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Dynamics of agglomeration and competition in the hotel industry: A geographically weighted regression analysis based on an analytical hierarchy process and geographic information systems (GIS) data

100%
Illescas-Manzano M. D., Martínez-Puertas S., Marín-Carrillo G. M., Marín-Carrillo M. B.
Oeconomia Copernicana
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2023
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vol. 14
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issue 1
213-252
EN
Research background: The effects of locating next to other establishments of equivalent activity is a decision with serious and far-reaching implications, not only from the point of view of location decisions but also with regard to competitive strategy, pricing, or promotion decisions. The literature provides evidence of the negative effects of being proximate to competitors (erosion of market share), but there are also benefits associated with the increased attraction of demand (attraction effect). This phenomenon is of particular interest in the case of hospitality, where hotel concentrations can be found around certain tourism resources, and is a crucial factor in hoteliers' decisions as they evaluate these contradictory effects. Purpose of the article: Drawing from the relevance that the confrontation between agglomeration and competition has in the hotel industry, our study aims to examine if this confrontation can be driven by geographical location and how both vertical and horizontal differentiation factors can unbalance it. Methods: Based on the use of geographical information systems and the estimation of a geographically weighted regression model with a wide dataset that includes 3,153 European hotels located in Spain, France and the United Kingdom. Findings & value added: We extend agglomeration and competition theoretical bodies related to location decisions by providing new findings about their simultaneous effect. Specifically, this study contributes to filling the gap regarding their combined effects on pricing and the conditions under which one prevails over the other. Results show that the role of geographical location and a hotel's online reputation are more decisive differentiation factors than hotel category when explaining the asymmetry of the effects of agglomeration and competition.
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Green innovations and their town applications

100%
Janiszek M.
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
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2018
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issue 502
85-94
EN
Actions that are environmentally friendly are increasingly being undertaken by private organizations, the public entities and the community. This process strives to meet the needs of society and to maintain balance between the natural environment and the economic activity. One of the solutions is sustainable building for energy efficient buildings, waste recycling and water saving and in addition, the use of renewable energy, regional materials and raw materials, recycled and environmentally friendly, as well as the promotion of bicycles and public transport. The process of making a dialogue between the local authority and residents is supported by spatial information acquisition and processing technologies and Internet communication tools The aim of the article is to analyze the resource-efficient and effective projects implemented in the city and to indicate the benefits for the economy. These benefits are to be achieved through green innovations that combine innovation with environmental sensitivity and ecological awareness.
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Virtualising Space – New Directions for Applications of Agent-Based Modelling in Spatial Economics

58%
Wozniak M.
Acta Universitatis Lodziensis. Folia Oeconomica
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2020
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vol. 1
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issue 346
7-26
PL
W związku z ogromnym postępem technologicznym przed naukami społeczno‑ekonomicznymi otworzyły się nowe płaszczyzny badań złożonych i nie do końca poznanych zjawisk. Jednym z podejść badawczych w tych obszarach jest tzw. modelowanie wieloagentowe (Agent‑Based Modeling) w połączeniu z danymi geograficznymi (GIS). Modelowanie wieloagentowe to metoda, w której budowane są złożone systemy składające się z autonomicznych jednostek (agentów). Między agentami zachodzą interakcje na poziomie mikro, których rezultatem jest ewolucja całego systemu na poziomie makro. Jednym z interesujących trendów modelowania wieloagentowego jest geosymulacja, czyli symulacja wieloagentowa osadzona w świecie wirtualnym, będącym odpowiednikiem realnej, fizycznej przestrzeni. Geosymulacja umożliwia zaawansowane i bardziej realistyczne badania na gruncie ekonomii przestrzennej, socjologii czy psychologii. Niniejszy artykuł pogłębia tę problematykę. Dokonano w nim identyfikacji i porównania dostępnych platform do symulacji wieloagentowej i wybrano trzy, które posiadają wsparcie dla danych geograficznych (GIS). Na tych platformach zaimplementowano dane GIS o zagospodarowaniu przestrzennym dla jednej z dzielnic Poznania. Dokonano również porównania funkcjonalności oprogramowania pod kątem trzech kryteriów: trudności programowania, funkcjonalności i współpracy z danymi GIS oraz dostępności materiałów szkoleniowych. Badania te stanowią wstępny etap opracowania złożonego, społeczno‑ekonomicznego systemu miejskiego, osadzonego w paradygmacie modelowania wieloagentowego.
EN
Due to enormous technological progress, socio‑economic science has gained new possibilities of investigating complex and not well‑known socio‑economic phenomena. One of the recent promising research approaches is agent‑based modelling (ABM) with connection to geographical (GIS) data. ABM is a bottom‑up research method concerning individuals that live and interact in the artificial environment. In this type of simulation, evolution of the whole system and macro‑level patterns results from individual behaviour of autonomous entities. Combining ABM with GIS data moves the simulation into the real geographical space. Applying this approach provides powerful possibilities of more realistic socio‑economic simulations concerning urban and spatial economics, sociology and psychology. Geosimulation also helps to answer questions about dependencies between geographical space and economic performances of modern cities. In this paper, a closer look at this topic is presented. We deal with the problem of implementation of GIS data into agent‑based modelling software. In the first step of our research procedure, we compare ABM programming platforms, then we chose three of them which provide GIS data support. In the second step, we implement OpenStreetMap GIS data for one of the districts of Poznań into these programming platforms. Finally, we compare the performance of ABM platforms regarding three major criteria: difficulty of programming, GIS data compatibility and available technical support. Our research is the first step in developing a comple Xsocio‑economic urban system under the ABM paradigm.
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