Information Landscape Research Articles

Oil shocks and the transmission of higher-moment information in US industry: Evidence from an asymmetric puzzle

Using a cross-quantilogram approach, this study analyzes the transmission of higher-moment information across US industries with high-frequency (1-min) data. We investigate the effects of oil demand and supply shocks on this transmission, revealing that the impact is asymmetric. Specifically, negative oil price shocks amplify the asymmetric transmission of higher-moment information, whereas positive shocks have the opposite effect. The findings highlight the complexity in information transmission dynamics in response to oil price fluctuations, highlighting the need for policy makers and investors to account for these nuances when assessing risk and making decisions. The results emphasize the critical role of the direction and magnitude of oil prices in shaping the information landscape across industries.

Collection Data: Sharing, Discovery, Inspiration, and Innovation

In recent years, the traditional use of digital collections as surrogates for the physical has shifted to a paradigm of viewing collections as data suitable for computational use and novel research methods. The burgeoning collections as data movement is gaining momentum among galleries, libraries, archives, and museums (GLAM) worldwide. Strategic initiatives, experimentation, innovation, and inspirational learning are occurring as digital libraries and digital humanities progress and work to develop sustainable approaches for collections as data programs. What is the position of collections as data in an ever-changing information landscape of open access, linked data, and shared data of cultural heritage collections? What has the past decade brought to the field?

Permafrost carbon cycle and its dynamics on the Tibetan Plateau.

Our knowledge on permafrost carbon (C) cycle is crucial for understanding its feedback to climate warming and developing nature-based solutions for mitigating climate change. To understand the characteristics of permafrost C cycle on the Tibetan Plateau, the largest alpine permafrost region around the world, we summarized recent advances including the stocks and fluxes of permafrost C and their responses to thawing, and depicted permafrost C dynamics within this century. We find that this alpine permafrost region stores approximately 14.1 Pg (1 Pg=1015 g) of soil organic C (SOC) in the top 3 m. Both substantial gaseous emissions and lateral C transport occur across this permafrost region. Moreover, the mobilization of frozen C is expedited by permafrost thaw, especially by the formation of thermokarst landscapes, which could release significant amounts of C into the atmosphere and surrounding water bodies. This alpine permafrost region nevertheless remains an important C sink, and its capacity to sequester C will continue to increase by 2100. For future perspectives, we would suggest developing long-term in situ observation networks of C stocks and fluxes with improved temporal and spatial coverage, and exploring the mechanisms underlying the response of ecosystem C cycle to permafrost thaw. In addition, it is essential to improve the projection of permafrost C dynamics through in-depth model-data fusion on the Tibetan Plateau.

CANCIÓN DE JINETE: o olhar equidistante da paisagem proibida

This communication proposes to analyse, from the perspective of comparative studies and landscape theory, the poem Canción de Jinete, by Federico García Lorca, and the Brazilian resistance poetry produced after the military coup of 1964 (Ferreira Gullar, Thiago de Mello, mimeograph generation…). To this end, the concepts of landscape and complexity (Claudio Guillén, Michel Collot, Anne Cauquelin, Agustín Berque, Alain Roger, Gilles Deleuze, Manuel Ángel Vázquez-Medel, Èdouard Glissant) will be taken as a theoretical and philosophical support to seek parallels and similarities, in the construction of the forbidden landscape, between the Spanish poet and Brazilian poetry. Military dictatorships have disastrous consequences on any community and one of the most persecuted segments, due to its power of persuasion, is the artistic/intellectual. Murders, torture and exile are the main resources used by usurpers to silence the voices of those who resist living under the shadow of totalitarianism. As a cultural construct, the literary landscape is influenced by the space-time circumstances in which the poet finds himself. The landscape apprehended in experiences of oppression and exile records the violence that human beings can exercise in situations of power, remaining as a historical testimony of a tragedy that should not be repeated, nor forgotten.

Landscape geographies: Interdisciplinary landscape research and a new framework to apply landscape as method

The landscape concept’s disciplinary ambiguity and its broad range of definitions have resulted in the term’s unruly reputation. More recent scholarship, however, suggests that the term’s interdisciplinary application challenges its contentious origins, creates new pathways for co-creation, and encourages more direct interventions in informing policy. I therefore suggest there is a growing realm of landscape geographies, exploring alternative ways of knowing and being in landscapes across broader spatial, temporal, and ontological scales. Given that it can be difficult to navigate the complicated matrix of landscape definitions, theories, and methodologies, I position landscape as a method and introduce a new model of landscape analysis that includes three overlapping approaches to investigate a landscape’s material, symbolic, and affective dimensions. I conclude that embracing a wider spectrum of landscape geographies will help to elevate a more diverse range of voices, inspiring interdisciplinary conversations that contend with landscape futures in a rapidly changing world.

Generative AI and the Future of Democratic Citizenship

Generative AI technologies have the potential to be socially and politically transformative. In this paper, we focus on exploring the potential impacts that Generative AI could have on the functioning of our democracies and the nature of citizenship. We do so by drawing on accounts of deliberative democracy and the deliberative virtues associated with it, as well as the reciprocal impacts that social media and Generative AI will have on each other and the broader information landscape. Drawing on this background theory, we outline some of the key positive and negative impacts that Generative AI is likely to have on democratic citizenship. The political significance of these impacts suggests the need for further regulation.

Adapting the Historic Urban Landscape Approach to Study Slums in a Historical City: The Mae Kha Canal Informal Settlements, Chiang Mai

Beyond conserving urban heritage, the concept of historic urban landscapes (HULs) aims to tackle poverty and inequality, as well as to improve the quality of human settlements, through a people-centered approach in the context of rapid urbanization. This paper demonstrates the adaption of HUL tools and methodologies to investigate a slum in a historical city—the informal settlements along the Mae Kha Canal in Chiang Mai. An on-site field survey of the characteristics of the settlement’s composition and interviews with stakeholders, local authorities, and inhabitants were conducted. The analysis revealed that there is a gap between the desired strategy of the Mae Kha Canal agenda and the actual conditions of the location. The aforementioned contrast is discussed to suggest alternate options for upgrading the informal community while preserving its ancient walls, in line with HUL principles. The conclusion highlights the benefits of introducing the HUL approach in a slum setting and provides recommendations for deteriorated neighborhoods elsewhere that are either surrounded by or adjacent to historical features needing resilience.

Culturally Responsive Learning : Linguistic Landscape Study of MINHA Tebuireng Jombang, Indonesia

This study aims to explore the learning of various values through the MINHA Islamic linguistic landscape, the learning of exemplary values of figures through the linguistic landscape of MINHA figures, and the learning of multicultural communication from information boards and sign names. The research employed Linguistic Landscape Research with a qualitative approach. The linguistic data used in this study were obtained from images containing written text and videos providing information about Islamic history, figures, and guidelines. The data collection methods included observation and interviews. The findings revealed that three groups of linguistic features could serve as educational tools in MINHA, including linguistic features related to Islam, characters, and instructions for using MINHA and its facilities. The diverse values embedded in these linguistic features can enhance the effectiveness of learning by catering to students with varied backgrounds. The use of language in public spaces, such as in MINHA, constitutes a form of Linguistic Landscape, which may manifest as stickers on buildings in formal or informal settings. Linguistic Landscape (LL) serves as a tool to promote multilingualism and highlight the benefits of language.

Strategies for Combating Adversarial Information Operations: Theory and Practical Applications

In the contemporary information landscape, the proliferation of disinformation and propaganda poses a significant challenge to societal discourse and democratic processes. This paper proposes a multi-disciplinary approach to combatting adversarial information operations, drawing upon theoretical frameworks and practical applications. Theoretical foundations are established through an examination of the Persuasive System Design (PSD) model (Oinas-Kukkonen, 2013) and its parallels with propaganda tactics. By analyzing the shared flaws and vulnerabilities, insights emerge into the manipulation techniques employed by threat actors in online information spaces. Building upon this theoretical framework, the paper presents a proactive strategy for countering disinformation: the development of Early Warning and Control Systems (EWACS). These systems leverage AI-assisted narrative discovery to monitor the digital information landscape continuously. By identifying emerging threats and inauthentic activity, strategic communicators gain valuable insights for crafting counter-narratives and pre-emptive communication strategies. Key components of the proposed approach include deterrence by denial and resilience-building measures. By shifting the cost-gain calculation of adversaries and enhancing societal resilience, the aim is to create an environment where propagandists face increased challenges in achieving their objectives. This paper emphasizes the importance of collaboration between diverse stakeholders, including governmental organizations, academia, NGOs, and journalists. By harnessing the collective expertise from multiple fields, more effective strategies can be developed to safeguard information integrity and restore public trust. In conclusion, this paper advocates for a convergence of theory and practice in addressing the complex challenges posed by adversarial information operations. By integrating theoretical insights with practical applications, the proposed approach offers a holistic framework for countering disinformation and propaganda in contemporary information environments.

How to build trust on entertaining farm stay in sharing economy? Trust formation and its impact on repurchase intention

Abstract Entertaining farm stay in sharing economy has become a unique and feasible accommodation option in China. This paper proposes a comprehensive framework with which to examine the trust-building mechanisms within this emerging sector. Utilizing data from 527 experienced tourists in China, this study conducted a structural equation modeling analysis. The findings indicate that system quality, information quality and service quality, all stemming from platform factors, significantly influence trust. Electronic word-of-mouth, influenced by guest factors, and media richness, influenced by host factors, positively affects perceived usefulness and trust. Notably, while system quality remains positively correlated with trust, its impact on perceived usefulness is diminishing, reflecting the changing information landscape and consumer preferences. This study extends the research on consumer trust on entertaining farm stay in sharing economy. It also provides certain theoretical guidance for trust building in entertaining farm stay market.

SLOW TOURISM AS A CONTEMPORARY TENDENCY IN THE TOURISM MARKET: IMAGE CONTENT AND GEOTAG ANALYSIS ON INSTAGRAM

Although it originated from the Slow Food and Cittaslow movements, slow tourism has spread to many spheres of tourism. The purpose of the paper is to investigate what people associate with slow tourism, and how and where they engage in slow tourism. Social media content analysis on Instagram, using hashtag #slowtourism, was performed in the research. The general conclusion is that people mostly associate slow tourism with different forms of architecture and landscape, and to lesser extent with transport and food. Also, there was significant content variation within the architecture and landscape categories, suggesting that people associate different types of architecture and tourism destinations with slow tourism. When it comes to location, the majority of photos were taken in Italy, which is not surprising, considering that Slow Food and Cittaslow movements originated in this country.

Positioning precarity: The contingent nature of precarious work in structure and practice.

Conceptualising precarity has come to rest on the multi-dimensional and differentiated insecurities of job and worker, this however belies the relationship between structure and experience where precarity originates. To bridge that relationship, I employ the landscape concept to position workers relative to the structural contingency of precarious work. To study this landscape, I conducted an ethnography involving job searching, working, and interviewing workers. While certainly insecure, these jobs displayed parallel characteristics of streamlined hiring and short-notice starts which workers took advantage of. I explore three ideal-typical 'jobs'-the first, only, and best job-to examine how vulnerability is balanced with contingency to produce precarity. This analysis and the landscape approach locate the political-economic transformation of work in the context of workers' lives and their labour market position. Taking precarious work is an act of balancing one's vulnerabilities in a way that constructs and thus naturalises precarity. Overall, the article contributes an image of an economy where workers have to be opportunistic in a continual struggle for work while stratified by their personal circumstances and position in this labour market.

Charting progress: a cultural odyssey through eco-heritage transformations

PurposeThis paper provides a comprehensive exploration of the historical evolution and contemporary transformations inherent in cultural landscapes, framed within the narrative of a cultural odyssey. The concept of cultural landscapes extends beyond the physical arrangement of landscape elements, encompassing social and cultural customs and economic dynamics in both tangible and intangible aspects of heritage. Instead of being confined to a linear evolutionary model of sacred-historic landscape development, these sites are understood to exist across different historical periods such as ancient, medieval, etc. reflecting their multifaceted nature.Design/methodology/approachThe paper utilizes a thorough and systematic examination of existing literature, covering several disciplines such as cultural studies, anthropology and environmental studies. The methodology prioritizes a holistic approach by including succinct discussion of many locations to improve the analysis. The collection of qualitative data on the cultural importance of eco-heritage involves conducting participant observations and focus group talks to capture a diverse range of perspectives.FindingsThe paper highlights the importance of preserving and interpreting cultural landscapes as living, evolving entities. By recognizing diverse layers of history and cultural significance within these sites, research suggests strategies for integrating sustainable practices in the management of cultural landscapes.Originality/valueThis work makes a substantial contribution to the academic field by examining the intersection where cultural heritage and eco-transformations converge. By embarking on a cultural odyssey, the paper not only charts the progress of societies but also sheds light on the transformative impact of eco-heritage interactions. The novel perspectives offer a new framework for scholars, policymakers and practitioners to analyze and value the complex interrelationships between cultural legacy and ecological changes.

The Natural Landscape as A Strategic Element in Nature Tourism Management

Objective: The aim of this study is to investigate the role of the natural landscape as a strategic element in nature tourism management, in order to understand its conceptual evolution, analyze its relationship with tourism activities and explore the processes of valorization and stereotyping of landscapes in the context of sustainable tourism development. Method: The methodology adopted for the research includes an exhaustive bibliographic search in high-impact databases such as Scopus and Web of Science, complemented with a search in regional databases in Spanish such as Scielo and Redalyc. The selected documents were subjected to a process of critical reading and content analysis to extract key concepts, theories and findings relevant to the study. Results and Discussion: The results revealed that the concept of landscape has evolved from a purely aesthetic and visual perspective to a more holistic understanding that encompasses social, cultural and economic dimensions. The discussion highlights the close relationship between natural landscape and tourism, with landscape serving as a key resource and attraction for nature-based tourism activities. The processes of valorization and stereotyping of landscapes are also explored, emphasizing their influence on tourists' perceptions and destination choice. Research Implications: The findings of this study have implications for sustainable tourism planning and management, especially in areas with significant natural and cultural landscapes. The research emphasizes the need for a multidisciplinary approach to landscape conceptualization and management, as well as the importance of considering landscape as a central element in the development of sustainable tourism products and experiences. Originality/Value: This study contributes to the literature by providing a comprehensive and up-to-date review of the relationship between natural landscape and nature tourism, bridging knowledge from diverse disciplines.

Exploring the Digital Maze: Unveiling Information Literacy within Moroccan English Department Students with a Focus on Developing a Research Strategy

This study explores the realm of information literacy amongst Moroccan English department students, unravelling the intricacies of their abilities in developing a research strategy. Getting data from the Standardized Assessment of Information Literacy Skills (SAILS) test, the research scrutinizes the performance of undergraduate, graduate, and doctoral students. The focus on the specific skill set of developing a research strategy sheds light on the students' competencies in areas such as conferring with instructors, identifying research topics, and understanding the role of desired end products in information retrieval. The findings reveal nuanced strengths and weaknesses among students at different academic levels. This exploration not only contributes to the understanding of information literacy within the Moroccan English departments' context but also provides insights for curriculum designers and faculty seeking to enhance students' proficiency in navigating the digital information landscape.

Impacts of the COVID-19 infodemic on emotions through cognitive appraisals

PurposeThe COVID-19 outbreak has been accompanied by a massive “infodemic”, characterized by an overabundance of information, both accurate and inaccurate, making it hard for people to find trustworthy sources and reliable guidance. This study aims to investigate how the COVID-19 infodemic (i.e. information overload and untrustworthiness) influences consumers’ emotions (i.e. fear, anxiety and hope) by shaping their cognitive appraisals of the pandemic (i.e. perceived risk and uncertainty). Additionally, this study also investigates how individual differences (i.e. COVID-19 involvement and infection experience) impact their emotion formation process.Design/methodology/approachData were collected from 815 US consumers aged between 18 and 65 in November 2021 via an online survey. Structural equation modeling and multi-group comparison from AMOS 23 were used to test the proposed relationships.FindingsInformation overload increased one’s perceived risk and perceived uncertainty of COVID-19, which, in turn, structured the emotional states of fear, anxiety and hope. Information untrustworthiness had a significant impact on risk perception, which led to an increased feeling of fear. Additionally, individuals’ COVID-19 involvement and their infection experience with the coronavirus were found to moderate the cognitive appraisal process in developing emotions.Originality/valueThis study offers insights into the relationships between the information landscape and cognitive appraisals regarding health crises, specifically the COVID-19 pandemic. Not only enriching emotional well-being literature, it also lends managerial implications for effective communication strategies in global health emergencies.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2023-0616

A Delve into the Implementation of Data Quality Framework on Very Large Databases

In today’s data-driven landscape, the reliability and accuracy of information are paramount for informed decision-making and operational efficiency. A robust data quality framework provides a structured methodology for managing and maintaining the quality of data as-sets throughout their lifecycle. It in-troduces a comprehensive data qual-ity framework encompassing four key pillars: data governance, data profil-ing, data cleansing, and data monitor-ing. The foundation of the framework lies in establishing clear data governance policies and procedures, defining owner-ship, responsibilities, and accountability for data quality across the organization. Data profiling techniques are then em-ployed to assess the quality of data, iden-tifying anomalies, inconsistencies, and inaccuracies. Subsequently, data cleans-ing processes are implemented to rec-tify these issues, employing techniques such as deduplication, standardization, and validation to ensure data integrity. Continuous data monitoring is integral to the framework, enabling proactive de-tection of data quality issues and facil-itating timely corrective actions. Ad-vanced analytics and machine learn-ing algorithms may be leveraged to au-tomate monitoring processes, flagging anomalies and deviations from prede-fined quality thresholds.

Non-Parametric Machine Learning Modeling of Tree-Caused Power Outage Risk to Overhead Distribution Powerlines

Trees in proximity to power lines can cause significant damage to utility infrastructure during storms, leading to substantial economic and societal costs. This study investigated the effectiveness of non-parametric machine learning algorithms in modeling tree-related outage risks to distribution power lines at a finer spatial scale. We used a vegetation risk model (VRM) comprising 15 predictor variables derived from roadside tree data, landscape information, vegetation management records, and utility infrastructure data. We evaluated the VRM’s performance using decision tree (DT), random forest (RF), k-Nearest Neighbor (k-NN), extreme gradient boosting (XGBoost), and support vector machine (SVM) techniques. The RF algorithm demonstrated the highest performance with an accuracy of 0.753, an AUC-ROC of 0.746, precision of 0.671, and an F1-score of 0.693. The SVM achieved the highest recall value of 0.727. Based on the overall performance, the RF emerged as the best machine learning algorithm, whereas the DT was the least suitable. The DT reported the lowest run times for both hyperparameter optimization (3.93 s) and model evaluation (0.41 s). XGBoost and the SVM exhibited the highest run times for hyperparameter tuning (9438.54 s) and model evaluation (112 s), respectively. The findings of this study are valuable for enhancing the resilience and reliability of the electric grid.

Adaptive responses to habitat change: Theory and tests with field experiments.

Habitat loss and change are often implicated as the primary causes of species extinction. Although any population can be instantly imperiled by catastrophe, most habitat loss occurs gradually, thus enabling affected individuals an adaptive advantage to occupy the best of their dwindling opportunities. I demonstrate how to infer the advantage between two habitats for any density and frequency-dependent strategy of habitat selection. I explore the concept of an Adaptive Dispersal Strategy Landscape to reveal the Evolutionarily Stable Strategy separately for ideal-free and ideal preemptive habitat selectors. Both solutions reveal an initially counterintuitive expectation that individuals living at high density gain insufficient adaptive advantage to disperse from a deteriorating habitat. Adaptive dispersal is constrained at high density because habitats of better quality are fully occupied. I test the theory with measures of movement and foraging in crossover experiments on a seminatural population of meadow voles. The experiment allowed the voles to choose among patches and between enclosures in which I differentially manipulated food and shelter. Although photographs from an infrared camera documented voles venturing from one habitat to the other, none became resident. Voles preferentially foraged in the richer of the two enclosures, even when I reversed treatments, and they foraged more in patches protected by mulched straw. The adaptive advantage of dispersal using a surrogate fitness proxy based on the voles' giving-up densities mirrored that generated by theory. The convergence between theory and experiment yields much-needed insight into our ability to test, predict, and hopefully resolve, the ecological, evolutionary, and conservation consequences of habitat loss.

Energy-based corridor identification for mammals between protected areas in Iran.

Body mass plays a crucial role in determining the mass-specific energy expenditure during terrestrial locomotion across diverse animal taxa, affecting locomotion patterns. The energy landscape concept offers a framework to explore the relationship between landscape characteristics and energy expenditure, enhancing our understanding of animal movement. Although the energy landscape approach solely considers the topographic obstacles faced by animals, its suitability compared to previous methods for constructing resistance maps and delineating corridors has not been comprehensively examined. In this study, we utilized the enerscape R package to generate resistance maps in kilocalories (kcal) by incorporating digital elevation models (DEMs) and body size data (kg). We assigned body sizes ranging from 0.5 to 100 kg to encompass a wide range of small and large mammals in Iran, adjusting maximum dispersal distances accordingly from 50 to 200 km. By analyzing these scenarios, we produced four resistance maps for each body size. Next, we identified potential corridors between terrestrial protected areas in Iran using the Linkage Mapper toolkit and examined barriers and pinch-points along these paths. Our study revealed significant findings regarding the shared corridors between small and large mammals in Iran's landscape. Despite their differing body sizes and energy requirements, many corridors were found to be utilized by both small and large mammal species. For example, we identified 206 corridors for mammals weighing 500 g, which were also recognized as the least-cost paths for 100 kg mammals. Thus, embracing a comprehensive method in resistance map creation, one that incorporates species-specific traits and human infrastructure becomes imperative for accurately identifying least-cost paths and consequently pinpointing pinch points and barriers.