Investigating the training and development of O24U NZ Ltd to improve employees’ performance

The topic of this research is to investigate the training and development of O24U to improve employees’ performance. This research aims to: firstly, investigate the process of O24U NZ Ltd using training and development; secondly, to research the relationship between the training and development and employees’ performance; and finally, to identify several recommendations on training and development to improve employees’ performance. O24U NZ Ltd was founded in 2015. and is located at Hamilton CBD. It mainly provides healthcare products made in New Zealand and Australia. There are four people currently working for the store, and there are about 20 competitors of O24U, such as Green, Sunshine and DeKang, in Hamilton. Literature for the review was chosen through the scope (training and development, healthcare product industry in New Zealand and China, strategic human resource management (SHRM) and benchmarking). The researcher conducted four interviews to gather the necessary data for this study (3 employees of O24U and one staff member from one of the competitors). The data were analysed through inductive thematic analysis. Six themes were analysed: the purpose, type and issues of training and development, on-boarding, SHRM and the benefits of Oceanian healthcare products. The researcher found that training and development are vital for any organisation, on-the-job training has become the most popular approach to operating training and development programmes, and the main function of SHRM is to manage employees’ values creation capacities. Several recommendations are made which include five aspects (situation of the store, using systems, stocktaking, packaging and cleaning)

Reveal quantum correlation in complementary bases

An essential feature of genuine quantum correlation is the simultaneous existence of correlation in complementary bases. We reveal this feature of quantum correlation by defining measures based on invariance under a basis change. For a bipartite quantum state, the classical correlation is the maximal correlation present in a certain optimum basis, while the quantum correlation is characterized as a series of residual correlations in the mutually unbiased bases. Compared with other approaches to quantify quantum correlation, our approach gives information-theoretical measures that directly reflect the essential feature of quantum correlation.Comment: 7 pages, 4 figure

From ambiguity and sensitivity to transparency and contextuality : a research journey to explore error-sensitive value patterns in data classification

University of Technology Sydney. Faculty of Engineering and Information Technology.“ , ”. This statement by John Locke, an English philosopher and medical researcher in the 1680s, is still relevant today, and this scope of error can be expanded from knowledge and judgement to result and process in terms of data analysis, to treat errors as a part of the knowledge to learn from rather than to simply eliminate. In the research area of data mining and classification, errors are inevitable due to various factors such as sampling and computation restriction, and measurement and assumption limitations. To address this issue, one approach is to tackle errors head-on, to focus on refining the mining and classification processes by way of theory and algorithm enhancement to reduce errors, and it has been favored by researchers because the research results can be verified directly and clearly. Another approach is to focus on the examination of errors together with the data closely to explore the further understanding of different aspects of the data, especially on attributes and value patterns which may be more sensitive to errors to help identify and reduce errors in a retrospective and indirect way. This research has taken up the latter and less favorable approach to learn from errors rather than simply eliminating them, to examine the potential correlation between the classification results and the specific characteristics of attributes and value patterns, such as value pattern ambiguity, error risk sensitivity and multi-factor contextuality, to help enhance understanding of the errors and data in terms of correlation and context between various data elements for the goal of knowledge discovery as well as error investigation and reduction, not just for researchers, but more importantly, for the stakeholders of the data. This research can be considered a four-stage journey to explore the ambiguity, sensitivity, transparency and contextuality aspects of value patterns from a philosophical and practical perspective, and the research work conducted in each stage of the journey is accompanied by the development of a new error pattern evaluation model to verify the results in a progressive and systematic way. It is all about exploring and gaining further understanding on errors and data from different perspectives and sharing the developments and findings with the aim of generating more interest and motivation for further research into data and correlated factors, internally and externally, transparently and contextually, for the benefit of knowledge discovery