Planning Strategies Research Articles

Path planning of manure-robot cleaners using grid-based reinforcement learning

The use of a robot cleaner for manure removal improves housing conditions for dairy cows in the face of labor shortages. However, current robot cleaners follow programmed fixed routes without considering the dynamic behaviors of cows. This cleaning approach is less efficient and leads to more cow-robot encounters or collisions, thus affecting animal welfare. To address these issues, this paper (1) developed heatmap models for cow locations and defecation behaviors; (2) proposed a dynamic path planning approach for the manure robot cleaner using Grid-based Reinforcement Learning; (3) incorporated cow location information and defecation behavior into the path planning process; (4) compared the performance of the proposed approach with two different cleaning methods: the current fixed programmed cleaning in practice and the ideal path produced by simulated annealing for traveling salesman problem. The simulations mimic the situation in a barn at Dairy Campus of Wageningen Livestock Research located in Leeuwarden (the Netherlands). Obviously, the best performance was achieved when the route was executed without cows present, resulting in no cow-robot collision. However, with cows present, the proposed dynamic path planning strategy achieved a 67.6% reduction in cow-robot encounters while maintaining 85.4% of the cleaning performance compared to the current programmed fixed routes. Compared to the ideal path produced by simulated annealing for traveling salesman problem, the proposed dynamic path planning approach achieved 5% better cleaning performance, at the cost of 25% more cow-robot encounters due to its longer working path. We conclude the proposed grid-based Reinforcement Learning solution for manure robots in barns cleaned most efficient with the least interference with cow traffic.

Health workforce forecast in the university hospital: evidence from Lithuania

BackgroundThe increasing shortage of staff in healthcare facilities worldwide calls for a human resource planning strategy in order to ensure safe, timely and patient-centred care. The purpose of this paper is to provide an analysis and supply and demand projections of nurses, midwives, and radiographers within the labor market of the largest university hospital in the Baltic States by 2030.MethodsThe staff supply was calculated on the intake and outflow of persons in the labour market annually for various factors. Projections for the demand of nurses, midwives, and radiographers took into account the different needs of the population, categorized by gender and age, for the services offered within the institution.ResultsThe analysis highlights significant projected shortages in the supply of nurses and radiographers by 2030, while the supply of midwives is expected to meet the demand. The projected supply of nurses in 2030 will be lower than in 2021. Projected nurses demand in 2025 according medium scenario - shortage of 59 nurses, on prospective scenario - of 331 nurses. In 2030 according medium scenario - shortage of 173 nurses on prospective - of 772 nurses. The projected supply of radiographers in 2030 will be higher than in 2021. Projected radiographers demand in prospective scenario which is the most likely in 2025 - shortage of 26 and in 2030 - shortage of 52 radiographers. The projected supply of midwives in 2030 will be higher than in 2021. The variables influencing the increase in the demand for midwives did not exceed the projected supply in the institution, indicating a balanced supply-demand scenario for midwives.ConclusionsDue to the rising demand for nurse and radiographer services from the aging population, the predicted supply of nurses and radiographers will be insufficient. To ensure the projected demand for nurses in the medium and prospective scenarios, the nurses recruited each year should increase up to 38% in the medium scenario and 69% in the prospective scenario from 2022. In the prospective demand scenario, the recruitment of radiographers should increase three-fold and the recruitment of midwives should be reduced by 30%.

Risk Assessment of Community-Scale High-Temperature and Rainstorm Waterlogging Disasters: A Case Study of the Dongsi Community in Beijing

With the advancement of urbanization and acceleration of global warming, extreme weather and climate events are becoming increasingly frequent and severe, and climate risk continues to rise. Each community is irreplaceable and important in coping with extreme climate risk and improving urban resilience. In this study, the Dongsi Community in the functional core area of Beijing was explored, and the risk assessment of high temperatures and rainstorm waterlogging was implemented at the community scale. Local navigation observations were integrated into a theoretical framework for traditional disaster risk assessment. The risk assessment indicator system for community-scale high-temperature and rainstorm waterlogging disasters was established and improved from a microscopic perspective (a total of 22 indicators were selected from the three dimensions of hazard, exposure, and vulnerability). Geographic Information Systems (GIS) technology was used to integrate geographic information, meteorological, planning, municipal, socioeconomic and other multisource information layers, thus enabling more detailed spatial distribution characteristics of the hazard, exposure, vulnerability, and risk levels of community-scale high temperatures and rainstorm waterlogging to be obtained. The results revealed that the high-risk area and slightly high-risk area of high-temperature disasters accounted for 13.5% and 15.1%, respectively. The high-risk area and slightly high-risk area of rainstorm waterlogging disasters accounted for 9.8% and 31.6%, respectively. The high-risk areas common to high temperatures and waterlogging accounted for 3.9%. In general, the risk of high-temperature and rainstorm waterlogging disasters at the community scale showed obvious spatial imbalances; that is, the risk in the area around the middle section of Dongsi Santiao was the lowest, while a degree of high temperatures or rainstorm waterlogging was found in other areas. In particular, the risk of high-temperature and rainstorm waterlogging disasters along Dongsi North Street, the surrounding areas of Dongsi Liutiao, and some areas along the Dongsi Jiutiao route was relatively high. These spatial differences were affected to a greater extent by land cover (buildings, vegetation, etc.) and population density within the community. This study is a useful exploration of climate risk research for resilient community construction, and provides scientific support for the planning of climate-adaptive communities, as well as the proposal of overall adaptation goals, action frameworks, and specific planning strategies at the community level.

Urban Agriculture: Exploring Its Potential, Challenges, and Socio-Economic Impacts

Urban agriculture, the practice of growing and cultivating food within urban and peri-urban areas, has garnered increasing attention in recent years due to its potential to address various challenges related to food security, environmental sustainability, and socio-economic development. This review article provides a comprehensive exploration of urban agriculture, examining its multifaceted potential, the challenges it faces, and its socio-economic impacts in greater detail. The article delves into the diverse forms of urban agriculture, ranging from rooftop gardens and community allotments to vertical farming and aquaponics, highlighting their contributions to local food production, green spaces, and community cohesion. Additionally, the review discusses the challenges and constraints associated with urban agriculture in more depth, including issues related to land availability, soil contamination, water management, and regulatory hurdles. Furthermore, it examines the socio-economic impacts of urban agriculture with a nuanced perspective, exploring how it can lead to improved access to fresh produce, job creation, poverty alleviation, and social empowerment at both individual and community levels. By shedding light on the complexities of urban agriculture and providing a more comprehensive analysis of its potential and challenges, this review aims to inform policymakers, urban planners, researchers, and practitioners about the transformative potential of urban agriculture and the need for supportive policies and interventions to foster its sustainable growth and maximize its benefits for urban communities, the review dives deeper into the various forms of urban agriculture, providing detailed insights into their unique characteristics, benefits, and challenges. Rooftop gardens, for example, are explored not only for their contribution to local food production but also for their role in mitigating urban heat island effects, improving air quality, and enhancing building energy efficiency. Community allotments are examined in the context of social cohesion, community engagement, and opportunities for education and skill-building. Vertical farming and aquaponics are discussed in terms of their innovative technologies, resource efficiency, and potential scalability to meet the growing demand for fresh produce in urban areas, the review delves into the challenges and constraints associated with urban agriculture, offering nuanced analyses of their underlying causes and potential solutions. Land availability issues are examined in relation to urban sprawl, land-use planning policies, and competing demands for space in densely populated cities. Soil contamination concerns are explored in light of industrial legacies, brownfield redevelopment, and strategies for soil remediation and regeneration. Water management challenges are discussed in the context of water scarcity, pollution, and the need for sustainable irrigation practices in urban agriculture. Regulatory hurdles are analyzed in terms of their impact on the viability and scalability of urban agriculture initiatives, highlighting the importance of supportive policy frameworks, zoning regulations, and land-use planning strategies. the review provides a comprehensive examination of the socio-economic impacts of urban agriculture, drawing on empirical evidence from case studies and research findings. It explores how urban agriculture can contribute to improved food access and nutrition outcomes, particularly for vulnerable populations living in food deserts and low-income neighborhoods.

Georeferencing Sunda pangolin Manis javanica records in Singapore

Abstract In Singapore, the Critically Endangered Sunda pangolin Manis javanica is threatened by habitat loss and fragmentation, and road traffic collisions. To mitigate these threats, an understanding of its spatiotemporal distribution is needed, as identified in the National Conservation Strategy and Action Plan for the species. However, Sunda pangolin occurrence data are held in multiple separate databases, are typically collected using non-standardized methods, and often lack accurate location details. To compile a complete georeferenced database of Sunda pangolin records in Singapore, we consolidated occurrence data from heterogeneous databases and mainstream and social media, and converted locality descriptions into geographical coordinates. We demonstrate the use of this database to analyse data on rescued pangolins and those killed on roads, to aid conservation efforts in Singapore, and describe other potential applications. We georeferenced 482 records of pangolin sightings, rescues and roadkill for 1996–2021, finding an increase in all three over the study period. Roadkill and rescues occurred mostly in central and western Singapore, close to forested areas, and were predominantly of subadults and adult males. The data can be used to inform threat mitigation strategies, post-rescue release plans and further research. The database has already been used in practice, contributing to environmental impact assessments and conservation recommendations. Overall, this georeferenced database demonstrates the value of citizen science and collating wildlife data from multiple sources, and the methods used can be applied to other taxa to aid conservation strategies.

Historical earthquakes in the Holy Cross Mountains, Poland, true or false? Unveiling insights through archaeoseismology

The Holy Cross Mountains are an intraplate range with a limited historical seismicity record. The only documented earthquakes include the February 6, 1837 M 4.3 event, which caused ground cracks, and swarm events from February 1932 (M ∼ 3.5), likely triggered by the Holy Cross Fault (HCF) or sub-perpendicular faults. The apparent lack of older destructive earthquakes in historical catalogs motivated us to conduct archaeoseismological research to improve seismic hazard assessment, risk mitigation, and urban planning strategies, ultimately benefiting local communities. We focused on the 12th-century Collegiate church of Saint Martin in Opatów, located near the Holly Cross Fault (HCF). We report numerous damage features, such as leaning, bulging, and twisted walls, dropped keystones in Romanesque and Gothic portals, strike-slip displacements of these portals, surplus, oversized buttresses, and walled-up portals. While some deformations may result from humid loess instability and war destructions, our data, combined with historical records, suggest two to three seismic events in the past 800 years as a cause. We argue these deformations were co-seismically triggered by either large far-field events, like the 1259 AD earthquake, or local, shallow small-magnitude events significantly amplified by site effects. This indicates potential seismic activity in the Holy Cross Mountains during Medieval times. The absence of historical records does not imply the absence of earthquakes.

Investigating urban morphological drivers of household water use in developing economies: A structural equation model approach

Urban populations are snowballing, increasing household (HH) water consumption. The growing housing density, the expanding infrastructure, and altered land use patterns place increasing pressure on the water supply and usage. This makes it harder for urban HHs to obtain clean water and worsens water scarcity, with infrastructural and environmental implications for highly populated metropolitan areas. This study aims to quantitatively evaluate the impact of urban morphology on household water use in a developing economy using a Structural Equation Model (SEM), specifically within the growing urban centres surrounding Kolkata in South Bengal. The primary hypothesis projects an increase in urban morphological indicators and HH characteristics that significantly affect water use. The findings reveal that increases in urban morphological indicators are associated with a 34.2% decrease in HH water use, highlighting the importance of urban planning strategies that emphasize compact and diverse urban forms. This work highlights new ways of building cities that consider morphological aspects and allow cities to expand in a way that conserves HH water while being resilient to rapid urban change.

Institutional change of the Colombian army 2012–2021

ABSTRACT Military transformations occur reactively in response to changes in environmental conditions and conflicts. Likewise, military transformations show a tendency to copy the best practices of the most powerful forces and of organizations like North Atlantic Treaty Organization (NATO). However, little is known about the effect of a proactive planning strategy on the transformation process. This article raises the theoretical debate on the institutional change of the Colombian Army, presenting evidence that allows us to define whether it has been carried out in a reactive, evolutionary way or with a design-based approach which would lead to the development of institutional work through the modification of the factors of military capabilities. The main result shows the presence of institutional work to generate disruptions in the Army. Particularly when altering the doctrine, changes in education and training are triggered, which allows the organizational structure to be redesigned to adopt new practices. However, limitations in the acquisition and deployment of new technologies and infrastructure inhibit institutional change and organizational transformation.

Enhancing safety feedback to the design of small, unmanned aircraft by joint assessment of impact area and human fatality.

Advantages of commercial UAS-based services come with the disadvantage of posing third party risk (TPR) to overflown population on the ground. Especially challenging is that the imposed level of ground TPR tends to increase linearly with the density of potential customers of UAS services. This challenge asks for the development of complementary directions in reducing ground TPR. The first direction is to reduce the rate of a UAS crash to the ground. The second direction is to reduce overflying in more densely populated areas by developing risk-aware UAS path planning strategies. The third direction is to develop UAS designs that reduce the product in case of a crashing UAS, where is the size of the crash impact area on the ground, and is the probability of fatality for a person in the crash impact area. Because small UAS accident and incident data are scarce, each of these three developments is in need of predictive models regarding their contribution to ground TPR. Such models have been well developed for UAS crash event rate and risk-aware UAS path planning. The objective of this article is to develop an improved model and assessment method for the product In literature, the model development and assessment of the latter two terms is accomplished along separate routes. The objective of this article is to develop an integrated approach. The first step is the development of an integrated model for the product . The second step is to show that this integrated model can be assessed by conducting dynamical simulations of Finite Element (FE) or Multi-Body System (MBS) models of collision between a UAS and a human body. Application of this novel method is illustrated and compared to existing methods for a DJI Phantom III UAS crashing to the ground.

Risk and vulnerability analysis of road network in landslide prone areas in Munnar region, India

Catastrophes like landslides have the potential to impair critical transportation infrastructure, particularly road networks. The hilly regions in the state of Kerala in India are particularly prone to hazards and changing climate conditions. During the monsoon season, landslides are common in the Western Ghats, and the intensity of adverse impacts is more severe due to its densely populated regions. The study area of this research is in Idukki district of Kerala, where over 60 % of the land is prone to landslides. The monsoon rains bring with them a slew of disastrous landslides in the region. Most of the roadways in the study area are often disrupted due to landslides. Landslide risk assessment (LRA) is a crucial component of research on adverse impacts of landslide. The use of Geographical information System (GIS) and Multi Criteria Decision Analysis (MCDA) using Analytical Hierarchical Process (AHP) for susceptibility mapping and hazard risk assessment assists in the identification of disaster-prone areas. The data collected by field surveys were used to confirm the study results and the high-risk zones of the region were identified and the risk maps are prepared for the region as well as for the road network in the region. The risk of landslides may be described as the possibility of negative repercussions on road network thereby adversely impacting the inhabitants of the region. The landslide risk assessment of the road network in a hilly region is carried out which gives important insights for risk management and for future planning of resilient development in the region. This study enhances the knowledge for management of road network risk and vulnerabilities in intricate hilly region settings by developing a thorough vulnerability analysis framework. The research advances by giving transportation engineers a useful quantitative tool for identifying the risk and vulnerabilities of road network and directing design strategies and mitigation measures to lessen the possible negative effects of disruptive events like landslides on road infrastructure. The research findings could be an input for policy makers to plan for alternative resilient strategies for landslide risk management in road networks. The rational methodology adopted here could be replicated for carrying out risk and vulnerability assessment in other landslide prone areas.

Study on temperature regulation function of green spaces at community scale in high-density urban areas and planning design strategies

In recent years, the frequency of extreme high-temperature events has gradually increased. To better understand the impact of urban green space coverage's spatial pattern on land surface temperature (LST), this study selected three sample areas along the urban-rural gradient in Shanghai. Using LST inversion and resampling methods, LST data for different grid sizes were obtained for spring, summer, and winter in the 2010s, 2015s, and 2020 s. A boosting regression tree model was employed to determine the key indicators affecting LST and effective cooling thresholds. The impact of green quality, structure, and pattern at the community scale on LST was discussed, providing feasible suggestions for green space planning and design in different urban spaces. The study found significant differences in the spatial patterns of green areas and LST among the three sample regions. The quantity and integrity of green spaces in the Huangpu, Minhang, and Songjiang sample areas have progressively improved, with overall green coverages of 19 %, 38 %, and 43 %, respectively. As grid size increases, the relative influence of fractional vegetation coverage (FVC) on LST generally decreases, whereas the relative influence of green structure and patterns gradually increases. Taking the summer of the 2020 s as an example, the influence of FVC on the three study sample areas was 80.79, 83.36, and 87.18 at a 30 m grid size, which decreased to 48.87, 40.59, and 47.64 at a 120 m grid size. The green structure's impact rose from 13.09, 15.22, and 10.6–30.01, 51.82, and 38.5; the influence of green patterns increased from 6.12, 1.42, and 2.21–21.13, 7.6, and 13.86. Key indicators affecting LST include FVC (Fractional Vegetation Coverage), AREA (Green Patch Area), PD (Patch Density), COHESION (Patch Cohesion Index), and ED (Edge Density). High temperatures in summer are one of the ecological issues that need special attention in Shanghai's green space design. Setting the green space proportion to 35 % while avoiding fragmentation and low vegetation coverage can achieve effective cooling. This study's main advancement lies in utilizing machine learning algorithms to identify the principal green spatial pattern impact factors and key thresholds influencing LST at the community scale in Shanghai. The related results and proposed strategies provide a research framework and strong basis for special regulations in urban green space system planning concerning urban thermal environments. They offer references for urban renewal and new town planning to address climate change and urban high-temperature issues, such as clear requirements for optimal green space area at the community scale, community park spatial layout and quantity regulations, and urban park planning design suggestions. This study also highlights obstacles in the practical application of planning and design strategies, which can help avoid difficulties in implementing planning policies. It attempts to set goals for community-scale vegetation planning in China from a policy perspective and provides relevant recommendations.

Impact of urban form on carbon emissions of residents in counties: evidence from Yangtze River Delta, China.

Urban form is a key factor affecting carbon emissions. Accurately estimating the impact of urban form on the carbon emissions of residents (CER) is an important prerequisite for China to adopt effective low-carbon spatial planning strategies and respond to climate change. However, counties mainly account for China's energy consumption, and the relationship between their urban form and the CER remains unclear, limiting their low-carbon development. Therefore, in this study, the PLS-SEM model and data from 90 counties in the Yangtze River Delta are used to determine the extent and ways that urban form affects the CER. The model considers the impact of both geometric-aspect urban form factors (urban scale, compactness, spatial structure, and urban shape) and built environment-aspect urban form factors (public service facilities, urban greening, road traffic, public transportation, and urban energy infrastructure) on the CER. The results indicate that urban form factors related to the built environment (public service facilities, urban greening, road systems, and municipal infrastructure) have a direct impact on the CER. Geometric-aspect urban form factors (size, compactness, spatial structure, and shape) not only directly affect the CER but also indirectly affect the CER by altering built environment-aspect urban form factors. This study identifies the complex relationship between urban form and the CER, facilitating the coordinated integration of multiple elements and providing a basis for the formulation of low-carbon spatial planning strategies for counties.

Few-Human-Interaction Reinforcement Learning for Autonomous Transbronchial Intervention.

The transbronchial interventional surgery presents challenges with winding and convoluted pathways, prone to compression and friction. Current autonomous planning struggles to reach deeper bronchial positions, and hard to consider multiple conflicting goals simultaneously. This article introduces an innovative planning scheme with preference weights to achieve smooth, frictionless, and collision-free autonomous transbronchial intervention with continuum robot (CR). A few-human-interaction twin-delayed deep deterministic policy gradient (FHITD3) generated from surgeon preference guidance is proposed, which determines the optimal strategy for the motion of CR. Preference knowledge is generated through interaction between human and few diversity samples. An abstract actuator space description is proposed for the posture and position representation of CR during movement within bronchus. A contact motion analysis strategy is proposed to calculate real-time attitude of CR in contact with bronchus. In addition, an oscillation suppression approach to address CR's unsmooth distal end trajectory is proposed. Simulated experiments show that the CR autonomously completes intervention tasks with a smooth and stable trajectory, reducing distal end oscillation by over 45%. It achieves a target endpoint within the fourth level bronchus (approximately 5 mm diameter) with over 90% probability.

Identifying the determinants of E-commerce offerings among grocery store locations in the United States: A spatial econometric analysis

This paper leverages store location data and analysis software from retail industry vendors to analyze the unique geographies of electronic commerce (e-commerce) offerings among major grocery chains in the United States. Join-Count statistics are calculated to identify patterns of clustering among offerings, and a spatial probit model is implemented to regress various trade area characteristics on a given grocery banner's decision to offer some form of e-commerce (pickup, delivery, or both) or no offering at a given store location. A regional case study of the Southeastern United States demonstrates how model results can shift based on scale, pointing to unique regional dynamics that deviate from broader national trends. This analysis carries implications for location planning and competitive defense strategies in the grocery industry, and also establishes avenues for future research.

A local collision-free motion planning strategy for hyper-redundant manipulators based on dynamic safety envelopes

A local collision-free motion planning strategy for hyper-redundant manipulators based on dynamic safety envelopes

Flood risk awareness and transportation mode choice in communities with varying flooding frequencies: The cases of Bozkurt, Kastamonu, Turkey and Malanday, Marikina, Philippines

This study investigates the post-flood transportation mode choices (TMC) of communities exposed to floods of varying frequencies, focusing on Bozkurt, Turkey, recently afflicted by a major flood, and Malanday, Philippines, which endures an average of 10 floods annually. The study considers 17 factors affecting TMC, including age, occupation, income, housing type, flood experience, education level, changes in travel time, primary transportation mode, duration of residence, gender, marital status, relocation status, personal losses, disruption of daily activities, time to return to routine, satisfaction with road maintenance, and satisfaction with flood measures. Data were collected through surveys and analysed using regression analysis.The findings indicate that personal and cultural characteristics, and flood frequency, have limited effects on TMC. The most impactful factors on post-flood TMC are changes in travel time (42.11 %), personal losses (23.75 %), and satisfaction with road maintenance (11.30 %). The study demonstrates that flood risk awareness is directly related to education level and flood experience. In Malanday, where 84 % of the population are university or high school graduates, floods are regarded as routine events. In contrast, in Bozkurt, where only 37 % have similar education levels, the community experienced panic under flood conditions, adversely affecting decision-making processes.The research provides insights into how communities exposed to floods adjust their TMC, offering essential information for mitigating flood risks and increasing flood awareness. Moreover, the findings deliver suggestive information for local governments and planners in developing more effective flood management and transportation planning strategies.

Navigating Financial Success: Comprehensive Strategies for Optimal Funding and Strategic Financial Planning

In the world today, globalization has made the business environment very dynamic, and as such, organizations must come up with good financial strategies that will help them remain viable in the long run. This paper aims to discuss general approaches to effective funding and financial planning which is vital in enhancing financial performance and reducing risks that may occur in the dynamic economic environment. The use of emerging financial technologies like blockchain, AI, and big data has changed how financial management is done and has made it more accurate and efficient. However, these technologies also present new problems such as cyber risk and legal concerns. Also, the increasing concerns of Environmental, Social, and Governance (ESG) factors in investment decisions show that financial planning should consider sustainability. The paper also focuses on the specific financial problems of SMEs and the necessity of targeted measures to help them improve their financial management. This paper, based on a literature review done between the years 2019 to 2024, aims at providing a framework for financial success in the form of strategic financial planning, efficient financing strategies, FinTech innovations, and ESG factors to help firms succeed in an ever-evolving economy. Keywords: Strategic Financial Planning. Optimal Funding, FinTech, Environmental, Social, and Governance (ESG), Small and Medium-Sized Enterprises (SMEs).

Advanced Imaging Techniques in Preoperative Planning for Brain Tumor Resection: Evaluating the Impact on Surgical Precision and Neurological Outcomes

This study investigates advanced imaging techniques and their impact on surgical precision and neurological outcomes in preoperative planning for brain tumor resections. Selected studies include large human sample sizes, peer-reviewed research, systematic reviews, and meta-analyses focusing on advanced imaging techniques and their impact on surgical precision and neurological outcomes. Latest imaging modalities experiments on animal studies are considered. Systematic review of recent literature on advanced imaging modalities—such as MRI, fMRI, PET, and DTI—and their application in preoperative planning. Our findings suggest advanced imaging techniques, including Functional MRI, Ultra-High Field MRI, Diffusion Tensor Imaging (DTI), PET/CT and Deuterium Magnetic Resonance Spectroscopy (2H MRS) improve surgical precision and neurological outcomes in brain tumor resections by enhancing tumor targeting, reducing morbidity, and improving resection accuracy. Future advancements should focus on integrating and optimizing these technologies to further improve preoperative planning and patient-specific treatment strategies.

Nature-Based Solutions Scenario Planning for Climate Change Adaptation in Arid and Semi-Arid Regions

Extreme climatic conditions cause a decrease in ecosystem services, the disruption of the ecological balance, and damage to human populations, especially in areas with socially vulnerable groups. Nature-based solutions applying blue-green infrastructure (BGI) against these negative impacts of climate change have an important role in planning sustainable cities. This study aims to identify priority areas and develop scenarios and strategies for spatial planning to understand the tradeoffs in approaches and to maximize the benefits of ecosystem services provided by BGI in cities with arid and semi-arid climates, using Phoenix, Arizona, a swiftly urbanizing city in the Sonoran Desert, as the study area. Using GIS-based multi-criteria decision-making techniques and the Green Infrastructure Spatial Planning model integrated with the city’s existing water structures, this study is conducted at the US census scale. The hotspots for BGI are mapped from the combined GIS-based multi-criteria evaluation and expert stakeholder-driven weighting. In the hotspots where priority areas for BGI in Phoenix are identified, the city center area with a high density of impervious surfaces is identified as the highest priority area. It is revealed that social vulnerability and environmental risks (flooding, heat) have a positive correlation in Phoenix, and stormwater management and the urban heat island are the criteria that should be considered first in BGI planning.

Determinants of customer buying behaviour in omnichannel retailing: a systematic literature review and future research directions

PurposeAdvances in digital technologies and the growing number of touch points have had a significant impact on the shopping behaviour of omnichannel customers. Several research papers have explored different facets of omnichannel, but only a few have thoroughly explored the literature on showrooming and webrooming simultaneously. This paper aims to identify the key groups of antecedents influencing customer buying behaviour in omnichannel, under the influence of digital technologies, with a particular focus on showrooming and webrooming.Design/methodology/approachOur study conducted a systematic literature review to identify the factors influencing customers’ buying behaviour in omnichannel, which have been the subject of academic discussion over the last decade. We finalized 149 articles for the thematic analysis and identified three groups of antecedents: channel-related, product-related and consumer-related with their subgroups.FindingsUnder channel-related antecedents, cost and perceived benefits, search convenience, need for interaction and situational circumstances have been identified as major attributes. The expressiveness of the product, product demonstration and search and experienced products have been identified under product-related antecedents, followed by price consciousness, past experiences, perceived risks and shopping motivations as leading attributes under consumer-related antecedents. The study revealed the multifaceted influence of digital technologies on omnichannel buying behaviour. Digital technologies are shaping the antecedents related to channels, products and consumers. Digital technologies simultaneously mediate between antecedents and the selection of a specific path within an omnichannel environment. Showrooming and webrooming should no longer be seen as general concepts. The rise of digital technologies has led to the development of new consumer journey patterns and the blurring of distinctions between showrooming and webrooming. A conceptual framework has been proposed to understand consumers' omnichannel behaviour, having considered the identified antecedents and the role of digital technologies.Practical implicationsThis study advances the academic understanding of consumer behaviour in omnichannel under the influence of digital technologies and provides important implications for omnichannel management. With the advancement of digital technologies such as augmented reality and virtual reality, retailers should implement channel integration strategies to bridge the gap between online and offline channels, providing a memorable shopping experience for omnichannel customers.Originality/valueThis study is unique because it identifies and analyses the antecedents of consumer behaviour in omnichannel settings under the influence of digital technologies. It also uncovers new potential combinations of showrooming and webrooming patterns. The proposed framework can help retailers in their future planning of omnichannel strategies.