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Are you a photographer that is looking to make some extra money? Do you want your work to be featured on posters, in advertisements or magazines? Do you want your best photos to be ‘in the picture’? Or are you a looking for affordable high-quality images to use on your website, flyers etc.? iStockphoto (iStock) is the place to go!

What is iStock?

iStock is one of the world’s leading online platforms for stock photography. They provide millions of customers with carefully selected, exclusive high-quality images for affordable tariffs. iStock was founded in 2000 and created the crowdsourced stock sector. Meanwhile it has become ‘the’ source of user-generated photos, illustrations and videos. They offer the contributors (artists, photographers, ect.) a platform to earn money with their passion, by assisting them by licensing their content to businesses and individuals. In return, these contributors receive commissions.

How and why does it work?

In order to become a contributor and upload images, photographers have to answer several questions regarding photographic knowledge, legal issues, policies etc. Before approval, the images are carefully screened for quality. Uploading images is completely cost free, therefore the platform charges a percentage of sales. The commissions that the contributors receive, range from 15% to 50% and depend on factors such as quality, quantity and exclusivity.

If you are a consumer, looking for images to use for publication, you can search the extensive and ever-increasing database full of images. The content is split into signature- and essential images. The signature content is less expensive than the essential content, which is of higher quality. There are 2 different ways to acquire content. The first one is to buy credits and spend these on purchases. By buying multiple images/credits at the same time, the costs decrease. The second way is to subscribe to an image subscription. This allows the subscriber to use 10-750 images each month, depending on the subscription. Credits are the best choice when a one-time purchase is conducted and when the future needs are hard to forecast. When consumers need images on a regular base, the subscription is more beneficial.

The iStock platform outsources the task of high quality stock photography to a large group of photographers, but why? These contributors are the experts on photography and are generally able to provide high quality content. Without the contributors, it would be very costly to provide unique images for the wishes of consumers. The quality, the range of content and especially the amount of content is drastically increased by outsourcing the task of photography to the crowd.

But why would these contributors publish their content on the platform? As mentioned, they receive a minor financial compensation for every sale of their content. However, it takes a lot of time, a high amount- and constant input of high-quality photos and a little bit of luck in order for these commissions to add up. Or are the intrinsic motivators, in the form of glory and love more important? Contributors can showcase their work to a large audience, which could positively influence his/her status. Other contributors might upload content, just because of their love for photography. Their work might inspire others and they might be inspired by other content.

Evaluation

iStock has a high-quality control, both contributors and contributions are evaluated in terms of quality and suitability. There provide guidelines and give penalties in case of plagiarism. The contributors are both extrinsically- and intrinsically motivated. Consumers of the content can purchase content in several ways, depending on what is most suitable for their situation.

Nevertheless, there are some points that need careful consideration. The platform thrives on the two-sided network effect, which implies that more contributors result in more consumers and vice versa. Therefore, it is very important that the platform is attractive for both user sides of the platform. Without one or another, the platform will lose popularity. Additionally, the fact that consumers can make eternal and unlimited use of the content, without any hard control of the contributors, might scare off contributors. Although the high number of available images might be attractive to consumers, it might also scare of possible contributors, as they feel their content will not stand out and be lost in the amount of content. Lastly, iStock does not provide exclusive content, which implies two issues. iStock can license purchased content to other customers as well, which could decrease the attractiveness of the content. Contributors can upload their work on other stock platforms as well, therefore making it easy to switch and decreasing the exclusivity of the platform for consumers. When contributors offer content exclusively for iStock, the commission is increased.

Conclusion

To conclude, the business model of iStock has proven to be effective. Moving forward, there are several points of attention that they can address to further improve the attractiveness of the platform for both contributors and consumers. Suggestions for improvement could be:

The implementation of contests, in which consumers can indicate their image wishes and provide price money. This would make it able for consumers to shop ‘on-demand’ and find content that better fits their needs.
Providing contributors with intangible rewards such as badges, to stimulate intrinsic motivation.
Creating a community in which contributors can discuss the art of photography with each other, and consumers can indicate what their needs are, so that contributors are able to learn from each other and align their content creation with what is in demand.

What suggestions do you have? Do you feel that the provided suggestions improve the platform & business model?

References

Piper, A. (2016). Here’s How You Can Make Extra Cash from Those Photos on Your Hard Drive. The Penny Hoarder. Retrieved 11 March 2018, from https://www.thepennyhoarder.com/make-money/selling-stock-photography/

Stock photos, royalty-free images & video clips. (2018). iStockPhoto.com. Retrieved 11 March 2018, from https://www.istockphoto.com/

Tsekouras, D. (2018). Customer Centric Digital Commerce Session 3. Presentation, Rotterdam School of Management.

Based on the ‘wisdom of the crowd’ effect (Surowiecki, 2005), consumers make use of reviews to make accurate product evaluations. However, due to the large amount of information and conflicting opinions in reviews, it becomes difficult for them to identify and consider the attributes that are relevant to their consumer situation.

Imagine you are browsing a webstore, looking for a new camera to take on your backpacking trip. For this situation, you prefer a camera that is lightweight, easy to use, shock-resistant and cheap. You don’t have a lot of experience with camera’s, so you decide to look at the reviews of other consumers that bought Camera X. As you browse through several reviews, you start to notice that a lot of reviews mention things like FPS, image stabilization, Wi-Fi connection and GPS tracking. However, the reviews are in conflict about the quality of the image stabilization and many mention the lack of a Wi-Fi connection. After reading most of the reviews, you decide that you want to look for a camera that has better image stabilization and a Wi-Fi connection, attributes which you originally didn’t pick as relevant for your situation …

The scenario above, is what Liu & Karahanna (2017) describe as the ‘swaying’ effect. After reading reviews, people might over-weigh irrelevant attributes and under-weigh relevant attributes. They suggest that attribute preferences are more heavily influenced by characteristics of the online reviews rather than by the relevance of the attributes to the consumers decision context.

Theory development & methodology

Liu & Karahanna (2017) developed their theory from the constructive preference perspective theory (Bettman, Luce, & Payne, 1998; Payne, Bettman, Coupey, & Johnson, 1992). This theory suggests that preferences are shaped by the interaction between the properties of the information environment of the choice problem and the properties of the human information-processing system. Liu & Karahanna (2017) propose that three characteristics of online reviews affect the assessment of attribute preference and theorize that these characteristics together may ‘sway’ attribute preferences.

the amount of information about attribute level performance,
the degree of information conflict about attribute level performance
the overall numeric rating and the attribute-level performance information

They conducted three studies, in which they provided the participants with a consumer scenario, asked them to weigh different attributes in terms of relevance and made them evaluate a digital camera based on reviews.

In study 1 they manipulated the three hypothesized factors and examined their effects on the attribute preferences. In study 2, they reproduced this study but added a monetary incentive to induce high motivation to process review information. The third study was a free simulation experiment to provide more realism and to allow for higher generalizability, in which verbal protocol analysis was used to capture and measure the factors.

Main findings

When the participants were asked to weigh the attributed based on the provided scenario, they placed more weight on the relevant attributed than the irrelevant attributes (in the scenario above, the attributes cost, ease-of-use and weight are relevant attributes, whereas image stabilization is not). But when they had to evaluate the camera based on reviews (that contained an uneven amount of information across different attributes, varying degrees of information conflict, and a numeric overall rating), the relevance of the attributes did not have a significant impact on attribute preferences.

CCDC — Figure 1. Participants’ Constructed Attribute Preferences (Liu & Karahanna, 2017)

The amount of attribute information in the reviews had the greatest impact on attribute preferences. Study 2 showed that the degree of attribute information conflict only affects attribute preferences when people have high motivation to process information. Study 3 showed consistent results. The studies provided evidence that attribute preferences that result from reading the reviews are primarily driven by the review characteristics and not by attribute relevance, thus supporting the hypothesized ‘swaying’ effect of online product reviews.

Practical implication.

What implications can be derived from these results? To support informed consumer decision making, it should be investigated how reviews should be organized and presented and how making sense of information conflicts can become less cognitively demanding. The effectiveness of some practical suggestions, such as providing a short description of the reviewer’s background (newegg.com), displaying the amount of positive and negative comments on an attribute (Q. (Ben) Liu, Karahanna, & Watson, 2011) and allowing people to see the overall rating from reviewers who have similar decision context, need to be investigated. Implementation of these suggestions allows consumer to filter reviews from people in a similar consumer scenario, makes making sense of conflicts become less demanding and causes the numeric overall rating to make more sense.

Strengths, weaknesses, suggested improvements

By conducting multiple studies with consistent results, the article provides strong evidence for generalizability & robust hypotheses, which enhances the external validity of the results. Nevertheless, there are some limitations. The study only examines a single product category (camera) and a single scenario. Additionally, the samples only consisted of students with a similar expertise of cameras. It would be interesting to examine whether the effects differ based on the consumer’s level of expertise with the product category (camera) or the product category itself. Additionally, to increase the generalizability of this study, it would be interesting to see if these results also apply on a sample that is more representative of the population (not only students).

I would love to hear your opinions on this. Do you recognize yourself in the ‘swaying’ effect? Are reviews influencing your preferences?

References

Bettman, J. R., Luce, M. F., & Payne, J. W. (1998). Constructive Consumer Choice Processes. Journal of Consumer Research, 25(3), 187–217. https://doi.org/10.1086/209535

Liu, Q. (Ben), Karahanna, E., & Watson, R. T. (2011). Unveiling user-generated content: Designing websites to best present customer reviews. Business Horizons, 54(3), 231–240. https://doi.org/10.1016/j.bushor.2011.01.004

Liu, Q. Ben, & Karahanna, E. (2017). The dark side of reviews: The swaying effects of online product reviews on attribute preference construction. MIS Quarterly, 41(2), 427–448. https://doi.org/10.25300/misq/2017/41.2.05

Payne, J. W., Bettman, J. R., Coupey, E., & Johnson, E. J. (1992). A constructive process view of decision making: Multiple strategies in judgment and choice. Acta Psychologica, 80(1–3), 107–141. https://doi.org/10.1016/0001-6918(92)90043-D

Surowiecki, J. (2005). The Wisdom of Crowds. American Journal of Physics, 75(908), 336. https://doi.org/10.1038/climate.2009.73