Advanced Econometic Models for Modeling Flows: Application to Shared Economy

Travel and tourism industry is undergoing transformation with the flourishing of online sharing economy marketplaces such as Bike Share services, Uber/Lyft (for taxi services), Eatwith (for community restaurants), and AirBnB (for accommodation). The current research effort contributes to literature on sharing economy service flow analysis by formulating and estiamting econometric approaches for analyzing frequency variables. The sharing economy alternatives investigated include: (a) accommodation service (AirBnB), (b) bikeshare service (Citi bike, NYC) and (c) ride hailing service (UBER/LYFT/Taxi). In the first part of the dissertation, we develop a copula based negative binomial count model framework to count AirBnB listings at census tract level to capture the snapshot of accommodation supply for tourists in NYC. In the second part, considering bike sharing as one of the transportation sharing systems, the dissertation identifies two choice dimensions for capturing the bike share system demand: (1) station level demand and (2) how bike flows from an origin station are distributed across the network. In the third part of the dissertation on ride sharing systems, we identify two choice dimensions: a demand component that estimates origin level transportation newtwork company (TNC) demand at the taxi zone level and (2) a distribution component that analyzes how these trips from an origin are distributed across the region. A linear mixed model is considered to estimate station or taxi zone level demand while a multiple discrete continuous extreme value (MDCEV) model to analyze flows distribution is employed. In the final part of this dissertation, we develop an innovative joint econometric model system to examine two components of the rapid ride share market transformation: (a) the increase in ride hailing demand and (b) the shift from traditional taxi services to TNC services. The first component is analyzed adopting a negative binomial (NB) count model while the second component is analyzed using a multinomial fractional split (MNLFS) model

Accommodating Exogenous Variable and Decision Rule Heterogeneity in Discrete Choice Models: Application to Bicyclist Route Choice

The thesis contributes to our understanding of incorporating heterogeneity in discrete choice models with respect to exogenous variables and decision rules. Specifically, we evaluate latent segmentation based mixed models that allow for segmenting population based on decision rules while also incorporating unobserved heterogeneity within the segment level decision rule models. In our analysis, we choose to consider the random utility framework along with random regret minimization approach. Further, instead of assuming the number of segments (as 2), we conduct an exhaustive exploration with multiple segments across the two decision rules. Within each segment we also allow for unobserved heterogeneity. The model estimation is conducted using a stated preference data from 695 commuter cyclists compiled through a web-based survey. The probabilistic allocation of respondents to different segments indicates that female commuter cyclists are more utility oriented, however the majority of the commuter cyclist\u27s choice pattern is consistent with regret minimization mechanism. Overall, cyclists\u27 route choice decisions are influenced by roadway attributes, cycling infrastructure availability, pollution exposure, and travel time. The analysis approach also allows us to investigate time based trade-offs across cyclists of different classes. Interestingly, we observed that the trade-off values in regret and utility based segments for roadway attributes are similar in magnitude; but the values differ greatly for cycling infrastructure and exposure attributes, particularly for maximum exposure levels

Possible fluid interpretation and tidal force equation on a generic null hypersurface in Einstein-Cartan theory

The dynamical evolution of the Hajicek $1$-form is derived in Einstein-Cartan (EC) theory. We find that like Einstein theory of gravity, the evolution equation is related to a projected part of the Einstein tensor $(\hat{G}_{ab})$ on a generic null surface $\mathcal{H}$, particularly $\hat{G}_{ab}l^a q^b_{~c}$, where $l^a$ and $q^a_{~c}$ are the outgoing null generators of $\mathcal{H}$ and the induced metric to a transverse spatial cross-section of $\mathcal{H}$ respectively. Under the {\it geodesic constraint} a possible fluid interpretation of this evolution equation is then proposed. We find that it has the structure which is reminiscent to the {\it Cosserat generalization} of the Navier-Stokes fluid provided we express the dynamical evolution equation of the Hajicek $1$-form in a set of coordinates adapted to $\mathcal{H}$ and in a local inertial frame. An analogous viewpoint can also be built under the motive that the usual material derivative for fluids should be replaced by the Lie derivative. Finally, the tidal force equation in EC theory on the null surface is also derived.Comment: Published in Phys. Rev.

TOPSIS for Single Valued Neutrosophic Soft Expert Set Based Multi-attribute Decision Making Problems

In the paper, we propose Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique for solving single valued neutrosophic soft set expert based multi-attribute decision making problems. Single valued neutrosophic soft expert sets are combination of single valued neutrosophic sets and soft expert sets. In the decision making process, the ratings of alternatives with respect to the parameters are expressed in terms of single valued neutrosophic soft expert sets to deal with imprecise or vague information. The unknown weights of the parameters are derived from maximizing deviation method. Then, we determine the rank of the alternatives and choose the best one by using TOPSIS method. Finally, a numerical example for teacher selection is presented to demonstrate the applicability and effectiveness of the proposed approach

An extended TOPSIS for multi-attribute decision making problems with neutrosophic cubic information

The paper proposes a new technique for dealing with multi-attribute decision making problems through an extended TOPSIS method under neutrosophic cubic environment. Neutrosophic cubic set is the generalized form of cubic set and is the hybridization of a neutrosophic set with an interval neutrosophic set. In this study, we have defined some operation rules for neutrosophic cubic sets and proposed the Euclidean distance between neutrosophic cubic sets. In the decision making situation, the rating of alternatives with respect to some predefined attributes are presented in terms of neutrosophic cubic information where weights of the attributes are completely unknown. In the selection process, neutrosophic cubic positive and negative ideal solutions have been defined. An extended TOPSIS method is then proposed for ranking the alternatives and finally choosing the best one. Lastly, an illustrative example is solved to demonstrate the decision making procedure and effectiveness of the developed approach

Bipolar Neutrosophic Projection Based Models for Solving Multi-Attribute Decision-Making Problems

Bipolar neutrosophic sets are the extension of neutrosophic sets and are based on the idea of positive and negative preferences of information. Projection measure is a useful apparatus for modelling real life decision making problems. In the paper, we define projection, bidirectional projection and hybrid projection measures between bipolar neutrosophic sets. Three new methods based on the proposed projection measures are developed for solving multi-attribute decision making problems. In the solution process, the ratings of performance values of the alternatives with respect to the attributes are expressed in terms of bipolar neutrosophic values. We calculate projection, bidirectional projection, and hybrid projection measures between each alternative and ideal alternative with bipolar neutrosophic information. All the alternatives are ranked to identify the best alternative. Finally, a numerical example is provided to demonstrate the applicability and effectiveness of the developed methods. Comparison analysis with the existing methods in the literature in bipolar neutrosophic environment is also performed