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The financial system plays an essential role in facilitating the intermediation process for economic growth. Policymakers stress on achieving a well-developed and regulated financial system to achieve economic development and resiliency. Using data from the State of Qatar, this paper aims to examine the impact of financial development indicator on economic growth; the impact of financial development indicator on hydrocarbon and nonhydrocarbon sector; the impact of Islamic banking on hydrocarbon and nonhydrocarbon economic growth.

The research uses quarterly data from 2007 to 2019 and adopts autoregressive distributed lag cointegration techniques to test the long- and short-run dynamic relationship between various measures of financial development and economic growth.

The results present evidence of long-term cointegration between overall financial development indicator and economic growth. Furthermore, the authors document the existence of long-term relationship between financial development and nonhydrocarbon sector. However, there is a lack of evidence on the long-run relationship between financial development and the hydrocarbon sector. Notwithstanding, Islamic banking contributes to overall economic development, as well as to the nonhydrocarbon sector.

This paper offers policymakers with insights to evaluate measures to diversify the economy. It also assists decision-makers in promoting Islamic finance, particularly to the banking sector as a vital contributor to economic growth.

To the best of the author’s knowledge, this paper is the first to evaluate financial development and economic growth for the case of Qatar in light of recent developments in Islamic finance.

This paper aims to analyze relative contribution of intensive margin (IM) and extensive margin (EM) to growth in India's agricultural exports for the period 2001 to 2020. It also analyses the determinants of IM and EMs through a standard gravity model.

The study uses export data from United Nations Comtrade, which is accessed through World Integrated Trade Solution (WITS) software. Data for the period 2001 to 2020 were compiled for analysis using the Harmonized System (HS) of commodity classification system at the six-digit level. This study decomposed the contribution of IM and EM in the growth of Indian agricultural trade by using Hummels and Klenow's approach. After performing the export decomposition analysis, the authors analyze the factors influencing IM and EM by using the Tobit regression model and Poisson pseudo-maximum-likelihood (PPML) method of estimation.

The EM grew at 1.24% per annum, while the intensive margin (IM) increased by 0.23%. The contribution of growth at the EM increased from 58.8% in 2001 to 70.2% in 2020. Export growth along the IM was relatively high for animal products and agricultural raw materials, while growth at the EM was an important contributor to the export growth of horticultural and processed agricultural products. There was a positive and significant effect of the free trade agreement (FTA) on export margins.

More disaggregated commodity-specific studies on value chain analysis would provide valuable insights into the issues hindering exports and realizing the untapped export potential.

There is a scarcity of holistic and recent studies illustrating the role of IM and EMs in agricultural trade growth, covering a large number of commodities and geographies associated with Indian agricultural trade. The study would be helpful to the stakeholders in facilitating informed policy decisions.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

The purpose of this study is to explore the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports.

Based on the theoretical analysis of the mechanism of the digital economy’s influence on the binary margin of agricultural exports, this study empirically examines the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports based on China’s customs export data from 2011 to 2016.

The relevant findings are threefold. (1) The digital economy significantly improves the binary margin of agricultural exports, and its effect on the intensive margin is stronger than that on the expansive margin. After the expansive margin is subdivided, the effects on the three sub-variables of the expansive margin are in the following order: old products exported to new markets > new products exported to old markets > new products exported to new markets. (2) The heterogeneity analysis reveals that the digital economy has a stronger role in promoting the binary margin of exports for enterprises in the eastern region, high-income countries as the destination of exports and state-owned enterprises. (3) Mechanism analysis shows that the digital economy promotes the binary margin of agricultural exports by reducing trade costs and intensifying market competition.

First, in terms of research perspective, although there are some studies on the impact of the digital economy on export trade in existing literature, the research objects mainly focus on manufacturing enterprises. In fact, agricultural trade is susceptible to natural conditions and seasonal factors, and countries may impose more SPS measures and TBT measures on agricultural trade due to risk considerations. The relationship between the digital economy and agricultural trade also has its own characteristics, but there are few research studies in this area. At present, only Liu and Gao (2022), based on the data of total imports and exports of different agricultural products from 2004 to 2018, have established a vector auto-regressive model to empirically analyse the heterogeneous dynamic impact of the digital economy on the trade volume of agricultural products. In addition, Ma and Guo (2023) conducted an empirical test on the total effect, regional heterogeneity and threshold effect of the digital economy on agricultural export trade based on China’s provincial panel data from 2011 to 2020. Therefore, under the new circumstances of continuous integration of digital technology and agriculture, this study interprets the impact effect and mechanism of the digital economy on the binary margin of agricultural exports from the perspective of the digital economy, providing new research perspectives and approaches for promoting the growth of agricultural exports. Second, in terms of theoretical analysis, the above studies have not been fully analysed in terms of the specific mechanism of the impact of the digital economy on agricultural exports. Based on the positive and negative characteristics of agricultural trade, this study introduces two kinds of roles into the theoretical analysis framework to comprehensively determine the trade impact effect of the digital economy. Third, in terms of research design, this study empirically examines the impact of the digital economy on the binary margin of agricultural products, passing a series of robustness tests and investigating the mediating roles of trade cost and market competition effects, producing an empirical basis for China to leverage the digital economy to promote the binary margin of agricultural exports.

The 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.

This work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.

The research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.

The finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

This paper aims to analyze the impact of the adoption of ISO 14001 and ISO 9001 on the performance of Portuguese companies. The sample includes the companies listed on Euronext Lisbon, with economic, financial and specific information – the specific being environmental information and quality information – for the period between 2015 and 2019, which corresponds to the post-Troika period when some economic growth started to be witnessed. The specific information of each area is translated into the environmental certification by the ISO 14001 standard, the quality certification by the ISO 9001 standard, and sustainability reports.

To achieve this aim, four variables were used as a measure of the companies' performance, Return on Assets (ROA), Return on Equity (ROE); Tobin's Q and EBITDA Margin. With this data, different panel models were tested to validate if ISO 9001 and ISO 14001 certifications impact Portuguese listed companies performance. Specifically, the authors have used the Generalized Method of Moments, GMM-System, an estimation method proposed by Arellano and Bover (1995) and Blundell and Bond (1998).

The results show that, in general, the environment and quality variables fail to explain the dependent variables, that is, ISO certifications do not provide positive or negative variations in the performance of companies, suggesting that they are not yet as much for civil society, as well as for current or potential shareholders. When used as an independent variable, certification according to the ISO 14001 or 9001 standards, negative and significant oscillations were verified in the dependent variable, MgEBITDA, suggesting that only for managers this variable is determinant, but with a negative impact, given the high costs, it entails without pressure from other stakeholders.

This study is the first to analyze the impact of the adoption of ISO 14001 and ISO 9001 on Portuguese companies' performance. This empirical study aims to show all investors, managers, regulators and civil society itself the long path that still needs to be taken toward sustainability.

The aim of this paper is to evaluate empirically the impact of oil price fluctuations on the relationship between banking sector development and economic growth in oil-importing MENA countries.

The study used the newly developed panel autoregressive distributed lagged (ARDL) approach in order to address any potential endogeneity between research variables.

The empirical results show a unidirectional causality in the long run from oil price to both economic growth and banking sector development for oil-importing countries. Also, banking sector development not only leads directly to economic growth but also can play a moderator role in the oil price—economic growth nexus.

The study has two principal limitations. On the one hand, this study was conducted in a relatively limited sample of countries. On the other hand, the study did not consider others indicators for banking sector development and others macroeconomic variables.

The results found have imperative implications for banks' managers, regulators and researchers. Bank managers should be more concerned with the negative repercussions of oil price fluctuations on the development of their banks. The regulatory authorities must emphasize policies and strategies to further strengthen their banking sector in order to alleviate the negative influence of oil price shocks on economic growth. Researchers focused on finance-growth nexus must take into account the potential influence of oil price shocks.

The developed conceptual model allows examining to what extent the oil price fluctuations might affect the relationship between economic growth and banking sector development. This effect is neither evaluated nor clarified in the relevant literature.

This paper aims to (1) identify the different performance drivers (lead indicators) and outcome measures (lag indicators) investigated in the literature concerning the four balanced scorecard (BSC) perspectives in operations management (OM) contexts and (2) understand how performance drivers and outcome measures (and substantiated perspectives) are related.

We undertake a systematic literature review of the BSC literature in OM journals. From the final sample of 40 articles, performance drivers and outcome measures have been identified, and the relationships amongst them have been synthesised according to the system dynamics approach.

Findings show (1) the most relevant performance drivers and outcome measures within each BSC perspective, (2) their relationships, (3) how the perspectives are linked through the performance drivers and outcome measures and (4) how the different measures relate systemically. Accordingly, four causal loops amongst identified measures have been built, which – jointly considered – allowed for the creation of a dynamic strategy map for OM.

This study is the first one that provides a comprehensive and holistic view of how the different performance drivers and outcome measures within and between the four BSC perspectives in OM relate systemically, increasing the knowledge and understanding of scholars and practitioners.

Research on financing for entrepreneurship has consolidated over the last decade. However, one question remains unanswered: how does the combination of external finance, such as equity and debt capital, and internal finance, such as working capital, affect the likelihood of grant funding over time? The purpose of this study is to analyse the relationship between different sources of financing and firms' ability to fundraise via innovation grants and to examine the role of female chief executive officer (CEO) in this relationship. Unlike equity and debt funding, innovation grants manifest a form of innovation acknowledgement and visibility, recognition of potential commercialization of inovation.

The authors use firm-level financial data for 3,034 high-growth firms observed in 2015, 2017 and 2019 across 35 emerging sectors in the United Kingdom (UK) to test the factors affecting the propensity of high-growth firms to secure an innovation grant as a main source of fundraising for innovation during the early stages of product commercialization.

The results do not confirm gender bias for innovation fundraising in new industries. This contrasts with prior research in the field which has demonstrated that access to finance is gender-biased. However, the role of CEO gender is important as it moderates the relationship between the sources of funding and the likelihood of accessing the grant funding.

This study does not analyse psychological or neurological factors that could determine the intrinsic qualities of male and female CEOs when making high-risk decisions under conditions of uncertainty related to innovation. Direct gender bias with regards to access to innovation grants could not be assumed. This study offers important policy implications and explains how firms in new industries can increase their likelihood of accessing a grant and how CEO gender can moderate the relationship between availability of internal and external funding and securing a new grant.

This study implicates and empirically demonstrates that gender bias does not apply in fundraising for innovation in new industries. As female CEOs represent various firms in different sectors, this may be an important signal for investors in new product development and innovation policies targeting gender bias and inclusion.

The authors draw on female entrepreneurship and feminist literature to demonstrate how various sources of financing and gender change the likelihood of grant funding in both the short and long run. This is the first empirical study which aims to explain how various internal and external sources of finance change the propensity of securing an innovation grant in new industries.

This research aims to examine the macro determinants that significantly affect financial development in the Middle East and North Africa (MENA) region, which could be used furtherly to play a major role in economic sustainability since one of the major driving forces for economic development is the financial development.

The significant determinants of financial development should be efficiently used by the MENA region countries for creating huge financial sector development and innovation, stimulating economic development in turn and leading to the completion of the cycle of development and sustainability. To achieve this study's objective, the researcher employed a quantitative method to develop an econometric model.

This model consisted of two Panel EGLS Cross-Section Random Effects Models (REMs) in which Domestic credit to the private sector as a percentage of GDP (?PCGDP?_it) and stock market capitalization ratio (?SMC?_it) were taken as the dependent variables. In addition, the independent variables included the corruption perception index, financial freedom (FF), political stability (PS) and trade openness (TO). The researcher extracted the data for the analysis from different databases including the World Bank, the Organization for Economic Cooperation and Development and the International Monetary Fund. Throughout the first – Panel EGLS Cross-Section Random Effects Model, it turned out that, while FF, TO and corruption index had a positive relationship with ?PCGDP?_it, PS had an adverse effect on ?PCGDP?_it. The second – Panel EGLS Cross-Section Random Effects Model showed that, while PS and TO had a positive effect on stock market performance, the corruption index and FF had an adverse effect on stock market performance.

Throughout the first – Panel EGLS Cross-Section Random Effects Model, it turned out that, while FF, TO and corruption index had a positive relationship with ?PCGDP?_it, PS had an adverse effect on ?PCGDP?_it. The second – Panel EGLS Cross-Section Random Effects Model showed that, while PS and TO had a positive effect on stock market performance, the corruption index and FF had an adverse effect on stock market performance.