Make-or-break during production: shedding light on change-orders,rework and contractors margin in construction

A considerable amount of research has examined the cost performance of construction projects, yet there has been a paucity of studies that have examined the impact that client initiated change-orders and rework have on contractors. This paper seeks to add further clarity to this issue by replicating previous empirically-based research to establish the validity and reliability of the key issues influencing a contractor's cost performance. A total of 98 projects were used to examine the value of rework and change-orders and their influence on a contractor's margin. Only 65% of projects experienced a cost increase, though a mean rework cost of 0.39% of the contracted value was incurred. The difference between approved client change-orders and those by the contractor for subcontractors was 0.5% of the total costs incurred, which adversely impacted the organisation's profit. Margin losses may well have been higher as rework is seldom formally documented and reported.     

FROM FLEXIBILITY TO INSECURITY: HOW VERTICAL SEPARATION AMPLIFIES FIRM‐LEVEL UNCERTAINTY

This article presents a model where firms may endogenously externalize part of their production process. We start from the premise that adaptation to uncertainty cannot be contracted upon in the worker/employer relationship. Vertical separation then balances flexibility gains against hold‐up costs of opportunistic behavior by outside contractors. In equilibrium, the degree of separation is shown to depend on the degree of product market competition, contractor's bargaining power, and the volatility of demand shocks. Our main result is that an increase in the degree of vertical separation amplifies the elasticity to demand shocks of firms' sales and employment. It does not, however, amplify aggregate uncertainty. Evidence from firm‐level data is shown to be largely consistent with the main implications of our theory. (JEL: L16, L23, L24)     

消费者效用测度与产业需求函数

把概率解释为Ramsey的信念度,商品效用便可赋予von Neumann-Morgenstern效用性质从而得到测度;按二元价值结构的消费偏好特性建立新的需求模型,可导出在严格意义上用于产业分析的非线性需求函数,为解释现代产业组织及竞争行为提供科学依据。     

Contractors’ and Agency Decisions and Policy Implications in A+B Bidding

The focus of this study is on the A+B transportation procurement mechanism, which uses the proposed cost (A component) and the proposed time (B component) to score contractors’ bids. Empirical studies have shown that this mechanism shortens project durations. We use normative models to study the effect of certain discretionary parameters set by state transportation agencies on contractors’ equilibrium bidding strategies, winner selection, and actual completion times. We model the bidding environment in detail including multi‐dimensional bids, contractors’ uncertainty about completion times, and reputation cost. The latter refers to a private penalty that accrues to tardy contractors from increased cost of posting bonds and reduced prospects of winning future projects. Our model explains why contractors may skew line‐item bids and why winners frequently finish earlier than bid. It has several policy implications as well. For example, we recommend that agencies set the daily incentive, disincentive, and road user cost to be equal and not cap incentives. This is a departure from current practice, where incentives are often capped and weaker than penalties. Furthermore, we show that agencies may be justified in setting daily road user cost strictly smaller than the true cost of traffic disruption during construction.     

Precautionary Bidding in Auctions

We analyze bidding behavior in auctions when risk‐averse buyers bid for a good whose value is risky. We show that when the risk in the valuations increases, DARA bidders will reduce their bids by more than the appropriate increase in the risk premium. Ceteris paribus, buyers will be better off bidding for a more risky object in first price, second price, and English auctions with affiliated common (interdependent) values. This “precautionary bidding” effect arises because the expected marginal utility of income increases with risk, so buyers are reluctant to bid so highly. We also show that precautionary bidding behavior can make DARA bidders prefer bidding in a common values setting to bidding in a private values one when risk‐neutral or CARA bidders would be indifferent. Thus the potential for a “winner's curse” can be a blessing for rational DARA bidders.     

EMPIRICAL UTILITY FUNCTIONS AND RANDOM DEVICES: AN EXPERIMENT

The primary purpose of the present experiment was to examine the effects on the empirical derivation of executive's utility functions caused by the use of random device analogues. The results indicate that utility functions obtained using a random device analogue imply more risk aversion than when these functions are determined by simulating actual decision situations. Furthermore, there is also evidence that the bias is directly related to the monetary amounts involved.     

定常风险偏好效用函数式及其参数确定问题

按von Neumann-Morgenstern期望效用理论建立风险偏好模型,构造一种关于未知效用度量的特殊函数方程,据此导出满足特定风险偏好性质的效用函数式,由于未知参数可严格确定,效用度量因此成了一种可按已知公式进行计算的问题。     

SUBJECTIVE EVALUATIONS FOR PRODUCT DESIGN DECISIONS

This paper presents a simple methodology to enable a firm to incorporate consumers' subjective evaluations early into the concept screening stage of a new product introduction process. The methodology involves eliciting ranked preference judgments toward a set of alternative product concepts, each described as a profile of attributes and derived from an interval-scaled utility score using Thurstone's comparative judgment model. The derived utility scores are then decomposed into simple effects attributable to each of the attributes, thus yielding functional representations of consumer preferences. Mathematical models are developed to utilize the functions to determine the best concept. Empirical illustrations are provided for application of the methodology.     

Individual Sense of Justice: A Utility Representation

We present an axiomatic model depicting the choice behavior of a self‐interest seeking moral individual over random allocation procedures. Individual preferences are decomposed into a self‐interest component and a component representing the individual's moral value judgment. Each component has a distinct utility representation, and the preference relation depicting the choice behavior is representable by a real‐valued function defined on the components utilities. The utility representing the self‐interest component is linear and the utility representing the individual's moral value judgment is quasi‐concave. The addition of a hexagon condition implies that the utility representing the individual's preference is additively separable in the components utilities.     

AN UPDATE ON THE APPLICABILITY OF AN OCCUPATIONAL GOAL-EXPECTANCY MODEL IN PROFESSIONAL ACCOUNTING ORGANIZATIONS

The validity of an occupation goal-expectancy model was evaluated using the actual position attainment behavior of professional public accounting firm employees. Actual position attainment behavior was monitored over a four-year period. The hypothesized model relationships between the model variables, goal choice behavior, and position attainment were tested using linear multiple discriminant analysis and simple classification matrices. A within-subject analysis was undertaken. The findings generally support the hypothesized relationships between expected utility, goal choice, and position attainment and the model's applicability within large public accounting firms.     

Level‐k Auctions: Can a Nonequilibrium Model of Strategic Thinking Explain the Winner's Curse and Overbidding in Private‐Value Auctions?

This paper proposes a structural nonequilibrium model of initial responses to incomplete‐information games based on “level‐k” thinking, which describes behavior in many experiments with complete‐information games. We derive the model's implications in first‐ and second‐price auctions with general information structures, compare them to equilibrium and Eyster and Rabin's (2005) “cursed equilibrium,” and evaluate the model's potential to explain nonequilibrium bidding in auction experiments. The level‐k model generalizes many insights from equilibrium auction theory. It allows a unified explanation of the winner's curse in common‐value auctions and overbidding in those independent‐private‐value auctions without the uniform value distributions used in most experiments.     

基于活动方法的瓶颈模型与拥挤收费问题研究

Vickrey提出的基于出行的瓶颈模型以出行作为分析单位,没有考虑出行与活动之间的相互关联.本文对Vickrey的瓶颈模型进行了拓展,提出了基于活动的瓶颈模型来研究通勤者早晨上班出发时间决策问题,模型考虑了通勤者对出行负效用与活动效用之间的权衡.在基于活动的瓶颈模型的基础上,分别研究了常数和线性边际活动效用下瓶颈动态拥挤收费和阶梯收费问题,并与传统的瓶颈模型的解进行比较.结果表明,当活动的边际效用为线性函数时,瓶颈处最优动态收费曲线不再呈分段线性关系,而是分段二次曲线;与基于活动的瓶颈模型相比,传统的基于出行的瓶颈模型将高估瓶颈处的排队延误、阶梯收费水平,以及早高峰的开始和结束时间;基于出行的瓶颈模型和常数边际活动效用下的瓶颈模型导致的最优阶梯收费是最优动态收费最大值的一半,并且刚好消除瓶颈处排队延误的一半;与线性边际活动效用下的瓶颈模型相比较,两者低估了阶梯收费能消除的瓶颈排队,从而低估了阶梯收费的效率.     

碳排放权的非对称拍卖模型及其配置效率

作为我国碳交易体系的试金石,“七省市”试点运营状况如何?是学界和管理层特别关注的一个焦点问题.以碳排放权的初始配置准则为切入点,展开理论探讨与定性分析,发现:在现行的溯源免费配置准则下,试点地区的碳交易市场有明显的“聚类效应”特征,其原因是排放权的误配导致企业逆向选择所致.为了从机制设计本源上消除企业减排的逆向选择,把拍卖有偿配置准则引入碳交易市场中,构建企业减排投资回报率指标,定义排放权的社会最优配置,建立碳排放权的非对称拍卖模型,分析异质性企业在碳排放权拍卖中的投标策略及其拍卖前的减排投资决策行为,剖析企业所有权差异对其减排投资和排放权配置结果的影响,阐述政府补贴企业减排投资的政策效果,基于政府补贴政策效果提出完善我国碳交易市场的相关建议.     

The 2007 Subprime Market Crisis Through the Lens of European Central Bank Auctions for Short‐Term Funds

We study European banks' demand for short‐term funds (liquidity) during the summer 2007 subprime market crisis. We use bidding data from the European Central Bank's auctions for one‐week loans, their main channel of monetary policy implementation. Our analysis provides a high‐frequency, disaggregated perspective on the 2007 crisis, which was previously studied through comparisons of collateralized and uncollateralized interbank money market rates which do not capture the heterogeneous impact of the crisis on individual banks. Through a model of bidding, we show that banks' bids reflect their cost of obtaining short‐term funds elsewhere (e.g., in the interbank market) as well as a strategic response to other bidders. The strategic response is empirically important: while a naïve interpretation of the raw bidding data may suggest that virtually all banks suffered an increase in the cost of short‐term funding, we find that, for about one third of the banks, the change in bidding behavior was simply a strategic response. We also find considerable heterogeneity in the short‐term funding costs among banks: for over one third of the bidders, funding costs increased by more than 20 basis points, and funding costs vary widely with respect to the country‐of‐origin. The funding costs we estimate using bidding data are also predictive of market‐ and accounting‐based measures of bank performance, reinforcing the usefulness of “revealed preference” information contained in bids.     

PERFORMANCE OF THE EXPECTED UTILITY METHOD AND TWO OTHER NORMATIVE METHODS IN INSURANCE DECISION MAKING*

In an experiment, thirty-six professional insurance men employed the utility method, the worry method, and the comparison method in two insurance problems to determine the appropriate insurance coverage. It was found that the best act with the utility method almost always was no insurance, whereas the best act with the other two methods tended to be complete insurance. The utility method best act rarely agreed with the subject's actual preferred act, while the comparison method best act usually was the same or almost the same as the actual preferred act. While the worry method suggests that the subjects typically are risk averse, the utility functions obtained tend to show that the subjects typically are not risk averse.     

Preference-Order Recursion for Finding Relevant Pure,Admissible and Optimal Statistical Decision Functions*

A preference-order recursion algorithm for obtaining a relevant subset of pure, admissible (non-dominated, efficient) decision functions which converges towards an optimal solution in statistical decision problems is proposed. The procedure permits a decision maker to interactively express strong binary preferences for partial decision functions at each stage of the recursion, from which an imprecise probability and/or utility function is imputed and used as one of several pruning mechanisms to obtain a reduced relevant subset of admissible decision functions or to converge on an optimal one. The computational and measurement burden is thereby mitigated significantly, for example, by not requiring explicit or full probability and utility information from the decision maker. The algorithm is applicable to both linear and nonlinear utility functions. The results of behavioral and computational experimentation show that the approach is viable, efficient, and robust.     

DEMAND MANAGEMENT: THE EVALUATION OF PRICE AND DUE DATE NEGOTIATION STRATEGIES USING SIMULATION

The research considers the problem of demand management in a firm where the firm's historical delivery service level reputation influences the number of quotation requests from its potential customers. Customers have a maximum and the firm has a minimum net price to due date tradeoff curve for each job. The demand management function bargains with the customer over price and promised due date. Bargaining finishes either with an agreed price and delivery date or with the customer refusing the firm's bid and placing the order elsewhere. The firm's objective is to maximize its long-term net revenue. The firm's demand management negotiation strategy guides this bidding process. The research demonstrates the use of simulation to test different demand management bidding and negotiation strategies for different market and firm scenarios. The demonstration uses 16 scenarios to test the different demand management negotiation strategies with a model of a classical job shop in a classical market. The investigation examines finite scheduling-based due date estimation methods, as well as the more traditional parameter-based methods. This demonstration shows that it is possible to test different bidding policies, using a simulation model of a firm and its customers, and to obtain usable results.     

MODEL FORMULATION FOR FLEET SIZE ANALYSIS OF A UNIVERSITY MOTOR POOL

A GPSS/360 model was developed to investigate the behavior of a university's motor pool dispatch fleet. Time-series data were collected and frequency distributions were constructed for vehicle request patterns and trip-duration times. Regression analysis was performed to formulate trip mileage generators as functions of service time. Appropriate statistical goodness-of-fit tests were conducted to ascertain the extent of congruence between actual system behavior and expectations based on a number of theoretical distributions. Analysis of simulated response variables indicates that the model's internal structure reproduces reality to a high degree. Fifteen years of simulated experience were generated for six alternative fleet size configurations; results suggest that reductions in existing fleet capacity could be realized without effecting undue impairment in service levels.     

A Polynomial Optimization Approach to Principal–Agent Problems

This paper presents a new method for the analysis of moral hazard principal–agent problems. The new approach avoids the stringent assumptions on the distribution of outcomes made by the classical first‐order approach and instead only requires the agent's expected utility to be a rational function of the action. This assumption allows for a reformulation of the agent's utility maximization problem as an equivalent system of equations and inequalities. This reformulation in turn transforms the principal's utility maximization problem into a nonlinear program. Under the additional assumptions that the principal's expected utility is a polynomial and the agent's expected utility is rational in the wage, the final nonlinear program can be solved to global optimality. The paper also shows how to first approximate expected utility functions that are not rational by polynomials, so that the polynomial optimization approach can be applied to compute an approximate solution to nonpolynomial problems. Finally, the paper demonstrates that the polynomial optimization approach extends to principal–agent models with multidimensional action sets.