Earticle

Visual representations for concepts in business management are quite challenging, especially those abstract concepts in Accountancy discipline. For example, there might not be a consensus on what to use to represent such abstraction as an asset, liability, or owner equity. This is because asset can be property, estate, resources, equipment, or any tangible or non-tangible valuables. Cognitive science concepts and behavior engagement have been used to develop visual representations for financial data. The concepts include spatial processing, big picture thinking, and metaphor. Review of past studies together with a brief research plan to test the usability for learning of four new augmented reality 0visuals are provided in the present paper.

In recent years, big data has usefully been deployed by organizations with the aim of getting a better prediction for the future. Moreover, knowledge management systems are being used by organizations to identify and create knowledge. Here, the output from analysis of big data and a knowledge management system are used to develop a new model with the goal of minimizing the cost of implementing new recognized processes including staff training, transferring and employment costs. Strategies are proposed from big data analysis and new processes are defined accordingly. The company requires various skills to execute the proposed processes. Organization’s current experts and their skills are known through a pre-established knowledge management system. After a gap analysis, managers can make decisions about the expert arrangement, training programs and employment to bridge the gap and accomplish their goals. Finally, deduction graph is used to analyze the model.

Often we receive misled conclusion in the research if properly variables are not analyzed. In different functional issues of management it is very essential that all the latent and observed variable are properly understood so management decisions will be relevant and effective. The objective of this paper is to investigate the use of different multivariate tools for analyzing in the management research : applied or basic. The sources of data is primary as well as secondary. The primary includes the observation of different research articles of the proceedings of different conferences. And the secondary includes different publications related to multivariate analysis. The study has revealed the reasons of not using such tools of research. The preliminary finding reveals that most of the researches do not use such analytical tools in a comprehensive manner. Carelessness in design while fixing the design aspect is the main reasons of not using appropriate design.

Many technology innovations fail. Only a few of them are successfully implemented. Most of the remaining are discontinued before long or fail to be routinized. Although employees attempted to adopt the innovation for some legitimacy reasons, they have not reached the stage of internalization in which they believe in the real value of the innovation and become committed to the innovation. The deficiency of internalization was utilized in many studies as an important factor for explaining the failed innovation cases. However, few empirical studies examine the role of internalization in technology adoption. This study aims to investigate a mediating effect of internalization on technology adoption.

Rapid technological advancements and widespread adoption of smart phones in recent years provide students with new opportunities for getting knowledge and making researches in innovation century. As the penetration of smart phone devices in education increases, there is a large growth in the use of these devices especially among the youth. In spite of increasing importance of smart devices in education, the significant features of these technology devices for general learning have not been experientially addressed. In this study we are going to investigate the comparison of smart phone devices and find the necessary conditions for using mobile devices as an educational tool by a conjoint method. There will be five attributes: screen size, batter type, mobile OS, memory capacity and price. By surveying we got the results which showed us the respondents’ desire of using specific smart phone; thus, we defined that screen size attribute is the most important device characteristic.

Growing information threats have threatened organization to lose information security controls in these days. Many organizations have accepted the various information security management systems does mention necessity of a continuous evaluation process for the executions of information security management in a theoretical aspect. This study suggests a continuous evaluation process for information security management reflecting the real execution of managers and employees in organizations.

This paper proposes a new software quality model composed of a hierarchy of software quality views and three software quality characteristics models. The software view hierarchy is composed of two levels : end view and means view at the first level, contingency view and intrinsic view as sub-views of means view. Three software quality characteristics models are activity quality characteristics model, contingency quality characteristics model, and intrinsic quality characteristics model, which correspond to end view, contingency view, and intrinsic view respectively. This paper also reclassifies characteristics of ISO/IEC 25000 series SQuaRE’s software product quality model according to the proposed software quality model. The results illustrate clearly the shortcomings of SQuaRE’s product quality model and how to overcome them. First of all, most of SQuaRE’s product characteristics should be redefined and conceptually clarified according to the views on which they are really rested. Much more characteristics should be supplemented too. After that, rigorous empirical researches will become relevant. Causal relationships between activity quality characteristics and characteristics of means view should be empirically researched.

This paper proposes a fast sound source localization method using a TDOA sign–based algorithm. We present an L-shaped microphone set-up which creates four major regions in the range of 0°~360° by the intersection of the positive and negative regions of the individual microphone pairs. Then, we make an initial source region prediction based on the signs of two TDOA estimates before computing the azimuth value. Also, we apply a threshold and angle comparison to tackle the existing front-back confusion problem. Our experimental results show that the proposed method is comparable in accuracy to previous three microphone array methods; however, it takes a shorter computation time because we compute only two TDOA values.