By Soumyadeb Chowdhury1, Alexander Kharlamov1, Oscar Rodriguez-Espindola1, Prasanta Dey1, Ian Maidment1, Peter Ball2, Carolyn Chew-Graham3, Steven Marwaha4, Joemon Jose5
1Aston University, 2University of York, 3Keele University, 4University of Birmingham, 5University of Glasgow
The importance of mental health and wellbeing is becoming widely recognised. Mental health and wellbeing are complex constructs and our understanding of it or its implications on organisational performance is limited. The context of Small and Medium Enterprises is particularly challenging.
In the EU and UK, SMEs are limited to fewer than 250 staff and are usually partitioned into micro firms (1-9 employees); small enterprises (10-49 employees); and medium enterprises (50-249 employees) (OECD, 2005). According to the Department for Business, Energy, and Industrial Strategy October 2019 Statistical Release, there were 5.9 million businesses in the UK. Of them, 5.82 million (99%) were micro or small businesses (up to 49 employees); 35,600 medium businesses (50-249 employees) and 7,700 large businesses (250 or more employees). While micro and small companies employed 47.8% of the UK workforce, medium employed 12.6% of the UK workers. In terms of turnover, micro and small companies’ share was 36.8% and medium businesses’ share was 15.4% of the total UK turnover at the start of 2019. Overall, the SME sector in the UK employed 16,630,000 people and generated £2,168,005 million. In terms of industrial composition, Construction had the largest number of SME businesses (17.68%), followed by Professional, Scientific, and Technical Activities (15%), and Wholesale and Retail Trade and Repair (9%). Yet, Wholesale and Retail Trade and Repair brought in the largest turnover (1/3 of SME turnover) and employed most people (14% of all SME employment). (Department for Business, Energy and Industrial Strategy, 2019).
SMEs usually face a large number of challenges, such as lack of stable financing and lack of scalability opportunities leading most SMEs to fail within the first year of existence (e.g., OECD, 2018). After analysing the data from Austria, Czech Republic, Estonia, Germany, Hungary, Italy, Latvia, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, and United Kingdom, a number of OECD studies concluded that “the productivity gap between large firms and smaller SMEs has widened” between 2005 and 2014, with micro firms (1-9 people firms) particularly suffering from decreased productivity in the manufacturing sector (OECD, 2018, p.6). These findings uncover an interesting paradox: even though the rapid development of SMEs is desirable for any economy, their prevalence does not guarantee increased productivity, which is one of the major factors for economic prosperity. At the same time, recent advances in business and economics literature suggest that productivity can be increased through the improvement of job satisfaction, life satisfaction as well as via increasing the level of wellbeing (e.g., Oswald et al. 2015; Clarke and Mahadi 2017; etc.). Under these circumstances, the link between individual wellbeing, SMEs and productivity becomes very interesting for further research.
Wellbeing and Productivity in the Business Enterprise Sector: The Curse of SME
In order to understand the link between productivity and wellbeing in the context of SME’s, we formulate the Business-Wellbeing-Productivity framework (Figure 1), which connects business size and organisational structure with wellbeing parameter, which, in turn, is correlated with productivity. Using country-level dataset of the OECD countries, we show that prevalence of SMEs in a country’s business sector is associated with the decrease in productivity of this country through the SMEs’ negative impact on the workforce wellbeing.
Figure 1 Business-Wellbeing-Productivity Framework
The development of SMEs within the business enterprise sector in a given country is related to the overall wellbeing of this country’s workforce and this wellbeing indeed affects country’s productivity. We propose a new Business-Wellbeing-Productivity (BWP) framework, linking business performance to business size through the workforce wellbeing factors and test this framework using data from 38 countries worldwide including Australia, Austria, Belgium, Bulgaria, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Latvia, Lithuania, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, and United States. We find that BWP relations are characterized by “the Curse of SMEs”: large number of SMEs in a country negatively influences this country’s workforce wellbeing determinants, which, in turn, directly (negatively) affect productivity. In other words, the prevalence of SMEs in any given economy negatively impact productivity because it leads to decline in people’s job and life satisfaction.
The initial impact of COVID-19 on SMEs in the UK on Mental Health, Wellbeing and Productivity
This study considers first-order effects of COVID-19 on SMEs in the UK with data collected in April 2020. In a comprehensive survey study (N=192), we measure a range of effects of the pandemic on the way SMEs handle the existing crisis. While under normal circumstances we would expect that wellbeing positively affects productivity in organizations consistent with previous research (e.g., Oswald et al., 2015; Sgroi, 2015) we do not observe the same relationships in times of crisis. We find that SME workers are overwhelmed by the income concerns – i.e., financial instability is a major factor explaining increased anxiety, declined wellbeing and decreasing productivity.
Figure 2 Relative position of income, wellbeing and SME performance under Normal vs Crisis conditions
The second most important predictor of productivity identified is the number of days working from home, which affects productivity negatively, meaning that the more SME workers are required to work from home the worse is the productivity of the business. General wellbeing is predicted by greater emotional stability, low number of jobs and greater income. Job satisfaction is predicted by company’s high innovativeness, higher individual’s conscientiousness and emotional stability, lower working hours and larger frequency of work-related training. Financial wellbeing is predicted by higher conscientiousness, lower anxiety and depression scores (i.e. better mental health), greater income, fewer work from home days, longer employment and greater frequency of trainings per year. Contrary to previous research, we demonstrate that in times of crisis securing basic income needs becomes a greater concern than the overall wellbeing together with the work mode which plays a critical role in ensuring that firms remain productive. Further research is required to understand the complex link between individual wellbeing and SME performance in times of crisis.
Modelling the Impact of COVID-19 on Small and Medium-sized Enterprises in the UK
By June COVID-19 pandemic caused global impact affecting individuals and organisations. The Small and Medium Enterprises (SMEs) have been some of the most affected sectors and beyond observed economic data most of the insight is anecdotal and our previous research during the early stages of the pandemic demonstrate that in times of crisis SME workers were overwhelmed by income concerns which predicted SME performance better than individual wellbeing. We explore the impact of COVID-19 on productivity considering wellbeing, job characteristics, firm characteristics, individual characteristics, leadership and mental health using Structural Equation Modelling on a sample of UK SME employees (N=163). We found that wellbeing strongly impacts productivity.
We consider a wide range of factors (such as organisational responsiveness, leadership, use of ICT and working remotely, government communication, change management within the organisation and resource adaptability) and tried to find the main determinants of successes and failures of SMEs as a result of pandemic. We are particularly interested in the effects of COVID-19 on productivity. Using a survey, conducted with British SMEs, we consider a broad range of factors from individual psychological characteristics to financial circumstances of companies in order to determine the main consequences of coronavirus on SME performance.
Our main finding is that individual wellbeing of the SME employees directly influences productivity. SMEs, where staff reports higher life and job satisfaction levels achieve better productivity outcomes. Mental health issues as well as Organisational flexibility has a negative impact on productivity. Wellbeing is positively dependent on financial wellbeing, general wellbeing job satisfaction, and leadership quality. Work strain has a strong negative impact on wellbeing. Even though previous literature showed that (i) human mental health may be affected by COVID-19 anti-spread measures (e.g., Galea et al., 2020) as well as (ii) demonstrated the positive effect of improvement in individual wellbeing on productivity in experimental setting (e.g., Oswald et al., 2015) and in the context of a developing economy under “business as usual” (e.g., Clarke and Mahadi, 2017), this research extends existing literature by establishing a strong link between wellbeing and productivity during crisis and in the context of SMEs, which has not been done before.
Clarke, N. and Mahadi, N., 2017. Mutual recognition respect between leaders and followers: Its relationship to follower job performance and well-being. Journal of business ethics, 141(1), pp.163-178.
Galea, S., Merchant, R.M. and Lurie, N., 2020. The mental health consequences of COVID-19 and physical distancing: The need for prevention and early intervention. JAMA internal medicine, 180(6), pp.817-818.
Oreg, S., 2003. Resistance to change: Developing an individual differences measure. Journal of applied psychology, 88(4), p.680.
Oswald, A. J., Proto, E., & Sgroi, D. (2015). Happiness and productivity. Journal of Labor Economics, 33(4), 789-822.