Customer Information, Big Data Analytics, Innovation Competence and Sustainable Development:A Cross-cultural Study on Financial Institutions

This study investigates the value creation process in the application of customer information, big data analytics, and innovation in financial institutions in different cultural contexts. A grounded theory approach is adopted, and themes are developed from primary interview data. 30 interviews were conducted with managers in 15 financial institutions in the UK, China, Bangladesh, Jordan, and Nigeria. A grounded theory model is developed to link the factors that influence the adoption of customer information, bid data analytics and the value creation process through innovation. This study found that the development of big data analytics technology, increased market competition and various cultural characteristics and customer needs to provide conditions for the case institutions to improve innovation competence through cultural, organisational, process, technology, product and service innovations. the case institutions improve innovation competence through cultural, organisational, process, technology, product and service innovations. Financial institutions reduce risk increase return, and improve customer satisfaction, accessibility, responsible finance, and sustainable development. An adaptation, innovation and sustainable development theory and some implications are proposed for academics and practitioners

Customer Information, Big Data Analytics, Innovation Competence and Sustainable Development:A Cross-cultural Study on Financial Institutions

This study investigates the value creation process in the application of customer information, big data analytics, and innovation in financial institutions in different cultural contexts. A grounded theory approach is adopted, and themes are developed from primary interview data. 30 interviews were conducted with managers in 15 financial institutions in the UK, China, Bangladesh, Jordan, and Nigeria. A grounded theory model is developed to link the factors that influence the adoption of customer information, bid data analytics and the value creation process through innovation. This study found that the development of big data analytics technology, increased market competition and various cultural characteristics and customer needs to provide conditions for the case institutions to improve innovation competence through cultural, organisational, process, technology, product and service innovations. the case institutions improve innovation competence through cultural, organisational, process, technology, product and service innovations. Financial institutions reduce risk increase return, and improve customer satisfaction, accessibility, responsible finance, and sustainable development. An adaptation, innovation and sustainable development theory and some implications are proposed for academics and practitioners

A Novel Architecture of Multi-GPU Computing Card

The data transmission between GPUS in the existing multi_GPU computing card is often through PCIE which is in relative low speed, so the PCIE has become bottleneck of Overall performance. A novel architecture of multi_GPU computing card have been proposed in this paper: A multi-channel memory which have multiple interfaces is added, including one common interface shared by different GPUs, which is connected with a FPGA arbitration circuit and several other interfaces connected with dedicated GPUs frame buffer independently, and this multi-channel memory is called "global shared memory". The result of a simulation of accelerating computer tomography algebraic reconstruction on multi-GPU demonstrates effectiveness of this approach. DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.3038

The Mediated Effect of Bounded Rationality on the Relationship between National Cultural Psychology and Irrationality in Financial Decision Making of Entrepreneurs: – An empirical study on the evidence from Ethnic Minority Business (EMBs) Entrepreneurs in West Midlands, UK

AbstractThe purpose of this study: Ethnic Minority Business Entrepreneurs’ (EMBs) financial behaviour is presumably shaped by their underlying cultural and cognitive factors. In this paper, it is expected to examine the tripartite relationship existing among National Culture, Bounded Rationality and Irrationality in Financial Decision Making of Sri Lankan ethnic minority entrepreneurs in the UK. Methodology: This research employs a psychometric questionnaire consisting five point Likert scaled questions to collect data. Based on Kline’s (2005) 10:1 rule of thumb sampling method, a sample of 200 of Sri Lankan EMB entrepreneurs in the UK were selected. Exploratory and Confirmatory Factor Analyses (EFA and CFA) are used to examine the tripartite relationship among the underlying constructs. Findings: The results from EFA show there are linkages among National Cultural Psychology (NCP), Bounded Rationality (BR) and Irrationality in Financial Decision Making (IFDM). CFA further proved a statistically significant direct effect in between IFDM and NCB (standardised estimation =0.403, p=0.002&lt;0.05), and Indirect effect of NCB to IFDM via Bounded Rationality (standardised estimation = 0.301, p=0.001&lt;0.05). Accordingly, it can be discovered a ‘Partial Mediation’ among these three constructs.Originality and Contributions: This paper developed a questionnaire to measure the concepts and statistically confirmed the links among National Cultural Psychology, Cognitive Biases and Irrationality in Financial Decision Making of Ethnic Minority Entrepreneurs. This study provides new knowledge for behavioural finance by looking through the lens of national culture and introducing a novel model as ‘Cultural and Behavioural Financial Decision Making (CBDFM)’ which explains how entrepreneurs are being diverted from rationality by their national cultural and cognitive factors. Practical Implications: EMB entrepreneurs are encouraged to understand their embodied cultural attributes which cause cognitive bias and eventually divert them from rational decision-making. Authorities who are empowering EMBs are recommended to consider the national cultural factors, and cognitive biases of EMB entrepreneurs when setting up new policies to promote EMBs. <br/

A learned conservative semi-Lagrangian finite volume scheme for transport simulations

Semi-Lagrangian (SL) schemes are known as a major numerical tool for solving transport equations with many advantages and have been widely deployed in the fields of computational fluid dynamics, plasma physics modeling, numerical weather prediction, among others. In this work, we develop a novel machine learning-assisted approach to accelerate the conventional SL finite volume (FV) schemes. The proposed scheme avoids the expensive tracking of upstream cells but attempts to learn the SL discretization from the data by incorporating specific inductive biases in the neural network, significantly simplifying the algorithm implementation and leading to improved efficiency. In addition, the method delivers sharp shock transitions and a level of accuracy that would typically require a much finer grid with traditional transport solvers. Numerical tests demonstrate the effectiveness and efficiency of the proposed method.Comment: 24 page

The Mediated Effect of Bounded Rationality on the Relationship between National Cultural Psychology and Irrationality in Financial Decision Making of Entrepreneurs: – An empirical study on the evidence from Ethnic Minority Business (EMBs) Entrepreneurs in West Midlands, UK

AbstractThe purpose of this study: Ethnic Minority Business Entrepreneurs’ (EMBs) financial behaviour is presumably shaped by their underlying cultural and cognitive factors. In this paper, it is expected to examine the tripartite relationship existing among National Culture, Bounded Rationality and Irrationality in Financial Decision Making of Sri Lankan ethnic minority entrepreneurs in the UK. Methodology: This research employs a psychometric questionnaire consisting five point Likert scaled questions to collect data. Based on Kline’s (2005) 10:1 rule of thumb sampling method, a sample of 200 of Sri Lankan EMB entrepreneurs in the UK were selected. Exploratory and Confirmatory Factor Analyses (EFA and CFA) are used to examine the tripartite relationship among the underlying constructs. Findings: The results from EFA show there are linkages among National Cultural Psychology (NCP), Bounded Rationality (BR) and Irrationality in Financial Decision Making (IFDM). CFA further proved a statistically significant direct effect in between IFDM and NCB (standardised estimation =0.403, p=0.002&lt;0.05), and Indirect effect of NCB to IFDM via Bounded Rationality (standardised estimation = 0.301, p=0.001&lt;0.05). Accordingly, it can be discovered a ‘Partial Mediation’ among these three constructs.Originality and Contributions: This paper developed a questionnaire to measure the concepts and statistically confirmed the links among National Cultural Psychology, Cognitive Biases and Irrationality in Financial Decision Making of Ethnic Minority Entrepreneurs. This study provides new knowledge for behavioural finance by looking through the lens of national culture and introducing a novel model as ‘Cultural and Behavioural Financial Decision Making (CBDFM)’ which explains how entrepreneurs are being diverted from rationality by their national cultural and cognitive factors. Practical Implications: EMB entrepreneurs are encouraged to understand their embodied cultural attributes which cause cognitive bias and eventually divert them from rational decision-making. Authorities who are empowering EMBs are recommended to consider the national cultural factors, and cognitive biases of EMB entrepreneurs when setting up new policies to promote EMBs. <br/

A multi-fidelity machine learning based semi-Lagrangian finite volume scheme for linear transport equations and the nonlinear Vlasov-Poisson system

Machine-learning (ML) based discretization has been developed to simulate complex partial differential equations (PDEs) with tremendous success across various fields. These learned PDE solvers can effectively resolve the underlying solution structures of interest and achieve a level of accuracy which often requires an order-of-magnitude finer grid for a conventional numerical method using polynomial-based approximations. In a previous work in [13], we introduced a learned finite volume discretization that further incorporates the semi-Lagrangian (SL) mechanism, enabling larger CFL numbers for stability. However, the efficiency and effectiveness of such methodology heavily rely on the availability of abundant high-resolution training data, which can be prohibitively expensive to obtain. To address this challenge, in this paper, we propose a novel multi-fidelity ML-based SL method for transport equations. This method leverages a combination of a small amount of high-fidelity data and sufficient but cheaper low-fidelity data. The approach is designed based on a composite convolutional neural network architecture that explore the inherent correlation between high-fidelity and low-fidelity data. The proposed method demonstrates the capability to achieve a reasonable level of accuracy, particularly in scenarios where a single-fidelity model fails to generalize effectively. We further extend the method to the nonlinear Vlasov-Poisson system by employing high order Runge-Kutta exponential integrators. A collection of numerical tests are provided to validate the efficiency and accuracy of the proposed method