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The chapter is devoted to the problem of creating effective tools for attracting extra-budgetary sources and increasing the interest of contemporary Russian enterprises in implementing projects to repair past (accumulated) environmental damage.

The objective of the research is the regions of the Russian Federation (constituent entities of the Russian Federation) and the mechanisms for financing the projects in the field of accumulated damage repair being implemented at the state level. This is possible by financing the project with the participation of the company involved in the accumulated damage in the regions.

The chapter deals with the investigation of the basic concepts of the problems of accumulated damage and the identification of the main problems and the contradictions in attracting financing for the implementation of damage repair projects in the Russian law enforcement field. The analysis of indicators characterizing the dynamics of financing of such projects in the Russian regions and the methodology of selecting priority objects of accumulated damage for their financing at the federal level is also examined.

The research resulted in the authors’ conclusion that the problem of attracting extra-budgetary sources to repair accumulated damage is connected not only with the contradictions in the Russian environmental legislation, but also with the insufficient development of such institutions as public-private and municipal-private partnerships. The chapter contains proposals for the development of results-based tools using the mechanism of public-private partnership to repair the accumulated damage.

The purpose of this paper is to propose a new temporal disaggregation method for time series based on the accumulated and inverse accumulated generating operations in grey modeling and the interpolation method.

This disaggregation method includes three main steps, including accumulation, interpolation, and differentiation (AID). First, a low frequency flow series is transformed to the corresponding stock series through accumulated generating operation. Then, values of the stock series at unobserved time is estimated through appropriate interpolation method. And finally, the disaggregated stock series is transformed back to high frequency flow series through inverse accumulated generating operation.

The AID method is tested with a sales series. Results shows that the disaggregated sales data are satisfactory and reliable compared with the original data and disaggregated data using a time series model. The AID method is applicable to both long time series and grey series with insufficient information.

The AID method can be easily used to disaggregate low frequency flow series.

The AID method is a combination of grey modeling technique and interpolation method. Compared with other disaggregation methods, the AID method is simple, and does not require auxiliary information or plausible minimizing criterion required by other disaggregation methods.

The purpose of this study is to determine distributional properties of the accumulated rate of interest when the instantaneous rate of interest evolves in terms of the Cox et al. (1985) square root process.

The law of iterated (or double) expectations is used to determine the mean and variance of the accumulated rate of interest on a cash management (or loan) account when interest accumulates at the instantaneous rates of interest implied by the square root process.

This study demonstrates how the accumulated rate of interest does not satisfy the strong mixing conditions necessary for convergence in distribution to the normal density function.

This study has strong educational value in determining distributional properties of the accumulated rate of interest when the instantaneous rate of interest evolves in terms of the Cox et al. (1985) square root process and demonstrating how the accumulated rate of interest does not satisfy the strong mixing conditions necessary for convergence in distribution to the normal density function.

This quantitative study aims to examine the impact of accumulated knowledge of accounting on the academic performance of Cost Accounting students.

The sample consisted of 89 students enrolled in the Accounting program run by a business college in Kuwait during 2015. Correlation and linear least squares regression analyses tested the study’s hypothesis.

Results indicated significant impact of accumulated knowledge on academic performance, with and without controls for other factors.

The findings provide administrators, academic advisors, accounting educators and researchers with a useful benchmark for the development of accounting curriculum, teaching plans and strategies and future academic research, and it forms the basis for comparative work aimed at the harmonization of international accounting education.

The study provides empirical support for the theoretical prediction that quantitative accumulated knowledge in accounting has an impact on the academic performance of students, especially in Cost Accounting. Internationally, it provides a foundation for future comparative studies, potentially leading to the harmonization of international accounting education. Regionally, it attempts to fill some of the gaps in the regional accounting education literature. Locally, the study seeks to improve the performance of the accounting students in Cost Accounting within the college where data were collected.

The purpose of this paper is to investigate the antecedents of business growth expectations and subsequent accumulated sales revenues and employment costs. Hypotheses are derived guided by the theory of planned behaviour.

The authors followed a sample of 207 incorporated businesses started in May/June 2002 over a ten-year period. The hypotheses are tested using hierarchical regression analysis.

The results suggest that the entrepreneurs’ need for social cohesion, subjective norm with regard to business growth and perceived self-efficacy with regard to opportunity recognition are positively and significantly associated with business growth expectations. These expectations, reported at the time of business registration, accurately predict subsequent short-term as well as long-term accumulated sales revenues and labour costs, but this is not the case for entrepreneurs with novel business ideas.

Since entrepreneurs’ attitude, subjective norm and self-efficacy are possible to change, the findings should interest policy makers and educators. Measures aimed at enhancing the antecedents of entrepreneurs’ growth expectations should be considered. The findings that growth expectations have a long-lasting effect on sales and employment stress the importance of entrepreneurs’ subjective expectations for outcomes in new businesses.

There is a lack of studies using a longitudinal design when investigating the link between initial business growth expectations and subsequent firm outcomes. This study contributes to the entrepreneurship literature in this regard by using high-quality secondary data to examine firm achievements.

The purpose of this paper is to introduce a novel computational method to evaluate damage accumulation in a solder joint of an electronic package, when exposed to operating temperature environment. A procedure to implement the method is suggested, and a discussion of the method and its possible applications is provided in the paper.

Methodologically, interpolated response surfaces based on specially designed finite element (FE) simulation runs, are employed to compute a damage metric at regular time intervals of an operating temperature profile. The developed method has been evaluated on a finite-element model of a lead-free PBGA256 package, and accumulated creep strain energy density has been chosen as damage metric.

The method has proven to be two orders of magnitude more computationally efficient compared to FE simulation. A general agreement within 3 percent has been found between the results predicted with the new method, and FE simulations when tested on a number of temperature profiles from an avionic application. The solder joint temperature ranges between +25 and +75°C.

The method can be implemented as part of reliability assessment of electronic packages in the design phase.

The method enables increased accuracy in thermal fatigue life prediction of solder joints. Combined with other failure mechanisms, it may contribute to the accuracy of reliability assessment of electronic packages.

In this article the aim is to propose a new form to densify parallelepipeds of R^N by sequences of α‐dense curves with accumulated densities.

This will be done by using a basic α‐densification technique and adding the new concept of sequence of α‐dense curves with accumulated density to improve the resolution of some global optimization problems.

It is found that the new technique based on sequences of α‐dense curves with accumulated densities allows to simplify considerably the process consisting on the exploration of the set of optimizer points of an objective function with feasible set a parallelepiped K of R^N. Indeed, since the sequence of the images of the curves of a sequence of α‐dense curves with accumulated density is expansive, in each new step of the algorithm it is only necessary to explore a residual subset. On the other hand, since the sequence of their densities is decreasing and tends to zero, the convergence of the algorithm is assured.

The results of this new technique of densification by sequences of α‐dense curves with accumulated densities will be applied to densify the feasible set of an objective function which minimizes the quadratic error produced by the adjustment of a model based on a beta probability density function which is largely used in studies on the transition‐time of forest vegetation.

A sequence of α‐dense curves with accumulated density represents an original concept to be added to the set of techniques to optimize a multivariable function by the reduction to only one variable as a new application of α‐dense curves theory to the global optimization.

The damping accumulated discrete MGM(1, m) power model is proposed for the problem of forecasting the share of agricultural output value and the share of employment in China.

In this study, the damping accumulated discrete MGM(1, m) power model was developed based on the idea of discrete modelling by introducing a damping accumulated generating operator and power index. The new model can better identify the non-linear characteristics existing between different factors in the multivariate system and can accurately describe and forecast the trend of changes between data series and each of them.

The validity and rationality of the new model are verified through numerical experiment. It is forecasted that in 2023, the share of agricultural output value in China will be 7.14% and the share of agricultural employment will be 21.98%, with an overall decreasing trend.

The simultaneous decline in the share of agricultural output value and the share of employment is a common feature of countries that have achieved agricultural modernisation. Accurate forecasts of the share of agricultural output value and the share of employment can provide an important scientific basis for formulating appropriate agricultural development targets and policies in China.

The new model proposed in this study fully considers the importance of new information and has higher stability. The differential evolutionary algorithm was used to optimise the model parameters.

Optimal switching angles are investigated for minimizing accumulated numerical errors when the dual‐Euler method is used in the simulation of angular rotation.

First, round‐off errors are theoretically modeled with a simplified mathematical representation of rotation. Round‐off errors take critical roles in the vicinity of indefinite points because they cause major numerical inaccuracy in very large numerical values represented with limited binary numbers. Optimal switching angles of (±π/4, ±3π/4) are derived and numerically examined. With a more practical and severe rotational model, the switching angles are numerically tested.

In conclusion, switching pitch angles of (±π/4, ±3π/4) yield near minimum numerical errors in angular parameters of pitch, yaw, and roll if truncation errors are not dominant by using high‐order integration algorithms and small step sizes. It is also noticed that accumulated numerical errors increase dramatically if pitch and roll angles are switched beyond the optimal angles with a little margin.

Optimal switching angles in the dual‐Euler method are identified based on the truncation error analysis. The mechanism of accumulated numerical errors in the dual‐Euler method, which depends on switching angles, is also revealed.

For firms entering a foreign market for the first time, institutional distance can be thought of as being insufficient in the sense that knowledge gap issues associated with large distances are not easily resolved. The purpose of this paper is to explore the concept of knowledge sufficiency and the implications that this concept holds for assuaging these issues.

The concept of knowledge sufficiency is developed into a practical framework. The framework is comprised of the knowledge that firms accumulate about potential host countries. This accumulated knowledge is disaggregated into components that provide the basic structure of the knowledge sufficiency framework and facilitate a systematic assessment of accumulated knowledge.

Accumulated knowledge about foreign market risk factors that exist in potential host countries is disaggregated into three components. The breadth of knowledge component is designed to help answer the question: what do firms know about foreign market risk factors in potential host countries? The depth of knowledge component is designed to help answer the question: how much do firms know about foreign market risk factors in potential host countries. The quality of knowledge component is designed to answer the question: are firms confident in what they know about foreign market risk factors in potential host countries?

There is a tendency for strategic decision makers in firms to feel that they have “deep” knowledge of foreign market risk factors when they may actually have only “surface” knowledge of these factors. The result is likely to be an unwarranted lowering of the risk they perceive to exist in potential host countries. Consequently, the host country selected for entry may not be optimal and the mode of entry may be inappropriate. The issue to be resolved is how to ascertain how much knowledge firms actually possess about these foreign market risk factors.

Selecting the “right” foreign market and entering that market in the “right” way is unquestionably one of the most important topics in the international literature and has been extensively studied. However, there is no central repository of finding from these studies that will help firms going international for the first time to systematically assess whether their choice of market and entry mode is optimal. Utilization of the knowledge sufficiency framework will significantly improve firms’ chances of entering the “right” foreign markets in the “right” way, which holds practical implications for their initial and long-term performance in these markets.

For firms entering a foreign market for the first time, answers to two questions are essential: what foreign market should we enter? How should we enter that foreign market? The extant literature does not provide a framework that allows firms to systematically search for answers to these questions such that, when satisfactorily found, will boost confidence that answers to these two questions are optimized. In addition to filling an important gap in the extant literature, the framework's usefulness as an aid for making internationalization decisions also makes an important contribution to practice.