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This paper aims to investigate the innovation pathway of gerontechnological enterprises under the market-organization-technology (MOT) perspective through configuration analysis.

Based on the analytical framework of technology, organization and market, this paper conducts configuration analysis on the cases of 55 elderly-friendly enterprises in China combined with fuzzy-set qualitative comparative analysis (fsQCA).

First, this study identifies the three first-level preconditions affecting innovation performance: organization's architectural innovation, technology adapting to aging and market environment attention on the innovation pathway of gerontechnological enterprises. These three first-level conditions include six sub-conditions. Second, this study investigates three innovation pathways by analyzing the configuration effects of preconditions: Configuration 1, technology-balanced type; Configuration 2, organization-market linkage type and Configuration, 3 balanced type. Third, there are differences in the distribution of different configuration types in subdivided industries. The technology-balanced configuration is mainly concentrated in design-driven innovative enterprises, the organization-market linkage configuration is mainly concentrated in medical auxiliary equipment enterprises and the balanced configuration is mainly concentrated in smart elderly care service platform enterprises empowered by digital technology. Fourth, there are differences in the innovation impact paths of the same configuration type. However, the essence lies in the high-level innovation performance formed by the coordinated evolution of technology, organization and market factors, reflecting the characteristics of the same goal through different routes.

The authors' study generates new insights for innovation managers of gerontechnological enterprises about the innovation pathway.

This research enriches innovation management by integrating the linkage adaptation relationship among market, organization and technology factors; further research studies on the different configuration types suitable for different types of enterprises, as well as differentiated innovation pathways under the same configuration type, could contribute to the study on the innovation pathway under a premise of MOT.

The business landscapes in Asia and Africa are predominantly characterized by small and medium enterprises (SMEs) facing significant resource constraints. Understanding the capability dynamics of these enterprises in such contexts carries significant implications for theory and practice. This paper aims to addresses a crucial question of whether increasing customer involvement capability consistently yields the necessary rent for enterprises operating under resource constraints in emerging markets in Asia and Africa. By investigating this question, the paper offers SMEs a more nuanced approach to capability development, enabling them to achieve better returns on their investments.

To ensure the robustness of the findings, data were collected from SME service firms operating in two emerging economies: India (Asia) and Ghana (Africa). Data were collected in two waves to allow for catering to specific environmental conditions not accounted for in the study. Two-stage data analysis was then conducted to test the hypothesized relationships across the two countries.

The findings reveal that customer involvement capability does not always lead to an increase in firm-level competitiveness, and the effect follows an inverted U-shaped pattern. However, the nature of this relationship varies under different market conditions in both contexts. Specifically, in periods of low customer demand and intense competition, the relationship is linear and positive. On the other hand, in periods of high demand and competition, the relationship becomes inverted U-shaped, returning to a direct relationship with firm-level competitiveness.

This paper provides a resolution to the critical issue of whether customer involvement capability consistently delivers firm performance benefits, particularly for resource-constrained SMEs in emerging markets. By explaining how SMEs in emerging markets can fully capitalize on their capability development to optimize their resources, this paper makes a distinctive contribution. Moreover, it sheds light on the importance of aligning involvement capabilities with prevailing market conditions for SMEs to reap the maximum benefits.

The purpose of this study is to address why managers enter the excessive market. A comparison of the facts and perceptions of entrants relative to success in the market shows that many entrants are confident about the viability of their businesses and enter the market. Accordingly, the authors simulate market entry decisions to detect behavioral biases.

The authors adapted the entry decisions simulation method, which is supported by the theoretical foundations of signal detection theory (SDT) and signaling theory. The simulation model is implemented on the Anaconda platform and written in Python 3.

The results of this study suggest that overestimation relates to excess market entry. Also, the proportion of excess entry under difficult conditions is always higher than under easy conditions.

This research helps managers and firms think about their and their competitors' abilities and evaluate them before entering the market. Policymakers and practitioners can also design programs such as experiential learning to help entrants assess their skills.

So far, no research has investigated the role of overconfidence under different market conditions. Accordingly, this study contributes to the current market entry literature by disentangling the debate between absolute and relative confidence and by considering the role of task difficulty.

This paper aims to explain the causal complexity between ecosystems of doing business and living standards based on the theoretical model of the ecosystem of doing business proposed by Li (2019) and Du et al. (2020). By integrating ecological theory, transaction cost theory and institutional logics theory, this study explored effective ecosystems of doing business that achieve high living standards and explained the interpretive mechanisms behind different ecosystems of doing business. Moreover, this study also analyzed whether there were any necessary elements that lead to high living standards and discussed how the interactions between these elements influence carrying capacity and transaction costs from government logic and market logic, thus affecting living standards.

In this study, fuzzy set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) were combined to analyze the data from the 2020 China City Statistical Yearbook, covering the main socioeconomic statistical data of cities at all levels in 2019.

This study found that no individual factor of the ecosystems of doing business was necessary to achieve high living standards, but the high level of human capital, innovation capacity, financial access and market demand play a significant role in achieving high living standards. Furthermore, two effective types of ecosystems of doing business lead to high living standards, namely, market dominance (government’s “invisible hand” or “nudging hand”) and government–market logic mutualism/symbiosis (government’s “helping hand”).

First, this work found that individual elements were not a necessary condition for high living standards, not only in kind but also in degree, complementing fsQCA with NCA, which indicates that environmental elements can be substituted by others. Second, this study considered the complex effects and explained the mechanisms behind different ecosystems of doing business, drawing on ecological theory, transaction cost theory and institutional logics theory from a configurational perspective. This study deepened the theories’ applications in the field of living standards and further discussed the elements interactions. Third, this study introduced configurational perspective and QCA into living standards research and adopted a mixed method that combines fsQCA and NCA to analyze the causal complexity between ecosystems of doing business and people’s living standards.

Stirred by scant regard for market phases in portfolio performance assessments, the current paper investigates the active versus passive investment strategies under the bull and bear market conditions in emerging markets focusing on South Africa as a case study.

Methodologically, the measures of Jensen's alpha and Treynor index are applied to the monthly returns of 20 funds from January 2010 to June 2022.

The results are enlightening; though they contradict developed market evidence, they are consistent with emerging market trends. The findings show that actively managed funds outperform the market benchmark and passive investing style under bear and normal market conditions. Passive investment strategy outperforms both market benchmark and actively investing style under bull market conditions.

In the face of improved market efficiency, increased liquidity and recent technological impact, the findings of this study have practical application. The study outcomes should inform and update global investors, especially asset managers interested in emerging markets; however, the limitations of the study should also be considered.

While limited studies consider market conditions when comparing and contrasting the performance of passive versus active investing, such consideration is lacking in emerging markets. The current study corrects this literature imbalance.

The authors target the interrelationships between non-fungible tokens (NFTs), decentralized finance (DeFi) and carbon allowances (CA) markets during 2021–2023. The recent shift of crypto and DeFi miners from China (the People's Republic of China, PRC) green hydro energy to dirty fuel energies elsewhere induces investments in carbon offsetting instruments; this is a backdrop to the authors’ investigation.

The quantile vector autoregression (VAR) approach is employed to examine extreme-quantile-connectedness and spillovers among the NFT Index (NFTI), DeFi Pulse Index (DPI), KraneShares Global Carbon Strategy ETF price (KRBN) and the Solactive Carbon Emission Allowances Rolling Futures Total Return Index (SOLCARBT).

At bull markets, DPI is the only consistent net shock transmitter as NFTI transmits innovations only at the most extreme quantile. At bear markets, KRBN and SOLCARBT are net shock transmitters, while NFTI is the only consistent net shock receiver. The receiver-transmitter roles change as a function of the market conditions. The increases in the relative tail dependence correspond to the stress events, which make systemic connectedness augment, turning market-specific idiosyncratic considerations less relevant.

The shift of digital asset miners from the PRC has resulted in excessive fuel energy consumption and aggravated environmental consequences regarding NFTs and DeFi mining. Although there exist numerous studies dedicated to CA trading and its role in carbon print reduction, the direct nexus between NFT, DeFi and CA has never been addressed in the literature. The originality of the authors’ research consists in bridging this void. Results are valuable for portfolio managers in bull and bear markets, as the authors show that connectedness is more intense under such conditions.

This study examined the impact of; COVID-19 investor sentiment, COVID-19 cases, geopolitical risk (GPR), economic policy uncertainty (EPU), oil returns and Islamic banking on bank stock returns. In addition, it examined whether Islamic bank stock returns differed from conventional banks when interacting with selected variables.

This study consisted of 137 conventional and Islamic stock market listed banks in 16 Middle East and North Africa (MENA) countries from February 2020 to July 2021. Monthly data were used for bank stock returns, number of COVID-19 cases, COVID-19 investor sentiment, oil price and EPU, while GPR data were obtained annually. This paper used unconditional quantile regression (UQR) in its analysis.

COVID-19 investor sentiment and EPU negatively influenced bank stock returns. However, oil returns were only positive and significant in first quantile. Conversely, GPR negatively impacted bank returns up to the median quantile, while the impact was positive in upper quantiles. Islamic banks outperformed conventional banks in all quantiles. Additionally, GPR negatively influenced Islamic bank returns up to 75th quantile, while oil returns negatively impacted Islamic bank returns up to 95th quantile. Ultimately, COVID-19 investor sentiment and EPU positively influenced Islamic bank returns up to 95th quantile.

Market conditions must be considered when implementing investment decisions and policies, as the effects of market shocks are mostly asymmetrical. For example, it is important for international investors to take into consideration asymmetric factors, such as market uncertainty in oil market. Especially in bearish Islamic markets, bad news concerning uncertainty can be perceived as riskier than good news.

A change in health sentiment, such as COVID-19 cases and COVID-19 investor sentiment, can be used to determine future direction of conventional and Islamic stock markets. Asymmetric effects associated with market news can make portfolio management more effective. COVID-19 investor sentiment states can be used to predict Islamic market index dynamics in MENA region.

This paper offered insight into heterogeneity of market conditions and dependencies of Islamic banks' stock market returns on COVID-19 investor sentiment and uncertainty, among others that should be considered when implementing investment decisions and policies.

This study aims to examine the tail connectedness between the Chinese and Association of Southeast Asian Nations (ASEAN) stock markets. More specifically, the authors measure the return spillovers at three quantile levels: median (t = 0.5), lower extreme (t = 0.05) and upper extreme (t = 0.95). The connectedness at extreme upper and lower quantiles provides insightful information to investors regarding tail risk propagation, which ultimately suggests that investors adjust their portfolios according to the extreme bullish and bearish market conditions.

The authors employ the quantile connectedness approach of Ando et al. (2022) to examine the quantile transmission mechanism among the ASEAN and Chinese stock markets.

The results show significant evidence of a higher level of connectedness between Chinese and ASEAN stock markets at extreme upper and lower quantiles compared to the median quantiles, which suggests the use of a quantile-based connectedness approach instead of an average-measure-based one. Furthermore, the time-varying connectedness analysis shows that the total spillovers reach the highest peaks during the global financial crisis, the Chinese stock market crash and the COVID-19 pandemic at the upper, lower and median quantiles. Finally, the static and dynamic pairwise spillovers between the Chinese and ASEAN markets vary over quantiles as well.

This study is the first attempt to examine quantile vector autoregression (VAR)-based return spillovers between China and ASEAN stock markets during different market statuses. Besides, the COVID-19 has intensified the uncertainty in Asian countries, mainly China and ASEAN economies.

This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.

This study investigates how the degree of internationalization (DOI) affects the financial performance of emerging market companies by making the distinction between export intensity and multinationality (i.e. foreign direct investment). The authors argue that the different DOI-performance patterns in the literature relate to different internationalization approaches, which are moderated in distinct ways by formal institutions in the home country.

Based on data of Brazilian firms in several industries and with different internationalization patterns including 100 exporting firms and 30 multinational companies with varying degrees of multinationality over a period of five consecutive years, the authors test their hypotheses using an unbalanced panel data with 346 firm-year observations. In order to test how the quality of formal institutions moderate the DOI-performance relationships, the authors estimate the changes in the slope of the regression line by adding and subtracting one standard deviation to the Worldwide Governance Indicators (WGI) variables.

A positive and linear association between export intensity-performance (EI-P) highlights the location specific comparative advantages of exporting Brazilian firms, while the multinationality-performance (M-P) relationship points to a horizontal S-shape pattern which conforms to the theoretical assumptions of the three-stage internationalization process. Formal institutions moderate positively the EI-P relationship, but moderate negatively each of the three stages of the M-P relationship.

The findings from this study provide critical insights that contribute to the ongoing debate on how formal institutions in the home country affect the DOI-performance relationship of emerging market companies (EMCs). However, the authors consider that it has limitations as they focused exclusively on formal institutions captured by governance institutions in the Brazilian context.

This study provides relevant insights to managers and policy makers. Findings reveal that strong formal institutions in the home country make it easier (cheaper) for EMCs to invest abroad, and, at the same time, increase the efficiency of exporting firms and positively influence financial performance. Moreover, results show that during downturns in their domestic markets, multinational EMCs outperform domestic firms. In that sense, while policy makers can promote the internationalization and competitiveness of EMCs by implementing more supportive formal institutions, managers should consider a proactive approach and invest abroad when conditions in the home country are favorable.

By making the distinction between export intensity and multinationality this study contributes to the literature on the DOI-performance of EMCs providing a more nuanced view on how formal institutions in the home country moderate the EI-P and M-P relationships in different ways.