Determining The Impact of the COVID-19 Pandemic on Commercial Activities in Istanbul

E. A. Alp, Selçuk Alp, Mefule Findikci Erdogan, Ahmet Oğuz Demir
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Abstract

The purpose of this study is to investigate the initial impacts of the COVID-19 pandemic on enterprises and identify differences in the effects of COVID-19 across scales and sectors. This study employed AHP to prioritize solution proposals, factor analysis to determine problem components by sectors and scales, and machine learning methods to estimate enterprise sector and scale based on survey data. The study included 255 statistically reliable samples collected between July to October 2020. Survey and comparison questions were used to determine the impact level of enterprise problems. Open-ended questions categorized pandemic-related commercial activity problems and solution proposals by enterprise scale and sector. The AHP analysis prioritized the same three problems across different scales and sectors, but machine learning-based classification analysis revealed varying criteria for determining sector and scale. Due to the fragility of developing markets public authorities expanding their economic activities during crises need to design appropriate different policies especially to protect SMEs s and keep enterprises standing. This paper presents a unique and high-quality dataset collected through a survey, examining similar issues from a historical perspective, and providing insight into the initial impacts of COVID-19 on enterprises for policymakers. The study stands out for its analysis of COVID-19 from both scale and sector perspectives, with Istanbul providing a representative sample of all sectors and scales due to Istanbul having the highest diversity among the regions in Turkey in terms of enterprises.
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确定 COVID-19 大流行对伊斯坦布尔商业活动的影响
本研究的目的是调查 COVID-19 大流行病对企业的初步影响,并确定 COVID-19 对不同规模和部门的影响差异。本研究采用 AHP 对解决方案建议进行优先排序,采用因子分析确定各部门和规模的问题组成部分,并采用机器学习方法根据调查数据估算企业部门和规模。研究包括 2020 年 7 月至 10 月间收集的 255 个统计可靠的样本。调查和比较问题用于确定企业问题的影响程度。开放式问题按企业规模和部门对与大流行病相关的商业活动问题和解决建议进行了分类。AHP 分析对不同规模和部门的三个问题进行了优先排序,但基于机器学习的分类分析显示,确定部门和规模的标准各不相同。由于发展中市场的脆弱性,在危机期间扩大经济活动的公共当局需要制定适当的不同政策,尤其是保护中小企业和保持企业活力的政策。本文介绍了通过调查收集到的独特而高质量的数据集,从历史角度研究了类似问题,并为政策制定者提供了关于 COVID-19 对企业的初步影响的见解。本研究从规模和行业两个角度对 COVID-19 进行了分析,其中伊斯坦布尔提供了所有行业和规模的代表性样本,因为伊斯坦布尔是土耳其企业多样性最高的地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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