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The main purpose of this study is to evaluate the extent of dropout students and identify the relationship between risk factors of dropout and the survival time of students.

The Kaplan–Meier estimator (KM), also known as the product-limit technique, is a nonparametric model function that is commonly used in estimating survival function events (Kaplan and Meier, 1958). The survival function's Kaplan–Meier estimators are used to estimate and graph survival probabilities as a function of time, as well as explanatory data analysis (EDA) for the survival data, including the median survival time, and compare for two or more of the survival events. In addition, Cox proportional hazards model is employed for modelling purpose.

Results of the Kaplan–Meier curves show that male students have lower survival rates than female, researchers have found that there is a difference between the survival times of the student's school types, results show students from English-based schools are higher than Arabic-based schools as suggested by the survival curve. Similarly, there is a difference between the survival times of students aging equal or greater than 25 and students aging less than 25 and survival function estimates of dropout according to high school grade marks has huge difference. These results were confirmed using log rank test as age, school type and marks were statistically significantly different while gender is not statistically significant.

There is no study of this kind from the Somalia context about the student's dropout. Subsequent to the outbreak of civil war in 1988 and the collapse of the central government in 1991, all public social services in Somalia including education centers were severely disrupted.

The statistical methods discussed in the previous section will be applied on a real dataset obtained from different offices of the university; most of the data were extracted from faculty of economics office and admission and record office. The data set comprised of 70 students from SIMAD university, consists of full-time faculty of economics students who enrolled at the university in the academic year of 2017–2018 until two years of diploma, students either complete 24 months of diploma or leave the university and that is the event of interest.

The purpose of this research is to undertake an examination of the impacts of socio‐demographic and economic variables on the probability of purchasing financial products. There is relatively little empirical research that has been taken to understand how the underlying economy affects customers' subsequent financial product purchase behaviours. Understanding this influence would improve prediction of when purchases will occur and hence is important for the Customer lifetime value models of financial service organisations.

Two proportional hazard modelling approaches – Cox and Weibull – are compared in terms of predictive ability on a data set from a major insurance company. The risk factors for purchase are both economic and socio‐demographic.

The results show that the external economic environment is an extremely important influence in driving customers' financial products purchasing behaviours. Furthermore, the results also indicate that Cox's proportional hazard models are superior to Weibull proportional hazard models in this case because of an annual purchase effect.

Financial organisations need to consider the current economic conditions before determining how much marketing effort to undertake.

The originality of this paper is that it considers economic conditions and socio‐demographic variables in modelling the long run purchase behaviour of customers for insurance and savings products. It has a large data set from a major insurance company. It is also one of the first papers to make a detailed comparison between the semi‐parametric and parametric proportional hazard models in the bank marketing area.

Various theories predict that firm buyouts survive longer than newly created firms. The study aims to know whether it is the case for worker-owned firms (WOFs), i.e. firms owned and controlled mostly by their workers.

The author conducted a comparative survival analysis of French WOFs distinguished by their entry mode (i.e. newly created, worker buyouts (WBOs) of sound conventional firms, WBOs of conventional firms in difficulty or WBOs of non-profit organizations).

The hazard of exit is 32% lower for WBOs of sound conventional firms than newly created WOFs, 18% for WBOs of conventional firms in difficulty and 64% for WBOs of non-profit organizations. The current study confirms that WBOs, even of conventional firms in difficulty, have on average a survival advantage over newly created WOFs. Surprisingly, the author also shows that this survival advantage is similar across sectors with different knowledge intensity but is lower in high capital-intensive sectors than in low capital-intensive ones.

Endogeneity issues limit the scope of the results and should be tackled in future research. Overall, these findings show that WOFs are composed of groups with different survival likelihoods that are obscured if one only looks at the aggregate population.

With caution, support agencies could foster WBOs of firms in difficulty and of non-profit organizations as viable forms of entrepreneurship.

The current study offers the first survival analysis distinguishing four modes of entry among WOFs.

The purpose of this paper is to assess the capacity of two methodological approaches – discrete choice and survival analysis models – to investigate the relationship between socio-economic characteristics and turnover in a retailing company. A comparison of the estimation results under each model and their interpretation is carried out. The study provides a guide to determine, assess and interpret the effects of different driving factors behind turnover.

The authors use a data set containing information about 1,199 workers followed up between January 2007 and December 2009. First, not distinguishing voluntary and involuntary resignation, a binary logistic regression model and a Cox proportional hazards (PH) model for univariate survival data are set up and estimated. Second, distinguishing voluntary and involuntary resignation, a multinomial logistic regression model and a Cox PH model for competing risk data are set up and estimated.

When no distinction is made, the results point that wage and age exert a negative effect on turnover. Risk of resignation is higher for male, single, not married and Spanish nationals. When the distinction is made, previous results hold for voluntary turnover: wage, age, gender, marital status and nationality are significant. However, when explaining involuntary turnover, all variables except wage lose explaining power. The survival analysis approach is better suited as it measures risk of resignation in a longitudinal way. Discrete choice models only study the risk at a particular cut-off point (24 months in case of this study).

This paper is a systematic application, evaluation and comparison of four different statistical models for analysing employee turnover in a single firm. This work is original because no systematic comparison has been done in the context of turnover.

This study examines the survival probability of the firms during the COVID-19 pandemic and identifies the effects of pandemic-era business strategies on firm survival across sectors and sizes.

This study combines World Bank Enterprise Survey data with three consecutive follow-up COVID-19 survey data. The COVID-19 surveys are the follow-up surveys of WBES, and they are done at different points of time during the pandemic. Both WBES and COVID-19 surveys follow the same sampling methods, and the data are merged based on the unique id number of the firms. The data covers 12,551 firms from 21 countries in different regions such as Africa, Latin America, Central Asia and the Middle East. The study applies Kaplan–Meier estimate to analyze the survival probability of the firms across sectors and sizes. The study then uses Cox non-parametric regression model to identify the effect of business strategies on the survival of the firms during the pandemic. The robustness of the Cox model is checked using the multilevel parametric regression model.

The study's findings suggest that a firm's survival probability decreases during the pandemic era. Manufacturing firms have a higher survival probability than service firms, whereas SMEs have a higher survival probability than large firms. During the pandemic period, business strategies significantly boost the probability of firm survival, and their impacts differ among firm sectors and sizes. Several firm-specific factors affect firm survival in different magnitudes and signs. Except in a few cases, the findings also indicate that one strategy positively moderates the influence of another strategy on firm survival during a pandemic.

COVID-19 pandemic has drastically affected the business across the globe. Firms adopted new business processes and strategies to face the challenges created by the pandemic. The critical research question is whether these pandemic-era business strategies ensure firms' survival. This study attempts to identify the effects of these business strategies on firms' survival, focusing on a comprehensive firm-level data set that includes firms from different sectors and sizes of countries from various regions.

The purpose of this paper is to suggest a method of selecting efficient customer service programmes and of providing relevant customer information to dealers, based on the analysis of repeat-purchase behaviour data in the automobile industry.

A recurrent event model is proposed and employed to determine which variables affect repurchasing behaviour in consumers' repurchase cycles. Unlike the conventional recurrent event model, the proposed model uses common variables for all strata, as well as stratum-specific variables.

Empirical results show that age, price difference, change in vehicle type, and marketing promotion affect the likelihood of repeat purchase. VIP service centres and repair services are effective marketing tools, and dealers should pay more attention to existing customers having certain characteristics, depending on prior purchase behaviour.

Though many customer service programmes are devised and implemented at great cost, Customer Relationship Management (CRM) data reveal that classic car-care services are the most essential. CRM can provide dealers with essential customer information that enables real purchases.

Collecting primary data on automobile purchase behaviour and customer service usage is difficult, and therefore, customer behaviour strategy is often formulated using basic principles alone. The paper proposes a method to construct a service strategy and formulate deal guidelines based on CRM data and statistical modelling.

The purpose of this paper is to identify the extent to which the company's post- initial public offering (IPO) outcome varies, along with the determinants of the post-IPO outcomes.

The authors use Cox proportional hazards models to examine what determines the company's post-IPO transition to one of the classified outcomes, delisting, acquisition due to strong performance, and acquisition due to weak performance. The authors develop models taking in a range of information concerning pre-IPO characteristics, offering characteristics, financial indicators, company specifics, industry features, and corporate ownership and governance.

Delisting is predominantly influenced by the company’ pre-IPO operating performance, as well as financial indicators and governance structure at the time of the IPO. Sound governance structure and good financial standing of the company aid it to achieve its goal. Mergers and acquisitions (M&As) of both forms are distinguished most significantly by ownership structure and industry features, which is consonant with the position that M&As are majorly motivated by social concerns and corporate control considerations. Centrally, corporate evolution is jointly shaped by market force and state control.

The findings can inform public policy decisions. There is a case for gradual introduction of institutional changes which facilitate, regulate, and monitor orderly market operations in line with the market mechanism and sound corporate governance.

The study is among the first efforts to examine what determines the company's transition to one of the post-IPO states following the IPO in China's stock market.

The purpose of this paper is to examine gender differences in promotion probabilities of the academic staff of a large university in The Netherlands, taking into account the sex segregated context of the faculty.

The study uses records of the university's personnel information system from 1990 to 2006, covering the data of 1,792 employees in the academic ranks who have entered since 1990. Cox regression models are used to test three hypotheses.

The findings show that women have lower promotion probabilities than men. The gender differences are primarily explained by differences in years of service and external mobility, and not by the sex segregated context of the faculty. A higher share of women decreases the odds of being promoted for both men and women. Gender differences in working hours do not explain the gender differences in promotion probabilities.

The paper adds to the existing literature because event history analyses have hardly been applied to personnel records for investigating the impact of the sex segregated context on promotion probabilities.

The role of list price is often discussed in a narrative describing sellers’ preferences or sellers’ price expectations. This paper aims to investigate a set of list price strategies that real estate brokers have available to influence the outcome of the sale, which may be many times self-serving.

By analyzing real estate brokers’ arguments on the choice of the list price level, a couple of hypotheses are formulated with regard to different expected outcomes that depend on the list price. This study empirically tests two hypotheses for the underlying incentives in the choice of list price from the real estate broker’s perspective: lower list price compared to market value leads to the higher sales price, lower list price compared to market value leads to a quicker sale. To investigate the two hypotheses, this paper adopts different methodological frameworks: H1 is tested by running a classical hedonic model, while H2 is tested through a duration model. This study further tests the hypotheses by splitting the full sample into two different price segments: above and below the median list price.

The results show that H1 is rejected for the full sample and for the two sub-samples. That is, contrary to the common narrative among brokers that underpricing leads to a higher sales price, underpricing lower sales price. H2, however, receives support for the full sample and for the two sub-samples. The latter result points to that brokers may be tempted to recommend a list price significantly below the expected selling price to minimize their effort while showing a high turnover of apartments.

Although there are a large number of previous studies analyzing list price strategies in the housing market, this paper is one of the few empirical studies that address the effect of list price choice level on auction outcomes of non-distressed housing sales.

This research considers the question of whether unemployment insurance benefit and labour-market activation measures induce the likelihood of re-employment and whether this effect differs for natives and immigrants.

Statistical processing was carried out on the European Union Statistics on Income and Living Conditions cross-sectional data for Finland for the period 2004 to 2016. Propensity score matching analysis was undertaken to investigate whether a treatment effect (unemployment insurance benefit) was a predictor of success in increasing re-employment rates, when controlling for participation in labour-market policy measures, subsidized employment and personal background characteristics.

We find that the probability of re-employment for recipients of unemployment benefits is half that of non-recipients of benefits. Due to the influence of subsidized employment, subsequent employment income decreases for recipients of unemployment benefits and especially for immigrants. Finally, we find that due to the influence of subsidized employment, time spent as a full-time employee decreases for recipients of unemployment benefits and especially for immigrants.

Although our results indicate that benefit determination has a marked impact on re-employment probabilities, unobserved variables turn to play a significant role in selection of labour-market activation measures. In this respect, we find the treatment assignment to activation policy measures depends on influence of unobserved variables and this effect is more important for the re-employment rates of natives than it is for immigrants.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2019-0668.