HR Systems Case
The impact of HRM digitalization on firm performance: investigating three-way interactions
Yu Zhou Renmin University of China, China
Guangjian Liu Renmin University of China, China
Xiaoxi Chang China University of Political Science and Law, China
Lijun Wang Renmin University of China, China
In this study, drawing from adaptive structuration theory (AST) and embeddedness theory, we
investigate the relationship between the interaction of HRM digitalization and HRM system matu-
rity on firm performance as well as the moderating role played by HR strategic and business
involvement. On the basis of a sample of 211 listed enterprises of China, our results indicate that
the interaction of HRM digitalization and HRM system maturity is positively related to firm perfor-
mance and that the relationship is strengthened by HR strategic and business involvement. The
implications of our findings for research and practice are discussed.
Keywords: adaptive structuration theory, HR business involvement, HR strategic involvement,
HRM digitalization, HRM system maturity
Key points
1 HRM digitalization can release a significant main effect to enhance firm
performance.
2 The maturity of HRM systems can strengthen the positive effect of HRM digitaliza-
tion on firm performance.
3 When HR departments are deeply involved in the organization’s strategic manage-
ment, the positive influence of HRM digitalization will be increased.
4 When HR departments are deeply involved in the business operation, the positive
impact of HRM digitalization will be enhanced.
Correspondence: Guangjian Liu, School of Business, Renmin University of China, No. 59 Zhongguancun Street, Haidian District, Beijing 100872, China; e-mails: iuguangjian@ruc.edu.cn and Xiaoxi Chang, School of Business, China University of Political Science and Law, 25 Xitucheng Lu, Haidian District, Beijing 100088, China; e-mail: xiaoxi.chang@cupl.edu.cn
Accepted for publication 9 March 2020.
Asia Pacific Journal of Human Resources (2020) ��, �� doi:10.1111/1744-7941.12258
© 2020 Australian HR Institute
Introduction
The digital economy has received increasing attention over the past several years (Amladi
2017; Calvard and Jeske 2018; Ru€el, Bondarouk and Looise 2004; Wang, Kung and Byrd
2018), and human resource management practices are becoming more digital (Bon-
darouk, Parry and Furtmueller 2017). Up to now, there are two research mainstreams
about the digital trend of human resource management. The first one focuses on making
the workplace and people management more intelligent with the adoption of information
technologies, such as e-HRM, which has been broadly defined as ‘an umbrella term cover-
ing all possible integration mechanisms and contents between HRM and information
technologies aiming at creating value within and across organizations for targeted
employees and management’ (Bondarouk and Ru€el 2009, 507). Researchers in the other
mainstream pay attention to conducting evidence-based HRM decision-making by data
analysis, such as HR analytics which was defined as ‘HR practices enabled by information
technology that uses descriptive, visual, and statistical analyses of data related to HR pro-
cesses, human capital, organizational performance, and external economic benchmarks to
establish business impact and enable data-driven decision-making’ (Marler and Boudreau
2017, 15). Although the above-mentioned two research mainstreams are closely connected
to each other, surprisingly, they are developing independently and few scholars have con-
ducted in-depth research on the internal relationship between them. One reason for this
phenomenon may be that the quantitative empirical research about HR analytics is quite
minimal, even though it has been discussed for many years (Marler and Boudreau 2017).
E-HRM researchers tend to focus on the antecedents of e-HRM, such as the size of
organization (Panayotopoulou, Galanaki and Papalexandris 2010), HR manager experi-
ence (Parry 2011) and the perceived compatibility (Quaosar 2017), but the consequences
gained relatively less attention (Bondarouk et al. 2017). Within the limited studies on the
consequences of e-HRM, the majority of existing studies mainly focus on its influence on
users’ attitudes and behaviors, such as perceived usefulness (Marler, Fisher and Ke 2009)
and frequency of use (Ru€el and Van der Kaap 2012), or on HR-related outcomes of the
organization, such as HRM service quality and HRM effectiveness (Obeidat 2016; Panos
and Bellou 2016). Moreover, the conclusions of whether e-HRM can bring positive orga-
nizational outcomes are inconsistent (Buckley, Minette, Joy and Michaels 2004; Reddick
2009). For example, Reddick (2009) did not find a significant relationship between e-
HRM usage and costs reducing and only Buckley et al. (2004) provided numerical data for
cost savings due to the application of e-HRM.
The reasons why e-HRM cannot yield expected results may be partly due to the lack of
effective analyses and the utilization of data held in e-HRM systems. In the era of ‘Big
Data’, it is quite necessary to consider these two mainstreams together, because on the one
hand, e-HRM systems can not only help to collect abundant and valuable data for HR data
analysis, but can also enhance the efficiency of analysis with the help of digital technolo-
gies (Angrave, Charlwood, Kirkpatrick, Lawrence and Stuart 2016); on the other hand,
the results of HR analyses can help to understand the effectiveness of e-HRM systems
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(e.g., e-learning system), through which insightful guidance can be carried out to optimize
e-HRM systems within organizations. In fact, some researchers have also called on com-
bining these two research mainstreams together, as HR analytics or e-HRM itself may not
predict productivity effectively when working separately (e.g., Aral, Brynjolfsson and Wu
2012; Marler and Boudreau 2017). With the aim of filling the abovementioned gap, we
conduct this exploratory study. After a thorough review of related literatures on ‘digital’
technologies as well as data analytics implemented in HRM (e.g., DeSanctis 1986; Liem
et al. 2018; Marler and Boudreau 2017; Obeidat 2016; Suen and Chang 2017), we extend
extant literatures by integrating the employment HR technology systems and HR data
analysis and putting forward ‘HRM digitalization’ which refers to ‘the processes of
employing digital technologies and appropriate data to promote the efficiency and effec-
tiveness of HRM activities’.
Apart from the gaps mentioned above, there is still a lack of theoretical foundations
and a clearly defined paradigm in this immature field and previous researchers have
been calling for more theoretical and empirical studies (Bondarouk et al. 2017; Marler
and Fisher 2013; Strohmeier 2007). In this study, we conduct a thorough investigation
of the influence of HRM digitalization on firm performance as well as the boundary
conditions mainly on the basis of adaptive structuration theory (AST). AST provides ‘a
model that describes the interplay between advanced information technologies, social
structures, and human interaction’ in organizations (DeSanctis and Poole 1994, 125).
According to AST, the effectiveness of advanced information technology varies depend-
ing on the task, the environment, and other contingencies that offer alternative
arrangement of organizational structures, for example, integrative organization systems,
and standard operating procedures can serve as a structural and institutional basis that
can be incorporated into the development and application of advanced technology
(DeSanctis and Poole 1994). In this study, we introduce HRM system maturity as the
institutional basis of an organization’s HRM digitalization practices. HRM system
maturity refers to the integrative and progressive level of HRM systems and processes
within an organization (Curtis, Hefley and Miller, 2009; Ford, Evans and Masterson
2012), and it can be described by some structural characteristics such as standardized
HRM practices and integrative HRM processes (Chen, Daugherty and Roath 2009).
HRM system (or processes) maturity is based on the Capability Maturity Model
(CMM) which was developed by the Software Engineering Institute (SEI) at Carnegie
Mellon University (CMU) to evaluate the maturity level of the software development
process and later has been extended to many other domains, such as human resource
management. Up to now, there are very few empirical studies on the HRM system (or
processes) maturity, and limited researches tend to pay attention to People CMM (e.g.,
Chen and Wang 2018; T€uretken and Demir€ors 2004; Zare, Tahmasebi and Yazdani
2018). Previous researchers have reported that the standardization of HR processes is
an important influencing factor when adopting human resource information systems
(Hannon, Jelf and Brandes 1996). Based on existing studies, we argue that the effect of
HRM digitalization on firm performance may be influenced by the maturity of HRM
© 2020 Australian HR Institute 3
Yu Zhou et al.
system structures (Hannon et al. 1996), as without a solid basis in the HRM system
and process, randomly adopting HRM digitalization practices tends to result in chaos
(Marler et al. 2009) or cannot give the full play of the advantages of HRM digitaliza-
tion efforts.
Besides the structural foundation (e.g. HRM system maturity), AST also contends
that the effect of advanced information technology relies on its interplay with human
interactions (DeSanctis and Poole 1994). However, the nature of these interactions is
not elaborated upon in detail in AST. In this study, we introduce embeddedness theory
as a complementary perspective to AST to investigate the contingent role played by
human interactions. Embeddedness theory asserts that there are two types of network
embeddedness: structural and relational embeddedness (Granovetter 1985; Gulati
1998). Structural embeddedness focuses on the informational role of the position an
actor occupies in the overall structure of the network, while relational embeddedness
refers to the quality of dyadic exchanges, including the degree to which actors consider
one another’s needs and goals as well as the behaviors that they exhibit toward one
another, such as trust, norms, reputation, sanctions, and obligations (Coleman 1990;
Granovetter 1985; Gulati 1998). By allying AST with embeddedness theory, this paper
investigates the influence of the interaction of HRM digitalization and HRM system
maturity on firm performance as well as the contingent role played by HR strategic and
business involvement.
The contributions of this paper are threefold: first, faced with the deficiency of
studies pertaining to the consequences of e-HRM, this exploratory study not only
introduces ‘HRM digitalization’ which highlights the importance of integrating the
employment of digital HR technologies and the analysis and utilization of HR data, but
also demonstrates the positive effects of the interaction of HRM digitalization and
HRM system maturity on firm performance. In addition, by introducing AST into this
study, we enrich the limited theoretical perspectives of e-HRM (Bondarouk et al. 2017)
and validate the point of view mentioned by AST, that is, advanced technology should
match the structure of the organization (DeSanctis and Poole 1994). Second, by allying
AST with embeddedness theory, we develop one of the basic rationales of AST, that is,
the effectiveness of advanced technology also hinges on human interaction (DeSanctis
and Poole 1994, 125), and demonstrate the contingent effect of two kinds of interacting
styles (i.e. participating in strategic decision-making processes and cultivating partner-
ships with business) on the effectiveness of advanced HRM technology (e.g. e-HRM).
Third, we further employ the two dimensions of structural embeddedness and rela-
tional embeddedness within embeddedness theory, which contributes to the deep inves-
tigation of the nature of actor interactions, particularly the interaction of HR
professionals with strategic makers and business managers. By testing two three-way
interaction models, we find that the positive relationship between the interaction of
HRM digitalization and HRM system maturity and firm performance is strengthened
when HR strategic (or business involvement) is high.
© 2020 Australian HR Institute4
Asia Pacific Journal of Human Resources ��
Theory and hypotheses
HRM digitalization, HRM system maturity and firm performance
AST asserts that the effectiveness of advanced technology depends not only on the tech-
nology itself but also on the characteristics of the social structure, such as reporting
hierarchies and standard operating procedures (DeSanctis and Poole 1994). In this sec-
tion, we examine the influence of HRM digitalization itself as well as its joint effect
with HRM system maturity. To be specific, we posit that HRM digitalization is capable
of boosting firm performance for at least two reasons: first, employee data can be effec-
tively collected, processed and utilized by employing advanced digital technologies,
moreover, organization can identify the key staff members whose performances make
the most significant difference to the business through data analysis (Boudreau and
Jesuthasan 2011). Such information can then be used for recruitment processes, inter-
views and team development (Amladi 2017), in turn helping an organization build a
more effective talent pool. Second, deeply analyzing HR related data with the help of
digital technologies, organizations can better understand the personal characteristics of
employees (e.g., work attitude and emotional and behavioral tendencies) in an accurate,
comprehensive and timely manner, which in turn lays a solid foundation to effectively
stimulate employee’s motivation and enthusiasm. For example, the existing literature
has found that e-HRM can enhance employees’ satisfaction (Lukaszewski, Stone and
Stone-Romero 2008; Panayotopoulou, Vakola and Galanaki 2007) and willingness to
remain with the company (Bondarouk and Ru€el 2009). At the same time, HRM digital-
ization may also provide a relatively transparent and flexible internal labor market
(Ru€el et al. 2004), which can increase the person-job fit as well as person-organization
fit to some extent.
Based on AST, social structures serve as templates for planning and accomplishing
tasks, and when advanced information technology fits with the social structure and
tasks at hand, the desired outcomes of the technology use result (DeSanctis and Poole
1994). In this study, we posit that the maturity of an organization’s HRM system (one
kind of social structure) has an important impact on the effectiveness of HRM digital-
ization (Hannon et al. 1996). First, under circumstances where HRM systems are
mature, HR professionals are more likely to have a good understanding of which data
are important to the organization’s development and should be accumulated and ana-
lyzed. Second, without mature HRM processes, HRM digitalization systems cannot
work effectively, and may even lead to confusion (Parry and Tyson 2011; Ru€el et al.
2004). Third, the problem of organizational politics and power exists in any kind of
organization (Rasmussen and Ulrich 2015). If the HRM system is incomplete, HRM
digitalization may become a tool through which power and personal benefits are con-
tested rather than serving the values of the organization. In other words, the promise
of HRM digitalization in reducing bureaucracy needs necessary organizational policies
© 2020 Australian HR Institute 5
Yu Zhou et al.
and processes to be in place to realize this potential (Bondarouk et al. 2017). Based on
the above statements, we propose:
Hypothesis 1 The interaction of HRM digitalization and HRM system maturity is
positively related to firm performance, such that the relationship between HRM dig-
italization and firm performance will be more positive when HRM system maturity
is high than when it is low.
The moderating effect of actors’ interaction
Adaptive structuration theory asserts that the nature of advanced information tech-
nology appropriations varies depending on the group’s internal system, such as
organization members’ style of interaction, members’ degree of knowledge and expe-
rience with the structures embedded in the technology and the degree to which
members agree on which structures should be appropriated (DeSanctis and Poole
1994, 131). Although AST emphasizes the importance of human interaction, ‘how
to interact’ is not clearly depicted. In this section, embeddedness theory is intro-
duced as a complementary perspective to AST. Embeddedness theory asserts that
there are two types of network embeddedness: structural and relational embedded-
ness (Granovetter 1985; Gulati 1998). Structural embeddedness addresses the posi-
tion that an actor occupies in the overall structure of the network, while relational
embeddedness refers to dyadic exchange relationships between different actors. When
the HR department has a high level of structural and relational embeddedness, the
effect of HRM digitalization is exerted more effectively because, on the one hand,
when the HR department has a high level of strategic involvement, it signals to
other departments that top managers attach more importance to HR functions,
which indicates that the HR department occupies a more central position in the
intra network of the organization (i.e. high structural embeddedness). In this case,
HR managers can have a more comprehensive understanding of the organization’s
strategy and have more access to valuable strategic information and data, which can
make the HRM digitalization activities generate more strategic value by combining
HR related data and firm’s strategic development data. On the other hand, if the
HR department has a high-level business involvement and establishes high-quality
relationships with business departments (i.e. high relational embeddedness), HR
managers can obtain more knowledge of the business development status, which
can help HR departments provide more customized optimizing programs for busi-
ness departments by analyzing both business data and HR related data, which may
help to increase the performance of each business department, and in turn enhanc-
ing the overall performance of the whole firm. In other words, high HR strategic
and business involvement can help to give full play to the advantages of HRM digi-
tization methods and tools.
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Asia Pacific Journal of Human Resources ��
The moderating role of HR strategic involvement
HR strategic involvement describes the extent to which HR managers interact with top
managers, which corresponds to HR managers’ structural embeddedness in this study.
Drawing from AST and embeddedness theory, we propose that, when HR managers are
deeply involved in firms’ strategy-making processes, the effect of HRM digitalization
(based on a mature HR system) on firm performance enhancement is strengthened. The
reasons are twofold: First, high strategic decision-making participation can help the HR
manager easily take on the roles of strategic partners (Ulrich 1997), understand the orga-
nization’s strategy more quickly, accurately and comprehensively, and in turn make HRM
digitalization practices (e.g., HR data collecting, processing and application) more in line
with the company’s strategic objectives. In addition, through deep strategic involvement,
HR managers can easily provide top managers with insightful information from rigorous
data analytics, which, in turn, develop the effectiveness of strategic decision-making.
Under these circumstances, the effectiveness of HRM digitalization is more likely to be
enhanced. Second, when the HR manager’s strategic involvement is high, it signals to
employees that top managers attach great importance to HRM in the organization, which
may encourage them to actively participate in the HRM digitalization practice (Marler
et al. 2009). In addition, according to embeddedness theory, high structural embedded-
ness implies status in the social network, that is, the high status of the HR department rep-
resented by its deep strategic involvement can make it easier for it to obtain cooperation
from other departments (Sheehan et al. 2007), which can amplify the positive impact of
HRM digitalization in enhancing firm performance. Based on the above arguments, we
propose:
Hypothesis 2 The positive relationship between the interaction of HRM digitaliza-
tion and HRM system maturity and firm performance is stronger when HR strategic
involvement is high than when it is low.
The moderating role of HR business involvement
HR business involvement describes the extent to which HR managers interact with line
managers, which corresponds to HR managers’ relational embeddedness in this study.
According to AST, organization members’ degree of knowledge and experience with the
structures embedded in the technology influences the skillful use of the technology
(DeSanctis and Poole 1994, 130). In other words, when HR departments are deeply
embedded in their business departments (i.e. high relational embeddedness) and establish
a high exchange quality with them, the effectiveness of HRM digitalization is strength-
ened. In this study, we propose that the extent to which HR managers are embedded
within a business influences the effect of HRM digitalization on firm performance for two
reasons: First, when HR managers have a high level of business involvement and close
© 2020 Australian HR Institute 7
Yu Zhou et al.
social connections with line managers, they are likely to develop common cognitive
ground for communication and collaboration, which is crucial for building a productive
social context for knowledge exchange and knowledge creation (e.g. Tsoukas 2010). In
these circumstances, HR managers can facilitate the formation of a shared language with
their business partners and have a better understanding of the current situation of HRM
in business departments, which can help them to conduct more targeted data collection
and analysis and provide more customized HRM support for their business partners to
increase their performance. Second, strong social bonding between HR professionals and
line managers is indispensable for the successful implementation of HRM policies (Brew-
ster, Gollan and Wright 2013; Kim and Ryu 2011). Because they have been trained in dif-
ferent occupational domains and they work for different organizational functions, HR
and line managers tend to develop divergent cognitive frameworks (Kim, Su and Wright
2018). Establishing cooperative relationships is likely to generate a strong HRM climate
throughout the organization (Bowen and Ostroff 2004), and the value and significance of
HRM digitalization will be deeply understood and supported by business departments. In
this case, line managers tend to pay more attention to HRM digitalization to motivate
their employees to put more effort into their jobs, and the positive effect of HRM digital-
ization on enhancing firm performance is strengthened. Based on the above arguments,
we propose:
Hypothesis 3 The positive relationship between the interaction of HRM digitaliza-
tion and HRM system maturity and firm performance is stronger when HR business
involvement is high than when it is low (Figure 1).
HRM digitalization ×
HRM system maturity
HRM strategic involvement
HR business involvement
Firm performance H1
H2
H3
Figure 1 Hypothesized model of relationships
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Asia Pacific Journal of Human Resources ��
Methods
Sample and procedure
This research was conducted with an online survey in conjunction with the largest ‘soft-
ware as a service’ company in China: Beisen. We collected the research data from 3012
Chinese companies during the spring of 2017. All the respondents were HR managers,
and they received an e-mail invitation to complete the questionnaire in the talent evalua-
tion system of Beisen. The online survey included a number of questions about the degree
of HRM digitalization, the maturity of the HRM system, the strategic and business
involvement of the HR manager as well as some basic information about the company
(e.g. firm size, industry and ownership style). We obtained usable responses from 2823
HR managers, yielding a response rate of 93.7%. Considering our research goal and the
integrity of the data, we chose to use the data from 211 listed companies (the firm perfor-
mance data of nonlisted companies is difficult to obtain). Most of the respondents
(70.1%) had more than three years of work experience and occupied at least an assistant
HR manager position (74.4%).
Measures
HRM digitalization
According to our interviews with amounts of HR managers and previous studies (Marler
and Parry 2015), a high level of HRM digitalization not only requires organizations to
accumulate and analyze work and workforce-related data to optimize HRM practices, but
requires organizations to apply digital technology to promoting the intelligent level of
organizations’ HRM practice. Therefore, in this study, we measured HRM digitalization
using two items: ‘To what extent is talent and HRM data analyzed and used in your enter-
prise?’ and ‘To what extent is digital HRM systems used in your enterprise?’ For the first
item, respondents were asked to choose from a 5-point scale from 1 (‘a minimal amount’)
to 5 (‘a great deal’). For the second item, respondents were asked to choose from a five-
point scale (from 1 to 5) with detailed descriptions: 1 – ‘none’; 2 – ‘mainly using paper and pen or simple office tools to implement HRM functions’; 3 – ‘proficient in using office software tools (e.g., Excel) to support relevant HRM functions’; 4 – ‘the HRM gen- eral functions have been operating with e-HR systems’; 5 – ‘in some specific HRM scenar- io, we develop and apply customized intelligent HRM tools based on internet and digital
technology’.
HRM system maturity
Based on the Capability Maturity Model (CMM) proposed by Mellon University (Curtis
et al. 2009), this study used a relatively simple approach with one item to measure HRM
system maturity: ‘What is the maturity level of your company’s human resources manage-
ment systems and processes?’ The respondents were asked to rate their responses on a 5-
point scale (from 1 to 5). To help the respondents clearly understand the definite meaning
of each point, we provided a detailed description of each level: 1 – ‘there are no written
© 2020 Australian HR Institute 9
Yu Zhou et al.
HRM processes, and the work is mainly carried out based on experience’; 2 – ‘there are basic HRM processes, which have been added into the standard documents of the com-
pany’; 3 – ‘according to the different HRM modules, the company has developed some main workflows and basic principles and issued them in the form of rules and regulations
throughout the whole company’; 4 – ‘in addition to the core rules and regulations, the human resources department has harmonized standards with other departments for com-
mon personnel tasks and has provided formal workflows and templates’; 5 – ‘in the face of different, unconventional HRM problems, each department has clear principles and stan-
dards of action and can find the corresponding systems and processes upon which to base
decisions’.
HR strategic involvement
Partly referring to previous studies (Klaas, McClendon and Gainey 1999; Marler and Parry
2015; Ordanini and Silvestri 2008; Sheehan and Cooper 2011), we measure HR strategic
involvement with one item: ‘To what extent are the HR departments of your enterprise
involved in strategic management?’ The respondents were asked to choose from a 5-point
scale (from 1 to 5): 1 – ‘there is no independent HR department’; 2 – ‘the HR department is subservient to the firm’s strategy’; 3 – ‘the HR department supports the firm’s strategy’; 4 – ‘the HR department is a collaborator with regard to the firm’s strategy’; 5 – ‘the HR department guides the firm’s strategy’.
HR business involvement
Referring to the literature on HR business partners (Cohen 2015; McCracken, O’Kane,
Brown and McCrory 2017), we measure HR business involvement using one item: ‘To
what extent are the HR departments of your enterprise embedded in the business opera-
tion?’ The respondents were asked to choose from a 5-point scale (from 1 to 5): 1 – ‘the business department often ignores the HR department and carries out its own personnel
work alone’; 2 – ‘the business department is not clear about the work of the HR depart- ment and just puts forward task requests that will be accomplished by the HR department
alone’; 3 – ‘the business department is clear about the various standards and action plans of the HR department and is willing to cooperate when needed’; 4 – ‘the business depart- ment incorporates HRM into its daily work and treats it as part of the work’; 5 – ‘the HR department develops a talent management approach, which is tailored to the characteris-
tics of and provides HRM support to the business department’.
Firm performance
According to Hanif (2011) and Lego (2001), the payback period, or the time it takes to
recoup the HRM digitalization investment, may be approximately one to three years. In
this study, because the development stage of each firm’s HRM digitalization has not been
considered, we cannot accurately estimate the added cost of HRM digitalization projects
to each organization. Therefore, we measure each firm’s financial performance using the
natural logarithm of its 2017 revenue.
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Asia Pacific Journal of Human Resources ��
Control variables
We controlled for a number of factors. First, previous HRM research has indicated that
firm size is positively related to firm performance (Guthrie, Flood, Liu and MacCurtain
2009; Huselid 1995). As such, the present study controlled for firm size, which was mea-
sured as the total number of employees in the company, and summarized it on a 6-point
ordinal scale from 1 (99 or less) to 6 (10 000 or more). Second, considering the differences
between eastern China and other areas of China in terms of economic development, a
dummy variable was included to indicate whether the organization was located in eastern
provinces (coded 1) or not (coded 0). Third, previous literature has indicated a need to
control for industry (Waddock and Graves 1997). In this study, industry was subdivided
into three categories (service, manufacturing, and others), and two dummy variables were
created (service = 1, others = 0; manufacturing = 1, others = 0). Fourth, consistent with existing researches, we also controlled for firm ownership type (state-owned enterprise
[SOE], private, joint venture, foreign venture, and others), and four dummy variables
were created. In addition, considering the possibility of interplay between the two inde-
pendent moderators (i.e. HR strategic involvement and HR business involvement), when
testing the moderating effect of one variable, we also controlled for the other variable.
Statistical analyses
In this study, we used a hierarchical regression analysis to test our hypotheses. To reduce
the potential problem of multicollinearity, independent variables and moderators were
mean-centered before creating the interaction term (Aiken and West 1991). The simple
slope test was used to examine the three-way interaction.
Results
Table 1 summarizes the means, standard deviations and correlations of our study vari-
ables. The two independent variables – that is, HRM digitalization and HRM system maturity – are both statistically significantly related to firm performance (r = 0.23, p < 0.01; r = 0.22, p < 0.01, respectively). The correlations for the other study variables are all in the expected directions.
The results of the regression analysis are presented in Table 2. Model 2 shows that
HRM digitalization is significantly and positively related to firm performance (b = 0.14, p < 0.05). Model 3 shows that the interaction of HRM digitalization and HRM system maturity is positively related to firm performance (b = 0.14, p < 0.05). Therefore, hypothesis 1 is supported.
Hypotheses 2 and 3 proposed that HR strategic involvement and HR business involve-
ment may play a moderating role in the relationship between the interaction of HRM digi-
talization and HRM system maturity and firm performance. Given the possibility of
interplay between the two moderators (i.e. HR strategic involvement and HR business
involvement), when we examine the effect of one variable, the effect of the other variable
was controlled. As shown in Model 7 of Table 2, after controlling for the effect of HR
© 2020 Australian HR Institute 11
Yu Zhou et al.
T a b le
1 M ea n s, st an d ar d d ev ia ti o n s an d co rr el at io n s o f st u d y v ar ia b le sa
V ar ia b le
M ea n
S D
1 2
3 4
5 6
7 8
9 1 0
1 1
1 2
1 . S iz e
3 .6 7
1 .0 4
2 . A re ab
.8 3
.3 7
.0 5
3 . O w n er sh ip
ty p e 1 c
.3 5
.4 8
�. 0 2
�. 1 0
4 . O w n er sh ip
ty p e 1 d
.5 8
.5 0
.0 4
.0 6
�. 8 5 **
5 . O w n er sh ip
ty p e 1 e
.0 5
.2 2
�. 1 1
.0 5
�. 1 7 *
�. 2 8 **
6 . O w n er sh ip
ty p e 1 f
.0 1
.1 2
.0 8
.0 5
�. 0 9
�. 1 4 *
�. 0 3
7 . In d u st ry
1 g
.4 9
.5 0
�. 0 3
�. 0 5
.1 8 **
�. 1 4 *
�. 0 2
�. 0 4
8 . In d u st ry
1 h
.4 1
.5 0
�. 0 0
.0 1
�. 1 2
.0 8
.0 7
.0 6
�. 8 2 **
9 . H R M
sy st em
m at u ri ty
3 .5 2
.9 8
.1 4 *
�. 1 1
.1 4 *
�. 0 9
�. 0 8
�. 0 6
.0 8
�. 0 4
1 0 . H R M
d ig it al iz at io n
3 .3 6
.9 0
.1 0
�. 0 8
.0 6
�. 0 5
.0 6
�. 0 5
.0 6
.0 3
.4 3 **
1 1 . B u si n es s in v o lv em
en t
3 .2 6
.9 8
.0 6
.0 3
.1 3
�. 0 8
.0 0
�. 1 1
.1 9 **
�. 0 9
.3 7 **
.3 9 **
1 2 . S tr at eg ic in v o lv em
en t
3 .2 7
1 .0 0
.1 5 *
.0 3
.1 0
�. 0 8
.0 9
�. 1 5 *
.1 3
�. 0 6
.4 0 **
.4 8 **
.4 7 **
1 3 . F ir m
p er fo rm
an ce
2 2 .5 9
1 .7 8
.1 1
�. 1 1
.3 7 **
�. 2 9 **
�. 0 5
�. 0 6
.0 6
�. 0 6
.2 2 **
.2 3 **
.1 1
.2 6 **
a N
= 2 1 1 ;
b ‘E as t’ = 1 , ‘n o t ea st ’ = 0 ;
c ‘S O E ’ = 1 , ‘n o t S O E ’ = 0 ;
d ‘P ri v at e’
= 1 , ‘n o t p ri v at e’
= 0 ;
e ‘J o in t v en tu re ’ = 1 , ‘n o t jo in t v en tu re ’ = 0 ;
f ‘ F o re ig n ’ = 1 , ‘n o t fo re ig n ’ = 0 ;
g ‘S er v ic e’
= 1 , ‘n o t se rv ic e’
= 0 ;
h ‘M
an u fa ct u ri n g ’ = 1 , ‘n o t m an u fa ct u ri n g ’ = 0 ;
*p < 0 .0 5 ; ** p < 0 .0 1 ; ** *p
< 0 .0 0 1
© 2020 Australian HR Institute12
Asia Pacific Journal of Human Resources ��
T a b le
2 R es u lt s o f re g re ss io n an al y si s
V ar ia b le
F ir m
p er fo rm
an ce
M 1
M 2
M 3
M 4
M 5
M 6
M 7
M 8
M 9
M 1 0
M 1 1
C o n tr o l v ar ia b le s
S iz e
.1 3
.0 9
.0 9
.0 9
.0 8
.0 8
.0 8
.1 2
.0 8
.0 9
.1 0
A re a
�. 0 8
�. 0 6
�. 0 6
�. 0 9
�. 0 6
�. 0 6
�. 0 4
�. 0 8
�. 0 6
�. 0 6
�. 0 5
O w n er sh ip
ty p e 1
1 .1 5 * * *
1 .1 1 * * *
1 .0 4 * * *
1 .0 8 * * *
1 .0 9 * * *
1 .0 4 * *
1 .1 1 * * *
1 .1 3 * * *
1 .0 9 * * *
1 .0 6 * *
1 .1 6 * * *
O w n er sh ip
ty p e 2
.8 1 *
.7 9 *
.7 4 *
.7 6 *
.7 8 *
.7 4 *
.8 2 *
.8 0 *
.7 8 *
.7 6 *
.8 6 *
O w n er sh ip
ty p e 3
.4 0 *
.3 9 *
.3 8 *
.3 6 *
.3 6 *
.3 6 *
.4 1 *
.4 0 *
.3 6 *
.3 8 *
.4 3 * *
O w n er sh ip
ty p e 4
.1 6
.1 7
.1 7
.1 9
.1 8
.1 8
.1 7
.1 7
.1 8
.1 8
.1 8
In d u st ry
1 �.
1 3
�. 1 7
� . 1 8
�. 1 7
�. 1 7
�. 1 7
�. 1 5
�. 1 5
�. 1 7
�. 1 6
�. 1 7
In d u st ry
2 �.
1 3
�. 1 7
�. 1 7
�. 1 6
�. 1 7
�. 1 7
�. 1 6
�. 1 5
�. 1 7
�. 1 6
�. 1 6
B u si n es s in v o lv em
en t
.2 1 * *
.1 6 *
.1 3
.1 2
S tr at eg ic in v o lv em
en t
.0 6
�. 0 8
�. 0 8
�. 0 7
In d ep en d en ts
H R M
sy st em
m at u ri ty
.1 1
.1 3
.0 9
.1 2
.0 6
.0 9
.1 0
.0 6
H R M
d ig it al iz at io n
.1 4 *
.1 4
.1 0
.1 1
.0 4
.1 0
.0 9
.0 6
M o d er at o rs
S tr at eg ic in v o lv em
en t
�. 0 8
�. 0 8
�. 1 4
B u si n es s in v o lv em
en t
.1 6 *
.1 2
.0 5
In te ra ct io n
H R M
sy st em
m at u ri ty
9 H R M
d ig it al iz at io n
.1 4 *
.1 0
.1 5 *
.0 8
.0 4
H R M
sy st em
m at u ri ty
9 S tr at eg ic
in v o lv em
en
.0 4
.0 3
© 2020 Australian HR Institute 13
Yu Zhou et al.
T a b le
2 (c o n ti n u ed )
V ar ia b le
F ir m
p er fo rm
an ce
M 1
M 2
M 3
M 4
M 5
M 6
M 7
M 8
M 9
M 1 0
M 1 1
H R M
d ig it al iz at io n 9
S tr at eg ic
in v o lv em
en t
.0 2
.0 2
H R M
sy st em
m at u ri ty
9 B u si n es s
in v o lv em
en t
.0 5
.0 5
H R M
d ig it al iz at io n 9
B u si n es s
in v o lv em
en t
.0 7
.1 0
H R M
sy st em
m at u ri ty
9 D ig it al iz at io n 9
S tr at eg ic in v o lv em
en t
.2 7 * * *
H R M
sy st em
m at u ri ty
9 D ig it al iz at io n 9
B u si n es s in v o lv em
en t
.1 8 *
R 2
.1 8
.2 3
.2 4
.2 3
.2 4
.2 6
.3 1
.1 9
.2 4
.2 6
.2 8
D R 2
.0 4
.0 2
.0 2
.0 1
.0 5
.0 5
.0 2
.0 2
D F
5 .7 2 * * *
5 .3 4 * *
4 .9 6 *
6 .4 9 * * *
1 .5 7 2
1 .2 4
1 3 .6 1 * * *
5 .1 9 * * *
4 .7 8 * *
1 .9 1
5 .3 9 *
* p < 0 .0 5 ; * * p < 0 .0 1 ; * * * p < 0 .0 0 1
© 2020 Australian HR Institute14
Asia Pacific Journal of Human Resources ��
business involvement, the three-way effect of HRM digitalization, HRM system maturity
and HR strategic involvement was significant (b = 0.27, p < 0.001). To advance further interpretations, we calculated the unbiased beta weights for each slope along with the t-
test for each pairwise comparison (Dawson and Richter 2006), and the result is shown in
Table 3. Our results show that slope 1, representing high levels of all three explanatory
variables, is significantly different from the other three slopes. Thus hypothesis 2 is con-
firmed (Figure 2).
Table 3 Slope differences for the three-way interaction among HRM digitalization, HRM system
maturity and HR strategic involvement
Pair of slopes t-value for slope difference p-value for slope difference
(1) and (2) 2.674 .008
(1) and (3) 3.642 .000
(1) and (4) 1.977 .049
(2) and (3) 1.197 .233
(2) and (4) �.845 .399 (3) and (4) �2.268 .024 (1) High HRM system maturity and high HR strategic involvement; (2) High HRM system matu-
rity and low HR strategic involvement; (3) Low HRM system maturity and high HR strategic
involvement; (4) Low HRM system maturity and low HR strategic involvement.
17
18F ir m
p e rf
o rm
a n ce 19
20
Low HRM digitalization High HRM digitalization
(1) High HRM system maturity, high strategic involvement
(3) Low HRM system maturity, high strategic involvement
(4) Low HRM system maturity, low strategic involvement
(2) High HRM system maturity, low strategic involvement
Figure 2 Three-way interaction among HRM digitalization, HRM system maturity and HR strate-
gic involvement (�1 standard deviation) © 2020 Australian HR Institute 15
Yu Zhou et al.
In testing the moderating effect of HR business involvement, HR strategic involvement
was controlled. As shown in Model 11 of Table 2, the three-way effect of HRM digitaliza-
tion, HRM system maturity and HR business involvement was significant (b = 0.18, p < 0.05). To further investigate these relationships, we also calculated the unbiased beta weights for each slope along with the t-test for each pairwise comparison (Dawson and
Richter 2006). The results are reported in Table 4, which show that slope 1, representing
Table 4 Slope differences for the three-way interaction among HRM digitalization, HRM system
maturity and HR business involvement
Pair of slopes t-value for slope difference p-value for slope difference
(1) and (2) 2.379 .018
(1) and (3) 2.459 .015
(1) and (4) 1.741 .083
(2) and (3) �.522 .602 (2) and (4) �1.004 .317 (3) and (4) �.509 .611 (1) High HRM system maturity and high HR business involvement; (2) High HRM system matu-
rity and low HR business involvement; (3) Low HRM system maturity and high HR business
involvement; (4) Low HRM system maturity and low HR business involvement.
17
18F ir m
p e rf
o rm
a n ce
19
20
Low HRM digitalization
High HRM digitalization
(1) High HRM system maturity, high business involvement
(3) Low HRM system maturity, high business involvement
(4) Low HRM system maturity, low business involvement
(2) High HRM system maturity, low business involvement
Figure 3 Three-way interaction among HRM digitalization, HRM system maturity and HR busi-
ness involvement (�1 standard deviation) © 2020 Australian HR Institute16
Asia Pacific Journal of Human Resources ��
high levels of all three explanatory variables, is also significantly different from the other
three slopes. Thus, hypothesis 3 is supported (Figure 3).
Discussion
Up to now, the empirical evidence of the consequences of HRM digitalization practices
and corresponding theoretical foundations are quite inadequate. By introducing AST,
supplemented by embeddedness theory, this study examines the predictive power of the
interaction of HRM digitalization and HRM system maturity on firm performance as well
as the moderating role played by HR strategic involvement and HR business involvement.
Our regression results show that all the three hypotheses in this study are supported. As
can be seen in Figure 2, the highest level of firm performance is found when HRM digital-
ization, HRM system maturity and HR strategic involvement are all high; however, firm
performance will be greatly affected when HRM digitalization or HRM system maturity is
low. As shown in Figure 3, the highest level of firm performance is found when HRM dig-
italization, HRM system maturity and HR business involvement are all high, whereas if
one of the three variables is low, firms may get relatively worse performance. In summary,
our results indicate that HRM digitalization and HRM system maturity may affect each
other in predicting firm performance, and the effect of the interaction of them will be
influenced by HR’s strategic and business involvement degree.
Theoretical implications
There are three major theoretical implications of this study.
By examining the positive effect of the interaction of HRM digitalization and HRM
system maturity on firm performance, this exploratory study contributes to the literature
in terms of the consequences of e-HRM. Although previous studies have explored the con-
sequences of e-HRM, most of them concentrate on the attitudinal or behavioral out-
comes, such as perceived usefulness (Ghazzawi, Al-Khoury and Saman 2014), user
information satisfaction (Haines and Petit 1997), and intention to use (Erdo�gmus� and Esen 2011), while the relationships between e-HRM employment and organization out-
comes have not been confirmed by previous studies (Buckley et al. 2004; Reddick 2009).
One of the reasons may be that previous e-HRM studies attach too much importance to
the employment of various information or web technologies (e.g. human resource infor-
mation systems and HR SaaS), but less consideration is given to the analysis and use of
HR related data. The present study extends existing e-HRM literatures not only by intro-
ducing ‘HRM digitalization’ which highlights the importance of integrating the digital HR
technology employment and data analysis, but also by demonstrating the positive effect of
the interaction of HRM digitalization and HRM system maturity on firm performance.
By combining AST and embeddedness theory in the context of human resources
management, we validate and develop AST. First, AST was first applied in the context of
group decision support systems (GDSSs) (DeSanctis and Poole 1994). Then, this theory
was used to explain the implications of a wide range of technologies, such as mobile
© 2020 Australian HR Institute 17
Yu Zhou et al.
phones (Jonathan 2010; Ling, Poorisat and Chib 2018) and enterprise resource planning
systems (Furumo and Melcher 2006). In addition, some researchers have applied AST to
investigate the success of virtual teams (e.g., Naik and Kim 2010; Thomas and Bostrom
2010). Inspired by these studies and the one conducted by Bondarouk et al. (2017) exam-
ining the moderating effect of the appropriation of e-HRM on the relationship between
the strength of HRM and the frequency of e-HRM use, we further expand the application
field of AST by applying it to human resources management. Second, although AST
emphasizes the interplay among advanced technology, social structure and human inter-
action (DeSanctis and Poole 1994), the rich connotation of this theory has not been fully
excavated by HRM researchers (Bondarouk et al. 2017). In this study, by covering all
three dimensions of AST – that is, advanced technology, social structure and human interaction – we provide an example of the utilization of AST in the context of human resources management. Third, although human interaction is a critical domain of AST,
‘how to interact’ has not been clarified by previous HRM researchers. In this study, by
utilizing embeddedness theory as a complementary perspective, we demonstrate that
deep structural embeddedness in strategic decision-making processes and relational
embeddedness in organization business are two kinds of critical interactions that refine
the connotation of human interaction within AST.
By demonstrating the moderating effect of HR strategic involvement and HR business
involvement, we contribute to the literatures pertaining to the boundary conditions of the
relationship between HRM digitalization and firm performance. In line with the logic of
AST that the nature of advanced information technology appropriations vary depending
on the group’s internal system (DeSanctis and Poole 1994), we demonstrate that, to fully
display the effect of HRM digitalization, HR managers should actively participate in orga-
nizational strategy and foster harmonious relationships with business managers apart
from optimizing the HRM systems. The results of our research are also consistent with the
statements of HR role model that HR managers should be ‘partners’ with senior and line
managers (Ulrich 1997, 1998; Ulrich and Brockbank 2005).
Limitation and future directions
Although our research contributes to the literature in important ways, we must acknowl-
edge its limitations.
First, research on digitalization of HRM in the Chinese context is in the relatively
early stage of development. Its definition and measurements have yet to be established
and agreed upon among researchers. Thus, this exploratory study inevitably contains lim-
itations in the development and operationalization of its conceptual and measurements.
By referring to previous studies (Marler and Parry 2015; Parry 2011) and interviewing
with amounts of HR managers, each of our variables is measured by one or two items.
However, unlike typical one-item Likert scales, our scales are descriptive and more com-
plex (Marler and Parry 2015). Furthermore, the use of one-item measures in macro
research is not unusual, and previous studies indicate that one-item measures typically
correlate well with richer measures of the same construct (Bergkvist and Rossiter 2007;
© 2020 Australian HR Institute18
Asia Pacific Journal of Human Resources ��
Cunny and Perri 1991). Given the highly descriptive nature of the scale used in this sur-
vey, we believe that our single measure is representative of its conceptual construct and
would correlate strongly with a multi-item measure (Marler and Parry 2015). Neverthe-
less, in order to increase the validity of the scales, we still encourage future researchers to
develop more valid measurements.
Second, although we investigate the interplay of HR managers, high-level managers
and business managers in predicting firm performance based on AST, it should be noted
that most of these variables are measured by the perceptions of HR managers. However,
because all the HR managers directly completed the questionnaire online and anonymity
and confidentiality were ensured, social desirability distortion is largely reduced (Chang,
Witteloostuijn and Eden 2010; Richman, Kiesler, Weisband and Drasgow 1999). Addi-
tionally, because our outcome variable is an objective performance indicator, the potential
risk of common method variance is also greatly minimized. Nevertheless, we still encour-
age future researchers to refine our study by collecting multisource data or by designing
multi-level research to further verify and expand our results, for example, future research-
ers can ground their model in the stakeholder theory and carefully select a list of indicators
to represent the concept of firm performance.
Third, the effectiveness of HRM digitalization may be influenced by many factors. In
this study, we only investigate the role of HRM system maturity, HR strategic involvement
and HR business involvement. In fact, some other factors, such as an organization’s data-
driven culture (Mikalef, Boura, Lekakos and Krogstie 2019), the maturity of an organiza-
tion’s IT infrastructure (Ragowsky, Licker and Gefen 2012) and individual’s digital skill
level can also impact the effectiveness of HRM digitalization. Thus we encourage future
researchers to further explore more influencing factors of the effectiveness of HRM digi-
talization from different levels and perspectives.
Fourth, our study is cross-sectional in nature. This type of study always leaves open
the possibility of reverse causality. However, we believe reverse causality to be a minor
limitation of our study because we collected the data about HRM digitalization, HRM
maturity, HR strategic involvement and HR business involvement in the spring of 2017,
while the performance data about all 211 listed companies, which were extracted from the
2823 sampled companies for reasons of data integrity, were obtained at the end of 2017,
largely reducing the possibility of reverse causality. To yield a more robust causal relation-
ship, we suggest that future researchers conduct longitudinal studies, such as collecting
real-time big data from the SaaS platform for a long period of time, to further examine
the effectiveness of HRM digitalization.
Practical implications
Our study results also reveal considerable practical implications. First, our research indicates
that the interaction of HRM digitalization and HRM system maturity is positively related to
firm performance. Thus, we suggest that, in the process of implementing digital HRM tech-
nology and conducting HR data analysis, organizations should also improve the existing
HRM system and streamline the work processes at the same time, because HRM
© 2020 Australian HR Institute 19
Yu Zhou et al.
digitalization and HRM system maturity can affect each other in predicting firm perfor-
mance. Second, as illustrated in our study, a high level of strategic involvement of HR man-
agers can play a significant role in the effective application of HRM digitalization. That is, to
give full play to HRM digitalization, HR managers should proactively participate in the orga-
nization’s strategic decision-making process and acquire necessary support from senior man-
agers. Third, the effectiveness of HRM digitalization is also affected by the extent to which
HR managers are embedded in organizational business. As is repeatedly mentioned in this
paper, the effects of advanced HRM technologies are less a function of the technologies
themselves than of how they are used (DeSanctis and Poole 1994). Therefore, to make full
use of digital HRM technology, HR professionals should cooperate closely with their business
partners and help them understand and utilize these new technologies more efficiently.
Conclusion
In conclusion, based on AST and embeddedness theory, the present research enhances the
knowledge on HRM digitalization by investigating the effect of the interaction of HRM
digitalization and HRM system maturity on firm performance as well as the moderating
role of HR strategic involvement and HR business involvements. To give full play to the
effectiveness of digital HRM technology, the organization should establish a solid system
foundation; HR managers should proactively participate in strategic decision-making pro-
cesses and develop harmonious relationships with line managers. Our results theoretically
and empirically contribute to the literature on HRM digitalization and AST and yield
many interesting questions that have not yet been addressed. By outlining a number of
these questions, we hope to inspire researchers to make further headway in these areas.
Acknowledgements
We are grateful to the generous support of the National Natural Science Foundation of
China (Grant Number 71372003) and the research fund from School of Business of Ren-
min University of China endowed to Yu Zhou on digitalization of organization and
HRM. The assistance of Beisen (the largest HR Saas company in China) and Daniela
ZHOU (Dean of Beisen talent management research institutie) are appreciated.
Yu Zhou (PhD) is an Associate Professor in the Organization and Human Capital Strategy, School
of Business, Renmin University of China, Beijing, China. He Specializes his research in people strat-
egy and organization innovation, HRM hybridism in Chinese and global context, partnership gov-
ernance and sharing mechanism.
Guangjian Liu (PhD, School of Business, Renmin University of China, Beijing, China).
Xiaoxi Chang (PhD) is an Assistant Professor in Organization and Management School of Busi-
ness, China University of Political Science and Law, Beijing, China.
Lijun Wang (PhD, School of Business, Renmin University of China Beijing, China).
© 2020 Australian HR Institute20
Asia Pacific Journal of Human Resources ��
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