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Relationship Between Skills Shortage and Firm Performance

Info: 12968 words (52 pages) Dissertation
Published: 19th Jan 2022

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Tagged: BusinessEmploymentInformation SystemsTechnology


There has been growing scholarly interest in the relationship between high performance work systems (HPWS) and firm performance. Yet, limited research attention has been given to the impact of HPWS on firm performance during skills shortages. In this study, we empirically examine the influence of HPWS on firm performance in the midst of skills shortages. Results from a study of 211 U.S. firms with 50 or more employees demonstrate that internal skills shortages are not related to firm profitability. Findings further show that the use of HPWS is more detrimental for firms when they face an internal skills shortage. These results are discussed and future research directions are offered.

Key words: Human resource management, high performance work systems, skill shortages, firm performance



In today’s competitive and complex environment, managing human capital is necessary to sustain competitive advantage (Mendenhall, Reiche, Bird, & Osland, 2012). Past research suggests that human capital (also called intellectual capital or human talent), embedded within high performance work systems (HPWS), create value for firms (Becker & Huselid, 1998). From a resource-based perspective, value is created when a firm is able to either decrease product/service costs or alternatively charge a premium price through product differention, or some combination of both (Barney, Wright & Ketchen, 2001).

These outcomes are key determinants of performance and enable firms to achieve sustained competitive advantage. The source of this advantage is human capital, and HPWS help create the human capital advantage that firms enjoy (Snell, Morris & Bohlander, 2016). Research has increasingly focused on the value of human capital at both micro- and macro-levels (Bell & Kozlowski, 2008; Mahaney & Pandian, 1992; Wright & McMahan, 2011) and scholars have called for developing a better understanding of the micro-dynamics of human capital advantages (Coff & Kryscynski, 2011). These calls are significant, particularly in the face of increased employee mobility, changing workforce demographics (such as the looming retirement of baby boomers and the relatively small “baby bust” cohort born in the 1970s), and the shortening of life cycles of jobs due to rapid technological advancement, among others (Beechler & Woodward, 2009; Vaiman, Scullion & Collings, 2012).

Notably, such changes have raised concerns about imminent skills shortages. While traditional HR frameworks have focused on developing and managing HR practices around existing skills, there is a paucity of research looking at how firms address talent/skills shortages (Brisco,Schuler & Claus, 2009; Gordon, 2009). Specifically little is known, both conceptually and empirically, about whether implementing a HPWS during skills shortages will benefit organizations. A goal of this study is to address this gap in the literature. Thus, the specific purpose of this study is to empirically investigate whether firms can improve and sustain their performance by managing their human resources in the midst of skills shortages.

Skills shortage, being defined as a situation when a firm’s existing employees do not have the skills needed to do their job effectively (Green & Ashton, 1992), has become increasingly challenging for firms and could directly affect firm performance. McKinsey & Co in its “War for Talent” study (Chambers, Foulon, Handfield-Jones, Hankin & Michaels, 1998) cautioned U.S. companies about the imminent labor shortages. Similarly, Michaels, Handfield-Jones and Axelrod (2001:1) warned that skills shortages can pose a serious threat to organizations because “a complex economy demands more sophisticated talent with global acumen, multi-cultural fluency, technological literacy, entrepreneurial skills, and the ability to manage increasingly de-layered, disaggregated organizations.” 

The lack of these skills could be determintal for firms in a fiercely competitive environment. Even during a recession, which is associated with a high unemployment rate, firms will still face skills shortages due to a lack of qualified candidates available in the labor market (Gordon, 2009). This trend is expected to grow as firms in advanced economies face a shortage of highly skilled labor, whereas low or moderately skilled employees will be in surplus (McKinsey Global Institute, 2012). This study focuses on internal skills shortage, and not on labor shortages in the external labor market. However, the impact that external labor shortages have on a firm’s internal skills shortage is acknowledged.

A number of studies and research reports have highlighted the issue of talent shortages and suggest that organizations take steps to manage talent effectively to cope with potential talent deficiencies (Cappelli, 2014). For instance, the U.S. Chamber of Commerce (2006:13) predicted that the “impending retirement of the baby boomers cohort would lead to an absolute decline in the size of the labor force and a severe worker shortage.” Similarly, a talent report within the manufacturing industry published by Deloitte (2011) drew attention to the severe shortage of qualified workers in that sector and how it could adversely affect critical functions such as new product development, new technology implementation and the achievement of performance targets. Likewise, McKinsey Global Institute (2012) cautioned against a potential shortage of about 38 to 40 million high-skilled workers across the developed economies by 2020.

Taken together, the evidence suggests that skills shortages are on the increase globally, which will create difficulties for firms to recruit skilled employees in such areas as sales, engineering, accounting and finance, management, IT, and production, among others (Manpower Group, 2015). Skills shortages, therefore, remain a significant challenge for firms, and the absence of key skills could lower firm performance. The first research question posed here, then, is – do skills shortages lower firm profitability? Furthermore, do high performance work systems (HPWS) allow firms to mitigate negative relationships between HPWS and profitability?

Organizations need HR-related systems, practices and tools to improve and sustain performance. HPWS are important mechanisms that allow organizations to capitalize on their existing human resources in the context of labor shortages. HPWS are a combination of various high performance work practices such as selection, recruitment, training, compensation and benefits, and career development (Huselid, 1995; Pfeffer, 1998). Research has increasingly examined mechanisms through which HPWS impact firm performance (e.g., Collins & Smith, 2006; Datta, Guthrie & Wright, 2005; García-Chas, Neira-Fontela & Castro-Casal, 2014; Jiang and Liu, 2015; Macky & Boxall, 2007). These studies demonstrated that HPWS positively impact employee outcomes (e.g., employee skills, abilities, motivation, improved social relationships and labor productivity and turnover), which in turn positively impact firm performance (that is, productivity and profitability).

Our research explores whether HPWS can enhance firm performance in organizations facing skills shortages. In so doing, we offer new empirical, theoretical, and practical contributions to the literature. From an empirical perspective, we introduce HPWS, an important yet hitherto unexplored contextual variable, that can influence the effects of skills shortages on firm performance. In doing so, we  explored the interaction effect of HPWS and skills shortages to determine whether the benefits they produce exceed the cost of implementing HPWS when firms face skills shoratges. In addition, understanding the processes through which HPWS impact firm performance when firms face skills shortage not only advances SHRM theory, but will also help practitioners justify whether or not to invest in HPWS in the face of skills shortages (cf. Combs, Liu, Hall & Ketchen, 2006).


Resource based view (RBV) of the firm

The resource-based view (RBV) is a meaningful lens to explore skills shortages in a firm. The RBV of the firm suggests that an organization can gain a sustainable competitive advantage over others on the basis of how it uses its resources (Barney et al., 2001; Nason & Wiklund, 2015). A firm can achieve a competitive advantage insofar as the resources it possesses satisfy the following characteristics:  They are:

(i) valuable, i.e. the degree to which resources allow a firm to outperform competitors;

(ii) rare, i.e. resources must not be easily and readily available to competitors;

(iii) in-imitable, i.e. competitors must find it very difficult to imitate/copy resources, implying that resources are socially complex and immobile, and therefore, unique only to a particular firm; and,

(iv) non-substitutable, i.e. there is no alternative or replacement to resources (Barney, 1991).

The lack of substitutability is crucial because even if the resource is rare, valuable and inimitable, if other competitors can counter the firm’s value-creating strategy by offering various substitutes, then the profit margins will shrink due to the competition, and the resource can no longer be a source of competitive advantage to the firm (Barney, 1991).

Scholars have highlighted various tangible and intangible resources as sources of competitive advantage for firms. Tangible resources include physical capital (e.g. plant, equipment, finances), while intangible resources include human capital (e.g. skills, knowledge judgment), and organizational capital (e.g. structure, monitoring) (Evans & Davis, 2005; Jackson & Schuler, 1995). Other scholars have also highlighted various intangible resources such as organizational culture, learning and ethics as  potential sources of competitive advantage (Barney, 1991, Fiol & Lyles 1985; Manroop, 2015). The underlying argument is that these resources are knowledge based and socially complex, and lead to “causal ambiguity,” which is a case when the actual source of competitive advantage is not known as these resources are idiosyncratic to the firm which possesses them.

When a firm possesses human capital in terms of the required skills needed to perform jobs, organizational performance is greater. However, when a firm lacks essential skills to meet strategic objectives at different hierarchical levels, its performance is hindered. Empirical evidence suggests that skills shortages can have a detrimental effect on a firm’s productivity level (Bennett & McGuinness, 2009; Cappelli, 2014). Haskel and Martin (1993) mentioned that the increased skills shortages during the mid-1980s reduced industry productivity growth by around 0.7% per annum. In a later study, Bennet and McGuinness (2009) examined the impact of skills shortages (being measured in terms of hard-to-fill and unfilled vacancies) on the performance of high-tech firms and found that both hard-to-fill and unfilled vacancies significantly impact firm performance.

More specifically, the findings showed that high performing firms were more likely to see skills shortages and the output level per worker was reduced by 65% in positions that were difficult to fill, and 75% in the case of vacant positions. These findings suggest that labor and skills shortages can disrupt the productivity gains of the top performing high tech firms (Bennet & McGuinness, 2009).

Research has shown that skilled employees feel a greater sense of responsibility, are likely to be more confident, can take charge of organizational change and innovation, and are better able to deal with complexity (Morrison & Phelps, 1999). Skilled employees offer more suggestions on how to improve processes and fill identified gaps (Song, Almeida, & Wu 2003). On the one hand, research has shown that the availability of skilled employees accelerates research and development investment by enhancing innovation (individual creativity, organizational change and the acquisition of external knowledge) (Piva & Vivarelli, 2008; Svetlik and Stavrou-Costea, 2007) and improving organizational performance (Arvanitis, 2005). On the other hand, information technology has also created more demand for high skilled employees (Bresnahan, Brynjolfsson & Hitt, 2002).

If skills shortages are not addressed, this can hinder achievement of the company’s strategic goals. It can also be argued that less skilled employees are less likely to come up with creative ideas and innovative solutions to organizational issues (Guthrie, 2001), and this lack of skills can impede technological initiatives. Therefore, at the firm level, employee skills are one of the key drivers for sustaining improved organizational performance (Bresnahan et al., 2002). During turbulent economic times, when firms undergo various technological and organizational changes, skills shortages may become a critical bottleneck for improving firm performance.

Based on above theoretical and empirical evidence is the following:

Hypothesis 1: A firm’s skills shortages will be negatively related to the firm’s performance.

The Moderating Role of High Performance Work Systems

High performance work system

In SHRM literature, scholars agree that HPWS represent an important driver for higher firm performance. This assertion has been supported in empirical studies that have consistently found a positive relationship between HPWS and firm performance (Datta et al., 2005, Collins and Smith, 2006). These positive outcomes are achieved through a positive impact on employee attitudes and such behaviors as job satisfaction, commitment, empowerment, and low absenteeism and turnover (e.g., Macky & Boxall, 2007).

HPWS refer to a combination of distinct but interrelated HR practices aimed at enhancing employee skills and efforts (Datta et al., 2005; Huselid, 1995). These individual practices are often referred to as high performance work practices (HPWPs) because they develop and leverage employees’ knowledge, skills and abilities to create more value for the firm. The HR practices commonly considered as HPWPs include compensation and benefits, recruitment and selection, career development, employee participation, training, and flexible work arrangements (Huselid, 2005; Pfeffer, 1998; Posthuma, Campion, Masimova, & Campion, 2013).

Previous research shows different mechanisms through which HPWPs affect firm performance: (i) HPWPs help a firm develop its human capital by focusing on enhancing employees’ knowledge, skills, and abilities (KSAs), (ii) HPWPs empower employees to leverage their skills for organizational benefits and to enhance their commitment and motivation to do so (Becker & Huselid, 1998; Delery & Shaw, 2001; Macky & Boxall, 2007), (iii) HPWPs build organizational social capital and improve internal social structures through information sharing, flexible job designs,  and resource exchanges among organizational members (Evans & Davis, 2005).

Evidence shows that an organization can gain competitive advantage by investing in HR practices and aligning these practices with the company’s overall business strategy (Cooke, 2007; Kaufman & Miller, 2011; Sirmon & Hitt, 2009). However, the effectiveness of HR practices can be increased even more by strategically configuring them, resulting in higher levels of synergistic alignment with organizational strategies (Buller & McEvoy, 2012; Subramony, 2009). When an organization bundles internally consistent and mutually reinforcing HR practices, it implements HPWS (Huselid, 1995). Research has shown that the impact of HPWS is greater than the individual HPWPs operating separately (Combs et al., 2006). This is because HR practices can have additive and synergistic effects (Delery, 1998; Huselid, 1995). However, HPWS are effective only when HPWPs result in “powerful combination” to maximize firm performance and avoid “deadly combination” that results in negative synergies (Becker and Huselid, 1998; Delery, 1998; Dyer & Reeves, 1995).


As stated above, according to the resource-based view (RBV), a company can gain a sustainable competitive advantage by creating value through internal resources which are rare and difficult to imitate by competitors. Although human capital is an important resource, a company needs HR practices to make the best use of this resource in order to gain a competitive edge.  HPWS are a source of competitive advantage as highlighted by many scholars (e.g., Wright et al., 2001; Patel & Conklin, 2012). HPWS are difficult to imitate because they represent intangible complex and dynamic social structures (Reed & De Filipi, 1990; Barney & Wright, 1998; Becker & Huselid, 1998).

In addition, HPWS are path-dependent, which is an important dimension of inimitability, thus making it difficult for competitors to replicate (Razouk, 2011). As such the unique historical conditions of the firm make it difficult for competitors to obtain the same assets or HPWS. It should be noted that inimitability can also result from causal ambiguity, which stresses that it is difficult to identify the true source of competitive advantage. It is not only the bundled-together HR practices that embody causal ambiguity but also the alignment of skills, motives, and most importantly, organizational structure, processes and systems simultaneously lend a firm competitive advantage. Because of path dependency and causal ambiguity inherent in HPWS, it would be difficult for competitors to imitate HPWS.

Skills shortage, HPWS, and firm performance

This section, suggests that HPWS can mitigate the negative effects of talent shortages on firm performance, that is, HPWS moderate the negative relationship between the firm’s talent shortages and its performance. HPWS allow a company to strategically align its HR practices with the overall business strategy. This strategic alignment will provide a unique focus to direct all of the company’s resources towards achieving the firm’s strategic objectives. In the context of the firm’s talent shortages, the mutually reinforcing HR practices in HPWS result in higher levels of synergic alignment with the business’ strategy (MacDuffie, 1995). HPWS constitute a key feature of the work environment and can often signify what the organization values and expects from its employees (Bowen & Ostroff, 2004; Van De Voorde & Beijer, 2015).

When an organization uses HPWS, employees tend to anticipate that their managers expect increased work effort and improved performance from them (Koys, 1988; Van De Voorde & Beijer, 2015). The implementation of HPWS will help improve organizational processes such as improving existing employees’ KSAs and motivation, and also improving internal social structures through information sharing and increased cooperation (Combs et al., 2006; Evans & Davis, 2005).

Such HR practices as extensive recruitment and selection will allow the company to find the best talent in the external labor market. When a company hires talented employees with multiple skills, it can deploy them in different areas and across different jobs in the organization (Guthrie, 2001). Wherever there is a need, HPWS employees could be transferred to those positions. When an organization faces talent shortages, it is imperative for it to retain key talent. Extensive training for existing employees will help develop and update existing skills and expand capability and flexibility (Guthrie, 2001).

Employees who receive training learn better how to apply their current and new skills to improve business processes (Gephart, Marsick, Van Buren & Spiro, 1996). In such circumstances, various programs (such as job flexibility, job involvement, job enlargement, and employee participation) that aim to improve employee engagement can also help retain employees. The contributions of high skilled employees will be limited when they are not provided with opportunities to utilize their expertise to implement new and better ways to do their jobs (Bailey, 1993).

The organizational structures listed above become even more important when the firm experiences talent shortages. With internal talent shortages, an organization cannot afford to lose existing talent to competitors. Providing career development opportunities and allowing employees to reach their potential is crucial for an organization to sustain its competitive advantage. Thus, the firm’s restructuring through “powerful connection” of HR practices (i.e. HPWS) (Becker, Huselid, Pickus & Spratt 1997) will be an important means to maximize employees’ contributions to maintain, improve and sustain their performance (Huselid, 1995), particularly when an organization faces talent shortages. Hence the following:

Hypothesis 2: HPWS moderate the relationship between the firm’s skill shortages and performance such that the negative relationship between the firm’s skill shortages and performance will be weak when the firm implements HPWS as compared to when it does not implement HPWS.


We tested the proposed hypotheses using data from the Talent Management Study: U.S. Workplaces in Today’s Business Environment, 2009. The data are publicly available and the study was funded by Alfred P. Sloan foundation (Pitt-Catsouphes & Sweet, 2009). The data are from a collection of about 700 workplaces in the US, and the study aimed to assess the extent to which organizations adapted to the significant socioeconomics changes and workforce aging.

The study also sought to understand the employee practices adapted by firms to improve workforce quality. The sampling frame was US workplaces from 10 industry sectors with 50 or more employees. In the pilot phase from February 1 to March 30, 2009, the data collection effort focused on assessing the number of participants to reach the response goal of 750 workplaces. The data collection phase spanned from April 1 to June 30, 2009. The data were collected using a web-based survey, and the questions were drawn from human resource practices and organizational composition. The data collection period ranged from March 11, 2009 to August 28, 2009.

The response rate was 42.7 percent from HR Directors or equivalent persons, and the final sample included 696 US work places. To test the proposed hypotheses, the authors included only for-profit firms (579 firms) and dropped non-profit firms (114 firms), as the motives for HPWS in non-profits differ fundamentally. In addition, the study did not use any filters and, based on pairwise deletion of the remaining variables, the final sample included 211 US workplaces.


Relative profitability. This variable was self-reported; each respondent reported “Profitability as compared to other organizations in sector” (1-poor/at the low end of the industry, 2-below average, 3-average or equal to most competitors, 4-better than average, 5-superior). The mean was 3.541, and the standard deviation was 0.873.

To further assess the fidelity of the self-reported relative profitability measure, we took three additional steps.

First, we test whether the relative profitability is  normally distributed. If the self-reported outcome measure is skewed to the right, then there may be a possibility of over-reporting firm performance. Shapiro-Wilk test (z = 1.180) suggested that we could not reject the null that relative profitability is normally distributed.

Second, we assessed correlation of relative profitability with ‘productivity relative to other organizations in the sector’ (r = 0.5780, p = 0.0000), ‘compared to 1 year ago, assessment of financial performance’ (r = 0.1828, p = 0.0000), or ‘Stock market performance (if publicly traded)as compared to other organization’ (r = 0.6344, p = 0.0000). The strong positive correlations suggest that agreement in the level of performance assessment relative to competitors.

Third, we run a factor analysis for the three alternate measures of performance, without including the the fourth measure of performance (stock market performance relative to other orgnaizations) as very few firms in the sample were publicly traded. The factor analysis resulted in a single factor. Although we cannot fully rule out the possibility of bias in reporting, as in many self-report studies, we conclude that there is a strong internal consistency in reporting of performance. Elsewhere, in other research, self-reported performance is comparable to objective performance (Dess & Robinson 1984; Miller, Washburn & Glick, 2013).

Skills shortage. The respondents were asked to rate “To what extent are the following skills in “short supply” at your organization?” (1- not at all, 2-to a limited extent, 3-to a moderate extent, 4-to a great extent) in 11 areas: management skills, operation skills, human resource skills, finance skills, administrative support skills, legal skills, technical computer skills, sales/marketing skills, basic literacy in writing and math, customer relations skills, and other. The authors took the mean of the responses. The mean of skills shortage was 1.744 (s.d. = 0.598).

HPWS. The HPWS measure is an index of 30-items. The respondents were asked to evaluate: “In your opinion, to what extent does your organization have programs or policies for recruitment, training, engagement, career progression, and retention for the employee groups noted below? (1-too few policies/programs, not enough; 2-just about the right number of policies/programs; 3-an excessive number of policies/programs, too many) in each of the five areas [recruitment, training, engagement, career progression, and retention]:

(i) For your employees, in general;

(ii) For employees who are racial/ethnic minorities;

(iii) For employees who are younger workers,

(iv) For employees who are midlife;

(v) For employees who are older workers; and

(vi) For employees who are women.

Each of the five questions was evaluated on the scale of 1 to 3 in individual areas of recruitment, engagement, career progression, and retention – resulting in 25 responses ([five areas of recruitment, training, engagement, career progression, and retention] multiplied by [five questions for employees in general, minority, younger, midlife, older, and women employees]). In addition to the 25-items, the authors also included five additional measures of HPWS:

(a) profit-sharing schemes;

(b) performance-related pay;

(c) stock options (if offered);

(d) bonuses for individual goals; and

(e) bonuses based on team goals

(“Approximately what portion of your workforce has ACCESS to the following employer-sponsored benefits or programs? 0 – None, 1-some (1% to 50%), 2-most (51% to 85%), 3-all/nearly all (approximately 86% to 100)).” The measures were averaged to create the HPWS index, and the mean was 1.644 (s.d. = 0.329).

Controls. To limit the effects of rival explanations, the authors included controls on the number of employees (count of employees), the count of worksites of an organization, and whether the firm is owned or controlled by the family (1= non-family firm; 2 = family-firm). As career development opportunities could mitigate the effects of skill shortages, the authors drew on a 13-item scale to measure career development. The lead question was “To what extent do you use […] to stimulate learning for career development? 1- not at all to 4-to a great extent).

The options included special tasks/projects, on the job training for career development, involvement in cross-functional tasks for career development, participation in project team work, networking for career development, formal career plans for career development, succession plans for career development, planned job rotation for career development, internal movement to a different department for career development, external movement to a partner business for a temporary period for care, coaching for career development, mentoring for career development, and E-Learning for career development.” The Cronbach’s alpha was 0.867.

As the data collection overlapped with the Great Recession, the survey asked respondents to evaluate “How would you characterize the impact of today’s economic circumstances? (1-very negative to 5-very positive): in

(i) your organization/company;

(ii) your industry;

(iii) all companies/organizations in the local/state/regional economy (not just for your company/organization), in general;

(iv) all companies/organizations operating in the U.S., in general;

(v) all companies/organizations around the world, in general;” and “When you think about the ways that economic circumstances affect business operations, how would you characterize today’s situation compared to one year ago? Compared to 1 year ago, impact of economic circumstances on (1-much worse than to 5-much better):

(vi) your organization/company;

(vii) your industry;

(viii) all companies/organizations in the local/state/regional economy (not just for your company/organization), in general;

(ix) all companies/organizations operating in the U.S., in general;

(x) all companies/organizations around the world, in general.” The 10-item scale is the proxy for assessment of recession effect. The Cronbach’s alpha was 0.87.

To control for centralized decision making on HR aspects, the authors drew on a four-item scale “Where are decisions primarily made about polices re: (i) compensation and bonus; (ii) talent management; (iii) training and development; (iv) lay-offs/reduction (1-local sites, 2-subsidiary or division, 3-national headquarters, 4-internaitonal headquarters, and 5-other).” The Cronbach’s alpha was 0.929.

In addition the authors controlled for sector effects with pharmaceutical as reference category – construction, manufacturing, wholesale trade, retail trade, transportation and warehousing, finance and insurance, professional scientific and professional services, administrative support and waste management and remediation services, health care and social assistance, accommodation and food services, among others.


Table 1 lists the mean, standard deviation, and pair-wise correlations. The reported correlations and the sample descriptives are based on casewise deletion resulting from all the variables included in the final model.

Table 2 presents the results from ordinary least squares (OLS). In the first step, we include controls and the HPWS measure (Modle 1). In the second step (Model 2) to assess the additional variance explained by skills shortage, and to test for Hypothesis 1, we introduce skills shortage variable. In the third step (Model 3), we introduce the interaction term to test for Hypothesis 2. Based on the recommendation of Aiken and West (1996) the authors mean-centered the variables. The variance inflation factor was 1.19 for skill shortage, and 1.28 for HPWS. The average variance inflation factor was 6.67. As all the variables were self-reported, in a Harman’s single factor analysis the authors used all variables in the model (except industry sector). The profitability measure had the uniqueness of 0.9286 across five identified factors, and skills shortage and HPWS had a uniqueness of 0.8941 and 0.6727, respectively. In the OLS the Wald Chi-square difference test between HPWS and skills shortage measure was (F(2, 191) =    2.82; prob > F = 0.0620).

Among the sectors all sectors except transportation and warehousing were positively associated with performance.


Insert Tables 1 and 2 and Figure 1 about here


Hypothesis 1 predicted that skills shortages would be negatively related to profitability; however, this hypothesis was not supported (Table 2, model 2: β = -0.0459, p > 0.10). While the direction of effect was negative as expected, the relationship was not statistically significant. Inclusion of skills shortage in Model 2 increased R-square by 3.5%.

Hypothesis 2 proposed that HPWS would mitigate the negative relationship between skills shortage and profitability (Table 2, model 3: β = -0.159, p < 0.05). As presented in Figure 1, with increasing skills shortage, higher levels of HPWS lower performance, whereas lower levels of HPWS increase performance. Thus, Hypothesis 2 is supported in the proposed direction. However, as theory would suggest, at lower levels of skills shortage, HPWS lead to higher performance (to the left of Figure 1), however, as skills shortage increases, returns from higher HPWS  decline, and returns from lower HPWS increase. The R-square increases from model 2 to 3 by 1.7%. The margins command in Stata 14.2 the value for each level was significant at 0.00. Using the bootstrap option the findings were similar. The inferences for Hypothesis 2 are in the opposite direction of the predicted relationship.


Our study showed that organizational context is more important than simply adopting HPWS. Although past research demonstrated that HPWS and firm performance are positively related to each other (Delaney & Huselid, 1996; Guthrie, 2001), the findings of this study demonstrate that the use of HPWS may not always yield better organizational performance, that is, when organizations face talent shortages, the use of HPWS might be detrimental to organizational performance. Hence, adopting HPWS when a firm is experiencing skills shortage can in fact be much more costly for the organization.

This study first hypothesized that skills shortage will be negatively related to a firm’s profitability. However, no support was found for this hypothesis. Hypothesis 2 proposed that HPWS would moderate the negative relationship between skills shortage and profitability. The findings show that the opposite is true, that is, a firm’s profitability is reduced when it implements HPWS in the context of labor shortages. It is interesting to note that the study found support that HPWS positively impact firm profitability (beta = 1.34, p <.05 in model 3). This finding is consistent with the existing research on HPWS, which demonstrated the positive association between the use of HPWS and firm performance (Datta et al., 2005; Takeuchi, Chen, & Lepak, 2009).

However, the results show that the interaction of HPWS with skill shortages changes the direction of the relationship, that is, it becomes negative. Instead of RBV of the firm, these findings support the contingent view of HRM suggesting that the use of various HR practices and the benefits associated with each configuration of HRM depend on contextual factors, that is, the effectiveness of HR bundles vary by sectors and business strategy (Arthur, 1994; Youndt, Snell, Dean & Lepak, 1996; Appelbaum, Bailey, Berg & Kalleberg, 2000). Previous research showed that environmental factors such as industry (Datta et al., 2005) and organizational factors such as strategy, culture and routines, and size play an important role in the effectiveness of HPWS (Huselid, 1995; Jackson & Schuler, 1995).

In line with this research, this study contributes to the existing HPWS literature by demonstrating that organizational skills shortage is another important factor that can affect the effectiveness of HPWS. It shows that in the context of skills shortage, HPWS will do more harm as manifested in the decline in profitability (beta = -.59, p <.05). These findings suggest that the benefits produced through the use of HPWS do not exceed the cost associated with implementing HPWS when a firm faces skill shortages. The findings are in line with previous research, which suggests that HPWS do not play any role in increasing firm output when considering organizational context (Sels, Winne, Maes, Delmotte, Faems, & Forrier, 2006). This could be explained through a labor process approach (Ramsay, Scholarios & Harley, 2000), suggesting that HPWS may directly or indirectly lead to work intensification.

When a firm uses HPWS, it uses extensive recruitment and selection practices, provides employees with extensive training, and gives them discretion to perform their job. In return, employees may feel obligated to give back to their employer by working harder and exerting extra effort. Consequently, employees may feel drained as a result of work intensification. The outcome of this approach would be that employees who are exposed to HPWS could experience higher stress levels leading to work intensification (Macky & Boxall, 2008), a factor which has been shown to negatively affect employee and organizational outcomes (Bamberger, Larsen, Vinding, Nielsen, Fonager, Nielsen, Ryom, 2015; Omari & Paull, 2015; Valeyre, 2004). Thus these opportunities for employees may come at the expense of such negative employee outcomes as strain, and work intensification and, ultimately, adverse organizational outcomes.

From a practical perspective, this study offers useful insights for HR practitioners and senior management. HPWS are usually considered as a panacea to increase firm performance; hence the usefulness of HPWS is accepted without question. This study shows that this is not the case when a firm experiences talent or skills shortage. Managers need to consider internal and external factors before implementing HPWS. In the case of skills shortage, the use of HPWS would be harmful and adversely affect the firm’s profitability as manifested by this study’s findings. In such circumstances some sort of control mechanism through the use of control-focused HR practices coupled with commitment-focused HR practices might be useful to keep employees on track as well as motivate and engage them at the same time (Arthur, 1994). The control-focused HR approach enhances efficiency and reduces direct labor costs by focusing on strict work procedures and basing rewards on outputs (Arthur, 1994). These practices could be used with other developmental practices such as training and constructive performance appraisals.

It is important to note that the data for the study were collected in 2009; since then, the context has changed in that the economy has slowly recovered, consumer spending has increased, fixed asset investment has accelerated, and the unemployment rate has declined (Financial Times, 2016). Although, the study controlled for the recessionary effects in the data analysis, caution is required when interpreting the results in today’s competitive business environment.

To the authors’ knowledge, this study is the first to demonstrate that internal skill shortage is an important contextual factor that could impede the effectiveness of HPWS. Thus, scholars doing research in strategic human resource management are encouraged to replicate the findings in a similar context in future studies. It is important to note that the study did not examine the inter linkages between HPWS and firm performance and one can only speculate that reduced profitability could  result from negative employee outcomes. Thus, the authors suggest that readers interpret the study’s results with caution. Scholars are encouraged to examine the process of how HPWS reduce firm’s profitability by incorporating employee outcomes in the context of labor shortages.

All data were collected through the same instrument, so common method bias could be an issue. However, the chance of such bias is less in moderation as Monte Carlo simulations have demonstrated significant interaction effects could not be generated through such bias (Evans, 1985). Nevertheless, the results should be interpreted with caution. The authors recommend using employee data on the usage of HPWS, as studies widely recognized that it is not the actual HR practices per se, but rather employees’ perceptions of these practices that affect employee and organizational outcomes (Nishii, Lepak & Schneider, 2008).

Note, too, that the authors used self-reported data of firm’s relative profitability. While objective measures are recommended due to the possibility of social desirability bias, the descriptive (M = 3.541, and S.D. = .873) shows that the responses were not biased towards over-reporting performance relative to competitors. Moreover, such subjective assessment about a company’s profitability is usually accurate as discussion on the company’s profitability is always on the meeting agenda for senior managers. Hence, the self-reported data should not cast doubt on the usefulness of the results as subjective measures of firm performance are widely used in organizational research and are considered to have good validity equivalent to objective measures (Wall, Michie, Patterson, Wood, Sheehan, Clegg & West, 2004; Woodside, 2010). Furthermore, the data were collected from U. S. companies; thus, the generalizability of the results could be limited and might not be applicable in other countries.


This research study sought to examine whether internal skills shortages lower firm profitability. Additionally, the study aimed to explore the role of HPWS in the context of internal labor shortages. Interestingly, the study found that internal skills shortage was not related to firm profitability. The findings also showed that the use of the HPWS lowers firm profitability when firms face internal skills shortages. The results suggest that the use of HPWS does not necessarily translate into higher firm performance; rather organizational context (that is, the availability of internal skills) should also be considered in order to make the most optimal use of firm’s human capital.


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      N Mean SD Min Max 1 2 3 4 5 6 7 8 9
1 Profitability   211 3.5924 0.9022 1 5 1                
2 Number of employees   211 1314.6490 6914.2100 30 80000 0.0736 1              
3 Number of worksites   211 23.2701 76.6004 1 600 0.0839 0.5441* 1            
4 Family owned   211 1.3649 0.4826 1 2 -0.0396 0.0786 0.1929* 1          
5 Centralized decision making 211 1.9171 0.9769 1 5 0.0682 0.036 0.0603 0.0847 1        
6 Career development   211 2.1819 0.5458 1 4 0.0895 0.2251* 0.0805 0.1362* 0.1625* 1      
7 Recession effect   211 1.9982 0.4527 1 3.8182 -0.0218 0.0833 0.0802 0.0466 0.1034 0.0179 1    
8 Construction   211 0.0995 0.3001 0 1 0.0978 -0.0355 0.0309 -0.1205 0.0242 0.0008 -0.0847 1  
9 Manufacturing   211 0.1517 0.3595 0 1 0.0006 -0.0621 -0.0777 -0.046 -0.0013 -0.1133 -0.0063 -0.1406* 1
10 Wholesale Trade   211 0.0332 0.1795 0 1 0.0545 -0.0308 -0.0488 0.0245 0.0972 -0.017 -0.0366 -0.0616 -0.0783
11 Retail Trade   211 0.1327 0.3401 0 1 0.0219 -0.0618 -0.0793 -0.1804* -0.0921 -0.0616 -0.0153 -0.13 -0.1654*
12 Transportation and Warehousing 211 0.0379 0.1914 0 1 -0.1858* -0.0353 -0.0523 -0.0474 0.0678 -0.0768 -0.0242 -0.066 -0.0839
13 Finance and Insurance 211 0.0758 0.2654 0 1 -0.0294 -0.0432 -0.0511 0.2291* 0.006 0.0662 -0.0674 -0.0952 -0.1211
14 Professional Scientific and Professional Services 211 0.0711 0.2576 0 1 0.0433 -0.0208 -0.0596 0.0968 0.1702* 0.0743 0.0679 -0.092 -0.117
15 Health Care and Social Assistance 211 0.1043 0.3063 0 1 -0.0178 0.0577 0.1894* 0.2246* -0.0068 -0.0066 0.2761* -0.1134 -0.1443*
16 Accomadation and Food Services 211 0.1564 0.3641 0 1 -0.0225 0.2074* 0.131 -0.0554 -0.1809* 0.0423 -0.0199 -0.1431* -0.1821*
17 Other   211 0.1280 0.3348 0 1 0.0158 -0.0252 -0.0299 -0.0251 -0.0111 0.0845 -0.0985 -0.1274 -0.1620*
18 Pharmaceuticals   211 0.0095 0.0971 0 1 -0.0644 -0.0174 -0.024 -0.0742 0.2091* 0.0088 0.0014 -0.0325 -0.0414
19 Skills shortage   211 1.7178 0.5713 1 3.7273 -0.0495 0.0568 0.0202 -0.0078 0.0017 -0.1051 -0.0533 -0.0525 0.0007
20 HPWS_new   211 1.7143 0.3376 1 2.5714 0.1093 0.0573 0.0136 0.0188 -0.0002 0.4149* 0.0351 0.0887 -0.0269


* p < 0.05 or below (two-tailed test)

Table 1 (contd.)

      10 11 12 13 14 15 16 17 18 19
10 Wholesale Trade   1                  
11 Retail Trade   -0.0725 1                
12 Transportation and Warehousing -0.0368 -0.0777 1              
13 Finance and Insurance -0.0531 -0.112 -0.0569 1            
14 Professional Scientific and Professional Services -0.0512 -0.1082 -0.0549 -0.0792 1          
15 Health Care and Social Assistance -0.0632 -0.1335 -0.0677 -0.0977 -0.0944 1        
16 Accomadation and Food Services -0.0798 -0.1684* -0.0855 -0.1233 -0.1191 -0.1469* 1      
17 Other   -0.071 -0.1498* -0.076 -0.1097 -0.106 -0.1307 -0.1649* 1    
18 Pharmaceuticals   -0.0181 -0.0383 -0.0194 -0.028 -0.0271 -0.0334 -0.0421 -0.0375 1  
19 Skills shortage   -0.1193 0.0622 -0.0007 0.1076 -0.1337 0.1368* 0.0987 -0.1362* -0.1076 1
20 HPWS_new   -0.034 -0.0604 0.0134 0.0187 0.0134 -0.0341 -0.0281 0.0555 0.0083 -0.2041*


* p < 0.05 or below (two-tailed test)


Hierarchical OLS

  (1) (2) (3)
VARIABLES Profitability Profitability Profitability
Skills shortage [H1]       -0.0459     0.953+
        (0.122)    (0.507)
Skills shortage × HPWS [H2]        -0.591*
HPWS 0.336*     0.256     1.335*
      (0.140)    (0.240)    (0.603)
Number of employees   5.36e-06   4.76e-06  5.72e-06
     (3.91e-06)   (6.79e-06)  (6.73e-06)
Number of worksites  -6.28e-05    0.000810   0.000825
     (0.000696)    (0.000835)   (0.000817)
Family owned    -0.0770    -0.133    -0.122
    (0.0911)    (0.149)    (0.148)
Career development    0.0268     0.0296      0.0105
    (0.0913)    (0.150)    (0.148)
Recession effect   -0.112    -0.0830    -0.0645
    (0.0910)    (0.162)    (0.163)
Centralized decision making    0.0489     0.0817     0.0809
    (0.0413)    (0.0742)    (0.0758)
Construction 0.678***   1.024***     0.986**
    (0.202)    (0.248)    (0.305)
Manufacturing    0.481**     0.847** 0.872**
    (0.186)    (0.257)    (0.317)
Wholesale trade    0.764**     1.073*     1.122*
    (0.292)    (0.463)    (0.490)
Retail trade    0.528* 0.903** 0.988**
    (0.208)    (0.280)    (0.337)
Transportation and warehousing    0.151    -0.0399    -0.0908
    (0.263)    (0.388)    (0.419)
Finance and insurance    0.571* 0.792**     0.826*
    (0.232)    (0.304)    (0.352)
Professional scientific and professional services    0.671**   0.945*** 0.935**
    (0.212)    (0.256)    (0.320)
Administrative support and waste management and remediation services 0.934***    

Robust standard errors in parentheses

*** p<0.001, ** p<0.01, * p<0.05, + p<0.10        

Table 2 (contd.)

  (1) (2) (3)
VARIABLES Profitability Profitability Profitability
Health care and social assistance 0.690** 0.834* 0.852*
     (0.209)     (0.338)     (0.382)
Accommodation and food services     0.404*      0.779**  0.765*
     (0.192)     (0.273)     (0.328)
Other     0.487*  0.834**   0.851**
     (0.194)     (0.262)     (0.319)
Pharmaceuticals [reference category],
Constant   2.624***    2.506***      0.632
     (0.361)     (0.603)    (1.204)
Observations 512   211 211
Adjusted R-squared     0.049      0.084      0.101
Change in Adjusted R-square   0.035 0.017
LR Chi-square   766.25(0)[1] 4.16(1)*

Robust standard errors in parentheses

*** p<0.001, ** p<0.01, * p<0.05, + p<0.10

Figure 1

Interaction plot

[1] As the number of variables in Model 1 and Model 2, are the same, the test is based on the assumption that Model 1 is nestd in Model 2. LR Chi-square tests are based without the ‘robust’ specification, as the lrtest option in Stata does not allow for robust specification.

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