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An integrated AHP-TOPSIS approach for bamboo product evaluation and selection in rural communities
(2024-09-01)
Chanpuypetch, Wirachchaya
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Niemsakul, Jirawan
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Atthirawong, Walailak
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Supeekit, Tuangyot
This study introduces a decision support model integrating the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select an economic tree product champion (bamboo) to benefit rural communities. An extensive literature review and expert discussions identified sixteen sub-criteria distributed across five main criteria. The study proposes four categories of bamboo products as alternatives, emphasizing community-level production capacity. The AHP determines priority weights, while TOPSIS prioritizes alternatives conducive to becoming the product champion within a community case study. The findings affirm the efficacy of Multi-Criteria Decision-Making (MCDM) in identifying a champion, with “Value addition potential,” “Domestic market demand,” and “International market (export) demand” identified as pivotal criteria. Bamboo culm-based products for energy-related applications emerged as the chosen product champion in a community case study in Thailand. This study offers practical implications for rural communities and potential investors in economic tree ventures, allowing the customization of decision criteria and alternatives for specific contexts. Socially, the focus on bamboo highlights diverse benefits along the entire supply chain, from upstream to downstream. The research pioneers a decision support model, providing insights into market opportunity analysis and supply chain network design based on the selected product champion.
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Assessment of Potential Area for Solar Energy Investment in Northeastern Thailand by Entropy-TOPSIS Method
(2024-01-01)
Phonphoon, Phichata
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Kiatcharoenpol, Tossapol
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Klongboonjit, Sakon
Agriculture is one of the important engines of Thailand's food industrial growth however the cost of fossil energy is quite high for Thai farmers. Since Thailand has great solar potential, especially northeastern region, renewable energy sources of sunlight in this region should be considered to be another energy source for Thai agriculture. To assess and classify the potential of the investment in agricultural solar power systems of 20 provinces in Thailand's northeastern region, this study applied the combining method of Entropy Weight Method and TOPSIS with secondary data of solar irradiance, farmer household density, and income of farmer households. With this combining method, the results showed that farmer household density and income of farmer household were more influence on assessing and classifying the potential of this investment than solar irradiance. Finally, all 20 provinces were classified into four groups of Group A (A<inf>12</inf>, A<inf>2</inf>, A<inf>4</inf>, A<inf>1</inf>, and A<inf>10</inf>), Group B (A<inf>8</inf>, A<inf>9</inf>, A<inf>19</inf>, A<inf>3</inf>, and A<inf>15</inf>)), Group C (A<inf>17</inf>, A<inf>13</inf>, A<inf>18</inf> A<inf>16</inf>, and A<inf>20</inf>) and Group D (A<inf>6</inf>, A<inf>11</inf>, A<inf>7</inf>, A<inf>14</inf>, and A<inf>5</inf>) from the most potential province group for investment in agriculture solar power system to the least potential province group for investment in agriculture solar power system.
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Priority of Wind Energy in West Coast of Southern Thailand for Installing the Water Pumping Windmill System with Combining of Entropy Weight Method and TOPSIS
(2023-10-01)
Klongboonjit, Sakon
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Kiatcharoenpol, Tossapol
Wind energy potential or quality serve as the primary determinants influencing the decisions of Thai farmers regarding the installation of water-pumping windmills with heights ranging from 9 to 15 m and a cut-in wind speed requirement of 4 m/s, aimed at reducing their fuel costs. To introduce a simplified calculation method as one of their decision-making tools, the combined approach of the entropy weight method with TOPSIS has been introduced to assist them in prioritizing and assessing the wind quality in their respective areas. This study focuses on the western region of Southern Thailand, known for its high agricultural productivity. Initially, only 18 out of the 227 sub-districts with a minimum monthly wind speed exceeding 4 m/s were selected for thorough investigation. Subsequently, the entropy weight method was applied to the monthly wind speed data of these 18 chosen sub-districts to calculate their monthly weight values. These monthly weight values provide a quantifiable characterization of the wind quality in these specific sub-districts, revealing variations in wind quality between seasons, with superior quality during the summer season compared to the rainy season. Following the calculation of monthly weight values, the TOPSIS technique was applied to the wind data in conjunction with these monthly weight values, resulting in the determination of performance scores (P<inf>i</inf>) for each of the 18 sub-districts. P<inf>i</inf> values were found to vary from 0.0641 to 0.9006. In the final step of the analysis, these 18 sub-districts were ranked based on their respective P<inf>i</inf> values, with the implication that sub-districts exhibiting higher P<inf>i</inf> values are more suitable for the installation of water-pumping windmills with heights ranging from 9 to 15 m compared to those with lower P<inf>i</inf> values.
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An Integrated Factor Analysis-Technique for Order Preference by Similarity to Ideal Solution for Location Decision in ASEAN Region: A Case Study of Thai Fabric Manufacturing Plant
(2023-01-01)
Atthirawong, Walailak
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Panprung, Wariya
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Wanitjirattikal, Puntipa
In this paper, we propose an integrated model for selecting a suitable location for fabric manufacturing plants in the ASEAN region. In the first phase, Cambodia, Vietnam and Indonesia were determined as candidate locations for evaluation from the screening process. In this regard, key criteria influencing location decisions were derived using factor analysis of responses extracted from questionnaires. In the second phase, criterion weights were calculated using the rank of centroid (ROC) method. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was then used to prioritize three location alternatives, and sensitivity analysis was also employed to verify the stability of the method. Based on TOPSIS method, Vietnam was the preferred location, followed by Indonesia while Cambodia was not recommended. Sensitivity analysis also showed that the proposed model was valid. The findings from this study provided references for enterprises engaged in international location decision making. The results can help them better understand the decision-making process and identify key criteria that can influence location decisions internationally.
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A conceptual framework of an integrated fuzzy ANP and TOPSIS for supplier selection based on supply chain risk management
(2014-11-18)
Sinrat, Sittichok
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Atthirawong, Walailak
Currently, many companies require agility in supply chains to manage disruption risks. Supplier selection is one of the most important decisions for the success of firms. It is the first step of the activities in the product realization process starts from the purchase of materials for production and then delivery products to end customers. The objective of this research is to develop a conceptual framework model for supplier evaluation based on an integrated of the fuzzy analytic network process (FANP) model and technique for order performance by similarity to ideal solution (TOPSIS), which incorporates the procurement risk, production risk, deliver risk, and environment risks. The proposed model will be later implemented in a manufacturing firm to priority weight factor and will be presented in a due course.

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