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This study aims to explore and clarify the mechanism by which recognition-based heuristic biases influence the investment decision-making and performance of individual investors, with the mediating role of fundamental and technical anomalies.

The deductive approach was used, as the research is based on behavioral finance's theoretical framework. A questionnaire and cross-sectional design were employed for data collection from the sample of 323 individual investors trading on the Pakistan Stock Exchange (PSX). Hypotheses were tested through the structural equation modeling (SEM) technique.

The article provides further insights into the relationship between recognition-based heuristic-driven biases and investment management activities. The results suggest that recognition-based heuristic-driven biases have a markedly positive influence on investment decision-making and negatively influence the investment performance of individual investors. The results also suggest that fundamental and technical anomalies mediate the relationships between the recognition-based heuristic-driven biases on the one hand and investment management activities on the other.

The results of the study suggested that investment management activities that rely on recognition-based heuristics would not result in better returns to investors. The article encourages investors to base decisions on investors' financial capability and experience levels and to avoid relying on recognition-based heuristics when making decisions related to investment management activities. The results provides awareness and understanding of recognition-based heuristic-driven biases in investment management activities, which could be very useful for decision-makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating the expensive errors that occur due to recognition-based heuristic-driven biases.

The current study is the first to focus on links recognition-based heuristic-driven biases, fundamental and technical anomalies, investment decision-making and performance of individual investors. This article enhanced the understanding of the role that recognition-based heuristic-driven biases plays in investment management. More importantly, the study went some way toward enhancing understanding of behavioral aspects and the aspects' influence on investment decision-making and performance in an emerging market.

The loans control system used at AWRE is described in detail. Punched cards produced in the library are used as input to a computer to provide the necessary control tools: reminders, borrower, and date listings. Details are given of a method of using the computer to perform a sort in UDC number order. Plans to integrate and mechanize the cataloguing and ordering operations using an IBM 870 system and an IBM 360/30 computer are also described.

After considering the search process and functions of index entries, a classification of entry types is offered, based on index term context, predominant term order, and between‐term function words. Then a multiple entry generation scheme is described, comprising rules for term manipulation, input and output. After discussing access points and cross reference measures, a preliminary linguistic analysis is given, showing links with psycholinguistics. The study forms the basis of a current laboratory investigation (EPSILON) into a number of entry types.

This program maintains two subject index files on magnetic tape, one for the main subject index and one for the press‐cuttings subject index. Although these are two distinct indexes, they are held physically as one file on the tape with all press‐cuttings items marked to distinguish them from the normal items. The complete combined file is held twice on the tape, once in alphabetical subject order and once in classification number order.

The following classified, annotated list of titles is intended to provide reference librarians with a current checklist of new reference books, and is designed to supplement the RSR review column, “Recent Reference Books,” by Frances Neel Cheney. “Reference Books in Print” includes all additional books received prior to the inclusion deadline established for this issue. Appearance in this column does not preclude a later review in RSR. Publishers are urged to send a copy of all new reference books directly to RSR as soon as published, for immediate listing in “Reference Books in Print.” Reference books with imprints older than two years will not be included (with the exception of current reprints or older books newly acquired for distribution by another publisher). The column shall also occasionally include library science or other library related publications of other than a reference character.

Classification is so fundamental and pervasive an activity that care is needed to define its scope when discussing a particular application, such as information retrieval.

EDITORIAL It's unfortunate that my first words as editor of VINE have to be the bad news that it is no longer to be available free of charge. In the accompanying note I have gone into detail about why this is so, and all I want to do here is to say that I hope the £10 a year won't deter too many people from reading VINE.

Modelling users' interactions online is envisaged to allow developers to increase the usability of online systems and will aid system developers in building better systems to meet users' needs, hereby creating better system design processes. This paper aims to investigate this issue.

The normative task model that was developed in this paper was created through an expert review of 14 online grocery stores, using a reverse engineering technique to model the features of the stores' ordering process.

The research identified three main areas of user experience when undertaking the process of adding a product to an online trolley: attempting to retrieve the product, receiving the results of the retrieval attempt, and adding the product to the trolley. These three classifications were used as the basis for an analysis of errors.

The findings present a model that can be used to further understand the processes of customers as they engage in an online grocery shopping visit. The normative task model presented is expected to help in the future design of online grocery stores by identifying the possible errors that users can encounter, and methods to reduce the occurrence of these errors. Errors are one area that traditional task‐modelling processes ignore, due to their focus on successful processes.

This paper presents the innovative process of the development of a normative task model for modelling user interactions when using online grocery stores.

Several bibliographical citation systems are in regular use in scholarly literature, associated with various intellectual disciplines. The aim of this paper is to document an analysis of their designs in the biosciences in order to construct a classification and to assess their comparative effectiveness for information transfer.

A historical survey of communications between scholars, including the reasons why authors cite others' works, was completed. The development of citation systems, specifically the Harvard system and various numeric systems, was traced, following which a universal classification with a new descriptive terminology was constructed.

Citation systems are defined herein as direct (with citation and reference together in the text) or indirect (with citation within the text, and reference outside the text). Direct systems may be described as implicit (the Linnaean style with abbreviated, undated, conceptual reference) or explicit (with full, dated, bibliographical reference). All indirect systems are explicit: the text citation (the referens) may be alphabetic, symbolic, numeric or alphanumeric and the reference (the referendum) may be a marginal note, footnote or end reference. A survey of citation systems in 101 bioscience journals is presented. Within indirect systems, most biomedical journals use a numeric system, but most veterinary, zoological and general biological journals use the Harvard system, which is considered herein to be the most effective for information transfer.

No philosophical analysis of citation systems appears to have been carried out before. Based upon historical, conceptual and logical aspects, a robust universal classification with a new descriptive terminology is presented to facilitate the unambiguous discussion of the principles and designs of citation systems. The classification and terminology are applicable to citation systems in any discipline.

This paper aims to propose a brand new ontology development methodology, called Yet Another Methodology for Ontology (YAMO) and demonstrate, step by step, the building of a formally defined large-scale faceted ontology for food.

YAMO is motivated by facet analysis and an analytico-synthetic classification approach. The approach ensures quality of the system precisely; it makes the system flexible, hospitable, extensible, sturdy, dense and complete. YAMO consists of two-way approaches: top-down and bottom-up. Based on YAMO, domain food, formally defined as large-scale ontology, is designed. To design the ontology and to define the scope and boundary of the domain, a group of people were interviewed to get a practical overview, which provided more insight to the theoretical understanding of the domain.

The result obtained from evaluating the ontology is a very impressive one. Based on the study, it was found that 94 per cent of the user’s queries were successfully met. This shows the efficiency and effectiveness of the YAMO methodology. An evaluator opined that the ontology is very deep and exhaustive.

The authors envision that the current work will have great implications on ontology developers and practitioners. YAMO will allow ontologists to construct a very deep, high-quality and large-scale ontology.

This paper illustrates a brand new ontology development methodology and demonstrates how the methodology can be applied to build a large-scale high-quality domain ontology.