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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.

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.

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.

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.

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

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.

Appropriate logistic planning for the pharmaceutical supply chain can significantly improve many financial and performance aspects. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of pharmaceuticals, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified requests.

The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized requests for pharmaceuticals in the network. Besides, the total transportation activities of different types of vehicles and related costs are considered as other objectives. 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 the second objective function while maintaining the optimality of the first objective function. The third objective function is optimized based on the optimality of other objective functions, as well. A non-dominated sorting genetic algorithm II-multi-objective particle swarm optimization heuristic method is designed for this aim.

The performances of the proposed model were analyzed in different cases and its results for different problems were 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.

The proposed methodology can be applied to find the best logistic plan in real situations.

In this paper, the authors have tried to use a multi-objective optimization model to guide and correct the pharmaceutical supply chain to deal with the related requests. This is important because it can help managers to improve their plans.

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.

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

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.

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.

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

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

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.

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.

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.

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.

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.

Using robust optimization approaches to balance mixed model assembly line.

This research project suggests that the decision‐making process in organizational buying may not be as much of a group process as is presently suggested by the literature. The job of organizational buyers is profiled and the decisions that are important to a seller — the buyer's choice of vendors to request bids from and the subsequent purchase choice of the buyer — is investigated. This research suggests that the decision rules used to select buyers for consideration are independent of the decision rules used to make the final purchase choice.

The analysis of consumer behaviour requires the consideration of various processes internal and external to the individual. To understand behaviour, it is necessary to examine the complex interaction of many influencing elements. This study deals with determinants of behaviour, culture and reference group influences, the relationships between individuals and their environments, perceived risks, and family decision processes. It concludes with an illustration of tourist behaviour modelling.

Organizational equilibrium theory is a theory of an inducements‐contributions balance within organizations; i.e. it ultimately aims to find conditions for organizational survival. Based on the Simon‐Smithburg‐Thompson postulates for the organizational equilibrium theory, an organizational equilibrium model under uncertainty is constructed. Using a multiple objective satisficing problem formulation, the survival conditions (i.e. existence conditions of viable solutions) are studied. The existence of uniformly better solutions than a given viable solution is also shown. Then, a unique solution (i.e. viable Pareto solution) is defined, and a problem whose solutions are viable Pareto solutions is specified. Finally, several organizational factors involved with the organizational equilibrium concept are discussed.

Recognizing the fundamental role of quality as a means to differentiate service organizations, the purpose of this paper is to propose a strategic decision making framework for service organizations, which prioritizes performance improvement strategies that are rooted to customer requirements, organizational goals and constrained by organizational resources.

The proposed framework is realized through the implementation of two stages and four distinct phases mirroring the combination of enhanced quality function deployment (first stage), and zero-one goal programming (second stage). It proposes the utilization of a mix of qualitative and quantitative methods, and the collection of data from multiple sources including customers, middle, and top management.

The application and validation of the proposed framework utilizes information from both customers and employees in the bank services sector. Overall, results from the specific study revealed that a combination of “reengineering” and “expansion” strategies was more appropriate corresponding to customer priorities, organizational goals and effective utilization of available resources.

The paper presents a novel two stage strategic framework for service organizations. It utilizes a balanced mixture of qualitative and quantitative methods in an effort to capture and delineate elusive customer requirements and design characteristics of services, allowing the assessment of different combinations of quality improvement strategies in response to management objectives.