Keywords

1 Introduction

The COVID-19 pandemic has affected firms’ businesses around the world and caused crises in the corporate sector. Previous research on such crises is relatively limited. However, studies have focused on how future crises can be detected in advance and whether operations can be adapted to the conditions that apply during ongoing crises. Studies of crises have mainly been concerned with negative effects caused by economic downturns, financial crises or natural disasters. However, the current pandemic is in many respects radically different from previous crises. COVID-19 has so far led to major restrictions on the functioning of society, partly because the business community has been given limited opportunities, and partly because powerful obstacles have been created that prevent civil society from functioning effectively.

The initial weeks of the pandemic meant that both demand and supply in the corporate sector were suddenly significantly reduced, and it was essential for many companies to implement cuts in operations. For smaller companies with limited resource potential, it became necessary to generate a range of different complementary efforts to cope with the first phase of the crisis, such as using previously accumulated resources but also actively using their corporate network for resource exchange and increased collaboration. The perspective at this time, however, was that these would be efforts to survive in the short term and that everything would soon return to normal. It has now been shown that significantly more sustainable efforts were needed, such as postponing ongoing investment projects as well as utilizing the support programmes that were gradually established during the first six months of the pandemic (Wenzel et al. 2020; Thorgren and Williams 2020). The crisis has reduced the opportunities to run efficiently commercially oriented operations at full scale, but it has also opened up new business opportunities. An example of this is “effectuation”, whereby companies that are in development processes do not necessarily have to adhere to an original business idea but can continuously develop the ability to change tracks and seek new business solutions, thus taking small steps to successfully manoeuvre in a turbulent and insecure environment (Sarasvathy 2001; Reymen et al. 2015).

This chapter reports on how companies have coped with the first six months of the COVID-19 pandemic. The basis for analyses consists of interviews with 1200 small companies from four different industry segments in Sweden. Some industry groups have suffered significant negative effects and continue to do so, while other categories have only been marginally affected. There is also a small group that has noticed growing sales and there are occasional signals from the market that new products and services are needed in the near future. It may even be the case that the industry repercussions of COVID-19 will open up new perspectives that affect and stimulate entrepreneurs, companies, customers and markets (Davidsson 2020).

2 Method and Selection

One objective in selecting the categories of companies to be included in this study was to cover the situation during the COVID-19 pandemic for small firms operating in both the manufacturing and service industries. The selection process followed Eurostat’s classifications of industries (Eurostat 2016) and, with regard to manufacturing industries, chose the broad group of companies characterized by high or medium use of technology in their operations. This applies to companies whose staff have experience and higher education, giving the recipient the capacity to run their own innovation processes but also to use externally available knowledge. Examples of industries in this category are medicine, chemistry, computer equipment and other digital products and services, as well as the automotive and transport sectors. The second group in the manufacturing sector comprises firms that have lower requirements for the core technology used in the business. Development is driven here by experience-based learning, development in smaller steps and the use of mature technology. Examples of industries with lower requirements for technology levels include the manufacture of products from metal and plastic, food products and products linked to forestry and agriculture.

Eurostat also has a standard for classifying service-oriented industries where the two main groups are knowledge-intensive and less knowledge-intensive activities. In this study, we found it appropriate to select two service industries that faced special challenges during the first half of the coronavirus pandemic. The first is hotels and restaurants, SNI 55 and SNI 56, which have been the industries hardest hit by the pandemic: available statistics show that turnover for companies in this sector decreased by 30–50% and that over 40% of the workforce was laid off in the short term during the period March–June 2020 (Statistics Sweden 2020). On the one hand, the other selected service industry is retail, SNI 47, where the food trade has seen radically increased sales due to redundancies and the rise in working from home. On the other hand, there are also sub-sectors in the retail trade that have been negatively affected by the ongoing pandemic.

From the industry categories, four random selections were made, one in each industry. Only active smaller firms were included in the study—that is, firms with 5–49 employees. Companies with fewer than five employees were excluded because many of these smallest micro-companies are relatively young and thus still in a start-up phase, where the business has not had time to fully develop. Another reason to exclude these smallest firms is that a certain proportion of them are conducted as activities in addition to a full-time job or involvement in other companies, or as “extra cracker companies”. Table 7.1 shows which sub-sectors were included, the total number of existing companies divided into two size classes and the sample size per stratum and for the entire study. The three groups that were finally included in the study were firms with 5–9 employees, those with 10–19 employees and those with 20–49 employees.

Table 7.1 Selected companies
Full size table
Table 7.2 Distribution between women and men
Full size table

The questionnaire was developed through a collaboration between the researchers, the scientific leader at Skandinavisk Opinion SKOP analysis and staff from Almi Företagspartner Ltd., who also ordered us as researchers of its research council to carry out this research project. A draft questionnaire was also examined in a special workshop with Almi’s research council. This research council consists of 14 researchers from different universities around Sweden; see www.almi.se for further information. The data collection was carried out by SKOP, and the selected companies were contacted by telephone. The interviewees were contacted at different times of the day to fit into the companies’ work schedules. In total, SKOP sought contact with 1537 business leaders, and the final number of interviews conducted was 1201. The staff at SKOP kept careful notes regarding the characteristics of the companies that dropped out (21%), but no distortions in the material occurred during the process. The companies contacted showed considerable interest in participating in the study, and reasons for not participating in many cases concerned temporary workloads. The strata that guided the random selection, with 300 companies in four different industry segments, were fully met. The answers have been weighted for processing, so that the four industry segments have an equal impact on the analysis. Our final assessment is that the size of the sample, the design of the survey and the implementation of the data collection create a data set that is representative of the population of companies in the four current industry segments and in the size range of 5–49 employees. With the aim of increasing the possibilities for a broader and in-depth analysis of the collected material, additional background information about the participating companies was also obtained and “docked” to the participating survey companies. This applies to key figures for these companies regarding the most recent years (2017–2019) before the pandemic struck in March 2020, such as number of employees, turnover, profitability and financial status.

3 Comparison of Women and Men as Operational Business Leaders

For several years, the Swedish Agency for Economic and Regional Growth, in partnership with Statistics Sweden, has mapped and analysed women in the business sector and shown that about 25% of all companies are led by women. The definition used is based on the term operational business manager, which is defined as “the person who handles the day-to-day management of a company with at least one gainfully employed person” (Statistics Sweden, 2019). This definition is not identical to the term entrepreneur, as the latter usually presupposes financial ownership, and the statistics show that 85% of women who are operational business leaders are also owners or partners in their companies. In this study, however, we have assumed that operational business management is nevertheless a useful definition for women with strategic management roles, especially considering that the object of the study is small firms with far-reaching entrepreneurial qualifications in business development and risk-taking. Seventy-nine per cent of these entrepreneurs are also owners or partners.

In the study, almost 20% (n = 229) of those who answered the survey represented women-led companies. An important reason why this share falls below the national norm of 25% is that we chose not to include the smallest micro-enterprises, those with 1–4 employees, which is a group that has a higher proportion of companies led by women. If the proportion of companies with women as business leaders is distributed between the four industries, then the two manufacturing categories had a lower proportion of women than expected, while the two service industries had a higher proportion of women in this role. When the material for this study is compared with other statistics, Statistics Sweden’s data material shows that the percentage of female operational business leaders in manufacturing companies is 15%, while the retail industry and hotel and restaurant industry have 24% and 30%, respectively. During the selection process, the two latter service industries were also selected because they have a higher proportion of women in leading positions, as well as because these businesses are generally characterized by occupational categories that include a significant number of women.

More than half of the companies (53%) belonged to the smallest size class, measured by number of employees; 30% were included in the company group with 10–19 employees; and 17% were in the group with 20–49 employees. The difference between companies led by women and men shows that the proportion of women in the role of leaders was highest for micro-enterprises (i.e., companies with less than 10 employees).

The age of the company leader was included because existing research clearly indicates that this can affect leadership style and company culture and thus also the way a company is led. We believe that leadership style becomes particularly important when a society is faced with a global pandemic that results in genuine uncertainty. A recent study conducted during the ongoing pandemic shows that elderly people are better able than younger people to deal with stressors in the environment. These results thereby indicate that elderly people in the role of business leaders are a force that can be used to handle the advanced stresses created by a pandemic (Carstensen et al. 2020). Having elderly business leaders also means that their network connections, which are based on established contacts with a large amount of trust, come to the fore in situations of great stress, risk and uncertainty (Newman et al. 2018).

The selection of companies shows that the distribution between women and men regarding the companies’ CEO positions mainly followed the 20–80 structure that applied to the basic selection. However, the group of companies having a female leader who is 61 years or older had a significantly lower share compared with the corresponding group on the male side.

The total proportion of women in the sample was 19%, and the proportion of men was 81%. The highest proportion of women was in the hotel and restaurant industry at 28%, with retail at 21%, and the highest proportion of men was in the manufacturing industry (high or medium innovation rate at 87% and low or medium innovation rate at 86%, respectively). We examined in more detail any differences between characteristics for men and women; proportions of the two groups and differences between them are not the same as characteristic differences.

The generality was limited by the choice of sub-industries and types of municipality, as well as by several additional division criteria. We continuously worked with a limited number of comparisons that we believe provide increased opportunities, overviews and conclusions. These are divisions into four sub-sectors, distribution of answers in three different types of municipality, turnover of small enterprises divided into three groups, number of employees in three groups of small enterprises, three groups of start-up years, gender (male or female), age of interviewees (divided into three age groups), entrepreneurs divided into domestic or foreign backgrounds and with three options for the effects of the pandemic. All relationships were tested for significance at the 95% level.

4 Three Regional Groups

One division basis used was to divide the material into three regional groups based on all of Sweden’s municipalities: firstly, large cities and municipalities close to the city; secondly, larger cities and municipalities close to larger cities and, thirdly, smaller cities or urban areas and rural municipalities.

Firstly, there are three divisions for the three regional types where there were no significant differences. This applies when comparisons are made as to what applies to relative proportions between municipality types for men and women, respectively. Of course, it can be difficult to divide all municipalities into three groups, but even if metropolitan areas were to be compared with other municipalities, the same result would be obtained. The results will be exactly the same as each gender’s relative share in the survey.

Secondly, women and men have similar opportunities to run companies in different types of regions. This conclusion is reinforced by the fact that age differences for both men and women seem to be unimportant for the possibilities of running companies in these types of regions.

Thirdly, the types of regions in which interviewees operate seem to be irrelevant to how they experienced the effects of the pandemic. This was measured by a question concerning whether entrepreneurs in different regional types assessed the effects of the pandemic as positive, negative or no impact.

However, there were differences regarding industries, sales, number of employees, start-up years and foreign background between the two of the region types. Large cities and municipalities close to metropolitan areas had relatively few companies with a low degree of innovation in the manufacturing industry, as well as many entrepreneurs in the hotel and restaurant industry, which seems reasonable due to a larger population base. Other factors that stand out for this group of municipalities are that many companies had a low turnover and few employees, and there were many relatively young companies.

Finally, with regard to the group of smaller cities or towns and rural municipalities, this group had a relatively large number of companies belonging to manufacturing industries with lower technology and few companies in the hotel and restaurant industry. There were also relatively many companies with high turnover, as well as a high proportion of companies with more than 20 employees and a high proportion of older companies. This group also had relatively few entrepreneurs with a foreign background.

In sum, there were differences between the most densely populated municipalities and the most sparsely populated municipalities, which should be exciting to study in more detail. There were many indications that in sparsely populated environments, companies are older and have higher turnover and more employees, while the proportion of new and young companies is low, which may indicate low dynamics.

5 Entrepreneurship in Four Sub-Business Sectors

It appears from the Method and Selection section that the selection took place from the four sub-sectors:

  1. A.

    Manufacturing—High and medium technology (SNI 20–21, 26–30)

  2. B.

    Manufacturing—Low and medium technology (SNI 10–19, 22–25, 31–33)

  3. C.

    Service—Retail (SNI 47)

  4. D.

    Hotel and restaurant (SNI 55–56)

For each industry, 300 telephone interviews were conducted. It is worth noting that some measurements can be assumed to show the same thing; for example, the probability was high that companies with the most employees would have higher turnover than companies with few employees, and older companies often also have more employees than younger ones.

Manufacturing industry with a high or medium degree of innovation (A) showed no differences for different municipal groups, had a relatively low proportion of companies with low turnover and had a high proportion of companies with high turnover. This also means that this sub-industry had few young companies with few employees and many older companies with relatively many employees. Furthermore, it is evident that this sub-industry had few younger entrepreneurs and rarely had entrepreneurs with a foreign background. Relatively many of the companies in this group stated that the pandemic did not have any effect on development, although few entrepreneurs stated that the pandemic had caused any positive development. Finally, the proportion of men was significantly higher than the proportion of women.

The manufacturing industry with a low or medium degree of innovation (B) shows broadly the same pattern as sub-industry A, except for a low proportion of small companies with high turnover and many employees. However, this sub-industry had an equal proportion of older companies, which indicates a lower growth rate in sub-industry B compared with sub-industry A. It would therefore be of interest to study in more detail the significance of the degree of innovation in small companies in the manufacturing industry for their growth. Sub-industry B also had the highest shares for the region-type smaller cities or urban areas and rural municipalities, and it had the lowest share for the region-type large cities and municipalities close to the city. This is a factor to take into account when analysing different levels of innovation.

For the sub-industry retail companies (C), there were no significant differences in terms of different regional types. However, this sub-industry had relatively few companies with low turnover but relatively many companies with few employees and relatively many companies with start-up years between 1991 and 2010. The relationships between the key figures for these companies thus differed compared with previous sub-sectors. Regarding comparisons between men and women, there were no significant differences, which also applied to age groups for interviewees. There were relatively few entrepreneurs here with a foreign background. A high proportion of entrepreneurs (close to 60%) had positive experiences of the pandemic, while only 16% had negative ones. This is clearly different from the other sub-industries studied. For example, for the sub-sector hotel and restaurant (D), the corresponding proportions are 9% positive and 34% negative. Other results for sub-sector D are a relatively high proportion of entrepreneurs with a foreign background, high proportions of young entrepreneurs, high proportions of women, relatively many young companies, low proportions regarding number of employees and turnover, and most companies in region type A and least in region type C.

6 Sales Pattern

Interviewees were asked about the share of sales in the local market (i.e., within ten miles) and the proportions of their sales for export and import. With regard to the local market, there were more women than men who answered “To a very large extent”, while the proportion of men who stated that exports were higher than the proportion of women. Note that there were no significant differences for the “Yes to a very large extent” option, either for export or for import.

One explanation for this may be that women are overrepresented in the retail and hotel and restaurant sub-sectors. The companies in these industries have low values; in the hotel and restaurant industry, only 1 in 20 companies export and 1 in 10 companies import, while 9 out of 10 companies have fairly or very large sales in the local market. In addition, men are overrepresented among the elderly, as well as in larger small companies with higher turnover, all of which are indicators of higher export shares, something that also emerged in the responses to the survey. With regard to imports, a similar pattern obtains: the majority of small companies with high export shares also have high import shares.

Six out of ten entrepreneurs had no exports. Companies with exports exist mainly in the manufacturing industry, for companies with higher turnover, with more employees, and those which have been on the market for long. Two out of ten entrepreneurs had fairly or very large exports. Five out of ten companies had no imports, and one out of four companies had fairly or very large imports. This mainly applies to companies in the manufacturing industry with a high or medium degree of innovation. Finally, in terms of sales in the local market (here defined as within a radius of 100 km), nine out of ten companies had some sales in this market. High values were obtained for companies in the retail sub-sector as well as in hotels and restaurants, for municipal groups in large cities and municipalities close to cities, the smallest companies, those with few employees and the youngest companies. Most of these groups had relatively more women, which largely explains the reported differences.

7 Impact and Support during the Pandemic

Regarding the overall positive or negative impact of the pandemic, there were no differences between women and men. About six out of ten entrepreneurs experienced negative effects, while four out of ten experienced positive effects or no impact.

Similar results were obtained concerning how profitability has been affected. There were major differences between different industries. Four out of ten small business owners in the retail trade believed that profitability has improved, while more than eight out of ten business owners in hotels and restaurants believed that it has deteriorated. There were no significant differences within different types of municipality. However, companies with the lowest turnover, as well as the youngest companies, believed to a greater extent that profitability has deteriorated. We observed no significant differences between men and women. This also applies to the answers to the question about how sales and order intake have been affected. There were also similar patterns regarding the answers to the question about the development of profitability.

During the coronavirus pandemic, research reports have already shown that younger companies have encountered greater challenges than established companies. This is because young companies in many cases have not had time to fully develop their business, which is also noticeable in financial key figures. The youngest companies included in this current study, those established between 2011 and 2020, have an equity-to-assets ratio of 36%, while the corresponding ratio for the group of companies established before 1991 is 48%. Through the survey, the companies also reported various changes, negative as well as positive, that have arisen in various areas as a result of the pandemic.

Opportunities for companies to obtain external financing are radically affected during crises. In addition, financing in smaller companies is associated with extra risks, a situation which escalates when a global pandemic breaks out. Brown and Rocha (2020) have shown in an international study that financing of new companies has decreased radically during COVID-19 and early sowing financing has almost completely disappeared.

It may be natural that initial phases among newly established companies are extra sensitive, with higher risks where any return is some way into the future, but the relationship can also be transferred to smaller companies in general where “liabilities of newness” affect risk levels and thus opportunities to gain access to external capital. Kuckertz et al.’s (2020) recent studies of small companies in Germany strengthened this picture wherein many start-ups are not “bankable”—that is, they have insufficient opportunities to provide collateral for loans and have unclear development plans, which lead to poorer interest rates—but also that they can be excluded from national support programmes during a crisis.

A Swedish study by Thorgren and Williams (2020) showed the importance of smaller companies having a stable financial situation when a crisis period starts. With the outbreak of COVID-19, most of the demand in many industries disappeared during the first months, while companies were still bound by fixed costs such as salaries, premises and current contracts. There was thus a clear demand for good liquidity during this shocking first period. Companies that were not sufficiently liquid could also find it difficult to apply for short-term loans because they already had a high debt-to-equity ratio. Coupled with this, COVID-19 created increased uncertainty and thus reduced the incentives for companies to take out new loans.

Regarding liquidity, just over four out of ten entrepreneurs stated that it had deteriorated, while just under two out of ten entrepreneurs stated that it had improved. Just over four out of ten stated that liquidity had not been affected. The highest proportion of negative impacts (seven out of ten) was reported by entrepreneurs in hotels and restaurants, while three out of ten entrepreneurs in the retail sub-sector reported an improvement. Here, 50% of the companies in the sub-sectors in the manufacturing industry reported no impact on liquidity. Entrepreneurs with the lowest turnover, few employees and young people (both for the company and for its leaders this year) reported half a negative impact on liquidity. Entrepreneurs with a foreign background also reported a highly negative impact. Finally, it can be mentioned that entrepreneurs who reported a positive impact of the pandemic believed to a large extent (60%) that liquidity had improved. No significant differences between men and women were evident here.

Interviewees were also asked how deliveries to and from small companies had been affected during the pandemic. Just over 50% of the companies had not seen any impact, while just over 40% stated that deliveries had been negatively affected. High values for non-impact were obtained for the manufacturing industry with a low degree of innovation, while deterioration in deliveries was reported to a high degree (just over 50%) by small entrepreneurs in the retail trade. No significant differences were found between small businesses in different types of municipality. No significant differences were shown between women and men, nor between small entrepreneurs in different size classes, or according to their start-up years, turnover or between domestic and foreign small entrepreneurs.

Regarding opportunities to recruit staff, about two out of three entrepreneurs stated that this was not considered during the pandemic case. Just under 10% reported improvements, while few (about 5%) reported deterioration. These relationships were largely repeated for all the different divisions. Consistency between women and men was high, with just under 10% reporting improvements, twice as many reporting no impact, two out of three reporting that recruitment was not relevant, and only just over 5% who stated that opportunities had deteriorated. It was mainly entrepreneurs stating that recruitment was not relevant who reported negative effects of the pandemic.

8 Support Programmes—Needs and Use

The public sector has set up various special resources and programmes with the aim of supporting business during the pandemic. The three support resources that companies have used to the greatest extent are reduced employer contributions, compensation for employees’ sick pay costs and short-term layoffs. Just under one in five used adjustment support and deferral of VAT and employer contributions. Only 2% of the companies used special financial support.

As previously pointed out, entrepreneurs answered a question concerning the extent to which they felt that different areas had affected their companies during the pandemic; the answers were given on a 5-point scale from “decreased a lot” to “increased a lot”. This concerns six different areas: sales, profitability, liquidity, deliveries, recruitment and external financing. To further analyse whether companies’ situations during the pandemic had an impact on their use of the various state aid programmes, users and non-users of aid programmes were compared. The support programme for short-term layoffs has been taken as an example, and for each of the six areas, the companies have indicated, on the 5-point scale, the extent to which the pandemic led to deteriorations or improvements. An average value has been calculated that has been compared for those who used or did not use this support programme.

This match shows a clear pattern. The companies that used the support programme for short-term redundancy reported a lower average value for all six areas where effects from the pandemic have been studied—that is, these companies deteriorated in these areas. This difference is also significant for the areas of sales, profitability, liquidity and deliveries. It may seem natural that it is the companies that experienced the biggest negative changes during the pandemic that also had the greatest need for support measures.

Although companies chose to use the support programmes specifically set up during the pandemic, the impact of these efforts may vary. To clarify the surveyed companies’ perceptions of the effect of the aid on their activities, a special question was included in the survey where the respondents were asked to give an overall assessment of the importance of the aid in saving the company, on a scale from small to crucial.

We have previously stated that the support in the form of reduced employer contributions is what about 90% of the companies used, but only a small part of these assessed that this form of support became of decisive importance for the business. The adjustment support attracted just under one in five, but as many as 34% of this group stated that this support was absolutely essential for their activities during the pandemic. The forms of support that just over 40% of the users considered to have provided little or no significance were those that provided reduced employer contributions and compensation for employees’ sick pay.

Women as leaders of smaller companies had a higher degree of activity with regard to applying for and using the current support programmes. This group corresponds to 19% of all companies included in the study, while between 20% and 26% of the companies that actively used programmes, or announced without support, were women-led companies. Based on answers to the question about the quality of the support programmes, it also appears that the support used by companies having women as operational business leaders was assessed as crucial to the companies’ activities during the pandemic to a greater extent than was stated by companies led by men.

The literature suggests that women and men, in their roles as business leaders, can generally have different perspectives for leading and developing their businesses and that these differences are activated when crises and other situations of genuine uncertainty arise. McGrath (2010) argued that women in such situations strive to minimize the risks that arise while men are more focused on uncovering and developing potential business opportunities. Manolova et al. (2020) have applied this to how women-owned companies have so far handled two coronavirus waves, reaching the conclusion that women have a higher presence in certain industries, such as hotels and restaurants, which have been exposed to traumatic shock effects during the pandemic much more than other industries, and this has adversely affected the opportunities to actively influence development. Two surveys of women-owned companies were conducted in the spring and autumn of 2020 within the framework of this study, which indicates that women, through support programmes and networking, have created the conditions for a restart. There are also indications that women have special abilities to develop business models, combining risk minimization with efforts for business development.

The results of our study indicate that women have at least as high an activity level as men with regard to applying for and using available support during the coronavirus pandemic. However, studies including that by Cowling et al. (2019), which concerned bank loans during the financial crisis in 2008, indicate that women apply for loans to a lesser extent than men in such crisis periods, but at the same time that women who apply for loans are more successful, in that their applications are accepted to a greater extent. This is explained in the study by the fact that women apply for smaller amounts and have better-developed applications, which in turn is explained by women being aware that they need to compensate for a negative entry value at the time of application (Malmström and Wincent 2018).

9 Support Programmes—Different Background Factors

Eight out of ten entrepreneurs did not believe that it was relevant to obtain external financing. Only 2% of entrepreneurs used bank loans with a government loan guarantee, which may be due to external financing not being relevant during this period. There was also a pattern in the use of various possible forms of state aid from which small businesses were able to benefit. The support that was primarily used was in forms that reduced companies’ costs.

Of state forms of support, entrepreneurs mainly benefited from reduced work fees (88%), compensation for sick pay costs (65%) and short-term layoffs (47%). Few entrepreneurs, just under 20%, notified or laid off staff without using the redundancy support. Adjustment support was used by 18% of entrepreneurs, while deferral of paying VAT and employer contributions, which should be seen as support that pushes costs forward in time, was used by 17% of entrepreneurs. The share of adjustment support can possibly be seen as the differences in the companies’ turnover being small.

The result shows that in terms of reduced employer contributions, there were few differences for our different division bases, apart from a higher proportion for small companies with the most employees. Here, 93% of entrepreneurs stated that they used this form of support. It is also interesting that, of those who used this support, approximately, as many entrepreneurs had positive experiences as negative ones.

The forms of support offered receive overall positive reviews. Nearly six out of ten small businesses stated that this support had been decisive or very or fairly important. For small business owners in hotels and restaurants, eight out of ten stated that this was the case. There were no differences between different types of municipality or number of employees. However, companies that had been active for fewer years seemed to agree more with this statement.

Four out of ten small businesses had waived or reduced wage withdrawals and benefits during the pandemic. This mainly applies to small business owners in hotels and restaurants, where seven out of ten business owners stated that this was the case. There were no differences between different types of municipalities or between women’s and men’s entrepreneurship. The age of employees did not seem to matter either, though to a greater extent foreign small entrepreneurs stated that this was the case.

Two out of three small business owners stated that the state had helped small businesses cope with the effects of the pandemic very or fairly well. There were large differences between industries (the hotel and restaurant share was just over 50%, while the manufacturing industry was between 70% and 75%), but not between municipality types, number of employees, companies’ start-up years, women and men, or entrepreneurs’ age.

Regarding the question of how the motivation of small businesses was affected by the pandemic, almost 20% stated that it had increased, while six out of ten stated that their motivation had not been affected. The highest proportions reporting that motivation was not affected were in the manufacturing industry, where just over seven out of ten stated that this was the case, while the proportion of small entrepreneurs in the retail trade who stated a positive effect was 25%. In the restaurant and hotel industry, half of the entrepreneurs reported a negative impact. Entrepreneurs reporting that motivation was unaffected tended to be within the municipal type smaller city or urban areas and rural municipalities, within companies with relatively high turnover, relatively many employees, companies with many years on the market, male entrepreneurs, older entrepreneurs and entrepreneurs without a foreign background.

Regarding the question about how the pandemic had affected entrepreneurs’ fear of failure, almost seven out of ten stated that the pandemic had not affected this fear. Relatively high values were obtained for the sub-sector hotels and restaurants (47%), young companies (40%), women (38%), younger entrepreneurs (39%) and entrepreneurs with a foreign background (43%).

When asked if the pandemic had led companies to discover and want to develop new business opportunities, almost 40% of entrepreneurs stated that this was the case. This mainly applies to entrepreneurs in hotels and restaurants (55%). Regarding the entrepreneurs’ need for new skills development, almost eight out of ten small entrepreneurs stated that they had not experienced such a thing. Here, too, there are higher values for hotels and restaurants, as just over 30% stated such a need. Similar values exist for managers with foreign backgrounds and for younger entrepreneurs.

10 Pandemic—Future and Employment

Processes to start and run a business are always associated with uncertainty and risk-taking. The ongoing global pandemic has so far had a major impact on companies’ opportunities to conduct commercial activities. Both supply and demand have declined for most industries, and companies have been forced to take a long list of measures, such as redundancies, advanced investments, and—during the most intense phases of the pandemic—closures and bankruptcies have also increased significantly. It is therefore natural to assume that business leaders and owners, as people responsible for their respective companies, today feel an increased anxiety about the future. This concern can thus negatively affect the entrepreneur’s self-confidence and inhibit the driving forces required for a restart of the business after the pandemic has subsided (Wennberg et al. 2013).

The shockingly rapid onset of the pandemic and the far-reaching negative effects that have followed have made it natural to ask business leaders if this has affected their fear or anxiety about continuing to fail as entrepreneurs. This question could be answered on a 5-point scale from “decreased a lot” to “increased a lot”. Almost 30% of the companies reported a large or small increase in such fear, while more than two-thirds were not affected at all, and the group with reduced anxiety was small, at about 4%.

A comparison between the sexes on the 5-point scale shows that business leaders who are women had a higher average value than men in the same role. The difference was significant and thus indicates that women have been affected more by the pandemic, which has led to them being more anxious about failing as entrepreneurs than men are. Previous studies also indicated that women perceive risk aspects as dominant during crisis periods—in other words, that women prioritize decisions and action to reduce risks (Cacciotti et al. 2016; Lee et al. 2020).

Corresponding analysis at the industry level shows that business leaders in the hotel and restaurant industry have a concern about failing as entrepreneurs to a much greater extent than in the other three industries. We have also previously noted that the proportion of women as operational leaders for companies in the hotel and restaurant industry is significantly higher than in the other industries, which is also the main reason why women have a greater presence and thus a higher degree of worry about failure in the future when all companies are included in the analysis.

Similarly, studies have found that financial crises, sharp economic downturns and natural disasters can affect entrepreneurs’ motivation to run companies. Our study shows that men in the role of operational business leaders have a higher motivation than female leaders to run their business after the ongoing coronavirus pandemic. It should be noted, however, that the motivation of both men and women has decreased rather than increased, and that the motivation of female business leaders has decreased the most.

As can be seen, the workforce has decreased in companies led by both women and men, by 299 and 657 people, respectively. Employment has increased by almost 300 people in the industry category where companies have a close connection to higher technology. As expected, the reverse is true for companies in the hotel and restaurant industry, which have seen a reduction in employment corresponding to 877 people.

The number of employees in the smallest size class, 5–9 employees, has decreased by 666 individuals and about half that number is among companies with 10–19 employees. The largest companies included in the study have increased marginally in size, measured by the number of employees. The two regional categories, large cities and larger cities and the surrounding area, have both been reduced in staff by up to 500 people each. However, the regional grouping of smaller cities and towns and the surrounding area has virtually maintained the same level of employment over the past nine months. It can also be seen that the group with the oldest companies, established in 1990 or earlier, together has increased its number of employees by 170 people, while the younger companies have decreased by 5–600 employees.

11 Conclusions

The purpose of this chapter is to assess how the pandemic has affected Swedish small businesses in four sub-industries. There is specific interest in highlighting differences and similarities between women’s and men’s entrepreneurship within different classification bases, based on responses from 228 women and 972 men who had the role of operational business leaders and/or owners. The shares regarding men and women depend on how many of each gender is represented in the various sub-sectors, of which there are two in the manufacturing industry and two in the service sector. In the various sub-sectors, women’s shares vary between 13% and 28%, with the lowest shares in manufacturing industries and the highest share in the hotel and restaurant sub-sector. This report analyses the similarities and differences between companies run by women and men, how small businesses have taken advantage of possible government measures, the significance of these measures and how these entrepreneurs perceived the future prospects of the pandemic’s effects over six to seven months from March to October 2020.

11.1 The Total Effects of the Pandemic Varied Greatly between Sub-Sectors, but the Total Effects on Employment Were Limited

The 1200 small businesses interviewed employed a total of about 15,000 people. Compared with 2019, the companies as a whole reduced employment in 2020 by approximately 6% or just over 950 people. The smallest companies lost the most employees, while companies in the largest size class saw a slight increase. On the one hand, there were fewer employees in small companies with women as leaders, which relatively means a greater effect than for men, because women relatively dominate in the smallest small companies. Men in the role of business leaders, on the other hand, dominate in, for example, the sub-industry of manufacturing with high and medium-high technology, an industry that has increased employees during the same period. In terms of sub-sectors, the largest reductions have taken place in hotels and restaurants.

11.2 Small Businesses Stated that they Benefited Greatly from State Support Programmes

Ranked by utilization rate, cost-cutting support was the most widely used. Such support mainly comprised reduced employer contributions (88%), compensation for sick pay costs (65%), short-term layoffs (47%) and adjustment support (18%). There were also deferrals of VAT and employer contributions (17%), a programme that provided opportunities to postpone costs. The lowest utilization rate was found for the financial support with a government loan guarantee. For the latter, one reason for the low rate is that eight out of ten small companies reported that external financing was not relevant during the pandemic.

Proportions of companies stating that support was of great or decisive importance varied between 58% and 87%. There were no differences between women and men in terms of utilization rate, except that women had a higher utilization rate for adjustment support and, to a greater extent than men, believed that the programmes were of decisive importance to the company. It was mainly companies with poorer financial development that requested state aid, which is natural.

11.3 In some Areas, there Were Significant Differences between Women and Men

For our selected sub-industries, there were some significant differences between women and men. This was the case in manufacturing, where men in the role of business leaders are dominant; and in the hotel and restaurant sub-industry, where women are overrepresented, men considered to a greater extent that their motivation was unaffected by the pandemic, while women believed that their motivation had decreased. Similarly, women reported to a greater extent than men that their fear of failure as an entrepreneur had increased. There is, of course, a connection between entrepreneurs reporting reduced motivation and increased fear. In addition, women-led companies have lower turnover and fewer employees than companies with men as business leaders. Women are also overrepresented in management roles for younger companies. The proportion of women with a foreign background who are entrepreneurs is lower than the corresponding proportion for men.

11.4 For Most Comparisons between Women and Men, there Were no Significant Differences

There were a number of areas where comparisons between women’s and men’s entrepreneurship showed no significant differences, such as between different regions in the country; in terms of how small businesses perceive that the state has helped them cope with the effects of the pandemic; regarding the need for new skills, where both groups (80%) say that there is no such need; and with regard to new business opportunities, with both genders to the same extent (about 40%) stating that they see such opportunities.

In previous research, there are summaries of similarities and differences between men and women as small businesses, see, for example, Holmquist and Sundin (2015). Our study used four sub-industries, two in the manufacturing industry and two in the service sector. There were more female than male small entrepreneurs in the two studied service industries and more men than women in the manufacturing industry compared with their relative share in the total sample. This was despite the fact that we chose a lower limit of at least five employees when selecting companies for the sample, but like the study above, we saw greater similarities between women and men than differences. Some further examples of this are the following.

There were no differences between women and men regarding the positive or negative effect of the pandemic. The majority of both genders feared a negative impact. The proportion of entrepreneurs who believed that motivation had increased was equally large for both genders. Just over four out of ten women and men had reduced or waived salaries or other remuneration during the pandemic, and in the sub-sector hotels and restaurants, this figure was seven out of ten for entrepreneurs of both genders. There were no differences between regions, number of employees or age of the entrepreneurs.

Additional areas where we did not see differences between men and women were in their perception of the pandemic’s effect on liquidity and profitability, the ability to recruit staff and obtain external financing, assessment of the effects of government measures, the effect on sales and order intake and how entrepreneurs viewed future uses of different digitization possibilities.

Our conclusion from this is that there are more similarities than differences and that it is, therefore, exciting in the future to analyse in more detail similarities between effects for women’s and men’s entrepreneurship.