Business Model Innovation 2010
Content
Business Model Innovation in the Digital and New Media Economy Joachim Hafkesbrink
innowise research & consulting GmbH Bürgerstr. 15, 47057 Duisburg, Germany E-mail: [email protected], www.innowise.eu
Markus Schroll
innowise research & consulting GmbH Bürgerstr. 15, 47057 Duisburg, Germany E-mail: [email protected], www.innowise.eu
Abstract: This paper1 outlines the increasing challenges of Business Model Innovation in the Digital and New Media Economy. It describes drivers of change, impacts on the innovation and business landscape, consequences for business modeling and the innovation process, as well as the implications for organizational adaptation. It presents in-depth observations from empirical research on 12 business cases in the Digital and Media Economy in Germany.2 Our findings show that business modeling in the Digital Economy needs to be continuously cross-linked to the innovation process to adapt to the ever changing business environment. It becomes clear that Business Models in the Digital Economy need to be “open” so as to be able to continuously embed them into the firm’s surrounding communities, and to ensure knowledge transfer and learning. We will align our arguments with earlier research on Open Innovation [7, 9, 10, 11] and Innovation 3.0 - which we have earlier called “Embedded Innovation” [8] - taking a more practical view on the implementation of new Business Models. Keywords: Business Model Innovation, Innovation 3.0, Open Innovation, Ambidextrous Organization, Organizational Adaptation, Communities of Knowledge, Digital Economy, New Media Economy
Preprint of an article submitted for consideration at the TII-Conference „Innovation 3.0 – Challenges, Needs and Skills of the new Innovation Era“, Düsseldorf, 28-30 April 2010. 2 The research underlying this paper relates to several R&D projects, supported by the German Ministry for Education and Research (BMBF), the State Chancellery of North-Rhine-Westfalia and the EU: ‘Organizational Attentiveness as a Basis for Corporate Innovativeness (ACHTINNO)’ BMBF-Contract No. 01FH09003; ‘Competence Development and Process Support in Open-Innovation Networks of the IT-Industry through Knowledge Modeling and Analysis (KOPIWA)’, BMBF-Contract No. 01FM0770; ‘Integrated Tools to Enhance the Innovative Capabilities of Publishing and New Media Companies’ (FLEXMEDIA)’; BMBF-Contract No. 01FH09011; ‘Local.mobile.NRW – Development of Smart Location Based Services for Mobile Devices’, NRW-Contract No. 29 00 923 02; ‘Locally-based-TV: Development of an Intelligent Regional IPTV Platform in the Münsterland’; Contract No. 29 00 938 02.
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1 Introduction
The so-called ‘Digital & New Media Economy’ embraces all actors in digital value creation and publishing processes, such as multi-media agencies, e-commerce agents, interactive online marketing and mobile solutions providers, games developers, social media providers, new media publishers etc. Business modeling in this ‘melting pot’ is influenced by a multitude of drivers, including new enabling technologies, the rapidly changing demands and life-styles of ‘digital natives’, the convergence of markets and media etc.
Figure 1 Technology-/Media Convergence in the Digital Economy
The innovation landscape is characterized as being extremely “open and dynamic”. Ideation, design, development and implementation of innovations are embedded in a cross-meshed network of especially SMEs (“multi-agent systems”) that are in continuous dialogue with their surrounding communities [8]. The critical success factor in these ‘multi-agent systems’ is to develop sufficient “gravitational embedding force” to link them to ‘Communities of Knowledge’. Amongst these communities are
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•
•
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Communities of Affinity (CoA): continuous dialogue with prosumers and end-consumers (B2C) to catch up with new (design) ideas, demands, moods, fashions and business opportunities; Communities of Practice (CoP): collaboration with each other (B2B), and with micro firms or freelancers to flexibly enhance knowledge flows, primarily for design and co-development; Communities of Interest (CoI): experience exchange with innovating firms from the same and other sectors to benefit from crossover ideas and complementary knowledge, Communities of Science (CoS): dialogue with the scientists to absorb new technologies.
The learning cycles in innovation and business modeling with respect to the different communities in the Digital & New Media Economy are depicted in Fig. 2:
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Figure 2: Embedding into ‘Communities of Knowledge’ to boost Innovation 3.0 [8] These ‘multi-agent systems’ and related communities define the dynamic context of business modeling. The notion of “embeddedness” clearly stresses the point that setting up new business models is an ongoing task. For instance, if we look at most of the innovative Internet services that have emerged in the past years, we recognize that the initial business models behind them have been altered over time in many ways – in terms of changing the functionality for customers (“value proposition”); modifying the usability for, and interaction with, customers (“CRM”); or in terms of amending the basic financing mode (e.g. “ad-financing” versus “pay per transaction”). One may argue that these adjustments of business models are a routine adaptation process, since even in the “Analogue Economy” incremental improvements of such models occur on a routine basis. However, the innovation process in the Digital Economy is different in some basic respects, namely in the areas of (a) innovation infrastructure, (b) corporate innovation policy, and (c) organizational adaptation and culture: (a) Innovation infrastructure: Innovation activities of the Digital Economy are embedded in a “digitalized infrastructure” with numerous easy accessible and easy to adopt digital enabling technologies. These technologies unfold a huge potential for new products and services, since combining and linking them to each other becomes - ‘bit by bit’ - more easy. Thus, the Digital Economy is at the center of a melting process of transferring horizontal technologies into vertical markets (see Fig. 3):
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Demographic Change
Technology Knowledge Sources
Changing Life-styles Competition regulation
Globalisation Convergence of Markets
Telecommunication
Basic services ValueServices Distribution Add. Services
Patentlaws
Multi-agent system of Innovation Actors
Standards
Market for Contents
Media-Technologies
Content Generation Packaging Distribution Enduser Devices
Market for Content Packaging & Applications
Technology Transfer
Melting Kernel
Market Demand
Market for Transmission Carriers
IT-/Electronics
Parts Software Platforms Distribution Add. Services
Market for Hardware
Semantic Techn.
.. . .. . ... ...
(end-user devices etc.)
eCommerceLaw Digital Signature Act Institutional Framework (Governance)
Media Law
Market for ...
Internationalisation
Figure 3: The Digital Economy as the Melting Kernel from Horizontal Technologies to Vertical Markets (b) Corporate Innovation Policy: In the Digital Economy, the value of goods and services is based on knowledge, application know-how, experience and business model sovereignty. Following Figure 4, the firm’s knowledge management system has to turn information into competences, while developing appropriate explicit and implicit skills to manage the innovation process. Hence, as the melting kernel needs to fuse very different technologies, firms understood very early that continuous learning was the key to innovation. Competence accumulation in an extremely diversified technology landscape is not possible, however, within a single innovation entity. As Henry Chesbrough [3] put it, ‘Not all the smart people in the field work for us; we need to work with smart people inside and outside the company’ [cited in 14] – thus collaboration is the order of the day. Hence, firms learned that it is more important to know who disposes of desired competences than to own all those competences themselves. Therefore, a distinctive openness of organizational borderlines is the ruling governance mode for innovation [7]. A decisive element in the accumulation of competences, then, is establishing permanent links to the firm’s surrounding knowledge communities and in absorbing external knowledge [8]. To gain maximum effectiveness in terms of knowledge transfer, the innovating firm has to balance the community orchestration [12], because different stakeholders (like “prosumers”, “experts”, “innovators” ,and “researchers” as representatives of the surrounding communities of knowledge) usually only cover certain knowledge artifacts [8] exploitable for the firm. For example, “Innovators” from Communities of Interest typically dispose of in-depth knowhow and experiences in their business domain, as well as of implicit skills in
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running domain-related business models. “Experts” from Communities of Practice are linked through the mutual interest of solving certain problems. These “Experts” typically embrace specialized knowledge artifacts and knowhow in applying this knowledge to defined problems and experiences from related application cases. Thus they usually do not have competences in running decisive business models, since they remain upstream in the “knowledge supply chain”, and provide in-depth technical expertise. “Researchers” generally collect data and information and transform these artifacts into knowledge. Of course, many “Researchers” from Communities of Science also dispose of extensive know-how, especially those working in applied joint research projects with industry. Finally, “Prosumers” from Communities of Affinity usually participate in producing ideas or design artifacts in an open innovation process: they give information on product or service usage by providing feedback or they engage in idea contests. Here as well, we increasingly find “Experts” who dispose of decisive know-how in product/service usage and ‘content production’, which has to be considered as an important external source of knowledge.
Prosumers
Experts
Semantic Enrichment
Resear -chers
Innova -tors
information management
competence management
+ competence
„expertise “ „knowhow“
+ denotation
sovereignty expertise
+ exercise + application + context
experience
know-how
Knowledge
Information
„cognition“
+ syntax
data
characters
Valorizationlevel „explicit skills“ „implicit skills“
„ intellectual capital “
Source: inspired by Auer-Consulting (n.d.)
Figure 4: Evolution from Characters to Sovereignty: the Up- and Downstream Artefacts of Knowledge (c) Organizational adaptation and organization culture To enable collaborative learning as the main feature of corporate innovation policy, the organization has to adapt to changing environments on a continuous basis. Community orchestration in this sense means establishing organizational anchors into surrounding communities so as to ensure a balanced knowledge transfer and absorption. Since stakeholders from surrounding communities usually have different impetuses on knowledge (see again Fig. 4), they are also
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involved differently in the innovation process (see Fig. 5). ‘Prosumers’ predominantly provide information on product usage from the market perspective and thus new ideas that enter the innovation funnel more upstream. ‘Researchers’ are usually involved in ideation and design, in pre-competitive joint research, and also in the development of innovation projects. ‘Innovators’ usually are engaged in the phase of development and production as co-operation partners. ‘Experts’ are – depending from their asset specifities - participating throughout the innovation process, predominantly from ideation to development:
Co-ideation
Co-design
Co-development
Co-production
Experts
Innovators
Prosumers Researc hers
Figure 5: Involvement of Various Stakeholders in the Open Innovation Process
To gain a proper “community orchestration”, the organization has to develop sufficient gravitational embedding force to establish effective and efficient relationships to knowledge communities. Thus, for a long time organizational change has been described as an important source of competitive advantage [13]. In the recent debate about ‘organizational renewal’, the main focus has been on “dynamic capabilities” [17] and “ambidextrous organizations” [18]. Accordingly, Teece et al. define the dynamic capabilities of a firm as ‘it’s ability to integrate, build, and re-configure, internal and external competences to address rapidly changing environments’ [17]. In more detail, the different attributes or pre-dispositions of organizational renewal capacities are discussed as “the ability to overcome established routines by self-organization and organizational renewal” [1], and being able “to organize for constant change and to establish collective organizational learning to continuously reinvent the company's core business processes” [16]. In this context, “Organizational Learning” is recognized as the “ability to maintain a continuous process of adjustment of search rules, attention rules, and goals of the
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organization” [1], or the “ability to undergo a continuous process of experimentation, adaptation and learning to pro-actively define the business environment” [2]. A relatively new issue in organizational adaption research is the notion of an “ambidextrous organization” [6, 18], which is defined as an organization’s ability to reconcile explorative and exploitative activities simultaneously” [6]. Ambidexterity is more or less a re-conceptualization of the discourse on ‘dynamic capabilities’ explicitly considering the necessity of flexibility and stability modes of an organization. The core question that ambidexterity seeks to answer is: “How are dynamic capabilities – the organization’s learning mechanisms – shaped in ambidextrous organizations in order to cope with contradictory environmental demands?”[6]. If we transform this question to the management of business model innovation, we may ask: What are the different dynamic organizational capabilities and modes of the organization (with respect to infrastructure, policy and culture) that ensure flexibility and stability, and enable it to adjust business models successfully to changing environments? The following figure shows the open innovation funnel [3], in terms of several opposite pairs following the notion of an “ambidextrous organizations”:
Characteristics of Ambidextrous Organizations
Implementation Mode Structural Mode Adaptation Condition Rules Decision Mak ing Communication Governance Control and Authority explorative organic flexible heuristical implicit leadership lateral advice and learning network and trust exploitative mechanistic stable routinized explicit leadership vertical desicions by superiors hierarchy
Co-ideation
Co-design
Co-development
Co-production
Figure 6: Ambidextrous Organizational Antecedents of Business Model Innovation According to Figure 6, empirical evidence in the literature reveals that organizations which can manage both modes of organizational design, are able to adapt more effectively and efficiently to changing environments [6, 18]. Obviously, ambidexterity produces relevant trade-offs between those phases of an innovation process where flexible adaptation to new ideas, designs, moods etc. (“De-compressive Openness”) is
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necessary with those phases of the innovation process that need straight-forward management (“Compression Mode”) [4]. Figure 6 suggests that there is a strict line separating explorative from exploitative modes, organic from mechanistic structures, stable from flexible phases, heuristics from routines etc. Of course in reality, we may experience a specific composition of these ambidextrous modes depending on the single innovation case, sector, environmental dynamics, community communication channels, learning requirements etc. We will return later to the underlying hypotheses on ambidextrous designs as the appropriate organizational adaptation mechanism when describing the business modeling cases investigated in this paper (see chapter 4).
2 Drivers for Business Model Innovation in the Digital Economy
If we look at the innovation landscape of the Digital & New Media Economy, we can identify more than a dozen of relevant trends and drivers for Business Model Innovation (see Fig. 7):
• • • • • • • • • • • • •
Crossmedia Publishing (from one-dimensional to multi-dimensional channels, products and services) Dynamics of Web-Generations (from Web 1.0 towards Web n) A5 - Anything, Anytime, Anywhere, Anyway, Anyone (from discrete to seamless information and communication) Mass Customization, Customer Profiling and Targeting (from standardized towards individualized and targeted products and services) Augmented Reality (augmentation of the real world with virtual information) Location Based Services (from general to geodata based services) Sector Convergence (from autonomous to fusioned branches) Usability (from complex to intuitive applications and interfaces) Online-Payment Systems (availability of micro-payment as enabling factor) Participation (from static to dynamic and anthropocentric networked consumers and communities) Demographic and Lifestyle Changes (i.a. appearance of Digital Natives and elderly society) Globalization (integration of regional economic and social communities through global communication networks) Legal Framework (regulatory push from sector specific laws).
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Relevant areas of Business Modeling
Ressources and Infrastructure ValueProposition CRM Human Resources Organization Value-add Workflownetwork Management Financing Cost Revenue structures streams
Technology
Trends
Crossmedia Publishing Dynamics of Web-Generations A5 - Anything, Anytime, Anywhere, Anyway, Anyone Mass Customization, Customer Profiling and Targeting Augmented Reality Location Based Services Sector Convergence Usability Online-Payment Systems Participation Demographics, Lifestyles etc. Globalization Legal Framework
Corporate Culture Knowledge Management Strategy
Figure 7: Trednmatrix: Metatrends and Business Modeling Areas in the Digital and New Media Economy We define the term “Business Model Innovation” as changing the building blocks of how value is produced, offered and delivered to customers [15]. Changing the buildings blocks may embrace • altering the value proposition and/or customer interaction, • combining new, or changing, human, technological and organizational (network) resources, • changing the innovation strategy, supportive knowledge management and corporate culture. Business Model Innovation then leads to different cost structures and revenue streams. It is obvious that due to the diversity of drivers and the portfolio of firms in the Digital & New Media Economy, their diverse competences and roles in the innovation process, that the impacts on business modeling are manifold. This introduces a distinctive variety of challenges and requirements that have different implications on the relevant building blocks of business modeling. In our research, we developed a set of hypotheses covering each cell in the matrix of Figure 7 to investigate the leverage effects of trends towards the building blocks of business modeling. In order to be as illustrative as possible, we will outline a set of twelve case studies on Business Model Innovation, including one in more detail (highlighted in Table 1). The business cases correspond, in part, to the ongoing innovation processes in our empirical portfolio. Thus, information is displayed anonymously wherever distinctive business interests are concerned.
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3 Business Model Innovation Cases
The following Table shows the business cases which we have investigated and their constitutive community pillars:
Type of firm Value Proposition
Publishing house (books and job printing) Community platform for book recommendations Provision of data security and filter systems for youth endangering contents Edutainment 3.0 platform to deliver HD educational content Interactive guide from pregnancy to young families
Links to Knowledge Communities in the Context of Business Model Innovation CoA CoP CoI CoS
User Generated Content – UGC (book recommendations) Blacklistings based on UGC Professional Generated Content - PGC (book recommendations) Blacklistings based on UGC PGC from teachers and further education institutions PGC - Medical advice Web 3-D repositories for virtual worlds based on Open Source Semantically enhanced ontology based on Open Source PGC – professional produced regional and local content PGC (interactive guide for compliance management) PGC of professional writers Tourist information based on professional writings, special technology solution providers PGC from training experts Link to mobile CMS based on Open Source ECommerce platform for other publishers (coopetition) Professional associations against youth endangering contents support Associations of further education support Medical associations support Cooperation with eLearning and serious games providers Medical associations support Co-competition with other publishers in the region Professional association of the Digital Economy B2B ad-partners for implementing the business model B2B cooperation with ad-partners, local trade-, tourism & event marketing organizations Professional association of further education institutions Professional association of the Digital Economy Recommendation engine based on semantic technologies Text recognition and comprehension based on mathematical algorithms Semi-automated annotation of videos Trend monitoring based on ITsupported Social Networking Analyses Fame Mirror Concepts to intrinsically motivate participants Semantic Technologies for search and annotation Semantic technologies for context-related adstargeting ---
IT-Services
Documentary Film Production Publishing house (periodicals)
UGC
UGC from fora and blogs
Full Service Internet Agency
Visualization of hyperlocal information
End-users of web 3-D and LBS services
Internet Platform Service Provider Publishing house (newspaper)
The Best Doctor for your health problem Regional IPTV to complement printed content Interactive online engine to ensure compliance with data laws Location Based Services for tourists on mobile devices Interactive mobile Guide with location based events & gaming services Web 2.0 based learning and competences monitoring Mobile CMS system to deliver content effectively to mobile devices
UGC – evaluations from patients UGC – regional and local content (non-professional journalism) End-user comments as source of compliance information UGC of tourists to enhance authentic information
Webanalytics
Publishing house (books)
Fame Mirror Concepts to intrinsically motivate participants
Full Service Internet Agency Learning Management system provider CMS provider
UGC – evaluations of events, restaurants, etc.
Enhanced GPS technology for mobile devices
UGC from learners UGC from mobile device users (usability feedbacks)
Competences ontology
Table 1: Business Model Innovation and Related “Community of Knowledge” Pillars
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As can be seen from Table 1, each business model includes relevant, and indispensable, contributions from different knowledge communities that are decisive for the running of the new business model. If we now mirror Table 1 against our business modeling template (see Fig. 7), we can advance a new business model generation template:
Community of Science Community of Interest Community of Practice Community of Affinity
Relevant areas of Business Modeling
Ressources and Infrastructure ValueProposition CRM Human Resources Organization Val ue-add Workflownetwork Management Financing Cost Revenue structures streams
Technology
Trends
Crossmedia Publishing Dynamics of Web-Generations A5 - Anything, Anytime, Anywhere, Anyway, Anyone Mass Customization, Customer Profiling and Targeting Augmented Reality Location Based Services Sector Convergence Usability Online-Payment Systems Participation Demographics, Lifestyles etc. Globalization Legal Framework
Corporate Culture Knowledge Management Strategy
Figure 8: Working Template of Business Model Innovation with respect to Community Embedding
4 Experiences from Business Model Innovation
In this section we will draw on the findings from the different Business Model Innovation cases we have undertaken, and focus especially on the role of organizational ambidexterity in mastering innovation challenges. Impacts of Trends on Business Model Innovation The first evaluation step includes an impact analysis of relevant drivers with respect to modeling different business cases. In this first step – based on internal workshops held in companies – an in-depth assessment of relevant impacts from external innovation drivers has been made (Fig. 9). The matrix displays the working template to assess trend impacts on business models. It allows first an evaluation of relevant drivers (horizontal variables) as already displayed in Fig. 7. Each variable is discussed within a firm specific workshop with the management asking for an assessment of the drivers dynamic impact on the firm’s business environment (is it changing rules of the game?), its cumulative intensity (can we expect that it is driving business continuously?), and its selectivity (does it have an impact on specific value propositions, resources etc.?). Second it allows analyzing the relative importance for and leverage effects on the specific business model (step 2 in Fig. 9, summarizing the evaluation of each of the business cases in Table 1).
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Using the example of business case 10, “Interactive Mobile Guide with Location Based Events & Gaming Services”, we can identify a strong impact of 7 and a medium impact of 9 drivers. The impacts of these drivers within this Business Model Innovation case study can be described as follows: Strong Impact Drivers: • Cross-Media Publishing: the new service is only marketable with a strong cross-media component. For a rich user experience, text, video and audio information has to be merged; dynamic content has to be provided connecting users locally in an immersive game context. • Mass-Customization: personalized information has to be provided that follows the demands and the preferences of users (tour guides’ recommendations, depending on choices of restaurants, cultural events etc.) and depending on the time-of-day (breakfast, lunch, dinner) etc. • Location Based Services: information about events and cultural artifacts has to be contextualized with geo-data to allow for instant information services depending on the geo-position of the user. • Sector Convergence: in this case, a mobile game provider is part of the business model architecture to boost user interaction in a C2C context. • Usability: an important driver for a broad diffusion and acceptance in B2C-markets • Digital Natives: this customer segment is supposed to use LBS and personalized services extensively. • Participation: user interaction (C2C) plays an important role in mobilizing a huge Community of Affinity for the new service, since these customers usually identify with each other through similar interests (e.g. night life, rock concerts). In addition, feedback tools are necessary to integrate User Generated Content. Medium Impact Drivers: • Dynamic Web Development: the new business model should make extensive use of Web 2.0 tools to enhance participation and user feedback (see above). The ‘anthropocentric touch’ of the service strongly supports incentives to join the
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• • • •
community. Web 3.0 technologies have to be integrated in terms of “Semantic Search and Ontologies” to allow flexible displaying of cross-linked data. Web 4.0 tools then could be the next step to further develop the local service towards a hyperlocality ‘web of things’3. E-payment systems have to provide options for micro-payment, since more flexibility in designing the operational cash-streams has to be implemented. Demographic Change and New Life-styles: the business model also needs to adjust usability and services also to the user behavior of elderly people. Globalization: in cities with a high tourist turnover, the service should always deliver up-to date information. Legal framework: technically, the service has to provide an opt-in procedure, since the use of, for example, geo-data is only allowed under certain legal pre-requisitions which vary from country to country.
Embedding into Knowledge Communities The second step is the elaboration of substantial answers to the relevant questions in the Business Model Canvas [15]. We regularly use this template during business model development. From the building blocks of our Business Model, we derive key questions (see again Fig. 7 and 8) which form our template:
Key Partners
Key Activities
Value Propositions
Customer Relationships
What type of relationship does each of our Customer Segments expect us to establish and maintain with them? Which ones have we established? How costly are they? How are they integrated with the rest of our business model?
Customer Segments
What Key Activities do our Value Propositions require? Our Distribution Channels? Customer Relationships? Revenue Streams? Who are our Key Partners? Who are our key suppliers? Which Key Resources are we acquiring from partners? Which Key Activities do Partners perform? What value do we deliver to the customer? Which one of our customer´s problems are we helping to solve? Which customer needs are we satisfying? What bundles of products and services are we offering to each Customer Segment?
Key Resources
Channels
Through which Channels do our Customer Segments want to be reached? How are we reaching them now? How are our Channels integrated? Which ones work best? Which ones are most cost-efficient? How are we integrating them with customer routines?
For whom are we creating value? Who are our most important customers?
What Key Resources do our Value Propositions require? Our Distribution Channels? Customer Relationships? Revenue Streams?
Cost Structure
What are the most important costs inherent in our business model? Which Key Resources are most expensive? Which Key Activities are most expensive?
Revenue Streams
For what value are our customers really willing to pay? For what do they currently pay? How are they currently paying? How would they prefer to pay? How much does each Revenue Stream contribute to overall revenues?
Source: Osterwalder/Pigneur (2009): Business Model Generation: A Handbook f or Visionaries, Game Changers, and Challengers
Figure 10: Business Model Canvas: Questions to Develop Business Model Innovation
3 The ‚Web of Things‘ is a kind of ‚Outernet‘ where information embodied in articles of daily use is meshed up with information in the Internet. This is also called Web 4.0 [8].
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This template contains standard questions that need to be addressed in the course of Business Model Innovation. Since our extended model also embraces the organizational anchors that are embedded into knowledge communities, these standard questions have to be complemented with additional queries related to Community Integration:
Value Propositions Customer Relationships Customer Segments
Prosumers
Communities of Affinity
B2C B2B
C2C
What value do we deliver to the customer? Which one of our customer´s problems are we helping to solve? Which customer needs are we satisfying? What bundles of products and services are we offering to each Customer Segment?
How can we combine our products / services with user generated value? Does user generated value support our value proposition?
What type of relationship does each of our Customer Segments expect us to establish and maintain with them?
Do we understand the relationships between our customers? How should we support conversation in the market and between customers? Do we need to address prosumers different from consumers?
For whom are we creating value? Who are our most important customers?
Who is creating value for your business model? What are the dynamics of value creation in your customers community?
Revenue Streams
For what value are our customers really willing to pay? For what do they currently pay? Is it possible to exploit user generated value commercially? Can we exploit our communities cross-laterally (e.g. combine revenue streams from pay per transaction and adverts?)
Figure 11: Extensions of Q&A for Business Model Innovation (downstream tasks)
If we look at the downstream tasks within Business Model Innovation, we need to be aware that stakeholders from Communities of Affinity are relevant contributors to our Business Model. With this background for the above mentioned business model innovation case on “Location Based Services (LBS)”, the following “must-dos” have been identified for the business case model on “LBS”: • No marketable products/services without UGC, • B2B customers (restaurants, shops, cultural institutions etc.) and consumers have to deliver content and have to pay for the products/services, • Pro-active community engineering: initiating a premium user-community, and setting up of an incentive system, • Clear IPR regulations, • Cross lateral exploitation (e.g. combining revenue streams from pay per transaction and adverts), • Integration of new enabling technologies (e.g. for trendscouting in the communities).
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Looking at the upstream tasks, we locate community integration into the Q&A template as follows:
Key Partners Key Activities Value Propositions
Community of Practice
ExWhat Key Activities do our perts Value Propositions require? What key activities are required to sustain our communities of knowledge?
Who are our Key Partners? Who are our key Community suppliers?Innova
of Interest
How can we ensure mutual learning within communities and
-tors
Key Resources
What Key Resources do our Value Propositions require?
Resear chers
What value do we deliver to the customer? Which one of our customer´s problems are we helping to solve? Which customer needs are we satisfying? What bundles of products and services are we offering to each Customer Segment? How can we combine our products / services with user generated value? Can we provide added value with complementary services our partners or communities?
Scientific Community
knowledge transfer to our business model?
What key ressources and organizational antecedents are required to embed successfully in our communities?
Cost Structure
What are the most important costs inherent in our business model? What are the cost impacts of Community involvement into your business model? Do we need to establish decisive incentive systems to ensure sustainable value creation through Communities?
Figure 12: Extensions of Q&A for Business Model Innovation (upstream tasks)
For our business model example “LBS” the outcome of the “must-dos” design discussion can be summarized as follows: • Pro-active community engineering, • Setting up a decisive incentive system, • Establishing learning arenas, • Trendscouting in the communities, • Integrating new enabling technologies (semantic technologies for search), • Collaborative design and development (games developer), • Controlling the transaction costs of community engineering. Organizational Adaptation with Ambidextrous Design Looking at the portfolio of requirements in the downstream and upstream tasks, Business Model Innovation needs to link the business model value architecture (in particular the configuration of the value-network partners) with the external communities [8]. In our case studies we have to consider at least four relevant communities (see again Fig. 8) as being of crucial importance for the performance of the new business model. We will illustrate thus using the example of the LBS Business Model Innovation:
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Communities of Affinity (CoAs): as already expressed, without User Generated Content, Web 2.0 tools for feedback and C2C interaction, there is no ‘lively system’ to attract users. The operating business architecture has to imply a strong “community engineering” unit to develop appropriate incentive systems for the mobilization of the community. The ‘basic settings’ of such a unit should comprise, “constant stimulating market conversation”, “perpetual monitoring of trends in market conversation to identify new user needs”, and “application of purposeful incentive systems” to stimulate affinity and identification-based trust amongst the community (e.g. by introducing a ‘famemirror’” [5]). Thus the organizational anchors into the community may be implemented with advanced social media tools and intelligent incentive systems to stimulate further user identification. These tools have to be designed on the basis of strict and reliable rules enhancing the confidence of users to participate. Communities of Practice (CoPs): the value-network has to sustain strong ties to surrounding value-partners who dispose of different types of data, information and knowledge. On the ‘content-side’, value-partners from, firstly, local and regional tourist information institutions, and, secondly, from event marketers, have to be involved to ensure content flows from professionally established content sources. Thus, links to experts and intermediaries that are engaged in the ‘knowledge space’ of tourism marketing, event marketing etc., have to be established carefully. Also weak ties to pools of professional authors of tourist information have to be developed to enable the flexible inclusion of professionally generated content into the application when needed. On the ‘technology side”, experts on multimedia data-integration, and the linking of different geo-data (including, for example, collaborative ontology-design engineering) have to be approached to ensure constant technology transfer and the provision of technical solutions to operate and further develop the business model. For organizational anchors to be embedded in these communities, we may at first consider developing a “transactive knowledge management system”, containing information on “Who knows what in tourism and event marketing?”, e.g. members and experts of regional tourism and event communities. A second implementation measure should be “membership of marketing and technology people from the value-network in selected communities of experts” to ensure knowledge transfer. Communities of Interests (CoIs): the value network has to extend its virtual organizational boundary along working groups of selected professional associations, (a) in the Digital and New Media Economy to include advertising agencies and onlinemarketing as well as search-engine optimizers, (b) in the tourism and event marketing sector to ensure support for the business model and links to B2B partners (e.g. shops and restaurants), and (c) in the local trade associations. The latter is an indispensable measure to connect to local trade partners as potential B2B-partners for the LBS application. Organizational anchors into these communities are clearly of the institutional kind, e.g. firms becoming members of the associations mentioned. Other paths into the CoIs involve recruiting freelancers who have formerly worked in the tourism and event marketing sectors as an initial step, and further networking along their personal relationships into the CoIs. Communities of Science (CoSs): One important aspect, already mentioned in the context of CoPs, is to establish strong ties to the Scientific Community on “Semantic Technologies and GPS technologies”. This is important in selecting personalized and geodata contextualized information - on the basis of time-of-day and life situation - for an
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immersive user experience. Thus conference visits, as means of loose ties to specialized scientific groups etc. are an appropriate organizational adaptation measure. Looking at the criteria of ‘ambidextrous design” (see Fig. 6), we may say in a nutshell that the value-networks needed to establish different adaptation mechanisms and to link them to relevant Communities of Knowledge can be summarized as:
LBS Business Case Implementation Mode Structural Mode Adaptation Condition Rules Decision Mak ing Communication Governance Control and Authority CoA
explorative mechanistic stable routinized explicit lateral learning trust
CoP
explorative organic flexible heuristical implicit lateral learning hierachy
CoI
exploitative mechanistic stable routinized explicit vertical advice hierarchy
CoS
exploitative organic stable heuristical implicit lateral learning hierarchy
Table 2: Organizational Adaptation: Ambidexterity Criteria for the Business Case “Location Based Services” To embed into the Community of Affinity, the LBS value network needs to establish reliable social media tools that stimulate identification-based trust amongst the community members. The required structural approach tends to be more ‘mechanistic’ at first glance, since it needs stable adaptation and reliable rules for feedback and market conversation. Decision making processes on, for example, how to display and exploit User Generated Content should be transparent and explicit, following equal rules of feedback and exploitation for all participants. At the same time, the organizational link to the CoA needs to enhance exploration and learning to ensure the exploitation of knowledge flows, especially UGC. For the Communities of Practice, the LBS value-network needs to be embedded more organically into the communities by engaging in working groups, establishing communication channels to different key stakeholders with specific knowledge etc. Thus, the adaptation mode should be more flexible, reaching from occasional participation to strong ties e.g. as an official member of special CoPs. The rules of embedding should be more heuristical, e.g. opening up organizational borderlines, including experience exchange with experts, and for inquiries from outside the firm. At the same time, there could be a need for controlling outside-in and inside-out flows of knowledge hierarchically. These should be agreed upon in the value-network, since the proper functioning of certain technological interfaces etc. is critical for the entire business model. In order to be embedded in Communities of Interest, the LBS value network may implement institutional engagements to install stable conditions for knowledge flows. Since the main aims are to exploit relevant knowledge from CoIs and to gain support for the business model, rules and decision models should be explicit, formalized, and stable over time.
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Finally, in order to link to Communities of Science, the LBS value-network needs to establish both strong and weak ties to certain technology providers, depending on the role and enabling potential of the technology. Thus, the principal mode should be exploitative (“What is the best technology, and how can I use it?”), and modes of participation may be organic (occasional participation in conference) etc.
5 Conclusions
In the Innovation 3.0 paradigm [8], Business Modeling is a challenging exercise, since the complexity of framework conditions, paths to embed into knowledge communities, exploitable technologies, architectural design of the value-network, interaction strategies with customers etc, is constantly rising. A multitude of trends that have impact on the future business model, as well as the crucial link to knowledge communities, pose additional questions in the course of Business Modeling that need to be considered. This paper has examined some of the main questions about Business Model Innovation in the Digital and New Media Economy. Expecting the trend to embed digital business processes into the - so far - “Analogous Industry”, we may expect similar questions and challenges of Innovation 3.0 to be raised in the “Old Economy” in the near future.
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References
[1] Antonacopoulou, E., Ferdinand, J., Graca, M., and Easterby-Smith, M. 2008. ‘Dynamic Capabilities and Organizational Learning: Socio-Political Tensions in Organizational Renewal’, Advanced Institute of Management Research Paper No. 014. DOI=http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1306958. [2] Boscherini, L., Cavaliere , A., Chiaroni A., Chiesa, V.,and Frattini, F. 2009. ‘The process of organizational change in Open Innovation models: evidence from a sample of high - tech firms’, in: Huizingh K.R.E., Conn, S., Torkkeli, M. and Bitran, I. (Eds.) Proceedings of the XX ISPIM Conference 2009. [3] Chesbrough, H. 2003. Open Innovation: the new imperative for creating and profiting from technology, Harvard Business School Press. [4] Eisenhardt, K.M., Tabrizi, B.N. 1995: ‘Accelerating adaptive processes: Product innovation in the global computer industry’, Administrative Science Quarterly, Vol. 40 pp.84 - 110. [5] Groh, G., Brocco, M., and Asikin, Y.A. 2010: ‘Contribution Awareness and Fame in Open Innovation Network’s, in: Hafkesbrink, J., Hoppe, H.-U., and Schlichter, J. 2010: Competence Management for Open Innovation – Tools and IT-support to unlock the potential of Open Innovation, (Eul Verlag). [6] Güttel, W.H., and Konlechner, S.W. 2007: Dynamic Capabilities and the Ambidextrous Organization: Empirical Results from Research-Intensive Firms, retrieved April 25th, 2010, from: http://www.synaxx. com/Referenced%20Material/ Guttel%20-SMS-2007 Dynamic%20Capabilities%20and%20 Ambidexterity.pdf. [7] Hafkesbrink, J /Schroll, M. 2010. Organizational Competences for Open Innovation in Small and Medium Sized Enterprises of the Digital Economy, in: Hafkesbrink, J./Hoppe, H.U./Schlichter, J. 2010: Competence Management for Open Innovation – Tools and IT-support to unlock the potential of Open Innovation, Eul Verlag. [8] Hafkesbrink, J./Evers, J. 2010: Innovation 3.0 – Embedding Embedding into community knowledge: the relevance of trust as enabling factor for collaborative organizational learning, Paper submitted to the XXI. ISPIM conference on the “Dynamics of Innovation”, Bilbao 6-9 June 2010. [9] Hafkesbrink, J./Krause, D./Westermaier, R. 2010: Old Wine in New Bottles? A Case Study on Organizational Antecedents for Open Innovation Management, in: Hafkesbrink, J./Hoppe, H.U./Schlichter, J. 2010: Competence Management for Open Innovation – Tools and IT-support to unlock the potential of Open Innovation, Eul Verlag. [10] Hafkesbrink, J./Scholl, H. 2010: Web 2.0 Learning- A Case Study on Organizational Competences in Open Content Innovation, in: Hafkesbrink, J./Hoppe, H.-U./Schlichter, J. 2010: Competence Management for Open Innovation – Tools and IT-support to unlock the potential of Open Innovation, Eul Verlag. [11] Hafkesbrink, J./Stark, A./Schmucker, M. 2010: Controlled Opening in pro-active SME Innovation - a Case Study on an ‘Open Innovation Audit’ in the Digital Economy, in: Hafkesbrink, J./Hoppe, H.-U./Schlichter, J. 2010: Competence Management for Open Innovation – Tools and IT-support to unlock the potential of Open Innovation, Eul Verlag. [12] Hurmelinna-Laukkanen, P. 2009: ‘Orchestration activities in international networks: The role of innovation appropriability’. In: Proceedings of The XX ISPIM Conference Huizingh K.R.E., Conn S., Torkkeli M., and Bitran, I. (Eds.) Vienna, Austria, 21-24 June 2009. [13] Kesting, P., and Smolinski, R. 2006: ‘Obstacles to Organisational Change - A Routine-Based View on Dynamic Capabilities.’ DOI= http://papers.ssrn.com/sol3/papers.cfm?abstract_i d=905526. [14] Kunz, R. 2009. ‘How do recent Trends in the Pharmaceutical and Biotech Industry influence Open Innovation Approaches?’ in: Proceedings of The XX ISPIM Conference Huizingh K.R.E., Conn S., Torkkeli M. & Bitran I. (Eds.) Vienna, Austria, 21-24 June 2009.
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[15] Osterwalder, A., and Pigneur, Y. (2009). Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers, ISBN: 978-2-8399-0580-0 [16] Schneckenberg, D. 2009. ‘Knowledge needs Liberty - The Link between Corporate Governance and the Use of Web 2.0 to foster Knowledge Management’ in: Proceedings of The XX ISPIM Conference Huizingh K.R.E., Conn S., Torkkeli M. & Bitran I. (Eds.) Vienna, Austria, 21-24 June 2009. [17] Teece, D.J., Pisano, G. and Shuen, A. 1997. Dynamic Capibilities and Strategic Management, Strategic Management Journal 18: 509-533. [18] Tushman, M., Smith, W., Wood, R., Westerman, G., and O’Reilly, C. 2002: ‘Innovation Streams and Ambidextrous Organizational Designs: On Building Dynamic Capabilities’. Retrieved April 20, 2010, from http://web.mit.edu/sloan/osg-seminar/f02_docs/TushmanEt Al_2002.pdf.
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innowise research & consulting GmbH Bürgerstr. 15, 47057 Duisburg, Germany E-mail: [email protected], www.innowise.eu
Markus Schroll
innowise research & consulting GmbH Bürgerstr. 15, 47057 Duisburg, Germany E-mail: [email protected], www.innowise.eu
Abstract: This paper1 outlines the increasing challenges of Business Model Innovation in the Digital and New Media Economy. It describes drivers of change, impacts on the innovation and business landscape, consequences for business modeling and the innovation process, as well as the implications for organizational adaptation. It presents in-depth observations from empirical research on 12 business cases in the Digital and Media Economy in Germany.2 Our findings show that business modeling in the Digital Economy needs to be continuously cross-linked to the innovation process to adapt to the ever changing business environment. It becomes clear that Business Models in the Digital Economy need to be “open” so as to be able to continuously embed them into the firm’s surrounding communities, and to ensure knowledge transfer and learning. We will align our arguments with earlier research on Open Innovation [7, 9, 10, 11] and Innovation 3.0 - which we have earlier called “Embedded Innovation” [8] - taking a more practical view on the implementation of new Business Models. Keywords: Business Model Innovation, Innovation 3.0, Open Innovation, Ambidextrous Organization, Organizational Adaptation, Communities of Knowledge, Digital Economy, New Media Economy
Preprint of an article submitted for consideration at the TII-Conference „Innovation 3.0 – Challenges, Needs and Skills of the new Innovation Era“, Düsseldorf, 28-30 April 2010. 2 The research underlying this paper relates to several R&D projects, supported by the German Ministry for Education and Research (BMBF), the State Chancellery of North-Rhine-Westfalia and the EU: ‘Organizational Attentiveness as a Basis for Corporate Innovativeness (ACHTINNO)’ BMBF-Contract No. 01FH09003; ‘Competence Development and Process Support in Open-Innovation Networks of the IT-Industry through Knowledge Modeling and Analysis (KOPIWA)’, BMBF-Contract No. 01FM0770; ‘Integrated Tools to Enhance the Innovative Capabilities of Publishing and New Media Companies’ (FLEXMEDIA)’; BMBF-Contract No. 01FH09011; ‘Local.mobile.NRW – Development of Smart Location Based Services for Mobile Devices’, NRW-Contract No. 29 00 923 02; ‘Locally-based-TV: Development of an Intelligent Regional IPTV Platform in the Münsterland’; Contract No. 29 00 938 02.
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1 Introduction
The so-called ‘Digital & New Media Economy’ embraces all actors in digital value creation and publishing processes, such as multi-media agencies, e-commerce agents, interactive online marketing and mobile solutions providers, games developers, social media providers, new media publishers etc. Business modeling in this ‘melting pot’ is influenced by a multitude of drivers, including new enabling technologies, the rapidly changing demands and life-styles of ‘digital natives’, the convergence of markets and media etc.
Figure 1 Technology-/Media Convergence in the Digital Economy
The innovation landscape is characterized as being extremely “open and dynamic”. Ideation, design, development and implementation of innovations are embedded in a cross-meshed network of especially SMEs (“multi-agent systems”) that are in continuous dialogue with their surrounding communities [8]. The critical success factor in these ‘multi-agent systems’ is to develop sufficient “gravitational embedding force” to link them to ‘Communities of Knowledge’. Amongst these communities are
•
•
•
•
Communities of Affinity (CoA): continuous dialogue with prosumers and end-consumers (B2C) to catch up with new (design) ideas, demands, moods, fashions and business opportunities; Communities of Practice (CoP): collaboration with each other (B2B), and with micro firms or freelancers to flexibly enhance knowledge flows, primarily for design and co-development; Communities of Interest (CoI): experience exchange with innovating firms from the same and other sectors to benefit from crossover ideas and complementary knowledge, Communities of Science (CoS): dialogue with the scientists to absorb new technologies.
The learning cycles in innovation and business modeling with respect to the different communities in the Digital & New Media Economy are depicted in Fig. 2:
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Figure 2: Embedding into ‘Communities of Knowledge’ to boost Innovation 3.0 [8] These ‘multi-agent systems’ and related communities define the dynamic context of business modeling. The notion of “embeddedness” clearly stresses the point that setting up new business models is an ongoing task. For instance, if we look at most of the innovative Internet services that have emerged in the past years, we recognize that the initial business models behind them have been altered over time in many ways – in terms of changing the functionality for customers (“value proposition”); modifying the usability for, and interaction with, customers (“CRM”); or in terms of amending the basic financing mode (e.g. “ad-financing” versus “pay per transaction”). One may argue that these adjustments of business models are a routine adaptation process, since even in the “Analogue Economy” incremental improvements of such models occur on a routine basis. However, the innovation process in the Digital Economy is different in some basic respects, namely in the areas of (a) innovation infrastructure, (b) corporate innovation policy, and (c) organizational adaptation and culture: (a) Innovation infrastructure: Innovation activities of the Digital Economy are embedded in a “digitalized infrastructure” with numerous easy accessible and easy to adopt digital enabling technologies. These technologies unfold a huge potential for new products and services, since combining and linking them to each other becomes - ‘bit by bit’ - more easy. Thus, the Digital Economy is at the center of a melting process of transferring horizontal technologies into vertical markets (see Fig. 3):
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Demographic Change
Technology Knowledge Sources
Changing Life-styles Competition regulation
Globalisation Convergence of Markets
Telecommunication
Basic services ValueServices Distribution Add. Services
Patentlaws
Multi-agent system of Innovation Actors
Standards
Market for Contents
Media-Technologies
Content Generation Packaging Distribution Enduser Devices
Market for Content Packaging & Applications
Technology Transfer
Melting Kernel
Market Demand
Market for Transmission Carriers
IT-/Electronics
Parts Software Platforms Distribution Add. Services
Market for Hardware
Semantic Techn.
.. . .. . ... ...
(end-user devices etc.)
eCommerceLaw Digital Signature Act Institutional Framework (Governance)
Media Law
Market for ...
Internationalisation
Figure 3: The Digital Economy as the Melting Kernel from Horizontal Technologies to Vertical Markets (b) Corporate Innovation Policy: In the Digital Economy, the value of goods and services is based on knowledge, application know-how, experience and business model sovereignty. Following Figure 4, the firm’s knowledge management system has to turn information into competences, while developing appropriate explicit and implicit skills to manage the innovation process. Hence, as the melting kernel needs to fuse very different technologies, firms understood very early that continuous learning was the key to innovation. Competence accumulation in an extremely diversified technology landscape is not possible, however, within a single innovation entity. As Henry Chesbrough [3] put it, ‘Not all the smart people in the field work for us; we need to work with smart people inside and outside the company’ [cited in 14] – thus collaboration is the order of the day. Hence, firms learned that it is more important to know who disposes of desired competences than to own all those competences themselves. Therefore, a distinctive openness of organizational borderlines is the ruling governance mode for innovation [7]. A decisive element in the accumulation of competences, then, is establishing permanent links to the firm’s surrounding knowledge communities and in absorbing external knowledge [8]. To gain maximum effectiveness in terms of knowledge transfer, the innovating firm has to balance the community orchestration [12], because different stakeholders (like “prosumers”, “experts”, “innovators” ,and “researchers” as representatives of the surrounding communities of knowledge) usually only cover certain knowledge artifacts [8] exploitable for the firm. For example, “Innovators” from Communities of Interest typically dispose of in-depth knowhow and experiences in their business domain, as well as of implicit skills in
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running domain-related business models. “Experts” from Communities of Practice are linked through the mutual interest of solving certain problems. These “Experts” typically embrace specialized knowledge artifacts and knowhow in applying this knowledge to defined problems and experiences from related application cases. Thus they usually do not have competences in running decisive business models, since they remain upstream in the “knowledge supply chain”, and provide in-depth technical expertise. “Researchers” generally collect data and information and transform these artifacts into knowledge. Of course, many “Researchers” from Communities of Science also dispose of extensive know-how, especially those working in applied joint research projects with industry. Finally, “Prosumers” from Communities of Affinity usually participate in producing ideas or design artifacts in an open innovation process: they give information on product or service usage by providing feedback or they engage in idea contests. Here as well, we increasingly find “Experts” who dispose of decisive know-how in product/service usage and ‘content production’, which has to be considered as an important external source of knowledge.
Prosumers
Experts
Semantic Enrichment
Resear -chers
Innova -tors
information management
competence management
+ competence
„expertise “ „knowhow“
+ denotation
sovereignty expertise
+ exercise + application + context
experience
know-how
Knowledge
Information
„cognition“
+ syntax
data
characters
Valorizationlevel „explicit skills“ „implicit skills“
„ intellectual capital “
Source: inspired by Auer-Consulting (n.d.)
Figure 4: Evolution from Characters to Sovereignty: the Up- and Downstream Artefacts of Knowledge (c) Organizational adaptation and organization culture To enable collaborative learning as the main feature of corporate innovation policy, the organization has to adapt to changing environments on a continuous basis. Community orchestration in this sense means establishing organizational anchors into surrounding communities so as to ensure a balanced knowledge transfer and absorption. Since stakeholders from surrounding communities usually have different impetuses on knowledge (see again Fig. 4), they are also
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involved differently in the innovation process (see Fig. 5). ‘Prosumers’ predominantly provide information on product usage from the market perspective and thus new ideas that enter the innovation funnel more upstream. ‘Researchers’ are usually involved in ideation and design, in pre-competitive joint research, and also in the development of innovation projects. ‘Innovators’ usually are engaged in the phase of development and production as co-operation partners. ‘Experts’ are – depending from their asset specifities - participating throughout the innovation process, predominantly from ideation to development:
Co-ideation
Co-design
Co-development
Co-production
Experts
Innovators
Prosumers Researc hers
Figure 5: Involvement of Various Stakeholders in the Open Innovation Process
To gain a proper “community orchestration”, the organization has to develop sufficient gravitational embedding force to establish effective and efficient relationships to knowledge communities. Thus, for a long time organizational change has been described as an important source of competitive advantage [13]. In the recent debate about ‘organizational renewal’, the main focus has been on “dynamic capabilities” [17] and “ambidextrous organizations” [18]. Accordingly, Teece et al. define the dynamic capabilities of a firm as ‘it’s ability to integrate, build, and re-configure, internal and external competences to address rapidly changing environments’ [17]. In more detail, the different attributes or pre-dispositions of organizational renewal capacities are discussed as “the ability to overcome established routines by self-organization and organizational renewal” [1], and being able “to organize for constant change and to establish collective organizational learning to continuously reinvent the company's core business processes” [16]. In this context, “Organizational Learning” is recognized as the “ability to maintain a continuous process of adjustment of search rules, attention rules, and goals of the
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organization” [1], or the “ability to undergo a continuous process of experimentation, adaptation and learning to pro-actively define the business environment” [2]. A relatively new issue in organizational adaption research is the notion of an “ambidextrous organization” [6, 18], which is defined as an organization’s ability to reconcile explorative and exploitative activities simultaneously” [6]. Ambidexterity is more or less a re-conceptualization of the discourse on ‘dynamic capabilities’ explicitly considering the necessity of flexibility and stability modes of an organization. The core question that ambidexterity seeks to answer is: “How are dynamic capabilities – the organization’s learning mechanisms – shaped in ambidextrous organizations in order to cope with contradictory environmental demands?”[6]. If we transform this question to the management of business model innovation, we may ask: What are the different dynamic organizational capabilities and modes of the organization (with respect to infrastructure, policy and culture) that ensure flexibility and stability, and enable it to adjust business models successfully to changing environments? The following figure shows the open innovation funnel [3], in terms of several opposite pairs following the notion of an “ambidextrous organizations”:
Characteristics of Ambidextrous Organizations
Implementation Mode Structural Mode Adaptation Condition Rules Decision Mak ing Communication Governance Control and Authority explorative organic flexible heuristical implicit leadership lateral advice and learning network and trust exploitative mechanistic stable routinized explicit leadership vertical desicions by superiors hierarchy
Co-ideation
Co-design
Co-development
Co-production
Figure 6: Ambidextrous Organizational Antecedents of Business Model Innovation According to Figure 6, empirical evidence in the literature reveals that organizations which can manage both modes of organizational design, are able to adapt more effectively and efficiently to changing environments [6, 18]. Obviously, ambidexterity produces relevant trade-offs between those phases of an innovation process where flexible adaptation to new ideas, designs, moods etc. (“De-compressive Openness”) is
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necessary with those phases of the innovation process that need straight-forward management (“Compression Mode”) [4]. Figure 6 suggests that there is a strict line separating explorative from exploitative modes, organic from mechanistic structures, stable from flexible phases, heuristics from routines etc. Of course in reality, we may experience a specific composition of these ambidextrous modes depending on the single innovation case, sector, environmental dynamics, community communication channels, learning requirements etc. We will return later to the underlying hypotheses on ambidextrous designs as the appropriate organizational adaptation mechanism when describing the business modeling cases investigated in this paper (see chapter 4).
2 Drivers for Business Model Innovation in the Digital Economy
If we look at the innovation landscape of the Digital & New Media Economy, we can identify more than a dozen of relevant trends and drivers for Business Model Innovation (see Fig. 7):
• • • • • • • • • • • • •
Crossmedia Publishing (from one-dimensional to multi-dimensional channels, products and services) Dynamics of Web-Generations (from Web 1.0 towards Web n) A5 - Anything, Anytime, Anywhere, Anyway, Anyone (from discrete to seamless information and communication) Mass Customization, Customer Profiling and Targeting (from standardized towards individualized and targeted products and services) Augmented Reality (augmentation of the real world with virtual information) Location Based Services (from general to geodata based services) Sector Convergence (from autonomous to fusioned branches) Usability (from complex to intuitive applications and interfaces) Online-Payment Systems (availability of micro-payment as enabling factor) Participation (from static to dynamic and anthropocentric networked consumers and communities) Demographic and Lifestyle Changes (i.a. appearance of Digital Natives and elderly society) Globalization (integration of regional economic and social communities through global communication networks) Legal Framework (regulatory push from sector specific laws).
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Relevant areas of Business Modeling
Ressources and Infrastructure ValueProposition CRM Human Resources Organization Value-add Workflownetwork Management Financing Cost Revenue structures streams
Technology
Trends
Crossmedia Publishing Dynamics of Web-Generations A5 - Anything, Anytime, Anywhere, Anyway, Anyone Mass Customization, Customer Profiling and Targeting Augmented Reality Location Based Services Sector Convergence Usability Online-Payment Systems Participation Demographics, Lifestyles etc. Globalization Legal Framework
Corporate Culture Knowledge Management Strategy
Figure 7: Trednmatrix: Metatrends and Business Modeling Areas in the Digital and New Media Economy We define the term “Business Model Innovation” as changing the building blocks of how value is produced, offered and delivered to customers [15]. Changing the buildings blocks may embrace • altering the value proposition and/or customer interaction, • combining new, or changing, human, technological and organizational (network) resources, • changing the innovation strategy, supportive knowledge management and corporate culture. Business Model Innovation then leads to different cost structures and revenue streams. It is obvious that due to the diversity of drivers and the portfolio of firms in the Digital & New Media Economy, their diverse competences and roles in the innovation process, that the impacts on business modeling are manifold. This introduces a distinctive variety of challenges and requirements that have different implications on the relevant building blocks of business modeling. In our research, we developed a set of hypotheses covering each cell in the matrix of Figure 7 to investigate the leverage effects of trends towards the building blocks of business modeling. In order to be as illustrative as possible, we will outline a set of twelve case studies on Business Model Innovation, including one in more detail (highlighted in Table 1). The business cases correspond, in part, to the ongoing innovation processes in our empirical portfolio. Thus, information is displayed anonymously wherever distinctive business interests are concerned.
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3 Business Model Innovation Cases
The following Table shows the business cases which we have investigated and their constitutive community pillars:
Type of firm Value Proposition
Publishing house (books and job printing) Community platform for book recommendations Provision of data security and filter systems for youth endangering contents Edutainment 3.0 platform to deliver HD educational content Interactive guide from pregnancy to young families
Links to Knowledge Communities in the Context of Business Model Innovation CoA CoP CoI CoS
User Generated Content – UGC (book recommendations) Blacklistings based on UGC Professional Generated Content - PGC (book recommendations) Blacklistings based on UGC PGC from teachers and further education institutions PGC - Medical advice Web 3-D repositories for virtual worlds based on Open Source Semantically enhanced ontology based on Open Source PGC – professional produced regional and local content PGC (interactive guide for compliance management) PGC of professional writers Tourist information based on professional writings, special technology solution providers PGC from training experts Link to mobile CMS based on Open Source ECommerce platform for other publishers (coopetition) Professional associations against youth endangering contents support Associations of further education support Medical associations support Cooperation with eLearning and serious games providers Medical associations support Co-competition with other publishers in the region Professional association of the Digital Economy B2B ad-partners for implementing the business model B2B cooperation with ad-partners, local trade-, tourism & event marketing organizations Professional association of further education institutions Professional association of the Digital Economy Recommendation engine based on semantic technologies Text recognition and comprehension based on mathematical algorithms Semi-automated annotation of videos Trend monitoring based on ITsupported Social Networking Analyses Fame Mirror Concepts to intrinsically motivate participants Semantic Technologies for search and annotation Semantic technologies for context-related adstargeting ---
IT-Services
Documentary Film Production Publishing house (periodicals)
UGC
UGC from fora and blogs
Full Service Internet Agency
Visualization of hyperlocal information
End-users of web 3-D and LBS services
Internet Platform Service Provider Publishing house (newspaper)
The Best Doctor for your health problem Regional IPTV to complement printed content Interactive online engine to ensure compliance with data laws Location Based Services for tourists on mobile devices Interactive mobile Guide with location based events & gaming services Web 2.0 based learning and competences monitoring Mobile CMS system to deliver content effectively to mobile devices
UGC – evaluations from patients UGC – regional and local content (non-professional journalism) End-user comments as source of compliance information UGC of tourists to enhance authentic information
Webanalytics
Publishing house (books)
Fame Mirror Concepts to intrinsically motivate participants
Full Service Internet Agency Learning Management system provider CMS provider
UGC – evaluations of events, restaurants, etc.
Enhanced GPS technology for mobile devices
UGC from learners UGC from mobile device users (usability feedbacks)
Competences ontology
Table 1: Business Model Innovation and Related “Community of Knowledge” Pillars
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As can be seen from Table 1, each business model includes relevant, and indispensable, contributions from different knowledge communities that are decisive for the running of the new business model. If we now mirror Table 1 against our business modeling template (see Fig. 7), we can advance a new business model generation template:
Community of Science Community of Interest Community of Practice Community of Affinity
Relevant areas of Business Modeling
Ressources and Infrastructure ValueProposition CRM Human Resources Organization Val ue-add Workflownetwork Management Financing Cost Revenue structures streams
Technology
Trends
Crossmedia Publishing Dynamics of Web-Generations A5 - Anything, Anytime, Anywhere, Anyway, Anyone Mass Customization, Customer Profiling and Targeting Augmented Reality Location Based Services Sector Convergence Usability Online-Payment Systems Participation Demographics, Lifestyles etc. Globalization Legal Framework
Corporate Culture Knowledge Management Strategy
Figure 8: Working Template of Business Model Innovation with respect to Community Embedding
4 Experiences from Business Model Innovation
In this section we will draw on the findings from the different Business Model Innovation cases we have undertaken, and focus especially on the role of organizational ambidexterity in mastering innovation challenges. Impacts of Trends on Business Model Innovation The first evaluation step includes an impact analysis of relevant drivers with respect to modeling different business cases. In this first step – based on internal workshops held in companies – an in-depth assessment of relevant impacts from external innovation drivers has been made (Fig. 9). The matrix displays the working template to assess trend impacts on business models. It allows first an evaluation of relevant drivers (horizontal variables) as already displayed in Fig. 7. Each variable is discussed within a firm specific workshop with the management asking for an assessment of the drivers dynamic impact on the firm’s business environment (is it changing rules of the game?), its cumulative intensity (can we expect that it is driving business continuously?), and its selectivity (does it have an impact on specific value propositions, resources etc.?). Second it allows analyzing the relative importance for and leverage effects on the specific business model (step 2 in Fig. 9, summarizing the evaluation of each of the business cases in Table 1).
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Using the example of business case 10, “Interactive Mobile Guide with Location Based Events & Gaming Services”, we can identify a strong impact of 7 and a medium impact of 9 drivers. The impacts of these drivers within this Business Model Innovation case study can be described as follows: Strong Impact Drivers: • Cross-Media Publishing: the new service is only marketable with a strong cross-media component. For a rich user experience, text, video and audio information has to be merged; dynamic content has to be provided connecting users locally in an immersive game context. • Mass-Customization: personalized information has to be provided that follows the demands and the preferences of users (tour guides’ recommendations, depending on choices of restaurants, cultural events etc.) and depending on the time-of-day (breakfast, lunch, dinner) etc. • Location Based Services: information about events and cultural artifacts has to be contextualized with geo-data to allow for instant information services depending on the geo-position of the user. • Sector Convergence: in this case, a mobile game provider is part of the business model architecture to boost user interaction in a C2C context. • Usability: an important driver for a broad diffusion and acceptance in B2C-markets • Digital Natives: this customer segment is supposed to use LBS and personalized services extensively. • Participation: user interaction (C2C) plays an important role in mobilizing a huge Community of Affinity for the new service, since these customers usually identify with each other through similar interests (e.g. night life, rock concerts). In addition, feedback tools are necessary to integrate User Generated Content. Medium Impact Drivers: • Dynamic Web Development: the new business model should make extensive use of Web 2.0 tools to enhance participation and user feedback (see above). The ‘anthropocentric touch’ of the service strongly supports incentives to join the
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• • • •
community. Web 3.0 technologies have to be integrated in terms of “Semantic Search and Ontologies” to allow flexible displaying of cross-linked data. Web 4.0 tools then could be the next step to further develop the local service towards a hyperlocality ‘web of things’3. E-payment systems have to provide options for micro-payment, since more flexibility in designing the operational cash-streams has to be implemented. Demographic Change and New Life-styles: the business model also needs to adjust usability and services also to the user behavior of elderly people. Globalization: in cities with a high tourist turnover, the service should always deliver up-to date information. Legal framework: technically, the service has to provide an opt-in procedure, since the use of, for example, geo-data is only allowed under certain legal pre-requisitions which vary from country to country.
Embedding into Knowledge Communities The second step is the elaboration of substantial answers to the relevant questions in the Business Model Canvas [15]. We regularly use this template during business model development. From the building blocks of our Business Model, we derive key questions (see again Fig. 7 and 8) which form our template:
Key Partners
Key Activities
Value Propositions
Customer Relationships
What type of relationship does each of our Customer Segments expect us to establish and maintain with them? Which ones have we established? How costly are they? How are they integrated with the rest of our business model?
Customer Segments
What Key Activities do our Value Propositions require? Our Distribution Channels? Customer Relationships? Revenue Streams? Who are our Key Partners? Who are our key suppliers? Which Key Resources are we acquiring from partners? Which Key Activities do Partners perform? What value do we deliver to the customer? Which one of our customer´s problems are we helping to solve? Which customer needs are we satisfying? What bundles of products and services are we offering to each Customer Segment?
Key Resources
Channels
Through which Channels do our Customer Segments want to be reached? How are we reaching them now? How are our Channels integrated? Which ones work best? Which ones are most cost-efficient? How are we integrating them with customer routines?
For whom are we creating value? Who are our most important customers?
What Key Resources do our Value Propositions require? Our Distribution Channels? Customer Relationships? Revenue Streams?
Cost Structure
What are the most important costs inherent in our business model? Which Key Resources are most expensive? Which Key Activities are most expensive?
Revenue Streams
For what value are our customers really willing to pay? For what do they currently pay? How are they currently paying? How would they prefer to pay? How much does each Revenue Stream contribute to overall revenues?
Source: Osterwalder/Pigneur (2009): Business Model Generation: A Handbook f or Visionaries, Game Changers, and Challengers
Figure 10: Business Model Canvas: Questions to Develop Business Model Innovation
3 The ‚Web of Things‘ is a kind of ‚Outernet‘ where information embodied in articles of daily use is meshed up with information in the Internet. This is also called Web 4.0 [8].
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This template contains standard questions that need to be addressed in the course of Business Model Innovation. Since our extended model also embraces the organizational anchors that are embedded into knowledge communities, these standard questions have to be complemented with additional queries related to Community Integration:
Value Propositions Customer Relationships Customer Segments
Prosumers
Communities of Affinity
B2C B2B
C2C
What value do we deliver to the customer? Which one of our customer´s problems are we helping to solve? Which customer needs are we satisfying? What bundles of products and services are we offering to each Customer Segment?
How can we combine our products / services with user generated value? Does user generated value support our value proposition?
What type of relationship does each of our Customer Segments expect us to establish and maintain with them?
Do we understand the relationships between our customers? How should we support conversation in the market and between customers? Do we need to address prosumers different from consumers?
For whom are we creating value? Who are our most important customers?
Who is creating value for your business model? What are the dynamics of value creation in your customers community?
Revenue Streams
For what value are our customers really willing to pay? For what do they currently pay? Is it possible to exploit user generated value commercially? Can we exploit our communities cross-laterally (e.g. combine revenue streams from pay per transaction and adverts?)
Figure 11: Extensions of Q&A for Business Model Innovation (downstream tasks)
If we look at the downstream tasks within Business Model Innovation, we need to be aware that stakeholders from Communities of Affinity are relevant contributors to our Business Model. With this background for the above mentioned business model innovation case on “Location Based Services (LBS)”, the following “must-dos” have been identified for the business case model on “LBS”: • No marketable products/services without UGC, • B2B customers (restaurants, shops, cultural institutions etc.) and consumers have to deliver content and have to pay for the products/services, • Pro-active community engineering: initiating a premium user-community, and setting up of an incentive system, • Clear IPR regulations, • Cross lateral exploitation (e.g. combining revenue streams from pay per transaction and adverts), • Integration of new enabling technologies (e.g. for trendscouting in the communities).
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Looking at the upstream tasks, we locate community integration into the Q&A template as follows:
Key Partners Key Activities Value Propositions
Community of Practice
ExWhat Key Activities do our perts Value Propositions require? What key activities are required to sustain our communities of knowledge?
Who are our Key Partners? Who are our key Community suppliers?Innova
of Interest
How can we ensure mutual learning within communities and
-tors
Key Resources
What Key Resources do our Value Propositions require?
Resear chers
What value do we deliver to the customer? Which one of our customer´s problems are we helping to solve? Which customer needs are we satisfying? What bundles of products and services are we offering to each Customer Segment? How can we combine our products / services with user generated value? Can we provide added value with complementary services our partners or communities?
Scientific Community
knowledge transfer to our business model?
What key ressources and organizational antecedents are required to embed successfully in our communities?
Cost Structure
What are the most important costs inherent in our business model? What are the cost impacts of Community involvement into your business model? Do we need to establish decisive incentive systems to ensure sustainable value creation through Communities?
Figure 12: Extensions of Q&A for Business Model Innovation (upstream tasks)
For our business model example “LBS” the outcome of the “must-dos” design discussion can be summarized as follows: • Pro-active community engineering, • Setting up a decisive incentive system, • Establishing learning arenas, • Trendscouting in the communities, • Integrating new enabling technologies (semantic technologies for search), • Collaborative design and development (games developer), • Controlling the transaction costs of community engineering. Organizational Adaptation with Ambidextrous Design Looking at the portfolio of requirements in the downstream and upstream tasks, Business Model Innovation needs to link the business model value architecture (in particular the configuration of the value-network partners) with the external communities [8]. In our case studies we have to consider at least four relevant communities (see again Fig. 8) as being of crucial importance for the performance of the new business model. We will illustrate thus using the example of the LBS Business Model Innovation:
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Communities of Affinity (CoAs): as already expressed, without User Generated Content, Web 2.0 tools for feedback and C2C interaction, there is no ‘lively system’ to attract users. The operating business architecture has to imply a strong “community engineering” unit to develop appropriate incentive systems for the mobilization of the community. The ‘basic settings’ of such a unit should comprise, “constant stimulating market conversation”, “perpetual monitoring of trends in market conversation to identify new user needs”, and “application of purposeful incentive systems” to stimulate affinity and identification-based trust amongst the community (e.g. by introducing a ‘famemirror’” [5]). Thus the organizational anchors into the community may be implemented with advanced social media tools and intelligent incentive systems to stimulate further user identification. These tools have to be designed on the basis of strict and reliable rules enhancing the confidence of users to participate. Communities of Practice (CoPs): the value-network has to sustain strong ties to surrounding value-partners who dispose of different types of data, information and knowledge. On the ‘content-side’, value-partners from, firstly, local and regional tourist information institutions, and, secondly, from event marketers, have to be involved to ensure content flows from professionally established content sources. Thus, links to experts and intermediaries that are engaged in the ‘knowledge space’ of tourism marketing, event marketing etc., have to be established carefully. Also weak ties to pools of professional authors of tourist information have to be developed to enable the flexible inclusion of professionally generated content into the application when needed. On the ‘technology side”, experts on multimedia data-integration, and the linking of different geo-data (including, for example, collaborative ontology-design engineering) have to be approached to ensure constant technology transfer and the provision of technical solutions to operate and further develop the business model. For organizational anchors to be embedded in these communities, we may at first consider developing a “transactive knowledge management system”, containing information on “Who knows what in tourism and event marketing?”, e.g. members and experts of regional tourism and event communities. A second implementation measure should be “membership of marketing and technology people from the value-network in selected communities of experts” to ensure knowledge transfer. Communities of Interests (CoIs): the value network has to extend its virtual organizational boundary along working groups of selected professional associations, (a) in the Digital and New Media Economy to include advertising agencies and onlinemarketing as well as search-engine optimizers, (b) in the tourism and event marketing sector to ensure support for the business model and links to B2B partners (e.g. shops and restaurants), and (c) in the local trade associations. The latter is an indispensable measure to connect to local trade partners as potential B2B-partners for the LBS application. Organizational anchors into these communities are clearly of the institutional kind, e.g. firms becoming members of the associations mentioned. Other paths into the CoIs involve recruiting freelancers who have formerly worked in the tourism and event marketing sectors as an initial step, and further networking along their personal relationships into the CoIs. Communities of Science (CoSs): One important aspect, already mentioned in the context of CoPs, is to establish strong ties to the Scientific Community on “Semantic Technologies and GPS technologies”. This is important in selecting personalized and geodata contextualized information - on the basis of time-of-day and life situation - for an
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immersive user experience. Thus conference visits, as means of loose ties to specialized scientific groups etc. are an appropriate organizational adaptation measure. Looking at the criteria of ‘ambidextrous design” (see Fig. 6), we may say in a nutshell that the value-networks needed to establish different adaptation mechanisms and to link them to relevant Communities of Knowledge can be summarized as:
LBS Business Case Implementation Mode Structural Mode Adaptation Condition Rules Decision Mak ing Communication Governance Control and Authority CoA
explorative mechanistic stable routinized explicit lateral learning trust
CoP
explorative organic flexible heuristical implicit lateral learning hierachy
CoI
exploitative mechanistic stable routinized explicit vertical advice hierarchy
CoS
exploitative organic stable heuristical implicit lateral learning hierarchy
Table 2: Organizational Adaptation: Ambidexterity Criteria for the Business Case “Location Based Services” To embed into the Community of Affinity, the LBS value network needs to establish reliable social media tools that stimulate identification-based trust amongst the community members. The required structural approach tends to be more ‘mechanistic’ at first glance, since it needs stable adaptation and reliable rules for feedback and market conversation. Decision making processes on, for example, how to display and exploit User Generated Content should be transparent and explicit, following equal rules of feedback and exploitation for all participants. At the same time, the organizational link to the CoA needs to enhance exploration and learning to ensure the exploitation of knowledge flows, especially UGC. For the Communities of Practice, the LBS value-network needs to be embedded more organically into the communities by engaging in working groups, establishing communication channels to different key stakeholders with specific knowledge etc. Thus, the adaptation mode should be more flexible, reaching from occasional participation to strong ties e.g. as an official member of special CoPs. The rules of embedding should be more heuristical, e.g. opening up organizational borderlines, including experience exchange with experts, and for inquiries from outside the firm. At the same time, there could be a need for controlling outside-in and inside-out flows of knowledge hierarchically. These should be agreed upon in the value-network, since the proper functioning of certain technological interfaces etc. is critical for the entire business model. In order to be embedded in Communities of Interest, the LBS value network may implement institutional engagements to install stable conditions for knowledge flows. Since the main aims are to exploit relevant knowledge from CoIs and to gain support for the business model, rules and decision models should be explicit, formalized, and stable over time.
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Finally, in order to link to Communities of Science, the LBS value-network needs to establish both strong and weak ties to certain technology providers, depending on the role and enabling potential of the technology. Thus, the principal mode should be exploitative (“What is the best technology, and how can I use it?”), and modes of participation may be organic (occasional participation in conference) etc.
5 Conclusions
In the Innovation 3.0 paradigm [8], Business Modeling is a challenging exercise, since the complexity of framework conditions, paths to embed into knowledge communities, exploitable technologies, architectural design of the value-network, interaction strategies with customers etc, is constantly rising. A multitude of trends that have impact on the future business model, as well as the crucial link to knowledge communities, pose additional questions in the course of Business Modeling that need to be considered. This paper has examined some of the main questions about Business Model Innovation in the Digital and New Media Economy. Expecting the trend to embed digital business processes into the - so far - “Analogous Industry”, we may expect similar questions and challenges of Innovation 3.0 to be raised in the “Old Economy” in the near future.
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