Forecasting the supply chain environment for food SMEs in Ireland: A Delphi approach

被引:0
|
作者
Henchion, M [1 ]
McIntyre, B [1 ]
Commins, P [1 ]
机构
[1] Natl Food Ctr, Dublin 15, Ireland
关键词
forecast; Delphi technique; supply chain environment;
D O I
暂无
中图分类号
F3 [农业经济];
学科分类号
0202 ; 020205 ; 1203 ;
摘要
For long-term planning and strategy development, SME owner/operators need to be aware not only of what is happening at present but also to have an understanding of what might be expected for the future. One group-based technique that may be used to forecast the future is the Delphi technique. Its application to forecasting the supply chain environment in which food SMEs in Ireland operate to 2007 is the subject of this paper. Following an outline of the Delphi technique, the paper presents some of the key findings of the methodology and draws some conclusions on the usefulness of the Delphi technique and on the future supply chain environment for food SMEs in Ireland. These include recognition that the Delphi produced a great quantity of information and provided the researcher with a good understanding of the issues involved. Furthermore, the results of the Delphi technique indicate that developments in the food supply chain environment are creating both opportunities and threats for SMEs. Opportunities are arising in a number of product areas and market sectors whilst threats are arising from increased barriers to entry and exit, greater investment requirements as well as higher operational costs and a greater requirement for more expensive, skilled employees. The net effect of these opportunities and threats will vary by company depending on skills, resources and the ability to change.
引用
收藏
页码:780 / 791
页数:12
相关论文
共 50 条
  • [31] Forecasting SMEs’ credit risk in supply chain finance with a sampling strategy based on machine learning techniques
    Liukai Wang
    Fu Jia
    Lujie Chen
    Qifa Xu
    Annals of Operations Research, 2023, 331 : 1 - 33
  • [32] Demand forecasting accuracy in the pharmaceutical supply chain: a machine learning approach
    Yani, Luh Putu Eka
    Aamer, Ammar
    INTERNATIONAL JOURNAL OF PHARMACEUTICAL AND HEALTHCARE MARKETING, 2023, 17 (01) : 1 - 23
  • [33] Modified top down approach for hierarchical forecasting in a beverage supply chain
    Mircetic, Dejan
    Nikolicic, Svetlana
    Stojanovic, Durdica
    Maslaric, Marinko
    19TH EURO WORKING GROUP ON TRANSPORTATION MEETING (EWGT2016), 2017, 22 : 193 - 202
  • [34] Forecasting blockchain adoption in supply chains based on machine learning: evidence from Palestinian food SMEs
    Hamdan, Ihab K. A.
    Aziguli, Wulamu
    Zhang, Dezheng
    Sumarliah, Eli
    Usmanova, Kamila
    BRITISH FOOD JOURNAL, 2022, 124 (12): : 4592 - 4609
  • [35] Supply Chain Management in SMEs: A case study
    Indian Institute of Foreign Trade , B-21, Kutab Institutional Area, New Delhi 110016, India
    不详
    不详
    Int. J. Manuf. Res., 2012, 2 (165-180):
  • [36] Supply chain management maturity and performance in SMEs
    Soderberg, Lennart
    Bengtsson, Lars
    OPERATIONS MANAGEMENT RESEARCH, 2010, 3 (1-2) : 90 - 97
  • [37] Supply chain management maturity and performance in SMEs
    Lennart Söderberg
    Lars Bengtsson
    Operations Management Research, 2010, 3 : 90 - 97
  • [38] CSR and the Supply Chain: Effects on the Results of SMEs
    Enrique Valdez-Juarez, Luis
    Gallardo-Vazquez, Dolores
    Alicia Ramos-Escobar, Elva
    SUSTAINABILITY, 2018, 10 (07)
  • [39] Mapping of supply chain learning: a framework for SMEs
    Thakkar, Jitesh
    Kanda, Arun
    Deshmukh, S.
    LEARNING ORGANIZATION, 2011, 18 (04): : 313 - +
  • [40] Potential Impact of Industry 4.0 in Sustainable Food Supply Chain Environment
    Ojo, Olumide Olajide
    Shah, Satya
    Coutroubis, Alec
    Torres Jimenez, Mercedes
    Munoz Ocana, Yolanda
    2018 IEEE INTERNATIONAL CONFERENCE ON TECHNOLOGY MANAGEMENT, OPERATIONS AND DECISIONS (ICTMOD), 2018, : 172 - 177