Business Modelling in the Dynamic Digital Space: An Ecosystem Approach

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Itier coordinates the actions of French ministries to promote the field of social innovation and the social economy. Uwais works to provide affordable and accessible microcredit to microenterprises. Wong has spearheaded social innovation and social enterprise in public policy with numerous governments across the Asia-Pacific region.

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Seelos develops insight that helps organizations make better strategic and operational decisions about innovation, scaling and system change. Frances Westley Canada , J. Westley specializes in the areas of social innovation, sustainable development, strategic change, visionary leadership and inter-organizational collaboration. The meeting will explore four themes: transforming markets, accelerating climate action, financing sustainable development and mobilizing action for inclusive societies.

For more information on the award categories and nominations for the award, please visit www. Read the Meeting Overview. The Forum engages the foremost political, business and other leaders of society to shape global, regional and industry agendas. In the case of digital products like mobile phones, for example, customers using the same hardware will rarely if ever make all of the same software choices, or use the devices in the same ways and in the same contexts.

Customers willingness to pay, too, will vary greatly. Instead of assuming value is delivered in standard quantities by digital products and services, then, it is more useful to see value as an experience created through use and perceived by each customer upon the enactment of a digital service.

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This perspective of value-in-use or value-as-experience or. Chesbrough This is even more true in digital business ecosystems. Digital services, unlike drills, do not even come off an assembly line looking the same. The value conversion perspective was written about by strategy researchers Normann and Ramrez and in recent years has grown into a bold new logic of value creation in the marketing field Vargo and Lusch , called the service-dominant logic SDL , this new theory holds that value is co-created by customers and a network of firms and other actors.

Whether these actors are providing activities services , or frozen activities in the forms of products like Levitts drill , what they are really exchanging are applications of capabilities, skills, and knowledge. Thus products and services are best thought of as value offerings or propositions. They have potential value that may or may not be exercised by customers. To create value, then, firms and customers are partners. Firms develop and deliver potentially-valuable offerings, and customers assemble and utilize these offerings in context to realize value.

Value is phenomenologically experienced and contextually interpreted by the customer Vargo and Lusch ; Chesbrough Thus value conversion is a subsequent step after value creation. This paradigm draws our attention to the importance of the unique characteristics of customers and the contexts in which they use services. One of the key takeaways from the service-dominant logic is that no service occurs unless customers apply the offering activity or product in context.

We may be used to thinking of a firms services as activities that it can provide. That may be appropriate when a firms service offerings are standardized and repeatedits analogous to treating services as commodity productsbut when studying digital business ecosystems where every enactment of a service is unique, we must study value creation by focusing on how service offerings are and are not actually applied. This leaves us with no good answer to the question of how managers can appropriate, or even measure, the value that they are co-creating with customers through digital services.

The literature of strategic management, by contrast, has a long tradition of theorizing about value appropriation in competition. The dominant strategy paradigm at the firm level of analysis is the resource-based view RBV in which competitive advantage accrues to firms that have control of strategically important resources, such as assets and capabilities Barney In its basic form, the RBV states that resources must be valuable have value-creating potential , rare among competitors, imperfectly imitable, and non-substitutablethe so-called VRIN characteristicsin order to be sources of competitive advantage.

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Combining the RBV with the value creation logic just discussed, one might argue that if a firm has a VRIN capability to perform an activity better, faster, or cheaper from the customers point of view than its competitors, its value proposition is more likely to be accepted. The VRIN conditions do not always hold, and are especially problematic in digital business ecosystems where capabilities evolve and become obsolete. These empirical problems have led some researchers to develop new variations on RBV theory to explain value appropriation in less ideal environments. The first variation argues that firms can profit from services in which they have no VRIN advantages as long as they have complementary assets that are VRIN Teece While IBM captures no value from sales of Linux, the widespread adoption of Linux allows it to capture value from its complementary offerings.

A related concept is that of cospecialization of resources; resources may be designed such that they have greater value potential together than separately Teece We might suppose, for example, that Intels microprocessors and Microsofts operating systems are not VRIN by themselves, but being designed to work in concert, the combination of the two may have unique advantages compared to other platforms. An interesting question is whether the RV theory applies the same way to platforms as it does to alliances.

In the years since Dyer and Singh wrote about dyadic alliances possessing VRIN resource combinations, we have seen a rise in the importance of digital platforms Gawer and Cusumano ; Iansiti and Levien Defined by standard architectures and interfaces, platforms allow modular connection of activities and resources across firms. Platforms are less exclusive than alliances, but potentially much more powerful. The open resource-based view Schlagwein et al. Thus, in a digital business ecosystem, value is co-created, co-converted, and co-captured together with the different players in the ecosystem: customers, competitors, complementors, and community see Fig.

In such a digital business ecosystem, one of the key issues is the balance between value creation, value conversion, and value capture Iansiti and Levien Thus, enterprises in keystone positions in the ecosystem may choose to leave many activities of value creation to others in the ecosystem, while choosing to focus on creating value that is critical to the ecosystems prosperity.

In digital business ecosystems, this may mean the creation of common digital platforms for the delivery of digital services whose value can be shared with the entire ecosystem, such that value conversion can take place. However, it also needs to ensure that it can capture part of the value. This balancing act between different players in a business ecosystem becomes much more complex when we are dealing with a digital business ecosystem.

It also means the design of effective digital business models for the. This requires an awareness of core changes and shifts in the ecosystem. They form a holistic interactive whole and influence each other. This is depicted in Fig. The emerging evolutions and disruptions in digital platforms that are taking hold are the easiest to identify.

While technological change is rapid, the adoption of new digital platforms in mass scale such that it influences the deep structure of the ecosystem takes a longer time El Sawy et al. For many years, the analyst firm Gartner has studied the technology adoption hype cycle and has shown that typically after an initial hype phase, all technological changes go through a period of diminished expectations, then the ones that survive and are adopted in mass scale go through a period of enlightenment where effective solutions and actionable innovations can be achieved by enterprises.

Table 1. The proliferation of broadband cloud computing The spread of serviceoriented architecture and modular applications The proliferation of untethered smartphones with multisensory interaction Augmented reality becomes practically useful. The forceast is for billions of This will generate a flood of data sensors and devices to be on the internet, as well as connected to the internet, and further bring to prominence growth of machine-tothe need for data analytics machine communication Computer hardware, software, Enterprises will have have the and data will be hosted on the digital capabilities to be cloud highly flexible and scale quickly Software applications will be Enterprises will be able to put aggregated through lego-like together new application smaller components software on the fly Smartphone devices will take The ubiquity and richness of advantage of haptics, body interaction with digital computing, and avanced voice devices and interfaces, will be recognition unprecedented Our real-world environment will We will finally be able to be enhanced through integrated digital technologies computer-generaated sensory into our physical world much input more effectively.

Transparency is Making actions, processes, and an expected relationships visible norm Open source A volunteerism and sharing of efforts sharing and and opinions with peers peering Digital attention The ubiquity of continuous internet disorder access and multitasking leads to continuous partial attention The rise of The combination of a global outlook glocalization and the need to preserve the local culture and context.

Strategy for sustainability as a business opportunity, rather than a constraint will yield new business models for the bottom of the pyramid Progressive companies will use digital technologies to augment transparency Social media will become the dominant mode of interaction and relationships Attention will be very scarce resource, and services based on business models that conserve it will be highly valued A new form of global markets will emerge that are both connected and segmented.

Our survey of the technological landscape for such changes in digital platforms through our knowledge of the industry through repeated interaction with CTM participating companies suggests that a number of such changes. We have identified five of those as being most likely to influence the structure of the digital business ecosystem in the year They are shown in Table 1. Similarly, we have identified a number of shifts in societal values worldwide.

These key changes in digital platforms and societal values interact with each other and the way that value is created in enterprises. We examine in the next section how the impacts of the changes that we have identified above will influence the enterprise in We articulate those changes for the enterprise in the form of what we have called game changers. A person who is a visionary is often referred to as a game changer. An enterprise which conceives a new strategy in its industry or ecosystemand that forces or induces other players to fundamentally change their strategiesis often.

An idea or an event that completely changes the way a situation develops is referred to as a game changer. Radically changing the way that something is done or thought about is referred to as a game changer. A disruptive event or crisis that disrupts industry boundaries or changes the rules of competition, or changes the fabric of a social order or society is often referred to as a game changer. Similarly, evolutionary changes which gather critical mass and momentum and are adopted by a large number of people can be game changers. So, for example the adoption of social networks such as FaceBook has been a game changer in how social relationships are maintained, how people interact and communicate, and how they share ideas.

And that game changer in turn in the case of social networks for example can also trigger and enable other phenomena which in turn also become game changers at the next level such as crowdsourcing, or open innovation, or management by consensus. Thus, game changers can also occur or be created in a cascaded manner over time. Thus, technological shifts and societal value shifts can beget enterprise game changers. Drawing on those two sets of shifts and their implications, we then show how they cascade into a set of enterprise phenomena that are likely to be game changers for the enterprise of We have combined the implications of Tables 1.

They are: the primacy of the customer experience, distributed co-creation of value, and continuous sense-and-respond experimentation. They are depicted in Fig. They are further explained below:. Designing more effective customer experiences around services provided through digital platforms will take center stage in designing new digital business models. With the shifts in digital platforms and societal values outlined above, there will be a constellation of phenomena around this game changer.

First, the notion of customization and personalization will become very elaborate and sophisticated. Second, each consumer will own a digital rich identity on the internet that captures his or her preferences, tastes, interests, etc. Third, given the scarcity of attention and the need for personalization, the dominant paradigm on the internet will change from search to discovery, in which services learn a customers preferences and discover them, sometimes proactively.

Fourth, this primacy of experience will be further augmented by multiple modes of access and devices with multisensory capabilities. This game changing constellation will transform the digital business models of enterprises in With the shifts in digital platforms and societal values outlined above, this will become a game changer for enterprises in , especially in terms of the different ways that value is co-created with customers, competitors, complementors and community.

The trends suggest that there will be a constellation of phenomena around this game changer. First, with distributed co-creation of value the boundaries of the enterprise will be much more porous and it will be more difficult to define where the enterprise ends and the other parts of the ecosystem begin. Second, open innovation will likely be a dominant mode of operations as new products and services need to come to market more quickly for diverse customers. Third, the notion of prosumption will take hold as consumers of services and products engage in their production through processes that we are already seeing in phenomena such as.

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Fourth, with the emphasis on sustainability and glocalization, we will see much more emphasis on the poor of the world or as they are often called the bottom of the pyramid. The launch of new products and services will be accompanied by digital online pilots that can cheaply and easily gather information. First, most new and emergent product testing will be done through online experiments in which products are tweaked and emerge continuously over time.

Second, with all the burgeoning of sensor data, there will be a surge in sophistication in sensor data analytics that will enable intelligent interpretation of data.

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Third, business intelligence will become rooted around social media and networks, and we will be able to troll social media for market insights. The whole area of mass opinion business intelligence combined with sensor data analytics will give enterprises tremendous new capabilities for sense-and-respond experimentation.

These three game changers provide the context for the enterprise in in which new digital business models will be designed and assessed, and we use them to generate scenarios and configurations for digital business models for Enterprise in Chap. A primary reason for such a seemingly random process is the lack of a generally accepted definition of the term business model within which to provide systematic analyses.

In fact, multiple definitions of business models exist, which pose significant challenges for understanding essential components. In general, there is no accepted definition of the term business model Shafer et al. Although, the origins of the expression business model can be traced back to the writings of Peter Drucker Ramon et al. Many have observed that the term business model became widely adopted by practitioners during the dotcom revolution of the s. While business model has been part of the business jargon for a long time, it has been argued that the focus initially involved a scientific analysis of firms has been on industry, and resources, as shown by the works of Porter and Wernerfeld Hoyer et al.

Others, in fact, some have argued that the concept of a business model, is relatively new, dating back to only the early s. Furthermore, there is little theoretical underpinning in the literature, Linder and Cantrell ; Morris et al. The plethora of definitions poses significant challenges for understanding the essential components of a business model. They also lead to confusion in terminology as business model, strategy, business concept, revenue model and economic model are often used interchangeably and moreover the business model has been referred to as architecture, design, pattern, plan, method, assumption and statement Morris et al.

For example some definitions of business models: a. Baden-Fuller et al. Timmers defines the business model as architecture for product, service and information flows, including a description of the various business actors and their roles; and a description of the potential benefits for various business actors; and a description of the sources of revenue Timmers Mahadevan defines a business as is a unique blend of three streams that are critical to the business.

These include the value stream for the business partners and the buyers, the revenue stream and the logistical stream Mahendran Johnson et al. Ostenwalder et al.


Therefore we must consider which concepts and relationships allow a simplified description and representation of what value is provided to customers, how this is done and with which financial consequences Ostenwalder et al. Teese, defines, business articulates the logic and provides data, and other evidence that demonstrates how a business creates and delivers value to customers. It also outlines the architecture of revenues, costs, profits associated with the business enterprise delivering value Teese Demil and Lecocq, define business model as, the description of the articulation between different business model components or building blocks to produce a proposition that can generate value for consumers and thus for the organization Demil and Lecocq Sorescu et al.

In addition, the concept of business models can be seen as having progressed in 5 stages as shown in Fig. In the initial phase, when the term business model started to become prominent, a number of authors suggested business model definitions and classifications. Then, during the second phase authors started to complete the definitions by proposing what elements belong into a business models. Initially, these propositions were simple shopping lists, just mentioning the components of a business model.

Only in a third phase followed detailed descriptions of these components Hamel ; Weill and Vitale ; Afuah and Tucci In a fourth phase researchers started to model the components conceptually culminating in business model ontologies. In this phase models also started to be more rigorously evaluated or tested. Finally, in the fifth phase, the reference models are being applied in management and IS applications. We assert that in the sixth phase, the focus is now on theory building and dynamic modeling.

A business model is a representation of the strategic choices that characterize a business venture. These choices are made either intentionally or by default, so the contribution of a business model is to make them explicit Morris et al. Thus, the business model can be seen as a communication or a planning tool. It allows entrepreneurs, investors, and partners to examine strategic choices for internal consistency, to surface the assumptions of the business plan, and to understand the vision toward which the business is being built.

Business model development may be part of new venture planning, but is often just as useful in sense making around a going concern, or when new opportunities and threats indicate a need for reinvention Johnson et al. HBR Furthermore, although properly formed business models are very useful and can be a strategic tool for a firm, many business models however suffer from 4 common problems Shafer et al. Limitations in the strategic choices considered; addressing and developing the business logic in only one component of the business model, and making untested assumptions about the others.

Misunderstanding about value creation and value capture; the inability of organizations to financially capitalize on the value they create, which may thus negatively affect the revenue generation aspects of business models. Flawed assumptions about the value network; assumptions that the current value created through the network would continue unchanged into the future and not change dynamically. Table 2. The number of components proposed in each model ranges from 3 to 9.

In general, three general categories of definitions based on their emphasis, namely economic, operational and strategic, each with their unique set of decision variables have been identified Morris et al. The economic approach focuses on how a firm can make a profit and key variables from this approach include revenue sources, pricing methodologies, cost structures, margins and expected volumes. Fundamentally stated, this approach deals with how a firm can make money and sustain its revenue stream into the future Stewart et al.

Alternatively, the operational approach focuses on the firms internal processes and design of infrastructure that enables firms to create value, with key components such as production or service delivery methods, administrative processes, resource flow and knowledge management, with the objective of key designing interdependent systems that create and sustain a competitive business Mayo and Brown In the strategic approach, emphasis in on the overall direction of the firms marketing position, interactions across organizational boundaries, and growth opportunities.

This approach espouses the totality of how a firm selects its customers, defines and differentiates its offerings, creates utility for its customers, define the tasks it will perform or outsource, configures its resources and ultimately captures profits Slywotzky Decision variables focus on stakeholder identification, value creation, visions, values and networks and alliances. We have progressively transitioned from a focus on the design of information systems, to the design of IT-enabled business processes, and more recently to the design of business models for services provided through digital platforms Fig.

While this attention to business models for digital platforms initially started in the networked digital industry telecom, media, entertainment, gaming. As more customers consume products and services offered through digital platforms, the managerial stakes in understanding those models is becoming much higher, especially when these products and services have to be offered to and priced for consumers.

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  5. A review of Table 2. Thus, digital business ecosystems are new and different. Companies operate in a technology-enabled and digitally interconnected environment characterized by new affordances, structures, and rules El Sawy et al. The information systems discipline has explored and explicated many of these differences.

    One of its most important conclusions is that technology and business are effectively fused. Dubosson-Torbay et al. Value proposition, value architecture, value finance, value network integrated approach. To theorize about new business models and by adding a few digital features to the theory would lead to what we call the horseless carriage fallacy. That term for the first automobiles constrained the imagination and blinded inventors to the fact that the new design challenge was fundamentally different than the old.

    We realize that a theory of digital business models and digital service must integrate the distinct attributes of digital business ecosystems from the get-go Yoo et al. There are at least three such attributes: time compression, turbulence, and new architectures. Responding to the velocity and turbulence of the environment, and taking advantages of the affordances of digital technology, firms and groups of firms have been prolific in establishing digital platforms for the combination of technologies and the delivery of services Gawer and Cusumano Taking advantage of the digital affordance of modularity, platforms enable firms to focus their attention and innovation on one part of a system at a time, and to assemble those partswhether they are products or activitiesinto a variety of configurations.

    As business models have become more digital, firm capabilities themselves have become more modular, more easily connectable, and more conveniently shareable. In prior decades it might have taken a formal alliance and a joint venture to make one firms technology compatible with anothers, but today, riding on rails of application programming interfaces APIs and broadband fiber optics, we can mash up digital services like Googles maps and Facebooks social newsfeed in no time and on a shoestring budget.

    Digital business ecosystems enable the possibility of combining capabilities across boundaries into innovative new offerings and solutions to create and capture value Schlagwein and Schoder The scientific objectives of this project are to advance our theoretical understanding of the structure of business models for digital platforms by devising a unified framework that brings together multiple elements and underlying drivers. This will allow us to better understand current and future business models, and to help the creation and categorization of a business model repository that researchers can continuously contribute to over time.

    This will also facilitate analyzing, from a more theoretical approach, the effects of disruptions and game changers. Understanding the theoretical structure of digital business models will also enable us to map the likely evolution of business models for the future. Information systems design theory was developed by Walls et al. Each of those constitutes of several components.

    On the design product side, a set of meta-requirements that describe the class of goals to which the theory applies is determined. The term meta-requirements rather than simply requirements was used because a design theory does not address a single problem but rather a class of problems. The second component on the product side is a meta-design which describes a class of artifacts hypothesized to meet the meta-requirements.

    Again, the concept of meta-design is used because a design theory does not address the design of a specific artifact e. A third component is a set of kernel theories. Table 3. Meta-requirements 2. Meta-design 3. Kernel theories 4. Testable design product hypotheses Design process 1.

    Design method 2. Kernel theories 3. Testable design process hypotheses. Describes the class of goals to which the theory applies Describes a class of artifacts hypothesized to meet the metarequirements Theories from natural or social sciences governing design requirements Used to test whether the meta-design hypotheses satisfies the metarequirements A description of procedure s for artifact construction Theories from natural or social sciences governing design process itself Used to verify whether the design hypotheses method results in an artifact which is consistent with the meta-design.

    The final component is a set of testable design process hypotheses that can be used to verify whether the meta-design satisfies the meta-requirements. On the design process side there are several components of a design theory. The first component is a design method that describes procedures for artifact construction.

    A second component is a set of kernel theories from the natural or social sciences governing the design process itself. These kernel theories may be different from those associated with the design product. The final component is a set of testable design process hypotheses that can be used to verify whether or not the design method results in an artifact that is consistent with the meta-design. In order to apply design theory to digital business models, there would be a requirement to construct and test such theories for classes of business models, rather than instances of business models.

    An Ecosystem Approach

    Thus, we believe we cannot a generic design theory for digital business models as we could not have a generic design theory for all classes of information systems. Thus, one could build design theories for each of executive information systems, knowledge management systems, transaction processing systems, customer relationship management systems, etcetera, as a class of information system. So, conceivably we could build design theories for different classed of digital business models. Similarly, we could build a design theory for long-tail business models, or social media business models, or open innovation business models, ex cetera.

    We could also use kernel theories from the social sciences such as consumer behavior, transaction cost theory of the firm, or organizational behavior. However, in order to do that we first need to develop a conceptual framework for articulation, development and better understanding o f the components of digital business models. In the information systems design theory field, we have agreement on what an information system is and what.

    We agree that there is hardware, software, procedures, users, etc.

    In design theory for digital business models we are not at that stage yet and we need to define a conceptual framework for what the components of a digital business model. These are the prerequisite precursors to design theory. Figure 3. Thus, the VISOR1 model attempts to integrate the different approaches in business model development, as well as to address unaddressed key elements such as the user experience and interface factors.

    While these factors are not explicitly recognized in most of the approaches as summarized in Table 2. At its core, a good business model must answer the age-old questions, as Peter Drucker is often quoted as asking, Who is the customer? And what does the customer value? How do we make money in this business? What is the underlying economic logic that explains how we can deliver value to the customers at an appropriate cost? Mageretta Thus, from the VISOR perspective, a successful business model is one that is able to align the respective components of the VISOR model so as to deliver the greatest value proposition that maximize the willingness to pay on the part of its target consumers, on the one hand, with the.

    Many researchers in the fields of strategy, e-commerce, and entrepreneurship have promoted frameworks for business model development. They differ slightly, but the common thread is that they begin with the question What value are we providing to the customer? In the unique environment of the NDI, we believe that this process requires five key steps:.

    The willingness to pay is a direct function of whether these applications provide value creation in that they satisfy an unmet latent end-user demand, or value substitution in that they provide only an alternative means for end-users to access an existing application or service. The business modeler must identify the value provided to the ultimate customer or end user, even if the firm is part of a multi-firm value chain and doesnt reach the consumer directly. The key tension here is between the broad definition of the customer base, and the specificity of the value proposition.

    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach
    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach
    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach
    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach
    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach
    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach
    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach
    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach
    Business Modelling in the Dynamic Digital Space: An Ecosystem Approach Business Modelling in the Dynamic Digital Space: An Ecosystem Approach

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