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The authors demonstrate the usage of data visualization for conveying educational administration research, with a specific focus on differential principal turnover. They model when and how principals move, over time, between six categories of turnover.

The authors construct several easy-to-interpret alluvial diagrams that reveal the patterns of differential turnover among 1,113 first-time Texas principals. Furthermore, the authors investigate how these patterns differ across educator characteristics (i.e. race and sex) and school contexts (i.e. school level and campus urbanicity).

Half of all first-time principals turn over within two years. Most principals who stay in leadership roles leave the district where they were first entered the principalship. Men are promoted more and women turn over less. In a connected finding, the authors conclude that elementary principals turn over less, and middle and high school principals are promoted more often. Principals of color are demoted more often than White principals. Urban school principals exit the system at a greater rate than rural principals.

The significance of this study lies in its direct response to two problems facing the administrator turnover knowledge base – a lack of methodological accessibility and the underutilization of data visualization. The authors’ is the first study to contain visualization of differential turnover outcomes over time. Second, the authors’ study provides a blueprint for data visualization that not only creates new knowledge but also speaks to a wider variety of education stakeholders by presenting complex data in a visual format.

The purpose of the work is to use a systematic process to identify the environmental and social impacts of small-scale alluvial gold mining projects using data from Ghana.

In this work, we used survey data collected from experts in the mining sector. This was followed by the use of a risk analysis approach to identify the significant and non-significant environmental and social impacts.

Seven key impacts associated with typical alluvial mining operations were identified. The first two are the loss of vegetation and the issue of airborne diseases from dust as a result of vegetation losses during the clearing of vegetation in the block out area. The third and fourth issues were loss of vegetation and airborne diseases as a result of vegetation losses during the removal of overburden. The fifth, sixth and seventh, most significant issues identified were the pollution from smoke fumes from the processing machines; and wastewater from the washing process. The last issue of significance was the dust pollution from the transportation of the washed gravel back to the mined pit.

One main limitation is that the data for this study were collected from Ghana.

The results indicate the need for proper and systematic measures to identify the environmental and social impacts of mining activities.

The work provides some insights into the strategies of identifying environmental and social impacts of mining activities. It is also one of the key works that systematically identify environmental and social impacts of small-scale alluvial gold projects.

Data visualizations in some form or another have served as decision-support tools for many centuries. In conjunction with advancements in information technology, data visualizations have become more accessible and more efficient to generate. In fact, virtually all enterprise resource planning and human resource (HR) information system vendors offer off-the-shelf data visualizations as part of decision-support dashboards as well as stand-alone images and displays for reporting. Plus, advances in programing languages and software such as Tableau, Microsoft Power BI, R, and Python have expanded the possibilities of fully customized graphics. Despite the proliferation of data visualization, relatively little is known about how to design data visualizations for displaying different types of HR data to different user groups, for different purposes, and with the overarching goal of improving the ways in which users comprehend and interpret data visualizations for decision-making purposes. To understand the state of science and practice as they relate to HR data visualizations and data visualizations in general, we review the literature on data visualizations across disciplines and offer an organizing framework that emphasizes the roles data visualization characteristics (e.g., display type, features), user characteristics (e.g., experience, individual differences), tasks, and objectives (e.g., compare values) play in user comprehension, interpretation, and decision-making. Finally, we close by proposing future directions for science and practice.

The purpose of this paper is to examine publication characteristics and dynamic evolution of the Industrial Management & Data Systems (IMDS) over the past 25 years from volume 94, issue 1, in 1994 through volume 118, issue 9, in 2018, using a bibliometric analysis, and identify the leading trends that have affected the journal during this time frame.

A bibliometric approach was used to provide a basic overview of the IMDS, including distribution of publication and citations, articles citing the IMDS, top-cited papers and publication patterns. Then, a complex network analysis was employed to present the most productive, influential and active authors, institutes and countries/regions. In addition, cluster analysis and alluvial diagram were used to analyze author keywords.

This study presents the basic bibliometric results for the IMDS and focuses on exploring its performance over the last 25 years. And it reveals the most productive, influential and active authors, institutes and countries/regions in IMDS. Moreover, this study detects the existence of at least five different keywords clusters and discovers how themes have evolved through the intricate citation relationships in IMDS.

The main contribution of this paper is the use of multiple analysis techniques from a complex network paradigm to emphasize the time evolving nature of the co-occurrence networks and to explore the variation of the collaboration networks in the IMDS. For the first time, the evolution of research themes is revealed with a purely data-driven approach.

This paper aims to provide a network study of the structural and dynamical characteristics of tourism flows in Europe from 1995 to 2012.

Travels in Europe were studied by following the network science research paradigm and by focusing on the whole network of intra-European tourism destinations. Network analysis was used to map and reveal the pattern of connections between states as shaped by bilateral tourism flows. Data were provided by the United Nations World Tourism Organization, and the data were integrated with tourism data available from national statistical offices of the individual countries, when necessary.

For 2012, results obtained from the UNWTO record-based network were compared to geo-located Twitter data as a proxy of human mobility patterns. The present analysis provides evidence of a shift towards an increased homogeneity in the travelling preferences of European tourists, an acquired attitude of visitors to travel shorter distances and a tendency of mobility patterns to merge. Finally, the comparison between UNWTO and Twitter data shows a different spatial distribution of visitors. These results provide a useful insight for policymakers involved in tourism planning.

The contribution of this study is threefold. First, to the best of the authors’ knowledge, this is the only study that focuses on the bilateral tourism flows between all countries falling, geographically or politically, under the definition of Europe. Second, evidence is provided of a shift towards a greater homogeneity in the travelling preferences of European tourists. Lastly, for the first time, this study provides a comparison between topological structure and bilateral mobility patterns of tourism flows, based on two different data-recording methods.

Protected designation of origin (PDO) and protected geographical indication (PGI) products form the core of the European Union (EU) quality food policy. Low and fragmented logo recognition perils the entire plan. This work aims to provide a “classification” of European consumers as regards logo awareness based on generic demographic and socio-economic characteristics and to test hypotheses relating PDO awareness with the purchasing behaviour of consumers.

The work utilises publicly available pan-European databases collected from Eurobarometer in four rolling surveys from 2012 to 2017. The statistical analysis exploits the spatially nested nature of the data.

The “logo aware” consumer is distinctively different from the average representative European consumer. A range of demographic, human capital and socio-economic characteristics and behavioural and attitudinal traits differentiate the consumers who are aware of the logo. Country and region effects are vital.

Benefits of large and representative samples accrue by utilising available Eurobarometer surveys. This comes at a cost. The individual researcher has no control over the questions included in the questionnaire.

Consumer classification forms the basis of awareness-raising strategies. It reveals the numerous segments of aware and non-aware consumers and opens a discussion about tools and methods to reach out to the European consumer.

This analysis holds an exact pan-European perspective and incorporates consumers' characteristics, behaviour, attitudes and country and region effects.

This study aims to review the literature on graph-theoretic mining methods for node importance in both static and dynamic world city networks, which is correspondingly categorised by graph-theoretic node importance mining on network topologies and transmission mechanisms.

The authors overview the graph-theoretic indicators of node importance: centrality and power. Then, the methods of graph-theoretic node importance mining on network topologies are assessed with node relevance, centrality- and power-based measurements, heterogeneous fusion and other miscellaneous approaches. The latest progress in transmission mechanisms is also reviewed in this study involving network evolution, node immunisation and robustness in dynamics. Finally, the findings are analysed and future directions in this field are suggested.

The method development of node importance mining is driven by complex application-based problems within a transmission mechanism. Fusion measurements, based on centrality and power, are extended by other graph mining techniques in which power has a significant role. In conclusion, the trends of node importance mining focus on power-embedded fusion measurements in the transmission mechanism-based complex applications.

This is the first systematic literature review of node importance from the view of graph-theoretic mining.

The purpose of this paper is to shed light on the changing pattern and characteristics of international financial flows in the emerging entrepreneurial ecosystems of Sub-Saharan Africa (SSA), provide a novel taxonomy to classify and analyze them, and discuss how such investments contribute to competence building and sustainable development.

In an exploratory study, the authors analyze the characteristics of international venture capital investors and the start-ups receiving funding in Kenya and map their interaction. The authors proceed by developing a novel taxonomy, classifying investors according to their main rationales (for-profit-for-impact), and start-ups according to the locus of needs and markets addressed by the start-up (local-global) and the locus of the start-ups capacity and knowledge (local-global).

The authors observe a new type of mainly western investors who support innovative ideas in SSA by identifying and investing in domestically developed technical innovations with the potential to address global market needs. The authors find such innovations to be mainly developed at the intersect of global and local knowledge.

The authors shed light on the – up to now – under-researched emerging phenomenon of international high-tech investments in SSA, and develop a novel taxonomy of technology investments in low-income countries, guiding further research on the conditions, impact, practical, and policy implications of this new form of finance flows.

This paper places a college at the centreof a multi-hazard assessment (earthquake, flood and landslide). The college is within a less studied, rural area of Ladakh, North India. Research focusses on a case study (Students Educational and Cultural Movement of Ladakh (SECMOL) College), close to Leh, Ladakh, and extends to incorporate/apply thinking from/to the wider Ladakh region. The approach adopted, centring on the hazard assessment of a single entity/local area, allows a rapid uptake of hazard recommendations within a college environment planning to continue its existence for decades ahead. A sister paper (Petterson et al., 2019) documents the active involvement of college staff and students in the principles of geohazard assessment and the development of student-centric hazard assessments of the college and their home village. SECMOL is a self-sufficient, alternative, college, organised along strong environmentally sustainable principles. The paper aims to discuss these issues.

This work has adopted different strategies for different hazards. Fieldwork involved the collection of quantitative and qualitative data (e.g. shape and size of valleys/river channels/valley sides, estimation of vegetation density, measurement of sediment clasts, angle of slopes, assessment of sediment character, stratigraphy of floodplains and identification of vulnerable elements). These data were combined with satellite image analysis to: define river catchment character and flood vulnerability (e.g. using the methodology of Collier and Fox, 2003), examine catchment connectivity, and examine landslip scars and generic terrain analysis. Literature studies and seismic database interrogation allowed the calculation of potential catchment floodwater volumes, and the collation of epicentre, magnitude, depth and date of seismic events, together with recent thinking on the return period of large Himalayan earthquakes. These data were used to develop geological-seismic and river catchment maps, the identification of vulnerable elements, and disaster scenario analyses.

This research concludes that SECMOL, and much of the Ladakh region, is exposed to significant seismic, flood and landslide hazard risk. High magnitude earthquakes have return periods of 100s to c. 1,000 years in the Himalayas and can produce intense levels of damage. It is prudent to maximise earthquake engineering wherever possible. The 2010 Leh floods demonstrated high levels of devastation: these floods could severely damage the SECMOL campus if storms were centred close by. This study reveals the connectivity of catchments at varying altitudes and the potential interactions of adjacent catchments. Evacuation plans need to be developed for the college. Northern ridges at SECMOL could bury parts of the campus if mobilised by earthquakes/rainfall. Slope angles can be lowered and large boulders moved to reduce risk. This work reinforces recommendations that relate to building quality and urban/rural planning, e.g. using spatial planning to keep people away from high-risk zones.

The frequency of hazards is low, but potential impacts high to very high. Hazard mitigation actions include engineering options for hazardous slopes, buildings to be earthquake-proofed, and evacuation management for large floods.

Methodologies undertaken in this research are well-tested. Linkages between disciplines are ambitious and somewhat original. The application of this work to a specific college centre site with the capacity to rapidly take up recommendations is novel. The identification of catchment inter-connectivity in this part of Ladakh is novel. This work complements a sister paper (Petterson et al., 2019) for community aspects of this study, adding to the novelty value.

This study aims to understand the process, structure and determinants of persistent illegal gold mining in Indonesia.

An exploratory study included a literature review, field observations and in-depth interviews. Fieldwork was conducted at two mining locations in Kalimantan, Indonesia. Sixteen respondents representing key stakeholders: government, mining companies, mining associations and community, including illegal miners, were interviewed. The findings of the literature review were categorized as the push or pull factors within the topics, and field observations verified the literature review results regarding Indonesia. Interview data were analyzed using content analysis methods. A structural diagram of the actors and causal loop diagrams among the determinants of illegal gold mining was created and interpreted.

A complex activity process and structure were revealed involving a range of actors. Politicians, government officials and law enforcement authorities added the complexity to the structure. Six main determinants of persistent illegal gold mining emerged: financial, low entry barrier, regulations and policies, supporting resources availability, politics and power and psychosocial factors.

This study provides a deeper understanding for policymakers to consider when formulating policies on natural resources, and insights for mining companies to minimize conflicts with the community.

The study contributes to our knowledge of the complex structure and main determinants of illegal gold mining in Indonesia, which supports efforts to curtail this illegal activity.