Incumbent business ecosystems in the face of new entry: An event study of Google's autonomous car announcement

2023 | Information & Management | Citations: 0

Authors: Zhu, Xiaochen; Du, Kui

Abstract: This study investigates the value implications for an incumbent business ecosyst ... Expand

Abstract: This study investigates the value implications for an incumbent business ecosystem when an innovation is newly introduced. We theorize the different entrance modes and pathways through which the innovation can join the value co-creation structure of an incumbent ecosystem. We further theorize how the innovation entrance can affect the value appropriation arrangements among innovators and various incumbent ecosystem actors. The automobile ecosystems and Google’s initial announcement of its autonomous cars serve as our empirical context. Applying our theories, we first qualitatively prescribe Google’s potential actions and predict their value impli­ cations on the incumbent automobile ecosystem. Then, through an event study, we empirically validate the predictions. We observe that, on average, the incumbent actors of the automobile ecosystem benefited from Google’s announcement. Moreover, car manufacturers particularly benefited from Google’s attempted entry, arguably because they held critical gatekeeping positions along Google’s entrance pathway. Car component manufacturers, but not other incumbent actors, were also able to benefit because of their tight integration with the gatekeepers. Our theoretical development and empirical exploration contribute to the emerging literature on ecosystem strategies by highlighting the dynamics and value implications when innovations are introduced into incumbent business ecosystems. Collapse

Topics: innovation management Google+ autonomous driving system digital ecosystem participatory design

Methods: event study longitudinal research theory development design methodology regression analysis method

Offerings That are “Ever-in-the-Making”

2022 | Business & Information Systems Engineering | Citations: 0

Authors: Lehmann, Julian; Recker, Jan

Abstract: Digital ventures are entrepreneurial young firms that introduce new digital arti ... Expand

Abstract: Digital ventures are entrepreneurial young firms that introduce new digital artifacts that are “ever-incomplete” and “perpetually-in-the-making” onto the market. The study examines how six digital ventures continued to develop their digital market offerings post launch. Three key designing mechanisms are identified that explain continuous post-launch product development in digital ventures: deploying complementary digital objects, architectural amplification, and porting. The study discusses how these mechanisms advance our understanding of how digital technologies change entrepreneurial processes and outcomes. Collapse

Topics: new product development digital product digital entrepreneurship innovation management electronic market

Methods: qualitative interview theory development case study design artifact archival research

Increasing the Business Value Of Free-Floating Carsharing Fleets By Applying Machine-Learning Based Relocations

2022 | European Conference On Information Systems | Citations: 0

Authors: Prinz, Christoph; Hellmeier, Malte; Willnat, Mathias; Harnischmacher, Christine; Kolbe, Lutz

Abstract: Free-floating carsharing (CS) services provide customers with a fleet of vehicl ... Expand

Abstract: Free-floating carsharing (CS) services provide customers with a fleet of vehicles distributed within an operation area. These services gained popularity because of their positive impact on societal and personal mobility. Understanding determinants of customer demand is a key challenge for developing and applying vehicle relocation strategies to prevent the formation of undersupply areas. In this study, we merge possible features from publicly available data sources with historical demand from CS services situated in three different-sized cities. We train and test a Random Forest (RF) regressor estimating demand based on the enhanced dataset. Building on this demand prediction, we developed a relocation strategy that optimizes vehicle availability at anticipated demand points. Our strategy improved the reservation acceptance ratio in all three reference systems between 7.1 % and 15.6 %. Furthermore, the number of relocations compared to a deterministic relocation strategy could be reduced by 82.3 % and 20.6 % in two cities. Collapse

Topics: ride sharing platform Python organizational value big data knowledge base

Methods: simulation computational algorithm machine learning design artifact design science

Modeling styles in conceptual data modeling: Reflecting observations in a series of multimodal studies

2022 | European Conference On Information Systems | Citations: 0

Authors: Rosenthal, Kristina; Wagner, Johannes; Strecker, Stefan

Abstract: A modeling style characterizes a modeler's sequencing of processing a modeling ... Expand

Abstract: A modeling style characterizes a modeler's sequencing of processing a modeling task in terms of applying the modeling language and its language concepts while constructing a conceptual model. Presently, surprisingly little is known about the different modeling styles modelers exhibit when performing conceptual data modeling. In this research, we combine complementary modes of observation including audio-visual protocols, recorded modeler-tool interactions, and pre-/postmodeling surveys of modelers to identify modeling styles in 24 data modeling processes performed by modelers at different stages of experience in data modeling. Our study identifies and characterizes three distinct modeling styles refining our current knowledge about data modeling processes and informing design science research on style-specific, targeted modeling (software tool) support for data modelers. Collapse

Topics: pandemic ergonomics usability

Methods: data modeling design science conceptual modelling survey modeling language

Theories: structured process modeling theory

Sustainability vs. Price: Analysis of Electric Multi-Modal Vehicle Sharing Systems under Substitution Effects

2022 | European Conference On Information Systems | Citations: 0

Authors: Demircan, Muhammed; Ahadi, Ramin; Ketter, Wolfgang

Abstract: To pave the path for sustainable mobility, Information Systems are a promising ... Expand

Abstract: To pave the path for sustainable mobility, Information Systems are a promising tool to encourage users to adopt more sustainable mobility behavior. In this study, we investigate how potential demand management interventions affect the economic and environmental metrics of a multi-modal vehicle sharing operator. To this end, we narrow our focus on two important user characteristics, namely the users' flexibility and willingness to pay an additional premium for more environmentally sustainable vehicles. Our study employs a combined discrete-event and multi-agent simulation approach, which we calibrate with realworld rental data of leading free-floating vehicle sharing platforms. The results show that it is economically and ecologically disadvantageous for both the society and the fleet operator to simply increase users' mode choice flexibility. However, we clearly observe that this picture flips once users are willing to pay a surcharge to rent more environmentally sustainable vehicles. Collapse

Topics: green IS willingness to pay application programming interface service quality sharing platform

Methods: simulation multinomial logistic regression agent based simulation regression analysis method Monte Carlo simulation

Theories: socio technical theory

Needs for Speed - Categorizing commuter types in the context of smart mobility systems

2021 | European Conference On Information Systems | Citations: 8

Authors: Anschütz, Christian; Ebner, Katharina; Smolnik, Stefan; Huber, Hans-Hendrik

Abstract: A large proportion of traffic congestion can be attributed to commuters and the ... Expand

Abstract: A large proportion of traffic congestion can be attributed to commuters and their travelling behavior. While smart mobility systems (SMSs) intend to address related challenges by actively changing commuters' behavior, many SMSs lack commuters' meaningful engagement. Research and practice have started examining engagement factors that increase meaningful engagement with SMSs. The existing approaches, however, often neglect individual commuting-related needs and personal traits -two crucial facets to sustain these systems' long-term engagement. This paper identifies relevant traffic-related needs and personal traits suitable to improve meaningful engagement. We developed a theoretically sound instrument to categorize commuters in the context of smart mobility and derive first clusters from a pilot study. In the process, we synthesize existing commuter categorizations from psychology and traffic research. This synthesis centers around individual commuting-related needs, personal traits, and objective commuting characteristics. The instrument and pilot study represent a first step toward designing sustainable SMSs with meaningful engagement. Collapse

Topics: smart city data protection systems design technology adoption pandemic

Methods: survey cluster analysis literature study k-means clustering data transformation

Privacy Concerns and Data Sharing in the Internet of Things: Mixed Methods Evidence from Connected Cars

2021 | Management Information Systems Quarterly | Citations: 33

Authors: Cichy, Patrick; Salge, Torsten-Oliver; Kohli, Rajiv

Abstract: The Internet of Things (IoT) is increasingly transforming the way we work, live ... Expand

Abstract: The Internet of Things (IoT) is increasingly transforming the way we work, live, and travel. IoT devices collect, store, analyze, and act upon a continuous stream of data as a by-product of everyday use. However, IoT devices need unrestricted data access to fully function. As such, they invade users' virtual and physical space and raise far-reaching privacy challenges that are unlike those examined in other contexts. As advanced IoT devices, connected cars offer a unique setting to review and extend established theory and evidence on privacy and data sharing. Employing a sequential mixed methods design, we conducted an interview study (n=120), a survey study (n=333), and a field experiment (n=324) among car drivers to develop and validate a contextualized model of individuals' data sharing decisions. Our findings from the three studies highlight the interplay between virtual and physical risks in shaping drivers' privacy concerns and data sharing decisions-with information privacy and data security emerging as discrete yet closely interrelated concepts. Our findings also highlight the importance of psychological ownership, conceptualized as drivers' feelings of possession toward their driving data, as an important addition to established privacy calculus models of data sharing. This novel perspective explains why individuals are reluctant to share even low-sensitivity data that do not raise privacy concerns. The psychological ownership perspective has implications for designing incentives for data-enabled services in ways that augment drivers' self-efficacy and psychological ownership and thereby encourage them to share driving data. These insights help reconcile a fundamental tension among IoT users-how to avail the benefits of dataenabled IoT devices while reducing the psychological costs associated with the sharing of personal data. Collapse

Topics: information privacy concern privacy psychological ownership internet of things mobile system

Methods: qualitative interview survey archival research mixed method field study

Theories: privacy calculus theory

Factors influencing demand in free-floating vehicle sharing platforms: Real-World evidence from multimodality

2021 | European Conference On Information Systems | Citations: 0

Authors: Demircan, Muhammed; Muires, Janik; Ketter, Wolfgang

Abstract: Free-floating vehicle sharing platforms offer flexible and sustainable means of ... Expand

Abstract: Free-floating vehicle sharing platforms offer flexible and sustainable means of transportation and have thus proliferated swiftly in many cities around the globe. The operations management of these platforms prevalently relies on sophisticated information systems along with detailed demand models. Despite the emergence of such platforms and the first apparent tendencies towards multimodality, virtually no comprehensive and comparative demand models exist for the prevailing modes. Using econometric modeling, we empirically examine the effect of a rich set of factors on demand for free-floating shared cars, scooters, electric kick scooters, and bikes using a unique real-world geo-tagged rental dataset. Our analyses indicate that demand for all transportation modes considered is widely determined by factors pertaining to trip comfort, trip purpose, and user characteristics. We also provide evidence that said platforms are a key component to enable sustainable intermodal mobility as we observe demand peaks for shared vehicles close to public transportation facilities. Collapse

Topics: application programming interface analytical information system ride sharing platform privacy information privacy concern

Methods: design artifact econometric modeling survey regression analysis method conceptual modelling

Theories: socio technical theory

Stochastic Multicriteria Acceptability Analysis of EV Sharing in Nordic Rural Areas Affected by Seasonal Residence and Counterurbanization

2021 | HICSS | Citations: 0

Authors: Einolander, Johannes; Kiviaho, Annamari

Abstract: Sharing economy and shared mobility has become a widespread trend in urban areas ... Expand

Abstract: Sharing economy and shared mobility has become a widespread trend in urban areas worldwide. Due to lower population density, car sharing, and other shared mobility applications are generally not accessible in rural areas. This paper utilizes a Stochastic Multicriteria Acceptability Analysis (SMAA) method to assess the criteria importance in siting problem of rural electric vehicle (EV) sharing systems. Nordic rural areas are used as a case study in this analysis, and we compare their feasibility to act as a pilot location for EV sharing. Seasonal residence, rural tourism and counterurbanization are common themes in Nordic rural areas and act as enablers for rural vehicle sharing. Based on our novel application of SMAA to this context, we found that Swedish rural areas would be most suitable for a rural EV sharing pilot. High tourism and low vehicle ownership were identified to be the most important criteria for this siting problem. Collapse

Topics: decision making ride sharing platform sharing platform open source

Methods: multiple criteria decision making case study trade-off analysis method

Alexa, you freak me out – Identifying drivers of innovation resistance and adoption of Intelligent Personal Assistants

2021 | International Conference on Information Systems | Citations: 0

Authors: Handrich, Matthias

Abstract: Intelligent Personal Assistants (IPAs) are increasingly being integrated in man ... Expand

Abstract: Intelligent Personal Assistants (IPAs) are increasingly being integrated in many consumer products such as smartphones or cars. However, according to recent research only 50% of the population is using IPAs displaying a certain resistance behavior. Moreover, studies on the reasons for IPA resistance are not available. Consequently, our study strives to close this research gap by identifying key drivers of innovation resistance and adoption behavior of IPAs. Using a large-scale online survey (n=168) we find that individual differences, data privacy concerns, trust in AI and perceived creepiness play an important role for innovation resistance. More specifically, trust in AI applications partially mediates the relationship between individual differences and innovation resistance. Additionally, perceived creepiness fully mediates the relationship between AI data privacy concerns and innovation resistance. Our results provide valuable implications for the development and marketing of IPAs emphasizing the importance of trust and perceived creepiness for a customer's innovation resistance. Collapse

Topics: innovation management artificial intelligence information privacy concern privacy self efficacy

Methods: survey partial least squares regression survey design theoretical contribution descriptive statistic