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The TQM Journal
Carpooling: travelers’ perceptions from a big data analysis
Maria Vincenza Ciasullo, Orlando Troisi, Francesca Loia, Gennaro Maione,
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Maria Vincenza Ciasullo, Orlando Troisi, Francesca Loia, Gennaro Maione, (2018) "Carpooling:
travelers’ perceptions from a big data analysis", The TQM Journal, https://doi.org/10.1108/
TQM-11-2017-0156
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Carpooling: travelers’perceptions
from a big data analysis
Maria Vincenza Ciasullo and Orlando Troisi
Department of Business Science –Management and Innovation Systems,
University of Salerno, Salerno, Italy
Francesca Loia
Department of Management, Sapienza University of Rome, Rome, Italy, and
Gennaro Maione
Department of Business Science –Management and Innovation Systems,
University of Salerno, Salerno, Italy
Abstract
Purpose –The purpose of this paper is to provide a better understanding of the reasons why people use or
do not use carpooling. A further aim is to collect and analyze empirical evidence concerning the advantages
and disadvantages of carpooling.
Design/methodology/approach –A large-scale text analytics study has been conducted: the collection of
the peoples’opinions have been realized on Twitter by means of a dedicated web crawler, named “Twitter4J.”
After their mining, the collected data have been treated through a sentiment analysis realized by means
of “SentiWordNet.”
Findings –The big data analysis identified the 12 most frequently used concepts about carpooling by
Twitter’s users: seven advantages (economic efficiency, environmental efficiency, comfort, traffic,
socialization, reliability, curiosity) and five disadvantages (lack of effectiveness, lack of flexibility, lack of
privacy, danger, lack of trust).
Research limitations/implications –Although the sample is particularly large (10 percent of the data
flow published on Twitter from all over the world in about one year), the automated collection of people’s
comments has prevented a more in-depth analysis of users’thoughts and opinions.
Practical implications –The research findings may direct entrepreneurs, managers and policy makers to
understand the variables to be leveraged and the actions to be taken to take advantage of the potential
benefits that carpooling offers.
Originality/value –The work has utilized skills from three different areas, i.e., business management,
computing science and statistics, which have been synergistically integrated for customizing, implementing
and using two IT tools capable of automatically identifying, selecting, collecting, categorizing and analyzing
people’s tweets about carpooling.
Keywords Sentiment analysis, Twitter, Fuzzy logic, Big data analysis, Carpooling
Paper type Research paper
1. Introduction
Nowadays, the travel sector is the driving force of many industrialized economies, capable of
contributing heavily to the development of any country (Orlikowski and Scott, 2013).
However, as with other sectors, travel has suffered a crisis from the beginning of the new
millennium, especially in those countries not properly ready for the technological upgrading
that has penetrated all kinds of markets (Lee, 1980). In recent years, in spite of the timid
economic recovery, the travel sector has become a protagonist of a new impetus due to the
emergence of the recognition of the need for a massive private sector reorganization. In fact,
positive data have emerged with particular emphasis on sustainable travel alternatives.
These are being promoted for reasons not only related to economic aspects but also because
they offer opportunities for providing concrete answers to various issues that have, for years,
been affecting the entire travel sector including inter alia, traffic congestion, high accident
rates, harmful emissions into the atmosphere and noise pollution (Ciasullo et al., 2017;
Díaz-Méndez et al., 2017; Ferreira Rebelo et al., 2014).
The TQM Journal
© Emerald Publishing Limited
1754-2731
DOI 10.1108/TQM-11-2017-0156
Received 21 November 2017
Revised 5 January 2018
Accepted 5 January 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1754-2731.htm
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These issues highlight both the ineffectiveness of previous public policies in responding to
the real needs of citizens (Baccarani and Bonfanti, 2015; Baccarani and Golinelli, 2011), on the
shifting focus of scholars, policy makers and entrepreneurs on the importance of making
the travel sector more oriented to the concept of sustainability in its broadest sense
(Douglas, 2015): in this context, from a purely environmental point of view, being sustainable
means reducing air and noise pollution (McKinnon et al., 2015; Golinelli, 2012); from an energy
utilization viewpoint, the objective of sustainability is to direct choices toward the use of
renewable sources (Franzitta et al., 2016); economic sustainability, on the other hand, favors
the use of relatively low tariffs (Lippiatt, 2000); whilst from a social perspective (Partridge,
2014), the goal is to ensure the same opportunities for mobility to anyone, including people
with impaired movement such as pregnant women or disabled people.
In the light of this, especially in recent years, the policies adopted at various government
levels, increasingly focused on the involvement of many actors (Mele and Polese, 2011) and
on the active participation not only of service providers but also of users (Polese et al., 2017;
Barile and Polese, 2010a, b; Maione et al., 2017), are gradually encouraging citizens to use
mass travel services such as trains, buses, trams and so on as well as shared transport
services such as bike sharing, car sharing and carpooling.
This approach aims to stimulate urban-territorial recovery and development through the
implementation of sustainable and intelligent travel systems based on cutting-edge ICT
(apps, web platforms, etc.) (Barile et al., 2017). This will help to improve the balance between
transport supply and demand and bring significant benefits in terms of both efficacy and
efficiency across the entire travel sector.
Despite this growing focus on travel sustainability, there are no contributions within the
extant academic literature which deal with the topic utilizing a very large sample of
travelers. This paper aims to fill that gap and enhance understanding of the actual reasons,
as stated by travelers themselves, for their resorting to alternative travel arrangements,
with particular emphasis on carpooling. To this end, the paper is structured in five sections:
first, it opens with a broad discussion of the reference literature, aimed at providing a
sufficiently exhaustive conceptual representation of carpooling, its evolution and various
forms spread over time throughout the world; then the big data collection and analysis
methodology is described; next the results of the analysis are described and the possible
implications discussed under both theoretical and practical profiles; and finally the
conclusions of the paper are presented along with the limitations of the study and ideas for a
future research agenda.
2. Literature review: the growth of carpooling
In recent years, there has been more and more emphasis on ensuring a high quality of life
for people alongside the development and subsequent diffusion of innovative technologies.
This has shifted the focus from the managerial strategies aimed at pursuing the
achievement and maintenance of high levels of efficacy and efficiency to those that also
promote respect for the concept of sustainability (not only environmental but also energy,
technological, social and economic).
In this regard, there are numerous studies, including the travel sector, highlighting a
mature awareness of the benefits arising from the adoption of sustainable practices: the
prevalent literature orientation emphasizes that more and more frequently every kind of
material and immaterial (economic, financial, human, cognitive, temporal and so on)
resources are invested in the development of strategies based on techniques, methods
and tools designed to improve overall results of citizens’choices about urban and
extra-urban mobility.
In this scenario, carpooling is one of the most valid solutions to solve many of the
issues of the travel sector (Ben-Akiva and Atherton, 1977). According to Dewan and
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Ahmad (2007), carpooling defined as the sharing of rides in a private vehicle involving two
or more individuals, represents the easiest and most common vehicle sharing
arrangement. Carpooling can be seen as an alternative and relatively new method of
travel where a person provides a vehicle (which he/she usually owns) and transports
one or more people to their destination in exchange for a pre-agreed amount of money
(tariff, rate or fee) (Chen and Hsu, 2013).
The most rudimentary form of this phenomenon dates back to the first years following
the Second World War. Although, in that period, the reasons for choosing to share means of
travel were mostly associated with the aftermath of war. In the 1970s, mainly because of the
oil crisis, the use of carpooling was given a new lease of life (Oliphant and Amey, 2010)
before falling out of favor again until the beginning of the new millennium. However, recent
technological developments and, more specifically, the affirmation of the internet and the
pervasive use of mobile devices (tablets and smartphones primarily), have given new
impetus to carpooling, leading to a level of uptake that in some countries exceeds 10 percent
of the total journeys made by motor vehicles (Chan and Shaheen, 2012). To date, the practice
of sharing a car is used in the countries of Northern Europe and in the USA, where specific
associations exist and the practice is also encouraged by road signs, indeed, in some USA
cities, motorway lanes have been set aside specifically for cars carrying more than one
person. These lanes are less congested and lead to faster journey times. It is increasingly
becoming a widespread mode of travel, especially in working or university environments,
where people traveling the same route at the same time spontaneously agree to travel
together and so reap the benefits from such a choice. One of the main conditions to be
respected in carpooling is the existence of at least two persons: the car’s owner and the
passenger. This condition is fundamental in distinguishing carpooling from other
similar, but different, forms of vehicle sharing. In particular, carpooling should not be
mistaken, or considered synonymous, with car sharing. They are different phenomenon.
Carpooling implies the sharing of a car among private individuals, whereas car sharing is a
membership-based service available to all qualified drivers in a community. All members
have access to a network of vehicles owned by a company that offers such a travel service.
(Car Sharing Association: http://carsharing.org/what-is-car-sharing/).
Over time, carpooling has taken on several connotations, very similar to each other but
different for a number of reasons, such as the type of users, the technology used,
the territorial context, the sector (public or private), the number of vehicles involved, etc.
(Bento et al., 2013). To date, among the most common forms of this alternative travel system,
there are dynamic, informal and flexible carpooling.
2.1 Dynamic carpooling
Dynamic carpooling has been defined by Arnould et al. (2011) as a particular form of
travel sharing aimed at offering a planning solution capable of reacting in real time to any
additional driver or passenger joining or leaving the “pool”of carpoolers. This implies
keeping in mind all events that could affect travel, such as traffic congestion, incidents,
accidents, roadworks and so forth. Dynamic carpooling probably dates back to the early
1990s, but it has been successful only since 2012. As Friginal et al. (2014) reported, recent
studies carried out in China (Xin et al., 2009) have underlined an increasing interest in
dynamic carpooling solutions, highlighting financial savings and traffic reduction as its
main advantages. It is characterized by the possibility of organizing specific routes
suddenly in exchange for the payment of a certain amount of money, thanks to the use
of a mobile device with GPS and connected to a social network (Mallus et al., 2017).
Dynamic carpooling, a novel social-inspired service that offers users the chance to easily
share a vehicle (Friginal et al., 2014), is also known as real-time ridesharing, on-demand
ridesharing, instant ridesharing and ad hoc ridesharing (Amey et al., 2011). Its diffusion is
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strongest in areas where traditional transport services (buses, trains, trams, taxis and so
on) are inadequate with respect to demand. What characterizes this form of carpooling
more than anything else is the tendency to resort to it only in times of urgency or
emergency, since for planned or cyclic needs, it is cheaper to use alternative travel
systems (Créno, 2016). In this regard, Massaro et al. (2009) reported that dynamic
carpooling challenges traditional carpooling restrictions by allowing a large membership
base of passengers and drivers to be matched with each other automatically in real time,
allowing for on-the-spot arrangement of rides. The latest dynamic carpooling systems
also provide the chance for users to travel a route using more than one vehicle. However,
this mode of travel, though potentially comfortable, is not achieving the hoped-for success
(Grgurevićet al., 2015).
2.2 Informal carpooling
Informal carpooling (also known as casual carpooling or slugging) is a form of carpooling
developed in the mid-1970s in order to meet the multiple needs of both passengers and
drivers (Chan and Shaheen, 2012). Indeed, the former can benefit from the opportunity to
reach a given destination for free or by paying a price lower than those charged by
traditional travel systems; drivers, on the other hand, because they are carrying more
people on board, have access to dedicated lanes specifically set aside by some local
governments (especially in the USA and Canada) to help minimize road congestion and
contribute to the reduction of atmospheric pollution (Masoud and Jayakrishnan, 2017).
However, it is worth pointing out that slugging was, and remains, an alternative travel
service organized and entirely operated by private individuals. The main motive
inducing people to offer an informal carpooling service is the ability to save time rather
than earn money. This aspect, along with the fact that they are used especially during
the morning, represents the characteristic that distinguishes it from other forms of
carpooling (Badger, 2011). As reported by Masoud and Jayakrishnan (2017), this form
of carpooling is usually pre-arranged and occurs between people who share things in
common other than the time and location of their trips. In this regard, Mote and
Whitestone (2011) have pointed out that the adoption of slugging has grown due to the
opportunity to fulfill the requirements of lanes on an informal basis, that is, without
coordinating and arranging the requisite number of passengers on a daily basis: to begin
slugging is very simple, since no registration or prior arrangements are required and
people typically learn about slugging through friends and co-workers ( by means of word
of mouth).
2.3 Flexible carpooling
Flexible carpooling is a form of carpooling started in the early 1980s (Chan and
Shaheen, 2012). It is halfway between dynamic carpooling and informal carpooling. In fact,
it implies the formal definition of routes that can be taken by drivers but without specifying
the departure or arrival time (Beroldo, 1990). In other words, users can benefit from this
alternative form of travel by going to a given meeting point where they can offer or receive
passage. Hence, the main advantage of flexible carpooling is the possibility of getting a car
ride in a certain direction without having to organize it in advance (Dorinson et al., 2009).
According to Minett (2009), the key feature of flexible carpooling is the absence of the need
for pre-arrangement on a trip-by-trip basis: people arrive at a meeting place and fill cars in
order of arrival, i.e., on a first-come-first-served basis. In the informal systems, rides are
offered and taken without a pre-registration process and without money changing hands.
Therefore, this form of carpooling is well-suited to the circumstances in which the need for
passage is manifested at the last moment. As Minett et al. (2008) have observed, flexibility
provides people with three main benefits: first, they can get into another user’s vehicle or
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allow another participant to get into their car; second, they can participate as both driver
and passenger, and switch at will each day between riding and driving; and third, they can
arrive to use the system at different times day-to-day. However, because of this greater
flexibility, it may be necessary to wait a long time at the meeting point before the user can
find an available vehicle or she/he may even wait in vain for its arrival (Shaheen et al., 2016;
Kelly, 2007). Therefore, flexible carpooling can be considered an emergency travel system as
it is impossible to rely on it with absolute certainty (Minett et al., 2008).
3. Research design
A large-scale text analytics study has been conducted with the main aim of understanding
the real motives pushing people to use innovative travel systems and in particular,
carpooling. The collection of users’opinions was realized via a specific social network
community named “Twitter.”Twitter was chosen due to its high popularity –in 2012, more
than 100 million users posted about 340 million tweets a day[1] and the service handled an
average of 1.6 billion search queries per day. In order to avoid interpretative distortions of
the comments posted by Twitter users, the analysis was performed over the course of a
12-month period, from the beginning of October 2016 to the end of October 2017. The reason
for such a long time span is that performing a big data analysis in a short time span could
see the emergence of results biased by specific factors such as the month, the season
(summer, autumn, winter and spring), the weather and so forth.
3.1 Data mining
The process of data collection has been realized by means of a web crawler named
Twitter4J. It allowed data to be gathered in nearly real time as background activity. It is
based on the use of API, which provided access to the public accounts on the chosen virtual
community (Twitter). Specifically, the data collection has been performed by establishing
and then implementing specific filters in order to identify all Twitter users’comments
including the hashtag #carpooling. The hashtag can be defined as a string of characters
preceded by a hash (#) character (Tsur and Rappoport, 2012) used to synthesize in a single
word a concept which is described later in 280 or less characters (see Figure 1).
Specifically, the crawler has taken into account only the tweets containing #carpooling
and has allowed the identification, selection, gathering and classification of lots of words,
thus obtaining a classification capable of highlighting many keywords connected to the
considered phenomenon, which, once analyzed, allowed understanding of the reasons why
people used or did not to use carpooling. Subsequently, a further screening of the extracted
words was made to avoid some of them complicating the interpretation of the results.
For instance, the crawler has automatically ignored individual letters, definite and indefinite
articles (a, an, the), prepositions ( from, by, with and so on) and other terms that, taken
individually, would not help in any way the understanding of the findings.
3.2 Data analysis
After mining, the collected data went through a sentiment analysis using software called
“SentiWordNet.”This is a lexalytics text mining tool (Ohana and Tierney, 2009;
Denecke, 2008) that enables the identification of people’s perceptions on a particular topic,
allowing understanding of the overall polarity of a set of words (Hung and Lin, 2013; Esuli and
Sebastiani, 2007). The most frequently used words identified and extracted in the previous
stage were passed to the submodule responsible for the sentiment check. Specifically, for each
word, the adjectives and expressions related to it were checked against a lexicon annotated
with sentiment values in order to establish their potential positive, negative or objective
value (Baccianella et al., 2010a, b). The submodule has returned, for each adjective/expression,
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values in the (0-1) range that represent the adjective/expression’s positivity, negativity, or
neutrality, whose sum total is 1. As such, for the i-th word, its corresponding positivity (Sp
i
),
negativity (Sn
i
)orneutrality(S
u
) values have been computed as follows:
Spi¼
P
K
k¼1
pk
K
Sni¼
P
K
k¼1
nk
K
Sui¼
P
K
k¼1
uk
K
where Kis the total number of adjectives/expressions found and evaluated, and p
k
,n
k
and u
k
are the kth positivity, negativity and neutrality value, respectively, for the
kth adjective/expression.
Source: https://twitter.com
Figure 1.
Screenshot of users’
comments with the
hashtag #carpooling
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Then, in order to evaluate the collective perception related to a single word, a fuzzy
inference system (FIS) (Guillaume, 2001) was used to obtain the value of the CP starting
from the sentiment scores Sp
i
,Sn
i
and S
u
of the word computed by the SDA module with the
formulas previously described. Such scores represent the inputs of the FIS and their
membership functions are reported in Figure 2. The FIS obtains a value for the collective
perception by “defuzzifying”the output (Kasabov and Song, 2002; Jang, 1993). The CP
value helps with the estimation of the community’s perception about the analyzed word
and with the understanding of the benefits and disadvantages felt by people (Chang and
Chang, 2006).
4. Findings
Overall, thanks to Twitter4J, about 10 percent of the data flow published on Twitter by
users from all over the world was analyzed. In order to provide an answer to the research
goal, only tweets containing the hashtag #carpooling were collected. This filter enabled the
consideration of about one million tweets (exactly 993,778) within which about 10,000 (9,342)
different words were automatically identified. Figure 3 shows a word cloud containing the
terms most frequently used by Twitter users in their posts about #carpooling, without
considering stopwords: the size of the words represented in the figure is directly
proportional to the number of times that they have been extracted by the web crawler.
To avoid interpretive distortions, the most widely used words were grouped into
categories (concepts) based on the affinity of their meanings. This action allowed the
identification of 12 main concepts, as shown in Table I.
Finally, the sentiment analysis enabled positive and negative concepts to be
distinguished, as shown in Tables II and III.
5. Discussion
5.1 Carpooling advantages
Economic efficiency. The results show that, regardless of what the theory in the literature
stated, the main reason why people resort to carpooling is the economic savings. In line with
what Chen and Hsu (2013) and Yang and Huang (1999) have pointed out, carpooling is an
alternative travel system that, besides lowering the tariff, also allows the minimization of a
Source: Authors’ elaboration
Low Medium High
Mean of positive scores Ver y
bad Bad Neutral Positive Ver y
positive
CP
Mean of neutral scores
Mean of negative scores
1
1
1
P
O
N
Figure 2.
Fuzzy variables and
membership of the
FIS for computing the
collective perception
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series of other costs associated with the use of motor vehicles, such as fuel, oil, tires, tolls,
parking and so forth Therefore, the success of carpooling seems to be due to the advantage
of ensuring an opportunity to save money not only to drivers but also to passengers. In this
respect, the analysis showed 8,957 tweets containing comments related to the concept of
“economic efficiency,”demonstrating people’s primary interest in carpooling was spending
less than they needed to spend to use traditional travel systems (trains, buses, trams, taxis,
private cars and so forth) (Shewmake, 2012).
Environmental efficiency. According to the findings, environmental efficiency is the
second most cited reason for people to use carpooling as a healthy alternative travel system.
The reading of the 8,835 comments posted by people on Twitter, in fact, emphasizes the
great attention paid to environmental issues. This growing interest derives from feeling an
increasingly need to counteract the dangerous effects of climate change that in recent
years has caused serious ecological, e.g., the melting glaciers caused by global warming
(Schipper and Pelling, 2006). This aspect, along with the inexorable depletion of traditional
natural resources (among which, primarily, fossil fuels such as oil) and the unstoppable
increase in demand for services by the world’s population, is increasingly emphasizing the
need to define and adopt business models that are efficient not only from an economic point
of view but also from a purely environmental point of view (Schaltegger and Wagner, 2017;
Tate et al., 2013). In this perspective, users are well aware that a reduction in the number of
cars on the roads will help to protect the environment and help to reduce air pollution.
In this regard, Vlek and Steg (2007) underline that this enhanced awareness among
consumers about the importance of respecting the environment is orienting market demand
toward sustainable lifestyles. Consistently, Amel et al. (2009) and Arbuthnott (2009)
highlight how, in current market contexts, increasingly characterized by consumerism,
indiscriminate waste, and uncontrolled exploitation of natural resources, healthy alternative
travel systems represent a winning strategy for achieving and maintaining a successful
impact in the long run.
Comfort. This is the third place most cited reason that consumers use carpooling:
comfort. Indeed, it emerges from the 7,971 tweets collected and analyzed from those that use
an innovative travel system based on the use of the latest generation of mobile devices that
Source: Authors’ elaboration
Figure 3.
The most used words
in the tweets with the
hashtag #carpooling
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carpooling makes the travel experience much less stressful and easier. In this regard,
numerous contributions can be found in the extant literature (Balcombe et al., 2009; Spake
et al., 2003) reporting the importance of comfort in influencing consumers’buying behavior.
The influence of comfort on consumer choices seems to be even greater in the travel sector,
where people prefer to be transported in comfort (Southward, 2015; Neumann et al., 1978).
Word Concept
Saving (3,189)
Money (2,122)
Moneysaving (2,110)
Savings (188)
Efficiency (825)
Efficient (523)
Economic efficiency (8,957)
Sustainability (3,128)
Air pollution (2,110)
Smog (1,100)
Health (1,099)
Nosmog (1,053)
Environmentalism (345)
Environmental efficiency (8,835)
Comfort (2,316)
Comfortable (2,080)
Coziness (1501)
Cozy (1,275)
Comforting (589)
Cosiest (210)
Cosy (158)
Comfort (7,971)
Traffic (2,214)
Congestion (1,894)
Traffic (4,108)
Socialize (958)
Relationships (714)
Socialization (658)
Friendship (579)
Socialization (2,909)
Effectiveness (879)
Effective (522)
Efficacy (111)
Efficacious (102)
Effectiveness (1,614)
Flexibility (588)
Flexible (215)
Suppleness (197)
Elasticity (119)
Flexibility (1,119)
Reliability (451)
Reliable (422)
Dependable (202)
Reliability (1,075)
Privacy (1,038) Privacy (1,038)
Danger (521)
Dangerous (122)
Risk (69)
Risky (55)
Danger (767)
Curious (320)
Curiosity (225)
Inquisitiveness (44)
Curiosity (589)
Trust (321)
Confidence (115)
Confident (102)
Trustful (44)
Trust (582) Table I.
The most used
concepts within tweets
about #carpooling
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Traffic. According to the big data analysis carried out, carpooling is one of the most
effective travel systems for reducing urban and extra-urban traffic, since the availability of
more seats (typically from two to seven) in the same car positively affects the number of
vehicles in circulation and contributes to a reduction in road congestion (Matsoukis, 2006).
Several studies (Ma et al., 2016; Patriksson, 2015; Sonnenberg et al., 2013; Buchanan, 2015;
Bryant et al., 2004) underline the importance of traffic as a variable capable of influencing
public opinion (especially those of daily commuters) on a particular travel system.
Socialization. As predicted (Baslington, 2008; Shim et al., 2005), socialization is among the
most important factors for stimulating carpooling. Socialization happens because the
sharing of the same means of travel allows the establishment of social relationships between
unknown people, stimulating the start-up and development of processes that are linked to
the framework of the sharing economy (Matos et al., 2014; Haustein et al., 2009). In this
regard, as stated in the tweets, socialization seems to be fostered by the opportunity for
passengers to share time with strangers randomly and, if desired, by the possibility to
choose from various available alternatives, the driver who theoretically, has more features
more compatible with their own personality. To this end, as pointed out by Selker and
Saphir (2010), many carpooling platforms are based on special algorithms able to suggest
users with whom there could be greater character compatibility in order to make the travel
experience more enjoyable. In this case, socialization is stimulated by the use of special
technologies, which, based on a series of personal information (such as gender, age, work,
hobbies, musical tastes, religion, literary interests, sports and so on) promote the birth of
relationships between people who use carpooling.
Technological reliability. Although it cannot be identified as one of the most important
reasons cited by people for using carpooling, the reliability of this travel system is still an
element that can contribute decisively to its popularity. In fact, in many of the 1,614 tweets
collected and analyzed, it is clear that users are quite satisfied with the technology
underlying the service, considering it to be sufficiently reliable, albeit, improvable. In fact,
lots of positive comments reveal a high level of users’satisfaction, which, through the
technological devices owned by anyone (such as smartphones, tablets, laptops, etc.) can
effectively and efficiently take advantage of the travel service. Technology reliability,
Ranking Concepts
1st Economic efficiency (8,957)
2nd Environmental efficiency (8,835)
3th Comfort (7,971)
4th Traffic (4,108)
5th Socialization (2,909)
6th Reliability (1,075)
7th Curiosity (589)
Table II.
Ranking of the
positive concepts
expressed with regard
to #carpooling
Ranking Concepts
1st Effectiveness (1,614)
2nd Flexibility (1,119)
3th Privacy (1,038)
4th Danger (767)
5th Trust (582)
Table III.
Ranking of the
negative concepts
expressed with regard
to #carpooling
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though it is only ranked sixth (after economic efficiency, environmental efficiency, comfort,
traffic and socialization) can be understood as the main benefit without which the other
advantages of carpooling would not exist (Fink et al., 2015; Cioppi, 2013).
Curiosity. Curiosity is ranked last of the motives triggering the success of carpooling.
However, this data are not consistent with the results from other studies (Park et al., 2015;
Foulds, 2014; Hill and McGinnis, 2007) where it is reported to be one of the main factors for
stimulating and orientating consumer behavior and choices. However, a plausible
explanation for this disagreement may be represented by the consumer’s tendency to
express judgment on a specific service only after having been used it, and by then any
curiosity might be already largely fulfilled and, therefore, no longer particularly considered
by users.
5.2 Carpooling disadvantages
Effectiveness. Among the most negative feelings about carpooling, ineffectiveness of the travel
service as a whole was the most cited: in many countries, the decision of local governments to
allocate preferential lanes for vehicles adhering to carpooling, although bringing benefits to the
users of this alternative travel system (Manzini and Pareschi, 2012), it also restricts the
space available to other vehicles. This caused problems such as the risk of a more congestion,
higher fuel consumption and the worsening of air pollution (Calvo et al., 2004).
Flexibility. Although, from its conception, carpooling has been acknowledged as a
highly flexible travel system, in practice results from the big data analysis have shown
high levels of dissatisfaction due to people being unable to make the service fit their needs
and expectations. Indeed, regardless of the technology implemented to facilitate the
operation characterizing the service as a whole, carpooling involves the necessary users’
availability to be flexible, since it encourages them to come to an agreement with an
unknown person to establish timing, route and fare (Li et al., 2007). This limit is less
evident in “flexible carpooling,”so called precisely because it does not require the prior
specification of the starting or arrival time,butonlyoftheroutesrunbyeachvehicle
(Dorinson et al., 2009).
Privacy. Like many other multiuser services, carpooling also implies the need for users to
sign up to the web platform, enabling their identification, the electronic traceability of their
information and leave feedback after using the alternative travel experience. However,
this inevitable action, while allowing minimal information about the actors involved
in the delivery and enjoyment of the service, on the other, entails privacy concerns
(Kladeftiras and Antoniou, 2015). In fact, as in any form of resource sharing, the private
sphere of people mixes with that one of other users, who, for example, can easily find
themselves in the position of listening to a phone call received or made by another passenger
or by the driver (Aïvodji et al., 2015; Friginal et al., 2014).
Danger. Danger, closely related to privacy, is another highly discussed issue about
carpooling. In fact, 767 tweets have made comments that show the existence of concerns by
individuals about their own safety inthe enjoyment of service shared with strangers. However,
such data needs to be analyzed more deeply, because at least until now, crimes linked to the
carpooling phenomenon are rare and, in any case, no more numerous than those occurring
with the traditional travel services (taxis, buses, trains and so on) (Minett et al., 2008).
Trust. Trust is among the top five reasons why people say they do not resort to
carpooling. As noted in the 582 comments posted by Twitter users, though all those who
intend to use the platform have to preventively sign up and the transactions made through
the platform are automatically traced, this is in any case a service shared with and between
unknown people, whom carpooling users voluntarily choose to spend a varying amount of
time with depending on the route.
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6. Theoretical implications
This paper might be considered useful to academics, since it attempts to foster a greater
awareness about the benefits and disadvantages arising from the use of one of the most
widespread alternative travel systems, carpooling.
From a purely theoretical viewpoint, the work offers some insights into the importance of
big data analysis for understanding what people really think about a given phenomenon.
Specifically, the paper tries to overcome the limiting feature of many contributions
dedicated to carpooling, that of a rather small sample of subjects. Indeed, big data analysis
allows for a more complete view of the phenomenon under study (Sagiroglu and Sinanc,
2013) highlighting not only its advantages but also its disadvantages: analyzing a large
amount of data means additional information can be extracted not normally obtainable from
a small sample, thus ensuring greater reliability and better generalization of the results.
Another interesting and useful theoretical insight for scholars is the application of fuzzy
logic to sentiment analysis. This approach to understanding peoples’opinions, though not
much used in management studies, actually offers many benefits, since it allows for a more
weighted and valid view of the topic being studied. In fact, the FIS, by means of “If-Then”
language rules, allows better understanding not only whether a concept expressed by a
person is positive, neutral, or negative, but also the degree of positivity or negativity. In
order to answer the research question, skills from three different areas, business
management, computing science and statistics, have been synergistically integrated for
customizing, implementing and using two IT tools (“Twitter4J”and “SetiwordNet”) capable
of identifying, selecting, collecting, categorizing and analyzing automatically people’s
tweets about carpooling. This way of working could suggest to scholars, not only interested
in management but also in any other scientific discipline, the importance of conducting
research by following a multidisciplinary approach to the study of a phenomenon, especially
whether it is relatively recent or completely new (Loia et al., 2017).
7. Practical implications
From a practical standpoint, this paper offers insights that might prove useful to the various
actors involved in business dynamics. In particular, the paper might encourage
entrepreneurs, managers and policy makers to reflect on actions to be taken to take
advantage of all the potential benefits that carpooling offers. In this regard, the work
highlights the 12 mostly considered variables, ranking them in order of occurrences,
allowing those who have invested or intend to invest in carpooling to know which aspects to
pay most attention. For example, based on the feedback provided by Twitter’s users, it is
useful to point out that the first variable to be considered in managing an alternative travel
service is almost certainly economic efficiency: it is not possible to think of investing in this
innovative and complex system without taking into account the considerable sensitivity of
potential and current users to the opportunity for saving money.
However, although saving money is the main reason for inducing people to use
carpooling (Bento et al., 2013), there are several other aspects that are important, such as
environmental efficiency, comfort, traffic, socialization, reliability of the travel system and
curiosity. This is an interesting result, especially given the current period of deep global
financial crisis, in which, very often, the only variable impacting consumers’buying
decisions is financial and whether or not they will save money. This trend is confirmed in
the context of urban travel, where frequently the choices between different travel
alternatives appear to be influenced mainly by the amount of money it will save consumers
if they change (De Grange et al., 2013).
However, the deep commitment of practitioners is necessary to promote the spread of
carpooling: there are still many perplexities and doubts about the effectiveness and
flexibility of this travel system. In addition, in order to induce people to rely on carpooling
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services, it seems necessary to be able to minimize the issues related to privacy protection
and the perception of the danger of traveling with strangers. In other words, it is necessary
to overcome the initial mistrust of carpooling before users (both drivers and passengers)
can develop full confidence in it.
In fact, as highlighted by (Minett et al., 2008; Minett, 2009), the question of safety is important
and of great interest to people when they first hear about carpooling. Mote and Whitestone
(2011) have also pointed out that getting up the courage to use carpooling for the first time is
often mentioned by carpoolers as the most difficult part of the travel system, but once that is
accomplished, they gradually acquire greater information about the best way to use it.
To this end, the intervention of public institutions could be useful (Polese et al., 2016;
Brennan and Douglas, 2002, 1998), if they adopted policies aimed at giving concrete support
to the spread of carpooling (e.g. through promotional and advertising campaigns, road
feasibility studies, test projects, etc.). Such policies may help to persuade people to increase
their trust in this alternative travel system (Dewan and Ahmad, 2007).
Finally, as discussed above, it is worth pointing out that worries about the risks linked to
the use of carpooling are not properly and completely justifiable, since, at least until now,
crimes linked to the carpooling phenomenon are rare and indeed no more frequent than
crimes occurring on traditional travel services (taxis, buses, trains and so on). Indeed, no
reports of rapes or assaults associated with casual carpooling exist (Minett et al., 2008).
8. Concluding remarks
The results of the work provide empirical evidenceabouttheexistenceofatleastseven
good reasons why people resort to carpooling and five motives pushing them to do not use
it. However, beyond what has emerged from the survey, it is worth pointing out that qthe
analysis has a limit that could make the findings questionable. In fact, although the
sample was particularly large (10 percent of the data flow published on Twitter from all
over the world in about one year), the automated collection of people’s comments has
prevented from going deeper in the analysis of users’complete thought. Such a weakness
could induce to perform a further analysis about the same topic to compare the results
emerged from this study with the findings that could arise by using a qualitative approach
(such as in-depth interviews).
Note
1. https://blog.twitter.com/official/en_us/a/2012/twitter-turns-six.html
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Further reading
Dakroub, O., Boukhater, C.M., Lahoud, F., Awad, M. and Artail, H. (2013), “An intelligent carpooling
app for a green social solution to traffic and parking congestions”,16th International IEEE
Conference on Intelligent Travelation Systems, IEEE, pp. 2401-2408.
Ferreira, J., Trigo, P. and Filipe, P. (2009), “Collaborative carpooling system”,World Academy of
Science, Engineering and Technology, Vol. 3 No. 6, pp. 683-687.
Gaur, S.S., Madan, S. and Xu, Y. (2009), “Consumer comfort and its role in relationship marketing
outcomes: an empirical investigation”, in Samu, S., Vaidyanathan, R. and Chakravarti, D. (Eds),
Asia-Pacific Advances in Consumer Research, pp. 296-298.
McKenzie-Mohr, D. (2000), “Fostering sustainable behavior through community-based social
marketing”,American Psychologist, Vol. 55 No. 5, pp. 531-537.
Corresponding author
Maria Vincenza Ciasullo can be contacted at: mciasullo@unisa.it
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