Making sense of purpose, direction and innovation : an embedded design led innovation case study in the Australian mining industry

The mining equipment technology services sector is driven by a reactive and user-centered design approach, with a technological focus on incremental new product development. As Australia moves out of its sustained mining boom, companies need to rethink their strategic position, to become agile to stay relevant in an enigmatic market. This paper reports on the first five months on an embedded case study within an Australian, family-owned mining manufacturer. The first author is currently engaged in a longitudinal design led innovation project, as a catalyst to guide the company’s journey to design integration. The results find that design led innovation could act as a channel for highlighting and exploring company disconnections with the marketplace and offer a customer-centric catalyst for internal change. Data collected for this study is from 12 analysed semistructured interviews, a focus group and a reflective journal, over a five-month period. This paper explores limitations to design integration, and highlights opportunities to explore and leverage entrepreneurial characteristics to stay agile, broaden innovation and future-proof through the next commodity cycle in the mining industry.

The Australian mining industry and the ideal mining woman : mobilizing a public business case for gender equality

Despite ongoing ‘boom’ conditions in the Australian mining industry, women remain substantially and unevenly under-represented in the sector, as is the case in other resource-dependent countries. Building on the literature critiquing business-case rationales and strategies as a means to achieve women’s equality in the workplace, we examine the business case for employing more women as advanced by the Australian mining industry. Specifically, we apply a discourse analysis to seven substantial, publically-available documents produced by the industry’s national and state peak organizations between 2005 and 2013. Our study makes two contributions. First, we map the features of the business case at the sectoral rather than firm or workplace level and examine its public mobilization. Second, we identify the construction and deployment of a normative identity – ‘the ideal mining woman’ – as a key outcome of this business-case discourse. Crucially, women are therein positioned as individually responsible for gender equality in the workplace.

ACE research briefing paper 007 : Ken Talbot - an entrepreneur's contribution to the growth of the Australian Mining Industry

Ken Talbot was one of Australian mining’s most successful entrepreneurs and rose to the top of his industry to become one of Australia’s wealthiest men. Although the nation’s resources industry is synonymous with global names such as Xstrata, BHP Billiton and Rio Tinto, Ken was an individual who made a big impact on the development and growth of the sector. This case study examines Ken’s achievements, his transition from employee to entrepreneur, and the qualities that enabled him to succeed at such a high level. In particular, it focuses on his Jellinbah and Coppabella mining developments that directly led to the creation of Macarthur Coal and the Talbot Group. By the time of his premature death in an African plane crash in 2010, Ken had amassed a fortune estimated at almost $1 billion and was aged just 59. The last publically available Talbot Group annual report for calendar year 2009 showed that the investment portfolio of the group returned 113 per cent that year. Even throughout the global financial crisis the portfolio made a positive return on investment of no less than 10 per cent. Ken’s sense of mateship and his tremendous people skills were keys to his success in the mining industry and the wider community. In addition to excelling in business, he is also remembered for his philanthropy and leaving 30 per cent of his estate to charity through the Talbot Family Foundation.

The emergent imperatives from a design-led innovation engagement within the mining industry

This research seeks a better and more detailed understanding of the processes of implementing design-led innovation in the mining equipment technology services (METS) sector, in a context where the traditional approach to manufacturing is being challenged. This longitudinal research specifically investigated the barriers to design-led innovation and opportunities that developed throughout this research, to understand how the organisation and culture of a METS company evolved, in order to progress towards design-led change. The significance of these findings is shown in the combined implementation of design imperatives leading towards design-led change at all business levels of an organisational structure.

Water use and wastewater discharge of industrial sector in China

Problem of water scarcity has been increasingly severe in China. Though industrial sectors play important role for the rapid economic growth, and they consumes water and discharge wastewater. The purpose of this study is to examine the efficiency of water use and wastewater discharge in comparison with those of other inputs and production output in Chinese industry. Measuring efficiency of each input and output factor from 2002 to 2008, we find the average inefficiencies of industrial water use and industrial wastewater discharge are higher than those of capital, labor, and production output in China. In addition, the productivity levels to save water in the water shortage areas are not higher compared to the others. The water use inefficiency has a high dispersion especially in the regions where the amounts of water resources per capita is less than 3000 cubic meter.

Creative interoperability: A new concept to guide, understand and evaluate innovation by cross-sector collaboration

Creative digital media are increasingly utilized by companies in all industries. Here cases studies of creative media innovations in manufacturing, mining and education were facilitated and evaluated. The cases dealt respectively with designs in manufacturing, visualizing mining data, and developing tools for adult literacy. The difficulties of merging creative media teams into these different contexts were noted and the idea of creative interoperability was developed. Creative interoperability explains how creative teams can connect with other disciplines to bring about innovations.

East Asian audio-visual collaboration and the global expansion of Chinese media

In recent years, many of the world’s leading media producers, screenwriters, technicians and investors, particularly those in the Asia-Pacific region, have been drawn to work in the People's Republic of China (hereafter China or Mainland China). Media projects with a lighter commercial entertainment feel – compared with the heavy propaganda-oriented content of the past – have multiplied, thanks to the Chinese state’s newfound willingness to consider collaboration with foreign partners. This is no more evident than in film. Despite their long-standing reputation for rigorous censorship, state policymakers are now encouraging Chinese media entrepreneurs to generate fresh ideas and to develop products that will revitalise the stagnant domestic production sector. It is hoped that an increase in both the quality and quantity of domestic feature films, stimulated by an infusion of creativity and cutting-edge technology from outside the country, will help reverse China’s ‘cultural trade deficit’ (wenhua maoyi chizi) (Keane 2007).

Panel Cointegration of Chinese A and B Shares

This paper uses panel unit root and cointegration methods to test the stationarity of the premium on domestic investors’ A shares over foreign investors’ B shares and cointegration between the A and B share prices on the Chinese stock exchanges. We find that the A share price premium is nonstationary until 2001, when the A and B share markets were partially merged, and that the A and B share prices are cointegrated in the panel.Cointegration is more likely to be found for firms in the service sector and for firms that issued B shares recently.

Chinese immigrants to Finland: A qualitative study of housing, employment, access to health care and child care as sociological dimensions in their settlement process

The Master’s thesis is qualitative research based on interviews of 15 Chinese immigrants to Finland in order to provide a sociological perspective of the migration experience through the eyes of Chinese immigrants in the Finnish social welfare context. This research is mainly focused upon four crucial aspects of life in the settlement process: housing, employment, access to health care and child care. Inspired by Allardt’s theoretical framework ‘Having, Loving and Being’, social relationships and individual satisfaction are examined in the case of Chinese interviewees dealing with the four life aspects. Finland was not perceived as an attractive migration destination for most Chinese interviewees in the beginning. However, with longer residence in Finland, the Finnish social welfare system gradually became a crucial appealing factor in their permanent settlement in Finland. And meanwhile, social responsibility of attending their old parents in China, strong feelings of being isolated in Finland, and insufficient integration into the Finnish society were influential factors for their decision of returning to China. Social relationships with personal friends, migration brokers, schools, employers and family relatives had great influences in the four life aspects of Chinese immigrants in Finland. The social relationship with the Finnish social welfare sector is supportive to Chinese immigrants, but Chinese immigrants do not heavily rely on Finnish social protection. The housing conditions were greatly improved over time while the upward mobility in the Finnish labour market was not significant among Chinese immigrants. All Chinese immigrants were satisfied with their current housing by the time I interviewed them while most of them had subjective feelings of being alienated in the Finnish labour market, which seriously prevented them from integrating into the Finnish society. In general, Chinese immigrants were satisfied with the low cost of accessing the Finnish public health care services and affordable Finnish child day care services and financial subsidies for children from the Finnish social welfare sector. This research also suggests that employment is the central basis in well-being. Support from the Finnish social welfare sector can improve the satisfaction levels among immigrants, especially when it mitigates the effects of low-paid employment. As well, my empirical study of Chinese immigrants in Finland shows that Having (needs for materials), Loving (needs for social relations) and Being (needs for social integration) are all involved in the four concrete aspects (housing, employment, access to health care and child care).

Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

Species identification of Chinese sturgeon using acoustic descriptors and ascertaining their spatial distribution in the spawning ground of Gezhouba Dam

This study has developed an improved subjective approach of classification in conjunction with Step wise DFA analysis to discriminate Chinese sturgeon signals from other targets. The results showed that all together 25 Chinese sturgeon echo-signals were detected in the spawning ground of Gezhouba Dam during the last 3 years, and the identification accuracy reached 90.9%. In Stepwise DFA, 24 out of 67 variables were applied in discrimination and identification. PCA combined with DFA was then used to ensure the significance of the 24 variables and detailed the identification pattern. The results indicated that we can discriminate Chinese sturgeon from other fish species and noise using certain descriptors such as the behaviour variables, echo characteristics and acoustic cross-section characteristics. However, identification of Chinese sturgeon from sediments is more difficult and needs a total of 24 variables. This is due to the limited knowledge about the acoustic-scattering properties of the substrate regions. Based on identified Chinese sturgeon individuals, 18 individuals were distributed in the region between the site of Gezhouba Dam and Miaozui reach, with a surface area of about 3.4 km(2). Seven individuals were distributed in the region between Miaozui and Yanshouba reach, with a surface area of about 13 km(2).

Evaluation of in Situ DGT Measurements for Predicting the Concentration of Cd in Chinese Field-Cultivated Rice: Impact of Soil Cd:Zn Ratios

DGT (diffusive gradients in thin-films) has been proposed as a tool for predicting Cd concentrations in rice grain, but there is a lack of authenticating data. To further explore the relationship between DGT measured Cd and concentrations in rice cultivated in challenging, metal degraded, field locations with different heavy metal pollutant sources, 77 paired soil and grain samples were collected in Southern China from industrial zones, a "cancer village" impacted by mining waste and an organic farm. In situ deployments of DGT in flooded paddy rice rhizospheres were compared with a laboratory DGT assay on dried and rewetted soil. Total soil concentrations were a very poor predictor of plant uptake. Laboratory and field deployed DGT assays and porewater measurements were linearly related to grain concentrations in all but the most contaminated samples where plant toxicity occurred. The laboratory DGT assay was the best predictor of grain Cd concentrations, accommodating differences in soil Cd, pollutant source, and Cd:Zn ratios. Field DGT measurements showed that Zn availability in the flooded rice rhizospheres was greatly diminished compared to that of Cd, resulting in very high Cd:Zn ratios (0.1) compared to commonly observed values (0.005). These results demonstrate the potential of the DGT technique to predict Cd concentrations in field cultivated rice and demonstrate its robustness in a range of environments. Although, field deployments provided important details about in situ element stoichiometry, due to the inherent heterogeneity of the rice rhizosphere soils, deployment of DGT in dried and homogenized soils offers the best possibility of a soil screening tool.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

Análisis de las relaciones comerciales entre China y Colombia en el sector textil desde la perspectiva de las estrategias diplomáticas. Periodo 2003-2008

Esta monografía pretende examinar la relación existente entre el comercio bilateral Colombo-Chino en el sector textil y las estrategias diplomáticas establecidas por cada uno de estos países respecto al otro entre los años 2003 a 2008. En especifico se analiza de que manera dichas estrategias definen o han definido el rumbo del comercio binacional en este sector.