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

Niazi, Abdul Aziz Khan; Qazi, Tehmina Fiaz; Basit, Abdul

doi:10.31703/grr.2021(vi-i).04

Cited by 3 publications

(1 citation statement)

References 52 publications

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“…An array of techniques of data analysis is considered, such as MABAC, COPRAS, MAIRCA, FUCOM, LBWA, TOPSIS, SWARA, VIKOR, GRA, AHP and so on. However, on the basis of simplicity, comprehensiveness and appropriateness, GRA is considered to be the most suitable technique to achieve the objectives of this study (Wu, 2002;Niazi et al, 2021a;Qazi et al, 2021a;. Asgharnezhad and Darestani (2022) applied Dempster-Shafer theory and grey relational analysis (GRA), and found that GRA is the more robust and more reliable technique of analysis.…”

Section: Introductionmentioning

confidence: 99%

Grey relational analysis of country-level entrepreneurial environment: A study of selected forty-eight countries

Zhu

Ubaidullah²,

Zhu³

et al. 2022

Front. Environ. Sci.

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The aim of this study is to evaluate the entrepreneurial environment of selected countries, and analyze and rank them on the basis of entrepreneurship related indicators. This study’s design comprises a review of the literature, extraction of secondary data on the phenomenon, and analysis. The research gap has been established through a review of the literature, leading toward the development of problem statement. The cross-sectional data, related to entrepreneurship indicators, is extracted from website of World Development Indicators (2021) for 48 selected countries. Using positivism as a research philosophy and deduction as a research approach, the data are analyzed through grey relational analysis (GRA). On the basis of grey relational grades, this study also classified the countries on the continuum of “much better” to “worse.” The results of the study show that the United States, United Kingdom, Japan, Australia, Hong Kong, France and Canada attained the highest grey relational grades and are considered the countries having much better entrepreneurial environment; whereas Poland, Kuwait, Namibia and so on attained the lowest grey relational grades and are considered the countries having worst entrepreneurial environment. This research has several practical implications for different economies/countries, entrepreneurial ventures, aspiring entrepreneurial, and researchers. On the basis of findings of this study, policy makers should refine country-level entrepreneurial policies while keeping in view the respective grey relational grades.

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Section: Introductionmentioning

confidence: 99%

Grey relational analysis of country-level entrepreneurial environment: A study of selected forty-eight countries

Zhu

Ubaidullah²,

Zhu³

et al. 2022

Front. Environ. Sci.

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Assessment of Agricultural Performance of Districts of Punjab Based On Composite Agricultural Indicators Using Grey Relational Analysis

Qazi

Niazi

Basit³

2021

GSSR

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The province of Punjab is considered the breadbasket of Pakistan. This study is aimed to evaluate and hierarchicalize the districts of Punjab based on agricultural indicators. It follows a ranking approach that uses secondary cross-sectional data obtained from Punjab Development Statistics 2016. This study has employed Grey System Theory and used GRA. It is a seminal study that uses a unique methodology that has integrated thirteen different indicators of agricultural development in one mathematical model and assigned a distinct composite grade to every district. Findings revealed that district Bahawalpur and Bahawalnagar have the highest Grey Relational Grade (GRG), hence depict the best agricultural performance in Punjab, whereas district Mianwali has the lowest GRG and accordingly least performance. This research provides insight to the policymakers, which will help them to take corrective measures and/or adjust the agricultural development policies

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Explicating the Causes of Frequent Floods in Pakistan: A Structural Modeling and Analysis

Qazi,

Niazi,

Aziz

et al. 2024

BBE

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Aim of study is explicating the causes of frequent floods in Pakistan. Overall design of the study comprises of relevant literature review, primary data collection and structural modelling & analysis of the phenomena. The method of modelling is ISM (Interpretive Structural Modeling) and method of analysis is MICMAC (cross impact matrix multiplication applied to classification). The population under study comprises the folk stakeholders of the phenomenon. The sampling design is purposive (i.e. a focus group consisting of a panel of experts) and the sample size is eleven experts (a medium-sized panel). Results of modeling show that causes namely: changes in land use, poor waste management, slums along rivers, erosion and sedimentation, improper flood control systems, river physiography, high rainfall, inadequate river capacity, water structures, land subsidence, damage to flood control structures, poor drainage system fall at Level I (the top level), therefore, are least critical. The causes namely: effects of high tides, lack of discipline among people, glacial melt fall at Level II (middle level) therefore are moderate critical. The cause namely: deforestation falls at Level III (the bottom level) therefore is the most critical. The scale-centric MICMAC analysis shows that all the causes are categorized in the linkage quadrant and the independent, dependent, and autonomous quadrants are empty. The data-centric MICMAC analysis shows that the effects of high tides, glacial melt, and deforestation fall in the independent quadrant. The erosion sedimentation and river physiography fall in the dependent quadrant. The changes in land use, poor waste management, improper flood control systems, slums along rivers, high rainfall, land subsidence, inadequate river capacity, water structures, lack of discipline among people, damage to flood control structures, and poor drainage system categorized in the linkage fall in the linkage quadrant, whereas, the autonomous quadrant is empty. The results of MICMAC analysis implicitly corroborate the results of modeling. It is an original valuable study because it is based on first-hand real experimental data collected by authors who have hands on job of data collection for decades. It also uses unique and different methodologies to collect data, perform modeling and analysis. This methodology is simple, unique, and understandable by a wide range of stakeholders. Its results are also logical and realistic that correspond to ground realities.

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

Cited by 3 publications

References 52 publications

Grey relational analysis of country-level entrepreneurial environment: A study of selected forty-eight countries

Grey relational analysis of country-level entrepreneurial environment: A study of selected forty-eight countries

Assessment of Agricultural Performance of Districts of Punjab Based On Composite Agricultural Indicators Using Grey Relational Analysis

Explicating the Causes of Frequent Floods in Pakistan: A Structural Modeling and Analysis

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