Situation-Based Shifts in Consumer Web Site Benefit Salience: The Joint Role of Affect and Cognition

This study addresses the process by which differences in web site benefit salience arise in consumers’ minds for different anticipated usage situations. We investigate two routes by which situation may determine consumer benefit salience and find support for both route structures. The results indicate that individuals’ relative benefit importance ratings shift between different anticipated usage situations, both directly, and indirectly, through consumers’ anticipated affective states. Furthermore, the number of benefits that is rated as important by consumers is found to also differ depending on their anticipated affective states, providing further insight into why consumer benefit salience may vary across situations.affective route;cognitive route;situatieafhankelijkheid;usage situation;web site benefit salience;HD9696.82

How Tolerable is Delay? Consumers' Evaluations of Internet Web Sites After Waiting

How consumers’ waiting times affect their retrospective evaluations of Internet Web Sites is investigated in four computer-based experiments. Results show that waiting can but does not always negatively affect evaluations of Web Sites. Results also show that the potential negative effects of waiting can be neutralized by managing waiting experiences effectively. A conceptual framework and formal random utility model is introduced.Marketing;consumer preference models;waiting experiences;Internet marketing

Shopping Context and Consumers' Mental Representation of Complex Shopping Trip Decision Problems

Depending on the shopping context, consumers may develop different mental representations of complex shopping trip decision problems to help them interpret the decision situation that they face and evaluate alternative courses of action. To investigate these mental representations and how they vary across contexts, the authors propose a causal network structure that allows for a formal representation of how context-specific benefits requirements affect consumers’ evaluation of decision alternative attributes. They empirically test hypotheses derived from the framework, using data on consumers’ mental representations of a complex shopping trip decision problem across four shopping contexts that differ in terms of opening hour restrictions and shopping purpose, and find support for the proposed structure and hypotheses.retailing;consumer decision-making;context effects;mental representations;shopping trip decisions

Optimal Effort in Consumer Choice: Theory and Experimental Evidence for Binary Choice

This paper develops a theoretical model of optimal effort in consumer choice.The model extends previous consumer choice models in that the consumer not only chooses a product, but also decides how much effort to apply to a given choice problem.The model yields a unique optimal level of effort, which depends on the consumer's cost of effort, the expected utility gain of a correct choice, and the complexity of the choice set.We show that the relationship between effort and cost of effort is negative, whereas the relationships between effort and product utility difference and choice task complexity are undetermined.To resolve this theoretical ambiguity and to explore our model empirically, we investigate the relationships between effort and cost of effort, product utility difference and choice task complexity using data from a conjoint choice study of two-alternative consumer restaurant choices.Response time is used as a proxy for effort and consumer involvement measures capture individual differences in (relative) cost of effort and perceived complexity.Effort is explained using the (estimated) utility difference between alternatives, the number of elementary information processes (EIP's) required to solve the choice problem optimally and respondent specific cost of effort and complexity perceptions.The predictions of the theoretical model are supported by our empirical findings.Response time increases with lower cost of effort and greater perceived complexity (i.e. higher involvement).We find that across the range of choice tasks in our survey, effort increases linearly with smaller product utility differences and greater choice task complexity.consumer choice;bounded rationality

Combining and Comparing Consumers' Stated Preference Ratings and Choice Responses

In this study we develop and test an econometric model for combining choice and preference ratings data collected from the same set of individuals.Choice data are modeled using a multinomial logit framework, while preference data are modeled using an ordered response equation.Individual heterogeneity is allowed for via random coefficients providing a link between the choice and ratings data.Parameters are estimated by Simulated Maximum Likelihood.An application of the model to consumer yoghurt choice in The Netherlands found that ratings based preference estimates differ significantly from choice based estimates, but the correlation between random coefficients driving the two is very strong.econometric models;preferences;consumer choice;maximum likelihood;JEL classifications;C35;M31

How tolerable is delay? : Consumers' evaluations of internet web sites after waiting

How consumer's waiting times affect their retrospective evaluations of Internet Web Sites is investigated in four computer-based experiments. Results show that waiting can but does not always negatively affect evaluations of Web Sites. Results also show that the potential negative effects of waiting can be neutralized by managing waiting experiences effectively. A conceptual framework and formal random utility model is introduced

Consumer Preferences for Mass Customization

Increasingly, firms adopt mass customization, which allows consumers to customize products by self-selecting their most preferred composition of the product for a predefined set of modules. For example, PC vendors such as Dell allow customers to customize their PC by choosing the type of processor, memory size, monitor, etc. However, how such firms configure the mass customization process determines the utility a consumer may obtain or the complexity a consumer may face in the mass customization task. Mass customization configurations may differ in four important ways – we take the example of the personal computer industry. First, a firm may offer few or many product modules that can be mass customized (e.g., only allow consumers to customize memory and processor of a PC or allow consumers to customize any module of the PC) and few or many levels among which to choose per mass customizable module (e.g., for mass customization of the processor, only two or many more processing speeds are available). Second, a firm may offer the consumer a choice only between very similar module levels (e.g., a 17” or 18” screen) or between very different module levels (e.g., a 15” or 21” screen). Third, a firm may individually price the modules within a mass customization configuration (e.g., showing the price of the different processors the consumer may choose from) along with pricing the total product, or the firm may show only the total product price (e.g., the price of the different processors is not shown, but only the computer’s total price is shown). Fourth, the firm may show a default version (e.g., for the processor, the configuration contains a pre-selected processing speed, which may be a high-end or low-end processor), which consumers may then customize, or the firm may not show a default version and let consumers start from scratch in composing the product. The authors find that the choices that firms make in configuring the mass customization process affect the product utility consumers can achieve in mass customization. The reason is that the mass customization configuration affects how closely the consumer may approach his or her ideal product by mass customizing. Mass customization configurations also affect consumers’ perception of the complexity of mass customization as they affect how many cognitive steps a consumer needs to make in the decision process. Both product utility and complexity in the end determine the utility consumers derive from using a certain mass customization configuration, which in turn will determine main outcome variables for marketers, such as total product sales, satisfaction with the product and the firm, referral behavior and loyalty. The study offers good news for those who wish to provide many mass customization options to consumers, because we find that within the rather large range of modules and module levels we manipulated in this study, consumers did not perceive significant increases in complexity, while they were indeed able to achieve higher product utility. Second, our results imply that firms when increasing the number of module levels, should typically offer consumers more additional options in the most popular range of a module and less additional options at the extremes. Third, pricing should preferably be presented only at the total product level, rather than at the module and product level. We find that this approach reduces complexity and increases product utility. Fourth, firms should offer a default version that consumers can use as a starting point for mass customization, as doing so minimizes the complexity to consumers. The best default version to start out with is a base default version because this type of default version allows the consumer to most closely approach his or her ideal product. The reason is that consumers when presented with an advanced default may buy a product that is more advanced than they actually need. We also found that expert consumers are ideal targets for mass customization offerings. Expert consumers experience lower complexity in mass customization and complexity has a less negative influence on product utility obtained in the mass customization process, all compared to novice consumers. In general, reducing complexity in the mass customization configuration is a promising strategy for firms as it not only increases the utility of the entire process for consumers, but also allows them to compose products that more closely fit their ideal product