Search results

This study aims to conduct a geographical analysis of the distribution and type of activities developed by social enterprises in rural and urban areas of Ireland.

The study analyses data of more than 4,000 social enterprises against a six-tier rural/urban typology, using descriptive statistics and non-parametric tests to test six hypotheses.

The study shows a geographical rural–urban pattern in the distribution of social enterprises in Ireland, with a positive association between the remoteness of an area and the ratio of social enterprises, and a lack of capital-city effect related to the density of social enterprises. The analysis also shows a statistically significant geographical rural–urban pattern for the types of activities developed by social enterprises. The authors observe a positive association between the remoteness of the areas and the presence of social enterprises operating in the community and local development sector whereas the association is not significant for social enterprises developing welfare services.

The paper shows the potential of using recently developed rural–urban typologies and tools such as geographical information systems for conducting geographical research on social enterprises. The findings also have implications for informing spatially sensitive policymaking on social enterprises.

The merging of a large national data set of social enterprises with geographical tools and data at subregional level contributes to the methodological advancement of the field of social enterprises, providing tools and frameworks for a nuanced and spatially sensitive analysis of these organisations.

The purpose of this paper is to investigate the geographic dissemination of work in International Business (IB) by investigating the extent to which research topics tend to see mostly local use – with authors from the same geographic region as the article identified by the topic model as the first article in JIBS building on the topic – vs global use – where topics are used by authors across the world.

Topic modeling is applied to all articles published in the Journal of International Business Studies between 1970 and 2015. The identified topics are traced from introduction until the end of the sampling period using negative binomial regression. These analyses are supplemented by comparing patterns over time.

The analyses show strong path dependency between the geographic origin of topics and their spread across the world. This suggests the existence of geographically narrow mental maps in the field, which the authors find have remained constant in North America, widened yet are still present in East Asia, and disappeared in Europe and other regions of the world over time. These results contribute to the study of globalization in the field of IB, and suggest that neither a true globalization nor North American hegemony has occurred in recent decades.

The application of topic modeling allows investigation of deeper cognitive structures and patterns underpinning the field, as compared to alternative methodologies.

Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks.

In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions.

By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.

This paper tries to project population distribution by modeling geo-homophily in OSNs.

This research aimed to maximize the value of date exports for the Kingdom of Saudi Arabia.

To achieve its objective, this study relied on secondary data and quantitative economic analysis represented by the Linear programming model.

This study showed that Saudi Arabia exports dates to the United Arab Emirates, Yemen, Kuwait, Turkey, Somalia, Jordan, Oman, India, Indonesia, Bangladesh Morocco, Lebanon, and others. The geographical concentration coefficient for the quantity and value of date exports was 35.05% and 34.74%, respectively, during the study period. Saudi Arabia exported a quantity of dates amounting to 83.08 thousand tons, representing 40.57% of the average total amount of Saudi dates exports during the study period, to Yemen, Somalia, India, Indonesia, Bangladesh, Egypt, China, Djibouti, Bahrain, and Ethiopia, at prices lower than the average export price of 1200.31 dollars/ton, and therefore the export policy needs to restructure the geographical distribution of date exports. Based on the models of geographical distribution, Saudi date exports value can be increased by 32.76–127.12 million dollars, meaning can be increased by 13.77% – 53.44%. In light of the results of the proposed models, this study recommends the need to restructure the geographical distribution of Saudi date exports so that the value of Saudi date exports can be increased by 127.12 million dollars from the current situation for the period 2017–2021.

The paper’s original contribution lies in its proposal to restructure the geographical distribution of Saudi date exports to increase the value of exports.

The purpose of this study is to identify research perspectives/clusters in the field of urban tourism (city tourism) in narrow sense and tourism cities (cities and tourism) in the broader sense to examine the complex relationship through the optics of science mapping. This paper believes that the existing qualitative assessments of this field can be experimentally verified and visualized.

First, the key conceptual dilemmas of research perspectives in urban tourism are highlighted. Based on the Web of Science (WOS) Core Collection and the VOSviewer (computer program for visualizing bibliometric networks), the data will be analyzed. Clustering is used to evaluate information retrieval (inclusivity or selectivity of the search query), publication patterns (journal articles), author keywords, terminology and to identify the respective cities and author collaborations between countries.

Terminological specificities and their contextuality (authors’ preferences) are elaborated, as the topic is studied by authors from different disciplinary fields. Compared to other specific tourisms, urban tourism includes geographic terms (variations of city names) and terms with different connotations (travelers, visitors). Recent Spanish (also Portuguese) linguistic/geographic contexts are noticeable and a strong presence of WOS Emerging Sources Citation Index papers. Research perspectives are represented in the network of clusters of connected terms. If the search is based on a narrower sense of strict urban tourism, then tourism-business topics predominate. If tourism and cities are less closely linked, socio-cultural and environmental-spatial perspectives emerge, as does tourism/cities vulnerability (climate change and health issues).

The construction of a search syntax for the purpose of retrieval is always marked by compromises, given different terminological usages. A narrow search query will miss many relevant documents. On the other hand, if the query is too general, it returns less relevant documents. To this end, this paper tested queries on three different levels of inclusivity or selectivity. More consistent use of terms would benefit authors in the field of urban tourism when searching for references (information retrieval) and, as a consequence, would allow better integration of the field.

This study provides a practical method for evaluating cities and tourism in combining the expertise of an information scientist and a sociologist. It points out numerous caveats in information retrieval. It offers an overview of publishing just prior to the outbreak of Covid-19, thus providing an opportunity for further comparative studies.

This study is the first to examine urban tourism using such a method and can serve as a complement to the existing systematization of qualitative approaches. The findings are consistent with numerous qualitative assessments of weak the research interconnection between the specifics of cities and tourism in terms of broader socio-spatial processes. However, the study suggests that such research linkage is increasing, which is noticeable in relation to issues of social sustainability (e.g. overtourism, Airbnb and touristification).

Fingerprints and blood samples are important for the identification of individuals and criminals. The present study aims to identify the predominant fingerprint patterns and the association between the fingerprint patterns and ABO–Rh blood groups in Omani population.

A cross-sectional study was conducted on 200 Omani individuals aged 18 years (104 males and 96 females). The imprints of all right and left-hand fingers were taken, and the types of the fingerprints were determined using a standard protocol. The blood group of all the subjects was recorded. Chi-square test was performed to identify the association between the fingerprint patterns and the ABO and Rh blood groups.

The loop fingerprint pattern was the most common in Omani subjects (49.4%), followed by whorl (44.9%) and arch (5.7%) pattern. A significant association (p < 0.001) was found between gender and fingerprint pattern. The loop was the highest occurring pattern in the females (54.6%), while the whorl was more in males (50.0%). The whorl pattern was the most common in the AB+ and O− groups. The loop was a predominant pattern in the A+, A−, B+, B− and O+ groups. The Chi-square test also revealed a significant correlation between different fingerprint patterns and blood groups of the subjects (p < 0.001).

The present study is an outcome of undergraduate student's research project thesis for the Doctor of Medicine (MD) program. The results of the present study may help in creating a data bank for biometrics, which can be useful for diagnosing associated diseases and also help in identification of individuals.

The purpose of this paper is to provide a comprehensive overview of the geography of mortgage lending in Great Britain. It uses a new mortgage dataset as a way to shed light on the spatial distribution of mortgage finance and to highlight the different lending patterns of seven major UK banks. It also examines the relationship between the distribution of mortgage finance and socio-economic status at the local level.

The methodology is based on simple quantitative techniques, including spatial analysis, location quotient analysis and socio-economic classification. Lending data for Great Britain’s 10,000 postcode sectors are the basis for analysis here.

The results suggest that some banks lend significantly less than others in poorer areas, but, owing to a lack of data, it is not possible to say why. It is possible to identify banks that appear to change their lending patterns in areas with different socio-economic characteristics. The paper concludes by reflecting on key messages and by making a small number of recommendations to improve transparency in the sector.

In the absence of demand-side metrics, it is not possible to determine which banks lend disproportionately high or low amounts in poorer areas.

This paper has implications in relation to increasing financial transparency in the residential mortgage sector. The most important implication would be to highlight the fact that this new data – whilst a welcome development – is a long way from providing proper transparency in the mortgage lending sector.

This paper fills a gap in the international literature in relation to our understanding of the geography of mortgage lending in a major world economy. It also highlights important differential lending patterns in relation to socio-economic status at the sub-national level.

This study aims to explore the similarities and differences between the three concepts that are commonly used to describe the knowledge of traditional and indigenous communities, namely, indigenous knowledge, traditional knowledge and local knowledge, with a view to contributing to the discourse on conceptualizing indigenous knowledge.

Data was extracted from the Scopus database using the main terms that are used for indigenous knowledge, namely, “indigenous knowledge” (IK), “traditional knowledge” (TK) and “local knowledge” (LK). Data were analyzed according to the themes drawn from the objectives of the study, using the VOSviewer software and the analytical tool embedded in the Scopus database.

The findings indicate that whereas IK and LK are older concepts than TK, TK has become more visible in the literature than the former; there is minimal overlap in the use of the labels in the literature; the three labels’ literature is largely domiciled in the social sciences; and that there were variations in representation of the labels according to countries and geographic regions.

The author avers that the scatter of literature on the knowledge of traditional and indigenous peoples under the three main labels has huge implications on the accessibility and use the literature by stakeholders including researchers, students, information and knowledge managers and information service providers.

This study demonstrates the application of informetrics beyond is traditional use to assess trends, nature and types of research patterns and mathematical modeling of information patterns to encompass the definition of the scope of concepts as covered in the literature.

In a dynamic, continuously evolving sports landscape, social media have become an indispensable tool for sports organizations to cultivate meaningful connections with fans. The rapid pace of technological advancements has elevated these digital platforms from a supplementary role to a pivotal position within strategic management frameworks. The existing literature explores how football clubs can utilize social media, but analyzing social media strategies within the context of football leagues is lacking. The absence of comparative studies benchmarking clubs across different geographical regions while simultaneously analyzing multiple social media platforms is especially noteworthy. In this study, a comprehensive analysis of social media engagement is undertaken within esteemed football leagues spanning Europe, South America and North America.

Drawing on relationship marketing and employing content analysis as a methodological tool, the study examined 10,772 posts from the official accounts of eight football leagues on Facebook, Twitter and Instagram.

Across the leagues, the findings reveal that content quality drives engagement more than frequency. In addition, several format combinations were identified that facilitate engagement and Instagram emerged as the top social media platform for generating fan engagement.

This is one of the first empirical studies focusing on optimizing the use of social media to amplify fan engagement across various geographies and social media accounts and formats simultaneously.

The choice of crops to produce at a location depends to a large degree on the climate. As the climate changes and food demand evolves, farmers may need to produce a different mix of crops. This study assesses how much cropland may be subject to such upheavals at the global scale, and then focuses on China as a case study to examine how spatial heterogeneity informs different contexts for adaptation within a country.

A global agricultural economic model is linked to a cropland allocation algorithm to generate maps of cropland distribution under historical and future conditions. The mix of crops at each location is examined to determine whether it is likely to experience a major shift.

Two-thirds of rainfed cropland and half of irrigated cropland are likely to experience substantial upheaval of some kind.

This analysis helps establish a global context for the local changes that producers might face under future climate and socioeconomic changes. The scale of the challenge means that the agricultural sector needs to prepare for these widespread and diverse upheavals.