Assessment of factors affecting the price fluctuations of selected vegetables to market retailers in Cavite / by Jerome R. Fernandez and Arvie E. Vargas.

By:

Fernandez, Jerome R [author]

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Material type: Text

TextLanguage: English Publication details: Indang, Cavite, Cavite State University- Main Campus, 2022.Description: xvii, 116 pages : illustrations ; 28 cmContent type:

text

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unmediated

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volume

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DDC classification:

338.5 F39 2022

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College of Engineering and Information Technology (CEIT)

Abstract: FERNANDEZ, JEROME R. and VARGAS, ARVIE E., Assessment of Factors Affecting the Price Fluctuations of Selected Vegetables to Market Retailers in Cavite. Undergraduate Thesis. Bachelor of Science in Industrial Engineering. Cavite State University, Indang Cavite. June 2022. Adviser: Ms. Mary Joyce P. Alcazar. This study was conducted to assess the factors that affect the price fluctuations of the selected vegetables to retail markets in Cavite. Specifically, the study aimed to: (1) identify the retail prices of chayote, corn, squash and eggplant in Cavite from year 2015 to 2020; (2) assess the behavior of these vegetable prices by the use of time series analysis; (3) determine which among the factor/s - production volume, average temperature, total rainfall, price of diesel, import growth and change in CPI of vegetables, affect/s the prices of chayote, corn squash and eggplant; (4) determine the relationship between the factors and the prices of vegetables; and (5) develop a framework that depicts the relationship of the factors and price of vegetables. Data of the dependent and independent variables were gathered from online databases of PSA, PAGASA and Trend Economy. Following the objectives of the study, these gathered data were then processed on different statistical tools and analyses using time series analysis, multicollinearity test, correlation analysis, regression equation modelling like the multicollinearity and elastic net regression and lastly, forecasting. As the results were summarized, it revealed that only a portion of variance of the price of corn and eggplant is explained by the selected factors in the equation model. However, regardless of the accuracy of the MAPE score obtained and due to the computed r squared and adjusted r squared it is concluded that there are still numerous factors that could explain the remaining variance of the retail price of the vegetables. Hence, future researchers were recommended to use artificial neural networks that is suitable in explaining even the most complex patterns and variation in a data set.

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Item type	Current library	Collection	Call number	Materials specified	URL	Status	Notes	Date due	Barcode
Theses / Manuscripts	Ladislao N. Diwa Memorial Library Theses Section	Non-fiction	338.5 F39 2022 (Browse shelf(Opens below))		Link to resource	Room use only	T-9123		00082000

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Thesis (Bachelor of Science in Industrial Engineering) Cavite State University

Includes bibliographical references.

College of Engineering and Information Technology (CEIT)

FERNANDEZ, JEROME R. and VARGAS, ARVIE E., Assessment of Factors Affecting the Price Fluctuations of Selected Vegetables to Market Retailers in Cavite. Undergraduate Thesis. Bachelor of Science in Industrial Engineering. Cavite State University, Indang Cavite. June 2022. Adviser: Ms. Mary Joyce P. Alcazar.

This study was conducted to assess the factors that affect the price fluctuations of the selected vegetables to retail markets in Cavite. Specifically, the study aimed to: (1) identify the retail prices of chayote, corn, squash and eggplant in Cavite from year 2015 to 2020; (2) assess the behavior of these vegetable prices by the use of time series analysis; (3) determine which among the factor/s - production volume, average temperature, total rainfall, price of diesel, import growth and change in CPI of vegetables, affect/s the prices of chayote, corn squash and eggplant; (4) determine the relationship between the factors and the prices of vegetables; and (5) develop a framework that depicts the relationship of the factors and price of vegetables. Data of the dependent and independent variables were gathered from online databases of PSA, PAGASA and Trend Economy. Following the objectives of the study, these gathered data were then processed on different statistical tools and analyses using time series analysis, multicollinearity test, correlation analysis, regression equation modelling like the multicollinearity and elastic net regression and lastly, forecasting. As the results were summarized, it revealed that only a portion of variance of the price of corn and eggplant is explained by the selected factors in the equation model. However, regardless of the accuracy of the MAPE score obtained and due to the computed r squared and adjusted r squared it is concluded that there are still numerous factors that could explain the remaining variance of the retail price of the vegetables. Hence, future researchers were recommended to use artificial neural networks that is suitable in explaining even the most complex patterns and variation in a data set.

Submitted copy to the University Library. 08/08/2022 T-9123

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