Processing, Please wait...

  • Home
  • 📚 Journals
    • IJIEC - Industrial Engineering Computations
    • IJDNS - Data and Network Science
    • CCL - Current Chemistry Letters
    • AC - Accounting
    • DSL - Decision Science Letters
    • USCM - Uncertain Supply Chain Management
    • JPM - Journal of Project Management
    • HE - Healthcare Engineering
    • SCI - Scientometrica
    • ESM - Engineering Solid Mechanics
    • JFS - Journal of Future Sustainability
    • MSL - Management Science Letters
  • 📝 Submit Article
  • 📊 Statistics
  • About Us
  • 📺 Tutorial
  • Search:
  • Advanced Search

Growing Science » Authors » Xiaohu Qian

📚 Highly Cited Articles

  • Jaya Algorithm
  • Rao Algorithm
  • TLBO Algorithm
  • Discrete Firefly
  • ChatGPT and Blended Learning

Journals

  • IJIEC (777)
  • MSL (2648)
  • DSL (690)
  • CCL (544)
  • USCM (1099)
  • ESM (428)
  • AC (562)
  • JPM (323)
  • IJDS (992)
  • JFS (101)
  • HE (42)
  • SCI (41)

🔑 Keywords

Supply chain management(168)
Jordan(167)
Vietnam(153)
Customer satisfaction(122)
Performance(116)
Supply chain(113)
Competitive advantage(98)
Service quality(98)
Artificial intelligence(96)
Tehran Stock Exchange(94)
Sustainability(91)
SMEs(91)
optimization(88)
Trust(84)
Financial performance(84)
TOPSIS(83)
Job satisfaction(81)
Knowledge Management(80)
Social media(79)
Genetic Algorithm(78)


» Show all keywords

✍️ Authors

Naser Azad(82)
Zeplin Jiwa Husada Tarigan(67)
Mohammad Reza Iravani(64)
Endri Endri(45)
Muhammad Alshurideh(42)
Hotlan Siagian(40)
Dmaithan Almajali(38)
Jumadil Saputra(36)
Muhammad Turki Alshurideh(35)
Ahmad Makui(33)
Barween Al Kurdi(32)
Hassan Ghodrati(31)
Basrowi Basrowi(31)
Sautma Ronni Basana(31)
Mohammad Khodaei Valahzaghard(30)
Haitham M. Alzoubi(29)
Shankar Chakraborty(29)
Ni Nyoman Kerti Yasa(29)
Sulieman Ibraheem Shelash Al-Hawary(28)
Prasadja Ricardianto(28)


» Show all authors

🌍 Countries

1. Algeria (52)
2. Angola (1)
3. Argentina (22)
4. Armenia (2)
5. Australia (52)
6. Austria (2)
7. Bahrain (26)
8. Bangladesh (56)
9. Belarus (3)
10. Belgium (3)
11. Benin (2)
12. Benin Republic (1)
13. Bhutan (1)
14. Bosnia and Herzegovina (1)
15. Botswana (8)
16. Brazil (39)
17. Brunei (1)
18. Bulgaria (1)
19. Burkina Faso (1)
20. Cameroon (1)
Total: 121 countries

Show all countries
Sort articles by: Volume | Date | Most Rates | Most Views | Reviews | Alphabet
1.

An efficient multi-attribute multi-item auction mechanism with ex-ante and ex-post satisfaction for 4PL transportation service procurement Pages 571-588 Right click to download the paper Download PDF

Authors: Na Yuan, Xiaohu Qian, Min Huang, Haiming Liang, Andrew Wai Hung Ip, Kai-Leung Yung

doi 10.5267/j.ijiec.2023.3.001 Crossmark

Keywords: Transportation service procurement, Efficient multi-attribute reverse auction, Ex-ante and ex-post satisfaction, Mechanism design

Abstract:
Reverse auction is an effective tool for a 4PL to purchase transportation services. This paper investigated a new transportation services procurement problem for 4PL, which involves three features: the 4PL’s loss-averse behavior, price and non-price attributes, and multiple transportation requests. An efficient multi-attribute multi-item reverse auction mechanism considering the 4PL ex-ante and ex-post satisfaction (EES-MMRA) is proposed to purchase transportation services for the 4PL. In the EES-MMRA, integrating the allocation rule with the 4PL ex-ante satisfaction, a 0-1 programming model is constructed to determine winning 3PLs and obtain efficient allocations. Then, a payment rule considering the 4PL ex-post satisfaction is established to ensure truthful bidding of 3PLs. And we discuss some desirable properties (e.g., incentive compatibility, individual rationality, efficiency, and budget balance properties) to justify the EES-MMRA mechanism, subsequently. Next, several numerical experiments are conducted to demonstrate the effectiveness and applicability of the EES-MMRA mechanism. Furthermore, sensitivity analysis presents the influences of the weights of the non-price attributes, risk attitude coefficients, and loss aversion coefficients. Finally, we conduct comparison analysis to show the advantages of the EES-MMRA mechanism over the known Vickrey–Clark–Groves (P-VCG) mechanism.
Details
  • 17
  • 1
  • 2
  • 3
  • 4
  • 5

Journal: IJIEC | Year: 2023 | Volume: 14 | Issue: 3 | Views: 1053 | Reviews: 0

 
2.

Contracts design for serial delivery with connecting time spot: From a perspective of fourth party logistics Pages 523-542 Right click to download the paper Download PDF

Authors: Yang Dong, Xiaohu Qian, Min Huang, Wai-Ki Ching

doi 10.5267/j.ijiec.2022.7.003 Crossmark

Keywords: Third-party logistics, Fourth-party logistics, Contract design, Principal-Agent Theory, Connecting time spot

Abstract:
For a serial delivery system, the latter 3PL needs to be prepared at the transshipment node in advance to reduce the total delivery time. In this paper, we propose the concept of Connecting Time Spot (CTS) to help 4PL schedule the latter 3PL when to wait at the transshipment node. We study a serial delivery system with a 4PL and two 3PLs, where 4PL designs optimal contracts with two types of CTS (GCTS is derived by system parameter and DCTS is determined by 4PL’s optimization) to induce 3PLs to exert the optimal effort levels. We analyze the effects of CTS on the system profit in the centralized system. For the decentralized system, we particularly investigate the optimal contracts in three penalty modes which are according to the occupancy of the warehouses. The results show that CTS can avoid 3PLs’ idle resources and enhance the system profit for serial delivery both in the centralized system and the decentralized system. Compared with GCTS, DCTS has a better performance in enhancing the system profits. Also, the optimal incentive contracts achieve Pareto improvement for system profits. Interestingly, one 3PL’s delivery penalty mode will not affect the other 3PL’s optimal contracts.
Details
  • 0
  • 1
  • 2
  • 3
  • 4
  • 5

Journal: IJIEC | Year: 2022 | Volume: 13 | Issue: 4 | Views: 1331 | Reviews: 0

 

® 2010-2026 GrowingScience.Com