BRADFORD SCHOLARS

    • Sign in
    View Item 
    •   Bradford Scholars
    • Management and Law
    • Management and Law Publications
    • View Item
    •   Bradford Scholars
    • Management and Law
    • Management and Law Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Bradford ScholarsCommunitiesAuthorsTitlesSubjectsPublication DateThis CollectionAuthorsTitlesSubjectsPublication Date

    My Account

    Sign in

    HELP

    Bradford Scholars FAQsCopyright Fact SheetPolicies Fact SheetDeposit Terms and ConditionsDigital Preservation Policy

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Managing food security through food waste and loss: Small data to big data

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    View/Open
    irani_et_al_2017.pdf (2.421Mb)
    Download
    irani_et_al_2018_gold.pdf (2.321Mb)
    Download
    Publication date
    2018-10
    Author
    Irani, Zahir
    Sharif, Amir M.
    Lee, Habin
    Aktas, E.
    Topaloğlu, Z.
    van't Wout, T.
    Keyword
    Food security; Qatar; Data framework; Food waste; Food loss; Fuzzy cognitive map; FCM; Interrelationships; Design science
    Rights
    © 2018 The Authors. This is an Open Access article distributed under the Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/)
    Peer-Reviewed
    Yes
    
    Metadata
    Show full item record
    Abstract
    This paper provides a management perspective of organisational factors that contributes to the reduction of food waste through the application of design science principles to explore causal relationships between food distribution (organisational) and consumption (societal) factors. Qualitative data were collected with an organisational perspective from commercial food consumers along with large-scale food importers, distributors, and retailers. Cause-effect models are built and “what-if” simulations are conducted through the development and application of a Fuzzy Cognitive Map (FCM) approaches to elucidate dynamic interrelationships. The simulation models developed provide a practical insight into existing and emergent food losses scenarios, suggesting the need for big data sets to allow for generalizable findings to be extrapolated from a more detailed quantitative exercise. This research offers itself as evidence to support policy makers in the development of policies that facilitate interventions to reduce food losses. It also contributes to the literature through sustaining, impacting and potentially improving levels of food security, underpinned by empirically constructed policy models that identify potential behavioural changes. It is the extension of these simulation models set against a backdrop of a proposed big data framework for food security, where this study sets avenues for future research for others to design and construct big data research in food supply chains. This research has therefore sought to provide policymakers with a means to evaluate new and existing policies, whilst also offering a practical basis through which food chains can be made more resilient through the consideration of management practices and policy decisions.
    URI
    http://hdl.handle.net/10454/14130
    Version
    Published version
    Citation
    Irani Z, Sharif AM, Lee H et al (2018) Managing food security through food waste and loss: Small data to big data. Computers and Operations Research. 98: 367-383.
    Link to publisher’s version
    https://doi.org/10.1016/j.cor.2017.10.007
    Type
    Article
    Collections
    Management and Law Publications

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.