Abstract
Orientation: Voluntary employee turnover, particularly among Generation Z employees, is a growing concern due to their higher mobility and evolving workplace expectations. Understanding how these employees evaluate the value of current versus alternative job opportunities is crucial for improving turnover prediction and management.
Research purpose: This study aimed to develop and validate the Alternative Job Net Value (AJNV) scale, a tool designed to measure the perceived net utility of present jobs versus job alternatives among Generation Z employees.
Motivation for the study: Existing turnover models lack precise measurements of how employees assess their current positions against external opportunities. Addressing this gap is essential for organisations aiming to predict and reduce voluntary turnover among Generation Z.
Research approach/design and method: Using an explanatory mixed-methods design, the study began with qualitative interviews to identify key factors influencing turnover, leading to the creation of an initial 28-item scale. The scale was refined through validity assessments and factor analyses. The final AJNV scale includes two subscales measuring the expected utility of the present job and job alternatives.
Main findings: The AJNV scale showed strong construct validity and reliability for the present job subscale and moderate reliability for job alternatives. It captures factors such as career development, rewards, and organisational policies that influence turnover intentions among Generation Z.
Practical/managerial implications: The AJNV scale offers organisations a diagnostic tool to assess turnover risk by comparing employees’ perceived value of current and alternative jobs, aiding retention strategies.
Contribution/value-add: This study contributes to turnover research by providing a psychometrically robust tool for measuring job alternatives’ comparative value.
Keywords: alternative job net value; voluntary turnover; Generation Z; scale validation; employee retention.
Introduction
Employee turnover has long been a significant concern for organisations, directly impacting operational efficiency, organisational knowledge and financial performance. Over the years, extensive research has identified numerous factors that influence turnover decisions, including job satisfaction, organisational commitment and the availability of alternative job opportunities (Griffeth et al., 2000; Mobley et al., 1979). However, despite these insights, traditional turnover models often fail to address the multifaceted nature of modern turnover behaviours. Recent studies highlight that these models fail to incorporate the complexities of employees’ assessments of alternative job opportunities, which are becoming increasingly influential in turnover decisions (Allen et al., 2010; Lee & Mitchell, 1994).
The urgency for a refined approach to turn over research is underscored by the evolving workforce dynamics, particularly with the integration of Generation Z. This generation introduces unique challenges as they prioritise career advancement, work-life balance, flexibility and alignment with personal values (Dhoundiyal et al., 2022; Schroth, 2019; Weng et al., 2022). These preferences reveal the limitations of existing turnover models, which predominantly focus on job satisfaction and organisational commitment, neglecting the nuanced evaluation of current roles versus potential alternatives (Lyons & Kuron, 2014; Twenge et al., 2010).
One critical aspect often overlooked in traditional turnover models is the way employees evaluate alternative job opportunities. This evaluation process, which involves weighing the potential benefits of leaving a current position against the costs and risks associated with transitioning to a new role, is central to understanding modern turnover behaviours. Existing models, while extensively addressing job satisfaction and organisational commitment, offer limited insights into how employees subjectively and dynamically assess these alternatives (Hom & Griffeth, 1995; Lee & Mitchell, 1994; Steel, 2002). This gap necessitates a closer examination of the ‘expected utility of alternative jobs’, a concept that captures the perceived value employees assign to external opportunities when making decisions about turnover. By linking this concept to established turnover frameworks, such as the unfolding model (Lee & Mitchell, 1994) and job embeddedness (Mitchell et al., 2001), researchers can better integrate the complexities of alternative job evaluations into contemporary theories of turnover.
Central to this challenge is the expected utility of alternative jobs, which refers to the value employees place on external job opportunities when making decisions about turnover. This concept builds directly on prior discussions of turnover models by extending their scope to incorporate both objective and subjective factors that influence decision-making. For example, while job satisfaction and organisational commitment remain foundational predictors of turnover, the expected utility of alternative jobs adds a layer of complexity by addressing how employees perceive and compare potential alternatives in real-world contexts (Mitchell et al., 2001; Steel, 2002). As employees weigh the potential benefits of leaving for a new job against the costs of such a decision, they are influenced by both tangible factors, such as salary and career prospects and intangible factors, including personal values, work-life balance and social networks. These subjective experiences are particularly relevant to Generation Z employees, who are known for their preference for flexibility, meaningful work and alignment with personal values (Holtom et al., 2008; Klotz & Bolino, 2016).
Moreover, while previous turnover studies have addressed the importance of alternatives, there is a notable gap in terms of how employees truly perceive and evaluate these alternatives. For instance, studies such as Griffeth et al. (2000) and Hom and Griffeth (1995) have predominantly focused on the availability of alternative job opportunities as an objective variable, often measured through labour market conditions or job offers. However, these studies do not delve into how employees subjectively assess the desirability and feasibility of these alternatives. Similarly, Mitchell et al. (2001) introduced the concept of job embeddedness, which partially accounts for the external forces that influence turnover decisions. Still, it does not explicitly examine the psychological processes employees use to evaluate alternative opportunities. This gap is critical, as it significantly influences turnover intentions, especially among younger generations who are more inclined towards flexibility and meaningful work (Holtom et al., 2008; Klotz & Bolino, 2016). In addressing this gap, this study makes a unique contribution to the literature by proposing a framework that integrates subjective evaluations of alternative job opportunities, emphasising both tangible and intangible factors, such as salary, career growth, work-life balance and alignment with personal values. This approach is particularly suited to understanding the turnover intentions of Generation Z employees, whose workplace preferences differ significantly from those of previous generations.
Thus, developing a robust and comprehensive alternative job net value (AJNV) measure has become critical. By explicitly incorporating the expected utility of alternative jobs, the AJNV measure addresses a key deficiency in existing turnover models, providing a more holistic and nuanced framework for understanding employee decision-making processes. This tool would address the current research gap by bridging the divide between job satisfaction and the expected utility of alternative opportunities, offering a holistic framework for understanding turnover intentions (Aguinis & Kraiger, 2009). By integrating objective and subjective factors, the AJNV measure would enable researchers and practitioners to better predict and manage employee retention strategies. It would provide a clearer understanding of how employees evaluate alternative job opportunities, allowing organisations to identify the underlying motivations that drive turnover in an increasingly complex and diverse workforce.
Considering employees’ changing expectations, particularly those from Generation Z, traditional turnover models must be adapted to remain relevant in today’s dynamic work environment. The introduction of the AJNV measure is crucial in providing organisations with a more accurate, nuanced and forward-thinking approach to turnover, enabling them to address employee needs more effectively and reduce unnecessary turnover costs.
Research question
This study’s research question is: ‘How can the development of a reliable and valid AJNV measurement tool improve the accuracy of turnover predictions among Generation Z employees in contemporary workplaces?’
The primary objective of this research is to develop a robust and valid measurement tool for evaluating the AJNV, which integrates objective and subjective factors that influence Generation Z employees’ perceptions of potential job opportunities. This tool will assess both measurable aspects, such as salary, career advancement and benefits; and subjective elements, including work-life balance, job satisfaction and personal growth opportunities. By accurately quantifying the perceived value of alternative job options, the AJNV tool aims to provide organisations with a deeper understanding of the factors influencing employees’ turnover intentions, extending beyond traditional predictors such as job satisfaction and organisational commitment.
Furthermore, this study seeks to enhance the accuracy of turnover prediction models by incorporating the AJNV into existing frameworks. By doing so, organisations will gain a more precise tool for forecasting employee turnover, grounded in a more comprehensive understanding of how employees compare their current roles to potential alternatives. By focusing explicitly on Generation Z employees, this research aims to address the unique turnover dynamics of this cohort, whose preferences for flexibility, meaningful work and alignment with personal values are reshaping workplace expectations. The ultimate goal is to refine turnover models to be more holistic and adaptable to the complexities of the modern workforce. Additionally, the AJNV tool will equip organisations with actionable insights to design targeted retention strategies that address the unique needs and expectations of their employees. By doing so, organisations will be better positioned to mitigate turnover risks while fostering greater employee satisfaction and loyalty.
Research design
This research adopts an exploratory mixed-methods design to develop and validate a psychometric instrument for measuring AJNV, specifically among Generation Z employees (born between 1997 and 2012). This methodological approach is grounded in Creswell and Clark’s (2018) mixed-methods research framework, which emphasises the complementary nature of qualitative and quantitative data in the development of instruments. The sequential exploratory design follows the established protocol of Creswell & Inoue (2025) and Hinkin (1998) for scale development, which recommends beginning with qualitative exploration to identify construct dimensions before proceeding to quantitative validation.
By integrating qualitative and quantitative methods, this study adopts a comprehensive approach that combines rich, contextual insights with empirical validation. The rationale for this mixed-methods approach is based on Churchill (1979) and DeVellis’ (2017) recommendations for psychometric instrument development, which advocate for an initial qualitative exploration to capture the full breadth of the construct before proceeding to quantitative testing. The qualitative phase identifies and explores the factors that influence Generation Z employees’ perceptions of alternative job opportunities. In contrast, the quantitative phase rigorously tests the instrument’s psychometric properties, ensuring reliability and validity. This dual-phase design leverages the strengths of both qualitative and quantitative approaches, enhancing the instrument’s robustness and applicability to the unique characteristics and workplace expectations of Generation Z employees.
The focus on Generation Z is theoretically justified by their distinct workplace characteristics, including higher expectations for job mobility, different career priorities and unique attitudes towards work-life balance compared to previous generations (Seemiller & Grace, 2016; Twenge, 2010). Research indicates that Generation Z employees exhibit distinct patterns of job satisfaction and turnover intentions, making it crucial to develop measurement tools specifically tailored to their experiences and expectations (Chillakuri & Mahanandia, 2018).
The study was conducted over 2 weeks, from 10 July 2024 to 25 July 2024, and followed strict ethical protocols. Informed consent was obtained from all participants, ensuring their voluntary participation and confidentiality. The study has two main phases (refer to Figure 1).
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FIGURE 1: Procedures for designing and psychometric evaluation of the Alternative Job Net Value Scale. |
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The methodological framework underlying the procedures presented in Figure 1 is based on the established scale development protocol outlined by DeVellis (2017) and adapted from the psychometric validation procedures recommended by the American Educational Research Association (2014). Phase 1 follows Braun and Clarke’s (2006) thematic analysis framework for qualitative data collection and analysis, while Phase 2 incorporates the psychometric validation procedures established by Hair et al. (2010) and Nunnally and Bernstein (1994) for construct validation.
Phase 1: Development of the alternative job net value instrument through qualitative methods targeting Generation Z employees
This phase focuses explicitly on Generation Z employees (born between 1997 and 2012) to develop the AJNV instrument, as this demographic demonstrates unique workplace characteristics, including higher job mobility, digital nativity and distinct career expectations compared to previous generations (Seemiller & Grace, 2016; Twenge, 2010). The methodological approach employed in this phase follows Creswell and Clark’s (2018) sequential explanatory mixed-methods design, where qualitative exploration precedes quantitative validation to ensure a comprehensive understanding of the phenomenon.
Online qualitative survey
Phase 1 of this study focused on developing the AJNV instrument using qualitative methods specifically designed to capture the unique perspectives and experiences of Generation Z employees, generating measurement items that reflect the complex factors influencing employee resignation and the consideration of alternative job opportunities. The qualitative approach in this initial phase is grounded in Braun and Clarke’s (2006) framework for exploratory research, which emphasises the importance of understanding participants’ lived experiences before developing measurement instruments. The first step in this process was implementing an online qualitative survey, which served as the primary data collection method. The survey targeted 40 Generation Z employees, specifically those who had recently resigned or planned to resign. This sample was selected to capture a broad range of experiences related to leaving a job, including the factors influencing this choice, such as emotional responses, decision-making processes and any alternative job opportunities being considered.
The online survey format was particularly advantageous for gathering open-ended responses, allowing participants to express their views reflectively and honestly. This approach aligns with Dillman et al. (2014) recommendations for web-based qualitative data collection, which emphasises the importance of creating a comfortable environment for participants to share sensitive workplace experiences. This flexibility provided the opportunity for detailed accounts of participants’ experiences with resignation. The responses revealed recurring themes related to key reasons for resignation, including job dissatisfaction, perceived job market opportunities and emotional triggers such as burnout, lack of career advancement and work-life imbalance. These identified themes were crucial for developing the AJNV measurement items, ensuring that the instrument would comprehensively address both objective factors (e.g., salary, benefits) and subjective factors (e.g., work-life balance, job satisfaction) that influence Generation Z employee resignation decisions.
Semi-structured and in-depth interviews
Semi-structured and in-depth interviews were conducted with a purposive sample of seven Generation Z participants to supplement the survey data and gain deeper insights into employees’ experiences of resignation. The decision to employ both semi-structured and in-depth interview techniques follows (Seidman, 2006) phenomenological interview approach, which allows for both structured exploration of predetermined themes and flexible investigation of emergent topics. These individuals were selected to ensure a diverse range of perspectives on the resignation process. The interviews, which lasted between 30 min and 60 min, provided an opportunity to explore the personal stories, emotional responses and motivations behind their decision to resign.
The semi-structured interviews followed a predetermined interview guide that focused on core themes identified from the literature on Generation Z workplace behaviour (Chillakuri & Mahanandia, 2018). Meanwhile, the in-depth interview segments allowed participants to elaborate on their unique personal experiences and contextual factors specific to their resignation decisions. The semi-structured format allowed for flexibility in questioning, enabling participants to elaborate on sensitive topics, such as their feelings towards their current job conditions and perceptions of potential job opportunities. This format proved valuable for capturing nuanced qualitative data that was difficult to obtain through the more structured online survey. The in-depth interview components specifically explored Generation Z’s unique workplace expectations, including their desire for immediate feedback, flexible work arrangements and meaningful work experiences (Seemiller & Grace, 2016). The interviews explored both objective factors, such as job benefits and career advancement opportunities, as well as subjective factors, including personal growth, emotional fulfilment and the need for improved work-life balance. The insights gathered from the interviews provided a richer and more comprehensive understanding of how Generation Z employees evaluate and prioritise alternative job opportunities.
Data integration and analysis
The data collected from online surveys and semi-structured interviews were systematically analysed and integrated using Braun and Clarke’s (2006) thematic analysis framework. This methodological approach was selected explicitly for its rigorous and systematic nature, which is particularly well-suited for exploring the complex factors influencing the resignation decisions of Generation Z employees (Braun & Clarke, 2019). The thematic analysis followed six key steps: familiarisation with the data, generating initial codes, searching for themes, reviewing themes, defining and naming themes and producing the report (Braun & Clarke, 2006). This approach involved transcribing interviews, followed by coding and iterative refinement of the emerging themes. This analysis identified key recurring patterns, including dissatisfaction with management practices, a lack of growth opportunities and a desire for a more flexible work environment. These patterns were then used to inform and refine the measurement items for the AJNV scale.
The in-depth semi-structured interviews were particularly valuable for capturing the nuanced perspectives of Generation Z employees, allowing for both structure and flexibility in data collection (Kallio et al., 2016). This interview approach enabled participants to elaborate on their experiences beyond the constraints of predetermined questions, providing rich qualitative data that complemented the broader patterns identified in the online surveys. The combination of these methods follows the sequential exploratory mixed-methods design outlined by Creswell and Clark (2018), where qualitative exploration precedes and informs the development of quantitative measurement.
The thematic analysis employed in this study followed an iterative and reflexive approach, consistent with best practices in qualitative research (Braun & Clarke, 2006; Nowell et al., 2017). This process ensured that the derived measurement items were not only grounded in the recurrent themes identified across survey responses but also sensitive to nuanced individual differences that emerged from the in-depth interviews. Through systematic triangulation of quantitative and qualitative data sources, the development of the AJNV instrument was designed to capture a holistic representation of the psychological, contextual and motivational factors that shape employees’ contemplation of alternative employment and their decision to leave voluntarily. This integrative approach enhances both the construct validity and practical relevance of the instrument, making it suitable for both applied organisational diagnostics and academic research.
Participant selection and data representation
Participants were selected based on specific inclusion criteria that ensured the data were representative of the target population: Generation Z employees (born between 1997 and 2012) with a minimum of a bachelor’s degree and at least 6 months of professional work experience. The focus on Generation Z is theoretically justified by research indicating that this cohort exhibits distinct workplace characteristics, including higher turnover intentions, different motivational factors and unique career development expectations compared to previous generations (Chillakuri & Mahanandia, 2018; Seemiller & Grace, 2016). The participants were specifically chosen for their recent or upcoming resignation status in the Indonesian context, aiming to capture the experiences of younger employees, a demographic often considered more mobile and willing to explore alternative job opportunities than older generations.
This targeted selection was crucial for obtaining relevant data on the resignation experiences of a group that plays a significant role in the evolving labour market dynamics and whose workplace behaviours significantly impact organisational retention strategies (Twenge, 2010).
Scale development and future steps
The qualitative insights obtained from the online survey and in-depth semi-structured interviews provided a strong foundation for the next phase of the research: the development of a refined AJNV scale. The mixed-methods approach employed in this study follows the instrument development and construct validation framework proposed by Onwuegbuzie et al. (2010), which recommends using qualitative methods to explore constructs before developing quantitative measures. This approach is particularly suitable for studying Generation Z employees, whose workplace values and behaviours may differ from those of previous generations, as documented in the existing literature (Goh & Lee, 2018). The measurement items generated from this phase will be used in the subsequent quantitative phase to test the scale’s psychometric properties. The items will be framed using a 4-point Likert scale, ranging from ‘strongly disagree’ to ‘strongly agree’, to assess employees’ expectations of alternative job opportunities.
This phase will be critical in developing an instrument that accurately captures both the objective (e.g., salary, benefits, career progression) and subjective elements (e.g., work-life balance, job satisfaction, personal growth) that influence employees’ decisions to leave their current employment. By integrating the qualitative data into the instrument development process, this study ensures that the AJNV scale is scientifically rigorous and grounded in real-world experiences.
The procedures outlined in Figure 1 follow the sequential instrument development process recommended by Boateng et al. (2018) and DeVellis (2017), which involves item generation through qualitative exploration, followed by expert review, pilot testing and psychometric validation. This established methodological framework ensures that the resulting instrument will be both theoretically sound and practically applicable for measuring turnover intentions among Generation Z employees.
Through this iterative data collection, integration and analysis process, the research ensures that the AJNV instrument is reliable, valid and capable of capturing the complexities of the factors that drive employee turnover. This comprehensive approach sets the stage for the subsequent validation phase, where the scale will undergo further testing and refinement.
Phase 2: Scale refinement and validation
In Phase 2 of this study, the development of the AJNV scale undergoes a thorough refinement and validation process, focusing on assessing the instrument’s psychometric properties for Generation Z employees. This phase employs a mixed-methods approach combining qualitative expert review with quantitative psychometric testing, following the guidelines established by DeVellis (2017) and Hinkin et al. (1997) for scale development. The integration of qualitative and quantitative methods in this phase is consistent with the instrument validation framework proposed by Luyt (2012), which emphasises the complementary nature of these approaches in establishing a robust measurement tool. This phase aims to evaluate the scale’s face validity, content validity, construct validity and reliability, ensuring that the AJNV scale accurately measures the constructs it is designed to assess and maintains internal consistency across diverse Generation Z sample groups.
Face validity
The AJNV scale underwent both qualitative and quantitative evaluation to assess face validity. Initially, four employees from Generation Z who had recently resigned or were considering resigning were selected to review the scale items. They provided feedback on the items’ clarity, relevance, comprehensibility and precise language. This qualitative feedback helped refine the scale, addressing potential ambiguities and aligning the items with the participants’ understanding of the factors influencing resignation.
Following the revisions, a quantitative evaluation was conducted using a 5-point Likert scale, where the same participants rated the importance of each item. The item impact score was calculated by multiplying the frequency of responses by the importance ratings, and items with a score of 1.5 or greater were retained. Based on Lawshe (1975), this approach ensured that only the most relevant items were retained for further analysis, thereby enhancing the scale’s validity and accurately measuring the intended construct.
Content validity
A two-step process combining qualitative and quantitative methods was employed to assess the content validity of the AJNV scale. Initially, seven experts in organisational behaviour and psychometrics were invited to review the scale’s items. These experts were selected based on their extensive experience in both fields and evaluated the items for grammatical correctness, relevance and alignment with the study’s theoretical framework. Expert feedback led to refinements in the wording and structure of several items, ensuring they reflected the intended constructs and remained relevant to the study’s objectives.
Following the expert review, a quantitative content validity assessment was conducted using the Content Validity Ratio (CVR) and Content Validity Index (CVI). The CVR was calculated to determine the proportion of experts who agreed on the necessity of each item, with a threshold of 0.99 for retention (Lawshe, 1975). The CVI evaluated the overall relevance and comprehensiveness of the items based on expert ratings using a 4-point Likert scale. Items with a CVI score of 0.79 or higher were retained, ensuring that only those items considered both relevant and essential were included in the scale (Davis, 1992). This dual approach ensured that the AJNV scale effectively measured the relevant constructs.
Construct validity
To establish the construct validity of the AJNV scale, a two-step approach was employed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). These statistical techniques were chosen to ensure that the scale accurately reflects the underlying constructs of employee turnover intentions, such as job dissatisfaction, perceived opportunities and emotional responses to work conditions.
In the first step, EFA was performed on data from 82 participants who met specific criteria, including having a minimum of a bachelor’s degree and either actively planning to resign or having recently resigned. The data were analysed using the maximum likelihood (ML) extraction method with Promax rotation to uncover the latent factors behind the AJNV scale items. The suitability of the data was assessed through the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s sphericity test, which confirmed that the sample was appropriate for factor analysis, with KMO values above 0.6 considered adequate. Items with factor loadings ≥ 0.4 were retained, indicating a strong relationship between the items and the identified factors (Hair et al., 2010). This process allowed for extracting the most significant latent factors influencing employee turnover decisions.
Following the EFA, CFA was conducted to validate the factor structure obtained from EFA. Confirmatory factor analysis was used to test how well the identified factors fit the observed data. To assess model fit, several fit indices were evaluated, including chi-square, root mean square error of approximation (RMSEA), comparative fit index (CFI) and Tucker-Lewis index (TLI). A good model fit was indicated by CFI and TLI values above 0.90 and RMSEA values below 0.08 (Jaccard & Wan, 1996; Meyers et al., 2017). The results from both EFA and CFA demonstrated that the AJNV scale’s factor structure was robust, confirming that the scale accurately measures the key constructs related to employee turnover intentions. This comprehensive approach to construct validity ensures that the AJNV scale is reliable and valid for capturing the factors influencing employees’ decisions to leave their jobs.
Reliability testing
Reliability refers to the consistency of a measurement tool in producing stable and consistent results. For the AJNV scale, internal consistency was evaluated using two widely accepted measures: Cronbach’s alpha (α) and McDonald’s omega (ω).
Cronbach’s alpha (α) is a statistic used to assess the correlation between items within the scale. An alpha value between 0.7 and 0.9 is acceptable, indicating that the items reliably measure the same construct. Values above 0.7 generally suggest good reliability, while values between 0.6 and 0.9 may still be acceptable, depending on the complexity of the construct (Hair et al., 2010; Meyers et al., 2017).
McDonald’s omega (ω) provides a more robust internal consistency estimate, especially for multidimensional scales. Unlike Cronbach’s alpha, which assumes a unidimensional structure, omega accounts for multiple factors within the scale. Omega values between 0.7 and 0.9 are also considered indicative of strong reliability.
For the AJNV scale, both Cronbach’s alpha and McDonald’s omega were calculated and yielded results within the acceptable range, confirming their internal consistency. Additionally, item-total correlations were assessed to ensure each item contributed meaningfully to the scale’s overall construct. Items with low correlations were flagged for potential removal, ensuring the scale’s items consistently measured the intended construct across different contexts and periods.
These findings confirm that the AJNV scale is reliable and consistently measures the intended constructs.
Ethical considerations
Ethical clearance to conduct this study was obtained from the Institutional Ethical Committee University of Surabaya (No. 399/KE/VII/2024). Prior to participation, all participants were fully informed about the study’s objectives and the nature of their involvement. Written consent was obtained from each participant, ensuring they understood their role in the research.
The voluntary nature of participation was clearly communicated, and participants were made aware of their right to withdraw from the study at any time without negative consequences. Throughout the research process, strict measures were implemented to maintain the confidentiality and anonymity of the participants. Personal information and responses were kept secure and were only used for the study in adherence to ethical guidelines and standards.
This study aimed to uphold the highest ethical standards by ensuring transparency, respect for autonomy, and safeguarding privacy. Ethical practices were consistently followed to protect the rights and well-being of all participants involved.
Results
The initial qualitative phase of this study involved conducting in-depth interviews with employees who had either resigned or were in the process of resigning. From these interviews, 13 thematic codes were identified. These codes were categorised into two main dimensions: organisational and individual factors. Organisational factors included company policies, rewards, workgroup dynamics, organisational size and management approaches. Individual factors, on the other hand, covered emotional states, career advancement opportunities, skill development prospects, personal interests, personality traits, family considerations and work-life balance. These factors were essential in understanding why employees decided to leave their jobs.
Thematic saturation was reached when no new themes emerged from the data, indicating that further interviews would not yield additional insights. It allowed the researchers to develop an initial scale based on the 13 identified codes and the two main themes. The scale initially consisted of 28 items, each related to the expected utility of the present job or job alternatives. These items were evenly distributed between the two dimensions, with 14 dedicated to each category. A 4-point Likert scale was used to rate each item, ranging from ‘strongly disagree’ to ‘strongly agree’.
In Phase 2 of the study, the scale underwent a face validity assessment. Two items were removed because of low impact scores (below 1.5) during this process, resulting in a reduced scale of 26 items. The researchers applied the content validity ratio (CVR) and the content validity index (CVI) to assess content validity. The CVR was calculated based on expert judgements regarding the relevance of each item. Lawshe (1975) states that a CVR value of at least 0.99 is acceptable. Six items were excluded because their CVR values were below this threshold.
Additionally, the CVI, which measures the agreement among experts on the relevance of items, ranged from 0.57 to 1, with the overall CVI or average value estimated at 0.79. Four more items were excluded because of insufficient CVI scores. After these revisions, the final scale was refined to 16 items, with 8 items related to the expected utility of the present job and 8 items related to job alternatives.
The demographic characteristics of the study participants are summarised in Table 1. The sample consisted of 82 participants, with the majority aged 25–26 years (46.4%) and 96.3% holding a bachelor’s degree. Most participants were employed in corporate settings (75.5%), and 53.7% held contract positions.
| TABLE 1: Demographic characteristics of the participants (N = 82). |
Exploratory factor analysis was performed to examine the scale’s factor structure and measure the expected utility of the present job and job alternatives. The analysis utilised ML estimation along with Promax rotation. The KMO test for sampling adequacy revealed values of 0.78 for the expected utility of the present job and 0.70 for job alternatives, indicating that the data were suitable for factor analysis. Bartlett’s test of sphericity was significant for both dimensions, with χ2 = 104.95, p < 0.01 for the expected utility of the present job, and χ2 = 42.84, p < 0.01 for job alternatives, further supporting the appropriateness of the factor analysis.
Although the scale was conceptualised as unidimensional, the EFA identified two distinct factors—present job utility and job alternatives utility—while the CFA supported a one-factor model for each. It suggests a need to clarify whether the scale measures a single higher-order construct or two closely related constructs. Recent literature emphasises the importance of aligning the conceptual framework with empirical factor-analytic results to enhance methodological coherence and interpretability (Brown, 2015; Reise et al., 2013). Therefore, we recommend future research to examine the potential for a higher-order factor structure that encompasses both dimensions, as well as to explicitly test the theoretical relationship between present job utility and job alternatives utility.
The factor extraction process identified two distinct factors: the expected utility of the present job and job alternatives. For the expected utility of the present job, the eigenvalue was 2.55, accounting for 52.0% of the total variance. For job alternatives, the eigenvalue was 1.98, explaining 33.6% of the variance. Based on the factor loadings, eight items were retained, four for each dimension. The principal component method was used with a minimum factor loading of 0.4 for item retention, excluding eight items.
Following the EFA, CFA was conducted to validate the scale. The final scale consisted of eight items – four related to the expected utility of the present job and four related to job alternatives – confirming that a one-factor structure accurately represented each dimension. These results are summarised in Table 2, which provides the refined scale and the corresponding factor loadings.
| TABLE 2: Exploratory factors extracted from the expected utility scale. |
The CFA results confirmed the adequacy of the factor structure for both scale dimensions, demonstrating excellent model fit indices. The CFA results supported a one-dimensional structure for each dimension: the expected utility of the present job and job alternatives. The model fit indices for both dimensions were as follows:
- Expected utility of the present job: χ2 = 1.35, p > 0.005, CFI = 1.00, TLI = 1.01, RMSEA = 0.00
- Expected utility of job alternatives: χ2 = 1.48, p > 0.005, CFI = 1.00, TLI = 1.01, RMSEA = 0.00
These values indicate a strong fit of the model to the data, with all indices falling within acceptable ranges, confirming that the final model adequately represents the data (as summarised in Table 3). Figure 2 and Figure 3 illustrate the modified CFA model for both dimensions, further supporting the one-dimensional structure for each.
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FIGURE 2: Confirmatory factor analysis model: Expected utility of the present job. |
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FIGURE 3: Confirmatory factor analysis model: Expected utility of job alternatives. |
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| TABLE 3: Fit indicators of the confirmatory factor analysis model of the assessment scale: the expected utility of the present job and job alternative. |
The reliability of the scale was evaluated using both Cronbach’s alpha (α) and McDonald’s omega (ω), with particular attention to the job alternatives dimension, which demonstrated lower reliability. For the expected utility of the present job, Cronbach’s alpha was 0.83, and McDonald’s omega was 0.80, indicating strong internal consistency. For the expected utility of job alternatives, Cronbach’s alpha was 0.68, and McDonald’s omega was 0.64. Although these values are within the acceptable range (Brunner & Süß, 2005; Hair et al., 2010), the lower reliability for the job alternatives dimension warrants further discussion. McDonald’s omega is generally considered a more robust estimator of internal consistency, especially in multidimensional scales or when tau-equivalence is violated (Dunn et al., 2014; Hayes & Coutts, 2020). The relatively lower omega for the job alternatives dimension may be attributed to several factors, including the small sample size, which can inflate error variance and attenuate reliability estimates (Bonett, 2002; Taber, 2018), as well as potential heterogeneity in participants’ experiences with alternative job options or ambiguities in item wording. To address this, future research should consider refining the items for clarity and relevance, increasing the sample size for greater statistical power, and possibly expanding the number of items to better capture the latent construct (DeVellis, 2017).
Furthermore, the effect of the small sample size should be acknowledged throughout the study, as it may impact both the stability of factor solutions and the precision of reliability estimates (Furr, 2022; Wolf et al., 2013). Nevertheless, the strong McDonald’s omega for the present job dimension, which is less influenced by sample size compared to Cronbach’s alpha, provides confidence in the robustness of this part of the scale (Dunn et al., 2014). The appropriateness of the sample for factor analysis was confirmed by KMO and Bartlett’s tests. However, future studies with larger and more diverse samples are recommended to strengthen the generalisability of these findings (Hair et al., 2010; Meyers et al., 2017; Murphy & Davidshofer, 2005).
Discussion
This study addresses a critical gap in the literature on employee turnover by introducing a psychometrically sound measurement tool to evaluate the AJNV, which compares the expected utility of an employee’s present job with the expected utility of job alternatives. Employee turnover remains a significant challenge for contemporary organisations. Although many turnover models recognise the importance of perceived alternatives, there has been a lack of consensus on their definition and measurement. Developing a reliable and valid AJNV tool provides a much-needed solution to this issue, as it allows for a more precise and standardised measurement of employees’ expected value of their current position and alternative job opportunities. This tool is particularly relevant for Generation Z employees with distinct expectations regarding career development, organisational benefits, leadership quality and work-life balance.
A major contribution of this study is creating a unidimensional framework that integrates both organisational and individual factors, offering a comprehensive tool for assessing job transition decisions. The tool includes eight items – four measuring the expected utility of the present job and four measuring the expected utility of job alternatives. These items reflect critical aspects that are highly valued by Generation Z employees, including opportunities for career growth, rewards, organisational policies and leadership quality. By explicitly focusing on these dimensions, the scale not only contributes to the existing body of literature but also provides a more nuanced understanding of the factors influencing turnover intentions among younger employees, aligning with findings from previous studies (Meret et al., 2018; Schroth, 2019; Schwabel, 2014).
One of the major challenges in prior research has been the lack of a consistent definition and measurement for perceived alternatives. Prior studies, such as those by Griffeth and Hom (1988), highlighted the ambiguous nature of this construct, which resulted in inconsistent findings across studies. This study directly addresses this gap by offering a clear conceptual definition of the expected utility of the present job and job alternatives, thus resolving the issue of measurement inconsistency. By doing so, this study presents a more accurate and reliable tool for predicting turnover intentions. Rather than focusing on general job satisfaction or organisational commitment, the AJNV tool specifically captures the perceived net value of staying in the current job compared to moving to a new position, offering a direct and actionable predictor of turnover.
The psychometric analysis conducted in this study, including CFA, confirmed the reliability and validity of the AJNV tool, with strong model fit indices (CFI = 1.00, TLI = 1.01, RMSEA = 0.00) for both dimensions. These results indicate that the tool is robust, offering a reliable measure of employees’ turnover intentions based on their perceptions of the relative benefits of current and alternative job opportunities. The Cronbach’s alpha and McDonald’s omega values for the dimensions of expected utility were within acceptable ranges, with the present job dimension (α = 0.83, ω = 0.80) showing strong internal consistency, and the job alternatives dimension (α = 0.68, ω = 0.64) indicating moderate reliability. The lower reliability for the job alternatives dimension may be partially attributed to the small sample size, as smaller samples are associated with greater sampling error and less stable reliability estimates (Bonett, 2002; Taber, 2018). In addition, the heterogeneity of participants’ experiences with alternative job options and potential item wording issues may have further contributed to the reduced internal consistency (DeVellis, 2017). To improve this dimension in future research, we recommend refining the item wording for clarity, expanding the item pool to capture the construct better and increasing the sample size to enhance the stability of the psychometric estimates. These values suggest that the tool is sufficiently reliable for real-world organisational settings, though further refinement could enhance the measurement of job alternatives.
Strengths and limitations
This study contributes significantly to employee turnover research, particularly by offering a psychometrically robust instrument for assessing the comparative value of present and alternative job opportunities. One of the primary strengths of this study lies in its focus on Generation Z employees, a demographic often underrepresented in turnover studies despite their increasing presence in the workforce. The AJNV scale developed in this research demonstrates strong face, content and construct validity and satisfactory reliability indicators, including Cronbach’s alpha and McDonald’s omega. These psychometric properties make the AJNV scale a reliable tool for understanding the decision-making processes of employees contemplating job transitions. Furthermore, the unidimensional structure of the scale offers simplicity and clarity, making it a feasible and user-friendly tool for researchers and practitioners aiming to assess the relative utility of present jobs versus job alternatives.
Despite these strengths, several limitations should be acknowledged. Firstly, the study focuses exclusively on Generation Z employees, and the findings cannot be directly generalised to other generational cohorts, such as Millennials, Generation X, or Baby Boomers, who may have different work expectations and turnover behaviours. Therefore, future research should consider expanding the scope of the study to include a broader range of generational groups to assess the scale’s applicability across various demographics. Secondly, the relatively small sample size of 82 participants limits the external validity of the findings. The small sample size may also affect the stability of factor-analytic results and the reliability coefficients, particularly for the job alternatives dimension (Taber, 2018; Wolf et al., 2013). While the psychometric evaluations conducted in this study are promising, replication with a larger and more diverse sample would be crucial to confirm the generalisability of the AJNV scale. Importantly, McDonald’s omega is considered to be less influenced by sample size compared to Cronbach’s alpha, making it a preferred indicator of internal consistency in small samples (Dunn et al., 2014; Hayes & Coutts, 2020).
Nevertheless, the findings should be interpreted with caution, and future studies should strive to increase the sample size to bolster the robustness of the results. Moreover, this study did not explore the relationship between the AJNV scale and other turnover-related variables, such as job satisfaction, organisational commitment and actual turnover behaviour. Examining these relationships in future research would provide a more comprehensive understanding of how the AJNV scale interacts with other predictors of turnover intention. Finally, the study’s focus on the Indonesian context may limit its applicability in different cultural and geographical settings. Exploring regional and cultural variations in work values, such as work-life balance, compensation and career development, could offer valuable insights into how cultural factors influence employee turnover decisions.
Conclusion
This study has successfully developed and validated a novel measurement tool, the AJNV scale, designed to assess the comparative utility of present and alternative job opportunities, specifically focusing on Generation Z employees. The AJNV scale is a reliable and valid tool for understanding the key factors influencing employees’ decisions to resign from their current roles, including career development, compensation, organisational policies and leadership quality. The psychometric evaluations, including tests for face validity, content validity, construct validity and reliability assessments using Cronbach’s alpha and McDonald’s omega, indicate that the scale is robust and suitable for academic research and practical applications in employee retention strategies.
While the AJNV scale offers valuable insights into employee turnover, particularly in the context of Generation Z, several limitations must be acknowledged. Most notably, the relatively small sample size may have affected the stability of factor-analytic results and the precision of reliability estimates, especially for the job alternatives dimension. This limitation underscores the need for future research to replicate these findings with larger and more diverse samples to enhance the generalisability and robustness of the scale. Furthermore, the lower internal consistency observed for the job alternatives dimension suggests opportunities for further refinement of item content and structure. Future studies should consider revising or expanding the item pool, clarifying item wording and ensuring greater representativeness of participants’ experiences with job alternatives.
In addition, the current study did not examine the relationships between the AJNV scale and other key variables such as job satisfaction, organisational commitment or actual turnover behaviour. Exploring these associations in future research could provide a more comprehensive understanding of the AJNV scale’s predictive validity and practical utility.
Finally, while the scale was developed and validated within an Indonesian context and among Generation Z employees, its applicability to other cultural, organisational and generational contexts remains to be established. Future research should test the scale across different settings and populations to confirm its broader relevance and adaptability.
Overall, the AJNV scale represents a significant advancement in the measurement of employee turnover intentions by offering a standardised and psychometrically sound instrument that captures the comparative value of present and alternative job opportunities. By addressing both conceptual and methodological gaps in the turnover literature, this tool provides organisations and researchers with a more precise basis for understanding and managing employee retention in an increasingly dynamic workforce.
Acknowledgements
We want to express our heartfelt gratitude to all the participants who generously devoted their time and shared their insights, making this study possible. Their contributions were essential to the success of this research. We also sincerely appreciate the HR professionals and university lecturers who provided valuable feedback during the review process. Their expertise and guidance were instrumental in refining the items and enhancing the quality of this work. Finally, we acknowledge the experts whose advice and judgement have significantly shaped the outcome of this study. Without their collective support, this research would not have been feasible.
Competing interests
The authors declare that they have no financial or personal relationships that could have inappropriately influenced them in writing this article.
Authors’ contributions
H.W.S.E. designed the study, conducted the data analysis and drafted the manuscript. R.H. served as the supervisor, guiding the research process. H.W.S.E., R.H. and A.H.P. contributed to the review and approval of the final manuscript.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
The data supporting this study’s findings are available from the corresponding author, H.W.S.E., upon reasonable request. Access to the raw data may be provided following a formal request, by applicable privacy or confidentiality agreements.
Disclaimer
The views and opinions expressed in this article are those of the authors and are the product of professional research. It does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or the publisher. The authors are responsible for this article’s results, findings and content.
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