A generic accounting model to support operations management decisions

Information systems are generally unable to generate information about the financial consequences of operations management decisions. This is because the procedures for determining the relevant accounting information for decision support are not formalised in ways that can be implemented in information systems. This paper describes a formalised procedure, which is based on the following theoretical propositions: (i) cost behaviour is described on the basis of a company's contracts for purchasing and selling resources, and (ii) hierarchical relationships between decisions are recognised, because some decisions have to be made earlier than others. Earlier decisions determine the feasible alternatives for later decisions (e.g. through constraints in available production capacity or components), and the plans that supported the earlier decisions serve as instructions for later decisions. The procedure can be implemented in information systems to provide accounting information in case later decisions deviate from these instruc tions (within the limits of the real-world constraints) because new information becomes available.     

Technology Choice and Capacity Portfolios under Emissions Regulation

We study the impact of emissions tax and emissions cap‐and‐trade regulation on a firm's technology choice and capacity decisions. We show that emissions price uncertainty under cap‐and‐trade results in greater expected profit than a constant emissions price under an emissions tax, which contradicts popular arguments that the greater uncertainty under cap‐and‐trade will erode value. We further show that two operational drivers underlie this result: (i) the firm's option not to operate, which effectively right‐censors the uncertain emissions price; and (ii) dispatch flexibility, which is the firm's ability to first deploy its most profitable capacity given the realized emissions price. In addition to these managerial insights, we also explore policy implications: the effect of emissions price level, and the effect of investment and production subsidies. Through an illustrative example, we show that production subsidies of higher investment and production cost technologies (such as carbon capture and storage technologies) have no effect on the firm's optimal total capacity when firms own a portfolio of both clean and dirty technologies, but that investment subsidies of these technologies increase the firm's total capacity, conditionally increasing expected emissions. A subsidy of a lower production cost technology, on the other hand, has no effect on the firm's optimal total capacity in multi‐technology portfolios, regardless of whether the subsidy is a production or investment subsidy.     

Role of Random Capacity Risk and the Retailer in Decentralized Supply Chains with Competing Suppliers

This research considers a supply chain under the following conditions: (i) two heterogeneous suppliers are in competition, (ii) supply capacity is random and pricing is endogenous, (iii) consumer demand, with and without an intermediate retailer, is price dependent. Specifically, we examine how uncertainty in supply capacity affects optimal ordering and pricing decisions, supplier and retailer profits, and the incentives to reduce such uncertainty. When two suppliers sell through a monopolistic retailer, supply uncertainty not only affects the retailer's diversification strategy for replenishment, but also changes the suppliers’ wholesale price competition and the incentive for reducing capacity uncertainty. In this dual‐sourcing model, we show that the benefit of reducing capacity uncertainty depends on the cost heterogeneity between the suppliers. In addition, we show that a supplier does not necessarily benefit from capacity variability reduction. We contrast this incentive misalignment with findings from the single‐supplier case and a supplier‐duopoly case where both suppliers sell directly to market without the monopolistic retailer. In the latter single‐supplier and duopoly cases, we prove that the unreliable supplier always benefits from reducing capacity variability. These results highlight the role of the retailer's diversification strategy in distorting a supplier's incentive for reducing capacity uncertainty under supplier price competition.     

Cybernetic approach to investment decision making

This paper summarizes the results of our research into applications of cybernetic concepts and artificial intelligence techniques to investment analysis: it outlines the philosophy underlying the cybernetic approach to market forecasting and investment selection. This approach is computer oriented—it enables us to automate or program directly the complex judgmental aspects of investment decision making. The cybernetic approach alleviates some deficiencies of conventional statistical methods. Specifically, it (1) explicitly includes the time dimension into investment analysis, (2) is based on methods for decision making under uncertainty rather than risk, (3) yields computationally feasible methods for coping with the high complexity in investment analysis, and (4) yields decisions that are optimal rather than satisficing, i.e. performance of the Cybernetic Investment Decision System (CIDS) gradually improves during its operation through learning from past experience. A simplified CIDS has been implemented and tested in actual investment analysis. The experimental results of these tests indicate that through the cybernetic approach quality of investment decisions can be improved.     

Gender Data Gap and its impact on management science — Reflections from a European perspective

As data increasingly inform every aspect of our lives, gender discrimination in the collection and application of female-based data has also risen. Because data are primarily sourced from (white) men, the solutions we design to address global problems are also primarily based on men, i.e. male bodies, male preferences and prototypical male life choices. The Gender Data Gap – referring to the circumstance that most data on which organisational decisions are based appear to be biased in favour of (white) men – describes this very absence of information about aspects of women's lives. In this article, we not only demonstrate how the Gender Data Gap (negatively) impacts society and management science, but also highlight how the gap can be overcome in the long run. Further, we showcase several initiatives, particularly European ones, that suggest opportunities to gradually close the Gender Data Gap.     

Quantifying Flood Risks in the Netherlands

The Flood Risk in the Netherlands project (Dutch acronym: VNK2) is a large‐scale probabilistic risk assessment for all major levee systems in the Netherlands. This article provides an overview of the methods and techniques used in the VNK2 project. It also discusses two examples that illustrate the potential of quantitative flood risk assessments such as VNK2 to improve flood risk management processes: (i) informing political debates about the risks of flooding and the effectiveness of risk management actions, and (ii) (re)directing research efforts towards important sources of uncertainty.     

Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.     

新产品供应链协调

定价和促销是新产品推出阶段的两个重要决策。有些产品可能在价格还未确定之前就已经在市场上进行促销宣传,而有些产品在完全上市价格确定之后才进行宣传促销。本文考虑由一个生产商和一个销售商构成的供应链,产品的需求受到价格和促销努力的影响,生产商决定产品的价格,销售商进行促销。我们考虑下列三种决策顺序:先定价后促销,先促销后定价,同时定价和促销。我们证明,促销成本分摊和收益共享结合的契约在三种情形下都能协调该供应链。本文进一步还分析了三种决策顺序对生产商、销售商和供应链的影响。结果表明:同时定价和促销的情形对生产商、销售商以及供应链最不利;对于生产商和销售商来说,先决策时具有主动权,能获得更高的利润,但是当需求对价格比较敏感以及促销成本较高时,后决策反而能获得更多的利润。最后,通过数值实验研究了参数对最优决策和供应链利润的影响。     

Adoption of Individual Flood Damage Mitigation Measures in New York City: An Extension of Protection Motivation Theory

This study offers insights into factors of influence on the implementation of flood damage mitigation measures by more than 1,000 homeowners who live in flood‐prone areas in New York City. Our theoretical basis for explaining flood preparedness decisions is protection motivation theory, which we extend using a variety of other variables that can have an important influence on individual decision making under risk, such as risk attitudes, time preferences, social norms, trust, and local flood risk management policies. Our results in relation to our main hypothesis are as follows. Individuals who live in high flood risk zones take more flood‐proofing measures in their home than individuals in low‐risk zones, which suggests the former group has a high threat appraisal. With regard to coping appraisal variables, we find that a high response efficacy and a high self‐efficacy play an important role in taking flood damage mitigation measures, while perceived response cost does not. In addition, a variety of behavioral characteristics influence individual decisions to flood‐proof homes, such as risk attitudes, time preferences, and private values of being well prepared for flooding. Investments in elevating one's home are mainly influenced by building code regulations and are negatively related with expectations of receiving federal disaster relief. We discuss a variety of policy recommendations to improve individual flood preparedness decisions, including incentives for risk reduction through flood insurance, and communication campaigns focused on coping appraisals and informing people about flood risk they face over long time horizons.     

Capitalized investments with entry and exit options and paradoxical tax effects

Investment decisions are often characterized by uncertainty, irreversibility, and timing flexibility. We use a binomial model to investigate the interdependencies of effects from profit taxation and both an option to delay and an option to abandon on investment decisions. We show that increasing the tax rate can lead to paradoxical tax effects, i.e. it may foster an investor’s willingness to invest. By contrast, if we abstract from the abandonment option, such paradoxical effects cannot be identified. Hence, we show that paradoxical tax effects can be caused by an abandonment option. Our results are helpful for investors facing risky investment opportunities and for improving typical valuation approaches.     

Managing Technology Selection and Development Risk in Competitive Environments

Managing development decisions for new products based on dynamically evolving technologies is a complex task, especially in highly competitive industries. Product managers often have to choose between introducing an incrementally better, safe new product early and a superior, yet highly risky, product later. Recommendations for managing such performance vs. time‐to‐market trade‐offs often ignore competitive reactions to development decisions. In this paper, we study how a firm could incorporate the presence of a strategic competitor in making technology selection and investment decisions regarding new products. We consider a model in which an innovating firm and its rival can introduce a new product immediately or pursue a more advanced product for later launch. Further, the firm can reduce the uncertainty surrounding product development by dedicating more resources; the effectiveness of this investment depends on the firm's innovative capacity. Our model generates two sets of insights. First, in highly competitive industries, firms can adopt different technologies and effectively use introduction timing to mitigate the effects of price competition. More importantly, the firm could strategically invest in the advanced product to influence its rival's technology choice. We characterize equilibrium development and investment decisions of the firms, and derive innovative capacity hurdles that govern a firm's choice between the risky and safe alternatives. The effects of development flexibility—where firms might have the option to revert to the safe product if the advanced product fails—are also considered.     

Flash Flood Risks and Warning Decisions: A Mental Models Study of Forecasters,Public Officials,and Media Broadcasters in Boulder,Colorado

Timely warning communication and decision making are critical for reducing harm from flash flooding. To help understand and improve extreme weather risk communication and management, this study uses a mental models research approach to investigate the flash flood warning system and its risk decision context. Data were collected in the Boulder, Colorado area from mental models interviews with forecasters, public officials, and media broadcasters, who each make important interacting decisions in the warning system, and from a group modeling session with forecasters. Analysis of the data informed development of a decision‐focused model of the flash flood warning system that integrates the professionals’ perspectives. Comparative analysis of individual and group data with this model characterizes how these professionals conceptualize flash flood risks and associated uncertainty; create and disseminate flash flood warning information; and perceive how warning information is (and should be) used in their own and others’ decisions. The analysis indicates that warning system functioning would benefit from professionals developing a clearer, shared understanding of flash flood risks and the warning system, across their areas of expertise and job roles. Given the challenges in risk communication and decision making for complex, rapidly evolving hazards such as flash floods, another priority is development of improved warning content to help members of the public protect themselves when needed. Also important is professional communication with members of the public about allocation of responsibilities for managing flash flood risks, as well as improved system‐wide management of uncertainty in decisions.     

An agent-based model for evaluating reforms of the National Flood Insurance Program: A benchmarked model applied to Jamaica Bay,NYC

Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building-level adaptation and flood insurance, the agent-based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk-based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry-floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk-mitigation investments improves the uptake and affordability of dry-floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make.     

Risk evaluation of investment projects

A survey is given of techniques for evaluation of risk in individual capital investment projects. The paper identifies the four types of relationships affecting project uncertainty: (1) Accounting-type relationships defining cash flow; (2) Statistical relationships among variables in a given time period; (3) Autocorrelation relationships among cash flows over time; and (4) Uncertainty about project life. Two types of decisions also can affect project profitability and uncertainty: (1) Strategy decisions; and (2) Abandonment decisions. Four types of models for risk evaluation are identified: (1) Certainty model; (2) Hillier model; (3) Monte Carlo model; and (4) Decision Tree model. These four types of models are compared and evaluated in terms of how easily they can incorporate the relationships and decisions mentioned above. Computational issues are also discussed. Suggestions are made for further research.     

考虑不同回收质量等级的再制造系统回收生产决策

废旧产品的回收再制造过程往往在回收质量、再制造成本、再制造产出率、再制造产品需求等方面存在不确定性因素,极大地增加了再制造生产管理决策的复杂性。本文在一个回收再制造系统中研究了存在多种回收质量等级时的两阶段回收—再制造联合优化决策问题,并扩展到需求与价格相关和再制造产出率随机两种情形。在最大化再制造商期望利润的决策目标下,基于每种回收质量等级的单位回收和再制造成本构造出再制造系统的有效生产前沿面,给出了不同决策情形下再制造商的最优回收数量、销售定价的解析解,并且分析了一些主要的参数对再制造商最优决策的影响。本文的研究结果表明：（1）含有多种回收质量等级的再制造系统中存在一个下凸的有效生产前沿面,不在该前沿面上的任何质量等级的回收产品都将不会被用于再制造;（2）在同等的政府补贴额度下,回收补贴方式对再制造商决策的影响程度大于再制造补贴方式;（3）当再制造品的市场需求与价格相关时,最优销售价格至少大于第一种被使用的回收质量等级的边际回收和再制造成本;（4）任意两种回收质量等级之间存在着替代或互补效应,由其成本差异决定,并且这种效应随着需求不确定性的增大而增大;（5）再制造产出率的不确定性和再制造品需求的不确定性之间存在"对冲"效应,这种效应随着再制造产出率不确定性的降低而减弱。本文的研究可为不确定性环境下再制造企业的回收、生产管理决策提供有益的管理启示。     

Managing Logistics in Regional Banknote Supply Chain Under Security Concerns

We study the logistics problem faced by Regional Branches (RBs) of a central bank in managing the currency supply under security concerns. While making banknote supply decisions to Sub‐Branches (SBs), the management of RB must achieve two goals simultaneously: (i) guarantee that each SB has sufficient inventories of all denominations of banknotes to satisfy the demands from all commercial banks within its service area, and (ii) control the annual spending on this banknote supply operation. Due to security concerns, the following methods are implemented in the process of transporting banknotes: (i) the capacity of a cash truck is limited by the total face value (instead of the physical space) of banknotes, and (ii) empty decoy trucks are deployed along with the trucks filled with banknotes. After deriving a polynomial‐time strategy to guarantee an optimal solution for the special Bin‐Packing Problem faced in this study, we provide an exact formulation for the RB's supply planning problem. We also propose several polynomial‐time algorithms for deriving either optimal or near‐optimal solutions for the problem under different settings. Using the weekly demand data obtained from the central bank, we verify the performance of our algorithms, and analyze the impacts of changes in these features and in the fleet capacity on the total cost incurred by an RB under various scenarios.     

How to integrate strategic planning into your management process

The primary purpose of strategic planning is to enable management to make decisions today which will affect the firm over the long run where the long run is characterized by risk and uncertainty. If strategic planning is to be useful to management it must be an integral part of the decision making process and not merely an appendage to the management process. In this paper we shall define some of the problems involved in integrating strategic planning and strategic planning tools into the decision process. We shall also suggest some possible solutions to these problems.     

Operational Hedging and Diversification under Correlated Supply and Demand Uncertainty

When facing supply uncertainty caused by exogenous factors such as adverse weather conditions, firms diversify their supply sources following the wisdom of “not holding all eggs in one basket.” We study a firm that decides on investment and production levels of two unreliable but substitutable resources. Applying real options thinking, production decisions account for actual supply capabilities, whereas investment decisions are made in advance. To model triangular supply and demand correlations, we adapt the concepts of random capacity and stochastic proportional yield while using concordant ordered random variables. Optimal profit decreases monotonically in supply correlation and increases monotonically in supply–demand correlation. Optimal resource selection, however, depends on the trivariate interplay of supply and demand and responds non‐monotonically to changing correlations. Moreover, supply hedges (i.e., excess capacity at alternative sources) can be optimal even if supply resources are perfectly positively correlated. To accommodate changing degrees of correlation, the firm adjusts the lower margin capacities under random capacity; but under stochastic proportional production capability, it uses either low‐ or high‐margin capacities to create tailored “scale hedges” (i.e., excess capacity at one source which can partially substitute for diversification).     

序列投资下的石油勘探投资最优时机选择

综合考虑石油勘探投资的不可逆性、序列性和不确定性，结合市场需求和勘探储量的不确定性刻画勘探储量转让价格的随机动态变化，运用实物期权思想下的序列投资决策方法探究了石油勘探项目的最优投资时机选择问题，得出各阶段最优投资时机临界值的解析表达式，并与一次性完成投资的决策结果进行对比，进而剖析了不确定性参数对各阶段最优投资时机的影响。结果表明，序列投资决策模型能够弥补一次性投资决策模型容易错失投资机会的局限性；各阶段最优投资时机临界值同市场需求波动率、勘探主体价格控制能力呈同向变动，同市场需求漂移率呈反向变动；随勘探进程的不断深入，最优勘探投资时机临界值对以上参数的敏感性程度不断增强。     

Transfer Pricing and Sourcing Strategies for Multinational Firms

Taking advantage of low tax rates using transfer pricing and taking advantage of low production costs using offshoring are two strategies multinational firms (MNFs) use to increase profits. We identify an important trade‐off that MNFs face in setting their transfer prices: the conflict between (i) the incentive role and (ii) the tax role of the transfer price. For MNFs, we find the profit‐maximizing transfer‐pricing strategies that motivate divisional management to (i) make good sourcing decisions and (ii) take advantage of favorable tax rates. We quantify the absolute and relative maximum inefficiency in terms of the after‐tax MNF's profit change from using a single transfer‐pricing system as compared to the dual transfer‐pricing system. We show that the highest relative loss is attained when the average sourcing cost and the tax differential are high. We demonstrate that the highest absolute loss is attained when the average outsourcing cost is approximately equal to the offshoring cost. We extend our results to two practical variations in MNF structures: an MNF that faces operational constraints on its offshoring capacity and an MNF that uses compensation contracts linked to after‐tax firm‐wide profits. Our insights help MNFs' managers identify when to use single and dual transfer‐pricing systems.