Early Warning of Agricultural Industrial Safety in Hunan Province: Based on Entropy Weighted Grey Relational Analyses

Wenxing XIAO, Yongjun MA, Yanhua LIU, Juan ZHANG

1.College of Business, Hunan University of Technology, Zhuzhou 412007, China; 2.College of Economics and Trade, Hunan University of Technology, Zhuzhou 412007, China

Abstract In this article, early warning analyses on agricultural industrial safety in Hunan Province from 2001 to 2013 are performed by constructing a four-indexed evaluation system and adopting the entropy weighted grey relational analysis model.The results show that Hunan’s agricultural industrial safety showed a good trend of transforming from "heavy warning" to "light warning"; the early warning results of agricultural industrial productivity index and the overall index remained consistent and performed well; the agricultural industrial competitiveness index and dependence index changed frequently and fluctuated around "medium warning"; and the control power index showed a deteriorating trend from "light warning" to "heavy warning".Therefore, support shall be increased continuously for the agricultural industry in terms of system construction, policy support and capital supply, and technological innovations and system innovations in the agricultural industry shall be promoted, especially for the improvement of the independent control of domestic capital, truly ensuring the efficiency, stability and safety of the agricultural industry development.

Key words Agricultural industrial safety, Four-indexed system, Grey relational analysis

1 Introduction

The safety of agricultural industry is a fundamental issue related to the survival and development of the Communist Party of China and China.Since China’s accession to the WTO in 2001, China’s agricultural opening has been continuously improved, and the industrial competitiveness and influence have been rising continuously.However, due to its inherent weakness and vulnerability to environmental factors at home and abroad, the development situation of China’s agricultural industry is not optimistic.For example, in recent years, there have been beheading actions carried out by multinational companies against leading agricultural companies in China, which have seriously threatened the safety of China’s agricultural industry.Therefore, constructing an early warning model for agricultural industrial safety to accurately assess the current agricultural safety situation in China and finding out the countermeasures has become an unescapable responsibility of agricultural economic workers.

The research on agricultural industrial safety can be divided into three categories.(i)Researches on the connotation of agricultural industrial safety.Liu Leshan regards solid foundation, healthy growth mode, sustainable development trend, strong autonomy, self-defense ability and competitiveness as an important research content of agricultural industrial safety[1].Xu Jiexiang divides agricultural industrial safety into independent productivity, independent control power and international competitiveness[2].Ni Hongxing focused on the comprehensive inspection of agricultural industrial safety in three aspects: the realization of the theme function, the situation of industrial control and the ability of industrial sustainable development[3].(ii)Analysis on factors affecting agricultural industrial safety.Based on the internal and external aspects, Zhu Xiaofeng focused on the effects of factors such as the agricultural production system, the ecological environment, and the medium and long-term effects of joining WTO[4].Lu Licai’s research results show that allowing foreign investment to enter at will is the main factor leading to the continuous decline of agricultural industrial safety in Latin America[5].Yang Wei found that structural effects and technology spillover effects did not appear in the process of foreign investment in China’s agriculture, but the safety of the agricultural industry was greatly threatened[6].Cao Qiuju carried out research on the mechanism and empirical research on the impact of open trade on agricultural industrial safety[7].(III)Assessment and early warning of agricultural industrial safety.He Weida conducted an assessment from three levels of industrial control power, industrial competitiveness, and industrial external dependence[8].Lu Xinye focused on early warning analyses on food safety[9].Sun Rong used the analytic hierarchy process to evaluate[10].Ning Xuemin used the data envelopment analysis model(DEA)for empirical analysis[11].Jin Saimei used factor analysis method for analysis[12].Xiao Wenxing chooses fuzzy comprehensive evaluation method for evaluation and early warning[13].Bao Yun used the sub-index method of expert weighting to provide early warning of soybean industrial safety[14].Dong Yinguo used the entropy method to empirically measure the safety of China’s agricultural industry from 2002 to 2012[15].

Based on the current research results, the following conclusions can be drawn:.(i)Currently, there is a lack of research on agricultural industrial safety early warning in Hunan Province.Hunan is a major agricultural province, and its total output value of agriculture, forestry, fishery and animal husbandry has always been among the top ten in China.How to maintain and improve the safety of the agricultural industry in Hunan Province needs further research.(ii)The research on the connotation of agricultural industrial safety is not thorough enough.How to construct a reasonable comprehensive index evaluation system needs further discussion.(iii)As an effective early warning model, the entropy weighted grey relational analysis method has been applied in public safety, corporate financial status,etc.However, it is rarely used in agricultural industrial safety early warning.

In this article, based on the knowledge of industrial economics, development economics, fuzzy mathematics, safety theory,etc., combining the existing research results, a new agricultural industrial safety evaluation system, four-indexed evaluation model is constructed, and taking Hunan Province as an example, a research on early warning of agricultural industrial safety is conducted by using the entropy weighted grey relational analysis method, so as to provide targeted suggestions for Hunan to accelerate the agricultural modernization and maintain agricultural industrial safety.

2 Four-indexed system for early warning of agricultural industrial safety

2.1 Connotation of the indicesDomestic and foreign scholars have constructed index systems for agricultural industrial safety early warning from different aspects, and some research results have been achieved.However, they put too much emphasis on industrial control power, competitiveness and external dependence but paid little attention to the requirements of the industry’s production environment and resilience.In the end, based on industrial economics, development economics and industrial safety theories, a four-indexed(productivity, competitiveness, control power, dependence)system for assessing the safety of agricultural industry is proposed in this article.The specific meaning and composition of indices at all levels are shown in Table 1.

2.2 Setting of index weightAccording to the four-indexed evaluation system, 13 economic indices such as industrial policy and capital cost were selected.Since the indices are divided into positive indices and negative indices and there is obvious incommensurability between the indices, direct calculation will result in distortion of evaluation results.Therefore, the necessary data processing will be carried out next.First, the inverse indices were converted into positive ones by using the reciprocal method.Then, dimensionless processing was performed for each index.

(1)

whereXijrepresents the actual value of thei-th index in thej-th year; andPijrepresents the dimensionless value of thei-th index in thej-th year.

Then, the entropy value of each evaluation index was determined according to the following formula:

(2)

Finally, the weight of each index was determined according to the following entropy method:

(3)

2.3 Early warning method(i)The ideal columnL0={X0(1),X0(2),X0(3)…X0(m)} and the comparison columns were selected.The four comparison columns selected wereL1={X1(1),X1(2),X1(3)…X1(m)},L2={X2(1),X2(2),X2(3)…X2(m)},L3={X3(1),X3(2),X3(3)…X3(m)} andL4={X4(1),X4(2),X4(3)…X4(m)}.These four comparative columns respectively represented the values of the 25%, 45%, 65% and 85% quantiles of the 13 indices in Table 1.The ideal columnL0was assigned as the maximum value of the 13 indices in Table 1 from 2001 to 2013.

(ii)The grey relational coefficient was calculated.Δj(x)=|X0(i)-Xj(i)|, wherein,Xj={Xj(1),Xj(2),Xj(3)…Xj(m)}.The calculation formula of the relational coefficient between L0andXjis as follows:

(4)

whereρis the resolution coefficient, usually 0.5.

(iii)The grey relational degree(Ej)was calculated according to the following formula:

(5)

(iv)The early warning level was divided.E1, E2, E3and E4are used to represent the gray relational degree of L1, L2, L3, L4and the ideal column L0, respectively.Early warning was divided into five levels: no warn(relational degree greater than L4), light warning(relational degree between L3and L4), medium warning(relational degree between L2and L3), heavy warning(relational degree between L1and L2)and serious warning(relational degree less than L1).

3 Empirical analysis

3.1 Data sourceThe original data of the 13 indices selected in the study were fromChinaStatisticalYearbook,ChinaRuralStatisticalYearbook,ChinaAgricultureYearbook,ChinaStatisticalYearbookonScienceandTechnology,InternationalStatisticalYearbook,ChinaTradeandExternalEconomicStatisticsYearbook,HunanStatisticsYearbook,HunanStatisticalYearbookonScienceandTechnologyand Wind database from 2001 to 2014.The missing data were replaced by the mean value.The reciprocals of the inverse indices were calculated and then subjected to pretreatment using formula(1).

3.2 Determination of index weightThe entropy value of each index was calculated according to formulas(2)and(3), and the results are shown in Table 2.

3.3 Analyses on calculation resultsThe relation coefficients between L1, L2, L3, L4and L0from 2001 to 2013 were calculated according to formula(4), and the results are shown in Table 3.Then, the grey-relation degrees were calculated according to formula(5), and the results are shown in Table 4.

As shown in Table 4, the warning level of agricultural industrial safety in Hunan Province was changing from "heavy warning" to "light warning", especially in the three years of 2009, 2010 and 2011, the warning level was in the range of "no warning".But at the same time, it could be seen that the state of Hunan’s agricultural industrial safety in the "no warning" or "light warning" range was still unstable.Especially under the background that the current world economic recovery is slow, the international market demand continues to shrink and the transformation of China’s economic structure accelerates, there are still certain risks in the safety of Hunan’s agricultural industry.

Table 2 Weight of indices for early warning of agricultural industrial safety in Hunan Province

In order to truly find out the factors affecting the safety of the agricultural industry in Hunan Province, early warning analyses was also performed for productivity, competitiveness, control power and dependence of agricultural industry using the method above.The results are shown in Table 5.

Table 5 Dynamics of early warning of agricultural industrial safety indices in Hunan Province from 2001 to 2013

Table 4 Grey relational degrees

Table 3 Grey relational coefficients

(i)The change trend of the agricultural industrial productivity index from 2001 to 2013 is consistent with the overall industrial safety index, showing a good trend of changing from "serious warning" to "light warning".Since joining the WTO in 2001, China has continuously increased its financial supports for agriculture, accelerated technological research and development, and promoted the process of agricultural modernization.Hunan Province has also strictly implemented tax incentives, financial guidance and support, and strengthened financial financing.In 2014, the contribution rate of agricultural scientific and technological progress exceeded 60%, 4.4 percentage points higher than the mean of China.As a result, the early warning level of agricultural productivity in Hunan Province continues to decline, and the development momentum is good.

(ii)The agricultural industrial competitiveness index from 2001 to 2013 had been oscillating around "medium warning", and the safety situation was not optimistic.Although the domestic and international share of Hunan’s agricultural exports continues to increase, Hunan Province has fewer leading agricultural enterprises with an output value of more than 1 billion, there are not enough well-known brands, and the technical content of exported agricultural products is still low.

(iii)The agricultural industrial control power index changed drastically from 2001 to 2013.Especially in 2012 and 2013, it was in the "heavy warning" range, indicating that the control power of the agricultural industry in Hunan Province had fallen to the edge of danger, the entry of foreign capital had produced an extremely significant crowding-out effect on local agricultural enterprises in Hunan Province, and sufficient attention must be paid.

(iv)The agricultural industrial dependence index changed frequently from 2001 to 2013, and in most of the years, it was in the "medium warning" range.Due to the inertia of agricultural enterprises’ dependence on foreign capital, this will restrict the sustainable development of the agricultural industry.

4 Main conclusions and policy recommendations

By using entropy weighted grey relational analysis method, early warning analyses were carried out on the four-indexed evaluation system of agricultural industrial safety in Hunan Province.The results show that during 2001-2013, the warning level of agricultural industrial safety had shown a good trend of changing from "serious warning" to "light warning".Among them, the evaluation results of the agricultural industrial productivity and the overall index were almost consistent, and the performance was good; the agricultural industrial competitiveness index and dependence index changed frequently and fluctuated around "medium warning"; and the agricultural industrial control power index showed a clear deteriorating trend, transforming from "light warning" to "serious warning", and the status is more severe.Therefore, in the context of the current supply-side reform, in order to maintain the safety of the agricultural industry in Hunan Province, the following policy recommendations are put forward.

4.1 Ensuring agricultural productivityInnovation is the core of agricultural productivity.Taking theOutlineoftheDevelopmentPlanforYangtzeRiverEconomicBeltas an opportunity, the cooperation with other provinces in the Yangtze River Economic Belt, especially with developed provinces such as Shanghai and Zhejiang in agricultural technology research and development can be strengthened.Taking the "100-piece, 1 000-park and 10 000-personnel" agriculture development project as a starting point, the reform of agricultural science and technology management system and the construction of agricultural science and technology collaborative innovation alliance should be deepened.Relying on the construction of agricultural science and technology innovation capabilities such as key scientific research projects in the agricultural field, focus is put on breakthroughs in common key technologies such as efficient use of agricultural resources and restoration of the ecological environment.Focusing on the integration of Internet and agriculture, the introduction of science and technology into villages and households and the construction of agricultural science and technology service cloud platform should be promoted to improve the efficiency of agricultural technology extension services, enhance farmers’ agricultural technology knowledge reserves and improve the level of agricultural intelligence and precision.

4.2 Cultivating and enhancing the core competitiveness of agricultureBy making full use of existing policy channels and enhancing supports for agricultural foreign co operations, the cultivation of agricultural enterprise groups with international competitiveness is accelerated.Relying on "The Belt and Road Initiative", agricultural cooperation with countries and key regions along the route should be developed to promote external cooperation of superior production capacity such as agricultural equipment and production materials, increase the intensity of external investment by Hunan agricultural enterprises, broaden the area for external investment, really enhancing the international influence and competitiveness of Hunan agricultural enterprises.

4.3 Firmly grasping agricultural control powerAt present, it is necessary to speed up the development of an assessment mechanism for the introduction of external investment.The prerequisite for the introduction of external investment in agriculture is to adhere to the basic requirements of ensuring the effective supply of major agricultural products and maintaining the safety of domestic agricultural industry and the interests of farmers.A research group for international mergers and acquisitions in the agricultural industry should be constructed to focus on the basic characteristics and harms of the typical cases of agricultural foreign investment mergers and acquisitions in recent years and evaluate the harms of future agricultural mergers and acquisitions, so as to make the correct response measures in time.

4.4 Paying more attention to the export quality of agricultural productsIt is necessary to strengthen the construction of export demonstration bases, promote standardized agricultural production, break through the trade barriers of importing countries, establish a quality and safety supervision system for exported agricultural products, establish and improve the quality and safety inspection and testing system of agricultural products, continuously improve the ability and level of agricultural product quality and safety law enforcement, strengthen the tracking and early warning of agricultural imports, carry out basic work required for industrial damage investigations and foreign trade barrier investigations, make efficient use of anti-dumping, countervailing, safeguard measures and other legal means to implement trade remedies in a timely manner, properly deal with trade frictions with foreign countries, and counter discriminatory trade protection measures using multilateral mechanisms, news propaganda, diplomatic consultations and other means to safeguard China’s agricultural exports.