Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Cultural effect on electronic consumer behaviour: the effect of uncertainty avoidance on online trust for the Egyptian Internet users

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The ubiquitous nature of e-commerce demands an innovative conceptualization of consumer behaviour that responds to various cultural preferences. Culture has been identified as an underlying determinant of consumer behaviour, and this extends to ecommerce. This research investigates this phenomenon for the Egyptian consumer. This research designed a plausible, integrated framework for investigating the target phenomenon, especially for un-explored cultures. To help to identify salient components of the phenomenon, a three-study exploratory phase, that included: interviews, a survey, and card sorting sessions, was undertaken. The exploratory results highlighted the roles of trust, uncertainty avoidance, Internet store familiarity, and reputation as the main salient factors affecting the perception of the targeted group toward e-commerce. The research hypotheses were then developed based on the exploratory results. Finally, a model testing phase to empirically assess the research hypotheses through a laboratory experiential survey with 370 Egyptian Internet users was undertaken. The experiential survey results support the significant role of the Internet store’s perceived familiarity and reputation as the main antecedents of online trust. The relationship between trust and its two antecedents are found to be culturally sensitive; the high uncertainty avoidance of the consumer is found to be associated with a stronger effect of the store’s reputation on trust, and a stronger effect of store’s familiarity on trust. The research also highlights the significant effect of trust on the attitude towards and the willingness to buy from an e-commerce site. This research, by providing an understanding of the cultural drivers of e-commerce, contributes to building a theory of consumer’s cultural trust within an Internet store context. The research reports on the development of an integrated cultural trust model that highlights recommendations for expanding the adoption of e-commerce. The systematic research framework, introduced by this research, can be a robust starting point for further related work in this area

Can Upward Brand Extensions be an Opportunity for Marketing Managers During the Covid-19 Pandemic and Beyond?

Early COVID-19 research has guided current managerial practice by introducing more products across different product categories as consumers tried to avoid perceived health risks from food shortages, i.e. horizontal brand extensions. For example, Leon, a fast-food restaurant in the UK, introduced a new range of ready meal products. However, when the food supply stabilised, availability may no longer be a concern for consumers. Instead, job losses could be a driver of higher perceived financial risks. Meanwhile, it remains unknown whether the perceived health or financial risks play a more significant role on consumers’ consumptions. Our preliminary survey shows perceived health risks outperform perceived financial risks to positively influence purchase intention during COVID-19. We suggest such a result indicates an opportunity for marketers to consider introducing premium priced products, i.e. upward brand extensions. The risk-as�feelings and signalling theories were used to explain consumer choice under risk may adopt affective heuristic processing, using minimal cognitive efforts to evaluate products. Based on this, consumers are likely to be affected by the salient high-quality and reliable product cue of upward extension signalled by its premium price level, which may attract consumers to purchase when they have high perceived health risks associated with COVID-19. Addressing this, a series of experimental studies confirm that upward brand extensions (versus normal new product introductions) can positively moderate the positive effect between perceived health risks associated with COVID-19 and purchase intention. Such an effect can be mediated by affective heuristic information processing. The results contribute to emergent COVID-19 literature and managerial practice during the pandemic but could also inform post-pandemic thinking around vertical brand extensions

Blogs as Infrastructure for Scholarly Communication.

This project systematically analyzes digital humanities blogs as an infrastructure for scholarly communication. This exploratory research maps the discourses of a scholarly community to understand the infrastructural dynamics of blogs and the Open Web. The text contents of 106,804 individual blog posts from a corpus of 396 blogs were analyzed using a mix of computational and qualitative methods. Analysis uses an experimental methodology (trace ethnography) combined with unsupervised machine learning (topic modeling), to perform an interpretive analysis at scale. Methodological findings show topic modeling can be integrated with qualitative and interpretive analysis. Special attention must be paid to data fitness, or the shape and re-shaping practices involved with preparing data for machine learning algorithms. Quantitative analysis of computationally generated topics indicates that while the community writes about diverse subject matter, individual scholars focus their attention on only a couple of topics. Four categories of informal scholarly communication emerged from the qualitative analysis: quasi-academic, para-academic, meta-academic, and extra-academic. The quasi and para-academic categories represent discourse with scholarly value within the digital humanities community, but do not necessarily have an obvious path into formal publication and preservation. A conceptual model, the (in)visible college, is introduced for situating scholarly communication on blogs and the Open Web. An (in)visible college is a kind of scholarly communication that is informal, yet visible at scale. This combination of factors opens up a new space for the study of scholarly communities and communication. While (in)invisible colleges are programmatically observable, care must be taken with any effort to count and measure knowledge work in these spaces. This is the first systematic, data driven analysis of the digital humanities and lays the groundwork for subsequent social studies of digital humanities.PhDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111592/1/mcburton_1.pd

Study on open science: The general state of the play in Open Science principles and practices at European life sciences institutes

Nowadays, open science is a hot topic on all levels and also is one of the priorities of the European Research Area. Components that are commonly associated with open science are open access, open data, open methodology, open source, open peer review, open science policies and citizen science. Open science may a great potential to connect and influence the practices of researchers, funding institutions and the public. In this paper, we evaluate the level of openness based on public surveys at four European life sciences institute

Understanding people through the aggregation of their digital footprints

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 160-172).Every day, millions of people encounter strangers online. We read their medical advice, buy their products, and ask them out on dates. Yet our views of them are very limited; we see individual communication acts rather than the person(s) as a whole. This thesis contends that socially-focused machine learning and visualization of archived digital footprints can improve the capacity of social media to help form impressions of online strangers. Four original designs are presented that each examine the social fabric of a different existing online world. The designs address unique perspectives on the problem of and opportunities offered by online impression formation. The first work, Is Britney Spears Span?, examines a way of prototyping strangers on first contact by modeling their past behaviors across a social network. Landscape of Words identifies cultural and topical trends in large online publics. Personas is a data portrait that characterizes individuals by collating heterogenous textual artifacts. The final design, Defuse, navigates and visualizes virtual crowds using metrics grounded in sociology. A reflection on these experimental endeavors is also presented, including a formalization of the problem and considerations for future research. A meta-critique by a panel of domain experts completes the discussion.by Aaron Robert Zinman.Ph.D

Cultural effect on electronic consumer behaviour

The ubiquitous nature of e-commerce demands an innovative conceptualization of consumer behaviour that responds to various cultural preferences. Culture has been identified as an underlying determinant of consumer behaviour, and this extends to ecommerce. This research investigates this phenomenon for the Egyptian consumer. This research designed a plausible, integrated framework for investigating the target phenomenon, especially for un-explored cultures. To help to identify salient components of the phenomenon, a three-study exploratory phase, that included: interviews, a survey, and card sorting sessions, was undertaken. The exploratory results highlighted the roles of trust, uncertainty avoidance, Internet store familiarity, and reputation as the main salient factors affecting the perception of the targeted group toward e-commerce. The research hypotheses were then developed based on the exploratory results. Finally, a model testing phase to empirically assess the research hypotheses through a laboratory experiential survey with 370 Egyptian Internet users was undertaken. The experiential survey results support the significant role of the Internet store’s perceived familiarity and reputation as the main antecedents of online trust. The relationship between trust and its two antecedents are found to be culturally sensitive; the high uncertainty avoidance of the consumer is found to be associated with a stronger effect of the store’s reputation on trust, and a stronger effect of store’s familiarity on trust. The research also highlights the significant effect of trust on the attitude towards and the willingness to buy from an e-commerce site. This research, by providing an understanding of the cultural drivers of e-commerce, contributes to building a theory of consumer’s cultural trust within an Internet store context. The research reports on the development of an integrated cultural trust model that highlights recommendations for expanding the adoption of e-commerce. The systematic research framework, introduced by this research, can be a robust starting point for further related work in this area.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Learning Representations of Social Media Users

User representations are routinely used in recommendation systems by platform developers, targeted advertisements by marketers, and by public policy researchers to gauge public opinion across demographic groups. Computer scientists consider the problem of inferring user representations more abstractly; how does one extract a stable user representation - effective for many downstream tasks - from a medium as noisy and complicated as social media? The quality of a user representation is ultimately task-dependent (e.g. does it improve classifier performance, make more accurate recommendations in a recommendation system) but there are proxies that are less sensitive to the specific task. Is the representation predictive of latent properties such as a person's demographic features, socioeconomic class, or mental health state? Is it predictive of the user's future behavior? In this thesis, we begin by showing how user representations can be learned from multiple types of user behavior on social media. We apply several extensions of generalized canonical correlation analysis to learn these representations and evaluate them at three tasks: predicting future hashtag mentions, friending behavior, and demographic features. We then show how user features can be employed as distant supervision to improve topic model fit. Finally, we show how user features can be integrated into and improve existing classifiers in the multitask learning framework. We treat user representations - ground truth gender and mental health features - as auxiliary tasks to improve mental health state prediction. We also use distributed user representations learned in the first chapter to improve tweet-level stance classifiers, showing that distant user information can inform classification tasks at the granularity of a single message.Comment: PhD thesi

Investigating Early Childhood Educators’ Experiences In Teaching Phonological Awareness: A Case Study

Literacy instruction, or teaching educators how to teach reading, is increasingly important as the effects of illiteracy impact everyone from the individual level to the societal level. The cost of illiteracy to the global economy is estimated at $1.2 trillion U.S. dollars (World Literacy Foundation, 2015). Improving literacy for all becomes a social justice concern as access to literacy opens avenues to further education and to improved physical and mental wellbeing. Over the past forty years, neurocognitive and behavioral science has demonstrated how the human brain learns to read. However, educator training programs and professional development have not kept pace with emergent science, leaving educators ill prepared to teach reading. The problem addressed in this study was the impact of professional development about the science of reading, specifically improving educators’ own understanding phonological awareness, beliefs and perceptions of reading instruction. Three research questions guided this study. Educators were asked to describe their professional development experiences in the areas of literacy and phonological awareness; to describe any changes they made to their pedagogical practices as a result of their learning; to use their observational skills and to indicate if they observed students responding to the changes the educators made to their instructional practices. Five themes emerged from the data analysis, including a) Change, b) Collaboration, c) Confusion, d) Confidence, and e) Communication. Findings from the case study described educators’ recommendations on how to improve professional development and instructional processes. Recommendations included clear consistent communication, differentiated and tiered professional development, and time for knowledge building, collaboration and application. Providing educators with the knowledge to fill in the gaps in their understanding, the time to process, reflect, and apply the research and strategies as well as the purpose and rationale behind the professional development will aid them in making meaningful pedagogical change