Business Ethics Students: Serle Siliani, Andrea Carrillo-Andrade Lecturer: Paul Blanchard June 6, 2021 ESE, Florence Table of content Ubering into chaos: ethical dilemmas in gig economy..................................................... 3 Executive summary .......................................................................................................... 3 Literature review............................................................................................................... 3 Methodology..................................................................................................................... 7 Case analysis .................................................................................................................... 8 Discussion....................................................................................................................... 13 Conclusion and recommendations .................................................................................. 17 Bibliography ................................................................................................................... 18 2 Ubering into chaos: ethical dilemmas in gig economy Executive summary By: Serle and Andrea Uber is self-defined as a tech startup that provides riding-sharing services. Since the beginnings, the company has been into ethical dilemmas that had social impact. At first, they were accused by taxicab drivers of unfair competitive advantage as they were offering lower fare rates sponsored by their partners. Besides, drivers that used the app were considered independent contractors. Then, society was concerned about the lack of diversity among the employees and the way the algorithm worked as discrimination cases began to be recurring in the fare rates and the rating that drivers were receiving according to their race or nationality. Finally, with the increasing awareness among the use of data, the lack of transparency and the distance between the amount of data that they are collecting from users vs the one that they provide to be even formal transparent. This case will be analyzed among the ethical dilemmas that Uber presents. For that, we will explore the concepts of integrity and fairness and we will consider the stakeholder analysis to drop conclusions around the ethical behavior of the company and the chances of occurrence. Literature review By: Andrea In 1776, Adam Smith published An Inquiry Into the Nature and Causes of the Wealth of Nations, where he explained how the 18th century economy worked. According to the author, individuals engaged directly with one another for commerce. In the next centuries, economy changed as State, employers and employees set a series of regulations that modified how businesses worked and were conceived. However, nowadays, in the digital era people has returned to the peer-to-peer exchange through the development of labor3 based digital platforms. This is related to gig-economy. “Gig workers” are the ones that are employed on a “freelance basis, carrying out short-term jobs or contracts” (Wilson, 2017). This type of jobs uses a work-performed payment structure, which implies no formal relationships among employers and employees. This new way to make business has had an impact in society, policies, and economy. In fact, “uberization of economy” implies an institutionalization of the way of making business (Chee, 2018). In concrete, they provide a platform with certain features that presents: businesses with levels of labor flexibility not available through standard forms of waged employment because (a) payment pertains only to tasks completed and (b) workers are not classified as employees, meaning that employers can avoid the costs associated with regular jobs (Fleming, Rhodes and Yu, 2019). In the ethical sphere, the uberization, has implications related to integrity and fairness. Firstly, integrity “relates to product quality, open communication, transparency, and relationships” (Ferrell, Fraedrich and Ferrell, 2019). Robinson (2016) links integrity with positive responsibility, which implies being responsible for projects in terms of stakeholders and ecology. The author uses Nestlé case study to explain that “integrity involves multiple responsibilities, including for culture, the organization and the wider social and physical environment” (Robinson, 2016: 110). Then, integrity implies thinking over relationships as they stablish a social identity: integrity is built around society. Moreover, integrity is related to trust. However, “trust-diagnostic situations often occur naturally and unintentionally during the ebb and flow of everyday life” (Simpson, 2007). In other words, integrity is a social perception, and it is built over not strong evidence. As it has been said lines above, the digital technologies and platforms “have facilitated nearly frictionless user participation and transactions, and capitalize on growing user bases via 4 reinforcing network effects” (Broekhuizen et al., 2021). The possibility of capitalization is crucial to understand integrity because labor-based digital platforms operate “in an industry where trust between strangers is vital” (Ferrell, Fraedrich and Ferrell, 2019); then, users by themselves represent capital. In terms of transparency —a characteristic of integrity—, political studies differenciate “formal” transparency —mainly related to legal requirements— from “useful” transparency, linked to the type of information in which citizens are interested (Cucciniello and Nasi, 2014). In fact, modern societies tend to evaluate more positively those governments and enterprises that publish their data. This has positive effects: information free policies are crucial for creativity, empower citizens and to improve the quality and speed of decision making (Birkinshaw and Cable, 2017). In contrast, businesses that do not share useful data as a strategy to avoid controversies, may generate the exact opposite and may experience citizen actions against them (Hidalgo Cordero and Salazar Daza, 2020). Transparency in digital business is a key element for their ethics. According to Jones’ model there are four stages to link the positive ethical decision making: recognizing moral issues, making moral judgments, establishing moral intent, and engaging in moral behavior (Rest, 1986). In past times, the lack of information was a reason for not recognizing moral issues, however, as citizens are aware that online business tend to process big data, the intentions for hiding it are as themselves a statement for nottransparent business. Secondly, fairness “is the quality of being just, equitable, and impartial” (Ferrell, Fraedrich and Ferrell, 2019: 60). In psychology, this concept is defined as the “evaluative judgments of the appropriateness of the treatment a person receives” (Chebat and Slusarczyk, 2005). Siadou-Martin et al. (2017) have linked the perception of fairness to 5 buyers’ satisfaction. The study concludes that “to guaranteeing a “fair” outcome, sellers must ensure that buyers are subject only to procedures that customers perceive to be fair” (Siadou-Martin et al., 2017: 221). Fairness is not a philosophical concept. It has been developped into doctrines to ensure neutrality and accountability (in the United States, the fairness doctrien and Australia and Europe “True and fair doctrine”). It can be broken down into equality, reciprocity, optimization (Ferrell, Fraedrich and Ferrell, 2019). For instance, in 2015 Toshiba went through a scandal based on the lack of diversity and the obvios preferences for “Japaneseness” perspectives (Bolza, 2015). It was revelead that Toshiba’s executive suite had pressured its subordinates into achieving ambitious profit targets”. The explanation for this is sustained in what is known as “Japanesse culture”: according to Sato, “[Japan’s] corporate culture encourages you to take the same action as others, and makes you believe that maintaining the status quo is the right thing to do”(Bolza, 2015). In fact, equality evolved from the recognition that “what was fair (or conservative) for credit granters might not be for stockholders” (Riahi-Belkaoui, 2019). Optimization has its basis in accountability: In general, the fairness concept implies that accounting statements have not been subject to undue influence or bias. Fairness implies that the preparers of accounting information have acted in good faith and employed ethical business practices and some accounting judgement in the presentation, production and auditing of accounting results (RiahiBelkaoui, 2019). Besides, accountability is related to corporate governance, which implies how decisions are made according to their strategic direction, legal and ethical considerations (Ferrell, 6 Fraedrich and Ferrell, 2019). Then, fairness is a fundamental criterion of information in managerial accounting: it ensures the integrity and accuracy while decision making. Reciprocity is related to coorporate social responsibility (CSR), which is the “organizations obligation to maximize its positive impact on stakeholders and minimize its negative impact” (Ferrell, Fraedrich and Ferrell, 2019: 35). This concept has evolved as initially it only considered the shareholders; then, this broader conceptualization takes into account the contributions of companies to social, environmental and ethical concern (Moon, Anastasiadis and Viganò, 2009). But what was fair (or conservative) fo fairness doctrine and in Australia and Europe as the “True and fair” doctrine. Methodology By: Serle The “Uber Hits a Bump in the Road” case was particularly appealing for this paper’s purposes as it presents different faces of ethical dilemmas that challenge the company regarding its operating both in the United States and abroad. These issues translate as a big threat for Uber and, if not faced responsibly, definitely have the power of critically damage the company’s reputation, shareholder confidence, reliability and last but not least its revenue. We will conduct our research using published articles, other case studies and academic material excerpted from books, paying attention to, evaluating and analyzing how the company responds to determined accusations or deals with structural and operational obstacles while integrating our examination with critical thinking. 7 Case analysis By: Serle Uber Technologies, Inc. is a multinational company that makes about $11 billion (TTM) in revenue (“Uber Announces Results for Fourth Quarter and Full Year 2020”, 2021). It offers a transportation service that connects drivers-for-hire and passengers that need a ride in the same city, and it was originally developed as a smartphone application for Android and iPhone called UberCab Inc. in 2009 by Travis Kalanick and Garret Camp. The company operates in more than 450 cities globally and is most popular in the United States, where its headquarters are in San Francisco, California. The digital services offered vary between more low-budget ones, such as UberPool (which allows people to ride together and split the cost) or UberX, to more premium luxurious options such as UberBlack or UberLux (Ferrell, Fraedrich and Ferrell, 2019). At first glance, it might be easy to draw a quick conclusion and state that nobody would actually need or use this service, as cabs already exist everywhere, but Uber managed to eat up a slice of the market share as big as 70% and has been able to maintain it until the end of the past year. After 2020, Uber’s market share slightly decreased falling at 67% as of March 2021, but the company remains the most utilized platform among its competitors (Wong, 2021) and can boast 30 million users every month (Ferrell, Fraedrich and Ferrell, 2019). This is possible because the app is extremely user-friendly and utilizes an integrated GPS system that can locate nearby drivers and therefore significantly reduce the customer’s waiting time. Regarding costs, Uber immediately established a leadership upon the taxi market and always claimed to provide lower fares– but it still relates to a surge pricing policy that is applied during times of higher demand. The passenger in need of a ride is notified of the price increase and can choose to pay more or wait and see if the rates go back down, while Uber’s service fee percentage remains untouched (“How Surge Pricing Works”, 8 2021). Purge the surge! This aspect has been one of the many Trojan horses that the company has had the need to face, as many customers have complained and accused Uber of capitalizing, as well as speculating on emergency situations, for example the one happened in Sidney, Australia in 2014 (Ferrell, Fraedrich and Ferrell, 2019). In this occasion, “the firm raised fares by as much as four times its normal rate when demand shot up during the siege that left three people dead.” (Lee, 2014). This event left people raging. The company defended itself by claiming that the true meaning behind price surging is to encourage drivers to accept more rides during busier times, but it was not enough to convince the public, so Uber decided to refund all the consumers in the Sidney area that were affected by the price spike (Lee, 2014). This demonstrates that price surging can be a valid marketing strategy, as it has been proved to increase the number of drivers available in a certain area, but it’s a technique that might be more profitable for driver-partners rather than for users —since its main goal is to incentivize them to accept rides during times where they would normally tend to avoid doing it— and a case study conducted by Hall, Kendrick and Nosko shows that the number of completed ride requests doesn’t really change when the price surge is activated (Hall, Kendrick and Nosko, n.d.). In fact, during New Year’s Eve 2015, the price surging algorithm stopped working for 26 minutes between 12am and 1am, and while some few lucky customers were able to catch some very convenient Uber rides, “the rate at which ride requests were fulfilled fell steeply, and most were left without a ride at all” (Hall, Kendrick and Nosko, n.d.). So, given this, what would have really happened in the Sidney’s hostage situation if the price surging algorithm had not been working? Maybe Uber rides would have been even harder to obtain. But if you were in that situation and all you could look at were inflated Uber prices, wouldn’t you be raging that one of your only chances to escape a great danger was still affected by the law of supply and demand? It seems like a reasonable reaction. The 9 thing is, how can an algorithm know how to make ethical decisions? Should an algorithm like this one be applied to all circumstances, even when people’s lives are at stake? The drivers vs Uber Another internal ethical dilemma that Uber has been facing is the company’s relationship with its driver-partners. They are addressed as self-employed and independent contractors because they have complete control over the amount of course they work, over their vehicle, their schedule and most of all they are free to work as drivers for other competitor companies, such as Lyft. As idyllic as that may sound, many Uber drivers have complained about the scarcity of their pay, caused by the company’s continuous effort in maintaining the lowest fares to gain advantage from their competitors —and by the fact that driver-partners autonomously and actively use their own funds for gas and vehicle up-keeping—. Considered the fact that Uber operates in a gig-economy environment, its integrity and fairness towards the drivers is expected to be immaculate, since trust should be at the base of any contractual relationship between stakeholders (Ferrell, Fraedrich and Ferrell, 2019). But things do not always go as planned. After the complaints, Uber started granting fixed hourly earnings to the drivers, but established a strict set of rules for them to be able to qualify for the earnings. These regulations significantly increased the working time for the drivers, basically forcing them to comply to a condition of exclusivity towards Uber —it made it practically impossible for them to work for any other company—. As of today, Uber has been strongly encouraged to redefine it rideshare drivers as employees rather than contractors, in several occasions, and therefore is facing numerous lawsuits. In 2015, the company was challenged when a California labor commissioner ruled that an Uber driver qualified as an employee (Ferrell, Fraedrich and Ferrell, 2019). Later in 2019, Uber was consequently accused of violating Assembly Bill 5 (AB5) by incorrectly referring to driver-partners as contractors instead of employees —the lawsuit was opened by California’s attorney general and other city 10 attorneys from the state— (Feiner, 2020). Assembly Bill 5 is a law that aims to protect gig workers by defining and underlining specific conditions that declare whether a worker can indeed be considered as self-employed or as an employee of a company, in the State of California. To be considered as independent contractors, workers need to meet all three of the conditions of a special test, called ABC Test, that states as follows: (a) the person is free from the control and direction of the hiring entity in connection with the performance of the work, both under the contract for the performance of the work and in fact. (b) the person performs work that is outside the usual course of the hiring entity’s business, and (c) the person is customarily engaged in an independently established trade, occupation, or business of the same nature as that involved in the work performed. (AB 5 – Employment Status, 2019). To all this confusion, Uber Technologies has always responded that its drivers are and always have been categorized as independent contractors as they establish a legal relationship with the passengers by accepting the rides on the app. CNBC wrote that on August 10th, 2020 “a trial court granted the state a preliminary injunction that would require Uber and Lyft to reclassify their drivers as employees. The injunction requires Uber to take on the additional costs related to employment if they continued to operate in the state, like payroll taxes and unemployment insurance.” (Feiner, 2020). Although the company stated that it respects the court’s decision, consequently to this, Uber campaigned and invested $30 million into a ballot measure called Proposition 22 (Prop. 22) that “exempts drivers for app-based ride-hailing and food delivery services from the employee classification required under the new state law, Assembly Bill 5” (Feiner, 2020). Unions are still fighting for other ongoing lawsuits in California, but it looks like for now, Uber Technology Inc. is in the clear. Unfortunately, though —as shown above— the company doesn’t really hold a good reputation when it comes to managing ethical dilemmas. Even many shareholders referred 11 to Uber’s corporate culture as aggressive and toxic, and some executives left the firm to avoid being associated with it (Ferrell, Fraedrich and Ferrell, 2019). The situation escalated so badly that a shareholder’s revolt involving two of the company’s major investors pressured Travis Kalanick —Uber’s CEO and co-founder— to resign in 2017. At that point, Uber’s corporate culture had already been undergoing several accusations, spanning from sexual misconduct, lack of transparency to lack of diversity, so Mr. Kalanick diplomatically decided to step down, while remaining in the company’s board of directors. In a personal statement he said: “I love Uber more than anything in the world and at this difficult moment in my personal life I have accepted the investors request to step aside so that Uber can go back to building rather than be distracted with another fight” (Isaac, 2017). Troubles for the former CEO of the company had begun earlier in 2017, and he had planned to take a leave of absence to also take care of some important personal issues, but the shareholders weren’t satisfied with that and pressured him to renounce to his role of CEO. This was an extreme but much needed action to cleanse Uber’s reputation projected on the public: as prominent as the role of a CEO is, its expression of personal morality is of great importance (Rhodes, Branicki and Brammer, 2020). Since Kalanick left, the company has been trying to mend its reputation back together and has actively fired more than 20 employees after them being investigated regarding inappropriate misconduct allegations (Isaac, 2017). Also, the fact that Kalanick was practically kicked out from the inside is a very powerful assessment, since it was in both the shareholder’s and stakeholder’s best interest to not take part and operate in a company that was letting its cultural and functional integrity crumble. To facilitate and maintain value between stakeholders, any company must assess and evaluate its internal stakeholder information through attentive research and by identifying “the concern about the business that are relevant to each stakeholder group” (Ferrell, Fraedrich and Ferrell, 12 2019). Keeping healthy stakeholder relationship is crucial in order to minimize being identified as a company with a negative social impact, and the entities responsible for this are the stakeholders themselves. Studies have shown that a company’s sales can and will be damaged by the unethical treatment of stakeholders (Ferrell, Fraedrich and Ferrell, 2019). In this case, Uber’s philanthropic, ethical, legal, and economical social responsibilities were actively challenged in different occasions, but not always the company has demonstrated to be willing to take accountability for its mistake. Social responsibility depends on stakeholder orientation and therefore can be affected and impacted by issues that are not always directly related to the business. Since we can look at social responsibility like a “contract with society” (Ferrell, Fraedrich and Ferrell, 2019), and even though trying to prevent or forecast needs that contribute to an “overall goodness” is almost impossible, we can say that Uber had the obligation to take action regarding the internal ethical dilemmas ongoing in the company. Discussion By: Andrea Uber ethical dilemmas becomes a huge problem due to its impact: Uber has experienced a transitions from being a company to an institution (Chee, 2018). As it has been explained lines above, Uber has fairness and integrity dilemmas. From the first category —fairness—, scandal thorough lack of diversity has not been solved. In fact, while Lyft has raised its figures (12 %) and hired black, Hispanic and latinos executives, in Uber they are just 2.4 % (Guynn, 2021). However, there is a worse discrimination problem related to the algorithm that the app has developed. In general terms, algorithms tend to look for mainstream to potentiate the impact of publications and reach the maximum audience; this leaves behind minorities. 13 For Uber, “generic social dominance orientation strongly influences his/her discriminatory attitudes in ridesharing, supporting the claim that behavior in shared mobility platforms can reflect long-standing social dominance attitudes”(Middleton, 2018). For instance, a study conducted by George Washington University concludes that “neighborhoods with larger non-white populations, higher poverty levels, younger residents, and high education levels are significantly associated with higher fare prices” (Pandey and Caliskan, 2021). Moreover, the “trust between strangers” is sustained in service rating that have proved to be racist and discriminatory. Then, the question that remind is how the corporate leadership has dealt with such ethical breach? The answer is lack of transparency —which is the second ethical dilemma that Uber faces— by resisting to release statistics. In fact, the Pandey and Caliskan (2021) research was conducted in Chicago because the regulations of this city mandated that transportation providers publish anonymized data on ride hailing. However, in most of the globe, Uber is not transparent about the data; and as it is the stereotype (model) for labor-based digital platforms, its policies shape the whole business. Corporate leadership have found in these platforms the place to avoid government regulations: ideologically, “there is a point of tension between governmental/regulatory bodies, “innovators” (Lehdonvirta, 2015) and users. Then, not even “formal transparency” has been achieved because of the lack of regulations. Moreover, these problematics of digital innovations and an inclusive critical dialog on app-driven services are becoming a priority day by day. What is important to underline is that the gig (uberization) economy is not just creating a new digital channel for freelance work, it is fathering a whole new economic activity and platforms like Uber, as powerful economic forces, will shape livelihoods. Then, even if the speech of micro-entrepreneurs is very common among app developers, the ones that 14 have real impact are still giant corporations, which is the main driver of sustained economic inequality (Piketty, 2014). For instance, Uber has engaged in strategic partnerships that have allowed them to cheapen the ridding costs, but this is profitable just for passengers because, in order to gain a competitive advantage in different markets, Uber cuts into driver earnings (Ferrell, Fraedrich and Ferrell, 2019: 353). Additionally, Uber is cataloged as a “tech startup” (Ferrell, Fraedrich and Ferrell, 2019: 349), not as a provider for driving services —which is, in fact, what they do—. Under this business conceptualization, they avoid regulatory obstacles. For example, the independent contractor status of the drivers is a main concern. This app considers workers as users, so they do not provide health ensure, equipment nor stability. These conditions lower the chances for workers to have a decent job and deteriorate the conditions for taxicab drivers because they take unfair competitive advantage as they offer cheaper fare rates. This, related to integrity, and seeing this model as a whole, sets us in front of a key aspect of the future of the work and future business models because it seems like categorization (framing) allows some enterprises to profit from others and to enter in a territory not regulated by law, which is also a key aspect of fairness as the possibility for accountability. In an even broader vision of the implications, the privatization of services and the weakening of public ones may generate more inequality among societies. Integrity and fairness which are related to Corporate Social Responsibility, in the case of Uber are in doubt. The privatization that they defend, and a lack of labor regulation present a significant savings to the passengers. These savings are seen as positive for citizens and then Uber may be perceived as “fair” (Chebat and Slusarczyk, 2005), but the social and environmental costs require consideration. In other words, this kind of sharingeconomy that profits from the void of the law may be pernicious for societies. 15 In this line of ideas, referring to digital economy, the use of data among users is an ethical dilemma that is winning prominence in the past years. The use of GPS and the access to personal data among app users have worried researchers and citizens, naturalizing sharing our current location and routines has an impact in our conception of privacy. Besides, what should call our attention is that even though the algorithm works based on data (optimization) that is gathered permanently, when it comes to neutrality and accountability, the lack of data and information should be perceived as part of their organizational culture. That is why it can be said that for Uber leaders, ethical breach is not a main concern because the business from its conception and social reason (tech startup) it avoids legal and social responsibility and operates in the margins of ambiguity. That is why, according to the research held by Chang (2013) for predicting unethical behavior and Rest (1986) model, it likely that Uber continues operating in a similar way to which it has already done. Rest’s (1986) four stages in ethical decision-making assumes that ethical choices are not just individual, “but are determined by social learning in the organization”. Besides, as the first step is “recognizing moral issues”, but Uber has become an institution, its power has become this tech startup into amoral: it can set the rules in the way to frame moral issues. That is why nowadays people is talking about the precarization of work in these platforms. That is why holding all variables constant and not relaying in connective action, this does not seems to change in a short period of time. In fact, as Chang (2013) evidenced, “the perception of whether they have the resources will affect their intention to perform the behavior, as well as the successful performance of the behavior”. So, mainstream businesses tend to sustain their behavior unless it affects their economic performance or there is a drastic change in the resources that they perceive. 16 Conclusion and recommendations By: Serle Thanks to the research conducted on this paper, we can conclude that Uber started off as a powerful and groundbreaking startup that revolutionized the ridesharing business model, as well as significantly challenging the taxi market through innovative technologies such as the surge-pricing algorithm. Through the analysis of the ethical issues the company has faced through the years though, it does not look like Uber has properly addressed and taken accountability for the ethical obstacles on its way to success, and if this strategy has seemed to be working relentlessly until a few years ago, things are definitely going to change for Uber now. Ethical dilemmas have become more and more prominent in the past years, customers base most of their decision on how a company is able to face ethical issues and on what position a company takes a stand towards them. In contrast to other ridesharing apps like Lyft, Uber does not provide enough transparency comparing to the extent of controversies it has raised during the years. Since the company is aiming to expand more and more globally, it would be a recommended for them to be more proactive and respectful towards international regulations, driver-partner’s security, and moral and ethical honesty as well, keeping in mind that stakeholder happiness is will always be directly linked to a business’ success 17 Bibliography Birkinshaw, J. and Cable, D. (2017) The dark side of transparency, McKinsey Quaterly. Available at: https://www.mckinsey.com/business-functions/organization/our- insights/the-dark-side-of-transparency#. Bolza, M. (2015) Lack of diversity caused Toshiba scandal, experts say, Human Resources Director. Available at: https://www.hcamag.com/asia/news/general/lack-ofdiversity-caused-toshiba-scandal-experts-say/143554. Broekhuizen, T. L. J. et al. (2021) ‘Digital platform openness: Drivers, dimensions and outcomes’, Journal of Business Research. Elsevier, 122(May 2019), pp. 902–914. doi: 10.1016/j.jbusres.2019.07.001. Chang, M. K. (2013) ‘Predicting Unethical Behavior: A Comparison of the Theory of Reasoned Action and the Theory of Planned Behavior’, in Michalos, A. C. and Poff, D. C. (eds) Citation Classics from the Journal of Business Ethics: Celebrating the First Thirty Years of Publication. Dordrecht: Springer Netherlands, pp. 433–445. doi: 10.1007/978-94-007-4126-3_21. Chebat, J.-C. and Slusarczyk, W. (2005) ‘How emotions mediate the effects of perceived justice on loyalty in service recovery situations: An empirical study.’, ournal of Business Research, 58(5), pp. 664–673. Available at: https://www-tandfonline- com.bibliotecavirtual.udla.edu.ec/doi/full/10.1080/1051712X.2017.1345261. Chee, F. M. (2018) ‘An Uber ethical dilemma: examining the social issues at stake’, Journal of Information, Communication and Ethics in Society, 16(3), pp. 261–274. doi: 10.1108/JICES-03-2018-0024. Cucciniello, M. and Nasi, G. (2014) ‘Transparency for Trust in Government: How Effective is Formal Transparency?’, International Journal of Public Administration. 18 Routledge, 37(13), pp. 911–921. doi: 10.1080/01900692.2014.949754. Edd.ca.gov. 2019. AB 5 – Employment Status. [online] Available at: <https://edd.ca.gov/ Payroll_Taxes/ab-5.htm> Feiner, L., 2020. Uber and Lyft’s California labor law battle is far from over. [online] CNBC. Available at: <https://www.cnbc.com/2020/08/21/uber-and-lyfts-californialabor-law-battle-is-farfrom-over.html> Ferrell, O. C., Fraedrich, J. and Ferrell, L. (2019) Business ethics: Ethical Decision Making and Cases. Boston: Cengage Learning. Fleming, P., Rhodes, C. and Yu, K. H. (2019) ‘On why Uber has not taken over the world’, Economy and Society. Taylor & Francis, 48(4), pp. 488–509. doi: 10.1080/03085147.2019.1685744. Guynn, J. (2021) With few Black and Hispanic executives, Lyft and Uber face long road to hailing a racially diverse workforce, USA Today. Available at: https://eu.usatoday.com/story/tech/2020/12/16/uber-lyft-diversity-hispanics-latinosafrican-americans-executives/3910429001/. Hall, J., Kendrick, C. and Nosko, C., n.d. The Effects of Uber’s Surge Pricing: A Case Study. Ph.D. Harvard University. Hidalgo Cordero, K. and Salazar Daza, C. (Ed. . (2020) Precarización laboral en plataformas digitales: una lectura desde América Latina. Quito: Friedrich-EbertStiftung. Available at: http://library.fes.de/pdf-files/bueros/quito/17108.pdf. Investor.uber.com. 2021. Uber Announces Results for Fourth Quarter and Full Year 2020. [online] Available at: <https://investor.uber.com/news-events/news/press-release- details/2021/ 19 Isaac, M., 2017. Uber Founder Travis Kalanick Resigns as C.E.O. (Published 2017). [online] Nytimes.com. Available at: <https://www.nytimes.com/2017/06/21/technology/uber-ceo-travis-kalanick. html> Lee, D., 2014. Uber 'truly sorry' for price rise during Sydney siege. [online] BBC News. Available at: <https://www.bbc.com/news/technology-30595406> Lehdonvirta, V. (2015) Uber and Airbnb make the rules now – but to whose benefit?, The Policy and Internet Blog. Available at: http://blogs.oii.ox.ac.uk/policy/uber-andairbnb%0Amake-the-rules-now-but-to-whose-benefit/. Middleton, S. (2018) Discrimination, Regulation, and Design in Ridehailing. Brown University. Available at: https://dspace.mit.edu/bitstream/handle/1721.1/117829/1051771653MIT.pdf?sequence=1. Moon, J., Anastasiadis, S. and Viganò, F. (2009) ‘The potential of CSR to support the implementation of the EU sustainability strategy: Editorial introduction’, Business Ethics: A European Review, 18, pp. 268–272. Pandey, A. and Caliskan, A. (2021) Disparate Impact of Artificial Intelligence Bias in Ridehailing Economy ’ s Price Discrimination Algorithms, Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (AIES ’21), May 19â•fi21, 2021, Virtual Event, USA. Association for Computing Machinery. doi: 10.1145/3461702.3462561. Piketty, T. (2014) El capital en el siglo XXI. Bogotá: Fondo de la Cultura Económica. Rest, J. R. (1986) Moral development: Advances in research and theory. New Yprk: Praeger. 20 Rhodes, C., Branicki, L. and Brammer, S., 2020. The Morality of “new” CEO Activism. [online] Available at: <https://link.springer.com/article/10.1007/s10551-020-04656-5> Riahi-Belkaoui, A. (2019) ‘Fairness in Business’, SSRN Electronic Journal, (September). doi: 10.2139/ssrn.3250410. Robinson, S. (2016) ‘Integrity and Positive Responsibility’, in The Practice of Integrity in Business. London: Palgrave Macmillan UK, pp. 97–126. doi: 10.1057/978-1-13751553-7_4. Siadou-Martin, B. et al. (2017) ‘Salespeople, Fairness, and Buyer Satisfaction: What about Emotions?’, Journal of Business-to-Business Marketing. Routledge, 24(3), pp. 221–233. doi: 10.1080/1051712X.2017.1345261. Simpson, J. A. (2007) ‘Psychological Foundations of Trust’, Current Directions in Psychological Science, 16(5), pp. 264–268. doi: 10.1111/j.1467-8721.2007.00517.x. Uber. 2021. How Surge Pricing Works. [online] Available at: <https://www.uber.com/us/en/drive/ driver-app/how-surge-works/> Uber-Announces-Results-for-Fourth-Quarter-and-Full-Year-2020/default.aspx> Wilson, B. (2017) ‘What is the “gig” economy? - BBC News’, BBC Business, (April), p. 1. Available at: https://www.bbc.co.uk/news/business-38930048. Wong, S., 2021. U.S. ride-hailing market share 2017-2021 | Statista. [online] Statista. Available at: <https://www.statista.com/statistics/910704/market-share-of-rideshare- companies-united-states/> 21
