Search results

The purpose of this paper is to review research on lapse in life insurance and to outline potential new areas of research in this field.

The authors consider theoretical lapse rate models as well as empirical research on life insurance lapse and provide a classification of these two streams of research. More than 50 theoretical and empirical papers from this important field of research are reviewed. Challenges for lapse rate modeling, lapse risk mitigation techniques, and possible trends in future lapse behavior are discussed.

Lapse rate modeling has been a very active field of research in the last years, as evidenced by the 44 papers on lapse modeling considered in this review. Moreover, a fair amount of empirical work (another 12 papers) has been done, especially on the issue of how environmental variables affect lapse. Research on individual policyholder and contract information is more scarce, since such information is typically treated as confidential.

The risks arising from lapse are of high economic importance. Lapsation is thus of interest not only to academics, but is highly relevant for the industry, regulators, and policymakers, especially in regard to designing an appropriate regulatory environment. Lapsation also impacts many actuarial tasks, such as product design, pricing, hedging, and risk management. A review of the recent literature might be helpful for these tasks.

To the best of the authors' knowledge, this is the first structured review of the increasingly important literature on life insurance lapsation. Next to the structured review of the existing models and the empirical evidence, the paper also contributes to the literature by discussing challenges for lapse rate modeling and possible trends.

Over the last decade, technological and social trends have significantly influenced the relationship between customers and insurers. New buying patterns, price comparison platforms and the usage of different interaction channels driving single-product purchases and impacting lapses have influenced insurers’ customer portfolios and development. The purpose of this paper is to study the features driving the customer relationship along three areas, namely, customer acquisition, development and retention.

After defining 14 related hypotheses, the authors use econometric analyses to quantitatively support these hypotheses in the three areas of interest. The authors build on a large-scale longitudinal data set from a Swiss insurance company covering the period from 2005 to 2014 and including 2,757,000 customer-years. The data comprise information on private customers, their contract history, including coverage and losses and the channels used for buying insurance. This analysis focuses on the two most common non-life insurance products, namely, household/liability and car insurance.

The authors provide descriptive statistics and results from econometric analyses to determine the significant features and patterns affecting customer development and retention. Among the main results, the authors underline the significant influence on cross-selling given by the customer’s age and the interaction channel. Customers from rural regions are more loyal and likely to conduct cross-buying when compared to their peers from urban regions. Car insurance holders are more likely to lapse than household/liability insurance clients. Finally, while newly acquired customers tend to buy only a single product, the authors show the importance of cross-selling for retaining customers. In fact, customer retention is positively influenced by the number of products hold.

This work is relevant for academics and practitioners alike, adding a quantitative basis to the understanding of managing customer relationships and for the development of further prospective models. Further work could investigate or add products, extend the study to other companies and focus on customer development with time.

This study explores a large-scale longitudinal data set. The analyses of customer acquisition, development and retention can support insurers to construct their own models for customer relationship management.

A variety of equity-linked insurance contracts such as variable annuities (VA) and equity-indexed annuities (EIA) have gained their attractiveness in the past decade because of the bullish equity market and low interest rates. Due to the complexity of their inherent nature, pricing and risk management of these products are quantitatively challenging and therefore have become sources of concern to many insurance companies. From a financial engineer's perspective, the options in VA and those embedded in EIA can be modeled as puts and calls, respectively, and enable the use of numerical option pricing techniques. Additionally, values of VA and EIA move in opposite directions in response to changes in the underlying equity value. Therefore, for insurers who offer both businesses, there are natural offsets or diversification benefits in terms of economic capital (EC) usage. In this chapter, we consider two specific products: the guaranteed minimal account benefit (GMAB) and the point-to-point (PTP) EIA contract, which belong to the VA and EIA classes respectively. Taking into account mortality risk and suboptimal dynamic lapse behavior, we build a framework that quantifies the value of each product and the natural hedging benefits based on risk-neutral option pricing theory. With Monte Carlo simulation and finite difference methods being implemented, an optimum product mixture of those two contracts is achieved that deploys capital the most efficiently.

This paper aims to present a mathematical model of the dynamics of the unmanned aerial vehicle (UAV) vertical take-off and landing (VTOL). It will be used to develop control laws to a multirotor that is inherently unstable. Also, the model will be used to design algorithms to estimate the attitude of an object.

The physical model of UAV assumes that it is a rigid body with six degrees of freedom acted by forces generated by the propellers, motors, aerodynamic forces, gravity and disturbance forces. The mathematical model was described by differential equations. However, drive system (propeller, BLDC motor and BLDC motor controller) was described by six transfer functions. These transfer functions were demarcated with Matlab/Simulink identification toolbox from data received from a specially designed laboratory stand. Moments of inertia of the platform have been analytically determined and compared with empirical results from the pendulum. The mathematical model was implemented in Matlab/Simulink.

The paper confirms the need of designing mathematical models. Moreover, mathematical models show that some parts of the object are better to be replaced by experimental results than by equations, which is proved by the data. The paper also shows advantages of using Matlab/Simulink. What is more the simulation of the model proves that multirotor is an unstable object.

The test results show that drive units are strongly dependent on ambient conditions. An additional problem is the different response of the drive set to increasing and decreasing the control signal amplitude. Next tests will be done at different temperatures and air densities of the environment, also it is need to explore drag forces.

The mathematical model is a simplification of the physical model expressed by means of equations. The results of simulation like accelerations and angular rate are noise-free. However, available sensors always have their errors and noise. To design control loops and attitude estimation algorithms, there is a need for identification of sensors’ errors and noise. These parameters have to be measured.

The paper describes a solution of correct identification of drive unit, which is a main component of the UAV.

Schedule UTP requires that firms disclose to the IRS the uncertain tax positions that comprise the federal portion of the tax reserve disclosed on their financial statements. To investigate whether Schedule UTP has been an effective audit tool to the IRS, we use financial statement disclosures of reductions in reserves due to a lapse in the statute of limitations (Lapse). We find that the probability of a Lapse is 3.4 percent lower after Schedule UTP. However, this result is driven by domestic firms; we do not find evidence that Schedule UTP has been effective in the audit of multinational firms.

The purpose of this paper is to develop a novel tool to support decision making for enhanced demolition process efficiency and material waste sortability through computerised 4D motion workflow simulation.

A time-lapse evaluation model was developed to classify and estimate the impact of building demolition processes and material waste recovery. The dynamic assessment of demolition, collision and mechanical impact was measured through computerised 4D motion game and physics engines. Waste recovery and treatment complemented the simulation algorithm. The simulation of the information workflow was tested through case study using two demolition strategies.

The simulation successfully estimated the efficiency and efficacy of the different demolition strategies. Thus, simulation results can potentially support better decision making related to the definition of demolition strategies associated with recycling and re-use targets.

The simulation was limited to a simple machine-led demolition strategy. Further research is required to understand the impact of complex machine mechanic movements and processes on complex building fabrics.

Modelling and evaluating the demolition process and its impact on material waste recovery with a time dimension is novel. The comparative analysis of quantitative data allows demolition professionals to find optimal and more sustainable demolition solutions and more efficient and safer implementation on site. It also contributes to a better understanding of the relationship between demolition strategy and waste sortability. This research represents a significant advancement in applied computing for building demolition waste recycling and notably, it improves the quality of information available in the definition of building demolition strategies.

The purpose of this paper is to improve the understanding of the impact of mass timber construction methods on construction performance through the successful delivery of the first-of-a-kind tall wood building, Brock Commons Tallwood House (Tallwood House). This paper is one of a set of papers examining the project; companion papers describe innovations used during the mass timber design and construction processes.

A mixed-method, longitudinal case study approach was used in this research project to investigate and document the Tallwood House project. Quantitative data were collected to perform the following analysis: hook time, the variability of productivity and schedule reliability. Members of the research team observed construction progress, meetings and decision-making, conducted periodic interviews and reviewed project artifacts.

The research presented in this paper is the culmination of a longitudinal study aimed at studying the innovation process on a project where radical innovations of structural systems were developed. Prefabrication, combined with the use of a virtual design and construction (VDC) model for planning and fabrication and early collaboration with trades, construction managers and consultants, increased the labor productivity of the on-site erection of the mass timber structural components and envelope panels and expedited the construction schedule.

This paper details an in-depth investigation into the construction productivity for a unique building project and lessons learned. The case study chosen is the construction of Tallwood House at the University of British Columbia. Tallwood House was the tallest mass-timber hybrid building in the world at the time of its construction.

This paper proposes an evaluation model for prefabricated construction to guide a supply chain with controllable costs. Prefabricated construction is prevalent due to area limitations. Nevertheless, the development is limited by budget control and identifying the factors affecting cost. The degree of close collaboration in the supply chain is closely interconnected with cost performance that includes direct and indirect factors. This paper not only quantizes these factors but also distinguishes the degree of influence of various factors.

System dynamics is applied to simulate and analyze the construction cost factors through Vensim software. It can also clarify the relationship between cost and other influencing factors. The input data are collected from an Internet of Things (IoT)-enabled system under a Building Information Modeling (BIM) system and Hong Kong government reports.

Simulation results indicate that prefabricated construction cost is mainly influenced by government promotion degree (GPD), working pressure from on-site construction (WPOSC), prefab quality (PQ), load-bearing capacity per vehicle (LBPV) and mold quality (MQ). However, it is more sensitive toward GPD, which indicates that the government should take measures to promote this construction technology. On-site worker management is also essential for the assembly process and indirectly influences the construction cost.

This paper quantifies indirect influential factors to clarify the specific features for prefabricated construction. The investigated factors are limited.

The contractor can identify all factors and classify the levels of influence to make decisions under the supply chain system boundary.

The input data are collected from an IoT-enabled system under a BIM system and Hong Kong government reports. Thus, the relationship between construction cost influential factors can be investigated.

This paper quantifies indirect influencing factors and clarifies the specific features in prefabricated construction. The contractor could identify these factors to make decisions and classify the levels of influence under the supply chain system boundary.

Introduction: International migration, a complex, dynamic and multifaceted process, grasps important challenges for the European economies, through its advantages and pitfalls.

Aim: This research is conducted to examine the fundamental credentials of immigration in Europe and its perspectives within the Brexit framework, an ongoing process that induced profound implications.

Method: The authors have applied the cluster analysis and structural equations as the main research methods on a balanced panel comprising 10 receiving countries (most targeted by migrants), members of the European Union (EU-10), for the 2000–2019 timespan (2019 being a Brexit milestone year).The authors have separately extrapolated a sample for 2020–2025 that was further used to identify some perspectives after the Brexit timeline in terms of migration determinants and effects on EU-10 host economies. Cluster analysis is based on a key scenario related to wellbeing, living standards (income level) and poverty risk at destination. These credentials are essentialfor the migration decision and important elements of migrant labour market integration strategies with keen economic consequences, further assessed through the structural equation models.

Findings: Results show that during 2000–2019, among EU-10, the main destination country for immigrants and asylum seekers in terms of welfare and living standards is Germany (both for economic and humanitarian migration), along with the United Kingdom (in the case of economic migration). This situation tends to remain unchanged for the following years even in the Brexit context, as reflected by the 2020–2025 forecast scenarios. Immigration effects on labour market outcomes and economic welfare are extremely significant, being largely discussed within the chapter.

The purpose of the study was to contribute to a better understanding of the climate change problem in naturally protected areas in developing countries, based on women's perceptions and to determine whether national parks should take an active role in providing climate change educational information and activities.

The work reported in this paper was carried out at Vulcan Poas National Park, Costa Rica, and the analysis drew on a sub‐sample of 162 Costa Rican women and 273 American women. The material collected was analyzed using a combination of ANOVA, correlation and standardized derived regression modelling using the forward elimination technique.

Climate change certainly ranks below personal and immediate risk in terms of perceived importance and the top‐level risks reported by respondents related to immediate personal concerns. The key explanatory variable in the case of the Costa Rican women is the relative educational level of the person and the park's ability to educate people about climate change. In the case of the American women, the variables included in the final model were: industrial emissions, deforestation and aerosol sprays. The results indicate that a significant difference exists between the two groups with regard to current perceptions about the threat from climatic change, and the likely importance of the problem in 50 years' time. Costa Rican women appeared to exhibit a more complex problem‐reaction‐action behavioural continuum than the American women in the study. In both cases it is unclear as to the role played by protected areas in terms of the impact of information and education provided in relation to climate change.

The role of the parks as a source of education and information about the topic is not clear. However, it was established that there is an overall interest in the topic among women visitors, particularly local women. This level of awareness could be harnessed to develop strategies for combating and mitigating climate change, and in this sense, national parks might play an enhanced role as a place of learning about the topic.

This study is the first of its kind. In previous studies, women's reactions to climate change have been investigated much less than men's.