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The literature on the economics of location regarding creative activities is relatively scarce. Estimations, based on 369 newly created firms operating in creative industries in Portugal, which incorporate spatial effects of neighbouring regions in the location choices, yield the following results: (i) the concentration of creative and knowledge-based activities play an important role in location decisions of new creative establishments; (ii) creative firms tend to favour a diversified industrial tissue and related variety, in order to enjoy from inter-sectorial synergies; (iii) high education at a regional level has a highly significant, positive effect on location decisions, while lower educational levels of human capital negatively affect those decisions; (iv) tolerant/open environments attract creative activities; (v) creative firms tend to favour municipalities where the stock of knowledge and conditions for innovative activity are higher; (vi) municipality's attributes are more important in terms of firms' location decisions than the characteristics of nearby regions. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to design a facility network for the weavers to do direct business in the Indian handloom industry by using tourists as potential customers. Design/methodology/approach: Data from 4,001 weavers of the handloom industry and 82 tourist locations of Varanasi city were collected. This data was analysed using the k-mean and elbow methods to determine the locations and the optimal number of collection centres, selling stores and warehouses to provide opportunities for the weavers to do direct business. Findings: The study's findings showed that a greater opportunity could be provided with four optimal collection centres and selling stores, along with two warehouses in the handloom industry of Varanasi city. These results provide valuable guidance for policymakers to plan the Varanasi handloom network of facilities efficiently and effectively to improve the conditions of weavers. Originality/value: Determining the optimal locations is crucial for designing a facility network. The proposed network will aid the government and policymakers in comprehending and pinpointing potential sites to establish new facilities in the handloom industry in Varanasi, a city with tourism potential. [ABSTRACT FROM AUTHOR]

Onsite production of gigawatt-scale wind- and solar-sourced hydrogen (H2) at industrial locations depends on the ability to store and deliver otherwise-curtailed H2 during times of power shortages. Thousands of tonnes of H2 will require storage in regions where subsurface storage is scarce, which may only be possible using liquid organic H2 carriers. We evaluate aboveground system with a focus on providing technical insights into toluene/methylcyclohexane (TOL/MCH) storage systems in locations suitable for gigawatt-scale wind- and solar-powered electrolyzer systems in the United States. Here we show that the levelized cost of storage, at a national median of US dollar $1.84/kg-H2 is spatially heterogeneous, causing minor impact on the cost of H2 supply in the Midwest, and significant impact in Central California and the Southeast. While TOL/MCH may be the cheapest aboveground bulk storage solution evaluated, upfront capital costs, modest energy efficiency, reliance on critical materials and pre-sulfided catalysts, and greenhouse gas emissions from heating are opportunities for further development. Dedicated wind-sourced hydrogen (H2) can decarbonize industries but requires thousands of tonnes of H2 storage. Storing H2 as methylcyclohexane can outcompete alternative aboveground solutions with modest effects on delivery costs. [ABSTRACT FROM AUTHOR]

The spider mite species Oligonychus perditus Pritchard and Baker 1955 (Acari: Tetranychidae) is native to China, Japan, Korea, and Taiwan, where it has been reported as a pest of Juniperus spp. and some other conifer plants (Cupressaceae). In Europe the species, has been repeatedly intercepted on imported juniper plants. The EPPO has included O. perditus on the A1 list of pests recommended for regulation as quarantine pests, mostly because its hosts are of importance to the European nursery trade. In a survey conducted in Serbia between 2020 and 2023 O. perditus was found in 16 sampling locations on plants of the genus Juniperus, from the family Cupressaceae, as well as in order 16 sampling locations on plants of the genera Prunus and, Malus from the family Rosaceae. This species was collected on individual trees in backyards, gardens, and orchards, as well as in ruderal habitats. Populations of O. perditus were small and without economic impact. Introduction of this species into Serbia is probably a consequence of insufficient quarantine measures and relatively loose afforestation rules. [ABSTRACT FROM AUTHOR]

This work holistically evaluates the factors that can aid decision makers in finding the optimal location for food businesses in developing economies. It integrates the analytic hierarchy process (AHP) in determining criteria weights (i.e. benefit, opportunity, cost, risk) and the newly introduced three-way decision – Technique for Order Preference by Similarity to Ideal Solution (3WD-TOPSIS) method in identifying the priority factors. Applying the AHP yields the assignment of more priorities to benefits and opportunities rather than costs and risks, reflecting the benefit – or opportunity-oriented attitudes of food businesses. Meanwhile, the implementation of 3WD-TOPSIS results in the identification of government regulations and restrictions, proximity to consumers, parking capacity, supply chain strategy, and socio-economic status as the most crucial location decision factors. Findings from the comparative analyses show a high agreement between the results and those of other comparable methods. Managerial insights from these findings are outlined in this work. [ABSTRACT FROM AUTHOR]

Copyright of Al-Adab / Al-ādāb is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to investigate the socio-economic conditions of entrepreneurs that influence the growth of micro and small enterprises (MSEs) in the South Andaman District. In this study, a scheduled questionnaire-based survey research design was used, and a sample of 344 small business owners was collected for analysis. The data were processed using SPSS, and chi-squared test was applied for statistical analysis. The study's findings revealed that factors such as entrepreneurs' business experience, income levels, the number of working employees and ownership of house property significantly impact the growth of enterprises in the island region. However, factors like business location and sector of enterprises were found to be statistically insignificant in determining MSEs' growth in the island region. The study suggests that policymakers and local administrations should enhance support for micro, small and medium-sized enterprises in island regions by implementing policies such as island capital investment subsidies and island transport subsidies for MSEs. As a result, small businesses play a pivotal role by contributing to local employment, production and investment opportunities in the island region. [ABSTRACT FROM AUTHOR]

In most of the manufacturing industry, the distributional assumption of the online working processes is customarily unknown or hard to meet. In such situations, parametric charting mechanisms generally designed under normality assumptions of the model yield more false alarms and invalid out-of-control (OOC) comparisons. The nonparametric (distribution-free) charts are a better choice for practitioners in such cases as their in-control (IC) run length (RL) profiles remain the same. The study intends to develop a new distribution-free adaptive CUSUM sign (NPACUSUM-SN; named hereafter) chart for monitoring the process location. The proposed NPACUSUM-SN chart estimates the unknown process mean shift using an unbiased function and updates adaptively the reference parameter of the CUSUM statistic. The IC robustness of the conventional adaptive CUSUM and the proposed NPACUSUM-SN charts under the symmetric, skewed, and contaminated normal (CN) distributions have been computed using Monte Carlo simulations. The OOC RL profiles of the proposed study have been assessed for the initial state and the shift delay (steady state) in the processes. The proposed NPACUSUM-SN chart shows more resistance against non-normality and effective behaviour as compared to its conventional competitor. The proposed NPACUSUM-SN chart provides uniformly efficient RL characteristics as compared to its counterparts. Implementation of the proposal is made by using a manufacturing industry dataset along with an artificial dataset. [ABSTRACT FROM AUTHOR]

The relationships between industrialization and urban regions, as well as technological advancements, innovations, and new work patterns and organizations, significantly impact the structuring of cities. Industrial sectors can become key drivers in shaping the form and macrostructure of a city over time. By examining and evaluating the existing system of structures and relations in the settlements in order to "estimate the land use differentiations" that may arise in the future and "to determine the spatial location of industrial facilities or sites," a model has been developed. This model aims to predict potential "land use differentiations" and determine the "spatial location selection of industrial facilities or sites" in the future based on the analysis and evaluation of existing structures and relational systems in settlements. The model consists of the integration of the LUCAM, which is based on a cellular automata operating system, along with the "GIS-Based Integrated Industrial Area Location Selection Model," which evaluates all data under the main headings of natural structure characteristics, socio-economic structure characteristics, and built environment characteristics using weighted overlay analysis. In this article, the general structure of the model developed within the scope of the research and İnegöl sampling are explained. The outputs of this model can be used for alternative separation for logistics centers, residential areas, secondary centers, reinforcement areas, and industrial sites in different settlements. In addition, in the research, a detailed model was designed by integrating decision-makers (central administrations, local administrations, registered users, NGOs) into the urban planning process. The proposed model can be used as a tool in designing transportation and other urban systems (distribution order of equipment areas, green area system, grading of centers, etc.). [ABSTRACT FROM AUTHOR]

This study assessed the small-scale hydropower potential (SHP) of the Gidabo River catchment. The Soil and Water Assessment Tool (SWAT) hydrological model was used to estimate the streamflow in the river networks. The model was calibrated and validated at Messa and Apposto gauging stations, and the results for the coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) revealed that the observed and simulated streamflow results agree fairly well at the calibration and validation locations. Thus, the simulated streamflow at the sub-catchment outlets was used to determine design discharge at 50%, 75%, and 95% flow dependability. The potential assessment was conducted under a scenario of 500, 1000 and 2000 m horizontal intervals along the stream networks. The study revealed that the river catchment has the potential to develop run-of-river-type plants at different locations with 50%, 75%, and 95% dependability, though it varies from place to place. [ABSTRACT FROM AUTHOR]

Summary: Soybeans (Glycine max) are a preferred source of plant‐based proteins and oil in various applications in foods and feeds. When soybean is converted to soybean meal (SBM), the quality is determined by the protein content and its digestibility. Protein digestibility is reduced by anti‐nutritional factors like trypsin inhibitors (TI) and processing. The abundant genetic variations in soybean germplasm affect the quantitative trait of protein content. This study analysed the effect of location and planting dates on genetically identical soybeans grown in North Carolina (NC) and then compared the nutritional traits to similar commonly grown soybean varieties in other locations in the USA. The soybeans were analysed using NIRS and wet chemistry. It was found that soybean protein content ranged from 38.14% to 44.92% among the different varieties grown in three different locations in NC. Similarly, TI levels ranged between 28.22 and 33.11 mg g−1 among these varieties. The same varieties, when planted as either a full season or double crop, had different TI levels and were also impacted by planting location. However, there were no significant differences in the TI levels between the varieties and planting seasons. Furthermore, no significant difference in protein content among the varieties within the planting dates was found. Compared to soybeans grown in other parts of the USA, the average crude protein (CP) content was similar to those grown in Arkansas and Minnesota. The TI levels were significantly higher than those grown in Ohio, similar to that of Arkansas, and significantly lower than that of Minnesota. [ABSTRACT FROM AUTHOR]

The main objective of this article is to determine the relationship between mobile money services and the growth of small and medium enterprises (SMEs). A sample of 50 SMEs was collected. The probit model was used to estimate the result. The study established that mobile money services have a positive and significant relationship with the growth of SMEs. The determinants of mobile money services observed are; experience in business management, frequency of bill payment, size of business, male entrepreneur, operation of mobile money account, frequency of purchasing airtime, distance to financial institutions, number of business branches, mobile money accounts held, secondary education, technical support, location of business, number of workers and size of capital transaction. The challenges faced by entrepreneurs in mobile money transactions observed are: wrong manipulation of account, delays, environmental complexities, and loss of money due to hawkers. The result suggests that SMEs should intensify the use of mobile money services in their daily business transactions. It is a wise step toward business expansion. Entrepreneurs of SMEs should take advantage of the drivers of mobile money services to encourage the diverse use of digital technologists. Finally, entrepreneurs should avoid risky manipulations of their mobile money gargets. [ABSTRACT FROM AUTHOR]

The paper delves into the normative Productive City concept as outlined in the New Leipzig Charter, focusing on urban manufacturing's heterogeneity. We define urban manufacturing as manufacturing sectors located in proximity to housing. Urban manufacturing is analyzed based on sectoral (company data classified by NACE codes into 13 types of material industry) and spatial data, considering the distance to priority roads, supply areas, and land-use categories. The methodology is applied to Bochum, Gelsenkirchen, and Herne in the Ruhr area, utilizing 2018 data to identify material industry locations. We highlight differences between central and accessible, and more dispersed sectors in three groups. Group I, including other consumer goods, food products, clothing goods, and repair services, is predominantly located in central and mixed-use locations, suggesting these types could be preserved or developed by urban planners under the Productive City framework. However, there is a clear need for commercial and industrial spaces for emitting industries (Group II) to fully realize this concept. Construction industries (Group III) are often found in residential areas due to off-site activities. Challenges arise in historical industrial cities especially in integrated areas where existing zoning regulations and grandfathering rights restrict changes in manufacturing types or expansions near residential zones. [ABSTRACT FROM AUTHOR]

The gas-gathering pipeline network is a critical infrastructure for collecting and conveying natural gas from the extraction site to the processing facility. This paper introduces a design optimization model for a star–tree gas-gathering pipeline network within a discrete space, aimed at determining the optimal configuration of this infrastructure. The objective is to reduce the investment required to build the network. Key decision variables include the locations of stations, the plant location, the connections between wells and stations, and the interconnections between stations. Several equality and inequality constraints are formulated, primarily addressing the affiliation between wells and stations, the transmission radius, and the capacity of the stations. The design of a star–tree pipeline network represents a complex, non-deterministic polynomial (NP) hard combinatorial optimization problem. To tackle this challenge, a hierarchical optimization framework coupled with an improved genetic algorithm (IGA) is proposed. The efficacy of the genetic algorithm is validated through testing and comparison with other traditional algorithms. Subsequently, the optimization model and solution methodology are applied to the layout design of a pipeline network. The findings reveal that the optimized network configuration reduces investment costs by 16% compared to the original design. Furthermore, when comparing the optimal layout under a star–star topology, it is observed that the investment needed for the star–star topology is 4% higher than that needed for the star–tree topology. [ABSTRACT FROM AUTHOR]

The PM2.5 and PM10 particles were characterized in terms of morphology (size and shape) and surface elemental composition at two different (traffic and industrial) locations in urban region of India and further linked to different morphological defining parameters. The overall PM2.5 and PM10 showed significant daily variability indicating higher PM10 as compared to PM2.5. PM2.5/PM10 ratio was found to be 0.58 ± 0.10 indicating the abundance of PM2.5. Soot aggregates, aluminosilicates, and brochosomes particles were classified based on morphology, aspect ratio (AR), and surface elemental composition of single particles. The linear regression analysis indicates the significant correlation between area equivalent (Daeq) and feret diameter (Dfd) (R2 0.86–0.98). Higher aspect ratio (1.48 ± 0.87–1.43 ± 0.50) was noted at traffic site as compared to industrial site (1.33 ± 0.58–1.29 ± 0.30), while circularity showed the opposite trend. Fractal dimension (Df) of soot aggregates estimated by the soot parameters method (SPM) were found to be 1.70, 1.72, and 1.88, mainly attributed to vehicular emissions, biomass, and industrial emission/coal burning, respectively. This further inferred that freshly emitted soot particles exhibited lacey in nature with spherical shape (Df 1.70) at traffic site, while at industrial location, they were different with compact shapes (Df 1.88) due to particle aging processes. This study inferred the synoptic changes in mass, chemical characteristics, and morphology of aerosol particles which provide the new insights into individual atmospheric particle and their dynamic nature. [ABSTRACT FROM AUTHOR]

The insectivorous Northern Pitcher Plant, Sarracenia purpurea, recruits a dynamic biotic community in the rainwater collected by its pitcher-shaped leaves. Insect capture and degradation within the pitcher fluid (phytotelma) has been well documented as a mechanism for supplementing the plant's nitrogen, phosphorous, and micronutrient requirements. Metagenomic studies have shown a diverse microbiome in this phytotelm environment, including taxa that contribute metabolically to prey digestion. In this investigation, we used high-throughput 16S rDNA sequencing and bioinformatics to analyze the S. purpurea phytotelm bacteriome as it changes through the growing season (May–September) in plants from the north-central region of the species' native range. Additionally, we used molecular techniques to detect and quantify bacterial nitrogenase genes (nifH) in all phytotelm samples to explore the hypothesis that diazotrophy is an additional mechanism of supplying biologically available nitrogen to S. purpurea. The results of this study indicate that while prokaryote diversity remains relatively stable in plants at different locations within our region, diversity changes significantly as the growing season progresses. Furthermore, nifH genes were detected at biologically significant concentrations in one hundred percent of samples, suggesting that nitrogen fixation may be an important contributor to the S. purpurea nutrient budget. [ABSTRACT FROM AUTHOR]

Copyright of Contaduría y Administración is the property of Facultad de Contaduria y Administracion-Universidad Nacional Autonoma de Mexico and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

UWB has been in existence for several years, but it was only a few years ago that it transitioned from a specialized niche to more mainstream applications. Recent market data indicate a rapid increase in the popularity of UWB in consumer products, such as smartphones and smart home devices, as well as automotive and industrial real-time location systems. The challenge of achieving accurate positioning in indoor environments arises from various factors such as distance, location, beacon density, dynamic surroundings, and the density and type of obstacles. This research used MFi-certified UWB beacon chipsets and integrated them with a mobile application dedicated to iOS by implementing the near interaction accessory protocol. The analysis covers both static and dynamic cases. Thanks to the acquisition of measurements, two main candidates for indoor localization infrastructure were analyzed and compared in terms of accuracy, namely UWB and LIDAR, with the latter used as a reference system. The problem of achieving accurate positioning in various applications and environments was analyzed, and future solutions were proposed. The results show that the achieved accuracy is sufficient for tracking individuals and may serve as guidelines for achievable accuracy or may provide a basis for further research into a complex sensor fusion-based navigation system. This research provides several findings. Firstly, in dynamic conditions, LIDAR measurements showed higher accuracy than UWB beacons. Secondly, integrating data from multiple sensors could enhance localization accuracy in non-line-of-sight scenarios. Lastly, advancements in UWB technology may expand the availability of competitive hardware, facilitating a thorough evaluation of its accuracy and effectiveness in practical systems. These insights may be particularly useful in designing navigation systems for blind individuals in buildings. [ABSTRACT FROM AUTHOR]

In this paper we analyze the role of pollution for industry location and residence choice. We present a new economic geography (NEG) model in which manufacturing generates local pollution (that does not accumulate) and uses two types of labour input: unskilled workers that cannot migrate and work where they live; and high-skilled entrepreneurs that choose where to produce and where to live. Taking on board costless commuting or, in alternative, distance working, entrepreneurs can live in a different location from production. Both types of households enjoy utility from consuming all commodities (locally and imported variants) and suffer from local pollution. The resulting model is of the footloose entrepreneur variant, but involves two dynamic equations: the standard one governing the residential choice of entrepreneurs, and another one governing where production is located. The current paper analyses the discrete time dynamic process defined by a two-dimensional piecewise smooth map. Depending on parameters this map can have possibly coexisting attractors of various types (fixed points, cycles, closed curves as well as chaotic attractors). We analytically obtain stability conditions for the fixed points. Using numerical methods we describe also some global dynamic properties of the considered map. Finally, we propose an economic interpretation of the results concerning local stability analysis and global dynamics. [ABSTRACT FROM AUTHOR]

Given the intricate interactions among the economy, land use, and transportation, it is important to assess the multifaceted impacts of the freight corridor on these systems. This study introduces a land‐use transport interaction (LUTI) modeling approach to quantify the scope and magnitude of the impact of a railway corridor on the distribution of freight flows within an intermodal service network and industrial locations. The proposed model operates on two levels to analyze regional interactions between industrial locations and transportation dynamics. The upper‐level model simulates the industrial interactions among regions. Meanwhile, at the lower level, interregional trade connections are converted into freight demand, which is then assigned to a transportation network. Calibration of the trip length distribution is achieved by integrating data from truck GPS, railway waybills, and ship visas to develop a connection between the intermodal service networks and economic systems. The improved model offers a LUTI modeling approach tailored for the context of intermodal transportation, considering economies of scale associated with intermodal transportation services. It can not only analyze the impact of a freight corridor on freight flow redistribution but also identify areas that may be adversely affected by such redistributions. Taking the Yangtze River Economic Belt (YREB) as a case study, study results indicate significant enhancements in the economies of scale of railway services within the middle part of the YREB due to the development of the Haoji Railway Corridor (HRC). These changes significantly influence the location utility of industrial activities, with the coal processing activities demonstrating the most sensitivity to the evolving transportation dynamics. This study offers insights into LUTI modeling approaches specifically tailored for intermodal transportation. [ABSTRACT FROM AUTHOR]

This work examines the potential of some of the Gulf Cooperation Council countries (GCC) (Saudi Arabia (KSA), the United Arab Emirates (UAE), Qatar (QA), Bahrain (BH), Oman (OM)), Yemen (YE), Iraq (IQ), and Jordan (JO) to use their abundant solar radiation to generate electricity through PV technology. The study is structured to help decision-makers access the necessary data related to the status of solar-energy infrastructure and power production in the study region. The study investigates current efforts to establish PV technology and the challenges hindering the development of this technology. These efforts and challenges are then benchmarked against their status in Australia, which has climate and landscape conditions similar to those of the countries in the study region. It was found that Australia is successfully adopting solar energy in households and industrial locations despite its historical reliance on fossil fuels for energy production. This offers a potential avenue for replicating the Australian model of PV development in the study region. This work also addresses the effect of natural and anthropogenic aerosols on the performance of the PV panels. Meanwhile, it also proposes a conceptual model to help local governments and decision-makers in adopting solar-energy projects in the study region. Additionally, a preliminary carbon-footprint analysis of avoided emissions from PV energy utilization compared to national grid intensity was performed for each country. Findings show that the countries in the study region have great potential for using solar energy to gradually replace fossil fuels and protect the environment. It is observed that more hours of daylight and clear-to-scattered cloud coverage help increase solar irradiance near the ground all year around. Dust and aerosol loadings, however, were found to greatly reduce solar irradiance over the GCC area, especially during large dust events. Despite the high potential for harvesting solar energy in the study region, only a handful of PV plants and infrastructural facilities have been established, mostly in the KSA, the UAE, and Jordan. It was found that there is a critical need to put in place regulations, policies, and near-future vision to support solar energy generation and reduce reliance on fossil fuels for electricity production. [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide insight into research and activities of in situ remediation to remove petroleum hydrocarbon pollutants from a contaminated aquifer's sediment, located near two radial collector wells of a water supply system. It was decided that the most appropriate method for remediation of this aquifer's sediment is in situ bioremediation because it is clean, efficient and sustainable technology. Before the start of the bioremediation process, it was necessary to isolate and cultivate the microorganisms present at the contamination site, so they could be later applied in the bioremediation process. The samples before and after the bioremediation were studied using both GC and GC × GC–MS to determine how the concentrations of contaminants changed over time. Additionally, in this paper, a spatiotemporal representation of the change in hydrocarbon content by depth within the zone of the highest contamination over time is shown. After 12 months of bioremediation, the hydrocarbon content in the samples decreased by 82.0%, and based on GCxGC-MS analysis, the order of degradation of various hydrocarbon groups was as follows: steranes (99.6%), isoprenoids (98.4%), benzene derivatives (98.4%), alkanes (97.2%), and terpenes (49.3%). The exponential decay model showed the greatest decomposition rate of hydrocarbons occurred at depths of 8–10 m, with an average decay constant of 0.227, independent of the initial concentration of hydrocarbons. To the best of our knowledge, to date, the described approach has not been applied to an aquifer (the simultaneous treatment of groundwater and its associated sediment layers). [ABSTRACT FROM AUTHOR]

This paper examines how geography matters for the location of industries in East Asia, employing regression analyses on a novel and comprehensive regional GDP dataset. This study examines how geography affects industrial location patterns, particularly the role of infrastructure, such as ports and airports. This paper analyzes the current economic geography of East Asia using the novel dataset. The regression analyses utilize location quotients as the dependent variable and incorporate explanatory variables, such as domestic/foreign market access, per capita income, population density, and distance-based dummies for ports and airports. The findings reveal that the determinants of industrial location differ significantly across industries. The relative importance of domestic versus foreign market access and proximity to ports and airports varies across sectors. The results imply that countries/regions cannot easily host industries of their choice, as different industries require distinct locational characteristics. [ABSTRACT FROM AUTHOR]

Using satellite imagery of retail firms' parking lots to measure time-varying local firm-specific performance, we document that analysts incorporate local information into their forecasts. Analysts rely more on local signals when less firm-wide information is available. This incorporation of noisy local firm information has firm-level implications. Examining across industries, we find causal evidence that geographic concentration of analysts increases consensus forecast errors and decreases firm liquidity. These effects are stronger for harder-to-value stocks. The market values geographic firm information, as the abnormal return around forecast revisions is higher for analysts who cover a firm from a unique location. [ABSTRACT FROM AUTHOR]

Research on clusters has highlighted that some geographical areas display superior conditions to nurture concentrations of businesses locally. But why do certain industries—despite ascribing their origin to specific locations—emerge away from their birthplace? We qualitatively investigate the influence that the town of Arco, Italy, and its periodic event "RockMaster" exerted on the emergence of the global sport climbing industry. We advance the concept of "catalyzing places" that support industry emergence and growth through an ongoing, cyclical process of three forces: "centripetal" (i.e., attracting), "catalyzing" (i.e., reacting), and "centrifugal" (i.e., ejecting). The forces attract communities of practice to the place, expose them to intense, transformational experiences toward entrepreneurship, and induce them to establish their businesses elsewhere. By redeploying the resources and reputation acquired in the place, these scattered communities enact a collective phenomenon of user entrepreneurship and ultimately industry emergence. We claim that the ongoing activities of the place, and the periodic ones of the event, are mutually reinforcing. We advance two novel elements—"portable economies" and "springboard firms"—that, in catalyzing places, exert the antithetical effect of "agglomeration economies" and "anchor firms" in clusters. We discuss our contribution to research on industry emergence, new practices, and user entrepreneurship. [ABSTRACT FROM AUTHOR]

In recent decades, the prime objective of the energy sector has been to replace conventional energy sources with renewable energy sources such as hydrogen power, solar energy, etc. The objective of the present communication is to computationally locate the best site for the establishment of the hydrogen power plant given the various uncertainty parameters in terms of inexact and incomplete information. The uncertainty components of the information are well dealt with by the incorporation of T -spherical fuzzy hypersoft information. In accordance, we present the new concept of T -spherical fuzzy hypersoft matrix (TSFHSM) with different matrix-theoretic structured possibilities having useful computational setups. Some standard matrix operations with their algebraic properties have also been studied. Next, the structure of the proposed matrix has been utilized in presenting two new methodologies for the decision-making selection problems — one with the help of choice/weighted choice T -spherical fuzzy hypersoft matrices and the other with the value & score T -spherical fuzzy hypersoft matrices. Further, an illustrative example where the set of sites for the selection of hydrogen power plants has been computationally studied with the help of the presented novel algorithms given the available criteria. The efficacy of the proposed algorithms and their implementations have been discussed along with a comparative analysis, advantages and a characteristic comparison table. [Display omitted] • Proposed the notion of T -spherical fuzzy hypersoft matrix with algebraic properties. • Construction of choice (weighted) T -spherical fuzzy hypersoft matrices. • Proposing new algorithms for the site selection problem for hydrogen power plants. • Comparative analysis with characteristic advantages for the proposed method. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic disrupted supply chains and caused wide market disorders. Its disastrous impact on the world economy exposed the vulnerability of globalized production systems and led to discussions on the responses to such a crisis. These responses, including a new global spatial organization of supply chains, challenged our conceptual understanding, assumptions, and application of location theory in the spatial organization of economic activities. Through reviewing the literature, we outlined the pandemic's profound economic disruption and identified firms' applicable responsive strategies through Industry 4.0 solutions and management adaptions. Then based on the responses of technological upgrading we speculated possible changes in regional industrial location, such as suburbanization of small manufacturers and service providers, growth of industrial agglomerations in the logistic hubs and corridors and increase of high-tech manufacturers and innovation networks in urban centers. Finally, we pointed out the challenges to industrial location studies and suggested updating methodology and topics - using network analysis, behavioral theory, and agglomeration theory - for location studies. [ABSTRACT FROM AUTHOR]

In modern China, industrialization has formed a critical foundation for the transition to modernization. However, the spatiotemporal evolution patterns and driving mechanisms of urban industrial development in Nanjing from 1840 to 1949 remain unclear. Based on textual historical sources, this study examined the spatiotemporal patterns of urban industrial development in Nanjing from 1840 to 1949 by using spatial analysis methods, GeoDetector, regression models and industrial structure indices. The results reveal the following: (1) The overall spatial distribution pattern of the industry in modern Nanjing exhibited a "one main, one secondary" dual-center "ladle-shaped" arrangement. Over time, industry has expanded from the urban center toward the east and north. (2) The modernization level of different industries was uneven, exhibiting a "center-periphery" spatial pattern. (3) At the micro level, transportation and population density were the primary influencing factors for industrial location, whereas at the macro level, government intervention mainly affected the industrialization pattern. (4) The industrial development pattern in modern Nanjing, in alignment with the "pole-axis" spatial system, serves as a microcosm of China's urban modernization transition. This study represents the application of GIS methods in the humanities and provides valuable insights for urban planning and development. [ABSTRACT FROM AUTHOR]

Research Summary: With increased political polarization, Americans are displaying more animus across, and affinity within, ideological identity groups. We argue this dynamic incentivizes firms to minimize ideological misalignments across their workforce by locating new establishments in areas that are ideologically proximate to their current operations. We further argue that the desire to minimize ideological distance to new establishments is stronger in knowledge‐intensive industries and young organizations. We find support for these arguments through the analysis of over 220,000 new establishment openings from 2009 to 2014. Critically, we find the effect of ideological distance on location is stronger when societal polarization is high. Our theory, and findings, contribute to several literatures and advance our understanding of the impact of polarization on strategy. Managerial Summary: Being a liberal or a conservative is central to many Americans' identity. As political polarization rises, individuals increasingly trust and favor others who share their ideological identity, while distrusting and avoiding those that do not. This study investigates how these societal trends affect where firms choose to locate new facilities. Because social ties and trust across workers support collaboration, resource‐sharing and organizational performance, we argue that managers will seek ideological alignment within their firms by locating new establishments in areas that are ideologically proximate to existing operations. Analysis of over 220,000 new establishment openings from 2009 to 2014 supports this contention, and shows that the tendency to avoid ideologically distant locations is stronger when societal polarization is higher. [ABSTRACT FROM AUTHOR]

The current study focuses on selecting the most suitable site location for a manufacturing industry using the Factor Rating Method (FRM). The study considers six key factors: Raw Materials Availability, Location, Availability of Labor, Transport, Availability of Utilities, and Environmental Impact. The FRM assign weights to each factor based on their relative importance. The results indicate that Raw Materials Availability holds the highest weight, suggesting its critical influence on site selection decisions. Subsequently, the Analytic Hierarchy Process (AHP) and Best Worst Method (BWM) are utilized to prioritize three available location alternatives through pairwise criteria comparisons. The analysis reveals that Location C emerges as the most favorable option, effectively meeting the manufacturing industry's requirements. The successful application of these methods demonstrates their value in aiding decision-making processes related to site location selection. By considering multiple factors and utilizing structured methodologies, organizations can make informed choices aligned with their specific needs and goals. This research contributes to the existing body of knowledge by providing insights into effective site selection strategies for the manufacturing industry. Further research opportunities exist in incorporating additional factors, addressing real-world constraints, and conducting sensitivity analyses to enhance the accuracy and applicability of site location decision-making. [ABSTRACT FROM AUTHOR]

Globalisation has led to the dominance and geographical expansion of urban areas. Companies consider a complex set of criteria when deciding on their locations, including the agglomeration area and the presence of similar companies or related businesses. This study examines the spatial distribution and industrial clustering of companies within the agglomeration of Győr, Hungary's sixth-largest city. The sample comprises 256 companies across 68 settlements, with data processed through map, quadrat and industry analysis. The analyses identified six settlements within the agglomeration where nearly half of the companies are located, five factors that seem to facilitate company location, and five main industrial sectors, four of which are closely related. The article concludes that the agglomeration area of Győr is characterised by a high degree of spatial concentration of companies, industrial clustering and the emergence of industry sub-centres. [ABSTRACT FROM AUTHOR]

Accurately measuring industrial spatial agglomeration patterns is crucial for promoting regional economic development. However, few studies have considered both agglomeration degrees and cluster locations of industries. Moreover, the traditional multi-scale cluster location mining (MCLM) method still has limitations in terms of accuracy, parameter setting, calculation efficiency, etc. This study proposes a new framework for analyzing industrial spatial agglomeration patterns, which uses the Duranton and Overman (DO) index for estimating agglomeration degrees and a newly developed local DO (LDO) index for mining cluster locations. The MCLM-LDO method was proposed by incorporating the LDO index into the MCLM method, and it was validated via comparisons with three baseline methods based on two synthetic datasets. The results proved that the MCLM-LDO method can achieve accuracies of 0.945 and 1 with computational times of 0.15 s and 0.11 s on two datasets, which are superior to existing MCLM methods. The proposed framework was further applied to analyze the spatial agglomeration patterns of the industry of computer, communication, and other electronic equipment manufacturing in Guangdong Province, China. The results showed that the framework gives a more holistic perspective of spatial agglomeration patterns, which can serve as more meaningful references for industrial sustainable development. [ABSTRACT FROM AUTHOR]

As a byproduct of the rapid development of China's economy, the tradeoff between environmental protection and economic growth has become increasingly prominent. Environmental violations, especially repeated environmental violations (REVs), are becoming an increasing concern. Nevertheless, previous studies mainly empirically analyze single and static environmental violations, and there is still a lack of attention paid to clearly defining REVs as well as clarifying their influence on enterprises. In this study, we introduce the concept of REVs and provide a mathematical measurement framework for quantifying them. Moreover, using a sample of Chinese listed companies, we further investigate the role of enterprises' ownership type, geographical location and industry type in the relationship between REVs and enterprises' financial losses. The results show that the average financial loss caused by REVs is significantly higher in state-owned enterprises (SOEs) than in nonstate-owned enterprises (NSOEs) and more intensive in high-pollution than in low-pollution enterprises. Moreover, enterprises operating in eastern China suffer greater losses than those in midwest China. The results also indicate that monetary penalties play a critical role in environmental regulations, while such regulations need to be further improved to address enterprise REVs. This study fills the gaps in the existing research on REVs and sheds light on the importance of environmental protection in developing countries. [ABSTRACT FROM AUTHOR]

In recent decades, it has become increasingly difficult for rural firms to attract workers with specialised skills, and employment rates have decreased. A majority of rural firms are family SMEs. Family SMEs are, therefore, important contributors to employment in rural areas. In spite of this, little attention has been given to rural family SMEs in terms of competence management, geographical location and comparative industry affiliation. Thus, the aim of this qualitative multiple case study of two labour-intensive industries in Sweden is to explore how industry affiliation and geographical location affect competence management in rural family SMEs using the resource-based view. The findings show that irrespective of industry affiliation, rural family SMEs face similar competence challenges as a consequence of their rural setting, and the examined industries employ similar yet different strategies to moderate the negative effects of these competence challenges. Due to the scarcity of internal competencies, rural family SMEs rely on coopetition, local networks, and mutual industry-specific recruitment to make ends meet. The finding that rural family SMEs gain a competitive advantage by cooperating with competitors contributes to the body of knowledge regarding the resource-based view, where competitive firm resources are mainly managed internally in the firm. [ABSTRACT FROM AUTHOR]

Regional migrants constitute a large share of the labour market in China and therefore have important implications for welfare, resource reallocation and economic development. However, few works exist in studying how regional migrants select industries in destination cities. This study examines the role of urban industry structures of migrants' origin and destination locations in determining the industry selection of regional migrant workers in China. We apply a variant of the Roy model to guide the empirical analysis and generate the following predictions: the industry selection of a cross‐province migrant is negatively affected by the industry strength of her home province and positively affected by that of her destination. Using data from a nationwide migrant survey in China, we verify the patterns of migrants' industry selection consistent with the predictions of the model. We also find that regional migration is more likely to occur between the origin and destination with more dissimilar industry structures. [ABSTRACT FROM AUTHOR]

This research was conducted at Udayana Park, Mataram City and aims to analyze the effect of business capital, length of business, working hours, and business location on microscale business income in Udayana Park, the data used in this study are primary data, obtained through observation, questionnaires, and documentation on objects that are relevant to this research. The results showed that the test results, business capital partially had a significant effect on business income (0.0011 <0.05). Duration of business has a significant effect on business income (0.0445 <0.05), then the variable working hours has a significant effect on income (0.0031 <0.05). While the business location has no significant effect on business income (0.9162> 0.05), then the results of the f test simultaneously show that the variables of business capital, length of business, working hours, and business location have a significant effect on micro-scale business income in Udayana Park, Mataram City. The results of the Adjusted R-squared calculation obtained a value of 0.352577 or 35.2%. This means that the contribution of business capital variables, length of business, working hours, and business location to microscale business income in Udayana Park, Mataram City is 35.2%, the remaining 64.8% is determined by other variables outside this study. [ABSTRACT FROM AUTHOR]

Recently, with the development in technology and increase in population, the waste generated becomes an important issue for countries. Some regulations of recently updated through Ministry of Environment and Urbanisation in Turkey; it is essential to use environmentally compatible physical, chemical, or biological technologies to ensure the recovery of municipal waste in accordance with the zero-waste management system. Currently, there is one pre-treatment facility at the Anatolian Side of Istanbul and a pre-treatment facility is needed to use waste recycling facilities more efficiently. In this research, a combined fuzzy multi-criteria decision-making (MCDM) methodology is developed for the mechanical biological treatment (MBT) location selection problem. The proposed method comprises of geographic information system (GIS), fuzzy best worst method (BWM), and hierarchical fuzzy MCDM approach. First, alternatives for the site selection problem were determined using expert opinions and web-based GIS. Second, the criteria determined for the literature and expert opinions were weighted using the fuzzy best worst method. Finally, most suitable alternative was determined using hierarchical fuzzy MCDM approach. This study creates a roadmap for the MBT facility needed in the Anatolian Side of Istanbul, and according to the literature survey, there is no other study conducted on this subject. The proposed method handles vagueness and uncertainty employing fuzzy set theory. Fuzzy BWM, which does not need to conduct pairwise comparison among all criteria, is employed to determine the criteria weights. Web-based GIS that presents spatial data on web environment offers ease of use and provides the opportunity to evaluate over ready data. [ABSTRACT FROM AUTHOR]

Industrial activities, through the human-induced release of Green House Gas (GHG) emissions, have been identified as the primary cause of global warming. Accurate and quantitative monitoring of these emissions is essential for a comprehensive understanding of their impact on the Earth's climate and for effectively enforcing emission regulations at a large scale. This work examines the feasibility of detecting and quantifying industrial smoke plumes using freely accessible geo-satellite imagery. The existing system has somany lagging factors such as limitations in accuracy, robustness, and efficiency and these factors hinder the effectiveness in supporting timely response to industrial fires. In this work, the utilization of grayscale images is done instead of traditional color images for smoke plume detection. The dataset was trained through a ResNet-50 model for classification and a U-Net model for segmentation. The dataset consists of images gathered by European Space Agency's Sentinel-2 satellite constellation from a selection of industrial sites. The acquired images predominantly capture scenes of industrial locations, some of which exhibit active smoke plume emissions. The performance of the abovementioned techniques and models is represented by their accuracy and IOU (Intersection-over-Union) metric. The images are first trained on the basic RGB images where their respective classification using the ResNet-50 model results in an accuracy of 94.4% and segmentation using the U-Net Model with an IOU metric of 0.5 and accuracy of 94% which leads to the detection of exact patches where the smoke plume has occurred. This work has trained the classification model on grayscale images achieving a good increase in accuracy of 96.4%. [ABSTRACT FROM AUTHOR]

The immigration of STEM specialists has a decisive impact on Germany's ability to innovate. Analyses by the German Economic Institute with a focus on India show high employment growth in recent years. Indian STEM specialists earn comparatively high median wages. The revised Skilled Labour Immigration Act offers the opportunity to further strengthen and accelerate this immigration process. [ABSTRACT FROM AUTHOR]

In this paper, the relocation decisions of manufacturing plants across the NUTS-3 regions of the German economy are investigated. A relocation decision concerns whether a plant (an incumbent) moves its location from one region to another over a given time period or whether it remains in the same region. This decision is distinct from a location decision (of a start-up). To analyze the relocations of plants, the rich information of the official German regional statistics as well as the official German firm statistics that are maintained by the German Federal Statistical Office and the Statistical Offices of the Federal States is exploited for the first time. Both pull and push factors that influence relocation decisions are investigated. The results reveal that, in particular, regional road infrastructure and accessibility of regions as well as the quality of the available labor force positively affect the decision to relocate a plant in the German economy. A reduction of 10% in travel time by road to reach the three nearest agglomeration centers leads to an increase in relocation probability of about 9.5% on average. Policy implications involve the need for improvement of accessibility and infrastructure as well as incentives to support human capital in order to attract businesses to move to a region. [ABSTRACT FROM AUTHOR]

The purpose of the study is to evaluate the system of dependencies and contradictions between the Forbidden City as an object of cultural heritage and the transformation of the historic environment. The research methodology is based on a comparative study of literary sources and quantitative and qualitative data analysis using the example of the study of the Forbidden City. Based on the analysis of existing concepts, a model for managing the changing historical environment within the framework of the sustainable development of the Forbidden City has been developed. According to the study, the Forbidden City today is between two complex processes related to preserving and transforming the historic environment. In recent years there has been an increase in the number of museums and collections of cultural relics in the urban historical environment of Beijing, which directly contributes to the growth of tourist activity. This model should be based on the interaction of innovative digitalisation tools, intelligent solutions in urban planning, a rational approach and cultural tourism. In practice, this will allow for the maintenance of a more reasonable population density and the rational location of industrial and economic facilities and preserve the traditional aesthetic. [ABSTRACT FROM AUTHOR]

The sophisticated olfactory system of insects plays crucial roles in host plant location. In comparison with comprehensive studies on the molecular mechanisms of olfactory cues detection in lepidopteran moths, little is known about how coleopteran beetles detect host plant cues. Phyllotreta striolata is a devastating coleopteran pest of Brassicaceae crops, and its larvae feed on roots underground, while its adults destroy leaves aboveground. In this study, we focus on the molecular basis of olfactory cues detection in P. striolata and attempt to determine whether P. striolata larvae share the same specific olfactory cues for host plant location with conspecific adults and whether the detection mechanism is conserved. A two-choice behavioral bioassay was conducted to examine the behavioral responses of P. striolata to different types of isothiocyanates (ITCs), which are the characteristic volatiles of Brassicaceae crops. The results showed that both P. striolata adults and larvae were attracted by allyl ITC, although adults showed a broader behavioral response range. The transcriptome sequencing of P. striolata adults and larvae was performed, and 157 chemosensory genes were identified, among which 6 OBPs, 2 CSPs, 1 OR, 1 IR and 1 GR were found to be preferentially expressed in both P. striolata adults and larvae. Functional studies of PstrOBP9, PstrOBP13 and PstrOBP17, three of the six OBPs that were highly expressed in both adults and larvae, revealed that PstrOBP9 strongly bound allyl ITC and eight other ITCs. Taken together, these findings demonstrated that P. striolata larvae and adults could employ the same olfactory proteins to detect specific plant volatiles for host location, which provides a new perspective on the development of environmentally friendly pest management targeting both P. striolata adults and larvae. [ABSTRACT FROM AUTHOR]

The implementation of ultra-wideband technology for accurate indoor location in industrial and public environments has recently been the basis of numerous research studies. Wireless sensor networks must take localization into consideration. Localization processes improve in various ways when mobility is established. As research progresses on range-free localization with UWB, enhancements in methods and optimal techniques need to be evaluated for the present scenario. Within a single localization zone, they focus is on accuracy. The objective of work is to improve the location accuracy by decreasing localization error with hybrid optimal techniques and algorithms. However, many large-scale applications will benefit from technologies developed for line-of-sight conditions. TDOA (Time Difference of Arrival) is a method for calculating the distance between two or more radio transmitters and one receiver. Distance vector routing protocols measure distance by the number of routers a packet has to pass through; one router counts as one hop. These protocols send the entire routing table to each neighbor every 30 s. DV-Hop method has been adopted for the present work, and hybridization has been considered as a means of enhancing the results. Accuracy with initial measurement techniques lies in 2D and 3D with Kalman filter linked with DV-Hop to reduce initial errors. Localization error in nodes' dynamic momentum was observed, and the deployment of beacons in the range-free selected area was estimated with an improved technique. Ensemble method (EM)-PSO-based optimization with hybrid HOP algorithms is proposed in the present work. The results of the present approach show a significant difference in localization error reduction compared to conventional DV-HOP. Finally, an error below 2% is observed using multiple iterations, and a variation of 15% is observed compared with other state-of-the-art existing techniques. Using hybrid algorithms, this increased accuracy can then be used to reduce the localization error in network for the application users in range-free conditions. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) energy has become a low-cost, renewable, and environmentally friendly alternative to meet increasing energy demand. Nevertheless, there is still a lack of projects in this field in Brazil. Therefore, this study compares the results of two studies on the optimal site selection of PV in the Brazilian state of Rio de Janeiro. These studies used different methodologies to reach the conclusions and the resulting map. First, the final map of both studies was divided into a grid, and then the results of each cell were weighted for PV site selection. To compare the results using the maps, an intersection of the 10% of the grid cells with the best results from each study was formed. The results showed an 83% similarity between the different Multi-Criteria Decision-Making (MCDM) methods. The other part of the comparison focused on the following rank similarity coefficients: Spearman Correlation Coefficient, WS Coefficient, Spearman Weighted Correlation Coefficient, and Blest Correlation Coefficient. All these coefficients had values greater than 0.9, indicating a high degree of correlation between the results of the studies. Therefore, the two studies have a high degree of similarity and a high potential for installing photovoltaic solar power plants in Rio de Janeiro, especially in its intersection zones. [ABSTRACT FROM AUTHOR]

To decide the number, size, and location of its plants, a firm balances the benefit of delivering goods from multiple plants with the cost of setting up and managing these plants and the potential for cannibalization among them. Modeling the decisions of heterogeneous firms in an economy with a vast number of distinct locations involves a large combinatorial problem. Using insights from discrete geometry, we study a tractable limit case of this problem in which these forces operate at a local level. Our analysis delivers predictions on sorting across space. Compared with less productive firms, productive firms place more plants in dense, high-rent locations and fewer plants in markets with low density and low rents. We present evidence consistent with these and several other predictions, using US establishment-level data. [ABSTRACT FROM AUTHOR]

Plants of the genus Kalanchoe are the most frequently purchased potted plants because of their decorative qualities and easy cultivation. Modern commercial plants have unique shapes that are usually not genetically determined; hence, in vitro cultures are used to propagate such specimens. The efficiency of regeneration is significantly affected by the type of explant used when that explant was previously located on one of several parts of a complex plant organ. The study aimed to investigate the influence of the topophysical location of collected explants on the regeneration efficiency of adventitious shoots. Various regeneration pathways were observed in the in vitro micropropagation of Kalanchoe daigremontiana leaf fragments, i.e., direct and indirect organogenesis from the callus stage. The results show a dependent relationship between the location of the collected explant and its regenerative potential. The most remarkable regenerative capacity of K. daigremontiana was found in leaf blade fragments taken from the middle and proximal zones. In addition, the explants collected from the marginal zone of the leaf blade were notably more valuable than those from the part located near the midrib. The research results indicate that the growth and development of new seedlings propagated vegetatively with the in vitro method depends on their location on the mother plant. [ABSTRACT FROM AUTHOR]