Transportsektorn dras med ett antal problem som är proportionerliga mot antalet bilresor. Kommuner som vill begränsa dessa kan utnyttja markanvändningspolitiken, där kommunen ofta har rådighet över parkeringstalen, d.v.s. kraven på antal bilparkeringsplatser som ska anläggas. Forskningen pekar på att sänkta parkeringstal är effektivt för att minska antalet bilresor, men ju mer effektiv sådan policy är, desto mindre acceptabel anses den ofta vara hos allmänheten. Syftet med denna uppsats är därför att undersöka vilka faktorer som är betydelsefulla för acceptansgraden och om kommuner kan påverka dessa för att öka acceptansen. Detta görs med en enkätstudie (n=245) bland boende i femtio olika flerbostadshus i Huddinge kommun, där samband mellan enkätsvaren och uppgifter om bostadshusets fysiska miljö samt dess parkeringsplanering undersöks med hjälp av multipel regression. Resultatet visar att individers upplevelse av andra medborgares grad av acceptans, individers uppfattning den befintliga trafikproblematiken samt individens preferenser för sitt eget resande är de viktigaste faktorerna som påverkar acceptansgraden. Studien visar vidare att sänkt parkeringstal vid bostaden är korrelerat med lägre acceptans för kommunens parkeringsriktlinjer, och att det därmed är angeläget att hitta sätt att skapa mer av den acceptans som annars riskerar att urholkas när låga parkeringstal tillämpas i allt fler flerbostadshus. De flesta faktorer som kommunen har kontroll över saknar samband med acceptansgraden, men resultatet pekar på att några möjligheter finns inom cykelparkeringsförbättringar och kort gångavstånd till kollektivtrafiken. Vidare skulle kommuner kunna använda sig av placering av parkeringsplatser längre från bostaden i stället för sänkt parkeringstal för att uppnå sina mål, eftersom forskning visar på liknande effekter, samtidigt som denna studie pekar på att avståndet från bostaden inte har något samband med acceptansen. / The transportation sector is affected by multiple issues that are proportional to the number of car trips. Municipalities who wish to mitigate these issues can alter their land use policy, in which it typically has the power to set minimum parking requirements (MPRs) for properties within its boundaries. Previous research shows that lowered MPRs are effective in reducing the number of car trips, but the more effective such policy is, the less acceptable it is typically deemed to be by the public. Therefore, the purpose of this thesis is to determine which factors affect policy acceptance and how the municipality can influence this. The study is conducted using a self-administered questionnaire (n=245) with participants from fifty different apartment buildings across the Huddinge municipality. Relationships among the questionnaire data, data about the physical environment at the respondent’s house and the land use policy applied during its construction are then examined using multiple regression. The results show that individuals’ perception of acceptance among other citizens, individuals’ perceptions of traffic problems and individuals’ own preferences related to travel behaviour are the most important factors affecting acceptance. Furthermore, the study shows that lower MPRs at the respondent’s residence is correlated with lower acceptance for the municipality’s present parking policy. Therefore, it is important to find ways to engender acceptance, since support for the policy might otherwise be undermined as low MPRs get implemented in a greater share of apartment buildings. Most factors that the municipality can control are not correlated with the degree of acceptance, but the results suggest some possibilities in residential bicycle parking improvements and shorter walking distances to public transport stops. Additionally, the municipality could shift the focus of its land use policy measures toward placement of parking spaces further away from entrances, since previous research show that this may have a similar effect on car trips, and this study shows that it is not correlated with the degree of acceptance.

Esta pesquisa objetivou uma melhor compreensão do processo de escolha do modo de viagem. Empregou-se a abordagem indutiva dirigida a dados livre de suposições a priori da mineração em banco de dados (Data Mining), utilizando redes neurais artificiais (RNA) como ferramenta mineradora, à procura de conhecimento, ou informação útil, a respeito de escolha e capaz de indicar qual das estruturas de decisão subjacentes aos modelos de escolha modal considerados mais se aproximaria ao do observado. Partindo-se da ideia de que nesse processo exista um padrão o qual pode ser captado por uma RNA, ajustou-se um modelo de RNA aos dados e extraiu-se então o conhecimento contido no modelo de RNA ajustado através de um algoritmo de extração de árvore de decisão de RNA chamado Trepan (Trees parroting network), que foi analisado e interpretado à luz dos objetivos desta pesquisa. Os dados que foram utilizados nesse processo de descoberta de conhecimento são provenientes de uma pesquisa de entrevista domiciliar realizada na cidade de Bauru - SP, para fins de estimativa da matriz de deslocamentos origem-destino dessa cidade. Obteve-se quatro árvores de decisão com estruturas simples e com a araucária preditiva de 75% aproximadamente para os três modos de viagem estudados. Embora o conhecimento extraído dos modelos neurais ajustados não tenham proporcionado a indicação de qual das estruturas de decisão subjacentes aos modelos de escolha modal mais se aproxima da obtida com o modelo neural, foi constatada nas árvores resultantes do processo de descoberta do conhecimento uma relação de compensação entre o atributo sexo e os atributos relacionados à capacidade econômica do domicílio na decisão de escolha do modo carro para a realização de uma viagem. Os resultados também sugerem a não necessidade de mais um atributo de entrada referente ao deslocamento realizado em uma viagem para modelagem por RNA do processo de escolha do modo de viagem no contexto estudado. / This research aimed at a better understanding of the mode travel choice process. The inductive data driven free from a priori assumptions of the data mining approach was employed, using artificial neural networks (ANN) as a mining tool, looking for knowledge or useful information, concerning the choice process and capable of indicating which of the underlying decision structures to the considered modal choice models would come closer to the observed one. Taking into consideration that there is a pattern in this process that can be captured by ANN, an ANN model was fitted (trained) to the data, and the knowledge contained in the trained ANN model was extracted by employing an ANN decision tree extraction algorithm called Trepan (Trees parroting network), which was analysed and interpreted in the light of the object of this research. The data which was employed in this knowledge discovery process come from a household survey carried out in Bauru - SP in order to estimate the O-D matrix in this city. Four decision trees with simple structures and predicting accuracy of approximately 75% for the three travel modes studied were obtained. Even though the knowledge extracted from the trained ANN model has not yielded the indication of which of the underlying decision structures to the modal choice models was closer to the neural model, a compensating relation between the sex attribute and the household economic-related attribute in the decision of choosing the car mode in order to travel was evidenced in the trees resulting from the process of knowledge discovery. The results also suggest the lack of necessity of more than one input travel attribute concerning the displacement performed in a trip for the ANN modelling of the mode travel choice process in the studied context.

Esta pesquisa objetivou uma melhor compreensão do processo de escolha do modo de viagem. Empregou-se a abordagem indutiva dirigida a dados livre de suposições a priori da mineração em banco de dados (Data Mining), utilizando redes neurais artificiais (RNA) como ferramenta mineradora, à procura de conhecimento, ou informação útil, a respeito de escolha e capaz de indicar qual das estruturas de decisão subjacentes aos modelos de escolha modal considerados mais se aproximaria ao do observado. Partindo-se da ideia de que nesse processo exista um padrão o qual pode ser captado por uma RNA, ajustou-se um modelo de RNA aos dados e extraiu-se então o conhecimento contido no modelo de RNA ajustado através de um algoritmo de extração de árvore de decisão de RNA chamado Trepan (Trees parroting network), que foi analisado e interpretado à luz dos objetivos desta pesquisa. Os dados que foram utilizados nesse processo de descoberta de conhecimento são provenientes de uma pesquisa de entrevista domiciliar realizada na cidade de Bauru - SP, para fins de estimativa da matriz de deslocamentos origem-destino dessa cidade. Obteve-se quatro árvores de decisão com estruturas simples e com a araucária preditiva de 75% aproximadamente para os três modos de viagem estudados. Embora o conhecimento extraído dos modelos neurais ajustados não tenham proporcionado a indicação de qual das estruturas de decisão subjacentes aos modelos de escolha modal mais se aproxima da obtida com o modelo neural, foi constatada nas árvores resultantes do processo de descoberta do conhecimento uma relação de compensação entre o atributo sexo e os atributos relacionados à capacidade econômica do domicílio na decisão de escolha do modo carro para a realização de uma viagem. Os resultados também sugerem a não necessidade de mais um atributo de entrada referente ao deslocamento realizado em uma viagem para modelagem por RNA do processo de escolha do modo de viagem no contexto estudado. / This research aimed at a better understanding of the mode travel choice process. The inductive data driven free from a priori assumptions of the data mining approach was employed, using artificial neural networks (ANN) as a mining tool, looking for knowledge or useful information, concerning the choice process and capable of indicating which of the underlying decision structures to the considered modal choice models would come closer to the observed one. Taking into consideration that there is a pattern in this process that can be captured by ANN, an ANN model was fitted (trained) to the data, and the knowledge contained in the trained ANN model was extracted by employing an ANN decision tree extraction algorithm called Trepan (Trees parroting network), which was analysed and interpreted in the light of the object of this research. The data which was employed in this knowledge discovery process come from a household survey carried out in Bauru - SP in order to estimate the O-D matrix in this city. Four decision trees with simple structures and predicting accuracy of approximately 75% for the three travel modes studied were obtained. Even though the knowledge extracted from the trained ANN model has not yielded the indication of which of the underlying decision structures to the modal choice models was closer to the neural model, a compensating relation between the sex attribute and the household economic-related attribute in the decision of choosing the car mode in order to travel was evidenced in the trees resulting from the process of knowledge discovery. The results also suggest the lack of necessity of more than one input travel attribute concerning the displacement performed in a trip for the ANN modelling of the mode travel choice process in the studied context.

In an era of increasing emphasis on sustainability across industries, the housing sector faces unique challenges in providing sustainable accommodations, particularly for international students. Efficient facility management in this context necessitates collaborative stakeholder efforts to achieve ecological, economic, and social sustainability goals amid cultural diversity that impacts occupant satisfaction. Akademiska Hus, a prominent Swedish company, leads sustainable housing initiatives for international students, leveraging digital innovations to enhance stakeholder satisfaction.This master's thesis aims to explore efficient and sustainable facility management approaches in student housing using a smartphone app. It culminates in the development of a prototype roadmap for delivering sustainable student accommodations. The roadmap is informed by a case study of Språkskrapan, a student accommodation facility owned by Akademiska Hus and managed by the University of Gothenburg.The study engages stakeholders, including housing providers and students, to identify needs and goals, assesses the performance of a smartphone app for facility management, and explores strategies for sustainable building management tailored to student requirements. The research follows the structured approach of the double- diamond design process: identifying student needs through interviews, defining challenges based on feedback, proposing solutions, and testing potential solutions.The findings will yield a comprehensive roadmap for offering sustainable student housing, providing insights into sustainable facility management aligned with digital innovation for student accommodation. This study serves as a blueprint for future community development projects, offering guidance on achieving sustainability objectives in resource-constrained environments. / I en tid då hållbarhet betonas allt mer i alla branscher står bostadssektorn inför unika utmaningar när det gäller att tillhandahålla hållbara boenden, särskilt för internationella studenter. Effektiv fastighetsförvaltning i detta sammanhang kräver samarbete mellan intressenter för att uppnå ekologiska, ekonomiska och sociala hållbarhetsmål mitt i kulturell mångfald som påverkar hyresgästernas tillfredsställelse. Akademiska Hus, ett framstående svenskt företag, leder hållbara bostadsinitiativ för internationella studenter och utnyttjar digitala innovationer för att öka intressenternas tillfredsställelse.Denna masteruppsats syftar till att utforska effektiva och hållbara metoder för fastighetsförvaltning i studentbostäder med hjälp av en smartphone-app. Det kulminerar i utvecklingen av en prototyp för en färdplan för att leverera hållbara studentbostäder. Färdplanen baseras på en fallstudie av Språkskrapan, ett studentboende som ägs av Akademiska Hus och förvaltas av Göteborgs universitet.Studien engagerar intressenter, inklusive bostadsleverantörer och studenter, för att identifiera behov och mål, utvärderar prestandan hos en smartphone-app för fastighetsförvaltning och utforskar strategier för hållbar fastighetsförvaltning som är skräddarsydd för studenternas krav. Forskningen följer det strukturerade tillvägagångssättet i designprocessen med dubbla diamanter: identifiera studenternas behov genom intervjuer, definiera utmaningar baserat på återkoppling, föreslå lösningar och testa potentiella lösningar.Resultaten kommer att leda till en omfattande färdplan för att erbjuda hållbara studentbostäder och ge insikter i hållbar fastighetsförvaltning i linje med digital innovation för studentbostäder. Denna studie fungerar som en plan för framtida samhällsutvecklingsprojekt och ger vägledning för att uppnå hållbarhetsmål i resursbegränsade miljöer.

Toute procrastination à lutter contre le changement climatique aura pour conséquence une augmentation croissante des coûts à l'avenir (voir par exemple Stern, 2006). Le manque de changement dans le comportement des individus, indépendamment de l'investissement dans les technologies de réduction des émissions, pourrait entraîner des coûts exorbitants. Ces derniers sont déjà aujourd'hui très élevés en raison du faible nombre d’options disponibles pour réduire les émissions (Abrell, 2007; Bottrill, 2006; Proost, 2008; SDC, 2005). Par conséquent, des efforts sont nécessaires pour introduire des mesures politiques efficaces le plus rapidement possible. Bien que cette question concerne de nombreux secteurs de l’économie, cette thèse se concentre sur le secteur des transports car il s’agit de l'un des plus grands émetteurs de CO2 (CE, 2012). C’est également un secteur, qui se caractérise par des coûts de dépollution élevés. Cela signifie que tout progrès vers une technologie moins carbonée sera coûteuse et prendra du temps (Kesicki, 2012).Ostrom et al. (2012) signalent qu’une solution peut être trouvée en établissant et en appliquant des limites sur les ressources communes. De nombreuses études ont été entreprises à ce sujet (voir par exemple Dudley, 1993; Hackett et al., 1994; Kramer et al, 1986;. Randall, 1975, 1978;. Walker et al, 1991, 1992). Cependant, ce dernier n'a pas encore été épuisé. Au contraire, de nouveaux instruments de politique soulèvent de nouvelles discussions et suscitent le besoin pour de nouvelles recherches. Les « Personal Carbon Allowances » (PCA), aussi dénommés en français par le terme « permis d’émission », sont un de ces instruments. Le PCA est un instrument de politique publique de plafonnement et d’échange (« cap-and-trade ») dans lequel les droits d’émissions de carbone sont attribués à des individus. D'un point de vue néoclassique, les permis d'émission constituent un instrument de politique efficace et efficient dans la lutte contre la pollution (Weitzman, 1974; Montgomery, 1972). Ils entraînent une augmentation des prix qui couvre le montant exact des émissions produites par un individu. Toutefois, des éléments socio-psychologiques compliquent le problème. Cette thèse tente d’apporter un éclaircissement sur la manière dont l'économie comportementale pourrait être utilisée pour lutter contre la pollution de l'environnement du transport personnel. Elle fait des propositions concernant la mise en place des PCA et comment ces derniers pourraient influencer les choix personnels de déplacement. Plusieurs conclusions et recommandations en matière d’économie comportementale sont formulées dans quatre articles. Aux fins de cette thèse, trois des quatre articles sont basés sur des expériences. Dans les expériences de laboratoire, les sujets ont géré leurs quotas sous la dénomination française de « permis d'émissions » (et non de PCA) dans la mesure où l'étude a été menée en France. Une des conclusions mise en évidence par les expériences est que l'étiquetage a une influence positive sur les participants. L'effet de l'étiquetage pourrait être introduit dans le système PCA de différentes manières. Par exemple, les quotas de carbone personnels accordés à l’ensemble des activités pourraient être étendus sous forme de quotas pour les transports en commun. Les transports en commun pourraient être étiquetés dans le budget. Il s’agirait d’une alternative moins polluante que les transports privés., Les expériences montrent que les sujets, qui disposent d’un certain nombre de PCA à dépenser exclusivement pour les transports publics sont incités à privilégier ce mode de transport. Une autre leçon qui peut être tirée de cette thèse est l’importance du retour d’informations et d’expérience. Les individus peuvent non seulement s’appuyer sur leurs expériences personnelles passées pour faire des choix (y compris des choix de transport) mais aussi vouloir étendre leurs connaissances grâce au retour d'expérience ... / The excessive anthropogenic activities related to burning of fossil fuels emit around 80 percent of greenhouse gases (GHG) in the atmosphere per year, according to the Intergovernmental Panel on Climate Change (IPCC, 2014). Among the GHG emissions, the anthropogenic CO2 emissions belong to the most dangerous ones. About 40 percent of these CO2 emissions have remained in the atmosphere (880 ± 35 GtCO2) since 1750, contributing to the global warming effect (IPCC, 2014). Since the 1950s, humanity is clearly responsible for more than half of the observed increases in temperatures (IPCC, 2014). The world energy consumption in 2011 tripled when comparing to 1965 and it has increased more rapidly than the world population (BP and UN, 2012). The above problem concerns a number of sectors, but only one of them has become the main subject of this dissertation. More precisely, this dissertation focuses on the transportation sector, which belongs to one of the greatest contributors of CO2 emissions to the atmosphere ((EC, 2012). Researchers warn that if the personal transportation demand continues to augment, which is likely due to the steady increase in population and greater accessibility to transport modes, the levels of congestion could become intolerable and even more costly to mitigate (Stern, 2006; EEA, 2010; Ostrom et al., 2012). Lack of changes in individual’s behavior, irrespectively of investment in abatement technologies, could lead to excessive costs, which already today are estimated to be high due to a very few low-carbon alternatives available (Abrell, 2007; Bottrill, 2006; Proost, 2008; SDC, 2005). The essays presented in this dissertation shed some light on how insights from the behavioral economics could be used to tackle the environmental pollution from personal transportation. At the core, lies the implementation of a market-based policy instrument (i.e., personal carbon allowances) in hypothetical commuting choices. The personal carbon allowances, abbreviated as PCA, constitute “a right to pollute” the atmosphere during personal activities, such as commuting and traveling (Roberts and Thumim, 2006; Howell, 2008; 2012; Parag et al., 2011). This dissertation provides suggestions on how a PCA design could influence personal choices of commuting. On the basis of four essays, a number of conclusions were drawn, and policy recommendations were formulated. For the purposes of this dissertation, PCA was defined to be any ‘cap-and-trade’ public policy instrument in which carbon emission rights are allocated to individuals. Three out of four essays encompassed laboratory experiments. The experimental subjects managed their allowances under a term emission permits (les permis d'émission, in French) because the study was conducted in France. One of the conclusions that should be highlighted is that the labeling effect had a positive influence on the experimental subjects and that it would be beneficial to consider it in the PCA scheme. For example, the personal carbon allowances that are granted for all activities could be extended by allowances that would be valid for public transportation only. The public transportation should be labeled in the budget because it is a less polluting alternative to private transportation. Having a certain number of allowances for public transportation at their disposal, subjects may be more willing to use this transport mode in replacement of commuting by private transportation. Another lesson that can be drawn from this dissertation is that the provision of feedback matters. Moreover, individuals may not only rely on their personal past experiences but also may want to extend their knowledge by the feedback on activities of their peers or neighbours....