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This study aims to examine what factors retailers and real estate owners deem important in the process of determining expected rent levels in today's climate within retail where e-commerce is growing at a quick pace. The elements of the research questions stand on the foundation of the theory of rational expectations as well as the theory of anchoring. The method used is of qualitative nature where a case study consisting of two cases have been conducted. One in which interviews with representatives from three geographically distinct selected shopping centres have been carried out and another in which representatives from well-established retail companies have been interviewed. From these two case studies, insights regarding the existing discrepancy between the two parties, retailers and real estate owners, have been gathered. It is concluded that expectations about the future have significant impact in rent negotiations and that differences in expectations might be adding to the existing discrepancy. Moreover, results of the study indicate that retailers and real estate owners might be subject to self-inflicted anchoring in rent negotiations. The study contributes to research in further generalizing two well established theories by providing insights on how the rational expectations' theory as well as the anchoring theory could be applied on rent negotiations. / Denna studie syftar till att undersöka vilka faktorer butiks- och fastighetsägare anser vara viktigast i att bedöma förväntade hyresnivåer mot bakgrund av dagens klimat inom fysisk handel där e-handel tar marknadsandelar. Studien tar avstamp i teorin om rationella förväntningar samt teorin om anchoring. Metoden som har använts är av kvalitativ natur där två fallstudier har utförts. En fallstudie där intervjuer med representanter från tre geografiskt skilda köpcentrum har utförts samt en fallstudie där intervjuer har genomförts med representanter från väletablerade butikskedjor. Genom dessa två fallstudier har insikter gällande den upplevda diskrepansen mellan de två parterna utkristalliserats. Det går att konkludera att förväntningar om framtiden har en betydande påverkan på förväntade hyresnivåer och att en anledning till den ovan nämnda diskrepansen kan vara att förväntningarna om framtiden skiljer sig parterna emellan. Dessutom visar resultaten av studien på att butiks- och fastighetsägare, i vissa fall, kan vara föremål för en självförvållad anchoring-effekt vilket innebär att de blir låsta vid vissa hyresnivåer i samband med hyresförhandlingar. Den här studien bidrar till forskningen i att ytterligare generalisera två väletablerade teorier genom att ge initial vägledning i hur teorin om rationella förväntningar samt anchoring kan tillämpas på hyresförhandlingar.

Automated trust negotiation is the process of establishing trust between entities with no prior relationship through the iterative disclosure of digital credentials. One approach to negotiating trust is for the participants to exchange access control policies to inform each other of the requirements for establishing trust. When a policy is received at runtime, a compliance checker determines which credentials satisfy the policy so they can be disclosed. In situations where several sets of credentials satisfy a policy and some of the credentials are sensitive, a compliance checker that generates all the sets is necessary to insure that the negotiation succeeds whenever possible. Compliance checkers designed for trust management do not usually generate all the satisfying sets. In this thesis, we present two practical algorithms for generating all satisfying sets given a compliance checker that generates only one set. The ability to generate all of the combinations provides greater flexibility in how the system or user establishes trust. For example, the least sensitive credential combination could be disclosed first. These ideas have been implemented in TrustBuilder, our prototype system for trust negotiation.

Computing devices are commonly equipped with multiple transport technologies such as IrDA, Bluetooth and WiFi. Transport switching technologies, such as Quality of Transport (QoT), take advantage of this heterogeneity to keep network sessions active as users move in and out of range of various transports or as the networking environment changes. During an active session, the goal is to keep the device connected over the best transport currently available. To accomplish that, this thesis introduces a two-phase decision making protocol. In phase one, intra-device prioritization, users indicate the relative importance of criteria such as speed, power, service charge, or signal range through a comprehensive user interface. QoT-enabled devices process this information with the prioritized soft constraint satisfaction (PSCS) scoring function to ascertain the transport that best meets the user's needs. The second phase, inter-device negotiation, facilitates two QoT-enabled devices in agreeing to a unified selection of the best transport. This phase uses a modified version of the PSCS scoring function based on the preferences of both users. Additionally, devices may utilize multiple transports simultaneously to more accurately meet user demands. The PSCS scoring function considers pairs of transports and calculates the ratio that will yield the desired performance. Another set of functions, also presented in this thesis, is then used to accomplish the desired performance level despite the potential introduction of additional overhead.

Trust negotiation allows two parties on the Internet to establish trust in each other according to the digital credentials thateach other possesses. Traditionally, trust negotiation uses certificates as digital credentials. However, certificates make trust negotiation difficult to use since people rarely have certificates available to them, and they must physically possess and secure all needed certificates in order to negotiate. To avoid these problems, this thesis proposes that credential authorities negotiate on behalf of the user. This thesis defines BrowserBased Trust Negotiation (BBTN) as a method for negotiating with credential authorities using the Secure Assertion Markup Language (SAML).

This study examined the legal issues of public employee labor relations in the United States. Included in this study is a review of relevant case law as it pertains to collective bargaining in the public sector. In addition to reviewing the case law, this study researched the statutory language of each state for public sector collective bargaining. The study includes a review, analysis, and summary of the state and federal laws for public sector collective bargaining. The collective bargaining process in the United States is designed to resolve disputes between two parties, the employer and the employee. The resolution of these disputes often depends on the relative bargaining power of each party. The private sector has a collective bargaining process that has been well established since the passage of the National Labor Relations Act in 1935 and the Labor-Management Relations Act of 1947. The federal laws that have been implemented in the last fifty years, to include the Civil Rights Act of 1964, the Equal Employment Opportunity Act of 1972, the American with Disabilities Act of 1990, among others, cover the scope of almost all of the private sector collective bargaining (Oberer, 1994). The public sector contains 50 different state laws and several federal laws defining the scope of collective bargaining for public employees. The bargaining process in the public sector takes place in the context of the political arena. This political influence, which is unique in each state and at each level of government, provides additional steps to the bargaining process that further differentiate public sector bargaining from private (Valletta, 1985). This study provides conclusions on certain aspects of public sector collective bargaining that lead to dispute resolution and contract negotiation to include fact-finding procedures, mediation, arbitration, and strike policies, in the current state of the law. Recommendations are made to public officials, policy makers, and other stakeholders for the future of public employee labor relations in the United States.

Canonical problems are simplified representations of a class of real world problems. They allow researchers to compare algorithms in a standard setting which captures the most important challenges of the real world problems being modeled. In this dissertation, we focus on negotiating a collaboration in space and time, a problem with many important real world applications. Although technically a multi-issue negotiation, we show that the problem can not be represented in a satisfactory manner by previous models. We propose the "Children in the Rectangular Forest" (CRF) model as a possible canonical problem for negotiating spatio-temporal collaboration. In the CRF problem, two embodied agents are negotiating the synchronization of their movement for a portion of the path from their respective sources to destinations. The negotiation setting is zero initial knowledge and it happens in physical time. As equilibrium strategies are not practically possible, we are interested in strategies with bounded rationality, which achieve good performance in a wide range of practical negotiation scenarios. We design a number of negotiation protocols to allow agents to exchange their offers. The simple negotiation protocol can be enhanced by schemes in which the agents add additional information of the negotiation flow to aid the negotiation partner in offer formation. Naturally, the performance of a strategy is dependent on the strategy of the opponent and the iii characteristics of the scenario. Thus we develop a set of metrics for the negotiation scenario which formalizes our intuition of collaborative scenarios (where the agents’ interests are closely aligned) versus competitive scenarios (where the gain of the utility for one agent is paid off with a loss of utility for the other agent). Finally, we further investigate the sophisticated strategies which allow agents to learn the opponents while negotiating. We find strategies can be augmented by collaborativeness analysis: the approximate collaborativeness metric can be used to cut short the negotiation. Then, we discover an approach to model the opponent through Bayesian learning. We assume the agents do not disclose their information voluntarily: the learning needs to rely on the study of the offers exchanged during normal negotiation. At last, we explore a setting where the agents are able to perform physical action (movement) while the negotiation is ongoing. We formalize a method to represent and update the beliefs about the valuation function, the current state of negotiation and strategy of the opponent agent using a particle filter. By exploring a number of different negotiation protocols and several peer-to-peer negotiation based strategies, we claim that the CRF problem captures the main challenges of the real world problems while allows us to simplify away some of the computationally demanding but semantically marginal features of real world problems.