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It has long been recognised that humans draw from a large pool of processing aids to help manage the everyday challenges of life. It is not uncommon to observe individuals adopting simplifying strategies when faced with ever increasing amounts of information to process, and especially for decisions where the chosen outcome will have a very marginal impact on their well-being. The transactions costs associated with processing all new information often exceed the benefits from such a comprehensive review. The accumulating life experiences of individuals are also often brought to bear as reference points to assist in selectively evaluating information placed in front of them. These features of human processing and cognition are not new to the broad literature on judgment and decision-making, where heuristics are offered up as deliberative analytic procedures intentionally designed to simplify choice. What is surprising is the limited recognition of heuristics that individuals use to process the attributes in stated choice experiments. In this paper we present a case for a utility-based framework within which some appealing processing strategies are embedded (without the aid of supplementary self-stated intentions), as well as models conditioned on self-stated intentions represented as single items of process advice, and illustrate the implications on willingness to pay for travel time savings of embedding each heuristic in the choice process. Given the controversy surrounding the reliability of self-stated intentions, we introduce a framework in which mixtures of process advice embedded within a belief function might be used in future empirical studies to condition choice, as a way of increasingly judging the strength of the evidence.

Increasing evidence suggests that choice behaviour in real world may be guided by principles of bounded rationality as opposed to typically assumed fully rational behaviour, based on the principle of utility-maximization. Under such circumstances, conventional rational choice models cannot capture the decision processes. The purpose of the chapter is to propose a modeling framework that can capture both decision outcome and decision process.

The modeling framework incorporates a discrete cognitive representation structure and implies several decision heuristics, such as conjunctive, disjunctive and lexicographic rules. This allows modeling unobserved decision heterogeneity involved in a single decision, for example, in the form of a latent-class specification, taking into account mental effort, risk perception and expected outcome as explanatory factors.

Two models based on this framework are applied to decision problems underlying pedestrian shopping behaviour and compared with conventional multinomial logit models. The results show that the proposed models may not be superior to logit models in terms of model selection criteria due to the extra complexity in selecting heuristics, but suggest more interesting insights to the underlying decision mechanisms.

Understanding decision processes additional to outcomes is a promising research direction. A more developed model should take into account more contextual and socio-demographic factors in the heuristic selection part. The assumptions of information processing must be subject to empirical tests to validate the model.

The proposed modeling framework bridges the long-existing contradicting approaches in the field of decision modeling, namely the rational approach and the bounded rational approach, by proving that non-compensatory decision heuristics can be inferred from compensatory model formulations with discretized information representations and decision criteria assumed. It also incorporates a heuristic choice part into the decision processes in the form of latent-class specifications and shows the viability of the new modeling framework.

In the study of choice processes the classical model is Utility Theory — its characteristics and limitations are discussed. Several taxonomies of choice heuristics from the literature are compared and information processing models are then analysed. The article concludes with suggestions for future research.

The purpose of this paper is to elaborate the picture of strategies and tactics for information seeking and searching by focusing on the heuristic elements of such strategies and tactics.

A conceptual analysis of a sample of 31 pertinent investigations was conducted to find out how researchers have approached heuristics in the above context since the 1970s. To achieve this, the study draws on the ideas produced within the research programmes on Heuristics and Biases, and Fast and Frugal Heuristics.

Researchers have approached the heuristic elements in three major ways. First, these elements are defined as general level constituents of browsing strategies in particular. Second, heuristics are approached as search tips. Third, there are examples of conceptualizations of individual heuristics. Familiarity heuristic suggests that people tend to prefer sources that have worked well in similar situations in the past. Recognition heuristic draws on an all-or-none distinction of the information objects, based on cues such as information scent. Finally, representativeness heuristic is based on recalling similar instances of events or objects and judging their typicality in terms of genres, for example.

As the study focuses on three heuristics only, the findings cannot be generalized to describe the use of all heuristic elements of strategies and tactics for information seeking and searching.

The study pioneers by providing an in-depth analysis of the ways in which the heuristic elements are conceptualized in the context of information seeking and searching. The findings contribute to the elaboration of the conceptual issues of information behavior research.

Independent travelers are those vacationers who have booked only a minimum of their transportation and accommodation arrangements prior to departure on the vacation. Independent travel is an important and growing sector of worldwide tourism. Choice of vacation itinerary for the independent vacation represents a complex series of decisions regarding purchase of multiple leisure and tourism services. This chapter builds and tests a model of independent traveler decision-making for choice of vacation itinerary. The research undertaken employs a two-phase, inductive–deductive case study design. In the deductive phase, the researcher interviewed 20 travel parties vacationing in New Zealand for the first time. The researcher interviewed respondents at both the beginning and the end of their New Zealand vacations. The study compares pre-vacation research and plans, and actual vacation behaviors, on a case-by-case basis. The study examines case study narratives and quantitative measures of crucial variables. The study tests two competing models of independent traveler decision-making, using a pattern-matching procedure. This embedded research design results in high multi-source, multi-method validity for the supported model. The model of the Independent Vacation as Evolving Itinerary suggests that much of the vacation itinerary experienced in independent travel is indeed unplanned, and that a desire to experience the unplanned is a key hedonic motive for independent travel. Rather than following a fixed itinerary, the itinerary of an independent vacation evolves as the vacation proceeds. The independent traveler takes advantage of serendipitous opportunities to experience a number of locations, attractions and activities that they had neither actively researched nor planned.

Using both qualitative and quantitative approaches, how consumers choose a financial institution for their checking accounts is investigated in this study. It was found that, although most consumers value convenience as one of the most important decision‐making criteria, their definitions of convenience vary across consumers. How different consumers use different decision‐making criteria and heuristics is reported, and the implications for financial service marketers are drawn from the findings.

This study aims to use product attributes and retail display information to develop cross‐national segments.

The study uses consumers' choice in wine stores to develop segments of consumers, based on the relative importance of 13 factors consumers use for the retail purchase of wine. Data are collected from 11 countries, using seven languages on five continents. Best worst scaling (BWS) and latent class analysis were used to develop the clusters.

A three‐cluster structure provides a straightforward and robust segmentation across the 11 countries. This model fits better than one based on 11 single country segments. The three segments reveal different ways in which consumers choose wines: cognitive‐based, assurance‐based, and in‐store promotion‐based.

The samples are convenience‐based and do not represent the population of wine drinkers in each country. Choice criteria, including retail communications, can be used to develop useful and robust segments cross‐nationally.

The three segments found in this study provide clear guidelines for wine marketers depending on whether they work for small or large wine companies. The use of choice attributes and BWS show the utility of this method in cross‐national research.

This research demonstrates that product attributes and retail communication devices like labels and displays can be used for cross‐national segmentation. Applying BWS and Latent Class Clustering to choice criteria leads to clear, usable, and robust segmentation across a wide range of cultures and product use histories.

Most of the research on collaborative consumption platforms (CCPs) has focused on motivational drives, and little research has been conducted on the problem of unbalanced information sharing, also known as the “lemons problem,” and signals. The paper aims to discuss these issues.

This study conducted a netnography and an experiment.

The netnographic study showed that participants tend to use low ratings and negative reviews as cues implying more searches, use ratings as an anchor to adjust other information, and employ differing cognitive information-processing styles. The experimental results show that, in a normal environment (when ratings are high), visualizers (verbalizers) have more of an intention to use CCPs when they are exposed to abundant pictures (textual cues); however, when the cues lead to a further information search (when the ratings are low), this search behavior pattern is reversed: visualizers (verbalizers) have more of an intention to use CCPs when they are exposed to abundant textual cues (pictures).

This study extends previous research by showing that people frequently use differing heuristics depending on the context; that ratings have an anchoring effect and guide people in selecting a signal to use and condition how they use it; and that visualizers prefer text cues to pictorial cues when trying to make informed decisions under a condition that points to a further information search. These results are opposite of previous assertion.

Marketers are advised to provide a mechanism by which users can extract the cues they need and reduce the less urgent ones; devise a mechanism that screens participants and divides them into two categories: those who post honest evaluations and those who do not; and reduce the opportunistic behaviors of partners on both sides.

The current study addresses consumers’ use of information posted by other consumers on CCPs and demonstrates that participants use low ratings and negative reviews as cues implying more searches, use ratings as an anchor to adjust other information, and employ differing cognitive information-processing styles. Previous research rarely addressed these information search behaviors of consumers on CCPs.

When consumers fulfill consumption goals they make decisions on first, from which product category to buy, and second, which brand to purchase within the product category. In this article, the relative effects of product‐level typicality and brand‐level typicality on goal‐driven consumer choice are examined. Which level of typicality is more diagnostic of choice? Empirical results show that consumers are, in goal‐derived usage contexts, more likely to choose a less typical and less favored brand from a typical product category than a typical and more favored brand from a less typical product category. Consequently, brands that consumers perceive as inferior may be chosen over superior brands because of the link between product categories and usage contexts. Our results indicate that it may be fruitful for marketers to associate brands and product categories with usage contexts, and that they need to consider brand competitors from other product categories.