Material Sourcing Characteristics and Firm Performance: An Empirical Study in Vietnam
Abstract
:1. Introduction
1.1. Role of Raw Materials
- (i)
- How do sources of raw materials affect SME’s performance?
- (ii)
- How do domestic sources of raw materials affect SME’s performance?
- (iii)
- How do international sources of raw materials affect SME’s performance?
1.2. Research Backgrounds
1.3. Contributions
- (i)
- By using fixed-effects regression models with year (Year_FEs), industry (Industry_FEs), and sectors (Sector_FEs), the findings precisely reflect domestic and international sources of materials, which provide firms with more opportunities to improve their productivity and engage in new product lines.
- (ii)
- Based on firm size and excessive raw material sourcing behaviors, this study strongly suggests the results of these effects, ensuring the application of the results in the long term for manufacturing firms.
- (iii)
- With the characteristics of an emerging country such as Vietnam, this study may apply to SMEs in other countries, reducing research time and providing more potential extensions for suppliers.
- (iv)
- More importantly, this study significantly contributes to this area, which is regarded as a foundation for future studies to exemplify more effects of the source of materials on firm performance.
2. Literature Review
2.1. Firm Performance
2.2. Domestic Raw Materials
2.3. International Raw Materials
3. Methodology
3.1. Methodology
- (i)
- The results accurately reflect the effects of each source of raw material on firm performance.
- (ii)
- Examining the effects with firms under similar years and industries.
- (iii)
- Combining greatly with panel data.
- (iv)
- Proposing long-term applications.
3.2. Data Description
4. Main Analysis and Discussion
4.1. Descriptive Statistic
4.2. Correlation Matrix
4.3. Regression Analysis
4.4. Additional Analysis
4.4.1. Non-Linear Regression
4.4.2. Firm-Size and Sourcing of Raw Materials
5. Conclusions, Implications and Limitations
5.1. Conclusions
5.2. Implications
5.3. Limitations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Kolotzek, C.; Helbig, C.; Thorenz, A.; Reller, A.; Tuma, A. A Company-Oriented Model for the Assessment of Raw Material Supply Risks, Environmental Impact and Social Implications. J. Clean. Prod. 2018, 176, 566–580. [Google Scholar] [CrossRef]
- Glöser, S.; Tercero Espinoza, L.; Gandenberger, C.; Faulstich, M. Raw Material Criticality in the Context of Classical Risk Assessment. Resour. Policy 2015, 44, 35–46. [Google Scholar] [CrossRef]
- Tsai, J.F.; Nguyen, P.H.; Lin, M.H.; van Nguyen, D.; Lin, H.H.; Ngo, A.T. Impacts of Environmental Certificate and Pollution Abatement Equipment on Smes’ Performance: An Empirical Case in Vietnam. Sustainability 2021, 13, 9705. [Google Scholar] [CrossRef]
- Hsu, C.-C.; Choon Tan, K.; Laosirihongthong, T. Antecedents of SCM practices in ASEAN automotive industry: Corporate entrepreneurship, social capital, and resource-based perspectives. Int. J. Logist. Manag. 2014, 25, 334–357. [Google Scholar] [CrossRef]
- Wisner, J.D. A Structural Equation Model Of Supply Chain Management Strategies And Firm Performance. J. Bus. Logist. 2003, 24, 1–26. [Google Scholar] [CrossRef]
- Yunarto, H.I.; Santika, M.G. Business Concepts Implementation Series in Inventory Management. Language 2005, 29, 24cm. [Google Scholar]
- Bendiksen, B.I.; Dreyer, B. Technological Changes—The Impact on the Raw Material Flow and Production. Eur. J. Oper. Res. 2003, 144, 237–246. [Google Scholar] [CrossRef]
- Oyelaran-Oyeyinka, B. Manufacturing Response in a National System of Innovation: Evidence from the Brewing Firms in Nigeria. Discuss. Pap. Ser. 2002, 3, 1–60. [Google Scholar]
- Behrens, A.; Giljum, S.; Kovanda, J.; Niza, S. The Material Basis of the Global Economy: Worldwide Patterns of Natural Resource Extraction and Their Implications for Sustainable Resource Use Policies. Ecol. Econ. 2007, 64, 444–453. [Google Scholar] [CrossRef]
- Georgise, F.B.; Thoben, K.-D.; Seifert, M. Supply Chain Integration in the Manufacturing Firms in Developing Country: An Ethiopian Case Study. J. Ind. Eng. 2014, 2014, 1–13. [Google Scholar] [CrossRef] [Green Version]
- Graedel, T.E.; Harper, E.M.; Nassar, N.T.; Nuss, P.; Reck, B.K. Criticality of Metals and Metalloids. Proc. Natl. Acad. Sci. USA 2015, 112, 4257–4262. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Trung, N.N.; Nghi, P.T.; Soldier, L.L.; Hoi, T.V.; Kim, W.J. Leadership, Resource and Organisational Innovation: Findings from State and Non-State Enterprises. Int. J. Innov. Manag. 2014, 18, 1450034. [Google Scholar] [CrossRef]
- Trang, H. Ministry of Industry and Trade: It Is Perfectly Acceptable to Continue Importing Raw Materials. Available online: https://doanhnhantrevietnam.vn/bo-cong-thuong-viec-tiep-tuc-nhap-khau-cac-nguyen-lieu-tho-la-hoan-toan-chap-nhan-duoc-d5274.html?fbclid=IwAR3CCrEOXvdBM6ONpkB7OkVKFxLYfaI3hizKFgXtORgcPxyVuY3C_F0lLJ8 (accessed on 14 March 2022).
- Haider, M.Z.; Ziaul, M. Raw Material Sourcing and Firm Performance: Evidence from Manufacturing Firms in South-West Bangladesh. Bangladesh Dev. Stud. 2010, 33, 51–61. [Google Scholar]
- Sucky, E.; Zitzmann, I. Supply Chain Risk Management in Sustainable Sourcing. In Social and Environmental Dimensions of Organizations and Supply Chains; Springer: Cham, Switzerland, 2018; pp. 135–151. [Google Scholar] [CrossRef]
- LuatVietnam. Decree No. 39/2018/ND-CP Dated March 11, 2018 of the Government on Detailing a Number of Articles of the Laws on Small and Medium-Sized Enterprises. Available online: https://english.luatvietnam.vn/decree-no-39-2018-nd-cp-dated-march-11-2018-of-the-government-on-detailing-a-number-of-articles-of-the-laws-on-small-and-medium-sized-enterprises-160820-Doc1.html#:~:text=39%2F2018%2FND%2DCP%20on%20detailing%20a%20number%20of,being%20offered%20free%20tuition%20frees (accessed on 5 April 2022).
- Bleischwitz, R.; Dittrich, M.; Pierdicca, C. Coltan from Central Africa, International Trade and Implications for Any Certification. Resour. Policy 2012, 37, 19–29. [Google Scholar] [CrossRef] [Green Version]
- Norgate, T.E.; Jahanshahi, S.; Rankin, W.J. Assessing the Environmental Impact of Metal Production Processes. J. Clean. Prod. 2007, 15, 838–848. [Google Scholar] [CrossRef]
- Schrijvers, D.; Hool, A.; Andrea Blengini, G.; Chen, W.-Q.; Dewulf, J.; Eggert, R.; Ellen, L.; Gauss, R.; Goddin, J.; Habib, K.; et al. A Review of Methods and Data to Determine Raw Material Criticality. Resour. Conserv. Recycl. 2019, 155, 104617. [Google Scholar] [CrossRef]
- Bach, V.; Berger, M.; Henßler, M.; Kirchner, M.; Leiser, S.; Mohr, L.; Rother, E.; Ruhland, K.; Schneider, L.; Tikana, L. Integrated Method to Assess Resource Efficiency–ESSENZ. J. Clean. Prod. 2016, 137, 118–130. [Google Scholar] [CrossRef] [Green Version]
- Cimprich, A.; Karim, K.S.; Young, S.B. Extending the Geopolitical Supply Risk Method: Material “Substitutability” Indicators Applied to Electric Vehicles and Dental X-Ray Equipment. Int. J. Life Cycle Assess. 2018, 23, 2024–2042. [Google Scholar] [CrossRef]
- Gemechu, E.D.; Sonnemann, G.; Young, S.B. Geopolitical-Related Supply Risk Assessment as a Complement to Environmental Impact Assessment: The Case of Electric Vehicles. Int. J. Life Cycle Assess. 2017, 22, 31–39. [Google Scholar] [CrossRef]
- Bauer, D.; Diamond, D.; Li, J.; Sandalow, D.; Telleen, P.; Wanner, B. US Department of Energy: Critical Materials Strategy. December 2010. Available online: https://www.osti.gov/servlets/purl/1000846 (accessed on 5 April 2022).
- Gauß, R.; Homm, G.; Gutfleisch, O. The Resource Basis of Magnetic Refrigeration. J. Ind. Ecol. 2017, 21, 1291–1300. [Google Scholar] [CrossRef]
- Habib, K.; Wenzel, H. Reviewing Resource Criticality Assessment from a Dynamic and Technology Specific Perspective–Using the Case of Direct-Drive Wind Turbines. J. Clean. Prod. 2016, 112, 3852–3863. [Google Scholar] [CrossRef]
- Helbig, C.; Bradshaw, A.M.; Wietschel, L.; Thorenz, A.; Tuma, A. Supply Risks Associated with Lithium-Ion Battery Materials. J. Clean. Prod. 2018, 172, 274–286. [Google Scholar] [CrossRef]
- Moss, R.L.; Tzimas, E.; Kara, H.; Willis, P.; Kooroshy, J. Critical Metals in Strategic Energy Technologies. Assessing Rare Metals as Supply-Chain Bottlenecks in Low-Carbon Energy Technologies. JRC Scientific and Technical Reports EUR 24884. 2011. Available online: https://static1.squarespace.com/static/5a60c3cc9f07f58443081f58/t/5ab3d83f0e2e721919e94cf3/1521735755642/CriticalMetalsinSET.pdf (accessed on 5 April 2022).
- Althaf, S.; Babbitt, C.W. Disruption risks to material supply chains in the electronics sector. Resour. Conserv. Recycl. 2021, 167, 105248. [Google Scholar] [CrossRef]
- Duclos, S.J.; Otto, J.P.; Konitzer, D.G. Design in an Era of Constrained Resources. Mech. Eng. 2010, 132, 36–40. [Google Scholar] [CrossRef] [Green Version]
- European Commission; Directorate-General for Internal Market Entrepreneurship and SMEs; Pennington, D.; Tzimas, E.; Baranzelli, C.; Dewulf, J.; Manfredi, S.; Nuss, P.; Grohol, M.; van Maercke, A.; et al. Methodology for Establishing the EU List of Critical Raw Materials: Guidelines; Publications Office of the European Union: Luxemburg, 2017. [Google Scholar]
- Liu, L.; Zhao, Q.; Goh, M. Perishable material sourcing and final product pricing decisions for two-echelon supply chain under price-sensitive demand. Comput. Ind. Eng. 2021, 156, 107260. [Google Scholar] [CrossRef]
- Hatayama, H.; Tahara, K. Criticality Assessment of Metals for Japan’s Resource Strategy. Mater. Trans. 2015, 56, 229–235. [Google Scholar] [CrossRef] [Green Version]
- Kuo, T.C.; Chen, K.J.; Shiang, W.J.; Huang, P.B.; Otieno, W.; Chiu, M.C. A collaborative data-driven analytics of material resource management in smart supply chain by using a hybrid Industry 3.5 strategy. Resour. Conserv. Recycl. 2021, 164, 105160. [Google Scholar] [CrossRef]
- National Research Council. Minerals, Critical Minerals, and the US Economy; National Academies Press: Washington, DC, USA, 2008; ISBN 0309112826. [Google Scholar]
- Morley, N.; Eatherley, D. Material Security: Ensuring Resource Availability for the UK Economy; C-Tech Innovation Limited: Chester, UK, 2008; ISBN 1906237034. [Google Scholar]
- Saha, R.; Shashi; Cerchione, R.; Singh, R.; Dahiya, R. Effect of Ethical Leadership and Corporate Social Responsibility on Firm Performance: A Systematic Review. Corp. Soc. Responsib. Environ. Manag. 2020, 27, 409–429. [Google Scholar] [CrossRef]
- Fernández-Temprano, M.A.; Tejerina-Gaite, F. Types of Director, Board Diversity and Firm Performance. Corp. Gov. 2020, 20, 324–342. [Google Scholar] [CrossRef]
- Ferraris, A.; Mazzoleni, A.; Devalle, A.; Couturier, J. Big Data Analytics Capabilities and Knowledge Management: Impact on Firm Performance. Manag. Decis. 2019, 57, 1923–1936. [Google Scholar] [CrossRef]
- Giljum, S.; Dittrich, M.; Lieber, M.; Lutter, S. Global Patterns of Material Flows and their Socio-Economic and Environmental Implications: A MFA Study on All Countries World-Wide from 1980 to 2009. Resources 2014, 3, 319–339. [Google Scholar] [CrossRef]
- Burger, A. Dynamic Effects of International Fragmentation of Production: Empirical Analysis of Slovenian Manufacturing Firms. Ph.D. Thesis, University of Ljubljana, Faculty of Economics, Ljubljana, Slovenia, 2009. Available online: http://www.cek.ef.uni-lj.si/doktor/burger267.pdf (accessed on 5 April 2022).
- Kristoffersen, E.; Mikalef, P.; Blomsma, F.; Li, J. The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance. Int. J. Prod. Econ. 2021, 239, 108205. [Google Scholar] [CrossRef]
- Luu, H.N.; Nguyen, L.Q.T.; Vu, Q.H.; Tuan, L.Q. Income Diversification and Financial Performance of Commercial Banks in Vietnam, Do Experience and Ownership Structure Matter? Rev. Behav. Financ. 2019, 12, 185–199. [Google Scholar] [CrossRef]
- Kamasak, R. The Contribution of Tangible and Intangible Resources, and Capabilities to a Firm’s Profitability and Market Performance. Eur. J. Manag. Bus. Econ. 2017, 26, 252–275. [Google Scholar] [CrossRef] [Green Version]
- Wu, M.-W.; Shen, C.-H. Corporate Social Responsibility in the Banking Industry: Motives and Financial Performance. J. Bank. Financ. 2013, 37, 3529–3547. [Google Scholar] [CrossRef]
- Becker, G.S. Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education; University of Chicago Press: Chicago, IL, USA, 1964; ISBN 0-226-04119-0. Available online: https://www.nber.org/books-and-chapters/human-capital-theoretical-and-empirical-analysis-special-reference-education-third-edition (accessed on 5 April 2022).
- Peni, E. CEO and Chairperson Characteristics and Firm Performance. J. Manag. Gov. 2014, 18, 185–205. [Google Scholar] [CrossRef]
- UNU-WIDER. Viet Nam SME Database. Available online: https://www.wider.unu.edu/database/viet-nam-sme-database (accessed on 5 April 2022).
- Taylor, R. Interpretation of the Correlation Coefficient: A Basic Review. J. Diagn. Med. Sonogr. 1990, 6, 35–39. [Google Scholar] [CrossRef]
- Massari, S.; Ruberti, M. Rare Earth Elements as Critical Raw Materials: Focus on International Markets and Future Strategies. Resour. Policy 2013, 38, 36–43. [Google Scholar] [CrossRef]
- Aron, D.J. Ability, Moral Hazard, Firm Size, and Diversification. Rand J. Econ. 1988, 19, 72–87. [Google Scholar] [CrossRef]
Micro-Enterprises | Small Enterprises | Medium Enterprises | ||||
---|---|---|---|---|---|---|
Manufacturing firms | Number of employees (Person) | Total annual revenue and total capital (VND billion) | Number of employees (Person) | Total annual revenue and total capital (VND billion) | Number of employees (Person) | Total annual revenue and total capital (VND billion) |
Less than 10 | Less than 3 in total annual revenue or 3 in total capital | From more than 10 to 50 | Less than 100 in total annual revenue or 50 in total capital | From more than 10 to 100 | Less than 300 in total annual revenue or 100 in total capital |
Variables | Measurement | Referring Source |
---|---|---|
Firm Performance | Return on assets (ROA), return on equity (ROE) | SMEs Surveys |
Materials from Non-state Enterprises | Number of raw materials from non-state Enterprises (%) | SMEs Surveys |
Materials from State Enterprises | Number of raw materials from state enterprises (%) | SMEs Surveys |
Materials from State Agencies | Number of raw materials from state agencies (%) | SMEs Surveys |
Importing Raw Materials | Number of raw materials imported from international markets (%) | SMEs Surveys |
Size | Ln (Total assets) | SMEs Surveys |
Firm Age | Ln (Operation years since firm’s establishment +1) | SMEs Surveys |
Fixed Assets | Fixed assets divided by total assets | SMEs Surveys |
Firm Capital | Equity divided by total assets | SMEs Surveys |
Education | Dummy variables, one if respondent accomplished upper secondary school, zero otherwise | SMEs Surveys |
Experience | Ln (Years that the respondent is in charge of the company) | SMEs Surveys |
Variable | n | Mean | sd | p25 | p50 | p75 |
---|---|---|---|---|---|---|
ROA | 7631 | 0.297 | 1.181 | 0.047 | 0.125 | 0.314 |
ROE | 7631 | 0.307 | 0.499 | 0.05 | 0.134 | 0.351 |
M_NSE | 7631 | 0.747 | 0.219 | 0.6 | 0.8 | 0.91 |
M_SE | 7631 | 0.145 | 0.151 | 0.05 | 0.1 | 0.2 |
M_SEA | 7631 | 0.003 | 0.018 | 0 | 0 | 0 |
Importing_M | 7631 | 0.015 | 0.093 | 0 | 0 | 0 |
Size | 7631 | 7.199 | 1.72 | 5.989 | 7.295 | 8.418 |
Firm Age | 7631 | 7.600 | 0.005 | 7.598 | 7.601 | 7.603 |
Fixed Assets | 7631 | 0.763 | 0.217 | 0.653 | 0.834 | 0.933 |
Firm Capital | 7631 | 0.927 | 0.147 | 0.925 | 1 | 1 |
Education | 7631 | 0.680 | 0.466 | 0 | 1 | 1 |
Experience | 7631 | 7.600 | 0.004 | 7.598 | 7.601 | 7.603 |
Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
ROA | 1.000 | |||||||||||
ROE | 0.503 *** | 1 | ||||||||||
M_NSE | 0.0207 | 0.0836 *** | 1 | |||||||||
M_SE | −0.0406 *** | −0.0945 *** | −0.649 *** | 1 | ||||||||
M_SEA | −0.0169 | −0.0276 * | −0.175 *** | 0.0392 *** | 1 | |||||||
Importing_M | 0.00434 | −0.0187 | −0.387 *** | −0.0412 *** | 0.0392 *** | 1 | ||||||
Size | −0.215 *** | −0.461 *** | −0.214 *** | 0.177 *** | 0.106 *** | 0.214 *** | 1 | |||||
Firm Age | 0.00541 | 0.0310 *** | −0.0430 *** | 0.0460 *** | 0.0222 | 0.0608 *** | 0.128 *** | 1 | ||||
Fixed Assets | −0.113 *** | −0.263 *** | 0.0294 * | −0.00594 | −0.0471 *** | −0.113 *** | 0.0445 *** | −0.160 *** | 1 | |||
Firm Capital | 0.00916 | −0.194 *** | 0.00808 | 0.0148 | −0.0404 *** | −0.117 *** | −0.115 *** | −0.104 *** | 0.319 *** | 1 | ||
Education | −0.0218 | −0.0702 *** | −0.0937 *** | 0.0745 *** | 0.0695 *** | 0.108 *** | 0.304 *** | 0.170 *** | −0.186 *** | −0.110 *** | 1 | |
Experience | −0.00245 | 0.0256 *** | −0.0663 *** | 0.0623 *** | 0.0257 * | 0.0599 *** | 0.167 *** | 0.760 *** | −0.167 *** | −0.103 *** | 0.196 *** | 1 |
(1) | (2) | (3) | (4) | (5) | (6) | |
---|---|---|---|---|---|---|
Variables | ROA | ROE | ROA | ROE | ROA | ROE |
M_NSE | 0.078 | 0.124 *** | −0.005 | 0.087 ** | ||
(0.115) | (0.043) | (0.126) | (0.043) | |||
M_SE | 0.001 | 0.075 | −0.111 | 0.036 | ||
(0.130) | (0.054) | (0.167) | (0.055) | |||
M_SEA | −1.002 | 0.824 ** | −1.199 | 0.735 ** | ||
(1.607) | (0.345) | (1.608) | (0.349) | |||
Importing_M | −0.436 | −0.301 ** | −0.330 | −0.215 * | ||
(0.285) | (0.117) | (0.324) | (0.123) | |||
Size | −0.297 *** | −0.197 *** | −0.297 *** | −0.199 *** | −0.290 *** | −0.198 *** |
(0.104) | (0.012) | (0.102) | (0.012) | (0.094) | (0.012) | |
Firm Age | −4.446 | −5.836 | −4.426 | −5.702 | −4.768 | −5.755 |
(4.540) | (3.807) | (4.543) | (3.798) | (4.690) | (3.796) | |
Fixed Assets | −0.297 ** | −0.146 *** | −0.303 ** | −0.147 *** | −0.297 ** | −0.145 *** |
(0.121) | (0.045) | (0.122) | (0.045) | (0.131) | (0.045) | |
Firm Capital | 0.212 ** | −0.665 *** | 0.221 ** | −0.658 *** | 0.215 * | −0.664 *** |
(0.105) | (0.085) | (0.100) | (0.084) | (0.112) | (0.085) | |
Education | 0.012 | 0.031 * | 0.013 | 0.030 * | 0.025 | 0.031 * |
(0.019) | (0.018) | (0.019) | (0.018) | (0.023) | (0.018) | |
Experience | 3.197 | 3.327 | 2.656 | 2.856 | 2.056 | 3.079 |
(3.527) | (2.878) | (3.629) | (2.878) | (4.170) | (2.873) | |
Constant | 11.937 | 21.786 | 15.822 | 24.253 | 24.856 | 22.991 |
(35.379) | (28.710) | (35.958) | (28.826) | (40.980) | (28.716) | |
Year_FEs | YES | YES | YES | YES | YES | YES |
Industry_FEs | YES | YES | YES | YES | YES | YES |
Sector_FEs | YES | YES | YES | YES | YES | YES |
R-Squared | 0.047 | 0.219 | 0.047 | 0.219 | 0.069 | 0.220 |
Observations | 7594 | 7594 | 7594 | 7594 | 7594 | 7594 |
Number of Firms | 3485 | 3485 | 3485 | 3485 | 3485 | 3485 |
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Variables | ROA | ROE | ROA | ROE |
M_NSE | 0.261 | 0.427 ** | ||
(0.592) | (0.176) | |||
M_SE | −0.290 | −0.129 | ||
(0.524) | (0.139) | |||
M_SEA | −22.67 | 0.350 | ||
(23.53) | (1.596) | |||
M_NSE Square | −0.149 | −0.259 ** | ||
(0.426) | (0.132) | |||
M_SE Square | 0.447 | 0.262 | ||
(0.765) | (0.202) | |||
M_SEA Square | 162.7 | 3.501 | ||
(165.2) | (11.92) | |||
Importing_M | 0.716 | −0.0400 | ||
(0.740) | (0.367) | |||
Importing_M Square | −1.716 | −0.489 | ||
(1.194) | (0.582) | |||
Size | −0.304 *** | −0.209 *** | −0.309 *** | −0.208 *** |
(0.102) | (0.0123) | (0.109) | (0.0124) | |
Firm Age | −4.164 | −5.240 | −3.893 | −5.400 |
(4.809) | (3.682) | (4.421) | (3.703) | |
Fixed Assets | −0.335 ** | −0.175 *** | −0.327 ** | −0.171 *** |
(0.134) | (0.0462) | (0.134) | (0.0464) | |
Firm Capital | 0.183 ** | −0.646 *** | 0.195 * | −0.655 *** |
(0.0907) | (0.0842) | (0.102) | (0.0846) | |
Education | 0.0162 | 0.0271 | 0.0186 | 0.0270 |
(0.0190) | (0.0179) | (0.0193) | (0.0179) | |
Experience | 0.525 | 2.570 | 0.876 | 2.860 |
−0.304 *** | (2.799) | −0.309 *** | (2.824) | |
Constant | 35.409 | 23.596 | 22.762 | 21.568 |
(42.510) | (28.780) | (40.439) | (28.748) | |
Year_FEs | YES | YES | YES | YES |
Province_Year_FEs | YES | YES | YES | YES |
R-Squared | 0.075 | 0.220 | 0.069 | 0.219 |
Observations | 7595 | 7595 | 7595 | 7595 |
Number of Firms | 3485 | 3485 | 3485 | 3485 |
Small Enterprises | Medium Enterprises | Larger Enterprises | ||||
---|---|---|---|---|---|---|
Variables | ROA | ROE | ROA | ROE | ROA | ROE |
M_NSE | −0.247 | 0.181 | 0.103 | 0.148 ** | 0.0004 | −0.026 |
(0.416) | (0.116) | (0.186) | (0.074) | (0.043) | (0.062) | |
M_SE | −0.115 | 0.165 | 0.093 | 0.066 | −0.040 | −0.094 |
(0.439) | (0.158) | (0.114) | (0.095) | (0.056) | (0.087) | |
M_SEA | −0.864 | 0.382 | 0.213 | 0.202 | 0.356 | 0.527 |
(1.780) | (1.729) | (0.446) | (0.350) | (0.365) | (0.350) | |
Importing_M | −99.391 *** | 0.023 | −0.073 | −0.161 | −0.470 | −0.274 * |
(0.514) | (0.259) | (0.220) | (0.205) | (0.363) | (0.146) | |
Size | −0.408 *** | −0.407 *** | −0.123 ** | −0.078 *** | −0.038 | −0.114 *** |
(0.039) | (0.032) | (0.049) | (0.029) | (0.056) | (0.021) | |
Firm Age | −25.486 | −22.005 * | 4.568 | 2.369 | −2.759 | 0.387 |
(15.659) | (12.770) | (3.687) | (3.052) | (4.504) | (2.951) | |
Fixed Assets | −0.155 | −0.089 | −0.217 *** | −0.132 | −0.207 ** | −0.115 |
(0.153) | (0.102) | (0.084) | (0.091) | (0.095) | (0.083) | |
Firm Capital | 0.354 | −1.395 *** | 0.272 | −0.592 *** | 0.062 | −0.147 |
(0.248) | (0.167) | (0.197) | (0.170) | (0.106) | (0.098) | |
Education | −0.001 | 0.028 | −0.019 | −0.017 | 0.012 | 0.000 |
(0.043) | (0.040) | (0.018) | (0.018) | (0.022) | (0.020) | |
Experience | 15.733 | 9.290 | −1.209 | 0.744 | 5.033 | 9.024 |
(10.678) | (8.961) | (2.980) | (3.692) | (4.761) | (5.656) | |
Constant | 76.477 | 100.101 | −24.793 | −22.580 | −16.909 | −70.207 |
(75.663) | (70.151) | (29.067) | (23.504) | (57.354) | (53.897) | |
Year_FEs | YES | YES | YES | YES | YES | YES |
Industry_FEs | YES | YES | YES | YES | YES | YES |
Sector_FEs | YES | YES | YES | YES | YES | YES |
R-Squared | 0.217 | 0.335 | 0.018 | 0.117 | 0.047 | 0.097 |
Observations | 2534 | 2534 | 2534 | 2534 | 2526 | 2526 |
Number of Firms | 1406 | 1406 | 1584 | 1584 | 1428 | 1428 |
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Nguyen, P.-H.; Hsu-Hao, L.; Pham, H.-A.; Thi, H.L.; Do, Q.M.; Nguyen, D.H.; Nguyen, T.-H. Material Sourcing Characteristics and Firm Performance: An Empirical Study in Vietnam. Mathematics 2022, 10, 1691. https://doi.org/10.3390/math10101691
Nguyen P-H, Hsu-Hao L, Pham H-A, Thi HL, Do QM, Nguyen DH, Nguyen T-H. Material Sourcing Characteristics and Firm Performance: An Empirical Study in Vietnam. Mathematics. 2022; 10(10):1691. https://doi.org/10.3390/math10101691
Chicago/Turabian StyleNguyen, Phi-Hung, Lin Hsu-Hao, Hong-Anh Pham, Huong Le Thi, Quynh Mai Do, Dieu Huong Nguyen, and Thu-Ha Nguyen. 2022. "Material Sourcing Characteristics and Firm Performance: An Empirical Study in Vietnam" Mathematics 10, no. 10: 1691. https://doi.org/10.3390/math10101691
APA StyleNguyen, P. -H., Hsu-Hao, L., Pham, H. -A., Thi, H. L., Do, Q. M., Nguyen, D. H., & Nguyen, T. -H. (2022). Material Sourcing Characteristics and Firm Performance: An Empirical Study in Vietnam. Mathematics, 10(10), 1691. https://doi.org/10.3390/math10101691