike Layer 3 actors who can reach national or international customers via digital platforms.
No Brand Presence or Digital Identity
These factories do not possess brand assets that could be leveraged for consumer trust or product differentiation. Their invisibility on digital platforms reduces demand elasticity and repeat purchase incentives.
Exposure to Demand Shocks
Lack of diversified channels makes these businesses vulnerable to abrupt shifts, such as buyer withdrawal, raw material delay, or regulatory crackdowns---without the buffering effect that platform-based actors may enjoy.

Synthesis: Structural Exclusion from the Productivity Loop

The factories in question exhibit what we term as "bounded productivity islands": they are productive within their internal loops but disconnected from the systemic mechanisms that enable scale, reward, and resilience. The overall effect is not merely inefficiency, but structural asymmetry---where productivity does not translate into better income or wider markets due to institutional and technological disjuncture.

This strengthens the case for a non-hierarchical integration strategy proposed by the 4-Layer Asymmetric Economy Model:
Rather than forcing these actors to prematurely "graduate" into Layer 3 or 4, we argue for the creation of adaptive interfaces---technological and institutional bridges that allow cross-layer transactionality, recognition, and support.

5. Policy Design and Interlayer Strategy

A. Adaptive Interconnection Instead of Forced Upgrading

Problem Statement:

The prevailing development paradigm in many policy circles implicitly assumes that economic actors in lower layers must "graduate" into higher layers---moving from informal or traditional modes of production to formal, digitalized, and AI-integrated systems. This linear and hierarchical assumption often fails in practice, especially in economies with persistent structural fragmentation like Indonesia.

As our observations in Tangerang and other similar ecosystems show, not all micro-actors are in a position to scale up or digitalize in a short timeframe. Moreover, forced transitions can disrupt existing social and economic ties, create technological debt, and erode organic market linkages that are locally resilient.

Policy Proposition: Adaptive Interconnection Framework

We propose a shift from the ideology of "upgrade or perish" to a model of adaptive interconnection, in which each economic layer (1 through 4) is enabled to interact symbiotically with others, without necessarily transforming its structural identity. This policy approach acknowledges the plurality of economic rationalities, production logics, and organizational forms.

Key Principles of the Approach:

1. Pluralist Legitimacy
All economic forms---traditional stalls, informal factories, online gig work, and AI-driven platforms---are recognized as legitimate contributors to the economy. Policy should not prioritize formality over functionality.
2. Interoperable Systems
Instead of enforcing digital literacy or QRIS usage as a precondition, systems can be designed to interoperate through mediating agents, such as trusted intermediaries, cooperatives, or hybrid platforms.
Example: A micro-distributor app that allows Layer 1 or 2 actors to plug into Layer 3 marketplaces via a proxy account or group representative.
3. Soft Interfaces, Not Hard Requirements
Policy should create soft interfaces that allow micro-actors to partially connect---e.g., enabling QRIS payments without full bank onboarding, or using voice-based AI for order placement by low-literacy actors.
4. Reverse Flow of Value
Higher-layer systems (e.g., Layer 4 AI economies) should be encouraged or incentivized to build backward linkages---sourcing inputs from traditional producers, investing in informal sectors, or integrating alternative credit scoring for small-scale actors.

Implementation Channels:

Regulatory Sandboxes for Mixed-Economy Systems
Establish zones where Layer 1--4 actors can co-exist and experiment with interconnectivity solutions under relaxed regulatory frameworks.
Data Dignity Platforms
Develop mechanisms where informal actors can voluntarily share data (e.g., transaction histories, production volumes) through trusted third parties, enabling visibility without full formalization.
Fiscal Incentives for Interlayer Cooperation
Offer tax breaks, grants, or soft loans to businesses or startups that design models intentionally bridging Layers 1--2 with Layers 3--4.
Interlayer Incubation Hubs
Public-private partnerships to create local hubs that foster co-presence and co-production between economic actors from different layers, building trust and technical affordances in context.

Outcomes Expected:

Increased transactionality across economic layers without forcing identity shifts.
Expanded labor absorption, especially in layers 1 and 2, through indirect digital integration.
Market broadening as traditional producers reach digital consumers via intermediated systems.
Improved inclusivity of national AI and fintech ecosystems, which currently miss large swaths of productive actors.

B. Context-Based Mechanisms for Technology and Policy Distribution

Rationale:

Top-down technological diffusion and uniform policy implementation often ignore the local heterogeneity of economic actors. In stratified economies like Indonesia's, where different layers coexist with vastly different resources, skills, and logics, context-free distribution of technology or policy can deepen exclusion. Layer 1 and 2 actors, in particular, risk being left behind---not due to lack of capability, but due to misalignment of delivery modes.

To address this, we propose a context-sensitive distribution mechanism, rooted in anthropological, sociotechnical, and behavioral insights, to ensure technologies and policies resonate with the lived realities of each economic layer.

1. Modular Technology Packages ("Teknologi Bertingkat")

Instead of deploying monolithic, one-size-fits-all tools, design tiered technology packages that match the infrastructure and social capacity of each layer:

Layer 1 (Traditional):
Low-tech tools such as SMS-based transaction records, solar-powered POS devices, verbal interface order systems.
Layer 2 (Proto-industrial):
Modular ERP systems with offline syncing, basic digital ledgers, hybrid logistic tracking based on human input.
Layer 3 (Digitized):
Intermediary marketplaces with adaptive onboarding for semi-formal producers, tax reporting modules with informality tolerance.
Layer 4 (AI-driven):
Algorithms that actively search for and integrate low-visibility suppliers, with contextual data parsing and uncertainty handling.
2. Localized Policy Design: Desa, Kecamatan, Klaster

Adopt a meso-level governance model in which policy instruments are tailored at the district or cluster level, with mechanisms such as:

Participatory Tech Mapping:
Engage local actors to co-map their economic ecosystems, infrastructure gaps, and interlayer potentials.
Cross-Layer Policy Forums:
Regular dialogue platforms where representatives of different layers identify bottlenecks, enabling bottom-up insight incorporation.
Adaptive Subsidy Frameworks:
Move from fixed subsidies to behavior-based or milestone-triggered incentives that respond to contextual change (e.g., weather, commodity cycles).
3. Embedded Intermediaries (Infrastruktur Sosial-Teknologis)

Introduce a class of intermediary agents or institutions that operate as bridges between economic layers. These can be:

Digital Cooperatives or Agent Networks:
Individuals or micro-firms trained to represent groups of traditional actors digitally, aggregating inputs, negotiating with platforms, or facilitating compliance.
Civic Tech Anchors:
NGOs or local government units empowered with tech toolkits to assist underserved communities in technology adoption on their own terms.
University/Polytechnic Extensions:
Students and lecturers engaged in ongoing living labs within economic layers 1 and 2, bringing knowledge and feedback loops.
4. Feedback-Responsive AI Integration

AI systems used for economic analytics, credit scoring, or supply chain optimization must be contextually re-trained using localized data and continuous feedback loops. Encourage:

Data Ethnography Pilots:
Before AI deployment, conduct qualitative fieldwork to identify local economic signals (e.g., types of trust, rhythms of trade).
Open Algorithm Interfaces:
Allow local actors to question and adjust system outputs (e.g., credit scores, risk ratings), embedding socio-contextual override mechanisms.

Outcomes Anticipated:

Technology becomes enabling rather than excluding.
Policy instruments gain resonance and legitimacy in diverse economic settings.
Greater visibility of informal productivity within AI systems.
Reduced frictions in vertical and horizontal economic interactions.

C. Hybrid Market Design and Interlayer Financial Systems

Rationale:

Indonesia's economic reality reveals not only a vertical stratification (from informal to formal) but also horizontal disconnection between coexisting economic layers. Layer 1 (traditional) and Layer 2 (proto-industrial) actors often operate outside formal banking and marketplace systems, while Layer 3 (digital economy) and Layer 4 (AI-driven economy) increasingly rely on algorithmic visibility and formal compliance. The result is a structural exclusion, not only from market participation but from capital flows, credit scoring systems, and growth opportunities.

To bridge this fragmentation, we propose a hybrid market design and a layer-sensitive financial ecosystem that enables fair exchange, capital circulation, and data interoperability across all four economic layers---without coercive formalization or forced platform migration.

1. Hybrid Marketplaces: Physical-Digital Synergy

Rather than replacing traditional markets, we propose multi-nodal marketplaces that integrate analog and digital actors with symmetric access:

QR-Enabled Pasar Tradisional:
Enable traders to receive payments via QRIS, while maintaining physical interaction and bargaining culture.
"Offline-first" Digital Marketplaces:
Mobile apps and kiosks that allow sellers to upload stock/prices via USSD or SMS for inclusion in digital listings.
Rotating Hybrid Bazaars:
Physical market events curated by digital platforms (Tokopedia, Shopee, Gojek) to discover and onboard offline microproducers.
2. Interlayer Financial Instruments

We advocate for the creation of financial products tailored to interlayer relations, such as:

Trust-Chain Microcredit:
Credit lines issued based on social capital, cooperative reputation, or community track records---not only formal collateral or AI credit scores.
Layered Wallet Systems:
E-wallets that allow value storage across physical cash, mobile money, and QRIS, with optional bridging to Layer 4 digital banks or blockchain-based services.
Informality-Aware Scoring Models:
Financial inclusion systems that integrate non-traditional indicators (e.g., volume of physical transactions, inventory cycles, community standing) into machine learning models for credit assessment.
3. Interoperable Identity and Transaction Layer

To make cross-layer interaction feasible, a lightweight, interoperable identity and transaction architecture is critical:

Pseudonymous Economic Identity:
Enable micro-entrepreneurs to build reputation capital across platforms without needing full formalization, using unique transaction tags, behavioral histories, or cooperatives as proxy holders.
Open Transaction Logging:
Create decentralized data ledgers (not necessarily blockchain) where even analog transactions (sales recorded on paper, SMS logs) can be digitized via intermediaries for aggregation.
Contextual Data Integration APIs:
Encourage fintechs, banks, and marketplaces to expose APIs that allow third-party agents (cooperatives, NGOs, local tech hubs) to upload context-tagged economic data for decision augmentation.
4. Layered Intermediation Nodes

To reduce the friction of trust and translation between economic layers, establish:

Interlayer Agents (ILA):
Professionals who understand both traditional economic logic and digital platforms, helping negotiate contracts, translate norms, and synchronize cycles across layers.
Community Treasury Hubs:
Decentralized financial institutions managed by community-based cooperatives that act as anchors for savings, lending, investment, and digital wallet access across layers 1--3.

Outcomes Anticipated:

More inclusive markets without erasing traditional practices.
Interoperable financial flows between layers without imposing full formalization.
Growth in digital trust and transaction visibility for Layer 1--2 actors.
Layered resilience: downturns in one layer don't collapse the others.

6. Conclusion

A. Rekap Model 4 Lapis dan Urgensi Pendekatan Baru

Indonesia's economic structure is not merely a spectrum of development stages, but a multilayered ecosystem consisting of four distinct yet overlapping economic strata:

1. Layer 1 -- Traditional Economy:
Characterized by cash-based transactions, mobile vendors, street hawkers, and tarpaulin stalls---rooted in socio-spatial immediacy and informal trust mechanisms.
2. Layer 2 -- Proto-Industrial Modern Economy:
Comprised of small factories, local workshops, and office environments operating with partial formalization and conventional banking access.
3.Layer 3 -- Digital Economy:
Enabled by cashless transactions, digital wallets, QRIS infrastructure, and online marketplaces---yet often exclusive due to technological and bureaucratic entry thresholds.
4. Layer 4 -- AI-Augmented Economy:
Dominated by algorithmic decision-making, data-driven financing, intelligent logistics, and predictive market systems---largely inaccessible to the majority of small-scale producers and informal actors.
Key Insights

These layers do not form a neat ladder of upward mobility. They often run in parallel, with limited bridges and a tendency toward exclusion rather than inclusion.
Classical models such as the Lewis Dual Economy or formal-informal dichotomies fail to capture the horizontal fragmentation and non-linear stratification observed in Indonesia's economy.
Technological advances, paradoxically, have widened the gaps between these layers. Digital and AI infrastructures are often blind to the rhythms, cycles, and informal logic of Layer 1 and 2 economies.
Urgency of a New Framework

To ensure economic justice, resilience, and productivity in the Indonesian context, we need a framework that:

Recognizes coexistence without enforcing convergence: Layer 1 actors should not be forced into digital conformity but supported with adaptive tools.
Enables interconnectivity across asymmetries: Financial, informational, and market links must be reimagined to respect the distinct nature of each layer.
Builds hybrid mechanisms for trust, transaction, and growth: Instead of digitizing everything, we must design symbiotic systems where traditional and modern economies can collaborate.
The 4-Layer Asymmetric Economy Model offers a conceptual and policy architecture that addresses these urgent needs. It reorients our development agenda from a vertical race to a horizontal integration strategy, one that values diversity, preserves contextual intelligence, and cultivates productivity across all layers of the national economy.

B. Policy Recommendations and Future Research Directions

Policy Recommendations

Based on the findings of this study, the following multi-layered policy strategies are recommended to address Indonesia's asymmetric economic landscape:

1. Contextual Technology Transfer
Introduce modular, low-barrier digital tools specifically tailored for Layer 1 and Layer 2 actors. Rather than top-down digital mandates, prioritize co-designed solutions that preserve local workflows while offering incremental access to Layer 3 and 4 services.
2. Asymmetric Financial Inclusion
Develop multi-credit scoring models that include non-traditional indicators such as community trust, informal turnover, and long-term relationships with suppliers or customers---making informal and semi-formal businesses visible to digital banking and micro-investment platforms.
3. Hybrid Market Infrastructure
Encourage multi-format commerce models (e.g., digital kiosks, offline-to-online hubs, local-to-global micro supply chains) that recognize the simultaneity of cash, QRIS, and trust-based trade. Hybrid marketplaces should be encouraged through tax incentives, tech partnerships, and local co-ops.
4. Interlayer Connector Institutions
Establish intermediary entities or digital cooperatives that understand the behavior, incentives, and constraints of each layer---especially to enable Layer 1 and 2 actors to participate in Layer 3 and 4 ecosystems without forced assimilation.

Future Research Directions

This paper opens new avenues for empirical and theoretical exploration, including:

1. Quantitative Mapping of Interlayer Flows
Using network science and supply chain analytics to track real-time flows of goods, money, and information across the four layers---highlighting disconnections and potential nodes of integration.
2. Cognitive-Economic Ethnographies
Explore how small actors in Layer 1 and 2 perceive and engage with digital systems and AI infrastructure. This includes studying technological ambivalence, informal innovation, and adaptive resistance.
3. Agent-Based Simulation of Multi-Layer Economies
Build models to simulate shock responses, policy diffusion, and emergent collaboration between layers under various scenarios (e.g., pandemic, price shocks, regulatory change).
4. Design of Alternative Economic Indicators
Traditional GDP or employment metrics do not capture the vibrancy or constraints of the asymmetric model. New metrics---such as Layer Elasticity Index, Informal Interconnectivity Quotient, or Tech Friction Coefficient---could enrich both policy and academic discourses.

Final Note

Understanding Indonesia's economy as a complex, stratified, and interwoven system of four distinct layers challenges linear development paradigms. The 4-Layer Asymmetric Economy Model invites a more inclusive, adaptive, and honest way to design, evaluate, and intervene in emerging economies---balancing innovation with equity, efficiency with empathy.

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