Escalation: The Role of Problem Recognition and Cognitive Bias

Escalation of commitment to a failing course of action is an enduring problem that remains central to the study of managerial behavior. Prior research suggests that escalation behavior results when decision makers choose to ignore negative feedback concerning the viability of a previously chosen course of action. Previous work has also suggested that certain cognitive biases might promote escalation behavior, but there has been little attempt to explore how biases other than framing affect escalation. In this article, we explore the extent to which decision makers actually perceive negative feedback as indicative of a problem and how this influences their decision to escalate. Although problem recognition and cognitive biases have been intensively studied individually, little is known about their effect on escalation behavior. In this research, we construct and test an escalation decision model that incorporates both problem recognition and two cognitive biases: selective perception and illusion of control. Our results revealed a significant inverse relationship between problem recognition and escalation. Furthermore, selective perception and illusion of control were found to significantly affect both problem recognition and escalation. The implications of these findings for research and practice are discussed. To improve problem recognition and reduce the incidence of escalation, practicing managers should implement modern project management practices that can help to identify and highlight potential problems while guarding against these two key cognitive biases that promote the behavior.     

Information Systems Project Continuation in Escalation Situations: A Real Options Model

Software project escalation has been shown to be a widespread phenomenon. With few exceptions, prior research has portrayed escalation as an irrational decision‐making process whereby additional resources are plowed into a failing project. In this article, we examine the possibility that in some cases managers escalate their commitment not because they are acting irrationally, but rather as a rational response to real options that may be embedded in a project. A project embeds real options when managers have the opportunity but not the obligation to adjust the future direction of the project in response to external or internal events. Examples include deferring the project, switching the project to serve a different purpose, changing the scale of the project, implementing it in incremental stages, abandoning the project, or using the project as a platform for future growth opportunities. Although real options can represent a substantial portion of a project's value, they rarely enter into a project's formal justification process in the traditional quantitative discounted cash‐flow‐based project valuation techniques. Using experimental data collected from managers in 123 firms, we demonstrate that managers recognize and value the presence of real options. We also assess the relative importance that managers ascribe to each type of real option, showing that growth options are more highly valued than operational options. Finally, we demonstrate that the influence of the options on project continuation decisions is largely mediated by the perceived value that they add. Implications for both theory and practice are discussed.     

New Product Development Decision‐Making Effectiveness: Comparing Individuals,Face‐To‐Face Teams,and Virtual Teams*

A total of 411 subjects participated in two decision‐making experiments in order to examine the effectiveness of new product development project continuation decisions. Using escalation of commitment theory, in Study 1, individual versus face‐to‐face team decision‐making effectiveness was compared. Study 2, an extension of Study 1, compared the new product development decision‐making effectiveness of individuals, face‐to‐face teams, and virtual teams. A virtual team is a geographically and temporally dispersed and electronically communicating work group. In Study 2, the virtual teams communicated asynchronously via groupware technology. Our findings suggest that teams make more effective decisions than individuals, and virtual teams make the most effective decisions.     

Organizational Silence and Whistle‐Blowing on IT Projects: An Integrated Model*

An individual's reluctance to report bad news about a troubled information technology (IT) project has been suggested as an important contributor to project failure and has been linked to IT project escalation as well. To date, information systems researchers have drawn from the mum effect and whistle‐blowing literature to gain a better understanding of the factors that influence bad news reporting. More recent theoretical work in the area of organizational silence offers a promising new conceptual lens, but remains empirically untested. In this research note, we integrate key elements of Morrison and Milliken's (2000) model of organizational silence, which has never been empirically tested, with the basic whistle‐blowing model adapted from Dozier and Miceli (1985) . Using a role‐playing experiment, we investigate how organizational structures/policies, managerial practices, and degree of demographic dissimilarity between employees and top managers create a climate of silence and how this climate, in turn, affects an individual's willingness to report. Our results show that all three types of factors contribute to a climate of silence, exerting both direct and indirect influence on willingness to report, as hypothesized. The implications of these findings and directions for future research are discussed.     

Robust Resource Allocation Decisions in Resource‐Constrained Projects*

The well‐known deterministic resource‐constrained project scheduling problem involves the determination of a predictive schedule (baseline schedule or pre‐schedule) of the project activities that satisfies the finish–start precedence relations and the renewable resource constraints under the objective of minimizing the project duration. This baseline schedule serves as a baseline for the execution of the project. During execution, however, the project can be subject to several types of disruptions that may disturb the baseline schedule. Management must then rely on a reactive scheduling procedure for revising or reoptimizing the baseline schedule. The objective of our research is to develop procedures for allocating resources to the activities of a given baseline schedule in order to maximize its stability in the presence of activity duration variability. We propose three integer programming–based heuristics and one constructive procedure for resource allocation. We derive lower bounds for schedule stability and report on computational results obtained on a set of benchmark problems.     

Incentives in a Stage‐Gate Process

Many large organizations use a stage‐gate process to manage new product development projects. In a typical stage‐gate process project managers learn about potential ideas from research and exert effort in development while senior executives make intervening go/no‐go decisions. This decentralized decision making results in an agency problem because the idea quality in early stages is unknown to the executive and the project manager must exert unobservable development effort in later stages. In light of these challenges, how should the firm structure incentives to ensure that project managers reveal relevant information and invest the appropriate effort to create value? In this study, we develop a model of adverse selection in research and moral hazard in development with a go/no‐go decision at the intervening gate. Our results show that the principal's uncertainty regarding early‐stage idea quality—a term we refer to as idea risk—alters the effect of late‐stage development risk. The presence of idea risk can alter the incentives offered to the agent and may lead the principal to reject projects that otherwise seem favorable in terms of positive net present value. A simulation of early‐stage ideas, found through search on a complex landscape, shows that the firm can mitigate the negative effects of idea risk by encouraging breadth of search and high tolerance for failure.     

Defining Problems Fast and Slow: The U‐shaped Effect of Problem Definition Time on Project Duration

This study examines how time spent in problem definition affects problem solving in projects such as Six Sigma projects. Our hypotheses are tested using data collected from 1558 Six Sigma projects in a company. The results show evidence of a U‐shaped relationship between the amount of time spent in the Define phase and project duration. This finding suggests that spending too little time on problem definition potentially causes poor problem formulation, which leads to deficient problem solving and lengthens overall project time. On the other hand, too much time spent on problem definition can lead to unneeded delays in project completion due to diminishing returns on problem definition efforts. Furthermore, the optimal balance between spending too little and too much time depends on prior project experience and project complexity. Prior project experience reduced project completion time and weakened the U‐shaped effect. Conversely, complex projects took longer and appeared to show some evidence of a stronger U‐shaped effect; this suggests balancing the time spent in the Define phase was more challenging for complex projects. Our study also underscores the importance of managing project duration, as projects that were completed faster tended to be associated with higher project savings.     

Distributed Decision‐Making in Supply Chains and Private E‐Marketplaces

This paper develops a distributed decision‐making framework for the players in a supply chain or a private e‐marketplace to collaboratively arrive at a global Pareto‐optimal solution. In this model, no player has complete knowledge about all the costs and constraints of the other players. The decision‐making framework employs an iterative procedure, based on the Integer L‐shaped method, in which a master problem is solved to propose global solutions, and each player uses his local problems to construct feasibility and optimality cuts on the master problem. The master problem is modeled as a mixed‐integer program, and the players' local problems are formulated as linear programs. Collaborative planning scenarios in private e‐marketplaces and in supply chains were formulated and solved for test data. The results show that this distributed model is able to achieve near‐optimal solutions considerably faster than the traditional centralized approach.     

Integrated project operations and personnel scheduling with multiple labour classes

The main theme of this paper is improving project schedules by integrating the scheduling of project jobs and labour resources. An ILP model is presented of the integrated project operations and personnel scheduling problem with multiple labour categories. Traditionally, this problem is solved in two steps: first, operations are scheduled by solving the resource-constrained project scheduling problem; then, labour categories are scheduled by solving the personnel days-off scheduling problem. The proposed model combines the two stages into an integrated problem, which is solved in one step. Using 48 test problems, the two methods were compared in terms of total cost, labour cost and scheduling efficiency. The results clearly indicate that the integrated model outperforms the traditional two-step method.     

The Influence of Forward‐Looking Antecedents,Uncertainty, and Anticipatory Emotions on Project Escalation*

This study extends research on the escalation of commitment phenomenon by investigating decision makers' tendency to look forward to project completion and develop anticipatory perceptions and emotions concerning goal attainment. We examine the influence of two project‐specific predictors of escalation (level of progress and presence of an alternative project) on perceived uncertainty and the extent to which anticipatory emotions (i.e., current affective reactions to possible future events) mediate the influence of uncertainty on levels of commitment to a failing project. Results indicated that level of progress and the presence of an alternative project affected uncertainty, which influenced anticipatory emotions. Lower levels of uncertainty and higher levels of positive anticipatory emotions increased the tendency to escalate commitment.     

The theory of S-curve discontinuity in the medical care field

Confusion reigns supreme in the health are field today. In a previous paper, I described my thoughts about the reasons for this chaos. This article reviews the gradual escalation of health care costs and many of the unsuccessful methods to control them, reiterates the theory of S-Curve discontinuity in health care and develops a "tool" that will enable physician executives to determine whether or not a product or process in health care will succeed in the near and distant future. This new tool can be of value to all health care providers, investors, health planners, politicians involved in evolving health care legislation, and any others who have an investment in the future of health care.     

基于最优停时理论的创业投资退出决策模型研究

创业投资的退出是创业投资运作过程中最关键的环节,对创业投资退出问题的研究是创业投资理论的关注重点。论文以研究创业投资不同退出方式的价值为对象,基于创业投资项目产生的现金流遵循几何布朗运动假设的基础上,分析了创业投资项目采取立即退出的价值和继续维持以获取最优退出方式的价值,以最优停时理论为建模依据,比较这两种情况的价值构建了创业投资退出时机的一般模型。在分析不同退出方式产生的退出损益基础上,结合一般模型构建了最优退出方式和最优退出时机相结合的退出决策模型。论文提出了一个分析创业投资退出决策的一般模型,并用该模型对一个实例进行模拟分析,以便验证模型的实用性。     

Reducing Requirement Incorrectness and Coping with Its Negative Impact in Information System Development Projects

The negative impact of incorrect requirements on information system development (ISD) project performance has long been acknowledged. This study addresses the problem of incorrect requirements by proposing a model that combines the error reduction and coping concepts proposed by Field, Ritzman, Safizadeh, and Downing (2006) with the view that ISD is a knowledge‐intensive process. The model hypothesizes that when developers and users possess an understanding of each other's primary domain of knowledge, the prevention of incorrect requirements and the mitigation of the negative consequences of incorrect requirements tend to improve project performance. Data collected from 250 ISD professionals on the basis of their experiences of recently completed ISD projects confirmed all of our hypotheses. The results demonstrate that the eliciting of incorrect requirements can be reduced when users and developers possess cross‐domain understanding and when requirement analysis methodologies and techniques are available. Furthermore, the negative impact of incorrect requirements on project performance can be mitigated when developers have sufficient ISD knowledge and behavioral knowledge.     

具有时间转换约束的离散时间-费用权衡问题研究

离散时间-费用权衡问题(DTCTP)是项目进度中研究最多的双目标优化问题,它通常以三种形式出现:(1)P1:截止日期问题,在项目截止日期约束下使完成项目的总费用最小;(2)P2:预算问题,在费用预算约束下使项目工期最短;(3)P3:工期-费用曲线问题,找出全部有效的工期-费用模式集合。然而,考虑时间转换约束(TSC)的DTCTP却很少被关注。本文首先介绍时间转换约束的问题描述,在此基础上,建立具有活动类型时间转换约束的DTCTPTSC-P2模型;从实用角度出发,设计求解模型的遗传算法;最后,用一个真实项目实例说明模型的合理性和算法的有效性,对算例分析结果表明,该模型对承包商更准确地进行项目工期-费用权衡决策具有借鉴意义。     

THE ROLE OF INFORMATION IN INNOVATION AND COMPETITION

Innovation is typically a trial‐and‐error process. While some research paths lead to the innovation sought, others result in dead ends. Because firms benefit from their competitors working in the wrong direction, they do not reveal their dead‐end findings. Time and resources are wasted on projects that other firms have already found to be fruitless. We offer a simple model with two firms and two research lines to study this prevalent problem. We characterize the equilibrium in a decentralized environment that necessarily entails significant efficiency losses due to wasteful dead‐end replication and an information externality that leads to an early abandonment of the risky project. We show that different types of firms follow different innovation strategies and create different kinds of welfare losses. In an extension of the core model, we also study a centralized mechanism whereby firms are incentivized to disclose their actions and share their private information in a timely manner. (JEL: O31, D92)     

Managing Knowledge Creation in High‐Tech R&D Projects: A Multimethod Study

R&D projects in high‐tech organizations bring together diverse knowledge domains to quickly develop new products and processes. The fast‐paced context of high‐tech organizations makes it challenging to create new knowledge and solve complex problems. Managing these R&D projects requires understanding both the mechanisms and the type of knowledge created to achieve project objectives. This research conducts a two‐phased multimethod study to understand knowledge creation in high‐tech R&D projects. The first phase uses qualitative data to develop a theory on knowledge creation in R&D projects. The second phase involves a survey that collects data from R&D projects to test the theory. Results from the case study find that R&D projects benefit from two types of knowledge – objective and intuitive. The case analyses show that intuitive and objective knowledge creation in high‐tech organizations occurs by creating not only diverse but also psychological safe project teams. The large‐scale survey finds that team diversity positively influences objective knowledge creation while psychological safety affects intuitive knowledge creation. Surprisingly, the results show that team diversity negatively affects intuitive knowledge creation. A post hoc analysis takes a more granular look at diversity and shows that different kinds of diversity have different effects on knowledge creation. This helps to better explain how to manage innovation across boundaries. Finally, the analysis shows that both objective and intuitive knowledge influence R&D project performance. Taken together, these results help explain how to manage innovation across functional boundaries to create knowledge and enhance R&D project performance.      

资源约束下可打断项目组合选择模型研究

首先,本文在已有可打断项目组合选择模型的基础上,引入了消耗性资源和可更新资源约束,构建了一个更符合实际的新模型;其次,为了达到模型简化的目的,本文给出了资金约束的现值表示,并给出了理论证明;最后,利用GAMS对模型进行了算例分析。数值实验结果表明：1）资源约束下的项目打断有时可以给企业带来积极效益,这有别于已有的研究;2）在考虑资源约束的情况下,资源消耗少且同时收益高的项目应优先执行;3）当资源的供给量较少时,资源约束是决定项目选择的关键因素。此外,通过企业实际的案例对数值实验结果进行了验证。     

Integrated Order Scheduling and Packing

We consider an integrated production–distribution scheduling model in a make‐to‐order supply chain consisting of one supplier and one customer. The supplier receives a set of orders from the customer at the beginning of a planning horizon. The supplier needs to process all the orders at a single production line, pack the completed orders to form delivery batches, and deliver the batches to the customer. Each order has a weight, and the total weight of the orders packed in a batch must not exceed the capacity of the delivery batch. Each delivery batch incurs a fixed distribution cost. The problem is to find jointly a schedule for order processing and a way of packing completed orders to form delivery batches such that the total distribution cost (or equivalently, the number of delivery batches) is minimized subject to the constraint that a given customer service level is guaranteed. We consider two customer service constraints—meeting the given deadlines of the orders; or requiring the average delivery lead time of the orders to be within a given threshold. Several problems of the model with each of those constraints are considered. We clarify the complexity of each problem and develop fast heuristics for the NP‐hard problems and analyze their worst‐case performance bounds. Our computational results indicate that all the heuristics are capable of generating near optimal solutions quickly for the respective problems.     

DAMS: A Model to Assess Domino Effects by Using Agent‐Based Modeling and Simulation

Historical data analysis shows that escalation accidents, so‐called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent‐based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent‐based modeling technique explains the domino effects from a bottom‐up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher‐level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large‐scale complicated cases.