Production Risk with Feasible Generalized Least Square

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dc.authorscopusid47561286600
dc.authorscopusid57210010318
dc.authorscopusid24481107300
dc.contributor.authorFerdushi, Kanis Fatama
dc.contributor.authorHossain, Md Kamrul
dc.contributor.authorKamil, Anton Abdulbasah
dc.date.accessioned2024-09-11T19:57:58Z
dc.date.available2024-09-11T19:57:58Z
dc.date.issued2020
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description1st International Conference on Advanced Information Scientific Development, ICAISD 2020 -- 6 August 2020 through 7 August 2020 -- Bekasi, West Java -- 165144en_US
dc.description.abstractThis study investigates production risk. A multistage stratified random sampling technique wasadopted to select sampling unit. In between Cobb Douglas and Linear quadratic model, the linear quadratic model had been picked through feasible generalized least square method. The numerical model, we utilize the information from rice cultivating in Bangladesh. The results show that uneven socioeconomic and farm-specific inputs are creating risk in rice production. Input variables such as area, labour, and fertilizer and managerial factors, for example, experience, schooling, contact with extension, training, natural calamity, member and status indicated a significant impact on rice productions uncertainty. This indicated that both input and managerial factors were important for the rice production. © 2020 Published under licence by IOP Publishing Ltd.en_US
dc.identifier.doi10.1088/1742-6596/1641/1/012109
dc.identifier.issn1742-6588en_US
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85097171049en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1088/1742-6596/1641/1/012109
dc.identifier.urihttps://hdl.handle.net/11363/8383
dc.identifier.volume1641en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIOP Publishing Ltden_US
dc.relation.ispartofJournal of Physics: Conference Seriesen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240903_Gen_US
dc.subjectCultivation; Managers; Personnel training; Generalized least square; Input variables; Linear-quadratic models; Managerial factors; Production risks; Rice production; Sampling units; Stratified random sampling; Least squares approximationsen_US
dc.titleProduction Risk with Feasible Generalized Least Squareen_US
dc.typeConference Objecten_US

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