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Describes an empirical study of real estate value estimates in Melbourne, Australia, for the purpose of testing to see if computer generated values are as good as those produced by ordinary manual processes. Describes computer systems, including MRA and a process known as comparables selection, a computer‐based system which is an attempt to emulate the manual comparable sale selection system. Finds that the manual method outperformed that carried out by computers.

The purpose of this paper is to apply boosted regression trees (BRT) to a heterogeneous data set of residential property drawn from a jurisdiction in Malaysia, with the objective to evaluate its application within the mass appraisal environment in Malaysia. Machine learning (ML) techniques have been applied to real estate mass appraisal with varying degrees of success.

To evaluate the performance of the BRT model two multiple regression analysis (MRA) models have been specified (linear and non-linear). One of the weaknesses of traditional regression is the need to a priori specify the functional form of the model and to ensure that all non-linearities have been accounted for. For a BRT model the algorithm does not require any predetermined model or variable transformations, making the process much simpler.

The results show that the BRT model outperformed the MRA-specified models in terms of the coefficient of dispersion and mean absolute percentage error. While the results are encouraging, BRT models still lack transparency and suffer from the inability to translate variable importance into quantifiable variable effects.

This paper presents a useful alternative modelling technique, BRT, for use within the mass appraisal environment in Malaysia. Its advantages include less intensive data cleansing, no requirement to specify the predictive underlying model, ability to utilise categorical variables without the need to transform them and not as data hungry, as for example, MRA.

This paper adds to the knowledge in this area by applying a relatively new ML model, BRT to residential property data from a jurisdiction in Malaysia. BRT has shown promise as a strong predictive model when applied in other disciplines; therefore this research empirically tests this finding within real estate valuation.

Provides an outline of research seeking to apply to computer assisted mass appraisal (CAMA) model capable of use within a geographic information system (GIS). The end product will be a working GIS/valuation integrated model. The model, in an operational context, can be utilized for property taxation purposes, to facilitate the rating and revaluation of residential properties in Northern Ireland. As the value of land and property is a function of economic, legal, physical and locational factors, consequently access to comprehensive, reliable and up‐to‐date transaction evidence is a prerequisite to property valuation. Valuation techniques depend on the collection and analysis of relevant data. Historically, the application of these techniques took place within a non‐spatial environment. Ultimately, market data support any estimate of value. Data searches and collection can prove both time consuming and expensive in relation to the fee earning potential of a valuation report. GIS can facilitate, in a spatial and aspatial context, the storage, manipulation and analysis of data, in a fraction of the time previously required. Current techniques for the mass appraisal of property, and for the prediction of residential property values, can be enhanced by utilizing the data handling capacity of GIS. Integration of a mass appraisal model within a GIS will add value to the valuation process.

Feminist perspectives from women of color did not emerge solely as a result from racism in the white feminist movements; such an assumption negates the agency of feminists of color (Roth, 2004). Instead, feminist perspectives by women of color emerged from historical and sociopolitical dynamics within their own communities of origin, as well as in relationship to each other, including in opposition to, and at times in concert with, the white feminist movements. This chapter explores the development, complexities, and unique contributions of Womanist, Black Feminist Thought, hip-hop, Chicana, Native American, global, Asian American, Arab American and ecofeminism. These feminist perspectives include overarching themes, such as the intersectionality of gender, race, ethnicity, class, sexual orientation, ability, age, religion, nationality, and other important identities and issues. Each contemporary feminist theory also explores the interstices of issues such as education, health, economics, reproduction, sociopolitical, historical, organizational, technological, and myriad interrelated dynamics.

Hype about information and communication technology (ICT) emphasizes potential positive outcomes; while enabling factors are under‐emphasized and potential negative outcomes are excluded. The purpose of this paper is to broaden the framing of ICT to include enabling factors and potential negative outcomes.

The paper takes the form of a critical realist study. Critical realist research seeks to improve understanding of causal mechanisms and causal contexts.

Comprehensive enablers for decision making include balanced unambiguous information; specific trustworthy communication; quiet sufficient decision spaces; and independent engaged decision makers. The introduction of a new ICT can make a contribution to, and/or detract from, realization of these principal enabling factors.

In this paper ICT is positioned within a preliminary comprehensive framing of enabling factors for decision making. ICT is used for other purposes. Nonetheless, the positioning of ICT in a preliminary comprehensive framing for decision making support reveals how hype about ICT can be mediated by consideration of enabling factors and potential negative outcomes.

The broader framing of enabling factors can provide a starting point for managers to undertake comprehensive improvement of information, communication, and contexts for decision making.

The originality of this paper is that it applies critical realism to mediate hype about ICTs that could be used to support decision making. The value of this paper is that it provides a detailed description of inter‐related factors that need to be managed in decision making support.

The purpose of this paper is to present the development of a system called Structured Hypermedia Algorithm Explanation (SHALEX), as a remedy for the limitations existing within the current traditional algorithm animation (AA) systems. SHALEX provides several novel features, such as use of invariants, reflection of the high‐level structure of an algorithm rather than low‐level steps, and support for programming the algorithm in any procedural or object‐oriented programming language.

By defining the structure of an algorithm as a directed graph of abstractions, algorithms may be studied top‐down, bottom‐up, or using a mix of the two. In addition, SHALEX includes a learner model to provide spatial links, and to support evaluations and adaptations.

Evaluations of traditional AA systems designed to teach algorithms in higher education or in professional training show that such systems have not achieved many expectations of their developers. One reason for this failure is the lack of stimulating learning environments which support the learning process by providing features such as multiple levels of abstraction, support for hypermedia, and learner‐adapted visualizations. SHALEX supports these environments, and in addition provides persistent storage that can be used to analyze students' performance. In particular, this storage can be used to represent a student model that supports adaptive system behavior.

SHALEX is being implemented and tested by the authors and a group of students. The tests performed so far have shown that SHALEX is a very useful tool. In the future additional quantitative evaluation is planned to compare SHALEX with other AA systems and/or the concept keyboard approach.

SHALEX has been implemented as a web‐based application using the client‐server architecture. Therefore students can use SHALEX to learn algorithms both through distance education and in the classroom setting.

This paper presents a novel algorithm explanation system for users who wish to learn algorithms.

The purpose of this paper is to examine the behavioral outcomes and effectiveness of organizational response to open complaints by consumers following a dissatisfactory service experience.

Three natural communities (WhatsApp groups) were used with reference to online food and grocery retailing. The respondents comprised community members sharing negative experiences on the group. A scenario implanted in a survey was used as the research approach.

Consumer advocacy, a form of complaining, is a way to help other community members. The relationship between consumer advocacy and community usefulness strengthens the argument of consumers’ collective concern as one of the motivational frames for consumer advocacy. Consumer advocates show stronger reactions, resulting in brand avoidance following voice complaining. An effective organizational response can mitigate brand avoidance.

Finding ways to restrict and alleviate brand avoidance is an area that is of major interest to practitioners. The study finds that prospective explanations could be a very effective antidote to brand avoidance.

The social side of complaining is a relatively under-researched area. This study examines the relationship between consumer advocacy, community usefulness and brand avoidance. To the best of the authors’ knowledge, this is the first study to examine the moderating effect of organizational response on consumer advocacy and its outcomes in the virtual context.

This paper aims to propose a set of flexible design principles for enhancing the flexibility of street furniture to deal with the diverse and changing urban environment. Flexibility is an important but less considered element of public design (otherwise called public environment and facility design), especially in regard to the street furniture that is encountered in everyday life. Taking Hong Kong as a case study, this paper gives an overview of the concepts of flexibility and flexible design, and identifies the current limitations and problems of the current street furniture design practices with respect to the diverse and changing urban environment.

Based on a review of the current literature and relevant documentation, interviews with government officers and different groups of users (including those with special needs), and field observations in Hong Kong’s urban areas over a period of four years, the policies relating to street furniture design in Hong Kong and its management and implementation were evaluated.

The results indicate that the current street furniture in Hong Kong is unable to adapt to or resist changes, can easily cause safety and management problems and is not adaptable to new developments. This paper proposes six principles for the flexible design of street furniture, namely, custom in use, multifunctional use, responds effectively to changing circumstances, easily and conveniently managed, universal in use and sustainable in use.

It is difficult to understand the diverse needs and preferences of different users in urban environments. The findings in this paper are based on intensive field work and broad industry experience. To deal with the rapid and ongoing urban change, this paper recommends a further long-term and in-depth study of street furniture.

Based on the findings, this paper proposes six flexible design principles for designing street furniture that is sufficiently flexible to meet the rapid and ongoing urban change and diverse users’ needs.

Different societies and urban areas faced different types and levels of changes. Therefore, a flexible approach to street furniture design is important and necessary.

The findings of this paper and the proposed six flexible design principles can provide insight and direction for government officials, design and planning professionals, developers, utility and management companies and communities on how to embed public design (i.e. policy, implementation and management) in the future.

Construction contract auctions are characterized by (1) a heavy emphasis on the lowest bid as it is that which usually determines the winner of the auction, (2) anticipated high outliers because of the presence of non‐competitive bids, (3) very small samples, and (4) uncertainty of the appropriate underlying density function model of the bids. This paper describes a method for simultaneously identifying outliers and density function by systematically identifying and removing candidate (high) outliers and examining the composite goodness‐of‐fit of the resulting reduced samples with censored normal and lognormal density function. The special importance of the lowest bid value in this context is utilized in the goodness‐of‐fit test by the probability of the lowest bid recorded for each auction as a lowest order statistic. Six different identification strategies are tested empirically by application, both independently and in pooled form, to eight sets of auction data gathered from around the world. The results indicate the most conservative identification strategy to be a multiple of the auction standard deviation assuming a lognormal composite density. Surprisingly, the normal density alternative was the second most conservative solution. The method is also used to evaluate some methods used in practice and to identify potential improvements.