An empirical analysis of the relationship between IT training sources and IT value

Information technology (IT) training has been identifie as a key factor for the success of IT applications and the most frequently applied coping mechanism to handle changing IT. However, there is a question as to how IT training has to be conducted to obtain desired outcomes (higher levels of IT value). This paper analyses the presence of IT training sources used by firm and examines the influenc on IT business value. Here, IT training is studied according to three IT training sources: in-house IT training, outside IT training, and self IT training by employees. In addition, differences in IT training sources are analysed according to two contingency factors: business size and business industry. Results show a positive relationship between IT training sources (outside and self IT training) and IT business value and confir that IT training sources are positively related to business size and differ moderately by business industry.Publicad

Improvement of value orientations in the process of forming the professional competence of teachers

This study examines the issues of value orientations of a teacher and their development as an integral part of professional competence. We drew attention to the relationship between the value orientations and the value sphere within the process of teacher’s professional development, the conditionality of professional competence by the value system. The aim of the research is the theoretical and empirical study of value orientations as a component of the professional competence of teachers. Particular attention is paid to the role and significance of creativity in the teaching performance. Based on the analysis of current literary sources, we examined the phenomenon of professional creativity of a teacher, made an attempt to define this concept and considered its structure and structural components. The research methodology and its algorithm were selected due to the purpose of the study. Experimental work included a complex psychological and pedagogical experiment and diagnostics of the stated parameters before and after the implementation of the advanced training. The study was carried out on the basis of the Institute of Foreign Languages of the Federal State Autonomous Educational Institution of Higher Education “The Peoples’ Friendship University of Russia” (RUDN). The results of the study allow us to conclude that there is a significant relationship between the professional creativity of a teacher and the effectiveness of professional performance, which is confirmed by the results of statistical processing of the data obtained. In the Russian psychological and pedagogical literature on the problem of professional competence two basic concepts are discussed, competence and competency. Researchers argue that these concepts are multidimensional and systemic in nature. In Russia, the difference between these concepts is most thoroughly substantiated in the glossary of the Federal State Educational Standard. It is indicated that competencies consist of knowledge, skills and abilities, as well as of practical experience. The ability to apply them in professional activities is called competence.

An analysis of the benefits for New Zealand banks of adopting a relationship banking model for small business clients

This thesis provides a discussion of research into the sources of value creation and addition accruing to banks through the use of relationship banking with small business clients. The investigation involves business managers in several banks and accordingly it portrays their perspective. The study addresses four key questions: (i) what does relationship-banking mean to the five major bank brands in New Zealand? (ii) How does the relationship-banking process actually work? (iii) What are the sources of value (i.e. benefits) of relationship banking to these five major bank brands when dealing with small businesses, and, (iv) how do these banks secure the benefits? Prior research into relationship banking and small business has concentrated on the potential benefits to the businesses. The literature contains both normative theorising and empirical work addressing aspects of the relationship and the benefits accruing to the small business. What is not supported by prior research is an understanding of why the banks engage in relationship management processes with small business. The obvious answer is that it is profitable. This in turn begs the questions of returns and risks faced by the banks and how these are managed. The nature of the research questions which are about investigating processes suggests the use of a qualitative research approach. A multiple case study approach points the research method toward conducting interviews with relationship managers, selected using theoretical sampling, from the five main bank brands and across the five metropolitan cities in New Zealand. The big five control 85% of the registered banks’ total assets in New Zealand and dominate the small business market. The primary data collected through interviews are analysed using the thematic analysis method. This research produces a number of key findings which directly address the research questions and go beyond. It is found that the working definition of relationship banking departs from that often quoted in the literature in a number of ways. This supports the contention that banks use relationship banking as an overarching approach, within which other lending technologies may be employed with their small business clients. Sources of value creation and addition stemming from relationship banking for the banks are clearly identified. In addition the processes and mechanisms by which banks operationalise and secure these benefits are revealed. How new relationship banking benefits are identified, creating and adding value to banks are traced through the interviews. The findings around these new benefits have important implications for the current research in regard to comparative studies of the different lending technologies in general and more specifically to the future of relationship banking which is challenged by an increasingly competitive financial markets. From an understanding of how bank relationship managers perceive the dynamics of their roles in creating relationship banking benefits a risk-return taxonomy is formulated. Issues emerging from this formulation/taxonomisation relate (i) practically, illustrating how these taxonomies can benefit banks, such as helping banks identify when to expect each benefit and to develop best practices (e.g. training staff and providing infrastructures), consequently ensuring the maximisation of the scooping up of all possible relationship banking benefits. Thus improving banks’ performance in terms of risk mitigation and increasing return. (ii) Conceptually, the thesis shows how the risk-return taxonomy, for example, can help in defining and positioning relationship banking at the heart of the banks’ decision making in regard to small business. The thesis contributes to the small business finance knowledge base in several ways. There is a clear identification of both the different types and different levels of relationship banking, depending on the criteria used by banks to silo businesses into online, small business, or medium business relationship banking models. The non-uniform, but definite similarities, between banks does indicate the contextual nature of the issues. The banks’ approach to retention is noteworthy and their respective investment into discouraging a small business from changing banks provides an insightful juxtaposition to prior research investigating the benefits and costs of changing banks. The thesis findings offer several opportunities for future research. One such example of a research agenda relating to the different levels of relationship banking discussed above is the modelling of the three different levels of relationship banking. This could utilise, for example, a piecewise type of function which could then be followed by an empirical study to test and measure the accuracy of the model. It would also serve to test the claims made in this thesis regarding the identification of both the different types and the different levels of relationship banking.

Using Backpropagation Neural Networks for the Prediction of Residual Shear Strength of Cohesive Soils

A complex nonlinear relationship exists between indicative soil parameters (liquid limit, plastic limit, clay fraction, sand fraction, and normal stress loading) and drained secant residual friction angle (ør’). Academic literature provides various empirical models for the prediction of ør’, though their predictions generally suffer from insufficient representation of the nonlinear relationship between parameters. In this study, an artificial neural network was developed for the prediction of ør’. Artificial neural networks are computational learning algorithms that derive their structure and learning procedures from phenomena observed in biological nervous systems. Their complex, interconnected structures allow for successful mapping of nonlinear relationships between parameters. This motivated the development and application of a network known as a backpropagation neural network (BPNN) as an alternative predictive model for ør’. The BPNN was trained to successfully map the relationship between indicative soil parameters and ør’ using a variety of soil datasets provided from academic literature and other sources. The BPNN’s performance was evaluated using a normalized root mean square error (RMSE) term. It was posited that the BPNN predictions could be improved by training individual networks on soil data subdivided by clay fraction ranges. Analysis showed that the division of data into subsets significantly reduced the BPNN’s predictive performance by limiting the amount of data available for individual network training. Where other predictive models generally neglect sand fraction as a predictive parameter for ør’, this study attempted to evaluate its predictive value. Comparison between a BPNN that included sand fraction and one that did not proved inconclusive as the results from multiple RMSE analyses between the two models were not statistically different. Correlation-based equations for the prediction of ør’ in Stark and Hussain (2013) are based on the subdivision of soil data by clay fraction ranges. A comparison of the BPNN predictive model to other empirical models was performed in order to evaluate the viability of a BPNN as an alternative to current predictive models. The BPNN outperformed a traditional, multivariate least-squares linear regression model as well as correlation-based equations from Stark and Hussain (2013). The normalized root mean square error for Stark and Hussain equation-based predictions of ør’ was 0.2270 in comparison to 0.1278 for the BPNN. Where Stark and Hussain’s equations performed well on the particular dataset used to create these empirical equations, it failed to accurately predict ør’ for other data sets provided in the literature. The BPNN model was more robust in its ability to predict ør’ over a variety of datasets in this study and suggests that the BPNN may provide a viable alternative to other predictive models for ør’

Determinants of innovativeness in SMEs. disentangling core innovation and technology adoption capabilities

This paper studies innovativeness in SMEs from a set of innovation indicators at the firm level, capturing various types of innovation (product, process, organisational, and marketing innovations) and the level of innovativeness in these firm’s developments. The article identifies two separate dimensions in the innovativeness of Spanish SMEs, using factor analysis techniques. One dimension is associated with the capabilities for core/internal innovation and the other with the capabilities for the adoption of technology. The paper shows that significant differences exist in the personal and organisational factors that favour these two dimensions. The entrepreneur’s motivation, business planning, and cooperation in R&D activities constitute significant factors when considering the core dimension of a firm’s innovativeness, but have no effect on the firm’s capabilities for technology adoption. However, the use of external consultancy services seems to have no significant effect on the core dimension of the innovativeness of anSME, whereas it is a relevant factor for its technology adoption. Furthermore, it is shown that the entrepreneur’s education plays a more significant role in the core dimension of a firm’s innovativeness than in its capabilities for technology adoption. Depending on the policy objectives, these differences should lead to the application of specific policy approaches when an attempt to stimulate innovation in SMEs is made

Risk assessment and relationship management: practical approach to supply chain risk management

The literature suggests the need for incorporating the risk construct into the measurement of organisational performance, although few examples are available as to how this might be undertaken in relation to supply chains. A conceptual framework for the development of performance and risk management within the supply chain is evolved from the literature and empirical evidence. The twin levels of dyadic performance/risk management and the management of a portfolio of performance/risks is addressed, employing Agency Theory to guide the analysis. The empirical evidence relates to the downstream management of dealerships by a large multinational organisation. Propositions are derived from the analysis relating to the issues and mechanisms that may be employed to effectively manage a portfolio of supply chain performance and risks

Domestic Outsourcing in the United States: A Research Agenda to Assess Trends and Effects on Job Quality

The goal of this paper is to develop a comprehensive research agenda to analyze trends in domestic outsourcing in the U.S. -- firms' use of contractors and independent contractors -- and its effects on job quality and inequality. In the process, we review definitions of outsourcing, the available scant empirical research, and limitations of existing data sources. We also summarize theories that attempt to explain why firms contract out for certain functions and assess their predictions about likely impacts on job quality. We then lay out in detail a major research initiative on domestic outsourcing, discussing the questions it should answer and providing a menu of research methodologies and potential data sources. Such a research investment will be a critical resource for policymakers and other stakeholders as they seek solutions to problems arising from the changing nature of work

New human resource management systems in non-based-knowledge firms: Applications for decision making on the business performance

The aim of this paper is double. First, it provides a conceptual framework and modelling of the relationship between human resource management (HRM) systems and non-based-knowledge firms. Second, using survey data on 1.518 Catalan firms (in Spain, with capital in Barcelona), the paper: 1) identify two system of HRM (in progress HRM system and non-HRM developed system); 2) build a causal model of determinants of HRM systems; and 3) describe the association links between in progress HRM system and firm's performance. Using factor and cluster analysis, we find that only one-third of firms use in progress HRM system. Using logit binomial analysis, we find that features which are structural, technological, strategic, organisational and performance-related explain the adoption of in progress HRM system. Finally, using association analysis, we find that firms that adopt in progress HRM system: 1) are more internationalised and show greater ability to adapt to the changing environment, to innovate and to collaborate; 2) focus on product/service differentiation strategy enhancing quality; 3) apply a greater degree of new forms of work organization; 4) have more technological equipment and use IT more intensively; and 5) invest more in training their employees, than firms with non-HRM system developed

Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data

It is an enduring question how to combine revealed preference (RP) and stated preference (SP) data to analyze travel behavior. This study presents a framework of multitask learning deep neural networks (MTLDNNs) for this question, and demonstrates that MTLDNNs are more generic than the traditional nested logit (NL) method, due to its capacity of automatic feature learning and soft constraints. About 1,500 MTLDNN models are designed and applied to the survey data that was collected in Singapore and focused on the RP of four current travel modes and the SP with autonomous vehicles (AV) as the one new travel mode in addition to those in RP. We found that MTLDNNs consistently outperform six benchmark models and particularly the classical NL models by about 5% prediction accuracy in both RP and SP datasets. This performance improvement can be mainly attributed to the soft constraints specific to MTLDNNs, including its innovative architectural design and regularization methods, but not much to the generic capacity of automatic feature learning endowed by a standard feedforward DNN architecture. Besides prediction, MTLDNNs are also interpretable. The empirical results show that AV is mainly the substitute of driving and AV alternative-specific variables are more important than the socio-economic variables in determining AV adoption. Overall, this study introduces a new MTLDNN framework to combine RP and SP, and demonstrates its theoretical flexibility and empirical power for prediction and interpretation. Future studies can design new MTLDNN architectures to reflect the speciality of RP and SP and extend this work to other behavioral analysis

Connotation Frames: A Data-Driven Investigation

Through a particular choice of a predicate (e.g., "x violated y"), a writer can subtly connote a range of implied sentiments and presupposed facts about the entities x and y: (1) writer's perspective: projecting x as an "antagonist"and y as a "victim", (2) entities' perspective: y probably dislikes x, (3) effect: something bad happened to y, (4) value: y is something valuable, and (5) mental state: y is distressed by the event. We introduce connotation frames as a representation formalism to organize these rich dimensions of connotation using typed relations. First, we investigate the feasibility of obtaining connotative labels through crowdsourcing experiments. We then present models for predicting the connotation frames of verb predicates based on their distributional word representations and the interplay between different types of connotative relations. Empirical results confirm that connotation frames can be induced from various data sources that reflect how people use language and give rise to the connotative meanings. We conclude with analytical results that show the potential use of connotation frames for analyzing subtle biases in online news media.Comment: 11 pages, published in Proceedings of ACL 201