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This study on corporate demand for general takāful (Islamic insurance) aims to identify potential growth areas and areas for improvement in takāful business practices in Malaysia.

A survey on corporates’ protection needs, takāful/insurance coverage obtained and awareness on takāful/insurance was conducted for this paper.

The findings from the survey are as follows: There is potential for takāful operators to further penetrate the corporate sector, as the majority of respondents indicated willingness to spend on takāful/insurance. Emphasis on takāful value propositions apart from its Sharīʿah compliance status is needed to attract corporates, as respondents were found to be indifferent on Sharīʿah compliance status of their protection. Strong market presence, expanded product offerings and efficient services were key determinants to attract takāful subscription. Respondents’ heavy reliance on intermediaries warrants strong collaboration with intermediaries to widen market outreach. The small and medium enterprises segment appeared promising, as it is found to be underserved despite having higher propensity to obtain takāful/insurance coverage compared to the overall respondents.

This study is limited to Malaysia’s experience. The findings are indicative (though they may not be conclusive) of the target segment as well as the takāful industry as a whole.

The insights on respondents’ considerations when obtaining takāful/insurance coverage and the correlation of these factors with respondents’ characteristics can assist takāful/insurance providers in structuring products and business strategies to better serve this market segment. The paper may also aid discussions among researchers and regulators on areas for further development of the industry.

To address requirements and specifications of construction project, academics need to build a project classification model. In recent years, project success concept, particularly on large-scale construction projects, has been a controversial issue, especially in developing countries. Hence, in this paper, after introducing a sustainable success index (SSI), a novel method called “rough set approach” had been adopted to induce decision rules and to classify construction projects. The paper aims to discuss these issues.

At first, 20 effective success factors and 15 success criteria based on three pillars of sustainability of economy, society and environment had been categorized. The research data used for analysis had been collected from 26 large-scale construction projects in Iran and five other countries. After collecting data collection, observations had been analyzed and 51 decision rules were generated, and the projects were classified. Eventually, in order to evaluate the performance of the generated rules, confusion matrix was applied, and the model was validated.

The results of the present study show that rough set theory (RST) can be an effective and valuable tool for building expert systems. Practical applications of these results along with limitations and future research are described.

Perhaps for the first time, in the present study, a number of large-scale construction projects are classified based on SSI. Applying RST for building rule-based system and classifying projects in construction project area are novel attempts undertaken in this paper. The rules induced in this study can be applied to develop a sustainable success prediction model in the future studies.

The COVID-19 pandemic has forced countries to consider how to reach vulnerable communities with extended outreach services to improve vaccination uptake. The authors created an optimization model to align with decision-makers' objective to maximize immunization coverage within constrained budgets and deploy resources considering empirical data and endogenous demand.

A mixed integer program (MIP) determines the location of outreach sites and the resource deployment across health centers and outreach sites. The authors validated the model and evaluated the approach in consultation with UNICEF using a case study from The Gambia.

Results in The Gambia showed that by opening new outreach sites and optimizing resource allocation and scheduling, the Ministry of Health could increase immunization coverage from 91.0 to 97.1% under the same budget. Case study solutions informed managerial insights to drive gains in vaccine coverage even without the application of sophisticated tools.

The research extended resource constrained LMIC vaccine distribution modeling literature in two ways: first, endogenous calculation of demand as a function of distance to health facility location enabled the effective design of the vaccine network around convenience to the community and second, the model's resource bundle concept more accurately and flexibly represented complex requirements and costs for specific resources, which facilitated buy-in from stakeholders responsible for managing health budgets. The paper also demonstrated how to leverage empirical research and spatial analysis of publicly available demographic and geographic data to effectively represent important contextual factors.

This study aims to analyze and assess 21 years of media coverage (2000–2020) of Flix, a small industrial village located in an rural area on north-eastern Spain, which has endured in these years a severe environmental and industrial crisis, with a strong potential for stigmatization of the place.

The research is conceptualized under the Social Amplification of Risk Framework, a theoretical/conceptual approach aimed at accounting for the huge gaps that often arise between public perception of technological or environmental risks of some technologies, products and places and the expert estimations of these risks. The authors studied the coverage on Flix by a local, a regional and a national newspaper through a content analysis where the corpus (1,524 news pieces) was coded for several variables, including tone, genre and thematic area.

The studied coverage was in general overwhelmingly negative and strongly focused on “bad news” relating to pollution and deindustrialization, although this was much less the case in the local newspaper than in the regional and, in particular, the national newspaper. Thus, a territorially escalated pattern clearly emerges from our research concerning the stigmatization potential of news media coverage for the specific case under scrutiny.

To the authors’ knowledge, this is the first time such a longitudinal study of media coverage and its potential for place stigmatization is performed with this specific territorial perspective.

Electric utility companies (EUC) are expected to play a key role toward implementing ambitious climate change aims being under critical scrutiny by regulators and stakeholders. However, EUC provide an under-researched field regarding sustainability reporting with the focus on economic, social and ecological concerns. This paper aims to gain insights of the sustainability reporting practice of EUC and the coverage of indicators based on the Global Reporting Initiative (GRI)-Guidelines.

A twofold documentary analysis of 186 GRI-G4 sustainability reports by EUC globally is conducted to investigate the coverage rates of G4-indicators. Neo-institutionalism and strategic stakeholder theory serve as theoretical lenses. A regression analysis is used to examine ownership, stock-exchange listing, area of activity and region as potential drivers of sustainability reporting.

Results show that the coverage of indicators based on triple-bottom-line dimensions is moderate in EUC leaving room for improvement. The coverage of sector-specific indicators lacks behind the coverage of standard disclosure indicators. Results show that private and listed EUC show better coverage rates than public and not-listed EUC.

Neo-institutionalism shows limited homogenization in the sector. Strategic stakeholder theory demonstrates insufficient stakeholder compliance of public and not-listed EUC.

This study contributes to sustainability reporting research by focusing on the under-researched electricity sector. It provides practical reporting insights for EUC, the GRI and regulators.

This paper aims to study the affecting factors on bird nesting on electronic railway catenary lines and the impact of bird nesting events on railway operation.

First, with one year’s bird nest events in the form of unstructured natural language collected from Shanghai Railway Bureau, the records were structured with the help of python software tool. Second, the method of root cause analysis (RCA) was used to identify all the possible influencing factors which are inclined to affect the probability of bird nesting. Third, the possible factors then were classified into two categories to meet subsequent analysis separately, category one was outside factors (i.e. geographic conditions related factors), the other was inside factors (i.e. railway related factors).

It was observed that factors of city population, geographic position affect nesting observably. Then it was demonstrated that both location and nesting on equipment part have no correlation with delay, while railway type had a significant but low correlation with delay.

This paper discloses the principle of impacts of nest events on railway operation.

Forest insurance is a popular way to reduce the loss of forest disasters, so it is necessary to actively involve stakeholders. In the multi-agent simulation model, the government, insurance companies and forest farmers participate as three main stakeholders. The purpose of this paper is to mainly simulate the behavior of forest farmers under different environmental variables in order to find the important factors affecting the coverage of forest insurance, so as to improve the ability of forest farmers to resist risks in the face of disasters.

In the simulation process, the decision-making rule of a forest farmer’s purchasing behavior is a binary selection chain, which is created at random. Forest farmer agents who adapt to the environment will remain; on the contrary, those will be eliminated. The eliminated agents will renew their behavior selection chains through learning others’ successful behavior based on genetic algorithm. The multi-agent mode is set up on the Eclipse platform by using Java language.

The adjustment simulation experiments of insurance premium, insurance subsidy and forest area were carried out. According to the result, conclusions and suggestions are as follows: at present, government subsidies are necessary for the implementation of forest insurance; in the future, with the expansion of the insured forest area and the upgrading and large-scale operation of forest farms, forest farmers will be more willing to join forest insurance program, and, then, the implementation of forest insurance no longer requires government subsidies for forest insurance premiums.

This paper explores the impact of three important factors on the implementation of forest insurance.

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.

The main objective of the research is to examine whether the possession and the consumption of the service of a mobile telephone by the families of rural zones has improved their wellbeing in the last 10 years (2007–2016).

A quantitative analysis of panel data is proposed in order to analyze the effect of the use of the mobile telephone in rural zones by region of Peru during the last 10 years and capture the unobservable heterogeneity during the said period. In this manner, it is hoped to investigate the effect of the increased use of said technology in Peru.

The results obtained show that the increase in the acquisitions of mobile telephones in rural zones has had a positive impact on the wellbeing of households. Continuous business innovation driven by citizens’ needs and the greater accessibility of mobile telephones are the main reasons based on the Peruvian context under study.

In Peru, there has been an explosive increase in users of mobile telephones in the last 10 years. The use of this technology may be arriving in rural households before other basic services, provoking individual and social changes and creating new employment and income opportunities. This would support the recent recognition of the mobile telephone as an essential tool for development, especially in underdeveloped countries.

This paper investigates the relationship between health and labour market participation considering the potential role played by the presence of children and elderly persons (with/without disabilities) in Italian households.

The authors use longitudinal data from the European Union Statistics on Income and Living Conditions and full-information maximum likelihood to estimate a two-equation model (one equation for labour force participation and one for health status) with instruments to address the endogeneity of the labour force participation choice. The model is estimated separately by gender.

The authors find that while the presence of children, elderly persons or both is positively associated with the health status of both genders, the presence of disabled elderly persons exerts a negative role. As for participation, interesting differences emerge. The presence of children discourages women's participation but is positively associated with men's labour force participation. Interestingly, a caring role for elderly persons without disability emerges for both genders when the presence of children is combined with that of elderly people. Gender differences are also at work for the role of childcare services and elderly and/or disabled home care/assistance.

The findings indicate a possible caring role for elderly persons without disabilities, neutralizing the effect of the presence of children on the labour force participation of both genders. The results also suggest that greater coverage of care services should increase the active participation of women in the labour market.