No abstract

Though organizations are increasingly aware that the huge amounts of digital data that are being generated, both inside and outside the organization, offer many opportunities for service innovation, realizing the promise of big data is often not straightforward. Organizations are faced with many challenges, such as regulatory requirements, data collection issues, data analysis issues, and even ideation. In practice, many approaches can be used to develop new datadriven services. In this paper we present a first step in defining a process for assembling data-driven service development methods and techniques that are tuned to the context in which the service is developed. Our approach is based on the situational method engineering approach, tuning it to the context of datadriven service development.

As information systems (IS) age, managers must determine whether to continue upgrading these systems or replace them with systems that have greater potential to offer organizational value. Given the widespread use of information systems and the challenges that IS replacement can present, understanding the forces that encourage managers to continue to upgrade existing systems is of considerable organizational importance. Hence, drawing on prior work we identify factors related to the value a system brings to an organization, the degree of organizational commitment to the system, and the evolvability of the system that influence managerial upgrade decisions. Data collected via a crosssectional survey of IS managers was analyzed using Partial Least Squares. Analysis of this data indicates that IS managers have a preference for upgrading systems that provide greater organizational value, suffer from fewer shortcomings, are more complex, less customized, and for which support is readily available.

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