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This paper aims to identify the opinions of undergraduate students on the importance of internet‐based information sources when they undertake academic tasks.

Based on a set of identified typical academic tasks for undergraduate students, three research questions were designed around the students' usage and views of information resources for completing these tasks. Web‐accessible questionnaires were used to collect data from participants in two universities in the USA and China, and the data were analyzed using quantitative methods, which included several statistic methods.

The results confirm that undergraduate students use different information resources for various academic tasks. In their tasks, online electronic resources including search engines are the most commonly used resources, particularly for complex academic tasks. Social networking sites are not used for the students' individual academic tasks, and traditional resources still play equal or more important roles in certain specific academic tasks. Students in collaborative tasks look for resources that make it easy to share documents. Participants from the two countries also exhibit interesting and important differences in their usage of information resources.

This study examines undergraduate students' usages and views of different information resources in their various academic tasks, and pays special attention to the impacts of being from their different countries. The study also considers both students' individual academic tasks and collaborative tasks. This study is an invaluable addition to the information seeking behaviour literature.

With the vast amount of multilingual information available online, it becomes increasingly critical for libraries to use various multilingual information access techniques in order to effectively support patrons' online information requests. However, this is still a relatively under‐explored area. This paper aims to study the effectiveness and the adoptability of query expansion and translation enhancement in the context of interactive multilingual information access.

Relying on an interactive multilingual information access system called ICE‐TEA, the authors conducted a controlled experiment (English‐to‐Chinese translation) involving human subjects to assess the retrieval effectiveness, analyzed the collected search logs to examine users' behavior, and employed pre‐ and post‐questionnaires to obtain users' opinions about the system.

The results confirm that significant improvement in retrieval effectiveness can be achieved by combining query expansion with translation enhancement (as compared to a case when there is no relevance feedback). However, users' ability to understand, interact with and even perceive the complex process of searches involving the combination of query expansion and translation enhancement may greatly impact the effectiveness of the techniques. The results also confirm that human‐generated queries were short queries, which calls for careful consideration of how longer queries perform in real search because many search engines rely on longer and more complex queries.

This study examines two important relevance feedback techniques in the context of human‐involved multilingual information access. This study is a valuable addition to the information seeking behaviour literature.

The purpose of this study is to use a steady-state model structure to investigate earnings management (EM) theoretically in the context of different expense theories. Empirically, the objective is to apply the theoretical model to investigate the implicit choice of expense theories for reporting expenses. The study aims to present a new approach to analyze EM.

The study makes use of ten-year time-series data originally from 1,015 Finnish public and private firms to estimate the parameters of the steady-state model, and to investigate which expense theories the firms implicitly follow in financial reporting. The parameters are estimated using the restricted least squares regression method. The final sample included data from 631 firms fulfilling restrictions for the consistency of estimates.

The paper provides empirical insights about expense theories that Finnish firms implicitly follow in financial reporting. Evidence shows that the reporting of expenses mainly follows the units-of-revenue and the rate-of-return theories. Only a small number of firms follow the interest expense theory.

The study is based on a steady-state approach, and therefore, the research results may lack generalizability as only 62% of the original sample firms obtained consistent estimates. Therefore, researchers are encouraged to use more general models for further theoretical and empirical work.

The paper includes implications for a new approach to EM. It also gives implications how to analyze different expense theories in the context of EM both theoretically and empirically.

This paper develops a new approach to investigate EM.

This article presents a novel user‐oriented interface for generalised informetric analysis and demonstrates how informetric calculations can easily and declaratively be specified through advanced data modelling techniques. The interface is declarative and at a high level. Therefore it is easy to use, flexible and extensible. It enables end users to perform basic informetric ad hoc calculations easily and often with much less effort than in contemporary online retrieval systems. It also provides several fruitful generalisations of typical informetric measurements like impact factors. These are based on substituting traditional foci of analysis, for instance journals, by other object types, such as authors, organisations or countries. In the interface, bibliographic data are modelled as complex objects (non‐first normal form relations) and terminological and citation networks involving transitive relationships are modelled as binary relations for deductive processing. The interface is flexible, because it makes it easy to switch focus between various object types for informetric calculations, e.g. from authors to institutions. Moreover, it is demonstrated that all informetric data can easily be broken down by criteria that foster advanced analysis, e.g. by years or content‐bearing attributes. Such modelling allows flexible data aggregation along many dimensions. These salient features emerge from the query interface‘s general data restructuring and aggregation capabilities combined with transitive processing capabilities. The features are illustrated by means of sample queries and results in the article.

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.

The increasing flood of documentary information through the Internet and other information sources challenges the developers of information retrieval systems. It is not enough that an IR system is able to make a distinction between relevant and non‐relevant documents. The reduction of information overload requires that IR systems provide the capability of screening the most valuable documents out of the mass of potentially or marginally relevant documents. This paper introduces a new concept‐based method to analyse the text characteristics of documents at varying relevance levels. The results of the document analysis were applied in an experiment on query expansion (QE) in a probabilistic IR system. Statistical differences in textual characteristics of highly relevant and less relevant documents were investigated by applying a facet analysis technique. In highly relevant documents a larger number of aspects of the request were discussed, searchable expressions for the aspects were distributed over a larger set of text paragraphs, and a larger set of unique expressions were used per aspect than in marginally relevant documents. A query expansion experiment verified that the findings of the text analysis can be exploited in formulating more effective queries for best match retrieval in the search for highly relevant documents. The results revealed that expanded queries with concept‐based structures performed better than unexpanded queries or Ñnatural languageÒ queries. Further, it was shown that highly relevant documents benefit essentially more from the concept‐based QE in ranking than marginally relevant documents.

This article investigates how consistent different newspapers are in their choice of words when writing about the same news events. News articles on the same news events were taken from three Finnish newspapers and compared in regard to their central concepts and words representing the concepts in the news texts. Consistency figures were calculated for each set of three articles (the total number of sets was sixty). Inconsistency in words and concepts was found between news articles from different newspapers. The mean value of consistency calculated on the basis of words was 65 per cent; this however depended on the article length. For short news wires consistency was 83 per cent while for long articles it was only 47 per cent. At the concept level, consistency was considerably higher, ranging from 92 per cent to 97 per cent between short and long articles. The articles also represented three categories of topic (event, process and opinion). Statistically significant differences in consistency were found in regard to length but not in regard to the categories of topic. We argue that the expression inconsistency is a clear sign of a retrieval problem and that query expansion based on semantic relationships can significantly improve retrieval performance on free‐text sources.

The purpose of this study is to introduce a matching function approach to analyze matching in financial reporting.

The matching function is first analyzed analytically. It is specified as a multiplicative Cobb-Douglas-type function of three categories of expenses (labor expense, material expense and depreciation). The specified matching function is solved by the generalized reduced gradient method (GRG) for 10-year time series from 8,226 Finnish firms. The coefficient of determination of the logarithmic model (CODL) is compared with the linear revenue-expense correlation coefficient (REC) that is generally used in previous studies.

Empirical evidence showed that REC is outperformed by CODL. CODL was found independent of or weakly negatively dependent on the matching elasticity of labor expense, positively dependent on the material expense elasticity and negatively dependent on depreciation elasticity. Therefore, the differences in matching accuracy between industries emphasizing different expense categories are significant.

The matching function is a general approach to assess the matching accuracy but it is in this study specified multiplicatively for three categories of expenses. Moreover, only one algorithm is tested in the empirical estimation of the function. The analysis is concentrated on ten-year time-series of a limited sample of Finnish firms.

The matching function approach provides a large set of important information for considering the matching process in practice. It can prove a useful method also to accounting standard-setters and other specialists such as managers, consultants and auditors.

This study is the first study to apply the new matching function approach.

It is generally recognised that numeric databases (NDBs) have become essential in information retrieval (IR). NDBs differ from traditional bibliographic databases (BDBs) with respect to their content, structural complexity, data manipulation capabilities, and the complexity of the user interfaces and user charging schemes. Recent trends in user interfaces and user charging for all online IR are towards charging for the information actually retrieved from the database rather than for the connect time. However, the viability of such charging schemes depends on the user's ability to estimate the charges in advance, during the query negotiation phase. This paper presents a systematic and general method for estimating user charges for retrieved information in advance, in the context of NDBs based on the relational data model (RDM). The method accepts relational algebra (RA) queries of any complexity, estimates the sizes of their results, and charges for them on the basis of the descriptions of the original database files. The method is a novel one and is directly applicable to any RDM‐based NDB. Tools based on the method are required in the query interfaces to NDBs in order to make query formulation and reformulation meaningful.

This study examines research methods utilized in five practitioner-oriented research journals – College and Research Libraries, Information Technology and Libraries, Journal of the Medical Library Association, Library Resources and Technical Services and Reference and User Services Quarterly. The study fills gaps identified in existing content analyses of methods in practitioner-based LIS research publications.

Based on analysis standards and coding schemes supplied by the studies of Kalervo Jarvelin and Pertti Vakkari, as well as Heting Chu, this study identifies the primary research method utilized in 6,387 articles published in these five journals from 1980 to 2019. Trends in the frequencies with which various research methods were used are identified and presented using a series of visualizations.

Significant shifts have occurred in the research methods used by articles in these practitioner-based journals over the past four decades. Notably, the proportion of case studies has dropped substantially, particularly among College and Research Libraries and Journal of the Medical Library Association articles. Diversity of research methods utilized in articles has increased over time, with College and Research Libraries, in particular, having a significant proportion of articles in recent years that employ data analytic or qualitative approaches.

While similar approaches have been used to examine research methods among other LIS journals, this study is the first to focus primarily on practitioner-based journals and document continuous change (as opposed to sampling a few years) over an extended, 40-year period.