Understanding Organizational Behavior with Wearable Sensing Technology (original) (raw)

Sociometric badges: wearable technology for measuring human behavior

2007

We present the design, implementation and deployment of a wearable computing research platform for measuring and analyzing human behavior in a variety of settings and applications. We propose the use of wearable sociometric badges capable of automatically measuring the amount of face-to-face interaction, conversational time, physical proximity to other people, and physical activity levels using social signals derived from vocal features, body motion, and relative location to capture individual and collective patterns of behavior. Our goal is to be able to understand how patterns of behavior shape individuals and organizations. We attempt to use on-body sensors in large groups of people for extended periods of time in naturalistic settings for the purpose of identifying, measuring, and quantifying social interactions, information flow, and organizational dynamics. We deployed this research platform in a group of 22 employees working in a real organization over a period of one month. Using these automatic measurements we were able to predict employees' selfassessment of productivity, job satisfaction, and their own perception of group interaction quality. An initial exploratory data analysis indicates that it is possible to automatically capture patterns of behavior using this wearable platform.

The Promise and Perils of Wearable Sensors in Organizational Research

Organizational Research Methods, 2015

Rapid advances in mobile computing technology have the potential to revolutionize organizational research by facilitating new methods of data collection. The emergence of wearable electronic sensors in particular harbors the promise of making the large-scale collection of high-resolution data related to human interactions and social behavior economically viable. Popular press and practitioner-oriented research outlets have begun to tout the game-changing potential of wearable sensors for both researchers and practitioners. We systematically examine the utility of current wearable sensor technology for capturing behavioral constructs at the individual and team levels. In the process, we provide a model for performing validation work in this new domain of measurement. Our findings highlight the need for organizational researchers to take an active role in the development of wearable sensor systems to ensure that the measures derived from these devices and sensors allow us to leverage ...

Sensible Organizations: Technology and Methodology for Automatically Measuring Organizational Behavior

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2000

We present the design, implementation, and deployment of a wearable computing platform for measuring and analyzing human behavior in organizational settings. We propose the use of wearable electronic badges capable of automatically measuring the amount of face-to-face interaction, conversational time, physical proximity to other people, and physical activity levels in order to capture individual and collective patterns of behavior. Our goal is to be able to understand how patterns of behavior shape individuals and organizations. By using on-body sensors in large groups of people for extended periods of time in naturalistic settings, we have been able to identify, measure, and quantify social interactions, group behavior, and organizational dynamics. We deployed this wearable computing platform in a group of 22 employees working in a real organization over a period of one month. Using these automatic measurements, we were able to predict employees' self-assessments of job satisfaction and their own perceptions of group interaction quality by combining data collected with our platform and e-mail communication data. In particular, the total amount of communication was predictive of both of these assessments, and betweenness in the social network exhibited a high negative correlation with group interaction satisfaction. We also found that physical proximity and e-mail exchange had a negative correlation of r = −0.55 (p < 0.01), which has far-reaching implications for past and future research on social networks.

Sociometric wearable devices for studying human behavior in corporate and healthcare workplaces

BioTechniques, 2021

Wearable sensor technology enables objective data collection of direct human interactions. The authors review sociometric wearable devices (SWD) and their application in healthcare. Human interactions captured by wearable sensors have been shown to correlate with social constructs such as teamwork and productivity in the office. Application of SWD in the field of healthcare requires special considerations: validation studies have shown technological disadvantages in acute medical settings. Application of SWD in healthcare should be considered based on the strengths and weaknesses of the methodology. SWD can also play an important role in investigation of human interaction and epidemic spread. When study designs and methodologies are carefully considered, incorporation of SWD in healthcare research has promising potential for new insights.

Sensible organizations: Changing our businesses and work styles through sensor data

2008

We introduce the concept of sensor-based applications for the daily business settings of organizations and their individual workers. Wearable sensor devices were developed and deployed in a real organization, a bank, for a month in order to study the effectiveness and potential of using sensors at the organizational level. It was found that patterns of physical interaction changed dynamically while e-mail is more stable from day to day.

Wearable communicator badge: Designing a new platform for revealing organizational dynamics

2006

We are developing a new wearable electronic badge that will enable people working in large organizations to communicate, find information, and interact in more efficient and intelligent ways. The badge will perform speech analysis and speech recognition using a microphone and state-ofthe-art micro-power electronics. It will be capable of playing audio messages and reminders through a speaker. An accelerometer will allow us to study how people move and behave throughout the day: Are they walking to a meeting? Are they talking to someone? Are they sitting in front of their computers? An infrared sensor will be used to capture face-to-face interactions and study social networks. A 2.4 GHz radio transceiver will send and receive information from base stations distributed along a specific area and a Bluetooth module will enable it to interface with cell phones, PDAs, portable computers, and other Bluetoothenabled sensors and devices.

Detecting Emerging Activity-Based Working Traits through Wearable Technology

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2017

A recent trend in corporate real-estate is Activity-Based Working (ABW). The ABW concept removes designated desks but offers different work settings designed to support typical work activities. In this context there is still a need for objective data to understand the implications of these design decisions. We aim to contribute by using automated data collection to study how ABW’s principles impact office usage and dynamics. To this aim we analyse team dynamics and employees’ tie strength in relation to space usage and organisational hierarchy using data collected with wearable devices in a company adopting ABW principles. Our findings show that the office fosters interactions across team boundaries and among the lower levels of the hierarchy suggesting a strong lateral communication. Employees also tend to have low space exploration on a daily basis which is instead more prevalent during an average week and strong social clusters seem to be resisting the ABW principles of space dyn...

Sensor-based organizational engineering

Proceedings of the Icmi Mlmi 09 Workshop, 2009

We propose the use of wearable and environmental sensors to capture and model social interactions in the workplace, combined with data mining techniques and social network analysis for organizational engineering applications. By combining behavioral sensor data with other sources of information such as text-mined documents, surveys, and performance data, it is possible to optimize organizations.

Wearable Technologies in Human Resource Management - A Comprehensive Analysis of Adoption and its Impact

ANU Journal of Commerce and Management, 2023

Wearable technology is any kind of electronic gadget designed to be worn on the user's body. A well-liked and practical way to gather biometric data while at rest and during exercise is with wearable physical activity trackers. A wide range of devices fall under the umbrella of wearable technology that includes wearable’s like smart watches, Bluetooth headsets, VR headsets, smart jewellery, web-enabled spectacles, and activity trackers like the Fitbit Charge. The data collected from wearables also aids in identifying trends and potential health risks within the organization. There are multiple ways and means through which these technologies have been used for the human resources management in the organization. By aggregating data from these wearables, HR professionals can spot emerging well-being issues and implement proactive solutions to address them. Wearables enable HR professionals to engage with employees in innovative ways, offering new tools to assess and enhance their performance and well-being. This paper describes the most used wearable technology and sensors, wearable computing, various applications and its adoption in Human resource management, impact of wearable technology on HR Practices and key challenges and concerns.

Capturing individual and group behavior with wearable sensors

2009

Abstract We show how to obtain high level descriptions of human behavior in terms of physical activity, speech activity, face-to-face interaction (f2f), physical proximity, and social network attributes from sensor data. We present experimental results that show that it is possible to identify individual personality traits as well as subjective and objective group performance metrics from low level data collected using wearable sensors.