Marketing to change public opinion on climate change : a case study

Corporate advertisers spend far greater budgets than any social marketing campaign and have great potential to change public opinion on the urgent need for action on climate change. However “green-washing” has become a widespread practice by companies that wish to appear to be socially responsible without a genuine commitment and consumers can be very cynical about green marketing campaigns. Can companies be climate change advocates and still satisfy shareholders? This paper offers a case study on an Australian insurance company that argues it can make money from doing the right thing.

Critical opinion : the Docklands Precinct

Every one and their dog has done a Docklands design studio at university if they were educated in Melbourne. And all designers have an opinion on the idea of Docklands and its potential in the future, but few, apart from the Docklands authority themselves, have a handle on what's going on there now and what constitutes its qualities.

State-of-the-Art Review on Opinion Mining from Online Customers’ Feedback

Dealing with the ever-growing information overload in the Internet, Recommender Systems are widely used online to suggest potential customers item they may like or find useful. Collaborative Filtering is the most popular techniques for Recommender Systems which collects opinions from customers in the form of ratings on items, services or service providers. In addition to the customer rating about a service provider, there is also a good number of online customer feedback information available over the Internet as customer reviews, comments, newsgroups post, discussion forums or blogs which is collectively called user generated contents. This information can be used to generate the public reputation of the service providers’. To do this, data mining techniques, specially recently emerged opinion mining could be a useful tool. In this paper we present a state of the art review of Opinion Mining from online customer feedback. We critically evaluate the existing work and expose cutting edge area of interest in opinion mining. We also classify the approaches taken by different researchers into several categories and sub-categories. Each of those steps is analyzed with their strength and limitations in this paper.

Inducing shades of meaning by matrix methods : a first step towards thematic analysis of opinion

This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.

Employee engagement : the development of a three dimensional model of engagement; and an exploration of its relationship with affective leader behaviours

This study was designed to examine affective leader behaviours, and their impact on cognitive, affective and behavioural engagement. Researchers (e.g., Cropanzano & Mitchell, 2005; Moorman et al., 1998) have called for more research to be directed toward modelling and testing sets of relationships which better approximate the complexity associated with contemporary organisational experience. This research has attempted to do this by clarifying and defining the construct of engagement, and then by examining how each of the engagement dimensions are impacted by affective leader behaviours. Specifically, a model was tested that identifies leader behaviour antecedents of cognitive, affective and behavioural engagement. Data was collected from five public-sector organisations. Structural equation modelling was used to identify the relationships between the engagement dimensions and leader behaviours. The results suggested that affective leader behaviours had a substantial direct impact on cognitive engagement, which in turn influenced affective engagement, which then influenced intent to stay and extra-role performance. The results indicated a directional process for engagement, but particularly highlighted the significant impact of affective leader behaviours as an antecedent to engagement. In general terms, the findings will provide a platform from which to develop a robust measure of engagement, and will be helpful to human resource practitioners interested in understanding the directional process of engagement and the importance of affective leadership as an antecedent to engagement.

How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabiesPetrogale penicillata

1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.

The leader in you : developing your leadership potential

Leadership research demonstrates that there are serious shortcomings in the quality and competence of leaders in our organizations. The recent global financial crisis has also reminded us that, if our society and economies are to move forward sustainability, we must have the right kind of leaders and the right kind of leadership throughout our organizations. "The Leader in You: Developing Your Leadership Potential" has been framed to be useful to all individuals who are currently in leadership roles, from chief executives to frontline managers, and for those who wish to step up to a leadership role. Organizations can also utilize this book to assist their leaders to increase their leadership potential or to complement leadership development programs. If you want to search for and develop leadership qualities in yourself, then this book is for you. If you want to set a higher standard in your organization and you think leadership is a serious matter in the lives of other people, then this book is for you. In the process of self-reflection, "The Leader in You: Developing Your Leadership Potential" will enable you to develop an individual leadership profile and an individual skills profile, culminating in the development of a plan for leadership improvement. This book aims to couple these outcomes with exposure to some practical skills that leaders need to lead in every day environments. The first four chapters allow the reader to develop an understanding of the concepts that underpin leadership performance, and to undertake exercises to develop a comprehensive understanding of their values, behaviors and personality. That is, to understand who they are and why they behave the way they do. An individual leadership profile is developed at the end of these chapters. Then, the remaining chapters look at issues that leaders will face in contemporary society, and at the skills required to address them in everyday environments. An individual skills profile is developed at the end of these chapters culminating in the development of a plan for leadership improvement.