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The quality level setting problem determines the optimal process mean, standard deviation and specification limits of product/process characteristic to minimize the expected total cost associated with products. Traditionally, it is assumed that the product/process characteristic is normally distributed. However, this may not be true. This paper aims to explore the quality level setting problem when the probability distribution of the process characteristic deviates from normality.

Burr developed a density function that can represent a wide range of normal and non-normal distributions. This can be applied to investigate the effect of non-normality on the studies of statistical quality control, for example, designs of control charts and sampling plans. The quality level setting problem is examined by introducing Burr’s density function as the underlying probability distribution of product/process characteristic such that the effect of non-normality to the determination of optimal process mean, standard deviation and specification limits of product/process characteristic can be studied. The expected total cost associated with products includes the quality loss of conforming products, the rework cost of non-conforming products and the scrap cost of non-conforming products.

Numerical results show that the expected total cost associated with products is significantly influenced by the parameter of Burr’s density function, the target value of product/process characteristic, quality loss coefficient, unit rework cost and unit scrap cost.

The major assumption of the proposed model is that the lower specification limit must be positive for practical applications, which definitely affects the space of feasible solution for the different combinations of process mean and standard deviation.

The proposed model can provide industry/business application for promoting the product/service quality assurance for the customer.

The authors adopt the Burr distribution to determine the optimum process mean, standard deviation and specification limits under non-normality. To the best of their knowledge, this is a new method for determining the optimum process and product policy, and it can be widely applied.

Continuous Sampling Plans (CSP) are used where processes are continuous and products are not grouped into lots. The principal design criterion for these plans is the Average Outgoing Quality Limit (AOQL), which is the worst outgoing quality over all possible values of the incoming quality level. These are generally applicable to in‐process and final inspections and have been found to be most effective when administered in such a way as to provide an incentive to clear up the faults promptly. In applying the traditional continuous sampling plans, it is necessary to revert to 100 per cent inspection when the quality deteriorates. Therefore, the inspection rate must be larger than production rate and the unit inspection cost must be low. The plan presented in this article relaxes the 100 per cent inspection restriction while reaching the same AOQL quality assurance as traditional CSP‐1. The Markov chain process and numerical analysis will be used to formulate the plan. Its results are then evaluated against CSP‐2.

Purpose: In reality, financial decisions are made under conditions of asymmetric information that results in either favorable or adverse selection. As far as financial decisions affect growth of the firm, the latter must also be affected by either favorable or adverse selection. Therefore, the core objective of this chapter is to examine the determinants of each financial decision and the effects on growth of the firm under conditions of information asymmetry.

Design/Methodology/Approach: This chapter uses data for the non-financial firms listed in S&P 500. The data cover quarterly periods from 1989 to 2014. The statistical tests include linearity, fixed, and random effects and normality. The generalized method of moments estimation method is employed in order to examine the relative significance and contribution of each financial decision on growth of the firm, respectively. Standard and proposed proxies of information asymmetry are discussed.

Findings: The results conclude that there is a variation in the impact of financial variables on growth of the firm at high and low levels of information asymmetry especially regarding investment and financing decisions. A similar picture emerges in the cases of firm size and industry effects. In addition, corporate dividen d policy has a similar effect on firm growth across all asymmetric levels. These findings prove that information asymmetry plays a vital role in the relationship between corporate financial decisions and growth of the firm. Finally, the results contribute to the vast literature on the estimation of information asymmetry by demonstrating that the classical and standard proxies for information asymmetry are not consistent in terms of the ability to differentiate between favorable or adverse selection (which corresponds to low and high level of information asymmetry).

Originality/Value: This chapter contributes to the related literature in two ways. First, this chapter offers updated empirical evidence on the way that financing, investment, and dividends decisions are made under conditions of favorable and adverse selection. Other related studies deal with each decision separately. Second, the study offers new proxies for measuring information asymmetry in order to reach robust estimates of the effects of financial decisions on growth of the firm under conditions of agency problems.

Considers that the problem of determining the Dodge‐Romig lot tolerance per cent defective (LTPD) double sampling plan (DSP) under the fuzzy environment satisfies the consumer’s risk closely and is an extension of Chakraborty’s work. Models the problem as fuzzy mathematical programming (FMP). A linear membership function and the minimum operator are assumed in FMP. The solution of the proposed model has a smaller average total inspection (ATI) than those of the traditional Dodge‐Romig LTPD DSP and Chakraborty’s.

Considers the problem of determining economic statistical np‐control chart designs under the fuzzy environment of closely satisfying type I and II errors. Goes on to model the problem as fuzzy mathematical programming, and uses a heuristic method to obtaining the solution.

This paper aims to show how implementing new information technology has expanded the role of librarians as educators and how this role has matched the evolution of new technology.

The paper looks at librarians' approaches to their role as educators and explores ways of most effectively implementing changes. By reviewing the literature and taking the old discourse around library education and information literacy, the paper reflects on the changing role of librarians in an era of greater access to technology, including Web 2.0.

Collaboration with faculty was found to be an essential feature of the most successful stories. Teaching students and faculty to use new information technologies may have become one of the major roles of librarians.

This paper demonstrates that the continual evolution of the web is causing a move from e‐libraries to mobile libraries, and that the educational role of the librarians must encompass this trend, and to anticipate similar future developments.

The Taguchi method is the conventional approach used in off‐line quality control. However, most previous Taguchi method applications have dealt only with a single‐response problem. The multi‐response problem has received only limited attention. Proposes an effective procedure on the basis of the quality loss of each response so as to achieve the optimization on multi‐response problems in the Taguchi method. The procedure is a universal approach which can simultaneously deal with continuous and discrete data. Evaluates a plasma‐enhanced chemical vapour deposition (PECVD) process experiment and a case study, indicating that the proposed procedure yields a satisfactory result.

This paper aims to examine and validate the effect of knowledge management systems (KMS) on innovation.

Survey data from 392 employees working in private and public organizations in the state of Kuwait were collected and used to test the proposed research model and hypotheses through structural equation modeling.

This study finds that system quality, information quality and service quality of KMS have a positive effect on perceived usefulness and perceived ease of use of the system, and in turn, they have a positive effect on actual use of KMS which leads to net benefit represented in an increased innovation for employees who use the KMS. Employees (users of the system) indicated that the use of the system helped them to improve their work, come up with new ways to conduct work, discover new solutions to solve problems, accomplish more complex tasks in less time and communicate in a better way with other employees.

The findings of this study analyzed the elements of KMS that influence innovation in public and private organizations at the individual level. This should be helpful for the designers of KMS to focus on those success factor elements when building KMS, which should make it easy for individuals to acquire knowledge, use it, share it and thus become more innovative and successful in the work they do and the decisions they make. The study also shows a positive relationship between usefulness, ease of use and attitude toward using KMS. Developers of KMS should also take these guidelines in consideration when designing a responsive KMS.

Both knowledge and innovation are considered as crucial sources for sustaining the competitive advantage for organizations. However, despite this, knowledge management (KM) and innovation have established themselves as separate fields and distinct areas of research. However, although KM has a strong relationship with innovation, it is unclear if the research literature in these two fields converge. There is a lack of research studies that deal with interrelation of KM and innovation in organizations. This study is among the first to attempt to fill this gap by empirically investigating the effect of KMS on innovation in both private and public organizations in the state of Kuwait.