scholarly journals Pick Your Poison: The Attribution Paradox in Cyberwar

2020 ◽  
Author(s):  
Eric Jardine ◽  
Nathaniel Porter
Keyword(s):  
Experimental Design ◽  
Discrete Choice ◽  
Conflict Escalation ◽  
Attribution Problem

Certainty matters in cyberspace. The so-called attribution problem can impede deterrence, making cyberattacks more likely. But attribution problems can also limit conflict escalation, keeping nations safer. Using a discrete choice experimental design, this article quantifies the scope of the attribution problem for both deterrence and escalation. The results suggest that the attribution problem is really only a problem for deterrence and actually helps limit conflict escalation by reducing support for more severe retaliatory options.

Efficient Experimental Design with Marketing Research Applications

1994 ◽  
Vol 31 (4) ◽  
pp. 545-557 ◽  
Author(s):  
Warren F. Kuhfeld ◽  
Randall D. Tobias ◽  
Mark Garratt
Keyword(s):  
Experimental Design ◽  
Discrete Choice ◽  
Relative Efficiency ◽  
Marketing Research ◽  
Orthogonal Arrays ◽  
Experimental Designs ◽  
Design Algorithms ◽  
Nonorthogonal Designs

The authors suggest the use of D-efficient experimental designs for conjoint and discrete-choice studies, discussing orthogonal arrays, nonorthogonal designs, relative efficiency, and nonorthogonal design algorithms. They construct designs for a choice study with asymmetry and interactions and for a conjoint study with blocks and aggregate interactions.

scholarly journals The status quo’s role in improving the estimation of willingness to pay in choice experiments

2019 ◽  
Vol 8 (5) ◽  
pp. 422
Author(s):  
Alexandru MAXIM ◽  
Teodora ROMAN
Keyword(s):  
Renewable Energy ◽  
Experimental Design ◽  
Willingness To Pay ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Clean Energy ◽  
Status Quo ◽  
Dual Model ◽  
The Status

European household consumers have seen a gradual increase in the cost of their electricity bill, partly due to ambitious support policies for the development of renewable energy. Some consumers may have a higher willingness to pay (WTP) for clean energy, which could constitute a competitive advantage for electricity suppliers branding themselves as “sustainable”.A discrete choice experiment has been used in order to estimate the WTP of households for renewable energy. For the last decade, researchers have debated whether to add a “status quo” / “not willing to pay for changes” option in the experimental design, as this may generate complications and not add sufficient benefits.In this paper we use an original approach based on two parallel model estimations applied to the same sample of respondents in order to demonstrate the effect of adding a “status quo” option. Our results show that not including it would have led to an overestimation of about one third of the respondents‟ WTP.While more research on the topic is needed, we demonstrate the risk of simplifying the experimental design and propose a facile method of enhancing the experiment with a dual model design.Keywords: discrete choice experiment, status quo, renewable energy, household consumers, willingness to pay

scholarly journals Experimental Design

2020 ◽  
pp. 37-49
Author(s):  
Petr Mariel ◽  
David Hoyos ◽  
Jürgen Meyerhoff ◽  
Mikolaj Czajkowski ◽  
Thijs Dekker ◽  
...  
Keyword(s):  
Experimental Design ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Statistical Technique ◽  
Statistical Techniques ◽  
The Core ◽  
Pros And Cons ◽  
Attribute Levels ◽  
Choice Tasks

AbstractThis chapter covers various issues related to the experimental design, a statistical technique at the core of a discrete choice experiment. Specifically, it focuses on the dimensionality of a choice experiment and the statistical techniques used to allocate attribute levels to choice tasks. Among others, the pros and cons of orthogonal designs, optimal orthogonal in the differences designs as well as efficient designs are addressed. The last section shows how a simulation exercise can help to test the appropriateness of the experimental design.

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