e-HRM and IT Governance: A User Department’s

Perspective using Diffusion of Innovations (DOI) Theory

Miguel R. Olivas-Luján

and Gary W. Florkowski

Clarion University of Pennsylvania & Tecnológico de Monterrey

Administrative Sciences – College of Business Administration

218 Still Hall, Clarion, PA, 16214, U.S.A.

University of Pittsburgh – Katz Graduate School of Business

278c Mervis Hall, Pittsburgh, PA, 15260, U.S.A.

Abstract. IT Governance, the responsibility for systematically making deci-

sions that will impact the acquisition, deployment, and overall usage of Infor-

mation Technologies (IT) in a firm has been touted as “the single most impor-

tant predictor of the value an organization generates from IT” [54]. In this pa-

per, we present the results of a survey-based study of US and Canadian firms

that utilize ITs for HR purposes (e-HRM). To investigate whether the mode of

HR-IT Governance matters in terms of the intensity of usage of HR Technolo-

gies, we used Diffusion of Innovations (DOI) theory in a moderated mediation

functional form [24]. We find support for the notion that indeed, the way an or-

ganization assigns responsibility for decision making for Human Resource

ICTs makes a difference in terms of the user (HR) and IS department factors

that predict the intensity of HR Technology usage.

1 Introduction

e-HRM, or the study of how Information and Communication Technologies (ICTs)

are transforming Human Resource Management (HRM) is an emerging research

stream in need of testing well-grounded Information Systems (IS) research paradigms

that might help explain the extant, equivocal results as to the consequences of using

ICTs in the Personnel area [47], [48]. [48] review of the extant literature on conse-

quences of e-HRM has found conflicting results of IT investments for HR purposes;

in some cases, IT appears to lead to more centralization, in others to decentralization

of HR decision making; a similar situation can be said about costs of operations, and

even about user satisfaction. One could surmise that there are important factors being

neglected in such studies so that these consequences of IT usage in the HR depart-

ment can be better explained.

One glaring deficiency in previous studies is the failure to consider how different

governance modes affect the proliferation and performance of ICTs. Yet, IT govern-

ance arrangements (i.e., the policies defining decision rights and accountability for IT

usage within the firm) have been touted as “the single most important predictor of the

value an organization generates from IT” [54]. A rigorous literature review did not

R. Olivas-Luján M. and W. Florkowski G. (2008).

e-HRM and IT Governance: A User Department’s Perspective using Diffusion of Innovations (DOI) Theory.

In Proceedings of the 2nd International Workshop on Human Resource Information Systems, pages 3-15

DOI: 10.5220/0001737100030015

 SciTePress

produce a single empirical investigation of e-HRM that incorporated this construct in

the chosen set of predictors. We address this gap by presenting the results of a cross-

sectional study of US and Canadian firms (n=136). Our analyses speak to the relative

influence that several user-department and IS-department factors have on HR-ICT

assimilation.

To test whether the IT Governance mode for HR ICTs makes a difference in terms

of the intensity of usage of HR Technologies, we used a moderated mediation func-

tional form [24]. Our conclusions suggest that the way an organization assigns re-

sponsibility for decision making for Human Resource ICTs has an impact on the

factors that predict intensity of HR Technology usage. This paper makes a contribu-

tion to the IT Governance literature in the sense that it incorporates the perspective

from a “user” department –in this case, the HR function—as opposed to the sole per-

spective of the IS function or the general manager’s.

2 Theoretical Overview and Hypotheses

Our review of the extant literature on the use of ICTs for HR purposes revealed sev-

eral shortcomings [19]. Firstly, rigorous empirical studies are uncommon: data analy-

ses rarely go beyond reporting percentages. Secondly, most reports target a profes-

sional practitioner audience, rather than a scholarly reader. Quite recently, [47] also

lamented the fact that the extant literature lacks theoretical sophistication. In this

study, we seek to explain the acquisition and usage of ICTs for HR purposes by util-

izing Diffusion of Innovations (DOI) theory [37] a well-validated paradigm that has

been used to explain diffusion patterns, adoption and adaptation for a wide variety of

innovations, including Human Resource (HR) and Information Systems (IS) innova-

tion. We followed the model depicted in Figure 1.

Fig. 1. Model for IT Governance as a moderated mediator of User Department Factors as pre-

dictors of HR Technology Intensity.

2.1 Dependent Construct: HRTI

Our main dependent construct (operationalized as our dependent variable or DV) is

Human Resource Technology Intensity (HRTI), an aggregate measure of the informa-

tion technologies deployed in the organization with HR purposes. To better under-

stand the intensity or “strength” with which an organization makes use of ICTs for

HR, three different but related dimensions must be combined. First, it is necessary to

measure the organizations’ set of ICTs, with respect to the number of technologies

utilized. Second, the assimilation stage [16] in which each of the ICTs is present in

the organization should be captured by the DV, lest the measure become a simple

count of technologies without truly describing the extent to which the technologies

have been incorporated. Third, the HR sub-functions that are automated with each of

those technologies–that is, the penetration of each of those ICTs—should be included

to quantify how much each of those ICTs is helping the HR function achieve its op-

erational objectives. This final dimension is necessary to differentiate organizations

that might have a large proportion of their work automated vs. those whose automa-

tion is minimal, even though the number of and assimilation stage of their ICTs might

be similar. Together, these three dimensions provide a technology-intensity index

(HRTI) that signifies how many ICTs are being used in the firm, to what extent these

technologies are being used, and in which HR sub-areas. This measurement approach

is also well legitimated within both the HR [18], [23], [27], [29], [55] and MIS litera-

tures [16], [20], [36], where researchers have used aggregation when operationalizing

such constructs as IT innovation by labor unions, technology diversity, intensity of

TQM adoption, and HR sophistication. These aggregated measures also aid in under-

standing complex, multidimensional phenomena that cannot be studied with simpler

measurement approaches [15].

2.2 HR-ICT Governance as a Moderating Mediator of HRTI

Studying the factors that predict innovation is a well-established modality within the

DOI literature, and particularly in MIS [13], [28], [35], [52]. [28] identified five

broad types of factors as predictors of innovations: (1) environment, (2) organization,

(3) user, (4) task, and (5) technology characteristics. This research focuses on the

second and third types of factors. Technology characteristics are not the explicit focus

of this study, with the purpose of following [15] aggregation research design in order

to increase the generalizability of the findings. [36], in his study of adoption of total

quality management practices in IS units, also excluded technology and user charac-

teristics but included those that pertain to the environment, the organization, and the

task context, as he found them most relevant for his organizational-level study.

The type of IT innovation in this study—HR Information and Communication

Technologies—, however, requires the inclusion of characteristics of the most rele-

vant unit in the organization for ICTs, the Information Systems (IS) function. Both

practitioner and academic literature suggest the inclusion of this factor. For example,

[21], in addition to [46] report that a sizable proportion of firms have shared govern-

ance or responsibility for ICTs, falling on the HR and the IS functions.

2.3 Predictors of HRTI

HR Function Factors –The “User Department” Factors. A type of factor that is

relevant for studies of firm-level innovations has usually been labeled “Individual

factors” [28] or “individual characteristics” [35]. [13], however, prefer the term

“User” (p. 125) which is more appropriate for this research, as it lends itself better to

denote the fact that ICTs (and other similar technologies) are not adopted by

individuals themselves; they are adopted by the department or function whose work is

being automated within the organization. End users can be HR staff or their internal

customers, but the majority of the benefits that may be generated by these service

innovations are vested with the HR function. Three constructs in this category are

included for empirical testing: (a) the HR Department’s Innovation Climate; (b) IT

Absorptive Capacity of the HR department; and (c) the presence of an HR

Technology Champion.

HR Department’s Innovation Climate. Recent research indicates that organiza-

tional or intra-organizational sub-climates may be an independent driver of innova-

tion. In one study, support for innovation within teams emerged as the main predictor

of hospital innovations [1]. Similar effects have been documented at the department

level. Consistent with the work of [31], [49] found that “a supportive [departmental]

climate led to role innovations” within the HR function (p. 189). Given these find-

ings, it is expected that HR departments with a strong innovation climate will encour-

age the introduction and utilization of Information Technologies across HR activities.

We thus derive:

Hypothesis 1: HR Innovation Climate is positively related to HR Technology In-

tensity.

IT Absorptive Capacity of the HR Department. The second factor, IT Absorptive

Capacity of the HR Department, is derived from IT studies based on [12] construct of

absorptive capacity. As [39] state it: “absorptive capacity, […] refers to the ability of

a firm’s employees to develop relevant knowledge bases, recognize valuable external

information, make appropriate decisions, and implement effective work processes and

structures…” (p. 267). By analogy, there is an expectation that the HR function’s IT

Absorptive Capacity will be an effective predictor of the presence and use of ICTs for

HR in the firm.

Hypothesis 2: IT Absorptive Capacity of the HR department is positively related to

HR Technology Intensity.

Presence of an HR Technology Champion. The third construct, an active HR Tech-

nology Champion, is well anchored in the DOI literature [37](p. 414). [5] rich, ethno-

graphic, and longitudinal work indicated that the absence of a champion was an al-

most insurmountable barrier to the implementation of advanced manufacturing tech-

nologies (i.e., computer aided design and/or manufacturing: CAD/CAM). Using more

generalizable methodologies, [22] reported that champion behaviors appear to be

related to environmental scanning. Champion behaviors, in turn, were positively

related to project performance at the time of implementation and one year afterward.

Accordingly:

Hypothesis 3: The presence of an HR Technology Champion is positively related

to HR Technology Intensity.

IS Function Factors –The Service Provider’s Factors. As stated earlier, there are both

intuitive and theory-based arguments that support including characteristics of the IS

function as a distinct set of factors. This category matters most when the HR function

is at least partially dependent on the IS function for the automation of its services. In

firms where the locus of responsibility rests on the IS function –i.e., a “centralized”

IT governance mode—, IS function factors are likely to mediate (at least partially) the

influence of the HR function factors. It follows that a “federal mode” (to use [39]

term for the shared responsibility for IT governance mode) should make characteris-

tics of both the IS and the HR units relevant for variations in HR Technology Inten-

sity. When the locus of responsibility for the management of HR Technology and its

use rests entirely on the HR department –a “decentralized” IT governance mode [7],

[39] —, the IS function factors are not expected to predict a significant amount of the

variance in HR Technology Intensity.

Locus of Responsibility for the management and use of HR Technology then is a

variable that triggers factors from the IS function as a mediator between the HR func-

tion factors and HR-Technology Intensity. [24], in their discussion of moderators,

mediators and related tests call the functional form between these constructs a “mod-

erated mediation” (p. 310). Two main constructs pertinent to the IS function factors

are included in this research: IS Resource Availability and the Relationship between

the IS (service provider) and HR (user) function. These two constructs are designed

to capture the “ability” and the “willingness” of the IS function to service the HR

department.

HR IS Resource Availability. HR IS Resource Availability is defined as the extent to

which the IS function has resources available to service the user department –HR in

this case. In the MIS-Innovations literature, [50] found that technical IT competences

were an important (although not sufficient) predictor for success of a process innova-

tion –business process redesign (BPR). Similarly, [26] reported that financial re-

source availability was strongly correlated with implementation policies and practices

for Manufacturing Resource Planning (MRP). Thus, the “ability” to service the HR

function, as represented by technical IT competences and general availability of re-

sources is expected to be strongly related to the use of ICTs in firms where the IS

function has a relevant role in its use.

IS Relationship with the HR Function. As stated above, this construct is intended to

capture the “willingness” of the IS function in servicing the HR department. In their

reviews of the factors related to IT implementation, [13], [28] include “appropriate

user-designer interaction and understanding” as imperatives to IT implementation

effectiveness [13] (pp. 123-124). Cooperation between the user and the IS function is

also stressed by [2] in the context of IT planning, the process that, at least in the best-

case scenario, should determine technology investment decisions. Similarly, [3] and

[51] have “emphasized that close relationships between business and IS staff are

necessary to ensure that IS plans support business strategies” [2] (p. 538). Thus, the

intuitive idea that the relationship between the IS and user function impacts various

stages of the IT systems life cycle has received support from the research community.

Locus of Responsibility for HR Technology. Figure 1 posits that the two IS factors

will mediate the relationship between User factors and HR Technology Intensity

when the Locus of Responsibility for HR Technology is either “centralized” with the

IS function (a full mediation form is expected) or shared among the IS and the HR

functions in a “federal” mode (a partial mediation is expected). In the event that the

IS function does not have any responsibility on HR Technology (a “decentralized” IS

governance mode), these factors are not expected to mediate the effect of the HR

function factors on HR Technology Intensity. In formal terms:

Hypothesis 4a: HR IS Resource Availability mediates the relationship between User

Factors and HR Technology Intensity, when

the Locus of Responsibility for HR Tech-

nology rests, at least partially, upon the IS function.

Hypothesis 4b: IS Relationship with the HR function mediates the relationship be-

tween User Factors and HR Technology Intensity, when

the Locus of Responsibility

for HR Technology rests, at least partially, upon the IS function.

3 Methods

3.1 Sample and Data Collection

Organizations with more than five hundred employees, located within Canada and the

United States, were targeted for this study. Using a three-contact protocol following

[14] Tailored Design survey method, 767 organizations in a wide variety of industries

were contacted for this web-based study –244 in Canada, 523 in the USA. One hun-

dred and fifty-five valid responses were recorded in the web-survey database (85

from the USA, 49 from Canada and 21 did not leave this information), which yields a

response rate of 21.3%. Response rates by country were 16.7% for the USA and

21.83% for Canada, which implies that conclusions from this report might be slightly

biased toward relationships that can be found more easily in Canadian than in US

American firms. Of 400 randomly selected firms in the database of prospective re-

spondents whose industry was identifiable, manufacturing firms accounted for

16.25%, whereas non-manufacturing ones comprised 83.75%. Most respondents had

positions in the HR area (116, or 97.5%; with the remaining 2.5% from the IS area).

Close to 60% reported being at the top of their functional area or at senior manage-

ment levels. We also used, with encouraging results, Harman’s one-factor test [34] on

the items included in the survey to examine the possibility that common method bias

had inflated the magnitude of the relationships. Finally, long tenure in respondents’

positions –average: 10.5 years; S.D.: 8.11—suggests that they know their firms well

and should be located in compelling positions to inform on the topic of the study.

Only twenty-six respondents (22.4%) had less than three years in their firms; forty of

them (34.5%) between 3 and 10 years of experience, and fifty respondents (43.1%)

reported ten or more years working for their firms.

In general, measures published with satisfactory psychometric properties for the

theoretical constructs above were used in this research. In several cases, the measures

were adapted to the context of the study (e.g., some scales that were designed for

studying Manufacturing Resource Planning systems or MRPs were reworded), and

some of the scales were shortened to between three to seven items, in an attempt to

balance questionnaire length with psychometric quality. Alpha coefficients of reliabil-

ity showed acceptable to excellent levels (.81 to .93). Given space limitations, a brief

description of the measures used to operationalize the dependent and mediating vari-

ables now follows; detail on independent variables may be obtained from the first

author.

3.2 Dependent Variable: Human Resource-Technology Intensity (HRTI)

Human Resource-Technology Intensity (HRTI) was created in the same spirit as other

innovation measures [18], [16], [20], [23], [27], [29], [36]; its operationalization is as

follows:

HRTI = Σj

(1)

: Varies from 1 to 8 with the following information technologies for HR ser-

vices: (1) Functional HR Applications; (2) Integrated HR Suite; (3) HR Integrated –

also known as Automated—Voice Response (IVR/AVR); (4) HR intranet;

(5) Employee Self-Service (ESS); (6) Manager Self-Service (MSS); (7) HR extranet;

and (8) HR portals. A low number of responses for wireless applications forced us to

delete this ninth category from further analyses. Detailed descriptions of these ICTs,

their end-users, purposes, features, and HR services typically automated through

these technologies can be found in [32].

: Assimilation stage [16]: 0 = not acquired; 1 = evaluation or trial use;

2 = purchased, not yet deployed; 3 = limited deployment (less than 25 %);

4 = generalized deployment (25 % or more).

: Penetration of functional HR areas where the corresponding i

-th

Information

Technology will be or has been deployed.

The first component of the variable (j

) was operationalized with the following

question: “In the delivery of HR services, does your company use:” followed by the

five assimilation stages described above, for each of the eight ICT’s (functional HR

applications through HR portals). The second component (p

) was operationalized by

the number of functional HR areas in which the ICT had been or would be deployed,

if it had already been purchased (third or higher stage in [16] assimilation model).

3.3 Moderated Mediator Variable: Locus of Responsibility for HR-ICTs as IT

Governance

Locus of Responsibility for HR-Technology was measured using six items to identify

the organizational unit whose scope of responsibility included HR-ICT-related activi-

ties such as leading the development, implementation, standards setting, and planning

of ICTs for HR. Sample questions include: “Priorities for the development and im-

plementation of HR-technologies are set by:” and “HR-Technology standards are set

by.” Response options included the IS function, the HR department, joint responsibil-

ity, business units, and so on. Coding for this variable was done in several steps: three

variables were created, one for each of the IT governance modes (centralized, or

located in the IS department; decentralized, when responsibility is in the HR unit; and

federal, for shared responsibility). These variables were then assigned one point for

each occasion in which the items indicated the governance mode for ICTs. The inter-

mediate variable having the largest value was then utilized to assign each case to one

of the three categories. Of twenty cases where two of the intermediate variables had

the same value, eight were resolved by crosschecking with the response to the ques-

tion of “Who participates in HRT planning in your firm?” We collapsed centralized

and federal governance modes to compare against the decentralized mode to test

Hypotheses 4a and 4b; this also allowed recoding ten of the firms that had not been

previously assigned to any of the governance modes, yielding 90 firms (58.1%) for

the Centralized+Federal category and 65 (41.9%) for the decentralized one. Admit-

tedly, this aggregation is less consistent with theory than if we had kept the three IT

governance categories, but the statistical analysis became more balanced as a result of

it.

4 Results

4.1 Moderated Mediation Analyses

To rigorously test the hypothesized moderated mediation form [24] of the IS Function

factors, as represented by Figure 1 and formally stated in Hypotheses 4a and 4b, we

used regression analyses; Table 1 summarizes the results. The first subset of regres-

sion equations utilized the records where the respondents reported that the IS Func-

tion played a significant role on HRTI Governance (either a Centralized or a Federal

governance mode); the second subset included only records where the role of the IS

Function was reported as less substantial (a Decentralized governance mode, where

the HR function has greater responsibility over ICTs than the IS function). It was

expected that IS Factors would mediate the relationship between the HR Function

factors and HRTI only when the IS Function was included in the locus of responsibil-

ity for HR-Technology.

Table 1. Tests of moderated mediation for IS function factors.

Regression equations Unstandard-

ized B

p-level Condition held?

Models where HR-ICT Governance is either Federal or Centralized (IS Function included) n =

1. HR-IS Relationship on HR Innovation

Climate

.66 .000 Yes

2. HRTI on HR Innovation Climate 6.60 .039 Yes

3. HRTI on HR Innovation Climate and on

HR-IS Relationship

.47

9.20

.894

.002

Yes

Mediation effect: Full

Models where HR-ICT Governance is Decentralized (the IS Function NOT included) n = 65

1. HR-IS Relationship on HR Innovation

Climate

.55 .015 Yes

2. HRTI on HR Innovation Climate 5.16 .277 No

3. HRTI on HR Innovation Climate and on

HR-IS Relationship

4.85

1.32

.315

.644

Mediation effect: Not supported (as theoretically expected)

Tests for mediation used [4] algorithm. As Table 1 shows, support was found for full

mediation in the set of records where HR-ICT Governance includes the IS Function,

thus supporting Hypothesis 4b. Also consistent with this hypothesis, when the regres-

sion equations were calculated on the subset of records where HR-ICT Governance

does not include the IS Function, only the first of the three regression equations was

significant, suggesting that the HR-IS Relationship does mediate the relationship

between HRTI and the HR Innovation Climate, solely when the locus of responsibil-

ity for HR-Technology includes the IS Function –a result that also supports Hypothe-

sis 1. Also shown is the number of records that were used in these calculations. Fifty-

eight percent (90/155) of respondents reported that the IS Function was included in

HR-ICT Governance, and the remaining respondents that this function was not. Mul-

ticollinearity was also tested with encouraging results.

Because the number of cases drops down to 46 in some of the regressions (listwise

deletion is used to maximize the stability of regression estimators), another regression

model was run on this sub-sample, to test whether the effect size of the HR Function

factors on the dependent variable is large enough to be perceived, even with the

smaller number of records, as hypothesized theoretically.

Results are not shown but they offer additional backing to the notion that, when

the governance role of the IS Function is less significant than that of the HR Func-

tion, the presence of an HR Technology Champion (B = 10.34; p = .002) is a strong

and significant predictor of HRTI, as predicted by Hypothesis 3. Somewhat surpris-

ingly, HR-IT Absorptive Capacity (B = –5.16; p = .093) received marginal support in

the direction opposite to the one hypothesized. Lack of statistical power is unlikely to

be the cause for the failure to find support for the connection between HRTI and the

HR-IS Relationship when the IS Function does not share responsibility for HRTI

Governance (Step 2 in the regression), further endorsing Hypothesis 4b.

5 Conclusions

Our results suggest that the influence of some user-factor predictors like the HR In-

novation Climate or an HR Technology Champion may be more significant when the

moderating mediator, HR-ICT Governance, places ultimate responsibility for ICT’s

on the HR Function than when this responsibility is shared with the IS Function. In

addition, our regression analyses suggest that, for organizations where the IS Func-

tion does not play a significant role in the management of ICTs, the existence of an

HR-Technology Champion is an important predictor of HR Technology Intensity.

Conversely, when the IS Function is included in Governance for HR-ICTs, a favor-

able HR-IS Relationship mediates the effect of user factors (specifically the HR Inno-

vation Climate).

There is an even more pressing need to document the effects that ICTs have on HR

and IS staff, the larger HR and IS functions, and the firm. How likely is it that HR’s

internal customers will fully embrace and use IVR systems, HR intranets, ESS/MSS

applications, or HR portals? The MIS literature has much to offer in explaining the

dynamics of technology acceptance by individual users. What impact does the auto-

mation of HR transactions have on HR staff? Do attitudes like job satisfaction, organ-

izational commitment and professional commitment improve because less time is

consumed performing mundane tasks, or is there heightened work stress, job insecu-

rity, and intentions to leave in the face of perceived changes in competency require-

ments? Does the productivity of HR staff actually increase as service delivery be-

comes more technology intensive, and is the relationship linear? Answers to these

questions would facilitate more effective change strategies for ICTs and more accu-

rate return analyses when trying to develop the business case for their introduction.

Contributions of this study are (1) the results underscore the importance of govern-

ance policies in the internal diffusion of HR-ICTs, (2) the analyses are based on the

most comprehensive operationalization of firm-level HRM-ICT usage to date, and (3)

the IT governance literature is extended by assessing the phenomenon through the

eyes of a heretofore unexplored source--HRM users. As technology becomes an in-

creasingly vital component of HR service delivery, researchers must expand their

efforts to understand the opportunities and threats that it fosters. Regardless of how

our understanding of these phenomena increases, investments in these innovations

will surely continue to swell, a fact that underscores the need to better understand the

effects that IT governance has on organizations.

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