In the group-buying transaction, consumers will not know the final price until the transaction is closed. It means that there are uncertainties of the final price and time to reach a desired price. In other words, consumers have financial risk and time risk in group-buying transactions. In addition, different pricing strategies of group-buying may result in different risks. The purpose of this study is to investigate how the perceived risks of consumers affect their intentions to participate the online group-buying with different pricing mechanisms, i.e. decreasing, neutral and increasing. The result shows that because group-buying models with different pricing mechanisms have different initial prices, final prices and discounts, the risks perceived by consumers are different and then, affect consumers¡¦ intention to participate the online group-buying. Among these three pricing mechanisms, decreasing pricing mechanism makes consumers perceive higher risk than other pricing mechanisms because its initial price is higher. The more the consumers¡¦ perceived risks are, the lower the consumers¡¦ intentions to participate the online group-buying are. Therefore, group-buying with decreasing pricing mechanism can not attract consumers to join the online group-buying efficiently. Furthermore, this study finds that perceived usefulness and satisfaction affect consumers¡¦ intentions to participate the online group-buying significantly. In addition, all consumers¡¦ perceived risks, perceived usefulness and intentions to participate online group-buying influence consumers¡¦ actual participating behavior significantly.

The efficient allocation of power is a major concern in today’s wireless communications systems. Due to the high demand in data rate and the scarcity of wireless resources such as power, the multi-user communication systems like the multiple access channel (MAC) and broadcast channel (BC) have become highly competitive environments for the users as well as the system itself. Theory of microeconomics and game theory provide the good analytical manner for the selfish and social welfare conflict problems. Instead of maximizing the system sum rate, our proposed system deals with fulfilling the utility (rate) requirement of all the users with efficient power allocation. The users formulate the signal to interference-plus-noise ratio (SINR) based quality-of-service (QoS) requirements. We propose the framework to allocate the power to each user with universal pricing mechanisms. The prices act as the control signal and are assumed to be some virtual currency in the wireless system. They can influence the physical layer operating points to meet the desired utility requirements. Centralized and distributed power allocation frameworks are discussed separately in the thesis with different pricing schemes. In wireless systems we have users that are rational in the game theoretic sense of making decisions consistently in pursuit of their own individual objectives. Each user’s objective is to maximize the expected value of its own payoff measured on a certain utility scale. Selfishness or self-interest is an important implication of rationality. Therefore, the mobiles which share the same spectrum have incentives to misinterpret their private information in order to obtain more utility. They might behave selfishly and show also malicious behavior by creating increased interference for other mobiles. Therefore, it is important to supervise and influence the operation of the system by pricing and priority (weights) optimization. In the centralized resource allocation, we study the general MAC and BC (with linear and nonlinear receiver) with three types of agents: the regulator, the system optimizer and the mobile users. The regulator ensures the QoS requirements of all users by clever pricing and prevents cheating. The simple system optimizer solves a certain system utility maximization problem to allocate the power with the given prices and weights (priorities). The linear and nonlinear pricing mechanisms are analyzed, respectively. It is shown that linear pricing is a universal pricing only if successive interference cancellation (SIC) for uplink transmission or dirty paper coding (DPC) for downlink transmission is applied at the base station (BS). For MAC without SIC, nonlinear pricing which is logarithmic in power and linear in prices is a universal pricing scheme. The prices, the resulting cost terms, the optimal power allocation to achieve the QoS requirement of each user in the feasible rate region are derived in closed form solutions for MAC with and without SIC using linear and nonlinear pricing frameworks, respectively. The users are willing to maximize their achievable rate and minimize their cost on power by falsely reporting their channel state information (CSI). By predicting the best cheating strategy of the malicious users, the regulator is able to detect the misbehavior and punish the cheaters. The infinite repeated game (RG) is proposed as a counter mechanism with the trigger strategy using the trigger price. We show that by anticipating the total payoff of the proposed RG, the users have no incentive to cheat and therefore our framework is strategy-proof. In the distributed resource allocation, each user allocates its own power by optimizing the individual utility function. The noncooperative game among the users is formulated. The individual prices are introduced to the utility function of each user to shift the Nash equilibrium (NE) power allocation to the desired point. We show that by implicit control of the proposed prices, the best response (BR) power allocation of each user converges rapidly. The Shannon rate-based QoS requirement of each user is achieved with minimum power at the unique NE point. We analyse different behavior types of the users, especially the malicious behavior of misrepresenting the user utility function. The resulting NE power allocation and achievable rates of all users are derived when malicious behavior exists. The strategy-proof mechanism is designed using the punishment prices when the types of the malicious users are detected. The algorithm of the strategy-proof noncooperative game is proposed. We illustrate the convergence of the BR dynamic and the Price of Malice (PoM) by numerical simulations. The uplink transmission within the single cell of heterogeneous networks is exactly the same model as MAC. Therefore, the results of the pricing-based power allocation for MAC can be implemented into heterogeneous networks. Femtocells deployed in the Macrocell network provide better indoor coverage to the user equipments (UEs) with low power consumption and maintenance cost. The industrial vendors show great interest in the access mode, called the hybrid access, in which the macrocell UEs (MUEs) can be served by the nearby Femtocell Access Point (FAP). By adopting hybrid access in the femtocell, the system energy efficiency is improved due to the short distance between the FAP and MUEs while at the same time, the QoS requirements are better guaranteed. However, both the Macrocell base station (MBS) and the FAP are rational and selfish, who maximize their own utilities. The framework to successively apply the hybrid access in femtocell and fulfill the QoS requirement of each UE is important. We propose two novel compensation frameworks to motivate the hybrid access of femtocells. To save the energy consumption, the MBS is willing to motivate the FAP for hybrid access with compensation. The Stackelberg game is formulated where the MBS serves as the leader and the FAP serves as the follower. The MBS maximizes its utility by choosing the compensation prices. The FAP optimizes its utility by selecting the number of MUEs in hybrid access. By choosing the proper compensation price, the optimal number of MUEs served by the FAP to maximize the utility of the MBS coincides with that to maximize the utility of the FAP. Numerous simulation results are conducted, showing that the proposed compensation frameworks result in a win-win solution. In this thesis, based on game theory, mechanism design and pricing framework, efficient power allocation are proposed to guarantee the QoS requirements of all users in the wireless networks. The results are applicable in the multi-user systems such as heterogeneous networks. Both centralized and distributed allocation schemes are analyzed which are suitable for different communication scenarios. / Aufgrund der hohen Nachfrage nach Datenrate und wegen der Knappheit an Ressourcen in Funknetzen ist die effiziente Allokation von Leistung ein wichtiges Thema in den heutigen Mehrnutzer-Kommunikationssystemen. Die Spieltheorie bietet Methoden, um egoistische und soziale Konfliktsituationen zu analysieren. Das vorgeschlagene System befasst sich mit der Erfüllung der auf Signal-zu-Rausch-und-Interferenz-Verhältnis (SINR) basierenden Quality-of-Service (QoS)-Anforderungen aller Nutzer mittels effizienter Leistungsallokation, anstatt die Übertragungsrate zu maximieren. Es wird ein Framework entworfen, um die Leistungsallokation mittels universellen Pricing-Mechanismen umzusetzen. In der Dissertation werden zentralisierte und verteilte Leistungsallokationsalgorithmen unter Verwendung verschiedener Pricing-Ansätze diskutiert. Die Nutzer in Funksystemen handeln rational im spieltheoretischen Sinne, indem sie ihre eigenen Nutzenfunktionen maximieren. Die mobilen Endgeräte, die dasselbe Spektrum nutzen, haben den Anreiz durch bewusste Fehlinterpretation ihrer privaten Informationen das eigene Ergebnis zu verbessern. Daher ist es wichtig, die Funktionalität des Systems zu überwachen und durch Optimierung des Pricings und Priorisierungsgewichte zu beeinflussen. Für den zentralisierten Ressourcenallokationsansatz werden der allgemeine Mehrfachzugriffskanal (Multiple Access Channel, MAC) und der Broadcastkanal (BC) mit linearen bzw. nichtlinearen Empfängern untersucht. Die Preise, die resultierenden Kostenterme und die optimale Leistungsallokation, mit der die QoS-Anforderungen in der zulässigen Ratenregion erfüllt werden, werden in geschlossener Form hergeleitet. Lineare und nichtlineare Pricing-Ansätze werden separat diskutiert. Das unendlich oft wiederholte Spiel wird vorgeschlagen, um Spieler vom Betrügen durch Übermittlung falscher Kanalinformationen abzuhalten. Für die verteilten Ressourcenvergabe wird das nichtkooperative Spiel in Normalform verwendet und formuliert. Die Nutzer wählen ihre Sendeleistung zur Maximierung ihrer eigenen Nutzenfunktion. Individuelle Preise werden eingeführt und so angepasst, dass die QoS-Anforderungen mit der Leistungsallokation im eindeutigen Nash-Gleichgewicht erfüllt werden. Verschiedene Arten des Nutzerverhaltens werden bezüglich der Täuschung ihrer Nutzenfunktion analysiert, und ein Strategy-Proof-Mechanismus mit Strafen wird entwickelt. Die Ergebnisse für den MAC sind anwendbar auf heterogene Netzwerke, wobei zwei neuartige Ansätze zur Kompensation bereitgestellt werden, die den hybriden Zugang zu Femtozell-Netzwerken motivieren. Mithilfe des Stackelberg-Spiels wird gezeigt, dass die vorgeschlagenen Ansätze in einer Win-Win-Situation resultieren.

The efficient allocation of power is a major concern in today’s wireless communications systems. Due to the high demand in data rate and the scarcity of wireless resources such as power, the multi-user communication systems like the multiple access channel (MAC) and broadcast channel (BC) have become highly competitive environments for the users as well as the system itself. Theory of microeconomics and game theory provide the good analytical manner for the selfish and social welfare conflict problems. Instead of maximizing the system sum rate, our proposed system deals with fulfilling the utility (rate) requirement of all the users with efficient power allocation. The users formulate the signal to interference-plus-noise ratio (SINR) based quality-of-service (QoS) requirements. We propose the framework to allocate the power to each user with universal pricing mechanisms. The prices act as the control signal and are assumed to be some virtual currency in the wireless system. They can influence the physical layer operating points to meet the desired utility requirements. Centralized and distributed power allocation frameworks are discussed separately in the thesis with different pricing schemes. In wireless systems we have users that are rational in the game theoretic sense of making decisions consistently in pursuit of their own individual objectives. Each user’s objective is to maximize the expected value of its own payoff measured on a certain utility scale. Selfishness or self-interest is an important implication of rationality. Therefore, the mobiles which share the same spectrum have incentives to misinterpret their private information in order to obtain more utility. They might behave selfishly and show also malicious behavior by creating increased interference for other mobiles. Therefore, it is important to supervise and influence the operation of the system by pricing and priority (weights) optimization. In the centralized resource allocation, we study the general MAC and BC (with linear and nonlinear receiver) with three types of agents: the regulator, the system optimizer and the mobile users. The regulator ensures the QoS requirements of all users by clever pricing and prevents cheating. The simple system optimizer solves a certain system utility maximization problem to allocate the power with the given prices and weights (priorities). The linear and nonlinear pricing mechanisms are analyzed, respectively. It is shown that linear pricing is a universal pricing only if successive interference cancellation (SIC) for uplink transmission or dirty paper coding (DPC) for downlink transmission is applied at the base station (BS). For MAC without SIC, nonlinear pricing which is logarithmic in power and linear in prices is a universal pricing scheme. The prices, the resulting cost terms, the optimal power allocation to achieve the QoS requirement of each user in the feasible rate region are derived in closed form solutions for MAC with and without SIC using linear and nonlinear pricing frameworks, respectively. The users are willing to maximize their achievable rate and minimize their cost on power by falsely reporting their channel state information (CSI). By predicting the best cheating strategy of the malicious users, the regulator is able to detect the misbehavior and punish the cheaters. The infinite repeated game (RG) is proposed as a counter mechanism with the trigger strategy using the trigger price. We show that by anticipating the total payoff of the proposed RG, the users have no incentive to cheat and therefore our framework is strategy-proof. In the distributed resource allocation, each user allocates its own power by optimizing the individual utility function. The noncooperative game among the users is formulated. The individual prices are introduced to the utility function of each user to shift the Nash equilibrium (NE) power allocation to the desired point. We show that by implicit control of the proposed prices, the best response (BR) power allocation of each user converges rapidly. The Shannon rate-based QoS requirement of each user is achieved with minimum power at the unique NE point. We analyse different behavior types of the users, especially the malicious behavior of misrepresenting the user utility function. The resulting NE power allocation and achievable rates of all users are derived when malicious behavior exists. The strategy-proof mechanism is designed using the punishment prices when the types of the malicious users are detected. The algorithm of the strategy-proof noncooperative game is proposed. We illustrate the convergence of the BR dynamic and the Price of Malice (PoM) by numerical simulations. The uplink transmission within the single cell of heterogeneous networks is exactly the same model as MAC. Therefore, the results of the pricing-based power allocation for MAC can be implemented into heterogeneous networks. Femtocells deployed in the Macrocell network provide better indoor coverage to the user equipments (UEs) with low power consumption and maintenance cost. The industrial vendors show great interest in the access mode, called the hybrid access, in which the macrocell UEs (MUEs) can be served by the nearby Femtocell Access Point (FAP). By adopting hybrid access in the femtocell, the system energy efficiency is improved due to the short distance between the FAP and MUEs while at the same time, the QoS requirements are better guaranteed. However, both the Macrocell base station (MBS) and the FAP are rational and selfish, who maximize their own utilities. The framework to successively apply the hybrid access in femtocell and fulfill the QoS requirement of each UE is important. We propose two novel compensation frameworks to motivate the hybrid access of femtocells. To save the energy consumption, the MBS is willing to motivate the FAP for hybrid access with compensation. The Stackelberg game is formulated where the MBS serves as the leader and the FAP serves as the follower. The MBS maximizes its utility by choosing the compensation prices. The FAP optimizes its utility by selecting the number of MUEs in hybrid access. By choosing the proper compensation price, the optimal number of MUEs served by the FAP to maximize the utility of the MBS coincides with that to maximize the utility of the FAP. Numerous simulation results are conducted, showing that the proposed compensation frameworks result in a win-win solution. In this thesis, based on game theory, mechanism design and pricing framework, efficient power allocation are proposed to guarantee the QoS requirements of all users in the wireless networks. The results are applicable in the multi-user systems such as heterogeneous networks. Both centralized and distributed allocation schemes are analyzed which are suitable for different communication scenarios. / Aufgrund der hohen Nachfrage nach Datenrate und wegen der Knappheit an Ressourcen in Funknetzen ist die effiziente Allokation von Leistung ein wichtiges Thema in den heutigen Mehrnutzer-Kommunikationssystemen. Die Spieltheorie bietet Methoden, um egoistische und soziale Konfliktsituationen zu analysieren. Das vorgeschlagene System befasst sich mit der Erfüllung der auf Signal-zu-Rausch-und-Interferenz-Verhältnis (SINR) basierenden Quality-of-Service (QoS)-Anforderungen aller Nutzer mittels effizienter Leistungsallokation, anstatt die Übertragungsrate zu maximieren. Es wird ein Framework entworfen, um die Leistungsallokation mittels universellen Pricing-Mechanismen umzusetzen. In der Dissertation werden zentralisierte und verteilte Leistungsallokationsalgorithmen unter Verwendung verschiedener Pricing-Ansätze diskutiert. Die Nutzer in Funksystemen handeln rational im spieltheoretischen Sinne, indem sie ihre eigenen Nutzenfunktionen maximieren. Die mobilen Endgeräte, die dasselbe Spektrum nutzen, haben den Anreiz durch bewusste Fehlinterpretation ihrer privaten Informationen das eigene Ergebnis zu verbessern. Daher ist es wichtig, die Funktionalität des Systems zu überwachen und durch Optimierung des Pricings und Priorisierungsgewichte zu beeinflussen. Für den zentralisierten Ressourcenallokationsansatz werden der allgemeine Mehrfachzugriffskanal (Multiple Access Channel, MAC) und der Broadcastkanal (BC) mit linearen bzw. nichtlinearen Empfängern untersucht. Die Preise, die resultierenden Kostenterme und die optimale Leistungsallokation, mit der die QoS-Anforderungen in der zulässigen Ratenregion erfüllt werden, werden in geschlossener Form hergeleitet. Lineare und nichtlineare Pricing-Ansätze werden separat diskutiert. Das unendlich oft wiederholte Spiel wird vorgeschlagen, um Spieler vom Betrügen durch Übermittlung falscher Kanalinformationen abzuhalten. Für die verteilten Ressourcenvergabe wird das nichtkooperative Spiel in Normalform verwendet und formuliert. Die Nutzer wählen ihre Sendeleistung zur Maximierung ihrer eigenen Nutzenfunktion. Individuelle Preise werden eingeführt und so angepasst, dass die QoS-Anforderungen mit der Leistungsallokation im eindeutigen Nash-Gleichgewicht erfüllt werden. Verschiedene Arten des Nutzerverhaltens werden bezüglich der Täuschung ihrer Nutzenfunktion analysiert, und ein Strategy-Proof-Mechanismus mit Strafen wird entwickelt. Die Ergebnisse für den MAC sind anwendbar auf heterogene Netzwerke, wobei zwei neuartige Ansätze zur Kompensation bereitgestellt werden, die den hybriden Zugang zu Femtozell-Netzwerken motivieren. Mithilfe des Stackelberg-Spiels wird gezeigt, dass die vorgeschlagenen Ansätze in einer Win-Win-Situation resultieren.