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Purpose – This chapter provides details of research that attempts to relate traffic operational conditions on uninterrupted flow facilities (e.g., freeways and expressways) with real-time crash likelihood. Unlike incident detection, the purpose of this line of work is to proactively assess crash likelihood and potentially reduce the likelihood through proactive traffic management techniques, including variable speed limit and ramp metering among others.

Methodology – The chapter distinguishes between the traditional aggregate crash frequency-based approach to safety evaluation and the approach needed for real-time crash risk estimation. Key references from the literature are summarised in terms of the reported effect of different traffic characteristics that can be derived in near real-time, including average speed, temporal variation in speed, volume and lane-occupancy, on crash occurrence.

Findings – Traffic and weather parameters are among the real-time crash-contributing factors. Among the most significant traffic parameters is speed particularly in the form of coefficient of variation of speed.

Research implications – In the traffic safety field, traditional data sources are infrastructure-based traffic detection systems. In the future, if automatic traffic detection systems could provide reliable data at the vehicle level, new variables such as headway could be introduced. Transferability of real-time crash prediction models is also of interest. Also, the potential effects of different management strategies to reduce real-time crash risk could be evaluated in a simulation environment.

Practical implications – This line of research has been at the forefront of bringing data mining and other machine-learning techniques into the traffic management arena. We expect these analysis techniques to play a more important role in real-time traffic management, not just for safety evaluation but also for congestion pricing and alternate routing.

The authors empirically investigate the impact of the existence of a stand-alone risk committee (RC) and its characteristics on the likelihood of stock price crash risk in listed financial firms on the Bursa Malaysia. The authors also test whether the effect of RC on crash risk is attenuating or amplifying by the level of institutional ownership.

The authors use a principal components analysis (PCA) to aggregate and derive a factor score for risk committee characteristics (i.e. independence, qualification, and size) as a proxy for the effectiveness of RC. The study also employs two distinct stock price crash risk measurements to corroborate the findings and partition institutional ownership into dedicated and transient to examine the potential impact of institutional shareholding on RC-stock price crash risk association.

Regression analysis reveals that only RC qualification has a significant negative impact on stock price crash risk. However, when RC characteristics are aggregated into one composite factor, the authors find that firms with effective RCs exhibit lower risk of stock price crash. The authors also find that firms with high level of institutional shareholdings and effective RCs are less likely to experience crash risk likelihood. The additional analyses indicate that the complementary moderating effect of institutional ownership on RC-crash risk nexus is likely to be driven by dedicated institutional ownership. The results are robust across two measures of stock price crash risk and regression specifications for a longer run window.

The study, to the best of the researchers' knowledge, is the first to provide evidence in an emerging market financial sector companies' perspective suggesting that effective RCs are individually and aggregately associated with lower stock price crash risk, which is further strengthened by dedicated institutional investors. These findings are unique and contribute to a small but growing body of literature documenting the need for effective RCs and specific institutional investors and their consequences of improvements in stock price crash risk environment. Results of our research in this area provide important insights to financial and capital market participants, investors, regulators, and policymakers in Malaysia.