Beyond discovery : a case study of teacher interaction, young children and computer tasks

The integration of computer technologies into everyday classroom life continues to provide pedagogical challenges for school systems, teachers and administrators. Data from an exploratory case study of one teacher and a multiage class of children in the first years of schooling in Australia show that when young children are using computers for set tasks in small groups, they require ongoing support from teachers, and to engage in peer interactions that are meaningful and productive. Classroom organization and the nature of teacher-child talk are key factors in engaging children in set tasks and producing desirable learning and teaching outcomes.

Investigating design, creativity and entrepreneurial processes

Entrepreneurship, creativity, and design are all ingredients of the innovation process and are sometimes confused, misapplied, and used interchangeably. This conceptual paper responds to recent calls for further investigation of the links between entrepreneurship and related disciplines, and explores a solution focused approach most strongly developed and applied in new product and enterprise development — that of design and design thinking. The paper extends prior research on entrepreneurship, creativity, and design, and argues for tighter links between these notions in the establishment and ongoing evolution of enterprises.

“Entrepreneurial management” as a strategic choice in firm behavior : linking it with performance

Establishing the core principals of “entrepreneurial management” within an organization describes a certain strategic choice that affects a company in six dimensions, according to Stevenson (1983). Our aim is to empirically measure entrepreneurial management (it’s existence and degree) and to link this measured strategic choice (for or against) entrepreneurial management with firm performance. Our argument here is that companies that follow core principals of entrepreneurial management should outperform other more administrative firms in certain measures of strategic performance. This paper builds on an empirical investigation published by Brown, Davidson & Wiklund (2001), who have developed and tested a reliable measurement instrument for Stevenson’s definition of “entrepreneurial management” (Stevenson 1983, Stevenson & Jarillo 1990). In the first part of our paper we aim to replicate and to some extent improve this study. In the second part we link the measured degree of “entrepreneurial management” with firm performance. To our knowledge, even so Stevenson’s definition of entrepreneurial management is commonly acknowledged and Brown et al. (2001) developed a reliable instrument to empirically capture this behavioral approach to management, the construct of entrepreneurial management never before has been linked to firm performance in an empirical study. Since most papers on corporate entrepreneurship and firm performance are based on Covin & Slevin’s (1991) or Miller’s (1983) concept of entrepreneurial orientation, we contribute to the literature on corporate entrepreneurship in a novel way, given the fact that the entrepreneurial management dimensions measured in our study can theoretically and empirically be clearly distinguished from the construct of entrepreneurial orientation as defined by Covin & Selvin (1991).

Entrepreneurial bricolage and firm performance : moderating effects of firm change and innovativeness

The behavioral theory of “entrepreneurial bricolage” attempts to understand what entrepreneurs do when faced with resource constraints. Prior research suggests that bricolage behaviors enable firms to “make do” through recombining existing resources and may assist in the development of firms that are better able to manage market uncertainties, survive and perhaps even flourish despite resource constraints. Using a new survey measure we further theorize and test the moderating effects of firm strategic change and innovativeness on bricolage and firm performance. Our findings suggest that changes in core elements of the business and degree of innovation reduce the positive effects of bricolage in young firm performance.

Human resource flexibility and strong ties in entrepreneurial teams

Human resource flexibility is important in entrepreneurial ventures that need to respond to the changing challenges of growing the new business. This research investigates the impact of previously well-known people (strong ties) as entrepreneurial team members on the human resource flexibility of new ventures. Data collected from German founding entrepreneurs in technology-oriented, incubator-based firms shows that choosing a well known individual to join the entrepreneurial team increases the founder's ability to modify the team member's work role, but complicates asking the team member to leave the team if required. Hence, strong ties both increase and reduce human resource flexibility. However, the effect of strong ties on role modifiability is statistically significant only with novice entrepreneurs. These research findings counsel founders to discuss role modification and exit during partnership and entrepreneurial team membership negotiations.

Online social networks as an emerging opportunity for entrepreneurship : a study of the music industry

The explosion in use of online social networks is an important phenomenon that provides a new set of entrepreneurial opportunities. Emerging musicians have been among the first to exploit this new market opportunity – and indeed, many have used it successfully. A recent study Carter (2009) reveals that artists who earned the most returns had an online presence on multiple social online sites and services such as MySpace and Facebook. These web pages are leveraged to build fan bases and develop different types of revenue streams. Yet, little is currently known about discovery or exploitation of such opportunities.

Comprehensive Australian study of entrepreneurial emergence (CAUSEE): project presentations an early results

It is widely acknowledged that entrepreneurship is one of the most important forces shaping changes in the economic landscape (van Praag and Versloot 2007). An understanding of the process by which new economic activity and business entities emerge is therefore vital. The Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) is a research project that aims to uncover the factors that initiate, hinder, or facilitate the process of emergence, survival, and success of new independent businesses.

Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE): design, data collection and descriptive results

The Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) is a research programme that aims to uncover the factors that initiate, hinder and facilitate the process of emergence of new economic activities and organizations. It is widely acknowledged that entrepreneurship is one of the most important forces shaping changes in a country’s economic landscape (Baumol 1968; Birch 1987; Acs 1999). An understanding of the process by which new economic activity and business entities emerge is vital (Gartner 1993; Sarasvathy 2001). An important development in the study of ‘nascent entrepreneurs’ and ‘firms in gestation’ was the Panel Study of Entrepreneurial Dynamics (PSED) (Gartner et al. 2004) and its extensions in Argentina, Canada, Greece, the Netherlands, Norway and Sweden. Yet while PSED I is an important first step towards systematically studying new venture emergence, it represents just the beginning of a stream of nascent venture studies – most notably PSED II is currently being undertaken in the US (2005– 10) (Reynolds and Curtin 2008).

Nascent entrepreneurship and the developing individual : early entrepreneurial competence in adolescence and venture creation success during the career

What predicts a person's venture creation success over the course of the career, such as making progress in the venture creation process and multiple successful venture creations? Applying a life span approach of human development, this study examined the effect of early entrepreneurial competence in adolescence, which was gathered retrospectively by means of the Life History Calendar method. Human and social capitals during the founding process were investigated as mediators between adolescent competence and performance. Findings were derived from regression analyses on the basis of prospective and retrospective data from two independent samples (N = 88 nascent founders; N = 148 founders). We found that early entrepreneurial competence in adolescence had a positive effect on making progress in the venture creation process. Nascent founders' current human and social capital also had a direct effect, but it did not mediate the effect of early competences. Finally, the data revealed that early entrepreneurial competence in adolescence positively predicted habitual entrepreneurship (multiple successful venture creations) exhibited over a longer period of the individual career (specifically, 18 years). In line with the results from prospective longitudinal studies on early precursors of entrepreneurship, our findings underscore the long neglected importance of adolescent development in the explanation of entrepreneurial performance during the subsequent working life.

Privacy v IP Litigation : preliminary third party discovery on the Internet

The enforcement of Intellectual Property rights poses one of the greatest current threats to the privacy of individuals online. Recent trends have shown that the balance between privacy and intellectual property enforcement has been shifted in favour of intellectual property owners. This article discusses the ways in which the scope of preliminary discovery and Anton Piller orders have been overly expanded in actions where large amounts of electronic information is available, especially against online intermediaries (service providers and content hosts). The victim in these cases is usually the end user whose privacy has been infringed without a right of reply and sometimes without notice. This article proposes some ways in which the delicate balance can be restored, and considers some safeguards for user privacy. These safeguards include restructuring the threshold tests for discovery, limiting the scope of information disclosed, distinguishing identity discovery from information discovery, and distinguishing information preservation from preliminary discovery.

Who is the corporate entrepreneur? Insights from opportunity discovery and Creation Theory

Recent research has begun to address and even compare nascent entrepreneurship and nascent corporate entrepreneurship. An opportunity based view holds great potential to integrate both streams of research, but also presents challenges in how we define corporate entrepreneurship. We extend (corporate) entrepreneurship literature to the opportunity identification phase by providing a framework to classify different types of corporate entrepreneurship. Through analysis of a large dataset on nascent (corporate) entrepreneurship (PSEDII) we show that these corporate entrepreneurs differ largely from each other in terms of human capital. Prior studies have indicated that independent and corporate entrepreneurs pursue different types of opportunities and utilize different strategies. Our findings from the opportunity identification phase challenge those differences and seem to indicate a difference between the opportunities corporate entrepreneurs identify versus the opportunities they exploit.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Effective pattern discovery for text mining

Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.

Mining positive and negative patterns for relevance feature discovery

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences, but many experiments do not support this hypothesis. The innovative technique presented in paper makes a breakthrough for this difficulty. This technique discovers both positive and negative patterns in text documents as higher level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the higher level features. Substantial experiments using this technique on Reuters Corpus Volume 1 and TREC topics show that the proposed approach significantly outperforms both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and pattern based methods on precision, recall and F measures.

An entrepreneurial model of economic and environmental co-evolution

A basic tenet of ecological economics is that economic growth and development are ultimately constrained by environmental carrying capacities. It is from this basis that notions of a sustainable economy and of sustainable economic development emerge to undergird the “standard model” of ecological economics. However, the belief in “hard” environmental constraints may be obscuring the important role of the entrepreneur in the co-evolution of economic and environmental relations, and hence limiting or distorting the analytic focus of ecological economics and the range of policy options that are considered for sustainable economic development. This paper outlines a co-evolutionary model of the dynamics of economic and ecological systems as connected by entrepreneurial behaviour. We then discuss some of the key analytic and policy implications.