8 December 2020, 08:40
COVID SURVEY by CECE, ERA and LECTURA:
Covid Special, part 10
Because surveys are self-report measures this article aims to look at the results from our COVID survey and think about their relevance in comparison with objective/hard data (e.g. production volume, market turnover, profit, etc.). We believe thinking about methodological characteristics of research methods may provide us with information about the level of certainty with what people can reflect and describe what they are going through/experiencing. Some sources have already discussed correlations between self-reports and objective measures. These correlations are between weak (0.1) to moderate (0.48). Therefore, this article may discuss some possible consequences of different methodological approaches and their advantages and disadvantages according to various aims of the research.
Using self-report measures in surveys
Self-reported measures are measures in which respondents are asked to report directly on their behaviors, beliefs, attitudes, or intentions. Historically, surveys have almost exclusively made use of this type of measure. However “self-reports” are usually biased by cognitive shortcuts and other distortions of thoughts. Though other types of measures are used when researching people's behavior, too. For example, behavioral ones relying on people's behavior observation, or physiological (e.g. galvanic skin response, blood pressure, etc.) relying on biological indicators of emotions.
In our covid survey, we asked our respondents directly how they experienced the crisis. Therefore their answers reflected the beliefs and opinions about the impact of the crisis of our respondents. On the other hand, when inspecting the impact of the crisis we can choose an alternative approach by exploring so-called hard data - for example, amount of purchase or sales and how the crisis influenced them.
Results of our survey
When inspecting the impact of the covid crisis, we aimed to distinguish between those who experienced an increase, those who suffered from decline, and those who experienced no change. Furthermore, the levels of decline were inspected. The respondents were provided with multiple choice questions with predefined options. We asked them to choose which of the predefined options (percentage intervals) best suits the impact of the crisis on their business. The results are presented below.
Overall, most of the respondents experienced no change during the crisis although statistically significant (p < 0.05) differences were found between the type of impact and levels of decrease.
Official European statistics
Official statistics usually report a decline caused by the coronavirus crisis but do not expect any long term effect (which is a similar situation to the economic crisis in 2008)
According to Eurostat providing data till September 2020, Industrial production in the EU remained stable after an increase in August. After strong declines in March and April, industrial growth had picked up in May, June, and July. Nevertheless, the total reduction since February 2020 persists. Speaking about concrete numbers after an unprecedented decline in March and April, construction production increased dynamically in May 2020 (22.2 %). In the subsequent months, construction production increased further yet not very strongly. In September 2020, only 95.7 % of the pre-crisis level of February 2020 had been regained. However, the Covid survey ran during May and reflected mostly the situation in the first half of the year. According to Eurostat, in the first half of the year, the impact was about a 25% decline. Compared to covid surveys, the average decline is about 20%, but inferring such results is very thorough because of wide predefined intervals.
Comparison of these two methodological approaches and its influence on the results
Our approach to use surveys does not provide us with such accurate results. However, it was not even the aim of our survey. The aim of the covid survey was rather to explore how people see or perceive the crisis. We focus on their perception of reality. The second important reason for using a survey with only roughly set options about covid impact was because of the sensitivity of the topic. We believe some people won't be willing to speak openly about the impact of the crisis on their business, especially when they face troubles. Even declared anonymity does not usually automatically guarantee people will not deceive.
On the other hand, the objective data mentioned above are provided by countries transmitting monthly construction production data to Eurostat. Therefore these data have to be more accurate to set possible predictions about trends in the construction industry in a case to set future interventions and see even small deviations. This is also a question about longitudinal and cross-sectional approaches. Our survey - cross-sectional does not focus on changes during the time but basically reflects the attitudes and thoughts of our respondents in a given time.
To conclude, a comparison of data from several research sources definitely has additional value. However, the issue is not so straightforward. Self-reports and objective data are usually used for different purposes, and different research methods are used. Rather than confirming or questioning the results from one research, the comparison with other research sources may help us to explore the research topic in breadth and depth. As seen above, the self-report methods tell us more about attitudes and thoughts of the respondents (which are usually researched on social science) whereas, the objective data represent the perspective of the economy rather. Although even this claim is too much simplifying because knowing the subjective reality of people is highly valued not only in social science.
Would you like to know more about the impact of COVID pandemic on the construction industry? Click here for the full report by LECTURA, ERA and CECE!
or continue reading the Covid Special ==> Part 1: The case study on German and British machine owners: similarities and differences in the coronavirus crisis management
==> Part 2: Differences between the coronavirus crisis impact according to the company size
==> Part 4: When facing a crisis, what type and from whom people expect to support?
==> Part 5: The influence of the coronavirus crisis on the dealers´ rental economy
==> Part 6: Areas of business for which we observe the greatest and the least impact
==> Part 7: The impacts of the COVID-19 crisis based on regional and historical-political factors
==> Part 8: What strategies did contractors use during the crisis to stay in the market?
Source: LECTURA Verlag GmbH