Auto-scaling is a major way of minimizing the gap between the demand and the availability of the computing resources for the applications with dynamic workloads. Even though a lot of effort has been taken to address the requirement of auto-scaling for the distributed systems, most of the available solutions are application-specific and consider only on fulfilling the application level requirements. Today, with the pay-as-you-go model of cloud computing, many different price plans have been offered by the cloud providers which leads the resource price to become an important decision-making criterion at the time of auto-scaling. One major step is using the spot instances which are more advantageous in the aspect of cost for elasticity. However, using the spot instances for auto-scaling should be handled carefully to avoid its drawbacks since the spot instances can be terminated at any time by the infrastructure providers. Despite the fact that some cloud providers such as Amazon Web Services and Google Compute Engine have their own auto-scaling solutions, they do not follow the goal of cost-effectiveness. In this work, we introduce our auto-scaling solution that is targeted for middle-layers in-between the cloud and the application, such as Karamel. Our work combines the aspect of minimizing the cost of the deployment with maintaining the demand for the resources. Our solution is a rule-based system that is built on top of resource utilization metrics as a more general metric for workloads. Further, the machine terminations and the billing period of the instances are taken into account as the cloud source events. Different strategies such as window based profiling, dynamic event profiling, and optimized scale-in strategy have been used to achieve our main goal of providing a cost-effective auto-scaling solution for cloud-based deployments. With the help of our simulation methodology, we explore our parameter space to find the best values under different workloads. Moreover, our cloud-based experiments show that our solution performs much more economically compare to the available cloud-based auto-scaling solutions.

The main aim of the study was to determine which measurement tool, existing or adapted, would be able to determine the levels of customer centricity within the sales channels of a specific organisation, operating in the South African financial industry. A literary study showed that in order to determine the levels of customer centricity, customer experience should be measured. Six questionnaires were administered, namely, EXQ, NPS, CES, Customer satisfaction, Word-of-Mouth and Behavioural loyalty intention. The data showed a statistical significance and a positive relationship between all the constructs within all the questionnaires except with that of CES. / MBA, North-West University, Potchefstroom Campus, 2014

<p>The aim of this study is to illustrate, adapt and develop methods of survival analysis in analysing and estimating customer survival time in subscription-based businesses. Two particular objectives are studied. The rst objective is to redene the existing survival analysis techniques in business terms and to discuss their uses in order to understand various issues related to the customer-rm relationship.</p>

Ο σκοπός της εργασίας είναι να δώσει στον αναγνώστη την δυνατότητα να γνωρίσει τον κόσμο της τεχνολογίας των πληροφοριών, την πελατοκεντρική φιλοσοφία και ειδικότερα την λειτουργία και τον διαχωρισμό των επιμέρους επιχειρηματικών εργαλείων που ονομάζονται CRM. / The objective of this paper is to make the reader familiar with the IT(Information Technology), the customer-centric philosophy and especially the functionality and the classification of the most common business tools called CRM.

<p>The aim of this study is to illustrate, adapt and develop methods of survival analysis in analysing and estimating customer survival time in subscription-based businesses. Two particular objectives are studied. The rst objective is to redene the existing survival analysis techniques in business terms and to discuss their uses in order to understand various issues related to the customer-rm relationship.</p>

The main aim of the study was to determine which measurement tool, existing or adapted, would be able to determine the levels of customer centricity within the sales channels of a specific organisation, operating in the South African financial industry. A literary study showed that in order to determine the levels of customer centricity, customer experience should be measured. Six questionnaires were administered, namely, EXQ, NPS, CES, Customer satisfaction, Word-of-Mouth and Behavioural loyalty intention. The data showed a statistical significance and a positive relationship between all the constructs within all the questionnaires except with that of CES. / MBA, North-West University, Potchefstroom Campus, 2014

Philosophiae Doctor - PhD / Subscription-based industries have seen a massive expansion in recent decades. In this type of industry the customer has to subscribe to be able to enjoy the service; there-fore, well-de ned start and end points of the customer relationship with the service provider are known. The length of this relationship, that is the time from subscription to service cancellation, is de ned as customer survival time. Unlike transaction-based businesses, where the emphasis is on the quality of a product and customer acquisition, subscription-based businesses focus on the customer and customer retention. A customer focus requires a new approach: managing according to customer equity (the value of a rm's customers) rather than brand equity (the value of a rm's brands). The concept of customer equity is attractive and straightforward, but the implementation and management of the customer equity approach do present some challenges. Amongst these challenges is that customer asset metric - customer lifetime value (the present value of all future pro ts generated from a customer) - depends upon assumptions about the expected survival time of the customer (Bell et al., 2002; Gupta and Lehmann, 2003). In addition, managing and valuing customers as an asset require extensive data and complex modelling. The aim of this study is to illustrate, adapt and develop methods of survival analysis in analysing and estimating customer survival time in subscription-based businesses. Two particular objectives are studied. The fi rst objective is to rede ne the existing survival analysis techniques in business terms and to discuss their uses in order to understand various issues related to the customer-fi rm relationship. The lesson to be learnt here is the ability of survival analysis techniques to extract important information on customers with regard to their loyalties, risk of cancellation of the service, and lifetime value. The ultimate outcome of this process of studying customer survival time will be to understand the dynamics and behaviour of customers with respect to their risk of cancellation, survival probability and lifetime value. The results of the estimates of customer mean survival time obtained from different nonparametric and parametric approaches; namely, the Kaplan-Meier method as well as exponential, Weibull and gamma regression models were found to vary greatly showing the importance of the assumption imposed on the distribution of the survival time. The second objective is to extrapolate the customer survival curve beyond the empirical distribution. The practical motivation for extrapolating the survival curve beyond the empirical distribution originates from two issues; that of calculating survival probabilities (retention rate) beyond the empirical data and of calculating the conditional survival probability and conditional mean survival time at a speci c point in time and for a speci c time window in the future. The survival probabilties are the main components needed to calculate customer lifetime value and thereafter customer equity. In this regard, we propose a survivor function that can be used to extrapolate the survival probabilities beyond the last observed failure time; the estimation of parameters of the newly proposed extrapolation function is based completely on the Kaplan-Meier estimate of the survival probabilities. The proposed function has shown a good mathematical accuracy. Furthermore, the standard error of the estimate of the extrapolation survival function has been derived. The function is ready to be used by business managers where the objective is to enhance customer retention and to emphasise a customer-centric approach. The extrapolation function can be applied and used beyond the customer survival time data to cover clinical trial applications. In general the survival analysis techniques were found to be valuable in understanding and managing a customer- rm relationship; yet, much still needs to be done in this area of research to make these techniques that are traditionally used in medical studies more useful and applicable in business settings. / South Africa

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This study extends our understanding of how information systems impact business value creation by examining the effect of digital enablement of business-to-business exchange on customer outcomes. We shed light on the connection between information technology investment and firm performance by focusing on how information technology is used (Devaraj and Kohli 2003) in an industrial services context and by highlighting the importance of indirect effects (Mittal and Nault 2009). A conceptual model is developed that combines a customer centric perspective (Sheth et al. 2000) with elements from the information systems success framework (DeLone and McLean 1992, DeLone and McLean 2003). Mediating factors are identified in the chain of effects from information technology specific business-to-business service quality characteristics to customer outcomes. In addition, we consider two contextual factors, relationship duration and customer dependence, which are known to alter the nature of buyer-supplier relationships but which have received little attention in research on digital enablement of business-to-business exchange. An empirical test of hypothesized relationships was performed using subjective and objective archival data from business-to-business exchange relationships for a logistics services vendor. All expected main effects were confirmed. Customer satisfaction was found to be a significant mediator in the chain of effects from information technology specific business-to-business service quality characteristics to customer outcomes. In addition, logistics service quality was found to mediate the relationships between system quality and customer satisfaction and between information quality and customer satisfaction. The hypothesized moderating effects, however, were not found to be significant. Robustness of the findings was confirmed by testing model hypotheses using data from exchange relationships with customers in two different industries, manufacturing and wholesale trade. Differences in analysis results are consistent with industry differences. This study contributes to the literatures on interorganizational information systems (Rai et al. 2006) and information technology business value (Melville et al. 2004) by identifying mediating mechanisms in the chain of effects from digital enablement of exchange to customer outcomes. Explication of mediating mechanisms improves our understanding about the indirect nature of impacts from information technology. This study also contributes to the literature on information systems by extending DeLone and McLean's (2003) model of information systems success to the context of business-to-business exchange relationships. In addition, this study contributes to the literature on services marketing (Zeithaml and Bitner 2003, Berry and Parasuraman 1993) by showing how system quality and information quality impact logistics service quality and customer satisfaction in a business-to-business exchange context.

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