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Academic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.

Using data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.

Our analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.

Our results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.

This study investigates the role of market concentration and efficiency in banking system stability during the COVID-19 pandemic. We empirically test the hypothesis that market concentration and efficiency are significant determinants of bank performance and stability during the time of crises, using a sample of 575 banks in 20 countries in the Middle East and North Africa (MENA).

The main sources of bank data are the BankScope and BankFocus (Bureau van Dijk) databases, World Bank development indicators, and official websites of banks in MENA countries. This study combined descriptive and analytical approaches. We utilize a panel dataset and adopt panel data econometric techniques such as fixed/random effects and the Generalized Method of Moments (GMM) estimator.

The results reveal that market concentration negatively affects bank profitability, whereas improved efficiency further enhances bank performance and contributes to the banking sector’s overall stability. Furthermore, our analysis indicates that during the COVID-19 pandemic, bank stability strongly depended on the level of market concentration, but not on bank efficiency. However, more efficient banks are more profitable and stable if the banking institutions are Islamic. Similarly, Islamic banks with the same level of efficiency demonstrated better overall financial performance during the pandemic than their conventional peers did.

The main limitation is related to the period of COVID-19 pandemic that was covered in this paper (2020–2021). Therefore, further investigation of the COVID-19 effects on bank profitability and risk will require an extended period of the pandemic crisis, including 2022.

This study provides information that will enable bank managers and policymakers in MENA countries to assess the growing impact of market concentration and efficiency on the banking sector stability. It also helps them in formulating suitable strategies to mitigate the adverse consequences of the COVID-19 pandemic. Our recommendations are useful guides for policymakers and regulators in countries where Islamic and conventional banking systems co-exist and compete, based on different business models and risk management practices.

The authors contribute to the banking stability literature by investigating the role of market concentration and efficiency as the main determinants of bank performance and stability during the COVID-19 pandemic. This study is the first to analyze banking sector stability in the MENA region, using both individual and risk-adjusted aggregated performance measures.

The study examines the changes in audit market concentration, auditor choice and audit quality in Russia following International Financial Reporting Standards (IFRS) adoption. Scholars have called for further examination of the effects of IFRS adoption on auditors, with an emphasis on the importance of analyzing emerging markets that are characterized by enforcement challenges and lack of proper infrastructure. It focuses on a unique feature of Russian companies – dual audits under Russian Accounting Standards (RAS) and IFRS – and investigates changes in audit concentration and audit quality for the two audit markets.

The authors rely on the audited financial statements of Russian public companies and perform pre-/post-IFRS adoption estimation using a logit regression to ascertain whether public firms change auditors from local firms with limited IFRS expertise to those with global reputation, namely Big 4 audit firms. Further, they examine whether the change in audit market concentration post-2012 affects audit quality as proxied by companies' propensity to receive a modified audit opinion and discretionary accruals. Auditor attributes were hand-collected from audited financial statements and matched with financial variables from Datastream.

The IFRS audit market was dominated by the Big 4 audit firms prior to 2012, and there is strong evidence that audit market share (concentration) increases for IFRS reports but not for RAS reports. In addition, companies are more likely to choose a Big 4 audit firm for an RAS audit, conditional upon a Big 4 firm conducting the IFRS audit. The authors do not find evidence of decrease in the probability of audit firms issuing a modified audit opinion under either RAS or IFRS, indicating that, in the Russian setting, increased auditor concentration post-IFRS adoption does not lead to enhanced risk or decline in audit quality. Moreover, they find that discretionary accruals decline post-2012. Overall, the findings indicate that the concern of global regulators regarding audit market concentration is not justified.

The Russian reporting environment is unique and generally characterized by significant agency problems, and the study’s estimation sample is not large, compared to prior studies conducted predominantly in Western jurisdictions. Nevertheless, the authors shed light on the audit concentration phenomenon within emerging markets, for which empirical evidence is scarce. Future research could explore the impact of other capital market events and exogenous shocks, not limited to IFRS adoption, on the characteristics of Russia's audit market.

The IFRS reporting regime is commonly associated with enhanced reporting quality and improved information transparency among public companies. Yet, impairment of audit quality as a result of IFRS-driven increase in audit market share of Big 4 can potentially negate these capital market effects. This study shows that the concerns of global regulators are not valid and that audit quality does not change with increased share of Big 4 post-IFRS adoption.

Dual audits, whereby companies must prepare two sets of financial statements per the IFRS mandate, are not unique to Russia, and the evidence of IFRS reporting on the structural changes in the audit market and implications for audit quality under a dual regime is scarce. Accordingly, the study's findings are important and timely and are expected to aid regulators of countries that have announced or are contemplating the adoption of IFRS for public reporting purposes.

This paper offers a new perspective on the potential motivation for the adoption of employee ownership based on market power. Employee ownership may be linked to market power, either through contributing to firm growth that leads to market power or through industry leaders adopting employee ownership as part of rent sharing or a broader consolidation of market position. Both employee stock ownership plan (ESOP) coverage and product market concentration (PMC) have been increasing in the past two decades, providing a good opportunity to see if and how these are related.

The authors predict ESOP adoption and termination using multilevel regressions based on 2002–2012 firm- and industry-level data from the Census Bureau, Compustat and Form 5500 pension datasets.

The authors find that the top four firms in concentrated industries are more likely to adopt Employee Stock Ownership Plans (ESOPs), while having an ESOP does not predict entering the top four, apart from firm-level predictors. Tests indicate the first result does not reflect simple rent sharing with employees but instead appears to reflect an effort by firms to consolidate market power through the attraction and retention (or “locking in”) of industry talent. Other positive predictors of ESOPs include company size, being in a high-wage industry and having a defined benefit (DB) pension.

To better distinguish among hypotheses, it would be helpful to have firm-level data on managerial attitudes, strategies, networks and monopsony measures. Therefore, future research using such data would be highly useful and encouraged.

The paper includes implications for the potential usefulness of ESOPs in attracting and retaining talent and for the design of nuanced policy to encourage more broadly based sharing of economic rewards.

While prior research focuses on firm-level predictors of employee ownership, this study uses market concentration and other industry-level variables to predict the use of ESOPs. This study makes a unique contribution, broadening the current thinking on firm motives and environmental conditions predictive of firm ESOP adoption.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

In China, engineering insurance has been questioned as not being beneficial as expected. This paper seeks to further understand how China's engineering insurance industry functions and to provide a macro perspective explanation for engineering insurance's underdevelopment.

Three industrial organization hypotheses were extended to the engineering insurance context: structure conduct performance (SCP), relative market power (RMP) and efficiency structure (ES) hypotheses. This paper employed the Generalized Method of Moments (GMM) and Data Envelopment Analysis (DEA) bootstrap to test the hypotheses using panel data from 2008 to 2017.

The results suggest that the SCP paradigm is validated in China's engineering insurance market, indicating a concentrated market where the welfare of consumers (e.g. owners, contractors and designers) may be eroded. Several factors are identified to have significant impacts on engineering insurers' performance, such as the investment return, percentage of engineering business, the ratio of outstanding claims, the number of large contractors, market rivalry and entry barriers.

Despite the sheer size of China's construction industry and the urgent need to improve risk management, the insurance industry that serves construction firms engineering insurance is underdeveloped. Engineering insurance is yet to be understood from a macro perspective, which may reveal the underlying reasons for engineering insurance's underdevelopment. The industrial organization theories provided a theoretical framework to test the functioning of this specific industry. The disaggregated data (engineering line specific) is employed to ensure effective regulation and policymaking.

This study aims to analyze the development of digital market characteristics particularly focusing on how the strategic choices of platforms are not fully reflected in pricing. In addition, the implications for the development of theories of harm are investigated to explore the necessity of a relevant market definition in assessing infringement and evaluating the adequacy of Indonesian competition law.

This study is a legal analysis that uses statutory approaches, cases, comparative law and the development of theories of harm in digital mergers. The case approach is conducted by analyzing three cases decided by the Indonesia Business Competition Supervisory Commission. This approach provides insight into the response of Komisi Pengawas Persaingan Usaha concerning the merger and acquisition cases in the digital era as well as the provision of different analyses in conventional markets. However, competition can be potentially damaged in digital markets and a comparative law approach is taken by analyzing digital merger cases decided by authorities in other countries.

Results reveal that the digital market has created a “relevant market” that is challenging and blurred due to multi-sided network effects and consumer data usage characteristics. Platform-based enterprises’ prices fluctuate due to the digital market’s network effect and consumer data statistics. Smartphone prices depend on the number of apps and consumer data. Neoclassical theory focusing on product markets and location applied in Indonesia must be revised to establish a relevant digital economy market. To evaluate digital mergers, new harm theories are needed. The merger should also protect consumer data. Law Number 27 of 2022 on Personal Data Protection and Government Regulation on the Implementation of Electronic Systems and Transactions protects online consumers, a basic step in due diligence for digital mergers. The Indonesian Government should promptly strengthen the notion of “relevant markets” in the digital economy, which could lead to fair business competition violations like big data control. Notify partners or digital merger participants of the accessibility of sensitive data like transaction history and user location.

The development of digital market characteristics has implications for developing theories of harm in digital markets. Indonesian competition law needs to develop such theories of harm to analyze the potential for anticompetitive digital mergers in the digital economy era.

A new round of technological revolution is impacting various aspects of society. However, the importance of technology adoption in fostering firm innovation is underexplored. Therefore, this study aims to investigate whether robot adoption affects technological innovation and how human capital plays a role in this relationship in the era of circular economy.

Based on the robot adoption data from the International Federation of Robotics (IFR) and panel data of China's listed manufacturing firms from 2011 to 2020, this study uses regression models to test the impact of industrial robots on firm innovation and the mediating role of human capital.

The results demonstrate that the adoption of industrial robots can significantly promote high-quality innovation. Specifically, a one-unit increase in the number of robots per 100 employees is associated with a 13.52% increase in the number of invention patent applications in the following year. The mechanism tests show that industrial robots drive firm innovation by accumulating more highly educated workers and allocating more workers to R&D jobs. The findings are more significant for firms in industries with low market concentration, in labor-intensive industries and in regions with a shortage of high-end talent.

Due to data limitations, the sample of this study is limited to listed manufacturing firms, so the impact of industrial robots on promoting innovation may be underestimated. In addition, this study cannot observe the dynamic process of human capital management by firms after adopting robots.

The Chinese government should continue to promote the intelligent upgrading of the manufacturing industry and facilitate the promotion of robots in innovation. This implication can also be applied to developing countries that hope to learn from China's experience. In addition, this study emphasizes the role of human capital in the innovation-promoting process of robots. This highlights the importance of firms to strengthen employee education and training.

The adoption of industrial robots has profoundly influenced the production and lifestyle of human society. This study finds that the adoption of robots contributes to firm innovation, which helps people gain a deeper understanding of the positive impacts brought about by industrial intelligence.

By exploring the impact of industrial robots on firm innovation, this study offers crucial evidence at the firm level to comprehend the economic implications of robot adoption based on circular economy and human perspectives. Moreover, this study reveals that human capital is an important factor in how industrial robots affect firm innovation, providing an important complement to previous studies.

This research aims to identify the optimal configuration of investment which leads firms to their best competitive positions, considering the degree of concentration in the market.

The methodology was quantitative and based on secondary data with samples of 124, 106 and 90 firms from competitive environment classified as perfect competition, monopolistic competition and oligopoly, respectively. Proposed models' parameters were estimated by means of genetic algorithms.

Adjustments on firm's investment are contingent on the degree of competition they face. Results are in line with existing academic research affirmation that the purpose of investments is to create and exploit opportunities for positive economic rents and that investments allow firms to protect from rivals' competitive actions and reinforce the need for investment decision makers to consider the environment in which the firm is competing, when defining the amount of investment that must be done to achieve and maintain a favorable competitive advantage position.

This research brings two main original contributions. The first one is the identification of the optimal amount of capital and R&D investments which leads firms to their best competitive positions, contingent to the degree of concentration of the competitive environment in which they operate, and the size of the firm. The second one is related to the use of genetic algorithms to estimate optimization models that considers the three competitive environments studied (perfect competition, monopolistic competition and oligopoly) and the investment variables in the linear and quadratic forms.

Which venture capital is more beneficial in the product innovation of entrepreneurial ventures? The authors study the drawbacks and different effects of corporate venture capital (CVC) and independent venture capital (IVC) on the effectiveness and efficiency of product innovation in entrepreneurial ventures to answer this question.

This study uses a panel dataset of 502 high-tech ventures and runs the Heckman model to correct potential endogeneity issues.

The authors find that CVC increases the product innovation effectiveness of entrepreneurial ventures, but decreases their efficiency. IVC reduces innovation effectiveness and enhances efficiency. However, CVC performs less positively, while IVC performs more positively in terms of innovation effectiveness and efficiency in the B2B market than in the B2C market.

This study provides insights into how to leverage venture capital to develop new products effectively and efficiently.

This study moves beyond the current understanding of the finance-marketing interface. It delineates the two faces of venture capital and reveals the joint effects of equity stakes and market stakes between different types of venture capital and transaction markets in product innovation.