Congjun Rao

Compound mechanism design of supplier selection based on multi-attribute auction and risk management of supply chain

Supplier selection for a type of divisible goods was investigated.We design a two-stage compound mechanism of selecting suppliers.This mechanism considers both the risk attributes and commercial attributes.The first stage can effectively motivate suppliers to report true information.Method of grey correlation degree of mixed sequence is proposed to rank supplier(s). The quality of the supplier base affects the competitiveness of firms and the attendant supply chain. The supplier selection decision is key to effective supply chain management. This paper investigates the problem of supplier selection under multi-source procurement for a type of divisible goods (such as coal, oil, and natural gas). By considering both the risk attributes and the attributes under a commercial criterion, we design a new two-stage compound mechanism for supplier selection based on multi-attribute auction and supply chain risk management. In the first stage, a multi-auction mechanism is established to determine the shortlist among all qualified suppliers based on four attributes (quality, price, quantity flexibility, and delivery time reliability) under a commercial criterion. In the second stage, seven risk attributes against the shortlisted suppliers are further considered, and a new ranking method based on grey correlation degree of mixed sequence is proposed to rank the finalists and to select the final winners. Moreover, the implementation, availability, and feasibility of the two-stage compound mechanism are highlighted by using an example of the multi-source procurement of electricity coal. This presented compound mechanism may well improve the procurement efficiency of divisible goods and greatly reduce the procurement risk.

Decision Mechanism for Supplier Selection Under Sustainability

Against the backdrop of responsible economic development, sustainable supply chain management (SSCM) is key to achieving the sustainable development for enterprise and industry. In this regard, sustainable supplier selection is crucial in SSCM. By integrating the three dimensions of sustainability, economic, environmental and social, this paper presents a new evaluation system for supplier selection from a sustainability perspective. Specifically, we design a decision mechanism for sustainable supplier selection based on linguistic 2-tuple grey correlation degree. In this proposed mechanism, the hybrid attribute values whereby real numbers, interval numbers and linguistic fuzzy variables coexist are transformed into linguistic 2-tuples. A ranking method based on linguistic 2-tuple grey correlation degree is then presented to rank the suppliers. An application example is presented to highlight the implementation, availability and feasibility of the proposed decision making mechanism.

Grey Coupled Prediction Model for Traffic Flow with Panel Data Characteristics

This paper studies the grey coupled prediction problem of traffic data with panel data characteristics. Traffic flow data collected continuously at the same site typically has panel data characteristics. The longitudinal data (daily flow) is time-series data, which show an obvious intra-day trend and can be predicted using the autoregressive integrated moving average (ARIMA) model. The cross-sectional data is composed of observations at the same time intervals on different days and shows weekly seasonality and limited data characteristics; this data can be predicted using the rolling seasonal grey model (RSDGM(1,1)). The length of the rolling sequence is determined using matrix perturbation analysis. Then, a coupled model is established based on the ARIMA and RSDGM(1,1) models; the coupled prediction is achieved at the intersection of the time-series data and cross-sectional data, and the weights are determined using grey relational analysis. Finally, numerical experiments on 16 groups of cross-sectional data show that the RSDGM(1,1) model has good adaptability and stability and can effectively predict changes in traffic flow. The performance of the coupled model is also better than that of the benchmark model, the coupled model with equal weights and the Bayesian combination model.

Bidding Behavior and Equilibrium Excursion of Uniform Price Auction Mechanism

Multiple equilibria (equilibrium excursion) affects the auction proceeds, and is bad for estimating auction efficiency. This paper examines the relationship between bidding behavior and equilibrium excursion. We analyze a uniform price auction mechanism based on a rationing strategy and common value information. In this uniform price auction mechanism, bidders (strategic and non-strategic) participate in an auction simultaneously, and the auctioneer rations the strategic bidders after observing their bids. The conclusions drawn suggest that a rationing strategy can effectively limit the strategic bidders from manipulating the auction, and the Nash equilibrium may not be unique (i.e., there exists an equilibrium excursion). As the number of bidders increases, or when the quantity that can be allocated to the non-strategic bidders is unconstrained, there exists asymptotically a unique equilibrium price which is the highest price the auctioneer could obtain. Based on these conclusions, we provide some strategies and suggestions on how to induce the equilibrium excursion state to a desired unique equilibrium state.