Engineering,a civilising influence?

The global environment is increasingly under threat and we face a challenge with little time to respond. Are we prepared to change the actions and attitudes that have led to this parlous situation, and if we are, how do we do it? Is the world ready for a more ecologically benign, less economically driven, peaceful and spiritually oriented way of living? My challenge lies in higher education. How do you encourage such values in a tertiary education system which has spent many years applying and rewarding a ‘respond to the market’ discourse? My responses are grounded in transformative education research with large diverse cohorts of first year engineering students. This paper also uses a critical futures methodology, Causal Layered Analysis, to update my concerns about Australian engineering education and the profession, using two recent reports. The aim is to offer constructive insights that may be transferable to educators in other contexts.     

Factors associated with single-vehicle and multi-vehicle road traffic collision injuries in Ireland

Generalised linear regression models were used to identify factors associated with fatal/serious road traffic collision injuries for single- and multi-vehicle collisions. Single-vehicle collisions and multi-vehicle collisions occurring during the hours of darkness or on a wet road surface had reduced likelihood of a fatal/serious injury. Single-vehicle ‘driver with passengers’ collisions occurring at junctions or on a hill/gradient were less likely to result in a fatal/serious injury. Multi-vehicle rear-end/angle collisions had reduced likelihood of a fatal/serious injury. Single-vehicle ‘driver only’ collisions and multi-vehicle collisions occurring on a public/bank holiday or on a hill/gradient were more likely to result in a fatal/serious injury. Single-vehicle collisions involving male drivers had increased likelihood of a fatal/serious injury and single-vehicle ‘driver with passengers’ collisions involving drivers under the age of 25 years also had increased likelihood of a fatal/serious injury. Findings can enlighten decision-makers to circumstances leading to fatal/serious injuries.     

The role of a firm's strategic orientation dimensions in determining market orientation

Little is known about how various strategic orientation dimensions determine market orientation. The authors identify four key dimensions of a firm's strategic orientation as critical antecedents to market orientation: the firm's aggressiveness, its future orientation, the extent of marketing formalization, and risk proclivity. Moderating effects of two environmental forces, competitive intensity and technology turbulence, are also considered in light of their relationship with various dimensions of strategic orientation and market orientation. Using a survey with firms spanning multiple industries, the proposed effects are tested with latent class analysis with multiple regimes. The results, based on an optimal two-regime solution, show that that although market orientation is significantly impacted by these strategic orientation dimensions, the pattern of influence differs based on a firm's membership in one of two regimes.     

Do farmers or governments make better land conservation choices? Evidence from China's Sloping Land Conversion Program

In developing countries with small holdings, targeting payments-for-environmental-services prices to site-specific environmental benefits becomes administratively impractical. Instead, governments fix price and either dictate parcel enrollment or let farmers decide, which might be expected to maximize environmental benefits and minimize opportunity costs, respectively. No paper has actually tested such hypotheses in a developing-country setting. This paper examines China's Sloping Land Conversion Program, with 32 million planting forests, using a unique dataset on 3397 parcels, including farmer-choice and government-choice parcels. Farmers consider similar criteria to local governments but weight land characteristics within the farm (not the landscape) and household characteristics.     

Contract selection and performance in competitive bidding for electricity generation

Third parties bidding to supply utilities with electric generation facilities is a new and increasingly important practice. Six states have either establishes bidding programmes or are considering doing so. The paper uses data from Maine, the first state to use electric generation bidding, to examine which bids are awarded contracts, and which contracts fail to fulfill their provisions. Results show that bid price plays a very small role, if any, in the selection process.     

Estimation employing a priori information within mass appraisal and hedonic pricing models

Both statistical appraisal and hedonic pricing models decompose houses into a set of individual characteristics. Regression estimates yield the contribution of each characteristic to total value. Unfortunately, straightforward application of OLS may produce untenable results such as implausible coefficient magnitudes or incorrect signs. Often the suspected cause is multicollinearity. This article examines the effect on estimation efficiency of differing levels of multicollinearity, R², and a priori information in the form of sub-market cost data, by comparing inequality restricted least squares (IRLS) with OLS in a series of Monte Carlo experiments. The IRLS procedure investigated here hybridizes the statistical market approach implemented by OLS, and the more traditional cost approach. The experiments show dramatic gains in estimation efficiency from exploiting a priori information through IRLS.     

Faster Implied Volatilities via the Implicit Function Theorem

We present a faster, more accurate technique for estimating implied volatility using the standard partial derivatives of the Black‐Scholes option‐pricing formula. Beside Newton‐Raphson and slower approximation methods, this technique is the first to provide an error tolerance, which is essential for practical application. All existing noniterative approximation methods do not provide error tolerances and have the potential for large errors.