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As a consequence of rapid urbanisation and globalisation, cities have become the engines of population and economic growth. Hence, natural resources in and around the cities have been exposed to externalities of urban development processes. This paper introduces a new sustainability assessment approach that is tested in a pilot study. The paper aims to assist policy‐makers and planners investigating the impacts of development on environmental systems, and produce effective policies for sustainable urban development.

The paper introduces an indicator‐based indexing model entitled “Indexing Model for the Assessment of Sustainable Urban Ecosystems” (ASSURE). The ASSURE indexing model produces a set of micro‐level environmental sustainability indices that is aimed to be used in the evaluation and monitoring of the interaction between human activities and urban ecosystems. The model is an innovative approach designed to assess the resilience of ecosystems towards impacts of current development plans and the results serve as a guide for policy‐makers to take actions towards achieving sustainability.

The indexing model has been tested in a pilot case study within the Gold Coast City, Queensland, Australia. This paper presents the methodology of the model and outlines the preliminary findings of the pilot study. The paper concludes with a discussion on the findings and recommendations put forward for future development and implementation of the model.

Presently, there is a few sustainability indices developed to measure the sustainability at local, regional, national and international levels. However, due to challenges in data collection difficulties and availability of local data, there is no effective assessment model at the micro‐level that the assessment of urban ecosystem sustainability accurately. The model introduced in this paper fills this gap by focusing on parcel‐scale and benchmarking the environmental performance in micro‐level.

The purpose of this study is to investigate whether the direct and indirect sentiment measures are similar in explaining mutual fund performance.

The authors examine the role of direct and indirect sentiment measures on fund performance in two scenarios. One is when a sentiment measure is added to market models, and the other is when it used independently. Also, the authors propose a system science theory to explain the findings.

The authors find that both direct and indirect sentiment measures are integral to the benchmark models to explain fund performance. However, while the explanatory power of the direct sentiment index is robust when used independently or collectively, the indirect sentiment measures can explain fund performance only when used along with other market factors.

Given the number of sentiment measures, it is critical to determine whether these measures contain the same information of sentiment. This paper represents the first study on this topic.

The purpose of this paper is to examine if temporal aggregation matters in the construction of house price indices and to test the accuracy of alternative index construction methods.

Five index construction models based on the hedonic, repeat‐sales and hybrid methods are examined. The accuracy of the alternative index construction methods are examined using the mean squared error and out‐of‐sample technique. Monthly, quarterly, semi‐yearly and yearly indices are constructed for each of the methods and six null hypotheses are tested to examine the temporal aggregation effect.

Overall, the hedonic is the best method to use. While running separate regressions to estimate the index is best at the broader level of time aggregation like the annual, pooling data together and including time dummies to estimate the index is the best at the lower level of time aggregation. The repeat‐sales method is the least preferred method. The results also show that it is important to limit time to the lowest level of temporal aggregation when construction property price indices.

This paper provides alternative method, the mean squared error method based on an out‐of‐sample technique to evaluate the accuracy of alternative index construction methods.

The introduction of financial products like the property derivatives and home equity insurances to the financial market calls for accurate and robust property price indices. However, the index method and level of temporal aggregation to use still remain unresolved in the index construction literature. This paper contributes to fill these gaps.

The purpose of this paper is to test the accuracy of the explicit time variable (ETV) and the strictly cross-sectional (SCS) hedonic models when constructing house price indices in developing markets using Ghana as a case study.

The quantitative research methodology is adopted where the accuracy of the two hedonic models used in the construction of house price indices is examined using the mean squared error (MSE) and out-of-sample technique. Yearly indices are constructed for each of the models using 60 per cent of the sample data and 40 per cent is used to forecast house prices for each observations based on which the MSEs are calculated.

The two models produce similar house price trend but the SCS model is more volatile. The ETV model produces the lower MSE, suggesting that it is better to pool data together and includes time dummies (ETV) to estimate indices rather than running separate regressions (SCS) to estimate the index. Using the Morgan–Granger–Newbold test, it is found that indeed the difference between the forecast errors of the two models are statistically significant on a 1 per cent level confirming the accuracy of the ETV model over the SCS model.

This paper has produced convincing results recommending the use of the ETV hedonic model to construct house price indices which is of use to practitioners and academics.

The introduction of financial products like the property derivatives and home equity insurances to the financial market calls for accurate and robust property price indices and the hedonic method is mostly used to construct these indices. While there have been a lot of test conducted as to which variant of the hedonic method to use in developed markets, little is known about the developing markets. This paper contributes to fill these gaps.

This paper is concerned with recent work in the theory of information retrieval. More particularly, it is concerned with theories which tackle the problem of retrieval performance, in a sense which will be explained. The aim is not an exhaustive survey of such work; rather it is an analysis and synthesis of those contributions which I feel to be important or find interesting.

Model order reduction (MOR) has been widely used in the electric networks but little has been done to reduce higher index differential algebraic equations (DAEs). The paper aims to discuss these issues.

Most methods first do an index reduction before reducing a higher DAE but this can lead to a loss of physical properties of the system.

The paper presents a MOR method for DAEs called the index-aware MOR (IMOR) which can reduce a DAE while preserving its physical properties such as the index. The feasibility of this method is tested on real-life electric networks.

MOR has been widely used to reduce large systems from electric networks but little has been done to reduce higher index DAEs. Most methods first do an index reduction before reducing a large system of DAEs but this can lead to a loss of physical properties of the system. The paper presents a MOR method for DAEs called the IMOR which can reduce a DAE while preserving its physical properties such as the index. The feasibility of this method is tested on real-life electric networks.

The main purpose of this research was to develop a universal model to evaluate the perceived value of tourism services and satisfaction with, and loyalty to, destinations from the consumers’ perspective and demonstrated the model’s applicability in this context.

Using the structural equation model, cause and effect relationships were identified between the proposed model’s constructs, and indices of quality, satisfaction and loyalty among tourists were estimated. This system was applied to a large set of data collected with a structured questionnaire distributed to tourists visiting the city of Seville through a non-probabilistic sampling by intentional quotas method. In total, 922 valid surveys were obtained.

The indices show that tourists who visit Seville report a high level of loyalty to, and satisfaction with, this place because of the perceived quality of a variety of services. It is observed that the perceived quality index is much higher (17.95 per cent) than the expected quality index, so the quality of the service received by the tourist during his/her visit to Seville is described as excellent.

Regarding this study’s limitations, other variables could have been included that influence tourist satisfaction, such as the climate, the effect of advertising medium, the prices and the emotional components. In addition, surveying tourists’ expectations before their visit is virtually impossible, as is surveying the same tourists again about their perceived value and satisfaction after their visit. Future lines of research could focus on the intersection of information between tourism offer and demand, providing information about an appropriate balance in specific markets. The proposed model can also be applied to other tourism places that are similar to Seville’s tourism offer, allowing useful comparisons and identification of critical points and ways to improve customer satisfaction continuously.

By establishing indices of expected and perceived quality and satisfaction and loyalty among tourists, tourism authorities and different economic agents involved in this sector can receive objective information about the results and quality of tourism services. Tourism managers, thus, can set objectives for improvements and competitiveness, as well as building and maintaining customer loyalty. At the same time, these indices allow comparisons with other organisations and places. By facilitating greater transparency in the measurement of quality and satisfaction, service providers connected to tourism can create a platform on which to articulate clearly their contributions to interested parties and local communities.

These results constitute strategies and findings that any tourism place has to consider in the planning and development of its products. Therefore the model can help to encourage a long-term market perspective among tourism sector regulators, investors and agencies. With the information obtained with this model, areas needing improvement can be identified and the appropriate procedures can be put into practice to improve the tourism offer, adjusting it to meet travellers’ needs according to their motivations to travel to the destination. Residents also can benefit from these measures, as their quality of life will improve through upgrades of the city’s tourism facilities.

The unique contribution of the present study lies in how the indices or indicators of quality of, satisfaction with and loyalty to destinations among tourists are easily measured by applying structural equation modelling. A new approach to measure satisfaction, loyalty and quality is used based on a scale from 0 to 100, and the index results are very useful for comparing different tourist places.

Water balance is measured by transpiration, which has a significant impact on the performance of geotechnical infrastructure (vegetated slopes), ecological infrastructure (wetlands), urban infrastructure (green roof, biofiltration units) and agricultural infrastructure. Past studies have formulated models using analytical modeling to evaluate the transpiration index based on energy balance and suction. In circumstance of impartial and uncertain information about the root and shoot properties and its effect on the transpiration index, the present work aims to introduce the new optimization algorithm of genetic programming (GP) to quantify and optimize the transpiration index of plant.

The GP framework, having objective function of structural risk minimization, is used for formulating the transpiration index model. The statistical metrics with 2D and 3D analyses of the models are conducted to determine its accuracy and understand the transpiration process.

The model analysis reveals that the proposed model extrapolates the transpiration index values accurately based on five inputs. 2D and 3D relationships between the transpiration index and the five inputs suggest that the total root area has the highest impact on the transpiration index followed by shoot length and root biomass. There is not much impact of the shoot mass and stem basal diameter on the transpiration index. It was also found that the transpiration index increases with an increase in total root area and root biomass.

This work is a first-of-its-kind study involving the extensive computation analysis for quantifying and optimizing the transpiration index of the soil for the complex civil systems.

The paper aims to conduct an empirical study of three models of property derivatives: index-based derivatives, factor hedges, and combinative hedges based on index and factors. The objective is to test whether the latter two models introduced by Lecomte dominate the index-based model used for existing property derivatives such as EUREX futures contracts.

Based on investment property database (IPD) historical database covering 224 individual office properties from 1981 to 2007, the study assesses ex ante hedging effectiveness of the three models. Nine simulations are run under different hypotheses involving individual buildings and portfolios. The 17 factors included in the study cover both macro-factors (e.g. macroeconomic indicators) and micro-factors linked to the properties (e.g. age).

Atomization and periodic rebalancing of property derivatives' underlying make it possible to substantially increase hedging effectiveness for a large majority of buildings in the sample. However, combinative hedges are overall superior to factor hedges owing to the overriding role played by IPD indices in capturing risk.

Due to confidentiality requirements inherent to the use of property level data, the study downplays the role of micro-factors on real estate risk at the property level.

The paper introduces a typology of optimal hedges aimed at individual property owners and portfolio holders in the City office property market.

This is the first time a comprehensive analysis of different models of property derivatives is conducted. The value of the paper stems from the use of property level data.

This article examines how reinsurance coupled with new financial instruments can expand coverage to areas exposed to catastrophe losses from natural disasters, and demonstrates how reinsurance and the catastrophe‐linked financial instruments can be combined to lower the price of protection from its current level. A simple example illustrates the relative advantages and disadvantages of pure catastrophic bonds and pure indemnity reinsurance in supporting a structure of payments contingent on certain extreme events occurring. The authors suggest ways to combine these two instruments using customized catastrophe indices to expand coverage and reduce the cost of protection. This article states six principles for designing catastrophic risk transfer systems and discusses practical issues for implementation, and then concludes with suggestions for future research.