Using Sensors in Organizational Research—Clarifying Rationales and Validation Challenges for Mixed Methods

Frontiers in Psychology

article

Jörg Müller¹  Sergi Fàbregues¹  Elisabeth Anna Guenther²  María José Romano¹ 

[1] IN3 – Universitat Oberta de Catalunya;Universität Klagenfurt, Universitätszentrum für Frauen- und Geschlechterstudien

关键词: mixed methods research;    wearable sensors;    Bluetooth;    indicator;    qualitative research;    quantitative research;    big data;   

DOI  :  10.3389/fpsyg.2019.01188

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Sensor-based data are becoming increasingly widespread in social, behavioral, and organizational sciences. Far from providing a neutral window on “reality,” sensor-based big-data are highly complex, constructed data sources. Nevertheless, a more systematic approach to the validation of sensors as a method of data collection is lacking, as their use and conceptualization have been spread out across different strands of social-, behavioral-, and computer science literature. Further debunking the myth of raw data, the present article argues that, in order to validate sensor-based data, researchers need to take into account the mutual interdependence between types of sensors available on the market, the conceptual (construct) choices made in the research process, and the contextual cues. Sensor-based data in research are usually combined with additional quantitative and qualitative data sources. However, the incompatibility between the highly granular nature of sensor data and the static, a-temporal character of traditional quantitative and qualitative data has not been sufficiently emphasized as a key limiting factor of sensor-based research. It is likely that the failure to consider the basic quality criteria of social science measurement indicators more explicitly may lead to the production of insignificant results, despite the availability of high volume and high-resolution data. The paper concludes with recommendations for designing and conducting mixed methods studies using sensors.

【 授权许可】

CC BY