Convergence or Divergence in Global e-HRM?
General Foundations and Basic Propositions
Stefan Strohmeier
Chair of Management Information Systems, Saarland University
Campus C3.1, 66123 Saarbrücken, Germany
Abstract. Though increasingly adopted in different countries our current
knowledge concerning the global adoption of electronic Human Resource
Management (e-HRM) is limited at present. In particular, it is unclear whether
e-HRM is a universal management practice or whether there are regional
differences in the organizational adoption of e-HRM. The present paper
therefore aims at an initial examination of this question, by a) elaborating the
general foundations of global e-HRM and b) developing some basic
propositions on global e-HRM. Discussing the foundations uncovers an
ambitious and voluminous research task. Based on an analysis of basic
institutional and cultural influences major results are the digital divide,
contextual openness, and functional congruence of e-HRM.
1 Electronic Human Resource Management – A Global
Management Practice?
Generally defined as the application of information technology for both networking
and supporting at least two individual or collective actors in their shared performing
of HR functions [59], electronic Human Resource Management (e-HRM) represents
an area of amplified importance. As a basic explanation for the increased adoption of
e-HRM diverse positive outcomes may be quoted [e.g. 44] that can be aggregated to
the general advantages of automating, informating, and collaborating (within) HRM
In accordance with this, diverse empirical studies in various countries uncover
high levels of e-HRM adoption (respectively of one of its functional subsets such as
e-recruiting) [e.g. 2, 4, 20, 24, 25, 29, 33, 39, 41, 45, 52, and 62]. This basically
demonstrates that e-HRM in the interim should be seen as an internationally well
established management practice rather than a passing fashion. However, initial
cross-national studies – though generally also confirming high adoption rates – hint at
clear cross-national differences. A recent study of e-HRM adoption in Europe, for
instance, reveals national adoption rates from less than twenty to nearly ninety
percent of organizations [59]. Hence, facing the ongoing academic debate on
convergence vs. divergence of HRM [e.g. 5, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 46,
47, 48 and 58] the question arises whether e-HRM is a universal management practice
or whether there are regional differences in the organizational adoption of e-HRM. So
Strohmeier S. (2009).
Convergence or Divergence in Global e-HRM? General Foundations and Basic Propositions.
In Proceedings of the 3rd International Workshop on Human Resource Information Systems, pages 106-119
DOI: 10.5220/0002197801060119
far, this question is only parenthetically addressed in previous conceptual [36] or
empirical [60] work. The present paper therefore aims at an initial examination of this
question. Concretely, a) general foundations of global e-HRM are elaborated, and b)
basic propositions on global e-HRM are developed. This should increase the current
understanding of e-HRM in a global context, and, hopefully, offers a basis for future
comparative research in e-HRM.
2 Foundations of Global e-HRM
Within the frame of comparative management research there are two major
paradigms: Universalism quotes that ubiquitous factors of globalisation and
competition will enforce cross-national comparable management practices.
Universalism hence stands for convergence of management practices. Contrarily,
contextualism supposes nationally and/or culturally differing factors that are
accountable for lasting differences in management practices. Contextualism hence
implies lasting divergence of management practices [e.g. 1]. There are diverse
theoretical approaches that directly or indirectly support the respective positions [e.g.
10, 46, and 48]. Universalism, for instance, is supported by transaction cost
economics or neo-institutionalism, by claiming that minimization of transaction cost
or global coercive pressures will enforce universal management practices [e.g. 22,
66]. Contextualism, for instance, is supported again by institutionalist or else
anthropologist theories, by claiming that lasting differences in national institutions
and/or cultures will enforce and preserve divergent management practices [e.g. 38,
Applying the above positions to e-HRM, universalism would postulate some
general competitive and/or institutional influences that will lead to a globally
converging adoption of e-HRM. Contrarily, contextualism would expect a diverging
adoption of e-HRM due to some spatially differing institutional and/or cultural
influences [e.g. 10, 46]. Hence, identifying and weighting such influences on
convergence or divergence seems to be an essential initial step to increase our
understanding of e-HRM adoption in a global context. However, before naïvely
speculating numerous imaginable influences, some general foundations have to be
discussed in more detail so as to get a more instructed view.
Firstly, the identification and categorisation of possible contextual influences on e-
HRM require a thorough discussion. Cross-national research literature repeatedly
reveals as a rough but sustainable categorization that institutional and cultural
influences could be distinguished. However, it is also quoted that both categories may
not be selective, since culture may well be conceptualized as institution, while
contrarily institutions may be understood as manifestations of culture [10]. Besides,
the explicit examination of cultural influences brings about a well recognized
problem of cross-cultural research, i.e. whether to choose an “etic” or “emic” mode of
theorizing [e.g. 45, 61]. The “etic” mode would suggest that theorized cultural
influences apply in all cultures. This would limit the complexity of influence
identification, however also may incur the critique of an ethno-centric and hence
biased way of theorizing contextual influences. Contrarily, the “emic” mode assumes
differences in cultural influences while therewith however clearly increasing effort
and complexity of research. Moreover, the dichotomy of institutional and cultural
influences is blocky and still comprises an (over-)abundant set of generally
conceivable influences. It becomes mandatory to select and categorise relevant
institutional and cultural influences in an appropriate manner [14]. Strictly speaking,
relevant influences should be selected based on recognized theories that are able to
justify the accruement, process, and intensity of proposed influences on e-HRM
adoption. However, since a single comprehensive theory of global (e-)HRM is
missing, this may as well lead to an eclectic accumulation of numerous influences,
while at the same time the overlooking of relevant influences cannot be excluded. As
an interim solution, identification of influences may be based on different existing
(however “etic”) frameworks [5, 13, 14, 31, 49], that could also be modulated and/or
completed so as to match peculiarities of e-HRM. Furthermore, also potential
interaction effects between different influences should be regarded. For instance,
there well may be interaction effects between institutional and cultural influences
such as that per se comparable legal influences on e-HRM are distinctly more
important in uncertainty avoiding cultures than in uncertainty tolerating cultures [for
a discussion see 14]. Though the consideration of these aspects will add intricateness,
it is necessary to assure proper identification and categorization of possible
Secondly, even if being mainly interested in the organizational adoption of e-HRM,
the multilevel character of adoption should be considered when theorizing contextual
influences. Customarily, the micro-level (adoption by individual users) and the
macro-level (adoption by entire organizations) of e-HRM adoption can be
distinguished. It is also agreed that there are – or at least may be – level interaction
effects, that however are not well understood at present [60]. For this reason,
theorizing a certain influence on e-HRM should carefully decide on the level(s) that
actually is/are influenced. For instance, supposed a certain cultural influence, it
should be explained whether this factor influences the individual level, the
organizational level, or both, and also whether and – if appropriate – which
interaction effects exist. Interestingly, this consideration of levels may also reveal the
simultaneousness of convergence and divergence, since there may be convergence on
the macro-level and divergence on the micro-level [e.g. 48]. Therefore, it may well be
that organizations in different countries adopting similar technologies offered by the
same international vendor thereby converging on the macro-level, while individual
level adoption may show marked divergence due to cultural differences. Being
another complication at first sight, theorizing contextual influences will finally profit
from considering different levels and their interactions.
Thirdly, the demarcation of the spatial entities to be used for comparing e-HRM
adoption needs further deliberation. Since even termed “cross-national research” the
usage of nations respectively countries as adequate spatial entities is widely taken as
given and potential divergences hence are explained based on national institutions
and national culture. Basically, this may indeed constitute a satisfactory procedure,
since particularly institutional influences usually are rather homogeneous within a
country. However, concerning cultural influences there are calls for a more refined
conception. On the one hand, there may be quite divergent subcultures within one
country, while on the other hand there may also be cultures that are shared by several
countries [e.g. 50]. Generalizing this, sometimes sub-national spatial entities will
prove adequate, while contrarily, sometimes also supra-national spatial entities will
be sufficient. Yet, which spatial demarcation is actually adequate crucially depends
on the kind of considered influences. It is foreseeable that a sufficient conception of
spatial areas with (rather) homogenous influences will turn out difficult. If for
pragmatic reasons countries still are used, this will imply that there may be intra-
national divergences in e-HRM adoption as well as regional convergence of diverse
countries together with global divergence [10]. There are examples concerning both
phenomena in general cross-national HR research [see the overview in 10, 46] that
hence could be tested regarding their additional feasibility for e-HRM research.
Fourthly, the dynamics of divergence and convergence should be regarded [47].
Convergence and divergence should not be conceptualized as static and unchangeable
situations but as dynamic processes. So as to illustrate this point, the above mentioned
empirical results of clearly divergent national adoption rates within Europe [60] may
indeed represent a divergence process with lasting or even increasing differences.
Otherwise, it may represent a convergence process towards final similarity as well.
Accepting that major influences may change, it is even imaginable that convergence
processes change to divergence processes et vice versa. Proper theorized influences
on global e-HRM should certainly consider such developments in time.
Finally, it is necessary to reflect e-HRM and its adoption in more detail.
Frequently, e-HRM is parenthetically treated as a “new” HR practice, while its
adoption usually is seen as a binary matter of either implementing or not
implementing respective technologies within an organization. As in other HR
functions, cross-national adoption of e-HRM therefore is frequently measured in
quantitative adoption rates, i.e. the percentage of organizations of a given country
[e.g. 60]. This is only a very rough concept that does not allow distinguishing major
differences in adoption. To offer a more nuanced basis for theorizing contextual
influences the quantity (“how much?”) and the quality (“what?”) of e-HRM adoption
should be distinguished (see Fig. 1).
e-HRM Adoption
Adoption Quantity
(„How Much?)
Adoption Quality
Adoption Width
(„Which Functions?“)
Adoption Depth
(„Which Extent?“)
Fig. 1. Categories of e-HRM adoption.
The quantity of adoption can be split into the dimensions of width and depth of
adoption. For this, it has to be recalled that e-HRM should not be considered as a
conventional HR function such as recruitment, compensation, or performance
management etc. Rather, it is a certain technology-based way of organizing and
performing such functions, while meanwhile almost every HR function can be
organized and performed as e-function, such as e-recruitment [e.g. 42], e-
compensation [e.g. 23], or e-performance management [e.g. 15]. Consequently,
within the group of e-HRM adopting organizations there may be organizations with
few or even only one e-function. There also may be organizations which perform all
HR functions as e-functions. Hence, the width of adoption considers which HR
functions of a given organisation are e-functions. Furthermore, e-functions may show
a different extent of “electronization”. For instance, within the group of organisations
that perform e-recruiting there may be organizations that perform only a small extent
of their recruiting activities as e-function such as publishing job offers electronically,
while other organisations may perform the entire recruiting process electronically.
The depth of adoption hence considers the extent of a given e-function that actually is
performed electronically. Beyond the mere quantity it is additionally useful to
consider the quality of adoption. Adoption quality refers to the basic kind of adoption
(e.g. the concrete practices performed, the specific methods implemented, the very
actors incorporated etc.) that is actually taken up in the e-HRM concept of a given
organization. Though uncommon in comparative HR research this distinction of
quality and quantity of adoption will refine the theorizing of divergence or
convergence since there may well be situations of quantitative convergence, but
qualitative divergence of e-HRM adoption.
3 Propositions on Global e-HRM
Based on the above deliberations, it becomes clear that properly theorizing contextual
influences on global e-HRM is both a difficult and a voluminous research task. It is
difficult since basic problems (which influence categories, which procedural mode,
which spatial entities, etc.) are unsolved. All the more it is difficult, since plain
patterns of either global divergence or global convergence that could be easily
expressed in a few non-competing propositions are not to be expected. It is
voluminous since predictably a larger number of influences have to be reasoned for a
larger number of different spatial entities. Aggravatingly, cross-spatial information
concerning possible influences – such as for instance trade union attitudes and
activities regarding e-HRM in different regions of the world – is largely missing at
present [60] and hence has to be laboriously ascertained. Given this, it is evident that
a single study cannot achieve a comprehensive and detailed analysis of comparative
global e-HRM. Preparing and supporting future studies, the following section hence
aims at deriving some basic propositions concerning contextual influences on global
e-HRM. These may be concretized, complemented, and modified so as to achieve
more specific statements in future work. Aiming at basic contextual influences on e-
HRM, political, educational, legal, co-determinational, and cultural systems are
selected and analyzed [13, 14]. For pragmatic reasons, cultural influences are
theorized in an etic mode, the micro-level adoption is blinded out, and, countries are
used as approximations of adequate spatial entities.
3.1 Political Influences
Firstly, the national political systems, in particular the information technology related
policies should be of interest. Information technology policies determine kind and
extent of technological infrastructures necessary for e-HRM. They range from the
reliable provision of electricity to the availability of Internet infrastructure. By now,
some comparative research into information technology policies is available [e.g. 21,
37]. Yet, the state of knowledge is far from a comprehensive overview that would
allow a simple derivation of influences on e-HRM. Results reveal numerous
diverging detail policies which need to be laboriously analyzed concerning
supporting or restraining influences. In general, most countries value information
technology. Explicit and generally technology-hostile national policies could not be
identified [21, 37]. Even countries that seemingly disesteem technology, for instance
by notoriously restricting access to Internet content, such as practiced in China,
promote information technology for their purposes [e.g. 67]. Hence, there seems to be
a basic convergence of IT-relevant positive political attitudes. Accepting this
convergence, there should be nonetheless marked divergence due to the simple fact of
marked divergence in the national resources necessary to execute technology
supporting programs [16]. Especially, developed countries should be able to invest in
information technology infrastructure what subsequently implies a “digital divide”
also in e-HRM. Hence:
P 1: Divergences in national infrastructural preconditions will lead to divergences
in quantitative adoption (“proposition of infrastructural digital divide”).
3.2 Educational Influences
The national educational systems should exert influences on e-HRM adoption, since
they are in charge of general as well as special information technology literacy.
General information technology literacy is necessary to use technology for instance as
employee or applicant [e.g. 44, 60], while special e-HRM literacy is necessary for HR
professionals and line managers [e.g. 30, 35]. Broader general and in particular
broader specific information technology education within a country therefore should
doubtlessly further e-HRM adoption. Again, cross-national knowledge concerning
information technology education is rare [e.g. 40, 53], while knowledge concerning
specific e-HRM related education is completely missing at present. In a rough
overview, there seems to be convergence in valuing information technology since
most countries have incorporated information technology as educational subject in
one way or another [see the results in 53]. Replicating the argumentation of
infrastructural digital divide, there seems to be marked divergences in educational
resources and intensity due to divergences in the economic development of countries.
P 2: Divergences in national general and specific educational preconditions will
lead to divergences in quantitative adoption (“proposition of educational
digital divide”).
3.3 Legislational Influences
As a third area, national legislation customarily influences HRM. Usually, national
labour legislation is focussed. However, since analyzing e-HRM there may be
additional influences of data protection legislation. Though there again is some
comparative work on labour law [e.g. 7, 57] it is still described as a “confusing
patchwork” of countless international treaties, conventions as well as national laws,
contracts, and voluntary codes of conduct concerning numerous aspects such as
individual contract making, dismissal protection, wages, working conditions, etc.
[57]. Doubtlessly, these multifaceted regulations will manifoldly influence national
adoptions of e-HRM. Again, this requires a laborious detail elaboration. Aiming at
basic propositions it is obvious that these regulations will considerably influence the
quality, but not the quantity of adoption. To give a plain illustration, since ranging
from marginal rules to comprehensive affirmative action regulations cross-national
equality and anti-discrimination legislation is rather divergent [7]. It is quite well
understood that such regulations lead to divergences in corresponding national
recruiting activities. E-HRM, respectively e-recruiting, however, is basically open to
map these diverging legal requirements, hence this institutional setting influences the
quality but not the quantity of adoption, what may be called “legal openness” of e-
HRM. As a consequence, e-HRM will basically show the same law induced by
national peculiarities as conventional HRM thereby reproducing the existing
convergence-divergence patterns of conventional HRM. Hence:
P 3: Labour law influences will mainly affect the quality of adoption but only
marginally the quantity of adoption and thereby reproducing the divergence-
convergence patterns of conventional HRM (“proposition of labour law
Contrary to labour law, data protection law may well exert influences on
quantitative adoption. Given that there may be rigid national laws that harshly restrict
or even forbid the storage, processing, and/or transmission of personal data, this of
course, should markedly affect e-HRM adoption. Though there are mentionable
divergences based on the available, yet again incomplete knowledge concerning
cross-national data protection, such strictly prohibitive laws could not be detected [6,
56]. Rather, there seem to be moderate restrictive or even liberal protection
regulations that allow processing, storing, and transmitting of employee data to the
extent necessary in e-HRM. Clear hints towards regional convergence for instance
can be indicated in the EU countries, where national data protection laws have to
adopt common EU standards. Even several non-EU countries have voluntarily
adopted these standards [55]. Since strictly prohibitive or deterring regulations are
missing, quantitative adoption should not be markedly affected. Hence:
P 4: Data protection laws will not induce manifest cross-national divergences in
quantitative as qualitative e-HRM adoption (“proposition of permitting data
protection laws”).
3.4 Co-determinational Influences
Major influences may further be expected from national systems of codetermination
[e.g. 3, 54]. The combination of negative attitudes towards e-HRM and
comprehensive (bargaining) power of national representational bodies such as works
councils or trade unions will of course constitute a major impediment to quantitative
adoption. Again, studies of attitudes and activities of representational bodies that
allow deriving some propositions are not available at present. An initial exploration
of national and international trade union activities reveals surprising passiveness. At
least, there are no e-HRM related lobbying activities, communiqués, publications etc.
[60]. Recalling the argument concerning the “labour law openness” there may be an
analogous phenomenon of “co-determinational openness”. Representational bodies
may not be that much interested in the mere adoption – after all trade unions seem to
increasingly use comparable technologies so as to realize “e-employment relations”
[e.g. 64]. However, representational bodies of course are interested in enforcing their
multiple interests in qualitative adoption, thereby reproducing the basic divergence-
convergence patterns of conventional HRM. Hence:
P 5: Co-determinational influences will affect mainly the quality of adoption but
only marginally the quantity of adoption thereby reproducing basic
divergence-convergence patterns of conventional HRM (“proposition of co-
determinational openness”).
3.5 Cultural Influences
Understanding culture as basic assumptions, values, and attitudes commonly shared
by a certain group [e.g. 27, 43], it is obvious that culture should constitute a further
source of influences on e-HRM [e.g. 51]. Suggested a directly appropriate cultural
dimension such as “technology orientation” that roughly distinguishes technophile
and technophobic cultures, evident influences on quantitative e-HRM adoption could
be easily derived. However, prominent conceptualizations of culture [32, 34, and 63]
do not comprise such a dimension [e.g. 50, 43]. In addition, the relations between the
often rather abstract cultural dimensions, such as “masculinity”, and e-HRM are at
best indirect and rather unclear. Aiming at an initial general proposition the usage of a
prominent concept of culture [32] may offer first insights. This concept basically
distinguishes power distance, uncertainty avoidance, masculinity (vs. femininity),
individualism (vs. collectivism), and temporal orientation as cultural dimensions.
Especially “uncertainty avoidance” is frequently considered as being relevant for
information technology adoption. It is argued that the adoption of information
technology is inherently risky. Thus, long-winding, unfamiliar, and result-open
implementation processes will be rather accepted by uncertainty tolerating cultures
that consequently should show higher quantitative adoption rates [see the research
overview in 43]. Though this may be valid for e-HRM adoption as well, it should be
recognized that uncertainty avoiding cultures show a strong preference for greater
structure, clear rules, and standardized operating procedures [32]. Since e-HRM
mandatorily structures and standardizes HR processes, and, all the more, offers
widespread information, it should be particularly valued in uncertainty avoiding
cultures. Prima facie, there are opposing influences of this cultural dimension. Given
permanently increasing experience and routine in e-HRM implementation the
restraining effect should lose influence by and by. Hence:
P 6: Uncertainty avoiding cultures will show a higher quantitative adoption of e-
HRM due to certainty provision potentials of information technology
(“proposition of certainty potentials”).
Concerning further dimensions, concrete influences on quantitative adoption are
hard to identify. Again, the quality of adoption should be influenced by culture, as
can be exemplarily shown by the “power distance” dimension. Basically, power
distance refers to the extent to which unequal distribution of power is expected and
accepted. As a consequence, decision making in cultures with high power distance
tends to be centralized, while cultures with low power distance diffuse hierarchical
power in organizations [32]. Such culturally induced differences can be mapped by
different e-HRM concepts which locate decision making either centrally or
decentrally. Generalizing this exemplary insight, e-HRM may be adapted to a broader
range of differing cultural influences. This certainly does not entirely “immunize”
quantitative e-HRM adoption, but it lowers its cultural exposure. Paralleling the
insights concerning the institutional openness of e-HRM, an additional cultural
openness can be supposed. Hence:
P 7: Cultural influences will mainly affect the quality of adoption and only
marginally the quantity of adoption (“propositions of cultural openness”).
3.6 Summarized Influences
Given the above deliberations, it is possible to summarize three, however somewhat
competing propositions.
Initially, summarizing and generalizing the political and educational influences
discussed above it is obvious that the degree of socio-economic development of a
country constitutes a major cause of quantitative adoption divergence. Developed
countries should show a markedly higher quantitative e-HRM adoption so as
compared to developing countries, thereby replicating the general “digital divide”
[e.g. 16]. Hence:
P I: Divergences in national socio-economic development will lead to divergences
in quantitative adoption (“summarized proposition of digital divide”).
In addition, since e-HRM constitutes a way of organizing and performing HR
functions, a basic consequence seems to be that major institutional and cultural
influences do not refer to the quantity but to the quality of adoption – a phenomenon
that may be called “contextual openness” of e-HRM. Since basically configurable and
designable, the actual quality of e-HRM concepts will of course be orientated towards
the major institutional and cultural forces of their national context. To a certain extent
this dampens institutional and cultural influences on the quantity of adoption,
however without entirely “immunizing” e-HRM. Hence:
P II: Contextual influences will refer mainly to the quality of adoption but only
marginally to the quantity of adoption (“summarized proposition of contextual
This argument subsequently implies that conventionally and electronically
performed HRM are comparable, at least on a basic level. Nevertheless, differences
between HRM and e-HRM shall not be ignored. E-HRM explicitly stands for
methodical, organizational, and procedural innovations and hence for differences
However, e-HRM can be particularly designed and configured, and since exposed to
the same institutional as cultural influences within a country, the quality of e-HRM
and the quality of conventional HRM should be congruent on a basic level.
Consequently, e-HRM and conventional HRM should show basically congruent
patterns of global divergence or convergence – independently of our knowledge of
these patterns. Hence:
P III: Equal contextual influences within a country will lead to basic qualitative
congruence of e-HRM and conventional HRM, and hence to the same basic
patterns of global convergence or divergence (“summarized proposition of
qualitative congruence”).
4 Conclusions
This paper aimed at the elaboration of the general foundations and the development
of basic propositions on global e-HRM.
Engaging with the foundations, the paper uncovered comparative e-HRM research
as an ambitious and voluminous task. The adequate identification of influences,
consideration of levels, definition of spatial entities, deliberation of dynamics, and
conceptualization of adoption could be pointed out as critical aspects. The
consideration of numerous influences for numerous regions elucidates the extensive
workload associated with the topic. Therefore, the above deliberations represent a
first approximation of the subject that can and does not give final answers.
Following conceptual deliberations, the quantitative and qualitative adoption were
distinguished. Concerning the quantitative adoption, the propositions of “digital
divide” and “certainty potentials” stand for quantitative divergence, while the
propositions of “institutional and cultural openness” rather tend towards quantitative
convergence. At least, the basic configurability of e-HRM allows meeting quite
different institutional and cultural requirements, therewith markedly broadening the
spatial application range. Tough these are somewhat competing propositions the
divergence should clearly prevail especially due to the “digital divide” argumentation.
Concerning the qualitative adoption, the proposition of “contextual openness”
initially shows that contextual influences will in particular refer to the quality of
adoption. Aiming at basic propositions, concrete qualitative aspects are not theorized.
However, based on the proposition of “qualitative congruence” it could be explained,
why e-HRM and HRM should demonstrate similar regional patterns, therewith also
reproducing existing patterns of spatial convergence or divergence.
Given these initial results, the conceptual refinement and subsequent empirical
evaluation constitute the obvious implications for future research. Influence factors
need to be particularized, and meticulously compared for the regions of the world,
thereby also considering interaction and level effects. Special attention should be
given to the actual intensity of influences, since recent work for instance questions
the weight of cultural influences on HRM [26]. Related to this, identified contextual
factors should also be balanced with universal factors, such as the size of
organizations [e.g. 60], so as to offer a comprehensive picture of adoption
Representing basic research, implications for practice are rather limited. Given
that managers may be interested whether e-HRM constitutes a globally applicable
management practice [14, 17] the analysis shows some institutional restriction based
on the digital divide. Based on the contextual openness, it should be possible to
establish diverging national varieties of e-HRM, what however may be incongruent
with the harmonization need of multinational organizations [28].
1. Adler, N.J.: Cross-Cultural Management Research: The Ostrich and the Trend, Academy of
Management Review, 8 (1983) 226-232.
2. Ball, K.S.: The Use of Human Resource Information Systems: A Survey. Personnel
Review, 30, 6 (2001) 677693.
3. Bamber, G., Lansburry, R.D., Wailes, N.: International and Comparative Employment
Relations. Globalisation and the Developed Market Economies, 4
ed. Sage, London
4. Beamish, N., Armistead, C., Watkinson, M., Armfield, G.: The deployment of e-learning in
UK/European corporate Organizations, European Business Journal,14, 3, (2002) 105-115.
5. Begin, J.P.: Comparative HRM: A Systems Perspective, International Journal of Human
Resource Management, 5, 3 (1992) 379-408.
6. Bennett, C.J.: Convergence Revisited: Toward a Global Policy for the Protection of
Personal Data. In: Agre, P.E., Rotenberg, M. (eds.): Technology and Privacy. The New
Landscape, Harvard, MIT Press (1998), 99-121.
7. Blanpain, R.L., Baker, J. (eds.): Comparative Labour Law and Industrial Relations in
Industrialized Market Economies, Kluwer Law International (2004).
8. Boxall, P.F.: Building the Theory of Comparative HRM. Human Resource Management
Journal, 5 (1995) 5-17.
9. Brewster, C.: Different Paradigms in Strategic HRM: Questions Raised by Comparative
Research, In: Wright, P., Dyer, J., Boudreau, J., Milkovich, G. (eds.): Research in
Personnel and HRM, JAI Press, Greenwich (1999) 213-238.
10. Brewster, C.: Comparing HR Policies and Practices Across Geographical Borders, In:
Stahl, G., Björkman, I. (eds.): Handbook of Research in International Human Resource
Management, Edward Elgar, Cheltenham et al. (2006) 68-90.
11. Brewster, C., Mayrhofer, W., Morley, M. (eds.): Human Resource Management in Europe.
Evidence of Convergence, Butterworth-Heinemann, London (2004).
12. Brewster, C., Tregaskis, O., Hegewitsch, A., Mayne, L.: Comparative Research in Human
Resource Management: A Review and an Example, International Journal of Human
Resource Management, 7, 3 (1996) 585-604.
13. Budhwar, P.S., Dehbra, Y.: Rethinking Comparative and Cross-National Human Resource
Management, International Journal of Human Resource Management, 12, 3 (2001) 497-
14. Budhwar, P.S., Sparrow, P.R.: An Integrative Framework for Understanding Human
Resource Management. Human Resource Management Review, 12, (2002) 377-403.
15. Cardy, R.L., Miller, J.S.: eHR and Performance Management: A Consideration of Positive
Potential and the Dark Side. In: Gueutal H.G., Stone D.L. (eds.), The Brave New World of
eHR: Human Resources Management the Digital Age. Wiley, San Francisco (2005) 138–
16. Chinn, M.D., Fairlie, R.W.: The Determinants of the Global Digital Divide: A Cross
Country Analysis of Computer and Internet Penetration, Oxford Economic Papers, 59
(2007) 16-44.
17. Clark, T., Pugh, D.: Similarities and Differences in European Conceptions of Human
Resource Management, International Studies of Management and Organization, 29, 4,
(1999/2000) 84-100.
18. Clark, T., Gospel, H., Montgomery, J.: The Management of Human Resources in
Comparative and International Perspective: An Evaluation of Twenty Years of Research,
International Journal of Human Resource Management, 10, 3 (1999), 52-544.
19. Clark, T., Grant, D., Heijltjes, M.: Researching Comparative and Cross-National Human
Resource Management, International Studies of Management and Organization, 29, 4,
(1999/2000) 6-23.
20. Comacchio, A., Scapolan, A.C.: The Adoption of Corporate E-Learning in Italy, Education
and Training, 46, 6/7 (2004) 315-325.
21. Coopey, R. (ed.): Information Technology Policy: An International History, Oxford,
Oxford University Press (2004).
22. DiMaggio, P., Powell, W.: The Iron Cage Revisited: Industrial Isomorphism and Collective
Rationality in Organizational Fields, American Sociological Review, 48, 2, (1983) 147–
23. Dulebohn, J.H., Marler, J.H.: e-Compensation – The Potential to Transform Practice? In:
Gueutal, H.G., Stone, D.L. (eds.): The Brave New World of eHR – Human Resources in
the Digital Age, Wiley, San Francisco (2005) 166-189.
24. Florkowski, G., Olivas-Luján, M.R.: Diffusion of Information Technology Innovations in
Human Resource Service Delivery: A Cross-Country Comparison, Personnel Review, 35,
6, (2006) 684-710.
25. Galanaki, E., Panayotopoulou, L.: Adoption and Success of e-HRM in European Firms, In:
Torres-Corronas, T., Arias-Oliva, M. (eds.): Encyclopedia of Human Resource Information
Systems , IGI Global, Hershey (2008) 24-30.
Gerhart, B., Fang, M.: National Culture and Human Resource Management: Assumptions
and Evidence, International Journal of Human Resource Management, 16, 6 (2005) 971-
27. Graham, J.L.: Culture and Human Resource Management, In: Rugman, A.M., Brewer, T.L.
(eds.): Oxford Handbook of International Business, Oxford University Press, Oxford,
(2001) 503-536.
28. Hannon, J., Jelf, G., Brandes, D.: Human Resource Information Systems: Operational
Issues and Strategic Considerations in a Global Environment. International Journal of
Human Resource Management, 7, 1, (1996) 245–269.
29. Hausdorf, P.A., Duncan, D.: Firm size and Internet recruiting in Canada: A preliminary
investigation. Journal of Small Business Management, 42, 3, (2004) 325334.
30. Hempel, P.S.: Preparing the HR Profession for Technology and Information Work. Human
Resource Management, 43, 2/3 (2004) 163–177.
31. Hiltrop, J.M.: A Framework for Diagnosing Human Resource Management Practices.
European Management Journal, 14 (1996) 243-254.
32. Hofstede, G.: Culture's Consequences: International Differences in Work-Related Values,
London, Sage (1980).
33. Hoi, L.W.: Implementing e-HRM: The Readiness of Small and Medium Sized
Manufacturing Companies in Malaysia”, Asia Pacific Business Review, (2006) 12, 4, 465-
34. House, R.J., Javidan, M., Dorfman, P.W.: Project GLOBE: An Introduction, Applied
Psychology: An International Review, 50, 4 (2001) 489-505.
35. Jones, W.J.: Human Resource Information System Courses: An Examination of
Instructional Methods. Journal of Information Systems Education, 16, 3, (2005) 321-328.
36. Kabst, R., Strohmeier, S.: Virtualization: Boundaryless Organizations and Electronic
Human Resource Management, In: Larsen, H.H., Mayrhofer, W. (eds): Managing Human
Resources in Europe, Abingdon/New York, Routledge (2006) 235-258.
37. Kagami, M., Tsuji, M., Giovanetti, E.: Information Technology Policy and the Digital
Divide: Lessons for Developing Countries, Edward Elgar, London (2004).
38. Keesing, R.M.: Theories of Culture. Annual Review of Anthropology, 3 (1974) 73-97.
39. Keim, T., Weitzel, T.: An Adoption and Diffusion Perspective on HRIS Usage, In: Torres-
Corronas, T. and Arias-Oliva, M. (eds.): Encyclopedia of Human Resource Information
Systems , IGI Global, Hershey, (2008) 18-23.
40. Kozma, R.B. (ed.): Technology, Innovation and Educational Change: A Global
Perspective, International Society of Technology in Education Publications, Eugene
41. Lau, G., Hooper, V.: Adoption of e-HRM in Large New Zealand Organizations, In: Torres-
Corronas, T., Arias-Oliva, M. (Eds.) Encyclopedia of Human Resource Information
Systems , IGI Global, Hershey, (2008) 31-41.
42. Lee, I: The evolution of e-recruiting: A content analysis of fortune 100 career web sites.
Journal of Electronic Commerce in Organizations, 3, 3 (2005) 57-68.
43. Leidner, D., Kayworth, T.: A Review Of Culture In Information Systems Research:
Toward A Theory Of Information Technology Culture Conflict, MIS Quarterly, 30, 2
(2006) 357-399.
44. Lengnick-Hall, M.L., Moritz, S.: The Impact of e-HR on the Human Resource
Management Function, Journal of Labor Research, 24, 3 (2003) 365-379.
45. Martin, G., Jennings, A.: The Adoption, Diffusion and Exploitation of eLearning in
Europe. An Overview and Analysis of the UK, Germany and France, Scottish Enterprise,
Dundee (2002).
46. Mayrhofer, W., Brewster, C.: European Human Resource Management. Researching
Developments over Time, Management Revue, 16, 1 (2005) 36-62.
47. Mayrhofer, W., Morley, M., Brewster, C.: Convergence, Stasis or Divergence? In:
Brewster, C., Mayrhofer, W., Morley, M. (eds.): Human Resource Management in Europe.
Evidence of Convergence?, Butterworth-Heinemann (2004) 1-26.
48. McGaughey, S., De Cieri, H.: Reassessment of Convergence and Divergence Dynamics:
Implications for International HRM. International Journal of Human Resource
Management, 10, 2, (1999) 235-250.
49. Murray, V.V., Jain, H.C., Adams, R.J.: A Framework for the Comparative Analysis of
Personnel Administration. Academy of Management Review (1976), 47-57.
50. Myers, M.D., Tan, F.B.: Beyond Models of National Culture in Information Systems
Research, In: Tan, F.B. (ed.): Advanced Topics in Global Information Management, Idea:
Hershey, (2003) 14-29.
51. Olivas-Luján, M.R., Ramirez, J., Zapata-Cantu, L.: e-HRM in Mexico: Adapting
Innovations for Global Competitiveness. International Journal of Manpower, 28, 5 (2007)
52. Parry, E., Wilson, H.: Online Recruiting within the UK: A Model of the Factors Affecting
its Adoption, In: Bondarouk, T., Ruël, H. (eds.): Proceedings of the First European
Academic Workshop on Electronic Human Resource Management, Twente (2006).
53. Plomp, T., Anderson, R.E., Law, N., Quale, E.: Cross-National Information and
Communication Technology Policy and Practices in Education, Information Age
Publications (2003).
54. Pool, M.: Industrial Relations: Origins an Patterns of National Diversity, Reprint,
Routledge (2003).
55. Poullet, Y.: EU Data Protection Policy. The Directive 95/46/EC. Ten years after, Computer
Law & Security Report, 22, 3, (2006) 206-217.
56. Reidenberg, J.R.: Resolving Conflicting International Data Privacy Rules in Cyberspace.
Stanford Law Review, 52 (2000) 1315-1376.
57. Roehling, M.V., Posthuma, R.A., Hickox, S.: Foundations of Understanding the Legal
Environment of HRM in a Global Context, In: Storey, J., Wright, P.M., Ulrich, D. (eds.):
The Routledge Companion to Strategic Human Resource Management, Routledge, London
(2009) 71-89.
58. Sparrow, P., Schuler, R., Jackson, S.E.: Convergence or Divergence: Human Resource
Practices and Policies for Competitive Advantage Worldwide, International Journal of
Human Resource Management, 5, 2 (1994) 267-299.
59. Strohmeier, S.: Research in e-HRM. Review and Implications, Human Resource
Management Review, 17, 1, (2007) 19-37.
60. Strohmeier, S., Kabst, R.: Organizational Adoption of e-HRM in Europe. An Examination
of Major Determinants, Paper accepted in Journal of Managerial Psychology (2009).
61. Teagarden, M.B., von Glinow, M.A.: Human Resource Management in Cross-Cultural
Contexts: Emic Practices versus Etic Philosophies, Management International Review, 37,
1 (1997) 7-20.
62. Teo, T.S.H., Lim G.S., Fedric, S.A.: The Adoption and Diffusion of Human Resource
Information Systems in Singapore”, Asia Pacific Journal of Human Resources, 45, 1 (2007)
63. Trompenaars, F.: Resolving International Conflict: Culture and Business Strategy, Business
Strategy Review, 7, 3 (1996) 51-68.
64. Waring, P., Burgess, J.: Developments in Electronic Employment Relations, International
Journal of Employment Studies, 14, 2 (2006) 83-102.
65. Whitley, R.: Divergent Capitalisms: The Social Structuring and Change of Business
Systems. Oxford (1999).
66. Williamson, O.E.: The Economics of Organization: The Transaction Cost Approach,
American Journal of Socioloy, 87, 3 (1981) 548-577.
Zhang, M.: Information Technology Policy-Making in the People’s Republic of China,
International Journal of Public Administration, 25, 5 (2002) 693-721.