Generic time- and method-interdependencies of empirical impact-measurements: A generalizable model of adaptation-processes of carsharing-users' mobility-behavior over time

Firnkorn, Jörg; Shaheen, Susan

doi:10.1016/j.jclepro.2015.09.115

Cited by 21 publications

(3 citation statements)

References 67 publications

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“…The study involved all three categories of PSS, investigating for example reuse and recycle in the case of product-oriented PSS (which can be considered the main elements behind circular economy concept), and collaborative consumption and sharing models in the case of use-oriented PSS. Indeed this example shows a renewed interest in business models and sustainability, as evidenced also by other recent works (Emili et al, 2016;Firnkorn and Shaheen, 2016;Pereira et al, 2016) Furthermore, from the analysis of main topics (Table 5), we found a very small number of publications dealing with the topic of economic analysis of PSS and with social/environmental analysis.…”

Section: Future Research Directionssupporting

confidence: 73%

Product service system: A conceptual framework from a systematic review

Annarelli

Battistella

Nonino

2016

Journal of Cleaner Production

301

188

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This paper sets out to contribute to a critical theory debate through the presentation and use of a framework for the categorisation of literature linked to Product Service System (PSS).Moving from the analysis of literature we provide a conceptual structure depicting the current situation of literature dealing with the analysis of economic impact and environmental/social impact of Product Service System. Moreover, we provide a methodological structure, concerning methodologies and research purpose behind papers.Despite the lack of a unique and well-accepted definition, authors seem to agree in recognizing the PSS as a business model, although this necessitates a deeper theoretical insight.Literature mainly agrees about PSS benefits, barriers, and partly also on drivers, but from the descriptive and thematic analysis what emerged is a lack of clarity about PSS and its main fields: it started as a topic closely connected with sustainability, but subsequently different fields have developed other terminologies and focuses of research, developing their own theoretical base and frameworks. Therefore, we have found a lack of interconnection among fields and subject areas.A critical aspect in current literature is about the analysis/evaluation of Product Service System performance: economic and environmental analyses should be updated with new methodologies and new perspectives (i.e. privileging an ex post perspective rather than an ex ante one). Furthermore, these analyses should be integrated in a unique tool, which would be essential in providing a complete perspective on the PSS phenomenon and its effects.Finally, we propose and discuss main future research directions, connected to the main current research streams: sustainability, Product Service System business models and collaborative consumption.

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Section: Future Research Directionssupporting

confidence: 73%

Product service system: A conceptual framework from a systematic review

Annarelli

Battistella

Nonino

2016

Journal of Cleaner Production

301

188

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“…This result could indicate a low perception of carsharing as a way of reducing environmental impact (since it is car-based). Despite the forecasted reduction in CO2 emissions and land use due to the use of carsharing instead of private cars [72], the impact assessment of the carsharing is complex, and it depends on the time framings of methodological designs (if it is cross-sectional, 'before-after' or longitudinal designs) [73]. Additionally, other factors can be more relevant to the decision to use carsharing, and concerns toward the environment are not always aligned with pro-environmental behavior performance [74].…”

Section: Discussionmentioning

confidence: 99%

The Psychology of Sharing: Multigroup Analysis among Users and Non-Users of Carsharing

Ramos

Bergstad

2021

Sustainability

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The present study investigates the determinants of intention to use carsharing services by an integrated model of psychological predictors of travel behavior. The model proposed is tested by multigroup confirmatory factor analysis (MGCFA) in structural equation modeling (SEM) with further discussion about analysis of invariance and its relevance for comparisons between groups. The sample was classified into four groups: Italian users, Italian non-users, Swedish users, and Swedish non-users of carsharing. The users were respondents who have used or are currently using carsharing, while non-users reported never using the carsharing services. The analysis of data from 6072 respondents revealed that control was the main predictor of intention to use carsharing; driving habits had stronger negative effects for users of carsharing than for non-users; subjective norms positively predicted the intention to use carsharing among all groups; trust was a predictor of intention only for the Italian groups; and climate morality had a small negative effect on the Swedish groups only. The outcomes of this investigation will increase the knowledge about the use of carsharing and help to identify the behavioral and psychological factors that primarily influence people’s intention to use it.

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“…In 2015, China presented the biggest fleet in the world with 753,508 bicycles, followed by France with 42,930, and Spain with 25,084 ( 4 ). Categorization of bike sharing systems can be defined by the use of stations or not: (a) station-based (SBBS), b) free-floating (FFBS), and c) a mix of the two ( 5 ).…”

mentioning

confidence: 99%

Built Environment Factors Affecting Bike Sharing Ridership: Data-Driven Approach for Multiple Cities

Durán-Rodas

Chaniotakis

Antoniou

2019

Transportation Research Record: Journal of the Transportation R

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Identification of factors influencing ridership is necessary for policy-making, as well as, when examining transferability and aspects of performance and reliability. In this work, a data-driven method is formulated to correlate arrivals and departures of station-based bike sharing systems with built environment factors in multiple cities. Ridership data from stations of multiple cities are pooled in one data set regardless of their geographic boundaries. The method bundles the collection, analysis, and processing of data, as well as, the model’s estimation using statistical and machine learning techniques. The method was applied on a national level in six cities in Germany, and also on an international level in three cities in Europe and North America. The results suggest that the model’s performance did not depend on clustering cities by size but by the relative daily distribution of the rentals. Selected statistically significant factors were identified to vary temporally (e.g., nightclubs were significant during the night). The most influencing variables were related to the city population, distance to city center, leisure-related establishments, and transport-related infrastructure. This data-driven method can help as a support decision-making tool to implement or expand bike sharing systems.

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Generic time- and method-interdependencies of empirical impact-measurements: A generalizable model of adaptation-processes of carsharing-users' mobility-behavior over time

Cited by 21 publications

References 67 publications

Product service system: A conceptual framework from a systematic review

Product service system: A conceptual framework from a systematic review

The Psychology of Sharing: Multigroup Analysis among Users and Non-Users of Carsharing

Built Environment Factors Affecting Bike Sharing Ridership: Data-Driven Approach for Multiple Cities

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