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Article
Publication date: 27 September 2024

Antti Mikael Rousi, Reid Isaac Boehm and Yan Wang

As national legislation, federated national services, institutional policies and institutional research service arrangements may differ, data stewardship programs may be organized…

302

Abstract

Purpose

As national legislation, federated national services, institutional policies and institutional research service arrangements may differ, data stewardship programs may be organized differently in higher education institutions across the world. This work seeks to elaborate the picture of different data stewardship programs running in different institutional and national research environments.

Design/methodology/approach

Utilizing a case study design, this study described three distinct data stewardship programs from Purdue University (United States), Delft Technical University (Netherlands) and Aalto University (Finland). In addition, this work investigated the institutional and national research environments of the programs. The focus was on initiatives led by academic libraries or similar services.

Findings

This work demonstrates that data stewardship programs may be organized differently within varying national and institutional contexts. The data stewardship programs varied in terms of roles, organization and funding structures. Furthermore, policies and legislation, organizational structures and national infrastructures differed.

Research limitations/implications

The data stewardship programs and their contexts develop, and the descriptions presented in this work should be considered as snapshots.

Originality/value

This work broadens the current literature on data stewardship by not only providing detailed descriptions of three distinct data stewardship programs but also highlighting how research environments may affect their organization. We present a summary of key factors in the organization of data stewardship programs.

Details

Journal of Documentation, vol. 80 no. 7
Type: Research Article
ISSN: 0022-0418

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Article
Publication date: 8 January 2025

Neeraj Dhiman, Honey Kanojia, Mohit Jamwal and Sachin Kumar

This study presents a systematic review of “employee happiness” research from 1991–2023. In this way, this study aims to critically appraise the existing literature, and…

70

Abstract

Purpose

This study presents a systematic review of “employee happiness” research from 1991–2023. In this way, this study aims to critically appraise the existing literature, and synthesize themes, thereby, paving a clearer understanding of the construct, along with providing the future research agenda.

Design/methodology/approach

By adopting a systematic approach, this study followed scientific procedures and rationales for systematic literature reviews for article selection. A total of 57 articles were finally chosen after a careful examination from 110 selected journals.

Findings

The current study identified three major themes after evaluating the selected literature on Employee happiness: (1) work, family and personal blend, (2) organizational support, and (3) Ebullience sentiment. Amidst an ambiguous usage of several related constructs in employee happiness research, the review provided a clear definition of “employee happiness” along with proposing crucial research directions.

Originality/value

There is a lack of systematic reviews on employee happiness in the existing literature. Thus, by far, this effort is one of the earliest endeavors that researchers undertook toward understanding employee happiness.

Details

Journal of Management History, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1751-1348

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Article
Publication date: 6 September 2023

Chen Zhu, Timothy Beatty, Qiran Zhao, Wei Si and Qihui Chen

Food choices profoundly affect one's dietary, nutritional and health outcomes. Using alcoholic beverages as a case study, the authors assess the potential of genetic data in…

279

Abstract

Purpose

Food choices profoundly affect one's dietary, nutritional and health outcomes. Using alcoholic beverages as a case study, the authors assess the potential of genetic data in predicting consumers' food choices combined with conventional socio-demographic data.

Design/methodology/approach

A discrete choice experiment was conducted to elicit the underlying preferences of 484 participants from seven provinces in China. By linking three types of data (—data from the choice experiment, socio-demographic information and individual genotyping data) of the participants, the authors employed four machine learning-based classification (MLC) models to assess the performance of genetic information in predicting individuals' food choices.

Findings

The authors found that the XGBoost algorithm incorporating both genetic and socio-demographic data achieves the highest prediction accuracy (77.36%), significantly outperforming those using only socio-demographic data (permutation test p-value = 0.033). Polygenic scores of several behavioral traits (e.g. depression and height) and genetic variants associated with bitter taste perceptions (e.g. TAS2R5 rs2227264 and TAS2R38 rs713598) offer contributions comparable to that of standard socio-demographic factors (e.g. gender, age and income).

Originality/value

This study is among the first in the economic literature to empirically demonstrate genetic factors' important role in predicting consumer behavior. The findings contribute fresh insights to the realm of random utility theory and warrant further consumer behavior studies integrating genetic data to facilitate developments in precision nutrition and precision marketing.

Details

China Agricultural Economic Review, vol. 15 no. 4
Type: Research Article
ISSN: 1756-137X

Keywords

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