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Cost-efficient food loss and waste management using the FANP analysis
(2026-01-01)
Krommuang, Apiwat
;
Suwunnamek, Opal
;
Buachoom, Wonlop Writthym
This study proposes a structured cost-efficiency framework for managing food loss and waste in the frozen food industry by integrating supply chain analysis with responsibility-based cost concepts. Data collected from key industry stakeholders were used to identify critical factors contributing to food loss and waste across the frozen food supply chain. The fuzzy analytic network process (FANP) incorporated with cost analysis was employed to prioritize these interdependent factors. The results from the FANP show that suppliers and farms, followed by handling and storage. The cost responsibility analysis reveal that 85.47% of total food loss and waste-related costs are controllable, while the weighted cost impact analysis, captures the interaction between factor importance and cost proportion, indicates that factors with the highest weighted cost impacts are predominantly concentrated at the supplier and farm stage. The findings provide clear managerial guidance by identifying priority intervention areas where cost reductions can be achieved most effectively. This study contributes to the literature by linking food loss and waste drivers with controllable cost structures and by demonstrating how FANP can be applied to support cost-efficient and targeted improvement strategies in frozen food supply chains, particularly in emerging food-exporting economies such as Thailand.
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Development of a Causal Model of Post-Millennials’ Willingness to Disclose Information to Online Fashion Businesses (Thailand)
(2024-01-01)
Krommuang, Apiwat
;
Kasisuwan, Jinnawat
This research examines the causal factors influencing the willingness of Central Post-Millennials to disclose information to online fashion businesses by using privacy calculus theory as the basic principle for modeling. The study has three primary objectives: (1) to investigate the causal factors influencing willingness to disclose information, (2) to analyze both the direct and indirect effects of perceived risk, perceived benefit, perceived value, perceived control over the use of personalization data, and trust on the willingness to disclose information, and (3) to develop a causal factor model for understanding the determinants of willingness to disclose information among Central Post-Millennials in the context of online fashion businesses. The research sample consists of 385 individuals, and data were collected using a structured questionnaire. Descriptive and inferential statistical methods were employed for data analysis. The relationships between variables were assessed using Pearson's Correlation Coefficient. The model's fit to the empirical data was evaluated using goodness-of-fit measures, and the transmission of influence was tested through structural equation modeling (SEM). The findings reveal that demographic factors do not significantly affect the willingness to disclose information. However, the study identifies perceived risk, perceived benefit, perceived value, perceived control over the use of personalization data, and trust as key determinants of willingness to disclose information to online fashion businesses. Among these, perceived control exhibits the strongest influence, closely followed by trust. These results highlight the antecedent processes influencing the willingness to disclose information, as represented by a model developed from a comprehensive literature review and empirically tested for consistency with the data.
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Internet of Things (IoT) Application for Management in Automotive Parts Manufacturing
(2022-01-01)
Krommuang, Apiwat
;
Suwunnamek, Opal
Automotive parts manufacturing focuses on sustainable development manufacturing capabilities with future technology changes. Internet of Things (IoT) plays an important role in applying internet technology to machines and equipment in manufacturing processes for transformation towards Industry 4.0 as well as creating values added and higher competitive advantage for the sustainability of the industries. This research aims to study factors that influence decision-makers in selecting IoT applications for managing auto parts production and they consist of connectivity, telepresence, intelligence, security, and value including their fifteen sub-factors. In this research, The Fuzzy Analytic Network Process (FANP) is a Multiple Criteria Decision Making (MCDM) technique used to analyze, identify, and prioritize factors in selecting IoT applications for managing production processes. The questionnaire is designed based on the FANP technique to survey the importance of weight for each factor from executives of 88 auto parts manufacturers who authorize as the decision-makers for selecting IoT applications. The results have indicated that telepresence is the most important factor that will assist them in controlling production to guarantee that production capabilities meet the objective and connectivity is the second important factor that must ensure that IoT applications are compatible with their machinery and equipment can be controlled smoothly and precisely. Meanwhile, performance is the most important sub-factor and other subfactors are ranked as functional orientation, data management, control, and compatibility respectively. Therefore, manufacturers can use this research as a criterion for selecting appropriate IoT applications for controlling their manufacturing for sustainable effectiveness.
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Prioritizing the Factors Affecting the Application of Industry 4.0 Technology in Electrical Appliance Manufacturing using a Fuzzy Analytical Network Process Approach
(2022-01-01)
Krommuang, Apiwat
;
Krommuang, Atchari
The fourth industrial revolution is a technological advancement that is posing new challenges in manufacturing and services. Industries must adopt innovations to create value-added for their products and services to gain a competitive advantage and increase production efficiency. Therefore, this research aims to study the factors that influence the application of Industry 4.0 technology for managing electrical appliance production by focusing on five major factors: the internet of things, cloud manufacturing, big data analytics, additive manufacturing, and cyber-physical systems, which can be further subdivided into 23 sub-factors. The fuzzy analytic network process (FANP) technique is used to prioritize the factors to develop criteria for selecting appropriate applications of Industry 4.0 technology in manufacturing. Besides, a questionnaire based on the FANP approach is used to collect data from 82 electrical appliance manufacturers to calculate the weight of each factor. Consequently, the Internet of Things is ranked first, followed by big data analytics and additive manufacturing. While the results have indicated the importance of sub-factors as data-driven, data collection, tracking, monitoring, and automation, respectively. The benefit of this research is that manufacturers of electrical appliances can use this research as a criterion for implementing Industry 4.0 technology for long-term effectiveness
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Structural equation modeling of supply chain management, employee involvement, and employee work performance in thailand's auto parts industry
(2021-12-01)
Krommuang, Apiwat
;
Suwunnamek, Opal
The objective of this research was to analyse the structural equation modelling (SEM) of supply chain management, employee involvement, and employee work performance in Thailand's auto parts industry. The sample group included 383 employees operating in the aforementioned industry using SEM processing by the AMOS program as the tool. From the research, the latent variable of supply chain management had a direct positive influence on the latency of employee involvement and employee work performance with statistical significance. Simultaneously, the latency of employee involvement had no direct positive influence on the latency of employee work performance. Therefore, the latency of supply chain management did not indirectly influence the latency of employee work performance through the latency of employee involvement.
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How job characteristics and employee involvement affect sustainable quality management practices in the Thai food industry
(2015-01-01)
Krommuang, Apiwat
;
Suwunnamek, Opal
This study investigated which employee-related factors affect the application of quality management practices, and the characteristics and dynamics of the relationship between them. This will help business organisations select and design their operating system for their employees. This study used a sample of 271 middle level executives from 74 companies operating in the Thai food industry. The structural equation modelling (SEM) was used to analyse results. Results showed that job characteristics had a positive effect on the application of quality management practices through significant development of employee involvement.
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How organizational characteristics and employee involvement affect quality management practices in the Thai food industry
(2014-01-01)
Krommuang, Apiwat
;
Suwunnamek, Opal
Quality management practices can help an organization thrive in an increasingly competitive global market. Based on a comprehensive literature review, this study identifies organizational characteristics that encourage employee involvement and improve quality management practices. The sample group was comprised of 271 people representing middle management in Thailand's food industry. The variables of employee involvement were intervening latent variables in the relationship. Structural Equation Modeling (SEM) was used to analyse the results which showed that fewer hierarchies of command and decentralized decision making power had a significantly positive affect on quality management practices in organizations. © 2014 Academic Journals Inc.

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