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Purpose

The main goal of the article is to identify, analyze and diagnose the relationships between employer branding (EB) and company performance results in multinational companies (MNCs) from the perspectives of their headquarters (HQs) and foreign subsidiaries in both non-crisis and crisis times, with the latter specifically referring to the COVID-19 pandemic period. Additionally, it is to reveal how the strategic approaches to EB adopted by these entities have influenced their ability to navigate and thrive during these two periods.

Design/methodology/approach

The empirical research included 200 MNCs from Central Europe. A computer-aided telephone interviewing (CATI) method was used for data collection. The raw data were converted using the efficiency index (EI) to accurately delineate the relationships between the variables under study. The research hypotheses were examined, and the mediating effects were assessed through partial least squares structural equation modeling (PLS-SEM).

Findings

The research findings provide valuable insights by exploring the mediating role of human resources management (HRM) outcomes between EB and company performance results, emphasizing HRM’s crucial role in enhancing results in finance, innovativeness and quality, particularly during crises. They underscore the strategic importance of HRM and EB in fostering organizational performance and resilience.

Practical implications

The findings offer actionable insights for various business practitioners, including managerial staff across different levels, specialists, business partners and managers and directors of HR departments. The evidence supports the notion that investment in EB serves not only immediate goals related to workforce management but also contributes to long-term strategic objectives. For MNCs, the study highlights the importance of contextualized and localized EB strategies that address the unique operational, cultural and regulatory environments of foreign subsidiaries, enhancing global performance.

Originality/value

The study introduces a novel methodological innovation by employing the EI for accurately quantifying the relationships between EB, HRM and company performance outcomes. However, the greatest added value of this article is the creation of the Crisis-Responsive EB-HRM Mediation Theory for MNC Performance and Resilience.

Employer branding (EB), sometimes called employer brand management, is the response of enterprises to competitive labor markets (Junça Silva and Dias, 2023; Poór et al., 2025), and recently to the intensification of such phenomena as Employee Great Resignation, Quiet Quitting (Stor, 2023b, pp. 96–97), Career Cushioning, and Loud Quitting (Gallup, 2023, p. 4), signaling a shift in employee behavior and expectations. It aims to attract and retain suitable employees to achieve organizational goals and competitive advantage (Rana et al., 2021) by aligning HRM and marketing practices (Ambler and Barrow, 1996; Deepa and Baral, 2019), leveraging brand equity and resource-based views, and focusing on building beneficial relationships between employers and employees (Cascio, 2014). Employer branding involves developing a unique employment value proposition (Backhaus, 2016) and marketing it to distinguish a company as a desirable employer both internally (Deepa and Baral, 2021) and externally (Foster et al., 2010). The idea is to become an employer of choice (Rampl, 2014). It affects not only potential and current employees but also managers and former employees, contributing to an organization’s attractiveness (Lievens and Slaughter, 2016).

It is anticipated that EB will have a beneficial effect on an organization’s performance. Nevertheless, some argue that EB does not have a direct impact on company performance (Theurer et al., 2018), whereas other researchers in their studies assert that such a direct effect can indeed be identified (Azhar et al., 2024). Yet, studies indicate that EB can indirectly influence company performance by enhancing HRM outcomes (Aldousari et al., 2017), which are closely linked to the overall business success (Tumasjan et al., 2020). This implies that the positive outcomes stemming from HRM initiatives focused on EB can significantly contribute to enhancing company performance (Huseynova et al., 2022).

However, the role, importance, and activities within both EB and HRM can vary significantly depending on the type of organization, whether it operates domestically or internationally (Baum and abst, 2013), and the specific challenges it encounters (c.f. Wang et al., 2022). Therefore, contextualization can play a crucial role (Sheehan and Shanahan, 2017), a concept particularly postulated in the area of HRM in multinational companies (MNCs) (Farndale and Paauwe, 2018). Undoubtedly, the most complex situation is faced by MNCs during a crisis of global scale (c.f. Tkalac Verčič and Špoljarić, 2023). These companies encounter unparalleled complexity during global crises due to their operations across varied regulatory, cultural, and economic landscapes (Farndale and Paauwe, 2018). This multifaceted environment necessitates tailored HRM (Špoljarić and Ozretić Došen, 2023) and EB strategies (Japutra et al., 2024) to navigate market volatilities, regulatory differences, and geopolitical risks (c.f. Gunnigle et al., 2013). Consequently, maintaining a strong EB is crucial for attracting and retaining talent, ensuring resilience (Newman et al., 2023), and fostering engagement (Kunerth and Mosley, 2011) across their global workforce during such periods (Hamouche, 2021).

In this context, the main goal of the article is to identify, analyze, and diagnose the relationships between EB and company performance results in MNCs from the perspectives of their headquarters (HQs) and foreign subsidiaries in both non-crisis and crisis times, with the latter specifically referring to the COVID-19 pandemic period. This goal will be achieved by discussing the findings of empirical research conducted on 200 Central European MNCs. This analysis aims to reveal how the strategic approaches to EB adopted by these organizations, both at their HQs and across their overseas units, have influenced their ability to navigate and thrive during periods of stability as well as in the face of global disruptions such as the pandemic.

In response to the main goal of the article as stated, the research provides compelling evidence that strategic EB practices play a crucial role in enhancing organizational resilience and performance, particularly in times of crisis. By analyzing the impacts from both HQs and foreign subsidiary perspectives, the study offers valuable insights into the complexities of managing EB in a multinational context and underscores the importance of tailored, context-sensitive EB strategies for achieving superior performance outcomes.

This study contributes to the management science by revealing the mediating role of HRM outcomes in the relationships between EB and company performance results. It also provides empirical evidence that supports the significance of EB and HRM practices in enhancing company performance, especially in times of crisis. The findings underscore the value of investment in EB as an integral component of HRM. Additionally, the use of employee key performance indicators (KPIs) as the efficiency index in analyzing the effect of the variables under study represents a novel approach. This new tool has been recently developed and used in research on employee performance appraisal (Stor, 2023c) and leadership talent management (Haromszeki, 2024). Its application marks a significant advancement in the field of management science, providing a versatile tool for measuring and analyzing the efficiency and impact of HRM practices, including EB, on organizational performance and achieved results. However, the greatest added value of this article is considered to be the creation of the Crisis-Responsive EB-HRM Mediation Theory for MNC Performance and Resilience, which is presented in its final section.

The structure of the article is as follows. It begins by presenting the theoretical framework, established through a review of existing literature. Next, it details the methods used in the empirical research. After that, it presents the results of the empirical study. In conclusion, the article summarizes the research findings and addresses the study’s limitations before outlining its contribution to management theory and busies practice.

As mentioned in the Introduction, literature raises doubts about the direct impact of EB on company performance (Theurer et al., 2018) due to its activities overlapping with HRM activities (Schuler and Jackson, 2014). However, while some researchers look for mediating variables (A Tumasjan et al., 2020), others have found specific direct relationships (Azhar et al., 2024).

In our conceptual framework, we assume that EB, understood as one of the subfunctions of HRM, can influence directly company performance results, based on several core principles. Our starting point is the definition we have adopted for EB, which posits that employer branding, also called employer brand management, is a set of activities the organization undertakes with the intention of promoting, distinguishing, and preserving its image on the internal and external labor market as an attractive and preferred employer, and thus, focused on current and potential employees to acquire and retain the right people in the organization, thanks to whom the organization is able to realize its goals and strategies. Thus, the overarching goal is to become an employer of choice (Stor, 2023b, p. 252). While traditional definitions of EB rooted in relationship marketing emphasized its role in attracting and retaining talent (Ambler and Barrow, 1996), recent research underscores its evolution into a strategic asset integral to organizational resilience and performance (Azhar et al., 2024). In the context of MNCs, where diverse cultural and operational landscapes present unique challenges, EB serves not only as a mechanism for talent management but also as a driver of adaptability and competitiveness. This study builds on these developments by examining EB’s differentiated effects across MNC contexts and periods, offering empirical evidence for its strategic significance.

As for the company performance results, in our framework, we distinguish between “company performance results” and “company performance,” focusing on the former as the ultimate outcomes of specific activities at a given moment in time. This contrasts with “company performance”, which we interpret as the processes through which these activities are executed (Stor, 2023b, p. 43). Regarding the results themselves, in our study they are categorized into four specific areas: HRM, finance, innovativeness, and quality.

The expectation of a direct impact of EB on selected categories of company performance results is grounded in the comprehensive role EB plays within an organization. Firstly, by effectively managing its employer brand, a company directly influences its attractiveness to high-caliber candidates (Lievens and Slaughter, 2016). This direct attraction translates into improved HRM outcomes, as the organization is more likely to hire and retain employees who align with its values and possess the requisite skills for driving performance (Chang et al., 2012). Secondly, in the financial domain, a strong employer brand can lead to cost savings through reduced turnover rates and lower recruitment costs, directly affecting the financial health of the company (Dženopoljac et al., 2023). Furthermore, a well-regarded employer brand fosters a culture of innovation by attracting creative and forward-thinking individuals (Špoljarić and Tkalac Verčič, 2022), thereby directly impacting the company’s innovativeness. Lastly, the quality of products and services (Schlager et al., 2011) is directly influenced by the level of employee engagement and motivation, which are outcomes of effective employer branding efforts (Kunerth and Mosley, 2011). Thus, the direct impact of EB on company performance results in these categories is both logical and expected, given its role in shaping the workforce that drives these results. Hence, one main hypothesis and four auxiliary hypotheses have been formulated to elucidate the relationships between EB and company performance results as follows.

H1.

EB directly and positively affects the company’s performance results.

H1A.

EB directly and positively affects the company’s performance results in HRM.

H1B.

EB directly and positively affects the company’s performance results in finance.

H1C.

EB directly and positively affects the company’s performance results in innovativeness.

H1D.

EB directly and positively affects the company’s performance results in quality.

HRM outcomes are anticipated to serve as a vital mediator in the relationships between EB and company performance results due to their integral position within the operational and strategic frameworks of an organization (Chang et al., 2012). This mediation stems from the understanding that effective HRM practices, shaped by a strong employer brand, can significantly enhance employee satisfaction, engagement (Kunerth and Mosley, 2011), and retention (Saini et al., 2022). These HRM outcomes, in turn, act as critical levers for improving performance across various domains including finance (Dženopoljac et al., 2023), innovativeness (Martin et al., 2011), and quality (Kim and Legendre, 2023).

A strong EB creates an environment that attracts (Cable and Turban, 2003) and retains top talent (Lievens and Slaughter, 2016), which is a fundamental HRM objective (Stor, 2023a). This talent is instrumental in driving the company’s financial success by contributing to increased productivity, innovation, and the delivery of high-quality products and services (Alnıaçık et al., 2014). Essentially, HRM outcomes serve as a conduit through which the positive effects of EB are channeled towards enhanced company performance. For instance, the alignment of EB with HRM practices ensures that employees are not only capable but also motivated to contribute their best efforts (Rampl, 2014), leading to improved financial results (Dženopoljac et al., 2023).

Similarly, a culture of innovation, fostered by a supportive and engaging employer brand (Kaur et al., 2024), is facilitated through HRM practices that encourage creativity and initiative among employees (McKeown, 2019). This culture is crucial for the development of new products and services, enhancing the company’s competitiveness and performance in innovativeness (Seeck and Diehl, 2017).

Furthermore, the quality of output, whether in terms of products, services, or customer interactions (Schlager et al., 2011), is heavily influenced by the level of employee engagement and commitment (Kunerth and Mosley, 2011). A well-managed EB, through effective HRM practices, ensures that employees are committed to the organization’s goals and quality standards (Sandeepanie et al., 2023), thereby directly impacting the company’s performance in quality (Schlager et al., 2011).

Following the aforementioned discussions, one primary hypothesis and three auxiliary hypotheses have been developed to explore the mediating role of HRM outcomes in the link between EB and company performance results. Additionally, it’s worth mentioning that for the purpose of maintaining consistent terminology, HRM outcomes are considered synonymous with the company’s performance results in HRM whenever HRM functions as a mediating variable. And the hypotheses are as follows.

H2.

The company’s performance results in HRM (HRM outcomes) mediate positively the relationships between EB and the company’s performance results.

H2A.

The HRM outcomes mediate positively the relationships between EB and the company’s performance results in finance.

H2B.

The HRM outcomes mediate positively the relationships between EB and the company’s performance results in innovativeness.

H2C.

The HRM outcomes mediate positively the relationships between EB and the company’s performance results in quality.

Research indicates that the role of HRM evolves significantly during crises (Johnstone, 2024), showcasing a dynamic shift in its impact on organizational performance (Ererdi et al., 2022). This evolution underlines the increasing importance of HRM’s strategic involvement in ensuring organizational resilience and adaptability, especially during turbulent times (Newman et al., 2023; Singh, 2024). As crises unfold, the agility and comprehensive approach of HRM to manage workforce needs become crucial in maintaining operational continuity and mitigating performance disruptions (Dubey et al., 2024).

In light of this, HRM’s mediation between EB and company performance results becomes increasingly pronounced during crises. This enhanced role is attributed to HRM’s capacity to adapt and innovate in response to emergent challenges, thereby ensuring that the employees remain engaged (Kunerth and Mosley, 2011), well-managed, and aligned with the organization’s strategic objectives (Sandeepanie et al., 2023). The agility of HRM practices in crisis situations (Moh’d et al., 2024) facilitates a stronger connection between EB initiatives and the realization of desired performance outcomes, emphasizing the strategic value of HRM in navigating through periods of uncertainty (Hamouche, 2021).

Given this backdrop, the necessity to explore the mediating role of HRM outcomes between EB and company performance results during crisis times becomes evident. This leads to the formulation of one main and three auxiliary hypotheses aimed at understanding the nuanced differences in HRM’s mediation effect between non-crisis and crisis periods.

H3.

During a crisis, the relationships between EB and the company’s performance results are mediated more strongly by the HRM outcomes than in non-crisis times.

H3A.

During a crisis, the relationships between EB and the company’s performance results in finance are mediated more strongly by the HRM outcomes than in non-crisis times.

H3B.

During a crisis, the relationships between EB and the company’s performance results in innovativeness are mediated more strongly by the HRM outcomes than in non-crisis times.

H3C.

During a crisis, the relationships between EB and the company’s performance results in quality are mediated more strongly by the HRM outcomes than in non-crisis times.

The role of HRM outcomes as a mediator grows more complex within MNCs (Špoljarić and Ozretić Došen, 2023) due to the diverse cultural and regulatory environments they operate in (Farndale and Paauwe, 2018), which can have a profound influence on the deployment and success of HRM strategies, EB included (Baum and Kabst, 2013). This complexity underscores the need for separate validation of the proposed hypotheses for the HQs of MNCs and their foreign subsidiaries (Sarkiunaite and Sciukauske, 2021). The unique operational, cultural, economic, and legal frameworks that subsidiaries find themselves in demand a customized approach to EB (Japutra et al., 2024), as what works in the HQs may not necessarily yield the same results in overseas markets (Sharma and Verma, 2023). Therefore, an in-depth analysis of EB’s role within both HQs and subsidiaries will offer more comprehensive insights into HRM outcomes’ mediation effect on company performance results in various contexts, crisis and non-crisis alike (c.f. Gunnigle et al., 2013). This approach will facilitate the development of more targeted and effective HRM strategies, catering specifically to the distinct requirements of each component of the MNC structure. Given these contextual differences, it is essential to investigate how the unique environments of HQs and foreign subsidiaries influence the effectiveness of EB strategies in driving company performance. Such analysis will provide nuanced insights into the strategic deployment of EB across these distinct organizational units. In light of this, the following hypothesis is proposed.

H4.

The effect of EB on company performance results will differ between HQs and subsidiaries.

The study outcomes discussed in this article stem from a broader investigative effort exploring the effects of 10 HRM subfunctions on company performance results. This text, adhering to its title, focuses explicitly on EB. The research, carried out in 2022, surveyed 200 non-financial MNCs with HQs in Central Europe (Poland). This section, reflecting the MNCs' Central European heritage (c.f. Sheehan and Buchelt, 2016; Poór et al., 2015), purposely employs “methodics” in its title to concentrate on particular aspects of the research endeavor. This choice of word sets it apart from “methodology”, which is understood as a wider academic field, following the definitions provided by Stor (2023b, p. 27) and adheres to the linguistic preferences of the region.

Drawing on data from the Polish Central Statistical Office, the chosen sample accounts for approximately 11% of the total category, boasting an 80% level of representativeness (Activity of enterprises …, 2022). The selection was meticulously made to mirror the economic sectors of the population as categorized by NACE, as well as by size and the nature of Foreign Direct Investment (FDI). This deliberate choice included MNCs with a global workforce of 76,740, overseeing more than 400 subsidiaries across roughly 30 countries, showcasing the expansive reach of the research.

This research utilized purposive sampling based on two primary considerations. Firstly, it was essential for the HQs and their foreign subsidiaries to predominantly be Polish-owned, guided by research suggesting that equity capital plays a vital role in shaping management decisions and strategies (Parry et al., 2021). This was intended to guarantee a uniform equity structure and management approach across the network, which is fundamental for benchmarking—an approach adopted in this study (Schlägel and Sarstedt, 2016). Secondly, the requirement was for the HQs and their subsidiaries to have been in operation for at least four years, allowing for the thorough examination of cause-and-effect relationships across varying circumstances, including both crisis and non-crisis situations.

The research employed Computer-Aided Telephone Interviewing (CATI) along with a structured questionnaire. It aimed at engaging respondents who had a deep understanding of company performance and HRM practices, ensuring they were well-acquainted with the pertinent measures (Richard et al., 2009). The group of respondents included business owners (1%), managing directors/CEOs (2%), HR directors (50%), HR managers (46%), and HR business partners (1%). They offered insights spanning two distinct periods: the pre-crisis time of 2018–2019 and the crisis span starting from early 2020 to the conclusion of Q1 2022, which matched the timing of the interviews.

The study focuses on four critical variables, detailed as follows.

  1. company performance results - analysis covers finance, innovativeness, quality, and HRM, with a comparison to peer organizations to understand performance;

  2. advancement level of EB - evaluates EB practices against the industry’s best, determining where they stand in terms of development;

  3. significance level of EB - focuses on the crucial role of EB practices in enhancing the company’s performance results;

  4. employee performance efficiency - reviews the efficiency of employees through the lens of established key performance indicators (KPIs).

The variables were assessed using a 5-point scale, as detailed in the lower section of Table 1, which provided standardized criteria for evaluating key metrics such as company performance results, employee performance efficiency, and the advancement and significance levels of EB. This approach specifically targeted the largest overseas subsidiary of an MNC to ensure comparability across entities.

The assessment was conducted through subjective benchmarking, rooted in self-evaluation, for two primary reasons. Firstly, the complexity of obtaining objective data on MNC subsidiary performance across diverse national contexts makes subjective managerial judgments a pragmatic alternative (Schlägel and Sarstedt, 2016). Secondly, such subjective assessments provide valuable contextual insights, enabling informants to reflect on performance through the lens of various factors and historical benchmarks (c.f. Richard et al., 2009). For example, performance was rated on a 5-point scale, enabling respondents to benchmark results relative to their industry peers while considering the unique circumstances of their operations.

It is important to recognize that numerous studies have shown the impact of HRM practices on the performance of both employees and organizations (Cascio et al., 2019; Garengo et al., 2022). However, improvements in productivity and achievements in KPIs do not invariably translate into increased profitability. This discrepancy can be attributed to various external factors such as labor market dynamics, competitive environments, and shifts in consumer preferences, a phenomenon particularly noted during significant economic downturns like the Great Recession and the COVID-19 crisis (Kim and Ployhart, 2014). While productivity plays a crucial role in facilitating resource allocation, growth, and innovation, its advantages can be constrained by these external influences. Consequently, there is a pressing need for research to delve deeper into the realms of action effectiveness and efficiency (Sharma and Singh, 2019) along with their resultant impacts (Zidane and Olsson, 2017). The concept of efficiency is tied to the judicious achievement of objectives (Rogers and Wright, 1998), quantified by the ratio of outputs to inputs (Stor, 2012), whereas effectiveness pertains to the attainment of specific goals and the degree of success in achieving these goals (Ostroff and Schmitt, 1993; Stor, 2012). Grasping the intricate relationship between EB, HRM practices, and the overall performance of organizations emerges as a significant research challenge.

To accurately delineate the actual interactions among the studied variables, specifically EB, HRM activities, and results of organizational performance, the raw data for these variables were refined using an efficiency index (EI). This distinctive and pioneering formula presented by the authors of this article has been previously applied in their earlier studies to examine connections between employee performance appraisal (Stor, 2023c), the management of leadership talent (Haromszeki, 2024), competency management (Stor and Haromszeki, 2024), managerial staff development (Stor, 2025) and company performance results. Consequently, the adjusted values for the EB variable were determined using formula (1), which calculates the ratio of EB’s advancement level to the efficiency of employees, assessed through KPIs employed in the examined organizations.

(1)

Where.

  • EI_EB - Efficiency index of employer branding

  • AL_EB – Advancement level of employer branding

  • EKPI – Employee key performance indicators

The recalculated values for the results of company performance were determined using the subsequent formula (2) which covers the ratio of the company performance results to the efficiency of employees measured by employee KPI used in companies:

(2)

Where.

  • EISCPR - Efficiency index of company performance results

  • (x) - one of the four categories of the company performance results, respectively in: human resources management (HRM), finance (F), innovativeness (I), and quality (Q).

  • CPR – Company performance results

  • EKPI – Employee key performance indicators

The formulas for calculating the values of distinct categories within the company performance results were crafted in a similar vein. Thus, in the referenced formula, relevant data regarding results in areas such as HRM, finance, innovativeness, and quality were used in substitution for (x).

The rationale behind employing the Efficiency Index lies in its ability to provide a standardized and efficiency-adjusted measure of EB and company performance results. Unlike raw performance indicators, which may exhibit scale-dependent variability and are influenced by exogenous variables such as firm size and resource allocation, the Efficiency Index helps isolate efficiency-driven mechanisms from absolute performance variations, ensuring a more standardized basis for comparison. By applying a ratio-based transformation, the index reduces scale-driven multicollinearity effects by normalizing performance measures relative to employee efficiency, which is particularly relevant in cross-sectional analysis of firm-level performance where heterogeneity must be accounted for. The incorporation of KPIs as a denominator functions as a normalization technique, analogous to ratio-based efficiency measures used in performance benchmarking, ensuring that employer branding advancements and company performance results are evaluated on a relative rather than an absolute scale, thereby reducing the influence of firm size and resource endowments. This approach improves the interpretability of mediation effects in structural equation modeling by accounting for differences in organizational scale and workforce efficiency, thereby enhancing robustness and external validity.

The analysis of the study’s data utilized descriptive statistics, correlations, and mediation analyses, starting with tests for normality (Kolmogorov-Smirnov and Shapiro-Wilk tests), progressing to one-way ANOVA and post-hoc Tukey HSD tests to compare differences across the analyzed contexts (headquarters vs. subsidiaries, pre-pandemic vs. pandemic) for various variables. Additionally, Spearman’s rank correlation was employed to examine the relationships between variables. To assess the variation in the strength of correlations, Fisher’s z-transformation was applied, while the presence of multicollinearity was checked using the Variance Inflation Factor (VIF), indicating no substantial issues as VIF was below 5 (Ringle et al., 2023). The analysis was conducted using TIBCO Statistica software (version 14.0.0.15).

During the ultimate stage of analysis, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed in R, utilizing the Lavaan package (version 0.6–12), to validate hypotheses and evaluate mediating effects (Rosseel, 2012; Savalei and Rosseel, 2022). Selected for its effectiveness with distributions that are not normally distributed and its applicability for analyzing theories and variances (Hair et al., 2023), PLS-SEM proves to be particularly suitable for investigating the effects of HRM practices on organizational performance results (Ringle et al., 2023). This method also facilitates the comparison of path coefficients among different sets of variables (Picón-Berjoyo et al., 2016), with the analysis being carried out on data that were adjusted using the Efficiency Index (EI).

Based on descriptive statistics, the study’s findings reveal consistent patterns across both types of entities, namely HQs of MNCs and their foreign subsidiaries (see Table 1). Specifically, performance metrics in HRM, finance, and quality were marginally superior during non-crisis periods, whereas innovativeness scores were higher in times of crisis. Innovativeness increased from x¯=3.77 to x¯=3.82 in HQs and from x¯=3.81 to x¯=3.90 in foreign subsidiaries. Employee performance (measured in KPIs) also experienced an uptick during the crisis period. In HQs, it rose from x¯=3.00 to x¯=3.24, and in foreign subsidiaries, it went from x¯=3.05 to x¯=3.19. Another observed pattern is the increase in the advancement and significance levels of EB in both entities during the crisis. In HQs, the advancement of EB rose from x¯=3.53 to x¯=3.57, and its significance level for the company’s performance results increased from x¯=3.52 to x¯=3.69. Meanwhile, in foreign subsidiaries, the advancement of EB went from x¯=3.33 to x¯=3.44, and its significance rose from x¯=3.41 to x¯=3.66.

These empirical data intriguingly suggest that crisis periods, typically perceived negatively, can actually foster innovation and enhance the significance and advancement of EB in both HQs and foreign subsidiaries of MNCs. It’s somewhat surprising to note that employee performance also increased during the crisis, indicating a heightened level of productivity and efficiency under pressure. While traditional performance metrics in HRM, finance, and quality may slightly decline, the urgency and challenges of a crisis seem to catalyze a drive for innovation and a more focused approach to EB. This could imply that crises not only push organizations to adapt and evolve but also inspire individual employees to perform better, highlighting the importance of flexibility and innovation in corporate strategy.

The collected research data were also analyzed using one-way ANOVA and post-hoc Tukey HSD tests to further examine the relationships between the studied variables across the four contexts (headquarters vs. subsidiaries, pre-pandemic vs. pandemic). The analyses revealed statistically significant differences (p < 0.05) for all variables, confirming that the impacts of EB varied across these contexts. Specifically: Finance: F(3, 396) = 13.50, p < 0.001; Quality: F(3, 396) = 9.41, p < 0.001; Innovativeness: F(3, 396) = 4.99, p = 0.030; HRM: F(3, 396) = 9.63, p < 0.001; Advancement of EP: F(3, 396) = 8.46, p < 0.001; Significance of EP: F(3, 396) = 10.94, p < 0.001. Post-hoc Tukey HSD analysis confirmed these differences, indicating that headquarters outperformed subsidiaries in key metrics such as finance, HRM, and quality, particularly during the pandemic period. Subsidiaries, on the other hand, showed relatively smaller advancements in these areas, while innovativeness exhibited more subtle distinctions across contexts. These findings enable the positive verification of H4, as they demonstrate that the effect of EB on company performance results indeed differs between headquarters and subsidiaries. This variability underscores the need for context-specific approaches in implementing and managing EB strategies within MNCs.

Analyzing the results from correlational statistics, it can be said that both periods showed significant correlations between the advancement level of EB and all types of company performance results (finance, product/service quality, innovativeness, and HRM). However, these correlations, with the exception of results in quality in HQs, were slightly stronger during times of crisis (see Table 2). This finding highlights the resilience of organizational structures and strategies in the face of adversity, suggesting that crises might actually serve as catalysts for strengthening the bond between EB and overall company performance.

Bringing together insights from descriptive and correlational analyses, these findings collectively illuminate an intriguing phenomenon: crises appear to act as a double-edged sword, imposing challenges that, while momentarily dampening some performance metrics, simultaneously trigger improvements in innovation, EB, and employee performance. Notably, the enhanced correlation between the advancement level of EB and company performance results during crises underscores the critical role of effective branding and employee engagement strategies under duress. This dynamic suggests that crises, though fraught with hurdles, may also present unique opportunities for organizations to refine their strategies, boost innovation, and foster a stronger alignment between branding efforts and performance results. Such resilience and adaptability are key to not just surviving but thriving in turbulent times, pointing to the importance of strategic flexibility and the potential benefits of reevaluating and reinforcing EB and innovation initiatives during periods of uncertainty.

The key findings from the path analysis conducted in PLS-SEM, presented in Tables 3–5, served as the basis for the verification of research hypotheses. These results indicate that the main hypothesis H1 can be accepted only partially, stemming from the incomplete positive verification of all auxiliary hypotheses. In the case of hypothesis H1A, the impact of EB on results in HRM is positive and statistically significant in each of the four contexts, i.e. in HQs before the pandemic (β = 0.67; p < 0.001) and during the pandemic (β = 0.70; p < 0.001), as well as in foreign subsidiaries both during the pandemic (β = 0.61; p < 0.001) and before it (β = 0.71; p < 0.001). Therefore, this hypothesis can be wholly validated. Regarding hypothesis H1B, EB positively affects the financial results in both HQs and foreign subsidiaries in both studied periods, but in foreign subsidiaries, this impact before the pandemic is statistically insignificant. A similar situation is encountered with hypothesis H1D. EB also positively affects the results in quality in both entities and both periods, but before the pandemic in foreign subsidiaries, this impact is statistically insignificant. As for hypothesis H1C, while EB does positively affect the results in innovativeness in each of the four contexts, this impact is statistically significant only in relation to HQs during the pandemic. All this reveals a nuanced impact of EB across different contexts and periods, emphasizing the varying significance of employer branding efforts on different aspects of performance, particularly during the pandemic.

The main hypothesis H2 is fully supported and can be confirmed as a whole, thanks to the successful validation of three related auxiliary hypotheses. It seems that HRM outcomes positively mediate the connection between EB and the financial performance results of the company (H2A) at the HQs during both the pre-pandemic (β = 0.80; p < 0.001) and pandemic periods (β = 0.77; p < 0.001), as well as in foreign subsidiaries for these same periods (β = 0.86; p < 0.001 and β = 0.73; p < 0.001, respectively). The HRM outcomes also mediate positively the relationships between EB and the results in innovativeness (H2B) both at the HQs and in the local subsidiaries in the pre-pandemic time (β = 0.68; p < 0.001 and β = 0.66; p < 0.001 respectively) and during the pandemic (β = 0.70; p < 0.001 and β = 0.79; p < 0.001 respectively). Furthermore, HRM outcomes also show the ability to positively mediate the relationship between EB and results in quality (H2C) both at the HQs and in the foreign subsidiaries in the pre-pandemic time (β = 0.54; p < 0.001 and β = 0.54; p < 0.001 respectively) and during the pandemic (β = 0.51; p < 0.001 and β = 0.42; p < 0.001 respectively). This comprehensive support for H2, through the mediating role of HRM outcomes in enhancing the relationship between EB and various performance results, underscores the multifaceted impact of effective human resources management across different operational and strategic areas, especially during variable economic conditions.

Hypothesis H3 can be accepted only to a limited extent, as only hypothesis H3B has been positively verified in full (see Figures 1–3). Namely, the indirect mediation effect of HRM outcomes between EB and the company’s performance results in innovativeness (H3B) is stronger during the pandemic (for HQs αβ = 0.50; for subsidiaries αβ = 0.56) compared to the pre-pandemic period (for HQs αβ = 0.45; for subsidiaries αβ = 0.40). In the case of the relationships between EB and the financial results (H3A), the mediating effect of HRM outcomes is greater in HQs during the pandemic (αβ = 0.54) than before it (αβ = 0.53), but in foreign subsidiaries, it remains the same in both periods (αβ = 0.52). Regarding the mediating effect of HRM outcomes between EB and the results in quality (H3C), it is the same in HQs during both studied periods (αβ = 0.36), while in foreign subsidiaries, it is greater before the pandemic (αβ = 0.32) than during the pandemic (αβ = 0.29). These results highlight that the role of HRM outcomes in linking EB to performance metrics shifts significantly across organizational contexts and timeframes, specifically between HQs and foreign subsidiaries and from pre-pandemic to pandemic periods. It particularly underlines the amplified role of HRM in boosting innovativeness and financial performance when facing adversity, showcasing its vital role in enhancing organizational agility and resilience during crises.

These path and mediation analyses unveil a compelling dynamic where EB and HRM outcomes interact differently across varying conditions, suggesting that crises like pandemics amplify the importance of HRM in mediating the impact of EB on company performance. Particularly, the strengthened role of HRM in enhancing innovativeness and financial performance during such times points to an essential strategic lever for organizations aiming to navigate through turbulence. The varied significance of EB across different performance aspects and periods, alongside the crucial mediating role of HRM, emphasizes the need for adaptive and resilient HR strategies that can pivot according to external pressures and internal performance goals.

The main goal of the article was to identify, analyze, and diagnose the relationships between EB and company performance results in MNCs from the perspectives of their HQs and foreign subsidiaries, during both non-crisis and crisis times, notably the COVID-19 pandemic period. Based on the in-depth analysis and empirical evidence gathered, this goal has been successfully achieved, with several key insights and conclusions drawn from the study substantiating this achievement.

Firstly, the empirical research findings provided a clear illustration of how EB significantly influences company performance results across various dimensions—HRM, finance, innovativeness, and quality. This observation is consistent with the insights from other researchers that were discussed in the theoretical part of this article, highlighting a broad consensus on the impact of EB on organizational success across its multiple dimensions (c.f. Azhar et al., 2024; Aldousari et al., 2017). The data indicated that during non-crisis times, organizations with strong EB practices generally reported better performance results. However, it was during the crisis times, specifically the COVID-19 pandemic, that the strategic value of EB became even more pronounced. This phenomenon has also garnered attention in the subject literature, indicating its significance as a focal point among scholars and practitioners (c.f. Ererdi et al., 2022; Johnstone, 2024). Companies that had invested in their employer brand were able to navigate the challenges of the pandemic more effectively, showcasing the resilience and adaptability of their EB strategies.

The verification of hypotheses further underscored the nuanced impact of EB on company performance results. While EB directly and positively affected HRM outcomes across all contexts, its influence on results in finance, innovativeness, and quality was more variable, highlighting the contextual dependence of these relationships. These research findings confirm the rationale behind the postulates put forward by other scholars, advocating for a broader emphasis on the significance of context (Farndale and Paauwe, 2018) and its influence within research (Špoljarić and Ozretić Došen, 2023; Japutra et al., 2024). In particular, the analysis revealed statistically significant differences between HQs and foreign subsidiaries, with HQs generally demonstrating greater improvements during the pandemic, especially in areas such as finance, HRM, and quality. Post-hoc Tukey HSD tests confirmed that headquarters consistently outperformed subsidiaries in these metrics, underscoring the importance of centralized EB strategies at HQs. However, the results also highlighted the need for localized approaches, as subsidiaries exhibited slower progress in certain areas, such as innovativeness, suggesting that EB solutions need to be culturally sensitive and operationally adaptive.

Moreover, the research illuminated the mediating role of HRM outcomes in the relationship between EB and company performance results. This finding suggests that the impact of EB on company performance results is not merely direct but is significantly enhanced through its positive influence on HRM outcomes, much like those already known from other studies, which include employee satisfaction, engagement (c.f. Kunerth and Mosley, 2011), and retention (c.f. (Deepa and Baral, 2021; Saini et al., 2022). Anyway, this mediating effect was found to be stronger during crisis times, indicating that in periods of uncertainty, the role of effective HRM practices becomes even more critical in leveraging the benefits of a strong employer brand.

The study’s findings also revealed an interesting dynamic regarding the role of EB during crises. Notably, the advancement and significance levels of EB within both HQs and foreign subsidiaries were observed to increase during the pandemic. This suggests that crises may act as catalysts for organizations to reassess and strengthen their EB efforts, driven by the heightened need to maintain employee engagement and attract talent in challenging times. This is consistent with observations from other researchers who emphasize that in times of crisis, it is primarily a strong EB that has the potential to create an environment that attracts (Cable and Turban, 2003) and retains top talent (Lievens and Slaughter, 2016), which is of fundamental importance for the success of an organization (Haromszeki, 2023) and the results it achieves in various areas of its operations (Alnıaçık et al., 2014).

Given the conducted research, an interesting outcome is the observation that the level of EB solutions implemented within MNCs, as defined and enhanced during the crisis times, notably the COVID-19 pandemic, underscores a critical insight into organizational resilience and adaptability (c.f. Singh, 2024). The article delineates EB as a set of activities aimed at promoting, distinguishing, and preserving a company’s image as an attractive employer, both internally and externally (Stor, 2023b, p. 252; Foster et al., 2010). This comprehensive approach to EB, which aligns with strategic HRM practices (Aldousari et al., 2017; Tumasjan et al., 2020), evidently had a direct positive effect on company performance results across various metrics, including HRM outcomes.

Summarizing, it can be generally concluded that the increased emphasis and advancement in EB practices during the crisis period suggests that MNCs may have leveraged their EB strategies as a crucial tool to navigate through the pandemic’s challenges. With the research highlighting EB’s direct and mediated positive impacts on company performance results, it can be also inferred that investing in EB not only supports immediate organizational goals but also serves as a long-term strategic asset in times of uncertainty. Moreover, the differentiation in EB’s effectiveness between HQs and foreign subsidiaries highlights the importance of localized and culturally sensitive EB approaches. The adaptability and customization of EB strategies to fit the unique contexts of foreign subsidiaries were key in maximizing their contribution to overall company performance and its results. This insight emphasizes the need for MNCs to adopt flexible and context-aware EB practices that resonate with diverse employee groups across their global operations.

In essence, the study’s findings articulate the value of dynamic and strategically integrated EB practices in enhancing organizational resilience, performance, and attractiveness as an employer. The adaptability of EB strategies, especially during times of crisis, emerges as a significant factor in sustaining and improving company performance results, illustrating EB’s role not just as a HRM tool, but as a central component of strategic organizational leadership.

Ultimately, a conclusion can also be formulated that appropriate EB is beneficial for both employees and employers within MNCs, particularly noticeable during times of crisis. This strategic approach allows both HQs and local subsidiaries to effectively counteract phenomena such as the Great Resignation, Quiet Quitting (Stor, 2023b, pp. 96–97), Career Cushioning, and Loud Quitting (Gallup, 2023, p. 4), as mentioned in the introduction. By aligning EB practices with the diverse needs and expectations of employees globally, MNCs can ensure that their actions not only meet employee expectations but also support the overarching goals of the organization. This includes achieving objectives related to various categories of company performance results, demonstrating the critical role of EB in sustaining organizational success across different geographic and operational contexts.

The study acknowledges certain constraints, such as a sample that might not completely represent the extensive population and the absence of contributions from informants at the local subsidiaries. It also leans on subjective judgments for qualitative comparisons, which could skew the results. Future investigations should apply objective criteria, such as concrete performance records or evaluations by external entities, to broaden the analysis and affirm these conclusions. The emphasis on perspectives from HR professionals might also narrow the findings to certain HRM impacts and approaches. Expanding the scope to include insights from line managers and other employees in forthcoming studies could offer a more holistic view of EB’s influence on organizational performance results. Additionally, the research does not account for the unique circumstances of individual foreign subsidiaries, an element that could enhance the richness of future research findings.

Despite the limitations discussed above, the findings presented in this article offer significant contributions to both management science and the practice of management and business. The research sheds light on the strategic importance of EB and its nuanced impact on organizational performance results across various dimensions, including HRM, finance, innovativeness, and quality, particularly accentuated during times of crisis such as the COVID-19 pandemic. These insights underscore the value of EB not merely as a tool for enhancing employee attraction and retention but as a critical component of strategic management capable of fostering organizational resilience and performance.

From a theoretical perspective, the study enriches management science by highlighting the mediating role of HRM outcomes in the relationship between EB and company performance. It contributes to a deeper understanding of how strategic HRM practices, influenced by a robust EB, can significantly enhance organizational outcomes. This mediation effect, especially pronounced during crisis periods, suggests the importance of adaptive HRM strategies that leverage EB to navigate through challenging times. Against this backdrop, the additional value of the research findings emerges, namely the Crisis-Responsive EB-HRM Mediation Theory for MNC Performance and Resilience, which is proposed in the next, final section of this article.

From a practical perspective, the findings offer actionable insights for various business practitioners, including managerial staff across different levels, specialists, business partners, and managers and directors of HR departments. The evidence supports the notion that investment in EB serves not only immediate goals related to workforce management but also contributes to long-term strategic objectives. For MNCs, the study highlights the importance of contextualized and localized EB strategies that address the unique operational, cultural, and regulatory environments of foreign subsidiaries, enhancing global performance.

Furthermore, the use of employee Key Performance Indicators (KPIs) as an efficiency index introduces a novel approach for assessing the impact of EB and HRM practices on organizational performance results. By employing the Efficiency Index, this study refines raw performance measures into efficiency-adjusted indicators, allowing for a more precise and standardized assessment of EB’s impact. Unlike absolute performance metrics, this index ensures that findings are not biased by firm size or resource allocation, making the evaluation of HRM effectiveness more reliable across different organizational contexts. This innovation provides both researchers and managers with a practical tool for measuring and analyzing the effectiveness of HRM initiatives, facilitating data-driven decisions that align with corporate strategies and goals.

In summary, the research articulated in this article advances our understanding of EB’s strategic role in management and offers a comprehensive framework for leveraging EB practices to achieve superior organizational performance. Future studies could build on these findings by exploring the differential impacts of EB across various industries and cultural contexts, further enriching the field of management science and enhancing the efficacy of business practices.

Finally, it can be said that the findings made in the article lead to the formulation of a theory, which can be named the Crisis-Responsive EB-HRM Mediation Theory for MNC Performance and Resilience. It is a cohesive theory that centers on the strategic role of EB in enhancing organizational performance and resilience through effective HRM practices in times of crisis. This theory repositions EB beyond its historical roots in relationship marketing and its traditional role as a tool for attracting and retaining talent, presenting it instead as a central element of strategic management capable of fostering resilience, adaptability, and sustainable performance improvement.

In a broader explanation, the core theory resulting from this study posits that EB transcends its conventional role in talent attraction and retention, emerging as a critical element in the strategic management matrix that drives organizational performance. It asserts that EB’s integration into strategic management frameworks contributes to organizational resilience, adaptability, and performance across critical dimensions, including finance, innovation, quality, and HRM outcomes. This enhanced strategic role of EB is particularly crucial during periods of crisis, where its contribution to HRM outcomes becomes a linchpin for navigating the complexities and challenges posed, thereby fostering a robust organizational framework capable of sustaining performance improvement and competitive advantage. The theory further emphasizes that EB’s strategic role is not confined to crisis management alone but extends to long-term resilience and adaptability, reinforcing its place as an essential pillar of modern organizational leadership.

Specifically, in the context of MNCs, this theory gains further significance as it highlights how strategic EB practices are intricately linked to the complex dynamics of managing diverse workforces across different national and cultural environments. Unlike traditional applications of EB, which focus on talent acquisition and retention, this theory highlights the multidimensional impact of EB within MNCs, where it serves as a mechanism for harmonizing global operations, facilitating cross-border HRM practices, and aligning diverse organizational cultures. The theory underscores that in MNCs, the strategic deployment of EB is instrumental in navigating not only the heterogeneity of global markets but also in mitigating the heightened challenges during crisis times. Such strategic emphasis on EB supports the development of a unified yet contextually sensitive framework that ensures operational coherence and competitive advantage across MNCs’ global landscapes.

This comprehensive approach to understanding the strategic significance of EB, particularly within the complex operational frameworks of MNCs, enriches the discourse in management science, providing a nuanced perspective on the pivotal role of EB in driving organizational success on a global scale. By positioning EB as a central component of strategic management in MNCs, this theory bridges the gap between traditional marketing perspectives and contemporary organizational needs, offering a framework for resilience, adaptability, and sustained performance in the face of global challenges.

The project was funded by the Ministry of Education and Science in Poland under the program “Regional Initiative of Excellence” 2019–2023 (No: 015/RID/2018/19).

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Data & Figures

Figure 1
A figure showing four H R M mediation models with arrows linking E B, H R M, and finance performance metrics.The figure presents four H R M mediation models arranged in a two-by-two grid. The first model on the top left is labeled “A. The H Q S - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position, and from this an arrow labeled “beta equals 0.67 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.44”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.80 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.83”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.16 (p less than 0.001)” points toward “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”. Above “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.53”. The second model on the top right is labeled “B. The H Q S - in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position, and from this an arrow labeled “beta equals 0.70 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”. Directly below this upper text box, a label reads “R squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.77 (p less than 0.001)” points toward a text box on the bottom right labeled “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.81”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.17 (p less than 0.001)” extends toward “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”. Above this finance box, a small square box contains the label “alpha beta equals 0.54”. The third model on the bottom left is labeled “C. The F Ss - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears, and from this an arrow labeled “beta equals 0.61 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this upper H R M box, a label reads “R squared equals 0.37”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.86 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.82”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.08 (p greater than 0.05)” points toward “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”. Above “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.52”. The fourth model on the bottom right is labeled “D. The F Ss- in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears, and from this an arrow labeled “beta equals 0.71 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this H R M box, a label reads “R squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.73 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.78”. From “Advancement level of E B (E I underscore E M equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.20 (p less than 0.001)” points toward “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”. Above “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.52”.

The HRM mediation model of the relationships between EB and company performance results in finance

Figure 1
A figure showing four H R M mediation models with arrows linking E B, H R M, and finance performance metrics.The figure presents four H R M mediation models arranged in a two-by-two grid. The first model on the top left is labeled “A. The H Q S - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position, and from this an arrow labeled “beta equals 0.67 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.44”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.80 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.83”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.16 (p less than 0.001)” points toward “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”. Above “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.53”. The second model on the top right is labeled “B. The H Q S - in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position, and from this an arrow labeled “beta equals 0.70 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”. Directly below this upper text box, a label reads “R squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.77 (p less than 0.001)” points toward a text box on the bottom right labeled “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.81”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.17 (p less than 0.001)” extends toward “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”. Above this finance box, a small square box contains the label “alpha beta equals 0.54”. The third model on the bottom left is labeled “C. The F Ss - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears, and from this an arrow labeled “beta equals 0.61 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this upper H R M box, a label reads “R squared equals 0.37”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.86 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.82”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.08 (p greater than 0.05)” points toward “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”. Above “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.52”. The fourth model on the bottom right is labeled “D. The F Ss- in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears, and from this an arrow labeled “beta equals 0.71 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this H R M box, a label reads “R squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.73 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.78”. From “Advancement level of E B (E I underscore E M equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.20 (p less than 0.001)” points toward “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”. Above “Company performance results in finance (E I F equals StartFraction F over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.52”.

The HRM mediation model of the relationships between EB and company performance results in finance

Close modal
Figure 2
A figure showing four models comparing E B, H R M, and innovativeness with pathways and beta values.The figure presents four models arranged in a two-by-two grid. The first model on the top left is labeled “A. The H Q S - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position, and from this an arrow labeled “beta equals 0.67 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.44”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.68 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.59”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.12 (p greater than 0.05)” points toward “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”. Above “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.45”. The second model on the top right is labeled “B. The H Q S - in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position, and from this an arrow labeled “beta equals 0.70 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”. Directly below this upper text box, a label reads “R-squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.70 (p less than 0.001)” points toward a text box on the bottom right labeled “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.64”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.13 (p less than 0.05)” extends toward “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”. Above this finance box, a small square box contains the label “alpha beta equals 0.50”. The third model on the bottom left is labeled “C. The F Ss - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears, and from this an arrow labeled “beta equals 0.61 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this upper H R M box, a label reads “R squared equals 0.37”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.66 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.46”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.02 (p greater than 0.05)” points toward “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”. Above “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.40”. The fourth model on the bottom right is labeled “D. The F Ss- in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears. From this an arrow labeled “beta equals 0.71 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this H R M box, a label reads “R squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.79 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.71”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.07 (p greater than 0.05)” points toward “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”. Above “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.56”.

The HRM mediation model of the relationships between EB and company performance results in innovativeness

Figure 2
A figure showing four models comparing E B, H R M, and innovativeness with pathways and beta values.The figure presents four models arranged in a two-by-two grid. The first model on the top left is labeled “A. The H Q S - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position, and from this an arrow labeled “beta equals 0.67 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.44”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.68 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.59”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.12 (p greater than 0.05)” points toward “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”. Above “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.45”. The second model on the top right is labeled “B. The H Q S - in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position, and from this an arrow labeled “beta equals 0.70 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”. Directly below this upper text box, a label reads “R-squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.70 (p less than 0.001)” points toward a text box on the bottom right labeled “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.64”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.13 (p less than 0.05)” extends toward “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”. Above this finance box, a small square box contains the label “alpha beta equals 0.50”. The third model on the bottom left is labeled “C. The F Ss - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears, and from this an arrow labeled “beta equals 0.61 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this upper H R M box, a label reads “R squared equals 0.37”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.66 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.46”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.02 (p greater than 0.05)” points toward “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”. Above “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.40”. The fourth model on the bottom right is labeled “D. The F Ss- in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears. From this an arrow labeled “beta equals 0.71 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this H R M box, a label reads “R squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.79 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.71”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.07 (p greater than 0.05)” points toward “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”. Above “Company performance results in innovativeness (E I I equals StartFraction I over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.56”.

The HRM mediation model of the relationships between EB and company performance results in innovativeness

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Figure 3
A figure showing four H R M mediation models linking E B, H R M, and quality outcomes.The figure presents four H R M mediation models arranged in a two-by-two grid. The first model on the top left is labeled “A. The H Q S - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position. From this, an arrow labeled “beta equals 0.67 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.44”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.54 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.50”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.22 (p less than 0.01)” points toward “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”. Above “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.36”. The second model on the top right is labeled “B. The H Q S - in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position. From this, an arrow labeled “beta equals 0.70 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”. Directly below this upper text box, a label reads “R-squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.51 (p less than 0.001)” points toward a text box on the bottom right labeled “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.44”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals negative 0.20 (p less than 0.05)” extends toward “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”. Above this finance box, a small square box contains the label “alpha beta equals 0.36”. The third model on the bottom left is labeled “C. The F Ss - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears. From this, an arrow labeled “beta equals 0.61 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this upper H R M box, a label reads “R squared equals 0.37”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.54 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.38”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.12 (p greater than 0.05)” points toward “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”. Above “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.32”. The fourth model on the bottom right is labeled “D. The F Ss- in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears. From this, an arrow labeled “beta equals 0.71 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this H R M box, a label reads “R squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.42 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.45”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.31 (p less than 0.001)” points toward “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”. Above “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.29”.

The HRM mediation model of the relationships between EB and company performance results in quality

Figure 3
A figure showing four H R M mediation models linking E B, H R M, and quality outcomes.The figure presents four H R M mediation models arranged in a two-by-two grid. The first model on the top left is labeled “A. The H Q S - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position. From this, an arrow labeled “beta equals 0.67 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.44”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.54 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.50”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.22 (p less than 0.01)” points toward “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”. Above “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.36”. The second model on the top right is labeled “B. The H Q S - in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears in the lower left position. From this, an arrow labeled “beta equals 0.70 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”. Directly below this upper text box, a label reads “R-squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.51 (p less than 0.001)” points toward a text box on the bottom right labeled “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.44”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals negative 0.20 (p less than 0.05)” extends toward “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”. Above this finance box, a small square box contains the label “alpha beta equals 0.36”. The third model on the bottom left is labeled “C. The F Ss - the non-crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears. From this, an arrow labeled “beta equals 0.61 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this upper H R M box, a label reads “R squared equals 0.37”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.54 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, and below this box, a label reads “R squared equals 0.38”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.12 (p greater than 0.05)” points toward “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”. Above “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.32”. The fourth model on the bottom right is labeled “D. The F Ss- in the crisis time”, and in this model, a text box labeled “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)” appears. From this, an arrow labeled “beta equals 0.71 (p less than 0.001)” arises upward and points toward a text box labeled “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, and below this H R M box, a label reads “R squared equals 0.50”. From “Company performance results in H R M (E I H R M equals StartFraction H R M over E K P Is EndFraction)”, a downward arrow labeled “beta equals 0.42 (p less than 0.001)” points downward to a text box on the bottom right labeled “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, and below this finance box, a label reads “R squared equals 0.45”. From “Advancement level of E B (E I underscore E B equals StartFraction A L underscore E B over E K P Is EndFraction)”, a right-pointing arrow labeled “beta equals 0.31 (p less than 0.001)” points toward “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”. Above “Company performance results in quality (E I Q equals StartFraction Q over E K P Is EndFraction)”, a small square box is labeled “alpha beta equals 0.29”.

The HRM mediation model of the relationships between EB and company performance results in quality

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Table 1

Descriptive statistics for the major variables

VariablesHQS in the non-crisis timeHQS in the crisis time
Valid NMeanMinMaxStd.DevValid NMeanMinMaxStd.Dev
Results in finance2004.033.05.00.322003.923.05.00.36
Results in HRM2003.983.05.00.382003.923.05.00.37
Results in quality2003.853.05.00.602003.772.05.00.58
Results in innovativeness2003.772.05.00.572003.822.05.00.54
Employee performance in KPIs2003.002.04.00.492003.242.04.00.53
Advancement level of EB2003.532.004.000.512003.572.005.000.53
Significance level of EB2003.522.005.000.582003.692.005.000.48
VariablesForeign subsidiaries in the non-crisis timeForeign subsidiaries in the crisis time
Valid NMeanMinMaxStd.DevValid NMeanMinMaxStd.Dev
Results in finance2003.993.05.00.242003.933.05.00.37
Results in HRM2003.983.05.00.312003.923.05.00.34
Results in quality2003.812.05.00.572003.773.05.00.54
Results in innovativeness2003.812.05.00.562003.903.05.00.50
Employee performance in KPIs2003.052.04.00.392003.192.04.00.51
Advancement level of EB2003.332.005.000.502003.442.004.000.55
Significance level of EB2003.412.005.000.622003.662.005.000.54

Note(s): Scales, Company performance results in HRM, finance, innovativeness, quality → benchmarked to the companies of similar business profile: 1 – poor, 2 – below average, 3 – similar to others, 4 – above average, 5 – very good, Employee performance in KPIs: 1 – significantly below standards, 2 – rather below standards, 3 – exactly with the standards, 4 – rather higher than standards, 5 – significantly higher than standards, Advancement level of EB → benchmarked to the best market practices: 1 – significantly lower, 2 – lower, 3 – similar to others, 4 – higher, 5 – significantly higher, Significance level of EB to the company’s performance results: 1 – not important, 2 – slightly important, 3 – important, 4 – very important, 5 – of critical significance

Source(s): Own empirical research

Table 2

The results of a correlation test for the major variables modified by the efficiency ratio (employee KPIs)

VariablesHQS in the NON-CRISIS timeHQS in the crisis time
Results in HRM (HRMEKPIs)Advancement level of ED (AL_EBEKPIs)Results in HRM (HRMEKPIs)Advancement level of ED (AL_EBEKPIs)
1. Results in finance (FEKPIs)0.91*0.69*0.89*0.71*
2. Results in quality (QEKPIs)0.69*0.58*0.65*0.56*
3. Results in innovativeness (IEKPIs)0.76*0.57*0.80*0.63*
4. Results in HRM (HRMEKPIs)1.000.67*1.000.70*
5. Advancement level of EB (AL_EBEKPIs)0.67*1.000.70*1.00
VariablesForeign subsidiaries in the NON-CRISIS timeForeign subsidiaries in the crisis time
Results in HRM (HRMEKPIs)Advancement level of ED (AL_EBEKPIs)Results in HRM (HRMEKPIs)Advancement level of ED (AL_EBEKPIs)
1. Results in finance (FEKPIs)0.90*0.59*0.87*0.71*
2. Results in quality (QEKPIs)0.61*0.45*0.64*0.60*
3. Results in innovativeness (IEKPIs)0.68*0.42*0.84*0.63*
4. Results in HRM (HRMEKPIs)1.000.61*1.000.71*
5. Advancement level of EB (AL_EBEKPIs)0.61*1.000.71*1.00

Note(s):* Marked correlations are significant at p <00.010

Source(s): Own empirical research

Table 3

Path analysis summary in PLS-SEM for EB and company performance results in finance

HQS in the non-crisis timeHQS in the crisis time
Variables in pathsβZp95%CIR2Variables in pathsβZp95%CIR2
EB → Finance0.163.41<0.001[0.07; 0.24]0.83EB → Finance0.173.65<0.001[0.08; 0.26]0.81
EB → HRM (α)0.6711.93<0.001[0.56; 0.77]0.44EB → HRM (α)0.7013.69<0.001[0.60; 0.80]0.50
HRM → Finance0.8013.05<0.001[0.68; 0.92]HRM → Finance0.7712.98<0.001[0.66; 0.89]
Mediation effect of HRM (αβ)0.537.80<0.001[0.40; 0.67]Mediation effect of HRM (αβ)0.549.81<0.001[0.44; 0.65]
Foreign subsidiaries in the non-crisis timeForeign subsidiaries in the crisis time
Variables in pathsβZp95%CIR2Variables in pathsβZp95%CIR2
EB → Finance0.081.90>0.050.82EB → Finance0.203.94<0.001[0.10; 0.29]0.78
EB → HRM (α)0.618.27<0.001[0.46; 0.75]0.37EB → HRM (α)0.7111.36<0.001[0.58; 0.83]0.50
HRM → Finance0.8612.35<0.001[0.72; 0.99]HRM → Finance0.7310.67<0.001[0.60; 0.87]
Mediation effect of HRM (αβ)0.527.50<0.001[0.38; 0.65]Mediation effect of HRM (αβ)0.529.11<0.001[0.41; 0.63]

Note(s): All variables modified by the efficiency ratio (employee KPIs)

Source(s): Own empirical research

Table 4

Path analysis summary in PLS-SEM for EB and company performance results in innovativeness

HQS in the non-crisis timeHQS in the crisis time
Variables in pathsβZp95%CIR2Variables in pathsβZp95%CIR2
EB → Innovativeness0.121.52>0.050.59EB → Innovativeness0.132.50<0.05[0.03; 0.24]0.64
EB → HRM (α)0.6711.93<0.001[0.56; 0.77]0.44EB → HRM (α)0.7013.69<0.001[0.60; 0.80]0.50
HRM → Innovativeness0.689.70<0.001[0.55; 0.82]HRM → Innovativeness0.7010.87<0.001[0.58; 0.83]
Mediation effect of HRM (αβ)0.457.11<0.001[0.33; 0.58]Mediation effect of HRM (αβ)0.508.63<0.001[0.38; 0.61]
Foreign subsidiaries in the non-crisis timeForeign subsidiaries in crisis time
Variables in pathsβZp95%CIR2Variables in pathsβZp95%CIR2
EB → Innovativeness0.020.23>0.050.46EB → Innovativeness0.071.03>0.050.71
EB → HRM (α)0.618.27<0.001[0.46; 0.75]0.37EB → HRM (α)0.7111.36<0.001[0.58; 0.83]0.50
HRM → Innovativeness0.666.52<0.001[0.46; 0.86]HRM → Innovativeness0.7914.77<0.001[0.69; 0.90]
Mediation effect of HRM (αβ)0.406.17<0.001[0.27; 0.53]Mediation effect of HRM (αβ)0.568.22<0.001[0.43; 0.69]

Note(s): All variables modified by the efficiency ratio (employee KPIs)

Source(s): Own empirical research

Table 5

Path analysis summary in PLS-SEM for EB and company performance results in quality

HQS in the non-crisis timeHQS in the crisis time
Variables in pathsβZp95%CIR2Variables in pathsβZp95%CIR2
EB → Quality0.223.14p < 0.01[0.08; 0.36]0.50EB → Quality0.202.34<0.05[0.03; 0.37]0.44
EB → HRM (α)0.6711.93<0.001[0.56; 0.77]0.44EB → HRM (α)0.7013.69<0.001[0.60; 0.80]0.50
HRM → Quality0.546.47<0.001[0.38; 0.70]HRM → Quality0.514.98<0.001[0.31; 0.70]
Mediation effect of HRM (αβ)0.365.28<0.001[0.23; 0.49]Mediation effect of HRM (αβ)0.364.95<0.001[0.21; 0.50]
Foreign subsidiaries in the NON-CRISIS timeForeign subsidiaries in the crisis time
Variables in pathsβZp95%CIR2Variables in pathsβZp95%CIR2
EB → Quality0.121.52>0.050.38EB → Quality0.313.37<0.001[0.13; 0.49]0.45
EB → HRM (α)0.618.27<0.001[0.46; 0.75]0.37EB → HRM (α)0.7111.36<0.001[0.58; 0.83]0.50
HRM → Quality0.544.97<0.001[0.32; 0.75]HRM → Quality0.424.31<0.001[0.23; 0.61]
Mediation effect of HRM (αβ)0.324.79<0.001[0.19; 0.46]Mediation effect of HRM (αβ)0.294.36<0.001[0.16; 0.43]

Note(s): All variables modified by the efficiency ratio (employee KPIs)

Source(s): Own empirical research

Supplements

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