Factors influencing new product development capability of small and medium-sized enterprises in the manufacturing and processing industry in Vietnam amid the economic crisis

Introduction

The manufacturing and processing industry in Vietnam is one of the key pillars of the economy, significantly contributing to GDP growth and generating high-added value. The development of this sector not only directly impacts economic growth but also has a spillover effect on other industries and the economy as a whole. During the period from 2011 to 2020, Vietnam's manufacturing and processing industry demonstrated its role as a growth driver, accounting for an average of 14.9% of GDP and achieving an impressive average growth rate of 10.44% per year, which is higher than the overall economic growth rate. This indicates the increasing dependence of the economy on the sustainable development of this sector. In the second quarter of 2024, Vietnam's manufacturing and processing industry experienced a diverse range of export and import activities. Certain export products, such as footwear, textiles, and electronics, saw robust growth, reflecting a recovery in these manufacturing sectors. However, imports of raw materials like crude oil, wood, and fabric also rose significantly, showing the sector's reliance on foreign supplies (General Statistics Office, 2024). Despite its crucial role in economic growth, Vietnam's manufacturing and processing industry still faces many limitations. Notably, small and medium-sized enterprises (SMEs), which constitute a large proportion of the sector, are grappling with various challenges during the economic crisis, yet they play a vital role in driving the sector's development. One of the major issues the manufacturing and processing industry faces is the low localization rate of products. The heavy reliance on imported raw materials and components makes domestic production vulnerable to global market fluctuations. This not only reduces the competitiveness of products but also limits the industry's sustainable development. SMEs, with their flexibility and adaptability, play an essential role in product diversification and meeting domestic market demand. However, these enterprises often struggle with limited access to capital, technology, and markets, which hinders their ability to invest in research and development, improve product quality, and scale up production.

Model and Estimation Results

Model and Variable Description

In this model, the dependent variable, New Product, is binary. Therefore, a logistic regression model (Logit) is used. The Logit model applies where the dependent variable Y is binary, taking values of 0 and 1. If we denote the independent variables (influential factors) as Xj (for j = 2,., k), the probability that the dependent variable Y equals 1 is given by the formula below:

Notation

The logit model can be written as:

  

the unknown coefficients that need to be estimated. Equation ( 2) is referred to as the logistic distribution function.

In this function, Xβ ranges from -∞ to +∞, so p takes values from 0 to 1, and pi is nonlinear with both Xj and the parameters β. The panel data regression model that evaluates the impact of various factors on the likelihood of product creation by small and medium-sized enterprises (SMEs) in the manufacturing and processing industries in this study is structured as follows: to improve or replace products to create better ones with higher competitiveness. Therefore, the author includes Profit as an independent variable in the model.  Export: In practice, companies that export are often affected by economic crises. Hence, the author incorporates the Export variable into the model to assess its impact on the likelihood of introducing new products.  Process: When a company enhances its technology or production processes, it contributes to the creation of new products. Thus, the author includes the production process variable (Process) in the model, expecting it to have a positive impact on the likelihood of introducing new products.  Ownership: The ownership form of the enterprise is also expected to affect its ability to create new products. In this study, the Ownership variable takes the value "0" if the ownership form is a household enterprise or a sole proprietorship, and "1" if the ownership form is a partnership, cooperative, limited liability company, jointstock company, joint venture, or state-owned enterprise.  Year: The year factor is also included in the model to assess the impact of crises on the likelihood of introducing new products. The Hausman test indicates that the random effects model is more appropriate. The estimation results (Table 2) show that: The variables Export, Process, and Sector are statistically significant at the 1% level, while the variables Ownership and Year are statistically significant at the 5% level. The coefficients of these variables are positive. The Profit variable is statistically significant at the 10% level, and its coefficient is also positive.

Conclusion and Policy Implications

Based on the estimated model results, the authors of the article propose the following policy implications: When businesses innovate their production technology processes, they are 3.5 times more likely to introduce new products compared to businesses that do not innovate their production technology processes (Assuming other factors remain unchanged and calculated at the mean value). This is consistent with the fact that when businesses change their production processes to improve labor productivity, they are often able to introduce new products that are better suited to the market and consumer preferences. Exporting businesses are 2.32 times more likely to introduce new products compared to non-exporting businesses (Assuming other factors remain unchanged and calculated at the mean value). This can be explained by the fact that exporting businesses are more flexible in their production activities, as the products they manufacture are not only supplied domestically but also exported to foreign markets where consumers tend to be more demanding and have higher requirements. However, this also presents an opportunity for businesses to innovate and develop new products that are better suited to the market, especially foreign markets. Additionally, the international environment is often more volatile, and export policies can change, meaning businesses are more likely to innovate and adapt their products accordingly. Moreover, the regression results also show that industry type affects the likelihood of businesses creating new products. Businesses in the petrochemical, metal, non-ferrous, and assembly industries are more likely to create new products than those in the food processing industry. This is also consistent with reality, as the food processing industry generally has readily available raw materials, lower product costs, and a largely stable domestic market. Therefore, changing products and creating new products to compete is not usually the primary objective for businesses in this sector. In contrast, businesses in resource-based industries (Such as oil, coal, etc.) often face resource depletion, prompting them to innovate their production processes and improve products to meet market demand. The ownership structure of businesses also affects their ability to create new products. Businesses that are corporations, cooperatives, limited liability companies, joint-stock companies, state-owned enterprises, or joint ventures are more likely to create new products than family businesses or private enterprises. This is in line with the fact that family businesses or private enterprises often face financial and technical constraints, so their ability to create new products is lower compared to businesses with stronger financial resources and technical expertise. A 1% increase in average profit will result in a business's likelihood of creating new products being 89% of the initial value (Assuming other factors remain unchanged and calculated at the mean value). The regression results also show that, compared to 2007, businesses in 2009 (After the crisis) had a 41% lower likelihood of creating new products. After the 2008 crisis, the likelihood of businesses introducing new products continued to drop by approximately 37% in 2011 compared to 2007. This can be explained by the fact that the economic crisis of 2008 created challenges for small and medium-sized enterprises, forcing them to focus on creating new products to recover and grow.

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