Network Externalities,Incumbent’s Competitive Advantage and the Degree of Openness of Software Start-Ups

This paper proposes a formal model that analyzes the degree of openness chosen by start-ups when entering the software industry. In line with the literature, we label as degree of openness the extent to which software start-ups mix open source (OS) and proprietary solutions in the portfolio of software products they offer. We relate the choice of the degree of openness to two key characteristics of the market segments in which software start-ups operate: the strength of the network externalities and the competitive advantage of the incumbent. Specifically, by modelling (price) competition between an incumbent and an entrant in two ways, i.e., the entrant is price-setter or price-taker, we derive the necessary condition(s) in terms of the strength of network externalities for observing the adoption of a business model that comprises the offering of both proprietary and OS solutions by the entrant (i.e., hybrid business model). Then, we highlight that, if a hybrid business model is the choice, the degree of openness chosen in equilibrium increases along with both the strength of the network externalities and the competitive advantage of the incumbent. This result holds indifferently whether the software start-up is modelled as a price-setter or a price-taker. An empirical test run on a sample of European start-ups in the software industry supports these theoretical predictions.     

Information Sharing Among Disaster Responders - An Interactive Spreadsheet-Based Collaboration Approach

Recent natural disasters have led crisis management organizations to revise their protocols so as to rely on the contribution of a wider range of actors, including simple citizens as well as expert operators, to support decision making activities. Reliable and timely information sharing among members of distributed teams of disaster responders has become paramount for the success of the overall crisis management process. In this paper we propose a crisis management system based on spreadsheet-mediated collaboration among on-site responders and decision makers. To share data a common spreadsheet artifact has been developed by using a participatory design approach which is accessed through mobile user interfaces. The evaluation results showed that the use of the spreadsheet artifact has resulted in more effective decision making relating to set of earthquake management scenarios in high-risk areas located in Italy.     

Synthesis and characterization of epoxidized styrene–butadiene rubber/silicon dioxide hybrid materials

Hybrid materials were synthesized from epoxidized (68, 43, or 14%) styrene–butadiene rubber (SBR) and the hydrolysis product of tetraethoxysilane (TEOS) in situ under ultrasonic irradiation. The products were characterized with thermal analysis (differential scanning calorimetry and thermogravimetric analysis), stress–strain tests, scanning electron microscopy (including energy‐dispersive spectrometry), and swelling in tetrahydrofuran and water. The most transparent were those prepared from SBR with the highest degree of epoxidation, whereas those obtained from less epoxidized SBR and with larger amounts of TEOS showed distinct phases that could be considered two hybrid phases (one rich in TEOS and another rich in SBR). © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 798–803, 2004     

Crosslink reaction of natural rubber with thiuram sulphur donors in the presence of a thiuram monosulfide

The vulcanization of natural rubber was studied with the sulfurating agents dipentamethylene thiuram tetrasulfide (DPTT) and tetramethylene thiuram disulfide (TMTD) in the presence of tetramethyl thiuram monosulfide (TMTM). This last accelerant affects the rate and efficiency of the vulcanization as well as the structures of crosslinks formed by the two sulphur donors. It may give rise to a polymerization between adjacent double bonds and generate a inhomogeneous crosslink distribution with an adverse effect on physical properties. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 491–499, 2002     

Nonionic water‐soluble polymer: Preparation,characterization, and application of poly(1‐vinyl‐2‐pyrrolidone‐co‐hydroxyethylmethacrylate) as a polychelatogen

The free‐radical copolymerization of water‐soluble poly(1‐vinyl‐2‐pyrrolidone‐co‐hydroxyethylmethacrylate) was carried out with a feed monomer ratio of 75:25 mol %, and the total monomer concentration was 2.67M. The synthesis of the copolymer was carried out in dioxane at 70°C with benzoyl peroxide as the initiator. The copolymer composition was obtained with elemental analysis and ¹H‐NMR spectroscopy. The water‐soluble polymer was characterized with elemental analysis, Fourier transform infrared, ¹H‐ and ¹³C‐NMR spectroscopy, and thermal analysis. Additionally, viscosimetric measurements of the copolymer were performed. The thermal behavior of the copolymer and its complexes were investigated with differential scanning calorimetry (DSC) and thermogravimetry techniques under a nitrogen atmosphere. The copolymer showed high thermal stability and a glass transition in the DSC curves. The separation of various metal ions by the water‐soluble poly(1‐vinyl‐2‐pyrrolidone‐co‐hydroxyethylmethacrylate) reagent in the aqueous phase with liquid‐phase polymer‐based retention was investigated. The method was based on the retention of inorganic ions by this polymer in a membrane filtration cell and subsequent separation of low‐molar‐mass species from the polymer/metal‐ion complex formed. Poly(1‐vinyl‐2‐pyrrolidone‐co‐hydroxyethylmethacrylate) could bind metal ions such as Cr(III), Co(II), Zn(II), Ni(II), Cu(II), Cd(II), and Fe(III) in aqueous solutions at pHs 3, 5, and 7. The retention percentage for all the metal ions in the polymer was increased at pH 7, at which the maximum retention capacity could be observed. The interaction of inorganic ions with the hydrophilic polymer was determined as a function of the pH and filtration factor. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 178–185, 2006     

Evaluation of the salt leaching method for the production of ethylene propylene diene monomer rubber foams

The thermomechanical behavior of ethylene propylene diene monomer (EPDM) foams produced with the salt leaching method has been investigated and compared with the behavior of EPDM foams obtained from conventional blowing agents. Moreover, the salt-leaching process has been optimized to minimize salt residues and the influence of different parameters (such as average particle size and particle size distribution) has been investigated. Scanning electron microscopy and density measurements highlighted that salt-leaching leads to the formation of open-cell porosity with cell dimensions of around 60 to 80 μm, while foams obtained with the two traditional foaming agents lead to closed-cell porosity. Compression set values indicate that the behavior of the foams produced with salt leaching are more similar to the unfoamed rubber, characterized by higher elasticity and low residual deformation. Two theoretical models were successfully applied to the compression curves (Mooney-Rivlin and Exponential-Logarithmic) and they highlighted the effect of foaming on the properties of EPDM rubber and in particular the higher chain extensibility obtained through the salt leaching foaming method.     

A multimodal feature learning approach for sentiment analysis of social network multimedia

In this paper we investigate the use of a multimodal feature learning approach, using neural network based models such as Skip-gram and Denoising Autoencoders, to address sentiment analysis of micro-blogging content, such as Twitter short messages, that are composed by a short text and, possibly, an image. The approach used in this work is motivated by the recent advances in: i) training language models based on neural networks that have proved to be extremely efficient when dealing with web-scale text corpora, and have shown very good performances when dealing with syntactic and semantic word similarities; ii) unsupervised learning, with neural networks, of robust visual features, that are recoverable from partial observations that may be due to occlusions or noisy and heavily modified images. We propose a novel architecture that incorporates these neural networks, testing it on several standard Twitter datasets, and showing that the approach is efficient and obtains good classification results.     

Privacy Preserving Geo-Linkage in the Big Urban Data Era

Big data technologies and a range of Government open data initiatives provide the basis for discovering new insights into cities; how they are planned, how they managed and the day-to-day challenges they face in health, transport and changing population profiles. The Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) project is one example of such a big data initiative that is currently running across Australia. AURIN provides a single gateway providing online (live) programmatic access to over 2000 data sets from over 70 major and typically definitive data-driven organizations across federal and State government, across industry and across academia. However whilst open (public) data is useful to bring data-driven intelligence to cities, more often than not, it is the data that is not-publicly accessible that is essential to understand city challenges and needs. Such sensitive (unit-level) data has unique requirements on access and usage to meet the privacy and confidentiality demands of the associated organizations. In this paper we highlight a novel geo-privacy supporting solution implemented as part of the AURIN project that provides seamless and secure access to individual (unit-level) data from the Department of Health in Victoria. We illustrate this solution across a range of typical city challenges in localized contexts around Melbourne. We show how unit level data can be combined with other data in a privacy-protecting manner. Unlike other secure data access and usage solutions that have been developed/deployed, the AURIN solution allows any researcher to access and use the data in a manner that meets all of the associated privacy and confidentiality concerns, without obliging them to obtain ethical approval or any other hurdles that are normally put in place on access to and use of sensitive data. This provides a paradigm shift in secure access to sensitive data with geospatial content.