This study presents a rigorous exploration of the effects of single versus multiple M&A deals on the performance of acquiring firms. A pooled ordinary least squares (OLS) regression analysis was employed to examine our key performance indicators: Value at Risk (VaR), Value of Return (VoR), and Returns across year, month, and week time frames. Findings reveal that multiple M&A deals can enhance stock performance and VoR, while also increasing VaR, indicating higher potential for downside risk. This research enriches the M&A literature by focusing on the differential impacts of single and multiple acquisitions on these crucial financial metrics. Its insights guide firms and investors in understanding the delicate interplay between the number of acquisitions, prospective gains, and related risks.

This thesis investigates Swedish market reactions to CEO turnover and further studies how the size of these market reactions can be explained by company specific and CEO specific factors. Through t-tests and multivariate analysis this study analyses 136 CEO turnover announcements from the years 2017-2022 to find proof of a market reaction and to find potential explanations to the size of these market reactions. The results of this study show that the Swedish market on average reacts positively to CEO turnover announcements regarding the studied firms abnormal return and cumulative abnormal return, which shows that CEO turnover announcements contain useful information for investors. Our study finds indications of differences market reactions size of CEO turnover announcements between small and big firms and differences in market reaction regarding the experience level of the appointed CEO. Our study also found that a company's ROA, M/B, and their appointed CEO's experience level influence the size of these market reactions. As the market reactions due to CEO turnover often occurred the days before the CEO turnover announcement, this study's also found indications of potential insider information leakage within Swedish firms.

Current return-to-drive recommendations for patients following rotator cuff repair (RCR) surgery are not uniform due to a lack of empirical evidence relating driving safety and time-after-surgery. To address the limitations of previous work, Badger et al. (2022) evaluated, on public roads, the driving fitness of patients prior to RCR and at multiple post-operative timepoints. The goal of the Badger, et al. study was to make evidence-based return-to-drive recommendations in an environment with higher fidelity than that of a simulator and not subject to biases inherent to surveys. Badger et al., however, do not fully investigate the driving practices exhibited by subjects, overlooking the potential presence of compensatory driver behaviors. Further investigation of these behaviors through observation of direct driving techniques and practices over time can specifically answer how drivers may modify their behaviors to address a perceived state of impairment. Additionally, the degree of success in vehicle operation by comparing an ideal turn to the path taken by the driver allows for a level of quantification of the effectiveness of the compensatory techniques. Moreover, driver trajectories inferred from the vehicle Controller Area Network (CAN) metrics and from global positioning system (GPS) coordinates are contrasted with the ideal turn to assess minimum requirements for future sensors that are used to make these trajectory comparisons. This investigation leverages pre-existing data collected by the Virginia Tech Transportation Institute (VTTI) and Carilion Clinic as used in the analysis performed by Badger et al. (2022). RCR patients (n=27) executed the same prescribed driving maneuvers and drove the same route in a preoperative state and at 2-, 4-, 6-, and 12-weeks post operation. Behavioral data were annotated to extract key characteristics of interest and related them to relevant vehicle sensor readings. To construct vehicle paths, data was obtained from the on-board data acquisition system (DAS). Behavioral metrics considered the use of ipsilateral vehicle controls, performance of non-primary vehicle tasks, and steering techniques utilized to assess the impact of mobility restrictions due to sling use. Sling use was found to be a significant factor in use of the non-ipsilateral hand associated with the operative extremity (i.e., operative hand) on vehicle functions and, in particular, difficulty with the gear shifting control. Additionally, when considering the performance of non-primary vehicle tasks as assessed through a prescribed visor manipulation, sling use was not a significant factor for the task duration or completion of the task in a fluid motion. Sling use was, however, significant with respect to operative hand position prior to the completion of the visor manipulation: the operative hand was often not on the steering wheel prior to the visor maneuver. In addition, the operative hand was never used to manipulate the visor when the sling was worn. One-handed steering was also more frequent with the presence of the sling. Further behavioral analysis assessed the presence of compensatory behavior exhibited by subjects during periods in which impairment was perceived. Perceived impairment was observed as a function of the different experimental timepoints. Findings indicated a significant decrease in the lateral vehicle jerk during post-operative weeks 6 and 12. Significant differences, however, were not observed in body position alteration to avoid contact with the interior vehicle cabin, in over-the-shoulder checks, and in forward leans during yield and merge maneuvers. Regarding trajectory analysis, sling use did not produce a significant difference in the error metrics between the actual and ideal paths. In completion of turning maneuvers, however, operative extremity was significant for left turns, with greater error against the ideal path observed from those in the left operative cohort compared to those in the right operative cohort. For the right turn, however, operative extremity was not found to be a significant factor. In addition, the GPS data accuracy proved insufficient to support comparison against the ideal path. Overall, findings from this study provide metrics beyond those used in Badger, et al. that can be used in answering when it is safe for rotator cuff repair patients to return-to-drive. With the limited differences observed as a function of study timepoint and sling use, it is recommended that patients are able to safely return-to-drive at two weeks post-operation. If anything, results suggest that overcompensation, as inferred from observation of safer driving behaviors than normal, is present during some experimental timepoints, particularly post-operative week 2. / Master of Science / Current recommendations based on when it is safe for rotator cuff repair patients to return-to-drive are not standard because of a lack of suitable evidence. Previous work and recommendations rely on surveys and simulators which do not create fully realistic conditions and are subject to biases. To address the limitations of previous work, Badger et. al (2022) studied actual rotator cuff repair patients on public roads prior and following operation at multiple timepoints. Badger et al., however, did not consider the potential adaptations in driver behavior due to mobility restrictions and the perception of inferiority due to injury. Additionally, the degree of success of the adaptive driving behaviors based on the error between the actual vehicle path taken and a defined ideal path have not been explored in conjunction with the injury. This investigation is based on the pre-existing data collected by the Virginia Tech Transportation Institute (VTTI) and Carilion Clinic as used in the analysis performed by Badger et al. (2022). RCR patients (n=27) executed identical driving maneuvers and drove the same route before operation and at 2-, 4-, 6-, and 12-weeks post operation. Behavioral observations were recorded and related to relevant vehicle sensor readings. To construct vehicle paths, data was taken from the on-board data acquisition system (DAS). Participants adopted different behaviors, such as using the right hand to use the turn signal when the left arm was in a sling and the left hand to operate the gear shifter when the right arm was on a sling, to assist in combating mobility restrictions. One-handed steering was also more prominent during periods of sling-use. Sling-use, however, did not produce a significant difference in error between the actual vehicle path taken and the ideal path available to the driver. For left-operated participants completing left turns, there was also greater error in comparison to the ideal path than for the group of right-operated patients. However, there was not a difference between left- and right-operated arm participant error in completion of a right turn. The GPS data did not provide a suitable approximation of vehicle trajectory. Overall, findings from this study help to answer when it is safe for rotator cuff repair patients to return-to-drive through evaluation of the effectiveness of compensatory behaviors adopted by participants. With no significant difference in turn execution based on sling use, results suggest that patients can safely return-to-drive at two weeks post-operation. In fact, results suggest that overcompensation towards safer behaviors is present during some experimental timepoints, particularly post-operative week 2.

Software systems are becoming increasingly bloated to accommodate a wide array of features, platforms and users. This results not only in wastage of memory but also in an increase in their attack surface. Existing works broadly use binary-rewriting techniques to remove unused code, but this results in a binary that is highly customized for a given usage context. If the usage scenario of the binary changes, the binary has to be regenerated. We present DYNACUT– a framework for Dynamic and Adaptive Code Customization. DYNACUT provides the user with the capability to customize the application to changing usage scenarios at runtime without the need for the source code. DYNACUT achieves this customization by leveraging two techniques: 1) identifying the code to be removed by using execution traces of the application and 2) by rewriting the process dynamically. The first technique uses traces of the wanted features and the unwanted features of the application and generates their diffs to identify the features to be removed. The second technique modifies the process image to add traps and fault-handling code to remove vulnerable but unused code. DYNACUT can also disable temporally unused code – code that is used only during the initialization phase of the application. To demonstrate its effectiveness, we built a prototype of DYNACUT and evaluated it on 9 real-world applications including NGINX, Lighttpd and 7 applications of the SPEC Intspeed benchmark suite. DYNACUT removes upto 56% of executed basic blocks and upto 10% of the application code when used to remove initialization code. The total overhead is in the range of 1.63 seconds for Lighttpd, 4.83 seconds for NGINX and about 39 seconds for perlbench in the SPEC suite. / Master of Science / Software systems are becoming increasingly bloated to accommodate a wide array of users, features and platforms. This results in the software not only occupying extra space on com- puting platforms but also in an increase in the ways that the applications can be exploited by hackers. Current works broadly use a variety of techniques to identify and remove this type of vulnerable and unused code. But, these approaches result in a software that has to be modified with the changing usage scenarios of the application. We present DYNACUT, a dynamic code customization tool that can customize the application at its runtime with a minimal overhead. We use the execution traces of the application to customize the ap- plication according to user specifications. DYNACUT can identify code that is only used in the initial stages of the application execution (initialization code) and remove them. DYNA- CUT can also disable features of the application. To demonstrate its effectiveness, we built a prototype of DYNACUT and evaluated it on 9 real-world applications including NGINX, Lighttpd and 7 applications of the SPEC Intspeed benchmark suite. DYNACUT removes upto 56% of executed basic blocks and upto 10% of the application code when used to remove initialization code. The total overhead is in the range of 1.63 seconds for Lighttpd, 4.83 seconds for NGINX and about 39 seconds for perlbench in the SPEC suite.

There is qualitative and anecdotal evidence that corporate management deviates from received risk management theory. These deviations include: an overall hesitancy to accept projects with greater levels of total risk, increased return requirements compensating for firm-specific risk, employment of hedging strategies, the insuring of diversifiable risks, corporate diversification outside of the industry constraint, and the utilization of portfolio and other variance reducing methods. The literature primarily contributes these behaviors to principal/agent conflicts. Evidence from studies on these deviations support strong arguments based in resource scarcity, cost and availability of capital, employee/community stability, and the increases in bankruptcy costs that these risk management deviation are in the interest of shareholders. When considered in the context of the long-term impact on value, the observed deviations from received corporate risk management theory contribute substantively to the perpetuation of the firm as a long-term store of value. This paper supports two hypotheses: (1) the deviation from received risk management theory by corporate managers is broadly practiced, and (2) these deviations are generally in the interest of shareholders. / Master of Arts

Unlike most of the existing literature on reverse supply chains, that focuses on product recovery or waste management, in this thesis we consider reverse supply chain operations for an independent retailer. The latter have forward and reverse supply chains that are independent of the manufacturers. We study three major problems related to Retail Reverse Supply Chains (RRSC) for independent retailers. In RRSCs, each retail store holds some products that are not selling (and/or under-selling) and wishes to salvage them optimally. We refer to these products as Ineffective Inventory. Salvage can be in many forms and take place by relocating a product within the reverse supply chain (RSC), such as sending the product from a franchise store back to a Distribution/Return Center (RC) and then forward to another franchise store, or returning it to a vendor, liquidation, etc. The RRSC network may includes system members such as stores (retailer owned and/or franchise), RCs, warehouses, vendors and liquidators. Each of the stores carries some inventory that is underselling, and it is important to reduce the inventory of such products in order to refill the space with inventory that is more likely to sell. In the first problem, we consider a basic RRSC with retail stores, vendors and a warehouse. The retail company allocates a budget for its RRSC activities. We refer to this budget as a Profit-Loss budget, due to lost income from the items that will be removed from the stores that was a part of the gains resulting from the previous year tax calculations. The objective is to use this Profit-Loss budgetary limitation as effectively as possible with the most suitable products to relocate products within the supply chain and/or return them back to their vendor. A heuristic algorithm is developed to solve this problem, by making use of the problem structure, and results are compared with the solutions of an exact state-of-the-art commercial solver. In the second problem, we consider a network optimization model with inventory decisions. The goal is to optimize ineffective inventory levels in stores and the disposition of their returns. We model a comprehensive RRSC network with multiple stores that could be Company-Owned or Franchise Stores, multiple warehouses, multiple RCs, multiple vendors, and liquidators. The objective of the retailer is to minimize costs for relocating some of this ineffective inventory within the network or scrapping. However, individual franchise stores have their own goals of how their excessive inventory should be handled. The franchisee goals may be conflicting with those of the franchisor in terms of how much inventory should be chosen from each store to be relocated. In return, this conflict may lead to a conflict among franchise stores. This issue is addressed and resolved through inventory transparency among all the supply chain members. The tactical decision making process of which RC should be used for handling returns is incorporated into the model. In order to overcome the complexities of the large size problem, a multi-stage heuristic is developed to solve this problem within reasonable times. The results are then compared with the solutions of state-of-the-art commercial solver. In the third problem, we focus on the strategic decision of developing optimal vendor contract parameters for the retailer, using optimization models. Specifically, we identify optimal return penalties and associated return thresholds, between an independent retailer and its vendors. This model will support the retailer in their contract re-negotiation for its RSC activities. Vendors use a multi-layered penalty structure that assigns higher penalties to higher returns. The objective is to find the optimal penalties and/or optimal return thresholds that should be negotiated with the vendors in order to pay a lower penalty in the upcoming return cycles compared to existing penalty structures. We first design a Mixed Integer Non-Linear Program (MINLP) where the model makes the decision of vendor penalty fees and return thresholds simultaneously for each vendor. We generate small size to large size problems and solve them via MINLP solvers such as DICOPT and ANTIGONE. In order to gain insights to the inner workings of the MINLP, the decision variables, vendor penalty fees and return thresholds, are considered as parameters and hence, two models are designed to find the optimal penalty structure and optimal return thresholds, respectively. Useful insights from both of the models’ solutions are derived in order to generate rule-of-thumb methodologies to find approximate solutions close to optimal penalty percentages and return thresholds via identifying all possible scenarios that can exist in the problem structure. / Thesis / Doctor of Philosophy (PhD) / This thesis deals with Retail Reverse Supply Chain (RRSC) management. We consider an independent retail company's and its franchise stores' ineffective inventory which may be constituted of unsold, under-selling, slow-moving, customer-returned, end-of-life, end-of-use, damaged, and faulty products within their inventory. We take into account the retailer's reverse supply chain structure and investigate the following problems: 1) How to manage a store's product returns under a given budgetary limitation for financial planning and taxation reasons, due to lost income from returned items, 2) Inventory optimization by taking into account the reverse supply chain structure of the retailer, and 3) Providing insight to the retailer on how it can best re-negotiate its vendor (buy-back) contracts for its product returns. The thesis covers decision making in all three levels: day-to-day operational decisions such as which products to be returned and where to allocate them within its reverse supply chain options, mid-term tactical decisions such as which Return Centers (RC) to be activated for the Reverse Logistics (RL) activities, and long-term strategic decisions such as what should be the optimal contract terms to re-negotiate with the vendors in order to cut future return costs.

To maximize the economics of a new commercial broiler cross, research on its nutritional specifications is necessary. Study 1 investigated the effects of feeding four amino acid densities (AAD) on performance and yield of Cobb MV × Cobb 500 broilers at d 33 and 36. Data demonstrated a stepwise decrease in feed conversion ratio (FCR) as AAD level increased. Improvements in performance, processing, and economic return were observed when feeding higher AAD levels. Study 2 estimated the digestible lysine (dLys) requirements of Cobb MV × Cobb 500 broilers from d 0-14 and evaluated the impact of varying starter dLys levels on their performance, processing, and economic return during a 42 d grow-out. Data suggested that d 0-14 dLys requirements varied based on broiler response and statistical model. Improvements in overall performance was observed when feeding ≥1.12% dLys during the starter phase. The greatest economic return was associated with feeding starter dLys of 1.20%. Due to the potential interaction between AA and apparent metabolizable energy (AME), Study 3 examined the response of Cobb MV × Cobb 500 to varying dLys and AME levels from d 0-14 on d 0-42 performance and processing. A dLys × AME interaction was observed for d 0-28 FCR and for dLys and AME for early performance parameters. However, this significance was lost by the end of the study. Due to the variation in broiler response to feeding strategies at different ages, Study 4 evaluated the impact of varying dLys and AME levels from d 14-28 on performance and processing of 42-day old Cobb MV × Cobb 500 broilers. Data demonstrated significant dLys × AME interactions for d 14-28 and 14-35 FCR, as well as significances for main effect of dLys and AME for performance and processing (d 42). Feeding grower diets formulated to 1.18% dLys + 3028 kcal/kg AME was the most profitable diet. Overall, this research demonstrates that higher AAD improved broiler performance, especially ≥1.12% starter dLys. Varying dLys and AME during the starter phase did not affect performance at d 42; however, it did when this regimen was exercised during the grower phase.

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