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This paper aims to explore why harmonisation, given its potential, is so difficult to achieve. It analyses the issues and challenges in achieving harmonisation of training and development across an industry.

The approach was a meta-analysis of six research projects undertaken in the Australian rail industry. These projects varied in duration from 12-24 months. Between 2009 and 2013, rail employees in varying roles and levels of seniority, including middle managers, front-line supervisors, rail incident investigators, track workers and drivers, were interviewed (n = 176) and surveyed (n = 341).

The meta-analysis identified a range of characteristics associated with harmonisation. It uncovered three categories of harmonisation, seven types of risk modelled in a layered risk pyramid and analysed key structural, environmental and organisational barriers to harmonisation. The paper concludes that harmonisation struggles to gain strategic significance and is hampered by operational pragmatism.

There are few published papers examining harmonisation across companies or based on meta-analyses, especially qualitatively. Despite limitations of insufficient detail to allow close analysis, potentially variable quality data across projects from which to develop a meta-analysis and the danger of comparing apples with oranges, more attempts using this approach would be helpful in gaining nuanced insights into an industry.

Achieving industry harmonisation requires significant change in the mindset of executives. To enhance the chances of harmonisation, there is need for a strong national entity with overview of the entire industry, high-quality training and development resources and activities and cost-benefit analyses and active campaigns. A major outcome of this research is the risk pyramid, which can be used by managers as a strategic evaluation tool. By using such tools based on sound research, leaders can be equipped to make informed decisions and reduce downstream risks.

This research has value in extending the literature in two main ways: through examining the notion of harmonisation across an industry as distinct from within organisations that has been the focus of most studies and through using qualitative meta-analysis in a field dominated by quantitative approaches. It analyses the grey areas between rhetoric about its potential and difficulties in its achievement.

The purpose of this paper is to propose a hybrid decision-making model for optimizing the initial design strategies of pre-sales housing, identifying factors affecting the initial design of housing, and developing different initial design approaches and strategies based on buyers’ preferences.

Indicators and factors in line with the local initial planning and design are created according to the design quality indicator framework. The important indicators and factors are screened out preliminarily with the fuzzy Delphi method and decision-making trial and evaluation laboratory based analytic network process. The performances of two actual cases under similar site conditions are checked with regard to the overall residential sales rate and time on the market (TOM).

The result shows that the proposed model can effectively improve the sales rate, shorten the TOM and better complies with buyer design strategy demands, and thus positively correlating to economic value.

Pre-sales make possible the customized strategy of allowing future residents to participate in the housing design process. However, buyers’ participation in the design process is highly limited, and developers usually determine their planning and initial residential design strategies based on experience and intuition. With the proposed approach, the initial residential design of a project can be effectively intervened, so that home users can truly participate in the design, and the residential construction service can be provided in a unique, but non-universal way.

The purpose of this study is to investigate how the degree of overpricing (DOP) and other variables are associated with the time on the market (TOM) and the final selling price (SP) for residential properties in the Paphos urban area.

The hedonic pricing model was used to examine the association of TOM and SP with various factors. The association of the independent variable of DOP and other independent variables with the two dependent variables of TOM and SP were investigated via ordinary least squares (OLS) regression models. In the first set of models the dependent variable was TOM and in the second set of models the dependent variable was SP. A sample of N = 538 completed transactions from Q1 2008 to Q2 2019 was used to estimate the optimum DOP that a seller must apply on the current market value of a property in order to achieve highest SP price in the shortest TOM.

The results of this study also suggest that the degree of overpricing in thin and less transparent markets is higher than that in transparent markets with high property transaction volumes. In mature markets like the USA and the UK where the actual sold prices are published, the DOP is around 1.5% which is much lower than the 11% DOP identified in this study.

It was found that buyers are willing to pay more for the same house in a bigger plot than a bigger house in the same plot. The outcome is that smaller houses sell faster at a higher price per square meter than larger houses. Smaller houses are more affordable than larger houses.

There is a large pool of buyers for smaller houses than bigger houses. Higher demand for smaller houses results in a higher price per square meter for smaller houses than the price per square meter for bigger houses. Respectively the TOM for smaller houses is shorter than the TOM for bigger houses.

The database used is unique, from an estate agent located in Paphos that managed to sell more than 27,000 properties in 20 years. This data set is the most accurate information for Cyprus' property transactions.

Time on the market (TOM) has been widely tested in the US real estate literature using listing and selling data of houses captured in the multiple listing services (MLSs). Unfortunately in the UK there are no MLSs so it is not possible to undertake similar analyses. The approach adopted in this paper differs from traditional TOM analyses in that it focuses on the speed or time the market takes to correct for information differences between open market valuations and traded prices. In this context the paper introduces the concept of equilibrium time on the market (ETOM). The study therefore adopts a different approach to estimating TOM and in addition also examines the phenomenon within the UK commercial real estate sector. Based on a simple present value model, the time taken for the difference between an appraiser's estimate of open market value and known selling prices define our time on the market under equilibrium market conditions. Using the annualised UK Investment Property Databank all‐property total return index for a sample period of 17 years between 1983 and 1999, the average ETOM was estimated to be 8.4 months. This figure, however, varied and depended on market conditions.

Developing residential units is crucial in the socio-economic development of a country. The investor faces not only uncertain transaction price (price risk), but also uncertainties about the marketing period risk. Predicting when the incurred money is being realized is difficult because of the imperfect nature of the real estate market. Thus, the purpose of this study is to analyze the variables that explain the time on the market (TOM) of housing units, identifying the relationships in-between and the effects on TOM of residential properties.

Following a multi-stage sampling process, a random sample of 120 housing units was selected. Data were collected using a self-administered questionnaire. The questionnaire contained 57 variables that can affect TOM. Semi-structured interviews were conducted to confirm some of the data and information on residential units from the developers. Direct observations were conducted to verify certain physical attributes and, finally, they were comprehensively analyzed using quantitative analysis techniques in SPSS 16.0 Statistical package.

Results confirmed that lesser advertising prices, attractive environment, proximity to the city center and proper shape of lands reduce the TOM. Similarly, higher prices, longer distance to the city center and irregular shape of land increase the TOM. The results strengthen the necessity of a comfortable environment appropriate to live, probably with greenery or water bodies, which is a key influential factor that reduces the TOM in Sri Lanka.

wIn the Sri Lankan context, there are few contributions to the real estate literature in this regard. Many scholars have concentrated on physical and economic characteristics, whereas this research adds the environmental factors. Therefore, this research makes a significant contribution to the body of knowledge in this area, as it puts more attention on including several variables, as well as newly introduced variables as determinants. Consumers can apply the research findings to assess the relative importance of housing attributes and services which they perceive most valuable, and then to make their purchase decisions. The findings also contribute to the investigations of the behavior of housing attributes and enable knowing as to what factors are to be promoted and what to be omitted to gain a shorter TOM.

This paper aims to explore one question: to what extent does urban rehabilitation impact the housing search cost of the low-income tenants.

This paper adopts the fixed effects time-on-market (TOM) model and pricing model to study the research question.

Urban rehabilitation lifts the subdivided units (SDUs’) prices by around 7%. For the SDU located in old districts, urban rehabilitation gives rise to the rental price up by 11%–12%. The SDUs in the area without urban rehabilitation experience a short marketing period of 16%–17%. The SDU located in the old district that is without urban rehabilitation would have a short marketing time.

To the best of the authors’ knowledge, this is the pioneering research to investigate the relationship between rehabilitation and low-income rental housing from the improved search theory. The improved search theory posits that under the circumstance of urban rehabilitation, low-income tenants’ options are limited and the search behavior will be restricted in the affordable areas, and then TOM will be shortened. With the concentration of SDUs in Hong Kong, the test of the search theory is broken down into two hypotheses. (H1) Urban rehabilitation leads to low-income housing prices increase. (H2) Low-income housing located in areas without urban rehabilitation has a shorter TOM.

In 1997 Tom was a 32‐year‐old man with a diagnosis of severe intellectual disability and autism who engaged in high‐rate challenging behaviour. Tom's out‐of‐area placement was about to break down and he needed help urgently. For 16 months specialist challenging behaviour services supported Tom directly in a single‐occupancy service. They conducted functional assessment and delivered multi‐level intervention, including medication withdrawal, environmental enrichment, skills teaching, augmented communication and targeted behavioural intervention. Support was then transferred to mainstream learning disability services. Following intervention, the rate of challenging behaviour shown by Tom fell significantly from more than 200 instances per day to almost none. Community involvement and engagement increased. Tom moved into shared accommodation with support from mainstream learning disability services at no additional cost. Improvement at intervention was still apparent 10 years later. Tom's story adds to a growing number of articles showing how focused intervention can deliver lasting improvement in quality of life. Four aspects of Tom's story are discussed in the light of the Mansell Report.

The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the repercussions of this pandemic on the US housing market. This study investigates the impact of the COVID-19 pandemic on a crucial facet of the real estate market: the Time on the Market (TOM). Therefore, this study aims to ascertain the net effect of this unprecedented event after controlling for economic influences and real estate market variations.

Monthly time series data were collected for the period of January 2010 through December 2022 for statistical analysis. Given the temporal nature of the data, we conducted the Durbin–Watson test on the OLS residuals to ascertain the presence of autocorrelation. Subsequently, we used the generalized regression model to mitigate any identified issues of autocorrelation. However, it is important to note that the response variable derived from count data (specifically, the median number of months), which may not conform to the normality assumption associated with standard regression models. To better accommodate this, we opted to use Poisson regression as an alternative approach. Additionally, recognizing the possibility of overdispersion in the count data, we also explored the application of the negative binomial model as a means to address this concern, if present.

This study’s findings offer an insightful perspective on the housing market’s resilience in the face of COVID-19 external shock, aligning with previous research outcomes. Although TOM showed a decrease of around 10 days with standard regression and 27% with Poisson regression during the COVID-19 pandemic, it is noteworthy that this reduction lacked statistical significance in both models. As such, the impact of COVID-19 on TOM, and consequently on the housing market, appears less dramatic than initially anticipated.

This research deepens our understanding of the complex lead–lag relationships between key factors, ultimately facilitating an early indication of housing price movements. It extends the existing literature by scrutinizing the impact of the COVID-19 pandemic on the TOM. From a pragmatic viewpoint, this research carries valuable implications for real estate professionals and policymakers. It equips them with the tools to assess the prevailing conditions of the real estate market and to prepare for potential shifts in market dynamics. Specifically, both investors and policymakers are urged to remain vigilant in monitoring changes in the inventory of houses for sale. This vigilant approach can serve as an early warning system for upcoming market changes, helping stakeholders make well-informed decisions.

The purpose of this paper is to develop a clear understanding of the features that increase the probability of condos’ sale, with a focus on design-related features.

The present research uses survival analysis (SA) and the Cox proportional-hazards regression (CPHR) to analyze condo sales data provided by the REALTORS® Association of Edmonton (RAE) (Alberta, Canada).

The analysis of the provided data shows that the listed price, building age, appliances and condo fees have less effect on the time a condo spends on the market compared to the condo’s physical features, such as construction material, interior finishing and heating type and source.

The data used in the present research comes from one geographical area (i.e. Edmonton, Canada). Furthermore, the data provided by the RAE does not include any real estate transactions not involving a realtor. Additionally, the present research, owing to its focus on design-related features, does not control features related to the external environment, such as community and transportation proximity.

The findings of the present research help construction practitioners (e.g. architects, builders and realtors) better understand the features that influence condo buyers’ decisions. This knowledge helps to develop designs and marketing strategies that increase the likelihood of selling and decrease the time listed condos spend on the market.

The present research expands our knowledge of the drivers influencing the purchasers’ decisions concerning the building’s physical features that can be controlled during the design stage. Also, analyzing the provided data by using SA and CPHR, as followed in this paper, facilitates the inclusion of records that are listed but not sold, which helps to overcome the survivorship bias and avoid the over-optimism that exists in the present literature.

This paper aims to consider the legitimacy challenges faced by hybrid organizations, examining the narrative strategies hybrids use in responding to these challenges and offering a framework for managers to consider in their choice of narratives.

A narrative analysis of texts addressing the legitimacy of the business models used by four hybrid organizations is conducted.

The results of the analysis suggest that the nature of conflicting stakeholder demands – centered on goals or means – is an integral factor influencing hybrids’ choice of narrative strategies to emphasize distinctiveness or conformity.

This paper adds to extant research examining the challenges hybrid organizations face and emphasizes that the choice of narrative strategies is an important factor hybrids must consider when managing legitimacy. Generalizability is a notable limitation of the case approach; the authors suggest areas for future research to address this limitation.

The research offers a practical framework for hybrids’ leaders, as they manage legitimacy, choosing to emphasize distinctiveness or conformity in the face of conflicts regarding goals or means.

By studying the legitimacy challenges faced by hybrid organizations, this study can form a more complete view of legitimation, encompassing different types of enterprises offering distinct value propositions.