Why Venture Activity Fails to Translate into Outcomes: Validation Alignment and Institutionally Mediated Market Formation

1. Introduction

1.1. Background and Context

Entrepreneurship scholarship has long treated visible venture activity as a reasonable indicator of forward movement. Prototype development, customer discovery, pilot launches, partnership announcements, and milestone completion are commonly interpreted as evidence that a venture is progressing toward commercialization. This intuition has been reinforced by experimentation-centered approaches, especially the lean startup literature, which has productively emphasized rapid learning, iterative testing, and disciplined feedback loops (Shepherd & Gruber, 2021). Yet a growing body of research on experimentation, pivoting, scaling, and early organizational design suggests that new venture development is not simply cumulative. Ventures do not advance because they do more; they advance because the activities they undertake become mutually enabling across technical, commercial, and institutional domains (Bohan et al., 2024; Burnell et al., 2023; Van Lancker et al., 2023).

This issue is especially acute in institutionally complex environments. In such contexts, a venture cannot rely on product functionality alone, nor can early customer enthusiasm substitute for regulatory or ecosystem acceptance. Commercialization depends on whether the venture can establish a credible pathway through multiple interdependent validation demands. African early-stage technology ventures provide a particularly revealing setting for examining these dynamics because they often operate amid fragmented markets, uneven regulatory infrastructures, heterogeneous customer segments, and institutional interfaces that are still being stabilized (Atiase et al., 2020; Züfle & von Carlowitz, 2026; Abdulai et al., 2026). These conditions do not merely add difficulty; they make alignment visible as a core developmental challenge rather than a background assumption.

1.2. Problem Statement

A persistent empirical anomaly remains under-theorized in entrepreneurship research: ventures frequently exhibit substantial activity without translating that activity into meaningful outcomes. They build products, run pilots, secure meetings, complete incubator milestones, and sometimes even attract positive stakeholder attention, yet they do not commercialize or scale. Existing explanations typically locate this failure in deficits such as limited resources, weak capabilities, or constraining institutional environments (Lee & Lévesque, 2023; Mair & Martí, 2009; Pardo-del-Val et al., 2025). These accounts are valuable, but they often treat constraints as static conditions rather than as elements within an unfolding process of coordination. As a result, the literature still lacks a sufficiently precise account of how venture activity becomes commercially consequential, and why apparently credible progress so often proves non-convertible.

1.3. Research Objectives

This article pursues three objectives. First, it seeks to explain why observable venture activity is often decoupled from commercialization outcomes. Second, it develops a process model that specifies how product, market, and institutional validation must align over time for activity to become commercially effective. Third, it introduces a theoretical lens, Institutionally Mediated Market Formation (IMMF), through which commercialization can be understood as a multi-domain and temporally sequenced process of legitimacy construction.

1.4. Research Questions

The analysis is guided by the following research questions: (1) Why does substantial venture activity fail to translate into commercialization outcomes in institutionally complex environments? (2) How do product, market, and institutional validation processes interact over time to generate commercialization, artificial progression, or stagnation? and (3) What mechanism links the temporal sequencing of validation efforts to the emergence of market formation?

1.5. Contributions and Paper Structure

The article makes four contributions. It first reframes venture progress as an alignment-dependent accomplishment rather than an activity count. It then theorizes artificial progression as a condition in which visible advancement within one or more domains does not yield commercialization because required validation remains misaligned. Third, it develops validation alignment as the central mechanism that links venture action to outcomes. Fourth, it advances IMMF as a process-based explanation of how ventures form markets under institutional complexity by sequentially constructing legitimacy across interdependent domains. The remainder of the article reviews the literature, develops the conceptual framework and analytical propositions, explains the longitudinal research design, presents the findings, and discusses the theoretical and practical implications.

2. Literature Review

2.1. From Activity Proxies to Process Explanations

Early-stage venture research has often relied on observable action as a proxy for progress. This tendency is understandable because nascent firms rarely have stable performance indicators; researchers therefore infer progress from experimentation intensity, prototype maturity, customer discovery efforts, or early traction. However, this inferential shortcut becomes problematic when ventures appear active without becoming viable. Recent work on experimentation and pivoting shows that learning-oriented action can improve venture adaptation, but only when learning is translated into consequential strategic reconfiguration rather than accumulated as disconnected tests (Burnell et al., 2023). Similarly, current work on scaling emphasizes that growth is not the straightforward extension of an already validated model, but a qualitatively different organizational challenge involving complementarities, bottlenecks, and sequencing problems (Bohan et al., 2024; Tippmann et al., 2023).

A process view therefore shifts the analytical question from whether ventures act to how their actions become developmentally coherent. This shift matters because early-stage ventures typically move through uncertain and contested environments in which technical readiness, customer uptake, and institutional acceptance develop at different speeds. Under these conditions, activity can be abundant while progress remains fragile. The theoretical challenge is not merely to show that venture development is non-linear; it is to explain the mechanism through which non-linear and interdependent activity becomes outcome-producing.

2.2. Signaling, Legitimacy, and the Limits of Visible Advancement

Signaling research has significantly improved understanding of how ventures reduce information asymmetries for investors, customers, and other stakeholders. Signals such as legal form, endorsements, pilots, and partnerships can increase perceived legitimacy and shape resource provision decisions (Bracht et al., 2024). Yet signaling theory primarily addresses perception. It explains how external audiences interpret observable cues, but it does not by itself establish whether the underlying venture is substantively prepared for commercialization. A venture may be highly legible to external audiences while still lacking the coordinated validation necessary for deployment.

The legitimacy literature is more attentive to this substantive dimension. Foundational studies show that new ventures must establish appropriateness, credibility, and taken-for-grantedness among multiple audiences (Aldrich & Fiol, 1994; Suchman, 1995; Zimmerman & Zeitz, 2002). More recent work underscores that legitimacy is temporally layered, audience-specific, and often internally contradictory (Fisher, 2020; Tracey et al., 2018). These insights are crucial because they suggest that legitimacy cannot be treated as a singular threshold. However, the literature still provides limited specification of how different forms of validation interact operationally across product, market, and institutional domains. This leaves unresolved why legitimate-looking ventures may still fail to commercialize.

2.3. Scaling, Support Organizations, and Coordination Problems

Research on scaling increasingly rejects the notion that early growth follows automatically from entrepreneurial energy or product-market fit. Scaling requires organizational redesign, role evolution, resource orchestration, and temporal coordination across multiple activities (Bohan et al., 2024; Tippmann et al., 2023; Van Lancker et al., 2023). This literature is useful because it foregrounds interdependence, but its center of gravity often remains inside the firm. By contrast, early-stage ventures in institutionally complex settings must manage not only internal coordination, but also the alignment of external validation systems that are partly outside their control.

Studies of entrepreneurial support organizations add a further layer to this issue. Support infrastructures can provide mentoring, knowledge, legitimacy spillovers, and ecosystem access, but they can also intensify reliance on visible milestone logic (Bergman & McMullen, 2022; Serpente et al., 2025). Recent African evidence likewise shows that milestone attainment and externally legible signal portfolios within university-affiliated accelerators can function as venture-quality signals under capital scarcity, thereby reinforcing the centrality of visible progress markers in support settings (Mukasa & Sangwa, 2025). However, when ventures are evaluated predominantly through visible and program-legible progress markers, such as staged milestones, concentrated mentor interactions, and demo-day-facing performance displays, support environments may inadvertently privilege visible motion over cross-domain validation coherence (Cohen et al., 2019; Hochberg, 2016). This does not imply that support organizations are counterproductive. Rather, it suggests that they can unintentionally amplify a weak theory of progress: one that equates activity with advancement without demonstrating cross-domain convertibility.

2.4. Institutional Complexity and Market Formation

Institutional scholarship has shown that ventures entering novel or weakly structured fields face profound legitimacy and coordination challenges. Institutional voids, regulatory ambiguity, and fragmented stakeholder expectations shape what entrepreneurs can credibly offer, to whom, and under what conditions (Mair & Martí, 2009). At the same time, ecosystem research emphasizes that value creation is structurally interdependent and depends on alignment across multiple actors and activities rather than on isolated firm effort (Adner, 2017; Spigel & Harrison, 2018). These insights are especially relevant for early-stage ventures attempting to form markets while simultaneously earning acceptance from customers, regulators, partners, and support organizations.

What remains underdeveloped is the micro-process through which ventures navigate these interdependencies. Public policy work now recognizes that the transition from startup to scale-up depends on institutional arrangements and policy support (Pardo-del-Val et al., 2025), but such work rarely theorizes how ventures move through validation bottlenecks in real time. The missing step is a venture-level account of how product feasibility, market demand, and institutional acceptance become synchronized or remain fragmented.

2.5. Research Gap and Theoretical Positioning

Three gaps follow from this review. First, the literature still overuses activity-based proxies for progress even while acknowledging that venture development is uncertain and non-linear. Second, work on signaling and legitimacy clarifies how ventures become visible and credible, but less clearly how these gains become commercially operative across multiple domains. Third, research on ecosystems, institutional complexity, and support systems highlights environmental conditions yet offers limited micro-level specification of the sequencing mechanism through which ventures convert activity into outcomes. This article addresses these gaps by theorizing validation alignment as the mechanism that converts venture activity into commercialization, by naming artificial progression as a distinct outcome of cross-domain misalignment, and by situating these dynamics within a broader theory of Institutionally Mediated Market Formation.

3. Conceptual Framework and Analytical Propositions

3.1. Venture Progress as a Conditional Accomplishment

We define venture progress not as the cumulative sum of actions taken, but as the conditional conversion of action into commercialization-relevant advancement. This definition rejects a simple additive logic. A venture does not progress because it has completed many tasks, but because the tasks completed in one domain increase the effectiveness of action in others. Progress is therefore relational and conditional. It depends on whether what has been validated in one sphere can travel across the others as usable legitimacy.

3.2. Three Interdependent Validation Systems

The framework distinguishes among three analytically separable but empirically interdependent validation systems. Product validation refers to the extent to which the offering works reliably and can deliver the value it promises. Market validation refers to evidence that specific users or customers recognize that value and are willing to adopt, pay for, or repeatedly engage with the offering. Institutional validation refers to the legitimacy, approvals, compliance, and ecosystem acceptance required for the offering to operate credibly within its environment. These systems are not substitutes. A technically strong product cannot commercialize without demand, demand cannot reliably convert without a deployable product, and both can be blocked by institutional non-acceptance.

This approach builds on prior work showing that ventures require multiple forms of legitimacy and resource orchestration, but it sharpens the argument by specifying validation systems as operational domains that must become mutually reinforcing (Fisher, 2020; Oftedal et al., 2024; Zimmerman & Zeitz, 2002). In that sense, the venture challenge is not simply validation, but the alignment of validation.

3.3. Validation Alignment

Validation alignment is defined here as the coordinated and mutually reinforcing evolution of product, market, and institutional validation over time. Alignment exists when advancement in one domain increases the probability, speed, or credibility of advancement in the others. Product readiness may make pilots meaningful; pilot data may strengthen the case for regulatory engagement; institutional acceptance may unlock deployment channels that reveal deeper market demand. Misalignment exists when progress in one domain does not travel. In such cases, the venture remains locally active but systemically blocked.

Alignment should not be understood as perfect simultaneity. It is a temporal accomplishment, and therefore sequencing matters (Langley et al., 2013; Adner, 2017). The central issue is whether the order and interaction of validation efforts create cumulative legitimacy rather than isolated advancement. This makes coordination capability, rather than raw effort, the critical determinant of progress.

3.4. Artificial Progression

Artificial progression refers to a structural condition in which ventures exhibit sustained and credible advancement signals in one or more domains without achieving commercialization because required validation remains cross-domain misaligned. The term artificial does not imply deception. Ventures may be genuinely developing a strong product, obtaining users, or satisfying incubator milestones. The problem is that these gains do not accumulate into a commercially operative configuration. Artificial progression therefore differs from symbolic action or impression management. It identifies a deeper disconnect between visible movement and outcome-producing readiness.

This construct is useful because it explains why ventures can remain active, funded, or publicly visible for extended periods while failing to cross into commercialization. It also helps reinterpret underperformance in institutionally complex settings. Some ventures do not stall because they do nothing; they stall because what they do does not align.

3.5. Institutionally Mediated Market Formation

Institutionally Mediated Market Formation (IMMF) is proposed as the overarching theoretical lens. IMMF conceptualizes commercialization as a process in which ventures form markets by sequentially constructing technical feasibility, market relevance, and institutional legitimacy in ways that become mutually reinforcing. Market formation, in this view, is not a direct consequence of innovation alone. It is mediated by institutional interfaces and by the venture’s ability to align validation across domains that are partly governed by different audiences, time horizons, and evaluative criteria. IMMF therefore integrates entrepreneurship, legitimacy, and ecosystem thinking into a process perspective on commercialization (Adner, 2017; Fisher, 2020; Navis & Glynn, 2010; Spigel & Harrison, 2018).

Figure 1 summarizes the article’s core argument. Venture activities feed into three validation systems. These systems only become developmentally effective when they are coordinated through validation alignment. When alignment occurs, ventures move toward commercialization. When it does not, visible advancement can devolve into artificial progression or stagnation.

3.6. Analytical Propositions

Because this study is process-oriented and draws on longitudinal multi-venture evidence rather than large-sample hypothesis testing, the theoretical expectations are framed as analytical propositions. These propositions specify the expected relationships that organize the empirical analysis and clarify the mechanism through which venture activity translates into divergent outcomes.

Table 1. Core analytical propositions.

Propositions	Statement
1	Higher levels of validation alignment are associated with movement toward commercialization.
2	Lower levels of validation alignment increase the likelihood of artificial progression, where visible advancement does not convert into commercialization.
3	Ventures characterized by artificial progression are more likely to experience delayed progression or stagnation than successful commercialization.
4	Sequencing capability, understood as the ability to coordinate the order and interaction of validation processes, is positively associated with validation alignment.

Note. These propositions organize the process analysis and are interpreted analytically rather than statistically.

Table 1. Core analytical propositions.

Propositions	Statement
1	Higher levels of validation alignment are associated with movement toward commercialization.
2	Lower levels of validation alignment increase the likelihood of artificial progression, where visible advancement does not convert into commercialization.
3	Ventures characterized by artificial progression are more likely to experience delayed progression or stagnation than successful commercialization.
4	Sequencing capability, understood as the ability to coordinate the order and interaction of validation processes, is positively associated with validation alignment.

Note. These propositions organize the process analysis and are interpreted analytically rather than statistically.

4. Method

4.1. Research Design and Logic of Inquiry

The study adopts a longitudinal, multi-venture design to explain how early-stage ventures progress toward, or fail to reach, commercialization under conditions of institutional complexity. The analytic logic is abductive and process-oriented. Rather than beginning with a closed causal model, the study moves iteratively between theory and temporally ordered venture evidence to identify a mechanism capable of explaining recurring outcome divergence. This design is appropriate because the phenomenon under investigation is not a static relationship among variables, but an unfolding developmental process in which the meaning of action depends on timing, sequencing, and interaction (Langley et al., 2013).

The core advantage of this design is that it avoids reducing venture development to retrospective perception or cross-sectional snapshots. Instead, it examines how actions in one quarter condition possibilities in the next, allowing commercialization and non-commercialization to be analyzed as trajectories rather than endpoints.

4.2. Empirical Context and Sample

The empirical setting comprises 15 early-stage technology ventures operating across multiple African markets over a 12-month period. The ventures are situated in contexts characterized by regulatory heterogeneity, fragmented demand structures, and uneven institutional support. These conditions render validation interdependencies especially visible (Atiase et al., 2020; Züfle & von Carlowitz, 2026; Abdulai et al., 2026). The sampled ventures span sectors such as digital platforms, fintech, and technology-enabled services, all of which typically require simultaneous attention to technical functionality, customer adoption, and institutional acceptance.

The sample is modest in size, but it is theoretically appropriate for mechanism identification. The aim is not statistical representativeness. Rather, the study seeks analytical generalization by examining whether a recurring pattern explains why ventures with apparently similar levels of activity diverge in outcomes. Because the ventures occupy broadly comparable early commercialization stages, the design reduces life-cycle heterogeneity and improves the interpretability of progression differences.

4.3. Data Sources and Temporal Structure

The analysis draws on four complementary sources of longitudinal venture evidence: milestone plans, quarterly progress reports, budget allocation records, and advisory or engagement records. Milestone plans indicate intended priorities and reveal how ventures sequence their efforts prospectively. Quarterly reports document implementation, traction, and emerging constraints. Budget allocation records provide behavioral evidence of what ventures actually prioritized. Advisory and engagement records capture structured interactions with mentors, support organizations, and other ecosystem actors. Taken together, these materials enable triangulation across intention, execution, resource commitment, and external interface management.

The temporal structure of the dataset is important. Rather than treating validation as a one-time event, the material allows the researcher to track how domains evolve quarter by quarter. This makes it possible to distinguish transient activity from cumulative progression.

4.4. Construct Operationalization

The coding framework translated the conceptual model into observable indicators at the venture-quarter level. Table 2 summarizes the central constructs and their empirical indicators. Coding focused on whether each venture-quarter showed advancement in product, market, and institutional validation, and whether such advancement appeared mutually reinforcing or fragmented.

4.5. Analytical Procedure

The analysis proceeded in three stages. First, all venture activities were coded into the three validation domains. Second, quarter-by-quarter sequences were examined to identify whether domain-specific progress was aligned, partially aligned, or misaligned. Third, these patterns were linked to observed outcome regimes: commercialization, artificial progression, or stagnation. Throughout the process, the analysis moved iteratively between emerging patterns and the evolving conceptual framework. Artificial progression emerged not as an a priori label imposed on the data, but as the most parsimonious explanation for ventures that remained visibly active yet non-commercializable.

4.6. Rigor, Validity, and Analytical Boundaries

Several steps strengthen the credibility of the analysis (Langley et al., 2013; Ridder, 2017). First, triangulation across plans, reports, budgets, and engagement records reduces reliance on any single indicator of progress. Second, the longitudinal design allows interpretations to be anchored in temporal sequences rather than retrospective rationalizations. Third, the coding scheme focused on observable behavior and documented interactions, which reduces the risk of inferring validation from aspirational language alone. At the same time, the design has clear analytical boundaries. It does not establish statistical causality, nor does it capture every informal interaction that may influence venture development. Its primary contribution is explanatory depth: specifying a mechanism that renders otherwise puzzling activity-outcome divergence intelligible.

5. Findings

5.1. Three Outcome Regimes

The longitudinal evidence reveals three recurrent venture outcome regimes: commercialization, artificial progression, and stagnation. Figure 2 maps ventures by their relative levels of product and market validation and shows a distinctly structured pattern. Ventures in the high product/high market zone are clustered in the commercialization regime. Ventures with moderate or uneven validation clusters in the artificial progression regime. Ventures with weak validation across domains cluster in stagnation. The pattern is theoretically consequential because it suggests that venture outcomes are not ordered primarily by activity intensity, but by the extent to which different forms of validation become mutually reinforcing.

This finding supports Proposition 1. Commercialization is most visible where product and market validation jointly accumulate rather than advance in isolation. It also provides initial support for Proposition 2, because the middle cluster is not inactive. On the contrary, it is characterized by visible motion. What differentiates it from commercialization is not lack of effort, but lack of convertibility.

5.2. Artificial Progression as Cross-Domain Misalignment.

The ventures in the artificial progression regime are analytically decisive. They demonstrate that visible advancement is not sufficient for commercialization. Some showed strong product development without commensurate market uptake. Others generated market interest without sufficient technical reliability or institutional clearance. Still others accumulated partnership activity and incubator milestones while lacking a pathway that connected those achievements to deployable market formation. In each case, the issue was not that ventures had no progress at all. The issue was that progress in one domain did not authorize or accelerate progress in the others.

This is why the concept of artificial progression is useful. It names a condition that standard metrics often miss. A venture may look dynamic in dashboards, reports, or demo environments and still remain commercially blocked. Proposition 2 is therefore not a claim that misaligned ventures are inactive. It is a claim that their activity remains structurally local rather than systemically cumulative.

5.3. Temporal Coordination and Sequencing Capability

The static clustering in Figure 2 identifies the outcome regimes, but it does not by itself explain how those regimes are produced. Figure 3 addresses that question by tracing the temporal dynamics of validation processes. Three pathways become visible. The first is aligned progression. Here, product, market, and institutional validation are sequenced so that gains in one domain enable gains in others. The second is artificial progression. In this pathway, one or two domains advance while another lags or deteriorates, preventing cumulative legitimacy. The third is stagnation, where none of the domains achieves sustained upward movement.

The temporal pattern supports Proposition 4. Sequencing capability emerges as a critical differentiator. Ventures that coordinated the order of product releases, market tests, and institutional engagements were more likely to build cumulative momentum. Ventures that pursued the same domains in fragmented, reactive, or parallel ways were more likely to produce short-lived or non-transferable gains. Sequencing capability therefore appears less as an abstract managerial trait than as an observable pattern of temporal coordination.

Across the findings, a single mechanism becomes visible: sequential legitimacy construction. Product validation generates credible technical claims; market validation converts those claims into adoption signals; institutional validation stabilizes those signals within broader systems of permission, interoperability, and trust. Commercialization occurs when this sequence is cumulative. Artificial progression occurs when one of the links fails to travel. Stagnation occurs when legitimacy is too weakly constructed to activate the sequence at all. Proposition 3 is supported in this sense: ventures trapped in artificial progression are materially less likely to commercialize and more likely to cycle through delay, rework, and stalled movement.

These findings motivate the move from venture progression to Institutionally Mediated Market Formation. What ventures are building is not merely a product or a customer base. They are building a viable market relation under conditions where institutional mediation remains consequential. IMMF captures this reality by showing that commercialization requires not only a value proposition, but an aligned pathway through multiple domains of validation.

6. Discussion

6.1. Theoretical Implications

The study contributes to entrepreneurship theory by showing that activity is an insufficient unit of explanation for venture progress. Much of the literature implicitly assumes that more experimentation, more traction, or more ecosystem engagement should move ventures forward (Bergman & McMullen, 2022; Bohan et al., 2024; Burnell et al., 2023; Shepherd & Gruber, 2021). The present analysis demonstrates a more conditional logic. Activity becomes progress only when validation is aligned across product, market, and institutional systems. This moves the conversation from activity counts to coordination quality.

A second contribution lies in the construct of artificial progression. Existing research on legitimacy and signaling explains why ventures work hard to appear credible and understandable to external audiences (Fisher, 2020; Suchman, 1995). However, it does not adequately capture cases in which ventures are genuinely advancing and yet remain non-commercializable. Artificial progression identifies this structural condition. It is therefore conceptually distinct from symbolic action, overclaiming, or failed execution. It describes a developmental mismatch rather than a communicative one.

Third, the article clarifies validation alignment as a mechanism. Prior work has richly described technical development, market experimentation, and institutional embeddedness, but often in separate literatures. By linking them through a process model, the study shows how these domains become mutually enabling or mutually blocking. This helps bridge entrepreneurship research with ecosystem and legitimacy scholarship. Adner’s (2017) notion of alignment in multilateral settings and Spigel and Harrison’s (2018) process account of entrepreneurial ecosystems become materially sharper when viewed through the validation sequences ventures must actually navigate.

Fourth, IMMF extends current work on market formation by relocating commercialization inside a process of institutionally mediated legitimacy construction. In many emerging and institutionally complex markets, what is being formed is not simply demand for a new solution. It is the broader set of permissions, expectations, interfaces, and credible routines that make repeated exchange possible (Adner, 2017; Fisher, 2020; Navis & Glynn, 2010; Spigel & Harrison, 2018). IMMF therefore reinterprets venture development as market formation under institutional mediation, rather than as firm growth alone.

6.2. Policy and Practice Implications

The findings have direct implications for venture support organizations, investors, and policy makers. First, they caution against overreliance on activity-based metrics such as milestone completion, prototype readiness, or engagement counts. These indicators are easy to observe but may conceal artificial progression. Evaluation systems should instead ask whether progress in one domain is making progress in the others more likely. Second, support programs should be designed around sequencing rather than generic simultaneity. Providing product mentorship, customer access, and regulatory advice in parallel is useful only if these interventions are synchronized around the venture’s actual validation pathway.

Third, investors should treat alignment as a more discriminating indicator of venture readiness than visibility. A venture with modest but coordinated progress may be more commercially viable than a venture with impressive isolated achievements. Fourth, policy interventions in emerging ecosystems should not be restricted to resource provision. They should also reduce institutional friction in the pathways through which ventures obtain approval, run pilots, integrate with public systems, or secure market-legible endorsements. In short, effective support should help ventures align validation systems, not merely accelerate activity within them.

6.3. Limitations and Future Research

The study has limitations. The sample is confined to a specific set of early-stage technology ventures observed within a bounded period and support context. Although this supports mechanism identification, it limits direct generalization across sectors and geographies. The data also capture structured venture records more readily than informal interactions, tacit negotiations, or hidden political dynamics that may matter for institutional validation. In addition, the study centers on three validation systems. Financial validation, team dynamics, and organizational design may also shape progression and deserve integration in future research.

These limitations nonetheless point toward a productive research agenda. Future studies could test the framework across sectors with different regulatory intensities, compare institutionally complex and institutionally mature markets, or operationalize validation alignment quantitatively at the venture-quarter level. Mixed-method and longitudinal econometric designs may also clarify whether particular sequencing patterns are more predictive of commercialization than others. A further avenue would examine whether support organizations can be redesigned to detect and interrupt artificial progression before it becomes path dependent.

7. Conclusion

This article set out to explain why substantial venture activity often fails to yield commercialization outcomes. The answer advanced here is straightforward but theoretically important: venture activity does not translate into outcomes unless validation is aligned across product, market, and institutional domains. From the longitudinal evidence, three regimes emerge: commercialization, artificial progression, and stagnation. These are not simply levels of success or failure. They are different process configurations produced by the temporal coordination, or miscoordination, of validation efforts.

By introducing validation alignment, artificial progression, and Institutionally Mediated Market Formation, the study offers a process-based explanation of venture progression under institutional complexity. Its central implication is that entrepreneurship theory should be less concerned with how much activity ventures generate, and more concerned with whether that activity becomes cross-domain legitimacy capable of supporting market formation. In institutionally complex environments, the decisive problem is not merely doing more. It is aligning what is done so that progress becomes cumulative, transferable, and commercially real.