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Supply chain finance is an important way of realising the transformation of the asset-heavy operation mode in car-sharing services to an asset-light operation mode, by transforming the ownership cost into a variable cost. This study considers a service supply chain with vertical shareholding comprising a vehicle manufacturer and a car-sharing operator; further, it establishes financing decision-making models under financial leasing (FL) and instalment factoring finance (IFF) and explores the impact of profitability and shareholding ratios on FL and IFF. The results how that service profitability has a fundamental influence on financing decisions. The pooling effect and service satisfaction rate affect ownership costs and rental income, respectively. In turn, these factors jointly affect the choice of financing strategy. Moreover, there is a threshold of financing strategy choice related to the shareholding ratio: a large shareholding ratio means IFF is optimal, while when the ratio is low, FL is optimal. Finally, under certain conditions, a composite contract with revenue sharing and linear transfer payment for the optimal financing strategies can be adopted to improve supply chain performance. This study thus provides effective strategies for realising asset-light operation in car sharing by transforming ownership cost into variable cost. [ABSTRACT FROM AUTHOR]

Autoencoders are dimension reduction models in the field of machine learning which can be thought of as a neural network counterpart of principal components analysis (PCA). Due to their flexibility and good performance, autoencoders have been recently used for estimating nonlinear factor models in finance. The main weakness of autoencoders is that the results are less explainable than those obtained with the PCA. In this paper, we propose the adoption of the Shapley value to improve the explainability of autoencoders in the context of nonlinear factor models. In particular, we measure the relevance of nonlinear latent factors using a forecast-based Shapley value approach that measures each latent factor's contributions in determining the out-of-sample accuracy in factor-augmented models. Considering the interesting empirical instance of the commodity market, we identify the most relevant latent factors for each commodity based on their out-of-sample forecasting ability. [ABSTRACT FROM AUTHOR]

This study aimed to replicate, revise, and validate the model of Institutional Performance in Graduation Rate developed by Fung based on Tinto and Astin theories. The sample included 706 public, 4-year, Title IV postsecondary institutions in the United States. Two CFA-SEM models were conducted with the IPEDS 2011–2017 data. The relationships among student background, finance, academic and social environment, retention rate, and graduation rate were reevaluated and remodeled. The final best fitting model reflects possible changes in the factors of student finance and academic environment in higher education since 2010. The practical application of the best fitting model was discussed, including the evaluation of an institution's graduation rate performance based on four latent factors. [ABSTRACT FROM AUTHOR]

In construction, risk is inherent in each project, and success involves meeting defined objectives beyond budget and schedule. Factors vary for infrastructure projects, and their correlation with performance must be studied. In the case of public–private partnership (PPP) transportation, the level of complexity is higher due to more involved parties. Risks and success factors in PPP projects affect each other, which may lead to project failure. Recognizing the critical risk factors (CRFs) and critical success factors (CSFs) is indispensable to ensure the success of PPP infrastructure project implementation. However, the existing research on the PPP risk and success relationship has not gone into sufficient detail, and more support to address the existing gaps in the body of knowledge and literature is necessary. Therefore, in response to the missing area in the public–private partnership transportation industry, this paper analyzed the correlation between PPP risks and success factors. It identified, explored, and categorized various risk and success factors by combining a literature review, expert panel interviews, and a questionnaire survey among both the public and private sectors, a win–win principle. The data collected were analyzed using the structural equation modeling (SEM) approach and relative significance. Results show the relationship between risk and success factors, their influence on PPPs, and the most important factors, known as CRFs and CSFs, with high loading factors (LF > 0.5) and high relative importance (NMS > 0.5). The top five CRFs include "Contract quality (incomplete, conflicting)", "Staff expertise and experience", "Financial market risk", "Conflicting objectives and expectations", and "Inefficient feasibility study". The top five CSFs were found as "Appropriate risk allocation and risk-sharing", "Strong financial capacity and capability of the private sector", "Government providing guarantees", "Employment of professional advisors", and "Realistic assessment of the cost and benefits". This study advances the understanding of risk and success factors in PPPs and contributes to the theoretical foundations, which will benefit not only public management, policy consultants, and investors but also academics interested in studying PPP transportation projects. [ABSTRACT FROM AUTHOR]

The present study examines the patterns of foreign direct investment (FDI) in Kazakhstan and draws comparisons with global trends. Based on statistical data spanning from 2000 to 2022, the study reveals that the growth of FDI in Kazakhstan has exhibited greater volatility and speed compared to developed nations. However, it is strongly associated with global FDI inflows and the growth of gross domestic product (GDP). This article aims to examine the patterns and determinants influencing FDI in Kazakhstan and to juxtapose these patterns with global trends. The main approach used in the study was systematic. The article's contribution lies in its provision of novel insights into the dynamics of FDI in Kazakhstan and its correlation with economic growth. Furthermore, the article elucidates the various factors that contribute to the expansion of FDI in Kazakhstan, while also offering suggestions for the development of public policy in this domain. The article provides a comprehensive examination of FDI patterns in Kazakhstan, comparing them to global trends and identifying the factors that influence the dynamics of FDI. Furthermore, the article offers suggestions for expanding the economic base of Kazakhstan beyond its reliance on the oil and gas industry, enhancing focus on high-tech and innovative sectors, and enhancing the institutional framework. [ABSTRACT FROM AUTHOR]

Information asymmetry is a prominent problem in the advancement of green finance, and because of the difficulty of capturing "information", research on the role of information factors in green finance has been limited. In this study, a quasi-natural experiment based on China's environmental information disclosure system in 2008 is conducted to investigate the effect of information factors on green finance. Using the panel datasets of China's 107 cities and 173 environmental protection firms from 2005 to 2015, this study, respectively, adopts the difference-in-difference (DID) method and triple difference (DDD) method to examine the effect of environmental information disclosure on regional green finance development and the utilization efficiency of green funds. According to the results, public disclosure of environmental information can promote both regional green finance development and the efficient utilization of green funds by energy-based environmental protection enterprises. Heterogeneity analysis at the regional level suggests that environmental information disclosure has a greater impact on green finance in regions with lower resource endowments and stronger environmental regulations. Heterogeneity analysis at enterprise level shows that compared to state-owned energy-based environmental firms, the efficiency of green capital utilization of non-state-owned energy-based environmental firms is more sensitive to the disclosure of environmental information. The findings of this paper provide a theoretical and empirical foundation for developing green finance. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chengdu University (Social Science) is the property of Journal of Chengdu University (Social Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigates the effects of cross- and stable shareholdings on the relationship between accounting quality and trade credit in Japan. Cross- and stable shareholdings are well-known features of Japanese corporate governance, as a private information-sharing system. The results indicate that the trade credit of customers without either cross- or stable shareholdings increases with accounting quality, and in most cases, such shareholdings weaken the relationship between accounting quality and trade credit. These findings suggest that close ties to cross- and stable shareholders reduce the importance of accounting information through sharing private information. The findings will enhance the understanding of ownership structure's potential impact. Overall, this study contributes to the literature by demonstrating the role of accounting quality in financing and the factors that reduce this role. In addition, this study highlights policy implications for the regulatory initiatives to unwind cross-shareholdings, which may affect private information sharing. Data Availability: Data are available from sources indicated in the text. JEL Classifications: G34; M41. [ABSTRACT FROM AUTHOR]

China's green financial pilot policies (GFPPs) are an important start to build a green financial system in China. It is also an important part of achieving the "dual-carbon" goal. This paper calculates China's total factor energy efficiency (TFEE), analyzes the impact of GFPPs on TFEE, and explores the conduction mechanism. The results show that the relationship between GFPPs and TFEE in the pilot areas is statistically significant. The GFPP mainly improves the TFEE through the green innovation effect and the optimization of the energy structure. The GFPP has a significant effect on TFEE enhancement in eastern coastal cities, non-old traditional industrial cities, and non-resource-based cities with high initial energy. China should continue to deepen the pilot work of green finance, formulate differentiated green finance policies, and ensure green technology innovation. This study provides empirical evidence for further optimization of green finance and energy efficiency. [ABSTRACT FROM AUTHOR]

Given the phenomenon of "financing is difficult and expensive" for MSEs, this paper empirically investigated the influencing mechanism of the credit demand side characteristics on the financing constraints of MSEs based on the information conveyance perspective. The conclusions show that MSEs in China are severely suffering from financing constraints and 57.17% and 50.00% of MSEs with credit demand have not applied for loans from formal and informal financing channels, respectively. In terms of enterprise characteristics, MSEs have low asset size, short establishment history, weak profitability, and lack of tools such as fixed assets, complete financial management system, professional technicians, and private brands to convey risk information to financing institutions, which are key factors resulting in their financing constraints. In terms of owner characteristics, young owners lack financing experience and convey higher risk information to financing institutions; therefore, owners' age negatively influences the financing constraints of MSEs. These findings suggest that banks can use big data credit technology as a tool to obtain risk information about MSEs, and the government should implement diversified interventions to improve the information environment in financial markets. These findings provide empirical evidence for banks and governments to address the financing constraints of MSEs. [ABSTRACT FROM AUTHOR]

Copyright of Revista Espacios is the property of Talleres de Impresos Oma and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the current era, entire global economies are transitioning to sustainable development because of global warming and climate change. Due to turbulence in environmental issues such as weather shocks, climate change and basic infrastructure and industrial planning, many countries are changing their approach and taking green steps. This paper assesses sustainable finance in India and the ways in which India can mitigate climate changing risk toward zero carbon policy and supporting SDGs 2030. It talks about the physical and transitional climate risks in India like surface temperature, heat wave concourse, etc., and provides a comprehensive analysis of how the corporate sector is imparting its role in sustainable nature through corporate social responsibility (CSR). India is an emerging economy where energy is an essential component. This study analyzes about supply of energy and how India is shifting from traditional energy sources to renewal energy sources. Thus, the objective of this study is to focus on the initiatives taken by the Indian government for sustainable finance through green bond policy at national and international platforms using the Panchamrit framework adopted by India thereby focusing on India's sustainable policy support for SDGs 2030. Also, this research proposes numerous recommendations for future sustainable finance research in the context to India, which includes developing and diffusing innovative sustainable financing instruments, magnifying, and managing the profitability and returns of sustainable financing, making sustainable finance more sustainable, and leveraging the power of new-age technologies for sustainable finance. [ABSTRACT FROM AUTHOR]

This article aims to identify and assess the impact of capital structure factors on financing strategies of mining industry enterprises in Central and E astern E uropean (CEE) countries in comparison to W estern E uropean (WE) Union countries. The research contributes to determining which of the main theories of capital structure best describes the financial strategies employed in the examined sector. The analysis encompasses mining companies from eight WE and four CEE countries, utilising panel data models with information spanning from 2000 to 2020. The study covers various firm-specific variables commonly employed in similar research, along with the effects of country and year. The main findings indicate a significant similarity in both the capital structure and the influence of the analysed factors on leverage across the two regions. This homogeneity is attributed to the industrial specificity of the mining sector, which appears to supersede country-specific or firm-size specific features. Moreover, examining the impact of variables on capital structure considering different debt maturity terms reveals that the financial strategies of the analysed companies align with the pecking order and agency theory of capital structure. This suggests that mining companies predominantly rely on internal financing, viewing debt primarily as a tool to discipline managers. Due to data limitations in the employed BACH database, the study does not encompass all E U countries, highlighting the potential for further research incorporating other regions. The identified similarities in capital structure, along with the impact of various factors, provide insights for financial decision-makers in mining firms, and investors operating in both CEE and WE E U countries. [ABSTRACT FROM AUTHOR]

This paper explores the use of nonparametric methods to estimate factor models in finance. Nonparametric methods are used to estimate alphas (pricing errors) and betas (factor loadings) in the conditional Capital Asset Pricing Model and conditional multifactor models. Nonparametric estimation of factor modeling involves choosing techniques which are different both technically and in application, but common in the nonparametric literature. Nonparametric methodology does not impose any functional form on how alphas or betas evolve over time. Local data is used in estimations, but of crucial significance is the bandwidth selection or optimal window size. Clearly, observations further away from time t are less relevant in estimating time t alphas and betas, if we are too far away from time t we potentially have a very large bias. However, if too small a bandwidth is selected, the estimate could be quite noisy, leading to a large variance. This paper discusses three topics in the realm of nonparametric multifactor modeling. I explore two contributions to the literature, a leave-one-outcross- validation technique and a plug-in technique, and compare their effectiveness. The cross-validation method is completely data driven, while the plug-in method relies on choosing an unknown parameter in estimating the optimal window size. Cross validation emerges as the more robust methodology. Using the same data, both nonparametric approaches are compared to the traditional parametric Fama-French three factor model. [ABSTRACT FROM AUTHOR]

A two‐echelon supply chain with a capital‐constrained retailer is investigated where uncertain demand and defective products are considered. As an intermediate between the retailer and the bank, the supplier provides a credit guarantee for the retailer. Two credit guarantee schemes are proposed, guarantee for quality and guarantee for both quality and sales (GQS). The partners' optimal decisions under different schemes are derived via Stackelberg game. As a critical influential factor to determine the financing cost, the loan interest rate is carefully examined with respect to its effect on the strategies of both partners. Furthermore, the influence of loss aversion on the participants' decisions is examined. Based on the theoretical analysis and numerical experiments, the following conclusions are drawn. First, the retailer's optimal order quantity is independent of the supplier's decision on the technology level, whereas the supplier's optimal decision is affected by the retailer's order size. Second, financing is not always attractive to the retailer, and is adopted only with a reasonably lower loan interest rate. Third, the GQS scheme is a win–win strategy for the supply chain if the loan interest rate is relatively high. Finally, the loss‐averse strategy is more robust for the retailer when the demand is volatile and unpredictable. [ABSTRACT FROM AUTHOR]

The objective of this study was to determine challenging factors in accessing finance by female microentrepreneurs in Anambra state, Nigeria. This study employed both qualitative and quantitative methods in data collection. Multi-stage sampling technique was adopted in selecting the sample, and the data analyzed using logit regression model based on the binary choice that describes the probability of women micro entrepreneur's choice between two mutually exclusive alternatives (accessing or not accessing microcredit). The study identifies fear of default, lack of collaterals, inability to get guarantors and information asymmetry as main factors challenging women's access to finance. The study recommends, among others, the need for financial education for female micro entrepreneurs. [ABSTRACT FROM AUTHOR]

Purpose: Referring to "behavioural finance" and "normative model" theories, this study explores the relative significance of behavioural heuristic biases in the investment decisions of real estate investment trusts (REITs) when compared with the conventional normative decision factors, with an ultimate aim to identify the significant behavioural factors that should be avoided to ensure rational asset acquisitions and market efficiency. Design/methodology/approach: A triangulation approach was adopted. Qualitative multiple case studies were conducted, with four cases selected from Australian and New Zealand REITs across the industry, to identify what normative and behavioural finance factors are involved in investment decisions. This formed the basis for the subsequent expert review survey to explore how significant the behavioural factors were manifested in the judgement when compared with the normative factors. Findings: Three out of four theoretical behavioural factors manifested themselves in the investment decisions: investor sentiment, anchoring factors and overconfidence. The overall impact of these three behavioural factors was that they were as significant as normative factors in investment decisions. The heuristic availability of information was found to have no significant effect on experienced REIT fund managers. Research limitations/implications: The findings were based on four multiple cases and an expert review survey of six frontline fund managers, which form a baseline upon which further research can be conducted to widen the scope of research to cover all REITs in Australasia so that the results can become more robust to benefit the entire market in the region. Practical implications: As behavioural factors are significant in the decision-making process, REIT fund managers should raise awareness to avoid the significant behavioural factors identified, in particular investor sentiment, which was found to be the most significant one. Originality/value: This study confirms the relative significance of behavioural factors in property investment decisions within the context of Australasian REITs and alerts fund managers to the ways they should follow to ensure rational investments and market efficiency. It also extends the scale of existing studies to cover not only Australia but also New Zealand for the benefit of the entire Australasian market. [ABSTRACT FROM AUTHOR]

Small and medium-sized enterprises (SMEs) are the driving force for the robust socioeconomic growth of a country. The study primarily aims to empirically evaluate the impact of certain firm-specific factors on the financing preferences of the listed SMEs with specific reference to India. It attempts to examine their financing practices and also investigates if they follow the order explained under various theories of finance. The sample consists of 134 listed SMEs on NSE as well as BSE SME exchange. They have been studied for the period from 2014 to 2019. The sample and the time period of the study differentiates it from the existing studies in the domain. It concludes that though majority of the variables included in the model are statistically significant, there is a possibility of influence of other micro-level variables or macro-level economic factors on the financing decisions of the listed SMEs. It is also revealed that for their financial needs, SMEs prefer short-term spontaneous sources, that is, payables and provisions, then accumulated profits followed by short-term borrowings and in last opt for the long-term debt. The study also found that there is no single theory that can completely explain the financing behavior of the listed SMEs. Moreover, it is also observed that no additional benefit is available for SMEs out of listing in India. [ABSTRACT FROM AUTHOR]

Investment decision making is something that is inevitable and a critical moment in determining the success of an investor in making their investment. This research conduct since investment decision making is very difficult to measure and seen directly. Hence, it is necessary to identify various factors that influence investment decision making including demographic factors, behavior finance, and risk tolerance. The type of research is quantitative with a population of all capital market investors who invest in shares on the Indonesia Stock Exchange (IDX), especially the LQ45 index as well as data processing uses AMOS 24. The results showed that demographic factors have an influence which causing specific behavior and tolerance thresholds related to risk, which in turn affect performance and optimization in investment decision making. Investors must also be aware of the existence of behavior finance which is found in the form of behavior or actions caused by psychological factors inherent. On the other hand, the role of risk tolerance also shapes behavior patterns and planning processes related to finance which are described in risk acceptance. Hence, the emergence of identified investor behavior will later make opportunities for momentum and investment strategies that improve the performance and success of their investments as well as the quality of excellent decision making. [ABSTRACT FROM AUTHOR]

An ever-expanding body of literature suggests the possible link between diasporas and the exacerbation of civil wars in their home countries. One of the most notable findings on the link between diaspora and armed conflict is derived from a set of arguments known as the Greed and Grievances Thesis. According to the said framework, a higher diasporic support to a homeland conflict is positively correlated with a higher incidence of civil war intractability. Applying this framework to the data on external support to the Moro Islamic Liberation Front (MILF) insurgency from 1990-2008, the study notes that there is a lack of support from the Moro diaspora which forced the MILF to secure peace with the Philippine government. On the contrary, the increase in conflict activities during the insurgency can be qualitatively attributed to the economic and political support from hostile states and international terrorist networks that support the Moro insurgents against the Philippine government. The study concludes that there is an absence of substantial evidence on the role of the Moro diaspora in funding the insurgents due to other factors such as internal financing for the rebellion and the role of international actors in prolonging the Moro conflict. [ABSTRACT FROM AUTHOR]

Changing economic situation of a country affects working capital by influencing lenders' financing abilities, firms' business activities, and managers' decisions. Hence, this paper explores the influence of macroeconomic factors in the relationship between working capital financing and firm performance over the period of 2000–2018. Applying the two‐step generalized methods of moments, we found a non‐linear and inverted U‐shaped relationship between working capital finance (WCF) and firm performance, significantly influenced by the macroeconomic indicators that is, gross domestic product (GDP) growth, Inflation rate, and interest rate. We segregated the data regarding the global financial recession period 2008–2010 and disclosed that the non‐linear and inverted U‐shaped relationship between WCF and firm performance turns to linear and negative during this recession period. We also evaluated the role of GDP growth, inflation, and interest rate in WCF and firm performance relationship during the global recession and found that these factors do not influence the nexus during this period. Firm managers, lending agencies, and researchers may use these results in choosing the best financing options in working capital under the changing situation of macroeconomic factors. The WCF and firm performance analysis during the global recession period (2008–2010) may be the best prediction model for the current financial crisis caused by COVID‐19. [ABSTRACT FROM AUTHOR]

Based on an analysis of the relationship between green finance and total factor carbon emission reduction efficiency, this article measures the levels of green finance and total factor carbon emission reduction efficiency in 30 provinces and cities in China. It also establishes a spatial Durbin model to quantitatively explore the impact of green finance on China's total factor carbon emission reduction efficiency. The results indicate that currently, green finance and total factor carbon emission reduction efficiency in China follow a distribution pattern of high in the east, medium in the central region, and low in the west. The impact of green finance on total factor carbon emission reduction efficiency demonstrates a U-shaped relationship, and the spatial spillover effect between the two displays a similar U-shaped trend. The mechanism analysis demonstrates that green finance exerts a U-shaped influence on the efficiency of reducing total factor carbon emissions through the interplay of technological progress and technical efficiency enhancements. Other variables, such as research and development investment, comprehensive energy consumption, human capital, infrastructure construction, and government regulation, also have an impact on total factor carbon emission reduction efficiency. Therefore, it is recommended that regions strengthen their green finance initiatives, support efforts to carbon emission reduction, and contribute towards achieving the "dual-carbon" goal. [ABSTRACT FROM AUTHOR]

Growing populations, expanding economies, industrialisation, and urbanisation pose a problem for waste management in developing countries. Their waste management methods, on the other hand, are not as efficient as they could be. Most developing countries' current waste management practices do not fully conform to developed countries' best practices for meeting socioeconomic goals. As a result, the importance of waste management in developing countries has grown in recent years. In order to highlight the socioeconomic perspectives of waste management practices, the present study examines the existing literature, policies, information, and records on waste management in developing nations. The findings indicate that essential socioeconomic factors such as finances, population density, per capita income, education level, policies, and technology have a significant impact on waste management, which encompasses waste generation, collection, composition, and disposal/treatment. Nonetheless, waste management has a number of economic benefits, including financial stability, job creation, and community cohesion. This study will inspire further research on the need for developing nations to consider the socioeconomic benefits of proper waste management and to develop a policy plan to achieve these benefits. [ABSTRACT FROM AUTHOR]

Project finance plays a key role in supporting UAE's infrastructure projects, driving economic growth and job creation. This financing approach isolates project funding from a sponsor's corporate debt, simplifying investment tracking and reducing the risk of underinvestment due to excessive debt. Nevertheless, it faces challenges from government regulations, political factors, environmental concerns, and complex procedures. Thus, this paper presents a study to investigate the relationship between project finance factors and economic development indicators. The relationship is translated to a PLS-SEM model development and assessment. To develop the model, the study adopted quantitative research approach where the data for the model was collected through a questionnaire survey using judgmental sampling for convenience. The sample size for the model is from 269 respondents, who are the employees in the Economic Department workforce in Abu Dhabi. The model's development and evaluation were conducted using SmartPLS software. The evaluation encompassed two stages: measurement and structural components, with the model successfully meeting all evaluation criteria. The results of hypothesis testing revealed that the relationships between Project Scope and Identifying Risk constructs with Economic Development construct are statistically significant with the strength 0f 0.520 and 0.227 respectively. Unfortunately, the relationships between Market Entry Strategy and Origination Capabilities with Economic Development are not statistically significant. In terms of model's goodness of fit, the model demonstrated a substantial overall explanatory power with GoF values of 0.667. While, the model's predictive relevancy with Q² value is 0.443, indicating how well the model can forecast economic development. In suggesting that the model explains approximately 44.3% of the variability in economic development. The findings of this study hold potential benefits for Economic Department employees dealing with project finance challenges. [ABSTRACT FROM AUTHOR]

Purpose: In the context of global economic downturn and intense competition, firms are increasingly resorting to supply chains to acquire capital support and achieve sustainability. This study aims to investigate the effect of supply chain finance (SCF) on corporate sustainability performance (CSP) and identifies SCF-related recipes for CSP. Design/methodology/approach: Based on a sample of 1,038 firms that disclose CSP – namely, corporate financial performance (CFP) and environmental, social and governance performance (ESGP) – the authors use a quasi-replication method consisting of empirical analysis with fuzzy-set qualitative comparative analysis (fsQCA) to investigate SCF's effects on CSP. Findings: The authors find that SCF has a "doing well by doing good" effect on CSP. CFP can promote the positive effect of SCF and ESGP while ESGP's positive effect on SCF and CFP is nonsignificant. In addition, heterogeneity tests show that SCF's promoting effect on CSP is affected by high-low CFP and ESGP. The fsQCA results verify the empirical findings and reveal five SCF-related recipes for achieving high CSP. Research limitations/implications: This study has the following two limitations. First, we do not consider how SCF affects CSP in different industries. There is a need to investigate whether industry heterogeneity changes SCF's effects on CSP, especially in prominent industries, such as the energy industry, with its high susceptibility to ESGP, and the manufacturing industry, with its extensive application of SCF. It will be important to investigate these industries to better understand SCF's role in sustainability. Second, we study the secondary supply chain – namely, core firm–suppliers and core firm–customers. The authors do not consider financial institutions (e.g. banks and guarantee institutions). SCF modes that include the participation of financial institutions, such as factoring financing and reverse factoring financing, cater more to the capital needs of diversified firms. In the future, studying specific industries that have made significant contributions to the application of SCF along with others that are more sensitive to environmental governance could better highlight the effect of SCF on sustainability and help supply chain managers understand the application value of SCF. Future research could also extend SCF participants into multiple roles to explore separate effects. Tracking financing demanders, fund providers and credit guarantors could capture SCF characteristics more comprehensively. Methodologically, it will be challenging to accurately measure SCF networks in terms of quantification. In future work, this could be performed with the help of artificial intelligence. Practical implications: First, our findings indicate that SCF has a "doing well by doing good" effect on core firms. SCF can not only overcome the capital shortage of SMEs but also provide significant benefits to core firms. Second, our findings provide SCF-related recipes to help firms fulfil ESGP obligations without sacrificing CFP under the pressure to "do good." The authors provide valuable insights and diverse recommendations to help supply chain managers, marketing executives and researchers adjust supply chain management strategies. Third, this work can guide executives in various fields to adopt SCF to achieve sustainability as a risk-mitigation strategy by means of marketing. Originality/value: This study identifies better, more straightforward SCF-related recipes for CSP (consisting of CFP and ESGP) using a quasi-replication analysis that improves upon conventional methods such as regression analysis, which have limited power. The authors provide valuable insights and diverse recommendations to help managers pursue sustainable development. The findings point to practical guidelines and feasible solutions that can support well-founded operational strategic and management decision-making, which can enhance a firm's competitiveness under uncertainty and a sluggish economy. [ABSTRACT FROM AUTHOR]

Problem definition: Smart contract improves the supply chain efficiency by enabling the supplier's commitment to postshipment financing decisions, which mitigates the bank's lending risk exposure and thereby reduces the financing cost. This paper investigates how smart contract adoption could facilitate trade finance activities and create value for supply chain firms. Academic/practical relevance: As the emerging blockchain technology could potentially reshape the trade financing landscape, understanding the impact of smart contract adoption and its interaction with trade finance activities is practically relevant and of great importance. Methodology: We develop a two-stage game-theoretic model and adopt supply chain finance theory to characterize the strategic interactions between supply chain firms in the presence of both operational risk (demand uncertainty) and financial risks (credit and liquidity risks). Results: We find that the value of smart contract depends critically on the trade finance structures, including both preshipment and postshipment financing schemes. Under the baseline trade finance model (with purchase order financing as preshipment financing and factoring as postshipment financing), smart contract alleviates the supplier's overpricing behavior caused by commitment frictions and helps restore the supply chain efficiency. When buyer direct financing serves as an alternative preshipment financing, smart contract might discourage the retailer from offering buyer direct financing, which significantly hurts the supplier and thus reduces the supply chain profit. When invoice trading serves as the alternative postshipment financing, the supplier always chooses invoice trading over factoring because of its trading flexibility, which in turn, makes the commitment frictions ubiquitous and unresolvable (namely, commitment trap). As a result, invoice trading could unexpectedly lead to a lower supplier's profit. Luckily, such an adoption dilemma can be resolved by smart contract adoption in conjunction with factoring. Managerial implications: Our findings provide guidelines for and insights into when smart contract should be adopted and its interactions with different trade finance schemes. In particular, smart contract adoption does not always benefit the supply chain. History: This paper has been accepted for the Manufacturing & Service Operations Management Special Section on the Interface of Operations, Finance and Technology. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1126. [ABSTRACT FROM AUTHOR]

Commercial businesses in an area affected by a natural hazard can have significant interruption and disruption because of damage and impeding factors including financing delays. The recovery of commercial buildings is a necessary but not solely sufficient condition for owners to reopen their businesses. At the community-level modeling scale for planning, the ability to model commercial recovery across the entire community, including short-term business operation disruption, is critical to understanding the interdependent recovery across engineering, economics, and social science. This study proposes a probabilistic commercial building recovery model to predict the recovery of commercial buildings over time following a hazard event and considers two critical types of downtime: (1) impeding factors such as financing delays, and (2) the repair process. A typical recovery resource portfolio available to business owners was developed and quantitatively incorporated into the proposed probabilistic commercial building recovery model. The ability to model commercial building recovery will inform decision makers of the entire recovery process for upcoming business recovery and community resilience metrics related to physical services stability, thereby improving community resilience planning. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Green finance is attracting a substantial amount of attention as an essential way to achieve green development. Through a sample of Chinese non-financial A-share listed companies from 2012 to 2020, we use the implementation of the green finance reform and innovation (GFRI) pilot zone policy that was introduced by the Chinese government in 2017 as a quasi-natural experiment and constructs a difference-in-differences-in-differences (DDD) model. The empirical evidence shows that the implementation of green finance reduces the total factor productivity (TFP) of heavily polluting enterprises in pilot zones. Our mechanism analysis shows that the GFRI pilot policy affects the TFP of enterprises through financing constraints and environmental protection investment rather than technological innovation. The heterogeneity analysis finds that the inhibitory effect of the GFRI pilot policy is more prominent in private enterprises, large enterprises, capital intensive enterprises, and small environmental responsibility enterprises. Further, the mechanism heterogeneity of the financing constraints analyses show that the GFRI pilot policy exerts greater levels of pressure on the financing constraints of private enterprises, large enterprises, and small environmental responsibility enterprises. The mechanism heterogeneity of the environmental investment analyses show that the GFRI pilot policy encourages environmental investment in private enterprises, small and medium enterprises, and small environmental responsibility enterprises. Our study provides evidence to support the expansion and promotion of GFRI and useful guidance on ways to implement green transformation in enterprises. [ABSTRACT FROM AUTHOR]

Although the Interim Regulations on the Management of Carbon Emissions Trading have been included in the annual legislative plan of China' s State Council for two years, they are still pending. The reason is that the existing carbon emissions trading system has not been standardized within the existing legal system. Therefore, as the logical starting point for the construction of the carbon emissions trading system, carbon emissions should be clarified as a usufructuary right at first, which is beneficial to the distribution and transfer of carbon emission rights in the primary market and to the circulation of carbon emission rights in the secondary market. This also conforms to the legislative purpose of the Interim Regulations on the Management of Carbon Emissions Trading and the logic of the legal economics theory. Secondly, the carbon emissions trading market should be constructed at three levels: ① The allocation and trading of carbon emission rights in the primary market can be conducted in two ways: for free or in the form of a paid auction. For projects involving major public interests, carbon emission rights can be allocated for free; for other carbon emission subjects, carbon emission rights should be allocated in the form of a paid auction. ② In the secondary market, it should be clarified that the transaction of security by carbon emission rights is in the form of a mortgage, not a pledge. At the same time, carbon emission right guarantee transactions should be registered in the registration system of the People' s Bank of China. ③ In the tertiary market, asset-backed securitization and factoring financing of carbon emission rights should be developed. Finally, in order to resist the price fluctuation and transaction risk caused by the failure of the market, it is necessary to establish an administrative supervision system. It is also vital to establish a repurchase and release mechanism and a storage and lending mechanism related to the stabilization of the carbon emission right transaction price so that the carbon emissions trading market can develop in a stable way. [ABSTRACT FROM AUTHOR]

The financial challenges of the last two years generated by the pandemic, military conflicts, etc. have determined Romanian companies to evaluate their businesses and choose the best sources in order to continue their economic activity. The companies' short- and medium-term objectives were shaped according to the new economic and social conditions. Access to financing is a key element for development, to build new jobs, to remain competitive. Consequently, the need for short-term financing increased and was honored by accessing factoring products by companies. Through the conducted study, it was highlighted that for small and medium-sized companies, factoring products are of interest and are very useful. The evolution of the products granted by Romanian financial institutions are in correlation with the international market, but the proportions are different. Developed countries promote financing through factoring, the proof is the volumes reported by factoring companies. At the same time, financial institutions maintain their prudential criteria in conditions where the economy is influenced by social and political factors, some unpredictable and with a high degree of risk. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the influence of integrated reporting (IR) on the cost of financing within the Turkish capital market. Specifically, we analyze the effects of IR on the weighted average cost of capital (WACC), cost of equity (COE), and cost of debt (COD) for companies listed on Borsa Istanbul. Additionally, we explore how IR moderates the relationship between environmental, social, and governance (ESG) scores and the cost of financing. Our panel data analysis reveals a positive association between IR and both WACC and COD, while the impact on COE is not statistically significant. However, the findings suggest that the utilization of IR by companies to enhance the communication of their value-creating activities can mitigate WACC and COD, thus indicating a moderating effect on the relationship between ESG factors and the cost of financing. [ABSTRACT FROM AUTHOR]

Modern finance theory assumes that the stock market is efficient, and stock prices reflect all available information. However, behavioral finance theory argues that stock prices can be influenced by psychological and emotional factors. This study aims to examine the impact of behavioral finance factors on investment decisions in the Saudi equity markets through the mediating variable of risk perception. An online questionnaire was distributed to 150 individual investors, out of which 134 were returned and ready for analysis. The data is analyzed using structural equation modeling (SEM). The results show that herding, disposition effect, and blue chip bias have a significant positive impact on risk perception. Overconfidence has a significant positive effect only on investment decision making, but not on risk perception. Risk perception is found to be significantly positively related to investment decision making. All four behavioral finance factors have a significant positive indirect effect on investment decision making through risk perception. This study is conducted in a particular cultural context, namely Saudi Arabia, and may not be generalizable to other cultural contexts. Moreover, this study focused only on four behavioral finance factors, and there may be other factors that could impact risk perception and investment decision making. The results highlight the importance of considering an individual's perception of risk when making investment decisions, as it can significantly impact their willingness to take risks and ultimately affect the performance of their investment portfolio. The results suggest the need for investors to consider their behavioral biases and for advisors and policymakers to develop strategies to mitigate their impact. [ABSTRACT FROM AUTHOR]

Copyright of Prometeo Conocimiento Científico is the property of Puerto Madero Editorial Academica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study is to reveal the factors affecting Industry 4.0 technology acceptance within the framework of a newly proposed Technology Acceptance Model (TAM) of medium and large-scale firms in Manisa and Izmir Organized Industrial Zones, which are important industrial centres in Turkey. Within the scope of the study, managers of 204 firms operating in Manisa and Izmir Organized Industrial Zones have been interviewed and the data obtained has been analysed by Structural Equation Modelling (SEM) within the scope of TAM. According to the findings, it has been found that perceived usability, perceived ease of use, perceived self-efficacy and financing factors affect attitude towards Industry 4.0 use. In addition, it has been concluded that the attitude towards the use of Industry 4.0 also affects the Industry 4.0 usage intention and the Industry 4.0 usage intention affects the usage behavior. [ABSTRACT FROM AUTHOR]

Summary: Earlier prediction of stock market details is an important factor in finance intersection. Moreover, predicting stock details is difficult as the stock datasets are unstructured and the entities differ based on each application. Hence, the conventional prediction model requires additional features for predicting stock prices. To end these issues, the presented article has focused on developing the novel African Buffalo‐based Bi‐Directional Recurrent Model (ABBRM) to predict stock details efficiently. Once the dataset is collected, preprocessing is performed in the hidden layer of the novel ABBRM. Moreover, the refined data is imported to the classification layer for feature selection and prediction processes. The incorporation of Buffalo fitness has afforded the most satisfactory stock price prediction outcome. Furthermore, the designed procedure is executed in the python environment with appropriate packages. Significant parameters like prediction accuracy, recall, precision, execution time, and error rate verified the projected model's robustness. Moreover, the presented model has attained an average accuracy of 93.5% for the short term and 99.91% for the long term. ABBRM was compared with existing techniques to identify the presented framework's effectiveness and has attained better results than other models. Here, the significance of the novel ABBRM is better prediction, which means the stock features were stored in the Buffalo memory fitness phase; during the execution phases, it helps to attain the exact prediction. Also, the Buffalo algorithm iterations were repeated continuously till a suitable prediction outcome was gained, and better training and testing outcomes were gained by the deep recurrent features in the designed model. Hence, this model is highly suitable for all prediction applications. [ABSTRACT FROM AUTHOR]

This paper investigates whether the effect of regional green finance (GF) on total factor carbon productivity (TFCP) differs by the level of environmental regulation intensity. Using data of 30 provinces in China from 2008 to 2020, we measure green finance based on the entropy weight method. Then, we employ the Super-slacks-based measure (SBM) model that incorporates undesirable outputs to calculate TFCP. Further, based on a dynamic panel threshold model, we empirically investigate the relationship between GF and TFCP. The main conclusions are as follows: (1) a nonlinear relationship exists between GF and TFCP in China. Moreover, we are the first to take market-based environmental regulation (MER) and command-and-control environmental regulation (CER) as threshold variables. With MER and CER as threshold variables, there was a double-threshold effect between both GF and TFCP. Hence, when GF has a negative impact on TFCP, the government should consider reasonably adjusting environmental regulations to reap the full benefits of GF in terms of TFCP growth. (2) The heterogeneity analysis states that the nonlinear effect of GF on TFCP in different regions is still significant under the thresholds of MER and CER. Therefore, the government should implement flexible environmental regulation policies to make GF promote TFCP according to region's characteristics. This study provides a new perspective on the relationship between green finance and total factor carbon productivity. [ABSTRACT FROM AUTHOR]

The study empirically tests the behavioral finance factors in the Nigerian Capital Market. It is argued that making investment decisions is not only influenced by rational factors but irrational factors like emotions and psychology of individual investor concern. To this end, the study employed four behavioral biases factors such as loss aversion, overconfidence, herding and risk perception to examine investors' decisions at the Nigerian Stock Market using the t-statistics and the ANOVA analysis. A total of one hundred (100) questionnaire were administered to relevant respondents of which about 88 were successfully retrieved. The empirical results revealed that Herding is the only behavioral biases factors that influences individual investors' decisions at the stock market with respect to age. The other factors failed the 5 significant tests. On the basis of the t-test analysis, herding behavior was again found to be statistically significant; suggesting that investors' decision to invest in the Nigerian Stock Market or not to invest, as indicated by the p value at the 5% level of significance {t = 0.462; p = 0.016}, is majorly influenced by the actions of other market participants (herding behavior). However, when the four behavioral biases were statistically ranked, the results showed that risk perception was first, followed by loss aversion, then herding and overconfidence. The study recommends among others that, investors should be very careful about the potential risks and consequences of herding attitudes in the market place (i.e. the tendency of being influenced by the actions of other market participants) which can miss-direct their judgments on the right investment decision if not properly and objectively evaluated. [ABSTRACT FROM AUTHOR]

The objectives in this study are: 1) To examine the effect of financial literacy variables on interest in using Islamic banks with financing factors, collection and distribution of funds with the sharia system. 2) To examine the effect of promotional variables on interest in using Islamic banks with financing factors, collection and distribution of funds with the sharia system. 3) To examine the effect of financial literacy and promotion variables on interest in using Islamic banks with financing factors, collection and distribution of funds with Islamic systems.The research was conducted using quantitative descriptive research methods. The population used was 374 members of Battalion D Pelopor Brimob Unit Polda Metro Jaya Cikarang West Java. The sample used was 79 respondents. The data analysis used Structural Equation Modelling (SEM). The expected research results are as follows: 1) the role of literacy has a positive effect on interest in using Islamic banks with financing factors, collection and distribution of funds with the sharia system. 2) the application of Promotion has a positive effect on the intention to use Islamic banks with financing factors, collection and distribution of funds with the Islamic system. 3) the role of literacy and the application of Promotion have a positive effect on the intention to use Islamic banks with financing factors, collection and distribution of funds with Islamic systems. [ABSTRACT FROM AUTHOR]

Purpose: As technological entrepreneurship has distinctive characteristics and needs particular conceptualizations, it is also important to have specific theoretical developments about its technological entrepreneurship. Studying the related domains like entrepreneurship and technology can be helpful in this path; however, their differences should be considered as well. The purpose of this study is to design a model in support of technological entrepreneurship. Since financing is considered as the main restriction on creating and developing technological entrepreneurship, the focus of this study is the research of financial policies of technological entrepreneurship.. Design/methodology/approach: This research is from the qualitative point of view and in terms of the purpose of application-development that has been done in the second part. At the first step, Iran's (IRI) national comprehensive policies have been studied from 1993 to 2020; out of 52 documents, 7 were relevant, of which 38 policies were eventually selected. Then, policy statements were explored, and open coding and categorization has been done through theme analysis approach to attain fundamental themes and organizational themes. In the second step, the themes were extracted in the form of soft research method with the approach of interpretive structural modeling to level the financing policies of technological entrepreneurship in Iran. Findings: The results show that the most important factors influencing financing and entrepreneurship in Iran are increasing the productivity of goods and services, supporting entrepreneurship, increasing the efficiency of monetary policies that are in the first level. Research limitations/implications: Research limitations include access to upstream documents, strategies, administrative and organizational coordination to study documents. Practical implications: These findings are very important to scholars, the policymakers and technological entrepreneurship operators in designing their financing strategies. The results show that the most important factors influencing financing and entrepreneurship in Iran are increasing the productivity of goods and services, supporting entrepreneurship, increasing the efficiency of monetary policies. Originality/value: To the best of the author's knowledge, this is the first study to explore the explanation and classification of technology-based entrepreneurship financing policies in Iran. Moreover, the findings of this study would prove useful in detailed studies of financing policies in the Middle Eastern countries as well. [ABSTRACT FROM AUTHOR]

With the development of technologies such as big data and artificial intelligence, digital technology and finance are becoming increasingly intertwined. At present, digital finance has altered the competitive environment of commercial banks, and the traditional competitive edges in service scenarios and channels, customer information, and capital have been challenged. Based on perfect competition and technology spillover effects, this study attempted to measure the impact of digital finance on commercial banks' total factor productivity (TFP) and its mediating and moderating mechanisms. We have used the data envelopment analysis-based Malmquist productivity index to measure the total factor productivity of 132 commercial banks in China between 2011 and 2019. The results show that (a) digital finance significantly enhances the TFP of commercial banks; (b) risk taking partially mediates the relationship between digital finance and TFP. The study further tests the effect of the nature of property rights and the moderating effect of diversification. The findings suggest that digital finance significantly improves the TFP of non-state-owned commercial banks but has no significant effect on the TFP of state-owned commercial banks. Additionally, the implementation of diversification can strengthen the effect of digital finance on TFP. [ABSTRACT FROM AUTHOR]

In order to deal with severe problems such as environmental pollution and climate change, the Chinese government has proposed the goal of carbon neutrality in 2030 and carbon peak in 2060. Strategic emerging industries have become key areas of high-quality growth of green economy. In order to solve the practical problems of insufficient funds and financing constraints, this paper empirically measures the financing efficiency of strategic emerging industries. Based on the Super Slack-Based Measure model, this paper selects the data analysis of listed companies in Beijing, Tianjin and Hebei from 2011 to 2020. At the same time, this paper systematically combs the index system that affects financing efficiency based on grounded theory. Based on the binary relation and structural level of adjacent matrix and reachable matrix, the explanatory analysis is carried out. On this basis, a systematic GMM model is established to explore the significance of different factors influencing financing efficiency. The research shows that the strategic emerging industry is still in the initial stage, the financing efficiency is not high and the financing output is insufficient. The factors affecting financing efficiency can be divided into 6 dimensions, 20 indicators in total and 5 multipole hierarchical levels. Credit financing, equity financing, financing constraints, technological innovation and government support are the important factors affecting financing efficiency. [ABSTRACT FROM AUTHOR]

Green agriculture is the direction of sustainable development of China's modern agriculture and the inherent requirement of taking the road of characteristic new agricultural modernization. As one of the main bodies of new agricultural management, professional large households are of great significance to lead the development of efficient agriculture and accelerate the development of green agricultural economy in Heilongjiang. Therefore, based on the theory of planned behavior, this article includes 275 major professional households in Heilongjiang Province as a sample of demonstration counties (cities) for green, high-quality, and efficient creation, combined with field research data and structural equation model, and discusses the willingness of large professional households to participate in green agricultural production financing and behavioral factors and mechanisms of action. The perceived behavior control (PBC), attitude toward the behavior (AB), and subjective norms (SNs) of large professional households to engage in green agricultural production determine their financing intentions (FNs), which further determines their financing behavior (FB). The results show that PBC, AB, and SN have a significant positive impact on the FN of large professional households, and further indirectly affect the FB. It should be noted that SNs have the most significant impact on the FN of large professional households to participate in green agricultural production. Therefore, it is necessary to establish effective government propaganda measures and preferential policies, improve the awareness of the importance of green agricultural production financing, and create a good social atmosphere for agricultural sustainable development and active participation in financing. The purpose of this study is to provide a reference for policymakers to formulate relevant policies to cultivate major professional households and develop green agricultural economy in Heilongjiang Province. [ABSTRACT FROM AUTHOR]

The objective of this study is to elaborate on the development of micro and small enterprises (MSEs) at the bottom of the economy, where most of them began as unbanked micro-ventures and may continue to be micro-enterprises even after being elevated to higher levels. This study contributes to the field of entrepreneurial finance by identifying the factors that influence the drivers and constraints of MSE upgrading. This paper employed models to show how unbanked MSEs transition to bankable ones, as well as to reveal the dynamics of MSEs' transition to bankability during the COVID-19 pandemic. This study's unit of analysis is MSEs, which initially have little or no access to bank loans. This study employs system dynamics (SD) modeling to investigate and manage the multifaceted response system of MSEs' growth toward bankability in the face of a coronavirus pandemic in Indonesia. This study also simulates a coronavirus pandemic outbreak to fine-tune MSEs' progress toward bankability. The dynamic models in this study reveal a number of variables that are critical in accelerating the bankability status of MSE from un-bankable to bankable, namely entrepreneurial MSE time to bankability, channel business, and MSE NPL. Policymakers can create high leverage policies for MSE bankability progression by changing these values. [ABSTRACT FROM AUTHOR]

Finance has a strong role in promoting green development; however, there are very few studies quantifying this relationship. To this end, based on the official green development indicator system of the Chinese government and province-level data from 2006 to 2017, the quantile regression model was used to analyze quantitatively the impact of finance on green development. The results show that financial development contributed significantly to green development, and furthermore, financial efficiency and green finance have a strong positive effect with the increase of the quantile, and financial scale also has a significant positive effect, but a diminishing marginal effect. In addition, the impact of financial development on green development has regional differences. In the eastern region, the finance factors can promote green development, but the financial scale and the green finance promotion function weaken along with the quantile increase. The financial scale and green finance do not support green development significantly in the central region. Financial scale, efficiency, and green finance support green development in the west region. [ABSTRACT FROM AUTHOR]

The study aimed to identify the influences on financing small-scale projects, either at the micro or macro level. And to identify the financing obstacles facing industrial projects in Iraq. And building a standard model for the factors affecting financing large projects. Providing goods that meet the needs and tastes Several conclusions have been reached, the most important of which is that the exchange rate does not have a significant long-term relationship with the volume of funding during the research period, due to the relative stability of the exchange rates during the research period. A set of recommendations was also reached, the most important of which is the need to find a cooperative formula between private financing institutions and government banks in order to open more windows for medium and small industrial projects to obtain financing [ABSTRACT FROM AUTHOR]

Chinese listed manufacturing companies face more serious financing constraints. Considering financing constraints and uncertainties, an accurate assessment of the innovation efficiency of China's listed manufacturing industry can provide decision support for China to become an innovation nation. We construct a heterogeneous stochastic frontier model to analyze the overall innovation efficiency, innovation quality efficiency, and innovation quantity efficiency of the Chinese manufacturing industry, using Chinese A-share listed manufacturing companies as a research sample from 2011–2019. The research results show that (1) Financing constraints make enterprises deviate from innovation efficiency, and internal financing significantly reduces enterprise financing constraints and does not bring uncertainty to subsequent financing, commercial credit, and external financing; although it can alleviate enterprise financing constraints, it will increase the uncertainty of subsequent financing constraints and the enterprise size.. (2) Internal financing, commercial credit financing, external financing, and firm size can effectively alleviate the financing constraint for firms to carry out quality innovation activities of invention patents and quantitative innovation activities of utility patents; internal financing, external financing, and firm size can effectively alleviate the financing constraint for quantitative innovation activities of design patents, while commercial credit financing has no significant effect. (3) The influence of factors such as financing constraints makes the real innovation efficiency of China's listed manufacturing industry only about 20%, and enterprises face more serious financing constraints. (4) The heterogeneity results found that the overall innovation efficiency, innovation quality efficiency, and innovation quantity efficiency in the eastern region are the highest, and the innovation efficiency level is higher than the national average, followed by the central and western regions. The overall innovation efficiency, innovation quality efficiency, and innovation quantity efficiency of the central region are higher than the national average, but the innovation quality efficiency and innovation quantity efficiency of the western region are lower than the national average; the overall innovation efficiency, innovation quality efficiency, and innovation quantity efficiency of large-scale enterprises are the highest and even higher than the average value of the whole sample, while the innovation efficiency of medium and small-scale enterprises are lower than the average value of the whole sample. [ABSTRACT FROM AUTHOR]