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This paper aims to outline the financial implications, while deploying information and communication technologies for implementing e‐learning, and to elucidate them, while implementing an e‐learning project in a conventional university environment.

The paper is a descriptive account of the various cost factors and benefits accrued in implementing an e‐learning project and draws on a variety of secondary sources both published and unpublished.

The paper identifies the various cost factors as well as the benefits involved in e‐learning implementation in conventional educational institutions, so that e‐learning implementation is a smooth process. Three modes of e‐learning exist, namely, substantially online mode; replacement mode; and supplemental mode, and the costs of e‐learning vary for each. The paper also describes how to assess the success or failure of an e‐learning project.

The paper presents a review of literature developed from secondary sources since e‐learning implementation is in a budding stage in conventional universities, particularly in the Asian context.

The paper outlines the financial implications of e‐learning and provides information on the various cost factors in implementing an e‐learning project for the first time. These factors should be duly acknowledged and given consideration, if the advantages of e‐learning are to be fully realised and e‐learning implementation is to succeed.

This paper provides a valuable summary of the state of affairs of financial implications, for instance the cost factors and benefits accrued while implementing an e‐learning project in the case of conventional universities. From this summary of the current situation, it goes on to suggest potential ways to transform the “digital divide” into “digital opportunities”.

I In a number of publications, but especially in the Boston Consulting Group's booklet Perspectives on Experience, it has been argued that a profitable corporate strategy is to maximise market share. This is because as accumulated output increases, average costs are supposed to fall substantially. This is attributed to economies of scale, technological progress, learning by doing and so forth. It is the present writer's contention that this argument is of doubtful validity. The aspect of the Boston Group's representation that has attracted considerable attention is the learning by doing aspect, but we shall begin our argument by examining the economist's view of costs.

The purpose of this paper is to investigate how a substantial organization gradually builds a management accounting system from scratch, changing its accounting routines by learning processes. The paper uses the experiential learning theory and the concept of learning style to investigate the learning process during management accounting change. The study aims to expand the domain of management accounting change theory to emphasize the learning-related aspects that can constitute it.

The paper provides an interpretation of management accounting change based on the model of problem management proposed by Kolb (1983) and the theory of experiential learning (Kolb, 1976, 1984). The study is based on a 14-year longitudinal case study (1994‐2007). The case examined can be considered a theory illustration case. Data were obtained from a broad variety of sources including interviews, document analysis and adopting an interventionist approach during the redesign of the costing system.

The paper contributes to two important aspects of management accounting change. First, it becomes apparent that the costing information change was not a discrete event but a process of experience and learning conducted through several iterations of trial-and-error loops that extended over the years. Second, the findings reveal that the learning process can alter management accounting system design in a radical or incremental way according to the learning style of the people involved in the process of change.

Because of the adopted research approach, results could be extended only to other organizations presenting similar characteristics. Several further areas of research are suggested by the findings of this paper. In particular, it would be of interest to investigate the links between learning styles and communication and its effect on management accounting change.

The paper includes implications for the management of learning during management accounting change, to improve the efficiency and effectiveness of this process.

This paper is one response to the call for an interdisciplinary research approach to the management accounting change phenomena using a “method theory” taken from the discipline of management to provide an explanation of the change in management accounting. In respect of the previous literature, it provides two main contributions, namely, the proposal of a model useful both to interpret and manage learning processes; the effect of learning style on management accounting routines change.

This paper aims to describe the use of a meta-learning framework for recommending cost-sensitive classification methods with the aim of answering an important question that arises in machine learning, namely, “Among all the available classification algorithms, and in considering a specific type of data and cost, which is the best algorithm for my problem?”

This paper describes the use of a meta-learning framework for recommending cost-sensitive classification methods for the aim of answering an important question that arises in machine learning, namely, “Among all the available classification algorithms, and in considering a specific type of data and cost, which is the best algorithm for my problem?” The framework is based on the idea of applying machine learning techniques to discover knowledge about the performance of different machine learning algorithms. It includes components that repeatedly apply different classification methods on data sets and measures their performance. The characteristics of the data sets, combined with the algorithms and the performance provide the training examples. A decision tree algorithm is applied to the training examples to induce the knowledge, which can then be used to recommend algorithms for new data sets. The paper makes a contribution to both meta-learning and cost-sensitive machine learning approaches. Those both fields are not new, however, building a recommender that recommends the optimal case-sensitive approach for a given data problem is the contribution. The proposed solution is implemented in WEKA and evaluated by applying it on different data sets and comparing the results with existing studies available in the literature. The results show that a developed meta-learning solution produces better results than METAL, a well-known meta-learning system. The developed solution takes the misclassification cost into consideration during the learning process, which is not available in the compared project.

The proposed solution is implemented in WEKA and evaluated by applying it to different data sets and comparing the results with existing studies available in the literature. The results show that a developed meta-learning solution produces better results than METAL, a well-known meta-learning system.

The paper presents a major piece of new information in writing for the first time. Meta-learning work has been done before but this paper presents a new meta-learning framework that is costs sensitive.

Decisions regarding the amount and form of training are central to human resources management. Yet it is generally recognised that the acquisition of skills may also arise from on‐the‐job experience. There will be many cases where learning by experience will be the most important method of skill acquisition. Yet learning from experience may be thought to require little planning, since it cannot be avoided. As such, little attention is generally given either to costing learning from experience or evaluating its implications. This article adopts an economics perspective to examine the costs of learning from experience for the firm. An implicit assumption of the analysis is the “economic” or “rational” manager and employee evaluating benefits and costs in order to maximise the difference. This may at first appear to the personnel manager less than realistic — but this is to misunderstand the nature of economic analysis. The analysis is based on building models containing (economic) assumptions of behaviour, and thus the effectiveness of market forces. It recognises that problems are highly complex and builds in simplifying assumptions with the intention that they are interpreted in this light.

The open‐learning student has far more responsibility for setting the learning agenda than in traditional systems. Guidance is needed to help confirm the choice of course and explain particular difficulties associated with open learning. Tasks of the tutor include defining aims and learning objectives; organising learning material; presenting this material and assessing and providing feedback on achievement. The emphasis within this mix of activities changes in open learning, with more time on counselling and providing a mark and comment service. Ready availability of individualised learning materials is critical to the development of open learning. Lack of resources has been one reason why open learning has not been more widely adopted. The more effective the investment in materials development, the less likely the requirement for high levels of tutorial support. Development costs of learning materials and calculation of the cost of delivery systems are discussed.

This chapter provides an innovative way to introduce a series of managerial assignments that will allow students to take an example of a real company that interests them and answer questions designated by the instructor. The assignments are individualized to let students choose their area of interest and apply accounting concepts. At the same time, the instructor formulates questions for students to answer based on the materials covered. This chapter also provides an implementation process and student feedback.

Presents a dynamic programming model for studying the effects of automation acquisition on the value, cost, and quality control processes in an aggregate single product environment. The model provides the optimal automation acquisition policy, that is the optimal amount of automation to be acquired and the optimal timing for acquiring it, so that the accumulated net product value can be maximized. The model can be used with different sets of learning rates and cost data. It can also be used with non‐uniform learning rates among the different processes, and non‐uniform automation effects on the value, cost, and quality control learning curves. The cases both of unbounded and bounded learning curves are examined. Selective results demonstrate that the early acquisition of the optimal amount of automation enhances the accumulated net product value.

This chapter describes a service learning (SL) project implemented in an upper-level undergraduate Cost Accounting course to enhance the coverage of costing concepts. Employing a variation of Lafond, Leauby, and Wentzel (2017) SL task, students actively gather cost data for a business venture by preparing peanut butter and jelly sandwiches which are then donated to a local soup kitchen. Comparison of scores on pre- and post-tests suggests that the SL assignment enhances students’ understanding of key cost accounting concepts. More specifically, improvements in mean post-test scores proved significantly greater in the experimental group after completion of the SL activity than in the control group. Feedback further suggests that students appreciated the opportunity to engage in SL by helping others less fortunate. Active SL tied to course objectives meets The Association to Advance Collegiate Schools of Business (AACSB, 2013) suggestions for honing students’ critical thinking skills, while also helping to instill SL values in future business leaders.

In this chapter, we examine the impact of pay-for-performance incentives on learning-by-doing. We exploit personnel data on fruit pickers paid under two distinct compensation contracts: a standard piece rate plan and one with an extra one-time bonus tied to output. Under the latter, we observe bunching of performance just above the bonus threshold, suggesting workers distort their behavior in response to the discrete bonus. Such bunching behavior increases as workers gain experience. At the same time, the bonus contract induces considerable learning-by-doing for workers throughout the productivity distribution who presumably hope to one day hit the target, and these improvements significantly outweigh the losses to the firm from the bunching. In contrast, under the standard piece rate contract, we find minimal evidence of bunching and only small performance improvements at the bottom of the productivity distribution. Our results suggest that contract design can help foster learning on the job, underscoring the importance of dynamic considerations in principle-agent models.