The promise of social signal processing for research on decision-making in entrepreneurial contexts

Datos Bibliográficos

ID14869045
AutoresWerner Liebregts (0000-0001-7983-9295, Tilburg University, autor de correspondencia), Pourya Darnihamedani (0000-0003-0898-9119, Utrecht University), Eric Postma (0000-0001-9627-1523, Tilburg University), Martin Atzmueller (0000-0002-2480-6901, Tilburg University)
Año2020
Volumen55
Número3
Páginas589-605
Fecha de publicación2020-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSmall Business Economics (JOURNAL)
Identificadores de la revistaISSN: 0921-898X • E-ISSN: 1573-0913
EditorialSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s11187-019-00205-1
OpenAlexW2952529317
IdiomaEN
Citas recibidas6
Referencias citadas141

In this conceptual paper, we demonstrate how modern data science techniques can advance our understanding of important decisions in the context of entrepreneurship that involve social interactions. We know that individuals’ decision-making is strongly affected by nonverbal behavior. The emerging domain of social signal processing aims at accurate computerized analysis of such behavior. Behavioral cues stemming from, for example, gestures, posture, facial expressions, and vocal expressions can now be detected and analyzed by state-of-the-art technologies utilizing artificial intelligence. This paper discusses and illustrates their potential value for future research on decision-making by entrepreneurs as well as by others yet directly affecting them (e.g., investors). In brief, social signal processing is more accurate and more efficient than conventional research methods and may reveal important characteristics that so far have been omitted in explaining decisions that are vital for firm survival and growth. We derive a total of five propositions from our newly developed conceptual framework, which we hope will be subject to extensive empirical scrutiny in future research

Business · Conceptual framework · Context (archaeology · Data science · Economics · Empirical research · Entrepreneurship · Epistemology · Gesture · Knowledge management · Machine learning · Management science · Political science · Scrutiny · Social science · Sociology · Value (mathematics · Cognitive Science and Education Research · Computer Science · Psychology · Artificial Intelligence