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This study aims to estimate the firm size distributions that belong to the service sector and manufacturing sector in Korea.

When estimating the firm size distribution, the author considers the following two major factors. First, the firm size distribution can have a gamma distribution rather than traditional accepted distributions such as Pareto distribution or log-normal distribution. In particular, industry-specific enterprises can have different size distributions of the type of gamma distribution. Second, the firm size distribution that is applied to this study’s data set should reflect a number of factors. For example, estimating mixture gamma distribution for firm size distribution should be required and compared, because the total amount of configuration data is composed of small businesses, medium-sized and large companies.

Using 8,230 number of firm data in 2013, the author estimates mixture gamma distribution for the firm size.

From the comparison, empirical results are found for the following characteristics of core firm size distribution: first, the firm size distribution of the manufacturing sector has a longer tail than firm size distribution of the service sector. Second, the manufacturing firm size distribution dominates the entire country firm size distribution. Third, one factor among the three factors that make up the mixed gamma firm size distribution is described for 99 per cent of the firm size distributions. From the estimated firm size distributions of the service sector and manufacturing sector in Korea, the author simply implies the strategy and policy implications for the start-up firm.

This study seeks to investigate whether a firm's financial disclosure size can help investors predict performance.

Controlling for size and industry, the relationship between financial disclosure size and subsequent stock performance for all Standard and Poor's (S and P) 500 firms over a seven‐year period is examined.

It is found that firms with smaller 10‐Ks tend to have better subsequent performance relative to their industries. However, the findings suggest that the performance explanation may not lie in the size of the 10‐K itself. Firms with smaller 10‐Ks tend to perform better because they are smaller in terms of total assets and more focused, with fewer business segments.

While the study is limited to examination of S and P 500 firms, no consistent evidence is found of a relation between changes in a firm's disclosure size and future performance changes.

The results suggest that more disclosure relative to a firm's size is not necessarily bad. Investors attempting to predict future firm performance cannot use the firm's disclosure size alone.

This paper extends two recent Merrill Lynch studies that appear to contradict the extant financial literature's view that increased disclosure reduces the informational asymmetry problem. While the results confirm the findings of these studies, they suggest that the performance explanation may not lie in the size of the 10‐K itself.

Industrial organization economists have generally treated the firms operating within industries as fairly homogeneous. The firms are assumed to be similar in terms of the main decision variables so that there are few differences in the price: output, and product strategies preferred by each firm. Furthermore, the firms are believed to enjoy similar market power so that market power is essentially a shared asset. Some of the recent literature rejects the shared asset view of market power. Among the more significant contributions to this literature is the concept of strategic groups. This paper focuses on the relevance of the strategic group concept for entry theory.

Taiwan OTC market is an electronic, order driven, call market. The purpose of this paper is to gain understanding of whether trade size or number of transaction provides more information on explaining price volatility and market liquidity in this market. The paper also aims to investigate how market condition can affect the relationship between information type and trading activities.

The paper uses data from the Taiwan OTC market to run the empirical tests. It divides firms into five size groups based on their market capitalization. Regression equations are run to test: whether number of transactions has a more significant impact on price volatility on the Taiwan OTC market; the impact of market information on number of transactions; the relative impact of firm specific and market information on number of transactions; and the impact of number of transaction of bid‐ask spread.

Findings show that the larger the number of transactions, the higher the price volatility. Smaller firms on the Taiwan OTC market are traded based on firm‐specific information. This relation is further affected by market trends. Especially for the larger firms, when the market is up and the amount of market information increases, number of transactions increases. When the market is down and the amount of market information increases, number of transactions decreases. Finally, it is found spread size is more likely to be influenced by number of transactions, instead of trade size. Overall, based on these empirical results, the information content of number of transactions seems to be higher than that of trade size in the Taiwan OTC market.

Investors now understand that number of transaction actually carry more information than trade size does.

The relation between market information and number of transaction, also that between market information and trade size is influenced by market condition. The paper fills a gap in the literature to show that market condition has an impact on the relation between information type and trader's behavior. A number of transactions are identified that provide more information than trade size does. It is also shown that market conditions can further affect the impact of information on trading activities.

This article estimates the loan spread equation taking into account the endogenous matching between banks and firms in the loan market. To overcome the endogeneity problem, I supplement the loan spread equation with a two-sided matching model and estimate them jointly. Bayesian inference is feasible using a Gibbs sampling algorithm that performs Markov chain Monte Carlo (MCMC) simulations. I find that medium-sized banks and firms tend to be the most attractive partners, and that liquidity is also a consideration in choosing partners. Furthermore, banks with higher monitoring ability charge higher spreads, and firms that are more leveraged or less liquid are charged higher spreads.

This study investigates the effects of elements of corporate governance along with firm specific variables on the financial leverage of listed Indian firms in the context of agency conflicts and new governance laws.

A series of panel ordinary least squares as well as fixed/random effects regression models of book and market value of financial leverage on variables of corporate governance (board size, board composition, board meeting, board attendance and board gender) along with a set of control variables (asset tangibility, firm size, growth, liquidity and profitability) were estimated by employing 113 listed Indian firms during 2010–2021. Dynamic panel generalized method of moments models were also estimated to check the robustness of empirical results. Further, the full sample of firms was divided into small and large board sized companies using the median approach to investigate differences between small and large board characteristics on financial leverage.

The evidence predominantly suggested that the governance variables have significant impact on leverage ratios of selected firms. Governance variables such as board size, composition, attendance and gender are significantly found to be reducing the financial leverage of firms indicating that in general these attributes in a way, through monitoring managers, put pressure on them to pursue lower financial leverage. Board meeting is found to be positive and significantly related with financial leverage suggesting that the frequency of meetings signals its monitoring ability that may influence lenders' risk assessment lowering borrowing cost. The results on small and large board sized companies indicate that firms with small boards relatively issue more debt compared to firms with large boards suggesting that small boards adopt high debt policy.

The main policy implication of the study is that elements of internal corporate governance is a significant governance tool that has the potential to reduce agency conflict between the managers and agents through monitoring and decision making that has tangible effects on critical corporate decisions such as capital structure choices.

This paper contributes to the existing literature by bringing new evidence relating to agency conflicts and capital structure decisions in an emerging market like India post adoption of new regulations related to corporate governance specified in Clause 49 of Securities and Exchange Board of India and Companies Act, 2013 as there is significant dearth of such empirical work.

Extending the work of Bayou (2001), we empirically investigate the relationship between firm size and resource productivity to assess whether the productivity of resources (value in use) and their underlying value at sale (value in sale) vary with firm’s size.

We use seemingly unrelated regression of revenues and equity values on assets and employees for a large sample over a wide time period and across all industries. We compare companies that are growing, declining, or continuing in size relative to their industry.

With some variability on growth, we find that smaller companies hold more productive resources based on their capacity to generate more revenues per unit of resources (assets) relative to large companies. Further, as predicted, a firm’s workforce has productive value in use, but limited value after a firm’s sale as measured by equity values.

Collectively, our findings suggest that firm size matters in influencing resource productivity, and a workforce has productive value in use, but low value in sale.

Extant research on non-financial service firms indicates that board size is a key determinant of firm performance. Property-liability (P&L) insurers, however, face a different set of agency costs and a more intense regulatory environment than most non-financial firms. Both of these factors were reinforced by the implementation of the Financial Services Modernization Act in 2000. We document a significant inverse relation between publicly traded P&L insurer performance and board size in the post-Financial Services Modernization Act period. Publicly traded P&L insurer performance, measured by market-to-book ratio, return on revenues, and the operating ratio, was enhanced for firms with smaller board sizes in 2000 and 2001. Ironically, we find that publicly traded P&L insurers on average increased board size in 2000 and 2001. In a post-Financial Services Modernization Act environment, board size appears to be related to publicly traded P&L insurer performance, but more research is necessary to develop a complete understanding of its role in P&L insurer corporate governance.

This systematic literature review analyzes the academic literature to understand SC risk and resilience across different organizational sizes and industries. The academic literature has well discussed the causes of supply chain (SC) risk events, the impact of SC disruptions, and associated plans for SC resilience. However, the literature remains fragmented on the role of two fundamental elements in achieving SC resilience: the firm's size and the firm's industry as firms' contingent factors. Therefore, it is important to investigate and highlight SC resilience differences by size and industry type to establish more resilient firms.

Building upon the contingent resource-based view of the firm, the authors posit that organizational factors such as size and industry sector have important roles in developing organizational resilience capabilities. This systematic literature review and analysis is based on the structural and systematic analysis of high-ranked peer-reviewed journal papers from January 2000 to June 2021 collected through three global scientific databases (i.e. ProQuest, ScienceDirect, and Google Scholar) using relevant keywords.

This systematic literature review of 230 high-quality articles shows that SC risk events can be categorized into demand, supply, organizational, operational, environmental, and network/control risk events. This study suggests that the SC resilience plans developed by startups, small and mdium-sized enterprises (SMEs), and large organizations are not necessarily the same as those of large enterprises. While collaboration and networking and risk management are the most crucial resilience capabilities for all firms, applying lean and quality management principles and utilizing information technology are more crucial for SMEs. For large firms, knowledge management and contingency planning are more important.

This study provides a comprehensive review of the literature on SC resilience plans across different organizational sizes and industries, offering new insights into the nature and dynamics of startups', SMEs', and large enterprises' SC resilience in different industries. The study highlights the need for further investigation of SC risk and resilience for startups, SMEs, and different industries on a more detailed level using empirical data. This study’s findings have important implications for researchers and practitioners and guide the development of effective SC resilience strategies for different types of firms.