Grey systems theory in economics – bibliometric analysis and applications’ overview

Purpose – As the grey systems theory has been used over the time in different economic areas, in the following, a short literature review will be put forward, starting from the usage of these theory in the supply chain management, decision-making process, financial performance evaluation, credit risk, energy consumption, investment efficiency, etc. The purpose of this paper is to identify some key studies from all the economic areas in which the grey systems can be used in order to open and to bring to the researchers new domains in which they can manifest their interest and in which they can successfully use the methods offered by the grey systems theory. Design/methodology/approach – Using the search engine offered by the Web of Science, a literature review has been performed for the economic grey systems applications developed over the time on both economic diagnosis and system’s forecasting. In addition, some hybrid grey systems theory – artificial intelligence techniques models have also been presented. Findings – The grey systems theory has brought its contribution to numerous economic application from various fields such as: supply chain management, decision-making process, financial performance evaluation, credit risk, energy consumption, investment efficiency, firms’ bankruptcy, product development, consumer income, monetization ratio, etc. Research limitations/implications – The present paper identifies the some of the most representative examples in which the grey theory has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space. Originality/value – Unlike other review papers written on the grey systems theory area, the present paper is only focusing on the economic applications in which this theory has been successfully used, bringing to the reader a general overview on this field and, in the same time, enabling new research perspectives.

PurposeThe purpose of this paper is to introduce the elementary concepts and fundamental principles of grey systems and the main components of grey systems theory. Also to discuss the astonishing progress that grey systems theory has made in the world of learning and its wide‐ranging applications in the entire spectrum of science.Design/methodology/approachThe characteristics of unascertained systems including incomplete information and inaccuracies in data are analysed and four uncertain theories: probability statistics, fuzzy mathematics, grey system and rough set theory are compared. The scientific principle of simplicity and how precise models suffer from inaccuracies are also shown.FindingsThe four uncertain theories, probability statistics, fuzzy mathematics, grey system and rough set theory are examined with different research objects, different basic sets, different methods and procedures, different data requirements, different emphasis, different objectives and different characteristics.Practical implicationsThe scientific principle of simplicity and how precise models suffer from inaccuracies are shown. So, precise models are not necessarily an effective means to deal with complex matters, especially in the case that the available information is incomplete and the collected data inaccurate.Originality/valueThe elementary concepts and fundamental principles of grey systems and the main components of grey systems theory are introduced briefly. The reader is given a general picture of grey systems theory as a new method for studying problems where partial information is known, partial information is unknown; especially for uncertain systems with few data points and poor information.

Based on the combination of rough set (RS) theory and grey system (GS) theory, this paper presents the grey-rough set modeling using constructive method (CM). Considering grey system theory having good ability in data preprocessing, grey number is used to describe the imprecise, uncertain, vague information in the information system through grey mapping, and then the grey information system is built. In this paper, CM is applied to investigate the RS. the definition of four pairs of approximate operators of grey rough set (GRS) is proposed using CM. At the same time, we investigated the GRS-related fundamental theory and delivered the algebra system of the GRS. It makes that the methods of GS classification can be used to describe the incomplete information more precisely, and enhance the ability of grey information covering, and therefore the connotative knowledge and rule in grey information system can be discovered more effectively and exactly.

PurposeAs the grey systems theory has been widely used in the field of sustainable development (SD) research, in the following, a short literature overview will be put forward, starting from the usage of these theories in the economic development, social inclusion and environmental protection contributions to the evolving process of SD during 2011–2021. The purpose of this paper is to identify some key studies from all the SD areas in which the grey systems can be used in order to open and to bring the researchers to new domains in which they can reveal their interest and in which they can successfully use the methods offered by the grey systems theory.Design/methodology/approachUsing the search engine offered by the Google Scholar and the Web of Science (WoS), a literature review has been performed for the grey systems applications on SD research on both grey relational analysis (GRA) and grey forecasting. In addition, some grey evaluation theories – clustering evaluation models and grey target decision models – have also been presented.FindingsMany grey models are widely used in the field of SD. Compared with other methods such as grey prediction, grey evaluation and decision-making model, GRA technology is the most used method, and the research using this method is more than three times that of all other methods.Research limitations/implicationsThe present paper identifies some of the most representative examples in which the grey system theory (GST) has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.Originality/valueThe present paper focuses on the SD applications in which GST has been successfully used, bringing to the reader a general overview on this field and, in the same time, enables new research perspectives.

PurposeThe purpose of this paper is to summarize the advances in grey system theory research and various application achievements in science and engineering. At the same time, it commemorates the 40th anniversary of the birth of grey system theory and the 10th anniversary of Grey Systems–Theory and Application.Design/methodology/approachFirstly, the innovations of theoretical research in grey system theory were summarized and some of the widely recognized new results are briefly described. By searching and combing the research results of grey system theory in China national knowledge infrastructure (CNKI) database and Web of Science by Institute for Scientific Information (ISI), this paper shows the rapid development trend of grey system theory in the past 40 years, and the successful applications of grey system theory in the fields of social sciences, natural sciences and engineering technologies.FindingsMore than 227 thousands literature were found by input 10 phrases such as grey system, grey number and sequence operator etc. in CNKI database. After entering the new century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year and more than 15 thousands papers have been included per year since 2014. Grey system method and model are widely used in physics, chemistry, biology and other fields of natural science, as well as transportation, electric power, machinery and other fields of engineering technology, and a large number of valuable results have been achieved.Practical implicationsIt can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development and high-level talent training from tens of thousands of literatures marked with important national science and technology projects and a large number of grey system literatures published by China’s double first-class universities and double first-class discipline construction universities.Originality/valueBoth innovations of theoretical research and practical application play important role in the growth of new theory. The innovations of theoretical research provide methods and tools for practical application, which is conducive to improve application efficiency and broaden application fields. A large number of practical applications needs have become the source of theoretical innovation and the solid background for the birth of theoretical innovation achievements.

Gray system theory is a new field of control theory, which is the product of applying cybernetics and methods to social and economic systems, and is also the product of the combination of control theory and operations research. It takes the gray system as the research object. Whitening, desalination, quantification, modeling, and optimization are the core of the gray system, and it aims to predict and control the development of various gray systems. The purpose of this paper is to study how to analyze and study the impact of higher education cooperation projects with the help of multi-dimensional gray theory and describe the gray system theory. The problem of analyzing the impact of cooperation projects proposed in this paper is based on the gray theory, so it is elaborated around its concept and related algorithms, and a case design and analysis of the impact of higher education cooperation projects are carried out. The experimental results show that the institutions responsible for infrastructure at the top of the school have the greatest impact on infrastructure projects, accounting for about 70%, with 20% weight for communication with government agencies, and about 10% for communication with users.

In recent years, there have been international movements advocating more sustainable societies, and as a result of such movements, a remarkably important sub-branch has been shaped in systems studies called sustainability. It would be vital to propose methods that could deal with inherent complexities and uncertainties in such systems. Grey systems theory (GST) represents a nascent method that could help to solve complexities in the face of multifaceted problems, uncertainty, and complexity in systems, and the theory could considerably contribute to sustainability studies. The present study sought to fill a gap and provide an updated review of the literature on the roles and impacts of GST-based methods in sustainability studies as one of the most significant areas of exploring economic, social and environmental systems. Primarily, the theoretical foundations of sustainability and GST were briefly reviewed. Next, by categorizing the studies conducted in the literature on sustainability studies, GST-based methods used in such studies were identified. Finally, the advantages, effects and functions of GST-based theories and their applications in sustainability studies were explicated. The papers found in this systematic review were searched on such databases as Scopus, Web of Science, and ScienceDirect, as published from 2010 up to the first three months of 2020, based on these keywords: grey relation or grey relational, grey model, grey system or grey systems, grey prediction, grey control, grey incidence, grey cluster, grey decision, grey input-output. The total number of publications found on all of the databases was 446, although (following a more meticulous investigation of the publications) 145 ones were used for the comprehensive analysis. The 10 different areas in which GST was used to explore sustainability in the publications were: sustainability assessment, industrial sustainability, urban sustainability, energy sustainability, sustainability development, businesses sustainability, agricultural sustainability, sustainable products, tourism sustainability, social sustainability. The results revealed that complexity, uncertainty, and inaccessibility of a large set of data and initial statistical distributions led researchers to rely on GST in sustainability studies, and that the applied areas of GST in terms of sustainability issues had some features in common, including linguistic variables, long-term projects, technological demands, conflicting goals, and uncertainty. Moreover, compared to other methods used to deal with uncertainty, GST did not require the formation of an extensive databank of classified rules and was more practical and efficient in sustainability calculations (as complex systems) with fewer numerical calculations. Ignoring systematic approaches, causal relations, cause-effect loops, and dynamic feedback was the missing link in the application of GST in sustainability studies as complex economic, social and environmental systems.

The scientific background that grey systems theory comes into being, the astonishing progress that grey systems theory has made in the world of learning and its wide employment in many scientific areas are presented in this paper. We compare grey systems theory with other kinds of uncertain information such as stochastic uncertainty, uncertainty, fuzzy uncertainty and rough uncertainty. Then the advances in grey systems theory and its applications are introduced by algorithms of grey numbers and grey algebraic systems, grey dynamic models and grey predictions, grey optimization analysis for decision-making, grey control models individually. We think that people engage in grey systems theoretical research should welcome and take all criticisms seriously. By doing so, existing problems and flaws can be overcome unceasingly, the new growing point be excavated unceasingly, exploring unceasingly, innovating unceasingly, make the grey systems theory grow upward unceasingly.

PurposeAs the demand for online auctions increases, the process of monitoring multiple auction houses, deciding which auction to participate in and making the right bids, become challenging tasks for consumers. Hence, knowing the closing price of a given auction would be an advantage, since this information will ensure a win in a given auction. However, predicting a closing price for an auction is not easy, since it is dependent on many factors. The purpose of this paper is to report on a predictor agent that utilises grey system theory to predict the closing price for a given auction.Design/methodology/approachThe focus of the research is on grey system agent. This paper reports on the development of a predictor agent that attempts to predict the online auction closing price in order to maximise the bidder's profit. The performance of this predictor agent is compared with two well‐known techniques, the Simple Exponential Function and the Time Series, in a simulated auction environment and in the eBay auction.FindingsThe grey theory agent gives a better result when less input data are made, while the Time Series Agent can be used with the availability of a lot of information. Although the Simple Exponential Function Agent is able to predict well with less input data, it is not an appropriate method to be applied in the prediction model since its formula is not realistic and applicable in predicting the online auction closing price. The experimental results also showed that using moving historical data produces a higher accuracy rate than using fixed historical data for all three agents.Originality/valueGrey system theory prediction model, GM(1, 1) has not been applied in online auction prediction. In this paper the authors have applied grey theory into an agent to predict the closing price of an online auction, in order to increase the profit of bidders in the bidding stage. The experimental results show that the accuracy of the grey prediction model is more then 90 per cent, with less then eight historical data inputs.

As the road traffic system is an uncertain system, the occurrence of traffic accidents is also an uncertain system with partial information known and the other unknown. Therefore, it's suitable to apply the gray model theory to predict the traffic accidents. This paper expounds the principles of gray model and gives an example to show the feasibility and practicability of the gray model applied in the forecasting of traffic accidents.

Grey system theory and rough set theory are two different mathematical tools that are used to deal with uncertain or incomplete information, and yet they are relevant and complementary to a certain degree. The appropriate hybrid of the two theories can overcome the shortages of their definitions and applications and thus has more powerful functions. This paper proposes An Integrated Methodology that extracting decision rules based on combining grey system and rough set theory. The effectiveness of the proposed methodology was verified by application of this methodology to discover grade rules of electrical transformer evaluation.

Grey system theory and rough set theory are two different mathematical tools that are used to deal with uncertain or incomplete information, and yet they are relevant and complementary to a certain degree. The appropriate hybrid of the two theories can overcome the shortages of their definitions and applications and thus has more powerful functions. This paper proposes An Integrated Methodology that extracting decision rules based on combining grey system and rough set theory. The effectiveness of the proposed methodology was verified by application of this methodology to discover grade rules of electrical transformer evaluation.

PurposeThe Grey System Theory (GST) is an emerging area of research within artificial intelligence. Since its founding in 1982, it has seen a lot of multidisciplinary applications. In just a short period, it has garnered some considerable strengths. Based on the 1987–2021 data collected from the Web of Science (WoS), the current study reports the advancement of the GST.Design/methodology/approachResearch papers utilizing the GST in the fields of economics and education were retrieved from the Web of Science (WoS) platform using a set of predetermined keywords. In the final stage of the process, the papers that underwent analysis were manually chosen, with selection criteria based on the information presented in the titles and abstracts.FindingsThe study identifies prominent authors, institutions, publications and journals closely associated with the subject. In terms of authors, two major clusters are identified around Liu SF and Wang ZX, while the institution with the highest number of publications is Nanjing University of Aeronautics and Astronautics. Moreover, significant keywords, trends and research directions have been extracted and analyzed. Additionally, the study highlights the regions where the theory holds substantial influence.Research limitations/implicationsThe study is subject to certain limitations stemming from factors such as the language employed in the chosen literature, the papers included within the Web of Science (WoS) database, the designation of works categorized as “articles” in the database, the specific selection of keywords and keyword combinations, and the meticulous manual process employed for paper selection. While the manual selection process itself is not inherently limiting, it demands a greater investment of time and meticulous attention, contributing to the overall limitations of the study.Practical implicationsThe significance of the study extends not only to scholars and practitioners but also to readers who observe the development of emerging scientific disciplines.Originality/valueThe analysis of trends revealed a growing emphasis on the application of GST in diverse domains, including supply chain management, manufacturing and economic development. Notably, the emergence of COVID-19 as a new research focal point among GST scholars is evident. The heightened interest in COVID-19 can be attributed to its global impact across various academic disciplines. However, it is improbable that this interest will persist in the long term, as the pandemic is gradually brought under control.

A hybrid model for stock market forecasting and portfolio selection based on ARX, grey system and RS theories

Using the method of bibliometrics, a 1982~2006 Grey Systems database was constructed for China from National Knowledge Infrastructure(CNKI). Gather documents with Grey System contained in their titles, by analyzing the year, institution, journal, high citation frequency, theme, subject, output manner etc. Quantitative Characteristics of distribution, structure change, research topic, research hotspots are depicted. The results concern: papers upon the grey system increase linearly; the research force mainly distributes in universities; the journals of natural science and engineering are the main carriers which present the achievements of the grey system research; the grey system has spread extensively in the natural science, engineering, agro-forestry, hygiene, human society science and many other fields.