An Autonomous Engine for Services Configuration and Deployment.

The runtime management of the infrastructure providing service-based systems is a complex task, up to the point where manual operation struggles to be cost effective. As the functionality is provided by a set of dynamically composed distributed services, in order to achieve a management objective multiple operations have to be applied over the distributed elements of the managed infrastructure. Moreover, the manager must cope with the highly heterogeneous characteristics and management interfaces of the runtime resources. With this in mind, this paper proposes to support the configuration and deployment of services with an automated closed control loop. The automation is enabled by the definition of a generic information model, which captures all the information relevant to the management of the services with the same abstractions, describing the runtime elements, service dependencies, and business objectives. On top of that, a technique based on satisfiability is described which automatically diagnoses the state of the managed environment and obtains the required changes for correcting it (e.g., installation, service binding, update, or configuration). The results from a set of case studies extracted from the banking domain are provided to validate the feasibility of this proposa

Justice, emotions and satisfaction in complaint behavior in services

This study proposes a marketing approach to service recovery (SR) models in order to help to explain what factors affect cumulative satisfaction, loyalty and word-of-mouth following complaint behavior. The model has its base on the definition of perceived justice and its influence on satisfaction with service recovery (SSR) and on emotions (positive and negative). Trust acts as a central construct in the model, receiving influence from the affective and cognitive aspect and mediating the relationship between SSR and cumulative satisfaction and between positive/negative emotions and loyalty. The sample for this study consists of 303 Spanish B2C-EC users who made a complaint after an electronic transaction. Results from the analysis show the influence of perceived justice ?mainly interactional justice and procedural justice? on SSR, and the relevance of positive emotions as a key factor in SSR processes, in contrast to the major role which negative emotions have traditionally played in these models. Furthermore, trust mediates the relation between SSR and cumulative satisfaction, and is the factor which has a higher influence on loyalty, whilst cumulative satisfaction becomes the more relevant factor affecting WOM.

Creating and modelling personal socio-economic networks in on-line banking

The banking industry is observing how new competitors threaten its millennial business model by targeting unbanked people, offering new financial services to their customer base, and even enabling new channels for existing services and customers. The knowledge on users, their behaviour, and expectations become a key asset in this new context. Well aware of this situation, the Center for Open Middleware, a joint technology center created by Santander Bank and Universidad Politécnica de Madrid, has launched a set of initiatives to allow the experimental analysis and management of socio-economic information. PosdataP2P service is one of them, which seeks to model the economic ties between the holders of university smart cards, leveraging on the social networks the holders are subscribed to. In this paper we describe the design principles guiding the development of the system, its architecture and some implementation details.

A personal data framework for exchanging knowledge about users in new financial services

Personal data is a key asset for many companies, since this is the essence in providing personalized services. Not all companies, and specifically new entrants to the markets, have the opportunity to access the data they need to run their business. In this paper, we describe a comprehensive personal data framework that allows service providers to share and exchange personal data and knowledge about users, while facilitating users to decide who can access which data and why. We analyze the challenges related to personal data collection, integration, retrieval, and identity and privacy management, and present the framework architecture that addresses them. We also include the validation of the framework in a banking scenario, where social and financial data is collected and properly combined to generate new socio-economic knowledge about users that is then used by a personal lending service.

Banking crises and government intervention

Intervention has taken different forms in different countries and periods of time. Moreover, recent episodes showed that in front of an imminent crisis, the promise of no interventions made by governments is barely credible. In this paper we address the problem of resolving banking crises from the government perspective, taking into account the fact that preventing banking crises is crucial for the government. In addition, we introduce the moral hazard problem, inherent in the banking system, and consider the interaction between regulation, policy measures and banks’ behavior. To the best of our knowledge, this is the first paper that compares different policy plans to resolve banking crises in an environment where insufficiently capitalized banks have incentives to take risk, and the government has to decide whether to provide public services or impede crises. We show that when individuals highly value public services then the best policy in terms of welfare is to apply the tax on early withdrawals, as the government can transfer those taxes to the whole population by investing in public services (although at some cost). Conversely, when individuals assign a low value to consuming public services, recapitalization is the dominant policy. Finally, when the probability of a crisis is sufficiently high, capital requirements should be used