Tag: Ecosystem

Synergy Value as Emergence

2025-09-10 / Kuncoro Wastuwibowo / 0 Comments

When considering mergers, acquisitions, alliances, or even intra-group synergies, it is useful to shift our perspective away from additive arithmetic and towards the philosophy of emergence. In complex systems, including business ecosystems as complex adaptive systems, value does not reside solely within the parts; rather, it arises through the patterned interactions between them. This emergent phenomenon is precisely what in corporate finance is labelled synergy value. In formal terms, we may describe the total incremental value of a collaboration as

where V(x; G) denotes the value of the whole system, generated by the vector of resources and activities x under a specific governance structure G, and ∑V represents the value of each entity in isolation. The very fact that ΔV may be greater than zero testifies to emergence: complementarities in action, dependencies properly orchestrated, and adaptive patterns unfolding across the system.

The Levers of Emergent Synergy

Four principal levers determine whether emergent value materialises or evaporates. The first is complementarity, or what economists term supermodularity. This describes the situation in which activities reinforce each other such that the marginal return of undertaking one activity is enhanced by the undertaking of another; formally, the cross-partial derivatives are positive (𝛿²V/𝛿xi 𝛿xj > 0). It is here that the popular slogan “one plus one equals more than two” has rigorous grounding.

The second lever is the interdependence structure. Every collaboration has a topology of dependencies, where some assets act as complements, others as substitutes, and some nodes become bottlenecks through which the value of the entire system is channelled. In business ecosystems, mapping this structure is indispensable, for it often dictates whether modularity and flexible linkages suffice, or whether full absorption is required.

The third lever is defined by the adaptive rules of the system. A collaboration is not static; it is a complex adaptive system in which local decisions, feedback loops, and routines create new global patterns. Where local experimentation is permitted, and where feedback loops are properly designed, valuable behaviours diffuse through the organisation or alliance. Where rigidity prevails, the system is condemned to stasis, and synergy remains a theoretical promise rather than an emergent reality.

Finally, there is the matter of orchestration capacity. This refers to the dynamic capabilities of leadership—sensing opportunities, seizing them through resource allocation, and reconfiguring the system as environments change. Ashby’s principle of requisite variety reminds us that the variety of governance and decision-making tools must match the variety and volatility of the environment. Without adequate orchestration, even strong complementarities and favourable topologies may collapse under the weight of integration costs.

Applications Across Collaboration Types

In mergers and acquisitions, the choice of integration model should mirror the degree of interdependence. The celebrated Haspeslagh–Jemison framework reminds us that absorption is not always optimal; linkage or preservation may unlock more emergent value when autonomy is vital. The risk of the so-called synergy mirage lies precisely in misjudging complementarities and ignoring the time it takes for emergent patterns to stabilise. Thus, every acquisition is less a completed transaction than a hypothesis about the future, whose proof lies in the integration process.

In alliances and joint ventures, synergy takes the form of options on emergence. Here, limited commitments allow parties to test complementarities without over-committing capital. The collaborative form is well-suited to contexts of uncertainty, where exploration of emergent patterns is required. Ecosystem logic also applies: co-opetition and the management of network externalities often define the extent of emergent value.

For intra-group business synergy, emergence must be cultivated across corporate units. Here, Herbert Simon’s notion of near-decomposability becomes instructive: groups should design modular interfaces so that subsidiaries adapt locally yet align globally. To maintain cooperation, emergent rents must be shared fairly; cooperative game theory suggests the Shapley value as one method of allocating incremental value in proportion to each unit’s marginal contribution. Without such fairness, group members are tempted to defect, undermining the collaborative potential of the system.

Measuring and Governing Emergence

Because synergy is emergent, it resists simple enumeration. Yet it is not beyond the reach of disciplined measurement. One may begin with a complementarity map, estimating where cross-partials are most positive, and therefore where joint action may yield the greatest return. Alongside, an ecosystem dependency graph may be drawn, in the spirit of Ron Adner’s ecosystem mapping, to reveal missing complements and bottlenecks whose removal could unlock value.

Where uncertainty is high, the logic of real options should prevail. Pilot projects, staged investments, or minority stakes serve as options to explore emergent potential without risking catastrophic downside. Parallel to this, a system of synergy accounting may be implemented, in which incremental value is decomposed using Shapley allocations, thereby aligning incentives with marginal contributions to the whole.

The Philosophical Bottom Line

Synergy lives not in assets but in interactions. Corporate actions—whether a merger, an alliance, or an intra-group initiative—are best understood as interventions in a complex system. When complementarities are strong, interdependencies are designed with care, adaptive rules permit experimentation, and orchestration capacity is sufficient, emergent synergy is more than a hopeful metaphor; it becomes an observable reality. Conversely, where these levers are mismanaged, the promised “1 + 1 > 2” dissolves into disappointment, integration costs, and value destruction.

Thus, the philosophy of emergence, long a staple of complexity science, is not an academic curiosity but a practical guide to business collaboration. It teaches us that the true measure of a deal or alliance lies not in the parts themselves, but in the patterns of interaction that the collaboration enables.

The Flawed Global Ecosystem Strategy

2025-04-10 / Kuncoro Wastuwibowo / 0 Comments

Last century, the US stood as the pinnacle of industrial power. With unmatched manufacturing capacity, cutting-edge innovation, and a dynamic domestic labour force, the US not only produced at scale, but also created a vast middle class through industrial employment. But since the early 21st century, this dominance had eroded. Despite the continued global success of Apple, Microsoft, etc, the US found its industrial core hollowed out. This paradox—where the strategy won, but the nation did not—is at the heart of this exploration.

The US led the global shift toward liberalisation and globalisation, embracing free trade, deregulation, and offshoring as strategies for economic growth and competitive advantage. These ideas crystallised during the Reagan-Thatcher era and were institutionalised in policies such as NAFTA and the support for China’s entry into the WTO. The logic was simple: relocate labor-intensive manufacturing to lower-cost countries, focus domestically on high-value services and innovation, and reap the benefits of global efficiency.

For US corps, this approach worked magnificently. Apple built one of the most valuable ecosystems in the world, with tightly integrated design, software, services, and hardware. But much of this hardware was manufactured and assembled overseas, particularly in China. Microsoft dominated software and enterprise services, but its global cloud and platform ecosystem increasingly depended on international data centers, developer networks, and supply chains that were vulnerable to political shifts.

What became apparent over time was that these ecosystem-based strategies—while brilliant in achieving scale, market control, and profitability—were fundamentally fragile. They were built on assumptions of a stable global environment, unrestricted cross-border flows of labour, capital, and data, and a geopolitical consensus that no longer exists. The COVID-19 pandemic, the US-China business war, and the rise of protectionist and nationalist policies globally exposed just how brittle these supply chains and platform dependencies were.

The heart of the flaw is in the over-optimisation for efficiency at the expense of resilience. By offshoring critical manufacturing, the US lost not only jobs but also industrial knowledge, logistics infrastructure, and the ability to rapidly pivot production domestically in times of crisis. This strategic vulnerability became clear when shortages of semiconductors, PPE, and other essentials during the pandemic brought entire industries to a standstill.

Moreover, the US model of capitalism encouraged short-termism. Public companies were driven to maximise quarterly earnings and shareholder returns, often by cutting labor costs or outsourcing rather than reinvesting in domestic capacity. Labor unions weakened significantly, and with them, the political and social infrastructure that once supported a strong working class. The cultural shift toward a “knowledge economy” reinforced the idea that physical production was less valuable than digital platforms, intellectual property, and financial engineering.

This ideology extended into the UK as well, which closely mirrored US strategies in economic liberalization. Under Thatcher in the 1980s, the UK privatized major industries, deregulated finance, crushed unions, and repositioned itself as a global hub for services—especially financial services. The “Big Bang” of 1986 opened up London’s financial markets, turning the City into a magnet for global capital. Much like the US, the U.K. allowed its manufacturing base to atrophy in favour of high-value services concentrated in the Southeast, particularly London.

However, the UK, unlike the US, lacked the scale, resource diversity, and global technological dominance to buffer the negative effects of this transition. The result was stark regional inequality, declining productivity, and chronic underinvestment in infrastructure and education in much of the country. Brexit, in many ways, was the political expression of this economic alienation—a rebellion against globalisation, centralisation, and the perception of being “left behind.”

In both countries, we see a core contradiction: while companies triumphed globally, the broader national economies suffered from fragility, inequality, and a loss of sovereignty in key strategic sectors. The ecosystem-based strategies of firms like Apple and Microsoft continue to generate massive returns, but they do so by depending on fragile geopolitical arrangements, low-cost labor overseas, and complex, just-in-time logistics networks that are increasingly prone to disruption.

The irony is that ecosystems, as conceptualised in nature, thrive on diversity, redundancy, and mutual support. Business ecosystems, as built by the tech giants, often lack these qualities. They tend toward centralisation, dominance, and efficiency, making them look more like monocultures than true ecosystems. When stress hits—in the form of sanctions, pandemics, or trade wars—these systems do not bend; they break.

So is the ecosystem model flawed? Not entirely. It remains one of the most powerful frameworks for value creation in a networked economy. But it needs to evolve. Firms must build ecosystems that are not just efficient, but resilient and adaptable. This means diversifying supply chains, investing in local capabilities, supporting the long-term health of partners, and accounting for political and environmental risks.

Nations, too, must rethink their approach. A return to protectionism is not the answer, but neither is blind faith in market liberalism. Strategic sectors must be rebuilt or supported domestically not only for economic competitiveness but for national resilience. Policies must incentivise long-term investment, regional regeneration, and industrial policy aligned with innovation.

Ultimately, the story of the past few decades is not that globalization and liberalization were inherently wrong. Rather, they were applied too narrowly, with too little foresight, and with insufficient regard for the long-term health of national economies. The US and the UK offer lessons—both cautionary and hopeful—for any country navigating the next era of global business, where resilience, sovereignty, and inclusive prosperity will be just as important as efficiency and innovation.

Signals and Boundaries

2025-01-02 / Kuncoro Wastuwibowo / 0 Comments

John Holland’s “Signals and Boundaries” has become a touchstone in the study of complex adaptive systems (CAS), offering an intuitive way to understand how local interactions give rise to emergent behavior. At its core, Holland’s framework posits that signals (=the carriers of information) and boundaries (=the limits that define and protect modules) play a pivotal role in the organisation, adaptation, and evolution of complex systems. His insights have helped shape our understanding of how simple, localised exchanges can lead to intricate global patterns.

The framework’s influence is widespread, resonating strongly within academic circles including the SFI. Scholars have incorporated Holland’s ideas into broader discussions on network theory and modularity, using them as a bridge between traditional adaptation models and more modern computational approaches. By emphasising the dual roles of communication through signals and compartmentalisation via boundaries, Holland provided researchers with a practical toolkit for analysing the dynamics of ecosystems, technological platforms, and social networks.

Holland’s Signals and Boundaries, read at the Soekarno Hatta International Airport

A significant strength of Holland’s theory lies in its capacity to illustrate how local interactions can generate emergent complexity. When agents within a system interact, they exchange signals that serve as feedback loops—adjusting behavior and influencing neighboring agents. Meanwhile, boundaries help maintain structure by isolating specific interactions from external noise, allowing subsystems to develop independently yet remain interconnected. This delicate balance between isolation and connectivity is what drives the self-organisation and adaptation observed in complex systems.

However, the notion that complexity is solely the product of local interactions has its critics. Some argue that focusing exclusively on bottom-up processes might neglect the role of global influences and top-down causation. In many systems, overarching constraints, environmental factors, and collective dynamics impose patterns and behaviors that local interactions alone cannot fully explain. This perspective contends that emergent phenomena may also be shaped by these global forces, suggesting a need for models that integrate both micro-level interactions and macro-level structures.

One contrasting perspective within the complexity paradigms is the idea of strong emergence. Proponents of strong emergence assert that certain higher-level properties of a system are fundamentally irreducible to the interactions of its constituent parts. In this view, while local interactions are essential, they cannot entirely account for phenomena that manifest at the macro scale. The emergent behaviors observed in complex systems may require explanations that go beyond the sum of local interactions, implying that there are holistic properties at play that necessitate a different conceptual approach.

There is also a growing consensus among some researchers that a dual approach—one that synthesises both local and global perspectives—is necessary for a complete understanding of complexity. Network theorists and systems dynamicists, for example, have highlighted the importance of long-range correlations and global feedback loops that complement local interactions. This integrated approach recognises that while signals and boundaries are crucial, the interplay with broader systemic forces can drive self-organisation and adaptation in ways that are not captured by local dynamics alone.

Holland’s signals and boundaries framework remains a seminal contribution to complexity science, celebrated for its clarity and applicability across diverse domains. It has provided a powerful lens for examining how decentralised, local interactions can lead to emergent behavior—a notion that has profoundly influenced our understanding of ecosystems, technological platforms, and social networks. Yet, as our grasp of complex systems deepens, it is equally important to acknowledge and incorporate contrasting views, such as the roles of strong emergence and global influences, to capture the full richness of complexity. This ongoing dialogue not only enriches the theoretical landscape but also drives innovation in how we model and manage complex systems in practice.

Cities Development as CAS

2024-12-20 / Kuncoro Wastuwibowo / 0 Comments

The research titled “Inter-City Firm Connections and the Scaling of Urban Economic Indicators” by Yang, Jackson, and Kempes, published in PNAS Nexus (Nov 2024), presents a fresh perspective on how cities generate economic output. While traditional urban scaling theories focus on how local, intra-city interactions drive economic productivity, this study argues that inter-city connections — especially through multinational firms — play an equally, if not more, significant role. By analysing GDP data from cities in the US, EU, and PRC, alongside the Global Network Connectivity (GNC) of multinational firms, the study reveals that cities with higher inter-city connectivity exhibit higher-than-expected GDP, even after accounting for population size. This finding challenges the conventional idea that urban scaling is driven solely by local social interactions, offering a new lens for understanding complexity in urban systems.

This study is an example of how complexity science can be applied to real-world systems like cities. Cities, as complex adaptive systems (CAS), exhibit emergent behaviours, such as superlinear scaling of GDP, where larger cities tend to be disproportionately more productive. Traditionally, this emergent property was attributed to denser local social interactions. However, the authors introduce a new dimension of complexity by demonstrating how inter-city firm connections serve as an additional mechanism for economic emergence. Using the concept of networked systems, cities are modelled as nodes connected by firms, and the GNC score quantifies the strength of these connections. The research shows that GDP is influenced not just by a city’s local population but also by its position within this global network. This insight extends the complexity science framework by highlighting the role of cross-city organisational linkages in shaping global economic output.

The study also provides methodological advances that enrich the complexity science toolkit. It uses Scale-Adjusted Metropolitan Indicators (SAMI) to compare how cities “overperform” or “underperform” in GDP relative to expectations. This allows for a nuanced view of which cities benefit most from inter-city connections. Furthermore, the use of multilevel regression models that incorporate both local (population) and global (GNC) factors reveals the nonlinear dynamics at play. Such nonlinear scaling, where population alone cannot explain GDP growth, suggests the presence of feedback loops where better-connected cities become more prosperous, and prosperous cities become better connected. These insights underscore how complexity science can offer more accurate, multi-layered models of urban growth, moving beyond simplistic population-based approaches.

The implications of this research go beyond academic curiosity. For policymakers, it suggests that urban economic development strategies should prioritise enhancing global connectivity. Cities can benefit from strengthening ties with multinational firms, facilitating cross-city collaborations, and becoming key nodes in the global urban network. This is a shift from the classic focus on improving only local conditions, such as infrastructure or intra-city mobility. For complexity science, this study exemplifies how theories of self-organisation, emergence, and adaptive networks can be operationalised in practical, high-impact research. The work highlights the potential for developing a more comprehensive urban scaling model that integrates both local and global processes. By bridging concepts from complexity science with urban development, the study opens new possibilities for future research into how global interconnections influence local outcomes, from economic growth to social inequality.

Source: Vicky Chuqiao Yang, Jacob J Jackson, Christopher P Kempes, 2024, Inter-city firm connections and the scaling of urban economic indicators, PNAS Nexus 3:11, DOI: 10.1093/pnasnexus/pgae503