Incentives and More: Four Aspects that Every Innovation in Scholarly Communication Needs To Consider—Answer to “Kingsley/Kennan: Open access: The whipping Boy for Problems in Scholarly publishing”

We discuss the scholarly publication model and the impact of the current technological change on knowledge and communication generally on the scholarly publication model. We propose that, rather than open access being the cause of the apparent and impending collapse of the scholarly publication industry, it is but one driver of a far wider change in scholarly publication. That change will have effects that extend well beyond the simple decision of whether a publication should be available by subscription or by one of the forms of open access. We also present several other changes to scholarly publication. The change is inevitable but its extent is as yet unclear

The Drivers of Entrepreneurial Intentions - An Empirical Study among Information Systems and Computer Science Students

The last decade has seen an enormous increase in research on entrepreneurship education. However, there is so far only little research on entrepreneurship education in the field of information technology. To address this research gap, we conducted an empirical study based on an extended model of the Theory of Planned Behavior among Information Systems and Computer Science students. We found Attitude being the main driver for Information Systems students, and having discovered a Business Idea being the most influential factor for Computer Science students. In a more detailed analysis, the perception that being an entrepreneur does not come with a high risk to fail, the opportunity for self-fulfillment, and the chance of a high monetary reward could be identified as the crucial drivers regarding Information Systems students. Based on our findings, we discuss the implications for developing more entrepreneurially-oriented courses tailored to both groups of students

Institutional Influences in Individual-level Innovation Adoption outside Organizational Contexts: A Scale Development Study

There has recently been a growing interest in IS innovation research regarding how institutional influences affect organizations’ adoption decisions under the label “organizational institutionalism”. However, there has been a lack of research regarding institutional influences on individual adopters in non-organizational adoption settings, although insitutional theory\u27s foundations apply to decisions made by actors in general. In our paper, we expand the use of institutional theory to also include the impact on individuals in non-organizational settings. We develop three constructs comprising “institutional influences on individual-level innovation adoption”- normative, cultural-cognitive, and regulative influences - in a non-organizational setting, and rigorously validate them through a state-of-the-art procedure. Subsequently, we empirically test the measurement model’s fit and the constructs’ validity and reliability through a web-based survey. Besides, we find that institutional individual-level influences\u27 impact on behavioral intention is mediated through performance expectations, which is in contrast to their direct impact on intention in organizational settings

The Role of Trust in Promissory Organizations in IS Innovation Adoption – Development of a Research Model

Promissory organizations like IS analysis companies or academic institutions have started to play an increasingly important role in the way organizations make sense of IS innovations. Research has so far neglected how the trust that potential adopters place in these promissory organizations affects institutional pressures that promissory organizations exert on them. In this research-in-progress paper, we develop a research model to analyze the effects of different trusting beliefs – integrity, competence, and benevolence beliefs – in IS analysis companies and IS scholars, and how they affect potential adopters’ performance expectations in the early diffusion stages of an IS innovation. We expect this model to contribute to a more nuanced understanding of the role of promissory organizations as a mechanism of producing institutional trust and the importance of institutional trust for potential adopter firms in IS innovation adoption

When is it Better to Have No Role Models? Evidence from the Internationalization of Companies in the German Software Industry

The internationalization of a company is a complex endeavor. However, because of the special characteristics of the software industry, the internationalization of a software company can be particularly critical to its success. This study is among the first to employ institutional theory to analyze a software company’s degree of internationalization. An analysis based on the survey of 306 German software companies shows that both managers’ perception of the domestic market as a “comfort zone” and debt investors’ pressures have a significant impact on the companies’ internationalization behavior. Besides, when they perceive the domestic market as unattractive, software companies that have other German IT companies as a role model internationalize to a lesser degree than companies without German role models. The study’s findings therefore point to successful strategies for policy-makers and managers alike that aspire to foster the internationalization of software companies

Human vs. Algorithmic Recommendations in Big Data and the Role of Ambiguity

Based on big data, decisions can increasingly be drawn from data-driven analytics and algorithmic decision support. However, it remains unclear whether recommendations issued by computer algorithms are equally accepted by individuals as human advices. This is particularly intriguing given that big data entails various forms of ambiguous decision situations in which individuals cannot assess the underlying database or possible consequences. We conceptually introduce ambiguity in the light of big data and conduct an experiment to identify whether individuals prefer algorithmic to human recommendations and how outcome and data ambiguity affect individuals’ adoption behavior of algorithmic decision support. We find a preference for human recommendations, independently from the level of inherent ambiguity. However, areas that are more data-driven have a higher potential to overcome resistance to algorithmic decision support. Our results imply that developers of algorithmic decision support should provide high levels of transparency in areas which currently lack support