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PurposeMaturity models are a prospering approach to improving a company's processes and business process management (BPM) capabilities. In fact, the number of corresponding maturity models is so high that practitioners and scholars run the risk of losing track. This paper therefore aims to provide a systematic in‐depth review of BPM maturity models.Design/methodology/approachThe paper follows the accepted research process for literature reviews. It analyzes a sample of ten BPM maturity models according to a framework of general design principles. The framework particularly focuses on the applicability and usefulness of maturity models.FindingsThe analyzed maturity models sufficiently address basic design principles as well as principles for a descriptive purpose of use. The design principles for a prescriptive use, however, are hardly met. Thus, BPM maturity models provide limited guidance for identifying desirable maturity levels and for implementing improvement measures.Research limitations/implicationsThe authors are confident that this review covers the majority of publicly available BPM maturity models. As the number of corresponding maturity models seems to be constantly growing, exhaustiveness can hardly be guaranteed. The study's results stimulate future research. Inter alia, adopters from industry require more elaborate support by means of ready‐to‐use and adaptable instruments for maturity assessment and improvement. The paper also reaffirms the need for maturity model consolidation in the field of BPM.Originality/valueAs existing literature reviews focus on process improvement or BPM in general, the paper's findings extend current knowledge. They also increase transparency. Its results provide guidance for scholars and practitioners involved in the design, enhancement, or application of BPM maturity models.

Purpose
– Process improvement is a fundamental activity of the business process management (BPM) lifecycle. However, practitioners still lack concrete guidance and adequate objectives for process improvement. Moreover, improvement projects typically tie up considerable amounts of capital and are very risky. Thus, more guidance is needed on how to derive concrete recommendations for process improvement in a goal-oriented manner. The paper aims to discuss these issues.


Design/methodology/approach
– The authors propose a decision model that determines along which paths the instances of a process should be routed to maximize the value contribution of the process. To do so, the decision model requires a process model and a set of historical process instances as inputs.


Findings
– The decision model builds on the idea that only the parameters of the process, i.e., the values according to which it is decided on which path an instance traverses the process, can be modified, without altering the structure of the process. The decision model determines the parameter setting that maximizes the value contribution of the process, which is measured in terms of the expected cash flow of the process. When determining the optimal parameter setting, the decision model considers that different instances and paths have different cash flow effects.


Practical implications
– The authors prototypically implemented the decision model and report on the insights from a demonstration example that is based on the order verification process of an IT distributor.


Originality/value
– The decision model complements existing approaches to process improvement as it reveals additional improvement potential by focussing on the decision points in a process without altering the structure of the process. The decision model also enables identifying an optimal parameter setting, as a concrete recommendation for process improvement, in line with the principles of value-based BPM.

PurposeIn an exploratory approach, the authors conducted a structured literature review to extract candidate process digitalization project (PDP) success factors (SFs) from the literature on business process management (BPM), project management (PM) and digitalization. After that, the authors validated, refined and extended these intermediate results through interviews with 21 members of diverse PDP teams. Finally, the authors proposed the PDP success model by linking the candidate SFs with relevant success criteria.Design/methodology/approachDigitalization substantially impacts organizations, which increasingly use digital technologies (DTs) to improve and innovate their business processes. While there are methods and tools for identifying process digitalization ideas and related projects (PDPs), guidance on the successful implementation of PDPs is missing. Hence, the authors set out to explore PDP SFs.FindingsThe PDP success model covers 38 PDP success factor candidates, whereof 28 are already backed by the literature and ten have emerged during the interviews. Furthermore, the SFs are structured according to seven categories from the literature covering a broad range of sociotechnical topics (i.e. strategy, structure, culture, people, process, project and technology) as well as equipped with preliminary success rationales.Originality/valueThe work is the first to systematically explore PDP SFs. The PDP success model shows that PDPs require a unique set of SFs, which combine established and hitherto underrepresented knowledge. It extends the knowledge on BPM and serves as foundation for future (confirmatory) research on business process digitalization and the successful implementation of PDPs.

Purpose
In a world of ever-changing corporate environments and reduced product life cycles, most organizations cannot afford anymore to innovate on their own. Hence, they open their innovation processes to incorporate knowledge of external sources and to increase their innovation potential. As the shift toward open innovation (OI) is difficult and makes many initiatives fail, the question arises which capabilities organizations should develop to successfully implement OI. As the literature encompasses mature but isolated streams on OI capabilities, there is a need for an integrated capability framework. The paper aims to discuss these issues.


Design/methodology/approach
This paper proposes the open innovation capability framework (OICF) that compiles and structures capabilities relevant for implementing OI. The OICF covers the outside-in and coupled processes of OI. To integrate multiple streams of the OI literature, the OICF builds on a structured literature review. The OICF was also validated in a two-step review process with OI experts from academia and industry.


Findings
The OICF comprises 23 capability areas grouped along the factors such as strategic alignment, governance, methods, information technology, people, and culture. To analyze the existing body of knowledge on OI capabilities, the authors compare the OICF with other OI-related capability frameworks and compile a heatmap based on the results of the literature review. The authors also discuss the experts' feedback on individual factors of the OICF as well as on interdependencies among these factors.


Practical implications
The OICF provides practitioners with a structured overview of the capabilities to consider when implementing OI. Based on the OICF, practitioners can define the scope of their OI initiatives. They can use the OICF as a foundation for prioritizing, selecting, and operationalizing capability areas as well as for deriving implementation roadmaps.


Originality/value
The OICF is the first framework to take a holistic perspective on OI capabilities. It integrates mature but isolated research streams of OI. It helps practitioners define the scope of OI initiatives and academics gain insights into the current state of the art on OI capabilities.

PurposeProcess redesign refers to the intentional change of business processes. While process redesign methods provide structure to redesign projects, they provide limited support during the actual creation of to-be processes. More specifically, existing approaches hardly develop an ontological perspective on what can be changed from a process design point of view, and they provide limited procedural guidance on how to derive possible process design alternatives. This paper aims to provide structured guidance during the to-be process creation.Design/methodology/approachUsing design space exploration as a theoretical lens, the authors develop a conceptual model of the design space for business processes, which facilitates the systematic exploration of design alternatives along different dimensions. The authors utilized an established method for taxonomy development for constructing the conceptual model. First, the authors derived design dimensions for business processes and underlying characteristics through a literature review. Second, the authors conducted semi-structured interviews with professional process experts. Third, the authors evaluated their artifact through three real-world applications.FindingsThe authors identified 19 business process design dimensions that are grouped into different layers and specified by underlying characteristics. Guiding questions and illustrative real-world examples help to deploy these design dimensions in practice. Taken together, the design dimensions form the "Business Process Design Space" (BPD-Space).Research limitations/implicationsPractitioners can use the BPD-Space to explore, question and rethink business processes in various respects.Originality/valueThe BPD-Space complements existing approaches by explicating process design dimensions. It abstracts from specific process flows and representations of processes and supports an unconstrained exploration of various alternative process designs.

Digitalization Cases Vol. 2 -- Foreword -- Preface -- Contents -- Editorial Board -- About the Editors -- Introduction to Digitalization Cases Vol. 2: Mastering Digital Transformation for Global Business -- 1 The Impact of Digitalization on Global Business -- 2 Structuring the Field of Digitalization -- 3 Introducing Cases of Digitalization -- 3.1 Digital Disruption -- 3.2 Digital Business -- 3.3 Digital Transformation -- 4 How to Read the Cases -- References -- Part I: Digital Disruption -- Enabling the Digitalization of Claim Management in the Insurance Value Chain Through AI-Based Prototypes: The ELIS Innovation ... -- 1 Introduction -- 2 Situation Faced -- 2.1 Use-Case 1: Sensitive Data Detection and Anonymization on Claim Images -- 2.2 Use-Case 2: Manipulation Detection on Claim Images -- 3 Action Taken -- 3.1 Problem Setting -- 3.2 Functional Model Analysis, Selection, and Evaluation -- 3.3 Data Preparation -- 3.4 Model Set-Up -- 3.5 Model Training, Validation, and Testing -- 3.6 Model Deployment -- 4 Results Achieved -- 5 Lessons Learned -- References -- Invoice Automation: Increasing Efficiency in the Office at Satherm GmbH Using Artificial Intelligence -- 1 Introduction -- 2 Situation Faced -- 3 Action Taken -- 4 Results Achieved -- 5 Lessons Learned -- References -- Digitalization of Manufacturing Processes with Startup Collaboration: Arçelik Developing a Digital Twin with Simularge -- 1 Introduction -- 2 Situation Faced -- 2.1 Background Information -- 2.2 Thermoforming Process -- 2.3 Attempts Before the Digital Twin Project -- 2.4 Alternative Paths to a Digital Twin -- 3 Action Taken -- 3.1 Locating a Startup to Collaborate -- 3.2 Teaming Up -- 3.3 Developing a Virtual Representation -- 3.4 Fine-Tuning the Digital Twin -- 3.5 The Digital Twin´s Structure -- 4 Results Achieved -- 4.1 Business Impact -- 4.2 Digitalization.