Measuring Connection at Work: Development and Validation of the Organisational Connection Measure

Abstract

Current models of employee perceptions, such as engagement, overlook crucial elements of how employees evaluate the social aspects of their work, which limits their utility for organisations aiming to make positive changes. This paper aims to address this gap by proposing a new model of employee connection, pertaining to an individual’s perceptions of their connection to their role, their organisation, and the people around them at work. The development of the 36-item Organisational Connection Measure (OCM) was undertaken across three studies, with this paper presenting the final validation study in detail. Results support a general factor structure, suggesting that connection can be understood as a coherent, overarching construct. Additional evidence supports the utility of six distinct sub-factors which show differential relationships with key workplace outcomes. The measure demonstrated strong associations with important self-report outcomes, including lower intention to quit, higher task and contextual performance, and lower reported counterproductive work behaviours. While the sub-factors were highly intercorrelated, their distinct predictive validity highlights their potential value for targeted organisational interventions. This work offers a promising new tool for understanding and enhancing employee connection in organisational contexts.

Share and Cite:

Cuppello, S. , Tatlow, M. , Semmelink, D.S. , Kalar, J. , Mhlanga, N. , du Plessis, E. and Victor, J. (2026) Measuring Connection at Work: Development and Validation of the Organisational Connection Measure. Psychology, 17, 452-476. doi: 10.4236/psych.2026.174025.

1. Introduction

Research has long supported the relationship between employee perceptions and business outcomes such as employee performance (e.g., Christian et al., 2011; Harter et al., 2002; Judge et al., 2001). Indeed, organisations are increasingly reliant on surveying staff to identify ways to improve employee experience and so increase productivity and decrease attrition (WorkBuzz, 2022). However, current models of employee perceptions may lack breadth and overlook crucial elements of modern work that drive employee behaviour.

Employee engagement has a long-established relationship with individual performance (e.g., Christian et al., 2011). Measured through well-regarded and extensively validated measures such as the Utrecht Work Engagement Scale (UWES; Schaufeli et al., 2002), engagement is typically concerned with aspects such as individuals’ energy, involvement, and dedication to their specific role. A recent meta-analysis found engagement to be correlated with factors such as turnover intention, performance, and wellbeing (Mazzetti et al., 2023). However, engagement does not capture employees’ perceptions of their social relationships at work. Thriving is another construct that has been applied to work (e.g., Porath et al., 2012) and found to be related to important organisational outcomes such as task performance (TP; see Kleine et al., 2019). Thriving does cover social aspects of work, such as feeling valued, supported, and heard by coworkers (Peters et al., 2021); however, these insights merely provide an understanding of the satisfaction of an individual with their perceptions of how others behave around them, while not capturing the extent to which an individual feels part of and connected to a collective at work. Satisfaction with one’s relationship with coworkers and the broader psychosocial work environment has been found to be related to work performance (Shahid et al., 2011), counterproductive work behaviour (CWB; Agervold, 2009), and manager derailment (Gentry et al., 2007). In overlooking these aspects of employees’ social experiences at work, existing employee experience models lack insights into perceptions that are arguably very important to them. As a result, organisations developing interventions based on insights from existing models may be overlooking features of work that could potentially represent the greatest potential for positive change.

This paper makes the case for a novel model and measure of employee perceptions, the Organisational Connection Measure (OCM), developed to be highly predictive of factors relevant for organisational success, by first outlining its broad theoretical foundations and rationale before documenting the approach to model and measure development and, finally, presenting initial validation research.

Connection

Research across psychology and organisational science consistently positions connection as a fundamental human need for belonging and relatedness (Maslow, 1943; van Bel et al., 2009) which fosters experiences of affiliation, acceptance, and meaningful social ties that support wellbeing and behaviour (Allen et al., 2021; Baumeister & Leary, 1995; Ryan & Deci, 2000). Prior work characterises social connectedness as a subjective sense of being part of significant, supportive relationships and of having social ties that feel salient in daily life (Allen et al., 2021; van Bel et al., 2009). More broadly, connectedness has been described as the extent to which people experience their relationships and environments as personally meaningful and important, highlighting the appraised significance of social bonds rather than their mere presence (Allen et al., 2021; Schulze & Naidu, 2014).

Building on this foundation, Holt-Lunstad (2018a) proposed that social connection encompasses multiple dimensions, including the structure of a person’s social network, the functions relationships serve, and the emotional quality of those interactions. These aspects capture not only the presence of social ties, but also the perceived availability of support and the positive or negative nature of interpersonal exchanges; all of which have been shown to contribute to positive health and behavioural outcomes.

In the present work, workplace connection is understood as individuals’ perceptions of their connection to their role, their organisation, and the people around them at work. It reflects how supported and included a person feels in their work environment. Importantly, connection is viewed as measurable and malleable: Once understood, it can be strengthened through intentional behaviours and supportive organisational practices (Holt‑Lunstad, 2018b, 2024). This perspective underpins the development of the OCM, which seeks to capture meaningful variations in employees’ experiences of connection at work.

In their meta-analysis on the impact of social relationships on mortality, Holt-Lunstad et al. (2015) found that a lack of connection (i.e., social isolation or loneliness) has a significant detrimental effect on an individual’s wellbeing and health and increases risk of chronic illnesses, mental health issues, and mortality. In fact, weak social ties can increase the risk of early death by 26% - 32%, which is comparable to other well-known risk factors such as heavy smoking, obesity, and physical inactivity (Holt-Lunstad et al., 2015). In the workplace, a lack of connection is prevalent and impacts people’s lives inside and outside of work, and research has supported that fostering greater connection can help organisations to ensure their staff are healthy and productive (Holt-Lunstad, 2018b).

The development of this measure was informed by a desire to create a broad measure of aspects of people’s perceptions of their work life that ultimately influence business performance and success. Through this, it is anticipated that this measure will arm organisations with useful insights to improve their employees’ perceptions to lead to better business outcomes. As such, criterion validity was the primary concern when developing this measure, rather than a desire to align with established models.

Existing Literature

As part of the development of the OCM, a literature review was conducted to understand the domains of employee experience relevant to connection that ultimately contribute to business success. Papers have been included if they relate connection to aspects of individual performance, group performance, or retention. Individual performance includes subjective and objective performance, underperformance, derailment, and counterproductive work behaviour. Group performance includes aspects related to organisational performance, team productivity, or team cohesion. Retention includes related factors such as intention to quit. The specific interest of this model is in changeable states related to connection rather than stable psychological traits such as personality, so the model exclusively measures constructs that organisations can endeavour to improve, which theoretically should lead to greater organisational success. A decision was also made to overlook aspects relating to perceptions towards specific individuals, such as managers or leaders, as these aspects would be better captured through activities such as manager and leader appraisals.

In all, 27 different constructs that relate connection to performance or retention were identified in the literature review. Papers highlighting the predictive validity of these constructs in the workplace are outlined in Table 1 at the end of this section. The constructs are presented in three broad themes (role connection, organisational connection, and interpersonal connection) merely for ease of reading, although there is significant overlap between themes. This review aims to justify the inclusion of these specific constructs in the OCM model, rather than serve as a comprehensive systematic review of existing literature. Excellent reviews of this nature already exist; for example, Rovetta et al. (2025) on team and organisational identity, Istiningtyas et al. (2025) on social embeddedness of thriving at work, Blau et al. (2023) on organisational belonging, Iovoli et al. (2025) on interpersonal problems and mental health outcomes, and Pietromonaco and Collins (2017) on close relationships and health.

Role Connection

There are ten constructs that have been categorised under role connection, namely clarity, autonomy, burnout, recognition, wellbeing, stress/pressure, work-life balance, perceived productivity, job satisfaction, and motivation. These are constructs that pertain to how connected individuals feel to the actual job they are performing, how able they are to do this job, and the impact it has on them. They were particularly related to factors relevant to individual performance.

Organisational Connection

This category comprises six constructs related to how individuals feel about their connection to the organisation they work for. These are: compensation, organisational commitment, organisational support, organisational justice, organisational identity, and work environment. Many of these factors are particularly important considering employee retention and intention to quit.

Interpersonal Connection

Eleven constructs have been categorised as part of interpersonal connection, namely trust, psychological safety, team identity, social connection, collaboration, conflict, peer support, communication effectiveness, size of network, social roles, and satisfaction with relationships. These constructs broadly pertain to how an individual feels about the social aspects of work and how connected they feel to those around them. These constructs were especially relevant to factors related to team and group performance. For simplicity’s sake, trust has been listed as a single construct; however, findings encompass multiple dimensions, including interpersonal and organisational trust.

Table 1. Constructs relating aspects of connection to relevant outcomes in the literature.

Category

Related Outcome

Construct (Predictor)

References

Role Connection

Underperformance

Lack of clarity

Low job autonomy

Van den Heuvel et al., 2010

Burnout and excessive work demands

Aboagye et al., 2019; Dyrbye et al., 2019; Shahid et al., 2011; Van den Heuvel et al., 2010

Lack of recognition

Hlengane & Bayat, 2013

Stress/pressure

Pflanz & Ogle, 2006; Shahid et al., 2011

Poor work-life balance

Shahid et al., 2011

Lack of motivation

Hlengane & Bayat, 2013

Counterproductive work behaviours

Lack of job autonomy

Browning, 2008; Marcus & Schuler, 2004; Penney et al., 2003; Vardi & Weitz, 2003

Burnout and high workload

Baillien et al., 2011; Blau & Andersson, 2005

Stress/pressure

Agervold, 2009; Hauge et al., 2009; Martinko et al., 2005; Vardi & Weitz, 2003

Poor work-life balance

Scott et al., 2015

Low job satisfaction

Hollinger & Clark, 1982; Mangione & Quinn, 1975; Spector & Fox, 2002

Derailment

Perceived productivity

Van Velsor & Leslie, 1995

Retention or intention to quit

Clarity

Ghosh et al., 2013; James et al., 2011

Autonomy

Koyuncu et al., 2006

Burnout

Malik et al., 2013

Recognition

James et al., 2011; Koyuncu et al., 2006; Nasir et al., 2019

Work-life balance

Nasir & Mahmood, 2016; Rasdi et al., 2018

Continued

Job satisfaction

De Sousa Sabbagha et al., 2018; Lyu et al., 2022; McGilton et al., 2013; Nasir & Mahmood, 2016

Motivation

De Sousa Sabbagha et al., 2018; Sarmad et al., 2016

Organisational Connection

Performance

Compensation

Hlengane & Bayat, 2013

Organisational justice

Hlengane & Bayat, 2013

Organisational support

Hlengane & Bayat, 2013

Counterproductive work behaviour

Organisational commitment

Mathieu & Zajac, 1990

Perceived organisational support

Alias & Rasdi, 2015; Ones et al., 2003

Organisational justice

Akinsola & Alarape, 2019; Hershcovis et al., 2007; Jones & Martens, 2009

Retention and intention to quit

Perceptions of one’s work environment

Bibi et al., 2017; Kundu & Lata, 2017; Nasir & Mahmood, 2016; Warraich et al., 2019

Compensation

Hussain & Rehman, 2013; Koyuncu et al., 2006; Nasir et al., 2019; Sarmad et al., 2016

Organisational commitment

Atif et al., 2011; Nasyira et al., 2014

Organisational support (including through training and development)

Haider et al., 2015; James et al., 2011; Janjua & Gulzar, 2014; Nasyira et al., 2014; Saleem & Affandi, 2014; Warraich et al., 2019

Perceptions of and alignment with organisational identity and culture

Haider et al., 2015; Hussain & Rehman, 2013; Matongolo et al., 2018

Team productivity

Organisational support

Salas et al., 2015

Organisational performance

Organisational support (through improved internal auditing and learning)

Carmeli & Zisu, 2009

Interpersonal Connection

Individual performance and underperformance

Poor communication

Hlengane & Bayat, 2013

Continued

Satisfaction with one’s relationships with coworkers

Shahid et al., 2011

Counterproductive work behaviour

Trust in the organisation

Thau et al., 2007

Social connection

Agervold, 2009

Interpersonal conflict

Chen & Spector, 1992; Frone, 1998; Hauge et al., 2009

Workplace derailment

Satisfaction with one’s relationships

Gentry et al., 2007; Lombardo & McCauley, 1988; Van Velsor & Leslie, 1995

Retention and intention to quit

Psychological safety

Kim et al., 2021

Collaboration and conflict

Belias et al., 2023

Communication effectiveness

Hussain & Rehman, 2013; Steiner et al., 2020

Social roles

Steiner et al., 2020

Team productivity

Interpersonal trust

Jarvenpaa & Leidner, 1999; Jarvenpaa et al., 2004

Collaboration

Stashevsky & Koslowsky, 2006

Psychological safety

Bergmann & Schaeppi, 2016

Team cohesiveness and productivity

Organisational and interpersonal trust

Cohen et al., 1996; Hansen et al., 2002; Mach et al., 2010

Team identity and climate

Casey-Campbell & Martens, 2009; Chen et al., 2008; Daspit et al., 2013; Hogg & Hardie, 1992

Collaboration

Wang et al., 2010; West et al., 2009

Positive conflict

Sullivan & Feltz, 2003; Sullivan & Shorts, 2011

Peer support

Mäkikangas et al., 2017

Effective communication

Holt & Sparkes, 2001; Mesmer-Magnus & DeChurch, 2009; Sullivan & Short, 2011

Size of network

Schulte et al., 2012

Continued

Organisational performance

Organisational trust (through improved internal auditing and learning)

Carmeli & Zisu, 2009

Size of network

Carmeli, 2007

Social capital

Carmeli, 2007

Psychological safety (through improved learning through failure)

Carmeli, 2007

Initial Development Process Preceding the Current Study

The current study presents the psychometric qualities of the novel OCM. The aim was to develop a psychometrically robust tool that can predict positive workplace outcomes. An iterative development process was used to refine the measure and ensure a balance between psychometric rigour and practical utility. Three studies were completed as part of the development of the OCM, with this paper being concerned with the final study demonstrating the validity and reliability of the final assessment. Each study built upon the last with a similar methodology but distinct occupational samples.

The first two studies have been documented in detail elsewhere (Thomas, 2025) and are summarised below as they relate to the present study. The initial item pool consisted of 108 items, with four items written for each of the 27 psychological components identified through the literature review. Items were authored to maximise content validity, avoid double-barrelling, and capture the breadth of each construct. Subject matter experts reviewed all items for clarity, redundancy, and conceptual alignment. Prior to analysis, inter-item correlations were inspected, and 24 items with correlations above 0.80 were removed, resulting in 84 items entering exploratory factor analysis (EFA). A parallel analysis supported an 8-factor solution, and an EFA using principal axis factoring with Oblimin rotation was conducted. Items with cross-loadings or loadings below 0.40 were removed, yielding 64 items. Although eight factors initially emerged, further theoretical inspection indicated conceptual overlap, and the structure was refined into six psychologically coherent dimensions. Specifically, Factor 1 and Factor 8 both focused on relationships and collaboration. Factor 6 and Factor 7 both reflected perceptions of effectiveness and ability to carry out the role. Although Factor 5 overlapped with relational themes, it was more closely aligned with psychological safety and trust. Based on factor loadings, predictive relationships with relevant outcomes (i.e., intention to quit, task performance, contextual performance, and counterproductive work behaviour), and coverage of the original conceptual domains, 54 items were retained for confirmatory factor analysis (CFA). Model fit indices, i.e., comparative fit indices (CFI > 0.95) and Tucker-Lewis indices (TLI > 0.95), and item performance guided further refinement, ensuring each factor retained strong theoretical coherence, internal consistency (ranging from α = 0.83 to 0.98), and predictive utility.

To strengthen underrepresented factors, 12 new items were added in the second study, resulting in 66 items tested in a subsequent CFA. Items were assigned to factors according to their highest loading and conceptual alignment, with no cross-loadings included. Skewness values ranged from −1.78 to 0.57. Most variables showed approximately normal distributions. As skewness values fell within the commonly accepted range of ±2 (e.g., Kline, 2016), no transformations were applied. All variables showed acceptable levels of kurtosis (−1.22 to 3.84), suggesting that the distributions slightly but did not significantly deviate from normality (Kline, 2016; Curran et al., 1996). The revisions made during the second study were therefore found to have strengthened the factor structure, improving both the theoretical and practical utility of the model. The first two studies also showed that the subdimensions exhibited differential predictive validity through differentiated patterns of relationships with predictive criteria: intention to quit, task performance, contextual performance, and counterproductive work behaviour, highlighting their unique contributions to workplace outcomes.

Through this iterative, evidence-based process, combining expert review, EFA/CFA outcomes, and predictive validity testing, the scale was reduced to a final, psychometrically robust set of 36 items representing six dimensions of organisational connection. Building on these prior studies, the present study sought to test the final version of the OCM, evaluating its robustness and predictive power in a more comprehensive manner.

2. Method

2.1. Participants

Given that the study focused on workplace perceptions, an occupational sample was utilised. All participants were working individuals who had voluntarily joined a research panel after completing a psychometric assessment with a large global psychometric publisher, undertaken for genuine occupational purposes such as recruitment or employee development. As such, all participants had experience in the working world.

Across the various studies undertaken, a total of 1,003 respondents participated. However, the present article focuses on the final sample of 307 respondents, of which 63% indicated being female, 34% male, and 3% other/no response. The majority were from the UK (58%), followed by South Africa (17%), USA (10%), Canada (7%), and Australia (5%), with 3% indicating other/no response. Their ages ranged from 19 to 74 years (M = 46.9, SD = 11.6).

2.2. Materials

Organisational Connection Measure (OCM)

For the current study, the final measure used was the 36-item OCM derived from prior research (Thomas, 2025). Respondents answered on a 7-point Likert scale (1 = strongly disagree to 7 = strongly agree) and were asked to think about their current job. Scores were calculated for each of the six factors (Appreciation, Cohesion, Belonging, Trust, Contribution, and Wellbeing), as well as an overall Connection score. Details of the factors, descriptions, and example items can be seen in Table 2.

Table 2. OCM factors, descriptions, and example items.

Factor

Description

Example Item

Appreciation

Fair reward for the work completed; feeling as though efforts are acknowledged and appreciated and achievements celebrated.

I feel valued for my work by my colleagues and peers.

Cohesion

Positive social relationships; individuals working together effectively towards the same goals; support for one another.

I work in a friendly and inclusive atmosphere.

Contribution

Access to resources required to be effective in role; clear expectations and autonomy to manage work and time.

I have access to the

information I need to perform my job effectively.

Belonging

Satisfaction and fulfilment with job role and alignment to wider goals, values, and success.

I am proud to be a member of my team.

Trust

Confidence in decision-making processes; feeling as though the work environment is a safe space for communication and that all voices matter.

I can rely on the promises and commitments made by my superiors.

Wellbeing

Healthy work-life balance; ability to manage stress and pressure effectively without it having a negative impact on health or performance.

My job promotes a sense of balance and wellbeing in my life.

The Individual Work Performance Questionnaire (IWPQ; Koopmans et al., 2012)

The IWPQ is an 18-item measure of self-reported work performance, based on three scales: task performance (TP), contextual performance (CP), and counterproductive work behaviour (CWB). It has been found to be valid and reliable and correlates well with other measures of work performance (Ramos-Villagrasa et al., 2019). Participants responded to items on a 5-point Likert scale and were asked to consider the last three months of work.

Intention to Quit

Intention to quit (ITQ) was measured using a self-constructed single item scale asking: “I often think about leaving my job”, existing on a 7-point Likert scale (1 = strongly disagree to 7 = strongly agree). Turnover intention is often used as a proxy for actual turnover, with evidence to suggest the two are related (Tett & Meyer, 1993).

2.3. Procedure

Participants were recruited via email and directed to an online survey platform. After providing informed consent, they completed the relevant measures for each study, followed by demographic questions. Participants completed the OCM, the ITQ question, and the IWPQ scale to enable the researchers to investigate the predictive validity of the items and scale. At the end of each study, participants received debrief information and were thanked for their participation.

2.4. Analysis

As exploratory factor analyses conducted in earlier studies helped establish an initial factor structure, the current study focused on confirmatory factor analysis to evaluate the finalised model, followed by correlations to examine relationships between study variables, and regression analyses to assess predictive validity. Prior to analysis, cases with missing data on key variables were removed. All analyses were performed using RStudio (Posit Team, 2025).

3. Results

3.1. Confirmatory Factor Analysis

To confirm the reduced 6-factor model and higher-order Connection model, a CFA was conducted using the diagonally weighted least squares (DWLS) estimator, which is recommended for ordinal data such as Likert-type responses due to its robustness and accuracy in estimating model fit (Flora & Curran, 2004). The 6-factor structure was specified based on the results of the preceding EFA, with items assigned to factors according to their highest loading and conceptual alignment. No cross-loadings were included. The aim of the CFA was to assess the model’s overall fit to the data and provide evidence for the factorial validity of the proposed structure.

Model fit was evaluated using a range of indices: the comparative fit index (CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA), and the standardised root mean square residual (SRMR), in accordance with recommended thresholds (Hu & Bentler, 1999). Internal consistency reliability was assessed for each of the six factors using both Cronbach’s alpha and McDonald’s omega total. While Cronbach’s alpha remains a widely used measure of reliability, it assumes tau-equivalence and may underestimate reliability when this assumption is violated. Therefore, McDonald’s omega total was also reported, as it provides a more accurate estimate of reliability in the presence of congeneric items (Sijtsma, 2009). Values above 0.70 were considered acceptable, with higher values indicating stronger internal consistency. Results can be seen in Table 3.

Table 3. Confirmatory factor analysis and reliability statistics of the OCM.

Factor

χ2/df

p-value

CFI

TLI

RMSEA

Confidence Interval

SRMR

α

ωt

No. Items

Connection

1.078

>0.05

0.998

0.998

0.016

0.000 - 0.025

0.065

0.96

0.97

36

Appreciation

0.856

>0.05

1.000

1.002

0.000

0.000 - 0.058

0.037

0.85

0.89

6

Continued

Cohesion

0.379

>0.05

1.000

1.019

0.000

0.000 - 0.009

0.031

0.81

0.85

6

Contribution

1.019

>0.05

1.000

0.999

0.008

0.000 - 0.065

0.046

0.80

0.85

6

Belonging

0.254

>0.05

1.000

1.013

0.000

0.000 - 0.000

0.023

0.87

0.91

6

Trust

0.441

>0.05

1.000

1.007

0.000

0.000 - 0.024

0.027

0.88

0.91

6

Wellbeing

1.367

>0.05

0.997

0.995

0.035

0.000 - 0.078

0.048

0.86

0.90

6

Factor loadings

Appreciation

Collaboration

Contribution

Belonging

Trust

Wellbeing

Item 1

0.677

0.472

0.696

0.863

0.782

0.797

Item 2

0.553

0.784

0.732

0.730

0.830

−0.5301

Item 3

0.883

0.780

0.668

0.750

0.810

0.716

Item 4

0.774

0.788

0.804

0.789

0.679

0.852

Item 5

0.795

0.650

0.644

0.731

0.794

0.930

Item 6

0.838

0.666

0.568

0.851

0.706

−0.7281

Connection

0.916

0.949

0.996

0.937

0.954

0.925

R2

0.840

0.901

0.992

0.879

0.909

0.856

Note. 1Reverse-phrased statement. Item 1 - 6 refers to the items of the respective factors where Item 1 of Appreciation is not the same as Item 1 of Collaboration, etc.

All six factors as well as the higher-order Connection factor demonstrated excellent model fit (see Table 3), with all achieving very strong comparative fit indices (CFI ≥ 0.997) and Tucker-Lewis indices (TLI ≥ 0.995). The higher‑order Connection factor and all subdimensions (Appreciation, Cohesion, Belonging, Trust, Contribution, and Wellbeing) showed particularly strong fit, with CFI and TLI values at or above 0.997 and RMSEA values ranging from 0.000 to 0.035, all within the recommended thresholds for close fit. SRMR values were consistently low across models (0.023 - 0.065), further indicating excellent model-data correspondence. Internal consistency was high across all subdimensions, with Cronbach’s alpha values ranging from 0.80 (Contribution) to 0.88 (Trust), and McDonald’s omega total values from 0.85 to 0.91, indicating robust reliability. The overall Connection factor also demonstrated excellent internal consistency (α = 0.96, ω = 0.97), supporting the coherence and stability of the 36‑item measure.

3.2. Correlations

To explore the relationships between the latent constructs, inter-factor correlations were examined. These correlations provide insight into the extent to which the factors are distinct yet related, offering evidence for the conceptual structure of the model. Given the theoretical overlap between some constructs (e.g., collaboration and psychological safety), moderate to strong correlations were expected. The correlation matrix for the six factors and overall connection, as well as intention to quit and the IWPQ, is presented in Table 4.

Table 4. Correlation matrix for the connection factors, ITQ, and IWPQ (Consisting of TP, CP, and CWB).

M

SD

1

2

3

4

5

6

7

8

9

10

1. Appreciation

28.11

8.21

-

2. Cohesion

30.77

6.47

0.66***

-

3. Contribution

30.59

6.90

0.80***

0.69***

-

4. Belonging

31.30

7.80

0.76***

0.73***

0.80***

-

5. Trust

27.55

8.23

0.75***

0.79***

0.76***

0.72***

-

6. Wellbeing

28.94

8.03

0.71***

0.73***

0.73***

0.74***

0.75***

-

7. Connection

177.26

40.45

0.89***

0.86***

0.90***

0.89***

0.90***

0.88***

-

8. ITQ

2.97

1.57

−0.63***

−0.55***

−0.61***

−0.71***

−0.63***

−0.67***

−0.72***

-

9. TP

15.06

3.59

0.19**

0.31***

0.28***

0.26***

0.21***

0.40***

0.31***

−0.13*

-

10. CP

25.25

5.69

0.21***

0.18**

0.31***

0.27***

0.14*

0.20***

0.25***

−0.07

0.46***

-

11. CWB

6.17

4.11

−0.33***

−0.42***

−0.41***

−0.42***

−0.43***

−0.44***

−0.46***

0.47***

−0.36***

−0.16**

Note. * = p < 0.05, ** = p < 0.01, *** = p < 0.001; ITQ = Intention to Quit, TP = Task Performance, CP = Contextual Performance, CWB = Counterproductive Work Behaviour.

The bivariate correlations in Table 4 show that the subdimensions were strongly and significantly intercorrelated (r = 0.66 - 0.80), suggesting that they share common variance, which is consistent with the presence of an overarching Connection factor. This is further supported by the very high correlations between each subdimension and the total Connection score (r = 0.86 - 0.90), demonstrating that each factor meaningfully contributes to the broader construct.

However, despite their shared variance, the subdimensions showed differentiated patterns of relationships with the predictive criteria, namely intention to quit, and IWPQ constructs Task Performance, Contextual Performance, and Counterproductive Work Behaviour. For example, Belonging demonstrated the strongest negative correlation with ITQ (r = −0.71), while Wellbeing had the strongest positive correlation with TP (r = 0.40) and Contribution with CP (r = 0.31). Wellbeing was most strongly negatively associated with CWB (r = −0.44); however, the relationships between all factors and CWB were of similar levels (r = −0.41 to −0.44).

3.3. Linear Regressions

Linear regression analyses were conducted to examine the relationship between Connection and the four outcome variables: ITQ, TP, CP, and CWB. Connection significantly predicted all four outcomes, as shown in Table 5.

Higher Connection was associated with lower intention to quit (B = −0.03, SE = 0.002, t(296) = −17.70, p < 0.001, 95% CI [−0.03, −0.02]), accounting for 51% of the variance in ITQ scores (R2 = 0.51). Connection positively predicted Task Performance (B = 0.03, SE = 0.00, t(296) = 5.61, p < 0.001, 95% CI [0.02, 0.04]), accounting for 10% of the variance in TP scores (R2 = 0.10), as well as Contextual Performance (B = 0.03, SE = 0.01, t(296) = 4.36, p < 0.001, 95% CI [0.02, 0.05]), accounting for 6% of the variance in CP scores (R2 = 0.06); and negatively

Table 5. Results from linear regressions showing connection predicting ITQ and IWPQ.

predicted Counterproductive Work Behaviour (B = −0.05, SE = 0.005, t(296) = −8.94, p < 0.001, 95% CI [−0.06, −0.03]), accounting for 21% of the variance in CWB scores (R2 = 0.21). These results suggest that stronger feelings of connection at work are associated with better performance and lower intentions to quit or performing of counterproductive work behaviours, with effect sizes ranging from small to large.

4. Discussion

The present study was the final study among a set of three to develop and validate a measure of workplace connection and examine its relationship with key organisational outcomes, including intention to quit, task performance, contextual performance, and counterproductive work behaviour. The findings provide strong support for the reliability and validity of the Organisational Connection Measure and its six subdimensions: Appreciation, Cohesion, Contribution, Belonging, Trust, and Wellbeing.

The CFA demonstrated excellent model fit across all subdimensions, with fit indices (CFI, TLI) at or above 0.995, RMSEA values at or near zero, and SRMR values all below 0.070. These results indicate that the Connection factors are psychometrically sound and capture distinct yet highly interrelated aspects of workplace connection. Reliability estimates were consistently strong, with Cronbach’s alpha and McDonald’s omega total values ranging from 0.80 to 0.97 across the dimensions, supporting the internal consistency of the measure.

Bivariate correlations revealed that while the subdimensions shared considerable variance, consistent with an overarching Connection construct, they also showed unique patterns of association with external criteria. In particular, Belonging demonstrated the strongest negative association with intention to quit, suggesting that employees who feel aligned to the organisation and its goals are less likely to consider leaving the organisation. Wellbeing, in turn, showed the strongest positive relationship with task performance, suggesting that employees who experience a healthy work-life balance have more energy and focus to complete their tasks well. Lastly, the finding that Contribution was most strongly related to contextual performance suggests that employees who are granted the autonomy and resources they need to take initiative and be effective in their work are willing to go above and beyond in their roles. These differentiated patterns suggest that while workplace connection operates as a coherent whole, its facets contribute uniquely to important organisational outcomes.

Regression analyses reinforced the utility of the measure in predicting outcomes, demonstrating that higher overall Connection significantly predicted lower turnover intentions and counterproductive work behaviours, and higher task and contextual performance. Notably, Connection accounted for a substantial 51% of the variance in intention to quit, highlighting its potential as a critical target for interventions aimed at improving employee retention. Although effect sizes for task and contextual performance were smaller, they were still statistically significant and meaningful, suggesting that fostering workplace connection can contribute to improved individual and organisational performance.

In a separate study of 178 respondents (Thomas, 2025), incremental validity was further supported in regression analyses: When turnover intention was first regressed on burnout alone, burnout strongly predicted intention to quit (β = 0.671, p < 0.001, R2 = 0.451). Adding Connection to the model substantially improved prediction (β = −0.538, p < 0.001, R2 = 0.611), with the part correlation of burnout dropping from 0.671 to 0.232 and Connection showing a unique part correlation of −0.400. These findings suggest that Connection captures variance in turnover intention not explained by burnout, supporting its discriminant and incremental validity relative to adjacent constructs.

We found strong support for a general factor of organisational connection, suggesting that a unifying sense of connection at work can be meaningfully captured. However, our findings also demonstrate that there is practical value in distinguishing between the six proposed sub-factors with a higher-order factor of Connection. Despite high intercorrelations among these sub-dimensions, each exhibited unique patterns of association with key work-related outcomes. This differentiation highlights the potential utility of the 6-factor model for organisational practice, particularly when seeking to diagnose and intervene in specific areas where connection may be lacking within teams or departments.

Overall, the results highlight the central role of workplace connection in shaping employee attitudes and behaviours. Employees who feel a greater sense of connection are more likely to remain with their organisation, perform better, and engage less in counterproductive behaviour, further underscoring the importance of organisational practices and leadership behaviours that cultivate a strong sense of connection among employees.

5. Limitations

This study relied on self-report measures rather than objective indicators, such as actual turnover, performance metrics, or multi-source assessments (e.g., 360-degree feedback). This may introduce common method bias and restrict the generalisability of findings to actual performance outcomes (Podsakoff et al., 2003). Future research could implement a latent common-method factor to assess its potential influence, as failing to account for common method bias may inflate the observed relationships among constructs. Nevertheless, previous studies have supported that both the self-report IWPQ and intention to quit have been related to work performance and turnover, respectively (Ramos-Villagrasa et al., 2019; Tett & Meyer, 1993), which supports their use in the present study.

Additionally, further validation of the Connection construct is needed, particularly its discriminant validity relative to related constructs. Although the present study focused primarily on internal structure and criterion relations, establishing that Connection is empirically distinct from related constructs such engagement, job satisfaction, person-job fit, and thriving, as well as psychosocial variables, such as facets of emotional intelligence, vocational interests, and preference for remote or hybrid work, remains an important next step. Discriminant validity testing using multitrait-multimethod approaches or structural equation modelling can help clarify the extent to which Connection captures a unique relational-motivational construct above and beyond related constructs. Incorporating more incremental validity analyses would further demonstrate whether Connection predicts meaningful outcomes (e.g., well-being, performance, retention intentions) above and beyond these established constructs. Including variables such as trait emotional intelligence (particularly facets like sociability, empathy, and well-being) and contextual preferences for remote work may be especially informative, as these represent individual differences that are likely to correlate with Connection but remain conceptually distinct from it. Together, these investigations will provide a more comprehensive validity framework and support the scale’s utility in both applied and research settings.

The sample was drawn primarily from Western populations, limiting confidence in generalisability to other cultural or occupational contexts. Although multiple English-speaking regions were included, replication with non-Western and more representative samples will be important. Future research should also examine the relationship between Connection and objective performance indicators (e.g., supervisor ratings, team metrics, absenteeism) and engagement, as well as potential demographic moderators such as age, gender, role seniority, and cultural background.

6. Conclusion

This research provides robust support for a comprehensive model of workplace connection, encompassing employees’ perceptions of their work, their organisation, and their colleagues. The findings also demonstrate the reliability, construct validity, and criterion validity of the connection measure, highlighting its relevance in predicting key work outcomes and its potential utility in both research and applied organisational contexts.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References

[1] Aboagye, E., Björklund, C., Gustafsson, K., Hagberg, J., Aronsson, G., Marklund, S. et al. (2019). Exhaustion and Impaired Work Performance in the Workplace: Associations with Presenteeism and Absenteeism. Journal of Occupational & Environmental Medicine, 61, e438-e444. [Google Scholar] [CrossRef] [PubMed]
[2] Agervold, M. (2009). The Significance of Organizational Factors for the Incidence of Bullying. Scandinavian Journal of Psychology, 50, 267-276. [Google Scholar] [CrossRef] [PubMed]
[3] Akinsola, O., S. & Alarape, P. A. I. (2019). Determinants of Counterproductive Work Behaviour among Local Government Workers in Ibadan, Oyo State, Nigeria. In Proceedings of the 9th International Conference on Humanities, Psychology and Social Sciences (p. 44). Acavent. [Google Scholar] [CrossRef
[4] Alias, M., & Rasdi, R. M. (2015). Organizational Predictors of Workplace Deviance among Support Staff. Procedia—Social and Behavioral Sciences, 172, 126-133. [Google Scholar] [CrossRef
[5] Allen, K., Kern, M. L., Rozek, C. S., McInerney, D. M., & Slavich, G. M. (2021). Belonging: A Review of Conceptual Issues, an Integrative Framework, and Directions for Future Research. Australian Journal of Psychology, 73, 87-102. [Google Scholar] [CrossRef] [PubMed]
[6] Atif, A., Kashif-Ur-Rehman, Ijaz-Ur-Rehman, Muhammad, A. K., & Asad, A. H. (2011). Impact of Organizational Commitment on Job Satisfaction and Employee Retention in Pharmaceutical Industry. African Journal of Business Management, 5, 7316-7324. [Google Scholar] [CrossRef
[7] Baillien, E., Rodriguez-Muñoz, A., Van den Broeck, A., & De Witte, H. (2011). Do Demands and Resources Affect Target’s and Perpetrators’ Reports of Workplace Bullying? A Two-Wave Cross-Lagged Study. Work & Stress, 25, 128-146. [Google Scholar] [CrossRef
[8] Baumeister, R. F., & Leary, M. R. (1995). The Need to Belong: Desire for Interpersonal Attachments as a Fundamental Human Motivation. Psychological Bulletin, 117, 497-529. [Google Scholar] [CrossRef] [PubMed]
[9] Belias, D., Rossidis, I., Sotiriou, A., & Malik, S. (2023). Workplace Conflict, Turnover, and Quality of Services. Case Study in Greek Seasonal Hotels. Journal of Quality Assurance in Hospitality & Tourism, 24, 453-476. [Google Scholar] [CrossRef
[10] Bergmann, B., & Schaeppi, J. (2016). A Data-Driven Approach to Group Creativity. Harvard Business Review.
[11] Bibi, P., Pangil, F., Johari, J., & Ahmad, A. (2017). The Impact of Compensation and Pro-motional Opportunities on Employee retention In Academic Institutions: The Moderating Role of Work Environment. Journal of Economic & Management Perspectives, 11, 378-391.
[12] Blau, G., & Andersson, L. (2005). Testing a Measure of Instigated Workplace Incivility. Journal of Occupational and Organizational Psychology, 78, 595-614. [Google Scholar] [CrossRef
[13] Blau, G., Goldberg, C., & Kyser, S. (2023). Developing a Scale of Organizational Belonging: A Comprehensive Literature Review. Journal of Organizational Psychology, 23, 45-60.
[14] Browning, V. (2008). An Exploratory Study into Deviant Behaviour in the Service Encounter: How and Why Front-Line Employees Engage in Deviant Behaviour. Journal of Management & Organization, 14, 451-471. [Google Scholar] [CrossRef
[15] Carmeli, A. (2007). Social Capital, Psychological Safety and Learning Behaviours from Failure in Organisations. Long Range Planning, 40, 30-44. [Google Scholar] [CrossRef
[16] Carmeli, A., & Zisu, M. (2009). The Relational Underpinnings of Quality Internal Auditing in Medical Clinics in Israel. Social Science & Medicine, 68, 894-902. [Google Scholar] [CrossRef] [PubMed]
[17] Casey‐Campbell, M., & Martens, M. L. (2009). Sticking It All Together: A Critical Assessment of the Group Cohesion-Performance Literature. International Journal of Management Reviews, 11, 223-246. [Google Scholar] [CrossRef
[18] Chen, N. Y., Lu, J., Tjosvold, D., & Lin, C. (2008). Effects of Team Goal Interdependence on Newcomer Socialization: An Experiment in China. Journal of Applied Social Psychology, 38, 198-214. [Google Scholar] [CrossRef
[19] Chen, P. Y., & Spector, P. E. (1992). Relationships of Work Stressors with Aggression, Withdrawal, Theft and Substance Use: An Exploratory Study. Journal of Occupational and Organizational Psychology, 65, 177-184. [Google Scholar] [CrossRef
[20] Christian, M. S., Garza, A. S., & Slaughter, J. E. (2011). Work Engagement: A Quantitative Review and Test of Its Relations with Task And Contextual Performance. Personnel Psychology, 64, 89-136. [Google Scholar] [CrossRef
[21] Cohen, S. G., Ledford, G. E., & Spreitzer, G. M. (1996). A Predictive Model of Self-Managing Work Team Effectiveness. Human Relations, 49, 643-676. [Google Scholar] [CrossRef
[22] Curran, P. J., West, S. G., & Finch, J. F. (1996). The Robustness of Test Statistics to Nonnormality and Specification Error in Confirmatory Factor Analysis. Psychological Methods, 1, 16-29. [Google Scholar] [CrossRef
[23] Daspit, J., Justice Tillman, C., Boyd, N. G., & Mckee, V. (2013). Cross‐functional Team Effectiveness: An Examination of Internal Team Environment, Shared Leadership, and Cohesion Influences. Team Performance Management: An International Journal, 19, 34-56. [Google Scholar] [CrossRef
[24] De Sousa Sabbagha, M., Ledimo, O., & Martins, N. (2018). Predicting Staff Retention from Employee Motivation and Job Satisfaction. Journal of Psychology in Africa, 28, 136-140. [Google Scholar] [CrossRef
[25] Dyrbye, L. N., Shanafelt, T. D., Johnson, P. O., Johnson, L. A., Satele, D., & West, C. P. (2019). A Cross-Sectional Study Exploring the Relationship between Burnout, Absenteeism, and Job Performance among American Nurses. BMC Nursing, 18, Article No. 57. [Google Scholar] [CrossRef] [PubMed]
[26] Flora, D. B., & Curran, P. J. (2004). An Empirical Evaluation of Alternative Methods of Estimation for Confirmatory Factor Analysis with Ordinal Data. Psychological Methods, 9, 466-491. [Google Scholar] [CrossRef] [PubMed]
[27] Frone, M. R. (1998). Predictors of Work Injuries among Employed Adolescents. Journal of Applied Psychology, 83, 565-576. [Google Scholar] [CrossRef] [PubMed]
[28] Gentry, W. A., Ekelund, B. Z., Hannum, K. M., & de Jong, A. (2007). A Study of the Discrepancy between Self-and Observer-Ratings on Managerial Derailment Characteristics of European Managers. European Journal of Work and Organizational Psychology, 16, 295-325. [Google Scholar] [CrossRef
[29] Ghosh, P., Satyawadi, R., Prasad Joshi, J., & Shadman, M. (2013). Who Stays with You? Factors Predicting Employees’ Intention to Stay. International Journal of Organizational Analysis, 21, 288-312. [Google Scholar] [CrossRef
[30] Haider, M., Rasli, A., Akhtar, C. S., Yusoff, R. B. M., Malik, O. M., Aamir, A., Arif, A., Naveed, S., & Tariq, F. (2015). The Impact of Human Resource Practices on Employee Retention in the Telecom Sector. International Journal of Economics and Financial Is-sues, 5, 63-69.
[31] Hansen, M. H., Morrow Jr., J. L., & Batista, J. C. (2002). The Impact of Trust on Cooperative Membership Retention, Performance, and Satisfaction: An Exploratory Study. The International Food and Agribusiness Management Review, 5, 41-59. [Google Scholar] [CrossRef
[32] Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002). Business-Unit-Level Relationship between Employee Satisfaction, Employee Engagement, and Business Outcomes: A Meta-Analysis. Journal of Applied Psychology, 87, 268-279. [Google Scholar] [CrossRef] [PubMed]
[33] Hauge, L. J., Skogstad, A., & Einarsen, S. (2009). Individual and Situational Predictors of Workplace Bullying: Why Do Perpetrators Engage in the Bullying of Others? Work & Stress, 23, 349-358. [Google Scholar] [CrossRef
[34] Hershcovis, M. S., Turner, N., Barling, J., Arnold, K. A., Dupré, K. E., Inness, M. et al. (2007). Predicting Workplace Aggression: A Meta-Analysis. Journal of Applied Psychology, 92, 228-238. [Google Scholar] [CrossRef] [PubMed]
[35] Hlengane, N. A., & Bayat, M. S. (2013). Poor Employee Work Performance: A Case Study Cambridge Police Station. Kuwait Chapter of Arabian Journal of Business and Management Review, 2, 80-92. [Google Scholar] [CrossRef
[36] Hogg, M. A., & Hardie, E. A. (1992). Prototypicality, Conformity and Depersonalized Attraction: A Self-Categorization Analysis of Group Cohesiveness. British Journal of Social Psychology, 31, 41-56. [Google Scholar] [CrossRef
[37] Hollinger, R., & Clark, J. (1982). Employee Deviance: A Response to the Perceived Quality of the Work Experience. Work and Occupations, 9, 97-114. [Google Scholar] [CrossRef
[38] Holt, N. L., & Sparkes, A. C. (2001). An Ethnographic Study of Cohesiveness in a College Soccer Team over a Season. The Sport Psychologist, 15, 237-259. [Google Scholar] [CrossRef
[39] Holt-Lunstad, J. (2018a). Why Social Relationships Are Important for Physical Health: A Systems Approach to Understanding and Modifying Risk and Protection. Annual Review of Psychology, 69, 437-458. [Google Scholar] [CrossRef] [PubMed]
[40] Holt-Lunstad, J. (2018b). Fostering Social Connection in the Workplace. American Journal of Health Promotion, 32, 1307-1312. [Google Scholar] [CrossRef] [PubMed]
[41] Holt‐Lunstad, J. (2024). Social Connection as a Critical Factor for Mental and Physical Health: Evidence, Trends, Challenges, and Future Implications. World Psychiatry, 23, 312-332. [Google Scholar] [CrossRef] [PubMed]
[42] Holt-Lunstad, J., Smith, T. B., Baker, M., Harris, T., & Stephenson, D. (2015). Loneliness and Social Isolation as Risk Factors for Mortality: A Meta-Analytic Review. Perspectives on Psychological Science, 10, 227-237. [Google Scholar] [CrossRef] [PubMed]
[43] Hu, L., & Bentler, P. M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1-55. [Google Scholar] [CrossRef
[44] Hussain, T., & Rehman, S. S. u. (2013). Do Human Resource Management Practices Inspire Employees’ Retention? Research Journal of Applied Sciences, Engineering and Technology, 6, 3625-3633. [Google Scholar] [CrossRef
[45] Iovoli, F., Rubel, J. A., Steinbrenner, T., & Lauterbach, R. (2025). Interpersonal Problems and Their Mental Health Correlates: A Meta‑Analytic Review. Journal of Clinical Psychology, 81, 1046-1056. [Google Scholar] [CrossRef] [PubMed]
[46] Istiningtyas, L., Purba, D. E., Poerwandari, E. K., Takwin, B., & Milla, M. N. (2025). Systematic Literature Review on the Theory of Social Embeddedness of Thriving at Work. SA Journal of Industrial Psychology, 51, a2229. [Google Scholar] [CrossRef
[47] James, J. B., McKechnie, S., & Swanberg, J. (2011). Predicting Employee Engagement in an Age-Diverse Retail Workforce. Journal of Organizational Behavior, 32, 173-196. [Google Scholar] [CrossRef
[48] Janjua, B. H., & Gulzar, A. (2014). The Impact of Human Resource Practices on Employee Commitment and Employee Retention in Telecom Sector of Pakistan: Exploring the Mediating Role of Employee Loyalty. IOSR Journal of Business and Management, 16, 76-81. [Google Scholar] [CrossRef
[49] Jarvenpaa, S. L., & Leidner, D. E. (1999). Communication and Trust in Global Virtual Teams. Organization Science, 10, 791-815. [Google Scholar] [CrossRef
[50] Jarvenpaa, S. L., Shaw, T. R., & Staples, D. S. (2004). Toward Contextualized Theories of Trust: The Role of Trust in Global Virtual Teams. Information Systems Research, 15, 250-267. [Google Scholar] [CrossRef
[51] Jones, D. A., & Martens, M. L. (2009). The Mediating Role of Overall Fairness and the Moderating Role of Trust Certainty in Justice-Criteria Relationships: The Formation and Use of Fairness Heuristics in the Workplace. Journal of Organizational Behavior, 30, 1025-1051. [Google Scholar] [CrossRef
[52] Judge, T. A., Thoresen, C. J., Bono, J. E., & Patton, G. K. (2001). The Job Satisfaction-Job Performance Relationship: A Qualitative and Quantitative Review. Psychological Bulletin, 127, 376-407. [Google Scholar] [CrossRef] [PubMed]
[53] Kim, M. K., Arsenault, C., Atuyambe, L. M., & Kruk, M. E. (2021). Predictors of Job Satisfaction and Intention to Stay in the Job among Health-Care Providers in Uganda and Zambia. International Journal for Quality in Health Care, 33, mzab128. [Google Scholar] [CrossRef] [PubMed]
[54] Kleine, A., Rudolph, C. W., & Zacher, H. (2019). Thriving at Work: A Meta-Analysis. Journal of Organizational Behavior, 40, 973-999. [Google Scholar] [CrossRef
[55] Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press.
[56] Koopmans, L., Bernaards, C., Hildebrandt, V., van Buuren, S., van der Beek, A. J., & de Vet, H. C. W. (2012). Development of an Individual Work Performance Questionnaire. International Journal of Productivity and Performance Management, 62, 6-28. [Google Scholar] [CrossRef
[57] Koyuncu, M., Burke, R. J., & Fiksenbaum, L. (2006). Work Engagement among Women Managers and Professionals in a Turkish Bank: Potential Antecedents and Consequences. Equal Opportunities International, 25, 299-310. [Google Scholar] [CrossRef
[58] Kundu, S. C., & Lata, K. (2017). Effects of Supportive Work Environment on Employee Retention: Mediating Role of Organizational Engagement. International Journal of Organizational Analysis, 25, 703-722. [Google Scholar] [CrossRef
[59] Lombardo, M. M., & McCauley, C. D. (1988). The Dynamics of Management Derailment (Tech. Rep. No. 34). Center for Creative Leadership.
[60] Lyu, X., Akkadechanunt, T., Soivong, P., & Juntasopeepun, P. (2022). Factors Influencing Intention to Stay of Male Nurses: A Descriptive Predictive Study. Nursing & Health Sciences, 24, 322-329. [Google Scholar] [CrossRef] [PubMed]
[61] Mach, M., Dolan, S., & Tzafrir, S. (2010). The Differential Effect of Team Members’ Trust on Team Performance: The Mediation Role of Team Cohesion. Journal of Occupational and Organizational Psychology, 83, 771-794. [Google Scholar] [CrossRef
[62] Malik, M. I., Sajjad, M., Hyder, S., Ahmad, M. S., Ahmed, J., & Hussain, S. (2013). Role Overload: A Cause of Diminishing Employee Retention and Productivity. Middle-East Journal of Scientific Research, 18, 1573-1577.
[63] Mangione, T. W., & Quinn, R. P. (1975). Job Satisfaction, Counterproductive Behavior, and Drug Use at Work. Journal of Applied Psychology, 60, 114-116. [Google Scholar] [CrossRef] [PubMed]
[64] Marcus, B., & Schuler, H. (2004). Antecedents of Counterproductive Behavior at Work: A General Perspective. Journal of Applied Psychology, 89, 647-660. [Google Scholar] [CrossRef] [PubMed]
[65] Martinko, M. J., Douglas, S. C., Harvey, P., & Joseph, C. (2005). Managing Organizational Aggression. In R. E. Kidwell, & C. L. Martin (Eds.), Managing Organizational Deviance (pp. 237-264). SAGE Publications, Inc. [Google Scholar] [CrossRef
[66] Maslow, A. H. (1943). A Theory of Human Motivation. Psychological Review, 50, 370-396. [Google Scholar] [CrossRef
[67] Mathieu, J. E., & Zajac, D. M. (1990). A Review and Meta-Analysis of the Antecedents, Correlates, and Consequences of Organizational Commitment. Psychological Bulletin, 108, 171-194. [Google Scholar] [CrossRef
[68] Matongolo, A., Kasekende, F., & Mafabi, S. (2018). Employer Branding and Talent Retention: Perceptions of Employees in Higher Education Institutions in Uganda. Industrial and Commercial Training, 50, 217-233. [Google Scholar] [CrossRef
[69] Mazzetti, G., Robledo, E., Vignoli, M., Topa, G., Guglielmi, D., & Schaufeli, W. B. (2023). Work Engagement: A Meta-Analysis Using the Job Demands-Resources Model. Psychological Reports, 126, 1069-1107. [Google Scholar] [CrossRef] [PubMed]
[70] McGilton, K. S., Tourangeau, A., Kavcic, C., & Wodchis, W. P. (2013). Determinants of Regulated Nurses’ Intention to Stay in Long-Term Care Homes. Journal of Nursing Management, 21, 771-781. [Google Scholar] [CrossRef] [PubMed]
[71] Mesmer-Magnus, J. R., & DeChurch, L. A. (2009). Information Sharing and Team Performance: A Meta-Analysis. Journal of Applied Psychology, 94, 535-546. [Google Scholar] [CrossRef] [PubMed]
[72] Mäkikangas, A., Bakker, A. B., & Schaufeli, W. B. (2017). Antecedents of Daily Team Job Crafting. European Journal of Work and Organizational Psychology, 26, 421-433. [Google Scholar] [CrossRef
[73] Nasir, F., Ashraf, M., & Riaz, M. (2019). The Role of Gender in Employee Retention: A Study of Private Hospitals in Karachi. International Journal of Experiential Learning & Case Studies, 4, 157-171. [Google Scholar] [CrossRef
[74] Nasir, S. Z., & Mahmood, N. (2016). Determinants of Employee Retention: An Evidence from Pakistan. International Journal of Academic Research in Business and Social Sciences, 6, 182-194. [Google Scholar] [CrossRef
[75] Nasyira, M. N., Othman, M., & Ghazali, H. (2014). Predictors of Intention to Stay for Employees of Casual Dining Restaurant in Klang Valley Area. International Food Research Journal, 21, 863-871.
[76] Ones, D. S., Viswesvaran, C., & Schmidt, F. L. (2003). Personality and Absenteeism: A Meta-Analysis of Integrity Tests. European Journal of Personality, 17, S19-S38. [Google Scholar] [CrossRef
[77] Penney, L. M., Spector, P. E., & Fox, S. (2003). Stress, Personality and Counterproductive Work Behaviour. In A. Sagie, S. Stashevsky, & M. Koslowsky (Eds)., Misbehaviour and Dysfunctional Attitudes in Organizations (pp. 194-210). Palgrave Macmillan UK. [Google Scholar] [CrossRef
[78] Peters, S. E., Sorensen, G., Katz, J. N., Gundersen, D. A., & Wagner, G. R. (2021). Thriving from Work: Conceptualization and Measurement. International Journal of Environmental Research and Public Health, 18, Article 7196. [Google Scholar] [CrossRef] [PubMed]
[79] Pflanz, S. E., & Ogle, A. D. (2006). Job Stress, Depression, Work Performance, and Perceptions of Supervisors in Military Personnel. Military Medicine, 171, 861-865. [Google Scholar] [CrossRef
[80] Pietromonaco, P. R., & Collins, N. L. (2017). Interpersonal Mechanisms Linking Close Relationships to Health. American Psychologist, 72, 531-542. [Google Scholar] [CrossRef] [PubMed]
[81] Podsakoff, P. M., MacKenzie, S. B., Lee, J., & Podsakoff, N. P. (2003). Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology, 88, 879-903. [Google Scholar] [CrossRef] [PubMed]
[82] Porath, C., Spreitzer, G., Gibson, C., & Garnett, F. G. (2012). Thriving at Work: Toward Its Measurement, Construct Validation, and Theoretical Refinement. Journal of Organizational Behavior, 33, 250-275. [Google Scholar] [CrossRef
[83] Posit Team (2025). RStudio: Integrated Development Environment for R. Posit Software.
[84] Ramos-Villagrasa, P. J., Barrada, J. R., Fernández-del-Río, E., & Koopmans, L. (2019). Assessing Job Performance Using Brief Self-Report Scales: The Case of the Individual Work Performance Questionnaire. Revista de Psicología del Trabajo y de las Organizaciones, 35, 195-205. [Google Scholar] [CrossRef
[85] Rasdi, R. M., Kusnin, N., & Chen, Y. S. (2018). Predictors and Intervening Variables of Talent Retention. International Journal of Academic Research in Business and Social Sciences, 8, 210-220. [Google Scholar] [CrossRef
[86] Rovetta, A., Bortolotti, A., & Palumbo, R. (2025). Integrating Team and Organizational Identity: A Systematic Literature Analysis. Frontiers in Organizational Psychology, 2, Article 1439269. [Google Scholar] [CrossRef
[87] Ryan, R. M., & Deci, E. L. (2000). Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. American Psychologist, 55, 68-78. [Google Scholar] [CrossRef
[88] Salas, E., Shuffler, M. L., Thayer, A. L., Bedwell, W. L., & Lazzara, E. H. (2015). Understanding and Improving Teamwork in Organizations: A Scientifically Based Practical Guide. Human Resource Management, 54, 599-622. [Google Scholar] [CrossRef
[89] Saleem, M., & Affandi, H. (2014). HR Practices and Employees Retention, an Empirical Analysis of Pharmaceutical Sector of Pakistan. IOSR Journal of Business and Management, 16, 111-116. [Google Scholar] [CrossRef
[90] Sarmad, M., Ajmal, M. M., Shamim, M., Saleh, M., & Malik, A. (2016). Motivation and Compensation as Predictors of Employees’ Retention: Evidence from Public Sector Oil and Gas Selling Organizations. Journal of Behavioural Sciences, 26, 174-188.
[91] Schaufeli, W. B., Salanova, M., González-romá, V., & Bakker, A. B. (2002). The Measurement of Engagement and Burnout: A Two Sample Confirmatory Factor Analytic Approach. Journal of Happiness Studies, 3, 71-92. [Google Scholar] [CrossRef
[92] Schulte, M., Cohen, N. A., & Klein, K. J. (2012). The Coevolution of Network Ties and Perceptions of Team Psychological Safety. Organization Science, 23, 564-581. [Google Scholar] [CrossRef
[93] Schulze, S., & Naidu, N. (2014). Exploring the Dependency of Type of School and Age with Adolescent Connectedness. Mediterranean Journal of Social Sciences, 5, 323-332. [Google Scholar] [CrossRef
[94] Scott, K. L., Ingram, A., Zagenczyk, T. J., & Shoss, M. K. (2015). Work-Family Conflict and Social Undermining Behaviour: An Examination of po Fit and Gender Differences. Journal of Occupational and Organizational Psychology, 88, 203-218. [Google Scholar] [CrossRef
[95] Shahid, M. N., Latif, K., Sohail, N., & Ashraf, M. A. (2011). Work Stress and Employee Performance in Banking Sector Evidence from District Faisalabad, Pakistan. Asian Journal of Business and Management Sciences, 1, 38-47.
[96] Sijtsma, K. (2009). On the Use, the Misuse, and the Very Limited Usefulness of Cronbach’s Alpha. Psychometrika, 74, 107-120. [Google Scholar] [CrossRef] [PubMed]
[97] Spector, P. E., & Fox, S. (2002). An Emotion-Centered Model of Voluntary Work Behavior: Some Parallels between Counterproductive Work Behavior and Organizational Citizenship Behavior. Human Resource Management Review, 12, 269-292. [Google Scholar] [CrossRef
[98] Stashevsky, S., & Koslowsky, M. (2006). Leadership Team Cohesiveness and Team Performance. International Journal of Manpower, 27, 63-74. [Google Scholar] [CrossRef
[99] Steiner, S., Cropley, M., Simonds, L., & Heron, R. (2020). Reasons for Staying with Your Employer: Identifying the Key Organizational Predictors of Employee Retention within a Global Energy Business. Journal of Occupational & Environmental Medicine, 62, 289-295. [Google Scholar] [CrossRef] [PubMed]
[100] Sullivan, P. J., & Short, S. (2011). Further Operationalization of Intra-Team Communication in Sports: An Updated Version of the Scale of Effective Communication in Team Sports (SECTS-2). Journal of Applied Social Psychology, 41, 471-487. [Google Scholar] [CrossRef
[101] Sullivan, P., & Feltz, D. L. (2003). The Preliminary Development of the Scale for Effective Communication in Team Sports (SECTS). Journal of Applied Social Psychology, 33, 1693-1715. [Google Scholar] [CrossRef
[102] Tett, R. P., & Meyer, J. P. (1993). Job Satisfaction, Organizational Commitment, Turnover Intention, and Turnover: Path Analyses Based on Meta‑Analytic Findings. Personnel Psychology, 46, 259-293. [Google Scholar] [CrossRef
[103] Thau, S., Crossley, C., Bennett, R. J., & Sczesny, S. (2007). The Relationship between Trust, Attachment, and Antisocial Work Behaviors. Human Relations, 60, 1155-1179. [Google Scholar] [CrossRef
[104] Thomas (2025). Organisational Connection Measure (OCM): Technical Manual. Thomas.
[105] van Bel, D. T., Smolders, K. C. H. J., Ijsselsteijn, W. A., & De Kort, Y. A. W. (2009). Social Connectedness: Concept and Measurement. In V. Callaghan, A. Kameas, A. Reyes, D. Royo, & M. Weber (Eds.), Ambient Intelligence and Smart Environments (pp. 67-74). IOS Press. [Google Scholar] [CrossRef
[106] van den Heuvel, S. G., Geuskens, G. A., Hooftman, W. E., Koppes, L. L. J., & van den Bossche, S. N. J. (2010). Productivity Loss at Work; Health-Related and Work-Related Factors. Journal of Occupational Rehabilitation, 20, 331-339. [Google Scholar] [CrossRef] [PubMed]
[107] Van Velsor, E., & Leslie, J. B. (1995). Why Executives Derail: Perspectives across Time and Cultures. Academy of Management Perspectives, 9, 62-72. [Google Scholar] [CrossRef
[108] Vardi, Y., & Weitz, E. (2003). Personal and Positional Antecedents of Organizational Misbehaviour. In A. Sagie, S. Stashevsky, & M. Koslowsky (Eds.), Misbehaviour and Dysfunctional Attitudes in Organizations (pp. 173-193). Palgrave Macmillan UK. [Google Scholar] [CrossRef
[109] Wang, M., Chen, W., Lin, Y., & Hsu, B. (2010). Structural Characteristics, Process, and Effectiveness of Cross-Functional Teams in Hospitals: Testing the I-P-O Model. The Journal of High Technology Management Research, 21, 14-22. [Google Scholar] [CrossRef
[110] Warraich, N. F., Ameen, K., & Malik, A. (2019). Recruitment and Retention of Information Professionals: Library Leaders’ Perspectives in Pakistan. Global Knowledge, Memory and Communication, 68, 568-580. [Google Scholar] [CrossRef
[111] West, B. J., Patera, J. L., & Carsten, M. K. (2009). Team Level Positivity: Investigating Positive Psychological Capacities and Team Level Outcomes. Journal of Organizational Behavior, 30, 249-267. [Google Scholar] [CrossRef
[112] WorkBuzz (2022). The State of Employee Engagement 2022. WorkBuzz.
https://workbuzz.com/resources/research-ebooks/state-of-employee-engagement/2022/

Copyright © 2026 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.