1 option
Data-driven decision-making research for supply chain finance / guest editors, Jie Wu and Ron Fisher.
- Format:
- Book
- Series:
- Industrial management & data systems (Unnumbered) ; Volume 121, Number 4.
- Industrial Management and Data Systems ; Volume 121, Number 4
- Language:
- English
- Subjects (All):
- Business logistics--Finance.
- Business logistics.
- Physical Description:
- 1 online resource (264 pages)
- Place of Publication:
- [Place of publication not identified] : Emerald Publishing Limited, 2021.
- Summary:
- This issue is about Data-driven Decision-making Research for Supply Chain Finance
- Contents:
- Cover
- Guest editorial
- Performance of China's ruralsupply chain finance: from theperspective of maximization of intermediate output
- A blockchain-driven cyber-credit evaluation approach for establishing reliable cooperation among unauthentic MSMEs in social manufacturing
- How monetary policies and ownership structure affect banksupply chain efficiency:a DEA-based case study
- Centralized selection of standardized modular containers:a multi-criteria method considering freight behavior andshipper segment
- A data-driven and network-aware approach for credit risk predictionin supply chain finance
- A data envelopment analysis approach by partial impacts between inputs and desirable undesirable outputs for sustainable supplier selection problem
- Agricultural loan efficiency in centralized bank supply chains with fairness concern:a DEA-based analysis
- Impact of data-driven online financial consumption on supplychain services
- Data-driven approach to find thebest partner for merger and acquisitions in banking industry
- Assessing the efficiency offinancial supply chain for Chinesecommercial banks: a two-stage AR-DEA model
- Analysis of two financing modes ingreen supply chains when considering the role of data collection
- Bank supply chain efficiency analysis based on regional heterogeneity: a data-drivenempirical study.
- Notes:
- Description based on print version record.
- ISBN:
- 1-80117-761-9
- OCLC:
- 1261364425
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.