Retail System Scenario Modeling Using Fuzzy Cognitive Maps

被引:3
|
作者
Petukhova, Alina [1 ]
Fachada, Nuno [1 ]
机构
[1] Lusofona Univ, COPELABS, Campo Grande 376, P-1749024 Lisbon, Portugal
关键词
retail; complex systems; fuzzy cognitive maps; scenario planning; SERVICE PROFIT CHAIN; CUSTOMER LOYALTY; SATISFACTION; KNOWLEDGE;
D O I
10.3390/info13050251
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A retail business is a network of similar-format grocery stores with a sole proprietor and a well-established logistical infrastructure. The retail business is a stable market, with low growth, limited customer revenues, and intense competition. On the system level, the retail industry is a dynamic system that is challenging to represent due to uncertainty, nonlinearity, and imprecision. Due to the heterogeneous character of retail systems, direct scenario modeling is arduous. In this article, we propose a framework for retail system scenario planning that allows managers to analyze the effect of different quantitative and qualitative factors using fuzzy cognitive maps. Previously published fuzzy retail models were extended by adding external factors and combining expert knowledge with domain research results. We determined the most suitable composition of fuzzy operators for the retail system, highlighted the system's most influential concepts, and how the system responds to changes in external factors. The proposed framework aims to support senior management in conducting flexible long-term planning of a company's strategic development, and reach its desired business goals.
引用
下载
收藏
页数:18
相关论文
共 50 条
  • [21] A Fuzzy Cognitive Maps Modeling, Learning and Simulation Framework for Studying Complex System
    Leon, Maikel
    Napoles, Gonzalo
    Rodriguez, Ciro
    Garcia, Maria M.
    Bello, Rafael
    Vanhoof, Koen
    NEW CHALLENGES ON BIOINSPIRED APPLICATIONS: 4TH INTERNATIONAL WORK-CONFERENCE ON THE INTERPLAY BETWEEN NATURAL AND ARTIFICIAL COMPUTATION, IWINAC 2011, PART II, 2011, 6687 : 243 - 256
  • [22] Modeling of Fuzzy Cognitive Maps with a Metaheuristics-Based Rainfall Prediction System
    Al Duhayyim, Mesfer
    Mohamed, Heba. G. G.
    Alzahrani, Jaber. S. S.
    Alabdan, Rana
    Mousa, Mohamed
    Zamani, Abu Sarwar
    Yaseen, Ishfaq
    Alsaid, Mohamed Ibrahim
    SUSTAINABILITY, 2023, 15 (01)
  • [23] A Theoretical Mathematical Modeling of Parkinson's Disease Using Fuzzy Cognitive Maps
    Groumpos, Peter P.
    Anninou, Antigoni P.
    IEEE 12TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS & BIOENGINEERING, 2012, : 677 - 682
  • [24] Using fuzzy cognitive maps as a decision support system for political decisions
    Tsadiras, AK
    Kouskouvelis, I
    Margaritis, KG
    ADVANCES IN INFORMATICS, 2003, 2563 : 172 - 182
  • [25] Fuzzy cognitive maps in the modeling of granular time series
    Froelich, Wojciech
    Pedrycz, Witold
    KNOWLEDGE-BASED SYSTEMS, 2017, 115 : 110 - 122
  • [26] Design of Fuzzy Cognitive Maps for Modeling Time Series
    Pedrycz, Witold
    Jastrzebska, Agnieszka
    Homenda, Wladyslaw
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2016, 24 (01) : 120 - 130
  • [27] Fuzzy Cognitive Maps in modeling supervisory control systems
    Stylios, CD
    Groumpos, PP
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2000, 8 (02) : 83 - 98
  • [28] Intuitionistic Fuzzy Cognitive Maps for Corporate Performance Modeling
    Prochazka, Ondrej
    Hajek, Petr
    33RD INTERNATIONAL CONFERENCE MATHEMATICAL METHODS IN ECONOMICS (MME 2015), 2015, : 683 - 688
  • [29] Modeling dependence and feedback in ANP with fuzzy cognitive maps
    Mazurek, Jiri
    Kiszova, Zuzana
    PROCEEDINGS OF 30TH INTERNATIONAL CONFERENCE MATHEMATICAL METHODS IN ECONOMICS, PTS I AND II, 2012, : 558 - 563
  • [30] Object oriented fuzzy cognitive maps for network modeling
    Jamadagni, NSS
    PEACHFUZZ 2000 : 19TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, 2000, : 412 - 415