A typology of technological enablers of website service failure prevention

An increasing range of services are now offered via online applications and e-commerce websites. However, problems with online services still occur at times, even for the best service providers due to the technical failures, informational failures, or lack of required website functionalities. Also, the widespread and increasing implementation of web services means that service failures are both more likely to occur, and more likely to have serious consequences. In this paper we first develop a digital service value chain framework based on existing service delivery models adapted for digital services. We then review current literature on service failure prevention, and provide a typology of technolo- gies and approaches that can be used to prevent failures of different types (functional, informational, system), that can occur at different stages in the web service delivery. This makes a contribution to theory by relating specific technologies and technological approaches to the point in the value chain framework where they will have the maximum impact. Our typology can also be used to guide the planning, justification and design of robust, reliable web services.

Perception of prescription medicine sample packs among Australian professional, government, industry, and consumer organizations, based on automated textual analysis of one-on-one interviews

Background Prescription medicine samples provided by pharmaceutical companies are predominantly newer and more expensive products. The range of samples provided to practices may not represent the drugs that the doctors desire to have available. Few studies have used a qualitative design to explore the reasons behind sample use. Objective The aim of this study was to explore the opinions of a variety of Australian key informants about prescription medicine samples, using a qualitative methodology. Methods Twenty-three organizations involved in quality use of medicines in Australia were identified, based on the authors' previous knowledge. Each organization was invited to nominate 1 or 2 representatives to participate in semistructured interviews utilizing seeding questions. Each interview was recorded and transcribed verbatim. Leximancer v2.25 text analysis software (Leximancer Pty Ltd., Jindalee, Queensland, Australia) was used for textual analysis. The top 10 concepts from each analysis group were interrogated back to the original transcript text to determine the main emergent opinions. Results A total of 18 key interviewees representing 16 organizations participated. Samples, patient, doctor, and medicines were the major concepts among general opinions about samples. The concept drug became more frequent and the concept companies appeared when marketing issues were discussed. The Australian Pharmaceutical Benefits Scheme and cost were more prevalent in discussions about alternative sample distribution models, indicating interviewees were cognizant of budgetary implications. Key interviewee opinions added richness to the single-word concepts extracted by Leximancer. Conclusions Participants recognized that prescription medicine samples have an influence on quality use of medicines and play a role in the marketing of medicines. They also believed that alternative distribution systems for samples could provide benefits. The cost of a noncommercial system for distributing samples or starter packs was a concern. These data will be used to design further research investigating alternative models for distribution of samples.

Making smart decisions : key steps towards a typology for emergency communication during natural hazards

Governments, authorities, and organisations dedicate significant resources to encourage communities to prepare for and respond to natural hazards such as cyclones, earthquakes, floods, and bushfires. However, recent events, media attention, and ongoing academic research continue to highlight cases of non-compliance including swift water rescues. Individuals who fail to comply with instructions issued during natural hazards significantly impede the emergency response because they divert resources to compliance-enforcement and risk the lives of emergency service workers who may be required to assist them. An initial investigation of the field suggests several assumptions or practices that influence emergency management policy, communication strategy, and community behaviours during natural hazards: 1) that community members will comply with instructions issued by governments and agencies that represent the most authoritative voice, 2) that communication campaigns are shaped by intuition rather than evidence-based approaches (Wood et al., 2012), and 3) that emergency communication is linear and directional. This extended abstract represents the first stage of a collaborative research project that integrates industry and cross-disciplinary perspectives to provide evidence-based approaches for emergency and risk communication during the response and recovery phases of a natural hazard. Specifically, this abstract focuses on the approach taken and key elements that will form the development of a typology of compliance-gaining messages during the response phase of natural hazards, which will be the focus of the conference presentation.

Framing student evaluations of university learning and teaching : discursive strategies and textual outcomes

Evaluation in higher education is an evolving social practice, that is, it involves what people, institutions and broader systems do and say, how they do and say it, what they value, the effects of these practices and values, and how meanings are ascribed. The textual products (verbal, written, visual, gestural) that inform and are produced by, for and through evaluative practices are important as they promulgate particular kinds of meanings and values in specific contexts. This paper reports on an exploratory study that sought to investigate, using discourse analysis, the types of evaluative practices that were ascribed value, and the student responses that ensued, in different evaluative instruments. Findings indicate that when a reflective approach is taken to evaluation, students’ responses are more considered, they interrogate their own engagement in the learning context and they are more likely to demonstrate reconstructive thought. These findings have implications for reframing evaluation as reflective learning.

Using textual analysis with Concept Inventories to identify root causes of misconceptions

Engineers must have deep and accurate conceptual understanding of their field and Concept inventories (CIs) are one method of assessing conceptual understanding and providing formative feedback. Current CI tests use Multiple Choice Questions (MCQ) to identify misconceptions and have undergone reliability and validity testing to assess conceptual understanding. However, they do not readily provide the diagnostic information about students’ reasoning and therefore do not effectively point to specific actions that can be taken to improve student learning. We piloted the textual component of our diagnostic CI on electrical engineering students using items from the signals and systems CI. We then analysed the textual responses using automated lexical analysis software to test the effectiveness of these types of software and interviewed the students regarding their experience using the textual component. Results from the automated text analysis revealed that students held both incorrect and correct ideas for certain conceptual areas and provided indications of student misconceptions. User feedback also revealed that the inclusion of the textual component is helpful to students in assessing and reflecting on their own understanding.

Machine learning approaches to analysing textual injury surveillance data: A systematic review

Objective To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Design Systematic review. Data sources The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. Selection criteria For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. Methods The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Results Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. Conclusions The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field.

Defective co-creation: Developing a typology of consumer dysfunction in professional services

Purpose This study aims to explore the scope of consumers’ defective co-creation behaviour in professional service encounters. One of the founding premises of service-dominant logic (Vargo and Lusch, 2004, 2008) is that consumers co-create the value they derive from service encounters. In practice, however, dysfunctional consumer behaviour can obstruct value co-creation. Extant research has not yet investigated consumers’ defective co-creation behaviour in highly relational services, such as professional services, that are heavily reliant on co-creation. Design/methodology/approach To investigate defective co-creation in professional services, 164 critical incidents were collected from 38 health-care and financial service providers using the critical incident technique within semi-structured, in-depth interviews. Thematic coding was used to identify emergent themes and patterns of consumer behaviour. Findings Thematic coding resulted in a comprehensive typology of consumers’ defective co-creation behaviour that both confirms the prevalence of previously identified dysfunctional behaviours (e.g. verbal abuse and physical aggression) and identifies two new forms of consumer misbehaviour: underparticipation and overparticipation. Further, these behaviours can vary, escalate and co-occur during service encounters. Originality/value Both underparticipation and overparticipation are newly identified forms of defective co-creation that need to be examined within the broader framework of service-dominant logic (SDL).

Methods for Answer Extraction in Textual Question Answering

In this thesis we present and evaluate two pattern matching based methods for answer extraction in textual question answering systems. A textual question answering system is a system that seeks answers to natural language questions from unstructured text. Textual question answering systems are an important research problem because as the amount of natural language text in digital format grows all the time, the need for novel methods for pinpointing important knowledge from the vast textual databases becomes more and more urgent. We concentrate on developing methods for the automatic creation of answer extraction patterns. A new type of extraction pattern is developed also. The pattern matching based approach chosen is interesting because of its language and application independence. The answer extraction methods are developed in the framework of our own question answering system. Publicly available datasets in English are used as training and evaluation data for the methods. The techniques developed are based on the well known methods of sequence alignment and hierarchical clustering. The similarity metric used is based on edit distance. The main conclusions of the research are that answer extraction patterns consisting of the most important words of the question and of the following information extracted from the answer context: plain words, part-of-speech tags, punctuation marks and capitalization patterns, can be used in the answer extraction module of a question answering system. This type of patterns and the two new methods for generating answer extraction patterns provide average results when compared to those produced by other systems using the same dataset. However, most answer extraction methods in the question answering systems tested with the same dataset are both hand crafted and based on a system-specific and fine-grained question classification. The the new methods developed in this thesis require no manual creation of answer extraction patterns. As a source of knowledge, they require a dataset of sample questions and answers, as well as a set of text documents that contain answers to most of the questions. The question classification used in the training data is a standard one and provided already in the publicly available data.

Insights into students' conceptual understanding using textual analysis: A case study in signal processing

Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering concepts exist due to a lack of mental frameworks, or schemas, for these types of concepts or conceptual areas. This study incorporated an open textual response component in a multiple-choice concept inventory test to capture written explanations of students' selections. The study's goal was to identify, through text analysis of student responses, the types and categorizations of concepts in these explanations that had not been uncovered by the distractor selections. The analysis of the textual explanations of a subset of the discrete-time signals and systems concept inventory questions revealed that students have difficulty conceptually explaining several dimensions of signal processing. This contributed to their inability to provide a clear explanation of the underlying concepts, such as mathematical concepts. The methods used in this study evaluate students' understanding of signals and systems concepts through their ability to express understanding in written text. This may present a bias for students with strong written communication skills. This study presents a framework for extracting and identifying the types of concepts students use to express their reasoning when answering conceptual questions.

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

Using Relationships for Matching Textual Domain Models with Existing Code

We address the task of mapping a given textual domain model (e.g., an industry-standard reference model) for a given domain (e.g., ERP), with the source code of an independently developed application in the same domain. This has applications in improving the understandability of an existing application, migrating it to a more flexible architecture, or integrating it with other related applications. We use the vector-space model to abstractly represent domain model elements as well as source-code artifacts. The key novelty in our approach is to leverage the relationships between source-code artifacts in a principled way to improve the mapping process. We describe experiments wherein we apply our approach to the task of matching two real, open-source applications to corresponding industry-standard domain models. We demonstrate the overall usefulness of our approach, as well as the role of our propagation techniques in improving the precision and recall of the mapping task.

Understanding transitions in a rural Indian building typology in the context of well-being

Rural settlements in Karnataka in India predominantly use locally available resources to build their dwelling units. The houses are constructed either by the villagers themselves or by local masons skilled in traditional architecture. However, traditional houses and lifestyle are slowly giving way to modern concrete dwellings and a new lifestyle. To analyse this trend of transition to modern dwellings in rural settlements, a case study was conducted in three villages near the city of Bengaluru in Karnataka. The present article discusses this transition in the context of sustainable well-being of rural settlements.

Style and the “Idea” of the sophist after Plato : the impact of form typology on sophistic teaching and writing on interdisciplinary scholarly work

Resumen: Después de la primera sofística, los sofistas actuaron entre el resto de los pensadores del Mediterráneo como un grupo definido. Dado que hay muchos ejemplos que muestran que los sofistas ejercían sus prácticas y que también eran personas comprometidas en otras actividades, vamos a examinar aquí diversos casos de semejanzas y diferencias entre ellos y otros grupos de pensadores. Nuestras tres preguntas fundamentales son: qué, cómo y por qué los sofistas escribían y enseñaban. Intentaremos responder haciendo un análisis diacrónico de las principales formas y géneros de escritura que produjeron (qué). El cómo lo responderemos en su desenvolvimiento como una actividad comunicativa más allá de las fronteras de las disciplinas de la época. El por qué tendrá su respuesta al enfatizar la necesidad de la actividad de los sofistas en la socialización de la época y en la educación de la antigüedad. Al aseverar que el estilo era la idea de los sofistas, ponemos la noción de idea en Platón en el contexto de idea derivado de los sofistas contemporáneos a él y de los sofistas posteriores (segunda sofística) y centramos el foco en la función de visualidad expresada en su concepto de idea desde las obras sofísticas más tempranas en la época de Platón hasta las contribuciones posteriores.

La articulación textual en los "Progumnásmata" de Nicolao de Mura

[ES]En este trabajo se estudia el uso de los marcadores del discurso y del asíndeton como medios de articulación textual entre los diversos enunciados que constituyen los "Progumnásmata" de Nicolao. Este estudio permite observar si existen diferencias entre las dos partes que componen la edición de Felten y si el uso de partículas de Nicolao es diferente del que hacen los demás autores de "Progumnásmata".