Cost-competitiveness and structural change in value chains – vertically-integrated analysis of the European automotive sector

Grodzicki, Maciej; Skrzypek, Jurand

doi:10.1016/j.strueco.2020.08.009

Cited by 30 publications

(13 citation statements)

References 60 publications

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“…For instance, Li et al (2021a) calculated trade in value-added of Outward Foreign Direct Investment (OFDI) using the Trade in Value added (TiVA) database initiated by the WTO and OECD [72]. Grodzicki (2020) applied vertically-integrated analysis to capture the combined contributions of all industries supplying their inputs to the automotive final production within a value chain [73]. Koopman et al (2014) decomposed the country's gross exports into sixteen value-added components based on the input-output table, and identified four double-counting terms [74].…”

Section: Appendix a Information On The Methodsmentioning

confidence: 99%

Energy Network Embodied in Trade along the Belt and Road: Spatiotemporal Evolution and Influencing Factors

Xue

Yan

et al. 2021

Sustainability

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As an important part of trade in the Belt and Road Initiative (BRI) area, significant research attention has been devoted to direct energy transfer, whereas studies on energy embodied in non-energy products have largely been neglected. To present an overview of energy trade for the BRI members, this study combined multi-regional input-output (MRIO) analysis with complex network analysis to model energy use flows within the BRI’s intermediate and final trade network during 2000–2015. Results showed that intermediate energy trade volume is about 7.29-fold larger than that of final trade. Russia and Mainland China were found to be the main net exporter and net importer in intermediate energy trade, respectively, but in final energy trade their roles are reversed. In intermediate energy trade, resource exploitation and heavy industry are the leading intermediate exporter and importer respectively, whereas household consumption is the largest importer (accounting for about three-fifths of the total) in final energy trade. Based on the complex network analysis, the BRI countries were found to trade widely in the final network while cooperating deeply in the intermediate network, with obvious small-world features. Mainland China and Russia were identified as key economies in both intermediate and final trade networks. In addition, quadratic assignment procedure (QAP) analysis was adopted to explore the determinants of the BRI energy trade from 2000 to 2015. It was found that geographic distance, land adjacency, and culture and language have a consistently significant impact on intermediate trade. Closer geographic distance, being adjacent to land, a higher level of economic development, and a larger size of population can promote final trade. This study aimed to supplement existing studies on direct energy trade and provides implications for understanding the sustainable energy development in the BRI area.

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Section: Appendix a Information On The Methodsmentioning

confidence: 99%

Energy Network Embodied in Trade along the Belt and Road: Spatiotemporal Evolution and Influencing Factors

Xue

Yan

et al. 2021

Sustainability

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“…produção, mas também pela produtividade de todos os outros setores dos quais demanda insumos, direta ou indiretamente. Alguns estudos usam esta metodologia para mensurar progresso técnico (Aulin-Ahmavaara, 1999;Cas & Rymes, 1991;De-Juan & Febrero, 2000;Fevereiro et al, 2015;Garbellini & Wirkierman, 2014;Lind, 2020;Panethimitakis, 1993), enquanto outros para avaliar características específicas do sistema econômico, envolvendo interconexão produtiva e subsistemas (Ciriaci & Palma, 2016;Di Berardino & Onesti, 2020;Grodzicki & Skrzypek, 2020;Montresor & Marzetti, 2011;Villani & Fana, 2020). Ainda com esta metodologia, é possível mensurar a quantidade de trabalho gerada em determinado setor que foi estimulada pela produção destinada à demanda final de outro setor.…”

Section: Introductionunclassified

Produtividade total do trabalho e estrutura produtiva: uma análise da economia brasileira a partir de subsistemas

Santini¹,

Acypreste²

2022

BKR

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O progresso técnico de um país contribui para o crescimento econômico e para a variação de sua estrutura produtiva. Uma análise multissetorial da evolução da produtividade dos setores econômicos demanda medidas que deem conta de toda sua cadeia produtiva, permitindo capturar o efeito de propagação de progresso técnico entre os setores, fato comumente ignorado em medidas convencionais. Com efeito, este trabalho pretende avaliar a produtividade total do trabalho no Brasil, entre 2000 e 2018, a partir do arcabouço teórico dos subsistemas, que considera o trabalho direto e indireto demandado por dado setor, advindos dos outros setores e de si mesmo, para atender à demanda final. Diante disso, nota-se que os setores industriais apresentam encadeamentos produtivos mais robustos, mas que vêm apresentando baixas taxas de crescimento de produtividade e perda na composição dos empregos no país. O setor agrícola, por outro lado, apresentou taxas de crescimento da produtividade elevados, o que indica alta competitividade, mas com sensível redução de requerimentos de mão de obra, tanto diretos quanto indiretos. Embora este setor tenha menos encadeamentos produtivos, ele ajudou a propagar progresso técnico para os demais setores que adquirem seus produtos como insumos, direta ou indiretamente.

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“…The automotive industry has always been a significant contributor to the global economy since it represents one of the largest manufacturing industries [1]. In Europe, this industry represents 6.1% of the total workforce and large percentage [2] of total production and capital investment in the manufacturing sector-a turnover over 7% of EU gross domestic product (GDP) [3].…”

Section: Introductionmentioning

confidence: 99%

Key Performance Indicators Selection through an Analytic Network Process Model for Tooling and Die Industry

2021

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In the last few decades, the fast technological development has caused high competitiveness among companies, encouraging a pursuit for strategies that allow them to gain competitive advantage, such as the monitoring of performance by using key performance indicators (KPIs). However, its selection process is complex since there are several KPIs available to evaluate performance and different relationships between them. To overcome this challenge, the use of a multiple criteria decision-making model (MCDM) was proposed, namely the analytic network process (ANP) through which a reduced number of them are prioritized. To identify which KPIs are suitable for the press cast and die manufacturing industry, a literature review was made, and 58 unique KPIs were identified. Thus, to validate the proposed methodology, a case study was carried out in an automotive press molding industry. With the implementation of the proposed ANP model it was possible to identify 9 KPIs that ensure the correct molding process monitoring, while being aligned with the Balanced Scorecard criteria. The results show that the proposed model is suitable for selecting KPIs for the molding industry.

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Cost-competitiveness and structural change in value chains – vertically-integrated analysis of the European automotive sector

Cited by 30 publications

References 60 publications

Energy Network Embodied in Trade along the Belt and Road: Spatiotemporal Evolution and Influencing Factors

Energy Network Embodied in Trade along the Belt and Road: Spatiotemporal Evolution and Influencing Factors

Produtividade total do trabalho e estrutura produtiva: uma análise da economia brasileira a partir de subsistemas

Key Performance Indicators Selection through an Analytic Network Process Model for Tooling and Die Industry

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