Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

My lawfully wedded workplace: identifying relational similarities of marriage and employment

My lawfully wedded workplace: identifying relational similarities of marriage and employment Purpose – The purpose of this paper is to introduce a novel direction of enquiry into predictions of employee turnover through the application of a qualitative method adapted from marital research. This method focuses on diagnosing the relationship, and has been able to predict divorce with an accuracy of over 90 per cent, as opposed to existing turnover prediction methods’ modest success of about 30 per cent. By demonstrating that the method can be applied to turnover research, this study completes a seminal step in developing this promising direction of enquiry. Design/methodology/approach – The Oral History Interview method for predicting divorce is adapted to employment settings, and tested on Australian legal and healthcare employees. A qualitative analysis of their responses maps the results from this inquiry onto separation-predicting processes identified in marital research. The results are compared to turnover data collected two years later. Findings – Similar relational processes exist in marital and employment relationships when the marital relationship diagnostics method is applied to organisational settings, demonstrating the utility of this tool in the employment context. Preliminary turnover data indicate that some relational processes are significantly associated with employee turnover. Research limitations/implications – Future research should examine the predictive power of this tool on a larger sample, and apply it to a wider range of professions, tenure, and positions. Practical implications – The results indicate that it is viable to diagnose an employment relationship using this diagnostics method developed in marital research. Social implications – The novel perspective offered in this paper has potential to greatly improve this employment relationship across jobs and organisations, thus improving organisational productivity and individual wellbeing. Originality/value – Researchers of employee turnover and practitioners seeking to understand and manage it can benefit from this novel and practical perspective on employment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Personnel Review Emerald Publishing

My lawfully wedded workplace: identifying relational similarities of marriage and employment

Personnel Review , Volume 44 (1): 21 – Feb 2, 2015

Loading next page...
 
/lp/emerald-publishing/my-lawfully-wedded-workplace-identifying-relational-similarities-of-3bojh3dWfW
Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0048-3486
DOI
10.1108/PR-12-2013-0232
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to introduce a novel direction of enquiry into predictions of employee turnover through the application of a qualitative method adapted from marital research. This method focuses on diagnosing the relationship, and has been able to predict divorce with an accuracy of over 90 per cent, as opposed to existing turnover prediction methods’ modest success of about 30 per cent. By demonstrating that the method can be applied to turnover research, this study completes a seminal step in developing this promising direction of enquiry. Design/methodology/approach – The Oral History Interview method for predicting divorce is adapted to employment settings, and tested on Australian legal and healthcare employees. A qualitative analysis of their responses maps the results from this inquiry onto separation-predicting processes identified in marital research. The results are compared to turnover data collected two years later. Findings – Similar relational processes exist in marital and employment relationships when the marital relationship diagnostics method is applied to organisational settings, demonstrating the utility of this tool in the employment context. Preliminary turnover data indicate that some relational processes are significantly associated with employee turnover. Research limitations/implications – Future research should examine the predictive power of this tool on a larger sample, and apply it to a wider range of professions, tenure, and positions. Practical implications – The results indicate that it is viable to diagnose an employment relationship using this diagnostics method developed in marital research. Social implications – The novel perspective offered in this paper has potential to greatly improve this employment relationship across jobs and organisations, thus improving organisational productivity and individual wellbeing. Originality/value – Researchers of employee turnover and practitioners seeking to understand and manage it can benefit from this novel and practical perspective on employment.

Journal

Personnel ReviewEmerald Publishing

Published: Feb 2, 2015

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$499/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month