Marketing and performance: a thematic study of firms in the UK and Ghana.

The issue being investigated in this thesis concerns the extent to which marketing practices impact upon business performance and how the competitive environment influences the market orientation-performance relationships in an industrialised nation and a developing economy. This thesis takes as its underlying theoretical framework, the marketing-performance paradigm of marketing strategy theory and practice and involves a thematic study of marketing practices, their relevance in different environmental scenarios and effects on a variety of performance measures. In order to determine the universal importance of marketing principles, the effects of various facets of marketing such as marketing culture, marketing effectiveness and market orientation on both customer-based and financial performance indicators, are investigated in the United Kingdom (UK) and Ghana. The contribution to knowledge stems from the systematic application of marketing principles to describe the behaviour of firms in a range of businesses and, on the basis of primary data, determine whether firms that engage in sound marketing practices, are characterised by relatively higher performance levels irrespective of the environment. This thesis contains eight empirical papers, one case study and one conceptual article on the U K and Ghana and the findings have been published/scheduled for publication in key internationally refereed journals in the management/ marketing fields. Within the U K context, issues relating to marketing culture, marketing effectiveness and their effects on various performance dimensions are explored. Moreover, the concept of market orientation, its impact upon measures of business effectiveness, efficiency and adaptability, and the extent to which environmental factors influence these relationships are examined. Sectors to which specific marketing constructs could be appropriately applied are selected for survey. These include marketing effectiveness in large organisations (over 500 employees), marketing culture in service firms, and market orientation in the small business (10 to 50 employees) and high technology (biotechnology) sectors. This approach facilitates a comprehensive testing of these different but related constructs in diverse contexts and provides useful conclusions on the efficacy of marketing principles in business practices. In the context of Ghana, the role of marketing is examined against the background of the International Monetary Fund's (IMF) structural adjustment policies (SAP). This is followed by a study of the effects of corporate culture on market orientation and a case study on performance of firms which have adapted successfully to the changes taking place in Ghana's liberalised economy through effective implementation of SAP-tailored marketing strategies. In addition, a comparison of the marketing activity-performance association among foreign and domestic firms is undertaken together with an investigation of the market orientation performance link and potential moderators of the relationship. Studying the role and effectiveness of marketing in these different scenarios provides invaluable insights into the relevance of marketing principles in a developing economy. Overall, this thematic approach facilitates a thorough exploration o f the significance of marketing practice in industrialised and developing economies and, more importantly, tackles the research question posed at the outset. Generally, the results indicate that in the UK, sound marketing practices exert a positive impact on performance while in Ghana, foreign firms' marketing practices are found to exert a greater effect on performance than those of domestic firms. Moreover, in the UK, a significant link between market orientation and performance emerges over a shorter period compared with a similar analysis in Ghana. Managerial implications o f the findings are subsequently highlighted and future research directions are identified and discussed

Interoperable services based on activity monitoring in ambient assisted living environments

Ambient Assisted Living (AAL) is considered as the main technological solution that will enable the aged and people in recovery to maintain their independence and a consequent high quality of life for a longer period of time than would otherwise be the case. This goal is achieved by monitoring human’s activities and deploying the appropriate collection of services to set environmental features and satisfy user preferences in a given context. However, both human monitoring and services deployment are particularly hard to accomplish due to the uncertainty and ambiguity characterising human actions, and heterogeneity of hardware devices composed in an AAL system. This research addresses both the aforementioned challenges by introducing 1) an innovative system, based on Self Organising Feature Map (SOFM), for automatically classifying the resting location of a moving object in an indoor environment and 2) a strategy able to generate context-aware based Fuzzy Markup Language (FML) services in order to maximize the users’ comfort and hardware interoperability level. The overall system runs on a distributed embedded platform with a specialised ceiling- mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels, to detect specific events such as potential falls and to deploy the right sequence of fuzzy services modelled through FML for supporting people in that particular context. Experimental results show less than 20% classification error in monitoring human activities and providing the right set of services, showing the robustness of our approach over others in literature with minimal power consumption

Potential groundwater pollution from improper oil and metal waste disposal in Suame, Ghana

Suame is an industrialized hub in Kumasi, Ghana, that is noted for vehicle repairs and servicing, sale of automobile spare parts, and metal fabrication. Some of these activities generate huge volumes of waste oil and metals that are often disposed off indiscriminately into the environment. These could pose a threat to the quality of groundwater in the area, especially if they continuously accumulate in the environment. This study, therefore, investigated the potential impact of the waste disposal on groundwater quality in the area. The methods employed involved mapping all the potential waste oil spillage sources and sampling the soils in such areas (at 0 – 30 and 30 – 60 cm depths) and groundwater supply points for laboratory analyses to determine the presence of the waste. In all, 36 samples (comprising 12 soil and 24 groundwater) were analysedfor the presence of heavy metals including Cd, Ni, Cu, Pb, Zn and Cr, which were used as traceelements for the presence of the waste in the samples. Computedgeo-accumulation indices from the results show the soils are moderately to heavily polluted with Cd and Pb whilst the groundwater, when compared to the WHO drinking water guidelines, is polluted with Pb and Ni. Althoughthe source of the high Pb content observed could be attributed to its transport directly from the activities in the area, the presence of high Ni makes it inconclusive since the Ni in the soil was within the concentration expected of the parent rock geochemistry. This notwithstanding, the study has indicated that groundwater in the area is not safe for human consumption unless the lead and nickel concentrations are reduced to acceptable standard for drinking.Keywords: Groundwater quality, pollution, waste disposal, Suame, Ghan

Space-time statistical analysis of malaria morbidity incidence cases in Ghana: A geostatistical modelling approach

Malaria is one of the most prevalent and devastating health problems worldwide. It is a highly endemic disease in Ghana, which poses a major challenge to both the public health and socio-economic development of the country. Major factors accounting for this situation include variability in environmental conditions and lack of prevention services coupled with host of other socio-economic factors. Ghana’s National Malaria Control Programme (NMCP) risk assessment measures have been largely based on household surveys which provided inadequate data for accurate prediction of new incidence cases coupled with frequent incomplete monthly case reports. These raise concerns about annual estimates on the disease burden and also pose serious threats to efficient public health planning including the country’s quest of reducing malaria morbidity and mortality cases by 75% by 2015. In this thesis, both geostatistical space-time models and time series seasonal autoregressive integrated moving average (SARIMA) predictive models have been studied and applied to the monthly malaria morbidity cases from both district and regional health facilities in Ghana. The study sought to explore the spatio-temporal distributions of the malaria morbidity incidence and to account for the potential influence of climate variability, with particular focus on producing monthly spatial maps, delimiting areas with high risk of morbidity. This was achieved by modelling the morbidity cases as incidence rates, being the number of new reported cases per 100,000 residents, which together with the climatic covariates were considered as realisations of random processes occurring in space and/or time. The SARIMA models indicated an upward trend of morbidity incidence in the regions with strong seasonal variation which can be explained primarily by the effects of rainfall, temperature and relative humidity in the month preceding incidence of the disease as well as the morbidity incidence in the previous months. The various spacetime ordinary kriging (STOK) models showed varied spatial and temporal distributions of the morbidity incidence rates, which have increased and expanded across the country over the years. The space-time semivariogram models characterising the spatio-temporal continuity of the incidence rates indicated that the occurrence of the malaria morbidity was spatially and temporally correlated within spatial and temporal ranges varying between 30 and 250 km and 6 and 100 months, respectively. The predicted incidence rates were found to be heterogeneous with highly elevated risk at locations near the borders with neighbouring countries in the north and west as well as the central parts towards the east. The spatial maps showed transition of high risk areas from the north-west to the north-east parts with climatic variables contributing to the variations in the number of morbidity cases across the country. The morbidity incidence estimates were found to be higher during the wet season when temperatures were relatively low whilst low incidence rates were observed in the warm weather period during the dry seasons. In conclusion, the study quantified the malaria morbidity burden in Ghana to produce evidence-based monthly morbidity maps, illustrating the risk patterns of the morbidity of the disease. Increased morbidity risk, delimiting the highest risk areas was also established. This statistical-based modelling approach is important as it allows shortterm prediction of the malaria morbidity incidence in specific regions and districts and also helps support efficient public health planning in the country

A computer vision approach to classification of birds in flight from video sequences

Bird populations are an important bio-indicator; so collecting reliable data is useful for ecologists helping conserve and manage fragile ecosystems. However, existing manual monitoring methods are labour-intensive, time-consuming, and error-prone. The aim of our work is to develop a reliable system, capable of automatically classifying individual bird species in flight from videos. This is challenging, but appropriate for use in the field, since there is often a requirement to identify in flight, rather than when stationary. We present our work in progress, which uses combined appearance and motion features to classify and present experimental results across seven species using Normal Bayes classifier with majority voting and achieving a classification rate of 86%

Human behavioural analysis with self-organizing map for ambient assisted living

This paper presents a system for automatically classifying the resting location of a moving object in an indoor environment. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a low-cost, low-power automated home-based surveillance system, capable of monitoring activity level of elders living alone independently. The proposed system runs on an embedded platform with a specialised ceiling-mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels and to detect specific events such as potential falls. First order motion information, including first order moving average smoothing, is generated from the 2D image coordinates (trajectories). A novel edge-based object detection algorithm capable of running at a reasonable speed on the embedded platform has been developed. The classification is dynamic and achieved in real-time. The dynamic classifier is achieved using a SOFM and a probabilistic model. Experimental results show less than 20% classification error, showing the robustness of our approach over others in literature with minimal power consumption. The head location of the subject is also estimated by a novel approach capable of running on any resource limited platform with power constraints

Si elegans: a computational model of C. elegans muscle response to light

It has long been the goal of computational neuroscientists to understand animal nervous systems, but their vast complexity has made it very difficult to fully understand even basic functions such as movement. The C. elegans nematode offers the opportunity to study a fully described connectome and link neural network to behaviour. In this paper a model of the responses of the body wall muscle in C. elegans to a random light stimulus is presented. An algorithm has been developed that tracks synapses in the nematode nervous system from the stimulus in the phototaxis sensory neurons to the muscles cells. A linear second order model was used to calculate the isometric force in each of the C. elegans body wall muscle cells. The isometric force calculated resembles that of previous investigations in muscle modelling

PLECO: New energy-aware programming languages and eco-systems for the Internet of Things

This paper outlines the aims of the Programming Language ECO-system (PLECO) to create new energy-aware programming languages and eco-systems for the Internet of Things (IoT). It builds upon the Lantern language and focuses on energy-awareness, security, resilience and communications for the large infrastructure underpinning the next generation of IoT. The paper outlines how IoT applications and deployments need to be developed in an energy-aware, secure and cost-effective manner using new secure, robust and energy-focused programming languages and the importance of taking such an approach

Improving the well-being of older people by reducing their energy consumption through energy-aware systems

Abstract-Fuel poverty is becoming a problem amongst the older community in the UK. We propose an assistive technology for reduced energy consumption in aid of active aging. We introduce how the well-being of older people within the community can be improved by reducing anxiety associated with fuel poverty. A recommender and behavioural change system will be introduced, which enables older people to improve their energy footprint through energy-aware systems. Using systems to help reduce fuel poverty will invariably improve their general well-being. Results show how this technology can be accepted and act as an enabler in improving the overall well-being of older people

Energy-aware systems for improving the well-being of older people by reducing their energy consumption

Fuel poverty is becoming a problem amongst the older community in the UK. To help reduce the anxiety that fuel poverty places on older members of the community, this paper will first address why such systems are necessary before introducing a system and various interfaces for engaging and promoting better energy usage. Key areas of the proposed prototype will be discussed which focuses on a recommender and behavioural change system which enables older people to improve their energy footprint through energy-aware systems. Using systems to help reduce fuel poverty will invariably improve their general well-being. Results show how this technology can be accepted and act as an enabler in improving the overall well-being of older people as well as other system considerations. In addition, a number of subsequent phases of the project will be detailed which will discuss a longer test duration, an analysis of the data harvested and future directions