Types and levels of collaboration in interdisciplinary research in the sciences

Types and Levels of Collaboration in InterdisciplinaryResearch in the Sciences

Jian Qin*School of Library and Information Science, University of Southern Mississippi, Southern Station Box 5146,Hattiesburg, MS 39406. E-mail: [email protected]

F. W. LancasterGraduate School of Library and Information Science, University of Illinois at Urbana-Champaign,501 E. Daniel St., Champaign, IL 61820. E-mail: [email protected]

Bryce AllenSchool of Library and Informational Science, University of Missouri-Columbia, 104 Stewart Hall-UMC,Columbia, MO 65211. E-mail: [email protected]

It is common today for scientists to conduct research in 20th century, significant research on this phenomenoncollaboration with their colleagues from different institu- did not begin until the 1950s. Researchers in sociology,tions and disciplines. This study collected a sample of psychology, and the history of science have initiated in-846 scientific research papers published in 1992 and

vestigations into how IDR in science is organized (Barm-tested three hypotheses on the relationship between re-ark & Wallen, 1980, 1986; Birnbaum, 1981; Caudill &search collaboration and interdisciplinarity. Collabora-

tion was measured by the number of authors, number of Roberts, 1951; Robertson, 1983), how scientists behaveinstitutional affiliations, number of affiliation disciplines, in interdisciplinary collaboration (Crane, 1976; Crow,and type of collaboration. Interdisciplinarity was mea- Levine, & Nager, 1992; Luszki, 1958; Meechan, 1978),sured by the number of disciplines represented in the

and how such activities could be facilitated through betterjournals cited. The results showed significant differ-management (King, 1964). Information scientists beganences in degrees of interdisciplinarity among different

levels of collaboration and among different disciplines. to investigate this area about two decades ago. AlthoughSome disciplines were shown to be highly collaborative, the literature on this topic is still somewhat sparse, re-while others were not. This analysis led to the conclusion search has been conducted by information scientists onthat collaboration contributed significantly to the degree

how scientists used information in interdisciplinary re-of interdisciplinarity in some disciplines and not in oth-search (Choi, 1988; Chubin, Porter, & Rossini, 1984;ers. In addition to an analysis of publications, this investi-Clark & Kinyon, 1989), the extent to which the interdisci-gation used a survey that asked authors about their

forms of collaboration, channels of communication, and plinarity has influenced the use of information (Hurd,use of information. The survey provided some qualitative 1992; McCain, & Bobick, 1981), and the implicationsexplanation for the bibliometric findings. Findings are IDR has for information systems and services (Allen,discussed from the perspective of scientist-scientist in-

1980). Research on such matters has practical signifi-teraction, scientist-information interaction, and informa-cance for the design of information systems and servicestion-information interaction.to support IDR.

IDR is an imprecise concept and difficult to define.INTRODUCTIONVaried definitions can be found in works by Lowell H.

While interdisciplinary research (IDR) has been com-Hattery (1986), Michael Anbar (1986), Frederick A.

mon practice in the scientific community since the early Rossini et al. (1981), and others. IDR has the followingcharacteristics as generalized by numerous writers (Al-

* To whom all correspondence should be addressed. pert, 1969; Birnbaum 1981; Blackwell, 1955; Caudill &Roberts, 1951; Luszki, 1958): (1) different bodies of

Received June 13, 1996; revised September 19, 1996; accepted Septem-knowledge are represented in the research group, (2)ber 19, 1996.group members use different approaches in attempting tosolve problems, (3) members of the group perform differ-q 1997 John Wiley & Sons, Inc.

JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE. 48(10) :893–916, 1997 CCC 0002-8231/97/100893-24

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FIG. 1. Scientific research environment.

ent roles in solving problems, (4) members of the group ciological, psychological, and historical perspectives. Inthe context of information science, interdisciplinarity canwork on a common problem, (5) there is a group responsi-

bility for the final product, (6) the group shares common be identified through three possible levels of interaction:scientist-scientist, scientist-information, and information-facilities, (7) the nature of the problem determines the

selection of group personnel, and (8) members are influ- information. Scientist-scientist interaction is implied bycollaborative authorship. Though there is a debate overenced by how others perform their tasks.

For the purpose of the present study, IDR is defined the extent to which the multi-authorship reflects collabo-ration in research, it generally has been considered asas the integration of disciplines within a research environ-

ment. The integration, implied in the several definitions an unobtrusive indicator of collaboration (Gordon, 1980;Meadows, 1974; Paisley, 1990). Another bibliometricmentioned above, consists of interactions among individ-

ual scientists, between individual scientists and their orga- measure—citations in research papers—has been usedvery frequently to study scientist-information or informa-nizations, and among different disciplines involved in the

research. All these interactions are motivated by a com- tion-information interactions. When scientists cite sourcesoutside their own disciplines, some level of interdisciplin-mon problem-solving purpose. Nilles (1975) called it:

‘‘the joint, coordinated, and continuously integrated re- arity is implied in this scientist-information interaction.At a more macrolevel, an interdisciplinary relationship issearch done by experts from different disciplinary back-

grounds, working together and producing joint reports, implied where journals in one field make frequent refer-ence to journals in other fields (information-informationpapers, recommendations, . . . so tightly interwoven that

the specific contribution of each researcher tends to be interaction). Carried to its logical conclusion, interdisci-plinary information-information interaction implies theobscured by the joint product.’’

As this definition of IDR implies, the integration of integration of information from two or more disciplines,as in a single paper drawing upon the literature of severaldisciplines involves various forms of interactions within

a research environment. This research environment, in its disciplines. But little study has been done to answer suchquestions as: To what extent do scientists interact withbroadest sense, is nature and society (Figure 1). In the

research cycle implied by the unidirectional arrows, scien- information in different disciplines? Do these interactionsdiffer among the levels of collaboration and among scien-tists interact together with their organizations and the re-

sources to tackle problems raised from the social and tific disciplines? What factors affect the interactions be-tween scientists and information and how do they affectnatural environment. This interaction, in turn, generates

products or solutions—new knowledge and/or informa- them? With all the changes brought about by informationtechnology, there is a need to renew our understandingtion, new research questions, an awareness of a lack of

information—for the research cycle to begin a new pro- of scholarly communication in science and rethink theinformation systems that can better facilitate the interac-cess or continue to complete the process. At the same

time, as the problems themselves are addressed, new tions in IDR.This project was primarily a bibliometric study of in-questions, problems or lack of information may be re-

vealed. Thus the interactions occur not only externally— terdisciplinary collaboration, i.e., scientist-scientist, sci-entist-information, and information-information interac-between the research cycle and the surrounding environ-

ment—but also internally among scientists, scientists and tion. A scientific research article enables us to study inter-disciplinary collaboration for the reasons that (1) itorganizations, and scientists and resources. To study IDR

in such a complicated environment, researchers from dif- represents a part or complete process of problem-solvingresearch; (2) if it is coauthored, it would entail interac-ferent disciplines have undertaken investigations from so-

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tions between individual scientists and their institutions; base with several other databases in studying corporateaddresses and found that the SCI database has more com-(3) the references cited in the paper reflect the informa-

tion environment in which the research was carried out; plete information on affiliations and addresses than otherdatabases. Besides, this database has the unique featureand (4) if the paper cited several different disciplines,

they should have been integrated into the wholeness of of including the publications cited in a paper. It offers arelatively complete data source for the present study.the end-product—the single article or articles. Birnbaum

(1983) has said that IDR is ‘‘a unified whole’’ that results The database contains 527,541 journal articles pub-lished in 1992. According to Cohen (1987), the necessaryfrom the integration of different disciplines. Thus, a pub-

lished article based on interdisciplinary collaboration sample size should be ¢764 for a multiple regressionanalysis to achieve high power of analysis and effect size.should be a unified whole describing research that repre-

sents the integration of two or more disciplines. Allowing for repetition, records without references, andother circumstances, the sample size was expanded fromThe number of disciplines represented by the journals

cited in scientific papers was used in this project as the 764 to 1,000. Thus 1,000 unique journal articles wererandomly selected from the 527,541 journal article re-dependent variable to measure the degree of interdisci-

plinarity of a paper. The independent variables investi- cords in the SCI database for 1992. Papers without refer-ences and four papers that had an exceptionally high num-gated included the number of authors, the number of their

departmental affiliations, the number of subject areas rep- ber of authors (ú15) were eliminated, reducing the num-ber of usable records from 1,000 to 846. The reason forresented by the departmental affiliations, and the type

of collaboration. The number of authors is the obvious excluding the papers with an exceptionally high numberof authors was that these papers, though very few in themeasure of the level of collaboration and has been used

in many studies, but the other two variables have been sample, could seriously distort the data and thus affectthe accuracy of analysis.used only rarely. These measures reflect collaboration at

individual (number of authors) , organizational (numberof affiliations) , and disciplinary (subject areas of depart- Coding of dependent variables. Choosing the num-

ber of disciplines of journals cited as the measure formental affiliations) levels. Another variable—type of col-laboration—reflects the scale and degree of collaboration interdisciplinarity was based on the rationale that (1) the

journal articles cited are usually those relevant to thethrough combining both individual and organizationalmeasures. Thus, collaboration can occur within a single citing papers, although many factors such as political

(Lancaster, et al., 1986), social (Abdullah and Lancaster,department, among departments within an institution,among two or more institutions in a single country, or at 1991), and academic importance could affect what scien-

tists cite; (2) a paper often reflects a smaller segment ofan international level. These four independent variablesreflect the characteristics of collaboration at various levels one or more subject areas than a journal does. In other

words, the subject areas or disciplines of journals usuallyand enable us to examine the association between collabo-ration and interdisciplinarity from the interaction perspec- represent higher levels in the knowledge hierarchy than

research articles do. Obviously, the lower the level a papertive.This research consisted of two parts. The first, a biblio- represents in the knowledge hierarchy, the more difficult

it becomes for us to categorize the paper. To avoid suchmetric analysis, focused on the differences in the degreeof interdisciplinarity among levels of collaboration and problems as inconsistency and inaccuracy in categorizing

journal articles, one practical and effective solution wouldamong scientific disciplines. The second component ofthe research was a survey of 50 scientists, whose research be to raise the level of the hierarchy, i.e., from journal

articles to the journals themselves. Although some infor-articles were included in the bibliometric sample, togather data to enhance the bibliometric findings. In this mation may be lost by this aggregation, the disciplines

represented by the journals cited seems a plausible mea-paper, the terms collaboration, muti-authorship, and sci-entist-scientist interaction are used interchangeably to re- sure to use in a project studying interdisciplinary collabo-

ration in science in general. The major advantage, offer to the joint production of a research paper by twoor more scientists. Collaboration was considered to be course, is the fact that subject coverage of the journal

level can be established by means external to the investi-‘‘interdisciplinary’’ when the departmental affiliations ofthe authors reflected the involvement of different source gation (e.g., how the journals are classified by libraries,

directories, or databases) whereas classification of thedisciplines.article level would have to be done by the investigatorsthemselves, a time-consuming and subjective process.

MethodologyTwo steps were followed for coding the dependent

variable: record the unique journal titles for each SCIBibliometric Study

record selected and search the titles against the CD-ROMversion of Ulrich’s International Periodicals DirectoryThe data were collected from all the papers published

in 1992 covered by the Science Citation Index (SCI) (Ulrich’s) to obtain subject category information forthese journals. Because this classification applies only todatabase. Bruin and Moed (1993) compared the SCI data-

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TABLE 1. Distribution of the 846 papers by percent of citations to journals.

Percent of citations No. of Percent of Cumulative no. Cumulativeto journals papers papers of papers percent

1–10 1 0.1 1 0.111–20 2 0.2 3 0.321–30 5 0.6 8 0.931–40 20 2.4 28 3.341–50 31 3.7 59 7.051–60 0 0 59 7.061–70 90 10.6 149 17.671–80 102 12.1 251 29.781–90 185 21.9 436 51.591–100 410 48.5 846 100.0

sions under the same broader discipline. For exam-journal titles, and for reasons of consistency in classifica-ple, physiology, microbiology, and zoology, all falltion, all items other than journal articles were excludedunder biology. If all three were represented in thefrom the study. The frequency distribution of citations injournals cited, three disciplines would be recognized.the pretest and the whole data set confirmed that this

(2) All the terms were at the secondary level but be-exclusion would not be a serious limitation since the ma-longed to at least two different broader disciplines.

jority of the citations were to journal articles (Table 1). For example, if physiology, genetics (both under bi-A significant problem in categorization was how to ology), and endocrinology (medical sciences) were

treat comprehensive journals such as Nature and Science. represented, three disciplines would be recognized.The decision was made to exclude the general science (3) Some terms were at the primary level and some atjournals from the categorization, although comprehensive the secondary. For example, physiology, chemistry,

and pharmacy and pharmacology (a division of thejournals dealing with a single discipline such as Lancetmedical sciences) also led to the recognition of threeand Annals of Chemistry were retained. Nevertheless, thedisciplines.number of citations to general science journals was re-

corded for each article. In all 846 records, 550 (65%)It could be argued that the third situation could havemade no reference to the general science journals, 154

involved more extensive and complicated interdisciplin-(18.2%) cited one or two articles from general scienceary work than the other two did and thus should get ajournals, and 80 (9.5%) cited three to five. The remainingdifferent score. However, the present study deals only5% cited six or more general science journals. Of course,with the quantitative aspects of interdisciplinary collabo-this problem would have been avoided if journal articlesration and not with qualitative differences in levels ofwere used as a dependent variable. But for reasons dis-collaboration. The scoring scheme used in this study re-cussed, this was considered impractical. The very smallflects how many different disciplines were involved, pre-number of citations that were made to sources outside thesuming that any research involving two or more disci-sciences were coded but ignored in the analysis.plines implies interdisciplinary interactions regardless ofThe rules for categorizing the journals cited by thethe level of such interactions in the scientific knowledgepapers included in this sample were set as follows: (1)hierarchy. At a practical level, two journals were consid-Only the Ulrich’s subject categories were used to countered to belong to different ‘‘disciplines’’ if Ulrich’s clas-the number of disciplines represented in the journals cited;sified them differently, whether or not these categories(2) If the journals cited in a particular article led to thefall into the same broad field of study. Thus, it couldassignment of an Ulrich’s classification at both primarybe said that we adopted a rather generous measure ofand secondary (general and specific) levels, only the moreinterdisciplinarity based on subdisciplines rather than thespecific (secondary) level was used; (3) The first levelmuch smaller number of broad disciplines reflected, for(general) term was used if no second-level (specific)example, in the major ‘‘disciplinary’’ databases.terms under this first level term were present among the

It should be noted that there exist large differencesother journal citations in the article; and (4) The numberamong scientific disciplines in degrees of formality andof unique subject terms derived from the above proce-organization, scope of a discipline, and degrees of receptiv-dures was used as the dependent variable, i.e., the numberity and growth patterns (Klein, 1990). An obvious exampleof unique subject terms represents the number of disci-is the difference in the number of subdivisions in mathe-plines cited in a paper.matics and in the medical sciences. While mathematicsThe above scoring scheme resulted in three possiblehas only one subdivision in the Ulrich’s, medical sciencessituations:branch out intoú30 subdivisions. This means that a mathe-matics paper is interdisciplinary only if it cited disciplines(1) All the unique subject terms were second level divi-


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other than mathematics, but a medical paper could easily in departmental affiliations indicates the interdisciplinaryenvironment of the collaborative research.become interdisciplinary within medicine itself. Because

the present study focused on the quantitative perspective of The types of collaboration in this study were defined asthe ways in which the collaboration was organized, whichscientist-information interactions, the coding method was

designed specifically to serve this purpose, i.e., study how could be easily obtained through the affiliation informationin the SCI’s records. The types were coded as:extensive such interactions were when presuming all the

other conditions constant. This presumption implied that,regardless of how far a research paper might have gone (1) 0, no collaboration;

(2) 1, collaboration in a department;from the level of the scientific knowledge hierarchy defined(3) 2, collaboration between two or more departmentsin this research, any unique disciplines (i.e., defined by

within an institution;Ulrich’s secondary subject categories) reflected in a pa-(4) 3, collaboration between two or more institutionsper’s citations would be considered as interdisciplinary in-

within a country; andteractions. Of course, the depth and intensity of interdisci-(5) 4, international collaboration.

plinary interactions might differ among levels of the scien-tific knowledge hierarchy. To study this, other measures

What should be made clear here is that, though typeand coding methods must be used.of collaboration was coded with numbers, this does notreflect quantities or a rank ordering of the categories toCoding of independent variables. Four independentwhich they were assigned. By using appropriate codingvariables were involved in this research: the number ofsuch as dummy coding when doing multiple regressionauthors, the number of institutional/departmental affilia-analysis, this categorical variable could be incorporatedtions, the number of disciplines reflected in departmentaleasily into multiple regression models with other continu-affiliations, and type of collaboration. The coding of theous variables (Pedhazur, 1982).number of authors was straightforward and simple. But the

coding of an author’s affiliation required greater care. Thenames of departments may not always reflect the exact Surveydiscipline (e.g., Beckman Institute, Interdisciplinary Lab,

Bibliometric studies are unobtrusive, and the measuresT. J. Watson Research Center). When this occurred, theare stable and easy to obtain. But they are post hoc indepartments were looked up in directories, such as Organi-nature and emphasize the end product of the research.zations Master Index (Gale Research, 1987), to identifyBibliometric data cannot tell what the relationships be-their disciplinary areas. If the sources consulted did nottween collaborators are, what factors have affected theprovide the subject area information but the name stronglyinitiation and ongoing process of collaborative research,suggested an interdisciplinary organization, the score forhow scientists communicated information, to what extentthe number of affiliation disciplines would be one. Anyscientists regard their collaborative research as interdisci-department that could not be identified as to subject wasplinary, and so on. To complement the bibliometric study,considered as a missing case. That is, disciplinary affiliationa questionnaire survey was designed to collect data on:had to be omitted for a very small number of authors al-

though it might be present for the paper as a whole in the(1) Forms of collaboration—The questions asked incase of collaborative authorship. As for those individual

this section focused on exploring what types of orga-authors having more than one affiliation, actual number ofnizations were involved in the research, how fre-affiliations and disciplinary areas were recorded.quently these types of collaboration occurred, what

To be consistent with the subject categories in the factors were important for determining whether ordependent variable, the scoring for departmental affilia- not and with whom scientists would collaborate, andtions followed the same rules as for the dependent vari- which kinds of working relationships would lead toable. For a collaborative paper, if the authors’ departments coauthorship in a research paper.shared the same discipline—for example, Department of (2) Means of communication—This section tried to

tackle scientific communication through three differ-Geology of two or more universities—they would beent approaches: first via various communication me-counted as only one discipline, even though they might bedia such as e-mail, telephone, fax, paper correspon-situated in different locations. Of course, some inaccuracydence, and personal visit; second, via mobilizationmight occur in this classification, because the name of aamong disciplines through visiting research anddepartment does not necessarily conform exactly with theteaching activities; and finally via informal conversa-author’s specialization and two departments bearing thetion. Of course, there are no absolute boundaries

same subject title may have different emphases in that among these three approaches. Informal conversa-discipline. There is no obvious solution to this particular tion, for instance, can be carried out over the phoneproblem. These two variables perform different functions or e-mail, as well as face-to-face.from the institutional perspective: the number of affilia- (3) Use of information—This section was designed totions reflects the extent to which different organizations obtain some insights relating to the citation data.

When scientists cite different disciplines in theirare involved, and the number of disciplines as reflected


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FIG. 2. Distribution of cumulative percent of papers by number of authors, author affilitations, and disciplines of author affiliations.

work, how did they discover the interdisciplinary were the most common, accounting for Ç68% of allinformation? Which information seeking tech- types. International collaboration occurred in Ç13% ofnique(s) has been used most frequently? For what the cases. Interdepartmental collaboration within an insti-purposes did they use interdisciplinary information? tution was the least developed type (Figure 3). These

results indicate that, on the basis of author affiliations atThese questions were designed to collect information least, much of the collaborative research represented in

needed to elucidate certain findings of the bibliometric the sample was performed by scientists in the same sub-data but for which unobtrusive measures could not be ject field—i.e., not crossing departmental boundaries.applied. Fifty first authors were selected from the sample Most of the papers (86%) had between 1 and 40 cita-papers that were categorized as collaborative research pa- tions (Figure 4). About 12% of papers cited 41–70pers. Because the purpose of the survey was to understand works, and very few cited ú71. The number of disciplinesinterdisciplinary collaboration, the selection of the 50 pa- represented in the journals cited (Figure 5) revealed thatpers only included those having cited two or more disci- most of the papers (91%) cited journals in more than oneplines. The questionnaires, with a cover letter, were dis- discipline. In those papers that cited journals from moretributed on October 1, 1994, and 24 of them were returned than one discipline, 87% covered two to six differentby November 20, 1994. disciplines, while 13% ranged from 7–13 disciplines.

Findings: Bibliometric Data Test of Hypotheses

Hypothesis 1: When measured by number of disciplinesGeneral Descriptionrepresented by the journals cited, significant differences

In the sample, only 14% of the papers were written by exist in the degree of interdisciplinarity of research paperssingle authors. More than 79% involved between two and among the several levels and types of collaborative au-six authors. The percent of papers became fractional afterthe number of authors exceeded eight. Figure 2 showsthat half of the papers were produced by authors from asingle departmental affiliation, whether they were single-authored or coauthored. The other half involved 2–11departmental affiliations either within or among the insti-tutions. Exactly two-thirds of the papers were producedby authors from departments in the same disciplines.Among the other one-third of papers, collaboration tookplace primarily between departments in two different dis-ciplines. Beyond two disciplines, the proportion of thepapers became fractional ( less than 9% altogether) .

In terms of the organizational scope of collaboration,FIG. 3. Percent of papers by type of collaboration.intradepartmental and interinstitutional collaborations


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FIG. 4. Frequency distribution of the number of citations.

thorship. ‘‘Levels’’ refers to the number of authors, num- creased and the percent of papers by five and more authorsber of institutional affiliations, and number of disciplines increased. The intermediate percentages for papers havingrepresented by the affiliations. ‘‘Types’’ are intra-institu- two, three, and four authors did not vary much.tional collaboration, interinstitutional collaboration, and The above data supported the hypothesis that the de-international collaboration. gree of interdisciplinarity differed at different levels of

collaboration. A one-way analysis of variance showedInterdisciplinary collaboration at individual level. that the average number of disciplines cited was signifi-

When comparing the authorship data with the number of cantly different between the papers having single authorsdisciplines of the journals cited, a strong tendency toward and those with multiple authors (P õ 0.05, except forinterdisciplinarity was apparent in both solo and collabo- the four author paper group; see Table 2). However, therative research (Figure 6). Only 22% of the single-au- lowest average (3.2 disciplines per single author paper)thored papers cited journals in a single discipline. In the only suggests least interdisciplinarity, rather than nonin-case of collaborative papers (a total of 724), 93.4% (676 terdisciplinarity.papers) cited more than one discipline compared with the77.9 for single author papers. Another phenomenon worth Interdisciplinary collaboration at organizational level.

At any given degree of interdisciplinarity, the distributionnoticing in the data is that, as the number of disciplinesincreased, the percent of papers by single authors de- of the percent of papers concentrated at one or two depart-

FIG. 5. Frequency distribution of the number of disciplines represented in the journals cited.


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FIG. 6. Comparison of solo and collaborative research in interdisciplinarity.

mental affiliations (Figure 7). There was not much differ- As discussed earlier, single departmental affiliation papersremained a high proportion at each level of interdisciplin-ence in the number (1–4) of disciplines cited for those

papers by authors from one affiliation and the proportions arity. This pattern reappeared when the affiliation datawere further categorized by the number of disciplinesof papers written by authors from two or more departmen-

tal affiliations fluctuated over different numbers of disci- reflected in them, which indicates that collaboration oc-curred most frequently not only in one or two departmen-plines, showing no regularity in the distribution pattern.

This suggests a weak relationship between the number of tal affiliations but also among departments within thesame disciplines or subject areas. However, the data indepartmental affiliations and the number of disciplines

cited, which was supported by the analysis of variance Table 4 indicate that there did exist significant differencesin the degree of interdisciplinarity among the papers by(Table 3). Thus this variable was not an important factor

and did not provide very useful information for explaining scientists from one or two disciplines and those from fouror more disciplines.the dependent variable.

When authors were from single discipline in terms ofInterdisciplinary collaboration across organizationsthe subject title of their department(s) , the number of

and countries. For all the collaborative papers, the per-papers declined as the degree of interdisciplinarity, ascentage of papers for each type of collaboration did notmeasured by number of disciplines cited, increased. Ondiffer much in terms of the degree of interdisciplinarity.the other hand, the opposite occurred for the papers byA careful study of the data showed that the largest per-authors from multidisciplines: the number of papers in-centages of papers fell in the groups involving two tocreased as the extent of interdisciplinarity increased (Fig-four disciplines within a department and four or five disci-ure 8). These different distribution patterns suggest thatplines for interinstitutional collaboration. The interna-having authors from different disciplines might have sig-tional collaboration data fluctuated over the whole spec-nificantly contributed to the degree of interdisciplinarity.trum of interdisciplinarity. These distributions imply that,generally speaking, as collaboration involved more orga-

TABLE 2. Comparisons for the mean number of disciplines of thenizations and countries, the degree of interdisciplinarityjournals cited at different levels of authorship.became higher (Figure 9). The analysis of variance (Ta-

No. of authors ble 5) shows that the mean number of disciplines citedMean no. of Standard No. of differed significantly between noncollaborative and col-

disciplines cited deviation authors 1 2 3 4 5 6 7 & up laborative research, but not between different levels ofcollaboration.3.1967 2.0835 1

The hypothesis that significant differences exist in the3.8950 2.1795 2 **4.0802 2.0418 3 ** degree of interdisciplinarity among different levels of col-3.9098 1.7899 4 laboration was supported for all the variables except for4.4432 1.8561 5 ** the number of affiliations. But large variations occurred4.3393 2.1173 6 **

in the analysis of variance. The variance of the dependent4.5741 1.8490 7 & up **variable accounted for by each independent variable was

** P õ 0.05. only a small portion (õ5%) of the total, which suggested


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FIG. 7. Distribution of percent of papers by the number of affiliations and the number of disciplines cited.

that the collaboration variables explained little in all the each of the eight disciplines showed several different pat-terns: biology and medical sciences papers were approxi-factors affecting interdisciplinarity. Even though the sta-

tistical test was significant for different levels of collabo- mately normally distributed, the peak locating at five dis-ciplines; those in chemistry, earth sciences, engineering,ration, the large variations within each group need to be

explored in greater depth to discover what factors have and physics were skewed to the left, with two or threebeing the distribution peaks; and mathematics papersnot been included in this research but have stronger im-

pact on interdisciplinarity. clearly were related negatively to the dependent variable,i.e., as the number of disciplines cited increased, the per-

Hypothesis 2: Significant differences exist among differ- cent of papers decreased. Agriculture had too many miss-ent scientific disciplines in terms of degree of interdisci- ing points along the scale—thus the percentage fluctuatedplinarity. and showed no clear distribution pattern (Figure 10). The

average numbers of disciplines cited ranged from 1.8 inThe above analysis for the four collaboration variables mathematics to 5.2 in agriculture. Compared with the

indicates that the degree of interdisciplinarity differed as grand mean of 4.0, only agriculture, biology, and medicalthe number of collaborators varied. The second hypothe- sciences cited above-average numbers of disciplines; allsis tested to what extent the degree of interdisciplinarity the other disciplines were below average (Table 7). Thevaried among individual disciplines in science. To allow differences in the degree of interdisciplinarity followedsuch analysis, all the 846 records were categorized into the grouping of the distribution patterns in Figure 10;eight disciplines according to the Journal Subject Cate- That is, the differences were significant only between thegory information provided in the SCI. The frequency groups having different distribution patterns. It is verydistribution of papers for each discipline is shown in Ta- clear that agriculture, biology, and the medical sciencesble 6. were in the same group in terms of interdisciplinarity,

Papers in biology and medical sciences comprised while chemistry, earth sciences, engineering, and physicsabout half of the total. Those in chemistry, engineering, fell in a second group. Mathematics stood on its own.and physics accounted for more than a third of the total.A frequency distribution of the dependent variable for Hypothesis 3: There is significant positive association

between collaboration and interdisciplinarity. Specifi-cally, the more authors, the higher the degree of interdis-TABLE 3. Comparisons for the mean number of disciplines of theciplinarity.journals cited at different organizational levels.

No. of affiliations Correlation between interdisciplinarity and collabora-Mean no. of Standard No. of

tion. The last hypothesis involved testing the associationdisciplines cited deviation affiliations 1 2 3 4 5 & morebetween the four collaboration (independent) variables

3.7453 1.9967 1 and the interdisciplinarity (dependent) variable, among4.1008 2.1991 2 which the number of authors was hypothesized to have4.2136 1.6666 3 contributed the most to the variability in interdisciplinar-4.7209 2.2182 4 **

ity. Table 8 includes correlation coefficients for the de-4.2500 1.9744 5 & morependent variable and all the independent variables except

** P õ 0.05. type of collaboration because of its categorical character-


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FIG. 8. Distribution of number of papers by number of affiliation disciplines and numbers of journal disciplines.

istic. Another variable, the number of citations, was also Å 0.015 and alpha-to-remove Å 0.015 in the multipleregression procedure. Only the number of authors and theincluded in the correlation matrix. All the correlation co-

efficients can be divided into three blocks: collaboration number of affiliation disciplines satisfied the criteria (Põ 0.05). Although the number of disciplines of author(X1–X3), citation (X4–X5), and the correlation be-

tween the variables in these two blocks. Within the collab- affiliations accounted for the largest proportion of thevariance in the degree of interdisciplinarity and the testoration block, the correlation between the number of de-

partmental affiliations and the number of disciplines of was significant, the two independent variables in themodel explained only a very small portion (i.e., Ç4%)departmental affiliations was the strongest (0.737). But

the number of authors did not seem to be so closely of the factors influencing interdisciplinarity.Due to the small portion of the variance accounted forcorrelated with the number of affiliations or the number

of affiliation disciplines. The strength of correlation was by the independent variables, a lack of fit test was addedto the SAS multiple regression procedure to test the valid-about the same in the citation block. The correlation be-

tween the variables in two blocks, however, was quite ity of the model. According to Ostle and Malone (1988),if the F ratio for a lack of fit test is larger than the tabulateddifferent from that in either block: all of the coefficients

were õ0.2, resulting in even smaller R 2 values. F value, i.e., the test is significant and the regressionmodel would inadequately describe the data. Table 9 re-The high correlation in the collaboration block showed

that there was a high multicollinearity between these four ports the SAS printout for the lack of fit test. The meansquares for lack of fit and the pure error did not differvariables, which implied a redundancy of information

provided by the collaboration variables. To select the in- significantly (F Å 1.04 with df Å 767 and 73, P ú 0.05).This conformed with the result of the quadratic test; thatdependent variables that accounted for most influence on

the dependent variable, a multiple regression analysis was is, the linear regression model was the true model andthus there was no need for a higher-order polynomialconducted to decide which independent variable(s)

should be included in the model. A SAS program was model in describing this set of data. Ostle and Malonealso point out that the test for lack of fit provides only theexecuted to run a stepwise selection with alpha-to-enter

TABLE 4. Comparisons for the mean number of disciplines of the journals cited at disciplinary levels.

No. of affiliation disciplinesMean no. of Standard No. of

disciplines cited deviation affiliation disciplines 1 2 3 4 & up

3.7478 2.0259 14.2963 1.8493 2 **4.3544 1.9570 35.6316 2.6710 4 & up ** **

** P õ 0.05.


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FIG. 9. Distribution of percent of papers by type of collaboration and the number of disciplines cited.

may have significantly degraded the strength of theinformation on whether or not a higher degree polynomialassociation between dependent and independent vari-should be used or a different model (but unspecified)ables. These extreme situations, presumably not theinvolving the same variables should be investigated. Thisnorm in IDR collaboration, need to be filtered fromtest does not tell whether some other independent vari-the sample and statistical analysis performed againables should have been measured.for those cases within the ‘‘norm’’ range; and

While the model for describing the relationship be- (3) The qualitative factors that were not reflected in thetween the dependent variable and the independent vari- measurements used (the factors determining collabo-ables appeared valid, it is difficult to draw a meaningful rative work, reasons for using interdisciplinary infor-interpretation for such a small variance accounted for by mation, and nature of the research).the independent variables. To deal with this problem andfind out what was weakening the association between The first two factors were taken into account in thecollaboration and interdisciplinarity, three factors were following analysis, while the third was examined in theconsidered: questionnaire survey.

(1) Variation among disciplines in science (because the Multiple regression analysis by discipline. In exam-multiple regression analysis used the sample from ining the first factor, the collaboration variables were re-the SCI database and examined it as a whole in sci- gressed on the number of disciplines cited for each ofence, it did not differentiate among disciplines in the eight disciplines (of the citing papers) . A multipleterms of the response of independent variables to the

regression analysis (stepwise selection) revealed thatdependent variable—such responses may be sig-

none of the collaboration variables significantly correlatednificant in some disciplines but not in others) ;with the dependent variable in agriculture, biology, chem-(2) Those cases having large numbers of collaboratorsistry, earth sciences, engineering, and physics. Thoughbut small numbers of disciplines cited, or vice versa,the F test was significant for mathematics and medical

TABLE 5. Comparisons for the mean number of disciplines of the TABLE 6. Number of papers by the discipline of the journal in whichjournals cited by type of collaboration. the paper was published.

Type of collaboration Discipline No. of papers PercentMean no. of Standard Type of

disciplines cited deviation collaboration 0 1 2 3 4 Agriculture 17 2.0Biology 186 22.0

3.1967 2.0835 0 Chemistry 109 12.93.9327 1.9459 1 ** Earth Sciences 60 7.14.4667 1.8166 2 ** Engineering 82 9.74.3255 2.0639 3 ** Mathematics 32 3.83.9286 2.0955 4 ** Medical Sciences 248 29.3

Physics 112 13.2** P õ 0.05.


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FIG. 10. Frequency distribution of the number of disciplines represented in the journals cited: by the discipline of the journals in which the paperwas published.

sciences, the collaboration variables that had been se- Based on the descriptive information of the sample, thecriteria for deciding an extreme case were set as follows:lected into the model were different. In mathematics, the

number of authors accounted for Ç30% of the variancein the number of disciplines of the journals cited (P õ

(1) A paper is in the category of highly collaborative0.05), but in medical sciences, the number of disciplinesbut slightly interdisciplinary if the number of authorsof author affiliations explained only a trace of the varianceis equal to or greater than five AND if the number(R 2 Å 0.02) in the dependent variable, though it wasof disciplines cited is equal to or less than two (which

statistically significant (P õ 0.05). is half of the grand mean number of disciplinesAnother source for the large error term in the model cited); and

might have come from the extreme cases in the sample. (2) A paper is in the category of highly interdisciplinaryTwo extremes—highly collaborative but slightly interdisci- individuals if the paper has a single author AND theplinary and highly interdisciplinary individuals—were number of disciplines cited is equal to or greater than

five (which is above the average).pulled out and examined separately from the norm cases.


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FIG. 10. (Continued)

A Kolmogorov-Smirnov test for normality showed ical sciences, the variables that were included in the modelhad changed: the number of authors in mathematics wasthat, even though the extreme cases were extracted from

the sample, the descriptive statistics remained essentially replaced by the number of affiliations, and in medicalsciences, the number of affiliation disciplines wasthe same (Table 10). Using the same SAS procedure, a

multiple regression analysis was reperformed for the new changed into the number of authors and type of collabora-tion.set of data (i.e., after the extremes were eliminated).

As shown in Table 11, the overall performance of the The multiple regression analysis based on the wholedata set suggests that the number of authors and the num-independent variables in explaining the relationship be-

tween dependent and independent variables was im- ber of affiliation disciplines were the collaboration vari-ables most closely associated with interdisciplinarity. But,proved. Compared with the data set before extreme cases

were drawn, the number of authors remained as the most when looking at the eight disciplines separately, largedifferences existed not only in the relationship betweenimportant variable in both models, and the second inde-

pendent variable has been replaced by type of collabora- collaboration and interdisciplinarity (some were signifi-cant while some were not) , but also in the order of impor-tion. The variance explained by collaboration variables

had increased from 125.35 to 318.76. The R 2 also in- tance of the collaboration variables (the number of au-thors was significant in mathematics while it was not increased to 0.1007, compared with 0.0355 before.

There were also improvements in the association when medical sciences; no collaboration variable was signifi-cant in other disciplines) . In testing the other two hypoth-multiple-regressing by discipline (Table 12). Not only

did the association become stronger, but also the test was eses, varied relationships were found between collabora-tion and interdisciplinarity in the sciences as a whole assignificant in more disciplines than was true before the

data were filtered. The number of authors was a significant well as in individual disciplines. We also have noticed thelarge portion of unexplained error term in the statisticalpredictor for interdisciplinarity in chemistry, engineering,

mathematics, and medical sciences. In earth sciences, all analysis. Through filtering extreme cases from the dataset, which preserved the integrity of the original data,four collaboration variables met the criterion (Põ 0.15),

and were selected into the model. While the test for the main indices for regression analysis have been greatlyimproved, and collaboration variables that closely associ-filtered data was still significant for mathematics and med-

TABLE 7. Comparisons of the average number of disciplines cited by the discipline of the journal in which the paper was published.

Mean no. of disciplines cited Discipline of the citing journal A B C EA EN MA M P

5.1765 (2.4040) Agriculture (A)4.8280 (1.8432) Biology (B)3.6147 (1.8654) Chemistry (C) ** **3.9000 (2.1839) Earth Sciences (EA) **3.1098 (1.6851) Engineering (EN) ** **1.7813 (1.0697) Mathematics (MA) ** ** ** ** **4.4879 (2.0559) Medical Sciences (M) ** ** ** **2.8739 (1.5194) Physics (P) ** ** ** **

Figures in brackets are standard deviations; ** P õ 0.05.


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TABLE 8. Correlation coefficients between variables.

Variable X1 X2 X3 X4 X5

No. of Authors (X1) 1.0000.0

No. of Affiliations (X2) 0.535 1.0000.0001 0.0

No. of Disciplines 0.461 0.737 1.000of Affiliations (X3) 0.0001 0.0001 0.0

No. of Citations (X4) 0.082 0.113 0.121 1.0000.0001 0.0001 0.0001 0.0

No. of Disciplines of the Journals Cited (X5) 0.161 0.115 0.161 0.489 1.0000.0001 0.0008 0.0001 0.0001 0.0

The first row in each cell is correlation coefficient and the second row the probability that thecoefficient equals to zero.

ated with interdisciplinarity were identified. To further Japan, and Norway; 14 (58.3%) were from academicinstitutions, 5 (20.8%) from corporate research depart-explore the findings in bibliometric data, the qualitative

data obtained from the questionnaire survey were used. ments, 3 (12.5%) from government organizations, and 2(8.3%) from hospitals. Most published within their owndiscipline. Some papers had more authors than the num-

Findings: Survey Databer of disciplines cited, and the reverse was true for oth-ers. A close study of the subject areas of the respondents,The concerns arising from the hypotheses discussed

earlier are related in the following questions: (1) When collaborators, citing journals, and cited journals foundthat most authors collaborated with others in their owna paper is the result of collaborative work, how did collab-

oration occur? In other words, what factors have led to or related subject areas, although the journals that werecited fell into many different disciplines. It should becollaboration and what types of working relationship have

resulted in coauthorship? (2) How did the means, content, noted that there was some delay between when the projectwas conducted and when this survey was carried out;and nature of communication affect collaborative re-

search? (3) How was the information located and used thus respondents might not remember well the detailsthat occurred during the process. Although specific papersin interdisciplinary collaborative research? (4) To what

extent do scientists consider their research interdisci- were mentioned in the cover letter, the questionnaire actu-ally addressed the respondent’s research behavior in gen-plinary?eral rather than focused exclusively on research for thispaper alone. The analysis for the survey data was limited

Profiles of Respondentsto descriptive summary only due to many zero cells.

To answer these questions, a questionnaire with 10questions was designed and distributed to 50 scientists

Forms of Collaborationwhose collaborative research was included in the biblio-metric sample. Twenty-four questionnaires were col- Questions in this section deal with what types of orga-

nizations were involved in collaborative research, whatlected. Of these, 17 came from respondents in the U.S.and 7 in Australia, Belgium, Canada, France, Hong Kong, factors determined the initiation of collaboration, what

TABLE 9. Analysis of variance for test of lack of fit.

Source of Sum of Meanvariation df squares square R2 F Ratio Prob ú F

Linear 2 125.35 62.67 0.0355 15.61 0.0001Quadratic 2 11.13 5.57 0.0031 1.39 0.2506Crossproduct 1 24.38 24.38 0.0069 6.07 0.0139Total Regress 5 160.87 32.17 0.0455 8.01 0.0001Residual 840 3373.51 4.02

Lack of Fit 767 3090.34 4.03 1.04 0.4325Pure Error 73 283.17 3.88

Total 845 3534.38


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TABLE 10. Descriptive statistics and Kolmogorov-Smirnov Good- cial resources available for research were another im-ness of Fit test. portant factor determining whether or not to collaborate

with other researchers. Only a very few people (8.7%)Before extreme After extreme

seemed not to be concerned with financial constraints. Itcases extracted cases extractedis worth noticing that, though the sponsors or funding(n Å 846) (n Å 787)agencies did not have important impact on most of the

Mean 3.9740 3.9733 research projects (59.1%), they did more or less affectStandard Deviation 2.0452 2.0065 the collaboration. Other factors such as expertise required,25th Percentile 2.0000 2.0000

belonging to the same research group, and track record50th Percentile 4.0000 4.0000were mentioned by three other respondents.75th Percentile 5.0000 5.0000

K-S Z 4.4243 4.2431 The answers to Question 3 formed two interesting ex-Two-tailed P 0.0001 0.0001 tremes: students as technical assistants fell at the lower

end (62.5%) and consultants from other subject areas atthe upper end (54.2%). The data here suggest that stu-dents worked as technical assistants because they had the

was the relationship between collaborators, and which training required to perform the technical operations fortypes of relationship were likely to result in coauthorship. the project. But consulting for a project involved the ex-Among the respondents to the first question (see Appen- pertise that might not be available among the colleaguesdix) , Ç96% answered that their research partners were in the same department and subject area. Based on thevery likely from academic institutions; 46% of respon- relationships presented here, we can consider the catego-dents chose government organizations as potential collab- ries ‘‘Student’’ and ‘‘Colleagues in the Same Depart-orators, while 41% thought it unlikely for them to collabo- ment’’ as intradepartmental collaboration. The propor-rate with government organizations. There was a big gap tions of intradepartmental collaboration, whether thein collaboration between the industrial sector and aca- collaborators played the role of technical assistant or co-demic and government organizations. Only 23% of re- investigator, were higher than all the other categories.spondents answered that it was likely for them to collabo- Another interesting phenomenon is that most co-inves-rate with the industrial sector. The majority (59%) main- tigators came from the same subject areas, either in thetained that collaborating with the industrial sector was same department or another institution. The consultantsunlikely. One respondent mentioned that collaborators were more likely to be the colleagues in other institutionsalso could come from professional bodies/societies. A and subject areas. The large percentage demonstrates thefurther examination of the data found that researchers prevalence of interdisciplinary research collaborationfrom different sectors followed different collaboration from two ways: as complex research problems burgeoned,patterns. For example, among 14 respondents from acade- it became impossible for a single discipline or professionmia, all of them were positive for collaborating with col- to possess all of the requisite information/skills to effec-leagues in academic organizations. Only 5 out of 14 said tively solve the problems—with the increasing complex-that they would collaborate with government agencies, ity in science, interdisciplinary collaboration was quicklyand fewer responded that they would choose collaborators becoming the rule rather than the exception (Benowitz,from the industrial sector. Government agencies tended 1995); and traditional departmental structures in acade-to collaborate more frequently with academic institutions mia were established for administrative and curricularthan with the industrial sector, but less frequently among purposes, including peer review, tenure, and promotion.themselves. They were and still are the roadblocks to interdisciplinary

All the respondents agreed that the subject or topic research collaboration. When cross-departmental or -in-of the research played an important role in determining stitutional collaboration was restricted by these traditionalwhether they would collaborate with other researchers or structures, hiring consultants from other disciplines couldnot. Many respondents (78%) considered personal ac- have enabled the researchers to go around these road-

blocks.quaintance with potential collaborators important. Finan-

TABLE 11. Result of multiple regression analysis by stepwise selection for the data set having eliminated the extreme cases.

Sum of MeanSource of variation df squares square R2 F ratio Prob ú F

ModelNumber of Authors 1 277.38 277.38 0.0877 75.42 0.0001Type of Collaboration 2 318.76 159.38 0.1007 43.91 0.0001

Residual 784 2845.68 3.63Total 786 3164.44


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TABLE 12. Multiple regression analysis by discipline: after the extreme cases were excluded (including only the disciplines where P õ 0.05 forthe test).

Source of variation df Sum of squares Mean square R2 F ratio Prob ú F

ChemistryNo. of Authors 1 16.28 16.28 0.0496 5.07 0.0266Residual 97 311.74 3.21Total 98 328.02

Earth SciencesNo. of Authors 1 23.75 23.75 0.1064 6.07 0.0171No. of Affiliations 2 46.38 23.19 0.2078 6.56 0.0030Type of Collaboration 3 60.11 20.04 0.2694 6.02 0.0014No. of Affili. Disciplines 4 70.15 17.54 0.3143 5.50 0.0010Residual 48 153.06 3.19Total 52 223.17

EngineeringNo. of Authors 1 17.38 17.38 0.0945 7.62 0.0073Residual 73 166.57 2.28Total 74 183.95

MathematicsNo. of Affiliations 1 12.41 12.41 0.3499 16.14 0.0004Residual 30 23.06 0.77Total 31 35.47

Medical SciencesNo. of Authors 1 27.46 27.46 0.0303 7.18 0.0079Type of Collaboration 2 35.43 17.71 0.0391 4.66 0.0104Residual 230 879.16 3.82Total 231 906.62

Thus, it was not surprising that 55% of consultants did content, and nature of communication in interdisciplinarynot become coauthors of research papers, because, under collaboration.this situation, they served primarily as a mechanism for Regarding communication means, telephone, fax, andobtaining the requisite expertise rather than working as personal visit were rated effective by 83% of the respon-team members. In contrast, co-investigators and technical dents, though one respondent said that personal visitsassistants were more likely to appear as coauthors (100 did not often happen. Here ‘‘personal visit’’ means thatand 52%, respectively) . Relating the responses above to traveling from one site to another is involved. Telephonethe bibliometric analysis, it was found that within-depart- and personal visits are two means that can be highlymental collaboration occurred more frequently than all interactive. Fax also can be considered as written corre-the other forms because of the fact that researchers knew spondence. The only difference is that fax is quicker. Ineach other better and had mutual interest among them- scientific communication, time is often a concern, andselves (Garvey and Gottfredson, 1977). The low percent- nontextual communication occurs all the time (Olsen,age of consultants being coauthors also explained to some Beattie, Brinkehoff, & Santucci, 1990). Fax was favoredextent why collaboration variables had less than satisfac- by most of respondents possibly due to its ability to trans-tory performance in predicting interdisciplinarity: a sub- mit text, graphics, and images instantly. E-mail, however,stantive portion of the interdisciplinary source—consul- as a relatively new medium, was considered effective bytants from other disciplines—was not included in the only 71% of respondents. Though studies have found thatcollaboration variables at all. Whether this inclusion e-mail increases the speed and effectiveness of communi-would have made a significant difference is a question cation, people sometimes do not like its ‘‘depersonal-for future studies.

ized’’ side (Crawford, 1982; Foster & Flynn, 1984).Compared with telephone and personal visits, e-mail canbe considered less personal and interactive. Written corre-

Channels of Communicationspondence was rated as an effective method by half of therespondents. One respondent included conference calls asCollaborative research can be affected by many fac-an effective communication means.tors. From the information science perspective, effective

The purpose of one question was to explain a findingcommunication plays a vital role in a successful collabo-in the bibliometric data: some single authors had tworative work, and particularly when such collaboration in-affiliations and most of them were highly interdisciplinaryvolves researchers from different locations and disci-

plines. In this section, the questions focus on the means, individuals. It is possible that the mobility of a scientist


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TABLE 13. Responses to survey questions (see Appendix).

Number of respondents (%)

1. Collaboration partner Likely Neutral Unlikely Total

Academic institutions 22 (95.7) 1 (4.3) — 23The industrial sector 5 (22.7) 4 (18.2) 13 (59.1) 22Government organizations 10 (45.5) 3 (13.6) 9 (40.9) 22Other 2 (66.7) — 1 (33.3) 3


2. Factors in determining collaboration Important Neutral Unimportant Total

The topic of the research 21 (100.0) — — 21The sponsor or funding agency 5 (22.7) 4 (18.2) 13 (59.1) 22Financial resources available 17 (73.9) 4 (17.4) 2 (8.7) 23Personal acquaintance with potential

collaborators 18 (78.3) 4 (17.4) 1 (4.3) 23Other 3 (100.0) — — 3

Colleagues in the Colleagues in the Colleagues insame department same discipline but in other disciplines

3. Relationships among coauthors Students (%) (%) other institutions (%) (%)

Technical Assistant 15 (62.5) 7 (29.2) 4 (16.7) —Co-investigator 3 (12.5) 20 (83.3) 14 (58.3) 6 (25.0)Consultant 1 (4.2) 5 (20.8) 13 (54.2) 13 (54.2)


4. Relationships likely leading to coauthorship Likely Neutral Unlikely Total

Technical assistant 12 (52.2) 7 (30.4) 4 (17.4) 23Co-investigator 24 (100.0) — — 24Consultant 5 (22.7) 5 (22.7) 12 (54.5) 22

Number of respondents (%)5. Communication means that makes collaboration

particularly effective Effective Neutral Ineffective Total

E-mail 15 (71.4) 5 (23.8) 1 (4.8) 21Telephone 20 (83.3) 4 (16.7) — 24Written correspondence 12 (50.0) 7 (29.2) 5 (20.8) 24Fax 20 (83.3) 3 (12.5) 1 (4.2) 24Personal Visit 20 (83.3) 4 (16.7) — 24Others 1 (100.0) — — 1

could have nurtured interdisciplinary collaboration. In this either research or teaching¢30–40 times in another insti-tution in both his own area and a related area. Participat-question, ‘‘taught’’ included visiting teaching, giving

seminars, workshops, and other education-oriented activi- ing in research in a totally different subject area seemedto be more difficult than any of the above two types.ties that took place in institutions other than the author’s

own. More than 80% of respondents had researched or Three respondents did once, two did twice, and none didthree or more times. No matter what factors could havetaught at other institutions at least once in the areas of

their own specialties over the past 5-year period. Most of been involved in blocking the mobility of scientists, it isclear here that mobility among disciplines (and/or educa-them did so three or more times. But mobility to other

subject areas was much smaller: 21% did once, 10% tional sites) can be significant channel to communicateinterdisciplinary information and develop interdisciplin-twice, and 21% three or more times. Nearly half of the

respondents had never had experience in doing research ary collaboration.The survey found that most of the respondents usedor teaching in another institution in a different but related

subject area. Nonetheless, exceptions occurred. One re- and/or favored interactive communication over noninter-active communication. When addressing a question re-spondent noted on the questionnaire that he had done


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TABLE 13. (continued)


Three or6. Interdisciplinary mobility Once Twice more Never Total

In the same subject field 1 (4.5) 6 (27.3) 11 (50.0) 4 (18.2) 22In a related subject field 4 (21.1) 2 (10.5) 4 (21.1) 9 (47.4) 19In a subject field unrelated to

one’s own but that of acollaborating colleague 3 (17.6) 2 (11.8) — 12 (70.6) 17


7. Communication partner Frequently Neutral Infrequently Total

Team members 22 (95.7) — 1 (4.3) 23The discussion groups of similar interest

in computer networks 3 (15.8) — 16 (84.2) 19Colleagues not in the team but in the

department 10 (47.6) 9 (42.9) 2 (9.5) 21Colleagues not in the team and outside

the department 10 (45.5) 8 (36.4) 4 (18.2) 22


8. Information seeking Frequently Neutral Infrequently Total

Through collaborators from other disciplines 17 (73.9) 1 (4.3) 5 (21.7) 23By searching databases 15 (62.5) 5 (20.8) 4 (16.7) 24By following up on citations in the articles

read 18 (75.0) 5 (20.8) 1 (4.2) 24By scanning journals in other fields 12 (52.2) 2 (8.7) 9 (39.1) 23Others 2 (100.0) — — 2


9. Use of interdisciplinary information Agree Neutral Disagree Total

Provide methodology 15 (68.2) 2 (9.1) 6 (27.3) 23Identify new research questions 15 (65.2) 6 (26.1) 2 (8.7) 23Provide theoretical support for research 17 (68.0) 5 (20.0) 2 (8.3) 24Others 2 (100.0) — — 2

10. Proportion of IDR Collaboration Number of Respondents (%)

Almost all Projects 7 (29.2)Most of the Projects 6 (25.0)Half of the Projects 6 (25.0)Few of the Projects 5 (20.8)None —Total 24

garding the subject content of the project, almost all the seemed to be used less than might be expected: only16 percent of respondents answered that they frequentlyrespondents said that team members were the main com-

munication party. Here ‘‘addressing a question’’ meant addressed their research questions in those discussiongroups.informal conversations. Colleagues not in the team but in

the department or in another institution of the same sub-ject area often were involved in such conversations. The

Use of Informationrelatively large percentage for the last category–col-leagues not in the team and outside the department–sug- Having analyzed the responses for the above questions,

we can draw a brief picture of interdisciplinary collabora-gested that informal communication accounted for a sub-stantial portion of interdisciplinary communication. Dis- tion and the links that tie it with other forces: primarily

within-departmental collaboration, extensive interdisci-cussion groups of similar interest in computer networks


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plinary communication by visiting and active interactions were able to see some interconnections of the subjectareas through the subject information as reflected in thewith outside-discipline or -subject colleagues, and only

about half of the outside-subject experts became coau- citations. Our direct observation of the use of interdisci-plinary information in the sample papers conformed withthors of research papers. One of the purposes of studying

this is the concern that information scientists share about the responses above. Worth mentioning also is that tworespondents used outside-subject information to tie seem-interdisciplinary information seeking and use. The results

of this study showed that 74% of respondents acquired ingly unrelated topics together or provide supporting evi-dence for the research.the outside-discipline or -subject information through col-

laborators from other subject fields, while following up While information from different subject areas wasincorporated into research in several different ways, re-on citations in the articles they read also was used fre-

quently. It was quite apparent that, in columns ‘‘neutral’’ spondents estimated differently the proportion of theirinterdisciplinary research: ‘‘Almost all the projects’’ hadand ‘‘infrequently’’, the percentages for both ‘‘Through

collaborators from other subject fields’’ and ‘‘Following the highest percentage—29%, and the lowest was thosehaving ‘‘Few of the projects’’ using information fromup on citations’’ were exactly the reverse, that is, citations

were consulted more often than collaborators from other other subject areas. On the whole, the data suggesteda high degree of interdisciplinarity for over half of thesubject areas. This could imply that following up citations

was the most used method in seeking interdisciplinary research.Although all respondents were the first authors of theinformation. Searching databases has been recognized as

an effective method for collecting comprehensive infor- sample papers, this does not necessarily mean that theywere the principal investigator of the project. One respon-mation on a topic. But this method was used less fre-

quently than the above two, and about two-thirds of the dent commented that the research paper (included in thesample under study) was done when he was a graduaterespondents answered that they frequently used database

searching for identifying information not in their special- student. He was not the person in charge of the wholeproject. Another respondent pointed out that the paperties. The percentages for scanning journals in other sub-

ject areas gave us an impression that there was a great ‘‘was not a result of an interdisciplinary group collabora-tion, rather a project executed by members of one team.’’demand for researchers to obtain information by this

method (52%). Noticeable also was the percentage of A respondent from the industrial sector also made aninteresting comment: ‘‘In industrial research in a largeinfrequent scanners (39%). There could be various rea-

sons for not using this way to seek information. Two company, most of your collaborators are ‘built-in.’ ( i.e.,members of your department already or in allied depart-factors might have been the main reasons: the availability

of and the accessibility to these journals. Because most ments) Also, there are experts in various other fieldswithin the research company.’’ This explained part oflarge academic libraries were organized by departmental

structure, i.e., collections of different disciplines are the reason why the industrial sector collaborated withacademic institutions so rarely.housed in departmental libraries that usually are located

in the departmental buildings, the disciplinary boundaries This survey, as a supplementary device, provided use-ful explanations and insights relating to the bibliometricrestrained the collection development policy, resource al-

location, and services that can be devoted to seemingly data. In relation to the hypotheses tested, the survey re-sults not only conformed with the bibliometric analysis,outside-disciplines or -subject areas. For those who might

have had the need to scan these journals, it was very but also partly explained the characteristics of IDR collab-oration as reflected through the bibliometric data. Forlikely that these journals were either not available in their

own library or located at an inconvenient distance. In example, the bibliometric data indicated a high percentageof intradepartmental collaboration. The survey found that,coping with such difficulty, one respondent said that he

frequently had to take selected visits to relevant institu- among other factors, personal acquaintance with potentialcollaborators played a very important role in collaborativetions for this purpose. Seminars and nonspecialized jour-

nals were also useful sources for interdisciplinary infor- research. With this in mind, it was further found thatthese personal acquaintances mostly came from the samemation searching.

Responses regarding the use of information were dif- department (ú83% as co-investigator) while 100% ofsuch collaboration resulted in coauthorship. On the otherficult to deal with because about two-thirds of the respon-

dents agreed that information in subject areas other than hand, consultants, especially those who were outside sub-ject specialists, were much less likely to become coau-their own was used to provide methodology, identify new

research problems, and supply theoretical support for re- thors.The survey data on communication channels and infor-search. Among the 24 papers authored by the respondents

and their collaborators, 21 (96%) of them cited more than mation seeking methods showed that much of the commu-nication took place within disciplinary boundaries, beingone subject area different from the one(s) in which the

paper was published. Although it was difficult to know most frequent among team members and much lessamong outside-team colleagues. Interdisciplinary com-how the respondents and their team members used the

information in different areas and for what purpose, we munication (including information seeking) is essentially


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a matter of ‘‘wordage’’ (Freeman, 1971), or understand- unit) , peer-reviewed (or not reviewed), or even article-free (data as distribution unit) . Such changes can haveing of terminologies across disciplines (Scaif, Curtis, &

Hill, 1994), and the vocabulary barriers of such commu- profound effects on collaboration, interdisciplinarity, andeven authorship.nication grow larger as more different disciplines join in.

Within-disciplinary collaboration minimizes the diffi- Papers categorized as ‘‘noncollaborative’’ revealedtwo interesting phenomena. One was that a single authorculties brought about by technical jargons and hence in-

creases the chances of success in communication. This is could have more than one institutional address. This phe-nomenon of single-author-with-multiple-affiliations is ev-perhaps why collaborators from outside-subject fields

were relied upon heavily for seeking outside-subject in- idence of moving across organizational boundaries, mean-ing more exposure to broader subject areas and interac-formation, because they were the ‘‘insiders’’ who had the

knowledge of other vocabularies. Searching databases for tions. Another was the papers by highly interdisciplinaryindividuals (papers with only one author but citing fiveinterdisciplinary information was used less than con-

sulting outside subject collaborators, which also may re- or more disciplines) . These papers often implied suchinterdisciplinary interaction that was not reflected in au-flect the difficulty in applying specialized vocabularies

from other disciplines. thorship. An article in zoology, for instance, discussedfindings in field observations on familial association,nymphal development, and population density in the Aus-

Discussion of Findingstralian giant burrowing cockroach. Information in the ac-knowledgment in the paper tells us that ¢10 people par-As stated earlier, the research questions for this project

were: to investigate the extent of scientist-information ticipated in some way, including advising, critical read-ing, providing information for study sites and theinteraction, the variations of the interaction among differ-

ent levels of collaboration and disciplines, and the factors cockroach, and field assistance. Another study that wasalso substantially field work involved even morethat affect such interaction. Developed from these re-

search questions were three hypotheses which tested the ‘‘subauthors’’: 10 for field work, 1 for observation shar-ing, 4 for data analysis, 4 for manuscript preparation. Thedifferences in the degree of interdisciplinarity by level

of collaboration and scientific discipline, and tested the situation described here has been studied by Blaise Croninand Kara Overfelt (1994). They summarize their findingsassociation of interdisciplinarity with collaboration. The

bibliometric findings, though quantitative in nature, de- in the use of acknowledgment as five categories: indicat-ing influence, intellectual connections, genealogy ofpicted three facets of interaction that could involve inter-

disciplinarity: scientist-scientist interaction, scientist-in- ideas, performance assessment, and standardization ofpractice. Their study indicates that acknowledgments canformation interaction, and information-information inter-

action. The survey data provided us with some insights provide ‘‘a simple yet potentially powerful insight intothe dynamics of collaboration within and across groups,into the factors that affected such interactions.institutions, fields and countries (p. 167).’’ The acknowl-edgment information in the present study casts light on

Extent of Scientist-Scientist Interactiona level of collaboration that is not reflected in the biblio-metric data. It is safe to say that ú85% of authors in theCollaboration among scientists can be considered the

most typical form of scientist-scientist interaction. It was sample interacted extensively with colleagues not onlyin their own department, but also in other geographicalexamined from data on authorship, author affiliation, and

the discipline of author affiliation. As a result, the single- locations and disciplines. Even in the papers of the non-collaboration category, extensive collaboration some-authored papers were categorized as noncollaborative re-

search. But, in many cases, noncollaborative papers did times occurred and was often reflected in the form of‘‘subauthorship’’.not necessarily imply no scientist-scientist interaction. As

the ‘‘invisible colleges’’ (Crane, 1972) literature has de- Whom a scientist collaborates with depends on severalfactors. Types of organizations affect the flexibility andscribed, this type of interaction, though not always pro-

ducing coauthorship, is still very important in scientific mobility of scientists who affiliate with them. The surveyfound that scientists in academic settings tended to havecommunication, leading to advice on experimental de-

sign, feedback in seminars, colloquia, etc., comments on more flexibility in collaborating with colleagues in differ-ent institutions and doing research and teaching in placesdraft manuscripts, discussion at conferences, and review

of submitted manuscripts. These activities now have beyond their own departments. Researchers in the indus-trial sector were much less likely to collaborate with col-evolved into ‘‘electronic invisible colleges’’ (Hurd,

1995) along with the developments of information tech- leagues outside of their organization. This may be ex-plained partially by concern for industrial secrecy andnology, computer networks, new research toward ‘‘big

science,’’ interdisciplinary research, and massive com- partly by the fact that industrial departments are oftenrelatively self-contained units that incorporate expertiseputer-generated/stored data sets. These new electronic

invisible colleges, according to Julie Hurd, are character- from many disciplines. On the whole, collaborationmostly occurred in the same department. If it happenedized as paperless, journal-free (article as distribution


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to be in more than one institution, it would be most likely specific, method-specific, or process-specific. These ex-treme cases (27 highly interdisciplinary individuals andamong those scientists within the same discipline or sub-

ject area, which was shown by both bibliometric and 31 highly collaborative but slightly interdisciplinary pa-pers) , though few in the whole sample, did cause a bigsurvey results. Other factors affecting collaboration were

the topic or subject of the research, personal networking difference in the association between collaboration andwith people, and funding. The survey data show that, if interdisciplinarity.the collaborator was a student who performs technical Most collaboration occurred among scientists from theoperations in a project, he or she had a 50–50 chance same department or discipline. While this was confirmedto be acknowledged as a coauthor. Consultants had less in both bibliometric and survey analysis, the data on inter-probability to be joint authors than technical assistants. disciplinarity revealed that most of the within-departmen-It is obvious that there is a great deal of scientist-scientist tal or within-disciplinary collaborative projects used in-interaction left unrecorded in the form of coauthorship. formation beyond their own specialties. This shows thatIt would be worth investigating what role this non-coau- limited scientist-scientist ( in terms of affiliation) interac-thorship collaboration plays in the scientist-information tion still can involve extensive scientist-information inter-interaction. action. This trend raises a question for us: How much do

we know about information seeking methods used byscientists to acquire interdisciplinary information and howExtent of Scientist-Information Interactioneffective are the existing information systems in meeting

The scientist-information interaction includes two as- such information needs? Interdisciplinary collaborationpects: The total amount of information used or absorbed challenges us to improve existing information systemsin a research project and the disciplines incorporated in and services to better facilitate scientist-information inter-a research project. If one regards them as an information actions across disciplinary boundaries.environment, scientists deal with information in this envi-ronment in terms of both quantity and quality. The former,the total amount of information used in a research project,

Extent of Information-Information Interactionwas measured in this research by the number of citations,and the latter by the number of disciplines of the journals

The information-information interaction is actually acited in a research project. On the average, a researchprocess in which the existing information in several dif-paper cited 25 references with a range from 1 to 161.ferent disciplines is integrated into new information/There were variations in different disciplines. Dividingknowledge. This interaction is subtler and more intangi-the eight disciplines into two groups by using the averageble than the other two discussed above. In the context ofnumber of citations per paper, the first group—biologythis study, sources cited in a paper were analogous to the(30), earth sciences (30), and medical sciences (28) —existing information/knowledge, and the research paperhad above-average numbers; the second group—agricul-that cited them represented itself the new information/ture (23), chemistry (22), engineering (18), mathemat-knowledge. While the number of disciplines cited wasics (13), and physics (19) —had below-averageused together with collaboration variables to study scien-numbers. A factor that possibly affected the number oftist-information interaction, this variable also was usedcitations and thus the number of disciplines cited was thetogether with the discipline(s) of the citing journal tosize of the body of a discipline. For example, medicalexamine the quantitative extent of the information-infor-sciences have 30 subdisciplines in Ulrich’s, while mathe-mation interaction. The number of disciplines of the jour-matics has only one (thus literally none). Obviously,nals cited measured how many different disciplines hadthen, bibliometric analyses are more likely to indicateparticipated in the interaction or had been integrated.interdisciplinarity in the medical sciences than in mathe-From the bibliometric data, we found that an average ofmatics.3.89 disciplines were involved in each integration pro-The test for hypotheses 1 and 2 was shown significant;cess; that is, 3.89 disciplines were cited per paper. Thisthat is, the degree of interdisciplinarity differed signifi-figure varied from discipline to discipline, ranging fromcantly among different levels of collaboration and among1.78 in mathematics to 5.18 in agriculture.scientific disciplines. The distribution of interdisciplinar-

The bibliometric data, basically quantitative, providedity is approximately normal: highly collaborative butus with a broad overview of interdisciplinarity in science.slightly interdisciplinary papers at one extreme and highlyIt should be noted that the dependent variable—the num-interdisciplinary individuals at the other. Assuming thoseber of journal disciplines represented in the referencesfalling into the middle are the ‘‘norm’’ of scientist-infor-cited—measured the end-product of a research projectmation interaction, the further analysis of the extremerather than the work process in which the integration ofcases revealed that, when a paper was highly collaborativedisciplines actually took place. But the process and thebut slightly interdisciplinary, the topic it dealt with tendedend-product are not isolated things. In fact, the latter isto be a narrower and very specific one and the nature of

the study tended to be either case-specific, substance- the direct reflection of the former.


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Conclusion senting these networks in information systems. Endeavorsin these areas can lead not only to solutions for ‘‘word-

To conclude, the present study investigated the status age’’ problems in IDR collaboration, but also to applica-of scientific communication in the context of interdisci- tions of more sophisticated techniques for informationplinary collaboration. The bibliometric data showed that analysis.the levels and types of interdisciplinary collaboration var-ied in different disciplines, but the general trend was to-

Acknowledgmentsward high interdisciplinarity, which especially was pro-nounced in biology and medical sciences. The bibliome- We thank Linda Smith, Ann Bishop, and two anony-tric data also suggested that, regardless of the two mous referees for their valuable suggestions and com-extremes, i.e., highly collaborative but slightly interdisci- ments.plinary and highly interdisciplinary individuals, collabo-ration positively correlated with interdisciplinarity. The

Appendix: A Survey Of Interdisciplinaryfindings of the questionnaire survey revealed some ofCollaborationthese factors affecting collaboration—such as type of in-

stitution, nature of research problems, personal contact I. Forms of Collaborationwith collaborators, and funding—that the bibliometric 1. When you are conducting collaborative research, howdata could not identify. The responses on communication likely are you to collaborate with researchers from:methods showed that interactive and/or high speed mech- Very likely } Very unlikely 1 2 3 4 5anisms were preferred by most scientists. Interdisciplinary 1) academic institutionsinformation seeking heavily relied on outside-subject ex- 2) the industrial sectorperts and used primarily conventional methods. 3) government organizations

The trend of limited scientist-scientist ( in terms of 4) other organizations, please specifyaffiliation) interaction with extensive scientist-informa- 2. How important are the following factors in determin-tion interaction has important implications for infor- ing whether you will collaborate with other researchers:mation systems and services. As many studies have Very important } Very unimportantindicated, the most difficult problem encountered in inter- 1 2 3 4 5disciplinary collaboration is the perception and under- 1) the subject or topic of the researchstanding of disciplinary terminologies and working 2) the sponsor or funding agencynorms. Such difficulties are compounded in the situation 3) financial resources availableof limited scientist-scientist interaction with extensive sci- 4) personal acquaintance withentist-information interaction. Most current information potential collaboratorssystems are of limited value in supporting cross-disciplin- 5) others, please specifyary information seeking because they tend to lack mutidi- 3. When one of your collaborative projects involves themensionality and quality filtering. Collaborative research, type of person listed in the 4 categories below, what isespecially when collaborators are from the same disci- usually their relationship with you?pline, needs information systems built for specific topics Student Colleagues Colleagues in Colleagues inon the basis of information analysis (e.g., antibiotic resis- in your your own other subjecttance, a highly interdisciplinary subject, must draw upon department subject area areasbiochemistry, biophysics, genetics, microbiology, phar- in othermacology, and many other fields) . Such focused informa- institutionstion systems, derived from information analysis activities, 1) Technical assistant (data collection,would be multidimensional—e.g., providing information performing experiments, etc.)on leading researchers, institutions, research fronts, im- 2) Co-investigatorportant publications, and so on, and have built-in gate- 3) Consultant (providing advice butways leading to the broader bibliographic information may not be involved in researchsystems. process

This study has confirmed the value of combining bibli- 4) Othersometric and survey techniques in investigating these types 4. Which of the above relationships are likely to resultof phenomena. The more qualitative data obtained from in coauthorship in a research paper?appropriate surveys can supplement, clarify, and aid the Very likely } Very unlikelyinterpretation of the purely bibliometric data. Qualitative 1 2 3 4 5analysis of interdisciplinary subject areas or topics is an- 1) Technical assistantother area that would promise valuable findings for reno- 2) Co-investigatorvating existing information systems and services. Such 3) Consultantstudies investigate the interdisciplinary networks of sub- 4) Others

II. Channels of Communicationjects or topics and the techniques of analyzing and pre-


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5. When you collaborate with someone from another de- 5) NeverIV. Commentpartment or another campus, which of the following

means of communication makes collaboration particularlyeffective?

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Types and levels of collaboration in interdisciplinary research in the sciences

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