The Impact of Social Comparison on Turnover Among Information Technology Professionals

Figures & data

Figure 1. A Model of Immediate Social Context and IT Professionals’ Turnover

Figure 2. Illustration of Organizational Network and Spread of Turnover in Sample Work Unit Consisting of Three Teams

Figure 3. Dynamic Network Analysis on a Weekly Basis

Table 1. Measures

Construct	Definition	Operationalization
Dependent variable
Turnover	Voluntarily leaving an IT job for an alternative job with a different employer [37].	Actual turnover behavior: Calculated as a binary variable that indicates whether a certain IT professional experienced turnover in the respective week.
Independent variable
Social influence^3	The influence of the immediate social context on turnover decisions among IT professionals. More specifically, the influence exerted by a departing coworker on an IT professional based on the immediate ego-network [8]. Considers direct contacts (first neighbors) with a work relationship within the last year.	Strength of turnover influence: Calculated as the number of hours worked during the last year with coworker(s) that experience turnover divided by the total number of hours worked with all coworkers during the last year [95].
Moderators
Contextual similarity in technical skills	IT professionals possessing the comparable skills and knowledge required to complete technical tasks are more likely to compare themselves in turnover situations [14, 47, 81]. This shared experience in applying technical skills consists of technical skills as well as the use of these skills to collaborate and complete IT tasks. In IT work context in which IT professionals either possess or acquire similar technical skills, there is a higher likelihood of team members comparing themselves to each other [75, 76].	Contract type: Contracts specify the work context in IT projects because less-specified contracts require intense interaction between project members than more-specified contracts [24]. Contracts can take one of two forms: time-and-materials (which are less specified and require a high degree of collaboration) and fixed-price (which are highly specified and require lower degrees of collaboration) [24].
Similarity in demographic attributes	Similarity in attributes refers to IT professionals having similar characteristics such as training, gender, age, and experience [81, 91].	Gender: Gender is a factor that codes male IT professionals as 1 and female IT professionals as 2. Age: Weekly calculation of current age based on the birth date of the IT professional.
Control variables
Job embeddedness	Conceptualized as a web that entangles an employee so that they cannot get out [58].	We calculate job embeddedness based on the centrality of a respective IT professional in the network.
Business confidence	Provides a prediction on future development in the software industry.	We employed the leading German business confidence index, the ifo business climate index, which is published on a monthly basis [12], for this calculation.
Unemployment rate	A measure of the competition between IT professionals on the job market.	Unemployment rates were obtained from the German Federal Statistics Office [78].
Dominant industry of projects	Describes the dominant industry of the projects in which the IT professional participated, as turnover rates vary across industries [77]. Since IT professionals work closely with the customer, they could be influenced by the customer’s industry.	Categorical variable: automotive, banking, insurance, ICT, manufacturing, public, utility, other industries, internal.
Success of projects	The extent to which projects contribute to the success of individuals, groups, organizations, and industries [69].	This variable is defined as the average profitability of the projects for which the IT professional worked during that week.
Department size	The number of ALPHA professionals that are working together on a project.	Continuous variable: number of employees working at the same time for the same customer.

Table 2. Means, Standard Deviations, and Correlations of Study Variables

	Mean	SD	1)	2)	3)	4)	5)	6)	7)	8)	9)
1) Turnover	0.002	0.05	1.00
2) Strength of turnover influence	0.01	0.04	0.02	1.00
3) Contract type	0.004	0.02	0.001	0.02	1.00
4) Gender	1.223	0.416	-0.001	-0.01	-0.1	1.00
5) Job embeddedness	46.32	54.49	-0.01	0.01	0.06	-0.04	1.00
6) Business confidence	103.2	8.59	0.00	-0.03	-0.03	0.05	-0.005	1.00
7) Unemployment rate	7.44	0.66	-0.006	-0.03	0.00	-0.10	0.00	-0.41	1.00
8) Success of projects	-0.19	2.2	0.00	-0.02	0.18	0.009	0.02	0.02	-0.04	1.00
9) Department size	1353	989.3	0.00	-0.01	-0.6	0.08	0.08	0.04	-0.16	0.08	1.00

Table 3. Overview of Cases and Data Collected

Case		Team task	Size	Turnover events (time span)	Development methodology	Similarity in demographic attributes	Similarity in technical ability
1	Furniture team^+	Software development	5	4 (8 months)	Agile (Scrum)	High	High
2	Insurance team*	IT consulting	5	4^# (6 months)	Waterfall	Low	Low
3	Auto team*	IT service	7	7 (24 months)	Agile (Kanban)	High	High
4	SmartDevice team^+	Software + hardware development	14	4 (8 months)	Waterfall	Low	Low
5	Aviation team^+	IT consulting	6	6^# (30 months)	Agile (Scrum)	High	Low

* Team within ALPHA (the same organization as Study 1). ⁺ Team from a different organization (not the same organization as Study 1). ^# Turnover events occurred during the COVID-19 pandemic.

Table 4. Survival Model for Turnover Influence from the Immediate Social Context

Variables	Base model	Model 1
Strength of turnover influence from the immediate social context		3.16 *** (0.27)
Job embeddedness	-0.001 * (0.0006)	-0.0009 (0.0006)
Factor (gender)	Insignificant	Insignificant
Factor (age)	Significant	Significant
Business confidence	-0.006 * (0.003)	-0.005 (0.003)
Unemployment rate	-0.43 *** (0.05)	-0.42 *** (0.05)
Factor (dominant industry)	Significant	Significant
Factor (dominant contract type)	Significant	Significant
Success of projects	0.004 (0.01)	0.009 (0.02)
Department size	-0.0001 ** (0.00009)	-0.0001 ** (0.00009)
Likelihood ratio test	2270 on 23 df ***	2348 on 24 df ***
Nagelkerke R2	11.90%	12.31%
Delta Nagelkerke R2		0.41%

*** significant at the 1% level, ** significant at the 5% level, * significant at the 10% level; standard error in parentheses

Table 5. Survival Models for Turnover Influence from the Immediate Social Context with or without Contextual Similarity in Technical Skills

Variables	Model 2	Model 3
Strength of turnover influence from the immediate social context with contextual similarity in ability (time and material contract)	0.10 *** (0.011)
Strength of turnover influence from the immediate social context without contextual similarity in skills (fixed price contract)		0.079 *** (0.012)
Job embeddedness	-0.001 * (0.0006)	-0.001 * (0.0006)
Factor (gender)	Insignificant	Insignificant
Factor (age)	Significant	Significant
Business confidence	-0.006 * (0.003)	-0.006 (0.003)
Unemployment rate	-0.42 *** (0.05)	-0.42 *** (0.05)
Factor (dominant industry)	Significant	Significant
Factor (dominant contract type)	Significant	Significant
Success of projects	0.005 (0.01)	0.007 (0.02)
Department size	-0.0001 ** (0.00009)	-0.0001 ** (0.00009)
Likelihood ratio test	2321 on 24 df ***	2296 on 24 df ***
Nagelkerke R2	12.17 %	12.03%
Delta Nagelkerke R2	0.27%	0.13%

*** significant at the 1% level, ** significant at the 5% level, * significant at the 10% level; Standard error in parentheses

Table 6. Survival Models for Turnover Influence from the Immediate Social Context with or without Similarity in Attributes (Gender)

Variables	Model 4	Model 5
Strength of turnover influence from the immediate social context with similarity in attributes (same gender)	0.09 *** (0.009)
Strength of turnover influence from the immediate social context without similarity in attributes (different gender)		0.05 *** (0.013)
Job embeddedness	-0.001 * (0.0006)	-0.001 * (0.0006)
Factor (age)	Significant	Significant
Business confidence	-0.005 (0.003)	-0.006 (0.003)
Unemployment rate	-0.42 *** (0.05)	-0.42 *** (0.05)
Factor (dominant industry)	Significant	Significant
Factor (dominant contract type)	Significant	Significant
Success of projects	0.008 (0.02)	0.006 (0.02)
Department size	-0.0001 ** (0.00006)	-0.0001 ** (0.00006)
Likelihood ratio test	2332 on 24 df ***	2282 on 24 df ***
Nagelkerke R2	12.23 %	11.97%
Delta Nagelkerke R2	0.33%	0.07%

*** significant at the 1% level, ** significant at the 5% level, * significant at the 10% level; standard error in parentheses

Table 7. Survival Models for Turnover Influence from the Immediate Social Context with or without Similarity in Attributes (Age)

Variables	Model 6	Model 7
Strength of turnover influence from the immediate social context with similarity in attributes (same age group)	0.02 * (0.001)
Strength of turnover influence from the immediate social context without similarity in attributes (different age group)		0.09 *** (0.001)
Job embeddedness	-0.01 * (0.0006)	-0.01 * (0.0006)
Factor (gender)	Significant	Significant
Business confidence	-0,005 * (0,003)	-0.005 * (0,003)
Unemployment rate	-0.42 *** (0.05)	-0.42 *** (0.05)
Factor (dominant industry)	Significant	Significant
Factor (dominant contract type)	Significant	Significant
Success of projects	0.004 (0.01)	0.006 (0.01)
Department size	-0.0001 * (0.00006)	-0.0001 * (0.00006)
Likelihood ratio test	2271 on 24 df ***	2231 on 24 df ***
Nagelkerke R2	11.90%	12.24%
Delta Nagelkerke R2	0%	0.34%

*** significant at the 1% level, ** significant at the 5% level, * significant at the 10% level; standard error in parentheses

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