Category Archives: Articles

The sharing economy: children’s toys


Nowadays the electronical screen devices provide endless entertainment opportunities for children. Apple has a special ‘kids’ section in de App Store offering numerous different kinds of apps as games apps, educative apps, book reading apps etc. A survey conducted in 2014 already concluded that touch screens are the primary play activity followed by game consoles as shown in the figure below. It is hard for the traditional toys business to compete with the rapidly developing online kids’ entertainment industry (Michael Cohen Group, 2014).

Afbeelding1 childrenSource: (Michael Cohen Group, 2014)

Parents try to limit the screen-time per day of their children as they want to promote an active lifestyle as the consequences of frequent use of screen devices are severe. Physical health issues are one of the main concerns for parents as research shows that excessive screen time can lead to serious problems including obesity, higher risk of Type 2 Diabetes and increase abdominal fat (Nightingale et al. 2017, Suchert et al. 2016). Furthermore, on-screen activities cannot replace certain essential skill developments as for example hand-eye coordination and creativity.

One of the main reasons children are not playing as much with physical toys is that they lose interest overtime. Toys are expensive and the majority of households are not able to afford new toys on a regular basis (Pley, 2018). The company Pley provides the solution to the abovementioned issues. As the founder states:

“Being frustrated with finding the appropriate toys to my children as their interests change constantly, I realized there had to be a smarter way to play. Inspired by the sharing economy, we envisioned Pley.”

-Ranan Lachman, Founder of Pley

 

Business Model

Pley is a subscription based toy delivery service company based in the United States. Currently the company has over 300.000+ subscriptions. Pley provides two different services:

(1) Surprise box subscription

Afbeelding2 children.pngThe surprise box is available in different themes. The price for the boxes depend on subscription around $22/box. The boxes are delivered every 2 months.

(2) Toy Library subscription

Afbeelding3 children.pngThe toy library is a subscription based toy rental service. Depending on the subscription $12.99 for 1 credit/month and $29.99 for 3 credits/month the customer can choose from over 500+ toys in the toy library. The service applies the pick-enjoy-return&repeat method. This is theoretically the most interesting service of Pley, therefore the blog will focus on the Toy Library.

The toy library of Pley makes use of the concept of the sharing economy, more specific the collaborative consumption. Collaborative consumption can be defined as “the peertopeer based activity of obtaining, giving, or sharing the access to goods and services coordinated through communitybased online services” (Hamari et al., 2015).  The coordination of the toys is monitored by Pley, acting as a platform arranging the exchanges as shown in the figure below. Furthermore, there is the possibility to send old toys to Pley and receive a monetary value.

Afbeelding4 children

The success of Pley is explained by the fact that the company actively takes into consideration the needs of the customer and developed a platform that serves the needs of the customers. The customers want to (1) let their children play with physical toys in order to improve health and develop critical skills (2) let their children play with novel toys regularly and (3) not spend too much money on toys. The toy library of Pley conforms to all the wishes by engaging the customer in Pley’s subscription based toy sharing platform.

Efficiency criteria

The business model of Pley’s toy library is based on joint profitability of both the company and the customers. The customers benefit as they are able to receive and return toys regularly at a low rate, which would otherwise not have been possible as the alternative for novelty in toys is to buy new toys in the store at a high rate or let the children play on on-screen devices, both not desired. Pley benefits from the profits made from providing the subscription based service and from toys send to Pley they can use in the toy library, in the long term providing profit.

Furthermore, Pley meets the feasibility of required reallocations criteria. First, the polity and judiciary aspects are not a factor of concern for the business model as the activities are political independent and within the U.S law. Efficient social norms are carefully considered as the company is a Certified B Corporation and applies the buy-one-give-one model where for every sold toy, one toy is given to a child in need an underdeveloped area in the world (Pley, 2018).

Bibliograpy

  1. Hamari, J., Sjöklint, M., & Ukkonen, A. (2015). The sharing economy: Why people participate in collaborative consumption. Journal of the Association for Information Science and Technology
  2. Michael Cohen Group, Toys, Learning, & Play Summit. (2014) From: http://www.mcgrc.com/wp-content/uploads/2015/03/MCGRC_Digital-Kids-Presentation_pdf Assessed: 17-02-18
  3. Nightingale, C.M., Rudnicka, A.R., Donin, A.S., Sattar, N., Cook, D.G., Whincup, P.H., & Owen, C.G. (2017). Screen time is associated with adiposity and insulin resistance in children. Archives of Disease in Childhood, 0:1-5.
  4. Pley, 2018. From https://www.pley.com/about. Assessed: 17-02-18
  5. Suchert, V., Hanewinkel, R., & Isensee, B. (2016). Screen time, weight status and the self-concept of physical attractiveness in adolescents. Journal of Adolescence, 48:11-17.

 

How to find commercially attractive user-generated entries?


Introduction

Letting users generate designs, also known as crowdsourcing, is the method when companies ask consumers to develop new ideas for products, slogans or specific problems. One of the pioneers within the field of asking ‘the crowd’ to contribute new products is the LEGO ideas platform. Here consumers can share their idea and gather support, hereafter LEGO will review all ideas and perhaps develop this particular idea into a new product.

Benefits

Crowdsourcing has several benefits for companies, such as the ability to solve problems, generate ideas, outsource tasks or use it as information pooling. (Tsekouras, 2018) However, Franke et al. (2006) found that users’ willingness to pay also increases substantially if they are allowed to design their own solutions. Resulting in a sales increase for the companies. The paper by Berg Jensen et al. (2014) studied which data can be used to help a focal producer firm to reduce its workload in the selection phase by predicting which user-generated designs it would most likely perceive as commercially attractive.

Lead-users

The study focused on the lead-users within the LEGO user community and their contributions to LEGO ideas. Lead-users were defined in 1986 by von Hippel as: “the members of a user population who get benefits of obtaining a solution to their needs and are at the leading edge of important trends in a marketplace.” Franke et al., (2006) elaborated further on this and found that lead-users tend to be the ones that come up with the most commercially attractive ideas in online communities. The study screened lead-users for input concerning relevant predictors and corresponding theories. It became apparent that one could distinguish between characteristics of the designs that lead-users tend to produce and the individual characteristics of lead-users.

Analysis

Berg Jensen et al. used 1799 designs from 116 user-designers to find whether firms can anticipate on the most commercially attractive ideas. The three prominent variables that were used by a focal producer firm of such a community for filtering of promising user-generated designs were:

  • The complexity of a given design
  • The positive feedback from the community on specific designs
  • The intensity of design activity by a user designer

The review of whether the focal producer firm perceives a user-generated design as attractive was done by measuring the assessment of two professional LEGO reviewers. These reviewers were trained by LEGO to find which design would be appealing to large market segments. However, regarding the data collection it is questionable whether this outcome is generalizable and attractive for other firms. As just two LEGO employees checked the designs, this could be highly biased and might have been checked twice or perhaps added a group of lead-users.

Complexity of design

The variable shows products that are rich in appearance and are therefore of great consumer value compared to alternative and competing designs. In this study the complexity is the number of pieces utilized in a given design. This also results in differentiation from competitors (Baldwin et al., 2006). The authors found an inverted U-shaped relationship between the complexity and its perceived commercial attractiveness. However, complexity can also result in higher production and distribution costs, as there is a point in time where the cost dimension outweighs the revenue dimension of a new design. The final turning point was found to be at 3950 pieces, which is highly context specific; therefore it is difficult to infer the application to a broad market of user-generated design platforms.

Positive community feedback

When a given design has attracted some endorsement from other users who may represent broader market segments this shows the positive community feedback (Baldwin et al., 2006). The authors found highly statistical significant evidence (.05083) that the relationship between the positive feedback received by a given user-generated design within the peer community and its perceived commercial attractiveness was positive. The empirical setting of the study was within a brand community where members have strong emotional attachments with the focal producer firm, which makes it hard for other firms’ communities to find lead-users that are such fanatics of their products.

Design activity by user designer.

The intensity of the design activity by a user designer is thus the number of designs generated and posted into LEGO ideas by a user. The results show there is a U-shaped relationship between the intensity of a certain user-designer’s activities and the likelihood that a given design by that user will be perceived as commercially attractive. The turning point turned out to be at a generation of 99 designs in two weeks time. This seems like an extreme amount, however, these types of user-designers are not uncommon in the brand community setting and might represent an important source of innovation.

 Community

There was no evidence to infer that whether the presence of a user-designer in the community increases the likelihood that a specific design by that user will be perceived as commercially attractive by the focal firm. This would show that that the community LEGO built does not add to the final commercial attractiveness of entire product. With this outcome the authors would show that the interaction within the community does not really have a commercial benefit.

Conclusion

Even though this study is difficult to generalize for other firms focusing on communities, the findings will help firms that use user-design platforms for physical prototypes, being a very niche market. This study is a first step towards a new web-based marketing research approach that can enable firms to filter vast number of user-generated designs more effectively and efficiently.

 

Sources

Baldwin, C., von Hippel, E. and Hienerth, C. (2006). How User Innovations Become Commercial Products: A Theoretical Investigation and Case Study. MIT Sloan Research Paper, (9).

Franke, N., von Hippel, E. and Schreier, M. (2006). Finding Commercially Attractive User Innovations: A Test of Lead-User Theory. Journal of Product Innovation Management, 23(4), pp.301-315.

Jensen, M., Hienerth, C. and Lettl, C. (2014). Forecasting the Commercial Attractiveness of User-Generated Designs Using Online Data: An Empirical Study within the LEGO User Community. Journal of Product Innovation Management, 31, pp.75-93.

Tsekouras, D. (2018). CUSTOMER CENTRIC DIGITAL COMMERCE – Session 3.

von Hippel, E. (1986). Lead Users: A Source of Novel Product Concepts. Management Science, 32(7), pp.791-805.

Sharing and Translating lyrics for the world: Musixmatch


“Words matter” or “Your free music sounds better with lyrics” are just two of the slogans that best describe Musixmatch, the Italian start-up that has come to be the world’s largest lyrics catalog and platform. Founded in 2010, the company has grown to reach more than 60 million users around the world. But how does Musixmatch work?

The Musixmatch catalogue, platform and app principally allow users to: 1) access lyrics and/or their translation in other languages; 2) share and/or review written down and/or translated lyrics from songs all around the world; 3) synchronize their music library of many music apps (e.g. Spotify, Deezer, Google Play Music) so that the lyrics pop up (like in Youtube lyrics videos) when one is listening to a song on a music app in his/her device; and 4) create the synchronization song(s) – lyrics, which will then be shared worldwide via Musixmatch and the apps in which Musixmatch is supported.

Musixmatch has been thus ideated for users who want to search for lyrics and also who want to see/think about the lyrics while listening to a song. In this respect, Musixmatch CEO Massimo Ciociola points out (paraphrased): “The fifth most searched category in Google is lyrics. Why, in accessing lyrics, can’t we provide a better, faster, more complete, more comprehensive catalogue and user experience with songs’ lyrics?” Another, peculiar aspect of Musixmatch is the size of its workforce compared to its users’ base. 30 employees (all engineers) vs more than 50 million users/downloads. These figures point out to an important feature of Musixmatch: the fundamental role that users and contributors have in creating value for the platform. In this respect, Musixmatch encourages users to contribute to the catalogue, by either writing, translating, reviewing or synchronizing songs’ lyrics. In this way, Musixmatch, like many other platforms, has been subjected to so-called “network effects”, where the value of the app to users has increased due to the increasing number of contributors. As CEO Ciociola points out: “Lyrics  missing? We ask the community”.  The incentive schemes for this crowd-sourced component can be best described by quoting the company’s website: “Inside the Musixmatch community users earn points based on the actions they do on the lyrics. Based on those points the user can reach a higher level and status in the community that give more power to his/her actions”. Therefore, the incentive scheme for users to generate value for the app does not include monetary rewards, but only recognition in terms of status/power of action in the user community.

Despite this absence of monetary rewards for contributing, and despite the fact that the company has not officially become profitable, there are several mutual benefits of this contribution-based system for both the firm and contributors.  Users, through their contribution(s), can “show-off” and gain “social” benefits, in terms of increased reputation and self-esteem in the community they belong to. Some top users can even become “curators”, which “gives them extra powers to control what’s happening in the community”.  Another aspect that Musixmatch emphasizes is the “feeling” aspect, where the firm asks “passionate” users who really enjoy to share lyrics to contribute. This emphasis is perfectly justified by the fact that people indeed love to share lyrics and the emotions that come with them and their blending with music in many social settings. We can think of Facebook, Twitter, or Youtube, but also of more offline settings like parties or night campfires with guitars and other instruments.

Musixmatch, from its point of view, sees the value of its platform increasing as more and more of its users contribute. Musixmatch’s current main source of revenue is data licensing , but the firm is also considering to  start selling advertising space. Either way, a platform with larger amounts of data, which results from the network effects from the increasing number of users, can be a greater source of revenue for Musixmatch. The costs of monitoring the crowd-sourcing process can be rather limited. The microtasking nature of sharing, reviewing and translating lyrics does not require high levels of cognitive ability, competences or a particular expertise to check the quality of users’ contribution. Also, often times quality checks for lyrics translation and composition are done by the users themselves. In this respect, the company has been able to successfully set up a firm and effective set of community rules that regulates users’ activities.

In terms of external arrangements, Musixmatch has been the first lyrics’ app and platform to formalize legal agreements with major international publishers, such as EMI Publishing, SonyATV and PeerMusic among others. This has permitted MusixMatch to legitimize its role in the apps and catalogues’ world, to increase its users’ base and to become the world’s largest lyrics’ platform, or, as CEO Ciociola points out, the “Music Vocabulary of the World”.

 

Sources: 

Blohm, I., Zogaj, S., Bretschneider, U., & Leimeister, J. M. (2018). How to Manage Crowdsourcing Platforms Effectively?. California Management Review, 60(2), 122-149.

“Musixmatch Wants to Be the ‘IMDb of Music Lyrics,’ Launches Lyric Video Messaging App”Billboard. Retrieved 2018-02-17

O’Hear, Steve. “Song Lyrics App Musixmatch Hacks Its Way To 50M Downloads/30M MAUs, Adds Spotify Support”TechCrunch. Retrieved 2018-02-17

https://www.musixmatch.com/

https://www.musixmatch.com/community-rules

 

 

 

Alexa, what is your business model?


Introduction
“The conversations of the future are between a person and a machine” (Hood, 2017). You might have seen the movie ‘Her’ where an advanced female AI voice-assistant and a man build a relationship together. We are not there yet, but conversations with machines are definitely on the rise. Today, 40% of the adults use voice search once per day and the prediction for 2020 is that 50% of the searches will be done through voice (Jeffs, 2018). Smart-speakers in houses and offices are used to channel voice-searches. Amazon Echo, had the first mover advantage in 2014, and currently dominates the market with a share of roughly 70% (Quartz, 2018). In 2017, Google Home was launched, followed by the Apple HomePod. Microsoft and Facebook are also aiming to release their first smart-speaker later in the year.

her-fp-0880
Joaquin Phoenix plays a man in love with an operating system in director Spike Jonze’s latest film, Her.

To better understand smart-speakers and virtual assistants this blog analyses the business model of the Amazon Echo with Alexa as virtual assistant.  Specifically the following questions are discussed:
1.How does Amazon create value for customers?
2.How does Amazon profit?
3.How does Amazon maximise efficiency in its developer’s network?
4.How does Amazon deal with privacy?

1. Customer value
voice-requests, music, calling and banking
The Echo allows customers to request actions at a virtual assistant using voice. Voice is faster and more convenient than typing and more easy to do while moving (Agrawal, 2017). You can ask Alexa to play specific music, search wikipedia for answers, do maths, set timers, set events or play voice games. More advanced uses cases are the ability to call, message someone, check your bank account or transfer money. More uses cases are available on the Amazon Echo and instead of the App terminology on mobile platforms, these voice programs called “Skills”.

Home-integration
The Echo can be connected with other devices such as your lights, fridge, thermostat, locks on doors. Routines can be set, for example with “Alexa goodnight” to shut down lights and lock-doors at once (Newman, 2017).

Shopping
You can order products from the Amazon store using your Echo. With the re-order command you can re-order a certain product and Alexa will review your purchase history to see what brand you want (Gartenberg, 2017)

Emergent Value
As Grönroos and Voimo (2013) discuss, Amazon can be seen as the value facilitator, offering the Echo, assistant and skills for the customer to create value in-use. Moreover, as experience increases more value for the customer emerges. Especially with AI learning from the customer, a system views can be taken towards value creation. Emergent properties arise, when the customer continuously interacts with AI, allowing the customer and AI to create more and more personalized value which could not be predicted ex-ante.

2. Profit
At this moment the monetisation of the Echo or Alexa is not the focus of Amazon. Amazon aims to capture the complete market and improve the product (Simonite, 2016).  Several revenue paths exists and will be more important as the customer base and frequency of use increases:

  1. Increased sales via improved recommendations. Recommendations stems from understanding the customer and delivery of recommendations (Adomavicius and Tuzhilin’s, 2005). Voice-conversations with Alexa provide valuable information on who the customer is, what he/she wants and in the customer funnel he/she is. This data can be merged with data with the other data Amazon has to form a completer picture. This customer understanding improves the recommendations Amazon can provide and increases the sales revenue for Amazon or marketing advice revenue. For the latter, Amazon can use the understanding to better advice other companies on how to target a specific customer.
  2. Increased sales via easier customer journey. Voice is more natural than typing and hence it has become easier to order a product. It is expected that replenishment orders, for example for toilet paper or batteries, will be increase. See figure 1 for a forecast of US voice payments and number of voice-users.
  3. Ads revenue. Amazon is looking into promoted search results for voice-searches on Alexa. Partner companies would bid to end up high in the search results, which is even more important for voice than with a desktop/mobile search (Newman, 2018).
  4. Skills commission fee. Similar to Apple taking a share from app purchases in the Appstore, Amazon could take a share from skill subscriptions or in-skill purchases to earn money from its open platform. This brings us to the next subsection: efficiency.
594adeaca3630f1b008b45b9-750-529
Figure 1: Forecast US voice (payments) adoption

3. Efficiency
Amazon has the platform challenge that it wants to increase participation on the customer as well as the developer side. Amazon is experimenting with its internal institutional arrangements (IA) with developers. Carson et al. (1999) would argue that a contractual arrangement is an efficient IA if it can, among other criteria, increase the profit of the system and of individual contributors. Since 2018, Amazon offers the option for in-skill purchases with Amazon Pay, such that users can pay developers. Subscriptions is a second channel through which developers can earn money. Profits for developers and Amazon can still be improved if discoverability of Skills, which is harder in a voice-based environment, increases. The contribution of developers also depends on the easy of use of the developer’s toolkit (Hollander, 2017).

4. Privacy
How does Amazon use your data. “Alexa uses your voice recording to answer your questions, fulfill your requests, and improve your experience and our services,” Amazon says. “This includes training Alexa to interpret speech and language to help improve her ability to understand and respond to your requests.” (Newman, 2018b).
Amazon only records data when Alexa is triggered, meaning, when the ‘wake word’ Alexa is mentioned, and allows users to review and delete voice-recordings. If you want to delete bulk recordings you need to go to the Amazon website. There is no method to have your recordings automatically deleted. (Barett, 2017)
Amazon aims to better and better understand the customer which includes deducting your emotions from speech (Dickson, 2018). The external institutions about privacy will highly influence what Amazon is able to do and not do with your data in the future and how specifically transparency information should be provided.

Concluding notes
Voice-search and virtual assistants are on the rise with smart speakers as their physical embodiment. Customer value is derived from using voice to ask questions, shop and control home furniture. As AI advances, more personalised and emergent value arises for the customer. Monetisation is not a focus yet for Amazon, but which massive adoption in the future, there will be plenty of ways to profit from the Echo and Alexa. Improved recommendation systems, sales, ad placement and commissions on Skill subscriptions are examples of profit avenues. Institutional challenges arise for Amazon in the best alignment of developer incentives and when future privacy regulations change.

References:

Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE transactions on knowledge and data engineering, 17(6), 734-749.

Agrawal 2017, accessed at:
https://www.forbes.com/sites/ajagrawal/2017/08/27/how-voice-search-will-change-the-future-of-seo/#636a046d7ca1

Barett, 2017, accessed at:
https://www.wired.com/story/amazon-echo-and-google-home-voice-data-delete/

Carson, S. J., Devinney, T. M., Dowling, G. R., & John, G. (1999). Understanding institutional designs within marketing value systems. The Journal of Marketing, 115-130.

Dickson, 2018, accessed at:
https://www.dailydot.com/debug/amazons-alexa-wind-monetizing-feelings/

Gartenberg 2017, accessed at:
https://www.theverge.com/2017/7/10/15947672/amazon-alexa-voice-controls-shopping-prime-echo-how-to

Hollander, 2017, accessed at:
http://www.businessinsider.com/amazon-rolls-out-monetization-tools-for-alexa-skills-2017-12?international=true&r=US&IR=T

Hood, 2017, accessed at:
https://mayvendev.com/blog/siri-alexa-conversational-systems-changing-business

Jeffs, 2017, accessed at:
https://www.branded3.com/blog/google-voice-search-stats-growth-trends/

Newman 2017, accessed at:
https://www.fastcompany.com/40474833/amazons-alexa-is-a-real-smart-home-platform-now

Newman, 2018
http://www.businessinsider.com/amazon-exploring-ad-options-echo-alexa-2018-1?international=true&r=US&IR=T

Newman, 2018b, accessed at:
https://www.fastcompany.com/40522226/can-mycrofts-privacy-centric-voice-assistant-take-on-alexa-and-google

Simonite 2016, accessed at:
https://www.technologyreview.com/s/601583/how-alexa-siri-and-google-assistant-will-make-money-off-you/

Quartz, 2017, accessed at:
Amazon Echo’s dominance in the smart-speaker market is a lesson on the virtue of being first

“THIS POST IS SPONSORED”


Effects of Sponsorship Disclosure on Persuasion Knowledge and Electronic Word of Mouth in the Context of Facebook

facebook-logo-100035675-mediumThey are everywhere. We all have seen one: a post on Facebook, Instagram or any other social media platform with a little sign saying that the post is sponsored. We see a celebrity enjoying a certain product and recommending it to the audience. We think to ourselves if the person in question is genuine in his or her motives of sharing it, whether they are actually using the product or whether we should follow their recommendation to purchase it ourselves and possibly share our newly found trophy with our family and friends. This simple everyday ritual we have with ourselves, sometimes multiple times a day, has prominent psychological mechanisms coming into play, guiding us through the journey starting from the recognition of the post as sponsored to eventually activating us to share it with our loved ones.

These psychological mechanisms lay the foundation of the research conducted by Boerman, Willemsen and Van der Aa (2017). The researchers identify the source of the sponsored post(brand or celebrity) as the initial step to recognizing it as carrying persuasive, or in other words, advertising value by consumers. This is defined as the activation of the conceptual persuasion knowledge, which in turn, activates the attitudinal persuasion knowledge. Attitudinal PK gets activated when consumers start developing critical and distrusting feelings towards the advertisement (Boerman, Van Reijmersdal and Neijens 2012).  All these are used as determinants to find out whether the consumers eventually engage in electronic word of mouth (eWOM; cf., Berger 2014).

Designing the experiment

Building on the theoretical foundations mentioned above, researchers conduct an online experiment with 409 participants. A post with David Beckham drinking an Illy branded cup of coffee with the text ‘Starting the day with a nice cup of coffee!’ (posted by David Beckham) and ‘David Beckham starts his day with a nice cup of coffee!’ (posted by the brand) is shown to participants to test the following hypotheses by having participants answer a series of questions:

H1. A Facebook ad that is accompanied by a sponsorship disclosure (‘Sponsored’) will be more likely to activate consumers’ conceptual persuasion knowledge, than a Facebook ad without a sponsorship disclosure.

H2. A Facebook ad that is posted by a celebrity will be less likely to activate conceptual persuasion knowledge, than a Facebook ad that is posted by a brand.

H3. The effects of a sponsorship disclosure on the use of conceptual persuasion knowledge are stronger when a Facebook ad is posted by a celebrity compared to when a Facebook ad is posted by a brand.

H4. Source moderates the effect of the sponsorship disclosure on attitudinal persuasion knowledge through the activation of conceptual persuasion knowledge: The mediated relationship of the disclosure on attitudinal persuasion knowledge will be stronger when the Facebook ad is posted by a celebrity (vs. a brand).

H5. When a Facebook ad is posted by a celebrity, a sponsorship disclosure activates conceptual persuasion knowledge, which results in the use of attitudinal persuasion knowledge and ultimately lowers eWOM. When a Facebook ad is posted by a brand, such serial mediation is less likely to occur.

The figure below clearly outlines the experiment design and the source of the Facebook post as the initial stimulus.

Screen Shot 2018-02-14 at 18.06.39

Anticipated results

In line with the expectations, researchers found evidence to support all five hypotheses. They found that the conceptual and attitudinal PK activation was significantly different when the source of the post was a celebrity in the presence of a sponsorship disclosure. This was not the case when the ad was posted on Facebook by the brand. Activation of the attitudinal PK after recognizing the post as an ad resulted in consumers engaging less in eWOM as a result of the distrusting feelings they developed by recognizing the post as advertising. An interesting finding of the study, however, indicates that little attention is paid to the sponsorship disclosures. The study shows that 59% of the participants did not recognize the sponsorship disclosure which is also in line with previous studies conducted (e.g., Boerman, Van Reijmersdal, and Neijens 2012; Campbell, Mohr, and Verlegh 2013; Wojdynski and Evans 2016). Intuitively, this has an impact on the interpretation of the results. Even though the activation of the conceptual and attitudinal persuasion knowledge of the consumers will result in less engagement, lowering the perceived success of the ad, this does not directly condemn sponsored celebrity Facebook posts to failure since the majority of the people won’t recognize the post as an ad.

 

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 Leveling the playing field

Although the study comes with its limitations due to its single product, brand (Illy coffee), celebrity (David Beckham) and geographical (conducted in the Netherlands) focus, it provides invaluable insights into the effect of sponsorship disclosures on Facebook posts. It seems the regulators’, such as FTC’s, disclosure requirements are not sufficient enough to level the playing field for consumers when it comes to social media advertising. Further research might reveal, however, how this could be overcome as well as consumers moving along the learning curve might become more aware themselves. Until then, better to think twice before you share that post by your favorite celebrity you saw on your newsfeed.

References

Berger, Jonah (2014), “Word of Mouth and Interpersonal Communication: A Review and Directions for Future Research,” Journal of Consumer Psychology, 24, 4, 586–607.

Boerman, Sophie C., Eva A. Van Reijmersdal, and Peter C. Neijens (2012),“Sponsorship Disclosure: Effects of Duration on Persuasion Knowledge and Brand Responses,” Journal of Communication, 62, 6, 1047–64.

Boerman, S., Willemsen, L. and Van Der Aa, E. (2017). “This Post Is Sponsored” Effects of Sponsorship Disclosure on Persuasion Knowledge and Electronic Word of Mouth in the Context of Facebook. Journal of Interactive Marketing, 38, 82-92.

Campbell, M., Mohr, G. and Verlegh, P. (2013). Can disclosures lead consumers to resist covert persuasion? The important roles of disclosure timing and type of response. Journal of Consumer Psychology, 23(4), pp.483-495.

Wojdynski, Bartosz W. and Nathaniel J. Evans (2016), “Going Native: Effects of Disclosure Position and Language on the Recognition and Evaluation of Online Native Advertising,” Journal of Advertising, 45, 2, 157–68.

Would you mind filling out this survey?


Many of us have struggled to find participants to fill out our bachelor’s thesis/dissertation survey. I remember logging in into Facebook and finding 5 to 6 “PM’s” (private messages) A DAY from classmates that have been abusing of the CTRL+C and CTRL+V command:

Hey “name”, how are you doing?
Could you please fill out my thesis survey? It’s about 5 minutes long and it’s completely anonymous. I can fill out yours if you want 😉

Good old days…

As bizarre as it sounds, I did not ask them to fill out my thesis survey back, but this is just because the sample of my thesis was ‘manufacturing companies‘, not students, not regular people.

However, if the respondents of my thesis were regular individuals, then I would consider spamming all the contacts of my Facebook friends list. However, this comes with some cons, first and mostly, annoying your friends… But I have good news for you!

Let me introduce you to the award winning start-up project “Survey Exchange”. Even though there have been identical platforms in the past, such as http://www.survey-x-change.com, these are either shut down or do not have very good Google SEO positioning because these type of pages are usually labeled as spam. As a mater of fact, when you try to log in via Facebook, even our beloved start-up has been denied from using Zuckerberg’s APIs or the developers have messed up somewhere in the Login code.

02_errorfb

Our start-up has been operating since 2016 and has won multiple student entrepreneurship awards in the UK (Linkedin.com, 2018). As of February 16th 2018, Survey Exchange is the first result to show up when googling the search words “survey exchange” and according to its founders it has a potential market share of half million users in the UK alone (Survey Exchange, 2018), which I honestly think is a long shot, because it’s delusional to think that 100% of British students will adopt their platform before it gets shut down or labeled as spam website and get lost in Google rankings.

The dynamics of this business model are very simple yet very effective. This start-up relies on crowd-sourcing the filling of the surveys to the users of the platform in a #like4like fashion.

Like4Like is a popular hashtag on Instagram whereby users indicate their willingness to receive likes on their posts in exchange of liking other users posts back (hasthagdictionary.com, 2015). It has the same dynamics as Follow for Follow in Twitter and Sub for Sub (subscribe) in Youtube.

In this case, users of the platform have to create a free account in surveyexchange.co.uk and as the users fill out the questionnaires they will earn “Q points” based on the length of the surveys. The more surveys a user answers, the more Q points it will earn, which can be used later to request more responses for their own surveys.

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The revenue model of the start-up is quite simple, it generates traffic by facilitating a crowd-sourcing platform for students that need to get their surveys filled in and shows them targeted GoogleAds advertisements in its website. In addition, as it can be be inferred from their privacy agreement, the crowd-sourcing platform is also planning to sell premium services and products that will require personal information (Survey Exchange, 2018). Such products and services are likely to be purchased “Q points” so that the users will get their crowd-sourced responses without having to fill out additional surveys.

The beauty of this business model is in its simplicity. Just setting up a platform where its users generate value by crowd-sourcing their own surveys in exchange of an equal amount of commitment. This is therefore a one-way platform where the value of the network grows in a Metcalfe’s law fashion as the number of the users increases.

Metcalfe’s law states that the value of a network is proportional to the square of the users connected to the system (Wikipedia, 2018). This is related to the fact that the number of total possible survey responses ‘n’ (assuming that each user has only 1 bachelor survey) can be calculated by n(n-1), which is asymptotically proportional to n^2.

total amount of responses

If there are 2 users, that means that each user will get 1 response for their survey (you can’t answer your own survey),  totaling 2 responses [2(2-1)=2]. If there are 4 users there will be 12 responses, if there are 8 users there will be 56 responses…

However, there are some limitations with the valuation of this platform. Not all users will be willing to respond to all surveys, and some users may even have more than one survey.

Users are not expected to stay in the platform for any time longer than their thesis/dissertation data collection process and therefore the traffic of the website is not expected to grow in such exponential fashion.

There are also obvious limitations when it comes to the quality of the answers of the survey, both in terms of reliability of the answers and in terms of validity of the sample.

Users that need large amount of responses are likely to give low quality answers without actually reading the questions in order to get as many Q points as possible within the shortest amount of time.

Another concern is that the owner of the survey has 0 control about the type of person that is filling the survey as at this point the platform does not offer the possibility to filter the responses by demographics nor by other type of variable. This could lead to a very heterogeneous convenience sample that may have nothing to do with the actual focal unit of the thesis/dissertation.

Additionally, due to the nature of this platform, users may abuse of the Social Media function, which allows a user to collect Q points via responses from friends, and get the site black-listed from important websites such as Facebook or Reddit because of the amount of unsolicited requests to visit a link.

Despite all those limitations, the crowd-sourced platform seems to be doing fine as the interface of the website has improved overtime and students do not generally care about the quality of their data as long as they can get it quickly and cheap.

At the end of the day, it is better to ask the crowd to fill out your survey in a negligent way rather than faking the responses yourself and risk to get caught of committing fraud.

Let me know in the comment sections what do you think about this business model. Is it sustainable? Do you think they will shut down their website like it happened to survey-x-change.com? Do you think it will get lost in Google’s search rankings due to being labeled as a spam website? Would you use it for your own thesis?

If the answer to the last question is yes, I encourage you to not make a comment 😉

Thank you for reading!

List of References:

Linkedin.com, (2018). [online] Available at: https://www.linkedin.com/in/jakub-zimola-706b01104 [Accessed 16 Feb. 2018].

Survey exchange. (2018). Survey exchange | Exchange your survey and get the right respondents. [online] Available at: http://www.surveyexchange.co.uk/ [Accessed 16 Feb. 2018].

Hashtagdictionary.com. (2018). #like4like | HashTag Dictionary. [online] Available at: http://hashtagdictionary.com/like4like/ [Accessed 16 Feb. 2018].

Surveyexchange.co.uk. (2018). Privacy Policy. [online] Available at: http://www.surveyexchange.co.uk/pdf/Privacy_policy.pdf [Accessed 16 Feb. 2018].

Missed another lecture? Don’t worry StudyDrive has got you covered


One of the biggest trade-offs students are facing in their academic career is going-out vs. going to the lecture. Some students want to join their friends for “just one drink” but somehow end up at Has at 6am and miss the lecture on the following day. On the other hand, there is also the ambitious student who comes to every class, takes notes and spends most of his time at university.

In the end, it doesn’t matter which type one is, as all students come to University to achieve the same outcome, namely, (hopefully) receive a degree at the end of their studies. In order to facilitate this process, StudyDrive has come up with a solution to make a students’ academic career easier.

What is StudyDrive?

StudyDrive is essentially a mediating platform created for students, which enables easy access to study materials. The platform allows students to upload their documents, as well as to access the work of their peers. Whether it is lecture notes, book summaries, past exams, everything can be uploaded and shared. The platform has similar features to Dropbox or WeTransfer, as it allows people to share documents in a fast and convenient way. However, it takes these features and adds a layer on top by organizing the study materials in a convenient way.

How does it work?

As a first step, a student is asked to sign up through either Facebook login or E-Mail address. Once this step is completed the student can select the University he or she is currently enrolled in. Next, the webpage allows the student to choose his area of study and exact program and starting year.

When the student has completed all of the previous steps he should be shown a list of all courses, which he is enrolled in. By clicking on one of the courses, he can access all the study materials and discussions related to this course, which have been uploaded by his (former) peers.

In order to ensure the quality of the uploaded work StudyDrive has created a governance mechanism in which peers assess each other’s work. Students can rate documents and communicate potential mistakes by commenting directly on the document.

However, the start-up has only been founded in April 2013 and heavily relies on network effects, which need to develop over time. This means that the more students join and actively participate the more students’ benefit from it. StudyDrive does not create any content itself. It only provides the structure of the website & app and server capacities for storing the content. This means that the list of courses, study materials, and reviews have to be created by the customers themselves (students).

What are the benefits of participating?

From the perspective of the lazy student missing lectures, the derived benefits are quite clear: Easy access to study materials. But how can StudyDrive motivate the well-organized and ambitious student to share his materials? In order to ensure this StudyDrive made use of an incentive governance mechanism (Blohm et al. 2018). StudyDrive hands out prizes in the form of credit points for students uploading documents, which can be exchanged for prices ranging from posters to iPads. Furthermore, there is a reputation system in place in which students receive karma points for reviewing the work of their peers to further motivate participants (StudyDrive 2018).

Where did StudyDrive originate and how does the company generate revenues?

Philipp Mackeprang, the founder, and CEO of StudyDrive developed the idea after sharing some documents with his former peers at the Maastricht University (Hahn 2014). Originally they used Dropbox to share their files, however, as they uploaded more and more files the site became confusing and difficult to manage. The founder, later on, decided to create his own platform.

One of the major difficulties he was facing was shaping the business model. He realized that students would not want to pay for such a site. However, through his time at University, he realized what great length companies go through to get in touch with students (Hahn 2014). He thus decided to approach potentially interested companies, and it was a success. StudyDrive managed to partner with around 400 companies such as KPMG, Roland Berger or EY. The partnering companies not only advertise themselves on the site but also use it as a recruitment platform by posting job openings or internship possibilities (StudyDrive 2018).

So far, the start-up has managed to offer their partners access to a base of more than 450.000 students, mainly located in Germany, Austria, Switzerland, and the Netherlands. However, StudyDrive is currently expanding to other European countries. The future is looking bright for the company, but how many more students and companies will StudyDrive manage to engage? Only time can tell.

Bibliography:

Blohm, I., Zogaj, S., Bretschneider, U., & Leimeister, J. M. (2018). How to Manage Crowdsourcing Platforms Effectively?. California Management Review, 60(2), 122-149.

Hahn, U 2014, Interview with Philipp Mackeprang of StudyDrive, in, Talkin’Business online magazine, viewed 16 February 2018, <http://www.talkinbusiness.nl/2014/10/interview-with-philipp-mackeprang-of-studydrive-getting-from-entrepreneurial-idea-to-successful-business/&gt;.

Get rewards for your study documents – Studydrive 2018, viewed 16 February 2018, <https://www.studydrive.net/rewards&gt;.

StudyDrive 2018, viewed 16 February 2018, <https://www.studydrive.net/for-companies&gt;.

 

Hip teens do(n’t) wear blue jeans


Did you know that each year, 135 million kilos of clothes are burned in the Netherlands alone? And that producing one regular pair of jeans usually takes up to 7000 liters of water? This makes fashion the second most polluting industry. Shocked yet? So was Bert van Son in 2013 when he founded MudJeans, which is why he decided to offer an alternative to fast fashion after 30 years in the industry. “Sounds nice”, you may think. But how, and more interestingly, at what price?

Take an eternal classic piece present in basically every wardrobe and combine it with two of the most important social trends of the last years – et voilà Bert’s idea. What I’m talking about? Leasable, environmental friendly produced jeans made of a combination of recycled and organic cotton as one of the newest interpretations of the circular economy and general sustainability awareness. Yes, you read right, leasable clothes. If it it works for your car, why not for your bottoms? For a monthly fee of €7,50 (for 12 months) and a one-time only payment of €20 to join the community, you get a pair of brand new jeans, which you can either chose to return after 12 months in exchange for a new pair or keep them until they are worn out and you’re sick of them.

Either way, MudJeans relies on you returning the jeans once you’re done with them – as a little bonus they even offer a €10 voucher (or one free month of leasing) for future use on the website and in their stores. And this even for jeans from other brands, as long as they are made of at least 96% cotton. This way, the company gets to upcycle and renew those jeans that are still in good condition to be reborn as a unique vintage pair, which is even named after its former owner (how cool is that?) and to recycle the less lucky ones to become brand new material for future seasons and models, i.e. the circular economy aspect. Normal return options for wrong sizes/ colors and even a free of charge repair service are also part of the game, and MudJeans even treats you to the shipping charges.

Bildschirmfoto 2018-02-16 um 13.32.55

And what’s in it for you?

A great pair of jeans is like a best friend: reliable, boosting your confidence when it needs uplifting and always has your back (literally). But finding the right one can be tricky (duhh) and once successful, you may discover that the washing machine is not a great match for your young love, or simply that you grow distant after some intense months together. And then?

This is where MudJeans comes into play: instead of hoarding these memories as blasts from the past and letting them rot in your closet, you get to refresh your wardrobe without feeling guilty or even lumbering your closet. And this at a reasonable price. In addition, you basically get to save the world with 78% less water consumption compared to a regular pair of jeans, also due to 60% organic cotton used and 40% recycled jeans material*. Oh, and did I mention that they’re vegan?

Sounds nice, but..

I know what you think. Green fashion? Really? But in this case, green doesn’t have to exclude stylish. On the contrary, the #mudjeans community is full of young, hip individuals caring about the environment and the way they consume – which should include us all. And with their vintage jeans they even offer you the possibility to own a completely unique pair, for example with patches and/ or the destroyed look which you can select after choosing a color and size. For €68. Whilst sustainable fashion used to be unaffordable and/or “basic” to say the least, times have changed. With MudJeans, you have the possibility to contribute to a sustainable way of looking good – at a normal price. Contrary to fast fashion you furthermore know about where your clothes are being produced – and not only in which factory, but who owns it, how it looks inside, how many women they employ and even how many holidays employees get:Bildschirmfoto 2018-02-16 um 15.33.52

And apart from three sites in north Africa, this even takes place in Europe.

Bildschirmfoto 2018-02-16 um 15.08.25

Excerpt from the #mudjeans community

Where can I get it?!

Ok, calm down. I know it’s a great idea – so go on www.mudjeans.eu or visit one of their hundreds stores from Iceland to Melbourne and try it out yourself!

Consumer driven pricing and personalization in the airline industry


There are several ways for companies to distinguish themselves in the way they price their products and services. They can choose for group pricing, which segments customers in groups that tend to behave similarly towards prices. For example, customers can be grouped based on age (such as student discount), gender or living area. Another option is to use versioning: to offer a product line and let customers decide on the trade-off between quality and price. The last form of differential pricing is perceived as difficult to achieve, namely personalized pricing. This means each individual customer receives a personal price for a specific product or service (Schofield, 2018). You may think that, in an offline world, no customer would accept personalized pricing. Can you imagine buying bread and cheese at a grocery store, and the person in front of you pays less for the exact same groceries? However, in an online world, this method has become a lot more feasible. Actually, there is a large chance you have already experienced personalized pricing online. One of the most obvious examples is eBay: one of the first companies to implement personalized pricing with their worldwide market place platform. However, it is important not to interpret personalized pricing as dynamic pricing. The main difference between these two forms of pricing is the variables that determine the final price. In dynamic pricing, the variables that are taken into account are, for example, time of the day, available supply or competitors’ prices (Baird, 2017). Personalized pricing has a customer focus and is interested in a specific customers’ behavior. Companies use data analytics to identify characteristics of the purchase environment or the customer’s profile and behavior that impact their willingness to pay. Bertini and Kounigsberg (2014) argue that the success of personalized pricing depends on at least the following three factors. First, abundant, high-quality data is needed. Also, the companies need to overcome various organizational challenges that come hand in hand with dedication to advanced analytics. Last, companies should be prepared to deal with customers who claim that the pricing approach is not fair.

Airline industry

One of the largest industries that divides consumer groups and price accordingly, is the airline industry. Different fares are charged for the exact same product, based on a market segment’s perceived ability to pay. For example, business travelers tend to pay more for their ticket as compared to leisure travelers, even when they fly the exact same route (Sumers, 2017). The key success is working to learn what the customer needs. Lufthansa, the largest European airline in teams of fleet size and passengers carried in 2017, is testing various approaches to better understand their customers. For example, they have deployed Bluetooth beacons and sensors, to be able to send out real time messages to their customers. When a targeted customer goes through security and has Bluetooth enabled on their phone, the personalization process is started. Or as Lufthansa calls it, the “Big Data Engine”. This program checks a traveler’s mobile boarding pass and looks at how much time the traveler has left before departure. If it is more than a set amount of time, the system examines the traveler’s profile in order to determine whether the customer would be interested in the “Miles and More” program, a discount for access to the airport lounge. This information is combined with the data from the sensors in the lounge, that register whether and how much space is left in the lounge, in real time. This lounge promotion program is part of SMILE., a companywide program that is dedicated to personalizing travel (Lufthansa, 2018). Companies can also use traveler data to offer two or more products or services as a package, increasing profits as it allows companies to appropriate a larger share of customer surplus, known as bundling (Hinterhuber and Liozu, 2014).

Future chances

Although airlines have quite an advanced personalized pricing and recommendation system, there is more potential to be revealed in the future. Lufthansa is working on larger projects that try to develop a Netflix-style algorithm that seeks to guess where its most frequent flyers would like to go to next (Sumers, 2017). The airline then offers a personalized price and ticket to this customer, and further develops its algorithm using customer data. For airlines to stay competitive, they need to keep a close eye on the current and future changes in the market. First of all, airline companies should fully embrace innovation. Data should be used not only to cut costs and to be able to deliver the cheapest flight tickets, but also to facilitate new customer experiences and deliver more personalized services. This leads to an increase in importance of brand loyalty, as consumers are more closely connected to the airline that is best at personalizing their prices and services. Last, the mobile wallet should be seen as the central hub for the digital consumers. Mobile transactions are a lot richer in terms of data collection and analysis, and it provides access to end-consumers, which can drive more sales (Popova, 2016)

 

Sources:

Baird, N. (2017) “Dynamic vs. Personalized Pricing”, https://www.rsrresearch.com/research/dynamic-vs-personalized-pricing, accessed at 13th of February 2018.

Bertini, M. and Koenigsberg, O. (2014) “When Customers Help Set Prices”, MITSloan Management Review, accessed at 14th of February 2018.

Hinterhuber, A. and Liozu, S. (2014) “Is innovation in pricing your next source of competitive advantage?” Elsevier Inc, accessed at 14th of February 2018.

Lufthansa (2018) “Official website”, http://www.lufthansa.com, accessed at 14th of February 2018.

Popova, N. (2016) “Has Personalization of Passenger Experience Entered a Critical Stage?”, https://skift.com/2016/12/29/has-personalization-of-passenger-experience-entered-a-critical-stage/, accessed at 14th of Febuary 2018.

Schofield, T. (2018) “Price discriminations: definition, types, and examples”, https://study.com/academy/lesson/price-discrimination-definition-types-examples.html, accessed at 13th of Febuary 2018.

Sumers, B. (2017) “Airlines Become More Sophisticated With Personalized Offers for Passengers”, https://skift.com/2017/02/03/airlines-become-more-sophisticated-with-personalized-offers-for-passengers/, accessed at 14th of February 2018.

How can I make my 1$ Million contest worth its money?


Innovation tournaments are an important tool of organizations today to tackle important innovation challenges. One of these examples is Netflix, who rewarded $1 million to the winner of their innovation tournament for improved movie recommendations. However, many managers struggle with the question how, and if, to influence the outcomes of these open innovation settings by providing in-process feedback. The study of Wooten & Ulrich (2017) aims to address this managerial challenge by investigating the effects of feedback on the participation and the outcome of innovation tournaments. (Wooten & Ulrich, 2017)

To investigate these effects are six field experiments conducted among two real-life online contest platforms. Each of the six field experiments performs a contest in search for a new company logo, is open to all participants, is unblind (all ideas and feedback are visible to all participants), and allows for multiple entry of participants. In each contest are the participants randomly selected to three different in-process feedback treatments. Consumers received either no feedback, ‘random’ feedback (feedback is not associated to the idea submitted), and direct feedback based on the submission made. The quality of each submitted idea is judged by a panel of consumers that fall within the stated target group. (Wooten & Ulrich, 2017)

One of the results that the researchers found was that contest participation can be boosted with in-process feedback, especially when the feedback is directed. However, the result indicated that this boost was little with respect to engaging new participants and mainly increased the number of entries. This boost in participation can be explained by increased engagement, as participants may feel more connected to the process. (Wooten & Ulrich, 2017)

The other results measured the outcomes of the contests and were evaluated in two ways, either on the quality of the ideas, or the variance in quality among the ideas. In line with Hildebrand, Herrmann & Landwehr (2013) either feedback provided resulted in idea generation that tends to move towards the average, resulting in less variance of quality. In addition, they found that the quality of ideas varied less in their second entry when a first submission was already of high quality. The quality measurement, however, did turned out to be affected by the type of feedback treatment that was used. The directed feedback treatment proved to be beneficial for the next ideas submitted, where random feedback actually resulted in a negative effect for subsequent submissions.  This effect was to be expected as Alexy, Criscuolo & Salter (2011) indicated that signalling information (of which feedback can be seen as such) can ensure that incoming ideas are of higher fit, and therefore might be judged as higher quality. (Wooten & Ulrich, 2017)

The question remains what do these result imply for the management community. As indicated earlier are managers struggling how, and if, to influence their innovation contests. This study provides valuable information to these managers on how they can support their specified targets. For example Alexi et al (2011) identified that some organizations use open innovation mainly to increase engagement, but do not focus on the outcomes of it due to the evaluation costs. This study provides valuable information that feedback increases the participation regardless of the feedback that is provided. This would mean that organizations can invest relatively little in providing feedback, as it can be meaningless, and still boost the participation to the contest. On the other hand this study is showing as well that if an organization is willing to invest time and effort, it can increase the quality of ideas by providing actual directed feedback to the ideas. (Wooten & Ulrich, 2017)

Although these results could be beneficial to organizations, manager should be aware of the weaknesses of this study. One of these weaknesses that this study experiences is that it measures solely the effects of daily feedback, and therefore didn’t incorporate different timeframes. Studies in other fields, such as retargeting adds, identified that customers did turn out to be sensitive to timeframes in which a response was received (Moriguchi et al., 2016). Future research should investigate if this applies in the field of innovation contests as well, but until that point should managers be cautious in choosing their feedback timeframes. Furthermore, the star rating feedback can be seen as a too simplistic method of providing feedback. It provides the advantages that results can be easily compared and that there is no ambiguity in the meaning of the feedback. The generalizability, however, is at stake for more technical contest in which the feedback actually is required to be more in-depth to give a sense of direction. Nevertheless, these weaknesses do not hamper the practical implications but should be used as a note of caution. (Wooten & Ulrich, 2017)

References:

Alexy, O., Criscuolo, P., & Salter, A. (2011). No soliciting: strategies for managing unsolicited innovative ideas. California Management Review, 54(3), 116-139.

Hildebrand, C., Häubl, G., Herrmann, A. and Landwehr, J.R. (2013). When social media can be bad for you: Community feedback stifles consumer creativity and reduces satisfaction with self-designed products. Information Systems Research, 24(1), 14-29.

Moriguchi, Takeshi and Xiong, Guiyang and Luo, Xueming (2016). Retargeting Ads for Shopping Cart Recovery: Evidence from Online Field Experiments.

Wooten, J. O., & Ulrich, K. T. (2017). Idea generation and the role of feedback: Evidence from field experiments with innovation tournaments. Production and Operations Management, 26(1), 80-99.

Image retrieved from:

Markets insider (2017). Netflix lost the biggest Emmy to Hulu  – but its customers couldn’t care less (NFLX), Retrieved fromhttp://markets.businessinsider.com/news/stocks/netflix-stock-price-emmy-2017-lost-to-hulu-but-its-customers-couldnt-care-less-2017-9-1002379405, 15-02-2018.

Philips HealthSuite: Digital Revolution


Healthcare Management Will Never Be The Same
Today people are more connected in more places than ever and we are becoming more active participants in our own health. At the same time healthcare providers are looking for deeper clinical insights and actionable information to make better decisions and improve patient outcomes. A digital revolution in healthcare might take place by the innovative launch of an online healthcare platform initiated by Philips. The Philips HealthSuite is an open platform of service capabilities and tools designed to inspire and enable the development of next generation connected health and wellness innovation. Imagine a mobile app paired with connected health devices that allows people managing diabetes to capture and monitor their diet, glucose, insulin and more, all from their smart phone. The same data can be shared with their healthcare providers so that they 1) get a better insight into the medical conditions 2) get reminders and alerts for medication and testing 3) have a program to support the persons individual treatment plan and 4) a curated social community of others managing diabetes. Unlike other cloud computing platforms, HealthSuite is purpose-build for healthcare. It’s health optimized infrastructure allows seemless integration with existing heath enterprise ecosystems (Philips.nl, 2018).

Philips HealthSuite Business Model
The highly innovative business model is based on connecting multiple stakeholders: pharmaceutical companies, patients and care professionals. Main goal is to establish and strengthen this medical network by digital connected devices from Philips.

  1. Where are the revenues coming from?
    Both pharmaceutical companies, patients and care professionals pay for using the online HealthSuite platform. Moreover, they have to buy the digital connected devices from Philips in order to be connected to the network. This is how Philips will mainly increase its revenue streams.
  2. What value is delivered to which markets?
    Philips’ main goal is to deliver customer value to people who need medical care, e.g. elderly or people with certain diseases. These customers will get more personalized care which they can monitor by themselves and which results in a more efficient treatment. After all, this treatment will be less stressful for patients since they are now able to stay in their own environment at home instead of going to the hospital. Patients thus get more personalized care which is the main value that Philips delivers to them.
    Secondly, Philip’s delivers value to the other side of the healthcare sector, i.e. the healthcare providers. By delivering an online platform and highly innovative infrastructure, it becomes less time-consuming for healthcare providers to monitor and treat their patients. Healthcare providers share their knowledge via the HeathSuite platform and can communicate with patients easier. Healthcare providers thus get more chance on sharing knowledge, provide efficient treatments and could thus increase their positive impact on patients via the digital platform.
  3. What costs are involved in delivering that value?
    Philips has to invest in research and development of digital connected devices and the online platform infrastructure. Another important cost item is the security of customer data which is very vulnerable in healthcare. Philips thus needs to invest in 1) improving the platform and innovating its products and 2) monitoring the data streams in order to protect data leakage.

CaptureFigure 1. HealthSuite Platform Stakeholders (Philips.com, 2018)

Theoretical Point-Of-View
Following Grönroos & Voima (2013), customer value creation depends on product and service interrelationships and product and service bundling. This resource integration-based view implies that customer satisfaction partly depends on its overall goodness of fit (Solomon and Buchanan, 1991). The Philips HealthSuite Platform does connect multiple stakeholders by providing a highly interactive platform where all stakeholders are connected and where both medical devices (products) and medical care (services) are bundled together. For example, a patient can monitor its own treatment at home while doctors can follow his or her results digitally. When needed, doctors can communicate with the patients and can provide them some extra treatments, such as medicines. Doctors will then switch to pharmacists via the platform to connect them with patients. In this case, Philips delivers customer value by interrelating products and services and bundling them together.
Following Karwatzki et al. (2017), individuals’ privacy valuation is a strong inhibitor of information provision in general. Following this line of reasoning, service providers need to align their service designs with consumers’ privacy preferences. Although Philips HealthSuite Business Model might be valuable in terms of revenues and costs, there is an important risk to consider. Medical data in healthcare industry is very sensitive and vulnerable. Patients may feel scared by sharing their personal data on such a highly intensive network. How will Philips elaborate on these dangers?

Capture 2Figure 2. Patient Relationship Management (Philips.com, 2018)

Call-to-action
A digital revolution in healthcare might take place by the innovative launch of an online healthcare platform initiated by Philips. Although this might be beneficial for many different stakeholders and delivers great customer value, we need to consider the ethical and legal dilemma’s of this revolution and protect customer privacy.

Are you curious?
In collaboration with Radbout University, Philips designed a digital application where patients can monitor their own diabetes and are able to share their results with professional doctors and other patients. The following video illustrates a prototype that could help patients with type-1 diabetes. Link to YouTube Video: HealthSuite Philips

Bibliography
Grönroos, C., & Voima, P. (2013). Critical service logic: making sense of value creation and co-creation. Journal of the academy of marketing science, 41(2), 133-150.

Karwatzki, S., Dytynko, O., Trenz, M., & Veit, D. (2017). Beyond the Personalization–Privacy Paradox: Privacy Valuation, Transparency Features, and Service Personalization. Journal Of Management Information Systems, 34(2), 369-400. doi:10.1080/07421222.2017.1334467.

Solomon, M. R., & Buchanan, B. (1991). A role-theoretic approach to product symbolism: mapping a consumption constellation. Journal of Business Research, 22(March), 95–109.

https://www.usa.philips.com/healthcare/innovation/about-health-suite

http://www.smarthealth.nl/trendition/2014/10/13/radboud-en-philips-werken-samen-aan-open-cloud-gebaseerd-zorgplatform/

Author
Daan Verpalen, Student MSc. Business Information Management, Erasmus University, Rotterdam School of Management, 2018 (studentnumber: 374199)

The world is your (peer)space


Want to throw an awesome party or work in a creative environment? But you cannot find the perfect space? Today, we live in a world where you can easily rent out your house, car or offer your skill set to others in exchange for a fee. So, why can’t you rent out your office space? Look no further. The app Peerspace will help you find your perfect space!

Tell me more

Peerspace, launched in 2014 and founded by Rony Chammas and Matt Bendett, is an online peer-to-peer marketplace that connects individuals and businesses to find one-of-a-kind spaces that otherwise go unused (Peerspace, 2018). The idea emerged when Rony was a student at NYU trying to find meeting places, and saw how much open and underutilized space there was (Bercovici, 2014). Finding spaces with benefits for both parties mostly happen through word-of-mouth or platforms as Craigslist, which is inefficient. Therefore, Peerspace’s mission is to find and book short-term space through an easy and transparent process (Peerspace, 2018). Whether looking for personal or professional space, Peerspace is the solution for finding unique locations for meet-ups, pop-ups, and classes to off-sites or brainstorming sessions. Currently, Peerspace is available in the USA and the start-up has raised 18 million dollars from funders (Magistretti, 2017). The popularity of the platform goes not unnoticed as 60,000 people from world-class companies (Google, Vice) attend a Peerspace booking every month (Peerspace, 2018).

 

Continue reading The world is your (peer)space

GE crowdsourcing platform – Let’s set the collective brain on fire!


We live in a fast-paced digital world and it can be challenging for companies to keep up with the speed of today’s ever changing digital era. However, new information technologies have also empowered more technologically savvy businesses by giving them new means to operate, promote their products and services, and engage with customers. One company that is constantly taking advantage of these new tools is General Electric (GE), an enterprise who has succeeded in part because of its willingness to take risks and embrace innovative technologies. The most recent example of this mindset is Fuse, their new open innovation platform that launched in late 2016. It is basically an open crowdsourcing platform, which allows users from all around the world to collaborate with each other and work with GE engineers to solve meaningful technical challenges.

How does Fuse work?

The first step is for the Fuse team to translate GE customers’ needs and “pain points” into projects on the Fuse platform. Whereas most projects are straightforward and thus directly released in the form of challenges, some appear to be less clear and hence are uploaded on the “Brainstorming Section” of the Fuse platform as “potential challenges”. These potential challenges include a (rather extensive) description of the problem to be tackled as well as precise requirements for the solution, and contributors are asked (1) whether they would be interested in such a challenge, and (2) what additional questions the Fuse team should answer before launching the challenge. Based on the feedback received, the Fuse team might decide on further actions. When released, each individual challenge comes with a description of the problem, clear requirements for solution submissions, judging criteria, a timeline, a description of the prizes for the winners, and the official rules of the competition (including property right issues).

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Example of a Fuse challenge

In a second step, contributors from all around the world are invited to submit innovative contributions. Note that even though anyone can sign up and take part in challenges, the very technical nature of the challenges serves as a skills-based filtering mechanism as only people with a certain degree of knowledge in engineering would be able to understand the challenges. Once on the Fuse platform, anyone can have access to all the relevant information related to the challenges, however only registered users are allowed to submit entries. During the whole duration of the challenge, contributors can use the discussion board to brainstorm together or ask the competition holders questions. Not only does the Fuse team rapidly answer these questions and provide regular feedback/input, but they also organize “live Q&A sessions”, during which the participants can submit questions that are answered live in a video feed.

 The final step is for the Fuse team to evaluate the submissions, select the winners (generally the three best entries) and allocate the money prizes. The interesting entries are also forwarded to GE’s technical team, where they are further developed into implementable solutions.

Efficiency Criteria

In less than two years, GE succeeded in creating an innovative community and successful products from their contributions (Picklett, 2017). This was made possible for the following reasons: combination of extrinsic and intrinsic incentives, good management, and well-structured governance including the mechanisms recommended by Blohm et al. (2018).

From a contributor’s perspective, the Fuse platform and its challenges are interesting not only because of the cash prizes, but also because it is designed towards building long-term relationships with its contributors. For instance, competition winners actually have an opportunity to further work with GE engineers on implementing their designs (Kloberdanz, 2017). In addition, there is also an attractive physical part to Fuse projects, which consists in a micro-factory in Chicago designed for rapid prototyping, small-batch manufacturing, and modular experimentation (Davis, 2017). This faculty will be open to contributors and can constitute an incentive for them to become part of the Fuse community as it is a good opportunity to bring their ideas to life, work with GE professionals, and meet like-minded innovators. Finally, the Fuse challenges are also a good opportunity for contributors to collaborate with other brilliant mind, expand their business network, build their professional reputation, and gain recognition from their peers.

From GE’s perspective, the Fuse platform is a new source of innovative and ideas, which can speed up content creation, cut R&D costs for the company, and provide GE with an opportunity to spot talents who might be valuable additions to their team. But how is GE able to overcome the challenges inherent to crowdsourcing (e.g. huge quantity, low quality, free-riding behaviour, risks of sharing information)? First, due to the technical nature of the Fuse challenges, the clearly defined guidelines provided to the participants, and the rapid feedback/additional inputs provided during the competition, GE ensures that only a manageable number entries of a certain quality are submitted, thus facilitating the evaluation process. The platform is also clear about the transfer of PI rights, which avoids troubles along the way. Second, for most challenges, challenge, entries are private and only viewable by the creator, admins, and judging panel. As a result, GE is able to avoid free-riding behaviours. However, contributors are still able to communicate with (and help) each-other via the discussion board, and the Fuse team makes sure to encourage the discussion with feedback and additional information, hence allowing contributors to still learn from each other. Finally, even though opening up GE’s internal workings/information of some products in order to run these challenges can be risky, the company acknowledges that “there are certain risks you just have to roll with if you want to make progress and that willingness to take those risks is what makes this exciting.” (Davis, 2017). This quotes shows that GE understands the need to willingly take risks in order to continuously transform the company and, so far, Fuse seems to be worth it as GE reunited more than 8000 contributor successfully implemented several ideas generated by the platform in less than a year (Davis, 2017).

In summary, the joint profitability criterion is met as the Fuse platform creates value for both GE and its contributors. Furthermore, the costs linked to this innovative business model are relatively low as the Fuse team only consists of 4 employees based in Chicago (Pickett, 2017). However, as the platform matures, hosts more challenges, and attracts more contributors one can assume that the number of employees will have to increase. Still, the costs-benefits ratio should remain interesting compared to doing everything in-house. Finally, the legal concerns are taken care of thanks to inclusion of PI agreements in the official rules of the Fuse challenges, and the social norm dimension is met as GE is a well-known, reputable brand, hence building trust with contributors.

References

Blohm, I., Zogaj, S., Bretschneider, U., & Leimeister, J. M. (2018). How to Manage Crowdsourcing Platforms Effectively?. California Management Review, 60(2), 122-149.

Davis, B. (2017). How GE is using co-creation as part of its digital transformation. Retrieved from https://econsultancy.com/blog/68902-how-ge-is-using-co-creation-as-part-of-its-digital-transformation

Fuse. (2018). Fuse Platform. Retrieved from https://www.fuse.ge.com

Kloberdanz, K. (2017). Working The Crowd: This Fuse Will Set The Collective Brain On Fire. Retrieved from: https://www.ge.com/reports/working-crowd-fuse-will-set-collective-brain-fire/

Pickett, L. (2017). GE Fuse’s open innovation platform invites NDT professionals to co-create solutions. Retrieved from https://www.qualitymag.com/articles/94304-ge-fuses-open-innovation-platform-invites-ndt-professionals-to-co-create-solutions

Share products you love


Imagine it’s July 2017 and you’re a freshly graduated BIM student. Together with a friend you decide to start your own company and sell your own products. You have some great ideas and great plans! Everything is elaborated in your business plan and you are ready to enter the market. But how are you going to reach your customer? Making use of social media would make sense, since almost 10 million people in the Netherlands visited Facebook (marketingfacts, 2017). How can you use these social media platforms in the most effective way? This is where Sellify comes along!

Sellify. What is it? Continue reading Share products you love

To Keep Or Not To Keep: Effects of Online Customer Reviews on Product Returns


By Madeleine van Spaendonck (365543ms)

In the US, the current average return rate for products bought online is approximately around 30% of purchases (The Economist, 2013). Most returns take place due to customers’ negative post-purchase product evaluation rather than product defects. One factor that is found to have an impact on this is the role of Online Consumer Reviews.

This is what Minnema et al. (2016) investigated in their study “To Keep or Not to Keep: Effects of Online Customer Reviews on Product Returns”. It uses a multi-year (2011-2013) dataset from a European online retailer that offers both electronics and furniture products. The paper examines the impact of three OCR characteristics (valence, volume and variance) on return decisions (figure 1). The researchers evaluate the net effect of OCRs, looking at its influence on both purchase and return decisions.

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Theory

The hypotheses examined are based on the ‘expectation disconfirmation mechanism’. Post-purchase satisfaction results from the combination of customer expectations formed at the purchase-moment, product performance, and the difference between them. Negative expectation disconfirmation therefore decreases satisfaction, leading to a higher return probability. Therefore, higher expectation levels should lead to higher purchase and return probabilities, while higher expectation uncertainty should lower these.

Main results

Figure 2 presents a summary of the results of the study.

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A particularly counterintuitive insight is that overly positive review valence (whereby the current OCR valence is higher than the long-term product average) leads to not only more sales but also a higher return probability. A potential reason for this is that OCRs induce the customer to form product expectations at the moment of purchase, leading to higher purchase probability. However, high expectations due to overly positive reviews may not be met. This leads to negative expectation confirmation, which then leads to higher return probability. Review volume and variance mostly affect purchase decisions, having little to no effect on product returns.

Strengths, Weaknesses and Suggested Improvements

While the majority of scholarly work in this field focuses on OCRs effects on product sales, this paper also addresses the lack of understanding of its effects on product returns. Taking into account both aspects is vital, because the prediction of OCR effects on retailer performance may be overly optimistic or pessimistic if only its effects on sales are considered. The study also shows that OCR effects advance beyond the moment of purchase and have the power to affect the decision to return a product. However, the model did not incorporate other information sources available at the purchase-moment that affect return-likelihood, such as product descriptions and pictures provided by the retailer. A comparative analysis could be used to evaluate whether reviews or retailer-provided information have the strongest impact on returns.

Managerial Implications

The study highlights the importance of considering product returns when evaluating OCR effects, as overly positive reviews may have negative consequences for retailers’ financial performance. Overly positive reviews, leading to more product returns, result in large reverse logistics costs. To reduce negative expectation disconfirmation, retailers should provide information and tools (besides OCRs) that allow consumers to set the right expectations and see if the product really meets their needs.

Sources:

Minnema, A., Bijmolt, T.H.A., Gensler, S., Wiesel, T. (2016). “To Keep or Not to Keep: Effects of Online Customer Reviews on Product Returns.” Journal of Retailing, 92(3), pp. 253–267.

The Economist. (2013). Return to Santa. December 21, (latest accessed March 8, 2017), http://www.economist.com/news/business/21591874-e- commerce-firms-have-hard-core-costly-impossible-please-customers- return-santa

Source for cover photo:

Ministry Ideaz, (2016), How do I return a product I no longer want? [ONLINE]. Available at: http://support.ministryideaz.com/customer/portal/articles/1022650-how-do-i-return-a-product-i-no-longer-want- [Accessed 8 March 2017].

Culture, Conformity and Emotional Suppression in Online Reviews


Paper: “Culture, Conformity and Emotional Suppression in Online Reviews” by Hong et al., 2016

“While Americans say, “the squeaky wheel gets the grease,” the Japanese say, “the nail that stands out gets pounded down.”

In other words, in the States, people who complain the loudest get the most attention while in Japan, people are discouraged to express personal opinions loudly especially if they don’t fit the community expectations. This phenomenon illustrates the differences between individualist (American) and collectivist (Japanese) cultures as defined by Hofstede (2001) and House et al. (2004). But this post is not entirely about cultural differences – it is about their influence on online reviews. Continue reading Culture, Conformity and Emotional Suppression in Online Reviews

Why users contribute knowledge to online communities: An empirical study of an online social Q&A community


Knowledge & the Internet

Ever since the inception of the Internet, the volume of knowledge has exceptionally increased, especially since it improve-knowledge-managementfacilitates crowdsourcing knowledge. Websites such as Wikipedia and Quora help individuals provide other individuals with information and answers to lingering questions. Quality control is also crowd controlled, where different kinds of voting systems enable fellow users to assess the provided answers and filtering out low-quality ones. Online Q&A communities are special social networks focused specifically on information sharing. They are a special place since there is usually no monetary incentive to motivate people to contribute. This paper focusses on these online communities and tries to explain the motivation behind the contributors.

Related Theory

There are 3 theories that are related to this study and on which the hypotheses are built, they are social cognitive theory, social capital & social exchange theory. The Social cognitive theory claims that that people’s thinking and actions are influenced by watching others through social interactions (Anderson, Winett, & Wojcik, 2007). The theory has been used to analyze how content is generated by users and how this content affects future contributions. Social capital is a known concept describing the value derived from interpersonal relationships and is built over time. It includes trust, respect & friendship among other things (M.M., 2005). The social exchange theory highlights intrinsic rewards from social interactions, similar to economic exchange theory it claims that individuals will behave in a certain way to acquire rewards from an interaction (Liu & Chen, 2005).

What is measured and how?

Based on the previously mentioned theories/concepts 4 aspects were identified that are possible drivers of knowledge contribution in online Q&A communities.

Identity Communication

Identity communication refers to an identityindividual’s efforts to express and present his/her identity. It explains who a person is and how he/she is different from others. It includes the concept of self-presentation information; the transfer of personal information about one’s personality, experience etc. so others understand their social identity (Tajfel & Turner, 1979). In the study, it is measured as a number of items that a user discloses about himself with a maximum of 11 (maximum of items available on the website).

H1: Individuals who disclose more self-presentation information will contribute more knowledge to online social Q&A communities.

Peer Recognition

The more knowledge becomes available the more attention is divided between different sources of information. The same goes for the information in online Q&A communities. Peer recognition is the positive feedback users receive on their behavior and is measured by the number of usefulness votes on a post.

H2: Individuals who receive more positive feedback will contribute more knowledge to online social Q&A communities.

Group-size Effects

Since most intrinsic rewards are based on transactions with others, as explained before, the presence of others and the number of possible recipients are important. A larger following means a wider reach and thus more social rewards (Nahapiet & Ghoshal, 1998). A member’s following is measures by the member’s so-called ‘followers’.

H3: Individuals with a larger group size will contribute more knowledge to online social Q&A communities.

Social Learning

Social learning is a type of learning that comes from observation of others. In online communities content feeds provide constant updates of other individuals actions, providing continuous learning opportunities (Anderson, Winett, & Wojcik, 2007). Social learning is measured by the number of topics, questions and members a participant is subscribed to, the more they are subscribed to the more learning opportunities a member has.

H4: Individuals with more social learning opportunities will contribute more knowledge to online social Q&A communities

Results

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The researchers have analyzed 1.762 data points from 306 members of a popular online Chinese Q&A community. These data points include all knowledge contribution behavior from March 15 to June 22, 2014. After processing the data H1, H2 & H4 are supported and H3 is rejected.

Why is this important?

The internet is a great tool to share knowledge, people from all over the world can distribute information to others. This can help people with a more difficult start in life acquire knowledge to help them further. Understanding why people contribute to online knowledge sharing can help increase knowledge that is available online.

References

Anderson, E., Winett, R., & Wojcik, J. (2007). Self-regulation, self-efficacy, outcome expectations, and social support: Social cognitive theory and nutrition behavior. Annals Of Behavioral Medicine34(3), 304-312. http://dx.doi.org/10.1007/bf02874555

Anderson, E., Winett, R., & Wojcik, J. (2007). Self-regulation, self-efficacy, outcome expectations, and social support: Social cognitive theory and nutrition behavior. Annals Of Behavioral Medicine34(3), 304-312. http://dx.doi.org/10.1007/bf02874555

Jin, J., Li, Y., Zhong, X., & Zhai, L. (2015). Why users contribute knowledge to online communities: An empirical study of an online social Q&A community. Information & Management52(7), 840-849. http://dx.doi.org/10.1016/j.im.2015.07.005

Liu, C. & Chen, S. (2005). Determinants of knowledge sharing of e-learners. International Journal Of Innovation And Learning2(4), 434. http://dx.doi.org/10.1504/ijil.2005.006665

M.M., W. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly: Management Information Systems29(1), 35-57.

Nahapiet, J. & Ghoshal, S. (1998). Social Capital, Intellectual Capital, and the Organizational Advantage. The Academy Of Management Review23(2), 242. http://dx.doi.org/10.2307/259373

What’s your recommended size?


Shopping online is more convenient, however it becomes tricky when shopping for clothes as we’re not able to try the clothes on. Hence, we purchase items in the size we think fits us best. This, unfortunately, may not always work in our favour. Often, we receive an item that doesn’t fit us well. We then either return it, store it at the back of our closets hoping one day it will fit, or give it to a friend. Essentially, a waste of time and money.

ASOS, a large online fashion retailer, just launched a new recommendation tool that helps solve this problem for their shoppers.

What is it?

The new tool provides customers with a personalized recommendation of a size it thinks will fit them best. It suggests a size based on customers’ past purchases and returns. Here’s how it works (Cherrington 2017):

  1. A recommended size instantly appears when the customer views an item.1
  2. Clicking the link shows the customer what the recommendation is based on.2
  3. Customers also have the option to provide input to improve recommendation accuracy by: (1) selecting which past purchases didn’t fit, (2) adding height, weight, age, and desired fit type (very tight to very loose), (3) selecting tummy shape, hip shape and bra size.

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If a customer is new, they can add in their height and weight and discover which size similar customers purchased and did not return.

ASOS has received a backlash for introducing this new tool. Some women have taken to Twitter to vent their frustrations that the tool is insulting and inaccurate. (Cherrington 2017)

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Others have responded more positively to the new tool, as customers no longer have to guess which size would fit and it saves the time and effort that would have been spent on returns and exchanges. It not only provides a personalized recommendation to customers, but it also includes the input of customers to produce better results, making customers feel like they are part of the creation process.

ASOS’ business model is to provide their customers with engaging content and experiences, great fashion at a great price and excellent service through an “effortless online and mobile shopping experience”. (ASOS 2017) More than just a fashion retailer, ASOS prides itself as a technology company – constantly innovating to improve service and customer experience. This new recommendation tool is a strong reflection of their business model and values.

Efficiency Criteria

The joint profitability criteria is met as this recommendation tool improves the joint value for both ASOS and its customers. While some customers are currently unhappy with this new tool, once ASOS improves the system to deliver more accurate recommendations, customers are likely to appreciate the tool more. It saves them from spending money on clothes that don’t fit and will increase customer satisfaction.

The investment cost of this new recommendation tool is low as the company only needs to improve the recommendation system based on feedback. The company also benefits from the increased customer satisfaction and sales from customers that previously abandoned their shopping cart due to size concerns.

The feasibility of the required allocations is also met. The polity and judiciary dimensions of the institutional environment do not relate directly, however the social norms dimension is met as ASOS has a strong reputable brand,  thus creating trust with customers.

References

ASOS 2017, ASOS Story, ASOS Plc, viewed 9 March 2017, <https://www.asosplc.com/asos-story&gt;.

Cherrington, R 2017, ‘ASOS Is Guessing What Size Its Customers Are, And They’re Not Happy About It’, The Huffington Post, 24 January, viewed 9 March 2017, <http://www.huffingtonpost.co.uk/entry/asos-size-recommendation_uk_58871c69e4b02085409924c3&gt;.

 

 

 

How Brand’s User Base Visibility in Social Media Platforms Effect Consumer’s Brand Evaluation


Social media is a widely used channel for companies to connect with consumers. Approximately 83% of Fortune 500 companies have used some form of social media by 2011 (Naylor et al., 2012), which have increased even more by now. Many consumers use these social media platforms to get deeper knowledge about a brand and who affiliates with it. This is useful because consumers reaction to a brand may be affected if they know who other users are (Bearden, Netemeyer, and Teel, 1989; Berger and Heath, 2007). Via these platforms, consumers have the possibility to see other people who affiliated with the brand. This passive exposure to a brand’s supporters is identified as ‘mere virtual presence’ (MVP). This research tries to answer what the effect are of the different types of MVP on brand evaluation and purchase intentions, as there is still little know about the subject.

Consumers find more affinity with a certain brand if they see that similar others support the brand (Berger and Heath, 2007; Escales and Bettman, 2003). Because of this, it is expected that individuals who deal with similar MVP with the brand’s user base will experience high levels of inferred commonality. Therefore, they positively evaluate the brand. On the contrary, if the consumer experience a dissimilar MVP, they will evaluate the brand downwards. Another research suggests that when there is no information available about others, consumers anchor on the self and assume that those others are like them (Naylor, Lamberton, and Norton, 2011). Thus, probably a more safe decision is not displaying pictures of others at all, which is called ambiguous MVP. This ambiguous MVP results in that consumers will project their own characteristics on the brand’s user base, hence higher affinity with the brand. However, a brand’s user base cannot be completely similar to a consumer and is more heterogeneous. Therefore, the last form of MVP this research investigate is that consumers evaluate a brand more positively if they are confronted with a small proportion of similar individuals in a large heterogeneous group.

Findings from this study have the following implications for positive brand evaluations: (1) If the brand’s user base is homogeneous and similar to the target audience, reveal their identity. (2) Second, if the brand’s user base is heterogeneous, but includes users who are similar to the target audience, also reveal their identity. (3) However, maintain ambiguous MVP if the brand’s user base is dissimilar from the target audience. This will result in that consumers evaluate the brand the same as in the similar MVP context. (4) Lastly, results indicate that when brands are jointly evaluated with other brands similar MVP yields better performance than ambiguous MVP. This positive brand evaluation consequently results in higher purchase intentions.

This study contributes to the literature how firms can best manage their social networks in meeting strategic objectives and enhance their brand evaluation. Moreover, this research help to guide brand managers when it is useful to reveal the identity of their online supporters or to remain an ambiguous MVP. Thus, managers are informed which social media platform they should choose because some control over specific fan base is necessary (similar consumers in heterogeneous population). These results are furthermore most useful for new brands to establish a larger supporter’s base. And to manipulate MVP and find similar consumers, firms can target consumers based on demographics. For example, Facebook displays advertisements mostly to certain demographic groups, thus emerging tracking and targeting tools can be used to do this.  Because of this tracking marketers know where their new supporters came from so that they can adjust their MVP and target consumers that fit this demographic profile. This will help brand managers to decide whether to display the brand’s user base or remain ambiguous.

MVP

Bearden, W.O., Netemeyer, R.G. and Teel, J.E. (1989) ‘Measurement of Consumer Susceptibility to Interpersonal Influence’, Journal of Consumer Research, 15: pp. 473-481.

Berger, J. and Heath, C. (2007) ‘Where Consumers Diverge from Others: Identity Signalling and Product Domains’, Journal of Personality and Social Psychology, 95: pp. 593-607.

Escales, J.E. and Bettman, J.R. (2003) ‘You Are What They Eat: The Influence of Reference Groups on Consumers’ Connection to Brands’, Journal of Consumer Psychology, 13, 3: pp. 339-348.

Naylor, R.W., Lamberton, C.P. and Norton, D.A. (2011) ‘Seeing Ourselves in Others: Reviewer Ambiguity, Egocentric Anchoring, and Persuasion’, Journal of Marketing Research, 48, 6: pp. 617-631.

Naylor, R.W. Lamberton, C.P. and Norton, D.A. (2012) ‘Beyond the “Like” Button: The Impact of Mere Virtual Presence on Brand Evaluations and Purchase Intentions in Social Media Settings’, Journal of Marketing, 76, 11: pp. 105-120.

 

Making an internet celebrity-the economy behind it


For most of us, Instagram is not only a way to share and post filtered photos of important subjects of our life like Sushi ate for dinner, friends’ cute cats and dogs as well as selfies, but also a procrastination tool to enjoy the eye candies from internet celebrities, i.e. posted pictures, meanwhile some are making real cash out of their influential photos. In case you are curious on how to make money like an internet celebrity, hope the following tutorial can help and it all comes down to a combination of product placement, endorsement and followers who gradually become consumers as well, since they are the target market of the internet celebrities they follow.

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Law 1: Instagram Endorsement

According to Forbes Magazine, Kylie Jenner who ranks the second on 2016’s Top-Earning’s Reality Stars list, earned $18million in 2016 (Robehmed, 2016). Among which, nearly 20% of the income came from endorsements on social media for promoting other brands’ products. She shilled for at least eight different brands through her Instagram page. It is said to have your product shown on her Instagram, each picture charges at least $300,000 (Lester, 2016), due to the fact that these internet celebrities have considerable audience to broadcast to and easily gather at least one million “likes” on Instagram. The actual advertising effect is also surprising. The year before a noteless make-up brand (Nip Fab) reached out to Kylie Jenner with a hefty bonus. Now that brand is gaining its popularity with a boost from her Instagram endorsement, the market value of the company has reached $100 million (Lankston,2015).

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Another example is from Selene Gomez who sits on 110 million followers on Instagram. Last year she broke a record of asking $500,000 for an endorsing photo from Coca-Cola. The picture is such a huge success that harvest of 6.5 million “likes” on Instagram immediately, which became the most “liked” Instagram in history.Screen Shot 2017-03-10 at 17.55.06

Law 2: Dress with product placement

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Kendall Jenner, sister of Kylie Jenner, who also attracts almost 76 million followers on Instagram, was spotted wearing a certain brand clothes for a long time when appearing in front of paparazzi or casually shot off pictures with the brand’s clothes on and posted on Instagram. While she was paid to by this newly set-up, yet no-fame Australian brand. Most importantly, sales revenue of the brand rocketed thanks to her implied efforts. Consequently, by partnering with Instagram influencers that have thousands or even millions of followers, brands can reach loads of consumers with a single post. Nowadays, many marketing agencies have turned to devote to pairing Instagram accounts that have sizable followers with companies looking for advertising or exposure aiming for certain target market.

Law 3: Establish own brand

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Seeing their promotion of other products sales went so well, Jenner sisters rushed to develop their own clothing line, but this brand is quite controversial. Followers who bought complained that regardless of style, the material or cutting are inferior, nevertheless the retailer prices are not cheap.

The economy behind it

Concerns are often raised whether buying products that recommended by internet celebrities is trustworthy or not as products that internet celebrities promoting are not supervised by any regulation as long as they are complied with law. Moreover, they do not have clear responsibilities for consumers who made purchases as a result of their product placement post. Nevertheless, these influencers still make certain impacts on their followers to help either brand build their business or discover their own selling opportunities.

Given the fact that internet star’s every move comes with commercial incentives driven by huge business interests, it is up to followers to identify contexts and contents on Instagram at the moment. Interestingly, followers are willing to invest their time and attention in the absence of interaction with the influencers, as Bateman et. al (2011) discovered that continuance community commitment (i.e. followers have adopted the habit to check on their following influencers’ posts) and affective community commitment (i.e. followers find intangible rewards as browsing pictures are enjoyable) were the form of commitment that have stronger impact on participants’ reply-posting behavior except that normative community commitment in the context of Instagram does not make every participant obligated to post pictures. Therefore the last piece of advise to become Instagram celebrity is to keep followers come back for more and new content of pictures and to sum up, as the internet celebrities mentioned above, they have leaned to what their audience is asking for and show them what they want, and they will become loyal.

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Reference:

Bateman, P. J., Gray, P. H., & Butler, B. S. (2011). The Impact of Community Commitment on Participation in Online Communities. Information Systems Research, 22(4), 841-854.

Instagram.com

Robehmed, N. (2016). Kylie Jenner’s Earnings: $18 Million In 2016.Available: https://www.forbes.com/sites/natalierobehmed/2016/11/16/kylie-jenners-earnings-18-million-in-2016/#581c6646303a. Last accessed 8th March 2017.

Lester, T. (2016). T The industry that has erupted within the modeling industry. Available: http://www.crfashionbook.com/book/it-pays-to-be-social/. Last accessed 8th March 2017.

Lankston, C. (2015). ‘Using Kylie in a campaign was risky, but it paid off’: Beauty guru reveals how celebrity fans like Kylie Jenner and Elle Macpherson helped her to build a $100 MILLION brand. Available: http://www.dailymail.co.uk/femail/article-3284503/It-s-secret-ingredients-Skincare-expert-loved-likes-Kylie-Jenner-Elle-Macpherson-reveals-secrets-100-MILLION-beauty-business.html. Last accessed 8th March 2017.

Morrison, L. (2015). How Do Instagram Stars Make Money? Here’s What Goes On Behind All The Valencia. Available: https://www.bustle.com/articles/127110-how-do-instagram-stars-make-money-heres-what-goes-on-behind-all-the-valencia. Last accessed 8th March 2017.