literature review on profitability pdf

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Factors influencing firm profitability: The literature review

A huge variety of different studies was conducted in the field of profitability research. There is an enormous contribution of published papers describing the role of firm's profitability in economic growth. This article deals with the concept of profitability and provides the external and internal factors that can affect the profitability or financial performance in companies or financial institutions. Previous researchers mostly have focused on manufacturing firms, insurance firms and banks. The topic of profitability in a tourism sector is not deeply discovered. There are only few research papers connected with this field in tourism. Generally, in foreign literature there are many theories on profitability that show different perspectives. The paper presents the main external and internal factors that have a great impact on company's profitability and performance.

A literature review of risk, regulation, and profitability of banks using a scientometric study

Shailesh Rastogi 1 ,
Arpita Sharma 1 ,
Geetanjali Pinto 2 &
Venkata Mrudula Bhimavarapu ORCID: orcid.org/0000-0002-9757-1904 1 , 3

Future Business Journal volume 8 , Article number: 28 ( 2022 ) Cite this article

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This study presents a systematic literature review of regulation, profitability, and risk in the banking industry and explores the relationship between them. It proposes a policy initiative using a model that offers guidelines to establish the right mix among these variables. This is a systematic literature review study. Firstly, the necessary data are extracted using the relevant keywords from the Scopus database. The initial search results are then narrowed down, and the refined results are stored in a file. This file is finally used for data analysis. Data analysis is done using scientometrics tools, such as Table2net and Sciences cape software, and Gephi to conduct network, citation analysis, and page rank analysis. Additionally, content analysis of the relevant literature is done to construct a theoretical framework. The study identifies the prominent authors, keywords, and journals that researchers can use to understand the publication pattern in banking and the link between bank regulation, performance, and risk. It also finds that concentration banking, market power, large banks, and less competition significantly affect banks’ financial stability, profitability, and risk. Ownership structure and its impact on the performance of banks need to be investigated but have been inadequately explored in this study. This is an organized literature review exploring the relationship between regulation and bank performance. The limitations of the regulations and the importance of concentration banking are part of the findings.

Introduction

Globally, banks are under extreme pressure to enhance their performance and risk management. The financial industry still recalls the ignoble 2008 World Financial Crisis (WFC) as the worst economic disaster after the Great Depression of 1929. The regulatory mechanism before 2008 (mainly Basel II) was strongly criticized for its failure to address banks’ risks [ 47 , 87 ]. Thus, it is essential to investigate the regulation of banks [ 75 ]. This study systematically reviews the relevant literature on banks’ performance and risk management and proposes a probable solution.

Issues of performance and risk management of banks

Banks have always been hailed as engines of economic growth and have been the axis of the development of financial systems [ 70 , 85 ]. A vital parameter of a bank’s financial health is the volume of its non-performing assets (NPAs) on its balance sheet. NPAs are advances that delay in payment of interest or principal beyond a few quarters [ 108 , 118 ]. According to Ghosh [ 51 ], NPAs negatively affect the liquidity and profitability of banks, thus affecting credit growth and leading to financial instability in the economy. Hence, healthy banks translate into a healthy economy.

Despite regulations, such as high capital buffers and liquidity ratio requirements, during the second decade of the twenty-first century, the Indian banking sector still witnessed a substantial increase in NPAs. A recent report by the Indian central bank indicates that the gross NPA ratio reached an all-time peak of 11% in March 2018 and 12.2% in March 2019 [ 49 ]. Basel II has been criticized for several reasons [ 98 ]. Schwerter [ 116 ] and Pakravan [ 98 ] highlighted the systemic risk and gaps in Basel II, which could not address the systemic risk of WFC 2008. Basel III was designed to close the gaps in Basel II. However, Schwerter [ 116 ] criticized Basel III and suggested that more focus should have been on active risk management practices to avoid any impending financial crisis. Basel III was proposed to solve these issues, but it could not [ 3 , 116 ]. Samitas and Polyzos [ 113 ] found that Basel III had made banking challenging since it had reduced liquidity and failed to shield the contagion effect. Therefore, exploring some solutions to establish the right balance between regulation, performance, and risk management of banks is vital.

Keeley [ 67 ] introduced the idea of a balance among banks’ profitability, regulation, and NPA (risk-taking). This study presents the balancing act of profitability, regulation, and NPA (risk-taking) of banks as a probable solution to the issues of bank performance and risk management and calls it a triad . Figure 1 illustrates the concept of a triad. Several authors have discussed the triad in parts [ 32 , 96 , 110 , 112 ]. Triad was empirically tested in different countries by Agoraki et al. [ 1 ]. Though the idea of a triad is quite old, it is relevant in the current scenario. The spirit of the triad strongly and collectively admonishes the Basel Accord and exhibits new and exhaustive measures to take up and solve the issue of performance and risk management in banks [ 16 , 98 ]. The 2008 WFC may have caused an imbalance among profitability, regulation, and risk-taking of banks [ 57 ]. Less regulation , more competition (less profitability ), and incentive to take the risk were the cornerstones of the 2008 WFC [ 56 ]. Achieving a balance among the three elements of a triad is a real challenge for banks’ performance and risk management, which this study addresses.

Triad of Profitability, regulation, and NPA (risk-taking). Note The triad [ 131 ] of profitability, regulation, and NPA (risk-taking) is shown in Fig. 1

Triki et al. [ 130 ] revealed that a bank’s performance is a trade-off between the elements of the triad. Reduction in competition increases the profitability of banks. However, in the long run, reduction in competition leads to either the success or failure of banks. Flexible but well-expressed regulation and less competition add value to a bank’s performance. The current review paper is an attempt to explore the literature on this triad of bank performance, regulation, and risk management. This paper has the following objectives:

To systematically explore the existing literature on the triad: performance, regulation, and risk management of banks; and

To propose a model for effective bank performance and risk management of banks.

Literature is replete with discussion across the world on the triad. However, there is a lack of acceptance of the triad as a solution to the woes of bank performance and risk management. Therefore, the findings of the current papers significantly contribute to this regard. This paper collates all the previous studies on the triad systematically and presents a curated view to facilitate the policy makers and stakeholders to make more informed decisions on the issue of bank performance and risk management. This paper also contributes significantly by proposing a DBS (differential banking system) model to solve the problem of banks (Fig. 7 ). This paper examines studies worldwide and therefore ensures the wider applicability of its findings. Applicability of the DBS model is not only limited to one nation but can also be implemented worldwide. To the best of the authors’ knowledge, this is the first study to systematically evaluate the publication pattern in banking using a blend of scientometrics analysis tools, network analysis tools, and content analysis to understand the link between bank regulation, performance, and risk.

This paper is divided into five sections. “ Data and research methods ” section discusses the research methodology used for the study. The data analysis for this study is presented in two parts. “ Bibliometric and network analysis ” section presents the results obtained using bibliometric and network analysis tools, followed by “ Content Analysis ” section, which presents the content analysis of the selected literature. “ Discussion of the findings ” section discusses the results and explains the study’s conclusion, followed by limitations and scope for further research.

Data and research methods

A literature review is a systematic, reproducible, and explicit way of identifying, evaluating, and synthesizing relevant research produced and published by researchers [ 50 , 100 ]. Analyzing existing literature helps researchers generate new themes and ideas to justify the contribution made to literature. The knowledge obtained through evidence-based research also improves decision-making leading to better practical implementation in the real corporate world [ 100 , 129 ].

As Kumar et al. [ 77 , 78 ] and Rowley and Slack [ 111 ] recommended conducting an SLR, this study also employs a three-step approach to understand the publication pattern in the banking area and establish a link between bank performance, regulation, and risk.

Determining the appropriate keywords for exploring the data

Many databases such as Google Scholar, Web of Science, and Scopus are available to extract the relevant data. The quality of a publication is associated with listing a journal in a database. Scopus is a quality database as it has a wider coverage of data [ 100 , 137 ]. Hence, this study uses the Scopus database to extract the relevant data.

For conducting an SLR, there is a need to determine the most appropriate keywords to be used in the database search engine [ 26 ]. Since this study seeks to explore a link between regulation, performance, and risk management of banks, the keywords used were “risk,” “regulation,” “profitability,” “bank,” and “banking.”

Initial search results and limiting criteria

Using the keywords identified in step 1, the search for relevant literature was conducted in December 2020 in the Scopus database. This resulted in the search of 4525 documents from inception till December 2020. Further, we limited our search to include “article” publications only and included subject areas: “Economics, Econometrics and Finance,” “Business, Management and Accounting,” and “Social sciences” only. This resulted in a final search result of 3457 articles. These results were stored in a.csv file which is then used as an input to conduct the SLR.

Data analysis tools and techniques

This study uses bibliometric and network analysis tools to understand the publication pattern in the area of research [ 13 , 48 , 100 , 122 , 129 , 134 ]. Some sub-analyses of network analysis are keyword word, author, citation, and page rank analysis. Author analysis explains the author’s contribution to literature or research collaboration, national and international [ 59 , 99 ]. Citation analysis focuses on many researchers’ most cited research articles [ 100 , 102 , 131 ].

The.csv file consists of all bibliometric data for 3457 articles. Gephi and other scientometrics tools, such as Table2net and ScienceScape software, were used for the network analysis. This.csv file is directly used as an input for this software to obtain network diagrams for better data visualization [ 77 ]. To ensure the study’s quality, the articles with 50 or more citations (216 in number) are selected for content analysis [ 53 , 102 ]. The contents of these 216 articles are analyzed to develop a conceptual model of banks’ triad of risk, regulation, and profitability. Figure 2 explains the data retrieval process for SLR.

Data retrieval process for SLR. Note Stepwise SLR process and corresponding results obtained

Bibliometric and network analysis

Figure 3 [ 58 ] depicts the total number of studies that have been published on “risk,” “regulation,” “profitability,” “bank,” and “banking.” Figure 3 also depicts the pattern of the quality of the publications from the beginning till 2020. It undoubtedly shows an increasing trend in the number of articles published in the area of the triad: “risk” regulation” and “profitability.” Moreover, out of the 3457 articles published in the said area, 2098 were published recently in the last five years and contribute to 61% of total publications in this area.

Articles published from 1976 till 2020 . Note The graph shows the number of documents published from 1976 till 2020 obtained from the Scopus database

Source of publications

A total of 160 journals have contributed to the publication of 3457 articles extracted from Scopus on the triad of risk, regulation, and profitability. Table 1 shows the top 10 sources of the publications based on the citation measure. Table 1 considers two sets of data. One data set is the universe of 3457 articles, and another is the set of 216 articles used for content analysis along with their corresponding citations. The global citations are considered for the study from the Scopus dataset, and the local citations are considered for the articles in the nodes [ 53 , 135 ]. The top 10 journals with 50 or more citations resulted in 96 articles. This is almost 45% of the literature used for content analysis ( n = 216). Table 1 also shows that the Journal of Banking and Finance is the most prominent in terms of the number of publications and citations. It has 46 articles published, which is about 21% of the literature used for content analysis. Table 1 also shows these core journals’ SCImago Journal Rank indicator and H index. SCImago Journal Rank indicator reflects the impact and prestige of the Journal. This indicator is calculated as the previous three years’ weighted average of the number of citations in the Journal since the year that the article was published. The h index is the number of articles (h) published in a journal and received at least h. The number explains the scientific impact and the scientific productivity of the Journal. Table 1 also explains the time span of the journals covering articles in the area of the triad of risk, regulation, and profitability [ 7 ].

Figure 4 depicts the network analysis, where the connections between the authors and source title (journals) are made. The network has 674 nodes and 911 edges. The network between the author and Journal is classified into 36 modularities. Sections of the graph with dense connections indicate high modularity. A modularity algorithm is a design that measures how strong the divided networks are grouped into modules; this means how well the nodes are connected through a denser route relative to other networks.

Network analysis between authors and journals. Note A node size explains the more linked authors to a journal

The size of the nodes is based on the rank of the degree. The degree explains the number of connections or edges linked to a node. In the current graph, a node represents the name of the Journal and authors; they are connected through the edges. Therefore, the more the authors are associated with the Journal, the higher the degree. The algorithm used for the layout is Yifan Hu’s.

Many authors are associated with the Journal of Banking and Finance, Journal of Accounting and Economics, Journal of Financial Economics, Journal of Financial Services Research, and Journal of Business Ethics. Therefore, they are the most relevant journals on banks’ risk, regulation, and profitability.

Location and affiliation analysis

Affiliation analysis helps to identify the top contributing countries and universities. Figure 5 shows the countries across the globe where articles have been published in the triad. The size of the circle in the map indicates the number of articles published in that country. Table 2 provides the details of the top contributing organizations.

Location of articles published on Triad of profitability, regulation, and risk

Figure 5 shows that the most significant number of articles is published in the USA, followed by the UK. Malaysia and China have also contributed many articles in this area. Table 2 shows that the top contributing universities are also from Malaysia, the UK, and the USA.

Key author analysis

Table 3 shows the number of articles written by the authors out of the 3457 articles. The table also shows the top 10 authors of bank risk, regulation, and profitability.

Fadzlan Sufian, affiliated with the Universiti Islam Malaysia, has the maximum number, with 33 articles. Philip Molyneux and M. Kabir Hassan are from the University of Sharjah and the University of New Orleans, respectively; they contributed significantly, with 20 and 18 articles, respectively.

However, when the quality of the article is selected based on 50 or more citations, Fadzlan Sufian has only 3 articles with more than 50 citations. At the same time, Philip Molyneux and Allen Berger contributed more quality articles, with 8 and 11 articles, respectively.

Keyword analysis

Table 4 shows the keyword analysis (times they appeared in the articles). The top 10 keywords are listed in Table 4 . Banking and banks appeared 324 and 194 times, respectively, which forms the scope of this study, covering articles from the beginning till 2020. The keyword analysis helps to determine the factors affecting banks, such as profitability (244), efficiency (129), performance (107, corporate governance (153), risk (90), and regulation (89).

The keywords also show that efficiency through data envelopment analysis is a determinant of the performance of banks. The other significant determinants that appeared as keywords are credit risk (73), competition (70), financial stability (69), ownership structure (57), capital (56), corporate social responsibility (56), liquidity (46), diversification (45), sustainability (44), credit provision (41), economic growth (41), capital structure (39), microfinance (39), Basel III (37), non-performing assets (37), cost efficiency (30), lending behavior (30), interest rate (29), mergers and acquisition (28), capital adequacy (26), developing countries (23), net interest margin (23), board of directors (21), disclosure (21), leverage (21), productivity (20), innovation (18), firm size (16), and firm value (16).

Keyword analysis also shows the theories of banking and their determinants. Some of the theories are agency theory (23), information asymmetry (21), moral hazard (17), and market efficiency (16), which can be used by researchers when building a theory. The analysis also helps to determine the methodology that was used in the published articles; some of them are data envelopment analysis (89), which measures technical efficiency, panel data analysis (61), DEA (32), Z scores (27), regression analysis (23), stochastic frontier analysis (20), event study (15), and literature review (15). The count for literature review is only 15, which confirms that very few studies have conducted an SLR on bank risk, regulation, and profitability.

Citation analysis

One of the parameters used in judging the quality of the article is its “citation.” Table 5 shows the top 10 published articles with the highest number of citations. Ding and Cronin [ 44 ] indicated that the popularity of an article depends on the number of times it has been cited.

Tahamtan et al. [ 126 ] explained that the journal’s quality also affects its published articles’ citations. A quality journal will have a high impact factor and, therefore, more citations. The citation analysis helps researchers to identify seminal articles. The title of an article with 5900 citations is “A survey of corporate governance.”

Page Rank analysis

Goyal and Kumar [ 53 ] explain that the citation analysis indicates the ‘popularity’ and ‘prestige’ of the published research article. Apart from the citation analysis, one more analysis is essential: Page rank analysis. PageRank is given by Page et al. [ 97 ]. The impact of an article can be measured with one indicator called PageRank [ 135 ]. Page rank analysis indicates how many times an article is cited by other highly cited articles. The method helps analyze the web pages, which get the priority during any search done on google. The analysis helps in understanding the citation networks. Equation 1 explains the page rank (PR) of a published paper, N refers to the number of articles.

T 1,… T n indicates the paper, which refers paper P . C ( Ti ) indicates the number of citations. The damping factor is denoted by a “ d ” which varies in the range of 0 and 1. The page rank of all the papers is equal to 1. Table 6 shows the top papers based on page rank. Tables 5 and 6 together show a contrast in the top ranked articles based on citations and page rank, respectively. Only one article “A survey of corporate governance” falls under the prestigious articles based on the page rank.

Content analysis

Content Analysis is a research technique for conducting qualitative and quantitative analyses [ 124 ]. The content analysis is a helpful technique that provides the required information in classifying the articles depending on their nature (empirical or conceptual) [ 76 ]. By adopting the content analysis method [ 53 , 102 ], the selected articles are examined to determine their content. The classification of available content from the selected set of sample articles that are categorized under different subheads. The themes identified in the relationship between banking regulation, risk, and profitability are as follows.

Regulation and profitability of banks

The performance indicators of the banking industry have always been a topic of interest to researchers and practitioners. This area of research has assumed a special interest after the 2008 WFC [ 25 , 51 , 86 , 114 , 127 , 132 ]. According to research, the causes of poor performance and risk management are lousy banking practices, ineffective monitoring, inadequate supervision, and weak regulatory mechanisms [ 94 ]. Increased competition, deregulation, and complex financial instruments have made banks, including Indian banks, more vulnerable to risks [ 18 , 93 , 119 , 123 ]. Hence, it is essential to investigate the present regulatory machinery for the performance of banks.

There are two schools of thought on regulation and its possible impact on profitability. The first asserts that regulation does not affect profitability. The second asserts that regulation adds significant value to banks’ profitability and other performance indicators. This supports the concept that Delis et al. [ 41 ] advocated that the capital adequacy requirement and supervisory power do not affect productivity or profitability unless there is a financial crisis. Laeven and Majnoni [ 81 ] insisted that provision for loan loss should be part of capital requirements. This will significantly improve active risk management practices and ensure banks’ profitability.

Lee and Hsieh [ 83 ] proposed ambiguous findings that do not support either school of thought. According to Nguyen and Nghiem [ 95 ], while regulation is beneficial, it has a negative impact on bank profitability. As a result, when proposing regulations, it is critical to consider bank performance and risk management. According to Erfani and Vasigh [ 46 ], Islamic banks maintained their efficiency between 2006 and 2013, while most commercial banks lost, furthermore claimed that the financial crisis had no significant impact on Islamic bank profitability.

Regulation and NPA (risk-taking of banks)

The regulatory mechanism of banks in any country must address the following issues: capital adequacy ratio, prudent provisioning, concentration banking, the ownership structure of banks, market discipline, regulatory devices, presence of foreign capital, bank competition, official supervisory power, independence of supervisory bodies, private monitoring, and NPAs [ 25 ].

Kanoujiya et al. [ 64 ] revealed through empirical evidence that Indian bank regulations lack a proper understanding of what banks require and propose reforming and transforming regulation in Indian banks so that responsive governance and regulation can occur to make banks safer, supported by Rastogi et al. [ 105 ]. The positive impact of regulation on NPAs is widely discussed in the literature. [ 94 ] argue that regulation has multiple effects on banks, including reducing NPAs. The influence is more powerful if the country’s banking system is fragile. Regulation, particularly capital regulation, is extremely effective in reducing risk-taking in banks [ 103 ].

Rastogi and Kanoujiya [ 106 ] discovered evidence that disclosure regulations do not affect the profitability of Indian banks, supported by Karyani et al. [ 65 ] for the banks located in Asia. Furthermore, Rastogi and Kanoujiya [ 106 ] explain that disclosure is a difficult task as a regulatory requirement. It is less sustainable due to the nature of the imposed regulations in banks and may thus be perceived as a burden and may be overcome by realizing the benefits associated with disclosure regulation [ 31 , 54 , 101 ]. Zheng et al. [ 138 ] empirically discovered that regulation has no impact on the banks’ profitability in Bangladesh.

Governments enforce banking regulations to achieve a stable and efficient financial system [ 20 , 94 ]. The existing literature is inconclusive on the effects of regulatory compliance on banks’ risks or the reduction of NPAs [ 10 , 11 ]. Boudriga et al. [ 25 ] concluded that the regulatory mechanism plays an insignificant role in reducing NPAs. This is especially true in weak institutions, which are susceptible to corruption. Gonzalez [ 52 ] reported that firm regulations have a positive relationship with banks’ risk-taking, increasing the probability of NPAs. However, Boudriga et al. [ 25 ], Samitas and Polyzos [ 113 ], and Allen et al. [ 3 ] strongly oppose the use of regulation as a tool to reduce banks’ risk-taking.

Kwan and Laderman [ 79 ] proposed three levels in regulating banks, which are lax, liberal, and strict. The liberal regulatory framework leads to more diversification in banks. By contrast, the strict regulatory framework forces the banks to take inappropriate risks to compensate for the loss of business; this is a global problem [ 73 ].

Capital regulation reduces banks’ risk-taking [ 103 , 110 ]. Capital regulation leads to cost escalation, but the benefits outweigh the cost [ 103 ]. The trade-off is worth striking. Altman Z score is used to predict banks’ bankruptcy, and it found that the regulation increased the Altman’s Z-score [ 4 , 46 , 63 , 68 , 72 , 120 ]. Jin et al. [ 62 ] report a negative relationship between regulation and banks’ risk-taking. Capital requirements empowered regulators, and competition significantly reduced banks’ risk-taking [ 1 , 122 ]. Capital regulation has a limited impact on banks’ risk-taking [ 90 , 103 ].

Maji and De [ 90 ] suggested that human capital is more effective in managing banks’ credit risks. Besanko and Kanatas [ 21 ] highlighted that regulation on capital requirements might not mitigate risks in all scenarios, especially when recapitalization has been enforced. Klomp and De Haan [ 72 ] proposed that capital requirements and supervision substantially reduce banks’ risks.

A third-party audit may impart more legitimacy to the banking system [ 23 ]. The absence of third-party intervention is conspicuous, and this may raise a doubt about the reliability and effectiveness of the impact of regulation on bank’s risk-taking.

NPA (risk-taking) in banks and profitability

Profitability affects NPAs, and NPAs, in turn, affect profitability. According to the bad management hypothesis [ 17 ], higher profits would negatively affect NPAs. By contrast, higher profits may lead management to resort to a liberal credit policy (high earnings), which may eventually lead to higher NPAs [ 104 ].

Balasubramaniam [ 8 ] demonstrated that NPA has double negative effects on banks. NPAs increase stressed assets, reducing banks’ productive assets [ 92 , 117 , 136 ]. This phenomenon is relatively underexplored and therefore renders itself for future research.

Triad and the performance of banks

Regulation and triad.

Regulations and their impact on banks have been a matter of debate for a long time. Barth et al. [ 12 ] demonstrated that countries with a central bank as the sole regulatory body are prone to high NPAs. Although countries with multiple regulatory bodies have high liquidity risks, they have low capital requirements [ 40 ]. Barth et al. [ 12 ] supported the following steps to rationalize the existing regulatory mechanism on banks: (1) mandatory information [ 22 ], (2) empowered management of banks, and (3) increased incentive for private agents to exert corporate control. They show that profitability has an inverse relationship with banks’ risk-taking [ 114 ]. Therefore, standard regulatory practices, such as capital requirements, are not beneficial. However, small domestic banks benefit from capital restrictions.

DeYoung and Jang [ 43 ] showed that Basel III-based policies of liquidity convergence ratio (LCR) and net stable funding ratio (NSFR) are not fully executed across the globe, including the US. Dahir et al. [ 39 ] found that a decrease in liquidity and funding increases banks’ risk-taking, making banks vulnerable and reducing stability. Therefore, any regulation on liquidity risk is more likely to create problems for banks.

Concentration banking and triad

Kiran and Jones [ 71 ] asserted that large banks are marginally affected by NPAs, whereas small banks are significantly affected by high NPAs. They added a new dimension to NPAs and their impact on profitability: concentration banking or banks’ market power. Market power leads to less cost and more profitability, which can easily counter the adverse impact of NPAs on profitability [ 6 , 15 ].

The connection between the huge volume of research on the performance of banks and competition is the underlying concept of market power. Competition reduces market power, whereas concentration banking increases market power [ 25 ]. Concentration banking reduces competition, increases market power, rationalizes the banks’ risk-taking, and ensures profitability.

Tabak et al. [ 125 ] advocated that market power incentivizes banks to become risk-averse, leading to lower costs and high profits. They explained that an increase in market power reduces the risk-taking requirement of banks. Reducing banks’ risks due to market power significantly increases when capital regulation is executed objectively. Ariss [ 6 ] suggested that increased market power decreases competition, and thus, NPAs reduce, leading to increased banks’ stability.

Competition, the performance of banks, and triad

Boyd and De Nicolo [ 27 ] supported that competition and concentration banking are inversely related, whereas competition increases risk, and concentration banking decreases risk. A mere shift toward concentration banking can lead to risk rationalization. This finding has significant policy implications. Risk reduction can also be achieved through stringent regulations. Bolt and Tieman [ 24 ] explained that stringent regulation coupled with intense competition does more harm than good, especially concerning banks’ risk-taking.

Market deregulation, as well as intensifying competition, would reduce the market power of large banks. Thus, the entire banking system might take inappropriate and irrational risks [ 112 ]. Maji and Hazarika [ 91 ] added more confusion to the existing policy by proposing that, often, there is no relationship between capital regulation and banks’ risk-taking. However, some cases have reported a positive relationship. This implies that banks’ risk-taking is neutral to regulation or leads to increased risk. Furthermore, Maji and Hazarika [ 91 ] revealed that competition reduces banks’ risk-taking, contrary to popular belief.

Claessens and Laeven [ 36 ] posited that concentration banking influences competition. However, this competition exists only within the restricted circle of banks, which are part of concentration banking. Kasman and Kasman [ 66 ] found that low concentration banking increases banks’ stability. However, they were silent on the impact of low concentration banking on banks’ risk-taking. Baselga-Pascual et al. [ 14 ] endorsed the earlier findings that concentration banking reduces banks’ risk-taking.

Concentration banking and competition are inversely related because of the inherent design of concentration banking. Market power increases when only a few large banks are operating; thus, reduced competition is an obvious outcome. Barra and Zotti [ 9 ] supported the idea that market power, coupled with competition between the given players, injects financial stability into banks. Market power and concentration banking affect each other. Therefore, concentration banking with a moderate level of regulation, instead of indiscriminate regulation, would serve the purpose better. Baselga-Pascual et al. [ 14 ] also showed that concentration banking addresses banks’ risk-taking.

Schaeck et al. [ 115 ], in a landmark study, presented that concentration banking and competition reduce banks’ risk-taking. However, they did not address the relationship between concentration banking and competition, which are usually inversely related. This could be a subject for future research. Research on the relationship between concentration banking and competition is scant, identified as a research gap (“ Research Implications of the study ” section).

Transparency, corporate governance, and triad

One of the big problems with NPAs is the lack of transparency in both the regulatory bodies and banks [ 25 ]. Boudriga et al. [ 25 ] preferred to view NPAs as a governance issue and thus, recommended viewing it from a governance perspective. Ahmad and Ariff [ 2 ] concluded that regulatory capital and top-management quality determine banks’ credit risk. Furthermore, they asserted that credit risk in emerging economies is higher than that of developed economies.

Bad management practices and moral vulnerabilities are the key determinants of insolvency risks of Indian banks [ 95 ]. Banks are an integral part of the economy and engines of social growth. Therefore, banks enjoy liberal insolvency protection in India, especially public sector banks, which is a critical issue. Such a benevolent insolvency cover encourages a bank to be indifferent to its capital requirements. This indifference takes its toll on insolvency risk and profit efficiency. Insolvency protection makes the bank operationally inefficient and complacent.

Foreign equity and corporate governance practices help manage the adverse impact of banks’ risk-taking to ensure the profitability and stability of banks [ 33 , 34 ]. Eastburn and Sharland [ 45 ] advocated that sound management and a risk management system that can anticipate any impending risk are essential. A pragmatic risk mechanism should replace the existing conceptual risk management system.

Lo [ 87 ] found and advocated that the existing legislation and regulations are outdated. He insisted on a new perspective and asserted that giving equal importance to behavioral aspects and the rational expectations of customers of banks is vital. Buston [ 29 ] critiqued the balance sheet risk management practices prevailing globally. He proposed active risk management practices that provided risk protection measures to contain banks’ liquidity and solvency risks.

Klomp and De Haan [ 72 ] championed the cause of giving more autonomy to central banks of countries to provide stability in the banking system. Louzis et al. [ 88 ] showed that macroeconomic variables and the quality of bank management determine banks’ level of NPAs. Regulatory authorities are striving hard to make regulatory frameworks more structured and stringent. However, the recent increase in loan defaults (NPAs), scams, frauds, and cyber-attacks raise concerns about the effectiveness [ 19 ] of the existing banking regulations in India as well as globally.

Discussion of the findings

The findings of this study are based on the bibliometric and content analysis of the sample published articles.

The bibliometric study concludes that there is a growing demand for researchers and good quality research

The keyword analysis suggests that risk regulation, competition, profitability, and performance are key elements in understanding the banking system. The main authors, keywords, and journals are grouped in a Sankey diagram in Fig. 6 . Researchers can use the following information to understand the publication pattern on banking and its determinants.

Sankey Diagram of main authors, keywords, and journals. Note Authors contribution using scientometrics tools

Research Implications of the study

The study also concludes that a balance among the three components of triad is the solution to the challenges of banks worldwide, including India. We propose the following recommendations and implications for banks:

This study found that “the lesser the better,” that is, less regulation enhances the performance and risk management of banks. However, less regulation does not imply the absence of regulation. Less regulation means the following:

Flexible but full enforcement of the regulations

Customization, instead of a one-size-fits-all regulatory system rooted in a nation’s indigenous requirements, is needed. Basel or generic regulation can never achieve what a customized compliance system can.

A third-party audit, which is above the country's central bank, should be mandatory, and this would ensure that all three aspects of audit (policy formulation, execution, and audit) are handled by different entities.

Competition

This study asserts that the existing literature is replete with poor performance and risk management due to excessive competition. Banking is an industry of a different genre, and it would be unfair to compare it with the fast-moving consumer goods (FMCG) or telecommunication industry, where competition injects efficiency into the system, leading to customer empowerment and satisfaction. By contrast, competition is a deterrent to the basic tenets of safe banking. Concentration banking is more effective in handling the multi-pronged balance between the elements of the triad. Concentration banking reduces competition to lower and manageable levels, reduces banks’ risk-taking, and enhances profitability.

No incentive to take risks

It is found that unless banks’ risk-taking is discouraged, the problem of high NPA (risk-taking) cannot be addressed. Concentration banking is a disincentive to risk-taking and can be a game-changer in handling banks’ performance and risk management.

Research on the risk and performance of banks reveals that the existing regulatory and policy arrangement is not a sustainable proposition, especially for a country where half of the people are unbanked [ 37 ]. Further, the triad presented by Keeley [ 67 ] is a formidable real challenge to bankers. The balance among profitability, risk-taking, and regulation is very subtle and becomes harder to strike, just as the banks globally have tried hard to achieve it. A pragmatic intervention is needed; hence, this study proposes a change in the banking structure by having two types of banks functioning simultaneously to solve the problems of risk and performance of banks. The proposed two-tier banking system explained in Fig. 7 can be a great solution. This arrangement will help achieve the much-needed balance among the elements of triad as presented by Keeley [ 67 ].

Conceptual Framework. Note Fig. 7 describes the conceptual framework of the study

The first set of banks could be conventional in terms of their structure and should primarily be large-sized. The number of such banks should be moderate. There is a logic in having only a few such banks to restrict competition; thus, reasonable market power could be assigned to them [ 55 ]. However, a reduction in competition cannot be over-assumed, and banks cannot become complacent. As customary, lending would be the main source of revenue and income for these banks (fund based activities) [ 82 ]. The proposed two-tier system can be successful only when regulation especially for risk is objectively executed [ 29 ]. The second set of banks could be smaller in size and more in number. Since they are more in number, they would encounter intense competition for survival and for generating more business. Small is beautiful, and thus, this set of banks would be more agile and adaptable and consequently more efficient and profitable. The main source of revenue for this set of banks would not be loans and advances. However, non-funding and non-interest-bearing activities would be the major revenue source. Unlike their traditional and large-sized counterparts, since these banks are smaller in size, they are less likely to face risk-taking and NPAs [ 74 ].

Sarmiento and Galán [ 114 ] presented the concerns of large and small banks and their relative ability and appetite for risk-taking. High risk could threaten the existence of small-sized banks; thus, they need robust risk shielding. Small size makes them prone to failure, and they cannot convert their risk into profitability. However, large banks benefit from their size and are thus less vulnerable and can convert risk into profitable opportunities.

India has experimented with this Differential Banking System (DBS) (two-tier system) only at the policy planning level. The execution is impending, and it highly depends on the political will, which does not appear to be strong now. The current agenda behind the DBS model is not to ensure the long-term sustainability of banks. However, it is currently being directed to support the agenda of financial inclusion by extending the formal credit system to the unbanked masses [ 107 ]. A shift in goal is needed to employ the DBS as a strategic decision, but not merely a tool for financial inclusion. Thus, the proposed two-tier banking system (DBS) can solve the issue of profitability through proper regulation and less risk-taking.

The findings of Triki et al. [ 130 ] support the proposed DBS model, in this study. Triki et al. [ 130 ] advocated that different component of regulations affect banks based on their size, risk-taking, and concentration banking (or market power). Large size, more concentration banking with high market power, and high risk-taking coupled with stringent regulation make the most efficient banks in African countries. Sharifi et al. [ 119 ] confirmed that size advantage offers better risk management to large banks than small banks. The banks should modify and work according to the economic environment in the country [ 69 ], and therefore, the proposed model could help in solving the current economic problems.

This is a fact that DBS is running across the world, including in India [ 60 ] and other countries [ 133 ]. India experimented with DBS in the form of not only regional rural banks (RRBs) but payments banks [ 109 ] and small finance banks as well [ 61 ]. However, the purpose of all the existing DBS models, whether RRBs [ 60 ], payment banks, or small finance banks, is financial inclusion, not bank performance and risk management. Hence, they are unable to sustain and are failing because their model is only social instead of a much-needed dual business-cum-social model. The two-tier model of DBS proposed in the current paper can help serve the dual purpose. It may not only be able to ensure bank performance and risk management but also serve the purpose of inclusive growth of the economy.

Conclusion of the study

The study’s conclusions have some significant ramifications. This study can assist researchers in determining their study plan on the current topic by using a scientific approach. Citation analysis has aided in the objective identification of essential papers and scholars. More collaboration between authors from various countries/universities may help countries/universities better understand risk regulation, competition, profitability, and performance, which are critical elements in understanding the banking system. The regulatory mechanism in place prior to 2008 failed to address the risk associated with banks [ 47 , 87 ]. There arises a necessity and motivates authors to investigate the current topic. The present study systematically explores the existing literature on banks’ triad: performance, regulation, and risk management and proposes a probable solution.

To conclude the bibliometric results obtained from the current study, from the number of articles published from 1976 to 2020, it is evident that most of the articles were published from the year 2010, and the highest number of articles were published in the last five years, i.e., is from 2015. The authors discovered that researchers evaluate articles based on the scope of critical journals within the subject area based on the detailed review. Most risk, regulation, and profitability articles are published in peer-reviewed journals like; “Journal of Banking and Finance,” “Journal of Accounting and Economics,” and “Journal of Financial Economics.” The rest of the journals are presented in Table 1 . From the affiliation statistics, it is clear that most of the research conducted was affiliated with developed countries such as Malaysia, the USA, and the UK. The researchers perform content analysis and Citation analysis to access the type of content where the research on the current field of knowledge is focused, and citation analysis helps the academicians understand the highest cited articles that have more impact in the current research area.

Practical implications of the study

The current study is unique in that it is the first to systematically evaluate the publication pattern in banking using a combination of scientometrics analysis tools, network analysis tools, and content analysis to understand the relationship between bank regulation, performance, and risk. The study’s practical implications are that analyzing existing literature helps researchers generate new themes and ideas to justify their contribution to literature. Evidence-based research knowledge also improves decision-making, resulting in better practical implementation in the real corporate world [ 100 , 129 ].

Limitations and scope for future research

The current study only considers a single database Scopus to conduct the study, and this is one of the limitations of the study spanning around the multiple databases can provide diverse results. The proposed DBS model is a conceptual framework that requires empirical testing, which is a limitation of this study. As a result, empirical testing of the proposed DBS model could be a future research topic.

Availability of data and materials

SCOPUS database.

Abbreviations

Systematic literature review

World Financial Crisis

Non-performing assets

Differential banking system

SCImago Journal Rank Indicator

Liquidity convergence ratio

Net stable funding ratio

Fast moving consumer goods

Regional rural banks

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Rastogi, S., Sharma, A., Pinto, G. et al. A literature review of risk, regulation, and profitability of banks using a scientometric study. Futur Bus J 8 , 28 (2022). https://doi.org/10.1186/s43093-022-00146-4

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Rational Investing with Ratios pp 85–104 Cite as

Profitability and Performance Ratios

Yannick Coulon 2
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This chapter explores the concept of profitability by establishing a dichotomy between book-value based and market-value based ratios.

Market-value based profitability ratios, namely the P/E and enterprise value (EV) multiples, constitute the core of the chapter.

Two case studies expose the link that exists between operating performance, financial profitability and their risk component, financial leverage. The first case study concentrates on current market profitability ratios while the second presents forward-looking multiples.

Key takeaways on profitability ratios and their limitations conclude the chapter.

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References and Further Reading

Anthony, Robert N., and James S. Reece. 1989. Accounting: Text and Cases . Irwin.

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Coulon, Yannick. January 2017. Guide pratique de la finance d’entreprise . Gualino.

———. 2018. L’essentiel des ratios financiers . Maxima Laurent du Mesnil.

Jones, Bill, Terry Jones, Theo Kocken, and Ben Timlett. March 2016. Boom Bust Boom . TV Documentary (USA).

Minsky, Hyman P. 2008. Stabilizing an Unstable Economy . McGraw-Hill.

Quiry, Pascal, and Yann Le Fur. 2019. Finance d’entreprise 2020 de Pierre Vernimmen . Dalloz.

Stowe, John D., Thomas R. Robinson, Jerald E. Pinto, and Dennis W. McLeavey. August 2002. Analysis of Equity Investments: Valuation . AIMR and CFA Institute.

Thibierge, Christophe. November 2013. Comprendre toute la finance , 2ème édition. Vuibert.

Walsh, Ciaran. 2008. Key Management Ratios , 4th ed. Financial Times Series. FT Prentice Hall. Pearson Education Limited.

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Coulon, Y. (2020). Profitability and Performance Ratios. In: Rational Investing with Ratios. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-030-34265-4_5

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Impact of working capital management on profitability: evidence from listed companies in Qatar

Journal of Money and Business

ISSN : 2634-2596

Article publication date: 8 March 2022

Issue publication date: 31 May 2022

This study aimed to find out whether working capital management policies affect the profitability of manufacturing companies listed on the Qatar Stock Exchange.

Design/methodology/approach

To assess the working capital management and profitability relationship, the authors applied a multiple regression analysis methodology in all manufacturing companies listed on the Qatar Stock Exchange (ten firms) between 2015 and 2019. Average collection period, inventory turnover, average payment period and cash conversion cycle were adopted as proxies for working capital management, and profitability was measured by operating profit margin (OPM), return on assets (ROA), return on capital employed (ROCE) and return on equity (ROE).

The study found that companies with shorter receivables collection periods and cash conversion cycles are more profitable. Longer inventory turnover periods and accounts payable payment periods are related to higher profitability of the firms.

Originality/value

Previous studies have assessed the relationship between working capital management and profitability. However, this study is the first one to use these four variables combined (OPM, ROA, ROCE and ROE) to measure profitability; this is what was limited in previous studies. In comparison, the previous studies were not comprehensive in studying the impact of working capital management on profitability from all aspects of profitability's variables [operational (OPM), economic (ROA), capitalist (ROCE) and financial (ROE)]. However, this study focused on all these aspects to make the results of the study more accurate. Also, it is worth mentioning that this study is the first research performed on Qatar Stock Exchange, although Qatar has achieved remarkable progress in the industrial sector in recent years, making it one of the first industrialized countries in the Middle East.

Qatar stock exchange
Manufacturing companies
Working capital management
Profitability

Aldubhani, M.A.Q. , Wang, J. , Gong, T. and Maudhah, R.A. (2022), "Impact of working capital management on profitability: evidence from listed companies in Qatar", Journal of Money and Business , Vol. 2 No. 1, pp. 70-81. https://doi.org/10.1108/JMB-08-2021-0032

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1. Introduction

Working capital management (WCM) is one of the challenges faced by companies, which can provide a convenient and appropriate level of liquidity for enabling companies to cover their short-term financial obligations – resulting from financing their operations – in order to ensure the continuity of the companies' business and maximize their profitability. WCM relates to current assets and current liabilities that represent an essential part of companies' total assets. Maintaining increased levels of current assets leads the company to achieve unprofitable profits on its total short-term investments. In contrast, relatively few current assets will make the firm vulnerable to difficulties and problems, perhaps rapid failure in managing the firm's operations, reducing the firm's capabilities to meet its short-term financial obligations, and increasing the firm's exposure to liquidity risk. Therefore, establishing a reasonable working capital policy will enable companies to increase profitability and create value for investors ( Nguyen et al. , 2020 ). Therefore, WCM plays a vital and influential role in the operational performance of the companies' owned resources, liquidity, profitability and thus on the company's value as a whole. Thus, companies strive to balance risks and returns resulting from investing in current assets to reach the optimum level of investment in working capital ( Tsagem et al. , 2015 ).

The importance of WCM also highlights the nature of the relationship between the method and cost of the financing assets, as current assets are usually financed from short-term sources of funds. The difference between current assets and current liabilities is the net working capital, which, if financed from long-term sources will increase the burdens and the costs incurred by the company, thereby negatively affecting its profitability ( Subramanyam, 2014 ). In addition, the current situation caused by the COVID-19 pandemic points to the lack of liquidity and constrained credit similar to that occurred during and after the 2007 financial crisis. This made WCM a driving force behind the performance of industrial companies, where the companies must provide the necessary liquidity to finance their operations through automatic financing (WCM Effective Management) and short-term loans.

Hence, it can be said that working capital in the company is considered its lifeblood and one of the most critical factors that contribute to the continuity of the company's work, where the effective management of the working capital is a necessary process to achieve the company's goals.

Various studies have tackled the relationship between WCM and profitability. However, this study is the first one to use these four variables combined [operating profit margin (OPM), return on assets (ROA), return on capital employed (ROCE) and return on equity (ROE)] to measure profitability; this is what was limited in previous studies. In comparison, the previous studies were not comprehensive in studying the impact of WCM on profitability from all aspects of profitability's variables [operational (OPM), economic (ROA), capitalist (ROCE) and financial (ROE)]. However, this study focused on all these aspects to make the study results more accurate, which will provide companies with multiple criteria for evaluating working capital, provide more robust recommendations for WCM and enable companies to identify shortcomings in WCM that could affect their profitability ( Osazevbaru et al. , 2021 ). Also, no study has been performed before on Qatar Stock Exchange (QSE), although Qatar has achieved salient progress in the industrial sector in recent years, making it one of the first industrialized countries in the Middle East. Hence, this study aimed to investigate how the components of WCM (accounts receivable, inventory, accounts payable and cash conversion cycle) affect the profitability of listed manufacturing companies on the QSE measured by OPM, ROA, ROCE and ROE.

2. Literature review

WCM is one of the management concepts that focus on finding the optimum level of cash, inventory and debtors, also financing this level at the lowest possible cost through current liabilities to meet the company's daily needs ( Brigham and Houston, 2009 ).

Companies have to know how to manage current assets and liabilities; there is a difference in managing each of its key elements, where appropriate management of each element affects the profitability of companies ( Ehrhardt and Brigham, 2011 ).

2.1 Accounts receivable (AR)

The accounts receivables management process begins with determining the company's credit policy. However, the company must have a system to monitor and control whether the credit conditions are applied and observed. Often there is a need to take corrective measures on some credit policies, and the only way to know if the situation is suitable and under control is to have a good receivables control system ( Ehrhardt and Brigham, 2011 ). From an empirical perspective, Bieniasz and Gołaś (2011) and Enqvist et al. (2014) found a negative relationship between AR and firm's profitability, which indicates that the decrease in the number of days' collection from debtors will lead to a positive change in profitability.

Jakpar et al. (2017) , Alvarez et al. (2021) and Amponsah-Kwatiah and Asiamah (2020) reported a positive relationship between AR and a firm's profitability.

Some authors have failed to find any significant relationship between AR and profitability ( Arnaldi et al. , 2021 ; Sensini et al. , 2021 ).

2.2 Inventory (INV)

The inventory management process is one of the most critical issues of production management. The company management is responsible for providing the capital necessary to maintain the stock, where the lack of goods stock affects the sale process, which is the most important source of revenue for manufacturing companies, which may affect the profitability of these companies. The goal of inventory management is to ensure that there is a sufficient stock to ensure the continuity of the production process and to reduce the cost of holding stock to the lowest possible level ( Brigham and Houston, 2009 ). Enow and Brijlal (2014) and Olaoye et al. (2019) pointed out that there is a positive relationship between INV and a firm's profitability where a high level of inventory prevents firms from losing sales ( Jayarathne, 2014 ) and diminishes their risk of incurring the breakage costs in their production or supplying chain ( Baños-Caballero et al. , 2014 ; Deloof, 2003 ).

Some studies have shown a negative relationship between INV and a firm's profitability ( Arnaldi et al. , 2021 ; Aytac et al. , 2020 ; Högerle et al. , 2020 ).

2.3 Accounts payable (AP)

The accounts payable includes trade credit and accrued expenses, which together provide financing for business operations continuously ( Bhattacharya, 2014 ). Previous studies have found a significant positive relationship between AP and profitability ( Gonçalves et al. , 2018 ; Hsieh et al. , 2013 ; Mathuva, 2015 ). In turn, the companies can achieve more profits by taking a long time to pay creditors' bills for using this liquidity to finance investments in short-term assets ( Jayarathne, 2014 ).

On the contrary, Deloof (2003) and Enqvist et al. (2014) identified a negative relationship between AP and profitability.

2.4 Cash conversion cycle (CCC)

Managing the cash conversion cycle is related to the period required to purchase and manufacture the raw materials and keep them in the form of stock, then sell the stock and collect the resulted cash or converting the debtors' bills to cash, all that depends on the nature of the work and the type of product ( Brigham and Houston, 2009 ). Multiple studies have studied the relationship between WCM and profitability and have found a negative relationship between cash conversion cycle and profitability, indicating that a decrease in the corporate CCC will lead to a positive change in profitability ( Arnaldi et al. , 2021 ; Bieniasz and Gołaś, 2011 ; Enow and Brijlal, 2014 ; Enqvist et al. , 2014 ; Muhammad Usman and Khan, 2017 ).

Nevertheless, others found a positive relationship between CCC and profitability ( Alvarez et al. , 2021 , Amponsah-Kwatiah and Asiamah, 2020 ).

In contrast to Jakpar et al. (2017) , Rey-Ares et al. (2021) and Osazevbaru et al. (2021) there was no statistically significant relationship between the cash conversion cycle and the profitability.

There is no significant relationship between WCM represented by accounts receivable, inventory, accounts payable and cash conversion cycle on OPM in the listed manufacturing companies on QSE.

There is no significant relationship between WCM represented by accounts receivable, inventory, accounts payable and cash conversion cycle on ROA in the listed manufacturing companies on QSE.

There is no significant relationship between WCM represented by accounts receivable, inventory, accounts payable and cash conversion cycle on ROCE in the listed manufacturing companies on QSE.

There is no significant relationship between WCM represented by accounts receivable, inventory, accounts payable and cash conversion cycle on ROE in the listed manufacturing companies on QSE.

3. Methodology

3.1 sample and data collection.

The study sample consisted of all the listed manufacturing companies on the QSE (ten manufacturing companies). The data were mainly collected from the published annual reports of listed manufacturing companies on the QSE during the period 2015–2019 taken from the Qatar e-Exchange website ( Qatar Stock Exchange website, 2015–2019 ).

3.2 Statistical analysis, models and variables

Descriptive statistics were used to describe the minimum, maximum, mean and standard deviation values of the dependent (OPM, ROA, ROCE and ROE), independent (AR, INV, AP and CCC) and control variables (ALog, SG and DR).

Pearson's correlation was used to explore the strength of the relationship between dependent, independent and control variables.

Variance inflation factor (VIF) was used to check the multicollinearity between the independent variables.

Multiple regression analysis was used to test the developed hypotheses; a linear regression analysis was performed to determine the essential component of working capital, which contributed more to forecasting the firm's profitability. Whereas the data looks like panel data, we are not interested in identifying (or comparing) the details of the companies among them in the manufacturing sector and the time factor. In fact, we are actually interested in the study variables in the manufacturing companies as a whole, so we will not use panel data analysis; we will use the multiple regression analysis methods. The regression equations are shown below.

Model 1: OPM it = β0 + β 1 ( AR it ) + β 2 ( INV it ) + β 3 ( AP it ) + β 4 ( CCC it ) + β 5 ( ALog it ) + β 6 ( SG it ) + β 7 ( DR it ) + ε it

Model 2: ROA it = β0 + β 1 ( AR it ) + β 2 ( INV it ) + β 3 ( AP it ) + β 4 ( CCC it ) + β 5 ( ALog it ) + β 6 ( SG it ) + β 7 ( DR it ) + ε it

Model 3: ROEC it = β0 + β 1 ( AR it ) + β 2 ( INV it ) + β 3 ( AP it ) + β 4 ( CCC it ) + β 5 ( ALog it ) + β 6 ( SG it ) + β 7 ( DR it ) + ε it

Model 4: ROE it = β0 + β 1 ( AR it ) + β 2 ( INV it ) + β 3 ( AP it ) + β 4 ( CCC it ) + β 5 ( ALog it ) + β 6 ( SG it ) + β 7 ( DR it ) + ε it

The study variables with measurements are illustrated in Table 1 .

4. Empirical result

4.1 descriptive statistics.

The mean and standard deviation of OPM, ROA, ROCE and ROE were calculated. On average, the companies took 78 days to collect receivables, 112 days to convert inventory to sales and make payments in 50 days. CCC took 140 days to buy and turn the raw materials into stock, sell goods, collect the money from the customers and pay the money to creditors. Besides that, the average and standard deviation of ALog, SG and DR were illustrated in Table 2 .

4.2 Pearson correlation analysis

Table 3 the correlation values for the independent and control variables range from −0.610 to 0.823, implying no multicollinearity because these values are below the 0.90 thresholds ( Kasozi, 2017 ).

4.3 Variance inflation factor (VIF)

Referring to Table 4 , the value of VIF was less than 10 for all the independent variables, which indicates the absence of multicollinearity between the independent variables and acceptance of the level of the variance in each independent variable for the study ( Newbold et al. , 2013 ).

4.4 Multiple regression analysis

For testing the developed hypotheses, a linear regression analysis was used to detect the most important component of working capital, which contributed more to the forecasting of the firm's profitability. The models' results were shown in Table 5 .

4.4.1 Results of Model 1

Table 5 shows the multiple regression analysis of the independent variables related to WCM and the control variables on the OPM. The value of Adjust R 2 – which represents the ratio of the influence or interpretation of the independent variables on the variance of the dependent variable – was 0.615. This means the independent variables of WCM and the control variables explained 61.5% of the variance in the OPM of listed manufacturing companies on QSE. Thus, the null hypothesis of the study was rejected. The alternative hypothesis was accepted, which states that there is a significant relationship between WCM represented by accounts receivable, inventory, accounts payable and cash conversion cycle on OPM in the listed manufacturing companies on QSE with F-sig (0.000). This result agreed with the works of Firmansyah et al. , (2018) , Khan and Choudhary (2020) and Mehtap (2016 ) and differed with the study of Panigrahi (2012 ). Moreover, Model 1 identified a statistically significant negative ( p < 0.05) relationship between AR and OPM, which indicated that the decrease in the number of days' collected from debtors would lead to a positive change in operating profit, where the decrease in AR is an indicator of the company's ability to collect money from customers and invest it in its operations, and thus the decrease in the company's need to finance its operations from external sources, which reduces the burden of external debt; and this is reflected positively on its ability to achieve operating profits this result consistent with the studies of Bieniasz and Gołaś (2011) and Enqvist et al. (2014 ) and contrary with the studies of Jakpar et al. (2017 ), Alvarez et al. (2021 ) and Amponsah-Kwatiah and Asiamah (2020 ). It also identified a statistically significant positive ( p < 0.01) relationship between AP and OPM, indicating that an increase in the corporate AP will lead to a positive change in operating profit, which means the companies withhold their payments to their creditors to take advantage of available cash for their working capital needs. Thus, the company can invest this additional money in short-term assets to increase profits. Nevertheless, it should be taken into account that a long repayment period may lead to the loss of good suppliers; therefore, the companies should maintain better relationships with their suppliers. This result is similar to the study of Gonçalves et al. (2018) , Hsieh et al. (2013 ) and Mathuva (2015 ) findings and opposite to the studies of Deloof (2003) , Enqvist et al. (2014 ) and Rey-Ares et al. (2021 ). The model found a statistically significant negative ( p < 0.05) relationship between CCC and OPM; this means the company can enhance the operational profitability by reducing the CCC, but this reduction must be in the limits of the optimum level because the continuous reduction below this limits will lead to a deficit in the net working capital which is necessary to support the operations and meet the demands of the companies. This result supported the findings of Arnaldi et al. (2021) , Bieniasz and Gołaś (2011 ), Enow and Brijlal (2014 ), Enqvist et al. (2014 ) and Muhammad Usman and Khan (2017 ) and inconsistent with the findings of Alvarez et al. (2021 ), Amponsah-Kwatiah and Asiamah (2020 ) and Jakpar et al. (2017 ).

4.4.2 Results of Model 2

Table 5 displays that there is a significant effect between WCM and ROA, where the value of Adjust R 2 is 0.385. Thus, the null hypothesis of the study is rejected, and the alternative hypothesis is accepted with F -sig (0.000). This result is similar with the findings of Arnaldi et al. (2021) , Nastiti et al. (2019 ), Singhania and Mehta (2017 ) and Vuković and Jakšić (2019 ) and conflicting with the study of Sarwat et al. (2017 ). Furthermore, Model 2 identifies a significant positive ( p < 0.05) relationship between INV and ROA. The firms will be able to create value and increase performance and profitability by increasing the INV where the high inventory levels indicate the production capacity of the company to cover and meet the demands of the customers at any time, thus not losing the clients gradually by their going to other companies to purchase their needs due to the lack of required goods. It must be taken into account that the increase of INV must be within a reasonable and optimal level to avoid incurring storage and obsolescence costs for the companies. This result was agreed with the findings of Enow and Brijlal (2014 ) and Olaoye et al. (2019 ) and differed with the findings of Arnaldi et al. (2021) , Aytac et al. (2020 ), Gonçalves et al. (2018 ) and Högerle et al. (2020 ). The model found a significant negative ( p < 0.05) relationship between CCC and ROA and also p < 0.01 between DR and ROA. These results are consistent with the findings of Arnaldi et al. (2021) , Nguyen et al . (2020 ) and Pais and Gama (2015 ) and contrary with the findings of Chowdhury et al. (2018) and Cristian and Raisa (2017 ).

4.4.3 Results of Model 3

Empirical evidence in Table 5 shows the multiple regression analysis of the independent variables of WCM and the control variables on the ROCE. The value of Adjust R 2 is 0.351. Thus, the null hypothesis of the study is rejected, and the alternative hypothesis is accepted with F -sig (0.001); this result supported the findings of Al Dalayeen (2017 ), Högerle et al. (2020 ) and Osazevbaru et al . (2021 ). Furthermore, this model identified a significant positive ( p < 0.01) relationship between AP and ROCE and p < 0.01 between DR and ROCE where the last result agreed with the findings of Chowdhury et al. (2018) and Cristian and Raisa (2017 ) and conflicted with the findings of Arnaldi et al. (2021) , Nguyen et al . (2020 ) and Pais and Gama (2015 ).

4.4.4 Results of Model 4

Table 5 reveals that there is no significant effect between WCM and ROE. Where the value of Adjust R 2 was −0.036, it was less than 20%, which means the independent variables of WCM and the control variables could not explain the variance in the dependent variable (ROE). Where F -sig is 0.627, it was more than 5%, which indicated that the regression is not significant and not statistically acceptable. Thus, the null hypothesis of the study was accepted. This result is attributed to the clear disparity in the value of equity in Qatari companies, especially that some companies were distinguished by the presence of retained losses with clear values. Others were characterized by the high volume of reserves and retained earnings, which was reflected in the impact of working capital management on the ROE in companies. This finding is consistent with the findings of Rey-Ares et al. (2021 ) and differed with the findings of Alvarez et al. (2021 ), Amponsah-Kwatiah and Asiamah (2020 ), Gill et al. (2011 ) and Gorondutse et al. (2017 ).

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A literature review of risk, regulation, and profitability of banks using a scientometric study

Introduction

Issues of performance and risk management of banks

Data and research methods

Determining the appropriate keywords for exploring the data

Initial search results and limiting criteria

Data analysis tools and techniques

Bibliometric and network analysis

Source of publications

Location and affiliation analysis

Key author analysis

Keyword analysis

Citation analysis

Page Rank analysis

Content analysis

Regulation and profitability of banks

Regulation and NPA (risk-taking of banks)

NPA (risk-taking) in banks and profitability

Triad and the performance of banks

Concentration banking and triad

Competition, the performance of banks, and triad

Transparency, corporate governance, and triad

Discussion of the findings

The bibliometric study concludes that there is a growing demand for researchers and good quality research

Research Implications of the study

Competition

No incentive to take risks

Conclusion of the study

Practical implications of the study

Limitations and scope for future research

Availability of data and materials

Abbreviations

Acknowledgements

Author information

Contributions

Corresponding author

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Profitability and Performance Ratios

Buying options

References and Further Reading

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Impact of working capital management on profitability: evidence from listed companies in Qatar

Design/methodology/approach

Originality/value

1. Introduction

2. Literature review

2.1 Accounts receivable (AR)

2.2 Inventory (INV)

2.3 Accounts payable (AP)

2.4 Cash conversion cycle (CCC)

3. Methodology

3.2 Statistical analysis, models and variables

4. Empirical result

4.2 Pearson correlation analysis

4.3 Variance inflation factor (VIF)

4.4 Multiple regression analysis

4.4.1 Results of Model 1

4.4.2 Results of Model 2

4.4.3 Results of Model 3

4.4.4 Results of Model 4

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