Affiliations: [a] Department of Sociology, Kohat University of Science and Technology, Kohat, Pakistan
| [b] Institute of Mathematics, Khawaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan
| [c] Department of Mathematics, Faculty of Arts and Science, Near East University, Cyprus, Turkey
| [d] Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon
| [e] Applied College, Khamis Mushait, King Khalid University, Abha, Saudi Arabia
Correspondence:
[*]
Corresponding author. Shahzaib Ashraf, Institute of Mathematics, Khawaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan. E-mail: [email protected].
Abstract: Achieving household food security is the tumbling issue of the century. This article explores the factors affecting household food security and solutions by utilizing a synergy of statistical and mathematical models. The methodology section is divided into two portions namely sociological and mathematical methods. Sociologically, 379 household heads were interviewed through structured questions and further analyzed in terms of descriptive and binary logistic regression. The study found that 4 independent variables (poverty, poor governance, militancy, and social stratification) showed a significant association (P = 0.000) to explain variations in the dependent variable (household FS). The Omnibus test value (χ2= 102.386; P = 0.000) demonstrated that the test for the entire model against constant was statistically significant. Therefore, the set of predictor variables could better distinguish the variation in household FS. The Nagelkerke’s R Square (R2 = .333) helps to interpret that the prediction variable and the group variables had a strong relationship. Moreover, 23% to 33% variation in FS was explained by the grouping variables (Cox and Snell R2 = 0.237 and Nagelkerke’s R2 = 0.333). The significant value of Wald test results for each variable confirmed that the grouping variables (poor governance P = 0.004, militancy P = 0.000, social stratification P = 0.021 and poverty P = 0.000) significantly predicted FS at the household level. Mathematically, all the statistics were validated further through the application of spherical fuzzy mathematics (TOPIS and MADM) to explore what factors are affecting household FS. Thus, the study found that F3 (poverty) > F2 (militancy) > F4 (social stratification) > F1 (poor governance) respectively. Thus, it could be concluded from these findings that the prevalence of poverty dysfunctional all the channels of household FS at the macro and micro levels. Therefore, a sound and workable model to eradicate poverty in the study area by ensuring social safety nets for the locals was put forward some of the policy implications for the government are the order of the day.
Keywords: Food security, militancy, poor governance, social stratification, poverty, logistic regression, TOPIS, MADM, spherical fuzzy set
