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![Influence Area on Quality of Web Services In contrast to classical e-Markets that simply syndicate services (influence area 1 of fig. 1), StrikeIron operates all services on its own domain, having influence on the transaction flow (influence area 1) as well as on the complete runtime environment (influence area 2). This allows for a proactive optimization of runtime related quality factors before initiating feedback-based optimization [3] of Web services. To allow and to ensure interoperability, StrikeIron provides predefined Web application programming interfaces. Also, several directives for purposes such as authentification are imposed on the service-enabling ecosystem to achieve a basic level of manageability and security. In a verification routine before Web service publishing, StrikeIron automatically verifies whether the basic directives are followed. If not, feedback is given to the respective service enabler, who has to mend and to rerun the routine. StrikeIron's consumption-based feedback is mainly focused on service level management quality (availability, accessability, successability, response time). According to the company's own information (www.strikeiron.com), multiple consumption agents from remote geographic locations constantly ping, invoke and inspect the Web services and their responses on a minute-by-minute-basis and thus create a real-time picture of the respective quality parameters of their Web services. This information is compiled and reported to the service enablers in real-time to motivate performance optimization. Furthermore, an escalation routine is in place to alarm service engineers at StrikeIron or the respective service enablers to rapidly resolve problems at an early stage. If necessary, StrikeIron excludes underperforming services from its platform. Feedback like publicly displayed usage information is missing. Also, StrikeIron does not provide consumer-based mechanisms for reputation measurement or a disclosure of a service's relevance. This complementary feedback information is applied e.g. by Salesforce to provide orientation to the consumers and to motivate its service enablers to retouch a specific service in case of consumer-perceived underperformance.](profile/Ulrich-Scholten-3/publication/228365530/figure/fig2/AS:667854408019975@1536240307430/Influence-Area-on-Quality-of-Web-Services-In-contrast-to-classical-e-Markets-that-simply.png)
Influence Area on Quality of Web Services In contrast to classical e-Markets that simply syndicate services (influence area 1 of fig. 1), StrikeIron operates all services on its own domain, having influence on the transaction flow (influence area 1) as well as on the complete runtime environment (influence area 2). This allows for a proactive optimization of runtime related quality factors before initiating feedback-based optimization [3] of Web services. To allow and to ensure interoperability, StrikeIron provides predefined Web application programming interfaces. Also, several directives for purposes such as authentification are imposed on the service-enabling ecosystem to achieve a basic level of manageability and security. In a verification routine before Web service publishing, StrikeIron automatically verifies whether the basic directives are followed. If not, feedback is given to the respective service enabler, who has to mend and to rerun the routine. StrikeIron's consumption-based feedback is mainly focused on service level management quality (availability, accessability, successability, response time). According to the company's own information (www.strikeiron.com), multiple consumption agents from remote geographic locations constantly ping, invoke and inspect the Web services and their responses on a minute-by-minute-basis and thus create a real-time picture of the respective quality parameters of their Web services. This information is compiled and reported to the service enablers in real-time to motivate performance optimization. Furthermore, an escalation routine is in place to alarm service engineers at StrikeIron or the respective service enablers to rapidly resolve problems at an early stage. If necessary, StrikeIron excludes underperforming services from its platform. Feedback like publicly displayed usage information is missing. Also, StrikeIron does not provide consumer-based mechanisms for reputation measurement or a disclosure of a service's relevance. This complementary feedback information is applied e.g. by Salesforce to provide orientation to the consumers and to motivate its service enablers to retouch a specific service in case of consumer-perceived underperformance.
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Continuous optimization of value co-creation in networks of con-sumers and autonomous service enablers describes a major challenge to mediat-ing platform operators. In analogy to systems theory, we propose to introduce customizable feedback loops from the service-enabling ecosystem to the service enablers via the platform operator. Relevant feedbac...
Citations
... Apple even shows a strategy-driven restrictive product range management to avoid conflicts with its own base value contribution or with its own core products. Offerings like Google Voice were refused in July 2009 as it seemed to be in conflict with Apple's business model on mobile communication (Chen, 2009 Fischer et al. (2009;, this kind of information could stimulate the self-regulatory processes and emergence within the ecosystem, as complementors suffer from 'information asymmetry' (Williamson, 1981): Being positioned in a dyadic relation in the shadow of the platform owner or the next tier complementor constitutes a significant limitation of accessible market and customer information (information asymmetry). In consequence, applications may run out of phase with the actual market demand, risks of bull-whip effects are high. ...
... This requires a more sophisticated monitoring approach as well as dedicated analyses of actual demand, offering and consumption. Currently, research on the conceptual and technical aspects as well as on its respective implementation has been primarily addressed by Fischer et al. (2009;. In addition to these rather reactive patterns of control, platform owners further need to ( In conclusion, the awareness on the strategic importance of two-sided platform businesses is continuously increasing both in academic research as well as in industry practices. ...
Todays global economy migrates from vertically integrated enterprises towards specialized enterprises. In consequence, companies have to closely interoperate with partners and competitors to flexibly satisfy the customers demand for individual product and service solutions, speed and high levels of product and service quality. In order to cope with these challenges, many companies implement open modular platform concepts, enabling them to create platform ecosystems around their offerings. As a result, an increasing number of companies strives for platform leadership, which represents a companys strategic intention to provide the platform for other companies to build and deploy products and services. This process cannot be reduced to simple outsourcing decisions, but is part of renewed strategies of Open Innovation in an increasingly dynamic economic climate.
Opening up dedicated interfaces to external complementary development resources, however, changes the companys business model from formerly being single-sided to then being two-sided. Two-sided platform businesses, therefore, differ significantly in their economic rational and strategic behavior from non-platform businesses, as indirect network externalities become crucial to their success. Indirect network externalities imply that the more buyers are attracted to a platform, the more valuable the platform becomes to sellers. In reciprocity, the more sellers are attracted to it. In turn, the more sellers are offering innovative complementary products and services of suitable quality on top of the platform, the higher is the variety and the likelihood to match individual customer requirements. As a result, the broader the customer choice of complementary offerings on top of the platform is, the greater is the utility customers are able to derive from the platform and the greater the platforms profitability for the platform owner and its complementors. This requires platform owners to manage and sustain a continuous supply of external innovative complementary products and services to secure the profitability of their investments into an open modular platform concept. These insights indicate that the management of innovational efforts in open modular platform contexts is no longer confined to the legal boundaries of an organization.
Given the differences between platform and non-platform businesses, the present work argues that the peculiarities of two-sided platform business models require significant modifications to the platform owners innovation management and innovation process in order to achieve competitive advantage in dynamic platform markets. Correspondingly, the present work seeks to (a) explore the peculiarities of innovation management in two-sided platform businesses and (b) to develop a platform-based innovation management framework that guides the platform owner in holistically managing open innovation efforts within the context of its platform leadership strategy.
... INTRODUCTION Traditionally, IS development processes have been centrally orchestrated through a single process owner [1]. The distributed service-oriented computing model in Cloud computing, however, changes this paradigm: Increasingly, the formerly centralized process ownership is now shared between Platform-as-a-Service (PaaS) providers, their surrounding ecosystems of Software-as-a-Service (SaaS) providers, and service consumers [2,3,4,5]. By exposing dedicated interfaces, PaaS providers leverage external development resources and creativity to extend their service portfolio. ...
... platform provider) on other participants is limited. We identified the following complications [3,5,7]: ...
Platform-as-a-service offerings continuously gain importance as two-sided markets, offering Software-as-a-Service (SaaS) to the respective customers. Market success is achieved by platforms, which excel in shaping ecosystems of users and autonomous SaaS suppliers around their basic value proposition — and in controlling quality of service in function of customer requirements. In this paper, we suggest a notation for dynamic networks ‘DYNO’, designed to help platform providers in creating PaaS, optimized on their specific requirements. In addition, DYNO gives support in properly allocating control mechanisms to guarantee high quality of service. In a use-case we describe how business analysts and service engineers may use DYNO-models to conceive PaaS ecosystems.
... Within these fast-changing environments, it is critical to adapt quickly to new service offers or evolving consumer demands. Recent studies reveal that despite efforts to improve service quality in general, Quality of Service (QoS) provided over service platforms still needs to be improved [10]. In contrast to physical goods, which are out of reach to their producers after delivery, composite services allow for agile methods to optimize single services and to improve an intermediary " s service portfolio: 1) Service providers can influence services during delivery to adhere to promised levels of service quality [38]. ...
... collecting and interpreting feedback, can be automated [9]. In related work, we concluded that opportunities arising from these observations are at best partially exploited today [10],[33]. Intermediaries such as Salesforce.com ...
... In the context of service marketplaces, e-services can be described as the outcome of SVNs, which in turn are consumer-driven instances of a business ecosystem [10]. Core parts of a service " s description are quality parameters. ...
Intermediaries for e-services continuously gain momentum, powered by a materializing Internet of Services. However, quality of service still exhibits considerable shortcomings, as no structured process to enhance consumer satisfaction is available yet. To improve the match of delivered e-service quality and expected service quality on the consumer side, we develop a portfolio optimization process that integrates both, the consumer's as well as the intermediary's perspective. First, we introduce a toolkit for an e-service oriented gap analysis. Thereupon, we identify monitoring points to measure service quality gaps automatically. A subsequent aggregation of measured data into customized feedback information allows for applying the toolkit to continuously optimize e-service portfolios. Instantiated in the AGORA e-service market, we conclude with a report on our recent implementation results.
... The latter promises lean development activities in the ecosystem, meaning complementary developments to those of the platform operator [38]. According to [15, 40, 41], this kind of information could stimulate the self-regulatory processes and emergence within the ecosystem, as service providers suffer information asymmetry [42]: Being positioned in a dyadic relation in the shadow of the platform operator (or the next tier platform provider) constitutes a significant limitation of accessible market and end customer information (information asymmetry). In consequence, services may run out of phase with the actual market demand, risks of bull-whip effects are high. ...
... This requires more sophisticated monitoring and analysis of actual service demand, offering and consumption. Further research on these conceptual and technical aspects and respective implementation is done by [40, 41]. In addition to these rather reactive patterns of control, platform providers need to improve their proactive influence towards satisfaction of undersupplied consumer demand and on a macroscopic perspective to ensure goal congruence. ...
... According to [15, 40, 41] automatically generated information, specifically customized per service provider, could stimulate targeted self-regulatory processes and emergence within the ecosystem [42]. Details on reference architectures on monitoring and analysis can be found in [41]. ...
Modular platforms have become the centerpiece of collaborative value creation in customer-driven platform ecosystems. Platform ecosystems co-create the platform's value proposition and support its market adoption as the more complementors join the ecosystem to supply complementarities, the more valuable the platform becomes to customers due to a greater variety of choice. This poses new requirements on managing innovation in open platform environments. While academic research stresses the relevance of complementary innovation for platform success, it lacks, however, a concrete understanding of how platform operators can direct external innovational efforts in complex self-organizing ecosystems to co-create and deliver value while ensuring the overall quality, reliability, and consistency of the `whole' product. Based on case study results, this paper presents a categorization of control mechanisms currently applied in platform markets, enabling the platform operator to steer external complementary innovation within the context of a platform strategy. From that an overall platform-based innovation management process is developed.
... According to [6] " businesses should view themselves as a federation of capabilities that collaborate with other enterprises within a business ecosystem. " The resulting service value networks (SVNs) can hence be interpreted as an instantiation of a business ecosystem at the time of composite service consumption [7]. Successful platform providers depend on a robust, highly productive business ecosystem of complementary third party companies to co-create the platform's overall value proposition and to support its market adoption [8]. ...
... Once having adopted a platform strategy, its long-term success depends on continuous innovation and renewal of the business ecosystem [12], embracing continuous services portfolio optimization and provision of superior customer value. This embraces are two primary risk factors with respect to a robust evolution of such an ecosystem: a) information asymmetry (as service providers lack a comprehensive market view) [7,13,14] and b) goal incongruence with the platform provider's objectives. The risk of missed goal congruence, for example, is currently visible in Apple's app store through a bias towards " games " of low technical quality [15]. ...
... In summary, we identify three fundamentally different types of feedback information that has to be generated by the EA component (seefig. 3): Preference feedback, describing the consumers' response to offered composite services; Structural feedback, correlating composite services with their supplying value nets, i. e. the service ecosystem's topology; Interpreted feedback, giving each service and platform provider the information needed to exert their respective corrective action [7]. IV. ...
With the emergence of digital business ecosystems, new control mechanisms are required to sustainably ensure responsiveness on dynamically evolving consumer demand, as well as goal congruence with the platform providers' strategic goals. Based on system theoretical reflections, we propose a 3-layer reference architecture that collects data on service interactions, aggregates monitoring and feedback information and thus provides data basis for the said control mechanisms.
... Clusters of consumption bundles can be built and correlated with their respective revenue. Communicating customized feedback to each service enabler will stimulate the self-organizing forces in the service-enabling ecosystem (Fischer et al., 2009). ...
Global economy migrates from vertically integrated enterprises towards specialized enterprises interoperating to create end-to-end
value to customers. Value nets, emerging around the value proposition of a platform offer, have become the centerpiece of
collaborative value creation, altering the traditional supply chain approach, while keeping pace with changing customer demands.
This modular approach allows for sophisticated, cost efficient composite solutions provided by dynamic ‘consumerdriven supply
chains’. We characterize these supply chains ‘consumer-driven’ as the services complementing the platform offer are built
based on loosely coupled supply chains of services, provided by an ‘open pool of autonomous service providers’, which we will
refer to as ‘service-enabling ecosystem’. In this paper, we describe the challenges platform operators face in the light of
consumer-driven supply chains. In particular, we focus on how to orchestrate a complex self-organizing service-enabling ecosystem,
on how to steer a continuous service supply and explicitly, on how to ensure sustainable service quality optimization. Based
on a conceptual model of feedback control, which we introduce in pursuit of the methods of control engineering, we propose
a managerial control process for service-enabling ecosystems as well as a corresponding typology of control mechanisms for
improved consumer-driven service supply on top of a platform.
... The latter promises lean development activities in the ecosystem, meaning complementary developments to those of the platform operator [38]. According to [15, 40, 41], this kind of information could stimulate the self-regulatory processes and emergence within the ecosystem, as service providers suffer information asymmetry [42]: Being positioned in a dyadic relation in the shadow of the platform operator (or the next tier platform provider) constitutes a significant limitation of accessible market and end customer information (information asymmetry). In consequence, services may run out of phase with the actual market demand, risks of bull-whip effects are high. ...
... This requires more sophisticated monitoring and analysis of actual service demand, offering and consumption. Further going research these conceptual and technical aspects and respective implementation is done by [40, 41]. In addition to these rather re-active patterns of control, platform providers need to improve their pro-active influence towards satisfaction of undersupplied consumer demand and on a macroscopic perspective to ensure goal congruence. ...
... More scalable however would be information-driven methods. According to [15, 40, 41] automatically generated information, specifically customized per platform provider, could hence stimulate targeted self-regulatory processes and emergence within the ecosystem [42]. Details on reference architectures on monitoring and analysis can be found in [41]. ...
During recent years, modular platforms have become the centerpiece of collaborative value creation in customer-driven platform ecosystems. Platform ecosystems co-create the platform's value proposition and support its market adoption as the more complementors join the ecosystem to supply complementarities, the more valuable the platform becomes to customers due to a greater variety of choice. This poses new requirements on managing innovation in open platform environments. While academic research stresses the relevance of complementary innovation for platform success, it lacks, however, a concrete understanding of how platform operators can direct external innovational efforts in complex self-organizing ecosystems to co-create and deliver value while ensuring the overall quality, reliability, and consistency of the 'whole' product. Based on case study results, this paper presents a categorization of control mechanisms currently applied in platform markets, enabling the platform operator to steer external complementary innovation within the context of a platform strategy. From that an overall innovation management process is developed.
Service Networks (SNs) are open systems accommodating the co-production of new knowledge and services through organic peer-to-peer interactions. Key to broad success of SNs in practice is their ability to foster and ensure a high performance. By performance we mean the joint effort of tremendous interdisciplinary collaboration, cooperation and coordination among the network participants. However, due to the heterogeneous background of such participants (i.e., business, technical, etc.), different interpretations of the shared terminology are likely to happen. Thus, confusion may appear in the multi-disciplinary communication of SNs participants which in turn may lead to performance anomalies. To deal with such a problem, we propose a novel framework of bi-dimensional (business vs technical) performance metric indicators built on the basis of a systems thinking mindset. By using our framework, a holistic picture of the multiple dimensions and structure of SNs is provided, so that the interdisciplinary service participants have a correct understanding of the service scope and required resources in operation. Moreover, and most importantly, it provides a way to examine the performance traceability of the services within a SN.
The correlations between services, service vendors and service platform, as well as environmental factors weave the service system into a complex ecosystem. Dynamic factors introduce continuous co-revolution to the system. Seeing the dynamic mechanism of service ecosystem is the premise of reforming and controlling the system. A research framework is proposed in this paper, which is built to explore what are the changes of services, which indicators can be used to evaluate the effects and how the dynamic factors are spread. We clarify the definition as well as structure of service ecosystem based on recent work. Then a stereo network model for service ecosystem is built. Also, the usual dynamic activities of services are presented and discussed, and then the most crucial indicators of service ecosystem are summarized. Finally, a research framework is built, and the relevancy of the dynamic activities, correlations and indicators is given.
Modular platforms have become the centerpiece of collaborative value creation in platform ecosystems. Platform ecosystems co-create the platform’s value proposition and support its market adoption as the more complementors join the ecosystem to supply complementarities, the more valuable the platform becomes to consumers due to a greater variety of choice. This poses new requirements on managing innovation in open platform environments. While academic research stresses the relevance of external complementary innovation for platform success, it lacks, however, a concrete understanding to guide platform owners in directing external innovational efforts in coopetive platform ecosystems to co-create and deliver value while ensuring the overall quality, reliability and consistency of the ‘whole’ solution. Based on the challenges platform ecosystems place on innovation management, this paper explores and categorizes control mechanisms leading platform owners in the ICT industry have implemented to steer external complementary innovation efforts. From that an overall platform-based innovation management process is developed.
