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The purpose of this study is to understand hospitality finance research through content analysis by examining articles published during the past two decades (1990 to 2009).

This study identified subject areas, methodologies, and citations from hospitality finance papers published in four major hospitality journals (Journal of Hospitality & Tourism Research, International Journal of Hospitality Management, International Journal of Contemporary Hospitality Management, and Cornell Hospitality Quarterly).

A perusal of 113 hospitality finance articles suggested that researchers have focused on several subjects, such as risk management, financing, bankruptcy, and capital structure. Even though qualitative analysis was the most common method in the 1990s, the use of quantitative analyses dramatically increased during the recent decade.

The data were collected from four hospitality journals. If data were collected from more hospitality journals, the most common subjects and citations might be different from the results of this study.

This study offers readers a perspective on how hospitality finance research has been conducted recently and also suggests a big picture about the potential direction of future research.

This study provides valuable information about past and current research streams, as well as the direction of hospitality finance research. Compared with previous review studies, this study concentrated on a specific segment of hospitality research in order to improve basic understanding of what is going on in the hospitality finance research, which has never been examined before.

The purpose of this paper is to systematically consolidate and analyze papers in behavioral finance in the past 20 years, and to provide an overall introduction to scholars and professionals in the industry who may be interested in behavioral finance in the future.

The research is based on searching keywords in databases of ISI Web of Science (WOS). Survey data covers the period from 1995 to 2013, with 124 journals and 347 articles. The authors are committed to finding the number of publications and times cited in the field of behavioral finance to measure the contribution of active researchers.

More research papers in behavioral finance are emerging, making it a significant area of study. Most of the papers can be classified as empirical or theory. The number of papers in the review class should be increased to assist scholars and professionals in understanding behavioral finance and its application. A number of personal and institutional main contributors have been making a considerable impact on the field of behavioral finance. With the vigorous development of financial markets all around the world, more and more scholars are becoming involved in behavioral finance research.

Articles published earlier than 1995 or not included in the WOS database cannot be included in the research; however, this does not diminish the contribution of older scholars in any way. Moreover, the research does not include non-SCI/SSCI articles.

Unlike a traditional literature review, which classifies and elaborates different research paths (Subrahmanyam, 2007), the research adopts the ISI WOS database as a tool for analysis. This new literature review methodology enables us to systematically consolidate and analyze papers in behavioral finance.

Academic institutions are under increasing pressure to show that their research output has impact. As this concept is easier to quantify in science-based disciplines, this chapter reviews how one interprets what “impact” is in finance. It suggests how best to incorporate it into academic research through the use of a simple to understand impact ratio. It provides an overview of the leading academic publications and their role in this process. It asks how impact within finance is understood, appreciated and subject to critique. It concludes that academics should demonstrate how they can facilitate the development of capital markets through evidence-based policy and enhancing capital market efficiency.

By providing a critical analysis of a recent literature review concerning environmental, social and governance (ESG) and corporate social responsibility (CSR) research in finance which was published in the Journal of Corporate Finance (Gillan et al., 2021), examining it in the light of several reviews on the same or similar lines of research, this paper aims to serve those who wish to do research in the CSR/ESG/corporate sustainability and the reporting thereof areas in finance.

This note serves to comment on Gillan et al.’s review.

Irrespective of the merits of the review, it should not be used by newcomers to the research on CSR in corporate finance given that it provides a very biased view of it.

This commentary serves the purpose of cautioning those interested in becoming acquainted with CSR-related research in corporate finance that the review on which it focuses should be used only as an entry point, given that it offers an incomplete and biased picture.

Deep learning (DL) is a new and relatively unexplored field that finds immense applications in many industries, especially ones that must make detailed observations, inferences and predictions based on extensive and scattered datasets. The purpose of this paper is to answer the following questions: (1) To what extent has DL penetrated the research being done in finance? (2) What areas of financial research have applications of DL, and what quality of work has been done in the niches? (3) What areas still need to be explored and have scope for future research?

This paper employs bibliometric analysis, a potent yet simple methodology with numerous applications in literature reviews. This paper focuses on citation analysis, author impacts, relevant and vital journals, co-citation analysis, bibliometric coupling and co-occurrence analysis. The authors collected 693 articles published in 2000–2022 from journals indexed in the Scopus database. Multiple software (VOSviewer, RStudio (biblioshiny) and Excel) were employed to analyze the data.

The findings reveal significant and renowned authors' impact in the field. The analysis indicated that the application of DL in finance has been on an upward track since 2017. The authors find four broad research areas (neural networks and stock market simulations; portfolio optimization and risk management; time series analysis and forecasting; high-frequency trading) with different degrees of intertwining and emerging research topics with the application of DL in finance. This article contributes to the literature by providing a systematic overview of the DL developments, trajectories, objectives and potential future research topics in finance.

The findings of this paper act as a guide for literature review for anyone interested in doing research in the intersection of finance and DL. The article also explores multiple areas of research that have yet to be studied to a great extent and have abundant scope.

Very few studies have explored the applications of machine learning (ML), namely, DL in finance, which is a much more specialized subset of ML. The authors look at the problem from the aspect of different techniques in DL that have been used in finance. This is the first qualitative (content analysis) and quantitative (bibliometric analysis) assessment of current research on DL in finance.

Studies of research influence commonly look at the overall field of finance. The purpose of this paper is to examine the sub-field of corporate finance at four different points in time to determine its evolution and range of influence, specifically focussing on the relative influence of seven leading journals.

Not all articles appearing in the set of journals are in corporate finance. The authors examine each article published in the journals for four key periods and identify those that are corporate. The impact factors (IFs) published in the Journal Citation Reports (JCR) are for all articles appearing in a journal. The authors are interested only in the corporate articles, so the authors calculate separate corporate IFs based on the citations to the corporate articles using the JCR technique.

The authors find a broad corporate research environment with influence that extends well beyond finance. The authors also find differences in the relative influence of the journals not only in their total influence, but in where the influence occurs outside finance and other business journals and even more broadly in the social sciences.

The exclusion of journals outside the seven selected may not uncover other areas where corporate finance articles impact research more broadly. Also, classification of articles is inherently subjective.

The authors draw comparisons between journals and corporate finance topic areas; indicating the breadth and depth research in these areas attain. These results should prove beneficial to researchers in determining areas of influence for their work, consequently providing opportunities for additional exchanges of ideas resulting in better and more informed research in the overall social sciences. Further, our approach to analyzing journal influence could prove fruitful for additional research.

The findings allow for a greater understanding of the influence of individual journals and their subsequent rankings by a number of different means. The authors propose that the means and measures employed here can lead to a greater understanding of how influential a journal really is. Further, the authors contend that the study provides comparisons of the scope and depth of influence for each journal in a way that could lead to new avenues of research.

The purpose of this research is to analyze both survey and non‐survey data to draw conclusions about the status of survey‐based research in finance.

The paper surveys editors from 15 core and 35 non‐core finance journals to learn their views about specific issues involving survey research and reviews 49 finance journals over the period 1985‐2005 to identify and classify published survey research.

Editors indicate that survey‐based manuscripts typically go through the same review process as other manuscripts. They view the chief strengths of surveys as producing data unavailable from other sources and suggesting new avenues for future research. The major weaknesses of surveys are the difficulty of generalizing the results and non‐response bias. A review of 49 finance journals shows that 63.3 percent published at least one survey article during this period. The most common topic area for published surveys was financial management.

The paper contains the normal limitations associated with the survey method including potential non‐response bias.

Survey‐based research has a definite place in financial research if such research is done to the same standards as other types of research.

This is the first study to examine the use of survey research in finance by asking journal editors their opinions and by inspecting finance journals' record of publication.

This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.

For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.

This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.

The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making their financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

The purpose of this paper is to review studies on ranking in finance journals, which have grown substantially in recent decades.

This paper depicts the trend and development of ranking studies in finance area, describes the regional work and lists the studies which focus on specific journal. This paper discusses some important and possible issues of ranking studies in finance in the future and makes some conclusions.

First, the authors find that the assessing method has changed from counting number to citation-based method. Second, the authors sort the ranking studies which focus on the research and publication quality based on regional area. Finally, in specific journal ranking studies, the authors can find how a journal reputation has changed, better or worse.

This paper reviews the ranking studies in finance area and particularly focusses on three parts. Because of the importance of ranking studies in research quality assessing, a series of issues are raised to improve the assessing objectiveness of journal ranking.

The purpose of this study is to present a brief overview of hospitality finance/accounting (HFA) research and to propose the utility of interdisciplinary research in the HFA field.

This study outlines HFA research and adds a brief summary of mainstream finance and accounting research topics. To further improve HFA research, this study suggests the need for interdisciplinary research that could effectively integrate finance/accounting with other management subjects in the hospitality field.

Despite its importance, interdisciplinary research has not been given enough attention in the field of HFA. This study sheds light on the need for interdisciplinary research and proposes paths for conducting interdisciplinary HFA research, such as behavioral finance, marketing-finance interface, human resource management finance/accounting, etc.

This study suggests that the results of interdisciplinary HFA research can provide useful practical implications from shareholder and organizational perspectives in the hospitality industry.

Although the interdisciplinary research concept is not really new, it has not been extensively addressed in hospitality academia. In this respect, this study suggests expanding the horizon for HFA researchers.