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Consumer segmentation in the market of joint consumption in Russia

Serebryanskiy Andrey Sergeevich

Москва 2017



Context

• Absract
• Introduction
• Chapter 1. Theoretical basis of segmentation process and sharing economy notion
• Segmentation
• Sharing economy as an innovative business model
• Practical models of users' innovation acceptance
• Chapter 2. Market analysis and segmentation of sharing economy users
• Market analysis
• Methodology of the empirical research
• Results
• Conclusions
• Recommendations
• References
• 

Absract

This research deals with the sharing economy notion, which is defined by Ratchel Botsman and Roo Rogers as “an economic model based on sharing underutilized assets from spaces to skills to stuff for monetary or non-monetary benefits”. The study examines sharing economy in Russian market using a quantitative research targeting mainly on segmentation of its users based on the motives frame. Core investigation is conducted through dimension reduction analysis on the basis of Theory of Planned Behavior in conjunction with Technology Acceptance Model. After revealing the key factors of the participation in sharing economy, its users are segmented by dint of cluster analysis. Basing on gained clusters the work attempts to give practical recommendations on the topic.



Introduction

This paper aims at revealing the nature of sharing economy. First definition of it was given by Rachel Botsman and Roo Gogers in their book “What's Mine is Yours: The rise of collaborative consumption”. They state that sharing economy is “an economic model based on sharing underutilized assets from spaces to skills to stuff for monetary or non-monetary benefits” (Botsman R. and Rogers 2011). More precisely it is a consumption model when a few people own a good and a lot of use it (i.e. One owns a car and share it with others for a little fee).

All over the world sharing economy companies are expanding their businesses. Now they have achieved the point when they outstrip firms in the same sector, but working in a traditional model. For example, Uber is estimated at $17 billion (Merced 2014). It is more than Avis and Hertz - the main players on the car-rent market - together. The same situation is with hotel booking services: AirBnB with market capitalization more than $10 billion has beaten previous leader Hyatt. Schumpter defined this process as “creative disruption”, meaning fall of giant and conservative market leaders after new competitor with an innovative model has entered the market.

Besides, sharing economy seems to be merging and fast-growing market. In the last three years six carsharing companies have appeared in the Russian market, two things sharing, three ridesharing. Online redistribution market has round 25 million users total audience and the leader of this branch Avito is the third popular site in Russian Internet (Forbes 2017).

Because the market is new for Russia and has a great growth potential according to the international experience knowledge of why do people accept new business model and take part in it is considered to be a thing of great importance (Botsman R. and Rogers 2011), (Hamari, Sjoklint and Ukkonen 2016), (Hawlitschek, Teubner and Gimpel 2016). To reveal the nature of intensives inspiring people to participate in sharing the reliable method of benefit segmentation (Wedel and Kamakura 1999) would be used. Drivers and impediments of participation are partly adapted from previous works on the same topic conducted in foreign studies (Hawlitschek, Teubner and Gimpel 2016), (Hamari, Sjoklint and Ukkonen 2016) and partly are invented by the authors.

The Introduction part of the work is followed by the theoretical Chapter, that mainly aims at examining a core of benefit segmentation, wide discussion of the sharing economy term and a brief overview of practical models used in the evaluation of technology acceptance. Next part of the research consists of the empirical research that could be divided in two parts: secondary data analysis and quantitative investigation, followed with market research and factor and cluster analysis. The final part of the project reports the conclusions on the entire work and practical recommendations basing om the results of the empirical research.

Problem statement

Investigation carried out in this research will command attention on the Russian sharing market and will try to reduce the uncertainty about its structure. Moreover, research will attempt to segment end users of collaborative consumption (the synonym to sharing economy (Belk 2007) (Botsman 2015), more precisely about see Chapter 1, “Sharing economy as an innovative business model” part) services. First of all, this work is positioned as an explorative study, that mainly aims at revealing the market structure and main target groups.

Main questions, that will be answered during the research work, are:

? How has sharing economy spread in the Russian market?

? Which services gained the biggest popularity?

? Who are the main users?

? Why do they participate in sharing economy?

Main aim of the research is to segment users of sharing economy by means of motives driving or stopping them from taking part in sharing.

Limitations of the study

To limit the investigation a number of definitions of sharing economy and related terms are combined together in the one that will put the restrictions on the vast field of investigation.

Below there is a list of sharing economy branches that are included in the market analysis:

? Car sharing

? Taxi sharing

? Things sharing

? Skills sharing

? Redistribution markets

? Ridesharing

? Short-term flat rental

It should be mentioned, that for the reason of different motives driving or stopping people in various spheres of sharing economy the motives investigation is carried on the group people that has an experience with particular sharing services: carsharing, things sharing and ridesharing. This is done to reduce the bias of the responses connected with wrong understanding of the sharing economy nature.

Professional significance

Despite sharing has come to Russia just several years ago there are a few investigations on a similar topic. The most wide one was conducted by Nielsen in 2013 - “Global Survey of Share Communities” (Nielsen 2014), where it also included Russia. It reveals, whether people are eager to share their belongings and to rent others and also the age structure of sharing economy users.

This investigation will delve into particularities of a Russian user consumption and examine distribution of different sharing services popularity. Moreover, it will range from simple descriptive measures to complex analytic schemes, thus providing knowledge of why do people share and how could they be segmented.

Thereby, study will be of primary significance for sharing economy entrepreneurs, who can find out marketing gaps, where they can invest. Besides, they can analyze the profile of their client gained by the research and make some corrections in their marketing strategy and communication message.

Secondly, it will reveal a wide uncovered field of sharing economy investigations and determine main vectors of further research.



Chapter 1. Theoretical basis of segmentation process and sharing economy notion

In this chapter the segmentation process, the nature of sharing economy notion and practical models used in the work are discussed in details.

Segmentation

The first idea of segmentation besides with the reasons why it should be applied appeared in the article of Wendel R. Smith in 1956, named “Product differentiation and market segmentation as alternative marketing strategies” (Smith 1956). It argues that both classical and neoclassical economic theories do not take into account the heterogeneity of the market and thus firms that do not divide their audience into particular segments or differentiate their product to expand a product line will be less efficient than those ones using these strategies.

An issue asserts that its contemporary marketing managers should instead of pushing company's marketing activity to achieve the convergence on the market should divide it in several smaller markets, choose the most perspective from them and then develop a special positioning for these smaller markets.

This conception mentioned above is also widely discussed by Filip Kotler and Kevin Lane Keller in their fundamental work “Marketing Management” as an STP model.

The basis of this concept lies in the idea that every product has its own target group or target groups. To maximize its profits a company should realize an STP-process:

1) Segmentation - dividing a target audience in several distinct groups combined on one particular feature.

2) Targeting - choosing several the most appropriate segments to command marketing activities on it

3) Positioning - applying a special communication and product strategy in the good's promotion to maximize the respond from the target customer.

Since the invention of market segmentation a great deal of techniques for audience dividing have been invented. In the 14^th edition of Marketing Management 25 variables are suggested for consumer markets segmentation, including geographical, socio-demographical, income, behavioral, Values and Lifestyle and many others (Kotler and Keller 2011).

To choose from the massive number of variables and methods to be used in segmentation process Michel Wedel and Wagner A. Kamakura in their book “Market Segmentation: Conceptual and Methodological Foundations” (Wedel and Kamakura 1999) suggest to rely, firstly, on the purpose of the research and, secondly, on the type of analyzed market.

Wedel and Kamakura basing on the previews investigations ground (Frank, Massey and Wind 1972), (Wrenn and Kotler 1988) assert that there are six criteria of the market segmentation efficiency and prediction power. They are:

· Identifiability - the extent to which different segment could be distinguished;

· Substantiality - the confidence that determined groups of customers represent enough big part of the market;

· Assessibility - the opportunity for company's managers to reach target audience defined by segmentation;

· Responsivness - every emphasized cluster should be homogenous and effective in its response on marketing actions of the firm;

· Stability - every group of customers remains relatively stable in time;

· Actionability - this criteria means that every determined segment provides a clear view on specification of marketing instrument appropriate particularly for this audience.

Then, they proceed with the dividing all market segmentation bases in four groups determined by segmentation bases. There are to dimensions of division: general - product-specific and observable - unobservable. First dimension is defined of whether or not the base is dependent on product, customer or circumstances (general is independent). Second dimension is observable, if characteristics could be measured directly (like age, gender, income or location) and unobservable, if they are inherent (like motives, behavioral reasons, values, etc.). Table two provides a pivot information on that methodology with the examples of the bases relating to every square.

General observable Age, income, geography	General unobservable Values, lifestyle, psychographics
Product-specific observable Loyalty, user status	Product-specific unobservable Elasticity, Benefits, gained from the product, attributions

Table 1 The classification of market segmentation bases (Wedel & Kamakura, 1999).

This investigation of sharing economy users' motives mainly aims at determining an appropriate communication message for different groups of customers on consumer market for a completely new and innovative product. Thus, it targets at revealing product-specific unobservable (latent) features and should use bases from the corresponding square (see Table 1).

The idea that descriptive methods of segmentation are not efficient in stead of a “benefit segmentation” was firstly widely discussed by Russell I. Halley in his work “Benefit Segmentation: A decision-oriented research Tool” (Halley 1968). This work suggests to use causal approach in stead of descriptive to reveal the nature of customer wants. Meanwhile, it does not assert refusing the traditional bases of segmentation (in that work only geographical, demographical and volume variables are discussed as traditional), it offers usage of benefit segmentation to divide users in clusters and than other collected data as region, age, income, etc. to describe those segments. This approach is supposed to represent a product to a target consumer “in the most favorable light possible”.

Later, Wind mentions that benefit segmentation is to be preferred method for “making decisions about positioning, new product concepts”, for it has a high rate of actionability (Wind 1978).

Moreover, Calantone and Sawyer in their work show that benefit segmentation is stable across samples on the line of two years (Calantone and Sawyer 1978).

Russian marketing practice also develops the idea of benefit segmentation. For instance, the work “Strategic Marketing: Value navigation of the firm” (Barkan and Rucheva 2015) aims at adapting the value-oriented model of Kamakura (Kamakura 2010) for the development of the marketing strategy in two Russian B2B companies. An issues also reveals the benefit segmentation process for B2B markets. In the May 2017 a big base of consumer benefit segmentation appeared in Russia, provided by GfK Consumer Life international platform (GFK 2017).

To describe gained segments different variables could be used. First of all, segments determined in this research are differentiated by means of their segmentation base - driver of impediment specific for particular cluster, then all groups of respondents are characterized by means of socio-demographic features and, finally, all of them are attempted to be attributed to a particular group of innovativeness (Hurt, Joseph and Cook 1977).

To conclude, a reliable method of benefit segmentation seems to be the most appropriate approach to define the particular users segments with the help of motives frame. Drivers and impediments are chosen as an investigation base for the study and socio demographic characteristic and scale of innovativeness serve as a description method for defined clusters.

Sharing economy as an innovative business model

The method lying in the basis of sharing economy is not innovative. Economic relationship, built on the trust were used by different societies throughout all human history. For instance, Kibbutzim in Israel in early 1900s or Community Gardens in Germany in 1860s (Saussier 2015).

However, with the rise of mobile technology and expanding of an Internet penetration sharing concept took a new giant step: now everyone, who has smartphone and Internet connection, can instead of buying goods, take it for a period of time, he needs it. Meanwhile, one can rent his underused property to others and this way gain regular passive income. All those changes allowed new and innovative business model of sharing economy appear.

For now, sharing has firmly entered our lives. In our everyday routine we got used to watch videos on YouTube, checking our news feeds in Facebook or Vkontakte, assessing hotels and restaurants before visiting with the help of reviews on Booking and TripAdvisor or studying notion on Wikipedia and, meantime, all those content is generated by other users of social networks and sites. In other words, those users shared their thoughts, leisure, opinions, valuations and knowledge with others.

The notion of “sharing economy” is inseparably connected with several other terms. The closest in its essence is “collaborative consumption” and it is necessary to understand differences and similarities between them. Moreover, there are many other terms, which include nearly the same meaning: “access-based economy”, “P2P-economy”, “on-demand economy”, “the mesh” and several others. All of them are frequently used interchangeably.

Below the pivot table of sharing economy definitions is provided.

Author	Heading of the work	Definition
A. Stephany	The Business of Sharing: Making it in the New Sharing Economy, (Stephany 2015, 9),	denotes the “Sharing Economy” with “the value in underutilized assets and making them accessible online to a community, leading to a reduced need for ownership of those assets.”
Rachel Botsman and Roo Rogers	What's Mine is Yours: The rise of Collaborative Consumption (Botsman R. and Rogers 2011)	“An economic model based on sharing underutilized assets from spaces to skills to stuff for monetary or non-monetary benefits”.
Rachel Botsman	Defining The Sharing Economy: What Is Collaborative Consumption-And What Isn't? (Botsman, Defining The Sharing Economy: What Is Collaborative Consumption-And What Isn't? 2015)	“An economic system based on sharing underused assets or services, for free or for a fee, directly from individuals”
Russell Belk	Why not share rather than own? (Belk, Why Not Share Rather Than Own? 2007)	“the act and process of distributing what is ours to others for their use and/or the act and process of receiving or taking something from others for our use.
Juho Hamari, Mimmi Sjo?klint, Antti Ukkonen	The Sharing Economy: Why People Participate in Collaborative Consumption (Hamari, Sjoklint and Ukkonen 2016)	The peer- to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services

Table 2 Definitions of sharing economy by different authors

Most of these definitions, however, is not considered to cover all spheres, meant under discussing notion. They, for instance, obviously miss carsharing companies (Bardhi and Eckhardt, Access-Based Consumption: The Case of Car Sharing 2012) and services like “Ebay” or “Юла” (“Yuola”), which do not imply any sharing and often happen not between individuals but also in B2C way, but surely are a part of this economical approach.

It is definitely necessary to discuss various types of "collaborative consumption" interpretations. This analysis has been already conducted by Belk in 2014 in the article “You are what you can access: Sharing and collaborative consumption online” (Belk 2014). There two previous definitions are provided and discussed, what do they lack to make an appropriate description of the notion and are followed by new interpretation by Belk.

First definition he discusses was proposed by Felson and Speath in 1978 (Felson and Speath 1978, 614). They argue that collaborative consumption consists of “those events in which one or more persons consume economic goods or services in the process of engaging in joint activities with one or more others”. Good example of this specification could be excursion in museum, when we do not want to pay expensive fee for an individual tour and collaborate with other tourists to take a group one. It doesn't mean sharing things, but it implies consuming things together. Obviously, this definition is far from how we approach this notion today.

Secondly, “collaborative consumption” term was reinvented by Rachel Botsman in 2009 in her book written together with Roo Rogers “What's mine is yours: the rise of collaborative consumption” (Botsman R. and Rogers 2011). They assert that collaborative consumption is “The reinvention of traditional market behaviors--renting, lending, swapping, sharing, bartering, gifting--through technology, taking place in ways and on a scale not possible before the internet”. The way it mentioned Belk in his article, Rachel Botsman and Roo Roger include excessively large field in the notion, “mixing marketplace exchange, gift giving, and sharing”.

Finally, Russel Belk proposes his own view on the term. He argues that “Collaborative consumption is people coordinating the acquisition and distribution of a resource for a fee or other compensation”. However, this definition seems to lack details and also does not include services, which are not provided by individuals.

The most appropriate understanding of the picture and more precise and all-encompassing view gives “on-demand economy” definition. It obviously stands for providing access to some asset on demand, but include not only peer-to-peer interactions (as it was with “P2P-economy”) and also does not require exactly process of sharing. Mainly, this term stands for short access to a good, removing a necessity of ownership to fulfil a need (Cartagena 2014).

“Access economy” is a direct synonym of this notion.

In 2015 Harvard Business Review published an article named “The Sharing Economy Isn't About Sharing At All” by Giana M. Eckhardt and Fleura Bardhi (Eckhardt and Bardhi 2015). They also assert that services understood under sharing economy notion are better described by access economy. To ensure their position they suggest their investigation carried on Zipsters (participants of a ZipCar rental - international service providing short-term auto rent). In the observing article they wrote (Bardhi and Eckhardt, Access-Based Consumption: The Case of Car Sharing 2012):

Our own research on Zipcar demonstrates this point. When consumers use the world's leading car sharing service they don't feel any of the reciprocal obligations that arise when sharing with one another. They experience Zipcar in the anonymous way one experiences a hotel; they know others have used the cars, but have no desire to interact with them. They don't view other Zipsters as co-sharers of the cars, but rather are mistrustful of them, and rely on the company to police the sharing system so it's equitable for everyone.

To conclude, we observed several definitions of nearly the same phenomena that could be described in four items:

1. It is built on modern technologies of widely available Internet connection and uses mobile apps and sites to exist;

2. It fulfils some need without particular process of buying or selling (it implies just temporal access to a good or service without ownership);

3. It uses underutilised asset of goods;

4. It includes either P2P or B2C business model.

In this work exactly this definition will be meant by “sharing economy” and “collaborative consumption”. Previously they were frequently used as synonyms and as it was shown above have nearly the same meaning. Though, these terms have obvious disadvantages discussed previously they are used most widely now and, in the meantime, are the only ones found in scientific periodicals. All other terms could be met just in fiction issues.

In order to achieve concision, to describe this collective notion to respondents a collaborative consumption term was used in a survey. It was chosen, because it had appeared first and seems to achieve the widest spread around the world, in conjunction with providing simple understanding of the sense.

It also should be mentioned here that this definition was used only for market analysis to ensure the widest coverage of spheres associated with the notion. Because different intensives rule people during their usage of different sharing economy services only those respondents who are familiar with companies associated with real process of sharing were used in the segmentation research. In this work only carsharing, ridesharing and things sharing branches are considered to include real sharing processes.

Practical models of users' innovation acceptance

To segment sharing economy users by means of the probability they will participate in it, it is necessary to estimate their intention to behave and, moreover, the extent to which each factor increases the likelihood. A perfect work of assessing the effectiveness of models aimed at innovation acceptance prediction was conducted in 2003 in the research paper “User Acceptance of Information Technology: Toward a Unified View” (Venkatesh, et al. 2003).

In the review authors describe eight previously used models and evaluate their efficiency on the sample of 250 respondents from four organizations accepting new technology on voluntary or mandatory basis.

After conducting a generalizing analysis authors propose their own model that combines the most effective factors that influence the innovation acceptance and further usage. This model is called UTAUT (Unified Theory of Acceptance and Use of Technology) and includes four constructs that were defined during previous models' test as the most influential: performance expectancy, effort expectancy, social influence and facilitating conditions.

All those constructs are adapted from earlier works and below a brief overview of them is provided. Those two models are chosen because of the biggest implementation usage in the innovation acceptance sphere.

To predict if one tries new product or not a Theory of Planned Behavior is frequently used. It was firstly introduced by Iсek Ijzen (Ajzen 1985) as an extension of his Theory of Reasoned Action with included behavioral control. Basically it consists of three items:

1) Attitude towards behavior - person's own perception of the action

2) Subjective norms - person's belief about how do significant others refer to expected behavior. In the UTAUT model this factor is reinvented as Social influence.

3) Perceived behavioral control - person's evaluation of perceived ease or difficulty of the expected behavior. In the next model the near in its sense item is called Perceived Ease of Use.

Assessing the extent those features are expressed in a person allows to estimate the probability of person behaving in an expected way.

To choose factors that drive or stop a user from trying new product a Technology Acceptance Model is chosen, for it to high extent describes main drivers and impediments of accepting an innovative business model. Besides, factors were supplemented by drivers and stoppers from previous investigations (Hamari, Sjoklint and Ukkonen 2016), (Hawlitschek, Teubner and Gimpel 2016) and developed by the researchers.

Firstly, this methodology was introduced by Davis F. in his work "Perceived usefulness, perceived ease of use, and user acceptance of information technology" (Davis 1989) and then was developed by Venkatesh and Davis in 2000 and by Venkatesh and Bala in 2008 in their TAM 2 and TAM 3 models respectively. If compare, the latest work better fits sharing economy investigation, because it analyses the particularities of first experience with e-commerce, which are very close to this research's field of investigation.

Technology acceptance model look through the way consumers learn to accept and use new technology. The decision to try or not try new technology lies in two dimensions: perceived usefulness (PU) (Performance expectancy in the UTAUT) and perceived ease of use (PEOU) (Effort expectancy on UTAUT).

Basically, perceived usefulness was defined by Davis "the degree to which a person believes that using a particular system would enhance his or her job performance". Perceived ease of use in turn stands for "the degree to which a person believes that using a particular system would be free from effort".

All those concepts, described above are used in the quantitative investigation except Facilitating conditions. Facilitating conditions factor stands for how the organization provides necessary information about new technology (manuals, training sessions, tutors, etc.).

Conclusions

The benefit segmentation approach is considered to be the most appropriate choice for the analysis of new and innovative sphere aimed at reducing the uncertainty about motives of consumers. Drivers and impediments of sharing economy participation are chosen as a segmentation base for the study.

In this work terms “sharing economy” and “collaborative consumption” are used interchangeably and stand for the services, that are particularly dependent on the mobile Internet, imply temporal access to a good, use underutilized assets of products and services and could be P2P or B2B.

To develop an empirical research a UTAUT of Vencatesh et al. was chosen. The study contains factors from the work, including those got from the Theory of Planned Behavior and Technology Acceptance Model.



Chapter 2. Market analysis and segmentation of sharing economy users

Market analysis

All over the world there are several market branches associated with sharing economy. Rachel Botsman divided those spheres in three sub-categories: product service systems, redistribution markets and collaborative lifestyles (Botsman R. and Rogers 2011).

In the first group «service enables multiple products owned by a company to be shared (car sharing, solar power, launderettes), or products that are privately owned to be shared or rented peer-to-peer (Zilok, Rentoid, RelayRides)». As it follows from the definition above there are two types of product service systems: when a company owns a good and when an individual owns o good. Both sides are integrated in the research: carsharing as an example of the first one and things sharing, short-term flat renting as an example of the second.

The second group as it meant in the its heading stands for reusage of goods. This part of sharing economy is also reflected in the study by analysis of secondary usage of things firms.

The third sub-category - collaborative lifestyle - is about sharing of skills, knowledge and spare time. To reveal this collaborative consumption sector taxi aggregators, skills sharing and ridesharing analysis is presented in the study.

Carsharing

At the present moment carsharing business is mainly rising in Moscow, however it has already appeared in St Petersburg, where Delimobil, YouDrive and Colesa are operating with 160 cars in total.

In august 2016 Moscow transport department published the review http://transport.mos.ru/common/upload/docs/1473085733_Karshering_2016_publichnaya_prezentatsiya.pdf about carsharing business. According to this issue Moscow possessed 636 cars involved in carsharing and it was planned to increase their number up to 2800 till the end of 2016. Number of carsharing users was evaluated at the point of 176 000.

Since that time “Delimobil” - the main player on Russian carsharing market grew his autopark up to 1100 https://delimobil.ru/o-proekte and new giant player “BelkaCar” entered the market with 300 cars in possession. Totally, there are 2305 cars as it is stated in the report of the site rentcarus.ru http://rentcarus.ru/karshering-v-rossii/.

The august report of Moscow transport department also provide a descriptive statistics of carsharing users. As it follows from the issue 90% of carsharers in Moscow are male, 58% are married, 64% have a car in ownership. It is necessary to mention that among those who own a car there are 39% ready to refuse their vehicle.

For now, carsharing companies are trying to expand the pull of needs they satisfy providing their services: for instance, all involved in carsharing firms in Moscow provide road-to-airport option, when you can access all main Moscow aero hubs and leave a car there without paying for parking. Another new and perspective growth vector is facilitating the way to some international or federal conference, meeting or concert placed at a distance from Moscow: in April 2017 YouDrive provided path to RIF Forum http://2017.russianinternetforum.ru.

Things sharing

This sector of sharing economy seems to be the least developed one. Either in Russia or in the entire world it didn't gained a lot of popularity. Forbes in its article “Купить нельзя - арендовать: сработают ли сервисы совместного потребления только для дорогостоящего имущества?” from the 11 of April 2017 (Артамонова 2017) reminds a case of NeighborGoods, Thingloop and SnapGoods - all three the services of P2P rental of goods, that were widely discussed 5 to 7 years ago. For now, all of them are bankrupt or near to it.

It is not entirely obvious what happens on Russian P2P rental market, for the high rate of uncertainty connected with lack of research works and open information. There are two main players offering rent from individual users: “Rentmania” (from 2013) and “Arendorium” (from 2014). The first has 2146 people renting their goods https://rentmania.org/earn_with_us and the second has no more than 150 subscribers in Twitter, Facebook and Vkontakte combined together. It is not considered to be a good indicator of popularity, but compared to, for instance, Delimobil' SMM activity (10 000 subscribers only in VK https://vk.com/delimobil), it seems to be a poor result. Even not so widely used Rentmania has 3000 subscribers in Vkontakte https://vk.com/rentmania social network.

Though, the growth seems to be very low, Rentmania recently has attracted $500 000 from investors https://vc.ru/n/rentmania-500k. The founders promise to spend this money on expanding marketing activities and increasing the team.

Skills sharing

Under skills sharing notion the usage of underutilized skills assets of people is understood. It is very large sphere specifically determined by Ratchel Botsman and Roo Rogers in the distinct category - “Collaborative lifestyle” (Botsman R. and Rogers 2011).

Freelance sites exist on the Russian market for more than 10 years. Simple google search allows to find more than twenty sites offering service of connecting business to freelancer. FL.ru, Weblancer.net and freelansim.ru http://www.onlineprojects.ru/tools/freelance/ are considered to be the biggest Russian projects on the market. Of course, there is also an international player - Upwork adding choice from more than 10 million workers all over the world.

Those sites mentioned above offer wide range of different services from freelancers, however there are few web-portals which choose narrow sphere оr business model to differentiate from bigger competitors. RuBrain offers a customer a premium service and personal manager for higher price. On the contrary, Kwork suggests fixed low price from freelancers registered on it. Workzilla and You.Do propose a range of specialists to decide technical tasks, Tranzilla and 2polyglot.com aims at translation and foreign languages problems (copywriting, guiding, teaching) etc.

New and very important sphere of sharing economy is P2P skills sharing. However, for now just a few services have appeared in Russia. Among them: Qlean offering cleaning services and Sobaka-Gulyaka (“Собака-Гуляка”) suggesting pet walking and dog sitting.

Taxi aggregators

It is arguable if new IT-facilitated taxi services are included in sharing economy (Meelen and Frenken 2015) (Botsman 2015) (Killick 2015). Mainly those debates are connected with the lack of exactly sharing process in the very traditional work of the taxi driver.

However, in this work drivers side of the process is not considered to be the basic theme of investigation. The framework of the research commands attention at users of sharing economy motives, thus, we have to analyze, if usage of app-facilitated taxi aggregators falls into the definition provided in this work:

1. It relies on mobile apps;

2. It suggests a temporal access to a good;

3. It do use underutilized asset of a taxi, for if apps like Uber, Gett or Yandex.Taxi are not in the market time of the cab staying and riding idle (Uber provides statistics showing that time “in trip” (with passenger) increased from 16 minutes in an hour in 2012 to 32 minutes in an hour in 2015) (UBER 2015).

4. It assumes both P2P and B2C business models.

Concerning market evaluation of online taxi aggregators in Russia, it could be sad that the overall market is estimated by the experts on the point from 6 to 9 billion dollars (Соколова 2016). Share of app-facilitated taxi companies varies greatly in Moscow and Saint-Petersburg and regions: for Moscow it reaches 65-70%, for Saint-Petersburg it is no more than 30% and in regions it is in average on the 8% level in cities with population more than 1 million and is about 3% in cities with less.

There is no detailed data about how do volumes are divided between three main players: Uber, Yandex.Taxi and Gett, but in 2015 Bogdan Conoshenko, CEO of “Evrotransservis” assessed the Moscow market structure as follows: 50% is occupied by Yandex, other 50% are divided by Uber, Gett and other smaller players. Uber has about 10% share (Пузырев, Телегина and Серегин 2016).

Secondary usage of things

It is also arguable, do platforms allowing P2P trade of already-in-use goods (like Ebay or Avito in Russia) refer to sharing economy. Rachel Botsman and Roo Rogers are sure (Botsman R. и Rogers 2011) that those services have to be included in collaborative consumption for they reduce the production, extending lifecycle of the product and make people collaborate with each other to utilize goods efficiently.

However, if we look throughout these services by means of definition given in this work, we will mention that they do not suit it, because the they do not ensure temporary access to a good without actual ownership. They do suggest buying thing in your own possession. At the same time this work in many ways aims at revealing the sense of ownership influence on decision to participate or not to participate in sharing economy activities.

Thus, though, online P2P ads platforms market structure will be analyzed by descriptive statistics, they will not be included in the main part of the research, concerning motives of the people.

With respect to main players of a segment it should be mentioned that this branch is almost a monopoly. Avito is an Internet giant in the Russian market. It is a third biggest IT-company from Forbes evaluation (Forbes 2017) with a monthly audience of 24,8 million users. For comparison: the nearest competitor “Youla” has only 2,5 million visitors in one month (Коммерсантъ 2016).

Ridesharing

Ridesharing or carpooling is defined as online service for collaborative town-to-town trips with payment only for the fuel.

The biggest player in the field, France startup “BlaBlaCar”, entered the market in 2014. For now it positions Russian market to be the main region of development in their international strategy, for Russia shows the fastest growth over all areas of BlaBlaCar presence (Кречетова 2017). In the summer 2016 company accomplished to service 1 million people. It is the same amount, as it was for the entire 2014 year (Forbes 2017).

In the previous year the second ridesharing platform, “Boombilla”, was launched in Russia. There is no open data about volume of sales or number of rides of this company, however when they entered the market in the previous spring they promised to attract 1 million users in two years В России запустили конкурента BlaBlaCar - (В России запустили конкурента BlaBlaCar, 2016)

Finally, in February of 2017 Mail.Ru Group launched its own carpooling service - “BeepCar” (Forbes 2017).

Short-term flat renting

The pioneer of P2P property rental AirBnB in July 2016 was evaluated at $30 mlrd (Сухаревская 2016). It appeared in Russia in 2012 and reached the point of 8 000 rental offerings in the next year (Chernikova 2014).

The second by its popularity in Russia service is Tvil.ru. It provides not only P2P rental, but also hotels and apartments booking.

After carrying out a secondary data analysis several spheres of sharing economy could be named as achieved wide spread in Russia. Among them, surely, are secondary usage of thing and freelance sites. Carsharing, ridesharing, short term flat rental and taxi aggregators are steadily growing, however, they still have weak increase rates in non-central regions. Finally, things sharing has achieved the poorest results on the market.

All those branches, mentioned above have slightly various target segments, and definitely have different motives to take part in it.



Methodology of the empirical research

The main aim of the research has been achieved by conducting a step-by-step procedure of quantitative empirical investigation. This section explains precisely the methods and procedures used in carrying out the study.

The methodology employed includes firstly a profound analysis of secondary literature to reveal main drivers and impediments to take part in sharing. Secondly, it consists of wide Internet survey of the sharing economy users and to conclude a subsequent data analysis.

Analysis of secondary data

Sharing economy is a vast field of investigation in its own right and many works have been conducted on the subject in USA and European periodicals. However, in Russia this topic was covered by just a few works conducted by international marketing research agencies.

Main book that deals with sharing economy and collaborative consumption is “What's mine is yours: the rise of collaborative consumption” by Rachel Botsman and Roo Rogers, published in 2010 in USA (Botsman R. and Rogers 2011). It provides main definitions of the notion, reveals a structured subdivision of it and also gives a wide base for a problem actualization, by consistent discussion of ecological, social and economical issues, which could be solved by means of collaborative consumption. Finally, it also describes a typical sharing economy user and briefly states common intensives for his participance in sharing activities.

A profound analysis of advantages and disadvantages of sharing economy and its current state of development on USA market is given in the book of Lisa Gansky - “The Mesh: Why the future of business is sharing” L. Gansky, “The mesh: Why the future of business is sharing”, Penguin, 2010.. She widens the range of reasons to participate in collaborative consumption and, besides, describe more frequent intensives, why do people refuse to take part in it.

Four studies were chosen as a theoretical baseline for the empirical research.

Firstly, it is “The theory of planned behavior. Organizational Behavior and Human Decision Processes” by I. Ajzen (1999). It deals with theory of planned behavior (TPB). Icek Ajzen asserts that human's behavior is driven by three types of beliefs. In particular, main impediments are “attitude towards behavior”, “subjective norms” and “perceived behavioral control”.

Secondly, it is "Technology Acceptance Model 3 and a Research Agenda on Interventions" by Venkatesh, V. and Bala, H. Venkatesh, V.; Bala, H. (2008), "Technology Acceptance Model 3 and a Research Agenda on Interventions", Decision Sciences, 39 (2): 273-315 In their work they develop a model of how consumers learn to accept and use new technology. From their point of view, the decision to try or not try new technology lies in two dimensions: perceived usefulness (PU) and perceived ease of use (PEOU). Firstly, this methodology was developed by Davis F. in his work "Perceived usefulness, perceived ease of use, and user acceptance of information technology" (Davis 1989) and was just adopted by Venkatesh and Bala, however the latest work better fits sharing economy investigation, because it analyses the particularities of first experience with e-commerce, which are very close to this research's field of investigation.

Finally, the major part of factors and indicators are adapted from two works: “The Sharing Economy: Why People Participate in Collaborative Consumption” (Hamari, Sjoklint and Ukkonen 2016) and “Understanding the Sharing Economy--Drivers and Impediments for Participation in Peer-to-Peer Rental” (Hawlitschek, Teubner and Gimpel 2016). These papers are practical investigations on a massive representative sample on the sharing motives topic.

These four studies will aid to form a questionnaire, that will evaluate which factors influence one's attitude to the sharing economy.

To take a brief insight in today's structure of sharing economy a unique investigation of Nielson company (Nielsen 2014) will be used. It reveals an age structure of collaborative consumption participants, describe the usage distribution of sharing economy services and, besides, asks people to what extent they are willing to take part in different variants of collaborative consumption.

Operationalization of key variables

As it was mentioned above four works were chosen to adapt factors and indices to evaluate if one is willing or not to participate in sharing and what mainly drives or stops him. The table of all factors with relative indices in English and Russian with the original sources is placed in Appendix 1.

To adapt attitude statements from English into Russian a reliable method of back translation was used.

Besides factors and indicators that were translated from foreign works own range of factors was also used. Among them “Lack of trust to strangers” (“Недоверие к незнакомцам”) and “unwillingness to take someone's else good” (“Нежелание брать чужое”). To form them a step-by-step algorithm mentioned in the scale development tutorial of Hinkin T. (Hinkin 1998) was followed.

Indicators evaluating one's inclination to innovative product are adapted from the work “Scales for the measurement of innovativeness” (Hurt, Joseph and Cook 1977).

Questionnaire structure

The wide online survey is used to disclose the market structure and general consumption trends. It was carried out by composing attitude questions on Likert scale from 1 to 7 with closed-ended ones about socio-demographic characteristics and previous participation/awareness in sharing, in conjunction with semantic differential to evaluate respondents' willingness to borrow others' goods and to rent their belongings

In the very beginning of the questionnaire, the profound description of sharing economy is given to get acquainted with the notion those respondents, who had never heard about it.

Filter questions opens the survey. They aid in dividing people in certain groups by their previous experience in sharing and intention to take part in it further. To estimate intention a semantic differential questions are used. Moreover, this part targets on market analysis of branches and brands' popularity distribution.

In the main part of the questionnaire respondents are asked to estimate their attitude to the statement: if they agree or disagree with it on the Likert scale from one to seven, where one is completely disagreeing and seven is completely agreeing. This segment of the survey consisted of 23 indicators concerning drivers of sharing economy participance, 14 indicators reflecting impediments (both drivers and impediments including Theory of Planned Behavior and Technology Acceptance Model indicators) and 20 indicators aiding in revealing the values model of the respondent.

To reduce the danger of common method bias problem questions of different types were mixed up and, therefore, a respondent did not get tired through the questionnaire.

Attitude questions were followed by closed-ended ones with a few variants of answer placed there to describe socio-demographical characteristics: age, location, income, gender, marital status and education.

Sample description

General population of the research was defined as all adult Internet users, that own smartphone and use it to access the web. Due to the GFK analysis “Проникновение Интернета в России: Итоги 2016 года” (GFK 2017) 56 million of population older than 16 years used mobile Internet. This number is considered to be the general population, because the usage of collaborative consumption services mandatory implies a mobile devices utilization.

The main part of investigation was carried on the audience of the on-line course “Marketing” held on the national online education platform “Open education https://openedu.ru/course/hse/MARK/”. For the reason they are involved in the online education, they are considered to be an active users of mobile devices and, thus, could be a potential sharing economy participants. The research was conducted through platform for Internet surveys “SurveyMonkey” from the 20^th of March 2017 to 29^th of March 2017.

The survey link was provided to the course participants on the 20th of March 2017 and they had a week to complete it. The survey was not an obligatory condition for successful course accomplishment, however it was recommended to be reviewed as a practical example of the marketing research tool.

11 000 users took part in the “Marketing” online course, 1600 users filled the survey. After deleting the responses with missing answers as well as not fully answered responses, 1488 qualified responses left. Thus, the response rate was 13,5%.

Socio-demographic characteristics are sum up in the table 3.

	N	%			N	%
Gender		Marital status
Male	442	29,8%		Married	727	48,9%
Female	1042	70,2%		Divorced	89	6,0%
		Single	671	45,1%
Age
Under 18	3	0,2%		Children
18-25	523	35,2%		Yes	480	32,5%
26-30	410	27,6%		No	997	67,5%
31-35	264	17,8%
36-40	134	9,0%		Subject RF
41-50	130	8,7%		Moscow	526	35,3%
51-60	19	1,3%		Saint-Petersburg	187	12,6%
Elder than 60	3	0,2%		Regions	775	52,1%
Education:		City size
Incomplete secondary education	6	0,4%		More than 1 mln.	997	67,1%
Secondary general education	26	1,7%		500 ths. - 1 mln.	190	12,8%
Secondary special education	51	3,4%		100-500 ths	171	11,5%
Incomplete higher education	258	17,3%		50-100 ths	45	3,0%
Higher education	929	62,4%		Less than 50 ths	44	3,0%
Two or more higher	169	11,4%		Difficult to answer	38	2,6%
PhD	49	3,3%
Income
Not enough money even for food	9	0,6%
Enough money only for food	56	3,8%
Enough money for food and clothes, but we can not allow bigger acquisitions	720	48,5%
We can not buy a car	423	28,5%
We can allow a new car, but a flat is not affordable.	235	15,8%
There is enough money not to reject anything.	41	2,8%

Table 3 Socio demograohic characteristics of respondents

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