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Describes how the idea of normalised impact factor came into being and the method of its determination. In all, five properties of the normalised impact factor have been identified and described. It is observed that the ranking of a journal in its own category is better revealed by the normalised impact factor and the average normalised impact factor seems to provide better indication of the comparative performance of a set of laboratories engaged in diverse areas of research.

Can the journal impact factors regularly published in the Journal Citation Reports (JCR) be shaped by a self‐fulfilling prophecy? This question was investigated by reference to a journal for which incorrect impact factors had been published in the JCR for almost 20 years: Educational Research. In order to investigate whether the propagation of exaggerated impact factors had resulted in an increase in the actual impact of the journal, the correct impact factors were calculated. A self‐fulfilling prophecy effect was not observed. However, shows that the impact factors for Educational Research published in the JCR were based on calculations that erroneously included citations of a journal with a similar title, Educational Researcher, which is not included in the JCR. Concludes that published impact factors should be used with caution.

The purpose of this paper is to determine the relationship between the access mode of research articles [Open Access (OA) and Toll-Access (TA)] and their subsequent citation counts in Biological and Physical Sciences in three Impact factor zones (High, Medium and Low).

Three subjects each from Biological Sciences (Biochemistry, Cell Biology and Genetics) and Physical Sciences (Astronomy, Oceanography and Optics) were selected for the study. A comprehensive list of journals (TA and OA) in select subjects of Biological and Physical Sciences was prepared by consulting Journal Citation Report’s Master Journal List (for the compilation of both Open Access and Toll Access journal list) and Directory of Open Access Journals (for the compilation of Open Access journal list). For each journal, essential details like content language, format, year of publication, access mode (Open Access or Toll Access), etc. were obtained from Ulrich’s Periodical Directory. Web of Science (WoS) was used as citations indexing tool in this study. The data set was run on the WoS to collect the citation data.

The results of the study indicate that open mode of access is not a prerequisite for higher citation boost as in the majority of the cases in this study, TA articles have garnered a greater number of citations as compared to open access articles in different Impact factor zones in Biological and Physical Sciences.

A novel approach has been adopted to understand and compare the research impact of open access (OA) and toll access (TA) journal articles in the field of Biological and Physical Sciences at three Impact factor zone levels to reveal the citation metrics encompassing three parameters, i.e. citedness, average citation count and year wise distribution of citations in select subjects of Biological and Physical Sciences.

The peer review history for this article is available at: https://publons.com/publon/[DOI]/10.1108/OIR-01-2021-0029

This paper aims to describe and debate a series of concerns that may affect, influence or manipulate the “Social Science Citation Index” (SSCI) and its impact factors.

A conceptual discussion of the SSCI and its impact factors are provided.

A series of concerns and potential biases of the SSCI and its impact factors are identified. These question the reliability of the SSCI and impact factors for identifying as tools the “best” journals in the marketing field.

The SSCI and its impact factors may cause both “win‐win” and “win‐lose” situations in and between stakeholders of the scholarly communities of the marketing discipline worldwide. The question is raised whether there may be a situation of the “prisoner's dilemma”.

The SSCI and its impact factors are gaining terrain and acknowledgement in scholarly marketing communities worldwide. This raises the crucial question of whether or not the SSCI and its impact factors will benefit the scholarly communities of the marketing discipline worldwide in the long‐term perspective.

A principal argument brought up for further debate is how the increasing acknowledgement and applications of the SSCI and its impact factors may influence the marketing discipline and its scholarly communities worldwide as a whole. Another principal argument brought up for further debate is that the current algorithm that underpins the impact factors of the SSCI may be affected, influenced (and at worst manipulated) in the self‐interest of the journal publishers, the editors and the editorial boards. Authors may also feel the pressure to match perceived expectations and potential requirements in their own self‐interest.

The purpose of this paper is to select the main impact factors of environment change automatically and identify and analyze the potential environmental impact factors with time delay by computer simulation, analyzing the impact rate of environmental impact factors. Then, the environmental impact factors analysis decision support system based on self‐organizing data mining model is designed.

Applying data mining methods in the analysis and decision making of regional environmental impact factors will have broad perspective. Self‐organization data mining is a new modeling method of complex systems modeling with strong modeling capability. It was first presented by A.G. Ivakhnenko, based on the principle of self‐organization of biological cybernetics and Kolmogoorov‐Gabor polynomial function. In this paper, the impact factors of regional environment quality evolution based on self‐organization data mining method is studied, selecting the main impact factors of environment change automatically by computer simulation, analyzing the impact contribution rate of environmental impact factors.

The environmental impact factors analysis decision support system based on self‐organizing data mining model is designed.

Accessibility and availability of data are the main limitations affecting which model will be applied.

The paper has important theoretical and practical significance for the sustainable development of regional environment, resource, economy system and the constitution of environmental protection and management measures.

This paper not only exploits new application domains of self‐organization data mining, but also explores new ways for regional environment impact factors analysis.

This study distinguishes the academic influence of different papers published in journals of the same subject or field based on the modification of the journal impact factor.

Taking SSCI journals in library and information science (LIS) as the research object, the authors first explore the skewness degree of the citation distribution of journal articles. Then, we define the paper citation ratio as the weight of impact factor to modify the journal impact factor for the evaluation of papers, namely the weighted impact factor. The authors further explore the feasibility of the weighted impact factor in evaluating papers.

The research results show that different types of skewness exist in the citation distribution of journal papers. Particularly, 94% of journal paper citations are highly skewed, while the rest are moderately skewed. The weighted impact factor has a closer correlation with the citation frequency of papers than the journal impact factor. It resolves the issue that the journal impact factor tends to exaggerate the influence of low-cited papers in journals with high impact factors or weaken the influence of high-cited papers in journals with low impact factors.

The weighted impact factor is constructed based on the skewness of the citation distribution of journal articles. It provides a new method to distinguish the academic influence of different papers published in journals of the same subject or field, then avoids the situation that papers published in the same journal having the same academic impact.

This paper aims to document the proliferating range of alternatives to the impact factor that have arisen within the past five years, coincident with the increased prominence of open access publishing.

This paper offers an overview of the history of the impact factor as: a measure for scholarly merit; a summary of frequent criticisms of the impact factor's calculation and usage; and a framework for understanding some of the leading alternatives to the impact factor.

This paper identifies five categories of alternatives to the impact factor: measures that build upon the same data that informs the impact factor; measures that refine impact factor data with “page rank” indices that weight electronic resources or web sites through the number of resources that link to them; measures of article downloads and other usage factors; recommender systems, in which individual scholars rate the value of articles and a group's evaluations pool together collectively; and ambitious measures that attempt to encompass the interactions and influence of all inputs in the scholarly communications system.

Librarians can utilize the measures described in this paper to support more robust collection development than is possible through reliance on the impact factor alone.

During the past decades, journal impact data obtained from the Journal Citation Reports (JCR) have gained relevance in library management, research management and research evaluation. Hence, both information scientists and bibliometricians share the responsibility towards the users of the JCR to analyse the reliability and validity of its measures thoroughly, to indicate pitfalls and to suggest possible improvements. In this article, ageing patterns are examined in ‘formal’ use or impact of all scientific journals processed for the Science Citation Index (SCI) during 1981‐1995. A new classification system of journals in terms of their ageing characteristics is introduced. This system has been applied to as many as 3,098 journals covered by the Science Citation Index. Following an earlier suggestion by Glnzel and Schoepflin, a maturing and a decline phase are distinguished. From an analysis across all subfields it has been concluded that ageing characteristics are primarily specific to the individual journal rather than to the subfield, while the distribution of journals in terms of slowly or rapidly maturing or declining types is specific to the subfield. It is shown that the cited half life (CHL), printed in the JCR, is an inappropriate measure of decline of journal impact. Following earlier work by Line and others, a more adequate parameter of decline is calculated taking into account the size of annual volumes during a range of fifteen years. For 76 per cent of SCI journals the relative difference between this new parameter and the ISI CHL exceeds 5 per cent. The current JCR journal impact factor is proven to be biased towards journals revealing a rapid maturing and decline in impact. Therefore, a longer term impact factor is proposed, as well as a normalised impact statistic, taking into account citation characteristics of the research subfield covered by a journal and the type of documents published in it. When these new measures are combined with the proposed ageing classification system, they provide a significantly improved picture of a journal‘s impact to that obtained from the JCR.

The purpose of this paper is to examine the effects of the use of the citation‐based journal impact factor for evaluative purposes upon the behaviour of authors and editors. It seeks to give a critical examination of a number of claims as regards the manipulability of this indicator on the basis of an empirical analysis of publication and referencing practices of authors and journal editors

The paper describes mechanisms that may affect the numerical values of journal impact factors. It also analyses general, “macro” patterns in large samples of journals in order to obtain indications of the extent to which such mechanisms are actually applied on a large scale. Finally it presents case studies of particular science journals in order to illustrate what their effects may be in individual cases.

The paper shows that the commonly used journal impact factor can to some extent be relatively easily manipulated. It discusses several types of strategic editorial behaviour, and presents cases in which journal impact factors were – intentionally or otherwise – affected by particular editorial strategies. These findings lead to the conclusion that one must be most careful in interpreting and using journal impact factors, and that authors, editors and policy makers must be aware of their potential manipulability. They also show that some mechanisms occur as of yet rather infrequently, while for others it is most difficult if not impossible to assess empirically how often they are actually applied. If their frequency of occurrence increases, one should come to the conclusion that the impact of impact factors is decreasing.

The paper systematically describes a number of claims about the manipulability of journal impact factors that are often based on “informal” or even anecdotal evidences and illustrates how these claims can be further examined in thorough empirical research of large data samples.

This communication describes the building of a list of constructed impact factors (CIF) for biomedical journals not included in the 1996 editions of the Journal Citation Reports (JCR). The online retrieval from the host DIMDI of the data needed for impact factor calculation is described in detail. At present, the CIF list comprises 338 titles. The top 100 (ranked according to their CIFs) are shown. The complete list is available via the World Wide Web at the URL: http://www.medizin.fu‐berlin.de/medbib/CIF/cif.html. The possible usefulness of constructed impact factors for citation and evaluation studies is discussed.