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To remedy the inherent defect in current research that focuses only on a single type of participants, this paper endeavors to look into the situation as an evolutionary game between a representative Logistics Service Integrator (LSI) and a representative Functional Logistics Service Provider (FLSP) in an environment with sudden crisis and tries to analyze how LSI supervises FLSP's operations and how FLSP responds in a recurrent pattern with different interruption probabilities.

Regarding the risks of supply chain interruption in emergencies, this paper develops a two-level model of single LSI and single FLSP, using Evolutionary Game theory to analyze their optimal decision-making, as well as their strategic behaviors on different risk levels regarding the interruption probability to achieve the optimal return with bounded rationality.

The results show that on a low-risk level, if LSI increases the degree of punishment, it will fail to enhance FLSP's operational activeness in the long term; when the risk rises to an intermediate level, a circular game occurs between LSI and FLSP; and on a high level of risk, FLSP will actively take actions, and its functional probability further impacts LSI's strategic choices. Finally, this paper analyzes the moderating impact of punishment intensity and social reputation loss on the evolutionary model in emergencies and provides relevant managerial implications.

First, by taking both interruption probability and emergencies into consideration, this paper explores the interactions among the factors relevant to LSI's and FLSP's optimal decision-making. Second, this paper analyzes the optimal evolutionary game strategies of LSI and FLSP with different interruption probability and the range of their optimal strategies. Third, the findings of this paper provide valuable implications for relevant practices, such that the punishment intensity and social reputation loss determine the optimal strategies of LSI and FLSP, and thus it is an effective vehicle for LSSC system administrator to achieve the maximum efficiency of the system.

We estimate a dynamic programming model of schooling decisions in which the degree of risk aversion can be inferred from schooling decisions. In our model, individuals are heterogeneous with respect to school and market abilities but homogeneous with respect to the degree of risk aversion. We allow endogenous schooling attainments to affect the level of risk experienced in labor market earnings through wage dispersion and employment rate dispersion. We find a low degree of relative risk aversion (0.93) and the estimates indicate that both wage and employment rate dispersions decrease significantly with schooling attainments. We find that a counterfactual increase in risk aversion will increase schooling attainments. Finally, the low degree of risk aversion implies that an increase in earnings dispersion would have little effect on schooling attainments.

Interruptions are prevalent in knowledge work, and their negative consequences have driven research to find ways for interruption management. However, these means almost always leave the responsibility and burden of interruptions with individual knowledge workers. System-level approaches for interruption management, on the other hand, have the potential to reduce the burden on employees. This paper’s objective is to pave way for system-level interruption management by showing that data about factual characteristics of work can be used to identify interrupting situations.

The authors provide a demonstration of using trace data from information and communications technology (ICT)-systems and machine learning to identify interrupting situations. They conduct a “simulation” of automated data collection by asking employees of two companies to provide information concerning situations and interruptions through weekly reports. They obtain information regarding four organizational elements: task, people, technology and structure, and employ classification trees to show that this data can be used to identify situations across which the level of interruptions differs.

The authors show that it is possible to identifying interrupting situations from trace data. During the eight-week observation period in Company A they identified seven and in Company B four different situations each having a different probability of occurrence of interruptions.

The authors extend employee-level interruption management to the system-level by using “task” as a bridging concept. Task is a core concept in both traditional interruption research and Leavitt's 1965 socio-technical model which allows us to connect other organizational elements (people, structure and technology) to interruptions.

Physician lateness and service interruptions are a significant problem in many health care environments but have received little attention in the literature. The purpose of this paper is to design appointment systems that reduce waiting times of the patient while maintaining utilization of the physician at a high level.

Empirical data from time studies and surveys of medical professionals from multiple outpatient clinics are used to motivate the study. Simulation optimization is used to simultaneously account for uncertainty and to determine (near) optimal scheduling solutions.

As lateness increases, it is shown that, in general, appointment slots should be shorter and pushed later in the session. Conversely, as interruptions rise, appointments in the middle of the session should be longer. These findings are fairly consistent over a variety of environmental conditions, including clinic sizes, service time variance, and costs of physician time compared to patients' time.

This paper demonstrates that the dome/plateau‐dome scheduling patterns that have been found in prior studies work well under many of the new factors modeled here. This is encouraging because it suggests that a generalizable pattern is emerging in the literature for the range of environments studied in these papers and this research provides guidance as to how to adjust the pattern to account for the factors studied here. In addition, it is shown that some environments will perform better with a different pattern, which the authors denote a “descending step” pattern.

This paper differs from most prior studies in that the complexity of environmental variables and stochastic elements of the model are simultaneously accounted for by the simulation optimization algorithm. The (very few) prior papers that have used simulation optimization have not addressed the factors studied here.

Exposure to a public health threat of significant proportions made current models inadequate to explain the failure phenomenon in small businesses. Hence, the need to reimagine the phenomenon. Borrowing from the principles of biology, this study extended theoretical and empirical perspectives on the failure phenomenon by unpacking its constituent elements and the measurement metrics using the regeneration lens.

Based on a cohort tracked over time, the study estimated the survival probabilities of small and medium-scale enterprises (SMEs) with and without regeneration using the Kaplan–Meier method. The study investigated the factors that predict enterprise regenerative capacity using the multivariate Cox proportional hazard ratios.

Rates of interruption in business activity, by month, ranged between 0% and 18% during the follow-up period. True mortality rates hovered between 0% and 4% over the same period. Over three in five SMEs that experienced interruption in business activity without ceasing operations regenerated at some point in time during the follow-up period. The survival probabilities beyond the follow-up period were 0.85 and 0.44 with and without regeneration effects, respectively. Fresh capital injection (+), the introduction of new/improved processes or products/services (+), perceived business outlook (+) and the presence of debt (−) influenced the capacity to regenerate.

The cohort was followed for only six months. There is a need to continue interrogating the failure phenomenon in other contexts over longer periods using the regeneration lens. Bringing on board academia, financial institutions and other SME-related ecosystem players will be strategic.

The approach provides a more nuanced understanding of the life and well-being of enterprises under conditions of disruption. Improving the precision and validity of failure-related statistics enhances their utility in policy and remediation-related discussions.

The results did not show significant differences in SME mortality rates between male and female-owned enterprises. The results provide further evidence that the failure phenomenon is ungendered. As such, financial institutions and the SME ecosystem at large must eliminate perceptual gender biases in the financing and other support to SMEs.

The study used the principles of biology to reimagine the failure phenomenon in small businesses. The approach breathes life into entrepreneurship research and policy.

Career interruptions of employees imply important issues for both firms and individuals, including a possibly lower compensation after returning to a job. Different compensation components are explored, as bonus payments frequently complement fixed salaries for many employees, making various channels of lower compensation possible. This paper aims to discuss this issue.

This study is based on a yearly salary survey among a rather homogeneous group of professionals and middle managers from the German chemical sector, which contains detailed information on compensation components next to individual and job characteristics. The incidence and duration of past career interruptions act as the most important independent variables. Mincer-type wage regressions are complemented by estimations on wage increases.

The results show that career interruptions are more related to lower subsequent bonus payments than they are to fixed salaries. Furthermore, interruptions caused by unemployment are associated with higher interruption pay gaps than those resulting from other reasons such as parental leave. The results even hint for catch-up effects following parental leave with regard to higher wage increases compared to individuals without interruptions. Career interruptions are more prevalent for female managers offering an explanation for a considerable part of gender pay gaps. Wage losses after career interruptions are more pronounced for male employees than they are for females, though.

This study extents the literature by disentangling the relation of career interruptions and different compensation components, bonus payments next to fixed salaries in particular. The role of interruption type and gender are also taken into account so that the paper deepens the understanding of the role of past career interruptions for employees’ remuneration.

The purpose of this paper is to inform facility managers of the type of failure affecting certain pipe types more than others. This is useful in asset management as preventive maintenance can be undertaken for those pipe types that experience high probabilities of failure.

The probability of a specific pipe type failing given the cause of break, age at failure, pipe diameter, and type of soil at the location of the break was found using inventory and main break data from the Honolulu Board of Water Supply (HBWS). Bayes’ theorem was then applied to find the posterior probabilities of failure starting from the prior probabilities of failure.

It was observed that the greatest probabilities of failure involved corrosion, pipes aged between 20‐30 years, 8″ pipes, and pipes in fill material. The pipe types were ranked and scored based on their probability of failing due to break cause, age, diameter, and soil type. Cast iron pipes were shown to have the highest probability of failing. As such, attention should be given to replace segments of cast iron pipes as they reach the end of their service lives.

This study serves to address a major query in asset management at a public utility, that of which pipes should be selected for replacement when they reach the end of their service life. In addition, this study helps to understand the causes of failure for the various types of pipe.

The importance of having reliable water supply at low cost has immense social implications in modern communities. To deliver such service, water pipe assets have to be managed efficiently.

This paper addresses the probability of failure in a straightforward manner that the water utility can easily apply to its own data, both in its design and asset management.

A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key attributes of disruptive events that may occur during the construction phase: probability and impact. This paper fills this research gap by developing a buffer allocation method that takes into account the synergistic impact of these two attributes on project activities.

This paper develops a three-step method, calculating the probability that project activities are disrupted in the first step, followed by measuring the potential impact of disruption on project activities, and then proposing a risk-informed buffer allocation index by simultaneously integrating probability and impact outputs from the first two steps.

The proposed method provides more accurate results by sidestepping the shortcomings of conventional fuzzy-based and simulation-based methods that are purely based on expert judgments or historical precedence. Further, the paper provides decision-makers with a buffer allocation method that helps in developing cost-effective buffering and backup strategies by prioritizing project activities and their required resources.

This paper develops a risk-informed buffer allocation method that differs from those already available. The simultaneous pursuit of the probability and impact of disruptions distinguishes our method from conventional buffer allocation methods. Further, this paper intertwines the research domains of complexity science and construction management by performing centrality analysis and incorporating a key attribute of project complexity (i.e. the interconnectedness between project activities) into the process for buffer allocation.

Drawing on the literature that has shown the prevalence of short-lived trade relationships, the purpose of this paper is to provide further understanding about this issue by exploring the impact of engaging in Global Value Chains (GVCs) on the chance of export survival at product-country level, paying special attention to the differences between advanced and developing countries. The authors also investigate whether the type of GVC participation (backward or forward) matters for export survival.

To capture to what extent a country’s exports are integrated in GVCs, the authors use the OECD Inter-Country Input-Output database to estimate value added incorporated in exports. Through the estimation of a discrete-time duration model, the authors explore the impact of engaging in GVCs on export survival using highly disaggregated trade data from the CEPII’s BACI database.

The findings endorse the hypothesis that deeper participation in GVCs is a key factor in explaining stability in trade relationships, mainly for developing countries where the trade flows are especially fragile. The authors also find different effects depending on the type of GVC involvement and on whether the value chain partners are advanced or developing.

The paper contributes to the literature by extending the understanding on the factors that promote the stability of exports, including among them, involvement on GVCs (and its forms) which is one of the most relevant factors to explain recent behavior of trade.