From the consciousness industry to the creative industries : consumer-created content, social network markets, & the growth of knowledge

In studies of media industries, too much attention has been paid to providers and firms, too little to consumers and markets. But with user-created content, the question first posed more than a generation ago by the uses & gratifications method and taken up by semiotics and the active audience tradition (‘what do audiences do with media?’), has resurfaced with renewed force. What’s new is that where this question (of what the media industries and audiences did with each other) used to be individualist and functionalist, now, with the advent of social networks using Web 2.0 affordances, it can be re-posed at the level of systems and populations as well.

Fashion as consumer entrepreneurship : emergent risk culture, social network markets, and the launch of 'Vogue' in China

China has a reputation as an economy based on utility: the large-scale manufacture of low-priced goods. But useful values like functionality, fitness for purpose and efficiency are only part of the story. More important are what Veblen called ‘honorific’ values, arguably the driving force of development, change and value in any economy. To understand the Chinese economy therefore, it is not sufficient to point to its utilitarian aspect. Honorific status-competition is a more fundamental driver than utilitarian cost-competition. We argue that ‘social network markets’ are the expression of these honorific values, relationships and connections that structure and coordinate individual choices. This paper explores how such markets are developing in China in the area of fashion and fashion media. These, we argue, are an expression of ‘risk culture’ for high-end entrepreneurial consumers and producers alike, providing a stimulus to dynamic innovation in the arena of personal taste and comportment, as part of an international cultural system based on constant change. We examine the launch of Vogue China in 2005, and China’s reception as a fashion player among the international editions of Vogue, as an expression of a ‘decisive moment’ in the integration of China into an international social network market based on honorific values.

How do retailers from emerging markets internationalize? : The case of Chilean retailers

This paper explores how retail firms from emerging markets internationalize and compete with multinational retailers from developed markets. Drawing on interviews with company managers, industry data and corporate reports, this paper provides insights into the successful internationalization process of two Chilean retailers in the Latin American region.

Service quality in Hong Kong : wet markets vs super markets

Purpose – The purpose of this paper is to determine consumer perceptions of service quality in wet markets and supermarkets in Hong Kong. Design/methodology/approach – A questionnaire was developed and distributed via a convenience sample to consumers in shopping malls in Causeway Bay, Mong Kok and Tsuen Wan. Findings – The study finds that supermarkets outperformed wet markets across all aspects of service quality as measured by SERVQUAL-P. Research limitations/implications – Implications suggest that wet market vendors are not providing the level of service quality demanded by their customers. In particular, findings suggest that wet market vendors need to improve the visual attractiveness of their stalls, work on making them look more professional and start using more modern equipment. Practical implications – Wet market vendors in conjunction with government representatives need to develop standards of service quality for wet markets across Hong Kong. This is imperative if the wet market model is to survive in what is a highly competitive food retailing industry. Without action, it appears that the supermarketization of the Hong Kong food retailing industry will continue unabated. Originality/value – This paper adds to a small but growing research stream examining service quality in the food retailing industry in Hong Kong. It provides empirical results that guide suggested actions for change.

Comparative assessment of characteristics influencing the industrial property markets in Sydney and Hong Kong

Industrial property is commonly located in a designated ‘industrial’ precinct. An industrial property has a specific design and a number of services to support industrial activities including manufacture, distribution and transportation. Although it has a unique characteristic, certain industrial factor might operate differently in different countries. The aim of this paper is to provide a comparison between the Sydney and Hong Kong industrial property characteristics and to highlight their similarities and differences. This exploratory research used secondary data to provide background information of government policy and market conditions. Two case studies were use to illustrate similarities, trends, differences and to explore town planning, specific property characteristics including location, design and layout. Then, analyse whether these factors influence the performance and value of an industrial asset. The location of industrial properties varies between each country and depends heavily on infrastructure. It was noted that the town planning restrictions not only vary between markets and cities but also between property lots. The market conditions of both industrial markets were investigated and the supply and demand and rental levels in both cities were distinctly opposite.

The impact of natural disasters on residential property markets

Over the past ten years various residential property markets throughout Australia in general and NSW in particular have been subject to substantial natural disasters. These occurrences have included floods, bushfires and hailstorms. In extreme cases the actual rectification costs have been up to AUD$1.5 billion, which occurred with the severe hailstorm in Sydney in April 1999 and cyclone Tracey in Darwin in 1974. Natural disasters such as severe storms and hailstorms have tended to be very indiscriminate in relation to frequency and the actual location of damage, whereas the nature of bushfire and flooding tends to be more defined. Although these extreme natural disasters tend to be infrequent, occurrences of floods and bushfires in residential property areas are more frequent, particularly as urban sprawl encroaches closer to national Parks, State recreation Parks and State forests. Considerable work has been carried out on flood effects on property markets by Bell (1999), Donnelly (1988), McClusky and Rausser (2001), Skrantz and Strickland (1987) in the US, and Chou and Shih (2001) in Taiwan. Fibbens (1994), Lambley and Cordery (1991) and Eves (1999, 2001, 2002) have carried out studies in relation to the effect of flooding on residential property values in the Sydney region, including the tracking of flood prone property values over time. However, no similar rigorous research has been carried out in relation to the impact of bushfires on residential property markets in the Sydney region.

Osteryoung square wave voltammetric determination of lactose in food samples by a derivative procedure

A method for determination of lactose in food samples by Osteryoung square wave voltammetry (OSWV) was developed. It was based on the nucleophilic addition reaction between lactose and aqua ammonia. The carbonyl group of lactose can be changed into imido group, and this increases the electrochemical activity in reduction and the sensitivity. The optimal condition for the nucleophilic addition reaction was investigated and it was found that in NH4Cl–NH3 buffer of pH 10.1, the linear range between the peak current and the concentration of lactose was 0.6–8.4 mg L−1, and the detection limits was 0.44 mg L−1. The proposed method was applied to the determination of lactose in food samples and satisfactory results were obtained.

Networks in the shadow of markets and hierarchies : calling the shots in the visual effects industry

The nature and organisation of creative industries and the creative economy has received increased attention in recent academic and policy literatures (Florida 2002; Grabher 2002; Scott 2006a). Constituted as one variant on new economy narratives, creativity, alongside knowledge, has been presented as a key competitive asset, Such industries – ranging from advertising, to film and new media – are seen as not merely expanding their scale and scope, but as leading edge proponents of a more general trend towards new forms of organization and economic coordination (Davis and Scase 2000). The idea of network forms (and the consequent displacement of markets and hierarchies) has been at the heart of attempts to differentiate the field economically and spatially. Across both the discussion of production models and work/employment relations is the assertion of the enhanced importance of trust and non-market relations in coordinating structures and practices. This reflects an influential view in sociological, management, geography and other literatures that social life is ‘intrinsically networked’ (Sunley 2008: 12) and that we can confidently use the term ‘network society’ to describe contemporary structures and practices (Castells 1996). Our paper is sceptical of the conceptual and empirical foundations of such arguments. We draw on a number of theoretical resources, including institutional theory, global value chain analysis and labour process theory (see Smith and McKinlay 2009) to explore how a more realistic and grounded analysis of the nature of and limits to networks can be articulated. Given space constraints, we cannot address all the dimensions of network arguments or evidence. Our focus is on inter and intra-firm relations and draws on research into a particular creative industry – visual effects – that is a relatively new though increasingly important global production network. Through this examination a different model of the creative industries and creative work emerges – one in which market rules and patterns of hierarchical interaction structure the behaviour of economic actors and remain a central focus of analysis. The next section outlines and unpacks in more detail arguments concerning the role and significance of networks, markets and hierarchies in production models and work organisation in creative industries and the ‘creative economy’.

The Evolution of the creative industries : creative clusters, creative citizens and social network markets 創意產業的演化 : 創意集群 ,創意公民, 社會網絡市場 [published in Chinese]

The creative industries are important because they are clustered at the point of attraction for a billion or more young people around the world. They're the drivers of demographic, economic and political change. They start from the individual talent of the creative artist and the individual desire and aspiration of the audience. These are the raw materials for innovation, change and emergent culture, scaled up to form new industries and coordinated into global markets based on social networks.

Dislodgement of commercial property public debt markets : the case of U.S. and Australia

The paper investigates if there are any discernible trends in the U.S. and Australian commercial property public debt markets with the onset of the global financial crisis (GFC). Commercial mortgage-backed securities and unsecured bonds issued by real estate investment trusts for the period 2000 to Q3:2009 are reviewed. It is shown that events in the equity markets have an impact on the pricing of these two instruments. Furthermore, the impact of subdued activity in these financing instruments on the commercial property market is discussed.

Numerical investigations of linear least squares methods for derivative estimation

The results of a numerical investigation into the errors for least squares estimates of function gradients are presented. The underlying algorithm is obtained by constructing a least squares problem using a truncated Taylor expansion. An error bound associated with this method contains in its numerator terms related to the Taylor series remainder, while its denominator contains the smallest singular value of the least squares matrix. Perhaps for this reason the error bounds are often found to be pessimistic by several orders of magnitude. The circumstance under which these poor estimates arise is elucidated and an empirical correction of the theoretical error bounds is conjectured and investigated numerically. This is followed by an indication of how the conjecture is supported by a rigorous argument.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.