Managing Risk of Supply Disruptions: Incentives for Capacity Restoration

A supplier facing the prospect of disruption has to decide whether or not to invest in restoration capability. With restoration capability, if disruption occurs, additional costly effort can be exerted to rebuild capacity, although its outcome is uncertain. We study how a firm (buyer) can use incentive mechanisms to motivate a supplier's investment in capacity restoration, and compare this approach with the traditional approach of diversifying part of the order to an expensive but reliable supplier. Under a Restoration Enhancement (RE) strategy, the buyer uses price and/or order quantity incentives to encourage the supplier's restoration investment decision. Two different cases are considered—when the incentive is committed to ex ante (prior to disruption) and when it is committed to ex post (after disruption). In contrast, under a Supplier Diversification (SD) strategy, the buyer splits orders between a reliable supplier and an unreliable supplier to hedge against the disruption risk. Here, the buyer does not provide any separate incentive to the unreliable supplier. Our analysis indicates that under the RE strategy, where the buyer offers incentives, both the buyer and the supplier (weakly) prefer the ex ante commitment over the ex post one. Furthermore, the RE strategy is preferred over the SD strategy when the unreliable supplier's restoration outcome is more predictable or when a high restoration outcome is more likely. However, the buyer's preference for the SD strategy increases as market demand increases.     

Long‐Term Contracting: The Role of Private Information in Dynamic Supply Risk Management

We examine the critical role of evolving private information in managing supply risk. The problem features a dyadic channel where a dominant buyer operates a multiperiod inventory system with lost sales and fixed cost. He replenishes from a supplier, whose private state of production is vulnerable to random shocks and evolves dynamically over time. We characterize the optimal inventory policy with a simple semi‐stationary structure; it distorts order quantity for limiting information rent only in the initial period; the optimal payment compensates for production cost in every period but concedes real information rent only in the initial period. These properties allow us to derive an easy‐to‐implement revenue‐sharing contract that facilitates ex ante strategic planning and ex post dynamic execution. This work advances our understanding on when and how to use private information in dynamic risk management.     

Obtaining Informationally Consistent Decisions When Computing Costs with Limited Information

We demonstrate the need to view in a dynamic context any decision based on limited information. We focus on the use of product costs in selecting the product portfolio. We show how ex post data regarding the actual costs from implementing the decision leads to updating of product cost estimates and potentially trigger a revision of the initial decision. We model this updating process as a discrete dynamical system (DDS). We define a decision as informationally consistent if it is a fixed‐point solution to the DDS. We employ numerical analysis to characterize the existence and properties of such solutions. We find that fixed points are rare, but that simple heuristics find them often and quickly. We demonstrate the usefulness and robustness of our methodology by examining the interaction of limited information with multiple decision rules (heuristics) and problem features (size of product portfolio, profitability of product markets). We discuss implications for research on cost systems.     

Income Distribution,Public Expenditure and Equality

Abstract. The increased role of public expenditure in industrialised countries involves new theoretical and empirical problems: general equilibrium models must be fully accommodated with the structural presence of the public sector and at the same time we need a better understanding of the redistributive impact of non-market rules. Therefore we suggest looking at our economies as a resource allocation mechanism. in which a Walrasian mechanism (without auctioneer) interacts with a political mechanism: we suggest that ex post resource equality is the driving force behind the increasing role of the public sector, and therefore it is also the crucial test against which to evaluate the impact of public expenditure. A stylised way to look at our economies therefore can be as follows: ex ante equality is the domain of market, whilst ex post equality is the domain of the public sector. This approach is compared with cross-section data of 16 countries and more detailed data, both cross-section and time-series, for the case of Italy: empirical results suggest that ex post equality is not a clearcut target, but rather it arises as the net outcome of contrasting forcas.     

A Multiperiod Audit Staff Planning Model Using Multiple Objectives: Development and Evaluation*

The audit staff planning problem, a specific type of manpower planning problem, has been modeled using goal programming and, more recently, multiple objective linear programming. Prior studies developed single-period models and did not go beyond the model building stage. This study develops a multiperiod audit staff planning model and evaluates the model using a test application involving actual decision makers (partners in public accounting firms). The multiperiod model includes seven objectives to be optimized: profit (to be maximized), late completion of work, work declined, staff augmentation, staff reduction, underutilization of the work force, and shortfall in meeting professional development targets (all to be minimized). Over a four-quarter planning horizon with one “busy season,” the model is subject to constraints with respect to the projected audit work load, ability to substitute personnel and to perform interim audit work, available staff hours (including overtime limitations), supervisory requirements, and professional development targets. Results of the test application showed that the model was capable of producing a range of values for each objective. The participants were exposed to much of that range when making their decisions. The results also showed that all objectives were important and that participants were consistent in choosing their preferred level of each objective over several runs of the model. These results and the reactions of the participants demonstrate that the model is usable by actual decision makers and has potential for a number of specific applications.     

ISO 9000—a marketing tool for U.S. agribusiness

The relevance of the ISO 9000 series of quality management systems (QMS) for U.S. agribusiness is analyzed. Certified firms from several industries were surveyed to determine their before (ex ante) and after (ex post) perspectives of the QMS. Results for the agribusiness subsample are compared to those for firms from other industries to determine if they behave differently. Anticipated marketing advantages (increasing market share and providing access to new markets) of the QMS were critical factors that encouraged the pursuit of the certificate. The average cost to attain certification was $101.400 and to maintain certification was an additional $26,500 per year.     

Zero-base budgeting—Dealing with conflicting objectives

While Zero-Base Budgeting (ZBB) has received considerable attention in the public sector, virtually all the studies dealing with the system have neglected or given cursory attention to the problem of multiple conflicting objectives. This paper presents a goal programming approach as a systematic means to develop the ZBB process for multiple objectives. This approach allows the administrators to more realistically portray the decision environment as well as their judgment in their budgetary planning models, thus making the budgeting an effective and pragmatic way to implement the planning and decision making process. This study demonstrates a goal programming based ZBB system in the public sector based on real-world data.     

A Newsvendor Who Chooses Informational Effort

We study a newsvendor who can acquire the services of a forecaster, or, more generally, an information gatherer (IG) to improve his information about demand. When the IG's effort increases, does the average ex ante order quantity rise or fall? Do average ex post sales rise or fall? Improvements in information technology and in the services offered by forecasters provide motivation for the study of these questions. Much depends on our model of the IG and his efforts. We study an IG who sends a signal to a classic single‐period newsvendor. The signal defines the newsvendor's posterior probability distribution on the possible demands and the newsvendor uses that posterior to calculate the optimal order. Each of the possible posteriors is a scale/location transform of the same base distribution. When the IG works harder, the average scale parameter drops. Higher IG effort is always useful to the newsvendor. We show that there is a critical value of order cost. For costs on one side of this value more IG effort leads to a higher average ex ante order and for costs on the other side to a lower average order. But for all costs, more IG effort leads to higher average ex post sales. We obtain analogous results for a “regret‐averse” newsvendor who suffers a penalty that is a nonlinear function of the discrepancy between quantity ordered and true demand.     

A general space-time model for combinatorial optimization problems (and not only)

We consider the problem of defining a strategy consisting of a set of facilities taking into account also the location where they have to be assigned and the time in which they have to be activated. The facilities are evaluated with respect to a set of criteria. The plan has to be devised respecting some constraints related to different aspects of the problem such as precedence restrictions due to the nature of the facilities. Among the constraints, there are some related to the available budget. We consider also the uncertainty related to the performances of the facilities with respect to considered criteria and plurality of stakeholders participating to the decision. The considered problem can be seen as the combination of some prototypical operations research problems: knapsack problem, location problem and project scheduling. Indeed, the basic brick of our model is a variable x_ilt which takes value 1 if facility i is activated in location l at time t, and 0 otherwise. Due to the conjoint consideration of a location and a time in the decision variables, what we propose can be seen as a general space-time model for operations research problems. We discuss how such a model permits to handle complex problems using several methodologies including multiple attribute value theory and multiobjective optimization. With respect to the latter point, without any loss of the generality, we consider the compromise programming and an interactive methodology based on the Dominance-based Rough Set Approach. We illustrate the application of our model with a simple didactic example.     

Can Environmental Insurance Succeed Where Other Strategies Fail? The Case of Underground Storage Tanks

Private risk reduction will be socially efficient only when firms are liable for all the damage that they cause. We find that environmental insurance can achieve social efficiency even when two traditional policy instruments—ex post fines and risk management mandates with ex ante fines—do not. Inefficiency occurs with ex post fines, when small firms declare bankruptcy and escape their liabilities, limiting the incentives from this policy tool. Firms ignore mandates to implement efficient risk management because regulatory agencies do not have sufficient resources to monitor every firm. The evolution of the U.S. Environmental Protection Agency's and states’ underground storage tank programs suggests that mandating environmental insurance can address inefficiency due to small firms declaring bankruptcy. Comparing insurance mandates to risk management mandates, the burden on a regulator is lower if all it has to do is to confirm that the firm has insurance rather than that the firm has actually, and effectively, implemented required management practices. For underground storage tanks, we show that insurance lowered toxic releases.     

Comparing a new technology with its predecessor—Steel making

This paper examines the physical and economic performance of a major innovation in steel making, the Basic Oxygen Furnace, and compares it with the performance of the traditional, open-hearth process. Evaluations are based on actual records from five American plants, covering three different time periods, and are set against engineering and management expectations as to the innovation's effects. Interviews with managers and technical personnel complemented the statistical findings. The analysis considers: how the attractiveness of the innovation was determined ex ante; the relative accuracy of the expected technological and economic expectations; the interactions of the innovation with the surrounding production system; and the objectives of post-installation technical and managerial adaptations.     

Measuring the Performance of Corporate Acquisitions: An Empirical Comparison of Alternative Metrics*

The choice of performance measure has long been a difficult issue facing researchers. This article investigates the comparability of four common measures of acquisition performance: cumulative abnormal returns, managers' assessments, divestment data and expert informants' assessments. Independently each of these measures indicated a mean acquisition success rate of between 44–56%, within a sample of British cross‐border acquisitions. However, with the exception of a positive relationship between managers' and expert informants' subjective assessments, no significant correlation was found between the performance data generated by the alternative metrics. In particular, ex‐ante capital market reactions to an acquisition announcement exhibited little relation to corporate managers' ex‐post assessment. This is seen to reflect the information asymmetry that can exist between investors and company management, particularly regarding implementation aspects. Overall, the results suggest that future acquisitions studies should consider employing multiple performance measures in order to gain a holistic view of outcome, while in the longer term, opportunities remain to identify and refine improved metrics.     

Policy Incentives for Dangerous (But Necessary) Operations

In industries where firms perform dangerous (but necessary) operations, liability costs—due to potential harm to third parties—can be significant. Firms may therefore find it optimal to exit the market, and this may lead to an inefficiently low number of incumbents. A social planner can discourage exit by offering appropriately designed subsidies. Ex ante subsidies defray the costs associated with making operations safer (e.g., funds to subsidize the purchase of safety equipment). Ex post subsidies mitigate the financial damages caused by an accident (e.g., funds to defray the cost of cleaning up a toxic spill). We consider a model where (i) firms have private information about their ability to improve reliability and (ii) reliability investments are unobservable. We demonstrate that when the social value of reliability outweighs the benefit of increased competition, it is optimal to offer ex ante subsidies alone (i.e., to subsidize the cost of making operations safer). Conversely, when the benefits of competition outweigh the benefits of reliability, a combination of ex ante and ex post subsidies is optimal (i.e., not only to subsidize safer operations, but also to share the costs of a potential accident).     

A disaggregation problem for a multiplant,multiproduct scheduling application

Abstract

This paper discusses an integer programming technique for planning production when there are multiple plants involved in the production of a number of products and the plants are relatively close. This allows for the closing of one plant during a planning period with a shift of the mobile resources, mainly labour, to other plants. The model is introduced and then an example problem is given. Finally, there is a discussion of why this method improves upon other techniques proposed to solve this problem. Some actual case studies are cited.     

Governmental planning and budgeting with multiple objective models

This paper presents a goal programming model development and application for a state level public health care agency. Only limited applications of macro planning processes related to health care have been presented in the literature. In that regard, this paper describes briefly the goal programming model, the background of the agency involved and the specific models developed. Three formulations of the model are presented involving (1) the resources required to achieve all goals, (2) the goal attainment status utilizing a likely budget and (3) a proposal for resolving the goal desire-resource limitation dilemma.     

Contingency Strategies in Managing Supply Systems with Uncertain Lead‐Times

The globalization of markets and geographic dispersion of production facilities, combined with a heavy outsourcing of supply chain processes, have substantially increased the exposure of supply chains to supply lead‐times of long and uncertain nature. In this paper, we study the potential use of two contingency strategies on top of the conventionally used time buffer—statically planned safety lead‐time (SL)—approach to deal with the lead‐time uncertainty. These are (1) the ex‐ante planning for disruption safety stock (DSS) to be released when a “disruption” (in this case, late delivery of the order) occurs; and (2) the ex‐post dynamic emergency response (DER), which dynamically decides on the timing and size of an emergency order to be placed. Our work elaborates on the optimal parameter setting for these strategies, compares their added values when used to complement the traditional SL approach, and examines how the use of the contingency strategies affects the SL and corresponding cycle length of a periodic review system. Our research finds that: (1) the above contingency strategies reduce the reliance on the SL and are cost effective when the coefficient of variation (CV) of the uncertain lead‐time is high; (2) it is important to re‐optimize the SL to account for the contingency plans; and (3) re‐optimization of the cycle length to account for the presence of the contingency responses, as opposed to using an EOQ‐determined cycle length, does not significantly improve the cost performance. However, such re‐optimization does well in the SL approach when the CV of the uncertain lead‐time is high.     

A survey of goal programming

In this paper the applications of goal programming to industrial and economic planning are reviewed, and it is shown how the linear programming framework can be extended to include a series of goals (or objectives). A planning method is suggested in which the decision maker is presented with a list of all the possible attainable goals from which he picks the most appropriate set.     

A goal programming model for paper recycling system

The conflict between economic optimization and environmental protection has received wide attention in recent research programs for waste management system planning. This has also resulted in a set of new waste management goals in reverse logistics system planning. The purpose of this analysis is to formulate a mixed integer goal programming (MIGP) model to assist in proper management of the paper recycling logistics system. The model studies the inter-relationship between multiple objectives (with changing priorities) of a recycled paper distribution network. The objectives considered are reduction in reverse logistics cost; product quality improvement through increased segregation at the source; and environmental benefits through increased wastepaper recovery. The proposed model also assists in determining the facility location, route and flow of different varieties of recyclable wastepaper in the multi-item, multi-echelon and multi-facility decision making framework. The use of the model has been illustrated through a problem of paper recycling in India.     

Ranked Items Auctions and Online Advertisement

We study auctions for a set of commonly‐ranked items where each buyer has unit demand. This setting has promising applications in areas such as keyword auctions in the search engine advertising industry, the sale of quality‐ranked raw materials, etc. An auction mechanism suitable for this setting is the simultaneous pooled auction (SPA), where each bidder simultaneously submits a single bid and is allocated an object based on the rank of his bid among all the bids. We study how to improve the seller's expected revenue by enforcing a reserve price in an SPA. We find that the use of an appropriate reserve price may significantly increase the seller's revenue, especially when the number of items for sale is relatively large compared to the number of participating bidders. One inherent problem in the SPA is that some bidders may incur ex post losses; that is, they pay more than what they value the received objects. We propose a tailored VCG mechanism that generates the same expected revenue as the SPA does, while bidders do not incur any ex post loss. We also discuss the potential applications of this research to keyword auctions.