Chapter 11 Big Data and Digital Marketing in the Sharing Economy
Published: April 2022
Component type: chapter
Published in: The Sharing Economy and the Tourism Industry
Parent DOI: 10.23912/9781915097064-4970
‘Big data’ refers to datasets that are continuously generated from many sources and can be fully structured or completely unstructured (Sheng et al., 2017: 98). Big data is considered beneficial because its effective use can improve revenue management, enhance market research, improve customer experience, and help with reputation management (Yallop & Seraphin, 2020). This chapter contributes to an understanding of the opportunities and risks of big data use in digital marketing activity for sharing economy businesses. It provides information on the characteristics and processes of big data and maps its sources. It critically assesses how big data is used in digital marketing and aligns big data techniques to the marketing challenges facing sharing economy businesses. Then the chapter summarizes the core critical debates surrounding big data use and identifies the barriers to generating business value from a range of digital marketing techniques, before concluding with a discussion of the managerial and policy implications.
- Kathryn Waite, Heriot-Watt University (Author)
- Rodrigo Perez-Vega, University of Kent (Author)
For the source title:
- Babak Taheri, Nottingham Business School (Editor) https://orcid.org/0000-0002-0912-9949
- Roya Rahimi, University of Wolverhampton (Editor) https://orcid.org/0000-0001-7520-3273
- Dimitrios Buhalis, Hong Kong Polytechnic University (Editor) https://orcid.org/0000-0001-9148-6090
Waite & Perez-Vega, 2022
Waite, K. & Perez-Vega, R. (2022) "Chapter 11 Big Data and Digital Marketing in the Sharing Economy" In: Taheri, B., Rahimi, R. & Buhalis, D. (ed) . Oxford: Goodfellow Publishers http://dx.doi.org/10.23912/9781915097064-5088
Aheleroff, S., Philip, R., Zhong, R. Y., & Xu, X. (2019) The degree of mass personalisation under industry 4.0, Procedia CIRP, 81, (3), 1394-1399.
Alharthi, A., Krotov, V., & Bowman, M. (2017) Addressing barriers to big data, Business Horizons, 60 (3), 285-292.
Baesens, B., Bapna, R., Marsden, J. R., Vanthienen, J., & Zhao, J. L. (2016) Transformational issues of big data and analytics in networked business, MIS Quarterly, 40 (4), 807-818.
Barham, H., (2017). Achieving competitive advantage through big data: A literature review. In 2017 Portland International Conference on Management of Engineering and Technology (PICMET). IEEE pp. 1-7.
Barron, K., Kung, E., & Proserpio, D. (2018) The effect of home-sharing on house prices and rents: Evidence from Airbnb, https://ssrn.com/abstract=3006832
Bhattacharjee, K., & Petzold, L. (2016) What drives consumer choices? Mining aspects and opinions on large scale review data using distributed representation of words, 16th International Conference on Data Mining Workshops (ICDMW) 12-15 December, Barcelona, Spain, 908-915.
Billger, M., Thuvander, L., & Wästberg, B. S. (2017) In search of visualization challenges: The development and implementation of visualization tools for supporting dialogue in urban planning processes, Environment and Planning B: Urban Analytics and City Science, 44 (6), 1012-1035.
Bird, S., Kenthapadi, K., Kıcıman, E., & Mitchell, M. (2019) Fairness-aware machine learning: Practical challenges and lessons learned, 2019 ACM International Conference on Web Search and Data Mining (WSDM), 11-15 February, Melbourne, Australia. 834-835.
Boyd, D. & Crawford, K. (2012) Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon, Information, Communication & Society, 15 (5), 662-679.
Bradlow, E. T., Gangwar, M., Kopalle, P., & Voleti, S. (2017) The role of big data and predictive analytics in retailing, Journal of Retailing, 93 (1), 79-95.
Braun, J. A., & Eklund, J. L. (2019) Fake news, real money: Ad tech platforms, profit-driven hoaxes, and the business of journalism, Digital Journalism, 7 (1), 1-21.
Buhalis, D., Andreu, L. & Gnoth, J. (2020) The dark side of the sharing economy: Balancing value co‐creation and value co‐destruction, Psychology & Marketing, 37 (5), 689-704.
Bumblauskas, D., Nold, H., Bumblauskas, P., & Igou, A. (2017) Big data analytics: Transforming data to action, Business Process Management Journal, 23 (3), 703-720.
Calic, G., & Ghasemaghaei, M. (2020) Big data for social benefits: Innovation as a mediator of the relationship between big data and corporate social performance, Journal of Business Research, https://doi.org/10.1016/j. jbusres.2020.11.003
Cecez-Kecmanovic, D., Marjanovic, O. & Vidgen, R. (2021) Algorithmic pollution: making the invisible visible, Journal of Information Technology, https://journals.sagepub.com/doi/pdf/10.1177/02683962211010356
Chen, Y. & Wang, L. (2019) Commentary: Marketing and the sharing economy: Digital economy and emerging market challenges, Journal of Marketing, 83 (5), 28-31.
Chen, Y. J., & Wu, C. H. (2017) On big data-based fraud detection method for financial statements of business groups, 6th IIAI International Congress on Advanced Applied Informatics, 9-13 July, Hamamatsu, Japan.
Hong, H., Xu, D., Wang, G. A., & Fan, W. (2017) Understanding the determinants of online review helpfulness: A meta-analytic investigation, Decision Support Systems, 102 (10), 1-11.
Hossain, M. (2020) Sharing economy: A comprehensive literature review, International Journal of Hospitality Management, 87 (5), 1-11.
Huang, L., Tan, C. H., Ke, W., & Wei, K. K. (2018) Helpfulness of online review content: The moderating effects of temporal and social cues, Journal of the Association for Information Systems, 19 (6), 503-522. Inamdar, Z., Raut, R., Narwane, V. S., Gardas, B., Narkhede, B., & Sagnak, M. (2020) A systematic literature review with bibliometric analysis of big data analytics adoption from period 2014 to 2018, Journal of Enterprise Information Management, 34 (1), 101-139.
Jeon, M., M. & Jeong, M. (2017) Customers' perceived website service quality and its effects on e-loyalty, International Journal of Contemporary Hospitality Management, 29 (1), 438-457.
Jhaver, S., Karpfen, Y., & Antin, J. (2018) Algorithmic anxiety and coping strategies of Airbnb hosts, 2018 CHI Conference on Human Factors in Computing Systems, 21-26 April, Montreal, 1-12.
Joseph G. & Varghese V. (2019) Analyzing Airbnb customer experience feedback using text mining, in: M. Sigala, R. Rahimi & M. Thelwall (eds) Big Data and Innovation in Tourism, Travel, and Hospitality, Singapore, Springer, 147-162.
Key, T. M. (2017) Domains of digital marketing channels in the sharing economy, Journal of Marketing Channels, 24 (1-2), 27-38.
Kwok, L., & Xie, K. L. (2019) Pricing strategies on Airbnb: Are multi-unit hosts revenue pros? International Journal of Hospitality Management, 82, 252-259.
Lambrecht, A., & Tucker, C. (2019) Algorithmic bias? An empirical study of apparent gender-based discrimination in the display of STEM career ads, Management Science, 65 (7), 2966-2981.
Lau, R.Y.K., Zhao, J.L., Chen, G. & Guo, X. (2016) Big data commerce, Information & Management, 53 (8), 929-933.
Lee, D. (2016) How Airbnb short-term rentals exacerbate Los Angeles's affordable housing crisis: Analysis and policy recommendations, Harvard Law & Policy Review, 10 (1), 229.
Lepri, B., Oliver, N., Letouzé, E., Pentland, A. & Vinck, P. (2018) Fair, transparent, and accountable algorithmic decision-making processes, Philosophy & Technology, 31 (4), 611-627.
Li, H., Meng, F., Jeong, M., & Zhang, Z. (2020) To follow others or be yourself? Social influence in online restaurant reviews, International Journal of Contemporary Hospitality Management, 32 (3), 1067-1087. Line, N.D., Dogru, T., El-Manstrly, D., Buoye, A., Malthouse, E. &
Kandampully, J. (2020) Control, use and ownership of big data: A reciprocal view of customer big data value in the hospitality and tourism industry, Tourism Management, 80 (5), 1-10.
Lutz, C. & Newlands, G. (2018) Consumer segmentation within the sharing economy: The case of Airbnb, Journal of Business Research, 88 (7), 187-196.
Mahajan, K. & Gokhale, L.A., (2017) Significance of digital data visualization tools in big data analysis for business decisions, International Journal of Computer Applications, 165 (5), 15-18.
Malthouse, E. C., & Li, H. (2017) Opportunities for and pitfalls of using big data in advertising research, Journal of Advertising, 46 (2), 227-235.
Martin, K. (2019) Ethical implications and accountability of algorithms, Journal of Business Ethics, 160 (4), 835-850.
Mody, M. & Gomez, M. (2018) Airbnb and the hotel industry: the past, present, and future of sales, marketing, branding, and revenue management, Boston Hospitality Review, 6 (3), 1-14.
Mody, M., Suess, C., & Lehto, X. (2019) Using segmentation to compete in the age of the sharing economy: Testing a core-periphery framework, International Journal of Hospitality Management, 78 (4), 199-213.
Mogaji, E., Olaleye, S., & Ukpabi, D. (2020) Using AI to personalise emotionally appealing advertisement, in N.P. Rana, E.L. Slade, G.P. Sahu, H. Kizgin, N. Singh, B. Dey, A. Gutierrez, & Y.K. Diwedi (Eds), Digital and Social Media Marketing, Cham: Springer, 137-150.
Narayanan, A., Huey, J., & Felten, E. W. (2016) A precautionary approach to big data privacy in S. Gutwirth, R. Leenes, & P. De Hert (Eds), Data Protection on the Move, Dordrecht: Springer, 357-385.
Narayanan, U., Paul, V., & Joseph, S. (2017) Different analytical techniques for big data analysis: A review, 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, 1st August, India.
Orenga-Roglá, S., & Chalmeta, R. (2016) Social customer relationship management: taking advantage of Web 2.0 and big data technologies, SpringerPlus, 5 (1), 1-17.
Paavola, J., Helo, T., Jalonen, H., Sartonen, M., & Huhtinen, A. M. (2016) Understanding the trolling phenomenon: The automated detection of bots and cyborgs in the social media, Journal of Information Warfare, 15 (4), 100-111.
Palos-Sanchez, P., Saura, J. R., & Martin-Velicia, F. (2019) A study of the effects of programmatic advertising on users' concerns about privacy overtime, Journal of Business Research, 96 (3), 61-72.
Pantano, E., Priporas, C.V., Stylos, N. & Dennis, C., (2019) Facilitating tourists' decision making through open data analyses: A novel recommender system, Tourism Management Perspectives, 31 (3), 323-331.
Perez-Vega, R., Kaartemo, V., Lages, C. R., Razavi, N. B., & Männistö, J. (2021) Reshaping the contexts of online customer engagement behavior via artificial intelligence: A conceptual framework, Journal of Business Research, 129 (May), 902-910.
Priporas, C. V., Stylos, N., & Fotiadis, A. K. (2017) Generation Z consumers' expectations of interactions in smart retailing: A future agenda, Computers in Human Behavior, 77 (12), 374-381.
Qi, J., Zhang, Z., Jeon, S., & Zhou, Y. (2016) Mining customer requirements from online reviews: A product improvement perspective, Information & Management, 53 (8), 951-963.
Qin, D., Lin, P. M., Feng, S. Y., Peng, K. L., & Fan, D. (2020) The future of Airbnb in China: industry perspective from hospitality leaders, Tourism Review, 75 (4), 609-624.
Reinold, S. & Dolnicar, S. (2018) Airbnb's business model, in S. Dolnicar (Ed.), Peer-to-Peer Accommodation Networks: Pushing the boundaries, Oxford: Goodfellow Publishers, 27-38.
Rohlfing, I., & Schneider, C. Q. (2018) A unifying framework for causal analysis in set-theoretic multimethod research, Sociological Methods & Research, 47 (1), 37-63.
Rovatsos, M., Mittelstadt, B. & Koene, A. (2019) Landscape summary: Bias in algorithmic decision-making: What is bias in algorithmic decision-making, how can we identify it, and how can we mitigate it?, https://www.gov. uk/government/publications/landscape-summaries-commissioned-bythe-centre-for-data-ethics-and-innovation
Saboo, A.R., Kumar, V. & Park, I. (2016) Using big data to model time-varying effects for marketing resource (re) allocation, MIS Quarterly, 40 (4), 911-939.
Sadowski, J. (2019), When data is capital: Datafication, accumulation and extraction, Big Data & Society, 6 (1), 1-12.
Salehan, M. & Kim, D.J. (2016) Predicting the performance of online consumer reviews: A sentiment mining approach to big data analytics, Decision Support Systems, 81 (1), 30-40.
Sheng, J., Amankwah-Amoah, J., & Wang, X. (2017) A multidisciplinary perspective of big data in management research, International Journal of Production Economics, 191 (9), 97-112.
Sigala, M. (2020). Technology and tourism: Themes, concepts and issues. In S.J. Page & J. Connell (Eds), Tourism, London: Routledge, 114-133.
Spiekermann, S. & Korunovska, J., (2017), Towards a value theory for personal data, Journal of Information Technology, 32 (1), 62-84.
Sthapit, E., Björk, P. & Jiménez Barreto, J. (2020) Negative memorable experience: North American and British Airbnb guests' perspectives, Tourism Review, https://doi/10.1108/TR-10-2019-0404
Stylos, N., Zwiegelaar, J. & Buhalis, D. (2021), Big data empowered agility for dynamic, volatile, and time-sensitive service industries: The case of tourism sector, International Journal of Contemporary Hospitality Management, 33 (3), 1015-1036.
Sutherland, W., & Jarrahi, M. H. (2018). The sharing economy and digital platforms: A review and research agenda. International Journal of Information Management, 43 (12), 328-341.
Sverdlik, Y. (2020), Study: Data centers responsible for 1 percent of all electricity consumed worldwide, Data Centre Knowledge, https://www.datacenterknowledge.com/energy/study-data-centers-responsible-1-percent-all-electricityconsumed-worldwide Talón-Ballestero, P., González-Serrano, L., Soguero-Ruiz, C., Muñoz-Romero,
S., & Rojo-Álvarez, J. L. (2018) Using big data from customer relationship management information systems to determine the client profile in the hotel sector, Tourism Management, 68 (5), 187-197.
Teubner, T. & Flath, C.M., (2019) Privacy in the sharing economy, Journal of the Association for Information Systems, 20 (3), 2.
Townley, C., Morrison, E. & Yeung, K. (2017) Big data and personalized price discrimination in EU competition law, Yearbook of European Law, 36 (1), 683-748. Villarroel Ordenes, F., Ludwig, S., De Ruyter, K., Grewal, D., & Wetzels, M. (2017) Unveiling what is written in the stars: Analyzing explicit, implicit, and discourse patterns of sentiment in social media, Journal of Consumer Research, 43 (6), 875-894.
Wu, L., & Grbovic, M. (2020) How Airbnb tells you will enjoy sunset sailing in Barcelona? Recommendation in a two-sided travel marketplace. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval 25-30 July, China.
Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017) A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism, Tourism Management, 58 (1), 51-65.
Xu, Z., Frankwick, G.L. & Ramirez, E. (2016) Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective, Journal of Business Research, 69 (5), 1562-1566.
Yallop, A. & Seraphin, H. (2020) Big data and analytics in tourism and hospitality: opportunities and risks, Journal of Tourism Futures, 6 (3), 257-262.
Yeh, C.L. (2018) Pursuing consumer empowerment in the age of big data: A comprehensive regulatory framework for data brokers. Telecommunications Policy, 42 (4), 282-292. Yun, J. T., Segijn, C. M., Pearson, S., Malthouse, E. C., Konstan, J. A., & Shankar,
V. (2020) Challenges and future directions of computational advertising measurement systems, Journal of Advertising, 49 (4) 1-13.
Zhang, T. (2019) Co-creating tourism experiences through a traveler's journey: a perspective article, Tourism Review, 75 (1) ,56-60.