Abraham Seidmann; Yabing Jiang; Jie Zhang

Bilge Atasoy; Refik Güllü; Tarkan Tan

Abstract We consider the production/inventory problem of a manufacturer (or a retailer) under non-stationary and stochastic supply availability. Although supply availability is uncertain, the supplier would be able to predict her near future shortages – and hence supply disruption to (some of) her customers –... [view more]

Abstract

We consider the production/inventory problem of a manufacturer (or a retailer) under non-stationary and stochastic supply availability. Although supply availability is uncertain, the supplier would be able to predict her near future shortages – and hence supply disruption to (some of) her customers – based on factors such as her pipeline stock information, production schedule, seasonality, contractual obligations, and non-contractual preferences regarding other manufacturers. We consider the case where the information on the availability of supply for the near future, which we refer to as advance supply information (ASI), is provided by the supplier. The customer demand is deterministic but non-stationary over time, and the system costs consist of fixed ordering, holding and backorder costs. We consider an all-or-nothing type of supply availability structure and we show the optimality of a state-dependent (s,S) policy. For the case with no fixed ordering cost we prove various properties of the optimal order-up-to levels and provide a simple characterization of optimal order-up-to levels. For the model with fixed ordering cost, we propose a heuristic algorithm for finding a good ordering strategy. Finally, we numerically elaborate on the value of ASI and provide managerial insights.

Ioannis Petrakis; Christian Hass; Martin Bichler

Abstract Mobile phone operators need to plan and schedule field force personnel for maintenance and repair tasks on mobile phone base stations across the country on a daily basis. In this paper, we will introduce the field force scheduling problem with priorities. Motivated by the rising popularity of ... [view more]

Abstract

Mobile phone operators need to plan and schedule field force personnel for maintenance and repair tasks on mobile phone base stations across the country on a daily basis. In this paper, we will introduce the field force scheduling problem with priorities. Motivated by the rising popularity of mobile field force management solutions, we compare online and offline heuristics as well as hybrids to solve the problem. The results help understand the benefits of dynamic scheduling based on real-time position information as compared to traditional daily offline planning.

Stefan Guericke; Achim Koberstein; Frank Schwartz; Stefan Voß

Abstract When designing global production and distribution systems an important aspect becoming more and more relevant is the question of how to deal with demand uncertainties. Due to the proliferation of product variants that have to be handled in production and distribution, long lead times due to overseas transportation... [view more]

Abstract

When designing global production and distribution systems an important aspect becoming more and more relevant is the question of how to deal with demand uncertainties. Due to the proliferation of product variants that have to be handled in production and distribution, long lead times due to overseas transportation and increasingly volatile, uncertain and market specific demands, an appropriate concept to deal with these problems has to be established. One concept that has been proposed but not yet been fully explored in this context is postponement. In this concept the customization and finalization of a product is procrastinated, i.e., the final products are not completed in factories but in facilities of a distribution network that are located on the network from factories to customers. This may also entail a resequencing of manufacturing steps.

Until now, research has mainly focused on general statements regarding advantages and disadvantages of postponement strategies. In contrast, quantitative models that allow for decision making for specific postponement implementations are rare, particularly models that explicitly take into account stochastic demands and long lead times. In order to allow for decision making for specific postponement implementations in uncertain environments, we present a two-stage stochastic mixed integer linear programming model in this paper. We design a case study inspired by decision support issues in the apparel industry. By means of this case study we show that the presented model formulation can support managers to determine an appropriate production and distribution network in uncertain environments. Benefits from the concept of postponement are exemplified using (commercially) available mathematical programming software.

Ting Li; Robert J. Kauffman

Abstract We propose a decision analytics approach that leverages adaptive learning in the refinement of service operations. We aim to integrate service design and service pricing with downstream operational decision-making related to service provision. This approach involves: collecting consumer data and establishing consumer behavior models; integrating consumer... [view more]

Abstract

We propose a decision analytics approach that leverages adaptive learning in the refinement of service operations. We aim to integrate service design and service pricing with downstream operational decision-making related to service provision. This approach involves: collecting consumer data and establishing consumer behavior models; integrating consumer behavior models with models for service operation decision-making; and iteratively evaluating service designs based on service delivery performance that evolves over time due to learning. We discuss how this approach enables service providers to set time-differentiated prices and evaluate the impact on transportation network performance. We use agent-based simulation to illustrate the application of our approach to the operations of a public rail transportation firm in a European urban setting. Our findings suggest that knowing the impacts of consumer responses in service operations is essential for devising cost-effective and value-bearing service designs. Our approach can support service providers who wish to adjust their pricing, consumer demand and capacity management models, and to develop more effective market forecasts of performance through adaptive learning, in the presence of “big data” from consumers and operations.

Esra Çınar; Refik Güllü

Abstract In this paper we study the inventory/production problem of a firm that uses operational level outsourcing to hedge against uncertainty. We consider an environment in which the maximum amount that can be produced in a period, the regular capacity of the system, is uncertain, but information... [view more]

Abstract

In this paper we study the inventory/production problem of a firm that uses operational level outsourcing to hedge against uncertainty. We consider an environment in which the maximum amount that can be produced in a period, the regular capacity of the system, is uncertain, but information on its realization (which we call the “advance capacity information” (ACI)) is available. We model the uncertainty in regular capacity, and present an ACI process that tracks and updates the information on the availability of the regular capacity. For this system we propose an ACI-dependent order-up-to level policy. We characterize the optimal solution under the order-up-to level policy, and through a numerical study we derive managerial insights with respect to the benefits of using outsourcing option and ACI.

Ravi Mantena; Vera Tilson; Xiaobo Zheng

Abstract Durable goods account for a significant portion of the economy and have been of considerable interest to academic researchers, especially economists, over the last four decades. Given the importance of strategic issues concerning durable goods markets to IS and OM researchers, our objective is to present a... [view more]

Abstract

Durable goods account for a significant portion of the economy and have been of considerable interest to academic researchers, especially economists, over the last four decades. Given the importance of strategic issues concerning durable goods markets to IS and OM researchers, our objective is to present a broad perspective of the research in this field that can serve as a starting point for their modeling efforts when analyzing these markets. Due to the complexity of these markets and the strategic interlinkage of decisions over time, a careful examination of the models is essential for the proper understanding and interpretation of the results from the literature. This paper provides a macro perspective of the research problems, a simple integrative framework for modeling durable goods, an introduction to the models and solution concepts commonly used in the literature, and a discussion of the primary results in the context of their modeling choices. Potentially interesting directions for future IS and OM research in this area are also identified.

Hemant K. Bhargava; Rachel R. Chen

Abstract Buyers are often uncertain about product valuations before they commit to purchase. In such situations, firms have an opportunity to influence the accuracy with which buyers can estimate their valuations. When buyers are uncertain about the product's fit with their personal preferences, firms can help resolve... [view more]

Abstract

Buyers are often uncertain about product valuations before they commit to purchase. In such situations, firms have an opportunity to influence the accuracy with which buyers can estimate their valuations. When buyers are uncertain about the product's fit with their personal preferences, firms can help resolve this uncertainty by offering product previews, sampling, trials or return guarantees. When a buyer's valuation uncertainty is caused by unpredictability in their consumption state, firms can choose advance selling – which makes buyers decide while they are unsure about their valuations – or enable buyers to make an informed decision by offering spot sales. This paper examines firms' incentive to adopt mechanisms that endow buyers with private information – hence increase information asymmetry against the firm – and are mean preserving in the aggregate across the market. Prior studies suggest that in this setting, selling to uninformed buyers is advantageous because it presents the firm with a narrower dispersion in valuations, making it easier to extract consumer surplus. Countering this intuition, we show that when the market consists of distinct heterogeneous consumer segments ex ante, selling to privately informed buyers can improve the firm's profit. This is because under certain conditions, the demand curve can become flatter in a relatively high price range as buyers become informed, enabling the firm to extract higher surplus. Our work suggests that firms may want to employ product preview mechanisms even when they increase dispersion in valuations while only maintaining (rather than increasing) the mean. Our study highlights the interplay between buyer valuation uncertainty and consumer heterogeneity in determining a firm's selling strategy.

Atanu Lahiri

Abstract Motivated by the recent strategy switch of a large software producer, this paper revisits the trade-offs associated with tolerating illegal distribution of software products. Conventional wisdom is that a higher level of positive network effects justifies a tolerant approach on the part of software producers—because illegal... [view more]

Abstract

Motivated by the recent strategy switch of a large software producer, this paper revisits the trade-offs associated with tolerating illegal distribution of software products. Conventional wisdom is that a higher level of positive network effects justifies a tolerant approach on the part of software producers—because illegal distribution leads to more users, amplifies positive network effects, and creates a greater demand for the legal version. I show that this wisdom does not hold in the context of supporting illegal versions with patches. Patches are used for plugging security vulnerabilities as well as for distributing functionality changes. Software producers have the option of supporting illegal versions with either or both kinds of patches. I find that, even in the presence of strong positive network effects, the least tolerant approach of denying illegal versions both kinds of patches can be optimal.

Yuliang Yao; Jie Zhang

Abstract We develop an analytical model and conduct subsequent empirical analyses using data collected from the online retailers of digital cameras and video games. We find that (1) Internet retailers' base prices are positively associated with on-time delivery probability but shipping charges are negatively associated with on... [view more]

Abstract

We develop an analytical model and conduct subsequent empirical analyses using data collected from the online retailers of digital cameras and video games. We find that (1) Internet retailers' base prices are positively associated with on-time delivery probability but shipping charges are negatively associated with on-time delivery probability; (2) Internet retailers will increase base prices when they offer free shipping; and (3) Internet retailers' shipping price difference between the standard and expedited shipping modes increases with the shipping time of standard shipping, but decreases with the shipping time of expedited shipping and also the Internet retailer's on-time probability. Our findings suggest that Internet retailers, to maximize profits, can strategically determine base price and shipping prices, and they can also strategically pace menu pricing for different shipping options.

Nelson Granados; Robert J. Kauffman; Hsiangchu Lai; Huang-chi Lin

Abstract Global distribution systems (GDSs) and online travel agencies (OTAs) have been providing critical intermediation services for the air travel services industry. Their systems services have eroded the airlines' revenue by encouraging consumers to do price comparison-based purchases though, which has caused the commoditization of ... [view more]

Abstract

Global distribution systems (GDSs) and online travel agencies (OTAs) have been providing critical intermediation services for the air travel services industry. Their systems services have eroded the airlines' revenue by encouraging consumers to do price comparison-based purchases though, which has caused the commoditization of air travel services. The airlines have begun to adopt à la carte pricing mechanisms in their direct distribution channel, especially through their Web sites. This way, they can provide travelers with an array of information for different airline product bundles and the flexibility to customize different bundles. This mechanism design may allow airlines to decommoditize their services in the minds of consumers. We analyze two years of data from a large international airline that sold airline tickets via several different direct and indirect distribution channels. Our results suggest that demand in the à la carte channel as a whole is less price-elastic. The results for price elasticity for different market segments and bundle types across channels were not altogether consistent with our predictions though. We find that, for some branded bundles of services, price elasticity is lower in the à la carte channel, and for others it is higher. We discuss the implications for managers and the design of à la carte selling mechanisms.