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This study examines challenges to the retrospective financial evaluation of continuous improvement (CI) activities. Through a review of the literature and active engagement with CI implementations, we identify several issues that may lead to divergence between operational and financial assessments. Out of this conflict emerges a set of concepts that we find important − the delineation of soft versus hard capacity benefits, the distinction between capacity used and capacity paid for, and the data gaps that relate to these benefits – and recognize operational improvement and financial improvement as distinct, yet interrelated, theoretical constructs. This study helps explain a series of persistent gaps in the management accounting literature: Conflict between operations and accounting managers, the divergent perspectives of Johnson and Kaplan after their publication of Relevance Lost (Johnson & Kaplan, 1987), and the need for both operational control (including detailed capacity control) and accounting control in CI firms. Instead of one control system being at odds with the other, or co-existing despite each other, each of these systems support a different component of the financial improvement process. Operational control systems in CI firms emphasize non-financial information and social and behavioral controls that empower decision-making by employees, while accounting control systems seek to motivate and translate operational gains into financial gains. Soft and hard benefits linked to capacity play an integral role in understanding the difference in focus of each control system, while data limitations help to explain why these systems remain loosely coupled in practice (or absent, as seems to be the case with detailed Capacity Management Systems).

Service experiences and waiting lines are often – unfortunately – seen to go hand in hand. This chapter explains why this is the case. Beginning with an exploration of capacity and operating constraints, discussion then delves into both the mathematical origins and psychological implications of waiting lines. The final section offers hope to managers and guests alike, with a survey of different operations strategies and tactics that can eliminate or abate the need to wait.

This study investigates the relationship between lean manufacturing practices, management accounting and performance measurement (MAC & PM) practices, organizational strategy, structure, and culture, and facility performance. We extended past research by examining the relationships between lean manufacturing, MAC & PM practices and performance in a broader organizational context. Our study was performed using survey data provided by managers and executives at 368 facilities that had contacted the Shingo Institute for information or that had entered a Shingo Prize competition. Consistent with past research we found a significant positive association between lean manufacturing practices and lean MAC & PM practices. We found that greater employee empowerment, use of process performance measures, and use of lean accounting practices were driven primarily by lean strategy and secondarily by the extent of lean manufacturing practices. We also found that changes in organization structure to support lean are driven primarily by lean strategy and secondarily by lean manufacturing practices. Change toward lean culture, on the other hand, is driven by the extent of lean manufacturing practices. Further, we found that emphasizing process performance measures does not reduce emphasis on results performance measures and emphasizing results performance measures leads to improved financial performance. Process and results measures are being used in tandem and value stream costing has not replaced traditional accounting. The results of our study provide important insights for managers of companies engaged in lean transformation and for academics who teach or research lean accounting.

Purpose – The adoption of performance measurement and evaluation systems comprising nonfinancial measures has rendered the investigation of behavioral consequences of such measures an increasingly important research issue. The purpose of this study is to investigate the process by which the use of nonfinancial measures affects employees’ perceptions of procedural fairness. It proposes that the effects of nonfinancial measures on procedural fairness are indirect through the mediating variables of (1) job relevant information and (2) role clarity.

Methodology – Data collected from a survey of 276 managers in different functional areas are used to test the models. The data are analyzed using structural equation modeling (Partial Least Square).

Findings – Results from structural models indicate that the use of nonfinancial measures has a positive impact on job relevant information, role clarity, and procedural fairness. In addition, the findings suggest that the use of nonfinancial measures is indirectly related to procedural fairness through job relevant information and role clarity. Specifically, the results indicate that the use of nonfinancial measures affects job relevant information. Job relevant information then influences role clarity. Role clarity, in turn, is positively related to procedural fairness.

Value of paper – This study provides systematic empirical evidence on how the use of nonfinancial measures for performance measurement and evaluation can affect employee perceptions of procedural fairness. It helps organizations to understand how this process occurs and provides them with some assurance that the adoption of nonfinancial measures may be beneficial particularly through the higher information content of such measures and the consequential enhancement of employee role clarity and perception of fairness. By studying the effects of nonfinancial measures, in isolation, this study also helps to demonstrate to organizations that some of the beneficial effects on employee outcomes found by prior management accounting studies involving a combination of financial and nonfinancial measures may be achievable from the use of nonfinancial measures alone without the need of financial measures. This may assist organizations in designing simpler performance measurement systems.

Forecasting is a vital part of hospitality operations because it allows businesses to make imperative decisions, such as pricing, promotions, distribution, scheduling, and arranging facilities, based on the predicted demand and supply. This chapter covers three main concepts related to forecasting: it provides an understanding of hospitality demand and supply, it introduces several forecasting methods for practical application, and it explains yield management as a function of forecasting. In the first section, characteristics of hospitality demand and supply are described and several techniques for managing demand and supply are addressed. In the second section, several forecasting methods for practical application are explored. In the third section, yield management is covered. Additionally, examples of yield management applications from airlines, hotels, and restaurants are presented.

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process planning techniques often minimize setup times. On the contrary, grouping with respect to component geometry and frequency has been proved to further minimize assembly time. Thus, we propose the Placement Location Metric (PLM) algorithm to recognize and measure the similarity between printed circuit board (PCB) patterns. Grouping PCBs based on the geometric and frequency patterns of components in boards will form clusters of locations and, if these clusters are common between boards, similarity among layouts can be recognized. Hence, placement time will decrease if boards are grouped together with respect to the geometric similarity because the machine head will travel less. Given these notions, this study develops a new technique to group PCBs based on the essences of both component commonality and the PLM. The proposed pattern recognition method in conjunction with the Improved Group Setup (IGS) technique can be viewed as an extended enhancement to the existing Group Setup (GS) technique, which groups PCBs solely according to component similarity. Our analysis indicates that the IGS performs relatively well with respect to an array of existing setup management strategies. Experimental results also show that the IGS produces a better makespan than its counterparts over a low range of machine changeover times. These results are especially important to operations that need to manufacture quickly batches of relatively standardized products in moderate to larger volumes or in flexible cell environments. Moreover, the study provides justification to adopt different group management paradigms by electronic suppliers under a variety of processing conditions.

In this chapter, an air cargo shipment planning problem is considered by including individual risk factors of any sub-contracted agents. Due to competitive market conditions, air cargo forwarders are advised to remain flexible in operations. A mixed integer linear programming formulation including the potential for divisible activities is developed to model the shipment planning problem. To solve this complicated problem, we employ an ant colony optimization (ACO) methodology. Numerical examples are generated using data from both the extant literature and from a global air cargo company, allowing investigation of the viability of the novel methodology. We find that the algorithm/methodology provides effective solutions for small problem sizes.

This article provides an overview of the panel vector autoregressive models (VAR) used in macroeconomics and finance to study the dynamic relationships between heterogeneous assets, households, firms, sectors, and countries. We discuss what their distinctive features are, what they are used for, and how they can be derived from economic theory. We also describe how they are estimated and how shock identification is performed. We compare panel VAR models to other approaches used in the literature to estimate dynamic models involving heterogeneous units. Finally, we show how structural time variation can be dealt with.

Lean manufacturing, a philosophy that revolutionized the manufacturing industry, is often linked to the Toyota Production System (TPS). At the core of a lean company, one can observe proper implementation of lean manufacturing tools and practices such as just-in-time, work teams, cellular manufacturing, lean layout, etc. The goal of lean production is to minimize the waste producing activities while offering the same or enhanced quality to customers.

The aim of this research is to investigate the implementation degree of lean manufacturing and its tools and practices focusing on the case of an SME in Albania as a concrete example. Higher attention is given to some of the pillars of lean manufacturing such as just-in-time and cellular manufacturing.

In this case study, researchers observed a variety of features of lean production. Just-in-time was implemented to a certain extent and cellular manufacturing at a more surprising level, which was facilitated especially by the U-shaped facility layout designs observed during the site visits. The value stream mapping showed a proper group technology in place and the management displayed signs of engagement and future advancement desire regarding this philosophy.

We examine the garbage can model as a case of organizational decision making under temporal order constraints such as in the case of a dispatcher on whose desk problems, solutions, and choice opportunities arrive in a stochastic order and get resolved at particular points in time. We follow the original (Cohen, March, & Olsen, 1972) simulation except their particular setup where the problems and decision makers have access to information regarding the decisions made up to the end of the previous period a rule that we consider to be myopic. Making the assignment (or rule) less myopic would be to provide information about problems that were attached in the current period and about decision makers that were assigned a choice this period to problems and to decision makers. We also bring in an expediter who can select one or two choices to expedite each period. The expediter is endowed with a total energy of 55 that can be expended on resolving any choice to decision. Each period after the problems are attached and decision makers assigned to choices, the expediter scans the choices. The expediter selects the two choices that are the closest to decision and expends energy to move them to decision. The simulations we ran show improvement in certain situations as measured by the number of unsolved problems. We discuss our results in the sense of providing simple design features to a complex decision situation. We also discuss the paradigm of the garbage can model in the larger context of organizational decision making.