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This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.

The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.

A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.

This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.

Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

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.

Safety efficiency is the key to balance safety and production in construction industry; but the existing safety efficiency evaluation methods have the limitations of overestimating efficiency and ignoring undesirable outputs; therefore, according to the characteristics of safety production in construction industry, this paper innovatively develops a new cross-efficiency data envelopment analysis method to analyze safety efficiency, which can solve the limitations of traditional methods; and then the safety efficiency and its influencing factors of China's construction industry are analyzed, and some useful conclusions are obtained to improve its safety efficiency.

A new cross-efficiency data envelopment analysis method with undesirable outputs is proposed; and the two-stage efficiency analysis framework is designed.

First, the construction industries in different areas have different reasons for affecting their safety efficiency; second, the evaluation results of global safety priority tend to be more acceptable; third, frequent safety accidents and low resource utilization lead to a slow downward trend of the safety efficiency of China's construction industry in the long run; fourth, construction engineering supervision, construction industrial scale, and construction industrial structure have the significant impact on safety efficiency.

Theoretically, a new cross-efficiency data envelopment analysis method with undesirable outputs is proposed for evaluating safety efficiency; practically, the safety efficiency and its influencing factors of China's construction industry are analyzed.

Based on dual information asymmetry, the two-stage segmented compensation mechanism for technological innovation of civilian enterprises’ participation in military (CEPIM) has been discussed.

On the basis of the traditional principal-agent problems, the incentive compatibility condition is introduced as well as the hybrid incentive compensation model is established, to solve optimal solution of the compensation parameters under the dynamic contract condition and the validity is verified by numerical simulation.

The results show that: (1) The two-stage segmented compensation mechanism has the functions of “self-selection” and “stimulus to the strong”, (2) It promotes the civilian enterprises to obtain more innovation benefit compensation through the second stage, (3) There is an inverted U-shaped relationship between government compensation effectiveness and the innovation ability of compensation objects and (4) The “compensable threshold” and “optimal compensation threshold” should be set, respectively, to assess the applicability and priority of compensation.

In this paper, through numerical simulation, the optimal solution for two-stage segmented compensation, segmented compensation coefficient, expected returns for all parties and excess expected returns have been verified under various information asymmetry. The results show that the mechanism of two-stage segmented compensation can improve the expected returns for both civilian enterprises and the government. However, under dual information asymmetry, for innovation ability of the intended compensation candidates, a “compensation threshold” should be set to determine whether the compensation should be carried out, furthermore an “optimal compensation threshold” should be set to determine the compensation priority.

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.

The purpose of this paper is to examine the impact of directors’ and officers’ liability insurance (D&O insurance hereafter) on corporate governance and firm performance, with a specific focus on investment efficiency.

Using a sample of Chinese A-share listed firms from the period 2007 to 2020, this study uses Ordinary Least Squares regressions to investigate the research questions, as well as moderating and mediating effects. Additionally, alternative measures of investment efficiency are used, and the Heckman two-stage model and propensity score matching model are used to demonstrate the consistency of the findings and to mitigate the risk of endogeneity.

The findings of this study suggest that purchasing D&O insurance has a detrimental impact on corporate investment efficiency, particularly in the context of over-investment activities; robust internal governance mechanisms, exemplified by a higher shareholding ratio of the top shareholder and enhanced internal control quality, alleviate this negative effect; and financing constraints act as a mediating factor in the association between D&O insurance and investment efficiency.

Corporate investment efficiency is of significant importance for both national macroeconomic growth and micro-enterprise development. Notably, the prevalence of D&O insurance among Chinese firms is progressively increasing, thus exerting a growing influence. This study contributes to the existing literature on D&O insurance and corporate investment efficiency, providing valuable insights into the economic impact of D&O insurance on Chinese firms. The empirical evidence presented herein facilitates future reforms and adjustments.

This Study aims to present the seismic hazard assessment of the earthquake-prone eastern of Iran that has become more important due to its growing economic importance. Many cities in this region have experienced life and financial losses due to major earthquakes in recent years. Thus, in this study the seismic hazard maps and curves, and site-specific spectrums were obtained by using probabilistic approaches for the region.

The seismotectonic information, seismicity data and earthquake catalogues were gathered, main active seismic sources were identified and seismic zones were considered to cover the potential active seismic regions. The seismic model based on logic tree method used two seismic source models, two declustered catalogues, three choices for earthquake recurrence parameters and maximum considered earthquakes and four ground motion predicting (attenuation) models (GMPE).

The results showed a wide range of seismic hazards levels in the study region. The peak ground acceleration (PGAs) for 475 years returns period ranges between 0.1 g in the north-west part of the region with low seismic activity, to 0.52 g in the south-west part with high levels of seismicity. The PGAs for a 2,475-year period, also ranged from 0.12 to 0.80 g for the same regions. The computed hazard results were compared to the acceptable level of seismic hazard in the region based on Iran seismic code.

A new probabilistic approach has been developed for obtaining seismic hazard maps and curves; these results would help engineers in design of earthquake-resistant structures.

Climate change and the COVID-19 pandemic are complex and have multifaceted effects on countries in an unpredictable and unprecedented manner. While both COVID-19 and the climate crisis share similarities, they also have some notable differences. Being both systemic in nature with knock-on and cascading effects that propagate due to high connectedness of countries, COVID-19, however, presents imminent and directly visible dangers, while the risks from climate change are gradual, cumulative and often distributed dangers. Climate change has more significant medium and long-term impacts which are likely to worsen over time. There is no vaccine for climate change compared to COVID-19. In addition, those most affected by extreme climatic conditions have usually contributed the least to the root causes of the crisis. This is in fact the case of island economies. The chapter thus investigates into the vulnerability and resilience of 38 Small Islands Developing States (SIDs) to both shocks. Adopting a comprehensive conceptual framework and data on various indices from the literature and global databases, we assess the COVID-19 and climate change vulnerabilities of SIDs on multiple fronts. The results first reveal a higher vulnerability across all dimensions for the Pacific islands compared to the other islands in the sample. There is also evidence of a weak correlation between climate change risk and the COVID-19 pandemic confirming our premise that there are marked differences between these two shocks and their impacts on island communities.

The overall objective of this study is envisaged to provide decision makers with actionable insights and access to multi-risk maps for the most in-danger stave churches (SCs) among the existing 28 churches at high spatial resolution to better understand, reduce and mitigate single- and multi-risk. In addition, the present contribution aims to provide decision makers with some information to face the exacerbation of the risk caused by the expected climate change.

Material and data collection started with the consultation of the available literature related to: (1) SCs' conservation status, (2) available methodologies suitable in multi-hazard approach and (3) vulnerability leading indicators to consider when dealing with the impact of natural hazards specifically on immovable cultural heritage.

The paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. The results highlight the danger at which the SCs of Røldal, in case of floods, and of Ringebu, Torpo and Øye, in case of landslide, may face and stress the urgency of increasing awareness and preparedness on these potential hazards.

The contribution for the first time aims to homogeneously collect and report all together existing spread information on architectural features, conservation status and geographical attributes for the whole group of SCs by accompanying this information with as much as possible complete 2D sections collection from existing drawings and novel 3D drawn sketches created for this contribution. Then the paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. Then it highlights the danger of floods and landslides at which the 28 SCs are subjected. Finally it reports how these risks will change under the ongoing impact of climate change.

This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.