Soraya Sedkaoui - Sharing Economy and Big Data Analytics

Several studies have dealt with these two concepts, but separately. Thus, in this book, we have tried to combine them and deduce the possible relationship between these two concepts. We have organized each chapter so that each reader can approach it with confidence. The next three sections highlight what is specifically covered in this book.

Part 1discusses a literature review on the theme of the sharing economy. It aims to sketch a congruent overview of the state of the art and the knowledge needed to understand this “phenomenon”. In this part, we will present the sharing economy as an alternative to an outdated economy that is unable to meet the socio-economic and environmental expectations of individuals. It will shed light on the challenges facing the practices of the sharing economy and the possible risks faced by companies and society. Talking about the sharing economy cannot be done without mentioning the technology that has led to the emergence of this new business model, namely digital platforms. The latter provide the foundations of the sharing economy, but also ensure its realization and future.

Chapter 1, “The Sharing Economy: A Concept Under Construction”, discusses the emergence of the “sharing economy” concept and its rise to becoming a business model that disrupts the practices of a bygone economy, to the extent that it has created socio-economic and environmental problems.

In Chapter 2, “An Opportunity for the Business World”, we look at the consequences of adopting the sharing economy, namely the potential opportunities for the business world, as an optional approach in order to gain a competitive advantage.

Chapter 3, “Risks and Issues of the Sharing Economy”, examines the inevitable risks and challenges that the sharing economy covers for economic agents. How would producers perceive the new consumer behavior? Would they be able to embrace it? Or would they be on the defensive? How would individuals, who would see their jobs gradually disappear, react?

Chapter 4, “Digital Platforms and the Sharing Mechanism”, highlights the involvement of digital platforms in the process that is revolutionizing the context of sharing in economy. Although there is some reluctance to make this spirit of exchange a reality in commercial transactions through digital platforms, they still play a major role in spreading the values associated with exchange between individuals.

This section presents a platform to examine different concepts related to Big Data and to show how this phenomenon transforms opportunities. It summarizes a considerable set of application examples in the sharing context. This section will be of interest to all types of readers, as it addresses the general context of Big Data and highlights its importance for sharing economy companies. It examines the different ways in which Big Data can be beneficial for these companies.

Chapter 5, “Beyond the Word ‘Big’: The Changes”, provides an overview of the basic concepts related to Big Data, while illustrating the changes that have led to this phenomenon. This chapter will also highlight the importance of data for businesses and how it can increase their efficiency.

Chapter 6, “The Art of Analytics”, covers the most basic form of data analysis, from descriptive analysis to prescriptive analysis, by covering predictive analysis. This chapter is also an opportunity to discover the different steps of the data analysis process.

Chapter 7, “Data and Platforms in the Sharing Context”, presents an overview of Big Data applications. These applications come from the business world and show the interest that large companies take in this phenomenon. This allows understanding the power of data and the importance of digital platforms when realizing the strategies of the sharing economy companies. This chapter thus addresses the different challenges related to data and highlights the importance of data openness.

Chapter 8, “Big Data Analytics Applied to the Sharing Economy”, is detailed enough and potentially useful in order to build a global approach around the subject. This chapter demonstrates that the successful implementation of the data-driven culture is an important factor to carry out sharing economy practices. It reviews different Machine Learning algorithms and advanced technological tools for data analysis.

This last part presents a range of advanced data analysis algorithms, including regression, classification and cluster analysis. It provides a set of techniques to anyone who wants to generate value from data based on the data analysis process. Using practical examples, we introduce fundamental principles of the Big Data analytics process.

Chapter 9, “Linear Regression”, discusses the essential techniques for modelling the linear relationships between explanatory variables and the outcome variable in order to make predictions on a continuous scale. After introducing the linear regression model, there is also a discussion of logistic regression, and Ridge and Lasso regressions. Based on an Airbnb database’s example, this chapter provides a practical guide to explore the data and build a predictive model more efficiently, using Python.

Chapter 10, “Classification Algorithms” , revisits the origin of supervised learning and introduces the most common classification algorithms. This chapter is an introduction to the fundamental principles of different techniques that help to better classify data. Using the same Airbnb database, this chapter will illustrate the most significant features in the model definition.

Chapter 11, “Cluster Analysis”, moves the focus to another sub-domain of Machine Learning: unsupervised learning. This chapter will examine clustering algorithms, mainly k-means and hierarchical classification. To better understand the principles discussed throughout this chapter, a practical example will be introduced in order to show how to find groups of objects that share a certain degree of similarity.

In conclusion, our ambition is to make this book one of the first basic references of the sharing economy practices boosted by Big Data. We hope that this book will open up new horizons for you, by presenting new approaches that you may not have known before. We also hope that this will help you sharpen your curiosity and stimulate your desire to learn more about it.

1 1 Jean-Louis-Auguste Commerson.

What cannot be eschew’d must be embraced .

William Shakespeare

The Merry Wives of Windsor , Act V, Scene 5

For more than 20 years, society’s behavior has changed in terms of daily consumption.

In the interest of economic rationality, people, without knowing each other or being part of the same family, agree to live together, travel in the same vehicle, work in the same space and participate in common projects. They decide to join forces in activities such as production, distribution and consumption.

In other words, they have a new approach to economics, which involves collaboration and a spirit of sharing: it is commonly referred to as “the collaborative economy” or “the sharing economy”.

A question challenges us: why did this concept appear?

Several factors have contributed to the advent of the sharing economy: the development of IT tools and mobile technology (smartphones, tablets), the globalization of the economy, the global economic crises and the environmental watch fueled by ecological awareness of the negative externalities of economic activity.