0000000000033343

AUTHOR

Jella Pfeiffer

showing 15 related works from this author

Integrating Keyword Advertising and Dynamic Pricing for an Online Market Place

2014

Keyword Advertising is a main marketing instrument for e-commerce companies in order to generate traffic from search engines on their website. The costs for Keyword Advertising are determined in an auction that is conducted for every single search query, which is entered in by a user. In case of an online market place, each adlink provided by the search engine refers to an ordered list of products on the website of the online market place. Hereby, the price of the product is oftentimes one important criteria for the user when deciding for one or the other product from the list. However, existing models assume the price of products to be exogeneous. By taking into account the prices of linke…

Product (business)Web search queryOrder (exchange)business.industryKeyword advertisingDynamic pricingAdvertisingBiddingDecision problembusinessOnline advertising
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The Influence of Task and Context-Based Complexity on the Final Choice

2011

In this chapter, we present a new approach for the design of choice task experiments that analyze the final respondent’s choice but not the decision process.1 The approach creates choice tasks with a one-to-one correspondence between decision strategies and the observed choices. Thus, a decision strategy used is unambiguously deduced from an observed choice. Furthermore, the approach systematically manipulates the characteristics of choice tasks and takes into account measurement errors concerning the preferences of the decision makers. We use this approach to generate respondent-specific choice tasks with either low or high complexity and study their influence on the use of compensatory an…

Attractivenessbusiness.industryComputer scienceContrast (statistics)Context (language use)Machine learningcomputer.software_genreTask (project management)CorrelationRange (mathematics)Decision strategyRespondentArtificial intelligencebusinesscomputer
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Summary, Conclusions, and Future Work

2011

In the present work, we addressed two research questions: (1) How does the complexity of a choice task influence decision-making behavior? (2) How can we consider knowledge about decision-making behavior for the design of IIMT? By answering the first research question, we contributed to current theory on decision-making behavior, while the main contribution of addressing the second research question is the development of INTACMATO, an IIMT-prototype for supporting choice decisions.

Summary conclusionsWork (electrical)Decision strategyCurrent theoryResearch questionsPsychologyResearch questionTask (project management)Cognitive psychology
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Inferring Decision Strategies from Clickstreams in Decision Support Systems: A New Process-Tracing Approach using State Machines

2011

The importance of online shopping has grown remarkably over the last decade. In 2009, every West European spent on average € 483 online and this amount is expected to grow to € 601 in 2014. In Germany, the number of online shoppers has almost doubled since 2000: 44% of all adults regularly buy products onlinetoday. In Western Europe, online sales reached € 68 billion in 2009 and Forrester research forecasts it will reach € 114 billion by 2014 with an 11% compound annual growth rate.

Decision support systemFinite-state machineProcess tracingWestern europeBusinessCompound annual growth rateMarketingDecision makerAttribute level
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On the influence of context-based complexity on information search patterns: An individual perspective

2014

Although context-based complexity measured as the similarity and conflict across alternatives is dependent on individual preference structures, existing studies investigating the influence of context-based complexity on information search patterns have largely ignored that context-based complexity is user- and preference-dependent. Addressing this research gap, this article elicits the individual preferences of decision makers by using the pairwise-comparison-based preference measurement (PCPM) technique and records individuals' search patterns using eye tracking. Our results show that an increased context-based complexity leads to an increase in information acquisition and the use of a mor…

Process (engineering)Cognitive NeuroscienceEconomics Econometrics and Finance (miscellaneous)Experimental and Cognitive PsychologyContext (language use)Task (project management)Behavioral NeuroscienceConstant (computer programming)decision strategiesEyetrackingSimilarity (psychology)preference measurementdecision behaviorApplied PsychologyeyetrackingDecision strategiesPerspective (graphical)context-based complexityPreferenceNeuropsychology and Physiological PsychologyDecision behaviorBusiness Management and Accounting (miscellaneous)Eye trackingContext-based complexityPsychologySocial psychologyCognitive psychologyPreference measurement
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The Influence of Context-Based Complexity on Decision Processes

2011

In this chapter, we present an empirical study which investigates the influence of context-based complexity on decision processes.1 To determine context-based complexity accurately, we measure each subject’s preferences individually with two advanced techniques from marketing research: choice-based conjoint analysis (CBC, Haaijer and Wedel 2007) and pairwise-comparison-based preference measurement (PCPM, Scholz et al. 2010), rather than relying on less precise estimates of preferences. Furthermore, we use eye tracking to trace the process of information acquisition precisely. Our results show that low context-based complexity leads to less information acquisition and more alternative-wise s…

Process (engineering)business.industryComputer scienceContext (language use)Machine learningcomputer.software_genreConjoint analysisEmpirical researchBusiness decision mappingEye trackingArtificial intelligenceMarketing researchbusinesscomputerTRACE (psycholinguistics)
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Reference point based multi-objective evolutionary algorithms for group decisions

2008

While in the past decades research on multi-objective evolutionary algorithms (MOEA) has aimed at finding the whole set of Pareto optimal solutions, current approaches focus on only those parts of the Pareto front which satisfy the preferences of the decision maker (DM). Therefore, they integrate the DM early on in the optimization process instead of leaving him/her alone with the final choice of one solution among the whole Pareto optimal set. In this paper, we address an aspect which has been neglected so far in the research on integrating preferences: in most real-world problems, there is not only one DM, but a group of DMs trying to find one consensus decision all participants are wille…

Mathematical optimizationProcess (engineering)Evolutionary algorithmA priori and a posterioriBayesian efficiencyFlow shop schedulingFocus (optics)Set (psychology)Multi-objective optimizationMathematics
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An Effort-Accuracy Framework for IIMT

2011

In this chapter, we analyze to what extent INTACMATO meets the requirement of low effort. We take an existing effort-accuracy model, adapt and extend it to INTACMATO and show analytically the savings of effort achieved.

Operations researchComputer scienceDecision strategyDecision makerAttribute level
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Interactive Decision Aids

2011

Decision support systems assist people in making a decision or choosing a course of action in a nonroutine situation that requires judgment (Haubl and Trifts 2000; Kasper 1996). In online webstores, vendors can easily offer highly interactive types of decision support. These co-called interactive decision aids (IDA) “help consumers in making informed purchase decisions amidst the vast availability of online product offerings” (Wang and Benbasat 2009, p. 3). However, the application of IDA is not restricted to purchase decisions. They are general enough to be of use in any kind of choice task where alternatives are known.

Course of actionDecision support systemKnowledge managementComputer sciencebusiness.industryDecision aidsPreference elicitationProduct (category theory)Aspiration levelRecommender systembusinessTask (project management)
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INTACMATO: An IIMT-Prototype

2011

In the previous chapter, we pointed out that although users evaluate IIMT very positively, only a limited number of IIMT are offered. We assume that the main reason for this is that online sellers do not know which IIMT they should offer and what they should exactly look like. We address these two aspects in this chapter. Firstly, we review literature on IDA in the field of human interaction. We discuss several drawbacks of current approaches as well as the resulting requirements for the design of IIMT. Secondly, we break down observed decision-making behavior into typical steps decision makers apply in their decision processes. These steps indicate which IIMT would offer appropriate decisi…

Decision support systembusiness.industryHuman interactionComputer scienceCollaborative filteringUsabilityAspiration levelDecision processbusinessData scienceField (computer science)Attribute level
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A genetic algorithm for analyzing choice behavior with mixed decision strategies

2009

In the field of decision-making a fundamental problem is how to uncover people's choice behavior. While choices them- selves are often observable, our underlying decision strategies determining these choices are not entirely understood. Previous research defined a number of decision strategies and conjectured that people do not apply only one strategy but switch strategies during the decision process. To the best of our knowledge, empirical evidence for the latter conjecture is missing. This is why we monitored the purchase decisions 624 consumers shopping online. We study how many of the observed choices can be explained by the existing strategies in their pure form, how many decisions can…

Operations researchbusiness.industryManagement scienceComputer scienceBusiness decision mappingGenetic algorithmDecision field theoryE-commerceSpace (commercial competition)businessEmpirical evidenceSet (psychology)Consumer behaviourProceedings of the 11th Annual conference on Genetic and evolutionary computation
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An Optimized Design of Choice Experiments: A New Approach for Studying Decision Behavior in Choice Task Experiments

2014

In this paper, we present a new approach for the optimal experimental design problem of generating diagnostic choice tasks, where the respondent's decision strategy can be unambiguously deduced from the observed choice. In this new approach, we applied a genetic algorithm that creates a one-to-one correspondence between a set of predefined decision strategies and the alternatives of the choice task; it also manipulates the characteristics of the choice tasks. In addition, this new approach takes into account the measurement errors that can occur when the preferences of the decision makers are being measured. The proposed genetic algorithm is capable of generating diagnostic choice tasks eve…

Choice setOperationalizationSociology and Political Sciencebusiness.industryComputer scienceStrategy and ManagementGeneral Decision SciencesContrast (statistics)Space (commercial competition)Machine learningcomputer.software_genreTask (project management)Arts and Humanities (miscellaneous)Similarity (psychology)Genetic algorithmArtificial intelligenceSet (psychology)businesscomputerApplied PsychologyJournal of Behavioral Decision Making
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Fundamentals on Decision-Making Behavior

2011

This introductory chapter describes the fundamentals for later analysis, modeling and discussion of choice tasks and behavior. Figure 2.1 depicts the basic elements of the choice process which are relevant for the present work. On the left hand side, we see the general problem the decision makers are faced with: the choice task. Generally speaking, a choice task defines the problem of choosing the preferred out of a discrete and finite set of alternatives. The decision makers’ preferences determine what the preferred alternative is. Thus, in Sect. 2.1, we define both choice tasks and preferences.

Work (electrical)Operations researchComputer scienceProcess (engineering)General problemDecision makerFinite setTask (project management)Attribute level
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Using PageRank for non-personalized default rankings in dynamic markets

2017

Abstract Default ranking algorithms are used to generate non-personalized product rankings for standard consumers, for example, on landing pages of online stores. Default rankings are created without any information about the consumers’ preferences. This paper proposes using the product centrality ranking algorithm (PCRA), which solves some problems of existing default ranking algorithms: Existing approaches either have low accuracy, because they rely on only one product attribute, or they are unable to estimate ranks for new or updated products, because they use past consumer behavior, such as previous sales or ratings. The PCRA uses the PageRank centrality of products in a product dominat…

Information Systems and ManagementGeneral Computer ScienceComputer science02 engineering and technologyManagement Science and Operations Researchcomputer.software_genreIndustrial and Manufacturing Engineeringlaw.inventionPageRanklaw0502 economics and business0202 electrical engineering electronic engineering information engineeringEconometricsProduct (category theory)Consumer behaviour05 social sciencesGraphRankingModeling and SimulationGraph (abstract data type)050211 marketing020201 artificial intelligence & image processingLearning to rankData miningCentralitycomputerEuropean Journal of Operational Research
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Quantitative Evaluation of INTACMATO

2011

The main purpose of the empirical study which we present in this chapter is to evaluate the IIMT-prototype (INTACMATO). INTACMATO is evaluated across the criteria: perceived ease of use (effort), perceived usefulness, shopping enjoyment, confidence, and satisfaction. The results show that – compared to a control group of more than 30 students who just saw a product-comparison matrix without any IIMTs – the web store with INTACMATO was evaluated more positively across all five evaluation criteria.

Matrix (mathematics)Empirical researchbusiness.industryComputer scienceGroup (mathematics)StatisticsUsabilitybusinessAttribute level
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