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  • 1.
    Bohlin, Magnus
    et al.
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Förutsättningarna för en utbyggd gränshandel i Sälen2012In: På gränsen – interaktion, attraktivitet och globalisering i Inre Skandinavien / [ed] Eva Olsson, Atle Hauge och Birgitta Ericsson, Karlstad: Karlstad University Press , 2012Chapter in book (Other academic)
  • 2.
    Bohlin, Magnus
    et al.
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Underlag för gränshandel och köpcentrum i Sälen2011Report (Other academic)
  • 3.
    Borgegård, Lars-Erik
    et al.
    Institutet för bostadsforskning (IBF).
    Fransson, Urban
    Institutet för byggforskning (IBF).
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Tollefsen, Aina
    Kulturgeografiska institutionen.
    Att flytta till glesbygden1993Report (Other academic)
  • 4.
    Borgegård, Lars-Erik
    et al.
    Institutet för bostadsforskning (IBF).
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Population and Housing Dynamics in a Metropolitan Region: The case of Stockholm1998Report (Other academic)
  • 5.
    Borgegård, Lars-Erik
    et al.
    Institutet för bostadsforskning (IBF).
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Population Concentration and Dispersion in Sweden since the 1970s1997In: Population planning and policies / [ed] Borgegård, L-E., Findlay, A.M., Sondell, E., Umeå: Umeå Universitet , 1997Chapter in book (Refereed)
  • 6.
    Borgegård, Lars-Erik
    et al.
    Institutet för bostadsforskning (IBF).
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Spridning och koncentration av befolkningen i Sveriges kommuner 1973-19921995In: Då, Nu och sedan: Geografiska uppsatser till minnet av Ingvar Jonsson / [ed] Ian Layton, Umeå: Umeå Universitet , 1995, p. 127-141Chapter in book (Other academic)
  • 7.
    Borgegård, Lars-Erik
    et al.
    Institutet för bostadsforskning (IBF).
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Müller, Dieter
    Kulturgeografiska institutionen.
    Concentration and Dispersion of Immigrants in Sweden, 1973-19921998In: The Canadian Geographer / Le Géographe canadien, ISSN 0008-3658, E-ISSN 1541-0064, Vol. 44, no 1, p. 28-39Article in journal (Refereed)
  • 8.
    Borgegård, Lars-Erik
    et al.
    Institutet för bostadsforskning (IBF).
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Müller, Dieter
    Umeå universitet, Kulturgeografiska institutionen.
    Hur förändras bosättningsmönstret när invandrarna blir fler?1995In: Invandrare & Minoriteter, no 5, p. 29-33Article in journal (Other academic)
  • 9.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Does Euclidean distance work well when the p-median model is applied in rural areas?2012In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 201, no 1, p. 83-97Article in journal (Refereed)
    Abstract [en]

    The p-median model is used to locate P centers to serve a geographically distributed population. A cornerstone of such a model is the measure of distance between a service center and demand points, i.e. the location of the population (customers, pupils, patients, and so on). Evidence supports the current practice of using Euclidean distance. However, we find that the location of multiple hospitals in a rural region of Sweden with anon-symmetrically distributed population is quite sensitive to distance measure, and somewhat sensitive to spatial aggregation of demand points.

  • 10.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Methodological issues in applying Location Models to Rural areas2010Report (Other academic)
    Abstract [en]

    Location Models are usedfor planning the location of multiple service centers in order to serve a geographicallydistributed population. A cornerstone of such models is the measure of distancebetween the service center and a set of demand points, viz, the location of thepopulation (customers, pupils, patients and so on). Theoretical as well asempirical evidence support the current practice of using the Euclidian distancein metropolitan areas. In this paper, we argue and provide empirical evidencethat such a measure is misleading once the Location Models are applied to ruralareas with heterogeneous transport networks. This paper stems from the problemof finding an optimal allocation of a pre-specified number of hospitals in alarge Swedish region with a low population density. We conclude that the Euclidianand the network distances based on a homogenous network (equal travel costs inthe whole network) give approximately the same optimums. However networkdistances calculated from a heterogeneous network (different travel costs indifferent parts of the network) give widely different optimums when the numberof hospitals increases.  In terms ofaccessibility we find that the recent closure of hospitals and the in-optimallocation of the remaining ones has increased the average travel distance by 75%for the population. Finally, aggregation the population misplaces the hospitalsby on average 10 km.

  • 11.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Var ska sjukhusen ligga?2013In: Ekonomiska samfundets tidskrift, ISSN 0013-3183, E-ISSN 2323-1378, no 3, p. 165-171Article in journal (Refereed)
    Abstract [sv]

    Denna artikel visar på en metod för att undersöka hur optimal befolkningens fysiska tillgänglighet till sjukvården är. Detta är relevant med tanke på den svenska storregionala omdaningen som säkerligen kommer provocera fram omprövningar av sjukhusens framtida placering.

    Med Dalarna som exempel fann vi att en ökning från dagens två till tre optimalt lokaliserade sjukhus skulle minska befolkningens genomsnittliga reseavstånd med 25 %.

    På basis av transportsektorns standardkalkyler för samhällsekonomisk effekter vid resande, samt av kostnader för drift av sjukvård sluter vi dessutom oss till att en komplettering av nuvarande två sjukhus i Dalarna med ett tredje vore samhällsekonomiskt effektivt.

  • 12.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics. HUI Research.
    Measuring CO2 emissions induced by online and brick-and-mortar retailing2014Report (Other academic)
    Abstract [en]

    We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

  • 13.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics. HUI Research.
    Measuring CO2 emissions induced by online and brick-and-mortar retailing2014Report (Other academic)
    Abstract [en]

    We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

  • 14.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics.
    Measuring transport related CO2 emissions induced by online and brick-and-mortar retailing2015In: Transportation Research Part D: Transport and Environment, ISSN 1361-9209, E-ISSN 1879-2340, Vol. 40, p. 28-42Article in journal (Refereed)
    Abstract [en]

    We develop a method for empirically measuring the difference in transport related carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their transport CO2 footprints by 84% when buying standard consumer electronics products. 

  • 15.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    An empirical test of the gravity p-median model2012Report (Other academic)
    Abstract [en]

    A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be implemented and tested empirically. We implemented the model in an empirical problem of locating locksmiths, vehicle inspections, and retail stores ofv ehicle spare-parts, and we compared the solutions with those of the p-median model. We found the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

  • 16.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Distance measure and the p-median problem in rural areas2012Report (Other academic)
    Abstract [en]

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

  • 17.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Distance measure and the p-median problem in rural areas2015In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 226, no 1, p. 89-99Article in journal (Refereed)
    Abstract [en]

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region with a sparse, heterogeneous network and a non-symmetric distribution of the population. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (1-100 facilities). We find that the network distance give as good a solution as the travel-time network. The Euclidean distance gives solutions some 4-10 per cent worse than the network distances, and the solutions tend to deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

  • 18.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Testing the gravity p-median model empirically2015In: Operations Research Perspectives, ISSN 2214-7160, Vol. 2, no 124, article id 132Article in journal (Refereed)
    Abstract [en]

    Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

  • 19.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    A compelling argument for the gravity p-median model2013In: European Journal of Operational Research, ISSN 0377-2217, E-ISSN 1872-6860, Vol. 226, no 3, p. 658-660Article in journal (Refereed)
    Abstract [en]

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population always travels to the nearest facility. Drezner and Drezner (2006, 2007) provide three arguments on why this assumption might be incorrect, and they introduce the extended gravity p-median model to relax the assumption. We favour the gravity p-median model, but we note that in an applied setting, the three arguments are incomplete. In this communication, we point at the existence of a fourth compelling argument for the gravity p-median model.

  • 20.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Short Communication: A compelling argument for the gravity p-median model2012Report (Other academic)
    Abstract [en]

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population always travels to the nearest facility. Drezner and Drezner (2006, 2007) provide three arguments on why this assumption might be incorrect, and they introduce the extended the gravity p-median model to relax the assumption. We favour the gravity p-median model, but we note that in an applied setting, Drezner and Drezner’s arguments are incomplete. In this communication, we point at the existence of a fourth compelling argument for the gravity p-median model.

  • 21.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Jia, Tao
    School of Remote Sensing and Information Engineering, Wuhan University.
    Out-of-town shopping and its induced CO2-emissions2013Report (Other academic)
    Abstract [en]

    Planning policies in several European countries have aimed at hindering the expansion of out-of-town shopping centers. One argument for this is concern for the increase in transport and a resulting increase in environmental externalities such as CO2-emissions. This concern is weakly founded in science as few studies have attempted to measure CO2-emissions of shopping trips as a function of the location of the shopping centers. In this paper we conduct a counter-factual analysis comparing downtown, edge-of-town and out-of-town shopping. In this comparison we use GPS to track 250 consumers over a time-span of two months in a Swedish region. The GPS-data enters the Oguchi’s formula to obtain shopping trip-specific CO2-emissions. We find that consumers’ out-of-town shopping would generate an excess of 60 per cent CO2-emissions whereas downtown and edge-of-town shopping centers are comparable.

  • 22.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Jia, Tao
    School of Remote Sensing and Information Engineering, Wuhan University.
    Out-of-town shopping and its induced CO2-emissions2013In: Journal of Retailing and Consumer Services, ISSN 0969-6989, E-ISSN 1873-1384, Vol. 20, no 4, p. 16p. 382-388Article in journal (Refereed)
    Abstract [en]

    Planning policies in several European countries have aimed at hindering the expansion of out-of-town shopping centers. One argument for this is concern for the increase in transport and a resulting increase in environmental externalities such as CO2-emissions. This concern is weakly founded in science as few studies have attempted to measure CO2-emissions of shopping trips as a function of the location of the shopping centers. In this paper we conduct a counter-factual analysis comparing downtown, edge-of-town and out-of-town shopping. In this comparison we use GPS to track 250 consumers over a time-span of two months in a Swedish region. The GPS-data enters the Oguchi’s formula to obtain shopping trip-specific CO2-emissions. We find that consumers’ out-of-town shopping would generate an excess of 60 per cent CO2-emissions whereas downtown and edge-of-town shopping centers are comparable.

  • 23.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics. HUI Research, Stockholm.
    The effect on CO2 emissions of taxing truck distance in retail transports2017In: Transportation Research Part A: Policy and Practice, ISSN 0965-8564, E-ISSN 1879-2375, Vol. 97, p. 47-54Article in journal (Refereed)
    Abstract [en]

    To finance transportation infrastructure and to address social and environmental negative externalities of road transports, several countries have recently introduced or consider a distance based tax on trucks. In competitive retail and transportation markets, such tax can be expected to lower the demand and thereby reduce CO2 emissions of road transports. However, as we show in this paper, such tax might also slow down the transition towards e-tailing. Considering that previous research indicates that a consumer switching from brick-and-mortar shopping to e-tailing reduces her CO2 emissions substantially, the direction and magnitude of the environmental net effect of the tax is unclear. In this paper, we assess the net effect in a Swedish regional retail market where the tax not yet is in place. We predict the net effect on CO2 emissions to be positive, but off-set by about 50% because of a slower transition to e-tailing.

  • 24.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics.
    The effects of taxing truck distance on CO2 emissions from transports in retailing2015Report (Other academic)
    Abstract [en]

    To finance transportation infrastructure and to address social and environmental negative externalities of road transports, several countries have recently introduced or consider a distance based tax on trucks. In the competitive retail market such tax can be expected to lower the demand and thereby reduce CO2 emissions of road transports. However, as we show in this paper, such tax might also slow down the transition towards e-tailing. Considering that previous research indicates that a consumer switching from brick-and-mortar shopping to e-tailing reduces her CO2 emissions substantially, the direction and magnitude of the environmental net effect of the tax is unclear. In this paper, we assess the net effect in a Swedish regional retail market where the tax not yet is in place. We predict the net effect on CO2 emissions to be positive, but off-set by about 50% because of a slower transition to e-tailing.

  • 25.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics.
    Optimal retail location and CO2 emissions2012Report (Other academic)
    Abstract [en]

    In this paper, the p-median model is used to find the location of retail stores that minimizes CO2 emissions from consumer travel. The optimal location is then compared with the existing retail location,and the excess CO2 emissions compared with the optimal solution is calculated. The results show that by using the environmentally optimal location, CO2 emissions from consumer travel could be reduced by approximately 25percent. 

  • 26.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics.
    Optimal retail location and CO2-emissions2013In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 20, no 14, p. 1357-1361Article in journal (Refereed)
    Abstract [en]

    In this paper, the p-median model is used to find the location of retail stores that minimizes CO2-emissions from consumer travel. The optimal location is then compared with the existing retail location,and the excess CO2-emissions compared with the optimal solution is calculated. The results show that by using the environmentally optimal location, CO2-emissions from consumer travel could be reduced by approximately 25 per cent.

  • 27.
    Han, Mengjie
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Lundmark, M.
    Intra-urban location of stores and labour turnover in retail2019In: International Review of Retail Distribution & Consumer Research, ISSN 0959-3969, E-ISSN 1466-4402, Vol. 29, no 4, p. 359-375Article in journal (Refereed)
    Abstract [en]

    The aim of this paper is to analyse labour turnover in retail firms with stores in different city locations. This case study of a Swedish mid-sized city uses comprehensive longitudinal register data on individuals. In a first step, an unconditional descriptive analysis shows that labour turnover in retail is higher in out-of-town locations, compared to more central locations in the city. In a second step, a generalized linear model (GLM) analysis is conducted where labour turnover in downtown and out-of-town locations are compared. Firm internal and industry factors, as well as employee characteristics, and location-specific factors are controlled for. The results indicate that commuting costs and intra-urban location have no statistically significant effect on labour turnover in retail firms. Instead, firm internal factors, such as human resource management, has a major influence on labour turnover rates. The findings indicate that in particular firms with multiple locations may need to pay extra attention to work conditions across stores in different places in a city, in order to avoid diverging levels of labour mobility. This paper complements previous survey-based studies on labour turnover by using a comprehensive micro-level dataset to analyse revealed rather th