Keyword

Talent Management (TM), Organisational performance, Confirmatory Factor Analysis.

Introduction

The most crucial resource for any firm is its human capital, according to recognised theory. It is generally acknowledged that organisations with the best employees succeed in the long run. This observation is corroborated by the fact that business leaders' top concerns centre on their human capital. Human capital is frequently seen as the most important aspect in helping organisations fulfil their missions and operationalise their strategic goals(Kehinde, 2012). Employees with strong professional competence and high development potential are more crucial than ever in today's competitive businesses that must operate under heavy pressure to adopt new technologies and quickly develop new products. The main objective of talent management (TM) is to develop a talented and dedicated workforce by strategically utilising personnel and intellectual processes to achieve organisational sustainability (Mistry, 2022). People capital is frequently seen as the most important aspect in helping organisations fulfil their missions and successfully implement their strategic goals (Lee and Van der Waldt, 2020).

Organisations struggle more with talent constraints than capital constraints (Kehinde, 2012). According to the literature, only 3-5% of an organisation's workforce is considered talented (Farndale, Agarwal &Budhwar, 2022). The key to improving and maintaining organisational performance is talent Farndale et al., 2022). Talent comprises a person's capabilities, experience, knowledge, intelligence, and qualifications, as well as their ability to learn and grow (Rop & Kwasira, 2015).

The main focus of this study is to investigate the current stance of TM practices in the diamond industry on sustainable organisational performance. However, prior studies in India have been conducted in the real estate, banking, IT, pharmaceuticals, and automobile industries. The diamond sector is significant from a labour perspective because it employs a huge number of people (Morris, 2016). However, the diamond business faces numerous challenges, including a shortage of funding and unskilled and inexperienced labour, which are fundamental limitations. Thus, the study aimed to fill the gap. Thus, the study aimed to fill the gap.The findings of this study will enable players in Surat's diamond industry to formulate an effective talent management strategy to achieve sustainable organisational performance.

Theoretical Foundation: Human Capital and Resource-Based Views

For a systematic account of the structural dimensions of talent management across this particular cluster, the empirical model must be anchored in established organisational theories. Human Capital Theory (Becker, 1962) and the Resource-Based View (RBV; Barney, 1991) are the most applicable here (MNC Mining Study, 2024). Human Capital Theory asserts that the time and money spent on employees' education, training, and skill preparation are investments that pay off in greater productivity for both the individual and the organisation (Becker, 1962; MNC Mining Study, 2024). Simultaneously, the Resource-Based View holds that an organisation can attain a sustainable competitive advantage only when it possesses resources that are valuable, rare, inimitable, and irreplaceable (Barney, 1991; MNC Mining Study, 2024).

Applied to the Surat diamond industry, the specialised, highly articulated, and refined skills of local diamond cutters and polishers (traditionally called ratna-kalakars) meet RBV’s criteria (Purani & Mehta, 2000; Rose, 2022). Uncut diamonds are a raw material that is a consolidated, traded good. The entire value enhancement and all resulting profit margins are almost exclusively attributable to the skill and ability of the diamond cutters and polishers during the planning, bruting, and polishing phases (Purani &Mehta, 2000; Rose, 2022). Thus, systematic talent management practices are the main mechanisms for developing, energising, optimising, and maintaining these valuable human resources (MNC Mining Study, 2024). This study combines these theories into a mathematical construct to demonstrate how talent attraction, development, and retention are utilised within a highly specialised, labour-intensive, emerging-economy cluster.

The Inclusive vs. Differentiated Talent Management Dilemma in Emerging Clusters

One of the primary focuses of current human resource literature is whether companies should utilise an “inclusive” or “differentiated” talent management strategy (Dries, 2013; MNC Mining Study, 2024). An “inclusive” strategy involves potential talent development for the entire workforce at all levels, and a “differentiated” strategy concentrates talent management resources on a small percentage (3-5%) of the workforce who are the highest performing and occupy “critical” positions that provide a competitive edge for the organization (Collings et al., 2019; Dries, 2013; MNC Mining Study, 2024).

Economic clusters in developing markets, such as the Surat diamond industry, have the potential to implement both strategies. The inclusive development of most workers in the diamond industry is supported by the fact that most are skilled artisans, and their collective productivity reflects the quality of the final product (Purani &Mehta, 2000; Rose, 2022). There are certain critical positions, including the role of the first “planners” who use advanced technology and software. These positions are differentiated by productivity and involve planning laser cuts on imperfect rough crystals, with software directing placement and minimising waste (Purani &Mehta, 2000; Rose, 2022). This study addresses this duality by validating a structural model that incorporates broad motivation and development strategies, while focusing on differentiated, high-value, retention and succession strategies.

The Socio-Economic Realities of Surat's Ratna-Kalakars

In Surat, to understand workers' motivation and talent retention, we must understand the industry’s human component. Surat is the world’s diamond-processing centre, with 80% to 90% of the world’s diamonds processed there (Ray, 2019; Rose, 2022). This export industry is supported by around 800,000 direct diamond cutters and polishers working in over 6,000 diamond-cutting and polishing units, largely located in the Varachcha and Katargam urban centres (Rose, 2022). The majority of the units’ employees are settled migrants from the dry regions of Saurashtra in Gujarat and a growing number of inter-state migrants from Bihar, Uttar Pradesh and Madhya Pradesh (Rose, 2022; Engelshoven, 1999).

Industry-generated wealth is significant, yet there is evidence of a growing gap between unit owners' prosperity and the precarity of the workforce (Varkkey & Kumar, 2013; Rose, 2022). The industry is highly unorganised, with 96% of units unregistered, unregulated, and family-owned; thus, workers face greater economic exposure (Arora, 2014; Rose, 2022). Workers endure poor working conditions for 10-12-hour shifts, during which they are restricted from moving freely and are provided with no formal social protection (Rose, 2022). High occupational stress is leading to eye strain. Chronic back pain is also a common complaint, as workers are not provided with adequate seating and are required to switch positions frequently (Rose, 2022). The unceremonious, mass layoffs of the global diamond skilled workforce continue to constitute a crisis. The workforce also experiences wage theft, especially after the 2008 crisis, the 2016 demonetization, and the COVID-19 sanctions (Varkkey &Kumar, 2013; Rose, 2022). The financial stress is leading to a surge in suicides, especially in the workforce community of Surat. Police records show that there have been 5,000 suicides in Surat since 2010. Many of those suicides also occurred among diamond workers who are deeply in debt (Dhodi & Dua, 2025). There has been a lack of structural research around talent management practices in Surat (Bolander, 2017; Rose, 2022; Varkkey & Kumar, 2013).

Research Gap

There is a significant research gap regarding the empirical application of talent management frameworks to informal, unorganised industrial clusters in emerging economies, despite the contemporary human resource literature having thoroughly examined these frameworks in developed, formal corporate contexts (Farndale et al., 2022).

Prior studies on talent management in India have mostly concentrated on formal, highly structured industries including banking, information technology, real estate, pharmaceuticals, and the automobile sector (Kehinde, 2012; Farndale, Agarwal & Budhwar, 2022). The unorganised sector, on the other hand, continues to receive little attention, both theoretically and practically, even though it employs the great majority of workers in emerging economies.

Additionally, there is a significant gap between business and social literature due to the extreme fragmentation of current studies on the Surat diamond sector. Sociological and labour studies have qualitatively documented the significant precarity, occupational health risks, and difficult socioeconomic conditions faced by Surat's migrant “ratna-kalakars” (Rose, 2022; Engelshoven, 1999). Conversely, traditional business literature concentrates on the cluster's marketing mix techniques, kin-based networking, and entrepreneurial innovation (Purani &Mehta, 2000; Kothari, 2014).

Empirical, quantitative studies on formal talent management concepts such as Attraction, Motivation, Retention, and Succession Planning are largely lacking in contexts of severe constraints (such as untrained labour and limited capital). By verifying a second-order Confirmatory Factor Analysis (CFA) model, this study fills this gap by offering an empirical link between macroeconomic labour precarity and microeconomic firm-level strategic talent strategies in Surat.

Research Methodology

Bright workers are no longer constrained to marketing their skills inside a single region due to globalisation; instead, they can now hunt for jobs in organisations around the world. Experts are concerned about fierce competition for talent and are focusing on the recruitment, retention, development, and management of talent (Tucker, 2009). With effective marketing techniques, diamond company businesses can overcome market hurdles (Kothari, 2014).

Given the scarcity of research on the functions of talent management methods and their effects on organisational performance, it is a particularly fascinating subject to explore. There are very few studies that can establish a connection between talent management techniques and their influence on organisational performance in the diamond sector, which is an issue in the Indian organisational literature. As a result, the current study sought to address a knowledge gap and provide a clearer understanding of how talent management strategies affect organisational performance in the Surat diamond sector.

Research Hypotheses

The following theories are developed to guide the higher-order Confirmatory Factor Analysis (CFA) measurement model, based on fundamental human resource development constructs and the localised structural realities of Surat's diamond units. We hypothesise that the overall multidimensional construct of "Talent Management" is positively associated with and structurally represented through five main dimensions in a second-order factor model:

H1: Talent Attraction and talent management tactics are positively correlated in the Surat diamond industry.

H2: Talent Retention and talent management tactics are positively correlated in the Surat diamond industry.

H3: Learning & Development and talent management tactics are positively correlated in the Surat diamond industry.

H4: Motivation and talent management tactics are positively correlated in the Surat diamond industry.

H5: Succession Planning and talent management tactics are positively correlated in the Surat diamond industry.

Methods

In this case, survey analysis and primary data are used in conjunction with the research tool. Compared with other data collection methods, such as interviews, survey research is less efficient but more accurate and quicker. This survey instrument was developed by modifying existing or freshly developed questionnaires to assess the research constructs. 457 employees who work in the Diamond units of Surat City were used as the sample population for the survey.

The initial values of Alpha, an indicator of the instrument's internal consistency, were determined to be within acceptable limits and are shown in Table 1.

Table 1 Reliability Test
Construct	Cronbach's Alpha	No. of Items
Talent Attraction (TA)	0.916	11
Learning and Development (LD)	0.905	7
Motivation (Motiv)	0.815	7
Talent retention (TR)	0.902	9
Succession Planning (SP)	0.835	7

Structural Equation Modelling (SEM)

The second-generation technique for examining the interactions between constructs with several elements in the model is structural equation modelling (SEM). The study employed a two-stage SEM approach, which included validating latent constructs through Confirmatory Factor Analysis (CFA) prior to modelling the structural model and conducting SEM for hypothesis testing. SEM, or synonymously Covariance-Structure Modelling, is a powerful multivariate statistical analysis procedure that employs a parametric approach for its data analysis.

Confirmatory Factor Analysis (CFA)

The study conducted Confirmatory Factor Analysis (CFA) to validate five latent constructs involved in the study, namely Talent attraction (11 items), Learning & Development (7 items), Motivation (6 items), Talent Retention (9 items), and Succession Planning (5 items) (shown in Figure 1), which presents the results after executing the Pooled-CFA procedure.

Assessment of the Constructs' Validity and Reliability

Construct Validity: All three types of fitness indices—Absolute Fit (RMSEA=0.058), Incremental Fit (CFI = 0.915), and Parsimonious Fit (Chisq/Df = 2.524)—were obtained from the fitness indices produced in Figure 1. Therefore, the criteria for construct validity have been met.

Reliability: The first column (shown in Table 2), CR, which stands for "Composite Reliability," displays the accuracy of the study's measuring scale. The threshold value is 0.7. As can be observed, all components' CR values were higher than 0.7, demonstrating the validity of the measurement tool in this case: the questionnaire.

Table 2 Construct Validity
	CR	AVE	MSV	MaxR(H)	MOTIV	TR	TA	LD	SP
MOTIV	0.849	0.49	0.263	0.862	0.699
TR	0.963	0.743	0.188	0.964	0.169	0.862
TA	0.92	0.513	0.113	0.928	0.336	0.28	0.716
LD	0.91	0.599	0.263	0.937	0.513	0.434	0.326	0.774
SP	0.836	0.508	0.08	0.85	0.238	0.176	0.042	0.283	0.712

Convergent Validity: The AVE column, which stands for "Average Variance Extracted," indicates convergent validity. Convergent validity must be established by AVE values greater than or equal to 0.5 for all variables, as demonstrated in this study (see Table 2). It means that the five latent elements are adequately described by the underlying variables. All variance extraction values—ranging from 49.0% to 74.3% for the five components—were higher than the 0.5 threshold (Hair et al., 2012b).

Discriminant Validity: Because all MSV values were lower than the corresponding AVE values (shown in Table 2), discriminant validity is proven. Following scale validation, a hierarchical second-order Confirmatory Factor Analysis (CFA) model was tested. The objective is to demonstrate that the multidimensional latent constructs of Talent Attraction, Learning and Development, Motivation, Talent Retention, and Succession Planning statistically converge into a single, higher-order construct of "Talent Management" which governs firm behaviour. The standardised regression estimates generated in AMOS are detailed in Table 3. All standardised factor loadings are exceptionally high and statistically significant (p < 0.001). Learning and Development (Estimate = 1.617) exhibits the strongest structural loading, closely followed by Talent Retention (Estimate = 1.203) and Talent Attraction (Estimate = 1.025). Motivation (Estimate = 0.880) and Succession Planning (Estimate = 0.480) also present highly significant structural pathways, thereby confirming the empirical validity of our main hypothesised pathways Figure 2.

Table 3 Talent Management Model: Second-Order Regression Estimates
Structural Pathway	Beta Estimate (β)	Std. Error (S.E.)	Critical Ratio (C.R.)	P-value	Decision
Motiv <-- TM	1				Significant
TA <-- TM	0.629	0.099	6.344	***	Significant
LD <-- TM	1.617	0.21	7.688	***	Significant
TRS <-- TM	1.203	0.167	7.182	***	Significant
SP <-- TM	0.48	0.094	5.088	***	Significant

Results and Discussion

The purpose of the article was to examine how five factors—talent acquisition, learning and development, retention, motivation, and succession planning—are impacted by talent management. According to Table 3, there is a considerable association between the two variables examined in testing their respective hypotheses.

Learning and Development's greatest loading factor (Estimate = 1.617) resolves a key theoretical conflict. A regional, unofficial "Gujarat Model of Entrepreneurial Innovation" was described in traditional literature on Surat diamond refining (Purani and Mehta, 2000). This conventional approach relied on unstructured, hands-on "roll-over skills," where trainees sat next to older artisans during the task. Skills were passed through community-based networks, primarily Saurashtrian Patidar (western peninsular region of Gujarat) kinship networks (Purani and Mehta, 2000; Rose, 2022). Our high statistical loading of LD demonstrates that modern Surat units have successfully systematised these practices. Modern factories have converted unstructured roll-over training into extremely rigid, specialised in-house programs in order to stay competitive in processing asymmetrical rough stones and imperfect crystals. They employ laser-cutting simulators, computer-aided design (CAD) software, and strict 4P (blocking, rounding, bottoming, and shining) skill stages (Rose, 2022). As a result, the cluster has developed into an institutionalised, high-density learning ecosystem from kin-based apprenticeship.

Additionally, Whitney Johnson's (2018) Career S-Curve framework can be used to interpret the highly significant factor loadings for Talent Retention (1.203) and Succession Planning (0.480) (Kidwai, 2025). A Surat diamond craftsman's career path consists of three distinct phases: (1) the apprentice launch point, which is marked by low piece-rate wages and high failure rates; (2) the artisan sweet spot, where the ratna-kalakar reaches maximum manual speed and precision; and (3) the plateau, where senior artisans experience back issues, eye conditions, and cognitive stagnation, which reduces their polishing productivity (Varkkey &Kumar, 2013; Rose, 2022; Nishant Engelshoven, 1999). In the past, informal employers would abandon artisans who reached this plateau, resulting in a significant loss of tacit knowledge. The empirical validation of Succession Planning as a core element in our model shows that units are actively working to preserve this important information. Units successfully preserve their priceless experience while reorganising S-curve routes for the younger generation by transitionally succession-planning senior craftsmen into crucial management, mentoring, or highly technical rough-planning responsibilities (using cutting-edge Sarin software) (Rose, 2022).

Conclusion

Using data from 457 employees, this study validated a second-order confirmatory factor analysis (CFA) model of talent management practices in the Surat diamond industry. The results confirmed that talent attraction, learning and development, talent retention, motivation, and succession planning collectively constitute the higher-order construct of talent management, and that the measurement model demonstrated adequate reliability and validity.

The findings underscore the need for an integrated talent management approach to improve employee development, retention, and organisational effectiveness. The study contributes to the limited literature on talent management in the Indian diamond industry by providing a validated measurement framework that can support both researchers and practitioners.

The study is limited to diamond units in Surat and uses a cross-sectional design, which may limit generalizability. Future research should consider other industries and geographical locations, use longitudinal research designs, and examine the effects of talent management practices on outcomes such as employee engagement, organisational commitment, and organisational performance. In general, the study emphasises the strategic importance of talent management in the organisation's sustainable success.

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Received: 30-July-2026, Manuscript No. AMSJ-26-17356; Editor assigned: 01-Aug-2026, PreQC No. AMSJ-26-17356(PQ); Reviewed: 14-Aug-2026, QC No. AMSJ-26-17356; Revised: 21-Aug-2026, Manuscript No. AMSJ-26-17356(R); Published: 28-Aug-2026