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This research proposes how Design for Six Sigma (DFSS) provides a complementary approach for business process management (BPM) lifecycle implementation in order to address gaps identified in the current literature.

The mandatory elements of a method (MEM) framework is used to illustrate DFSS's maturity as a process redesign method. The use of DFSS in a BPM context is described through several action research case examples.

This research specifies the procedure model (order of development activities), techniques, results, roles and information/meta model (conceptual data model of results) associated with using DFSS to address BPM-related challenges. The action research case examples provided discuss the details of implementing BPM using DFSS to design, implement and test redesigned processes to ensure they fulfill the needs of process participants.

While the case examples discussed were performed in only a few settings, which limits the generalizability of their results, they provide evidence regarding the wide range of domains in which the proposed DFSS-BPM approach can be applied and how the tools are used in different contexts.

This research offers a road map for addressing the challenges practitioners often face with BPM lifecycle implementation.

This research provides the first attempt to integrate DFSS as a complementary method for BPM lifecycle implementation.

The rapid advancement of technology has transformed the health-care industry and enabled the emergence of m-Health solutions such as health apps. The viability and success of these apps depends on the definition of a monetization model appropriate to their specificities. In this sense, the purpose of this paper is to study the mechanisms of monetization of health apps, to stablish how alternative revenues determine if a health app is to be free or paid.

Probability models are used to identify the factors that explain if a health app is free or paid.

Results show that the presence of alternative monetization mechanisms negatively impacts the likelihood of a health app being paid for. The use of personal data to customize advertising (the monetization of “privacy capital”) or the inclusion of ads on the app are alternative means of monetization with potential to decrease the likelihood of a health app being paid for. The possibility of in-app purchases has a lower negative impact on the probability of a health app being paid for. The choice of platform to commercialize an app is also a strategic decision that influences the likelihood of an app being paid for.

This work stands out for bringing together the two largest platforms present in Portugal and for focusing on the perspective of revenue and monetization of health apps and not on the perspective of downloads.