تحلیل کتاب سنجی مقالات حوزه درماندگی مالی: وضعیت فعلی، روندهای در حال ظهور (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
هدف: با توجه به اثرات هزینه های بالای درماندگی مالی، پیش بینی آن از همان ابتدا موردتوجه محققان قرار گرفته است. ازاین رو، هدف از این پژوهش مرور ادبیات مقالات مربوط به درماندگی در این دو حوزه با استفاده از روش شناسی کتاب سنجی است. روش پژوهش: روش تحقیق این پژوهش بر اساس یک پروتکل سه مرحله ای تنظیم، پایش و تجزیه وتحلیل مجموعه داده ها انجام شده است. در مرحله اول، مقاله منتشرشده در زمینه درماندگی مالی از پایگاه داده Web of Science در بازه زمانی سال های 1980 تا 2023 جمع آوری و سپس در مرحله دوم، اسناد و مقالات پایش و 801 مقاله به منظور مرور ادبیات این حوزه انتخاب شد و درنهایت با استفاده از جعبه ابزار تحلیل کتاب سنجی مقالات موردبررسی قرار گرفت. همچنین به منظور تحلیل مقالات این حوزه از نرم افزار VOSviewer بهره گرفته شده است. یافته ها: یافته های این پژوهش حاکی از وجود شش جریان اصلی پژوهش (روش های پیش بینی درمانگی مالی، عوامل پیش بینی کننده درماندگی مالی، استراتژی تجدید ساختار، حاکمیت شرکتی، ورشکستگی بانک ها و مدیریت سود) در حوزه درماندگی مالی می باشد. همچنین نتایج پژوهش علاوه بر اینکه حاکی از اهمیت مسئولیت اجتماعی شرکت است مؤکد این موضوع نیز هست که با پیشرفت فناوری، استفاده از ابزار هوش مصنوعی جهت افزایش دقت پیش بینی افزایش یافته است.A Bibliometric Analysis of Financial Distress Research: Current Status, Emerging Trends
Purpose: The rapid development of technology and extensive environmental changes have accelerated economic growth, and the increasing competition among enterprises has restricted access to profit and increased the probability of enterprises ' financial distress. Due to the effects of high costs of financial distress, its prediction has attracted the attention of researchers since the beginning. Therefore, this paper aims at a bibliometric analysis of financial distress research in the accounting, management and economic areas. Design/methodology/approach: The research method is based on a three-step protocol of dataset setting, dataset refining, and analyzing the data. First, the published articles in the financial distress field were collected from the Web of Science database. Second, the document information was refined, and 801 articles were chosen for literature review in this area. Finally, we used the bibliometric analysis toolbox to investigate the documents. Also, bibliometric analysis in this research was conducted using VOSviewer software. Findings: The findings of this research indicate the existence of six main streams of research (methods of predicting financial distress, predictors of financial distress, restructuring strategy, corporate governance, bank bankruptcy and earnings management) in the field of financial distress. Additionally, the results highlight the importance of social responsibility of the company, also demonstrate that improvements in technology, particularly the use of artificial intelligence tools, have enhanced predicting accuracy. IntroductionIn the life cycle of any company, while there are many opportunities for growth, prosperity, and success, there are also situations where the company may face decline, crisis, and failure. Theoretically, it is assumed that business companies operate indefinitely with the aim of making a profit.However, in the modern era of the global economy, companies not only become significantly more established but also face financial distress more frequently than in the past. In other words, due to globalization and the integration of national economies, the incidence of business failures and bankruptcies has risen. Financial failure is not an instantaneous event but a dynamic and generally lengthy process that affects the company's capital structure, investment policies, and performance. Therefore, identifying the factors of financial distress enables the prediction of an enterprise's financial distress.Identifying the factors influencing the financial distress of companies, firstly, enables the taking of appropriate actions by providing necessary warnings. Secondly, investors can distinguish favorable investment opportunities from unfavorable ones and invest their resources in situations and places where they are less likely to lose money.Given the importance and effects of financial distress and the high rate of failure of current businesses, a literature analysis in this area appears necessary. A review of the literature in the field of financial distress uncovers a multitude and variety of topics in past research. Thus, it is crucial to conduct a systematic review of past research to understand its intellectual structure. Moreover, the keywords used in past research represent the field’s main ideas and topics. Therefore, this study is going to draw the intellectual structure of financial distress research through quantitative techniques of co-word analysis, citation, co-citation, bibliometric, and co-authorship analysis. Research Question(s)This research, employing bibliometric analysis, reviewed the literature on financial distress in the fields of accounting, management, and economics. It also analyzed the content of articles in this field to answer the following questions:RQ1. What is the trend of publications in financial distress research?RQ2. What is the citation structure in the financial distress research?RQ3. What are the fundamental streams of financial distress research?RQ4. What are the emerging themes in the financial distress research? MethodologyThe research method is based on a three-step protocol: dataset setting, dataset refining, and analyzing the data. First, the published articles in the financial distress field were collected from the Web of Science database. Second, the document information was refined, and 801 articles were chosen for literature review in this area. Finally, we used the bibliometric analysis toolbox to investigate the documents. Additionally, bibliometric analysis in this research was conducted using VOSviewer software. ResultsOur findings indicate an increasing trend in the number of research studies on financial distress literature over the past six years, with approximately 54% of articles published during this period.We also document that "In Search of Distress Risk" is the most cited paper, receiving 881 citations in the Web of Science database; "Altman" is identified as the most influential author; and the USA emerges as the most influential country in this research field. This predominance can largely be attributed to the fact that most journals indexed in the Web of Science in the fields of accounting and finance are associated with the United States. Consequently, it is evident that the publication of articles by universities and researchers based in this country is more prevalent than in other countries worldwide. The findings of this research reveal the existence of six main streams of research: methods of predicting financial distress, predictors of financial distress, restructuring strategy, corporate governance, bank bankruptcy, and earnings management in the field of financial distress. Additionally, the results of the research not only underscore the importance of a company’s social responsibility but also highlight how technological advancements, particularly the use of artificial intelligence tools, have enhanced the accuracy of financial distress predictions. Discussion and ConclusionIn this study, first, the evolution of literature in this field has been reviewed through bibliometric analysis over the last four decades. Secondly, from a performance perspective, the indicators related to the article, citation indicators, and combined article and citation indicators have been examined. Additionally, scientific mapping of articles in this field has been conducted through citation analysis, co-citation analysis, co-authorship analysis, and co-word analysis. Finally, clustering and content analysis of the articles in this field have been performed.First, performance analysis was conducted to answer the first two research questions. The research findings confirm that during the last four decades, the literature on financial distress has significantly grown. Examining the growth trend of the articles’ number indicates the effect of changes in the business environment on financial distress. Thus, this trend shows an increase in the number of articles from 2010 onwards, the reason for which is attributed to the financial crisis of 2008, which caused many companies to face financial distress due to the impossibility of financing. Additionally, the trend of published articles shows a significant increase in articles during the period of COVID-19 and after (2020, 2022, 2023). The limitation caused by this public crisis (COVID-19) has increased the possibility of financial distress for companies, and many researchers have investigated this issue. Secondly, to examine the third question of the research, co-citation and bibliographic coupling analysis have been used. As indicated in the mentioned findings section, the studies conducted can be classified into three clusters: predicting financial distress, which is mainly based on accounting data criteria; a cluster of default risk and systematic risk, which provides information about the prospects of the company and the volatility of assets; and finally, the cluster of restructuring strategies, which includes studies that seek to exit this cycle of financial distress using these strategies. The Bibliographic coupling analysis indicates that six main streams of research (financial distress prediction methods, financial distress prediction factors, restructuring strategy, corporate governance, bankruptcy of banks, and earnings management) exist in the financial distress field.Thirdly, the co-word analysis was conducted to answer the fourth question of the research. The increase in the frequency of the words ‘machine learning’ and ‘social responsibility of the company’ in recent years indicates the development of advanced techniques and models in data mining. This development has become so widespread that a large number of research papers are published every year in many fields, including finance, using techniques and algorithms of artificial intelligence and machine learning. Additionally, regarding social responsibility, this trend suggests the primary purpose of enterprises has shifted from profit maximization to increasing shareholder wealth and protecting the interests of other stakeholders, including society and the environment. Therefore, it is expected that future studies will focus increasingly on social responsibility and sustainability.
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