Introducing the Circular Economy to IT Management through Architectural Thinking

Introduction and theoretical background Due to environmental damages and regulatory changes, more companies across various sectors are embracing circular business practices [1]. This transition requires changes within the organization (e.g., business models, product design, technological innovation) and beyond (e.g., industrial symbiosis, material sourcing, product maintenance, and consumer relationships). From an organizational perspective, shifting or introducing a circular business model encompasses all domains and departments, including strategic planning, research and development, operations management, sustainability management, service management, and information technology (IT) management [2]. As companies rely on increasingly complex data ecosystems for collaboration, tracking sustainability and CE-related tasks becomes challenging [3]. Given the complexities and novelty of the CE concept, IT managers and departments face the challenge of integrating sustainability and CE into enterprise information systems and associate organization strategy and sustainable outcomes [4]. We argue that the intertwinement problem of organizational sustainability, CE tasks and decisions, and data ecosystems requires a utility-centered approach to designing enterprise IT systems. Consequently, this study builds on the concept of architectural thinking (AT) [5], which involves more than the IT department in everyday decision-making on long-term system aspects and fundamental design principles. Architecture includes the fundamental concepts, properties, and principles governing an entity’s realization and evolution within its environment [6]. In Enterprise Architecture (EA), the “entity” refers to an organization. Despite the benefits of EA management, scholars point out that its impact may be limited when restricted to IT departments [5, 7]. Consequently, an emerging trend shifts EA management toward AT, a more flexible and user-oriented approach, enabling broader engagement in the analysis, planning, and transformation of architecture and IS structures [5]. Hence, this approach encourages including stakeholders with varied domain knowledge (e.g., business, sustainability, and IT) when designing enterprise IT systems [7]. AT can be fostered by developing modeling competencies for systematically analyzing socio-technical interactions [8]. Accordingly, we state our research question as follows: Which aspects and relations should be integrated into an architecture meta-model to incorporate sustainability and circular economy and thereby leverage architectural thinking in the context of digitalizing the circular economy in organizations? The study aims to create a Circular Economy Information Systems (CE IS) architecture meta-model to promote AT and address sustainability and CE within IS. This meta-model is intended to guide business, sustainability, and IT stakeholders in addressing sustainability and CE-related concerns from an organizational perspective. Methods and Results This research employs the Design Science Research (DSR) methodology, which focuses on creating real-world solutions and contributing to the design knowledge for IS artifacts, such as instantiations, methods, models, or concepts [9]. DSR can yield two types of contributions: novel design artifacts and design theories. We followed the DSR guidelines of Peffers et al. [10], and conducted three design cycles with six stages each: (1) problem identification and motivation, (2) defining objectives of a solution, (3) design and development, (4) demonstration, (5) evaluation, and (6) communication. The design cycles yielded our novel design artifact, namely the preliminary CE IS architecture meta-model. The meta-model comprises four horizontal layers, structured according to the TOGAF standard architecture, and three vertical perspectives. The horizontal layers are titled business, information service (or application), data, and IT [11]. The three vertical perspectives focus on specific topics within the architecture, namely system, environment, and governance. This meta-model serves as a template to highlight key socio-technical aspects and relationships, offering flexibility for adaptation when instantiating an EA model to meet stakeholders’ needs and concerns. The following subsection details each layer of the meta-model. Conclusions We address the research question by outlining a meta-model that allows business, sustainability, and IT stakeholders to create EA models that address specific challenges related to CE tasks and decision-making. EA project teams can slice and use the meta-model in various configurations (horizontally, vertically, or diagonally) to tailor architectural models to their needs, fostering organizational AT of sustainability concerns. The meta-model shows that design choices regarding data processing and volume can impact Carbon and Material Footprints, enabling EA project teams to optimize data use for a circular business while minimizing environmental impact and eventually achieving data sufficiency. Consequently, the meta-model fosters the alignment between sustainability/IT strategies and sustainability/IT implementations. [1] I.-M. García-Sánchez, F.-M. Somohano-Rodríguez, V. Amor-Esteban, and J.-V. Frías-Aceituno, "Which region and which sector leads the circular economy? CEBIX, a multivariant index based on business actions," Journal of environmental management, early access. doi: 10.1016/j.jenvman.2021.113299. [2] M. V. Barros, R. Salvador, G. F. do Prado, A. C. de Francisco, and C. M. Piekarski, "Circular economy as a driver to sustainable businesses," Cleaner Environmental Systems, vol. 2, 2021, doi: 10.1016/j.cesys.2020.100006. [3] A. Ixmeier, J. J. Kranz, J. Recker, and R. Zeiss, "How to unlock the potential of information systems for a circular economy," in Research handbook on information systems and the environment (Research handbooks in information systems), V. A. Cooper, J. J. Kranz, S. K. Mathew, and R. T. Watson, Eds., Cheltenham UK, Northampton, MA, USA: Edward Elgar Publishing, 2023, pp. 74–99. [4] C. Harnischmacher, B. Herrenkind, and L. Weilbier, "Yesterday, Today, and Tomorrow - Perspectives on Green Information Systems Research Streams," in ECIS 2020 Proceedings, Marrakech, 2020. [5] R. Winter, "Architectural Thinking," Bus Inf Syst Eng, vol. 6, no. 6, pp. 361–364, 2014, doi: 10.1007/s12599-014-0352-2. [6] Software, systems and enterprise: Architecture description, 42010:2022, International Standards Organization, 2022. [7] S. Aier, N. Labusch, and P. Pähler, "Implementing Architectural Thinking," in Advanced Information Systems Engineering Workshops: CAiSE 2015 International Workshops, Stockholm, Sweden, June 8-9, 2015, Proceedings, A. Persson and J. Stirna, Eds., vol. 215, 2015, pp. 389–400, doi: 10.1007/978-3-319-19243-7_36. [8] K. Sandkuhl et al., "From Expert Discipline to Common Practice: A Vision and Research Agenda for Extending the Reach of Enterprise Modeling," Bus Inf Syst Eng, vol. 60, no. 1, pp. 69–80, 2018, doi: 10.1007/s12599-017-0516-y. [9] R. Baskerville, A. Baiyere, S. Gergor, A. Hevner, and M. Rossi, "Design Science Research Contributions: Finding a Balance between Artifact and Theory," JAIS, vol. 19, no. 5, pp. 358–376, 2018, doi: 10.17705/1jais.00495. [10] K. Peffers, T. Tuunanen, M. A. Rothenberger, and S. Chatterjee, "A Design Science Research Methodology for Information Systems Research," Journal of Management Information Systems, vol. 24, no. 3, pp. 45–77, 2007, doi: 10.2753/MIS0742-1222240302. [11] The TOGAF® Standard, The Open Group, 2022. [Online]. Available: https://pubs.opengroup.org/togaf-standard/index.html