All posts by 460728

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

Norms, Moods and Free Lunch

Paper: “Norms, moods, and free lunch: Longitudinal evidence on payments from a Pay-What-You-Want restaurant”

The restaurant “Wiener Deewan” in Vienna is among the 11 existing restaurants allowing customers to determine the price, a.k.a. pay-what-you-want (PWYW). Due to the adoption of the pricing model from the beginning, Riener and Traxler (2011) could study the evolution of payments for PWYW at the restaurant and the corresponding influence of norms and moods. Here are some more facts about the study:


Main findings

The first research contribution of the paper shows patterns found in the collected data:


The revenue was increasing as the number of visitors was increasing, but the average payment declined from approx. 5,5 to 5 euros.

The second research contribution provides an explanation of the previously presented results. Social norms affect long-term fluctuations in payment distributions as regular guests adjust their perceptions of social norms over time. Moods are the main source of short-term fluctuations as people in a good mood are expected to pay more. The number of sunshine hours is selected as an influencer and indicator of mood.



plusThe greatest strength of this paper is the lack of pre-existing payment recommendations such as reference prices or prior prices, which is a rare opportunity and an important prerequisite for the study of norms’ influence. The variance and evolution of the average price also serve as a proof of the gradual formation of social norms as repeating visitors steadily shape their perception of the pricing norm.

plus This study is the first continuous longitudinal study of PWYW as previous studies were conducted for a short-term (e.g. Kim et al., 2009) or for a discontinuous period (e.g. Regner and Baria, 2010). As a long-term study, it provides useful insights into the specific developments and evolution of mean and median PWYW payments, showing that payments’ variance decreased over time as the majority of payments came closer to the mean.
Figure 1. The evolution of daily mean and median PWYW payments

plusminusThe inclusion of both new and returning clients make the study applicable to regular business situations. However, as 81% of the guests visited the restaurant repeatedly (Riener,2010), it would have been interesting to distinguish between the new and returning customers to study behavioral changes after each visit, i.e. if people are (and how) affected by social norms development.
minusAlthough mood has a strong correlation with sunshine and weather, as confirmed by various studies, the research doesn’t provide a convincing explanation and prove that sunshine is one of the main reasons for lower average payments. Sunshine might not influence all visitors equally as mood also depends on other external factors.To confirm the hypothesis, it would have been more useful for the researchers to conduct a survey, and quantify and establish the presence of corresponding mood conditions. 

Insights for businesses and academicians

Businesses might be surprised that PWYW pricing models don’t necessarily lead to clients paying nothing or a much lower price. The examined study shows that PWYW can bring a higher revenue and increase the number of visitors, presenting a long-term business strategy (Greiff et al., 2013). However, it is not clear if the model will be that successful if there were competitors using the same pricing model, which is an idea for future research.

Figure 2.Distribution of payments

Additionally, it will be interesting to observe if there are any differences in the evolution of payments between products and services (and further between commodity and luxury/enjoyable goods) as services have an inconsistent quality (e.g. a dish will taste slightly differently each time) while many products have a consistent one (e.g. a model of t-shirt looks and feels exactly the same).



Greiff, Matthias, Henrik Egbert, and Kreshnik Xhangolli. “Pay What You Want-But Pay Enough! Information Asymmetries and PWYW Pricing.” Management & Marketing 9.2 (2014): 193.

Kim, J., Natter, M., Spann, M.. “Pay what you want: a new participative pricing
mechanism”. Journal of Marketing 73 (1), 44–58.

Photo: Inês Lizard.

Regner, T., Barria, J. Do consumers pay voluntarily? The case of online music.
Journal of Economic Behavior and Organization 71 (2), 395–406.

Riener, G., 2010. How Free is your Lunch? University of Jena, mimeo.

Riener, Gerhard and Christian Traxler. “Norms, Moods, And Free Lunch: Longitudinal Evidence On Payments From A Pay-What-You-Want Restaurant”. The Journal Of Socio-Economics, vol 41, no. 4, 2012, pp. 476-483. Elsevier BV, doi:10.1016/j.socec.2011.07.003.



“Buy a present for my wife” said Jan to the phone

This year St. Valentine’s Day caught millions of men by surprise, again, leaving them wondering what present to buy for their partners. What if somebody or something could perform this burdensome task in a timely manner? There might be a solution…


Viv is an intelligent personal assistant introduced to the market on May 9, 216 and acquired by Samsung in October 2016. Similar products such as Siri, Google Now, Microsoft’s Cortana and Amazon’s Alexa can perform some basic tasks but nothing beyond the tasks they’ve been programmed to do. Due to artificial intelligence, Viv can generate code by itself and learn about the world as it gets exposed to more user requests and new information.

This makes it by no means a universal product. Viv is expected to learn and store information about every user, and learn with time how to serve him or her personally. For example, if the owner asks: “I need to buy a present for my life for St. Valentine’s Day”, Viv should be able to predict what a suitable present would be or perhaps book a table for two at a fancy restaurant downtown.

Continue reading “Buy a present for my wife” said Jan to the phone