Innovation and Firm Growth: Evidence from an Emerging Economy

Abstract

Innovation is widely recognised as a key driver of firm performance, yet empirical evidence from emerging economies remains limited. This study examines how different forms of innovation affect sales and employment growth among Vietnamese firms using firm-level data from the 2023 World Bank Enterprise Survey. The analysis considers product and process innovation, R&D expenditure, and R&D participation, while controlling for firm characteristics and institutional constraints. Using an instrumental variable (IV) approach with two-stage least squares (2SLS), we find that innovation is significantly associated with improvements in firm performance, with product and process innovations associated with substantial gains in sales growth. In contrast, the impact on employment growth is positive but more moderate, indicating that revenue expansion does not fully translate into job creation. R&D expenditure shows only incremental effects, suggesting limited short-term returns. Export participation is associated with stronger sales growth, whereas legal and regulatory obstacles are associated with lower employment expansion. Overall, the findings highlight that innovation is an important but context-dependent driver of firm growth in Vietnam, with more pronounced effects on revenue than on employment.

1. Introduction

Innovation plays an important role in shaping firm performance, but its effects vary substantially across business environments. In dynamic industries characterised by rapid technological and market changes, firms must continuously innovate to adapt and remain competitive, while those that fail to do so risk declining performance or market exit. Innovation in such contexts enables firms to sustain competitive advantage and supports growth and performance [1,2,3]. By contrast, in more stable environments—where producers, customers, and suppliers exhibit strong preferences for established technologies, innovation may generate limited or even negative performance effects. When markets are resistant to change, innovative activities may not be readily adopted, reducing their commercial value and potentially placing innovative firms at a competitive disadvantage relative to firms that follow existing norms [4,5]. These contrasting findings suggest that the performance effects of innovation are highly context dependent, shaped not only by industry dynamism but also by country-specific institutional and market conditions that influence firms’ ability to realise performance gains.

Vietnam provides a particularly informative setting for examining the relationship between innovation and firm performance. Since the introduction of the “Doi moi” reforms in 1986, the country has undergone rapid economic transformation alongside a growing policy emphasis on science, technology, and innovation. Building on earlier frameworks, Vietnam’s current Science, Technology, and Innovation Development Strategy prioritises research capacity, digital infrastructure, human capital development, and the integration of innovation into production systems in response to Industry 4.0 [6]. While these initiatives signal a strong commitment to innovation-driven growth, innovation engagement remains highly uneven across firms—particularly among small and medium-sized enterprises—which continue to face financing constraints, limited technological capabilities, skills shortages, and regulatory frictions. This combination of strong policy commitment and persistent structural constraints makes Vietnam a valuable case for understanding how innovation translates into firm-level performance. Moreover, the insights generated from this context are relevant to other emerging and transition economies with similar development trajectories, institutional environments, and firm structures, where innovation is increasingly promoted as a growth strategy but remains unevenly realised in practice.

Prior research on Vietnam, while informative, has several limitations: many studies rely on small or sector-specific samples [7,8,9], employ limited measures of innovation [10], or focus narrowly on profitability rather than broader performance outcomes.

This study seeks to address these gaps by providing new empirical evidence on the relationship between innovation and firm performance in Vietnam using the most recent 2023 World Bank Enterprise Survey (WBES). This article investigates how various forms of innovation, including product innovation, process innovation, R&D expenditure, R&D participation, influence firm growth in sales and employment. The study also incorporates a rich set of control variables related to firm characteristics and external constraints (e.g., legal, regulatory, financial, and labour-related obstacles). This comprehensive approach makes it possible to capture both internal and external determinants of innovative performance, offering a more nuanced understanding of the innovation–performance nexus in Vietnam.

This study makes two main contributions. First, it provides updated and context-specific evidence on the relationship between innovation and firm performance in Vietnam using the most recent 2023 World Bank Enterprise Survey data, addressing the limited availability of recent firm-level evidence in this context. Second, it compares multiple forms of innovation—including product and process innovation as well as R&D expenditure and participation—and distinguishes their effects across two key performance dimensions: sales growth and employment growth. This allows for a more comprehensive understanding of how different types of innovation contribute to firm growth in an emerging economy.

We find that innovation is strongly associated with firm growth in Vietnam, though its effects vary across outcomes. Product and process innovations are associated with higher sales growth of about 50 and 57 per cent, respectively. While investments in R&D further support revenue expansion, the employment effects are more moderate: product and process innovations raise employment growth by approximately 36 and 41per cent. We also find that legal and regulatory obstacles limit firms’ ability to convert innovation into job creation. Export participation strengthens the sales benefits of innovation, whereas small firms experience weaker growth. Overall, the findings highlight the context-dependent nature of innovation-driven growth in emerging economies, where revenue gains do not necessarily translate into proportional employment expansion.

The remainder of the article is organised as follows. Section 2 reviews the literature on innovation and firm performance. Section 3 describes the data source, variable construction, and empirical methodology. Section 4 presents empirical findings and robustness checks. Section 5 concludes with a summary of key insights, policy recommendations, and directions for future research.

2. Innovation and Firm Growth: A Review of Literature

Innovation is widely regarded as a key mechanism through which firms enhance competitiveness, respond to market changes, and achieve growth [11,12]. Growth-oriented perspectives emphasise that innovation enables firms to increase demand for their products, improve production efficiency, and strengthen their market position. Innovative firms tend to grow faster than non-innovative firms, especially in terms of sales [13,14]. Innovation is not limited to technological change in products and processes but also encompasses marketing and organisational dimensions. Reference [15] identifies four main types of innovation: product, process, marketing, and organisational innovation. Product innovation refers to the introduction of new or significantly improved goods or services, while process innovation involves new or improved production or delivery methods aimed at enhancing efficiency, quality, or cost performance. Marketing innovation concerns the adoption of new marketing methods related to product design, promotion, placement, or pricing, with the aim of better meeting customer needs or accessing new markets. Organisational innovation involves new organisational practices or structures that improve coordination, knowledge sharing, and overall firm performance. Different types of innovation affect firm growth through distinct channels, highlighting the importance of disaggregating innovation when analysing its performance implications.

2.1. Product Innovation and Firm Performance

Product innovation—defined as the introduction of new or significantly improved goods or services—is the type of innovation most consistently associated with firm growth. From the Resource-Based View perspective, product innovation reflects the effective deployment of firm-specific knowledge and technological resources to create value that competitors cannot easily replicate [16,17]. Also, the Dynamic Capabilities theory further suggests that firms capable of sensing market opportunities and reconfiguring resources to introduce new products are better positioned to sustain growth in competitive environments [18]. By differentiating products and better matching customer needs, product innovation directly expands demand and supports sales growth. Empirical evidence suggests that firms introducing product innovations experience higher revenue growth and stronger market positioning [13,19].

In emerging markets, product innovation is particularly important for firms seeking to compete with imported goods or move up value chains. Existing literature consistently shows that product innovation enables firms to access new customer segments and export markets, contributing to sustained sales expansion [20,21]. In contrast, its implications for employment growth are less clear. Employment effects may be limited if increases in demand are absorbed primarily through productivity gains rather than labour expansion. Reflecting this heterogeneity, empirical studies report mixed evidence on the employment effects of product innovation: while some find positive employment responses [22,23,24], others identify small or statistically insignificant effects [25,26,27]. These mixed findings emphasise the importance of examining sales and employment outcomes separately when evaluating the growth implications of product innovation.

2.2. Process Innovation and Firm Performance

Process innovation focuses on improvements in production methods, logistics, or delivery systems, with the primary objective of increasing efficiency and reducing costs. The literature generally agrees that process innovation enhances productivity and operational performance. More efficient production allows firms to lower prices, improve quality, or increase output capacity, which can indirectly support sales growth [7,28].

From a theoretical perspective, the relationship between process innovation and employment growth is ambiguous. The employment effects of innovation depend on the relative strength of displacement and compensation mechanisms. Process innovation is typically motivated by cost reduction and efficiency improvements and may therefore reduce labour demand through displacement effects. At the same time, productivity gains from new processes can lower production costs, stimulate output expansion, or enable the introduction of new or improved products and services, generating compensatory effects that may offset initial labour reductions [29,30]. Empirical studies reflect this ambiguity, with some finding positive employment effects [31,32] while others reporting neutral or negative outcomes, particularly in manufacturing sectors [33,34].

2.3. Investment in R&D and Firm Performance

Investment in research and development (R&D) represents a key input into the innovation process, enabling firms to build technological capabilities and generate new products and processes. From a resource-based and dynamic capabilities perspective, R&D investment enhances firms’ ability to accumulate knowledge and sustain competitive advantage [35]. Empirical evidence suggests that R&D is positively associated with firm growth, particularly over longer time horizons and in technology-intensive industries [36].

In this study, R&D is captured using two complementary measures: R&D participation and R&D expenditure. R&D participation is a binary variable indicating whether a firm engages in R&D activities, reflecting the extensive margin of innovation. In contrast, R&D expenditure measures the amount invested in R&D, capturing the intensity of innovation investment.

In emerging economies, innovation often takes the form of incremental adaptation, imitation, and development-oriented activities rather than formal research-intensive processes [11]. As a result, participation in R&D activities may capture firms’ engagement in applied innovation processes and their involvement in knowledge adaptation and commercialisation. In contrast, R&D expenditure reflects the intensity of formal investment in research and technological capability building. These two measures therefore represent distinct aspects of the innovation process and may affect firm performance through different channels. While R&D participation is more likely to generate immediate and applied performance effects, R&D expenditure is expected to contribute to longer-term capability development with less immediate impact on firm growth.

Distinguishing between these measures is important, as firms differ not only in whether they engage in R&D but also in the scale of their investment. This distinction allows us to examine whether firm performance is more closely associated with the decision to undertake R&D or with the intensity of R&D investment.

2.4. Research Hypotheses

Building on the theoretical and empirical literature, we develop testable hypotheses on the relationship between different types of innovation and firm performance, measured by sales growth and employment growth.

Product innovation is expected to enhance firm performance by enabling differentiation, expanding market demand, and improving competitive positioning. Firms introducing new or significantly improved products are therefore more likely to experience higher growth.

H1: 

Product innovation has a positive effect on firm performance.

Process innovation is expected to improve firm performance through efficiency gains, cost reduction, and increased production capacity. While process innovation may reduce labour demand through displacement effects, compensatory effects arising from output expansion may offset these reductions.

H2: 

Process innovation has a positive effect on firm performance.

R&D expenditure represents firms’ investment in knowledge creation and technological capability. Such investments are expected to support firm performance by strengthening innovation capacity, although the benefits may materialise over time.

H3: 

R&D expenditure has a positive effect on firm performance.

R&D participation reflects whether firms engage in R&D activities. Firms that participate in R&D are expected to achieve higher performance outcomes.

H4: 

R&D participation has a positive effect on firm performance.

3. Data and Research Methodology

3.1. Data

This study utilises the most recent firm-level data from the World Bank Enterprise Survey for Vietnam (Available at http://www.enterprisesurveys.org) (accessed on 10 February 2026) [37], a nationally representative survey designed to capture firm characteristics, innovation activities, performance outcomes, and business environment conditions in developing and emerging economies. The WBES is widely used in empirical research on innovation and firm performance due to its standardised methodology, cross-country comparability, and detailed coverage of both formal and informal innovation activities [38,39,40].

The WBES applies a stratified random sampling design to ensure representativeness of the formal private sector. In Vietnam, firms are stratified along three dimensions: industry, firm size, and geographic location. Industry stratification follows the International Standard Industrial Classification (ISIC), covering manufacturing and selected service sectors. Firm size is defined based on the number of permanent full-time employees and categorised as small (5–19 employees), medium (20–99 employees), and large (100 or more employees). Geographic stratification ensures coverage across major regions and economic centres within Vietnam.

Within each stratum, firms are selected randomly from an official business registry, which reduces sampling bias and allows inference at the national level. Sampling weights provided by the World Bank are available to adjust for unequal probabilities of selection.

The Vietnam WBES covers a broad cross-section of firms operating in manufacturing and services, including both domestic and foreign-invested enterprises. This diversity is particularly valuable for analysing innovation behaviour, as firms differ substantially in access to finance, technology, and international markets. Export-oriented and foreign-owned firms tend to exhibit higher innovation intensity, while domestic small and medium-sized enterprises (SMEs) face greater resource constraints.

The initial dataset consists of 1028 surveyed firms. Observations with missing information on key variables—namely innovation indicators, sales growth, employment growth, or core control variables—are excluded from the analysis. Additionally, to mitigate the influence of outliers, we follow [41] to winsorise the sales and employment growth variables at the 2.5th and 97.5th percentiles. After excluding observations with missing values for key variables and constructing growth measures, the final estimation sample comprises 667 firms. The exclusion of observations due to missing data may introduce potential selection bias if the dropped firms differ systematically from those retained in the sample. However, the final sample continues to exhibit substantial variation across firm size, sector, ownership structure, and innovation activities, suggesting that the main results are unlikely to be driven solely by sample selection.

Survey weights are available in the WBES dataset but are not applied in the baseline analysis, as the focus is on estimating relationships rather than population-level aggregates.

The WBES is particularly well suited to the Vietnamese context, where innovation often takes incremental and non-patent-based forms. Many firms engage in product or process innovation without conducting formal R&D, making traditional innovation indicators such as patents or R&D intensity inadequate. The survey’s direct questions on product innovation, process innovation, and innovation-related expenditures allow for a more accurate representation of firm-level innovation behaviour.

In addition, the WBES includes firm-reported measures of business environment constraints, such as access to finance and regulatory obstacles, which are central to Vietnam’s STI environment. Incorporating these variables enables the analysis to control for institutional factors that jointly influence innovation decisions and firm growth outcomes. Detailed definitions and descriptions of all variables used in the analysis are provided in

Table A1. Definition and Description of Variables.

Variable	Type	Description
Employment growth rate	Numeric (Percentage)	Employment growth (percentage) measures the average annual growth of full-time permanent employees over a two-year period, calculated based on the change in employment between the last fiscal year and two years earlier.
Sales growth rate	Numeric (Percentage)	Sales growth (percentage) measures the average annual growth of firm sales over a two-year period, calculated based on the change in total annual sales between the last fiscal year and three years earlier.
New product	Binary (1/0)	Firm introduced a new product in the last three years (1 = Yes).
New process	Binary (1/0)	Firm introduced a new process in the last three years (1 = Yes).
R&D participation	Binary (1/0)	Firm spent on R&D in the last fiscal year (1 = Yes).
R&D expenditure	Numeric (Million VND)	The amount firm spent on R&D last year (in million VND).
Financial obstacle	Numeric (Scale: 0–4)	Financial obstacle rating (0 = No obstacle, 4 = Very severe obstacle).
Legal obstacle	Numeric (Scale: 0–4)	Legal obstacle rating (0 = No obstacle, 4 = Very severe obstacle).
Age	Numeric (Year)	Firm age calculated as 2023 minus the establishment year.
Certified	Binary (1/0)	Firm has an internationally recognised quality certification (1 = Yes).
Government	Binary (1/0)	Firm is government-owned (1 = Yes).
Foreign	Binary (1/0)	Firm has foreign ownership (1 = Yes).
Exporter	Binary (1/0)	Firm exports goods or services (1 = Yes).
International	Binary (1/0)	Firm operates internationally beyond exports (1 = Yes).
Manufacturing	Binary (1/0)	Firm is in the manufacturing sector (1 = Yes).
Competition	Binary (1/0)	Firm has significant competition (1 = Yes if competitors > 50)
Small	Binary (1/0)	Firm is classified as a small enterprise (1 = Yes).
Medium	Binary (1/0)	Firm is classified as a medium-sized enterprise (1 = Yes).

in the Appendix A.

Table 1. Summary Statistics.

Variable	Mean	Median	SD	Min	Max
Employment growth	−0.804	0	14.604	−77.119	41.421
Sales growth	1.304	4.447	23.329	−96.838	42.551
Product innovation	0.081	0	0.273	0	1
Process innovation	0.063	0	0.243	0	1
R&D participation	0.03	0	0.171	0	1
R&D expenditure	15.868	0	149.625	0	2200
Financing obstacle	0.829	0	1.02	0	4
Legal obstacle	0.258	0	0.597	0	4
Age	14.709	15	7.49	3	63
Certified	0.28	0	0.45	0	1
Government	0.012	0	0.109	0	1
Foreign	0.12	0	0.325	0	1
Exporter	0.219	0	0.414	0	1
International	0.177	0	0.382	0	1
Manufacturing	0.121	0	0.327	0	1
Competition	0.736	1	0.441	0	1
Small	0.651	1	0.477	0	1
Medium	0.3	0	0.459	0	1

presents the summary statistics for the key variables used in the empirical analysis, including firm performance indicators, innovation activities, institutional constraints, and firm characteristics in the sample. The average employment growth rate is −0.804 per cent, with a median of zero, indicating that many firms experienced little or no employment expansion during the period considered. The large standard deviation (14.604) and the wide range from −77.119 to 41.421 suggest substantial heterogeneity in employment outcomes across firms. In contrast, sales growth is on average positive at 1.304 per cent, with a median of 4.447. However, the high standard deviation (23.329) and wide range from −96.838 to 42.551 indicate that firms differ significantly in their revenue performance.

The mean of 0.081 indicates that only 8.1 per cent of firms in the sample report introducing a new product, while 6.3 per cent implemented a new process innovation. In absolute terms, this corresponds to 54 firms introducing product innovations and 42 firms implementing process innovations. The relatively small number of innovative firms may limit statistical precision, particularly for estimates related to innovation variables. However, this distribution is consistent with existing evidence that innovation activity is concentrated among a subset of firms in emerging economies. Engagement in R&D-related activities is also low, with only 3 per cent of firms reported spending on R&D. Although the mean value of R&D expenditure is 15.868 million VND, the median is zero, indicating that most firms do not invest in formal R&D activities. This pattern suggests that innovation among Vietnamese firms is concentrated among a small subset of enterprises and is likely to be incremental rather than research intensive.

The average firm age is approximately 14.7 years, indicating a mix of relatively young and established firms. About 28 per cent of firms hold an internationally recognised certification, while foreign ownership accounts for 12 per cent of the sample. Around 21.9 per cent of firms have export activities, and 17.7 per cent operate internationally. Small firms dominate the sample (65.1 per cent), followed by medium-sized firms (30 per cent). Overall, these statistics highlight the diverse structure of the sample and provide important context for the subsequent empirical analysis.

Table A2. Pairwise Correlations Among Variables.

	Employment Growth	Sales Growth	Product Innovation	Process Innovation	R&D Participation	R&D Expenditure	Financing Obstacle	Legal Obstacle	Age
Employment growth	1
Sales growth	0.307	1
Product innovation	0.147	0.131	1
Process innovation	0.088	0.089	0.466	1
R&D participation	0.083	0.1	0.206	0.353	1
R&D expenditure	0.086	0.092	0.190	0.225	0.604	1
Financing obstacle	0.014	0.068	0.096	0.056	0.012	0.023	1
Legal obstacle	−0.064	0.034	0.043	0.004	−0.011	−0.018	0.259	1
Age	−0.044	−0.023	−0.001	0.085	0.069	0.000	−0.038	0.016	1
Certified	0.000	0.098	0.023	0.031	0.027	0.035	0.038	0.091	0.085
Government	−0.069	−0.018	−0.033	−0.029	−0.019	−0.012	−0.049	0.026	0.227
Foreign	−0.002	0.118	−0.042	−0.02	−0.065	−0.039	−0.035	0.087	−0.024
Exporter	−0.006	0.175	0.069	0.072	0.034	0.041	0.013	0.036	0.043
International	0.023	0.155	0.021	0.09	0.057	−0.002	0.034	0.052	0.116
Manufacturing	0.021	0.053	0.209	0.017	0.042	0.012	0.051	0.089	0.119
Competition	−0.019	−0.022	−0.047	0.029	0.006	−0.018	0.095	0.007	0.064
Small	−0.058	−0.203	−0.025	−0.017	−0.037	−0.015	−0.017	−0.116	−0.16
Medium	0.036	0.168	0.046	0.032	0.058	0.027	−0.007	0.128	0.15
	Certified	Government	Foreign	Exporter	International	Manufacturing	Competition	Small	Medium
Certified	1
Government	0.146	1
Foreign	0.458	0.044	1
Exporter	0.259	−0.025	0.418	1
International	0.375	0.021	0.288	0.334	1
Manufacturing	0.013	0.001	0.018	0.181	0.188	1
Competition	−0.179	−0.059	−0.041	−0.029	−0.097	−0.007	1
Small	−0.397	−0.064	−0.368	−0.433	−0.369	−0.142	0.068	1
Medium	0.284	0.078	0.232	0.31	0.323	0.147	−0.068	−0.893	1

in the Appendix A presents the pairwise correlation matrix for the main variables used in the analysis. Overall, the correlations between the explanatory variables are relatively low, suggesting that multicollinearity is unlikely to pose a serious concern for the regression analysis. Both employment growth and sales growth show positive but weak correlations with the innovation variables, including product innovation, process innovation, and R&D expenditure and R&D participation. R&D expenditure captures the amount invested in research and development activities, while R&D participation is a binary variable indicating whether the firm spent on R&D activities. The correlation coefficients are generally below 0.15, indicating that although innovative firms tend to experience better performance outcomes, the relationships are not strong.

Among the innovation variables, moderate correlations are observed between process innovation and innovation-related expenditures, particularly R&D expenditure and R&D participation, suggesting that firms engaging in process improvements are also more likely to invest in innovation-related activities. Institutional constraints, such as financing and legal obstacles, exhibit weak correlations with both innovation measures and firm growth indicators. This pattern indicates that while these factors may influence firm behaviour, their effects are unlikely to dominate the relationships. Overall, the low magnitude of the correlations supports the use of multivariate regression to further examine the relationship between innovation and firm performance. To further assess potential multicollinearity, we compute Variance Inflation Factors (VIF) for the combined OLS specification used as a robustness check. The VIF values are generally low, with most variables below 2. Although the small and medium firm indicators exhibit slightly higher VIF values, this reflects their construction as mutually exclusive size categories rather than problematic multicollinearity. All VIF values remain well below the conventional threshold of 10, indicating that multicollinearity is not a serious concern (see

Table A3. Variance Inflation Factors (VIF) for Multicollinearity Diagnostics.

Variable	VIF
Small	6.539
Medium	5.507
R&D participation	1.729
R&D expenditure	1.600
Certified	1.554
Foreign	1.553
Exporter	1.474
Process innovation	1.451
Product innovation	1.393
International	1.359
Manufacturing	1.153
Firm age	1.136
Financing obstacle	1.114
Legal obstacle	1.108
Government ownership	1.093
Competition	1.069

Note: VIF values are computed from the combined OLS specification including all innovation and control variables.

in the Appendix A).

3.2. Empirical Specification

To address potential endogeneity in the relationship between innovation and firm performance, this study employs an instrumental variable (IV) approach. Endogeneity may arise due to reverse causality, measurement error, or omitted variables. For instance, firms with higher growth may be more likely to invest in innovation, leading to reverse causality. In addition, unobserved managerial ability or firm-specific characteristics may influence both innovation decisions and performance outcomes, resulting in biased ordinary least squares (OLS) estimates.

To mitigate these concerns, we instrument innovation variables using access to external financing, measured by the availability of financial sources. This instrument is chosen based on its relevance to firms’ ability to undertake innovation activities, as access to external finance can ease liquidity constraints and enable investment in new products, processes, and development activities. Conditional on observable firm characteristics, access to financing is assumed not to affect firm performance directly, except through its influence on innovation. While financing conditions may shape firms’ overall investment capacity, their direct effect on short-term sales or employment growth is expected to be limited once firm characteristics and market conditions are controlled for. This assumption is consistent with prior studies emphasising the role of financial constraints in shaping innovation rather than directly determining firm performance, thereby supporting the validity of the exclusion restriction.

We apply two-stage least squares (2SLS) to estimate the impact of innovation on firm performance. In the first stage, the innovation variable is regressed on the instrumental variable and other control variables:

$${Innovation}_i={\alpha }_0+{\alpha }_1{IV}_i+{\alpha }_2{X}_i+ u_i$$

(1)

where ${Innovation}_i$ represents one of the innovation measures (product innovation, process innovation, R&D expenditure, or R&D participation). ${IV}_i$ denotes the instrument variable, $X_i$ is a vector of control variables including firm characteristics, ownership structure, and market conditions, $u_i$ is the error term capturing unobserved factors that influence firms’ innovation activities but are not included in the model.

In the second stage, the predicted values from the first stage are used to estimate their effect on firm performance:

$${Performance}_i={\mathrm{\beta }}_0+{\mathrm{\beta }}_1\widehat{{Innovation}_i}+\beta X_i+{\epsilon }_i$$

(2)

where ${Performance}_i$ denotes either sales growth or employment growth for firm i; ${\mathrm{I}\mathrm{n}\mathrm{n}\mathrm{o}\mathrm{v}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}_i$ is the predicted values of innovation; $X_i$ denotes the vector of control variables; and ${\epsilon }_i$ is the error term. The coefficient ${\mathrm{\beta }}_1$ captures the estimated effect of innovation on firm performance. The innovation variables are included separately in the baseline specifications to avoid multicollinearity and to isolate the effects of different types of innovation, which may operate through distinct channels. This approach is also necessary due to identification constraints in the IV framework, as a single instrument does not allow for the simultaneous instrumentation of multiple endogenous innovation variables.

To assess the strength and validity of the instrument, we report first-stage F-statistics for weak instrument diagnostics and the Wu–Hausman test for endogeneity. Following conventional thresholds, an F-statistic above 10 indicates that the instrument is sufficiently strong. These diagnostics are presented alongside the regression results to support the reliability of the IV estimates.

Consistent with prior research, firm performance is measured using sales growth and employment growth, which capture distinct but complementary dimensions of firm expansion. Sales growth reflects market performance and demand-side effects of innovation, while employment growth captures labour demand responses and broader developmental implications [42,43]. The literature emphasises that innovation may affect these outcomes through different channels and with varying intensity, underscoring the importance of analysing them separately [13,44].

Innovation activities are operationalised through four variables reflecting different aspects of innovation investment and engagement. Our approach is consistent with the view that innovation is a multidimensional process and that different types of innovation may generate heterogeneous performance effects. (1) Product innovation, measured by the introduction of new or significantly improved products, captures firms’ ability to differentiate offerings and respond to market demand. The literature finds that product innovation is positively associated with sales growth and, in some cases, employment growth, as firms expand output and market reach [19,28]. Product innovation is therefore expected to exert a positive effect on both performance measures. (2) Process innovation reflects improvements in production or delivery methods aimed at enhancing efficiency and reducing costs. Prior studies show that process innovation improves productivity and competitiveness, which can indirectly support firm growth [34]. However, its effect on employment is theoretically ambiguous, as efficiency gains may reduce labour intensity even as output expands. (3) The amount of R&D expenditure is included as an indicator of firms’ commitment to knowledge creation and capability development. From a resource-based and dynamic capabilities perspective, R&D investment strengthens absorptive capacity and supports long-term innovation outcomes. Empirical evidence suggests that R&D expenditure is positively related to firm performance, particularly sales growth, though effects may be delayed or context-dependent in emerging economies [35]. (4) R&D participation captures whether firms engage in innovation activities, measured as a binary variable indicating whether the firm spent on R&D in the last fiscal year. This measure complements R&D expenditure by capturing whether the firm undertakes R&D at all, rather than the amount spent. Firms participating in R&D activities achieve higher sales growth. R&D participation may facilitate the commercialisation of innovation and generate more immediate performance effects. Prior studies find that such investments are positively associated with firm performance, especially when firms face technological and institutional constraints [11].

We employed a set of control variables to account for firm characteristics and institutional conditions that influence performance outcomes, thereby reducing omitted variable bias. Financing obstacles are included to capture constraints on firms’ ability to invest in innovation and scale operations. The literature identifies access to finance as a critical determinant of firm growth in emerging economies, with financing constraints shown to negatively affect sales and employment growth [37]. Legal and regulatory obstacles reflect the institutional environment in which firms operate. Regulatory burdens and weak legal frameworks can increase compliance costs and hinder firm expansion, particularly in terms of employment. Prior studies suggest that such obstacles are associated with weaker growth outcomes [37]. Firm age is included to account for lifecycle effects.

Older firms may benefit from accumulated experience and networks but may also face organisational rigidity and slower growth. Empirical evidence indicates that the relationship between age and growth is context-dependent, with effects that may be negative or neutral in emerging economies [34]. Quality certification is used as a proxy for managerial capability and operational efficiency. Certified firms are often better positioned to compete in domestic and international markets [45]. Export status captures access to international markets, which can enhance learning, scale, and innovation incentives. Exporting firms tend to exhibit stronger performance outcomes due to exposure to global competition and demand [7]. International linkages, such as licencing agreements or participation in global networks, reflect knowledge spillovers and access to external technology. These linkages are expected to be positively associated with innovation outcomes and firm performance [46]. Foreign ownership is included to control for differences in capital access, technology, and managerial expertise. Foreign-owned firms often outperform domestic firms in sales, though employment effects may vary depending on production structure and technology intensity [36]. Industry controls, including a manufacturing sector indicator, are included to account for structural differences across sectors. No directional effect is imposed a priori, as industry effects primarily serve to control for heterogeneity. Firm size captures scale effects. Smaller firms may exhibit higher relative growth rates but also face greater resource constraints. The literature suggests that the relationship between size and growth is mixed and context-specific [40].

To further assess potential multicollinearity, we compute Variance Inflation Factors (VIF) for the combined OLS specification used as a robustness check. The VIF values are generally low, with most variables below 2. Although the small and medium firm indicators exhibit slightly higher VIF values, this reflects their construction as mutually exclusive size categories rather than problematic multicollinearity. All VIF values remain well below the conventional threshold of 10, indicating that multicollinearity is not a serious concern (see Table A3 in the Appendix A).

All statistical analyses are conducted using R version 4.5.3.

4. Results and Discussion

4.1. Main Findings

Table 2. Innovation and Sales Growth.

	Model 1	Model 2	Model 3	Model 4
Product innovation	50.889 *
	(27.546)
Process innovation		57.892 *
		(32.225)
R&D expenditure			0.434
			(0.629)
R&D participation				111.437
				(67.923)
Financing obstacle	0.233	0.648	−0.290	1.220
	(1.183)	(1.111)	(3.628)	(1.134)
Legal obstacle	−0.272	0.098	2.780	0.422
	(1.715)	(1.768)	(6.265)	(1.963)
Firm age	−0.137	−0.329 *	−0.140	−0.311 *
	(0.138)	(0.169)	(0.370)	(0.179)
Certified	−2.616	−1.929	−11.464	−3.239
	(2.861)	(2.835)	(17.033)	(3.370)
Government ownership	1.952	3.665	7.464	4.287
	(9.583)	(10.120)	(28.595)	(11.209)
Foreign ownership	4.056	3.517	17.431	7.574
	(4.062)	(4.064)	(25.807)	(5.790)
Exporter	2.091	1.562	−6.805	2.299
	(3.158)	(3.387)	(18.247)	(3.503)
International	6.237 **	1.841	9.780	2.778
	(3.058)	(3.433)	(10.757)	(3.527)
Manufacturing	−8.052	1.388	−0.370	−0.518
	(5.567)	(3.234)	(8.408)	(3.551)
Competition	1.178	−1.250	1.378	−0.877
	(2.423)	(2.387)	(6.593)	(2.577)
Small firm	−11.640 **	−12.511 **	−18.857	−11.401 *
	(5.570)	(5.919)	(21.063)	(6.221)
Medium firm	−4.565	−4.526	−13.300	−5.525
	(5.343)	(5.487)	(22.334)	(6.257)
Constant	6.795	11.593 *	12.077	10.160
	(6.009)	(6.787)	(17.971)	(7.115)
Observations	667	667	667	667
Weak IV F-stat	11.889	11.146	0.505	6.010
Wu-Hausman p-value	0.100	0.073	0.048	0.069

Note: The IV (2SLS) estimates, standard errors (in parentheses) are robust to heteroskedasticity. * Significant at 10%; ** significant at 5%.

reports the instrumental variable (IV) regression results for the determinants of sales growth, using external financing as an instrument for innovation. The results indicate that product and process innovation are key drivers of revenue expansion, while the effects of R&D-related variables are less precisely estimated.

Product innovation is positively associated with sales growth, with a coefficient of approximately 50.9 percentage points, significant at the 10% level. This suggests that firms introducing new or significantly improved products tend to exhibit substantially higher revenue growth than non-innovators. The magnitude of the effect highlights the importance of product differentiation as a source of competitive advantage, consistent with the Resource-Based View [17]. It also aligns with empirical evidence from developing economies showing that product innovation plays a central role in market expansion [19,28]. In the Vietnamese context, where many firms compete primarily on cost and incremental quality improvements, the large estimated effect underscores the importance of differentiation strategies for achieving superior performance.

Process innovation is also positively associated with sales growth, with an estimated effect of approximately 57.9 percentage points, significant at the 10% level. This finding supports the view that efficiency-enhancing innovations improve productivity and competitiveness, thereby contributing to revenue growth [7,34]. The relatively large magnitude suggests that, in emerging markets such as Vietnam, process improvements may be associated with output expansion and enable firms to compete more effectively in price-sensitive markets.

In contrast, R&D expenditure does not exhibit a statistically significant effect on sales growth, despite a positive coefficient. This indicates that increases in formal R&D expenditure do not translate immediately into higher revenues, which is consistent with the literature emphasising the uncertain and long-term nature of returns to R&D investment [35]. Similarly, the R&D participation variable shows a large positive coefficient but lacks statistical significance, reflecting substantial heterogeneity across firms. These results suggest that realised innovation outputs—such as new products and processes—have a more direct and measurable impact on firm performance than innovation inputs.

Among the control variables, most factors do not exhibit statistically significant effects on sales growth. Firm size shows a consistent pattern: small firms experience significantly lower sales growth relative to large firms, by approximately 11–12 percentage points, highlighting the importance of scale and resource availability in translating innovation into performance gains. This finding is consistent with prior research indicating that smaller firms face greater constraints in leveraging innovation effectively [47]. Other firm characteristics, including ownership structure and institutional obstacles, do not show robust direct effects on sales growth in the IV specification, suggesting that their influence may operate through indirect or context-dependent channels.

The findings also provide insight into the mechanisms through which innovation affects firm performance. Product innovation appears to operate primarily through demand expansion, enabling firms to attract new customers and increase market share. In contrast, process innovation is likely to enhance performance through efficiency improvements, reducing production costs and increasing output capacity. These channels suggest that innovation is associated with firm growth through both market-driven and productivity-enhancing mechanisms.

The diagnostic tests indicate that the instrument is sufficiently strong in the sales growth specifications, with first-stage F-statistics exceeding the conventional threshold of 10. Overall, the results provide evidence that product and process innovation play a central role in driving sales growth among Vietnamese firms, while the effects of R&D inputs are less immediate and more uncertain.

Table 3. Innovation and Employment Growth.

	Model 1	Model 2	Model 3	Model 4
Product innovation	35.836 **
	(17.796)
Process innovation		40.768 *
		(21.021)
R&D expenditure			0.306
			(0.440)
R&D participation				78.473 *
				(45.572)
Financing obstacle	−0.442	−0.149	−0.810	0.253
	(0.765)	(0.725)	(2.538)	(0.761)
Legal obstacle	−1.939 *	−1.679	0.209	−1.451
	(1.108)	(1.154)	(4.383)	(1.317)
Firm age	−0.068	−0.203 *	−0.070	−0.190
	(0.089)	(0.110)	(0.259)	(0.120)
Certified	−1.871	−1.387	−8.101	−2.309
	(1.849)	(1.849)	(11.916)	(2.261)
Government ownership	−5.057	−3.851	−1.176	−3.413
	(6.191)	(6.601)	(20.006)	(7.520)
Foreign ownership	1.525	1.146	10.944	4.003
	(2.624)	(2.651)	(18.056)	(3.885)
Exporter	−3.754 *	−4.127 *	−10.019	−3.608
	(2.040)	(2.209)	(12.766)	(2.350)
International	1.671	−1.424	4.167	−0.764
	(1.975)	(2.239)	(7.526)	(2.366)
Manufacturing	−4.824	1.824	0.586	0.482
	(3.597)	(2.110)	(5.883)	(2.382)
Competition	0.468	−1.241	0.609	−0.979
	(1.565)	(1.557)	(4.612)	(1.729)
Small firm	−8.377 **	−8.990 **	−13.459	−8.208 **
	(3.599)	(3.861)	(14.737)	(4.174)
Medium firm	−5.627	−5.600	−11.779	−6.303
	(3.452)	(3.579)	(15.625)	(4.198)
Constant	6.462 *	9.840 **	10.182	8.831 *
	(3.882)	(4.427)	(12.573)	(4.773)
Observations	667	667	667	667
Weak IV F-stat	11.889	11.146	0.505	6.010
Wu-Hausman p-value	0.078	0.051	0.029	0.040

Note: The IV (2SLS) estimates, standard errors (in parentheses) are robust to heteroskedasticity. * Significant at 10%; ** significant at 5%.

reports the instrumental variable (IV) regression results for the determinants of employment growth, using external financing as an instrument for innovation. The results indicate that innovation is positively associated with labour demand, although the magnitude and statistical significance of the effects vary across different innovation measures.

Product innovation is positively associated with increasing employment growth by approximately 35.8 percentage points. This suggests that firms introducing new or significantly improved products expand their workforce to support increased production, marketing, and distribution activities. The magnitude of the effect is economically substantial, indicating that product innovation plays a key role in driving job creation. This finding is consistent with studies highlighting the labour-augmenting effects of product innovation, particularly in developing economies where production remains relatively labour-intensive [7,19].

Process innovation is also positively associated with employment growth, with an estimated effect of approximately 40.8 percentage points, significant at the 10% level. This result is notable given the theoretical ambiguity surrounding the employment effects of process innovation. While process improvements may reduce labour demand through efficiency gains, the positive coefficient suggests that, in the Vietnamese context, output expansion effects dominate displacement effects. This finding aligns with empirical evidence from developing economies where process innovation often accompanies firm expansion rather than labour substitution [29,34].

In contrast, R&D expenditure does not exhibit a statistically significant effect on employment growth, despite a positive coefficient. This suggests that increases in R&D spending are not immediately associated with workforce expansion, which is consistent with the literature emphasising that R&D primarily contributes to long-term capability building rather than short-term job creation [35]. Similarly, R&D participation shows a positive and moderately significant effect, with a coefficient of approximately 78.5 percentage points. This indicates that firms engaging in R&D tend to experience higher employment growth, although the relatively large standard error suggests substantial heterogeneity across firms. Together, these findings imply that participation in innovation activities is more closely linked to employment expansion than the intensity of R&D investment alone.

Among the control variables, legal obstacles are negatively and statistically significant in some specifications, indicating that regulatory burdens may constrain firms’ ability to expand employment. Firm size also plays an important role: small firms exhibit significantly lower employment growth relative to large firms, with reductions of approximately 8–9 percentage points. This highlights the importance of scale, resource availability, and risk considerations in hiring decisions, and is consistent with prior research showing that smaller firms face greater constraints in expanding their workforce [47].

Exporter status is negatively associated with employment growth and is statistically significant in some specifications, suggesting that firms engaged in export markets may rely more on productivity improvements or capital intensification rather than labour expansion. This result is consistent with studies indicating that revenue growth does not necessarily translate into domestic job creation, particularly when firms adopt more efficient production technologies [13]. Other firm characteristics, including ownership structure and international engagement, do not show robust direct effects on employment growth, suggesting that their influence may operate through indirect channels.

The findings also provide insight into the mechanisms through which innovation affects employment. Product innovation appears to increase labour demand primarily through expansion in production, marketing, and distribution activities associated with new or improved products. Process innovation, while potentially reducing labour requirements through efficiency gains, may generate compensatory effects by enabling firms to expand output and enter new markets, thereby supporting employment growth. These mechanisms suggest that the net employment impact of innovation reflects the balance between productivity improvements and demand expansion.

The diagnostic tests indicate that the instrument is relatively weak in the employment growth specifications, with first-stage F-statistics below the conventional threshold in some models. While the Wu–Hausman test provides limited evidence of endogeneity, the weaker instrument strength implies that the IV estimates for employment should be interpreted with caution.

Overall, the results suggest that innovation—particularly product and process innovation—is associated with employment growth among Vietnamese firms. However, the effects are less consistent and more sensitive to firm characteristics and model specification than those observed for sales growth, highlighting the context-dependent nature of innovation-driven job creation in emerging economies.

4.2. Robustness Checks

To ensure that our findings are not sensitive to sampling choices, model specification, or firm heterogeneity, we conduct several robustness checks.

First, we examine the sensitivity of the results to alternative treatments of outliers and sample composition. In the baseline analysis, sales and employment growth are winsorised at the 2.5th and 97.5th percentiles. As a robustness check, we apply a less restrictive winsorisation at the 1st and 99th percentiles, which retains a larger number of observations. The results remain qualitatively unchanged in terms of both coefficient magnitude and statistical significance. This indicates that the main findings are not driven by extreme observations or sample trimming decisions.

Second, we assess the robustness of the results across different subsamples by estimating the models separately for manufacturing and non-manufacturing firms. The results for the manufacturing subsample are consistent with the baseline findings. This suggests that the positive relationship between innovation and firm performance is particularly strong within the manufacturing sector, where innovation is more closely linked to production processes and output expansion. For the non-manufacturing subsample, the estimated coefficients on innovation variables remain consistent in sign with the baseline results but are statistically insignificant. This may reflect greater heterogeneity in innovation activities and performance outcomes in the service sector, as well as reduced statistical power. Nevertheless, the consistency in coefficient signs provides supporting evidence for the overall direction of the relationship.

Third, we examine whether the effects of innovation differ across firm size by interacting innovation variables with a small firm variable. The interaction terms are generally statistically insignificant and accompanied by relatively large standard errors, indicating no strong evidence of systematic differences in the impact of innovation between small and larger firms. While some interaction coefficients are negative, these estimates are not precisely measured. Overall, this suggests that the baseline results are not driven by firm size heterogeneity and that the positive effects of innovation on firm performance are broadly consistent across firms.

Taken together, these robustness checks confirm that the main findings are stable across alternative treatments of outliers, different sample compositions, and firm size variations, thereby reinforcing the reliability of the empirical results.

As an additional robustness check, we estimate a specification in which all innovation variables are included jointly in an ordinary least squares (OLS) framework. The results indicate that none of the innovation variables remain statistically significant when entered simultaneously. This likely reflects the moderate correlations between innovation measures (see Table A2), which reduce the precision of the estimates in a combined specification.

Importantly, the instrumental variable (IV) approach used in the baseline analysis does not allow for the simultaneous inclusion of multiple endogenous innovation variables due to identification constraints, as only a single instrument is available. As a result, the baseline specifications estimate the effects of different types of innovation separately.

Overall, these results suggest that while individual innovation measures are associated with firm performance when instrumented, their effects are difficult to disentangle when considered jointly, highlighting potential overlap in the channels through which different innovation activities affect firm outcomes.

4.3. Limitations of Cross-Sectional Identification

This study is based on cross-sectional firm-level data, which imposes important limitations on the interpretation of the empirical results. In particular, the cross-sectional nature of the data restricts our ability to draw causal inferences regarding the relationship between innovation and firm performance. While the empirical strategy, including the use of instrumental variables, is designed to mitigate potential endogeneity concerns, it cannot fully eliminate issues such as reverse causality or omitted variable bias.

As a result, the estimated coefficients should be interpreted as capturing associative relationships rather than definitive causal effects. The findings therefore provide evidence of a strong and consistent link between innovation and firm performance, but do not establish that innovation directly causes improvements in sales or employment growth.

Future research using panel data or quasi-experimental approaches would be valuable in establishing more robust causal relationships and examining the dynamic effects of innovation over time.

5. Conclusions

This study set out to examine how different forms of innovation influence firm performance in Vietnam, a country characterised by a strong policy emphasis on innovation alongside persistent structural and institutional constraints. Using unique firm-level data from the World Bank Enterprise Survey, the analysis provides new empirical evidence on the innovation–performance relationship in an emerging economy where innovation is largely incremental and unevenly distributed across firms.

Our findings show that innovation is strongly associated with firm growth, but its effects vary systematically across performance dimensions. Product and process innovation are strongly associated with higher sales growth, while the evidence for R&D expenditure and R&D participation is weaker, confirming that both market-oriented and efficiency-enhancing innovations contribute to revenue expansion. These results are in line with theoretical perspectives such as the Resource-Based View and Dynamic Capabilities theory, which emphasise the role of innovation in strengthening competitive advantage and enabling firms to respond to changing market conditions. However, the effects on employment growth are more moderate and selective. While innovation is positively associated with job creation, the magnitude of these effects is smaller and more sensitive to firm characteristics and institutional conditions. This divergence highlights a central insight of the study: innovation-driven revenue growth does not necessarily translate into proportional employment expansion.

The analysis also demonstrates that the returns to innovation are conditional on complementary factors. Firms with access to international markets are better able to translate innovation into sales growth, while small firms face persistent constraints in scaling innovation-driven expansion. In addition, regulatory barriers are found to limit employment growth, underscoring the importance of the institutional environment in shaping labour outcomes. These findings reinforce the argument advanced in the introduction that the performance effects of innovation are highly context dependent, particularly in developing economies where firms operate under resource and institutional constraints. They also highlight the prominent role of development-oriented and adaptation-based innovation, reflecting the practical realities of innovation in Vietnam.

This study contributes to the literature by providing updated firm-level evidence on the heterogeneous effects of innovation across performance dimensions in an emerging economy context. By jointly analysing multiple forms of innovation and distinguishing between sales and employment outcomes, the paper offers a more nuanced understanding of the mechanisms through which innovation affects firm growth. The results also extend existing research by highlighting the importance of commercialisation-oriented innovation activities and the role of institutional constraints in shaping employment outcomes.

This study has several limitations. First, the analysis is based on cross-sectional data, which limits the ability to capture the dynamic effects of innovation over time. Second, while the instrumental variable approach is employed to address endogeneity concerns, the strength of the instrument varies across specifications, particularly for employment growth, which may affect the precision of the estimates. Third, the measures of innovation are derived from survey data and may be subject to measurement error. These limitations suggest that the results should be interpreted with appropriate caution.

Several avenues for future research emerge from this analysis. First, the use of panel data would allow for stronger identification of causal relationships and a better understanding of the persistence of innovation effects over time. Second, further research could examine interaction effects between innovation and institutional factors, particularly in relation to regulatory reforms and access to finance. Third, extending the analysis to additional outcomes such as productivity, job quality, and wage dynamics would provide a more comprehensive assessment of the broader economic implications of innovation.

These findings have several policy implications. First, targeted support for small and medium-sized enterprises (SMEs) is essential to help them scale innovation activities, particularly through improved access to finance and technical support. Second, reducing regulatory and legal barriers may facilitate employment growth by lowering constraints on firm expansion. Third, policies that support innovation activities, including product, process, and R&D-related activities, may be particularly effective, as these forms of innovation are more closely linked to firm performance in the Vietnamese context. Together, these results suggest that innovation policy should be complemented by institutional reforms to maximise its impact on firm growth.