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The study focused on online public access catalog (OPAC) users’ cross-device search behavior. The purpose of this paper is to understand the characteristics of cross-device OPAC searches, and to identify query reformulation (QR) patterns during device transitions.

The transaction log from a university library, spanning six months, was used to conduct the quantitative analysis. The query vocabulary richness, which refers to the average number of unique words each query contains in a search session, can evaluate query diversity, and contribute to the analysis of QR.

The results show that PC-PC transition is the most important pattern of device transition. The time interval of device transition was different to the time interval of transitions in web searches. Short device transitions mainly occurred in daytime, and the number of transitions that occurred in less than one minute was higher than on the web. Searches for Industry and Technology triggered the most device transitions, and the users tended to choose the same search field. In addition, the authors made a detailed analysis of the reasons for same-type device transitions and different-type device transitions. Furthermore, the authors focused on the characteristics of adjacent QR patterns. The authors not only refined the concept of cross-device to include the same-type device transition, but also summarized the characteristics of the cross-device QR patterns, which can be used to predict post-switch queries.

This study extends research into cross-device interaction and cross-device search to the domain of digital library research. The authors also introduced QR perspective on cross-device interaction on OPAC.

This paper discusses the differences in search pattern transitions for mobile phone, tablet and desktop devices by mining the transaction log data of a library online public access catalogue (OPAC). We aimed to analyze the impacts of different devices on user search behavior and provide constructive suggestions for the development of library OPACs on different devices.

Based on transaction logs which are 9 GB in size and contain 16,140,509 records of a university library OPAC, statistics and clustering were used to analyze the differences in search pattern transitions on different devices in terms of two aspects: search field transition patterns and query reformulation patterns.

Search field transition patterns are influenced by the input function and user interfaces of different devices. As reformulation times increase, the differences between query reformulation patterns among different devices decrease.

Mobile-side libraries need to optimize user interfaces, for example by setting web page labels and improving input capabilities. Desk-side libraries can add more suggestive content on the interface.

Unlike previous studies, which have analyzed web search, this paper focuses on library OPAC search. The search function of mobile phones, tablets and desktops were found to be asymptotic, which was a good illustration of how devices have a large impact on user search behavior.

With access to the large-scale search data from Rightmove plc, the paper firstly indicated the possibility of using user-generated data from online property portals to predict housing market activities and secondly embraced a GIS approach to explore what people search for housing and what they chose and investigated the issue of mismatch between search patterns and revealed patterns. Based on the analysis, the paper contributes a visual GIS-based approach which may help planners and designers to make more informed decisions related to new housing supply, particularly where to build, what to build and how many to build.

The paper used the 2013 housing search data from Rightmove and the 2013 price data from Land Registry with transactions made after the search period and embraced a GIS approach to explore the potential housing demand patterns and the mismatch between searches and sales. In the analysis, the paper employed the K-means approach to group prices into five levels and used GIS software to draw maps based on these price levels. The paper also employed a simple analysis of linear regression based on the coefficient of determination to investigate the relationship between online property views and values of house sales.

The result indicated the strong relationship between online property views and the values of house sales, implying the possibility of using search data from online property portals to predict housing market activities. It then explore the spatial housing demand patterns based on searches and showed a mismatch between the spatial patterns of housing search and actual moves across submarkets. The findings may not be very surprising but the main objective of the paper is to open up a potentially useful methodological approach which could be extended in future research.

It is important to identify search patterns from people who search with the intention to buy houses and from people who search with no intention to purchase properties. Rightmove data do not adequately represent housing search activity, and therefore more attention should be paid to this issue. The analysis of housing search helps us have a better understanding of households' preferences to better estimate housing demand and develop search-based prediction models. It also helps us identify spatial and structural submarkets and examine the mismatches between current housing stock and housing demand in submarkets.

The GIS approach in this paper may help planners and designers better allocate land resources for new housing supply based on households' spatial and structural preferences by identifying high and low demand areas with high searches relative to low housing stocks. Furthermore, the analysis of housing search patterns helps identify areas with latent demand, and when combined with the analysis of transaction patterns, it is possible to realise the areas with a lack of housing supply relative to excess demand or a lack of latent demand relative to the housing stock.

The paper proves the usefulness of a GIS approach to investigate households' preferences and aspirations through search data from online property portals. The contribution of the paper is the visual GIS-based approach, and based on this approach the paper fills the international knowledge gap in exploring effective approaches to analysing user-generated search data and market outcome data in combination.

In order to test the impact of system and domain knowledge on search behaviour in an online catalogue, an experiment was set up in a university library where students from three specialisation areas performed a number of search tasks in the online catalogue. The subjects differed in the amount of domain and system knowledge. In two sessions the subjects performed searches inside and outside their ‘own’ domain. During the first session all subjects had little system knowledge. After the first session, half of the group received instruction in catalogue use and the other half did not. To observe whether the induced differences in system knowledge had effects on the search performance, a second session was carried out. Subjects' search behaviour was videotaped and their comments recorded (they were encouraged to think aloud). Results show the the amount of system knowledge had a significant effect on search time as well as on the number of search patterns observed. Regarding domain knowledge, only one out of the six analyses concerning search time or the amount of patterns yielded a significant effect. A possible explanation for this result could be the questionable validity of the criteria used to distinguish between known and unknown domains. The difference in knowledge regarding familiar and unfamiliar domains is not as large as had been expected. The notion of end‐users displaying habitual modes of behaviour is given considerable support by the data. This is reflected by the limited number of patterns observed.

This study aims to determine the antecedents and consequences of information source choice to support a purchase decision for services high in experience attributes.

The authors conduct two studies to test their propositions. Study 1 is a single-category application using data from a national survey of 974 consumers who recently made a hotel-stay purchase/reservation. Correspondence analysis was used to identify search patterns, and regression analysis was used to identify their antecedents and influence on search outcomes. Study 2 is a cross-category study using data from a survey of 422 MTurk respondents reporting on search processes across six different services contexts, including hotel reservations. In this study, the authors seek generalization of their results to other services categories.

The authors identify four dimensions that characterize what information sources consumers, on average, use together when purchasing services. It is found that loyalty program membership and consistency in service delivery across a brand’s outlets for the brands in a consumer’s evoked set are important determinants of search patterns. Search patterns partially mediate the impact of consumer characteristics, choice context and choice set characteristics on search effort and, ultimately, on price paid.

An understanding of the factors that are associated with consumers’ choices of information sources and whether these choices are systematically related to search outcomes has implications for market segmentation and for marketers’ initiatives with respect to what information content to emphasize across sources.

The contribution is an understanding of the antecedents and consequences of consumer search patterns – and what information sources consumers tend to use together, considering the diversity of both internet and non-internet sources. There are limited insights in the services literature regarding how the internet impacts information search processes.

For digital libraries, it is useful to understand how users search in a collection. Investigating search patterns can help them to improve the user interface, collection management and search algorithms. However, search patterns may vary widely in different parts of a collection. The purpose of this paper is to demonstrate how to identify these search patterns within a well-curated historical newspaper collection using the existing metadata.

The authors analyzed search logs combined with metadata records describing the content of the collection, using this metadata to create subsets in the logs corresponding to different parts of the collection.

The study shows that faceted search is more prevalent than non-faceted search in terms of number of unique queries, time spent, clicks and downloads. Distinct search patterns are observed in different parts of the collection, corresponding to historical periods, geographical regions or subject matter.

First, this study provides deeper insights into search behavior at a fine granularity in a historical newspaper collection, by the inclusion of the metadata in the analysis. Second, it demonstrates how to use metadata categorization as a way to analyze distinct search patterns in a collection.

A behavioural approach to information retrieval system design is outlined based on the derivation of a behavioural model of the information seeking patterns of academic social scientists. The information seeking patterns of a variety of academic social scientists were broken down into six characteristics: starting, chaining, browsing, differentiating, monitoring, and extracting. These characteristics constitute the principal generic features of the different individual patterns, and together provide a flexible behavioural model for information retrieval system design. The extent to which these characteristics are available on existing systems is considered, and the requirements for implementing the features on an experimental system are set out.

Purpose – This study develops a theoretical argument that social networks are embedded in the macro-level institutional environment. From the perspective of institutional embeddedness, I investigate the changing patterns and implications of social networks in job search and job earnings after China's overhaul of its employment system in the mid-1990s.Methodology/approach – The empirical evidence is drawn from 2003 Chinese General Social Survey data. I conduct statistical analyses to examine the roles of networks in job search and earning disparity by comparing two groups who obtained the job before and after the emerging labor market in urban China, respectively.Findings –Social networks have become much more popular in job search in the emerging labor market. Use of social networks in job search has also become more differentiated across job positions and employment organizations. While managerial status of the key helper and direct ties yield greater returns to employee earnings, strong indirect ties make less contribution to job earnings in the emerging labor market than that under the state-dominated employment system.Research implications – The findings suggest that we should analyze the concrete institutional environment to appreciate the roles of social networks in job search and social inequality.Originality/value – This study highlights that institutions are the key factor to shape the patterns and significance of social networks. As institutions evolve, network patterns and their significance can change accordingly.

Users' search logs are implicit feedbacks on how searchers interact with online information retrieval (IR) systems. The purpose of this paper is to analyze search query reformulation (SQR) patterns of University of Dar es Salaam remote OPAC users.

Qualitative and quantitative analysis of transaction logs were employed to ascertain the characteristics of search queries and the patterns in which remote OPAC users reformulate their search queries. The study covered a period of six months, commencing from January to June 2019.

A total of 30,474 search hits were submitted by remote OPAC users during the period under study. Individuals from academic and research institutions, computing consortia, and telecommunication companies are the main users of the system. Most of the searches originated from North America and Europe, with few searches coming from China and India. Besides improving search results, SQRs are linked with the existence of multiple information demands as manifested by the use of heterogeneous headwords within individual search episodes.

Data collected covered only six months. Similarly, it was however not possible to analyze users' search query formulation within specific contexts such as task-based information searching.

A query recommendation system should be integrated into the OPAC functionalities to improve users' search experiences. Alternatively, there should be a migration to a new system that offers more advanced search features and functionalities.

The study has contributed new insights in SQR studies particularly on how non-institutional affiliated users translate their information needs into search queries during information searching processes.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2020-0389

This study aims to explore the evidence-based usage patterns of higher education commission (HEC) subscribed e-journal databases in the university digital library used by the scholarly community and the academics’ online searching behaviour at a higher education institution in Pakistan.

The study used an explanatory sequential mixed methods approach. Raw transaction log data were collected for quantitative analysis, and the interview technique was used for qualitative data collection and thematic analysis.

Log analysis revealed that HEC subscribed databases were used significantly, and among those, scholarly databases covering various subjects were more frequently used than subject-specific society-based databases. Furthermore, the users frequently accessed the needed e-journal articles through search engines like Google and Google Scholar, considering them sources of free material instead of the HEC subscribed databases.

It provides practical implications for examining the evidence-based use patterns of e-journal databases. It suggests the need for improving the access management of HEC databases, keeping in view the usage statistics and the demands of the scholars. The study may also help create market venues for the publishers of scholarly databases by offering attractive and economical packages for researchers of various disciplines in developing and underdeveloped countries. The study results also guide the information professionals to arrange orientation and information literacy programs to improve the searching behaviour of their less frequent users and enhance the utilization of these subscribed databases.

The study is part of a PhD project and, to the best of the authors’ knowledge, is the first such work in the context of a developing country like Pakistan.