Demographic Analysis
Based on the result, it is clear that the female respondents have the highest proportion (66.9%), followed by the male with 33.1%. This result shows that the respondents the aged 19 to 30 years old have the highest percentage with 46.5%, while 14.8% came from the age group of 31 to 40 years old, followed by the age group 51 to 60 years old with 10.6%, 4.2% for the age group 60 years old and above and lastly 1.4% for the age group 18 years old and below.
The third item in the demographic section is race and it is clear that the majority of the respondents are Malay with 89.4%. This is because most of the residents in Langkawi Island are Malays. There are 6.3% of Chinese respondents, 2.1% Indians followed by 1.4% from other races, 0.7% for Non-Bumiputera, and finally 0% for Bumiputera. The next item in the demographic section is the type of industry and it is shown that Food and Beverages hold the biggest percentage in the industry with 51.4% followed by others with 18.3%. Other industries include retail, fashion, automotive, and advertising.
Destination fun and thrill rank third in the type of industry with 11.3% followed by hotel and accommodation (9.2%), arts and crafts (7.7%), and transportation with 2.1%. In terms of years of operation, the highest percentage with 26.8% is shared between 1 to 3 years and more than 10 years, followed by 4 to 6 years (16.2%), 6 to 12 months (12.0%), while less than 6 months and 7 to 9 years ranked last with 9.2%. Based on the data gathered, less than RM5,000 ranked first for the monthly income or profit with 60.6% while RM5,000 to RM10,000 ranked second with 25.4%, followed by RM10,000 to RM20,000 (9.2%) and more than RM20,000 (4.9%).
Reliability Test
The table above shows the reliability test for a total of six independent variables and one dependent variable. The Cronbach Alpha (CA) indicated that all the constructed factors were between 0.626 and 0.916. These values showed that these factors have correlations that are of medium, high and very high strength to build the constructs. For the independent variable, production supply has the highest Cronbach Alpha value which is 0.916 followed by employee health and welfare at 0.857, financial issues at 0.807, customer demand at 0.798, government restrictions at 0.761 and lastly, adapting to changes at 0.749. The dependent variable which is the business performance has resulted with 0.626 Cronbach Alpha value. As a result, the construct's reliability can be assured
Correlation Test
The correlation analysis result is shown in the table below. This analysis is a statistical method used to discover the relationship between two variables or datasets and to know the strength of the relationship. Based on the P-value, it indicates that all P-value readings are acceptable with different strengths of correlation. There is a moderate correlation for the independent variable financial issues (0.457), employee health and welfare (0.494), customer demand (0.439), adapting to changes (0.549), and government restrictions (0.406). However, for the independent variable production supply, it is shown to have a weak correlation with only 0.275. This indicates that production supply might not be the major factor that affects SME’s business performance in Langkawi Island. Therefore, this analysis proves that all variables measured are correlated to the business performance.
Regression Test
Multiple regression was conducted in this research to examine whether financial issues, employees' health, and welfare, production supply, customers' demand, adapting to changes, and government restrictions affect SMEs' business performance. This model explained that all the independent variables are significant with 47% of variance which indicates that it has 47% of the influence on SMEs' business performance. The adjusted R Square penalizes the addition of 0.442 units of the independent variables to the model.
To examine the significance level of the total independent variables, the researcher has calculated the p-value for the F-test. It is shown that the p-value is 0.000 which indicates that the data is significant as it is lower than the significance level of the alpha value of 0.05. This determines that all independent variables in the model demonstrate too in tailored. As a result, the regression model is significant.
SmartPLS Model
Discussions
Financial issues:
On findings, it shows that the relationship between financial issues and business performance is significant. The result from the analysis interpreted that some business owners have had difficulty in planning and execution due to the limited financial, workforce, and resources. For the financial dimension, item FD1 which is impeded cash flow has the highest mean which is 4.39 as most SMEs became financially fragile during Covid-19. As stated by Kaushal and Srivastava (2020), some of the challenges faced by many the organizations during Covid-19 are very common such as managing fixed expenses, payroll, the morale of the employees, and especially cash flow. Therefore, it can be concluded that when SMEs have difficulties in maintaining their finances during Covid-19, it is shown that their business performance drops and they have a hard time continuing the business.
Employees' health and welfare:
Based on this research, the result from the hypothesis testing indicates that employees' health and welfare have a significant relationship with SMEs' business performance. In addition to that, the highest mean in employees' health and welfare, is shared by items ED2 and ED3. Based on this result researchers found out that the respondents agreed that it is difficult to maintain employees' health and welfare during Covid-19 and that the limitation of employees on business premises has a big effect on the business performance. Robinson et. al. (2020) stated in their research that the COVID-19 is spreading through person-to-person transmission and therefore, the tourism industry has become one of the prime carriers of this disease. Priyono et.al. (2020) also supported this with their statement that firms that manufacture physical products experience challenging situations because the production processes and delivery value processes require direct contact.
Production supply:
The result of this current study shows the significant relationship between production supply and SMEs' business performance. According to Priyono et al. (2020), when orders originate from individual clients, there will be a problem with manufacturing because the number of orders will not attain production economies of scale. Based on the analysis, the production dimension has a weak correlation but is still significant. The researchers concluded that production does not strongly affect SMEs' business performance as there were not really many customers and had very low demand during Covid-19 therefore, their supply is available, and does not need to face the difficulties in production and supply.
Customers demand:
Next, based on the results of hypothesis testing, The analysis also shows that most of the items in customers' demand dimension have high means. This indicates that there is an obvious change in customer demand during Covid-19 and it has affected the SMEs' business performance on Langkawi Island. This is supported by Aftab et.al. (2020), that these uncertain situations such as Covid-19, it brings troubles for small and medium enterprises in the form of disruption in supply chains and a decrease in the demand for their products and services. Shafi et al. (2020) investigated the state of micro, small, and medium-scale enterprises (MSMEs) in Pakistan following the outbreak of Covid-19 and discovered that MSMEs in Pakistan was experiencing serious issues because of a drop in demand for their products and services. As a result, the researchers believe that customer demand has a significant impact on SMEs' business performance in Langkawi island during Covid-19.
Government restrictions:
Lastly, the researchers have found that Government Restrictions give the biggest impact on SME business performance. Based on the findings, item GRD4 has the highest mean with 4.49. The item states that the Interstate Controlled Movement has given an impact on the business in terms of demand. Aftab et.al. (2020) stated that the forceful and mandatory closures of businesses and restrictions on the level of operations have harmful effects on small and medium enterprises. This is supported by Robinson et.al. (2020) who state that a large part of the income was reduced by social distancing and international travel bans. Furthermore, a large number of SMEs indirectly dependent on tourism such as hotels, travel agents, suppliers, tour operators, and tour guides are on the verge of collapse (Fernandes, 2020). This proves that lockdown, standard operating procedures, closure of all non-essential business premises, and political instability have greatly influenced SME business performance in Langkawi Island during Covid 19.
Adapting to changes:
The research is also to determine the relationship between adapting to changes and SMEs' business performance. Based on the analysis, item ACD1 has the highest mean with 4.25. This represents that most of the respondents agree that their business needs to adapt to the changes during Covid-19, especially in marketing strategies. This is because it has become harder to gain customers during Covid-19 especially when people are avoiding buying unnecessary things. Many organizations still assume typical conditions in their planning process during times of disruptive change, such as during Covid-19, according to Priyono et al. (2020), and while this approach can still be used, it is viewed as less relevant, whereas an emergent approach with a flexible strategy is viewed as more relevant. Hence, adapting to changes affects the business performance of SMEs in Langkawi during Covid-19.
Based on data analysis, the researchers determined the independent variables that affected the SMEs’ business performance during Covid-19 in Langkawi Island, Malaysia: financial issues, employees' health, and welfare, production supply, customers' demand, adapting to changes, and government restrictions.
In this study, there are 6 variables verified using the Likert scale are financial issues, employees' health and welfare, production supply, customers demand, adapting to changes, and government restrictions.