Exploring Consumer Perceptions of Rating Mechanisms in Shared Economy

This project explores the perceptions of customers on rating mechanisms used by shared economy platforms. It identifies existing rating mechanisms, evaluates their pros and cons, and analyzes consumer usage patterns and preferences regarding shared economy platforms like Uber and AirBnB. The study aims to understand how rating systems influence consumer choice and trust, and explores ways to increase customer confidence in these platforms. Conducted in Johannesburg, the research focuses on customer perceptions of safety and excludes provider perspectives and online safety concerns. The study reviews literature on rating systems, rating scores, and the impact of subjective experiences on customer reviews, highlighting the importance of a reliable and comparable rating system to enhance consumer trust and prevent adverse safety incidents. Desklib provides access to this project and many other study resources for students.

Running head: PROJECT MANAGEMENT
Project Management
-Shared Economy
Name of the Student
Name of the University
Author Note

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Introduction:
-Background
Sharing Economy can be understood as a new form of ‘peer to peer’ form of business
platform or an open source community that facilitates access to shared resources according to
Koopman et al. (2015). The technological advancements have fostered an exponential growth
of the platform of share economy across various categories which have caused disruptions in
various industries such as personal, home or car loan industry (GCFGlobal.org, 2019).
It has been argued that a shared economy platform has a built in trust between the
consumers and service providers which allows sharing of the resources in the first place.
Thus inherent trust between the providers and consumers have been successfully utilized by
companies such as Uber and AirBnB as the providers trusts the customers to act sensibly,
responsibly and with consideration, while the customers trusts the providers about the
providence of safety and security of the passengers (Guttentag, 2015; Smith, 2016).
Trust therefore plays a significant part in the success of the shared economy system
and therefore any organization willing to invest in it should consider strategies to foster trust
between the customers and providers (Hawlitschek et al., 2016).
Companies such as Uber or AirBnB has a system of background checks that is used to
vet the credibility and competency of the driver, and therefore providing a rating mechanism
that can be used to rate service providers, and thereby provide assurance to the customers
about their safety (Guttentag, 2015; Smith, 2016). The rating mechanism can allow the
customers to choose the service providers based on their rating as providers with a good

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rating can foster greater trust among the customers and also provide both the providers and
the customer a point of bargain (Ye et al. 2017).
-Problem Statement
Even though background checks are used by the providers to vet the credibility and
profiles of the drivers, the system is not thorough and can often be circumvented which
affects the credibility of the process and can erode the trust of the customers on the providers
and also increase risks of adverse safety incidents (Dillahunt & Malone, 2015).
-Purpose statement
The purpose of the study is to understand the perceptions on the rating mechanisms
that are used to rate service providers by the customers of shared economy platforms.
-Research objective/research question
In order to address the purpose of the study, the following objectives would be considered
in the project:
1. Identification of the existing mechanisms of rating used by service providers
2. Evaluating the pros and cons of each of those mechanisms
3. Identifying the consumers of the shared economy platform, the services used by them,
the frequency of their usage, patterns of usage and whether the rating systems
influence their choice of shared economy platforms (such as uber and taxify) and
service provider ( such as AirBnB accommodation).
4. Identifying how to increase customer confidence on sharing economy platforms
using other mechanisms
(Ye et al., 2017; Codagnone & Martens, 2016; Smith, 2016)

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-Context and units of analysis
The study would be conducted in the context of understanding the perceptions of the
customers on different shared economy platform. Using questionnaires preference of the
customer towards various shared economy platforms and service providers would be
measured using a likert scale that would help to assess how much they would trust that
provider or platform. The questionnaire would also identify customer’s choice for other
rating mechanisms that can make them feel safer when using the system as well as the factors
that can foster the trust of the customer on the shared economy platforms and service
providers.
-Importance and benefits of the proposed study
The study can help to identify and understand the factors that can facilitate the trust of
the customer on the business, understand the perceptions the customers have on the existing
system or platform and how to best address the safety concerns of the customers by
developing a better system of rating that is thorough (Brace, 2018). Enhancing the safety
concerns of the rating mechanisms can ensure better prevention of adverse safety and security
incidents and therefore promote better brand image (Stemler, 2016).
Delimitations and Assumptions:
The study would only be limited to the analysis of the perceptions of the customers on
various service providers and the factors that they believe affects their trust on the services
and would not assess the perceptions of the providers. The study would also be limited to the
customers in Johannesburg from which the target sample would be selected.
One important assumption made in the study would be regarding the concept of
customer safety, which would refer only to the personal and physical safety of the customer

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and not their online safety (such as risks of identity theft or data theft). Another important
assumption would be to consider that the rating is influenced only by the perceptions of
safety by the customers and therefore better rating is caused due to better perceptions of
safety.
Definitions of key terms:
Outlined below are the definitions of some of the key terms used in the study:
Shared Economy: This is defined as a peer to peer based action of acquiring, sharing or
providing access to resources or services facilitated by community based platforms online.
Big Data: This refers to very large sets of data that can reveal patterns, associations and
trends in people’s (consumer/customer) behavior and interactions and are designed for data
processing software to analyze complex interactions and behavior of people.
Physical Assets: These can be defined as any item that has commercial, ec0nomic or
exchange value and are known as tangible assets such as properties, inventory or equipments.
Business to Business (B2B) interactions: This form of interaction occurs between two
businesses instead between a business and a consumer/customer.
Open Source: This can be defined as a platform which supports free accessibility of
individuals to copyright materials in a way in which the materials can be modified and
distributed for their own purposes without the necessity of a permission or authorization from
the owner.
Online Marketplace: This is a form of a multi-channel e-commerce platform where multiple
third parties are involved in the providence of products or services, while the transactions

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themselves are processed by the market operators and can also be used to streamline
operations.
Product-Service Systems: This can be defined as a business model that supports delivery of
products and services and facilitate a collaborative consumption of the product and service.
Redistribution Market: This is also a form of peer to peer platform in which pre-owned goods
are passed from individuals who have little or no use of those goods to others who would like
to use those goods for a price.
Collaborative Lifestyles: Just like the redistribution markets, collaborative lifestyle also helps
in sharing between multiple users. However, in this case resources are shared in the form of
money, time, skills and space instead of actual goods.
(Koopman et al., 2015; Stemler, 2016)
Literature Review:
From a review of academic literature, several important factors could be identified
that influences the perceptions of the customers regarding the rating mechanisms used by the
shared economy platforms and factors that can enhance their perceptions of safety on these
rating mechanisms. The factors have been thematically outlined below:
Rating Systems:
According to Stemler (2016), mechanisms of online feedbacks and provider
reputation system fosters a significant word of mouth network in which the consumers
(product or service users) can share their opinions and experiences about various service
providers and shared economy platforms. The advent of networked digital platforms has
allowed a democratized system of reviewing service providers or product manufacturers and

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has allowed the consumers or customers to give rating for multiple businesses thereby
fostering a more open process of providing reviews (Codagnone & Martens, 2016).
Various approaches can be used to support online rating system for the customers or
consumers. The reviews can be local (made on a single product, service or platform),
distributed (made on he company’s website) or comparative (made on multiple product,
platform or service providers providing an overall assessment by consumers). In addition,
review mechanism for shared economy can also include one partner of the shared economy
independently evaluating the other or both the parties being involved in the process of
developing a review through a collaborated effort (Schor & Fitzmaurice, 2015). According to
Hasan & Birgach (2016), rating systems that provides rating for multiple services, platforms
and providers can help the consumers to compare the providers and thereby identify the
provider that best suits the needs of the customer.
Additionally, the rating systems that are being used for commercial platforms (such as
rating products purchased from eCommerce sites like Flipkart or ebay) or for developing
online reviews for individual providers in an online market platform (such as individuals
selling books in Amazon’s online market) shows that rating of products or services
significantly differ between the consumers/customers and a business player/owner even when
the business deals are done in a commercial context (Srinivasan, 2017). This shows the
importance of a rating system that can be used to rate multiple services, business or services
in the same shared economy platform (Teubner et al., 2016).
Also, according to Stemler (2016), a diverse rating system used by different providers
can also be confusing for the customers as they find it challenging to compare the systems
and thus the businesses on an equal platform and therefore a rating system that can be used

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for multiple providers or platforms supports better comparison of the results and thus aid
consumer’s decisions.
Rating Scores:
Traditional grading systems like Michelin Guide uses a diverse distribution of high
and low values seems to have a diverse distribution of scores and generally tend to be
positive (Henderson, 2017). Studies by Bridges & Vásquez (2018), showed that majority of
service providers using this approach tend to get an average rating of four out of five and also
foster more positive feedbacks and comments (99.1%) compared to negative feedbacks
(0.6%) and neutral response (0.3%).
According to Lee (2016) neutral responses were caused when the experience of the
customers were problematic (due to bad communication or delays) and negative reviews and
feedbacks were primarily the result of a negative experience by the customers (incidents
where the trust of the customers are eroded). Zervas et al. (2015) suggested that 95% of the
600,000 properties owned by AirBnB were rated 4.5 or 5 (out of 5), while there was almost
no 3.5 stars. According to Mallet et al. (2014), a normal distribution was not followed in there
rating systems since in case of a normal distribution, all the values are close to the mean
value and large deviations from the mean value is seen rarely. However, the rating scores lies
outside of the normal distribution curve which reduces the reliability of the approach.
According to Ghisellini et al. (2016), most companies use a voluntary system of
review, due to which only the individuals who have reviewed the service are counted. Studies
by Yaraghi and Ravi (2017) show that even though more than 50% of the customers gave
feedbacks after sale of the product or service, only 13% of the customers gave reviews. The
study shows that for some reason that is not clearly understood, people tend to give positive
reviews, and when they do not find any positive aspect, they avoid reviewing at all.

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Mallet et al. (2014) additionally pointed out that rating can be influenced by
subjective experiences and expectations and the same product or service can be rated
differently by to different consumers or customers. This is because what one individual might
find appealing or attractive, might be completely different from the expectations of another
individual from the same product. Due to this is is important to view different aspects of a
product or service needs to be viewed and analyzed from various angles and points of view
(Richard & Cleveland, 2016).
Rating System Design and Algorithm
Since the process of designing and interpreting ratings and reviews are based on
cognitive as well as subjective and social functions, grading the reviews and ratings in a
quantitative manner is a problematic issue. The rating systems themselves are also are
designed differently and the categories that has been defined by a platform as important
might not be the ones that ioffer any benefit or advantage to the consumers or the service
providers (Eslami et al., 2017). According to Dellink et al. (2017), the outcomes of ranking
systems depends heavily on specifications and the design of the assessments and therefore
facilitate a material-discursive practice of rating.
In case of sharing platforms where both the service providers and consumers can rate
each other using various systems of rating that are aligned to different role, differences in the
perspectives of the providers and the consumers are exhibited in the ratings either as a single
value or a visual representation and qualitative data are given less priority than the
quantitative data calculated from the ranking scores. Some businesses use the qualitative data
(like feedbacks and reviews) by arranging the latest information at the top and also allows
some of the comments to be hidden, which can erode the trust of the customers and
consumers (Bellotti et al., 2015).

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Companies such as Yelp uses recommendation system as a ranking mechanism in
which the ratings and reviews of the users are segregated into sub categories such as activity,
reliability, and quality. Due to this strategy, the reviewers who are more active attracts more
trust from the consumers. Additionally, this system provides more importance to the
participants who are active and therefore give them more visibility compared to those who
are not active (Dellink et al., 2017).
Trust:
Trust is one of the cornerstones of a shared economy or peer to peer business
platform. Social networking tools are widely used by the consumers and customers to identify
trustworthy businesses (Hawlitschek et al., 2016). According to Yang et al. (2016), rating
systems are an important ‘trust building tool’ that can help businesses working on shared
economy platforms to foster and attract the trust of the customers based on the positive
reviews of other users. Trust also needs to be developed at every level of the operations and
relation between the business and customers especially in relation to the payment and
evaluation system (Mittendorf, 2016). According to Fox et al. (2017), trust can be understood
as a mental state based on desired expectations from the outcomes of the actions of others and
can be considered as a basic element needed to mitigate risks and improve collaboration
between people (businesses and consumers) and create an order.
The concept of trust has been extensively researched by many studies in different
disciplines such as psychology, sociology and economy. According to Yang et al. (2016),
trust can be considered a calculative decision based on favorable experiences and outcome
and helps to develop social capacity and social networks and ties and thereby facilitate better
relations with people. According to the social exchange theory, two forms of interactions or
exchanges can influence motivation among people, which includes social interactions and

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economic interactions and while social interactions are based on reciprocity as well as
feelings of diffused responsibilities which are primarily personal in nature, an economic
exchange on the other hand tends to be dependent on impersonal factors (Mittendorf, 2016).
Hawlitschek et al (2016) further posited that for both these types of interactions, trust is a
vital part.
Older researches on behavioral psychology identified trust as a more personal
experience but later studies considered it to be more relational which requires both an agency
as well as reciprocity. This led to the development of a more process oriented and practice
theoretical approach towards the concept of trust, and shifting the focus from the term ‘trust’
to the term ‘trusting’. This new concept refers to the process of fostering and maintaining the
trust or developing attributes which can facilitate it. This also implies a constant
interpretation of the relationships with other people and develop trust on others based on their
past action (Fox et al., 2017).
Research Design and Methods:
-Inquiry Strategy and broad research Design:
The strategy that would be used to inquire about the perceptions of the customers on
the rating mechanisms currently used by different shared economy platforms using a
questionnaire to collect primary, quantitative data from the sample population. The research
design would be of a primary research using quantitative data from the questionnaires.
-Sampling
--Target Population, context and units of analysis
The target population would include customers of shared economy platforms in
Johannesburg, South Africa. The context of the study would be to understand their

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perceptions and a likert scale would be used as an unit of analyzing the perceptions of safety
on different rating mechanisms.
--Sampling method
Random sampling would be used for the study to select the sample population.
--Sample Size
The selected size of the sample would be 40
--Demography:
Location: Suburbs of Johannesburg
Age: 20 to 50 years
Gender: Male and female
-Data Collection Methods
The data would be collected from online survey questionnaires and recorded on a
Microsoft Excel Spreadsheet.
-Data Analysis Methods
Analysis of the primary data would be done graphically, showing the average ratings
of different shared economy platforms and service providers from the 40 responses thereby
explaining the overall perceptions of the providers or platforms in terms of the effectiveness
of the rating systems shown by the target crowd.
-Research Ethics and Ethical Considerations
For the study, informed consent would be taken from all the respondents, ensure that
the study does not violate any intellectual property rights for any businesses as well as