Environment Relationships Research Articles

Digital Transformation and E-Commerce Growth: Impact on Consumer Behavior and SMEs

This study investigates the factors influencing online shopping interest and consumer trust in e-commerce platforms, focusing on the Shopee platform. Through surveys and interviews with MSME players, the study reveals that perceived risk, particularly psychological risk, does not significantly affect online shopping interest or consumer trust. Conversely, perceived usefulness, especially in terms of time-saving, positively and significantly influences both online shopping interest and trust. While electronic word-of-mouth (e-WOM) does not impact online shopping interest, it positively and substantially affects trust. Trust mediates the relationship between perceived usefulness and online shopping interest, as well as between e-WOM and online shopping interest. These findings highlight the complexity of factors influencing online shopping behavior and underscore trust's critical role in mediating these relationships. The implications suggest that e-commerce platforms should enhance perceived usefulness and consumer trust through improved service and product quality, and active customer engagement. Strategies include improving customer service quality, incentivizing positive reviews, and ensuring transparency in return policies and data privacy. MSME players can leverage these insights to develop more effective marketing strategies, boost consumer engagement, and strengthen consumer relationships in the e-commerce environment.

A Holistic Approach for Coastal–Watershed Management on Tourist Islands: A Case Study from Petra–Molyvos Coast, Lesvos Island (Greece)

Shoreline configurations are a complex outcome of the dynamic interplay between natural forces and human actions. This interaction shapes unique coastal morphologies and affects sediment transport and erosion patterns along the coastline. Meanwhile, ephemeral river systems play a vital role in shaping coastlines and maintaining ecosystem sustainability, especially in island settings. In this context, the present study seeks to develop a holistic approach that views coast and watershed systems as a continuum, aiming to investigate their relationships in an island environment, while accounting for human interventions in the river regime. For this task, the empirical USLE method was employed to quantify sediment production and transport from the catchment area to the coast, while hydraulic simulations using HEC-RAS were conducted to assess sediment retention within flood-affected areas. Moreover, coastal vulnerability to erosion was evaluated by applying the InVEST CVI model in order to identify areas at risk from environmental threats. The coastal zone of Petra–Molyvos, Lesvos, Greece, was selected as the study area due to ongoing erosion issues, with particular emphasis on its interaction with the Petra stream as a result of significant human intervention at its mouth. According to the study’s findings, the examined coastal zone is highly vulnerable to combined erosion from wind and waves, while the river’s mouth receives only a small amount of sediment from water fluxes. Evidently, this leads to an increase in beach retreat phenomena, while highlighting the necessity for integrated coastal–watershed management.

Does CEO duality moderate environmental, social, and governance performance-earnings management relationship? Evidence from emerging markets

Does CEO duality moderate environmental, social, and governance performance-earnings management relationship? Evidence from emerging markets

A mathematical framework for the statistical interpretation of biological growth models

Biological entities are inherently dynamic. As such, various ecological disciplines use mathematical models to describe temporal evolution. Typically, growth curves are modelled as sigmoids, with the evolution modelled by ordinary differential equations. Among the various sigmoid models, the logistic, Gompertz and Richards equations are well-established and widely used for the purpose of fitting growth data in the fields of biology and ecology. The present paper puts forth a mathematical framework for the statistical analysis of population growth models. The analysis is based on a mathematical model of the population–environment relationship, the theoretical foundations of which are discussed in detail. By applying this theory, stochastic evolutionary equations are obtained, for which the logistic, Gompertz, Richards and Birch equations represent a limiting case. To substantiate the models of population growth dynamics, the results of numerical simulations are presented. It is demonstrated that a variety of population growth models can be addressed in a comparable manner. It is suggested that the discussed mathematical framework for statistical interpretation of the joint population-environment evolution represents a promising avenue for further research.

Learning Environment, Classroom Participation and Innovative Behavior of Chinese College Students

The competition for knowledge and talent has become increasingly fierce in the 21st century. The innovative consciousness and ability of college students are of great significance for improving the level of talent cultivation and enhancing comprehensive national strength in China. Among the many factors that affect the innovative behavior of college students, their learning environment and classroom participation play a positive role in promoting their innovative behavior. This research aims to explore the relationship between classroom involvement and creative conduct among Chinese university students, how the learning environment influences this interaction. The study technique adopted a literature analysis and empirical inquiry. A total of 425 college students from four colleges and universities in Hebei Province in China consisting of freshmen, sophomores, and juniors from Humanities, Sciences, and Engineering majors were the respondents of the study. Data were collected through a survey questionnaire and were treated using correlational analysis. Descriptive statistical results show that participants in this study are more inclined to establish good teacher-student relationships in the learning environment, exhibited a more positive state of cognitive participation in classroom participation, and more positive attitudes towards academic learning and thinking patterns in their innovative behavior. In addition, the results of the Mann-Whitney Test found that there were differences in the three variables at the grade level, majors and family location. Students from cities and lower grades have a better learning environment; Science majors, and lower grade students have more active classroom participation; Boys, younger students, science majors, and urban students have better innovative behaviors. In addition, correlation analysis indicates a highly significant correlation between these three variables.

HYBRID APPROACH TO LEARNING BASED ON EMOTIONAL EXPERIENCE AND THE DEVELOPMENT OF INNOVATIVE METATHINKING IN POST-WAR UKRAINE

Purpose of the study is to synthesize generalized metaheuristic and metacognitive models, the use of which in project culture contributes to the formation of innovative creative-critical metathinking of an individual. Methodology. The methodology for studying creative activity and training of a designer is based on the post-neoclassical paradigm of scientific knowledge, subject-object integrity of the system of relations and dialectically developing relationships in a hybrid innovative learning environment. The methodology also includes new methods of interdisciplinary research and modeling of reality, integrating physical and social ontology. It is shown that the development of a structural-functional approach to the perception of physical and digital reality takes into account the peculiarities of an individual's brain activity. Results. The main results obtained are a triad of generalized author's metamodels, namely: 1. A heuristic metamodel of post-neoclassical perception of physical reality by a designer, in which the independence of cognition cycles, as well as the complementarity of paradigms (synergetic, triadic and semiotic) combines physical and social ontology, which creates new opportunities for the formation of a designer's creative metathinking in the process of experience. activity. 2. A heuristic metamodel of post-neoclassical perception and reflection of physical and virtual reality by a conceptual designer, in which the dependence of cycles of cognition, as well as the complementarity of heuristic metamodels, is achieved through universal triangles (fractal, Pascal, Sierpinski), the structures of which contribute to innovative activity of the conceptual designer. 3. Cognitive meta-model for the formation of meta-thinking of a designer-conceptualist, which is based on the spatio-temporal balance of explicit and hidden relationships, the cognitive visualization of which contributes to the search for harmony in the process of experience-oriented learning and creative activity through semiotic tools. Scientific novelty is determined by the complementarity of the structures of the author's metamodels of physical and digital reality, the synergy of which contributes to the optimization of experience-oriented models of teaching and self-learning. The interrelation of the structures of metamodels and their complementarity is the basis of successful activities in a hybrid learning environment (real physical and virtual mathematical), which facilitates the transfer of emotional and intellectual content between objects and subjects of the digital world. Practical significance of complementarity and interconnection of new metamodels of metathinking allows us to develop: universal criteria for determining the quality of design objects using GenAI; a method for identifying triads of interconnected opposites in information sources of various natures, the visualization of which simplifies interdisciplinary interaction between designers; create a personal e-assistant, e-consultant, e-expert using GenAI. In post-war Ukraine, interdisciplinary exchange of ideas, methods and successful experiences is extremely relevant within the framework of a hybrid approach to understanding the harmony of physical and digital reality, which promotes successful creative activity based on the perception of the harmony of nature to achieve the unattainable. Further development of experiential learning through the formation of metathinking is necessary to improve mental health and adapt to inevitable social transformations.

The gendered forest: Digital surveillance technologies for conservation and gender-environment relationships

Forests are critical spaces that shape and enable gendered subjectivities in culturally and historically specific ways. However, scholarly work on forest or biodiversity conservation continues to take a very perfunctory view on gender–environment relationships. Many projects remain gender blind or view everyday practices of forest resource collection by women through a transactional or economic lens. Research has shown that forests are spaces wherein identities of women are entwined with their everyday activities in the forest. In this article, we demonstrate the gendered nature of forests of the Corbett Tiger Reserve (CTR) in India, and their different socio-cultural framings. We reveal how the forest spaces of the CTR are used by women for a wide variety of cultural and livelihood needs. We further show how biodiversity conservation practice in such forest spaces alters the activities of women in a myriad of ways. The increasing use of digital technologies in biodiversity conservation shapes how the forest space is observed and governed. We argue that the use of digital technologies for forest governance such as camera traps and drones tends to transform these forests into masculinized spaces that extend the patriarchal gaze of society to the forest. Finally, we reflect on how the use of digital technologies for biodiversity conservation is easily co-opted for purposes beyond conservation that reinforce patriarchal norms and propagate gendered structural violence.

Observational benchmarks inform representation of soil organic carbon dynamics in land surface models

Abstract. Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Machine learning models can help identify dominant environmental controllers and establish their functional relationships with SOC stocks. The resulting knowledge can be integrated into ESMs to reduce uncertainty and improve predictions of SOC dynamics over space and time. In this study, we used a large number of SOC field observations (n=54 000), geospatial datasets of environmental factors (n=46), and two machine learning approaches (namely random forest, RF, and generalized additive modeling, GAM) to (1) identify dominant environmental controllers of global and biome-specific SOC stocks, (2) derive functional relationships between environmental controllers and SOC stocks, and (3) compare the identified environmental controllers and predictive relationships with those in models used in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Our results showed that the diurnal temperature, drought index, cation exchange capacity, and precipitation were important observed environmental predictors of global SOC stocks. While the RF model identified 14 environmental factors that describe climatic, vegetation, and edaphic conditions as important predictors of global SOC stocks (R2=0.61, RMSE = 0.46 kg m−2), current ESMs oversimplify the relationships between environmental factors and SOC, with precipitation, temperature, and net primary productivity explaining > 96 % of the variability in ESM-modeled SOC stocks. Further, our study revealed notable disparities among the functional relationships between environmental factors and SOC stocks simulated by ESMs compared with observed relationships. To improve SOC representations in ESMs, it is imperative to incorporate additional environmental controls, such as the cation exchange capacity, and refine the functional relationships to align more closely with observations.

Spatial Prediction of Soil Continuous and Categorical Properties Using Deep Learning Approaches for Tamil Nadu, India

Large-scale mapping of soil resources can be crucial and indispensable for several of the managerial applications and policy implications. With machine learning models being the most utilized modeling technique for digital soil mapping (DSM), the implementation of model-based deep learning methods for spatial soil predictions is still under scrutiny. In this study, soil continuous (pH and OC) and categorical variables (order and suborder) were predicted using deep learning–multi layer perceptron (DL-MLP) and one-dimensional convolutional neural networks (1D-CNN) for the entire state of Tamil Nadu, India. For training the deep learning models, 27,098 profile observations (0–30 cm) were extracted from the generated soil database, considering soil series as the distinctive stratum. A total of 43 SCORPAN-based environmental covariates were considered, of which 37 covariates were retained after the recursive feature elimination (RFE) process. The validation and test results obtained for each of the soil attributes for both the algorithms were most comparable with the DL-MLP algorithm depicting the attributes’ most intricate spatial organization details, compared to the 1D-CNN model. Irrespective of the algorithms and datasets, the R2 and RMSE values of the pH attribute ranged from 0.15 to 0.30 and 0.97 to 1.15, respectively. Similarly, the R2 and RMSE of the OC attribute ranged from 0.20 to 0.39 and 0.38 to 0.42, respectively. Further, the overall accuracy (OA) of the order and suborder classification ranged from 39% to 67% and 35% to 64%, respectively. The explicit quantification of the covariate importance derived from the permutation feature importance implied that both the models tried to incorporate the covariate importance with respect to the genesis of the soil attribute under study. Such approaches of the deep learning models integrating soil–environmental relationships under limited parameterization and computing costs can serve as a baseline study, emphasizing opportunities in increasing the transferability and generalizability of the model while accounting for the associated environmental dependencies.

Transforming Summer Literacy: How Innovative Programs Cultivate a Passion for Reading and Stronger Student Connections

This study examines the perspectives of children enrolled in a six-week summer literacy program and its impact on their attitudes toward books and reading. Specifically, the research aimed to explore how culturally relevant pedagogy and engaging literacy activities influenced children’s motivation to read by addressing the following two research questions: What are participants’ perspectives on the benefits of a summer literacy program? and What are participants’ perspectives on reading and books after immersion in a summer literacy program? The sample consisted of 21 children in grades 1–6. Using a mixed-methods approach, including surveys and open-ended questions, the study investigated participants’ perceptions of the program’s content, structure, and the quality of relationships with instructors and peers. The research focused on how the use of culturally relevant literature and enrichment activities shaped children's reading experiences and the role of child-staff relationships in fostering engagement. Outcomes revealed that the program's diverse literature, coupled with interactive activities, significantly contributed to cultivating a passion for reading. A supportive, nontraditional learning environment and positive relationships between children and staff further enhanced participants’ perceptions of reading and learning. This study highlights the effectiveness of innovative summer literacy programs in fostering a love for reading and strengthening student engagement.

Assessing the Recreational Resource Value of National Park Based on Visitor Perception—A Case of Three-River-Source National Park in China

National parks serve as critical practical sites for advancing the concept of “harmonious coexistence between humans and nature” and hold a strategic role in establishing global ecological security barriers. Scholars and decision-makers have expressed significant interest in rigorous assessments of the recreational resource value in national parks. This paper focuses on the Three-River-Source National Park, examining the characteristics and components of its recreational resource value through the lens of human–environment relationship theory. Analysis spans dimensions of geological and geomorphological value, ecological service value, historical and cultural value, and aesthetic landscape value. By extracting visitor comments rich in vocabulary related to their perceptions, this study compares variations in resource values and the “resource value–visitor perception” synergy within Three-River-Source National Park, employing text analysis, semantic network analysis, and coordination analysis methods. The findings reveal that (1) Visitor perceptions of recreational resource value display a clear hierarchy, with aesthetic landscape value (43.6%) ranking highest, followed by geological and geomorphological value (26.7%), historical and cultural value (19.3%), and ecological service value (10.4%), showing significant variation among categories; the vocabulary across these value types exhibits a pronounced long-tail distribution. (2) The recreational resource value in the park forms a distinct core centered on prominent attractions, accompanied by patterns of vocabulary aggregation and dispersion. (3) Visitors demonstrate strong synergy in their perception of geological and aesthetic value, weaker perception regarding historical and cultural value, and a relatively narrow understanding of ecological service value. This research enhances public comprehension of the recreational resource value of national parks and provides a scientific foundation for the conservation and sustainable use of recreational resources in national parks, advancing the realization of their recreational functions.

Evaluating third places, walkability, and positive mood in Los Angeles, USA: using social media data

ABSTRACT Past studies have stressed the importance of designing urban neighborhoods to be walkable and accessible to local amenities; however, the psychological benefits of urban design have been vastly understudied. The current study integrates theoretical insights from urban planning and environmental psychology literature in analyzing spatial relationships between third places, walkability, and positive mood across Los Angeles city blocks. To measure positive mood, this study utilized geotagged social media (Twitter) data to conduct sentiment analysis on tweets, using mood as a proxy for psychological well-being. Regression analyses revealed the independent and joint positive influences of third places and walkability on the expected number of positive tweets. The results indicated that more positive tweets were expected on blocks that (a) were more walkable and (b) had more third places. Notably, the number of third places on focal and surrounding blocks mattered more for psychological well-being on less walkable blocks. This research shows how big data can be leveraged by urban planners to make sense of human – environment relationships and the neighborhood context of well-being.

Marine steel corrosion prediction and zonation using feature extraction and machine learning in the seas around China

To reduce the losses caused by the marine corrosion of steel, it is important to establish a prediction model to determine the corrosion rate of steel in depth-varying aggressive marine environments. The use of statistical feature extraction methods and machine learning modeling for marine steel corrosion prediction and zoning in the seas around China is investigated. In this study, 856 samples were collected. Mean and standard deviation were selected as environmental characteristics and corrosion loss time-varying relationships were log-transformed. Subsequently, four main supervised machine learning (ML) algorithms including Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), and XGBoost were explored for predicting corrosion loss in different depth-varying marine exposure zones. The GB model showed the best prediction accuracy and generalization ability with MSE, RMSE, MAE, and R2 values of 0.08, 0.43, 0.19, and 0.92, respectively. The spatial and temporal distribution of corrosion loss and zoning map in the seas around China were obtained. According to the corrosion zoning map of the splash zone, the South China Sea has a higher degree of corrosion, particularly in its northwestern region.

Impact of natural resource rents on global trade dynamics in RCEP: Economic and geopolitical interdependencies

This research analyzes the impact of natural resource revenues on global economic trends in the RCEP countries, emphasizing the importance of resource exploitation in the financial development process. The work explores complex interdependencies between resource extraction, geopolitical risk, economic environment, and trade relationships. Energy efficiency, geopolitical risk, and GDP are the control variables. These findings highlight the importance of natural resource rents, GDP, geopolitical risk, and energy conservation on the trade structure of the RCEP trading partners. Quantile regression studies show the negative effect of oil revenues on world trade, thus providing evidence of the multifaceted link between natural resource earnings and trade outcomes. The findings underscore the significance of policymakers and businesses understanding these interrelated links and their implications for global trade relations. The report offers policy directions for RCEP countries to foster sustainable economic development and enhance export competitiveness. These recommendations aim to further the resource sector's growth, financial infrastructure, and managing geopolitical risks.

How do local public health teams in North Wales consider their role in influencing the obesogenic environment through planning processes? A qualitative study

BackgroundOverweight and obesity affect 2·6 billion people worldwide, causing significant morbidity and 4 million deaths annually. In Wales, over 60% of people are affected. Betsi Cadwaladr University Health Board Public Health team recently began systematically to provide public health advice and evidence in response to planning applications to try to influence the obesogenic environment. This study aims to explore team members’ experiences of responding to fast-food outlet applications. MethodsQualitative, semi-structured online interviews were conducted with 12 practitioners, registrars and consultants in the team. The interviews addressed the planning process, application prioritisation, power over the obesogenic environment and stakeholder relationships. Interview transcripts were in vivo coded and subjected to thematic analysis. Ethical approval granted on June 6, 2023 by the Institute of Population Health Research Ethics Committee at the University of Liverpool (ref: 12503). FindingsParticipants’ interpretations of the nature, scope and determinism of the obesogenic environment varied considerably. Regardless, the concept was considered to have significant real-world applicability for problematising fast-food outlets. Complexity, the evidence base and defining unhealthy outlets were thought problematic. Participants considered their skills in evidence provision, impact assessment and networking essential. However, no relationship-building strategy was defined, and contradictory approaches were adopted, due to capacity, inadequate legal standing and fear of backlash. Most felt public health lacked power to effect lasting change through planning. Hopes were placed in a favourable future policy environment despite recognition that current supportive policy is routinely ignored. Intervention success was unclearly defined. InterpretationThis is the first study to consider public health professionals’ beliefs about using planning to modify the fast-food environment in Wales’ specific policy environment. It highlights the need for logic-based strategies which maximise effectiveness, rather than achieve adherence with established processes. Public health contributions tailored to other stakeholders’ priorities and language, especially in the absence of supportive policy and law, may be essential. Procedural, policy and research recommendations to strengthen public health impact on the obesogenic environment are made. FundingNone.

Bottom Trawling and Multi‐Marker eDNA Metabarcoding Surveys Reveal Highly Diverse Vertebrate and Crustacean Communities: A Case Study in an Urbanized Subtropical Estuary

ABSTRACTEstuarine habitats serve as critical feeding and nursery grounds for many aquatic species and support fisheries. However, monitoring these complex ecosystems using conventional trawling methods is destructive, costly, and labor‐intensive. This study compared trawling and a multi‐marker environmental DNA (eDNA) metabarcoding approach to monitor marine vertebrate and crustacean communities in an estuarine environment in subtropical Hong Kong. We analyzed 16 bottom trawl samples and the eDNA from 32 two‐liter water samples using primer sets specific to fishes and mammals (MiFish‐U, 12S‐V5, and Berry‐Fish) and decapod crustaceans (MiDeca). We found that the eDNA approach detected more pelagic and demersal fishes (237 vs. 106 in trawling) and elasmobranchs (6 vs. 3) than trawling. The eDNA approach was also more effective than trawling in detecting threatened vertebrates (16 vs. 4), including the Indo‐Pacific Finless Porpoise and the critically endangered Large Yellow Croaker. Among the detected fish at species level, 70 species were detected by both approaches, 32 species were detected by trawling only, and 142 species were detected by the eDNA approach only. Regarding crustaceans, the eDNA approach detected slightly fewer decapods (61 vs. 77) and stomatopods (5 vs. 8) than trawl surveys. However, the eDNA approach could be enhanced through the development of suitable decapod‐specific primers and the expansion of the local reference database. In addition, multivariate analyses of the eDNA data revealed spatial patterns of fish and crustacean assemblages that might be associated with sediment loading, oxygen, and nutrient levels. Furthermore, there was a positive correlation between eDNA read counts and trawl catch, but their correlation coefficient was low. We conclude that eDNA metabarcoding can provide high‐resolution detection of species, composition, and unravel community–environment relationships in estuarine ecosystems. Overall, integrating the non‐destructive eDNA approach can complement the conventional trawling method for better‐informed sustainable fishery management and conservation.

Relationship of the Perioperative Nurse Work Environment With a Culture of Safety and High Reliability

PurposeThe purpose of this study was to examine dimensions of the perioperative work environment and their associations with the operating room (OR) culture of safety and high-reliability characteristics. DesignA predictive correlational design using a cross-sectional survey was used. MethodsA convenience sample of perioperative nurses (N = 96) was used to evaluate strength of associations of their work environment with OR safety culture and high-reliability organizational culture. In addition, the best predictive models for OR culture of safety and high-reliability characteristics were used. FindingsFindings indicated that the five dimensions of the work environment are significant predictors of a safety culture; however, only Collegial Relationships and Nursing Foundations for Quality of Care significantly predict high reliability. ConclusionsDue to the extraordinary responsibility perioperative nurses hold to maintain safety standards for surgical patients, it is critical to fortify elements of the nurse work environment.

Stress in novice nurses in new work environments: a systematic review.

Inexperienced nursing care can compromise the quality of care and the well-being of patients. The aim of this study was to assess the main sources of stress encountered by nurses and novice nurses in a setting not previously experienced. A systematic review was conducted following the PRISMA format in Pubmed, Scopus, Web of Science, and CINAHL electronic databases in March 2024. A total of 395 studies were identified, of which 16 met the inclusion criteria. Selection was made on the basis of topic relevance and methodological quality, assessed using the critical tools of the Joanna Briggs Institute (JBI). A total of 16 studies were included in this review. Of the 16 selected, 10 were cross-sectional studies, 3 were cohort studies, 2 were qualitative, and 1 was a systematic review. The studies revealed that the main stressors for novice nurses included time management, workload, and interpersonal relationships. The results underline that organizational factors, such as lack of support and high work demands, play a key role in generating stress. Identifying and addressing the key challenges faced by novice nurses, such as workload, adjustment to the environment, professional expectations, and interpersonal relationships, is crucial to sustain their professional engagement and ensure the quality of health care. This understanding is essential for creating efficient policies and practices that enhance the occupational well-being and stability of nurses in the workforce. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024520651, CRD42024520651.

The influence of emotional intelligence and employee motivation on employee performance in telecommunication companies in the sultanate of Oman

This study examines the impact of emotional intelligence (EI) and employee motivation on employee performance within the telecommunication industry in the Sultanate of Oman. The target population consisted of 4344 non-managerial employees across nine telecommunication companies, including Omantel, Ooredoo, Vodafone, Oman Broadband Company, Awasr Oman & Co, TEO, Oman Tower Company L.L.C, Helios Tower, and Connect Arabia International. Employing a deductive research approach, finally data were collected via an online survey from 354 respondents. The hypotheses were tested using multiple regression analysis. The results indicate that all dimensions of EI self-awareness, self-regulation, empathy, and social skills positively and significantly influence employee performance, with social skills having the strongest effect. Furthermore, both intrinsic motivation factors, such as work itself and career development, and extrinsic motivation factors, including wages, rewards, working environment, and co-worker relationships, significantly enhance employee performance. The interaction between EI and employee motivation was found to amplify these positive effects. Among control variables, age and education level showed significant impacts, while gender did not. These findings underscore the critical role of both emotional intelligence and motivation in driving employee performance. The study suggests that managers and policymakers should adopt integrated strategies that develop EI competencies and enhance motivational factors to optimize employee performance, thereby contributing to the success of organizations in the telecommunication sector.

Riskscapes: A framework for risk assessment in colonial contexts

Risk assessment is a critical aspect of coping with environmental changes. The identification of values at risk — entities, attributes, and ideas that are important to a community — is a key component of a population's ability to resist or adapt to hazards. In colonial contexts, risk assessment must take into account the distinct relationality to the land of Indigenous and non-Indigenous groups and the historicized power relations. Most risk assessment frameworks ignore or oversimplify the cultural heterogeneity of human–environment relationships by using generalized value concepts. The few context-dependent frameworks that have been proposed do not account for different sociocultural groups living on the same land. We propose a spatial-based risk assessment approach inspired by the concept of riskscape, acknowledging diverse perceptions of risk and landscape among different sociocultural groups. We present a risk assessment method eliciting values for different sociocultural groups in their specific contexts using separate valuation methods, and then aggregating them into a joint geospatial interface to highlight convergent and competing interests. Illustrated with the boreal region of northwestern Quebec (Canada), we discuss how the riskscape framework balances Indigenous and non-Indigenous perspectives in a non-hierarchical assessment of values at risk.