A Decision-Making Framework for Public–Private Partnership Model Selection in the Space Sector: Policy and Market Dynamics Across Countries

Abstract

The increasing complexity and commercialization of the global space sector have elevated the strategic role of public–private partnerships (PPPs). However, the criteria for selecting suitable PPP models remain underexplored, particularly regarding the influence of national policy and market environments. This study proposes a decision-making framework that links six indicators—national strategic goals, government role preferences, regulatory structures, capital access, private-sector capabilities, and commercial demand—to four distinct PPP models in the space sector. Drawing on Eisenhardt’s multi-case theory-building methodology, this study analyzes PPP evolution in four countries representing mature, emerging, and nascent countries: the United States, Japan, India, and the United Arab Emirates. The cross-case analysis reveals that high-autonomy PPP models emerge only when institutional, financial, and market factors are systemically aligned. Divergence in PPP forms is driven not solely by technical capabilities but also by governance postures and regulatory designs. The findings contribute to addressing ongoing challenges related to policy reform and increasing private-sector involvement in the space sector by developing a practical decision-making tool for public and private-sector actors engaged in space governance. Specifically, the diagnostic framework enables stakeholders to assess national readiness and select appropriate PPP models. It also supports strategic planning by highlighting the reforms and capacity-building measures required for countries with nascent and emerging economies to transition from government-led missions to commercially integrated space ecosystems.

1. Introduction

Public–private partnerships (PPPs) are complex collaborations that bring together governmental bodies and the private sector to deliver services and infrastructure traditionally provided by the public sector (Roehrich et al., 2014). Public–private partnerships (PPPs) have become a defining feature of space-sector governance, enabling governments to mobilize private-sector capabilities for strategic missions while managing budgetary constraints and accelerating innovation (Kim, 2023a, 2023b; Roehrich et al., 2014; Zancan et al., 2024). As the space economy transitions from a monopolistic, government-centric model to a more hybridized and commercially competitive landscape, PPPs are increasingly viewed not only as procurement mechanisms but also as instruments for cultivating national space power, fostering technological diffusion, and asserting global market leadership (Mazzucato & Robinson, 2018; Melamed et al., 2024). When appropriately applied, PPPs can accelerate market growth and strengthen national capabilities while supporting policy objectives (Gifford et al., 2024; Link, 1999).

Yet, despite growing interest, the operational and analytical complexity of selecting appropriate PPP models remains under-theorized in the space policy literature, particularly when compared to more established domains such as transportation, healthcare, or infrastructure (Kim, 2023a; Tinoco, 2018; Zancan et al., 2024). Recent studies have emphasized that space-sector PPPs are structurally distinct from terrestrial analogs due to their dual-use technologies, extended development timelines, capital intensity, and diverse national objectives, which range from scientific advancement to strategic deterrence and economic competitiveness (Kallender, 2016; Kavvadia, 2024; Paikowsky, 2024).

While generic PPP frameworks highlight cost-efficiency, risk-sharing, and life-cycle optimization (Boardman et al., 2015; Castelblanco et al., 2025; Hodge & Greve, 2007), these principles are not adapted to the distinctive institutional and market dynamics of the space domain. As Kim (Kim, 2023b) and Zancan (Zancan et al., 2024) have shown, space-specific PPPs operate across a spectrum of governance models, from legacy, state-led procurement structures to emergent NewSpace paradigms built on regulatory experimentation, modular innovation, and private-sector autonomy.

However, a major gap exists between space-sector PPPs in theory and in practice. Although the academic literature on PPPs is comprehensive and varied, the literature on PPPs in the space sector is limited, and such robust foundational literature is notably absent primarily because space has traditionally been viewed as a domain of the public sector and the involvement of the private sector is a relatively recent development. Existing space PPP literature mostly focuses on certain space PPP missions (Autry, 2018; Entrena Utrilla, 2017; Stone, 2018) or on broader discussions of the new space environment (Rementeria, 2022; Tinoco, 2018; Zancan et al., 2024).

A structural typology of space-sector PPPs has been introduced by Kim (2023b), comprising four models: Operation Concession (OCon), Partially Finance–Design–Develop (PFD), Partially Finance–Design–Develop and Fully Own–Operate (PFD-FO), and Partially Finance and Fully Design–Develop–Own–Operate (PF-FDO). However, there is currently no analytical framework linking these PPP types to the underlying national contexts in which they emerge and operate, thus restricting the space sector’s ability to understand how contextual factors determine PPP model selection.

In other words, the existing typology does not explain how specific policy and market conditions determine the suitability or progression of each model. These gaps hinder informed decision-making, limit the development of specific strategies, and prevent the selection of PPPs aligned with national policy and market environment.

This gap is particularly pressing as more nations, especially those with emerging or nascent space programs, seek to adopt PPP strategies. Without a contextual framework, decision-makers lack guidance on which PPP model aligns with their strategic objectives, regulatory posture, or private-sector capacity and how that model might evolve through policy reform or market development. As the global space sector becomes more diversified, countries must understand not only which PPP type is currently feasible but also what type they may transition toward as their environment matures.

To address this shortcoming, this study thus addresses the following core question: How can a country’s policy and market environment inform the selection of a sustainable public–private partnership model in the space sector?

This study develops a decision-making framework that links six contextual indicators—three associated with policy environments (national strategic goals, governance role preference, regulatory structure) and three with market environments (capital access, private-sector capability, commercial demand)—to the selection of analytically distinct PPP models. The framework is grounded in Eisenhardt’s (1989) case study theory-building methodology and is tested through comparative case studies of the United States, Japan, India, and the United Arab Emirates. These countries were selected based on their divergent governance structures, regulatory evolution, and degrees of PPP maturity, offering a basis for theoretical replication and contrastive analysis (Kim, 2023b; Sadeh, 2010, 2013).

By grounding PPP selection in observable institutional and market conditions, the framework offers both analytical clarity through typological refinement and practical utility through a diagnostic tool for policymakers and commercial stakeholders. As competition for space-based capabilities intensifies, the ability to structure context-appropriate PPPs becomes essential not only for infrastructure delivery but for long-term national power projection and industrial leadership (Davis et al., 2024; Mazzucato & Robinson, 2018; Melamed et al., 2024).

This article is structured as follows: Section 2 presents the theoretical framework and typology of PPP models in the space sector. Section 3 describes the methodology, including case selection and data sources. Section 4 reports the main findings from the within-case and cross-case analyses and introduces a novel decision-making framework for selecting PPP models in the space sector. Section 5 discusses the results in light of the existing literature and outlines their implications. Finally, Section 6 concludes with recommendations and directions for future research.

2. Theoretical Framework

Public–private partnerships (PPPs) in the space sector operate along a spectrum of institutional arrangements and private-sector participation, ranging from conventional public procurement to fully commercialized models. Figure 1 illustrates this procurement.

It situates PPPs as hybrid mechanisms between state-led and market-driven models, providing the conceptual basis for evaluating task allocation and governance types.

This section introduces the space-specific PPP typology proposed by Kim (2023b), which categorizes partnership models based on the allocation of five core functions: finance, design, development, operations, and ownership (Kim, 2023b). Building on this typology, this study presents six indicators, with three related to policy and three related to market conditions, to support theory-building through multi-case analysis, consistent with the methodological approach outlined by Eisenhardt (Eisenhardt, 1989) and Eisenhardt and Graebner (Eisenhardt & Graebner, 2007). The selection of these indicators is aligned with the task allocation in Kim’s framework, and their conceptual validity is reinforced by established theoretical perspectives in public administration (Hodge & Greve, 2007), institutional theory (Batley et al., 2004; Kettl, 2000), and innovation systems (Freeman, 1995; Mazzucato & Robinson, 2018; Robinson & Mazzucato, 2019).

2.1. Space PPP Typology

The PPP typology in the space sector have gained traction as a hybrid governance mechanism that mobilizes private-sector capabilities while serving national missions (Alan Lindenmoyer et al., 2015; Taylor, 2007). However, most scholarly accounts remain generalized and overlook space-specific task structures. Kim (2023a) addresses this limitation by introducing a sector-specific typology of PPPs based on the allocation of five critical functions. Each of the four space PPP models in the typology represent increasing degrees of private-sector autonomy and institutional delegation. In the typology developed by Kim (2023a), the OCon model reflects minimal private-sector involvement, limited to operations, while all other tasks, including finance, design, development, and ownership, remain within the public sector (Kim, 2023a). In the PFD model, private actors contribute to one or more tasks, either jointly with public agencies or independently, but operational authority and asset ownership are retained by the state (Kim, 2023a). The PFD-FO model reflects an institutional configuration similar to PFD in terms of task distribution finance, design, and development but differs fundamentally where the private sector assumes full ownership and operational control (Kim, 2023a). Finally, the PF-FDO model represents the highest level of private-sector autonomy, in which the private entity leads across all five functions, with public involvement limited only to partial financing (Kim, 2023a). These models reflect broader governance logics and capacity thresholds, providing a structured overview for comparative analysis and subsequent case studies.

2.2. Policy Environment Indicators

The policy environment plays a central role in shaping whether and how governments adopt specific public–private partnership (PPP) configurations across diverse economic and institutional contexts. This section defines three key policy environment indicators that influence governmental decisions regarding task allocation in space-sector PPPs: national strategic goals (P1), public-sector priorities (P2), and regulatory structure (P3). Policy indicators (P1–P3) were analyzed using thematic typologies derived from the structure and stated objectives of national policy narratives. This approach draws on established thematic analysis techniques used in recent cross-national PPP studies (Batra, 2021; Rahman et al., 2022). From the perspective of public administration theory, PPPs are not solely technical or economic tools but are embedded in broader institutional and governance traditions. As Hodge and Greve (2007) argue, PPPs reflect evolving paradigms of public management shifting from hierarchical, command-and-control models to more networked and collaborative forms of governance (Hodge & Greve, 2007).

2.2.1. National Strategic Goals (P1)

This indicator reflects the strategic orientation of a country’s space policy priorities and how these priorities shape willingness to delegate authority in PPPs (Kim, 2023b; OECD, 2015; Rausser et al., 2023). Building on the space policy literature (Jakhu & Pelton, 2017; Oltrogge & Christensen, 2020; Sadeh, 2013; Tkatchova, 2018), four recurring archetypes can be identified across mature, emerging, and nascent actors (CAO, 2025; ISRO, 2023a; UAESA, 2019b; WhiteHouse, 2020b):

• Leadership and national security prioritize sovereignty, defense capabilities, and technological supremacy, typical of established space powers with codified space doctrines and long-standing military–industrial space infrastructures.
• Economic growth and national security frame space as a catalyst for industrial growth, technological diffusion, and employment, common in emerging space systems pursuing liberalization.
• National security, scientific advancement, and market expansion emphasize research, innovation, and gradual commercial integration, common among technologically advanced yet institutionally conservative space actors.
• Strategic diversification and national prestige use space initiatives for international visibility, soft power projection, and symbolic capital and is often found in nascent space programs seeking global legitimacy or recognition.

2.2.2. Government Role Preference (P2)

The government role preference indicator assesses the extent to which governments are prepared to delegate responsibilities and collaborate with private-sector actors in the design, financing, and implementation of space projects (Stewart, 1995; Tinoco & Yu, 2016; Uppal, 2009; Ward & Mitchell, 2004). This indicator evaluates the governance posture of the state in structuring public–private partnerships (PPPs) within the space sector. Drawing on governance theory (Bult-Spiering & Dewulf, 2008; Hodge & Greve, 2007) and comparative PPP governance frameworks (Batley et al., 2004; Kettl, 2000; Wade, 2004), we identified three types:

• Principal role: The government retains centralized control, retaining exclusive authority over financing, design, ownership, and operational control. In the principal model, the government utilizes PPPs primarily as conventional procurement mechanisms, defining project scope, establishing performance metrics, and overseeing implementation to safeguard public interests and maximize societal benefits (Zancan et al., 2024). The private sector performs the role of a contractor, executing tasks based on predetermined public-sector specifications (Olusola Babatunde et al., 2012).
• Partner role: The government engages more interactively in an integrative approach with the private sector, engaging in co-financing arrangements, joint ventures, and decision-making within collaborative structures, while strategic oversight remains public, and elements of risk and ownership are distributed across sectors. This model involves shared risk, resources, and strategic planning between public and private entities (Brinkerhoff, 2002; Newman, 2022).
• Enabler role: The government acts as a facilitator, establishing enabling regulatory and institutional frameworks that support private-sector innovation and leadership. This approach minimizes direct state involvement and emphasizes deregulation and privatization, allowing private actors to initiate and implement projects while the public sector provides oversight and policy support (Alan Lindenmoyer, 2014; Stone et al., 2008). This model reflects a market-led innovation strategy.

2.2.3. Regulatory Structure (P3)

This indicator captures the spectrum of regulatory environments shaping space-sector PPPs. It reflects how legal and institutional frameworks govern public and private actors, categorized as restrictive, structured and predictable, or flexible. These categories are derived from national space policy documents across mature, emerging, and nascent actors (CAO, 2025; ISRO, 2023a; UAESA, 2019b; WhiteHouse, 2020b) and supported by broader regulatory scholarship emphasizing flexibility (Gunningham et al., 1998; Young et al., 2018), predictability (Baldwin et al., 2011; Fazekas et al., 2024), and structured regulatory governance (Coglianese, 2012; Sykes, 2003).

• Restrictive: Characterized by stringent licensing processes, bureaucratic hurdles, and limited and selective private-sector involvement, this framework often acts as a deterrent to potential PPP ventures in the space domain (Howlett, 2023). This environment exhibits a high degree of governmental control, potentially stifling innovation and hindering the agility required for successful commercial space operations (Baumann et al., 2018).
• Structured and predictable: This category signifies a more mature regulatory framework, offering clear guidelines and legal frameworks, transparent processes for private-sector entry, and established legal precedents for space activities, thereby fostering investor confidence and encouraging long-term commitments to PPP projects (Hofmann & Blount, 2018).
• Flexible: This category represents regulatory environments that prioritize adaptability and responsiveness to the rapidly evolving space sector. It emphasizes streamlined approval processes, accommodates novel technologies and business models by using adaptive tools such as regulatory sandboxes, and prioritizes innovation responsiveness (Allan Lindenmoyer, 2006).

2.3. Market Environment Indicators

This section introduces three market-related variables—capital access (M1), private-sector capability (M2), and commercial demand (M3)—that assess private-sector readiness to take on financial, design and development (D&D), operational, and ownership responsibilities within space-sector public–private partnership (PPP) models. In this study, market environment indicators were assessed using a three-level ordinal scale (high, moderate, and low) aligned with comparative frameworks commonly employed in PPP readiness evaluations (Hartwich & Tola, 2007).

2.3.1. Capital Access (M1)

Capital access refers to the availability and diversity of financial instruments and funding channels that enable private-sector actors to assume meaningful financial responsibility in public–private partnership (PPP) arrangements. This includes venture capital, private equity, sovereign wealth funds, development finance institutions (DFIs), and blended finance models (OECD, 2021a; WorldBank, 2021). The conceptual foundation lies in financial market development theory, which argues that diverse and efficient capital markets are essential for private investment, innovation, and long-term growth (Beck et al., 2000; Levine & Zervos, 1998). In the space sector, where projects are high-capital and long-horizon, mobilizing private capital is critical for risk-sharing, innovation, and market maturation (Gifford et al., 2024; Rausser et al., 2023). By contrast, underdeveloped financial systems result in PPP structures being dominated by public-sector funding (Babatunde & Perera, 2017; Osei-Kyei & Chan, 2017). Capital access is classified into three levels:

• High accessibility: liquid capital markets, mature venture capital ecosystems, and active private-equity participation in PPPs.
• Moderate accessibility: financing is led by public or quasi-public institutions through grants, development funds, or sovereign vehicles, while private capital plays a supplementary role.
• Low accessibility: Funding is dominated by state budgets, with private investment minimal or structurally constrained. PPPs almost entirely depend on public financing.

2.3.2. Private-Sector Capability (M2)

Private-sector capability refers to the technical and organizational capacity of space firms to participate in space-sector projects. This indicator is grounded in innovation systems theory, which highlights how national and sectoral innovation environments shape industrial development and technological autonomy (Freeman, 1995; Mazzucato & Robinson, 2018). It evaluates whether private-sector actors demonstrate the ability to engage in multiple phases of the space value chain, such as upstream and downstream. This indicator provides a conceptual foundation by capturing the maturity of private-sector actors in space-sector PPPs for evolving end-to-end space missions, and their reliance on public or foreign entities.

Countries with high private-sector capability environments are typically marked by operational independence, the ability to contribute across multiple project phases, and demonstrable technical expertise (OECD, 2021b; Rementeria, 2022). Countries where private-sector capability is constrained, whether due to limited technological readiness or dependence on public leadership, usually participate only in the restricted model. Such patterns are especially evident in emerging and nascent space economies (Harding, 2012; Suzuki, 2019).

Private-sector capability is categorized into three levels:

• High capability: private firms can design, develop, launch, and operate space systems with autonomy in both upstream and downstream space markets.
• Moderate capability: private firms are active and may possess technical competencies but remain dependent on government contracts or foreign partnerships, a common emerging commercial ecosystem under state guidance.
• Low capability: Few private firms operate independently in the space sector. These ecosystems often rely on foreign prime contractors or international partnerships for mission execution, which is common in nascent space countries.

2.3.3. Commercial Demand (M3)

This indicator captures the scale, stability, and diversity of demand for space-based services focusing on the presence of commercial buyers beyond the state (Irvine, 2022; OECD, 2023). In mature markets, commercial demand is supported by government procurement programs, and PPPs can evolve beyond subsidy-driven models into performance-based, innovation-led partnerships. These countries have developed robust ecosystems characterized by large, stable, and diversified domestic markets. Public–private contracting is widespread to both domestic and international clients (Gustetic et al., 2015; Paikowsky, 2024; Ustin & Middleton, 2024). In emerging or nascent markets, demand remains concentrated in public-sector initiatives. Government agencies sustain early private-sector engagement through infrastructure subsidization, guaranteed procurement contracts, or strategic partnerships (Babatunde & Perera, 2017; OECD, 2021a). These efforts help establish early market credibility but are still transitioning toward diversified, autonomous demand (Harding, 2012; Rausser et al., 2023). The following are the classifications of this indicator:

• High demand: Robust and diversified domestic and international markets exist, and private firms compete for contracts.
• Moderate demand: Commercial interest is emerging, but the market remains largely shaped by public procurement or state-led initiatives.
• Low demand: Domestic commercial demand is minimal or underdeveloped. The market is driven almost entirely by government procurement, and commercial buyers are scarce.

3. Methods and Data

3.1. Methodology

This study adopts the multiple-case, theory-building approach developed by Eisenhardt (Eisenhardt, 1989), which is well-suited to exploring under-theorized domains through cross-case comparison. It draws on the works of key grounded theory authors such as Glaser and Strauss (1967) and other major key case researchers such as Yin (1981). The method is particularly effective for analyzing complex, context-specific phenomena such as PPPs in the space sector. It supports the development of structured, empirically grounded frameworks through iteratively engaging with data, emergent patterns, and existing literature (Eisenhardt, 1989, 2021). This methodology builds conceptual models from the observed complexity of real-world cases, integrating elements of grounded theory and case study research to generate analytically generalizable insights (Eisenhardt & Graebner, 2007; Yin, 2018). In this study, Eisenhardt’s approach is applied to construct a decision-making framework that links national policy and market conditions to PPP model selection in the space sector. The guiding research question, “How do national policy and market environments inform the selection of PPP models in the space sector?”, requires a methodological approach capable of accommodating institutional variation and contextual diversity. Eisenhardt’s framework supports this analysis through theoretical sampling, within-case coding, and cross-case pattern recognition (Eisenhardt, 1989). Its comparative logic enables the rigorous identification of patterns across country cases that differ substantially in institutional maturity and market structure. The goal is to construct a decision-making framework grounded in empirical comparison. The analysis is structured around six predefined indicators derived from the relevant literature and specified in the analytical framework. The method consists of nine clearly defined stages.

Table 1. Application of Eisenhardt’s nine-step methodology.

Step	Eisenhardt Process	Application in This Study
1	Getting Started	Defined research question; identified six analytically integrated indicators drawn from policy and market theory.
2	Selecting Cases	Chose four countries representing mature, emerging, and nascent institutional systems.
3	Crafting Instruments	Developed coding logic with a high–moderate–low classification scheme based on indicator structure.
4	Entering the Field	Collected data from national space policy documents and space industry reports.
5	Analyzing Within-Case Data	Independently analyzed each case by six indicators; developed structured country profiles.
6	Searching for Cross-Case Patterns	Conducted cross case analysis and pairwise pattern comparisons.
7	Shaping Hypotheses	Derived propositions linking indicator patterns to space PPP model types.
8	Enfolding Literature	Compared findings with space PPP and innovation system literature.
9	Reaching Closure	No additional insights or pattern emerged.

outlines the nine-step process as applied. Emphasis on case heterogeneity in this study, including mature, emerging, and nascent national systems, supports the development of robust and transferable insights (Eisenhardt & Graebner, 2007).

3.2. Case Selection and Theoretical Sampling

Consistent with Eisenhardt’s (1989) multiple-case theory-building methodology, this study employs theoretical sampling to select cases that represent strategically contrasting system types (Eisenhardt, 1989). The objective is to maximize institutional and market diversity in order to explore how distinct national contexts shape public–private partnership (PPP) models in the space sector. Following Eisenhardt and Graebner (2007), case variation is guided by constructive replication logic, or the deliberate inclusion of variation across theoretically relevant dimensions to strengthen external validity (Eisenhardt & Graebner, 2007). In this methodology, theoretical sampling is explicitly designed to choose cases that fill conceptual categories, rather than to represent a population statistically (Eisenhardt, 1989; Eisenhardt & Graebner, 2007), and unlike large-sample quantitative research, case studies aim for analytical generalization (theory building), not statistical generalization.

Case selection was informed by the six analytical indicators introduced in Section 2.2 and Section 2.3, which span both policy and market environments. Countries were categorized into three groups, mature, emerging, and nascent, to reflect variation in institutional development, regulatory infrastructure, and private-sector engagement. Consistent with Eisenhardt (1989), the cases represent polar types selected to make contrasts transparently observable, thereby sharpening theoretical insight and strengthening external validity (Eisenhardt, 1989).

The United States was selected as a mature system, characterized by a highly developed regulatory framework, institutional openness to private-sector participation, and longstanding commercial space activity. India and Japan were selected as emerging systems, though with contrasting institutional characteristics. India reflects a trajectory of regulatory reform and expanding institutional capacity, while Japan presents a technically advanced but institutionally conservative profile with a strong emphasis on science and market expansion. The United Arab Emirates (UAE) was selected as a nascent system, distinguished by its recent but ambitious investments in space, high-level national space goals, and evolving regulatory and market institutions. This combination of cases ensures theoretical contrast, allowing for the systematic examination of how different institutional environments and policy priorities shape PPP configurations. By deliberately selecting cases that span a range of development stages, the study is positioned to generate context-sensitive, empirically grounded insights that are analytically generalizable across global space governance contexts.

Each case was chosen to provide theoretically relevant contrasts. The United States illustrates a commercially mature system; India reflects an emerging system undergoing regulatory reform and expanding institutional capacity; Japan represents an emerging but technologically advanced system with conservative institutional structures; and the UAE exemplifies rapid institution-building in a nascent environment.

3.3. Data Collection

Data collection followed Eisenhardt’s case-based methodology, which emphasizes the triangulation of diverse evidence to ensure construct validity and theoretical grounding (Eisenhardt, 1989; Eisenhardt & Graebner, 2007). For each of the four national cases—India, Japan, the United States, and the United Arab Emirates—evidence was systematically gathered around six analytically defined indicators (

Table 2. Summary of data sources by indicator type.

	Indicator	Key Data Sources (All Countries)
Policy	P1. National Strategic Goals	National space policy documents, space agency strategies, and planning documents published by relevant government organizations.
	P2. Government Role Priorities	National space policy documents and government institutional reports.
	P3. Regulatory Structure	National space regulations, licensing frameworks, regulatory guidelines, official government documents, and industry regulatory reports.
Market	M1. Capital Access	Space investment databases, venture capital trackers, and multilateral and national investment reports.
	M2. Private-Sector Capability	Industry capability assessments, national firm-level reports, and technical readiness frameworks.
	M3. Commercial Demand	Space market demand reports, industry outlooks, national procurement statistics, and commercial uptake data.

).

Primary data sources included government policy documents, national strategies, and regulatory frameworks, which were accessed through official government portals and agency repositories. These were supplemented by secondary materials such as institutional reports, industry analyses, and investment databases (e.g., OECD, Space Capital, BryceTech). Searches were conducted iteratively through academic databases, government archives, and open institutional repositories to identify the most relevant and recent materials.

Consistent with case study methodology, multiple sources were triangulated for each indicator, and evidence was systematically reviewed across cases. This approach aligns with Eisenhardt’s emphasis on combining archival and documentary data with replication logic, thereby strengthening construct validity and ensuring robustness of the dataset.

4. Results

4.1. Within-Case Analysis

4.1.1. United States Within-Case Analysis Findings

The United States exhibits a policy market configuration highly conducive to deploying high-autonomy public–private partnership (PPP) models. At the policy level, national strategic goals (P1) consistently frame space as a domain of leadership and security (WhiteHouse, 2020b, 2021), reinforcing sovereign capability while enabling commercial expansion. This dual imperative exemplifies an enabler-oriented governance role (P2) (Vidmar, 2021), in which the state provides initial support through contracting mechanisms, infrastructure access, and regulatory structure (P3) while delegating development, ownership, and operations to capable private actors. Program such as Commercial Orbital Transportation Services (COTS), Commercial Resupply Services (CRS), and Commercial Lunar Payload Services (CLPS) show this model. In this model, firms retain full design, ownership, and operational control; NASA primarily pays for achieving performance milestones and subsequently purchases transportation as a service (Denis et al., 2020). This institutional logic is advanced through flexible procurement instruments, most notably milestone-based Space Act Agreements (SAAs) (NASA, 2025b) and Other Transaction Authorities (OTAs) (Halchin, 2008). The regulatory structure is similarly flexible (Baldwin et al., 2011), exemplified by the FAA’s adaptive licensing framework and the moratorium on occupant safety regulation, both prioritizing responsiveness and innovation over rigid rule standardization (FAA, 2021, 2024).

Capital market access (M1) in the United States is high. Financial development theory indicates that the depth of investable funds, together with a diversified set of financing instruments, is essential for mobilizing private investment and achieving successful public–private partnerships (Beck et al., 2000; Levine & Zervos, 1998). The contemporary U.S. space economy meets both conditions, demonstrating a high-capital access environment. Public equity access has expanded through Special Purpose Acquisition Company (SPAC) mergers, while government programs further enhance capital access through NASA’s SBIR/STTR and Tipping Point initiatives (NASA, 2023a, 2025a).

The United States’ private-sector capability (M2) satisfies the definition of a high-capability environment in which firms operate autonomously across the entire value chain and field hardware is proven at TRL 9, the highest level recognized by NASA (Freeman, 1995; Lundvall, 2024; NASA, 2023b; Robinson & Mazzucato, 2019). Firms operate across the full value chain, from upstream to downstream services. Commercial demand (M3) is equally robust, sustained by institutional procurement and growing private-sector buyers in both domestic and international markets (SIA, 2024; SPACEX, 2025; THAICOM, 2024).

Table 3. United States—six indicators, corresponding features, and representative examples.

	Indicator	Classification	Features	Representative Examples
Policy	(P1) National Strategic Goals	Leadership, National Security	Space as strategic leadership and security domain	1. The U.S. National Space Policy designates space as a strategic interest, emphasizing leadership and security (WhiteHouse, 2020b, 2021).
	(P2) Government Role Preference	Enabler	Delegation of routine operations; Space Act agreements; market-shaping ecosystem	1. Transferring routine operations to private sector and avoiding direct competition (NOAA, 2015; Villhard & Hogan, 2004; WhiteHouse, 2020a). 2. NASA has increasingly relied on milestone-based SAA (Denis et al., 2020). 3. NASA provide advance-purchase commitments and technical insight, while leaving capital investment, and operations to industry (Mazzucato & Robinson, 2018; Tinoco, 2018; Zancan et al., 2024).
	(P3) Regulatory Structure	Flexible	Adaptive licensing; procurement flexibility; supportive innovation climate	1. FAA Part 450 consolidates launch licenses (FAA, 2021). 2. NASA’s use of Space Act Agreements under OTA bypasses FAR constraints (Halchin, 2008; NASA, 2014). 3. Moratorium on human spaceflight safety regulations until 2028; milestone-based contracts (CRS, 2025).
Market	(M1) Capital Access	High	Robust venture capital market; public equity liquidity access; government co-investment mechanism	1. USD 347.9 billion raised across 2197 space deals (SpaceCapital, 2025). 2. USD 4 billion raised via SPAC mergers with strong public equity access and investor liquidity (BryceTech, 2023). 3. NASA SBIR/STTR (NASA, 2025a) and Tipping Point program (NASA, 2023a).
	(M2) Private Sector Capability	High	Full value-chain autonomy; launch dominance; downstream maturity	1. U.S. firms operate across full value chain with TRL 9 systems (NASA, 2023b). 2. 145 of 259 global launches in 2024 (PayloadSpace, 2024). 3. Downstream markets led by firms such as Starlink, Planet, and Maxar (Pfandzelter & Bermbach, 2023).
	(M3) Commercial Demand	High	Stable institutional procurement; large domestic and international market	1. NASA and DOD contract commercial services (Autry, 2018; Rausser et al., 2023; Zapata, 2023). 2. Expanding satellite data services market (SIA, 2024; SPACEX, 2025). 3. International reliance on U.S. launch providers (SAPCENEWS, 2024; THAICOM, 2024)

provides a structured synthesis of these features, outlining their classifications and representative examples from the USA’s policy and market environment.

4.1.2. Predominant PPP Models in the United States: PF-FDO and PFD-FO

The United States removes the constraints on private autonomy and allow high-autonomy PPP models to dominate. Within this environment, PF-FDO and PFD-FO models predominate. Nonetheless, the United States selectively adopts lower-autonomy models, such as PFD and OCon, when project conditions require heightened government oversight or long-term institutional continuity. These include national security missions and sectors with insufficient commercial demand. This context-sensitive application of multiple PPP forms underscores the U.S. government’s strategic flexibility in tailoring PPP structures to program-specific requirements, even within a policy environment that broadly favors private-sector leadership and innovation.

4.1.3. Japan Within-Case Analysis Findings

Japan’s current space strategy reflects a shift from its traditionally non-military stance toward a proactive regional security role aligned with the doctrine of proactive pacifism (Kallender-Umezu, 2013). National strategic goals (P1) integrate security, scientific advancement, and market expansion (CAO, 2020, 2025), but they are pursued through state-led governance and market structures that limit private autonomy. In this strategic setting, Japan exhibits a policy–market configuration defined by centralized state authority, restrictive regulation, and limited market diversity, which collectively constrain the development of high-autonomy PPP models.

The government role preference (P2) model is fundamentally principal-oriented. The state defines mission scope, allocates funding, and manages implementation, while private actors operate in a subordinate technical role (Pekkanen, 2020; Tani-Hatakenaka, 2023). This model reflects a legacy of strong institutional coordination, centralized authority, and national interest orientation (Suzuki, 2005, 2013; Wakimoto, 2019) but limits decentralized innovation and private-sector autonomy.

The regulatory structure (P3) reinforces this orientation. Anchored in the Basic Space Act 2008 (Aoki, 2008; Sawako, 2009) and the Space Activities Act 2016 (CAO, 2017a, 2017b), Japan’s licensing system is highly structured, strictly territorial, and procedurally demanding (Aoki, 2009; CAO, 2016, 2017b).

Within the market environment, Japan combines substantial public funding with limited private financial diversity, resulting in moderate capital access (M1). The Space Strategy Fund (SSF) supports R&D and technology demonstration through grants and entrustment, but it explicitly excludes equity investment (JAXA, 2024). Programs like J-SPARC offer co-financing and technical support for start-ups, yet it is framed as a government-directed rather than a market-driven investment vehicle (JAXA, 2018). Private-sector capability(M2) is similarly moderate: the space sector follows a triple helix model (Etzkowitz & Leydesdorff, 2000), with firms acting more as government contractors than independent operators with limited orbital success. Commercial demand (M3) is weak, with institutional procurement dominating sales and exports accounting for only a small share of revenue (SJAC, 2024; Weforum, 2024).

Table 4. Japan—six indicators, corresponding features, and representative examples.

	Indicator	Classification	Features	Representative Examples
Policy	(P1) National Strategic Goals	Security, Scientific Advancement, Market Expansion	Space as a multi- dimensional strategic domain	1. The strategy integrates three mains interlinked objectives (CAO, 2020, 2025). 2. QZSS and IGS support national defense and civil infrastructure (CAO, 2023). 3. Artemis and ISS collaboration (Araki et al., 2022; Pekkanen et al., 2024a, 2024b; Tsuchida et al., 2011). 4. Large public fund aimed at doubling the industry’s size to JPY 8 trillion (CAO, 2017c).
	(P2) Government Role Preference	Principal	Mission authority centralized; cabinet-led, multi-ministerial governance; JAXA act as a technical execution agency	1. Government defines scope, funds development, and oversees system management (Pekkanen, 2020; Tani-Hatakenaka, 2023). 2. Cabinet Office consensus required prior to implementation (Uchino, 2017). 3. JAXA acts as technical agent executing multi-ministry directives (Kallender, 2017).
	(P3) Regulatory Structure	Restrictive	Multi-stage licensing with high-level government approval; stringent compliance and liability standards; strictly territorial, which constrains commercial flexibility	1. Separate licenses required for launch and operation; Prime Ministerial approval mandated under 2016 Space Activities Act (CAO, 2017a, 2017b). 2. Operators must meet detailed requirements; no fast-track options (CAO, 2016; Kozuka, 2023). 3. Licensing applies only to launches within Japanese territory or from Japanese-registered platforms (Aoki, 2009).
Market	(M1) Capital Access	Moderate	Large-scale public funding focused on grants, not equity; limited financial diversity	1. JPY 1 trillion Space Strategy Fund (SSF) (JAXA, 2024), JAXA unable to make equity investments or issue unrestricted R&D subsidies (Uchino, 2017). 2. Absence of scalable public–private equity partnerships, and externally funded BERD remains rare (OECD, 2024).
	(M2) Private Sector Capability	Moderate	Private-sector firms active across upstream and downstream, but primarily reliant on government-led programs	1. In upstream, launch startups have not reached orbit independently (InterstellarTechnologies, 2024; SPACEONE, 2025). 2. Downstream firms operate under state-led programs (Axelspace, 2021; Synspective, 2025).
	(M3) Commercial Demand	Low	Demand dominated by government procurement, low export share, and limited demand diversity across sectors	1. Only 3% of upstream revenue came from exports, and 68% of domestic space sales related to public-sector buyers (SJAC, 2024). 2. “The biggest customer for space-company services still tends to be the government” (Weforum, 2024).

provides a structured synthesis of these features, outlining their classifications and representative examples from Japan’s policy and market environment.

4.1.4. Predominant PPP Models in Japan: PFD, Early-Stage PFD-FO

Japan’s indicator constellation favors PPP models with low to moderate private autonomy. Consistent with Kim’s (2023b) typology, PFD structures dominate upstream sectors, where private firms co-finance development under JAXA-led programs that retain IP and mission control. Early PFD-FO pilots appear in downstream applications (e.g., J-SPARC SAR analytics), where firms operate post-handover but remain bound by public milestones and data-sharing rules.

OCon models are selectively applied to ground segment and data-distribution services under tightly specified performance contracts. These patterns reflect Japan’s broader strategic mix: national security drives sovereign control, science initiatives promote PFD models with multilateral cost-sharing, and market-expansion goals allow limited PFD-FO experimentation. However, principal-led governance (P2), restrictive regulations (P3), and low commercial demand (M3) constrain higher-autonomy models like PF-FDO. Until financing tools and domestic demand deepen, PFD will remain the ceiling of PPP autonomy, with OCon used tactically.

4.1.5. India Within-Case Analysis Findings

India’s 2023 Space Policy articulates dual national strategic goals (P1), which are national security and socio-economic development, positioning space as a dual-purpose strategic domain (ISRO, 2023a). Rajagopalan and Stroikos (2024) highlight India’s pursuit of strategic autonomy through state-controlled indigenous capabilities in launch, navigation, and earth observation. These objectives are pursued through a government preference role (P2) that reflects an ongoing transition from state control to collaborative partnership. In this strategic setting, India exhibits a policy–market configuration defined by partnership and structured regulation but still limited market diversity, which collectively constrain the development of high-autonomy PPP models.

India’s approach to public–private partnerships has evolved from gatekeeping to strategic co-development, reflecting a recalibrated state role (IN-SPACe, 2023a). The establishment of the dual framework of IN-SPACe and NSIL illustrates this shift (ISRO, 2023a): IN-SPACe promotes, guides, and authorizes private activity and enables a push-and-pull structure in which liberalization creates opportunities, institutional support provides infrastructure, and procurement is ensured (Van der Waldt & Fourie, 2022), while NSIL commercializes ISRO technologies (NSIL, 2023c). India’s regulatory structure (P3) has shifted from ISRO-centric discretion to a codified, rule-based framework. The Indian Space Policy (ISRO, 2023a) explicitly emphasizes the creation of “a stable and predictable regulatory framework to provide a level playing field to Non-Government Entities in the Space sector” through the IN-SPACe act as a “single window” agency (ISRO, 2023a). While implementation gaps remain, such as unified IP rules and inter-agency coordination (Chitra & Shet, 2024), the system reflects a legally grounded regulatory shift.

India combines expanding financial channels such as space-focused venture capital and FDI reforms (PIB, 2024a, 2024c) as a strategic investment tool, wherein governments establish dedicated VC vehicles to align national innovation ecosystems with long-term strategic goals (Mehta, 2024; Rajagopalan & Stroikos, 2024), producing moderate capital access (M1). Private-sector capability (M2) is similarly moderate: firms are increasingly active across upstream and downstream activities but remain dependent on public infrastructure and procurement (Nagendra & Basu, 2016; Saxena, 2023). Commercial demand (M3) is also moderate, with upstream markets anchored by government contracts and downstream services only gradually expanding through partnership models (Baluragi & Suresh, 2020; Cottom, 2022; Porel & Singh, 2025).

Table 5. India—six indicators, corresponding features, and representative examples.

	Indicator	Classification	Features	Representative Examples
Policy	(P1) National Strategic Goals	National Security, Economic Development	Space as a dual-purpose strategic domain	1. Dual national objectives: national security and socio-economic development (ISRO, 2023a). 2. Strategic autonomy through state-controlled indigenous capabilities in launch (PSLV, GSLV, small-lift vehicles) (ISRO, 2023b), navigation (NavIC), and Earth observation (ISRO, 2025). 3. Liberalizing “the entire value-chain” for private-sector participation and expansion of global market share (ISRO, 2023a).
	(P2) Government Role Preference	Partner	Dual framework: IN-SPACe authorizes private activity; NSIL commercializes ISRO technologies	1. NSIL’s contract with a HAL-L&T consortium for end-to-end PSLV-XL production (NSIL, 2022). 2. LVM-3 tender under a build–operate–transfer model, marking India’s first heavy-launch PPP (NSIL, 2023b).
	(P3) Regulatory Structure	Structured and Predictable	IN-SPACe as a “single window” regulator empowered to issue norms	IN-SPACe’s Norms, Guidelines, and Procedures (NGPs) standardized application processes, 75–120-day statutory review timelines, and objective assessment criteria covering technical readiness, financial solvency, and liability insurance (IN-SPACe, 2023b; JSA, 2024).
Market	(M1) Capital Access	Moderate	FDI liberalization improves cross-border access, but capital ecosystem remains shallow; government-focused venture capital fund	1. There is 100% foreign ownership in satellite manufacturing and 74% in operations (PIB, 2024b). 2. IN-SPACe-administered INR 1000 crore fund launched for startup finance (DOS, 2024).
	(M2) Private Sector Capability	Moderate	Private-sector firms active across both upstream and downstream but remain operationally dependent on public infrastructure and contracts	1. In upstream, Skyroot Aerospace and AgniKul focus on small launch vehicles in the demonstration phase (Bhalodia, 2024). 2. Large firms like L&T operate as ISRO contractors (L&T, 2023). 3. In downstream, Pixxel has deployed EO constellations but remains limited in scale (Pixxel, 2024).
	(M3) Commercial Demand	Moderate	Government-led upstream demand; growing downstream demand under government partnership procurement	1. NSIL’s earned ~USD 360 million via Contracts FY 2022–23 contracts (EUTELSAT, 2022; NSIL, 2023a). 2. GSAT-7B public-funded PPP (PIB, 2023a). 3. NSIL–Tata Play’s GSAT-24 direct-to-home (PIB, 2023b).

provides a structured synthesis of these features, outlining their classifications and representative examples from India’s policy and market environment.

4.1.6. Predominant PPP Models in India: PFD and Early-Stage PFD-FO

India’s policy and market conditions favor PPP models with mid-level private autonomy, supported by a partner-oriented governance approach and a structured, predictable regulatory framework. Consistent with Kim’s (2023b) typology, PFD models dominate upstream sectors, where private firms co-finance development under government-led programs managed by ISRO and NSIL. Early PFD-FO pilots are emerging downstream, notably through the IN-SPACe Seed Fund, where private firms finance, own, and operate satellites under government-defined data-sharing milestones.

OCon models are selectively used in ground infrastructure and telecom payload operations, under performance-linked agreements. However, limited capital access (M1), moderate private-sector capability (M2), and developing commercial demand (M3) constrain the adoption of higher-autonomy models like PFD-FO and PF-FDO.

4.1.7. United Arab Emirates Within-Case Analysis Findings

The UAE’s national space goals (P1) outline six distinct goals, centering on two overarching imperatives: economic diversification and international prestige (UAESA, 2019b). Simultaneously, space serves as a platform for global soft power (Al Rashedi et al., 2020). This logic aligns with broader patterns in UAE policymaking, where emerging sectors are often shaped by national branding and soft power projection (Antwi-Boateng & Alhashmi, 2022; Ulrichsen, 2016).

In the UAE, government preference role (P2) in the space sector follows a highly centralized and directive model, in which the state assumes the role of principal. Private-sector and international actors primarily contribute as subsystem providers or service contractors, operating within tightly defined state agendas (Al Jawali et al., 2022).

This model is anchored by two core institutions: the UAE Space Agency (UAESA) defines requirements, retains tasking rights, and governs data access, even with private or international partners (SPACENEWS, 2022), and the Mohammed bin Rashid Space (MBRSC) leads technical execution and program delivery (UAESA, 2019b). This reflects the Steer-and-Enable model from New Public Management (NPM), where delegation occurs within strict state-defined rules (Kalimullah et al., 2012; Osborne, 2006). The UAE has established a restrictive and comprehensive regulatory structure (P3) for space activities (UAELegistlation, 2023; UAESA, 2023), under which all space-related operations fall under the exclusive jurisdiction of the UAESA.

Within the market environment, capital access (M1) is low and insufficiently diversified, reflecting policy instruments (Hussainey & Aljifri, 2012), where innovation pipelines are strongly curated and financed by public agencies, leaving limited room for independent financial actors’ entrepreneurship (Lamine et al., 2021). It is primarily administrated by the UAE Space Agency, sovereign wealth channels, and a state-owned conglomerate (EDGE, 2025; Mubadala, 2024). The United Arab Emirates’ private space sector capability (M2) is low and best described as early-stage, small in scale, and structurally dependent on government leadership and international collaboration (Alzaabi et al., 2024; Vernile, 2018). The UAE’s commercial demand (M3) is low in scope and structurally state-led, with private firms acting primarily as contractors to public agencies (Mubadala, 2024; UAESA, 2019a), and most missions are positioned around national prestige, bilateral cooperation, or capacity-building rather than commercial revenue streams.

Table 6. The UAE—six indicators, corresponding features, and representative examples.

	Indicator	Classification	Features	Representative Examples
Policy	(P1) National Strategic Goals	Strategic Diversification and Prestige	Space as a platform for global soft power and economic diversification	1. National space objectives center on two overarching imperatives: economic diversification and international prestige (UAESA, 2019b). 2. The Emirates Mars Mission and astronaut program (Amiri et al., 2022).
	(P2) Government Role Preference	Principal	Highly centralized and directive; private and international actors contribute as subsystem providers or service contractors	1. Dubai Sat-1&2 were developed with South Korean partners (Al Harmi, 2016). 2. In the communications domain, Thuraya-4 was developed with Airbus, under state ownership and operational control with Yahsat, a government-owned entity (AIRBUS, 2024; Al Tair, 2017).
	(P3) Regulatory Structure	Restrictive	Centralized and discretionary licensing with broad evaluative scope; permission required before entity formation	1. Federal Decree Law No. 46 in 2023 and the Regulation on the Authorization of Space Activities in 2023 centralized licensing; (UAELegistlation, 2023; UAESA, 2023); Article 5 allows review based on any criteria “deemed appropriate” before granting a license (UAESA, 2023). 2. Prior No-Objection Certificate (NOC) required before entity formation from the Space Agency (UAESA, 2023).
Market	(M1) Capital Access	Low	Dominant government funding and sovereign wealth channels; absence of diverse investment channels	1. Space Economic Zone and Space Means Business programs for start-ups and small and medium-sized enterprises and National Space Fund (UAESA, 2024). 2. Sovereign entities such as Mubadala and EDGE control strategic financing (EDGE, 2025; Mubadala, 2024). 3. JV firms such as Orbit works and Stellaria rely on state-linked institutions (The U.S.–U.A.E. Business Council, 2024).
	(M2) Private Sector Capability	Low	Early-stage capability and structurally dependent on government leadership and international collaboration	1. Hope Probe and Rashid Rover led by MBRSC; all launches procured internationally (Amiri et al., 2022; ispace, 2025; MBRSC, 2025). Downstream initiatives are led by state-affiliated entities such as SPACE42 (Space42, 2024). 2. Startups remain limited to early-stage R&D (The U.S.–U.A.E. Business Council, 2024).
	(M3) Commercial Demand	Low	Dominated by state-led demand with limited demand diversity; international demand developing	1. Yahsat’s Thuraya DTH and VSAT services primarily serve government clients (WAM, 2023). 2. Al Yah 3 expansion into Brazil and Africa is state-backed Via Mubadala and G42 (WAM, 2014).

provides a structured synthesis of these features, outlining their classifications and representative examples from the UAE’s policy and market environment.

4.1.8. Predominant PPP Models in the UAE: PFD

The UAE’s PPP model reflects low private autonomy, shaped by a centralized governance structure. In line with Kim’s (2023b) typology, the dominant form is PFD, where private firms support government-led missions through subsystem provision or engineering services but do not take on ownership or operational responsibility. Higher-autonomy models such as PFD-FO and PF-FDO are absent. While policy documents signal interest in expanding private-sector roles, there is no current evidence of firms independently owning or operating space assets. Given the current constraints on financing (M1), limited technical autonomy in the private sector (M2), and narrow market demand (M3), PFD remains the ceiling for PPP model maturity. The UAE’s space PPPs are best understood as delivery partnerships, not as vehicles for private-sector leadership.

Table 7. Predominant PPP models across the four cases.

Country	Predominant PPP Models
USA	PF-FDO, PFD-FO
Japan	PFD, early stage of PFD-FO
India	PFD, early stage of PFD-FO
UAE	PFD

summarizes the predominant PPP models across the four case countries: the United States, Japan, India, and the United Arab Emirates. These within-case analysis results set the analytical foundation for the cross-case analysis that follows, where key patterns, divergences, and causal mechanisms behind model variation are explored in depth.

4.2. Cross-Case Analyses

This section presents a comparative analysis of six country pairs, building directly on the findings established in the within-case assessments. The analysis follows the second tactic outlined in Eisenhardt’s theory-building methodology (Eisenhardt, 1989, 2021), which involves the systematic comparison of case pairs to identify structural similarities, categorical differences, and consistent explanatory patterns.

Figure 2 shows the spectrum of four PPP models across the six pairs analyzed in this section, capturing the variation in institutional delegation and private-sector participation among different governance and market configurations. The cross-case analysis was conducted through six pairwise comparisons across the four countries. While these six comparisons highlighted variations in pathways, the results converged into four distinct patterns of PPP model outcomes, as illustrated in Figure 2. This synthesis demonstrates that countries may arrive at similar PPP configurations through different policy–market dynamics.

• USA–UAE: This comparison contrasts a fully aligned PPP ecosystem (U.S.) with a structurally constrained one (UAE). Both pursue ambitious space strategies but diverge in purpose: the U.S. emphasizes strategic leadership (P1), while the UAE focuses on prestige and symbolic advancement. The U.S. combines enabling governance (P2), flexible regulation (P3), and high market readiness (M1–M3), supporting full delegation through PF-FDO and PFD-FO models. In contrast, the UAE exhibits principal-led governance, discretionary regulation, and low private capability, capital access, and commercial demand. These structural limitations—not just policy intent—constrain PPPs to basic PFD forms, where private actors serve as vendors within state-owned systems. High-autonomy PPPs require both institutional willingness and market enablers. Where either is absent, especially in all three market environment indicators, delegation becomes structurally impossible, not merely politically undesirable.
• Japan–India: This comparison examines two emerging space powers that, despite distinct institutional trajectories, converge on similar PPP typologies of PFD and early-stage PFD-FO models shaped under moderate capital access (M1) and private-sector capability (M2). Divergent governance structures can yield structurally similar outcomes when filtered through differing institutional constraints. Japan maintains a principal-led approach emphasizing control and mission assurance, while India adopts a partner-style posture, aiming to crowd in private actors through regulatory reform. Both exhibit moderate M1 and M2, but Japan’s restrictive regulation (P3) and hierarchical coordination limit delegation. The key differentiator is commercial demand (M3). India’s is moderately diversifying through defense payloads and hybrid satellite services, whereas Japan remains supply-driven, with weak private contracting and minimal demand-side dynamism. The absence of PF-FDO models in both countries underscores that PPP advancement requires more than technical capacity or funding. It hinges on the co-evolution of regulatory devolution, market liberalization, and demand diversification. While India moves toward autonomy, Japan’s governance logic reinforces centralization and institutional path dependence. PPP outcomes are shaped not only by market indicators but by how those indicators interact with governance intent and institutional design.
• UAE–Japan: Both Japan and the UAE feature principal-led governance, restrictive regulatory regimes (P3), low commercial demand (M3), and public-sector-dominated funding structures (M1), offering a critical test of the emerging construction of systemic alignment. Despite their shared constraints, PPP outcomes diverge. Japan supports early-stage PFD-FO models, particularly in analytics and subsystem integration, while the UAE remains confined to low-autonomy PFD configurations. This asymmetry is explained by differences in private-sector capability (M2), capital access (M1), and strategic intent (P1). Private-sector capability (M2) and capital access (M1) are critical preconditions for PPP advancement, particularly in centralized, regulation-heavy systems. Japan’s moderate M1 and M2 levels enable limited evolution despite rigid institutions, the UAE’s low levels in both dimensions result in structural stasis. Under a principal-led governance model with restrictive regulation, it is the strength of market environment indicators, not policy reform alone, that enables PPPs to move toward higher autonomy.
• UAE–India: This comparison explores how institutional reform rather than market maturity alone can enable PPP progression. Both India and the UAE maintain centralized, mission-driven governance, but they diverge in regulatory and strategic orientation: the UAE operates a principal-led model with discretionary restrictive regulation, while India follows a partner-style framework underpinned by structured and predictable regulation and reform. As a result, PPP outcomes differ. The UAE remains confined to low-autonomy PFD models dominated by public funding and operations. India has advanced to early PFD-FO models in downstream services, allowing limited private ownership under state-defined conditions. Strategically (P1), India’s dual goals of economic growth and security incentivize capability devolution, while the UAE’s prestige-driven posture limits private enablement. This comparison highlights that PPP evolution in centralized systems depends not just on regulatory reform but on capital diversification, private capability, and strategic intent. India demonstrates that structured reform can enable upward PPP mobility; the UAE illustrates the limits of symbolic liberalization without systemic enablers.
• India–USA: This comparison illustrates how institutional logics and market structures condition PPP autonomy. Both countries support commercial participation but diverge in how far delegation proceeds. The U.S. operates an enabling government role system (P2) with flexible regulation (P3), a robust market environment, and private operation and ownership in PF-FDO and PFD-FO models. India shows transitional dynamics: structured regulation, moderate market indicators, and emerging markets enable early PFD-FO models, especially in downstream domains. However, upstream projects remain publicly controlled. The contrast illustrates that structural asymmetries, not just policy vision, explain model divergence. The U.S. framework is aligned across all indicators; India’s capacity-building is partial. This case suggests that policy reform must coincide with capital depth, industrial autonomy, and institutional readiness to enable full-cycle delegation. Policy reform must coincide with strong market environment conditions: specifically, high levels of capital access, private-sector capability, and commercial demand, as well as enabling and flexible governance structures to support higher autonomy PPP models.
• Japan–USA: The juxtaposition of Japan and the United States reveals how structurally divergent space governance systems produce distinct public–private partnership (PPP) outcomes. The U.S. system embodies a delegative logic, in which the state retains strategic oversight but intentionally decentralizes operational authority to private firms. Japan, by contrast, is governed by a stewardship logic in which the state preserves centralized control not only to safeguard national objectives but to manage systemic interdependencies. Government agencies prioritize mission integrity over market autonomy, producing PPPs that favor institutional certainty over flexibility. These contrasting approaches demonstrate that PPP evolution is not only a function of resource levels or regulatory thresholds but of how national innovation systems assign authority, structure accountability, and internalize uncertainty. This distinction explains why PPPs in Japan, despite moderate capital access, remain bounded within state-defined performance corridors.

Across all six comparisons, PPP model evolution is configurational, path-dependent, and institutionally mediated. No single factor is sufficient on its own. Rather, progression toward high-autonomy models (PFD-FO, PF-FDO) emerges when market capacity (M1–M3) aligns with institutional intent (P1–P3). Private-sector capability (M2) consistently appears as a threshold condition: where it is absent, even policy reforms stall; where present, it enables partial delegation, as seen in Japan and India. Commercial demand (M3) determines whether capable firms can sustain independent operations or remain government dependent. Capital access (M1) plays a contingent role, enabling scale but not initiating evolution. Governance posture (P2) and regulation (P3) emerge as differentiators of autonomy, particularly when technical and financial maturity exist but delegation does not. Cases like India–UAE illustrate how governance restructuring can unlock progression even under constrained conditions, while Japan–USA shows that technical readiness alone does not guarantee transition without institutional willingness. These findings reinforce that PPP forms must be understood within their systemic context, not as static types but as reflections of broader alignment.

4.3. Decision-Making Framework for Selecting PPP Models

To support analytically grounded PPP model selection, a decision-making framework is developed as a two-step evaluative mechanism linking national conditions to suitable partnership configurations. This framework acts as a diagnostic tool that not only categorizes existing PPPs but also aligns PPP model complexity with institutional and market conditions. It enables decision-makers to identify key levers, such as regulatory reform or capital access, for progressing toward more autonomous and commercially driven configurations.

• Step 1: Assessment of Current Market and Policy Conditions

This step evaluates a country’s policy and market environment using six diagnostic indicators, organized into two categories: policy environment indicators (P1–P3) and market environment indicators (M1–M3). Policy indicators are analyzed using thematic typologies derived from the structure and stated objectives of national space policy narratives. Market environment indicators are assessed using a three-level ordinal scale (high, moderate, or low) aligned with comparative frameworks commonly used in PPP readiness evaluations. This structured assessment generates a contextual profile of national readiness, which serves as the input for Step 2.

• Step 2: Model Matching Based on Indicator Configuration

Once the indicator profile is established, it is matched against a spectrum of typical space PPP configurations. Although P1 is not used to distinguish between PPP models in Step 2, it acts as a foundational condition that informs the state’s willingness and purpose for engaging in PPPs. These models are arranged along a continuum of increasing private-sector responsibility and autonomy, and each is characterized by distinctive combinations of M1–M3 and P1–P3 indicators. Figure 3 illustrates the decision-making framework for selecting space PPP models.

5. Discussion

This study addresses a critical gap in space policy discourse: the absence of a structured, comparative framework to guide governments in selecting public–private partnership (PPP) models suited to their institutional and market conditions. As the space domain enters an era marked by commercialization, geopolitical competition (Doboš, 2018; Steele, 2023), and decentralized mission leadership (Lanaj et al., 2013), PPPs have emerged not only as procurement mechanisms but also as tools for advancing innovation, building capacity, and asserting strategic influence (Aliberti, 2018; Carbonara & Pellegrino, 2020; Jakhu & Pelton, 2017).

Despite their growing prevalence, policymakers, space agencies, and private actors still lack analytical tools to identify models aligned with their strategic objectives and systemic capabilities. To address this gap, this study introduces a framework that integrates policy and market indicators across three maturity levels in the space sector: mature, emerging, and nascent. Cross-case analysis of the United States, Japan, India, and the United Arab Emirates demonstrates that PPP typologies are not merely functions of technical capacity or capital depth. Rather, they reflect broader configurations of governance posture, regulatory design, and market structure. This study finds that high-autonomy models such as PFD-FO and PF-FDO are only possible when critical systemic factors capital access, regulatory flexibility, institutional alignment, and private-sector capability are simultaneously reinforced. This underscores a key insight: PPPs do not evolve linearly, and technical capacity alone is insufficient; governance choices and institutional design shape what models can emerge. Japan, for example, exhibits strong technical capabilities but is constrained by rigid regulatory frameworks, which prevent it from achieving high-autonomy PPPs.

The framework developed in this study makes three contributions. First, it challenges techno-centric assumptions (Brennan, 2015; Servaes & Hoyng, 2017) by showing that PPP variation is deeply shaped by national governance posture, not just technical maturity. Second, it demonstrates that systemic alignment across institutional, financial, and market domains is essential for enabling high-autonomy, commercially viable PPPs. Third, it offers a practical, integrated decision-making tool that enables governments to benchmark readiness, identify structural levers such as regulatory reform or capital access, and select PPP models suited to their unique context, especially in emerging and nascent space economies. Accordingly, this study offers practical steps for policymakers in emerging and nascent space economies seeking to evolve from lower-autonomy PPP models toward higher-autonomy configurations. A combination of reforms could support this transition. Strengthening regulatory frameworks—shifting from restrictive regimes toward structured, predictable, and ultimately flexible models—can provide the foundation for credible private-sector participation. Expanding access to capital through targeted public–private venture initiatives and easing restrictions on foreign investment can diversify financial channels beyond traditional state funding. Capability-building measures such as technology transfer, incubator support, and incentives for joint ventures can enable firms to progress from subcontracting roles toward operational independence. Commercial demand-side interventions, such as anchor tenancy agreements or guaranteed procurement, may also play a stabilizing role in early- and mid-stage markets as private demand develops. As commercial demand becomes more diversified, space PPPs can evolve beyond subsidy-driven models toward higher-autonomy partnerships that reduce costs and stimulate competitiveness.

While existing PPP frameworks provide important foundations, they remain limited in scope relative to the objectives of this study. Performance measurement models, such as Liu et al.’s (2015) stakeholder-oriented prism, emphasize aligning strategy, processes, and capabilities with stakeholder contributions across the project life cycle. These approaches underscore the importance of systemic coherence but are primarily evaluative tools, designed to assess success after implementation rather than to guide model selection in advance. Similarly, risk-oriented frameworks such as Zitron (2006) and contract design methodologies emphasize value-for-money assessment and optimal risk allocation during procurement. However, they do not address how governments should determine which type of PPP is institutionally feasible at a given stage of policy and market development. Sector-specific decision tools in transport, health, and utilities (Akintoye et al., 2015; Darko et al., 2023; Nutt, 2006) provide valuable project-level insights, often applying multi-criteria or analytic hierarchy methods, but they remain context-bound and do not generalize to the macro-level institutional environments examined here.

Within the space sector, the PPP literature has been even more limited, focusing primarily on case narratives and typologies. Kim’s (2023b) typology offers an essential classification of space PPP models but stops short of embedding them within national policy or market contexts. Other analyses (Tinoco, 2018; Zancan et al., 2024) highlight the uniqueness of NewSpace arrangements yet remain thematic. Consequently, no existing framework provides governments, particularly those in emerging or nascent economies, with a structured means of matching their institutional and market conditions to appropriate PPP models. To date, no structured decision-making framework exists to help governments, space agencies, and the private sector select appropriate PPP models based on national readiness. This distinction clarifies the novelty of the present study. By linking PPP typology to six analytically defined indicators of policy and market environment, the framework advances beyond evaluation or contract design toward model-selection logic.

While the framework is tailored to the space sector, its underlying logic is namely that PPP forms emerge through the alignment of governance structure and market conditions discussed in the broader PPP literature (Savas & Savas, 2000; Sehgal & Dubey, 2019). Scholars such as Hodge and Greve (2007) and Grimsey and Lewis (2002) have also long emphasized that institutional context and governance capacity and market environment critically shape PPP success across sectors, including transport, health, and utilities. Link and Scott (2019) underscore the interplay between institutional design and market evolution.

What distinguishes the space domain, however, is the elevated role of strategic autonomy, national prestige, and dual-use technology considerations, which intensify the need for context-sensitive model selection. Nonetheless, the diagnostic approach proposed here holds conceptual resonance with other domains where public interest intersects with high-capital, innovation-driven industries. As such, while this framework is empirically grounded in the space domain, its applicability may extend to emerging PPPs in advanced technology sectors, offering a foundation for comparative institutional analysis beyond the space economy. Future research could extend the application of this framework to other domains that are undergoing public–private transformation, such as artificial intelligence or digital infrastructure, where governance structures and market readiness similarly shape partnership models.

This framework represents the first empirically grounded tool for PPP-type selection in the space sector and one of the earliest efforts to formalize model-selection logic in the broader PPP literature.

6. Conclusions and Recommendations

This study introduces the first decision-making framework for selecting public–private partnership (PPP) models in the space sector based on national policy and the market environment by linking six analytically defined indicators—national strategic goals, governance role preference, regulatory structure, capital access, private-sector capability, and commercial demand. The framework particularly supports governments in countries with emerging or nascent space programs in benchmarking their current conditions and identifying realistic pathways toward high-autonomy PPPs and innovation-oriented PPP configurations.

Key beneficiaries of this framework include national space agencies, policy planners, and public procurement bodies tasked with shaping industrial partnerships in the space domain. Development banks, international organizations, and capacity-building entities may also use this framework to assess structural gaps and align investments with institutional capacity. In addition, private space firms can gain insight into which national environments are most conducive to sustained collaboration and market entry. For scholars and researchers, this study offers a foundational contribution to the emerging literature on space-sector PPPs, establishing the first structured decision-making framework that can support future academic inquiry into how public–private models evolve in response to national and global forces.

This study is not without limitations. While the framework centers on national-level institutional and market conditions, it does not incorporate geopolitical dynamics that increasingly shape the strategic context of space sector development. As geopolitical competition, alliance dynamics, and global power shifts are increasingly central to national space strategies, factors such as strategic alignment with global space powers and regional competition can influence a country’s appetite for the selection of different forms of public–private collaboration, particularly in dual-use or security-sensitive sectors. Although these dimensions operate largely at a transnational level and remain beyond the analytical scope of this study, future research may examine how geopolitical alignments intersect with PPP selection type.

Ultimately, this study offers the first framework for understanding how PPPs evolve in the space domain. It provides stakeholders with a structured basis for deciding where to begin; which models to pursue; and what institutional, regulatory, or market reforms are required to move toward more strategically aligned forms of public–private partnership in an increasingly complex space environment.