Efficiency Analysis of Scientific and Technological Innovation in Grain Production Based on Improved Grey Incidence Analysis

Analyzing and evaluating the efficiency of scientific and technological innovation in grain production is conducive to the rational allocation of resources, promoting the development of scientific and technological innovation in grain production and providing guarantee for grain security. By refining the elements of grain production and scientific and technological innovation, an evaluation system of scientific and technological innovation in grain production is constructed. Firstly, combining linear programming together with the traditional grey synthetic incidence analysis model, a incidence analysis of the scientific and technological innovation indicators of grain production is carried out, and the key and secondary indexes affecting grain outputs are screened by an improved grey incidence analysis model. Secondly, based on DEA-Malmquist index model and taking the grain production process as the research object, the scientific and technological achievement transformation indicators are divided into pre-production, in-production and post-production indicators. The key indicators and secondary indicators of scientific and technological innovation of grain production in various cities of Henan Province from 2010 to 2019 are used to analyze the efficiency of scientific and technological innovation in each stage of grain production. The results show that: (1) The type of basic ability of scientific and technological innovation indicators and the transformation ability of scientific and technological innovation achievements are the major indicators influencing grain outputs, and the investment of basic resources of scientific and technological innovation and the transformation of scientific and technological innovation achievements are the most important to improve grain outputs. (2) In addition, the study reveals that the secondary indicators of the technological innovation efficiency of grain production based on the DEA-Malmquist index model are more efficient than the key indicators in the pre-production, in-production and post-production stages. And there are gaps in the scientific and technological innovation performance of grain production among cities in Henan Province, and the index of technological progress is the leading factor for the gap.

Evaluating Unemployment through Grey Incidence Analysis Model: A Study of One Hundred Thirteen Selected Countries

The purpose of the study is to gauge the unemployment level of selected one hundred and thirteen countries. The design of the study includes a survey of the literature, extraction of relevant data and analysis. The study follows a quantitative paradigm of research that uses secondary data set taken from the website of World Development Indicators (WDI). The analysis encompasses selected countries based on the availability of data. The data has been analyzed using Grey Incidence Analysis Model, commonly known as GRA. For interpretation of the results, the methodology has been augmented with the scheme of ensigns (i.e. classification of countries into Extremely Low, Very Low, Low, Moderate, High, Very High, Extremely High) of the level of unemployment. Results show that J&APR have an extremely low level of unemployment and member countries of SADC have an extremely high level of unemployment. Pakistan fall under the ensign of very low, therefore have a low level of unemployment. It is valuable to study equally useful for governments, academia and the international community. This study provides critical new information on the phenomenon.

Composite Appraisal of Women Development in Selected Thirty-six Countries with Special Focus on Pakistan: Applying Grey Incidence Analysis Model

Aim of the study is to appraise women development in selected thirty-six countries with special reference to Pakistan. The design of the study comprises of survey of literature, data elicitation and analysis. The study uses grey incidence analysis model (usually known as Grey Relational Analysis or simply GRA). The model has been applied on the secondary data extracted from the website of World Development Indicators (WDI). The countries included in the analysis have been selected on the basis of availability of data. From the result of GRA it can be learnt that thirty-six countries of the world are classified into seven different categories. There are five countries (namely Estonia, Hungary, Slovak Republic, Thailand and Ecuador) categorized as countries having exceptionally high women development, whereas, five countries under each next ensign (very high, high, moderate, low and very low). There are six countries (namely Tanzania, Madagascar, Cote d'Ivoire, Pakistan, Nigeria and Afghanistan) categorized under the ensign of exceptionally low. Pakistan fall under the ensign of exceptionally low. This study is designed on an original country level data extracted from very reliable source and the results of the study are useful for regulators, researchers, NGOs and other stakeholders of the phenomenon by way of providing deeper and new information.