The determinants of online loan applications from small businesses

Purpose – The purpose of this paper is to examine both the characteristics of the business customers and the types of venture which make use of online loan applications. Despite the growth in the use of technology in banking and the advent of online banking, little research has been conducted on the factors underlying online loan application behaviour amongst business banking customers. Design/methodology/approach – A multivariate analysis is conducted on a USA dataset to empirically test the hypotheses derived in this paper. The empirical evidence is drawn from the US Survey of Small Business Finances, which contains 3,561 sample ventures, representing 5.3 million small businesses in the USA. Findings – The paper finds that online loan behaviour is largely determined by the characteristics of the entrepreneur, rather than that of the venture. It is also found that factors that trust, evident in the length of the relationship between the applicants and their primary lender, is important. Moderating these effects is further evidence that suggests the number of lenders and distance between lenders and applicants has a marked effect on online loan behaviour. Originality/value – This paper identifies the factors determining small business online loan application behaviour. This is important because the nature of online loan behaviour is changing the existing relationships between banks and customers. Whilst online loan applications afford banks the opportunity to substantially reduce costs, the danger is that long term relationships with customers are harder to cement.

Incremental processing in head-final child language: online comprehension of relative clauses in Turkish-speaking children and adults

The present study investigates the parsing of pre-nominal relative clauses (RCs) in children for the first time with a realtime methodology that reveals moment-to-moment processing patterns as the sentence unfolds. A self-paced listening experiment with Turkish-speaking children (aged 5–8) and adults showed that both groups display a sign of processing cost both in subject and object RCs at different points through the flow of the utterance when integrating the cues that are uninformative (i.e., ambiguous in function) and that are structurally and probabilistically unexpected. Both groups show a processing facilitation as soon as the morphosyntactic dependencies are completed and parse the unbounded dependencies rapidly using the morphosyntactic cues rather than waiting for the clause-final filler. These findings show that five-year-old children show similar patterns to adults in processing the morphosyntactic cues incrementally and in forming expectations about the rest of the utterance on the basis of the probabilistic model of their language.

Online orthographies

The representation in online environments of non-Roman-based script languages has proved problematic. During the initial years of Computer-mediated Communication, the American Standard Code for Information Interchange character set only supported Roman-alphabeted languages. The solution for speakers of languages written in non-Roman scripts was to employ unconventional writing systems, in an effort to represent their native language in online discourse. The first aim of this chapter is to present the different ways that internet users choose to transliterate or even transcribe their native languages online, using Roman characters. With technological development, and consequently the availability of various writing scripts online, internet users now have the option to either use Roman characters or their native script. If the latter is chosen, internet users still seem to deviate from conventional ways of writing, in this case, however, with regards to spelling. The second aim, therefore, is to bring into light recent developments, by looking at the ways that internet users manipulate orthography, to achieve their communicative purposes.

Generic intertextuality in online social activism: the case of the It Gets Better project

The It Gets Better project has been held up as a model of successful social media activism. This article explores how narrators of It Gets Better videos make use of generic intertextuality, strategically combining the canonical narrative genres of the exemplum, the testimony, and the confession in a way that allows them to claim ‘textual authority’ and to make available multiple moral positions for themselves and their listeners. This strategy is further facilitated by the ambiguous participation frameworks associated with digital media, which make it possible for storytellers to tell different kinds of stories to different kinds of listeners at the same time, to simultaneously comfort the victims of anti-gay violence, confront its perpetrators, and elicit sympathy from ‘onlookers’. This analysis highlights the potential of new practices of online storytelling for social activism, and challenges notions that new media are contributing to the demise of common narrative traditions.

Do online hotel rating schemes influence booking behaviors?

Travelers’ hotel booking behaviors increasingly depend on peers' opinions and online ratings. This study investigates the effects of online hotel ratings on travelers' attitudes toward the hotel and booking intentions, using a 2 × 2 experimental research design. The results suggest that online rating lists are more useful and credible when published by well-known online travel communities (e.g., TripAdvisor). More favorable attitudes toward a hotel and higher booking intentions emerge when the hotel appears in best hotels lists. Finally, for the entries on best hotels lists, better attitudes and higher booking intentions result if the list is published on a well-known online travel community (Tripadvisor), whereas for entries on a worst hotel list, attitudes and booking intentions decrease even further if the list appears on TripAdvisor.

Raphael into the Baroque: drawing in the Carracci workshop

Discussion of the influence of Raphael's drawings on the practice of the workshop of Annibale Carracci in Rome.

Workshop: sensory objects

The Sensory Objects project was represented by co-researchers Judith Appiah and Tim Elson supported by Beverley Agard from the Tower Project, who co-presented with Nic and Kate at ENGAGE 2014 conference in Bristol.

Elderly learners and Massive Open Online Courses: a review

Background: Massive open online courses (MOOCs) have become commonplace in the e-learning landscape. Thousands of elderly learners are participating in courses offered by various institutions on a multitude of platforms in many different languages. However, there is very little research into understanding elderly learners in MOOCs. Objective: We aim to show that a considerable proportion of elderly learners are participating in MOOCs and that there is a lack of research in this area. We hope this assertion of the wide gap in research on elderly learners in MOOCs will pave the way for more research in this area. Methods: Pre-course survey data for 10 University of Reading courses on the FutureLearn platform were analyzed to show the level of participation of elderly learners in MOOCs. Two MOOC aggregator sites (Class Central and MOOC List) were consulted to gather data on MOOC offerings that include topics relating to aging. In parallel, a selected set of MOOC platform catalogues, along with a recently published review on health and medicine-related MOOCs, were searched to find courses relating to aging. A systematic literature search was then employed to identify research articles on elderly learners in MOOCs. Results: The 10 courses reviewed had a considerable proportion of elderly learners participating in them. For the over-66 age group, this varied from 0.5% (on the course “Managing people”) to 16.3% (on the course “Our changing climate”), while for the over-56 age group it ranged from 3.0% (on “A beginners guide to writing in English”) to 39.5% (on “Heart health”). Only six MOOCs were found to include topics related to aging: three were on the Coursera platform, two on the FutureLearn platform, and one on the Open2Study platform. Just three scholarly articles relating to MOOCs and elderly learners were retrieved from the literature search. Conclusions: This review presents evidence to suggest that elderly learners are already participating in MOOCs. Despite this, there has been very little research into their engagement with MOOCs. Similarly, there has been little research into exploiting the scope of MOOCs for delivering topics that would be of interest to elderly learners. We believe there is potential to use MOOCs as a way of tackling the issue of loneliness among older adults by engaging them as either resource personnel or learners.

Kinetics analysis and automated online screening of aminocarbonylation of aryl halides in flow

Temperature, pressure, gas stoichiometry, and residence time were varied to control the yield and product distribution of the palladium-catalyzed aminocarbonylation of aromatic bromides in both a silicon microreactor and a packed-bed tubular reactor. Automation of the system set points and product sampling enabled facile and repeatable reaction analysis with minimal operator supervision. It was observed that the reaction was divided into two temperature regimes. An automated system was used to screen steady-state conditions for offline analysis by gas chromatography to fit a reaction rate model. Additionally, a transient temperature ramp method utilizing online infrared analysis was used, leading to more rapid determination of the reaction activation energy of the lower temperature regimes. The entire reaction spanning both regimes was modeled in good agreement with the experimental data.

Towards expressive rule induction on IP network event streams

In order to gain insights into events and issues that may cause errors and outages in parts of IP networks, intelligent methods that capture and express causal relationships online (in real-time) are needed. Whereas generalised rule induction has been explored for non-streaming data applications, its application and adaptation on streaming data is mostly undeveloped or based on periodic and ad-hoc training with batch algorithms. Some association rule mining approaches for streaming data do exist, however, they can only express binary causal relationships. This paper presents the ongoing work on Online Generalised Rule Induction (OGRI) in order to create expressive and adaptive rule sets real-time that can be applied to a broad range of applications, including network telemetry data streams.

Reproducibility of the online Food4Me food-frequency questionnaire for estimating dietary intakes across Europe

Background: Accurate dietary assessment is key to understanding nutrition-related outcomes and is essential for estimating dietary change in nutrition-based interventions. Objective: The objective of this study was to assess the pan-European reproducibility of the Food4Me food-frequency questionnaire (FFQ) in assessing the habitual diet of adults. Methods: Participantsfromthe Food4Me study, a 6-mo,Internet-based, randomizedcontrolled trial of personalized nutrition conducted in the United Kingdom, Ireland, Spain, Netherlands, Germany, Greece, and Poland were included. Screening and baseline data (both collected before commencement of the intervention) were used in the present analyses, and participants were includedonly iftheycompleted FFQs at screeningand at baselinewithin a 1-mo timeframebeforethe commencement oftheintervention. Sociodemographic (e.g., sex andcountry) andlifestyle[e.g.,bodymass index(BMI,inkg/m2)and physical activity] characteristics were collected. Linear regression, correlation coefficients, concordance (percentage) in quartile classification, and Bland-Altman plots for daily intakes were used to assess reproducibility. Results: In total, 567 participants (59% female), with a mean 6 SD age of 38.7 6 13.4 y and BMI of 25.4 6 4.8, completed bothFFQswithin 1 mo(mean 6 SD: 19.26 6.2d).Exact plus adjacent classification oftotal energy intakeinparticipants was highest in Ireland (94%) and lowest in Poland (81%). Spearman correlation coefficients (r) in total energy intake between FFQs ranged from 0.50 for obese participants to 0.68 and 0.60 in normal-weight and overweight participants, respectively. Bland-Altman plots showed a mean difference between FFQs of 210 kcal/d, with the agreement deteriorating as energy intakes increased. There was little variation in reproducibility of total energy intakes between sex and age groups. Conclusions: The online Food4Me FFQ was shown to be reproducible across 7 European countries when administered within a 1-mo period to a large number of participants. The results support the utility of the online Food4Me FFQ as a reproducible tool across multiple European populations. This trial was registered at clinicaltrials.gov as NCT01530139.

A constrained recursive least squares algorithm for adaptive combination of multiple models

In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.