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The study evaluates the influence of human capital efficiency (HCE) and market power on bank performance.

The study employs two measures of bank performance: profitability and stability. Unbalanced panel data of 35 banks operating in Kenya for 2005–2020 collected from published financial statements is utilized. The study employs the feasible generalized least squares (FGLS) method in the analysis and the two-step system generalized method of moments (GMM) for robustness check.

The study affirms an inverted U-shaped relationship between market power and bank performance. The effect of market power on bank profitability is enhanced when a bank has highly efficient human capital. Further, HCE significantly impacts bank stability for banks with low HCE. Interestingly, a further increase in HCE narrows the net interest margins for banks with high HCE, conferring welfare benefits to customers as interest rate spreads shrink.

This study provides important insights into the role of human capital in bank performance. First, banks ought to invest in promoting HCE through training and development. As regulators root for bank consolidation, attention to HCE is imperative for fostering profitability and stability.

The study fills an essential gap in the literature by evaluating the effect of firm-level market power on bank performance in an emerging market. We adopt a novel stochastic frontier estimator to generate the Lerner index. Further, this is the first study known to the authors to evaluate the effect of market power on bank performance in the context of human capital efficiency variations.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

This study aims to examine the resilience of Peruvian startups during the COVID-19 pandemic using a framework proposed by Lengnick-Hall et al. (2011), in which resilience impacts organizational strengthening. The goal is to identify those characteristics that allowed certain startups to discover growth opportunities amid this crisis.

This study analyzed human, social and entrepreneurial capital variables in Peruvian startups using data from a survey conducted in July 2020. Binary logistic regression was used to determine which organizational resources increased the probability of identifying growth opportunities during the pandemic.

The findings suggest that human capabilities become secondary in extreme crises such as pandemics. Critical factors for startup resilience include commercial partnerships with established firms, founders’ capital investment, business maturity and adoption of advanced digital technologies.

This research provides unique insights into startup resilience and growth in Peru during the COVID-19 crisis. The authors observed that business growth during this period was largely unpredictable, with less emphasis on human capabilities. The study highlights the importance of external factors in resilience, the role of collaboration between established firms, the integration of advanced digital technologies and the influence of founders’ investments and business maturity in navigating difficult times.

Este estudio examina la resiliencia de las startups peruanas durante la pandemia de COVID-19 utilizando un marco propuesto por Lengnick-Hall et al. (2011), en el que la resiliencia tiene un efecto en el fortalecimiento de las organizaciones. Su objetivo es identificar las características que permitieron a ciertas startups descubrir oportunidades de crecimiento en medio de esta crisis.

Analizamos variables de capital humano, social y empresarial en startups peruanas utilizando datos de una encuesta realizada en julio de 2020. Se utilizó regresión logística binaria para determinar qué recursos organizativos incrementaban la probabilidad de identificar oportunidades de crecimiento durante la pandemia.

Nuestros hallazgos sugieren que las capacidades humanas pasan a un segundo plano en crisis extremas como las pandemias. Los factores críticos para la resiliencia de las startups incluyen las asociaciones comerciales con empresas establecidas, la inversión de capital de los fundadores, la madurez empresarial y la adopción de tecnologías digitales avanzadas.

Esta investigación proporciona una visión única sobre la resiliencia y el crecimiento de las startups en Perú durante la crisis COVID-19. Observamos que el crecimiento empresarial durante este período fue en gran medida impredecible, con menos énfasis en las capacidades humanas. El estudio subraya la importancia de los factores externos en la resiliencia, el papel de la colaboración con las empresas establecidas, la integración de tecnologías digitales avanzadas, la influencia de las inversiones de los fundadores y la madurez empresarial para navegar en tiempos difíciles.

Este estudo examina a resiliência das startups peruanas durante a pandemia da COVID-19 usando uma abordagem proposta por Lengnick-Hall et al. (2011), na qual a resiliência tem um efeito fortalecedor nas organizações. Seu objetivo é identificar as características que permitiram que determinadas startups descobrissem oportunidades de crescimento em meio a essa crise.

Analisamos variáveis de capital humano, social e empresarial em start-ups peruanas usando dados de uma pesquisa realizada em julho de 2020. A regressão logística binária foi usada para determinar quais recursos organizacionais aumentaram a probabilidade de identificar oportunidades de crescimento durante a pandemia.

Nossas análises sugerem que as capacidades humanas se tornam secundárias em crises extremas, como as pandemias. Os fatores essenciais para a resiliência das startups incluem parcerias comerciais com empresas estabelecidas, investimento de capital dos fundadores, maturidade dos negócios e adoção de tecnologias digitais avançadas.

Esta pesquisa fornece informações exclusivas sobre a resiliência e o crescimento de startups no Peru durante a crise da COVID-19. Observamos que o crescimento das empresas durante esse período foi amplamente imprevisível, com menos ênfase nas capacidades humanas. O estudo destaca a importância de fatores externos na resiliência, o papel da colaboração com empresas estabelecidas, a integração de tecnologias digitais avançadas e a influência dos investimentos dos fundadores e da maturidade dos negócios na superação de tempos difíceis.

This study aims to investigate the relationships between managers’ cognitive styles, dynamic managerial capabilities and firms’ perceived international performance. The study is based on cognitive-experiential self-theory, dynamic managerial capabilities and international entrepreneurship.

Data were collected from 283 managers of small medium enterprises (SMEs) in Türkiye, an emerging economy. The research was conducted using quantitative methods, and Smart partial least squares (PLS) 4 software was used for data analysis. The data were examined through structural equation modelling and mediation analyses.

Findings indicate that rational cognitive styles positively influence managerial human capital, managerial social capital, managerial cognition and perceived international performance. However, the effect of intuitive cognitive styles was confirmed only on managerial cognition. Additionally, it was found that managerial cognition positively affects perceived international performance, whereas managerial social capital has a negative impact. However, the effects of managerial human capital could not be confirmed. Moreover, a full mediation relationship of managerial cognition between intuitive cognitive styles and perceived international performance was identified.

This research carves out a unique niche by synergizing cognitive-experiential self-theory with dynamic managerial capabilities to investigate their conjoined effect on firms’ international performance, an area previously underexplored. Unveiling insights from burgeoning economies like Türkiye enriches the existing body of knowledge, offering substantial contributions to the field of international business.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.

In the context of an absence of studies examining the interrelationship between Indian construction industry and residential real estate sector, the study aims to develop and test a conceptual framework to stimulate construction industry through optimisation of housing market in India. The developed conceptual framework lays down a blueprint to assess the interaction between construction industry and housing market in other countries.

Means of stimulation of construction industry by residential real estate sector were identified. Housing market was examined to identify factors constituting consumer-centric delivery and consumer-empowered demand. Supply side of housing market was probed to identify underlying factors stifling housing delivery. The identified factors were put together to form the conceptual framework. A questionnaire was developed and administered to the delivery-side stakeholders of housing market.

The study demonstrates significant correlations between real estate investment-led construction industry output stimulation and consumer-centric residential real estate delivery. The deterrents to consumer-centric housing delivery have been ascertained to be having an impact on time, cost and scope of housing projects. Significant correlations have been ascertained between the deterrents. On the demand-side, skills, awareness and engagement of consumers are strongly correlated with each other. Affordability of housing is rightfully correlated with all the three means of stimulation of construction industry output.

Specific to the Indian context, the study presents and validates a novel conceptual framework aimed at stimulation of construction industry output through interventions in housing market.

Surprisingly little is known of the various methods of security analysis used by financial analysts with industry-specific knowledge. Financial analysts’ industry knowledge is a favored and appreciated attribute by fund managers and institutional investors. Understanding analysts’ use of industry-specific valuation models, which are the main value drivers within different industries, will enhance our understanding of important aspects of value creation in these industries. This paper contributes to the broader understanding of how financial analysts in various industries approach valuation, offering insights that can be beneficial to a wide range of stakeholders in the financial market.

This paper systematically reviews existing research to consolidate the current understanding of analysts’ use of valuation models and factors. It aims to demystify what can often be seen as a “black box”, shedding light on the valuation tools employed by financial analysts across diverse industries.

The use of industry-specific valuation models and factors by analysts is a subject of considerable interest to both academics and investors. The predominant model in several industries is P/E, with some exceptions. Notably, EV/EBITDA is favored in the telecom, energy and materials sectors, while the capital goods industry primarily relies on P/CF. In the REITs sector, P/AFFO is the most commonly employed model. In specific sectors like pharmaceuticals, energy and telecom, DCF is utilized. However, theoretical models like RIM and AEG find limited use among analysts.

This is the first paper systematically reviewing the research on analyst’s use of industry-specific stock valuation methods. It serves as a foundation for future research in this field and is likely to be of interest to academics, analysts, fund managers and investors.

This study aims to identify necessary conditions for innovative entrepreneurship in cities and determine similarities in entrepreneurial configurations among them.

The authors assessed the necessary conditions for various levels of entrepreneurial output and categorized cities based on similar patterns by applying necessary condition analysis (NCA) and cluster analysis in a sample comprised of 101 cities from the entrepreneurial cities index, representing a diverse range of urban environments in Brazil. A comprehensive data set, including both traditional indicators from official Bureau of statistics and nontraditional indicators from new platforms of science, technology and innovation intelligence, was compiled for analysis.

Bureaucratic complexity, urban conditions, transport infrastructure, economic development, access to financial capital, secondary education, entrepreneurial intention, support organizations and innovation inputs were identified as necessary for innovative entrepreneurship. Varying levels of these conditions were found to be required for different entrepreneurial outputs.

The static nature of the data limits understanding of dynamic interactions among dimensions and their impact on entrepreneurial city performance.

Policymakers can use the findings to craft tailored support policies, leveraging the relationship between city-level taxonomy and direct outputs of innovative entrepreneurial ecosystems (EEs).

The taxonomy and nontraditional indicators sheds light on the broader societal benefits of vibrant EEs, emphasizing their role in driving socioeconomic development.

The cluster analysis combined with NCA’s bottleneck analysis is an original endeavor which made it possible to identify performance benchmarks for Brazilian cities, according to common characteristics, as well as the required levels of each condition by each city group to achieve innovative entrepreneurial outputs.

We expect to provide a complete theoretical framework and large sample evidence on the impact of corporate social responsibility (CSR) on the efficiency of labor investment. We also hope to provide micro-evidence based on labor investment behavior for the two-sided impact of corporate CSR behavior.

This paper measures labor investment efficiency by estimating the difference between actual and expected net hiring of enterprises. CSR is measured on the basis of the CSR score of Chinese listed companies published by Hexun.com. A regression model is constructed to analyze the relationship between CSR and labor investment efficiency. Possible endogeneity problems are controlled by lagging independent variables, propensity score matching method and difference-in-difference method.

Results show that CSR can improve labor investment efficiency by reducing over-hiring and under-hiring in emerging markets. The existence of the mediating effect of agency cost, information disclosure quality and employment fluctuation confirms that CSR improves labor investment efficiency through two mechanisms of corporate governance and labor market friction. The improvement effect of CSR on labor investment efficiency is more significant in non-state-owned, high CEO shareholding ratio and high-average urban wage enterprises.

In conclusion, our study is an important supplement to the existing research on the factors affecting labor investment efficiency. Our research conclusions will be helpful for enterprises in developing countries or enterprises in labor-intensive industries to improve labor investment inefficiency. The conclusion of the mechanism analysis in this paper provides more complete and reliable microscopic evidence for accurately identifying the specific path of CSR's impact on labor investment efficiency. This paper verifies the positive impact of CSR from the perspective of labor investment efficiency in the context of a developing country, which provides evidence for the theoretical conflicts related to CSR based on the effectiveness of enterprise labor investment decisions.

The aims of the current study were twofold: first, to rank the world’s emerging economies based on a novel National Intellectual Capital Index (NICI) and its components; and second, to examine the impact of NICI and its components on economic growth, measured in terms of real GDP per capita.

We employed principal component analysis (PCA) to construct the novel NICI based on five key socio-economic indicators including (1) national human capital, (2) national structural capital, (3) national relational capital, (4) national informational capital and (5) national innovational capital. These indicators are publicly available for many countries. The index was generated by considering the most appropriate socio-economic indicators as precise measures of NIC from the Penn world table (version 10.0), the World Bank’s database of world governance and development indicators and the KOF globalization across the selected emerging economies.

The empirical findings revealed that national human capital is a significant driver of NIC, corresponding to higher economic growth. This is followed by national informational capital, national relational capital, national innovation capital and national structural capital. Furthermore, results indicate that the contribution of national structural capital is marginal compared to other critical strands of NIC.

NIC is generally considered the most valuable strategic resource for driving knowledge economies, especially in the Industry 5.0 revolution. Ranking emerging economies based on the NICI sheds light on the accumulated stock of NIC and how it contributes to and improves the economic growth of these economies. The stock of NIC is considered a critical success factor for measuring both current and future economic prosperity. Therefore, using the socio-economic indicators of KOFGI as accurate measures of NICI will assist policymakers in formulating and implementing relevant policies to enhance the accumulation of knowledge-based capital, which are critical components of NIC.

To the best of the authors' knowledge, this is the first study of its kind, both theoretically and empirically, to measure the National Intellectual Capital Index (NICI) using the most nascent socio-economic indicators of NIC. Moving forward, this study evaluates the impact of NICI and its components on economic growth, which is a relatively sparse area of research in the context of emerging knowledge economies.