Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

Mobile apps usage and dynamic capabilities: A structural equation model of SMEs in Lagos, Nigeria.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Significant knowledge exists regarding the application of dynamic capability (DC) frameworks in large firms, but their impact on smaller organisations is yet to be fully researched. This study surveyed 1162 small and medium sized enterprises (SMEs) in Lagos in an effort to understand how SMEs in developing country contexts use mobile apps to enhance their businesses through DCs. Through the use of the covariance-based structural equation modelling (SEM) technique, the study explored the fitness of a conceptual formative model for SMEs. The model assembled 7 latent variables namely: mobile app usage, adaptive capability, absorptive capability, innovative capability, opportunity sensing ability, opportunity shaping ability and opportunity seizing ability. Subsequently, 15 hypotheses aimed at testing the relationships between the latent variables were developed and tested. The findings revealed that mobile app usage increases the adaptive, absorptive and innovative capabilities of SMEs. Absorptive capabilities help SMEs to maximise opportunities, while innovative capabilities negatively influence SMEs’ tendency to maximise opportunities. The results failed to establish a direct relationship between mobile app usage and SMEs’ ability to maximise opportunities. The research outcomes indicate that SMEs in Lagos respond to opportunities innovatively but they seldom exhibit innovation in order to create opportunities. The heterogeneous nature of SMEs complicates any clear-cut narrative as to how SMEs in Lagos should employ mobile apps to create and maximise opportunities. However, mobile apps could induce innovation and, as such, impact significantly when developed and applied to the contextual requirements of SMEs. The research revealed the untapped potential of SMEs’ mobile app usage in Lagos

Diagnosis and the management constituency of small-scale fisheries

Diagnosis and adaptive management can help improve the ability of small-scale fisheries (SSF) in the developing world to better cope with and adapt to both external drivers and internal sources of uncertainty. This paper presents a framework for diagnosis and adaptive management and discusses ways of implementing the first two phases of learning: diagnosis and mobilising an appropriate management constituency. The discussion addresses key issues and suggests suitable approaches and tools as well as numerous sources of further information. Diagnosis of a SSF defines the system to be managed, outlines the scope of the management problem in terms of threats and opportunities, and aims to construct realistic and desired future projections for the fishery. These steps can clarify objectives and lead to development of indicators necessary for adaptive management. Before management, however, it is important to mobilize a management constituency to enact change. Ways of identifying stakeholders and understanding both enabling and obstructive interactions and management structures are outlined. These preliminary learning phases for adaptive SSF management are expected to work best if legitimised by collaborative discussion among fishery stakeholders drawing on multiple knowledge systems and participatory approaches to assessment. (PDF contains 33 pages

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalised clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking.Comment: 16 pages, 5 figure

Developing a panarchy model of landscape conservation and management of alpine-mountain grassland in Northern Italy.

This paper explores methods of applying resilience theory to a case study of natural resource management and the cultural landscape of upland and alpine pasture in northern Italy. We identify that the close interaction between alpine pastures and its managers offers a strong fit with the concept of a social-ecological system that maintains the cultural landscape. We first considered a descriptive approach looking historically at socio-economic development in the study area. We explored whether this can be related to resilience phenomena such as regime shifts, thresholds and/or regime stability through adaptive processes. However, we found it difficult at this overarching level to conceptually combine natural and social capital of alpine pastures and their managers in any quantitative way. We also interpreted our data through considering economic, social and ecological information as acting within separate but interacting domains. This led us to construct conceptual models of adaptive cycles to describe the alpine mountain grassland ecosystem of our study site and to conclude that a panarchy model can offer a powerful metaphor for its ecological dynamics. This has practical implications both for the management of Natura 2000 interest and the maintenance of the cultural landscape in which this Alpine interest occurs. We suggest that Resilience theory through its dynamic approach of interacting scales of adaptive cycles offers useful insights into the resource management (of valued cultural and natural attributes) but that care is needed in distinguishing between descriptive metaphor and predictive model or "real" system.natural resource management, natural and social capital