International Journal of Emerging Markets最新文献

Purpose

The aim of the paper is to rank and analyze the key strategies to sustainable finance adoption in the manufacturing sector using Fuzzy Delphi method (FDM), Interpretive Structural Modeling (ISM) and MICMAC (impact matrix cross-reference multiplication applied to a classification) analysis.

Design/methodology/approach

The study develops a novel framework to identify and analyze the mutual relationships among set of sustainable policies using extensive literature survey and experts opinion. Initially, the study found 14 strategies to implement sustainable finance with the help of vast literature. Then, the list of identified factors were screened through Fuzzy Delphi Method (FDM). Based on driving and dependence power, the final list of factors are divided into three categories.

Findings

The study findings reveal that “environmental rules and practices”, “financial incentives, tax reduction and subsidy”, have strongest driving power for promoting sustainable financial system in Pakistani manufacturing sector. Furthermore, “environmental awareness” and “long term vision” are found to be highly influenced by other corresponding elements in a system.

Practical implications

The ISM approach assists professionals, academics, and managers in identifying and ranking policies in implementing green business techniques. The hierarchical representation of ISM results provides a roadmap for decision-makers to navigate and prioritize factors effectively, facilitating the implementation of strategies that contribute to sustainable growth within organizations.

Social implications

The study results provide interesting clues regarding green finance policies that provide the foundations, incentives, protections or other provisions that support the ecological conservancy’s mission. Specifically, the findings guide that government must offer research grants to private enterprises, research and development institutions, and universities to promote environmental protection and develop transformative technologies such as waste recycling, renewable energy, carbon capture, and power consumption.

Originality/value

The exploration of strategies for sustainable finance adoption with the help of mixed methodological approach and classification of these strategies on the basis of importance level is a new attempt in the field of manufacturing sector.

Purpose

This study investigates the relationship between corporate social responsibility (CSR) and financial performance of the banking sector from the prospective of emerging countries.

Design/methodology/approach

This study obtained balance sheet and income statement data for 173 banks in 20 emerging countries from the Bankscope database from 2005–2018. The CSR-related data were taken from the Thomson Reuters ASSET4 database. Moreover, macroeconomic controls such as GDP per capita, inflation, and financial development are attained from the GFDD. The series of institutional quality indices (Political Stability, Rule of Law, Control of Corruption, Government Effectiveness, and Regulatory Quality) is obtained from the WGI. At the same time, national culture and bank regulation are attained from Hofstede Insights and Barth et al. (2013). We used the panel fixed-effects model in our baseline estimations, while 2SLS and GMM were applied to control for endogeneity.

Findings

The finding shows that CSR activities significantly improve bank performance, but the effect varies across the bank. Only environmentally friendly activities have shown a significant positive relationship with banking performance for CSR dimensions. However, the social and government dimensions did not significantly affect bank performance. Moreover, a sound institutional and regulatory environment and national norms play an important role in the nexus of CSR activities and bank performance.

Originality/value

This study provides empirical evidence that sheds light on CSR and bank performance in an emerging market context.

Purpose

This study examines the effect of social media marketing on voting intention applying a combination of fuzzy logic methodology and a multidimensional panel data model.

Design/methodology/approach

The study adopts a multidimensional panel data method that includes several fixed effects. The dependent variable is a multifaceted construct that measures the participants’ intention to vote. The independent variables are electronic word of mouth (eWOM), customisation (CUS), entertainment (ENT), interaction (INT), trendiness (TRD), candidate’s perceived image (CPI), religious beliefs (RB), gender and age. The grouping variables that signify fixed effects are employment status, level of education, mostly used social media and religion. First, the significance of said fixed effects was tested through an ANOVA process. Then, the main model was estimated, including the significant grouping variables as fixed effects.

Findings

Employment status and level of education were significant fixed effects. Also, eWOM, ENT, INT, CPI, RB and gender significantly affected participants’ voting intention.

Research limitations/implications

Being based on a questionnaire that asked participants about how they perceive different aspects of social media, the present study is limited to their perceptions. Therefore, further studies covering the voters’ behaviour in action could be efficient complements to the present study.

Practical implications

The findings could guide the political parties into prioritizing the aspects of social media in forming an effective campaign resulting in being elected.

Social implications

The findings have the potential to help the public in making better informed decisions when voting. Furthermore, the results of this study indicate applications for social media which are beyond leisure time fillers.

Originality/value

Fuzzy logic and multidimensional panel data estimates are this study’s novelty and originality. Structural equation modelling and crisp linguistic values have been used in previous studies on social media’s effect on voting intent. The former refines the data gathered from a questionnaire, and the latter considers the possibility of including different grouping factors to achieve a more efficient and less biased estimation.

Purpose

The study measures the total systemic risks and connectedness across commodities, stocks, exchange rates and bond markets in Africa during the Covid-19 pandemic.

Design/methodology/approach

The study uses the Diebold-Yilmaz spillover and connectedness measures in a generalized VAR framework. The author calculates the net transmitters or receivers of shocks between two assets and visualizes their strength using a network analysis tool.

Findings

The study found low systemic risks across all assets and countries. However, we found higher systemic risks in the forex market than in the stock and bond markets, and in South Africa than in other countries. The dynamic analysis found time-varying connectedness return shocks, which increased during the peak periods of the first and second waves of the pandemic. We found both gold and oil as net receivers of shocks. Overall, over half of all assets were net receivers, and others were net transmitters of return shocks. The network connectedness plot shows high net pairwise connectedness from Morocco to South Africa stock market.

Practical implications

The study has implications for policymakers to develop the capacities of local investors and markets to limit portfolio outflows during a crisis.

Originality/value

Previous studies have analyzed spillovers across asset classes in a single country or a single asset across countries. This paper contributes to the literature on network connectedness across assets and countries.

Purpose

The aim of the research is to examine in depth the relationship between financial support, entrepreneurship and economic growth in emerging African economies.

Design/methodology/approach

The study adopts the system-generalized methods of moments (sys-GMM) technique for data analysis and hypothesis testing on a sample of 34 African emerging economies (340 observations) from 2010 to 2019.

Findings

The results show that there is significant positive correlation between financial support, entrepreneurship, and economic growth. Moreover, entrepreneurship served as a partial mediator between financial support and economic growth in African emerging economies.

Practical implications

This research suggests that African governments should focus on entrepreneurial systems, which are essentially networks driven by the pursuit of individual opportunities and the promotion of new business creation; and introduce other forms of financial assistance, such as loans, loan guarantees, interest subsidies, technical assistance, insurance, etc.

Originality/value

The main novelty of the paper is that the authors empirically investigate the mediating role of entrepreneurship in the association between financial support and economic growth in 34 African emerging economies.

Purpose

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Design/methodology/approach

Employing a multifaceted approach, the study combines parametric and nonparametric tests, robustness checks, and regression analysis to assess the impact of Airbnb’s announcements on emerging economy stock markets.

Findings

Airbnb’s announcements affect emerging economies' stock markets with a distinct pattern of cumulative abnormal returns (CAR): negative before the announcement and positive afterward. Informed investors strategically leverage this opportunity through short selling before the announcement and acquiring positions following it. Regression analysis validates these trends, revealing that stock index returns and inbound tourism affect CAR before announcements, while GDP growth influences CAR afterward. Announcements pertaining to emerging economies exert a more pronounced impact on stock indices compared to city-specific announcements, with COVID-19 period announcements demonstrating greater significance in abnormal returns than non-COVID-19 period announcements.

Originality/value

This study advances existing literature through a comprehensive range of statistical tests, differentiation between emerging countries and cities, introduction of five macroeconomic variables, and reliance on credible primary Airbnb data. It highlights the potential for investors to leverage Airbnb announcements in emerging markets for stock market profits, emphasizing the need for adaptive investment strategies considering broader macroeconomic factors.

Purpose

While some countries have used debt to drive economic growth, the asymmetric effect on sub-Saharan African (SSA) countries has received little attention in the empirical literature. This paper therefore examines the asymmetric effect of external debts on economic growth.

Design/methodology/approach

The panel nonlinear autoregressive distributed lag (NARDL) approach was employed in the study for 29 sub-Saharan African countries from 1990 to 2021. The cross-sectional dependence test was used to determine the presence of cross-sectional dependence, while the second-generation panel unit root tests was used to examine the unit-root properties.

Findings

The empirical results show that external debt has an asymmetric effect on economic growth in both the short and long run. In the long run, a positive shock in external debts of 1% triggers an upturn in economic growth by 0.216% while a negative shock triggers 0.354% decline in economic growth. This implies that the negative shock of external debts has a much stronger impact on economic growth than the positive shock. In the short run, a positive shock in external debts by 1% triggers a decline in economic growth by 0.641%, while a negative shock of 1% triggers a fall in economic growth of 0.170%.

Originality/value

The paper used the NARDL model to examine the asymmetric impact of external debt on the economic growth of SSA countries, which has not been extensively studied. It is recommended that governments in the selected countries in sub-Saharan Africa should drive economic growth by promoting domestic revenue mobilization since external debts impede economic growth.

Purpose

The purpose of this research is to evaluate corruption in the context of India, spanning the period between 1988 and 2021. Additionally, it aims to provide an in-depth comprehension of the factors that drive its prevalence and to propose policy directives for addressing these underlying issues.

Design/methodology/approach

The study instead of relying on perception-based measures, takes a distinct approach by formulating a corruption index derived from reported instances, thus ensuring a more objective assessment. Furthermore, we employ stochastic frontier analysis to tackle the issue of under-reporting within the corruption index based on reported cases. Subsequently, an auto regressive distributed lag (ARDL) methodology is applied to ascertain the principal drivers of corruption, encompassing both long and short factors.

Findings

This study reveals that corruption in India is notably influenced by economic growth and income inequality. Conversely, government effectiveness and globalization display a tendency to mitigate corruption. However, our rigorous analysis demonstrates that financial development does not wield a substantial influence in our study. Moreover, our inquiry uncovers a nonlinear relationship between economic growth and corruption. Additionally, we ascertain that the long run and short run impacts of corruption remain relatively stable across both models utilized in our study.

Originality/value

This study differs from previous research in the subsequent manners. Primarily, we employed an objective measure to formulate the corruption index, coupled with addressing the underreporting issues via stochastic frontier analysis. Moreover, this study pioneers the identification of a non-linear relationship between corruption and economic growth within the Indian context, a facet unexplored in previous investigations.

Purpose

The study investigates the inter-linkages between geopolitical risk (GPR) and food price (FP).

Design/methodology/approach

By employing the bootstrap full- and sub-sample rolling-window Granger causality tests.

Findings

The empirical results show that there is a time-varying bidirectional causality between GPR and FP. High GPR leads to a rise in FP, suggesting that geopolitical events usually may disrupt supply and demand conditions in food markets, and even trigger global food crises. However, the negative effect of GPR on FP does not support this view in certain periods. This is mainly because GPR is also related to the global economic situation and oil price, which together have impacts on the food market. These results cannot always be supported by the inter-temporal capital asset pricing model, which states that GPR affects FP in a positive manner. Conversely, there is a positive impact of FP on GPR, indicating that the food market is an effective tool that can reflect global geopolitical environment.

Originality/value

In the context of the Russia–Ukraine conflict, these analyses can assist investors and policymakers to understand the sensitivity of FP to GPR. Also, it will provide significant revelations for governments to attach importance to the role of food price information in predicting geopolitical events, thus contributing to a more stable international environment.

Purpose

This study reviews the literature on institutional theory in international business and examines the institutional factors behind the success or failure of multinational corporations (MNCs) in emerging markets.

Design/methodology/approach

This systematic literature review analysed 116 peer-reviewed articles published in leading journals between 2005 and 2022. The R package Bibliometrix and VOSviewer visualization software were used for analysis. A hybrid methodology combining bibliometric and content analyses was utilized to obtain a descriptive evaluation of the publication impact along with a keyword co-occurrence map, context-specific institutional effects and subsidiary strategies.

Findings

The Journal of International Business Studies, along with influential authors such as Mike W. Peng, Klaus Meyer, and Mehmet Demirbag, have taken the lead in advancing institutional theories for MNC internationalization in emerging markets. The clusters from the co-word analysis revealed dominant MNC entry modes, institutional distances and MNC localization strategies. The content analysis highlights how the institutional environment is operationalized across the macro-, micro- and meso-institutional contexts and how the MNC subsidiary responds in emerging markets. Meso-level interactions emphasize the relational aspects of business strategies in emerging markets.

Practical implications

Contextualizing subsidiary strategies and institutional forms can help managers align their strategic responses to the dynamic relationship between subsidiaries and the institutional environment. The review findings will enable policymakers to simplify regulatory policies and encourage MNC subsidiary networks with local stakeholders in emerging markets.

Social implications

Legitimacy strategies such as corporate community involvement in emerging markets are crucial for enhancing societal support and removing stakeholders' scepticism for MNC business operations in emerging markets. Moral legitimacy should be implemented by managers, such as lending support to disaster management efforts and humanitarian crises, as they expand to new business environments of emerging markets.

Originality/value

This study is the first to explore institutional diversity and subsidiary strategic responses in a three-layered institutional context. The findings highlight the relevance of contextualizing institutional perspectives for international business scholars and practitioners as they help build context-specific theoretical frameworks and business strategies. Future research recommendations are suggested in the macro-, micro- and meso-institutional contexts.