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This paper aims to present a methodology for activity‐based costing, which combines simulation modeling and association rule mining, one of the core data‐mining techniques. The objective of the proposed methodology is to deal with the problem of defining cost drivers.

Activity‐based costing uses the output produced by the simulation of cost drivers as inputs. As opposed to the integration of the ABC technique with simulation modeling, the possibility of estimating an empirical distribution of the simulated cost drivers does not exist in the proposed methodology. This is achieved with the use of data‐mining techniques and is based on the proposition that, if an association is found between a cost driver, whose estimation or calculation is time‐consuming, and another cost driver, which can easily be estimated or calculated, then the latter can lead to the estimation or calculation of the former.

The extracted association rules correspond to existing dependencies between the cost drivers.

The paper presents a combined methodology to deal with the problem of defining cost drivers in activity‐based costing. An example of the proposed methodology in healthcare is also presented.

This paper aims to focus on applications of stochastic linear programming (SLP) to managerial accounting issues by providing a theoretical foundation and practical examples. SLP models may have more implications – and broader ones – in industry practice than deterministic linear programming (DLP) models do.

This paper introduces both DLP and SLP methods. In addition, continuous and discrete SLP models are explained. Applications are demonstrated using practical examples and simulations.

This research work extends the current knowledge of SLP, especially concerning managerial accounting issues. Through numerical examples, SLP demonstrates its great ability of hedging against all scenarios.

This study serves as an addition to building a cumulative tradition of research on SLP in managerial accounting. Only a few SLP studies in managerial accounting have focused on the development of such an instrument. Thus, the measurement scales in this research can be used as the starting point for further refining the instrument of optimization in managerial accounting.

Random media uncertainties exhibit a significant impact on the properties of electromagnetic fields that usually deterministic models tend to neglect. As a result, these models fail to quantify the variation in the calculated electromagnetic fields, leading to inaccurate outcomes. This paper aims to introduce an unconditionally stable finite-difference time-domain (FDTD) method for assessing two-dimensional random media uncertainties in one simulation.

The proposed technique is an extension of the stochastic FDTD (S-FDTD) scheme, which approximates the variance of a given field component using the Delta method. Specifically in this paper, the Delta method is applied to the locally one-dimensional (LOD) FDTD scheme (hence named S-LOD-FDTD), to achieve unconditional stability. The validity of this algorithm is tested by solving two-dimensional random media problems and comparing the results with other methods, such as the Monte-Carlo (MC) and the S-FDTD techniques.

This paper provides numerical results that prove the unconditional stability of the S-LOD-FDTD technique. Also, the comparison with the MC and the S-FDTD methods shows that reliable outcomes can be extracted even with larger time steps, thus making this technique more efficient than the other two aforementioned schemes.

The S-LOD-FDTD method requires the proper quantification of various correlation coefficients between the calculated fields and the electrical parameters, to achieve reliable results. This cannot be known beforehand and the only known way to calculate them is to run a fraction of MC simulations.

This paper introduces a new unconditional stable technique for measuring material uncertainties in one realization.

This paper aims to propose a novel approach which integrates collocations and domain concepts for Chinese cosmetic word of mouth (WOM) sentiment classification. Most sentiment analysis works by collecting sentiment scores from each unigram or bigram. However, not every unigram or bigram in a WOM document contains sentiments. Chinese collocations consist of the main sentiments of WOM. This paper reduces the complexity of the document dimensionality and makes an improvement for sentiment classification.

This paper builds two contextual lexicons for feature words and sentiment words, respectively. Based on these contextual lexicons, this paper uses the techniques of associated rules and mutual information to build possible Chinese collocation sets. This paper applies preference vector modelling as the vector representation approach to catch the relationship between Chinese collocations and their associated concepts.

This paper compares the proposed preference vector models with benchmarks, using three classification techniques (i.e. support vector machine, J48 decision tree and multilayer perceptron). According to the experimental results, the proposed models outperform all benchmarks evaluated by the criterion of accuracy.

This paper focuses on Chinese collocations and proposes a novel research approach for sentiment classification. The Chinese collocations used in this paper are adaptable to the content and domains. Finally, this paper integrates collocations with the preference vector modelling approach, which not only achieves a better sentiment classification performance for Chinese WOM documents but also avoids the curse of dimensionality.

This paper aims to analyse the open data business models (ODBMs) as a source of knowledge and innovation to generate economic and social value. A framework for understanding ODBMs is presented. First, the knowledge structure of the ODBMs literature is identified. Second, a conceptual model for analysing the ODBMs is proposed. And finally, the future trends in ODBMs research are discussed.

In this paper, co-word analysis is performed to identify the topics related with ODBMs.

The ODBMs structure of knowledge is articulated in five themes: business model, smart city, business ecosystem, decision-making and innovation. Based on these results, a five-step model for analysing ODBMs is proposed. Finally, a discussion of the future trends of ODBMs focussed on a knowledge management perspective, open data ecosystems and business intelligence is presented.

The paper presents a picture of what, where, for whom and for what ODBMs have been studied and develops a new model to explain the value creation process of ODBMs. Taking a step further, applying the principles and models of knowledge management and business intelligence to ODBMs is also recommended in order to transfer and transform open data into valuable knowledge that can be used for developing apps. In that context, the importance of encouraging collaboration between different agents in the so-called open data ecosystem is presented.

This paper aims to introduce a computationally efficient hybrid analytical–finite element (FE) methodology for loss evaluation in electric vehicle (EV) permanent magnet (PM) traction motor applications. In this class of problems, eddy current losses in PMs and iron laminations constitute an important part of overall drive losses, representing a key design target.

Both surface mounted permanent magnet (SMPM) and double-layer interior permanent magnet (IPM) motor topologies are considered. The PM eddy losses are calculated by using analytical solutions and Fourier harmonic decomposition. The boundary conditions are based on slot opening magnetic field strength tangential component in the air gap in the SMPM topology case, whereas the numerically evaluated normal flux density variation on the surface of the outer PM is implemented in the IPM case. Combined analytical–loss evaluation technique has been verified by comparing its results to a transient magnetodynamic two-dimensional FE model ones.

The proposed loss evaluation technique calculated the total power losses for various operating conditions with low computational cost, illustrating the relative advantages and drawbacks of each motor topology along a typical EV operating cycle. The accuracy of the method was comparable to transient FE loss evaluation models, particularly around nominal speed.

The originality of this paper is based on the development of a fast and accurate PM eddy loss model for both SMPM and IPM motor topologies for traction applications, combining effectively both analytical and FE techniques.

This paper seeks to demonstrate an application of a methodology, which is based on the integration of three techniques, with the purpose of modelling activity‐based costing (ABC) in restaurants. The proposed methodology serves as a tool for effectively computing values of cost drivers in the restaurant industry, as well as making accurate cost estimations.

The methodology is based on the integration of three techniques: simulation modelling, association rule mining (ARM) and ABC. Simulation modelling is used to model process variability and produce a range of cost values, instead of a point estimate of the cost, by generating a range of values for the simulated cost drivers. The advantage of the proposed methodology lies on the effective utilization of ARM in the ABC model; it extracts dependencies between a cost driver, whose estimation is time‐consuming, with another cost driver, which can easily be calculated. These associations can assist the estimation of the empirical distributions of those cost drivers, which were difficult to calculate.

The extracted associations verify the hypothetical relations between the cost drivers. The output produced is more precise values of the cost drivers that are included in an ABC model and were difficult to estimate. More accurate cost estimate means better pricing decisions for the restaurant managers.

The proposed methodology is an innovative technique that provides more accurate accounting information in the restaurant industry.

Accumulators are cutting‐edge stock derivative investments that have been the subject of much controversy in Hong Kong over the past year. Accumulators are exotic options composed of a full year of daily long up‐and‐out call options and short up‐and‐out put options. Because accumulators are so new, the understanding of accumulators is currently very limited. This paper attempts to characterize and understand the properties of this fairly unknown and new stock derivative investment.

The study analyzed and characterized accumulators based on observations from past history of 11 stocks of the Hang Seng Index. Using historical stock data covering from January 3, 2006, and onward, the profit and loss for each accumulator contract was calculated.

Through the research it is understood that the profit and loss of accumulator contracts depends primarily on the following factors: knockout percentage, discount percentage, variability of the underlying stock, and the overall market trends, among other factors.

This pioneer simulation is an empirical exploratory post factum study that gives researchers and practitioners further insight how to formulate a risk neutral pricing model for accumulators in the future.

This study aims to explore talent retention in knowledge-intensive industries by investigating the mediating processes between the existence and application of human resource management (HRM) and employee turnover. Toward this end, drawing on the conservation of resources and job demands–resources theories, a three-dimensional model is examined, which includes the relationship between HRM, knowledge management (KM) and change management (CM), as well as their relationship with employee engagement and employee turnover intention.

The proposed research model has been studied with a sample of 168 talented employees in over six European countries, using a quantitative approach, involving the structural equation modeling method. All data were gathered by a multidimensional questionnaire via prolific, an academic crowdsourcing platform.

Results indicated that knowledge-intensive services firms may achieve higher talent retention through the interaction of HRM with KM and CM practices, which may lead to enhanced employee engagement.

Possible limitations of the study include the relatively small sample size, the self-rate questions for the collection of data and the use of cross-sectional data.

To retain their talented employees, organizations should identify ways to improve their HRM, CM and KM practices. In addition, HR practitioners ought to include their talented employees in all organizational change and KM processes and create mechanisms that successfully support knowledge acquisition, creation, sharing, retention and codification.

To the best of the authors’ knowledge, this is the first study to examine various factors of retaining talented employees in knowledge-intensive services. Furthermore, the study took place in six European countries, i.e. UK, Poland, Italy, Germany, Portugal and Greece, where the research on talent retention is very limited.

This paper aims to attempt to bring together various organisational aspects that have never been collectively investigated before in the strategic management literature. Its main objective is to examine the relationship between “strategic orientation” and “firm performance”, in the light of two firm-specific factors (“distinct manufacturing capabilities” and “organisational structure”). The proposed research model of the present study is built upon the resource-based view (RBV) of the firm and the organisational aspect of the VRIO framework (the “O” from the VRIO model).

The study proposes a newly developed research model that adopts a four-factor approach, while examining a number of direct and indirect effects. The examination of the proposed research model was made with the use of a newly developed structured questionnaire that was distributed on a sample of Greek manufacturing companies. Research hypotheses were tested using the structural equation modelling technique. The present study is explanatory (examines cause and effect relationships), deductive (tests research hypotheses), empirical (collects primary data) and quantitative (analyses quantitative data that were collected using a structured questionnaire).

The empirical results suggest the coexistence of three distinct categories of effects on “firm performance”: strategy or “utility” effects, depending on the content of the implemented strategy; firm-specific effects, depending on the content of the organisational resources and capabilities; and organisational effects, depending on the implemented organisational structure. More specifically, the statistical analysis underlines the significant mediating role of “strategic orientation” and the complementary role of “organisational structure”. Finally, empirical results support the argument that “strategy follows structure”.

The use of self-reported scales constitutes an inherent methodological limitation. Moreover, the present study lacks a longitudinal approach because it provides a static picture of the subject under consideration. Finally, the sample size of 130 manufacturing companies could raise some concerns. Despite that, previous empirical studies of the same field, published in respectable journals, were also based on similar samples.

When examining the total (direct and indirect) effects on “firm performance”, it seems that the effect of “organisational structure” is, almost, identical to the effect of “distinct manufacturing capabilities”. This implies that “organisational structure” (an imitable capability) has, almost, the same contribution on “firm performance” as the manufacturing capabilities of the organisation (an inimitable capability). Thus, the practical significance of “organisational structure” is being highlighted.

There has been little empirical research concerning the bundle of firm-specific factors that enhance the impact of strategy on business performance. Under the context of the resource-based view (RBV) of the firm, the present study examines the impact of “organisational structure” on the “strategy-capabilities-performance” relationship, something that has not been thoroughly investigated in the strategic management literature. Also, the present study proposes an alternate measure for capturing the concept of business strategy, the so-called factor of “strategic orientation”. Finally, the study adopts a “reversed view” in the relationship between structure and strategy. More specifically, it postulates that “strategy follows structure” and not the opposite (“structure follows strategy”). Actually, the empirical data supported that (reversed) view, challenging the traditional approach of Chandler (1962) and calling for additional research on that ongoing dispute.