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The purpose of this paper is to study the optimal sequential information acquisition process of a rational decision maker (DM) when allowed to acquire n pieces of information from a set of bi-dimensional products whose characteristics vary in a continuum set.

The authors incorporate a heuristic mechanism that makes the n-observation scenario faced by a DM tractable. This heuristic allows the DM to assimilate substantial amounts of information and define an acquisition strategy within a coherent analytical framework. Numerical simulations are introduced to illustrate the main results obtained.

The information acquisition behavior modeled in this paper corresponds to that of a perfectly rational DM, i.e. endowed with complete and transitive preferences, whose objective is to choose optimally among the products available subject to a heuristic assimilation constraint. The current paper opens the way for additional research on heuristic information acquisition and choice processes when considered from a satisficing perspective that accounts for cognitive limits in the information processing capacities of DMs.

The proposed information acquisition algorithm does not allow for the use of standard dynamic programming techniques. That is, after each observation is gathered, a rational DM must modify his information acquisition strategy and recalculate his or her expected payoffs in terms of the observations already acquired and the information still to be gathered.

The purpose of this paper is to demonstrate an effective and robust numerical solution for Raman fiber amplifier (RFA) equations which have no explicit solution. MATLAB BVP solvers are addressed for the solution.

The continuation method proposed for the solution of RFA equations using MATLAB BVP solvers is explained. Scripts for improving the power values at the boundaries with continuation, extending fiber length with continuation and calculation of the analytical partial derivatives using the MATLAB Symbolic toolbox are introduced. Comparisons among the different MATLAB BVP solvers have been made. Using the continuation method, signal evolutions for different kinds of RFA amplifier configurations are plotted.

The paper finds that MATLAB BVP solver with the continuation method can be used in the design of various kinds of RFAs for high powers/long gain fiber spans.

The paper will assist the fiber optic research community who suffer from two or more point boundary‐value problems. Moreover, the stiffness of the signal evolution which is faced with high pump powers and/or long fiber lengths can be solved with continuation. This superiority of the solver can be used to overcome any stiff changes of the signals for future studies.

The increased research interests and practical demands for RFAs have been calling for reasonable and efficient means for the performance evaluation of RFAs before the real amplifiers are fabricated. The solution method presented in this paper will be an efficient means for the solution of this issue.

MATLAB BVP solvers have been proven to be effective for the numerical solution of RFAs with multiple pumps and signal waves. Using the continuation method, in a distributed RFA with ten pump sources, 2,400 mW total input pump power is achieved. The improvement of the total power is about 1.4 times compared with those of the previously reported methods. Using the MATLAB BVP solvers, total power/fiber span can be improved further using the continuation process with the cost of computational time. This is a notable and promising improvement from a RFA designer's point of view.

The paper aims to propose a consistent and robust pricing/hedging methodology for callable fixed income structures with embedded caplet‐linked options.

A range of recently published (1997‐2003) works about the Libor Market Model (LMM) tackle the problems of modelling the forward curve with more than two factors and calibrating it to caps either/or to swaps. Other articles involve the pricing of Bermudan options using Monte Carlo simulation. In the form of case study, the very popular structure of multicallable range accrual bonds is used. A complete calibration methodology is described in detail, which links the structure's price to the market caps and swaptions prices as well as to the historical correlations between forward rates. We present the direct implementation of the Monte Carlo technique for this particular problem. Furthermore, we explore the application of the Longstaff–Schwartz least squares algorithm and its variations for the estimation of the expected value of continuation.

This paper suceeds in producing a consistent and robust pricing/hedging methodology for callable fixed income structures with embedded caplet‐linked options.

The increased complexity of similar fixed income structures makes traditional approaches like Black–Derman–Toy or Hull‐White trees inadequate for the task of consistent pricing and hedging. Therefore, care must be taken to ensure consisted hedging across the different volatility markets.

This article explores variations and settings of the popular LMM and the Longstaff‐Scwartz algorithm that can be relatively consistent with both the cap and swaption volatility market. The framework is built using as a benchmark the most liquid fixed income structure so that it can be tested for robustness.

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.

As volunteering research in nonprofit organizations is growing significantly, the purpose of this paper is to examine the effects of volunteering drivers and work engagement on volunteer continuation will.

Building on empirical and theoretical perspectives, the authors hypothesized that work engagement mediates the relationship between volunteering drivers and volunteer continuation will. To verify our hypotheses, we examined data collected from 372 active volunteers from Palestinian nonprofit organizations. The authors conducted structural equations modeling (SEM) analyses using the AMOS 24 platform to investigate direct and indirect effects.

The results of the study show that work engagement is a significant predictor of volunteer continuation will; mediates the relationship between career driver of volunteering and volunteer continuation will; and mediates the relationship between the protective driver of volunteering and volunteer continuation will.

The research design limits establishing cause and effect relationships among the examined variables.

The results of the current study may be of use for nonprofit organizations managers formulating effective recruitment and training policies to retain their volunteers.

The paper contributes to the limited empirical body of the volunteering research. The study is novel as it is one of the few studies conducted using data coming from a non-western context.

This paper examines which basis functions are efficient to employ a combined method of Hull and White (1990) with the Monte Carlo simulation when we price a callable range note or a callable bond. We use the Huge and Rom-Poulsen (2007) method which has modified the least squared Monte Carlo simulation proposed by Longstaff and Schwartz (2001) to reduce the estimation errors of the continuation value or the underlying assets. To use Monte carlo Simulation for pricing the early exercise premium, it is essential to accurately estimate the continuation value, because the investors will choose the higher value between the exercise and the continuation value at the possible early exercise dates. The main purpose of this paper is to analyze the estimation errors originating from the choice of the basis functions for the underlying asset and the continuation value estimation.

We choose the callable bond and the callable range accrual note to show which basis functions are reliable to reduce the estimation errors. For this purpose, we replicate the callable range accrual note with a portfolio of a fixed rate bond and a delayed digital option. We use several basis functions such as a constant, the instantaneous interest rates, and the range in order to see which basis function is efficient for our purpose. We examine several combinations of the basis functions depending on which basis functions will be used for the underlying asset or the continuation value estimation. We show that the range which is an important determinant of the callable range accrual note is an effective basis function to accurately determine the underlying asset and the continuation value for the pricing of the callable range accrual note.

The success and survival of any form of online community relies on the presence and active participation of its users. Hence, ensuring active user participation and retaining existing users is a key concern of the moderators of online communities. To address these challenges, the purpose of this paper is to investigate the epistemic, emotional, and social values that influence users’ intention to continue using an online social media brand community. Moreover, the study also investigates the differences in the influence of the investigated constructs and users’ various activity levels.

This study utilized the consumption value theory framework for testing the relationship between different measures. An empirical analysis of the consumption values of 577 users in an online social media brand community was accomplished using structural equation modeling.

The study findings revealed that emotional and social values exert partial influence in predicting users’ intention to continue using online social media brand communities. In particular, social enhancement and playfulness predict users’ continuation intentions. Moreover, the results show that the influence of the investigated constructs (except playfulness) is consistent across users with various activity levels in online social media brand communities.

These findings pave the way for further theoretical and practical considerations of the role of consumption values in resolving challenges of user participation and retention. However, there are still some open gaps concerning the generalizability of the findings as well as other factors that could potentially influence the user intentions. Future studies should validate the findings by recruiting diverse users in terms of their age and cultural background.

The study findings are of special relevance for the service operators interested in practicing user-centric innovation. Moreover, the findings can help online social media brand community managers to kick start user-centric innovation activities in their community.

The study provides a novel perspective on the challenges of assessing users’ consumption behavior. The perceived values have been conceptualized using the constructs of social influence, problem solving, playfulness, social enhancement, and social interaction.

The purpose of this paper is to examine how the real option theory is applicable to evaluation of cases of escalation and premature termination of Management Information Systems (MIS) projects.

The paper compares the implications of psychological and economic escalation theories with lessons from the real option theory as applied to MIS projects. Then, it examines published case studies, and discuss when project continuation enhances and reduces value for the manager and the firm.

Escalation of commitment is continuation of an investment project after receiving negative signals. Escalation was identified as a significant problem in MIS projects often explained by the desire of the manager to avoid recognizing mistakes and to protect reputation. The opposite problem of premature termination of certain investment projects was also identified. This study argues that accurate application of real option theory is critical to distinguish between escalation and premature termination. Under the real option theory, an investment project is analogous to a financial option, in that there is an opportunity to continue the project, but no obligation. Continuation has value when there is uncertainty and new information about the project may be revealed. Failure to account for the real options in a project is value‐reducing as it may lead to mistakes in premature termination of projects when projects with real option value are labeled as cases of irrational escalation.

The paper details the implications of real option theory to evaluating project continuation in the MIS setting.

This paper applies insights from real option theory to studies of escalation in MIS. Continuing a project may be seen as escalation when it actually has value for the firm, as new information received by continuing the project reduces uncertainty.

Today, most of the car manufacturers world-wide have embraced the principles of lean manufacturing on strategic and operational level. On strategic level car companies like Toyota (Womack et al., 1990) shifted 63 per cent of the value of the car towards the first, second and third tier suppliers for the co-production and co-development of cars as an effect of lean implementation. However, lean implementation was also followed by for instance Ford and GM in the USA, the latter company faced a sudden disruption in 2009 due to the break-out of the financial crisis in 2008, while Ford survived. Could this be foreseen? The exclusive use of (classic) financial performance indicators may give a false image of a company’s current and future performance. There is a need for a model to identify “the stars and the laggards’ regarding car companies by taking into account non-financial and intangible dimensions as advocated by Neely et al. (2003) regarding the third generation of business performance measurement systems. The purpose of this paper is therefor to propose a method to measure and benchmark car company performance which includes the non-financial R&D dimension as well as supply chain, value creating and employee dimensions. These dimensions are present in the value leverage model (van Blokland et al., 2012a, 2012b) which can serve as a basis for this method. The aim is to contribute to the third generation business performance measurement systems by further development of the value leverage model towards a maturity model for benchmarking car company performance. The proposed method can provide a big picture and give insight regarding company performance and direction of the performance.

Value leverage can be measured by a correlation analysis regarding three dimensions, namely, supply chain, R&D and value creation, all relative to the employee or capita which results in the average value leverage (AVL) factor. This AVL factor can be used to compose a combined relative and absolute ranking. The score regarding the AVL results in a relative ranking expressing the level of stability regarding the car companies value chain and system. For the absolute ranking the car companies receive per variable parameter a score according to their absolute performance relative to the other car companies. The relative and absolute ranking are presented on the vertical and horizontal axes forming a matrix. The matrix is the basis for the stability-value leverage maturity model for measuring and benchmarking company performance. With the proposed method, the following main research question can be answered: “How can company performance be measured and benchmarked from a stability-value leverage perspective?”.

With the proposed method, stability-value leverage performance can be measured. The relative ranking on the vertical axis and the absolute ranking form together a matrix which is presented by a scatterplot. A matrix with four maturity levels emerged from the analysis by introducing the average score of all the car companies together in the data set crossing the matrix vertical and horizontal. The four levels are as follows: Level I, low stability – low value leverage; Level II, low stability – high value leverage; Level III, high stability – low value leverage; and Level IV, high stability – high value leverage. Stability-value leverage performance of car companies can be measured over time which makes it possible to observe to which direction the car company migrates for instance from Level I to Level III, before and after the financial crises in 2008. The car companies BMW, Daimler, Audi, Ford and Honda are the best performing companies in stability-value leverage over the period 2000-2014, as they are situated at Level IV. With the findings, the main research question can be answered. The value leverage indicators can be used for measuring and benchmarking company performance regarding four maturity levels of stability and value leverage. The direction of performance can be observed as well.

This research is limited to the car industry. Further research is devised to test the indicators for instance on the truck manufacturing industry. Further research towards new variables is part of the ongoing research.

With the value leverage maturity model, it is possible to inform stakeholders about stability, value leverage and value creation capability of car companies. Weak performing companies can be identified in an early stage with this method to anticipate for instance on possible discontinuation of a car company effecting in merger an acquisition processes.

With the method stakeholders such as employees, users of cars and investors can be informed about how and why car companies perform in an unstable or stable manner.

This research towards ranking and classification of car companies aligns with theories regarding lean manufacturing and maturity models, as these models are used to compare companies on their level of perfection or excellence.

Assuming that supplier knowledge can either strengthen the partnership by nurturing the commitment and trust between partners or allow the buyer to be more calculative, this study aims to propose two types of knowledge sharing in supplier relationship – a type benefiting the partnership and another privately benefiting only one partner.

Using structural equation modeling and a surveyed dataset from 352 buyer–supplier partnerships, this study tested the research model of dual mechanism, where two types of knowledge sharing co-exist and have opposite effects on partnership longevity.

This study found that the two types of knowledge sharing create divergent effects on partnership continuation. For a buyer firm developing supplier knowledge, its supplier firm reciprocates by sharing knowledge with the buyer. While relation-specific knowledge promotes partnership longevity through developing trust, institutionalized knowledge hampers partnership longevity.

Findings overall indicate that knowledge plays a more instrumental role in sharing knowledge in a buyer–supplier relationship, and alternative forces simultaneously work in the partnership. Although this study explicates two mediating mechanisms for the effect of supplier knowledge, there remain many unknown aspects of the effect.

From the buyer’s perspective, it is possible its institutionalized knowledge can facilitate its relationship with a current supply chain partner so that it can gain more benefits from the relationship. From the supplier’s perspective, caution should be exercised in selecting the type of knowledge to share.

This study may have a broad impact on public policy by theorizing and testing why some partnerships last longer/shorter than others in association with the dynamics of the relationship initiated by one’s relational knowledge and the other’s knowledge sharing.

What this study contributes to involves the theorizing and testing the effects of the dual mechanism of knowledge sharing on partnership longevity. This study provides an example of a private investment in knowledge that is reciprocated with each type of knowledge – benefiting the partner and also benefiting the focal buyer firm.