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Cloud Manufacturing (CMfg) is a promising approach that leverages the sharing economy to reduce costs and enhance supply chain flexibility. Particularly, when utilised alongside Additive Manufacturing (AM), CMfg is considered a key enabler for collaborative production (CP) systems. However, there is still a lack of planning models that reduce entry barriers for CP. Therefore, we propose a decentralised CP planning framework for AM. In our approach, machines autonomously select jobs from an existing production plan to forward them to other suppliers that can produce these parts more efficiently. A CMfg platform facilitates job forwarding and creates promising part bundles and manufacturing machines autonomously places bids on the packages via a combinatorial $ 2^{nd} $ 2 nd price reverse auction. Costs of the reallocated bundles are shared throughout a Shapley value-based approach without the need to disclose critical information. We benchmark our proposed framework against a centralised planning approach and find that it achieves comparable effectiveness as the benchmark solution. We also show that this mechanism promotes individual rationality and that agents particularly benefit when participating in both offering and acquiring production jobs through the auction. [ABSTRACT FROM AUTHOR]

Using primary data collected from 389 sample households in Dangla district, Amhara region of Ethiopia, this study examined smallholder farmers' willingness to pay for ZM-GrowTM foliar fertiliser. The study employed the Tobit model to estimate the determinants of the maximum willingness to pay and a seemingly unrelated bivariate probit model to estimate the mean willingness to pay for foliar fertiliser. The results of the Tobit regression model showed that the education level of the farm household, total annual income, access to credit service, access to agricultural extension service, perception about fertiliser, and cost of the existing fertiliser have a positive and significant effect on farm households' willingness to pay. On the other hand, the age of farm households, availability of labour, and initial bid price have negative and significant effect on farm households' willingness to pay for ZM-GrowTM foliar fertiliser. The mean willingness to pay for ZM-GrowTM foliar fertiliser, estimated using the seemingly unrelated bivariate probit model, was 121.16 birr/litre (2.75 USD/litre). The corresponding mean willingness to pay amount estimated from an open-ended format was 161.105 Birr/litre (3.65 USD/litre). The results suggest that foliar fertilisers could be good alternatives to the existing fertilisers and its adoption can be further facilitated through improved access to knowledge and finance/credit. [ABSTRACT FROM AUTHOR]

The foreign exchange (FX) market has evolved into a complex system where locally generated information percolates through the dealer network via high-frequency interactions. Information related to major events, such as economic announcements, spreads rapidly through this network, potentially inducing volatility, liquidity disruptions, and contagion effects across financial markets. Yet, research on the mechanics of information flows in the FX market is limited. In this paper, we introduce a novel approach employing conditional transfer entropy to construct networks of information flows. Leveraging a unique, high-resolution dataset of bid and ask prices, we investigate the impact of an announcement by the European Central Bank on the information transfer within the market. During the announcement, we identify key dealers as information sources, conduits, and sinks, and, through comparison to a baseline, uncover shifts in the network topology. [ABSTRACT FROM AUTHOR]

Background: One of several logistics contexts in which pricing decisions are made involves truckload carriers using reverse auctions to bid for prices they want for their transportation services while operating under uncertainty about factors such as their (i) operations costs and (ii) rivals' bids. This study's main purpose is to explore humans' use of fast and frugal heuristics (FFHs) to navigate those uncertainties. In particular, the study clarifies the logic, theoretical underpinnings, and performance of human FFHs. Methods: The study uses behavior experiments as its core research method. Results: The study's key findings are that humans use rational FFHs, yet, despite the rationality, human decisions yield average profits that are 35% below profits from price optimization models. The study also found that human FFHs yield very unstable outcomes: the FFH coefficient of variation in profit is twice as large as price optimization. Novel contributions inherent in these findings include (a) clarifying connections between spot market auction pricing and behavioral theories and (b) adding truckload spot markets to the literature's contexts for measuring performance gaps between human FFHs and optimization models. Conclusions: The contributions have implications for practical purposes that include gauging spot pricing decisions made under constraints such as limited access to price optimization tools. [ABSTRACT FROM AUTHOR]

In the article at hand neural networks are used to model liquidity in financial markets, under conic finance settings, in two different contexts. That is, on the one hand this paper illustrates how the use of neural networks within a two-price economy allows to obtain accurate pricing and Greeks of financial derivatives, enhancing computational performances compared to classical approaches such as (conic) Monte Carlo. The methodology proposed for this purpose is agnostic of the underlying valuation model, and it easily adapts to all models suitable for pricing in conic financial markets. On the other hand, this article also investigates the possibility of valuing contingent claims under conic assumptions, using local stochastic volatility models, where the local volatility is approximated by means of a (combination of) neural network(s). Moreover, we also show how it is possible to generate hybrid families of distortion functions to better fit the implied liquidity of the market, as well as we introduce a conic version of the SABR model, based on the Wang transform, that still allows for analytical bid and ask pricing formulae. [ABSTRACT FROM AUTHOR]

Traditional revenue management systems are built under the assumption of independent demand per fare. The fare adjustment theory is a methodology to adjust fares that allows for the continued use of optimization algorithms and seat inventory control methods, even with the shift toward dependent demand. Since accurate demand forecasts are a key input to this methodology, it is reasonable to assume that for a scenario with uncertainties it may deliver suboptimal performance. Particularly, during and after COVID-19, airlines faced striking challenges in demand forecasting. This study demonstrates, firstly, the theoretical dominance of the fare adjustment theory under perfect conditions. Secondly, it lacks robustness to forecast errors. A Monte Carlo simulation replicating a revenue management system under mild assumptions indicates that a forecast error of ± 20 % can potentially prompt a necessity to adjust the margin employed in the fare adjustment theory by - 10 % . Moreover, a tree-based machine learning model highlights the forecast error as the predominant factor, with bias playing an even more pivotal role than variance. An out-of-sample study indicates that the predictive model steadily outperforms the fare adjustment theory. [ABSTRACT FROM AUTHOR]

This paper develops algorithms to solve strong-substitutes product-mix auctions: it finds competitive equilibrium prices and quantities for agents who use this auction's bidding language to truthfully express their strong-substitutes preferences over an arbitrary number of goods, each of which is available in multiple discrete units. Our use of the bidding language and the information it provides contrasts with existing algorithms that rely on access to a valuation or demand oracle. We compute market-clearing prices using algorithms that apply existing submodular minimization methods. Allocating the supply among the bidders at these prices then requires solving a novel constrained matching problem. Our algorithm iteratively simplifies the allocation problem, perturbing bids and prices in a way that resolves tie-breaking choices created by bids that can be accepted on more than one good. We provide practical running time bounds on both price finding and allocation and illustrate experimentally that our allocation mechanism is practical. Funding: E. Baldwin and P. Klemperer were supported by the Economic and Social Research Council [Grant ES/L003058/1]. P. W. Goldberg and E. Lock were supported by a JP Morgan faculty fellowship during the work on the final version of the paper. Supplemental Material: The online companion is available at https://doi.org/10.1287/moor.2019.0248. [ABSTRACT FROM AUTHOR]

This study addresses the multi-item, multi-sourcing supplier-selection and order-allocation problem. We propose an iterative procurement combinatorial auction mechanism that aims to reveal the suppliers' minimum acceptable selling prices and assign orders optimally. Suppliers use a flexible bidding language to submit procurement bids. The buyer solves a Mixed Integer Non-linear Programming (MINLP) model to determine the winning bids for the current auction iteration. We introduce a buyer's profit-improvement factor that constrains the suppliers to reduce their selling prices in subsequent bids. Moreover, this factor enables the buyer to strike a balance between computational effort and optimality gap. We develop a separate MINLP model for updating the suppliers' bids while satisfying the buyer's profit-improvement constraint. If none of the suppliers can find a feasible solution, the buyer reduces the profit-improvement factor until a pre-determined threshold is reached. A randomly generated numerical example is used to illustrate the proposed mechanism. In this example, the buyer's profit improved by as much as 118% compared to a single-round auction. The experimental results show that the proposed mechanism is most effective in competitive environments with several suppliers and comparable costs. These results reinforce the importance of fostering competition and diversification in a supply chain. [ABSTRACT FROM AUTHOR]

This study aims to investigate the impact of auction houses on the demand for business and cultural tourism, influencing travel experiences and shaping tourist expenditures. Using a decade of data and field observations, indepth researches were conducted with auction house stakeholders to explore the gap between starting and final selling prices and the tourist flow at these establishments. Tourist numbers were determined through "Office for National Statistics" data, and auction data were analysed using product catalogues and bid prices. Descriptive statistics and regression analysis were used to examine the relationship between tourist numbers and auction prices. The findings revealed no significant correlation between the selling prices of Islamic artifacts and tourist numbers; however, a strong correlation was observed between auction prices and final selling prices. It is recommended to analyse additional factors affecting tourist numbers in more detail. In light of these results, strategies emphasizing cultural and historical value are proposed for auction houses to enhance their tourist appeal, including the use of digital marketing and a reassessment of pricing strategies. This research underscores the need for a deeper understanding of the intricate relationship between auction houses and the tourism industry, emphasizing the necessity for further studies to make progress in comprehending and developing more effective strategies within a concise framework. [ABSTRACT FROM AUTHOR]

Demand response (DR) can potentially provide a cost-efficient alternative for balancing the electricity grid by replacing fossil-fuelled power plants for the provision of flexible capacity. This paper aims to quantify the cost reduction potential of DR from a system perspective. Historical data of balancing markets are studied using regression and average bid price analysis to quantify the effect of the participation of DR resources on the price of flexible capacity for the provision of balancing reserves by focusing on two case studies in Great Britain and the Netherlands. It is estimated that DR bids are, on average, 35% lower than the market average. The regression analysis concluded that 1% higher participation of DR in balancing markets leads, on average, to a 2.7% lower prices for flexible capacity. The results verify the hypothesis that flexible DR capacity is offered at a lower price on balancing markets compared to conventional generation resources, resulting in lower costs for grid operators to balance the grid, thus reducing societal costs for electricity provision and overall emissions through the integration of low-carbon balancing resources. [ABSTRACT FROM AUTHOR]

It is common for suppliers to underestimate costs in procurement auctions, thereby decreasing the bid price and profit on completion of the supply, and potentially resulting in supply disruptions. We study the bidding decisions of suppliers that underestimate costs when the buyer uses first‐price or second‐price sealed‐bid procurement auctions. We study the effects of underestimating costs on the bid prices and performance decisions under different auction modes and propose renegotiations after procurement auctions to cope with supply disruptions. The results show that: (1) using first‐price or second‐price auctions, underestimating costs does not guarantee a positive profit on completion of the supply. When the winning supplier's degree of underestimation is high enough, underestimating costs may cause supply disruptions. (2) When the buyer faces supply disruptions, if the expected payment for re‐selecting another supplier is not less than a certain threshold value, the buyer can prevent supply disruptions through renegotiations after procurement auctions. (3) Compared to the situation where all suppliers' budgeted costs are accurate, underestimating costs always decreases the supplier's profit. For the buyer, when the supplier completes the supply under the original or renegotiated contract, underestimating costs can decrease the procurement costs. Finally, we show the main conclusions with numerical examples. [ABSTRACT FROM AUTHOR]

Bid rigging is a fraudulent scheme in procurement auctions resulting in non-competitive bids awarded at prices above the competitive market. Bid rigging is a global problem that wastes public agencies' resources and taxpayers' money. While various methods and tools have been developed to detect bid rigging, it remains challenging for public agencies to identify what a competitive baseline auction looks like in the absence of collusion. Such a baseline is commonly known as a reference scenario, which involves analyzing the behavior of honest bids in previous auctions to determine if future bids could be collusive. Research on formulating reliable reference scenarios for bid rigging detection in the auctions of infrastructure projects has received limited attention. Hence, our paper analyses the key criteria required to develop a reference scenario for public agencies to detect bid rigging during an auction. Drawing on data from Brazilian public procurement and oversight agencies, a procedure for composing robust reference scenarios for detecting bid rigging in infrastructure first-priced auctions is presented and discussed. We then test our procedure's generalizability using data from four countries (Australia, Brazil, Spain, and the United States) in two auction formats (i.e., capped and uncapped). A better understanding of the reference scenario formulation will allow public officials to increase the likelihood of detecting bid rigging when it exists and avoid flagging it as such when no collusive practices are involved. [ABSTRACT FROM AUTHOR]

The Constant Leverage covering strategy for the equity momentum portfolio (CLvg) developed in this project cannot mask its shortcomings by increasing leverage. It has to successfully forecast and avoid more losses than profits to perform better than the momentum portfolio. This approach is different from other covering strategies available in the literature that focus on increasing the right tail of the momentum returns distribution at a faster rate than they increase the left tail. The CLvg strategy only depends on past information and uses the daily volatility of the loser portfolio to determine episodes of high and low volatility. The daily volatility of the loser portfolio has a stronger relationship with large negative momentum returns than the daily volatility of the momentum portfolio. The daily volatility of the loser portfolio also has a weaker relationship with larger positive monthly returns, and it is more predictable because it has a higher volatility persistence. The negative effects of transaction costs on the CLvg strategy are measured using bid and ask prices reported by CRSP from 1992 to 2021. During this period, the stock market presented an average excess return of 9.19% and a Sharpe ratio of 0.61, and 9.74% of its returns were crashes, which is a better performance than the momentum portfolio. The CLvg adjusted by transaction costs presented excess returns of 16.93% and a Sharpe ratio of 0.84, and only 8.31% of its returns were crashes. [ABSTRACT FROM AUTHOR]

Highest stoppage games in economics—first price sealed bid auction and Dutch auction, among others—have produced striking puzzles, including violation of revenue equivalence between auctions and adjustment of behavior across interfaces. The latter is also observed in risk elicitation. Here, we use existing puzzles to shed light on each other, by nesting auction and risk tasks in a common environment. We find behavior consistent with a spatial interface imparting the same relevant auction-theoretic surplus and probability information as does an interactive numerical calculation tool. Empirical revenue equivalence (respectively, risky choice) can thus be altered by design. [ABSTRACT FROM AUTHOR]

Using a dataset of institutional bids for IPOs, we study how relationships with lead underwriters impact institutional investors' bidding strategy in the auctioned IPOs. Our paper finds that strong business ties lead to higher bid prices. The effect is more pronounced among IPO firms that receive less market attention, and is attenuated for IPOs certified by reputable intermediaries. We propose that rent-seeking incentives may be the potential mechanism for this relationship-based bidding. Our study highlights that the business connection between underwriters and institutional investors has effect on the IPO pricing. [ABSTRACT FROM AUTHOR]

Conic finance theory, which has been developed over the past decade, replaces classical one-price theory with the bid-ask price economy in option pricing since the one-price principle ignores the bid-ask spread created by market liquidity. Within this framework, we investigate the European option pricing problem when stochastic interest rate, stochastic volatility, and double exponential jump are all taken into account. We show that the corresponding bid and ask prices can be formulated into a semi-analytical form with the Fourier-cosine method once the solution to the characteristic function is obtained. Some interesting properties regarding the new results are displayed via numerical implementation. [ABSTRACT FROM AUTHOR]

This study designs a two-stage algorithm to address the bid generation problem of carriers when adding new vehicle routes in the presence of the existing vehicle routes to provide transportation service. To obtain the best auction combination and bid price of the carrier, a hybrid integer nonlinear programming model is introduced. According to the characteristics of the problem, a set of two-stage hybrid algorithms is proposed, innovatively integrating block coding within a genetic algorithm framework with a depth-first search approach. This integration effectively manages routing constraints, enhancing the algorithm's efficiency. The block coding and each route serve as decision variables in the set partition formula, enabling a comprehensive exploration of potential solutions. After a simulation-based analysis, the algorithm has been comprehensively validated analytically and empirically. The improvement of this research lies in the effectiveness of the proposed algorithm, i.e., the ability to handle a broader range of problem scales with less time in addressing complex operator bid generation in combinatorial auctions. [ABSTRACT FROM AUTHOR]

As an on-demand mobility service, parking reservations can greatly alleviate the issue of parking challenges. There are currently three primary strategies for parking reservation: first-come-first-served, permit reservation, and auction. In contrast to the first-come-first-served and permit-reserved strategies, the auction strategy uses dynamic pricing to allocate parking supplies efficiently based on the auction, which attracts more scholars for the research. However, parking reservations based on the auction process may have an inequity issue because drivers' age, gender, income level, and location of residence fluctuate. This inequity may limit the growth of reserved parking by influencing parking drivers' acceptance of reserved parking. But currently, very few scholars focus on the issue of reserved parking equity, and even fewer measure this nebulous and personal issue. In consideration of this, the Lorenz curve of parking reservation and the vertical equity index of parking reservation are proposed in this paper along with the calculation method for the index, which enables the problem of reserved parking vertical equity to be visualized and made concrete. The numerical experimental method is used to analyze the vertical equity of drivers with varying income levels, utilizing the Vickrey–Clarke–Groves (VCG) auction process as an example. According to the research, loss-averse drivers are more than gain-neutral and gain-seeking drivers when the income levels of the drivers using reserved parking are the same. With the increasing number of high-income drivers involved in the parking reservation, medium to low-income drivers would lose their chances of successful reservations because of their uncompetitive bid price which leads to inequity issues when the number is less than the number of parking spaces. In contrast, the vertical equity index changes more for gain-seeking drivers while being generally steady when loss-averse and gain-neutral drivers participate. For instance, when the profit and loss coefficient is 3 and 15% of drivers with high-income levels use the parking reservation platform, the vertical equity index rises from 0.09128 to 0.45434. The reference price has a moderating influence on the vertical equity index when the number of driver participants at high-income levels remains constant. In general, within a reasonable range, the higher the reference price, the more equitable the parking reservation procedure and the lower the vertical equity index. [ABSTRACT FROM AUTHOR]

Privatization auctions are seen as culprit for rising prices in eastern Germany. This study aims to analyse whether privatization auctions could have earned even higher revenues by setting optimal reserve prices. For this purpose, a structural estimation approach is applied to determine reserve prices and to compare the resulting expected revenues with actual revenues. The data set includes land auctions in eastern Germany from 2005–2019. The empirical results illustrate that room for increasing revenues exists, but reserve prices would be required to be higher than actual land prices. A potential consequence of high reserve prices is the risk of delays in the privatization process. [ABSTRACT FROM AUTHOR]

Auction-based parking mechanisms (ABPM) have been recognized as promising solutions to the parking problem. As the operator of the ABPM, the parking platform should not only be well-operated to provide parking services for demanders in need but also maintain commercial viability for sustainable operations. Motivated by this, we propose three ABPMs, namely, the ABPM without withdrawal right, the ABPM with costless withdrawal right, and the ABPM with non-free withdrawal right. Particularly, we characterize the parking demanders' withdrawal behaviors in the ABPMs. This behavior is motivated by the demanders' negative utilities derived from the auction sequence, where the demanders will first submit bid prices and are then allowed to withdraw from the parking market after the announcement of auction results when they are aware of their true valuations. We derive the equilibrium bidding strategies and the platform's expected revenues under the above three mechanisms and compare them in terms of the analytical results. It has been found that the introduction of withdrawal right will stimulate demanders to raise their bids for winning and the ABPM with non-free withdrawal right generates the highest revenue under certain conditions. A case study of parking in Beijing Financial Street has been conducted to illustrate the findings and explore managerial implications, including adapting the ABPM with non-free withdrawal right, narrowing the parking supply-demand gap, and enhancing travel experiences on the way to parking. • Parking demanders' endogenous withdrawal behaviors are modeled in the auction-based parking mechanism (ABPM). • Three ABPMs regarding the usage of withdrawal right are designed and compared under the market equilibrium framework. • The withdrawal right stimulates parking demanders to raise bids for winning. • The ABPM with non-free withdrawal right generates the highest revenue under certain conditions. • Managerial implications regarding boosting the parking platform's revenue are proposed. [ABSTRACT FROM AUTHOR]

We study an online retail marketplace's incentive to manipulate sellers' product attractiveness to consumers (e.g., through fake sales, fake reviews, or dishonest endorsement) and sellers' placement ranking. In this paper, we study an online retail marketplace's incentive to manipulate sellers' product attractiveness to consumers (e.g., through fake sales, fake reviews, or dishonest endorsement), as well as sellers' placement ranking. We design a model of an online retail marketplace with a platform that manipulates sellers' product attractiveness and sellers' organic ranking order, and the sellers decide product prices and bid for sponsored advertising space on the platform. We find that the platform may manipulate an inferior seller's product to appear more attractive to intensify sellers' competition to bid for advertising and also manipulate a superior seller's organic placement to either compensate or penalize the superior seller. We show that public policies, such as banning fake sales and fake reviews only by third-party sellers, may not necessarily eradicate manipulation on the platform if they ignore the platform's incentive for manipulation in the first place. History: Anthony Dukes served as the senior editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mksc.2023.1446. [ABSTRACT FROM AUTHOR]

Short selling is a common practice in financial markets. Although there is extensive research concerning short selling and short sellers, in the behavioral and experimental economics literature, there are only a few studies that examine it. This paper investigates the pricing of two forms of short selling both theoretically and experimentally—selling a lottery short and paying to close the short position. The theoretical framework presents and analyzes the two positions and the influence of the anchoring and uncertainty effects on the pricing. To test the theoretical framework, we asked participants in an experiment about the price they were willing to accept for the obligation to pay the lottery's outcome and the price they were willing to pay to close the obligation to pay the lottery's outcome they held. Moreover, we used a simple lottery with different framings, each one with a different anchor. Our results suggest that in the short‐selling position, behavioral biases, such as anchoring and uncertainty, impact the decision‐makers' bid prices. [ABSTRACT FROM AUTHOR]

Dynamic spectral risk measures define a claim's valuation bounds as supremum and infimum of expectations of the claim's payoff over a dominated set of measures. The measures at which such extrema are attained are called extreme measures. We determine explicit expressions for their Radon-Nykodim derivatives with respect to the common dominating measure. Based on the formulas found, we estimate the extreme measures in two cases. First, the dominating measure is calibrated to mid prices of options and valuation bounds are given by options bid and ask prices. Second, the dominating measure is estimated from historical mid equity prices and valuation bounds are given by historical 5-day high and low prices. In both experiments, we find that the market determines upper bounds by testing scenarios in which losses are significantly lower than expected under the dominating measure, while lower bounds by ones in which gains are only slightly lower than in the base case. [ABSTRACT FROM AUTHOR]

The Battery Energy Storage System (BESS) is one of the possible solutions to overcoming the non-programmability associated with these energy sources. The capabilities of BESSs to store a consistent amount of energy and to behave as a load by releasing it ensures an essential source of flexibility to the power system. Nevertheless, BESSs have some drawbacks that pose limitations to their utilization. Indeed, effectively managing the stored and released energy is crucial, considering the degradation of performance associated with these systems over time. The substantial capital expenditure (CAPEX) required to install these systems represents a current constraint, impeding their broader adoption. This work evaluates a techno-economic analysis of a 2MW/2MWh BESS providing multiple services, namely participating in capacity and balance markets. The analysis is based on a BESS model implemented in SIMULINK, adopting online data gathered from a Lithium Iron Phosphate (LFP) battery facility. The model evaluates the auxiliary power consumption, state-of-charge (SoC), state of health (SoH), and the round-trip efficiency (RTE) of the overall system. The analysis is based on three price profiles: 2019 (Business-As-Usual), 2020 (COVID-19), and 2022 (Gas Crisis). Furthermore, this work conducts a case study to analyze the behavior of the BESS. It entails a sensitivity analysis, specifically evaluating the influence of CAPEX and upward bid price on the economic viability of the project. The results show a strong relation between the CAPEX variation and the Internal Rate of Return (IRR) of the project. [ABSTRACT FROM AUTHOR]

The construction land quota pricing mechanism with cost plus pricing method is not sufficient to reflect its intrinsic value. This diminishes the willingness of farmers to voluntarily reclaim abandoned residential and other rural construction land, leading to suboptimal efficiency in rural land utilization and an excessive squandering of rural land resources. Thus, a sequential auction model with two stages for complementary goods was constructed, which considered the synergic characteristics between the land and quota. Further, regret psychology of bidder was considered in the case of winning or losing. A rational pricing mechanism has been developed to allocate construction land quotas, aiming to enhance farmers' motivation to the vacant homesteads of reclamation and revitalizing the stock of rural construction land. The results revealed that the regret psychology in the case of winning would decrease the transaction price of the quota, i.e., the greater the perceived regret in the case of winning, the more significant the reduction in the bidding price offered. Moreover, the regret psychology in the event of losing/failure would increase the transaction price of quota. Furthermore, publishing only the winner's price after the auction leads to the highest price of the quota offered by the bidder. In contrast, publishing only the loser's bidding price leads to the lowest transaction price of the quota offered by the bidder. In addition, the fee for delayed construction would increase the bidding price of the construction land quota. Therefore, local governments should consider announcing only the winner of price after the quota auction has ended. In addition, imposing a fee for delayed construction would enhance the transaction price of land quota, increase farmers' revenue from land reclamation, and incentivize farmers to reclaim unused rural land. [ABSTRACT FROM AUTHOR]

This paper develops a dynamic model of tender offers in which there is trading on the target's shares during the takeover, and bidders can freeze out target shareholders (compulsorily acquire remaining shares not tendered at the bid price), features that prevail on almost all takeovers. We show that trading allows for the entry of arbitrageurs with large blocks of shares who can hold out a freezeout—a threat that forces the bidder to offer a high preemptive bid. There is also a positive relationship between the takeover premium and arbitrageurs' accumulation of shares before the takeover announcement, and the less liquid the target stock, the stronger this relationship is. Moreover, freezeouts eliminate the free-rider problem, but front-end loaded bids, such as two-tiered and partial offers, do not benefit bidders because arbitrageurs can undo any potential benefit and eliminate the coerciveness of these offers. Similarly, the takeover premium is also largely unrelated to the bidder's ability to dilute the target's shareholders after the acquisition, also due to potential arbitrage activity. [ABSTRACT FROM AUTHOR]

Since COVID 19 pandemic hit Indonesia, many small harbor contractors have been forced to provide low bid prices ( < 80% HPS) for harbor auctions sourced from APBN funds in 2019-2022. Even though the bid price given is low, many contractors are able to complete the work according to the quality and price required in the contract agreement. This research analyzes the factors that cause contractors who have successfully completed the work, dare to provide low bids in the auction process. From the data obtained an processed using SEM-PLS method, it is know that the company’s internal condition factors have the most significant influence with a path coefficient of 0.464. The biggest indicator of the company’s internal condition is the company’s need to achieve the minimum sales/ profit target in one year, with a path coefficient value of 0.866. Financial characteristic factors also have a significant influence with a path coefficient value of 0.223. Meanwhile the technical characteristics factors has an influence with a path coefficient value of 0.213. [ABSTRACT FROM AUTHOR]

In a model with correlated and interdependent values/costs, we identify for the buyer's bid double auction the asymptotic distributions of the price and of two order statistics in the first order conditions for optimal bidding/asking, all of which are normal. Substitution of the asymptotic distributions into the first order conditions can permit the solution for approximately optimal bids/asks that provide insight into what is " first order" in a trader's strategic decision-making, which has been difficult to obtain through analysis of equilibrium. [ABSTRACT FROM AUTHOR]

Almost all limit orders are canceled. We examine two economic channels that can motivate cancellations: reductions in the expected profit at execution, and reductions in the probability of execution. An order‐level analysis shows that changes in depth at the best bid and offer prices, as well as changes in the order queue position, influence cancellation in a way consistent with the former channel, that market makers monitor the expected profit at execution of each limit order. Although buy‐side investors use passive orders extensively, our findings indicate that limit order cancellations on aggregate are best understood through models of liquidity provision. [ABSTRACT FROM AUTHOR]

Competitive bidding in design-bid-build contracts holds the potential to lower bid prices, maximize project outcomes, and promote growth in the construction industry. However, these potential benefits of competitive bidding are contingent upon adequate competition among bidders. State highway agencies (SHAs) traditionally evaluate competition levels predominantly based on the number of bidders, neglecting other key elements such as bidders' competitiveness. Moreover, little research focuses on addressing this limitation. This study proposes a novel data-driven network theory approach to measure competition from the owners' perspective. Specifically, competition is modeled as a bidirected network of connected bidders using their past winning and losing records. We propose different measures of contractors to provide unique insights into the competitiveness of the bidders. These centrality measures are further correlated with the bidding performance using Spearman's rank correlation coefficient. Our findings demonstrate that these proposed centrality measures bear stronger correlations with bidding performance than the number of bidders. By employing this novel approach, SHAs can better understand contractor competitiveness and competition levels during the project-letting phase. [ABSTRACT FROM AUTHOR]

Contractors fail to meet project objectives for a variety of reasons. One of the major reasons for this has been attributed to the current criteria for awarding contract ineffectiveness in identifying contractors capable of meeting today's demands and challenges. Therefore, there is a need to develop alternative contract-awarding systems for public building construction projects. Thus, the purpose of this study is to develop multiple contractor selection criteria and a selection model by integrating the Delphi and Fuzzy AHP methods. First, this study conducted an extensive literature review of related studies to determine the contractor selection criteria to select contractors for building projects. Thirty sub-criteria were finalized under six major criteria categories, such as Bid Price, Financial Capacity. Technical Capacity. Management Capacity, Experience and Reputation, and Health, Safety and Environment. Two rounds of the Delphi method were then employed to finalize and categorize the contractor selection criteria. Finally, the Fuzzy AHP method was employed to assign weights to the contractor selection criteria and then rank them according to their importance. The study revealed that among all sub-criteria, Bid Price, Projects completed on time and within budget; Experience on Similar types and sizes of projects; and Qualification, Number and Experience of Staff are the most important selection criteria. The last four sub-criteria in the row with slight weight differences are innovative methods, liquidity, credit rating, and organizational structure. The results of this study serve as a benchmark for the application of multiple contractor selection criteria procurement in Ethiopia, and as a basis for future research. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the extent of price clustering in a selection of Islamic stocks listed in Indonesia, Malaysia and Pakistan and also investigates the determinants of the phenomenon at the firm level. Design/methodology/approach: The author test the uniformity of price distribution in the selected securities. Then, the determinants of price clustering were investigated through multivariate analysis based on a binary logistic regression model. Following the arguments of Narayan et al. (2011), who emphasize the importance of considering firm heterogeneity when studying the phenomenon, the author conducts the empirical study at the firm level. Findings: The evidence indicates that Islamic stocks show a mild level of price clustering. Only half of the stocks under analysis rejected the uniformity test in the distribution of prices. In these cases, investors exhibited a preference for prices ending at zero and five. The evidence does not confirm the cultural clustering theories. Price clustering is found to be positively associated with price level and relative bid-ask spread. Overall, the negotiation hypothesis, which predicts that investors prefer round prices to minimize the costs associated with negotiations, best explains most of our results. Research limitations/implications: The existence of price clustering is difficult to reconcile with the prediction of the efficient market hypothesis that prices should follow a random walk. Moreover, the evidence indicates that Muslim investors share a preference for round prices in some settings, under the assumption that Islamic stocks are mostly traded by Muslim investors. Originality/value: To the author's best knowledge, this is the first study to address the subject of price clustering in Islamic stocks. [ABSTRACT FROM AUTHOR]

This study aimed to improve the truthfulness and efficiency of double auction mechanism in the cloud computing environment. In an auction, bidders have a high incentive to announce an unrealistic price, that is, each cloud user tends to announce a lower price and each cloud service provider tends to bid higher price than the actual one. This untruthful behavior will have catastrophic consequences to the market, leading to participants' fear of being misused. Therefore, it seems vital to provide a mechanism for the realization of truthfulness involving no unrealistic offer by the users. On the other hand, it has been proven that it is not possible to achieve the characteristics of truthfulness, budget balance and economic efficiency at the same time. There is a weak budget balance in a truthful mechanism with a price difference greater than zero between the total price paid by the cloud users and that received by the cloud service providers. In this paper, a mechanism is proposed to encourage participants to offer truthful prices by rewarding honest participants. The proposed called the reward mechanism uses a repository to store bidders' information, including the number of bids and the number of honest bids per auction as well as a ranked list of bidders based on their bidding history in offering honest prices. The results show that the proposed mechanism not only motivates the bidders to announce honest bids, but also solve the problem of weak budget balance by dividing the bid amount among the winning bidders. [ABSTRACT FROM AUTHOR]

The paper investigates two-player double-auction bargaining with private values in a setting with discrete two-point overlapping distributions of traders' valuations. We characterize parameter settings in which there exists a fully efficient equilibrium, and show that if there are traders that behave naively, i.e., set bid or ask equal to their valuation, then there is no equilibrium achieving full efficiency. We conduct an experiment to test the theoretical possibility that the presence of naive traders can reduce efficiency. We find, however, that efficiency is not lower in the presence of naive traders. Subjects mostly set bid/ask prices strategically but they do not coordinate on a fully efficient equilibrium and the extent of strategic behavior is not different in the presence of naive players. We show that a learning model of noisy strategy adjustment explains the observed behavior better than other (equilibrium or non-equilibrium) models. [ABSTRACT FROM AUTHOR]

Introduction Life cycle costing is an important management tool that takes into account the implications of planning, acquiring, operating, maintaining, and disposing of an asset during its complete life cycle. A major hindrance to the procurement of expensive equipment in developing countries is the lack of a reliable framework combining and integrating all the equipment life cycle aspects into procurement process. Methods The study was conducted from the data collected from the bids that were received for procurement of two robotic track-based central laboratories which were installed at All India Institute of Medical Sciences (AIIMS), New Delhi. The procurement was done as per the guidelines laid down under General Finance Rules (GFR) 2017 following the two bid systems: technical bid and price/commercial bid. Results A complete financial analysis of the robotic laboratory was done that involved gathering of all the pertinent financial information into one place and then using that data to analyze the feasibility of the bid. The life cycle costs of both the labs were calculated by assuming the life of equipment as 10 years and by factoring in cost of equipment including 5-year warranty, comprehensive maintenance from years 6 to 10, indicative cost of all reagents for 10 years, and indicative cost of all other consumables for 10 years. Conclusion Results showed that the cost of equipment alone should not be the sole predictor of making purchase decisions of equipment. Further research may additionally explore differences between processes being followed in government versus private organizations, as well as national guidelines and subnational practices. [ABSTRACT FROM AUTHOR]

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Construction bid documents may contain uncertain or incomplete information that can affect project pricing as well as project performance, if not addressed prior to bidding. To resolve the uncertainties and clarify project requirements, the risk and uncertainties prevailing in the document should be identified at an early stage of the project life cycle. In this study, pre-bid request for information (RFI) is utilized as a key clue to quantify project ambiguities and uncertainties of a bid document, as pre-bid RFI is generated by bidders when any ambiguous or incomplete information is encountered in the bid document. Despite the significance of pre-bid RFI in quantifying project uncertainty, studies considering pre-bid RFI to identify project uncertainty are limited. Driven by document-based analysis, this study aims to investigate what uncertainties are frequently encountered in bid documents and how they affect project pricing. To achieve the research goal, this study will (1) identify the prevailing risks/uncertainties in the bid document; (2) determine the most common risks/uncertainties and their impacts on bid price; and (3) verify the significance of pre-bid RFIs in bid uncertainty prediction models. To achieve these objectives, public project data from US state Departments of Transportation (DOTs) were collected and used for frequency analysis, correlation testing, and machine learning-based prediction models. The results of uncertainty prediction models showed that uncertainties driven by pre-bid RFI analysis can improve the project risk prediction up to 15%, verifying the significance of RFIs in the bid price prediction model. This study will contribute to the construction management body of knowledge by clarifying the likelihood of errors and uncertainties that should be checked before bidding, thereby proactively preventing future design changes, claims, and dispute risks. [ABSTRACT FROM AUTHOR]

This study investigates how potential target firms' environmental, social, and governance (ESG) performance affects bid premiums during the merger and acquisition (M&A) process. Using a sample of 5658 M&A deals between 2009 to 2020, we provide new evidence that target firms' ESG rating is positively correlated to bid price, particularly when the target firm scores highly on their singular environmental and governance ratings, whereas the targets with high single social ratings alone are not correlated to bid price. Our results also implied that when the target has lower environmental and governance performance, M&A deals are less likely to face bid premiums. We additionally find that the target firms of non‐state‐owned enterprises (non‐SOEs) are more likely to have a higher bid price as opposed to state‐owned enterprises' (SOEs) target firms. Additionally, we find that targets' ESG rating is positively correlated to target shareholder value creation, as well as being positively correlated to short bid deal negotiation times. Overall, our findings are in line with target‐resistance theory, which states that high ESG performance targets can use their ESG advantages to increase their bid price, as well as increase stakeholder engagement and generation of post‐M&A synergy. [ABSTRACT FROM AUTHOR]

This study proposes a versatile model for the dynamics of the best bid and ask prices using an extended Hawkes process. The model incorporates the zero intensities of the spread-narrowing processes at the minimum bid–ask spread, spread-dependent intensities, possible negative excitement, and nonnegative intensities. We apply the model to high-frequency best bid and ask price data from U.S. stock markets. The empirical findings demonstrate a spread-narrowing tendency, excitations of the intensities caused by previous events, the impact of flash crashes, characteristic trends in fast trading over time, and the different features of market participants in the various exchanges. [ABSTRACT FROM AUTHOR]

With the rapid development of the new power system, the proportion of renewable energy participating in the electricity market is constantly increasing, and the uncertainty of renewable energy power output and market clearing price brings risks to its participation in long‐term contract bidding. Therefore, a method of contract bidding involving bidding amount and bidding price of PV power station is proposed. Firstly, the multi‐order weighted Markov chain model is used to forecast the distribution of weather states in the trading cycle, and the fuzzy C‐means (FCM) method is used to cluster the joint samples of power output indicators and market clearing price indicators, and then Latin hypercube sampling is used to generate power output scenarios and market clearing price scenarios. Then, an optimization method for long‐term contract bidding strategy of PV power station considering conditional value at risk (CVaR) and transaction probability is established, and the model is divided into two stages and solved in an alternate iterative way. Finally, an example is used to verify that the constructed model enables PV power stations to effectively avoid risks and obtain more stable revenue. [ABSTRACT FROM AUTHOR]

Cost overruns are a common problem for public works projects, often due to modifications to the original design. While the causes of these modifications have been studied, the legal framework's impact and limitations on these modifications have received extensive treatment, with no specific case studies from different countries. This paper explores the relationship between modifications in Spanish public works projects and their compliance with legal limits, investigating the alignment between base bidding prices and eventual costs after adjustments. The study also delves into the strategic behaviour of construction companies in Spain, which frequently involves manipulating project costs to match the initially proposed bidding price. Statistical methods, such as the Spearman correlation test and graphical analysis, confirm a nearly exact relationship between base bid price and final price. Also, a modification costs comparison for two different legal periods highlights the legal framework's influence, as a less restrictive framework leads into higher average cost overruns. It provides valuable information to avoid malpractice for tendering institutions, practitioners, and legal developers, as well as those interested in the Spanish public works sector, and opens the door for future research on solving this problem. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to provide one of the first empirical examinations of the liquidity conditions in the international sukuk market. It also provides evidence on how those differences have changed over time. Design/methodology/approach: The study uses propensity score matching in combination with two price-based liquidity measures, bid-ask and high-low spreads, to compare the liquidity conditions of international sukuk issuances with similar international conventional bonds. Findings: The results confirm that sukuk issuances are significantly less liquid than their conventional equivalents. The results also show that this difference in liquidity is more prominent in the case of corporate issuances. Finally, the analysis shows a general decline in these liquidity differences over time as the sukuk market matures and as more investors and issuers enter the market. Originality/value: The study addresses the gap in the literature regarding the absence of an empirical examination of the liquidity conditions in the international sukuk market. The findings of this study also suggest that prior empirical findings regarding the diversification benefits offered by sukuk are likely to be driven by the lack of liquidity in the sukuk market rather than underlying economic factors. [ABSTRACT FROM AUTHOR]

Winners in online auctions frequently fail to complete purchases. Major auction platforms therefore allow "second‐chance" offers (the runner‐up bidder pays his own bid price) and let sellers leave negative feedback on buyers who default. We show theoretically that (i) all else equal, the availability of second‐chance offers reduces bids; (ii) sellers have no incentive to exclude bidders, even if they are nearly certain to default; (iii) buyer reputation systems reward bidders known to default with a positive probability. Our experiments show that the economic forces identified in the theoretical model are important enough to have predictive power for bidder behavior. [ABSTRACT FROM AUTHOR]

Major emerging market countries issue significant amounts of local currency bonds in order to finance their budget deficits. As liquidity is a substantial feature of the financial markets, understanding bond liquidity dynamics is essential. The bid-ask spread is an important measure of bond liquidity and reflects explicit transaction costs. We apply a panel regression model in order to analyze bond-level and country-level characteristics' effects on bond liquidity and bid-ask spread. Results show that volatility, credit risk and duration have significant effects on emerging market bond liquidity. Emerging market sovereign bonds with lower volatility, lower credit risk and shorter duration have narrower bid-ask spreads, on average. [ABSTRACT FROM AUTHOR]

The bull buying behavior of Iowa cattle producers was assessed using an online simulated bull auction. Participants (n = 45) were asked a series of questions to determine the bull type they wished to bid on and the purchase price for the bull. Questions included the breeding objective of the producer and whether the bull would be bred to heifers. Participants were asked to identify the breed of bull they were interested in purchasing, the traits that were the most important to their breeding objective, and the maximum amount that they would be willing to pay. Once the buyer information was complete, the responses were randomly redistributed to other participants. As a result, a participant would receive the buyer information from another individual involved in the simulated bull auction. At this point, the participant role would change from buyer to bidder. A list of 70 bulls with expected progeny differences (EPD) was provided to each participant, and the simulated bull auction was accessed through an online auction platform via cell phones. Participants bid for bulls on behalf of the instructions of the buyer. After the sale, the bidder was asked if they were able to purchase the bull to fit the criteria requested by the buyer and if it was purchased within the given price range. The purchase information was returned to the original participant (i.e., the buyer). The buyer then stated if they were satisfied with the purchased bull. Questionnaires were collected, and information was compiled. The most common breeding objectives were replacement heifers, feeder calves, fed cattle, and profit. Important traits for purchasing a bull were calving ease direct, yearling weight, terminal traits, and docility. Only 16 participants indicated using indexes for selection. Criteria for removing a bull from consideration included low EPD for calving ease direct and docility, and if the bull was horned. Poor index values were listed by 9 participants as a reason to eliminate a bull. Responses from participants as the bidder, 83.7% indicated that the bull was purchased within the provided price range, while 16.3% were unable to purchase a desired bull within the given price range. When asked why the bidder bid on a specific bull, 28 stated the bull met the EPD profile, 16 stated the bull was in the correct price range, seven bulls met a phenotypic profile, and five bulls were purchased due to the bidder running out of time. Of the bulls purchased, 80% of the buyers were satisfied with the bull purchased by the bidder. The results from this simulated bull auction provide insight into tools and methods used by cattle producers when purchasing bulls and what, if any, genetics tools for selection are being used. [ABSTRACT FROM AUTHOR]