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We compare allocation rules in uniform price divisible-good auctions. Theoretically, a “standard allocation rule (STANDARD)” and a “uniform allocation rule (UNIFORM)” admit different types of low-price equilibria, which are eliminated by a “hybrid allocation rule (HYBRID).” We use a controlled laboratory experiment to compare the empirical performances of these allocation rules.

We conduct three-bidder uniform price divisible-good auctions varying the different allocation rules (standard, uniform, or hybrid) and whether or not explicit communication between bidders is allowed. For the case where explicit communication is allowed we also study six-bidder auctions.

We find that prices are similar across allocation rules. Under all three allocation rules, prices are competitive when bidders cannot explicitly communicate. With explicit communication, prices are collusive, and we observe collusive prices even when collusive agreements are broken. Collusive agreements are particularly fragile when the gain from a unilateral deviation is larger, and an implication of this is that collusive agreements are more robust under STANDARD.

We do not find conclusive evidence of differences in performance among allocation rules. However, there is suggestive evidence that STANDARD may be more vulnerable to collusion.

Divisible-good uniform price auctions are used in financial markets, but it is not possible to use naturally occurring data to test how alternatives to the standard format would perform. Using laboratory methods we provide an initial test of alternative allocation rules.

Digital disruption offers an innovative opportunity to address housing affordability issues through the use of market design theory and two-sided matching markets. The purpose of this paper is to scope a model for how “uberisation” can revolutionise the traditional apartment delivery model in Australia, leading to improved housing affordability.

This paper uses semi-structured interviews with operators of online real estate platforms and deliberative developers to examine how the principles of “uberisation”, that is two-sided matching markets, are driving innovation in the apartment supply process.

Findings confirm that real estate internet platforms and deliberative developers innovators are informed by the benefits of aggregating demand to reduce development risk, thus enabling apartments to be provided at a substantially lower price than by traditional methods.

The number of interviews is small reflecting the limited number of market actors currently engaged in the innovations investigated.

This research is innovative as it introduces theoretical understandings gained from market design theory and applies those concepts to disrupt the apartment development process.

Objective – This chapter examines the performance of the market to discover efficient equilibrium under alternative auction designs.

Background – Auctions are increasingly being used to allocate emissions allowances (“permits”) for cap and trade and common-pool resource management programs. These auctions create thick markets that can provide important information about changes in current market conditions.

Methodology – This chapter uses experimental methods to examine the extent to which the predicted increase in the Walrasian price due to a shift in willingness to pay (perhaps due to a shift in costs of pollution abatement) is reflected in observed sales prices under alternative auction formats.

Results – Price tracking is comparably good for uniform-price sealed-bid auctions and for multi-round clock auctions, with or without end-of-round information about excess demand. More price inertia is observed for “pay as bid” (discriminatory) auctions, especially for a continuous discriminatory format in which bids could be changed at will, in part because “sniping” in the final moments blocked the full effect of the demand shock.

Conclusion – Uniform-price auctions (clock and sealed-bid uniform-price, and continuous uniform-price) generate changes in purchase prices that are reasonably close to predicted changes. There is some evidence of tacit collusion causing prices to be too low relative to predictions in most cases. The worst price tracking was observed for discriminatory auctions.

Application – Uniform-price auctions appear to perform at least as well as other auction designs with respect to discovery of efficient market prices when there are unexpected and unannounced changes in willingness to pay for permits.

Purpose – This study constitutes a first attempt to experimentally test the performance of a 100% auction versus a 100% free allocation of CO2 permits under the rules and parameters that mimic the EU ETS (imperfect competition, uncertainty in emissions' control, and allowing banking), with environmental targets more restrictive than the current ones but foreseeable for the near future.

Methodology/approach – Two experimental treatments were run to achieve our goal. Both included the rules and the parameters that parallel the EU ETS structure, the only difference being the rule for the primary allocation of permits.

Findings – Our experimental results indicate that the EU ETS has the potential to reduce CO2 emissions, achieving targets considerably more restrictive than the current ones at high efficiency levels, both with auctioned and free emission permits.

Practical implications – Concerns about undue scarcity, and corresponding high prices, in secondary markets generated by a primary auction market are not warranted under the proposed dynamic auction format. This adds arguments favoring auctioning over grandfathering as the rule for the initial allocation of emission permits in the EU ETS.

Originality/value of chapter – This study implements a theoretically appropriate auction format for the primary allocation of emission permits (the Ausubel (2004) auction) and incorporates a first attempt to include in the analysis measures of the risk preferences of subjects participating in emission permits experiments. These characteristics are for the first time implemented under a complex experimental design (including uncertainty of emission abatement, and banking), trying to parallel the EU ETS trading environment.

This study addresses the production optimization of a cellular manufacturing system (CMS) in magnetic production enterprises. Magnetic products and raw materials are more critical to transport than general products because the attraction or repulsion between magnetic poles can easily cause traffic jams. This study needs to address a method to promote the scheduling efficiency of the problem.

To address this problem, this study formulated a mixed-integer linear programming (MILP) model to describe the problem and proposed an auction and negotiation-based approach with a local search to solve it. Auction- and negotiation-based approaches can obtain feasible and high-quality solutions. A local search operator was proposed to optimize the feasible solutions using an improved conjunctive graph model.

Verification tests were performed on a series of numerical examples. The results demonstrated that the proposed auction and negotiation-based approach with a local search operator is better than existing solution methods for the problem identified. Statistical analysis of the experiment results using the Statistical Package for the Social Sciences (SPSS) software demonstrated that the proposed approach is efficient, stable and suitable for solving large-scale numerical instances.

An improved auction and negotiation-based approach was proposed; The conjunctive graph model was also improved to describe the problem of CMS with traffic jam constraint and build the local search operator; The authors’ proposed approach can get better solution than the existing algorithms by testing benchmark instances and real-world instances from enterprises.

To transform donations “in kind” into cash, charities of all sizes use auctions and raffles. Despite this, neither the theory nor the practice of efficient fund-raising – and, in particular, charity auctions – has received sufficient attention from economists, especially the fact that participation in fund-raisers is endogenous. We describe, in detail, the design and implementation of an experiment to examine 15 charity auction mechanisms. While some of the mechanisms have already received attention from both theorists and empiricists, ours is the first comprehensive examination of all existing mechanisms and the first to explore the potential of a few new formats. Our analysis focuses on participation differences among the formats and how theory and supplemental survey data can help explain some of these differences.

The purpose of this paper is to examine the underpricing effect in Treasury auctions.

The paper compares two winner's curse models using a dataset on multi‐unit auctions. The dataset is from Swedish Treasury auctions, which is under a discriminatory auction mechanism. One model is a single‐unit equilibrium model assuming that each bidder bids for 100 percent of the auctioned securities, which is described by Wilson and solved by Levin and Smith. The other model is a multi‐unit model calibrated by Goldreich using the US Treasury auctions data and assumes that each bidder bids for one unit of the auctioned securities.

The empirical results show that, although both models work well in predicting the bid‐shading, the multi‐unit model fits the Swedish Treasury auctions data better than the single‐unit model.

The evidence implies that bidders rationally adjust their bids due to the winner's curse/champion's plague.

This study provides close quantitative predictions of the amount of bid‐shading using both single‐unit model of Wilson and multi‐unit model of Goldreich, and indicates that winner's curse or champion's plague worries bidders in countries other than the USA.

The purpose of this paper is to determine consumers’ willingness to pay (WTP) for tomatoes carrying different organic labels.

The data were collected from 878 randomly selected consumers in Shandong Province, China, using the Becker-DeGroot-Marschak auction experiment. The authors used the multivariate probit (MVP) model to analyze the factors influencing consumer preferences.

Results indicated that consumers’ WTP for tomatoes carrying the European Union (EU) organic label was significantly higher than those carrying the Chinese organic label. However, no significant difference was found between consumers’ WTP for tomatoes carrying the EU organic label and that for tomatoes carrying both Chinese and EU labels. The results of the MVP model analysis demonstrated that the consumers with different individual characteristics had heterogeneous preferences for organic labels. Food safety consciousness and organic knowledge both had positive effects on consumers’ WTP, meanwhile, environmental awareness had no prominent effect on consumer preferences.

This research is of academic value and of value to policy makers and suppliers. To satisfy diverse market requirements, governments, and manufacturers should consider consumer preferences for different certification labels in strategy development.

Although the value of artificial intelligence (AI) has been acknowledged by companies, the literature shows challenges concerning AI-enabled business-to-business (B2B) marketing innovation, as well as the diversity of roles AI can play in this regard. Accordingly, this study investigates the approaches that AI can be used for enabling B2B marketing innovation.

Applying a bibliometric research method, this study systematically investigates the literature regarding AI-enabled B2B marketing. It synthesises state-of-the-art knowledge from 221 journal articles published between 1990 and 2021.

Apart from offering specific information regarding the most influential authors and most frequently cited articles, the study further categorises the use of AI for innovation in B2B marketing into five domains, identifying the main trends in the literature and suggesting directions for future research.

Through the five identified domains, practitioners can assess their current use of AI and identify their future needs in the relevant domains in order to make appropriate decisions on how to invest in AI. Thus, the research enables companies to realise their digital marketing innovation strategies through AI.

The research represents one of the first large-scale reviews of relevant literature on AI in B2B marketing by (1) obtaining and comparing the most influential works based on a series of analyses; (2) identifying five domains of research into how AI can be used for facilitating B2B marketing innovation and (3) classifying relevant articles into five different time periods in order to identify both past trends and future directions in this specific field.

Unlike some developed countries, Chinese food safety certification system is multi-level including organic/green/hazard-free certifications. The purpose of this paper is to assess consumers’ preferences for tomatoes carrying these different labels.

Data used in this study came from choice experiments (CEs) conducted in Shandong province, China. Based on experiment data, a random parameter logit model was established to analyze consumers’ willingness-to-pay (WTP).

Consumers’ WTP for organic tomatoes was higher than that for hazard-free and green-certified tomatoes. Furthermore, consumers’ WTP for the European Union (EU) organic label was higher than that for the Chinese organic label, whereas a non-significant difference existed between the levels of consumers’ WTP for hazard-free and green-certified tomatoes. Consumers with different food safety risk perception (FSRP) had large differences in WTP, whereas those with varying environmental awareness (ENAW) had similar levels of WTP.

This contribution is the first research which focuses on consumers’ WTP for EU organic label, Chinese organic label, green label, or hazard-free label on tomato through CEs in China. Furthermore, the influence of consumers’ FSRP and ENAW on their preference was analyzed through a random parameter logit model.