Miracle-dz/UniFAR-FTUs huggingface dataset:
Moderating Effect of Smartphone Addiction on Mobile Wallet Payment Adoption

Abstract This study attempts to identify the catalytic role of smartphone addiction in driving mobile wallet payment adoption behavior in emerging economies such as India. The research model was tested using a questionnaire-based response collected from 512 young consumers. The findings of structural equation modeling and multi-group analysis helped in understanding the influence and importance of the research constructs of perceived ease of use, perceived usefulness, and subjective norms in the adoption of mobile wallet payments by young people. The results indicated that the moderating effect of smartphone addiction played a substantial role in the adoption of mobile wallet payments. It has also revealed the importance of communication to the right consumer through proper channels and the appropriate age group. The outcome of the study can be utilized by marketers to frame strategies for positioning their services among an appropriate consumer base, thereby enhancing Internet business opportunities.
Mapping the ESG Behavior of European Companies. A Holistic Kohonen Approach

In the context of increased awareness for complying with the multiple requirements for sustainable development, the stakeholders need to have the proper information for analyzing the corporate behaviors from various perspectives. Thus, the purpose of this research is to investigate and map the sustainability patterns of European companies at the beginning of 2019, in order to uncover valuable insights into the corporate sustainable behaviors. The Environmental, Social and Governance (ESG) performances of 1165 European companies were considered by applying the Kohonen neural network for clustering purposes at three main levels: (1) ESG overall level, including country and sectoral perspectives; (2) ESG thematic level; (3) ESG four-folded innovative level (stakeholder, perspective, management level and focus views). All three analyses carried out show a three-clustering solution—Lower, Middle and Higher ESG clusters. Most firms are top ESG performers and the companies with good ESG scores also have more related controversies. The results highlight the sustainability profiles of the examined companies. Firstly, the environmental and social priorities are preferred over corporate governance targets. Secondly, companies tend to implement a business-customized ESG approach for achieving organizational efficiency and competitiveness. Thirdly, there is a higher consideration of employees, external-directed measures, operational issues and process-orientation in the corporate ESG performance and development. The ESG approach of the European reporting companies is mainly mature, strategic and long-term oriented, aimed to increase the corporate competitiveness and to support the societal well-being altogether.
The Real Effects of Stock Prices: Learning, Disclosure and Corporate Social Responsibility

This paper develops a tractable model to study the impact of corporate social responsibility (CSR) on real decisions (i.e., production and disclosure decisions) of a firm which can learn from the stock price. Firms with high CSR disclose more precise information, improving the stock liquidity and price efficiency, which also benefit liquidity traders and consumers. Interventions by regulators in firms’ disclosure decisions, such as mandatory disclosure, can improve social welfare, but their effectiveness depends on the degree of CSR. We also discuss the implications of learning from the price.
Mathematical and computer modelling of the enteric nervous system

The enteric nervous system (ENS) runs within the intestinal wall and is responsible for initiating and enacting several reflexes and motor patterns, including peristalsis and the complex interdigestive motor programs, known as migrating motor complexes (MMCs). The ENS consists of several neuron types including intrinsic sensory neurons, interneurons and motor neurons. A great deal is known about the anatomy, pharmacology and electrophysiology of the ENS, yet there is almost no understanding of how enteric neural circuits perform the functions that they do and how they switch from one function to another. The ENS contains intrinsic sensory neurons (ISNs) that connect to every neuron type in the ENS, including making recurrent connections amongst themselves. Thus, they are likely to play a key role, not just in sensory transduction, but in coordination of reflexes and motor patterns. This thesis has explored how these functions are performed by developing and analysing mathematical and computer models of the network of ISNs. ISNs interact with each via slow excitatory post-synaptic potentials (EPSPs). Experimentally, slow EPSPs require several presynaptic stimuli to evoke, last several seconds to several minutes, the onset can be delayed by several hundred milliseconds and the membrane potential response sums nonlinearly in the inputs. Slow EPSPs are thus qualitatively different from fast, directly ligand gated EPSPs usually included in network models. Therefore the first part of this work was to develop a mathematical model of slow synaptic transmission in the ENS. The model was based on an abstraction of the processes of activation, inactivation and summation of a cAMP, protein kinase A (PKA)-dependent second messenger cascade. The model describes the activation of receptors, G-proteins and production of cAMP as the first
The Term Structure of Option-Implied Volatility and Future Realized Volatility

ABSTRACT We extract the short-, medium-, and long-term factors from the term structure of the option-implied volatility (OIV) of the S&P 500, the FTSE 100, and the Chinese 50 Exchange-Traded Funds (ETF), using an extension of the Nelson-Siegel (N-S) model and use estimated factors to predict future realized volatility (FRV) in the US, UK, and Chinese markets. Several interesting findings emerged from our study. First, we confirmed that the VIX is more informative than historical realized volatility (HRV) in predicting FRV. Second, we find that the volatility term structure contains some additional information compared with the VIX and HRV. Third, we verify that the three factors extracted from the N-S model are strongly cointegrated, related to volatilities. Moreover, based on the normalized error term of the cointegrated pairs, we construct straddles and delta-hedging option trading strategies. Without taking transaction costs into account, the straddle call trading strategy achieves a mean return of 37.59% monthly, and, at the same time, the exponential cumulative returns for the straddle call strategies are 4.2411 at a threshold of 1.1 in the S&P 500. As the threshold increases, the volume of transactions declines, leading to a fall in cumulative mean returns.
Examining the Impact of Training in the Unified Theory of Acceptance and Use of Technology

ABSTRACT This research identifies, examines, and presents an empirical evaluation of the existing technology acceptance constructs as they relate to end-user participation in training programs. The analysis of technology acceptance constructs and their fit with the existing training paradigms suggests a significant positive correlation between training reactions and behavioral intention to use information technology. In addition, an extended modeling framework that includes a training reaction construct as an intermediary factor between the training paradigms and the existing technology acceptance constructs, as reflected in the UTAUT model, is introduced and evaluated. We find that the relationship between training reactions and behavioral intentions to use were partially mediated by facilitating conditions.
The efficacy of cheap talk in collective action problems

Incomplete information exacerbates the problems inherent in collective action. Participants cannot efficiently coordinate their actions if they do not know each other’s preferences. I investigate when ordinary communication, or cheap talk, may resolve mutual uncertainty in collective action problems. I find that the efficacy of communication depends critically on the relationship between contributions and the value of the joint project. The incentive barriers to honesty are highest when every contribution increases the project’s value. Participants then have a strict incentive to say whatever would induce others to contribute the most, so cheap talk lacks credibility. By contrast, when contributions may be marginally worthless, such as when the project has no value unless contributions hit a certain threshold, communication may help participants avoid wasted effort. Using these findings, I identify which collective action problems in politics might benefit from communication and which require more expensive solutions to overcome uncertainty.
4D-Interleaving of Isolated ISOP Multi-Cell Converter Systems for Single Phase AC/DC Conversion

The multi-cell converter approach allows to break the performance barriers of conventional systems by leveraging the advantages of using multiple interleaved low voltage and/or low current converter cells. In this digest, a fourth dimension of interleaving is proposed which considers the time dependent degrees of freedom in the control of the entire multi-cell converter system. This new control concept is based on the possibility to decouple the operation of the series connected input stages from the parallel connected output stages by using the energy storage capability of the DC-link capacitors. This digest shows how the 4D-interleaving concept improves the system performance such as the efficiency which will be demonstrated with measurement results on a hardware prototype system in the final paper.
Traditional Political Institutions and Democracy: Reassessing Their Compatibility and Accountability

This article revisits prominent frameworks for understanding traditional political institutions which make pessimistic assessments about their compatibility with democracy. Traditional political institutions are often assumed to be unaccountable because they are led by undemocratic leaders who are not subject to electoral sanctioning. However, drawing on new information from the TradGov Group dataset, an expert survey on the contemporary practices of more than 1,400 ethnic groups that currently have traditional political institutions, we show that these institutions contain their own distinct mechanisms of accountability. In a majority of cases, decision-making is consensual and leaders must account for their actions in various ways. We challenge the electoral accountability framework for understanding the quality of traditional leaders’ performance, instead arguing that traditional political institutions can be compatible with democracy and even accountable to their citizens insofar as they adopt inclusive decision-making processes and their leaders have strong nonelectoral connections to the communities they represent.
Ensemble Learning for Visual Recognition

xii List of Abbreviation Used . xiii Acknowledgements . xiv Chapter
Retirement and the Sectors: Do Private and Public Personnel Differ in Their Retirement Decision?

Retirement is a field of growing interest in both the public and the private sectors. Given the aging workforce in Western countries, understanding the factors that contribute to an employee’s decision to retire is an area of increasing interest to political, economic, social, and organizational scholars. Most retirement studies concentrate on a narrow set of factors, examining their impact on retirement in isolation of the broader context. Drawing from public management theory, and based on theories of person–organization fit (POF), we examine whether and when private and public personnel differ in their retirement decision. Findings indicate that previously shown relationships between individual-level financial status and the decision to retire are contingent on employment sector. The results of this research extend knowledge regarding the normative influence of mechanisms driving retirement and demonstrate the broader implications of sector on retirement decision-making.
A Note on Mossin's Theorem for Deductible Insurance Given Random Initial Wealth

Mossin's theorem for deductible insurance given random initial wealth is re-examined. For a fair premium, it is shown that a necessary and sufficient condition, in the spirit of the Generalized Mossin Theorem for coinsurance, is impossible using the notion of expectation dependence. Next, it is established that for a fair premium, full insurance will be optimal for a risk-averse individual if the random loss and the random initial wealth are negative quadrant dependent, improving upon an extant result in the literature. In view of a set of examples given in this paper, such a sufficient condition cannot be obtained using the notion of expectation dependence. Finally, for an unfair premium, it is shown that partial insurance will always be optimal, irrespective of the risk preference of the individual as well as the dependence structure between the random loss and the random initial wealth.
The function of ability, benevolence, and integrity-based trust in innovation networks

ABSTRACT This study contributes to the understanding of how trust based on perceived ability, benevolence, and integrity functions in networks. It adopts a mixed-method approach with quantitative and qualitative data from five Norwegian innovation networks. The study demonstrates how trust based on perceived benevolence, ability, and integrity influences different aspects of network interaction and network outcomes against the background of the network members’ perceptions of risk. Moreover, it finds that these dimensions of trust function differently at the inter-organisational and at the network level. The former level here concerns trust between the organisations in the network, while the latter concerns trust in the network more generally. Benevolence-based trust is identified as particularly salient at both levels for promoting open and honest communication as well as knowledge sharing, enabling both more successful collaboration in general, and more innovation specifically.
Dual Business Relationships, Opportunity Knowledge, and New Product Development: A Study on Returnee Young Ventures

The effects on innovation of the dual embeddedness of returnee young ventures (RYVs) in both domestic and international networks of relationships and knowledge contexts are important for value creation, growth, and success of these firms and embody a unique research opportunity. Drawing on a framework combining a business relationship perspective and the knowledge-based view, the authors propose that RYVs take advantage of business relationships and opportunity knowledge from both international and domestic markets to nurture their innovation. They test their model on a sample of 200 RYVs in China. The findings reveal that business relationships are essential for acquiring knowledge about technological and business opportunities, though only international opportunity knowledge and domestic business relationships positively influence new product development. In addition, the interaction between international and domestic business relationships constrains firms’ capacity for obtaining international opportunity knowledge. This study offers insights into how the trade-offs between dual relationships and subsequently sourced knowledge contribute to new product development in emerging markets, and it extends the discussion on the paradox view of business relationships with geographically dispersed actors.
A framework for FPGA-based acceleration of neural network inference with limited numerical precision via high-level synthesis with streaming functionality

A Framework for FPGA-Based Acceleration of Neural Network Inference with Limited Numerical Precision via High-Level Synthesis with Streaming Functionality Ruo Long Lian Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2016 Deep neural networks (DNN) are achieving state-of-the-art performance in many artificial intelligence tasks, such as computer vision and speech recognition. Due to the high computational requirements of DNN, there is an increasing need to design custom hardware for accelerating the DNN computation with a low power budget. This thesis proposes an FPGA-based acceleration solution for DNN inference, realized on a SoC device where software controls the execution and off-loads compute-intensive operations to the hardware accelerator. To minimize the hardware cost, limited precision data representations are investigated for DNN computations, and incorporated in the accelerator design. Streaming functionality is added to the LegUp high-level synthesis tool, allowing the hardware accelerator to be designed entirely in C-language and synthesized to pipelined hardware. The accelerator solution is not tied to a particular DNN architecture; rather, it is configurable in software, permitting the acceleration for a range of DNN architectures proposed in recent literatures.
Graphical Models for Peptide Identification of Tandem Mass Spectra

Graphical Models for Peptide Identification of Tandem Mass Spectra John T. Halloran Co-Chairs of the Supervisory Committee: Professor Jeff A. Bilmes Electrical Engineering Professor William S. Noble Genome Sciences Graphical models (GMs) provide a flexible framework for modeling phenomena. In the past few decades, GMs have become indispensable tools for machine learning and computational biology. They afford a wide range of modeling granularity, from restricting only exact events of interest to occur to allowing all possible events in a phenomenon’s event space. For all such modeling considerations, GMs afford efficient algorithms to perform inference over the probabilistic quantities of interest. In this thesis, we show how GMs may be leveraged to improve both identification accuracy and search runtime of tandem mass (MS/MS) spectra. For the majority of existing MS/MS scoring algorithms, we give equivalent GMs and show how search time may be algorithmically improved. We present GMs for posterior based (sum-product) and max-product inference which offer state-of-the-art performance and, most importantly, are amenable to efficient parameter estimation. Furthermore, we show how a GM which generatively models the stochastic process by which peptides produce MS/MS spectra may be utilized to calculate features for improved classification between correctly and incorrectly identified spectra, leading to significantly improved identification accuracy.
USING CONTEXTUAL CONDITIONAL PREFERENCES FOR RECOMMENDATION TASKS: A CASE STUDY IN THE MOVIE DOMAIN

Recommendation engines aim to propose users items they are interested in by looking at the user interaction with a system. However, individual interests may be drastically influenced by the context in which decisions are taken. We present an attempt to model user interests via a set of contextual conditional preferences. We show that usage of proposed preferences gives reasonable values of the accuracy and the precision even when the dataset is quite small.
Nudging pro-environmental behavior: evidence from a web experiment on priming and WTP

Investigations on state-dependent and endogenous preferences have gained momentum. There is now abundant empirical literature on whether, and how, external stimuli influence or predict people’s behavior and appraisals. In recent decades, attempts have been made to enlarge this strand of research to determine whether “nudging” may help in managing environmental problems and boosting social preferences. Following this line of investigation, we describe a web experiment to analyze the impact of priming on environmental and ethical attitudes and willingness to pay (WTP) for environmental protection. We found that while priming does make pro-environmental attitudes more salient, its frame affects the probability of WTP a premium for environment-friendly goods and the size of the premium. Unlike other authors, we used a visual priming technique based on a short video cartoon about a smartphone lifecycle.
Determinants of Work-Related Training: An Investigation of Observed and Unobserved Firm-, Job- and Worker-Heterogeneity

One of the most important policy goals in industrialized countries is to increase the skill level of the labor force by life-long-learning strategies. In this paper our aim is to explain to what extent the variation in training investments is determined either by (observed and unobserved) heterogeneity of firms or of workers, hence we put a new perspective on the determinants of training. Rather than analyzing single determinants or groups of variables, we decompose the variation into a worker-specific and a firm-specific part and show how much of the unexplained variation is independent of both. Our results show that both firm-, job- and worker-level heterogeneity explains training participation and that firm heterogeneity is far less important compared to the others. Also interesting, is the finding that a large part of the overall variance is not driven by firm- or worker heterogeneity, hence training participation seems to be to some extent an unexplained event which happens by chance.
The Role of the New Goods Margin for New EU Countries Trade

Recent literature on international trade has devoted increased attention to the role played by the extensive margin of trade for economies engaged in liberalization and structural transformation processes, such as the new EU countries. This article documents the leading role of the new goods margin in trade growth for the new member states that have acceded the EU in 2004 and 2007. Product trade data is used to analyse the trade share of the new goods over the sample period 1999&#8211;2014. The results show that the extensive margin of trade grew from 10 to around 50 per cent for most bilateral trade flows of the new EU member states. Further decomposition of the new goods margin shows that the goods already traded though in small volumes at the beginning of the period play a leading role.
The Economics of Conflict and Peace

To know where we are going, we need to know where we stand and where we come from. I will thus first describe in the current introduction section 1 the main existing results in the literature on the economics of conflict and peace. 2 After this, I will describe in section 2 what the main cutting-edge lines of research and emerging trends are, and will then in section 3 offer some conclusions and formulate –somewhat more speculative– views on which turn the literature may be taking in the coming years.
Welfare Effects of a Non-Contributory Old Age Pension: Experimental Evidence for Ekiti State, Nigeria

Many countries in the developing world have implemented non-contributory old-age pensions. Evidence of the impact of such policies on the elderly in Sub-Saharan Africa is scarce, however. In this paper, we provide the first evidence from a randomized evaluation of an unconditional, non-contributory pension scheme targeted at the elderly in Ekiti State, Nigeria. Our findings show that treated beneficiaries self-reported better quality of life, more stable mental health, and better general health. We also provide evidence of spillover effects on labor outcomes and on household expenditure patterns as well as support for demand- side interventions aimed at improving the welfare of elderly poor citizens and other household members.