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

[60].

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

 SciTePress

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,

65].

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

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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

influences.

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

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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

(„What?“)

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

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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.

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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.

Hence:

P 2: Divergences in national general and specific educational preconditions will

lead to divergences in quantitative adoption (“proposition of educational

digital divide”).

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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

openness”).

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”).

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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

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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

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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

openness”).

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,

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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

determinants.

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].

References

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) 677−693.

3. Bamber, G., Lansburry, R.D., Wailes, N.: International and Comparative Employment

Relations. Globalisation and the Developed Market Economies, 4

ed. Sage, London

(2004).

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).

116

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-

415.

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–

165.

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–

160.

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.

26.

Gerhart, B., Fang, M.: National Culture and Human Resource Management: Assumptions

and Evidence, International Journal of Human Resource Management, 16, 6 (2005) 971-

986.

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) 325−334.

117

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-

485.

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

(2003).

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.

118

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)

418–434.

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)

44-62.

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.

67.

Zhang, M.: Information Technology Policy-Making in the People’s Republic of China,

International Journal of Public Administration, 25, 5 (2002) 693-721.

119