The Scholarly Influence of Heinz Klein: Ideational and Social Measures of His Impact on IS Research and IS Scholars

Abstract

Heinz Klein was a fine scholar and mentor whose work and life have inspired us to explore the notion of ‘scholarly influence’ which we cast as ‘ideational’ and ‘social influence’. We adopt a portfolio of measures approach, using the Hirsch family of statistics to assess ideational influence and Social Network Analysis centrality measures for social influence to profile Heinz Klein's contribution to information systems (IS) research. The results show that Heinz was highly influential in both ideational terms (a significant body of citations) and social terms (he is close to the heart of the IS research community). Reflecting on the major research themes and scholarly values espoused by Klein we define a ‘Kleinian view of IS research’, grounded in Habermas’ Theory of Communicative Action, and use that to frame four affirmative propositions to address what we observe to be a distortion and attenuation of the academic discourse on the evaluation of scholarly production. This paper argues that focus should be shifted from the venue of publication of the research to the uptake of the ideas contained in it, thus increasing the openness of the discourse, participation in the discourse, truthfulness, and reduction of the inequities in power distribution within academia.

Full text

AUTHOR COPY
The scholarly influence of Heinz Klein:
ideational and social measures of his
impact on IS research and IS scholars
Duane Truex
1,2
,
Michael Cuellar
3
,
Hirotoshi Takeda
1,3,4
and Richard Vidgen
5
1
CIS Department, J. Mack Robinson College of
Business, Georgia State University, Atlanta, GA,
U.S.A.;
2
Mittuniversitetet, Department of
Information Technology and Media, Sundsvall,
Sweden;
3
School of Business, North Carolina
Central University, Durham, NC, U.S.A.;
4
University of Paris Dauphine, Centre de
Recharche en Management & Organization
Centre de Recharche Economique, Paris Ce
´
dex;
5
School of Information Systems, Technology and
Management in the Australian School of
Business, University of New South Wales,
Australia
Correspondence: Duane Truex,
CIS Department, J. Mack Robinson College of
Business, Georgia State University, 33 Broad
Street, Atlanta, GA 30303-3083, U.S.A.
Tel: þ 1 404 413 7380
Received: 31 July 2010
Revised: 8 February 2011
Accepted: 17 March 2011
Abstract
Heinz Klein was a fine scholar and mentor whose work and life have inspired us
to explore the notion of ‘scholarly influence’ which we cast as ‘ideational’ and
‘social influence’. We adopt a portfolio of measures approach, using the Hirsch
family of statistics to assess ideational influence and Social Network Analysis
centrality measures for social influence to profile Heinz Klein’s contribution to
information systems (IS) research. The results show that Heinz was highly
influential in both ideational terms (a significant body of citations) and social
terms (he is close to the heart of the IS research community). Reflecting on the
major research themes and scholarly values espoused by Klein we define a
‘Kleinian view of IS research’, grounded in Habermas’ Theory of Commu-
nicative Action, and use that to frame four affirmative propositions to address
what we observe to be a distortion and attenuation of the academic discourse
on the evaluation of scholarly production. This paper argues that focus should
be shifted from the venue of publication of the research to the uptake of the
ideas contained in it, thus increasing the openness of the discourse,
participation in the discourse, truthfulness, and reduction of the inequities in
power distribution within academia.
European Journal of Information Systems advance online publication, 10 May 2011;
doi:10.1057/ejis.2011.16
Keywords: Heinz Klein; scholarly influence; Hirsch statistics; social network analysis;
lexical analysis; critical social theory; ideational influence; social influence
Introduction
This paper is a continuation of a stream of research examining the
construct we call simply ‘scholarly influence’. This work began as a direct
offshoot of the ‘Festschrift’ for Heinz K. Klein that we quickly organized on
May 18 and 19 2007 in Atlanta upon learning of the status of his health.
One goal of the event was to identify research themes in Heinz’s work,
which many of us had shared, to explore intellectual themes of common
interest, and to imagine a trajectory of those themes in future work. In our
work of categorizing the themes and periods in Heinz’s work and in
preparing to summarize the impact of Heinz’s work and in hearing from
the many people who responded to the invitation to participate in the May
2007 event, we identified a set of issues and formulated research questions
that fuel our work to this day. In one sense, this paper is a homage to a
mentor, a close friend, an important and we believe influential if quixotic,
figure in the information systems (IS) research community. But in a much
more important sense this research is an exploration of a notion of
scholarship, which epitomized the intellectual focus of Heinz Klein’s life.
European Journal of Information Systems (2011) 1–18
&
2011 Operational Research Society Ltd. All rights reserved 0960-085X/11
www.palgrave-journals.com/ejis/

AUTHOR COPY
Heinz was a prolific writer, a formidable scholar, and an
excellent mentor to students and junior colleagues. He
established a circle of loyal and respected friends.
Prima facie, there is a large amount of evidence of
Klein’s influence on IS research: he was awarded honorary
doctoral degrees by the University of Oulu (Finland) and
the University of Pretoria (South Africa), received the IFIP
Outstanding Service Award (1995), received an MISQ Best
Paper Award (with Michael Myers in 1999) and has
published some of the most highly cited works in the IS
literature. However, this anecdotal information does not
give us a complete picture of his influence in the IS field.
The aim of this paper is therefore to explore Klein’s
scholarly influence. To assess his influence, we must ask a
number of other questions: what is scholarly influence,
how is it manifested in both intellectual and social terms
and how can it be measured and valued?
Accordingly we have a three-fold purpose in this paper.
First, we examine the components commonly thought
to be essential to garnering influence as a scholar and
how that influence might be measured. This examination
leads us to cast scholarly influence as comprising:
(1) ideational influence, that is how a scholar’s ideas, as
published in various forms, are taken up and impact
other scholar’s ideas; and (2) social influence, that is
how a scholar influences other scholars by means of
social interactions (Takeda et al., 2010). Second, we
analyze Heinz’s academic contribution through the lens
of ideational and social influence. Third, we reflect on
Klein’s espoused values and published principles on the
conduct of research to frame what we call a Kleinian
Approach to IS Research that we then use to critique and to
offer four affirmative positions in response to what we
consider to be a systematically distorted discourse on the
matter of evaluating scholarly productivity.
Why the term ‘influence’ rather than ‘quality’
While the literature notes its importance, there has not
been an agreed upon definition of ‘quality’ in terms of
journals (Locke & Lowe, 2002) nor is there yet a theory of
scholarly quality that might be applicable to papers,
journals or an individual scholar. To us, the practice of
determining quality seems largely an implicit one based
on the collective assumptions of those assessing the
paper, journal or scholar. The approach used to define
quality seems similar to that used by U.S. Supreme Court
Justice Potter Stewart in approaching obscenity: ‘y I
know it when I see it’ (Stewart, 1964). Journal lists and
rankings have traditionally been developed based on
opinion using implicit definitions which then leads to a
subjectivity in rankings (Walstrom et al., 1995; Chua
et al., 2002; Podsakoff et al., 2005; Serenko & Bontis,
2011). In these studies a higher ranking is taken to mean
‘higher quality’ and that papers published by these
‘higher quality’ journals are therefore of high quality.
But, there is evidence that 25% of the papers that these
higher ranked journals publish are not ultimately well
cited by the field; moreover 63% of the most highly
regarded papers are published by lower ranked journals
(Singh et al ., 2007). Truex et al. (2009) argue that not
all articles published in top-tier journals qualify as top
articles, that ‘top management journals are not the sole
venue, nor even the majority venue, where these so
called top articles are published’ (p. 587). This suggests
that the notion of quality is problematic and that if the
concept ‘quality’ is to be used, there is a great need to
define and operationalize it in a context of assessing
journals, papers, and scholars. As of yet, this definition
and operationalization has not been developed. Lacking a
metric for quality, we turn to the concept of influence
instead. As will be seen below, there is a long literature
stream on the assessment of influence in the information
sciences field. This literature will provide us with
definitions and operationalization of the construct as
well as metrics by which to measure it.
How is scholarly influence evaluated?
We define scholarly influence as the ability of a scholar to
have his/her ideas considered by others in the course of
their own research. This concept is distinct from the
notion of quality in that no assessment is attempted as to
whether it is ‘good’ or ‘bad’ research. Rather, the question
is whether the ideas generated by the research are used,
considered by, or at least known to other scholars. We
argue that this is an important consideration in the
evaluation of a scholar. If a scholar’s research is rigorously
executed and flawlessly written but is unknown, then it is
as if the research were never done. In contrast, how much
a scholar’s ideas are taken up by the field is a key pointer
to the direction of the field and what it considers to be
important. Further, we view the process of research as a
collaborative and communal endeavor rather than the
work of individual (lone) geniuses. Therefore, with whom
a researcher works is an important aspect of influence. Of
course, influence can come in many forms. Appearing in
a top-ranked journal may influence those who read it but
not necessarily be translated into a citation, as may a late
night discussion between academics at a conference
dinner. However, our concern is with tracing or measur-
ing visible expressions of influence, especially where the
measurement process is transparent, replicable, open to
all, amenable to being automated, and uses public data.
We identify two forms of influence: ideational influence
(who is using your work?) and social influence (who are
you working with?). We consider each form in turn.
Ideational influence
Ideational influence may be defined as the uptake of a
scholar’s ideas by the field. The concept is that if a
scholar’s research is influential, then we will see it being
used in many other scholars’ research. In the IS field,
citation counting is the primary way influence is
measured. Using citation data allows us to create a proxy
for the uptake of ideas from the scholar in the field. In
essence, citation data allow us to make an assessment
of the influence of a scholar. Of course, having been
The influence of Heinz Klein Duane Truex et al2
European Journal of Information Systems

AUTHOR COPY
published (i.e., productive) is a necessary prerequisite to
being cited. A scholar’s productivity can also be measured
in terms of how many papers they publish. The scholar’s
influence derives not just from their ideas alone, but also
from having a continuing stream of ideas published and
available to others.
The assessment of ideational influence has been an
ongoing project in the information sciences field for over
80 years. Beginning in 1926, there has been a stream of
investigation to ‘determine, if possible, the part which
men of different caliber contribute to the progress of
science’ (Lotka, 1926, p. 317). This stream, the so-called
Lotkaian scientometrics, has led more recently to the
development of what has been termed the Hirsch, or
h-family, statistics. The h-indices balance the productivity
of the scholar against the citations to those publications
thus providing a metric that demonstrates both the
productivity and uptake of the scholar’s publications
(Hirsch, 2005; Cuellar et al., 2008).
The application of the Hirsch statistics to the assess-
ment of scholarly influence in the IS discipline has been
advanced elsewhere (Serenko & Bontis, 2009; Truex et al.,
2009) and the calculation of the indices is described
there. In this paper, we used three of the Hirsch family
indices to assess the ideational influence of a scholar.
The first h-statistic proposed is what we will refer to as
the ‘native h-index’ or simply ‘h-index’. The h-index
has been developed with the goal of ‘quantify[ing]the
cumulative impact and relevance of an individual’s
scientific research output’ (Hirsch, 2005).
Although promising, a naı
¨
ve use of the ‘native-h’
statistic is problematic. The index has been challenged
as being ‘biased’ in several ways. For example, consider a
scholar who produces a paper, which garners a large
number of citations, but his other papers are not highly
cited. The native h-index is insensitive to the number of
citations to a work once the paper has received a number
of citations higher than the h-index itself. The question
asked is: when given two scholars with the same h-index,
does not the one having a higher number of citations
to her papers have greater influence? To address this con-
cern and adjust for this difference, Egghe has proposed
the ‘g-index’ (Egghe, 2006). The g-index gives greater
weight to highly cited articles. Another criticism of the
h-index is that it favors older publications. Articles that
have been in print for a longer period of time have had
more of a chance to gain citations. Newer articles may be
as influential or become more influential than older
articles given sufficient time. To address this concern, the
contemporary h-index or hc-index has been proposed
(Sidiropoulos et al., 2006). The hc-index weights citations
to more recent articles more highly. By using the
hc-index, we can compensate for the effects of time and
create comparability between papers of different ages.
It is our position that by using these three indices
together h, hc, and g, we can build a profile of the ide-
ational influence of scholars that can be used to compare
their relative influence. These profiles can be used for a
variety of purposes, for example promotion to full
professor, hiring decisions for full professors, or as in this
case demonstrating the influence of a scholar (Truex
et al., 2009). Ideational influence is, however, only one
form of influence.
Social influence
The development of scientific knowledge is well recog-
nized as being a social activity (Pinch & Bijker, 1984;
Latour, 1987; Bhaskar, 1997). As researchers work
together, they interact with each other to help flesh out
theories and test these theories either formally through
the publication process or informally through interac-
tions at conferences and other meetings or through
media such as telephone and email. These interactions
mold and shape the ideas of those interacting and
eventually help foster the consensus that determines
what the field regards as ‘truth’. Such interactions help
develop understanding and sometimes in building trust
and greater social connectedness between scholars.
And, at a minimum, they put a human voice or face on
ideas. As these interactions take place, the informal
interactions sometimes lead to formalization of relation-
ships: becoming a doctoral student-advisor, joining a
faculty and becoming co-workers on the same faculty,
forming research teams, co-editing conference proceed-
ings, co-authoring research papers, and the like.
In this process of interaction, some scholars are more
persuasive than others, in terms of influencing others as
to the validity of their ideas. The differences in these
levels of influences arise through differential social skills,
varying comfort levels in social settings, affinity between
scholars, commonality of thought and so on. This ability
to influence others through the processes of social
interaction we term ‘Social Influence’. On the one hand a
scholar may be said to have higher social influence if
he/she is able to have their ideas considered by other
scholars through their social interactions with them.
Ideational influence, on the other hand, is in view when
the influence is exercised strictly through their published
works, that is through the force of their ideas without
their social interaction.
Since social interaction takes place in largely informal
situations, operationalization would seem to be diffi-
cult – we cannot observe directly changes in thought.
However as this interaction often formalizes into
partnerships, we can use these partnerships to assist in
operationalizing the concept of social influence. These
partnerships such as doctoral student-advisor and co-
researchers are also often difficult to collect data on.
Therefore, we suggest that both academic collaborations
will likely be manifested in co-authored and citable
resources, such as journal and conference papers, edited
collections, special issues, and conference panels. As
advisors take their students through the process of
learning how to conduct research, the advisor teaches
the student accepted methods and also introduces them
to the field’s literature and interprets it with him/her.
The influence of Heinz Klein Duane Truex et al 3
European Journal of Information Systems

AUTHOR COPY
This is a position of great influence (Avison & Pres-Heje,
2005). The student often shows the advisor new streams
of literature or performs innovative research that con-
tributes new knowledge. Thus the student is reciprocally
influential to the advisor. Similarly, the relation-
ship between research partners is one in which exists a
significant communication between them exchanging
ideas and interpreting the findings. Thus each exerts
influence on the other. One of the results of these
processes of interaction is the production of citable
academic artifacts (e.g., jointly produced papers, edited
collections, and panel discussions) that document and
report their collaboration. These citable artifacts, there-
fore, represent the result of academic collaborations and
can serve as a proxy for the social influence that occurred
between them.
Klein’s influence as a scholar
To build a profile of Heinz Klein’s scholarly influence we
sought to apply our formulations of ideational and social
influence to Klein’s publication and academic collabora-
tion record. We generated a profile of Klein’s Hirsch
statistics and social network (Social Network Analysis
(SNA)) centrality measures and then compared his profile
against the profiles of other scholars within the IS field.
Klein’s ideational influence
Initial work on Heinz Klein’s influence started with
gathering his publications. We started with his Curricu-
lum Vitae, and then added searches of various biblio-
graphic databases such as EBSCOhost, Academy of
Science, ACM electronic library, and the IEEE electronic
library. Some of the problems in acquiring all of Klein’s
data included the lack of electronic versions of the
research, language problems, and author identification.
We had problems of finding electronic versions of
research, especially when the research was published
prior to 1992. The date of 1992 seems to be close to the
cutoff of where bibliometric databases started to emerge
and thus electronic versions of research started to appear.
While we find more and more examples of new research
since the early 1990s that have been both published in
electronic and paper form (or just electronic form) the
conversion of paper-only research prior to 1992 is a time-
consuming project. This has meant that electronic
versions of research prior to 1992 were either missing,
or hard to find. However in recent years, we have seen a
rush by electronic databases to provide older, paper-only
era research in electronic form and these data are
increasingly becoming available online.
A second problem was that Klein started his academic
career in Germany, which meant that there were some
German texts that appeared in his list of publications.
The third problem was that there are other researchers
sharing similar names, for example Karlheinz Kautz, or
sharing a set or subset of Heinz K. Klein’s name, for
example Gary Klein, Hans K. Klein, or the physicist also
named H.K. Klein. The data cleansing in our search of
Heinz K. Klein required disambiguating from the ‘Klein’
alternatives.
The search yielded a total of 161 publication entries
that included: journal papers, books, book chapters,
conference proceedings, special journal issue calls, and
published presentations.
The current Klein data reveal that he has an h-index of
27, g-index of 72, and an hc-index of 16. To place Klein’s
scores in a larger context, we examined 448 prominent IS
researchers identified by Clark et al. (2009) and computed
their h-index, g-index, and hc-index scores and rank-
ordered this list. Klein’s position in this ranking was 48
according to the h-index, position 31 according to the
g-index, and position 93 according to the hc-index.
The H-statistics were computed in early June 2010, a
relevant point because the H-stats change over time. The
h-indices peer group (Table 1) shows a list of the scholars
surrounding Heinz Klein for comparison.
As can be seen, Klein has an over-all influence rating
roughly equivalent to such well-known scholars as Enid
Mumford, K.K. Wei, Suzanne Rivard, and Joey George.
Recalling that the g-index gives greater weight to highly
cited articles, we note that Klein has the highest g-index
in this peer group indicating that his most cited papers
tend to be more highly cited than the others in the peer
group. The hc-index compensates for the effects of time
and creates comparability between papers of different
ages by increasing the weights of more recent citations.
We note that his hc-index scores were slightly lower than
the median of this peer group. This may indicate that
his ideas were not immediately recognized or taken up.
We interpret this as evidence of his status as a ‘critical
Table 1 List of scholars with similar h-indices to Klein
(ranks in parenthesis)
Scholar last Scholar first h-index g-index hc-index
Rai Arun 28 (43) 55 (68) 21 (31)
Sahay Sundeep 28 (43) 51 (77) 19 (46)
George Joey 28 (43) 66 (38) 18 (60)
King John 28 (43) 56 (63) 18 (60)
Wei Kwok-Kee 28 (43) 53 (73) 18 (60)
Irani Zahir 27 (48) 42 (120) 20 (38)
Rivard Suzanne 27 (48) 56 (63) 19 (46)
Briggs Robert 27 (48) 55 (68) 19 (46)
Rafaeli Sheizaf 27 (48) 58 (58) 18 (60)
Han Ingoo 27 (48) 44 (110) 18 (60)
Love Peter 27 (48) 40 (137) 18 (60)
Klein Heinz 27 (48) 72 (31) 16 (93)
Mumford Enid 27 (48) 48 (89) 13 (146)
Varshney Upkar 26 (56) 49 (85) 20 (38)
Siau Keng 26 (56) 46 (100) 19 (46)
Chau Patrick 26 (56) 61 (48) 18 (60)
Tam Kar Yan 26 (56) 59 (54) 18 (60)
Gupta Alok 26 (56) 44 (110) 18 (60)
Swanson Burton 26 (56) 69 (34) 17 (77)
Krishnan Ramayya 26 (56) 44 (110) 16 (93)
The influence of Heinz Klein Duane Truex et al4
European Journal of Information Systems

AUTHOR COPY
outsider’ who advanced ideas and critiques of extant
dogma before others, a point we discuss more fully in the
reflections portion of this paper.
Table 2 shows a section of the table sorted by g-index
and then h-index, presenting Klein’s g-index peer group.
When re-sorting and ranking by the g-index Klein
ranks very well even though most of his neighbors have
higher h-indices than his. Once again, this shows that his
highest cited papers are equivalent to those produced by
other well-recognized and well-established scholars of
high overall influence in our field. Klein’s hc-index ranks
at the bottom of this peer group indicating again that
ideas took longer to catch on but are acknowledged
eventually and become highly cited. We interpret this as
evidence of his outsider status as a critical social theorist
who as a researcher/author was introducing the field to
the principles and values of an unfamiliar theory.
Klein’s social influence
To assess social influence we use the methods commonly
used in SNA. In SNA, formal (e.g., such as the co-
authoring relationship described above) and informal
(e.g., who you have dinner with when attending confer-
ences) relationships between researchers exist. Some of
them can be mapped (Vidgen et al., 2007). Formal rela-
tionships are easier to map, as co-author information
is readily available from public information. Data on
informal relationships are harder to mine – it is neither
easy nor appropriate to map who had dinner with whom
at a conference. We will, therefore, focus on academic
collaborations that result in a co-authored, citable
research artifact: conference and journal papers, edited
collections (such as a special issue of a journal), and panel
discussions.
By examining the centrality measures of the academic
collaboration network we can arrive at a profile of
measures that assess the social influence of the members
of a research community. Proper comparison of these
profiles allow evaluators to assess the social influence
of the scholar and along with the ideational measures
provided by the Hirsch indices can be combined to create
a fuller assessment of the scholar’s intellectual contribu-
tion. The common unit of currency for evaluating
ideational and social influence is a citable research
artifact.
SNA provides three primary measures of centrality –
degree, betweenness, and closeness (Freeman, 1979;
Wasserman & Faust, 1994) – to analyze the aggregate
distances between one academic and the rest of the
network.
Degree centrality indicates how many times a particular
academic has collaborated, indicating the number and
intensity of collaboration relationships a researcher has.
Degree is a measure of the level of activity of a scholar.
Betweenness centrality indicates how many paths linking
academics intersect an individual academic, or put
differently, how many connections either originate or
pass through a given academic, thus indicating that he/
she is a ‘hub’ for social influence. The higher this measure
is then the higher the scholar’s power in the network and
the greater their social influence.
Closeness centrality indicates the average number of links
when connecting to other people in the network. A larger
closeness score indicates that this person has a shorter
distance in terms of academic collaborators. This means
that the academic is more central to the flow of ideas and
is well-placed to learn about new ideas quickly from
others and can spread their own ideas through their local
network.
Klein’s direct co-authorships To explore Klein’s academic
social network, we collected the co-authorship data from
Klein’s work. This resulted in a list of co-authors and a co-
author matrix for Klein. The number of co-authors that
Klein worked with totaled 99 over a period of 35 years.
From Klein’s collaborations there were 235 pairings of
authors. This included pairings of other authors when
they worked with Klein. For example, if Klein worked
with Rudy Hirschheim, Kalle Lyytinen, and Duane
Truex on one paper, then there were six pairings (Klein-
Hirschheim, Klein-Lyytinen, Klein-Truex, Hirschheim-
Lyytinen, Hirschheim-Truex, and Lyytinen-Truex).
The most frequent co-authors are shown in Table 3.
There were 11 others with two co-authorships, and 66
others with one co-authorship.
For the purpose of data analysis we identified the close
knit researchers as the top 10 researchers that Klein
worked with. We identified them as the ‘Kleinian’ ten and
they are: R. Hirschheim, K. Lyytinen, D. Truex, H. E.
Nissen, J. Iivari, K. Kumar, O. Ngwenyama, M. Myers, P. B.
Andersen, and E. Monod. The h-indices of the Kleinian
ten are shown in Table 4.
Table 2 Scholars near to Klein in g-index
Scholar last Scholar first h-index g-index hc-index
Chen Yen-Liang 50 (4) 76 (26) 30 (7)
King William 41 (12) 76 (26) 24 (23)
Smith Michael 38 (16) 76 (26) 28 (9)
Watson Richard 38 (16) 75 (29) 25 (18)
Wigand Rolf 22 (94) 73 (30) 17 (77)
Keil Mark 34 (23) 72 (31) 25 (18)
Baskerville Richard 33 (26) 72 (31) 22 (29)
Klein Heinz 27 (48) 72 (31) 16 (93)
Avison David 26 (56) 70 (33) 15 (110)
Clemons Eric 34 (23) 69 (34) 19 (46)
Swanson Burton 26 (56) 69 (34) 17 (77)
Sambamurthy V. 32 (32) 67 (36) 24 (23)
Rees Jackie 24 (71) 67 (36) 21 (31)
Shaw Michael 40 (15) 66 (38) 23 (26)
George Joey 28 (43) 66 (38) 18 (60)
Gurbaxani Vijay 21 (109) 66 (38) 15 (110)
The influence of Heinz Klein Duane Truex et al 5
European Journal of Information Systems

AUTHOR COPY
Thus it can be seen that Klein’s co-authors include
three of the highest-ranking scholars in the IS field.
The Kleinian direct co-authorship network (Figure 1)
is realized in the network mapping tool, Pajek. The
frequency and strength (repeated co-authorships) are
taken into account for the Cartesian distance in the
network. The more co-authorships a researcher has with
Klein, the closer to the center the researcher will appear.
Also the more frequently a set of co-authors work with
Klein the closer the set of co-authors will appear in the
network. We see that the Kleinian ten appear centrally in
this figure.
Klein’s centrality within the IS field The SNA centrality
measures used in this research were calculated from a
large set of citable research artifacts from a wide range of
IS venues. This set of 30 different publication sources
included eight of the major IS journals and all the
major annual AIS-affiliated IS conferences from inception
(Table 5). We eventually extracted roughly 18,000 research
artifacts – these include conference papers, journal papers,
edited collections, and panels – and 5000 unique
researchers for the database. To reduce the amount of
data analysis required, we again selected the list of 448
scholars identified by Clark et al. (2009) as scholars who
published over three articles in the AIS ‘Basket of 8’ over
the period 2003–2007. The connections through co-
authorship were then calculated for each of these
researchers using the centrality measure calculations
described above. The main component used for the SNA
contains 391 academics connected by co-authorship
relationships – the reduction from 448 is due to authors
who only sole authored in the database or were part of
separate collaboration networks that were not connected
to the main component.
Klein’s SNA centrality
The centrality measures computed for Klein were as
follows: degree (23), betweeness (0.40), and closeness
(31.86). With these numbers Klein ranks 50th (degree),
155th (betweenness), and 55th (closeness) among the top
448 IS researchers identified by Clark et al. (2009). The
data tell us that Klein had many connections and worked
with many people during his career, as evidenced by his
high ranking in degree. We also see that Klein’s closeness
ranking was relatively high which meant that he was a
mainstream player in the IS community and not the
maverick outsider that we might have thought. Finally
his betweeness ranking is still close to the top third,
meaning that he was more likely than average to serve as
a link through whom one IS researcher is connected to
another IS researcher in the 488 Clark et al. IS researchers.
Table 6 illustrates the scholars who had similar degree
centrality to that of Klein.
When looking at the degree centrality we see that Klein
shares a score similar to Salvatore March, Claudia
Loebbecke, Dan Robey, and William King. Note, however,
that if there are researchers that tend to single author
more than co-author, their degree centrality will be ‘hurt’
due to the fact that a single authored research artifact
receives no connection through a co-authorship relation-
ship. Table 7 shows the scholars close to Klein in terms of
closeness centrality.
Looking at the ‘closeness centrality’, Klein ranks higher
than other well-recognized IS scholars. Note also that in
this group Klein ranks relatively high in degree centrality
as compared to his neighbors. This suggests that
Klein was more open to collaboration than his peers
with whom he shared similar closeness scores in the IS
research network.
Table 3 Klein’s most common co-authors
Co-Author Number of time co-authored
R. Hirschheim 58
K. Lyytinen 18
D. Truex 12
H. E. Nissen 9
J. Ivari 9
K. Kumar 9
O. Ngwenyama 8
M. Myers 7
P. B. Andersen 5
E. Monod 5
B. Holmqvist 4
G. Fitzgerald 4
N. Findler 4
R. Alvarez 4
W. Kirsch 4
D. Avison 3
J.L. DeGross 3
J. Venable 3
M. Newman 3
R. J. Boland 3
R.J. Welke 3
R. Posner 3
T. Wood-Harper 3
Z. Asif 3
Table 4 h-indices of the Kleinian 10 (in alphabetical
order following Klein)
Researcher h-index g-index hc-index
Heinz Klein 27 72 16
P. B. Andersen 18 32 12
Rudy Hirschheim 41 87 24
Juhani Iivari 20 42 15
K. Kumar 15 50 15
Kalle Lyytinen 42 80 26
Emmanuel Monod 7 12 4
Michael Myers 29 84 22
Ojelanki Ngwenyama 15 35 12
H. E. Nissen 7 15 4
Duane Truex 14 31 9
The influence of Heinz Klein Duane Truex et al6
European Journal of Information Systems

AUTHOR COPY
To summarize the results of this analysis, we see that
Klein ranks in the top 12% of the 448 scholars analyzed
in terms of closeness, indicating that he is central to the
IS core and therefore ranks high in social influence. His
influence is most like that of the well-recognized William
King and Ritu Agarwal. Thus once again, Klein is shown
to be an influential scholar comparing favorably and
even scoring higher than many more famous IS scholars
in terms of his social influence. His central position in the
network can be seen clearly in Figure 2.
Klein’s social influence through mentoring
As well as through the social relationship of co-authoring
research artifacts, academics exert considerable influence
through formal mentoring, notably via the training and
examination of doctoral students, and via informal
relationships, such as providing advice and guidance to
more junior academics and engaging in discussion and
giving critical commentary to peers. This form of
influence derives from an acknowledgement of the junior
participant (mentee) that there is much to learn from the
senior partner (mentor, master) and therefore defers a
considerable amount of judgment to the senior partner in
terms of topic, approach, and style to the mentor. This
influence manifests itself explicitly in direct discussion,
but there is also a transfer of implicit knowledge through
an imbibing of the standards of the ‘community of
practice’ (Lave & Wenger, 1991; Nonaka et al., 2000; Seely
Brown & Duguid, 2001). Accounting for and measuring
informal mentoring relationships is difficult, if not
impossible, to track and document. However, mentoring
interaction is often manifest via co-authoring relation-
ships and this be captured in part through social
influence metrics.
Klein’s role as mentor includes both formal mentoring,
notably via the training of students, and via informal
relationships. We have ample evidence of Heinz’s role
as an informal mentor from persons attending his
Festschrift in 2007, in reports from colleagues and in
evidence from his role as thesis committee member or as
an external examiner on four continents. Because
informal mentoring relationships are difficult, if not
impossible, to measure, an extended analysis of his role as
informal mentor is beyond the scope of this paper.
Nevertheless, anecdotal evidence indicates that Klein was
generous in this realm, providing copious feedback and
face time to those asking for his advice. Secondary
evidence of his engagement as mentor and good
academic colleague came through the continuous stream
of international visitors who were ensconced for varying
lengths of time at SUNY Binghamton. People chose the
remote Upstate New York site for a U.S. sabbatical or
other non-permanent academic residence in preference
to higher profile institutions. One example is the
prominent colleague, Richard Baskerville, who chose
SUNY Binghamton as a long-term academic base, in large
part because of Heinz and the scholarship he engendered.
The list of visitors is too long to fully enumerate, but
Figure 1 Heinz Klein co-author network.
The influence of Heinz Klein Duane Truex et al 7
European Journal of Information Systems

AUTHOR COPY
familiar names to the EJIS and IFIP WG 8.2 community
include: K. Lyytinen, R. Hirschheim, M. Myers, A. Lee,
J. Iivari, J. Bansler, J. Stage, T. Wood-Harper, D. Avison,
H-E Nissen, Frantz Rowe, and J. Pries-Heje.
Klein’s formal role as thesis advisor was reserved for a
modest number of Ph.D. students: only 10 students over
a 20-year period. The sheer number is not astounding.
By comparison Colette Roland, University of Paris, has
Table 5 Publication sources used in the social influence analysis publication
Dates included
ACIS 2001–2008
AIS Transactions on Human-Computer Interaction 2009
AMCIS 1998–2009
BLED 2001–2009
Communications of the Association for Information Systems 1999–2010
CONFIRM 2008
DIGIT 2001–2009
ECIS 1993–2009
EIS 2008
European Journal of Information Systems 1993–2007
GlobDev 2008
ICDSS 2007
ICIS 1994–2009
Information Systems Journal 1991–2010
Information Systems Research 1990–2009
International Research Workshop on IT Project Management 2006 – 2009 2006–2009
Internationale Tagung Wirtschaftsinformatik 1999, 2001, 2003, 2007
Journal of Information Technology Theory and Application (JITTA) 1999–2010
Journal of Management Information Systems 1984–2009
Journal of the Association for Information Systems 2000–2010
MCIS 2007–2008
MG 2009
MIS Quarterly 1977–2010
Pacific Asia Journal of the Association for Information Systems 2009
PACIS 1993–2009
Revista Latinoamericana Y Del Caribe De La Associacion De Sistemas De Informacion 2008–2009
Scandinavian Journal of Information Systems 1989–2009
SIGHCI 2003–2009
The Journal of Strategic Information Systems 1991–2009
Wirtschaftsinformatik 2005
Table 6 Scholars near to Klein degree centrality
Scholar last Scholar first Degree Between Closeness
March Salvatore 27 1.85 38.27
Gupta Alok 26 2.29 32.34
Pan Shan 26 1.04 30.90
Avital Michel 25 0.70 34.18
Loebbecke Claudia 25 1.41 34.73
Klein Gary 24 0.33 28.02
Rai Arun 24 1.51 31.53
Agarwal Ritu 23 1.56 31.99
Klein Heinz 23 0.40 31.86
Sharman Raj 23 0.03 23.10
Wigand Rolf 23 0.03 30.85
King William 22 1.59 31.81
Liang Huigang 22 0.13 27.78
Robey Daniel 22 1.80 32.77
Teo Hock Hai 22 0.52 28.24
Xue Yajiong 22 0.13 27.78
Table 7 Scholars near to Klein closeness centrality
Scholar last Scholar first Degree Between Closeness
Chen Hsinchun 19 3.93 32.28
Te
0
eni Dov 19 0.91 32.28
Courtney James 18 2.92 32.26
Lucas, Jr Henry 13 0.84 32.20
Carte Traci 21 0.53 32.07
Avison David 17 0.42 32.05
Agarwal Ritu 23 1.56 31.99
Bharadwaj Anandhi 12 0.80 31.94
Klein Heinz 23 0.40 31.86
Mukhopadhyay Tridas 15 2.35 31.86
King William 22 1.59 31.81
Porra Jaana 13 0.20 31.78
Majchrzak Ann 14 0.56 31.73
Slaughter Sandra 20 0.73 31.66
Gregor Shirley 12 0.58 31.55
Rai Arun 24 1.51 31.53
The influence of Heinz Klein Duane Truex et al8
European Journal of Information Systems

AUTHOR COPY
supervised 95 Ph.D. thesis students in a 30-year career.
But proportionately it compares well to the 18 Ph.D.
students advised by Dan Robey, who had the benefit of
working for 37 years at research-oriented Carnegie 1
designated Ph.D.-granting research universities in the
U.S. Although Klein’s Ph.D. advising may have been
modest in number, our research discovered that even
though not all of Klein’s students chose to stay in
academe or to work at Ph.D. granting institutions, many
of the Klein students have themselves become extremely
influential scholars in their own right. To date those
ex-students have produced nearly 50 ‘Kleinian grand-
baby-docs’ on four continents. This suggests that, just as
he chose his academic collaborators well, his influence
was magnified via his choice of students.
Discussion: toward a Kleinian evaluation of
scholarly endeavor
Our findings show that Heinz Klein at the end of his
career achieved the status of a highly influential scholar.
To some readers, his case might suggest that publishing in
top rated journals is the only path to influence. But the
truth is that, of his 10 most cited papers, fully half were
not published in what would now be considered top IS
journals: the earliest four were published in IS journals
such as ACM publications and the IFIP 8.2 conference
series ‘Research Methods in Information Systems’, giving
additional weight to the argument that publication in the
top IS journals is not the only path to influence in the IS
field (Truex et al., 2009). Klein did not stay in the
conventional paradigm, which would have gotten him
earlier acceptance into the establishment journals, rather
he persisted in putting forward his controversial ideas
and building a small following of like-minded thinkers.
Initially it was a struggle for those works to gain a broader
hearing and, not being accepted at major journals, he
published where he could publish, when he could get in.
For example, two of his early papers, ‘The Poverty of
Scientism’ (Klein & Lyytinen, 1985b) and ‘The Critical
Theory of Ju
¨
rgen Habermas as a Basis for a Theory of
Information Systems’ (Klein & Lyytinen, 1985a) were
published in Research Methods in Information Systems, a set
of papers from an early IFIP 8.2 conference. His quirky
and often intellectually confrontational nature in search
of the truth probably cost him social influence and
created barriers that he otherwise would not have
encountered. He teamed up wisely, however, working
with well-selected colleagues and Ph.D. students, had
original ideas, produced quality papers and published
where people would read them. Over time, he was
increasingly cited and gained a larger audience. Finally,
in the later stages of his academic career, he was accepted
into the major journals. In the following section we
suggest how Klein’s intellectual persistence contributed
to these achievements; how he insisted on having a voice
and speaking his ‘truth’ until it was heard.
What constitutes a Kleinian research approach?
It would not be right to complete a contribution to a
special issue on Heinz Klein without a discussion of the
critical implications of these findings or to identify what
we consider to be a Kleinian approach to IS Research. We see
principal contributions arising from his embrace of the
principles in the critical social theory of Ju
¨
rgen Habermas
among others, which led to his co-development of
criteria and principles, consistent with principles of
Critical Social Theory, for the conduct of research in the
domains of interpretative research and IS development.
His recurring and most persistent contribution was, in
our view, in his introduction and espousal of Habermas’s
Figure 2 Heinz Klein’s position in the IS collaboration network (produced using Netdraw with spring-embedding layout and Klein
position highlighted).
The influence of Heinz Klein Duane Truex et al 9
European Journal of Information Systems

AUTHOR COPY
notions of Communicative Action, which we explore
more extensively in the following section.
One of his earliest contributions as a critical theorist IS
researcher was a scathing critique of the dominant
empirical positivist research methods and of the under-
lying epistemological and ontological assumptions in our
own field. The gauntlet was thrown down in a 1984
paper, ‘The Poverty of Scientism’ (1985) written with a
self-termed ‘angry young man’ (Kalle Lyytinen) in which
they uncovered, critiqued and challenged prevailing
beliefs and social practices of the extant IS research
dogma and then built arguments advocating interpreta-
tive and qualitative research in the IS field. These ideas
were subsequently developed via extended discussions
and debates in conference presentations, panels and
papers and in 1999 culminated in Klein’s most highly
cited paper (with Michael Myers): the MISQ paper titled
‘A Set of Principles for Conducting & Evaluating Inter-
pretive Field Studies in Information Systems’. This work
continued and is further manifest in Myers and Klein’s
(2011) paper ‘A Set of Principles for Conducting Critical
Research in Information Systems’ in which readers are
reminded that three elements of critical research are
‘insight, critique and transformation’ (p. 24). As a critical
social theorist particularly attracted to Ju
¨
rgen Habermas’s
Theory of Communicative Action (Habermas, 1985),
Heinz Klein sought to apply Habermas’ ideas in the
realm of IS development (Klein, 1986, 1991) and to IS
research (Lyytinen & Klein, 1985a, b; Ngwenyama &
Klein, 1994; Klein & Truex, 1996; Cecez-Kecmanovic
et al., 2008; Asif & Klein, 2009). Over a 25-year period
Klein was instrumental in shaping the discourse on what
counted as admissible forms of evidence in IS research
and profoundly changed our field.
In these streams of work – IS development, ISD
methods, and IS research – the role of speech as a
fundamental action type and as a means of uncovering
and representing contextual reality, agreements. and
shared ‘truths’ were central constructs. Moreover, in his
own behavior Heinz was personally inclined to support,
and expect, an open and fair academic discourse, what
Habermas would call an ‘ideal speech situation’ and
Mingers & Walsham (2010) term ‘deliberative democ-
racy’. Heinz was well read and a student of philosophy
(he had studied both Greek and Latin) and was especially
familiar with the work of the German continental
scholars. As a native German speaker, Klein was able to
read Habermas in the original language. Klein was thus
very familiar with the nuances of Habermas’ ideas and
the arguments of Habermas’ critics, all of which he read
in the original language. Klein was especially interested
in the debates between Ju
¨
rgen Habermas and Nicolas
Luhman about a theory of communication and action.
Klein, like Habermas saw language as the fundamental
way humans organize and coordinate and that ‘the
ability to communicate is grounded on the capacity to
understand each other’ (Mingers & Walsham, 2010,
p. 840). He believed in the power of the dialectic and
that the better argument would carry more credibility
than lesser arguments. And, in his own dealings with
students, colleagues, or intellectual opponents, he in-
sisted that all parties to a debate have fair and equal
opportunity to present arguments and views relatively
unfettered by power differentials. But Klein still reserved
the right, and may have seen it as his responsibility to
‘encourage’ speakers to reveal their underlying beliefs
and to challenge those beliefs or behaviors when he
sensed deceptive (strategic) action was in play. He used to
remind students that as critical theorists we had to ‘eat
our own dog food’ and expect that others would require
the same standards of us in challenging the validity
claims of our arguments. That is, we had the obligation to
be reflexively critical of our own ideas and beliefs. So
presenting research before Klein required being prepared
to defend any truth claim. Serious discussions with Klein
required intellectual honesty and a large measure of
personal integrity. He simply had a way to get to the crux
of an argument and surface a person’s underlying
epistemological and ontological assumptions. A discus-
sion with Klein could be an arduous exercise, but it was
almost always one in which both parties grew in under-
standing and wherein the clarity of argument improved
with the exercise. Often it leads to a furtherance of
mutual respect as well as mutual understanding. It is in
this sense of his values and his behavior that we use the
term ‘Kleinian’.
It is our view that Klein internalized and practiced the
principles required to achieve a Habermassian ideal
speech situation. Walsham & Mingers (2010, p. 840)
articulate three conditions required for ideal speech, to
which, following Klein’s own model, we add a fourth
condition:
1. All potential speakers are allowed equal participation
in a discourse.
2. Everyone is allowed to
2.1. question any claims or assertions made by anyone
2.2. introduce any assertion or claim into the dis-
course
2.3. express their own attitudes, desires, or needs.
3. No one should be prevented by internal or external,
overt or covert coercion from exercising the above
rights.
4. The participants must be truthful with each other,
seeking agreement and not deception.
When these conditions are met, in Habermassian terms,
there is the possibility of true argumentation, consensus,
and an open discourse. Consensus is not the only
presumed outcome of an open discourse, but is a goal.
One may still have disagreement or dissensus, but it will
have been reached openly and fairly in the realm of
communicative action (Wijnia, 2004). Whether consen-
sus or dissensus is the outcome, the communicative act
has left space for continued open and fair development of
the discourse at a later time.
The influence of Heinz Klein Duane Truex et al10
European Journal of Information Systems

AUTHOR COPY
A key aspect of Klein’s worldview, and of his behavior,
whether as a scholar, mentor, educator, editor, confer-
ence chair, or co-author, was his commitment to main-
taining, and establishing through force of intellect and
will something closer to an ideal speech situation.
Indeed, the social quirkiness and quixotic behavior we
alluded to earlier may be attributed to his project to
assure that all parties to a discourse had open, fair,
honest, and power-balanced opportunities to participate.
His presumption that any academic discussion would
proceed according to these values came at some political
cost to him personally. But we believe that he was true to
his carefully formulated and reflexively examined beliefs
system.
In Klein’s last published work, in the MIS Quarterly
(Myers & Klein, 2011), he and Michael Myers lay out a set
of principles for critical research which might be regarded
as a follow-on or companion to the earlier and highly
cited 1999 MIS Quarterly paper providing principles for
conducting and evaluating interpretive field studies.
Because they were aware that the 1999 paper has been
frequently (and sometimes inappropriately in their view)
used as a kind of rubric for interpretive work, in 2011
Myers and Klein are careful to caution against providing a
single set of principles for conducting critical research.
However, they also say ‘it is better to have some
principles than none at all’ (p. 18). In the 2011 paper
Myers and Klein focus on the last two of the three ‘key’
elements of critical research – ‘Insight’, ‘Critique’, and
‘Transformation’ – arguing that the 1999 paper covers the
first element sufficiently. From a study of both manu-
scripts it is plain that Klein had a clear set of insights
guiding his work and view of research as a critical
theorist. The principles enumerated and discussed in
the 1999 and 2011 papers (see Table 8) provide a clear
sense of what we would also incorporate in our view of a
Kleinian research perspective. This is particularly true
when understood in concert with Klein’s views towards
achieving, to borrow the term from Walsham and
Mingers (2010), a ‘democratic discourse’. Table 8 frames
the balance of this paper, and with our knowledge of
Heinz Klein and his published work, aids us in defining
what it means to take a ‘Kleinian perspective on information
systems research’.
We define a Kleinian Research Perspective as: a composite
attitude and behavior toward the process of scholarly
inquiry in which the researcher seeks to further commu-
nicative understanding and shared contingent truths by
exposing and critiquing distorted truth claims with the goal
of emancipating people and organizations from unwar-
ranted power abuse.
This means that as IS researchers, we cannot simply
measure, describe, and explain phenomena. In addition
Table 8 Summary research principles (Klein & Myers, 1999; Myers & Klein, 2011)
The Element of Insight
Concerned with interpretation and gaining insight.
Seven tenets of critical systems theory (CST)
articulated in Klein and Myers, 1999
(1) The Hermeneutic circle; (2) contextualization; (3) interaction between researchers
and subjects (4) abstraction and generalization; (5) dialogical reasoning; (6) multiple
interpretations, and; (7) suspicion of biases and systematic distortions.
The Element of Critique
Concerned with critique, the genealogy of knowledge and the social practices of control and reproduction. Goes beyond interpretation to
focus on power structure lying behind accepted interpretations.
Principle 1: using core concepts from critical social
theorists
Organize data collection and analysis around core concepts and ideas from one or
more critical theorists
Principle 2: taking a value position Advocate values such as open democracy, equal opportunity or discursive ethics –
drives for principles 4–6 of Insight.
Principle 3: revealing and challenging prevailing
belief and social practices
Critical researchers should identify important belief and social practices and balance
them dialectically
The Element of Transformation
Concerned with suggesting improvement to the conditions of human existence, social arrangements and social theories with theories seen as
fallible lenses through which people instigate change.
Principle 4: individual emancipation All critical theory is “yoriented towards facilitating the realization of human needs
and potential, critical self reflection and self-transformation.”
Principle 5: improvements in society Improvements in society are believed possible; hence the goal of CST research is not
just critique but propositions for overcoming unwarranted power abuse.
Principle 6: improvements in social theories All CST researchers understand that theories are fallible and improvements in theories
are possible; that there are always competing truth claims to guide analysis,
understanding and interventions.
The influence of Heinz Klein Duane Truex et al 11
European Journal of Information Systems

AUTHOR COPY
to the identification of the nature of an IS-related
phenomena, we must make an evaluation of that IS from
the standpoint of creating or impeding an ideal speech
situation, critique it and then offer proposals for
improvement in the social environment which would
lead to individual emancipation from unjust/oppressive
situations and contribute to a more ideal speech
environment and, if possible, extend theoretical devel-
opment. Such a philosophy informs not only Critical
Social Theory, but also Critical Realism (Bhaskar, 1998). A
critical IS researcher is not satisfied with a detached
understanding of the phenomena, but rather views the IS
field for what it is: an inherently social science in which
he/she is passionately and personally engaged. He/she
seeks to look with eyes steadfastly open on the phenom-
ena seeking to know it as it is. He/she then evaluates it
from the standpoint of how truth is obscured or revealed
to privilege or oppress. With that insight, he/she then
seeks to find ways to liberate individuals from structures
and ideologies that limit their knowledge of the truth,
thus helping them in achieving their potential. We
believe that this is how Heinz Klein viewed his role in
the academy. The quixotic project that informed his life
was nothing more or less than his living out this critical
approach or as he would put it ‘eating his own dog food’.
His ‘Heinzing’ of students, colleagues, and presentors was
part of his passionate pursuit of the truth. This passion is
also reflected in his willingness to take on and challenge
anyone who referred to the academic life as mere ‘game-
playing’. We can only imagine his response to Peng &
Dess’ (2010) analogy that academic life is nothing more
than a set of mental Olympic games irrelevant to real life.
Much of his work involved articulating critical theory
and how it applied to our field; a good bit of his
published work was theoretical. Yet in his work on ISD
methods and in his proposals for the renewal of doctoral
studies (Klein & Rowe, 2008) we can see his concern for
emancipatory action. In the next section we take the
‘Kleinian approach to IS research’ and use it as a lens to
examine the existing system for the evaluation of
scholarly output.
A Kleinian analysis of extant approaches to evaluating
scholarly endeavor
In conducting a program of research exploring the nature
of scholarly influence, initiated for the Klein Festscrift in
2007, we have grown to believe that (cf., principle 1 –
taking a value position)
1
the characteristics of the present
academic discourse about scholarly influence, the evalua-
tion of researchers and of journal outlets has become
systematically distorted in several important ways
(cf., principle 3 – revealing and challenging prevailing
beliefs and social practices). We articulate and support
this position through the lens of the ideal speech
situation or democratic discourse (cf., principal 1 – using
core CST concepts) and only have space in this article to
describe the arguments we have fleshed out in other
works published, in press, under review (Cuellar et al .,
2008; Truex et al., 2009; Takeda, 2011).
 First, parties do not have equal access to participation.
The gate keeping functions in the reviewing process
restrict access to those in general conformance to
dominant paradigms and research topics. For reason
of politics, resistance to change and potential loss of
power and of market failure, dominant views and
beliefs hold top billing (Easton, 2007; Segalla, 2008).
‘They [publishers] are unlikely to take risks in this
process and will mainly support new journals where
they can be shown to be conformist. This is clearly a
market where competition is at best constrained, at
worst a case of market failure. Put bluntly, what is
occurring is economic (self?) exploitation of the
academic community and possibly stagnation in terms
of the creation of new and important knowledge’
(Segalla, 2008, p. 634).
 Second, there are distinct power differences present
throughout the academic assessment and publications
process (cf., principle 3). These power distances in
creating, reviewing, editing, and evaluating publica-
tions, bias the production toward the standards and
topics of those reviewing, editing, and evaluating
publications (MacDonald & Kam, 2007; Mingers &
Walsham, 2010).
 Third, there is evidence suggesting that the ‘truthful-
ness and agreement conditions’ of an ideal discourse
are marred by the ‘gamesmanship’ described by
Macdonald & Kam (2007) and Peng & Dess (2010).
This distortion extends to the peer-reviewing process.
For instance, in the realm of peer-reviewing Mahone
(1977) determined the presence of confirmatory bias,
the tendency to emphasize and believe experiences
which support one’s views and to ignore or discredit
those which do not, wherein reviewers were strongly
biased against manuscripts which reported results
contrary to their own theoretical perspective (cf.,
Principle 3).
Space forbids a fuller development of this argumentation
here. But if the reader is willing for the sake of argument
that the discourse on the evaluation of academic
productivity might be systemically and systematically
distorted then this begs the questions: How might we
change conditions such that they lead to the possibility
for the creation of more ideal speech situations? How do
we improve the discourse for both individuals and for
our communities of research and of practice (Principles 4
and 5 – ‘individual emancipation’ and ‘improvements in
society’)?
1
We are testing our analysis, beliefs and positions against the
set of principals set forth by Klein & Myers (1999, 2011). We do
this by explicitly identifying the principle we believe is present
in our narrative.
The influence of Heinz Klein Duane Truex et al12
European Journal of Information Systems

AUTHOR COPY
Four affirmative propositions for creating a more ideal
speech situation in the discourse on evaluating
scholarly endeavor (cf., Principle 6 – improvements in
social theories)
In the spirit of Heinz Klein, we propose a set of
principles of our own to be considered by the field
(cf., Principle 5 – improvements in society ). To reiterate,
the four conditions required in an ideal speech situa-
tion are:
(1) ‘openness’ – any party to a discourse must have an
equal opportunity to start a discourse;
(2) ‘participation’ – any party may participate in a
discourse;
(3) ‘coercion and power’ – internal or external, overt or
covert coercion and differences in power between the
participants should not prevent participation; and
finally;
(4) ‘truthfulness’ – the participants must be truthful with
each other, seeking genuine agreement and not
deception.
(1) Openness. We seek to open the discourse about
alternative methods for judging scholarly output. We
advocate a movement away from an evaluation of the
venue of publication to the reception of a publication
itself by an interested and informed audience; the
scattering of many seeds on the ground to let the field
sort out the wheat from the chaff and to let many flowers
bloom (Walsham, 2005). In short, the process could
become more democratized (cf., Principle 2). Under this
proposition ‘The Wisdom of Crowds’ (Surowiecki, 2005)
is in effect the collective wisdom of the field unbounded
by limits on which publications may be admitted to the
discourse and hence be cited (cf., Principle 4). The current
‘authority-view’, focused on the venue itself, is not
democratic because it limits the discourse to those who
pass the gate keeping of journal editors. If the system is
more democratized, it would also begin to respect the
affordances of the Internet technologies now in hand
which did not exist when the current system of evalua-
tion was created. Technologies such as Google Scholar
allow for fuller and more complete searches of topics,
ideas, and authors in print broadening and changing the
nature of the discourse itself and fosters a climate
wherein more parties have the opportunity to enter the
discourse on a given topic.
The openness notion also addresses the controversy
over whether to count only academic citations vs
practitioner and popular press citations. We argue that
all forms of influence are important not just those where
academics speak to other academics. As business school
faculty whose positions exist in part to help improve
business practice (Klein & Rowe, 2008), it seems that
when our ideas are taken up by practitioners and the
popular press this should count as much as when an
academic takes up an idea. The relative importance of our
ideas is filtered out by whether they endure in the
discourse. As Cronin et al. say: ‘ y one needs at the very
least to distinguish between, on the one hand, enduring
scholarly impact, as suggested by a cumulating citation
record–and, on the other hand, Web-based measures of
“street cred” or transient group interest y a digital
equivalent of Andy Warhol’s fifteen minutes of fame y’
(Cronin & Shaw, 2002).
(2) Participation. With greater openness (as described in
point 1), equal participation in creating discourse is
enabled. To provide openness to participation in the
discourse, evaluation systems must shift from evaluation
based on venue to evaluation based on citation and
collaboration. With the use of Google Scholar and the
Hirsch family of indices, SNA and other possible exten-
sions, this becomes possible (Truex et al ., 2009; Takeda,
2011). Google Scholar and Hirsch-family statistics and
social network analysis are egalitarian; anyone can speak
because these measures and tools can include all venues,
not only those tightly ‘gate kept’ journals. Using the
Hirsch family statistics removes the elites from positions
of determining what is good and bad research leaving
that to the judgment of the field as a whole. It is more
democratic and it acknowledges current suggestions that
knowledge resides in networks of many people, not in the
few. Indeed, we may see ‘crowdsourcing’ developments
(Howe, 2008) where research problems are proposed by
industry and proposals and solutions are then offered
by members of the research community (e.g., the
InnoCentive scientific community, www2.innocentive.-
com) who may then work collaboratively to investigate
problems and research questions of relevance to business
(cf., Principle 5).
(3) Coercion and power. The movement away from
recognizing and counting only publications in selected
venues as the principle means of evaluation towards the
use of the Hirsch family of indices and SNA centrality
measures also helps level the power differences in the
evaluation process. By de-centering the venue from the
evaluation process in favor of influence measures, it
removes the power of those who would block dissident
discourse in the journal venues. It also puts the power in
the hands of the field to determine how important some
research is rather than in the hands of administrative
decision makers.
It is therefore our proposition that the evaluation of
scholarly production should not be predicated upon
publication in an exclusive and limited set of journal
venues, but rather based on a more open and egalitarian
set of measures of scholarly influence (cf., Principle 4).
Firstly, those measures should properly include measures
of productivity and published participation in the
scholarly discourse in places and ways that are mean-
ingful to scholars and others. Secondly, the set of
measures should include ways of examining the degree
to which a scholar contributes to the ‘tending of the
commons’ by working with Ph.D. students, junior
The influence of Heinz Klein Duane Truex et al 13
European Journal of Information Systems

AUTHOR COPY
scholars, as well as knowledge and reputation building
activities in the discipline. And, finally, the set should of
course consider some consideration of the merit of the
ideas and topics one is investigating. These informal
modes of influence would be expected, ultimately, to be
manifested in tangible form through collaboration and
citations. Influence, based on citation and collaboration,
removes the prejudice toward establishment and opens
the discourse to dissident and counter-cultural ideas
and arguments. We need also to consider influence not
just from the academic’s but also from the practitioner’s
point of view. This leads us to the concept of open
publication standards (Easton, 2007). As Cronin and
Shaw say:
The world of citation is the closed world of the clerisy; we
trade citation with other scholars, not with the public at
large. The world of the web, by contrast is more open and
egalitarian in character (equal opportunity invocation y)
here we are linked to, mentioned by our peers, but also, on
occasion, by practitioners yand sundry others who may
have a special or passing interest in the issues we address as
academics and/or public intellectuals. The web extends the
discursive space within which scholars operate. (Cronin &
Shaw, 2002, p. 69)
It is our vision that we pay less attention to the venue of
publication and move toward truly open publication
where the discourse is open and unfettered and
the conversation joined by any and all who have an
interest in it (Howe, 2008). We do not believe that
scholars need to be ‘vetted’ by ‘gatekeepers’ but rather
through the use of critical thinking and judgmental
rationality (Archer et al., 2004) that a true progression
toward discovery of aleithic truth can be made (cf.,
Princip le 2 ).
We are aware that our proposed notions of scholarly
influence as ideational and social and their associated
measures of citations and network centrality will be
subject to performative issues, just as journal rankings
are. Thus, if P&T decisions are to be based on citations
and network position then new ways of game-playing
will emerge as academics trade citations with others and
peripheral players court powerfully positioned players to
co-author with them (cf., Principle 6).
(5) Truthfulness. By this we mean open, transparent,
reproducible. Evaluation systems should be open and
visible to all parties. Today small groups make subjective
judgments based on criteria not known to all parties or
even to themselves. The evaluation for academic rewards
such as tenure and promotion is based on publication in
selected venues selected by surveys of people using
disparate, often contradictory thoughts whose criteria
are unknown. The movement to the use of citation
statistics creates an open, known, reproducible standard
that lets all parties to the discussion understand the
criteria. We advocate the use of the Hirsch family of
statistics and the SNA measures of collaboration for this
purpose since they are public, accessible, stable, and
reproducible (Truex et al., 2009) (cf., Principal 2). In effect
they are transparent unlike other measures, such as
journal influence factors, which, being based on a limited
set of publication venues, are unstable, are not transpar-
ent and may be amenable to manipulation (Gallivan,
2009).
Recognizing the limitations of these analyses
approaches
We note of, course, that all measures are performative
and that the consequences of adding new performance
measure are unpredictable. Once any performance
measure is adopted and recognized as having the poten-
tial to impact one’s career and paycheck, people will work
to perform to, and sometimes play games with, that
measure. So, we must again reflect critically on how our
own preferred ‘basket of measures’ approach to the
analysis of scholarly influence might be gamed or
manipulated.
Citation manipulation: there are several ways an author or
groups of authors, or journal editors and publishers
might attempt to manipulate citation counts. Journals or
editors might require or strongly ‘encourage’ authors of
submitted papers to add citations to papers in their own
journal. This has been the subject of discussion in recent
ISWorld threads but no systematic indications of the
practice have yet been uncovered. Given the transpar-
ency of the process we believe that if the practice became
widespread it would be reported and those participating
would be shamed back in line. We acknowledge that the
possibility of abuse in the short run however does exist.
Authors might attempt to manipulate citation counts by
creating direct and indirect citation ‘rings’ wherein
authors make implicit or explicit agreements to simply
cite one another’s work specifically for the purpose of
increasing citation counts. Self-citation is a legitimate
practice that might be abused if the works being cited
have no direct bearing on the paper topic at hand.
Co-authorship networks and citation counts can be
simultaneously enhanced if one were to simply add
authors to a paper even if those persons added had
nothing to do with the production of the research and
the manuscript. These possibilities for abuse having been
acknowledged, it is our opinion that these behaviors
would have little effect for several reasons. Building
meaningful counts via self-citing requires a lot of work,
for example actually getting publishing and only adds
one citation count per paper. Our own analysis and other
unpublished work suggest that self-citation does not
materially impact the H-family stats. Moreover, there are
techniques and tools that look for and exclude self-
citation from analysis. There are also pragmatic issues to
consider. These techniques are visible, bold, and risky in
that they are likely to be found out, and they require a lot
of coordination. Also clearly they represent a violation of
the fifth principle we have proposed, that of truthfulness.
The influence of Heinz Klein Duane Truex et al14
European Journal of Information Systems

AUTHOR COPY
We tend to give the academic community and academics
in general the benefit of the doubt. Given the relative
risk of damage to one’s reputation and the limited benefit
of these behaviors we doubt these behaviors will become
a major threat to the basket of measures we have
recommended. This is not to say other issues do not still
loom and that other unintended and unforeseen con-
sequences won’t ensue. One of those issues discussed in
the method discussion above remains problematic;
namely the problem of data quality. The citation counts
needed to compute the ideational and social measures
require that the researcher or the tool (such as Publish-or-
Perish) has access to reasonably accurate and ‘clean’ data.
But as we discussed earlier data sources such as Google
Scholar are assembled by reference to the bibliographies
of the many papers being indexed. If the creators of the
bibliography make an error, in author name spellings for
instance, a citation count will be diminished. We have
experienced this problem recently with our own work.
Our JAIS paper (Truex et al., 2009) has been cited
incorrectly in three recent, and relatively high profile
papers. Thus, because of these bibliographic errors, cita-
tions to our own work do not show up in a perfunctory
search of Google Scholar. This is not fatal of course,
because after a certain point the H-stats are self-correct-
ing. Once the h of h cites is achieved one more or one
fewer citation adds or detracts very little. The techniques
we favor adhere to our first principle, that of openness or
transparency, and data quality errors are quickly and
readily apparent to the attentive researcher and can be
corrected, albeit with some effort.
Finally, there is one other concern we should note
about the whole notion of citation counts. That is what
do citations actually mean or connote? This is a point raised
implicitly by Hansen et al. (2006) in a paper in which
they examine how one of the field’s better known works,
Markus’ 1983 Communications of the ACM ‘Power, Politics
and MIS Implementation’ (Markus, 1983) was used in
seven different streams of IS research over a 22-year
period. Hansen et al. show that citations serve different
functions and may be ‘enrolled’ to serve different ends.
Of course one never knows the purpose of the citation
simply counting mentions when tabulating bibliogra-
phies. Takeda (2011) reminds us that, within any paper,
citations can be used as positive or as negative evidence
of a point, a warrant to a claim made in a paper, a homage
to important figures in a field, or to important papers on
a topic, or simply as a defensive reference to avoid the
admonition of reviewers. Our own position has been,
that in the calculation of the notion of scholarly influence
any of these reasons are an indication that a work and/or
a scholar has received recognition in the mind of a writer
such that she/he feels obliged to make reference to the
work. Of course we would hold for the standard set forth
in the debate by Karl Weick (1995) and by Sutton & Staw
(1995) on how to properly (ethically) use citations. Our
more charitable spirit trusts that an honorable scholar
does not knowingly misuse a citation. And we hold that
the process of apprenticeship typical of Ph.D. training
and that of mentoring, senior to junior scholar, will
reinforce the appropriate standard of citation use.
Conclusion
In this paper we explore a set of constructs leading to a
description of a notion we call scholarly influence. We
examined the influence of Heinz Klein in the academic
community and demonstrated that in terms of ideational
influence he is the equivalent to many well-known and
highly regarded scholars. In terms of social influence,he
collaborated with many very highly respected scholars
and is central to the social network of the IS field. In the
network of IS scholars, he was in the most central 12% of
the 448 scholars on the Clark et al. (2009) list. We then
defined the notion of a Kleinian research perspective.
We noted that Klein was open and allowed different
discourses. He never constrained his students to topic or
theory. He listened, admitted, and then challenged other
positions. From his earliest work Klein posed uncomfor-
table questions, challenged the status quo, and, in pursuit
of a fair and more ideal communicative environment,
contested taken-for-granted assumptions to better test
the mettle of an argument – and sometimes the person
making it.
Our deliberations lead us to believe that none of the
extant dominant approaches toward assessing the quality
of a scholar’s output are sufficient to the task. We
therefore argue that by using the concept of ‘influence’,
the uptake of ideas by the field, those needing to evaluate
scholarly output can measure its perceived quality. This
yields an evaluation by the entire field (and this can
include industry and practitioners) and not just by a
handful of scholars.
This research is therefore aimed at identifying and
developing a composite (multi-dimensional) set of mea-
sures allowing a transparent, fair, replicable, and compar-
able indication of scholars’ influence. To date we have
identified two classes of measures those we call ideational
influence measures, that represent a scholar’s productivity
of published works and the uptake of those works by the
community of scholars and social influence measures,
representing the extent that a researcher participates in
academic collaborations that lead to the production
of citable research artifacts. Using citations contributes
to the democratization of research and using social
network position promotes research collaboration. How-
ever, the measures are not independent: the ‘quality’ of a
research artifact can be assessed in terms of the number of
citations and of the networks of the co-authors. Taken
together these measures are thus closer to the ideal
communicative act proposed by Ju
¨
rgen Habermas (1985,
1987) and the practices of our friend and mentor, Heinz
Klein. Further, we believe these measures are useful
because they can be calculated automatically using data
publicly available through the Internet (e.g., Harzing
.com’s ‘publish or perish’). There are currently issues
about data completeness, data quality, and the unique
The influence of Heinz Klein Duane Truex et al 15
European Journal of Information Systems

AUTHOR COPY
identification of authors but, given time, these will be
resolved.
We flatter ourselves and think that Heinz might have
liked to read our proposals, particularly since they arise
directly from a consideration of the role he has played in
shaping a discourse in our own field and in raising in us a
set of questions and a scholarly ‘itch’ leading us to
develop a whole research program built around a critical
examination of the construct of scholarly influence. We
also recognize that the ‘Kleinian’ project is bigger than
the concerns that have occupied our present interests and
that Heinz would likely have challenged our own core
assumptions, the quality of our narrative, and probably
our understanding of Habermas’ theory. He would not,
however, endeavor to silence our inquiries. Thus we
dedicate them to his memory.
Acknowledgements
The authors would like to thank and recognize Lynette
Kvasny for h er comme nts, encouragement and pointers to
literature addressing power imbalances and distorted
communication in gender and race in the academic
discourse and to Michael Gallivan for his critical insights
that continue to help fuel this whole research program. We
would also like to acknowledge the people who were able
to reallocate time in their extraordinarily busy s chedules
to travel, some over great distance, to Atlanta, 18–19
May 2007 and p articipate in the workshop and festschrift
event titled ‘Beyond Singer – Kleinian Inquiry into the IS
Discipline’ on very short notice. In a real sense each of
these persons helped shape this paper. Those attend ees
were: Zaheer Asif, Jayailak a Bandul a, Raymond Bar nes,
Andrew Basden, Richard Baskerville, Richard Boland , Lisa
Caldwell, Kevin Crowston, Michael Cuellar, Uld arico ‘Rex’
Dumdum,DelvinGrant,NikHassan,MargarathaHen-
drickx, Rudy Hirschheim, Heinz Klein, Munir Mandviwalla,
Lars Mathiassen, Eph McLean, Ojelanki Ngwenyama, Hans
Oppelland, Owen Plowman, Gabriel Ramirez, Dan Robey,
Hiro Takeda, Duane Truex III, John Venable , and Richard
Welke.
About the authors
Duane Truex researches how emergent language proper-
ties influence ISD methods, information systems and
enterprise architectures. He also studies enterprise
information systems implementation and is currently
co-principal investigator examining ERP post-implemen-
tation governance and integration issues in six countries.
Recent publications explore the nature of scholarly
influence, as both ideational and social constructs, in
academic communities. Truex is active in the IFIP
working groups 8.2 and 8.6 research communities and
has been a general chair, program chair, track chair or
doctoral consortia co-chair of several major international
conferences including the ICIS 2008-Paris. He is a
member of GSU’s CIS faculty and has professional
research affiliations with the Mittuniversitetet (Sweden)
and the University of Nantes (France).
Michael J. Cuellar is an Assistant Professor of Compu-
ter Information Systems at North Carolina Central
University. His research focuses on the areas of project
management, outsourcing and social theory for Infor-
mation Systems. He has substantial experience in
industry having held management positions for EDS
and American Software managing software product
development and infrastructure services, as well as
systems management sales. He has published papers in
the Journal of the Association for I nformation Systems,
the European Journal of Operational Research,andthe
e-Ser vices Journal,aswellastheICIS,AMCIS,andthe
International Research Workshop on Project Manage-
ment conferences. He is on the boards of the Journal for
Information Systems Education, the Southern Association
for Information Systems and the AIS Project Manage-
ment SIG.
Hirotoshi Takeda is an Adjunct Professor of Computer
Information Systems at North Carolina Central Univer-
sity. He has seven years of industry experience in
telecommunications, semiconductor manufacturing,
and IT consulting. He completed his Ph.D. in Computer
Information Systems at Georgia State University and is
finishing a Ph.D. in Management from the University of
Paris Dauphine. His research interests include discourse
analysis, mobile computing, bibliometrics, virtual com-
munities, and knowledge management. His research has
appeared in the Journal of the Association for Information
Systems, Information Systems Educators Journal as well as
the proceedings of the ICIS, AMCIS, SAIS, UKAIS,
ICECON, and IFIP WG 8.2.
Richard Vidgen is Professor of Information Systems in
the School of Information Systems, Technology and
Management in the Australian School of Business at the
University of New South Wales, Australia. Following
15 years working in the IT industry he studied for a
Ph.D. in Information Systems. He has produced two
books on IS development and many research papers,
including journals such as Information Systems Research,
Information & Management, the Information Systems
Journal, and the European Journal of Information Systems.
His current research interests include the complex
adaptive systems theory and agile teams, high perfor-
mance workplaces, and social network analysis studies of
knowledge-production networks.
The influence of Heinz Klein Duane Truex et al16
European Journal of Information Systems

AUTHOR COPY
References
ARCHER M, COLLIER A and PORPORA DV (2004) Transcendence: Critical
Realism and God. Routledge, London.
A
SIF ZandKLEIN HK (2009) Open and free deliberation: a prerequisite
for positive design. [doi: DOI: 10.1016/j.infoandorg.2009.04.003].
Information and Organization 19(3), 186–197.
A
VISON DandPRES-HEJE J (Eds) (2005) Research in Information Systems:
A Handbook for Research Supervisors and their Students. Elsevier
Butterworth Heinemann, London.
B
HASKAR R (1997) A Realist Theory of Science, 2nd edn, Vol. 9, Verso,
London.
B
HASKAR R (1998) Facts and values: theory and practice. In Critical Realism
Essential Readings (A
RCHER M, BHASKAR R, COLLIER A, LAWSON TandNORRIE
A, Eds), pp 409–443, Routledge, London.
C
ECEZ-KECMANOVIC D, KLEIN HK and BROOKE C (2008) Exploring the
critical agenda in inform ation systems research. Information Systems
Journal 18(2), 123–135.
C
HUA C, CAO L, COUSINS KandSTRAUB D (2002) Measuring researcher-
production in information systems. Journal of the Association of
Information Systems 3, 145–215.
C
LARK JG, WARREN JandAU YA (2009) Assessing researcher publication
productivity in leading information systems journals: a 2003–2007
update. Communications of the Association for Information Systems
24(14), 225–254.
C
RONIN BandSHAW D (2002) Banking (on) different forms of symbolic
capital. Journal of the American Society of Information science and
Technology 53(14), 1267–1270.
C
UELLAR MJ, TAKEDA HandTRUEX DP (2008) The Hirsch family of
bibliometric indices as an improved measure of IS academic journal
impact. In 14th America’s Conference on Information Systems,
(P
ARSONS JandYUAN Y, Eds), pp 1–10, Association for information
Systems, Toronto, Ontario Canada.
E
ASTON G (2007) Liberating the markets for journal publications:
some specific options. Journal of Management Studies 44(4),
628–639.
E
GGHE L (2006) Theory and practice of the g-index. Scientometrics 69(1),
131–152.
F
REEMAN LC (1979) Centrality in social networks: 1. conceptual
clarification. Social Networks 1, 215–239.
G
ALLIVAN MJ (2009) Unpacking the journal “Impact Factor” and its effect
on IS research: does it do more harm than good? In Proceedings of the
America’s Conference on Information System s (K
ENDALL K and VARSHNEY U,
Eds), paper #55., Association for Information Systems, San Francisco,
CA.
H
ABERMAS J (1985) The Theory of Communicative Action: Reason and the
Rationalization of Society, Vol. 1, Beacon Press, Boston MA.
H
ABERMAS J (1987) The Theory of Communicative Action: Lifeworld and System:
A Critique of Functionalist Reason, Vol. 2, Beacon Press, Boston MA.
H
ANSEN S, LYYTINEN KandMARKUS ML (2006) The legacy of “power and
politics” in disciplinary discourse: a citation analysis. In ICIS 2006
Proceedings, pp 407–424, paper 28, AIS, Milwaukee, WI.
H
IRSCH JE (2005) An index to quantify an individual’s scientific research
output. Proceedings of the National Academy of Sciences of the United
States of Am erica 102(46), 16569–16572.
H
OWE J (2008) Crowdsourcing: How the Power of the Crowd is Driving the
Future of Business. Random House, New York.
K
LEIN HK (1986) The critical social theory perspective of information
systems development. In Proceedings of the 18th Annual Meeting of the
Decision Sciences Institute-MIS Researcher’s Workshop (J
ENKINS AM, Ed.),
pp 375–377, Decision Sciences Institue, Honolulu, Hawaii.
K
LEIN HK (1991) Conceptual advances in information systems develop-
ment: the critical social theory paradigm. Paper presented at the 14th
IRIS (Information systems Research seminar In Scandinavia), orga nized
by the University of Umea.
K
LEIN HK and LYYTINEN K (1985a) The critical theory of jurgen Habermas
as a basis for a theory of information systems. In Research Methods
in Information Systems (M
UMFORD E, HIRSCHHEIM R, FITZGERALD Gand
W
OOD-HARPER AT, Eds), pp 219–236, Elsevier, Amsterdam.
K
LEIN HK and LYYTINEN K (1985b) The poverty of scientism in information
systems. In Research Methods in Information Systems (M
UMFORD E,
H
IRSCHHEIM R, FITZGERALD GandWOOD-HARPER T, Eds), pp 131–161,
Elsevier Science Publishers, Amsterdam.
K
LEIN HK and MYERS MD (1999) A set of principles for conducting and
evaluating interpretive field studies in information systems. MIS
Quarterly 23(1), 67–93.
K
LEIN HK and ROWE F (2008) Marshalling the professional experience of
doctoral students: a contribution to the practical relevance debate.
MIS Quarterly 32(4), 675–686.
K
LEIN HK and TRUEX DP (199 6) Discourse analysis: an approach to
the investigation of organizational emergence. In Signs of Work,
Semiosis and Information Processing in Organisations (H
OLMQVIST B,
A
NDERSEN PB, KLEIN HandPOSNER R Eds), pp 227–268, W alter de
Gruyter, Berlin.
L
ATOUR B (1987) Science in Action.HarvardUniversityPress, Cambridge, MA.
L
AVE JandWENGER E (1991) Situated Learning: Legitimate Peripheral
Participation. Cambridge University Press, Cambridge.
L
OCKE JandLOWE A (2002) Problematising the construction of journal
quality: an engagement with the mainstream. Accounting Forum
26(1), 45–71.
L
OTKA AJ (1926) The frequency distribution of scientific productivity. The
Journal of the Washington Academy of Sciences 16, 317–323.
L
YYTINEN K and KLEIN HK (1985a) Critical social theory as a basis for the
theory of information systems. In Research Methods in Information
Systems (M
UMFORD E, HIRSHHEIM R, FITZGERALD GandWOOD-HARPER AT,
Eds), pp 219–236, North-Holland, Amsterdam.
L
YYTINEN KandKLEIN HK (1985 b) The critical theory of Ju
¨
rgen Habermas
as a basis for a theory of informat ion systems. In Research Methods in
Information Systems (M
UMFORD E, HIRSCHHEIM R, FITZGERALD G and
W
OOD-HARPER AT, Eds), pp 219–236, Elsevier Science Publishers, BV,
Amsterdam.
M
ACDONALD SandKAM J (2007) Ring a ring o’ roses: quality journals and
gamesmanship in management studies. Journal of Management Studies
44(4), 640–655.
M
AHONE MJ (1977) Publication prejudices: an experimental study of
confirmatory bias in the peer review system. Cognitive Therapy and
Research 1(1), 161–175.
M
ARKUS ML (1983) Power, politics and mis implementation. Commu-
nications of the ACM 26(6), 430–444.
M
INGERS JandWALSHAM G (2010) Toward ethical information
systems: the contribution of discourse ethics. MIS Quarterly 34(4),
833–854.
M
YERS MandKLEIN HK (2011) A set of principles for conducting critical
research in information systems. MIS Quarterly 35(1), 17–36.
N
GWENYAMA O and KLEIN H (1994) An exploration of expertise of
knowledge workers: towards a definition of the Universe of Discourse
for knowledge acquisition. Information Systems Journal (formerly Journal
of Information Systems, Blackwell Scientific 4(2), 129–140.
N
ONAKA I, TOYAMA RandKONNO N (2000) SECI, Ba and leadership: a
unified model of dynamic knowledge creation. Long Range Planning
33, 5–34.
P
ENG MW and DESS GG (2010) In the spirit of scholarship. Academy of
Management Learning and Education 9(2), 282–298.
P
INCH TJ and BIJKER WE (1984) The social construction of facts and artefacts:
or how the sociology of science and the sociology of technology might
benefit each other. Social Studies of Science 14, 399–441.
P
ODSAKOFF PM, MACKENZIE SB, BACHRACH DG and PODSAKOFF NP (2005)
The influence of management journals in the 1980s and 1990s.
Strategic Management Journal 26, 473–488.
S
EELY BROWN JandDUGUID P (2001) Knowledge and organization: a
social-practice perspective. Organization Science 12(2), 198–213.
S
EGALLA M (2008) Publishing in the right place or publishing the right
thing: journal targeting and citations’ strategies for promotion and
tenure committ ees. European Journal of International Management
2(2), 122–127.
S
ERENKO A and BONTIS N (2009) A citation-based ranking of the business
ethics scholarly journals. International Journal of Business Governance
and Ethics 4(4), 390–399.
S
ERENKO AandBONTIS N (2011) What’s familiar is excellent: the impact of
exposure effect on perceived journal quality. Journal of Informetrics 5,
219–223.
S
IDIROPOULOS A, KATSAROS D and MANOLOPOULOS Y (2006) Generalized
h-index for disclosing latent facts in citation networks. Scientometrics
72(2), 253–280.
The influence of Heinz Klein Duane Truex et al 17
European Journal of Information Systems

AUTHOR COPY
SINGH G, HADDAD KM and CHOW CW (2007) Are articles in “top”
management journals necessarily of higher quality. Journal of Manage-
ment Inquiry 16(4), 319–331.
S
TEWART P (1964) Concurring opinion in Jacobellis vs. Oregon, 378
C.F.R. y 378.
S
UROWIECKI J (2005) The Wisdom of Crowds, Vol. ppbk, Random House,
New York.
S
UTTON RandSTAW B (1995) What theory is not. Administrative Science
Quarterly 40, 371–384.
T
AKEDA AH (2011) Examining scholarly influence: a study in Hirsch
metrics and social network analysis. Unpublished Ph.D, George State
University, Atlanta.
T
AKEDA H, TRUEX DandCUELLAR M (2010) Evaluating scholarly influence
through social network analysis: the next step in evaluating scholarly
influence. In AMCIS 2010 Proceedings (L
EIDNER DandELAM J, Eds),
pp 1–12, paper 573, Association for Information Systems Lima, Peru.
T
RUEX III DP, CUELLAR MJ and TAKEDA H (2009) Assessing
scholarly influence: Using th e Hirsch indices to reframe the
discourse. Journal of the Association of Information Systems 10(7),
560–594.
V
IDGEN R, HENNEBERG SandNAUDE P (2007) What sort of community
is the European Conferenc e on information systems? A soc ial
network analysis 1993–2005. Euro pean Jo urnal of Inform ation Systems
16, 5–19.
W
ALSHAM G (2005) Agency theory: integration of a thousand flowers.
Scandinavian Journal of Information Systems 17(1), 153–158.
W
ALSTROM KA, HARDGRAVE BC and WILSON RL (1995) Forums for
management information systems scholars. Communications of the
ACM 38(3), 93–107.
W
ASSERMAN SandFAUST K (1994) Social Network Analysis: Methods and
Applications, 1st edn, Cambridge University Press, Cambridge.
W
EICK KE (1995) What theory is not, theorizing is. Administrative Science
Quarterly 40(3), 385–390.
W
IJNIA E (2004) This is why we need discourse according to Habermas.
[WWW document] http://elmine.wijnia.com/weblog/archives/cat_
habermas.html.
The influence of Heinz Klein Duane Truex et al18
European Journal of Information Systems