The survival and development of SMEs (small and medium enterprises) is an important issue for the Chinese economy. In particular, business succession in SMEs is a persistent issue. Business succession involves selecti...The survival and development of SMEs (small and medium enterprises) is an important issue for the Chinese economy. In particular, business succession in SMEs is a persistent issue. Business succession involves selection of a successor, asset inheritance, transfer of management rights, accumulation of business connections and technology succession, and soforth. This all requires smooth execution of a business succession plan. However, many SMEs do not have a business succession plan, nor are they preparing one. Our task is to explore the reasons these preparations are not being made. Here, the purpose of our research is to get a picture of the status of preparations for business succession in SMEs in China, and the actual circumstances of succession, based on the results of a fact-finding survey of Chinese SMEs, and at the same time bring to the surface the primary factors which influence preparations and plans. The results of the analysis shed light on the status of business succession preparations, successor’s awareness of issues, decision making, and so on. This survey highlights the awareness of business succession among business managers.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
文摘The survival and development of SMEs (small and medium enterprises) is an important issue for the Chinese economy. In particular, business succession in SMEs is a persistent issue. Business succession involves selection of a successor, asset inheritance, transfer of management rights, accumulation of business connections and technology succession, and soforth. This all requires smooth execution of a business succession plan. However, many SMEs do not have a business succession plan, nor are they preparing one. Our task is to explore the reasons these preparations are not being made. Here, the purpose of our research is to get a picture of the status of preparations for business succession in SMEs in China, and the actual circumstances of succession, based on the results of a fact-finding survey of Chinese SMEs, and at the same time bring to the surface the primary factors which influence preparations and plans. The results of the analysis shed light on the status of business succession preparations, successor’s awareness of issues, decision making, and so on. This survey highlights the awareness of business succession among business managers.
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.
