The book addresses the complex issue of quality uncertainty due to information asymmetry in the backdrop of information economics, total quality management and marketing science. Reliability Engineering, Seven Management Tools and System Dynamics are used to develop theories on quality uncertainty and perception. Quality perception is identified as a multidisciplinary measure of business performance. The tools are developed to minimize quality uncertainty or to maximize quality perception. A few worksheets are provided for applying these theories to improve business performance.

Zusammenfassung
It has been observed that the studies of quality are pursued in various disciplines like economics, quality management, and marketing science, and are seen isolated. The treatments imparted to these studies are also different and has the backdrop of discipline in which the work has been pursued. The nature of isolation is equally seen when quality uncertainty and perceived quality were pursued separately without showing any inkling that these can be complimentary. Economist and Nobel Laureate, Akerlof (1970), wrote a seminal piece The market for lemons: quality uncertainty and market mechanism, where he described quality uncertainty due to information asymmetry. It refers to the fact that a party in a transaction may have more information than the other. This is information asymmetry. If the seller has more information than the buyer about the product quality, he/she may sell it, as if it is a high-quality product. In reality, it could be a low-quality product. The buyer does not have the information regarding the quality of the offered product. The market condition that led to this transaction is quality uncertainty due to information asymmetry.

Inhalt
1 Introduction 1.1 Recent metrics for business performance 1.2 Quality pursued in various disciplines 1.3 Quality commonality and multidisciplinary approach 1.4 Management of quality uncertainty and perception 2 Quality uncertainty due to information asymmetry 2.1 Prelude to quality uncertainty 2.2 Information asymmetry and quality uncertainty 2.3 Examples of information asymmetry and quality uncertainty 2.4 Implications of asymmetric information 2.5 Product manufacturing and quality uncertainty 2.6 Causes of quality uncertainty due to information asymmetry 3 Perceived quality through time 3.1 Emergence of perceived quality 3.2 Factors of perceived quality 3.3 SERVQUAL as a metric of perceived quality 3.4 Marketing science approach to product-quality perception 3.5 Expected quality approach from information economics 3.6 Critical appraisal of existing approaches 3.7 Need of a robust approach 4 Quality uncertainty and quality perception 4.1 Theoretical background of probability and reliability engineering 4.2 System reliability 4.3 Success tree and failure tree method 4.4 Paradigm for mathematical modelling 4.5 Behaviour of asymmetry and quality uncertainty 4.6 Fault tree or success tree analysis 4.7 Market with multiple players 4.8 Computation of quality uncertainty and perception 4.9 Product life cycle and information asymmetry 4.10 Managerial implications and strategies Appendix A Worksheets 1 and 2 5 Root cause and failure analysis of quality uncertainty 5.1 Theoretical background of seven management tools 5.2 Cause-and-Effect methodology 5.3 An illustrative case of ball bearing 5.4 Root-cause analysis of quality uncertainty 5.5 Innovative method of failure analysis 5.6 Generic solutions 5.7 Contributions to the theory of quality uncertainty 5.8 Managerial implications of the root-cause method Appendix B Worksheets 3 and 4 6 Dynamics of quality perception 6.1 System dynamics methodology 6.2 Causal loop mapping of quality perception 6.3 Preliminary model, variables, data and analysis 6.4 Towards market dynamics 6.5 Quality perception and market dynamics 6.6 Observations from simulation runs 6.7 Evolving hierarchy of policies for quality management 6.8 Managerial implications Appendix C Worksheets 5 and 6 7 Future directions of quality perception References Index