Unit VI RM

profilebreal
DEIC.pdf

Navigating Job Satisfaction: Unveiling the Nexus of Diversity, Equity, Inclusion, Accessibility (DEIA), Perceived Supervisory Support, and Intrinsic Work Experience. Published in: Public Personnel Management, Mar2025,Business Source Ultimate

This study aims to unravel the intricate interplay among diversity, equity, inclusion, and

accessibility (DEIA), along with perceived supervisory support (PSS) and intrinsic work

experience (IWE), as pivotal determinants influencing the job satisfaction (JSC) of employees

with disabilities. The research sample used comprises civil servants employed in government

organizations in Indonesia. Utilizing covariance-based structural equation modeling (CB-

SEM), the analysis encompasses confirmatory factor analysis (CFA) and the evaluation of a

structural model, coupled with hypothesis testing, to confirm the findings. The study's

findings affirm not only the direct influence of DEIA components and IWE on the JSC of

employees with disabilities, but also highlight the indirect mediation of DEIA components

and JSC through PSS. This study stands as a pioneering effort in exploring the interplay

between DEIA, PSS, and IWE with regard to the JSC of employees with disabilities.

Keywords: diversity; equity; inclusion; and accessibility (DEIA); perceived supervisory support;

intrinsic work experience; job satisfaction; government institutions

Introduction

In the evolving landscape of the contemporary workplace, the pursuit of job satisfaction (JSC)

has taken center stage as a driving force behind employee engagement, retention, and

overall organizational prosperity ([ 4 ]; [58]; [64]). As organizations strive to create

environments that foster a sense of belonging and purpose, the intricate interplay of various

factors that influence JSC is being closely examined ([ 9 ]; [35]; [50]). This study embarks on a

journey of exploration, delving into the dynamic relationships between diversity, equity,

inclusion, and accessibility (DEIA), perceived supervisory support (PSS), and intrinsic work

experience (IWE), to uncover how these factors collectively shape the vital aspect of JSC for

employees with disabilities.

In the realm of the modern workplace, the pursuit of a nurturing work environment

characterized by DEIA has recently gained substantial momentum ([39]; [49]; [57]). In

Indonesia, specifically, the legislation outlined in Law No. 8/2016 concerning individuals with

disabilities mandates that both government institutions and private organizations must

employ individuals with disabilities, constituting at least 2% of their total workforce. The

acknowledgment of diverse backgrounds, perspectives, and abilities has brought about a

paradigm shift in organizational dynamics ([28]). Equity and inclusion have emerged as

pivotal factors for ensuring fair treatment and cultivating a sense of worth among all

employees, including those with disabilities, thereby fostering a shared sense of purpose ([ 5

]; [49]; [55]). The concept of accessibility, which aligns seamlessly with the DEIA principles,

advocates for environments, which are designed to accommodate the unique needs of

employees, ensuring their full engagement and contribution ([16]; [54]; [60]). However, amid

the backdrop of such DEIA endeavors, a potential shadow emerges—the specter of stigma.

Stigma theory posits that individuals with unique attributes, such as those associated with

disabilities or minority status, are likely to face societal stereotypes, discrimination, and

prejudice, which can detrimentally impact their self-esteem and well-being ([22]; [46]; [47]).

On the other hand, when the DEIA principles are implemented effectively, employees are

more likely to feel a sense of belonging, empowerment, and fulfillment in their roles. In turn,

this can enhance employees' IWE by fostering a positive culture where individuals feel valued

for their unique perspectives and contributions, leading to higher levels of motivation,

engagement, and JSC ([28]; [40]; [60]). Moreover, DEIA efforts can also create opportunities

for skill development, career advancement, and professional growth, further enriching IWE

for employees ([38]; [49]; [64]).

In addition, PSS is a vital aspect of this intricate nexus. PSS reflects the degree to which

employees, including those with disabilities, believe that their supervisors genuinely prioritize

their well-being, professional growth, and overall career development ([ 9 ]; [38]; [43]). Such

support can significantly contribute to mitigating barriers and fostering an inclusive

environment where employees with disabilities can thrive and contribute effectively to

organizational goals and success.

To navigate these unique interconnections, the emergence of stigma theory introduces a

multifaceted and largely unexplored territory. Individuals who face stigma due to their

identities or abilities (i.e., employees with disabilities) may encounter barriers to inclusion

and equitable treatment ([ 2 ]; [44]; [47]). This stigma can harm their IWE, diminish the impact

of PSS, and subsequently influence overall JSC. With organizations striving to promote DEIA

and foster supportive environments, recognizing and addressing the potential ramifications

of stigma takes on a position of paramount significance ([63]).

The aim of this study is to untangle the complex interconnections among DEIA, PSS, and IWE

as pivotal factors that influence the JSC of employees with disabilities. By scrutinizing

empirical evidence and real-world insights, this article seeks to offer a comprehensive

understanding of how these factors collectively shape these employees' overall work

experience, with a specific focus on employees with disabilities within Indonesian

government institutions. The contention is that disabled employees within government

institutions possess unique characteristics due to their connection to public service and their

position within a large workforce. As this investigation unfolds, it strives to shed light on a

trajectory that can lead to the establishment of work environments where JSC thrives,

facilitated by the seamless amalgamation of DEIA and the core principles of PSS, which

include supervisors demonstrating empathy, maintaining clear communication, offering

guidance and feedback, and advocating for employee well-being and growth, alongside

IWEs. Considering this context, the present study endeavors to address the following

research questions (RQs):

RQ1: What is the extent of the direct impact of the DEIA components and IWE on the JSC

of employees with disabilities?

RQ2: To what extent does the influence of the DEIA components on the JSC of

employees with disabilities occur indirectly through PSS?

This study contributes to the scientific discourse in three notable ways. First, it illuminates the

combined influence of DEIA, PSS, and IWE on the holistic JSC of employees with disabilities.

By comprehensively investigating the relationships between these variables in conjunction

with each other, this research advances the present understanding of the intricate interplay

of factors shaping diversity research ([ 6 ]; [50]; [57]). Notably, the context of employees with

disabilities remains underexplored in the existing literature, making this study particularly

significant in filling this gap. Second, this study provides evidence-based insights that can

empower government institutions to enhance the JSC of employees with disabilities. By

grasping the interplay between DEIA, PSS, IWE, and stigma theory, government institutions

can devise targeted strategies aimed at cultivating inclusive and supportive environments,

ultimately fostering elevated levels of JSC. These empirical discoveries hold significance due

to the prevailing focus of prior research in this field on qualitative studies or systematic

literature reviews ([ 6 ]; [18]; [57]). Finally, a distinctive contribution of this research is the

integration of stigma theory within the context of DEIA, PSS, IWE, and JSC. This study seeks to

uncover how stigma theory shapes the dynamics between these variables, potentially

molding individuals' perceptions and experiences within diverse and inclusive workplace

settings.

The remainder of this article begins with the theoretical background and hypotheses,

followed by the research methods used. Following these sections, the results and empirical

findings are presented, while theoretical and practical implications are provided in the final

section.

Theoretical Background and Hypotheses

Stigma Theory and the Inclusion of Employees With Disabilities in the Workplace

Stigma theory plays a pivotal role in understanding the intricate relationship between DEIA,

PSS, IWE, and employee JSC, particularly in the context of individuals with disabilities. This

theory, rooted in social psychology, focuses on the negative attitudes and beliefs that society

holds toward individuals who possess unique attributes or characteristics that deviate from

societal norms. These attributes can include disabilities, minority status, or other

distinguishing features ([63]).

Stigma theory provides a lens through which this study can examine how societal

stereotypes, prejudices, and discrimination can influence the experiences of employees with

disabilities ([17]). Stigma theory suggests that individuals who face stigma due to their

disabilities might encounter barriers to inclusion and equitable treatment. This can lead to

feelings of marginalization, reduced self-esteem, and psychological distress ([ 1 ]; [36]; [50]).

When applied to the DEIA framework, stigma theory implies that despite efforts to promote

diversity, equity, and inclusion in the workplace, employees with disabilities may still

encounter stereotypes and discriminatory attitudes ([22]; [51]). This can hinder their sense of

belonging, thwart their efforts to engage fully in their work, and potentially impact their IWE

and overall JSC. Negative perceptions and attitudes from colleagues and supervisors, as well

as self-stigmatization, can undermine the positive effects of DEIA initiatives on the well-being

of employees with disabilities.

Moreover, stigma theory also intersects with PSS. Employees who perceive their supervisors

as unsupportive or insensitive to their unique needs might experience heightened feelings of

stigma and exclusion ([54]). On the other hand, supportive supervisors who actively work to

mitigate stigma and foster an inclusive environment can alleviate the negative effects of

stigma on employees' JSC. Supervisors who understand and address the challenges faced by

employees with disabilities can contribute to their sense of belonging and psychological well-

being, thereby positively influencing their JSC ([64]).

In essence, stigma theory provides a comprehensive framework for understanding how the

stigma associated with disabilities can impact the interplay between DEIA, PSS, IWE, and

employee JSC. By recognizing and addressing the potential consequences of stigma within

the context of workplace diversity and inclusion efforts, organizations can take proactive

steps to create an environment that minimizes the negative effects of stigma, fosters a sense

of belonging, and ultimately enhances JSC for employees with disabilities.

The Impact of DEIA Components on the JSC of Disabled Employees

The relationship between DEIA and the JSC of disabled employees is intricately linked, and

can be understood through the lens of stigma theory, as well as through previous research.

Stigma theory posits that individuals who possess unique attributes, such as disabilities,

might encounter negative societal attitudes, stereotypes, and discriminatory behaviors.

These experiences can lead to feelings of marginalization, reduced self-esteem, and

psychological distress ([17]; [63]). In the workplace context, this can translate to challenges in

achieving a sense of belonging, equitable treatment, and overall JSC.

Previous studies have shown that despite efforts to create inclusive workplaces, disabled

employees may face both external and internal stigma ([ 2 ]; [39]). External stigma refers to

discrimination and negative perceptions from colleagues, supervisors, or the broader

organizational culture. Internal stigma, also known as self-stigma, occurs when individuals

internalize societal stereotypes and view themselves negatively due to their disabilities.

Empirical evidence has indicated that disabled employees who perceive higher levels of

external stigma are more likely to experience reduced JSC ([ 7 ]; [35]; [42]). Discrimination and

exclusionary behaviors can lead to feelings of isolation and dissatisfaction with the work

environment. In addition, disabled employees who internalize negative stereotypes about

their abilities may experience diminished self-worth, affecting their overall well-being and JSC

([58]).

Conversely, research has demonstrated that when organizations effectively address and

mitigate stigma, disabled employees experience higher levels of JSC ([ 9 ]; [64]). Inclusive

practices, supportive policies, and awareness campaigns aimed at reducing stigma can create

a more positive work environment ([24]). Organizations that prioritize diversity by promoting

equitable treatment, fostering inclusive practices, and ensuring accessibility have been found

to have a positive impact on employees' overall JSC ([61]). This is particularly true for disabled

employees, who often face unique challenges in the workplace. Based on these arguments

and prior research, the following concurrent hypotheses can be formulated:

_I__B_Hypothesis 1a (H1a): Perception of diversity has a direct effect on enhanced JSC

among employees with disabilities._i_

_I__B_Hypothesis 1b (H1b): Perception of equity has a direct effect on enhanced JSC

among employees with disabilities._i_

_I__B_Hypothesis 1c (H1c): Perception of inclusion has a direct effect on enhanced JSC

among employees with disabilities._i_

_I__B_Hypothesis 1d (H1d): Perception of accessibility has a direct effect on enhanced

JSC among employees with disabilities._i_

The Influence of Intrinsic Work Experience on the JSC of Disabled Employees

Previous research suggests that IWE is closely linked to the JSC of disabled employees ([ 9 ];

[38]). IWE refers to the fulfillment, purpose, and satisfaction that employees derive from their

roles. Studies have consistently shown that disabled employees who perceive a strong

positive IWE generally exhibit higher levels of JSC ([ 4 ]; [59]). When employees find meaning

and purpose in their work, they are more likely to be engaged, committed, and satisfied with

their jobs ([ 5 ]).

Research has also indicated that IWE can serve as a buffer against the negative effects of

stigma ([63]). Disabled employees who possess a strong IWE may exhibit greater resilience in

the face of stigma, as the internal satisfaction derived from their job enables them to

maintain a focus on the positive aspects of their work and effectively navigate challenges

associated with their disabilities. Moreover, IWE has been shown to empower disabled

employees to actively pursue opportunities for personal and professional development,

thereby contributing to their overall JSC ([ 4 ]; [38]; [64]). Based on these insights and prior

research, the next hypothesis can be formulated:

Hypothesis 2 (H2): Perception of IWE has a positive and direct effect on JSC among

employees with disabilities.

Perceived Supervisory Support as a Mediating Variable

DEIA initiatives can be carefully crafted to establish a workplace ambiance where every

employee, irrespective of their background or abilities, experiences a sense of worth,

inclusivity, and equal opportunities ([59]). These measures collectively contribute to a

nurturing work environment that upholds the overall welfare of employees. According to

stigma theory, individuals with disabilities often face societal prejudices and discriminatory

attitudes that can negatively impact their self-esteem and JSC. However, when organizations

implement DEIA initiatives, they actively challenge these stigmatizing beliefs and create an

environment where employees feel valued, respected, and empowered to succeed. Moreover,

when employees perceive their work to be aligned with their personal values, offering

avenues for personal growth and imbuing a sense of purpose, their likelihood of expressing

elevated levels of JSC increases ([ 4 ]; [38]; [61]).

In this context, the significance of PSS takes center stage. Employees with disabilities who

identify their supervisors as active advocates for DEIA initiatives and facilitators of requisite

support and accommodations are more likely to experience heightened JSC ([ 9 ]; [30]; [32]).

Supportive supervisors contribute to fostering an atmosphere characterized by trust and

comprehension, thereby facilitating effective job performance and circumventing

unnecessary impediments ([32]). Moreover, the role of PSS plays a critical part in shaping the

aforementioned interplay. Employees with disabilities who perceive their supervisors as

sources of support, accommodations, and genuine care for their well-being tend to

encounter a positive IWE ([54]). Supportive supervisors create an environment conducive to

employees' growth, enabling them to navigate challenges and find significance in their roles

([ 5 ]; [30]).

In addition, supervisors who demonstrate support and advocacy for DEIA initiatives can

create a positive environment where employees feel psychologically safe, respected, and

empowered to bring their authentic selves to their jobs. This type of positive relationship with

supervisors can enhance IWE by providing employees with the necessary guidance,

resources, and feedback to succeed in their roles. Moreover, supportive supervisors can

create opportunities for meaningful work assignments, recognition of accomplishments, and

constructive feedback, which are essential components of IWE and JSC ([ 9 ]; [32]; [37]; [42]).

Drawing on these insights and prior research, the following concurrent hypotheses can be

formulated:

_I__B_Hypothesis 3a (H3a): Perception of diversity indirectly influences JSC among

employees with disabilities, through the avenue of PSS._i_

_I__B_Hypothesis 3b (H3b): Perception of equity indirectly influences JSC among

employees with disabilities, through the avenue of PSS._i_

_I__B_Hypothesis 3c (H3c): Perception of inclusion indirectly influences JSC among

employees with disabilities, through the avenue of PSS._i_

_I__B_Hypothesis 3d (H3d): Perception of accessibility indirectly influences JSC among

employees with disabilities, through the avenue of PSS._i_

_I__B_Hypothesis 4 (H4): PSS has a positive and indirect effect on JSC among employees

with disabilities, facilitated by IWE._i_

Figure 1 depicts the theoretical framework of this study.

Graph: Figure 1. Theoretical framework and path relationships between latent variables.

Research Methods

Participants and Procedures

This research employs a sample of civil servants working in Indonesian government

institutions. Specifically, this study focuses on employees with disabilities, as they have

relevant experience with variables, such as DEIA (see Figure 1). For data collection, the Prolific

company was used (https:// www.prolific.co/), as it provides a reliable platform for this type of

study ([33]). In comparison to Amazon Mechanical Turk (MTurk), which primarily consists of

workers from the United States ([41]), Prolific better suits the needs of this study, given the

location of the sample in Indonesia. The sampling framework used comprises over 3.5 million

employees, encompassing civil servants and contracted government employees. Before

conducting the survey, non-probability sampling techniques were utilized to select target

respondents based on the criteria mentioned earlier. The total sample pool comprises of

1,081 employees with disabilities.

Prolific is an online survey platform that facilitates the collection of high-quality data and

allows researchers to reach participants across the world. Utilizing this platform enables

efficient and reliable data collection on a large scale. For this study, the survey was conducted

between May and June 2023, and the employees with disabilities were invited via

personalized email messages, each containing a unique survey link and instructions.

Participants were given approximately 1 month to complete the survey, with additional time

allowed if necessary. To enhance response rates, reminder emails were sent weekly to those

who had not responded, with the final reminder sent on the day before the data collection

period ended, indicating that the survey would close the next day.

At the conclusion of the research deadline and after closing the survey, a total of 418

completed questionnaires were received, with 16 of these subsequently excluded for being

incomplete or containing missing values. This yielded a final response rate of 37.2%. Several

studies, such as [26], have indicated that the response rate achieved can be considered high

and aligns with the response rates commonly found in organizational research. Thus, this

response rate meets the rule of thumb regarding the minimum level required for survey-

based research, as suggested by [11].

The characteristics of the respondents, describing the details of the sample used in this study

([10]), can be summarized as follows. Based on gender, the majority of respondents were

male, accounting for 68.7% of the sample, while women made up 31.3%. Regarding work

experience, the largest segment of participants (33.8%) reported having worked for 6 to 10

years, followed by those with 2 to 5 years of experience (30.9%), and individuals with less

than 2 years of experience (23.4%). Conversely, respondents with over 10 years of experience

represented only approximately 11.9% of the sample. Furthermore, all respondents identified

themselves as individuals with disabilities (100%). Finally, in terms of age distribution, the

most common response fell within the range of 35 to 45 years, comprising 40.8% of

respondents.

Measures

The measurement items used in this study were derived from the questionnaire utilized in

the 2022 Federal Employee Viewpoint Survey (FEVS). Items from the FEVS were chosen due to

their prior use in surveying government agency employees with disabilities ([12]).

Approximately, 25 relevant questions were identified as suitable for measuring the latent

variables in the proposed model. To ensure that these items accurately captured the essence

of each construct, principal component analysis (PCA) was conducted through factor analysis.

The validity and reliability of each variable were tested to ensure the formation of a single

factor.

Using IBM SPSS 28.0 software, a Kaiser–Meyer–Olkin Measure of Sampling Adequacy (KMO-

MSA) value greater than 0.50 was obtained for each latent variable, with one component

extracted. In addition, the factor loading values for each item exceeded 0.748, and

Cronbach's alpha for each construct exceeded 0.806, further supporting the formation of a

single factor ([21]; [48]). Table 1A presents the full list of the 25 items selected for this study.

To measure DEIA, IWE, PSS, and JSC, multiple items were employed with responses recorded

on a 5-point Likert-type scale, ranging from 1 = "strongly disagree" to 5 = "strongly agree."

Data Analysis

Covariance-based structural equation modeling (CB-SEM) was applied to assess the

comprehensive model, incorporating confirmatory factor analysis (CFA) and structural model

evaluation, along with hypothesis testing, to validate the findings. CB-SEM is recognized as

well-suited for testing latent factors with reflective indicators, rendering it particularly useful

for estimating common factor models based on theory ([31]). Scholars such as [34] and [62]

emphasize that CB-SEM is a robust and reliable approach, providing unbiased parameter

estimates. Some of the acknowledged advantages of this method include its ability to

produce goodness-of-fit indices (GOFI), accounting for measurement error in model

estimation, and testing causal relationships between latent variables. In addition, the

availability of sophisticated software makes CB-SEM an advantageous choice for researchers

([20]; [27]; [34]).

Results

In this study, the CB-SEM estimation was conducted using the SmartPLS 4 software. The CB-

SEM algorithm in SmartPLS is specifically designed to handle non-normal data conditions, as

the model estimation utilizes bootstrapping instead of the maximum-likelihood (ML)

estimator to calculate standard deviation ( SD ), which was considered relevant for this study.

Given that a Likert-type scale, which falls under the ordinal category of data, was utilized, it

was challenging to meet the assumption of normality. Hence, several preliminary tests were

conducted, and are detailed in Appendix. The outcomes of these preliminary tests affirmed

the appropriateness of the approach taken.

The descriptive statistics were analyzed for each variable. The results indicate that the mean

values for all latent variables are below 5, and the SD values do not exceed 2. According to

[10], these values do not surpass either the maximum or minimum threshold. In addition, the

variance inflation factor (VIF) for each predictor was calculated, and all VIF values obtained

were less than 3.3 (refer to Table 2A). These findings suggest that the model is free from

multicollinearity issues ([21]).

Assessment of Method Biases

Two potential method biases in online surveys have been extensively examined due to their

potential to influence the results of this study; specifically, non-response bias ([56]) and

common method variance (CMV) ([52]). Following the outcomes of the analysis delineated in

Appendix, it has been deduced that these two method biases do not pose a threat to the

validity of the findings herein.

Assessment of Validity and Reliability

The validity and reliability of the measurement items were evaluated through CFA and the

CFA model fit was also assessed. Based on the results presented in Appendix, it was

determined that all measurement items in the model were valid (refer to Tables 1A and 2A)

and met the criteria for construct reliability. Moreover, the measurement model exhibited a

satisfactory level of fit.

Assessment of the Full Model

The full model was assessed by running a bootstrapping procedure within the context of

non-normal data. Employing 10,000 resamples for robust estimates ([34]), key metrics

examined in this stage encompass r -square ( R 2 ), effect size ( f 2 ), p values, and t -statistics.

In terms of model performance, the proposed model yields R 2 values of 0.554, 0.229, and

0.587 for PSS, IWE, and JSC, respectively (as illustrated in Figure 2). According to [ 8 ], these R 2

values fall within the accepted range for social science research. To supplement the insights

gained from the significance tests of hypotheses, f 2 values were computed; these varied

from 0.030 to 0.287, all surpassing 0.02. These values confirm the extent to which the null

hypothesis is false and provide support for alternative hypothesis testing ([29]).

Graph: Figure 2. Findings derived from Structural Equation Modeling.

Testing of Hypotheses

The methodology recommended by SEM experts to perform hypothesis testing was followed

to test the hypotheses of this study. This involved examining key parameters, such as the

beta coefficient (β), SD, p -value, and t -statistics ( t ) at a significance level of 5% (one-tailed

test). This approach was based on the guidelines of [27] and [34]. For this study, standardized

estimates were employed to simultaneously test the hypotheses of the full model. The results

of this model estimation consistently upheld the proposed hypotheses. These outcomes are

visually presented in Table 1 and Figure 2. Notably, this study offers empirical substantiation

for the direct relationships between DEIA and IWE concerning the JSC of employees with

disabilities. The beta (β) values were 0.146 ( SD = 0.072) for diversity, 0.293 ( SD = 0.124) for

equity, 0.424 ( SD = 0.098) for inclusion, 0.542 ( SD = 0.072) for accessibility, and 0.628 ( SD =

0.084) for IWE, all with p values <.05, respectively. Drawing on these results, support can be

confidently attested for hypothesis 1a (H1a), hypothesis 1b (H1b), hypothesis 1c (H1c),

hypothesis 1d (H1d), and hypothesis 2 (H2).

Table 1. Results of Hypothesis Confirmation.

Graph

Connection between latent variables Coef. (β)

SD p- value

t- statistics

Finding

Direct effect

Diversity (DV) → job satisfaction (JSC) 0.146 0.072 .022* 2.025* H1a supported

Equity (EQ) → job satisfaction (JSC) 0.293 0.124 .009** 2.368** H1b supported

Inclusion (IS) → job satisfaction (JSC) 0.424 0.098 .000*** 4.322*** H1c supported

Accessibility (AC) → job satisfaction (JSC) 0.542 0.072 .000*** 7.520*** H1d supported

Intrinsic work experience (IWE) → job satisfaction (JSC) 0.628 0.084 .000*** 7.437*** H2 supported

Indirect effect

Diversity (DV) → perceived supervisory support (PSS) → job satisfaction (JSC)

0.112 0.052 .016* 2.144* H3a supported

Equity (EQ) → perceived supervisory support (PSS) → job satisfaction (JSC)

0.143 0.049 .002** 2.935** H3b supported

Inclusion (IS) → perceived supervisory support (PSS) → job satisfaction (JSC)

0.184 0.053 .000*** 3.481*** H3c supported

Accessibility (AC) → perceived supervisory support (PSS) → job satisfaction (JSC)

0.179 0.080 .013* 2.240* H3d supported

Perceived supervisory support → intrinsic work experience (IWE) (PSS) → job satisfaction (JSC)

0.489 0.069 .000*** 7.127*** H4 supported

1 Note(s) : Coef. (β) = standardized beta coefficient; SD = standard deviation; *│ t │ ≥ 1.65 at p

<.05 level; **│ t │ ≥ 2.33 at p <.01 level; ***│ t │ ≥ 3.09 at p <.001 level.

In the final phase of hypothesis testing, the potential mediating role played by PSS was

investigated. This study provides concrete empirical support for the indirect effect paths

connecting DEIA with JSC among employees with disabilities. These connections occur

through the influence of PSS. Notably, these indirect paths received robust confirmation from

the analysis conducted. Specifically, for diversity and equity through PSS, the beta (β) values

obtained were 0.112 ( SD = 0.052) and 0.143 ( SD = 0.049), respectively, while for inclusion and

accessibility through PSS, they were 0.184 ( SE = 0.053) and 0.179 ( SE = 0.080), respectively.

Furthermore, these relationships exhibit significance levels with p values <.05. As a result, it

can be asserted that the findings provide substantial support for hypothesis 3a (H3a),

hypothesis 3b (H3b), hypothesis 3c (H3c), and hypothesis 3d (H3d). Ultimately, the indirect

effect between PSS, IWE, and JSC were examined (beta = 0.489, SD = 0.069, p value =.000).

Based on these results, it can also be inferred that hypothesis 4 (H4) is substantiated.

Robustness Checks

Particular attention was paid to addressing concerns related to endogeneity bias within the

model. To tackle this bias, a series of straightforward regression models were employed.

Through the utilization of the Gaussian copulas approach, via the Stata software, the

significance of p -values was scrutinized. The outcomes of these tests, as indicated by [13],

revealed that no statistically significant p -values emerged at the 5% significance level. This

leads to the assertion that endogeneity bias is absent and does not pose a threat to the

validity of these findings.

Discussion and Conclusions

Government institutions play a vital role in serving diverse populations. By researching the

interaction between DEIA initiatives, PSS, IWE, and JSC among employees with disabilities, as

depicted in Figure 1, these institutions can ensure that their internal practices align

harmoniously with their external goals. The JSC of employees has a direct influence over their

dedication to providing high-quality services. When employees with disabilities encounter a

favorable work environment fostered by DEIA initiatives and bolstered by supportive

supervisors, their engagement and satisfaction in their roles are enhanced ([28]; [61]). This

amplifies service delivery efficacy and fortifies the efficiency of government operations.

Aligned with the tenets of stigma theory, the main findings of this study can be outlined as

follows. Based on hypothesis testing, this investigation has yielded four key insights. To begin

with, a direct and favorable relationship between DEIA efforts and the JSC of employees with

disabilities in government institutions has been uncovered. This indicates that the

implementation of DEIA initiatives within Indonesian government institutions is attuned to

the needs of employees with disabilities, ultimately impacting their JSC. Specifically, these

results indicate that practices promoting inclusion and the provision of accessibility are

particularly influential in shaping the satisfaction levels of individuals with disabilities. In

addition, the examination conducted here uncovered varying impacts of each DEIA

component, underscoring the significance of complementarity among them ([24]). These

findings harmonize with prior research ([ 4 ]; [ 9 ]; [61]; [64]) suggesting that initiatives related

to DEIA can enhance the engagement and satisfaction of individuals with disabilities in the

workplace.

Furthermore, this study has revealed a direct and constructive relationship between IWE and

JSC among employees with disabilities within Indonesian government agencies. This implies

that Indonesian government agencies have accorded significance to nurturing IWE for

individuals with disabilities, culminating in a positive work environment for disabled

employees and leading to heightened levels of JSC. This discovery can be elucidated by the

fact that government institutions are legally mandated to address the needs and roles of

employees with disabilities, thereby enriching their IWEs, which subsequently influence their

JSC. These findings echo those of previous studies ([ 5 ]; [38]).

Moreover, a positive and indirect relationship between DEIA initiatives and the JSC of

employees with disabilities in Indonesian government agencies has been discerned,

mediated by PSS. This highlights the role of PSS in aiding employees with disabilities to

navigate challenges within the framework of Indonesian government agencies. PSS indirectly

shapes their sense of belonging and identity within the organization. Once more, these

findings indicate that inclusion practices and the provision of accessibility, backed by PSS,

play a prominent role in shaping the JSC of individuals with disabilities. This corroborates

findings from earlier research conducted by [ 1 ], [32] and [61].

Finally, a favorable and indirect association between PSS, IWE and the JSC of employees with

disabilities in Indonesian government institutions has been ascertained. This finding

highlights the role of PSS in assisting employees with disabilities in navigating the intricacies

of work within Indonesian government establishments, thereby enhancing their IWE and JSC.

This indirect effect on their sense of group affiliation and organizational identity corresponds

to insights derived from prior research by [54].

Theoretical Implications

In terms of theoretical implications, the primary findings of this study, as discussed earlier,

hold significant value for human resources managers and government institutions aiming to

establish a workplace that is more inclusive for employees with disabilities. To elaborate

further, the concept of stigma theory brings to light the formidable challenges that

individuals confront when they become the target of societal stereotypes ([63]). Employees

with disabilities often grapple with stigma, which can engender feelings of exclusion and

diminish their JSC. By delving into the role of DEIA initiatives, this study directly addresses

how organizational endeavors can impact the mitigation of stigmatization. When

organizations prioritize DEIA, they cultivate an environment wherein employees with

disabilities can receive recognition, inclusivity, and fair opportunities. This nurturing

environment counteracts the adverse effects of stigma, fostering a sense of belonging and

consequently heightening JSC.

Furthermore, the significance of stigma theory lies in its emphasis on the pivotal role of

supportive social interactions in ameliorating the repercussions of stigma. Here, the pivotal

role of PSS comes into play as a key mediator. Supervisors who actively champion DEIA

initiatives and provide essential support contribute to dismantling stigmatizing notions and

shaping a positive working atmosphere. PSS functions as a safeguard against the detrimental

impact of stigma, improving employees' IWE and overall JSC.

In essence, this research brings these theoretical insights into a pragmatic context. By

recognizing the challenges of stigma and acknowledging the role of DEIA initiatives and PSS,

human resources managers and government institutions can strategically formulate policies

and practices that foster inclusivity, create supportive workplace environments, and

ultimately enhance JSC for employees with disabilities.

Practical Implications

In terms of practical implications, this research offers valuable insights that can guide

strategic decision-making, policy formulation, and practices aimed at creating a more

inclusive and satisfying work environment. First, understanding how DEIA initiatives, PSS, and

IWE collectively influence JSC provides organizations with a roadmap to enhance their overall

effectiveness. By fostering an environment where all employees, including those with

disabilities, feel valued and supported, organizations can boost employee morale,

motivation, and commitment. This, in turn, positively impacts productivity, reduces turnover

rates, and contributes to a healthier organizational culture.

Second, the findings of this research offer human resources professionals' concrete insights

into developing tailored strategies that cater to the diverse needs of employees, particularly

those with disabilities. Organizations can design training programs for supervisors to

enhance their ability to provide necessary accommodations, demonstrate empathy, and

advocate for inclusivity. These strategies contribute to a more supportive work environment,

enhancing JSC, and overall well-being. Furthermore, this study sheds light on the pivotal role

of DEIA initiatives in shaping JSC. Organizations can use these insights to prioritize diversity

recruitment, equal pay, accessible facilities, and supportive policies. Consistent with the

findings of [25], the integration of DEIA components is imperative, not only aligning with

ethical imperatives but also strengthening the organization's reputation as an inclusive and

socially responsible entity.

Finally, recognizing the significance of PSS in mediating the relationship between DEIA and

JSC encourages organizations to invest in supervisor training. Equipping supervisors with the

skills to foster an inclusive and supportive environment contributes to higher levels of JSC

among employees with disabilities.

Limitations and Suggestions for Future Research

This study is not without certain inherent limitations, and also offers potential directions for

further research. Primarily, this investigation exclusively centers on employees with

disabilities within Indonesian government institutions. Consequently, its scope is confined to

research conducted within the public sector. Given the distinct variations in the treatment

and experiences of employees with disabilities across different countries, the generalizability

of the research findings herein is therefore restricted. To address this, future researchers may

transcend this limitation by undertaking surveys of disabled employees in diverse countries

and encompassing a broader spectrum of organizational types, including private firms, small

and medium-sized enterprises, as well as non-governmental organizations. Moreover,

delving deeper into the specifics of disability type and severity could offer valuable insights

for further analysis.

In addition, future research endeavors could introduce variables, such as accommodation

([54]), climate for inclusion ([35]), or organizational support ([ 9 ]) as potential moderating

factors. Incorporating these variables could potentially fortify the relationships observed in

this study's model. Moreover, there exists the possibility of exploring other facets that are

pertinent to the disabled community, such as their challenges in securing employment ([ 2 ]; [

5 ]), disparities in compensation between disabled and non-disabled workers ([22]; [36]), or

even investigating alternative outcomes, such as turnover intention ([ 7 ]; [54]).

Finally, this study solely embraces the perspective of stigma theory to elucidate the

interrelationships among the variables under study. Future research endeavors could diverge

from this approach by adopting alternative theoretical frameworks, such as social identity

theory (SIT) or self-verification theory, to provide nuanced explanations for the observed

relationships. These potential areas of exploration serve to acknowledge the limitations of

this study and indicate promising avenues for enriching understanding of the complex

dynamics surrounding DEIA, PSS, IWE and JSC among employees with disabilities.

Appendix

Preliminary Testing

Several preliminary tests were conducted and are outlined as follows. First, through the

Cramér–von Mises test, it was observed that the skewness and kurtosis values obtained were

statistically significant at the 5% level, leading to the conclusion that the data used were not

normally distributed ([20]; [31]; [34]). Second, upon examining outliers in our data, it was

found that all cases had Z -score values below 2.58, which adheres to the general rule of

thumb and indicates the absence of outliers ([48]). Finally, the heteroscedasticity of these

observations was assessed. Through the chi-square test, it was determined that there is no

significant residual variance at the 5% level, thus confirming that the assumption of

homoscedasticity is met.

Method Bias Testing

Initially, testing of biases was focused on non-response bias through applying multivariate

analysis of variance (MANOVA) to several demographic variables, as outlined by [14]. This

analysis demonstrated no significant differences in the main variable across different

demographic categories, at a significance level of 5%. To further validate these findings, t -

tests were carried out for both survey waves (early vs. late) among respondents who

completed the questionnaire. Once again, no statistically significant distinction between the

two groups was observed ([56]). Based on these analyses, it can be confidently concluded

that the data collection process was not affected by non-response bias.

Finally, the potential for CMV was addressed using the marker variable approach, a

contemporary method for detecting CMV as outlined by [52]. CMV was employed first

through the survey design, by separating predictor and outcome variables. Following the

systematic procedure described by [45], a new variable was introduced into the

questionnaire, which was unrelated to the focal constructs. This additional variable was then

assessed using correlation coefficients and GOFI. Upon analyzing the CFA marker, no

significant correlations ( r = < 0.087 at p >.05) were observed between the marker variable

and the focal constructs in the model. Furthermore, it is worth mentioning that the model

incorporating the CFA marker yielded inferior GOFI in comparison to the main CFA model.

Taking both these observations into account, it can be confidently concluded that CMV was

not present during the data collection process and poses no threat to the validity of the

findings of this study.

Validity and Reliability Testing

To gauge convergent validity, the standardized factor loading (SFL) and average variance

extracted (AVE) methods were employed. Meanwhile, divergent validity was evaluated using

metrics, such as the heterotrait–monotrait ratio (HTMT and HTMT2), maximum shared

variance (MSV) and average shared variance (ASV). Examining Table 1A reveals that all items

exhibit SFL values exceeding 0.724, and the AVE values are higher than 0.627 for all

constructs, with the exception of JSC2 which, although slightly lower at 0.565, remains

acceptable. Consequently, convergent validity aligns with the stipulated criteria in this case ([

3 ]; [19]; [27]). Furthermore, both the HTMT and HTMT2 ratios remained below 0.85, and both

MSV and ASV values were smaller than the AVE values, as evident in Table 2A. Based on these

outcomes, it can be confidently asserted that the measurement items meet the requirements

for divergent validity, aligning with established guidelines ([23]).

Table 1A. Results of Validity and Reliability Assessment.

Graph

Item FA SFL AVE MSV ASV RRC ρ c

A. Diversity, equity, inclusion and accessibility (DEIA) (Source: Adapted from Federal Employee Viewpoint Survey, 2022)

Diversity 0.807 0.362 0.344 0.888 0.889

My organization's management practices promote diversity (e.g., outreach, recruitment, promotion

DV1 0.949 0.841

Item FA SFL AVE MSV ASV RRC ρ c

opportunities)

My supervisor demonstrates a commitment to workforce diversity (e.g., recruitment, promotion opportunities, development)

DV2 0.949 0.952

Equity 0.759 0.471 0.433 0.902 0.904

I have similar access to advancement opportunities (e.g., promotion, career development, training) as others in my work unit

EQ1 0.909 0.840

My supervisor provides opportunities fairly to all employees in my work unit (e.g., promotions, work assignments)

EQ2 0.928 0.884

In my work unit, excellent work is similarly recognized for all employees (e.g., awards, acknowledgements)

EQ3 0.912 0.889

Inclusion 0.760 0.454 0.440 0.935 0.937

Employees in my work unit make me feel I belong IS1 0.932 0.943

Employees in my work unit care about me as a person IS2 0.912 0.922

I am comfortable expressing opinions that are different from other employees in my work unit

IS3 0.856 0.780

In my work unit, people's differences are respected IS4 0.911 0.866

I can be successful in my organization while being myself IS5 0.883 0.838

Accessibility 0.903 0.365 0.353 0.964 0.965

I can easily make a request of my organization to meet my accessibility needs

AC1 0.959 0.930

My organization responds to my accessibility needs in a timely manner

AC2 0.970 0.956

My organization meets my accessibility needs AC3 0.972 0.965

B. Intrinsic work experience (IWE) (Source: Adapted from Federal Employee Viewpoint Survey, 2022)

0.627 0.431 0.364 0.894 0.896

I feel encouraged to come up with new and better ways of doing things

IWE1 0.845 0.821

My work gives me a feeling of personal accomplishment IWE2 0.856 0.828

Item FA SFL AVE MSV ASV RRC ρ c

I know what is expected of me on the job IWE3 0.812 0.724

My talents are used well in the workplace IWE4 0.853 0.822

I know how my work relates to the agency's goals IWE5 0.824 0.760

C. Perceived supervisory support (PSS) (Source: Adapted from Federal Employee Viewpoint Survey, 2022)

0.639 0.441 0.405 0.875 0.876

My supervisor is committed to a workforce representative of all segments of society

PSS1 0.852 0.831

Supervisors in my work unit support employee development

PSS2 0.875 0.832

My supervisor supports my need to balance work and other life issues

PSS3 0.841 0.765

My supervisor provides me with constructive suggestions to improve my job performance

PSS4 0.850 0.766

D. Job Satisfaction (JSC) (Source: Adapted from Federal Employee Viewpoint Survey, 2022)

0.649 0.394 0.373 0.821 0.822

Considering everything, how satisfied are you with your job?

JSC1 0.903 0.888

Considering everything, how satisfied are you with your pay?

JSC2 0.748 0.565

Considering everything, how satisfied are you with your organization?

JSC3 0.923 0.916

2 Note(s) : FA = factor analysis; SFL = standardized factor loading; AVE = average variance

extracted; MSV = maximum shared variance; ASV = average shared variance; RRC = Raykov's

reliability coefficient; ρ c = composite reliability.

Table 2A. Divergent Validity Results and Descriptive Statistics Among Latent Variables.

Graph

Latent variable 1 2

Accessibility (AC)Diversity (DV)Equity (EQ)Inclusion (IS)Intrinsic work

(0.85)0.6720.6820.7170.6310.6760.6574.0600.8862.180 0.670(0.85)0.8060.7330.6370.700

 

Latent variable 1 2 experience (IWE)Job satisfaction (JSC)Perceived supervisory support (PSS)MeanStandard deviation (SD)Variance inflation factor (VIF)

3 Note(s) : Below the diagonal are the HTMT values. Above the diagonal are the HTMT2 values.

Diagonal and bold elements are cut-off values for HTMT and HTMT2.

In a subsequent phase, the constructs' reliability was assessed using both Raykov's reliability

coefficient (RRC) and composite reliability (ρ c ), both of which are deemed suitable for CFA.

[53] recommend values exceeding 0.70 for both measures. The findings, detailed in Table 1A,

demonstrate values exceeding 0.821 for both measures, aligning with the stipulated criteria.

Furthermore, the GOFI calculated for the CFA model yielded the following results: minimum

discrepancy function divided by the degrees of freedom (CMIN/DF) = 0.096, comparative fit

index (CFI) = 0.920 > 0.90, normed fit index (NFI) = 0.918 > 0.90, goodness of fit index (GOFI) =

0.897 > 0.85, parsimony GFI (PGFI) = 0.690 > 0.60, and root mean square error of

approximation (RMSEA) = 0.041 < 0.08 ([31]; [34]; [62]). Based on these GOFI results from the

CFA model, it can be confidently asserted that all of them meet the prescribed standards and

indicate a favorable fit.

References

1 Araten-Bergman T. (2016). Managers' hiring intentions and the actual hiring of qualified workers

with disabilities. The International Journal of Human Resource Management, 27(14), 1510–1530.

2 Bainbridge H. T. J., Fujimoto Y. (2018). Job seekers with musculoskeletal or sensory disabilities:

Barriers and facilitators of job search. British Journal of Management, 29(1), 82–98.

3 Bandalos D. L., Finney S. J. (2019). Factor analysis: Exploratory and confirmatory. In Hancock G.

R., Stapleton L. M., Mueller R. O. (Eds.), The reviewer's guide to quantitative methods in the social

sciences (2nd ed., pp. 98–122). Routledge.

4 Baumgärtner M. K., Dwertmann D. J. G., Boehm S. A., Bruch H. (2015). Job satisfaction of

employees with disabilities: The role of perceived structural flexibility. Human Resource

Management, 54(2), 323–343.

5 Beatty J. E., Baldridge D. C., Boehm S. A., Kulkarni M., Colella A. J. (2019). On the treatment of

persons with disabilities in organizations: A review and research agenda. Human Resource

Management, 58(2), 119–137.

6 Cavanagh J., Bartram T., Meacham H., Bigby C., Oakman J., Fossey E. (2017). Supporting workers

with disabilities: A scoping review of the role of human resource management in contemporary

organisations. Asia Pacific Journal of Human Resources, 55(1), 6–43.

7 Chordiya R. (2020). Organizational inclusion and turnover intentions of federal employees with

disabilities. Review of Public Personnel Administration, 42(1), 60–87.

8 Cohen J., Cohen P., West S. G., Aiken L. S. (2003). Applied multiple regression/correlation analysis

for the behavioral sciences (3rd ed.). Lawrence Erlbaum Associates.

9 Coll C., Mignonac K. (2023). Perceived organizational support and task performance of

employees with disabilities: A need satisfaction and social identity perspectives. The International

Journal of Human Resource Management, 34(10), 2039–2073.

Cox K. S., Holcomb Z. C. (2022). Interpreting basic statistics: A workbook based on excerpts from

journal articles (9th ed.). Routledge.

Dillman D. A., Smyth J. D., Christian L. M. (2014). Internet, phone, mail, and mixed mode surveys:

The tailored design method (4th ed.). Wiley.

Dwertmann D. J. G. (2016). Management research on disabilities: Examining methodological

challenges and possible solutions. The International Journal of Human Resource Management,

27(14), 1477–1509.

Eckert C., Hohberger J. (2022). Addressing endogeneity without instrumental variables: An

evaluation of the Gaussian Copula approach for management research. Journal of Management,

49(4), 1460–1495.

Fawcett S. E., Waller M. A., Miller J. W., Schwieterman M. A., Hazen B. T., Overstreet R. E. (2014). A

trail guide to publishing success: Tips on writing influential conceptual, qualitative, and survey

research. Journal of Business Logistics, 35(1), 1–16.

Federal Employee Viewpoint Survey. (2022). Office of Personnel Management, Washington, DC.

www.opm.gov/FEVS .

Ferraro C., Hemsley A., Sands S. (2023). Embracing diversity, equity, and inclusion (DEI):

Considerations and opportunities for brand managers. Business Horizons, 66(4), 463–479.

Follmer E. H., Talbot D. L., Kristof-Brown A. L., Astrove S. L., Billsberry J. (2018). Resolution, relief, and

resignation: A qualitative study of responses to misfit at work. Academy of Management Journal,

61(2), 440–465.

Fujimoto Y., Rentschler R., Le H., Edwards D., Härtel C. E. J. (2014). Lessons learned from community

organizations: Inclusion of people with disabilities and others. British Journal of Management,

25(3), 518–537.

Garson G. D. (2023). Factor analysis and dimension reduction in R. Routledge.

Gunzler D. D., Perzynski A. T., Carle A. C. (2021). Structural equation modeling for health and

medicine. CRC Press.

Hair J. F., Black W. C., Babin B. J., Anderson R. E. (2019). Multivariate data analysis (8th ed.).

Cengage Learning.

Hallock K. F., Jin X., Waldman M. (2022). The total compensation gap, wage gap and benefit gap

between workers with and without a disability. British Journal of Industrial Relations, 60(1), 3–31.

Henseler J. (2021). Composite-based structural equation modeling: Analyzing latent and emergent

variables. Guildford Press.

Ho J. A., Bonaccio S., Connelly C. E., Gellatly I. R. (2022). Representative-negotiated i-deals for

people with disabilities. Human Resource Management, 61(6), 681–698.

Hoang T., Suh J., Sabharwal M. (2022). Beyond a numbers game? Impact of diversity and inclusion

on the perception of organizational justice. Public Administration Review, 82(3), 537–555.

Holtom B., Baruch Y., Aguinis H., Ballinger G. A. (2022). Survey response rates: Trends and a validity

assessment framework. Human Relations, 75(8), 1560–1584.

Hoyle R. H. (Ed.). (2023). Handbook of structural equation modeling (2nd ed.). Guilford Press.

Husar Holmes M., Elias N. M., D'Agostino M. J. (2023). Inclusion in public-sector workplaces:

Charting a path for theory and practice. Public Personnel Management, 52(4), 491–497.

Iacobucci D., Popovich D. L., Moon S., Román S. (2023). How to calculate, use, and report variance

explained effect size indices and not die trying. Journal of Consumer Psychology, 33(1), 45–61.

Jones M. K. (2016). Disability and perceptions of work and management. British Journal of

Industrial Relations, 54(1), 83–113.

Jöreskog K. G., Olsson U. H., Wallentin F. Y. (2016). Multivariate analysis with LISREL. Springer.

Kensbock J. M., Boehm S. A. (2016). The role of transformational leadership in the mental health

and job performance of employees with disabilities. The International Journal of Human Resource

Management, 27(14), 1580–1609.

Khenfer J., Shepherd S., Trendel O. (2020). Customer empowerment in the face of perceived

Incompetence: Effect on preference for anthropomorphized brands. Journal of Business Research,

118, 1–11.

Kline R. B. (2023). Principles and practice of structural equation modeling (5th ed.) Guilford Press.

Klinksiek I. D., Jammaers E., Taskin L. (2023). A framework for disability in the new ways of working.

Human Resource Management Review, 33(2), 100954.

Kruse D., Schur L., Rogers S., Ameri M. (2018). Why do workers with disabilities earn less?

Occupational job requirements and disability discrimination. British Journal of Industrial Relations,

56(4), 798–834.

Kulkarni M. (2016). Organizational career development initiatives for employees with a disability.

The International Journal of Human Resource Management, 27(14), 1662–1679.

Kulkarni M., Gopakumar K. V. (2014). Career management strategies of people with disabilities.

Human Resource Management, 53(3), 445–466.

Kulkarni M., Lengnick-Hall M. L. (2013). Obstacles to success in the workplace for people with

disabilities: A review and research agenda. Human Resource Development Review, 13(2), 158–180.

Li R., Liu H., Chen Z., Wang Y. (2023). Dynamic and cyclic relationships between employees' intrinsic

and extrinsic motivation: Evidence from dynamic multilevel modeling analysis. Journal of

Vocational Behavior, 140, 103813.

Litman L., Robinson J. (2021). Conducting online research on Amazon Mechanical Turk and beyond.

SAGE.

Luu T. (2019). Relationship between benevolent leadership and the well-being among employees

with disabilities. Journal of Business Research, 99, 282–294.

Lyons B. J., Baldridge D. C., Yang L.-Q., Bryan C. (2023). Disability severity, professional isolation

perceptions, and career outcomes: When does leader–member exchange quality matter? Journal of

Management. Advance online publication. https://doi-

org.libraryresources.columbiasouthern.edu/10.1177/01492063221143714

McKinney E. L., Swartz L. (2021). Employment integration barriers: Experiences of people with

disabilities. The International Journal of Human Resource Management, 32(10), 2298–2320.

Miller B. K., Simmering M. J. (2023). Attitude toward the color blue: An ideal marker variable.

Organizational Research Methods, 36(3), 409–440.

Mitra S., Kruse D. (2016). Are workers with disabilities more likely to be displaced? The International

Journal of Human Resource Management, 27(14), 1550–1579.

Nelissen P. T. J. H., Hülsheger U. R., van Ruitenbeek G. M. C., Zijlstra F. R. H. (2016). How and when

stereotypes relate to inclusive behavior toward people with disabilities. The International Journal of

Human Resource Management, 27(14), 1610–1625.

Newbold P., Carlson W. L., Thorne B. M. (2023). Statistics for business and economics (10th ed.).

Pearson.

Newman M. A., Ali S., Powell A., South J. (2023). The experience of local governments in promoting

equity and inclusion. Public Personnel Management, 52(4), 624–649.

Peng K. Z., Cooke F. L., Wei X. (2023). Managing minority employees in organizations in Asia Pacific:

Towards a more inclusive workplace? Asia Pacific Journal of Management, 40(3), 877–902.

Pérez-Conesa F. J., Romeo M., Yepes-Baldó M. (2020). Labour inclusion of people with disabilities in

Spain: The effect of policies and human resource management systems. The International Journal

of Human Resource Management, 31(6), 785–804.

Podsakoff P. M., Podsakoff N. P., Williams L. J., Huang C., Yang J. (2024). Common method bias: It's

bad, it's complex, it's widespread, and it's not easy to fix. Annual Review of Organizational

Psychology and Organizational Behavior, 11, 17–61.

Raykov T., Marcoulides G. A. (2011). Introduction to psychometric theory. Routledge.

Samosh D., Maerz A., Spitzmuller M., Boehm S. (2023). Accommodation, interpersonal justice, and

the turnover intentions of employees with disabilities. The International Journal of Human

Resource Management, 34(1), 128–153.

Santuzzi A. M., Waltz P. R. (2016). Disability in the workplace: A unique and variable identity. Journal

of Management, 42(5), 1111–1135.

Scheaf D. J., Loignon A. C., Webb J. W., Heggestad E. D. (2023). Nonresponse bias in survey-based

entrepreneurship research: A review, investigation, and recommendations. Strategic

Entrepreneurship Journal, 17(2), 291–321.

Schloemer-Jarvis A., Bader B., Böhm S. A. (2022). The role of human resource practices for including

persons with disabilities in the workforce: A systematic literature review. The International Journal

of Human Resource Management, 33(1), 45–98.

Shantz A., Wang J., Malik A. (2018). Disability status, individual variable pay, and pay satisfaction:

Does relational and institutional trust make a difference? Human Resource Management, 57(1),

365–380.

Shore L. M., Randel A. E., Chung B. G., Dean M. A., Holcombe Ehrhart K., Singh G. (2010). Inclusion

and diversity in work groups: A review and model for future research. Journal of Management,

37(4), 1262–1289.

Sweeting K. D. (2023). Executive orders: Mandating inclusion in the federal workplace: Insights

from federal executive departments' strategic plans. Public Personnel Management, 52(4), 590–

623.

Trochmann M., Stewart K., Ragusa J. (2023). The impact of employee perceptions of inclusion in a

racially diverse agency: Lessons from a state government survey. Public Personnel Management,

52(4), 543–565.

Whittaker T. A., Schumacker R. E. (2022). A beginner's guide to structural equation modeling (5th

ed.). Routledge.

Zhang R., Wang M. S., Toubiana M., Greenwood R. (2020). Stigma beyond levels: Advancing

research on stigmatization. Academy of Management Annals, 15(1), 188–222.

Zhu X., Law K. S., Sun C., Yang D. (2019). Thriving of employees with disabilities: The roles of job

self-efficacy, inclusion, and team-learning climate. Human Resource Management, 58(1), 21–34.

Footnotes

The author(s) declared no potential conflicts of interest with respect to the research, authorship,

and/or publication of this article.

The author(s) disclosed receipt of the following financial support for the research, authorship,

and/or publication of this article: This research was funded by Diponegoro University through its

highly reputed international publication research (RPIBT) program with non-state budget (Non-

APBN) sources for the fiscal year 2023. The authors gratefully acknowledge this financial support.

Hersugondo Hersugondo

Graph https://orcid.org/0009-0006-7794-3455

~~~~~~~~

By Hersugondo Hersugondo; Kardison Lumban Batu; Charbel Jose Chiappetta Jabbour; Ana

Beatriz Lopes de Sousa Jabbour and Hengky Latan

Reported by Author; Author; Author; Author; Author

Hersugondo Hersugondo currently holds the position of Associate Professor at Diponegoro

University in Semarang, Indonesia. He has authored numerous articles indexed in Scopus

and Web of Science (WOS).

Kardison Lumban Batu currently holds the position of Associate Professor at Diponegoro

University in Semarang, Indonesia. He has authored numerous articles indexed in Scopus

and Web of Science (WOS).

Charbel Jose Chiappetta Jabbour has been appointed as Head of the Information Systems,

Supply Chain Management & Decision Support department and Professor of Green, Circular,

and Responsible Supply Chains at NEOMA Business School, France. He is one of dozens of

French-based scholars to have been included in the prestigious Clarivate/Web of Science

Highly Cited Researcher awards, due to having multiple articles ranked among the top 1% of

most cited papers globally.

Ana Beatriz Lopes de Sousa Jabbour is currently a Professor of Supply Chain Management for

Sustainable Development at EM Normandie Business School—Paris Campus, France. Her

research explores contemporary pressing issues related to sustainability in supply chains,

circular economy, and the nexus between sustainability and digital technologies. She has

been recognized as a highly cited researcher by Clarivate.

Hengky Latan currently serves as research director at the FTD Institute and senior researcher

at HLC Consulting, Indonesia. He has authored over 15 books and published over 55 articles,

most of them in leading international journals. He has also been included in Stanford

University's ranking of the 2% most cited scientists globally since 2021. According to Google

Scholar, his works have been cited more than 18,000 times (H-index = 49) in just 10 years of

his academic career.

Copyright of Public Personnel Management is the property of Sage Publications Inc. and its content may not be

copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written

permission. However, users may print, download, or email articles for individual use.

This document was generated by a user of EBSCO. Neither EBSCO nor the user who have generated this content is responsible for the content of this printout.

© 2025 EBSCO Information Services, LLC. All rights reserved. EBSCO | 10 Estes Street | Ipswich, MA 01938