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Why was Italy the first country to introduce prepaid mobile phone billing services in 1996? What was the key to its success that led seventy-five telecommunications operators to introduce prepaid billing by 1998 and accelerated the mass adoption of mobile phones around the world? This article examines why prepaid was successful in light of national policies and sociocultural shifts. Along with SMS, handhelds, GSM, and the digitization of mobile communications, prepaid billing played a role in the rapid and immense spread of the mobile phone worldwide. As an innovative means of paying for mobile phone usage, prepaid represented a departure from operators' previous mobile phone payment methods. The article argues that by overlooking the contribution of this form of payment, telephone historians, the media, and business scholars have ignored this important driver of the success of mobile phones. [ABSTRACT FROM AUTHOR]

All public transportation was closed, ambulant military checkpoints were set up, and quarantine violators were forced into thirty-day quarantines at confinement centers. All nonessential businesses were closed.[9] The logistics of quarantine centers were put in the hands of the military.[10] With the first documented case of COVID-19 on March 18, a thirty-day military enforced quarantine was declared.[11] Only one person per household was allowed to travel outside the home, twice a week, and only for "essential business." "What can COVID do to me?" The social exclusion experienced by inhabitants of places such as El Cerro has allowed for early COVID-19 emergency measures to take the form of social triage (Biehl 2005). [Extracted from the article]

Background: We describe addiction consult services (ACS) adaptations implemented during the Novel Coronavirus Disease 2019 (COVID-19) pandemic across four different North American sites: St. Paul's Hospital in Vancouver, British Columbia; Oregon Health & Sciences University in Portland, Oregon; Boston Medical Center in Boston, Massachusetts; and Yale New Haven Hospital in New Haven, Connecticut. Experiences: ACS made system, treatment, harm reduction, and discharge planning adaptations. System changes included patient visits shifting to primarily telephone-based consultations and ACS leading regional COVID-19 emergency response efforts such as substance use treatment care coordination for people experiencing homelessness in COVID-19 isolation units and regional substance use treatment initiatives. Treatment adaptations included providing longer buprenorphine bridge prescriptions at discharge with telemedicine follow-up appointments and completing benzodiazepine tapers or benzodiazepine alternatives for people with alcohol use disorder who could safely detoxify in outpatient settings. We believe that regulatory changes to buprenorphine, and in Vancouver other medications for opioid use disorder, helped increase engagement for hospitalized patients, as many of the barriers preventing them from accessing care on an ongoing basis were reduced. COVID-19 specific harm reductions recommendations were adopted and disseminated to inpatients. Discharge planning changes included peer mentors and social workers increasing hospital in-reach and discharge outreach for high-risk patients, in some cases providing prepaid cell phones for patients without phones. Recommendations for the future: We believe that ACS were essential to hospitals' readiness to support patients that have been systematically marginilized during the pandemic. We suggest that hospitals invest in telehealth infrastructure within the hospital, and consider cellphone donations for people without cellphones, to help maintain access to care for vulnerable patients. In addition, we recommend hospital systems evaluate the impact of such interventions. As the economic strain on the healthcare system from COVID-19 threatens the very existence of ACS, overdose deaths continue rising across North America, highlighting the essential nature of these services. We believe it is imperative that health care systems continue investing in hospital-based ACS during public health crises. [ABSTRACT FROM AUTHOR]

This paper studies how the rates of deduction for early retirement have to be determined in pay-as-you-go (PAYG) systems in order to keep their budget stable. The derivation of these deductions requires the use of a multiperiod intertemporal budget constraint that involves assumptions about the retirement behavior of past, present, and future cohorts. In general, it is not possible to calculate budget-neutral deductions from the budget constraint of a single individual who retires before the target retirement age—an approach that dominates the related literature. Only for specific cases one can use this second approach but then one has to adjust the discount rate to the assumption about collective retirement. If there is only one deviating individual, then the right choice is the market interest rate while for a stationary retirement distribution it is the internal rate of return of the PAYG system. In this case, the necessary deductions are lower than under the standard approach. This is also true for retirement ages that fluctuate randomly around a stationary distribution. Various long-run developments (e.g., increases in life expectancy or permanent changes in the average retirement age) might cause challenges for the sustainability of the pension system. These developments, however, can only be dealt with by adequate adjustments to the basic pension formulas and not by the use of deduction rates. [ABSTRACT FROM AUTHOR]

Bulgarian pension system consists of three pillars. The first one functions on a pay-as-you-go principle and is a mandatory one, the second and third pillars are fully funded. The insurance into the second column is compulsory and that into the third one is voluntary. The unfavorable demographic trends in the country have an adverse effect on the pay-as-you-go part of the system. At the same time the minor accumulation of resources into the second and third pillar makes the sustainability of the pension system under question especially in the long term. The current research is trying to put some light on this issue by following the reforms made in the recent years and the tendencies concerning the government decisions on each of the pillars of the pension system. The paper is structured in two parts. The first one focuses on the pay-as-you-go part of the system and the factors that influence its financial health. The second one concentrates on the current problems of the funded component of the pension system and the way it must be strengthened in the long term to effectively support the dominant state pension system. Further reforms are needed to raise the sustainability of the pension system as a social security structure in the long term. [ABSTRACT FROM AUTHOR]

Bulgarian pension system consists of three pillars. The first one functions on a payas- you-go principle and is a mandatory one, the second and third pillars are fully funded. The insurance into the second column is compulsory and that into the third one is voluntary. The unfavorable demographic trends in the country have an adverse effect on the pay-as-you-go part of the system. At the same time the minor accumulation of resources into the second and third pillar makes the sustainability of the pension system under question especially in the long term. The current research is trying to put some light on this issue by following the reforms made in the recent years and the tendencies concerning the government decisions on each of the pillars of the pension system. The paper is structured in two parts. The first one focuses on the pay-as-you-go part of the system and the factors that influence its financial health. The second one concentrates on the current problems of the funded component of the pension system and the way it must be strengthened in the long term to effectively support the dominant state pension system. Further reforms are needed to raise the sustainability of the pension system as a social security structure in the long term. [ABSTRACT FROM AUTHOR]

In recent business practice, firms, to fulfill their IT requirements, are using both dedicated "on-premise" capacity infrastructure and "on-demand" capacity requirements provided by companies such as AWS, OpenStack, and VMware. In this research, we analyze the scenario where a business first invests in "on-premise" (or in-house) capacity and also procures the excess demand requirements through the public cloud provider utilizing the pay-as-you-go pricing model. We study the impact of factors such as demand correlation in buyers' market and demand load profile on the capacity decision. We find various cloud computing strategies and link them with real-life business practices. [ABSTRACT FROM AUTHOR]

Highlights • We measure the welfare effects of switching costs through permanence clauses in the mobiles market in Colombia (2014-2016). • We find that fixed-length terms in telecommunications contracts are associated to higher markups in the mobile terminal. • Permanence clauses generate significant switching costs that derive in lower consumer surplus during the period of analysis. • Firm surplus increased due to the elimination of permanence clauses. The variation was perceived mostly by retail sales firms. • We find that in the absence of permanence clauses, consumers would substitute away from prepay to postpay plans. [ABSTRACT FROM AUTHOR]

My intro for that piece read, "While journalists obsessabout media raids by the Australian Federal Police afortnight ago, much of the public is sceptical, trustingthe security services more than the fourth estate in anera of fake news and activist reporting." I used a more recent example in my June 17 column, againinvolving the AFP, raids on journalists and a story thatwas clearly in the public interest but damagingpolitically. In my view the media's case has not been helped byoverheated rhetoric suggesting Australia is on the pathto totalitarianism because of two raids on journalists,even on successive days. Nor do I buy the idea that conservative governments suchas those of Howard and former prime minister Tony Abbottrepresent a particular threat to the media. [Extracted from the article]

Abstract Cloud computing as a model to deliver distributed resource and services on the pay-as-you-go policy has become increasingly popular for all organizations including industry. However, the inherent dynamicity in this environment makes it prone to various types of performance problems which introduce many challenges in the area of distributed resource management. Advances in the big data learning approaches can bring the opportunity for a data aware dynamic management of resources in the cloud. The collected data from the performance indicators of the system can be a valuable source of information to identify unusual behaviors in the resource consumptions or application performance. Different types of problems can cause the performance degradations at VM or system level. System administrators are overwhelmed with the huge amount of data to be analyzed to find the problems and overall health of the system. In this paper, we argue that a better selection of dynamic resource scaling policies can be employed for better performance by predicting the anomalies in the system and narrowing down the possible cause of the anomaly to one of the attributes of the system. Therefore, we propose a 2-level cause aware auto-scaling framework which leverages two types of resource management solutions, horizontal and vertical, as the corrective actions when the performance is degraded. We show the effectiveness of vertical scaling strategy as a quick solution for cases that a VM is exposed to some type of the local anomaly, while the horizontal scaling solutions can be used for system wide anomaly to add new VMs in the system. Moreover, our data analysis module can predict anomalies to give sufficient time to the scaling system to make an effective scaling decision. The proposed unsupervised anomaly detection module leverages a new updating strategy for renewing the models which considers the changes in the state of the system to reduce the overhead of recurrent model trainings. We have performed a comparison of the proposed framework with an approach which is used by several popular cloud providers to show the advantage of mixing the multi-level auto-scaling with the knowledge of anomaly detection analysis in resolving performance problems in the cloud. Highlights • Proposing an anomaly prediction module to detect future performance problems. • Applying unsupervised Isolation-Trees based approach with a new strategy for model updating. • Investigating types of performance anomalies including CPU and memory bottlenecks. • Proposing a two-level auto-scaler by categorizing anomalies into two levels local and global. • Extending CloudSim simulator by adding characteristics of the elastic VMs. [ABSTRACT FROM AUTHOR]

There are three main challenges facing pay-as-you-go public pension systems. First, pension systems need to provide an adequate income for pensioners in the retirement phase. Second, participants wish a fair level of benefits in relation to the contributions paid. Last but not least, the pension system needs to be financially sustainable in the long run. In this paper, we jointly analyse the adequacy, fairness and sustainability of both defined benefit and defined contribution schemes. Finally, risk sharing mechanisms, that involve changes in the key variables of the system, are designed to restore the financial sustainability while we study their consequences on the adequacy and fairness of the system. [ABSTRACT FROM AUTHOR]

The effects of a 90% reduction in mobile termination rates (MTRs) are evaluated over the period between 2009 and 2017 in South Africa. Prepaid prices and quality-adjusted postpaid prices declined by over 40%. However, only approximately 30% of the decline in prepaid prices and 60% of the reduction in quality-adjusted postpaid prices can be explained by lower MTR costs. On-net and off-net prepaid prices converged as MTR costs dropped. Regulators concerned about high retail prices and differences between on-net and off-net prices should reduce MTRs. [ABSTRACT FROM AUTHOR]

Instead of upfront investment in infrastructure, many organizations have moved towards cloud computing to fulfill their computational resource needs, as cloud computing model provides ondemand, scalable resources on pay-as-you-go basis. In cloud computing, it is not possible to predict the volume of user requests in the future, so cloud computing models must be capable of handling thousands of concurrent user requests. An efficient load balancing technique plays an important role in distributing the workload evenly among the servers, so that no server is overloaded or underloaded. The paper proposes a load balancing and task scheduling algorithm, Dynamic VM Load Balancer (DVLB). While making a load balancing decision, DVLB takes both the server processing power and request (task) processing requirement into consideration. The algorithm is implemented using cloudsim 3.0.2 tool, and its performance is compared with two existing load balancing methods, Round Robin and Equally Spread Current Execution (ESCE) algorithm. [ABSTRACT FROM AUTHOR]

Many current computing systems such as clouds and supercomputers charge users for their resource usages. A user’s demand is often changing over time, indicating that it is difficult to keep the high resource utilization all the time for cost efficiency. Resource sharing is a classical and effective approach for high resource utilization. In view of the heterogeneous resource demands of users’ workloads, multi-resource allocation fairness is a must for resource sharing in such pay-as-you-use computing systems. However, we find that, existing multi-resource fair policies such as Dominant Resource Fairness (DRF), implemented in currently popular resource management systems such as Apache YARN [4] and Mesos [23] , are not suitable for the pay-as-you-use computing systems. We show that this is because of their memoryless characteristic that can cause the following problems in the pay-as-you-use computing systems: 1). users can get resource benefits by cheating; 2). users might not be able to get the total amount of resources that they are entitled to in terms of their resource contributions. In this paper, we propose a new policy called H-MRF, which generalizes DRF and Asset Fairness with the long-term notion. We show that it can address these problems and is suitable for pay-as-you-use computing systems. We have implemented it into YARN by developing a prototype called MRYARN. Finally, we evaluate H-MRF using both testbed and simulated experiments. The experimental results show that there are about $1.1\sim 1.5$ sharing benefit degrees and $1.2\times \sim 1.8\times$ performance improvement for users with H-MRF, better than existing fair schedulers. [ABSTRACT FROM AUTHOR]

Proactive subscriber churn management strategies of mobile network operators (MNOs) require that steps are taken to keep customers before they hand over a formal notice of termination to their provider. Therefore, several studies have analyzed how MNO customers who gave a termination announcement differ from individuals who did not communicate this message. However, no work has examined such differences among subscribers who recently switched to another tariff of their MNO. Therefore, this paper explores socio-demographic, service consumption and tariff change differences between contract cancellation “announcers” and “non-announcers” in a sample of 1810 postpaid customers who had changed their rate plan not long ago. Cancellation announcers were more likely to be males who decreased their mobile voice consumption after their tariff switch, had already attempted to churn in the past, had moved from an unmetered to a metered rate type, paid higher monthly bill amounts and received no discounts on their current rate plan that was introduced on the market some time ago. Among subscribers who gave a termination notice, early (late) cancellation announcers were more likely to be older (younger) customers with a growing (shrinking) SMS consumption after their tariff switch, had not attempted (had already tried) to leave their current MNO in the past, and were in a rate plan that was (not) recently introduced. The findings contribute to the literature on mobile customer retention and have implications for practitioners and scholars. [ABSTRACT FROM AUTHOR]

Many decisions are made daily based on the simple mental processing. This way of decision making is suitable for the simple personal daily issues. But when decisions are concerned with general and sensitive sectors, this way of decision making is unacceptable. Nowadays, Geospatial Information Systems help in making more accurate decisions in a lot of sections that would be built on accurate information by way of drawing maps and visualizing data to clearly judge which option is the best for that particular situation. This paper raises a framework that integrates the Geospatial Information Systems with the Hybrid Cloud Computing to let them work together and get greater powerful benefits via applying the concept of cloud computing to overcome the flaws related to the desktop GIS including the huge startup cost and the storage capacity and to provide the feature of location independence accessibility where the GIS can be accessed from anywhere and anytime. The hybrid cloud computing was picked to be integrated with the GIS to gain the elasticity and security of dealing with different types of data; private and public data. This integration is presented in three dimensions. The first one is architecture with seven segments that illustrate the main structure for the Hybrid Cloud GIS within a mix of private environment and public environment. The second one is the types of the participants and their workflow within the two environments. The last dimension is a case study for applying this integration in the health sector in Egypt. [ABSTRACT FROM AUTHOR]

Municipal solid waste (MSW) generation significantly outpaces growth in municipal recycling and this trend has substantial environmental, health and economic consequences. Several community and sociodemographic factors have been proposed to affect municipal recycling rates. Using a telephone and Internet-based assessment, we examined community-level recycling policies, practices and resources in 245 Massachusetts municipalities. We sought to determine whether these factors, along with important sociodemographic factors, significantly predicted average municipal recycling rates ( diversion rates ) over a 5-year period. Multiple regression analysis indicated that Pay-as-you-throw (PAYT) trash programs were the most significant factor positively predicting recycling rates. Conversely, communities having to pay for recycling services resulted in significantly lower average recycling rates. Providing residents with recycling information resulted in higher municipal recycling rates and several important demographic variables significantly predicted recycling rates. Implications of our findings are discussed in conjunction with community-level policies and practices to improve recycling rates. [ABSTRACT FROM AUTHOR]

The primary uses for cloud computing are to store data and share resources. The cloud has become a dominant and preferred method to store large amounts of data and enable the sharing of that data among several users. It also enables the use of pay-as-you-go pricing models. Today’s cloud computing environment has required data centers to increase the amount of available storage. There are two main concerns with cloud storage: data reliability and cost of storage. This paper discusses the issue of data recovery in case of a disaster in a Multi-Cloud environment. We propose a preventive approach for data backup and recovery aiming at minimizing the number of replicas and ensure high reliability for data before the disaster. The approach named Preventive Disaster Recovery Plan with Minimum Replica (PDRPMR) which is a cost-effective mechanism to reduce the number of replications in the cloud to be 1 or 2-replicas only without compromising the data reliability. The name PDRPMR originates from its preventive action checking of the availability of replicas and monitoring of denial of service attacks to maintain data reliability. Several experiments have been carried out to demonstrate that PDRPMR reduces the amount of storage space used by one third to two-thirds compared to typical 3-replicas replication strategies, which in turn reduces the cost of storage. [ABSTRACT FROM AUTHOR]

The incredible growth of telecom data and fierce competition among telecommunication operators for customer retention demand continues improvements, both strategically and analytically, in the current customer relationship management (CRM) systems. One of the key objectives of a typical CRM system is to classify and predict a group of potential churners form a large set of customers to devise profitable and targeted retention campaigns for keeping a long-term relationship with valued customers. For achieving the aforementioned objective, several churn prediction models have been proposed in the past for the accurate identification of the customers who are prone to churn. However, these previously proposed models suffer from a number of limitations which place strong barriers towards the direct applicability of such models for accurate prediction. Firstly, the feature selection methods adopted in majority of the past work neglected the information rich variables present in call details record for model development. Secondly, selection of important features was done through statistical methods only. Although statistical methods have been applied successfully in diverse domains, however, these methods alone without the augmentation of domain knowledge have the tendency to yield erroneous results. Thirdly, the previous models have been validated mainly with benchmark datasets which do not provide a true representation of real world telecom data consisting of noise and large number of missing values. Fourthly, the evaluation measures used in the past neglected the True Positive (TP) rate, which actually highlights the ability of a model to correctly classify the percentage of churners as compared to non-churners. Finally, the classifiers used in the previous models completely neglected the use of fuzzy classification methods which perform reasonably well for data sets with noise. In this paper, a fuzzy based churn prediction model has been proposed and validated using a real data from a telecom company in South Asia. A number of predominant classifiers namely, Neural Network, Linear regression, C4.5, SVM, AdaBoost, Gradient Boosting and Random Forest have been compared with fuzzy classifiers to highlight the superiority of fuzzy classifiers in predicting the accurate set of churners. [ABSTRACT FROM AUTHOR]

This paper analyzes the participation path of workers in the formal and informal sectors throughout their lives and their pension eligibilities, as well as how the social security scheme can change the aforementioned participation path. High levels of informality have impacts on the benefits that workers receive, especially their pension benefits. I use Argentinean panel data from 1995 to 2008 to construct a structural discrete choice model which estimates the population's labor path and their pension eligibilities. I find evidence that low-educated workers have difficulties to obtain a pension by the age of 65 and even by age 70. Policy experiments show that if the parameters are fixed as in the pay-as-you-go (PAYG) model, there is a slight reduction in the years worked in the formal sector and the percentage of workers who obtain a Full pension. If the pension requirements (minimum age and years contributing) are stricter, there is an increase in the years spent in the formal sector but it is not sufficient to achieve the benchmark level of pension coverage. If the requirements are looser, there is a reduction in the amount of time spent in formality to contribute up to the new threshold. [ABSTRACT FROM AUTHOR]

In recent years various domestic and international organisations have proposed financial coverage for the population as a whole. This does not mean that there is currently no coverage: aid in different countries extends to different levels. In this context a universal basic social benefit could be one way of responding to those international proposals. However, such a scheme might be too expensive to be viable, which might lead instead to partial benefits payable to non-workers being considered, as the group in most need of coverage. This paper seeks to analyse whether a model of financing can be found under which a basic minimum social benefit can be implemented in a way that is socially and financially viable and sustainable and can be maintained over time. Following the usual system for the distribution of budget allocations by public administrations, this model uses a multi-year period - in this case 12 financial years. Spain is presented as a case study, based on a number of forward-looking demographic and economic assumptions in which the various aid systems used in the country's autonomous regions are brought together to provide a minimum coverage. The main conclusion drawn is that the current level of contributions is sufficient to provide a viable, sustainable partial social benefit. However, a universal benefit would require a considerable increase in extraordinary contributions to meet its cost, though those contributions could be replaced in part by extraordinary state contributions or funding from other sources. [ABSTRACT FROM AUTHOR]

When outsourcing their logistics operations to transportation companies, manufacturers/retailers need to design a contract, under which payment can be made either in a lump sum or over time (i.e., per each delivery). This paper investigates how the payment method (i.e., type of contracts) impacts the transporter's delivery schedule by developing an analytical model based on the optimal control and game theories. Our findings show that the transporter's delivery schedule depends on the method of payment and the overall cost of hiring a transporter varies with the types of contracts. We provide theoretical explanations to these findings along with managerial implications. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we consider to improve scientific workflows in cloud environments where data transfers between tasks are performed via provisioned in-memory caching as a service, instead of relying entirely on slower disk-based file systems. However, this improvement is not free since services in the cloud are usually charged in a “pay-as-you-go” model. As a consequence, the workflow tenants have to estimate the amount of memory that they would like to pay. Given the intrinsic complexity of the workflows, it would be very hard to make an accurate prediction, which would lead to either oversubscription or undersubscription, resulting in unproductive spending or performance degradation. To address this problem, we propose a concept of minmax memory claim (MMC) to achieve cost-effective workflow computations in in-memory cloud computing environments. The minmax-memory claim is defined as the minimum amount of memory required to finish the workflow without compromising its maximum concurrency. With the concept of MMC, the workflow tenants can achieve the best performance via in-memory computing while minimizing the cost. In this paper, we present the procedure of how to find the MMCs for those workflows with arbitrary graphs in general and develop optimal efficient algorithms for some well-structured workflows in particular. To further show the values of this concept, we also implement these algorithms and apply them, through a simulation study, to improve deadlock resolutions in workflow-based workloads when memory resources are constrained. [ABSTRACT FROM PUBLISHER]

We examine how international transfers affect the welfare levels of a donor with a higher marginal propensity to save and a recipient with a lower marginal propensity to save when both countries adopt a pay-as-you-go (PAYG) pension system using a one-sector overlapping generations model. We demonstrate that in a dynamically efficient economy, except at the golden rule, when a per capita PAYG pension contribution of either a donor or a recipient increases marginally, the effect of the transfer on the donor's welfare can be reduced, whereas whether the effect of the transfer on the recipient's welfare is reduced is ambiguous. These results imply that the existence of a PAYG pension might hinder the effectiveness of the transfer on the donor's welfare, and the adoption of a PAYG pension system is likely to cause a weak transfer paradox in which both a donor and a recipient immiserize. Our results also suggest that the introduction of a PAYG pension system, which is used as a domestic policy instrument for intergenerational income redistribution, reduces the donor's incentive to make an international transfer to a recipient, which is a form of international income redistribution. [ABSTRACT FROM AUTHOR]

Now-a-days accuracy of databases is much more important, as it is primary and crucial for maintaining a database in current IT-based economy and also several organizations rely on the databases for carrying out their day-to-day operations. Consequently, much study on duplicate detection can also be named as entity resolution or facsimile recognition and by various names that focuses mainly on the pair selections increasing both the efficiency and recall. The process of recognizing multiple representations of the things with or in the same real world is named as Duplicate Detection. Among the indexing algorithms, Progressive duplicates detection algorithms is a novel approach whereby using the defined sorting key, sorts the given dataset, and compares the records within a window. So in order to get even faster results, than the traditional approaches, a new algorithm has been proposed combining the progressive approaches with the scalable approaches to progressively find the duplicates in parallel. This algorithm also proves that without losing the effectiveness during limited time of execution, maximizes the efficiency for finding duplicates. [ABSTRACT FROM AUTHOR]

Pay-as-you-consume, as a new type of cloud computing paradigm, has become increasingly popular since a large number of cloud services are gradually opening up to consumers. It gives consumers a great convenience, where users no longer need to buy their hardware resources, but are confronted with how to deal effectively with data from the cloud. How to improve the performance of the cloud platform as a consumer-centric cloud computing model becomes a critical issue. Existing heterogeneous distributed computing systems provide efficient parallel and high fault tolerant and reliable services, due to its characteristics of managing largescale clusters. Though the latest cloud computing cluster meets the need for faster job execution, more effective use of computing resources is still a challenge. Presently proposed methods concentrated on improving the execution time of incoming jobs, e.g., shortening the MapReduce (MR) time. In this paper, an adaptive scheme is offered to achieve time and space efficiency in a heterogeneous cloud environment. A dynamic speculative execution strategy on real-time management of cluster resources is presented to optimize the execution time of Map phase, and a prediction model is used for fast prediction of task execution time. Combing the prediction model with a multi-objective optimization algorithm, an adaptive solution to optimize the performance of space-time is obtained. Experimental results depict that the proposed scheme can allocate tasks evenly and improve work efficiency in a heterogeneous cluster1. [ABSTRACT FROM PUBLISHER]

In this paper we employ survival analysis methods to analyse the impact of driving patterns on distance travelled before a first claim is made by young drivers underwriting a pay-as-you-drive insurance scheme. An empirical application is presented in which we analyse real data collected by a GPS system from a leading Spanish insurer. We show that men have riskier driving patterns than women and, moreover, that there are gender differences in the impact driving patterns have on the risk of being involved in an accident. The implications of these results are discussed in terms of the ‘no-gender’ discrimination regulation. [ABSTRACT FROM AUTHOR]

Using a pay-as-you-go strategy, we allow for a community of users to validate or invalidate mappings obtained by an automatic ontology matching system using consensus for each mapping. The ultimate objectives are effectiveness - improving the quality of the obtained alignment (set of mappings) measured in terms of F-measure as a function of the number of user interactions - and robustness - making the system as much as possible impervious to user validation errors. Our strategy consists of two major steps: candidate mapping selection, which ranks mappings based on their perceived quality so that users are presented first with those mappings with lowest quality, and feedback propagation, which seeks to validate or invalidate those mappings that are perceived to be similar to the mappings already presented to the users for validation. The purpose of these two strategies is twofold: achieve greater improvements earlier and minimize overall user interaction. There are three important features of our approach: the use of a dynamic ranking mechanism to adapt to the new conditions after each user interaction, the presentation of each mapping for validation more than once - revalidation - because of possible user errors, and the immediate propagation of the user input on a mapping without first achieving consensus for that mapping. We study extensively the effectiveness and robustness of our approach as several of these parameters change, namely the error and revalidation rates, as a function of the number of iterations, to provide conclusive guidelines for the design and implementation of multi-user feedback ontology matching systems. [ABSTRACT FROM AUTHOR]

This paper studies the redistribution and welfare effects of increasing the flexibility of individual pension take-up. We use an overlapping-generations model with Beveridgean pay-as-you-go pensions and heterogeneous individuals who differ in ability and lifespan. We find that introducing flexible pension take-up can induce a Pareto improvement when the initial pension scheme contains within-cohort redistribution and induces early retirement. Such a Pareto improving reform entails the application of uniform actuarial adjustment of pension entitlements based on average lifespan. Introducing actuarial non-neutrality that stimulates later retirement further improves such a flexibility reform. [ABSTRACT FROM AUTHOR]

The rising level of long-term care (LTC) expenditures and their financing sources are likely to impact savings and capital accumulation and henceforth the pattern of growth. This paper studies how the joint interaction of the family, the market and the State influences capital accumulation and welfare in a society in which the assistance the children give to dependent parents is triggered by a family norm. We find that with a family norm in place, the dynamics of capital accumulation differ from those of a standard Diamond (Am Econ Rev 55:1126-1150, ) model with dependence. For instance, if the family help is sizeably more productive than other LTC financing sources, pay-as-you-go social insurance might be a complement to private insurance and foster capital accumulation. [ABSTRACT FROM AUTHOR]

ABSTRACT The aim of the article is to theoretically investigate if a pay-as-you-go (PAYG) pension system is sustainable in the presence of a declining population and increasing longevity of the retired generation. For this purpose, we use an overlapping generation model with endogenous fertility, endogenous longevity and human capital accumulation in a small open economy. We find that pensions will always increase as long as it is beneficial for parents to invest in human capital. Furthermore, we get the result that the ratio between pension benefits and the consumption of the young generation will strive to a positive limit value, and that a pure PAYG pension system will not run into any solvency problem due to a decreasing fertility rate or ageing. [ABSTRACT FROM AUTHOR]

In the traditional community-supported agriculture (CSA) model, members “pay up-front” for a seasonal subscription to the farm and receive, in return, a weekly box of farm-fresh produce. Long-term sustainability depends on high levels of member retention and/or recruitment. Low retention rates have led some CSAs to offer non-produce items, to allow customers to choose box contents, or to use a “pay-as-you-go” model. This research aimed to provide insight into the viability of a flexible pay-as-you-go CSA by examining member characteristics, motivations for joining and maintaining membership, and dietary behavior. An anonymous e-mail-linked survey was sent to current and former J&P Organics farm CSA subscribers. A total of 536 respondents were placed into 4 groups based on ordering frequency (ranging from weekly to fewer than 1 box per month). This study’s findings strongly indicate that a flexible pay-as-you-go CSA subscription model would increase CSA subscriber membership and possibly frequency of ordering, especially for those likely to order a box less frequently than every week but who in other ways (demographics, motivations, satisfaction levels, length of subscription) are similar to the traditional pay up-front subscriber. [ABSTRACT FROM AUTHOR]

This research focuses on the factors of customer loyalty in the service industry particularly in telecommunication industry and aims to solve the issues related to the prepaid mobile services. The research was conducted to evaluate the relationship between service quality, customer perceived value and customer trust against customer loyalty. Surveys are conducted using survey responses from a sample of 398 respondents. The result of this research indicates that there is a positive relationship between customer support service, service reliability, emotional value and customer trust with customer loyalty. The results are also compared with previous earlier findings and implications for future research are discussed. Suggestion was made to conduct future research using longitudinal evidence by evaluating the relationship among and in-between variables towards customer loyalty in service industry. [ABSTRACT FROM AUTHOR]

The study has taken twin objectives- to find the determinants of service providers and to report the problems the respondents are exposed to in accessing the prepaid mobile services in Agartala. Based on a pre-tested interview-schedule, a sample size of 183 respondents, the empirical results have indicated that the principal influencing factors in choosing a service provider include customer care & facility, network coverage, tariff plan & recharge facilities. A significant relationship has been established between the gender of the respondents and their choice of service provider. The decision for subscription is further significantly influenced by their experiences of unsatisfactory services. Policy implications are derived from the study and it acknowledges few limitations. [ABSTRACT FROM AUTHOR]

Improving access to sustainable energy services and reducing the carbon footprint and deforestation of developing countries presents a substantial challenge to the development industry. This paper aims to critically assess two prevalent business models emerging to meet this challenge: financial institution-technology provider partnerships and the one-stop-shop, pay-as-you-go (PAYG) model. The authors find that collaborations between financial institutions and energy providers need to address grey areas such as product quality standards, marketing, and post-sales services, and incorporate feedback loops to continually evaluate the performance of the partnership. Pay-as-you-go presents an intriguing business case to leapfrog more traditional energy access programmes. However, more robust results from the field need to be reported before the PAYG movement can claim success. Ultimately, collaborative and integrated actions by all stakeholders are needed to achieve universal energy access. [ABSTRACT FROM AUTHOR]

Duplicate detection is the process of identifying multiple representations of same real world entities. Today, duplicate detection methods need to process ever larger datasets in ever shorter time: maintaining the quality of a dataset becomes increasingly difficult. We present two novel, progressive duplicate detection algorithms that significantly increase the efficiency of finding duplicates if the execution time is limited: They maximize the gain of the overall process within the time available by reporting most results much earlier than traditional approaches. Comprehensive experiments show that our progressive algorithms can double the efficiency over time of traditional duplicate detection and significantly improve upon related work. [ABSTRACT FROM AUTHOR]

Attempts to replace pay-as-you-go pension schemes with private funded systems came to a halt in Central and Eastern Europe after 2005. However, more recently, the region has witnessed two belated reformers: the Czech Republic and Romania. Both countries decided to partially privatize pensions despite the rising tide of evidence concerning the challenges associated with the policy. We argue that while part of the domestic political elite remained supportive of private funded pensions, the difficulties experienced by earlier reformers and reduced support from International Financial Institutions led to the adoption of small funded pension pillars. Such cautious attempts at privatization might become more common in the future as large reforms have proven politically unsustainable. [ABSTRACT FROM AUTHOR]

Information and Communications Technology (ICT) has gone through different phases of development, and the world is witnessing the emergence of a new technology paradigm called cloud computing. Cloud computing has pervasive access, its usage is simple and utilities are offered in pay-as-you-use. It therefore has the potential to open up ICT penetration in education, transaction, collaboration, information dissemination and in other areas of the life of a modern man. The cloud ecosystem describes the complex system of interdependent components that work together to enable cloud services provided to user. This paper presents a critical analysis of the benefits and challenges posed by the adoption and usage of cloud computing. Also presented is the relationship between important stakeholders in the cloud ecosystem. The paper further proposes methods of optimizing the benefits of cloud computing while reducing the challenges that might occur due to its adoption. [ABSTRACT FROM AUTHOR]

It's been very tough competition among the various mobile service providers in all over the world. The Indian mobile market continues to be dominated by prepaid subscribers. There has been a massive growth rate of subscribers. Indian mobile market is one of the fastest growing markets and is forecasted to reach 868.47 million users by 2013. The availability of a number of subscriber options for consumers and varied tariff rates of each player, lead the consumers to switch between service providers. Everyday number competitors come with new and attractive promotional schemes and or services that has made possible to reduce the tariff rates at all time low, which directly or indirectly affect the consumers and it encourages customers to change the mobile service providers. With this reference the proposed study is designed to know the existing subscribers, their switching behaviour and most important factors contributing to their switching behaviour with the sample size of 400 customers in the region of north Gujarat. [ABSTRACT FROM AUTHOR]