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Introduction: According to the existing research, one of the key determinants of a company’s survival and market development is its ability to get bank loans or other external sources of finance for business expansion.

Purpose: The study aims to explore the factors affecting access to finance and their effects on the development of medium- and small-sized businesses. These factors include business size and age, profitability, the length of a company’s association with a commercial bank, and banking sector characteristics.

Need for the study: It is particularly crucial for small- and medium-sized businesses since they often have trouble getting funding from banks because they don’t supply the banks with the information they need to assess their loan application prospects, however, when a company’s economic and financial situation improves, banks get access to more information about the firms, and financing is thus more readily available.

Methodology: This research is based on qualitative methods, focus on an elaborative study of the existing literature, and provide suggestions based on the same.

Findings: The findings show that small- and medium-sized businesses, like those in other European nations, have less access to finance than large businesses. It revealed that the company’s size, liquidity, profitability, and banking industry state significantly influence the availability of bank loans.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

This paper makes a novel attempt to estimate the potential impact of credit risk on foreign direct investment (FDI hereafter), thereby focusing on a completely unexplored area in the existing empirical literature.

To provide a comprehensive understanding of the relationship between credit risk and FDI inflows, the study incorporates all the eight-member economies of the South Asian Association of Regional Cooperation (SAARC hereafter) and analyzes a panel data set, over the period 2011 to 2019, extracted from the World Development Indicators, using the suitable econometric techniques for the efficient estimations of the specified models.

The results indicate a negative and statistically significant relationship between the credit risk of the banking sectors and FDI inflows. Similarly, market size and inflation rate appear to be the two other main factors behind the increasing FDI inflows in the SAARC member economies. Interestingly, the size of the market became irrelevant in attracting FDI inflows when the Indian economy is excluded from the sample due to its higher economic weight. On the other hand, FDI inflows are not dependent on the level of trade openness, with most of the specifications showing either an insignificant or negative coefficient of the variable.

The obtained results are unique and robust to alternative methodologies, and hence, the SAARC economies could consider them as the critical inputs in formulating the appropriate policies on FDI inflows.

The findings are unique and original. The authors have established a relationship between credit risk and FDI for the first time in the SAARC context.

This paper aims to review the literature extensively by analysing recent work and providing a guide for models, data sets and research findings.

This paper reviews the literature extensively by analysing recent work and providing a guide for models, data sets and research findings within the context of capital market imperfections. The authors further break down the literature into closer-in-nature categories for reader’s convenience and comprehension. Finally, the authors address gaps in the existing literature and propose government policies that can tone down the potential effect of credit rationing on employment.

This paper provides a map of the literature so as to help future researchers in the relevant literature and give a short insight of what has been explored so far.

This paper is original and is the result of a thorough review of an extensive literature.

This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.

The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.

The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.

Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

This paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.

The author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.

Long-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.

This research applies to markets that require some home equity contributions from buyers of housing services.

Stakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.

Existing literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

Introduction: Small- and medium-sized enterprises (SMEs) play a vital role in the economic development of economies by generating job opportunities. Considering their significance, understanding the challenges and skills required in these enterprises becomes essential and timely.

Purpose: This study aims to discuss the limitations and skill gaps faced by SMEs in emerging economies, such as India, Indonesia, Brazil, China, Malaysia, Ghana, Hungary, Saudi Arabia, South Africa, Türkiye, UAE, Iran, Kazakhstan, Türkiye, Zambia, Romania, and Vietnam.

Methodology: The study adopts a systematic review and meta-synthesis approach, utilising a literature review to comprehensively analyse, synthesise, and map the existing literature by identifying overarching themes.

Findings: The study examines the challenges SMEs encounter in emerging economies, including resource scarcity, limited access to credit, inadequate infrastructure, low technology adoption, restricted global market access, and ineffective marketing strategies. There is a notable shortage of skilled labour and development initiatives within SMEs in India even though the country has a sizeable pool of qualified workers. There is a pressing need for additional technical and managerial skills to remain competitive in the market. The findings of this study will assist HR managers in addressing skill shortages among employees in SMEs operating within emerging economies