PurposeThis research seeks to develop a better understanding of internationalization patterns of agrifood firms and explains why different paths are adopted. Further, a conceptual framework to support public and private decision-making is proposed.Design/methodology/approachAn exploratory qualitative research framework was developed featuring case studies about three highly internationalized Brazilian meat processing firms. Top managers were interviewed, and documents were collected to support the intraand crosscase analyses.FindingsResults suggest that meat processing firms tend to adopt a dual internationalization pattern. Distribution-oriented foreign direct investment (FDI) is normally established gradually, whilst horizontal FDI – the establishment of foreign production facility – tends to be conducted through a fast-paced expansion mode. Interestingly, it was found that food safety issues play a central role in internationalization decisions.Originality/valueAn extension to the Uppsala model was provided by considering agrifood characteristics in the analysis. The results have broad appeal to managers and policymakers. Agribusiness managers could use the theoretical and empirical evidence to support their internationalization decisions. Policymakers can also use this research to gain a better understanding of how agrifood firms expand internationally to either attract or foster FDI.
Researchers have developed new catalysts for fuel cells (FC), whose performances are compared after applying different normalization procedures. However, there is not a standard procedure. The current produced from CO electrooxidation was compared for Pt 4 Ru 5 Sn 1 /C and homemade Pt/C nanoparticles (NPs) normalized by different methods and the use of different methods renders different interpretations. Since the whole field aims to maximize the cost-effectiveness, a complementary method to normalize currents and power in terms of the total cost of the nanocatalyst, the Catalyst-based Cost method (CbC), was proposed. CbC considers the cost of all metals employed to build the catalyst, not only those ones with available surfaces. By applying a simple smoothing method on the prices in a time series, we were able to forecast the prices and consequently the power density of a FC. CbC provides tools for industrials forecast the designing of nanomaterials with improved efficiency and low cost.Keywords: fuel cell, catalyst, normalization of current and power, cost of metal, forecasting activity IntroductionThe continuous growth of the energy demand opened a wide field of research for energy converters, among which fuel cells have been exhaustively studied. Fuel cells can produce energy with low environmental impact since they generate power by the oxidation of a fuel at the anode and reduction of O 2 at the cathode. Fuel cells can be fed by H 2 or small alcohols, as methanol and ethanol. The catalysts, both anodes and cathodes, are mainly based on Pt, which is historically an expensive material.1 This is the main reason why many efforts have been made to replace Pt (at least partially) in catalysts used in fuel cells.When a new nanoparticle catalyst is produced, the normalization of the electrochemical current generated by its use is imperative in electrocatalysis, since this procedure allows distinct surfaces to be directly compared for a given reaction in terms of their intrinsic electroactivities. In this context, different normalization methods generate multiple interpretations about the activity of a catalyst. This lack of consensus hinders the comparison of different materials in terms of their electrochemical performances and generates impasses that prevent a faster development of the research area.A method commonly used consists in normalizing the currents by the electrochemically active surface area (ECSA), which is highly useful but not easily accessed for many materials. For Pt-based catalysts (as PtRu/C Zanata et al. 1981 Vol. 27, No. 11, 2016 and PtRuSn/C) the ECSA is sometimes estimated by the charge involved in the H desorption region.2-5 For Pd-based catalysts, the ECSA is usually calculated by the charge involved in the reduction of a PdO monolayer. [6][7][8] The main concern about using the ECSA for multi-metallic catalysts calculated by these methods lies on the fact that the metal lattice parameter suffers intense modifications when an additional element is inserted into its structure. 9,10 In t...
O presente estudo teve como objetivo caracterizar e avaliar a eficiência dos terminais intermodais brasileiros. Os objetivos propostos nesta pesquisa foram alcançados por meio de um estudo quali-quantitativo. Com a utilização de três insumos e um único produto, a mensuração da eficiência dos terminais foi realizada por meio do modelo Variable Return to Scale orientado a produto da técnica Análise Envoltória de Dados. Dos 24 terminais analisados, 8 foram considerados 100% eficientes, dezesseis ineficientes, sendo que quinze terminais apresentaram nível de eficiência abaixo de 51,7%, que foi a média do setor encontrada. Cabe ressaltar que o trabalho limitou-se à mensuração da eficiência operacional, não levando em consideração aspectos financeiros. Os resultados da pesquisa apontam potencial de aumento de transbordo nos terminais intermodais brasileiros, mantendo insumos inalterados. Os resultados da pesquisa podem, portanto, servir como apoio à decisão para gestores, visando ao aumento da eficiência dos terminais e do transporte intermodal no país.
Purpose This study seeks to empirically and theoretically show how and why food chain specific advantages along with country-specific and firm-specific advantages impact the development of competences and shape distinct strategies for international growth.Design/methodology/approach Case studies were conducted with three Brazilian meatpacking firms with solid global operations. Top managers in charge of international operations were interviewed and documents were collected. Data were coded and submitted to triangulation. Content analysis was used as data analysis technique.Findings Results suggest that a meso-level of analysis is important to understand the development of competences and strategies for internationalization of meatpacking firms. Additionally, it was found that the internationalization process of meatpacking firms are supported by four supportive competences, namely: technical, production, sales and logistics competences. Findings also reveal that these companies tend to pursue either a raw material seeker or local taste supplier strategy.Originality/value International business scholars have struggled to incorporate meso-level characteristics into mainstream literature. This paper tries to fill in this gap by incorporating distinctive features from the food supply chain in the analysis. Two novel international strategy typologies were introduced by considering firm-, food chain- and country-specific advantages. It also proposes sound theoretical and managerial evidence to support public and private decision-making.
This article aims to present the differences between the profile of plants and the global value chains (GVC) of two aircraft manufacturers, Embraer and Boeing. After, literature review about the theories of internationalization, global value chains, and internationalization of manufacturing. It is concluded that Embraer leads a value chain called Relational. At the same time, Boeing opted for the type called Hierarchy after a failed experience with the Relational type of value chain during the development of the 787 Dreamliner model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.