Search results

This study considers online searching by health information consumers as a learning process. We focus on search sequences, query reformulation, and conceptual changes.

A qualitative user study (30 participants; three health information seeking tasks) investigated mobile searching behavior. Recorded screen activity, questionnaires, and in-depth personal interview data were collected and analyzed.

(1) Search platform sequences of health information consumers in search as a learning process were exacted and their features were highlighted. (2) Query sequence and reformulation pattern of health information consumers were exacted and discussed. (3) The types and degree of conceptual changes of health consumers were reflected by their query reformulation behavior and differ from different health information search tasks. (4) Characteristics of health consumers' search as learning process were revealed.

(1) A novel perspective of consumer health information studies was proposed by exacting search platform sequence, query sequence and linking them with conceptual changes during the search as learning process. (2) Conceptual changes in the searching as a learning process are regarded as a measure of search outcome in this study, in which terms extracted from queries were used to reflect conceptual changes in consumers' mind. (3) Our findings provide evidences that types of health information seeking tasks do have significant influences on the search as a learning process.

The findings of this study can lead to the fit-to-needs of the search platforms, provide advice for information architecture of search list of search platforms, and guide the design of knowledge graph of health information systems.

Potential relationships between information-seeking behavior and conceptual changes in search as a learning process relative to health information were revealed.

Consumers are increasingly using search-based advertising in e-Business platforms to seek their desirable products. Platforms will choose a centralized advertising mechanism (CAM) or decentralized advertising mechanism (DAM) to offer a search advertising service to lower consumer search cost, as represented by using search time length. It is important for the platform to decide how to choose advertising mechanisms, and how to determine the optimal advertising price and search time length. To address these issues, this study aims to develop a theoretical approach under each mechanism to examine the platform’s optimal search-based advertising strategy by considering search cost.

In this study, two models are developed to examine the optimal search-based advertising strategy by considering consumer search cost (i.e. search time length). By comparing the platform’s profits under two models, the optimal advertising strategy, search time length and price are explored.

It is found that when the seller’s reserve benefit is sufficiently large, the platform benefits from choosing the DAM; otherwise, the CAM is a better choice. The advertising service is usually offered with a shorter search time length accompanied by a higher charge, and a longer search time length accompanied by a lower charge. Specifically, when the seller’s reserve benefit is substantially high, a DAM that benefits both the platform and seller is a better choice. This can explain why many platforms offer advertising services with a DAM.

This paper is the first theoretical study on addressing the search-based advertising strategy, especially the choice of advertising mechanisms, in the online advertising context. It is also the first piece of analytical research that considers the effect of consumer search cost on product demand, and then examines the optimal advertising price and search cost (i.e. search time length) for online platforms.

This study develops an empirical framework to address how large third-party sellers (TPSs) can apply customer acquisition strategies to improve their performance in consumers’ person-goods matching process and how the platform firm’s similar strategies moderate the effects of TPSs’ strategies.

Using data collected from the top ten TPSs from a Chinese e-commerce platform, the fixed effect model is used to validate the conceptual model and hypotheses.

The study results show that both market detection strategy and matching optimization strategy can help large TPSs improve their sales performance. Moreover, the similar market detection strategy applied by the platform firm weakens the effect of large TPSs’ customer acquisition strategies, while the similar matching optimization strategy applied by the platform firm strengthens the effect of large TPSs’ customer acquisition strategies.

This study provides firsthand evidence on the performance of large TPSs’ and the platform firm’s strategies. It demonstrates the effectiveness of large TPSs’ market detection strategy and matching optimization strategy, which can be adopted to meet consumers’ search and evaluation motivations in their person-goods matching process respectively. Moreover, it identifies the role of platform firms by showing the moderating effect of similar strategies adopted by the platform firm on the effect of large TPSs’ customer acquisition strategies.

This paper aims to understand user information behaviours when they perform multilingual information retrieval. It also offers reference for the development of multilingual information retrieval systems and relevant service platforms.

The authors designed an experiment on multilingual information retrieval with WorldWideScience, utilized Camtasia studio7 (a screen capturing and recording tool) to record overall operational processes of subjects and collected participants’ thought processes with think-aloud protocols. Meanwhile, a questionnaire survey and interviews were used to examine the subjects’ background information, their feelings for the experiment and their ideas about the experimental platform, respectively. Thirty-two valid data points were obtained by 41 subjects.

The users preferred their own language for retrieval. Most users from social science chose general search or advanced search freely according to the tasks. The majority of the participants selected key words directly from the tasks as search terms. Doctoral candidates were more likely to construct a search query with logic symbols. Translation tools were utilized for assisting retrieval and solving doubts of translation. When facing obstacles, users stayed on the original web page to explore continually, followed by back to homepage.

This paper provides a study of user behaviour through investigating how users behave on the whole process of retrieving multilingual information. The findings offer advice for optimizing the function of multilingual information retrieval systems and service platforms.

This chapter presents a summary of the literature on the influence of the Internet and other digital innovations on markets, consumers, and firms. The review leads to a list of topics in need of research in the general areas of big data, online and mobile advertising, consumer search, online privacy, online reviews, social networks, platforms for online transactions, and the impact of the Internet on retail markets, including multi-channel and omni-channel retailing. We discuss the big data approaches that have been applied to problems of targeting and positioning and suggest areas for further development of these approaches. We also discuss the emerging area of mobile advertising, which can further enhance targeting. On the consumer side, the evidence indicates that the Internet has greatly lowered the costs of search and access to retailers. Much of the consumer data are transmitted to sellers, and much of the online advertising is transmitted to consumers, through platforms, such as Google. We conclude that better models of competition among these platform firms are needed and that they need to be examined for anti-trust violations. While online retailing has grown rapidly, it still has a relatively small share of retail sales. Since sellers can combine the advantages of online and offline channels, it has been common for sellers to branch into multi-channel retailing. Given the increased availability of detailed consumer data, omni-channel selling, which emphasizes strategies for the various touchpoints that lead to a transaction, is an area for further development.

The purpose of this paper is to identify the most popular places, gadgets, searching tools and techniques adopted by users of Dr Y.S. Parmar University of Horticulture and Forestry (DYSPUH & F), Nauni, Solan, Himachal Pradesh, while searching electronic information resources (EIRs).

A survey was conducted with the help of a structured questionnaire used as a data collection tool.

It is found that department/office chamber (42 per cent), hostel (29 per cent) and home (26 per cent) prove to be the most popular places of access. Majority of users use laptops to access and read EIRs. Among all popular platforms, users of DYSPUH & F library prefer to use “search engines”, and “Google” proves to be the number one search engine. Majority of users search the information through “title” followed by “keywords/subject terms”. The users are not yet well-versed with most of the advanced search techniques, as less than half of them are able to use only Boolean operators, and less than 10 per cent of them claim to know other search techniques. Majority of users have learnt to use information search and retrieval skills through self-study.

Only one agricultural university of northern India was surveyed; hence, the results cannot be generalised for the entire northern region of the country.

The findings will help the library authorities to see what are the prime areas of concern so far as the search discourse and accessibility of e-resources is concerned.

No such survey has been conducted in the University till date.

The mobile medical consultation (MMC) service is growing rapidly, but not all consumers are always willing to actively engage with it. To address this issue, based on IT identity theory, this study explores the underlying mechanism of how two types of platform-related consumer experience influence MMC platform identity, in turn, result in consumer negatively-valenced engagement in MMC.

The data was collected from 400 consumers with the experience of MMC and analyzed by the partial least square (PLS) method.

The findings unfold that these two distinct consumer experience, servicescape experience (i.e. perceived telepresence and perceived platform surveillance) and service search experience (i.e. perceived diagnosticity and perceived serendipity), are associated with MMC platform identity and consumer negatively valenced engagement with MMC.

Research on consumer negatively-valenced engagement in the field of MMC is still in a nascent stage. The study identifies consumer experience in accordance with the unique context of the MMC platform and fills the research gap on the role of IT identity in consumer negatively valenced engagement.

This study investigates system dynamics (SD) applications in performance measurement (PM) research and practice. A bibliometric analysis was conducted to investigate the maturity of this research area and identify opportunities for development.

A systematic literature review (SLR) was conducted to provide a comprehensive and rigorous review of the existing literature. The search was conducted on 10 platforms identifying 97 publications, which were evaluated using bibliometric analysis.

The analysis revealed that applications of SD are most commonly used in the PM system design phase to model organisational performance. In addition, the bibliometric results showed a highly dispersed author set, with most studies using exploratory methods, suggesting that the research is in a relatively early stage of development. The results also showed that over 50 per cent of the causal models were not validated, emphasizing an important methodological gap in this research area.

This SLR is limited to indexed publications on 10 platforms, the search strategy was relatively precise and only available papers in English language were used for the literature review.

PM systems supported by SD can help managers understand and improve organisational behaviours by addressing dynamic complexities and relationship between variables. This study evaluates the maturity of this research area including information about the current development of this area and opportunities to build on existing knowledge.

This study identifies how SD approaches are applied to PM and highlights areas that require further research consideration. This paper is the first of two publications to result from this study and focuses on evaluating the current state of this research area.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

The paper aims to assess the utility of non‐agriculture‐specific information systems, databases, and respective controlled vocabularies (thesauri) in organising and retrieving agricultural information. The purpose is to identify thesaurus‐linked tree structures, controlled subject headings/terms (heading words, descriptors), and principal database‐dependent characteristics and assess how controlled terms improve retrieval results (recall) in relation to free‐text/uncontrolled terms in abstracts and document titles.

Several different hosts (interfaces, platforms, portals) and databases were used: CSA Illumina (ERIC, LISA), Ebscohost (Academic Search Complete, Medline, Political Science Complete), Ei‐Engineering Village (Compendex, Inspec), OVID (PsycINFO), ProQuest (ABI/Inform Global). The search‐terms agriculture and agricultural and truncated word‐stem agricultur‐ were employed. Permuted (rotated index) search fields were used to retrieve terms from thesauri. Subject‐heading search was assessed in relation to free‐text search, based on abstracts and document titles.

All thesauri contain agriculture‐based headings; however, associative, hierarchical and synonymous relationships show important inter‐database differences. Using subject headings along with abstracts and titles in search syntax (query) sometimes improves retrieval by up to 60 per cent. Retrieval depends on search fields and database‐specifics, such as autostemming (lemmatization), explode function, word‐indexing, or phrase‐indexing.

Inter‐database and host comparison, on consistent principles, can be limited because of some particular host‐ and database‐specifics.

End‐users may exploit databases more competently and thus achieve better retrieval results in searching for agriculture‐related information.

The function of as many as ten databases in different disciplines in providing information relevant to subject matter that is not a topical focus of databases is assessed.