Open source innovation in physical products : advantages and disadvantages, a corporate perspective

A better understanding of Open Source Innovation in Physical Product (OSIP) might allow project managers to mitigate risks associated with this innovation model and process, while developing the right strategies to maximise OSIP outputs. In the software industry, firms have been highly successful using Open Source Innovation (OSI) strategies. However, OSI in the physical world has not been studied leading to the research question: What advantages and disadvantages do organisations incur from using OSI in physical products? An exploratory research methodology supported by thirteen semi-structured interviews helped us build a seven-theme framework to categorise advantages and disadvantages elements linked with the use of OSIP. In addition, factors impacting advantage and disadvantage elements for firms using OSIP were identified as: „h Degree of openness in OSIP projects; „h Time of release of OSIP in the public domain; „h Use of Open Source Innovation in Software (OSIS) in conjunction with OSIP; „h Project management elements (Project oversight, scope and modularity); „h Firms. Corporate Social Responsibility (CSR) values; „h Value of the OSIP project to the community. This thesis makes a contribution to the body of innovation theory by identifying advantages and disadvantages elements of OSIP. Then, from a contingency perspective it identifies factors which enhance or decrease advantages, or mitigate/ or increase disadvantages of OSIP. In the end, the research clarifies the understanding of OSI by clearly setting OSIP apart from OSIS. The main practical contribution of this paper is to provide manager with a framework to better understand OSIP as well as providing a model, which identifies contingency factors increasing advantage and decreasing disadvantage. Overall, the research allows managers to make informed decisions about when they can use OSIP and how they can develop strategies to make OSIP a viable proposition. In addition, this paper demonstrates that advantages identified in OSIS cannot all be transferred to OSIP, thus OSIP decisions should not be based upon OSIS knowledge.

General characteristics of anticipated user experience (AUX) with interactive products

Providing a positive user experience (UX) has become the key differentiator for products to win a competition in mature markets. To ensure that a product will support enjoyable experiences for its users, assessment of UX should be conducted early during the design and development process. However, most UX frameworks and evaluation techniques focus on understanding and assessing user’s experience with functional prototypes or existing products. This situation delays UX assessment until the late phases of product development which may result in costly design modifications and less desirable products. A qualitative study was conducted to investigate anticipated user experience (AUX) to address this issue. Twenty pairs of participants were asked to imagine an interactive product, draw their product concept, and anticipate their interactions and experiences with it. The data was analyzed to identify general characteristics of AUX. We found that while positive AUX was mostly related to an imagined/desired product, negative AUX was mainly associated with existing products. It was evident that the pragmatic quality of product was fundamental, and significantly influenced user’s anticipated experiences. Furthermore, the hedonic quality of product received more focus in positive than negative AUX. The results also showed that context, user profile, experiential knowledge, and anticipated emotion could be reflected in AUX. The understanding of AUX will help product designers to better foresee the users’ underlying needs and to focus on the most important aspects of their positive experiences, which in turn facilitates the designers to ensure pleasurable UX from the start of the design process.

“More tick-the-box”: the challenge of promoting interdisciplinary learning in the middle years through the Australian history curriculum

The Australian Curriculum marks national reforms in social science education, first with the return to the disciplines of history and geography and second, through a new approach to interdisciplinary learning. This paper raises the question of whether the promise of interdisciplinary learning can be realised in the middle years of schooling if teachers have to teach history as a discipline rather than within an over-arching integrated curriculum framework. The paper explores the national blueprints and considers the national history curriculum in light of theories of teachers’ knowledge and middle school education. Evidence from teacher interviews indicates that historical understanding can be achieved through integrated frameworks to meet the goals of middle schooling.

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Top Ten Box Office Blockbusters of All Time

‘Top Ten Box Office Blockbusters in Dollars’, is an ongoing series of works that represent the production budgets and worldwide gross profits of the top ten grossing films of all time. By displaying this data on top of the full running time of each blockbuster, the viewer’s attention is drawn back and forth between the amassing dollar figures, and the original film’s highly polished presentation. In doing so, the work aims to provide a new opportunity to enjoy these immensely popular films with a new sense of value. The exhibition was selected for the Artistic Program at MetroArts, Brisbane in 2010

Using performance management systems as identity products

This paper explores how the effective use of performance management systems (PMS) essentialises collective identities through the use of textual performances. The discursive effect of PMS operates to simplify members’ logic to allow them to understand and negotiate the complex nature of collective performance. Two case studies, drawing on a qualitative study of the implementation of PMS in two public sector organisations, point to the unique contribution of symbolic effects of one popular PMS, the balanced scorecard (BSC). Findings suggest that the BSC visualising the trajectory of achieving organisational vision through multiple perspectives, measures and linkages is a valuable identity product to achieve organisational success. The case studies also provide an analysis that contrasts aspects of the diffusion and promotion of collective identities through the use of the BSC. This demonstrates that clear direction in the identity management process is an important factor in the design and implementation of successful PMS programs. The value of this paper is to heighten recognition of the symbolic agency of PMS, as it serves as a subtle mechanism for identity management, and also to foster the collaboration of communication specialists and management accountants to achieve common organisational goals.

Unlocking black box models of leadership effectiveness: Exploring alternative research and policy metaphors

There is an intimate interconnectivity between policy guidelines defining reform and the delineation of what research methods would be subsequently applied to determine reform success. Research is guided as much by the metaphors describing it as by the ensuing empirical definition of actions of results obtained from it. In a call for different reform policy metaphors Lumby and English (2010) note, “The primary responsibility for the parlous state of education... lies with the policy makers that have racked our schools with reductive and dehumanizing processes, following the metaphors of market efficiency, and leadership models based on accounting and the characteristics of machine bureaucracy” (p. 127)

Integrating collaborative filtering and search-based techniques for personalized online product recommendation

The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

Developing a fuzzy multi-criteria decision-making model for selecting design-build operational variations

Many academic researchers have conducted studies on the selection of design-build (DB) delivery method; however, there are few studies on the selection of DB operational variations, which poses challenges to many clients. The selection of DB operational variation is a multi-criteria decision making process that requires clients to objectively evaluate the performance of each DB operational variation with reference to the selection criteria. This evaluation process is often characterized by subjectivity and uncertainty. In order to resolve this deficiency, the current investigation aimed to establish a fuzzy multicriteria decision-making (FMCDM) model for selecting the most suitable DB operational variation. A three-round Delphi questionnaire survey was conducted to identify the selection criteria and their relative importance. A fuzzy set theory approach, namely the modified horizontal approach with the bisector error method, was applied to establish the fuzzy membership functions, which enables clients to perform quantitative calculations on the performance of each DB operational variation. The FMCDM was developed using the weighted mean method to aggregate the overall performance of DB operational variations with regard to the selection criteria. The proposed FMCDM model enables clients to perform quantitative calculations in a fuzzy decision-making environment and provides a useful tool to cope with different project attributes.

Integration of opinion into customer analysis model

Nowadays, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes. A use case study is also presented in this paper to show the advantages of using OLAP and data cubes to analyze costumers’ opinions.

The stimulation of proliferation and differentiation of periodontal ligament cells by the ionic products from Ca7Si2P2O16 bioceramics

The ultimate goal of periodontal tissue engineering is to produce predictable regeneration of alveolar bone, root cementum, and periodontal ligament, which are lost as a result of periodontal diseases. To achieve this goal, it is of great importance to develop novel bioactive materials which could stimulate the proliferation, differentiation and osteogenic/cementogenic gene expression of periodontal ligament cells (PDLCs) for periodontal regeneration. In this study, we synthesized novel Ca7Si2P2O16 ceramic powders for the first time by the sol–gel method and investigated the biological performance of PDLCs after exposure to different concentrations of Ca7Si2P2O16 extracts. The original extracts were prepared at 200 mg ml-1 and further diluted with serum-free cell culture medium to obtain a series of diluted extracts (100, 50, 25, 12.5 and 6.25 mg ml–1). Proliferation, alkaline phosphatase(ALP) activity, Ca deposition, and osteogenesis/cementogenesis-related gene expression (ALP, Col I, Runx2 and CEMP1) were assayed for PDLCs on days 7 and 14. The results showed that the ionic products from Ca7Si2P2O16 powders significantly stimulated the proliferation, ALP activity, Ca deposition and osteogenesis/cementogenesisrelated gene expression of PDLCs. In addition, it was found that Ca7Si2P2O16 powders had excellent apatite-mineralization ability in simulated body fluids. This study demonstrated that Ca7Si2P2O16 powders with such a specific composition possess the ability to stimulate the PDLC proliferation and osteoblast/cemenoblast-like cell differentiation, indicating that they are a promising bioactive material for periodontal tissue regeneration application.

What's in your tool box?

This is a professional practice paper for Psychology practitioners to reflect on their skills and therapeutic practices. A Master- practitioner model or Artizan - apprentice analogy is used to understand the development of a practicing psychologist from his/her "salad days" (when we are green [Shakespeare- Anthony and Cleopatra]) to our Autumn years in the profession.

Lean supply chain performance evaluation method

Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost which demand of continuous improvements techniques. In this paper, we propose a fuzzy based performance evaluation method for lean supply chain. To understand the overall performance of cost competitive supply chain, we investigate the alignment of market strategy and position of the supply chain. Competitive strategies can be achieved by using a different weight calculation for different supply chain situations. By identifying optimal performance metrics and applying performance evaluation methods, managers can predict the overall supply chain performance under lean strategy.