An Interdisciplinary Review of Investor Decision-Making in Crowdfunding

A quickly growing body of research is exploring the emerging crowdfunding phenomenon. However, in contrast to traditional startup financing or bank loans, decision-making for investments in crowdfunded ventures is not well researched. Many individual studies investigate aspects that influence investor decision-making in crowdfunding campaigns, but an integrated view of those aspects was not provided to date. We conduct a systematic and interdisciplinary literature review to examine which factors influence investment decision-making in crowdfunding. Based on the analysis of 69 articles we construct a comprehensive framework of relevant influence factors. We elicit systematic differences between crowdfunding and traditional investments, such as venture capital. The differences are: an even higher impact of social capital, the substitution of necessary with available information, and high impact of the digital context. We discuss how information systems (IS) drive those differences. Finally, we derive take-aways for IS researchers and practitioners with focus on interfaces and interactions

HOW CAN DIGITAL START-UPS SUCCESSFULLY RECRUIT IT PROFESSIONALS?

We investigate how digital start-ups can successfully recruit senior IT professionals. This is a challenge, which many young companies face due to their liabilities of newness and smallness but also due to market characteristics such as talent scarcity. We highlight success factors throughout the whole process of senior IT recruiting in a start-up context using an in-depth single case study. Our results suggest that the use of state-of-the-art technology and free choice of hardware are very important recruiting factors. Using multiple platforms to recruit first highly qualified candidates attracts further good talents. Not only typical recruiting platforms are important, but our results show that the use of expert online forums by already employed IT staff can send important signals, strengthen ties with potential candidates, and enable referrals. The recruiting process itself must be fast and interviews should communicate the appraisal of seniority, learning opportunities and management accessibility

An interdisciplinary review of investor decision-making in crowdfunding

Abstract: The Dynamic Principal Component Analysis is an adequate tool for the monitoring of large scale systems based on the model of multivariate historical data under the assumption of stationarity, however, false alarms occur for non-stationary new observations during the monitoring phase. In order to reduce the false alarms rate, this paper extends the DPCA based monitoring for non-stationary data of linear dynamic systems, including an on-line means estimator to standardize new observations according to the estimated means. The effectiveness of the proposed methodology is evaluated for fault detection in a interconnected tanks system

A systemizing research framework for Web 2.0

Web 2.0 has recently been one of the most discussed topics in Information Systems science and practice. However, little consensus is found on what its components and characteristics actually are and what a comprehensive conceptualization might look like. This paper tries to shed light on these questions by systemizing the phenomenon’s characteristics in a hierarchical framework. In a first step, we apply content and cluster analysis on contributions of the field and inductively identify 103 raw categories which are then clustered into ten subcategories and two main categories. Namely these identified main categories of Web 2.0 are: ‘Technological Characteristics’ and ‘Socioeconomic Characteristics’. In a second step, we pretest and optimize the constructs for applicability and ambiguities and finally apply them to evaluate on the importance and weighting of the discovered subcategories. The resulting framework is found to comply with common quality measures for content analysis and classification schemes. It can be used to analyze and explore economic or social phenomena associated with Web 2.0 in a systematic manner

Building Taxonomies in IS and Management – A Systematic Approach Based on Content Analysis

Classification schemes such as taxonomies are important groundwork for research on many topics in Information Systems (IS) and Management. They make investigating topics manageable by allowing researchers to delimit their work to certain taxa or types and provide a basis for generalization. Opposed to theoretically grounded typologies, taxonomies are empirically derived from entities of a phenomenon under investigation and therefore have several advantages such as more detailed and exhaustive coverage. Nevertheless, research is still missing a clear set of procedures on how to empirically build taxonomies. We tackle this topic by suggesting an inductive approach based on the procedures of content and cluster analysis. Each of the proposed six steps is amended with comprehensive state of the art guidelines, suggestions, alternatives and formative measures of reliability and validity

USING THE WISDOM OF THE CROWD TO PREDICT POPULAR MUSIC CHART SUCCESS

Abstract The peculiarities of the recording industry system, such as fashion cycles, the hedonic nature of music, socionetwork effects, informa

Revisiting Signaling Theory for Initial Coin Offerings

Blockchain applications such as Initial Coin Offerings (ICOs) have recently garnered significant attention as means of entrepreneurial financing. While receiving attention in the press, the majority of ICOs do not meet their financial goals. Lacking traditional ways to estimate value or gather information (e.g. a centralized valuation authority or a centralized platform of communication), ICOs have turned to using persuasion signals on social media to directly communicate the alleged value of their offerings to investors. In this study, we draw on signaling theory and lock-up situations, to examine the efficacy of the most commonly used persuasion signals of ICOs (social proof and authority). Technology induced lock-up periods in this context are defined as the inability to sell the purchased tokens for an unknown period of time and have not been in the focus of academic literature so far. To quantitatively test our hypotheses, we conducted a 2x2 factorial online experiment with 473 participants. Our experimental study suggests that persuasion signals were effective in the absence of a lock-up period. However, when the ICO includes a lock-up period, the persuasion signals do not work as expected from existing theory. The results even suggest that the perceived plausibility of an ICO is significantly reduced because of the combination of a lock-up period and persuasion signals