The Utah Department of Transportation (UDOT) manages and maintains a complex state-wide network of highways. Recent incidents such as the collapse of the I-35W bridge in Min- neapolis, Minnesota, and the I-85/Piedmont Road fire and subsequent bridge collapse in Atlanta, Georgia, have brought identification of transportation network vulnerabilities to the forefront of UDOT’s planning efforts. Traditional estimates of transportation network impacts have focused on increases to user travel time or the volume of affected traffic, but studies of these disasters have revealed that when facing a degraded transportation network, people adjust their trip making in terms of destination, mode, and route choice. The objective of this thesis is to evaluate the relative systemic criticality of highway links on Utah’s highway network using a logit-based model sensitive to changes in destination choice, mode choice, and route path. The current Utah Statewide Travel Model (USTM) does not incorporate user mode or destination choice, making it unsuitable for this task in its present condition. Consequently, this thesis develops a logit-based model structure that evaluates the cost of impaired destination choices and mode choices for home-based and non-home-based personal trips resulting from a damaged highway network. The choice model logsums capture the total value of user choices and can be readily converted to monetary values, making them ideal for this purpose. The logit-based model is then applied to 40 highway links located at strategic locations on Utah’s network. When compared with a more traditional travel time increase estimation, the logsum and travel time models provide categorically different cost estimates, where the logsum results are typically lower than travel time estimates, with implications for policy making and UDOT’s planning strategy. The results further suggest that freight trips are likely more important considerations than passenger trips, and should be considered in future research.

Detta examensarbete syftar till att svara på ett av Trafikverket fastställt problem: en gemensam regional cykelplanerings process skulle göra dem billigare och mer jämförbara. De erbjuder för närvarande planerarna en modell som utvecklades av Kågeson 2007. Denna modell har formen av en rapport som ger råd om när man ska bygga en cykelväg mellan städer eller platser i en region. Ändå används den bara i endast 6 av de 21 svenska länen. Trafikverket kräver ett nytt planeringsstödverktyg, mer interaktivt och komplett än Kågeson-modellen. Några nya önskade funktioner är separationen av efterfrågan per syfte, införandet av e-cyklar, olika resesyfte och en prioritering av investeringarna.  Examensarbetet är att designa och implementera det här verktyget, även kallat Planning Support System (PSS), som syftar till att jämföra utbud och efterfrågan på cykelväg till prioritering av infrastrukturförbättringar. En huvudbegränsning för modellen är att den måste vara billig datavis, men så komplett och exakt som möjligt. Det baseras på flera öppna dataleverantörer, till exempel OpenStreetMap, den svenska nationella vägdatabasen (NVDB) eller reseundersökningar från Sverige och Nederländerna. Resultatet är en modell, uppdelad efter turändamål och typ av cykel.  Del för efterfrågeuppskattning anpassar en klassisk fyrsteg transportmodell till cykelplanering och begränsad data. För olika resändamål genereras och distribueras resor tack vare en ursprungs begränsad gravitationsmodell. Valet av cykelläge är anpassat till det faktiska resebeteendet genom logistisk regression med en binär logit-modell. Resorna tilldelas sedan nätverket med tilldelnings metoden "allt-eller-ingenting" genom Dijkstras algoritm. För att utvärdera cykelförsörjningen använde vi ett mått som heter Level of Traffic Stress (LTS), som uppskattar den potentiella användningen av en nätverkslänk för olika delar av befolkningen som en funktion av vägnätvariablerna. Prioriteringsrankningen är då förhållandet mellan mått på efterfrågan och utbud.  Detta nya verktyg implementeras med opensource Geographic Information System (GIS) som heter QGIS och med Python 3 och testas i Södermanlands län / This Master Thesis main objective is to answer a problem set by the Swedish Transport Administration: a common regional bicycle planning process would them cheaper and more comparable. They currently offer the planners a model developed by Kågeson in 2007. This model takes the form of a report which advises on when to build a bicycle path between cities or places of a region. Still, it is only used in only 6 of the 21 Swedish counties. Trafikverket requires a new planning support tool, more interactive and complete than the Kågeson model. Some new desired features are the separation of demand per purpose, the inclusion of e-bikes, different trip purposes, and a prioritization of the investments.  The Degree Project work is to design and implement this tool, also called Planning Support System (PSS), which compares supply and demand for bicycle path to prioritizing infrastructure improvements. A main constraint for the model is that it needs to be cheap data-wise, but as complete and precise as possible. It bases on several open data providers, such as OpenStreetMap, the Swedish National Road Database (NVDB), or Travel Surveys from Sweden and the Netherlands. The result is a model, disaggregated by trip purpose and type of bicycle.  The demand estimation part adapts a classic four-step transportation model to bicycle planning and limited data. For different trip purposes, trips are generated and distributed thanks to an origin-constrained gravity model. Bicycle mode choice is fit to actual travel behaviour through logistic regression with a binary logit model. The trips are then assigned to the network using the "all-or-nothing" assignment method through the Dijkstra algorithm. To evaluate bicycle supply, we used a metric called Level of Traffic Stress (LTS), which estimates the potential use of a network link by different parts of the population as a function of the road network variables. The prioritization ranking is then the ratio between demand and supply metrics.  This new tool is implemented with the opensource Geographic Information System (GIS) called QGIS and with Python 3, and it is tested on Södermanland County.

Movements of cyclists and m.otor vehicles at intersections involve a wide variety of potential conflicting interactions. In Australia, the high numbers of motor vehicles, particularly light passenger vehicles, mixed with cyclists results in many bicycle-light passengervehicle (LPV) crashes (3,135 crashes during 2002-2014). About 68% of cyclist deaths at Australian intersections in 2016 were due to crashes between bicycles and LPVs (DITRLDG, 2016). The high number ofLPV crashes among fatalities among cyclists is an increasing safety concem. When an LPV collides with a cyclist, the resulting impact forces in.tluence the probability of cyclist injury severity outcom.e. Therefore, the goa1 at intersections should be to understand whether and which particular crash patterns are more injurious, in order to better inform approaches to reduce the impact forces to levels that do not result in severe injury outcomes. To examine how crash pattem (or mechanism) influences the injury severity of cyclists in bicycle-motor vehicle crashes at intersections, researchers typically describe the crash mechanism in terms of crash types, such as angle crashes, head--on crashes, rear-end crashes, and sideswipe crashes (e.g., Kim et al., 2007; Pai, 2011 ). While crash types explain crash mechanisms to some extent, this study hypothesiz.es that the trajectories of the crash involved vehicles may provide additional information because they better capture the movements of the vehicles prior to collision. Furthermore, it is argued that injury pattem might be in.tluenced by vehicle travel direction and manoeuvre (Isaksson-Hellman and Wemeke, 2017). For example, when a car is moving straight ahead it is likely to have a higher speed than when it is turning, and if cyclists are struck at a higher impact speed, they tend to sustain more severe injury (Badea-Romero and Lenard, 2013). While many studies have evaluated the association between cyclist injwy severity and crash types, the factors that might influence cyclist injury severity related to trajectory types (vehicle movement and travel direction) have not yet been thoroughly investigated. This study aims to examine the factors associated with cyclists' injury severity for 'trajectory types• compared with the typically used 'crash types' at intersections.

The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using a Pre and Post-Deployment DMS Survey (henceforth referred to as "pre and post-deployment survey") analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA have been working over the past two years to add several fixed DMS on their toll road network. At the time of the pre-deployment survey, only one DMS was installed on the OOCEA toll road network. At the time of the post-deployment survey, a total of 30 DMS were up and running on the OOCEA toll road network. Since most of the travelers on the OOCEA toll roads are from Orange, Osceola, and Seminole counties, this study was limited to these counties. This thesis documents the results and comparisons between the pre and post-deployment survey analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interviews. The pre-deployment survey was conducted during early November of 2006, and the post-deployment survey was conducted during the month of May, 2008. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most traveled toll road, county of residence, and length of residency) were asked to the respondents. The results of both the pre and post-deployment surveys are discussed in this thesis, but it should be noted that the more telling results are those of the post-deployment survey. The results of the post-deployment survey show the complete picture of the impact of DMS on travelers' experience on the OOCEA toll road network. The pre-deployment results are included to show an increase or decrease in certain aspects of travel experience with relation to DMS. The results of the pre-deployment analysis showed that 54.4% of the OOCEA travelers recalled seeing DMS on the network, while a total of 63.93% of the OOCEA travelers recalled seeing DMS during the post-deployment analysis. This showed an increase of almost 10% between the two surveys demonstrating the people are becoming more aware of DMS on the OOCEA toll road network. The respondents commonly agreed that the DMS were helpful for providing information about hazardous conditions, and that the DMS are easy to read. Also, upon further research it was found that between the pre and post-deployment surveys the travelers' satisfaction with special event information provided on DMS and travel time accuracy on DMS increased significantly. With respect to formatting of the DMS, the following methods were preferred by the majority of respondents in both the pre and post-deployment surveys: ● Steady Message as a default DMS message format ● Flashing Message for abnormal traffic information (94% of respondents would like to be notified of abnormal traffic information) ● State road number to show which roadway (for Colonial - SR 50, Semoran - SR 436 and Alafaya - SR 434) ● "I-Drive" is a good abbreviation for International Drive ● If the distance to the international airport is shown on a DMS it thought to be the distance to the airport exit The results from the binary logit model for "satisfaction with travel information provided on OOCEA toll road network" displayed the significant variables that explained the likelihood of the traveler being satisfied. This satisfaction model was based on respondents who showed a prior knowledge of DMS on OOCEA toll roads. With the use of a pooled model (satisfaction model with a total of 1775 responses - 816 from pre-deployment and 959 from post-deployment), it was shown that there was no statistical change between the pre and post-deployment satisfaction based on variables thought to be theoretically relevant. The results from the comparison between the pre and post-deployment satisfaction models showed that many of the coefficients of the variables showed a significant change. Although some of the variables were statistically insignificant in one of the two survey model results: Either the pre or post-deployment model, it was still shown that every variable was significant in at least one of the two models. The coefficient for the variable corresponding to DMS accuracy showed a significantly lower value in the post-deployment model. The coefficient for the variable "DMS was helpful for providing special event information" showed a significantly higher value in the post-deployment model. The final post-deployment diversion model was based on a total of 732 responses who answered that they had experienced congestion in the past 6 months. Based on this final post-deployment diversion model, travelers who had stated that their most frequently traveled toll road was either SR 408 or SR 417 were more likely to divert. Also, travelers who stated that they would divert in the case of abnormal travel times displayed on DMS or stated that a DMS influenced their response to congestion showed a higher likelihood of diversion. These two variables were added between the pre and post-deployment surveys. It is also beneficial to note that travelers who stated they would divert in a fictitious congestion situation of at least 30 minutes of delay were more likely to divert. This shows that they do not contradict themselves in their responses to Revealed Preference and Stated Preference diversion situations. Based on a comparison between pre and post-deployment models containing similar variables, commuters were more likely to stay on the toll road everything else being equal to the base case. Also, it was shown that in the post-deployment model the respondents traveling on SR 408 and SR 417 were more likely to divert, but in the pre-deployment model only the respondents traveling on SR 408 were more likely to divert. This is an expected result since during the pre-deployment survey only one DMS was located on SR 408, and during the post-deployment survey there were DMS located on all toll roads. Also, an interesting result to be noted is that in the post-deployment survey, commuters who paid tolls with E-pass were more likely to stay on the toll road than commuters who paid tolls with cash. The implications for implementation of these results are discussed in this thesis. DMS should be formatted as a flashing message for abnormal traffic situations and the state road number should be used to identify a roadway. DMS messages should pertain to information on roadway hazards when necessary because it was found that travelers find it important to be informed on events that are related to their personal safety. The travel time accuracy on DMS was shown to be significant for traveler information satisfaction because if the travelers observe inaccurate travel times on DMS, they may not trust the validity of future messages. Finally, it is important to meet the travelers' preferences and concerns for DMS.

Alzheimer's Disease (AD) affects nearly 5.4 million Americans as of 2016 and is the most common form of dementia. The disease is characterized by the presence of neurofibrillary tangles and amyloid plaques [1]. The amount of plaques are measured by Braak stage, post-mortem. It is known that AD is positively associated with hypercholesterolemia [16]. As statins are the most widely used cholesterol-lowering drug, there may be associations between statin use and AD. We hypothesize that those who use statins, specifically lipophilic statins, are more likely to have a low Braak stage in post-mortem analysis. In order to address this hypothesis, we wished to fit a regression model for ordinal outcomes (e.g., high, moderate, or low Braak stage) using data collected from the National Alzheimer's Coordinating Center (NACC) autopsy cohort. As the outcomes were matched on the length of follow-up, a conditional likelihood-based method is often used to estimate the regression coefficients. However, it can be challenging to solve the conditional-likelihood based estimating equation numerically, especially when there are many matching strata. Given that the likelihood of a conditional logistic regression model is equivalent to the partial likelihood from a stratified Cox proportional hazard model, the existing R function for a Cox model, coxph( ), can be used for estimation of a conditional logistic regression model. We would like to investigate whether this strategy could be extended to a regression model for ordinal outcomes. More specifically, our aims are to (1) demonstrate the equivalence between the exact partial likelihood of a stratified discrete time Cox proportional hazards model and the likelihood of a conditional logistic regression model, (2) prove equivalence, or lack there-of, between the exact partial likelihood of a stratified discrete time Cox proportional hazards model and the conditional likelihood of models appropriate for multiple ordinal outcomes: an adjacent categories model, a continuation-ratio model, and a cumulative logit model, and (3) clarify how to set up stratified discrete time Cox proportional hazards model for multiple ordinal outcomes with matching using the existing coxph( ) R function and interpret the regression coefficient estimates that result. We verified this theoretical proof through simulation studies. We simulated data from the three models of interest: an adjacent categories model, a continuation-ratio model, and a cumulative logit model. We fit a Cox model using the existing coxph( ) R function to the simulated data produced by each model. We then compared the coefficient estimates obtained. Lastly, we fit a Cox model to the NACC dataset. We used Braak stage as the outcome variables, having three ordinal categories. We included predictors for age at death, sex, genotype, education, comorbidities, number of days having taken lipophilic statins, number of days having taken hydrophilic statins, and time to death. We matched cases to controls on the length of follow up. We have discussed all findings and their implications in detail.

No description available.

The hospitality industry has experienced significant changes in its competitive environment over the past 30 years, driven by the growth of alternative accommodations, the widespread use of the internet for searching and booking accommodations, and the adoption of asset-light business models. In this new competitive landscape, hospitality firms struggle to gain a competitive advantage, particularly as they lack rare and inimitable resources, which are considered crucial for achieving competitive advantage according to resource-based view literature. This dissertation explores three sets of strategies that enable hotel firms to attain a competitive edge despite their resources being non-rare and easily imitated by competitors. The first essay examines the potential for hotel firms to benefit from competitors' resources by co-locating with them. Although this strategy has been widely studied in organizational research, recent developments in the competitive market, such as internet adoption and the growth of short-term leases, have not been considered. Evidence suggests that internet adoption decreases the likelihood of low-level hotels entering markets with high-level hotels and negatively moderates the positive effect of branded hotels on independent hotels' performance, as well as nullifying the effect of low-level hotels on high-level hotels' performance. Additionally, short-term leases impact hotels' decisions and performance, as hotels tend to avoid co-locating with short-term leases with similar price points, and short-term leases can appropriate positive agglomeration externalities created by high-level hotels. The second essay investigates whether hotels can outperform competitors by gaining an advantage in resource appropriation through entering the market with a dual-branded hotel. Results indicate that a competitive advantage is achieved when at least one brand in the composition possesses better resources than competitors. Lastly, the third essay concentrates on the potential for hotels to leverage tacit knowledge transmission to increase the difficulty for competitors to imitate them. Findings reveal that the closer a hotel or short-term lease is to the nearest accommodation managed by the same hotel management company or host, the higher the chances of achieving a competitive advantage. Moreover, short-term leases can base their competitive advantage on idiosyncratic knowledge transferred from the platform, and they can compete in size with incumbent hotels if they have a high concentration of ownership in the market. / Doctor of Philosophy / The lodging industry has undergone numerous changes in the past 30 years, with the widespread adoption of the internet, the growth of the short-term lease market, and the implementation of asset-light strategies significantly impacting how hotels compete locally. This dissertation examines various market-entry strategies that can enable hotel firms to achieve a competitive advantage in local markets. The first essay explores the advantages of co-locating with competitors. Results indicate that previously identified benefits, such as reduced search costs for customers leading to higher performance for clustered competitors, have been diminished or nullified by the extensive use of the internet for searching and booking hotels. Independent hotels may still gain agglomeration advantages by co-locating with branded hotels, but the benefits are substantially reduced due to internet usage. Furthermore, the presence of different levels of short-term leases in the market affects hotels' entry patterns, which tend to diverge from short-term leases. Additionally, low-level short-term leases tend to capture agglomeration benefits created by high-level hotels, resulting in decreased performance for low-level hotels. The second essay investigates the optimal strategy for entering the market with a dual-branded hotel. Results show that, overall, adopting a vertically diversified strategy (i.e., where one of the two brands in the composition is of a higher class compared to the other) is preferable, with the higher class above the market's average class and the lower class below it. Conversely, the least effective strategy is to adopt a vertically diversified approach where both brands are below the market's average class. The third essay examines knowledge sharing among hotels and short-term leases managed by the same hotel management company or short-term lease host. Findings suggest that accommodations should be located near other properties managed by the same entity to facilitate operating knowledge transmission through face-to-face interactions, coordination among units, and the easy transfer of key personnel. Additionally, the study found that hotels should carefully consider entering a market with a high concentration of short-term lease ownership, as a higher concentration of short-term leases owned by the same host leads to lower hotels' RevPAR in the market.

<p dir="ltr">The objective of this research was to evaluate the impact of salespeople’s characteristics on their sales process. A cluster analysis procedure was used to develop a segmentation of business-to-business salespeople. The segments were developed by seven variables that describe the percentage of time salespeople spend on specific selling activities: prospecting, building trust/ relationship, probing, presenting products/ services, handling objections, negotiating/ obtaining commitment, and service/ follow-up.  The result indicated the presence of three clusters: customer-focused, sales-focused, and balance segments.  Differences across these segments have essential implications on the choice of sales strategy. </p>

Land is a major factor in agricultural production, so agricultural land allocated to smallholder farmers through Land Reform Program or by traditional leader need to be actively utilised for enhancement of agricultural business. The study assessed land utilisation by small and emerging farmers in the Greater Tzaneen Municipality. Data was collected from 86 farms and analysed using SPSS Version 23. The results indicate that 74% of the farmers fully utilised their farm lands. Results of Logit model revealed that, the amount received from leasing, value adding to products, annual farm income and savings had positive significant impact on the area of cultivation, while skills pertaining to farming activities and the proportion of farm inputs purchased with the farmer’s own money had negative impact. The significant variables should be considered to influence full farmland utilisation by small and emerging farmers in the study area; farmers need production inputs, affordable loans and other forms of funding to improve farmland utilisation / Agriculture, Animal Health and Human Ecology / M. Sc. (Agriculture)

本論文主要目地是在研究財務比率對上市公司發生下市事件之預測。我們運用歷史事件研究法和Cox迴歸模型去研究上市公司發生下市事件之原因。同時，我們也針對Cox迴歸模型和Logit模型在發現對下市事件有顯著影響的財務比率作比較。 / This study applies the event history analysis and the Cox regression model to examine the causes of firm delisting, and also compares the performance of the Cox regression model with that of the logit model in detecting factors that have a statistically significant impact on the delisting event. The empirical results show that the hazard rate of firm delisting increases with the ratio of current liabilities to current assets, a binary variable indicating if the total liabilities of a firm is greater than its total assets, and a binary variable indicating if the net income of a firm was negative for the last two quarters, while the hazard rate of firm delisting decreases with increases in the firm size and the ratio of funds provided by operations to total liabilities.