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Keywords search is intuitive, simple to use and convenient. It is also the de facto input interface for textual and multimedia retrieval. However, individuals often perform poorly when faced with exploratory search tasks that are common during learning, resulting in poor quality searches. The purpose of this paper is to examine how adolescent learners search and select videos to support self-learning. The findings allow for the identification of design concepts of video retrieval interface and features that can facilitate better exploratory searches.

Participants were assigned two customized video search tasks. The think-aloud protocol is used to allow participants to verbalize their actions, thoughts and feeling. This approach offered rich insights to the participants’ cognitive processes and considerations when performing the search tasks.

This study identified five themes for exploratory video search behavior: selection of internet resources, query formulation/reformulation, selection of the video(s) for preview, getting acquainted with the video content, and making a decision for the search task. The analysis of these themes led to a number of design concepts, ranging from supporting exploration of topics to better interaction with metadata.

The findings can inform future development of dedicated video retrieval systems interfaces that seeks to facilitate effective exploratory searches by learners.

This study contributes by suggesting design concepts for video retrieval system developers to support exploratory video searches.

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

The purpose of this paper is to investigate when and how people working collaboratively could be assisted in a fact-finding task, specifically focusing on team size and its effect on the outcomes of such a task. This is a follow-up to a previously published study that examined exploratory search tasks.

This research investigates the effects of team size on fact-finding tasks using a lab study involving 68 participants – 12 individuals, ten dyads, and 12 triads. The evaluation framework developed in the preceding work is used to compare the findings with respect to the earlier traditional exploratory task (Task 1) and the complex fact-finding task reported here (Task 2), with task type being the only difference.

The analyses of the user study data show that while adding more people to an exploratory search task could be beneficial in terms of efficiency and effectiveness, such findings do not apply in a complex fact-finding task. Indeed, results showed that the individuals were more efficient and effective doing Task 2 than they were in Task 1. Moreover, they outperformed the dyads and triads in Task 2 with respect to these two measures, which relate to the coverage of useful information and its relation to the expression of information needs. If the total time taken by each team is disregarded, the dyads and triads did better than the individuals in answering the fact-finding questions. But considering the time effect, this performance boost does not keep up with the increased group size.

The findings shed light not only on when, how, and why certain collaborations become successful, but also how team size affects specific aspects of information seeking, including information exposure, information relevancy, information search, and performance. This has implications for system designers, information managers, and educators. The presented work is novel in that it is the first empirical work to show the difference in individual and collaborative work (by dyads and triads) between exploratory and fact-finding tasks.

Past studies have paid extensive attention to investigate learning issues in individual, organizational and team contexts. Learning activities in the workplace, however, often occur in the interdisciplinary dyadic context. Hence, the purpose of this paper is to clarify what factors make interdisciplinary dyads lead to better learning effects. The authors attempted to clarify two major agendas: What knowledge factors (intellectual capitals) owned by the parties of the dyads can induce better learning effects? What contextual factors (learning tasks) can make better learning effects during the dyadic learning process?

To examine the previous agendas, the authors first conducted in-depth interviews and an exploratory survey so that a four-element dyadic intellectual capital (DIC) architecture was circumscribed: knowledge interdependency, expertise similarity, collaborative routines and mutual trust. Dyadic learning tasks were classified as exploitative and exploratory learning. The authors then sampled 248 respondents for the formal empirical survey to examine the relationship between DIC, dyadic learning tasks and knowledge sharing.

The statistical evidences confirmed the positive relationships between DIC and knowledge sharing, and the results also signified the previous relationships with a mediating effect from exploratory learning, while the effect of exploitative learning was not supported. Thus, only dyads (the two heads) with knowledge interdependency and mutual trust can make the exploratory task better than that of one individual (the one head).

This study provides a new insight into the learning issue with an interdisciplinary dyadic perspective to supplement the existing gap between academic efforts and learning practices in the workplace.

Virtual try-on apps (VTOs) hold great potential to transform online apparel shopping, yet their acceptance by consumers has been lukewarm. By drawing on two theories – Sirgy’s theory of the self and Sundar’s theory of interactive media effects (TIME) – the study tests a PLS model with two new constructs: Photo Satisfaction and Consumer Inspiration, and their impact on Adoption Intention.

This mixed methods study examines the effects from personalization and customization affordances in the latest generation of apparel VTOs. The proposed model was tested in a quasi-experimental within-subjects design, as 61 female participants completed a goal-directed and an exploratory apparel shopping task using two VTO apps available on the market.

Inspiration induced from the customization affordance in the exploratory task influenced Adoption Intention as strongly as Fit Confidence did. For both conditions, users’ satisfaction with their avatar picture had a stronger effect on Perceived Augmentation than the individual trait of Body Esteem. The study also demonstrates how TIME’s Sense of Agency component could help theorize positive consumer responses to mobile marketing technology, which in our study were induced via the app’s Mix and Match feature. Also demonstrated was that Perceived Augmentation could be influenced by body-image affective judgments made during the pre-task VTO avatar creation phase.

VTO’s customization feature “Mix and Match” appears vital for the adoption of such apps for exploratory m-shopping of apparel. Also important is the satisfaction with one's photograph during the avatar-creation phase. We further suggest that apparel retailers work with Augmented Reality developers to include dynamic avatar capability as well as social sharing affordances in VTOs.

60 billion USD worth of returns occur annually in the online apparel retail industry, mostly related to fitting problems, not to mention the larger carbon footprint from the increased transportation. A more wide-spread adoption of VTOs can not only help with these problems but also lighten the traffic in brick and mortar fitting rooms, a potential hazard at this time of pandemic.

This is the first study to examine Consumer Inspiration in the context of online apparel retailing and to demonstrate the importance of Photo Satisfaction during the avatar-creation phase in influencing the subsequent user experience in apparel VTOs.

The purpose of this paper is to extract appropriate terms to summarize the current results in terms of the contents of textual facets. Faceted search on XML data helps users find necessary information from XML data by giving attribute–content pairs (called facet-value pair) about the current search results. However, if most of the contents of a facet have longer texts in average (such facets are called textual facets), it is not easy to overview the current results.

The proposed approach is based upon subsumption relationships of terms among the contents of a facet. The subsumption relationship can be extracted using co-occurrences of terms among a number of documents (in this paper, a content of a facet is considered as a document). Subsumption relationships compose hierarchies, and the authors utilize the hierarchies to extract facet-values from textual facets. In the faceted search context, users have ambiguous search demands, they expect broader terms. Thus, we extract high-level terms in the hierarchies as facet-values.

The main findings of this paper are the extracted terms improve users’ search experiences, especially in cases when the search demands are ambiguous.

An originality of this paper is the way to utilize the textual contents of XML data for improving users’ search experiences on faceted search. The other originality is how to design the tasks to evaluate exploratory search like faceted search.

The challenge of unforeseen uncertainties in exploratory projects requires the lead firm in a project alliance to effectively manage exploratory co-innovation. The purpose of this paper is to investigate the types of capabilities a lead firm required in exploratory projects and how these capabilities enable the exploratory innovation of the project alliance.

A multiple-case study was done to provide empirical evidence for the rationale of the capabilities of the lead firm. The provided analysis used abductive reasoning of two typical exploratory projects in China.

This paper identifies two types of capabilities: innovation-related capabilities and network-related capabilities. Furthermore, a process model of the capabilities of the lead firm is developed that enables exploratory co-innovation in a project alliance. The capabilities of the lead firm input varied at four different stages.

Innovation-related capabilities and network-related capabilities could form the foundation for the lead firm in an exploratory project alliance. This will enable an exploratory co-innovation and collaboratively overcome the barriers of exploratory projects.

Although exploratory project attracts extensive attention for its unique characteristics and universal value, there is limited amount of research on the context of joint exploratory projects. This study starts from the role of lead firm in an exploratory project alliance, contributes toward the comprehension of the link between the lead firm’s capabilities and the process of exploratory co-innovation. The findings will be of value in supporting the management of exploratory innovation in a project alliance.

The purpose of this paper is to explore the differences between collaborative and individual search techniques in a scenario-based task focussed on query behavior, cognitive load, search time, and task type about the search.

To help understand the influences on searching for relevant information in pairs or individual contexts, the authors conducted an exploratory user study with 30 participants, using two search tasks completed in a controlled laboratory setting.

On the basis of the analysis, the authors found that collaborative search teams resulted in more queries, more diverse query terms, and more varied query results compared to those working individually. The study results indicated that the cognitive load imposed on the participants did not differ between a collaborative search and an individual search except for the component of performance on the NASA Task Load Index. The results further showed that the total search time was a significant difference on average between the two conditions (i.e. individual information search and collaborative information search) for the second task. And there were significant differences of the mean of total search time between the two tasks for the both conditions. The authors also found that there was no significant relationship between query behavior and the total cognitive load.

The findings from this study have implications for a better understanding of collaborative search interface design, searchers’ cognitive load, query behavior, and general collaborative information search.

The purpose of the study is to examine enterprise searching practices across different work areas and work tasks in an enterprise search system in an international biotechnology company.

A mixed-method approach studying employees' authentic search activities during a 4-month period by log data, questionnaire survey and interviews. The log data analysed the entire active searcher group, whereas the questionnaire and interviews focused on frequent searchers.

The three studies provided insight into the searching activities and an understanding of the way searchers used the enterprise search system to search for information as part of their work tasks. The data identified three searcher groups, each with specific search characteristics. Four work task types were identified, and for all four types the searchers applied a tracing searching technique with use of contextual and historical relationships as paths.

The findings point to the importance of knowledge on historical and contextual relations in enterprise search.

The work sheds new light on enterprise searchers' information search practices. A significant contribution is the identification of a tracing search method used in relation to four essential work task types. Another contribution is the importance of historical and contextual knowledge to support the tracing search and decide what paths to follow.

XML has become a standard data format for many applications and efficient retrieval methods are required. Typically, there are roughly two kinds of retrieval methods, namely path‐based method (e.g. XPath and XQuery) and keyword search, but these methods do not work when users do not have any concrete information need. To expand feasibility of XML data retrieval is an important task and this is the purpose of this paper.

The paper's strategy is to apply faceted navigation for XML data. Faceted navigation is an exploratory search which enables the exploration of data making use of attributes, called facets. General faceted navigation methods are applied for attributed objects but XML data have no criteria because XML nodes are objects and facets. Thus, the paper's approach is to construct a framework to enable faceted navigation over XML data. It first extracts objects based on occurrence of nodes and facets. Then it constructs a faceted navigation interface for extracted objects and facets.

The framework achieves semi‐automatic construction of faceted navigation interface from an XML database. In the experiments, the show feasibility of the framework is shown by three faceted navigation interfaces using existing real XML data. On the other hand, the user study shows the retrieval method helps users to find required information.

There are only a few works which apply faceted navigation for XML data and these works are based on predefined objects and facets which need human effort. In contrast, this framework needs human decision making only when choosing objects and facets to be used in the faceted navigation interface.