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Big Data and Service Operations
Author(s) -
Cohen Maxime C.
Publication year - 2018
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/poms.12832
Subject(s) - big data , leverage (statistics) , hacker , business , data breach , identity theft , service (business) , data quality , marketing , computer security , computer science , machine learning , operating system
This study discusses how the tremendous volume of available data collected by firms has been transforming the service industry. The focus is primarily on services in the following sectors: finance/banking, transportation and hospitality, and online platforms (e.g., subscription services, online advertising, and online dating). We report anecdotal evidence borrowed from various collaborations and discussions with executives and data analysts who work in management consulting or finance, or for technology/startup companies. Our main goals are (i) to present an overview of how big data is shaping the service industry, (ii) to describe several mechanisms used in the service industry that leverage the potential information hidden in big data, and (iii) to point out some of the pitfalls and risks incurred. On one hand, collecting and storing large amounts of data on customers and on past transactions can help firms improve the quality of their services. For example, firms can now customize their services to unprecedented levels of granularity, which enables the firms to offer targeted personalized offers (sometimes, even in real‐time). On the other hand, collecting this data may allow some firms to utilize the data against their customers by charging them higher prices. Furthermore, data‐driven algorithms may often be biased toward illicit discrimination. The availability of data on sensitive personal information may also attract hackers and gives rise to important cybersecurity concerns (e.g., information leakage, fraud, and identity theft).