UK food sustainability and global food supply chains: a sustainability impact study of Ghana's fresh vegetable exports to the UK
Notice bibliographique
Résumé
The purpose of this research is to explore the opportunities for reducing sustainability implications associated with the UK's global food supply chains by analysing Ghana's fresh vegetables exports. Existing literature assesses sustainability implications focusing on the traditional sustainability dimensions; namely, the environmental, social, and economic dimensions. Further, studies on the assessment of the UK food sustainability are yet to consider sustainability concerns generated by global food sources. To facilitate a holistic evaluation of the UK's global food supply chains and propagate its vision of global leadership in food sustainability, there is a need to consider all other relevant sustainability dimensions and their impacts associated with the activities and operations of global food suppliers. Case study data involving interviews and focus groups, together with survey data, are obtained from producers of Ghanaian fresh vegetables, such as smallholder farmers, outgrowers, local farmers, and exporters. The interviews and focus groups are first analysed using NVivo 11 software, following a thematic approach. Multilinear Regression (MLR) is performed using the Statistical Package for the Social Sciences (SPSS) to analyse the survey, in order to examine the relationship between sustainable food supply chains (sustainable FSC) and sustainability dimensions identified from the thematic analysis of the interviews and focus groups. \n \nThese findings indicate that six sustainability dimensions and their associated impacts are important in analysing Ghana's fresh vegetable exports to the UK. These are environmental, social, and economic dimensions, regulatory frameworks, collaboration, and producers' complexities in developing sustainable food supply chains (sustainable FSC). Interestingly, the survey results suggest that four of these dimensions are statistically significant; these are environmental, social, regulatory frameworks, and collaboration. The survey further revealed that an increase in regulatory frameworks and mechanisms can reduce sustainable FSC; whereas an increase in the practices and activities of the environmental, social, and collaborative dimensions increases sustainable FSC, thus improving overall sustainability. Revelations and findings from both the thematic and survey analysis were utilised to develop, test and validate the Sustainability Impact Assessment (SIA) model (thus, a conceptual framework of the study). \n \nThis study contributes to the body of knowledge in several ways. To theory, an SIA model is suggested, demonstrating the capture of all important sustainability dimensions; namely, environmental, economic, social, regulatory, collaboration, and complexities of food supply chains. It extends the discussion on sustainability impact assessments and sustainability development and encourages research in sustainability assessment. In practice, this SIA model can facilitate easy capture, examination, and evaluation of all relevant sustainability implications and allow new insights into the development and assessment of the stream of sustainability development. \n \nAmong many other implications such as promoting collaboration, policymakers need to encourage FairTrade for producers in developing countries, and regulatory mechanisms should be re-designed to enhance profitability by using simple conformity and economic incentives. Further, food trade partners and FSC professionals should encourage smart strategies and technologies to enhance logistics that minimise food waste and energy consumption, while boosting producers' welfare. Moreover, governments and policymakers should ensure that the sustainability concerns of overseas countries are captured in food policies and strategies to help facilitate global leadership in food sustainability.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».