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• 181. [Article] Environmentally Sustainable and Affordable Housing Near Transit in Los Angeles

  Providing affordable housing and reducing greenhouse gases are common goals in cities worldwide. Transit-oriented development (TOD) can provide an opportunity to make incremental progress on both fronts, ...

  Citation × Citation Citation Abstract Copy Title: Environmentally Sustainable and Affordable Housing Near Transit in Los Angeles Author: Boarnet, Marlon Year: 2017 Providing affordable housing and reducing greenhouse gases are common goals in cities worldwide. Transit-oriented development (TOD) can provide an opportunity to make incremental progress on both fronts, by building affordable housing near transit and by providing alternative transport modes such that households reduce driving. While the existing literature has focused on the relationship between TOD and housing and TOD and greenhouse gas emission reduction as separate issues, it has seldom touched on the possibility that TOD could address both goals jointly. We provide evidence to show that focusing on either housing affordability or greenhouse gas emission reduction in isolation can lead to strategies that achieve one goal to the detriment of the other. Using the case of Los Angeles, we develop a scenario planning model that allows simultaneous consideration of housing and transportation goals, and illustrates the tradeoffs of different policy approaches. The results show that larger increases in residential densities combined with a small inclusionary housing requirement yields greater benefits, in terms of both reduced driving and more affordable housing, than would a higher inclusionary percentage with smaller increases in density. Title: Environmentally Sustainable and Affordable Housing Near Transit in Los Angeles Author: Boarnet, Marlon Year: 2017 Providing affordable housing and reducing greenhouse gases are common goals in cities worldwide. Transit-oriented development (TOD) can provide an opportunity to make incremental progress on both fronts, by building affordable housing near transit and by providing alternative transport modes such that households reduce driving. While the existing literature has focused on the relationship between TOD and housing and TOD and greenhouse gas emission reduction as separate issues, it has seldom touched on the possibility that TOD could address both goals jointly. We provide evidence to show that focusing on either housing affordability or greenhouse gas emission reduction in isolation can lead to strategies that achieve one goal to the detriment of the other. Using the case of Los Angeles, we develop a scenario planning model that allows simultaneous consideration of housing and transportation goals, and illustrates the tradeoffs of different policy approaches. The results show that larger increases in residential densities combined with a small inclusionary housing requirement yields greater benefits, in terms of both reduced driving and more affordable housing, than would a higher inclusionary percentage with smaller increases in density. Close

• 182. [Article] TRM for Household Refrigerator

  Since the first refrigerator was patented in 1834, the technology, cost, and ease of use has made it an essential part of the home kitchen of today. General Electric (GE), one of the leading producers ...

  Citation × Citation Citation Abstract Copy Title: TRM for Household Refrigerator Author: Jiang, Jing, Thompson, Justin, Al-Mulla, Nameer, Boulos, Zina Year: 2013 Since the first refrigerator was patented in 1834, the technology, cost, and ease of use has made it an essential part of the home kitchen of today. General Electric (GE), one of the leading producers of refrigerators in the world is being modeled as the manufacturer of choice because they possess the diverse technological know-how to improve this product. GE was chosen as the model manufacturer because they exhibit the forward thinking traits and large business diversification to prepare a technology roadmapping study. This paper will utilize technology roadmapping to create a plan for how GE could focus their effort and resources in their refrigeration business unit to develop a refrigerator in the future which will harness the market drivers to capture more of the market share. Technology Roadmapping is collaborative process first developed by the CEO of Motorola and allows to experts and researchers in the field of study to determine the market drivers, technologies, products/components, and resources. These items are put to a time line during the iterative initial steps then are connected through links. The benefit of using this method in this study is that it allows many different market drivers that consumers have to develop a refrigerator that largely meets those needs. In essence, GE wishes to find out the market pull to develop technologies that push consumers more towards their refrigerators. This study will show that technology roadmapping can be successfully used to create a plan of action over a time span of only 20 years that will integrate existing refrigerator technology and identify gaps in those technologies. The refrigerator GE ultimately creates for this hypothetical future is not set in stone which comes from the fact that market drivers and other issues may change. Technology roadmaps are not commandments for an organization to follow, but must be adapted as new knowledge becomes available. Title: TRM for Household Refrigerator Author: Jiang, Jing, Thompson, Justin, Al-Mulla, Nameer, Boulos, Zina Year: 2013 Since the first refrigerator was patented in 1834, the technology, cost, and ease of use has made it an essential part of the home kitchen of today. General Electric (GE), one of the leading producers of refrigerators in the world is being modeled as the manufacturer of choice because they possess the diverse technological know-how to improve this product. GE was chosen as the model manufacturer because they exhibit the forward thinking traits and large business diversification to prepare a technology roadmapping study. This paper will utilize technology roadmapping to create a plan for how GE could focus their effort and resources in their refrigeration business unit to develop a refrigerator in the future which will harness the market drivers to capture more of the market share. Technology Roadmapping is collaborative process first developed by the CEO of Motorola and allows to experts and researchers in the field of study to determine the market drivers, technologies, products/components, and resources. These items are put to a time line during the iterative initial steps then are connected through links. The benefit of using this method in this study is that it allows many different market drivers that consumers have to develop a refrigerator that largely meets those needs. In essence, GE wishes to find out the market pull to develop technologies that push consumers more towards their refrigerators. This study will show that technology roadmapping can be successfully used to create a plan of action over a time span of only 20 years that will integrate existing refrigerator technology and identify gaps in those technologies. The refrigerator GE ultimately creates for this hypothetical future is not set in stone which comes from the fact that market drivers and other issues may change. Technology roadmaps are not commandments for an organization to follow, but must be adapted as new knowledge becomes available. Close

• 183. [Article] Technological Innovation and Strategicc Analysis on the Smart Grids of Cisco

  The term ‘smart grid’ has been trending in the media for the last decade, but not everyone knows what is a grid and by what definition, it is called smart. We can think of smart grid as smart phones. In ...

  Citation × Citation Citation Abstract Copy Title: Technological Innovation and Strategicc Analysis on the Smart Grids of Cisco Author: Madan, Abdullah Al, Zhang, Pei Year: 2015 The term ‘smart grid’ has been trending in the media for the last decade, but not everyone knows what is a grid and by what definition, it is called smart. We can think of smart grid as smart phones. In the term ‘smartphones’, a phone is the device that enables voice or video communications between users when they are not in the same vicinity. Therefore, to add the ‘smart’ characteristic, smartphones enable more functions than only telecommunications. Smartphones would have touchscreen interface, Internet access, app download, and game console [1]. Likewise, ‘the grid’ is the electric grid that contains a network of transmission lines, substations, transformers, and more equipment that deliver power system from the power plants to the power plug-in at your home or business. Now the question will rise that what makes a grid ‘smart’. The official website of smart grid provides a clear answer to this question: In short, the digital technology that allows for two-way communication between the utility and its customers, and the sensing along the transmission lines is what makes the grid smart. Like the Internet, the Smart Grid will consist of controls, computers, automation, and new technologies and equipment working together, but in this case, these technologies will work with the electrical grid to respond digitally to our quickly changing electric demand [2]. According to Professor Chandler, an adjacent Electrical Engineering professor at Portland State University, “society is now connected to the Internet” [3]. Chandler’s comment was in response to the smart grid technology development stage. Therefore, in the case of smartphones, the Internet is the main driver to develop this product. Likewise, Internet is a technology leaning on the Internet. Smart grid will allow interoperability between different firms in the power system such as interoperability between electric utilities and the households. Title: Technological Innovation and Strategicc Analysis on the Smart Grids of Cisco Author: Madan, Abdullah Al, Zhang, Pei Year: 2015 The term ‘smart grid’ has been trending in the media for the last decade, but not everyone knows what is a grid and by what definition, it is called smart. We can think of smart grid as smart phones. In the term ‘smartphones’, a phone is the device that enables voice or video communications between users when they are not in the same vicinity. Therefore, to add the ‘smart’ characteristic, smartphones enable more functions than only telecommunications. Smartphones would have touchscreen interface, Internet access, app download, and game console [1]. Likewise, ‘the grid’ is the electric grid that contains a network of transmission lines, substations, transformers, and more equipment that deliver power system from the power plants to the power plug-in at your home or business. Now the question will rise that what makes a grid ‘smart’. The official website of smart grid provides a clear answer to this question: In short, the digital technology that allows for two-way communication between the utility and its customers, and the sensing along the transmission lines is what makes the grid smart. Like the Internet, the Smart Grid will consist of controls, computers, automation, and new technologies and equipment working together, but in this case, these technologies will work with the electrical grid to respond digitally to our quickly changing electric demand [2]. According to Professor Chandler, an adjacent Electrical Engineering professor at Portland State University, “society is now connected to the Internet” [3]. Chandler’s comment was in response to the smart grid technology development stage. Therefore, in the case of smartphones, the Internet is the main driver to develop this product. Likewise, Internet is a technology leaning on the Internet. Smart grid will allow interoperability between different firms in the power system such as interoperability between electric utilities and the households. Close

• 184. [Article] Who Uses Peer-to-Peer Carsharing? Early Exploration

  Peer-to-peer (P2P) carsharing is a system where a facilitating company connects car owners to car renters. Such systems are relatively new in the U.S. This paper aims to understand who is participating ...

  Citation × Citation Citation Abstract Copy Title: Who Uses Peer-to-Peer Carsharing? Early Exploration Author: Mathez, Anaïs Year: 2015 Peer-to-peer (P2P) carsharing is a system where a facilitating company connects car owners to car renters. Such systems are relatively new in the U.S. This paper aims to understand who is participating in P2P carsharing as a renter (as opposed to as an owner), why they join, whether and how often they rent vehicles, and why. Exploring these questions may provide insight on the potential for P2P carsharing to meet public policy objectives of reducing the impacts of personal vehicle ownership and use and providing mobility options for underserved populations. The analysis is based on 465 study participants who enrolled in a P2P carsharing service in Portland, Oregon during its first two years of operation (February 2012 to June 2014). The data, which come from a series of online surveys, are part of an on-going, multi-year research project and, as such, should be considered early findings. The people who joined P2P carsharing and this study tend to be younger and well-educated, consistent with research on traditional carsharing. Given two trends in vehicle ownership – the longstanding positive correlation with income and the emerging trend of younger Americans eschewing vehicle ownership in greater numbers than before - we created a typology of potential P2P renters to explore reasons for joining and the potential influence of P2P carsharing on vehicle ownership and mobility. The typology consists of: (1) Student Millennials,(2) Non-student Millennials, (3) Lower Income Non-millennials, and (4) Higher Income Non-millennials. Study participants were highly motivated to join simply because they like the idea of P2P carsharing. Not surprisingly, the Higher Income Non-millennials were less motivated by economic reasons. By June 2014, just over half (52%) of the study participants had rented a vehicle through the service. Actual use of the service is negatively correlated with car ownership. There are some early indications that the service may be expanding mobility options for lower income households. Title: Who Uses Peer-to-Peer Carsharing? Early Exploration Author: Mathez, Anaïs Year: 2015 Peer-to-peer (P2P) carsharing is a system where a facilitating company connects car owners to car renters. Such systems are relatively new in the U.S. This paper aims to understand who is participating in P2P carsharing as a renter (as opposed to as an owner), why they join, whether and how often they rent vehicles, and why. Exploring these questions may provide insight on the potential for P2P carsharing to meet public policy objectives of reducing the impacts of personal vehicle ownership and use and providing mobility options for underserved populations. The analysis is based on 465 study participants who enrolled in a P2P carsharing service in Portland, Oregon during its first two years of operation (February 2012 to June 2014). The data, which come from a series of online surveys, are part of an on-going, multi-year research project and, as such, should be considered early findings. The people who joined P2P carsharing and this study tend to be younger and well-educated, consistent with research on traditional carsharing. Given two trends in vehicle ownership – the longstanding positive correlation with income and the emerging trend of younger Americans eschewing vehicle ownership in greater numbers than before - we created a typology of potential P2P renters to explore reasons for joining and the potential influence of P2P carsharing on vehicle ownership and mobility. The typology consists of: (1) Student Millennials,(2) Non-student Millennials, (3) Lower Income Non-millennials, and (4) Higher Income Non-millennials. Study participants were highly motivated to join simply because they like the idea of P2P carsharing. Not surprisingly, the Higher Income Non-millennials were less motivated by economic reasons. By June 2014, just over half (52%) of the study participants had rented a vehicle through the service. Actual use of the service is negatively correlated with car ownership. There are some early indications that the service may be expanding mobility options for lower income households. Close

• 185. [Article] Impact of Bike Facilities on Residential Property Prices

  As many cities are investing in street improvement or transportation infrastructure upgrade projects to provide better bike access or more complete bike networks, the economic value of bike infrastructure ...

  Citation × Citation Citation Abstract Copy Title: Impact of Bike Facilities on Residential Property Prices Author: Shi, Wei Year: 2017 As many cities are investing in street improvement or transportation infrastructure upgrade projects to provide better bike access or more complete bike networks, the economic value of bike infrastructure and bike facilities remains an area where many practitioners, planners and policy makers are seeking more conclusive evidence. Using residential property values as indicators of consumer preferences for bicycle infrastructure, this study focuses on advanced bike facilities which represent higher levels of bike priority or bike infrastructure investments that have been shown to be more desirable to a larger portion of the population. Estimating ordinary least squares hedonic pricing models and spatial autoregressive hedonic models separately for single and multi-family properties, we find that proximity to advanced bike facilities (measured by distance) has significant and positive effects on all residential property values, highlighting household preferences for high quality bike infrastructure. Furthermore, we also show that the extensiveness of the bike network (measured by density) is a positive and statistically significant contributor to the property prices for all residential property types, even after controlling for proximity to bike facilities and other property, neighborhood and transaction characteristics. Finally, estimated coefficients are applied to assess property value impacts of a proposed Portland “Green Loop” signature bike infrastructure concept, illustrating the importance of considering both accessibility and extensiveness of bike facility networks. Title: Impact of Bike Facilities on Residential Property Prices Author: Shi, Wei Year: 2017 As many cities are investing in street improvement or transportation infrastructure upgrade projects to provide better bike access or more complete bike networks, the economic value of bike infrastructure and bike facilities remains an area where many practitioners, planners and policy makers are seeking more conclusive evidence. Using residential property values as indicators of consumer preferences for bicycle infrastructure, this study focuses on advanced bike facilities which represent higher levels of bike priority or bike infrastructure investments that have been shown to be more desirable to a larger portion of the population. Estimating ordinary least squares hedonic pricing models and spatial autoregressive hedonic models separately for single and multi-family properties, we find that proximity to advanced bike facilities (measured by distance) has significant and positive effects on all residential property values, highlighting household preferences for high quality bike infrastructure. Furthermore, we also show that the extensiveness of the bike network (measured by density) is a positive and statistically significant contributor to the property prices for all residential property types, even after controlling for proximity to bike facilities and other property, neighborhood and transaction characteristics. Finally, estimated coefficients are applied to assess property value impacts of a proposed Portland “Green Loop” signature bike infrastructure concept, illustrating the importance of considering both accessibility and extensiveness of bike facility networks. Close

• 186. [Article] Forecasting Super-Efficient Dryers Adoption in the Pacific Northwest

  Energy efficiency is now estimated to be the third source of electricity in the USA (in the form of virtual power capacity equal to the savings resulted from efficiency). The Pacific NorthWest is among ...

  Citation × Citation Citation Abstract Copy Title: Forecasting Super-Efficient Dryers Adoption in the Pacific Northwest Author: Gupta, Apeksha, Barham, Husam, Lavoie, Joao, Lilja, Tania, Nguyen, Tin Year: 2016 Energy efficiency is now estimated to be the third source of electricity in the USA (in the form of virtual power capacity equal to the savings resulted from efficiency). The Pacific NorthWest is among the leading regions in the US when it comes to energy efficiency [1, 2], in fact, it is estimated that energy efficiency will meet all the new demands in the Pacific NorthWest region through 2035. The Northwest Energy Efficiency Alliance (NEEA), is an alliance of more than 140 Northwest utilities and energy efficiency organizations, dedicated to accelerating both electric and gas energy efficiency, leveraging its regional partnerships to advance the adoption of energy-efficient products, services and practices. One product NEEA has been evaluating recently is super-efficient dryers, a product that promises energy efficiency as much as 40% of the current energy being consumed by a typical dryer in the region [4]. Before NEEA can promote and support this product, they need to understand its market potentials, so two separated studies were conducted to forecast this product future, however; the studies indicated different results. In this project, the objectives are to forecast the adoption and market share of super-efficient dryers (SED’s) and to provide additional information that could help organizations like NEEA to promote and disseminate SED’s, creating market transformations towards the adoption of energy efficient products. More specifically, our goal is to help NEEA by providing them with yet another counter-factual model of the super efficient dryers adoption (focusing on a specific market segment), and also to enable NEEA to use this model as a tool to convince manufacturers to increase their marketing efforts towards a larger adoption. The next section brings a literature review on technology forecasting, energy efficiency and other important topics for this study, followed by methodology, analysis and results, conclusions, limitations and future research. Title: Forecasting Super-Efficient Dryers Adoption in the Pacific Northwest Author: Gupta, Apeksha, Barham, Husam, Lavoie, Joao, Lilja, Tania, Nguyen, Tin Year: 2016 Energy efficiency is now estimated to be the third source of electricity in the USA (in the form of virtual power capacity equal to the savings resulted from efficiency). The Pacific NorthWest is among the leading regions in the US when it comes to energy efficiency [1, 2], in fact, it is estimated that energy efficiency will meet all the new demands in the Pacific NorthWest region through 2035. The Northwest Energy Efficiency Alliance (NEEA), is an alliance of more than 140 Northwest utilities and energy efficiency organizations, dedicated to accelerating both electric and gas energy efficiency, leveraging its regional partnerships to advance the adoption of energy-efficient products, services and practices. One product NEEA has been evaluating recently is super-efficient dryers, a product that promises energy efficiency as much as 40% of the current energy being consumed by a typical dryer in the region [4]. Before NEEA can promote and support this product, they need to understand its market potentials, so two separated studies were conducted to forecast this product future, however; the studies indicated different results. In this project, the objectives are to forecast the adoption and market share of super-efficient dryers (SED’s) and to provide additional information that could help organizations like NEEA to promote and disseminate SED’s, creating market transformations towards the adoption of energy efficient products. More specifically, our goal is to help NEEA by providing them with yet another counter-factual model of the super efficient dryers adoption (focusing on a specific market segment), and also to enable NEEA to use this model as a tool to convince manufacturers to increase their marketing efforts towards a larger adoption. The next section brings a literature review on technology forecasting, energy efficiency and other important topics for this study, followed by methodology, analysis and results, conclusions, limitations and future research. Close

• 187. [Article] Assessing Portland's Smart Growth: A Comprehensive Housing Supply and Location Choice Modeling Approach

  There are extensive empirical studies on the impacts and effectiveness of Smart Growth policies; however, very few of them consider the perspective of individual decision makers and, to this author's knowledge, ...

  Citation × Citation Citation Abstract Copy Title: Assessing Portland's Smart Growth: A Comprehensive Housing Supply and Location Choice Modeling Approach Author: Dong, Hongwei Year: 2010 There are extensive empirical studies on the impacts and effectiveness of Smart Growth policies; however, very few of them consider the perspective of individual decision makers and, to this author's knowledge, none have studied developers as location-aware decision-making agents. This study tries to fill this gap partially by assessing the impacts of Portland's smart growth policies on developers' location choice behavior with developer-based location choice models. The dissertation has two purposes. By assessing the impacts of Smart Growth policies on individual home developer's location choice, it provides a micro- and behavioral foundation for the understanding of Smart Growth policies. As a bi-state metropolitan area located on the border between Oregon and Washington, the Portland region provides a unique environment that allows my research to examine whether home developers react to Smart Growth policies differently in the two states with different land use policy systems. The dissertation also aims to create a developer-based land development forecast model, which can be used as a scenario analysis tool for the Portland region's long-term land use and transportation planning. Besides the developer location choice model mentioned above, the components of this comprehensive developer-based land development model also include a time series regression model that predicts annual new housing supply in the region and a model that synthesizes housing projects in a forecast year. The study shows that home developers in the Portland metropolitan area are sensitive to most Smart Growth policies that have been implemented in the region, but they react to them differently across the border between Oregon and Washington. Single-family home (SFH) and multi-family home (MFH) developers show different preferences for location attributes. The most significant predictors of where a developer will choose to locate a project are the locations of previous projects. After controlling for all of the other factors discussed above, there remains a strong preference for developing SFH units outside of the UGB in both Oregon and Washington sides of the Portland metropolitan area. Latent class models have been developed to detect taste variations among home developers in the SFH and MFH markets separately. Estimation results show clear taste variations across developers and housing projects with respect to site attributes in their location choice. With other variables in the segmentation model being the same, project size provides a better fit to the data than developer size, indicating that developers have taste variations among their different projects. Large size SFH projects developed by contractor-owners are more likely to be within the UGB and their locations tend to have higher residential density, housing diversity, transportation accessibility, road density, and land price. With most MFH projects within the UGB, estimation results show that large size MFH projects prefer the locations with higher residential density, housing diversity, mixed use, road density, land price, average household income, and proportion of young and middle age households. The three-step new housing supply and location choice forecast model seem to be able to capture the basic trend of housing market and land development in the Portland region. Three different aggregate housing supply forecast models, an conditional time series regressive model, a unconditional time series regression model, and an auto-regression integrated moving average (ARIMA) model were tested and their advantages and disadvantages were discussed. Both the SFH and MFH project synthesis models can simulate housing projects well for a forecast year. Three location choice models were developed to allocate synthesized housing projects into space. The three models are characterized separately as: (1) assumed market homogeneity and atomization of development projects; (2) deterministic market segmentation and synthesis of projects by size; and (3) probabilistic market segmentation and synthesis of projects by size, using a latent class approach. Examination of forecast results shows that all three models can successfully capture the basic spatial pattern of housing development in the region; however, the spatial distribution of MFH development is lumpier and more unpredictable. While Models 2 and 3 are more sophisticated and make more sense from a theoretical perspective, they do not return better forecast results than Model 1 due to some practical issues. Models 2 and 3 would be expected to perform better when those practical issues are solved, at least partially, in future research. Title: Assessing Portland's Smart Growth: A Comprehensive Housing Supply and Location Choice Modeling Approach Author: Dong, Hongwei Year: 2010 There are extensive empirical studies on the impacts and effectiveness of Smart Growth policies; however, very few of them consider the perspective of individual decision makers and, to this author's knowledge, none have studied developers as location-aware decision-making agents. This study tries to fill this gap partially by assessing the impacts of Portland's smart growth policies on developers' location choice behavior with developer-based location choice models. The dissertation has two purposes. By assessing the impacts of Smart Growth policies on individual home developer's location choice, it provides a micro- and behavioral foundation for the understanding of Smart Growth policies. As a bi-state metropolitan area located on the border between Oregon and Washington, the Portland region provides a unique environment that allows my research to examine whether home developers react to Smart Growth policies differently in the two states with different land use policy systems. The dissertation also aims to create a developer-based land development forecast model, which can be used as a scenario analysis tool for the Portland region's long-term land use and transportation planning. Besides the developer location choice model mentioned above, the components of this comprehensive developer-based land development model also include a time series regression model that predicts annual new housing supply in the region and a model that synthesizes housing projects in a forecast year. The study shows that home developers in the Portland metropolitan area are sensitive to most Smart Growth policies that have been implemented in the region, but they react to them differently across the border between Oregon and Washington. Single-family home (SFH) and multi-family home (MFH) developers show different preferences for location attributes. The most significant predictors of where a developer will choose to locate a project are the locations of previous projects. After controlling for all of the other factors discussed above, there remains a strong preference for developing SFH units outside of the UGB in both Oregon and Washington sides of the Portland metropolitan area. Latent class models have been developed to detect taste variations among home developers in the SFH and MFH markets separately. Estimation results show clear taste variations across developers and housing projects with respect to site attributes in their location choice. With other variables in the segmentation model being the same, project size provides a better fit to the data than developer size, indicating that developers have taste variations among their different projects. Large size SFH projects developed by contractor-owners are more likely to be within the UGB and their locations tend to have higher residential density, housing diversity, transportation accessibility, road density, and land price. With most MFH projects within the UGB, estimation results show that large size MFH projects prefer the locations with higher residential density, housing diversity, mixed use, road density, land price, average household income, and proportion of young and middle age households. The three-step new housing supply and location choice forecast model seem to be able to capture the basic trend of housing market and land development in the Portland region. Three different aggregate housing supply forecast models, an conditional time series regressive model, a unconditional time series regression model, and an auto-regression integrated moving average (ARIMA) model were tested and their advantages and disadvantages were discussed. Both the SFH and MFH project synthesis models can simulate housing projects well for a forecast year. Three location choice models were developed to allocate synthesized housing projects into space. The three models are characterized separately as: (1) assumed market homogeneity and atomization of development projects; (2) deterministic market segmentation and synthesis of projects by size; and (3) probabilistic market segmentation and synthesis of projects by size, using a latent class approach. Examination of forecast results shows that all three models can successfully capture the basic spatial pattern of housing development in the region; however, the spatial distribution of MFH development is lumpier and more unpredictable. While Models 2 and 3 are more sophisticated and make more sense from a theoretical perspective, they do not return better forecast results than Model 1 due to some practical issues. Models 2 and 3 would be expected to perform better when those practical issues are solved, at least partially, in future research. Close

• 188. [Article] The Determinants of Women's Work: A Case Study from Three Urban Low-income Communities in Amman, Jordan

  This study addresses the determinants of women's economic activity in three low income communities in Amman, the capital of Jordan. These communities represent what is typically referred to as "pockets ...

  Citation × Citation Citation Abstract Copy Title: The Determinants of Women's Work: A Case Study from Three Urban Low-income Communities in Amman, Jordan Author: Tubbeh, Taghrid Khuri Year: 1994 This study addresses the determinants of women's economic activity in three low income communities in Amman, the capital of Jordan. These communities represent what is typically referred to as "pockets of urban poverty." Besides addressing the demographic and socio-economic variables, the study identifies and includes cultural variables in a model of female labor force participation. Modern economic systems developed definitions and measurements of productivity that render the majority of women's work as non-productive. Activities within the domestic sphere that do not earn monetary returns are not measured as productive economic activities, and hence are dropped from the calculations of gross national and domestic products of most if not all developing nations. In the Arab Middle East, where women's work outside the home is relatively a recent phenomenon, labor statistics are measuring only female labor force in the "formal sector" of the labor market. The scope and magnitude of women's economic activity within the domestic sphere, or in what is termed the informal sector, is neglected, or at best, underestimated, by labor force statistics. In such cultural contexts where women's economic activity outside the home is still considered secondary to the array of their reproductive and home-related activities, the underlying thesis is that cultural factors play an important role in shaping the outcomes of women's decisions regarding labor force participation. A field survey covered the sample of adult women, aged 15 years and over. To achieve a 95% level of significance, 435 women were interviewed. Three field surveyors were trained to thoroughly probe and depict all types of economic activity for the purpose of raising cash, be it in the formal or the informal sectors of the labor market. A nested logit model assesses the effects of demographic and socio-economic variables on women's employment status. Employment status is defined as a dichotomous dependent variable indicating whether a woman does or does not work. The second step of the logit model incorporates cultural variables in addition to the demographic and socio-economic variables. Each logit run segregates women by marital status, and one run addresses the pooled sample of women, with marital status included as a predictor variable. The results indicate that age and marital status (in the pooled sample) are important variables in determining the employment status of women. The presence of a resource person to help the ever-married woman in child-care also had a significant effect on women's employment decisions. Household income, which represents the need for the woman's income, is also a significant variable. In the second step of the nested logit model, education significantly influences women's work outside the home. Segregation (a cultural variable that represented a constraint to women's work in a mixed environment) is also a significant variable in influencing women's work inside the home. This study shows that when addressing the determinants of female labor force participation, it is important to include cultural variables and assess their effect on influencing the outcome of women's decisions to undertake economic activity. Policies that seek to increase female employment need to be aware of the cultural and demographic (fertility related) considerations. Consequently, employment creation and enhancement programs need to be formulated and designed with this consideration in focus. For example, child-care facilities could be established within communities. This will free sometime of mothers with children to work outside the home, and will create child-care jobs within the community. Realizing that, due to cultural barriers, some women will still desire to only work at home, agencies providing marketing channels for such activities need to be established. Title: The Determinants of Women's Work: A Case Study from Three Urban Low-income Communities in Amman, Jordan Author: Tubbeh, Taghrid Khuri Year: 1994 This study addresses the determinants of women's economic activity in three low income communities in Amman, the capital of Jordan. These communities represent what is typically referred to as "pockets of urban poverty." Besides addressing the demographic and socio-economic variables, the study identifies and includes cultural variables in a model of female labor force participation. Modern economic systems developed definitions and measurements of productivity that render the majority of women's work as non-productive. Activities within the domestic sphere that do not earn monetary returns are not measured as productive economic activities, and hence are dropped from the calculations of gross national and domestic products of most if not all developing nations. In the Arab Middle East, where women's work outside the home is relatively a recent phenomenon, labor statistics are measuring only female labor force in the "formal sector" of the labor market. The scope and magnitude of women's economic activity within the domestic sphere, or in what is termed the informal sector, is neglected, or at best, underestimated, by labor force statistics. In such cultural contexts where women's economic activity outside the home is still considered secondary to the array of their reproductive and home-related activities, the underlying thesis is that cultural factors play an important role in shaping the outcomes of women's decisions regarding labor force participation. A field survey covered the sample of adult women, aged 15 years and over. To achieve a 95% level of significance, 435 women were interviewed. Three field surveyors were trained to thoroughly probe and depict all types of economic activity for the purpose of raising cash, be it in the formal or the informal sectors of the labor market. A nested logit model assesses the effects of demographic and socio-economic variables on women's employment status. Employment status is defined as a dichotomous dependent variable indicating whether a woman does or does not work. The second step of the logit model incorporates cultural variables in addition to the demographic and socio-economic variables. Each logit run segregates women by marital status, and one run addresses the pooled sample of women, with marital status included as a predictor variable. The results indicate that age and marital status (in the pooled sample) are important variables in determining the employment status of women. The presence of a resource person to help the ever-married woman in child-care also had a significant effect on women's employment decisions. Household income, which represents the need for the woman's income, is also a significant variable. In the second step of the nested logit model, education significantly influences women's work outside the home. Segregation (a cultural variable that represented a constraint to women's work in a mixed environment) is also a significant variable in influencing women's work inside the home. This study shows that when addressing the determinants of female labor force participation, it is important to include cultural variables and assess their effect on influencing the outcome of women's decisions to undertake economic activity. Policies that seek to increase female employment need to be aware of the cultural and demographic (fertility related) considerations. Consequently, employment creation and enhancement programs need to be formulated and designed with this consideration in focus. For example, child-care facilities could be established within communities. This will free sometime of mothers with children to work outside the home, and will create child-care jobs within the community. Realizing that, due to cultural barriers, some women will still desire to only work at home, agencies providing marketing channels for such activities need to be established. Close

• 189. [Article] What Country Makes the Best Place for Work? By using Hierarchical Decision Model (HDM)

  Work is very basic practice in human civilization. Starting with billions of years ago, a human was busy with farming, lumberjack, hunting, and sailor. Indeed, the role of labor and the development of ...

  Citation × Citation Citation Abstract Copy Title: What Country Makes the Best Place for Work? By using Hierarchical Decision Model (HDM) Author: AL Saglab, Bashair Year: 2017 Work is very basic practice in human civilization. Starting with billions of years ago, a human was busy with farming, lumberjack, hunting, and sailor. Indeed, the role of labor and the development of different kinds of jobs have been prime to our growth and wealthiest; as a result, human will seek to the most convenient place in the earth that will provide a good place for work. From this concept, finding the best country for work is important in these days. Because human cannot live without work, finding the most desirable country to work is essential. Based on the evaluation of the most priority needs from a set of criteria, a good decision for selecting the criteria that are influencing the decision can be taken. In fact, a good evaluation tool will help human to select the adequate country for work. This paper is about decision-making model for selection a country for work that a family or an indivisible will choose to ensure a better quality of life, happiness, and comfort. This paper develops a framework to determine the most outstanding country for work from different countries around the global. The decision model used in this research paper is a comprehensive evaluation tool for a personal decision analysis that answers this question "What country makes the best place for work?" Indeed, a hierarchical decision model (HDM) was constructed for the framework. Experts judgments were used in this research paper to provide a pair-wised comparison evaluation for choosing one of the country outcomes that are: KSA, USA, UAE, and UK. The hierarchy model includes three levels: criteria, sub-criteria, and alternatives. The results of this analysis show that working in The United Kingdom is the best place to work because of the weighted score for political stability, tolerance for other customs, and Language barriers. This model would be helpful for an individual case who is qualified to start looking for a good work opportunity in either KSA, USA, UAE, and UK and have these characteristics of a limited budget, special traditions, and socially interactive. Though this paper highlighted several issues in selecting the best place for work, this would make a good topic for future research. Indeed, addressing the size of the company and the size of the family who lives in the household. And the education level for the work seeker, also the working experience period. Title: What Country Makes the Best Place for Work? By using Hierarchical Decision Model (HDM) Author: AL Saglab, Bashair Year: 2017 Work is very basic practice in human civilization. Starting with billions of years ago, a human was busy with farming, lumberjack, hunting, and sailor. Indeed, the role of labor and the development of different kinds of jobs have been prime to our growth and wealthiest; as a result, human will seek to the most convenient place in the earth that will provide a good place for work. From this concept, finding the best country for work is important in these days. Because human cannot live without work, finding the most desirable country to work is essential. Based on the evaluation of the most priority needs from a set of criteria, a good decision for selecting the criteria that are influencing the decision can be taken. In fact, a good evaluation tool will help human to select the adequate country for work. This paper is about decision-making model for selection a country for work that a family or an indivisible will choose to ensure a better quality of life, happiness, and comfort. This paper develops a framework to determine the most outstanding country for work from different countries around the global. The decision model used in this research paper is a comprehensive evaluation tool for a personal decision analysis that answers this question "What country makes the best place for work?" Indeed, a hierarchical decision model (HDM) was constructed for the framework. Experts judgments were used in this research paper to provide a pair-wised comparison evaluation for choosing one of the country outcomes that are: KSA, USA, UAE, and UK. The hierarchy model includes three levels: criteria, sub-criteria, and alternatives. The results of this analysis show that working in The United Kingdom is the best place to work because of the weighted score for political stability, tolerance for other customs, and Language barriers. This model would be helpful for an individual case who is qualified to start looking for a good work opportunity in either KSA, USA, UAE, and UK and have these characteristics of a limited budget, special traditions, and socially interactive. Though this paper highlighted several issues in selecting the best place for work, this would make a good topic for future research. Indeed, addressing the size of the company and the size of the family who lives in the household. And the education level for the work seeker, also the working experience period. Close

• 190. [Article] Factors Affecting Behavioral Changes in Response to Road Fees: Some Analyses of the Effect of Attitudes, Transit Access, and Fuel Efficiency on Changes in Miles Driven

  Objective The Oregon Department of Transportation conducted a test of an innovative technology to replace fuel taxes with mileage fees. In the test, some vehicles were charged a flat fee per mile and others ...

  Citation × Citation Citation Abstract Copy Title: Factors Affecting Behavioral Changes in Response to Road Fees: Some Analyses of the Effect of Attitudes, Transit Access, and Fuel Efficiency on Changes in Miles Driven Author: Rufolo, Anthony M. Year: 2009 Objective The Oregon Department of Transportation conducted a test of an innovative technology to replace fuel taxes with mileage fees. In the test, some vehicles were charged a flat fee per mile and others were charged differential fees that were higher for travel in the Portland metropolitan area during weekday peak hours and lower for other travel. I was charged with developing the database for the project and analyzing the behavioral responses of the participants. The database is quite extensive, including responses to three surveys as well as information on mileage in various categories. The experiment ended on April 1, 2007 and the final report on the project is due June 30, 2007. This is also the time when funding for the project will end. The final report will include information on key behavioral changes, such as the reduction in miles traveled per day during the peak for the congestion charge group. However, the database has the potential for much more extensive analysis. In addition, a different type of congestion charging experiment was conducted by the Puget Sound Regional Council, and a public use dataset from that experiment is expected to become available within the next six months. The objective of this proposal is to extend the analysis of changes in behavior by subjects in the ODOT Road User Fee Pilot Project, and to draw on other sources, such as the Puget Sound project, to compare the behavioral changes observed in this experiment with those found in other contexts. Scope A substantial amount of data was collected on participants in the Oregon Road User Fee Pilot Project. Basic analysis of the data is being conducted as part of the project. However, there is potential to gain further information on characteristics that caused or prevented changes in participants’ driving patterns. For example, participants were asked the distance from their home to the nearest transit stop, but that was the only information on transit service that was available for analysis. It would be possible to use the participant’s address to generate much more comprehensive measures of transit service availability to determine whether these other dimensions of transit service affected the response to road pricing. In addition, information on day of week and morning versus evening peak travel is being aggregated for the existing study, but this data holds the potential for further information on the nature of the responses. Methodology A variety of statistical analyses will be conducted to evaluate both the extent of response to a vehicle mileage fee and the interaction with both demographic and attitudinal characteristics of the participants. A GIS analysis will be used to link household location with better measures of transit service. Results Results would include a better understanding of how pricing interacts with other factors in affecting driving patterns and in particular in affecting driving during peak periods. It would also provide a better understanding of the revenue potential from such charges. Title: Factors Affecting Behavioral Changes in Response to Road Fees: Some Analyses of the Effect of Attitudes, Transit Access, and Fuel Efficiency on Changes in Miles Driven Author: Rufolo, Anthony M. Year: 2009 Objective The Oregon Department of Transportation conducted a test of an innovative technology to replace fuel taxes with mileage fees. In the test, some vehicles were charged a flat fee per mile and others were charged differential fees that were higher for travel in the Portland metropolitan area during weekday peak hours and lower for other travel. I was charged with developing the database for the project and analyzing the behavioral responses of the participants. The database is quite extensive, including responses to three surveys as well as information on mileage in various categories. The experiment ended on April 1, 2007 and the final report on the project is due June 30, 2007. This is also the time when funding for the project will end. The final report will include information on key behavioral changes, such as the reduction in miles traveled per day during the peak for the congestion charge group. However, the database has the potential for much more extensive analysis. In addition, a different type of congestion charging experiment was conducted by the Puget Sound Regional Council, and a public use dataset from that experiment is expected to become available within the next six months. The objective of this proposal is to extend the analysis of changes in behavior by subjects in the ODOT Road User Fee Pilot Project, and to draw on other sources, such as the Puget Sound project, to compare the behavioral changes observed in this experiment with those found in other contexts. Scope A substantial amount of data was collected on participants in the Oregon Road User Fee Pilot Project. Basic analysis of the data is being conducted as part of the project. However, there is potential to gain further information on characteristics that caused or prevented changes in participants’ driving patterns. For example, participants were asked the distance from their home to the nearest transit stop, but that was the only information on transit service that was available for analysis. It would be possible to use the participant’s address to generate much more comprehensive measures of transit service availability to determine whether these other dimensions of transit service affected the response to road pricing. In addition, information on day of week and morning versus evening peak travel is being aggregated for the existing study, but this data holds the potential for further information on the nature of the responses. Methodology A variety of statistical analyses will be conducted to evaluate both the extent of response to a vehicle mileage fee and the interaction with both demographic and attitudinal characteristics of the participants. A GIS analysis will be used to link household location with better measures of transit service. Results Results would include a better understanding of how pricing interacts with other factors in affecting driving patterns and in particular in affecting driving during peak periods. It would also provide a better understanding of the revenue potential from such charges. Close