8 research outputs found
Business models & business cases for point-of-care testing
Point-Of-Care Testing (POCT) enables clinical tests at or near the patient, with test results that are available instantly or in a very short time frame, to assist caregivers with immediate diagnosis and/or clinical intervention. The goal of POCT is to provide accurate, reliable, fast, and cost-effective information about patient condition. POCT can be part of the solution to the rising healthcare and welfare costs without any loss of healthcare quality. In this research, business models are used to create business cases in order to assess the viability of POCT. Two methods to create business models were designed by tailoring and extending them from an existing method. It was found that the method used has impact on the resulting business case. POCT was assessed to be viable in all business cases created for the specific case study used
Business Model Evaluation: A Systematic Review of Methods
Background: As a result of factors such as digitization and rapid technology change, organizations are compelled to innovate their business models at an accelerated pace. While the domain of business model innovation has focused on understanding and structuring the process of innovation, it offers limited guidance for evaluating business models during the innovation process. Business model evaluation plays a vital role in supporting decision-making about the performance or viability of new business models and motivating continued investments. Existing literature on methods for business model evaluation and their application is limited and available information is scattered. Furthermore, as the BMI process covers a broad spectrum of activities - from business model initiation to implementation - the evaluation challenges and the effectiveness of evaluation methods vary across the phases of innovation. Thus, there is a need for a better understanding on methods for business model evaluation, and their timing and application for business model innovation.
Method: Through a systematic literature review, we have investigated the methods available for business model evaluation and focused on understanding their characteristics and effective timing of application in the business model innovation process.
Results: We have identified six groups of methods used for business model evaluation. Additionally, we find that early phase business model evaluation is predominantly qualitative in nature, whereas late phases of business model innovation are generally supported through quantitatively-oriented methods. Moreover, we observe that limited evaluation support is available in the literature to support the initiation phase of business model innovation. Based on our findings, we propose a guiding structure for aligning the available methods with the respective innovation phases.
Conclusion: The proposed guiding structure offers guidance for business model evaluation in practice and serves as a basis for future research in developing more effective methods and tools for business model evaluation and development
Smart Service Innovation: Organization, Design, and Assessment
Background: The emergence of technologies such as the Internet of Things, big data, cloud computing, and wireless communication drives the digital transformation of the entire society. Organizations can exploit these potentials by offering new data-driven services with innovative value propositions, such as carsharing, remote equipment maintenance, and energy management services. These services result from value co-creation enabled by smart service systems, which are configurations of people, processes, and digital technologies. However, developing such systems was found to be challenging in practice. This is mainly due to the difficulties of managing complexity and uncertainty in the innovation process, as contributions of various actors from multiple disciplines must be coordinated. Previous research in service innovation and service systems engineering (SSE) has not shed sufficient light on the specifics of smart services, while research on smart service systems lacks empirical grounding.
Purpose: This thesis aims to advance the understanding of the systematic development of smart services in multi-actor settings by investigating how smart service innovation (SSI) is conducted in practice, particularly regarding the participating actors, roles they assume, and methods they apply for designing smart service systems. Furthermore, the existing set of methods is extended by new methods for the design-integrated assessment of smart services and service business models.
Approach: Empirical and design science methods were combined to address the research questions. To explore how SSI is conducted in practice, 25 interviews with experts from 13 organizations were conducted in two rounds. Building on service-dominant logic (SDL) as a theoretical foundation and a multi-level framework for SSI, the involvement of actors, their activities, employed means, and experienced challenges were collected. Additionally, a case study was used to evaluate the suitability of the Lifecycle Modelling Language to describe smart service systems. Design science methods were applied to determine a useful combination of service design methods and to build meta-models and tools for assessing smart services. They were evaluated using experiments and the talk aloud method.
Results: On the macro-level, service ecosystems consist of various actors that conduct service innovation through the reconfiguration of resources. Collaboration of these actors is facilitated on the meso-level within a project. The structure and dynamics of project configurations can be described through a set of roles, innovation patterns, and ecosystem states. Four main activities have been identified, which actors perform to reduce uncertainty in the project. To guide their work, actors apply a variety of means from different disciplines to develop and document work products. The approach of design-integrated business model assessment is enabled through a meta-model that links qualitative aspects of service architectures and business models with quantitative assessment information. The evaluation of two tool prototypes showed the feasibility and benefit of this approach.
Originality / Value: The results reported in this thesis advance the understanding of smart service innovation. They contribute to evidence-based knowledge on service systems engineering and its embedding in service ecosystems. Specifically, the consideration of actors, roles, activities, and methods can enhance existing reference process models. Furthermore, the support of activities in such processes through suitable methods can stimulate discussions on how methods from different disciplines can be applied and combined for developing the various aspects of smart service systems. The underlying results help practitioners to better organize and conduct SSI projects. As potential roles in a service ecosystem depend on organizational capabilities, the presented results can support the analysis of ex¬ternal dependencies and develop strategies for building up internal competencies.:Abstract iii
Content Overview iv
List of Abbreviations viii
List of Tables x
List of Figures xii
PART A - SYNOPSIS 1
1 Introduction 2
1.1 Motivation 2
1.2 Research Objectives and Research Questions 4
1.3 Thesis Structure 6
2 Research Background 7
2.1 Smart Service Systems 7
2.2 Service-Dominant Logic 8
2.3 Service Innovation in Ecosystems 11
2.4 Systematic Development of Smart Service Systems 13
3 Research Approach 21
3.1 Research Strategy 21
3.2 Applied Research Methods 22
4 Summary of Findings 26
4.1 Overview of Research Results 26
4.2 Organizational Setup of Multi-Actor Smart Service Innovation 27
4.3 Conducting Smart Service Innovation Projects 32
4.4 Approaches for the Design-integrated Assessment of Smart Services 39
5 Discussion 44
5.1 Contributions 44
5.2 Limitations 46
5.3 Managerial Implications 47
5.4 Directions for Future Research 48
6 Conclusion 54
References 55
PART B - PUBLICATIONS 68
7 It Takes More than Two to Tango: Identifying Roles and Patterns in Multi-Actor Smart Service Innovation 69
7.1 Introduction 69
7.2 Research Background 72
7.3 Methodology 76
7.4 Results 79
7.5 Discussion 90
7.6 Conclusions and Outlook 96
7.7 References 97
8 Iterative Uncertainty Reduction in Multi-Actor Smart Service Innovation 100
8.1 Introduction 100
8.2 Research Background 103
8.3 Research Approach 109
8.4 Findings 113
8.5 Discussion 127
8.6 Conclusions and Outlook 131
8.7 References 133
9 How to Tame the Tiger – Exploring the Means, Ends, and Challenges in Smart Service Systems Engineering 139
9.1 Introduction 139
9.2 Research Background 140
9.3 Methodology 143
9.4 Results 145
9.5 Discussion and Conclusions 151
9.6 References 153
10 Combining Methods for the Design of Digital Services in Practice: Experiences from a Predictive Costing Service 156
10.1 Introduction 156
10.2 Conceptual Foundation 157
10.3 Preparing the Action Design Research Project 158
10.4 Application and Evaluation of Methods 160
10.5 Discussion and Formalization of Learning 167
10.6 Conclusion 169
10.7 References 170
11 Modelling of a Smart Service for Consumables Replenishment: A Life Cycle Perspective 171
11.1 Introduction 171
11.2 Life Cycles of Smart Services 173
11.3 Case Study 178
11.4 Discussion of the Modelling Approach 185
11.5 Conclusion and Outlook 187
11.6 References 188
12 Design-integrated Financial Assessment of Smart Services 192
12.1 Introduction 192
12.2 Problem Analysis 195
12.3 Meta-Model Design 200
12.4 Application of the Meta-Model in a Tool Prototype 204
12.5 Evaluation 206
12.6 Discussion 208
12.7 Conclusions 209
12.8 References 211
13 Towards a Cost-Benefit-Analysis of Data-Driven Business Models 215
13.1 Introduction 215
13.2 Conceptual Foundation 216
13.3 Methodology 218
13.4 Case Analysis 220
13.5 A Cost-Benefit-Analysis Model for DDBM 222
13.6 Conclusion and Outlook 225
13.7 References 226
14 Enabling Design-integrated Assessment of Service Business Models Through Factor Refinement 228
14.1 Introduction 228
14.2 Related Work 229
14.3 Research Goal and Method 230
14.4 Solution Design 231
14.5 Demonstration 234
14.6 Discussion 235
14.7 Conclusion 236
14.8 References 23
Creating a Business Case from a Business Model
Intuitively, business cases and business models are closely connected. However, a thorough literature review revealed no research on the combination of them. Besides that, little is written on the evaluation of business models at all. This makes it difficult to compare different business model alternatives and choose the best one. In this article, we develop a business case method to objectively compare business models. It is an eight-step method, starting with business drivers and ending with an implementation plan. We demonstrate the method with a case study for innovations at housing associations. The designed business case method can be used to compare and select the best business model successfully. In doing so, the business case method increases the quality of the decision making process when choosing from possible business model
Creating a Business Case from a Business Model
Intuitively, business cases and business models are closely connected. However, a thorough literature review revealed no research on the combination of them. Besides that, little is written on the evaluation of business models at all. This makes it difficult to compare different business model alternatives and choose the best one. In this article, we develop a business case method to objectively compare business models. It is an eight-step method, starting with business drivers and ending with an implementation plan. We demonstrate the method with a case study for innovations at housing associations. The designed business case method can be used to compare and select the best business model successfully. In doing so, the business case method increases the quality of the decision making process when choosing from possible business model