Online Customer Experience : What is the Experience and how is it Difference for Frequent and Infrequent Purchasers, Age Cohorts and Gender Groups?

What do we know? • Customer Experience is increasingly becoming the new standard for differentiation in both offline and online retailing, and offers a sustainable competitive advantage. o The economic value of a company’s offering has been observed to increase when the customer has a fulfilling shopping experience (Pine & Gilmore, 1998) o Crafting engaging and customer experience is a known method of generating loyalty, advocacy and word of mouth (Tynan & McKechnie, 2009). o A good experience can entice consumers to shop for longer and spend more (Kim, 2001). • The customer’s experience is made up of diverse elements occurring before, during and after the purchase itself. (Discussed further on page 5). It is cumulative over time and can be influenced by touch points across multiple channels. What remains unclear? • How do Coles customers respond to the elements of online customer experience? • How does the online customer experience differ for frequent and infrequent purchasers? • Do differences between genders and age cohorts for online customer experience exist?

Privacy concerns and purchase of travel product online

The travel and tourism industry has come to rely heavily on information and communication technologies to facilitate relations with consumers. Compiling consumer data profiles has become easier and it is widely thought that consumers place great importance on how that data is handled by firms. Lack of trust may cause consumers to have privacy concerns and may, in turn, have an adverse impact on consumers’ willingness to purchase online. Three specific aspects of privacy that have received attention from researchers are unauthorized use of secondary data, invasion of privacy, and errors. A survey study was undertaken to examine the effects of these factors on both prior purchase of travel products via the Internet and future purchase probability. Surprisingly, no significant relationships were found to indicate that such privacy concerns affect online purchase behavior within the travel industry. Implications for managers are discussed.

Towards pose-robust face recognition on video

This thesis investigates face recognition in video under the presence of large pose variations. It proposes a solution that performs simultaneous detection of facial landmarks and head poses across large pose variations, employs discriminative modelling of feature distributions of faces with varying poses, and applies fusion of multiple classifiers to pose-mismatch recognition. Experiments on several benchmark datasets have demonstrated that improved performance is achieved using the proposed solution.

Multiscale features and information extraction of online strain for long-span bridges

The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 10^5, 10^2 and 10^0 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10^-2, 10^-1 and 10^0 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.

Aspect-based opinion extraction from customer reviews

Text is the main method of communicating information in the digital age. Messages, blogs, news articles, reviews, and opinionated information abounds on the Internet. People commonly purchase products online and post their opinions about purchased items. This feedback is displayed publicly to assist others with their purchasing decisions, creating the need for a mechanism with which to extract and summarize useful information for enhancing the decision-making process. Our contribution is to improve the accuracy of extraction by combining different techniques from three major areas, named Data Mining, Natural Language Processing techniques and Ontologies. The proposed framework sequentially mines product’s aspects and users’ opinions, groups representative aspects by similarity, and generates an output summary. This paper focuses on the task of extracting product aspects and users’ opinions by extracting all possible aspects and opinions from reviews using natural language, ontology, and frequent “tag” sets. The proposed framework, when compared with an existing baseline model, yielded promising results.

Challenges in improving chronic disease survivorship outcomes using tele-health and self-managed online solutions

The advances in modern information and communication (ICT) technology continue to address the challenges and improve` health outcomes for the survivors of chronic disease such as prostate cancer. The management of survivorship is increasingly becoming an important need for the survivors to manage their chronic conditions. The technology interventions such as tele-health as well as self-managed technology applications have shown a potential to improve survivorship outcomes. However, the application of these tools should be supported by strong health economics evidence. This work discusses the challenges of technology led survivorship care models and presents an integrated approach to address these challenges.

Case Study 4: Education Doctoral Student - "An Exploratory Study of Online Social Networking within a Doctorate of Education Program"

Introduction The professional doctorate is specifically designed for professionals investigating real-world problems and relevant issues for a profession, industry, and/or the community. The focus is scholarly research into professional practices. The research programme bridges academia and the professions, and offers doctoral candidates the opportunity to investigate issues relevant to their own practices and to apply these understandings to their professional contexts. The study on which this article is based sought to track the scholarly skill development of a cohort of professional doctoral students who commenced the course in January 2008 at an Australian university. Because they hold positions of responsibility and are time-poor, many doctoral students have difficulty transitioning from professional practitioner to researcher and scholar. The struggle many experience is in the development of a theoretical or conceptual standpoint for argumentation (Lesham, 2007; Weese et al., 1999). It was thought that the use of a scaffolded learning environment that drew upon a blended learning approach incorporating face to face intensive blocks and collaborative knowledge-building tools such as wikis would provide a data source for understanding the development of scholarly skills. Wikis, weblogs and similar social networking software have the potential to support communities to share, learn, create and collaborate. The development of a wiki page by each candidate in the 2008 cohort was encouraged to provide the participants and the teaching team members with textual indicators of progress. Learning tasks were scaffolded with the expectation that the candidates would complete these tasks via the wikis. The expectation was that cohort members would comment on each other’s work, together with the supervisor and/or teaching team member who was allocated to each candidate. The supervisor is responsible for supervising the candidate’s work through to submission of the thesis for examination and the teaching team member provides support to both the supervisor and the candidate through to confirmation. This paper reports on the learning journey of a cohort of doctoral students during the first seven months of their professional doctoral programme to determine if there had been any qualitative shifts in understandings, expectations and perceptions regarding their developing knowledge and skills. The paper is grounded in the literature pertaining to doctoral studies and examines the structure of the professional doctoral programme. Following this is a discussion of the qualitative study that helped to unearth key themes regarding the participants’ learning journey.

Online estimation of Allan variance parameters

A new online method is presented for estimation of the angular randomwalk and rate randomwalk coefficients of inertial measurement unit gyros and accelerometers. In the online method, a state-space model is proposed, and recursive parameter estimators are proposed for quantities previously measured from offline data techniques such as the Allan variance method. The Allan variance method has large offline computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of approximately 100 calculations per data sample.

Submission to the Australian Government’s Online Copyright Infringement Discussion Paper

Now is not the time to increase the strength of copyright law. Copyright law is facing a crisis of legitimacy: consumers increasingly appear to doubt its moral weight. To a large extent, this can be traced to the fact that Australian consumers do not believe they are being treated fairly by (predominantly US-based) copyright producers and distributors. Compared to their overseas peers, Australian consumers pay much more for access to books, films, television, and computer games, and are often subjected to long delays before material is available in Australia. Our research shows that this perceived unfairness increases the willingness of Australian consumers to seek out alternative distribution channels. Put simply, the failure of content distributors to meet consumer demand in Australia is a leading factor in copyright infringement. This submission argues that the best strategy to reduce copyright infringement in Australia, at the present time, is for distributors to focus on providing timely, affordable, convenient and fair access to copyright goods. Until this is done, the prevalence of copyright infringement in Australia should be seen as essentially a market problem, rather than a legal one. The Australian Government, meanwhile, should address the recommendations of the IT Pricing Report as a matter a priority. As a first step, the Government should urgently consider repealing the IP exception to competition law in s 51(3), as recommended by the Ergas committee, the IT Pricing report, and the ALRC. This change alone may go a long way to enhancing the efficiency of the copyright market in Australia.

Creative Commons Australia and Organization for Transformative Works submission to the Australian Government’s online copyright infringement discussion paper

This submission focuses on the adverse effects that the Government’s proposals are likely to have on the legitimate use of copyright works. Copyright exists to support the production of new expression. Because new expression always builds on existing culture, any extension of copyright protection necessarily also increases the costs of creative expression. As a threshold matter, we do not believe that these further increases to the force of copyright law are justified. In recent years, the balance at the heart of copyright law has tipped too far in the direction of established producers and distributors, and now imposes unnecessary costs on ordinary creators. The available evidence does not support a further increase in the penalties and enforcement mechanisms available under copyright law.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

Text recognition approaches for indoor robotics : a comparison

This paper evaluates the performance of different text recognition techniques for a mobile robot in an indoor (university campus) environment. We compared four different methods: our own approach using existing text detection methods (Minimally Stable Extremal Regions detector and Stroke Width Transform) combined with a convolutional neural network, two modes of the open source program Tesseract, and the experimental mobile app Google Goggles. The results show that a convolutional neural network combined with the Stroke Width Transform gives the best performance in correctly matched text on images with single characters whereas Google Goggles gives the best performance on images with multiple words. The dataset used for this work is released as well.

Machine learning for activity recognition : hip versus wrist data

Problem addressed Wrist-worn accelerometers are associated with greater compliance. However, validated algorithms for predicting activity type from wrist-worn accelerometer data are lacking. This study compared the activity recognition rates of an activity classifier trained on acceleration signal collected on the wrist and hip. Methodology 52 children and adolescents (mean age 13.7 +/- 3.1 year) completed 12 activity trials that were categorized into 7 activity classes: lying down, sitting, standing, walking, running, basketball, and dancing. During each trial, participants wore an ActiGraph GT3X+ tri-axial accelerometer on the right hip and the non-dominant wrist. Features were extracted from 10-s windows and inputted into a regularized logistic regression model using R (Glmnet + L1). Results Classification accuracy for the hip and wrist was 91.0% +/- 3.1% and 88.4% +/- 3.0%, respectively. The hip model exhibited excellent classification accuracy for sitting (91.3%), standing (95.8%), walking (95.8%), and running (96.8%); acceptable classification accuracy for lying down (88.3%) and basketball (81.9%); and modest accuracy for dance (64.1%). The wrist model exhibited excellent classification accuracy for sitting (93.0%), standing (91.7%), and walking (95.8%); acceptable classification accuracy for basketball (86.0%); and modest accuracy for running (78.8%), lying down (74.6%) and dance (69.4%). Potential Impact Both the hip and wrist algorithms achieved acceptable classification accuracy, allowing researchers to use either placement for activity recognition.

CoWs, Google and online possibilities : creating digital posters to enhance student engagement

A new Bachelor of Science (BSc) course was introduced at Queensland University of Technology (QUT) in 2013 and focused on inquiry-based, collaborative and active learning. Two of the first year units required that students carry out a group poster assessment task. This poster provides a preliminary evaluation from an academic staff perspective of the assessment approach used, whereby students created digital posters to utilise the affordances of new learning spaces. The digital posters approach was first introduced to a group of academic staff from the Science and Engineering Faculty (SEF) in 2012 during a professional development program to explicitly develop skills and shared understandings of teaching in collaborative learning spaces (Steel & Andrews, 2012). Considerations were given to the pedagogical requirements of a poster assessment task, the affordances of the learning space and an identification of possible benefits of using Google Sites to create digital posters. Positive feedback from this group (as highlighted in the quotes shown) and subsequent approval from unit coordinators for two of the new first year BSc units meant that the approach was adopted for Semester 1, 2013 with approximately 360 students in each unit.