1,720,973 research outputs found
Cultural Intelligence and Social Capital: Investigating expatriates’ working relationships in Malaysia
Full text linkThis thesis examines the effect of Cultural Intelligence on expatriates’ relationship quality with their culturally diverse host national work colleagues in Malaysia from a social capital perspective. Malaysia presents a highly culturally diverse host country which has increasingly become attractive for global organizations over the last few decades. A high-quality relationship with host national employees allows expatriates to access valuable resources which facilitate their adjustment and performance. Such
resources represent expatriates’ social capital. However, it is still unknown why some expatriates are more successful in developing higher level of social capital with Host
Country Nationals than others.
Prior research shows that expatriates with higher level of Cultural Intelligence often feel more comfortable to interact with Host Country Nationals (HCNs). Therefore, Cultural Intelligence would be expected to have a positive impact on expatriates’ relationship quality with HCNs and, hence, improving social capital. The relationship between
Cultural Intelligence and social capital is, however, under researched especially with little focus given to the effect of metacognitive, cognitive, motivational, and behavioural
dimensions of Cultural Intelligence.
Following mixed methods approach, this thesis uses quantitative survey and Multiple Linear Regression to identify general relationships between the four dimensions of Cultural Intelligence and expatriates’ social capital. Additionally, qualitative semi-structured interviews and Thematic Analysis are used to explore how and why Cultural
Intelligence may influence expatriates’ development of social capital.
The results suggest that expatriates’ metacognitive, motivational, and behavioural Cultural Intelligence have a positive effect on expatriates’ development of social capital. However, the effect of cognitive Cultural Intelligence is very limited. The qualitative findings provide insights on the challenges in expatriates’ work relationship with HCNs due to their cultural differences, and how the different dimensions of Cultural Intelligence
may help to solve them, thereby contributing to expatriates’ development of social capital. One important finding concerns the mediating role of recognition and appraisal respect in facilitating expatriates’ development of social capital with their host national colleagues.
This thesis contributes to the expatriate literature by being the first to examine how and why expatriates’ metacognitive, cognitive, motivational, and behavioural Cultural Intelligence may influence the development of social capital with their host national work colleagues. The findings of this thesis also have practical implications concerning the selection of future expatriates and the design of more effective training programs to enhance expatriates’ probability of success by receiving more useful resources from HCNs
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Regulatory risk disclosure in the banking industry: a scoring model approach
Full text linkBanks communicate their regulatory risk exposures through disclosure reports to market participants. These reports are based on the Basel III Pillar 3 guidelines, implemented in the European Union in form of the Capital Requirements Directive and Regulation (CRD IV/CRR).
Agency theory views such disclosures as one viable option to reduce the information asymmetry between the banks’ managers and investors. Also, high-quality risk disclosures can strengthen the competitive position of banks through lower cost of capital and higher stock liquidity. It is therefore in the interest of banks to prepare high-quality disclosures and evaluate current disclosure practices.
This thesis proposes a scoring model that measures the quality of bank regulatory risk disclosures and thereby supports banks and their stakeholders in their decision-making process on risk communication. The model builds on a two-dimensional framework including 1) a risk dimension comprising credit risk, market risk, operational risk, other risks including liquidity risk, and risk management in general; and 2) a quality dimension covering the criteria readability, comprehensiveness, meaningfulness, time comparability, and sector comparability. The quality criteria are operationalised and applied to the risk categories to facilitate the calculation of composite disclosure scores for regulatory risk disclosure reports of a sample of thirty large European-headquartered banks for the period 2016 to 2018.
Prior research shows that disclosure quality depends on both qualitative and quantitative elements. Therefore, a multi-methods approach is applied in this thesis to build the scoring model based on a pragmatic research philosophy. In the research design, qualitative elements are captured with semantic content analysis, while quantitative elements are explored using factor analysis.
The calculation of composite disclosure scores results in an average composite disclosure score of 3.86 (out of a maximum of 5) with a spread of about 20% to both sides. The analysis finds that reading difficulty across individual disclosure reports is generally very high, disclosure quantity varies substantially, banks are reluctant to provide forward-looking information, and only few information on time and sector comparability is included. This, therefore, makes it difficult for different stakeholders to benefit from bank disclosure reports and leaves ample space for banks to improve on their risk communication.
The main academic contribution of this thesis is the development of a scoring model that captures the quality of regulatory risk disclosures in the EU banking industry. Such a practice-based model does not yet exist and has long been called for in prior literature. This research also introduces a comprehensive word-based approach that is an adequate proxy for measuring disclosure quality. Finally, the thesis adds to the understanding of how the term “information content” is interpreted differently across EU banks in the context of agency theory.
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For the professional contribution, the proposed scoring model enables banks to analyse their current disclosure practices and points them to areas for improvements. Supervisory authorities and analyst houses also benefit from the scoring model through a more efficient and effective analysis of disclosure reports. Finally, consultancies and software firms can benefit from such a model to expand their offerings on business intelligence.
JEL classification: M48 (Government Policy and Regulation)
Keywords: Banking risk reporting; Regulation; Disclosure; Basel III Pillar 3; CRD IV/CRR; Quality scoring model
Investigating antecedents of service innovation in the bank industry: evidence from Jordan
Full text linkIn today's highly competitive marketplaces, innovation is generally seen as one of the major
factors influencing a firm's long-term success. Service innovation represents an additional
means by which firms can improve their market performance and efficiency, which in turn may
contribute to competitive advantage in today’s business environment.
Market orientation, technology orientation and learning orientation are suggested collectively
to be key drivers influencing service innovation and firm performance. However, very little
research has been done so far to examine in one single model the impact of these three strategic
orientations on service innovation and firm performance. Additionally, while many studies
have examined transformational leadership as having a moderating impact between different
variables, there is a lack of studies that have examined the impact of transformational
leadership as a moderator between market orientation, technology orientation and learning
orientation on service innovation towards improving firm performance in banking industry.
Therefore, this study aims to examine the impact of the three orientations on service innovation
and firm performance and the moderating impact of transformational leadership between the
three orientations and service innovation.
After identifying and reviewing the relevant literature in depth, the contingency theory was
used to develop the conceptual model and associated hypotheses. This study employed a
quantitative research design where 199 questionnaires were collected from bank managers in
the first-second-third lines operating in Jordanian banks, to obtain necessary data to test the
hypotheses developed for the study. Hierarchical regression analysis and Structural Equation
Modelling through SPSS and AMOS were performed to analyse the research data.
The main findings indicate that market, technology and learning orientations have a direct and
positive impact on service innovation. Moreover, transformational leadership is found to
moderate the relationship between market and learning orientation and service innovation.
However, transformational leadership evidently has no moderating impact on the relationship
between technology orientation and service innovation. Finally, service innovation is found to
have a positive and direct impact on banks’ financial and non-financial performance.
The current study contributes to the current literature at different levels. First, at the theoretical
level, this study develops a conceptual framework which crosses different streams of literature,
mainly market orientation, technology orientation, learning orientation, transformational
leadership, service innovation and firm performance. Unlike previous studies, the model: (i)
examines the direct impact of market, technology and learning on service innovation and offers
a view of how service innovation can improve firm performance (financially and nonfinancially);
(ii) examines the moderating impact of transformational leadership. Previous
research has focused primarily on one or a few dimensions of strategic orientations. None of
the previous studies, including those conducted in banks, combined the three orientations and
transformational leadership in a single study to understand the effects on service innovation
and, consequently, firm performance. Second, at the empirical level, this study is conducted in
the Jordanian banking industry. As such this study is one of the very few studies to use
empirical data from the study context to examine and report how different orientations and
transformational leadership can impact service innovation and in turn improve firm
performance. No previous literature has been found that has studied this orientation in the
banking industry in the Middle East and in particular in Jordan; moreover, no studies have been
found that integrated these kinds of orientations into one single model to improve firm
performance
The impacts of diversification strategy on the financial performance of insurers
Full text linkThe thesis examines the impacts of diversification strategy on the financial performance of firms in the insurance industry. It investigates the impacts of different dimensions of the diversification strategy, including product, geographic, staff, and technological diversification, on insurers' financial performance while considering some essential control variables such as type, size, age, and ownership structure of the companies. The research measures financial performance with the return on equity (ROE) and the return on assets (ROA).
The thesis employs the mixed methods research methodology using qualitative and quantitative data collected from Iranian insurance companies, while the data is analysed quantitatively. Two separate studies are conducted to evaluate the impacts of different dimensions of diversification strategy on firms' financial performance. Specifically, the first study focuses on the impact of technological diversification strategy on a firm's financial performance. This study uses the primary data associated with technological diversification through a questionnaire survey with managers from 31 Iranian insurance companies, as the data for technological diversification is not available as secondary data. The data associated with firms' financial performance is collected from reports annually published by the Central Insurance of Iran. Employing the Structural Equation Modelling method enabled by Smart PLS 3 software to analyse the primary data, the study reports mixed effects of technological diversification on the financial performance of Iranian insurers. The second study focuses on investigating the impacts of product, geographic and staff diversification strategies on the financial performance of Iranian insurers. This study employs secondary data collected from the annual reports of the Central Insurance of Iran (from 2011 to 2020). Using econometric techniques for panel data (e.g., fixed effects) enabled by EViews 10 software, the study finds some
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significant impacts of different dimensions of diversification strategy on the financial performance of Iranian insurers.
This thesis is novel in several ways. First, it uses new measurement methods for different dimensions of the diversification strategy, specifically for product diversification and technological diversification. Second, this is the first study in diversification-firms' financial performance literature that combines all four dimensions in a single study. Third, this research benefits from different theoretical perspectives to synthesise the literature and interpret the findings. Therefore, the thesis is not bound or biased to any single theoretical lens. Finally, it provides robust and comprehensive findings for both researchers and practitioners in the insurance industry
Home-bias in online fundraising: an analysis of international reward-based crowdfunding
Full text linkHome Bias is the recognized tendency of individuals to choose geographically proximate interaction partners. In business finance, Home Bias is to the detriment of both investors and entrepreneurs because it promotes an uneven distribution of capital and contributes to the Global Finance Gap. The aim of this thesis is to examine the existence of Home Bias in the emerging financing channel of reward-based crowdfunding. Crowdfunding, in general, is different from traditional financing because it shifts the entire fundraising process to a digital space on the internet. Moreover, it introduces new community-based trust mechanisms and eliminates some of the distance-related costs. The focus of this thesis lies on reward-based crowdfunding, which is currently the most popular, unrestricted and, therefore, most international form of crowdfunding.
To assess whether international reward-based crowdfunding is prone to Home Bias, this thesis employs a Negative Binomial regression model that examines the relationship between the count of crowdfunding project backers and their respective distance to entrepreneurs. The model builds on an aggregate data sample of 1,118,654 project-specific country-to-country investment observations (from 211,695 projects) that occurred on Kickstarter platform between 2009 and 2020, making it the largest and most up to date crowdfunding study.
Although large sample or “Big Data” models provide many advantages (e.g., higher representativeness), and have been commonly used in the crowdfunding literature, they however introduce some caveats that have been mostly ignored by previous research. One main issue that might distort results in Big Data models is that they are capable to identify marginally small patterns in the data that, although statistically significant in terms of p-values, might have little relevance in practice. Therefore, this thesis goes beyond the traditional analysis of statistical significance and devotes great attention to the assessment of different marginal effect sizes to identify the practical relevance of findings.
The thesis also investigates the effect of additional variables that may have potential effect on the count of backers namely GDP per capita of backers and entrepreneurs, project category, third-party endorsements, herding behaviour and Covid-19 pandemic.
The results suggest that although geographical distance appears to have a statistically significant negative influence on the count of backers, its practical effect is very small. This indicates that Home Bias has a comparably small relevance in international reward-based crowdfunding and that entrepreneurs should not overestimate its impact when planning their crowdfunding campaigns. Moreover, neither individual wealth of backers nor entrepreneurs, project category or global economic crises seem to affect the success of crowdfunding campaigns in a practically relevant manner. However, herding behaviour and third-party endorsements do seem to have a statistically and practically relevant influence on the count of backers and, therefore, should be considered in the planning of crowdfunding campaigns.
The overall findings of this thesis suggest that some of the prior research in crowdfunding might have overestimated the practical relevance of certain influencing factors (e.g., geographical distance and individual wealth), perhaps by focusing too much on statistical significance while ignoring the capability of Big Data models to identify marginally small and practically irrelevant patterns in the data
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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