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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.

The purpose of this paper is to utilize a cost and revenue driver model for commercial banking to examine the differential effects of the drivers within and between banking functions, and to examine the role of information technology (IT) in moderating the relationship between costs and cost drivers and revenue and revenue drivers.

The model is estimated on a cross‐sectional sample of 121 banks from the functional cost and profit analysis data set collected by the Federal Reserve Banks. Multivariate regression analysis with interaction terms is utilized to examine the differential impact of IT in two contrasting banking functions.

The results document the role of transactional IT on the cost driver relationships in the labor cost models in both the demand deposit and commercial loan functions. The role of strategic IT in the revenue driver models is documented for the demand deposit function but not for the commercial loan function.

Only two banking functions are selected. Expanding the model and testing it on other banking functions may be useful.

By disaggregating the IT variable and incorporating IT in a cost and revenue driver model managers can utilize the model to examine the impact of IT in banking.

A model that disaggregates the IT variable by allocating support costs to functions and delineates links between IT variables and cost and revenue drivers in banking.

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.

The objective of a cost management system is to provide accurate and useful information to help companies in utilizing their valuable resources for producing quality goods and services in a competitive environment. Activity‐based costing (ABC) has been found more appropriate for capital intensive manufacturing environments. However, there is no systemic framework for design and implementation of ABC. Realizing the importance of ABC, an attempt has been made in this paper to develop a framework for the design of an ABC system. It is based on the review of literature on the design and implementation of ABC. In ABC, the activities required to manufacture a product should be identified and then quantified by their consumption of resources. The cost of each activity that is required to produce the product/parts will be calculated in such a way that the factors causing or driving the cost (cost drivers) of the activity in question can be determined. The cost driver rate will be used to allocate the cost of activities to a product/part according to the volume of the cost driver. In addition, the advantages and limitations of ABC are also discussed.

This study aims to develop a success factor model to understand and facilitate improved cost management system (CMS) implementation in low-cost housing (LcH) project delivery in Nigeria.

Literature findings highlight 13 drivers affecting effective implementation within the CMS and uses series of brainstorming sessions and questionnaire surveys to validate the drivers. Factor analysis (FA) identifies possible contextual relationships among the validated drivers and groups them into three success factors. The results of the FA are refined using interpretive structural modelling (ISM). The ISM identifies and models the influential drivers and aids the development of the success factor model.

Effective team qualities, information and management actions and a stable operational environment are the three essential success factors for effective CMS implementation.

The paper highlights effective team qualities as the most important CMS considerations for Nigerian LcH project delivery. This finding creates the needed awareness to guide project sponsors and project managers in the appropriate selection of the project management team (PMT) as well as the procurement system that facilitates their collaboration.

This study is a novel research using FA and ISM to investigate the influence of success factors needful for effective implementation within the CMS. It further develops a hierarchy model that aids the PMT with better understanding of the drivers and factors interrelationships for use on LcH projects within the Nigerian context.

This study aims to focus on the supply chain (SC) cost drivers of healthcare industries in the USA, as SC costs have increased 40% over the last decade. The second-most significant expense, the SC, accounts for 38% of total expenses in a typical hospital, while most other industries can operate within 10% of their operating cost. This makes healthcare centers supply-chain-sensitive organizations with limited facilities for high-quality healthcare services. As the cost drivers of healthcare SC are almost unknown to managers, their jobs become more complex.

Guided by pragmatism and positivism paradigms, a cross-sectional study has been designed using quantitative and deductive approaches. Both primary and secondary data were used. Primary data were collected from health centers across the country, and secondary data were from healthcare-related databases. This study examined the attributes that explain the most significant variation in each contributing factor. With multiple regression analysis for predicting cost and Student's t-tests for the significance of contributing factors, the authors of this study examined different theories, including the market-based view and five-forces, network and transaction cost analysis.

This study revealed that supply, materials and services represent the most significant expenses in primary care. Supply-chain cost breakdown results in four critical factors: facility, inventory, information and transportation.

This study examined the data from primary and secondary care institutions. Tertiary and quaternary care systems were not included. Although tertiary and quaternary care systems represent a small portion of the healthcare system, future research should address the supply chain costs of highly specialized organizations.

This study suggests methods that can help to improve supply chain operations in healthcare organizations worldwide.

This study presents an empirically proven methodology for testing the statistical significance of the primary factors contributing to healthcare supply chain costs. The results of this study may lead to positive policy changes to improve healthcare organizations' efficiency and increase access to high-quality healthcare.

The costs of cleaning owner‐operated office buildings amount to an approximate 20 per cent share of the operating costs. As a result of their cost relevance and the growing cost pressures on real estate divisions, cleaning costs are increasingly coming under focus. This interest manifests itself in the search for cost indicators and their drivers to be used as a basis for the management of real estate. This paper seeks to address this issue.

A study of the specialist literature revealed, from a theoretical perspective, the relevant drivers of cleaning costs. The empirical study is based on cost and property information collected, on a uniform basis, from over 100 owner‐operated office buildings in Switzerland, with the analysis of cost drivers being carried out using regression analysis.

The cleaning cost indicators of the examined properties revealed a median of 41 CHF/m² usable floor area and year. With regard to cost drivers, it was established that both building characteristics and usage determine the costs. However, the decisive drivers are, above all, the management strategies and the owners' main objectives.

The management strategies proved to be specific to the individual project partners. The causal relationships between strategies (e.g. outsourcing strategies) and costs may be considered to be well‐substantiated hypotheses, which require verification by means of future analyses.

The study identified both indicators and relevant drivers of cleaning costs. To this end, this study collected data from over 100 owner‐operated office buildings within Switzerland and examined these data using regression analysis. As a result, the cleaning costs of the examined properties were ascertained.

As the manufacturing environment moves to computer‐integrated manufacturing and the products that are manufactured are diverse, conventional cost systems can report seriously distorted product costs. Discusses the solutions to these problems. Activity‐based costing, initiated and popularized by Robin Cooper and Robert S. Kaplan, can solve these distorted problems. Activity‐based costing (ABC) is defined as “the collection of financial and operation performance tracing the significant activities of the firm‐to‐product cost”. Discusses the ABC system design and ABC implementation. The five steps in the design of an ABC system are: aggregate actions into activities; report the cost of activities; identify activity centres; select first‐stage cost drivers; and select second‐stage cost drivers. The implementation plan consists of seven phases: an ABC seminar; a design seminar; design and data gathering; progress meetings; an executive seminar; result meetings; and interpretation meetings.