School of Economics and Management, Huizhou University, Huizhou, 516007, People's Republic of China.
School of Economics and Management, Nanjing University of Science and Technology, 210094, Nanjing, People's Republic of China.
Environ Sci Pollut Res Int. 2023 May;30(22):61496-61510. doi: 10.1007/s11356-022-20178-1. Epub 2022 Apr 20.
The study aims to assess a sustainable green financial environment by exploring the underlying structure of monetary seismic aftershocks of the COVID-19 pandemic. This study is qualitative and uses a review of literature, primary data collection methods, and qualitative analysis techniques as the study's overall design. The data is collected by one-to-one interview using a matrix style questionnaire from a panel of experts based on the purposive sampling technique. Interpretive structural modeling (ISM) combined with Matrices' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) is used for assessment, modeling, and analysis of data. The monetary aftershocks, namely, "more cash in hand required," "decreased travel costs," "shift to more certain or fixed revenue streams," "lower rent costs," "more zealous monitoring of cash collection cycle," and "decreased entertainment costs," occupy level I (top of the model being least critical shocks), and "tedious regulations" occupy level VIII (bottom of the model being the most vital). Other aftershocks form the middle of the model being moderate critical. Analysis of MICMAC shows that monetary seismic aftershocks high fees for assistance regarding SOPs, tedious regulations, and more downtime due to pandemic alerts are independent. This study addresses the core issue from within the aftermath of the COVID-19 pandemic. It provides new important information regarding the structure of a sustainable green financial environment that is useful for economists, financial analysts, commercial and central bankers, accountants and finance managers from the organization's public/and private sectors, local and international community, and researchers of the domain. It provides an informative structural model and classification of critical aftershocks. There are specific data/methodological/resource-related limitations of the study. The study's data are collected from a focus group; the study's methodology is qualitative and indicates relations among variables that do not quantify the associations. The study is a typical initiative of academic researchers with limited financial/physical resources; therefore, the generalizability of the study results is accordingly limited. The study is based on original, essential data and innovatively and creatively approaches the problem. It provides a unique model of an unprecedented phenomenon for reverberating the sustainable green financial environment.
本研究旨在通过探索 COVID-19 大流行后货币地震余波的潜在结构，评估可持续绿色金融环境。本研究为定性研究，采用文献回顾、原始数据收集方法和定性分析技术作为研究的总体设计。数据是通过使用基于目的抽样技术的专家小组的矩阵式问卷进行一对一访谈收集的。解释结构模型（ISM）与矩阵的影响巡航乘法应用于分类（MICMAC）结合使用，用于评估、建模和分析数据。货币余震，即“手头需要更多现金”、“旅行成本降低”、“转向更确定或固定的收入流”、“租金成本降低”、“更热心地监控现金回收周期”和“娱乐成本降低”，占据了一级（模型顶部是最不关键的冲击），而“繁琐的规定”占据了八级（模型底部是最关键的）。其他余震构成了模型的中间部分，是中等关键的。MICMAC 分析表明，与 SOP 援助相关的高额费用、繁琐的规定以及由于大流行警报导致的更多停机时间，这些货币地震余波是相互独立的。本研究从 COVID-19 大流行的余波中解决了核心问题。它提供了有关可持续绿色金融环境结构的新的重要信息，对经济学家、金融分析师、商业银行家和中央银行家、来自组织公共/私营部门、当地和国际社会的会计和财务经理以及该领域的研究人员都非常有用。它提供了一个信息丰富的结构模型和关键余震的分类。该研究存在数据/方法/资源方面的具体限制。研究数据是从焦点小组收集的；研究方法是定性的，表明了变量之间的关系，但没有量化关联。该研究是学术研究人员的典型举措，他们的财力和物力资源有限；因此，研究结果的普遍性相应受到限制。该研究基于原始的、必要的数据，并创新性和创造性地解决了问题。它为可持续绿色金融环境的回荡提供了一个前所未有的独特模型。
