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This study aims to focus on asset management of large‐scale information systems supporting infrastructures and especially seeks to address a methodology of their statistical deterioration prediction based on their historical inspection data. Information systems are composed of many devices. Deterioration process i.e. wear‐out failure generation process of those devices is formulated by a Weibull hazard model. Furthermore, in order to consider the heterogeneity of the hazard rate of each device, the random proportional Weibull hazard model, which expresses the heterogeneity of the hazard rate as random variables, is to be proposed.

Large‐scale information systems comprise many components, and different types of components might have different hazard rates. Therefore, when analyzing faults of information systems that comprise various types of devices and components, it is important to consider the heterogeneity of the hazard rates that exist between the different types of components. In this study, with this in consideration, the random proportional Weibull hazard model, whose heterogeneity of hazard rates is subject to a gamma distribution, is formulated and a methodology is proposed which estimates the failure rate of various components comprising an information system.

Through a case study using a traffic control system for expressways, the validity of the proposed model is empirically verified. Concretely, as for HDD, the service life at which the survival probability is 50 percent is estimated as 158 months. However, even for the same HDD, use environment differs according to usage. Actually, among the three different usages (PC, server, others), failures happen earliest in the case of PCs, which have the highest heterogeneity parameter and a survival probability of 50 percent after 135 months of usage. On the other hand, as for others, its survival probability is 50 percent at 303 months.

To operationally express the heterogeneity of failure rates, the Weibull hazard model is employed as a base, and a random proportional Weibull hazard model expressing the proportional heterogeneity of hazard rates with a standard gamma distribution is formulated. By estimating the parameter of the standard proportional Weibull hazard function and the parameter of the probability distribution that expresses the heterogeneity of the proportionality constant between the types, the random proportional Weibull hazard model can easily express the heterogeneity of the hazard rates between types and components.

Research in the area of financial distress often uses a proportional hazards model to determine the influence of covariates on the duration of time that precedes financial distress. Acritical issue in the use of a proportional hazards model is the use of time‐invariant and time‐dependent covariates. Time‐invariant covariates remain fixed while time‐dependent covariates change during the estimation of the model. Although the choice of covariates might substantially affect the estimation of the proportional hazards model, existing literature often fails to consider the potential effect of this choice on model estimation. This paper reviews the distinction between time‐invariant and time‐dependent covariates and the effect of covariate selection on the estimation of a proportional hazards model. Using a sample of financially distressed and non‐financially distressed firms, this paper suggests the choice of time dependence substantially influences model estimation and that covariate selection should be given more serious consideration in financial distress research.

The purpose of this paper is to investigate hazards for minor users while they are exposed to social networks. In particular, it provides the statistical relationship of these hazards with the exposure time as well as the amount of published personal information.

An experiment was conducted that has revealed a huge number of personal information exposed by users of social network applications. Moreover, a significant amount of suspicious activity against minors has been recorded. Experimental data led to the hypothesis that online hazards can be modeled with known statistical distributions. In order to examine this hypothesis, survival analysis techniques, which involve the estimation of certain functions that reflect the relation of a disastrous event with time, were applied.

The results show that the incoming hazards for minor female profiles follow the Logistic distribution, while the corresponding hazards for minor male profiles follow the Normal distribution.

The findings of this work are crucial for developing an effective system for automated grooming recognition in real time by optimizing the detection threshold as a function of time. Thus, the threshold sensitivity can be appropriately adjusted such that lower frequencies of occurrence lead to lower threshold sensitivities, and higher frequencies of occurrence lead to higher threshold sensitivities.

The problem is to devise a life‐test acceptance procedure of an electrical item that has a Weibull failure distribution with an increasing hazard rate. The test‐bed facility has some constraints on the number of test samples and testing time.

The life‐test plan is obtained using censoring of experiments and the properties of order statistics. In this article, the author has derived expressions for order statistics and their moments for some commonly used hazard‐rate functions; for example, constant, linearly increasing, exponentially increasing, power function, etc. and the same is used in planning the life‐test acceptance procedure.

Results and findings are discussed in full. It is postulated that further research in this direction will definitely bring some fruitful results that have immense importance in the field of reliability analysis and life‐testing experiments.

The same methodology can be adopted for devising life‐test acceptance procedure using censoring of experiments.

This paper aims to introduce the use of hazards functions for studying the relationship between internationalization and performance in small and medium-sized enterprises (SMEs) from emerging economies.

Hazards functions analysis is applied to a sample of 64 companies, previously grouped into two subsets of manufacturing SMEs from an emerging economy. The first group contains firms that have attained an accelerated internationalization. And the second one those that have followed a sequential internationalization.

The results show strong evidence that internationalization positively affects the probability of a better performance, and therefore more competitiveness of SMEs.

The proposed methodology is an invitation to use models other than linear regression to explain the relationship between internationalization and performance, studying the risk function of poor performance, whose characterization in the lifetime of SMEs. The result of this study clearly illustrates how internationalization affects the performance of SMEs for both those SMEs with accelerated internationalization and those with a sequential process of internationalization.

The implementation of quantitative methodologies, such as the analysis of hazards, has implications in the social practice of research in international business, by inviting the return of data from primary sources, obtained from direct sources, which, although they are not large samples, they are representative, and therefore the results of the well-applied methodology offer powerful and high-reliability information. Irreproducible and non-replicable research results threaten the credibility, usefulness and the very basis of all scientific fields. Studies in entrepreneurship, management and in international business are not exempt from this problem that affects the ethics and credibility of research works.

A literature review is presented exposing the disadvantages of the use of traditional correlation methodologies and proposes the methodology traditionally used in industrial engineering studies of hazard functions as a simple option, free of previous assumptions about the relation between internationalization and performance. Finally, the methodology is subjected to triple testing of conceptualization and measurement of internationalization, performance and the relation between internationalization and performance.

This chapter aims at providing an understanding of the research and devlopment (R&D) process in the pharmaceutical industry, by exploring the methodological challenges and approaches in the assessment of the determinants of innovation in the pharmaceutical industry. It (i) discusses possible methodological approaches to model occurrence of events; (ii) describes in detail competing risks duration models as the best methodological option in light of the nature of pharmaceutical R&D processes and data; (iii) concludes with an estimation strategy and overview of potential covariates that have been found to correlate with the likelihood of failure of R&D pharmaceutical projects.

Damage functions constitute an essential part of the modelling of critical infrastructure (CI) performance under the influence of climate events. This paper aims to compile and discuss publications comprising damage functions for transport assets.

The research included the collection of contemplable literature and the subsequent screening for damage functions and information on them. In conclusion, the derived damage curves and formulae were transferred to a unified design.

Damage functions for the transport sector are scarce in the literature. Although specific damage functions for particular transport assets exist, they mainly consider infrastructure or transport in general. Occasionally, damage curves for the same asset in different publications vary. Major research gaps persist in wildfire damage estimation.

The study scope was restricted to the hazards of fluvial floods and wildfires. Despite all efforts, this study did not cover all existing literature on the topic.

This publication summarises the state of the art of research concerning transport asset damage functions, and hence contributes to the facilitation of prospective research on CI performance, resilience and vulnerability modelling.

The purpose of this paper is to determine if lender experience in disposing of repossessed single‐family houses in the local market is significantly related to the probability a property will sell. In addition, other factors that are significantly related to the market duration of repossessed houses are identified.

The Cox proportional hazard model is used to analyze transaction data for 2,099 single‐family houses in Dayton, Ohio. Title to each of these properties was obtained by lenders through foreclosure. The study period approximates the first three years of the subprime mortgage crisis in the USA: 2007‐2009.

The marketing efforts of lenders with more local property disposition experience are found to be superior to the efforts of less experienced lenders. The results also indicate that the selling rate function increased over the study period, and there is seasonality in the data which is consistent with lenders attempting to limit holding costs.

The study is limited to the experience of lenders in a single local market over a three year study period. Additional research to determine if similar results apply in other markets would be a valuable addition to the literature.

While foreclosure is not a desirable outcome for any of the parties involved in a mortgage loan, the paper's results offer a bit of good news for lenders. The results are consistent with organizational learning theory which posits that experience should enhance performance. Given predictions that the mortgage crisis has not yet run its full course, lenders' performance in disposing of repossessed houses is likely to continue to improve.

This is the first study to apply the proportional hazard model to the study of foreclosed houses. This technique offers an advantage over previously applied methodologies because it allows the researcher to include properties that lenders did not sell during the study period into the analysis. All previous efforts were limited to sold properties and this restriction may have biased the previous results.

Credit derivatives continue to grow in popularity as well as complexity. While single‐name credit default swaps are still the most popular instruments, second‐generation products have become more commonplace. Second generation products are those whose payoffs are contingent on the viability of a number of firms and include instruments such as default baskets and synthetic collateralized debt obligations. The purpose of this paper is to provide a transparent and detailed account of default basket valuation along with thorough and intuitive explanations of comparative statics and the relationship between basket values and default correlation.

The paper delineates the standard approach to valuing default baskets and with its implementation examines results for two copula functions and the input assumptions which are critical to the valuation process.

It is found that the assumptions are critical to the valuation and that the copula chosen also has an impact on pricing and comparative statics.

This paper is very practical in its orientation and takes a pedagogical approach in its explanation of default baskets, the standard model, and key assumptions.

This paper fills a gap in the literature as prior works are more focused on certain enhancements or nuances of modeling basket credit derivatives while this work centers on the standard model and provides a thorough analysis and explanation of the comparative statics as well as a discussion of model limitations. This paper is ideal reading for those that seek an understanding of the modeling and risks associated with multi‐name credit derivatives.