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In this chapter we develop sustainability implications of the Savall, Zardet, Bonett, and colleagues’ approach, known worldwide as socioeconomic approach to management (SEAM). SEAM can be used as a way of doing management and organizational inquiry into the ecological sustainability of practices with planetary boundaries. We conclude that a socially responsible approach to management needs to consider the hidden costs to an enterprise if it is not being sustainable to planetary resource limits.

The purpose of this study, with its central thesis placed on excelling at business measures, is to underscore the need for business entities to understand the significant implication of hidden failure costs and its impact on their business processes. The study also stresses the need for organizations to systematically break the many norms.

This study looked at capturing the often‐overlooked component of poor quality cost via a simple function of measurement which requires an effortless yet painstaking way of collecting data pertaining to intangible wastages in the form of time, service charges and material.

A simple formula is introduced, using three types of indicators that could be used to monitor the level of poor quality costs (PQC), to quantify the total failure costs by accumulating the values of both hidden and visual failure costs.

The study breaks the boundaries of existing methods of understanding and calculating the all‐embracing cost of doing business, hence paving the way to make inroads in business processes improvement, enhanced job‐scope comprehension, agility and performance, further intensification of internal and external customer satisfaction.

The purpose of this paper is to present a report on the implementation of a quality cost program in a continuous‐process manufacturing company, with particular emphasis on the unearthing of hidden quality costs, as well as gaining a closer understanding of the resistance against implementation.

Using an action research approach, the researchers participated – directly and indirectly – in the implementation of quality costing at the case company. The research process comprises iterative cycles of gathering data through documentary reviews, observations of company operations, discussions with operatives, analyzing data, undertaking actions and evaluating results. Following Sandoval‐Chavez and Beruvides, the poor quality cost analysis includes an additional category to the conventional prevention‐appraisal‐failure model to reflect the cost of lost opportunities.

The study unearthed a significant portion of hidden quality costs which may be termed an “opportunity loss”. The findings indicate that the company's total quality costs actually far exceed its current profit margin, and that the company could improve its competitive position if it focused on the elimination of these quality costs.

This paper focuses on uncovering hidden quality costs. However, the measuring of quality costs only serves to identify opportunities for improvement. It is follow‐up corrective actions that will lead to organizational effectiveness. The research findings support the contention that tracking of poor quality costs is an important step in the quality management process.

This paper presents a proactive way of tracking hidden quality costs.

This paper aims to draw on the field of real estate management to explore the cost of flex-offices as well as the corporate discourse toward it and to identify the possible gap between real estate directors' discourse and the real cost of flex-offices.

This paper follows the grounded theory approach. Three studies were conducted: 16 semi-structured interviews with real estate actors, categorization of internal corporate documents and a thorough content analysis of the press discourse.

There is a positive vision as well as a very optimistic outlook on the flex-office on the part of real estate actors and the press. This research shows that reality does not reflect the discourse as 12 hidden costs identified are not currently factored into costs when setting up a flex-office, which can distort the discourse and efficiency. It will be interesting to measure those hidden costs in future research so as to have an objective discourse and a better cost estimate when deploying this kind of workspace.

Contradict the widespread discourse about flex-offices by highlighting the hidden costs that should be taken into consideration to allow managers to make accurate estimates. Although these hidden costs may seem ancillary at first sight, they might have an impact on efficiency.

IT-enabled service offshoring has become a vital and widespread practice for firms seeking to realize various advantages. However, many firms suffer from “hidden costs” (the discrepancies between the expected and actual costs of offshoring), and these firms often find a disappointing outcome from their offshoring decisions. The purpose of this paper is to explore whether and how the adoption of an offshoring strategy can reduce such hidden costs and how this effect can be moderated by contextual factors, including the complexity of tasks and the accumulation of experience.

Based on survey data from the Offshoring Research Network, this study uses hierarchical regression analysis to empirically test the hypothesized relationships.

A corporate-wide strategy for guiding offshoring decisions may effectively reduce cost-estimation errors. This effect is amplified by increasing task complexity, but decreases with growing offshoring experience. Regardless of whether a strategy is initially in place, most firms learn to avoid cost-estimation errors only after several years. This finding suggests that firms have a limited ability to mitigate hidden costs in the short term.

The guidelines specified by an overarching strategy can better rationalize cost estimation and goal setting for individual offshoring projects, provide incentives for project participants to achieve preset aspirations, and enhance cost-efficiency in fulfilling offshoring activities and in coping with emerging contingencies. Firms tend to benefit more from establishing a formal strategy to reduce the hidden costs of more complex projects, especially if the firms involved have little offshoring experience.

This study empirically examines the hidden costs in offshoring from a strategic management perspective. This approach extends our understanding of cost estimates in offshoring, and it explores the influence of corporate strategy in the alignment of expected and achieved performances from IT-enabled service offshoring. The study also examines the boundaries of strategy’s ability to affect hidden costs, and it expands our knowledge of the relationship between strategy and experience.

There is need for a new, more precise, more integrated system for logistics costing. The integration of purchasing, transportation (traffic) and storage operations throughout the vertical stream, from source of materials to the consumer is discouragingly complex. It cannot be accomplished by departmentalising logistics functions, performing average and joint commodity costing, and dealing primarily with direct costs. The volume of records may be representative, but there is a very apparent lack of costing systems to facilitate logistics planning. The volume of shipment is the key to logistics cost analysis, just as volume of production is the independent variable in conventional economic analysis. Logistics costs vary with changes in the volume of shipment. Cost per hundredweight is the unit for cost analysis under the Cellular Flow Planning System. It is measured on a specific commodity, between specific points. Purchase price, transport rate, linear increasing costs, constant and single payment decreasing costs are the five classes of costs used to compare competitive volumes of shipment. All significant logistics costs can be so classified. This article presents only the rationale behind the unit for cost measurement, the classification of costs, and the means of comparison.

The purpose of this paper is to explore the use of knowledge management (KM) principles and technologies to improve the outcomes of software acquisition projects. Software acquisition organizations typically contract‐out their software projects to reduce the risks associated with developing the software internally and to control their cost.

This paper is based on a study of contracted software projects. Research results by the authors emphasize the need for institutionalizing processes for the collection of data about contracting costs within an organization so that databases of metrics about completed projects can be built and later used to forecast costs for future projects to improve the decision‐making processes about outsourcing.

A study of two‐dozen contracted projects indicates that such organizations face unique risks and hidden costs that are particular to software acquisitions. KM models, practices, and tools are potentially valuable for improving software outsourcing activities.

KM can be useful for identifying the organizational structures, processes and informational technologies for measuring, collecting, and analyzing costs and risks incurred before, during and after the contract award. The same framework can also be used to collect data on the acquisition activities and processes such as writing requests for proposals, contractor evaluation and selection, predicting needed resources, and identifying risks. Such knowledge can be used on future projects to improve the acquisition processes by allocating adequate resources and identifying risks to improve the likelihood of project success.

There are costs associated with the acquisition, implementation, and operation of information systems beyond the price of hardware and software. As these costs sometimes account for budget shortfall, it is important to recognize problem areas and minimize their impact on the organization. Potential hidden costs, including costs that may be hidden by managers, as well as costs that may be hidden from them, are identified and recommendations offered for avoiding serious consequences.

Quality cost is usually considered as a means to measure the quality level in a quality system. Since the interrelationship among quality cost components is complex, a general quantitative model for describing their relationship is not easy to construct for improving the quality. In the assessments of quality cost, some hidden quality costs, such as the goodwill loss due to lost customers’ reliability, are often neglected in the existing analysis methods. This may lead to reaching a sub‐optimal decision. In addition, the assessments of quantitative quality cost items are usually approximated, and therefore are imprecise in nature. Based on these considerations, we propose fuzzy approaches to evaluate quality improvement alternatives because of its fuzzy nature. An evidence fusion technique, namely Choquet fuzzy integral, is employed to aggregate the quality cost information. A composite index is determined to find the best quality improvement alternative. Finally, a numerical example is used to demonstrate the applicability of the approach.

The purpose of this paper is to model a block-based inspection policy for a multi-component system with stochastic dependence. Some components may develop a hidden failure, an occurrence of which neither stops the system nor accelerates the other components’ deterioration. On the other hand, other components may experience three states: healthy, defective and revealed failures. Any revealed failure of each component not only stops the system but also generates a shock to all the other ones, which increases their occurrence rate of hidden, defect and revealed failures.

A block-based inspection policy is considered to take advantage of economic dependence as follows. In addition to the periodic inspections, the system is also inspected at revealed failures’ moments of each component to detect and fix both defects and hidden failures on all the other components. To calculate the expected total cost, the recursive equations for the required expected values is first mathematically derived. Then, due to computational complexity, an efficient Monte Carlo simulation algorithm is designed to calculate the expected values.

The proposed approach is illustrated through a numerical example, and the optimal periodic inspection interval over a finite time horizon is obtained via minimization of the expected total cost. Finally, the correctness of the results is validated by conducting sensitivity analysis.

Planning an appropriate inspection policy over a finite time horizon becomes more complicated when considering a multi-component system because different units may experience different failure modes with stochastic dependence.