Identifying and Assessing Vulnerable Micro-Enterprises in Lithuania
Abstract
:1. Introduction
2. Literature Review
3. Research Methodology
3.1. Objective of Research Methodology
3.2. Subject and Sample Size
3.3. Data and Period
3.4. Vulnerability Factors
3.5. Vulnerability Indicators
3.6. Impacts
4. Results
4.1. Fuel Expenditure and Share of Fuel Expenditure in Total Operating Costs
4.2. Number of Vulnerable Micro-Enterprises
4.2.1. Number of Micro-Enterprises with High Fuel Expenditure
4.2.2. Number of Micro-Enterprises with a High Share of Fuel Expenditure in Total Operating Costs
4.2.3. The Most Vulnerable Lithuanian Municipalities
4.2.4. Number of Low-Profit and Low-Solvency Micro-Enterprises
4.3. Developments in Economic Outcome of Vulnerable Micro-Enterprises
4.3.1. Value Added
4.3.2. Number of Employees
5. Discussion
5.1. Practical Implications
5.2. Theoretical Implications
- –
- A share of fuel cost in total operating costs higher than the industry’s 2M. When the industry’s 2M is higher than the national 2M, then the indicator is calculated from the national 2M;
- –
- Net profitability lower than the industry’s 2M. When the industry’s 2M is lower than the national 2M, then the indicator is calculated from the national 2M;
- –
- The equity-to-liabilities ratio of the ME is 0.5 or less;
- –
- Fuel intensity is higher than the industry’s 2M. When the industry’s 2M is higher than the national 2M, then the indicator is calculated from the national 2M.
5.3. Comparison of Research Results with Global Findings
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Group | Energy Performance Class | Total | Total, % | |||||
---|---|---|---|---|---|---|---|---|
≤D | C | B | A | A+ | A++ | |||
1. Residential buildings | 342,160 | 176,116 | 43,305 | 8077 | 837 | 19 | 570,513 | 86 |
1.1. Private houses | 311,020 | 170,969 | 38,912 | 7814 | 765 | 12 | 529,492 | 80 |
1.2. Multi-apartment buildings | 31,140 | 5146 | 4393 | 263 | 72 | 7 | 41,021 | 6 |
2. Non-residential buildings | 78,175 | 6059 | 5689 | 713 | 125 | 9 | 90,770 | 14 |
2.1. Industrial buildings | 44,552 | 2091 | 1920 | 178 | 29 | 5 | 48,775 | 7 |
2.2. Administrative buildings | 9085 | 689 | 505 | 81 | 17 | 0 | 10,377 | 2 |
Educational buildings | 3743 | 634 | 322 | 11 | 5 | 0 | 4715 | 0.7 |
Trading buildings | 7129 | 526 | 865 | 103 | 35 | 2 | 8760 | 1.3 |
Health care buildings | 1422 | 189 | 221 | 4 | 2 | 1 | 1839 | 0.3 |
Cultural facilities | 4474 | 1066 | 1095 | 246 | 18 | 1 | 6900 | 1.0 |
Accommodation buildings | 2029 | 155 | 147 | 7 | 3 | 0 | 2341 | 0.4 |
Service facilities | 4121 | 411 | 438 | 78 | 11 | 0 | 5059 | 0.8 |
Other buildings | 1620 | 198 | 176 | 5 | 5 | 0 | 2004 | 0.3 |
Vulnerability Factor | Vulnerability Indicator | Indicator Restricted for Sharing: Ministry’s Set of Indicators | Indicator Not Restricted for Sharing: Researchers’ Set of Indicators |
---|---|---|---|
Impact of ETS2 on prices |
| √ | |
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Limited access to capital |
| √ | |
Financial capacity |
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Market structure and competitiveness |
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Regional development | The aforementioned indicators for Lithuanian regions. | √ | |
Availability, accessibility, and affordability of public transport or transport alternatives | The vulnerability factors are covered in detail by the category “vulnerable households”; therefore, they are not considered as part of the category of “vulnerable MEs”. No primary and precise data on transport in MEs are available. | N/A | N/A |
Mixed vulnerability indicator |
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| √ |
Economic Activity | Median of Fuel Expenditure, EUR | Median of Fuel Expenditure in Total Operating Costs, % | ||||
---|---|---|---|---|---|---|
2010 | 2015 | 2023 | 2010 | 2015 | 2023 | |
Agriculture, forestry, and fishing | 4209 | 4011 | 9431 | 8.93 | 9.53 | 12.73 |
Manufacturing | 201 | 328 | 416 | 0.53 | 0.72 | 0.67 |
Electricity, gas, steam, and air conditioning supply | 10,065 | 781 | 892 | 22.77 | 3.96 | 2.70 |
Water supply; sewerage, waste management, and remediation activities | 2052 | 1846 | 3662 | 2.96 | 3.64 | 4.21 |
Construction | 700 | 705 | 1877 | 1.87 | 1.43 | 3.05 |
Wholesale and retail trade | 1010 | 1307 | 1084 | 1.53 | 2.48 | 0.62 |
Transportation and storage | 4760 | 5926 | 17,216 | 12.93 | 17.17 | 24.96 |
Accommodation and food service activities | 205 | 370 | 1022 | 0.71 | 0.98 | 1.18 |
Publishing, broadcasting, and content production and distribution activities | 113 | 134 | 462 | 0.39 | 0.52 | 0.77 |
Financial and insurance activities | 176 | 202 | 1348 | 0.56 | 0.62 | 1.52 |
Real estate activities | 203 | 259 | 863 | 0.86 | 1.22 | 2.32 |
Professional, scientific, and technical activities | 310 | 325 | 1932 | 1.15 | 1.2 | 3.43 |
Public administration and defense; compulsory social security | 403 | 860 | 828 | 2,1 | 4.48 | 4.20 |
Education | 159 | 211 | 640 | 0.73 | 0.75 | 1.55 |
Human health and social work activities | 188 | 224 | 916 | 1.07 | 1.16 | 1.82 |
Arts, sports, and recreation | 254 | 396 | 717 | 1.25 | 1.85 | 2.62 |
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Bobinaite, V.; Neniskis, E.; Konstantinaviciute, I.; Tarvydas, D. Identifying and Assessing Vulnerable Micro-Enterprises in Lithuania. Sustainability 2025, 17, 5405. https://doi.org/10.3390/su17125405
Bobinaite V, Neniskis E, Konstantinaviciute I, Tarvydas D. Identifying and Assessing Vulnerable Micro-Enterprises in Lithuania. Sustainability. 2025; 17(12):5405. https://doi.org/10.3390/su17125405
Chicago/Turabian StyleBobinaite, Viktorija, Eimantas Neniskis, Inga Konstantinaviciute, and Dalius Tarvydas. 2025. "Identifying and Assessing Vulnerable Micro-Enterprises in Lithuania" Sustainability 17, no. 12: 5405. https://doi.org/10.3390/su17125405
APA StyleBobinaite, V., Neniskis, E., Konstantinaviciute, I., & Tarvydas, D. (2025). Identifying and Assessing Vulnerable Micro-Enterprises in Lithuania. Sustainability, 17(12), 5405. https://doi.org/10.3390/su17125405