Tsan-Ming (Jason) Choi

Management Information Systems · 2004–2020

A researcher in the Science corpus: 21 papers; trusts 31 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

Whom Tsan-Ming (Jason) Choi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Andy A. Tsay
  2. Chun-Hung Chiu
  3. Nir Kshetri
  4. Gérard P. Cachon
  5. G. Huang
  6. Xianghua Gan
  7. Karen Donohue
  8. Suresh P. Sethi
  9. Houmin Yan
  10. Qin-Yu Zhu

Who trusts Tsan-Ming (Jason) Choi overall

  1. Chun-Hung Chiu
  2. Dmitry A. Ivanov
  3. Hubert Pun
  4. Alexander Spieske
  5. Zugang Liu
  6. Xin Wen
  7. Jacob Lohmer
  8. Jayashankar M. Swaminathan
  9. Juzhi Zhang
  10. Maciel Manoel de Queiroz

Papers from Tsan-Ming (Jason) Choi's perspective

Ordered by how strongly the researchers Tsan-Ming (Jason) Choi trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Supply Chain Coordination with Revenue-Sharing Contracts: Strengths and Limitations (Management Sciences)
  2. Supplier‐buyer contracting: Asymmetric cost information and cutoff level policy for buyer participation
  3. Designing Supply Contracts: Contract Type and Information Asymmetry (Management Sciences)
  4. Contracting and Information Sharing Under Supply Chain Competition (Management Sciences)
  5. Decentralized Supply Chains with Competing Retailers Under Demand Uncertainty (Management Sciences)
  6. Channel Coordination with a Risk‐Neutral Supplier and a Downside‐Risk‐Averse Retailer
  7. Cooperative Advertising and Pricing in a Dynamic Stochastic Supply Chain: Feedback Stackelberg Strategies (Portland International Conference on Management of Engineering and Technology)
  8. Data-intensive applications, challenges, techniques and technologies: A survey on Big Data (Information Sciences)
  9. Toward an ontology-driven blockchain design for supply-chain provenance (Intell. Syst. Account. Finance Manag.)
  10. Optimal Contract Design for Mixed Channels Under Information Asymmetry

Their papers