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The maritime freight transportation industry has played an important role in the Korean economy. The Korean maritime freight transportation industry is faced with a period of transforming it competitively and efficiently in this global age. This paper, therefore, aims to identify the impact of the maritime freight transportation industry in the Korean national economy. Hence, this paper provides policy-makers with accessible and reliable information regarding the role of the Korean maritime freight transportation industry. This study employs input-output (I-O) analysis to examine the role of the maritime freight transportation industry in the national economy for the period 1995-2003, with specific application to Korea. This study pays particular attention to the maritime freight transportation industry by taking the industry as exogenous variable and then investigates its economic impacts. We identify inter-industry linkage effects in 20 sectors, production-inducing effects, added value-inducing effects, and supply-shortage effects of the maritime freight transportation industry.

This study analyzed Korea's relations table through network analysis. In particular, among the centralities, eigenvector centrality, PageRank centrality and degree were used. The author studied which network characteristics affected the value-added rate.

A network analysis method was used.

It is the inward relationship that affects the value-added ratio of Korea's industries and the outward relationship has less influence. In particular, the inward relationship not only acts as a cost but also has an effect on the rate of added value recently.

Since the three years of 2010, 2015 and 2019 are the target, the data are somewhat insufficient to generalize.

As for the value-added ratio of an industry, input is more important than output (sales). Therefore, where the input is received is very important.

It is possible to increase the understanding of the determinants of the value-added rate of Korean industries.

(1) It was clarified which side is inward or outward in determining the industry in Korea. (2) The relationship between PageRank, eigenvector centrality and degree was analyzed in Korean cases. (3) Input is a cost and acts to increase added value.

In today’s multi-channel distribution environment, it is crucial for the competitiveness of retail stores and companies to improve efficiency of dedicated logistics centers (DLCs) servicing types of retail outlets such as large retail-stores, super supermarkets, and convenient stores. This paper derives efficiency improvement strategies for DLCs through efficiency analyses. To this end, this paper empirically analyzes the efficiency of DLCs by applying DEA (data envelopment analysis) approaches using real data from a Korean distribution company. In detail, this paper analyzes operations, finance, and service efficiencies of DLCs and performs a comparison analysis on the efficiency between DLCs. Finally, this paper discusses the analysis results considering the DLCs’ characteristics and derives managerial and operational implications.

The aim of this study is to provide energy supply chain in Indonesia. Therefore, the best scenario has been created to fulfill energy scarcity by global supply chain partnership. All impact social-economy will be advantages. The input output analysis has been applied in this paper. The impact of output and impact of job creation are possible to describe, significantly. All barriers and opportunities that can be achieve from the lowest price, efficiency and also to reduce unemployment rate during a decade of building nuclear power plants. This research work can be applicable model for future nuclear power plants construction or other type of energy source construction that give significant impact to the economy and business sustainability. Therefore, by this project plan will cover energy needs for domestics and improve the local corporate productivity, especially for nuclear power plants equipment.

Understanding China's carbon dioxide (CO2) emission status is crucial for getting Carbon Neutrality status. The purpose of the paper is to calculate two possible scenarios for CO2 emission distribution and calculated input-output flows of CO2 emissions for every 31 China provinces for 2012, 2015 and 2017 years.

In this study using the input and output (IO) table's data for the selected years, the authors found the volume of CO2 emissions per one Yuan of revenue for the industry in 2012 and the coefficient of emission reduction compared to 2012.

Results show that in the industries with a huge volume of CO2 emissions, such as “Mining and washing of coal”, the authors cannot observe the reduction processes for years. Industries where emissions are being reduced are “Processing of petroleum, coking, nuclear fuel”, “Production and distribution of electric power and heat power”, “Agriculture, Forestry, Animal Husbandry and Fishery”. For the “construction” industry the situation with emissions did not change.

“Transport, storage, and postal services” and “Smelting and processing of metals” industries in China has the second place concerning emissions, but over the past period, emissions have been sufficiently reduced. “Construction” industry produces a lot of emissions, but this industry does not carry products characterized by large emissions from other industries. Authors can observe that Jiangsu produces a lot of CO2 emissions, but they do not take products characterized by significant emissions from other provinces. Shandong produces a lot of emissions and consumes many of products characterized by large emissions from other provinces. However, Shandong showed a reduction in CO2 emissions from 2012 to 2017.

This paper applies the decomposition method proposed by Wang et al. (2013), together with the multi-national input-output tables from World Input-Output Database (WIOD) to estimate the value-chain transition in East Asian production network. Specifically, we calculate and examine the domestic value-added absorbed abroad, foreign value-added embodied in country’s gross exports, and vertical specialization measures to explore the relative positions of major East Asian countries in the global production chain over the period of 1995-2011. The analyses are at country-aggregate, country-sector, bilateral-aggregate and bilateral-sector levels. Based on our results, we answer the important question of whether Taiwan and South Korea have used China’s production chains as an intermediary to re-export their products to other countries in the world. Furthermore, we answer the question that over the 1995-2011 periods, have Taiwan and South Korea exploited cheap labor from China to add value to their products before re-exported them to the rest of the world?

The main goal of this paper is to examine the evolution of Latin American productive integration in terms of the regional value added incorporated in intra-regional exports of Argentina, Brazil, Chile, Colombia, Mexico and Peru. In addition, the study traces the trade and productive integration trajectories for each of these countries from 1995 to 2015.

Based on the use of OECD’s global ICIO input-output tables, this paper applies the methodological framework by Wang et al. (2018) for the analysis of trade flows at the bilateral level, which allows breaking down the value of gross exports of each sector-country, depending on the origin of the value added contained in exports, as well as their use.

The estimates show very low shares of value added from regional partners in the intra-regional exports of the countries studied. Conversely, the weight of the value added incorporated in these exports by countries outside the region has increased in tandem with China’s expanding involvement in Latin America. This development, along with the downward trend in domestic value added incorporated in exports, indicates a lack of a regional integration process of any depth.

This article addresses an economic problem of conventional importance from a global value chain perspective using a novel methodology based on the use of global input–output tables.

This paper aims to assess the application of seven statistical and data mining techniques to second-stage data envelopment analysis (DEA) for bank performance.

Different statistical and data mining techniques are used to second-stage DEA for bank performance as a part of an attempt to produce a powerful model for bank performance with effective predictive ability. The projected data mining tools are classification and regression trees (CART), conditional inference trees (CIT), random forest based on CART and CIT, bagging, artificial neural networks and their statistical counterpart, logistic regression.

The results showed that random forests and bagging outperform other methods in terms of predictive power.

This is the first study to assess the impact of environmental factors on banking performance in Middle East and North Africa countries.

In the current literature, there is little systematic research on the relationship among adjustment of the income distribution, change in economic structure and improvement of macroeconomic efficiency.

This paper expands Marx's reproduction schema into the “Marx–Sraffa” three-department structure table comprising fixed capital, general means of production and means of consumption and employs China's input–output table from 1987 to 2015 to portray the relationship between income distribution and macroeconomic efficiency under investment-driven growth.

This paper calculates the wage–profit curve of China's economy and evaluates the space of macroeconomic efficiency improvement in China based on the deviation between actual and potential income distribution structure.

The results show that there is a downward trend of the profit rate, which meets Marx's theoretical prediction, and the decline in the profit rate is mainly attributed to an increase in the organic composition of capital arising from the rapid growth of fixed capital investment under extended growth. The analysis of macroeconomic efficiency shows that the space for improving macroeconomic efficiency is extremely limited under traditional growth pattern and that China must transform its economic development pattern and foster new economic growth drivers.

This paper aims to study the inter-sectoral linkages in the Egyptian economy, to increase the efficiency of allocating L.E 100bn fiscal stimulus package (FSP) to tackle the economic fallout from COVID-19 based on the strength of the backward and forward linkages of various sectors, and the values of both employment and value-added multipliers. The paper also measures the impact of the new FSP on the capability of various sectors in creating job opportunities and increasing economic growth.

The paper studies the intersectoral linkages by calculating backward and forward linkages index based on the latest input and output tables available for the Egyptian economy published in 2018. It also depends on a bivariate optimization model to distribute new investments allocated through the FSP based on the values of both employment and value-added multiplier for those sectors. The paper calculated both employment and value-added coefficients to measure the impact of the FSP on creating job opportunities and increasing growth rates.

Based on the results of the empirical analysis, both key sectors (with strong backward and forward linkages) and sectors with strong backward linkages have the highest impact on creating job opportunities and increasing growth rates in the Egyptian economy, which means that allocating FSPs in a way which targets those sectors, especially during economic crisis, could help in increasing the positive impacts of those packages.

The paper is based on the unbalanced growth theory of Hirschman and uses the empirical analysis to study the intersectoral linkages and allocate new investments through FSP through different sectors. The main policy implication of the empirical results of this paper suggests targeting the key sectors and the sectors with strong backward linkages during tough economic times related to COVID-19, to increase the positive impact of the package on the whole economy.