This article examines how product and consumer characteristics moderate the influence of online consumer reviews on product sales using data from the video game industry. The findings indicate that online reviews are more influential for less popular games and games whose players have greater Internet experience. The article shows differential impact of consumer reviews across products in the same product category and suggests that firms' online marketing strategies should be contingent on product and consumer characteristics. The authors discuss the implications of these results in light of the increased share of niche products in recent years.

/pdf/impact-of-online-consumer-reviews-on-sales-the-moderating-53shopqfp1.pdf

Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics

Mechanical Turk (MTurk), an online labor market created by Amazon, has recently become popular among social scientists as a source of survey and experimental data. The workers who populate this market have been assessed on dimensions that are universally relevant to understanding whether, why, and when they should be recruited as research participants. We discuss the characteristics of MTurk as a participant pool for psychology and other social sciences, highlighting the traits of the MTurk samples, why people become MTurk workers and research participants, and how data quality on MTurk compares to that from other pools and depends on controllable and uncontrollable factors.

/pdf/inside-the-turk-understanding-mechanical-turk-as-a-33lzlsoyyp.pdf

Inside the Turk Understanding Mechanical Turk as a Participant Pool

https://repository.arizona.edu/bitstream/10150/623545/1/Brandimarte_Beyond_Turk.pdf

Beyond the Turk: Alternative platforms for crowdsourcing behavioral research

Reasoning is generally seen as a means to improve knowledge and make better decisions. However, much evidence shows that reasoning often leads to epistemic distortions and poor decisions. This suggests that the function of reasoning should be rethought. Our hypothesis is that the function of reasoning is argumentative. It is to devise and evaluate arguments intended to persuade. Reasoning so conceived is adaptive given the exceptional dependence of humans on communication and their vulnerability to misinformation. A wide range of evidence in the psychology of reasoning and decision making can be reinterpreted and better explained in the light of this hypothesis. Poor performance in standard reasoning tasks is explained by the lack of argumentative context. When the same problems are placed in a proper argumentative setting, people turn out to be skilled arguers. Skilled arguers, however, are not after the truth but after arguments supporting their views. This explains the notorious confirmation bias. This bias is apparent not only when people are actually arguing, but also when they are reasoning proactively from the perspective of having to defend their opinions. Reasoning so motivated can distort evaluations and attitudes and allow erroneous beliefs to persist. Proactively used reasoning also favors decisions that are easy to justify but not necessarily better. In all these instances traditionally described as failures or flaws, reasoning does exactly what can be expected of an argumentative device: Look for arguments that support a given conclusion, and, ceteris paribus, favor conclusions for which arguments can be found.

/pdf/why-do-humans-reason-arguments-for-an-argumentative-theory-19genwgdwy.pdf

Why Do Humans Reason? Arguments for an Argumentative Theory

Participant attentiveness is a concern for many researchers using Amazon’s Mechanical Turk (MTurk). Although studies comparing the attentiveness of participants on MTurk versus traditional subject pool samples have provided mixed support for this concern, attention check questions and other methods of ensuring participant attention have become prolific in MTurk studies. Because MTurk is a population that learns, we hypothesized that MTurkers would be more attentive to instructions than are traditional subject pool samples. In three online studies, participants from MTurk and collegiate populations participated in a task that included a measure of attentiveness to instructions (an instructional manipulation check: IMC). In all studies, MTurkers were more attentive to the instructions than were college students, even on novel IMCs (Studies 2 and 3), and MTurkers showed larger effects in response to a minute text manipulation. These results have implications for the sustainable use of MTurk samples for social science research and for the conclusions drawn from research with MTurk and college subject pool samples.

/pdf/attentive-turkers-mturk-participants-perform-better-on-10n740ojph.pdf

Attentive Turkers: MTurk participants perform better on online attention checks than do subject pool participants

Mechanical Turk (MTurk), an online labor system run by Amazon.com, provides quick, easy, and inexpensive access to online research participants. As use of MTurk has grown, so have questions from behavioral researchers about its participants, reliability, and low compensation. In this article, we review recent research about MTurk and compare MTurk participants with community and student samples on a set of personality dimensions and classic decision-making biases. Across two studies, we find many similarities between MTurk participants and traditional samples, but we also find important differences. For instance, MTurk participants are less likely to pay attention to experimental materials, reducing statistical power. They are more likely to use the Internet to find answers, even with no incentive for correct responses. MTurk participants have attitudes about money that are different from a community sample’s attitudes but similar to students’ attitudes. Finally, MTurk participants are less extraverted and have lower self-esteem than other participants, presenting challenges for some research domains. Despite these differences, MTurk participants produce reliable results consistent with standard decision-making biases: they are present biased, risk-averse for gains, risk-seeking for losses, show delay/expedite asymmetries, and show the certainty effect—with almost no significant differences in effect sizes from other samples. We conclude that MTurk offers a highly valuable opportunity for data collection and recommend that researchers using MTurk (1) include screening questions that gauge attention and language comprehension; (2) avoid questions with factual answers; and (3) consider how individual differences in financial and social domains may influence results. Copyright © 2012 John Wiley & Sons, Ltd.

/pdf/data-collection-in-a-flat-world-the-strengths-and-weaknesses-18eu8fjf8f.pdf

Data collection in a flat world: the strengths and weaknesses of mechanical turk samples

Mechanical Turk (MTurk), an online labor system run by Amazon.com, provides quick, easy, and inexpensive access to online research participants. As use of MTurk has grown, so have questions from behavioral researchers about its participants, reliability, and low compensation. In this paper we review recent research about MTurk and compare MTurk participants to community and student samples on a set of personality dimensions and classic decision-making biases. Across two studies, we find many similarities between MTurk participants and traditional samples, but we also find important differences. For instance, MTurk participants are less likely to pay attention to experimental materials, reducing statistical power. They are more likely to use the Internet to find answers, even with no incentive for correct responses. MTurk participants have attitudes about money that are different from a community sample’s attitudes, but similar to students’ attitudes. Finally, MTurk participants are less extraverted and have lower self-esteem than other participants, presenting challenges for some research domains. Despite these differences, MTurk participants produce reliable results consistent with standard decision-making biases: They are present biased, risk-averse for gains, risk-seeking for losses, show delay/expedite asymmetries, and show the certainty effect — with almost no significant differences in effect sizes from other samples. We conclude that MTurk offers a highly valuable opportunity for data collection, and recommend that researchers using MTurk 1) include screening questions that gauge attention and language comprehension, 2) avoid questions with factual answers, and 3) consider how individual differences in financial and social domains may influence results.

/pdf/data-collection-in-a-flat-world-strengths-and-weaknesses-of-1y6f89xxwa.pdf

Data Collection in a Flat World: Strengths and Weaknesses of Mechanical Turk Samples

This research studies a psychosocial cost associated with positive word of mouth (WOM): positive WOM can decrease the uniqueness of one’s possessions, which hurts high-uniqueness individuals (pilot study 1). As a result, high- (vs. low-) uniqueness individuals are less willing to generate positive WOM for publicly consumed products that they own. However, high uniqueness does not decrease willingness to generate WOM for privately consumed products (studies 1 and 2) or for products that participants don’t intend to buy (study 2). The effect of uniqueness is more pronounced for WOM that includes positive recommendations, compared to WOM that only contains product details (study 2). Illustrating the process, pilot study 2 demonstrates that for publicly consumed products, WOM recommendations are perceived to be more persuasive than WOM that provides details. Study 3 confirms that high- (vs. low-) uniqueness consumers are less willing to recommend a public product to others, but are as willing to discuss product details. Study 4 analyzes content of real-world WOM and finds evidence that supports these results.

The Effect of Need for Uniqueness on Word of Mouth

This research examines the psychosocial cost associated with positive word of mouth (WOM), which can decrease the uniqueness of possessions and thus harm high-uniqueness consumers (pilot study). As a result, high- (versus low-) uniqueness consumers are less willing to generate positive WOM for publicly consumed products that they own. However, high uniqueness does not decrease willingness to generate WOM for privately consumed products (Study 1). Study 2 demonstrates that for publicly consumed products, WOM that includes positive recommendations is more persuasive than WOM that only contains product details. Consequently, the effect of uniqueness is more pronounced for WOM recommendations than for WOM that only provides details (Study 3). Study 4 confirms that high- (versus low-) uniqueness consumers are less willing to recommend a public product to others but are equally willing to discuss product details. Study 5 analyzes real-world WOM content and finds evidence in support of these results.

The objective of the present research is to study consumer decisions to utilize a line of credit. The life-cycle hypothesis from economics argues that consumers should intertemporally reallocate their incomes over their life stream to maximize lifetime utility. One form of intertemporal allocation is to use past income (in the form of savings) in the future. A second form is the use of future income in the present. This can only be done if consumers have access to a temporary pool of money that they can draw from and replenish in the future--a function performed by consumer credit. However, our research reinforces prior findings that consumers are unable to correctly value their future incomes, and that they lack the cognitive capability to solve the intertemporal optimization problem required by the life-cycle hypothesis. Instead, we argue that consumers use information such as the credit limit as a signal of their future earnings potential. Specifically, if consumers have access to large amounts of credit, they are likely to infer that their lifetime income will be high and hence their willingness to use credit (and their spending) will also be high. Conversely, consumers who are granted lower amounts of credit are likely to infer that their lifetime income will be low and hence their spending will be lower.However, based on research in the area of consumer skepticism and inference making, we also argue for a moderating role of the credibility associated with the credit limit. Specifically, we argue that the above effect of credit availability would be particularly strong for consumers who believe that the credit limit credibly signals their future earnings potential (i.e., a naive consumer who has limited experience with consumer credit). However, as consumers gain experience with credit, they start discounting credit availability as a predictor of their future and start questioning the validity of the process used to set the credit limit. Hence, with experience the effect of credit limit on the willingness to use credit should be attenuated.We test these predictions in five separate studies. In the first experimental study, we manipulate credit limit and credibility and pose subjects with a hypothetical purchase opportunity. Consistent with our prediction, credit limit impacted the propensity to spend, but only when the credibility was high. In the second experimental study, we replicate these findings even when subjects were given information about their expected future salaries, and also show that the credit limit influences their expectation of future earnings potential. In the third study, we show that the mere availability (and increase) of current liquidity cannot explain our findings. In the fourth study, we conduct a survey of consumers in which we measure a number of demographic characteristics and also ask them for their propensity to spend in a given purchase situation. In the fifth study we use the Survey of Consumer Finances (SCF) dataset, a triennial survey of U.S. families that is designed to provide detailed information on the use of financial services, spending behaviors, and selected demographic characteristics. Results from both studies 4 and 5 provide further support for our proposed framework--credit limits influence spending to a greater extent for consumers with lower credibility: younger consumers and less-educated consumers. Across all studies we achieved triangulation by using a variety of approaches (surveys and experiments), subjects types (young students and older consumers), nature of predictor variables (manipulated and measured), dependent measures (purchase likelihood, credit card balance, new charges), and methods of analysis (ANOVA and regression), and consistently found that increasing credit limits on a credit card increases spending, especially when the credibility of the limit is high.This paper joins a growing body of literature in marketing and behavioral decision theory that goes beyond the traditional domains of inquiry (e.g., product choice, effects of marketing mix variables) and focuses on consumer decisions relating to the appropriate use of income to finance consumption. Our framework differs from prior research on the effect of payment mechanisms on spending in two significant ways. First, we are interested in the effects of the availability of credit on spending, and not necessarily in the effect of the transaction format that is associated with each payment mechanism. Second, while prior research has studied the point-of-purchase and historic (i.e., prepurchase) effects of credit, the present research is concerned with the availability of credit in the future. Specifically, our framework is invariant to the current and prior usage of credit by the consumer.

/pdf/the-effect-of-credit-on-spending-decisions-the-role-of-the-2zkcehibtl.pdf

Amar Cheema

Papers

Data collection in a flat world: the strengths and weaknesses of mechanical turk samples

Data Collection in a Flat World: Strengths and Weaknesses of Mechanical Turk Samples

The Effect of Need for Uniqueness on Word of Mouth

The Effect of Need for Uniqueness on Word of Mouth

The Effect of Credit on Spending Decisions: The Role of the Credit Limit and Credibility