scholarly journals Evaluation of Environmental Impact of Car Sharing in Consideration of Uncertainty of Influential Variables

2020 ◽  
Vol 14 (6) ◽  
pp. 975-983
Author(s):  
Katsuya Tsuji ◽  
◽  
Kiyo Kurisu ◽  
Jun Nakatani ◽  
Yuichi Moriguchi
Keyword(s):  
Sensitivity Analysis ◽  
Service Providers ◽  
Rebound Effect ◽  
Environmentally Friendly ◽  
Sharing Economy ◽  
Influential Factors ◽  
Car Sharing ◽  
New Production ◽  
Rebound Effects ◽  
The Impact

Sustainable production and consumption are categorized as target 12 in the United Nations’ Sustainable Development Goals. The “sharing economy” has been developing globally as a new consumption style, and it is often recognized as being environmentally friendly by both consumers and service providers. Several aspects of the practice, such as the avoidance of new production, can reduce the impact to the environment. However, additional factors, such as the expansion of consumption, namely rebound effects, can increase the impact to the environment. Although many variables exist to determine the total impact of sharing services on the environment, additional and rebound effects and the uncertainty of influential variables have not been well considered. In this study, we aim to reveal the conditions that car-sharing practices place in increasing or decreasing environmental loads, and to identify the significant influential factors on the environment imposed by car-sharing services. We analyze the CO2 emission of car sharing by considering various influential factors and their distributions. Furthermore, we consider differences in car size, fuel type, ownership condition, and several other factors in the simulation. The distribution of each variable is determined, and a Monte Carlo simulation is conducted. The CO2 emissions from the production and operational stages over a 10-y period are estimated. The simulation is conducted with sensitivity analysis to identify the variables that contribute significantly to the total CO2 emission. In some cases, the CO2 emission involved in car sharing exceeded cases in which car sharing is not practiced. Among those cases, although the main contributor to the total CO2 emission is in the operational stage, CO2 emission from the production stage increased the amount of emission. It is discovered that the number of cars increased significantly during the target 10 y after sharing is introduced in some cases. These results indicate a high probability that car sharing can achieve CO2 reduction, but the increase in CO2 emission can occur under certain conditions. Additionally, the sensitivity analysis shows that the main determinants of CO2 emission are the ratio of people who eliminated their private cars, degree of rebound effect, and increasing ratio of number of cars introduced to car-sharing practices. This suggests that whether car sharing becomes environmentally friendly depends substantially on consumer behavior and the manner in which sharing services are operated.

Drivers, Riders, and Service Providers: The Impact of the Sharing Economy on Mobility

2021 ◽  
Author(s):  
Saif Benjaafar ◽  
Harald Bernhard ◽  
Costas Courcoubetis ◽  
Michail Kanakakis ◽  
Spyridon Papafragkos
Keyword(s):  
Operations Management ◽  
Service Providers ◽  
Sharing Economy ◽  
Car Ownership ◽  
Full Time ◽  
Ride Sharing ◽  
Finite Set ◽  
Nonatomic Game ◽  
Payoff Functions ◽  
The Impact

It is widely believed that ride sharing, the practice of sharing a car such that more than one person travels in the car during a journey, has the potential to significantly reduce traffic by filling up cars more efficiently. We introduce a model in which individuals may share rides for a certain fee, paid by the rider(s) to the driver through a ride-sharing platform. Collective decision making is modeled as an anonymous nonatomic game with a finite set of strategies and payoff functions among individuals who are heterogeneous in their income. We examine how ride sharing is organized and how traffic and ownership are affected if a platform, which chooses the seat rental price to maximize either revenue or welfare, is introduced to a population. We find that the ratio of ownership to usage costs determines how ride sharing is organized. If this ratio is low, ride sharing is offered as a peer-to-peer (P2P) service, and if this ratio is high, ride sharing is offered as a business-to-customer (B2C) service. In the P2P case, rides are initiated by drivers only when the drivers need to fulfill their own transportation requirements. In the B2C case, cars are driven all the time by full-time drivers taking rides even if these are not motivated by their private needs. We show that, although the introduction of ride sharing may reduce car ownership, it can lead to an increase in traffic. We also show that traffic and ownership may increase as the ownership cost increases and that a revenue-maximizing platform might prefer a situation in which cars are driven with only a few seats occupied, causing high traffic. We contrast these results with those obtained for a social welfare-maximizing platform. This paper was accepted by Charles Corbett, operations management.

Preferences for car sharing service attributes among university students: Evidence from an emerging market

2019 ◽  
Vol 24 (4) ◽  
pp. 636-653
Author(s):  
Nataša Bojković ◽  
Veljko Jeremić ◽  
Marijana Petrović ◽  
Slaven Tica
Keyword(s):  
University Students ◽  
Service Providers ◽  
Stated Preference ◽  
Emerging Market ◽  
Developed Countries ◽  
Sharing Economy ◽  
User Preferences ◽  
Point Of View ◽  
Car Sharing ◽  
Initiation Phase

Car sharing is a specific business model that allows a new form of personal mobility. University students, generally very receptive to the concept of a sharing economy, are recognized as a prospective customer group for car sharing operators. This paper proposes an ex ante analysis that aims to reveal how students from an area where car sharing is underdeveloped perceive this mobility option. University students in Belgrade were asked to state their preferences regarding a mix of attributes and levels replicating service design from current practice. Preferences for particular service attributes were explored using stated preference survey and Choice-Based Conjoint analysis, while further preference-based segmentation was obtained using the Partitioning Around Medoids method. The contribution of this work is that it delivers findings on an emerging car-sharing market where there is very little research on user profiles. From a methodological point of view, we form distinctive customer clusters based on the uniformity of their preferences. By being aware of users’ prior expectations, service providers can determine their operational priorities more easily when unlocking the market. The paper outlines both the similarities and differences between students in an emerging market and their counterparts in more developed countries. Our findings reveal that the student population is homogeneous regarding critical aspects of service adoption like cost, distance to vehicles, and parking convenience. Specific service attributes such as the pricing scheme and keeping vehicles clean are found to be issues of peculiar interest in our study market. Although our proposed approach to shaping user preferences was developed for car sharing analysis it is applicable to other service-oriented businesses in the initiation phase.

scholarly journals Does Car-Sharing Reduce Car Ownership? Empirical Evidence from Germany

2021 ◽  
Vol 13 (13) ◽  
pp. 7384
Author(s):  
Aaron Kolleck
Keyword(s):  
Business Models ◽  
Operating Mode ◽  
Sharing Economy ◽  
Car Ownership ◽  
Future Research ◽  
Vehicle Miles Traveled ◽  
Car Sharing ◽  
The Impact ◽  
German Cities ◽  
Additional Station

The sharing economy is making its way into our everyday lives. One of its business models, car-sharing, has become highly popular. Can it help us increase our sustainability? Besides emissions and vehicle miles traveled, one key aspect in the assessment regards the effect of car-sharing on car ownership. Previous studies investigating this effect have relied almost exclusively on surveys and come to very heterogeneous results, partly suggesting spectacular substitution rates between shared and private cars. This study empirically explores the impact of car-sharing on noncorporate car ownership and car markets in 35 large German cities. The analysis draws on publicly available data for the years 2012, 2013, 2015, and 2017, including, among others, the number of shared cars per operating mode (free-floating and station-based) and the number of cars owned and registered by private individuals (i.e., excluding company cars). We find that one additional station-based car is associated with a reduction of about nine private cars. We do not find a statistically significant relation between car ownership and free-floating car-sharing. Neither type of car-sharing appears to impact the markets for used and new cars significantly. Given the measurable impacts on car ownership levels, this result is surprising and invites future research to study car-sharing’s impact on the dynamics of car markets.

scholarly journals The sharing economy and management of a sustainable environment in the tourism sector on a global scale

Turyzm ◽  
2019 ◽  
Vol 29 (2) ◽  
pp. 19-22
Author(s):  
Ruhet Genç
Keyword(s):  
Environmental Sustainability ◽  
Global Economy ◽  
Service Providers ◽  
Global Scale ◽  
Sharing Economy ◽  
Ecological Sustainability ◽  
Collaborative Consumption ◽  
Sustainable Environment ◽  
Tourism Sector ◽  
The Impact

The paper will discuss the impact of development of sharing economy on ecological sustainability for the tourism sector at global scale since the main focus in the literature is generally limited to economic and social impacts. It will provide a mathematical model in order to measure the impact of the sharing economy on the welfare of individuals who take part in particular tourism destinations as well as providing benefits for other individuals as a positive external outlook. The development of the model will be dependent on the findings obtained in this study. The results will show that the sharing economy together with collaborative consumption in the tourism sector is an increasing trend in global economy that contributes to ecological sustainability as well. By sharing the means of production, transportation, communication etc both tourists and service providers are capable of decreasing their ecological footprints. In conclusion the paper will contribute to the literature by filling a gap with respect to the lack of connection between environmental sustainability and sharing economy in tourism sector.

Competition Between Two-Sided Platforms Under Demand and Supply Congestion Effects

2020 ◽  
Author(s):  
Fernando Bernstein ◽  
Gregory A. DeCroix ◽  
N. Bora Keskin
Keyword(s):  
Service Providers ◽  
Supply And Demand ◽  
Relative Number ◽  
Sharing Economy ◽  
Problem Definition ◽  
Ride Sharing ◽  
Managerial Implications ◽  
The Impact ◽  
Number Of Customers ◽  
Congestion Effects

Problem definition: This paper explores the impact of competition between platforms in the sharing economy. Examples include the cases of Uber and Lyft in the context of ride-sharing platforms. In particular, we consider competition between two platforms that offer a common service (e.g., rides) through a set of independent service providers (e.g., drivers) to a market of customers. Each platform sets a price that is charged to customers for obtaining the service provided by a driver. A portion of that price is paid to the driver who delivers the service. Both customers’ and drivers’ utilities are sensitive to the payment terms set by the platform and are also sensitive to congestion in the system (given by the relative number of customers and drivers in the market). We consider two possible settings. The first one, termed “single-homing,” assumes that drivers work through a single platform. In the second setting, termed “multihoming” (or “multiapping,” as it is known in practice), drivers deliver their service through both platforms. Academic/practical relevance: This is one of the first papers to study competition and multihoming in the presence of congestion effects typically observed in the sharing economy. We leverage the model to study some practical questions that have received significant press attention (and stirred some controversies) in the ride-sharing industry. The first involves the issue of surge pricing. The second involves the increasingly common practice of drivers choosing to operate on multiple platforms (multihoming). Methodology: We formulate our problem as a pricing game between two platforms and employ the concept of a Nash equilibrium to analyze equilibrium outcomes in various settings. Results: In both the single-homing and multihoming settings, we study the equilibrium prices that emerge from the competitive interaction between the platforms and explore the supply and demand outcomes that can arise at equilibrium. We build on these equilibrium results to study the impact of surge pricing in response to a surge in demand and to examine the incentives at play when drivers engage in multihoming. Managerial implications: We find that raising prices in response to a surge in demand makes drivers and customers better off than if platforms were constrained to charge the same prices that would arise under normal demand levels. We also compare drivers’ and customers’ performance when all drivers either single-home or multihome. We find that although individual drivers may have an incentive to multihome, all players are worse off when all drivers multihome. We conclude by proposing an incentive mechanism to discourage multihoming.

COVID-19 effective reproduction number determination: an application, and a review of issues and influential factors

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Luis Alfredo Bautista Balbás ◽  
Mario Gil Conesa ◽  
Blanca Bautista Balbás ◽  
Gil Rodríguez Caravaca
Keyword(s):  
Sensitivity Analysis ◽  
Web Application ◽  
Reproduction Number ◽  
Infected Individual ◽  
National Level ◽  
Conclusive Evidence ◽  
Influential Factors ◽  
Estimation Methods ◽  
Serial Interval ◽  
The Impact

Abstract Objectives An essential indicator of COVID-19 transmission is the effective reproduction number (R t ), the number of cases which an infected individual is expected to infect at a particular point in time; curves of the evolution of R t over time (transmission curves) reflect the impact of preventive measures and whether an epidemic is controlled. Methods We have created a Shiny/R web application (https://alfredob.shinyapps.io/estR0/) with user-selectable features: open data sources with daily COVID-19 incidences from all countries and many regions, customizable preprocessing options (smoothing, proportional increment, etc.), different MonteCarlo-Markov-Chain estimates of the generation time or serial interval distributions and state-of-the-art R t estimation frameworks (EpiEstim, R 0). This application could be used as a tool both to obtain transmission estimates and to perform interactive sensitivity analysis. We have analyzed the impact of these factors on transmission curves. We also have obtained curves at the national and sub-national level and analyzed the impact of epidemic control strategies, superspreading events, socioeconomic factors and outbreaks. Results Reproduction numbers showed earlier anticipation compared to active prevalence indicators (14-day cumulative incidence, overall infectivity). In the sensitivity analysis, the impact of different R t estimation methods was moderate/small, and the impact of different serial interval distributions was very small. We couldn’t find conclusive evidence regarding the impact of alleged superspreading events. As a limitation, dataset quality can limit the reliability of the estimates. Conclusions The thorough review of many examples of COVID-19 transmission curves support the usage of R t estimates as a robust transmission indicator.

scholarly journals Shared accommodation as a globalization trend in tourism

2020 ◽  
Vol 74 ◽  
pp. 03002
Author(s):  
Miroslava Kostková
Keyword(s):  
Service Providers ◽  
Marketing Research ◽  
Sharing Economy ◽  
Playing Field ◽  
Global Trend ◽  
Traditional Service ◽  
Modern Economic ◽  
Tourism Service ◽  
Tourist Accommodation ◽  
The Impact

Modern tourism trends have a distinctly global character. They include the use of online tourism service platforms and the sharing of services based on sharing economy. Governments and municipalities create regulatory measures to operate in accordance with the destination’s municipal, financial, security, and tourism interests to ensure transparency and a level playing field for entrepreneurship. The paper deals with this global trend in the field of the accommodation services through the Airbnb platform in the Czech Republic and in the Silesian Moravian Region, in the use and provision of tourist accommodation services and identification of the impact on tourism development and tourist attendance the destination, within the project Trends of tourism in the Moravian-Silesian Region, using the methods of marketing research. The results declare that shared economy platforms in the field of accommodation have a place in the modern economic system, they put competitive pressure on tourism service providers, the offer expands for the consumers and traditional service providers force to move to innovative concepts. The hoteliers want to offer the creation of standards that the sharing accommodation providers should follow and public administration and city representatives want to clearly describe the duties for each accommodation provider and regulate accommodation through Airbnb.

scholarly journals Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of Mangroves

2021 ◽  
Vol 13 (13) ◽  
pp. 2617
Author(s):  
Chunyue Niu ◽  
Stuart Phinn ◽  
Chris Roelfsema
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Vegetation Indices ◽  
Influential Factors ◽  
Canopy Reflectance ◽  
Biophysical Properties ◽  
Area Index ◽  
Fractional Cover ◽  
Sensitivity Indices ◽  
The Impact

Remote sensing has been applied to map the extent and biophysical properties of mangroves. However, the impact of several critical factors, such as the fractional cover and leaf-to-total area ratio of mangroves, on their canopy reflectance have rarely been reported. In this study, a systematic global sensitivity analysis was performed for mangroves based on a one-dimensional canopy reflectance model. Different scenarios such as sparse or dense canopies were set up to evaluate the impact of various biophysical and environmental factors, together with their ranges and probability distributions, on simulated canopy reflectance spectra and selected Sentinel-2A vegetation indices of mangroves. A variance-based method and a density-based method were adopted to compare the computed sensitivity indices. Our results showed that the fractional cover and leaf-to-total area ratio of mangrove crowns were among the most influential factors for all examined scenarios. As for other factors, plant area index and water depth were influential for sparse canopies while leaf biochemical properties and inclination angles were more influential for dense canopies. Therefore, these influential factors may need attention when mapping the biophysical properties of mangroves such as leaf area index. Moreover, a tailored sensitivity analysis is recommended for a specific mapping application as the computed sensitivity indices may be different if a specific input configuration and sensitivity analysis method are adopted.

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