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The purpose of this paper is the development of an analytic computational model for electromagnetic (EM) wave scattering from spherical objects. The main application field is the modeling of electrically large objects, where the standard numerical techniques require huge computational resources. An example is full-wave modeling of the human head in the millimeter-wave regime. Hence, an approximate model or analytical approach is used.

The Mie–Debye theorem is used for calculating the EM scattering from a layered dielectric sphere. The evaluation of the analytical expressions involved in the infinite sum has several numerical instabilities, which makes the precise calculation a challenge. The model is validated through an application example with comparing results to numerical calculations (finite element method). The human head model is used with the approximation of a two-layer sphere, where the brain tissues and the cranial bones are represented by homogeneous materials.

A significant improvement is introduced for the stable calculation of the Mie coefficients of a core–shell stratified sphere illuminated by a linearly polarized EM plane wave. Using this technique, a semi-analytical expression is derived for the power loss in the sphere resulting in quick and accurate calculations.

Two methods are introduced in this work with the main objective of estimating the final precision of the results. This is an important aspect for potentially unstable calculations, and the existing implementations have not included this feature so far.

To integrate environmental management systems into daily operations, the environmental aspects of management control systems (MCS) are enhanced. Although different approaches and concepts for Environmental Management Control Systems (EMCS) have been developed, two main problems appear: First, insights into how to implement EMCS are rare. Second, concepts are constructed mainly for large companies rather than for SMEs.

To close these research gaps, an implementation framework for SMEs is developed based on Epstein’s corporate sustainability framework. By using an action-oriented research approach, the implementation framework is analysed and tested on three Logistics Service Providers (LSPs).

The framework worked well with two of the firms analysed and failed with the third firm. The case study results enable a first evaluation of the implementation requirements that are essential for implementing EMCS in SMEs.

The causal relationship between the size of welfare benefits and the birth decisions of women on welfare has been explored in a number of studies using a variety of analytical approaches applied to vital statistics data, data from the Current Population Survey, the Panel Study of Income Dynamics, or similar survey data. These studies typically use non-experimental methods to relate differences in birth rates or birth decisions across states to differences in welfare benefits levels. Analyses of this type have been criticized on several grounds. Benefits across states may be correlated with unobserved interstate differences that may also be related to birth decisions. Very often, these studies measure the key independent variable, welfare benefits level, as the cash benefit guarantee under the Aid to Families with Dependent Children (AFDC) program for a household of fixed size, varying this amount by state of residence. Actual benefits paid will vary with household size, number of AFDC-eligible household members, other sources of income, and other factors.

This paper aims to assess the impact of big data analytics capabilities (BDAC) on organizational innovation performance through process-oriented dynamic capabilities (PODC), as a mediator, as well as the moderating roles of organizational culture (OC) and management accountants, in this artificial intelligence (AI) era. This paper also aims to provide information on the emerging trends and implications of the abovementioned relationships by focusing on these relationships and interactions.

This exploratory study used the close-ended questionnaire approach based on the resource-based view and socio-materiality theories. This included sending questionnaires to top-level management, including Chief Financial Officer/Chief Executive Officers/Chief Information Officers (CFO/CEOs/CIOs), having an in-depth understanding of the concepts, practical applications and usage of big data as well as BDAC.181 valid questionnaire-based responses were analyzed using the partial least square structural equation modelling technique and bootstrapping moderated mediation method.

This study provides empirical insights into how BDAC impact innovative performance through PODC as well as the moderating effects of OC and management accountants. This involves a shift in focus from almost standardized approaches to developing BDAC without contextual focus on approaches that are much more heterogeneously related to each organization and hence are more focused on the context of the pharmaceutical industry.

The main aim of key research questions in this study is to increase the contributions of BDAC toward improving innovation performance in the presence of the abovementioned variables and relationships that exist between them. The chosen research approach can be improved by carrying out interviews with the top management to obtain more relevant and detailed information for developing a better understanding of the abovementioned relationships.

This study outlines how organizations that are developing BDAC approaches can focus on relevant factors and variables to help their initiatives and its role in organizational innovative performance. This will also help them develop sustainable competitive advantage in manufacturing concerns, specifically in the health industry, namely, the pharmaceutical industry.

This study investigated the effects and implications of big data on organizations in the AI era that aim to achieve innovation performance. At the same time, it provides an original understanding of the contextual importance of investing in BDAC development. It also considers the role of management accountants as a bridge between data scientists and business managers in a big data environment, especially in the pharmaceutical industry. The current study used first-time data from surveys involving CFOs, CEOs or CIOs of pharmaceutical companies in Pakistan and analyzed the proposed model using bootstrapping moderated mediation analysis.

The purpose of this paper is to compare and contrast perceptions about the research-practice “gap” as it may apply within management accounting, from the perspective of professional accounting bodies in Australia and Germany.

The findings reported in this paper is based on the collection and analysis of data from interviews with 19 senior representatives from four Australian Professional bodies and 14 representatives of German Professional accounting bodies.

In Australia and Germany, there exist common as well as unique barriers preventing a more effective engagement of academic research with practice. Common to both countries is the perception that the communication of research represents a major barrier. In Australia, practitioner access to academic research is seen to be a principal obstacle; in Germany, the relevance of topics researched by academics is perceived to represent a significant barrier to academic research informing practice.

This paper directly engages with, and extends recent empirically based research into the extent to which academic research may “speak” to management accounting practice. It extricates both common and specific barriers contributing to the oft-quoted “research-practice gap” in management accounting, and points to the pivotal nature of an intermediary to act as a conduit between academics and practice.

By investigating this issue in two quite different cultural, educational, academic and practice contexts, this paper provides much-needed empirical evidence about the nature, extent and pervasiveness of the perceived research-practice gap in management accounting, and provides a basis for further investigation of this important topic.

The study seeks to evaluate the effect of capital adequacy and competition on the liquidity creation of Kenyan commercial banks.

Unbalanced panel data from 36 Kenyan commercial banks with licenses from 2001 to 2020 is used in the study. The generalized method of moments (GMM), a two-step system, is employed in the investigation. To increase the robustness and prevent erroneous findings, serial correlation tests and instrumental validity analyses are used. The methodology developed by Berger and Bouwman (2009) is used to estimate the commercial banks' levels of liquidity creation.

The study supports the financial fragility-crowding out hypothesis by finding a significant negative effect of capital adequacy on the liquidity creation of commercial banks. The research also identifies a significant inverse relationship between competition and liquidity creation, depicting competition's value-destroying effect.

A trade-off exists between capital adequacy and liquidity creation, which must be carefully evaluated as changes in capital requirements are considered. The value-destroying effect of competition on liquidity creation presents a case for policy geared toward consolidating banks' operations through possible mergers and acquisitions.

To the best of the authors' knowledge, this is the first study to empirically offer evidence concurrently on the effect of competition and capital adequacy on the liquidity creation of commercial banks in a developing economy such as Kenya. Additionally, the authors employ a novel measure of competition at the firm level.