Suchergebnisse

Through a study of the butcher trade, this article explores the meanings that men give to 'dirty work', that is jobs or roles that are seen as distasteful or 'undesirable'. Based on qualitative data, we identify three themes from butchers' accounts that relate to work-based meanings: sacrifice through physicality of work; loss and nostalgia in the face of industrial change; and distinction from membership of a shared trade. Drawing on Bourdieu, we argue that sacrifice and distinction help us understand some of the meanings men attach to dirty, manual work – forming part of a working-class 'habitus'. Further, these assessments can be both 'reproductive' and 'productive' as butchers reinforce historically grounded evaluations of work and mobilize new meanings in response to changes in the trade.

Through a study of small scale independent theatre companies, generally known as 'fringe', this article explores how passion is drawn on and activated as company founders seek an outlet for their work. Drawing on a social constructionist approach to emotions, we highlight the multiplicity of passion through its positive and negative dimensions as well as how these may intersect. Further, by positioning passion within a set of power relations we point to its performative role in reflecting and reinforcing contextually specific discursive regimes. We contribute to the literature on the social and emotional performance of entrepreneurialism and to understandings of passion that characterize the affective entrepreneurial condition.

In recent years Government departments and public/private organizations are becoming increasingly transparent with their data to establish the whole new paradigm of big open data. Increasing research interest arises from the claimed usability of big open data in improving public sector reforms, facilitating innovation, improving supplier and distribution networks and creating resilient supply chains that help improve the efficiency of public services. Despite the advantages of big open data for supply chain and operations management, there is severe shortage of empirical analyses in this field, especially with regards to its acceptance. To address this gap, in this paper we use an extended Technology Acceptance Model (TAM) to empirically examine the factors affecting users' behavioural intentions towards public sector big open data. We outline the importance of our model for operations and supply chain managers, the limitations of the study, and future research directions.

In recent years Government departments and public/private organisations are becoming increasingly transparent with their data to establish the whole new paradigm of big open data. Increasing research interest arises from the claimed usability of big open data in improving public sector reforms, facilitating innovation, improving supplier and distribution networks and creating resilient supply chains that help improve the efficiency of public services. Despite the advantages of big open data for supply chain and operations management, there is severe shortage of empirical analyses in this field, especially with regard to its acceptance. To address this gap, in this paper we use an extended technology acceptance model to empirically examine the factors affecting users' behavioural intentions towards public sector big open data. We outline the importance of our model for operations and supply chain managers, the limitations of the study, and future research directions.