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Proceedings of the 2018 International Conference on Multidisciplinary Research



This book is the proceedings of the 2018 International Conference on Multidisciplinary Research.
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This paper, based upon a field research project commissioned by the Panos Institute SouthernAfrica, investigates the communicative efficacy of the radio listening clubs project implementedby the Institute in Malawi and Zambia. The investigation takes the form of a ‘second-orderinterpretation’ of the key findings of the field research. The findings are analysed in terms of theparticipatory communication model of development communication. The paper argues that theclubs live up to some of the ideal-typical attributes of participatory communication. This is evidentin the following areas: (i) a propensity for social mobilisation; (ii) acquisition of skills and knowledge;(iii) communally induced motivation to listen to the radio; (iv) the possibility of interpersonal influencewithin groups; (v) the benefit of being ‘organised’ structures; (vi) the ‘massive’ reach of the clubs;and (vii) the dialogic interchanges between the rural-based groups and the urban-based policymaking elites.
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Trip attraction rates are major inputs needed in traffic impact assessment of commercial developments. The objectives of this study are to develop models to estimate trip attraction rates for person trips and vehicle trips and to develop parking standards for three-wheelers, motorcycles, cars/vans for supermarkets in the Kandy area. The number of vehicles entering and leaving the supermarkets and the number of people visiting the supermarkets at every fifteen minute interval during peak hours will be surveyed using a smart-phone based Android application. Multiple linear regression analysis will be used to analyse data. Central limit theorem will be used to develop parking standards. For each category a sophisticated model for supermarket designers and simplified model for local authorities will be developed. The results show that the wine shop area is the governing factor of the trip attraction rate and parking standards in the Kandy area.
Organizations collect a vast amount of data of different types, from various sources, and through different channels. Primarily, these data are used by these organizations to facilitate their core business processes. However, today we witness a growing tendency to use these data for other purposes than that they are collected for. To this end, the data from one information system are combined with those of other information systems. Subsequently, the combined data are analyzed with advanced data analytics tools. Although there is a strong and practical need to apply such findings of data analytics to improve, among others, organizations’ (social) services, it is often not straightforward how to apply these findings in practice. This is due to many challenges arising from legal, ethical, and data quality concerns. In this chapter, we discuss the main reasons that hamper the application of data analytics findings, particularly pertaining to data collection processes and data analysis processes (like data mining and statistics). These reasons include inadequate transformations of statistical truths to individual cases, chances to fall into the trap of system realities, and required efforts to deal with the evolving semantics of data over time. The latter is due to the fact that our (social) environment is subjected to constant changes. We discuss two strategies to harvest data analytics findings in a responsible way. By means of some real-life examples in the field of social services we illustrate the applications of the strategies in practice. Furthermore, we argue that the findings from data-driven analytics may augment real-world ecosystems if they are applied with caution and responsibly.