Identifying car-sharing quality determinants: a data-driven approach to improve engineering design
Identifying car-sharing quality determinants: a data-driven approach to improve engineering design
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Purpose – This study aims at identifying the quality determinants of car-sharing services, analyzing unstructured User-Generated Contents (UGCs) and, more specifically, online reviews generated by users of the same car-sharing service. Moreover, this paper discusses the implication of the proposed data-driven approach on engineering design.
Methodology – A large dataset of car-sharing users’ online reviews was analyzed by means of the Structural Topic Model (STM), i.e. a variant of Latent Dirichlet Allocation (LDA) technique which discovers underlying topics in a collection of documents also using document-level covariate information.
Findings – This paper reports an analysis of UGCs related to different car-sharing services. The analysis unveils 20 determinants of car-sharing quality: customer service (physical office); accident
& damages management; registration process; charges & fees; parking areas; app reliability; end trip issues; car condition; convenience; use rates; car proximity; car availability; efficacy; sharing benefits; customer service responsiveness; intermodal transportation; car start-up issues; customer service courtesy; billing and membership; car reservation.
Originality – This paper proposes a novel approach to identify quality determinants by analyzing UGCs. The study of the quality determinants of a car-sharing service is a scarcely discussed field of research although the car-sharing sector is an increasingly important part of the transport economy.
See paper
Aggarwal, C. C. and Zhai, C. (2012) Mining text data. Springer-Verlag New York.
Blei, D. M. (2012) ‘Probabilistic topic models’, Communications of the ACM, Vol. 55 No. 4, pp. 77–84.
Blei, D. M. and Lafferty, J. D. (2007) ‘A correlated topic model of science’, The Annals of Applied Statistics, Vol. 1 No. 1, pp. 17–35.
Blei, D. M., Ng, A. Y. and Jordan, M. I. (2003) ‘Latent dirichlet allocation’, Journal of machine Learning research, Vol. 3 , pp. 993–1022.
Boyaci, B., Zografos, K. G. and Geroliminis, N. (2015) ‘An optimization framework for the development of efficient one-way car-sharing systems’, European Journal of Operational Research, Vol. 240 No. 3, pp. 718–733.
Costa, E., Lorena, A., Carvalho, A. and Freitas, A. (2007) ‘A review of performance evaluation measures for hierarchical classifiers’, in Evaluation Methods for machine Learning II: papers from the AAAI-2007 Workshop, pp. 1–6.
Frost & Sullivan (2016) ‘Future of Carsharing Market to 2025’. Available at: https://www.statista.com/statistics/415636/car-sharing-number-of-users-worldwide/.
Guglielmetti Mugion, R., Toni, M., Di Pietro, L., Pasca, M. G. and Renzi, M. F. (2019) ‘Understanding the antecedents of car sharing usage. An empirical study in Italy’, International Journal of Quality and Service Sciences, Vol. 11 No. 4, pp. 523–541.
Guo, Y., Barnes, S. J. and Jia, Q. (2017) ‘Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation’, Tourism Management, Vol. 59 , pp. 467–483.
Illgen, S. and Höck, M. (2019) ‘Literature review of the vehicle relocation problem in one-way car sharing networks’, Transportation Research Part B: Methodological, Vol. 120 , pp. 193–204.
Jeong, Y., Yang, Y., Suk, J. and Kim, K. (2019) ‘A text-mining analysis of online reviews on car- sharing services’, in International Conferences on Internet Technologies & Society 2019, pp. 167– 169.
Jivani, A. G. (2011) ‘A comparative study of stemming algorithms’, International Journal of Computer Applications in Technology, Vol. 2 No. 6, pp. 1930–1938.
Mastrogiacomo, L., Barravecchia, F. and Franceschini, F. (2019) ‘A worldwide survey on manufacturing servitization’, The International Journal of Advanced Manufacturing Technology, Vol. 103 , pp. 3927–3942.
Mastrogiacomo, Luca, Barravecchia, F. and Franceschini, F. (2020) ‘Definition of a conceptual scale of servitization: Proposal and preliminary results’, CIRP Journal of Manufacturing Science and Technology, Vol. 29 No. Part B, pp. 141–156.
Mastrogiacomo, L., Barravecchia, F. and Franceschini, F. (2020) ‘Enabling factors of manufacturing servitization: empirical analysis and implications for strategic positioning’, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 234 No. 9, pp. 1258–1270.
Meyer, D., Hornik, K. and Feinerer, I. (2008) ‘Text mining infrastructure in R’, Journal of statistical software, Vol. 25 No. 5, pp. 1–54.
Möhlmann, M. (2015) ‘Collaborative consumption: Determinants of satisfaction and the likelihood of using a sharing economy option again’, Journal of Consumer Behaviour, Vol. 14 No. 3, pp. 193– 207.
Müller, O., Junglas, I., vom Brocke, J. and Debortoli, S. (2016) ‘Utilizing big data analytics for information systems research: challenges, promises and guidelines’, European Journal of Information Systems, Vol. 25 No. 4, pp. 289–302.
Nassirtoussi, A. K., Aghabozorgi, S., Wah, T. Y. and Ngo, D. C. L. (2014) ‘Text mining for market prediction: A systematic review’, Expert Systems with Applications, Vol. 41 No. 16, pp. 7653–7670.
Prescient & Strategic Intelligence (2019) Carsharing Market by Car, by Fuel Type, by Business Model, by Application, by Geography Global Market Size, Share, Development, Growth, and Demand Forecast, 2014-2025. Available at: https://www.psmarketresearch.com/market-analysis/car- sharing-market.
Roberts, M. E., Stewart, B. M., Tingley, D., Lucas, C., Leder‐Luis, J., Gadarian, S. K., Albertson, B. and Rand, D. G. (2014) ‘Structural topic models for open‐ended survey responses’, American Journal of Political Science, Vol. 58 No. 4, pp. 1064–1082.
Roberts, M. E., Stewart, B. M. and Tingley, D. (2019) ‘STM: R package for structural topic models’, Journal of Statistical Software, Vol. 91 No. 2, pp. 1–40.
Scott, J. and Baldridge, J. (2013) ‘A recursive estimate for the predictive likelihood in a topic model’, Journal of Machine Learning Research, Vol. 31 , pp. 527–535.
Shaheen, S. A. and Cohen, A. P. (2007) ‘Growth in worldwide carsharing: An international comparison’, Transportation Research Record, Vol. 1992 No. 1, pp. 81–89.
Shaheen, S. A. and Cohen, A. P. (2013) ‘Carsharing and personal vehicle services: worldwide market developments and emerging trends’, International Journal of Sustainable Transportation, Vol. 7 No. 1, pp. 5–34.
Wallach, H. M., Mimno, D. M. and McCallum, A. (2009) ‘Rethinking LDA: Why priors matter’, Advances in neural information processing systems, Vol. 23 , pp. 1973–1981.
Zaki, M. and McColl-Kennedy, J. R. (2020) ‘Text Mining Analysis Roadmap (TMAR) for Service’, Journal of Services Marketing, Vol. 34 No. 1, pp. 30–47.
Car-sharing, Quality determinants, User-Generated Contents, Topic modelling
