Showing papers on "Service provider published in 2016"

Long-Term Care Providers and services users in the United States: data from the National Study of Long-Term Care Providers, 2013-2014.

Abstract: Long-term care services provided by paid, regulated providers are an important component of personal health care spending in the United States. This report presents the most current national descriptive results from the National Study of Long-Term Care Providers (NSLTCP), which is conducted by the Centers for Disease Control and Prevention's National Center for Health Statistics (NCHS). Data presented are drawn from multiple sources, primarily NCHS surveys of adult day services centers and residential care communities (covers 2014 data year); and administrative records obtained from the Centers for Medicare and Medicare Services (CMS) on home health agencies, hospices, and nursing homes (covers 2013 and 2014 data years). This report provides information on the supply, organizational characteristics, staffing, and services offered by paid, regulated providers of long-term care services; and the demographic, health, and functional composition of users of these services. Services users include residents of nursing homes and residential care communities, patients of home health agencies and hospices, and participants of adult day services centers. This report updates "Long-Term Care Services in the United States: 2013 Overview" (available from: http://www.cdc.gov/nchs/data/nsltcp/long_term_care_services_2013.pdf), which covered data years 2011 and 2012. In contrast, the title of this report and future reports will reflect the years of the data used rather than the publication year, in this case 2013 through 2014. A forthcoming companion product to this report, "Long-Term Care Providers and Services Users in the United States—State Estimates Supplement: National Study of Long-Term Care Providers, 2013–2014," contains tables and maps showing comparable state estimates for the national findings in this report, and will be available from: http://www.cdc.gov/nchs/ nsltcp/nsltcp_products.htm.

Dynamic Pricing in a Labor Market: Surge Pricing and Flexible Work on the Uber Platform

Abstract: In many markets, new technologies allow traditional jobs to be divided into discrete tasks that are widely distributed across workers and dynamically priced given prevailing supply and demand conditions. This "sharing" or "gig" economy represents a more flexible work system, and is most common in two-sided markets in which a firm acts as a platform to connect service providers and consumers. One prominent example of this is the ride-sharing company Uber, which connects riders and driver-partners, and dynamically prices trips using a system known as "surge" pricing. In this talk, I discuss the practical problems of designing such a dynamic pricing system, how that dynamic pricing coordinates workers who can now earn compensation on a flexible schedule, and more broadly how the "gig" economy is evolving and growing as a form of market organization.

A Systematic Mapping Study in Microservice Architecture

Abstract: The accelerating progress of network speed, reliability and security creates an increasing demand to move software and services from being stored and processed locally on users' machines to being managed by third parties that are accessible through the network. This has created the need to develop new software development methods and software architectural styles that meet these new demands. One such example in software architectural design is the recent emergence of the microservices architecture to address the maintenance and scalability demands of online service providers. As microservice architecture is a new research area, the need for a systematic mapping study is crucial in order to summarise the progress so far and identify the gaps and requirements for future studies. In this paper we present a systematic mapping study of microservices architectures and their implementation. Our study focuses on identifying architectural challenges, the architectural diagrams/views and quality attributes related to microsevice systems.

Dynamic Pricing and Energy Consumption Scheduling With Reinforcement Learning

Abstract: In this paper, we study a dynamic pricing and energy consumption scheduling problem in the microgrid where the service provider acts as a broker between the utility company and customers by purchasing electric energy from the utility company and selling it to the customers. For the service provider, even though dynamic pricing is an efficient tool to manage the microgrid, the implementation of dynamic pricing is highly challenging due to the lack of the customer-side information and the various types of uncertainties in the microgrid. Similarly, the customers also face challenges in scheduling their energy consumption due to the uncertainty of the retail electricity price. In order to overcome the challenges of implementing dynamic pricing and energy consumption scheduling, we develop reinforcement learning algorithms that allow each of the service provider and the customers to learn its strategy without a priori information about the microgrid. Through numerical results, we show that the proposed reinforcement learning-based dynamic pricing algorithm can effectively work without a priori information about the system dynamics and the proposed energy consumption scheduling algorithm further reduces the system cost thanks to the learning capability of each customer.

Measurement of Quality of Experience of Video-on-Demand Services: A Survey

Abstract: Video-on-demand streaming services have gained popularity over the past few years. An increase in the speed of the access networks has also led to a larger number of users watching videos online. Online video streaming traffic is estimated to further increase from the current value of 57% to 69% by 2017, Cisco, 2014. In order to retain the existing users and attract new users, service providers attempt to satisfy the user's expectations and provide a satisfactory viewing experience. The first step toward providing a satisfactory service is to be able to quantify the users' perception of the current service level. Quality of experience (QoE) is a quality metric that provides a holistic measure of the users' perception of the quality. In this survey, we first present a tutorial overview of the popular video streaming techniques deployed for stored videos, followed by identifying various metrics that could be used to quantify the QoE for video streaming services; finally, we present a comprehensive survey of the literature on various tools and measurement methodologies that have been proposed to measure or predict the QoE of online video streaming services.

Cost Aware Service Placement and Load Dispatching in Mobile Cloud Systems

Abstract: With proliferation of smart phones and an increasing number of services provisioned by clouds, it is commonplace for users to request cloud services from their mobile devices. Accessing services directly from the Internet data centers inherently incurs high latency due to long RTTs and possible congestions in WAN. To lower the latency, some researchers propose to ‘cache’ the services at edge clouds or smart routers in the access network which are closer to end users than the Internet cloud. Although ‘caching’ is a promising technique, placing the services and dispatching users’ requests in a way that can minimize the users’ access delay and service providers’ cost has not been addressed so far. In this paper, we study the joint optimization of service placement and load dispatching in the mobile cloud systems. We show this problem is unique to both the traditional caching problem in mobile networks and the content distribution problem in content distribution networks. We develop a set of efficient algorithms for service providers to achieve various trade-offs among the average latency of mobile users’ requests, and the cost of service providers. Our solution utilizes user's mobility pattern and services access pattern to predict the distribution of user's future requests, and then adapt the service placement and load dispatching online based on the prediction. We conduct extensive trace driven simulations. Results show our solution not only achieves much lower latency than directly accessing service from remote clouds, but also outperforms other classical benchmark algorithms in term of the latency, cost and algorithm running time.

A Scalable Algorithm for the Placement of Service Function Chains

Abstract: Network function virtualization (NFV) decouples software implementations of network functions from their hosts (or hardware). NFV exposes a new set of entities, the virtualized network functions (VNFs). The VNFs can be chained with other VNFs and physical network functions to realize network services. This flexibility introduced by NFV allows service providers to respond in an agile manner to variable service demands and changing business goals. In this context, the efficient establishment of service chains and their placement becomes essential to reduce capital and operational expenses and gain in service agility. This paper addresses the placement aspect of these service chains by finding the best locations and hosts for the VNFs and to steer traffic across these functions while respecting user requirements and maximizing provider revenue. We propose a novel eigendecomposition-based approach for the placement of virtual and physical network function chains in networks and cloud environments. A heuristic based on a custom greedy algorithm is also presented to compare performance and assess the capability of the eigendecomposition approach. The performance of both algorithms is compared to a multi-stage-based method from the state of the art that also addresses the chaining of network services. Performance evaluation results show that our matrix-based method, eigendecomposition of adjacency matrices, has reduced complexity and convergence times that essentially depend only on the physical graph sizes. Our proposal also outperforms the related work in provider’s revenue and acceptance rate.

Smart Cloud Storage Service Selection Based on Fuzzy Logic, Theory of Evidence and Game Theory

Abstract: Cloud platforms encompass a large number of storage services that can be used to manage the needs of customers. Each of these services, offered by a different provider, is characterized by specific features, limitations and prices. In presence of multiple options, it is crucial to select the best solution fitting the customer requirements in terms of quality of service and costs. Most of the available approaches are not able to handle uncertainty in the expression of subjective preferences from customers, and can result in wrong (or sub-optimal) service selections in presence of rational/selfish providers, exposing untrustworthy indications concerning the quality of service levels and prices associated to their offers. In addition, due to its multi-objective nature, the optimal service selection process results in a very complex task to be managed, when possible, in a distributed way, for well-known scalability reasons. In this work, we aim at facing the above challenges by proposing three novel contributions. The fuzzy sets theory is used to express vagueness in the subjective preferences of the customers. The service selection is resolved with the distributed application of fuzzy inference or Dempster-Shafer theory of evidence. The selection strategy is also complemented by the adoption of a game theoretic approach for promoting truth-telling ones among service providers. We present empirical evidence of the proposed solution effectiveness through properly crafted simulation experiments.

Scoping the Sharing Economy: Origins, Definitions, Impact and Regulatory Issues

Abstract: This report selectively draws on the systematic review of a large set of data sources, which is presented elsewhere, and comprises 430 secondary sources (Codagnone, 2016). The report also provides a critical overview of key analytical, empirical, and normative dimensions of the ‘sharing economy’. It reviews both the rhetorical and controversial debates currently surrounding the topics and the available empirical evidence in order to sharpen our understanding of relevant policy and regulatory issues. The broad umbrella term 'sharing economy' is critically assessed and a typology developed that identifies the commercial 'peer to peer' sharing economy as the main focus of both controversies and policy-relevant issues. Empirical evidence of the benefits and costs of the sharing economy and its implications for sustainability and employment is very limited and inconclusive, particularly as regards the European landscape. This critical review, hence, shows that, as yet, there are no unambiguous answers to some of the fundamental questions about the ‘sharing economy’. The available research is too limited and patchy to give us a comprehensive and coherent picture. This report’s main contribution is to clear some of the conceptual and empirical fog around the ‘sharing economy’ and to identify where possible answers might be found in the future. It is suggested that the definition of sharing platforms should focus on P2P activities, as most of the policy concerns are found there. These include regulatory and consumer protection issues resulting from the informal production of services, potentially unfair competition with formal B2C service providers, and questions related to dominance and market power of P2P platform operators as commercial businesses.

Interrelationships of risks faced by third party logistics service providers: A DEMATEL based approach

Abstract: This paper analyses the interrelationships between risks faced by third party logistics service providers (3PLs) in relation to one of its customers using DEMATEL. Novel analysis of both within and between risk categories and generation of threshold value to prioritize risks generate useful insights. Results show that arms-length relationship between the customer and the 3PLs has strong influence on other risks and there is a need for collaborative relationships between 3PLs and its customers. Moreover, analysis indicates that the 3PLs need to improve internal processes related to quality management, flexibility of its operations and also geographical coverage of their services.

Computing for rural empowerment: enabled by last-mile telecommunications

Abstract: Increasing economic and educational exposure, and promotion of global health and wellness can be achieved through the power of sharing knowledge, technology, and resources. ICT can play a key role in disseminating such knowledge across the world. But a digital divide exists between urban and rural/remote areas, which results in economic and social disparities across regions. Developing last-mile telecommunication technologies for rural/remote areas is a crucial aspect in providing computing and ICT services that can integrate millions of stakeholders in rural/remote areas globally into the digital age, particularly with the advent of cloud computing. This article focuses on the different aspects of providing last-mile rural telecommunication access such as interfering factors, technology options, and deployment trends. This article aims to guide service providers, industry practitioners, and local entrepreneurs with a technology-and-deployment-trend analysis to choose, deploy, and operate suitable telecommunication networks depending on the unique features of the rural/remote area. Our goal is to bring attention to accessible and affordable technologies with practical considerations.

Cloud-Based Commissioning of Constrained Devices using Permissioned Blockchains

Abstract: In this paper we describe a privacy-preserving method for commissioning an IoT device into a cloud ecosystem. The commissioning consists of the device proving its manufacturing provenance in an anonymous fashion without reliance on a trusted third party, and for the device to be anonymously registered through the use of a blockchain system. We introduce the ChainAnchor architecture that provides device commissioning in a privacy-preserving fashion. The goal of ChainAnchor is (i) to support anonymous device commissioning, (ii) to support device-owners being remunerated for selling their device sensor-data to service providers, and (iii) to incentivize device-owners and service providers to share sensor-data in a privacy-preserving manner.

After 30 years of dissemination, have we achieved sustained practice change in motivational interviewing?

Abstract: Aims Motivational interviewing (MI) is the most successfully disseminated evidence-based practice in the substance use disorder (SUD) treatment field. This systematic review considers two questions relevant to policymakers and service providers: (1) does training in MI achieve sustained practice change in clinicians delivering SUD treatment; and (2) do clinicians achieve a level of competence after training in MI that impacts upon client outcomes? Methods A systematic review was conducted and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, examining training outcomes for MI in the SUD treatment sector, and for clinicians working in a SUD treatment role. We determined a training method to have resulted in sustained practice change when over 75% of participants met beginning proficiency in MI spirit at a follow-up time-point. Results Of the 20 studies identified, 15 measured training at a follow-up time-point using standard fidelity measures. The proportion of clinicians who reached beginning proficiency was either reported or calculated for 11 of these studies. Only two studies met our criterion of 75% of clinicians achieving beginning proficiency in MI spirit after training. Of the 20 studies identified, two measured client substance use outcomes with mixed results. Conclusions A broad range of training studies failed to achieve sustained practice change in MI according to our criteria. It is unlikely that 75% of clinicians can achieve beginning proficiency in MI spirit after training unless competency is benchmarked and monitored and training is ongoing. The impact of training on client outcomes requires future examination

3D printing services: classification, supply chain implications and research agenda

Abstract: Purpose: The purpose of this paper is to identify and classify the available types of 3D printing services, with the scope of determining the potential implications that such services could have on the supply chains of manufacturing firms and creating a research agenda for future studies. Design/methodology/approach: The authors review the current literature on the potential supply chain impacts of 3D printing and evaluate the 3D printing services provided by 404 firms in selected European markets. Findings: The results show that 3D printing services form a rapidly evolving industry, with new service providers entering the market on a regular basis. Evidence from the European markets investigated suggests that services can be classified into three distinct categories: generative, facilitative and selective services. Research limitations/implications: This paper represents an attempt to take stock of a fastmoving and potentially paradigm-shifting market. The implications are dynamic as new applications, business models and techniques are continually being developed. Further studies are required to substantiate the findings. Practical implications: Three categories of 3D printing services that could significantly impact supply chain configurations of the future are proposed. Several issues specific to 3D printing services raised in the research agenda require further scrutiny and substantiation before services can reach their full potential. Originality/value: This paper provides an overview of the growing 3D printing services industry, highlighting how the market might change as additive manufacturing technology matures.

Discrete Distribution Estimation under Local Privacy

Abstract: The collection and analysis of user data drives improvements in the app and web ecosystems, but comes with risks to privacy. This paper examines discrete distribution estimation under local privacy, a setting wherein service providers can learn the distribution of a categorical statistic of interest without collecting the underlying data. We present new mechanisms, including hashed K-ary Randomized Response (KRR), that empirically meet or exceed the utility of existing mechanisms at all privacy levels. New theoretical results demonstrate the order-optimality of KRR and the existing RAPPOR mechanism at different privacy regimes.

Developing environmentally sustainable logistics. Exploring themes and challenges from a logistics service providers' perspective

Abstract: The purpose of this paper is to explore themes and challenges in developing environmentally sustainable logistical activities. The approach is explorative with a cross sectional design that takes advantage of ten case studies out of selected logistics service providers (LSPs) operating primarily in the Scandinavian countries. The findings illustrate the major themes by analyzing current and future activities in developing environmentally sustainable logistical activities. In addition, four categories of challenges are identified: customer priorities, managerial complexity, network imbalance, and technological and legislative uncertainties. It is concluded that there is a great need for a holistic perspective where LSPs and product owners together analyze and design future logistical setups. The suggested holistic and integrative model, building on a three-dimensional concurrent engineering framework, provides new opportunities for research. Further research is needed to improve the interrelationship between LSPs and their customers in the development of sustainable logistical solutions. This paper puts forward recommendations for the sustainable development of logistics by combining the results from the case studies with a review of related literature. This will be beneficial for managers and policy makers when they approach sustainable logistical challenges. The emergence and synthesis of themes and challenges are critical for a sustainable society.

Discrete distribution estimation under local privacy

Abstract: The collection and analysis of user data drives improvements in the app and web ecosystems, but comes with risks to privacy. This paper examines discrete distribution estimation under local privacy, a setting wherein service providers can learn the distribution of a categorical statistic of interest without collecting the underlying data. We present new mechanisms, including hashed k-ary Randomized Response (k-RR), that empirically meet or exceed the utility of existing mechanisms at all privacy levels. New theoretical results demonstrate the order-optimality of k-RR and the existing RAPPOR mechanism at different privacy regimes.

On-Demand Service Platforms

Abstract: An on-demand service platform connects waiting-time sensitive customers with independent service providers (agents) This paper examines how two defining features of an on-demand service platform -- congestion-driven delay disutility and agent independence -- impact the platform's optimal per-service price and wage Congestion reduces expected utility for customers and agents, which suggests that the platform respond by decreasing the price (to encourage participation of customers) and increasing the wage (to encourage participation of agents) These intuitive price and wage prescriptions are valid in a benchmark setting without uncertainty in the customers' valuation or the agents' opportunity costs However, uncertainty in either dimension can reverse the prescriptions: Congestion increases the optimal price when customer valuation uncertainty is moderate Congestion decreases the optimal wage when agent opportunity cost uncertainty is high and expected opportunity cost is moderate Under agent opportunity cost uncertainty, agent independence decreases the price Under customer valuation uncertainty, agent independence increases the price if and only if valuation uncertainty is sufficiently high

Outsourcing decisions in reverse logistics: Sustainable balanced scorecard and graph theoretic approach

Abstract: Reverse logistics has become an important issue for most of the organizations due to increased flow of product returns and growing concern for the environment, legislation, and corporate social responsibility. Reverse logistics activities include product collection, inspection and sorting, disposition (reuse, repair, remanufacture or recycle), and redistribution of products. One of the important decisions is whether such activities must be outsourced partly or all must be outsourced or nothing must be outsourced. The articles on the selection of third party reverse logistics service providers are abundant but the articles on outsourcing reverse logistics fully or partly are very limited. The proposed study develops a framework for outsourcing decisions in reverse logistics by using graph theoretic approach. The ability of graph theoretic approach to consider interdependencies and maintaining hierarchical relationship among attributes and sub-attributes makes it an attractive approach. The attributes and sub-attributes were selected by combining four traditional balanced scorecard perspectives i.e. stakeholder, internal business process, learning and growth, and finance with triple bottom line aspects of sustainability known as sustainable balanced scorecard. By considering sustainable balanced scorecard based attributes and sub-attributes, organizations can ensure their contribution toward sustainability even after outsourcing the reverse logistics activities. The proposed framework is illustrated by case example of a mobile manufacturing firm. Scenario based alternatives were developed and “outsourcing index” were calculated for all the alternatives by evaluating permanent function using graph theoretic approach. The best alternative was selected based on the “outsourcing index”. The proposed framework will help managers and practitioners in outsourcing reverse logistics decisions.

The biodiversity–ecosystem service relationship in urban areas: a quantitative review

Abstract: By 2050, up to 75% of people globally will live in cities. Despite the potential ramifications of this urbanization for ecosystem services (ES), and the importance of locally produced ES for the health and wellbeing of urban residents, syntheses addressing the underlying ecology of ES provision rarely include urban areas. Here, I conduct a quantitative review of urban ES studies in the ecological literature, synthesizing trends across the discipline. I also quantify the extent to which this work considers the organisms and ecosystem components responsible for ES provision using two approaches: assessment of biodiversity–ES relationships, and an adaptation of the service provider concept. The majority of urban ES studies were conducted in western, developed countries, and typically assessed a single service in a single city – largely ignoring ES synergies and tradeoffs, and cross-city comparisons. While several different ES are studied in urban ecosystems, the field is dominated by weather and climate-related regulating services, with assessments of cultural services particularly lacking. Most studies described a habitat type as the service provider; however, studies that considered the biodiversity–ES relationship were more likely to identify a specific functional group, community, or population as the key provider of an ES. The biodiversity–ES relationship itself was most frequently characterized as dependent on the composition of species, functional traits, or structures, rather than correlated with the magnitude of any specific biodiversity metric. While the study of ES in urban ecosystems is increasing, there exists considerable room for further research. Future studies would benefit by expanding the number and categories of ES assessed within and across cities, as well as broadening the geographical scope of urban ES research. Biodiversity–ES assessments in urban ecosystems would also benefit from an expansion of the biodiversity types considered, particularly regarding non-species based approaches, and consideration of non-native and invasive species. Synthesis Urban ecosystem services (ES) affect the health and wellbeing of over 3.5 billion people who live in cities. However, syntheses addressing ES provision rarely include urban areas. I conducted the first quantitative review focused explicitly on the ecology of urban ES, including the role of biodiversity in service provision. I found that studies typically measure only a single service in one city, precluding assessment of ES synergies, tradeoffs, and cross-city comparisons. I also found that while most studies attribute ES provision to a habitat or land-use type, studies that consider biodiversity-ES relationships are more likely to recognize a specific functional group, community, or population as the key provider of an ES.

Analyzing user perspective on the factors affecting use intention of mobile based transfer payment

Abstract: Purpose – This study makes an integrated approach in identifying the factors affecting usage intention of mobile-based payment services. Such services are being marketed aggressively by cellular service providers and are different from usual mobile-based banking. The study incorporates prominent factors like the technical characteristics, technology-specific characteristics, user-specific characteristics, and task-specific characteristics and others from published literature. The purpose of this paper is to highlight those factors which have significant impact on the adoption of such service so that the adoption rate can be increased. Design/methodology/approach – A nationwide primary survey was conducted using validated questionnaire requesting response for the factors obtained from published literature. In total, 196 respondents participated in the survey. Totally, 11 hypotheses were formulated and statistically tested for their significance in context to the study. Confirmatory study was on the signifi...

Linking service design to value creation and service research

Abstract: Purpose - The purpose of this paper is to develop a framework for understanding service design and how service design relates to central concepts within service marketing. Design/methodology/approa ...

Why are Customers Loyal in Sharing-Economy Services? A Relational Benefits Perspective

Abstract: Purpose – This study seeks to:(1) introduce a systematic taxonomy of relational benefits that drive consumers to select a service provider and then to maintain the relationship with them in sharing-economy businesses; (2) assess the relative strengths of these relational benefits in influencing consumers’ behavioral intentions on sharing-economy services; and (3) examine how commitment mediates the influence of relational benefits on customer loyalty in this context.Design/methodology/approach – This study first conducted a focus group discussion and then collected data from online surveys completed by 440 respondents in China. The study employed structural equation modeling to test the hypotheses.Findings – The findings of the study show that confidence and social benefits, as previous studies indicate, have significant and positive effects on commitment in sharing-economy services. Moreover, safety benefits, a new type of relational benefits discovered in sharing-economy services, also have significant effects on commitment. Furthermore, this study finds that commitment acts as the mediating mechanism, through which confidence, social, and safety benefits operate with respect to their effects on customer loyalty. Interestingly, special treatment benefits were found to have insignificant effects on commitment and loyalty in this context.Practical implications – This paper provides sharing-economy managers with insight on how to better create and sustain loyal relationships through the provision of relational benefits.Originality/value – First, this study provides a framework for incorporating relationship marketing and sharing-economy services. Second, this study takes the initial step to offer a clear view of why customers would like to be involved in the peer-to-peer relationship in the sharing economy and to explain how to strengthen the relationships between customers and the peer service providers.

Designing Password Policies for Strength and Usability

Abstract: Password-composition policies are the result of service providers becoming increasingly concerned about the security of online accounts. These policies restrict the space of user-created passwords to preclude easily guessed passwords and thus make passwords more difficult for attackers to guess. However, many users struggle to create and recall their passwords under strict password-composition policies, for example, ones that require passwords to have at least eight characters with multiple character classes and a dictionary check. Recent research showed that a promising alternative was to focus policy requirements on password length instead of on complexity. In this work, we examine 15 password policies, many focusing on length requirements. In doing so, we contribute the first thorough examination of policies requiring longer passwords. We conducted two online studies with over 20,000 participants, and collected both usability and password-strength data. Our findings indicate that password strength and password usability are not necessarily inversely correlated: policies that lead to stronger passwords do not always reduce usability. We identify policies that are both more usable and more secure than commonly used policies that emphasize complexity rather than length requirements. We also provide practical recommendations for service providers who want their users to have strong yet usable passwords.