Using Big Data Analytics to Forecast Trade Volumes in Global Supply Chain Management

As the supply chains become more global, the operations (such as procurement, production, warehousing, sales, and forecasting) must be managed with consideration of the global factors. International trade is one of these factors affecting the global supply chain operations. Estimating the future trade volumes of certain products for specific markets can help companies to adjust their own global supply chain operations and strategies. However, in today's competitive and complex global supply chain environments, making accurate forecasts has become significantly difficult. In this chapter, the authors present a novel big data analytics methodology to accurately forecast international trade volumes between countries for specific products. The methodology uses various open data sources and employs random forest and artificial neural networks. To demonstrate the effectiveness of their proposed methodology, the authors present a case study of forecasting the export volume of refrigerators and freezers from Turkey to United Kingdom. The results showed that the proposed methodology provides effective forecasts.

China’s Belt and Road Initiative with ASEAN Countries: Examining the Trade Cooperation and Impact of Coronavirus

The rising US–China tension in the global trade war increased the trade cooperation between China and the ASEAN. Consequently, China’s total import and export volume with ASEAN increased tremendously to 684.60 billion USD in 2020, up by 6.7% year on year. This trend is part of the Belt and Road Initiative (BRI) which promotes China’s infrastructure building program in the neighboring ASEAN countries and exports China’s technical know-how and engineering standards. However, the recent coronavirus outbreak that stormed China and the rest of the world caused delays to many BRI projects. Subsequently, this outbreak also hit the ASEAN countries and halted many of their mega-projects under the BRI framework. Thus, this study attempts to highlight the trade cooperation and project developments of BRI in the ASEAN countries. In addition, the study features the landscape of BRI projects that were affected by the coronavirus amongst the ASEAN countries.

Competitiveness and Determining Factors of Indonesian Tea Export Volume in the World Market

Indonesia is one of the world's tea exporters, but the decline in the volume and value of its exports to date continues to occur. This study aims to 1) analyze the production trend and export volume of Indonesian tea. 2) analyze Indonesian tea competitiveness in the International market compared to other exporter countries (China, India, Kenya, Sri Lanka, and Vietnam). 3) analyze the determining factors of Indonesia's tea export volume to 7 major destination countries (Malaysia, Russia, Pakistan, USA, Germany, Poland, and Australia). The analysis methods used are simple linear regression, Revealed Comparative Advantage (RCA), Trade Specialization Ratio (TSR), and data panel regression. The results showed that the production and volume of Indonesian tea export will decrease every year. Indonesian tea has a very strong comparative competitiveness, but still below India, Kenya, Sri Lanka, and Vietnam. Indonesia tends to be an exporter of tea to the international market at the stage of export expansion. Factors determining the volume of Indonesian export are Indonesian tea production, the population of importer countries, real GDP per capita of importer countries, level of trade openness of importer countries, and importer countries' inflation rate.

Competitiveness or complementarity: Analysis of agricultural trade between China and Brazil

The competitiveness and complementarity of trade reflect the advantages and disadvantages of exports and future trade trends. After China joined the WTO, the import and export volume of agricultural products has increased significantly, but the import volume and import growth rate have greatly exceeded the export volume and export growth rate. China is the world’s largest importer of agricultural products, and Brazil has become the world’s largest exporter of agricultural products. As a country with the largest increase in agricultural exports, China and Brazil have close agricultural trade exchanges. China has become Brazil’s largest importer of agricultural products for four consecutive years. In addition, both China and Brazil are BRIC countries; therefore, the establishment of a cooperation mechanism is more conducive to the development of agricultural trade. This study uses quantitative research methods to investigate the agricultural trade between China and Brazil by calculating the revealed comparative advantage index, trade complementarity index, and trade intensity index. The study found that due to the different endowments of agricultural resources and the significant differences in agricultural structure, China and Brazil’s agricultural trade competitiveness is weak and they are highly complementary. The main agricultural products exported by China are labor-intensive processed products (pulp and waste paper, textile fibers, vegetables and fruits), and the main agricultural products exported by Brazil are land-intensive products (oilseeds and oily fruits, vegetable oils, raw hides and furs). Complementary advantages in agricultural trade were analyzed. In the future, the two countries have huge potential for cooperation and development.

Effectivity of adding some types of organic manure on red ginger (Zingiber officinale Rosc. var. rubrum)

Red ginger (Zingiber officinale Rosc. var. rubrum) is a medicinal plant that belongs to the flowering family (Zingiberaceae). Indonesian potential production of red ginger was about 22 tons Ha−1 within export volume up to 3,000 tons in 2018. This value is completely different from production yields, which decreased every year. Fertilization is one of the cultivation techniques that can increase production. This study aimed to determine the type of organic fertilizer that effectively increases the growth and yield of red ginger. The research was conducted in Jatiyoso, Karanganyar from March to August 2020 with one-factor RCBD and five treatments, it is T0 (Control), T1 (Marketed Manure), T2 (Cow Manure), T3 (Goat Manure), and T4 (Chicken Manure). Plants applied with goat manure (T3) resulted in the highest growth and yield. The growth of red ginger in terms of plant height (72.77 cm), number of tillers (14.93), and weight of fresh straw (30.89 g) tended to be higher in plants applied with goat manure. The yield of fresh rhizome weight and stored rhizome weight applied with goat manure, which is 1033.8 g and 916.8 g, was the highest value above all treatments.

Export Technological Sophistication of China: Measurement and Impact Factor

What matters for China’s future growth is not the volume of exports, but whether China will continue to enhance the export competitiveness of high-tech products. Using the export data of 25 countries from 1998 to 2019, this paper measures the export technological sophistication of machinery and transport equipment and constructs an empirical model to study the impact factors of export technological sophistication of machinery and transport equipment in China. The results show that the export technological sophistication is not high, although the export volume of machinery and transportation equipment is large. FDI, human capital, and the previous phase of export technological sophistication have a significant positive effect on the technological sophistication of export; however, the abundant natural resource has a significant negative effect. Finally, some countermeasures and suggestions are put forward based on the empirical results.

Use of Machine Learning Methods for Gas Export Volume Predictions

Gas sales volume have a significant impact on oil production in the Karachagank field due to gas injection constraints. Ambient temperature is one of the variables influencing gas sales volume. As global warming takes a toll on a climate, extreme weather conditions become frequent in the region hindering hydrocarbon production. The author used machine-learning techniques to predict gas sales volume based on weather forecast data. The results of prediction allow foreseeing potential possible drops in export volumes that can help field staff in proactive planning for opportunity maintenance on wells, the surface network, and a gas plant thus helping in avoiding large negative impacts caused by high ambient temperature.

Analisis Peramalan Volume Ekspor Melon di PT Bumi Sari Lestari Temanggung Jawa Tengah

Export is an activity of sending goods abroad carried out by a company to increase profits and obtain a better selling price. Companies can optimize profits by minimizing uncertainty in the future by calculating sales forecasting which is useful for planning product inventory to be marketed. PT. Bumi Sari Lestari is one of the exporters in Central Java which exports one of the vegetable and fruit horticultural commodities, namely melons. The purpose of this study was to determine how much the forecast value of the volume of melon exports for the first quarter and second quarter of 2020 at PT. Bumi Sari Lestari uses the trend analysis method. This research was conducted on January 13, 2020 - February 9, 2020 at PT. Bumi Sari Lestari, Temanggung, Central Java. Determination The location of the study was determined intentionally (purposive). The research method used in this research is a case study. The data used are PT Bumi Sari Lestari's melon export sales data in the period of 2017-2019 (time series), monthly data analyzed quarterly from January 2017 - December 2019 with a total of 12 observations. The data analysis method uses the quadratic trend analysis method. The data stationarity test results show that the data is stationary. Melon export volume forecasting results at PT. Bumi Sari Lestari using the quadratic trend method gets results for forecasting in the first quarter of 2020 amounted to 15,767,427 kg and in the second quarter of 2020 amounted to 9,916,788 kg.

Forecasting Model for the Value of Areca Nut’s Export of Thailand

Having accurate information about the agricultural situation is very important. The predicting trends of agricultural product will allow to make right decision in economy nowadays. The aims of the paper are to demonstrate the trend in areca nut export in Thailand and import in India to specific period and to plan our strategy and policies accordingly to promote areca nut production and export. With this meaning, a study on areca nut export in Thailand and import and production in India from 2013 to 2020 was conducted. The result found that Exponential Growth Model is the most effective for forecasting in the export and import volume of areca nut. The data also was illustrated the trends in 5 years from 2021- 2025. The result revealed that the forecasting trend of export volume of areca nut in Thailand for 2021 – 2025 is linearly decreasing from 3.47610MTs in 2020 to 0.450858MTs in 2025. While, the forecasting trend of import volume of areca nut in India for 2021 – 2025 is linear increasing gradually, from35.5783 MTs in 2020 to 37.2886 MTs in 2025. Areca nut should be considered as an economics crop significantly of Thailand in future for export of Thailand because there are needs in the international market and price still be reasonable. Driving and implementing sustainable agriculture should focus on efficiency and effectiveness truly.

Modeling the Price Volatility of Cassava Chips in Thailand: Evidence from Bayesian GARCH-X Estimates

Thailand is a significant global exporter of cassava, of which cassava chips are the main export products. Moreover, China was the most important export market for Thailand from 2000 to 2020. However, during that period, Thailand confronted fluctuations in the cassava product price, and cassava chips were a product with significant price volatility, adapting to changes in export volumes. This study aims to analyze the volatility of the price of cassava chips in Thailand from 2010 to 2020. The data were collected monthly from 2010 to 2020, including the price of cassava chips in Thailand (Y), the volume of cassava China imported from Thailand (X1), the price of the cassava chips that China imported from Thailand (X2), the price of the cassava starch that China imported from Thailand (X3), the substitute crop price for maize (X4), the substitute crop price for wheat (X5), and Thailand’s cassava product export volume (X6). The volatility and the factors affecting the volatility in the price of cassava chips were calculated using Bayesian GARCH-X. The results indicate that the increase in X1, X2, X3, X4, and X6 led to an increase in the rate of change in cassava chip price volatility. On the other hand, if the substitute crop price for wheat (X5) increases, then the rate of change in the volatility of the cassava chip price decreases. Therefore, the government’s formulation of an appropriate cassava policy should take volatility and the factors affecting price volatility into account. Additionally, the government’s formulation of agricultural policy needs to consider Thailand’s macro-environmental factors and its key trading partners, especially when these environmental factors signal changes in the price volatility of cassava.