This study aims to explore the application of financial supply chain management on agricultural product trade, and an example simulation case that Thai durian exports to China. After collection of variables and relationships in previous literature, a model of durian trade supply chain with material flow and cash flow has been created. As a result of the simulation, we found that cash flows of downstream participants are strongly higher than the upstream, which is partly proving that the downstream participants have more opportunities to invest upstream for intervention. Besides, we suggest government agencies, business sector, and financial institutions should strengthen communication and cooperation to maintain stability of current Thai durian trade supply chain, meanwhile, remain on high alertness to postharvest, delivery delays and durian demand to prevent the impact of supply chain disruption on cash flow.

Micro, small, and medium-sized enterprises (MSMEs) are important in driving a country’s economy and cover the entire manufacturing sector. Therefore, entrepreneurs with specific characteristics are needed for MSMEs to be successful. This study analyzed the exploratory components of entrepreneur characteristics in sustainably successful MSMEs. Data from interviewing 500 entrepreneurs who successfully operated MSMEs were analyzed using descriptive, referential, and multivariate statistics. Analysis of the entrepreneur characteristics’ exploratory components revealed that their Kaiser-Meyer-Olkin index was 0.969, and eigenvalues after axis rotation were 6.545–8.899. Four components were extracted: leadership, personality, management skills, and morality/ethics. Entrepreneurs’ characteristics in sustainably successful MSMEs include the ability to prioritize tasks appropriately, punctuality, people management skills, consideration of non-violation of rights, and non-imitation of others.

Gas Metal Arc Welding (GMAW) is an extensively implemented arc welding process through the control of input process parameters and the metal from the filler wire. Despite its popular use in various industries, the complex interrelationship between the actual bead and the varying welding parameters makes it challenging to predict appropriate bead geometries via mathematical modeling in a continually changing welding process. In this study, the Regression Learner App was used to compare the performance of supervised Machine Learning (ML) predictive models comprising the Linear Regression (LR), Regression Tree (RT), Support Vector Machine (SVM), Ensembles of Tree (ET), Gaussian Process Regression (GPR), and Artificial Neural Network (ANN) using GMAW dataset. The dataset was scaled and normalized at a range of -1 to +1 to facilitate the visualization of the variation effect. The wire feed speed, voltage, weld velocity, unmelted wire length, and melted wire volume were considered as the input parameters to predict the bead geometry. In addition, the five-fold cross-validation was employed to avoid overfitting and poor generalization. Finally, statistical indicators, namely the Coefficient of Determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), were performed on all developed models to evaluate their performance. Thus, the fine tree and ANN models achieved the highest prediction accuracies of 88–91%, signifying their potential use in future research. In short, the present study demonstrated the performance of various supervised ML algorithms for bead geometry prediction, which would assist the selection of appropriately supervised ML algorithms in future studies.

This paper introduces a covering model for collaborative bidirectional multi-period vehicle routing problems under profit-sharing agreements (CB-VRPPA) in bulk transportation (BT) networks involving one control tower and multiple shippers and carriers. The objective is to maximize the total profits of all parties subject to profit allocation constraints among carriers, terminal capability limitations, transport capability limitations and time-window constraints. The proposed method includes three stages: (a) generate all feasible routes of each carrier, (b) eliminate unattractive feasible routes via a proposed screening technique to reduce the initial problem size, and (c) solve the reduced problem using a branch-and-bound algorithm. Computational experiments are performed for real-life, medium- and large-scale instances. The proposed method provides satisfactory results when applied to solve the CB-VRPPA. We also conduct a sensitivity analysis on a critical parameter of the profit-sharing agreement to confirm the effectiveness of the proposed method.

On average, Guangxi experiences 2 severe tropical cyclone disasters yearly. A large number of disaster victims need governments at all levels to raise enough emergency supplies to carry out effective relief. However, there is no proper reserve center for tropical cyclone disaster storage and collection of emergency supplies in Guangxi, so it is urgent to choose a suitable location to build the Guangxi tropical cyclone disaster emergency supplies reserve center. The data of 16 severe tropical cyclone disasters and rescues in Guangxi from 2014 to 2021 were collected. An optimal location model of the emergency supplies reserve center for tropical cyclone disasters in Guangxi was established using the improved center of gravity method based on GIS. After four iterations of calculation, the longitude and latitude coordinate S5(108.64, 21.98) were used as a suitable site to construct the Guangxi Tropical Cyclone Disaster Emergency Supplies Reserve Center to ensure the fastest and lowest cost delivery of emergency supplies to the disaster areas in Guangxi. According to the map of Tiandi, the actual place corresponding to this coordinate is near Liuwu Village next to Qinzhou East Railway Station, Qinnan District, Qinzhou, Guangxi. This location coordinate S5 can provide a reference for the Guangxi Zhuang Autonomous Region government to select a suitable address to construct the Guangxi Tropical Cyclone Disaster Emergency Supplies Reserve Center. The improved center of gravity location model based on GIS can also provide a reference for other provinces or cities to carry out emergency supplies reserve center locations.

This research aimed to study the antecedents and consequences of brand coolness for fashion clothing brands in the millennial consumer context. The data was collected through an online questionnaire on 380 consumers who used to buy brand-name fashion clothing. The data were analyzed using the structural equation model. The results showed that the antecedents of brand coolness consisted of brand experience and brand identification, both of which positively influence brand coolness. Brand coolness (i.e., reference, singular, personal, esthetic, functional, energetic, and high status) was the key driver that creates brand equity. The research results were able to explain 94% of the variance in brand coolness and 81% of the variance in brand equity. This research is empirical support that helps expand the perspective on brand coolness and presents a dimension to measure brand coolness in a more transparent and complete method. The research result also complements the marketing knowledge that can guide academics and practitioners in creating substantial brand equity in the customers' hearts.

Smart farming is a feasible solution to help farmers effectively and sustainably manage the potential threats and risks those traditional farmers face, such as product quality, increased production costs, the environment, climate change, natural catastrophes, pests, and inferior goods. Using a survey research design, this research examined smart farming adoption and risk management models by combining the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT). The research sampled 400 farmers who are members of community enterprises in the northeastern region of Thailand. Data was collected using a questionnaire and analyzed using a statistical package program in four steps: confirmatory factor analysis, path analysis, structural equation model analysis (SEM), and Sobel's test. The findings revealed that government support variables had the most significant influence by adopting smart farming to risk management. Based on the research results, the government can apply this model to create strategies to encourage farmers to adopt smart farming and increase the production efficiency of agricultural products. The farmer can manage the risks of smart farming, which leads to sustainable smart farming and is useful for further academic acceptance and risk management studies. Furthermore, this study contributes to the existing literature on combining TAM and IDT in model adoption and risk management. The limitations include the small sample size adopted and the limited coverage area for the study, which restricts the generalization of the findings. However, the findings offer a glimpse into the benefits of smart farming.

The objective of this study was to examine the role of Industry 4.0 in the sustainable supply chain (SSC). The relationship between Industry 4.0, data storage, data assessment, performance evaluation, data inquiry and SSC were examined. To achieve the study objective, the mediation effect of data storage, data assessment, performance evaluation and data inquiry between Industry 4.0 and SSC was examined. Employees of textile companies were selected for data collection in Indonesia. Results of the study highlighted that Industry 4.0 had a significant positive effect on SSC. Better implementation of Industry 4.0 showed a positive effect on SSC. In addition to this, Industry 4.0 had a positive effect on data storage, data assessment, performance evaluation and data inquiry. Finally, data storage, data assessment, performance evaluation and data inquiry had a positive effect on SSC.

This research aimed to study the approach of the community toward the decision to grow rice and economic crops, including appropriate resource allocation for use on a farm under a large plot agricultural system. The study areas were in Phan district, Chiang Rai province, Thailand, and the data were collected from a sampling of 400 field agriculturalists. The method used was to develop a mathematical model for growing crops with multi-objectives and in multi-periods, together with an agriculturist representative and experts in multiple-criteria decision-making (MCDM). This was to prioritize the importance of alternative crops and find the appropriate allocation of the resources to achieve the targeted goal. The results showed that agriculturists prioritized most toward the criteria for growing Japanese rice with a weight of 0.179 Kg., followed by transplanted rice, transplanted glutinous rice, garlic, sown paddy rice, and sown glutinous paddy rice, respectively. The study’s results also showed that the price fluctuation of the crop products resulted in more use of land and labor in order to increase the production to compensate for the low price, and this also resulted in the higher opportunity cost of growing transplanted rice. Therefore, growing transplanted rice during in season planting was considered the most effective way, while during the off season, either garlic or Japanese rice could be grown. A collective pattern for planning for using resources together in large plot agricultural areas, together with a clear marketing target would bring about effective use of the resources and reduce the risk in revenue from the fluctuation in prices and uncertainty of yields from drought. Moreover, technology development to solve the problem of the lack of labor would be deemed an important approach toward the enhancement of the competitiveness of agriculturists in the future as well.

Red jasmine rice is recognized as a healthy food with high phenolic compounds. These compounds present antibacterial and anti-free radical properties. Moreover, colored rice exhibits a biological activity against anticancer. Objectives of this study are 1) exploring a biological screening and cell viability of 70% ethanol and aqueous extracts of red jasmine rice, 2) investigating cytotoxicity to fibroblast NIH3T3 (IC80) that is one hundred cells were found cell viability 80 cells. Red jasmine rice extracts were dried and transformed into a powder using the freeze-drying method. The extracts were treated with fibroblast NIH3T3 for MTT. The highest of IC50 of red jasmine rice extract to scavenge the DPPH and ABTS radicals was found in ethanol extract (53.20±7.37 and 64.17±5.76, respectively). The experiment showed that the ethanol and aqueous extract of red rice did not show cytotoxicity to fibroblast NIH3T3 (IC80). The extracts of red rice show the biological screening of anti-oxidation with total phenolic compounds and flavonoid contents. Moreover, it does not modify the physical properties of the cream formula. It can be concluded that the red rice extract is highly promising for the value addition.