Individual deservingness and group-based equality as rules of distribution have routinely been conflated in past research. These two studies are an attempt to further establish the differences between these two as moral values named fairness and social justice, respectively. In both studies, participants rated “moral acceptability” of eight real-world scenarios that either upheld fairness and violated social justice or vice versa. Each of these scenarios was presented at two time points: at time 1, the upheld principle was presented and the violation of the other was implied, but at time 2, the violation was made apparent with a second sentence. Individual preferences for fairness and social justice were also measured. Study 1 primed basic principles of each value with a sentence scramble task before participants responded to the scenarios. Priming social justice principles significantly decreased moral acceptability ratings of fair scenarios before the social injustice was made apparent compared to the control condition, but ultimately individual differences in preferences for each principle were most predictive of moral acceptability ratings of both types of scenarios. Study 2 primed individual and collective perspectives with a writing prompt before participants responded to scenarios. Both priming tasks increased moral acceptability ratings of socially just scenarios before the unfairness was made apparent. This may have been due to the nature of the writing prompts, both of which required the participant to think of others, suggesting that social justice involves the consideration of social categories rather than simply a collection of people. In both studies, priming tasks and individual differences were generally unable to encourage recognition of the violation one or the other value, prompting the discussion of what else might promote such effortful thinking.

Future cellular networks, the so-called 5G, are expected to provide explosive data volumes and data rates. To meet such a demand, the research communities are investigating new wireless transmission technologies. One of the most promising candidates is in-band full-duplex communications. These communications are characterized by that a wireless device can simultaneously transmit and receive on the same frequency channel. In-band full-duplex communications have the potential to double the spectral efficiencywhen compared to current half duplex systems. The traditional drawback of full-duplex was the interference that leaks from the own transmitter to its own receiver, the so- called self-interference, which renders the receiving signal unsuitable for communication.However, recent advances in self-interference suppression techniques have provided high cancellation and reduced the self-interference to noise floor levels, which shows full-duplex is becoming a realistic technology component of advanced wireless systems. Although in-band full-duplex promises to double the data rate of existing wireless technologies, its deployment in cellular networks is challenging due to the large number of legacy devices working in half-duplex. A viable introduction in cellular networks is offered by three-node full-duplex deployments, in which only the base stations are full-duplex, whereas the user- or end-devices remain half-duplex. However, in addition to the inherent self-interference, now the interference between users, the user-to-user interference, may become the performance bottleneck, especially as the capability to suppress self-interference improves. Due to this new interference situation, user pairing and frequency channel assignment become of paramount importance, because both mechanisms can help to mitigate the user-to-user interference. It is essential to understand the trade-offs in the performance of full-duplex cellular networks, specially three-node full-duplex, in the design of spectral and energy efficient as well as fair mechanisms. This thesis investigates the design of spectral efficient and fair mechanisms to improve the performance of full-duplex in cellular networks. The novel analysis proposed in this thesis suggests centralized and distributed user pairing, frequency channel assignment and power allocation solutions to maximize the spectral efficiency and fairness in future full-duplex cellular networks. The investigations are based on distributed optimization theory with mixed integer-real variables and novel extensions of Fast-Lipschitz optimization. The analysis sheds lights on two fundamental problems of standard cellular networks, namely the spectral efficiency and fairness maximization, but in the new context of full-duplex communications. The results in this thesis provide important understanding in the role of user pairing, frequency assignment and power allocation, and reveal the special behaviourbetween the legacy self-interference and the new user-to-user interference. This thesis can provide input to the standardization process of full-duplex communications, and have the potential to be used in the implementation of future full-duplex in cellular networks. / <p>QC 20170403</p>

No description available.

Mobile crowdsourcing solves complex problems by utilizing the untapped power of a crowd, connected through the fantastic mobile devices we use in our daily life. These gadgets are equipped with a versatile set of sensor that could be used for gathering data about a specific location in combination with questions to the human carrier. Common problems in crowdsourcing systems is how to ensure that the contributed data from the crowd is of a high quality and how to do task allocation fairly. A large population of users is often needed to ensure a high quality of data and coverage, every participant is important and the system have to do be designed with the population in mind.In this thesis we discuss the responsibilities of the server in a crowdsourcing system and presents a system model which tries to tackle the problems of quality and fairness. A prototype of the system model was developed (CrowdS) to determine its potential, for both Android and iOS devices.A long running test was performed to evaluate the performance of CrowdS with the main focus on determine how well the system performed in terms of coverage of the search area and fairness of earnings and prices. The test was executed on both platforms for a couple of weeks. The vast majority of all completed tasks were finished within 10 minutes of being created, with a median time of 3 minutes and 32 seconds seconds. Jain’s fairness index measured an overall high fairness for both the price of tasks at 0.944 and the earnings made by participants at 0.941. The radius of the search area had to be extended to maximum of 800 meters for roughly on third of the tasks to find the required number of participants. / Mobil crowdsourcing löser komplexa problem genom att utnyttja kapaciteten av en grupp, sammankopplad med de mobila enheter vi använder dagligen. Dessa maskiner är utrustade med en mångsidig uppsättning av sensorer som kan användas för att samla in data om en specifik plats i kombination med frågor till den mänskliga bäraren. Vanliga problem med gruppbaserad problemlösning är hur man försäkrar att den insamlade informationen är av en hög kvalite´ och hur man utför uppdragsallokering rättvist. En stor användargrupp behövs för att uppnå en hög kvalite´ av data och täckning, varenda deltagare är viktig och systemet måste utformas med denna användargrupp i åtanke.I denna avhandling diskuterar vi ansvaret som en server har i mobil gruppbaserad problemlösning och presenterar en systemmodel som försöker hantera problemen med kvalite´ och rättvisa. För att utvärdera systemmodellen utvecklades en prototyp (CrowdS), för både Android och iOS-enheter.Ett långvarande test utfördes för att utvärdera Crowds prestanda med huvudfokus på att bestämmahur bra systemet presterade inom täckning för sökområdet och rättvishet för vinster och priser. Testet utfördes på båda plattformarna under ett par veckor. Den stora majoriteten av alla utdelade uppgifter var avklarade inom 10 minuter efter att de hade skapas, med en median tid på 3 minuter och 32 sekunder. Jain’s rättvise index användes för att få en uppfattning om hur rättvist vinster och priser var för uppgifter, det räknades till 0,944 respektive 0,941. Radien för sökområdet behövde utsträckas till dess maximum av 800 meter för cirka en tredjedel av uppgifterna för att hitta det tillräckligt många deltagare.

No description available.

Most people will experience rejection in the job selection process. Rejection from job opportunities is often issued via a letter from a hiring manager. These letters elicit reactions from applicants who may, in turn, have less favorable self perceptions and less favorable perceptions of the organization from which the applicant was rejected. Numerous research articles have been published that deal with delivering notification of selection and/or rejection to applicants in the job selection process. However, relatively few use a realistic laboratory design to obtain results. This study examined the effects of sensitivity and information in notifications of rejection when applicants are rejected in the job selection process. A more realistic laboratory design was used to increase the psychological fidelity of the job selection situation. One hundred forty undergraduate students participated in this study. Participants were told to imagine that they were graduate school applicants. Then, the participants completed a fake graduate school admissions test and received notification of rejection from a fake graduate school. Participants were assigned to conditions (letters varying in sensitivity and information type) randomly and the participants completed a post-notification of rejection survey that captured their self and organizational perceptions. Additionally, moderating variables were explored.

This dissertation consists of two essays in which I study the impact of two interdependent consumer behaviors, fairness concerns and exclusivity seeking, on a companys marketing strategies and profits specifically in a context where it tries to expand its clientele with the objective of generating repeat purchases, for example by running deals on daily deal platforms. In the first essay, I examine the impact of customers fairness concerns on the profitability of a company running promotions on daily deal platforms. With the prevalence of social media and the internet, information about such targeted promotions can become available to all consumers including those who did not have access to the platform and paid a full-price. Conducting a laboratory experiment, I demonstrate that knowledge about targeted promotions often leads to post-promotional fairness concerns among these consumers resulting in an increased tendency to switch providers. Incorporating the results of the experiment in a two-period game-theoretic model I analyze the impact of customers post-promotional fairness concerns on the profits of quality differentiated companies who compete by running targeted promotions. I find that the low quality provider always suffers from consumers sensitivity to unfairness. Contrary, I show that the high quality provider can counterintuitively benefit from consumers fairness concerns as long as its quality advantage is not too large. Furthermore, I analyze how profits are impacted when information about the targeted deals leaks to non-targeted customers who would have bought at the regular price. I find that, counterintuitively, competing firms profits increase with leakage. In the second essay of this dissertation, I start with the observation that many platform members are new customers and are uncertain about the quality of the companys product or service until they consume it. In such a context, I examine a high quality sellers optimal signaling strategy in a market where consumers prefer to purchase a scarce product due to desire for exclusivity or to receive a service in a non-crowded environment due to better experience and service delivery. Utilizing a repeat purchase signaling model I show that, consistent with prior literature, the high quality firm signals its quality by making its product scarce as well as charging a high price when consumers desire for exclusivity is high and cost of quality is great. Contrary, I also find conditions under which the high quality firm counterintuitively makes its product widely available and prices it low to signal its quality. The model may in part explain how high quality sellers market their products or services on daily deal websites.

Most studies on organizational justice have focused on individuals’ reactions to justice. As such, a key question has been left largely unanswered: Why do individuals act fairly or unfairly? The present research adopted a person-situation interactionist approach (Trevino, 1986) to examine psychological and situational antecedents of individuals’ fair behavior. The social identity model of deindividuation (SIDE; Reicher, Spears, & Postmes, 1995) and side-bet theory of continuance commitment (Becker, 1960) was used to examine how organizational identification and continuance commitment might influence employees’ fair or unfair behavior depending on an organization’s justice climate. Based on SIDE, it was hypothesized that organizational identification relates positively to employees’ feelings of deindividuation. Based on side-bet theory, it was further hypothesized that employees’ continuance commitment relates positively to their adoption of a subordinate role. Both deindividuation and adoption of a subordinate role were argued to make employees more susceptible to external influences and, therefore, make individuals more likely to behave in ways that are normative in a given context. Individuals who have higher levels of continuance commitment and organizational identification were, therefore, argued to engage in fair or unfair behavior depending on the level of the justice climate and the strength of the justice climate of their workgroup. The results of three studies provided support for the majority of hypotheses. Theoretical and practical implications of the results are discussed.

The dissertation studies the value of both investment banks' services on the whole and fairness opinions specifically, which the banks provide to the acquiring firms. In the first chapter, I examine how investment banks and acquiring firms' governance quality interact to affect shareholders' wealth in corporate mergers and acquisitions. Although the wealth impact of investment banks in mergers and acquisitions is widely studied in the literature, existing studies do not consider the interaction between governance quality and investment banks. I examine how investment banks and governance quality of acquiring firms interact to affect the wealth of acquiring firms' shareholders. I find that acquiring firms with poor governance are more likely to use investment banks in the deal. This association holds even after controlling for deal feature and other characteristics. I find that the use of investment banks per se does not result in a wealth reduction for the acquiring firms' shareholders. However, when the acquiring firm has poor governance, the use of investment bank is associated with extra value loss for the shareholders. The finding suggests that investment banks may help managerial empire building at the expense of shareholders under some circumstances. The study indicates that when studying investment bank's impact it is important to consider the quality of the hiring firms' governance. In the second chapter, I investigate the wealth implications of fairness opinions that the board of an acquiring firm purchases in corporate mergers from investment banks. Using the propensity score matching method to address the self-selection issue, I find that firms undertaking opinioned mergers under-perform firms with non-opinioned matching mergers in short windows around the announcement date. In the long run, the firms with opinioned merger do not perform better than firms with non-opinioned mergers. The acquiring firms perform poorly relative to their performance before the mergers, irrespective of whether their mergers are opinioned. Over a 12-month window after the mergers, the acquiring firms involved in both opinioned and non-opinioned mergers under-perform matching firms that do not make mergers. These findings are consistent with the hypothesis that the board buys a fairness opinion for its self-protection instead of maximization of shareholder wealth. The implication of this finding is that when investors evaluate mergers, they should focus primarily on deal characteristics, not fairness opinion.

Optical networking, employing wavelength division multiplexing (WDM), is seen as the technology of the future for the Internet. This dissertation investigates several important problems affecting optical circuit switching (OCS) and optical burst switching (OBS) networks. Novel algorithms and new approaches to improve the performance of these networks through effective routing and channel scheduling are presented. Extensive simulations and analytical modeling have both been used to evaluate the effectiveness of the proposed algorithms in achieving lower blocking probability, better fairness as well as faster switching. The simulation tests were performed over a variety of optical network topologies including the ring and mesh topologies, the U.S. Long-Haul topology, the Abilene high-speed optical network used in Internet 2, the Toronto Metropolitan topology and the European Optical topology. Optical routing protocols previously published in the literature have largely ignored the noise and timing jitter accumulation caused by cascading several wavelength conversions along the lightpath of the data burst. This dissertation has identified and evaluated a new constraint, called the wavelength conversion cascading constraint. According to this constraint, the deployment of wavelength converters in future optical networks will be constrained by a bound on the number of wavelength conversions that a signal can go through when it is switched all-optically from the source to the destination. Extensive simulation results have conclusively demonstrated that the presence of this constraint causes significant performance deterioration in existing routing and wavelength assignment (RWA) algorithms. Higher blocking probability and/or worse fairness have been observed for existing RWA algorithms when the cascading constraint is not ignored. To counteract the negative side effect of the cascading constraint, two constraint-aware routing algorithms are proposed for OCS networks: the desirable greedy algorithm and the weighted adaptive algorithm. The two algorithms perform source routing using link connectivity and the global state information of each wavelength. Extensive comparative simulation results have illustrated that by limiting the negative cascading impact to the minimum extent practicable, the proposed approaches can dramatically decrease the blocking probability for a variety of optical network topologies. The dissertation has developed a suite of three fairness-improving adaptive routing algorithms in OBS networks. The adaptive routing schemes consider the transient link congestion at the moment when bursts arrive and use this information to reduce the overall burst loss probability. The proposed schemes also resolve the intrinsic unfairness defect of existing popular signaling protocols. The extensive simulation results have shown that the proposed schemes generally outperform the popular shortest path routing algorithm and the improvement could be substantial. A two-dimensional Markov chain analytical model has also been developed and used to analyze the burst loss probabilities for symmetrical ring networks. The accuracy of the model has been validated by simulation. Effective proactive routing and preemptive channel scheduling have also been proposed to address the conversion cascading constraint in OBS environments. The proactive routing adapts the fairness-improving adaptive routing mentioned earlier to the environment of cascaded wavelength conversions. On the other hand, the preemptive channel scheduling approach uses a dynamic priority for each burst based on the constraint threshold and the current number of performed wavelength conversions. Empirical results have proved that when the cascading constraint is present, both approaches would not only decrease the burst loss rates greatly, but also improve the transmission fairness among bursts with different hop counts to a large extent.