Try Before You Buy: How to Design Information Systems to Enhance Consumer Willingness to Test Sustainable Innovations

More and more business organizations recognize the relevance of sustainable innovations as driving factor for their corporate strategies, products and processes. But while the concept of sustainability is generally ratified by employees and consumers, their willingness to actually use or buy such innovations can be low. One of the most important facilitators for the adoption of innovations is self-experience generated by testing the innovation. This paper provides insight on how sustainable innovation testing affects consumer mindsets and which barriers consumers face when considering testing a sustainable innovation. The study draws on the data from an in-depth interview study with seven providers and consumers of electric cars (as sustainable innovation) in business and private environments. Insights about the nature of consumer’s willingness to test are extracted and recommendations for the design and use of information systems as facilitators for testing sustainable innovations are derived

Towards Multi-Sourcing Maturity: A Service Integration Capability Model

When outsourcing IT services, many enterprises today resort to multi-sourcing. It allows them to reduce costs and assemble a best-of-breed service portfolio. However, this usually also increases complexity. Despite the economic importance of multi-sourcing, though, there is no systematic understanding of the capabilities required to successfully integrate interdependent services and to manage multi-sourcing. This paper develops a capability model for service integration in a grounded coding approach based on literature and expert interviews. The model identifies six key capabilities and 18 sub-capabilities. We evaluate its applicability and validity via an empirical survey and two in-depth case studies. In addition, provide various insights into the implementation of service integration functions. Our contribution should provide orientation for companies how to direct their transformation efforts. It outlines an agenda for future research and builds a solid foundation for maturity models to improve multi-sourcing readiness – ultimately leading to more effective multi-sourcing solutions

Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Workers Through Explainable Artificial Intelligence

While recent advances in AI-based automated decision-making have shown many benefits for businesses and society, they also come at a cost. It has long been known that a high level of automation of decisions can lead to various drawbacks, such as automation bias and deskilling. In particular, the deskilling of knowledge workers is a major issue, as they are the same people who should also train, challenge, and evolve AI. To address this issue, we conceptualize a new class of DSS, namely Intelligent Decision Assistance (IDA) based on a literature review of two different research streams---DSS and automation. IDA supports knowledge workers without influencing them through automated decision-making. Specifically, we propose to use techniques of Explainable AI (XAI) while withholding concrete AI recommendations. To test this conceptualization, we develop hypotheses on the impacts of IDA and provide the first evidence for their validity based on empirical studies in the literature

Automatically Extracting and Analyzing Customer Needs from Twitter: A “Needmining” Prototype

Automated and scalable elicitation of customer needs is still in its infancy. With the proposed “Need mining” prototype, we aim to enable automated customer need extraction from the micro blog platform Twitter

Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Work Through Explainable Artificial Intelligence

While recent advances in AI-based automated decision-making have shown many benefits for businesses and society, they also come at a cost. It has for long been known that a high level of automation of decisions can lead to various drawbacks, such as automation bias and deskilling. In particular, the deskilling of knowledge workers is a major issue, as they are the same people who should also train, challenge and evolve AI. To address this issue, we conceptualize a new class of DSS, namely Intelligent Decision Assistance (IDA) based on a literature review of two different research streams -- DSS and automation. IDA supports knowledge workers without influencing them through automated decision-making. Specifically, we propose to use techniques of Explainable AI (XAI) while withholding concrete AI recommendations. To test this conceptualization, we develop hypotheses on the impacts of IDA and provide first evidence for their validity based on empirical studies in the literature

A Capability Framework for IT Service Integration and Management in Multi-Sourcing

Multi-sourcing, the blending of services from multiple external and internal providers, has gradually become the standard mode of operation in IT outsourcing. It allows companies to assemble a best-of-breed provider portfolio and to reduce costs. A key difference between single- and multi-sourcing is the potential interdependence between services delivered by multiple providers. To deliver a seamless service to the client’s business units, various services often need to be integrated and managed as an end-to-end service. This activity is denoted as service integration and management. Many clients, however, are having difficulties implementing and performing this important task. Therefore, we explore which IT capabilities organizations need to build for performing service integration and management. \ \ After deriving challenges from literature, we perform a multi-stage qualitative study based on a series of focus group sessions and expert interviews. In a qualitative content analysis, we develop a framework of IT capabilities which enable successful service integration and management by addressing the key challenges. We, thus, aim to contribute to more effective multi-sourcing solutions in practice and to lay the groundwork for future research in this important field

How to Cope with Change? - Preserving Validity of Predictive Services over Time

Companies more and more rely on predictive services which are constantly monitoring and analyzing the available data streams for better service offerings. However, sudden or incremental changes in those streams are a challenge for the validity and proper functionality of the predictive service over time. We develop a framework which allows to characterize and differentiate predictive services with regard to their ongoing validity. Furthermore, this work proposes a research agenda of worthwhile research topics to improve the long-term validity of predictive services. In our work, we especially focus on different scenarios of true label availability for predictive services as well as the integration of expert knowledge. With these insights at hand, we lay an important foundation for future research in the field of valid predictive services

ADAPTING IT SERVICE MANAGEMENT FOR SUCCESSFUL MULTI-SOURCING SERVICE INTEGRATION

Over the last years, IT outsourcing customers have shifted their focus to multi-sourcing. To cope with the ever-increasing complexity of their multi-provider portfolios, companies aim to develop and hone their service integration capabilities. They adapt their IT organizations to enable more efficient and effective service management for their broad service landscapes. Nowadays, most IT service management implementations build on best practice of the IT Infrastructure Library (ITIL). ITIL, however, does neither reflect multi-tenant sourcing models nor end-to-end service integration. IT service management needs to evolve to meet the new requirements of service integration. So far, however, there is a lack of guidance on how to adequately adapt IT service management for integration of multiple sourcing arrangements. Our research contributes to both theory and practice by developing a ranking of IT service management processes according to their importance for service integration success. For three important processes, we then reveal adequate implementations and process designs derived from real-life scenarios. Our results are developed during an multi-stage research study, incorporating insights from expert interviews, a quantitative questionnaire study, and case study research. The insights gained should enable multi-sourcing customers to build more successful service integration solutions, as well as academics to shape future research in this area