scholarly journals Analyzing Relationship between Financing Constraints, Entrepreneurship, and Agricultural Company Using AI-Based Decision Support System

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Xiaohu Liu ◽  
Han Li ◽  
Hong Li

Decision support technology has become a key link in modern information strategy. With the deepening of research, introduced expert systems have been introduced into decision support systems. In this way, decision support systems gradually become more uncertain and capable of handling uncertainties. The development direction of decision support system is typically based on qualitative analysis. Intelligent decision support system is a system that combines decision support system with artificial intelligence technology. This study attempts to assess in an innovative way the relationship between financing constraints, entrepreneurship, and agricultural firms. The most recently proposed intelligent decision support system, AI-assisted Intelligent Decision Support System (AIIDSS), is used to predict the impact of entrepreneurship on corporate performance. The paper constructs an entrepreneurship index from five aspects: innovation, competitiveness, human capital accumulation, management capability, and adventurous spirit. The method intends to construct the Kaplan–Zingales (KZ) index to evaluate financing constraints. Through an empirical study, it was found that entrepreneurship can significantly promote the growth of listed agricultural companies. The study can drastically reduce the difficulties involved in financing constraints normally faced by agricultural companies. The impact paths include increasing agricultural company operating cash flow, improving stock liquidity, and increasing debt financing. The research suggests that if listed agricultural companies are to improve financing constraints, entrepreneurs must improve their own competitiveness and management capabilities. This will help in reasonably controlling research and development investment besides the impulse to take risks. As the growth of an enterprise relies on considering the determinants of financing constraints, this research provides an effective investigation technique. Moreover, the findings of the study will help entrepreneurs, particularly agricultural companies, to bear most of the risks and to avail most of the opportunities.

2016 ◽  
Vol 17 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Hela Ltifi ◽  
Saber Amri ◽  
Mounir Ben Ayed

The development of intelligent decision support systems requires much research effort to solve decision-making problems’ complexity. In fact, the combination of both intelligent components and visualization aspects in intelligent decision support system required a lot of efforts in order to develop advanced information visualization schemes for decision-making processes. For this, an efficient evaluation of these systems has become a major concern for applications in multiple fields. The reports of the existing usability evaluation studies are helpful to verify the potential and the limitations of these tools. However, it is important to integrate more relevant metrics for visual analytics tasks in dynamic intelligent decision support system. The proposed method consists of a questionnaire that is given to the users and a subsequent analysis of the resulting data using fuzzy logic. The advantage of the fuzzy model is its ability to transform the input survey scores into linguistic variables, as well as linguistic evaluation of the overall intelligent decision support system visualization tool. With this approach, it is possible to model the vagueness in the ordinal judgments obtained from the users’ evaluation about the visualizations of intelligent decision support system and to support uncertainty in such evaluation.


2017 ◽  
Vol 26 (06) ◽  
pp. 1750025
Author(s):  
Nady Slam ◽  
Wushour Slamu ◽  
Pei Wang

This article summarizes reviews regarding the evolution of intelligent decision-support systems (IDSS). After doing an extensive literature survey, it was apparent that the theoretical foundation of IDSS has not undergone much improvement. The emergence and development of Artificial General Intelligence (AGI) provides a new theoretical perspective for constructing and developing IDSS. An AGI project, Non-Axiomatic Reasoning System (NARS), is built into the framework of a unified reasoning system, with a logic, Non-Axiomatic Logic (NAL). In this paper, we propose a formal model with unified planning, learning and uncertainty representation capabilities using NAL. We have developed a prototype decision-support system for urban fire-fighting within this framework, and obtained results demonstrating that this method can provide an effective way for intelligent decision-support systems.


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