No.
|
Concept
|
No. of records
|
1
|
Knowledge Management
|
2,788
|
2
|
Knowledge Acquisition
|
2,461
|
3
|
Knowledge Transfer
|
768
|
4
|
Tacit Knowledge
|
750
|
5
|
Explicit Knowledge
|
687
|
6
|
Indigenous Knowledge
|
505
|
7
|
Knowledge Creation
|
475
|
8
|
Knowledge Production
|
468
|
9
|
Knowledge Development
|
386
|
10
|
Organizational Knowledge
|
329
|
11
|
Implicit Knowledge
|
301
|
12
|
Intellectual Capital
|
290
|
13
|
Corporate Knowledge
|
69
|
4.2 Productivity trends for each concept
Table 2 and Fig 1 illustrate the publication trend in literature on KM and its related concepts. Each concept witnessed continued growth throughout the period of study. Knowledge management literature grew from a mere 12 records in 1986-1990, to a total of 1735 records in 2001-2005, a percentage increase of 14358%. Likewise, Table 2 shows that knowledge acquisition literature increased from 16 to 702 records between 1981 and 2005, while knowledge transfer records upped by a total of 365 from just 3 records in 1981-1985 to stand at 368 records by 2005. Similar patterns were revealed in other subject domains.
Table 2: Yearly distribution of records
No.
|
Rank
|
Concepts
|
1981-
1985
|
1986-
1990
|
1991-
1995
|
1996-
2000
|
2001-
2005
|
2006-
2007
|
TOTAL
|
1
|
1
|
Knowledge Management
|
0
|
12
|
43
|
390
|
1735
|
608
|
2788
|
2
|
2
|
Knowledge Acquisition
|
16
|
99
|
689
|
724
|
702
|
231
|
2461
|
3
|
3
|
Knowledge Transfer
|
3
|
9
|
58
|
126
|
368
|
204
|
768
|
4
|
4
|
Tacit Knowledge
|
6
|
5
|
75
|
180
|
350
|
134
|
750
|
5
|
5
|
Explicit Knowledge
|
1
|
3
|
82
|
183
|
302
|
116
|
687
|
6
|
6
|
Indigenous Knowledge
|
5
|
2
|
40
|
127
|
233
|
98
|
505
|
7
|
7
|
Knowledge Creation
|
1
|
5
|
27
|
97
|
253
|
92
|
475
|
8
|
8
|
Knowledge Production
|
13
|
1
|
30
|
102
|
231
|
91
|
468
|
9
|
9
|
Knowledge Development
|
8
|
6
|
53
|
118
|
152
|
49
|
386
|
10
|
10
|
Organizational Knowledge
|
0
|
1
|
20
|
76
|
165
|
67
|
329
|
11
|
11
|
Implicit Knowledge
|
1
|
6
|
42
|
84
|
113
|
55
|
301
|
12
|
12
|
Intellectual Capital
|
1
|
2
|
8
|
109
|
131
|
39
|
290
|
13
|
13
|
Corporate Knowledge
|
0
|
1
|
5
|
20
|
35
|
8
|
69
|
Fig 1: Trend of publication
Fig 1 illustrates this trend in a graphical representation that indicates that the most productive period was 2001-2005 for all subjects. Most notable is the emergence of some of the concepts between 1986 and 1990, among them being knowledge management, organizational knowledge and corporate knowledge. The rest (i.e. 10 out of 13) appeared in literature during or before the 1981-1985 year period.
4.3 Growth of KM literature
The growth of knowledge in a discipline can be measured according to various indicators. Some of these include an increase or decrease in the number of researchers conducting research within the subject domain, the institutions behind research activities, countries in which the research is conducted, publication languages, document types, sources through which the research findings are disseminated, and the subject categories that utilize and contribute theories and practices to a given discipline. Table 3 provides the growth of the literature in terms of the cited indicators. The Table reveals that the number of authors increased from 83 in 1981-1985, to 8533 in 2006-2007, while the number of countries rose rapidly over the years from 12 to 98 over the same period. Similar patterns were recorded in an analysis of document types, which made a leap from 4 in 1981-1985, to 13 in 1996-2000, and subsequently declined to 9 in 2006-2007. The number of institutions behind research, which stood at 50 in 1981-1985, rose to 130 between 1986 and 1990 (a percentage increase of 160%), and continued to its highest peak in 2001-2005 (i.e. 2565). The languages, sources and subject categories, however, have witnessed slower growth rates, as reflected in the percentage increments.
Table 3: Growth of the literature on KM and its related concepts
No.
|
Variable
|
1981-1985
|
1986-1990
|
1991-1995
|
1996-2000
|
2001-2005
|
2006-2007
|
1
|
Authors
|
83
|
259
|
2080
|
3823
|
8237
|
8533
|
Increase in number of authors
|
-
|
176
|
1821
|
1743
|
4414
|
296
|
Percentage increase
|
-
|
212.05
|
703.09
|
83.80
|
115.46
|
3.59
|
2
|
Countries
|
12
|
22
|
62
|
72
|
98
|
86
|
Increase in number of countries
|
-
|
10
|
40
|
10
|
26
|
-12
|
Percentage increase
|
-
|
83.33
|
181.82
|
16.13
|
36.11
|
-12.24
|
3
|
Document types
|
4
|
8
|
10
|
13
|
10
|
9
|
Increase in number of document types
|
-
|
4
|
2
|
3
|
-3
|
-1
|
Percentage increase
|
-
|
100.00
|
25.00
|
30.00
|
-23.08
|
-10.00
|
4
|
Institutions
|
50
|
130
|
845
|
1421
|
2565
|
1359
|
Increase in number of institutions
|
-
|
80
|
715
|
576
|
1144
|
-1206
|
Percentage increase
|
-
|
160.00
|
550.00
|
68.17
|
80.51
|
-47.02
|
5
|
Language
|
2
|
5
|
7
|
10
|
14
|
8
|
Increase in number of languages
|
-
|
3
|
2
|
3
|
4
|
-6
|
Percentage increase
|
-
|
150.00
|
40.00
|
42.86
|
40.00
|
-42.86
|
6
|
Sources
|
49
|
82
|
539
|
869
|
1402
|
771
|
Increase in number of sources
|
-
|
33
|
457
|
330
|
533
|
-631
|
Percentage increase
|
-
|
67.35
|
557.32
|
61.22
|
61.33
|
-45.01
|
7
|
Subject categories
|
37
|
58
|
156
|
171
|
198
|
174
|
Increase in number of subject categories
|
-
|
21
|
98
|
15
|
27
|
-24
|
Percentage increase
|
-
|
56.76
|
168.97
|
9.62
|
15.79
|
-12.12
|
Table 4: Subject categories utilizing and contributing to KM research (N=9229)
No.
|
Subject category
|
No. of records
|
%
|
No.
|
Subject Category
|
No. of records
|
%
|
1
|
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
|
1405
|
15.22%
|
31
|
PSYCHOLOGY, EDUCATIONAL
|
122
|
1.32%
|
2
|
MANAGEMENT
|
1370
|
14.84%
|
32
|
PSYCHOLOGY, APPLIED
|
121
|
1.31%
|
3
|
COMPUTER SCIENCE, INFORMATION SYSTEMS
|
950
|
10.29%
|
33
|
AUTOMATION & CONTROL SYSTEMS
|
116
|
1.26%
|
4
|
COMPUTER SCIENCE, THEORY & METHODS
|
752
|
8.15%
|
34
|
MATHEMATICS, APPLIED
|
112
|
1.21%
|
5
|
INFORMATION SCIENCE & LIBRARY SCIENCE
|
728
|
7.89%
|
35
|
ANTHROPOLOGY
|
98
|
1.06%
|
6
|
OPERATIONS RESEARCH & MANAGEMENT SCIENCE
|
716
|
7.76%
|
36
|
PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
|
95
|
1.03%
|
7
|
BUSINESS
|
634
|
6.87%
|
37
|
MULTIDISCIPLINARY SCIENCES
|
94
|
1.02%
|
8
|
ENGINEERING, ELECTRICAL & ELECTRONIC
|
483
|
5.23%
|
38
|
ENGINEERING, CIVIL
|
84
|
0.91%
|
9
|
COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
|
451
|
4.89%
|
39
|
PSYCHOLOGY, DEVELOPMENTAL
|
83
|
0.90%
|
10
|
ENGINEERING, INDUSTRIAL
|
370
|
4.01%
|
40
|
ECOLOGY
|
80
|
0.87%
|
11
|
EDUCATION & EDUCATIONAL RESEARCH
|
346
|
3.75%
|
41
|
ENGINEERING, CHEMICAL
|
78
|
0.85%
|
12
|
PSYCHOLOGY, MULTIDISCIPLINARY
|
285
|
3.09%
|
42
|
COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
|
70
|
0.76%
|
13
|
ENGINEERING, MULTIDISCIPLINARY
|
275
|
2.98%
|
43
|
EDUCATION, SCIENTIFIC DISCIPLINES
|
70
|
0.76%
|
14
|
PSYCHOLOGY, EXPERIMENTAL
|
259
|
2.81%
|
44
|
HISTORY & PHILOSOPHY OF SCIENCE
|
70
|
0.76%
|
15
|
COMPUTER SCIENCE, SOFTWARE ENGINEERING
|
258
|
2.80%
|
45
|
COMMUNICATION
|
65
|
0.70%
|
16
|
COMPUTER SCIENCE, CYBERNETICS
|
255
|
2.76%
|
46
|
STATISTICS & PROBABILITY
|
64
|
0.69%
|
17
|
ENGINEERING, MANUFACTURING
|
216
|
2.34%
|
47
|
BEHAVIORAL SCIENCES
|
62
|
0.67%
|
18
|
PLANNING & DEVELOPMENT
|
209
|
2.26%
|
48
|
TELECOMMUNICATIONS
|
61
|
0.66%
|
19
|
MEDICAL INFORMATICS
|
196
|
2.12%
|
49
|
ENGINEERING, BIOMEDICAL
|
59
|
0.64%
|
20
|
ERGONOMICS
|
183
|
1.98%
|
50
|
AGRICULTURE, MULTIDISCIPLINARY
|
56
|
0.61%
|
21
|
PSYCHOLOGY
|
175
|
1.90%
|
51
|
PHARMACOLOGY & PHARMACY
|
56
|
0.61%
|
22
|
ENVIRONMENTAL STUDIES
|
171
|
1.85%
|
52
|
SPORT SCIENCES
|
53
|
0.57%
|
23
|
NURSING
|
166
|
1.80%
|
53
|
CHEMISTRY, MULTIDISCIPLINARY
|
52
|
0.56%
|
24
|
ECONOMICS
|
165
|
1.79%
|
54
|
PSYCHOLOGY, BIOLOGICAL
|
51
|
0.55%
|
25
|
GEOGRAPHY
|
165
|
1.79%
|
55
|
SOCIAL WORK
|
51
|
0.55%
|
26
|
ENVIRONMENTAL SCIENCES
|
162
|
1.76%
|
56
|
WATER RESOURCES
|
49
|
0.53%
|
27
|
HEALTH CARE SCIENCES & SERVICES
|
161
|
1.74%
|
57
|
CONSTRUCTION & BUILDING TECHNOLOGY
|
48
|
0.52%
|
28
|
SOCIAL SCIENCES, INTERDISCIPLINARY
|
158
|
1.71%
|
58
|
ENGINEERING, MECHANICAL
|
47
|
0.51%
|
29
|
NEUROSCIENCES
|
152
|
1.65%
|
59
|
MEDICINE, GENERAL & INTERNAL
|
47
|
0.51%
|
30
|
SOCIOLOGY
|
134
|
1.45%
|
60
|
APPLIED LINGUISTICS
|
45
|
0.49%
|
Subject categories
An analysis of the subject categories in KM literature and related concepts was meant to examine the most productive discipline or subject domain in terms of the number of publications. In this way, we could make inferences concerning the disciplines or subject domains that are utilizing and contributing to the theory development of KM. Table 4 reveals that “computer science, artificial intelligence” and “management” contributed the most literature, by producing a combined total of 2775 records. Of the total 9229 records, “computer science, information systems” contributed 950, followed by “computer science, theory and methods” (752, 8.15%); “Information Science & Library Science” (728, 7.89%); “Operations Research & Management Science” (716, 7.76%); “Business” (634, 6.87%); and “Engineering, Electrical & Electronic” (483, 5.23%).
4.5 Growth in the number of records vis-à-vis citations
The average number of citations per paper, which is sometimes used to measure the influence of an entity (i.e. author, institution, country, article/publication, or source (e.g. journal) was computed to examine the past and forecast the future influence of literature on KM and other subject domains. Table 5 and Figs 2 and 3 present the trends of productivity and impact between 1981 and 2007. Generally, Table 5 shows a continued increase in the number of publications and citations. Whereas the publications grew by 198.25% between 1981-1985 and 1986-1990, and by 585.35% between 1986-1990 and 1991-1995, the number of citations increased by 545.71% and 429.65%, respectively. There were drops in both cases in 2006-2007. The average number of citations showed a continued growth rate, except for 1991-1995 where a decline was recorded.
Table 5: Growth in the number of records and citations
|
|
1981-1985
|
1986-1990
|
1991-1995
|
1996-2000
|
2001-2005
|
2006-2007
|
TOTAL
|
RECORDS
|
Number of records
|
57
|
170
|
1160
|
2230
|
4234
|
1378
|
9229
|
|
Change in no. of records
|
-
|
113
|
990
|
1070
|
2004
|
-2856
|
-
|
|
% change in no. of records
|
-
|
198.25
|
582.35
|
92.24
|
89.87
|
-67.45
|
-
|
|
Cumulative no. of records
|
57
|
227
|
1387
|
3617
|
7851
|
9229
|
-
|
|
Change in cumulative no of records
|
-
|
170
|
1160
|
2230
|
4234
|
1378
|
-
|
|
% change in cumulative of records
|
-
|
298.25
|
511.01
|
160.78
|
117.06
|
17.55
|
-
|
|
Mean no of records per year
|
11.40
|
34.00
|
232.00
|
446.00
|
846.80
|
918.67
|
341.81
|
CITATIONS
|
Number of citations
|
70
|
452
|
2394
|
9654
|
27595
|
14454
|
54619
|
|
Change in no. of citations
|
-
|
382
|
1942
|
7260
|
17941
|
-13141
|
-
|
|
% change in no. of citations
|
-
|
545.71
|
429.65
|
303.26
|
185.84
|
-47.62
|
-
|
|
Cumulative no. of citations
|
70
|
522
|
2916
|
12570
|
40165
|
54619
|
-
|
|
Change in cumulative no. of citations
|
-
|
452
|
2394
|
9654
|
27595
|
14454
|
-
|
|
% change in cumulative no. of citations
|
-
|
645.71
|
458.62
|
331.07
|
219.53
|
35.99
|
-
|
|
Mean no. of citations per year
|
14.00
|
90.40
|
478.80
|
1930.80
|
5519.00
|
9636.00
|
2022.93
|
Average cites per record
|
1.23
|
2.66
|
2.06
|
4.33
|
6.52
|
10.49
|
5.92
|
Figs 2 and 3 provide graphical representations of the patterns of growth shown in Table 5. They reveal that whereas the average number of papers per year grew linearly, the number of citations per year recorded an exponential growth pattern. Similarly, the number of papers linearly increased while that of the citations increased exponentially.
Fig 2: Trends of growth of papers, citations, papers per record and citations per paper, 1981 and 2007
Fig 3: Growth of publications and citations
4.6 Countries utilizing and contributing to theory and practice of KM and other subject domains
An analysis of the most productive countries between 1981 and 2007 was meant to provide an insight into the countries from which theories, practices and knowledge on knowledge management and related concepts originate. Table 6 shows that the lion’s share of publications originated from the USA (3179, 34.45%), followed by England (1101, 11.93%), Germany (695, 7.53%), Canada (625, 6.77%), Australia (341, 3.69%), France (330, 3.58%), Netherlands (301, 3.26%), China (275, 2.98%), Japan (258, 2.80%), and Italy (249, 2.70%).
Table 6: Productivity by country (N= 9229)
No.
|
Country
|
1981-
1985
|
1986-
1990
|
1991-
1995
|
1996-
2000
|
2001-
2005
|
2006-
2007
|
TOTAL
|
Percentage
|
1
|
USA
|
23
|
98
|
469
|
831
|
1306
|
475
|
3179
|
34.45%
|
2
|
ENGLAND
|
4
|
12
|
91
|
241
|
532
|
225
|
1101
|
11.93%
|
3
|
GERMANY
|
|
5
|
84
|
151
|
331
|
124
|
695
|
7.53%
|
4
|
CANADA
|
1
|
8
|
106
|
135
|
256
|
120
|
625
|
6.77%
|
5
|
AUSTRALIA
|
|
|
29
|
80
|
176
|
56
|
341
|
3.69%
|
6
|
FRANCE
|
1
|
3
|
57
|
86
|
141
|
43
|
330
|
3.58%
|
7
|
NETHERLANDS
|
1
|
5
|
39
|
87
|
123
|
47
|
301
|
3.26%
|
8
|
CHINA
|
|
|
6
|
23
|
167
|
79
|
275
|
2.98%
|
9
|
JAPAN
|
|
|
57
|
68
|
91
|
42
|
258
|
2.80%
|
10
|
ITALY
|
|
2
|
24
|
44
|
133
|
46
|
249
|
2.70%
|
11
|
TAIWAN
|
|
1
|
13
|
45
|
111
|
72
|
242
|
2.62%
|
12
|
SPAIN
|
|
1
|
13
|
35
|
123
|
59
|
231
|
2.50%
|
13
|
AUSTRIA
|
|
|
8
|
23
|
89
|
22
|
142
|
1.54%
|
14
|
SWEDEN
|
1
|
|
24
|
28
|
73
|
16
|
141
|
1.53%
|
15
|
SCOTLAND
|
1
|
|
16
|
27
|
79
|
18
|
140
|
1.52%
|
16
|
SOUTH KOREA
|
|
|
6
|
23
|
67
|
40
|
136
|
1.47%
|
17
|
SWITZERLAND
|
|
3
|
11
|
25
|
62
|
23
|
124
|
1.34%
|
18
|
FINLAND
|
|
|
12
|
22
|
63
|
19
|
116
|
1.26%
|
19
|
SINGAPORE
|
|
1
|
14
|
16
|
56
|
23
|
110
|
1.19%
|
20
|
BRAZIL
|
|
1
|
4
|
11
|
65
|
25
|
106
|
1.15%
|
21
|
BELGIUM
|
|
|
16
|
29
|
35
|
24
|
104
|
1.13%
|
22
|
INDIA
|
|
1
|
11
|
30
|
47
|
13
|
102
|
1.11%
|
23
|
SOUTH AFRICA
|
|
1
|
6
|
14
|
50
|
22
|
93
|
1.01%
|
24
|
GREECE
|
|
1
|
9
|
13
|
45
|
22
|
90
|
0.98%
|
25
|
NEW ZEALAND
|
|
|
3
|
18
|
47
|
19
|
87
|
0.94%
|
26
|
NORWAY
|
|
1
|
8
|
16
|
43
|
13
|
81
|
0.88%
|
27
|
DENMARK
|
|
|
5
|
14
|
44
|
15
|
78
|
0.85%
|
28
|
ISRAEL
|
1
|
1
|
9
|
23
|
28
|
16
|
77
|
0.83%
|
29
|
POLAND
|
1
|
3
|
3
|
7
|
29
|
14
|
56
|
0.61%
|
30
|
MEXICO
|
|
|
3
|
13
|
24
|
13
|
53
|
0.57%
|
5. Discussion, conclusions and recommendations
Although KM is a relatively new concept – having been born in the mid-1990s (Jacobs, 2004:212) – results have shown that knowledge and KM practices have always existed, although not as much as they are known and applied today. For instance, Plato defined knowledge as “justified true belief”38. Today, most scholars have faulted this definition and attempted to offer different perspectives on what knowledge means. Information professionals see knowledge as internalized information, as reflected in the DIKW model – Data, Information, Knowledge and Wisdom. Some of the knowledge management practices that have existed for decades include knowledge transfer and knowledge acquisition. According to the Wikipedia online encyclopedia:39
One aspect of knowledge management, knowledge transfer, has always existed in one form or another. Examples include on-the-job peer discussions, formal apprenticeship, corporate libraries, professional training and mentoring programs. However, with computers becoming more widespread in the second half of the 20th century, specific adaptations of technology such as knowledge bases, expert systems, and knowledge repositories have been introduced to further simplify the process.
This revelation is supported by the findings of this study, which show that among the concepts appearing in the literature published in the early 1980s were knowledge acquisition, knowledge transfer, tacit knowledge, explicit/implicit knowledge, indigenous knowledge, knowledge creation, knowledge development, intellectual capital and corporate knowledge.
Fig 1 shows that all KM-related concepts (e.g. processes and types of knowledge) have shown an exponential trend in growth. KM has the highest rate of growth, implying an increased amount of interest from various scholars, as reflected by the different subject categories. We must note, however, that records on KM include those of knowledge management system(s), which is said to have evolved in the early 1970s in the United States of America (http://www.ultradevguru.com/ver2_hypertext/kms.htm). This therefore implies that the early use of knowledge management, as reflected in the literature, refers to knowledge management systems, defined as systems (largely IT-based) for managing knowledge in organizations, and supporting the creation, capture, storage and dissemination of information. The rapid increase in the number of publications for each concept may imply a growth of knowledge in the respective subject domains. In addition, the growth in the number of authors (researchers), countries, document types, institutions, languages, sources and subject categories can be attributed to the interest KM has generated in several disciplines. It has also been observed that knowledge management is a multi-disciplinary subject, in which case one would expect an increased interest from a variety of researchers who are affiliated to different institutions and countries. The rapid growth rate of the literature is likely to persist for a long time, especially as we transit from an information age to the knowledge society. It is worth noting, however, that the growth in the amount of literature and citations alone can not reliably inform us about the future prospects of a new subject. Further studies need to be conducted (using expert opinions, surveys, etc) to validate the results generated from informetric studies. Nevertheless, previous studies have shown that informetric studies provide substantive information that can be used to determine the trend of a subject (e.g. hot topics, etc) (see http://in-cites.com/).
An analysis of the subject categories reveals that computer science, management, library and information science, business, and electrical & electronic engineering, are major contributors and utilizers of knowledge and knowledge management theories and practices. Similar findings were reported by Jacobs (2004) and Onyancha & Ocholla (2006). Seemingly, this pattern will continue until such time that ‘knowledge management’, or an alternative subject category to describe knowledge - and knowledge management-specific literature - is introduced by ISI. Presently, there is no subject category in ISI’s list of subject categories that specifically describes knowledge or knowledge management literature.
On average, a comparison of the number of papers and citations reveals that the latter has continued to increase exponentially, while the former can be said to follow a linear trend of growth. This, in our view, is characteristic of a newly introduced subject or discipline. We generally feel that authors would tend to heavily cite the few papers that have been published in a new domain. Simply put, the number of researchers outweighs the number of sources that specifically deal with this area of research, and therefore it is likely that most (if not all) researchers will use the same sources of information in their reviews and citations. This trend is likely to continue because KM is still at its early stages of development.
Another aspect that was considered in this study was the countries that are the most productive. Results indicate that Europe and the Americas are and will remain the most productive countries. Table 6 shows that most of the publications originated from the USA, England, Germany, Canada, Australia, France, and the Netherlands. Asia put up a good show, with China, Japan and Taiwan taking positions 8, 9 and 11, respectively. The implication of this pattern of productivity is that these countries have and will continue to influence the direction of KM research. KM theories will continue to originate from the West and partly the East. Africa and the other continents will have little impact in influencing research, theory development and even the curriculum of KM.
In conclusion, we note that KM has increasingly become a household term and a vital activity, particularly in business circles. It is fast moving from being a concept, to a course within a variety of disciplines, to a discipline in its own right. KM research, in keeping with most newly introduced subject domains, has shown a tremendous amount of growth in literature and impact. Although KM is young, it has shown signs of growing even stronger. Exactly how long it will sustain its current growth rate may be difficult to predict. But, going by its exemplary performance over such a short period of time, we can safely assume that KM will remain a ‘hot’ topic in research and study, particularly in the knowledge society.
References
Chaudhry, A.S. & Higgins, S.E. (2001). Perspectives on education for knowledge management: paper presented to 67th IFLA Council and General Conference. Retrieved May 4th, 2005 from www.ifla.org/IV/ifla67/papers/036- 115ae.pdf
Cunningham, S. (2001). The Birth of a Field: an Analysis of the 1994-2000 ACM Digital Libraries Conferences. In: Davis, M. & Wilson, C. S., (eds.). Proceedings of the 8th International Conference on Scientometrics and Informetrics, Sydney, 16-20 July 2001, 1, 31-39.
Garg, K. C. (2001). Scientometrics of laser research in India and China. In: Davis, M. & Wilson, C. S., (eds.). Proceedings of the 8th International Conference on Scientometrics and Informetrics, `Sydney, 16-20 July 2001, 1, 167-177.
Gordon, M.D. (1980). A critical reassessment of inferred relations between multiple authorship, scientific collaboration, the production of papers and their acceptance for publication. Scientometrics, 2(3):193-201
Gupta, B.M. & Karisiddappa, C.R. (2000). Modelling the growth of literature in the area of theoretical population genetics. Scientometrics, 49(2):321-355
Hartinah, S., Davis, M., Hydari, A. & Kent, P. (2001). Indonesian nutrition research papers 1979- 98: a bibliometric analysis. In: Davis, M. & Wilson, C. S., (eds.). Proceedings of the 8th International Conference on Scientometrics and Informetrics, Sydney, 16-20 July 2001, 1, 225- 177.
Jacobs, D. (2004). “Growth and development in knowledge management research: A bibliometric study”. In: TJD Bothma & A. Kaniki. 2004. ProLISSA 2004. Proceeding of the 3rd biennial ProLISSA Conference, Pretoria, 28 - 29 October 2004. Pretoria: Infuse, pp. 211 – 220. Also published online: www.dissanet.com
Onyancha, O.B. & Ocholla, D.N. (2006). Trends and patterns of ‘knowledge management’ research in South Africa: an informetric analysis of tacit and explicit knowledge management. In: XVII Standing Conference of Eastern, Central & Southern Africa Library & Information Associations. Dar es Salaam: The Library and Information Association of Tanzania, pp 338-361
Ravi, S. (2001). Growth and collaborative trends in nuclear science research literature: a case of I ndia, 1980-1994. In: Davis, M. & Wilson, C. S., (eds.). Proceedings of the 8th International Conference on Scientometrics and Informetrics, Sydney, 16-20 July 2001, 2, 573-585.
Tague, J., Beheshti, J. & Rees-Potter, L. (1981). The Law of exponential growth: evidence, implementation and forecasts. Library Trends, 30, 125-149
Vanston, J. (2003). Better forecasts, better plans, better results: enhance the validity and credibility of your forecasts by structuring them in accordance with the five different ways people view the future. Research Technology Management, 47-58
Dostları ilə paylaş: |