Journal of Sustainable Tourism and Entrepreneurship (JoSTE) ISSN: 2714-6480.
Vol 7.
No 1, 2025, 17-34 https://doi.
org/10.
35912/joste.
Government support for revitalizing performance of tourism MSMEs: A resource advantage theory Prabodya Munasingha1.
Ruwan Ranasinghe2.
Dinushi Ranathunga3.
Shashika Pattiyagedara4 Uva Wellassa University of Sri Lanka.
Sri Lanka1,2,3,4 prabodya555@gmail.
com1, ruwan@uwu.
lk2 , dinunawanji@gmail.
com3, shashika.
p@uwu.
Abstract Purpose: The study aims to investigate the impact of Government Support on revitalizing the Environmental and Financial Performance of Tourism MSMEs with the Resource Advantage theory perspective.
Methodology/approach: Data were collected from 384 TMSMEs through a snowball sampling technique using a self-administered structured questionnaire.
Three multiple linear regression models were constructed to investigate the impact of Government Support as an independent variable on performance as a dependent variable, and the Statistical Package for Social Sciences (SPSS) was employed to Article History analyze the data.
Received on 27 November 2024 1 Revision on 13 December 2024 Results/findings: The results indicate that both Government 2nd Revision on 18 December 2024 Financial (GFS) and Non-Financial Support (GNFS) significantly 3rd Revision on 9 January 2025 influence the financial and environmental performance of TMSMEs 4th Revision on 19 February 2025 at a 5% level.
Moreover.
GFS shows a slightly high impact on Accepted on 25 February 2025 financial performance GNFS, although both supports show a significant impact on revitalizing the performance of businesses in emerging economies.
Conclusion: The study concludes that government financial and nonfinancial support are critical determinants of tourism MSME Strengthened support not only enhances financial viability but also fosters environmental accountability, aligning with the principles of sustainable development.
Limitations: The study focused on TMSMEs in selected emerging tourism regions of Sri Lanka, a least-developed economy, using a quantitative approach.
Business performance was assessed through subjective measures due to owners' reluctance to disclose financial Contribution: The study contributes to R-A theory by highlighting how government support strengthens firms' resource capabilities, leading to superior performance.
It also facilitates policymakers, tourism entrepreneurs, and regulators in fostering regional development by revitalizing TMSMEs, reducing socio-economic disparities, and increasing per capita income.
Keywords: Environmental Performance.
Financial Performance.
Government Support.
R-A Theory.
Tourism MSMEs How to Cite: Munashinga.
Ranasinghe.
Ranathunga.
, &
Pattiyagedara.
Government support for revitalizing performance of tourism MSMEs: A resource advantage theory Journal of Sustainable Tourism and Entrepreneurship, 7.
, 17-34.
Introduction Tourism is a vital industry that significantly impacts social, environmental, and economic development In today's world, economic growth and job opportunities in tourism have extended beyond traditional boundaries.
Tourism is a crucial source of foreign exchange earnings for many developing nations and contributes to economic progress.
Therefore, tourism plays a pivotal role in generating revenue, enhancing quality of life, and fostering sustainable regional development at both macro and micro levels (Rajabi & Ghalehteimouri, 2.
Tourism plays a pivotal role in developing economies by elevating socioeconomic standards such as unemployment, inflation, and income deviation.
Tourism in Sri Lanka ranks as the third-largest foreign income generator, contributing 4.
9% to the overall GDP, according to the Sri Lanka Tourism Development Authority (SLTDA, 2.
However, recent adversities, such as the Easter Sunday terrorist attack in 2019, the COVID-19 pandemic, and economic crises, have led to its collapse and affected the entire economy.
Therefore, the government focuses on rejuvenating the performance of tourism service providers, considering it an option for a sustainable economy.
Micro Small and Medium Enterprises (MSME.
have proven to be a vital sector for emerging economies, offering potential solutions to poverty, unemployment, income disparities, and economic growth.
According to the census and statistics .
MSMEs in different industries contribute significantly to GDP .
%) and employment .
%).
SLTDA .
categorizes total tourism employment into direct and indirect, where indirect represents ancillary services such as handicraft trade, retail shops, gem and jewelry shops, and liquor TMSMEs are identified as crucial parties in the industry as they are more responsive to the needs of tourists than macro-level service providers, where the spending directly flows to the local community, where a multiplier effect can be witnessed.
Table 1 elaborates on the growth of tourism employment from 2017 to 2022, and indirect employment represents the TMSMEs sector.
Table 1.
Employment in Tourism
Year
Source: Annual Report of SLTDA,2022 Direct
156,369
169,003
173,592
175,990
Indirect (Estimate.
202,846 219,484 229,015 171,767 Enterprises are categorized as Micro.
Small.
Medium, or Large based on two primary dimensions: the number of employees and annual turnover.
In Sri Lanka.
MSMEs are defined as businesses with fewer than 300 employees and annual turnover of less than LKR 750 million (NPR Deyshappriya & Abeyweera, 2.
Table 2.
Classification of Service Sector MSMEs in Sri Lanka Company Category Number of Employees Micro Small Medium Source: Census and Statistics.
Sri Lanka .
3/2.
Annual Turnover (Millio.
O LKR 15
O LKR 16-250
O LKR 251-750
Sri Lanka, with its favorable geography and climate, presents an ideal environment for tourism development.
However, this region also faces considerable challenges, including high poverty, a lack of resources and opportunities, and inadequate government support.
Rejuvenating MSMEs is a critical strategy for addressing the socio-economic standards within the community.
Certain notable emerging tourism regions in Sri Lanka represent a significant percentage of the country's annual tourist arrivals (Urban Development Authorit.
Moreover, the occupancy rate is higher in Badulla District by 17.
2% compared to Colombo District .
(SLTDA, 2.
Thus, this study investigates emerging tourism regions in Sri Lanka based on evidence from the Uva Provincial Tourism Ministry.
The performance of MSMEs in the tourism sector lags behind market competitiveness due to financial constraints, a lack of managerial skills, limited access to market information, and insufficient awareness of technological advancements (Jeewanthia & Bhavan, 2.
Research indicates that seven out of ten MSMEs in developing economies struggle to secure market catastrophes (Xiang & Worthington, 2.
Recognizing 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 this, the government provides Government Support (GS) in the form of Government Financial Support (GFS) and Government Non-Financial Support (GNFS) to support them.
Aziz and Sharifuddin .
Nakku.
Agbola.
Miles, and Mahmood .
and researchers have identified a relationship between government support and the performance of MSMEs in the context of manufacturing and agriculture.
However, limited attention has been paid to tourism-related MSMEs in developing Xiang and Worthington .
found that government financial incentives positively impact the performance of MSMEs and firms aided by GFS to obtain GNFS in the future.
Moreover.
Nakku et al.
studied the financial and environmental performance through financial and non-financial government support and explored that government support has a significant impact on the financial and environmental performance of MSMEs.
MSMEs face difficulties in implementing environmental initiatives due to a lack of information, knowledge, and finance to perform sustainably, although there is growing interest in environmental accountability.
According to uvarede.
lk/ .
, in the Uva Province of Sri Lanka, the active employment is 691,696, representing half of the population.
There is a 5.
6% unemployment rate in the Uva Province, which is the second highest unemployment rate in Sri Lanka, after the Central Province .
7%), and it has contributed to 9.
9% of the national poverty of Sri Lanka (Uva Provincial Council Websit.
However, the shutdown rate of TMSMEs is high in Sri Lanka, as enterprises are unable to adhere to market The efficacy of GS on the performance of MSMEs related to the tourism industry has rarely been discussed in the context of a developing economy.
Thus, this study employs the Resource Advantage (R-A) theory to investigate how GS, as an external factor, influences the enhancement of EP and FP of TMSMEs to address the following objectives.
A To identify the impact of GFS and GNFS on rejuvenating the performance of TMSMEs.
A To investigate the relationship between GFS and GNFS in rejuvenating the performance of TMSMEs.
Literature review 1 Resource Advantage Theory The R-A theory explains competitive advantage and firmsAo superior performance in terms of the availability of resources.
The capital assets of MSMEs significantly affect firm performance and are acquired through internal or external methods (NP Deyshappriya & Nawarathna, 2.
Resources are the inputs of a business to ensure high performance through competitive advantage and can be categorized as tangible and intangible.
Resources encompass financial, human, physical, organizational, legal, informational, and relational resources, which are heterogeneous to industry.
Researchers such as Grimmer.
Miles, and Grimmer .
have examined the relationship between SMEs and development using R-A theory and elaborated external factors that provide conditions for SMEs to acquire the necessary resources to revitalize the superior performance of the firm.
Previous literature contributes to the R-A theory based on the performance of SMEs in the manufacturing and retail industries regarding resources, but limited studies have been conducted on the service industry from the perspective of GS as an external resource to enhance firmsAo superior 2 MSMEs in Sri Lanka Micro, small, and medium-scale tourism entrepreneurship in emerging markets holds significant potential for economic growth and social development (Yuliastuti et al.
, 2.
MSMEs are crucial for Sri LankaAos economy, as they represent 90% of the total enterprises, and tourism represents more than 80% of the total tourism enterprises.
MSMEs collectively contribute significantly to the nation's economy, accounting for 52% of its GDP and providing employment to 45% of its workforce (NP Deyshappriya & Nawarathna.
Moreover.
MSMEs act as catalysts for fostering entrepreneurship, improving living standards, supporting community development, and reducing unemployment (Ratnayake.
Menike, & Perera, 2.
The classification of MSMEs in Sri Lanka is based on the number of employees and annual turnover of the business (DCS, 2.
According to a survey of enterprises in Sri Lanka, the growth rate of these SMEs in Sri Lanka is relatively low at 2.
9%, compared to the global average of 5.
2% (Jeewanthia & Bhavan, 2.
In Sri Lanka, the number of SMEs is high in commercial cities such as Colombo.
Kandy, and Gampaha, where the accessibility of resources is prominent.
Although the SME count is high, the survival rate of SMEs is comparatively low due to limited resources (Jeewanthia & Bhavan, 2.
Therefore, this study focuses 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 on TMSMEs in tourism regions of Sri Lanka with limited resource accessibility, which facilitates community comfort and regional development.
3 TMSMEs: An Engine of Growth As an important economic activity in most regions, tourism has significant indirect effects on the economy (Pattiyagedara & Ranasinghe, 2.
Many studies have reported the significance of tourism for the development of a countryAos economy, regardless of the level of development that the country beholds.
TMSMEs can be travel agents, handicraft and souvenir shops, retailers, homestays, guest houses, and food and beverage outlets operating on a micro-scale (Seow.
Choong, & Ramayah, 2.
Many of these TMSMEs are considered informal tourism service providers, as a significant portion of them are not registered with the Sri Lanka Tourism Development Authority (SLTDA, 2.
In the context of developing countries.
MSMEs play a key role in delivering tourism services, and TMSMEs critically influence how tourists perceive destinations and the image of the destination (NP Deyshappriya & Nawarathna, 2.
TMSMEs are an engine of growth.
they stimulate regional growth and community livelihood, reduce unemployment, improve market effectiveness, and introduce innovation-based customer needs (Kaur and Sharma 2.
(Seow et al.
, 2.
Furthermore.
MSMEs promote destination image (Henrekson & Johansson, 2.
TMSMEs are more responsive to demand than large businesses because of their level of adaptability, flexibility, and locational advantages (Seow et al.
, 2.
TMSMEs facilitate and encourage marginalized groups in the economy, such as women, migrants, and the disabled, who are economically inactive (Rao.
Verma.
Rao, & Joshi, 2.
4 TMSMEs: Barriers and Challenges TMSMEs face various barriers and challenges.
According to Salubre.
Bahalla, and Almagro .
COVID-19 has severely impacted global economies and health, leading to a supply demand imbalance that has slowed economies and affected all sectors, including micro-small and medium-sized enterprises (SME.
Most services in the Badulla tourism Development Secretariat divisions are provided by TMSMEs in the accommodation, food and beverage, and retail sectors rather than large enterprises.
Key challenges faced by MSMEs such as limited access to credit, inadequate managerial skills, low awareness of sustainable initiatives, lack of innovation, and technological implementation, all of which affect their performance (Amanah.
Sena.
Suhendra.
Yatim, & Zaki, 2.
Government bureaucracy, a shortage of skilled workers, difficulty in obtaining financing, and limited access to technology are additional barriers identified by Jauriyah.
Sarkawi.
Jaaffar, and Abdul Rahim .
Lack of access to finance remains a primary constraint for TMSMEs, especially following long-term industry shutdowns.
Insufficient awareness and knowledge present another significant challenge for SMEs, hindering their ability to engage in environmental initiatives and improve their environmental performance (Anwar & Li, 2021.
Clement & Hansen, 2.
In contrast to developed countries, where resources are more evenly distributed among SMEs, developing countries face common challenges of resource inequality and limited resource access (Xiang & Worthington, 2.
5 Government Support (GS) GS refers to different kinds of support given by the government to assist, promote, and rejuvenate a firmAos performance, enhance the level of capabilities, diversify, create new firms, and ensure effective and efficient business growth (Arshad.
Ahmad.
Ali.
Khan, & Arshad, 2.
The GS is classified into two main categories: financial and non-financial support.
GS is an external resource that helps achieve and sustain MSMEs' performance in different industries, which is determined through the resource advantage of the firm (Hiong.
Ferdinand, & Listiana, 2.
Alkahtani.
Nordin, and Khan .
and Aziz and Sharifuddin .
found that financial and tax incentives significantly impact Return on Investment(ROI).
Profitability, and Return on Assets(ROA), which can alleviate the financial inability of the firm (Aziz & Sharifuddin, 2.
The environmental performance of a firm is significantly affected by GFS (Clement & Hansen, 2.
GNFS
can be measured by training programs or workshops, trade fairs.
Business Development Support (BDS), and technical support organized by the government to assist MSMEs with informational and technology updates that enable high business performance (Amanah et al.
, 2024.
Nakku et al.
, 2.
GNFS has a significant impact on the performance of MSMEs in emerging countries (Alkahtani et al.
, 2020.
Anwar & Li, 2.
2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 6 MSMEs Performance According to Vij and Bedi .
, business performance is defined as the overall ability of a firm to satisfy the interests of stakeholders in terms of financial or non-financial measures.
In measuring profitability, indicators like Return on Investment(ROI).
Return on Assets(ROA) and Return on Equity(ROE) and indicators like Market share growth.
Asset growth.
Net revenue growth, and Net revenue income growth are used to measure the growth performance (Hiong et al.
, 2020.
Santos & Brito, 2.
Environmental initiatives offer businesses opportunities to enhance eco-competitiveness, including cost reduction, resource efficiency, environmental protection, sustainable product delivery, and overall growth (Clement & Hansen.
Environmental pollution regulations encourage firms to adjust their operations to improve environmental performance (Nulkar, 2.
This study employed variables used by Martinez-Conesa.
SotoAcosta, and Palacios-Manzano .
and Santos and Brito .
to measure EP of the TMSMEs.
7 Conceptual Framework and Hypothesis Development 1 GFS on Financial Performance of TMSMEs In developing countries, limited access to finance is one of the main constraints on MSMEs in ensuring superior performance (Jeewanthia & Bhavan, 2.
However, as the tourism industry is subject to seasonal demand, during off-peak periods, businesses reframe their resources and capacities to cater to the upcoming seasonal demand (Karunarathne.
Ranasinghe.
Sammani, & Perera, 2.
Therefore, to reframe capacities, capabilities, and innovation, the GS is highly appreciated by small-scale tourism enterprises (Cong & Thu.
More than ever, the GFS is pivotal for TMSMEs to rejuvenate performance due to industry fluctuations (Branchet.
Augier.
Boissin, & Quere, 2.
High taxes and financial burdens tend to degrade SMEs' development.
Hence.
Picas.
Reis.
Pinto, and Abrantes .
identified that tax incentives directly impact the profitability and ROA of MSMEs.
Moreover.
MSMEs that obtained GFS experienced high performance compared to firms without government financial aid (Alkahtani et al.
, 2.
Clement and Hansen .
mentioned that SMEs' performance significantly depends on external aids to expand their operations to the international level.
Aziz and Sharifuddin .
have identified that GFS significantly impacts of market performance of SMEs in the manufacturing industry.
According to Grimmer et al.
SMEs with financial support positively improve performance and SMEsAo long-term survival and growth from the perspective of R-A theory.
Hence, the present study posits the following hypothesis from past H1: There is a relationship between GFS and Profitability of TMSMEs H2: There is a relationship between GFS and Growth of TMSMEs 2 GFS on Environmental Performance of TMSMEs Businesses, regardless of their size, intend to achieve a competitive advantage.
The governments of Australia.
Japan, and the United Kingdom have started sponsoring initiatives that foster sustainable business output (Anwar & Li, 2.
There is a growing interest in environmental accountability, where environmental performance (EP) is treated equally as financial performance (Gylgeci.
Gligor.
Tatoglu, & Arda, 2.
The Chinese have determined that SMEs' weak environmental performance is mostly caused by three factors: insufficient incentives and policies, negligence of environmental responsibility, and high cost of initiation.
Laari.
Tyyli, and Ojala .
emphasize that neglecting EP negatively affects the overall competitiveness of firms, as it provides new opportunities for SMEs to broaden their business.
Anwar and Li .
emphasize that GFS has a high influence on environmental performance.
In particular, the government significantly grants and aids SMEs in initiating environmental practices, creating a win-win situation for both parties (Clement & Hansen, 2.
Tourism also negatively impacts the environment at the destination, and government assistance in terms of finance is critical for TMSMEs to initiate relevant practices in their business.
TMSMEs are considered an element in the sustainable development of however.
GFS on the EP of TMSMES has rarely been discussed in previous studies.
Therefore, the impact of this relationship remains unclear.
H3: There is a relationship between GFS and EP of TMSMEs 3 GNFS on Financial Performance of TMSMEs During the crises, governments provided diverse support programs related to technical assistance, managerial knowledge, and financial skills to strengthen the MSMEs' performance (Mahmoud.
Mahmoud.
Abubakar.
Garba, & Daneji, 2.
Proprietors of TMSMEs are required to participate in business training 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 programs, awareness programs, and other non-monetary assistance provided by the government, which helps them improve their knowledge of potential markets, competition, globalization, and integration to boost their financial performance by capturing new opportunities (Choi.
Lee, & Lee, 2.
GNFS, such as technology support.
BDSs, and informational assistance, help achieve innovative capabilities and significantly contribute to a firmAos performance (Alkahtani et al.
, 2.
A firm that acquires GFS can gain GNFS in the future, which supports MSMEs in enhancing financial performance by optimizing innovations and entrepreneurial orientations.
H4: There is a relationship between GNFS and Profitability of TMSMEs H5: There is a relationship between GNFS and Growth of TMSMEs 4 GNFS on Environmental Performance of TMSMEs GS is considered an external factor that provides conditions for MSMEs to perform well in the market (Grimmer et al.
, 2.
GNFS includes training programs.
BDSs, and technology support, which help nurture awareness of environmental accountability and its benefits (Martinez-Conesa et al.
, 2.
According to Anwar and Li .
GNMAs have significantly encouraged MSMEs to contribute to environmental TMSMEs are responsible for creating destination images by implementing environmental practices.
However, insufficient support from the government has led to a decline in sustainable and environmental performance (Zhang.
Khan.
Lee, & Salik, 2.
In recent years, emerging economies have established environmental protection policies for businesses.
EP is measured through renewable energy consumption, eco-packaging, water consumption, and environment cleaning.
(Anwar & Li, 2.
Moreover.
Sah.
Chaudhary.
Naik.
Nidhan, and Agrawal .
emphasize that GNMAs such as training and awareness workshops conducted based on environmental practices significantly influence EP.
MSMEs with government financial and non-financial aid can cease operational costs to witness sustainable competitiveness (Anwar & Li, 2.
H6: There is a relationship between GNFS and EP of TMSMEs Government Support FirmAos Performance Financial Performance Government Financial Support Profitability Growth Government NonFinancial Support Environmental Performance Source: Developed by the Researcher .
Research methodology 1 Sample & Data Collection The participants in this study were owners of TMSMEs in Sri Lanka.
The majority of decision-making on performance is made by the proprietor of the business.
Apart from that, ancillary services like tourist shops, handicraft shops, gem and jewelry, and all other informal businesses in tourism are taken under the MSMEs According to statistics, around 80% is represented by MSMEs.
Therefore, the study employed 384 TMSMEs representing emerging tourism regions of the Badulla district based on the classification of the 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 Uva Tourism Ministry of Sri Lanka.
Data were collected through the snowball sampling technique as statistics of tourism-related MSMEs are absent in government institutions.
Thus, concerning specific traits as tourism service providers.
TMSMEs in each selected tourism region are taken into the sample to represent the universe of the research study.
Primary data were collected through a self-administered questionnaire, and the objectives of the study were answered using the Five Point Likert Scale, which ranges from strongly agree .
to strongly disagree .
Moreover, the study used subjective measures from the literature by Amanah et al.
Anwar and Li .
Santos and Brito .
to measure dependent and independent variables.
2 Data Analysis Method The study adopted a quantitative approach, and data analysis was performed using the Statistical Package for Social Sciences (SPSS).
Further, the study used data analysis methods such as Descriptive Statistics.
Correlation Coefficient, and Regression Analysis to analyze the data.
The correlation coefficient was used to determine the relationship between GS and the Performance of TMSMEs.
Regression analysis was implemented to measure the impact of GS on the EP and FP of TMSMEs.
Descriptive statistics were used to understand the demographic details of the study population.
Furthermore, the study constructed three multiple linear regression models to emphasize the relationship between GS and the Performance of TMSMEs.
The overall significance of the variables of the regression equation was measured by T-test.
P-value on t, and the statistical significance level was measured using a 05 significant level that determines the confidence percentage of the variables.
In addition, the AuGoodness of FitAy was used to check the overall significance of the model by analyzing the value of the coefficient of determination R2 and the F-test.
Results and discussion 1 Cronbach's Alpha Reliability Analysis and Descriptive Statistics CronbachAos alpha is a measure used to evaluate the reliability or internal consistency of a set of scale or test items used to measure the independent and dependent variables of the study.
Hence, the following table illustrates that there is reliability and internal consistency of a set of items used for the study as the CronbachAos Alpha value is greater than 0.
Table 3.
Employment in Tourism Variable CronbachAos Alpha Items Government Monetary Support Government Non-Monetary Support Profitability Growth Performance Environmental Performance Source: SPSS output from field information According to Table 4, the mean values lie in the range of 3.
5 OX< 5, which indicates that the independent and dependent variables of the study can be identified as almost agreed variables.
Furthermore, the dependent variables, profitability, growth performance, and environmental performance, have mean values 81, 3.
82, and 3.
85, respectively.
The independent variables.
GFS and GNFS, had mean values of 3.
70, respectively.
The coefficient of variance implies the opinions of the current study on the impact of government assistance on tourism MSMEs performance.
The variance values of the main variables were less than 30%, indicating that the respondents of the sample had the same opinion about the impact of GS on the performance of TMSMEs.
2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 The Standard Deviation is used to test the dispersion of the data about the mean value.
A high SD means that values are generally far away from the mean, and a low SD implies values clustered closer to the mean The SD of all the main variables shows a low value, as shown in Table 4, which implies that the values are clustered closer to the mean value of the variables.
Furthermore, the dependent variables showed a high SD value compared to the independent variables.
Table 4.
Descriptive Analysis Results Variable Mean Variance Standard Deviation (SD) GFS Skewness Kurtosis Std.
Error Skewness Std.
Error of Kurtosis GNFS Source: SPSS output from field information To test the normality of the data, the values of skewness, kurtosis, and their standard errors were used.
Skewness values between -1 and 1 are considered approximately normally distributed.
Therefore, according to Table 4, the coefficient of skewness of all the variables belongs to the normally skewed category, where values are greater than -0.
5 and less than 0.
As the absolute value of skewness is less than three times the standard error of skewness, the data are normally distributed.
According to the statistical output of this study, the standard error of skewness was 205, and 3* 0.
205 = 0.
Considering this result, the absolute value of skewness is less than 0.
Therefore, all variables were normally distributed.
If the absolute value of kurtosis is less than three times the standard error of kurtosis, the data are normally According to the calculation, three times the error of kurtosis 3*0.
407= 1.
221, and the absolute value of kurtosis is less than 1.
Hence, all variables were normally distributed.
2 RespondentAos Profile A demographic analysis was conducted to understand the dimensions or dynamics of the collected data.
this study, distinct characteristics such as DS division distribution, age distribution, years of business operation, previous work experience in the tourism industry, nature of the business, and education level of tourism-related MSMEs in the Badulla district are illustrated in the table below.
Table 5.
Descriptive Analysis Results Characteristics Percentage Tourism Regions Badulla Welimada Haputale Ella Bandarawela Mahiyanganaya Age 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 Above 56 Gender Male Female Year of Business Operation 9 Years & above Previous Tourism Industry Experience Yes Registration of Business District Secretariat or Municipal Council SLTDA/Both Nature of Business Accommodation Travel & Excursion Food & Beverage Retail Service & other Number of Employees Education Qualification No formal education Ordinary level Advanced level Graduate Source: SPSS output from field information As shown in Table 5, the Ella.
Haputale.
Badulla, and Bandarawela tourism regions represent the highest concentration of TMSMEs, and the least representation is shown in Welimada and Mahiyanganaya at 10.
The results show that areas with high concentrations of TMSMEs have intrinsically and extrinsically been supported to enhance their contribution to the tourism industry compared to areas with low concentrations.
The highest percentage .
6 %) of business owners were in the 36-45 age category, which is the prime age of workers in the Badulla District.
In contrast, the age category of 19-25 involvement in tourism, which has led to high young unemployment in the Badulla District.
Off the owners of TMSMEs, 86.
4% are male and the remaining 13.
6% are female business owners, which emphasizes that women's involvement is significantly low and the tourism industry is male-dominated.
Furthermore, the majority of TMSMEs' operation are 3-5 years which highlights that most TMSMEs are in the introductory stage of their business or developing stage, where GS is crucial in sustaining the market during external shocks.
Moreover, 80% of business owners do not have industry experience when starting their businesses.
Only 20% of the sample had prior experience in the tourism industry.
There were three categories: SLTDA registered, registered in the Divisional Secretariat or Municipal Council, or both.
However, only 11.
4% of TMSMEs are registered in the SLTDA, which may result in a lack of support from the government on TMSMEs since statistical data related to the MSMEs category is unavailable due to the low ability to track businesses and aid them in need.
The majority of TMSMEs .
7 %) belong to the accommodation sector, and the next highest is the food and beverage sector category MSMEs .
1 %).
Retail services and other categories showed comparatively low percentages of 25.
7% and 6.
4 %, respectively, with the travel and excursion sector having the lowest 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 Based on employee count, most of the businesses in the Badulla district related to tourism are microenterprises, denoting a percentage of 74.
3%, and small and medium category enterprises represent 25% and 7%, respectively.
The majority of owners have at least one formal educational qualification from the mentioned categories, which reflects the knowledge background of the respondents.
3 Multiple Regression Analysis This study constructed three .
multiple regression models to test the impact of GFS and GNFS on the performance of TMSMEs, and the basic four assumptions were met before running the regression analysis.
The first regression model explains the impact of GS on the Profitability Performance of TMSMEs.
1 Regression Model 1 Table 6.
Model Summary of Multiple Regression Analysis Model R Square Adjusted R Square Std.
Error of the Estimate Source: SPSS output from field information GFS and GNFS explained 94.
6% of the variance in the profitability performance of TMSMEs and defined 1% of the unexplained variation in this model.
The variance is strong and significant, as the variance of 946 is greater than 0.
The Adjusted R2 represents the modification of R2, which is adjusted for the number of explanatory variables in the model.
Therefore, the adjusted R2 .
6%) was not significantly different from the R2 value .
5%).
This indicates that the regression equation was fitted to the study sample.
Furthermore, the standard error of the estimate is 0.
05925, which is less than the mean value of the dependent variable .
The following represents the variance of the model by presenting the sum of squares, degrees of freedom.
F-value, and P-value.
Table 6.
Analysis of Variance for Multiple Regression Analysis Model Sum of Squares Mean Square Regression Residual Total Source: SPSS output from field information Sig.
The total sum of squares is 6.
649, and 5.
950 of variance can be explained by the regression and the 0.
700 of dependent variable is explained by the residual.
Hence, the null hypothesis is rejected, as the model is wellfitted and significant at the 1% level.
Furthermore, the model is statistically significant in explaining the profitability performance of TMSMEs.
Table 6.
Multiple Regression Analysis Ae Model 1
Predictor
Coefficients Standard Error
Constant
GFS
GNFS
Source: SPSS output from field information t-Value P-Value According to Table 6.
2, multiple linear regression model 1 for this study can be expressed as follows:
yaayayayayayayaoyauyayauyayaya_yaa = yu0 yu1GFS1 yu2GNFS2 u Profitability_P = 0.
555GFS1 0.
553 GNFS2 u 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 The t-value of coefficients is greater than 2, which means the estimated coefficients are statistically significant, and the P-value of coefficients is significant at a 5% level, which depicts 95% confidence in estimated coefficients.
Furthermore, 29.
2% of profitability can be observed when GS is zero.
The changes in profitability are approximately 50% due to a one-unit change in GFS and GNFS.
2 Regression Model 2 This multiple regression model shows the impact of different GS on the Growth Performance of TMSMEs.
Table 7.
Model Summary of Multiple Regression Analysis Model R Square Adjusted R Square Source: SPSS output from field information Std.
Error of the Estimate As shown in Table 7.
GFS and GNFS explained 94% of the variance in the growth performance of TMSMEs and defined 5.
6% of the unexplained variation in this model.
The explained variance of 0.
940 is greater than Hence, the variance was strong and significant.
The Adjusted R2 was adjusted for the number of explanatory variables in the model.
The regression equation was fitted to the sample as the adjusted R2 .
2%) had no extensive difference compared to the R2 value .
4%).
Furthermore, the standard error of the estimate is 0.
06328, which is less than the mean value of the dependent variable .
Table 7.
Analysis of Variance for Multiple Regression Analysis Model Sum of Squares Mean Square Regression Residual Total Source: SPSS output from field information Sig.
The regression model explains 5.
902 of the variance model and the 0.
665 of dependent variable is explained by the residual.
The null hypothesis is rejected because the overall model is statistically significant in predicting the growth of TMSMEs.
Table 7.
Multiple Regression Analysis Ae Model 2
Predictor
Coefficients Standard Error
t-Value P-Value Constant
GFS
GNFS
Source: SPSS output from field information According to Table 7.
2, multiple linear regression model 2 for this study is expressed as follows:
yaIyayayayaya_yaa = yu0 yu1GFS1 yu2GNFS2 u Growth_P = 0.
591GFS1 0.
515 GNFS2 u The t-value of coefficients is greater than 2, which means the estimated coefficients are statistically significant, and the P-value of coefficients is significant at a 5% level, which depicts 95% confidence in estimated coefficients.
Furthermore, growth is 0.
282 when the GS is zero.
The changes in the growth performance were 0.
591 or 0.
515 due to a one-unit change in GFS and GNFS.
2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 3 Regression Model 3 This multiple regression model shows the impact of GFS and GNFS on the Environmental Performance of TMSMEs.
Table 8.
Model Summary of Multiple Regression Analysis Model R Square Adjusted R Square Source: SPSS output from field information Std.
Error of the Estimate According to Table 8.
GFS and GNFS explained 91.
9% of the variance in the environmental performance of TMSMEs and defined 8.
1% of the unexplained variation in this model.
The explained variance of 0.
was greater than 0.
Hence, the variance was strong and significant.
The Adjusted R2 represents the modification of R2, which is adjusted for the number of explanatory variables in the model.
Therefore, the adjusted R2 .
2%) was not significantly different from the R2 value .
4%).
This indicates that the regression equation fits the sample of the study.
Furthermore, the standard error of the estimate is 0.
0866, which is less than the mean value of the dependent variable .
Table 8.
Analysis of Variance for Multiple Regression Analysis Model Sum of Squares Mean Square Regression Residual Total Source: SPSS output from field information Sig.
The regression explains 5.
572 of the variance, and the residual explains 1.
029 of the dependent variable.
Thus, the model is well-fitted and significant at the 1% level.
This means that the null hypothesis is rejected, and the overall model is statistically significant in predicting the dependent variable, environmental Table 8.
Multiple Regression Analysis Ae Model 3
Predictor
Coefficients Standard Error
t-Value P-Value Constant
GFS
GNFS
Source: SPSS output from field information According to Table 8.
2, multiple linear regression Model 3 for the study can be expressed as follows:
yaEyayayayayayayayayayayaoyau_yaa = yu0 yu1GFS1 yu2GNFS2 u Environmental_P = 0.
571GFS1 0.
460GNFS2 u According to the information in Table 8.
2, the t-value of coefficients is greater than 2, which means the estimated coefficients are statistically significant, and the P-value of coefficients is significant at the 1% level, which depicts 99% confidence in estimated coefficients.
Furthermore, the yu0 Value is 0.
044 which defines EP of TMSMEs when GS is equal to zero.
The changes in environmental performance were 0.
462 due to a one-unit change in GFS and GNFS.
4 Correlation- Coefficient Analysis PearsonAos Correlation analysis was used to examine the relationship between independent and dependent variables and to determine the acceptance of the hypothesis created for the study.
Hence, this study used 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 PearsonAos correlation to compute the relationship between GS and the performance of TMSMEs through bivariate correlation.
Table 9.
Overall Correlation Analysis Independent Variables Profitability Performance Pearson Correlation Sig.
-taile.
Pearson Correlation GNFS Sig.
-taile.
Correlation is significant at the 0.
01 level .
-taile.
Source: SPSS output from field information GFS Dependent Variables Growth Financial Performance Performance Environmental Performance According to the above table, the overall relationship between GFS and GNFS as independent variables on dependent variables, such as financial and environmental performance, shows a strong positive linear Financial performance as a dependent variable is measured in two dimensions: profitability and growth All hypotheses were developed separately for each.
Therefore, the probability of the association between GS and Profitability and Growth performance is 0.
000, which means the relationship is statistically significant at the 1% level.
The coefficient of correlation values of GFS and GNFS on profitability and growth are 0.
925, 0.
930, 0.
920, and 0.
919, respectively.
Therefore, the null hypothesis (H.
was rejected, and alternative hypotheses H1.
H2.
H4, and H5 were accepted.
The probability of association between GFS.
GNFS, and Environmental Performance is 0.
000, which means the relationship is statistically significant at the 1% level, and the values of the coefficient of correlation mentioned in the above table imply a strong positive relationship.
Therefore, the null hypothesis (H.
was rejected, and alternative hypotheses H3 and H6 were accepted.
5 Discussion on Data Analysis The results of CronbachAos alpha reliability analysis and the descriptive statistics indicate strong internal consistency for the measures of government support and performance of TMSMEs used in this study.
Furthermore, the descriptive statistics indicated that the data were normally distributed.
The demographic analysis reveals the characteristics of TMSMEs in the Badulla District.
With the high tourism potential.
Ella.
Haputale, and Bandarawela tourism regions show a high concentration of MSMEs who serve the tourism demand of the country.
This regional distribution implies that intrinsic and extrinsic factors in these areas foster tourism business activities Nakku et al.
Shamsuddoha.
Yunus Ali, and Oly Ndubisi .
stated that enhances business performance through external support and shared national The age distribution, predominantly in the 26-45 range, indicates an active entrepreneurial base but also highlights low participation from the 19-25 age group.
This could be due to barriers such as a lack of capital, education, or experience witnessed by small businesses in developing economies or emerging tourism destinations.
(David, 2.
The gender disparity, with 86.
4% male ownership, reflects the ongoing gender biases in the tourism industry network, as stated by Surangi .
The multiple regression analysis shows that GFS and GNFS explain 94.
6% of the variance in the profitability and growth performance of TMSMEs.
This strong relationship is supported by previous studies, such as Anwar and Li .
and Picas et al.
, which found that government incentives and support significantly enhance the profitability of tourism businesses, which ultimately contributes to financial performance by scaling up the business in the future.
The impact of GFS and GNFS suggests that both types of support, financial and advisory, are crucial, reinforcing the argument Mahmoud et al.
in business 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 success.
Overall, the GFS has a slightly higher impact on the financial performance of TMSMEs than GNFS, although both supports show a significant impact on revitalizing the financial performance of businesses in emerging economies.
The analysis indicates that GFS and GNFS account for 91.
9% of the variance in the environmental performance of TMSMEs, which is a highly concerned aspect in a novel world.
The tourism industry mostly lies in the natural resources of the economy.
therefore, every individual or commercial entity in the industry is accountable for destination security from an environmental perspective.
The significant role of financial support in environmental initiatives aligns with these findings.
Alkahtani et al.
found that limited government support constrains the adoption of environmentally sustainable practices in small businesses in Saudi Arabia.
The findings of the data analysis suggest that adequate tangible and intangible support from the government in least-developed economies is crucial for optimizing overall business performance, where the statement is proven by R-A theory from the perspective of resources aided by the external environment on performance revitalization as an advantage derived from the availability of resources.
Furthermore.
PearsonAos correlation analysis shows strong positive relationships between government support and the performance metrics of TMSMEs by synthesizing the findings of the regression analysis.
This demonstrates that both financial and non-financial support from the government positively correlate with a businessAos financial and environmental performance.
The statistical significance of these relationships supports the hypothesis that government support is a critical determinant of MSME performance in emerging tourism destinations on the least developed small islands.
Conclusion 1 Theoretical Conclusion to R-A Theory The findings of this study provide statistical proof of resource-advantage (R-A) theory in the context of resources and firmsAo financial and environmental performance.
As proven by previous research (Anwar & Li, 2021.
Aziz & Sharifuddin, 2019.
Clement & Hansen, 2003.
Xiang & Worthington, 2.
in developed and developing economies in the context of manufacturing and agricultural MSMEs, the environmental accountability of businesses shows significant growth in TMSMEs as tourists and stakeholders pay attention to green products and services, and TMSMEs unveil efforts to adopt green business strategies to enhance environmental performance as well as the financial performance of the business.
Furthermore, external factors, such as government support to enhance a firm's resource capability in tangible and intangible ways, contribute to superior performance.
The results show nearly 50% of the performance accomplished by the firm with the availability of resources received from both the government and the firm itself.
Therefore, this study contributes to R-A theory from the perspective of external support for enhancing financial and environmental performance by providing statistical evidence on the relationship between GFS.
GNFS, and superior performance of MSMEs in the tourism industry.
Finally, this study contributes to the further development of the model concerning sustainable performance, which is an emerging critical concern in the tourism activities of MSMEs, as large-scale businesses allocate resources to treat environmental performance the same as financial performance, as large-scale tourism service providers have sufficient resources to invest in green practices.
Furthermore, the findings provide theoretical knowledge on GS and the performance of businesses in the service-oriented industry, highlighting the significance of MSMEs as a primary level for national sustainable development.
2 Conclusion to Objective on Impact of GS on TMSMEs Performance Based on the results from multiple regression and Correlation Coefficient analyses.
GFS and GNFS have a significant impact on the performance of TMSMEs in terms of Profitability.
Growth performance to measure Financial Performance, and Environmental Performance, where environmental accountability is crucial for business operations.
In particular, the shift in touristsAo demand towards responsible traveling draws big attention to green business operations and their environmental performance.
TMSMEs represent the largest composition of tourist service providers in the Badulla District, which has a prestigious authentic nature and a community to promote.
Thus, different forms of governmental support through tangible or intangible resources help service industry MSMEs in emerging economies to rejuvenate firmsAo performance in market 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 3 Conclusion on Demographic Profile According to the demographic analysis findings in chapter four, results were derived related to the distribution of TMSMEs in tourism DS divisions, age, gender, years of business operation, registration, nature of the business, number of employees, and educational qualifications.
Thus, the findings revealed that most of the TMSMEs can be found in popular tourism DS divisions such as Ella.
Haputale, and Bandarawela.
The majority of owners were in the 35-45 age category, and almost 86% were males.
This evidence proves that women's empowerment in tourism is still not at the same level as male tourism entrepreneurs.
The years of operation in the tourism industry of all the TMSMEs that have been interviewed belong to 3-5 years operation period.
TMSMEs in the Badulla district were registered with district secretariats or municipal councils, and only a few of the respondents were registered with the SLTDA.
Furthermore, the highest proportion of TMSMEs is in the accommodation and food and beverage sectors.
With the findings related to the number of employees, micro and small category establishments have the highest composition among tourism service providers.
Finally, most of the owners of the TMSMEs in the Badulla District have advanced or ordinary level educational qualifications, and there were the least number of respondents who started businesses with experience in the tourism industry.
Most respondents with tourism experience had worked for international tourism-related organizations, such as hotels and airlines.
4 Limitation and Future Research The study was limited to TMSMEs in selected emerging tourism regions in Sri Lanka using a quantitative approach, and the performance of businesses was measured using subjective measures.
The study also limits secondary data, such as annual income and profits, as TMSMEs were reluctant to provide financial figures.
Therefore, future studies should consider qualitative data related to current studies in different tourism regions in developing economies to generalize the findings.
Furthermore, the researcher recommends studying other variables for competitive advantage, sustainable performance.
Green Practices, and any relevant ones to compare with the current findings of the study to contribute to Resource Advantage (R-A) theory in future studies.
5 Suggestion The implications of this study are comprehensive for both policymakers and tourism entrepreneurs.
First, the obtained results provide valuable insights for government regulatory bodies and tourism development authorities to determine the necessary government-supportive programs to enhance the financial and environmental performance of TMSMEs to witness sustainable performance in making sound decisions on uplifting potential entrepreneurs, catalysts, or businesses categorized under the informal sector to witness regional development through rejuvenating TMSMEs to mitigate poverty and unemployment in the local community and raise per capita income.
Further, the study elaborates on the importance of facilitating MSMEs by the government, as the spending of tourists on tourism MSMEs products or services is not an economic leakage transaction but benefits all three pillars of sustainability.
Therefore, the evaluation of existing financial and non-financial programs, along with the performance of MSMEs in different areas with high tourism contribution or potential tourism destinations, provides the most required assistance to rejuvenate the performance of the business to cater to potential tourism demand in the future, one of the recommendations to policymakers.
Moreover, as emphasized in the literature, tourism entrepreneurs can extract the findings of the study to understand the importance of going green and acquiring government support to enhance business performance in market catastrophes.
Thus.
GS in different forms helps mitigate socioeconomic disparities at the regional level to foster regional economic growth, consequently contributing to the countryAos GDP.
Sri Lanka, as a developing economy, has identified the critical importance of empowering MSMEs to ensure economic growth by supporting them to rejuvenate their performance after industry shutdowns or malfunctions to cater to future demand.
Hence, this study provides valuable insights for academic and relevant government or non-governmental policymakers to make sound decisions regarding rejuvenating TMSMEs.
Acknowledgment I would like to express my heartfelt gratitude to Prof.
C Ranasinghe.
Faculty of Management of Uva Wellassa University, for his invaluable support, advice, and numerous instructive conversations.
I am also deeply grateful to my supervisor.
Ms.
Ranatunga.
Ms.
Pattiyagedara, lecturers in the Department of Tourism Studies at Uva Wellassa University, for their unwavering support and guidance from 2025 | Journal of Sustainable Tourism and Entrepreneurship / Vol 7 No 1, 17-34 the beginning to the end of this research.
I would like to thank both my supervisors once more for their direction, encouragement, and critical contributions in reviewing the findings and assisting with the data Special thanks to the Department of Tourism Studies at Uva Wellassa University of Sri Lanka for providing the necessary resources and facilities to conduct this research smoothly.
I owe my deepest gratitude to the respondents from the Badulla District who participated in the survey and generously shared their information with me.
References