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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 COVID-19 pandemic severely impacted tourism, and the hotel and restaurant industry was the most affected sector, which faced issues related to business uncertainty and unemployment during the crisis. The analysis of recovery time and the influence factors is significant to support policymakers in developing an effective response and mitigating the risks associated with the tourism crisis. This study aims to investigate numerous factors affecting the recovery time of the hotel and restaurant sector after the COVID-19 crisis by using survival analysis.

This study uses the quarterly value added with the observation time from quarter 1 in 2020 to quarter 1 in 2023 to measure the recovery status. The recovery time refers to the number of quarters needed for the hotel and restaurant sector to get value added equal to or exceed the value added before the crisis. This study applies survival models, including lognormal regression, Weibull regression, and Cox regression, to investigate the effect of numerous factors on the hazard ratio of recovery time of hotels and restaurants after the COVID-19 crisis. This model accommodates all cases, including “recovered” and “not recovered yet” areas.

The empirical findings represented that the Cox regression model stratified by the area type fit the data well. The priority tourism areas had a longer recovery time than the non-priority areas, but they had a higher probability of recovery from a crisis of the same magnitude. The size of the regional gross domestic product, decentralization funds, multiplier effect, recovery time of transportation, and recovery time of the service sector had a significant impact on the probability of recovery.

This study contributes to the literature by examining the recovery time of the hotel and restaurant sector across Indonesian provinces after the COVID-19 crisis. Employing survival analysis, this study identifies the pivotal factors affecting the probability of recovery. Moreover, this study stands as a pioneer in investigating the multiplier effect of the regional tourism and its impact on the speed of recovery.

In the corporate world, there is no certainty of survival. This research aims to identify firm-level factors that increase or decrease a firm's probability of exit and survival.

The study examines 153 listed textile sector firms in Pakistan over a 10-year period from 2009 to 2018, comprising 1,413 observations. The semi-parametric Cox regression model is used to process the results.

The study finds that larger and exporting firms are more likely to survive, while those with a high ratio of fixed assets to total assets, high expenditure on advertising and variable costs are less likely to survive. The relationship between age and firm survival is inconclusive.

Adaptability to the external environment provides a competitive advantage that is crucial for textile firms to reduce their chances of exit. The research is valuable for strategic managers and policymakers to identify focus areas to prevent firm exit.

This study supports the active learning theory, which suggests that new entrants in the textile sector of Pakistan should focus on becoming active market players, increasing efficiency and reducing variable costs to survive.

Pakistan ranks third globally in terms of newborn deaths occuring within the first 24 hours of life. With a neonatal mortality rate of 42.0%, it carries the highest burden compared to neighboring countries such as Bangladesh (17%), India (22.7%) and Afghanistan (37%). While there has been a decline in neonatal mortality rates in Pakistan, the pace of this decline is slower than that of other countries in the region. Hence, it is crucial to conduct a comprehensive examination of the risk factors contributing to neonatal mortality in Pakistan over an extended period. This study aims to analyze the trends and determinants of neonatal mortality in Pakistan over three decades, providing valuable insights into this persistent issue.

The study focused on neonatal mortality as the response variable, which is defined as the death of a live-born child within 28 days of birth. Neonates who passed away during this period were categorized as “cases,” while those who survived beyond a specific timeframe were referred to as “noncases.” To conduct a pooled analysis of neonatal mortality, birth records of 39,976 children born in the five years preceding the survey were extracted from four waves (1990–2018) of the Pakistan Demographic and Household Survey. The relationship between risk factors and the response variable was examined using the Cox Proportional Hazard Model. Neonatal mortality rates were calculated through the direct method using the “syncmrates” package in Stata 15.

During the extended period in Pakistan, several critical protective factors against neonatal mortality were identified, including a large family size, improved toilet facilities, middle-aged and educated mothers, female children, singleton live births, large size at birth and longer birth intervals. These factors were found to reduce the risk of neonatal mortality significantly.

This study makes the first attempt to analyze the trends and patterns of potential risk factors associated with neonatal mortality in Pakistan. By examining a large dataset spanning several years, the study provides valuable insights into the factors influencing neonatal mortality.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0604

The purpose of this study is to demonstrate the effect of initial international joint ventures (IJV) structural conditions on two main equity-based instability facets: change of IJV ownership structure and acquisition of the IJV by one of the IJV partners. Drawing on the transaction cost theory, the authors examine three key initial structural conditions: IJV formation mode, number of partners and IJV’s ownership structure.

The authors apply the “Event history analysis” technique to test the hypotheses using a data set of 140 French-foreign JVs.

The findings show that the mode of an acquisitive IJV and unequal equity positions held by partners increase the likelihood of a change of IJV’s ownership structure and its eventual acquisition by one of the partners. In addition, the findings show that while an increase in the number of IJV partners is directly related to the change of IJV ownership structure, it has a statistically insignificant effect on IJV acquisition.

Drawing on “transaction costs” arguments, this study advances the literature by offering fine-grained results related to the effects of initial structural conditions on aspects of unintended instability in French-foreign JVs.

This study aims to contribute to discussions on peace between hostile nonmajor powers by focusing on the behavior of major powers. Specifically, alliances between nonmajor and major powers are explored to determine whether such ties contribute to transitions to higher levels of peace. Moreover, systemic factors involving power dynamics and relationships between major powers are also evaluated.

Multiple data sets which altogether covered the era from 1816 to 2010 were analyzed. All pairs of countries that were former foes were considered. Cox hazard regression was conducted.

Systemic instability is influential at transitions from lowest levels of peace for nonmajor power dyads. Eras where major powers are operating multilaterally appear to play a highly limited role in nonmajor powers attaining stable peace. However, alliances with major powers are relatively more crucial in these discussions for nonmajor powers and contribute to higher levels of peace being attained by nonmajor powers.

Further research in particular with case studies can help to elucidate and extend the statistical findings.

Based on the findings, the design and operations of alliances can create more space to hear a wider range of issues that allies can be facing.

While major powers clearly have considerable capacity and global outreach, there has been little attention to whether and how they contribute to former foes attaining higher quality of peace.

In this paper, the authors study the failure of Russian banks between 2012 and 2019.

The authors analyze the entire population of Russian banks and combine a logit model with the survival analysis.

In addition to the usual determinants, the authors find that not-failed banks have higher levels of fulfillment of the Central Bank requirements of solvency, liquidity, provide fewer loans to their shareholders and own more shares of other banks. The results of this study suggest an asymmetric effect of the strategic orientation of banks: whereas the proportion of deposits from firms is negatively related to the probability of failure, the loans to firms are positively related to bankruptcies. According to this research, the fact of being controlled by a foreign bank has a significant negative relationship with the likelihood of failure and moderates the effect of bank size, performance and growth on the bankruptcy likelihood.

On the whole, the results of this study support the new Central Bank rules, but show that the thresholds imposed by the Russian regulator actually do not make a difference between failed and not failed banks in the short and medium term.

The authors specially focus on the effectiveness of new rules issued by the Central Bank of Russia in 2013.

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.

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.

This paper aims to provide a brief review of the work on startup survival and a conceptual framework of factors influencing a startup firm’s survival. In addition, it lists significant gaps and recommends avenues for future research.

This paper conducted a systematic literature review of peer-reviewed journal articles indexed in Scopus, Web of Science and EBSCO databases using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A total of 140 articles published in 72 journals between 1993 and 2021 were considered for the review.

The comprehensive review revealed that most of the studies have applied a single theoretical lens and have taken place in advanced economies, with a narrow focus on emerging economies. Empirical research has prominently applied regression-based models to analyse the relationship between the antecedents and the outcomes. Internal resources such as human capital, financial capital and physical capital and non-financial performance measures such as survival, growth and employment are the studies’ prominently used antecedents and outcome variables. However, a limited number of studies have used mechanisms of mediation and moderation.

Despite the substantial scientific and practical discussion on startup survival, to the best of the authors’ knowledge, no comprehensive review has been undertaken to date, which provides a systematic and comprehensive compilation of the knowledge on the topic. This study aims to develop a unique landscape of scientific advancement by methodically reviewing, categorising and synthesising the current body of knowledge on the topic.