Recently,data science techniques utilize artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to take an influence and grow their businesses.For SMEs,owing to the inexistence...Recently,data science techniques utilize artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to take an influence and grow their businesses.For SMEs,owing to the inexistence of consistent data and other features,evaluating credit risks is difficult and costly.On the other hand,it becomes necessary to design efficient models for predicting business failures orfinancial crises of SMEs.Various data classification approaches forfinancial crisis prediction(FCP)have been presented for predicting thefinancial status of the organization by the use of past data.A major process involved in the design of FCP is the choice of required features for enhanced classifier out-comes.With this motivation,this paper focuses on the design of an optimal deep learning-basedfinancial crisis prediction(ODL-FCP)model for SMEs.The proposed ODL-FCP technique incorporates two phases:Archimedes optimization algorithm based feature selection(AOA-FS)algorithm and optimal deep convo-lution neural network with long short term memory(CNN-LSTM)based data classification.The ODL-FCP technique involves a sailfish optimization(SFO)algorithm for the hyperparameter optimization of the CNN-LSTM method.The performance validation of the ODL-FCP technique takes place using a benchmarkfinancial dataset and the outcomes are inspected in terms of various metrics.The experimental results highlighted that the proposed ODL-FCP technique has out-performed the other techniques.展开更多
Previous literature showed mixed results about the impact of CEOs’financial literacy(CFL)on small and medium-sized enterprises’(SMEs)innovation.This relationship can be motivated by relevant variables,which are miss...Previous literature showed mixed results about the impact of CEOs’financial literacy(CFL)on small and medium-sized enterprises’(SMEs)innovation.This relationship can be motivated by relevant variables,which are missing in the previous literature and make a difference as mediators.In this sense,based on the theoretical framework related to upper echelon theory and resource-based view,this study focuses on the mediating effect of risk-taking attitude and management control systems(MCS)varia-bles.Empirical data from 310 SMEs gathered using a qualitative research questionnaire are analyzed using structural equation modeling methodology.Specifically,estimations are carried out considering the partial least square method.Findings show that MCS and managers’risk attitudes fully mediate the relationship between financial literacy(FL)and innovation.Between these two mediating variables,the implementation of MCS stands out because it also enables the mediating effect of CEOs’risk-taking in the CFL–technological innovation relationship.As the results do not support the significant direct relationship between FL and risk attitude,they confirm an indirect effect through MCS.Furthermore,based on the study findings,SMEs’directors and owners,business associations,and public authorities can improve SMEs’technological innovation by implementing training programs and policies to foster CFL.They can also acknowledge the interdependency between organizational factors and individual characteristics to enhance SMEs’technological innovation.展开更多
As an important force in promoting economic and social development,small and medium-sized enterprises play a crucial role in enhancing China’s economic strength,creating employment opportunities,and promoting industr...As an important force in promoting economic and social development,small and medium-sized enterprises play a crucial role in enhancing China’s economic strength,creating employment opportunities,and promoting industrial structural transformation.However,due to their inherent weaknesses,small and medium-sized enterprises often face difficulties in financing within the traditional financial service system.This makes it difficult for small and medium-sized enterprises to inject vitality into the development of the market economy by expanding their financing scale.Since 2013,China has vigorously developed inclusive finance and extended the services of traditional financial institutions to small and medium-sized enterprises,providing policy guidance,resource support,and technical support to alleviate the financing difficulties of small and medium-sized enterprises.Based on this,this article focuses on the current financing problems faced by small and medium-sized enterprises and specifically elaborates on how to lower the financing threshold for small and medium-sized enterprises and broaden their financing channels through inclusive finance,in order to promote the development of inclusive finance and a virtuous cycle of financing for small and medium-sized enterprises.展开更多
In present digital era,data science techniques exploit artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to have an impact and develop their businesses.Data science integr...In present digital era,data science techniques exploit artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to have an impact and develop their businesses.Data science integrates the conventions of econometrics with the technological elements of data science.It make use of machine learning(ML),predictive and prescriptive analytics to effectively understand financial data and solve related problems.Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations.At the same time,it is needed to develop an effective tool which can assist small to medium sized enterprises to forecast business failure as well as financial crisis.AI becomes a familiar tool for several businesses due to the fact that it concentrates on the design of intelligent decision making tools to solve particular real time problems.With this motivation,this paper presents a new AI based optimal functional link neural network(FLNN)based financial crisis prediction(FCP)model forSMEs.The proposed model involves preprocessing,feature selection,classification,and parameter tuning.At the initial stage,the financial data of the enterprises are collected and are preprocessed to enhance the quality of the data.Besides,a novel chaotic grasshopper optimization algorithm(CGOA)based feature selection technique is applied for the optimal selection of features.Moreover,functional link neural network(FLNN)model is employed for the classification of the feature reduced data.Finally,the efficiency of theFLNNmodel can be improvised by the use of cat swarm optimizer(CSO)algorithm.A detailed experimental validation process takes place on Polish dataset to ensure the performance of the presented model.The experimental studies demonstrated that the CGOA-FLNN-CSO model has accomplished maximum prediction accuracy of 98.830%,92.100%,and 95.220%on the applied Polish dataset Year I-III respectively.展开更多
The direct effect of access to finance on the growth of Small and Medium Enterprises(SMEs)run by entrepreneurs is well studied.However,there is limited understanding on the difference in the rate of entrepreneurship g...The direct effect of access to finance on the growth of Small and Medium Enterprises(SMEs)run by entrepreneurs is well studied.However,there is limited understanding on the difference in the rate of entrepreneurship growth across a nation.Further,the empirical findings relating to the financial literacy of entrepreneurs significantly differ across different geographic communities.Thus,the purpose of this study is to examine the impact of financial literacy on the relationship between access to finance and the business growth of the SME Sector in the Northern Province of Sri Lanka in the post-civil war context,as SMEs promote resilience of communities to recover from adversities such as civil war.The Indebtedness of Northern Province has suddenly increased,as there is a sharp growth evident in the average debt per family in the post-civil war context.Thus,demonstrating the lack of proper financial literacy and the discipline required to be financially stable,is a crucial benchmark for a successful business.According to the model of ambidextrous management in entrepreneurial growth companies,entrepreneurship is process where the entrepreneurial orientation turns into implementation and thereby leads to the business growth.However,the effect of access to finance to the entrepreneurs and the impact of financial literacy of the entrepreneur on this relationship are not examined.Thus,this study incorporates the effect of access to finance and the moderating effect of financial literacy to the existing model.It was evident from this study that,access to finance has a direct impact on the growth of the SMEs in the Northern Province of Sri Lanka.The result also reflects that the financial literacy and ability to make the financial decisions influence access to finance,resulting in business growth.展开更多
Financing has been always diffi cult for small and micro enterprises(SMEs() in Enshi nationality area mainly because of its higher fi nancing cost, immaturity and high monopoly of the fi nancial market. This paper, ba...Financing has been always diffi cult for small and micro enterprises(SMEs() in Enshi nationality area mainly because of its higher fi nancing cost, immaturity and high monopoly of the fi nancial market. This paper, based on classical theories and model as well as fi nancial market status in Enshi, combs and analyzes major factors infl uencing fi nancing of small and micro enterprises in Enshi, sets up a FFMO model and proves that reform measures of fi nancial organization competition promotion and reduction of small and micro enterprises’ cost adopted by large fi nancial organizations in order to pursue maximized profi t under the market environment with rising barriers can balance the fi nancial market and make it favorable for development of small and micro enterprises’ fi nancing.展开更多
文摘Recently,data science techniques utilize artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to take an influence and grow their businesses.For SMEs,owing to the inexistence of consistent data and other features,evaluating credit risks is difficult and costly.On the other hand,it becomes necessary to design efficient models for predicting business failures orfinancial crises of SMEs.Various data classification approaches forfinancial crisis prediction(FCP)have been presented for predicting thefinancial status of the organization by the use of past data.A major process involved in the design of FCP is the choice of required features for enhanced classifier out-comes.With this motivation,this paper focuses on the design of an optimal deep learning-basedfinancial crisis prediction(ODL-FCP)model for SMEs.The proposed ODL-FCP technique incorporates two phases:Archimedes optimization algorithm based feature selection(AOA-FS)algorithm and optimal deep convo-lution neural network with long short term memory(CNN-LSTM)based data classification.The ODL-FCP technique involves a sailfish optimization(SFO)algorithm for the hyperparameter optimization of the CNN-LSTM method.The performance validation of the ODL-FCP technique takes place using a benchmarkfinancial dataset and the outcomes are inspected in terms of various metrics.The experimental results highlighted that the proposed ODL-FCP technique has out-performed the other techniques.
文摘Previous literature showed mixed results about the impact of CEOs’financial literacy(CFL)on small and medium-sized enterprises’(SMEs)innovation.This relationship can be motivated by relevant variables,which are missing in the previous literature and make a difference as mediators.In this sense,based on the theoretical framework related to upper echelon theory and resource-based view,this study focuses on the mediating effect of risk-taking attitude and management control systems(MCS)varia-bles.Empirical data from 310 SMEs gathered using a qualitative research questionnaire are analyzed using structural equation modeling methodology.Specifically,estimations are carried out considering the partial least square method.Findings show that MCS and managers’risk attitudes fully mediate the relationship between financial literacy(FL)and innovation.Between these two mediating variables,the implementation of MCS stands out because it also enables the mediating effect of CEOs’risk-taking in the CFL–technological innovation relationship.As the results do not support the significant direct relationship between FL and risk attitude,they confirm an indirect effect through MCS.Furthermore,based on the study findings,SMEs’directors and owners,business associations,and public authorities can improve SMEs’technological innovation by implementing training programs and policies to foster CFL.They can also acknowledge the interdependency between organizational factors and individual characteristics to enhance SMEs’technological innovation.
文摘As an important force in promoting economic and social development,small and medium-sized enterprises play a crucial role in enhancing China’s economic strength,creating employment opportunities,and promoting industrial structural transformation.However,due to their inherent weaknesses,small and medium-sized enterprises often face difficulties in financing within the traditional financial service system.This makes it difficult for small and medium-sized enterprises to inject vitality into the development of the market economy by expanding their financing scale.Since 2013,China has vigorously developed inclusive finance and extended the services of traditional financial institutions to small and medium-sized enterprises,providing policy guidance,resource support,and technical support to alleviate the financing difficulties of small and medium-sized enterprises.Based on this,this article focuses on the current financing problems faced by small and medium-sized enterprises and specifically elaborates on how to lower the financing threshold for small and medium-sized enterprises and broaden their financing channels through inclusive finance,in order to promote the development of inclusive finance and a virtuous cycle of financing for small and medium-sized enterprises.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under Grant Number(RGP 1/147/42),www.kku.edu.sa.This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-Track Path of Research Funding Program.
文摘In present digital era,data science techniques exploit artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to have an impact and develop their businesses.Data science integrates the conventions of econometrics with the technological elements of data science.It make use of machine learning(ML),predictive and prescriptive analytics to effectively understand financial data and solve related problems.Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations.At the same time,it is needed to develop an effective tool which can assist small to medium sized enterprises to forecast business failure as well as financial crisis.AI becomes a familiar tool for several businesses due to the fact that it concentrates on the design of intelligent decision making tools to solve particular real time problems.With this motivation,this paper presents a new AI based optimal functional link neural network(FLNN)based financial crisis prediction(FCP)model forSMEs.The proposed model involves preprocessing,feature selection,classification,and parameter tuning.At the initial stage,the financial data of the enterprises are collected and are preprocessed to enhance the quality of the data.Besides,a novel chaotic grasshopper optimization algorithm(CGOA)based feature selection technique is applied for the optimal selection of features.Moreover,functional link neural network(FLNN)model is employed for the classification of the feature reduced data.Finally,the efficiency of theFLNNmodel can be improvised by the use of cat swarm optimizer(CSO)algorithm.A detailed experimental validation process takes place on Polish dataset to ensure the performance of the presented model.The experimental studies demonstrated that the CGOA-FLNN-CSO model has accomplished maximum prediction accuracy of 98.830%,92.100%,and 95.220%on the applied Polish dataset Year I-III respectively.
文摘The direct effect of access to finance on the growth of Small and Medium Enterprises(SMEs)run by entrepreneurs is well studied.However,there is limited understanding on the difference in the rate of entrepreneurship growth across a nation.Further,the empirical findings relating to the financial literacy of entrepreneurs significantly differ across different geographic communities.Thus,the purpose of this study is to examine the impact of financial literacy on the relationship between access to finance and the business growth of the SME Sector in the Northern Province of Sri Lanka in the post-civil war context,as SMEs promote resilience of communities to recover from adversities such as civil war.The Indebtedness of Northern Province has suddenly increased,as there is a sharp growth evident in the average debt per family in the post-civil war context.Thus,demonstrating the lack of proper financial literacy and the discipline required to be financially stable,is a crucial benchmark for a successful business.According to the model of ambidextrous management in entrepreneurial growth companies,entrepreneurship is process where the entrepreneurial orientation turns into implementation and thereby leads to the business growth.However,the effect of access to finance to the entrepreneurs and the impact of financial literacy of the entrepreneur on this relationship are not examined.Thus,this study incorporates the effect of access to finance and the moderating effect of financial literacy to the existing model.It was evident from this study that,access to finance has a direct impact on the growth of the SMEs in the Northern Province of Sri Lanka.The result also reflects that the financial literacy and ability to make the financial decisions influence access to finance,resulting in business growth.
文摘Financing has been always diffi cult for small and micro enterprises(SMEs() in Enshi nationality area mainly because of its higher fi nancing cost, immaturity and high monopoly of the fi nancial market. This paper, based on classical theories and model as well as fi nancial market status in Enshi, combs and analyzes major factors infl uencing fi nancing of small and micro enterprises in Enshi, sets up a FFMO model and proves that reform measures of fi nancial organization competition promotion and reduction of small and micro enterprises’ cost adopted by large fi nancial organizations in order to pursue maximized profi t under the market environment with rising barriers can balance the fi nancial market and make it favorable for development of small and micro enterprises’ fi nancing.
