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This chapter covers total quality management (TQM) with respect to the Lean and Six Sigma methods used to improve the effectiveness and efficiency of hospitality operations. In the first section, TQM is discussed. In the second section, Lean and Six Sigma techniques are examined individually. Then, Lean and Six Sigma are connected with an example of a housekeeping case study that applies both methodologies. In the third section, business analytics are explored and statistical process control analysis is demonstrated using a hotel room cleanliness example. The fourth section summarizes the concepts of change management, which is critical for embracing the philosophies of TQM. Finally, project management is discussed in the fifth and last section.

Control charts are designed to be effective in detecting a shift in the distribution of a process. Typically, these charts assume that the data for these processes follow an approximately normal distribution or some known distribution. However, if a data-generating process has a large proportion of zeros, that is, the data is intermittent, then traditional control charts may not adequately monitor these processes. The purpose of this study is to examine proposed control chart methods designed for monitoring a process with intermittent data to determine if they have a sufficiently small percentage of false out-of-control signals. Forecasting techniques for slow-moving/intermittent product demand have been extensively explored as intermittent data is common to operational management applications (Syntetos & Boylan, 2001, 2005, 2011; Willemain, Smart, & Schwarz, 2004). Extensions and modifications of traditional forecasting models have been proposed to model intermittent or slow-moving demand, including the associated trends, correlated demand, seasonality and other characteristics (Altay, Litteral, & Rudisill, 2012). Croston’s (1972) method and its adaptations have been among the principal procedures used in these applications. This paper proposes adapting Croston’s methodology to design control charts, similar to Exponentially Weighted Moving Average (EWMA) control charts, to be effective in monitoring processes with intermittent data. A simulation study is conducted to assess the performance of these proposed control charts by evaluating their Average Run Lengths (ARLs), or equivalently, their percent of false positive signals.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

In the almost twenty years since Vasarhelyi and Halper (1991) reported on their pioneering implementation of what has come to be known as Continuous Auditing (CA), the concept has increasingly moved from theory into practice. A 2006 survey by PricewaterhouseCoopers shows that half of all responding firms use some sort of CA techniques, and the majority of the rest plan to do so in the near future. CA not only has an increasing impact on auditing practice, but is also one of the rare instances in which such a significant change was led by the researchers. In this paper we survey the state of CA after two decades of research into continuous auditing theory and practice, and draw out the lessons learned by us in recent pilot CA projects at two major firms, to examine where this unique partnership between academics and auditors will take CA in the future.

High-involvement work processes (HIWPs) are associated with high levels of employee influence over the work process, such as high levels of control over how to handle individual job tasks or a high level of involvement at team or workplace level in designing work procedures. When implementations of HIWPs are accompanied by companion investments in human capital – for example, in better information and training, higher pay and stronger employee voice – it is appropriate to talk not only of HIWPs but of “high-involvement work systems” (HIWSs). This chapter reviews the theory and practice of HIWPs and HIWSs. Across a range of academic perspectives and societies, it has regularly been argued that steps to enhance employee involvement in decision-making create better opportunities to perform, better utilization of skill and human potential, and better employee motivation, leading, in turn, to various improvements in organizational and employee outcomes.

However, there are also costs to increased employee involvement and the authors review the important economic and sociopolitical contingencies that help to explain the incidence or distribution of HIWPs and HIWSs. The authors also review the research on the outcomes of higher employee involvement for firms and workers, discuss the quality of the research methods used, and consider the tensions with which the model is associated. This chapter concludes with an outline of the research agenda, envisaging an ongoing role for both quantitative and qualitative studies. Without ignoring the difficulties involved, the authors argue, from the societal perspective, that the high-involvement pathway should be considered one of the most important vectors available to improve the quality of work and employee well-being.

Healthcare-associated infections (HAIs) are a major cause of concern because of the high levels of associated morbidity, mortality, and cost. In addition, children and intensive care unit (ICU) patients are more vulnerable to these infections due to low levels of immunity. Various medical interventions and statistical process control techniques have been suggested to counter the spread of these infections and aid early detection of an infection outbreak. Methods such as hand hygiene help in the prevention of HAIs and are well-documented in the literature. This chapter demonstrates the utilization of a systems methodology to model and validate factors that contribute to the risk of HAIs in a pediatric ICU. It proposes an approach that has three unique aspects: it studies the problem of HAIs as a whole by focusing on several HAIs instead of a single type, it projects the effects of interventions onto the general patient population using the system-level model, and it studies both medical and behavioral interventions and compares their effectiveness. This methodology uses a systems modeling framework that includes simulation, risk analysis, and statistical techniques for studying interventions to reduce the transmission likelihood of HAIs.

Simons (1995b) suggests that most writing on empowerment often fails to recognize that empowerment requires greater control. Accordingly, we investigate the type of control via rewards and punishment systems, which fits best in the context of empowered work teams. Specifically, we hypothesized that empowerment will lead to improvement in manufacturing performance only when rewards are based on group performance, i.e. a situation where the collective benefit of both individual team members and those of the firm are maximized. Utilizing a survey methodology, four compensation types were examined, including fixed pay, fixed+non-monetary incentives, individual-based incentives, and group-based incentives. Results show that the favorable effect of work team empowerment was not observed under fixed-pay, fixed+non-monetary incentives, or individual-based incentives. In many instances, fixed-pay or individual-based incentives interact with work team empowerment to produce a negative effect on manufacturing cost, manufacturing lead time, or non-value-added-activities. On the other hand, manufacturing plants which use group-based incentives were able to reap the benefit of work team empowerment and translate that into enhanced performance.