Introduction

Micro, small and medium-sized enterprises (MSMEs) were one of the sectors most affected by the measures taken during the Covid-19 pandemic (^{Fabeil et al., 2020}; ^{Kantis and Angelelli, 2020}; Fink et al., 2021; etc.). This situation has prompted the study of the key factors or determinants of company performance in the face of new challenges. The identification of these key aspects makes it possible to learn from past experiences and avoid situations of failure, as well as to design programs and measures to support MSMEs. For this reason, it is important to characterize the enterprises and identify the critical factors that have an impact on business survival and success in the post-pandemic period.

Much of the literature has focused on the study of business failure, emphasizing models that predict and rank firms rather than pointing to the elements that explain and distinguish successful firms from those that fail (^{Alaka et al., 2017}; ^{Scherger et al., 2018} and ²⁰¹⁹, among others). That is, most of the literature focuses on estimating the best indicators capable of predicting failure situations based on different methodologies. ^{Halabí and Lussier (2014)} review the main questions that the literature on the subject tries to answer and mention that the identification and measurement of critical success factors is an area of gap.

The objective of this paper is to identify the key determinants for the performance of MSMEs¹ in the Southwest of the province of Buenos Aires (Argentina) during the post-pandemic period, considering three possible scenarios: a good, a fair or a bad situation. As explanatory variables, selects a set of factors identified in the literature to explain business failure and firm performance. The characteristics of the MSMEs and of the owners, the strategies and practices implemented, the resilience capacity, the availability of financing and the impact of external factors outside the management of the MSMEs are considered. The data used in the study come from a proprietary survey of Argentinean MSMEs conducted during the months of July and August 2021. We propose the use of an Ordinal Logit model to assess the relevance of a set of factors on firm performance.

It is considered that this work makes an important contribution to the study of the subject because it uses data from a particular sample and because there are no similar works for this region of Argentina that study the incidence of the pandemic from the perspective of business failure.

The structure of the article is as follows: the first section presents the introduction to the subject and the objective of the paper; the second section presents a review of the literature related to business failure and the identification of key factors for the performance and survival of companies and in particular the specific aspects of the post-pandemic context. The third section presents the working hypotheses, data and methodology used. The fourth section shows the results obtained and the fifth section discusses the findings and then the conclusions of the work.

Literature review

^{Altman (1968)} defines failure as the end of the company's activity (or bankruptcy), referring to the moment in time when a marked change occurs that threatens the continuity of the organization. However, a crisis does not necessarily imply bankruptcy. A crisis can be a temporary situation in the life of a company, and in this case, the capacity to adapt and the strategies used to survive are central (^{Beaver, 1966}). Given this discussion on the definition of failure, authors such as ^{Lizano et al. (2010)} classify companies into several segments: i) companies with negative results (economic failure); ii) companies with negative net worth (financial failure); iii) companies in receivership (more acute financial failure); and iv) companies in bankruptcy (economic and financial failure). The Covid-19 pandemic revealed different scenarios for MSMEs, showing business opportunities and crisis situations that could lead to different trajectories, including insolvency and bankruptcy. Therefore, in this context it is relevant to study the causes of business failure (^{Argenti, 1983}; ^{Gabás, 1997}; ^{Ooghe and De Prijcker, 2008}) in a broad sense, considering the characteristics and behaviors of MSMEs to overcome the pandemic.

Most traditional models aim to determine the best economic-financial indicators or ratios capable of predicting insolvency situations in companies (^{Beaver, 1966}; ^{Altman, 1968}; among others). Over the years, efforts in the literature have focused on overcoming the methodological limitations of these models through the introduction of more sophisticated techniques and the use of other quantitative variables to improve the results of the estimates, identifying very few works that delve into the analysis of the causes of business failure, most of which are enunciative works that list the causes relevant to the analysis. The most relevant contributions are discussed chronologically below.

One of the first authors to work on the analysis of causes is ^{Argenti (1976} and ¹⁹⁸³⁾ who points out a set of relevant factors for the prediction of business failure. ^{Argenti (1983)} proposes an A-score to diagnose companies based on the assessment of causes and errors. Among the factors he identifies poor administrative management, a passive board of directors, competition, the weak role of the financial director, the absence of middle management, the lack of budgetary control, the absence of financial planning, the lack of accounting and the lack of response to change as the determinants of poor company performance. It also identifies errors related to high indebtedness, the development of projects beyond the company's possibilities and uncontrolled growth.

^{Gabás (1997)} then presents a list of the most common causes of business failure, distinguishing between internal, special and external causes. Among the external causes, he includes market factors (competition and falling demand) and those related to the economic and social environment (depressive phase, external crises and shocks, government policy and significant social changes). Internal causes include management inefficiency, wrong and inappropriate strategies, inefficiencies in the production system, bad investments, high indebtedness, problems related to bankruptcy costs, late payments, the age of the company and the stage in the life cycle of the product. Finally, special causes refer to the high mortality of start-ups and young companies during the first years of life.

From these early developments, other authors such as ^{McGahan and Porter (1997)} and ^{Rumelt (1997)} find that external factors are the ones that best explain the performance of firms, to the detriment of internal causes. Among these factors they identify changes in demand and market structure and variations in consumer preferences, rivalry among current and potential competitors, falling demand and technological uncertainty, among others. ^{Becchetti and Sierra (2003)} consider it convenient to include in the analysis of performance variables related to the organization’s strategy, for example, the competitive position, the degree of market concentration and the firm's level of exporting. Then, ^{Grunert et al. (2005)} highlight the importance of including age, type of business and sector in combination with economic and financial ratios as well as qualitative variables to explain failure.

^{Cardon et al. (2011)} carry out an analysis of the causes that can be controlled with respect to those that cannot be monitored by the company's management or the entrepreneur, and therefore assess the impact of external causes on factors internal to the organization. ^{Halabí and Lussier (2014)} estimate three categories of SME performance considering as variables the use of internet and networks, working capital, availability of financial and accounting information, planning, partner involvement, educational level, family management background and marketing to predict small business performance. On the other hand, ^{Scherger et al. (2014} and ²⁰¹⁵⁾ propose a formal framework for causal analysis through the integration of a fuzzy business diagnostic model and the balanced scorecard, which is used by firms for continuous business monitoring. They propose 72 causes distributed in 14 strategic areas of the firm (business learning, innovation and technology, labour, cost optimization, technical efficiency, purchasing policy, distribution and logistics, exogenous changes, commercial management, sector evolution, customer satisfaction, quality and prices, financial management, risk management and activity results) that allow identifying the area where the problem is registered and disaggregating until the specific cause is found. The causes and symptoms identified through the analysis are used to diagnose the economic and financial situation of enterprises and then to estimate the causes of business failure and/or performance.

^{Khelil (2016)} proposes three key categories of failure: external causes, factors linked to entrepreneurs' decisions and behaviors, and emotional causes. In addition, they identify five different profiles of entrepreneurs that could generate different entrepreneurial trajectories. Other contributions, such as ^{Amankwah-Amoah (2016)}, highlight the interaction between the firm's situation and external factors as a potentially robust explanation of entrepreneurial failure. On the other hand, ^{Eschker et al. (2017)} point to entrepreneurial experience, availability of external funds (from family or personal), mentoring, use of the internet for information and networking, having a clear business plan and marketing advice as the best indicators of success for rural entrepreneurs.

In turn, ^{Kücher et al. (2020)} suggest that internal firm attributes such as leadership, management, resources, capabilities and firm age are the root causes of business failure, ruling out the influence of external factors as the main causes of business failure or success. Along these lines, ^{Caballero-Morales (2021)} identifies that innovation and cost optimization were key aspects of business recovery in the post-pandemic recovery period. ^{Sanhokwe (2022)} also focuses on internal causes by studying the survival probabilities of MSMEs, incorporating the introduction of new and improved processes or products and services to reduce the probability of failure. In turn, ^{Heredia Bustamante et al. (2022)}, based on a study of Mexican SMEs, argue that entrepreneurs recognize that the implementation of innovative approaches in the accounting area of the organization can be a determining factor in consolidating a management focused on integrated accounting information systems, as well as for the generation of reports with reliable information that facilitates decision-making in highly complex contexts.

^{Molina-Sánchez et al. (2023)}, through a study of 1416 Mexican MSMEs, analyze the factors that determine the resilience of MSMEs and confirm that business management, innovation and access to finance have a positive and significant influence on their resilience. ^{García-Contreras et al. (2021)} find for a set of SMEs in Mexico and Chile that both the COVID-19 crisis and resilience factors have an influence on SME performance. Likewise, ^{Ponce Andrade et al. (2020)} analyze the fall in sales, lack of liquidity, paralysis of the supply chain and the absence of policies to support MSMEs as decisive factors in the mortality of companies in the pre- and post-pandemic period in Ecuador. All studies conducted for global and/or specific regions show the reaffirmation of the factors that explain failure, as well as the change of dynamics and the identification of other relevant factors as a consequence of the pandemic.

The Covid-19 crisis is considered one of the largest simultaneous economic and public health crises in recent history, leading to significant drops in consumption and employment worldwide (^{Wenzel et al., 2020}; ^{Meahjohn and Persad, 2020}; ^{Brown et al., 2020}; ^{Liguori and Pittz, 2020}; ^{Sharma et al., 2020}; ^{Fabeil et al., 2020}; ^{Donthu and Gustafsson, 2020}; ^{Baque-Cantos et al., 2020}). In response to the crisis, governments around the world adopted social distancing measures, closed borders and devised programs to support small and large businesses to heal the situation.

^{Portuguez and Gómez (2021)} present a review of the literature, analyzing the studies that link entrepreneurship, resilience and the post-pandemic crisis situation of companies. They highlight that resilience is a key capacity that allows firms to adapt and strengthen themselves in these situations and identify as factors of this capacity those related to the attitudes and strategies adopted in the face of the crisis, the characteristics of the business and the entrepreneur, relations with institutions, human and social capital and the strategic management of the business.

All these studies show that MSMEs were heavily affected by the pandemic and that firm performance is linked to multiple causes that interact to result in trajectories of success or failure.

According to the literature review in Table 1, the articles that refer to the determinants of entrepreneurial success and failure are presented.

Among them, ^{Gabás (1997)}, Madrid and García (2006), ^{Scherger et al. (2015)}, ^{Insights (2021)}, ^{Caballero-Morales (2021)} and ^{Sanhokwe (2022)} highlight the importance of innovation and technology activities, cost optimization, technical efficiency and improvements in quality and prices as relevant factors to avoid failure. Other authors (^{Lussier, 1995}; ^{Theng and Lim, 1996}; ^{Halabi and Lussier, 2014} and ^{Eschker et al., 2017}) highlight the incidence of business strategies for business development.

In the literature, financial resources are one of the most recognized constraints to business development, therefore, it is argued that the availability of financial sources improve the performance of MSMEs (^Argenti,1983; ^{Lussier, 1995}; ^{Gabás, 1997}; ^{Ghosh et al., 2001}; ^{Halabí and Lussier, 2014}; ^{Eschker et al., 2017}). Notably, ^{Sanhokwe (2022)} shows that capital injection improves firms' chances of survival after the pandemic.

In turn, ^{Argenti (1976)}, ^{Gabás (1997)}, ^{Scarlat and Delcea (2011)} and ^{Scherger (2015)} comment on the importance of flexibility in the structure of firms to respond to changes in the market; i.e. they highlight resilience as one of the determinants to improve the situation of firms. ^{Portuguez and Gómez (2021)} and ^{Kantis and Angelelli, (2020)} highlight that resilience is a key capability that allowed firms to become stronger in times of pandemics.

In terms of some authors, the management of a company is related to the manager's experience, planning, budget control, counselling, staff quality and networking (^{Gabás, 1997}; ^{Lussier, 1995}; ^{Ghosh et al., 2001}; ^{Ooghe and De Prijcker, 2008}; ^{Scherger 2015}; ^{Kücher et al., 2020}) as relevant for the success of an organization, considering that if the business management is orderly and adequate, it is possible that better strategic decisions are taken. On the other hand, some authors (^{Klyver et al., 2013}; ^{Khan and Vieito, 2013} and Brahma et al., 2019) consider that the gender of owners or managers affects the success of firms, identifying that women may have advantages in business management, through greater attention to detail, an interpersonal oriented approach, multitasking ability and greater risk aversion. However, barriers and inequalities have also been identified that limit women's participation and success in entrepreneurship through limited access to finance. Along these lines, other authors (^{Bhave, 1994}; ^{DeTienne and Chandler, 2007}; ^{Kautonen et al., 2011}) consider the effect of the age of owners and/or managers on the performance of MSMEs, although they argue that the relationship between the age of the manager and the success or failure of the firm is complex and depends on many other factors, such as previous entrepreneurial experience, education and entrepreneurial skills.

Likewise, the age and size of the firm (^{Dörr et al., 2022}) are also determinants of business success. ^{Kantis and Angelelli (2020)} identify that the firms most affected by the pandemic are younger firms, although they note that firms in the technology sector and some dynamic start-ups had less pronounced impacts than older firms.

On the other hand, the literature highlights the impact of external factors on the performance of MSMEs. These exogenous changes are considered by most authors studying the causes of business failure (^{Argenti, 1976} and ¹⁹⁸³; ^{Gabás, 1997}; ^{Scherger, 2015}; ^{Khelil, 2016}). ^{McGahan and Porter (1997)} and ^{Rumelt (1997)} mentioned that external factors best explain business failure, rather than internal causes that can be controlled by managers. In contrast, ^{Kücher et al. (2020)} suggest that internal causes are at the root of problems, dismissing the influence of external factors as primary causes of business failure or success. Given the importance of external factors, despite the discrepancies, it is proposed to consider in this variable the impact of the macroeconomic situation, the impact of measures triggered by Covid-19 and of public policy programs on firm performance.

All these causes mentioned in the literature are considered in order to investigate the trajectories (good, fair and bad) of MSMEs in the post-pandemic period with the aim of identifying the relevant aspects to survive, succeed or avoid failure. The present study is carried out on the basis of a specific survey designed to detect the characteristics of the enterprises and the manager/owner, the strategies used and the impact of external factors on the performance of the enterprises.

Working hypothesis, data and methodology

Based on the literature review and models that analyze the causes of business survival and failure, the following working hypotheses are presented. They reflect the expected impact of the variables analyzed on the post-pandemic situation of MSMEs.

H₁: Improvements in production and internal management processes, as well as increased resilience, improve the company's post-pandemic situation.

H₂: The incidence of macroeconomic environment factors and other exogenous variables affect the firm's post-pandemic performance.

H₃: Strategies implemented by MSMEs increase the likelihood of recording a good post-pandemic situation.

In our country, MSMEs are a major driver of economic activity and employment generation. However, it is known that in developing countries between 50 and 75% of enterprises cease to exist during their first years of life (^{Stam and Wennberg, 2009}).

In order to assess the impact of the pandemic and the implementation of palliative and strategic measures to boost activity, an exploratory analysis was carried out to detect the economic situation of MSMEs in the Southwest of the province of Buenos Aires (SOB), in Argentina. This region is composed, from a political/administrative point of view, of a group of districts comprising rural and urban areas, and its population centres range from small settlements to the intermediate city of Bahía Blanca. Furthermore, the region represents 25% of the territory of the province of Buenos Aires (^{Schroeder and Formiga, 2011}). It is characterized by an important petrochemical pole, a strong presence of agro-industrial and service companies; and represents a strategic node for the country's economic development given that it has the largest deep-water port in the country, and a road and rail transport system that allows the transport of goods to and from other areas (^{Elías and Barbero, 2017}).

The survey was conducted online, during the months of July and August 2021, using snowball methodology. Snowball sampling is a type of non-probability sampling used when potential participants are difficult to find or when the sample is limited to a very small subset of the population. The municipalities in the region, business chambers and entrepreneurs' groups collaborated in disseminating the survey. The localities that participated in the survey are: Bahía Blanca (85), Coronel Pringles (11), Coronel Dorrego (1), Coronel Rosales (26), General Lamadrid (1), Patagones (3), Pigüé (6), Puán (4), Tornquist (8), Tres Arroyos (3), Tres Lomas (1) and Villarino (2). Of the total number of responses, only 3 companies did not disclose their location.

The survey was carried out using a google form, guaranteeing the confidentiality of the data and used for research purposes. Of the 168 responses obtained, 154 active enterprises were identified and selected to assess the post-pandemic situation.

The application of Ordinal Logit models is proposed and the post-pandemic situation of MSMEs is selected as the dependent variable, grouped into 3 categories: good, fair and bad situation. ^{Long (1997)} points out that these models can be developed from a latent variable y^*, which is linearly related to the explanatory variables, through the structural model presented in (1).

The latent variable y^* (post-pandemic situation) is related to the observed variable yio through Equation (2):

Where, τ are the cut-off points to be estimated.

For the ordinal model, the dependent variable yio is defined as:

yi*=1, -if the MSME considers the post-pandemic situation to be good.

yi*=2, -if the MSME considers the post-pandemic situation to be regular.

yi*=3, -MSMEs consider the post-pandemic situation to be bad.

Much of the literature uses a traditional view of success as related to positive economic or financial performance, measured by some indicator. However, there is a recent trend to measure performance based on the opinion of the owner or manager of the company, especially in SMEs that are not required to file financial statements (^{Wang, 2008}).

Given the proposed segmentation, the sample is divided into 79 MSMEs belonging to the good situation (yi*=1), 53 that say they are in a fair situation (yi*=2) and 21 MSMEs that consider the situation to be bad (yi*=3).

Considering the hypotheses put forward, the independent variables relevant to success and/or survival are presented. In the analysis, ordinal scale variables, continuous variables and dichotomous variables are used. In the case of the scale variables, they are measured through linguistic labels grouped into 4 ordinal categories (Very much: 1; Quite a lot: 0.75; Little: 0.5; Almost nothing: 0.25) that reflect the opinion of the MSME entrepreneurs regarding the incidence of the different factors on the performance of the company. The labels were applied following ^{Zimmermann (1991)}, who argues that the highest values correspond to the causes or factors with the highest incidence. First, a set of linguistic labels are selected so that experts can assess the existence of each cause. Then, the linguistic labels are translated into a quantitative scale that shows the incidence of each cause calculated through the cumulative frequency for the scale defined in each case.

Table 2 describes the variables selected for the estimation of the models and the description of the issues assessed in each of them.

Results

Discussion of the results

The results obtained in model 1 confirm that improvements in the production process increase the likelihood of MSMEs to belong to group 1, highlighting the importance of innovation activities and technical efficiency (^{Insights, 2021}; ^{Caballero-Morales, 2021}; ^{Sanhokwe, 2022}). ^{Eschker et al. (2017)}, ^{Kücher et al. (2020)} and ^{Portuguez and Gómez (2021)} highlight the importance of management for the development of MSMEs, noting that firms that are more likely to belong to group 1 in the post-pandemic have more capable owners or managers with more experience in managing the firm.

Particularly in the context of the pandemic, several papers comment on the importance of the adaptability and flexibility of the company to overcome the crisis (^{Pedroni, 2022}; ^{Izquierdo, 2021}; ^{Caballero-Morales, 2021}; ^{Portuguez and Gómez, 2021}). This capacity for resilience to respond to unexpected market changes has a significant impact on the success of MSMEs and increases their chances of belonging to group 1.

In turn, as observed in model 3, size (measured through the variable Nivel_Fact) positively affects the probability of showing a good post-pandemic situation (^{Dörr et al., 2022}). The same is reflected in the firm's age variable (^{Gabás, 1997}; ^{Berger and Udell, 1998}; ^{Guercio et al., 2019}; ^{Kantis and Angelelli, 2020}) since older MSMEs are more likely to experience a good stage because they have experience that allows them to overcome those factors that alter the functioning of the firm.

On the other hand, the availability of funding sources (Financing) did not show the expected sign. In this case, the greater availability of sources of finance reduced the chances of a good post-pandemic situation. The public support variable, which represents the support programs provided to MSMEs in the context of the pandemic, behaved similarly. These results confirm that those companies in the sample that received either more funding or more aid, given the risk taken, were not able to compensate for their economic-financial situation. In developing countries, particularly in Argentina, according to ^{Corzo et al. (2022)} the financial instruments available to MSMEs are scarce and require high reporting requirements and are difficult to comply with.

MSMEs in the context of the pandemic had to apply various strategies to overcome the crisis, including the incorporation of new technologies, remote work and digitization of processes, among others. In summary, the post-pandemic presented both challenges and opportunities for companies, with those that were able to be flexible and adapt quickly to changes in technology, human capital, finance and innovation being better positioned to overcome the new challenges.

Conclusions

The study proposes to identify the key variables that affect the performance of MSMEs in the post-pandemic period. Based on the literature on business failure and business diagnostics, the relevant variables for the analysis are detected and working hypotheses that reflect the incidence of the different factors on the performance of the firms are proposed. Ordinal Logit models are estimated to show the probability that MSMEs belong to different groups, good, fair and bad trajectories, considering post-pandemic situation as the dependent variable.

Four models are presented, identifying that the significant variables for firm performance are those linked to issues inherent to entrepreneurial capabilities and skills, to aspects related to efficiencies in the production process, to flexibility and resilience, to the availability of finance, to the size and age of the firm, and to the age of the owner/manager.

According to the results obtained, those MSMEs that have less management capacity, are less resilient, of smaller size and age, and with young owners or managers, are more likely to end up in a bad situation despite implementing new strategies and tools during the pandemic. Therefore, the marginal effect of firms' ability to react and resilience to adapt to the new reality is highlighted as a determinant of post-pandemic performance. The results confirm the view of ^{Kücher et al. (2020)}, among other authors who suggest that internal causes are at the root of the problems while dismissing the influence of factors external to the firm.

The identification of these factors is of vital importance for the design of support programs that enhance the success and survival of MSMEs, which are indispensable agents for achieving economic growth.

This article is novel in its application to the subject and given the use of its own database focused on a particular region, its results are not generalizable. As future lines of research, it is proposed to delve deeper into the problems and strategies implemented in a broader sample, as well as to consider economic and financial indicators that allow for the identification of other performance measures.