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The purpose of this study is to identify US textile and apparel (TAP) products and categories that demonstrate export comparative advantage and their respective country destinations.

Revealed comparative advantage (RCA) and normalized revealed comparative advantage (NRCA) in the long term (1996-2016) and short term (2010-2016) using two-digit Harmonized Commodity Description and Coding System codes (HS codes) provide an insight into export advantage of TAP products. Non-parametric rank correlation (i.e. Spearman rank correlation) tests consistency between RCA and NRCA. Subsequently, NRCA using four-digit HS codes identify textile sub-categories with export comparative advantage. Bilateral trade data identify export destinations for sub-categories that indicate US export comparative advantage in the short term.

Aggregated product-level comparison of RCA and NRCA ranking indicates a consistent positive correlation between the two indices. The disaggregated findings reveal cotton fiber HS5201, artificial filament tow HS5502, non-wovens HS5603, cotton yarn HS5205, carpet and other floor coverings HS5703 and worn clothing HS6309 as sources of US TAP export advantage.

This research provides a comprehensive, current analysis of the US competitive position within the TAP global environment. Incorporation of NRCA into the study’s design demonstrates the flexibility of this measure in a new industry context.

This study aims to examine the export competitiveness of Vietnam’s apparel sector by identifying the precise product categories that create its comparative advantage.

Revealed comparative advantage (RCA) and normalized revealed comparative advantage (NRCA) form the research methodology, and the RCA/NRCA values are calculated for the 2011–2020 period.

In total, 29 out of 34 product categories at four-digit levels and 65 out of 217 subcategories at six-digit levels elicited a consistent export comparative advantage throughout the 10-year study timeframe. The study also identified 13 subcategories at six-digit levels, which indicated 10 consecutive years of relative disadvantages.

The study’s findings have far-reaching implications for economic policy, development strategies and global economic integration. By providing a nuanced understanding of a country’s export strengths in the international apparel trade, this study offers valuable guidance for informed decision-making at various levels. The findings will serve as a significant source of information for policymakers and help them formulate novel policies aiming to diversify Vietnam’s apparel product offerings and export destinations. The results will also inform the government regarding the industry’s potential and attract necessary support, enabling it to grow further. This study reveals patterns in Vietnam’s apparel trade but does not provide insights into the underlying causes of comparative advantage.

The study provides an in-depth overview of Vietnam’s comparative advantages and disadvantages at two-, four- and six-digit harmonized system levels and helps understand Vietnam’s apparel export competitiveness.

The purpose of this study is to estimate revealed comparative advantage and normalized revealed comparative advantage (NRCA) indices of India’s computer and information services (CIS) export competitiveness with regard to information technology (IT) competing developing nations, such as China, Philippines, Malaysia and Brazil.

Using annual data of total exports for CIS, transportation (TNS), travel (TVL) and insurance (INS) services under service categories of the balance of payment, the present study estimates the pattern of comparative advantage (CA) in India’s CIS exports with respect to IT competing developing nations such as China, Philippines, Malaysia and Brazil from 2000 to 2018. The choice of the study period is determined by the availability of consistent data on IT service exports of these nations. The study also estimates the export position of CIS export in comparison to India’s traditionally strong commercial services export of TNS, TVL and INS during the study period.

Both the indices showed that India had a strong CA in CIS compared to the selected nations, indicating India’s relative export performance to be stronger than that of China, Malaysia, Philippines and Brazil. The cross-service index showed that India’s relative specialization level in CIS with respect to the world’s average specialization level was stronger than its relative specialization level in TNS, TVL and INS services. Furthermore, The NRCA cross-nation index showed that India’s NRCA index score has been declining since 2010 with respect to these nations, which implied a decline in the competitiveness of CIS. On the other hand, NRCA has increased in the case of Philippines, Malaysia and Brazil for most of the period post-2010.

IT is a dynamic area of economic activity, and when the pace of change is so rapid, the relevance of individual factors can change over time. The study period is also limited to the available data.

The paper has implications for attaining sustainability in IT export growth. It is suggested that policies are directed at enhancing the overall performance of IT sector.

The novelty of the present study lies in the estimation of India’s competitiveness in IT exports in relation to the group of reference countries. With its policy recommendations, this research is helping to shape the sustainability of the IT sector.

This study aims to measure the competitiveness of top apparel exporting nations competing with China in different apparel product categories across the global environment.

Compound annual growth rate, trade competitiveness, market share percentages, revealed comparative advantage and its variant normalized revealed comparative advantage using two-, four- and six-digit harmonized system codes for the period of 2016–2021 were used to understand the comparative advantage of competing apparel exporting nations.

The findings revealed that China still holds a more decisive comparative advantage than its competitors over the majority of the product categories within the knitted or not knitted apparel and clothing accessories. The other competing nations hold better export competitiveness over China in specific categories. However, that is not sufficient to be the “Next China.”

The study has important implications for different stakeholders of the global apparel industry, such as governments, industry officials, policymakers, investors, researchers and students. The study’s limitations arise from using product categories as competitiveness indicators, notably relying on a macro level approach for measurement while the micro level perspective is not analyzed, which constitutes a significant limitation of the study.

This research thoroughly analyzes the competitive position of the top ten apparel-exporting countries in the global market.

Given the dominant share of India in global production of fruits and vegetables, this paper intends to analyze the export competitiveness of India and other major food exporters in the world trade. The purpose of this study is to examine export structure, substitutability and complementarity of selected fresh and processed fruits and vegetables of top ten food exporters for the period 2010-20.

Balassa’s (1965) revealed comparative advantage (RCA) index was used to measure RCA indices of selected fruits and vegetables under study. Also, revealed symmetric comparative advantage (RSCA) and normalized RCA (NRCA) indices have been calculated. Further, Spearman rank correlation coefficients were computed to analyze changes over the study period for India and other competing countries. The export data have been sourced from UN Comtrade, an electronic database of United Nations, as well as World Trade Statistical Review, a database of World Trade Organization. The analysis was undertaken at Harmonized System (HS) four-digit classification for the period 2010-20.

The results disclosed an improvement in India’s comparative advantage over the period of 2010-20 in HS 07 product category, whereas the advantage ceded to other competitive nations in HS 08 product category. Further, Spearman rank correlation coefficients revealed that India faces competition from countries like China, Indonesia, Brazil, Thailand, Argentina and European Union for HS 07 product category, while countries like Mexico, Indonesia, Brazil and Thailandare the major competitors of India in HS 08 product category.

The paper expands the existing agricultural trade literature in three ways. First, it is one of the very few studies that have analyzed RCA for Indian fresh and processed fruits and vegetables using three different types of indices, namely, Balassa’s RCA, RSCA and NRCA. Second, the authors provide a number of comparisons related to RCA for Indian fruits and vegetables with other top food exporters in the world for a period of 10 years (2010-20). Third, the authors contribute to agricultural trade literature by assessing the substitutability or complementarity of India in the export of fruits and vegetables with other competing nations by using Spearman rank correlation coefficients.

This study aims to (1) identify the agricultural competitiveness of ASEAN countries in the global markets; (2) analyze the dynamics of these indicators for the period 1997–2015; and (3) test the consistency between trade indices.

The study uses RCA, RTA, and NRCA for the first objective; OLS method and Markov matrix for the second objective; and statistic tool for the final purpose.

The results show that: (1) ASEAN countries achieve the strongest competitiveness in rice, rubber, spices, vegetable fat and oils, wood, fuel wood, fish, and crustacean. Vietnam, Thailand, and Indonesia are the strongest competitive whilst Brunei, Singapore, and Cambodia are the weakest competitive; (2) They have convergent patterns in agricultural competitiveness; (3) They successfully maintain rankings of the strong competitive sectors; and (4) ASEAN countries obtain benefits from the regional integration and the specialization in competitive products.

ASEAN countries with strong competitiveness should specialize in and maintain their rankings to enhance competitiveness and maximize social welfare while the countries with weak agricultural competitiveness should specialize in the processed products and services based on their advantages of economic resources.

Comprehensive results of the static and dynamic agricultural competitiveness of ASEAN countries as a whole are provided. The findings and policy recommendations can be used by policymakers and enterprises to improve competitiveness and benefit. The discussions and findings should be a significant reference for economists.

This paper aims to present structural changes and trade competitiveness in Indian pharmaceutical industry in pre and post product patent regime. The study shows the impact of product patent on market structure, ownership, trade, revealed comparative advantage, R&D and mergers and acquisitions.

The study is based on secondary data and extensive relevant conceptual and empirical literature review.

The study finds that this oligopoly Indian dominant pharmaceutical industry has many challenges ahead such as in R&D expenditure, patent expiration of many major drugs manufactured in Ireland, growing competition in generic global market, bulk drugs dependence on China, rise in the number of M&As, rising costs of new drug discovery and tightening safety and efficacy testing requirements. The smaller firms are likely to act as the contract manufacturers for medium and bigger companies at a lower value chain. The Normalised Revealed Comparative Advantage (NRCA) index was calculated for top exporters of pharmaceutical. It was found that NRCA index of IPI has shown deterioration from 1996 to 2005 and thereafter, improvement except in the year 2009. Switzerland, Belgium and Ireland are the top three countries in NRCA index, which are followed by Germany, the UK and France.

It attempts to capture recent trends in market structure, comparative advantage indices, R&D, trade, M&A and ownership, especially in new IPR regime. There is a dearth of studies providing detailed analyses of India’s comparative advantage vis-a-vis other leading exporters of pharmaceutical products in the world. The paper would be of value to practitioners and scholars interested in structural changes of IPI, especially in product patent regime. The findings have significant implications for managers and government for future policymaking.

The purpose of this paper is to evaluate the global competitiveness of the top ten wooden furniture exporting countries with several approaches and to test the effect of export prices (EXPRs) on the global competition.

Countries' competitiveness levels were measured with revealed comparative advantage (RCA), normalised RCA (NRCA), revealed symmetric comparative advantage (RSCA) and trade balance index. Furthermore, panel regression analysis techniques were used to test the effects of EXPR on RCA, NRCA and RSCA in the wooden furniture industry (WFI).

Although the comparative advantage approaches give different results, the global competitiveness of Poland and Vietnam is at a high level in all approaches. Canada has been the country with the weakest global competitiveness in all approaches. According to the results of the analysis, EXPRs positively affect all the competitive advantage indexes. As a result, the competitiveness of the WFI is affected by the non-price factors instead of the EXPR.

The framework allows us to measure and illustrate the export competitiveness of the WFI and permits a global comparison. Similar analyses can be made for different labour-intensive sectors. In addition, analysis can be made to identify non-price factors for the WFI sector. Thus, more specific inferences can be made.

This study is useful for policymakers, government officials, the industry associations and the company executives to assess their export competitiveness in the WFI. Thus, they can determine whether to shift scarce resources to this industry or other industries. In addition, this study may affect the price competition policy of the sector representatives in the global market.

This study deals with the competitiveness of the WFI with different approaches. And this study determines the importance of price for global competition in this sector.

This paper aims to examine the competitiveness trends and rankings of the Irish dairy sector at the farm and trade levels, relative to selected European Union (EU) Member States, in the context of the removal of the EU milk quota in 2015.

Competitiveness indicators including partial productivity measures and accountancy-based indicators were used for farm competitiveness, and net export market share and normalised revealed comparative advantage (NRCA) were used for export competitiveness.

Amongst the countries examined, Ireland had the highest growth in partial productivity indicators and was ranked first with the lowest total costs and cash costs per kg of milk solids post-quota. However, the total economic cost sub-components showed that Irish dairy farmers had high opportunity costs for owned land and labour. While Irish dairy products such as butter and powders have demonstrated growth potential in competitiveness post-quota with Irish butter and whey ranked in top three relative to other countries, other products, i.e. cheese and liquid milk have declined in competitiveness according to key export competitiveness indicators used.

The challenge for Irish dairy farmers is how to mitigate relatively high land and labour costs, which can limit farm competitiveness in the long run. The key players in the Irish dairy industry can now better position themselves in the global dairy market, recognizing the competitiveness dynamics of the different dairy products and their competitors. Policy implications and further areas of research have been identified to help improve the overall competitiveness position. It is surprising that Irish butter is a leader in the EU, yet not much research has been done to understand the market dynamics of this sector.

To the best of the authors’ knowledge, this study is the first of its kind to use both farm and export competitiveness measures to analyse the Irish dairy industry relative to other countries in the context of quota abolition. Unlike previous studies on dairy export competitiveness, this study has disaggregated the processed dairy products, which allowed for the ranking of countries and comparability across countries using NRCA.

This paper aims to propose a new node energy-efficient algorithm with energy threshold to replace cluster heads. The proposed algorithm uses node ranking to elect cluster heads based on energy levels and positions of the nodes in reference to the base station (BS) used as a sink for gathered information. Because the BS calculates the number of rounds a cluster head can remain for as a cluster head in advance, this reduces the amount of energy wasted on replacing cluster heads each round which is the case in most existing algorithms, thus prolonging the network lifetime. In addition, a hybrid redundant nodes duty cycle is used for nodes to take turn in covering the monitored area is shown to improve the performance further.

Authors designed and implemented the proposed algorithm in MATLAB. The performance of the proposed algorithm was compared to other well-known algorithms using different evaluation metrics. The performance of the proposed algorithm was enhanced over existing ones by incorporating different mechanisms such as the use of an energy-based threshold value to replace CHs and the use of a hybrid duty-cycle on nodes.

Through simulation, the authors showed how the proposed algorithm outperformed PEGASIS by 15 per cent and LEACH by almost 70 per cent for the network life-time criterion. They found that using a fixed pre-defined energy threshold to replace CHs improved the network lifetime by almost 15 per cent. They also found that the network lifetime can be further improved by almost 7 per cent when incorporating a variable energy threshold instead of a fixed value. In addition to that, using hybrid-redundant nodes duty-cycle has improved the network lifetime by an additional 8 per cent.

The authors proposed an energy-efficient clustering algorithm for WSNs using node ranking in electing CHs and energy threshold to replace CHs instead of being replaced every round.