Search results

This paper aims to give an overview of the history and evolution of commercial search engines. It traces the development of search engines from their early days to their current form as complex technology-powered systems that offer a wide range of features and services.

In recent years, advancements in artificial intelligence (AI) technology have led to the development of AI-powered chat services. This study explores official announcements and releases of three major search engines, Google, Bing and Baidu, of AI-powered chat services.

Three major players in the search engine market, Google, Microsoft and Baidu started to integrate AI chat into their search results. Google has released Bard, later upgraded to Gemini, a LaMDA-powered conversational AI service. Microsoft has launched Bing Chat, renamed later to Copilot, a GPT-powered by OpenAI search engine. The largest search engine in China, Baidu, released a similar service called Ernie. There are also new AI-based search engines, which are briefly described.

This paper discusses the strengths and weaknesses of the traditional – algorithmic powered search engines and modern search with generative AI support, and the possibilities of merging them into one service. This study stresses the types of inquiries provided to search engines, users’ habits of using search engines and the technological advantage of search engine infrastructure.

As museums and other memory institutions continue to invest considerably in mass-digitising collections and participating in large search portals, it is essential to understand existing and potential users, their motivations and search needs to inform collections’ documentation. In this article, we discuss insights from a collaborative project with National Museums Scotland, set up to enhance the findability of collection images and inform documentation practices by understanding the collections users and their search terms.

The research involved interviews with National Museums Scotland staff, users and non-users of the Museums’ Search our Collections portal encompassing a concept mapping and card sort activity; online surveys and content analysis of user search queries.

The project revealed that participants are interested in searching the online collections by terms often not represented in collections metadata, including terms related to identity (their own but also others’) and social context (e.g. through seasonal and social events); emotional and sensory interests (e.g. visual characteristics) and narrative themes (e.g. on under-represented histories).

Based on the findings, we further theorise the semantic gap in online museum collection metadata. To bridge this gap and cater to how users search, we argue for a paradigm shift in documentation practices: suggesting practitioners should not only view collection images as information but also tap into their rich potential for enabling social and affective connections.

This study aims to explore the mechanism of boundary-spanning search on firm’s innovation performance under environmental dynamics from the perspective of strategic knowledge integration.

A survey was conducted among Chinese firm managers and R&D personnel, resulting in the collection of 315 valid samples. Hierarchical regression analysis was mainly adopted to demonstrate the hypothesized relationships, while the Sobel test and bootstrap method were used to further validate the mediating effects.

The results demonstrate that boundary-spanning search in different dimensions is a critical factor in the improvement of firm innovation performance (FIP). Two types of strategic knowledge integration are the main factors causing FIP and mediate the influence of boundary-spanning search on FIP. Furthermore, environmental dynamics moderate the relationship among boundary-spanning search, strategic knowledge integration and FIP.

Managers need to strengthen the boundary-spanning search for market and technical knowledge, which will promote firm innovative performance. Managers also need to implement strategic knowledge integration, which specifically includes using planned strategic knowledge integration to compensate for knowledge deficiencies, thereby achieving predetermined objectives; and using emergent strategic knowledge integration to update their understanding of internal and external environments, and to reset strategic objectives. In dynamic environments, managers should emphasize strategic knowledge management activities more.

From a strategic management perspective, this study categorizes strategic knowledge integration into planned and emergent forms. By applying the logic of knowledge acquisition, integration and creation, it explores how boundary-spanning search affects FIP through strategic knowledge integration as the intermediary and the boundary conditions of environmental dynamics. This not only provides a deeper understanding of the nature and effects of boundary-spanning research but also enhances the theory of strategic knowledge management.

This study investigates the effect of entrepreneurial orientation and government support on the innovation openness of South Korean manufacturing firms. By compartmentalizing entrepreneurial orientation and government support, this study seeks to elucidate their effects on the breadth and depth of firms' knowledge searches.

The study utilizes Poisson regression analysis with empirical data from 2,353 South Korean manufacturing firms collected from Korean Innovation Survey data.

Analysis reveals nuanced influences of various factors on firms' open innovation activities. Innovativeness positively affects knowledge search breadth and depth, highlighting the role of innovation-oriented processes, while competitive aggressiveness influences depth, thereby underscoring the pursuit of specialized knowledge acquisition. Proactiveness positively affects breadth but negatively affects depth, suggesting the importance of maintaining broad perspectives. Government support scope positively affects both breadth and depth, reflecting the significance of external support in encouraging inclusive knowledge exploration. The importance of government support positively influences depth, emphasizing its vital role in establishing collaborative relationships to enhance in-depth knowledge acquisition.

This study provides novel insights by exploring the nuanced implementation of open innovation in latecomer economies, especially South Korea, which experienced rapid economic development by leveraging innovation. The identification of specific factors influencing knowledge search breadth and depth contributes to the literature on open innovation by providing strategic guidelines for firms and policymakers. This practical implications of this study suggest that firms should align their strategies with entrepreneurial orientation while leveraging pertinent government support.

Informational conflict and uncertainty are common features across a range of sources, topics and tasks. Search engines and their presentation of results via search engine results pages (SERPs) often underpinned by knowledge graphs (KGs) are commonly used across tasks. Yet, it is not clear how search does, or could, represent the informational conflict that exists across and within returned results. The purpose of this paper is to review KG and SERP designs for representation of uncertainty or disagreement.

The authors address the aim through a systematic analysis of material regarding uncertainty and disagreement in KG and SERP contexts. Specifically, the authors focus on the material representation – user interface design features – that have been developed in the context of uncertainty and disagreement representation for KGs and SERPs.

Searches identified n = 136 items as relevant, with n = 4 sets of visual materials identified from these for analysis of their design features. Design elements were extracted against sets of design principles, highlighting tensions in the design of such features.

The authors conclude by highlighting two key challenges for interface design and recommending six design principles in representing uncertainty and conflict in SERPs. Given the important role technologies play in mediating information access and learning, addressing the representation of uncertainty and disagreement in the representation of information is crucial.

Internet search is a $120bn business that answers lists of search terms or keywords with relevant links to Internet webpages. Only a few companies have sufficient scale to compete and thus economics of the process are paramount. This study aims to develop a detailed industry-specific modeling of the economics of internet search.

The current research develops a stochastic model of the process of Internet indexing, search and retrieval in order to predict expected costs and revenues of particular configurations and usages.

The models define behavior and economics of parameters that are not directly observable, where it is difficult to empirically determine the distributions and economics.

The model may be used to guide the economics of large search engine operations, including the advertising platforms that depend on them and largely fund them.

This conceptual paper aims to demonstrate a holistic, multifaceted framework of interest development, information search, and knowledge construction (ISK) on children’s diverse information search behaviors.

By reviewing previous literature on children’s interest development, online information seeking and search, and knowledge construction, we propose the ISK framework. Then, we provide example case studies with pilot analyses using qualitative approaches (e.g. video-based interaction analysis, thematic analysis) showing how the framework can be applied to different types of authentic information-seeking situations for children.

The ISK framework demonstrates the multifaceted interplays between children’s information behavior and their cognitive and affective development. This framework was supported using previous studies and pilot empirical applications. We also included potential research questions that could be addressed using the framework.

Our paper provides a conceptual grounding to an in-depth, multidimensional understanding of children’s information behavior, which have been limitedly addressed in previous studies. Considering that children begin to search from their early stage of development and their search behaviors are tightly associated with other developmental states, our paper highlights the importance of investigating children’s search and information seeking and provides theoretical and empirical implications.

This study constructed an information search process model based on costs and benefits to reflect different information search processes under different decisions from a behavioural economics perspective.

This study used a deductive approach to conceptualise the costs, benefits, and uncertainties of the information search process. Subsequently, we constructed an information search process model based on the costs and benefits using graphical reasoning, loss aversion theory, bounded rationality theory, the satisficing theory of behavioural economics, and the uncertainty changes of information search process.

The model revealed four types of user behaviours in the information search process: (1) avoiding search at the initiation of the search process; (2) exiting in the middle of a search; (3) stopping at the point of satisficing; and (4) continuing the search until experiencing physical discomfort.

The model constructed in this study treats the information search as a process based on costs and benefits with uncertainty. This model integrates information search avoidance and stopping into an information search process model. The model identifies users’ bounded rationality by evaluating ideal and real situations. Moreover, the model explains relative and absolute information overloads and the area beyond the user’s bounded rationality. These findings could help improve users’ information literacy and optimise information systems.

This study explores job search dynamics among employed individuals. We focus on factors related to employees initiating their job searches and changing its intensity.

We conducted a qualitative study with 41 employed job seekers using semi-structured interviews.

Our analysis reveals six catalysts that initiate employee job searches and nine modulators that influence fluctuations in job search effort. We highlight the significant roles of social actors, resource dynamics, and personal, professional, and environmental factors in shaping employees’ job searches.

The diverse sample strengthens theory building but may not represent all employed job seekers. Future research would benefit from longitudinal designs.

This study underscores the influence of social actors on employee job search processes. Our findings offer valuable insights for policymakers and employers seeking to support employed job seekers and proactively manage voluntary turnover.

This research advances our understanding of employee job search beyond its traditional role in voluntary turnover. By integrating Conservation of Resources (COR) theory, we provide a framework for understanding employee job search initiation and modulation.

This paper aims to critically review the intersection of searching and learning among children in the context of voice-based conversational agents (VCAs). This study presents the opportunities and challenges around reconfiguring current VCAs for children to facilitate human learning, generate diverse data to empower VCAs, and assess children’s learning from voice search interactions.

The scope of this paper includes children’s use of VCAs for learning purposes with an emphasis on conceptualizing their VCA use from search as learning perspectives. This study selects representative works from three areas of literature: children’s perceptions of digital devices, children’s learning and searching, and children’s search as learning. This study also includes conceptual papers and empirical studies focusing on children from 3 to 11 because this age spectrum covers a vital transitional phase in children’s ability to understand and use VCAs.

This study proposes the concept of child-centered voice search systems and provides design recommendations for imbuing contextual information, providing communication breakdown repair strategies, scaffolding information interactions, integrating emotional intelligence, and providing explicit feedback. This study presents future research directions for longitudinal and observational studies with more culturally diverse child participants.

This paper makes important contributions to the field of information and learning sciences and children’s searching as learning by proposing a new perspective where current VCAs are reconfigured as conversational voice search systems to enhance children’s learning.