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Steam explosions are a major safety concern in many modern furnaces. The explosions are sometimes caused by water ingress into the furnace from leaks in its high-pressure (HP) cooling water system, coming into contact with molten matte. To address such safety issues related to steam explosions, risk based inspection (RBI) is suggested in this paper. RBI is presently one of the best-practice methodologies to provide an inspection schedule and ensure the mechanical integrity of pressure vessels. The application of RBIs on furnace HP cooling systems in this work is performed by incorporating the proportional hazards model (PHM) with the RBI approach; the PHM uses real-time condition data to allow dynamic decision-making on inspection and maintenance planning.

To accomplish this, a case study is presented that applies an HP cooling system data with moisture and cumulated feed rate as covariates or condition indicators to compute the probability of failure and the consequence of failure (CoF), which is modelled based on the boiling liquid-expanding vapour explosion (BLEVE) theory.

The benefit of this approach is that the risk assessment introduces real-time condition data in addition to time-based failure information to allow improved dynamic decision-making for inspection and maintenance planning of the HP cooling system. The work presented here comprises the application of the newly proposed methodology in the context of pressure vessels, considering the important challenge of possible explosion accidents due to BLEVE as the CoF calculations.

This paper however aims to optimise the inspection schedule on the HP cooling system, by incorporating PHM into the RBI methodology, as was recently proposed in the literature by Lelo et al. (2022). Moisture and cumulated feed rate are used as covariate. At the end, risk mitigation policy is suggested.

In this paper, the proposed methodology yields a dynamically calculated quantified risk, which emphasised the imperative for mitigating the risk, as well as presents a number of mitigation options, to quantifiably affect such mitigation.

This study examines the effect of the informational content of local credit rating announcements in emerging markets on the liquidity of their bond markets. This study analyses the liquidity of bonds in various emerging bond markets using a sample of nine countries: Argentina, Mexico, Peru, Hungary, Poland, Spain, Turkey, Hong Kong and Greece. The sample includes daily data on sovereign bonds that go from July 2009 to July 2017. The main focus is on the period before and after the sovereign debt crisis. This study notes that the bond liquidity is affected due to the sign of the rating granted by the rating agencies for each country.

This study aims to question the sources of liquidity problem of sovereign bonds issued by the emerging countries. The study’s database consists of daily data of all nine emerging countries for the period from July 2009 to July 2017. Panel data were collected from the Datastream database.

This study first directly tests the information content of bond ratings announcements and their effect on bond market liquidity. Next, the impact of rating changes on sovereign bond liquidity around the rating announcements is studied. Rating changes can affect sovereign bond's price, trading and liquidity around the announcement date. In particular the rating changes that move the bonds out of the investment grade category can elicit selling pressure or even fire sale of the fallen angels.

This research aims to present data on the prices of sovereign bonds that react to changes in credit rating by studying the price movements around the announcement of changes in credit rating. The literature is very rich in studies on credit rating changes on stocks and corporate bonds, but this study is perhaps the first attempt on sovereign bonds.

In Egypt, the IUD is the most common contraceptive method since 1988 and has remained so despite a recent drop in its share from 59.9% in 2008 to 51.5% in 2014 in favour of hormonal methods, which increased from 19.7% for pills and 12.3% for injectables in 2008 to 27.4% and 14.5% in 2014 according to 2014 Egypt demographic and health survey (EDHS). The recent shift away from intrauterine contraceptive device (IUDs) to hormonal methods have contributed to increased discontinuation. This paper aims to answer three questions: To what extent does the method type influence the hazard of contraceptive discontinuation in Egypt? Is the interaction between method type and duration of use a predictor of the probability of discontinuation after controlling other variables? What are the other important background variables that affect the hazard of contraceptive discontinuation?

Using data from EDHS2014, separate multilevel discrete-time proportional hazard models for events of interest (abandoned use while in need, switched to another method in the month following discontinuation and method failure) were built.

Only IUD users are significantly less likely to abandon use while in need and to experience method failure and a reduced risk of switching. During the first 6–10 months of use, all types of discontinuation can be significantly reduced for all three methods. Demographic variables do not significantly affect abandonment but strongly affect switching and significantly affect failure. Socio-economic variables do not significantly affect abandonment and switching. Exposure to media has a significant effect on abandonment but not on switching. Community contraceptive prevalence rate strongly affects switching.

Results confirm that the counselling should be more intense during the first year of method use and should pay special attention to women who are 25 years old and above and those who have two or more children. Also, media campaigns are important and especially those addressing the issue of abandoning while in need.

There has been significant growth in entrepreneurship research over the past several decades. Yet with all of the knowledge gained and presumably improved training of would-be entrepreneurs, firm failure rates remain persistently high. It is argued here that the historical and continued research focus on successful entrepreneurs has limited the field. Entrepreneurs are often considered to possess uniquely positive capabilities relative to the general population; this paper explores the possibility that the majority of entrepreneurs suffer from overconfidence and that this leads most entrepreneurs to make “bad bets” that result in underperformance and firm failure.

In this paper, a qualitative review of the literature was performed.

Based on the literature review, three formal propositions are developed. The first two suggest that the majority of entrepreneurs are overconfident in their personal capabilities and the prospects for their new ventures. It is then proposed that this overconfidence leads to errors in judgment that results in financial underperformance and failure found among most new ventures.

This paper makes an important contribution to the entrepreneurship literature by arguing that overconfidence negatively impacts pre-founding decision-making such that entrepreneurs pursue flawed opportunities. Studying the issues raised in this paper may spur new lines of research and knowledge that lead to better entrepreneurial outcomes.

This paper proposes a heuristic, data-driven approach to the rapid performance evaluation of periodic maintenance on complex production plants. Through grouping, maintenance interval (MI)-based evaluation and performance assessment, potential nonvalue-adding maintenance elements can be identified in the current maintenance structure. The framework reduces management complexity and supports the decision-making process for further maintenance improvement.

The evaluation framework follows a prescriptive research approach. The framework is structured in three steps, which are further illustrated in the case study. The case study utilizes real-life data to verify the feasibility and effectiveness of the proposed framework.

Through a case study conducted on 9,538 pieces of equipment from eight offshore oil and gas production platforms, the results show considerable potential for maintenance performance improvement, including up to a 23% reduction in periodic maintenance hours.

The problem of performance evaluation under limited data availability has barely been addressed in the literature on the plant level. The proposed framework aims to provide a quantitative approach to reducing the structural complexity of the periodic maintenance evaluation process and can help maintenance professionals prioritize the focus on maintenance improvement among current strategies.

The proposed framework is especially suitable for initial performance assessment in systems with a complex structure, limited maintenance records and imperfect data, as it reduces management complexity and supports the decision-making process for further maintenance improvement. A similar application has not been identified in the literature.

This study aims to investigate how Germans' misperceptions of the nature of entrepreneurship influence their attitudes towards entrepreneurial failure.

Adopting a multivariate regression analysis, the study used data collected from a commercial online market research panel (N = 2,027) reflecting the overall German working population. Attitudinal items on business failure were used to measure the study variables. The study controlled for age, education, employment status, gender, income, whether the respondent knows a failed entrepreneur and the German federal state in which the respondent resides.

The findings suggest that reservations about failed entrepreneurs become stronger as misperceptions of the nature of entrepreneurship worsen. The results also show that failure reservations vary regionally over the 16 German federal states.

Nationwide efforts regarding the stimulation of entrepreneurship and the acceptance of entrepreneurial failure are insufficient for removing failure reservations, as they neglect regional cultural differences. The results suggest that it is not enough just to invest in efforts to create a failure-friendly culture, and that a better general education about the realities of entrepreneurship is a prerequisite.

The study generates insights into how the overall population in an innovation-driven economy perceives entrepreneurship and entrepreneurial failure. Moreover, the work delves into the reasons why parts of German society reject failed entrepreneurs. Hence, this study can aid the drafting of effective policy initiatives at the regional and national levels.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

This paper aims to shed light on features of successful innovation and on the role played by downstream open innovation (OI) dynamics in the Fast Moving Consumer Goods (FMCG) industry. It also explores the reasons for the decline in the number of disruptive innovations in this industry in the European Union (EU).

The authors interpret the data in a Kantar consumer panel dataset on disruptive innovations in Spain through an exploratory research including in-depth interviews with 19 managers in the industry.

Results show that downstream open innovation in this industry is mostly limited to the executional stage in the process and highlight the crucial role played by the point of purchase in the success of innovations. The authors build up a virtuous circle of innovation based on features such as the use of OI processes, company focus and marketing support, transparency and collaboration with retailers, as well as the product's uniqueness and its potential to become viral.

The paper focuses on Spain and, thus, results cannot be generalised. Further research in other countries would be interesting.

The study describes the features of disruptive innovators and develops an extensive list of success factors.

The development of disruptive innovation is a source of competitive advantages and one of the most relevant activities of managers today. Nevertheless, the number of disruptive innovations is in decline, and only a few succeed, negatively affecting consumer welfare.

Through this study, the authors provide insights on the features of successful innovators in FMCGs and describe the factors affecting the decreasing trend in the number of breakthrough innovations. Further, this paper fulfils an identified need to study OI in low-tech industries.

The purpose of this study is to systematically review available state-of-the-art literature on comparative studies on Quick Commerce (Q-commerce) and E-commerce and their greenhouse gas (GHG) emissions.

The literature survey methodology is based on the funneling approach of Kitchenham (2004), where results are obtained according to inclusion and exclusion criteria. The literature review methodology used for this study covers the period from 2016 to 2022. The areas considered for the survey are operations, logistics and supply chain network design for the distribution of goods in e-business. After deciding on the criteria, a total of 140 articles were extracted from 9 journal articles that study e-commerce and environmental emissions.

The result of this study reveals that GHG emissions from both modes of shopping depend on various parameters such as speed of delivery, last-mile depot locations, logistics and vehicle efficiency, customers’ order patterns and average basket size. Furthermore, the findings also highlight the difference between Q-commerce and E-commerce supply chain networks.

This study only accounts for GHG emissions from logistics activities, but there are other sources of GHG emissions in the overall supply chain that are not taken into consideration. Supply chain/business analysts in Q-commerce companies might refer the findings from this study to measure GHG emissions from their operations.

This is the first study in the Q-commerce field that uses a structured approach to find relevant literature from the years 2016 to 2022 and focuses on GHG emission measurement.

The brake controller is a key component of the locomotive brake system. It is essential to study its safety.

This paper summarizes and analyzes typical faults of the brake controller, and proposes four categories of faults: position sensor faults, microswitch faults, mechanical faults and communication faults. Suggestions and methods for improving the safety of the brake controller are also presented.

In this paper, a self-judgment and self-learning dynamic calibration method is proposed, which integrates the linear error of the sensor and the manufacturing and assembly errors of the brake controller to solve the output drift. This paper also proposes a logic for diagnosing and handling microswitch faults. Suggestions are proposed for other faults of brake controller.

The methods proposed in this paper can greatly improve the usability of the brake controller and reduce the failure rate.