Exploring accuracy factors in cost estimating practice towards implementing Building Information Modelling (BIM)

Cost estimating has been acknowledged as a crucial component of construction projects. Depending on available information and project requirements, cost estimates evolve in tandem with project lifecycle stages; conceptualisation, design development, execution and facility management. The premium placed on the accuracy of cost estimates is crucial to producing project tenders and eventually in budget management. Notwithstanding the initial slow pace of its adoption, Building Information Modelling (BIM) has successfully addressed a number of challenges previously characteristic of traditional approaches in the AEC, including poor communication, the prevalence of islands of information and frequent reworks. Therefore, it is conceivable that BIM can be leveraged to address specific shortcomings of cost estimation. The impetus for leveraging BIM models for accurate cost estimation is to align budgeted and actual cost. This paper hypothesises that the accuracy of BIM-based estimation, as more efficient, process-mirrors of traditional cost estimation methods, can be enhanced by simulating traditional cost estimation factors variables. Through literature reviews and preliminary expert interviews, this paper explores the factors that could potentially lead to more accurate cost estimates for construction projects. The findings show numerous factors that affect the cost estimates ranging from project information and its characteristic, project team, clients, contractual matters, and other external influences. This paper will make a particular contribution to the early phase of BIM-based project estimation.

Estimating the parameters of stochastic volatility models using option price data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

Assessment of transit quality of service with occupancy load factor and passenger travel time measures

This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

Measuring route passenger load diversity for capacity and quality of service assessment

This paper develops theory that quantifies transit route passenger-relative load factor and distinguishes it from occupancy load factor. The ratio between these measures is defined as the load diversity coefficient, which as a single measure characterizes the diversity of passenger load factor between route segments according to the origin-destination profile. The relationship between load diversity coefficient and route coefficient of variation in occupancy load factor is quantified. Two tables are provided that enhance passenger capacity and quality of service (QoS) assessment regarding onboard passenger load. The first expresses the transit operator’s perspective of load diversity and the passengers’ perspective of load factor relative to the operator’s, across six service levels corresponding to ranges of coefficient of variation in occupancy load factor. The second interprets the relationships between passenger average travel time and each of passenger-relative load factor and occupancy load factor. The application of this methodology is illustrated using a case study of a premium radial bus route in Brisbane, Australia. The methodology can assist in benchmarking and decision making regarding route and schedule design. Future research will apply value of time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent aboard. This would also assist in transit service quality econometric modeling.

Measuring route passenger load diversity for capacity and quality of service assessment

This poster introduces Passenger Relative Load Factor for a route or individual bus service as a capacity and quality of service measure, distinguishing it from Occupancy Load Factor. It introduces Load Diversity Coefficient as the ratio of Passenger Relative Load Factor to Occupancy Load Factor, and relates Load Diversity Coefficient to Coefficient of Variation in Occupancy Load Factor. It qualifies the operator’s and passengers’ perspectives of load factor based on Coefficient of Variation in Occupancy Load Factor along a route. A case study using weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia illustrates the methodology. The compendium paper also qualifies the operator’s and passengers’ perspectives of these load factors along with Passengers’ Average Travel Time for capacity and quality of service assessment.

Who is the South African retail giant behind the David Jones bid?

Yesterday morning came the news South African retailer Woolworths had offered $4 a share to acquire David Jones, a proposal that has the approval of the department store’s board. This offer, worth an estimated A$2.15 billion, represents a 25% premium over the current share price value. An earlier offer, from rival Myer, was rejected earlier this year. But who is Woolworths? Not to be confused with Australia’s largest supermarket, Woolworths SA is one of South Africa’s largest retailers.

Is Aldi’s move to woo cashed-up shoppers a risk?

While Aldi’s launch of their new “trial” stores may seem to be an attempt to capture middle income shoppers, it may end in disaster. Aldi’s four new trial stores located in Queensland, NSW, ACT and Victoria, will offer improved lighting, larger layouts and an expanded offering of fresh food including extending produce ranges, in-house bakeries and premium brands. Employing Nielsen’s 2014 Homescan Report, Aldi have determined that only 30% of their customers were now considered “low-income shoppers”. Some 34.4% were from middle-income households and the remaining 35.6% now had household incomes greater than AUD$90,000 a year - a segment which has grown by 6.7% since 2011. So this probably the reason for Aldi’s foray into new stores and ranges. However, such a move is considered risky.

The accounting and accountability practices of Fairtrade International (FLO)

This study examines the accounting and accountability practices of Fairtrade International (FLO), one of the largest Fair Trade umbrella organizations. Our aim is to explore whether new forms of accounting and related disclosures emerge in the reporting practices of FLO and how these reflect their self-declared social mission towards the emancipation and sustainability of producers. Using thematic analysis and reflecting on Bourdieu’s theory of symbolic power, we analyse FLO’s reporting practices from 2006 to 2013. Our findings reveal that FLO mobilises the taken-for-granted images and symbols of ’fairness’ in the Fair Trade system by using descriptive statistics of Fair Trade premium distributions and pictures of producers but keeps silent to current concerns surrounding the limitations of Fair Trade. Such findings extend important insights into how new forms of accounting and related disclosure are used to legitimise the practice of Fair Trade.

Consumer’s comparison between local and imported organic products: A hedonic analysis of the Japanese table wine market

Although hundreds of thousands of organic products are traded on a daily basis, it is less known how imported organic products are evaluated by consumers in an importing country. The paper analyzes Japanese wine point of sale (POS) data to examine whether consumers differentiate between local and imported organic products. The results of our hedonic analyses show that the premium for imported organic red (white) wines is about 42.996 % (8.872 %) while that for domestic red (white) organic wines is about 6.440 % (1.214 %), implying that Japanese consumers pay higher premiums for imported organic agricultural products than for those produced in Japan.