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This study examines the impact of urbanization on growth and the role of international financial flows in the urbanization-growth nexus.

The study applies the panel least square estimation to examine the impact of urbanization on growth using panel data from 50 developing countries from 1980 to 2016. Further, addressing the endogeneity issues in panel estimations, the study applies the dynamic System-GMM approach to investigate the role of financial flows in urbanization and their impact on economic growth in developing countries.

Contrary to the conventional literature, we found a non-linear (U-shaped) relationship between urbanization and growth. Our findings demonstrate that growth is reduced at a lower level of urbanization due to less availability, concentration, and synchronization of production factors. The concentration of physical and human capital and technological advancement in urban areas help developing countries achieve economic growth at a higher level of urbanization. Robust estimations divulged that foreign aid spent on infrastructure development and expanding urban regions helps promote economic growth. Nevertheless, as a resilient factor, remittances buffer the rapid pace of urbanization and reduce growth by resisting the migration of labor and capital from rural to urban areas.

The paper's findings suggest policymakers promote urban infrastructure and development using local and international funds since its increased level spurs economic growth. Further, the results advise policymakers to reduce aid dependency, attract FDI, and facilitate the easy and low-cost transfer of money to promote remittance inflows since both FDI and remittances positively contribute to economic growth.

The paper contributes significantly to the literature by determining the U-shaped relationship between urbanization and growth and highlighting the role of international flows in the urbanization-growth nexus.

This study empirically examines the moderating role of geopolitical risk on the tourism–economic growth nexus by applying a recent geopolitical risk indicator developed by Caldara and Iacoviello (2022) in a cross-country panel data growth model context for a sample of 24 countries.

A Dummy Variable Least Squares panel data model, nonparametric covariance matrix estimator and SYS-GMM estimation techniques are employed for the analysis. The authors capture the GPR moderating effect by disaggregating the cross-country sample according to low versus high country GPR score and through a GPR interaction coefficient. Several controls are included in the models such as gross fixed capital formation and—consistent with Barro (1990)—government consumption. Trade openness is used to account for the export-led growth effect. In line with neoclassical growth theory (e.g. Barro, 1991), the authors also include the real interest rate, to account for policy makers' commitment to macroeconomic stability, financial depth, as a proxy for financial development, population growth and the level of secondary school education. The authors also control for unobserved country-specific and time-invariant effects.

The research finds that the interaction term of geopolitical risk significantly contributes to the predictive ability of the regression and provides empirical evidence that confirms that only in low geopolitical risk countries international tourism positively and significantly contributes to economic growth. Important theoretical and policy implications flow from these findings.

The study not only contributes to advancing academic knowledge on the tourism–growth nexus, it also has impact beyond academia. Many countries have in the past pursued and many continue to pursue, tourism specialization and/or tourism-led growth strategies based on the theoretically well-established and empirically validated positive link between inbound tourism and economic growth. The findings alert policy makers in such countries to the significant moderating role that geopolitical risk plays in affecting the above-mentioned relationship and to the importance of prioritizing geopolitical stability as a policy precursor for the successful implementation of such strategies.

The aim of this article is to assess the macroeconomic consequences of some specific aspects of financialization (i.e. share buy-back) using a hybrid post-Keynesian model of growth and distribution based on Kaldorian and Kaleckian characteristics.

The study follows a post-Keynesian approach and deals with financialization issues by implementing several numerical simulations.

The numerical simulations reveal the negative real impacts of massive share repurchases on the rate of accumulation because they immediately siphon off revenues directly intended for investment projects. Moreover, the negative effect of share buy-backs is reinforced especially when firms' investment decisions are more sensitive to a variation in retained earnings. Next, this macro-model also reproduces several well-known figures of the Kaleckian tradition and the paradox of costs.

The present article can be considered as a starting point for further theoretical extensions and requires empirical validation.

The Kaldor-Kalecki macro-model could be useful for policymakers who are interested in containing some of the negative excesses of financialization.

Although marketing is essential for a firm’s survival and growth, a set of entrepreneurial strategic orientations may help it gain a competitive advantage. Entrepreneurial marketing (EM) is critical for growing businesses to succeed in today's fast-paced industry. The present study aims to measure the role of EM on the business performance (BP) of Indian startups.

For this purpose, a thorough literature review was conducted to develop a scale from the proposed conceptual framework – EMICO by Jones and Rowley (2009b). To assess the reliability and validity of the scale (62 items), the data are analyzed by employing partial least square-structural equation modeling (PLS-SEM).

The scale is empirically tested, and the results lead to discussions. The results show the positive impact of entrepreneurial orientation (EO), marketing orientation (MO), innovation orientation (IO) and customer orientation (CO) on the BP of the startups. The paper concludes by suggesting managerial and practical implications, also providing future research agenda.

Our objective is to address the existing dearth of comprehensive scales for evaluating EM by undertaking a rigorous statistical approach. Notably, our research represents the pioneering effort in adopting the EMICO framework and subsequently formulating and empirically validating a robust scale specifically tailored for nascent or small-scale startups within the Indian context.

This study examines the contribution of urban development to Vietnam's economic progress over the period 1986–2020. The study uses an augmented Solow framework, where urbanization is included as a shift variable in addition to capital per worker and accounts for structural breaks. It examines the cointegration and the long-run and short-run effects of urban development from four different cases of cointegration (constant, restricted constant, restricted trend and trend options), with each case accounting for the effect of a significant structural break. Also, the study provides causality nexus to check the presence of urbanization-led growth hypothesis. From the results, we note a long-run positive effect of urbanization on economic growth, but no short-run effects. In all cases, a 1% increase in population results in 0.8–0.9 increase of output, hence supporting a positive and momentous effect of urbanization over the long-term. We note a significant positive effect of a single structural break period (1991), which is a period of major shift towards economic progress. We note bidirectional causality between capital and output and a unidirectional causality from output and capital to urbanization. The former suggests a mutually reinforcing effect of capital accumulation and economic growth, and the latter indicates that urban development necessitates economic growth and capital accumulation. The findings derived from this study provide further impetus for urban development and urban policies and consider urbanization as a critical source of economic growth for Vietnam.

Green, lean and six sigma (GLSS) practices are widely used and well accepted techniques that have the capability to improve the economic, social and environmental performance of Pakistani small and medium enterprises (SMEs). However, implementation of these practices in an integrated approach has not yet been witnessed in Pakistani SMEs due to a variety of challenges. To overcome the implementation challenges, this study has analyzed the impact of GLSS implementation over the sustainability in Pakistani SMEs.

This study consists of two phases. In phase 1, interviews were conducted to scrutinize the elements of GLSS implementation to simplify the model and in phase 2, a questionnaire survey was conducted to collect the data from the SMEs. The partial least squares structural equation modeling (PLS-SEM) approach is used to analyze the relationships among the latent variables and constructs.

Results showed that, leadership for GLSS, understanding GLSS techniques and technology upgradation are considered the most important elements for GLSS implementation in Pakistani SMEs. The environmental and social perspectives have been given more weightage compared to economical perspective. This inferred that there is a need to focus more on environmental and social perspectives in SMEs as compared to economic perspectives to achieve sustainable growth. Moreover, the results of the hypothesis testing revealed that GLSS implementation has a significant positive impact over the sustainability in SMEs considering the Pakistani scenario (β = 0.529, STDEV = 0.078, t = 6.81, p = < 0.001).

This study is the first of its kind for Pakistani SMEs. The structural model developed in this study for Pakistani SMEs will help practitioners to understand the important elements of GLSS implementation and sustainability dimensions.

This article employs a panel vector autoregression (PVAR) model to examine the relationship between digital financial inclusion (DFI), economic growth (EG), and gender equality (GE) across different levels of financial development.

Based on the current financial development dynamics, this study applies the PVAR method to two groups of countries: the first group represents the high financial development group, and the second group represents the low financial development group, during the period from 2015 to 2021.

The findings from impulse response functions reveal that digital financial inclusion fosters economic growth in nations with advanced financial systems, while simultaneously mitigating gender inequality. Conversely, in countries with less developed financial infrastructures, digital financial inclusion stimulates economic growth but exacerbates gender disparities. Moreover, the variance decomposition analysis indicates that the linkage between economic growth, digital financial inclusion, and gender inequality is more intertwined in countries with limited financial development than in those with well-established financial systems.

Effective deployment of new technologies relies heavily on technological infrastructure. This policy focuses on constructing and developing information technology infrastructure to create favorable conditions for the implementation of new DFI technologies. This study also emphasizes promoting equitable education and training by ensuring that both women and men have equal opportunities to access quality education and training. This may involve investing in early childhood education, providing access to primary education, and offering scholarships to women in technology, science, and engineering fields.

The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and congruence theory, this research investigates the complex impact of supply chain concentration on financial growth in agri-food supply chains.

The cluster analysis and response surface methodology are employed to analyse the data collected from 207 Chinese agri-food companies from 2010 to 2022.

The results indicate that different combination patterns of supply chain concentration can lead to different levels of financial growth. We discover that congruent supplier and customer concentration is beneficial for companies’ financial growth. This impact is more pronounced when the company is in the agricultural production stage of agri-food supply chains. Post-hoc analysis indicates that there exists an inverted U-shaped relationship between the overall levels of supply chain concentration and financial growth.

Our research uncovers the complex interplay between supply chain base and financial outcomes, thereby revealing significant ramifications for agri-food supply chain managers to optimise their strategies for exceptional financial growth.

This study proposes a combined approach of cluster analysis and response surface analysis for analysing configuration issues in supply chain management.

The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.

We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.

Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.

These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.

Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.

Social value creation (SVC) is the primary emphasis for unifying the various issues in contemporary social entrepreneurship (SE) literature and practice since it highlights the fundamental problem of sustainability in SE business. Accordingly, SVC as an outcome of SE represents the primary drive of social entrepreneurs (SEs). However, SEs encounter multi-dimensional challenges as they work to build their SE businesses and create social value. In the current context of digitally transforming entrepreneurship scenario, this study investigates the role of SE compassion and digital learning orientation (DLO) for SVC ability of SEs.

The study utilized a quantitative survey approach for primary data collection from social entrepreneurs in Saudi Arabia. A total of 158 valid replies from social entrepreneurs were obtained for the study. Using SmartPLS (3.0), partial least square structural equation modeling was used to analyze the data.

The results validated a model of SVC in which the SE compassion and DLO positively impact the SVC ability in SEs. However, the impact of DLO in moderating the SE compassion - SVC relationship in SEs was not proven.

The study established the role of SE compassion in explaining the distinctive SVC ability in SEs. Meanwhile, given the expanding necessity for SEs to leverage digital technologies for SE missions, the study provides implications for nurturing positive outcomes in terms of SE compassion and DLO outcomes among SEs. This organized knowledge can help entrepreneurs, educators and policymakers better incorporate these concerns in SE education, and social enterprises and entrepreneurs’ developmental initiatives.

This work is pioneering in that it conceptualizes and tests a theoretical framework that links SE compassion, DLO, and SVC in SEs. Meanwhile, the study is the first to operationalize the DLO in entrepreneurs. The study thus generates fresh insights about SVC in SE amid the digitally transforming entrepreneurship scenario.