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In order to meet the requirements of 6σ management and to overcome the deficiencies of the theory for using the pre-control chart to evaluate and monitor quality stability, the purpose of this paper is to probe into the quality stability evaluation and monitoring guidelines of small batch production process based on the pre-control chart under the conditions of the distribution center and specifications center non-coincidence (0<ɛ≤1.5σ), the process capability index C _p ≥2 and the virtual alarm probability α=0.27 percent.

First, the range of the quality stability evaluation sampling number in initial production process is determined by using probability and statistics methods, the sample size for the quality stability evaluation is adjusted and determined in initial production process according to the error judgment probability theory, and the guideline for quality stability evaluation has been proposed in initial production process based on the theory of small probability events. Second, the alternative guidelines for quality stability monitoring and control in formal production process are proposed by using combination theory, the alternative guidelines are initially selected based on the theory of small probability events, a comparative analysis of the guidelines is made according to the average run lengths values, and the monitoring and control guidelines for quality stability are determined in formal production process.

The results obtained from research indicate that when the virtual alarm probability α=0.27 percent, the shifts ɛ in the range 0<ɛ≤1.5σ and the process capability index C _p ≥2, the quality stability evaluation sample size of the initial production process is 11, whose scondition is that the number of the samples falling into the yellow zone is 1 at maximum. The quality stability evaluation sample size of the formal production process is 5, and when the number of the samples falling into the yellow zone is ≤1, the process is stable, while when two of the five samples falling into the yellow, then one more sample needs to be added, and only if this sample falls into the green zone, the process is stable.

Research results can overcome the unsatisfactory 6σ management assumptions and requirements and the oversize virtual alarm probability α of the past pre-control charts, as well as the shortage only adaptable to the pre-control chart when the shifts ɛ=0. And at the same time, the difficult problem hard to adopt the conventional control charts to carry out process control because of a fewer sample sizes is solved.

This chapter describes an institutional choice that most Latin American countries have taken in the past 25 years: the creation of national Public Performance Monitoring and Evaluation (PPME) systems. We summarize research assessing their institutionalization, identify their shortcomings, and discuss trends demonstrating a potential – not yet realized – to fulfill their vocation as instruments of political and democratic accountability. Despite remarkable progress in their institutionalization, the evidence suggests that the systems fall short in producing strong results-oriented democratic accountability. Key factors hindering this aspiration include the systems' low credibility, problems associated to their diversification, low institutional coherence, and lack of effective coordination mechanisms to improve information legibility, its quality, its usefulness, and thus its use by both public managers and citizens. We suggest that PPME systems depend on environmental conditions beyond government structures and processes and argue that citizen-oriented mechanisms and entry points for social participation around the systems are required to fulfill their accountability function.

We present a model of organizational monitoring that integrates organizational justice and information privacy. Specifically, we adopt the position that the formation of invasiveness and unfairness attitudes is a goal-driven process. We employ cybernetic control theory and identity theory to describe how monitoring systems affect one's ability to maintain a positive self-concept. Monitoring provides a particularly powerful cue that directs attention to self-awareness. People draw on fairness and privacy relevant cues inherent in monitoring systems and embedded in monitoring environments (e.g., justice climate) to evaluate their identities. Discrepancies between actual and desired personal and social identities create distress, motivating employees to engage in behavioral self-regulation to counteract potentially threatening monitoring systems. Organizational threats to personal identity goals lead to increased invasiveness attitudes and a commitment to protect and enhance the self. Threats to social identity lead to increased unfairness attitudes and lowered commitment to one's organization. Implications for theory and research on monitoring, justice, and privacy are discussed along with practical implications.

Employee evaluation and monitoring have been common in America since colonial times. With industrialization, employers have implemented increasingly creative ways to monitor employees. For example, in the early part of this century, Ford Motor Company employed investigators to enter employees' homes to verify that employees were not overly drinking and that their homes were clean

This study aims to analyze the outcome features of effective monitoring and evaluation in construction projects delivery.

The study adopted a quantitative research approach. Questionnaire survey was administered to 230 participants who were drawn from metropolitan, municipal, district assemblies and regional coordinating councils in Ghana. Data collected were analyzed to determine the key and underlying monitoring and evaluation outcome features in project delivery. A Cronbach’s α value of 0.953 was achieved based on standardized items, while the Kaiser–Meyer–Olkin measure of sampling adequacy recorded was 0.876. The result of Bartlett’s test of sphericity also revealed a significance level of 0.000 (p < 0.05).

The study discovered that value for money, successful project closure, end-user satisfaction, timely completion of projects and fitness for purpose were the top five monitoring and evaluation outcome features. Similarly, three principal monitoring and evaluation outcome features were identified, namely, performance, satisfaction and value outcome.

The study, thus, seeks to guide project planning and implementation of effective construction project M&E.

The study contributes to the body of knowledge by establishing top and key success outcomes (KSO) in the implementation of monitoring and evaluation.

The TARGET approach aims at establishing a reflexive gender equality policy in research performing and research funding organisations. Monitoring has enormous potential to support reflexivity at both the institutional and the individual levels in the gender equality plan (GEP) development and implementation context. To exploit this potential, the monitoring system has to consist of meaningful indicators, which adequately represent the complex construct of gender equality and refer to the concrete objectives and policies of the GEP. To achieve this, we propose an approach to indicator development that refers to a theory of change for the GEP and its policies. Indicator development thus becomes a reflexive endeavour and monitoring a living tool. This requires constant reflection on data gaps, validity of indicators and the further development of indicators. Furthermore, we recommend the creation of space for reflexivity to discuss monitoring results with the community of practice.

Within the last decade many projects have been implemented in order to provide technical assistance (TA) to countries, which have initiated their transition from centrally planned to market economies (mainly countries of Central and Eastern Europe being previously under the Soviet regime). The monitoring and evaluation exercise aims at assisting these TA projects in achieving their objectives, by providing management information on the projects’ implementation, so that structured management decisions can be taken, if and when needed. In this framework, the necessity for creation of an overall M&E database system emerged. The IMES was developed for the needs of the European commission (DGLA) and its main objective was to improve the Management Reporting on Tacis progress and results, by extracting relevant information on projects’ performance from the monitoring and evaluation reports and by producing overall statistics at NIS (New Independent States) level.

This paper aims to examine the role of project monitoring and evaluation (M&E) in international development (ID) project stakeholders' relationships. This study draws on agency theory to examine the specific role M&E plays in improving ID project impact.

Qualitative data comprising of in-depth interviews were collected from ID project stakeholders such as project donors, implementing partners and steering committee members.

Results of the study show that project M&E activities can serve multiple purposes including the collection of data for the assessment of inputs, outputs, outcomes and impact. This information is shared with stakeholders to assist in evidence-based decision-making to improve project impact on community. This study shows that M&E activities strengthen the relationship between stakeholders by involving multiple stakeholders at different stages of ID projects to identify community needs and to demonstrate the positive community impact. Agency issues such as goal incongruence, information asymmetry and risk-sharing affect the relationship between the stakeholders. Investing in different M&E activities can reduce these issues, ultimately leading to a positive impact at the community level.

There has been limited research that explores the principal-agent relationship between project stakeholders of ID projects through the lens of agency theory. The role of M&E to collect project data and address agency issues between project stakeholders to improve project impact is the novel contribution of this paper.

Increased investments in employee further training have resulted in a growing interest in ensuring and improving the quality of these measures. However, little is known about the operational decision to initiate an evaluation of further training. Therefore, the purpose of this paper is to investigate under which circumstances firms decide to evaluate training measures.

The study analyzes the evaluation decision of firms and external suppliers, and differentiates between internal and external further trainings. Theoretically, two goals of evaluations – monitoring and feedback – and their relevance for the decision makers are considered. Using a unique linked employer–employee data set, the study employs multi-level models to analyze three influencing factors on the evaluation decision: characteristics of the further training measure itself, the employees and the employers.

The results show that evaluation decisions are not based on general organizational practices but on case-by-case cost-benefit considerations. Interestingly, firms are more likely to evaluate internal further training measures than external ones. Therefore, evaluations seem to be more frequently used as a feedback instrument than for the purpose of monitoring. For external further training measures, firms seem to trust market mechanisms as a monitoring instrument, instead of conducting an internal evaluation.

Although further training has become increasingly important, little is known about firms’ quality management in this respect. This paper provides a theoretical framework for the usage of evaluation procedures and analyzes firms’ strategies for ensuring quality based on a large set of variables to give new insight into the organizational decision-making processes.

The purpose of this paper is to develop a conceptual framework of integrated supply chain model that can be used to measure, evaluate and monitor operational performance under dynamic and uncertain conditions.

The research methodology consists of two stages: configuration of a conceptual framework of integrated supply chain model linked with performance measures and illustration of the integrated supply chain model and delivery performance using a case of dairy industry. The integrated supply chain model is based on a unitary structuring technique and forms the basis for measuring and evaluating supply chain performance. Delivery performance with variation of demand (forecast and actual) is monitored using a fuzzy-based decision support system, based on three inputs: capacity utilization (influenced by production disruption), raw materials shortage and quality of dairy products.

Integration of supply chain components (materials, resources, operations, activities, suppliers, etc.) of key processes using unitary structuring approach enables information integration in real time for performance evaluation and monitoring in complex supply chain situations. In addition, real-time performance monitoring is recognized as being of great importance for supply chain management in responding to uncertainties inherent in the operational environment.

Implementation of an integrated model requires maintenance of supply chain components with all necessary data and information in a system environment such as enterprise resource planning.

The integrated model provides decision-makers with an overall view of supply chain components and direct links that need to be maintained for supply chain performance evaluation and monitoring. Wider adaptation and diffusion of the proposed model require further validation of the model and feasibility of implementation, using real-time data and information on selected performance measures.

Integration of supply chain components across supply chain processes directly linked with performance measures is a novel approach for effective supply chain performance evaluation and monitoring in complex supply chains under dynamic and uncertain conditions.