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Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

In Trinidad and Tobago, there is significant reliance on the traditional and centralized police service to engage in crime response and suppression in urban and rural areas. In this regard, policing scholarship has largely focused on the impact of policing within urban areas, producing a gap in knowledge on what policing rural spaces entails. Despite this, there is some understanding that policing rural spaces can engender diverse challenges and calls for variability in policing strategies. The current study examines the lived experiences of police officers stationed in rural communities in Trinidad and Tobago.

Using the descriptive phenomenological approach, semi-structured interviews were conducted with eleven police officers stationed in rural communities throughout the country.

Interviewees narrated the importance of community dynamics and community-specific needs in shaping their roles and functions when operating in and serving these communities. Three major themes were identified: (1) network activity in policing; (2) engagement in localistic and service-oriented approaches and (3) community-specific challenges.

The findings suggest that while there is an emphasis on traditional law enforcement responsibilities, in the rural context, police responsibilities and duties are constantly being redefined, reframed and broadened to meet the contextual community and geographic-specific diversities and demands.

Australia appears to be encountering a crisis in the protection of certain heritage places, despite its strong reputation in heritage conservation built up since the 1970s. Consequently, this paper examines changes to national cultural heritage management policy over the last few decades to understand more about this crisis.

Indigenous (Aboriginal and Torres Strait Islander heritage) was selected as the key focus. This paper applies a cultural heritage management framework tested first in Hong Kong to measure Australian paradigm change over 45 years.

It found the 1990s shift away from the provision of independent technical advice on national heritage policy has had a major impact. This shift is based on a change in ethos away from the earlier Whitlam/National Estate broader vision of heritage responsibilities towards a narrower more conservative one at the national level. Also, it found that studies and policymaking should allow for Indigenous voices. More Indigenous input in heritage policy formulation at all levels of government would further decolonise Indigenous heritage governance to deal justly with Indigenous Australians and their heritage.

Resources did not allow for comparative studies of the non-Indigenous (historic) and natural heritage as part of the current study.

The study also included a consultation paper and an online conference presentation that have raised questions about the efficacy of current national policy on Indigenous places, on which a national conversation is urgently needed. The recent review of the National Heritage Strategy by the Australian Commonwealth Government based some of its proposed options on those listed in the consultation paper to initiate this conversation in a limited way.

One finding is that attention to heritage policy and protection must be ongoing at all levels of government and inclusive of First People's human rights, particularly those concerning their heritage. In regard to Australia, most Aboriginal and Torres Strait Islander respondents in this study would like to see targeted funding return for more than just iconic Indigenous places and for the creation of a more independent heritage body that allows them more self-determination in the care of their heritage.

The paper's value is that it investigates the Australian Heritage Commission's impact in the development of Australian cultural heritage management and associated national policy. Also, it provides insights for other postcolonial or New World settler societies dealing with the same issues or any decision-makers considering establishing a national independent body to oversee heritage protection and policymaking.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

In this article, the aim is to document the divergences/convergences between the market perceptions of quality and the financial estimations for office buildings relative to the notion of centrality and the distance to the central business district (CBD).

Based on a hierarchical approach that decomposes and estimates the perceived quality of buildings from the stakeholders’ perspectives, we study the geographies of perceived quality measures in the Greater Paris Metropolis and compare them to the financial geography.

The perceived location quality decreases with distance from the CBD whereas judgments on the built structure and the workplace do not, exhibiting a ring-shaped pattern. The gradient of the components of the perceived quality are heterogeneous, having positive, negative or null values. Appraisers tend only to consider the quality of location in their estimations.

This article raises the issue of fair spatial judgments by appraisers and the financial market. Monocentricity is not the rule in the market perceptions of quality. It suggests that financial estimates are strongly biased, with mental representation of centrality as a judgmental heuristic.

Using a real-time road network combined with historical traffic data for Al-Salt city, the paper aims to propose a new federated genetic algorithm (GA)-based optimization technique to solve the dynamic vehicle routing problem. Using a GA solver, the estimated routing time for 300 chromosomes (routes) was the shortest and most efficient over 30 generations.

In transportation systems, the objective of route planning techniques has been revised from focusing on road directors to road users. As a result, the new transportation systems use advanced technologies to support drivers and provide them with the road information they need and the services they require to reduce traffic congestion and improve routing problems. In recent decades, numerous studies have been conducted on how to find an efficient and suitable route for vehicles, known as the vehicle routing problem (VRP). To identify the best route, VRP uses real-time information-acquired geographical information systems (GIS) tools.

This study aims to develop a route planning tool using ArcGIS network analyst to enhance both cost and service quality measures, taking into account several factors to determine the best route based on the users’ preferences.

Furthermore, developing a route planning tool using ArcGIS network analyst to enhance both cost and service quality measures, taking into account several factors to determine the best route based on the users’ preferences. An adaptive genetic algorithm (GA) is used to determine the optimal time route, taking into account factors that affect vehicle arrival times and cause delays. In addition, ArcGIS' Network Analyst tool is used to determine the best route based on the user's preferences using a real-time map.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.