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The purpose of this paper is to describe how 3D printing and scanning technology was implemented by the Dalhousie University Libraries in Halifax, Nova Scotia. Insights will be outlined about the benefits of these technologies in terms of data visualization and archival practices, as well as the potential user base for library‐centered 3D printing and scanning services.

This paper describes why the Dalhousie University Libraries purchased a 3D printer and scanner, the challenges of maintaining these technologies and instructing students in their use, and how Dalhousie faculty members and students have made use of these technologies for their own research purposes.

3D printing and scanning technologies can be of use to a much wider range of Faculties than have traditionally had access to them. The unique role libraries have on university campuses allows them to function as universal access points for these technologies. By offering 3D scanning technology, they can also use this technology internally for archival purposes.

While much has been written on 3D printing and scanning technology, very little has been written about how these technologies could relate to academic libraries. This paper sets the groundwork for further exploration into how 3D technologies can improve and expand library services.

Health service quality is an important determinant for health service satisfaction and behavioral intentions. The purpose of this paper is to investigate requirements of e‐health services and to develop a measurement model to analyze the construct of “perceived e‐health service quality.”

The paper adapts the C‐OAR‐SE procedure for scale development by Rossiter. The focal aspect is the “physician‐patient relationship” which forms the core dyad in the healthcare service provision. Several in‐depth interviews were conducted in Switzerland; first with six patients (as raters), followed by two experts of the healthcare system (as judges). Based on the results and an extensive literature research, the classification of object and attributes is developed for this model.

The construct e‐health service quality can be described as an abstract formative object and is operationalized with 13 items: accessibility, competence, information, usability/user friendliness, security, system integration, trust, individualization, empathy, ethical conduct, degree of performance, reliability, and ability to respond.

Limitations include the number of interviews with patients and experts as well as critical issues associated with C‐OAR‐SE. More empirical research is needed to confirm the quality indicators of e‐health services.

Health care providers can utilize the results for the evaluation of their service quality. Practitioners can use the hierarchical structure to measure service quality at different levels. The model provides a diagnostic tool to identify poor and/or excellent performance with regard to the e‐service delivery.

The paper contributes to knowledge with regard to the measurement of e‐health quality and improves the understanding of how customers evaluate the quality of e‐health services.