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Book part
Publication date: 31 January 2015

Soora Rasouli and Harry Timmermans

This chapter reviews models of decision-making and choice under conditions of certainty. It allows readers to position the contribution of the other chapters in this book…

Abstract

Purpose

This chapter reviews models of decision-making and choice under conditions of certainty. It allows readers to position the contribution of the other chapters in this book in the historical development of the topic area.

Theory

Bounded rationality is defined in terms of a strategy to simplify the decision-making process. Based on this definition, different models are reviewed. These models have assumed that individuals simplify the decision-making process by considering a subset of attributes, and/or a subset of choice alternatives and/or by disregarding small differences between attribute differences.

Findings

A body of empirical evidence has accumulated showing that under some circumstances the principle of bounded rationality better explains observed choices than the principle of utility maximization. Differences in predictive performance with utility-maximizing models are however small.

Originality and value

The chapter provides a detailed account of the different models, based on the principle of bounded rationality, that have been suggested over the years in travel behaviour analysis. The potential relevance of these models is articulated, model specifications are discussed and a selection of empirical evidence is presented. Aspects of an agenda of future research are identified.

Details

Bounded Rational Choice Behaviour: Applications in Transport
Type: Book
ISBN: 978-1-78441-071-1

Keywords

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Book part
Publication date: 13 October 2009

Bartosz Sawik

This chapter presents the portfolio optimization problem formulated as a multi-criteria mixed integer program. Weighting and lexicographic approach are proposed. The…

Abstract

This chapter presents the portfolio optimization problem formulated as a multi-criteria mixed integer program. Weighting and lexicographic approach are proposed. The portfolio selection problem considered is based on a single-period model of investment. An extension of the Markowitz portfolio optimization model is considered, in which the variance has been replaced with the Value-at-Risk (VaR). The VaR is a quantile of the return distribution function. In the classical Markowitz approach, future returns are random variables controlled by such parameters as the portfolio efficiency, which is measured by the expectation, whereas risk is calculated by the standard deviation. As a result, the classical problem is formulated as a quadratic program with continuous variables and some side constraints. The objective of the problem considered in this chapter is to allocate wealth on different securities to maximize the weighted difference of the portfolio expected return and the threshold of the probability that the return is less than a required level. The auxiliary objectives are minimization of risk probability of portfolio loss and minimization of the number of security types in portfolio. The four types of decision variables are introduced in the model: a continuous wealth allocation variable that represents the percentage of wealth allocated to each asset, a continuous variable that prevents the probability that return of investment is not less than required level, a binary selection variable that prevents the choice of portfolios whose VaR is below the minimized threshold, and a binary selection variable that represents choice of stocks in which capital should be invested. The results of some computational experiments with the mixed integer programming approach modeled on a real data from the Warsaw Stock Exchange are reported.

Details

Financial Modeling Applications and Data Envelopment Applications
Type: Book
ISBN: 978-1-84855-878-6

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Article
Publication date: 1 April 1977

R. Angelmar and B. Pras

Demonstrates that the objective here is to discuss some recent findings in consumer behaviour thereby showing implications for the types of appeal strategies. Describes…

Abstract

Demonstrates that the objective here is to discuss some recent findings in consumer behaviour thereby showing implications for the types of appeal strategies. Describes the three main types of consumer evaluation process models, going on to research findings concerning the conditions under which consumers follow each type. Points out the implications for advertising appeal strategy. Highlights the three main types of consumer evaluation process models as: compensatory models; satisfying models; and lexographic models. Concludes that multiple appeal strategies are most appropriate for new product introductions and brand repositioning.

Details

European Journal of Marketing, vol. 11 no. 4
Type: Research Article
ISSN: 0309-0566

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Book part
Publication date: 1 November 2008

Bruno Busacca, Michele Costabile and Fabio Ancarani

This paper focuses on customer value analysis and measurement, framing customer value management as one of the main antecedents of the company value-creation process. The…

Abstract

This paper focuses on customer value analysis and measurement, framing customer value management as one of the main antecedents of the company value-creation process. The paper builds on three main pillars. First, the paper highlights the critical role of customer value in business-to-business markets, focusing on the links between the company's ability to manage customer value-creation processes and the positive financial and economic outcomes generated by loyalty effects. Secondly, the paper develops key analytical stages for an understanding of customer value. The focus is on the customer value-chain concept, including consideration of the customer information and acquisition process and its decision rules. Third, the paper illustrates the measurement process, offering an organizational framework for selecting the most suitable method for measuring perceived customer value. The methodological alternatives range from desk measures (e.g., technical computation of the total cost of ownership (TCO)) to field analysis, like those considered under both compositional and the decomposition approaches (e.g., conjoint analysis). The paper concludes with remarks on the managerial implications of these measures, as well as offering suggestions for further research on value for the customer.

Details

Creating and managing superior customer value
Type: Book
ISBN: 978-1-84855-173-2

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Book part
Publication date: 3 February 2015

Bartosz Sawik

This chapter presents two optimization multicriteria models (bi and triple objective) using a lexicographic approach. Solved models are formulated as assignment of workers…

Abstract

This chapter presents two optimization multicriteria models (bi and triple objective) using a lexicographic approach. Solved models are formulated as assignment of workers to different jobs or services of a real hospital, taking into account the available budget and requirements of each job. Presented problems have been solved using AMPL programming language with solver CPLEX v9.1, with the use of branch and bound method for mixed integer mathematical programming.

Details

Applications of Management Science
Type: Book
ISBN: 978-1-78441-211-1

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Article
Publication date: 3 June 2021

Mohammad Mahdi Ershadi and Hossein Shams Shemirani

Proper planning for the response phase of humanitarian relief can significantly prevent many financial and human losses. To this aim, a multi-objective optimization model

Abstract

Purpose

Proper planning for the response phase of humanitarian relief can significantly prevent many financial and human losses. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of injured people, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified injured people.

Design/methodology/approach

The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized injured people in the network. Besides, the total transportation activities of different types of vehicles are considered as another objective function. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize transportation activities as the second objective function while maintaining the optimality of the first objective function.

Findings

The performances of the proposed model were analyzed in different cases and its robust approach for different problems was shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.

Practical implications

The proposed methodology can be applied to find the best response plan for all crises.

Originality/value

In this paper, we have tried to use a multi-objective optimization model to guide and correct response programs to deal with the occurred crisis. This is important because it can help emergency managers to improve their plans.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2042-6747

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Article
Publication date: 1 June 2003

Michel Laroche, Chankon Kim and Takayoshi Matsui

This study empirically investigates consumers’ use of five heuristics (conjunctive, disjunctive, lexicographic, linear additive, and geometric compensatory) in the…

Abstract

This study empirically investigates consumers’ use of five heuristics (conjunctive, disjunctive, lexicographic, linear additive, and geometric compensatory) in the consideration set formation, a critical first phase before actual choice behavior. Data were collected on the selection of beer brands and fast food outlets by real consumers. Using a decomposition approach in determining the consumers’ choice heuristics, it was found that the conjunctive heuristic is the most often used decision model in the consideration set formation for the two product classes. Implications for brand managers and future research directions are developed.

Details

Journal of Consumer Marketing, vol. 20 no. 3
Type: Research Article
ISSN: 0736-3761

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Article
Publication date: 1 October 2006

Manoj Kumar, Prem Vrat and Ravi Shankar

The primary objective of this paper is to show how mathematical modeling can be used for solving a third party logistics (3PL) allocation problem.

Abstract

Purpose

The primary objective of this paper is to show how mathematical modeling can be used for solving a third party logistics (3PL) allocation problem.

Design/methodology/approach

The solution approach consists of finding a compromise solution for the six different strategies, defined in the paper by using lexicographic goal programming involving three objectives under some realistic constraints related to capacities of the markets.

Findings

This study investigates the usefulness and efficacy of the proposed method for a 3PL allocation problem for a case example of a typical fish supply network. The decision‐makers can evaluate the alternative solutions with respect to a set of decision criteria. The result indicates substantial improvement by reducing the number of 3PL service providers and reallocating them to the case fish markets.

Practical implications

The work provides a useful decision model for practicing managers, policy makers and researchers of this area.

Originality/value

This model would help a decision maker to resolve the issues related to selection of 3PL under a set of conflicting multi‐objective criteria.

Details

International Journal of Physical Distribution & Logistics Management, vol. 36 no. 9
Type: Research Article
ISSN: 0960-0035

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Book part
Publication date: 15 February 2011

Tim Schwanen and Karen Lucas

Abstract

Details

Auto Motives
Type: Book
ISBN: 978-0-85-724234-1

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Article
Publication date: 13 November 2009

Weida Xu and Tianyuan Xiao

The purpose of this paper is to introduce robust optimization approaches to balance mixed model assembly lines with uncertain task times and daily model mix changes.

Abstract

Purpose

The purpose of this paper is to introduce robust optimization approaches to balance mixed model assembly lines with uncertain task times and daily model mix changes.

Design/methodology/approach

Scenario planning approach is used to represent the input data uncertainty in the decision model. Two kinds of robust criteria are provided: one is min‐max related; and the other is α‐worst scenario based. Corresponding optimization models are formulated, respectively. A genetic algorithm‐based robust optimization framework is designed. Comprehensive computational experiments are done to study the effect of these robust approaches.

Findings

With min‐max related robust criteria, the solutions can provide an optimal worst‐case hedge against uncertainties without a significant sacrifice in the long‐run performance; α‐worst scenario‐based criteria can generate flexible robust solutions: through rationally tuning the value of α, the decision maker can obtain a balance between robustness and conservatism of an assembly line task elements assignment.

Research limitations/implications

This paper is an attempt to robust mixed model assembly line balancing. Some more efficient and effective robust approaches – including robust criteria and optimization algorithms – may be designed in the future.

Practical implications

In an assembly line with significant uncertainty, the robust approaches proposed in this paper can hedge against the risk of poor system performance in bad scenarios.

Originality/value

Using robust optimization approaches to balance mixed model assembly line.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 28 no. 6
Type: Research Article
ISSN: 0332-1649

Keywords

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