Estimating the potential impact of entry fees for marine parks on dive tourism in South East Asia

Marine reserves are increasingly being established as a mechanism to protect marine biodiversity and sensitive habitats. As well as providing conservation benefits, marine reserves provide benefits to recreational scuba divers who dive within the reserve, as well as to recreational and commercial fishers outside the reserve through spill-over effects. To ensure benefits are being realised, management of marine reserves requires ongoing monitoring and surveillance. These are not costless, and many marine reserve managers impose an entry fee. In some countries, dive tourism is major income source to coastal industries, and a concern is that high entry fees may dissuade divers. In this paper, the price elasticity of demand for dive tourism in three countries in South East Asia – Indonesia, Thailand and Malaysia – is estimated using a travel-cost model. From the model, the total non-market use value associated with diving in the area is estimated to be in the order of US$4.5 billion a year. The price elasticity of demand in the region is highly inelastic, such that increasing the cost of diving through a management levy would have little impact on total diver numbers.

Modelling the impact of traffic incidents on travel time reliability

Traffic incidents are recognised as one of the key sources of non-recurrent congestion that often leads to reduction in travel time reliability (TTR), a key metric of roadway performance. A method is proposed here to quantify the impacts of traffic incidents on TTR on freeways. The method uses historical data to establish recurrent speed profiles and identifies non-recurrent congestion based on their negative impacts on speeds. The locations and times of incidents are used to identify incidents among non-recurrent congestion events. Buffer time is employed to measure TTR. Extra buffer time is defined as the extra delay caused by traffic incidents. This reliability measure indicates how much extra travel time is required by travellers to arrive at their destination on time with 95% certainty in the case of an incident, over and above the travel time that would have been required under recurrent conditions. An extra buffer time index (EBTI) is defined as the ratio of extra buffer time to recurrent travel time, with zero being the best case (no delay). A Tobit model is used to identify and quantify factors that affect EBTI using a selected freeway segment in the Southeast Queensland, Australia network. Both fixed and random parameter Tobit specifications are tested. The estimation results reveal that models with random parameters offer a superior statistical fit for all types of incidents, suggesting the presence of unobserved heterogeneity across segments. What factors influence EBTI depends on the type of incident. In addition, changes in TTR as a result of traffic incidents are related to the characteristics of the incidents (multiple vehicles involved, incident duration, major incidents, etc.) and traffic characteristics.

Destination image: identifying baseline perceptions of Brazil, Argentina and Chile in the nascent Australian long haul travel market

While the popularity of destination image research has increased exponentially in the literature, there has been relatively little published about perceptions held by international consumers of destinations in South America. The purpose of this paper is to report the findings of a research project that aimed to identify the baseline market perceptions of Brazil, Argentina and Chile amongst Australian residents, at the time of the emergence of this long haul market. Of interest was the extent to which Australians differentiate the three distinct countries versus perceiving the continent as a gestalt. These baseline perceptions enable the effectiveness of future marketing communications in Australia by the three national tourism offices to be monitored over time. Importance-Performance Analysis (IPA) is used as a practical analytical tool to guide decision makers. In terms of operationalising destination image, a key research finding was the very high ratio or participants using the ‘Don’t know’ (DK) option for each destination performance scale item. This finding has practical implications for the destination marketers, as well as for researchers engaged in destination image research in long haul and/or emerging markets.

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Individual process management: A first step towards the conceptualization of individual activities

Understanding activities of individuals is of major importance because their actions are the main foundation of economic activity. However, there is a lack of understanding with regard to how individual activities are characterised. Thus, we develop a first conceptual classification for individual activities extending the view on business processes. The classification scheme contains personal care, education, professional work, domestic work, leisure and travel as primary activities and individual organization, procurement, information gathering and self-expression as secondary activities. We extend mainly prior literature on customer management by structuring processes of individuals independently from their status as customer. This enables new theoretical insights in the way companies can design their offers from a strategic point of view. Companies can use IPM to systematically analyze individual processes independent from specific products and services which is assumed to foster the development of innovative product and service offers.

Links between emotional job demands and occupational well-being: Age differences depend on type of demand

In the growing health care sector, meeting emotional job demands is crucial to organizational outcomes but may negatively affect employees’ well-being. Drawing on the emotional aging literature, we predicted that two common emotional job demands, display demands (expressing positive, negative, and neutral emotions toward clients) and sensitivity demands (knowing what the client is feeling), affect older health care workers’ occupational well-being differently than young workers, as indicated by their job satisfaction and need for recovery. Survey data from employees of senior care homes (N = 141, aged between 17 and 62 years) confirmed the moderating role of age for links between emotional job demands and occupational well-being indicators. Emotional display demands were generally positively associated with emotional dissonance; however, the association between demands to display neutral emotions and emotional dissonance was stronger among young compared with older employees. In contrast, among older but not young employees, emotional dissonance was negatively associated with job satisfaction, and emotional sensitivity demands were positively associated with need for recovery. These findings suggest that age may confer both advantages (facing neutral display demands) and vulnerabilities (facing emotional dissonance and sensitivity demands) in managing emotional job demands.

Indoor air quality and energy management through real–time sensing in commercial buildings

Rapid growth in the global population requires expansion of building stock, which in turn calls for increased energy demand. This demand varies in time and also between different buildings, yet, conventional methods are only able to provide mean energy levels per zone and are unable to capture this inhomogeneity, which is important to conserve energy. An additional challenge is that some of the attempts to conserve energy, through for example lowering of ventilation rates, have been shown to exacerbate another problem, which is unacceptable indoor air quality (IAQ). The rise of sensing technology over the past decade has shown potential to address both these issues simultaneously by providing high–resolution tempo–spatial data to systematically analyse the energy demand and its consumption as well as the impacts of measures taken to control energy consumption on IAQ. However, challenges remain in the development of affordable services for data analysis, deployment of large–scale real–time sensing network and responding through Building Energy Management Systems. This article presents the fundamental drivers behind the rise of sensing technology for the management of energy and IAQ in urban built environments, highlights major challenges for their large–scale deployment and identifies the research gaps that should be closed by future investigations.

Understanding urban rail travel for improved patronage forecasting

Improved forecasting of urban rail patronage is essential for effective policy development and efficient planning for new rail infrastructure. Past modelling and forecasting of urban rail patronage has been based on legacy modelling approaches and often conducted at the general level of public transport demand, rather than being specific to urban rail. This project canvassed current Australian practice and international best practice to develop and estimate time series and cross-sectional models of rail patronage for Australian mainland state capital cities. This involved the implementation of a large online survey of rail riders and non-riders for each of the state capital cities, thereby resulting in a comprehensive database of respondent socio-economic profiles, travel experience, attitudes to rail and other modes of travel, together with stated preference responses to a wide range of urban travel scenarios. Estimation of the models provided a demonstration of their ability to provide information on the major influences on the urban rail travel decision. Rail fares, congestion and rail service supply all have a strong influence on rail patronage, while a number of less significant factors such as fuel price and access to a motor vehicle are also influential. Of note, too, is the relative homogeneity of rail user profiles across the state capitals. Rail users tended to have higher incomes and education levels. They are also younger and more likely to be in full-time employment than non-rail users. The project analysis reported here represents only a small proportion of what could be accomplished utilising the survey database. More comprehensive investigation was beyond the scope of the project and has been left for future work.