The nature of engineering change in a complex product development cycle

The complex dynamics of modern business mean companies are constantly exposed to rapid and radical change. The way by which a company copes with change, can act as an insight into its propensity for sustainable profitability and hence predicted longevity. In complex product development cycles, engineering change must be managed as efficiently and effectively as possible. This paper presents a case study of one hundred engineering changes, taken over a sixty seven day period, of a complex product development cycle, during the detailed design phase of the project. It establishes the specific engineering change process utilised as a reactive process, which takes a mean of 126 days to complete its impact analysis phase and compliments this with a review of change stimuli and effects. It was found that the stimuli behind change are frequently not understood, with 68.4% reasons being classified as 'other'. The most effected entities were found to be the bill of materials, baseline and structural changes respectively; however it was found that each specific stimulus had a unique effect profile, which differed from the cumulative effect profile for all change stimuli

Determining citizens’ opinions about stories in the news media: analysing Google, Facebook and Twitter

We describe a method whereby a governmental policy maker can discover citizens’ reaction to news stories. This is particularly relevant in the political world, where governments’ policy statements are reported by the news media and discussed by citizens. The work here addresses two main questions: whereabouts are citizens discussing a news story, and what are they saying? Our strategy to answer the first question is to find news articles pertaining to the policy statements, then perform internet searches for references to the news articles’ headlines and URLs. We have created a software tool that schedules repeating Google searches for the news articles and collects the results in a database, enabling the user to aggregate and analyse them to produce ranked tables of sites that reference the news articles. Using data mining techniques we can analyse data so that resultant ranking reflects an overall aggregate score, taking into account multiple datasets, and this shows the most relevant places on the internet where the story is discussed. To answer the second question, we introduce the WeGov toolbox as a tool for analysing citizens’ comments and behaviour pertaining to news stories. We first use the tool for identifying social network discussions, using different strategies for Facebook and Twitter. We apply different analysis components to analyse the data to distil the essence of the social network users’ comments, to determine influential users and identify important comments

Vote buying revisited: implications for receipt-freeness

In this paper, we analyse the concept of vote buying based on examples that try to stretch the meaning of the concept. Which ex- amples can still be called vote buying, and which cannot? We propose several dimensions that are relevant to qualifying an action as vote buy- ing or not. As a means of protection against vote buying and coercion, the concept of receipt-freeness has been proposed. We argue that, in or- der to protect against a larger set of vote buying activities, the concept of receipt-freeness should be interpreted probabilistically. We propose a general definition of probabilistic receipt-freeness by adapting existing definitions of probabilistic anonymity to voting