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Geography is an exciting discipline involving the interrogation of place, space, and mobility. Film is too powerful and assessable tool that engages audiences. Therefore, this article builds a rationale for utilizing film in the teaching of geography. Particularly geographic mobility, which is the study of spatial patterns of movement and viewing them with positive or negative social meaning and as embedded within structures of power.

This is not a research paper so there is no methodology to detail.

This is not a research paper so there are no findings to detail.

The article introduces three films (Selma, Hidden Figures, and The Green Book) and describes how they can be used to enrich the teaching of geographic mobility.

The data economy, emerging from the current hyper-technological landscape, is a global digital ecosystem where data is gathered, organized and exchanged to create economic value. This paper aims to shed light on the interplay of the different topics involved in the data economy, as found in the literature. The study research provides a comprehensive understanding of the opportunities, challenges and implications of the data economy for businesses, governments, individuals and society at large, while investigating its impact on business value creation, knowledge and digital business transformation.

The authors conducted a literature review that generated a conceptual map of the data economy by analyzing a corpus of research papers through a combination of machine learning algorithms, text mining techniques and a qualitative research approach.

The study findings revealed eight topics that collectively represent the essential features of data economy in the current literature, namely (1) Data Security, (2) Technology Enablers, (3) Business Implications, (4) Social Implications, (5) Political Framework, (6) Legal Enablers, (7) Privacy Concerns and (8) Data Marketplace. The study resulting model may help researchers and practitioners to develop the concept of data economy in a structured way and provide a subset of specific areas that require further research exploration.

Practically, this paper offers managers and marketers valuable insights to comprehend how to manage the opportunities deriving from a constantly changing competitive arena whose value is today also generated by the data economy.

Socially, the authors also reveal insights explaining how the data economy features may be exploited to build a better society.

This is the first paper exploring the data economy opportunity for business value creation from a critical perspective.

This study aims to investigate how the Chinese Belt and Road Initiative (BRI) and Chinese outward foreign direct investments (FDI) impact the Belt and Road countries (BRCs). It draws on postcolonial theory to investigate the (geo)political objectives behind the financial and economic means.

In line with the nature of postcolonial studies, the study applies a discourse analysis integrating it with empirical data on indebtedness and trade.

This study finds that FDI and the BRI, as a development project, need to be considered a double-edged sword for the receiving countries. The authors provide evidence that China has instrumentalized financial and economic means to gain political influence and pursue geopolitical ambitions. Moreover, investments into sensitive sectors (e.g. energy, infrastructure), combined with the BRCs’ inability to pay back loans, could eventually lead to China gaining control of these assets.

The study investigates the financial and economic means that are instrumentalized to gain political influence while not considering flows of technology and know-how. It also limits itself to the study of FDI coming from one specific country, i.e. China. Therefore, no comparison and evaluation are made of FDI from other countries, such as the USA or European countries.

By revealing noncommercial objectives and geopolitical ambitions that China pursues through the BRI, the authors derive policy implications for the BRCs, third countries and China.

The study contributes to postcolonial theory and neocolonialism by investigating how China uses financial and economic means to achieve noncommercial objectives and pursue geopolitical ambitions. Additionally, the authors enhance the understanding of FDI by highlighting more subtle aspects of the complex and contextual nature of FDI as a social phenomenon, which have been overlooked thus far. The authors challenge the predominant positive framing of FDI and provide a counterpoint to the way FDI is often coined.

This study aims to empirically examine the relationship between Internet use and personal privacy risk perceptions, the mediating effect of trust and the moderating effect of satisfaction on that relationship, which is exactly conducive to the practice of personal information protection.

A moderated mediation model will be employed to test the hypothesized relationships using the 2017 Chinese Society Survey data.

The authors find that Internet use positively relates to citizens' risk perceptions toward privacy security, and trust partially mediates the relationship between Internet use and privacy risk perception. In addition, the analysis of moderating effects showed that satisfaction with social life significantly enhances the negative impact on individuals' privacy risk perceptions of interpersonal trust. The positively moderating effect of satisfaction with local governments' work mainly reveals the relationship between interpersonal trust (or institutional trust) and citizens' privacy risk perception. Moreover, satisfaction with Internet platforms positively moderates the relationship between consumer trust and privacy risk perception.

This article contributes to the social risk amplification framework by applying it to the personal privacy information protection field, which was rarely discussed before. It also enriches privacy research by identifying the internal mechanism of how Internet use influences citizens' risk perceptions towards privacy information leakage.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.