Do Financial Strategy, Survival Strategy and Business Innovation Influence Small and Medium Enterprises (SMEs) Sustainability During COVID- 19 Pandemic? A Malaysian Evidence

Do Financial Strategy, Survival Strategy and Business Innovation Influence Small and Medium Enterprises (SMEs) Sustainability During COVID- 19 Pandemic? A Malaysian Evidence

Siti Hajar Idayu Daud¹, Erlane K. Ghani², Kamaruzzaman Mohammad³, Maz Ainy Abdul Azis^4* and Elvira Luthan⁵

^1,2,3,4Faculty of Accountancy, Universiti Teknologi MARA, 42300 Bandar Puncak Alam, Selangor, Malaysia; maz731@uitm.edu.my (M.A.A.A.).

⁵Fakultas Ekonomi & Bisnis, Universitas Andalas. 25175 Padang, Indonesia.

DOI: https://dx.doi.org/10.47772/IJRISS.2025.908000078

Received: 25 July 2025; Accepted: 31 July 2025; Published: 28 August 2025

ABSTRACT

This study examines factors that influence the business sustainability of Small and Medium Enterprises (SMEs) during COVID-19 pandemic. In particular, it assesses the effect of financial strategy, survival strategy and business innovation on the SMEs sustainability during pandemic. Using a survey questionnaire as the research instrument on 132 of SMEs the results show that there is a positive relationship between survival strategy and business innovation on the SMEs sustainability. Financial strategy however shows an adverse result by the significant negative relationship towards SMEs sustainability. The findings also demonstrate that all the three factors have significant influence on SMEs sustainability during COVID-19 pandemic. This study provides understanding on the SMEs owner’s viewpoint and their strategies they adapted during the critical period such as Pandemic COVID-19 to remain sustain and resilience. This study also provides significant practical implications and inputs for the Regulatory bodies in formulating intervention strategies in the future. In addition, this study will help academics in understanding the factors related to business sustainability that are important inputs in their studies.

Keywords: Financial strategy, Survival strategy, Business innovation, SMEs sustainability, COVID- 19.

INTRODUCTION

Small and Medium Enterprises (SMEs) play a major role in most economies, particularly in developing countries. SMEs account for over 90% of global business, significantly contributing to job creation and the development of an inclusive economy. The World Bank [1] predicts a need for about 600 million jobs by 2030 to accommodate the growing global workforce. This makes the development of SMEs a priority for most governments all over the world. The Department of Statistics, Malaysia (DOSM) released its latest data in the Malaysia Statistical Business Register (MSBR), revealing that 1,151,339; or 97.2% of all SMEs’ business establishments, were recorded by SME Corp [2]. The performance of SMEs in 2020 indicates that they contributed 13.5% to Malaysia’s export segment, 38.2% to the country’s Gross Domestic Product (GDP), and 48.0% to employment.

Political, economic, sociological, technological, environmental, and legislative changes influence the growth and performance of SMEs, but since the early documented pandemics, safety and health have also become significant factors. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the Coronavirus Disease 2019 (COVID-19), an ongoing global pandemic. In December 2019, Wuhan, China first identified the virus. The World Health Organization (WHO) declared a public health emergency of international concern regarding COVID-19 on January 30, 2020, and later declared a pandemic on March 11, 2020. Urgency of International Concern regarding COVID-19 on 30 January 2020 and later declared a pandemic on 11 March 2020. Beyond businesses, the pandemic has had devastating effects on households and individuals through loss of jobs or reduced incomes. Microenterprises and SMEs, the informal sector, the urban poor, and the elderly are among the most vulnerable groups affected by the pandemic. The broader impact of the pandemic on households is caused by the widespread loss of employment in small businesses, informal workers in temporary jobs, gig economy workers, as well as the services sector.

Since March 2020, Malaysian entrepreneurs have faced a movement control order and a total lockdown, which have fundamentally changed the way SMEs operate in the country. Only essential services remained open during that period, with the public closing the rest of the non-essential services. This unexpected event made the SMEs entrepreneurs find ways to persevere in their business. Hence, this study aims to examine the factors influencing the resilience of SMEs during COVID-19 pandemic periods. More specifically, this study investigates the impact of financial strategy, survival strategy, and business innovation on the sustainability of SMEs during the COVID-19 pandemic. This study offers insights into the perspectives of SMEs owners and the strategies they implemented during critical periods, like the COVID-19 pandemic, to ensure their sustainability and resilience. This study also provides significant practical implications and inputs for the regulatory bodies in formulating intervention strategies in the future. Furthermore, this study will assist academics in comprehending the factors associated with business sustainability, which are crucial components of their research. The next section, Section 2, provides the literature review relevant to this study. Section 3 explains the research design, while Section 4 presents the results and discussion. The last section, Section 5, concludes this study.

LITERATURE REVIEW

Sustainability is an issue that has always been discussed when responding to significant changes in the environmental problems. Some examples of threats to sustainability are natural disasters, terrorist attacks, economic recessions, and pandemic diseases as suggested by Hamsal and Ichsan [3]; as well as Purnomo, et al. [4]. The threat above brings potentially uncertain and severe challenges to the sustainability of an organisation’s operation and infrastructure as they are interconnected with each other in the business lifecycle.

The concept of sustainable development is very different from that of sustainability, as the word ‘development’ clearly points to the idea of change, in the sense of ‘improvement’. Sustainable development is a process of change that can improve the system in a sustainable manner. According to Eswarlal and Vallesi [5], this transformation of the system can be used to improve the system, to improve the output, or to improve both. Sustainability, understood as a set of functional principles of systems, makes it possible to define a sustainable development style as a social choice that includes multiple objectives in accordance with certain scales of value and variable contexts that gradually change over time and produce permanent feedback process Gallopín, et al. [6].  This study highlights the importance of discussing sustainability for Small and Medium Enterprises (SMEs) as it bridges the practical knowledge gap. Practical knowledge gap is defined as a gap that tends to be discrepant that can motivate new research in this direction. A practical knowledge conflict arises when the actual behavior of a professional is different from their advocated behavior.  In this case, research could seek to determine the scope of the conflict and to uncover the reason for its existence.

Previous studies such as Hidayat, et al. [7] have addressed several aspects of business resilience, which is strongly influenced by the entrepreneurial spirit of SMEs owners when facing the. Practical knowledge gaps, however, encompass several unexplored dimensions that have lately attracted research attention in other disciplines, as mentioned by Hamsal and Ichsan [3]; Hu and Kee [8]; as well as Weaven, et al. [9]. Hamsal and Ichsan [3]; Hu and Kee [8]; as well as Weaven, et al. [9] agreed that unexplored business sustainability strategy appears to be important and worthy of investigation with a focus on business model innovation as a factor to remain sustainable during a pandemic. Gallopín, et al. [6] in their article, mentioned the theory of evolutionary technology, where theoretical viewpoints on sustainable development as maintaining co-evolutionary adaptive capacity in terms of knowledge and technology react to uncertainties, fostering economic diversity of actors, sectors, and technologies. Therefore, SMEs sustainability can be achieved to remain resilient in the economic turbulence situation by adding competitive advantage into the organisation’s decision-making process. According to Bryce, et al. [10], the strategic business model can be important here, where innovation, diversity, flexibility, and the ability to work across boundaries may encourage new and adaptive approaches in the face of adversity.

Prior studies by de Waal and Mollema [11]; as well Nurunnabi [12] have evidenced that financial strategy acted as a significant factor in SMEs sustainability during the pandemic. Tansey, et al. [13] asserted that the implementation of stricter financial management, cutting off administrative costs, laying off employees, and renegotiating loan agreements were said to be components of financial strategies during a crisis. A company’s condition can be determined by reviewing its financial status and the strength of its internal organization. The company’s financial status determines whether it has the financial capacity needed to adopt and execute a specific course of action. The financial status of an organisation can be characterised as strong when the company has sufficient funds to undertake new operations; reasonable when the company needs to adopt a cautious financial approach but nevertheless has some scope for new investments; and weak when a situation in which the company must be financially extremely cautious. Nurunnabi [12] in his article stated that financial sustainability is a top priority vision in the pandemic season where SMEs owners tend to manage costs effectively and hold regular customers to survive.

Besides cost control and profit monitoring, de Waal and Mollema [11] described six courses of action that companies can adopt in times of crisis. The first three courses of action are defensive, where the primary objective of the organisation is to survive. The other three courses of action are offensive, where the intention of the company is to benefit from a crisis by growing profitably and becoming the market leader. Chan and Abdul-Aziz [14] conducted a comprehensive analysis of the financial statements and annual reports of 35 property development companies listed on the Kuala Lumpur stock exchange. The companies were then categorised into non-distressed and distressed companies. Survival strategies adopted by distressed companies include the disposal of assets to improve cash flow, refinancing loans, delaying the launch of new projects, and reducing their workforce; reducing leverage; minimising costs; reducing wages; and downsizing to survive. Aghimien, et al. [15] explained three generic strategies, which are cost leadership, differentiation, and focus. The aspect of cost leadership has to do with an organisation aiming at being a low-cost producer in an industry for a given level of standard. Differentiation deals with an organization adopting innovative practices to stand out among its competitors.  Focus strategy is seen as a way for an organisation to focus on its available resources in a specific market. These strategies involve the organisation trying to serve specific segments more effectively than its competitors. Over the years, several strategies for survival have evolved from these generic strategies and have been adopted in crisis management. As financial strategy seemed to be important towards SMEs sustainability, this study develops the first hypothesis: 

H1: There is a significant relationship between financial strategy and SMEs sustainability during the COVID-19 pandemic.

Survival strategy was mentioned by Che Omar, et al. [16]; as well as Fletcher and Griffiths [17] to be a crucial element towards SMEs survival during the crisis. According to Fletcher and Griffiths [17], the outline of marketing strategies and digital transformation during MCO was said to be components of survival strategies during crisis. Che Omar, et al. [16] scrutinised the implications of the COVID-19 Movement Control Order (MCO) on SMEs to identify survival strategies based on the owner’s perspective in Malaysia. A qualitative approach was performed through telephone interviews with the owners of six SMEs. The findings show that the SMEs survival strategies come under financial and marketing strategies. Fletcher and Griffiths [17] investigated the digital transformation during lockdown and reflected on how the pandemic has uncovered the fragility of digitally immature organisations. The article provides three salient points. First, organisations need to improve their digital maturity. Second, organisations that are less digitally mature have greater fragility. Finally, organisations with a higher level of digital maturity have greater flexibility.

Tomiˇ [18] explained that business models aim to ensure continuity and improve business activities during lockdowns. Even if the implementation of digital technologies that support business activities was not planned and decided involuntarily, it leads to gains in terms of competitiveness and resilience. SMEs need to be flexible in this new strategy to enable them to survive. Nurunnabi [12] refers to the White Paper 03 of the Global SME Policy Network (GSPN) that focuses on recovery planning of SMEs in Saudi Arabia during the COVID-19 pandemic. The recovery planning includes a renewal strategy or business transformation and cost leadership strategy to recover from the pandemic. Weaven, et al. [9] examined dynamic capabilities contributing to SMEs survival and growth during an economic downturn. Under survival mechanisms, it confirms the importance of business owner characteristics and firm resources. Three dimensions of dynamic capabilities are sensing (business assessment and information acquisition), seizing (product portfolio decisions and investment in technologies and human resources), and reconfiguring (innovation, decentralisation, and knowledge management). It was found that performative routine aspects were more dominant, demonstrating the flexibility and context-dependence in the deployment of dynamic capabilities among SMEs. As survival strategy seemed to be important towards SMEs sustainability, this study develops the following hypothesis.

H2: There is a significant relationship between survival strategy and SMEs sustainability during COVID-19 pandemic.

Business innovation plays an important role during the pandemic as many SMEs started to review their business plan, make innovations on business products, adopt product differentiation strategies, and do marketing and process innovation to cope with the pandemic limitations. Several studies such as Purnomo, et al. [4] and Fitriasari [19] outlined the business model canvas to be used during the crisis. Chaarani, et al. [20] explained four types of strategy of competitive innovation, namely marketing innovation, organisation innovation, product innovation, and process innovation that have influenced the financial performance of SMEs during the pandemic. They concluded that marketing and process innovation play an important role in developing the financial resilience of SMEs during the pandemic.

Fitriasari [19] described a business model that can be applied to SMEs in the COVID-19 pandemic using a business model canvas approach. A qualitative method was used with the data sources that were taken from printed and electronic media, books, and electronic journals. A meta-analysis was conducted, and three critical factors of business resilience were highlighted: product excellence, people behaviour, and process reliability. Alara [21] described management commitment, worker commitment, and safety education and training as essential parts in a pandemic where the author explained institutional theory as a basis to investigate the role of an organisation in the safety practices focusing on the construction industry in Nigeria. The regulation mandates the use of face masks in workplaces, places restrictions on gathering, requires a physical distance of at least 2 m between workers, restricts more than 50 persons in an enclosed space, permits access to only critical personnel on-site, and prohibits a worker with a body temperature above 38 degrees Celsius entry to the site and such worker be advised to immediately seek medical attention.

Institutional theory by DiMaggio and Powell [22] postulates that “organisations respond to pressures arising from their external and internal business environments and adopt structures and practices that are accepted as appropriate organisational choices and considered legitimate by other organisations in their fields”. DiMaggio and Powell [22] classified these pressures into three; the emergence of new rules enacted by the state can propel organisational strategic response (coercive pressures), pressures arising from the need to copy successful competitors during periods of high uncertainty can propel organisational change (mimetic pressures), and lastly, pressures because of norms in certain vocations (normative pressures). These pressures guide organisations toward isomorphism. Studies revealed that although the central idea of institutional theory is isomorphic in behaviour, organisations differ in their strategic responses to institutional forces, and organisations may decide to avoid, compromise, defy, or manipulate the institutional environment based on organisational characteristics. As business innovation seemed to be important towards SMEs sustainability, this study develops the final hypothesis 3 in this study.

H3: There is a significant relationship between business innovation and SMEs sustainability during the COVID-19 pandemic.

RESEARCH DESIGN

Sample Selection

The sample of this study is the owners of Small and Medium Enterprises (SMEs) who are working in the SMEs companies located in Kompleks PKNS Shah Alam (KPSA), which was used as the population frame with the latest list of SMEs companies registered with PKNS Real Estate Sdn Bhd (PREC) on 29 February 2020. PREC’s tenant list reveals a total of 200 SMEs establishments in Level G and Level 1 of Kompleks PKNS. This study used simple random sampling where all 200 SMEs are considered from the list, and each of them has an equal chance of being chosen as the sample. Given a total population size of 200, 132 respondents would constitute a sufficient sample size for this study. Sekaran and Bougie [23] supports the notion that sample sizes larger than 30 and less than 500 are appropriate for most research.

Research Instrument

This study used the questionnaire survey as the research instrument, which is generally designed to collect large numbers of quantitative data. The researchers adapted the questionnaire from previous literature such as Hidayat, et al. [7]; Weaven, et al. [9]; also, de Waal and Mollema [11] to establish the validity and reliability of the survey. The survey questionnaire consists of five sections to describe each variable measurement. The first section, known as Section A, pertains to the general information of the respondent, specifically their demographic profile. The demographic profile comprises seven (7) items, including the business registration name, the type of business activities, the duration of business in Kompleks PKNS, the type of business ownership, the paid-up capital, the education level, and the gender of the respondent. The provided information will aid in conducting the descriptive analysis for this study. Hidayat, et al. [7] also mentioned that obtaining demographic information portrays the sample population of the research.

Section B comprises financial strategy statements that assess the impact on the sustainability of SMEs during the COVID-19 pandemic. The financial strategy measurement comprises ten statements, including instances where the company encountered cash flow issues prior to the COVID-19 pandemic, made financial preparations for unforeseen events like a pandemic or economic downturn, requested a payment delay during the pandemic, and compared prices from various suppliers before making a purchase. Section C consists of statements on survival strategy that measure the effect on SMEs sustainability during the COVID-19 pandemic. The measurement for survival strategy consists of nine statements, such as the company is confident in the security data shared in the digital platform in the new norm, the company has knowledge about the digital platform before COVID-19, the company incurs additional costs preparing IT facilities for the digital platform during COVID-19, and the company is selling on a cash basis only before COVID-19.

Section D consists of a statement on business innovation strategy that measures the effect on SMEs sustainability during the COVID-19 pandemic. The measurement for business innovation strategy consists of ten statements, such as the company pays a social media advertiser to get promoted on a website, the company adopts a decentralised management structure in business during COVID-19, the company makes rapid promotion to increase sales during COVID-19, and the company periodically reviews business strategy during the crisis.

Section E in this study measures the dependent variable, which is SMEs sustainability during the COVID-19 pandemic. The measurement for SMEs sustainability consists of eight statements, such as the company experienced significant reduction in revenue during COVID-19, the company took up the moratorium offered by the bank during the crisis, the company used existing resources to operate business during the crisis, and the company faced reality without showing excessive optimism during the crisis.

Data Collection

Due to the pandemic and for safety purposes, the researcher distributed the questionnaires in new norm methods through electronic platform engines via Google Form. The formal invitations, as well as the link to access the online questionnaire survey, were shared through the WhatsApp application with the SMEs owners randomly based on the provided list by PREC. However, the response from SMEs owners was slower than expected; due to that, the researcher took the initiative to distribute the survey questionnaire face-to-face while adhering to the new normal procedure. The 200-survey questionnaire was distributed, and from the total, 132 questionnaires were returned, representing a response rate of 66%. There was no need for an elimination process because all the questionnaires were usable. 

RESULTS

SMEs Profile

Table 1 presents the types of business activity dominated in Kompleks PKNS Shah Alam (KPSA), which are apparel and shoe stores, 60 (45.5%). This majority of business activity is significant and popular among Shah Alam residents during the Hari Raya season and holiday festival. The next Small and Medium Enterprises (SMEs) with other services is 28 (21.2%), followed by food and beverages with 10 (7.6%), printing and stationery 9 (6.8%), health and beauty shops 7 (5.3%), jewellery stores 6 (4.5%), barber and hair stylist 5 (3.8%), convenience stores 3 (2.3%), and photo shops and mobile phone shops, both were 2 (1.5%).

Table 1. Type of Business

Table 2 shows business duration in KPSA, where SMEs with more than 30 years’ experience monopolise inside KPSA with 53 (40.2%). This is followed by SMEs with 20-29 years of experience with 39 (29.5%) and SMEs with the same frequency of 20 (15.2%) for 1-9 years of establishment, and SMEs with 10-19 years of experience.

Table 2. Business Duration in KPSA Source

Sole proprietorships dominate most business ownership types in KPSA, accounting for 90 (68.2%), followed by partnerships with 30 (22.7%) and limited liability companies with 12 (9.1%). Table 3 summarises the type of business ownership.

Table 3. Type of Business Ownership Source

Table 4 presents paid-up capital for SMEs. SMEs with capital below RM 30,000 with a total of 39 (29.5%). SMEs with capital of RM31,000 to RM 60,000 have a total of 57 (43.2%), while SMEs with capital of RM61,000 to RM 90,000 consist of 13 (9.8%), and SMEs with capital above RM 90,000 consist of 23 (17.4%) respondents.

Table 4. Paid Up Capital Source

Descriptive Analysis

This study measured the first independent variable, financial strategy, using 10 items on an ordinal scale presented in this section. The choice of answer was coded numerically with 1 = minimum to 5 = maximum categories. Table 5 shows the results on average, showing a mean score for the statement. The company faced a cash flow problem before COVID-19 (mean = 4.15 and SD of 1.06). Companies have emergency savings before COVID-19 (mean = 4.18 and SD of 1.11). Companies have more than one source of income to generate revenue (mean = 3.87 and SD of 1.27). Company prepared financially for unexpected events such as a pandemic or economic downturn. (Mean = 3.57 and SD of 1.52). Company fully aware of debt status (mean = 2.25 and SD of 1.44).

Company confident paying monthly commitment during COVID-19 (mean = 3.09 and SD of 1.48). Company requested a deferment of payment during COVID-19 (mean = 3.31 and SD of 1.49). The company switched to another supplier during COVID-19. 19 (mean = 2.84 and SD of 1.62). Company hiring new workers during COVID-19 (mean = 4.00 and SD of 1.10). Last statement: The company compares prices between suppliers before making purchases during COVID-19 (mean = 3.72 and SD of 1.22). The highest means score reported are companies face cash flow problems before COVID-19 (mean = 4.15 and SD of 1.06) and companies have emergency savings before COVID-19 (mean = 4.18 and SD of 1.11). Many respondents agree that business challenges are real and that businesses can experience both good and bad times. Therefore, they always take precautions by maintaining an emergency fund to ensure their sustainability for at least twelve consecutive months.

Table 5. Mean value and Standard Deviation Value of Financial Strategy

Survival strategy is the second independent variable in this study, which was measured with 9 items using an ordinal scale presented in this section. The choice of answer was coded numerically with the 1 = minimum to the 5 = maximum categories. Table 6 summarizes the statement.

Table 6. Mean value and Standard Deviation Value of Survival Strategy

Table 6 displays the mean scores and standard deviation values of survival strategies, with the average results indicating a mean score for each statement. Companies relied on walk-in customers before COVID-19 (mean = 4.50 and supported with lower SD of 1.03). Company selling on a cash basis only before COVID-19 (mean = 4.09, SD = 1.37). Companies used cashless transactions before COVID-19 (mean = 3.56, SD = 1.62). The company has knowledge about digital platforms before COVID-19 (mean = 3.74, SD = 1.31). Companies feeling confident adapt to the new normal in business during COVID-19 (mean = 3.78, SD = 1.15).

Companies used digital platforms in operation during COVID-19 (mean = 3.37, SD = 1.58). Companies are confidence in the security of data shared in digital platform (Mean=2.94, SD= 1.56) Company incur cost in adapting to the new normal in business during COVID-19 (mean = 3.81, SD = 1.24). Lastly, a statement on the company incurring costs preparing IT facilities for the digital platform during COVID-19 (mean = 3.00, SD = 1.42).

The highest mean score is for the statement: Companies relied on walk-in customers before COVID-19 (mean = 4.50 and supported with lower SD of 1.03). SMEs in KPSA agree that they really depend on physical customers; therefore, when COVID-19 hit the country, all SMEs had to be shut down, and this affected their income. The lowest mean score for the statement of Companies is confident in the security of data shared on digital platforms (mean = 2.94, SD = 1.56). Most SMEs owners are of the older generations; therefore, some of them are illiterate in using online transactions and not confident when sharing data on digital platforms.

Table 7. Mean value and Standard Deviation Value of Business Innovation

This study measured Business Innovation strategy, the third independent variable, using 10 items on an ordinal scale presented in this section. The choice of answer was coded numerically with the 1 = minimum to the 5 = maximum categories. Table 7 summarises the statement. Table 7 presents the mean scores and standard deviation value of business innovation, and the results on average show a mean score for statement mean score for Company periodically reviews business strategy during the crisis. (Mean = 4.15, SD = 1.06) Company does cost cutting for unnecessary expenses during COVID-19 (Mean = 4.05, SD = 1.26). Company adopts cost leadership strategy to its product during COVID-19 (Mean = 3.87, SD = 1.27). Company adopts product differentiation strategy during COVID-19 (Mean = 3.57, SD = 1.52). Company pays social media advertiser to get promoted on the website. (Mean = 2.25, SD = 1.44).

Companies made innovations to business products during COVID-19. (Mean=3.09, SD=1.48) Company makes rapid promotion to increase sales during COVID-19 (Mean=3.31, SD=1.49). Company introduces special events to attract customers during COVID-19. (Mean=2.84, SD=1.62) Company adopt resource-based view (RBV) strategy during COVID-19 (Mean=4.00, SD=1.10). Companies adopted a decentralised management structure in business during COVID-19 (mean = 3.72, SD = 1.22). The highest score by respondents is on the statement, Company periodically reviews business strategy during the crisis (mean = 4.15, SD = 1.06), followed by Company does cost cutting for unnecessary expenses during COVID-19 (mean = 4.05, SD = 1.26) and Company adopts resource-based view (RBV) strategy during COVID-19 (mean = 4.00, SD = 1.10). Respondents agree that these three statements confirm that the pandemic at the early stage affected SMEs badly, and their course of action in improving internal strength aligns with the theory used in this study. The lowest mean score for the statement is Company pays social media advertiser to get promoted on the website. (Mean = 2.25, SD = 1.44). SMEs owners that apply cost reduction in their operation and take the opportunity to do online marketing by themselves can save money and train themselves in improving digital platforms in their business.

SMEs sustainability is a dependent variable in this study that was measured with 8 items using an ordinal scale presented in this section. The choice of answer was coded numerically with the 1 = minimum to the 5 = maximum categories. Table 8 summarises the statement.

Table 8. Mean Value and Standard Deviation Value of SMEs

Table 8 presents the mean scores and standard deviation value of SMEs sustainability, and the results on average show a mean score for statement mean score for companies experienced a significant reduction in revenue during COVID-19 (mean = 4.56, SD = 0.95). Company aware of the stimulus packages offered by the government (mean = 4.20, SD = 1.24). Company taken up of stimulus packages offered by the government. (Mean = 3.05, SD = 1.64) The company took up the moratorium offered by the bank during the crisis. (Mean=2.57, SD=1.56) Company faces reality without showing excessive optimism during a crisis. (Mean = 4.10, SD = 9.26) The company is ready if MCO is imposed again during the COVID-19 period (mean = 2.54, SD = 1.43). The company does change management during the crisis. (Mean=1.83, SD=1.21) Company uses existing resources to operate business during the crisis. (Mean = 4.33, SD = .80). Respondents highlight four statements that represent the highest mean score, which are Company experienced a significant reduction in revenue during COVID-19 (mean = 4.56, SD = 0.95). The company is aware of the SIP PRIHATIN stimulus packages offered by the government (mean = 4.20, SD = 1.24). The company faces reality without showing excessive optimism during a crisis. (Mean= 4.10, SD=9.26) The company used existing resources to operate business during the crisis (Mean= 4.33, SD= .80).

In the early pandemic and followed by subsequent lockdowns imposed by the government, SMEs owners agree that they experienced a significant reduction in revenue during the pandemic. Even though the government of Malaysia offered a stimulus package and moratorium by financial institutions to help ease the burden, not every SMEs owner took the opportunity to remain sustainable. SMEs owners themselves take the opportunity during lockdown to increase their internal strength, facing the reality without showing excessive optimism during the crisis, and use their existing resources to operate during the crisis.

Normality Test

The normality test is a statistical process that determines the standard normal distribution data of the sample. Normality tests for this study can be assessed by obtaining skewness and kurtosis values generated based on the Z-score measurement of each of the variables, as suggested by Field [24]. The purpose of a normality test is to compute how likely the data drawn from a normally distributed population would fit before conducting regression analysis, as it is the main assumption for the test. According to Hair, et al. [25], skewness focuses on assessing the symmetry of the distribution data, where the curve can be skewed either to the left or right. Kurtosis measures the sharpness and the height of the central peak relative to a normal distribution curve. George and Mallery [26] concluded that there are many opinions on the rule of thumb for the skewness and kurtosis where all variables are acceptable as normally distributed if the values range between –2.0 and +2.0. Besides that, skewness and kurtosis values must be whittled down within -3.00 and +3.00 to ensure normal distribution is acceptable by Hair, et al. [25]. Kline [27] stated that the overall results are accepted with the requirement of a benchmark of ±3.00 and ±10.00, respectively. Based on Table 9, the results show the K-S test result shows financial strategy = .089, p = .012 above p < .001; scores were normal.

Table 9. Test Kolmogorov Smirnov Financial Strategy

Table 10 shows the skewness score is -0.422, and the kurtosis z-scores are -0.115, which indicate slight problems with skew, kurtosis, or both (at p < .05). However, because of the large sample, this is not unexpected; hence it can be referred to the central limit theorem.

Table 10. Skewness and Kurtosis Financial Strategy Source

Figure 1 shows the histograms of financial strategy according to frequency. The financial strategy result shows the scores are reasonably normally distributed, with most scores occurring in the centre, tapering out toward the extremes. The graph shows a very slight negative skew, which indicates a higher proportion at the end of the distribution, therefore representing a normal distribution.

Figure 1. Histogram financial strategy

Figure 2 provides the Q-Q plot, which shows there is no sign of a major problem with kurtosis (the dots do not particularly sag above or below the line), and there is some slight skew in the low and above results. The graph shows that the quantiles fall very close to the diagonal line, therefore. representing a perfect normal distribution. Therefore, it can be concluded that the financial strategy variable has a normal distribution

Figure 2. Normal Q-Q plot of financial strategy

Table 11 presents the results of the normality test for survival strategy. The K-S test result shows survival strategy = .079, p = .042 above p < .001; scores were normal.

Table 11. Kolmogorov Smirnov Survival Strategy

Table 12 shows the skewness scores = -.211, and the kurtosis z-scores are -.689, indicating no problem with skew, kurtosis, or both (at p < .05). However, because of the large sample, this is not surprising, and so this study can take comfort from the central limit theorem.

Table 12. Skewness and Kurtosis Survival Strategy

Figure 3 shows the histograms of survival strategy according to frequency. The result shows the scores are reasonably normally distributed, with most scores occurring in the centre and a few tapering out toward the extreme distributions. The graph shows a perfect distribution and normal skew, which indicates a higher proportion at the end of the distribution, therefore representing a normal distribution.

Figure 3. Histogram survival strategy

Figure 4 shows the Q-Q plot shows there is no sign of a major problem with kurtosis (the dots do not particularly sag above or below the line), and there is some slight skew in the above result. The graph shows that the quantiles fall very close to the diagonal line, therefore representing a perfect normal distribution. Therefore, it can be concluded that the survival strategy variable has a normal distribution.

Figure 4. Q-Q plot survival strategy

Table 13 presents the results of the normality test for business innovation. The results show that the K-S test results show business innovation = .098, p = .003 above p < .001; scores were normal.

Table 13. Kolmogorov Smirnov Business Innovation

Table 14 shows the skewness scores are -0.526 and the kurtosis z-scores are 0.178, which indicate a slight problem with skew, kurtosis, or both (at p < .05); however, because of the large sample, this is not surprising, and so therefore, we can take comfort from the central limit theorem.

Table 14. Skewness and Kurtosis Business Innovation

Figure 5 shows the histograms of business innovation according to frequency. Business innovation results show the scores are reasonably normally distributed, with most scores occurring in the centre, a few only tapering out toward the distributions. The graph shows a very slight negative skew, which indicates a higher proportion at the end of the distribution, therefore representing a normal distribution.

Figure 5. Histogram business innovation

Figure 6 presents the Q-Q plot, which shows there is no sign of a major problem with kurtosis (the dots do not particularly sag above or below the line), and there is some slight skew in the low and above results. The graph shows that the quantiles fall very close to the diagonal line, therefore representing a perfect normal distribution. Therefore, it can be concluded that the business innovation variable has a normal distribution.

Figure 6. Q-Q plot business innovation

Table 15 presents the results of the normality test for SMEs sustainability. The K-S test result shows SMEs sustainability statistics = .082, p = .029 above p < .001; scores were normal.

Table 15. Kolmogorov Smirnov SMEs Sustainability

Table 16 shows the skewness scores are -0.395, and the kurtosis z-scores are 0.615, indicating slight problems with skew, kurtosis, or both (at p < .05). However, because of the large sample, this is not surprising, and so therefore, can take comfort from the central limit theorem.

Table 16. Skewness and Kurtosis SMEs Sustainability

Source: Computed Data Analysis

Figure 7 shows the histograms of SMEs sustainability according to frequency. SMEs sustainability results show the scores are reasonably normally distributed, with most scores occurring in the centre, only a few tapering out toward the distributions. The graph shows a very slight negative skew, which indicates a higher proportion at the end of the distribution, therefore representing a normal distribution.

Figure 7. Histogram SMEs sustainability

Figure 8 shows that the Q-Q plot shows there is no sign of a major problem with kurtosis (the dots do not particularly sag above or below the line), and there is some slight skew in the low and result. The graph shows that the quantiles fall very close to the diagonal line, therefore representing a perfect normal distribution. Therefore, it can be concluded that the SMEs Sustainability Variable has a normal distribution.

Figure 8. Q-Q Plot SMEs sustainability

Reliability Test

A measure’s reliability is an indication of stability and consistency.  It is significant to ensure the reliability of data so that the outcomes of the result are free from error and consistent across time while the internal consistency of measures is indicative of the homogeneity of the items that should hang together as a set. It should be capable of independently measuring the same concept so that the respondents attach the same overall meaning to each of the items. According to Sekaran and Bougie [23], this can be seen by examining whether the items and the subsets of items in the measuring instrument are correlated highly.

Cronbach’s Alpha Coefficient is used as the internal consistency indicator. It is the most popular method by Cronbach [28] and commonly used when it has multipoint-scaled items in a survey questionnaire that wish to determine if the scale is reliable. The consideration of reliability analysis for this study reflects the data that can be dichotomous, ordinal, or interval, however according to IBM Corporation [29] they should be coded numerically. Tavakol and Dennick [30] suggested that an alpha score of .90 or above implies excellent reliability; a score in the range of .70 to .90 is considered high reliability, while a moderately reliable score is from .50 to .70, and a result below .50 shows poor reliability.

Table 17 describes the Cronbach’s Alpha outcome for this study. For financial strategy, the alpha score is .770, which is excellent and reliable with 10 statements. The survival strategy alpha score is .672, moderately reliable with 9 statements; the business innovation alpha score is .786, excellent reliability with 10 statements; and the SMEs sustainability alpha score is .592, moderately reliable with 7 statements. The alpha value for overall scale is .804. This indicates that the internal consistency of reliability for all 36 scaled items is also excellent. Hence, all the statements used to measure the variables have passed the reliability test and proven appropriate for this study.

Table 17. Cronbach’s Alpha Value for Variable

Correlation Coefficient Analysis

Correlation analysis was performed to measure the direction, strength, and significance of the association between any two variables tapped in this study, known as bivariate relationships, which were measured at an ordinal, interval, and ratio level. According to Schober, et al. [31], the correlation was derived by assessing the variations in one variable as another variable also varies. The Pearson Correlation Coefficient, r, was executed in this study with the primary concern to find out whether a relationship exists and analyse its magnitude and direction through the rules of thumb proposed by Hinkle, et al. [32]. Additionally, this is done to determine which variables exhibit a significant (2-tailed) correlation with the dependent variable, and to provide a table titled “Rule of Thumb for Interpreting the Size of a Correlation Coefficient”. It is also used to check the multicollinearity issue between the variables. The correlation between variables, which does not imply any causal relationship, and a very high correlation between different independent variables show problems with collinearity. Sekaran and Bougie [23] posited that multicollinearity arises when the variable provides redundant information, leading to either insignificant or misleading interpretations.

Table 18. Correlation Coefficient Financial Strategy with SMEs Sustainability

Table 18 shows the first correlation coefficient was computed to assess the association between financial strategy and SMEs sustainability; there was a negligible correlation between the two (r = -0.056, p < 0.05), indicating that financial strategy has no relationship and is not significant with SMEs sustainability.

Table 19. Correlation Coefficient Survival Strategy with SMEs Sustainability

Table 19 shows that the second correlation coefficient was computed to assess the association between survival strategy and SMEs sustainability. There was a low positive correlation between the two (r = 414, p < .05), indicating that survival strategy has a positive relationship and is significant with SMEs sustainability.

Table 20. Correlation Coefficient Business Innovation with SMEs Sustainability

Lastly, a correlation coefficient was computed to assess the association between business innovation and SMEs sustainability. There was a low positive correlation between the two (r = 442, p < .05), indicating that business innovation has a positive relationship and is significant with SMEs sustainability. The overall result shows that the Pearson’s correlation coefficient, r, value was between -.056 and .442 with all p-values less than .05. To sum up, only survival strategy and business innovation have significant associations with SMEs sustainability during the COVID-19 pandemic. The results also imply that there is no multicollinearity issue since no pair of independent variables with a correlation coefficient value is greater than .80 or .90 or less than -.80 or -.90, which is considered by Hinkle, et al. [32] to be highly correlated to each other; thus, Hair, et al. [25] suggested that the value should not be greater than .90 to avoid the multicollinearity problem.

Multiple Linear Regression Analysis

Multiple Linear Regression analysis is conducted to predict the variance value of several independent variables that vary in the value of a single dependent variable that has cause-effect relations via a regression model. In regression analysis there are many assumptions about the model, namely, non-multicollinearity, consistent variance, linearity, and autocorrelation. If one or more assumptions are violated, then the model in hand is not acceptable in estimating the population parameters.

Table 21 shows the results of R Square = .238. It is expressed as a percentage (multiply by 100, by shifting the decimal point two places to the right); this means that this model (which includes financial strategy, survival strategy, and business innovation) explains 23.8 percent of the variance in SMEs sustainability.

Table 21. Model Summary Multi Linear Regression Analysis

Table 22 shows the Model regression show F value =13.336 and Sig = <.001, p <.005) therefore is significant.

Table 22. ANOVA Table

Table 23 shows the highest beta is from business innovation with Beta .307, Sig. .001, p < .005 is significant. Followed by survival strategy Beta .240, Sig. .012 p < .005 significant and financial strategy Beta -.061, Sig .433 p < .005 not significant. As a summary, R Square is 23.8 percent of the variance in SMEs sustainability. The highest Beta is from Business Innovation, which is 3.07, followed by Survival Strategy. 240 represents significant variable variance in SMEs sustainability.

Table 23. Coefficient Table

DISCUSSION

The first objective of this study is to examine the influence of financial strategy on Small and Medium Enterprises (SMEs) sustainability during the COVID-19 pandemic. Thus, this study performed regression analysis to determine the relationship between the independent variables and the dependent variable. Based on the output of the regression coefficient, there is statistically no relationship between financial strategy and SMEs sustainability with (coefficient β = -.061, t (132) = -7.87, p < .05). Since the p-value is more than the alpha value of .05, hypothesis 1 (H1), which states that there is a significant relationship between financial strategy and SMEs sustainability, is not accepted. Since H1 is not accepted, this study concludes that the financial strategy during the pandemic does not significantly influence SMEs sustainability.

The second objective of this study is to examine the influence of survival strategy on SMEs sustainability during the COVID-19 pandemic. The outcome of the regression coefficient for survival strategy shows a statistically significant positive relationship between survival strategy and SMEs sustainability with (coefficient β = .240, t (132) = 2.554, p < .05). Since the p-value is less than the alpha value of .05, hypothesis 2 (H2), which states that there is a significant relationship between survival strategy and SMEs sustainability, is accepted. The findings conclude that H2 is accepted. The results are consistent with the studies by Fletcher and Griffiths [17] and Che Omar, et al. [16].

The third objective of this study is to examine the influence of business innovation on SMEs sustainability during the COVID-19 pandemic. The outcome of the regression coefficient for business innovation shows a statistically significant positive relationship between business innovation and SMEs sustainability with (coefficient β = .307, t (132) = 3.26, p < .05). Since the p-value is less than the alpha value of .05, hypothesis 2 (H3), which states that there is a significant relationship between business innovation and SMEs sustainability, is accepted. The findings conclude that H3 is accepted. The results are consistent with the studies by Fitriasari [19] and Purnomo, et al. [4].

CONCLUSION

COVID-19 pandemic is a serious health issue that hit the world in this new era, bringing mankind to the stage that we never imagined before. The new variant of COVID-19, namely Omicron, brings this health issue into no way out from this disease. Small and Medium Enterprises (SMEs) are not exceptions; thus, SMEs need to adapt in conducting business in the new norm to maintain resilience and survive during the pandemic. Therefore, researchers take this opportunity to study how SMEs can sustain business during the pandemic. and explore more on the reason behind this decision.

The main objective of this study is to examine the influence of financial strategy, survival strategy, and business innovation on SMEs sustainability during the COVID-19 pandemic. Resource-Based View Theory is employed as the relevant perspective in supporting the view of independent variables towards SMEs sustainability. This study managed to distribute 200 sets of questionnaires to SMEs companies located in Kompleks PKNS Shah Alam (KPSA). In total, 132 respondents returned the questionnaire with completed answers, representing a 66% survey rate return. Regression analysis was performed in this study, and the results prove that the R-squared value shown is low, positive, and significant, and there is consistent variance with the value. 238, which indicates that about 23.8% of the variation in SMEs sustainability is explained by the variance of all three independent variables. The larger the R-squared value, the better the regression model of this study. Thus, the factors chosen are relevant for performing in this study.

This study examines the effect of financial strategy on SMEs sustainability in KPSA. Financial strategy was determined based on the statement as a company request for deferment of payment during the pandemic, the company hiring new workers during the pandemic, the company switching to other suppliers during the pandemic, and the company making price comparisons before purchases during the pandemic. Throughout this study it is found that financial strategy statistically has no significant relationship with SMEs sustainability. This study also examines the effect of survival strategy on SMEs sustainability during the COVID-19 pandemic. Survival strategy is the technique used by the SMEs owner to strengthen internal control. Survival strategy was determined based on the statement that the company relied on walk-in customers and accepted cash only before COVID-19, and during the pandemic, the company had knowledge about digital platforms, the company used digital platforms in business operations, and the company incurred additional costs for preparing IT facilities for business. This study found that survival strategy is also a significant factor in contributing to SMEs sustainability during a pandemic, and there is a statistically low positive relationship between survival strategy and SMEs sustainability. Finally, this study examines the effect of business innovation on SMEs sustainability during the COVID-19 pandemic. The pandemic has triggered the emergence of both new opportunities and new constraints for SMEs. Business innovation was determined based on the statement that the company always reviews business strategy during a pandemic, the company does cost-cutting during the pandemic, and the company makes product innovation during the crisis. This study found that business innovation is also a significant factor in contributing to SMEs sustainability during a pandemic, and there is a statistically low positive relationship between business innovation and SMEs sustainability.

In sum, the findings of this study help in terms of national budget allocation, where special allocation to help SMEs affected by the pandemic, allocation to help unemployed workers, allocation to upgrade broadband infrastructure, allocation to reduce tax rates for companies affected by the pandemic, and grants for start-up SMEs. The findings of this study can also contribute to more literature on national contingency plans during economic downturns so that the government can implement the best policies to guide and improve weaknesses and policy strategies of economic recession in Malaysia in the future.

ACKNOWLEDGMENT

The authors would like to thank the Faculty of Accountancy, UiTM for funding and support of this project.

REFERENCES

1. The World Bank, Small and Medium Enterprises (SMEs) Finance, 2021. https://www.worldbank.org/en/topic/smefinance
2. SME Corp, SME Definition, 2021. https://smecorp.gov.my/index.php/en/policies/2020-02-11-08-01- 24/sme-definition
3. M.Hamsal and M. Ichsan, “Business sustainability in the times of crisis: Propositions and framework,” IOP Conference Series: Earth and Environmental Science, vol. 729, no. 1, 2021. https://doi.org/10.1088/1755-1315/729/1/012049
4. B. R. Purnomo, R. Adiguna, W. Widodo, H. Suyatna and B. P. Nusantoro, “Entrepreneurial resilience during the Covid-19 pandemic: navigating survival, continuity and growth,” Journal of Entrepreneurship in Emerging Economies, vol. 13, no. 4, pp. 497–524, 2021. https://doi.org/10.1108/JEEE-07-2020-0270
5. V. K. Eswarlal and M. Vallesi, “Different stages of business sustainability: a visual metaphor,” Management Research, vol. 12, no. 3, pp. 308–325, 2014. https://doi.org/10.1108/MRJIAM-12-2013-0535
6. G. Gallopín, L. M. J. Herrero and A. Rocuts, “Conceptual frameworks and visual interpretations of sustainability,” International Journal of Sustainable Development, vol. 17, no. 3, pp. 298–326, 2014. https://doi.org/10.1504/IJSD.2014.064183
7. M. Hidayat, F. Latief, S. Bahasoan, A. Widiawati and D. A. Nianty, “Factors Influencing Resilience of Micro Small and Medium Entrepreneur (MSME) during COVID 19 Outbreak in South Sulawesi Province Indonesia,” TEST Engineering & Management, vol. 83, no. may-June 2020, pp. 26707-26721, 2020. http://www.testmagzine.biz/index.php/testmagzine/article/view/12646
8. M. K. Hu and D. M. H. Kee, “Fostering sustainability: reinventing SME strategy in the new normal,” Foresight, ahead-of-print, (2021). https://doi.org/10.1108/fs-03-2021-0080
9. S. Weaven, S. Quach, P. Thaichon, L. Frazer, K. Billot and D. Grace, “Surviving an economic downturn: Dynamic capabilities of SMEs,” Journal of Business Research, vol. 128, no. June 2018, pp. 109–123, D. 2021. https://doi.org/10.1016/j.jbusres.2021.02.009
10. C. Bryce, P. Ring, S. Ashby and J. K. Wardman, “Resilience in the face of uncertainty: early lessons from the COVID-19 pandemic,” Journal of Risk Research, vol. 23, no. 7–8, pp. 880–887, 2020. https://doi.org/10.1080/13669877.2020.1756379
11. A. de Waal and E. Mollema,” Six courses of action to survive and thrive in a crisis,” Business Strategy Series, vol. 11, no. 5, pp. 333–339, 2010. https://doi.org/10.1108/17515631011080740
12. M. Nurunnabi, “Recovery planning and resilience of SMEs during the COVID-19: experience from Saudi Arabia,” Journal of Accounting and Organizational Change, vol. 16, no. 4, pp. 643–653, 2020. https://doi.org/10.1108/JAOC-07-2020-0095
13. P. Tansey, J. P. Spillane and X. Meng, “Linking response strategies adopted by construction firms during the 2007 economic recession to Porter’s generic strategies,” Construction Management and Economics, vol. 32, no. 7–8, pp. 705–724, 2014.
14. T. K. Chan and A. R. Abdul-Aziz, “Financial performance and operating strategies of Malaysian property development companies during the global financial crisis,” Journal of Financial Management of Property and Construction, vol. 22, no. 2, pp. 174–191, 2017, https://doi.org/10.1108/JFMPC-02-2016-0009
15. D. O. Aghimien, E. I. Aghimien, A. O. Fadiyimu and T. F. Adegbembo, “Survival strategies of built environment organisations in a challenging economy,” Engineering, Construction and Architectural Management, vol. 25, no. 7, pp. 861–876, 2018. https://doi.org/10.1108/ECAM-06-2017-0106
16. R. Che Omar, S. Ishak and M. A. Jusoh, “The impact of Covid-19 Movement Control Order on SMEs’ businesses and survival strategies,” Malaysian Journal of Society and Space, vol. 16, no. 2, 2020. https://doi.org/10.17576/geo- 2020-1602-11
17. G. Fletcher and M. Griffiths, “Digital transformation during a lockdown,” International Journal of Information Management, vol. 55, pp. 102185, 2020. https://doi.org/10.1016/J.IJINFOMGT.2020.102185
18. Gregurec, I., Tomičić Furjan, M., & Tomičić‑Pupek, K, “The Impact of COVID‑19 on Sustainable Business Models in SMEs,” Sustainability, 13(3), 1098, 2021
19. F. Fitriasari, “How do Small and Medium Enterprises (SMEs) survive the COVID-19 outbreak?,” Research method, vol. 05, no. 02, pp. 53–62, 2020.
20. H. Chaarani, P. D. Vrontis, S. el Nemar and Z. el Abiad, “The impact of strategic competitive innovation on the financial performance of SMEs during COVID-19 pandemic period,” Competitiveness Review, 2021. https://doi.org/10.1108/CR-02-2021-0024
21. S. A. Alara, “Organizational characteristics and COVID-19 safety practices among small and medium construction enterprises (SMEs) in Nigeria,” Frontiers in Engineering and Built Environment, vol. 1, no. 1, pp. 41–54, 2021. https://doi.org/10.1108/febe- 02-2021-0006
22. P. J. DiMaggio and W. W. Powell, “The Iron Cage Revisited: Institutional Isomorphism in Organizational Fields,” American Sociological Review, vol. 48, no. 2, pp. 147–160, 1983. http://www.jstor.org/stable/2095101
23. U. Sekaran and R. Bougie, Research Methods for Business: A Skill-Building Approach. West Sussex: Wiley & Sons, 2016.
24. A, Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE Publications, 2013
25. F. Hair, W. C. Black, B. J. Babin and R. E. Anderson, Multivariate Data Analysis. New York: Pearson, 2010.
26. George and M. Mallery, SPSS for Windows Step by Step: A Simple Guide and Reference. Boston: Pearson, 2010.
27. B. Kline, Principles and practice of structural equation modeling. Guilford Press, 2005.
28. L. J, “Coefficient alpha and the internal structure of tests”. Psychometrika, 16(3), 297–334, 1951
29. IBM Corp., “Reliability Analysis: Data Considerations,” IBM SPSS Statistics Documentation, IBM Knowledge Center, 2020. https://www.ibm.com/docs/en/spss-statistics/28.0.0?topic=analysis-data-considerations.
30. Tavakol and R. Dennick, “Making Sense of Cronbach’s Alpha,” International Journal of Medical Education, vol. 2, pp. 53-55, 2011.
    http://dx.doi.org/10.5116/ijme.4dfb.8dfd
31. Schober, C. Boer and L. Schwarte, “Correlation Coefficients: Appropriate Use and Interpretation,” Anesthesia & Anesthesia, vol. 126, pp. 1763-1768, 2018. https://doi.org/10.1213/ANE.0000000000002864
32. E. Hinkle, W. Wiersma and S. G. Jurs, Applied Statistics for Behavioural Sciences. Chicago: Rand McNally College Publishing, 1998.