Sustaining entrepreneurial business: a complexity perspective on processes that produce emergent practice

This article examines the management practices in an entrepreneurial small firm which sustain the business. Using a longitudinal qualitative case study, four general processes are identified (experimentation, reflexivity, organising and sensing), that together provide a mechanism to sustain the enterprise. The analysis draws on concepts from entrepreneurship and complexity science. We suggest that an entrepreneur’s awareness of the role of these parallel processes will facilitate their approaches to sustaining and developing enterprises. We also suggest that these processes operate in parallel at multiple levels, including the self, the business and inter-firm networks. This finding contributes to a general theory of entrepreneurship. A number of areas for further research are discussed arising from this result

Problematizing fit and survival: transforming the law of requisite variety through complexity misalignment

The law of requisite variety is widely employed in management theorizing and is linked with core strategy themes such as contingency and fit. We reflect upon requisite variety as an archetypal borrowed concept. We contrast its premises with insights from the institutional literature and commitment literature, draw propositions that set boundaries to its applicability, and review the ramifications of what we call “complexity misalignment.” In this way we contradict foundational assumptions of the law, problematize adaptation- and survival-centric views of strategizing, and theorize the role of human agency in variously complex regimes

A generative score space for statistical dialog characterization in social signalling

The analysis of human conversations under a social signalling perspective recently raised the joint attention of pattern recognition and psychology researchers. In particular, the dialog classification represents an appealing recent application whose aim is to go beyond the meaning of the spoken words, focusing instead on the way the sentences are pronounced by capturing natural (or hidden) characteristics, such the mood of the conversation. An effective strategy to face this issue is to encode the turn-taking dynamics in a generative model, whose structure is composed by conditional dependencies among first-order Markov processes. In this paper, we follow this strategy, investigating how to boost the classification performances of this model and of the related higher-order Markov extensions, through the definition of a novel generative score space. Generative score spaces are employed to increase generative classification in a discriminative way, also allowing a deep understanding of the processed data through the use of standard pattern recognition strategies. Experiments on real data certify the goodness of our intuition

Bounds for the Bayes Error in Classification: A Bayesian Approach Using Discriminant Analysis

Overlapping coefficient, Discriminant analysis, Misclassification, Lissack and Fu bounds, Bhattacharyya bounds, Hypergeometric functions, Bernoulli, Beta distribution,

Conversation analysis at work: detection of conflict in competitive discussions through semi-automatic turn-organization analysis

This study proposes a semi-automatic approach aimed at detecting conflict in conversations. The approach is based on statistical techniques capable of identifying turn-organization regularities associated with conflict. The only manual step of the process is the segmentation of the conversations into turns (time intervals during which only one person talks) and overlapping speech segments (time intervals during which several persons talk at the same time). The rest of the process takes place automatically and the results show that conflictual exchanges can be detected with Precision and Recall around 70% (the experiments have been performed over 6 h of political debates). The approach brings two main benefits: the first is the possibility of analyzing potentially large amounts of conversational data with a limited effort, the second is that the model parameters provide indications on what turn-regularities are most likely to account for the presence of conflict