What Can We Learn from Business Innovation Fail-ure of Uber in Southeast Asia Market?

Uber is a global pioneer in the sharing economy platform entitled ride-hailing. It started to enter the Asian market in 2013-2014 with various community responses in each region. In March 2018, Uber withdrew from the competition in Southeast Asia after being acquired by one of the dominant players in the region, Grab. In connection with Uber's failure to operate its business in the region, this paper discusses Uber's business model, business expansion, competition in the market, and the factors that led to Uber's failure in the Southeast Asian market. To comprehensively describe the developing context, we used a qualitative method with a systematic data collection approach from literature reviews in conducting this study. This study emphasizes that large funding supports do not guarantee the success of business operations in a more globalized setting. Different market characteristics require different approaches. The case of Uber's failure in the Southeast Asian market, even though it was supported by large funds to "Uberize the entire world," proves that the characteristics made more "localized" are more likely at a certain point in time to survive. This study also underlines some learning points from the dominant factors causing the failure of Uber's business operations in the region that require immediate adaptation: non-conformity with market preferences, challenges from prevailing policies and infrastructure issues, and strong competition from local competitors

Exploration of the Current State and Directions of Dynamic Ridesharing

Dynamic ridesharing (DRS) is an emerging transportation service based on the traditional concept of shared rides. DRS makes use of web-based real-time technologies to match drivers with riders. Enabling technologies include software platforms that operate on mobile communication devices and contain location-aware capabilities including Global Positioning Systems (Agatz, Erera, Savelsberg, & Wang, 2012). The platforms are designed to provide ride-matching services via smartphone applications differing from early systems that used non-real time services such as internet forums, or telecommunications, where responses were not immediate. The study of DRS is important when considering its role as an emerging transportation demand management strategy. DRS reduces travel demand on singleoccupancy vehicles (SOVs) by filling vehicle seats that are typically left vacant. The most recent statistics of vehicle occupancy rates were measured in 2009 by the National Household Travel Survey (NHTS), conducted by the U.S. Department of Transportation. According to the NHTS, the 2009 occupancy rate for all purposes was a meager 1.67 persons per vehicle (Federal Highway Administration, 2015). Vehicle occupancy rates examined against the total of all registered highway vehicles in the U.S. as of 2012, calculated at 253,639,386 (Bureau of Transportation Statistics, 2015), reveals the magnitude of the impact of SOVs. Left unattended, the ramifications for environmental outcomes is substantial. Among the major energy consuming sectors, transportation\u27s share is largest in terms of total CO2 emissions at 32.9% (Davis, Diegel, & Boundy, 2014, p. 11-15). DRS offers promise to fill empty vehicle seats. Evidence indicates that specific demographic subgroups are inclined to use DRS services. For example, data suggest that the subgroup of 18 to 34-year-olds, the so-called millennials , have negative attitudes towards private car ownership unlike previous age groups (Nelson, 2013). Data collected for this study revealed that the millennial subgroup represents half of all DRS users. Millennials also revealed they tended to use DRS more than other subgroups to replace a private vehicle. Further research is needed to determine if the trend towards DRS by 18 to 34-year-olds represents current economic factors or a fundamental cultural shift away from the SOV transportation model

No woman's land:Feminist approaches to the ride-hailing sector and digital labor platforms in India

In this dissertation, I investigate the concerns, issues and opportunities for platform labor reform with a focus on the ride-hailing sector using Bardzell (2010)’s feminist lens. The feminist viewpoint keeps the marginal user at the center committing to equity, diversity, identity, empowerment, and social justice to improve the work conditions of gig workers in the Global South. By conducting in-depth qualitative interviews with the different stakeholders of the ride-hailing sector, and analysing case studies, media coverage, policy papers, and research reports, I suggest guidelines for redesigning the digital labor platforms

No woman's land:Feminist approaches to the ride-hailing sector and digital labor platforms in India

In this dissertation, I investigate the concerns, issues and opportunities for platform labor reform with a focus on the ride-hailing sector using Bardzell (2010)’s feminist lens. The feminist viewpoint keeps the marginal user at the center committing to equity, diversity, identity, empowerment, and social justice to improve the work conditions of gig workers in the Global South. By conducting in-depth qualitative interviews with the different stakeholders of the ride-hailing sector, and analysing case studies, media coverage, policy papers, and research reports, I suggest guidelines for redesigning the digital labor platforms

Review of California Wildfire Evacuations from 2017 to 2019

Between 2017 and 2019, California experienced a series of devastating wildfires that together led over one million people to be ordered to evacuate. Due to the speed of many of these wildfires, residents across California found themselves in challenging evacuation situations, often at night and with little time to escape. These evacuations placed considerable stress on public resources and infrastructure for both transportation and sheltering. In the face of these clear challenges, transportation and emergency management agencies across California have widely varying levels of preparedness for major disasters, and nearly all agencies do not have the public resources to adequately and swiftly evacuate all populations in danger. To holistically address these challenges and bolster current disaster and evacuation planning, preparedness, and response in California, we summarize the evacuations of eleven major wildfires in California between 2017 and 2019 and offer a cross-comparison to highlight key similarities and differences. We present results of new empirical data we collected via an online survey of individuals impacted by: 1) the 2017 October Northern California Wildfires (n=79), 2) the 2017 December Southern California Wildfires (n=226), and 3) the 2018 Carr Wildfire (n=284). These data reveal the decision-making of individuals in these wildfires including choices related to evacuating or staying, departure timing, route, sheltering, destination, transportation mode, and reentry timing. We also present results related to communication and messaging, non-evacuee behavior, and opinion of government response. Using the summarized case studies and empirical evidence, we present a series of recommendations for agencies to prepare for, respond to, and recover from wildfires

Peer-to-Peer Energy Trading in Smart Residential Environment with User Behavioral Modeling

Electric power systems are transforming from a centralized unidirectional market to a decentralized open market. With this shift, the end-users have the possibility to actively participate in local energy exchanges, with or without the involvement of the main grid. Rapidly reducing prices for Renewable Energy Technologies (RETs), supported by their ease of installation and operation, with the facilitation of Electric Vehicles (EV) and Smart Grid (SG) technologies to make bidirectional flow of energy possible, has contributed to this changing landscape in the distribution side of the traditional power grid. Trading energy among users in a decentralized fashion has been referred to as Peer- to-Peer (P2P) Energy Trading, which has attracted significant attention from the research and industry communities in recent times. However, previous research has mostly focused on engineering aspects of P2P energy trading systems, often neglecting the central role of users in such systems. P2P trading mechanisms require active participation from users to decide factors such as selling prices, storing versus trading energy, and selection of energy sources among others. The complexity of these tasks, paired with the limited cognitive and time capabilities of human users, can result sub-optimal decisions or even abandonment of such systems if performance is not satisfactory. Therefore, it is of paramount importance for P2P energy trading systems to incorporate user behavioral modeling that captures users’ individual trading behaviors, preferences, and perceived utility in a realistic and accurate manner. Often, such user behavioral models are not known a priori in real-world settings, and therefore need to be learned online as the P2P system is operating. In this thesis, we design novel algorithms for P2P energy trading. By exploiting a variety of statistical, algorithmic, machine learning, and behavioral economics tools, we propose solutions that are able to jointly optimize the system performance while taking into account and learning realistic model of user behavior. The results in this dissertation has been published in IEEE Transactions on Green Communications and Networking 2021, Proceedings of IEEE Global Communication Conference 2022, Proceedings of IEEE Conference on Pervasive Computing and Communications 2023 and ACM Transactions on Evolutionary Learning and Optimization 2023

Shifting from Driving to Riding: a study of the impacts of on-demand cab services on public transit ridership and vehicle ownership in Hyderabad, India

This thesis explores the effects of on-demand cab services, Uber and Ola, on public transit ridership and vehicle ownership in Hyderabad, India. India has grown to be Uber’s third largest market in the world but still lacks any comprehensive policies at the federal level to regulate on-demand cab services. These services have risen in popularity and have led to the evolution of new ownership and financial models to help populations afford a car to “drive to work.” This research examines the spatial effects of this rising popularity on public transit ridership and vehicle ownership in Hyderabad. This research found that there has been a shift in the proportion of on-demand cabs and cars to all vehicles from 2010 to 2016. This research also found that annual occupancy ratio along bus routes in the city has decreased from 2014 to 2016. This research found that these relationships are localized in the city. This thesis concludes by recommending further studies be carried out to understand the full extent of these effects to effectively incorporate these technologies and plan for the future mobility of city residents