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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.

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.

Wage employees enter self-employment either directly or in a staged manner and may subsequently undertake multiple stints at self-employment. Extant research on the relationship between entry modes and the persistence and outcomes of self-employment is inconclusive. This study investigates the relationship between wage employees’ initial mode of entry into self-employment and the duration of the subsequent first two stints of self-employment.

This study used a matched longitudinal sample of 9,550 employees who became majority owners of incorporated firms from 2005 to 2016.

The findings demonstrate that the initial mode of entry into self-employment matters for the first two stints at self-employment. Staged entry into self-employment was associated with a shorter first stint and became insignificant for the second stint. Staged entry into self-employment was positively related to the odds of becoming self-employed for the second time in the same firm.

Using a comprehensive and reliable dataset, the paper shifts focus from the aggregated onward journey of novice entrepreneurs (survival as the outcome) to the duration of their self-employment stints. By doing so, the paper offers insights into the process of becoming self-employed and the patterns associated with success/failure in entrepreneurship associated with self-employment duration.

This paper aims to review, discuss and synthesize the literature focusing on the Indian initial public offering (IPO) market. Understanding the Indian IPO market can help answer broader corporate finance questions. The growing number of IPOs in the Indian context, coupled with the increasing importance of the Indian economy in the global market, makes this review an essential topic.

The systematic literature review methodology was adopted to review 111 papers published between 2002 and 2021. The authors used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach during the review process. Additionally, the authors use a bibliometric review methodology to examine the pattern and trend of research in this area of interest. Furthermore, the authors conduct a critical review and synthesis of the top 20 papers based on citations. The authors also use a co-citation network and manual content analysis method to identify key research themes.

This review helps in identifying major themes of research in this area of interest. The authors find that majority of the research has focused on IPO performance whereas post-IPO performance needs critical attention as well. The authors develop a comprehensive framework and future research agenda based on their discussion.

Meta-analysis of the literature can be conducted to gain better insights into the findings of prior studies.

This review paper develops a comprehensive overview on Indian IPO market which can be of interest not only to Indian scholarship. India as an economy is increasingly gaining attention at the global level. Hence, the future research objectives as illustrated in the study can be of interest for the global scholarship also.

To the best of the authors’ knowledge, this is the first comprehensive review paper that examines, synthesizes and outlines the future research agenda on Indian IPO studies. This review can be useful for researchers, business policymakers, finance professionals and anyone else interested in the Indian IPO market.

The study aims to determine the outcomes of mentorship in an online game system, as well as the characteristics of good mentors.

A combination of anonymized survey measures and in-game behavioral measures were used to power longitudinal analysis over an 11-month period in which protégés and non-mentored new players could be compared for their performance, social connections and retention.

Successful people were more likely to mentor others, and mentors increased protégés' skill. Protégés had significantly better retention, were more active and much more successful as players than non-protégés. Contrary to expectations, younger, less wealthy and educated people were more likely to be mentors and mentors did not transfer their longevity. Many of the qualities of the mentor remain largely irrelevant—what mattered most was the time spent together.

This is a study of an online game, which has unknown generalizability to other games and to offline settings.

The results show that getting mentors to spend dedicated time with protégés matters more than their characteristics.

Good mentorship does not require age or resources to provide real benefits.

This is the first study of mentorship to use survey and objective outcome measures together, over time, online.

This study examines the appropriate measures that need to be intensified among African countries to achieve sustainable environment to mitigate climate change.

The study employs panel data covering the period 2000 to 2020 among 54 African countries and Cox proportional hazard model for the analysis.

Estimates indicate that the practice of carbon farming, the development of rooftop gardens, renewable energy production and consumption contribute positively toward achieving sustainable environment, while governance adversely affects this objective of achieving sustainable environment.

The study recommends that governments should enforce the constant practice of carbon farming among these countries through passing laws to enforce its application among farmers and allocate 2% of ministry of agriculture's budget toward financing carbon farming for poor farmers.

Empirical studies have been carried out exploring measures to deal with climate change. Nonetheless, the appropriate measures of achieving sustainable environment to mitigate climate change have less been explored in literature on Africa. Hence, this study fills the gap in existing empirical studies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2023-0290.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

Strategic flexibility (SF) has become increasingly important for firms because of the fast changes in the external environment. In line with the practical importance of SF, an emerging research field has developed around it that has attempted to understand the nature of SF and the key relationships. The aim of this study is to unveil the semantic structure of the recent literature on SF and to suggest new promising areas for future research.

The authors conduct a systematic literature review with a bibliographic analysis technique, which allows authors to identify the main recent streams in the literature, as well as offer reflections and suggestions for future research.

The authors uncover three main emerging areas in the research on SF, namely SF as a dynamic capability, the role of knowledge management for SF and the relationship between a firm SF and the external environment. The authors put forward three avenues for future research on SF: Avenue 1. SF, business model innovation (BMI) and other dynamic capabilities (DC), Avenue 2. Digital technologies and SF/organizational agility and Avenue 3. SF and sustainability. Articles included in the special issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” contribute to Avenue 2, thus paving the way for filling some of the identified gaps regarding the relationship between SF and digitalization.

To the best of authors’ knowledge, this is the first literature review on SF that uses a bibliometric approach to draw conclusions on the findings in the literature. The review contributes to the theoretical understanding of SF by illustrating and explicating core topics that have persisted over time, as well as by presenting three main avenues for further developing authors’ knowledge around SF.

This study aims to investigate a startup accelerator’s decisions toward exerting effort in an information acquisition process and selecting an information disclosure strategy. In particular, the authors are interested in examining which factors may cause the accelerator to report more or less accurate information, which will subsequently affect the investment decision and the outcome of the ventures. This study examines the impact of the equity share taken by the accelerator on the effort level being exerted in the information acquisition process, as well as the accelerator’s decision on the information disclosure regime.

The authors use mathematical models built upon well-established theoretical and practical concepts to analyze the research problems and derive the findings.

The authors show that when the accelerator takes a sufficiently large equity share from the entrepreneur in exchange for admitting the entrepreneur’s venture into the acceleration program, the accelerator is motivated to exert a significant level of effort to observe an accurate signal for the quality of the venture, and then disclose the information about the venture’s quality consistently with the observed signal (informative disclosure regime). On the other hand, if the accelerator takes a small equity share, it is optimal for her to exert no effort in the information acquisition process and simply adopt the basic disclosure regime, where the accelerator reports the quality of the venture based solely on the ex ante expected payoff of the venture, regardless of the observed signal.

The results indicate that an equity sharing scheme, which awards a sufficient amount of equity to the accelerator, can be an effective tool to help obtain accurate information about the quality of a startup venture and make a well-informed investment decision.

This research illustrates that the ownership stake of the accelerator can potentially indicate the accuracy of the information about the venture provided by the accelerator to outside investors. That is, when the stake held by the accelerator is large, the investors can conjecture that the information about the venture reported by the accelerator may be highly accurate and reliable. In contrast, if the accelerator holds a small stake, then it is likely that the information provided by the accelerator may not add any value to the publicly available information. These insights can guide investors (e.g. angle investors, venture capitalists, etc.) in making well-informed startup investment decisions.

Family policy is an area where policy transfer has garnered a lot of attention lately. A growing body of research demonstrates policymakers' interest in and willingness to adopt foreign family policies. However, previous studies have tended to neglect the second mechanism of policy transfer: resistance. This manuscript aims to address this research gap by exploring both the willingness and resistance to policy transfer in Czech and Korean childcare and leave policies.

This study employs a qualitative research design, incorporating structured expert interviews instrumental in in-depth thematic analysis.

The analysis shows that policymakers in both countries demonstrated interest and willingness to transfer family policies, albeit employing different strategies and to varying extents. Moreover, the two countries exhibited significant differences in resistance to family policy transfer, with resistance in the Czech Republic being more frequent and effective. Resistance is directed towards both forced and voluntary transfers, although it isn't always against transfers that require a paradigm change. Policy transfer and non-transfer can concurrently be perceived as threats.

The study concludes that integrating both policy transfer and resistance in the analyses helps to shed light on cross-national differences in family policy change and contributes to a more nuanced portrayal of the world of policy transfer in this policy field.