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This study addresses how algorithmic recommendations and their affordances shape everyday information practices among young people.

Thematic interviews were conducted with 20 Finnish young people aged 15–16 years. The material was analysed using qualitative content analysis, with a focus on everyday information practices involving online platforms.

The key finding of the study is that the current affordances of algorithmic recommendations enable users to engage in more passive practices instead of active search and evaluation practices. Two major themes emerged from the analysis: enabling not searching, inviting high trust, which highlights the how the affordances of algorithmic recommendations enable the delegation of search to a recommender system and, at the same time, invite trust in the system, and constraining finding, discouraging diversity, which focuses on the constraining degree of affordances and breakdowns associated with algorithmic recommendations.

This study contributes new knowledge regarding the ways in which algorithmic recommendations shape the information practices in young people's everyday lives specifically addressing the constraining nature of affordances.

Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering.

This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined.

The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50.

To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.

With so many placement opportunities around the students in their final or prefinal year, they start to feel the strain of the season. The students feel the need to be aware of their position and how to increase their chances of being hired. Hence, a system to guide their career is one of the needs of the day.

The job role prediction system utilizes machine learning techniques such as Naïve Bayes, K-Nearest Neighbor, Support Vector machines (SVM) and Artificial Neural Networks (ANN) to suggest a student’s job role based on their academic performance and course outcomes (CO), out of which ANN performs better. The system uses the Mepco Schlenk Engineering College curriculum, placement and students’ Assessment data sets, in which the CO and syllabus are used to determine the skills that the student has gained from their courses. The necessary skills for a job position are then extracted from the job advertisements. The system compares the student’s skills with the required skills for the job role based on the placement prediction result.

The system predicts placement possibilities with an accuracy of 93.33 and 98% precision. Also, the skill analysis for students gives the students information about their skill-set strengths and weaknesses.

For skill-set analysis, only the direct assessment of the students is considered. Indirect assessment shall also be considered for future scope.

The model is adaptable and flexible (customizable) to any type of academic institute or universities.

The research will be very much useful for the students community to bridge the gap between the academic and industrial needs.

Several works are done for career guidance for the students. However, these career guidance methodologies are designed only using the curriculum and students’ basic personal information. The proposed system will consider the students’ academic performance through direct assessment, along with their curriculum and basic personal information.

Escalation in the number of online food ordering platforms, along with extensive junk food marketing, lucrative offers and discounts, innovation in food flavors, and doorstep delivery of food, have triggered the consumption of high-calorie and unhealthy food products which pose serious threats to the health and future well-being of individuals by making them more obese. To date, several public policy frameworks have been developed to confront obesity; however, their efficacy seems debatable. Directionally, the objective of this study is to highlight the potential influence of “digital nudging” which aims at steering individuals in desired directions, at the same time delimiting their freedom of choice. The study also establishes the effectiveness of digital nudges promoting a healthy lifestyle by steering individuals toward healthier food choices. The author strongly believes that this conceptual perusal will offer immense inputs to healthy food marketers and researchers alike in addressing the matters of obesity. Addressing the menace of obesity calls for joint efforts of the government, the public, researchers, and more specifically food product manufacturers/marketers who should incorporate healthier food options into their portfolios. E-tailers are also urged to adopt such practices in virtual markets and promote healthier food options to effectively tackle obesity.

In this study, the authors sought to investigate how the implicit social ties of both project owners and potential backers are associated with crowdfunding project success.

Drawing on social ties theory and factors that affect crowdfunding success, in this research, the authors developed a model to study how project owners' and potential backers' implicit social ties are associated with crowdfunding projects' degrees of success. The proposed model was empirically tested with crowdfunding data collected from Kickstarter and social media data collected from Twitter. The authors performed the test using an ordinary least squares (OLS) regression model with fixed effects.

The authors found that project owners' implicit social ties (specifically, their social media activities, degree centrality and betweenness centrality) are significantly and positively associated with crowdfunding projects' degrees of success. Meanwhile, potential project backers' implicit social ties (their social media activities and degree centrality) are negatively associated with crowdfunding projects' degrees of success. The authors also found that project size moderates the effects of project owners' social media activities on projects' degrees of success.

This work contributes to the literature on crowdfunding by investigating how the implicit social ties of both potential backers and project owners on social media are associated with crowdfunding project success. This study extends the previous research on social ties' roles in explaining crowdfunding project success by including implicit social ties, while the literature explored only explicit social ties.

Cultivating loyal customers is a pressing concern for streamers. The present study investigates how to build interpersonal relationships with streamers and whether different interpersonal relationship factors lead to repurchase intention and WOM intention in live streaming commerce. The moderating effect of gender is also examined.

A self-administered questionnaire was completed by 429 live streaming commerce users in mainland China. Partial least squares structural equation modeling was used to test the research hypotheses.

The results indicate that all four streamer attributes (expertise, authenticity, attractiveness, and homophily) have a positive influence on swift guanxi, and swift guanxi is effective in predicting both calculative commitment and affective commitment. In addition, all interpersonal relationship factors (swift guanxi, calculative commitment, and affective commitment) significantly affect repurchase intentions, with only affective commitment being linked to WOM intention. Also, the moderating role of gender was confirmed in expertise – swift guanxi, attractiveness – swift guanxi, cognitive commitment – repurchase intention and affective commitment – repurchase intention linkages.

This paper contributes to the live streaming commerce literature by integrating swift guanxi, calculative commitment, and affective commitment to understand the repurchase intention and WOM intention from the relationship-building process perspective. In addition, this paper enriches the source credibility and source attractiveness models by identifying gender boundaries on the effectiveness of these models in predicting swift guanxi.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

Multiple topics often exist on social media platforms that compete for users' attention. To explore how users’ attention transfers in the context of multitopic competition can help us understand the development pattern of the public attention.

This study proposes the prediction model for the attention transfer behavior of social media users in the context of multitopic competition and reveals the important influencing factors of users' attention transfer. Microblogging features are selected from the dimensions of users, time, topics and competitiveness. The microblogging posts on eight topic categories from Sina Weibo, the most popular microblogging platform in China, are used for empirical analysis. A novel indicator named transfer tendency of a feature value is proposed to identify the important factors for attention transfer.

The accuracy of the prediction model based on Light GBM reaches 91%. It is found that user features are the most important for the attention transfer of microblogging users among all the features. The conditions of attention transfer in all aspects are also revealed.

The findings can help governments and enterprises understand the competition mechanism among multiple topics and improve their ability to cope with public opinions in the complex environment.

This study, a conceptual paper, analyses the growth of curation in tourism and hospitality and the curator role in selecting and framing products and experiences. It considers the growth of expert, algorithmic, social and co-creative curation modes and their effects.

Narrative and integrative reviews of literature on curation and tourism and hospitality are used to develop a typology of curation and identify different curation modes.

Curational techniques are increasingly used to organise experience supply and distribution in mainstream fields, including media, retailing and fashion. In tourism and hospitality, curated tourism, curated hospitality brands and food offerings and place curation by destination marketing organisations are growing. Curation is undertaken by experts, algorithms and social groups and involves many of destination-related actors, producing a trend towards “hybrid curation” of places.

Research is needed on different forms of curation, their differential effects and the power roles of different curational modes.

Curation is a widespread intermediary function in tourism and hospitality, supporting better consumer choice. New curators influence experience supply and the distribution of consumer attention, shaping markets and co-creative activities. Increased curatorial activity should stimulate aesthetic and stylistic innovation and provide the basis for storytelling and narrative in tourism and hospitality.

This is the first study of curational strategies in tourism and hospitality, providing a definition and typology of curation, and linking micro and macro levels of analysis. It suggests the growth of choice-based logic alongside service-dominant logic in tourism and hospitality.

In recent decades, a significant number of research contributions have been made to the intersection of digital technologies and the tourism industry. However, a thorough examination of digitalization and digital transformation in the tourism industry has not been given sufficient consideration. This study aims to provide a bibliometric review of digitalization and digital transformation research in the tourism industry and devise future research agendas to advance the research field.

This study uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol and a bibliometric analysis to examine the research progress and scientifically map the research domain of digitalization and digital transformation in the tourism industry from 2002 to 2023 using bibliographic data retrieved from the Scopus and Web of Science.

This study presents the trends in publications and citations within the digitalization and digital transformation research domain in tourism. The findings also provide insights into the four primary clusters of the research field: digital innovation, smart tourism ecosystem, eTourism and smart destination experience. To further augment the application of digital transformation, this study offers several recommendations for future research on digitalization and digital transformation of the tourism industry.

This study provides valuable implications to researchers, managers and policymakers seeking to understand the current state and future research directions in tourism’s digitalization and digital transformation research field.

This study advances the research field of digitalization and digital transformation in the tourism industry by thoroughly examining the primary research clusters in the research corpus of the past two decades. Furthermore, it guides future research, thereby setting the stage for further progress in this domain.

近几十年来, 数字技术与旅游业的交叉领域做出了大量研究贡献。 然而, 对旅游业数字化和数字化转型的深入审视尚未得到充分考虑。本研究旨在对旅游业数字化和数字化转型研究进行文献计量回顾, 并制定未来的研究议程以推进该研究领域的发展。

本研究利用系统文献综述的科学程序和原理（SPAR-4-SLR）协议和文献计量分析来检验研究进展并科学地绘制旅游业数字化和数字化转型的研究领域 使用从 Scopus 和 Web of Science (WOS) 检索到的书目数据从 2002 年到 2023 年。

本研究呈现了旅游业数字化和数字化转型研究领域出版物和引用的趋势。 研究结果还提供了对该研究领域的四个主要集群的见解：数字创新、智能旅游生态系统、电子旅游和智能目的地体验。 为了进一步增强数字化转型的应用, 本研究为旅游业数字化和数字化转型的未来研究提出了几点建议。

本研究通过深入研究过去二十年研究语料库中的主要研究集群, 推进了旅游业数字化和数字化转型的研究领域。 此外, 它指导了未来的研究, 从而为该领域的进一步进展奠定了基础。

本研究为寻求了解旅游业数字化和数字化转型研究领域现状和未来研究方向的研究人员、管理者和政策制定者提供了有价值的启示。

En las últimas décadas, se ha realizado un número significativo de contribuciones de investigación a la intersección de las tecnologías digitales y la industria del turismo. Sin embargo, no se ha prestado suficiente atención a un examen exhaustivo de la digitalización y la transformación digital en la industria del turismo. Este estudio tiene como objetivo proporcionar una revisión bibliométrica de la investigación sobre digitalización y transformación digital en la industria del turismo y diseñar futuras agendas de investigación para avanzar en el campo de la investigación.

Este estudio utiliza el protocolo de Procedimientos y fundamentos científicos para revisiones sistemáticas de la literatura (SPAR-4-SLR) y un análisis bibliométrico para examinar el progreso de la investigación y mapear científicamente el dominio de investigación de la digitalización y la transformación digital en la industria del turismo. de 2002 a 2023 utilizando datos bibliográficos recuperados de Scopus y Web of Science (WOS).

Este estudio presenta las tendencias en publicaciones y citas dentro del dominio de investigación sobre digitalización y transformación digital en turismo. Los hallazgos también brindan información sobre los cuatro grupos principales del campo de investigación: innovación digital, ecosistema de turismo inteligente, turismo electrónico y experiencia de destino inteligente. Para aumentar aún más la aplicación de la transformación digital, este estudio ofrece varias recomendaciones para futuras investigaciones sobre la digitalización y la transformación digital de la industria turística.

Este estudio avanza en el campo de investigación de la digitalización y la transformación digital en la industria del turismo al examinar en profundidad los principales grupos de investigación en el corpus de investigación de las últimas dos décadas. Además, orienta la investigación futura, sentando así las bases para mayores avances en este ámbito.

Este estudio proporciona implicaciones valiosas para los investigadores, administradores y formuladores de políticas que buscan comprender el estado actual y las direcciones futuras de la investigación en el campo de la digitalización y la transformación digital del turismo.