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Replication is a primary self-correction device in science. In this paper, we have two aims: to examine how and when the results of replications are used in management and organization research and to use the results of this examination to offer guidelines for improving the self-correction process.

Study 1 analyzes co-citation patterns for 135 original-replication pairs to assess the direct impact of replications, specifically examining how often and when a replication study is co-cited with its original. In Study 2, a similar design is employed to measure the indirect impact of replications by assessing how often and when a meta-analysis that includes a replication of the original study is co-cited with the original study.

Study 1 reveals, among other things, that a huge majority (92%) of sources that cite the original study fail to co-cite a replication study, thus calling into question the impact of replications in our field. Study 2 shows that the indirect impact of replications through meta-analyses is likewise minimal. However, our analyses also show that replications published in the same journal that carried the original study and authored by teams including the authors of the original study are more likely to be co-cited, and that articles in higher-ranking journals are more likely to co-cite replications.

We use our results to formulate recommendations that would streamline the self-correction process in management research at the author-, reviewer- and journal-level. Our recommendations would create incentives to make replication attempts more common, while also increasing the likelihood that these attempts are targeted at the most relevant original studies.

The purpose of this paper is to find out which research topics and methods in information science (IS) articles are used in other disciplines as indicated by citations.

The study analyzes citations to articles in IS published in 31 scholarly IS journals in 2015. The study employs content analysis of articles published in 2015 receiving citations from publication venues representing IS and other disciplines in the citation window 2015–2021. The unit of analysis is the article-citing discipline pair. The data set consists of 1178 IS articles cited altogether 25 K times through 5 K publication venues. Each citation is seen as a contribution to the citing document’s discipline by the cited article, which represents some IS subareas and methodologies, and the author team's disciplinary composition, which is inferred from the authors’ affiliations.

The results show that the citation profiles of disciplines vary depending on research topics, methods and author disciplines. Disciplines external to IS are typically cited in IS articles authored by scholars with the same background. Thus, the export of ideas from IS to other disciplines is evidently smaller than the earlier findings claim. IS should not be credited for contributions by other disciplines published in IS literature.

This study is the first to analyze which research topics and methods in the articles of IS are of use in other disciplines as indicated by citations.

Technology acquisition is a common phenomenon of acquiring external knowledge, but we have a limited understanding of conditions in which the acquirer integrates the target or not. On one hand, the acquirer may have a policy to integrate the target to benefit from its prior knowledge. On the other hand, the target may face challenges in continuing its knowledge creation and the acquirer may want to provide it autonomy to not disrupt it. This paper aims to identify conditions in which targets tend to be less integrated after acquisitions, allowing them to maintain more autonomy and contribute more to knowledge creation.

We test our arguments in the empirical setting of the global biopharmaceutical industry using a difference-in-difference approach on a longitudinal dataset of matched patents. We examine self-cites received by patents belonging to acquirers and the targets before and after the acquisitions.

We find that, on average, the targets’ prior patents do not receive more self-cites after the acquisition. We conclude that this is because their R&D activities are disrupted, suggesting a higher level of post-acquisition integration. However, more nuanced findings reveal that it may not be the case all the time. When the target has more research experience, is international or is specialized in complementary technologies, prior patents of targets continue to receive more self-cites after the acquisition. It indicates that the targets in such conditions continue knowledge creation, suggesting a lower level of post-acquisition integration.

Our findings contribute to post-acquisition integration research. While post-acquisition integration downside is common, we present conditions in which such a downside may be less likely. We highlight that the context of an acquisition may be an important determinant of the extent of integration of the target. Moreover, we supplement the integration research (cultural, structural and human resource and leadership perspectives of integration) by adding a knowledge-based perspective to it. Such dynamics have important implications for acquirers and targets in deriving value from the acquisition.

Citation searching has been available for decades, although in a limited form. This article discusses the advantages and limitations of searching by cited references, and also some alternatives in searching for cited references, before presenting a case study involving citation searching in full‐text indexes.

The purpose of this paper is to discuss databases with cited references.

The paper considers the dimensions of cited reference enhanced database subsets.

The typical database has the ski slope shape, as there is a fairly steady, gradual growth in the yearly number of records added. This is not true for the shape of the cited references subset, as in most databases cited references have been added to the records only for the past few years.

There are many features which are specific to cited references, and thus the traditional bibliographic database design is just not sufficient.

The paper examines the issues surrounding cited reference enhanced database subsets.

This study aims to explore the journal bibliometric characteristics of the Journal of Documentation (JOD) and the subject relationship with other disciplines by citation analysis.

The citation data were drawn from references of each article of JOD during 1998 and 2008. Ulrich's Periodicals Directory, Library of Congress Subject Heading, retrieved from the WorldCat and LISA database were used to identify the main class, subclass and subject of cited journals and books.

The results of this study revealed that journal articles are the most cited document, followed by books and book chapters, electronic resources, and conference proceedings, respectively. The three main classes of cited journals in JOD papers are library science, science, and social sciences. The three subclasses of non‐LIS journals that were highly cited in JOD papers are Science, “Mathematics. Computer science”, and “Industries. Land use. Labor”. The three highly cited subjects of library and information science journals encompass searching, information work, and online information retrieval. The most cited main class of books in JOD papers is library and information science, followed by social sciences, science, “Philosophy. Psychology. Religion.” The three highly cited subclasses of books in JOD papers are “Books (General). Writing. Paleography. Book industries and trade. Libraries. Bibliography,” “Philology and linguistics,” and Science, and the most cited subject of books is information storage and retrieval systems.

Results for the present research found that information science, as represented by JOD, is a developing discipline with an expanding literature relating to multiple subject areas.

This paper argues for precision in citing. It proposes an approach to citation analysis that would encourage that precision, and contrasts this approach with one based on inferred motivations for citing. It argues that it is misguided to classify citation‐signallers by the nature of the motivations inferred to underlie their use, the inference process being both philosophically and methodologically less satisfactory than the approach this paper proposes; and that, moreover, it is unnecessary, since certain formal characteristics of citation‐signallers of themselves provide ample means of classification.

The purpose of this paper is to suggest an alternative to the widely used Times Cited criterion for analysing citation networks. The approach involves taking account of the natures of the papers that cite a given paper, so as to differentiate between papers that attract the same number of citations.

ArticleRank is an algorithm that has been derived from Google's PageRank algorithm to measure the influence of journal articles. ArticleRank is applied to two datasets – a citation network based on an early paper on webometrics, and a self‐citation network based on the 19 most cited papers in the Journal of Documentation – using citation data taken from the Web of Knowledge database.

ArticleRank values provide a different ranking of a set of papers from that provided by the corresponding Times Cited values, and overcomes the inability of the latter to differentiate between papers with the same numbers of citations. The difference in rankings between Times Cited and ArticleRank is greatest for the most heavily cited articles in a dataset.

This is a novel application of the PageRank algorithm.

This paper examines the diffusion of Jerry Hausman's econometric ideas using citation counts, citing authors, and source journals of his most referenced citers. Bibliographic information and citation counts of references to econometrics papers were retrieved from Thomson Reuters Web of Science and analyzed to determine the various ways in which Hausman's ideas have spread in econometrics and related disciplines. Econometric growth analysis (Gompertz and logistic functions) is used to measure the diffusion of his contributions. This analysis reveals that the diffusion of Hausman's ideas has been pervasive over time and disciplines. For example, his seminal 1978 paper continues to be strongly cited along exponential growth with total cites mainly in econometrics and other fields such as administrative management, human resources, and psychology. Some of the more recent papers have a growth pattern that resembles that of the 1978 paper. This leads us to conclude that Hausman's econometric contributions will continue to diffuse in years to come. It was also found that five journals have published the bulk of the top cited papers that list Hausman as a reference, namely, Econometrica, Journal of Econometrics, Review of Economic Studies, Academy of Management Journal, and the Journal of Economic Literature. “Specification tests in econometrics” is Hausman's dominant contribution in this citation analysis. We found no previous research on the econometric modeling of citation counts as done in this paper. Thus, we expect to stimulate methodological improvements in future work.

This study explored the influence of Dervin’s sensemaking methodology (SMM).

Citation context analysis was used to identify the most influential SMM concepts in 948 articles citing 34 SMM-related studies by Dervin that were published between 1983 and 2017. Moreover, the bibliometric method and content analysis were incorporated to examine the disciplines and research topics influenced by the SMM-related studies and the role of cited content in SMM-related studies.

The influence of SMM is concentrated in information behavior research in the field of library and information science (LIS). The 1992 book chapter From the mind’s eye of the user was most frequently cited, followed by the first SMM study from 1983; 14 of the 18 content categories were relevant to SMM. “Sensemaking,” at the core of SMM, was the most influential cited concept, primarily cited from the 1983 SMM-related study. Although the SMM was developed as a research method, it has not been primarily applied to design research methods in other studies.

This study explored the interdisciplinary influence of Dervin’s SMM from several aspects and demonstrated the complex information dynamics between SMM-related works and citing articles.