Jari Juga, Jouni Juntunen and Timo Koivumäki
This study aims to explicate the behavioral factors that determine willingness to share personal health data for secondary uses.
Abstract
Purpose
This study aims to explicate the behavioral factors that determine willingness to share personal health data for secondary uses.
Design/methodology/approach
A theoretical model is developed and tested with structural equation modeling using survey data from Finland.
Findings
It is shown that attitude toward information sharing is the strongest factor contributing to the willingness to share personal health information (PHI). Trust and control serve as mediating factors between the attitude and willingness to share PHI.
Research limitations/implications
The measures of the model need further refinement to cover the various aspects of the behavioral concepts.
Practical implications
The model provides useful insights into the factors that affect the willingness for information sharing in health care and in other areas where personal information is distributed.
Social implications
Sharing of PHI for secondary purposes can offer social benefits through improvements in health-care performance.
Originality/value
A broad-scale empirical data gives a unique view of attitudes toward sharing of PHI in one national setting.
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Minna Pikkarainen, Laura Kemppainen, Yueqiang Xu, Miia Jansson, Petri Ahokangas, Timo Koivumäki, He Hong Gu and Julius Francis Gomes
Covid has increased the usage of multisided digital platforms. For companies, this has become a business opportunity. Data usage on platforms requires that platform companies…
Abstract
Purpose
Covid has increased the usage of multisided digital platforms. For companies, this has become a business opportunity. Data usage on platforms requires that platform companies co-create services for common customers. In this case, the target is not to make the same value proposition but rather to use the resources such as data, knowledge, technology, or institutions in a complementary manner. Platforms are characterized as a combination of hardware and software including standards, interfaces, and rules making it possible for different ecosystem players to complement and interact in the ecosystem. Current ecosystems include several platforms that do not work without resource integration. The purpose of this study is to increase understanding what do we mean by resource complementarity in service ecosystems.
Design/methodology/approach
This study was done via an in-depth qualitative case study in which a health service ecosystem co-creating technological surgery innovation was used as a unit of analysis.
Findings
The authors’ findings suggest that key resource capabilities, to enable complementarity in service ecosystems, are motivation, knowledge, skills, data and complementary designed technology components.
Research limitations/implications
The authors’ study increases theoretical understanding of what does one mean by construct of resource complementarity.
Practical implications
From a managerial perspective, it is shown that organizations need to develop adaptive capabilities to utilize internal and external competencies and resources and enable co-creative processes within the service ecosystem.
Originality/value
Very few empirical studies in the marketing literature have focused on multi-sided digital platforms and their resource complementarity in the data-driven healthcare ecosystem settings.
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Nicola Cobelli and Emanuele Blasioli
The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management…
Abstract
Purpose
The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.
Design/methodology/approach
This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.
Findings
Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.
Originality/value
To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.
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Matti Haverila, Caitlin McLaughlin, Kai Christian Haverila and Julio Viskovics
The purpose of this research is to compare two different sample populations (student and general) to determine the impact of brand community motives on brand community engagement.
Abstract
Purpose
The purpose of this research is to compare two different sample populations (student and general) to determine the impact of brand community motives on brand community engagement.
Design/methodology/approach
Two samples were drawn for the purpose of the current research. The first sample was drawn among the members of various brand communities from a general North American population sample (N = 503). The second sample was drawn purely from students, belonging to a variety of brand communities, from a middle-sized Canadian university (N = 195). Partial least squares structural equation modelling was used to analyse the strength, significance and effect sizes of the relationships between brand community motive and engagement constructs.
Findings
The findings indicate that the impact of brand community motives varied by sample population. The information and entertainment motives were significantly related to brand community engagement in both sample populations with roughly equal effect sizes. The social integration motive was again significantly related to the brand community engagement construct in the student sample population – but not for the general North American general population sample. Further, the self-discovery motive and status enhancement motives were significantly related to brand community engagement in the North American sample, but not for the student sample. This indicates significant differences between the two sample populations.
Originality/value
The results of the current research demonstrate that student populations are significantly different from the general population regarding their motives towards brand communities. This indicates that brand community managers need to be aware of the motives of different brand community members and also that they need to exercise caution about utilizing purely student data to make decisions about brand community management.