Multi-Platform Access to Digital Content
“Multi-Platform Access to Digital Content,” Inaugural Platform Strategy Research Symposium, Boston, MA 2013
Sellers of digital content such as media, entertainment, software, and other information goods, are grappling with new selling strategies because consumers today want the same content multiple times on multiple devices. Content providers have responded with different strategies, ranging from independent pricing on each platform to a single price for access to all platforms.
Salesforce Compensation with Network Effects
“Salesforce Compensation under Network Effects”, Workshop on Information Systems Economics (WISE), Dallas, TX, 2015
This paper examines the management problem of “selling” platforms, i.e., designing appropriate salesforce management and incentives schemes to obtain participation by paying customers. The paper shows that network effects increase not only the mean, but also the variance of the performance metrics used to compensate sales agents.
Versioning and Launch Timing for Platform Technologies
“Platform technologies and network goods: insights on product launch and management”, Information Technology and Management 15.3 (2014), pp. 199–209, ISSN: 1385-951X
The article examines the tension between growth and profitability for network goods (such as Skype, Dropbox, Facebook, smart phone platforms, etc.). It discusses various levers of control available to the firm including managing product design and the intensity of network effects, managing the timing of product announcement vs. actual product release, selecting the target market for initial product launch, and whether to sell a single version or an expanded product line.
Research Expertise: Operations and supply chain management, service operations and dynamic pricing
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The Benefit of Information Asymmetry: When to Sell to Informed Customers?
Decision Support Systems, 2012
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.
Although stochastic programming is a powerful tool for modeling decision-making under uncertainty, various impediments have historically prevented its wide-spread use. One key factor involves the ability of non-specialists to easily express stochastic programming problems as extensions of deterministic models, which are often formulated first. A second key factor relates to the difficulty of solving stochastic programming models, particularly the general mixed-integer, multi-stage case.
This book by Professor David Woodruff and co-authors William Hart and Jean-Paul Watson from Sandia National Laboratories and Carl Laird from Texas A&M provides a complete and comprehensive guide to Pyomo—Python Optimization Modeling Objects—for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners.
Introduction to Computational Optimization Models for Production Planning in a Supply Chain, 2nd Edition
The book by Professor David Woorduff and co-author Stefan Voß from the University of Hamburg begins with an easy-to-read introduction to the concepts associated with the creation of optimization models for production planning. These concepts are then applied to well-known planning models, namely mrp and MRP II. From this foundation, the book develops fairly sophisticated models for supply chain management.
Optimal Multiple-breakpoint Quantity Discount Schedules for Customers with Heterogeneous Demands: All-unit or Incremental?
IIE Transactions, 2012
The supplier’s problem of designing a quantity discount schedule is much more complicated when she faces customers who vary in size. This article by Associate Professor Rachel Chen and co-author Lawrence W. Robinson from Cornell University considers both all-unit and incremental discount schedules with multiple breakpoints that maximize the supplier’s net savings.
Implementing Management Innovations: Lessons Learned from Activity Based Costing in the U.S. Automobile Industry
Implementing Management Innovations: Lessons Learned from Activity Based Costing in the U.S. Automobile Industry is the result of a long-term study of the implementation of activity-based costing (ABC) inside two of America’s largest automobile companies.
The research advances our theoretical and practical understanding of the implementation of management innovations by tracing the evolution of ABC from the corporate level down to its eventual rollout at the plants. Another distinguishing feature of the study is the blend of field research methods and hypothesis testing to determine the factors that led to implementation success for managers and ABC development teams. Many of the findings of the study have implications for the implementation of other types of management innovations.
This paper provides field evidence on management control practices used to mitigate risk and to enhance cooperation in strategic alliances. The data are extensive field interviews with 38 managers in three large U.S. companies that have significant alliance risk exposure.
Instead of holding customers captive in an idled plane on a tarmac during unforeseen delays, airlines should give passengers the choice to leave or stay—and compensate them either way.
Modeling and Solving a Large-scale Generation Expansion Planning Problem under Uncertainty
Energy Systems, 2011
In this paper, Professor David Woodruff and co-authors Shan Jin and Sarah Ryan from Iowa State University, and Jean-Paul Watson from Sandia National Laboratories formulate a generation expansion planning problem to determine the type and quantity of power plants to be constructed over each year of an extended planning horizon, considering uncertainty regarding future demand and fuel prices.
Pyomo: Modeling and Solving Mathematical Programs in Python
Mathematical Programming Computation, 2011
In this study, Professor David Woodruff and co-authors William E. Hart and Jean-Paul Watson from Sandia National Laboratories describe Pyomo, an open source software package for modeling and solving mathematical programs in Python. Pyomo can be used to define abstract and concrete problems, create problem instances, and solve these instances with standard open-source and commercial solvers.
Research Note: the Point of Diminishing Returns in Heuristic Search
International Journal of Metaheuristics, 2011
In this paper, Professor David Woodruff and co-authors Ulrike Ritzinger from Vienna University of Technology and Johan Oppen from Molde University College provide a computable definition for the intuitive concept of the point of diminishing returns in a heuristic search. The authors also demonstrate that with proper scaling, the time point for a small instance can provide some guidance concerning the time point on larger instances. This paper presents computational results for a range of problems and search methods.
Progressive Hedging Innovations for a Class of Stochastic Mixed-integer Resource Allocation Problems
Computational Management Science, 2011
Numerous planning problems can be formulated as multi-stage stochastic programs and many possess key discrete (integer) decision variables in one or more of the stages. Progressive hedging (PH) is a scenario-based decomposition technique that can be leveraged to solve such problems.
Estimating the Implied Value of the Customer’s Waiting Time
Manufacturing & Service Operations Management, 2011
Almost all research in appointment scheduling has focused on the trade-off between customer waiting times and server idle times. In this paper, Associate Professor Rachel Chen and co-author Lawrence W. Robinson of Cornell University present an observation-based method for estimating the relative cost of the customer waiting time, which is a critical parameter for finding the optimal appointment schedule.
To group, or not to group: That’s the question for retailers considering the strategy of cooperative buying. Despite lower wholesale prices, retailers may not always benefit from pooling their purchasing power, especially when they are competing with each other, according to Assistant Professor Rachel Chen.
An Empirical Examination of Goals and Performance-to-Goal Following the Introduction of an Incentive Bonus Plan with Participative Goal Setting
Management Science, 2010
Prior research documents performance improvements following the implementation of pay-for-performance (PFP) bonus plans. However, bonus plans typically pay for performance relative to a goal, and the manager whose performance is to be evaluated often participates in setting the goal.
Strategic Cost Management in Supply Chains, Part 2: Executional Cost Management
Accounting Horizons, 2009
In the first paper in this two-part series, Professor Shannon Anderson and co-author Henri C. Dekker from the University Amsterdam reviewed structural cost management in supply chains. In this second paper of the series they consider executional cost management in supply chains, which employs measurement and analysis tools (e.g., cost driver analysis, supplier scorecards) to evaluate supply chain performance and sustainability.
Strategic Cost Management in Supply Chains, Part 1: Structural Cost Management
Accounting Horizons, 2009
Strategic cost management is the deliberate alignment of a firm’s resources and associated cost structure with long-term strategy and short-term tactics. Although managers continue to pursue efficiency and effectiveness within the firm, increasingly, improvements are obtained across the value chain: through reconfiguring firm boundaries, relocating resources, reengineering processes, and re-evaluating product and service offerings in relation to customer requirements.
High demand for a service means more revenue and more profits for the service provider. However, when peak demand is unpredictable and it occurs in a confined space (e.g., restaurants, resorts, trains, and airplanes), the service quality tends to decline. Customers are likely to have a bad experience because of longer wait times, overcrowded spaces and inattentive employees. That result: lost revenue because of customer dissatisfaction and defection. Whether the customer chooses to stick it out or walk out, future profits are in jeopardy.
Management Control for Market Transactions: The Relation Between Transaction Characteristics, Incomplete Contract Design, and Subsequent Performance
Management Science, 2005
Using an unusually comprehensive database on 858 transactions for information technology products and accompanying services, Professor Shannon Anderson and co-author Henri Dekker from the University of Amsterdam study how close partners exposed to opportunistic hazards structure and control a significant transaction.
Using Electronic Data Interchange (EDI) to Improve the Efficiency of Accounting Transactions
The Accounting Review, 2002
Electronic data interchange (EDI) is an information technology that standardizes the exchange of information between transacting parties. Using data from a major U.S. office furniture manufacturer who adopted EDI primarily to improve the efficiency of accounting transactions, Professor Shannon W. Anderson and co-author William N. Lanen from the University of Michigan evaluate whether EDI reduces order processing time (the time from sales order receipt to sales order scheduling) and whether this improvement is greater for more complex orders.