Special Libraries, September 1960

Volume 51, Issue 7https://scholarworks.sjsu.edu/sla_sl_1960/1006/thumbnail.jp

Special Libraries, September 1962

Volume 53, Issue 7https://scholarworks.sjsu.edu/sla_sl_1962/1006/thumbnail.jp

Understanding entrepreneurial deviance through social learning and entrepreneurial action theory: an empirical study

Purpose: The purpose of this exploratory study is to examine entrepreneurial deviance from the perspective of New Zealand's commercial honey producers. The study adopts entrepreneurial action and social learning theories and proposes a theoretical framework in the context of entrepreneurial deviance. Design/methodology/approach: Data were collected through online surveys from 52 professional beekeepers. Findings: Overstocking of beehives, encroachment, biosecurity threats and unfair competition were most common forms of deviance affecting participants. While these predominantly responded through investing in disease prevention, security equipment or by reporting deviant incidents, finding proper solutions remains elusive. The findings revealed robust alignments with both theories. Overall, offenders’ perceived incentives to act illustrate alignment with social learning theory’s four key constructs. Entrepreneurial action emerged through individual perpetrators’ evaluation and subsequent maximisation of potentially lucrative opportunities. Originality/value: The study addresses an important and under-researched dimension, notably, the negative or “dark” side of entrepreneurs, in this case, illustrated through greed and disregard for fair and proper ways of conducting business. This knowledge gap is even more obvious among small and medium business, which is also the focus of the research. © 2020, Emerald Publishing Limited

Model-driven development for pervasive information systems

This chapter focus on design methodologies for pervasive information systems (PIS). It aims to contribute for the efficiency and effectiveness on software development of ubiquitous services/applications supported on pervasive information systems. Pervasive information systems are composed of conveniently orchestrated embedded or mobile computing devices that offer innovative ways to support existing and new business models. Those systems are characterized as having a potential large number of interactive heterogeneous embedded/mobile computing devices that collect, process, and communicate information. Additionally, they are target of high rates of technological innovations. Therefore, changes on requirements or in technology demands for frequent modifications on software at device and system levels. Software design and evolution for those requires suitable approaches that cope with such demands and characteristics of pervasive information systems. Model-driven development approaches (which essentially centre the focus of development on models, and involves concepts such as Platform-Independent Models, Platform-Specific Models, model transformations, and use of established standards) currently in research at academic and industrial arenas to design of large systems, offer potential benefits that can be applied to design and evolution of these pervasive information systems. In this chapter, we raise issues and propose strategies related to the software development of PIS using a model-driven development perspective

Workshop proceedings: Information Systems for Space Astrophysics in the 21st Century, volume 1

The Astrophysical Information Systems Workshop was one of the three Integrated Technology Planning workshops. Its objectives were to develop an understanding of future mission requirements for information systems, the potential role of technology in meeting these requirements, and the areas in which NASA investment might have the greatest impact. Workshop participants were briefed on the astrophysical mission set with an emphasis on those missions that drive information systems technology, the existing NASA space-science operations infrastructure, and the ongoing and planned NASA information systems technology programs. Program plans and recommendations were prepared in five technical areas: Mission Planning and Operations; Space-Borne Data Processing; Space-to-Earth Communications; Science Data Systems; and Data Analysis, Integration, and Visualization

The Advocate, Vol. 14, No. 2, 1983

https://dc.suffolk.edu/ad-mag/1043/thumbnail.jp

The Observer [Volume V, Issue 1]

Vol. V, Issue