Keywords

Global Economics, COVID-19, Embroidery SMEs, Business performance

Introduction

When the financial crisis hit the world in 1998 and 2008, the Small and Medium Enterprise (SME) sector was not the major contributor to the economy as the majority of the then SMEs did not have a huge amount of capital invested in them. As a result, they were not much affected by the then financial crisis. However, at present, the SME sector is the most affected one by the coronavirus pandemic. Goldman Sachs data shows that as much as 96% of SMEs’ owners in the United States have felt the effects of the COVID-19 pandemic and 75% of the businesses across the world have experienced a decline in sales. While Indonesian SMEs’ sale has decreased by 70% in the past week (Zayed et al., 2020a; Zayed et al., 2020b; Zayed et al., 2021a; Zayed et al., 2021b).

The use of technology will be the best solution to face the global financial crisis caused due to coronavirus that can help SMEs to continue to run their business (Shil et al., 2020). In addition to financial assistance, social media marketing and office automation will facilitate SMEs to devise strategies appropriate for the current and future business scenarios (Afrina et al., 2020).

Nowadays, businesses are growing very fast. Competition is perceived both at the local and global levels. The improvement of organizational resources is the way to achieve a competitive advantage. It could be improved by developing internal and external processes. Moreover, SMEs have a significant role in strengthening the economy by improving income, providing employment, helping in poverty elimination, fostering exports, encouraging entrepreneurship, empowering the indigenous knowledge, and fortifying the rural economy (Tambunan, 2008). In addition, SMEs can stimulate the national economy and provide many occupations (Ansir, 2005; Tambunan, 2008). In a developing country such as Indonesia, SMEs also play a crucial role in boosting economic growth, not only in developing countries but also in developed countries (Janita & Chong, 2013).

Since the role of SMEs has been realized the governments and the people across the world have shifted their focus on the development of this sector (Onugu, 2005; Samson & Mahmood, 2015). Chen & Miller (2014) revealed that all companies have to deal with the challenge of environmental uncertainty as a result of competition. The dynamic environment forces the SMEs to struggle in sustaining their business. Many competitors enter the market becoming not only the threats but also the opportunities that should be harnessed and managed well. Also, SMEs should benefit from their strengths and work on their weaknesses to sustain in the ever-changing market conditions. It would require planning the organizational resources to excel in organizational performance. Therefore, the researchers propose a new pattern of the relationship between Environmental Dynamics (ED), Entrepreneurial Orientation (EO), and management resources, which can influence Business Strategy (BS) on Business Performance (BP) (Figure 1).

Many companies face challenges from environmental uncertainty, due to the rapidly changing competition. Therefore, the new pattern of competition dynamics becomes necessary. The business environment is characterized by rapid technological change and intense competition. It means that the companies should succeed in the competition by marketing their products and utilizing their resources backed by adequate technical knowledge. Environmental uncertainty categorized as environmental dynamics comprises of the change of technological innovation performance (Lin, 2014), environment variability (Lumpkin & Dess, 2001), industry and market rate (Lumpkin & Dess, 2001; Wiklund & Shepherd, 2005), and the ever-changing customer behavior (Samson & Mahmood, 2014).

Methods

In testing the hypotheses, a survey was undertaken using a questionnaire. This method is appropriate to evaluate organizational behavior (Lumpkin & Dess, 2001) as it minimizes the researcher’s intervention (McGrath, 1981). The researchers have used Partial Least Square (PLS) to test the hypotheses and identify the relationships between the variables and the cross-sectional study to analyze data. The research has been conducted using a structured questionnaire that follows a Likert scale. Structured questionnaire comprised of category, list, rating, scale, quantity, and matrix.

A sample is a unit number as a representative of the population. The population of this research is the owners and managers of Embroidery SMEs in East Java province of Indonesia. There are total of 4,180 business units of various SMEs into embroidery businesses across 22 cities of districts in East Java. The researchers divide the sampling into 2 phases using 2 different sampling methods. The first phase of sampling considers the SMEs that employ aminimum of 100 embroidery craftsmen. Total 3608 SMEs met the criterion is located in Pasuruan, Lamongan, Gresik, Bojonegoro, and Tulungagung. Then, the Cochran formula shown in Equation 1 is applied to calculate the sample size.

Where

n is the sample size,

N is the population size,

t is the normal standard deviation (usually determined by 2, according to degrees of freedom).

P is the proportion of certain traits that are estimated in the population (if it is not known, the proportion is known as 0.5).

Q = 1 – P

D = population variance or degree of accuracy expected (usually set at 0.05 or 0.01)

Based on the aforementioned equation, the sample can be determined as follows:

The second phase uses proportional random sampling to determine the sample size for each of the above-mentioned districts. The district-wise sample size is presented in the following Table 1.

Table 1 The District-Wise Sample Size of Embroidery-SMES In East Java, Indonesia
No.	Districts	Population	Sample size
1.	Pasuruan	2,451	(2,451: 3608) x 360 = 245
2.	Lamongan	485	(485: 3608) x 360 = 48
3.	Gresik	368	(368: 3608) x 360 = 37
4.	Bojonegoro	180	(180: 3608) x 360 = 18
5.	Tulungagung	124	(124: 3608) x 36 = 12
	Total	3.608	360

Results

Assessment of Measurement Model

The analysis using Smart PLS 2.0 yields inner and outer models. The inner model analysis is employed to determine the relationship between variables in the model under study. Meanwhile, outer model analysis is utilized to measure validity and reliability. The attributes reliability, consistency, and validity were measured. The outer loading can be shown in Table 2.

Table 2 Outer Loading
	Business Performance	Business Strategy	Entrepreneurial Orientation	Environmental Dynamics	Managerial Ability
X.1.4.1			0.772
X1.2.2			0.884
X1.2.3			0.767
X1.3.3			0.802
X1.4.2			0.766
X1.4.3			0.833
X2.1.2				0.771
X2.2.1				0.705
X2.2.2				0.779
X2.2.3				0.866
X2.2.4				0.795
X3.1					0.811
X3.10					0.785
X3.5					0.676
X3.6					0.847
X3.7					0.788
X3.8					0.858
X3.9					0.777
X4.1.1		0.786
X4.1.2		0.779
X4.2.1		0.821
X4.2.2		0.704
X4.2.6		0.636
X5.1.1	0.842
X5.1.2	0.688
X5.1.3	0.85

The above-mentioned table shows an outer loading value > 0.6. If it is less than 0.6, it should be removed. Based on the results, all values are more than 0.6, which means the quality of data is good. The good quality of data represents the relationship between indicators and variables.

Then, the reliability, consistency, and validity of the constructs are presented in Table 3.

Table 3 Convergent Reliability and Validity
	Cronbach's Alpha	Composite Reliability	Average Variance Extracted (AVE)
Business Performance	0.724	0.838	0.635
Business Strategy	0.801	0.863	0.560
Entrepreneurial Orientation	0.891	0.917	0.648
Environmental Dynamics	0.844	0.889	0.616

The reliability is presented by Cronbach's Alpha and composite reliability. The researcher has considered the value of Cronbach's alpha and composite reliability of the construct variables that are more than 0.7 as shown in Table 3. Further, the validity of the construct variables can be shown as Average Variance Extracted (AVE). The researcher considers the value of AVE which is above 0.5. Table 3 reveals all values that satisfy the thumb rule of reliability and validity (Hair et al., 2010). The discriminant validity is assessed by analyzing the cross-loading and using the Fornell Larcker criterion. All indicators of cross loading are of value that is more than 0.6 thus; meet the requirement.

Also, the loading factor value of each variable in this model can be seen scaling up. Therefore, the result of crossing loadings analysis indicates that all the variables are related to each other and that there is no multicollinear data in this research.

The Goodness of Fit

The assessment of the goodness of fit aims to identify the value of Q2 predictive relevance for the variable on model. Q2 value can predict how well the model can produce the observational value and its parameters’ estimate. Q2 value should be greater than 0 which means the model has a predictive relevance, whereas the Q2 value less than 0 shows that the model has less predictive relevance. The calculation of Q2 predictive relevance is:

Q²=1-(1-R21) (1- R22)
Q²=1-(1-0.303) (1-0.661)
Q²=1-(0.697) (0.339)
Q²=1-0.2363
Q²=0.7637

 

The results show that the Q2 value is more than 0 which indicates that the model has relevant predictive value.

Assessment of Structural Mode

Table 4 shows that all hypotheses tested in the research were supported by data. The EO has shown its major impact on Managerial Ability (MA). Thus BScan also be a mediator that connects the EO and EDwith BP (Figure 2).

Table 4 Hypotheses Result
Hypothesis	Path Coefficient	t-statistics	P-Value	Decision
H1:EO →BS	0.278	4.477	0.000	Accepted
H2:EO →BP	-0.579	6.454	0.023	Accepted
H3:ED →BS	0.438	9.137	0.000	Accepted
H4:ED →BP	-0.353	4.586	0.041	Accepted
H5:BS →BP	0.394	4.195	0.002	Accepted

The results of the analysis show that the highest R² in the research is 66.1%. This indicates that the relationship between latent variables BS and BP inferred from EO, ED, and MA is 66.1%. This implies that 33.9% of the BS variables are explained by other variables which are not examined the research.

Table 5 R2
	R Square	R Square Adjusted
Business Performance	0.303	0.294
Business Strategy	0.661	0.657

Discussion

Table 4 shows that EO influences BS. This finding is supported by the research that simultaneous market orientation and entrepreneurial orientation significantly influence the business strategy of the SMEs that are into the creative industries (Nuvriasari et al., 2018; Alayo et al., 2019; Asemokha et al., 2019). The research states that the higher the entrepreneurial orientation, the higher the business strategy or vice versa. For small businesses, entrepreneurial behavior can be realized in two ways, namely effective leading business and appropriate business planning to respond to market needs. Entrepreneurial orientation of the company emerged as a multidimensional concept in the entrepreneurship literature and strategic management. Furthermore, entrepreneurial orientation can be an important indicator of an organizational structure and has an ability to provide a competitive advantage to the organization (Altinay & Wang, 2011; Kusa et al., 2019; Yamin, 2020; Kristinae et al., 2019; Baker et al., 2019; Fatoki, 2019).

The observations of the research are consistent with an opinion, which states that SMEs need to have dynamic resources and strategies that are able to grab the opportunities and build up the market (Wardoyo et al., 2015). Global business pressure and competition including globalization, technological improvement, demographic and social change, the ability to innovate, financial support, and entrepreneurship affect SMEs. Entrepreneurial orientation reflects the extent to which companies identify and take advantage of the opportunities that have not been explored as an organizational principle in the company (Baker & Sinkula, 2009). Strategic business addresses the problem of how companies face competition and handle global impacts. To deal with the situation at hand and have a competitive advantage, the company needs a good business strategy along with good entrepreneurial orientation.

The entrepreneurial presentation has a significant and negative effect on business performance. The research has successfully proved the effect of entrepreneurial orientation on business performance. The better the entrepreneurial orientation, the higher the MSME business performance. These findings are consistent with findings of the research which state that a higher entrepreneurial orientation can improve a company's ability to market products towards better business performance (Covin & Slevin, 1991; Wardoyo et al., 2015). Entrepreneurial orientation of business leaders can improve business performance. The entrepreneurship agency holds an important role (Keh et al., 2007).

The Negative Effects of Entrepreneurial Orientation on Business Performance

COVID-19 has significantly impacted the businesses of cooperatives, MSMEs, whose economic turnover is highly dependent on the transportation of goods, services, and individuals, whose movement is being restricted. As a result, the productivity of SMEs’ ecosystem has decreased which has in-turn affected the welfare of the SME sector.

COVID-19 has greatly impacted the business continuity of SMEs (Shahriar et al., 2021; Igbal et al., 2021; Islam et al., 2021). As per the survey results, as many as 96% of SMEs have experienced the negative impact of COVID-19 on their business processes. As many as 75% of them have experienced a significant decline in sales. Moreover, 51% of SMEs believe that it is very likely that the existing business will last only for the next 1 month to 3 months. As many as 67% of SMEs have experienced uncertainty in obtaining access to emergency funds, and 75% feel that they do not understand how to make policies in times of this global crisis. Only 13% of SMEs believe that they have a crisis management plan and they can find a solution to continue their business.

In dealing with this emergency, the Ministry of Cooperatives and SMEs of the Republic of Indonesia is implementing necessary measures in the form of policies, regulations, programs, and facilitation, with the aim of sustaining the SMEs and the perpetrators in this crisis.

Research findings indicate that environmental dynamics has a significant impact on business strategy and business performance. The environmental dynamics supported by business strategies help improve business performance. This finding is consistent with the findings of the research that states that the changes in the business environment should be handled in a particular manner since most of the changes are beyond the control of the company (Meiliawati's, 2017; Doppelt, 2017; Hickman & Silva, 2018; Trost, 2020, Hock-Doepgen et al., 2020). Companies that respond to the changing business environment dynamically can benefit themselves; however, for companies that tend to be static, the change will be a threat to their survival. The external environment and the business itself reciprocally influence each other (Brooks & Weatherston, 2000; Lawrence & Weber, 2011).

Positive Impact of Business Strategy on Business Performance

Another research states similar findings as that of the research that a good business strategy impacts the business performance positively (Rusdian & Purwantini, 2015). A good strategy helps the organization to adjust as per the changing business environment so as to achieve a competitive advantage. Porter (1980) points out that sustainable competitive advantage can only be achieved through continuous brainstorming of design and strategies to realize it.

The observations of the research are similar to the observations of previous research that a business strategy is an organizational activity that encompasses the activities related to cost leadership, marketing differentiation, and differentiated innovation (Miller, 1988). Cost leadership is established by performing the company operations cost-efficiently. The marketing differentiation strategy can be is implemented by providing a better service to customers and have a better distribution policy. The differentiated innovative strategy is implemented through the application of new technology and quality design in a creative manner (Rusdianti & Purwantini, 2015).

In these times of global crisis, businesses must improve their business processes by implementing sophisticated technologies that save time and energy. They can make the most of these technologies with various strategies such as digital marketing and tools such as social media, and online delivery services.

Conclusion

Entrepreneurship and environmental dynamics have a positive as well as a negative impact on business strategy and business performance. Similarly, a business strategy can in turn affect business performance. Good entrepreneurial orientation and environmental dynamics accompanied by good business strategies can improve business performance. The research ascertains that the business strategies that support the improvement of SME performance based on entrepreneurial orientation and environmental dynamics are able to deal with the impact of COVID-19 on the global economy.

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