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This study aims to empirically investigate the potential impact of the Trans-Pacific Partnership (TPP) on US textile and apparel manufacturing.

This study adopts the Global Trade Analysis Project (GTAP) computable general equilibrium model based on the latest GTAP9 database.

The findings of the study suggest that: the “yarn-forward” rule will not work effectively in the context of TPP; and the development of Vietnam’s local textile industry is a critical threat to the survival of US textile and apparel (T&A) manufacturing in the long run.

The findings of the study augment the understanding of the T&A-specific sectoral impact of TPP and address the particular concerns of the US T&A manufacturers with regard to the new business environment and the possible scenarios after the implementation of the agreement.

The purpose of this paper is to calculate regional contents in the exports of the major regional blocs to the world, Trans-Pacific Strategic Economic Partnership (TPP), and Regional Comprehensive Economic Partnership (RCEP), respectively, to find the backward trade linkages between them instead of normal forward linkages.

To calculate “a region” content in intermediate and value-added exports, this paper uses OECD’s inter-country input-output table (ICIOT), and tries to decompose the contents of trade. Using the information of ICIOT, Koopman et al. (2014) and Wang et al. (2013) decompose gross exports of a country’s exports.

TPP is a loosely tied bloc featured by openness to the Asia-Pacific region. Trade linkages between members are stronger in RCEP than those in TPP, particularly in the trade of intermediate goods. Trades in RCEP are closely connected to exports to TPP, but the opposite direction is not clear.

First of all, the recent base year of the data on value added in trade is 2011, which can be regarded as a little bit out of date. Therefore, it should be cautious in interpreting the results in that it may not reflect the characteristics of current trade. Second, this paper uses ICOIT instead of world input-output table.

A large portion of trades in RCEP and TPP is triggered by a global production network (fragmentation, vertical specialization), different from traditional trade focusing on inter-industry trade or competition between countries. Thus, the formation of TPP or RCEP is predicted to stimulate trade of the other instead of discriminating nonmember countries.

In particular, the authors have special concern in the backward linkages between RCEP and TPP, the distinct characteristics of the two regional blocs and, finally, major countries’ preferences of the one over the other and industrial conflicts toward TPP or RCEP even in an economy.

Although this paper uses the approach by Baldwin and Lopez-Gonzalez, this paper is the first research on the analysis of the export contents in major trading blocs in the Asia-Pacific region.

The purpose of this paper is to measure the effects of TPP on Korean economy focussing on the changes in the number of firms and productivity.

Following Melitz (2003) and Balistreri et al. (2011), the authors apply CGE simulation to five groups of 140 countries.

The authors find that welfare increases in Korea to join the TPP regardless the size of the TPP through productivity improvement of participating firms and increases in the number of exporting firms, factor prices and outputs.

This study helps tentative member countries of TPP decide to join.

The effects of TPP to Korean economy is measured with Melitz model, which has not yet attempted before.

The purpose of this paper is to analyze a thermal power plant (TPP) by taking into consideration its key components, namely, boiler, turbine, conveyor and generator, which are handled by a human operator. It is well known fact that the continuous power generation through a power plant depends on the reliability/availability of its components.

The various performance measures of a TPP are obtained by using mathematical modeling, Markov process and supplementary variable technique.

Reliability, i.e. mean time to failure with respect to different components of a TPP, has been obtained and demonstrated with the help of graphs. Critical components of the system are identified through sensitivity analysis.

In the present paper, a mathematical model based on the functioning of a TPP has been developed. Conclusions in this paper are good references for the design of a TPP.

The purpose of this paper is as follows: first, it aims to explain the overall economic implications of the trans-pacific partnership (TPP). Second, it aims to provide an in-depth analysis of the TPP’s quantitative impact on an upper-middle economy such as Mexico, as well as on the USA.

The analysis is performed using a computable general equilibrium (CGE) model.

The results suggest that in the short run, both Mexico and the USA would slightly benefit from the TPP. Tariff reductions would lead to less bilateral trade between Mexico and the USA and the stronger integration of both countries with the rest of the TPP members. The opposite is true after a decrease in non-tariff barriers (NTBs). Overall, in terms of the impact on Mexico, trade integration with the rest of the TPP members prevails. This suggests that a TPP without the USA could still be beneficial.

Previous studies on the TPP have mainly focused on its impact for the USA, which is also analysed in the present study. The effects of the TPP are estimated for a broad set of micro and macroeconomic variables, paying particular attention to the reductions of NTBs.

Vietnam has been actively integrated into a multilateral trading system based on its accession to the WTO and the implementation of a series of ASEAN+1 FTAs. Now Vietnam is negotiating to be a member of the Trans-Pacific Partnership (TPP) agreement, which is a region-wide FTA in the Asia-Pacific region, and a total of 21 working groups have been negotiating 29 chapters of the TPP. This paper tries to assess major issues of Vietnam’s joining the TPP, and to draw policy implications such as initiatives for Vietnam’s acceleration of its renovation and economic restructuring programs; and domestic measures for facilitating FTA implementation by firms and enhancing the country's implementation capacity.

The purpose of this study is to predict the thermal protective performance (TPP) of flame-retardant fabric more economically using machine learning and analyze the factors affecting the TPP using model visualization.

A total of 13 machine learning models were trained by collecting 414 datasets of typical flame-retardant fabric from current literature. The optimal performance model was used for feature importance ranking and correlation variable analysis through model visualization.

Five models with better performance were screened, all of which showed R2 greater than 0.96 and root mean squared error less than 3.0. Heat map results revealed that the TPP of fabrics differed significantly under different types of thermal exposure. The effect of fabric weight was more apparent in the flame or low thermal radiation environment. The increase in fabric weight, fabric thickness, air gap width and relative humidity of the air gap improved the TPP of the fabric.

The findings suggested that the visual analysis method of machine learning can intuitively understand the change trend and range of second-degree burn time under the influence of multiple variables. The established models can be used to predict the TPP of fabrics, providing a reference for researchers to carry out relevant research.

The findings of this study contribute directional insights for optimizing the structure of thermal protective clothing, and introduce innovative perspectives and methodologies for advancing heat transfer modeling in thermal protective clothing.