Online grocery shopping: The impact of shopping frequency on perceived risk

Online grocery shopping has enjoyed strong growth and it is predicted this channel will continue to grow exponentially in the coming years. While online shopping has attracted an abundance of research interest, examinations of online grocery shopping behaviour are only now emerging. Shopping online for groceries differs considerably from general online shopping due to the perishability and variability of the product, and frequency of the shopping activity. Two salient gaps underpin this research into online grocery shopping. This study responds to calls to investigate the online shoppers’ experience in the context of online purchasing frequency. Second, this study examines the mediating effect of perceived risk between trust and online repurchase intention of groceries. An online survey was employed to collect data from shoppers who were recruited from a multi-channel grocery e-retailer’s database. The online survey, comprising 16 reflective validated scale items, was sent to 555 frequent and infrequent online grocery shoppers. Results find that while customer satisfaction predicts trust for both infrequent and frequent online grocery shoppers, perceived risk fully mediates the effect of trust on repurchase intentions for infrequent online grocery shoppers. Furthermore path analysis reveals that the developed behavioural model is variant across both groups of shoppers. Theoretically, we provide a deeper understanding of the online customer experience, while gaining insight into two shopper segments identified as being important to grocery e-retailers. For managers, this study tests an online customer behavioural model with actual purchasing behaviour and identifies the continued presence of perceived risk in grocery e-retailing regardless of purchase frequency or experience.

Multi Pattern Dynamic Time Warping For Automatic Speech Recognition

We are addressing the problem of jointly using multiple noisy speech patterns for automatic speech recognition (ASR), given that they come from the same class. If the user utters a word K times, the ASR system should try to use the information content in all the K patterns of the word simultaneously and improve its speech recognition accuracy compared to that of the single pattern based speech recognition. T address this problem, recently we proposed a Multi Pattern Dynamic Time Warping (MPDTW) algorithm to align the K patterns by finding the least distortion path between them. A Constrained Multi Pattern Viterbi algorithm was used on this aligned path for isolated word recognition (IWR). In this paper, we explore the possibility of using only the MPDTW algorithm for IWR. We also study the properties of the MPDTW algorithm. We show that using only 2 noisy test patterns (10 percent burst noise at -5 dB SNR) reduces the noisy speech recognition error rate by 37.66 percent when compared to the single pattern recognition using the Dynamic Time Warping algorithm.

The ACA effect: Examining how current affairs programs shape victim understandings and responses to online fraud

In recent years, numerous current affairs stories on online fraud victimisation have been broadcast on Australian television. These stories typically feature highly organised, international ‘sting’ operations, in which alleged offenders are arrested and investigated by law enforcement. These portrayals of police responses influence the expectations that some online fraud victims have about how their individual cases will be handled by law enforcement. Based on interviews with 80 online fraud victims, this article argues that a narrow media portrayal of online fraud by television current affairs programs — termed the ‘ACA effect’ — informs victims’ understandings of online fraud and their responses to it. In particular, current affairs programs influence what victims of online fraud expect from police. The article further demonstrates that current affairs programs present themselves as de facto law enforcement agencies, to which victims who receive an unsatisfactory response from police might turn. Overall, the article highlights the importance of current affairs programs portraying a more realistic image of official responses to online fraud.

Odour emissions from anaerobic piggery ponds. 2: Improving estimates of emission rate through recognition of spatial variability

Odour emission rates were measured for seven different anaerobic ponds treating piggery wastes at six to nine discrete locations across the surface of each pond on each sampling occasion over a thirteen month period. Significant variability in emission rates were observed for each pond. Measurement of a number of water quality variables in pond liquor samples collected at the same time and from the same locations as the odour samples indicated that the composition of the pond liquor was also variable. The results indicated that spatial variability was a real phenomenon and could have a significant impact on odour assessment practices. Considerably more odour samples would be required to characterise pond emissions than currently recommended by most practitioners, or regulatory agencies.

Enhancing human action recognition with region proposals

Deep convolutional network models have dominated recent work in human action recognition as well as image classification. However, these methods are often unduly influenced by the image background, learning and exploiting the presence of cues in typical computer vision datasets. For unbiased robotics applications, the degree of variation and novelty in action backgrounds is far greater than in computer vision datasets. To address this challenge, we propose an “action region proposal” method that, informed by optical flow, extracts image regions likely to contain actions for input into the network both during training and testing. In a range of experiments, we demonstrate that manually segmenting the background is not enough; but through active action region proposals during training and testing, state-of-the-art or better performance can be achieved on individual spatial and temporal video components. Finally, we show by focusing attention through action region proposals, we can further improve upon the existing state-of-the-art in spatio-temporally fused action recognition performance.

The Google Online Marketing Challenge: A Transnational Comparison of Classroom Learning with Real Clients, Real Money, and Real Advertising Campaigns

In 2008, a collaborative partnership between Google and academia launched the Google Online Marketing Challenge (hereinafter Google Challenge), perhaps the world’s largest in-class competition for higher education students. In just two years, almost 20,000 students from 58 countries participated in the Google Challenge. The Challenge gives undergraduate and graduate students hands-on experience with the world’s fastest growing advertising mechanism, search engine advertising. Funded by Google, students develop an advertising campaign for a small to medium sized enterprise and manage the campaign over three consecutive weeks using the Google AdWords platform. This article explores the Challenge as an innovative pedagogical tool for marketing educators. Based on the experiences of three instructors in Australia, Canada and the United States, this case study discusses the opportunities and challenges of integrating this dynamic problem-based learning approach into the classroom.

Constellations: A participatory, online application for research collaboration in higher education interdisciplinary courses

The research establishes a model for online learning centering on the needs of integrative knowledge practices. Through the metaphor of Constellations, the practice-based research explores the complexities of working within interdisciplinary learning contexts and the potential of tools such as the Folksonomy learning platform for providing necessary conceptual support.

The con-stitutional re-cognition (s)cam-pain: The campaign for the hidden recognition of first nations peoples' racial inferiority

The constitutional recognition campaign has received party-wide support and its efforts have been promoted by Prime Minister Tony Abbott as being something that would ‘complete our Constitution.’ The broader rhetoric surrounding this campaign suggests that it will result in a just, albeit delayed, recognition of indigenous peoples in the Australian legal system. However, beneath the surface of this seemingly benevolent gesture, is a reaffirmation of the colonial subordination and erasure of the several hundred original nations’ peoples and ways of being.

PMU measurement based dynamic load modeling using SVC devices in online environment

Online dynamic load modeling has become possible with the availability of Static Voltage Compensator (SVC) and Phasor Measurement Unit (PMU) devices. The power of the load response to the small random bounded voltage fluctuations caused from SVC can be measured by PMU for modelling purposes. The aim of this paper is to illustrate the capability of identifying an aggregated load model from high voltage substation level in the online environment. The induction motor is used as the main test subject since it contributes the majority of the dynamic loads. A test system representing simple electromechanical generator model serving dynamic loads through the transmission network is used to verify the proposed method. Also, dynamic load with multiple induction motors are modeled to achieve a better realistic load representation.

Impact of online privacy concerns and brand reputation on consumer willingness to provide personal information

The aim of this research was to identify the role of brand reputation in encouraging consumer willingness to provide personal data online, for the benefits of personalisation. This study extends on Malhotra, Kim and Agarwal’s (2004) Internet Users Information Privacy Concerns Model, and uses the theoretical underpinning of Social Contract Theory to assess how brand reputation moderates the relationship between trusting beliefs and perceived value (Privacy Calculus framework) with willingness to give personal information. The research is highly relevant as most privacy research undertaken to date focuses on consumer related concerns. Very little research exists examining the role of brand reputation and online privacy. Practical implications of this research include gaining knowledge as to how to minimise online privacy concerns; improve brand reputation; and provide insight on how to reduce consumer resistance to the collection of personal information and encourage consumer opt-in.

SF06016 Low Chill Peaches Online

The aim of this project is to bring information on low chill stonefruit varieties to a user in a clear and friendly format to aid in that decision process. Low Chill Australia see this project as high priority for its members to be competitive by growing high quality, early season peach and nectarine fruit varieties. Data will be collated from grower surveys, breeder’s descriptions and literature, and entered into an Access Database and published on the web for stonefruit growers in tropical and sub-tropical regions across Australia. Links will be available from the Low Chill Australia and Summerfruit Australia websites.

Advanced practice: A survey of current perspectives of Australian pharmacists

Background An Advanced Pharmacy Practice Framework for Australia (the ‘APPF’) was published in October 2012. Further to the release of the APPF, the Advanced Pharmacy Practice Framework Steering Committee planned to develop an advanced practice recognition model for Australian pharmacists. Aim To gauge the perspectives of the pharmacy profession relating to advanced practice, via an online survey, in order to inform the design of the model. Method A survey was developed and administered to Australian pharmacists through SurveyMonkey . The survey content was based on findings from a review of national and international initiatives for recognition of advanced practice in pharmacy and other health disciplines, including medicine and nursing. Results The results of the survey showed that a high proportion of respondents considered they were already working at, or working towards achieving, an advanced level of practice. The responses relating to the assessment methods showed a clear preference for ‘submission of a professional portfolio’. A ‘written examination’ had a low level of support and in relation to an ‘oral examination by a panel’ there was a marked preference for a panel of multidisciplinary health professionals over a panel of pharmacists. Conclusion The survey outcomes will inform the development of an advanced pharmacy practice recognition model for Australian pharmacists, particularly in relation to the assessment methods. Survey outcomes also demonstrated that there is scope to further enhance the application of the APPF in the development and recognition of advanced practitioners, and to build greater awareness of the breadth of competencies encompassed by ‘advanced practice’.

Recognition and enforcement in cross-border insolvency law: A proposal for judicial gap-filling

This Article analyzes the recognition and enforcement of cross-border insolvency judgments from the United States, United Kingdom, and Australia to determine whether the UNCITRAL Model Law’s goal of modified universalism is currently being practiced, and subjects the Model Law to analysis through the lens of international relations theories to elaborate a way forward. We posit that courts could use the express language of the Model Law text to confer recognition and enforcement of foreign insolvency judgments. The adoption of our proposal will reduce costs, maximize recovery for creditors, and ensure predictability for all parties.

An Online Implementable Differential Evolution Tuned Optimal Guidance Law

This paper proposes a novel application of differential evolution to solve a difficult dynamic optimisation or optimal control problem. The miss distance in a missile-target engagement is minimised using differential evolution. The difficulty of solving it by existing conventional techniques in optimal control theory is caused by the nonlinearity of the dynamic constraint equation, inequality constraint on the control input and inequality constraint on another parameter that enters problem indirectly. The optimal control problem of finding the minimum miss distance has an analytical solution subject to several simplifying assumptions. In the approach proposed in this paper, the initial population is generated around the seed value given by this analytical solution. Thereafter, the algorithm progresses to an acceptable final solution within a few generations, satisfying the constraints at every iteration. Since this solution or the control input has to be obtained in real time to be of any use in practice, the feasibility of online implementation is also illustrated.