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Published on HR Daily





Workers who proactively engage in career planning and skill development can reduce the stress and career dissatisfaction that comes with job insecurity, new research shows.


It is becoming increasingly common for workers to experience uncertainty about their current and future jobs, with the number of temporary contracts increasing and more and more jobs being replaced by machines, the Curtin University and University of Amsterdam researchers say.


These perceptions can lead to more stress, poorer health and poorer career prospects, and policymakers have noted insecurity as one of the most rapidly accelerating psychosocial hazards in the workplace.


In their study of 432 current and former workers of a European staffing organisation, the researchers found engaging in proactive career behaviour, including career planning, skill development, career consultation and networking, can mitigate the lack of control that arises from insecure work situations.


They say, however, that different types of insecure work might call for different proactive coping efforts. For example, the above career behaviour didn't mitigate feelings of insecurity for those experiencing chronic insecure work – such as a high probability of a type of job being digitalised – as opposed to acute insecure work – such as a temporary contract expiring.


"Chronic insecure work situations might require longer-term strategies executed over considerable periods of time (e.g., transitioning to a new occupation; obtaining a new educational degree), whereas acute insecure work situations might require more immediate proactive behaviour."


COVID-19 insecurity is "less threatening"


Curtin University professor Sharon Parker tells HR Daily the feelings of job insecurity arising from automation and digitisation are distinct to those caused by pandemic-related job losses and uncertainty.


"The fact that many people are unemployed for reasons that are out of their control, probably makes it feel a bit less threatening," she says.


"There are more people unemployed, and people understand that it's not your fault... maybe right now, it's not as challenging as it can be for people during non-COVID times, where perhaps they were in the minority."

During this period of greater unemployment, Parker still encourages individuals to be proactive in improving their career opportunities. In doing so, unemployed members of the labour force will not only be better prepared to re-enter the workforce, but remaining productive will ease the stress of job insecurity, she says.


"Even though it might not necessarily lead to a job, it's going to help you into the future if you are thinking about these things and building the network, getting the skills that you might need," she says.


It's not going to do employees any harm, she notes. "It's probably going to help, and it's going to help [them] feel better as well."



Sharon Parker

Jessie Koen



The Organisational Behaviour Division of the Academy of Management has announced the winner of the Best Paper for 2019. Congratulations Fangfang and Sharon for publishing the Best Paper of 2019 in the field of Organisational Behaviour!


The Best Paper of 2019 was selected by a Committee (chaired by Jin Nam Choi) who read each of the papers published in 2019, and then identified the top papers through a rating and ranking process. A special thank you to Jin Nam and the Committee members for their service: Frederik Anseel, Frank Belschak, William Bommer, Jeewon Cho, Kevin Cruz, Travis Grosser, Thomas Ng, Christian Vandenberghe, Le (Betty) Zhou.


The second runner up paper was also authored by Sharon with colleagues from UWA, Francesco Cangiano (now at Bond University) and Gillian Yeo.

The achievements of Fangfang and Sharon reflect their dedication and also the contribution of everyone at CTWD in creating a culture that supports meaningful and impactful research.


Best Paper of 2019


Fangfang Zhang & Sharon K. Parker


Summary

Two dominant perspectives of job crafting—the original theory from Wrzesniewski and Dutton (2001) and the job demands resources perspective from Tims, Bakker, and Derks (2014) —remain separate in research. To synthesize these perspectives, we propose a three‐level hierarchical structure of job crafting, and we identify the aggregate/superordinate nature of each major job crafting construct. The first level of the structure is job crafting orientation, or approach versus avoidance crafting, which we argue is an essential yet often neglected distinction in the literature. We address the debate surrounding cognitive crafting and identify crafting form (behavioral versus cognitive crafting) as the next hierarchical level of constructs. Finally, we concur that job resources and job demands, or crafting content, capture different ways that individuals craft their jobs. Using this integrated hierarchical structure, we were able to review antecedents and outcomes from both perspectives. We show, for example, that approach crafting in its behavioral form is very similar to other proactive behaviors in the way it functions, suggesting a need for closer synthesis with the broader proactive literature, whereas avoidance crafting appears to be less proactive and often dysfunctional. On the basis of our review, we develop a road map for future research.




By Meredith Carr


Imagine you were asked to diagnose a patient whose medical condition has, thus far, completely baffled their treating medical practitioners. Producing a definitive diagnosis would not only advance the medical community’s understanding of highly complex and indeed rare medical conditions, it would greatly improve the patient’s medical care and provide meaningful answers for them and their family.


This near impossible task is the reality facing a team of expert medical and health practitioners from a range of specialities when they meet once a month to decode a diagnostic riddle, wrapped in the medical mystery of a selected patient. This much needed and progressive approach to diagnosing complex and long standing medical conditions, is known as the Undiagnosed Diseases Program, and is a part of the International Undiagnosed Diseases Network. Since the first Undiagnosed Diseases Program expert panel meeting was held in Western Australia in March 2016, the diagnostic rate of patients going through the Western Australian program has nearly doubled to 55%, when compared to the previous approach. [1]


So what is it about these monthly meetings that has led to an increased diagnostic rate and provided patients and their families with valuable answers? Like the challenge facing the multidisciplinary expert panel meetings, CAT has enabled my team at the Centre for Transformative Work Design to decode a team interaction riddle, wrapped in a…let’s just say CAT provides a platform to capture the problem-solving processes that occur during these monthly meetings.


CAT enabled us to develop our own coding scheme and identify the specific time points at which important knowledge was shared – and by whom – within each expert panel meeting. In effect, CAT made possible our near impossible task of tracking and measuring complex communication patterns while unobtrusively observing the ‘live’ expert panel meetings.

Using data from CAT, our research is revealing that the answer may lie in the type of knowledge-sharing undertaken by the expert team members [2][3]. In fact, the expert panel meetings operate on a delicate balancing act of team members exploiting and exploring their clinical knowledge with each other.


So what does that mean? Well, knowledge exploitation occurs when a person, in this case an expert panel member, shares information they consider factual with other members. This means that the meeting members are communicating knowledge they already possess, like facts about the patient’s medical history and previous test results, as well as descriptions of medical conditions.


In contrast, knowledge exploration occurs when a person, ‘thinks out loud’ and shares information that they are still considering or offers information they believe might provide insight into the problem [4][5]. In terms of the expert panel meetings, members’ employ knowledge exploration when they share ideas about potential diagnoses and suggest possible diagnostic testing options.


So, it seems that experts considering all possibilities including novel and innovative ideas, in light of a patient’s medical history and their collective knowledge of medical conditions could hold the key to decoding a diagnostic riddle, wrapped in a medical mystery, inside an enigma. And the key to decoding how experts problem solve near impossible diagnostic riddles…well that’s not a mystery, it’s using CAT.

Check out this short video where Meredith talks about her experience of using CAT in her work with the Undiagnosed Diseases Program:



Still not sure if you could use CAT in your work? Stay tuned for the next post in this series, where we will give other examples of how CAT can be used, including videos from our very own ‘CAT lovers!’

For further detail on the functionality and history of CAT, and how to access it, click here.

For the original Curtin University media release on CAT, click here.

[1] Baynam, G., Pachter, N., McKenzie, F., Townshend, S., Slee, J., Kiraly-Borri, C., ... & Verhoef, H. (2016). The rare and undiagnosed diseases diagnostic service–application of massively parallel sequencing in a state-wide clinical service. Orphanet Journal of Rare Diseases, 11(1), 77.

[2] Klonek, F. E., Meinecke, A. L., Hay, G., & Parker, S. K. (2020). Capturing team dynamics in the wild: The communication analysis tool. Small Group Research, 51(3), 303-341.

[3] Kostopoulos, K. C., & Bozionelos, N. (2011). Team exploratory and exploitative learning: Psychological safety, task conflict, and team performance. Group & Organization Management, 36, 385–415.

[4] Uitdewilligen, S., & Waller, M. J. (2018). Information sharing and decision-making in multidisciplinary crisis management teams. Journal of Organizational Behavior, 39, 731–748.

[5] March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71–87.

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