Situation Variation in Consumers’ Media Channel Consideration

In this article, the authors investigate consumers’ consideration of media channels during different usage situations. They develop a model that explains consumers’ media channel consideration as a function of the media channel’s perceived benefits. In addition, they hypothesize that the usage situation affects consumers’ media channel consideration and that situation-based benefit requirements moderate the effect of the benefits on their channel consideration. The authors test the hypothesized relationships using survey data from 341 consumers regarding their consideration of 12 different media channels used by manufacturers to communicate product information across three product-related usage situations. The results of the analyses support the proposed model structure and confirm the expected relationships among perceived media channel benefits, usage situations, media channel requirements, and consumers’ media channel consideration.marketing ;

Consumer Preferences for Mass Customization

Increasingly, firms allow consumers to mass customize their products. In this study, the authors investigate consumers’ evaluations of different mass customization configurations when asked to mass customize a product. For instance, mass customization configurations may differ in the number of modules that may be mass customized. The authors find – in the context of mass customization of personal computers – that mass customization configuration affects the product utility consumers can achieve in mass customization as well as their perception of mass customization complexity. In turn, product utility and complexity affect the utility consumers derive from using a certain mass customization configuration. More specifically, product utility has a positive, and complexity has a negative effect on mass customization configuration utility. The effect of complexity is direct as well as indirect, because complexity also lowers product utility. The authors also find that consumers with high product expertise find mass customization configurations less complex than consumers with low product expertise and that for more expert consumers complexity has a less negative impact on product utility. The study has important managerial implications for how companies can design their mass customization configuration to increase utility and decrease complexity.marketing ;

Behavioral Finance, Decumulation, and the Regulatory Strategy for Robo-Advice

This working paper surveys the decumulation services offered by investment robo-advisors as a case study with which to examine regulatory and market structure issues raised by automated financial advice. We provide a short introduction to decumulation, describing some of the uncertainties involved in identifying optimal decumulation strategies and sketching a few of the ‘rules of thumb’ that financial advisors have developed in this area in the face of this uncertainty. Next we describe behavioral effects that could inhibit consumers from following an optimal decumulation strategy, concluding that, left to their own devices, consumers are likely to make sub-optimal decumulation decisions. Then we describe some potentially useful automated decumulation services that are available on the market and present the results of a survey assessing whether those services are offered by investment robo-advisors. Finally, we discuss market structures that may inhibit financial advisors from implementing optimal decumulation strategies for their clients and explore whether there are regulatory strategies that could encourage financial advisors to provide better decumulation services. Two promising strategies are (1) adopting a record-keeping requirement for robo-advisors that is conceptually similar to the ‘black box’ requirement for commercial airlines, and (2) developing a set of robo-advice ‘do’s and don’ts’ and related input/output tests to confirm that these requirements are met

Behavioral Finance, Decumulation, and the Regulatory Strategy for Robo-Advice

This chapter examines the regulatory and market structure concerns raised by automated financial advisors, and arrives at two conclusions. First, the principles-based regulatory approach of the 1940 Investment Advisors Act in the U.S. appears adequate and sufficiently flexible to address the new issues raised by automation, at least for now. Second, there is a pressing need to develop new mechanisms for encouraging investment robo-advisors (and financial advisors generally) to provide high quality decumulation services to their customers, because neither of the two prevailing compensation approaches – assets under management and commissions – provides sufficient incentive at present, and consumers are poorly equipped to evaluate the quality of decumulation services on their own

Regulating Robo Advisors: Old Policy Goals, New Challenges

Financial “robo advice”—an automated service that ranks or matches consumers to financial products—has gained significant attention in the investment industry and on the Hill, but there has not yet been a consensus on how to regulate these new services. Robo advisors often are on par with and can exceed the standards of human advices, but they don’t fit into the category of fiduciary, and therefore won’t be held to the same regulatory standard that humans advisors are. Nonetheless, they are subject to systemic risks and the potential for abuses that can hurt consumers. Professors Tom Baker and Benedict Dellaert offer a regulatory trajectory to follow as the technology of robo advisors continues to develop and expand.https://repository.upenn.edu/pennwhartonppi/1049/thumbnail.jp

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

Regulating Robo Advice Across the Financial Services Industry

Automated financial product advisors – “robo advisors” – are emerging across the financial services industry, helping consumers choose investments, banking products, and insurance policies. Robo advisors have the potential to lower the cost and increase the quality and transparency of financial advice for consumers. But they also pose significant new challenges for regulators who are accustomed to assessing human intermediaries. A well-designed robo advisor will be honest and competent, and it will recommend only suitable products. Because humans design and implement robo advisors, however, honesty, competence, and suitability cannot simply be assumed. Moreover, robo advisors pose new scale risks that are different in kind from that involved in assessing the conduct of thousands of individual actors. This essay identifies the core components of robo advisors, key questions that regulators need to be able to answer about them, and the capacities that regulators need to develop in order to answer those questions. The benefits to developing these capacities almost certainly exceed the costs, because the same returns to scale that make an automated advisor so cost-effective lead to similar returns to scale in assessing the quality of automated advisors

Situation Variation in Consumers’ Media Channel Consideration

In this article, the authors investigate consumers’ consideration of media channels during different usage situations. They develop a model that explains consumers’ media channel consideration as a function of the media channel’s perceived benefits. In addition, they hypothesize that the usage situation affects consumers’ media channel consideration and that situation-based benefit requirements moderate the effect of the benefits on their channel consideration. The authors test the hypothesized relationships using survey data from 341 consumers regarding their consideration of 12 different media channels used by manufacturers to communicate product information across three product-related usage situations. The results of the analyses support the proposed model structure and confirm the expected relationships among perceived media channel benefits, usage situations, media channel requirements, and consumers’ media channel consideration

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