Highlights from 2013‚Äôs Putting Research into Practice (PRP) course articles
What makes online content go viral?
Does an emotion (positive or negative) attached with specific content dictate whether it will be shared more or less online? Contrary to popular belief that negative content tends to be shared more, it was found in a recent study by Berger & Milkman (2012) that positive news is actually more viral. But while sad content is less viral, anger or anxiety inducing articles are both more likely to make the paper’s most emailed list. It is important to realize that emotions associated with arousal such as awe, anxiety and anger are positively linked with virality.
The findings shed light on why people share online content and provide insight into how to design effective viral marketing campaigns. It may be important to rectify experiences that make customers anxious rather than disappointed. More practically useful, interesting, and surprising content is more viral.
Users’ Attention to Text Advertisements
Is text advertising subject to the same “blindness” effects as banner advertising? Chaparro et al. (2011) examined whether users are blind to text advertisements and the effects of search type (exact or semantic) and target location on the degree of blindness. The results demonstrated that users will ignore text advertisement placed on the top and right side of the page. However when the advertisement was placed within the content of the page, users were more likely to pay attention to it. Users actively ignore text advertising unless it is required to complete their task or it is perceived as not being advertising.
Barriers and Drivers for Non-shoppers in E-Commerce
A lot of ecommerce research focuses on the behaviors of online shoppers &ndash ;but what about the people who are not shopping online? Why they are not shopping online and what will motivate them to do so? In a research study by Iglesias-Pradas et al. (2012), 1499 participants from Spanish households who did not have prior experience shopping online were asked to respond to two open ended questions which included:
(1) Reason/s for not buying a product/service online?
(2) What factors would influence their online shopping in the future?
The results identified four types of non-shoppers based on their reasons to not make online purchases. Half of them were concerned by security and trust issues but some were infrastructure (lack of resources to engage online) and product-conditioned (concerns about shipping, delivery, etc.). Six groups were found based on the drivers. Most of them could become e-shoppers if they perceived an improvement in safety of online transactions or if they found a product that was not available in the offline channels.
Sorting Behavior and Consumer Decision-Making
Does product sorting on a product web page influence decision-making? Researchers Cai and Xu (2008) considered the perception of quality and price points, and whether presenting the product (e.g. a camera) information in descending order, ascending order, or random order made a difference to the users” decision making processes.
When the cameras were shown in descending order (highest quality at the top), then the importance of quality was ranked the highest. Price was not deemed that important. If the cameras were shown in ascending or random order, then quality was not deemed to be that important, and price was a more important consideration. The average price of the camera the participants picked when the cameras were shown in random order was $672. The average price when a descending quality order was used was $801, which is a 19% increase.
Quality of a product affects consumers’ purchasing decisions at least for high-end items. The human brain is averse to losing value or attributes. This study shows that the best sort order, at least for selling high-end items like cameras, might be in descending order by quality.
Older Adults and the Use of the Internet
Are older adults using the internet for social reasons only? Not anymore. A recent survey by the American Association of Retired Persons (AARP) reported that older adults are going online for a variety of tasks including researching information, buying products online, making travel reservations, online banking, using social networks, reading online newspapers, magazines and books, taking online courses, searching for jobs and so on. There is a growing need to understand the diverse needs and interests for content and service delivery among older adults.
Effect of language on perceived risk online
Is perceived risk online affected by the language in which a user browses a given website? Alc√°ntara-Pilar et al. (2013) were interested to find out if the risk perceived by the users from cultures with a high degree of uncertainty avoidance (i.e. cultures affected by uncertainty, ambiguity and the unknown) will be greater when they browse a commercial website that is in their primary language than when the site in question is in a second language that comes from a culture of lower uncertainty avoidance. Spain and Great Britain were chosen as the two cultures due to their difference in uncertainty avoidance index (Spain: 86, Great Britain: 35). A fictitious tourist destination site was created with two versions ‚Äď one written in Spanish and the other in English.
The researchers found that the Spanish sample had a higher value for perceived risk online when they browse in Spanish (their primary language). The difference in the perception of risk was not significantly different between English and Spanish sites for the British sample. It is important to realize that information processing is biased by the cultural values of the language and the degree of bilingualism in an individual. It might be useful to use a language associated with lower UA, when you want to reduce the perceived risk associated with a communication message. In a tourism-related communication campaign, it may be advisable to include some words that communicate the culture of the destination.