Factors Affecting the Support of Industrial Businesses’ Performance in Vietnam’s Digital Economy

This study analyzes the factors that affect the technical efficiency (TE) of firms in the supporting industry in the context of Vietnam’s digitalized economy. Stochastic frontier analysis (SFA), Fixed Effect Models, and System-GMM methods are applied to reach the findings that the quality of human resources, capital intensity, and firm size have positive effects on TE. Furthermore, exogenous environmental factors, such as the domestic demand of an industry impacting all upstream businesses, which use inputs that are products of that industry (BSpill-ratio), and the FDI backward effect (BFSpill), also exhibit positive effects. These confirm that the linkage between domestic supporting industry suppliers and FDI assembly enterprises plays an important role in improving TE. Vietnam’s digital transformation since 2020 has also created some interesting changes in the correlation coefficient. Location, sectors, competitiveness, and investment environment are also considered, and the results suggest that they are all determinants to be considered in management policies at both the firm level and the government level. Our contribution in this study is new policies aligned with many major changes in the world economic context, such as the tough tariff policy implemented by recent presidential administrations and a series of reforms of the Vietnamese Government, as well as strong digital transformation in Vietnam. The key findings of this research are important as they confirm which factors are really determinants for the Vietnamese government to implement investment policies for this industry effectively.

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Publication Details

Journal
Sustainability
Published
2025-09-04
DOI
https://doi.org/10.3390/su17177996
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
0.00

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article

Factors Affecting the Support of Industrial Businesses’ Performance in Vietnam’s Digital Economy

Duong Phuong Thao Pham, Tho V. Le, Khanh-Duy Le, Duc Huynh
Sustainability
Efficiency Analysis Using DEA
article

Factors Affecting the Support of Industrial Businesses’ Performance in Vietnam’s Digital Economy

Duong Phuong Thao Pham, Tho V. Le, Khanh-Duy Le, Duc Huynh
article en

Abstract

This study analyzes the factors that affect the technical efficiency (TE) of firms in the supporting industry in the context of Vietnam’s digitalized economy. Stochastic frontier analysis (SFA), Fixed Effect Models, and System-GMM methods are applied to reach the findings that the quality of human resources, capital intensity, and firm size have positive effects on TE. Furthermore, exogenous environmental factors, such as the domestic demand of an industry impacting all upstream businesses, which use inputs that are products of that industry (BSpill-ratio), and the FDI backward effect (BFSpill), also exhibit positive effects. These confirm that the linkage between domestic supporting industry suppliers and FDI assembly enterprises plays an important role in improving TE. Vietnam’s digital transformation since 2020 has also created some interesting changes in the correlation coefficient. Location, sectors, competitiveness, and investment environment are also considered, and the results suggest that they are all determinants to be considered in management policies at both the firm level and the government level. Our contribution in this study is new policies aligned with many major changes in the world economic context, such as the tough tariff policy implemented by recent presidential administrations and a series of reforms of the Vietnamese Government, as well as strong digital transformation in Vietnam. The key findings of this research are important as they confirm which factors are really determinants for the Vietnamese government to implement investment policies for this industry effectively.

SustainabilityVol. 17(17)
University of Economics Ho Chi Minh City (VN)
Bộ Giáo dục và Ðào tạo
Openalex Percentile: Top 72%
Efficiency Analysis Using DEA
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