Designing Software Tools for Reflecting Sustainability

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Full Reference:

Schoormann, T., Behrens, D., and Knackstedt, R. (2018): The Noblest Way to Learn Wisdom is by Reflection: Designing Software Tools for Reflecting Sustainability in Business Models. In: Proceedings of the International Conference on Information Systems (ICIS 2018), San Francisco, USA. Online available: https://aisel.aisnet.org/icis2018/design/Presentations/7/

Software Tools for Reflecting Sustainability in Business Models

The Noblest Way to Learn Wisdom is by Reflection: Designing Software Tools for Reflecting Sustainability in Business Models Completed Research Paper

Thorsten Schoormann University of Hildesheim Universitätsplatz 1, 31141 Hildesheim, Germany thorsten.schoormann@ uni-hildesheim.de

Dennis Behrens University of Hildesheim Universitätsplatz 1, 31141 Hildesheim, Germany dennis.behrens@ uni-hildesheim.de

Ralf Knackstedt University of Hildesheim Universitätsplatz 1, 31141 Hildesheim, Germany [email protected] Abstract Business models can boost fundamental changes in behavior to act more economically, ecologically, and socially. To support the development of such business models, various approaches like business model notations and software tools have been proposed. However, while most of these approaches focus on economic aspects, ecological and social sustainability is rather neglected. In this article, we report on a design science study, in which we explore how to design information systems that effectively facilitate reflection of sustainability in business models in a multidimensional manner. Drawing on theoretical work, we iteratively derive design requirements and design principles as well as implement them in the form of a software prototype to demonstrate the feasibility. Doing so, we aim to contribute to the design knowledge that can be projected into concrete IT-artifacts and help practitioners to reflect sustainability already during the construction of a business model or during the analysis of existing ones. Keywords: Business Model Development Tools, Design Principles, Design Science, Sensemaking Theory, Reflection Theory

Introduction The rapid deterioration of the natural environment and concerns over growth of population are just some examples of current issues that pose fundamental challenges for our society (Brundtland 1987). Facing these challenges ‘sustainability’ has increasingly gained importance in business research and practice (e.g., Brocke et al. 2012; Elliot 2011; Melville 2010; Seidel et al. 2013), and businesses need to transform themselves to fulfill new stakeholder demands, for instance, being environmentally friendly (Hanelt et al. 2017). One central aspect for such transformations is the development of more sustainable business models that find novel ways for delivering and capturing value (Schaltegger et al. 2012). These novel ways often premise not only to rethink the value proposition, but rather radical innovations across entire businesses (Nidumolu et al. 2009). Thus, existing business models need to be rethought by both companies and

Thirty ninth International Conference on Information Systems, San Francisco 2018

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customers likewise to promote essential changes in behavior and practice (e.g., in consumption and production). Following Confucius, reflection is the noblest way to learn wisdom, which however, is challenging concerning the multidimensional concept of sustainability, and thus, needs to be supported. Approaches from business model research can be applied to capture the essence of a business as well as to visualize, innovate, and evaluate businesses (Veit et al. 2014). To do so, different business model modelling languages (e.g., the Business Model Canvas by Osterwalder and Pigneur) are proposed, which represent the basic logic and the important elements of a business model (John et al. 2017). Although these languages are well-established and applied in practice, they do not focus on sustainability necessarily (Bocken et al. 2015), which however is important to foster the design of innovative businesses, for example, by considering new financings or cleaner products (e.g., Lüdeke-Freund 2010). Thus, suitable approaches that allow reflecting sustainability (Lozano 2018) as well as appropriate software tools that facilitate the application of such languages and provide additional functions are required (Recker 2012; Veit et al. 2014). Software-based tools—business model development tools (BMDTs)—allow digitally representing and editing business models. They have enormous potential to contribute to certain actions (e.g., sharing and assessing) more efficiently than the ‘pen & paper’ versions as well as enable actions that go beyond the development with paper-based approaches (e.g., Ebel et al. 2016; Kamoun 2008; Osterwalder et al. 2005). Although various of these BMDTs have been developed, two main deficits occur, namely virtually no design knowledge for such tools is available (Szopinski et al. 2017), and challenges for reflecting multidimensional sustainability are not implemented. Accordingly, the primary goal of our research project is to address these deficits by deriving design knowledge for the class of software tools that allow for reflecting economic, ecological, and social sustainability in business models. Doing so, we respond to recent calls to explore facets of IT/IS support for visualizing and developing business models ( Osterwalder et al. 2005; Veit et al. 2014) by providing theory-grounded design principles. Consequently, we raise the following key question: How to design business model development tools for reflecting sustainability in business models? To pursue our goal, we conduct a design science research (DSR) study in which we iteratively develop and evaluate design principles for the class of business model development tools. Because there is a growing body of literature regarding business models and sustainability as well as an increasing availability of corresponding software tools, we aim to contribute to the functionality that should be proposed by such tools. Being aware of sustainability as a multidimensional issue, the concepts suggested in this article aim to analyze businesses not only from an economic view, but also from an ecological and social one. We provide knowledge that can be projected into concrete IT-artifacts, and if implemented, help practitioners to consider sustainability already during the construction of a business model or during the analysis of existing ones. For academics our contribution may act as a foundation for advanced theories that, for example, attempt to explain how specific functions affect the awareness of acting in a sustainable manner. In line with the DSR publication schema (Gregor and Hevner 2013), we first outline and discuss related empirical and theoretical work to position, motivate and justify our study (Section 2). Following the method by Kuechler and Vaishnavi (2008), we consecutively derive design requirements and design principles by building on general knowledge and theory as well as by conducting prototyping sessions (Section 3). Next, we translate the design principles into design features and implement them in a software prototype (Section 4). For evaluation, we use a Green IT business case from an industry partner and conduct workshops in which the participants reflect this case with our prototype (Section 5). As the evaluation led to the adjustment of the principles, we afterwards present the final design principles (Section 6). Finally, we discuss our findings, implications and limitations (Section 7), and conclude with our study (Section 8).

Research Background Related Work Business models have been a booming topic for both research and practice in various disciplines (e.g., Chesbrough 2002; Gordijn et al. 2000; Zott et al. 2011). A good business model answers: “Who is the customer? And what does the customer value? […] How do we make money in the business? What is the underlying economic logic that explains how we can deliver value to customers at an appropriate cost?” (Magretta 2002, p. 4) In general, the following components are used to describe a business: value proposition, customer segments, channels, customer relationships, key resources, key activities, key


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partners, revenue streams, and cost structure (Osterwalder and Pigneur 2010). Research on business models is heterogeneous, and thus, different streams exist such as taxonomies (e.g., categorizing types of businesses), business components (e.g., providing key constructs), methodologies (e.g., supporting innovation), or business model modelling languages (e.g., visualizing elements) (Kamoun 2008; Zott et al. 2011). In respect of the term ‘business model’, some authors refer (1) real company attributes, (2) cognitive and linguistic schemas, or (3) the conceptual/model aspect (Massa et al. 2017). In order to allow a software-supported development of business models, a specified business model understanding is required in particular (Osterwalder et al. 2005). Thus, various software tools for have been proposed, which support the application of certain modelling languages (conceptual/model aspects) for business models (e.g., Gordijn et al. 2000; Szopinski et al. 2017). These tools, BMDTs, allow representing and editing business models in distributed teams more efficiently than ‘pen & paper’, and are not limited to paper-based features. However, to the best of our knowledge, only limited research deal with the functions that these BMDTs should have. Ebel et al. (2016) explored functions for innovating business models in a general manner (e.g., install a business model template), and Schoormann et al. (2016) who, based on an review over 1.500 business model studies, provide a typology of customizations of the business model understanding (e.g., adding building blocks or integrating views). Nonetheless, we lack designrelevant knowledge concerning the functions that these BMDTs should possess in general (Szopinski et al. 2017) as well as functions aiming to facilitate sustainability-oriented reflection of business models. Contributing to sustainability presumes crucial changes in consumption and production from businesses and society alike. Sustainability is a complex term (Malhotra et al. 2013), which is usually divided into three dimensions, for example: Triple Bottom Line/Three Pillars (social, ecological, economic) or Triple Ps (people, planet, profit) (Elkington 1997). According to the Brundtland report, it is the “development that meets the needs of the present without compromising the ability of future generations” (Brundtland 1987, p. 43). Although the three pillars are rather an ‘ideal idea’ and hard to implement, our design principles for considering sustainability in business models follow the integrative definition of sustainability that aims to incorporate all dimensions equally. The coherence of business models and sustainability has been increasingly discussed in research over the last few years (e.g., Bocken et al. 2015; Lüdeke-Freund et al. 2017; Schaltegger et al. 2016; Upward and Jones 2016). Generally, a sustainable business model seeks to capture “economic value while maintaining or regenerating natural, social, and economic capital beyond its organizational boundaries” (Schaltegger et al. 2016, p. 6). Achieving a ‘more sustainable business model’ requires “a holistic and systemic reflection of how company operationalizes its strategy, based on resource efficiency (…), so the outputs have more value and contribute to sustainability more than the inputs.” (Lozano 2018, p. 6). Although the improvement of the sustainability performance often lacks in businesses (e.g., due to expected disadvantages like increased costs or lower efficiency), some studies identified positive consequences such as greater willingness to pay for green products, improved image, lower costs by reducing inputs (e.g., Hanelt et al. 2017; Nidumolu et al. 2009). However, to contribute, business model research has to critically deliberate and adapt their artifacts to provide constructs and features that allow reflecting multidimensional sustainability.

Theoretical Foundations One essential aspect of conducting rigorous DSR is to draw on existing theories (e.g., Gregor and Jones 2007), the knowledge base (Hevner et al. 2004). To provide a valid grounding and to understand how the class of software tools for business model development can allow reflecting sustainability-oriented concepts, we build on knowledge from business models and IS-enabled sustainability transformation. We argue that first it is reasonable to consider sensemaking theory to explore how people create a shared awareness and allocate their experiences meanings (Weick 1995), which is already applied for transforming businesses towards sustainability by using IS (e.g., Degirmenci and Recker 2016, 2018; Seidel et al. 2013, 2017; Tallon and Kraemer 2007). The theory is used to explain situations in which complex, uncertain and changing environments are faced. Reflecting and ultimately developing more sustainable business models is a multi-layered and complex task because it requires the consideration of economic, ecological, and social factors as well as is surrounded by uncertainty and ambiguity (e.g., global market and availability of resources). Triggered by such an uncertainty and ambiguity, sensemaking allows providing a frame to interpret and understand the challenging tasks related to sustainability transformation (Seidel et al. 2013), which therefore seems to be a valuable starting point for our research.


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Sensemaking has become increasingly important in the study of individual and social activities (Weick 1995) to improve sustainability-oriented performance or transformation (Seidel et al. 2013). According to Weick (1995), sensemaking is a highly social and retrospect process in which people generate awareness of certain situations and give meanings to their experiences. In doing so, it specifies the “cognitive process involved in sensing, weighing and synthesizing external stimuli into a single point of statement of belief.” (Tallon and Kraemer 2007, p. 15) In organizational sensemaking, two fundamental features need to be addressed (Seidel et al. 2013): ‘reflective disclosure’ (i.e., monitoring, analysis, and representation of environmental indicators), and ‘information democratization’ (i.e., information access and interaction). In general, seven characteristics are proposed including grounded in identify, retrospective, enactive of the environment, social, ongoing, focused on extracted cues, and driven by plausibility (Weick 1995). Because our purpose of contributing to sustainability in business models is complex, and thus, requires collective information sharing and assessment, sensemaking may help to understand how tools can enable sensing of certain issues as well as facilitate weighing and synthesizing knowledge of articulated business alternatives. Second, we consider reflection theory to understand how experiences can be reflected to derive learnings for the future (Boud et al. 1985). In general, reflection theory has some overlaps with sensemaking theory such as understanding the past in a collaborative manner. However, the main difference is that reflection has a strong focus on deriving insights for the future (Prilla 2014), which is important to guide further actions related to the design of new or alternative business models. Hence, reflection is a common part of individual and cooperative work aiming at continuous re-assessing experiences to gain insights and guide decision-making for prospective improvements (Boud et al. 1985; Kolb 1984). Reflective thinking is especially important when managers face novel challenges for which they do not have mental models (Schoen 1983), or when a team has to deal with unsolved problems (Daudelin 1996) and perplexed troubled, or confused situations (Dewey 1933), which both apply to the case of developing sustainable business models as this can be a complex, conflicting, and multidimensional task. Due to the challenging nature of sustainability, we would argue that the analysis and rethinking of a business model (element) or the selection of an alternative depends on the object/concept that is used for comparison (e.g., is ‘A’ better than ‘B’ in a certain perspective?). Thus, it is rather a relative construct. Nonetheless, because making clear what has to be reflected against what—‘reflection as comparison’ (List 2006)—to derive adequate solutions for the future pose various challenges, we further refer to reflection theory (Boud et al. 1985; Kolb 1984). Reflection has been endorsed as a practicable approach in education and industry (Lynch and Metcalfe 2003). Generally, reflection involves activities for collecting experiences, re-assessing them in the current context and deriving learnings (i.e., concrete action plans) for prospective work (Boud et al. 1985; Gibbs 1988). To do so, the two basic steps of (1) articulating tacit knowledge as well as of (2) exploring the represented knowledge in a critical manner have to be carried out (Maheswari and Boland 1995). Reflection is usually classified into two types (Schoen 1983): ‘reflection-in-action’ (i.e., assumptions and alternatives are evaluated during the action) and ‘reflection-on-action’ (i.e., retrospective analysis of actions and their effects). From a pragmatic view (Dewey 1933), one fundamental issue is to specify what has to be reflected against what. To ensure rigorousness reflection, a set of explicit concepts (e.g., trying to be environmentally friendly) has to be reflected on an intuitive solution. As a result, creating innovative concepts against which a person can reflect to, becomes an essential task. Reflection theory tries to facilitate the process of reflecting, motivate certain activities, and integrate existing knowledge (Lynch and Metcalfe 2006), which might help to understand how software can contribute to the reflection of sustainability in business models.

Research Method ‘Design science’ is appropriate for investigating IT support in the context of business model development (Veit et al. 2014). While new approaches for reflecting sustainability in business model tools still need to be designed, the maturity of the problem of acting in a sustainable manner is high. Therefore, we position our work as an improvement research (Gregor and Hevner 2013), which addresses better solutions for known problems. The development of design knowledge is of high importance in research and practice (Kuechler and Vaishnavi 2008). Design principles are the prevailed way to capture such knowledge about instances of a class of artifacts in IS research (Chandra et al. 2016), which is helpful for both technology oriented and management oriented audiences (Sein et al. 2011). They provide a general solution that can be instantiated into concrete IT applications, and thus, are an IT meta-artifact (Iivari 2007). For developing such design principles, we first solve a specific problem by building concrete artifacts and derive general solution concepts for the class of business model tools afterwards (Iivari 2015).


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Our research process for deriving design principles is well-grounded by the method from Kuechler and Vaishnavi (2008), which is already applied in business model research (e.g., Augenstein and Mädche 2017). In total, we ran through three different cycles—over approximately two years—of suggesting, developing, and evaluating our artifact until the current set of design principles was developed . In each of these cycles, we apply a staged approach that differentiates between three activities (Meth et al. 2015): First, based on general knowledge and theoretical foundations, we derive design requirements that are rather generic and can instantiated by any artifact from this kind of design. Second, to meet the design requirements, we determine a set of design principles that generalize knowledge about artifacts. Third, because design principles are commonly free from technical aspects, we describe design features (here understood as a specific way for implementation), which are afterwards instantiated in the form of a software prototype serving as an expository instantiation (Figure 1). Next, each design cycle will be described in detail. Applied DSR Method

Cycle 1: Initial Design Principles

Cycle 2: Revised Design Principles

Cycle 3: Final Design Principles

Outcome

Awareness of Problem

Literature review; tool analysis

Analysis of lessons learned from the evaluation in Cycle 1

Analysis of lessons learned from the evaluation in Cycle 2

Design requirements

Suggestion

Conceptualization of design principles based on empirical findings and theoretical findings

Revision and consolidation of design principles (Cycle 1) based on lessons learned

Revision and consolidation of design principles (Cycle 2) based on lessons learned

Design principles

Development

Instantiation of design principles as a paper prototype (prototyping session, n=32, year 2016)

Instantiation of design principles as a paper prototype (prototyping session, n=41, year 2017)

Implementation of revised design principles as a software prototype

Design features and artifact instantiations

Evaluation

Qualitative evaluation of prototype (workshop, n=3; written exams, n=23, year 2016)

Qualitative evaluation of prototype (workshop, n=3; written exams, n=29, year 2017)

Qualitative evaluation of software prototype (workshop, n=19; observation, year 2017)

Evaluation results

Analysis and reflection of all results

Abstracted design knowledge

Conclusion

Figure 1. Research Method Adopted from Kuechler and Vaishnavi (2008) Cycle 1: initial design principles. Based on an extensive analysis of software tools and literature related to business models, our study started with an awareness of two major problems: the current lack of (1) comprehensible design knowledge of features that support reflection of sustainability in business models, and (2) appropriate software tools that contribute to the application of these features. Thus, the purpose of the artifact to be designed is to provide prescriptions on the development of the class of BMDTs that support sustainability-oriented reflection. Therefore, we specify design principles that can be instantiated, for example, in concrete software prototype. The identification of such principles should be well-grounded in theory (i.e., use of existing knowledge) and empiricism (i.e., demonstrating and evaluating its applicability) (Goldkuhl 2004). To achieve this, we apply deduction by reviewing prior literature and theories, and induction by conducting several prototyping sessions, workshops, and analyzing written exams. For suggesting a solution, we build on existing theories that help to explain and justify the technical design, namely sensemaking to understand how a shared awareness of sustainability can be supported (Weick 1995), and reflection theory to understand how experiences are reflected while specifying future steps (Boud et al. 1985). Furthermore, we make use of related studies (Ebel et al. 2016; Schoormann et al. 2016)—see research background. In the development phase, we carried out prototyping sessions for respecting potential users and their needs already at an early stage. Therefore, interdisciplinary groups of 32 students (IS and Environmental Preservation) with knowledge related to sustainability and business model development were formed randomly. These groups (each with 4-6 students) developed paper prototypes that provide features for instantiating the design principles. To do so, as a first step, we discussed the set of principles with the participants to reduce issues within the exercise itself. Next, the students had 90 minutes to represent negative and positive effects of sustainability in a specific case by using the current principles. For evaluation, the results of each group were discussed and consolidated with all the students and three researchers in a follow-up workshop. In this workshop, each prototype was presented by (a) indicating the concrete results of representing sustainability, (b) reflecting the applicability of the principles as well as (c) verify the set of principles. Finally, the participants consolidated all findings independently to provide more insights regarding the understandability and applicability of the artifact. Therefore, 23 students discussed relevant features—instantiation of principles—in a written exam (with an incentive scheme; 120 minutes) in which they reflected sustainability in a given business model.


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Cycle 2: revised design principles. Based on the problems learned in Cycle 1, we suggested a revised set of design principles, which are—similar to the cycle before—instantiated in prototyping sessions with 41 participants who did not attend in the first round. In order to evaluate the results, again, a follow-up workshop was conducted in which the findings were discussed and consolidated with the participants and three researchers. Moreover, 29 students reflected the findings independently in a written exam. Cycle 3: final design principles. Afterwards, we analyzed the lessons learned and consolidated the knowledge gathered during the previous cycles with three researchers, which again led to the adjustment and revision of the design principles. Based on this, we suggest a new set of principles that are implemented in a web-based software prototype. For evaluation, five groups of knowledgeable master students (n=19) were formed that used the software prototype to complete a given task dealing with the representation and analysis of a real-world business model from an industry partner that addresses social and ecological aspects (see Section 5). For practical relevance, we discussed the results with our industry partner.

Artifact Description Derivation of Design Principles As we argue that reflection of sustainability can be supported by specific features, our study refers to the designed system and its features as IT artifact. The principles emerge from the theoretical-driven derivation (Cycle 1), the empirical revision (Cycle 2), and the consolidation in the beginning of the current iteration (Cycle 3). For presenting our principles, we first specify an ID (DP1-DP6) and a short title of each design principle. Second, we follow (Chandra et al. 2015, p. 4045) who suggest to address the material property, activity of users, and boundary conditions (here: user groups that are engaged in the development, analysis, and innovation of business models, particularly in terms of ecological and social sustainability). Moreover, we use design requirements (DR1-DR10) to mark theoretical foundations (see also Figure 3). DP1a—representation. Provide features for representing the basic logic of a business model in order for users to create a transparent and shared understanding of the business during the development of new business models or the analysis of existing business models within a team. Making sense in distributed teams premises a shared understanding (DR1) of the object—‘information disclosure’ (Seidel et al. 2013)—that is of interest (Weick et al. 2005), which can be in a visual and a multimodal mode (Weick 1995). Therefore, to create transparency, experiences and information need to be articulated (DR2), which is the basis for reflection because thoughts have to become visible to further reflect them (Daudelin 1996; Gibbs 1988; Maheswari and Boland 1995), and for experience ambiguity to create an initial sense that can be further interpreted (Weick 1995). Business model modelling languages support communication and documentation by usually using graphic notations to represent the basic logic and the most important elements of a business model (e.g., John et al. 2017). The two most important types of business model modelling languages are (Kamoun 2008) process-oriented approaches such as e3-value (Akkermans and Gordijn 2003) and holistic-oriented approaches such as the Business Model Canvas (Osterwalder and Pigneur 2010). By using these languages, the user can create transparency of the core business logic and thereby contribute to a shared understanding in an efficient and effective manner. Also previous studies recommend to install a common business model template (Ebel et al. 2016). DP1b—adaptation. Provide features for customizing a selected business model representation in order for users to integrate sustainability-oriented semantics in a purposeful schema during the development of new business models or the analysis of existing business models within a team. The representation of information in a schema that aids the analysis and development of insights (DR3) is fundamentally (Pirolli and Card 2005). To reflect sustainability, existing business model modelling languages are often adapted to provide sustainability-oriented semantics (Schoormann et al. 2016). For example, in addition to the original Business Model Canvas, context-specific variants for sustainability have been suggested such as the Triple Layered Business Model Canvas (Joyce and Paquin 2016) or the Flourishing Business Canvas (Upward and Jones 2016). During the workshops, the participants applied different adaptations like adding new components for ‘society and environment’, ‘social impacts’ and ‘ecological benefits’ or dividing ‘costs’ into ‘social, ecological and economical costs’. For example, in Cycle 2, 23/29 added new blocks, 16/29 divided blocks, 6/29 changed the arrangement, and 4/29 renamed blocks.


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DP2a—key concepts. Provide features for emphasizing sustainability-oriented key concepts, strategies and questions in order for users to consider established concepts that can be reflected against during the development of new business models or the analysis of existing business models within a team. To provide concepts against that can be reflected (DR4) (Lynch and Metcalfe 2003), relevant information in terms of sustainability should be highlighted, for example: strategies like efficiency, consistency and sufficiency, the 17 Sustainable Development Goals (United Nations 2018), or concrete approaches like ‘use renewable resources’ and ‘look at the entire life cycle’. To support reflection, a software tool needs to promote certain features (DR5), for example, through pop-up dialogues (Prilla 2014). In the prototyping sessions, we could also observe that it is helpful to pop-up such type of information in order to allow continuous comparison of the business model elements against sustainable key concepts. During the workshops, the users applied these concepts to identify improvements and to get ideas for the (re-)design. DP2b—perspective. Provide features for creating and applying sustainability-oriented perspectives on business models in order for users to take different views such as economic, ecological and social ones that can be reflect against during the development of new business models or the analysis of existing business models within a team. To promote reflection, it is helpful to take different views (DR6) on a business model or on a single business model element. Sensemaking theory suggests to focus on and by extracted cues (Mills et al. 2010), so certain elements should be focused while interpreting them. In addition, reflection theory emphasizes the use of different filters on a current situation as well (List 2006). Accordingly, the aim of this principle is to lower the complexity and enable taking various views on the construction, analysis, and interpretation of a business model, for example, by using established frameworks that recommend perspectives for economic, ecological, and social sustainability (e.g., Elkington 1997). During the evaluation, we observed that some of the participants (Cycle 2: 11/29) in the workshops added perspectives to analyze each business model component and business model element from the three perspectives separately. Moreover, these views therefore act as concrete concepts against that a reflection can be carried out (Lynch and Metcalfe 2006). DP3—assessment. Provide features for assessing sustainability-oriented impacts of a business model (element) in order for users to identify improvement needs and plan precise future efforts during the development of new business models or the analysis of existing business models within a team. While reflecting sustainability in a business model, the consideration of positive and negative consequences related to different options is essential (Lynch and Metcalfe 2006; Prilla 2014). Therefore, it has to be verified whether certain experiences were good or bad (DR7) to estimate which impacts might occur (Gibbs 1988). Reflecting issues of a business like ‘what needs to be improved?’, and ‘which impacts does it have?’ presumes a rating of the elements modelled. The workshop participants argued that “an easy assessment of business model elements is needed to support the identification of improvement potential quickly”. DP4—collaboration. Provide features for interacting in order for users to discuss and share sustainability-oriented aspects that can be reflect against individually a collaboratively during the development of new business models or the analysis of existing business models within a team. Collaboration is important for both theories. Sensemaking is a social systems and interaction, conversation, and communication, whether physically present or not, (DR8) is important to make sense of the environment (Mills et al. 2010; Weick 1995). Further, to support ‘information democratization’, access and interaction to ongoing discussions should be provided (Seidel et al. 2013) in order for users to share and learn from each other (Degirmenci and Recker 2018). Moreover, in sensemaking, it is of relevance who we are and what factors have shaped our lives (Weick 1995), so user profiles (DR9) including, for instance, user competencies are assumed valuable for software tools (Ebel et al. 2016). For promoting reflection, tools should address critical discourses within a team, sharing of experiences, and commenting (Maheswari and Boland 1995; Prilla 2014), because also in real-world people are used to discuss challenging situations with more experienced colleagues to find a solution (Daudelin 1996). Overall, innovating business models requires the involvement of people from various disciplines and is therefore a highly collaborative task. DP5—predefined characteristics. Provide features for categorizing and visualizing a set of appropriate business model constructs in order for users to reflect current business model elements against sustainability-oriented alternatives during the development of new business models or the analysis of existing business models within a team.


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One of the challenges for rigorous reflection is to develop a range of appropriate concepts (DR10) that can be compared to each other (Lynch and Metcalfe 2006). To contribute to this, meaningful alternatives to the current situation should be described (Seidel et al. 2013) to provide a set of categorized alternative business solutions (Prilla 2014; Weick et al. 2005). These categorized aspects build a basis for comparison as well as for figuring out possible next actions (Mills et al. 2010; Seidel et al. 2017). Business models often have common characteristics and the availability of these characteristics allows for systematic configuration as well as for an easy comparison of existing business models like from the same domain (Osterwalder et al. 2005). The use of such characteristics (e.g., in form of business model patterns) provides a considerable reduction of complexity (Remane et al. 2016; Schoormann et al. 2017). In the workshops, we could observe that it is helpful to select from predefined characteristics during the development like for weighing up alternatives for an element (e.g., how to replace an element that has negative effects on sustainability?). DP6—reasoning. Provide features for tracking reasons in order for users to reconstruct certain sustainability-oriented design choices during the development of new business models or the analysis of existing business models within a team. During the workshops, participants asked for features that allow documenting the history and justifying changes, which might be also in line with the retrospective nature of sensemaking (Weick 1995). While constructing a business model, knowledge at various levels is developed, for example, in terms of the design choices and decisions that have been made. Different stakeholders in a modelling project should know the rationale behind a certain business model, element or decision (e.g., ‘why we used the element that has more emissions?’—‘Because of technical constraints’). Therefore, the chain of reasoning should explicated (Knackstedt et al. 2014). Evidentiary reasoning (Pirolli and Card 2005) is also demanded by sensemaking.

Implementation of Design Principles As business model development is a highly collaborative task, we decided to implement our prototype (GBM Editor) as a web-based application. Following a common three-tier architecture, it consists of a presentation tier (user interface), logic tier (application logic), and data tier (storage etc.). By using the Model View Controller (MVC) pattern we are able to monitor user interactions as well as connect the three tiers. The presentation tier is implemented by using the open source toolkit Bootstraps that enables HTML, CSS, and JavaScript to be developed. The logic tier exchanges data via JavaScript Object Notation (JSON) and the controller transmits these data to a corresponding model. The data tier is realized with a MySQL database. As design principles are free from technical specifications and there are various ways to instantiate them (Meth et al. 2015; Morana et al. 2014), we first translate them to more specific design features (DF1-DF12), which are than translated into our software prototype. Next, the design features are presented. DP1a—specifying an underlying business model modelling language. As stated in Section 2, the Business Model Canvas (Osterwalder and Pigneur 2010) is by far the most widely used modelling language for business models in both research and practice. Accordingly, we initially implemented the Business Model Canvas as an underlying approach (DF1). Furthermore, we allow extending the set of notations by adding additional approaches and designing completely new approaches. DP1b—adapting the underlying business model modelling language. Although the Business Model Canvas is well-accepted, different variants and extensions of the original canvas for representing sustainability are proposed (Schoormann et al. 2016). Accordingly, we provide features that allow adapting the canvas including adding new, dividing, linking/merging and renaming building blocks as well as changing the arrangement of the building blocks (DF2). Overall, users can easily customize an underlying approach as well as modify colors, sizes, titles, and shapes in their projects (DF3). DP2a—considering key concepts and questions for sustainability. In order to provide additional information and concepts related to sustainability, we implemented checklists (DF4). Checklists are a type of information artifact, which indicate work that has been carried out or should be carried out (Reijers et al. 2017). Initially, we draw on checklist items that include key concepts for environment (e.g., closed-loop production or cradle-2-cradle), society (e.g., creating local jobs), and economy (e.g., comply with regulations) (Schoormann et al. 2016). In doing so, the users get ideas, incentives, and directions for (re)designing a business model in terms of sustainability. Because we observed during the workshops that common strategies (e.g., efficiency, consistency, and sufficiency) were applied to identify improvement potential, our tool support allows using existing checklists, extending them, and creating new ones.


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DP2b—specifying perspectives. Although sustainability is a complex term, it is—according to the common Three Pillar Model—often divided into economic, ecological, and social dimensions. In addition, business model modelling languages make already use of it and differentiate between these views (e.g., Joyce and Paquin 2016). In order to provide corresponding features, views for economic, ecological, and social sustainability are available by default. In addition, we allow specifying individual perspectives in a modelling project. These can be controlled via different tabs like in a web browser (DF5). DP3—assessing sustainability. Based on our workshops and an extensive literature review (Schoormann et al. 2018), we suggest a comparison-oriented assessment in the form of a trade-off analysis (DF6) in which the users can unrestricted collect and discuss positive as well as negative consequences regarding sustainability of a single element within a team. The discussion in a team contributes to an initial assessment of elements, and thus, to the identification of improvement potentials towards sustainability. A heterogeneous team in particular allows for considering different point of views and goes beyond single knowledge basis, which is helpful as assessing sustainability is a multi-perspective issue. In our prototype, the number of collected reasons is displayed in each element, here Post-Its. Furthermore, the coloration of single blocks of an underlying modelling approach (e.g., the value proposition) and single elements is supported (DF7). With respect of the metaphor of a traffic light, these blocks and elements can be colored to represent the ‘degree of sustainability’, which has been often applied during the prototyping sessions. DP4—supporting collaboration. As collaboration supports sensemaking and reflection of current business models as well as the development of innovative alternative business solutions, we provide features that, for example, allow creating user profiles (e.g., including own interests and competencies) (DF8), inviting other users, and sharing business model projects. For sharing a project, the owner can specify email addresses of users to be invited. Afterwards, the other users can access an individual copy of the modelling project. Moreover, business models can be exported, which allows for exchanging data (DF9). To support discussion during the business model development, we integrated a chat (DF10). DP5—using predefined characteristics. To provide characteristics, we implemented a building-blockbased modelling approach (e.g., Schoormann et al. 2017). Therefore, we allow selecting from existing building blocks (i.e., repository of characteristics) as well as adding new ones. The basic concept contains three major parts: First, a repository that includes all created building blocks. Second, the search and selection of suitable blocks for an individual case (i.e., a domain filter, for example, to limit the selection of items available). Third, the application of the blocks selected (DF11). In doing so, the users get an overview of typical elements and can select an alternative solution that might have better impacts on sustainability. DP6—documenting reasons. Tracking why an element is modelled as it currently is may contribute in different situations (e.g., a user identified potential for improvement but does not know that this cannot be modified—thus, the action cannot be carried out anyway. We provide features that allow tracking reasons including a title, description, and a timestamp to generate the history of changes from an element (DF12).

Evaluation DSR evaluation can be conducted ex ante or ex post the design as well as in an artificial or naturalistic setting (Venable et al. 2016). For evaluating the software prototype, we carried out an ex post artificial evaluation in an educational context. Artifacts that characterize the structure of a system are typically evaluated through the implementation of prototypes, which demonstrate the applicability by building illustrative scenarios of a synthetic or real-world-situation (Peffers et al. 2012). As our artifact instance is in a prototype stage, the validation in an artificial setting is appropriate (Sonnenberg and vom Brocke 2012). We conducted a workshop in which the participants use the prototype demonstrating the utility and efficacy in a real-world case to indicate that the artifact is useful for its intended purpose. For practical validation, we interviewed our industrial partner. Afterwards, we derived lessons learned with three researchers.

Setting of Evaluation Workshop At the beginning, five groups with 19 participants (i.e., each group with 3-4 members) of knowledgeable master-level students from IS, Information Management, and Environment Prevention were chosen as subjects. These randomly formed groups reflected sustainability in a real Green IT business case from an industry partner that addresses ecological and social aspects. The business focuses on remarketing of IT


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hardware provided by regional companies and public administrations (ecological). The process of preparing (e.g., deleting data) and recycling is mostly conducted by staff who have a disability (social). In total, the workshop was divided into three major parts, each with a length of 90 minutes. First, to create a sufficient information basis and to ensure the relevance in practice, the sales manager of our partner introduced their business case and discussed essential components with the participants (who are allowed to make memos). In the second and third part, each group was confronted with the following task: reflect sustainability while modelling the business case presented with our software prototype. Moreover, each group created a ‘change log file’ in which customization of the underlying business model modelling language (here, Business Model Canvas) should be described, and the application of certain software features should be justified. To obtain additional information regarding the handling of our prototype, each group was observed by a researcher who created an ‘observation log file’. In this log file questions regarding the adaptation, procedure of modelling, use of features, and general organization within each group (e.g., typical roles or decision-making processes) had to be answered. Next, to validate the quality and ensure practical relevance of the resulting business model representation, we interviewed an expert of our industry partner. We particularly focus on (1) the correctness and completeness of the business model, (2) the usefulness of the customizations of the underlying language, and (3) the visualization of the business model strengths and weaknesses. Overall, most aspects are represented correctly and just some supplements were suggested like adding the real names of the company’s partners or prioritizing some sticky notes by putting them into the top a business model component. Due to the fact that a ‘common’ representation does not necessarily allow communicating sustainability-oriented aspects in a direct manner, the expert especially like the idea of adding blocks for social and environmental benefits as well as drawbacks. He argued that is important to ensure transparency, which includes presenting positive efforts as well as admitting negative effects. Moreover, the representation should not only focus on environmental or social aspects because, to be competitive and sustainable in the market, it is fundamental to be perceived by the customers as a ‘professional company’. Thus, the main aspect in the value proposition should be a generalized activity. Green Business Modelling Editor (beta) Project

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