**6. Pan-European evidence of collaborative behavior**

In order to obtain a representative sample and to compare the situation of collaboration consumption in the countries of the European Union, the European Commission [45] dedicated a *Flash Eurobarometer* (number 438) to a survey of the use of collaborative economy platforms. *Flash Eurobarometers* are ad hoc statistical operations consisting of short—landline and mobile—telephone interviews on a topic of interest. *Flash Barometer* 438 obtained data on the use of collaborative economy platforms from a sample of 14,050 citizens aged 15 years and above in the 28 countries of the European Union (Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Ireland, Greece, Spain, France, Croatia, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, the Netherlands, Austria, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, and the United Kingdom) through approximately 500 interviews per country. The universe of the survey consisted of the 412,630,644 European Union citizens aged 15 years and above. The sample design for each country was probabilistic and representative. The margins of error at the 95% confidence level in the case of maximum indetermination (p = q = 50) were +0.4% for the entire sample, and around +1.9% for individual country samples. The fieldwork was carried out on March 15 and 16, 2016.

The questionnaire defines a collaborative platform (CP) as "an Internet-based tool that enables transactions between people providing and using a service. They can be used for a wide range of services, from renting accommodation and car sharing to small household jobs ([45], p. 29)." Based on that approach, the survey asked the respondents about their awareness of such platforms and gave them the following options for their answers on use: (1) unaware (UNAWARE) or "You have never heard of these platforms"; (2) aware but does not use (AWNOTUSE) or "You have heard of these platforms but you have never visited them"; (3) initial use (INIUSE) or "You have been on one or more of these platforms and paid for a service once"; (4) occasional use (OCCAUSE) or "You use the services of these platforms occasionally (once every few months)"; and (5) regular use (REGUSE) or "You use the services of these platforms regularly (at least every month)." For all users of such platforms (TOTUSE), which includes initial use, occasional use, and regular use, the survey also gathered data about providing goods and services and gave the respondents the following options for their answers: (1) no provision (NOPROV) or "No, you haven't"; (2) initial provision (INIPROV) or "You have offered a service on one or more of these platforms once"; (3) occasional provision (OCCAPROV) or "You offer services via these platforms occasionally (once every few months)"; and (4) regular provision (REGPROV) or "You offer services via these platforms regularly (every month)." All providers of such platforms (TOTPROV) include initial provision, occasional provision, and regular provision. The various options

**169**

*Collaborative Behavior and the Sharing Economy: Pan-European Evidence for a New Economic…*

of those two variables were transformed into individual variables. All of these new individual variables were dichotomous, where 1 = the respondent was aware of and used or provided goods or services via collaborative platforms, and 0 = the respon-

Having stipulated the levels of use and provision, the survey looked at the driving factors (benefits) and impeding factors (problems) of collaborative platforms compared to the traditional forms of commerce of goods and services. Regarding the driving factors, the survey gave those respondents who were aware of and users of collaborative platforms the following options for their answers: (1) service cost (PRICE) or "It is cheaper or free"; (2) service newness (NEWNESS) or "It offers new or different services"; (3) service convenience (CONVEN) or "The access to services is organized in a more convenient way"; and (4) nonmonetary exchanges (NONMONET) or "The ability to exchange products or services instead of paying with money." Regarding the impeding factors, the survey gave those respondents who were aware of and users of collaborative platforms the following options for their answers: (1) lack of a responsible person when problems arise (LRESPON) or "Not knowing who is responsible in case a problem arises"; (2) lack of fulfillment of service expectations (LFULLSERV) or "Being disappointed because the services and goods do not meet expectations"; (3) lack of information (LINFORM) or "Not having enough information on the service provided"; (4) lack of trust in the agents (LTRUSTAG) or "Not trusting the provider or seller"; and (5) lack of trust in the Internet (LTRUSTINT) or "Not trusting the Internet transactions in general." All of these variables were dichotomous, where 1 = the respondent answered positively about the driving or impeding factors, and 0 = the respondent answered otherwise. Lastly, the survey gathered sociodemographic data in order to be able to characterize the users and the providers of collaborative platforms. Specifically, data were gathered on age, gender, years of education, number of household members, type of locality (village or rural area, small, midsized, or large town/city), and occupational status: self-employed or business person, employee (director, qualified professional, manual worker, and nonmanual worker), unemployed or nonemployed

(stay-at-home parent/carer, student, retiree, or unemployed person).

**Table 3** shows the descriptive statistics of the variables relating to the use and provision of collaborative platforms in Europe. Regarding awareness and use of collaborative platforms, the survey found that more than half of European citizens were unaware of these new forms of exchange (53.2%), while a further third was aware of them but had never used them (33.9%). Thus, 12.9% of the European population aged 15 years and above stated that they were users of collaborative platforms, with the following distribution: 3.2% initial use (one transacted exchange), 6.5% occasional use (once every few months), and 3.2% regular use (at least every month). In relation to the provision of goods and services via collaborative platforms, of the users of such platforms (12.9%), almost three quarters had never provided any (72.1%). The remaining 27.9% of users (3.6% of the European population) had provided goods and services, with the following distribution: 7.3% (0.9% of the total) had made an initial provision (provided goods or services once), 15.7% (2.1% of the total) had made an occasional provision (once every few months), and 5.0% (0.6% of the total) had made a regular provision (every month). For those who were aware of (33.9%) and users of (12.9%) such platforms (46.8%), the survey also gathered data about the driving and impeding factors of their use. Among the driving factors, convenience (39.1%) and price (31.4%) were cited the most, whereas service newness (22.4%) and the possibility of carrying out nonmonetary exchanges (21.8%) came some way behind the two main motivations. Regarding the factors that would limit the use and provision of such platforms, the lack of a responsible person when problems arise in the exchange (36.5%) was the main reason given, followed at some distance by the lack of fulfillment of service expectations

*DOI: http://dx.doi.org/10.5772/intechopen.83608*

dent answered otherwise.

*Collaborative Behavior and the Sharing Economy: Pan-European Evidence for a New Economic… DOI: http://dx.doi.org/10.5772/intechopen.83608*

of those two variables were transformed into individual variables. All of these new individual variables were dichotomous, where 1 = the respondent was aware of and used or provided goods or services via collaborative platforms, and 0 = the respondent answered otherwise.

Having stipulated the levels of use and provision, the survey looked at the driving factors (benefits) and impeding factors (problems) of collaborative platforms compared to the traditional forms of commerce of goods and services. Regarding the driving factors, the survey gave those respondents who were aware of and users of collaborative platforms the following options for their answers: (1) service cost (PRICE) or "It is cheaper or free"; (2) service newness (NEWNESS) or "It offers new or different services"; (3) service convenience (CONVEN) or "The access to services is organized in a more convenient way"; and (4) nonmonetary exchanges (NONMONET) or "The ability to exchange products or services instead of paying with money." Regarding the impeding factors, the survey gave those respondents who were aware of and users of collaborative platforms the following options for their answers: (1) lack of a responsible person when problems arise (LRESPON) or "Not knowing who is responsible in case a problem arises"; (2) lack of fulfillment of service expectations (LFULLSERV) or "Being disappointed because the services and goods do not meet expectations"; (3) lack of information (LINFORM) or "Not having enough information on the service provided"; (4) lack of trust in the agents (LTRUSTAG) or "Not trusting the provider or seller"; and (5) lack of trust in the Internet (LTRUSTINT) or "Not trusting the Internet transactions in general." All of these variables were dichotomous, where 1 = the respondent answered positively about the driving or impeding factors, and 0 = the respondent answered otherwise.

Lastly, the survey gathered sociodemographic data in order to be able to characterize the users and the providers of collaborative platforms. Specifically, data were gathered on age, gender, years of education, number of household members, type of locality (village or rural area, small, midsized, or large town/city), and occupational status: self-employed or business person, employee (director, qualified professional, manual worker, and nonmanual worker), unemployed or nonemployed (stay-at-home parent/carer, student, retiree, or unemployed person).

**Table 3** shows the descriptive statistics of the variables relating to the use and provision of collaborative platforms in Europe. Regarding awareness and use of collaborative platforms, the survey found that more than half of European citizens were unaware of these new forms of exchange (53.2%), while a further third was aware of them but had never used them (33.9%). Thus, 12.9% of the European population aged 15 years and above stated that they were users of collaborative platforms, with the following distribution: 3.2% initial use (one transacted exchange), 6.5% occasional use (once every few months), and 3.2% regular use (at least every month). In relation to the provision of goods and services via collaborative platforms, of the users of such platforms (12.9%), almost three quarters had never provided any (72.1%). The remaining 27.9% of users (3.6% of the European population) had provided goods and services, with the following distribution: 7.3% (0.9% of the total) had made an initial provision (provided goods or services once), 15.7% (2.1% of the total) had made an occasional provision (once every few months), and 5.0% (0.6% of the total) had made a regular provision (every month).

For those who were aware of (33.9%) and users of (12.9%) such platforms (46.8%), the survey also gathered data about the driving and impeding factors of their use. Among the driving factors, convenience (39.1%) and price (31.4%) were cited the most, whereas service newness (22.4%) and the possibility of carrying out nonmonetary exchanges (21.8%) came some way behind the two main motivations. Regarding the factors that would limit the use and provision of such platforms, the lack of a responsible person when problems arise in the exchange (36.5%) was the main reason given, followed at some distance by the lack of fulfillment of service expectations

*Strategy and Behaviors in the Digital Economy*

of collaborative behavior:

collaborative platforms.

March 15 and 16, 2016.

With the idea of broadening the set of motivations and the diversity of forms and stakeholders of the collaborative behavior, literature has also analyzed the role of sociodemographic characteristics [25]. Women and young people were more likely to share most of the products/objects. Particularly interesting is the result that shared consumption had more to do with personal mind-set or psychological disposition than with some sociodemographic aspects, like income levels. In this sense, I can formulate a working hypothesis about the sociodemographic predictors

**Hypothesis 4**: Sociodemographic characteristics predict the use and provision of

In order to obtain a representative sample and to compare the situation of collaboration consumption in the countries of the European Union, the European Commission [45] dedicated a *Flash Eurobarometer* (number 438) to a survey of the use of collaborative economy platforms. *Flash Eurobarometers* are ad hoc statistical operations consisting of short—landline and mobile—telephone interviews on a topic of interest. *Flash Barometer* 438 obtained data on the use of collaborative economy platforms from a sample of 14,050 citizens aged 15 years and above in the 28 countries of the European Union (Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Ireland, Greece, Spain, France, Croatia, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, the Netherlands, Austria, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, and the United Kingdom) through approximately 500 interviews per country. The universe of the survey consisted of the 412,630,644 European Union citizens aged 15 years and above. The sample design for each country was probabilistic and representative. The margins of error at the 95% confidence level in the case of maximum indetermination (p = q = 50) were +0.4% for the entire sample, and around +1.9% for individual country samples. The fieldwork was carried out on

The questionnaire defines a collaborative platform (CP) as "an Internet-based tool that enables transactions between people providing and using a service. They can be used for a wide range of services, from renting accommodation and car sharing to small household jobs ([45], p. 29)." Based on that approach, the survey asked the respondents about their awareness of such platforms and gave them the following options for their answers on use: (1) unaware (UNAWARE) or "You have never heard of these platforms"; (2) aware but does not use (AWNOTUSE) or "You have heard of these platforms but you have never visited them"; (3) initial use (INIUSE) or "You have been on one or more of these platforms and paid for a service once"; (4) occasional use (OCCAUSE) or "You use the services of these platforms occasionally (once every few months)"; and (5) regular use (REGUSE) or "You use the services of these platforms regularly (at least every month)." For all users of such platforms (TOTUSE), which includes initial use, occasional use, and regular use, the survey also gathered data about providing goods and services and gave the respondents the following options for their answers: (1) no provision (NOPROV) or "No, you haven't"; (2) initial provision (INIPROV) or "You have offered a service on one or more of these platforms once"; (3) occasional provision (OCCAPROV) or "You offer services via these platforms occasionally (once every few months)"; and (4) regular provision (REGPROV) or "You offer services via these platforms regularly (every month)." All providers of such platforms (TOTPROV) include initial provision, occasional provision, and regular provision. The various options

**6. Pan-European evidence of collaborative behavior**

**168**


**171**

ment to total use.

*Collaborative Behavior and the Sharing Economy: Pan-European Evidence for a New Economic…*

(25.9%), the lack of trust in the Internet in general (27.2%), and the lack of trust in the agents (buyers and sellers) of the exchange in particular (25.0%). Lastly, the lack of

Regarding sociodemographic characteristics, the mean age was 54 years and the majority of the respondents were women (58.4% women, 41.6% men). Of the individuals in the sample, 43.4% had 20 or more years of formal education. From an occupational perspective, of note was the high presence of retirees (37.3%) and of manual workers (20.3%). Most households comprised two members (44.0%). Finally, regarding the localities of European citizens (rural, small or mid-sized town/city, or large metropolitan town/city), the sample was equally divided (into three-thirds). Furthermore, in relation to countries, the sample skewed toward the European Union's

most populous countries in central and Eastern Europe (35.7% of the sample).

The basic aim of my study is to find out if these sociodemographic characterization variables, together with the motivation/barrier variables, can be turned into predictors of use and provision behavior on collaborative platforms. To that end, we performed an odds ratio (OR) analysis. Formally, it is usually defined as the ratio of the odds of a condition occurring in a population group to the odds of it occurring in another group. It is a measure of the statistical association between dichotomous variables, which has been widely used in social research for three main reasons: firstly, because the OR determines a predictor and a confidence interval (95% CI) between binary dichotomous variables, which enables probability relationships to be established; secondly, because it is useful for examining the predictive effect of one variable on another, while the other variables remain constant in a logistic regression model; and thirdly, because OR offers a quick and efficient interpretation

The interpretation of an OR analysis is as follows. If the value of the OR is less than 1 and the confidence interval (95% CI) is situated below the unit, the predictive relationship between the two variables analyzed is an inverse relationship. If the value of the OR is greater than 1 and the confidence interval (95% CI) is situated above the unit, the predictive relationship between the two variables analyzed is a direct relationship. Whenever the confidence interval (95% CI) includes the unit, the predictive relationship between two variables cannot be determined [46, 47]. If I begin by taking the use of collaborative platforms (n = 1792), the first thing to highlight is that its driving forces are clearly linked to motivations of an economic and practical nature (**Table 4**). Convenience and price are the two main drivers of collaborative platform use in Europe. In contrast, the driving factor relating to nonmonetary exchange, which could be identified as being ideological in an antiestablishment or anticapitalism sense, clearly disincentives the use of collaborative platforms. Among the impeding forces, it should be noted that the lack of fulfillment of expectations in relation to the service offered via the collaborative platform disincentives the use thereof. In contrast, the lack of trust in the Internet would not act as an impedi-

Among the sociodemographic predictors of the use of collaborative platforms in Europe, the analysis performed provides us with a set of results worth highlighting. Firstly, men are more inclined than women to use such platforms. Secondly, the younger age ranges (54 years and below) are more likely to make a total use than the older age ranges. And thirdly, households with more members have a greater probability of having a user of collaborative platforms among them than households with fewer members. Regarding human capital and occupational status, the joint use of collaborative economy platforms in Europe is also linked to the fact of being a student or having many years of education and to professional contexts of entrepreneurship, managerial responsibility, or being highly qualified. In fact, students or people with 20 or more years of formal education are much more likely to use collaborative platforms

information (18.6%) was the reason that the respondents cited the least.

*DOI: http://dx.doi.org/10.5772/intechopen.83608*

in case studies and controls.

#### **Table 3.**

*The use and provision of collaborative platforms in Europe.*

#### *Collaborative Behavior and the Sharing Economy: Pan-European Evidence for a New Economic… DOI: http://dx.doi.org/10.5772/intechopen.83608*

(25.9%), the lack of trust in the Internet in general (27.2%), and the lack of trust in the agents (buyers and sellers) of the exchange in particular (25.0%). Lastly, the lack of information (18.6%) was the reason that the respondents cited the least.

Regarding sociodemographic characteristics, the mean age was 54 years and the majority of the respondents were women (58.4% women, 41.6% men). Of the individuals in the sample, 43.4% had 20 or more years of formal education. From an occupational perspective, of note was the high presence of retirees (37.3%) and of manual workers (20.3%). Most households comprised two members (44.0%). Finally, regarding the localities of European citizens (rural, small or mid-sized town/city, or large metropolitan town/city), the sample was equally divided (into three-thirds). Furthermore, in relation to countries, the sample skewed toward the European Union's most populous countries in central and Eastern Europe (35.7% of the sample).

The basic aim of my study is to find out if these sociodemographic characterization variables, together with the motivation/barrier variables, can be turned into predictors of use and provision behavior on collaborative platforms. To that end, we performed an odds ratio (OR) analysis. Formally, it is usually defined as the ratio of the odds of a condition occurring in a population group to the odds of it occurring in another group. It is a measure of the statistical association between dichotomous variables, which has been widely used in social research for three main reasons: firstly, because the OR determines a predictor and a confidence interval (95% CI) between binary dichotomous variables, which enables probability relationships to be established; secondly, because it is useful for examining the predictive effect of one variable on another, while the other variables remain constant in a logistic regression model; and thirdly, because OR offers a quick and efficient interpretation in case studies and controls.

The interpretation of an OR analysis is as follows. If the value of the OR is less than 1 and the confidence interval (95% CI) is situated below the unit, the predictive relationship between the two variables analyzed is an inverse relationship. If the value of the OR is greater than 1 and the confidence interval (95% CI) is situated above the unit, the predictive relationship between the two variables analyzed is a direct relationship. Whenever the confidence interval (95% CI) includes the unit, the predictive relationship between two variables cannot be determined [46, 47].

If I begin by taking the use of collaborative platforms (n = 1792), the first thing to highlight is that its driving forces are clearly linked to motivations of an economic and practical nature (**Table 4**). Convenience and price are the two main drivers of collaborative platform use in Europe. In contrast, the driving factor relating to nonmonetary exchange, which could be identified as being ideological in an antiestablishment or anticapitalism sense, clearly disincentives the use of collaborative platforms. Among the impeding forces, it should be noted that the lack of fulfillment of expectations in relation to the service offered via the collaborative platform disincentives the use thereof. In contrast, the lack of trust in the Internet would not act as an impediment to total use.

Among the sociodemographic predictors of the use of collaborative platforms in Europe, the analysis performed provides us with a set of results worth highlighting. Firstly, men are more inclined than women to use such platforms. Secondly, the younger age ranges (54 years and below) are more likely to make a total use than the older age ranges. And thirdly, households with more members have a greater probability of having a user of collaborative platforms among them than households with fewer members.

Regarding human capital and occupational status, the joint use of collaborative economy platforms in Europe is also linked to the fact of being a student or having many years of education and to professional contexts of entrepreneurship, managerial responsibility, or being highly qualified. In fact, students or people with 20 or more years of formal education are much more likely to use collaborative platforms

*Strategy and Behaviors in the Digital Economy*

*Awareness and use* Unaware (UNAWARE)

Aware but not use (AWNOTUSE)

Initial use (INIUSE)

Occasional use (OCCAUSE)

Regular use (REGUSE)

Total use (TOTUSE)

No provision (NOPROV)

Initial provision (INIPROV)

Regular provision (REGPROV)

Total provision (TOTPROV)

*Driving factors*

Newness (NEWNESS)

Convenience (CONVEN)

Nonmonetary (NONMONET)

*Impeding factors* Lack responsible person (LRESPON)

Lack fulfilling expect (LFULLSER)

Lack information (LINFORM)

Lack trust in agents (LTRUSTAG)

Lack trust in Internet (LTRUSTINT)

*The use and provision of collaborative platforms in Europe.*

Occasional provision (OCCAPROV)

*Provision of goods and services*

**N Mean SD Minimum Maximum Skewness Kurtosis**

13,837 0.532 0.499 0 1 −0.128 −1.984

13,837 0.339 0.473 0 1 0.682 −1.535

13,837 0.032 0.177 0 1 5.298 26.068

13,837 0.065 0.247 0 1 3.530 10.465

13,837 0.032 0.177 0 1 5.291 26.998

13,837 0.129 0.336 0 1 2.207 2.872

1778 0.721 0.448 0 1 −0.987 −1.028

1778 0.073 0.259 0 1 3.298 8.890

1778 0.157 0.364 0 1 1.888 1.567

1778 0.050 0.217 0 1 4.158 15.303

1788 0.279 0.449 0 1 0.987 −1.028

6477 0.224 0.417 0 1 1.324 −0.247

6477 0.391 0.488 0 1 0.449 −1.779

6477 0.218 0.413 0 1 1.368 −0.127

6477 0.365 0.481 0 1 0.560 −1.687

6477 0.259 0.438 0 1 1.099 −0.792

6477 0.186 0.389 0 1 1.614 0.605

6477 0.250 0.433 0 1 1.154 −0.668

6477 0.272 0.445 0 1 1.027 −0.947

Price (PRICE) 6477 0.314 0.464 0 1 0.801 −1.359

**170**

**Table 3.**


**173**

*Collaborative Behavior and the Sharing Economy: Pan-European Evidence for a New Economic…*

Three **1.212 (1.067–1.377)** 1.067 (0.821–1.386) Four or more **1.203 (1.053–1.374)** 0.906 (0.685–1.198)

Village or rural area **0.736 (0.658–0.823)** 1.042 (0.824–1.318) Small or mid-sized town/city 0.940 (0.848–1.043) 0.980 (0.789–1.217)

Continental Europe1 **1.249 (1.113–1.403)** 1.207 (0.954–1.526) Mediterranean Europe2 **0.735 (0.651–0.831)** 1.000 (0.773–1.294) Northern Europe3 1.058 (0.932–1.202) **0.748 (0.566–0.987)** Central and Eastern Europe4 1.029 (0.928–1.141) 1.028 (0.829–1.276)

*Notes: OR: odds ratio and 95% CI: confidence intervals at 95%. ORs and 95% CI in bold are significant.*

*Continental Europe: Belgium, France, Luxembourg, the Netherlands, Austria, and Germany.*

*Mediterranean Europe: Greece, Spain, Italy, Portugal, Cyprus, Malta, and Croatia.*

*Northern Europe: Denmark, Finland, Sweden, the United Kingdom, and Ireland.*

*Predictors of P2P platform use and provision in Europe.*

**Users (n = 1792) Providers (n = 496) OR (95% CI) OR (95% CI)**

**1.419 (1.280–1.574)** 0.986 (0.795–1.222)

than people with fewer years of education. As far as occupational status is concerned, the self-employed and business people, employees who are directors, employees who are qualified professionals, and employees who are nonmanual workers are the most likely to use collaborative platforms. In contrast, employees who are manual workers, stay-at-home parents/carers, the unemployed and, in particular, retirees are much

*Central and Eastern Europe: Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania,* 

Finally, the predictors by geographical area also provide relevant information, firstly, because the impetus behind collaborative consumption comes from large towns/cities and metropolitan areas, whereas living in villages and rural areas would disincentive collaborative consumption via platforms. By country, we also observe a greater likelihood to use collaborative platforms in continental Europe— Belgium, France, Luxembourg, Netherlands, Austria, and Germany—whereas in Mediterranean Europe—Greece, Spain, Italy, Portugal, Cyprus, Malta, and

The analysis of predictive factors for the provision of goods and services via collaborative platforms (n = 496) in Europe (**Table 4**) reveals a picture that clearly differs from the use of such platforms. Of the motivational predictors of collaborative provision, the first element to highlight is that such provision has a clearly ideological component, in an antiestablishment or anticapitalism sense, because the possibility of doing nonmonetary exchanges becomes a driving factor. Moreover, nonmonetary exchange was the only provision-driving predictor to be identified, because the other economic and convenience factors were not significant. Regarding the impeding forces, the lack of a responsible person would not disincen-

From the perspective of the sociodemographic predictors, the collaborative provision of goods and services in Europe would be motivated by a much narrower set of factors than the one identified for collaborative uses. Men, the young

less inclined toward collaborative consumption via platforms.

tive the collaborative provision of goods and services.

Croatia—the situation is the inverse.

*DOI: http://dx.doi.org/10.5772/intechopen.83608*

*Locality*

*1*

*2*

*3*

*4*

**Table 4.**

Large town/city or metropolitan area

*Country groupings*

*Slovenia, and Slovakia.*

*Collaborative Behavior and the Sharing Economy: Pan-European Evidence for a New Economic… DOI: http://dx.doi.org/10.5772/intechopen.83608*


*Notes: OR: odds ratio and 95% CI: confidence intervals at 95%. ORs and 95% CI in bold are significant.*

*1 Continental Europe: Belgium, France, Luxembourg, the Netherlands, Austria, and Germany.*

*2 Mediterranean Europe: Greece, Spain, Italy, Portugal, Cyprus, Malta, and Croatia.*

*3 Northern Europe: Denmark, Finland, Sweden, the United Kingdom, and Ireland.*

*4 Central and Eastern Europe: Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovenia, and Slovakia.*

#### **Table 4.**

*Strategy and Behaviors in the Digital Economy*

*Motivations/barriers (driving and impeding factors)*

Lack of fulfillment service

*Sociodemographic predictors*

*Human capital (years of education)*

*Occupational status*

Employees—qualified professionals

Nonemployed—parents/

*Household members*

workers

carers

Employees—nonmanagement

expectation

*Age*

**Users (n = 1792) Providers (n = 496) OR (95% CI) OR (95% CI)**

**1.234 (1.093–1.394)** 1.234 (0.986–1.544)

**2.181 (1.832–2.596)** 1.147 (0.820–1.605)

**1.572 (1.403–1.762) 0.688 (0.539–0.878)**

**0.598 (0.475–0.754)** 0.822 (0.491–1.376)

Price **1.687 (1.505–1.890)** 1.063 (0.860–1.312) Newness 1.094 (0.962–1.245) 1.077 (0.846–1.372) Convenience **2.334 (2.089–2.608)** 0.953 (0.775–1.173) Nonmonetary exchange **0.668 (0.580–0.769) 1.384 (1.062–1.803)** Lack of a responsible person 1.089 (0.973–1.218) **0.747 (0.601–0.929)**

Lack of information 1.055 (0.918–1.212) 0.990 (0.760–1.289) Lack of trust in the agents **1.217 (1.076–1.377)** 1.043 (0.828–1.314) Lack of trust in the Internet **0.878 (0.775–0.994)** 0.973 (0.767–1.236)

15–24 years **1.262 (1.039–1.532)** 0.871 (0.578–1.311) 25–34 years **2.386 (2.077–2.740) 1.436 (1.106–1.866)** 35–44 years **2.097 (1.858–2.367)** 0.989 (0.775–1.262) 45–54 years **1.420 (1.260–1.601)** 0.878 (0.684–1.595) 55–64 years **0.755 (0.680–0.883)** 1.070 (0.815–1.406) 65 years and above **0.246 (0.212–0.286)** 0.727 (0.514–1.028) Gender (1 = male, 0 = female) **1.456 (1.318–1.608) 1.409 (1.144–1.736)**

Still studying **1.536 (1.240–1.903)** 0.887 (0.570–1.381) Up to 15 years **0.170 (0.128–0.226)** 1.224 (0.669–2.237) 16–19 years **0.616 (0.553–0.687)** 0.839 (0.664–1.059) 20 or more years **2.313 (2.088–2.563)** 1.170 (0.943–1.453)

Self-employed/entrepreneurs **1.828 (1.573–2.125) 1.843 (1.391–2.443)** Employees—directors **3.012 (2.575–3.522)** 1.006 (0.746–1.356)

Employees—manual workers **0.781 (0.626–0.974) 1.673 (1.087–2.574)**

Nonemployed—students **1.373 (1.092–1.726)** 0.787 (0.482–1.284) Non-employed—retirees **0.271 (0.237–0.310) 0.718 (0.527–0.977)** Unemployed—job seekers 0.886 (0.680–1.153) 1.330 (0.787–2.247)

One **0.598 (0.524–0.681)** 1.200 (0.915–1.574) Two **1.137 (1.029–1.257)** 0.915 (0.742–1.127)

**172**

*Predictors of P2P platform use and provision in Europe.*

than people with fewer years of education. As far as occupational status is concerned, the self-employed and business people, employees who are directors, employees who are qualified professionals, and employees who are nonmanual workers are the most likely to use collaborative platforms. In contrast, employees who are manual workers, stay-at-home parents/carers, the unemployed and, in particular, retirees are much less inclined toward collaborative consumption via platforms.

Finally, the predictors by geographical area also provide relevant information, firstly, because the impetus behind collaborative consumption comes from large towns/cities and metropolitan areas, whereas living in villages and rural areas would disincentive collaborative consumption via platforms. By country, we also observe a greater likelihood to use collaborative platforms in continental Europe— Belgium, France, Luxembourg, Netherlands, Austria, and Germany—whereas in Mediterranean Europe—Greece, Spain, Italy, Portugal, Cyprus, Malta, and Croatia—the situation is the inverse.

The analysis of predictive factors for the provision of goods and services via collaborative platforms (n = 496) in Europe (**Table 4**) reveals a picture that clearly differs from the use of such platforms. Of the motivational predictors of collaborative provision, the first element to highlight is that such provision has a clearly ideological component, in an antiestablishment or anticapitalism sense, because the possibility of doing nonmonetary exchanges becomes a driving factor. Moreover, nonmonetary exchange was the only provision-driving predictor to be identified, because the other economic and convenience factors were not significant. Regarding the impeding forces, the lack of a responsible person would not disincentive the collaborative provision of goods and services.

From the perspective of the sociodemographic predictors, the collaborative provision of goods and services in Europe would be motivated by a much narrower set of factors than the one identified for collaborative uses. Men, the young population aged between 25 and 34 years, the self-employed or entrepreneurs, or manual workers would be the most likely to make collaborative provisions of goods and services. In contrast, nonmanual workers, retirees, or citizens of countries in northern Europe—Denmark, Finland, Sweden, the United Kingdom, and Ireland would be the least likely to make collaborative provisions.

#### **7. Discussion: new consumer behavior, new economic approaches**

Through an analysis of a representative sample of 14,050 citizens aged 15 years and above in the 28 countries of the European Union in 2016, in this study I have characterized the profiles of users (1792) and providers (496) of collaborative platforms and have identified their motivational and sociodemographic predictors. The main strength of this study is that it provides us with results based on a representative sample of the entire European population; this adds value to the literature because samples that are not representative of the population, or that focus on specific collaborative platforms or consumption, have habitually been analyzed thus far [17, 27, 28]. Two main conclusions were drawn from this analysis.

Firstly, through an odds ratio (OR) analysis, the study obtained a set of forces (motivational and sociodemographic) that are capable of predicting the use and provision of collaborative platforms in Europe. Regarding users, the main driving forces identified were of an economic and practical nature (Hypothesis 2: convenience and price), and the impeding forces would also be situated on this line (Hypothesis 3: lack of fulfillment of service expectations and lack of trust in the Internet). Beyond these results, which are consistent with studies confirming the importance of motivations of practicality and utility in the explanation of the use of collaborative consumption platforms [8, 9, 26, 44], emphasis should be placed on the importance of predictors of a sociodemographic nature (Hypothesis 4). Younger people; men; people living in households with more members; people with more years of education; people within entrepreneurship, managerial responsibility, or highly qualified contexts; people living in large towns/cities or metropolitan areas; and people who are citizens of continental Europe are more likely to engage in collaborative consumption via digital platforms. Given that a number of studies have pointed out that lifestyle is more important than level of income [25], this finding is important because certain sociodemographic profiles were identified that, in population contexts (i.e., in representative samples of the entire population), would incentivize collaborative consumption and behavior.

And secondly, the results obtained for the predictors of the provision of goods and services via collaborative platforms in Europe are clearly different from those for the predictors of use. The first thing to note is that, unlike use—and as some studies have already highlighted [27, 40, 41]—provision has a clearly ideological motivational component (Hypothesis 1). The possibility of doing nonmonetary exchanges is the only predictive provision-driving factor. Among the impeding factors, the lack of a responsible person would not disincentive provision via collaborative platforms. As in the case of users, there is a set of sociodemographic predictors for providers, albeit fewer in number: men, the young population aged between 25 and 34 years, the self-employed or entrepreneurs, or manual workers would be the most likely to make provisions of goods and services. In contrast, nonmanual workers, retirees, or citizens of countries in northern Europe would be the least likely to make such provisions.

Particularly interesting is the identification of categories of specific occupational status that would incentivize or be more sensitive to use and provide P2P collaborative platforms. The self-employed or entrepreneurs would be the most likely to make provisions and uses of goods and services, and this is consistent with

**175**

*Collaborative Behavior and the Sharing Economy: Pan-European Evidence for a New Economic…*

the dual role that research in consumer theory has identified [48]. This result has important implications regarding the management strategy. It is true that management research has identified a group of strategic recommendations for firms that would like to understand and take advantage of the sharing economy [5, 49–51], but literature has not counted occupational status as a predictor. Based on our results, entrepreneurs and self-employed are more prone to value initiatives that are oriented as an alternative of the usual consumption models. Self-employment or entrepreneurship entails a mindset of aspects that firms may desire to attract or promote for some stakeholders. Broadening the set of motivations allows firms to better understand how their stakeholders are more likely or not to be participating in collaborative consumption. Profiles such as entrepreneurs and self-employed have a dynamism that firms may encourage, and understanding how these profiles are motivated is crucial to attack the right people or to develop marketing using the

On the contrary, managers and qualified employees have more practical and monetary motivations, so that they are more sensible to sharing initiatives oriented toward the practical utility of sharing. In this context, knowing the practical and useful motivations of managers and qualified workers is also relevant to the firm strategy, especially for those who choose to develop collaborative platforms more oriented to economic optimization than to alternative exchange and behavior.

However, all this new evidence does not yet address the multidimensional set of factors that would explain the transformations of economic behavior related to the emergence of sharing exchange and P2P markets [34, 38, 52, 53]. In my empirical exercise, we have identified a number of additional sociodemographic motivations, but we still know very little about the effects of collaborative consumption and behavior. For example, what form does the collaborative consumption function take? Does it complement or replace the noncollaborative consumption function? What proportion of total consumption does collaborative consumption represent? How does this new form of consumption affect other aggregates of the economy? What is its multiplier? The search for answers to these questions will

In the meantime, a connection between the conceptual frameworks of the sharing economy should be noted. The salient idea behind this connection is that, through new forms of collaborative consumption and behavior, exchange evolves toward a new interpretative paradigm, from initial digital formats into sharing formats. And for a more adequate interpretation of the sharing exchange theory, the economy will have to move forward and develop a formal apparatus that takes into consideration a set of relatively unusual principles, especially interpretative models that consider a combination of emotional and rational decision-making, individual interest-based as well as prosocial motivations, exchange compensation through a monetary or nonmonetary fee, and the set of sharing economies, that it may generate. In the same way, the business strategy should begin to combine the traditional financial approach to the benefits with the concept of profit, that better

The author appreciates the comments of the participants in the seminars on "The sharing economy in Europe" that the Faculty of Economics and Business of the Universitat Oberta de Catalunya organized on January 11 and 24, 2017, and on January 25, 2018. This research did not receive any specific grant from funding agencies in the

*DOI: http://dx.doi.org/10.5772/intechopen.83608*

undoubtedly set the course of future research.

summarizes the collaborative behavior.

public, commercial, or not-for-profit sectors.

**Acknowledgements**

right strategies.

#### *Collaborative Behavior and the Sharing Economy: Pan-European Evidence for a New Economic… DOI: http://dx.doi.org/10.5772/intechopen.83608*

the dual role that research in consumer theory has identified [48]. This result has important implications regarding the management strategy. It is true that management research has identified a group of strategic recommendations for firms that would like to understand and take advantage of the sharing economy [5, 49–51], but literature has not counted occupational status as a predictor. Based on our results, entrepreneurs and self-employed are more prone to value initiatives that are oriented as an alternative of the usual consumption models. Self-employment or entrepreneurship entails a mindset of aspects that firms may desire to attract or promote for some stakeholders. Broadening the set of motivations allows firms to better understand how their stakeholders are more likely or not to be participating in collaborative consumption. Profiles such as entrepreneurs and self-employed have a dynamism that firms may encourage, and understanding how these profiles are motivated is crucial to attack the right people or to develop marketing using the right strategies.

On the contrary, managers and qualified employees have more practical and monetary motivations, so that they are more sensible to sharing initiatives oriented toward the practical utility of sharing. In this context, knowing the practical and useful motivations of managers and qualified workers is also relevant to the firm strategy, especially for those who choose to develop collaborative platforms more oriented to economic optimization than to alternative exchange and behavior.

However, all this new evidence does not yet address the multidimensional set of factors that would explain the transformations of economic behavior related to the emergence of sharing exchange and P2P markets [34, 38, 52, 53]. In my empirical exercise, we have identified a number of additional sociodemographic motivations, but we still know very little about the effects of collaborative consumption and behavior. For example, what form does the collaborative consumption function take? Does it complement or replace the noncollaborative consumption function? What proportion of total consumption does collaborative consumption represent? How does this new form of consumption affect other aggregates of the economy? What is its multiplier? The search for answers to these questions will undoubtedly set the course of future research.

In the meantime, a connection between the conceptual frameworks of the sharing economy should be noted. The salient idea behind this connection is that, through new forms of collaborative consumption and behavior, exchange evolves toward a new interpretative paradigm, from initial digital formats into sharing formats. And for a more adequate interpretation of the sharing exchange theory, the economy will have to move forward and develop a formal apparatus that takes into consideration a set of relatively unusual principles, especially interpretative models that consider a combination of emotional and rational decision-making, individual interest-based as well as prosocial motivations, exchange compensation through a monetary or nonmonetary fee, and the set of sharing economies, that it may generate. In the same way, the business strategy should begin to combine the traditional financial approach to the benefits with the concept of profit, that better summarizes the collaborative behavior.

#### **Acknowledgements**

The author appreciates the comments of the participants in the seminars on "The sharing economy in Europe" that the Faculty of Economics and Business of the Universitat Oberta de Catalunya organized on January 11 and 24, 2017, and on January 25, 2018. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

*Strategy and Behaviors in the Digital Economy*

would be the least likely to make collaborative provisions.

incentivize collaborative consumption and behavior.

population aged between 25 and 34 years, the self-employed or entrepreneurs, or manual workers would be the most likely to make collaborative provisions of goods and services. In contrast, nonmanual workers, retirees, or citizens of countries in northern Europe—Denmark, Finland, Sweden, the United Kingdom, and Ireland—

**7. Discussion: new consumer behavior, new economic approaches**

Through an analysis of a representative sample of 14,050 citizens aged 15 years and above in the 28 countries of the European Union in 2016, in this study I have characterized the profiles of users (1792) and providers (496) of collaborative platforms and have identified their motivational and sociodemographic predictors. The main strength of this study is that it provides us with results based on a representative sample of the entire European population; this adds value to the literature because samples that are not representative of the population, or that focus on specific collaborative platforms or consumption, have habitually been analyzed thus far [17, 27, 28]. Two main conclusions were drawn from this analysis.

Firstly, through an odds ratio (OR) analysis, the study obtained a set of forces (motivational and sociodemographic) that are capable of predicting the use and provision of collaborative platforms in Europe. Regarding users, the main driving forces identified were of an economic and practical nature (Hypothesis 2: convenience and price), and the impeding forces would also be situated on this line (Hypothesis 3: lack of fulfillment of service expectations and lack of trust in the Internet). Beyond these results, which are consistent with studies confirming the importance of motivations of practicality and utility in the explanation of the use of collaborative consumption platforms [8, 9, 26, 44], emphasis should be placed on the importance of predictors of a sociodemographic nature (Hypothesis 4). Younger people; men; people living in households with more members; people with more years of education; people within entrepreneurship, managerial responsibility, or highly qualified contexts; people living in large towns/cities or metropolitan areas; and people who are citizens of continental Europe are more likely to engage in collaborative consumption via digital platforms. Given that a number of studies have pointed out that lifestyle is more important than level of income [25], this finding is important because certain sociodemographic profiles were identified that, in population contexts (i.e., in representative samples of the entire population), would

And secondly, the results obtained for the predictors of the provision of goods and services via collaborative platforms in Europe are clearly different from those for the predictors of use. The first thing to note is that, unlike use—and as some studies have already highlighted [27, 40, 41]—provision has a clearly ideological motivational component (Hypothesis 1). The possibility of doing nonmonetary exchanges is the only predictive provision-driving factor. Among the impeding factors, the lack of a responsible person would not disincentive provision via collaborative platforms. As in the case of users, there is a set of sociodemographic predictors for providers, albeit fewer in number: men, the young population aged between 25 and 34 years, the self-employed or entrepreneurs, or manual workers would be the most likely to make provisions of goods and services. In contrast, nonmanual workers, retirees, or citizens of countries in northern Europe would be the least likely to make such provisions. Particularly interesting is the identification of categories of specific occupational status that would incentivize or be more sensitive to use and provide P2P collaborative platforms. The self-employed or entrepreneurs would be the most likely to make provisions and uses of goods and services, and this is consistent with

**174**
