The Design and Introduction of Product Lines When Consumer Valuations are Uncertain

This article presents a model of the design and introduction of a product line when the firm is uncertain about consumer valuations for the products. We find that product line introduction strategy depends on this uncertainty. Specifically, under low levels of uncertainty the firm introduces both models during the first period; under higher levels of uncertainty, the firm prefers sequential introduction and delays design of the second product until the second period. Under intermediate levels of uncertainty the firm's first product should be of lower quality than one produced by a myopic firm that does not take product line effects into consideration. We find that when the firm introduces a product sequentially, the strategy might depend on realized demand. For example, if realized demand is high, the firm's second product should be a higher‐end model; if demand turns out to be low, the firm's second product should be a lower‐end model or replace the first product with a lower‐end model.     

Optimal Inventory Control with Retail Pre‐Packs

A pre‐pack is a collection of items used in retail distribution. By grouping multiple units of one or more stock keeping units (SKU), distribution and handling costs can be reduced; however, ordering flexibility at the retail outlet is limited. This paper studies an inventory system at a retail level where both pre‐packs and individual items (at additional handling cost) can be ordered. For a single‐SKU, single‐period problem, we show that the optimal policy is to order into a “band” with as few individual units as possible. For the multi‐period problem with modular demand, the band policy is still optimal, and the steady‐state distribution of the target inventory position possesses a semi‐uniform structure, which greatly facilitates the computation of optimal policies and approximations under general demand. For the multi‐SKU case, the optimal policy has a generalized band structure. Our numerical results show that pre‐pack use is beneficial when facing stable and complementary demands, and substantial handling savings at the distribution center. The cost premium of using simple policies, such as strict base‐stock and batch‐ordering (pre‐packs only), can be substantial for medium parameter ranges.     

Managing Demand Risk in Tactical Supply Chain Planning for a Global Consumer Electronics Company

We consider the problem of managing demand risk in tactical supply chain planning for a particular global consumer electronics company. The company follows a deterministic replenishment‐and‐planning process despite considerable demand uncertainty. As a possible way to formally address uncertainty, we provide two risk measures, “demand‐at‐risk” (DaR) and “inventory‐at‐risk” (IaR) and two linear programming models to help manage demand uncertainty. The first model is deterministic and can be used to allocate the replenishment schedule from the plants among the customers as per the existing process. The other model is stochastic and can be used to determine the “ideal” replenishment request from the plants under demand uncertainty. The gap between the output of the two models as regards requested replenishment and the values of the risk measures can be used by the company to reallocate capacity among different products and to thus manage demand/inventory risk.     

Demand and Production Management with Uniform Guaranteed Lead Time

Recently, innovation‐oriented firms have been competing along dimensions other than price, lead time being one such dimension. Increasingly, customers are favoring lead time guarantees as a means to hedge supply chain risks. For a make‐to‐order environment, we explicitly model the impact of a lead time guarantee on customer demands and production planning. We study how a firm can integrate demand and production decisions to optimize expected profits by quoting a uniform guaranteed maximum lead time to all customers. Our analysis highlights the increasing importance of lead time for customers, as well as the tradeoffs in achieving a proper balance between revenue and cost drivers associated with lead‐time guarantees. We show that the optimal lead time has a closed‐form solution with a newsvendor‐like structure. We prove comparative statics results for the change in optimal lead time with changes in capacity and cost parameters and illustrate the insights using numerical experimentation.     

The Role of Behavioral Responses in the Total Economic Consequences of Terrorist Attacks on U.S. Air Travel Targets

U.S. airports and airliners are prime terrorist targets. Not only do the facilities and equipment represent high‐value assets, but the fear and dread that is spread by such attacks can have tremendous effects on the U.S. economy. This article presents the methodology, data, and estimates of the macroeconomic impacts stemming from behavioral responses to a simulated terrorist attack on a U.S. airport and on a domestic airliner. The analysis is based on risk‐perception surveys of these two scenarios. The responses relate to reduced demand for airline travel, shifts to other modes, spending on nontravel items, and savings of potential travel expenditures by U.S. resident passengers considering flying domestic routes. We translate these responses to individual spending categories and feed these direct impact results into a computable general equilibrium (CGE) model of the U.S. economy to ascertain the indirect and total impacts on both the airline industry and the economy as a whole. Overall, the estimated impacts on GDP of both types of attacks exceed $10B. We find that the behavioral economic impacts are almost an order of magnitude higher than the ordinary business interruption impacts for the airliner attack and nearly two orders of magnitude higher for the airport attack. The results are robust to sensitivity tests on the travel behavior of U.S. residents in response to terrorism.     

A shelf-space optimization model when demand is stochastic and space-elastic

The more customer demand is impulse-driven, the more it is space-dependent and the more it is subject to variation. We investigate the corresponding problem of retail shelf-space planning when demand is stochastic and sensitive to the number and position of facings. We develop a model to maximize a retailer׳s profit by selecting the number of facings and their shelf position under the assumption of limited space. The model is particularly applicable to promotional or temporary products.We develop the first optimization model and solution approach that takes stochastic demand into account, since the current literature applies deterministic models for shelf-space planning. By the means of an innovative modeling approach for the case with space- and positioning effects and the conversion of our problem into a mixed-integer problem, we obtain optimal results within very short run times for large-scale instances relevant in practice. Furthermore, we develop a solution approach to account for cross-space elasticity, and solve it using an own heuristic, which efficiently yields near-optimal results. We demonstrate that correctly considering space elasticity and demand variation is essential. The corresponding impacts on profits and solution structures become even more significant when space elasticity and stochastic demand interact, resulting in up to 5% higher profits and up to 80% differences in solution structures, if both effects are correctly accounted for. We develop an efficient modeling approach, compare the model results with approaches applied in practice and derive rules-of-thumb for planners.     

Reciprocal relationships between psychosocial work characteristics and sleep problems: A two-wave study

Sleep problems are common and impair the health and productivity of employees. Work characteristics constitute one possible cause of sleep problems, and sleeping poorly might influence wellbeing and performance at work. This study examines the reciprocal associations between sleep problems and psychosocial work characteristics. The participants were 1744 full-time employed individuals (56% women; mean age 38 years in 2007) from the Young Finns study who responded to questionnaires on work characteristics (conceptualised by the demand–control model and effort–reward imbalance model) and sleep problems (Jenkins Sleep Scale) in 2007 and 2012. Cross-lagged structural equation models are used to examine the associations. The results show that low control and low rewards at baseline predicted sleep problems. Baseline sleep problems predicted higher effort, higher effort–reward imbalance, and lower reward. Sleep problems also predicted lower odds for belonging to the low (rather than high) job strain group and active jobs group. The association between work characteristics and sleep problems appears to be reciprocal, with a stressful work environment increasing sleep problems, and sleep problems influencing future work characteristics. The results emphasise the importance of interventions aimed at both enhancing sleep quality and reducing psychosocial risks at work.     

冲击型负荷下的生产存储模型研究

建立了考虑冲击需求、变化生产率的最优生产存储库存策略. 其特点是:把一个生产周 期分为多个生产阶段,各个生产阶段时间可以不同;在每个生产阶段中,允许生产率小于需求 率,允许提前生产;而且,最大生产率要小于最大需求率. 研究发现,为满足冲击需求,提前存储 较多而启动机器数量较少,或提前存储较少而启动机器数量较多,不一定能够取得最佳效益, 要根据存储费用和启动费用共同确定. 在有限生产率的条件下,得出一种寻求最优生产- 库存 策略,为此类库存系统的管理决策提供了理论依据.     

流动性约束与消费行为关系的实证研究

流动性约束是指资本市场的资金流动具有单向性,流动性约束的存在可以提高储蓄水 平,降低当期累积消费. 通过三阶段生命期界的最优消费模型,证明了流动性约束的定量存在, 并通过实证检验发现,我国消费总量中受流动性约束影响的比例达到83. 46 %. 因此,增强信 贷市场的流动性,对于扩张有效需求将起重要作用.