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The purpose of this paper is to present an ontology‐based approach of context‐sensitive computing for the optimization of flexible manufacturing systems (FMS).

A context‐sensitive computing approach is presented, integrated on top of FMS control platform. The approach addresses how to extract manufacturing contexts at source, how to process contextual entities by developing an ontology‐based context model and how to utilize this approach for real time decision making to optimize the key performance indicators (KPIs). A framework for such an optimization support system is proposed. A practical FMS use case within SOA‐based control architecture is considered as an illustrative example and the implementation of the core functionalities to the use case is reported.

Continuous improvement of the factory can be enhanced utilizing context‐sensitive support applications, which provides an intelligent interface for knowledge acquisition and elicitation. This can be used for improved data analysis and diagnostics, real time feedback control and support for optimization.

The performance of context‐sensitive computing increases with the extraction, modeling and reasoning of as much contexts as possible. However, more computational resources and processing times are associated to this. Hence, the trade‐off should be in between the extent of context processing and the required outcome of the support applications.

This paper includes the practical implications of context‐sensitive applications development in manufacturing, especially in the dynamic operating environment of FMS.

Reported results provide a modular approach of context‐sensitive computing and a practical use case implementation to achieve context awareness in FMS. The results are seen extendable to other manufacturing domains.

Describes intuitively the fact that four types of formal languages can be generated by four types of grammars or can be recognized by four types of automata. Gives the relationships between context‐sensitive languages and computer programming languages. Defines and investigates parallel productions, parallel grammars, and context‐free parallel grammars. Shows that context‐sensitive languages exist which can be generated by context‐free parallel grammars. In addition, states the advantages of context‐free parallel grammars. Also shows that context‐free languages (CFL) are a proper subset of context‐free parallel languages (CFPL). Furthermore, CFPL is a more effective tool for modelling computer programming languages than CFL, especially for parallel computer programming languages, for example, the ADA programming language. Also illustrates context‐sensitive property of recognizing hand‐written characters. The results may have useful applications in artificial intelligence, model parallel computer programming languages, software engineering, expert systems and robotics.

Vast volumes of rich online consumer-generated content (CGC) can be used effectively to gain important insights for decision-making, product improvement and brand management. Recently, many studies have proposed semi-supervised aspect-based sentiment classification of unstructured CGC. However, most of the existing CGC mining methods rely on explicitly detecting aspect-based sentiments and overlooking the context of sentiment-bearing words. Therefore, this study aims to extract implicit context-sensitive sentiment, and handle slangs, ambiguous, informal and special words used in CGC.

A novel text mining framework is proposed to detect and evaluate implicit semantic word relations and context. First, POS (part of speech) tagging is used for detecting aspect descriptions and sentiment-bearing words. Then, LDA (latent Dirichlet allocation) is used to group similar aspects together and to form an attribute. Semantically and contextually similar words are found using the skip-gram model for distributed word vectorisation. Finally, to find context-sensitive sentiment of each attribute, cosine similarity is used along with a set of positive and negative seed words.

Experimental results using more than 400,000 Amazon mobile phone reviews showed that the proposed method efficiently found product attributes and corresponding context-aware sentiments. This method also outperforms the classification accuracy of the baseline model and state-of-the-art techniques using context-sensitive information on data sets from two different domains.

Extracted attributes can be easily classified into consumer issues and brand merits. A brand-based comparative study is presented to demonstrate the practical significance of the proposed approach.

This paper presents a novel method for context-sensitive attribute-based sentiment analysis of CGC, which is useful for both brand and product improvement.

The purpose of this paper is to investigate performance measurement practices in venture capital firms. Specifically, the author examines how two organizations make complexity and uncertainty manageable by mobilizing performance measurement. This study draws on the framework of pragmatic constructivism (PC) (Nørreklit et al., 2016; Nørreklit et al., 2006, 2010), focusing on the integration between the four dimensions of PC, namely, facts, values, possibilities and communication.

The paper adopts a comparative case study methodology.

The findings show that performance measurement practices are strongly influenced by values playing out via integration in actor-world relations, whereas Venture A mobilizes an actor-centric approach, leading to an open, holistic performance measurement system (PMS) which is based on non-financials, a close involvement in operational matters and actors’ judgement using accounting as “learning machines” (Burchell et al., 1980); and Venture B draws on an analytical approach emphasizing on the role of financial indicators and control enacting accounting as “answer machines” and as “tool for computation” (Burchell et al., 1980). These different approaches to PMS, actor-centric vs analytical, are guided by different values about actor-world relation(s).

The paper provides a context-sensitive account on the relationship between uncertainty and performance measurement practices. First, this paper contributes by providing evidence on how actors use accounting to manage uncertainty and complexity by differently integrating actor-world relation(s) (Nørreklit, et al., 2016; Nørreklit et al., 2006). Second, this study resonates with recent calls for more industry-specific and context-sensitive investigations (Messner, 2016). Finally, the author contributes to the literature asking for more research on the role accounting plays in managing uncertain conditions (Chenhall and Moers, 2015).

The aim of this paper is to present an architecture and prototypical implementation of a context‐sensitive software system which combines the tangible user interface approach with a mobile augmented reality (AR) application.

The work which is described within this paper is based on a creational approach, which means that a prototypical implementation is used to gather further research results. The prototypical approach allows performing ongoing tests concerning the accuracy and different context‐sensitive threshold functions.

Within this paper, the implementation and practical use of tangible user interfaces for outdoor selection of geographical objects is reported and discussed in detail.

Further research is necessary within the area of context‐sensitive dynamically changing threshold functions, which would allow improving the accuracy of the selected tangible user interface approach.

The practical implication of using tangible user interfaces within outdoor applications should improve the usability of AR applications.

Despite the fact that there exist a multitude of research results within the area of gesture recognition and AR applications, this research work focuses on the pointing gesture to select outdoor geographical objects.

SFX is an XML‐based product designed to inter‐link electronic resources with other resources in context‐sensitive manner. SFX was first developed at the University of Ghent by Herbert Van de Sompel and has been released as a commercial product by Ex Libris. Use statistics garnered from SFX’s statistics module since the implementation in July of 2001 are discussed in the context of an academic research library environment. The results from usability testing conducted at Washington State University are reported. These usage statistics demonstrated a pattern of increasing use and exceptional use from FirstSearch databases.

To determine the human and environmental values that need to be protected at every ethical decision‐making point, given that resources are finite and that the needs of future generations have no upper limit.

A search was made of the Humanities and Area Studies Databases and Articles, the Philosophers' Index, RenDa Fuyin Baokan Ziliao (People's University reprints series), the Arts and Humanities Citation Index on ISI Web of Knowledge, the Arts and Humanities Data Service, the British Philosophy Database, Dissertation Abstracts International, the Routledge Encyclopaedia of Philosophy (REP Online), ZETOC (Electronic Table of Contents) through MIMAS, and Academic Search Elite. Relevant arts and humanities journals were hand‐searched, and reference lists examined for further relevant reports.

Although decision making in environmental policy relies on logic, empirical fact and intuition, it does not make sense to have a “universal master plan” covering living persons, the unborn, and the non‐human world when designing an environmental policy. Environmental policy options are meaningful in specific contexts; since each context has its own underpinnings and specific preferences on the basis of its own peculiar socio‐cultural and economic circumstances, the necessity of narrative ethics in decision making becomes evident.

As this review demonstrates, the initial concern in environmental matters may centre on the preservation of human health, clean health, clean air and water, endangered species, jobs and the needs of future generations. Decisions may then be reached through cost benefit analysis, which tends to be whether or not the chosen course of action produces greater balance, the greatest happiness to the greatest number. But there are difficulties in determining what constitutes “cost” or “benefit”.

It became evident from this study that, to stand the test of time, context‐sensitive environmental paradigms should be capable of enriching themselves with ideas from other approaches to decision making such that, although problems may have a global dimension, the solutions to them must be context‐sensitive.

Purpose – The aim of this study is to examine the impact of co-operative governance structures on citizen participation in public service provision.Methodology – Using a multiple case study-approach, we analyse and compare five examples of co-operative public–citizen partnerships in Austria and Germany.Findings – The study clearly shows that co-operatives can be a tool for both, (1) the bottom-up self-organization of citizens (co-operative as ‘contested space’) and (2) the top-down organization to canalize citizen participation (co-operative as ‘invited space’). Co-operative public–citizen partnerships therefore represent a balancing act between dependency through public funding and autonomy through community-based decision making.Research implications and limitations – The chapter underlines the importance of context-sensitive qualitative research. Limitations might stem from the fact that municipal areas might differ in other countries than Germany and Austria, for example, due to legal prerequisites.Practical implications – If regional government representatives are supporting a bottom-up initiative, they are more inclined to provide crucial resources for the public–citizen partnership and tensions between different stakeholders involved are weakened.Social implications – Co-operative public–citizen partnerships might enhance participatory democracy and seem to strengthen solidarity and social cohesion on the neighbourhood level.Originality/value of chapter – In showing that co-operatives are a suitable governance structure for community organizations, which enhance democratic decision making and foster social innovation in public service delivery, we support the findings of other studies. The chapter suggests that in order to enhance our understanding of citizen participation, context-sensitive research that goes beyond merely descriptive governance analysis is needed, taking into account the historical trajectories of public–citizen partnerships.

The study maps workplace stakeholders’ perceptions of living wage (LW) impacts in New Zealand. Empirical findings inform an inaugural model of LW impacts and contingent factors at individual, organisation, sector/industry and national levels.

Data from a national employee survey, semi-structured interviews with business sector representatives, and staff in two LW organisation cases were subjected to thematic content analysis.

Informants emphasised anticipated LW impacts amid complex workplace and regulatory dynamics. Employers/managers stressed its cost effects. However, employees, human resource (HR) advocates and other LW proponents highlighted employee “investment” impacts that improve worker productivity and societal circumstances.

This study highlights the need for further context-sensitive LW analysis. An initial model of LW impacts provides a framework for comparative and longitudinal work in other national contexts.

The proposed model categorises perceived LW effects and can inform policy development. Findings also stress a need for cross-agency initiatives to address LW concerns, including a key role for HR.

The findings highlight perceptions of a LW impacting within and beyond the workplace. Whilst higher-quality management is seen to encourage better-informed decisions about “going living wage”, a LW's positive socio-economic impacts require multi-lateral initiatives, suggesting that those initiatives are is part of wider obligations for policy makers to encourage decent living standards.

This study provides a much-needed and inaugural focus on the intertwined workplace and wider impacts of a LW, extending extant econometric analyses. The paper also synthesizes different data sources to develop an inaugural, context-sensitive model of perceived LW effects.

The purpose of this paper is to consider Turing's test and his objections to the idea that a machine might eventually pass it. Discusses behavioural diversity in relation to the Turing test.

The paper argues that this objection cannot be dismissed easily, taking the view that the diversity exhibited by human behaviour is characterised by a kind of context‐sensitive adaptive plasticity. Draws on Descartes' arguments and artificial intelligence to interpret the Turing test.

It is found that the distinctive context‐sensitive adaptive plasticity of human behaviour explains why the Turing test is such a stringent test for the presence of thought and why it is much harder to pass than Turing himself may have realised.

This paper provides an unique view of Turing's test that will assist researchers in assessing its value and its goals.