Business process outsourcing enhanced by fuzzy linguistic consensus model

被引:17
作者
Ciasullo, Maria Vincenza [1 ]
Fenza, Giuseppe [1 ]
Loia, Vincenzo [1 ]
Orciuoli, Francesco [1 ]
Troisi, Orlando [1 ]
Herrera-Viedma, Enrique [2 ,3 ]
机构
[1] Univ Salerno, Dipartimento Sci Aziendali Management & Innovat S, I-84084 Fisciano, SA, Italy
[2] Univ Granada, Dept Comp Sci & Artificial Intelligence, Granada, Spain
[3] King Abdulaziz Univ, Fac Engn, Dept Elect & Comp Engn, Jeddah 21589, Saudi Arabia
关键词
Context awareness; Fuzzy linguistic consensus model; Value net; Reinforcement learning; Business processes outsourcing; GROUP DECISION-MAKING; SUPPORT-SYSTEM; INFORMATION;
D O I
10.1016/j.asoc.2017.12.020
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Business process outsourcing represents a strategic option to obtain the overall improvement of performance in business process management context. It consists in externalizing whole sub-processes (e.g., production, logistics, human resources) of a value chain. Last decade, the concept of value chain moved toward the more flexible concept of value net that implies the assembly of several value chains tailored to specifics, objectives, markets, etc. Thus, the composition of a value chain within a value net environments can be understood as the modeling of a macro business process in which sub-processes can be outsourced. Such composition activity foresees crucial decision-making moments that need to be sustained by a group of decision-makers owning several and heterogeneous competences in order to select the most suitable external providers to which delegate specific sub-processes. This work proposes a framework to enhance business process outsourcing by introducing group decision-making support that relies on a fuzzy linguistic consensus model. In addition, the framework implements algorithms to learn and assign different weights to decision-makers considering the context and time at which they participate in the group decision making. The framework is applied to an Italian footwear company by describing a numerical example. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:436 / 444
页数:9
相关论文
共 56 条
  • [1] Aagesen G, 2015, Handbook on business process management 1: introduction, methods, and information systems, P219, DOI [DOI 10.1007/978-3-642-45100-310, 10.1007/978-3-642-45100-3_10, DOI 10.1007/978-3-642-45100-3_10]
  • [2] A linguistic consensus model for Web 2.0 communities
    Alonso, S.
    Perez, I. J.
    Cabrerizo, F. J.
    Herrera-Viedma, E.
    [J]. APPLIED SOFT COMPUTING, 2013, 13 (01) : 149 - 157
  • [3] Group Decision Making with Incomplete Fuzzy Linguistic Preference Relations
    Alonso, S.
    Cabrerizo, F. J.
    Chiclana, F.
    Herrera, F.
    Herrera-Viedma, E.
    [J]. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2009, 24 (02) : 201 - 222
  • [4] [Anonymous], 1999, CEUR WORKSHOP P
  • [5] The seven deadly sins of outsourcing
    Barthélemy, J
    [J]. ACADEMY OF MANAGEMENT EXECUTIVE, 2003, 17 (02): : 87 - 98
  • [6] Lean or agile - A solution for supply chain management in the textiles and clothing industry?
    Bruce, M
    Daly, L
    Towers, N
    [J]. INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT, 2004, 24 (1-2) : 151 - 170
  • [7] Bryce DavidJ., 1998, EUR MANAG J, V16, P635
  • [8] Soft consensus measures in group decision making using unbalanced fuzzy linguistic information
    Cabrerizo, F. J.
    Al-Hmouz, R.
    Morfeq, A.
    Balamash, A. S.
    Martinez, M. A.
    Herrera-Viedma, E.
    [J]. SOFT COMPUTING, 2017, 21 (11) : 3037 - 3050
  • [9] Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks
    Cabrerizo, F. J.
    Moreno, J. M.
    Perez, I. J.
    Herrera-Viedma, E.
    [J]. SOFT COMPUTING, 2010, 14 (05) : 451 - 463
  • [10] Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence
    Capuano, Nicola
    Chiclana, Francisco
    Fujita, Hamido
    Herrera-Viedma, Enrique
    Loia, Vincenzo
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (03) : 1704 - 1718