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The agribusiness co-operative sector in Canada has been affected by ongoing changes in economic, political, and social policies. Increased competition from local investor-owned firms and multinational companies, deregulation and globalization of trade and increased concentration of suppliers and purchasers have put tremendous competitive pressure on agribusiness marketing co-operatives. The enhanced level of competitive rivalry may force co-operatives into lowering costs and prices. Improvement in cost or operating efficiency of agribusiness marketing co-operatives may be crucial as changes in regulation, technology, and other market developments bring into question the long-term viability of co-operative businesses. Therefore, information as to the efficiency with which agribusiness co-operative firms operate would be useful.

The purpose of this paper is to examine the impact of directors’ and officers’ liability insurance (D&O insurance hereafter) on corporate governance and firm performance, with a specific focus on investment efficiency.

Using a sample of Chinese A-share listed firms from the period 2007 to 2020, this study uses Ordinary Least Squares regressions to investigate the research questions, as well as moderating and mediating effects. Additionally, alternative measures of investment efficiency are used, and the Heckman two-stage model and propensity score matching model are used to demonstrate the consistency of the findings and to mitigate the risk of endogeneity.

The findings of this study suggest that purchasing D&O insurance has a detrimental impact on corporate investment efficiency, particularly in the context of over-investment activities; robust internal governance mechanisms, exemplified by a higher shareholding ratio of the top shareholder and enhanced internal control quality, alleviate this negative effect; and financing constraints act as a mediating factor in the association between D&O insurance and investment efficiency.

Corporate investment efficiency is of significant importance for both national macroeconomic growth and micro-enterprise development. Notably, the prevalence of D&O insurance among Chinese firms is progressively increasing, thus exerting a growing influence. This study contributes to the existing literature on D&O insurance and corporate investment efficiency, providing valuable insights into the economic impact of D&O insurance on Chinese firms. The empirical evidence presented herein facilitates future reforms and adjustments.

The purpose of this study is to extend previous literature and examine risk management efficiency among Takaful (TI) and conventional insurance (CI) firms in the Kingdom of Saudi Arabia (KSA) and the United Arab Emirates (UAE). This study also aims to determine whether Takaful firms are more efficient in managing risks, compared to CI firms.

This study examines risk management efficiency among Takaful and CI firms in the KSA and the UAE for a sample of 20 insurance firms comprising 10 TI firms and 10 CI firms for the period 2018–2020. The authors use Data Envelopment Analysis to estimate efficiency scores among insurance companies to compare risk management efficiency between CI and TI companies and apply two-way analysis of variance to statistically analyze the data.

The results of this study show that TI firms have a higher efficiency score than CI firms, but not significantly and that insurance firms in KSA have higher efficiency scores than insurance firms in UAE. The results also reveal that TI firms did not significantly outperform CI firms in managing risks; however, there is a significant difference in efficiency scores among insurance firms in KSA and UAE.

The authors also contribute to the literature by providing important insights into how the operational business environment of the country can influence the risk management efficiency of CI and TI companies.

This study promotes understanding the insurance industry, its efficiency and risk management, thus offering key implications for decision-makers, regulators and managers associated with the insurance industry in UAE, KSA and other emerging insurance markets. Regulators could provide enabling policies that foster and promote the business environment, as there is a need to improve risk management efficiency in the insurance industry. Also, the results of this study show that the operating status of the UAE insurance industry in terms of efficiency and risk management is lower than that of KSA. Hence, it would be useful for UAE managers and regulators in taking steps to improve the overall insurance industry market.

The results of this study make significant contributions by providing new insights to the existing literature on the risk management efficiency in the insurance industry, as it adopts a different methodological approach that examines risk management efficiency among TI and CI companies.

First, this study assesses the link between research and development (R&D) expenses and firm efficiency. Second, this study explores how family control moderates the link between the two.

This study uses two measures of time-based firm efficiency, namely, a window slacks-based measure (WSBM) and a window epsilon-based measure (WEBM) of data envelopment analysis (DEA). Then, 216 firm-year observations are analyzed in the Taiwanese cultural and creative industries from 2005 to 2017.

This study finds that R&D expenses significantly worsen firm efficiency, and that family control positively moderates this effect. A further test separating the sample into family-controlled and nonfamily-controlled firms indicates that R&D expenses negatively affect the efficiency of nonfamily-controlled firms but positively affect that of family-controlled firms.

The existing literature has examined the link between R&D expenses and corporate performance. However, the process by which R&D expenses affect corporate performance from a production perspective remains unknown.

Overall, this study provides insights for policymakers to scrutinize resource management and R&D expenses from the production and resource-based perspectives.

The purpose of this paper is to examine the relation between chief executive officer (CEO) compensation and firm performance proxied by efficiency estimated from data envelopment analysis (DEA) of the US property‐liability (P&L) insurance industry.

This study was conducted in two stages. First the authors applied DEA model to calculate efficiency scores. In the second stage, a translog model was used to correlate the level and structure of CEO compensation and the efficiency for the sample P&L insurers over the period of 2000‐2006.

Firm efficiency is positively and significantly associated with total CEO compensation. While revenue efficiency is associated with CEO cash compensation, cost efficiency is associated with incentive compensation.

These findings suggest that while CEO compensation is tied to both revenue and cost efficiency, revenue efficiency is more important in determining cash compensation, and cost efficiency is more prevalent in influencing incentive compensation.

This is the first paper to use efficiency scores as proxies for firm performance to explore the relation between CEO compensation and firm performance in the P&L insurance industry. Due to the nature of insurance business, using efficiency as a performance measurement is more appropriate than accounting and financial ratios since it enables us to net out the effects of differences in exogenous firm‐specific conditions that are beyond management's control.

This paper evaluates the working capital management (WCM) efficiency of the Indian manufacturing industries through data envelopment analysis (DEA) and empirically investigates the influence of several exogenous variables on the WCM efficiency.

WCM efficiency was calculated using BCC input-oriented DEA model. Further, the panel data fixed effect model was used on a sample of 1391 Indian manufacturing firms spread across nine industries, covering the period from 2008 to 2019.

Firstly, the WCM efficiency of Indian manufacturing industries has been stable over the analysis period. Secondly, the capacity to generate internal resources, size, age, productivity, gross domestic product and interest rate significantly influence WCM efficiency.

First, the selected study period has observed various economic uncertainties including demonetization and recession, so the scenario might differ in normal conditions or country-wise. Second, the findings might not be generalizable to the developed economies, since the current study sample belongs to a developing economy, which further provides scope for comparative study.

An efficient model for managing the working capital comprising most vital determinants could enhance the firms' valuation and goodwill. Also, this study would be helpful for financial executives, manufacturers, policymakers, investors, researchers and other stakeholders.

This study estimates the industry-wise WCM efficiency of the Indian manufacturing sector and suggests measures to the concerned parties on areas to focus on and provide evidence on the estimated relationships of firm-level and macroeconomic determinants with WCM efficiency.

Firms are working in a complex environment in which the updated information increase the pace of precise decision making and reduce the risk of wrong decisions. Therefore, discovering firms’ performance is a major issue. The purpose of this paper is to evaluate the efficiency of Iranian plastic producing companies by using data envelopment analysis (DEA). It also discovers various drivers that significantly affect the efficiency of enterprises.

The authors studied a sample of 17 manufacturing firms to examine the relative efficiency of companies. They, then, evaluated the effects of efficiency drivers and used two methods for these purposes: DEA and bootstrapped Tobit regression model.

The study has shown that two manufacturing firms out of selected 17 are efficient under the Charnes, Cooper, and Rhodes model. Also, nine out of 17 plastic producing companies are productive under the Banker, Charnes, and Cooper model. The results of Tobit regression shows that only two efficiency drivers out of four have a significant positive influence on the efficiency of plastic producing firms.

Considering one industry and country limits the generalizability of the results provided. Besides, data availability has limited the analysis in some parts, particularly in bootstrapped Tobit regression.

The authors listed this section into benchmarking and strategical management; more importantly, the suggestions for improving the chemical industry and its future evolution are presented.

The paper is classified into two issues: the efficiency of plastic producing firms in Iran and evaluating the reason for inefficiency, apart from internal managerial procedures.

Financial analysts are frequently viewed as information intermediaries who process and interpret firms' financial reports for other market participants. Much recent research, however, has cast doubts on analysts' ability to fully utilize the information in firms' financial reports. Using an alternative approach, this study aims to provide evidence on how sophisticated analysts are at using information in firms' financial reports.

The paper estimates different measures of firms' operational efficiency, all of which are derived from financial statement data, and compares the strength of the association between these measures and analysts' absolute forecast errors. It then compares a sophisticated frontier‐based measure of firms' operational efficiency that evaluates firms' performance relative to their competitors with three more traditional efficiency measures; specifically the return on asset (ROA) ratio, industry‐adjusted ROA, and the return on equity ratio.

The results indicate that the more sophisticated frontier‐based measure is more strongly negatively associated with analysts' absolute forecast errors than the other three measures. The results thus suggest that analysts are capable of undertaking a sophisticated analysis of the information in firms' financial reports, at least as it pertains to operational efficiency.

To the extent that analysts serve as a key group of users of financial information, these results are likely to be of interest to accounting policy makers.

Did the Soviet development strategy of according high priority to firms in heavy industry give these firms an advantage during Russia's transition to a market‐oriented economy? This paper seeks to answer this question.

To document industry variation in efficiency between priority and non‐priority sectors, the paper uses firm‐level data collected in 1992 and 1995 to estimate a stochastic frontier production function for 11 industries. It then aims to investigate which firm characteristics contributed to variation in technical efficiency between 1992 and 1995.

Firms in low‐priority sectors exhibited higher efficiency in 1992 than firms in high‐priority sectors; by 1995, efficiency differences diminish. Efficiency gains were relatively higher in industries which experienced the largest percentage output declines. Non‐state ownership tends to improve efficiency, but the ownership effect varies by industry and over time. The paper rejects the hypothesis that export experience increases efficiency, and this result is especially strong in 1995. Location in Moscow proved to be a positive factor, and the benefit grew over time.

Panel data were not used because near‐hyper‐inflationary conditions and changes in capital valuation methods make it impossible to accurately adjust output and capital values between 1992 and 1995; and because firms that divided into multiple units or changed industry classification between 1992 and 1995 would need to be dropped, reducing sample size considerably and making industry‐level analysis impossible.

The paper provides a baseline for analyzing the impact of the transition on the performance of Russian manufacturing firms. It evaluates the influence of location (capital city effect) on firm performance, and demonstrates that privatization alone is not sufficient to improve efficiency.

This is the first study to examine the initial impact of transition on the efficiency of Russian firms across 11 industries, with focus on differences between former priority and non‐priority sectors. The results underscore the magnitude of structural dislocation caused by planners' preferences in the former Soviet economy.

This study examines the innovation-efficiency linkage for Indian and Chinese manufacturing and service firms.

We applied the stochastic production and cost frontier approach to determine the output and cost efficiency of the firms surveyed in World Bank enterprise surveys. We then used both unconditional and conditional propensity score matching (PSM) estimation techniques to examine the effects of innovation as well as R&D on output and cost efficiency of the firms surveyed.

The study results suggest that innovation-efficiency linkage varies between countries and sectors. Innovations significantly raise output and cost efficiency of Indian manufacturing firms, whereas innovations in Chinese manufacturing firms are cost-oriented and negatively affect output efficiency. For the service firms of both countries, innovations are significantly positively linked with output and cost efficiency. The study also suggests that R&D acts as a crucial moderator for innovation-efficiency linkage for Chinese manufacturing firms but not for Indian firms, and the interaction effects of innovations are not substantially higher in magnitude than their individual effects. Finally, conditional PSM results suggest knowledge spillover for effective innovations of Indian firms, whereas R&D is a must for substantial innovation-efficiency linkage in Chinese firms.

This study offers quite a few crucial policy decisions concerning the relationship between innovation and efficiency as well as the moderation effect of R&D on innovation-efficiency linkage. It concludes that the effects of innovation on firms' efficiency and the role of R&D as a moderator of the innovation-efficiency relationship differ between India and China across the manufacturing and service sectors.