scholarly journals Quantity and quality food losses across the value Chain: A Comparative analysis

Food Policy ◽  
2020 ◽  
pp. 101958
Author(s):  
Luciana Delgado ◽  
Monica Schuster ◽  
Maximo Torero
2020 ◽  
Vol 12 (15) ◽  
pp. 6093 ◽  
Author(s):  
Julia Kleineidam

The literature contains many analyses of measures against food loss. However, there exists no structured analysis of the objective of these measures. This study employs a systematic literature analysis and open expert interviews, combining the perspectives of science and practice. For each analyzed case, we identified the objectives behind the implemented measures. Using qualitative clustering, we categorized the located objectives into fields of action. The identified 13 fields of action provide an overview of the objectives of food loss prevention measures. The results indicate that different levels of importance can be assigned to these fields of action. In particular, the results show the relevance of increased network cooperation and transparency within a company and along the entire value chain. Furthermore, the study indicates that the creation of transparency provides the greatest overall added value in terms of reducing food losses.


Author(s):  
Demissie Damite Degato

The traditional approach to innovation assessment has mainly focused on the economic outcomes and failed to capture the ecological and social dimensions of sustainability. By giving high attention to the role of specific kind of innovation (technological innovation), there is little empirical work on whether combining different kinds of innovation leads to progress in social-ecological sustainability in developing countries. The sustainability orientation in the assessment of innovation performance becomes increasingly important for achieve successful transformation towards sustainability. The research question of this study is under what condition or combination of conditions the intervention for innovation reconciles the trade-offs between socioeconomic and ecological performance and thus improve progress towards sustainability in poor countries. Combing concepts and methods from literature on strategic corporate social responsibility (CSR), value chain upgrading, sustainability, and technological capability, this study identifies different mechanisms and conditions for building innovation capacity and then empirically evaluates the relationship between the degree of innovation capacity and the progress towards social-ecological sustainability by taking four cases from Ethiopia. The data for this study is collected using key informant interviews, focus group discussion, and biodiversity and innovation scorecard questionnaire. Mixed methods combing comprehensive fuzzy evaluation, biodiversity scorecard and qualitative comparative analysis are used for analysis. The study found that combing value chain innovation and green governance innovation either with technological upgrading or innovation platform learning are sufficient conditions for achieving social-ecological sustainability. We also found that innovation in green governance and in value chain are necessary conditions for sustainability. By developing and applying fuzzy comprehensive evaluation model for measuring innovation capacity and fuzzy set qualitative comparative analysis for identifying necessary and sufficient conditions for sustainability, this study made an important methodological contribution to existing literature.


2021 ◽  
Author(s):  
Luciana Delgado ◽  
Monica Schuster ◽  
Maximo Torero
Keyword(s):  

2019 ◽  
Vol 16 (2) ◽  
pp. 58-71
Author(s):  
Audrone Kvedariene

Abstract Research purpose. High technology creation, as a rule, requires national support systems although the flow of the created value in an international level is unexplored. The national innovation systems are becoming globalized; thus the distinct process of creation, dissemination and implementation of high technologies is becoming globally fragmented and therefore the added value distribution within the global value chain (GVC) should be investigated. Design/Methodology/Approach. The brief and extensive academic literature review dedicated to high technology creation is introduced, although the empirical investigation is narrowed to the scientific research and development sector, depicted as M72 by NACE statistical classification. Thus empirical research design is based on the sectoral level data, considering M72 sector as the main economic activity for high technology creation. The data for the comparative analysis of countries is retrieved from the 2014 world input–output data (WIOD) which enables to exclude double counting of added value inherent for the convenient import and export data and holds information of intermediate and final consumption of added value within a country and between different countries. The descriptive statistic based on WIOD data is provided and further prescriptive statistics for the data interpretation is conducted. While developing the predictive models, the number of investigated countries varies while the data for M72 sector is not available for all countries provided in WIOD and including to the model basic science and technology indicators as independent variables, retrieved from the Organisation for Economic Co-operation and Development database, the number of countries reduced additionally, also due to the data shortage. Findings. The key result is the provided methodology for the positioning of the countries evaluating the involvement in the upstream and downstream GVC processes, hereby introducing new indicators that may have an impact on the sector’s performance. Originality/Value/Practical implications. The evaluation of high technologies creation performance would provide insights into the international management and innovation policies, and the matrix concept for the positioning countries by the pattern of involvement to the GVCs could be applied to other sectors.


2019 ◽  
Vol 11 (23) ◽  
pp. 6576 ◽  
Author(s):  
Sabine Ludwig-Ohm ◽  
Walter Dirksmeyer ◽  
Kathrin Klockgether

Food losses occur in all agricultural value chains, but are especially high in the fruit and vegetable sector. This study quantifies losses of selected fruits (strawberries, apples) and vegetables (lettuce, carrots), identifies the main reasons for food losses, and assesses effective measures for the reduction of these losses. Data were collected in structured interviews with value chain actors from production to food retail and validated in regional expert workshops. Results show that in average years, about 25% of the analysed vegetables are lost at farm level. The range of fruit losses differs widely, from 15% to 20% for strawberries and only 6% to 16% for apples. Weather is a major factor for crop losses, since it can strongly affect product appearance and hence marketability in the food retail sector. There is a lack of alternative market channels for products, which do not meet the high-quality standards for fresh products in the retail sector. Effective measures to reduce food losses are protected cultivation in greenhouses or under hail nets, continuous cooling systems, improved packaging and training of staff. More cooperation and coordination between producers, wholesalers and retailers could also increase the share of marketable products.


Author(s):  
Jiazi Zhou ◽  
Xin Wen

As the internal requirement of the development of China’s traditional manufacturing industry, intelligent transformation has gradually become the main goal of China’s regional manufacturing transformation. From the perspective of manufacturing value chain, this paper proposes a conceptual model of intelligent transformation of manufacturing industry. Taking 22 sample cities as cases, the paper uses fuzzy set qualitative comparative analysis method to identify the necessary factors of intelligent transformation of manufacturing industry and the configuration analysis of each factor combination, and then obtains three realization paths to promote intelligent transformation. The results show that intelligent technology innovation and intelligent industry investment are the necessary conditions for the intelligent transformation of manufacturing industry, and there are three configuration paths: collaborative R&D and processing, external factor driven and value chain climbing, which promote the intelligent transformation of manufacturing industry. This paper enriches the research on intelligent transformation of manufacturing industry from the perspective of value chain, and uses the qualitative comparative analysis method of fuzzy set to provide countermeasures and suggestions for the direction and path of intelligent transformation of manufacturing industry.


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