Purpose
The purpose of this paper is to organize and present the literature related to firm’s capital structure across the years and find the most relevant publications and authors in the research area. Moreover, the authors pretend to fill the gap in the literature by studying different works and their compatibility with the main theories.
Design/methodology/approach
The systematic literature review is conducted by using the Scopus database. The methodology applied is through a concise searching considering keywords, the most cited papers, the latest publications and theories that explain small and medium enterprises (SMEs) capital structure.
Findings
Some key aspects about the capital structure of firms and SMEs are identified, such as documents per year, type of publications, the most used languages, the top journals, the most cited papers, the most productive and influential authors and the latest published papers.
Research limitations/implications
The information presented is only informative from the Scopus database. Hence, this work only gives a general orientation of the most relevant research and its tendency of this database. More exhaustive works could be done using different keywords and analyzing other firms’ characteristics.
Practical implications
This kind of study is effective in evaluating the scientific production and to find the most important contributions of the subject. Furthermore, this information is useful for researchers’ studies on SME capital structure to underline the research direction and to be acquainted with the literature tendency.
Originality/value
There are not similar works that delve into the literature respect to SME capital structure and compare the main theories in relation to empirical works. Therefore, a synthesized evolution of previous works related to the capital structure of firms and SMEs is presented.
The paper aims to develop an adjustment index based on OWA operators to enrich the results of diagnostic fuzzy models of business failure. A proposal to verify the diseases prediction accuracy of the models is also added. This allows a reduction of the map of causes or diseases detected in strategic defined areas. At the same time, these key areas can be disaggregated when an alert indicator is identified, and shows which of the causes need special attention. This application of OWA can encourage the development of suitable computer systems for monitoring companies' problems, warn of failures and facilitate decision-making. In addition, taking Vigier and Terceño's 2008 model as a benchmark, causes aggregation operators are introduced to evaluate alternative groupings, and the adjustment measure using approximate solutions is proposed to test the model's prediction.The empirical estimation and the verification of the improvement proposals in a set of small and medium-sized enterprises (SMEs) in the construction industry are also presented. The functionality and the prediction capacity are thus measured and detected by monitoring key areas that warn about insolvency situations in the firm.
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