TITLE:
Classification of Briquettes Selection Criteria Using Principal Components Analysis Approach
AUTHORS:
Denis O. Kiobia, Yusto M. Yustas, Werenfrid M. Tarimo, Susan A. Mbacho, Nelson R. Makange, Avitus T. Kashaija, Erasto B. Mukama, Festo R. Silungwe
KEYWORDS:
Preference, Biomass, Environment, Charcoal, Wastes
JOURNAL NAME:
Journal of Power and Energy Engineering,
Vol.10 No.6,
June
29,
2022
ABSTRACT: The briquettes have the potential to reduce reliance
on charcoal and firewood while addressing employment issues for youths and
women through briquette-making value chain components. However, the marketing
that would increase the acceptance of the briquettes requires an essential
understanding of the briquettes’ critical selection criteria considered by
potential briquette users. This study assesses the classes of briquette energy
and their preferences. The study specifically investigated the following: 1) level of interest in briquette’s geometric shapes, 2) classes for briquette geometric shapes 3) class components leading to purchasing the briquettes. A baseline
survey was conducted, which included 330 households in the Morogoro district’s
urban, peri-urban, and rural communities. The study used a snowball technique
to meet with respondents, especially in families with youth and women. Securing
information in objectives one and two used the five Likert scales (Strongly
Agree, Agree, Neutral, Disagree, and strongly disagree). In contrast, objective
three utilized the five Likert scales of 1, 2, 3, 4, and 5 in the order of
importance. The Principal Component Analysis (PCA) method assisted in
classification and interpreting the motive behind preferences. The results
found that the motive behind the shape preferences was in two categories, each
including three principal components. The categories are 1) geometric shapes: round, long, and circular/plate forms, and 2) purchasing influences: performance, attractiveness, and personal capacity. Therefore, the briquettes with technically improved round shapes
produced based on the performance factors are recommended for adoption and
marketability.