New product launch decisions with robust optimization

We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal...

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Vydané v:Computational management science Ročník 13; číslo 2; s. 263 - 292
Hlavní autori: Cetinkaya, Elcin, Thiele, Aurélie
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2016
Springer Nature B.V
Predmet:
Budgeting
Business and Management
Collaboration
Communication channels
Customer services
Decision making
Decisions
Durable goods
Growth models
Innovations
Launches
Linear programming
Markets
Mathematical models
Operations Research/Decision Theory
Optimization
Optimization techniques
Original Paper
Pharmaceutical industry
Product development
Product introduction
Studies
Technology adoption
Uncertainty
United States > US
Bass models
New product introduction
Robust optimization
ISSN:1619-697X, 1619-6988
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Abstract We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal launch sequence. We present a robust optimization approach that incorporates such uncertainty on the Bass diffusion model for new products as well as on the price response function of partners that collaborate with the company in order to bring its products to market. The decision-maker optimizes his worst-case profit over an uncertainty set where nature chooses the time periods in which (integer) units of the budgets of uncertainty are used for worst impact. This leads to uncertainty sets with binary variables. We show that a conservative approximation of the robust problem can nonetheless be reformulated as a mixed integer linear programming problem, is therefore of the same structure as the deterministic problem and can be solved in a tractable manner. Finally, we illustrate our approach on numerical experiments. Our model also incorporates contracts with potential commercialization partners. The key output of our work is a sequence of product launch times that protects the decision-maker against parameter uncertainty for the adoption rates of the new products and the response of potential partners to partnership offers.
AbstractList We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal launch sequence. We present a robust optimization approach that incorporates such uncertainty on the Bass diffusion model for new products as well as on the price response function of partners that collaborate with the company in order to bring its products to market. The decision-maker optimizes his worst-case profit over an uncertainty set where nature chooses the time periods in which (integer) units of the budgets of uncertainty are used for worst impact. This leads to uncertainty sets with binary variables. We show that a conservative approximation of the robust problem can nonetheless be reformulated as a mixed integer linear programming problem, is therefore of the same structure as the deterministic problem and can be solved in a tractable manner. Finally, we illustrate our approach on numerical experiments. Our model also incorporates contracts with potential commercialization partners. The key output of our work is a sequence of product launch times that protects the decision-maker against parameter uncertainty for the adoption rates of the new products and the response of potential partners to partnership offers.
Issue Title: Robust Optimization and Applications We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal launch sequence. We present a robust optimization approach that incorporates such uncertainty on the Bass diffusion model for new products as well as on the price response function of partners that collaborate with the company in order to bring its products to market. The decision-maker optimizes his worst-case profit over an uncertainty set where nature chooses the time periods in which (integer) units of the budgets of uncertainty are used for worst impact. This leads to uncertainty sets with binary variables. We show that a conservative approximation of the robust problem can nonetheless be reformulated as a mixed integer linear programming problem, is therefore of the same structure as the deterministic problem and can be solved in a tractable manner. Finally, we illustrate our approach on numerical experiments. Our model also incorporates contracts with potential commercialization partners. The key output of our work is a sequence of product launch times that protects the decision-maker against parameter uncertainty for the adoption rates of the new products and the response of potential partners to partnership offers.
Author Thiele, Aurélie
Cetinkaya, Elcin
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Cites_doi 10.1287/mksc.5.2.169
10.1016/j.ejor.2003.10.046
10.1016/0148-2963(88)90079-3
10.1287/mnsc.15.5.215
10.1287/mksc.13.3.203
10.1016/j.disopt.2006.12.002
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10.1287/mksc.1.1.57
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Robust optimization
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Snippet We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the...
Issue Title: Robust Optimization and Applications We consider a problem where a company must decide the order in which to launch new products within a given...
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StartPage 263
SubjectTerms Budgeting
Business and Management
Collaboration
Communication channels
Customer services
Decision making
Decisions
Durable goods
Growth models
Innovations
Launches
Linear programming
Markets
Mathematical models
Operations Research/Decision Theory
Optimization
Optimization techniques
Original Paper
Pharmaceutical industry
Product development
Product introduction
Studies
Technology adoption
Uncertainty
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