Business Model Innovation of Industry 4.0 Solution Providers Towards Customer Process Innovation

Müller, Julian M.; Däschle, Simon

doi:10.3390/pr6120260

Cited by 79 publications

(48 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These should be based on innovative hybrid product and service solutions as well as individualization as another way to increase competitiveness. Especially for SME providers of Industry 4.0-based solutions, the retrofitting of existing machinery with customer-tailored service and an orientation to address actual customer requirements could represent a prosperous path [7,96].…”

Section: Discussion and Risk Frameworkmentioning

confidence: 99%

Development of a Risk Framework for Industry 4.0 in the Context of Sustainability for Established Manufacturers

et al. 2019

View full text Add to dashboard Cite

The concept of "Industry 4.0" is expected to bring a multitude of benefits for industrial value creation. However, the associated risks hamper its implementation and lack a comprehensive overview. In response, the paper proposes a framework of risks in the context of Industry 4.0 that is related to the Triple Bottom Line of sustainability. The framework is developed from a literature review, as well as from 14 in-depth expert interviews. With respect to economic risks, the risks that are associated with high or false investments are outlined, as well as the threatened business models and increased competition from new market entrants. From an ecological perspective, the increased waste and energy consumption, as well as possible ecological risks related to the concept "lot size one", are described. From a social perspective, the job losses, risks associated with organizational transformation, and employee requalification, as well as internal resistance, are among the aspects that are considered. Additionally, risks can be associated with technical risks, e.g., technical integration, information technology (IT)-related risks such as data security, and legal and political risks, such as for instance unsolved legal clarity in terms of data possession. Conclusively, the paper discusses the framework with the extant literature, proposes managerial and theoretical implications, and suggests avenues for future research.

show abstract

Section: Discussion and Risk Frameworkmentioning

confidence: 99%

Development of a Risk Framework for Industry 4.0 in the Context of Sustainability for Established Manufacturers

et al. 2019

View full text Add to dashboard Cite

show abstract

“…This also relates to the fact that a large proportion of emissions is not generated when running cars, but producing them. This is especially true for Battery-electric vehicles, as well as the integration of further technical aspects [4][5][6][79][80][81][82][83][84].…”

Section: Discussionmentioning

confidence: 99%

Comparing Technology Acceptance for Autonomous Vehicles, Battery Electric Vehicles, and Car Sharing—A Study across Europe, China, and North America

Müller

2019

Sustainability

View full text Add to dashboard Cite

The automotive industry today faces three major transitions: the emergence of autonomous driving, electric powertrain replacing the internal combustion engine, and changes in possession of automobiles, e.g., increased usage of car sharing. As all three transitions are fostered by technologies that drive digital transformation of automobiles, the Technology Acceptance Model (TAM) by Davis represents the underlying research model of this paper. Hypotheses are developed and tested for a sample of 1177 participants using Partial Least Squares Structural Equation Modeling (PLS-SEM). Group differences are investigated for three markets: Europe, North America, and China. The paper confirms the underlying assumptions of the Technology Acceptance Model in the context of automobiles. Further, it illustrates influential societal norms and individual experiences for technology acceptance. In addition, compound effects for technology acceptance are found, e.g., the perceived enjoyment of electric driving affects the acceptance of autonomous driving and car possession behavior. The novel approach to integrate three different technologies within the Technology Acceptance Model requires unifying items to a level which makes them comparable, limiting the results for each individual technology. For practice, automotive manufacturers obtain advice on how to foster technology acceptance. For society, the paper uncovers the role of societal norms for technology acceptance in the context of automobiles. Policy makers can obtain insights on how to successfully increase technology acceptance, e.g., for environmental purposes. Conclusively, the paper applies the Technology Acceptance Model for three developments in the context of automobiles, thereby extending current research using the Technology Acceptance Model.

show abstract

“…The challenge, in this case, is to find ways to collect data to use in the analysis. The prominent context of Industry 4.0 might provide an adequate ecosystem for BMI [108] once businesses become immersed in data.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Operationalizing Business Model Innovation through Big Data Analytics for Sustainable Organizations

et al. 2019

View full text Add to dashboard Cite

Business model innovation is considered key for organizations to achieve sustainability. However, there are many problems involving the operationalization of business model innovation. We used a design science methodology to develop an artifact to assist business model innovation efforts. The artifact uses performance measurement indicators of the company's business model, which are powered by Big Data analytics to endow customer-driven business model innovation. Then, we applied the artifact in a critical case study. The selected company is a fashion ecommerce that proposes a vegan and sustainable value using recycled plastic bottle yarn as raw material, and ensures that no material with animal origin is used. Our findings show that the artifact successfully assists a proactive and continuous effort towards business model innovation. Although based on technical concepts, the artifact is accessible to the context of small businesses, which helps to democratize the practices of business model innovation and Big Data analytics beyond large organizations. We contribute to the business model innovation literature by connecting it to performance management and Big Data and providing paths for its operationalization. Consequently, in practice, the proposed artifact can assist managers dealing with business model as a dynamic element towards a sustainable company.Sustainability 2020, 12, 277 2 of 29 to frequent unsuccessful results about the underlying business logic and, therefore, perpetuating failures that slow down the process of knowledge creation and, thus, undermining possibilities for growth. In this regard, there is a gap between what has been studied in academia and what can be potentially useful for managers willing to innovate their BM [8,9].Thus, BM innovation, validation, and experimentation processes need to be structured and implemented. This is relevant in several industries as the greater frequency of disruption and dislocation are shortening business model life cycles and the sustainability of any specific business model is unclear [10,11]. In a scenario of constant change and need for a better structured management process for BMI, it is important to consider alternatives for testing and experimenting with new alternatives of BM. However, it is not clear in the BMI literature how to do this in the face of the recognized complexity of this process [12,13].Christensen, Bartman, and van Bever [14] argue that there is the need for a systematic mechanism to evaluate the relationship between opportunities and BM. Besides, it is necessary to consider that innovation in BM cannot be generated randomly through guesswork. Nonetheless, Laudien and Daxböck [15] show that, in many cases, innovations in BM are not deliberate strategic options but rather a result of an emergent process, often unplanned. Strategic options, however, are usually related to a company's performance management which means the measurement of a set of indicators on various perspectives of the company [16,17]. In this sense, it seems natura...

show abstract

Business Model Innovation of Industry 4.0 Solution Providers Towards Customer Process Innovation

Cited by 79 publications

References 46 publications

Development of a Risk Framework for Industry 4.0 in the Context of Sustainability for Established Manufacturers

Development of a Risk Framework for Industry 4.0 in the Context of Sustainability for Established Manufacturers

Comparing Technology Acceptance for Autonomous Vehicles, Battery Electric Vehicles, and Car Sharing—A Study across Europe, China, and North America

Operationalizing Business Model Innovation through Big Data Analytics for Sustainable Organizations

Contact Info

Product

Resources

About