1. Introduction
Digital transformation (DT) is becoming increasingly important, both in an academic [
1] and a business [
2] context, with events such as the COVID-19 pandemic having triggered companies to speed up their plans for DTs [
3]. DT is defined as “a process that aims to improve an entity by triggering significant changes to its properties through combinations of information, computing, communication, and connectivity technologies” [
4]. Based on an extensive literature review, Vial [
4] presents a DT framework consisting of eight building blocks: use of digital technologies, disruptions, strategic responses, changes in value creation paths, structural changes, organizational barriers, negative impacts, and positive impacts.
DT can play an important role in sustainable development and environmental sustainability (ES). For instance, ref. [
5] suggest that integrating the digital economy and the real economy can help resolve the contradiction between economic growth and environmental quality, after studying the relationship between industrial digitalization and enterprise environmental performance showing a significant environmental improvement by reducing the number of pollutants produced in the front-end production process. In addition, including ES in an organization’s value proposition can be an important differentiating factor from both the customer and employee perspectives [
6]. ES, however, is noticeably absent from Vial’s [
4] DT framework. ES, as defined by [
7], involves responsible natural resource management to meet current needs without compromising future generations. Although Vial [
4] acknowledges the necessity of incorporating ethical considerations like corporate social responsibility in DT, the author overlooks the connection between ES and DT.
As DT relies significantly on the application of Digital Technologies [
4], not including ES in the DT effort can cause companies to miss out on potential opportunities for reductions in their environmental footprint (EF) when transforming the organization. The EF can be expressed as the environmental consequences of the activities a company performs [
8]. Even worse, organizations could be running the risk of ignorantly increasing their EF, unaware of the potential negative effect a DT can have on ES. This potential negative effect in terms of energy consumption and related greenhouse gas (GHG) emissions should not be underestimated: Digital technology’s energy consumption increased by almost 70% between 2013 and 2020 [
9]. In a 2019 study, the world’s collective footprint of CO
2 equivalent emissions (a metric to compare different greenhouse gas emissions based on their global warming potential) associated with digital technology was calculated to account for nearly 3.7% of all GHG emissions and is projected to double by 2025 [
9]. This number corresponds with a more recent publication comparing different estimation techniques, resulting in an estimate of 2.1–3.9% of GHG emissions in 2020 being due to information and communications technology (ICT) [
10]. The major contributors to ICT emissions are data centres (45%) and communication networks (24%) [
11].
Even though these numbers are significant by themselves, the reality seems even more dire. Freitag et al. [
10] identify three main reasons why current ICT emission estimates are underestimated and why emissions will continue to increase. First, processor efficiencies are reaching a limit due to transistor size limits. Second, improvements in energy efficiencies and processing power of ICT trigger an increased adoption of these technologies, leading to rebound effects where efficiency gains are counterbalanced by demand growth. In addition, a natural peak in emissions (e.g., due to a limited number of devices per person) is unlikely due to trends such as the Internet of Things (IoT), which require little to no person-time and can operate in the background, driving both embodied and use phase emissions for devices, networks, and data centres. Third, current studies in ICT GHG emissions often omit important energy-intensive ICT growth areas such as Blockchain Technology (BT, including cryptocurrencies), IoT, and Artificial Intelligence (AI), leading to an incomplete picture. Significant investment in the development and adoption of the latter technologies will result in further GHG emission increases.
Recognizing the simultaneous challenges and opportunities of DT and ES, the European Council has proposed a digital-driven shift towards a climate-neutral economy, urging the need for policy frameworks to mitigate any environmental drawbacks of digitalization [
12]. However, despite the introduction of initiatives to reduce or limit the GHG emissions of ICT, there is a clear lack of incentives or enforcement mechanisms for the decarbonization of ICT [
10]. Policy makers are working towards the use of digitalization to accelerate the transition towards climate-neutrality [
12]; nevertheless, the urgency of global warming does not afford the luxury of waiting for the enforcement of policies to trigger a change in the right direction. Organizations need to proactively take up responsibility for their EF and take action in lowering emissions. This kind of corporate environmental responsibility requires organizational awareness concerning the EF throughout all layers of the organization and leveraging transformational opportunities such as DTs to actively decrease the EF.
In the review article Sustainability through digital transformation: A systematic literature review for research guidance [
13], the author concluded that research on the relationship between DT and sustainability is extremely fragmented into sectors, functions, and methods. The author found that published research is mostly industry-specific (e.g., agriculture or industry 4.0) or ICT theme-specific (e.g., big data or digital twins) and concludes that the specificity of the sectors and contexts highly limits the generalizability and transferability of research findings and calls for a more generalizable approach. For further research, the author proposes research questions such as “How can digital and sustainability transformations be combined?” and “What factors influence the relationship between sustainability and digitalization?” [
13]. The growing prevalence of DT thus presents a distinctive opportunity to enhance ES through planned or ongoing organizational transformations. However, achieving this necessitates a comprehensive and practical strategy supported by concrete tools and frameworks. This paper proposes that such a strategy could be realized by employing an Enterprise Architecture (EA) approach. Van Riel and Poels [
14] define EA as serving three fundamental purposes: value creation, enterprise coherence, and strategic alignment. EA coordinates the roles, processes, information, applications, and technology necessary for an enterprise to fulfil its objectives, thereby promoting value creation. It ensures enterprise coherence by integrating these diverse resources into a unified, cooperative system. Strategic alignment, a pivotal aspect of EA, involves transforming strategic resource decisions into an organizational blueprint. This blueprint channels resources towards value creation, in harmony with strategic goals and the overarching vision of the enterprise. Moreover, the EA approach can incorporate ES objectives in the DT strategy, facilitating the strategic integration of sustainability aspects into the organization’s digital transformation.
Several studies have also connected EA with ES [
15,
16,
17,
18,
19,
20]. However, they generally remain very high-level and conceptual or are still in a preliminary research phase. As such, they currently lack specific and actionable EA information, tools, and techniques to leverage DTs for improving an organization’s ES. Other tools and frameworks exist to lower an organization’s EF. Environmental Management (EM) systems such as ISO 14001 already offer a holistic framework to manage, monitor, and control environmental issues, focusing on, for instance, efficient use of resources and reduction of waste [
21]. However, in the realm of EA, organizations often adopt a multi-layered approach that covers various aspects of their operations, such as the business layer, which defines governance and processes, the data layer that determines how data are structured and managed, and the application layer, which deals with software solutions. Unfortunately, the mentioned systems, such as ISO 14001, fail to establish a clear link between DT and these diverse architecture layers within an organization. This misalignment complicates the integration of DT initiatives that should ideally span across these layers. Adding to the complexity, EM initiatives often lack cohesion, being scattered across specific business units instead of being harmonized throughout the entire enterprise [
17].
Feroz et al. [
22] presented research trends regarding DTs in the ES domain. The authors concluded, however, that there is a lack of studies covering the capabilities required for sustainably transforming businesses and incorporating digital technologies. As such, Feroz et al. [
22] propose a research agendum “Capabilities for environmentally sustainable digital transformation”, including incorporating ES in the decision-making process at the strategic level. The practice of Capability-Based Management is a recognized EA approach towards achieving strategic alignment, enterprise coherence, and value creation [
14]. In this context, a capability is defined as the ability and capacity that enable an enterprise to attain a given goal in a certain context [
23]. Capabilities are realized through dynamic configurations of four dimensions: people, information, processes, and technology [
14,
24]. Examples of frequently occurring capabilities include Develop Vision and Strategy, Develop and Manage Human Capital, and Manage Information Technology [
25]. For this study, there are two ways in which applying Capability-Based Management can be relevant. First, to improve the DT outcome and related ES, the configuration of the dimensions of existing capabilities, often labelled as the operating model, will have to be aligned with the DT and ES objectives. Second, it is expected that new capabilities will have to be sourced or created in order to realize these DT and ES objectives.
This paper attempts to leverage the strength of EA in providing a holistic view of an organization and guiding its DT while extending it with ES concepts, actions, and tools to help incorporate ES into DT. We propose the term Green Enterprise Architecture (Green EA or GREAN) to represent this ES-extended EA concept. To achieve this, the research in this paper focuses on answering the research question (RQ): How can EA be leveraged as an actionable tool in supporting the inclusion of ES in current or future DT initiatives? The final aim is to provide, next to an academic contribution, a first framework for practitioners that can be used to indicate and assess areas where actions can be taken to improve their ES. Our research advocates for a comprehensive Green EA approach to ensure environmentally sustainable outcomes in digital transformations. This paper primarily addresses the integration of ES into DT initiatives using the principles of EA. While the significance of DTs and ESs grows, the incorporation of ES into DT remains underemphasized. To remedy this gap, we introduce Green EA as an evolution of traditional EA, which explicitly prioritizes ES and provides a bridge between DT and ES in the organizational context. By consolidating existing (yet fragmented) research and literature, this paper presents a novel representation of these insights, making them actionable for organizations. Green EA, focusing on the Capability-Based Management (CBM) approach and the organizational strategy, business, data, application, and technology layers, empowers organizations to seamlessly integrate ES considerations throughout their DT initiatives. As a result, businesses are equipped with a comprehensive view of their environmental impact, allowing them to keep their digital advancements congruent with sustainable practices. Furthermore, our unique contribution lies in curating the extensive literature into Courses of Action (CoAs), which provide a first tangible base for organizations to get started with these insights. This will facilitate translating academic knowledge into a first form of pragmatic organizational strategies. The integration of these CoAs into a capability map further enhances the practicability of the Green EA framework. Utilizing CBM, we present a framework that allows organizations to align their DT endeavours with sustainable practices. Another key contribution is the proposition of an ES-aware business capability modelling approach, an innovative business modelling approach that integrates environmental sustainability principles into the organization’s capabilities by using (in a novel way) the presentation and analysis methods that capability mapping offers.
The remainder of this paper is structured as follows: the next section (
Section 2) provides background information on the most relevant topics and reviews the related research.
Section 3 describes the research method, how the academic state of the art concerning EA as leverage for ES has been studied, and the design and development of the presented artefact.
Section 4 then presents the artefact and its substantiation, forming the core of this paper. Next, the findings are discussed in
Section 5, where practical implications, limitations, and future research are discussed. Finally,
Section 6 presents the conclusions of this study.
2. Background and Related Work
As discussed in
Section 1, research on the relationship between DTs and sustainability is insufficiently generalized, limiting the transferability of research findings. In addition, there is a lack of studies covering the capabilities required for sustainably transforming businesses and incorporating digital technologies. Also, existing systems do not offer a clear link between DTs and the different architectural layers within an organization. There is thus a need for a holistic and actionable approach supported by concrete and usable tools and frameworks, for which EA is proposed. To validate the research gap of Green EA, the academic state of the art concerning EA as leverage for ES is studied through a systematic literature review (SLR).
A Boolean literature search has been performed on the databases Web of Science and EBSCOhost. The search terms and fields of the first iteration are presented in
Table 1. A second iteration of the SLR was performed via Google Scholar: three searches were performed using the search terms (1) Green enterprise architecture, (2) “Enterprise architecture” environmental footprint, and (3) “Enterprise architecture” environmental sustainability. Iteration 1 resulted in a total of 127 potential sources, including duplicates, while, for iteration 2, the first 10 results pages for each search were included. First, relevant papers were selected through abstract scanning using the inclusion criteria: English language, time period 2007–2022, sustainability refers to environmental sustainability, and the author focuses on improving ES through the use of enterprise architecture. This selection was then further trimmed by reading the entire paper using the same inclusion criteria. The SLR resulted in 12 relevant references (
Table 2). This rather low yield indicates a lack of research on the topic.
The usability of EA development methodologies to support enterprise sustainable development has been studied by Pankowska [
30] with a focus on Green ICT. EA is positioned as ensuring transparency, credibility, comprehensiveness, and consistency for corporate sustainability. The author states that since changes in an organizational strategy lead to changes in EA, a sustainable strategy formulation must be followed by enterprise engineering coupled with a feedback loop to update that strategy. The author concludes, however, that existing EA frameworks poorly support ES [
30]. The following references mostly attempt to bridge this existing gap by extending EA frameworks or by proposing new EA frameworks that include ES.
One of the earliest mentions of coupling EA with ES is presented by Isom et al. [
29], who propose the concept of Intelligent EA for Green and beyond to enable a green organisation. Their work focusses mostly on the methodology of Intelligent EA coupled with the concept of Smarter Planet, which involves a vision to bring a new level of intelligence to the interaction of people, organizations, and systems. The authors briefly discuss a scenario with green initiatives from a technology–architecture point of view to enable greening within and across the organization. Examples of such initiatives include server storage virtualization, more efficient cooling, and using cloud services as enablers for green enterprises [
29].
Stating that environmental responsibility is fast becoming an important aspect of strategic management and recognizing that the implementation of environmental reporting and management systems are often not properly integrated into the overall business strategy, Noran [
17] argues for the integration of EM projects into the continuous EA. The author states that businesses are not achieving the maximum benefits from implementing and operating EM projects and proposes achieving a synergy between the EM system and the organization by presenting a reference architecture framework and meta-methodology using EA artefacts. Noran [
17] mentions the usually disjointed nature of EM efforts with regard to the enterprise and discusses four key success parameters for EM projects that are typically well-addressed by EA: (1) top-management support for the project champion, (2) sufficient authority and appropriate human/infrastructure resources, (3) a suitable strategy integrated with the general company strategic direction, and (4) a cross-departmental approach. The author argues that EA can provide an overarching and life-cycle-based approach for EM projects aiming to set up an EM system in an integrated and coherent manner concerning the organization and its environment. For this, the author selected, as the architecture framework, the Generalised Enterprise Reference Architecture and Methodology (GERAM) [
32]. The author concludes that integrating EM into EA best addresses the lack of EM integration with business and Information Systems (IS) and the pitfall that EM initiatives need to be internally driven and permeating throughout the business to achieve cultural change. The focus of the paper is facilitating EM implementation through EA. For this, a few EA artefacts are described; these, however, remain at a conceptual level and are insufficiently concrete to allow immediate application in a business context.
Leveraging the GERAM framework has also been discussed by Alves et al. [
18], who focus on the incorporation of sustainable development (SD) requirements into EA frameworks. The authors discuss that none of the most common EA frameworks explicitly consider SD and present guidelines to extend components of GERAM with ISO standards and frameworks related to sustainability. They propose the incorporation of the ISO frameworks ISO 9001 [
33], ISO 14001 [
34], and ISO 26000 [
35] to achieve, respectively, the economic, environmental, and social requirements of SD. Indicating the lack of SD requirements in GERAM, the authors propose including a sustainability view in the framework inspired by ISO 14001 to increase awareness of the enterprise and its involvement in environmental practices through continuous improvement, including the management of a green supply chain through, e.g., selection of suppliers [
18]. The recommendations, however, remain very high-level and conceptual, making them insufficiently actionable.
The term “Green Enterprise Architecture” was only encountered once in this SLR, in the work of Unhelkar [
31], who views Green EA as an all encompassing strategic approach towards Green ICT within and across an organization. The author discusses the use of green ICT systems, such as carbon emission management software, for greening an organization. Capturing carbon emission related data, upgrading traditional business intelligence systems to incorporate environmental data, and disseminating these data through a green ICT portal is discussed [
31]. The focus of the presented Green EA is mainly on carbon emission management software and its incorporation in a concrete solution architecture.
Sutherland and Hovorka [
15] investigate the use of EA at two large natural resource extraction organizations through a sustainability lens to reveal the ICT contribution to the sustainability aspects of the organizational mission. The authors focus on sustainability as composed of three aspects: environmental, economic, and social. Via semi-structured interviews of high-level business managers and ICT professionals, they found that there was generally (1) poor awareness of the sustainability vision from an architectural perspective and (2) little alignment thinking. In addition, they found that (3) ICT was not typically leveraged for achieving broader sustainability goals, awareness, and action. Furthermore, (4) sustainability factors were not considered explicitly in EA approval boards or the ICT architecture and governance, while some sustainability consideration was present in the business architecture [
15]. These findings are in line with those of Plessius et al. [
16], who performed semi-structured interviews in five various organizations to develop directives on how EA can be used for green ICT. Interview questions were centred around three topics: if and how sustainability is implemented in the architecture, if and how sustainability goals are monitored by architects during implementation, and main sustainability concerns for organizations. From these interviews, the authors concluded that (1) all visited organizations have adopted sustainability goals, (2) only one organization linked sustainability goals to EA, and (3) sustainability was not taken into account in decision boards handling project prioritization and budgeting [
16].
Sutherland and Hovorka [
15] discuss that, while senior management’s direction of the organization was focused on sustainability on paper, the vertical integration of the sustainability agenda dissipated as the message filtered to lower levels of the organizational hierarchy. They suggest that EA processes can provide alignment of an organizational sustainability agenda with specific ICT initiatives by leveraging, among others, the following opportunities: reducing duplication of technology resources, data analytics for energy consumption, ecological reporting, and integrated sustainability planning [
15]. However, the paper is presented as exploratory research and the recommendations and opportunities remain very high-level and conceptual.
Emphasizing the unclarity of how to integrate business strategy with ICT operations in relation to sustainability, Plessius et al. [
16] focus on how EA may contribute to the traceable transformation from sustainability principles towards requirements on green ICT in the field of higher education. The authors differentiate between greening of ICT (making ICT itself more sustainable) and greening through ICT (using ICT to increase the sustainability of other capabilities or processes). In view of this, the authors emphasize the paradox where greening through ICT leads to the increased use of ICT (increasing, e.g., energy consumption and materials use). Because of this, EA is proposed as an intermediate party to prioritize projects regarding green ICT. The authors reference the Sustainable Information Systems Management (SISM) model in how it guides in determining important areas for aligning the sustainability strategy of an organization with its ICT and Information Systems (IS) activities, but they state that it does not provide answers on how to implement such an alignment. Leveraging EA, the authors present the SISM Revisited model: The SISM model guides in the identification of areas of interest for aligning the sustainability strategy of an organization with its IS/ICT activities, while the SISM Revisited model advises on how to implement the alignments as well [
16]. While promising, this paper is positioned as research in progress and offers preliminary results without any follow-up research having been found.
Taking the perspective of a circular economy, Laumann and Tambo [
19] examine the necessary steps for analysing and designing the EA model, aiming to facilitate the transformation of an enterprise from operating in a linear manner to operating in a circular economy model. The authors propose a new EA framework, named the Circular Economy Enterprise Architecture Framework (CEEAF). This framework suggests extending: (1) business architecture to include the facilitation of the circulation of materials; (2) data architecture to encompass supplier, age, materials, transformations, and usages to optimize utilization; (3) technology architecture to include technologies that are capable of long traces without the possibility of being amended (like BT) to trace quality aspects throughout the lifetime of any goods; and (4) application architecture to include intelligent design in sub-system interaction to support data flow related to the circulation of goods. The authors also hint towards the use of a capability model to visualize the functions that an organization wants to achieve and to facilitate strategic decision-making. The focus of the paper is on a circular economy transition which provides an interesting aspect of environmental impact.
Recognizing the need for an overall system perspective (“big picture”) regarding the greening of individual IS components, Debnath [
20] proposes leveraging EA to handle the multi-dimensionality of the involved areas and views. The author uses the Zachman framework to explore the link between IS and its greening from the perspectives of different stakeholders, utilizing the interrogative questions what, how, where, who, when, and why regarding the greening of IS. The proposed scope of green IS is to enable the flow of information reflecting the environmental embeddedness of business functions and processes, where relevance and meaningfulness of information would allow people and processes to connect and optimize environmental sustainability. The author mentions linking green IS to the different organizational layers (business, data, application, technology) but, unfortunately, does not offer any concrete methods or references for greening the different layers.
Perdana et al. [
26] identify EA as the right tool in implementing digital transformation towards a sustainable enterprise and address the lack of sustainability integration in current EA frameworks. The authors propose a strategy framework for incorporating sustainability into EA consisting of the building blocks motive, nature, object, method, and output [
26]. The proposed framework, however, is presented at only a very high level, without clarity on how to implement it. García-Escallón et al. [
27] propose a methodology for the specification of EA patterns for sustainable organizations. The authors classified characteristics of sustainable organizations and mapped these classes to the ArchiMate modelling language, limited to the ArchiMate motivation layer. Examples of classes are adoption factors, customers channels, and key partners. They proposed sustainability patterns linked to the TOGAF architecture development method [
36] where, for instance, an Architecture Vision phase is utilized to define the architecture vision of a sustainable organization. Validation of the methodology presented mixed results regarding usability, and even confusion about the relationship between the architecture development method and the proposed methodology [
27].
Offering a much more concrete way to introduce ES into the enterprise, Iseke [
28] discusses the use of EA and ArchiMate for sustainability. The author maps environmental concepts to the ArchiMate language, guided by the most common sustainability reporting tools found in literature (ISO 14001, ISO 14031 [
37], the Eco-Management and Audit Scheme [
38], and the Sustainability Reporting Guidelines G3 [
39]) and expert evaluation. Both a qualitative and a quantitative approach to environmental performance modelling are presented, aiming to improve the organizational environmental performance from an architectural perspective [
28]. The author proposes a list of 22 environmental concepts that are modelled using 9 original ArchiMate elements and 10 new ArchiMate elements (specializations). For a quantitative analysis of environmental performance, Iseke [
28] proposes a combination of a bottom-up approach, where the environmental impact for every business process and architectural component can be computed and cumulated, and a top-down approach, where impact is assessed per action or actor (e.g., client request). This quantitative approach enables the discovery of heavy polluters and the design of a to-be architecture that is optimized for environmental performance; by coupling these heavy polluters with the business criticality of the component, quick wins can be identified for removal, replacement, or optimization. The proposed artefact was found to lower the threshold for organizations to take action concerning environmental assessments within the enterprise by making environmental performance parameters a part of the default processes in EA modelling [
28].
Although several papers discuss the combination of EA with ES aspects, most of them remain very high-level and conceptual, making them insufficiently actionable to allow immediate application in a business context. Other papers are still preliminary research or discuss only a very specific aspect of ES or the layered organizational complexity. This current lack of a holistic yet actionable and generalizable tool for including ES in DTs is addressed by the presented research. Based on this review, the envisioned artefact will be a framework and set of views that should fulfil the following requirements:
Solution objective 1: Guidance on which concrete actions to take throughout all of the enterprise’s layers to optimize ES.
Solution objective 2: Guidance on how to set up the required EA capabilities for mapping and improving the EF throughout the different enterprise layers.
Solution objective 3: Holistic insight into the entire enterprise’s environmental impact.
To meet the first objective, we propose to search scientific and non-scientific literature and tools to find Courses of Action (CoAs) that represent knowledge for improving ES. Next, to make the solution actionable and manageable, we propose CBM, with a strong focus on applying capabilities and capability maps.
2.1. Capabilities
In the realm of Enterprise Architecture, the term “capability” refers to “what” a business accomplishes to achieve a specific outcome, abstracting from details such as where, when, by whom, and how these activities transpire [
40]. According to [
23], a capability combines ability and capacity that equips an enterprise to meet an objective within a given context. This definition includes “ability”, the competence in employing resources, and “capacity”, the availability of diverse resources. These resources can be adjusted to match the context to achieve the intended goals.
Capabilities are realized through the dynamic configuration of resources across several dimensions, often indicated as people, information, processes and technology [
14,
24]. The people dimension not only pertains to the competencies and expertise of individuals required to execute specific activities but also encompasses organizational topics, such as team structure, behaviour, and culture. The information dimension refers to the data and knowledge essential for informed decision-making and execution. The processes dimension outlines the sequential activities and workflows to achieve desired outcomes. Lastly, the technology dimension encompasses the tools, software, and infrastructural elements necessary to support, enhance, and streamline operations. This configuration, which we refer to as the “how” of capabilities, allows an organization to create value and achieve its goals. Thus, in addition to defining “what” actions to perform to realize its strategic vision, an organization must outline “how” to perform them.
Aligning capabilities with ES objectives has implications across their four dimensions. This alignment ensures that ES objectives are met and resonate with the goals of DT and ES. Capabilities offer a structured perspective of an organization, thus fostering better alignment, as highlighted by [
14]. Delving deeper, Capability-Based Management (CBM) capitalizes on analytical insights to guide decision-making, emphasizing alignment and strategic execution. With its focus on an organizational structure rooted in capabilities, CBM effectively translates strategic ambitions, ensuring the desired alignment [
41]. This becomes especially crucial in the milieu of Digital Transformation, as noted by [
42].
Therefore, as part of the EA domain, CBM can be viewed as an actionable tool that can support the incorporation of ES in ongoing or future DT initiatives. It provides a means of conducting a gap analysis, presenting its outcomes, and crafting an execution roadmap, taking into account what an organization needs to achieve, both with a focus on ES as well as DT.
2.2. Capability Map
The effective management of these capabilities demands a structured framework, commonly known as a capability map, which is a key component of the organization’s overall enterprise architecture description [
43,
44]. This capability map offers a systematic depiction of the organization’s capabilities, including those that are simply referenced, planned, aspired to, or partially realized. Its representation may be graphical, as shown by the simple example in
Figure 1, or in a purely textual format, sometimes referred to as a capability catalogue or library.
A significant advantage of a capability map is its stability, deriving from its emphasis on the “what” of capabilities and the exclusion of the more variable “how” (the four dimensions). This leads to a representation that is relatively stable, as opposed to, for example, process maps, whose scope can be unclear due to their dynamic nature. Easier to define, a capability map is similar to a process map in that both represent functional decomposition with specific scopes. The uniqueness of a capability map, however, stems from its abstraction of the associated dimensions such as processes, which circumvents intricate scope-related discussions. The relations between capabilities and processes can be part of a further analysis when needed, but they should be kept out of the capability map. It is noteworthy that multiple processes can realize a single capability and, conversely, a single process can help actualize multiple capabilities. Keeping this complex relation out of this view helps to keep the model stable and clear. The capability map’s clarity is, thus, another benefit: by omitting intricate details associated with the four dimensions, the map serves as a conceptual model that accurately portrays the organization’s functions without excessive complexity or detail.
2.3. Documenting Use Cases of Capability Mapping
In this study, we aim to use capability mapping (and, in extension, CBM). In order to describe the use cases of capability mapping in this context, we use the template as presented by [
42]. Based on the 5W1H framework, used for describing systems [
45,
46], the template aims to capture the how, the why, and the who of such a use case. The documented use cases can be found in
Appendix A and
Appendix B.
2.4. Layers of Enterprise Architecture
According to The Open Group, the purpose of EA is to optimize, across the enterprise, the often-fragmented legacy of manual and automated processes into an integrated environment that responds to change and supports the delivery of the business strategy. EA achieves this by effectively managing information and DT by providing a strategic context for the evolution and reach of digital capabilities in response to the constantly changing needs of the business environment [
47]. Since ES can be viewed as an emerging business need arising from the constantly changing business environment, EA is proposed as an ideal tool for managing ES throughout the enterprise. Through the use of The Open Group Architecture Framework (TOGAF)’s four primary architecture domains, business, data, application, and technology [
48], abbreviated as BDAT, EA aims to provide a transparent and holistic view throughout all layers of an organization. Each layer can be described by different models and views, while policies, principles, and guidelines guide an organization’s growth. The BDAT concept will be used to structure the remainder of this paper. Given the importance of incorporating ES in the decision-making process at the strategic level [
22] and the strategic nature of DTs, an additional emphasis will be placed on the strategy of an organization. Even though TOGAF describes this as part of the business architecture layer, we prefer to add a separate strategy layer, as this allows us to look beyond the traditional concepts covered by business architecture. Adding this separate layer results in the acronym SBDAT.
Table 3 presents a brief description of the different layers.
In understanding the intricate relationships between architecture layers and capability resource dimensions within an organization, it is essential to recognize their complementary nature. The architecture layers, encompassing strategy, business, data, application, and technology, provide a foundational framework for delineating the design and operation blueprint of an enterprise. On the other hand, capability resource dimensions populate and breathe life into this blueprint, facilitating its operationalization. In practical scenarios, however, they overlap and cannot be seen separately. The strategy layer is reflected by the capabilities on the highest level, setting forth overarching goals and objectives. The business layer, then, which delineates operational workflows and roles, aligns seamlessly with the people and processes dimensions, charting out the human and procedural aspects necessary for strategy realization. The data layer, focused on the architectural organization of data, finds its operational counterpart in the information dimension, which details the specific data content utilized in the organization. Lastly, the confluence of the application and technology layers shapes the technological edifice of the organization, defining requisite tools, software, and foundational tech components. The technology dimension operationalizes this by detailing the deployment and usage of these technological assets in daily enterprise functions. In essence, this symbiotic integration between architecture layers and resource dimensions ensures that an organization’s design and operational resources harmonize, fostering a cohesive and efficient organizational system. As such, insights from each of the architecture SBDAT layers could impact specific capabilities, or they could impact multiple capabilities by impacting the capability dimensions.
3. Method
To answer the RQ stated in
Section 1, a Design Science Research (DSR) method is proposed. This method is centred around the creation of artefacts and processes that help solve problems in the environment (application domain) while contributing to the scientific knowledge base [
49]. Based on the DSR Knowledge Contribution Framework [
50], the type of knowledge contribution will be Improvement, as the EA application domain maturity can be considered quite high, but the environmental sustainability solution maturity is low; at present, EA frameworks offer insufficient insights and support on how to optimize the ES during DTs. Following the DSR methodology proposed by Peffers et al. [
51], the present research will start with a Problem-Centred Initiation. The DSR methodology consists of six phases: Identify problem and motivate, define objectives of a solution, design and development, demonstration, evaluation, and communication [
51].
The first phase of the DSR methodology consists of the identification and motivation of the problem, as presented in
Section 2.
The second phase of the DSR methodology consists of the definition of objectives for the solution. The artefact resulting from answering the RQs will be created from a general perspective, not specific to a given industry or sector, and not based on a specific case study. As such, it will be an attempt to close the gap of a more generalizable approach and serve as a capability-building framework and source of insights for any organization that is undergoing (or is planning to undergo) an environmentally sustainable DT. The artefact objectives are defined based on the results of phase one, as presented in
Section 2.
The third phase involves designing and developing the artefact. This artefact pivots around the organizational SBDAT layers. For insights into how to incorporate ES within these layers, keyword searches were conducted on Web of Science, Google Scholar, and Google. By amalgamating scientific and non-scientific literature and tools, we sought a balance between rigorous scientific foundations and tangible real-world insights. This study does not aim for a systematic literature review (SLR) of each organizational layer, but, instead, offers a practical solution, collecting and presenting existing knowledge in a novel way. Consequently, a limitation lies in potentially overlooking significant references from both scientific and non-scientific spheres.
The initial artefact presents concrete Courses of Action (CoAs) based on extant literature, guiding organizations on integrating ES across enterprise layers. Each CoA is largely standalone, targeting specific ES objectives. For a systems-thinking perspective on CoA implementation, we leverage Capability-Based Management (CBM) in alignment with [
14]. For the second artefact, we derive capabilities from these CoAs that enable the concept of Green Enterprise Architecture (EA) within organizations. By drawing from the APQC process classification framework [
25], we discern which capabilities are enhanced, or “greened”, by specific CoAs. For instance, “Manage business processes” evolves into “Manage green business processes”. When APQC capabilities do not match directly, new capabilities are introduced. A prime example is the absence of an APQC capability centred on Artificial Intelligence (AI). In such instances, we have proposed new capabilities like “Manage Green AI”, which serves as a subset of the broader and already existing “Analyze emerging technology concepts” capability. It is crucial to understand that each CoA might affect multiple Green EA capabilities. Advancing these Green EA capabilities empowers the organization to pursue new CoAs promoting ES, creating a symbiotic relationship between CoA and Green EA capability.
For the third artefact, an Environmentally Sustainability-aware business capability modelling approach is proposed as a concrete CoA to provide a holistic one-page overview of an organization’s environmental footprint (EF). ES-aware business capability modelling refers to a business modelling approach that integrates ES principles into the organization’s capabilities by using (in a novel way) the presentation and analysis methods that capability mapping offers. This means that, when planning, executing, or evolving business capabilities, considerations related to ES are central. It is an approach that does not just consider the typical business metrics (like profitability, efficiency, or growth) but also places a significant emphasis on the environmental impact and sustainability of these capabilities. It is about leveraging the existing practice of capability mapping to ensure that, as a business evolves and transforms its capabilities, it does so with a clear understanding and integration of sustainable practices. In our framework, we started from an existing reference architecture (APQC) and identified each capability that could be linked to relevant CoAs derived from established literature. These specific capabilities can be included in the ES-aware capability modelling as well. However, ES-aware capability modelling has a broader focus. It provides a way to assess a capability based on Key Environmental Indicators (KEIs). The defined CoAs can contribute to achieve these, but other, non-identified CoAs can contribute as well. This ES-aware business capability modelling can be used to, first, assess the as-is EF of the organization coupled with the organization’s business capabilities. As such, it can serve as a baseline for ES performance and identifying ES initiatives. Next, it can be used to measure ES progress by applying the CoAs and building the Green EA capabilities during DT. This ES-aware business capability modelling is introduced as a concept and deserves a dedicated avenue for further research. A conceptual example is presented, composed of capabilities based on the APQC process classification framework [
25]. This example is then coupled with CoAs and ES concepts from the scientific literature.
Phases four (demonstration) and five (evaluation) will be part of a future study, where the proposed artefacts will be applied in a specific business context through case studies. The effectiveness and suitability of the artefacts will be evaluated, and the design of the artefacts will be iteratively improved. However, in
Section 5, a first demonstration and validation is proposed based on a fictional case and example. Phase six (communication) will be in the form of a scientific publication.
5. Discussion
As discussed in the introduction, DTs provide a unique opportunity to improve an organization’s ES. Unfortunately, ES is insufficiently taken into account during DTs. To bridge this gap, EA is proposed as a tool for linking DTs to ES. However, currently, there are insufficiently specific and actionable EA publications, tools, and techniques. To address this, a set of research questions have been proposed and answered. This section will discuss the paper’s contributions and practical implications, its limitations, and future research opportunities.
5.1. Contribution and Practical Implications
As a result of the performed SLR, the current state of the art concerning the combination of EA and ES was found to be limited to a very conceptual level, making it insufficiently actionable to allow immediate application in a business context. This paper seeks to close this gap between academic research and practice by offering a holistic, yet actionable and generalizable, tool for embedding ES into DTs through EA.
The main RQ presented in the introduction “
How can EA be leveraged as an actionable tool in supporting the inclusion of ES in current or future DT initiatives?” is answered by the consolidation of the three proposed solution objectives. Solution objective 1 is attained by providing an overview of concrete CoAs (
Table 4) that can be taken in each of the enterprise SBDAT layers, resulting in the inclusion of ES in an organization’s strategy, business, data, application, and technology. The capabilities needed for the realization of Green EA have been discussed throughout the text and have been summarized in
Figure 3, fulfilling solution objective 2.
Table 5 presents an overview of the proposed Green EA capabilities and how to start building them using the proposed CoAs and additional actions, processes, and roles based on the presented literature. Neither the Green EA capabilities nor the proposed actions are meant to be exhaustive, but rather to provide a starting point for growing the capabilities needed to align DTs with ES. Furthermore, our study did not include the weighing or scoring of the Green EA capabilities in practice, as this would require a model for scoring these capabilities in order to be able to compare them objectively. However, there is a certain sense of priority when it comes to implementing these capabilities. The capabilities in the strategic layer should receive the highest priority, as they provide the guidance required for the other layers. After all, an organization cannot implement solutions if there is no clear vision on where to go. Similarly, it can be argued that some of the capabilities in the business layer would be required for making the right decisions in the technology, application, and data layers. Once again, as technology aims to serve and support business processes, it should be clear what these processes will be.
Solution objective 3 is attained by introducing the concept of ES-aware business capability modelling, an example of which is presented in
Figure 4, providing a tool for organizations to create a high-level holistic view of its environmental impact and subsequent opportunities for improvement. ES-aware business capability modelling is proposed because of the current gap between green strategy and execution, since the main focus of green practices in the business layer is on business process improvements, lacking a holistic approach. The combination of these three artefacts is proposed as an actionable tool to help organizations include ES in current and future DT initiatives.
The scientific contribution of this paper is twofold. Firstly, by addressing the conspicuous gap in the literature concerning the integration of EA and ES, the study pioneers a holistic, actionable framework that marries these two vital paradigms. This synthesis not only extends the boundaries of what is currently known but also establishes a tangible pathway for their practical confluence. Secondly, the proposed model provides a starting point for future research and can be expanded as a Green EA framework, offering best practices and more detailed guidance on how to implement these.
Concerning the practical benefits, the artefacts should allow the organizations adopting them to have a structured set of actions and focus domains (capabilities) that can help them drive their ES effort and combine it with their DT effort. By adopting the already existing practices related to CBM and elevating these with a new ES focus, organizations should be able to start transforming ambitions related to ES into actionable initiatives. However, possible challenges are identified: First, adopting the GREAN framework to the fullest implies embracing CBM and capability-oriented thinking. Organizations with low EA maturity might find this more difficult to perform. They can stick to the proposed CoAs as a source of inspiration. Second, the defined CoAs provide guidance (e.g., on where to start looking for areas to improve), but they provide no tangible directions other than those provided by the identified studies from which they were derived. Future research should look into elaborating on these CoAs and what they mean for the different capabilities in terms of people, processes, data, applications, and so on.
Given the extensiveness of each of the enterprise layers, this paper does not offer an exhaustive set of actions or views concerning the subject of ES. Practitioners are suggested to select the actions that are most relevant or valuable for their specific situation and to study the referenced publications for a deeper understanding of the topics. For organizations that are new to the concept of ES, GREAN can provide foundational guidance. These organizations just starting to embark on their sustainability journey can use Green EA, as it provides an introductory roadmap. It offers them a first structured overview to understand and prioritize ES within their DT initiatives. The artefact offers a starting point of how to initiate the integration of digital strategies with sustainability goals, ensuring they start on the right footing. For organizations that have been undertaking steps towards better ES, GREAN can provide means for enhancement and realignment. Organizations that have some sustainability measures in place can utilize Green EA to identify gaps, realign their strategies, and further integrate environmental considerations into their digital efforts. The capability-based approach embedded in the artefact can aid in refining and optimizing existing processes, ensuring a more holistic and effective integration of sustainability. Finally, for more advanced organizations in the domain of ES, GREAN can serve as a critical evaluation tool, allowing these organizations to check and fine-tune their sustainable digital practices.
5.2. Artefact Validation
A thorough artefact validation through case studies is planned for a follow-up study. However, a first validation through a fictive case study can already indicate the usefulness of the artefact. For this fictive case study, we present Company Z, a retail company that is planning to undertake an organization-wide DT.
5.2.1. Case Context
In recent years, Company Z has grown through several mergers and acquisitions. The largest companies were allowed to retain their way of working, their systems, their processes, etc. At present, Company Z comprises five business units that each have their operating model. Company Z has now decided to undertake a DT and to identify opportunities for uniformization throughout the business units. After engaging an outside consultancy organization for help, Company Z has decided to merge three of the five business units. In addition, they have decided to uniformize the supporting capabilities, such as managing IT and some of the core capabilities such as managing supply chain. The approach to facilitate this uniformization is centred around business process alignment throughout the organization coupled with the adoption of a new enterprise resource planning and supply chain software.
The CEO of Company Z has launched several initiatives in recent years to improve the company’s environmental footprint, but none have successfully managed to create a holistic and lasting change. In light of the current DT, which will trigger a fundamental change in the organization, the CEO has decided to leverage this opportunity to embed ES into the core of the organization. The CEO tasks Company Z’s Enterprise Architect to create a plan for making this a reality. After scouring the existing literature, she has decided that the presented Green EA framework can be used to incorporate ES into their current DT.
5.2.2. Identifying CoAs
The Enterprise Architect reads through the CoAs presented in
Table 4 and immediately identifies several opportunities to include ES in the organization. First, she learns about the importance of including ES in the organization’s strategy and realizes that, although several ES initiatives have been launched, Company Z has no clear strategy on ES, nor does it have a way to measure progress. She proposes to embed ES into corporate vision, strategy, and objectives (SCoA1) and to implement ESG reporting tools and processes (SCoA2). In addition, she realizes that ES is currently not taken into account in new or existing projects, and she decides to identify architecture principles for green strategy execution (SCoA6), such as environmental impact (measured through, e.g., energy consumption) will be included as a quality attribute (QA) in architecture trade-off analyses when choosing new architectures or technologies. When reading through the remaining SBDAT layers, the Enterprise Architect identifies several more CoAs that can be immediately applied to the current DT, ranging from defining ES roles and responsibilities (BCoA6) to assessing the EF of IoT projects and including this in the project business case (TCoA2). One CoA that stands out is adopting the use of Green Business Process Management (BCoA3). Up until now, the business processes of the different business units have been charted through the use of Business Process Model and Notation (BPMN) to facilitate their uniformization. However, no attention has been paid to the environmental impact of these processes, causing Company Z to miss out on the opportunity to fundamentally improve its ES.
5.2.3. Using the Capability Map
To communicate her findings to the CEO, the Enterprise Architect utilizes the Green EA capability map presented in
Figure 3. Using this viewpoint, she is able to show that her proposed CoAs are embedding ES throughout all the layers of the organization, that these CoAs impact certain existing capabilities, and they even trigger the creation of new capabilities. Leveraging the technique of CBM, she is able to show that building the needed green capabilities requires investments in the four dimensions that make up these capabilities. The proposed CoAs are a good first step for immediately including ES into the ongoing DT. However, Company Z needs to invest in people, processes, information, and technology to become a green company. From this discussion, the CEO identifies a few additional capabilities in which Company Z should invest to become a true green company, such as manage green culture, as this would impact the people dimension of all capabilities. To obtain a clear view of the organization’s holistic environmental impact, the Enterprise Architect proposes to adopt the practice of CBM and the use of ES-aware business capability modelling (BCoA10). She proposes building a capability map for the organization similar to
Figure 4. Using this view, she first focuses on the capabilities that are most impacted by the DT. For instance, she is able to show that the capability manage supply chain currently has a very high environmental impact; she is able to show this by cumulating the KEIs used in her newly proposed Green BPMN. By performing this step, she shows that the dimension processes needs ES improvement. In addition, the dimension data needs improvement since insufficient environmental data are being captured throughout the supply chain. She is now also able to show that there is a lot of variability in the ES of the supply chain processes throughout the different business units, and she proposes uniformizing the processes based on the most environmentally friendly business unit. By adopting this method for other capabilities, the Enterprise Architect can build a dashboard showing the environmental impact of Company Z on a page. Company Z is now aware of its ES and can steer investments for improving its ES, focusing first on the capabilities that are being impacted most by the ongoing DT. The Enterprise Architect has thus provided a tool for the organization to measure its environmental impact and to consciously and continuously improve its ES while growing towards becoming a truly green company.
5.3. Limitations and Future Research
The presented paper has several limitations throughout multiple aspects of the research. Firstly, regarding the SLR on green EA: This included many different keywords concerning environmental sustainability. However, the term “Enterprise Architecture” was always included; as such, other holistic greenifying approaches akin to EA could have been overlooked. Concerning the different enterprise layers (strategy, business, data, application, and technology), it was not the goal of this paper to perform an SLR for each of them but rather to provide actionable pointers for each layer. As such, a limitation of this paper is that important scientific and non-scientific references and greenifying actions might have been overlooked. To address this limitation, future research might entail performing a systematic literature review of each of the discussed enterprise layers concerning ES. This would give a more complete picture of the current state of the art in how to pursue ES throughout the organization. Another limitation of this paper is in the means of artefact evaluation: Since this paper has been produced through desk research and analysis of existing literature, future research avenues could focus on the validation of the proposed artefacts. Observational evaluation is recommended in the form of case or field studies to properly evaluate the use and effectiveness of the artefacts in a business environment.
Additional recommendations for future research include the concept of ES-aware business capability modelling, further extending and formalizing the method and validating its impact on ES in a business environment. A next course of research could be expanding and strengthening the model towards a full framework, which can be used to include best practices and more detailed guidance on how to use certain proposed capabilities. Best practices regarding people, processes, information, and technology could be investigated and added in a manner similar to that used to define KPIs for each of the proposed Green EA capabilities. The final aim of this research could then be to use the framework as an implementation and even as an audit tool.
6. Conclusions
Digital Transformation (DT) is growing in importance in both academic and business settings, with events like the COVID-19 pandemic further accelerating this trend. Although DT has the potential to significantly impact sustainable development, there is often a lack of focus on Environmental Sustainability (ES) within these transformation efforts. There is a clear need to include ethical considerations, such as corporate social responsibility, into the DT process. Current research on the relationship between DT and sustainability lacks the transferability of research findings to applications in organizations. Additionally, few studies focus on the specific capabilities needed to transform businesses sustainably while integrating digital technologies. This paper introduces Enterprise Architecture (EA), known for offering a clear and comprehensive view of all layers of an organization, as a potential solution to the problem of integrating DT with ES.
By making use of EA, and, specifically, Capability-Based Management (CBM), this study provides a way for organizations to understand their structure and guide their DTs. The integration of this with ES strategies and tools leads to a new concept: Green EA. Using a Design Science Research (DSR) approach, the Green EA artefact was developed, with its knowledge contribution type being “Improvement”. This artefact serves as a capability-building framework and source of insights for organizations aiming for environmentally sustainable DT.
To validate the need for Green EA, a Systematic Literature Review (SLR) was conducted. This review showed that the existing literature often lacks practical application in the business world. To address this gap, the proposed artefact was designed around the organizational SBDAT layers, suggesting specific Courses of Action (CoAs) based on established literature. These CoAs guide organizations on how to integrate ES into every layer of their enterprise. Furthermore, these CoAs were used to identify the capabilities needed to enact Green EA within organizations. A significant proposition made is an ES-aware business capability modelling approach, aiming to give organizations a clear overview of their environmental impact by leveraging business capability mapping [
14,
42]. Environmental Sustainability-aware business capability modelling refers to an innovative business modelling approach that integrates environmental sustainability principles into the organization’s capabilities, by using (in a novel way) the presentation and analysis methods that capability mapping offers. This approach encourages organizations to look beyond typical business metrics with a strong emphasis on environmental impact, ensuring that, as businesses evolve, they prioritize and incorporate sustainable practices.
For organizations beginning their journey towards environmental sustainability, this paper can be a starting point. For organizations that are already on this journey, the proposed artefact can serve as a reference model. It is important to note that the actions proposed here are not exhaustive. Practitioners are encouraged to choose actions that best fit their specific contexts and dive deeper into the provided literature for a richer understanding. For future research, a deeper look into each enterprise layer regarding ES and the translation of the CoAs into actionable guidelines for implementation would be beneficial. It is also relevant for future scholars and practitioners to validate the suggested artefacts through real-world case studies to determine their value and effectiveness in a business environment. Future researchers could focus on expanding the Green EA capability model, transforming it into a more comprehensive framework that guides and audits an organization’s environmental sustainability efforts. Finally, the proposal of ES-aware business capability modelling, while still in its early stages, requires further exploration and development. Defining relevant KEIs, as well as novel analysis and reporting methods based on the capability map, would certainly enrich and improve this practice and make it more relevant for practitioners.