INTRODUCTION

The economic repercussions of the crisis triggered by the COVID-19 pandemic have been unprecedented in the last two centuries. In a very short time, virtually all countries were forced to adopt emergency health measures and mobility restrictions, which significantly impacted the daily lives of companies. At the same time, different governments were forced to adopt public policies of a heterodox nature aimed at maintaining employment and income levels and stimulating productive initiatives. Companies, in turn, in addition to being forced to quickly empty physical workspaces, began to face new challenges caused, for example, by interruptions and compromises in logistics and supply chains.

We live in a world in crisis, with profound repercussions on business life. From an organizational perspective, the crisis would be "a sudden and unexpected event that threatens to disrupt an organization’s operations and poses both a financial and a reputational threat" (Coombs & Holladay, 2010, p. 163). Scenarios of this type tend to induce companies to adopt procyclical strategies involving reducing operations and cutting costs and investments (Tellis & Tellis, 2009). However, other organizations can see, precisely in times of crisis, good opportunities, such as lower investment costs. Strategies in this direction are called countercyclical (Navarro et al., 2010).

The literature has extensively explored procyclical strategies (Kaszowska-Mojsa, 2020; Larson & Vieregger, 2021). However, studies that associate the influence of procyclical and countercyclical strategies with organizational performance are still rare (Conti et al., 2015). However, studies that associate the influence of procyclical and countercyclical strategies with organizational performance are still rare (Herbane, 2019), in small and medium-sized companies (SMEs), in turn, such research is practically unexplored.

A better understanding of this context is fundamental. Indeed, around 98% of companies in Brazil are micro and small, “more susceptible to market fluctuations and the fragile economic situation, exposing them to risk situations” (Nassif et al., 2020, p. 3). The lack of studies on procyclical and countercyclical strategies is even more evident when considering their adoption in crisis contexts. Searching for articles by title, abstract, and keywords in Scopus and Web of Science, no papers were found that sought to understand the impact of adopting both strategies on the performance of small and medium-sized companies in the face of the Covid-19 crisis. This article, seeking to fill part of the research gaps, proposes to answer the following question:

RQ1: What is the impact of procyclical and countercyclical strategies on the performance of small and medium-sized companies in Minas Gerais in the last 24 months (between 2019 and 2020)?

The sample consisted of 118 micro, small, and medium-sized companies in Minas Gerais, Brazil, which allows extrapolation of the results to the universe of interest. The base literature on procyclical and countercyclical strategies supported the reflections. While studies that associate both strategies limit the categories of analysis to marketing, R&D, or capital expenditures (Navarro et al., 2010). This article associates eight categories to the empirical analysis of the study: i) recruitment; ii) production; iii) purchases; iv) marketing; v) prices; vi) innovation; vii) credit policy; and viii) investments. In doing so, it allows for essential contributions. In theory, it responds to recent calls that highlight the need for more research on organizational performance in times of crisis (Chabossou et al., 2021; Martínez Serna & García Guerra, 2021; Nyikos et al., 2021; Rababah et al., 2020). In addition, expanding the categories of analysis allows for a more integrated understanding of coping strategies. From a practical-political point of view, this article allows entrepreneurs and public policymakers to learn about the best strategies to be adopted in pandemic contexts. Furthermore, the regression model presented here can be helpful for managers to calibrate their strategies, prioritizing the factors with the most significant impact on organizational performance.

THEORETICAL FOUNDATION

Identification and management of organizational crises in small and medium-sized enterprises

In general, organizational crises have four characteristics: i) sources of uncertainty, interruption, and change (Bundy & Pfarrer, 2015); ii) harmful or threatening to organizations and their stakeholders, many of whom have conflicting needs and demands (Kahn et al., 2013); iii) behavioral phenomena, socially constructed by actors (Coombs & Holladay, 2010), and; iv) Part of more effective processes, instead of discrete events (Jaques, 2009). On the one hand, the literature suggests that small and medium-sized companies are more vulnerable to crisis events (Kurschus et al., 2015). This is because such companies often suffer financial losses, reductions in sales volume, inability to fulfill contract terms, cash deficits, and even business closures (Arellano & Mendoza, 2019; Doern, 2016; Wille et al., 2017).

On the other hand, due to the smaller size and level of bureaucracy, authors point out how SMEs can have advantages in terms of flexibility, learning capacity, and innovation, among others (Bonatto et al., 2020; Cantele & Zardini, 2018; Chawinga & Chipeta, 2017). The literature suggests different strategies for overcoming crises, such as innovation in product planning, alliances with suppliers, information management, and adaptation of their business models (Crick & Crick, 2020; Liu et al., 2017; Okoli & Watt, 2018).

Crisis coping strategies

The literature on coping with crises is part of two fundamental perspectives. The first is internal, and the second is external (Bundy & Pfarrer, 2015). The first focuses on dynamics from within the organization. It concerns risk management, complexity, and technology (Borisova et al., 2019; Gephart Jr. et al., 2009; Kiselitsa & Shilova, 2016). In this perspective, management involves the design of organizational structures to prevent the occurrence, reduce the impact, and promote learning from the crisis. The second focuses on organizations' interactions with external actors. It considers that crisis management involves coordinating with stakeholders to prevent, resolve, and exit crises (Conti et al., 2015; Kaszowska-Mojsa, 2020; Larson & Vieregger, 2021; McClelland & Rust, 2018).

Procyclical and countercyclical strategies in crisis contexts

Procyclical strategies follow the market trend (Casillas et al., 2019; Mann & Byun, 2017; Rico et al., 2021). Given the demand reduction, increased competition, and uncertainty, companies usually adopt such strategies amid crises. They aim at market survival and involve initiatives such as cutting costs (Bromiley et al., 2008; Casillas et al., 2019; Rico et al., 2021) and investments (Conti et al., 2015). In turn, countercyclical strategies involve, even in crisis contexts, the search for opportunities in a more offensive way. Latham and Braun (2011) have emphasized the positive relationship between countercyclical strategies and performance. Such strategies include maintaining or increasing investments, staffing, among others (Bromiley et al., 2008; Conti et al., 2015). The literature, which associates both strategies, usually limits the categories of analysis to marketing, R&D, or capital expenditures (Navarro et al., 2010). Innovatively, this article expands the categories to eight dimensions: i) recruitment; ii) production; iii) purchases; iv) marketing; v) prices; vi) innovation; vii) credit policy; and viii) investments.

The first dimension is recruitment, whose strategies are usually procyclical. While in periods of economic expansion, companies invest in hiring professionals, in times of recession, they usually try to stabilize themselves through initiatives such as employee layoffs (Latham & Braun, 2011). However, Piccarozzi et al. (2021) have emphasized how companies that adopt countercyclical recruitment strategies can benefit. By avoiding layoffs, such companies boost employee morale, for example. In this sense, instead of worrying about job security, these professionals focus on their tasks, maintaining and increasing productivity. In addition, companies can also benefit from hiring professionals with lower wages, given the greater availability of labor in recessionary periods (Hall, 2005).

The second dimension is related to production, with usually procyclical strategies. In periods of retraction, sales generally decrease, stimulating companies to reduce production to dispose of available stock (Zarnowitz, 1985). However, a countercyclical strategy of increasing production may be appropriate in such contexts. For example, to avoid the shortage of products, usually seen when the market recovers, companies can invest in production, seeking opportunities related to earning revenue and market share in the economic recovery (Bromiley et al., 2008). Furthermore, during recessions, companies can take advantage of lower labor and material costs (Conti et al., 2015).

The third dimension refers to purchases, which are also procyclical. As recessions reduce demand, companies use fewer inputs, some of which are eventually available in stock. In this sense, organizations reduce purchases to reduce storage costs (Apaydin, 2011). However, increasing purchases (countercyclical strategy) during recessions allows companies to take advantage of lower prices and better supplier credit conditions (Conti et al., 2015). The fourth dimension is mainly associated with marketing, advertising, and promotion strategies. Characteristically procyclical, companies typically invest in advertising and promotions in market expansions, cutting them in periods of contraction (Apaydin, 2011; Srinivasan et al., 2011). Despite this, Ang et al. (2000) and Conti et al. (2015) advocate more aggressive advertising investment in times of crisis. This is because media companies offer more attractive rates, as most companies reduce investments of this kind. The authors point out that companies that advertise obtain the greatest return on their investments during periods of recession.

The fifth dimension is price. On the one hand, in crisis contexts, companies observe more significant pressure to reduce their prices, given the decrease in consumer purchasing power (Ang et al., 2000). Economic theory suggests that companies respond to reduced demand by lowering prices. However, marketing studies warn that such cuts can reduce the brand's value, hindering its long-term positioning (Latham & Braun, 2011). Furthermore, research demonstrates how consumers expect lower prices to continue after the economic recovery, reducing long-term revenues (Apaydin, 2011). Evidence shows companies do not change their prices in recessions (Geroski & Gregg, 1993), even raising them on certain occasions (Lamey et al., 2012).

The sixth dimension involves innovation. Pressured to control costs during recessions, companies often reduce research and development (R&D) programs, increasing short-term cash flow (Srinivasan et al., 2011). However, when they adopt countercyclical behavior, adding new features and updating their products, for example, such organizations can generate better performance by meeting new demand patterns in such contexts (Apaydin, 2011). In addition, companies can also take advantage of lower costs to achieve higher returns on their R&D investments. The penultimate dimension is related to credit policy. In recession contexts, due to lower profits, companies face cash flow challenges and reduced bank credit (Ivashina & Scharfstein, 2010). In such scenarios, it is common for customers to request flexibility in payment terms (Ang et al., 2000). In order to maintain sales, companies usually succumb to the pressures, expanding their credits. However, they can monitor their customers' performance (countercyclical strategy), adjusting credit or collections depending on conditions (Sibony et al., 2009).

The last dimension is that of investments, restricted in recessive periods. Latham and Braun (2011) emphasize how companies sell assets to stabilize their finances in such scenarios (procyclical). If, on the one hand, this pattern can lead to overinvestments with consequent excess production capacity during the recovery, it can, in turn, imply the need for exaggerated cuts during recessions (Apaydin, 2011). On the other hand, companies that take advantage of lower prices during recessions to invest in fixed assets, for example, can guarantee adequate capacity and modern equipment. Such a strategy helps organizations offer superior products and gain market share in the recession and its subsequent recovery (Bromiley et al., 2008). Table 1 presents a summary of the dimensions of interest and the pro and anti-cyclical initiatives:

Table 1
Dimensions of interests and their pro and counter-cyclical strategies
Note: Elaborated by the authors.

The literature generally supports that countercyclical strategies related to the dimensions of interest here (Recruitment, Production, Purchases, Marketing, Prices, Innovation, Credit, and Investment) are associated with superior performance. According to Lopes and Carvalho (2021), “results regarding organizational performance are associated with technical evolution, innovation and the quality of human, structural and relational factors”. For this work, the performance of micro and small-sized companies will be considered based on their productivity, profitability, and billing (Sá & Amorim, 2018). Analogously, it is assumed that procyclical would be associated with lower performanc. Figure 1 illustrates the conceptual model of this study.

Figure 1
Conceptual model
Note: Elaborated by the authors.

METODOLOGIA

Demographic profile and sampling design

The research universe involves micro, small, and medium-sized enterprises (MSMEs) in Minas Gerais, Brazil. The population of MSMEs in Minas Gerais is 1,914,064, of which 1,775,694 are micro-enterprises, 63,610 are small-sized companies, and 74,760 are medium-sized companies (Sebrae, 2020). The sample was stratified by size within each stratum; the selection was made by simple random sampling, calculated considering a 90% confidence interval, with an error margin of 8%, resulting in a total of 118 companies (Cochran, 1977).

Questionnaire

The research allowed the elaboration of a collection instrument with 20 structured questions derived from the conceptual model. Two blocks were part of the questionnaire. In the first, the questions were related to the characteristics of the companies. In the second, the questions aimed at information on how the Covid-19 crisis impacted companies, according to the eight thematic dimensions of interest. The statements were based on the literature on crisis management and coping strategies for content validation. Following Perrien et al. (1984), the researchers initially used a representative number of closed-question options to cover the answers. In addition, questions strictly related to the research topic were applied. The implications of the questions were considered in the tabulation and data analysis procedures.

Pre-test

The pre-test considered clarity and precision of terms, number of questions, form, order, and introduction (Gil, 2002). Telephone interviews conducted with 15 entrepreneurs operationalized the pre-test. The number of respondents met the criteria suggested for the stage (Malhotra, 2011). The procedure served to evaluate the electronic platform in terms of public acceptance and assess the respondents' understanding of the statements.

Data collection

The companies were contacted through an online platform, operationalized by sending e-mails and a telephone survey. The structured interviews took place between February and May 2021. It is noteworthy that confidentiality was maintained. Free and informed consent was established in the register on the virtual platform used in the study. A team of experienced professionals carried out the collection: three researchers, one coordinator-supervisor, and two technicians. We carried out the following practices to verify the quality of data collection: i) audit of transcripts of electronic forms; ii) call the interviewees to confirm information; and iii) assessment of full completion of the forms, as recorded in the electronic research system.

Nonresponse and common method bias

In order to verify the occurrence of common method bias, the single-factor Harman test was performed (Podsakoff et al., 2003). When the explained variance of the factor analysis does not exceed 50%, the common method used in data collection does not deserve concern (Podsakoff et al., 2003). Using the SPSS® v.25 software, the principal components extraction method and the unrotated factorial solution were adopted. The result showed a variance of 35.87%; therefore, no significant evidence of common method bias was found.

Measuring instruments

The reliability of the scales was performed using Cronbach's Alpha Coefficient (α) (Malhotra, 2011). Landis and Koch (1977) establish that the internal consistency of the scales is acceptable at values above 0.61. In this research, the coefficient obtained was 0.724. In addition, we assessed the existence of missing data, suspicious response patterns, outliers, and linear response patterns (straight lining), which may indicate acquiescence bias (Podsakoff et al., 2003). To verify outliers, the univariate analysis admitted values greater than four standard deviations as a reference for characterizing an atypical observation (Hair et al., 2013). The researchers developed indices to measure countercyclical or procyclical strategies, making it possible to verify the initiatives to face the crisis implemented by companies. These indices were operationalized through questions on a Likert scale. The questions were grouped into nine key categories, including performance (Table 2).

Table 2
Questions according to variables of interest
Note: Elaborated by the authors.

The questions mentioned above, grouped in the mentioned categories, are made up of specific questions for each element of interest; for example, the performance category made up of question P1 (indicate how the current COVID-19 crisis has impacted the following indicators), has an intensity check at the levels: 1.1) productivity, 1.2) profitability and 1.3) billing, using a scale that varies between negative and positive impact. The other questions were also elaborated on using intensity scales.

The researchers conducted normality and correlation tests between each category and the performance variable, verifying statistical significance. Afterward, multiple linear regression analysis associated with the t-test was performed. The objective was to verify whether the variables of interest explain the variations in performance to obtain the equation for the model. In this sense, we propose hypothesis H1:

H1: Companies that practice countercyclical strategies for each category perform better than companies that practice procyclical strategies during the COVID-19 crisis.

Data analysis

The analysis was multidimensional data (Hair et al., 2013). The data provided by the questionnaire were grouped according to analysis categories and based on questions structured on a Likert scale. We analyzed the aggregated results statistically, as the total response is not entirely proportional to the population. The statistical tests and contrasts carried out in the subsequent phases of the analysis had levels of significance or degrees of precision determined from the data effectively obtained in the research, that is, disregarding “absent” answers and according to the statistical techniques used and the established level of aggregation in each situation.

RESULTS

Of the entrepreneurs, 75.2% are men, 24.8% are women, and 51.3% are microenterprises (Padovez-Cualheta et al., 2019). In addition, 75.2% have higher education. Regarding the period of operation, 47% are less than five years old, 66.4% are less than ten years, and 79.2% are less than 20 years. Table 3 shows the composition of the sample.

Table 3

Sample

Table 3
Sample
Note: Elaborated by the authors based on the research data.

The Shapiro-Wilk test was performed from the data for sample normality, obtaining a p-value<0.05. Spearman's correlation was used based on the sample size, obtaining data described in Table 4.

Table 4
Spearman correlation for the variables of interest
Note: ** The correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Research data. Elaborated by the authors based on the research data.

There is a positive correlation between performance and dimensions of countercyclical strategies and a negative correlation between performance and procyclical ones. The categories with the highest correlation (closer to 1) are countercyclical human resources, marketing, and production. The countercyclical strategy of maintaining prices was positive, along with the credit policy. For the correlation analysis, the classification proposed by Cohen (2013), was adopted, in which values below 0.30 are considered small; between 0.30 and 0.49, moderate; and equal to 0.50, large. The method of multiple linear regression was used to verify whether the categorical variables predict oscillations in performance, obtaining a mathematical model of this relationship. The model's output variable (dependent) was performance, and the predictor variables (independent) were recruitment, production, purchases, marketing, prices, credit policies, and investments. Table 5 presents the forward method, in which each variable was inserted in turn. The model with all variables had a higher adjusted R² of 0.642 and R of 0.818, indicating its ability to explain 64% of variations in performance; the better, the closer the R is to 1.

Table 5
Model summary
Note: Elaborated by the authors based on the research data.

When submitting the model to the ANOVA test (Table 6), observa-se p-valor<0,05, indicando ajuste diferente de modelo sem nenhum previsor; tal resultado levou à conclusão que inclusão de categorias analíticas melhoram o modelo.

Table 6
Anova
Note: Elaborated by the authors based on the research data.

The analysis resulted in a statistically significant model [F(8.99)=24.962; p<0.001; R²=0.669]. However, when checking the t-test for each variable, it was observed that the results varied for each category. Some categories presented p-value>0.05, not rejecting the null hypothesis that the components were randomly generated. In this sense, a new model excluding such variables was processed, keeping only those related to production, price, HR, marketing, and investments. When subjected to multiple regression, we found a higher adjusted R² of 0.634 and R of 0.807, explaining about 65.1% of the variance in performance (Table 7).

Table 7
Final model summary
Note: Elaborated by the authors based on the research data.

When submitting the model to the ANOVA test, the p-value<0.05 indicates validity as a predictor (Table 8).

Table 8
Final model ANOVA
Note: Dependent variable: Performance. Predictors: (Constant), Price, HR, Marketing, Production, Investments. Elaborated by the authors based on the research data.

The authors also verified collinearity statistics (Table 9). We sought to observe whether the tolerance values for each category were more significant than 0.1 and the VIF values less than 9, characterizing the absence of multicollinearity. Regarding the residuals, we identified the existence of outliers.

Table 9
Coefficients
Note: Dependent variable: Performance. Elaborated by the authors based on the research data.

The production strategies (β=0.181; t=2.738; p<0.05); recruitment (β=0.405; t=6.148; p<0.05); marketing (β=0.344; t=5.482; p<0.05); prices (β=-0.244; t=-4.077; p<0.05), and investment (β=0.181; t=2.917; p<0.05) are performance predictors. The model equation is given by y=0.343 + 0.214(Production) -0.180(Price) + 0.480(RH) + 0.214(Marketing) + 0.154(Investment). Thus, despite the positive correlation between countercyclical strategies and performance and a negative one between procyclical strategies and performance (Table 4), at a statistical significance level of 0.05, only the production variable (countercyclical), HR (countercyclical), marketing (countercyclical), prices (procyclical), and investment (countercyclical) are performance predictors and procyclical pricing strategies negatively interfere with it.

Discussion

This study investigated the dimensions of recruitment, production, purchases, marketing, prices, innovation, credit, and investments, starting from the hypothesis that countercyclical strategies perform better in times of crisis (Bromiley et al., 2008; Conti et al., 2015). In recruitment, it was found that companies that avoided layoffs (Hall, 2005; Piccarozzi et al., 2021) performed better (ρ=0.614 and p-value<0.01). In addition, the more companies invested in employee satisfaction, taking advantage of available labor, the more outstanding the performance (β=0.405; t=6.148; p<0.05). Spearman's correlation tests and t-test results confirmed the hypothesis that the countercyclical recruitment strategy performs better (Bromiley et al., 2008; Conti et al., 2015).

Countercyclical production strategies also showed a positive correlation with performance (0.507) and significance at the 0.01 level (β=0.181; t=2.738; p<0.05) (Bromiley et al., 2008). When verifying whether companies increase purchases, taking advantage of the favorable conditions of their suppliers (Conti et al., 2015), a positive correlation with performance (0.386) is observed. However, the t-test showed significance above 0.05, concluding that the countercyclical purchasing strategy does not predict superior performance. Concerning countercyclical marketing strategies, maintaining and investing more aggressively in advertising and promotion initiatives are positively associated with performance (0.524, p-value<0.01) (Ang et al., 2000; Conti et al., 2015). The t-test showed significantly lower than 0.05, indicating performance prediction (β=0.344; t=5.482; p<0.05).

The correlation between procyclical pricing strategy and performance was negative (-.0196, at a significance level of 0.05). Although the intention to lower prices seeks to increase sales (Ang et al., 2000), such a strategy is associated with lower performance. Data suggest the possibility of depreciation of the company's positioning in the long term (Latham & Braun, 2011). In other words, the lesser the use of the price reduction strategy (procyclical), the greater the performance will tend to be (β=-0.244; t=-4.077; p<0.05). As for innovation, the countercyclical strategy presents a positive correlation (0.422, significance level of 0.01). However, the t-test showed a p-value greater than 0.05, denoting a non-prediction of performance. Concerning credit policy, the procyclical strategy of extending customers' payment conditions (Ang et al., 2000), common in times of crisis, showed a negative correlation (-0.035). The t-test also showed no prediction (p>0.05). This result indicates that extending payment terms (procyclical strategy) does not present significant differences in performance. Finally, the countercyclical investment strategy (Bromiley et al., 2008) showed a positive correlation (0.391, significance level of 0.01), indicating that the more significant its use, the greater the performance (β=0.181; t=2.917; p<0.05).

The study results align with recent studies on strategies used by companies during the pandemic. Wenzel et al. (2020) suggest that perseverance and innovation strategies are more effective than cost containment and investment strategies. In this direction, Klyver and Nielsen (2021), when analyzing the performance of Danish SMEs, realized that containment strategies are less effective than containment and innovation strategies. Nevertheless, Kuckertz et al. (2020), Ma and Zhang (2022) and Kusa et al. (2022), reinforce the need for a quick and resilient posture in times of crisis, and Eggers (2020) for innovation and strategic orientation, to the detriment of everyday strategies of coping.

CONCLUSIONS

Theoretical and methodological implications

This study presents essential contributions. By associating still new dimensions, such as HR, marketing, and production, among others, this article helps to fill gaps associated with, even today, a lack of work that seeks integrated models capable of better understanding the impact that crises, such as COVID-19, generated in business management involving specific areas (Piccarozzi et al., 2021). Indeed, by expanding the analysis beyond the traditional categories of marketing, R&D, capital expenditures (Navarro et al., 2010), billing, and capital (Conti et al., 2015), this article allows for a more integrated understanding of the variables that impact business performance.

Practical implications

Initially, this article emphasizes the importance of MSMEs' better understanding of different crisis coping strategies. The proposal of a model that integrates several variables, such as those proposed here, can help them in this direction. Indeed, knowledge of these strategies and their relationship with organizational performance can help managers formulate initiatives that allow superior performance even in crises. Furthermore, by demonstrating that cuts in investments in marketing and other areas produce adverse effects on performance and that organizations benefit by keeping employees instead of firing them, this study sheds light on the relevance of countercyclical strategies, which still need to be explored. Finally, the regression model proposed here can be a valuable tool for managers to calibrate their initiatives to face the crisis, prioritizing factors of greater productivity in performance.

Implications for public policies

As mentioned, different governments began to adopt less restrictive or orthodox economic policies associated with maintaining minimum income levels for the population and support for the productive sector. In line with such policies and considering possible benefits arising from adopting countercyclical strategies, development agents could create mechanisms to encourage the adoption of strategies of this type (whether for investment, job creation, etc.) in companies in critical sectors. The results benefit the company and, consequently, the productive sector as a whole.

Limitations

This study has limitations. The first is related to the cross-sectional analysis of performance. The study addresses the immediate returns of the countercyclical and procyclical strategies investigated here. However, some strategies may have a long-term effect, which can be better observed in a time horizon longer than that understood in this work. Another limitation is presumed causality. It was hypothesized that countercyclical strategies promote superior performance. However, reverse causality cannot be ruled out. That is, superior performance may have influenced the choice of countercyclical strategy. Thus, this study confirms the association between the variables, not their causality.

Suggestions for future research

New research could investigate the influence of entrepreneurs' cultural characteristics on the choice of countercyclical investments during recessions. In addition, some variables, such as countercyclical innovation strategies, countercyclical purchases, and procyclical credit policy, did not predict performance, representing research opportunities. To that extent, such strategies appear to have resulted in long-term horizons; longitudinal studies are shown to be necessary (Hair & Fávero, 2019).

Acknowledgments

We thank the partnership of the Iberoamerican Observatory of MSMEs linked to FAEDPYME.

Conflit of interest statement

The authors declare that there is no conflict of interest.

Authors’ statement of individual contributions

Note: Acc. CRediT (Contributor Roles Taxonomy): https://credit.niso.org/

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Author notes

wilquer1@hotmail.com

Additional information

JEL classification:: L10, L00, H12, C21, L26, L25

Article ID:: 2399

Editor-in-Chef1 or Adjunct2:: ¹ Dr. Edmundo Inácio Júnior, Univ. Estadual de Campinas, UNICAMP

Associate Editor:: Dr. Cristiano Morini, Univ. Estadual de Campinas, UNICAMP

Executive1 or Assistant2 Editor:: ² M. BA. João Paulo Moreira Silva

How to Cite:: Ferreira, W. S. de S., Vale, G. M. V., & Andrade, N. A. de. (2023). Procyclical and countercyclical strategies in MSMes performance in a crisis context: A study based on the COVID-19 pandemic. REGEPE Entrepreneurship and Small Business Journal, 12(2), e2311. https://doi.org/10.14211/regepe.esbj.e2311

Related item (isTranslationOf):: https://doi.org/10.14211/regepe.esbj.e2311