Tuuli Turja

Dr. Tuuli Turja


Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 December 2017 in International Journal of Social Robotics
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Journal Article
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NSNina Savela
Nina Savela
TTTuuli Turja
Tuuli Turja
Atte OksanenAtte Oksanen
Atte Oksanen

1 April 2019 in Computers in Human Behavior
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Journal Article
Closed access
RLRita Latikka
Rita Latikka
TTTuuli Turja
Tuuli Turja
Atte OksanenAtte Oksanen
Atte Oksanen

7 February 2019 in International Journal of Social Robotics
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Journal Article
Open access
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TTTuuli Turja
Tuuli Turja
Atte OksanenAtte Oksanen
Atte Oksanen
Robots are increasingly being used to assist with various tasks ranging from industrial manufacturing to welfare services. This study analysed how robot acceptance at work (RAW) varies between individual and national attributes in EU 27. Eurobarometer surveys collected in 2012 (n = 26,751) and 2014 (n = 27,801) were used as data. Background factors also included country-specific data drawn from the World Bank DataBank. The study is guided by the technology acceptance model and change readiness perspective explaining robot acceptance in terms of individual and cultural attributes. Multilevel studies analysing cultural differences in technological change are exceptionally rare. The multilevel analysis of RAW performed herein accounted for individual and national factors using fixed and random intercepts in a nested data structure. Individual-level factors explained RAW better than national-level factors. Particularly, personal experiences with robots at work or elsewhere were associated with higher acceptance. At a national level, the technology orientation of the country explained RAW better than the relative risk of jobs being automated. Despite the countries’ differences, personal characteristics and experiences with robots are decisive for RAW. Experiences, however, are better enabled in countries open to innovations. The findings are discussed in terms of possible mechanisms through which the technological orientation and social acceptance of robots may be related.


23 March 2018 in Nursing Open
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Journal Article
Open access
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TTTuuli Turja
Tuuli Turja
LALina Van Aerschot
Lina Van Aerschot
TSTuomo Särkikoski
Tuomo Särkikoski
Atte OksanenAtte Oksanen
Atte Oksanen
Aim: To answer the question: ‘How prepared healthcare professionals are to take robots as their assistants in terms of experience and acceptance?’Background: The ageing population, increasing care needs and shortage of healthcare professionals pose major challenges in Western societies. Special service robots designed for care tasks have been introduced as one solution to these problems.Design: A correlative designMethods: Eurobarometer data (N = 969) and survey data of nurses and other healthcare professionals (N = 3800) were used to assess the relationship between robot acceptance and experiences with robots while controlling for the respondents’ age, gender, occupational status and managerial experience.Results: Healthcare professionals had less experience with robots and more negative attitudes towards them than the general population. However, in healthcare, robot assistance was welcomed for certain tasks. These regarded, for example, heavy lifting and logistics. Previous experiences with robots were consistently correlated with robot acceptance.

27 March 2019 in International Journal of Social Robotics
Verified
Journal Article
Open access
PDF file
TTTuuli Turja
Tuuli Turja
STSakari Taipale
Sakari Taipale
MKMarkus Kaakinen
Markus Kaakinen
Atte OksanenAtte Oksanen
Atte Oksanen
Successful implementation of robots in welfare services requires that the staff approves of them as a part of daily work tasks. In this study, we identified psychological and socio-demographic determinants associated with readiness for robotization among professional Finnish care-workers. National survey data were collected from professional care workers (n = 3800) between October and November 2016. Random samples were drawn from the member registers of two Finnish trade unions. The data were analyzed with regression models for respondents with and without firsthand experience with robots. The models explained 34–39% of the variance in the readiness for robotization. The readiness was positively associated with self-efficacy, perceived social norms, interest in technology, and perceived impacts on employment. It was also found that the readiness was less determined by age, gender, profession and job satisfaction among the respondents with firsthand robot experience. Among care workers with no experience with robots, older age and lower job satisfaction predicted a readiness for robotization. Care workers stand out as a distinctive group of potential service robot users, with their high confidence in using new technology and low job satisfaction predicting a higher readiness for robotization. Social norms among care workers emerged as an important factor in the readiness for robotization.