Björn Hildebrandt

Uncovering the Role of IS in Business Model Innovation - A Taxonomy-driven Approach to Structure the Field

Business model innovations (BMIs) are one of the key activities organizations must undertake to survive and thrive. As information systems (IS) penetrate more and more aspects of life, they become an important factor affecting both the process and the outcome of business model innovations. The increased importance of IS in a growing number of industries has led various researchers to focus on examining the role of IS in innovation. However, these insights concentrate on process, product, and service innovations, while business model innovations encompass characteristics that are fundamentally different from these. Therefore, in this paper we use a rigorous taxonomy-building approach to uncover the distinct roles IS play in this important endeavor, employing a meta-perspective and drawing from documented empirical research on business model innovations. We found that IS act, first, as enablers of business model innovation, second, as capabilities in the business model innovation process, and third, as frames of reference for business model innovations. Our findings indicate that IS are thus both operand and operant resources in business model innovations. Hence, business managers must be aware of all of these roles, as they could have transformative impacts in every industry.

Sharing Yet Caring - Mitigating Moral Hazard in Access-Based Consumption through IS-Enabled Value Co-Capturing with Consumers

The quest for creating smart and sustainable cities entails various substantial challenges, such as environmental degradation and a shortage of space. To negotiate these hurdles, innovative approaches must be implemented. A key aspect in this regard is the shared use of resources via forms of access-based consumption. Owing to advances in the digitalization of contemporary societies, these concepts have recently attracted both consumer and scholarly interest. However, the digitally enabled separation of ownership and use brings along the risk of moral hazard by consumers using resources in careless or wasteful ways, which is detrimental to the sustainability of the overall system. In this study, the authors conceptualize and empirically investigate how these adverse effects can be mitigated by applying the potentials of connectivity and digital data to enable users to participate economically while acting favorably from a collective perspective. The results of the quasi-experimental research design, situated in a carsharing context and comprising data records of 2,983 bookings, indicate that this form of value co-capturing with consumers can significantly motivate users to alter their behavior. From these findings, the authors derive important implications for research on the sustainability of digital business eco-systems in the specific context of smart cities.

Valuing Battery Degradation from a Battery Lessor’s Perspective

In order to promote the market-introduction phase of electric mobility, car manufacturers will have to face the residual value risk of electric cars for consumers, particularly concerning the battery. An increasingly common trend to minimize uncertainties for the consumer, is the separate leasing of the battery. In this paper we examine degradation in lithium-ion batteries from a lessor’s perspective. We suppose that battery life can be influenced directly by the user. In the case of a lease contract, the battery always remains the property of the lessor. In this respect, there are no direct incentives for the user to increase battery life by expending additional effort. Therefore, we discuss the idea of a dynamic leasing concept as an opportunity for car manufacturers to encourage consumers to adopt a gentle treatment of the battery in order to extend battery lifetime and thus the residual value. Therefore, we examine the effects of different charging strategies on a battery’s residual value to verify whether there is potential for a deeper investigation of a dynamic battery leasing approach. In order to quantify the extent of user influence on battery life, lifetime simulations are performed for different charging scenarios. For our calculations we use a degradation model as a function of the depth of discharge. Furthermore, realistic driving patterns are taken into account to estimate the quantity of energy processed as a function of use mode.