Value creation in software service platforms

In order to benefit from operating an IT service platform (e.g., SaaS platform), platform providers need to find a way to keep their existing users and application services active sources of value. However, the understanding of how to achieve that is limited due to the newness of this kind of business. This paper investigates whether all stakeholders of the platform ecosystem can generate sufficient value when participating in the platform. As stakeholders, we consider application service users, service developers, and service platform providers. We also analyse the interrelationship between these stakeholders. The analysis outcome is a value creation model that allows the calculation of the stakeholders’ values. The model also helps inferring the relative impact of different factors on the evolution of values of the software service platform stakeholders. Our simulation results confirm that all stakeholders of a service platform mainly benefit from a growing installed base of application users. However, in a mature market, a large service variety mainly benefits the service platform provider, while the other stakeholders obtain a reduced increase in their benefits. In particular, the utility growth of application users becomes constrained as the benefit from new connections with other users decreases and the number of new services used decreases. Similarly, the revenue of service developer decreases, making service development less profitable. Therefore, we can state that not only a large fraction of the value creation goes to the platform provider but also that the software service ecosystem can collapse, if no mutually beneficial pricing of services is implemented.     

Converting freemium customers from free to premium—the role of the perceived premium fit in the case of music as a service

Freemium seems to be a promising solution for content providers to earn money now that Web 2.0 users feel entitled to free services and content services like Spotify generally accept this concept. Providers using freemium offer their service in free basic and paid premium versions. To prompt users to pay, a free version has fewer functions. However, no studies have yet investigated whether limiting features is the best strategy for converting users into paying customers, and, if so, how many functional differences there should be between free and premium versions. Therefore, our study aims to measure whether a free service’s limitations impact the evaluation of free and premium versions. Drawing on the Dual Mediation Hypothesis and the Elaboration Likelihood Model, we examined 317 freemium users’ survey responses. Our results indicate that companies providing freemium services can increase the probability of user conversion by providing a strong functional fit between their free and premium services.     

聚合模式下网约车市场的定价策略研究

针对聚合模式给网约车市场带来的收益分配和价格竞争问题,引入平台抽成和出行服务商服务差异刻画聚合模式下网约车市场的特征,构建了聚合平台和两服务商的斯坦伯格博弈模型,探讨了在聚合模式下网约车市场的定价均衡。随后引入平台补贴定价策略,分析了补贴策略对市场均衡定价以及聚合平台、出行服务商期望收益的影响。研究表明：聚合模式下出行服务商服务差异是影响平台抽成比例和网约车市场服务定价的重要因素,对聚合平台和出行服务商的期望收益有双向影响;平台对出行者的价格补贴提高了补贴前网约车市场的服务定价,导致平台抽成增加;采用合理的补贴定价策略可以有效提升出行服务商和聚合平台的收益,同时改进社会福利。     

Customer entrepreneurship on digital platforms: Challenges and solutions for platform business models

Drawing on the mixed methods of qualitative research and agent‐based simulation, this study examines: (a) how end‐users use digital platforms to become customer–entrepreneurs undertaking commercial activities on platforms; and (b) how platform providers can convert this customer entrepreneurship into a revenue stream. Considering that end‐users have traditionally been defined as passive and uncharged actors in platform business models, an in‐depth understanding of their commercial activities and the viable revenue model to monetize this emerging customer practice is warranted. Our qualitative study reveals that customer–entrepreneurs make substantial use of platform offerings to advertise their products; communicate with end‐consumers; and accept payments. These commercial activities are largely exercised for free on platforms, even though they could otherwise serve as a source of revenue. On this point, our simulation results identify two pricing models achieving the generation of nearly identical revenues over time. First, platform providers may charge both advertising and transaction fees, which maximize the survival of professional customer–entrepreneurs. Second, platform businesses may levy advertising fees only, which maximizes the survival of informal customer–entrepreneurs operating on a micro‐scale and part‐time basis. This study offers theoretical, methodological, and managerial implications for platform studies.     

A Scalable Pricing Model for Bandwidth Allocation

In this paper, we present a scalable pricing model for dynamic bandwidth allocation. Using simulation we demonstrate that service providers can achieve increased revenue as well as better resource utilization without compromising user specified levels of Quality of Service (QoS). Our model allows for increasing the revenue while maintaining an acceptable level of QoS, this is done by selecting an appropriate bandwidth allocation policy, to reduce the number of blocked users.     

Internet Service Pricing: Flat or Volume?

In this paper, we study the pricing of Internet services under monopoly and duopoly environments using an analytic model in which a service provider and users try to maximize their respective payoffs. We compare a few popular pricing schemes, including flat, volume-based, two-part, and nonlinear tariffs, with respect to revenue, social welfare, and user surplus. We perform a study of the sensitivity of these schemes to the estimation errors. In the duopoly situation, we formulate a simple normal form game between two service providers and study their equilibrium behaviors. Our main findings include: (1) the flat pricing generates higher revenue than the pure volume pricing when the elasticity of demand is low; (2) the volume-based pricing is better for society and users than the flat pricing regardless of the elasticity; (3) the market is segmented into two when one provider provides flat pricing and another provides volume based pricing.     

A cloud service selection model using improved ranked voting method

Cloud computing is an upcoming and promising solution for utility computing that provides resources on demand. As it has grown into a business model, a large number of cloud service providers exist today in the cloud market, which further is expanding exponentially. Many cloud service providers, with almost similar functionality, pose a selection problem to the cloud users. To assist the users in the best service selection, as per its requirement, a framework has been developed in which users list their quality of service (QoS) expectation, while service providers express their offerings. Experience of the existing cloud users is also taken into account in order to select the best cloud service provider. This work identifies some new QoS metrics, besides few existing ones, and defines it in a way that eases both the user and the provider to express their expectations and offers, respectively, in a quantified manner. Further, a dynamic and flexible model, using a variant of ranked voting method, is proposed that considers users' requirement and suggests the best cloud service provider. Case studies affirm the correctness and the effectiveness of the proposed model. Copyright © 2016 John Wiley & Sons, Ltd.     

Modeling online service discontinuation with nonparametric agents

The internet and world wide web are an increasingly important resource, both as a market and as an information source, to both individual users and business entities. An estimated 120 million active web users exist in the United States alone. Access to these electronic marketplaces and information sources is accomplished through either a direct internet connection or through a service provider. Internet service providers (ISPs) enable internet and web access for most of these users either via dial-up modems (62.2 percent), or DSL connections (17 percent). Customers of ISPs frequently switch or discontinue service. The model selection perspective is used to extend previous work in this area through the development of a multi-agent system with neural network wrappers. The nonparametric (neural network) agents identify over 92 percent of those users that either stop or change service, which is a 15 percent increase over previous models.     

Pricing and brokering services over interconnected IP networks

In this paper we consider an IP-based communication platform, characterized by a novel architectural model where barrier-free business and market interactions can be performed. We assume that the network is able to deliver application services which need of network service performance guarantees. In this scenario, we present the concept of the network commodity that is traded in the marketplace among network service providers, application service providers and customers. Moreover, we use this concept to define a new usage-based tariff model. Then, we especially focus on the activity of the so-called Network Resource Brokers, which have the goal of finding the end-to-end inter-domain path to deliver an application service that maximizes the users' benefit, in terms of price and perceived service level. In this regard, we present a QoS-and-price based inter-domain routing algorithm, analyze its computational complexity, and show its effectiveness in a selected simulation scenario.     

On web user tracking of browsing patterns for personalised advertising

On today’s Web, users trade access to their private data for content and services. App and service providers want to know everything they can about their users, in order to improve their product experience. Also, advertising sustains the business model of many websites and applications. Efficient and successful advertising relies on predicting users’ actions and tastes to suggest a range of products to buy. Both service providers and advertisers try to track users’ behaviour across their product network. For application providers this means tracking users’ actions within their platform. For third-party services following users, means being able to track them across different websites and applications. It is well known how, while surfing the Web, users leave traces regarding their identity in the form of activity patterns and unstructured data. These data constitute what is called the user’s online footprint. We analyse how advertising networks build and collect users footprints and how the suggested advertising reacts to changes in the user behaviour.     

基于可信第三方实现多云平台的交互和选择

随着云计算商业模式的成功推进,形成了三大主流的云计算服务模式:平台即服务、软件即服务和基础架构即服务。传统行业的供应商纷纷加入云计算的队伍。但由于激烈的竞争环境,使得云计算的标准化道路举步维艰,致使跨平台的交互和移植难以实现。同时,由于对不同的云平台没有形成统一可信的评价标准,使得众多的平台服务让用户无从选择。本文通过具体分析各种应用场景对跨平台服务的需求,得出构建"跨平台即服务"模式的必要性和必然性,提出利用可信第三方来实现"跨平台即服务"模式,给出跨平台的数据交互和移植行为在可信第三方监控下的规范化流程,并提出以可信第三方为中心的云平台安全和信誉评价标准,为企业选择合适的云平台提供参考。     

Performance issues and performance analysis tools for HPC cloud applications: a survey

Cloud Computing is an eminent emerging technology that surpasses Grids from their IT resource administrations and arduous Grid middleware solutions. At present, users could access an abundant number of pre-defined cloud services or run their programs on demand as a pay-as-you-go processing model without much distribution problems. In addition, the IT business market has pumped enough revenue for establishing salient common-use cloud solutions. Despite adequate researchers have been involved in the cloud development, scientific application developers are still reluctant to execute their applications in the cloud due to the performance concerns, such as, scalability, availability, and service level agreement violations of the cloud providers. In this paper, a survey of various High Performance Computing (HPC) applications and possible performance concerns while executing applications in cloud is presented. Pointing out the need for Performance Analysis (PA) tools, this paper focuses on the study of cloud-based PA tools in detail. This paper could leverage HPC application developers to cope with the performance issues and to best utilize the available performance analysis tools of clouds.     

移动云计算中基于协作式博弈模型的资源分配方案

提出一种基于协作式博弈的资源分配方案。首先, 在服务提供商创建长期可用预留资源公用库完毕后, 通过一种访问控制机制为用户提供移动应用服务, 提出一种优化算法实现访问控制的最优决策; 其次, 提出一种协作式博弈模型进行利益分配, 在服务提供商建立合作后, 通过使用资源公用库而获得的运营收入, 在服务提供商之间进行分配博弈。仿真实验结果表明, 该方法是有效的, 能够帮助服务提供商就容量提升制定最优策略, 以实现利益最大化。     

IaaS云服务定价机制的仿真研究

定价机制是影响云计算用户利益和云服务提供商收益的关键因素。本文以IaaS云服务定价机制为研究对象,首先将IaaS云服务定价机制分为固定定价和动态定价2大类,其中固定定价细分为即用即付费和预订定价2种,从理论上分析2类定价机制对IaaS云服务提供商收益的影响;然后,分别建立即用即付费和预订定价机制下IaaS云服务提供商的收益模型,并用启发式算法构建动态定价机制下IaaS云服务提供商的收益模型;最后,基于Repast Simphony建立多主体仿真模型,比较分析3种不同定价机制下IaaS云服务提供商的收益。研究结果表明,随着服务时长和顾客数量的增加,动态定价机制更能为IaaS云服务提供商带来更多收益,同时IaaS云服务提供商可以通过改变服务等级和资源价格等相关参数,改变顾客行为,使顾客数量增加,从而提高收益。     

考虑产能需求方交期和价格敏感的产能分享平台定价策略

基于双边市场理论,考虑产能分享双边市场具有网络外部性特性,同时考虑产能需求方对加工交期和价格敏感,研究垄断型制造业产能分享平台的定价策略.首先,建立平台和双边用户的两阶段决策模型;然后,通过计算求解探索了注册费和交易费收费模式下的平台均衡利润,并分析了交叉网络外部性等外生变量对各方决策和平台利润的影响.研究发现:注册费模式下的平台均衡利润大于固定交易费模式下的平台均衡利润;两种定价模式下的平台利润与双边用户的网络外部性均正相关,与产能需求方的交期预期偏差均负相关,与产能需求方的产能价格预期均正相关;产能需求方的交期敏感度在实际交期早于或晚于预期交期时对平台利润有不同影响,产能需求方的产能价格敏感度在产能实际价格低于或高于预期价格时对平台利润也有不同影响.     

云计算弹性评测模型的研究与实现

当前,越来越多的企业开始将自己的核心业务与数据迁移到云上,其中很多业务需要相应的弹性服务来应对负载的实时变化,因此对弹性的评测正变得越来越重要,然而当前缺少一种较为全面的弹性评测方法。为解决以上问题,从资源分配、QoS、资源配置时间等多个角度,对云计算的弹性进行较为全面的分析,提出适用于供应商和用户两个角度的评测方法。在已有基础上,提出资源分配、资源配置时间两个方面的计算模型,并对现存的罚金模型进行改进。最后,在CloudStack云平台上,使用auto-scaling和scale-out两种弹性扩展策略,以TPC-W为负载验证了所提方法的有效性。     

类电子商务模式的CNERN数据资源管理与服务信息平台

国家生态系统观测研究网络(National Ecosystam Research Network of China, CNERN)平台的数据资源管理与服务模式与开放式电子商务平台架构存在很大的相似性, CNERN 基于 B2B2C 电子商务模式构建了数据资源管理与服务信息平台,有助于改善资源使用者访问和获取数据资源的体验,改进资源提供者进行数据资源管理及数据资源服务的效率。本文分析了数据资源特点,介绍了数据资源内容,详细分析了信息平台架构、系统组成与功能, 介绍了 CNERN 信息平台如何对多方异地管理、异构存储、不同开放服务方式的数据资源进行类似电子商务模式的规范化管理及自动化服务的整体解决方案。     

充分发挥电网企业优势 加快拓展基于多能互补的综合能源服务业务

在当前能源转型和电力体制改革的新形势下,电网企业转型开展综合能源服务是必然选择。同时,随着能源互联网技术发展,使得能源之间互联、能源和信息融合进一步加强,为发展综合能源服务提供了可能。电网企业开展综合能源服务顺应客户需求,市场渣力巨大,是未来重要的利润増长点。如何充分发挥电网企业的优势,运用互联网思维,促进多种新能源的模化利用,将多种能源的源、网、荷、储深度融合,拓展出种类丰富的新型商业模式,为用户量身定制能源产品和服务搭配方案,是当下电网企业转型综合能源服务商考虑的首要问题。本文提出了一种适用于IES的扩展ewton－Raphson综合能源系统稳态多能流计算方法,构建综合能源系统多异质能流统一调度模型,进一岁构建智慧能源综合管理平台。将当下电力市场改革环境下实施的较为成功的商业模式与综合能源平台有机结合,可拓展出种类丰高的新型商业模式,进而组成一个从生产到消费再到增值服务的整个综合能源产业链。