Narrow Results

Background: Entrepreneurial intention (EI) is the determination of the behavior that leads to entrepreneurship. The research study is mainly concerned with the factors that influence EI of women. And also to comprehend the constraints and hurdles women face towards starting an entrepreneurial venture. Azjen’s theory of planned behavior is being employed to comprehend the EI of Indian Muslim women. The theory contains the personal attitude, perceived behavioral control (PBC) and subjective norms (SN). Furthermore, intentions are also discussed in the context of religion.

Methods: A semi-structured interview schedule was carried out where a total of 7 Muslim women were interviewed in order to understand their intentions and motivations in starting a business. After gathering the data, the data were analyzed by NVivo software. This paper focused on the codes and themes generated by the software. The validity of the study was determined by content analysis, auto-coding and perusal of the themes by a subject matter expert.

Findings: The findings portray the importance of the role of family and society in deciding an entrepreneurial venture by Muslim women. The investigative outcomes of the study depict the unawareness of government schemes, limited role models and lack of training. One important factor that was discovered was the fear and insecurity Muslim women have due to their visible Muslim identity. All these features have a paramount influence on the EI of Muslim women.

This study aims to describe and understand the start of team start-ups through answering why and how team entrepreneurship (TE) is initiated, how teams form, and what kinds of criteria are used in team building. While the above topics have been examined by many scholars, we aim to elaborate new insights into understanding the very first steps of initiating a new venture by an entrepreneurs’ collective. We employ a qualitative multiple-case study approach and analyze individual and group interview data from four high-technology team start-ups through inductive thematic analysis. We find that TE starts with an impetus established by a collective desire, collective value orientation, collective demand, and collective encouragement to TE. The impetus concretizes in coming together of team members where one or some need to take initiative to form the team, and search for members with specific criteria for membership that include not only technical but social-psychological dimensions. The study suggests that emergence of entrepreneurial opportunities at the collective-level might be distinctive from the individual-level. It contributes to researchers, prospective entrepreneurs, investors, policy-makers, and educators’ understanding of TE as a versatile and dynamic phenomenon where individual and group levels of analysis and technical and social-psychological aspects intertwine.

Scientific modeling provides mathematical abstractions of real-world systems and builds software as implementations of these mathematical abstractions. Ocean science is a multidisciplinary discipline developing scientific models and simulations as ocean system models that are an essential research asset. In software engineering and information systems research, modeling is also an essential activity. In particular, business process modeling for business process management and systems engineering is the activity of representing processes of an enterprise, so that the current process may be analyzed, improved and automated. In this paper, we employ process modeling for analyzing scientific software development in ocean science to advance the state in engineering of ocean system models and to better understand how ocean system models are developed and maintained in ocean science. We interviewed domain experts in semi-structured interviews, analyzed the results via thematic analysis, and modeled the results via the Business Process Modeling Notation (BPMN). The processes modeled as a result describe an aspired state of software development in the domain, which are often not (yet) implemented. This enables existing processes in simulation-based system engineering to be improved with the help of these process models.