Methane production is a trait of increasing importance for the Australia sheep industry, it is being recorded on industry and reference flocks, with project breeding values provided to participating breeders. The current sheep index development in Australia uses traits related to production and reproduction, and from this methane production can be predicted and included in a sustainability index if desired. The purpose of this study was to estimate genetic and phenotypic correlations between methane production and commonly recorded production traits, and to assess the benefit of including direct measurements of methane using genomic prediction in a selection index. This analysis included 6,086 purebred Australian Merino sheep with methane production recorded using portable accumulation chambers. The estimated heritability for methane production was 0.19 ± 0.03. A series of bivariate animal models were used to estimate covariances for methane and commonly recorded production traits. The genetic correlations between methane and the following production traits were: weight at the time of recording (0.36 ± 0.08), weaning weight (0.47 ± 0.05), adult weight (0.34 ± 0.08), yearling c-site fat depth (-0.09 ± 0.08), yearling greasy fleece weight (0.21 ± 0.07), yearling fibre diameter (-0.02 ± 0.07), and yearling faecal egg count (-0.05 ± 0.10). The genetic correlations between methane and the production traits were within the parameter space of published literature. The estimated genetic parameters were used along with selection index theory, to predict selection accuracy and response to selection. Each of the production traits was assumed to have a genomic prediction accuracy similar to having 10 recorded progeny. The assumed genomic prediction accuracy for methane production was 0.40 (based on heritability). Methane production had 100% of the selection pressure for both with and without genomic prediction. The EBV accuracy for methane predicted only based on correlated traits (0.38) was considerably lower compared to adding a genomic prediction for methane (0.52). These results indicate there is a benefit to developing a reference population for methane rather than relying on correlated traits, however, this is dependent on an assumed genomic prediction accuracy of 0.40. In this study, only commonly recorded traits were analysed, and only single trait selection was investigated. A balanced selection index that contains relevant economic values for multiple traits will be more appropriate. Further research is expanding the analysis to include other breeds and a broader range of traits, including reproduction traits, and to integrate these findings into index development for Australian sheep. These results underscore the value of continued methane measurement strategies and the need for increasing the reference population. The results also demonstrate that direct selection can mitigate methane production more effectively than indirect selection based purely on correlated responses.

The contemporary debate and research on transit-oriented development (TOD) has continued to progress within the context of sustainable development. At its core, this refers to providing essential transit services with an efficient manner which is achieved by including accessible public transport, mixed land use, and walkable neighbourhoods so as to reduce the volume of private cars on the road. We have analysed the theoretical development of TOD studies. Based on a scientometric analysis, this paper has collected 442 TOD articles through the Web of Science and used VOSviewer to visually map and analyse four main topics of TOD studies, including “correlation among TOD, smart growth and land use”, “TOD financing and the impacts of TOD on housing price”, “impacts of TOD on travel behaviour”, and “correlation among TOD attractiveness, accessibility and ridership”. And we also provide the current status of research and implications for Australia

With increasing mindfulness of car dependency, several strategies included developing sharing-economy mobility systems have been offered to help in restricting private vehicle usage. This study providesthe survey results of two progressive and innovative shared-mobility schemes (GoGET and UBER) that have recently commenced operations in Adelaide, South Australia based on the online survey data collected from the actual users of the service. The data was then described and analysed using statistical analysis included correlation tests, mean comparing tests, and analysis of variance. While confirming several aspects already discussed in the literature, this research revealed that, due to their different characteristics, the market of shared-mobility is not sufficiently developed in the City of Adelaide (the inner suburban and belt and CBD), whereas its current market demand is highly dependent on the sociodemographic characteristics.

The study and analysis of the impact of organizational innovation on supply chain resilience in manufacturing companies in the field of metal industries based in Shahrekord industrial towns are the main objective of this study. The research method was descriptive - correlation and its statistical society, managers and employees of the supply chain of procurement, production, operations and commerce of manufacturing companies in the field of metal industries based on these companies, numbering 600 people, using the Cochran sample size formula 235 people were selected in a class The tool used in this study is Caraboolot Enterprise Innovation Questionnaire (including dimensions of manufacturing innovation, process innovation, marketing innovation and organizational innovation) and supply chain resilience inventory. Its validity was confirmed by content-based method and the reliability coefficient of the questionnaire was calculated using the Cronbach's alpha formula for organizational innovation questionnaire 0.85 and for the resiliency questionnaire 0.88.

Descriptive and inferential statistics (regression test) were used to analyze the data. The findings showed that manufacturing innovation, marketing innovation, and organizational innovation had a direct impact on supply chain resilience, with the highest impact of 0.94 on organizational innovation and the lowest impact (0.26) on the dimension of manufacturing innovation