رفتار ارزیابی مناقصه در مزایده های تأمین تجهیزات آنلاین شامل کارشناسان فنی و کسب و کار

Multi-attribute reverse auction-based procurement has been widely used by large organizations. The attributes of the auctioned objects are usually divided into two groups: technical and business attributes. They are reviewed and scored by technical and business experts who act as referees in the bid evaluation process. To analyze their bid evaluation behavior, we built a model for a multi-attribute reverse auction. With correlations between the bid evaluations of the different referee groups across the attributes, the bid evaluation problem is not the usual multi-attribute decision-making problem. We assess the cause–effect relationship that is present, and show that antagonism between referee groups tends to grow over time. We tested how this works with data from simulated auctions. To diminish the potential for antagonism between the two referee groups, we propose a modified bid evaluation mechanism. We also conducted role-playing experiments involving the referee behaviors as a means for assessing the proposed mechanism. Our results suggest that the modified bid evaluation mechanism is beneficial.

Reverse auctions on the Internet can save purchasing expenses, reduce costs, and benefit auctioneers (Olson and Boyer, 2003 and Hur et al., 2007). They are widely used for centralized procurement and construction projects of large enterprise groups and government departments. Because the purchased supplies in reverse auctions usually possess multiple attributes, such as quality, performance, service level and price, the focus has typically been on multi-attribute reverse auctions ( David et al., 2006 and Cheng, 2008). Also, since there is more than one criterion for bid evaluation, the determination of the winner in a multi-attribute reverse auction is not as simple as when there is only a single attribute such as price. Generally, a bid evaluation process determines the winner. Because some attribute values of the supplies are described in other than quantifiable terms, they need to be initially assessed by using attribute scores ( Lin and Chen 2004). Then, the total score for all of the bids can be calculated based on the weighted sums of the scores of all of the attributes. The bid with the highest total score will be the winner of the reverse auction. Bid evaluation for large construction projects and equipment procurement is professional work for experts. Generally, the attributes for procurement auctions, including large projects and equipment, can be divided into two types: technical attributes and business attributes. They are usually reviewed and scored by technical and business experts. The two groups of bid evaluation experts have difference objectives and responsibilities to the enterprises that engage them. As a result, they may be cooperative and antagonistic in how they play their roles in the bid evaluation process. Their behavior will affect the fairness of the auction results. From bid evaluation data obtained from real-world enterprises, we found that the antagonism between the two expert referee groups tends to grow as they participate in more auctions. This may affect the perceived fairness of the auctions and cause the procuring organization to experience an economic loss. This research is intended to analyze the behavior of technical and business experts, and to design and assess a new mechanism to reduce antagonism between the groups. Reverse auctions have studied for a long time (Tunca and Wu 2009), and increasing attention has been paid to the models and mechanisms they use. Wagner and Schwab (2004) surveyed research and applications of web-based reverse auctions. Amelinckx et al. (2008) studied the relationship between sellers and buyers in this context, and Ray et al. (2011a) assessed the efficiency of reverse auction mechanisms when the number of bidders is limited. Multi-attribute reverse auctions have been a key area of study in the literature (David et al. 2006). Perrone et al. (2010) presented an overview of multi-attribute reverse auctions and discussed the attributes of price and time in product design and development. The winner determination problem is a multi-attribute decision-making problem that is interesting due to its computational complexity ( Sipahi and Esen 2010). In practice, e-procurement auctioneers require information on the standards that must be met for the different attributes of the supplies that are to be procured ( Costa et al., 2002 and Lai et al., 2004). Then, expert referees score all of the attributes according to the agreed-upon standards for the bid evaluation process. Winner determination is based on the total scores for all of the bids. Ray et al. (2011b) presented a Markov decision process model for the winner determination problem in multi-attribute reverse auctions. Padhi and Mohapatra (2010) solved the problem of bid evaluation with a binary goal programming model, and Hosny and Elhakeem (2012) suggested a novel bid evaluation approach called optimum markup estimation. In recent years, behavioral operations management has become an active research area (Bendoly et al., 2006 and Loch and Wu, 2007). When the traditional assumption of perfect rationality is relaxed, individual behavior is no longer negligible in the operational performance of any system with human participation (Leeuw and van den Berg 2010). Most of the prior work has been on the behaviors of bidders and auctioneers in auction games (Peters and Bodkin, 2007 and Onur, 2010). Expert referee behavior for bid evaluation has not received much attention. An exception is Rodriguez et al. (2007), who studied referee behavior for conference bidding. The authors conducted a behavioral analysis of bid evaluation in a multi-attribute reverse auction for a Chinese conference (Wang 2010). To study bid evaluation behavior for groups of expert referees, we adopted a number of empirical approaches in this research. We initially describe a process model for the bid evaluation of multi-attribute reverse auctions. Then, we will discuss problems with the current bid evaluation mechanism, and analyze auction data from an actual organization. To reduce antagonism between the two expert referee groups, we propose a modified bid evaluation mechanism. To verify the effectiveness of the mechanism, we will conduct a role-playing experiment on the behavior of two expert referee groups. The results show that the new bid evaluation mechanism can efficiently reduce antagonism between the two groups, and increase the perceived fairness of the auction results. Hereafter, Section 2 describes the online procurement process, and our model for multi-attribute reverse auctions. Section 3 discusses problems with the bid evaluation process. Section 4 analyzes the causal relationship among factors and roles in reverse auction bid evaluations, and we present a modified mechanism. Section 5 presents the design and results of a role-playing experiment on bid evaluation behavior, and Section 6 concludes with thoughts on what has been learned in this research.

Multi-attribute reverse auctions can allow large enterprises to save purchasing expenses and reduce costs for online centralized procurement. The current bid evaluation mechanism may be biased due to antagonistic feelings that arise across different referee groups. This, in turn, may lead to unfair, auction results. To solve the problem, we propose a mathematical model for multi-attribute auctions evaluated by such referees. We pointed out that, once a correlation exists the evaluation attributes put forth by different referee groups, the bid evaluation problem will no longer be a standard multi-attribute decision-making problem. By analyzing the cause–effect relationship for the formation of cross-referee group antagonism, and bid evaluation data, we showed that the antagonistic feelings between the referee groups grows as they participate together in more auctions, based on reverse auctions from a large enterprise group in China. We proposed a redesigned bid evaluation mechanism to help to alleviate the referees’ antagonism. There are three main points. (1) The first is creating a third group of cross-functional referees to evaluate the different bids that are received from the technical and business referees together, and to use it as a means of offsetting the antagonism bias that will build up over time with two separate groups of expert referees. (2) The second is using bid evaluation criteria that can be shared across the two kinds of referee groups. And (3) the third is giving each referee group access to relevant information so the cross-group information structure is symmetric. To confirm antagonism between the two groups and evaluate the recommended bid evaluation mechanism, we conducted role-playing experiments on the referees’ behavior with subjects acting as technical and business referee experts. The experimental results provided evidence of cross-referee group antagonism, and showed that the recommended bid evaluation mechanism helps to mitigate.