Lexical inferencing is considered a listening strategy that is commonly employed by advanced EFL (English as a Foreign Language) listeners and a factor that contributes to successful listening comprehension. However, investigations of the factors that influence inferencing success in listening as well as how much each factor contributes to success are scant, as more studies have been conducted exploring lexical inferencing in reading. In addition, even though idiomatic expressions such as smell a rat, jump the gun, and go cold turkey are ubiquitous in the English language, especially in oral communication, and they are considered crucial in both first language (L1) and second language (L2) acquisition, little is known about the effectiveness of inferencing strategies where idiomatic expressions are concerned.Three goals motivated the current study. The first goal was to investigate whether inferencing is an effective strategy in the case where the target item is an idiomatic expression. The second goal was to investigate how four person-level factors, familiarity, listening proficiency, listening vocabulary size and working memory, two sentence-level factors, lexical density and sentence length, and two lexical-level factors, L1–L2 congruency and semantic transparency, influence the inferencing success of English idiomatic expressions in listening. The third goal, related to the second goal, was to determine which of the two lexical component factors, L1–L2 congruency and semantic transparency, is more important to inferencing success. A mixed methods design, the explanatory sequential design (Creswell & Plano Clark, 2018), was employed in this study. Quantitative data were collected from 89 EFL Japanese university students using a Listening Vocabulary Levels Test, a Listening Span Test, and an Idiom Inferencing Elicitation Task. The collected data were examined using mixed-effects logistic regression. Twelve participants were invited to participate in follow-up interviews based on their response patterns on the Idiom Inferencing Elicitation Task. The quantitative results indicated that familiarity, listening comprehension skills, working memory, and L1–L2 congruency were significant factors influencing inferencing success and the qualitative results supported these findings. In addition, the qualitative analyses suggested that depth of vocabulary is another potentially important factor. Furthermore, listening comprehension moderated the L1–L2 congruency effect. The finding that semantic transparency is not an influential factor in successful inferencing of unfamiliar idiomatic expressions provides evidence that the semantic transparency of known idiomatic expressions formed after learners acquire the meaning of the expression is a different construct from the perceived semantic transparency of unfamiliar idiomatic expressions. In addition, even though the sentence-level factors were not statistically significant in successful idiom inferencing in this study, further studies are required in order to see if this result holds true when the characteristics of the listening tasks differ from those of the task used in this study. It is hoped that the findings provide insights into how to help Japanese university EFL learners improve their listening skills, especially in tasks that include unfamiliar idiomatic expressions. / Teaching & Learning

No / There is interest in deriving case-mix adjusted standardised mortality ratios so that comparisons between healthcare providers, such as hospitals, can be undertaken in the controversial belief that variability in standardised mortality ratios reflects quality of care. Typically standardised mortality ratios are derived using a fixed effects logistic regression model, without a hospital term in the model. This fails to account for the hierarchical structure of the data - patients nested within hospitals - and so a hierarchical logistic regression model is more appropriate. However, four methods have been advocated for deriving standardised mortality ratios from a hierarchical logistic regression model, but their agreement is not known and neither do we know which is to be preferred. We found significant differences between the four types of standardised mortality ratios because they reflect a range of underlying conceptual issues. The most subtle issue is the distinction between asking how an average patient fares in different hospitals versus how patients at a given hospital fare at an average hospital. Since the answers to these questions are not the same and since the choice between these two approaches is not obvious, the extent to which profiling hospitals on mortality can be undertaken safely and reliably, without resolving these methodological issues, remains questionable.

This thesis examines how regional-level factors combined with firm-level factors influence innovation in an emerging economy – India. Past literature has shown that differences in both country contexts and firm-level factors influence innovation. The bulk of this literature tended to focus on developed economies. The handful of studies that have considered contextual differences have studied these at the country-level or within regional blocks such as regions of Europe or Africa. There is a paucity of research, which investigates how differences in state-level factors within a single country combined with firm-level factors influence innovation within firms. Therefore, it is an open question whether the findings derived from developed economies and country-level studies apply equally to emerging economies, particularly at the state level within a single country. Thus, there is a gap in the literature regarding our understanding of the impact of combined state- and firm-level factors on innovation within a single country. This thesis aims to contribute to a better understanding of how state and firm-level factors drive innovation in India, an emerging economy. India is selected because it is a fast-growing emerging economy that is increasingly being integrated into the globalized world economy and thus understanding how these factors influence innovation in an emerging economy would complement the literature that focuses on developed countries. Moreover, India is a huge country with substantial varieties in resources, capabilities, institutions (both formal and informal institutions) as well as ethnic, religious, and cultural varieties. Contextually, these state-level differences are quite different from regions in the developed world where institutional differences tend to be relatively consistent (less varieties). Thus, the insights generated from this study of the Indian context complement prior research by identifying the state and firm factors that combine to drive firm-level innovation. This study also extends the innovation literature by focussing on state-level differences within a single emerging economy, for which there is limited research. The findings could also have practical managerial and policy implications. From a policy perspective, policymakers in India can get a deeper understanding of the relevant factors that influence firm-level innovation so that they can direct policy and resources to promote innovation in their respective states. From a managerial perspective, managers can also get a better understanding of strategies and investments they should take to enhance innovation within their firms. This study is based on data gathered from various sources including the World Bank Enterprise Survey and several sources from within India (Indiastat.com, NCAER State Investment Potential Index, India Innovation Index). The World Bank Enterprise Survey provides firm-level data while state-level data were obtained from the other reputable sources in India. The data were analyzed using logistic regression and multi-level modeling, given that firms are nested within states, thus, we can simultaneously model the micro and macro levels to assess the relevance of the regional context. The results of this study show that regional factors such as regulatory quality, corruption, and rule of law barriers negatively influence innovation in firms that invest in internal R&D to promote innovation. The results also show that regions that devote a higher proportion of their gross domestic product to innovation achieve higher levels of innovation. Further, regions that have higher levels of human capital stock (more skilled workers) and export technology tend to be more innovative. At the firm level, investments in both internal and external R&D and those that have highly experienced managers are more innovative than their peers. These results suggest that governments and policymakers can increase innovative activities of firms by providing a highly skilled labor force, invest heavily in R&D, reduce corruption, regulatory quality, and the rule of law barriers. For firm-level managers, this study indicates that higher levels of managerial capability and greater investments in both internal and external R&D can enhance the technical and innovative capabilities (absorptive capacity) of their firms. This may result in a competitive advantage through increased innovation.