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This special issue of the Review of Finance and Accounting presents six papers which use survival analysis as a research method to examine a wide range of research questions in accounting, economics, and finance. Although researchers have increased their use of survival analysis as a research method in recent years, its presence in the methods ‘toolbox’ of these disciplines is not comparable to the physical sciences or other social sciences. Whereas survival analysis is routinely used in biomedicine, sociology, and engineering to study questions related to patient survival, marriage, and equipment failure, the use of survival analysis in economic‐based disciplines is not comparable to other disciplines. This issue was assembled in order to highlight the use of survival analysis in economics‐based disciplines with the express purpose of encouraging its use as a research method to examine a wider range of research issues. The papers assembled in this issue are written by authors who have previously demonstrated an interest in survival analysis.

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.

To determine the relationship among covariates used in financial distress studies.

The study selects four specific bankruptcy studies and employs canonical correlation analysis to determine the relationship among the different variable sets that these studies used as predictors of financial distress. Canonical correlation analysis identifies the relationship and provides an indication of the amount of redundancy that exists between two variable sets. The four studies are representative of the genre, similar as to choice of statistical technique, and frequently cited by researchers.

The research findings indicate that the relationships between the alternative variable sets are very weak and alternative variable sets do not represent similar financial relationships. Redundancy coefficients suggest that, if one variable set is redundant to another variable set, it is because the redundant variable set, is much smaller than the predictor variable set.

The results suggest that there is not much similarity among the variable sets used in financial distress studies; to the extent that there is any similarity, it is due to variables common to each set or one variable set being larger than the other variable set. Ad hoc variable selection in financial distress studies results in the use of alternative variable sets containing heterogeneous variables unrelated to one another.

A common criticism of financial distress research is that a theory of corporate failure does not exist. Variable selection is not prompted by economic theory but is based upon suggestions in the literature, the success of variables in earlier studies, or the selection of a large set of variables with an accompanying data reduction procedure. Despite nearly 30 years of research in the area, the absence of an inter‐correlational structure among alternative variable sets highlights the atheoretical nature of financial distress research.

The control of an inventory where spare parts demand is infrequent has always been difficult to manage because of the randomness of the demand, as well as the existence of a large proportion of zero values in the demand pattern. The purpose of this paper is to propose a just-in-time (JIT) spare parts availability approach by integrating condition monitoring (CM) with spare parts management by means of proportional hazards models (PHM) to eliminate some of the shortcomings of the spare parts demand forecasting methods.

In order to obtain the event data (lifetime) and CM data (first natural frequency) required to build the PHM for the spares demand forecasting, a series of fatigue tests were conducted on a group of turbomachinery blades that were systematically fatigued on an electrodynamic shaker in the laboratory, through base excitation. The process of data generation in the numerical as well as experimental approaches comprised introducing an initial crack in each of the blades and subjecting the blades to base excitation on the shaker and then propagating the crack. The blade fatigue life was estimated from monitoring the first natural frequency of each blade while the crack was propagating. The numerical investigation was performed using the MSC.MARC/2016 software package.

After building the PHM using the data obtained during the fatigue tests, a blending of the PHM with economic considerations allowed determining the optimal risk level, which minimizes the cost. The optimal risk point was then used to estimate the JIT spare parts demand and define a component replacement policy. The outcome from the PHM and economical approach allowed proposing development of an integrated forecasting methodology based not only on failure information, but also on condition information.

The research is simplified by not considering all the elements usually forming part of the spare parts management study, such as lead time, stock holding, etc. This is done to focus the attention on component replacement, so that a just-in-time spare parts availability approach can be implemented. Another feature of the work relates to the decision making using PHM. The approach adopted here does not consider the use of the transition probability matrix as addressed by Jardine and Makis (2013). Instead, a simulation method is used to determine the optimal risk point which minimizes the cost.

This paper presents a way to address some existing shortcomings of traditional spare parts demand forecasting methods, by introducing the PHM as a tool to forecast spare parts demand, not considering the previous demand as is the case for most of the traditional spare parts forecasting methods, but the condition of the parts in operation. In this paper, the blade bending first mode natural frequency is used as the covariate in the PHM in a laboratory experiment. The choice of natural frequency as covariate is justified by its relationship with structural stiffness (and hence damage), as well as being a global parameter that could be measured anywhere on the blade without affecting the results.

This paper investigates how well regulator examinations predict bank failures and how best to incorporate examination information into an econometric model of time‐to‐failure. We estimate proportional hazard models with time‐varying covariates and find that examiner ratings help explain the failure hazard. Both the overall rating of a bank's condition and management, i.e., the composite CAMELS rating, and ratings of specific components contain information. In addition, we find that the marginal “effect” of ratings is non‐linear, in that the impact of a rating downgrade on the hazard is larger, the weaker a bank's initial rating.

One of the key elements of survival models is that they enable the researcher to determine whether the length of time an individual (or economic entity) spends in a particular state affects the probability of exiting that state. Natural applications in economics and finance include the analysis of unemployment spells, corporate bankruptcies and mortgage pre‐payments. The distinguishing feature of most applications is the definitive event that marks the transition from the origin to the transition state. We believe that limiting the use of survival analysis to applications in which the event duration appears to be ‘naturally’ available is an unnecessary constraint. For example, the date of emergence from Chapter 11 bankruptcy protection is a subjective management decision and the true event duration, though treated as definitive, is in reality quite ambiguous. We propose that survival models can and should be extended to analyze researcher‐defined events such as the length of time a stock takes to reach a preset price target. We illustrate our point with an examination of IPO aftermarket behavior.

The purpose of this study is to clarify the relationship between getting quality awards by companies and their financial performance in Iran's business.

In the first step, the relationship between awards scores and financial performance by canonical correlation analysis was examined. Then, binary and multinomial logistic regression was used to determine the degree of impact of each financial performance measure on getting quality awards. Finally, two forecasting functions were explored: the probability of achieving quality awards and the probability of achieving different levels of these awards.

Based on the analyzed data of 112 companies through canonical correlation analysis, there was a weak relationship between financial performance and getting quality awards. Also, by using logistic regression, no result was found to prove the impact of financial performance measures on getting Iran's national quality awards. It can be concluded that conceptually, deployment of excellence organizational models will not result in favorable outcomes, especially in the financial scope. Also, practically, excellence models have not been well deployed in Iranian companies, or these models do not fit to Iran's business environment. Organizational culture may not be consistent with quality.

Quality awards are given to qualified companies following the establishment of models of excellence such as the European Foundation for Quality Management (EFQM). The main novelty of this research is to clarify the relationship between getting quality awards by companies and their financial performance in Iran's business.

The purpose of this paper is to analyze the level and forms of advertising in the French telecommunications sector between 1952 and 2002 in order to understand the transformation of the leading organization in the sector and its succesful adoption of increasingly sophisticated practices. The context of increased market orientation is examined to investigate how such practices emerge.

Extensive historical study of primary source material and secondary sources was conducted to develop acomparison of three eras. For each era, major changes in relation to advertising and promotional practices are identified along with key contextual elements to understand the relative importance of internal or external influences on the adoption of market-oriented practices.

Initially, advertising and promotional practices studied were introduced gradually within the state-run organization (1952–1973). They subsequently became increasingly important and systematic (1974–1985) before finally becoming those of a modern organization (1986–2002) in the competitive sphere. In addition to single institutional messages aimed at either consumer or business markets, more abstract forms of communication were used over time and publicity was increasingly targeted at different segments.The French telecommunications sector was aware of the necessity to engage in advertising and promotional activities prior to the existence of competition in its main consumer market. Adoption of such customer-oriented practices was more pronounced initially in the business segment. Advertising and promotional activities to consumers became increasingly significant as the administration modernized and developed innovative services. This growth in promotion and in its sophistication accelerated within the new competitive environment following deregulation and, in particular, with the growth of the mobile sector. Both the external environment and internal organizational transformations thus need to be taken into account when analyzing growing adoption of advertising and promotion.

This systematic study of the introduction of advertising and promotional practices in the French telecommunications sector highlights how public organizations can introduce practices linked to market orientation. In the organization studied, the fact that increased advertising and promotional activity was driven by organizational transformation in the second of the three eras studied indicates the importance of investigating internal influences and external factors such as competition.