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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.

The purpose of this study is to examine factors affecting the extent of consumers’ use of electronic word-of-mouth (eWOM), specifically online product reviews (OPRs), during their decision-making process. It also examines their motives for using OPRs.

The study uses an exploratory qualitative research methodology involving observation and free-flowing face-to-face interviews with consumers who have previously made a purchase online and who read OPRs during the decision-making process. An adaptation of the grounded theory method is used for collection, coding and data analysis.

Findings confirm previously uncovered motives for consumers’ use of OPRs. In addition, the findings suggest that two previously unidentified factors influence the extent of consumers’ use of OPRs: “decision-making drive” and “decision-making drag”. Decision-making drive is a mental momentum created when one or more factors that enhance decision-making readiness are present. This momentum tends to accelerate the decision-making process and shorten the information search process, leading to a reduction in the extent of OPR use. In contrast, decision-making drag is a mental resistance created when one or more factors that impede decision-making readiness are present. This resistance tends to decelerate the decision-making process and lengthen the information search process, leading to an increase in the extent of OPR use.

Focused on the pre-consumption phase of eWOM, between the stages of product need recognition and information search, this study is the first to identify decision-making drive and decision-making drag as additional psychological mechanisms affecting the extent of OPR use by consumers. For marketers, understanding these mechanisms has strategic marketing implications that can provide guidance to brands, websites and online review systems.

This paper seeks to develop a conceptual model that enables understanding of consumer purchase decisions in relation to the first customized products, including steps of the decision process, determinants, and consequences of each step.

The classic grounded theory approach was used.

The study found that the process consists of six steps called knowledge learning and preliminary information searching, problem recognition, budget setting, detailed information searching and solution creating, purchase involvement, and use and post‐purchase. The process is distinct from the process of traditional models of consumer decision mainly from three aspects: the process starting from “knowledge learning and information searching”, not from “problem recognition”, while “problem recognition” is the second step; information searched in the process mainly on components of products, with little on products; and the process includes a step “solution creating”, but without steps “alternative evaluation” and “choice”. The consequences of the first step consist of knowledge mastered, market information acquired, pre‐decisions, perceived value of customized PC, positive attitude towards customized PC, and self‐confidence, which are the main determinants of the following steps. Besides these determinants, others included are interest, curiosity, work with computers as tools, sources of knowledge and information on PC, and income.

The study provides a foundation for future quantitative research on determinants of consumers' purchasing the first customized products and provides insights into marketing: for example, target consumers of customized PC are characterized at least by having great self‐confidence in their capability to make an effective decision in purchasing customized PC, and having mastered enough PC knowledge.

Across a variety of domains, consumers are demanding increased customized products. While consumer decision making has become a prominent research topic in various fields of marketing and consumer science over the past decades, surprisingly little research has examined consumer purchase decisions in relation to the first customized personal computer (PC) and factors influencing such a process. The study may fill this gap.

Develops and tests a general model for understanding the influence of query‐based decision aids (QBDA) on consumer decision making in the electronic commerce environment. The results show that the use of well‐designed query‐based decision aids leads to increased satisfaction with the decision process and increased confidence in judgements. The number of stages of phased narrowing of the consideration set was higher in the case of subjects who had access to the query‐based decision aids. The mediating variables through which this influence occurs are size of the consideration set, similarity among the alternatives in the consideration set, cognitive decision effort, and perceived cost savings. The size of the consideration set and the similarity among the alternatives in the consideration set were higher in the case of subjects who had access to the query‐based decision aid. Subjects who had access to the query‐based decision aid perceived an increased cost savings and a lower cognitive decision effort associated with the purchase decision. This research is done in the context of consumers searching for information on the World Wide Web prior to the purchase of cars.

Both marketing executives and consumers engage in a combination of automatic and strategic (i.e. controlled) thinking and doing processes when they become aware of problems/opportunities. Similarities and departures in these processes among executives and consumers occur through all stages of their decisions. This article includes a paradigm describing similarities (S_i) and departures (D_i) in the stream of thinking and behaviors of executives and consumers. For example, both executives and consumers apply simplifying categorizing rules for defining decision contexts; for repetitive decision‐making contexts, categorization rules are more often formalized in writing by executives but not by consumers. The extant literature on the quality of decision processes offers several easy‐to‐apply, but often unknown rules helpful for both executives and consumers for improving the quality of their decisions; these rules are examined briefly within the framework of similarities and departures. Formal study by all marketers of such similarities and departures of consumer/business buying decisions may be helpful for recognizing nuances critical in selling‐buying processes for achieving desired outcomes – such as getting a sale or building a marketing relationship. The article describes “direct research” studies of decision processes implemented by executives and consumers; direct research studies hold particular promise for uncovering similarities and departures when comparing the two areas of study.

In an online shopping environment, individual reviews and aggregated ratings are important anchors for consumers’ purchasing decisions. However, few studies have considered the influence of aggregated ratings on consumer decision-making, especially at the neural level. This study aims to bridge this gap by investigating the consumer decision-making mechanism based on aggregated ratings to uncover the underlying neural basis and psychological processing.

An event-related potential experiment was designed to acquire consumers’ electrophysiological records and behavioral data during their decision-making processes based on aggregated ratings. The authors speculate that during this process, review valence categorization (RVC) processing occurs, which is indicated by late positive potential (LPP) components.

Results show that LPP components were elicited successfully, and perceptual review valence can modulate its amplitudes (one-star [negative] and five-star [positive] ratings evoke larger LPP amplitudes than three-star [neutral] ratings). The electroencephalogram data indicate that consumer decision-making processes based on aggregated ratings include an RVC process, and behavioral data show that easier review valence perception makes the purchase decision-making easier.

This study enriches the extant literature on the impact of aggregated ratings on consumer decision-making. It helps understand how aggregated ratings affect consumers’ online shopping decisions, having significant management implications. Moreover, it shows that LPP components can be potentially used by researchers and companies to evaluate and analyze consumer emotion and categorization processing, serving as an important objective physiological indicator of consumer behavior.

Decision aids (DAs) in online retail stores ease consumers' information processing. However, online consumers do not use all decision aids in purchase decision-making. While the literature has documented the effects of individual decision aids or two decision aids at a time, no study has compared the efficacy of multiple decision aids simultaneously. Also, very few studies have looked at the use of decision aids for consumers with maximizing and satisficing tendencies. Hence, this study aims to understand the preferences of maximizers and satisficers towards online decision aids during the choice-making process.

This is an observational study with 60 individuals who were asked to purchase either a search-based or an experience-based product online. Participants' browsing actions and verbalizations during online shopping, were recorded and analysed using NVivo, and later the use of decision aids was mapped along their choice process.

Consumer's preference of decision aids varies across the two stages of the choice process (that is, consideration set formation and evaluation & choice). In their choice formation, maximizers use different decision aids in both stages, that is, filter tool and in-website search tool for search products, and collaborative filtering-based recommender systems and eWOM for experience products. Satisficers used more decision aids as compared to maximizers across the two stages for both product types.

This study is an exploratory attempt to understand how consumers use multiple decision aids present on e-commerce websites.

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.