Search results

There is considerable variation in the extent of globalization across industries. The authors attempt to identify the structural conditions of the industry that lead to these variations.

Based on a sample of 33 manufacturing industries over the nine-year period from 2007 to 2016, the authors test for antecedents of industry globalization.

The authors find that industry globalization is positively affected by medium levels of barriers to entry, industry competition, industry assistance, low and mediums levels of capital intensity, industry concentration and industry regulation and negatively affected by low levels of technological change and industry assistance. In addition, the life cycle stage of the industry has an impact on the level of globalization with the growth stage having the highest level of globalization.

First, the major limitation of the paper is that the authors rely entirely on trade data to measure the level of industry globalization. The authors did not have a choice because foreign direct investment (FDI) data are available only at the country level. Second, given that globalization can occur at the country, industry and firm levels, the focus on industry-level structural characteristics alone may be seen as a limitation.

The results of the study can provide guidance to practicing managers to apply industry analysis for predicting the potential for and direction of globalization of their industries. This will enable them to formulate appropriate strategies to cope with global competition.

The study has important public policy implications. National governments have many levers at their command that can be used to influence the structural characteristics of industries, such as industry regulation, industry assistance and industry concentration. They can selectively use these levers to either facilitate or impede globalization.

Much of the empirical focus of prior research on globalization has been on countries, rather than industries, as the unit of analysis. There is clearly variation in the extent of globalization across industries with some industries highly integrated while others remain primarily local or regional. Based on a novel approach to measure the extent of globalization at the industry level, the authors identify its antecedents. The value of the paper lies in the fact that the analysis of 33 manufacturing industries over a ten-year period shows that the structural characteristics of the industries drive their extent of globalization.

The purpose of this paper is to answer for questions regarding vertical specialization in the Korea’s key exporting industries, such as the changing pattern toward VS or VS1 and the changing trend in the location of slicing up the value chain in these industries.

The framework of Koopman et al. (2014) is adopted to calculate the industry-level vertical specialization indices, VS and VS1.

VS1 is a dominant type of vertical specialization in the key exporting industries of Korea. The increasing net vertical trades (VS1−VS) verifies the upward trends in the locations of slicing up the value chain in the industries empirically.

The net vertical trade (VS1−VS) of each industry is an important indicator of the location of slicing up the value chain in the environment of the international production network.

The industry-level calculations of VS and VS1 are necessary in order to remedy the aggregation bias from the country-level calculation of VS and VS1 functioning in the opposite direction.

The paper examines the impact of export activity on productivity and how this effect is moderated by R&D investment and foreign ownership.

A time-lag effect is taken into account when examining the proposed model. Data are collected from the Annual Industrial Survey of the National Bureau of Statistics of China. A dataset containing 117,340 firms across the sample period (2001–2007) are used to test the hypotheses.

The results indicate that while R&D investment plays a significant role in strengthening the positive effect of export activity on a firm's productivity, foreign ownership surprisingly has a negative moderating role.

Scholarly interest in the links between export activity and productivity is on the rise. However, the bulk of research has been focused on understanding the effects of export activity on productivity at the country or industry level. Little has been done at the firm level. Another gap in the literature is that the mechanism through which the impact of export activity can be leveraged to enhance the firm's productivity has been largely ignored. To address these issues, the study adopts the learning-by-exporting theory to examine the relationship between export and productivity at the firm-level and how R&D investment and foreign ownership may explain how learning can be leveraged to enhance the firm's productivity. Finally, these relationships are examined in the context of firms from an emerging market, China, which is especially relevant for the learning-by-exporting argument used in this study.

The objective of this study is to investigate how country risk, different political actions from the government and bureaucratic behavior influence the activities in industry supply chains (SCs) in emerging markets. The main objective of this study is to investigate the influence of these external stakeholders’ elements to the demand-side and supply-side drivers and barriers for improving competitiveness of Ready-Made Garment (RMG) industry in the way of analyzing supply chain. Considering the phenomenon of recent change in the RMG business environment and the competitiveness issues this study uses the principles of stakeholder and resource dependence theory and aims to find out some factors which influence to make an efficient supply chain for improving competitiveness. The RMG industry of Bangladesh is the case application of this study. Following a positivist paradigm, this study adopts a two phase sequential mixed-method research design consisting of qualitative and quantitative approaches. A tentative research model is developed first based on extensive literature review. Qualitative field study is then carried out to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. A survey is carried out with sample of top and middle level executives of different garment companies of Dhaka city in Bangladesh and the collected quantitative data are analyzed by partial least square-based structural equation modeling. The findings support eight hypotheses. From the analysis the external stakeholders’ elements like bureaucratic behavior and country risk have significant influence to the barriers. From the internal stakeholders’ point of view the manufacturers’ and buyers’ drivers have significant influence on the competitiveness. Therefore, stakeholders need to take proper action to reduce the barriers and increase the drivers, as the drivers have positive influence to improve competitiveness.

This study has both theoretical and practical contributions. This study represents an important contribution to the theory by integrating two theoretical perceptions to identify factors of the RMG industry’s SC that affect the competitiveness of the RMG industry. This research study contributes to the understanding of both external and internal stakeholders of national and international perspectives in the RMG (textile and clothing) business. It combines the insights of stakeholder and resource dependence theories along with the concept of the SC in improving effectiveness. In a practical sense, this study certainly contributes to the Bangladeshi RMG industry. In accordance with the desire of the RMG manufacturers, the research has shown that some influential constructs of the RMG industry’s SC affect the competitiveness of the RMG industry. The outcome of the study is useful for various stakeholders of the Bangladeshi RMG industry sector ranging from the government to various private organizations. The applications of this study are extendable through further adaptation in other industries and various geographic contexts.

We are interested in modeling the impact of spatial and interindustry dependence on firm-level innovation of Chinese firms The existence of network ties between cities imply that changes taking place in one city could influence innovation by firms in nearby cities (local spatial spillovers), or set in motion a series of spatial diffusion and feedback impacts across multiple cities (global spatial spillovers). We use the term local spatial spillovers to reflect a scenario where only immediately neighboring cities are impacted, whereas the term global spatial spillovers represent a situation where impacts fall on neighboring cities, as well as higher order neighbors (neighbors to the neighboring cities, neighbors to the neighbors of the neighbors, and so on). Global spatial spillovers also involve feedback impacts from neighboring cities, and imply the existence of a wider diffusion of impacts over space (higher order neighbors).

Similarly, the existence of national interindustry input-output ties implies that changes occurring in one industry could influence innovation by firms operating in directly related industries (local interindustry spillovers), or set in motion a series of in interindustry diffusion and feedback impacts across multiple industries (global interindustry spillovers).

Typical linear models of firm-level innovation based on knowledge production functions would rely on city- and industry-specific fixed effects to allow for differences in the level of innovation by firms located in different cities and operating in different industries. This approach however ignores the fact that, spatial dependence between cities and interindustry dependence arising from input-output relationships, may imply interaction, not simply heterogeneity across cities and industries.

We construct a Bayesian hierarchical model that allows for both city- and industry-level interaction (global spillovers) and subsumes other innovation scenarios such as: (1) heterogeneity that implies level differences (fixed effects) and (2) contextual effects that imply local spillovers as special cases.

The primary purpose of this paper is to take an in-depth look at the question of whether liberalizing trade in agriculture can generate dynamic productivity gains comparable to those in the manufacturing sector.

In contrast to the manufacturing sector that has generated firm/plant-level trade data, there is a lack of farm-level trade data that are needed for empirical measurement of dynamic productivity gains. Therefore, the authors use thought experiments to analyze the sequence of events that would occur when trade is liberalized for agriculture; delineate the expected behaviors of the actors involved in the trade and draw inferences about whether there would be dynamic productivity gains from agricultural trade.

The central finding is that there would be little dynamic gain from agricultural trade at the farm level due to the limited role of producers in shaping their international competitiveness. Yet, agricultural trade may generate dynamic gains if states or input supply corporations respond to the freer trade environment by making more investments for research and development (R&D). Further, when intraindustry prevails, there can be productivity gains at the industry level due to the transfer of resources from less to more efficient farm producers.

The findings of the paper are expected to present insights into value for researchers working in the area of agricultural trade; for agricultural trade policymakers in developing countries and for trade negotiators engaged in reforming or designing World Trade Organization (WTO)’s trade rules for agriculture.

The purpose of this paper is to measure and analyze industry export competitiveness of India and it tries to achieve this by presenting a multi‐dimensional framework for measuring and illustrating industry export competitiveness.

The framework considers industry specialization, industry export growth rate, and relative export market share for a dataset of 97 different Indian industries over a five year period (2001‐2005).

The analyses identifies four different types of industry groups, namely domestic static, domestic dynamic, global dynamic and global static. The result shows that the majority of Indian industries are dynamic and growing faster than the world export growth rate for the period of study. A total of 40 percent of India's industries are more global, in terms of industry specialization, compared to the world average, with such highly specialized industries as silk, gums, carpets and textiles, floor coverings, pearls, precious stones and metals. The authors show that industry specialization leads to dominance in worldwide export market share. India's global dynamic industries are mainly in the raw materials, commodities and skilled manual labor rather than high tech or manufacturing sectors.

The framework allows us to measure and illustrate industry export competitiveness and permits an intra‐country comparison, a comparison of various industries of one country, or permits an inter‐country comparison, a comparison of one industry across different countries.

The framework should help policymakers, government officials, industry associations, and company executives to assess their export competitiveness and focus on protecting or promoting certain industries by directing scarce resources to sectors where they may count the most. The findings of the study can also be useful for international bodies such as UNCTAD and world‐bank in identifying regional industry that can foster growth of trade and economies in the South‐Asian region.

The framework used is conceptually innovative and applicable to a variety of contexts for modeling industry export competitiveness. The framework also facilitates inter‐ and intra‐country export benchmark analyses.

Recently published studies stress the importance of trade in intermediate goods. The literature on determinants of trade, however, have largely focused on the sources of comparative advantage in determining aggregate trade flows rather than trade in intermediate goods. The purpose of this paper is to examine the role of institutional quality and trade costs to explain the determinants of trade in intermediates.

The simple model is based on the model of comparative advantage in the gravity framework used by Eaton and Kortum (2002) and Chor (2010) to relate trade flows of intermediate goods to institutional parameters, factor endowments and geography. The empirical tests use a data set containing 172 countries and 17 industries spanning ten years.

The results confirm the theoretical prediction that a country with higher institutional quality has a comparative advantage in institution-intensive goods and trade costs have a negative effect on trade. The author further finds that these effects are stronger in share of trade in intermediate goods vis-à-vis final goods.

To highlight the distinct nature of trade in intermediate goods, the author separates industry trade flows as intermediate input trade and final goods (consumption goods) trade to compare the importance of different sources of comparative advantage among different types of trade flows. Unlike Eaton and Kortum (2002) and Chor (2010) who used cross-sectional data for final goods trade, the ten-year industry-level panel data are used to compare the relative importance of institutions and geography as determinants in trade in intermediate goods compared to final goods trade and capture the macroeconomic time variant factors as well as industry–country pair characteristics. A significant caveat in gravity regression is that an empirical finding may often be driven by omitted variables. Inclusion of a set of country variables such as GDP, production costs and institutional level may still allow omitted variables to bias the estimation. To avoid this problem, the author includes a fixed effect of exporter and importer as well as industry and year, instead of a set of country characteristics.

The purpose of this paper is to identify some of the major issues relating to the conceptualization and operationalization of industry globalization.

Globalized industries have four important characteristics: cross-border product flows, cross-border capital flows, dispersal of global value chains and global competition. However, lack of availability of data limits our ability to develop an operationalization that encompasses all these four aspects of globalization.

The authors identify some of the most important factors driving industry globalization as well as the major impediments to globalization.

Although the term “globalization” has attained a nearly “taken for granted” status, its meaning is rather vaguely specified and is often context dependent. This paper delineates the domain of the construct and identifies many of the practical issues in operationalizing the construct.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.