The performance costs of interruption during visual search are determined by the type of search task

Prior research has shown that interruptions lead to a variety of performance costs. However, these costs are heterogenous and poorly understood. Under some circumstances, interruptions lead to large decreases in accuracy on the primary task, whereas in others task duration increases, but task accuracy is unaffected. Presently, the underlying cause of these costs is unclear. The Memory for Goals model suggests that interruptions interfere with the ability to represent the current goal of the primary task. Here, we test the idea that working memory (WM) may play a critical role in representing the current goal and thus may underlie the observed costs associated with interruption. In two experiments, we utilized laboratory-based visual search tasks, which differed in their WM demands, in order to assess how this difference influenced the observed interruption costs. Interruptions led to more severe performance costs when the target of the search changed on each trial. When the search target was consistent across trials, the cost of interruption was greatly reduced. This suggests that the WM demands associated with the primary task play an important role in determining the performance costs of interruption. Our findings suggest that it is important for research to consider the cognitive processes a task engages in order to predict the nature of the adverse effects of interruption in applied settings such as radiology.

Optimized crew selection for scheduling of repetitive projects

PurposeThe purpose of this paper is to identify optimum crew formations at unit execution level of repetitive projects that minimize project duration, project cost, crew work interruptions and interruption costs, simultaneously.Design/methodology/approachThe model consists of four modules. The first module quantifies uncertainties associated with the crew productivity rate and quantity of work using the fuzzy set theory. The second module identifies feasible boundaries for activity relaxation. The third module computes direct cost, indirect cost and interruption costs, including idle crew cost as well as mobilization and demobilization costs. The fourth module identifies near-optimum crew formation using a newly developed multi-objective optimization model.FindingsThe developed model was able to provide improvements of 0.2, 16.86 and 12.98% for minimization of project cost, crew work interruptions and interruption costs from US$1,505,960, 8.3 days and US$8,300, as recently reported in the literature, to US$1,502,979, 6.9 days and US$7,222, respectively, without impacting the optimized project duration.Originality/valueThe novelty of this paper lies in its activity-relaxation free float that considers the effect of postponing early finish dates of repetitive activities on crew work interruptions. The introduced new float allows for calculating the required crew productivity rate that minimizes crew work interruptions without delaying successor activities and without impacting the optimized project duration. It safeguards against assignment of unnecessary costly resources.

Economic Impact of Current SIF, Flexibility, Inspection and Manufacturing Changes As They Relate to the B31 Piping Codes

Research shows how the impact of inaccurate fatigue calculations (SIFs), poor quality materials and manufacturing shortcuts will eventually result in pipe content leaks that will cause significant business interruption costs and potentially casualties in a very small population of operating piping systems. B31J-2017 corrects many of these inaccurate SIFs but has been slow to be implemented by the piping user community because failures due to thermal overstresses occur much closer to the end of the piping system life than the beginning. Fortunately for the owner this leaves time to correct for any errors once they have been recognized. Relatively simple screening is described that allows the owner and designer to identify the relatively small population of piping systems that should be addressed.

Costs of Demand Response from Residential Customers’ Perspective

Electricity demand in a certain locality varies during the day, depending on weather conditions, daily life routines, or a social event in a town. During high/peak demands, expensive power plants are put into operation, which affects electricity prices. Moreover, power lines are overloaded. If generation capacity is insufficient, a blackout may result. Demand response (DR) programs are widely proposed in energy research to tackle these problems. Although the benefits of DR programs are well known, customer response levels to these programs is low. This is due to the small fraction of benefits they receive against the loss of comfort, lost leisure time, and other inconveniences. The objective of this work is to study DR costs from the customer perspective by considering these factors. A customer survey-based direct approach is used to evaluate the willingness of customers to accept (WTA) a certain compensation when shifting the load is adopted. Two different methods are used to calculate DR costs: percentage compensation, which customers are WTA, and one based on a macroeconomic model, which considers the dependency factor of customers on loads and hourly wage. A linear mathematical model is presented based on both these techniques. This study reveals that DR costs are much less than interruption costs paid by the utility company, and hence is in the best interests of all stakeholders, i.e., customers, utility company, and transmission company.

Assessment of Business Interruption of Flood-Affected Companies Using Random Forests

Losses due to floods have dramatically increased over the past decades, and losses of companies, comprising direct and indirect losses, have a large share of the total economic losses. Thus, there is an urgent need to gain more quantitative knowledge about flood losses, particularly losses caused by business interruption, in order to mitigate the economic loss of companies. However, business interruption caused by floods is rarely assessed because of a lack of sufficiently detailed data. A survey was undertaken to explore processes influencing business interruption, which collected information on 557 companies affected by the severe flood in June 2013 in Germany. Based on this data set, the study aims to assess the business interruption of directly affected companies by means of a Random Forests model. Variables that influence the duration and costs of business interruption were identified by the variable importance measures of Random Forests. Additionally, Random Forest-based models were developed and tested for their capacity to estimate business interruption duration and associated costs. The water level was found to be the most important variable influencing the duration of business interruption. Other important variables, relating to the estimation of business interruption duration, are the warning time, perceived danger of flood recurrence and inundation duration. In contrast, the amount of business interruption costs is strongly influenced by the size of the company, as assessed by the number of employees, emergency measures undertaken by the company and the fraction of customers within a 50 km radius. These results provide useful information and methods for companies to mitigate their losses from business interruption. However, the heterogeneity of companies is relatively high, and sector-specific analyses were not possible due to the small sample size. Therefore, further sector-specific analyses on the basis of more flood loss data of companies are recommended.

Regional Differences in Economic Impacts of Power Outages in Finland

Estimation of the worth of continuity of electricity supply is of interest of industry, authorities and research society. There are numerous methods to calculate the Customer Interruption Costs (CICs). Each method has its advantages and disadvantages. This paper approaches the problem from Distribution System Operators’ (DSOs) point of view and adopts two existing analytical models. One model is used by the Finnish Energy Market Authority and the second one was proposed by the authors at a previous study. The model suggested by the authors as an alternative to the one used by the Finnish Energy Market Authority proposes a simple and straightforward methodology which will provide credible and objective estimations by only utilizing publicly available analytical data. We made use of cost and reliability indices data of 78 DSOs in Finland from the year 2016. In addition to cost estimations, this paper highlights regional differences in CIC estimations in different parts of Finland and critically overviews the existing standard customer compensation scheme in Finland.