Abstract
Purpose
The human resource and talent management fields have been increasingly focusing on the process and criteria to identify employees’ potential for career advancement due to their impact on the competitive advantage of organizations. This paper expands the extant theoretical and empirical evidence regarding these complex decisions, namely through the combined analysis of multidimensional sources of employees' capital.
Design/methodology/approach
This is a cross-sectional study. Data were collected from 384 individuals assessed by their line managers. The research model and hypotheses were tested using structured equation modeling.
Findings
The results show a positive and significant influence of four employees’ capital sources, namely: human capital (what you know), social capital (whom you know), psychological capital (who you are) and reputational capital (how others perceive us) with regard to judgments of potential for career advancement. The model explains 52% of the total variance in those judgments.
Research limitations/implications
The data were collected using a questionnaire at a single point in time and thus, not allowing cause-effect inferences.
Practical implications
The results provide guidance to organizational leaders to improve the decision-making process regarding judgments of potential for career advancement.
Originality/value
To our knowledge, this is the first study to examine managers’ judgments regarding the potential for career advancement using four sources of employees' capital: human, social, psychological and reputational capital. Furthermore, it considers that reputation plays a mediation role.
研究目的
:在人力資源和人才管理的領域裡,越來越多的焦點被放在找出員工職業發展所需潛能的過程和標準上,這是因為機構和組織的競爭優勢會受其影響。本文擬擴展關於這類複雜的判斷和決定的現存理論和經驗證據; 研究人員使用的方法為對員工資本的多維來源進行綜合分析。
研究設計/方法/理念
:本研究為橫斷面研究。數據來自384 名受其直線經理評估的個別員工; 研究人員使用了結構方程模型,去測試其研究模型和各個假設。
研究結果
:研究結果顯示,就員工職業發展所需潛能的判斷而言,存在著會帶來正面和重大影響的四個員工資本來源,這包括人力資本 (你所瞭解的事物) 、社會資本 (你所認識的人物) 、心理資本 (你是誰) 和聲譽資本 (我們予人的印象) 。有關的模型可說明判斷百分之五十二的總方差。
研究的局限/啟示
:由於數據的收集是於單一時間點和透過問卷調查而完成的,故未能收因果推斷的效果。
實務方面的啟示
:研究結果給予組織領袖實際的指引,使他們在關於職業發展所需潛能的判斷上，能夠改善其決策的過程。
研究的原創性/價值
:就我們所知,本研究為首個研究、以四個員工資本來源,即人力資本、社會資本、心理資本和聲譽資本,去探討經理如何就職業發展所需的潛能作出判斷; 而且，本研究認為聲譽是扮演著調節角色的。
Keywords
Citation
Botelho, C. (2024), "The impact of multiple sources of employees’ capital on judgments regarding potential for career advancement", European Journal of Management and Business Economics, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/EJMBE-12-2022-0379
Publisher
:Emerald Publishing Limited
Copyright © 2024, Carlos Botelho
License
Published in European Journal of Management and Business Economics. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Academic and business literature show that talent management (TM) has become a key part of human resource management (HRM) and human resource development (HRD) strategies in contemporary organizations (Cappelli and Keller, 2017; Jooss et al., 2021a; McDonnell et al., 2017). A key argument for positioning talent and its management as a source of competitive advantage can be found in the resource-based view (RBV) of the firm theory (Collings et al., 2017a; Collins, 2021; Harsch and Festing, 2019).
The TM practices are crucial for ensuring employees’ career outcomes as well as HRM/HRD effectiveness, among which stand out the evaluation of employees’ promotability or potential for career advancement (PCA) and the criteria used for identifying high-potential (HP) employees (Collings et al., 2017a; Finkelstein et al., 2018). Furthermore, it has been acknowledged that organizations with reliable processes for predicting employees’ PCA tend to acquire a competitive advantage (Hollenbeck and Jamieson, 2015; Jooss et al., 2021b). The assessment of employees’ potential entails a highly complex process that encompasses making decisions based on present estimates about something that can only be verified in the future and observing something that only exists in a small percentage of employees (Finkelstein et al., 2018; Jooss et al., 2021b; Silzer and Church, 2009). The predominant perspective on TM associates the concept of HP with employees’ readiness to achieve career advancement, thus expressing employees’ capability to assume, in the future, positions of greater complexity and responsibility (Cascio et al., 2017; McDonnell et al., 2017; Silzer and Church, 2010).
Furthermore, extant literature on HRM and HRD has considered different employees’ capital sources – namely, human, social and emotional or psychological – as relevant determinants of employees’ career advancement and success (Gratton and Ghoshal, 2003; Järlström et al., 2020; Luthans et al., 2007; Rabenu, 2021). Other characteristics have been suggested in the academic literature – for example, Sparrow et al.’s (2015) definition of talent includes reputational capital as well (RC).
This research responds to the recent call from HRM/TM scholars for more applied studies identifying criteria for making accurate predictions about how successful an employee might be in the long term. This fundamental research problem is related to two specific research questions:
What is the incremental impact of each source of employees’ capital, i.e. human capital, social capital, psychological capital and reputational capital, regarding the decisions on PCA?
What is the type of relationship between the three traditional sources of employees’ capital – human, social and psychological – and the emergent reputational capital?
This study has four main contributions to the HRM/HRD field. First, it presents a multidimensional framework using the concept of capital as a lens for understanding PCA judgments. Second, it analyzes the incremental or relative value of different sources of employees' capital for determining PCA. Third, it offers new evidence about the mediation role of RC with regard to human, social and psychological capital’s influences on PCA. Finally, to our best knowledge, no extant study has analyzed these sources as part of a common framework for TM decisions.
The paper is organized as follows: we begin by presenting an extensive review of the literature on HRM/HRD, TM and promotability judgments, from which we then build our hypotheses and research model. Next, we present and explain the methodology used in the study. Then, the study’s main findings are presented and interpreted. The paper ends with a discussion of the theoretical and managerial implications and possible directions for future research.
2. Literature review and hypotheses
In contemporary organizations, managing people effectively is widely recognized as a critical competitiveness factor (Lawler, 2017; Silzer and Church, 2010; Skuza et al., 2021). Thus, the strategic role played by talent in ensuring organizational success and the HR practices necessary for attracting, developing and retaining workforce talent have emerged as core themes in HRM/HRD and TM (Gallardo-Gallardo et al., 2020; Jooss et al., 2021a; Khoreva et al., 2017). Despite this emphasis, there is scant evidence that most organizations have successfully managed talent (Collings, 2014; Collings et al., 2017b; Meyers et al., 2013) and understood who should be considered a talent and why (Harsch and Festing, 2019; Skuza et al., 2021).
To address the aforementioned challenges, it is necessary to clarify the concept of talent. There are two main approaches or philosophies in this regard: one focuses on managing the talent of all employees (inclusive approach) and the other focuses on managing the talent of a sub-group of high-potential or high-performing employees (an exclusive approach) (Kwon and Jang, 2021; Thunnissen, 2016). Due to the growing interest in workforce differentiation, we will adopt the exclusive perspective in this study, which has increasingly dominated academic and business literature on TM (Collings et al., 2017b; Kwon and Jang, 2021). This approach can facilitate a more deliberate utilization of organizational resources so that employers can invest substantially greater resources in the ones they believe will offer higher returns; it necessarily involves the proactive identification of employees with the potential to fill key positions within the organization structure (Crowley-Henry et al., 2019; Day and O’Connor, 2017).
One recurring TM issue is determining the organization’s talent pool. This group of employees includes both high performers who are now serving in strategic job roles and HP employees who may do so in the future (Jooss et al., 2021b; Lawler, 2017; McDonnell and Skuza, 2022). One major challenge in identifying HP employees is the inherent complexity of making predictions about how successful a person might be in the long term. It involves defining what one is trying to predict, assessing a person against the appropriate criteria and making predictions about future performances (Silzer and Borman, 2017; Silzer and Church, 2009, 2010).
Due to the strategic and critical impact of workforce talent, organizations are finding it increasingly important to accurately assess their employees’ potential; thus, they need to increase the validity and accuracy of such assessments (MacRae et al., 2018; McDonnell and Skuza, 2022). The extant literature offers a vast and diverse list of factors that can be considered as possible components of potential, which might be useful for developing an assessment framework (Church et al., 2015; Finkelstein et al., 2018; MacRae et al., 2018). Two early, large reviews of organizational practices (Silzer and Church, 2009, 2010) put together a list of factors that organizations often use to identify HP. These include leadership competencies, performance records, motivation to advance, results orientation, risk taking, adaptability/flexibility, experience, learning ability, commitment to the organization, personality and positive attitudes. It is noteworthy that the underlying model for determining potential has raised the assumption that employees who are perceived as HP generally have the capability to learn, grow and develop (McDonnell and Skuza, 2022; Meyers et al., 2013).
Other scholars, such as Sparrow et al. (2015), who have looked at HRM literature through the lens of talent and the concept of capital, have suggested that it is important to assess three perspectives: human capital (stock of competencies and knowledge, social and personality attributes); social capital (the sum of the resources that can be mobilized through membership in social networks) and reputational capital (for example, being known in one’s network for getting things done). Similarly, previous work by Gratton and Ghoshal (2003) built a model of so-called personal human capital, which contained three elements: intellectual capital (knowledge, skills and expertise), social capital (structure and quality of relationship networks) and emotional capital (courage and resilience with regard to taking actions).
By combining these approaches, we can collate sufficient robust theoretical and empirical support for considering a multidimensional framework of employees’ capital that encompasses human and social capital (the two most common features) and two other sources, namely, reputation and emotional or psychological capital.
First, human capital (HC), which encompasses the productive resources possessed by workers, overall refers to their knowledge, work experiences, skills and abilities, which are necessary for achieving superior performance (Dokko and Jiang, 2017; Järlström et al., 2020). The literature provides empirical evidence of positive relations between HC and several employees’ outcomes (e.g. future performance potential and career success) (Ballout, 2007; De Vos and Chambré, 2017; Spurk et al., 2019).
Second, social capital (SC) encompasses the relationships between organizational members. It is based on the capacity of employees to create, transfer and leverage knowledge between internal (employees and managers) and external contacts. This can help improve working conditions and individual and organizational performance (Dokko and Jiang, 2017; Seibert et al., 2017; Tamer et al., 2014). The size and quality (trust) of the network of relationships built by one employee may be considered a form of capital in the sense that it can create a productive resource for accessing and facilitating employee performance. Trust is often mentioned as a key aspect of SC because it facilitates the functioning of the network, opens communication channels and promotes knowledge sharing. Empirical data suggest that it facilitates teamwork and collaboration (Tsai and Ghoshal, 1998) and improves employees’ performance (Wang et al., 2015).
Third, psychological capital (PC) has a multidimensional nature, and its four building blocks are hope, self-efficacy, optimism and resilience (Kauffeld and Spurk, 2022; Luthans et al., 2007). Overall, there is a good amount of evidence to suggest that PC is linked to a number of individual and organizational outcomes, such as performance, citizenship behaviors and the quality of social connections (Kauffeld and Spurk, 2022; Tamer et al., 2014). It is assumed that PC has incremental value beyond the two more traditional sources of HC and SC.
In summary, HC, SC and PC can influence performance and career progression (Greenhaus and Kossek, 2014; Kauffeld and Spurk, 2022). Furthermore, Xu et al. (2023) conclude that the three types of capital interact with each other and synergistically influence individual career development. According to the multiple regression analysis, PC has the biggest impact, then SC and HC. Other recent studies, for example, Huang et al. (2021) and Xu et al. (2022), found that when HC, PC and SC were added to the regression equation, the model increased its explanation power.
In line with previous studies, we predict the following set of hypotheses:
HC is positively related to employees’ PCA.
SC is positively related to employees’ PCA.
PC is positively related to employees’ PCA.
Fourth, a relevant stream of literature claims that career decisions are made within a social context and that personal reputation – that is, how others perceive us (Blickle et al., 2011; Zinko et al., 2017). According to Greenhaus and Kossek (2014), a professional career is built through a pattern of consistent behaviors, performance and work experiences that unfold throughout an employee’s life in their organization. Employees who are perceived to be proficient and to have high levels of certain competencies and aptitudes will have a better chance of being promoted and achieving success in their careers (Laird et al., 2013; Zinko and Rubin, 2015; Zinko et al., 2017). According to Zinko et al. (2012, 2016), an employee’s reputation capital (RC) is based on how consistently other people perceive them to act, which is mostly influenced by the results they get and the character and integrity they have shown.
Hence, we hypothesize the following:
RC is positively related to employees’ PCA.
Fifth, the literature on RC has referred to both HC and SC as antecedent variables. HC influences employee reputation based on the levels of knowledge, competencies and achievements displayed by the employees; SC refers to the quality of employees’ social interactions and the degree of control they wield over their social networks. Even though PC has gotten less attention, it is also likely related to employees' professional reputation because it affects how well they do their jobs, which is important to how others perceive them (Kauffeld and Spurk, 2022; Luthans et al., 2007; Zinko et al., 2012).
Furthermore, we focused on considering the HC, SC and PC as relevant antecedent factors of RC, i.e. the building of our reputation by relevant others, for the purpose of our study, the managers who mostly have a decision on who is promotable or not in the organization.
Therefore, we made the following hypothesis:
HC, SC and PC are antecedent factors of RC.
HC is positively related to RC.
SC is positively related to RC.
PC is positively related to RC.
Finally, HRM/HRD literature pays special attention to the promotion process. This subject is an as yet incomplete area of academic research with regard to our understanding of antecedents and related variables (Claussen et al., 2014; Jawahar and Ferris, 2011; Ren et al., 2019; Seibert et al., 2017). Promotion decisions tend to be driven by individuals’ readiness to move to a higher job – what is referred to as promotability judgments. According to studies that have been done on these kinds of decisions (Ferris et al., 1992; Gurbuz et al., 2016; Sibunruang and Kawai, 2022), performance evaluations, organizational politics, potential assessments, reputation and interpersonal relationships are all important in making decisions.
In the organizational context, promotions signal career success. When individuals are perceived as being promotable, they are considered to possess the necessary capabilities for performing roles of higher responsibility in the future (Bagdadli and Gianecchini, 2019; Slizer and Borman, 2017). According to empirical research, elements like the relationship between manager and employee, challenging work opportunities, one’s reputation, citizenship behaviors and political skills can all have a positive impact on career progression decisions (Blickle et al., 2011; Gentry et al., 2012; Seibert et al., 2017).
The developmental perspective associated with the concept of career could be related to the notion of potential, since it should be based not only on an analysis of current performance but also on the capacity to perform well in the future, at a higher level and in jobs with a greater amount of responsibility (Collings et al., 2017a; Collings and Mellahi, 2009). Furthermore, reputational capital can hinder or facilitate employees’ career progression based on their social representation and the manner in which they make the most of their organizational political environment (Blickle et al., 2011; Zinko et al., 2012; Zinko and Rubin, 2015).
Hence, we propose the following hypothesis:
RC mediates the association between human (H6a), social (H6b) and psychological (H6c) capital and employees' PCA.
Figure 1 illustrates the theoretical research model built to synthesize the above-mentioned variables and their effects, as well as the resulting hypotheses.
3. Method
3.1 Sample and data collection procedures
This cross-sectional study collected data through a survey in order to obtain the perceptions of relevant persons (line managers) regarding focal individuals' qualities of HC, SC, PC, RC and PCA judgments. One manager evaluated each focal individual. Our goal was to get a large and diverse sample of workers so that we could generalize our results to the Portuguese context.
The sample was formed using two different approaches: first, we addressed 150 HR managers from medium- and large-sized private organizations from different economic sectors in Portugal through LinkedIn. This procedure ensures that only organizations with formal HRM practices are contacted. In 68 cases, those who accepted were asked to identify two or three qualified employees and send their line managers the link to the survey. Second, we gathered additional data from two other medium-sized firms with the assistance of the HR manager, who chose a group of employees and invited their managers to participate in the study.
The organization’s workforce size ranged from 50 to 250 (62%), 250 to 1.000 (29%) and more than 1.000 (9%).
Our final sample included 384 valid individuals, excluding cases where the assessor had not worked for a minimum of one year with the focal person and the current performance was rated below average – consistent with our exclusive TM approach. This group had the following characteristics: knowledge workers in jobs requesting a degree or managers; an average age of 35.83 years (ranging from 20 to 55 years old) and 56% female and 44% male.
The survey utilized scales available in academic literature after making the necessary adjustments to reflect this study’s objectives. We employed a conventional double-back translation strategy in which a qualified bilingual translator translated the original English items into Portuguese before translating them back into English. The variables were measured using a seven-point Likert-type scale: 1 (“totally disagree”) to 7 (“totally agree”).
3.2 Measures
Human capital (HC) – HC was assessed using two different measures: first, a five-item scale that Zinko et al. (2012) suggested using the concept of expertise. We slightly reworded the items in order to adapt them for use in more general contexts; two examples of items are “She/he is an expert at his/her job” and “She/he gives good technical suggestions.” Second, we used the prospector, an instrument that McCall et al. (1994) developed. It measures employees’ competencies and ability to learn from experience (Silzer and Borman, 2017) using 11 dimensions: seeks opportunities to learn, acts with integrity, adapts to cultural differences, is committed to making a difference, seeks broad business knowledge, brings out the best in people, is insightful, has the courage to take risks, seeks and uses feedback, learns from mistakes and is open to criticism. To control the survey length, we used only the operational description for each dimension.
Social capital (SC) – SC was measured based on two dimensions: the quality of relationships and the type and size of employees’ contacts with relevant sources. The former is a six-item scale adapted from McAllister (1995), which covers both the cognitive and affective dimensions of interpersonal trust. Some examples of such items are as follows: “If I shared my problems with this person, I know (s)he would respond constructively and caringly” and “This person approaches his or her job with professionalism and dedication.” The latter measures employees’ social networks (Dokko and Jiang, 2017; Seibert et al., 2017), and it includes their internal relationships with colleagues and managers – both in their own department and other areas of the organization – and external contacts (customers, suppliers and other organizations).
Psychological capital (PC) – PC was measured based on the four dimensions of the construct of psychological capital (PsyCap) developed by Luthans et al. (2007). To keep our questionnaire a reasonable length, we used only one operational description of each of the following dimensions: hope, efficacy, resilience and optimism.
Reputational capital (RC) – RC was measured using ten items from a 12-item scale that was originally developed by Hochwarter et al. (2007) and later used in a study by Zinko et al. (2012). The two deleted items were recommended in this latter study. A few examples are as follows: “This individual is regarded highly by others” and “This individual is regarded as someone who gets things done.”
Potential for career advancement (PCA) – The measure of promotability was inspired by two proposals used in studies conducted by Jawahar and Ferris (2011) and Gurbuz et al. (2016). We used three items to reflect the criteria of ability, motivation and opportunity (along with the AMO theory in HRM, Day and O’Connor, 2017) to assess progress in a career. The items were as follows: “This person demonstrates the ability necessary for successfully performing jobs at a higher level of responsibility,” “This person has the necessary ambition for successfully performing jobs at a higher level of responsibility” and “This person will progress (move up) in their career in this organization.”
3.3 Control variables
Consistent with previous studies, we aimed to verify the potential influence of two demographic variables related to our sample: age and gender. Since no significant differences were identified in the sample, we excluded them from our data analysis.
3.4 Data analysis
We analyzed the study data using the structure equation modeling (SEM); we used SPSS and AMOS version 25 to conduct the analysis. The analysis was carried out in three phases. First, we tested each variable’s measurement model. Second, we tested the proposed theoretical model’s goodness-of-fit and compared it with alternative models, then tested our hypotheses. Third, we analyzed the mediating hypotheses, using the Sobel’s test to examine the statistical significance of the indirect effects. This test is recommended for testing the significance of a mediation effect in SEM, which is the case with our RC variable. We used Hayes’s macro-PROCESS version 4.0.2 (Hayes, 2022), which gives us percentile and bias-corrected bootstrap (5,000 bootstraps for percentile bootstrap confidence intervals) confidence intervals for drawing conclusions about indirect effects in models with a mediation component. We also used the Sobel test.
4. Results
4.1 Measurement model
The initial step consisted of performing confirmatory factor analysis (CFA) for the different measures that were part of the full model by using some of the most common fit indices, comparative fit index (CFI), goodness of fit index (GFI), normed fit index (NFI) and root mean square error of approximation (RMSEA) to test the quality of the adjustment (Hair et al., 2018). Additionally, we considered the χˆ2/df ratio, ideally ranging from less than three to a maximum of five. All the measures exhibited overall acceptable properties (see Table 1). The factorial solutions revealed that for the measure of HC a second-order general factor that includes the scales of expertise and ability to learn; for SC, a second-order general factor that consists of interpersonal trust and social network; and for PC, RC and PCA, general factors based on the respective first-order indicators.
Furthermore, the descriptive statistics (means, standard deviations, alpha values and intercorrelations) for all the variables are shown in Table 2. The evidence supports the presence of good reliabilities (as measured by a Cronbach’s alpha, with all of the cases exceeding the cut-off point of 0.70); furthermore, there was no evidence of possible constraints due to the non-normality of the multivariate data based on kurtosis and skewness, which were suggested to be close to 0 with no case of skewness >2 and kurtosis >7. However, since all the data came from the same respondents, the variance inflation factor (VIF) and tolerance were used to check for multicollinearity risks. The VIF scores were between 2.251 and 4.014 and the tolerance scores were between 0.249 and 0.397. These values were in line with what Hair et al. (2018) recommends.
4.2 Structural models
An SEM methodology was used for testing the theoretical research model (Figure 1) and the associated hypotheses. We analyzed the theoretical research model (where all paths relating to the constructs were estimated). This model did not show acceptable adjustment indices, CFI, GFI, NFI and RMSEA below the recommended threshold values. In order to get a better adjustment for the research model, the data analysis suggested deleting the effect of SC on PCA (Figure 2). This updated model displays excellent fit indices, namely CFI, GFI and NFI above 0.95 and RMSEA below 0.05. Furthermore, the three alternative models that were used for comparison against this baseline model displayed much worse fit indices (Table 3). These models were as follows: (1) the four factors of personal capital with independent effects on PCA; (2) HC, SC and PC forming a latent common factor with a mediated effect on PCA through RC and (3) the four factors of personal capital forming a common latent factor with a direct effect on PCA. Accordingly, we proceeded with all further analyses (hypotheses and overall model) based on the adjusted theoretical model (see Figure 2, which illustrates the path model and the measurement results with the standardized path coefficients and the adjusted R2 values).
4.3 Hypothesis testing
The findings show that the theoretical model explained 52% of the PCA judgments. Moreover, all four types of personal capital – human, social, psychological and reputational – had a direct and/or indirect effect that was important and meaningful.
All the hypotheses, with one exception, were confirmed, thus providing support for the relevance of the four personal capital sources in forming managers’ perceptions of employees’ potential for career advancement.
There was only one case that did not show a significant direct effect on our endogenous variable (PCA), and that was SC (despite its moderate-high correlation of 0.56). Two of the three partial mediation effects foreseen by the theoretical model were confirmed. The only one that did not occur was the effect of SC over RC with regard to PCA (H6 b). On the other hand, the study findings confirmed the partial mediation effect of RC over HC and PC, which effects employees’ PCA (H6 a) and H6 c) (see the Sobel tests presented below).
Our results also demonstrate that, when considering the effects on RC, the dominant effect is of SC, β = 0.41, while the other two variables, HC and PC, exhibit equal effects of β = 0.27. On the whole, these three variables explain 75% of RC. However, when the target variable is the PCA, we see significant direct effects from HC, β = 0.23, PC, β = 0.37 and RC, β = 0.19.
5. Discussion
5.1 General conclusions and theoretical implications
One fundamental research question and two main objectives served as the study’s guiding principles. To start, its main goal was to add to the existing theoretical and empirical evidence on two major topics in HRM/HRD literature: the “what” and “how” of using the TM process to give companies a competitive edge (Claussen et al., 2014; McDonnell et al., 2017; Ren et al., 2019). Thus, using the perspective of TM, we have highlighted the need for stronger theoretical frameworks and more effective assessment models of talent (Lacey and Groves, 2021; McDonnell and Skuza, 2022).
First, the current study aimed to improve understanding of the role of HR practices in applied studies on TM, specifically employee potential assessment and career management. One key focus area is the search for ways to improve decision makers' ability to make informed decisions on TM issues so that organizations can maximize their investments in HC (Kravariti and Johnston, 2020; Robledo-Ardila and Román-Calderón, 2022). Criteria used by organizations to determine the so-called HP (Crowley-Henry et al., 2019; Silzer and Church, 2010) play an important role in these decisions.
Second, it is derived from a research perspective that seeks to explore a definition of talent based on the concept of employees’ capital. Gratton and Ghoshal (2003), Luthans et al. (2007), Sparrow et al. (2015) and Zinko et al. (2016), among others, have looked at different sources of human, social, and emotional or psychological capital as important predictors of employees' career advancement and success.
Considering these aims, our study adopted and tested a model that describes and measures employees’ capital from a multidimensional perspective – that is, by including four capital sources: HC (what you know); SC (whom you know); PC (who you are) and RC (how others perceive us). Our findings support the existence of a positive and significant influence from these four sources on the assessment of career advancement potential. This evidence reinforces previous arguments for the use of multidimensional models, which are closely related to a more holistic view of potential (Cascio et al., 2017; Sparrow et al., 2015).
We contend that our theoretical contribution is a threefold.
First, our results make an important contribution to the study of what causes employees' PCA and help to clarify the decision criteria used to find HP employees (Jawahar and Ferris, 2011; Robledo-Ardila and Román-Calderón, 2022). By doing so, our study expands current knowledge by focusing on one particular sub-system of HRM, high potential identification, contributing to what Storey et al. (2019) claimed to be the need to have studies focused on “HR targeting practices.”
Second, by finding the connections between the human, social, psychological and reputational capital sources of employees, we broaden the debate about what makes someone talented and what gets them promoted. Our results add to what other studies (Huang et al., 2021; Xu et al., 2022, 2023) have found about how three types of employee capital – HC, SC and PC – affect career development and job performance in the field of TM. In particular, they fill in the gaps about their relevance in identifying the potential for career advancement.
Third, the findings regarding personal reputation’s role as a source of employees’ capital may be useful for expanding the conceptual debate about its nature, thus highlighting both its “hard” roots (knowledge, skills and other attributes) and a more “relational” view. It is very illuminating to understand this double facet of reputation, especially considering that HC and PC combined have a greater influence than SC in forming managers’ perceptions of employees’ reputation. Therefore, personal reputation is a valid and useful construct when it comes to managing talent. Therefore, we put forward conceptual and empirical evidence to clear up the construct as well as rule out the risk of its subjective nature.
5.2 Managerial implications
From a management point of view, the results of this study may be of interest to organizational leaders who are looking for ways to get the most out of their TM policies and practices to improve business performance and gain a competitive edge (Crowley-Henry et al., 2019). Also, these results may help organizations look at their current criteria for including people in the HP pool and link management tools in use to the four types of capital that employees have.
Another important suggestion for organizational leaders is the fact that these findings could also help to clarify that assessing PCA is a complex, multidimensional phenomenon that should encompass a variety of criteria (Finkelstein et al., 2018; Skuza et al., 2021).
This study emphasizes the technical and social nature of this process and supports personal reputation as a valid core component, minimizing its conceptual and empirical overlap with impression management tactics. It also shows how each source of employees' capital affects career outcomes in a unique way when integrated into a common framework, as they often do in organizations.
In addition, our study may be of interest to HR managers who want to strengthen their strategic roles. Boudreau and Ramstad (2005) say that this effort will be an important step in maximizing the contribution of the HR function to organizational decision-making and performance.
Furthermore, the study can benefit the underlying transparency of this critical HRM process by bringing the perception of fairness to the forefront of this management decision. By doing so, we can have the expectation that society will be better able to create the right opportunities for people to achieve their potential and also make the best use of collective human capital.
5.3 Limitations and suggestions for future research
We must emphasize that, despite the substantial effects of our four predictors – HC, SC, PC and RC – in explaining judgments regarding employees’ PCA (52% of variance), we strongly recommend that future research use the necessary caution in the interpretation of results, especially with regard to the causal model that is tested in the theoretical research model. Given our use of cross-sectional data, no causal inferences could be made with regard to the relationships in this study, although the relationships depicted in our research model were based on a sound theoretical framework – that is, capital as productive resources. So, any future research studies that use a longitudinal design will help the field by looking at how being considered for a promotion at a certain point in time can really help employees move up in the organization faster and higher than others.
Another study limitation could be attributed to our data collection method and its potential for bias; additionally, even though we exercised caution by collecting data from an external assessor (line managers), we were unable to completely eliminate bias. In the future, researchers could look into a variety of assessors.
Third, regarding this study’s utilized measures, we suggest some caution in considering the psychological capital scale because, due to the length of our questionnaire, we opted to use an operationalization based on the four dimensions definition; thus, we are not testing the PsyCap inventory.
Finally, using a profile method analysis, it would be interesting to closely examine the dynamics between the four personal capital sources.
6. Conclusion
The current study contributes some novel ideas to the talent management theory and practice, particularly in the context of talent pools. It is the only empirical study to date that has looked at the combined impact of HC, SC, PC and RC on employee assessment of their potential for career advancement. Our findings also contribute to a better understanding of the underlying mechanisms of reputational capital and show how it mediates the effects of HC, SC and PC on PCA. It also emphasizes the significance of focusing on what Luthans et al. (2007) defined as a synergistic integration of human, social and psychological capital in order to realize human potential. Finally, the study sheds light on an important empirical question: what is the optimal combination of key characteristics of high-potential employees? Skuza et al. (2021).
Figures
Evaluation of measurement models for the constructs used in the study
| Variables | χ2 | df | p | χ2/df | NFI | CFI | GFI | RMSEA/IC LO |
|---|---|---|---|---|---|---|---|---|
| Human capital – two factors a) | 183.692 | 92 | 0.000 | 1.997 | 0.939 | 0.969 | 0.951 | 0.049/0.038 |
| Social capital – two factors b) | 74.574 | 28 | 0.000 | 2.663 | 0.964 | 0.977 | 0.967 | 0.063/0.046 |
| Psychological capital – four factors c) | 7.762 | 2 | 0.021 | 3.881 | 0.988 | 0.991 | 0.991 | 0.083/0.038 |
| Reputational capital – ten factors d) | 82.247 | 27 | 0.000 | 3.046 | 0.973 | 0.965 | 0.965 | 0.070/0.053 |
| Potential for career advancement – three factors e) | 3.306 | 2 | 0.191 | 1.653 | 0.991 | 0.995 | 0.995 | 0.039/0.000 |
Note(s): a) This factor solution is based on a second-order general factor that includes the scales of expertise and ability to learn
b) This factor solution is based on a second-order general factor that includes the scales of interpersonal trust and social network
c) This factor solution is based on a general factor comprising four first-order factors
d) This factor solution is based on a general factor comprising ten first-order factors
e) This factor solution is based on a general factor comprising three first-order factors
Source(s): Table by the author
Descriptive statistics and correlations for the constructs used in the study
| Variables | Mean | SD | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|---|
| Human capital – two factors | 5.01 | 0.68 | (0.83) | ||||
| Social capital – two factors | 5.09 | 0.73 | 0.81 | (0.72) | |||
| Psychological capital – four factors | 4.97 | 0.81 | 0.72 | 0.68 | (0.83) | ||
| Reputational capital – ten factors | 5.19 | 0.79 | 0.80 | 0.81 | 0.74 | (0.94) | |
| Potential for career advancement – three factors | 4.94 | 0.87 | 0.64 | 0.56 | 0.67 | 0.64 | (0.79) |
Note(s): Internal consistency reliabilities are in parentheses along the diagonal. All correlations are significant at the 0.01 level (two-tailed)
Source(s): Table by the author
Fit indices for structural models
| Structural models | χ2 | df | p | χ2/df | NFI | CFI | GFI | RMSEA |
|---|---|---|---|---|---|---|---|---|
| Updated theoretical model | 1.580 | 1 | 0.209 | 1.580 | 0.994 | 0.998 | 0.998 | 0.037 |
| Alternative Model 1 a) | n.a | n.a | n.a | n.a | n.a | n.a | n.a | n.a |
| Alternative Model 2 b) | 41.447 | 4 | 0.000 | 10.362 | 0.837 | 0.847 | 0.952 | 0.149 |
| Alternative Model 3 c) | 41.821 | 5 | 0.000 | 8.364 | 0.836 | 0.850 | 0.951 | 0.132 |
Note(s): a) the four factors of personal capital with independent effects on PCA
b) HC, SC and PC forming a latent common factor with a mediated effect on PCA through RC
c) The four factors of personal capital forming a common latent factor with a direct effect on PCA and, n.a. – not adjusted
Source(s): Table by the author
References
Bagdadli, S. and Gianecchini, M. (2019), “Organizational career management practices and objective career success: a systematic review and framework”, Human Resource Management Review, Vol. 29 No. 3, pp. 353-370, doi: 10.1016/j.hrmr.2018.08.001.
Ballout, H.I. (2007), “Career success: the effects of human capital, person-environment fit and organizational support”, Journal of Managerial Psychology, Vol. 22 No. 8, pp. 741-765, doi: 10.1108/02683940710837705.
Blickle, G., Schneider, P.B., Liu, Y. and Ferris, G.R. (2011), “A predictive investigation of reputation as mediator of the political-skill/career-success relationship”, Journal of Applied Social Psychology, Vol. 41 No. 12, pp. 3026-3048, doi: 10.1111/j.1559-1816.2011.00862.x.
Boudreau, J.W. and Ramstad, P.M. (2005), “Talentship, talent segmentation, and sustainability: a new HR decision science paradigm for a new strategy definition”, Human Resource Management, Vol. 44 No. 2, pp. 129-136, doi: 10.1002/hrm.20054.
Cappelli, P. and Keller, J.R. (2017), “The historical context of talent management”, in Collings, D.G., Mellahi, K. and Cascio, W.F. (Eds), The Oxford Handbook of Talent Management, Oxford University Press, Oxford, pp. 23-40.
Cascio, W.F., Boudreau, J.W. and Church, A.H. (2017), “Using a risk-optimisation lens: maximizing talent readiness for an uncertain future”, in Sparrow, P. and Cooper, C.L. (Eds), A Research Agenda for Human Resource Management, Edward Elgar, Cheltenham, pp. 55-77.
Church, A.H., Rotolo, C.T., Ginther, N.M. and Levine, R. (2015), “How are top companies designing and managing their high-potential programs? A follow-up talent management benchmark study”, Consulting Psychology Journal: Practice and Research, Vol. 67 No. 1, pp. 17-47, doi: 10.1037/cpb0000030.
Claussen, J., Grohsjean, T., Luger, J. and Probst, G. (2014), “Talent management and career development: what it takes to get promoted”, Journal of World Business, Vol. 49 No. 2, pp. 236-244, doi: 10.1016/j.jwb.2013.11.007.
Collings, D.G. (2014), “Toward mature talent management: beyond shareholder value”, Human Resource Development Quarterly, Vol. 25 No. 3, pp. 301-319, doi: 10.1002/hrdq.21198.
Collings, D.G. and Mellahi, K. (2009), “Strategic talent management: a review and research agenda”, Human Resource Management Review, Vol. 19 No. 4, pp. 304-313, doi: 10.1016/j.hrmr.2009.04.001.
Collings, D.G., Mellahi, K. and Cascio, W.F. (2017a), “Introduction”, in Collings, D.G., Mellahi, K. and Cascio, W.F. (Eds), The Oxford Handbook of Talent Management, Oxford University Press, Oxford, pp. 3-22.
Collings, D.G., McDonnell, A. and McMackin, J. (2017b), “Talent management”, in Sparrow, P. and Cooper, C.L. (Eds), A Research Agenda for Human Resource Management, Edward Elgar Publishing, Cheltenham, pp. 39-54.
Collins, C.J. (2021), “Expanding the resource-based view model of strategic human resource management”, The International Journal of Human Resource Management, Vol. 32 No. 2, pp. 331-358, doi: 10.1080/09585192.2019.1711442.
Crowley-Henry, M., Benson, E. and Al Ariss, A. (2019), “Linking talent management to traditional and boundaryless career orientations: research propositions and future directions”, European Management Review, Vol. 16 No. 1, pp. 5-19, doi: 10.1111/emre.12304.
Day, D.V. and O'Connor, P. (2017), “Talent development: building organizational capability”, in Collings, D.G., Mellahi, K. and Cascio, W.F. (Eds), The Oxford Handbook of Talent Management, Oxford University Press, Oxford, pp. 343-360.
De Vos, A. and Chambré, B. (2017), “Career management in high performing organizations: a set-theoretic approach”, Human Resource Management, Vol. 56 No. 3, pp. 501-518, doi: 10.1002/hrm.21786.
Dokko, G. and Jiang, W. (2017), “Managing talent across organizations: the portability of individual performance”, in Collings, D.G., Mellahi, K. and Cascio, W.F. (Eds), The Oxford Handbook of Talent Management, Oxford University Press, Oxford, pp. 115-133.
Ferris, G.R., Buckley, M.R. and Allen, G.M. (1992), “Promotion systems in organizations”, Human Resource Planning, Vol. 15 No. 3, pp. 47-68.
Finkelstein, L.M., Costanza, D.P. and Goodwin, G.F. (2018), “Do your high potentials have potential? The impact of individual differences and designation on leader success”, Personnel Psychology, Vol. 71 No. 1, pp. 3-22, doi: 10.1111/peps.12225.
Gallardo-Gallardo, E., Thunnissen, M. and Scullion, H. (2020), “Talent management: context matters”, The International Journal of Human Resource Management, Vol. 31 No. 4, pp. 457-473, doi: 10.1080/09585192.2019.1642645.
Gentry, W.A., Gilmore, D.C., Shuffler, M.L. and Leslie, J.B. (2012), “Political skill as an indicator of promotability among multiple rater sources”, Journal of Organizational Behaviour, Vol. 33 No. 1, pp. 89-104, doi: 10.1002/job.740.
Gratton, L. and Ghoshal, S. (2003), “Managing personal human capital: new ethos for the ‘volunteer’ employee”, European Management Journal, Vol. 21 No. 1, pp. 1-10, doi: 10.1016/s0263-2373(02)00149-4.
Greenhaus, J.H. and Kossek, E.E. (2014), “The contemporary career: a work–home perspective”, Annual Review of Organizational Psychology and Organizational Behavior, Vol. 1 No. 1, pp. 361-388, doi: 10.1146/annurev-orgpsych-031413-091324.
Gurbuz, S., Habiboglu, O.S. and Bingol, D. (2016), “Who is Being Judged Promotable: good actors, high performers, highly committed or birds of a feather?”, International Journal of Selection and Assessment, Vol. 24 No. 2, pp. 197-208, doi: 10.1111/ijsa.12141.
Hair, J., Anderson, R., Black, B. and Babin, B. (2018), Multivariate Data Analysis (8th ed.), Cengage, Hampshire.
Harsch, K. and Festing, M. (2019), “Dynamic talent management capabilities and organizational agility—a qualitative exploration”, Human Resource Management, Vol. 59 No. 1, pp. 43-61, doi: 10.1002/hrm.21972.
Hayes, A.F. (2022), Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach, 3rd ed., Guilford Press, New York.
Hochwarter, W.A., Ferris, G.R., Zinko, R., Arnell, B. and James, M. (2007), “Reputation as a moderator of the political behavior–work outcomes relationships: a two-study investigation with convergent results”, Journal of Applied Psychology, Vol. 92 No. 2, pp. 567-576, doi: 10.1037/0021-9010.92.2.567.
Hollenbeck, J.R. and Jamieson, B.B. (2015), “Human capital, social capital, and social network analysis: implications for strategic human resource management”, The Academy of Management Perspectives, Vol. 29 No. 3, pp. 370-385, doi: 10.5465/amp.2014.0140.
Huang, S.S., Yu, Z., Shao, Y., Yu, M. and Li, Z. (2021), “Relative effects of human capital, social capital and psychological capital on hotel employees' job performance”, International Journal of Contempary Hospitality Management, Vol. 33 No. 2, pp. 448-466, doi: 10.1108/ijchm-07-2020-0650.
Järlström, M., Brandt, T. and Rajala, A. (2020), “The relationship between career capital and career success among Finnish knowledge workers”, Baltic Journal of Management, Vol. 15 No. 5, pp. 687-706, doi: 10.1108/bjm-10-2019-0357.
Jawahar, I.M. and Ferris, G.R. (2011), “A longitudinal investigation of task and contextual performance influences on promotability judgments”, Human Performance, Vol. 24 No. 3, pp. 251-269, doi: 10.1080/08959285.2011.580806.
Jooss, S., Burbach, R. and Ruël, H. (2021a), “Examining talent pools as a core talent management practice in multinational corporations”, The International Journal of Human Resource Management, Vol. 32 No. 11, pp. 2321-2352, doi: 10.1080/09585192.2019.1579748.
Jooss, S., McDonnell, A. and Burbach, R. (2021b), “Talent designation in practice: an equation of high potential, performance and mobility”, The International Journal of Human Resource Management, Vol. 32 No. 21, pp. 4551-4577, doi: 10.1080/09585192.2019.1686651.
Kauffeld, S. and Spurk, D. (2022), “Why does psychological capital foster subjective and objective career success? The mediating role of career-specific resources”, Journal of Career Assessment, Vol. 30 No. 2, pp. 285-308, doi: 10.1177/10690727211040053.
Khoreva, V., Vaiman, V. and Van Zalk, M. (2017), “Talent management practice effectiveness: investigating employee perspective”, Employee Relations, Vol. 39 No. 1, pp. 19-33, doi: 10.1108/er-01-2016-0005.
Kravariti, F. and Johnston, K. (2020), “Talent management: a critical literature review and research agenda for public sector human resource management”, Public Management Review, Vol. 22 No. 1, pp. 75-95, doi: 10.1080/14719037.2019.1638439.
Kwon, K. and Jang, S. (2021), “There is no good war for talent: a critical review of the literature on talent management”, Employee Relations: The International Journal, Vol. 44 No. 1, pp. 94-120, doi: 10.1108/er-08-2020-0374.
Lacey, M. and Groves, K. (2021), “Approaches to developing high-potential talent”, in Tarique, I. (Ed.), The Routledge Companion to Talent Management, Routledge, London, pp. 457-470.
Laird, M.D., Zboja, J.J., Martinez, A.D. and Ferris, G.R. (2013), “Performance and political skill in personal reputation assessments”, Journal of Managerial Psychology, Vol. 28 No. 6, pp. 661-676, doi: 10.1108/jpm-10-2011-0097.
Lawler, E.E. III. (2017), Reinventing Talent Management, Berrett-Koehler, Oakland.
Luthans, F., Youssef, C.M. and Avolio, B.J. (2007), Psychological Capital: Developing the Human Competitive Edge, Oxford University Press, Oxford.
MacRae, I., Furnham, A. and Reed, M. (2018), High Potential: How to Spot, Manage and Develop Talented People at Work, 2nd ed., Bloomsbury, London.
McAllister, D.J. (1995), “Affect and cognition-based trust as foundations for interpersonal cooperation in organizations”, Academy of Management Journal, Vol. 38 No. 1, pp. 24-59, doi: 10.2307/256727.
McCall, M.W., Spreitzer, G.M. and Mahoney, J. (1994), Identifying Leadership Potential for Future International Executives: A Learning Resource Guide, University of Southern California: School of Business Administration, Lexington.
McDonnell, A. and Skuza, A. (2022), “Talent spotting: a review of meanings and identification tools”, in Tarique, I. (Ed.), The Routledge Companion to Talent Management, Routledge, New York, pp. 435-444.
McDonnell, A., Collings, D.G., Mellahi, K. and Schuler, R.S. (2017), “Talent management: a systematic review and future prospects”, European Journal of International Management, Vol. 11 No. 1, pp. 86-128, doi: 10.1504/ejim.2017.10001680.
Meyers, M.C., van Woerkom, M. and Dries, N. (2013), “Talent - innate or acquired? Theoretical considerations and their implications for talent management”, Human Resource Management Review, Vol. 23 No. 4, pp. 305-332, doi: 10.1016/j.hrmr.2013.05.003.
Rabenu, E. (2021), Twenty-first Century Workplace Challenges, Lexington Books, London.
Ren, S., Yang, F. and Wood, R. (2019), “How work-related capabilities influence job performance: a relational perspective”, The International Journal of Human Resource Management, Vol. 30 No. 7, pp. 1157-1180, doi: 10.1080/09585192.2017.1288154.
Robledo-Ardila, C. and Román-Calderón, J.P. (2022), “Potential: in search for meaning, theory and avenues for future research a systematic review”, Management Review Quarterly, Vol. 72 No. 1, pp. 149-186, doi: 10.1007/s11301-020-00207-4.
Seibert, S.E., Sargent, L.D., Kraimer, M.L. and Kiazad, K. (2017), “Linking developmental experiences to leader effectiveness and promotability: the mediating role of leadership self-efficacy and mentor network”, Personnel Psychology, Vol. 70 No. 2, pp. 357-397, doi: 10.1111/peps.12145.
Sibunruang, H. and Kawai, N. (2022), “The instrumental role of employee voice in achieving promotability: social influence perspective”, Personnel Review, Vol. 52 No. 3, pp. 687-702, doi: 10.1108/pr-05-2020-0332.
Silzer, R. and Borman, W. (2017), “The potential for leadership”, in Collings, D.G., Mellahi, K. and Cascio, W.F. (Eds), The Oxford Handbook of Talent Management, Oxford University Press, Oxford, pp. 87-114.
Silzer, R. and Church, A.H. (2009), “The pearls and perils of identifying potential”, Industrial and Organizational Psychology, Vol. 2 No. 4, pp. 377-412, doi: 10.1111/j.1754-9434.2009.01163.x.
Silzer, R. and Church, A.H. (2010), “Identifying and assessing high-potential talent”, in Silzer, R. and Dowell, B.E. (Eds), Strategy-driven Talent Management: A Leadership Imperative, Jossey-Bass, CA, pp. 213-279.
Skuza, A., Zaharie, M. and Scullion, H. (2021), “Talent management: contemporary issues”, in Wilkinson, A., Dundon, T. and Redman, T. (Eds), Contemporary Human Resource Management, 6th ed., Sage, London, pp. 532-556.
Sparrow, P., Martin, H. and Cooper, C. (2015), De We Need HR? Repositioning People Management for Success, Palgrave Macmillan, Hampshire.
Spurk, D., Hirschi, A. and Dries, N. (2019), “Antecedents and outcomes of objective versus subjective career success: competing perspectives and future directions”, Journal of Management, Vol. 45 No. 1, pp. 35-69, doi: 10.1177/0149206318786563.
Storey, J., Ulrich, D. and Wright, P.M. (2019), Strategic Human Resource Management: A Research Overview, Rutledge, London.
Tamer, I., Dereli, B. and Sağlam, M. (2014), “Unorthodox forms of capital in organizations: positive psychological capital, intellectual capital and social capital”, Procedia-Social and Behavioral Sciences, Vol. 152, pp. 963-972, doi: 10.1016/j.sbspro.2014.09.351.
Thunnissen, M. (2016), “Talent management: for what, how and how well? An empirical exploration of talent management in practice”, Employee Relations, Vol. 38 No. 1, pp. 57-72, doi: 10.1108/er-08-2015-0159.
Tsai, W. and Ghoshal, S. (1998), “Social capital and value creation: the role of intrafirm networks”, Academy of Management Journal, Vol. 41 No. 4, pp. 464-476, doi: 10.5465/257085.
Wang, C., Yen, C. and Liu, G.H.W. (2015), “How intellectual capital influences individual performance”, Computers in Human Behavior, Vol. 51, pp. 930-937, doi: 10.1016/j.chb.2014.10.044.
Xu, Q., Hou, Z., Zhang, C., Yu, F., Guan, J. and Liu, X. (2022), “Human capital, social capital, psychological capital, and job performance: based on fuzzy-set qualitative comparative analysis”, Frontiers in Psychology, Vol. 13, 938875, doi: 10.3389/fpsyg.2022.938875.
Xu, Q., Hou, Z., Zhang, C., Cui, Y. and Hu, X. (2023), “Influences of human, social, and psychological capital on career adaptability: net and configuration effects”, Current Psychology, Vol. 43 No. 3, pp. 2104-2113, doi: 10.1007/s12144-023-04373-y.
Zinko, R. and Rubin, M. (2015), “Personal reputation and the organization”, Journal of Management and Organization, Vol. 21 No. 2, pp. 217-236, doi: 10.1017/jmo.2014.76.
Zinko, R., Ferris, G.R., Humphrey, S.E., Meyer, C.J. and Aime, F. (2012), “Personal reputation in organizations: two‐study constructive replication and extension of antecedents and consequences”, Journal of Occupational and Organizational Psychology, Vol. 85 No. 1, pp. 156-180, doi: 10.1111/j.2044-8325.2010.02017.x.
Zinko, R., Gentry, W.A. and Laird, M.D. (2016), “A development of the dimensions of personal reputation in organizations”, International Journal of Organizational Analysis, Vol. 24 No. 4, pp. 634-649, doi: 10.1108/ijoa-04-2015-0854.
Zinko, R., Furner, Z.Z., Hunt, J. and Dalton, A. (2017), “Establishing a reputation”, Journal of Employment Counseling, Vol. 54 No. 2, pp. 87-96, doi: 10.1002/joec.12056.