Journal of Applied Statistics and Information Technology

Economic Factors Affecting the Industry Group Index and Business Sector Index of the Stock Exchange of Thailand

Pimmada Klaynarong — 2024-12-24

The purpose of this research is to examine the economic factors affecting The Stock Exchange of Thailand’s industry group index and sector index. The economic factors include the price of gold (GOLD), the price of crude oil (OIL), the Thai Baht to United States Dollar exchange rate (THB_USD), the consumer price index (CPI), and the rate of interest of the Bank of Thailand (RATE). The study was conducted using monthly data from January 2018 to December 2023, totaling 72 months. Data were divided into three sets: 1) before the Covid-19 outbreak of 2018, 2) during the Covid-19 outbreak of 2020, and 3) after the Covid-19 outbreak of 2022 - 2023, using multiple regression analysis based on generalized least squares. A significance level of 0.05 indicated that both the consumer price index (CPI) and the Thai Baht to United States Dollar exchange rate (THB_USD) were significantly related to the prices of industrial groups and business categories prior and after the outbreaks of COVID-19. In the event of a COVID-19 outbreak, the price of crude oil (OIL), the Thai Baht to United States Dollar exchange rate (THB_USD), and the rate of interest of the Bank of Thailand (RATE) will affect the price index of industry groups and business sectors.

Factors affecting perceived learning in asynchronous online foreign language courses

Phanurut Peammetta — 2024-12-25

As the world becomes increasingly interconnected, the demand for asynchronous online language learning has surged, highlighting the need for engaging and effective instructional design in this area. Online educators are challenged to meet diverse learner needs and optimize learning outcomes in asynchronous environments. Learners face various challenges, such as limited real-time interaction, which can lead to feelings of isolation and delays in feedback. Additionally, learners must develop strong self-discipline and time management skills. Other complicating factors include technology accessibility, cultural and linguistic barriers, and maintaining motivation throughout the learning process.

To address these issues, it is essential to examine factors like online learner motivation and other determinants of learning outcomes. This study, drawing on Garrison, Anderson, and Archer’s Community of Inquiry (CoI) framework and Deci and Ryan’s intrinsic motivation theory, proposed and tested a model of perceived learning in online language courses. Data were collected from 140 learners with prior experience in asynchronous courses through an online questionnaire and analyzed using Structural Equation Modeling to test hypotheses and assess model fit. The results demonstrated that the model had an excellent fit (p-value = 1.000, SRMR = 0.0680, CFI = 1.0000, GFI = 0.977, RMSEA = 0.00004).

The findings supported the mediating effect of the CoI framework's three interactions -- social presence, cognitive presence, and teaching presence -- on perceived learning through intrinsic motivation. These interactions, when mediated by intrinsic motivation, positively influenced perceived learning, though they did not directly predict learning outcomes. This study suggests a new model for developing effective asynchronous online language courses and recommends further research to explore additional constructs and refine this model.

The design of the layout and placement of goods within an automotive spare parts warehouse

Sakarn Jaisai — 2024-12-25

This research aims to investigate the methods of product assignment to design an optimal layout and storage location of automotive spare parts in a warehouse. The objective is to reduce the travelling distance of pickers during the picking process. This study compares three models: 1) Class-based ABC layout, which groups products by picking frequency; 2) Optimal-based layout, which uses linear programming, so-called, Storage Location Assignment Problem to determine optimal storage locations; and 3) Association-based layout, which utilizes association rules to design the warehouse layout with the idea that the products that usually pick together must place close to each other. The results indicate that the layout utilizing Association Rules in conjunction with ABC classification is the most suitable, as it minimizes the walking distance for pickers.

Exploring the Use of Real-Time Location Systems (RTLS) to Improve Warehouse Management

Chanin Kansith — 2024-12-25

This research investigates the application of Real-Time Location System (RTLS) technology for enhancing warehouse management efficiency. The study was conducted in two phases. The first is Experimental Design and Data Collection within a Smart Logistics Laboratory: Various scenarios were simulated to assess the impact of RTLS on congestion patterns. The collected data was subsequently analyzed and utilized to improve workflow through simulations incorporating the Traveling Salesman Problem (TSP) Strategy model. The second is Queuing Analysis and Layout Optimization. It proposes to identify Bottlenecks within the warehouse were identified through queuing analysis, and warehouse layouts were redesigned to optimize operational processes. The results of the experiment demonstrate the efficacy of applying RTLS data to significantly improve warehouse management efficiency. For instance, the analysis of RTLS data facilitated the identification of congestion issues, which led to the development of multiple scenario simulations and the implementation of efficient space utilization strategies. Additionally, the acquired data was utilized in simulations to ascertain optimal solutions for enhancing warehouse workflow. A primary limitation of this research was the constraint imposed by limited space. Consequently, future research should consider utilizing actual warehouse spaces and processes to thoroughly evaluate the potential benefits of RTLS implementation.