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Theeuwes and Adriaansen (1994), among others, have asserted that activity-based costing (ABC) is inappropriate for operational decision-making. In this article, ABC is modified to reflect separate flexible and committed cost driver rates for an activity. This enables the model to reflect the difference in the behavior of an activity’s flexible and committed costs needed for operational planning decisions. The modified ABC facilitates determining the resources required to produce the product mix developed from the firm’s strategic plan and the excess capacity that will result. The modifications made to ABC aid in determining an optimal product mix when the firm has excess capacity, while the traditional ABC may not. Equally important, it facilitates measuring the financial implications of the resource allocation decisions that comprise the firm’s operational plan. As the operational plan is implemented, operational control is used to ensure that it is performed in an efficient and effective manner. The modified ABC enables the firm’s managers to compute the different types of deviations that arise from using flexible and committed resources at the unit, batch, and product levels of the firm’s operations. This aids in understanding problematic aspects of the firm’s operations and identifying where management resources are needed to improve operational efficiency.

Outlines previous research on capacity planning and considers how the underlying ideas can be applied to higher education institutions (HEIs). Illustrates the components of operational and capacity plans for an HEI, pointing out the differences from and similarities to the manufacturing and service sectors; and discusses various components of the capacity plan (e.g. classroom utilization, enrolment, scheduling etc.) in more detail. Believes that this approach to resources would improve on the present US system where external pressures (e.g. politicians, donors etc.) rather than need may determine expansion, but recognizes the practical barriers to this and calls for further research.

Early twentieth century transatlantic migration was both a massive transoceanic population transfer and a complex travel business. The successful growth of this multinational commerce was based not on fare reductions, but on risk management strategies. Shipping lines provided costly carrying capacity sufficient to accommodate severely fluctuating demand for transatlantic migration, and did so in a manner which improved the reliability and quality of travel for migrants.

Although research attention has been given to the modelling process for simultaneous demand‐output management in manufacturing systems, little interest has been demonstrated in service organisations despite the fact that such organisations face unique conditions that further complicate the demand‐output management issue. In response to this lack of emphasis, we review the relevant research from both marketing and operations management and present a cost‐effectiveness model for balancing demand and service output.

Introduces the concept of a manufacturing strategy based on a service orientation. Traditional manufacturing strategies have often been driven by cost minimization decisions and have encouraged the over‐reliance by managers on inventories to satisfy demand. In today′s business environment, a reliance on inventory is often not feasible. Suggests a reliance on capacity available to meet demand, as used by the service industry. Such a strategy is in direct conflict with most cost‐accounting systems because of the absorption of overhead costs based on direct labour. Proposes two alternatives for changing the accounting system, to enhance the move towards the service‐based strategy. Lastly, presents a case study of a US plant to illustrate the results that a company adopting this approach should expect.

Two reasons are identified for studying the impact of capacity measurements on organizations. First, firms which make the best use of their resources can be expected to outperform their competitors. The second arises from the potential structuration effect of capacity metrics. Such an investigation makes capacity a visible, and hence an actionable, construct. This paper aims to address these issues.

To explore these issues, a combination of analytics and qualitative field research methodology was used. The measurement dimensions were developed by analyzing the different reports, baseline measures, and metrics included in the various capacity models as suggested by the literature. These analytics were enriched with observations obtained from field research.

Maximizing the value created within an organization starts with understanding the nature and capability of all the company's resources. The outcome is the identification of capacity systems specifically suited for particular types of operations, both manufacturing and service.

Such frameworks would allow organisations in developing economies, to make visible, the drivers of waste and productivity and to identify the primary assumptions and implications of various capacity limits.

This paper fills the gap between defining and measuring the productive limits of a machine or system, and the impact of various assumptions about the productive potential of the nature and informativeness of capacity cost management systems. The authors focused on the various ways in which multi‐dimensional limits (for example, time, space, volume and/or value‐creating ability) can be used to define productive capacity. Specifically, the research suggests that the limits used in establishing the capacity cost management system restrict the amount and nature of the information the system is capable of providing to management.

In Guangzhou, the largest city in southern China, car ownership is increasing beyond the capacity of the road system. This leaves streets gridlocked and parking facilities inaccessible, thus under-utilized. At the same time, Guangzhou's zoning code calls for additional off-site parking which is likely to encumber development. This chapter documents and discusses policies in Guangzhou that affect and are affected by parking and how they relate to City goals.

The chapter explores the relationship between three interrelated topics: (1) today’s parking policies in Guangzhou, regulated by a variety of municipal agencies, (2) case studies of two large developments and their respective parking supplies and demands, and (3) city goals and objectives.

There is opportunity for Guangzhou to implement strategies to manage its parking supply relative to its roadway capacity, plus integrate its parking policies to the overall transportation system.

Emerging cities can learn from other’s experiences. Parking supply affects the decisions people make about how they will travel and this in turn affects congestion, air quality and quality of life. Using smart parking regulations means an end to inadvertently fostering dependency on the car and the start of creating sustainable communities.

The value of the chapter comes from the way it builds from existing evidence to further understand the challenges of an emerging, fast-growing city.