The presence of substitution among multiple similar products plays an important role in inventory management. It has been observed in the literature that incorporating the impact of substitution among products can substantially improve the profit and reduce the understock or overstock risk. This thesis focuses on exploring and exploiting the impact of substitution on inventory management problems by theoretically analyzing mathematical models and developing efficient solution approaches. To that end, we address four problems. In the first problem, we study different pricing strategies and the role of substitution for new and remanufactured products. Our work presents a two-stage model for an original equipment manufacturer (OEM) in this regard. A closed-form one-to-one mapping of product designs onto the optimal product strategies is developed, which provides useful information for the retailer. Our second problem is a multi-product newsvendor problem with customer-driven demand substitution. We completely characterize the optimal order policy when the demand is known and reformulate this nonconvex problem as a binary quadratic program. When the demand is stochastic, we formulate the problem as a two-stage stochastic program with mixed integer recourse, derive several necessary optimality conditions, prove the submodularity of the profit function, develop polynomial-time approximation algorithms, and show their performance guarantees. Our numerical investigation demonstrates the effectiveness of the proposed algorithms and, furthermore, reveals several useful findings and managerial insights. In the third problem, we study a robust multi-product newsvendor model with substitution (R-MNMS), where both demand and substitution rates are uncertain and are subject to cardinality-constrained uncertainty set. We show that for given order quantities, computing the worst-case total profit, in general, is NP-hard, and therefore, address three special cases for which we provide closed-form solutions. In practice, placing an order might incur a fixed cost. Motivated by this fact, our fourth problem extends the R-MNMS by incorporating fixed cost (denoted as R-MNMSF) and develop efficient approaches for its solution. In particular, we propose an exact branch-and-cut algorithm to solve small- or medium-sized problem instances of the R-MNMSF, and for large-scale problem instances, we develop an approximation algorithm. We further study the effects of the fixed cost and show how to tune the parameters of the uncertainty set. / Doctor of Philosophy / In a multi-product supply chain, the substitution of products arises if a customer's first-choice product is out-of-stock, and she/he have to turn to buy another similar product. It has been shown in the literature that the presence of product substitution reduces the assortment size, and thus, brings in more profit. %and reduce the inventory level. However, how to quantitatively study and analyze substitution effects has not been addressed in the literature. This thesis fills this gap by developing and analyzing the profit model, and therefore, providing judicious decisions for the retailer to make in order to maximize their profit. In our first problem, we consider substitution between new products and remanufactured products. We provide closed-form solutions, and a mapping that can help the retailer in choosing optimal prices and end-of-life options given a certain product design. In our second problem, we study multi-product newsvendor model with substitution. We first show that, when the probability distribution of customers' demand is known, we can tightly approximate the proposed model as a stochastic integer program under discrete support. Next, we provide effective solution approaches to solve the multi-product newsvendor model with substitution. In practice, typically, there is a limited information available on the customers' demand or substitution rates, and therefore, for our third problem, we study a robust model with a cardinality uncertainty set to account for these stochastic demand and substitution rates. We give closed-form solutions for the following three special cases: (1) there are only two products, (2) there is no substitution among different products, and (3) the budget of uncertainty is equal to the number of products. Finally, similar to many inventory management problems, we include a fixed cost in the robust model and develop efficient approaches for its solution. The numerical study demonstrates the effectiveness of the proposed methods and the robustness of our model. We further illustrate the effects of the fixed cost and how to tune the parameters of the uncertainty set.

In a world where calls for climate action grow louder by the day, the role of renewable energy and energy efficient generation sources has become extremely important. One such energy efficient resource that can increase the penetration of renewable energy into the grid is the Combined Heat and Power technology. Combined Heat and Power (CHP) plants produce useful thermal and electrical power output from a single input fuel source and are widely used in the industrial and commercial sectors for reliable on-site power production. However, several unfavorable policies combined with inconsistent regulations have discouraged investments in this technology and reduced participation of such facilities in grid operations. The potential benefits that could be offered by this technology are numerous - improving grid resiliency during emergencies, deferring transmission system updates and reducing toxic emissions, to name a few. With increased share of renewable energy sources in the generation mix, there is a pressing need for reliable base generation that can meet the grid requirements without contributing negatively to the environment. Since CHP units are good candidates to help achieve this two-fold requirement, it is important to understand the present barriers to their deployment and grid involvement. In this thesis work, we explore some of these challenges and propose suitable grid integration technology as well as market participation approaches for better involvement of distributed CHP units in the industrial and commercial sectors. / Master of Science / Combined Heat and Power is a generation technology which uses a single fuel source to produce two useful outputs - electric power and thermal energy - by capturing and reusing the exhaust steam by-product. These generating units have much higher efficiencies than conventional power plants, lower fuel emissions and have been a popular choice among several industries and commercial buildings with a need for uninterrupted heat and power. With increasing calls for climate action and large scale deployment of renewable based energy generation sources, there is a higher need for reliable base-line generation which can handle the fluctuations and uncertainty of such renewables. This need can be met by CHP units owing to their geographic distribution and their high operating duration. CHPs also provide a myriad of other benefits for the grid operators and environmental benefits, compared to the conventional generators. However, unfavorable and inconsistent regulatory procedures have discouraged these facility owners from actively engaging in providing grid services. Therefore, it is imperative to look into some of the existing policies and understand where the changes and incentives need to be made. In this work, we look into methods that can ease CHP integration from a technological and an economic point of view, with the aim of encouraging grid operators and CHP owners to be more active participants.

Despite declining rates since the 1980s, HIV remains a significant public health concern in the US, especially among ethnic and sexual minorities, as well as other marginalized groups. This present dissertation addresses this challenge by using simulated markets to investigate the potential acceptance of HIV vaccines among at-risk population groups in the US. Four experiments were conducted to explore various factors influencing vaccine acceptance. Experiment 1 investigated the impact of vaccine-dependent factors, such as perceived dosage and mode of administration, on HIV vaccine demand. Experiment 2 assessed the effect of cost on the discounting of delayed but effective HIV vaccines. Experiment 3 examined the influence of cost on the discounting of uncertain but effective HIV vaccines. Experiment 4 explored how bundling HIV vaccines with complementary health commodities could enhance vaccine demand. The findings revealed that mucosal administration and a single-dose regimen had the most significant impact on vaccine demand. Additionally, the requirement to pay for vaccines led to more pronounced discounting of both delayed and uncertain vaccines, compared to when they were offered for free. Among the various health commodities examined, eye examinations and mental health counseling had the most significant impact on HIV vaccine demand when bundled. The dissertation also examined the effect of personal and interpersonal covariates on HIV vaccine acceptance. These findings aim to inform public health interventions and policy formulation regarding HIV vaccines, anticipating their widespread availability both in the US and globally.

The Swedish electricity market has seen a surge in demand over the past fifty years. Since the deregulation in 1996, both the demand and supply side of the market has evolved into a competitive space for market actors. This has resulted in unique conditions, characterizing the nordic electricity market as being very much dependent on demand predictability. Demand flexibility has been investigated frequently, but as certain sector developments constantly affect electricity consumption, such as price volatility and green technology development, the price- and temperature elasticities should be revised continuously. Hourly-price contracts specifically, are on the rise in price area SE1, with a rise from 6 percent to 8 percent during the middle of 2023, meaning consumption patterns are of interest for the future as the trend continues. This has, to the authors’ knowledge, not been investigated within the municipality of Luleå, which is the basis for this master’s thesis. Two methodologies were adopted to investigate the elasticities, (1) an ordinary least squares (OLS) regression model and (2) two weighted least squares (WLS) regression models. The results indicate that the price elasticity of demand in Luleå is still very inelastic, with temperature bearing the main explanatory power for household electricity consumption patterns.

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Women often experience having to stand in line in order to use public restrooms. The primary purpose of this exploratory study was to determine the number and types of activities performed in the restroom, along with the amount of time spent in the restroom, as these factors might influence the revision of plumbing codes and the design of public restrooms. Data were collected by a self administered questionnaire at four sites--an airport, highway rest area, sports arena, and conference center. The subjects were also timed. The sample consisted of 230 male and 224 female respondents. Males and females were similar in the types of activities performed in the restroom. Urination, washing hands, and checking appearance were the three activities performed most frequently by both genders. Females were more likely to have to stand in line to use the restroom than males, though the wait was usually fewer than five minutes. At two of the sites, airport and sports arena, females, on an average, performed more activities than males. At all four sites, females spent a significantly greater amount of time in the restroom than did males. For female respondents the mean time ranged from 152.5 seconds (sports arena) to 180.6 seconds (rest area). For male respondents the mean time ranged from 83.6 seconds (sports arena) to 112.5 seconds (airport). There was no significant relationship between age and the amount of time spent in the restroom, for either gender at any of the four sites. The results from two sites, however, showed a slight trend toward older people spending more time in the restroom. There was no clear pattern with regard to explaining the relationship between the amount of time spent in the restroom and the number of activities performed. For males only, there were significant differences among the four sites and the amount of time spent in the restroom. For both males and females, there were significant differences between number of activities performed and site. This research indicates that females need a greater number of elimination fixtures than do males, and that revision of plumbing codes, based on further research, is needed. / Ph. D.

The adoption of Electric Vehicles (EVs) represents a transformative change in the automotive industry. As more households make the transition to EVs, the traditional dependence on fossil fuels for transportation is being replaced by electricity as the primary energy source. This transition has the potential to increase the electricity consumption within households as well as the demand on the power grids. To maximize the environmental and economic benefits of EV adoption, strategies regarding efficient energy management, integration of renewable energy source, and grid capacity are becoming essential considerations. The current dissertation research is motivated toward evaluating the adoption of EV and its impact on the US household’s energy demand. In pursuit of these goals, this research has made several contributions. First, we proposed an econometric framework to estimate the factors influencing customers’ vehicle purchase decisions. Second, a comparative analysis is conducted between two econometric frameworks –panel mixed random utility maximization MNL model and panel mixed random regret minimization MNL model to estimate the evolving landscape of EV adoption over time. Third, we employed an advanced econometric framework- Multiple Discrete Continuous Extreme Value (MDCEV) model– to evaluate the factors that influence the energy consumption profile of various household end-uses along with their alternating trends over time. Fourth, we employed a novel fusion approach to the MDCEV model to assess the impact of travel behavior along with several household socioeconomic characteristics on various energy end-uses. Finally, by predicting household EV ownership, projections of total household energy demand for the city of Atlanta for the years 2030, 2040 and 2050 are performed. A set of independent variables including vehicle attributes, socio-economic attributes, travel behavior-related attributes, dwelling attributes, appliance-use related attributes, and climate-related attributes from various data sources are employed in this study. The research concludes with an analysis of different policy implications.

Yes / Based on their study of the food distribution supply chain, Can Eksoz and Dilek Önkal argue that the distributor has largely been overlooked in the principles we’ve created for collaborative demand and supply planning. Their article re-inserts the distributor into the supply chain and examines the challenges of collaboration from the distributor’s vantage point. This is a good lesson in how collaborative agreements must address the particular structures of the supply chain as well as the markets in which the supply-chain partners operate.

Yes / Measures to manage demand include implicit and explicit messages about domestic water-users which have important potential impacts on their perceptions and practices. Drawing on recent literature, this paper identifies three different ¿dimensions¿ along which demand management measures¿ constructions of the water-user may vary: these relate to whether the water user is passive or active, whether they are motivated by individual or common needs, and whether they perceive water as a right or a commodity. Demand management measures currently used in England and Wales are then discussed and analysed. The paper concludes by highlighting the importance of communications associated with demand management, and in particular, notes the need to consider the cumulative impact of messages and their interactions with people¿s existing understandings.

Thirty-six drivers of both genders from three different age groups performed auditory cognitive tasks while driving an instrumented vehicle. The tasks were of two types. The first type of task was the selection of a driving route from a list presented as a recorded sound. These tasks represented the use of In-Vehicle Information Systems (IVIS). The second type of task consisted of a conversation like series of questions designed to replicate the use of a cellular telephone while driving. The IVIS tasks consisted of two levels of information density (short-term memory load) and four element types (complexity levels) including listening, interpretation, planning, and computation. The effects of age, information density, and element type on driving performance were assessed using a composite set of performance measures. Primary measures of driving performance included lateral tracking, longitudinal control and eye glances. Secondary task performance was assessed by task completion time, skipped tasks and task errors. Additionally, subjective assessment was done using a situational awareness probe question and a modified NASA-TLX question set. Results showed that drivers demonstrated a general decrease in their ability to maintain their lateral position with increased task complexity. Additionally, speed and following distance were less stable during tasks. During tasks, drivers glanced less at their mirrors and instruments and left their lane more often than during baseline driving periods. Even during difficult tasks, drivers had high self-confidence in their awareness of surroundings. One result of particular interest was an increase in lane deviations and headway variance coupled with increased forward eye glance durations. It is believed that this is evidence of a condition called "Cognitive Capture" in which a driver, though looking more extensively at the forward roadway, is having difficulty tracking the lead vehicle and lane position. High cognitive load is causing the driver to disregard or shed visual information to allow processing of auditory task-related information. Another result of concern is the inability of drivers to assess their own impairment while performing in vehicle tasks. During tasks drivers demonstrated reduced scanning of mirrors and vehicle instrumentation. This clearly demonstrates reduced situational awareness. Additionally, during tasks lane tracking and headway maintenance performance decreased as well. However, during all tasks drivers assessed their workload higher than baseline driving even though they rated it near the bottom of the scale. Also, drivers perceived no decrease in their situational awareness. The results of this study show that driving performance can be negatively impacted by even fairly simple cognitive tasks while a driver is looking at the road with their hands on the wheel. Even while viewing the road, a driver may perform an auditory task and be cognitively overloaded to the point of safety concerns. An additional concern is that drivers underestimate the degree of their cognitive load and its impact on their driving performance. / Master of Science