Forecasting sustainability performances of firms using grey theory and Markov models

被引:0
|
作者
Abhinav, Pathak [1 ]
Rajesh, R. [2 ]
机构
[1] ABV Indian Inst Informat Technol & Management, Gwalior, India
[2] IIM Tiruchirappalli, Dept Operat Management & Decis Sci, Tiruchirappalli, India
关键词
IKEA's IWAY; Sustainability; Grey theory; Grey prediction; Markov models; SUPPLY CHAIN; BIG DATA; NETWORK; IMPACT;
D O I
10.1108/BIJ-12-2023-0856
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
PurposeSustainability has been receiving increasing attention in recent times, due to increasing pressures from consumers and stakeholders. Based on few selected indicators, we suggest a method for calculating and forecasting the degree of sustainability supply chain considering the case of the IKEA Group.Design/methodology/approachIn order to predict the sustainability of IKEA's supply chain, utilizing IWAY fulfillment scores, this research uses the concept and theory of grey prediction models and moving probability-based Markov models.FindingsAccording to the findings of prediction, we observe that the level of supply chain sustainability is declining for the case in the forecast year 2022. The results are perceived as per the outcomes of the first-order, one-variable-based grey prediction model (GM (1, 1) model) and the grey moving probability state Markov model-based error correction.Research limitations/implicationsOperationalizing sustainability, we consider the contribution a company's supply chain toward the advancement of human rights, ethical labor practices, environmental improvement and anti-corruption principles into the account of supply-chain sustainability.Practical implicationsIn order to understand the future trends in the supply chain sustainability performances of the firms and make corrective actions, managers may take a note on the results of prediction and they can subsequently work on the policy implications.Originality/valueWe build an advanced prediction model for forecasting the level of sustainability performances for a case firm using the indicator of human rights, ethical labor practices, environmental improvement and anti-corruption principles.
引用
收藏
页数:23
相关论文
共 50 条
  • [21] Forecasting Model Based on Improved Grey-Markov
    Cao Qun
    Liu Bingxiang
    Cheng Xiang
    ADVANCES IN MANUFACTURING TECHNOLOGY, PTS 1-4, 2012, 220-223 : 2758 - +
  • [22] Improved grey-Markov chain algorithm for forecasting
    Li Zhijun
    Wang Weiwei
    Chen Mian-yun
    KYBERNETES, 2009, 38 (3-4) : 329 - 338
  • [23] Forecasting Balancing Market Prices Using Hidden Markov Models
    Dimoulkas, Ilias
    Amelin, Mikael
    Hesamzadeh, Mohammad Reza
    2016 13TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM), 2016,
  • [24] Financial Sustainability Evaluation and Forecasting Using the Markov Chain: The Case of the Wine Business
    Rekova, Nataliya
    Telnova, Hanna
    Kachur, Oleh
    Golubkova, Iryna
    Balezentis, Tomas
    Streimikiene, Dalia
    SUSTAINABILITY, 2020, 12 (15)
  • [25] Explanation of terms of grey forecasting models
    Liu, Sifeng
    Yang, Yingjie
    GREY SYSTEMS-THEORY AND APPLICATION, 2017, 7 (01) : 123 - 128
  • [26] A historic Review of Grey Forecasting Models
    Xie, Naiming
    Wang, Ruizhi
    JOURNAL OF GREY SYSTEM, 2017, 29 (04): : 1 - 29
  • [27] A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies
    Yu, Min-Chun
    Wang, Chia-Nan
    Nguyen-Nhu-Y Ho
    SUSTAINABILITY, 2016, 8 (09):
  • [28] Shipment forecasting for supply chain collaborative transportation management using grey models with grey numbers
    Wen, Yuh-Horng
    TRANSPORTATION PLANNING AND TECHNOLOGY, 2011, 34 (06) : 605 - 624
  • [29] Long-term load forecasting using grey system theory
    Morita, Hironobu
    Zhang, De-Ping
    Tamura, Yasuo
    Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi), 1995, 115 (02): : 11 - 20
  • [30] The sustainability performances of sustainable business models
    Alonso-Martinez, Daniel
    De Marchi, Valentina
    Di Maria, Eleonora
    JOURNAL OF CLEANER PRODUCTION, 2021, 323