The Managerial Skill That Turns Government Ties Into Factory Growth

For small manufacturers in Nairobi, who you know inside government agencies, industry associations, and the wider business community can matter as much as what you own. A new study from Kenya suggests, however, that knowing the right people is only half the equation. The other half is a managerial skill the researchers call social resource orchestration competence, and their data indicate it may be the single strongest driver of growth for manufacturing small and medium enterprises.

The research, published in Frontiers in Human Dynamics, surveyed 393 executives from Kenya Association of Manufacturers-registered SMEs across 14 manufacturing sub-sectors in Nairobi County. Respondents included business owners, heads of operations, and heads of finance. Using structural equation modelling in SmartPLS 4.0, preceded by confirmatory factor analysis to establish reliability and validity, the team led by Loise Wanjiru Kanotha Oburu of Strathmore Business School tested how three types of institutional social network resources translate into business growth, and whether orchestration competence changes that translation.

The three network types follow the classic pillars of institutional theory. Regulatory resource networks cover ties with government agencies, local authorities, banks, and industry associations that provide commercial support, credit access, and information. Normative resource networks involve shared values, community engagement, social responsibility, and mutual monitoring among organizations. Cultural-cognitive resource networks rest on shared mental models and relationships with local cultural institutions, religious and community leaders, and the customs of the host community.

In the direct path analysis, all three network types showed significant positive associations with SME growth. Regulatory networks had the strongest effect (β = 0.332, p < 0.05), followed by normative networks (β = 0.285, p < 0.05) and cultural-cognitive networks (β = 0.162, p < 0.05). Effect sizes were small by Cohen’s guidelines, with regulatory networks at f² = 0.082, normative at 0.051, and cultural-cognitive at 0.030, indicating each contributes uniquely but modestly to explaining growth variation.

Everything changed when the researchers introduced social resource orchestration competence as a moderator. Orchestration competence, defined as structuring a resource portfolio, bundling resources into capabilities, and leveraging those capabilities for competitive advantage, emerged as the dominant growth factor with a main effect of β = 0.543 (p < 0.05). In other words, the ability to acquire, accumulate, divest, stabilize, and configure social resources into distinct organizational capabilities explained growth far better than the institutional networks themselves.

The moderation results were strikingly asymmetric. Orchestration competence significantly amplified the growth value of regulatory networks (interaction β = 0.162, p < 0.05), suggesting firms with strong managerial orchestration extract far more from government ties, industry associations, and formal partnerships. It had no significant moderating effect on normative networks (β = 0.129, p > 0.05), implying shared community norms retain their positive impact regardless of a firm’s orchestration skill. Most unexpectedly, it significantly attenuated the contribution of cultural-cognitive networks (β = −0.429, p < 0.05), eroding their growth link.

The researchers interpret the negative interaction through the resource-based view: orchestration competence acts as a superordinate resource. Firms with high orchestration competence can sense, seize, integrate, and strategically prioritize high-value institutional networks, reducing reliance on cultural-cognitive ties. Once a firm has superior capabilities for deploying regulatory and formal resources, the informal cultural ties that substitute for weak capabilities become less relevant to growth.

To make these findings actionable, the study introduces the Social Exchange Orchestration Grid, a novel theoretical framework mapping the differential economic value of institutional network archetypes against orchestration competence. Quadrant A holds normative networks, valuable regardless of competence. Quadrant B holds regulatory networks, whose full potential is unlocked only by high orchestration competence. Quadrant C holds cultural-cognitive networks, whose limited value erodes further under high competence. Quadrant D shows orchestration competence itself as the ultimate determinant of economic value from social exchanges, independent of any network type.

Theoretically, the findings advance Social Exchange Theory by offering preliminary evidence that the economic value of institutional network exchanges varies with the firm’s orchestration competence. The study integrates SET with the resource-based view and institutional theory: institutional theory explains why SMEs form ties with regulatory, normative, and cultural-cognitive networks; the resource-based view identifies what constitutes valuable resources and the capabilities through which value is extracted; and SET explains the relational mechanisms of trust, loyalty, and reciprocation that facilitate access and mobilization of institutional resources.

For policy in sub-Saharan Africa, the implications are potentially significant. The authors emphasize that building orchestration capabilities may be a more critical investment than network acquisition per se. Training programs, incubators, and innovation hubs that teach managers to structure, bundle, and leverage social resources could yield greater growth returns than simply encouraging firms to join associations or cultivate government contacts. The authors caution that the focus on KAM-registered SMEs introduces external validity constraints, and future research should examine these relationships longitudinally and across other Kenyan counties and African manufacturing contexts to test the generalizability of the framework beyond Nairobi.

The distinction between the three institutional pillars traces back to foundational work in institutional theory, which holds that organizational behavior is shaped not only by formal rules but also by the norms people absorb and the taken-for-granted assumptions they carry into economic life. What the Kenyan study adds is a measurement challenge: most prior research in this tradition examined one pillar at a time, often in large listed firms, whereas small manufacturers in developing economies typically draw on all three simultaneously and with limited slack resources. By modeling the three network types side by side within a single structural equation model, the study makes it possible to see which pillar carries the most weight when the others are held constant, a comparison that earlier bivariate designs could not deliver.

The choice of respondents also matters for interpreting the results. Because the sample combined business owners with heads of operations and heads of finance, the measures of orchestration competence arguably capture how the top management team as a whole evaluates the firm’s ability to structure, bundle, and leverage social resources, rather than the perception of a single founder. In small firms, where ownership and management often overlap, this distinction can blur, but the multi-respondent design reduces the risk that the strong main effect of orchestration competence is simply an artifact of one optimistic individual answering every question. Purposive sampling from the Kenya Association of Manufacturers register further ensured that all firms operate in the formal manufacturing economy, which is precisely the setting where regulatory ties to licensing bodies, tax authorities, and standards agencies are most consequential.

Nairobi’s institutional density gives the findings a concrete backdrop. The county hosts the highest concentration of registered manufacturing SMEs in Kenya, alongside professional bodies, government institutions, and development organizations that firms can approach for collaboration, technical advice, and market intelligence. National policy reinforces this environment: Vision 2030, the government’s long-term development blueprint, explicitly positions manufacturing as a vehicle for industrial transformation, which raises the stakes for understanding why some SMEs convert institutional access into growth while others do not. The study’s answer, that conversion depends on managerial orchestration, reframes a familiar policy problem. Programs that merely connect firms to networks, such as matchmaking events or association membership subsidies, may underperform relative to interventions that build the internal capability to exploit those connections.

The asymmetric moderation pattern invites closer reading. A positive interaction with regulatory networks but a negative one with cultural-cognitive networks suggests that different network archetypes obey different economic logics. Regulatory ties resemble investments whose returns depend on complementary capabilities: a firm that can bundle a licensing relationship, a credit line, and an association membership into a coherent capability extracts compounding value. Cultural-cognitive ties, by contrast, appear to function as substitutes for capability rather than complements to it. Firms embedded in community expectations and informal reciprocity may rely on those ties precisely because they lack the orchestration machinery to mobilize formal resources; once that machinery exists, the informal ties lose their marginal contribution. This substitution logic is consistent with broader observations in the social capital literature that strong informal ties matter most under institutional voids, and their value declines as formal market and state institutions become accessible.

The null result for normative networks is equally informative. Shared values, community engagement, and mutual monitoring among organizations appear to confer growth benefits that do not depend on how skillfully a firm orchestrates them. One plausible reading is that normative resources operate through reputation and legitimacy, mechanisms that accrue to the firm automatically once it participates in the normative order, rather than requiring active managerial configuration. If so, normative networks occupy a middle position in the Social Exchange Orchestration Grid: neither fully competence-dependent like regulatory ties nor competence-eroded like cultural-cognitive ones.

Methodologically, the study follows the conventions of partial least squares structural equation modeling, assessing convergent and discriminant validity and collinearity against established thresholds before estimating paths. This matters because moderation analysis in PLS-SEM is sensitive to measurement quality; poorly discriminated constructs can inflate or deflate interaction terms. The cross-sectional design nonetheless limits causal claims. Growth, orchestration competence, and network embeddedness plausibly reinforce one another over time, with faster-growing firms developing stronger orchestration capabilities and richer institutional ties in a virtuous cycle. Longitudinal designs, which the authors themselves call for, would be needed to disentangle this reciprocity from the directional effects reported here.

For practitioners, the practical translation is a portfolio question. Managers of manufacturing SMEs can ask where their current institutional relationships sit on the grid: are they investing heavily in cultural-cognitive ties whose growth value may already be fading, or in regulatory ties whose returns they have not yet unlocked because internal orchestration is weak? The framework implies that an audit of orchestration competence should precede any decision about network investment, since the same relationship yields different economic value depending on the firm’s capability profile. For business support organizations across sub-Saharan Africa, the results suggest that curricula covering resource structuring, bundling, and leveraging, embedded in incubators and industry association training, could complement, and perhaps outperform, the conventional emphasis on expanding firms’ contact lists. Whether the grid holds for firms outside the formal KAM register, in other counties, and in neighboring economies remains an open empirical question that the authors flag for future work.

Subject of Research: Social network resources and orchestration competence in Kenyan manufacturing SME growth

Article Title: Institutional-based social network resources, social resource orchestration competence, and business growth of manufacturing small and medium enterprises: evidence from Kenya

Article References: Wanjiru Kanotha Oburu, L., Onyango, J. O., & Ndirangu, A. (2026). Institutional-based social network resources, social resource orchestration competence, and business growth of manufacturing small and medium enterprises: evidence from Kenya. Frontiers in Human Dynamics, 8, Article 1861807. https://doi.org/10.3389/fhumd.2026.1861807

Image Credits: AI Generated

DOI: 10.3389/fhumd.2026.1861807

Keywords: Kenya, manufacturing, SMEs, social networks, resource orchestration, business growth, Nairobi, structural equation modelling, Institutional-based, social, network, resources