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Selection of logistics service provider (LSP) (also known as Third-party logistics (3PL) is a critical decision, because logistics affects top and bottom line as well. Companies consider logistics as a cost driver and at the time of LSP selection decision, many important decision criteria’s are left out. 3PL selection is multi-criteria decision-making process. The purpose of this paper is to develop an integrated approach, combining quality function deployment (QFD), and Taguchi loss function (TLF) to select optimal 3PL.

Multiple criteria are derived from the company requirements using house of quality. The 3PL service attributes are developed using QFD and the relative importance of the attributes are assessed. TLFs are used to measure performance of each 3PL on each decision variable. Composite weighted loss scores are used to rank 3PLs.

QFD is a better tool which connects attributes used in a decision problem to decision maker’s requirements. In total, 15 criteria were used and TLF provides performance on these criteria.

The proposed model provides a methodology to make informed decision related to 3PL selection. The proposed model may be converted into decision support system.

Proposed approach in this paper is a novel approach that connects the 3PL selection problem to practice in terms of identifying criteria’s and provides a single numerical value in terms of Taghui loss.

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.

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.

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.

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.

This study involves a content analysis of research published from 2000 to 2018 about American Indian students with the principal aim to identify investigations addressing the supportive factors that contribute to student academic success. Secondary aims involved better understanding the parameters of the investigations, such as sample tribal affiliations and journal outlets.

Out of 6,341 total articles published in PsycARTICLES, PsycINFO and Education Resources Information Center over the time period, 86 articles covering the pre-school to college age years were identified, almost evenly distributed between pre-college (n = 42, 48.8%); and college age samples (n = 44, 51.2%). The 86 articles account for a mere 1.4% of all published articles over the 19 year period. A community cultural wealth approach (Yosso, 2005) was used as a framework for understanding the myriad of strengths students bring to their school experiences and was used as a lens for interpreting the study findings.

When disaggregated, the most common supports for pre-college age youth were culturally-sensitive schooling, personal/intrinsic qualities along with family and social support. For college age students, the most common supports were university personnel, community-based supports and student intrinsic factors. Further results, study limitations and implications are discussed.

This research is original.