Technologies in caregiving: professionals’ strategies for engaging with new technology

This article explores the adoption of new technology in organisations that provide senior citizen care. Inspired by Niklas Luhmann’s systems theory, we study how technology reduces complexity by identifying client needs and ensuring predictability in service delivery. However, how technologies are adopted in practice is not determined by technology since it is also structured by care-workers' continuous decision-making. Against this backdrop, we explore how technologies alter the conditions for decision-making in two settings of elderly care, and we describe how care workers seek to adapt technologies to their practical needs as well as conception of care ethics. Developing a systems theory approach, the article eschews a priori assumptions of technological constraint on care-workers’ professional autonomy, offering a more open-ended exploration of diversified strategies for coping with new technology. Our case studies show that employees develop diversified strategies for technology adoption, including both non-usage, heated resistance, excessive embrace, and creative adaption.     

Khat-chewing in liminal leisure spaces: British-Somali youth on the margins

Khat-chewing, a controversial leisure activity within the Somali diaspora in Britain, has received little attention within the academic field of Leisure Studies. This paper reports on ethnographic research to provide insights into the unique locations where young British-Somali men chew khat, exposing the liminal qualities of such localities. The paper begins with an overview of the contentious position khat-chewing occupies within Somali communities in Britain, highlighting reasons why young British-Somali men hide their association with the leisure practice. The discussion that follows considers how young male khat users conceptualise spatial environments, exposing how these locations temporarily produce a dual sense of privacy and sociality. The ambiences of such temporary leisure spaces remain open to the prospect of discovery, resulting in the use of discretionary tactics to maintain a sense of secrecy. In this context, we discuss how khat-chewing offers a sense of cultural identity and belongingness while also marking young British-Somali men as outsiders – even within their own communities.     

Coping with coopetition—Facing dilemmas in cooperation for sustainable development: The case of the Dutch smart grid industry

This paper is amongst the first to examine coopetition strategy for sustainable development at the network level. Companies who want to successfully implement complex innovative technologies that support sustainable development need to collaborate with other actors of the innovation ecosystem, including their competitors, so that they can develop standards, interoperable products, pool knowledge, and resources and bundle forces to compete against other technologies. Collaboration with competitors brings benefits, but also many risks. We investigated how firms cope with these risks when establishing an innovation ecosystem to implement a new technology in society. We conducted research in the Dutch smart grids sector and explored how these firms minimize inherent risks of coopetition. We found that system‐building actors in the Dutch smart grid field not only minimize inherent risks, but from the start of their collaboration they implement so‐called enablers to prevent these risks upfront.     

Contagion of network products in small-world networks

We formulate a model in which agents embedded in an exogenous social network decide whether to adopt a new network product or not. In the theoretical part of the paper, we characterize the stochastically stable equilibria for complete networks and cycles. For an arbitrary network structure, we develop a novel graph decomposition method to characterize the set of recurrent communication states, which is a superset of stochastically stable equilibria of the adoption game presented in our model. In the simulation part, we study the contagion process of a network product in small-world networks that systematically represent social networks. We simulate a generalization of the Morris (Rev Econ Stud 67(1):57–78, 2000) Contagion model that can explain the chasm between early adopters and early majority. Our numerical analysis shows that the failure of a new network product is less likely in a highly cliquish network. In addition, the contagion process reaches to steady state faster in random networks than in highly cliquish networks. It turns out that marketers should work with mixed marketing strategies, which will result in a full contagion of a network product and faster contagion rates with a higher probability.

     

Climate for conflict management,exposure to workplace bullying and work engagement: a moderated mediation analysis

The present study investigates a potential preventive factor in relation to workplace bullying. Specifically, we examine how climate for conflict management (CCM) may be related to less bullying, increased work engagement, as well as whether CCM is a moderator in the bullying engagement relationship. The study was based on a cross-sectional survey among employees in a transport company (N = 312). Hypotheses were tested simultaneously in a moderated mediation analysis which showed that bullying and job engagement were related (H1), CCM was related to less reports of bullying (H2), CCM was related to work engagement (H3) and that CCM was indirectly related to job engagement through bullying (H4), but only when CCM was weak (H5). That is, CCM moderated the relationship between bullying and work engagement in that this relationship only existed when CCM was low. The present study contributes to theory within this research field by showing that organizational measures may not only prevent bullying, but may also affect how employees react when subjected to bullying. Furthermore, the effect of climate in relation to bullying may be down to the narrow bandwidth facet of CCM. The study informs employers how they may act to prevent bullying while also reducing the potential negative outcomes of those cases of bullying that inevitably will show up from time to time.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Ownership structure and hospital service costs and fees: A decomposition approach

This paper analyzes hospital characteristics that are associated with higher average costs and charges for venipuncture, computed tomography procedures (computerized axial tomography [CAT] scans), and electrocardiograms (EKG). Using data from a Medicare database, our results indicate that higher wages, larger hospital sizes, and greater service quality are associated with higher procedure costs, whereas system membership is generally associated with lower procedure costs. Blinder‐type decompositions, which are the main focus of this study, suggest (a) that venipuncture costs are about 17% to 19% lower at proprietary hospitals than at nonprofit or government hospitals, (b) CAT scan costs are about 6% to 12% lower at nonprofit hospitals than at proprietary and government hospitals, and (c) that EKG costs are about 3% lower at proprietary hospitals than at nonprofit or government hospitals. Lastly, large portions of each of these differences are found to be due to both differences in mean values of the hospitals' characteristics by ownership type and differences in the mechanism by which the hospitals' characteristics are transmitted to procedure costs.