Anxiety and Ephemeral Social Media Use in Negative eWOM Creation


Introduction

You have probably, at one time or another, found yourself in a situation where your favorite sports team just undeservedly lost a game and the sadness and anger you felt at that loss was overwhelming you. In the past, you might have vented those emotions in the living room, aiming your fiery rant at your friends or unsuspecting spouse. Nowadays, when consumers encounter “negative brand experiences” such as the loss of their favorite sports team, they respond with coping behavior (Duhacheck 2005) on social media, such as creating electronic word-of-mouth (eWOM) to complain (Stephens and Gwinner 1998) or to gain social support for their sentiments (Hennig-Thurau et al. 2004).

Article 

However, posting such eWOM causes stress and anxiety because individuals realize that their online content will be scrutinized by others (Krämer and Winter 2008). This may be reinforced when the message is negative, as this conflicts with an individual’s online impression management goals, namely achieving positive self-presentation (Berger 2014). Wakefield and Wakefield (2018) study this phenomenon in combination with the use of ephemeral social media. They apply the S-O-R theory (Mehrabian and Russel 1974), which states that stimuli (S) may alter consumers’ organismic state (O) leading to a response (R). In their research set-up,  brand experience is defined as the stimulus which alters consumers’ disposition in the form of message negativity and task anxiety, leading to a certain response depicted as message availability.

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Fig. 1 The S-O-R- theory as applied by Wakefield & Wakefield (2018)

It could be argued that the conflict between expressing negative brand experiences and self-presentation would lead to consumers attempting to avoid consequences of negative messages by reframing them more positively, using humor or staying silent. However, individuals facing an emotional experience appear to need to share it (Pennebaker, Zech, and Rimé 2001) even under social constraints (Pennebaker 1993). Therefore, the authors posit:

H1: Negative brand experiences will result in greater anxiety when creating eWOM compared to positive brand experiences

This leads to coping behavior in which the individual attempts to minimize the anxiety and stress caused by their negative expression, which is where ephemeral social media come in. Ephemerality facilitates coping with the conflict related to managing impressions through the limiting of message availability. This can, for instance, offer the perception of a smaller audience size (Ellison et al. 2011) or eliminate concern for the content’s future exposure. Based on this, the authors further hypothesize:

H2: The greater the negativity in a message, the shorter the message availability

H3: The greater the task anxiety, the shorter the message availability

The first study is conducted on a sample of 164 U.S. participants recruited through Amazon’s Mechanical Turk service. This sample is asked to create eWOM in a sports team setting similar to the one described in the introduction. The results provide preliminary support for the three hypotheses.

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Fig. 2 Relationship results from Study 1

However, in order to ensure generalizability, the experiment is replicated in a second study containing six other brand categories. Furthermore, post-task anxiety is now measured to see if setting a time limitation on negative eWOM will decrease anxiety. Additionally, the authors attempt to provide support for the impression management goals as a source of conflict, assuming that the greater the message availability, the more positive words for self-presentation purposes are used. Finally, the difference between objective economic brand experiences and subjective non-economic brand experiences is explored by having three search goods (clothing, automobiles, and restaurants) and three experience goods (banks, insurance and hotels) as brand categories. This leads to the addition of four new hypotheses to the first three:

H4. Post-task anxiety will be less than task anxiety         

H5. The greater the message availability, the greater the self-presentation.

H6a. Message availability for economic brand experiences will be greater than non-economic brand experiences as negativity increases.

H6b. Message availability for economic brand experiences will be greater than non-economic brand experiences as anxiety increases.

 

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Fig. 3 Task & post-task anxiety by message availability

The results from the second study replicate the findings of the first study with respect to H1-H3, thus demonstrating the generalizability of these relationships. Furthermore H4 is supported as anxiety decreased after restricting message availability, the effect being strongest for those who felt significantly greater anxiety during eWOM creation (fig. 3).

 

 

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Fig. 4 Message availability by message negativity

The same goes for H5, lending credence to impression management as an underlying concern. H6a is rejected, but H6b supported, indicating that consumers do differ in their restriction of message availability according to experience type (economic vs non-economic) with respect to the message negativity, but not with respect to task anxiety (fig.4).

 

Managerial implications

This study provides interesting implications for brand marketers interested in why and how eWOM can be constrained. To start with webcare management, this study suggests that a reactive strategy to negative eWOM may not be the optimal one. Although other research such as that of Proserpio and Zervas (2017) posits that management responses to negative feedback leads to less negative feedback, in the light of this study, management response would extend the availability of the message and prolong the incident for the consumer, discouraging the consumer to share his/her brand experience in the future. A better alternative is to address the anxious and negative consumers privately and/or offline, wherein ideally the consumer decides to share the resolution online of their own accord.

Furthermore, brand managers should realize that dependent on the type of good they work with, they should interpret online sentiment differently. For instance, brand managers of non-economic goods should be aware that negative online sentiment with respect to their goods is available for a shorter time and diluted with positive words and that consumers’ experiences could thus well be much worse than stated online.

Most importantly, the trade-off between impression management and negative eWOM creation is removed, or at least mitigated, when the consumer controls message availability. This means that a firm can solicit negative feedback through ephemeral social media in a win-win scenario where the company gets to improve their service/product whilst suffering the least possible amount of negative publicity and reducing their customer’s anxiety levels.

 

Strength & Weaknesses

A notable weakness of the article lies in the sample respondents, which were U.S. participants (n = 164) recruited through Amazon’s Mechanical Turk. Crowdsourcing respondents through MT has become a popular and easy way to find respondents, however there are several limitations to this method. Firstly, character misrepresentation may occur, as respondents have an incentive to falsify identity, ownership and activity information in order to qualify for a study (Wessling et al. 2017). Secondly, crowd-sourced respondents cannot be scrutinized and could thus be multi-tasking, or be interrupted, during the study. Furthermore, they self-select into studies and can quit at any time, thus MT workers may not provide reliable data or be particularly representative of the real-world consumers. Finally, the validity of data obtained from participants who have accumulated experience with social studies is questionable (Goodman & Paolacci 2017).

However, it must be noted that these are recent findings and that 43% of consumer research studies use MT workers as respondents (Goodman & Paolacci 2017). Moreover, the use of college students as study respondents has been critiqued for years before that, and these still seem to be seen as a viable respondent source.

The main strength of this article lies in its exploration of new drivers of eWOM characteristics, namely anxiety during creation and the enablement of limitations to message availability.  Furthermore, the authors immediately ascertained generalizability by replicating their first study on a broader array of brand categories, allowing for strong managerial implications to be made.

 

Bibliography

Duhachek, Adam (2005), “Coping: A Multidimensional, Hierarchical Framework of Responses to Stressful Consumption Episodes,” Journal of Consumer Research, 32, 1, 41–53

Ellison, Nicole B., Rebecca Heino, and Jennifer Gibbs (2006), “Managing Impressions Online: Self-presentation Processes in the Online Dating Environment,” Journal of Computer-Mediated Communication, 11, 2, 415–41.

Emmanuelle Zech, and Bernard Rimé (2001), “Disclosing and Sharing Emotion: Psychological, Social, and Health Consequences,” Handbook of Bereavement Research: Consequences, Coping, and Care, p.517–43

Goodman, J.K., and Paolacci, G., 2017. “Crowdsourcing Consumer Research”, Journal of Consumer Research, Volume 44(1) p.196-210

Hennig-Thurau, Thorsten, Kevin P. Gwinner, Gianfranco Walsh, and Dwayne D. Gremler (2004), “Electronic Word-of-Mouth via Consumer-Opinion Platforms: What Motivates Consumers to Articulate Themselves on the Internet?” Journal of Interactive Marketing, 18, 1, 38–52.

King, R.A., Racherla, P. and Bush, V.D., 2014. “What we know and don’t know about online word-of-mouth: A review of synthesis of the literature. Journal of Interactive Marketing, Volume 28(3), p.167-183

Krämer, Nicole C. and Stephan Winter (2008), “Impression Management 2.0: The Relationship of Self-esteem, Extraversion, Self-efficacy, and Selfpresentation within Social Networking Sites,” Journal of Media Psychology, 20, 3, 106–16.

Mehrabian, Albert and James A. Russell (1974), An Approach to Environmental Psychology. Cambridge, MA: MIT Press.

Pennebaker, James W. 1993, “Mechanisms of Social Constraint,” in Handbook of Mental Control. D.M. Wegner, J.W. Pennebaker, editors. Englewood Cliffs, NJ: Prentice Hall. p. 200–19

Proserpio, D. and Zervas, G., 2017. Online reputation management: Estimating the impact of management responses on consumer reviews. Marketing Science, 36(5), p.645-665.

Stephens, Nancy and Kevin P. Gwinner (1998), “Why Don’t Some People Complain? A Cognitive-Emotive Process Model of Consumer Complaint Behavior,” Journal of the Academy of Marketing Science, 26, 3, 172–89.

Wessling, K.S., Huber, J., and Netzer, O., 2017. “ MTurk Character Misrepresentation: Assessment and Solutions” Journal of Consumer Research, Volume 44(1), p. 211-230

iStockphoto


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

What is iStock?

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

How and why does it work?

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

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

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

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

Evaluation

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

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

Conclusion

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

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

 

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

 

References

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

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

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

The Cloakroom


The shift from brick and mortar store to online store was shift and sudden. The new online e-commerce environment provided consumers with endless possibilities especially for the clothing industry. With a total amount of US $332.1 billion in 2016 this industry accounted for 28% of the total eCommerce market. Additionally the industry is expected to grow at an average annual growth rate of 13.8% (Bohnhoff 2016).

Despite this increase in online sales and ecommerce there are still consumers that are hesitant to order online. The biggest part of this hesitation is the distrust in technology and the supply chain involved, but next to that little is known about online “innovators” and “early adopters” (Goldsmith and Goldsmith 2002). Enter the Cloakroom, a Dutch start-up determined to change the scene!

What is the Cloakroom?

Launched in a small apartment in Amsterdam the cloakroom is dedicated to bringing curated shopping to the public. With a simple vision: “We believe that every man deservers the luxury of having his own personal shopper”, founders Asbjørn Jorgensen & Kasper Petersen set out to become market leader in their own curated shopping niche.

How does it work?

Instead of focussing on the logistic parts and providing customers with an extensive amount of choices, the cloakroom focusses on the consumer and provides him with the personal shopping advice necessary. Customers apply through the website and fill in an online survey regarding preferences, these preferences lead to a profile which in the next step is discussed during a phone consultation. Based on the customer information and extensive knowledge of personal shoppers the customers receive 10 to 15 pieces of apparel. This apparel is send for free and can also be returned without any costs, this provides those customers warry about online purchases with an extra certainty. After a customer has ordered a box, picked out his favourites, and returned the leftovers,  he is provided with the opportunity to provide feedback to his personal shopper. This feedback is hence forward used to alter the customer profile and future apparel choices (The Cloakroom n.d.).

The Customer-Centric Cloakroom

What makes the Cloakroom customer centric is their intricate knowledge of their customers, before being send a clothing box customers are thoroughly analysed through surveys, phone interviews and store visits. This allows the Cloakroom, and its personal shoppers, to identify and provide the customer with their preferred product. The personal approach whereby the customer can get in touch with his personal shopper through both online, Facebook and WhatsApp, and offline, phone and store visits, allows for the building of customer trust. Trust which is deemed crucial for the growth and success of mobile commerce (Siau and Shen  2003). Additionally, the Cloakroom is able to take returns, a major pain point in eCommerce, and turn it into an opportunity. First of all it allows them to gain a better understanding of their customer, and secondly customers who have had good return experiences  will spend significantly more on return trips than other customers (Rivero and Zhu 2016).

Apart from providing customers with the experience that suits their needs, The Cloakroom also leads to joint profitability in the ecommerce sector. The company absorbs part of the risk traditional ecommerce companies have with regards to returns, additionally it provides consumers with a hassle free shopping experience and excellent service. Part of this risk absorption is possible due to the customer centric approach of the Cloakroom providing them with information about their customers traditional ecommerce companies do not have.

Since the founding of the Cloakroom many traditional ecommerce and clothing companies have started their own ventures (Zalon from Zalando, The Box Office from Suitsupply etc.) This is to show that the model employed by Cloakroom is a promising new model. A business model that is customer focused, allows for quick adaptations and feedback, and provides join profitability.

Bibliography

Bohnhoff, T. (2016). E-Commerce: Fashion. [PDF] Hamburg: Statista. Available at: https://statcdn.com/pdf/ca_study_readsample/DMO_sample_38340.pdf [Accessed 10 Mar. 2018].

Goldsmith, R. E., & Goldsmith, E. B. (2002). Buying apparel over the Internet. Journal of Product & Brand Management11(2), 89-102.

Siau, K., & Shen, Z. (2003). Building customer trust in mobile commerce. Communications of the ACM, 46(4), 91-94.

Rivero, P. and Zhu, Z. (2016). Online Clothes Shopping An Industry Landscape Study Focusing on Returns. [PDF] California: Sutardja Center. Available at: http://scet.berkeley.edu/wp-content/uploads/zhuzihan_late_4894259_68726594_IEOR-290-final-report-1.pdf [Accessed 10 Mar. 2018].

Making the most out of your marketing efforts in the context of eWOM


Think about it, who is your favourite advisor when it comes to finding your next, undiscovered restaurant? Your mum or perhaps your best friend? Sometimes they might not give the best advice, luckily you have kind strangers who write reviews online, which you can consult. Review platforms such as Yelp.com, enable people to write and read reviews on products and/or services. But how do businesses handle marketing efforts in the context of electronic word-of-mouth (eWOM)? This is an important question for managers since the rise of the Internet has changed how they allocate marketing expenditure, turning more to online advertising (Lu et al. 2013), but is this effective? To answer this question Lu et al. research the influence of promotional marketing on third-party review platforms.

What was their approach?
Lu et al. examined the impact of online coupons, keyword sponsored search and eWOM on weekly restaurants’ sales using a three-year panel study. They focused on restaurants since going out to dinner is a high-involvement service and eWOM is particularly important for high-involvement products and/or services (Gu et al. 2012). With high-involvement products customers spend considerable time searching for information before purchasing. Lu et al. collected their data from one of the largest restaurant review websites in China. Online coupons are displayed on this platform and the keyword sponsored search works as follows: restaurants buy keywords and when users search for restaurants using that keyword, the restaurants will be displayed at the top of the platform’s search results.

Key insights
One of the key insights Lu et al. found is that both promotional marketing and eWOM have a significant impact on sales. Keyword sponsored search and eWOM have a positive impact on sales. Likewise, offering online coupons has a positive impact on sales, however this relationship is not present for coupon value, indicating that the presence of online coupons is more important than their value since it increases awareness among users (Leone and Srinivasan 1996). Another key insight is that interaction between eWOM and promotional marketing is significant. The interaction between eWOM and coupon offerings is negative, indicating that they substitute one another and thus only one is needed to attract sales. On the other hand, the interaction between eWOM and keyword sponsored search is positive, indicating that they complement one another and together increase sales. Furthermore, if you would use both promotional marketing tools simultaneously, this would negatively impact sales since too many marketing tools  at the same time is experienced as too intrusive by customers. Altogether, these insights highlight different sources of information, with different levels of credibility, while still both sharing the power to inform and attract customers.

Looking to promote your business?
The study’s strength is that it presents some very useful advices when it comes to using promotional marketing in the context of eWOM. First of all, it is good to know that allowing promotional marketing activities on third-party platforms does not hurt the platform’s credibility and thus indicates some interesting marketing possibilities. According to Lu et al., you should stimulate users to generate more positive eWOM since this increases sales. Businesses could use online coupons to get customers’ attention, but if the volume of eWOM is high, this tool becomes less effective. In the case of high eWOM volume, businesses should rather buy keywords to increase sales. However, businesses should not use these two promotional marketing tools simultaneously since this decreases sales, rather they should focus on the tool that is most suitable for them.

Although these insights are useful, managers should note the study’s weaknesses. One of these weaknesses is the study’s generalisability. Firstly, the study only included restaurants from Shanghai, while other academics indicate the presence of cross-cultural differences (King et al. 2014). Secondly, the study focused on high-involvement products, while many studies examine low-involvement products, e.g. books and films, and find that eWOM has a significant impact on sales (Chevalier and Mayzlin 2006; Duan et al. 2008). Thirdly, the study focused on one platform, while other studies indicate that eWOM across platforms can impact sales (Gu et al. 2012). Therefore, future research could focus on whether the study’s results also apply cross-culturally, across different product and across different platforms. Another weakness of this study is the limited dimensions of eWOM and promotional marketing captured. For instance, Chavelier and Maryzlin (2006) indicate that the length of reviews also influences customers’ purchasing behaviour. Besides, the measurement of promotional marketing is two-fold, while other options such as banners or pop-up ads also exist. Future research could therefore investigate whether results differ for other promotional marketing tools and if adding more dimensions for eWOM might indicate different results. To conclude, although the paper has some weaknesses, it does not overturn the practical implications, managers should however be cautious and decide whether the study applies to their specific situation or if their situation deviates from the study’s setting.

References
Chevalier, J.A. and D. Mayzlin (2006) ‘The Effect of Word of Mouth on Sales: Online Book Reviews’, Journal of Marketing Research 43(3): 345-354.

Duan, W., B. Gu and A.B. Whinston (2008) ‘The dynamics of online word-of-mouth and product sales – An empirical investigation of the movie industry’, Journal of Retailing 84(2): 233-242.

Gu, B., J. Park and P. Konana (2012) ‘Research Note – The Impact of External Word-of-Mouth Sources on Retailer Sales of High-Involvement Products’, Information Systems Research 23(1): 182-196.

King, R.A., P. Racherla and V.D. Bush (2014) ‘What We Know and Don’t Know About Online Word-of-Mouth: A Review and Synthesis of the Literature’, Journal of Interactive Marketing 28(3): 167-183.

Leone, R.P. and S.S. Srinivasan (1996) ‘Coupon face value: Its impact on coupon redemptions, brand sales, and brand profitability’, Journal of Retailing 72(3): 273-289.

Lu, X., S. Ba, L. Huang and Y. Feng (2013) ‘Promotional Marketing or Word-of-Mouth? Evidence from Online Restaurant Reviews’, Information Systems Research 24(3): 596-612.

 

Instacart: Bringing Community, Personalization, and the Sharing Economy to you


Instacart is a U.S. based personal shopping platform that involves three major consumer groups: full-service shoppers, brick-and-mortar grocers, and end-customers.

 

Process Overview

Instacart holds contracts with several grocers and markets including the likes of Whole Foods, CostCo, PetCo, CVS Pharmacy, and Spec’s liquor store. Instacart offers jobs that involve shopping for groceries, bagging, and delivering goods to the homes of customers. Each shift, these shoppers are expected to safely acquire and transport hot and cold groceries to customers in their delivery zone. End customers peruse through the app or online catalog which features products available at the stores contracted by Instacart. Customers select their desired items and a time frame they are available to receive the goods at their workplace or residence. Using location-based technology, the Instacart application notifies customers when their personal shopper is in the store and sends live updates as items from the shopping list are added to the cart. Instacart shoppers – or Instashoppers –  are trained to accept orders, arrive at the store, collect the requested items, and purchase the groceries using a company card. Prior to checkout, shoppers communicate with customers about any adjustments that may have been made given the available selection at the store. Additionally, customers and shoppers are able to chat with each other during the shopping process to discuss products, availability, adjustments, and any other customer service issue each party may have.

Once bagged, Instashoppers return to their vehicles, load the goods, travel to the customer, and make the drop. Customers are able to rate and add an additional tip for shoppers based on their performance and service. Although customers are allowed to schedule deliveries for later, the process typically takes 75 minutes from the moment a shopper accepts an order to the confirmation of delivery, all recorded in the application.

The Instacart model incorporates three major Customer-centric ideologies: the sharing economy, community, and online personalization and product recommendations.


Community

Instacart encourages community support among shoppers in delivery zones which reap numerous benefits. After he or she passes a background check, an invite is sent to new Instashoppers to visit a local grocery store where a Shopper Supervisor holds orientation seminars. Here, new shoppers gain firsthand exposure to the shopping procedure and undergo a demonstrative experience of the job. Additionally, these recruits meet several other new and experienced Instashoppers from which they will receive tricks of the trade, a branded lanyard, a company credit card, and a branded T-shirt that serves the purpose of unifying shoppers and intriguing regular grocery store shoppers about the Instacart service. Plus, Instashoppers are invited to a third-party mobile-based community on GroupMe where hundreds of shoppers and supervisors are able to have a chat offering advice or asking questions about the shopping experience in their zone. Given that the communication platform is outsourced, the shoppers can express joys or frustrations about customers they come across, grocers, and even the corporate policies like ones that incentivize new shoppers.


Personalization

Instacart uses product recommendations to influence shoppers and customers alike. In the likely event an item is unavailable in the store, shoppers are asked to use common sense in order to fill the likely request of the customer. For example, the customer wants Moo-Moo Farms 2% milk, but the grocer has run out of this item. Once the shopper informs the app and customer of the stocking issue, the app may turn around and suggest adding 2% Milk from Oak Farms to the shopping list, as this is an item the customer has ordered in the past. Furthermore, the app may offer nonsensical items based on algorithms that an intelligent shopper might have to identify like the suggestions of Moo-Moo Farms Chocolate Milk or Creamer. Other cases may include how a lack of fresh fruits and vegetables in the store may be replaced by packaged and canned versions of the products. On the customer end, Instacart employs big data analytics to predict items that may be desired based on past purchases, demographics, and information based on location and shopping patterns of neighbors. If one’s shopping behavior mirrors that of other new moms, young singles, or larger families, he or she can expect to see coupons for products people like them typically buy.


Sharing Economy

The biggest benefit this ideology helps Instacart with is the ability to rent human capital and delivery vehicles. Instashoppers use bags, coolers, cars, wagons, temperature-controlled bags, and any other personal product that helps them to shop and deliver groceries. For long distance deliveries of over 15 miles between store and customer, shoppers are offered a five dollar bump for the additional time and gas required for the delivery. This method allows for Instacart to circumvent the issue of car maintenance in their operations as their hired employees use personally owned vehicles to fulfill orders. Given the low-skill requirement, minimal overhead, and manageable physical effort requirements, the barrier to entry is low and new shoppers join every day. Instacart thrives by offering jobs to people young and old who can deliver groceries to their less-abled or more affluent neighbors willing to pay a premium on groceries for the added convenience of delivery and avoidance of long lines and hellish parking lots on busy Sunday afternoons.

 

Social influence and high-technology products


As discussed in the last lecture, social influence can have an impact on the behaviour of consumers in the online music community. But, social influence can also have an effect in other contexts. Therefore, Risselada et al. (2014) analyse the effects of social influence and direct marketing on the adoption of new, high-technology products.

Based on previous literature, the researchers expect that social influence will play a role since the decision to adopt a high-involvement product requires information gathering from different sources (Godes, 2011). They study this assumption on the basis of two research questions: (1) ‘What are the effects of social influence variables – in particular, recent and cumulative adoptions – on the adoption of a new product when accounting for the effect of direct marketing?’ and (2) ‘How do these effects and the effect of direct marketing change from the product introduction onward?’ (Risselada et al., 2014)

Figure 1 shows an overview of the conceptual framework. As mentioned, the dependent variable is the product adoption of an individual. In addition to the hypotheses, they control for sociodemographics and relationship characteristics. To study the hypotheses and aforementioned research questions, they used data from a large sample of customers from a Dutch mobile telecommunications operator. This sample was based on random selection.

conceptualmodel.png

Main Findings

This study presents a few main findings: First of all, they proved that social influence indeed affects adoption, which is what they expected. Furthermore, they found that the social influence effect from recent adoptions is positive and remains constant from the introduction of the product onward. The same accounts for cumulative adoptions. However, this positive effect decreases from the product introduction onward. Lastly, the effect of direct marketing is positive and decreases from the product introduction onward.

Strengths

Although many studies have already been done about social influence and its effect, several issues remain unexplored. One example is that most studies assume that the effects of social influence remain constant from the product introduction onward (Bell and Song, 2007). This study dives deeper in these unexplored issues by providing new insights into the adoption of high-technology products by analysing dynamic effects of social influence and direct marketing simultaneously. Furthermore, this study discusses and assesses how the social influence effect varies from the introduction of the product onward.  Therefore, this study fills a gap in the current literature.

Secondly, this study accounts for homophily and tie strength (the intensity and tightness of a social relationship). This is a strength since these variables could have an influence on the outcomes. They use both homophily and tie strength as weights to construct two social influence variables in addition to the unweighted ones. At the end, this research shows that homophily is an important dimension when it comes to social influence. However, this also creates a weakness, which will be elaborated more on later.

Lastly, they used random sampling for gathering the data. In this way, the sample represents the target population and sampling bias has been eliminated. This makes it more generalizable.

Weaknesses

This study also has few limitations and weaknesses. First, in this paper, they focus on the marketing literature and do not adopt a social psychological view on social influence. As a result, the researchers do not study the mechanisms and processes that cause the influence, such as compliance and identification. They are simply not able to examine this because they do not have access to the required data. However, this could have been interesting to research since it has managerial importance. They could have somehow explained the mechanisms by providing theoretical explanations or by gaining access to more data.

Secondly, as mentioned before, the researchers used one homophily measure. The results showed that homophily has a great impact on social influence. Therefore, this research is too limited in providing a more in-depth analysis about the underlying dimensions. Since the researchers did not expect this, future research could focus more on this aspect.

 

References

Bell, D. R., Song, S. (2007), Neighbourhood effects and trial on the internet: Evidence from online grocery retailing, Quantitative Marketing and Economics, 5(4), 361-400.

Godes, D. (2011), Opinion leadership and social contagion in new product diffusions, Marketing Science, 30(2), 224-229

Risselada, H., Verhoef, P. C., Bijmolt, T. H. A (2014), Dynamic Effects of Social Influence and direct marketing on the adoption of high technology products, Journal of Marketing, 78(2), 52-68

 

The effects of brand communities on brand trust


Introduction

Having a social media based brand community (SMBBC) is becoming a vital part of having a successful business model with an active consumer group. Traditional ways of reaching customers are fading, while social media influence is increasing. The rise in social media comes with an ideal opportunity to build brand communities, since they often overlap with social media. Previous research has shown that brand communities based on social media influence relationships among customer and brand, product, trust and loyalty (Laroche et al, 2013). However, the research about the benefits and consequences of brand communities based on social media platforms is limited. This article develops a conceptual framework that shows how building blocks of a brand community established on social media can influence brand trust.

Strengths of the paper

The article clearly describes the role of different factors that have an impact on the building blocks of a brand community, for instance consumer relationships with product, brand, company and other consumers (McAlexander et al., 2002). Furthermore, they clearly describe the current main three research streams about brand communities. They also discuss that brand communities can be vastly different based on social contexts and forms, and that there for the outcomes of the communities are very different. After this, they mention the importance of trust for brands, which can be improved by decreasing information asymmetry, by giving more information about product and brand. This leads back perfectly to the benefits of SMBBCs. Also, the methodology used for this article is clearly described. They used an online questionnaire that was answered by people who were part of a brand community. The final sample consisted of 569 questionnaires with 284 different brand communities. The largest age range was 21-30-year-old people (51%), with about 80% of respondents saying that that they logged in to their social networking site once or multiple times a day, while 49% of respondents also checked for their personal brand community at least once per day. This seems like a very representative sample for the population. The hypothesis that followed were clearly described and elaborated on. The rejection of one of the hypothesis, that the customer-other customers relationship negatively influences brand trust, was explained by the lack of hierarchy that could influence trust in other members, which I found an interesting conclusion.

Weakness of the paper

The return of investment for social media and SMBCC’s is shortly discussed in the article, but only by discussing the challenges of determining this rate. They could have focused more on what kind of ROI’s there are for business social media usage, and also mention the key differences compared to traditional marketing. Also, they mention that consumers make strong relationships with different aspects of brand communities based on their primary consumption motivations, but which motivations are indicators of future behavior of consumers in a brand community? Also, they form a hypothesis that consumers with high engagement have stronger relationships with a brand than people with low engagement, but that was already clear from the literature research that was done in a previous chapter. Instead of this, they could have focused more on brand value impacting trust for example, since I think people will trust a firm with a high brand value more easily. Additionally, the 284 brand communities that were used for answering the questionnaire could have been specified more. Since the sample included so many different brand communities, I think it is important to conduct more specific studies across various product categories to find more insights that are linked to certain products.

Managerial Implications

One of the main marketing objectives for a company is often to gain consumers’ trust in their brand (Sirdeshmukh et al, 2002). Therefore, knowing if and how social media-based brand communities (SMBBCs) influence brand trust can be vital information. Consumers often have a need for a brand to feel ‘genuine’ before making a purchase, which is why a SMBBC can be the perfect tool for this by providing the interaction between customer and company. They clearly describe the importance of social media for brand communities, and that companies that use this to their advantage outperform other companies. There are five dimensions that make SMBBCs unique: social context, structure, scale, storytelling and affiliated brand communities. Studying these dimensions compared to previous brand communities is inevitable for managers to be sure that their company stays up to date.

Take away for researchers

The findings of the article show that customer-brand relationships add to brand trust through SMBBCs,  but more research has to be done about negative relationships between customers occurring and what effect this has on the brand community. Negative posts or comments have five times the effect of positive ones (Corstjens & Umblijs, 2012; Powers et al., 2012), so moderating the brand community might be necessary. The disadvantage of this is that removing posts on a social media page could be seen as a censorship move from the brand which decreases the trust of consumers, which should be researched in more detail.

References

Article used: Habibi, M. R., Laroche, M., & Richard, M. O. (2014). The roles of brand community and community engagement in building brand trust on social media. Computers in Human Behavior37, 152-161.

Laroche, M., Habibi, M. R., & Richard, M. O. (2013). To be or not to be in social media: How brand loyalty is affected by social media?. International Journal of Information Management33(1), 76-82.

Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of marketing66(1), 15-37.

McAlexander, J. H., Schouten, J. W., & Koenig, H. F. (2002). Building brand community. Journal of Marketing, 66(1), 38–54

Powers, T., Advincula, D., Austin, M. S., Graiko, S., & Snyder, J. (2012). Digital and social media in the purchase decision process: A special report from the Advertising Research Foundation. Journal of Advertising Research, 52(4), 479–489.