Economics of Procrastination: The Case of EU Grants

Lukasz Konopielko , Michal Kochanski , Krzysztof Wozniak
European Research Studies Journal, Volume XXII, Issue 4, 544-557, 2019
DOI: 10.35808/ersj/1528

Abstract:

Purpose: This article concerns the study of economic effects of procrastination. The research sample consists of 6568 grant applications under EU programs in Poland, collated in order to establish whether the delay in submitting the application is a statistically significant factor affecting the quality of the application and the final financing decision. Design/methodology/approach: The study is based on three logistic regression models in which the dichotomous explained variable was a negative or a positive decision on the application. The most important explanatory variable for the study is the percentile of time in which the application is submitted - it represents the delay of the applicant. Findings: The result is confirmed by previous studies, which have proven that procrastination negatively affects organizations, and that the significant weight of undertaken projects can cause procrastination among leaders. Practical implications: As the study concerns European grants, determining the impact of procrastination on financing decisions can serve to better prepare potential beneficiaries for submitting an application, providing them with knowledge on whether an earlier submission translates into the probability of the application being successful or whether the persons managing the application process should better supervise their timely submission. Originality/value: To date, little research has been devoted to confirming the economic impact of procrastination. Previous studies mainly concern cost estimation caused by delaying employees, however, this study shows that procrastination has a real, significant impact on the economic efficiency of management activities. The methodology is innovative, because procrastination has not been previously analysed in terms of the time orientation of grant applications. Machine learning techniques have never been used in procrastination research. Moreover, the majority of research to date has focused primarily on individuals, on explaining what factors are statistically significantly related to procrastination or can lead to it through modelling, however, no research has been conducted to date in which statistical models would directly examine the economic impact of procrastination.


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