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The performance of behavioral targeting (BT) mainly relies on the effectiveness of user classification since advertisers always want to target their advertisements to the most relevant users. In this paper, the authors frame the BT as a user classification problem and describe a machine learning–based approach for solving it.

To perform such a study, two major research questions are investigated: the first question is how to represent a user’s online behavior. A good representation strategy should be able to effectively classify users based on their online activities. The second question is how different representation strategies affect the targeting performance. The authors propose three user behavior representation methods and compare them empirically using the area under the receiver operating characteristic curve (AUC) as a performance measure.

The experimental results indicate that ad campaign effectiveness can be significantly improved by combining user search queries, clicked URLs and clicked ads as a user profile. In addition, the authors also explore the temporal aspect of user behavior history by investigating the effect of history length on targeting performance. The authors note that an improvement of approximately 6.5% in AUC is achieved when user history is extended from 1 day to 14 days, which is substantial in targeting performance.

This paper confirms the effectiveness of BT on user classification and provides a validation of BT for Internet advertising.

This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

The purpose of this paper is to review studies on the use of virtual reality (VR) and gamification to engage students in higher education for marketing issues to identify the research topics, the research gaps and to prepare a future research agenda.

A literature review is performed based on two search terms applied to Web of Science, resulting in a final pool of 115 articles. A text-mining approach is used to conduct a full-text analysis of papers related to VR and gamification in higher education. The authors also compare the salient characteristics presented in the articles.

From this analysis, five major research topics are found and analysed, namely, teaching methodologies and education, experience and motivation, student engagement, applied theories in VR and gamification. Based on this and following the theory concept characteristics methodology framework, the paper provides directions for future research.

There is no comprehensive review exploring the topics, theories, constructs and methods used in prior studies concerning VR and gamification applied to higher education services based on all the articles published in well-regarded academic journals. This review seeks to provide deeper insights, to help scholars contribute to the development of this research field.

En este documento se revisan los estudios sobre el uso de la realidad virtual (RV) y la Gamificación para involucrar a los estudiantes en la educación superior en marketing, se identifican los principales temas de investigación tratados, las lagunas de investigación y se sugiere una agenda futura de investigación.

Una revisión de la literatura basada en dos búsquedas en Web of Science (WOS) permitió identificar 115 artículos. La minería de textos se utilizó para realizar un análisis de texto completo de los artículos relacionados con RV y gamificación en la educación superior. Los autores también compararon las características más destacadas de los artículos.

A partir de este análisis, se encuentran y analizan cinco grandes temas de investigación: metodologías de enseñanza y educación, experiencia y motivación, compromiso de los estudiantes, aplicadas a la RV y la gamificación. Basándose en esto y siguiendo el marco del TCCM, el artículo proporciona una agenda futura de investigación.

No hay una revisión exhaustiva que explore los temas, las teorías, construcciones y métodos utilizados en estudios anteriores relativos a RV y gamificación aplicados a servicios de educación superior basados en todos los artículos publicados en revistas académicas. Esta revisión proporciona una panorámica más detallada y sugiere a los académicos nuevas líneas de trabajo para seguir desarrollando este campo de investigación.

本文的目的是回顾为了提高学生参与高等教育而使用虚拟现实(VR)和游戏化的营销方面的研究，以确定它们的研究主题，研究差距，并以此准备未来的研究议程。

本文的文献综述是基于Web of Science的两个搜索词进行的，最终搜索出115篇文章。本文采用文本挖掘方法，对与高等教育中的虚拟现实和游戏化相关的论文进行全文分析。作者还比较了这些文章中呈现的显著特征。

从这一调查中，我们发现并分析了五大研究主题，即教学方法与教育、体验与动机、学生参与、虚拟现实应用理论和游戏化。在此基础上，遵循理论概念、特征、方法论框架，为今后的研究提供了方向。

目前，在权威学术期刊上发表的所有文章，都没有对以往关于虚拟现实和游戏化应用于高等教育服务的研究的主题、理论、结构和方法进行全面的综述。本文旨在提供更深刻的见解，以帮助学者们为这一研究领域的发展做出贡献。

In the most recent years, social, innovative, economic and political changes in the European context have characterized consumers' behaviours. The paper aims to understand if the use of electronic commerce differs in a situation characterized by uncertainty.

An innovative approach to categorising online consumer behaviour considers the self-determination theory and basic psychological needs in an uncertain scenario. The research is based on a quantitative analysis obtained by clustering algorithms on a sample of 1,000 digital users in European countries. A structured questionnaire was administered online and distributed through the leading online social platforms and direct mailing.

The results show online activities during changes in consumer behaviour patterns and retailers' strategies. This research will allow online retail managers and practitioners to obtain important information to help them define appropriate customer-oriented strategic actions to enhance value in the electronic context for both customers and firms.

The innovation of this research approaches the categorization of online consumer behaviour by exploiting the self-determination theory in an uncertain scenario. Precisely, the novelty of this research is to highlight three detailed categories of electronic commerce consumers, namely, unwilling, halfback and digital, to collect, store and disseminate information about these categories of Online Consumers Behaviours.

The data economy mainly relies on the surveillance capitalism business model, enabling companies to monetize their data. The surveillance allows for transforming private human experiences into behavioral data that can be harnessed in the marketing sphere. This study aims to focus on investigating the domain of data economy with the methodological lens of quantitative bibliometric analysis of published literature.

The bibliometric analysis seeks to unravel trends and timelines for the emergence of the data economy, its conceptualization, scientific progression and thematic synergy that could predict the future of the field. A total of 591 data between 2008 and June 2021 were used in the analysis with the Biblioshiny app on the web interfaced and VOSviewer version 1.6.16 to analyze data from Web of Science and Scopus.

This study combined findable, accessible, interoperable and reusable (FAIR) data and data economy and contributed to the literature on big data, information discovery and delivery by shedding light on the conceptual, intellectual and social structure of data economy and demonstrating data relevance as a key strategic asset for companies and academia now and in the future.

Findings from this study provide a steppingstone for researchers who may engage in further empirical and longitudinal studies by employing, for example, a quantitative and systematic review approach. In addition, future research could expand the scope of this study beyond FAIR data and data economy to examine aspects such as theories and show a plausible explanation of several phenomena in the emerging field.

The researchers can use the results of this study as a steppingstone for further empirical and longitudinal studies.

This study confirmed the relevance of data to society and revealed some gaps to be undertaken for the future.

The article investigates different types of strategies for managing user-generated content (UGC) and provides some insights into their implications.

A unique sample of Italian hotels with current and prospective customers in the digital environment is investigated. A taxonomy of user-provider interactions mediated by UGC is developed. A mixed approach was designed to meet the study aims. Firstly, an exploratory factor analysis was performed in order to illuminate different strategies of UGC and electronic word-of-mouth (E-WOM) management. Secondly, a cluster analysis was implemented in order to explain hoteliers' behavior toward users' contents.

The study results suggested the existence of three clusters, which reflected three different types of interactions between hotels and customers in the digital domain. Interestingly, most of Italian hotels were found to adopt a reductionist approach to UGC and E-WOM management, turning out to be ineffective to exploit them for the purpose of quality improvement and hospitality service excellence.

Hotels were found to be largely unaware of the importance of UGC and web-based communication with customers to improve their digital business strategy. Tailored management approaches are needed to realize the full potential of hotels' online content responsiveness for the purpose of value co-creation and service co-production.

This is one of the first studies investigating the strategic and management perspectives embraced by hotels to handle their interactions with customers in the digital arena.

Mobile services are expanding rapidly, and in this tremendously dynamic environment, companies should provide value-added services to meet users’ demand. In this context, the study aims to determine whether different user groups exist in this market and profile them.

Based on the information of 568 mobile service users, a research was developed in the context of a mature mobile services market – Spain. A behavior-based cluster analysis is developed by means of confirmatory factor analysis (CFA), followed by two-step clustering. Then, an ANOVA and post hoc Tukey tests are conducted to confirm differences among the obtained clusters.

The study findings show that mobile service users cannot be perceived as a homogenous group, as different users with different behaviors coexist in this market. More specifically, four behavior-based segments emerge in the mobile service sector: “service connoisseurs,” “uninvolved pragmatics,” “potential switchers” and “delighted loyal”; “potential switchers” being the most challenging segment for mobile service companies.

This study reports mobile service users’ heterogeneity; and in turn, mobile service managers should consider customers as four different types, instead of considering them as one single customer.

Los servicios móviles se están expandiendo rápidamente y en este entorno tremendamente dinámico, las compañías de servicios móviles deberían de proporcionar servicios de valor añadido para satisfacer la demanda de sus usuarios. En este contexto, esta investigación tiene como objetivo determinar si existen diferentes grupo de usuarios en este mercado y aportar su pefil.

Sobre la base de información de 568 usuarios de servicios móviles se lleva a cabo una investigación en el contexto de un mercado de servicios móviles maduro –España-. Se lleva a cabo un análisis clúster basado en el comportamiento de los usuarios, mediante un análisis factorial confirmatorio (CFA), seguido de un análisis clúster bi-etápico. A continuación, se realizan un test Anova y un test pos hoc de Tuckey para confirmar las diferencias entre los grupos obtenidos.

Los resultados de la investigación muestran que los usuarios de servicios móviles no pueden ser percibidos como un grupo homogéneo, ya que en este mercado coexisten diferentes usuarios con diferentes comportamientos. Más específicamente, cuatro segmentos de usuarios surgen en el sector de los servicios móviles basados en su comportamiento: “conocedores del servicio”, “pragmáticos no involucrados”, “potenciales cambiadores de servicio” y “leales encantados”, siendo “potenciales cambiadores de servicio” los que presentan un mayor desafío las empresas de servicios móviles.

Este estudio muestra la heterogeneidad de los usuarios de servicios móviles, y por tanto, los gestores de los servicios móviles deben considerar a sus clientes como cuatro tipos diferentes, en lugar de considerarlos como un único tipo de cliente.

移动服务正在迅速扩张，在这个巨大的动态环境中，企业应该提供增值服务来满足用户的需求。在此背景下，本研究旨在确定该市场是否存在不同的用户群体，并对其进行分析。

基于568名移动服务用户的信息，在一个成熟的移动服务市场（西班牙）的背景下开展了本次研究。通过确认性因子分析（CFA）进行基于行为的聚类分析，然后进行两步聚类。最后，方差分析和事后Tukey检验被用于确认获得的聚类之间的差异。

研究结果表明，移动服务用户不能被看作是一个同质的群体，因为在这个市场上共存着不同的用户，他们具有不同的行为。具体来说，移动服务领域可以划分为基于用户行为的四个细分市场："服务行家"、"不参与的实用主义者"、"潜在的转换者 "和 "愉悦的忠诚者"；其中，"潜在的转换者 "是对移动服务企业来说最具挑战性的细分市场。

本研究报告了移动服务用户的异质性；反过来，移动服务管理者应该考虑把客户划分为四种不同的类型，而不是将他们视为一个单一的整体。

This study aims to assess the technological capability of Chinese internet platforms (BAT: Baidu, Alibaba, Tencent) compared to US ones (GAFA: Google, Amazon, Facebook, Apple). More specifically, this study explores Baidu’s technological catching-up process with Google by analyzing their patent textual information.

The authors retrieved 26,383 Google patents and 6,695 Baidu patents from PATSTAT 2019 Spring version. The collected patent documents were vectorized using the Word2Vec model first, and then K-means clustering was applied to visualize the technological space of two firms. Finally, novel indicators were proposed to capture the technological catching-up process between Baidu and Google.

The results show that Baidu follows a trend of US rather than Chinese technology which suggests Baidu is aggressively seeking to catch up with US players in the process of its technological development. At the same time, the impact index of Baidu patents increases over time, reflecting its upgrading of technological competitiveness.

This study proposed a new method to analyze technology mapping and evolution based on patent text information. As both US and China are crucial players in the internet industry, it is vital for policymakers in third countries to understand the technological capacity and competitiveness of both countries to develop strategic partnerships effectively.

This chapter establishes the conceptual and analytic framework for the book. It relates not only to much of the existing work in evolutionary and institutional economics, but also to work in cultural science and cultural semiotics domains as well as in media convergence and transmedia studies. The central concept it first deploys is ‘innovation systems’ as applied in national, regional, international and sectoral contexts. It then builds on the general theory of economic evolution by Kurt Dopfer and Jason Potts and reviews the tools this theory provides to carry out a meso-level analysis of industries co-innovating and converging. It then proposes a new concept – ‘cross-innovation’ – to refer to the emergence of new structures and ‘rules’ at the boundaries of existing industries.

The purpose of this paper is to propose a scheme that allows users to interactively explore relations between entities in knowledge bases (KBs). KBs store a wide range of knowledge about real-world entities in a structured form as (subject, predicate, object). Although it is possible to query entities and relations among entities by specifying appropriate query expressions of SPARQL or keyword queries, the structure and the vocabulary are complicated, and it is hard for non-expert users to get the desired information. For this reason, many researchers have proposed faceted search interfaces for KBs. Nevertheless, existing ones are designed for finding entities and are insufficient for finding relations.

To this problem, the authors propose a novel “relation facet” to find relations between entities. To generate it, they applied clustering on predicates for grouping those predicates that are connected to common objects. Having generated clusters of predicates, the authors generated a facet according to the result. Specifically, they proposed to use a couple of clustering algorithms, namely, agglomerative hierarchical clustering (AHC) and CANDECOMP/PARAFAC (CP) tensor decomposition which is one of the tensor decomposition methods.

The authors experimentally show test the performance of clustering methods and found that AHC performs better than tensor decomposition. Besides, the authors conducted a user study and show that their proposed scheme performs better than existing ones in the task of searching relations.

The authors propose a relation-oriented faceted search method for KBs that allows users to explore relations between entities. As far as the authors know, this is the first method to focus on the exploration of relations between entities.