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Fish farmers in Africa often operate on small-scale culture units, primarily due to poor access to funding and low technology adoption. Digital innovation platforms seek to enhance farmers’ access to finance, production and farmers’ income. However, there is a lack of empirical evidence to support these claims. Therefore, this study investigated the factors influencing fish farmers’ access to microcredit from digital innovation platforms and the impact of this microcredit on fish farms’ yield and income in Nigeria.

A mixed-methods approach was adopted, and data were gathered from 387 fish farmers through a well-structured questionnaire and focus group discussion. The data were analyzed using probit regression and instrumental variable two-stage least squares regression.

The results revealed that ownership of smartphones, awareness of digital agricultural innovation platforms, farmers’ education, income, fish farming as a primary occupation, cooperative society and extension contacts positively influenced farmers’ access to microcredit from digital innovation platforms. The age of farmers and household size negatively influenced their access to digital microcredit. Digital microcredit positively and significantly impacted fish farms’ yield and farmers’ income.

Digital microcredit significantly increased fish farm yield and income. Therefore, digital innovation platforms should be encouraged and promoted through the creation of awareness about their ability to solve inadequate financing in agriculture by agricultural extension agents.

This study contributes to our understanding of the influencing factors for farmers accessing digital microcredit and how digital microcredit enhances farm yield and income.

In this paper, the heterogeneity of the linkages among financial development, productivity and growth across income groups is emphasized.

An empirical analysis is conducted with an illustrative sample of 130 economies over the period 1991–2019 and classified into four subsamples: Organisation for Economic Co-operation and Development (OECD), developing, least developed and net food importing developing countries. Forecast error variance decompositions and panel vector auto-regressive estimations are computed, with insightful findings.

Higher levels of output stimulate the economic development in the agricultural sector, mainly via the productivity channel and, in the most developed economies, also through access to credit. Differently, in developing and least developed economies, the role of access to credit is marginal. The findings have practical implications for stakeholders involved in the planning of long-run investments. In less developed economies, priorities should be given to investments in technology and innovation, whereas financial markets are more suited to boost the development of the agricultural sector of developed economies.

The authors conclude on the credit–output–productivity nexus and contribute to the literature in (at least) three ways. First, they assess how credit access, agricultural output and agricultural productivity are jointly determined. Second, they use a novel approach, which departs from most of the case studies based on single-country data. Third, they conclude on potential causality links to conclude on policy implications.

Financial technologies form the heart of considerable disruptive innovation. Fintech is the emerging financial infrastructure for modern business. Big data are the feedstock for artificial intelligence (AI) that drives many fintech sectors – start-up finance, commodities and investment instrumentation, payment systems, currencies, exchange markets/trading platforms, market-failure response forensics, underwriting, syndication, risk assessment, advisory services, banking, financial intermediaries, transaction settlement, corporate disclosure, and decentralized finance. This chapter demonstrates how analyzing big data, largely processed through cloud computing, drives fintech innovations, scholarship, forensics, and public policy. Despite their apparent virtues, some fintech mechanisms can externalize various social costs: flawed designs, opacity/obscurity, social media (SM) influences, cyber(in)security, and other malfunctions. Fintech suffers regulatory lag, the delay following the introduction of novel fintechs and later assessment, development, and deployment of reliable regulatory mechanisms. Big data can improve fintech practices by balancing three key influences: (1) fintech incentives, (2) market failure forensics, and (3) developing balanced public policy resolutions to fintech challenges.

For over 25 years, the United States Green Building Council (USGBC) has significantly influenced the US sustainable construction through its leadership in energy and environmental design (LEED) certification program. This study aims to delve into how Baton Rouge, Louisiana, fares in green building adoption relative to other US capital cities and regions.

The study leverages statistical and geospatial analyses of data sourced from the USGBC, among other databases. It scrutinizes Baton Rouge’s LEED criteria performance using the mean percent weighted criteria to pinpoint the LEED criteria most readily achieved. Moreover, unique metrics, such as the certified green building per capita (CGBC), were formulated to facilitate a comparative analysis of green building adoption across various regions.

Baton Rouge’s CGBC stands at 0.31% (C+), markedly trailing behind the frontrunner, Santa Fe, New Mexico, leading at 3.89% (A+) and in LEED building per capita too. Despite the notable concentration of certified green buildings (CGBs) within Baton Rouge, the city’s green building development appears to be in its infancy. Innovation and design was identified as the most attainable LEED benchmark in Baton Rouge. Additionally, socioeconomic factors, including education and income per capita, were associated with a mild to moderate positive correlation (0.25 = r = 0.36) with the adoption of green building practices across the capitals, while sociocultural infrastructure exhibited a strong positive correlation (r = 0.99).

This study is beneficial to policymakers, urban planners and developers for sustainable urban development and a reference point for subsequent postoccupancy evaluations of CGBs in Baton Rouge and beyond.

This study pioneers the comprehensive analysis of green building adoption rates and probable influencing factors in capital cities in the contiguous US using distinct metrics.

This chapter examines the patterns influencing the trajectory of fintech enterprises. With the looming challenge of climate change, the financial realm's responsibility in mitigating climate risks has surged into focus. This chapter investigates fintech enterprises' response to climate-related corporate social responsibility in six main domains: (1) climate risk assessment tools, (2) green bonds and sustainable investment tools, (3) ESG integration, (4) carbon trading and carbon credits, (5) sustainable banking, and (6) DeFi and climate initiatives. It also investigates how fintech firms recognize the impact of climate change within their official declarations and efforts to amplify consciousness about climate-related concerns. This chapter assesses climate-linked terminology and expressions using quantitative and qualitative approaches, illuminating these firms' dedication to assimilating climate risk within their operational blueprints.

This chapter examines why the central banks might need to engage in innovation work. Externalities and public good rationales for innovation at central banks are examined. This chapter then looks at different tools such as sandboxes, innovation hubs and TechSprints that the central banks might use to promote innovation with external stakeholders, and how the central banks can promote internal innovation within the central banks. Governance issues related to innovation promotion are also examined.

This study aims to respond to the latest research calls to precisely revisit the nexus between corporate green innovation (CGI) and financial decisions through deeply investigating the mediating effect of corporate environmental performance measured by the effectiveness of emission reduction.

This study analyzes nonfinancial-listed firms on the Australian Securities Exchange from 2002 to 2019 using multiple regression analysis on a panel data set. Initially, different static panel data approaches were used. To account for the potential endogeneity issue and generate robust outcomes, the authors apply the one-step system generalized method of moment, two-stage least squares and lagged model approaches.

The results provide a clear indication that the practices of green innovation can favorably contribute to the level of environmental performance, which in turn affect the firm’s ability in opening the new financial doors and shape solid capital structure. In this context, the effective environmental performance fully mediates the nexus between CGI and capital structure of a firm. More importantly, the outcomes are robust and coherent across different estimation techniques.

The originality of this study lies in its utilization of mediation analysis to explore the relationship between CGI and a firm's financial structure. This approach distinguishes it from previous research by offering a thorough and nuanced understanding of how green innovation practices influence the financing decisions of a firm.