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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.

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.

Context is known to affect evaluation for many goods. For example, a house of any given size is more likely to be viewed as adequate the larger it is relative to other houses in the same locale. If evaluations of some goods are more sensitive to context than others, there is no presumption that privately optimal consumption patterns will be socially optimal. Rather, consumers will spend too much on goods whose evaluations depend most strongly on context and too little on those whose evaluations depend least strongly on context. For instance, if evaluations of houses are more sensitive to context than evaluations of leisure, then people will spend too much money on houses and too little time with family and friends. But if context sensitivity is the same for all goods, no distortions result.

This paper suggests theoretical grounds for expecting context sensitivity to differ across goods. Evaluations should be more sensitive to context for goods whose consumption is more readily observed by others and also for goods for which relative consumption is linked to other important payoffs. The quality of school that a child attends, for example, is often strongly linked to its parents’ relative expenditures on housing.

A survey of empirical evidence suggests that observed differences in context sensitivity track the differences predicted on theoretical grounds.

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.

The purpose of this paper is to investigate the development of a culturally sensitive and end‐user‐centric software architectural framework for the development of eService applications in information and communication technologies for development (ICTD) contexts. The research is undertaken within the Siyakhula Living Lab (SLL) in South Africa.

Action research is the approach undertaken in this research with an extensive literature review to inform the development of the architecture, which is later qualitatively and quantitavely validated.

Various factors have to be taken into consideration for technology solutions to be effective in their context of deployment. The authors have provided an architecture that intrinsically enables software solutions to be developed from the ground up with concern for flexibility for context sensitivity. The PIASK architecture separates the presentation, interaction, access, social networking and knowledge base components into five distinct functional layers. This architecture is validated for: technical viability through a development of a knowledge portal in SLL; cultural sensitivity through Dooyeweerd's theory of modal aspects; and user centricity using a SALUTA‐based evaluation.

The successful evolution of any society towards a knowledge society is predicated on technology solutions that embrace and that are sensitive to the socio‐cultural diversity of that society. The PIASK architecture developed in this research is a tool that can be used in the realization of services and applications for ICTD contexts in South Africa and other third‐world countries.

The software architecture developed specifically for ICTD contexts to encapsulate context sensitivity and user centricity is the primary and novel contribution of this research.

The purpose of this paper is to present a systems perspective of context avenues that impact the knowledge‐sharing process.

Following a brief introduction of the meaning of context, an example of face‐to‐face interaction is used to explore the term “context‐sensitive” in terms of sharing knowledge in a one‐way single exchange from a source to a perceiver. Eight different context avenues are presented, their relationship to the conscious and unconscious mind addressed, and their impact on the sharing of knowledge considered.

The authors posit that there are eight primary context avenues that potentially impact the creation of knowledge in terms of shared understanding and meaning, and that the higher the number of related patterns forwarded through content and context the greater the resonance of shared understanding. Further, that the unconscious mind plays a significant role in embedding context and creating meaning.

This paper provides a shift in perception from the transmission of information to the sharing and re‐creation of knowledge in terms of shared understanding and meaning. It also presents a new model of context avenues impacting the sharing of knowledge.

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.

Schools in resource challenged communities require principal approaches that break patterns of low expectations and low student achievement. This study identifies Alabama’s “outlier” schools that have been consistently successful in attaining higher student outcomes than their neighboring schools despite their similar community conditions. Then, it describes the perspectives and practices of principals leading these outlier schools. The purpose of this paper is to discuss findings on principal leadership in five of Alabama's outlier schools.

In a sequential, explanatory mixed-methods design, the authors first use state administrative data to identify which Alabama schools had better results than their peers as evidenced by standardized testing between 2016 and 2020. Then, through semi-structured interviews, they examine the beliefs and approaches of five principals who are currently leading an outlier school. The frame of contextual leadership provides a deeper understanding of how these principals navigate successful schools in the midst of challenging community influences.

The evidence demonstrated that (1) community factors of low education, high unemployment, single-parent households and generational poverty are associated with considerably lower levels of student growth and achievement; (2) measured school and community factors do not explain student growth and achievement in these outlier schools; (3) outlier principals have a realistic view of their community’s challenges but focus on supporting students through a context sensitive, relational approach that emphasizes assets over limitations.

While research has attended to leadership in turnaround schools and effective schools, there is little literature on principals leading in positive outlier schools. This study contributes to the literature on school leadership in resource challenged contexts by identifying high performing, resource challenged schools and then showing the perspectives and practices of principals who lead in schools that have consistently achieved better than expected student outcomes. It extends the construct of “outlier leadership” in education and connects it to contextual leadership in schools.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

While the literature on multitier supply chain management traditionally assumes that first-tier suppliers belong to the visible proportion of the supply base, intermediaries might limit focal firms' visible horizon already at this stage. High power asymmetries promoting centrality and complexity in the supply network are seen as a particular root cause that limits the impact of governance mechanisms for sustainability. To map the space for governance mechanisms in a network-sensitive context more comprehensively, the study analyzes supply network characteristics from a power perspective.

This research is conceptual. To better understand power imbalances and mutual dependencies from network centrality and complexity, network configurations were constructed drawing on resource dependence theory. These configurations allow deducing the impact of (non-)mediated governance mechanisms for a sustainable development in the supply network. An agenda to stimulate future empirical and model-based research is accordingly presented.

The research shows that those networks with densely interconnected first-tier suppliers promote network centrality and complexity, leading to an inverted U-shape relationship between the focal firm's exertion of coercive power and the sustainability performance in the supply network. The findings allow a more comprehensive theoretical grounding for mapping governance approaches in a network-sensitive context and provide insights on how to avoid negative effects from power asymmetries.

The findings suggest the need for accompanying, indirect governance mechanisms already at the stage of first-tier suppliers based on non-mediated forms of power, such as referent power, also promoting disintermediation. Purchasing companies may also consider using digital platform technologies that foster disintermediation, such as blockchain technology.

By studying intermediaries from a power and network perspective, the conceptualization adds to the discussion on governance in multitier sustainable supply chain networks in various industries. Furthermore, it contributes to the increasing efforts of middle-range theorizing in logistics and supply chain management. The results partially challenge previous assumptions on the moderating role of specific network characteristics.