Table of Contents
Understanding consumer motivation and satisfaction is vital in maintaining quality in an organization. This paper addresses the issue of quality in the sharing economy. With a specific focus on ride-sharing agencies, the article indicates the importance of customer satisfaction as a measure for quality service delivery. Additionally, the paper also demonstrates the application of the lean six-sigma model to improve quality. The cross-sectional survey outlines the primary source of dissatisfaction to be the driver. It also recommends enhanced vetting processes to promote the trustworthiness and competency of drivers to improve customer satisfaction.
The sharing economy is the perhaps the most significant and innovative business model of the decade. The economy takes advantage of the availability of demand and supply from ordinary people. As such, the sharing economy ensures a connection between the two factors to generate convenience and revenue generation. For instance, Uber and Airbnb acted as the frontrunners of this business model. Uber finds people with cars to offer rides to commuters at discounted prices as a deviation from the traditional taxicab model. Similarly, Airbnb applies the same context to discover people with a spare room and get them to offer brief settlement to those in need. As such, it deviates from the traditional hotel and accommodation model at discounted prices. The unifying factor in linking the demand and supply is the application of digital communication technologies such as the internet and smartphones. After all, these organizations operate using mobile apps. However, despite these innovative advances in the supply chain, the process involves numerous drawbacks that may influence the effectiveness of services offered. As such, it is essential to establish measures of customer service where trust is a crucial component. Customer satisfaction is a measure of the value of a function in meeting the needs of the consumer. In the ride-sharing industry, the level of satisfaction goes beyond functionality to include aesthetics such as ride comfort and the competency of the driver in managing customers. A growing concern in the industry is the level of competence of the driver that can be described as the trustworthiness of the interactions during the shared ride. This research paper will delve into the value of lean six-sigma in improving customer satisfaction through a cross-sectional study of the role of trust and determinants of happiness.
SIGNIFICANCE AND JUSTIFICATION OF THE PROBLEM
The weight of this investigation stems from the growing popularity of ride sharing. The rise of new organizations such as Lyft in this market niche indicates growth and general acceptance of the business model. More people are using the services across the globe as internet connectivity increases. However, the issue of customer satisfaction, specifically trust, remains a hurdle to the revolutionary innovation. As such, people may feel uncomfortable using the service due to similar complaints from other customers who feared for their safety or had a challenging time trusting their driver. These companies all have review functions where riders rate their drivers. However, this approach is an afterthought since the customer can only provide a rating after the completion of the service. In doing so, the riders cannot assess first-time drivers, or deter any malicious intentions held by the driver. This study will help to establish the gravity of the situation as well as provide approaches to increase customer satisfaction and increase trust in the service.
Few researchers have tried to apply the lean six-sigma model to the ride-sharing context. Despite the intriguing research provided on the topic of ride sharing, little of this study focuses on improving quality and enhancing rider experience. As such, his research will offer much-needed insight to bridge this gap and promote safe and comfortable service delivery. Additionally, it will also form a basis for future research into specifics on customer satisfaction and trust in the broader sharing economy. By doing so, it will have significant implications for the hiring and employee management practices of organizations within this burgeoning industry.
The sharing economy became a popular movement in the 2010s. Little evidence exists on the model before this period. The sharing economy involves a mediating partner to oversee the implementation of critical business processes such as recruitment, service quality, and payment born out of necessity and innovation. However, the concept of the sharing economy is based on the fundamental principle of collective use (Cici, Markopoulou, Frias-Martinez & Laoutaris, 2014). Much like carpooling, ridesharing allows people to share their vehicles with other individuals, also referred to as riders. However, unlike the concept of carpooling, the passengers are strangers whose relationship is a result of digital mediation by companies such as Uber and Lyft. This revolutionary technology provided a revenue source that was otherwise overlooked. The drivers have the opportunity to make additional income by driving riders while the customers save money by using the discounted rates provided. Additionally, the amount of savings or revenue created is subject to supply and demand ensuring that users have an advantage during peak demand periods (Santos & Xavier, 2015). However, beyond the revolutionary nature of the industry, it does raise numerous concerns among users on the safety of the ride. After all, giving a stranger access to your person in a confined environment can be a cause for suspicion, paranoia, and even alarm.
Customer satisfaction drives the sharing economy, much like the broader service industry. As such, ride-sharing organizations such as Uber and Lyft have an inherently pivotal perception of the value of customer experience and feedback. For instance, people would not be comfortable using a service that is infamous for providing a hostile workplace characterized by assault and other forms of inappropriate behavior. It would put off new and returning customers and contribute to the collapse of the entire business model. As such, one can establish that the level of satisfaction that the customer can derive from the service is essential in maintaining its validity and existence. Additionally, it is in the interest of the mediating organizations to enhance this satisfaction as a way to establish a competitive edge over rivals. However, in some cases, the user convenience can be a drawback to customer satisfaction as is with the case of ride-sharing applications. Recruitment of drivers occurs in a simplified process that does not take into account the need of the consumers. For example, the absence of strict human resources procedures in vetting drivers raises the risk of including drivers who have criminal histories and the potential for inappropriate behavior in the workplace (Lee, Rahafrooz & Lee, 2017). An industry driven by customer satisfaction needs to place significance on the quality of the ride and the reputation of the organization. Negative perception has the potential to undermine trust and consequently, reduces the willingness of customers to use the service.
The environment that these ride-sharing organizations exist is unregulated. National policies across the globe did not anticipate the rise in popularity of the service, and as such, did not have adequate procedures to influence and regulate their activities. Unlike traditional taxicab services, enrollment to the organization is not subject to thorough vetting (Kleiner, 2017). Similarly, the fact that these services are global leads to disorganized if not haphazard policy development to accommodate the concept. Primarily, the business model makes it difficult to establish the appropriate category for the service. It could fit in numerous categories including transportation and internet services. As such, regulation can be quite a challenge without clarity on the business model. In places such as London, regulating the ride-sharing is a continuous effort that has little to no precedence (Kollewe & Topham, 2017). Therefore, the environment that the service exists is a significant factor influencing the structure and practices of the ride-sharing organizations.
Across the globe, ride-sharing drivers have been subjected to allegations of assault and sexual abuse among other criminal offenses. These claims are mainly alarming due to their frequency and the popularity of the service for drivers and customers alike. These allegations have surfaced in the past few years indicating that ride-sharing could be a convenient way for malicious individuals to circumvent the law and conduct criminal acts against unsuspecting passengers. For example, London has had to place a ban on all Uber operations by refusing to renew its license after numerous allegations surfaced about sexual assault. According to The Independent, the past year recorded 32 sexual attacks including rape and inappropriate conduct (Samuel, 2016). On a similar note, the Chicago Tribune reported such an incident referring to a driver operating for Lyft. The driver is said to have restrained the customer before sexually assaulting and robbing her using a deadly weapon (Rosenberg-Douglas, 2017). Such incidents have grown in frequency leading to widespread panic on the safety of using these ride-hailing applications.
- User experience and customer satisfaction are dependent on the quality of the ride
- Trust influences rider perception of the service
- Lean six-sigma can improve trust and satisfaction through refined recruitment procedures
Numerous literatures exist on the topic of the sharing economy. In addition, various solutions exist to solving quality management issues in the service industry. This section will provide a review of these resources to establish relevance to the topic at hand.
We can do it today.
The supply chain in the sharing economy
The sharing economy is a product of technological disruption of the traditional supply chain. The growth of ICT infrastructure has promoted the ability to influence the business models of many organizations and consequently, their supply chains. The sharing economy is one of the manifestations of the influence of this technology on the supply chain. The central principle of this revolution is the ability and freedom associated with sharing information due to the presence of the technological infrastructure. Ye and Wang (2013) use their article to illustrate the influence of ICT on the supply chain. According to the authors, technology has a positive impact on the supply chain through process improvement. A business that integrated technology into the supply chain experienced a reduction in costs of operation accompanied by the development of the various logical processes included. This study indicates that technology is an increasing influence in the design of the supply chain. It is also an essential to maintain competitiveness with other players in the market. The author’s understanding of the value of ICT in business validates the success evidenced by the ride-sharing market. The introduction and incorporation of ICT in the transport sector acted as a mediating element that linked supply and demand. In doing so, the approach disrupted traditional taxicab business models.
Ocicka and Wieteska (2017) describe the sharing economy as a collaborative use of resources such as assets and information. The authors claim that the sharing economy operates on a revolutionized supply chain that integrates numerous industries to create an environment that is not only sustainable but also instrumental in fulfilling the triple-bottom-line. The sharing economy thrives on the ability of participants to share information amongst them. In the case of ridesharing, the driver acts as a member of the transportation industry and a user of the service as well. He or she interacts with communication providers to gain access to the asset-sharing platform that acts as a mediator between the driver and the customer. By doing so, the driver can realize an income. Gobble (2017) suggests the value of ICT in the sharing environment is pertinent to its continued success. Establishing a peer-to-peer linkage improves the constituent business processes significantly to create clear advantages. The authors also compare the sharing economy model to the traditional business models to develop the main benefits. One clear such advantage is the dynamic nature or flexibility of this kind of economy. It emphasizes on participation based on independence and voluntary engagement. These authors also acknowledge the process improvement value of sharing tangible and intangible assets. For instance, it improves service delivery times by increasing the convenience of accessing a particular resource. They also highlight the importance of quality as a process in the supply chain of this business model.
Ganapathy (2016) uses the term “Uberization” to refer to the refinement of the supply chain through partnerships among various industry players. The author uses Uber as an example to illustrate this change in the conventional supply chain. Uber does not offer the rides instead; it acts as a mediator between the driver, or ride provider, and the customer. The author considers Uberization to be a viable and potentially dominant approach to supply chain management. It transfers organizational processes such as marketing, payment processing, and communication to the mediator and leaves the delivery of the service to the users. In a way, one can consider it an intense version of outsourcing where the ride-sharing organization contracts people with vehicles to provide the service on their behest. The author also claims that the Uber model is growing significantly across numerous industries. Gonzalez-Padron (2017) considers the flow of information to and from every participant in the chain vital since it helps to facilitate the execution of the rides across the globe and multiple platforms. The micro-entrepreneurs or drivers alongside customers share information such as GPS locations increasing the efficiency of the service and surpassing the traditional model. Similarly, data from the customers may include their level of satisfaction from the ride and translating to the quality of the service. This feedback is evidenced through ratings and reviews provided by riders.
Quality in ride-sharing applications
Mohlman (2015) uses his article to establish the parameters for customer satisfaction in the sharing economy. The study evaluates the different variables essential to determining the level of comfort held by the users of the service. The document exercises a general look at the business model by using two companies in the accommodation and transportation industries. The findings indicate that the level of satisfaction held by the customers is based on four determinants. According to the author, trust is a vital and ever-present factor influencing the level of contentment that a client derives from a service in the industry. In fact, the research shows that it is the most crucial factor in the case of ride-sharing services such as Uber. The author also defines trust as the feeling of comfort established through a provider’s reliability. The result of confidence is loyalty to the given service. However, the concept of trust is highly dependent on the level of security that the customer can experience during the interaction. Therefore, the level of protection afforded to the client influences their perception of quality and satisfaction of the service. It is a deviation from the traditional taxicab model where trust was not an issue as much as comfort and pricing.
According to Khuong and Dai (2016), the customers focused on the comfort and price of the service rather than trust. The associations in charge of these cabs assure specific standards of trust that are not provided for in the app-based infrastructure. For instance, drivers in these organizations were bound by a code of conduct as well as organizational policies. The enforcement of these systems was also secure since the taxicab association operates at a local capacity using locally sourced labor. As such, the organizations had physical contact with the drivers. They also provided vetting mechanisms that weeded out employees with questionable backgrounds. The use of background checks or interviews supplied a robust recruitment framework that is absent in the app-based infrastructure. On the other hand, the app-based organizations barely have any policies and codes that govern behavior in the workplace. Those that do, often find it hard to enforce standards of quality that is necessary to ensure customer satisfaction. The author claims that the absence of a rigid structure as witnessed in traditional taxicab services undermines the ability to regulate the drivers’ conduct.
Further assessment of customer satisfaction leads to Zhu, Kevin, and Hudson (2017). The authors develop an understanding of consumer motivations to use mobile applications to access the sharing economy. The authors try to identify the sources of value that can be found by using the sharing economy. Despite the author’s generalization of the sharing industry, some of the insights make it clear that the functional, emotional, and social motivations apply across the board. The operational needs involve the convenience of moving from one place to another. The psychological motivation arises from the feelings of security and comfort that one experiences in the course of the ride. Finally, the social aspect of the motives exists based on the need for interaction between individuals during the trip or in the exchange of information. Therefore, it is evident that the emotional aspect carries significant weight in the industry. The feeling of safety, bolstered by trust, is a substantial factor influencing the likelihood that a customer will use the service.
with any paper
Regulation of the ride-sharing industry
Management of the ride-sharing market has proven quite challenging. The dynamic nature of technological innovation coupled with divisive opinions makes it a challenge for policymakers to install effective policies that ensure rider safety and smooth operation of the service.
Elaine (2016) undertakes a legal perspective towards defining the ride-sharing economy. The author describes safety and security in a public transit system to be a significant consideration in the definition of quality in the industry. According to the article, ride-sharing services like Uber enjoy functioning at the fringes of the law making them almost immune to transport regulations. The sharing economy leaves these companies undefined making it difficult to categorize them in an existing regulatory framework. The result is an inability to provide oversight and institute standards of operation, including those of processes that influence quality. For instance, the registration to the application is insufficient since it does not vet the drivers adequately. As such, controversy surrounds this emerging business model. Its streamlined nature presents advancements in supply chain management, but it also leaves substantial challenges in its execution. The problem of regulating these app-based services does not make any assurances about quality and customer assessment, especially the safety of the customers.
Elliot (2015) echoes this understanding by capitalizing on the scanty regulatory framework that governs the ride-sharing industry. According to the author, regulation of the industry is a highly divisive and controversial topic. In fact, this complexity is evidenced by the presence of numerous stakeholders in the politicization of the market niche. For instance, drivers and many passengers enjoy the services offered by these companies. On the other hand, some view the ride-sharing industry as a way to undercut taxicab corporations. Finally, some of the stakeholders take a robust stand for enhanced regulation. The rationale behind those that call for additional vetting of drivers is that a responsible and competent workforce is the key to reducing the frequency of assaults and promotes user safety. However, the data on the transport industry indicates severe opinion divisions among stakeholder. This situation is bound to make creating and enforcing regulatory policies difficult and slow.
Little information exists about quality improvement in the sharing economy. As an emerging industry, scholars are yet to evaluate the issue of customer safety and satisfaction in the industry. However, the lean six-sigma approach to supply management has the potential to inform decision making in the industry.
The application of the lean six-sigma model requires an understanding of its constituent parts. Antony, Snee, and Hoerl (2017) use their paper to provide a background and forecast of the model. The authors claim that the LSS is a combination of the lean philosophy and the six-sigma approach to quality improvement and continuous improvement. The author defines the lean theory as an approach that assesses the processes within the supply-chain and makes configurations that reduce waste and increase the value of these systems. On the other hand, the six-sigma approach is a consumer-driven strategy that eliminates defects by assessing the supply-chain to correct these errors. The integration of the two concepts allows them to complement each other in improving process management in any business. Qureshi, Bashir, Zaman, Sajjad, and Fakhr (2012) suggest that the application of the lean six-sigma approach occurs from the perspective of the customer. It means that the proposal is not only aimed at enhancing efficiency in the organization but also increase customer satisfaction. Therefore, eliminating aspects of the business that do not lead to any additional value and replacing them with systems that promote user satisfaction is vital in ensuring the success of LSS.
Psychogios, Atanasovski, and Tsironis (2012) use their paper to develop an idea of the application of the lean six-sigma model in the service industry. In the article, the authors define the various factors that influence the implementation of the LSS model. These factors include the corporate culture and the management processes including IT policies. As such, it is clear that the LSS model is dependent on the available corporate systems prevalent within the organization. It also establishes the value of LSS in the decision-making process. Jayaraman, Leam Kee, and Lin Soh (2012) further elaborate on the issue by emphasizing the importance of including the management in instituting an organization-wide revolution through the LSS model. As such, the development of policies and their execution is vital for the continued improvement of the services provided. The authors define the goals of the LSS to be a determinant of the customer’s requirements. Therefore, the development of policies, as well as engagement by the top management, needs to reflect this understanding.
Human resources management is a crucial aspect of the LSS process. As established in the previous literature, the role of management in quality improvement is vital to the success of the LSS model. Tsironis and Psychogios (2016) consider HR support essential in the successful implementation of the LSS approach. The authors claim that a precise definition of roles and responsibilities as well as a code of conduct is necessary to avoid subversion of the customer-orientation goal of the LSS approach. The practices and systems set in place to guide the employee culture should be reflected by recruiting operations in the company. As such, the employees are aware of the limitations imposed upon them by the management. Sahay (2015) evaluates the role of HR practices as processes of value addition. The author presents an integration of the LSS model with HRM practices since talent acquisition is vital to the quality of the business outcome. As such, talent acquisition should be aligned to the goals of the organization and the customer’s requirements under the LSS framework. In addition, constituent operations such as assessment and vetting should occur with value addition in mind. Spasojevic Brkic and Tomic (2016) consider employees to be a valuable aspect of any quality improvement operation. Furthermore, the employees are especially crucial in the service industry where they are instrumental in delivering a particular service to the customer. Therefore, employees are a necessary variable in the achievement of customer satisfaction under the LSS framework.
your paper for you
The study adopted a cross-sectional design using a mixed-methods approach. The mixed method approach utilized both qualitative and quantitative data. Primary insights from respondents acted as qualitative data while a review of organizational data served as quantitative data. The source of primary data was the respondents who are users of Uber and Lyft ride-sharing services. The source of secondary data included independent oversight organizations such as www.whosdrivingyou.org that collect user data on Uber and Lyft services.
The sampling approach for this research mainly focused on the primary data collection. Through random sampling techniques, a sample size of 250 was determined to be sufficient. The absence of a total population led to settling on a particular figure that proved most useful in providing accurate information. The target population was composed of people who use Uber and Lyft. The selection of these two companies was due to their essential and favored status in the sharing economy. As such, it was easier to recruit users of these services than other smaller facilities. The results were indicative of the current ride-sharing environment being a cross-sectional survey. It offers neither predictive insight nor account for past developments in this industry. The sample population was recruited through a social media ad campaign. The campaign involved the circulation of posters and advertisements looking for people who use Uber on a regular basis. No incentive was used to recruit these people to avoid fabricated information.
Data collection was done through the distribution of customer satisfaction surveys. These surveys were based on the Likert Scale where respondents had the option of selecting the qualitative answer that best suited their opinion. The questionnaires covered numerous points including overall satisfaction and reasons for dissatisfaction. Additionally, the data collection involved consulting independent monitoring agencies such as www.whosdrivingyou.com. The site provided a wealth of data including statistics of assault cases associated with the services that were essential in developing an understanding of allegations of inappropriate conduct. Similarly, the website focused on matters concerning Uber and Lyft services.
The research applied proper ethical considerations in conducting the study. The names of individuals who responded to the ad campaign were omitted from the results as a way to enhance their anonymity. Anonymity is a vital aspect of any study that seeks to protect the identity of its respondents. Additionally, the communication with the study’s participant included a description of the research and its aims to obtain informed consent from participants. Informed consent is necessary for any study where participants will be required to disclose their opinions and private details. As such, this study placed due significance to the issue of informed consent. Additionally, we promised participants that the information provided would remain confidential.
Preliminary results from the study indicated that female respondents used the ride-sharing service more often than their male counterparts do. The data suggest that 71.2% or 178 women used the service compared to 28.8% or 72 men. Additionally, only 18% of the sample population used Uber on a daily basis, 64.8% used it on a weekly basis, and 43 people used it less than three times a month.
Customer satisfaction survey
The information presented on the Likert scale indicated that 68.8% of the respondents were happy with the service delivery in both Uber and Lyft as opposed to 22.8% who felt negatively about the service delivery. It is crucial to note that 0.84% of this population did not offer an opinion to the query. Additionally, people who were happy or unhappy with the service provided a moderate to high belief as shown in the table.
Further assessment of the results indicated that the people were most unsatisfied by three significant factors in the ride experience. It also shows that these factors influence their perception of the ride-sharing service. The data shows that 40.45% were unsatisfied due to routing problems that led to a slow ride and lateness to their drop-off point. 36.4% people felt that the driver was rude or unresponsive to their presence throughout the trip. 17.2% of the respondents felt unsafe during the ride. Finally, 0.64% of respondents provided a neutral response to the sources of dissatisfaction as seen in the table.
The survey also investigated the various factors that customers considered in determining the quality of the service delivery. Among the options were a comfort, pricing, length of the ride, and the driver. The results are as indicated in the table.
The closing inquiry on the questionnaire asked whether the customers would use the service more if the drivers were vetted appropriately and assurances provided by the mediating organization. In response, 71.6% of the participants claimed these changes would allow them to increase the use of the service.
|Length of the ride||25.2%||–||74.8%|
|Vetting of drivers||71.6%||0.01%||37.2%|
Table 1: respondent responses on the Likert survey
Secondary data from www.whosdrivingyou.com
www.whosdrivingyou.com is an independent monitoring organization that focuses on incidents reported by Uber and Lyft customers as well as police and press statements. This website is perhaps the most comprehensive account of such incidences around the world today. It provided data on numerous incidents associated with these ride-sharing companies as shown below.
|Incident||No. of people|
|Alleged sexual assaults||332|
|Other Serious incidents||Numerous|
Table 2: Information collected from whosdrivingyou.com
The information collected indicates that overall satisfaction with the ride-sharing services is mainly high. It is a representation of the growing popularity of the ride-sharing service. However, the cross-sectional survey indicates that these services are preferred among the sample population. However, it also shows some challenges since the dissatisfaction rate is quite high as well. Negative feedbacks constituting almost a quarter of the respondents indicate severe problems in service delivery. The six-sigma approach requires that approximately 99.99966% of deliverables occur without a defect. However, the case here is extremely low standing at 78% of deliverables. As such, it is evident that there are significant problems in the reliability of quality in the ride-sharing industry. It also signifies a need for quality improvement in ensuring higher levels of satisfaction.
Further evaluation of the data shows that the customers rely on numerous factors to determine the quality of the ride. In this case, the rudeness of the driver and the safety of the trip were significant issues influencing customer satisfaction. Quite a large proportion of the riders felt that unsafe conditions and rude drivers led to a negative ride experience and reduced their satisfaction. Additionally, driver conduct was a factor that many of the respondents considered vital in promoting repeat rides with the same service. All these factors concern the driver. Therefore, one can conclude that the driver is a significant aspect of the trip and their competency and behavior contributed significantly to the customer’s level of satisfaction. This assessment shows that the driver should be the primary concern when instituting improvements to the service delivery process. This standpoint is emphasized by the data collected from www.whosdrivingyou.com. According to the site, drivers often operate without proper vetting. As such, the rideshare industry suffers significantly from criminal activities. As shown in the results section, drivers are responsible for numerous criminal acts including but not limited to sexual assault, kidnapping, murder, as well as other felonious acts. In fact, the data also shows that felon drivers and imposters even exist within the ride-sharing framework.
According to the lean philosophy, improvement occurs through the elimination or alterations of processes that contribute to waste. In this case, it remains evident the drivers are a source of significant problems. For instance, their association with criminal acts and the absence of proper vetting protocols undermine public confidence and trust in the business model leading to low adoption and consumer rates. In line with the lean philosophy, eliminating the challenge is necessary to facilitate increased satisfaction and to improve public trust in ride sharing. Therefore, current recruitment protocols should be abolished. Instead, they should be replaced with procedures that enhance accountability and responsibility among the drivers. For instance, ride-sharing organizations should request background checks for all its drivers before allowing them to use the service. These agencies should also follow up on the authenticity of the criminal history or lack thereof before commencing operations. Additionally, they should also use identification procedures such as facial recognition to ascertain the identity of the driver before initiating any ride. These measures are vital in ensuring rider satisfaction and deterring malicious acts.
- Excellent quality
- 100% Turnitin-safe
- Affordable prices
The ride-sharing industry thrives on customer satisfaction. It is because it deals directly with riders who can choose to maintain their subscription to the service or move onto another service. As such, these mediating companies have an obligation to ensure that customers receive the best possible service. However, the flexible and decentralized approach taken by the sharing economy has made it difficult to enforce policies and regulations at national or organizational levels. As an innovative product, the ride-sharing industry is susceptible to public perception sourced from rider experiences. For instance, there seem to be significant deficiencies in the quality of service provided mainly due to the conduct of the drivers. Inappropriate or criminal conduct allegations directed towards the drivers have a negative impact on the organization by diminishing the mediating organization’s reputation. Following the lean six-sigma approach, levels of satisfaction fall far below expectations. Therefore, improvement processes can focus on the driver, who is the cause of the dissatisfaction, by improving hiring and management processes. Ride-sharing organizations need to apply adequate recruitment techniques such as comprehensive vetting as well as management practices such as requiring identification before initiating a ride. These developments would enhance consumer confidence and trust in the industry.
FURTHER RESEARCH AND LIMITATIONS OF THE STUDY
The implications of this study focus on the value of the lean six-sigma model in defining, measuring, analyzing, and improving the supply chain. The sharing economy is a comparatively fresh concept in the business world today. As such, little research exists concerning quality assurance and improvement. Therefore, this study provides an exploratory or rather, foundation for future research on the topic. Recommended areas of research include driver welfare, customer safety, or accountability in the industry.
The main limitation of the study is the minimal nature of secondary information detailing incident records. Ride sharing is a global phenomenon indicating the presence of massive amounts of data on the issue. However, no single repository of this information exists. As such, the scope of the study is limited to the available data on the topic.
- Antony, J., Snee, R., & Hoerl, R. (2017). Lean six sigma: Yesterday, today and tomorrow. The International Journal of Quality & Reliability Management, 34(7), 1073.
- Cici, B., Markopoulou, A., Frias-Martinez, E., & Laoutaris, N. (2014, September). Assessing the potential of ride-sharing using mobile and social data: a tale of four cities. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 201-211). ACM.
- Comprehensive List of Uber Incidents and Assaults (2017). Who’s Driving You?. Retrieved 2 November 2017, from http://www.whosdrivingyou.org/rideshare-incidents
- Elliott, R. E. (2015). Sharing App or Regulation Hackney: Defining Uber Technologies, Inc. J. Corp. L., 41, 727.
- Ganapathy, V. (2016). Case Study: The Uberisation of Supply Chain. SAMVAD, 11, 26-31.
- Gobble, M. M. (2017). Defining the sharing economy. Research Technology Management, 60(2), 59. doi:10.1080/08956308.2017.1276393
- Herndon, N. C. (2017). The sharing economy: Opportunities and challenges for marketing channels and supply chains. Journal of Marketing Channels, 24(1-2), 1. doi:10.1080/1046669X.2017.1346970
- Jayaraman, K., Leam Kee, T., & Lin Soh, K. (2012). The perceptions and perspectives of lean six sigma (LSS) practitioners. The TQM Journal, 24(5), 433-446. doi:10.1108/17542731211261584
- Khuong, M. N., & Dai, N. Q. (2016). The Factors Affecting Customer Satisfaction and Customer Loyalty–A Study of Local Taxi Companies in Ho Chi Minh City, Vietnam. International Journal of Innovation, Management, and Technology, 7(5), 228.
- Kleiner, M. M. (2017). Regulating Access to Work in the Gig Labor Market: The Case of Uber. Employment Research Newsletter, 24(3), 2.
- Kollewe, J., & Topham, G. (2017). Uber apologizes after London ban and admits ‘we got things wrong.’ The Guardian. Retrieved 2 November 2017, from https://www.theguardian.com/business/2017/sep/25/uber-tfl-concerns-vows-keep-operating-london-licence
- Lee, C., Rahafrooz, M., & Lee, O. K. D. (2017). What are the Concerns of Using a Ride-Sharing Service?: An Investigation of Uber.
- Möhlmann, M. (2015). Collaborative consumption: Determinants of satisfaction and the likelihood of using a sharing economy option again. Journal of Consumer Behaviour, 14(3), 193-207. doi:10.1002/cb.1512Ocicka, B., & Wieteska, G. (2017). Sharing Economy in Logistics and Supply Chain Management. LogForum, 13(2).
- Ocicka, B., & Wieteska, G. (2017). Sharing Economy in Logistics and Supply Chain Management. LogForum, 13(2).
- Psychogios, A. G., Atanasovski, J., & Tsironis, L. K. (2012). Lean six sigma in a service context. International Journal of Quality & Reliability Management, 29(1), 122-139. doi:10.1108/02656711211190909
- Qureshi, M. I., Bashir, N., Zaman, K., Sajjad, N., & Fakhr, S. (2012). Customer Satisfaction Measurement and Analysis Using Six Sigma in Telecom Sector of Pakistan. European Journal of Sustainable Development, 1(1), 53.
- Rosenberg-Douglas, K. (2017). Prosecutors: Lyft driver accused of zip-tying, sexually assaulting passenger. chicagotribune.com. Retrieved 2 November 2017, from http://www.chicagotribune.com/news/local/breaking/ct-lyft-driver-arrested-after-zip-tying-sexually-assaulting-passenger-20170721-story.html
- Sahay, P. (2015). Lean six sigma tools in the hiring process. Strategic HR Review, 14(1/2), 22-29. doi:10.1108/SHR-06-2014-0040
- Samuels, G. (2016). Uber drivers accused of 32 rapes and sex attacks in London over the past year. The Independent. Retrieved 2 November 2017, from http://www.independent.co.uk/news/uk/uber-drivers-accused-of-32-rapes-and-sex-attacks-on-london-passengers-a7037926.html
- Santos, D. O., & Xavier, E. C. (2015). Taxi and ride sharing: A dynamic dial-a-ride problem with money as an incentive. Expert Systems with Applications, 42(19), 6728-6737.
- Spasojevic Brkic, V., & Tomic, B. (2016). Employees factors importance in lean six sigma concept. The TQM Journal, 28(5), 774-785. doi:10.1108/TQM-10-2015-0131
- Tsironis, L. K., & Psychogios, A. G. (2016). Road towards lean six sigma in service industry: A multi-factor integrated framework. Business Process Management Journal, 22(4), 812-834. doi:10.1108/BPMJ-08-2015-0118
- Ye, F., & Wang, Z. (2013). Effects of information technology alignment and information sharing on supply chain operational performance. Computers & Industrial Engineering, 65(3), 370-377.