Aims: The purpose of this study is to examine the conceptualization of financial distress research in the textile and apparel industries, particularly in terms of research scope and methodology. Furthermore, this article attempts to systematically analyze the network formed by these literatures. Methodology: In this study, a qualitative approach was used through the literature review method, with 41 specific articles about financial distress in the textile and garment sector serving as the research corpus and drawn from the Litmaps database. To interpret and describe the frequency patterns and relationships visualized using RStudio and Gephi devices, text mining, network analysis, and content analysis were used. Results: This study discovers that a frequently discussed issue is the influence of financial variables, both dependent and independent, on the prediction of financial distress or vice versa, using various quantitative approaches and models of financial distress. This claim is supported by the findings of a systematic analysis, which reveals a positive correlation between global cloud output and network analysis. Implication/Applications: The corpus aspect of this research is limited, and the research scope is limited to the Indonesian context. Future research with broader literature sources and different types of company sectors is highly anticipated. This literature review can provide a comprehensive framework for researchers and practitioners who are interested in cases of financial distress. The Originality of the Study: Furthermore, this is a recent study that conducts a systematic review of the literature on financial distress in Indonesian textile and garment companies.
Aims: The objective of this research is to glance at the projections of financial distress in the textile and garment sub-sectors listed on the IDX. Methodology: The case study method is used in this study to employ the descriptive quantitative method approach. While the IDX is the source of the case study data, the purposive sampling method was used on the financial statements of textile and garment sub-sector companies in 2019 and the first quarter of 2020. While the cross-sectional method is used for case study analysis, or by comparing the Z-score (multiple discriminant analysis) that has been performed between one company and the standard zone that has been carried out simultaneously. Results: This study discovered that the case study using multiple discriminant analysis models in the first quarter of 2020 shows a significant impact of Covid-19 on the financial condition of companies listed on the IDX in the textile and garment industry, with 88 percent of companies in a stress zone. This study also shows that both internal and external factors can lead to a company's demise. As a result, corporate financial management decision-making must consider the company's liquidity, debt proportion, and the efficient use of working capital. Implication/Applications: The findings of this study can be useful not only for researchers, but also for practitioners who are interested in financial distress cases. The Originality of the Study: One of the study's limitations is that the sample is still limited to the research scope, which only covers the two sectors. Furthermore, this study only employs a single model of financial distress. As a result, it is hoped that in the future, research will be conducted with various types of company sectors and using various financial distress models.
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