dc.contributor.author | Bakewell, L | |
dc.contributor.author | Vasilieiou, K | |
dc.contributor.author | Long, K | |
dc.contributor.author | Atkinson, M | |
dc.contributor.author | Rice, H | |
dc.contributor.author | Barreto, M | |
dc.contributor.author | Barnett, J | |
dc.contributor.author | Wilson, M | |
dc.contributor.author | Lawson, S | |
dc.contributor.author | Vines, J | |
dc.date.accessioned | 2018-02-12T15:53:57Z | |
dc.date.issued | 2018-04-21 | |
dc.description.abstract | This paper examines how data-driven performance
monitoring technologies affect the work of
telecommunications field engineers. As a mobile workforce,
this occupational group rely on an array of smartphone
applications to plan, manage and report on their jobs, and to
liaise remotely with managers and colleagues. These
technologies intend to help field engineers be more
productive and have greater control over their work; however
they also gather data related to the quantity and effectiveness
of their labor. We conducted a qualitative study examining
engineers’ experiences of these systems. Our findings
suggest they simultaneously enhance worker autonomy,
support co-ordination with and monitoring of colleagues, but
promote anxieties around productivity and the interpretation
of data by management. We discuss the implications of datadriven
performance management technologies on worker
agency, and examine the consequences of such systems in an
era of quantified workplaces. | en_GB |
dc.description.sponsorship | This work
was supported by RCUK grant ES/M003558/1, funded
through the Empathy and Trust in Online Communicating
(EMoTICON) funding call administered by the Economic
and Social Research Council in conjunction with the RCUK
Connected Communities, Digital Economy and Partnership
for Conflict, Crime and Security themes, and supported by
the Defence Science and Technology Laboratory (Dstl) and
Centre for the Protection of National Infrastructure (CPNI). | en_GB |
dc.identifier.citation | ACM Conference on Human Factors in Computer Systems (CHI 2018), April 21–26, 2018, Montreal, QC, Canada | en_GB |
dc.identifier.doi | 10.1145/3173574.3173945 | |
dc.identifier.uri | http://hdl.handle.net/10871/31427 | |
dc.language.iso | en | en_GB |
dc.publisher | Association for Computing Machinery (ACM) | en_GB |
dc.rights.embargoreason | Under embargo until 27 April 2018 until the conclusion of the conference | en_GB |
dc.rights | © 2018 Copyright is held by the owner/author(s). Permission to make digital or hard copies of part or all of this work for
personal or classroom use is granted without fee provided that copies are
not made or distributed for profit or commercial advantage and that copies
bear this notice and the full citation on the first page. Copyrights for thirdparty
components of this work must be honored. For all other uses, contact
the Owner/Author. | en_GB |
dc.subject | performance management | en_GB |
dc.subject | occupational health | en_GB |
dc.subject | quantified workplace | en_GB |
dc.subject | qualitative study | en_GB |
dc.subject | Remote monitoring | en_GB |
dc.title | Everything We Do, Everything We Press: Data-Driven
Remote Performance Management in a Mobile Workplace | en_GB |
dc.type | Conference paper | en_GB |
dc.description | This is the author accepted manuscript. The final version is available from ACM via the DOI in this record | en_GB |