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Missing data are a pervasive problem in special education research. The purpose of this chapter is to provide researchers with an overview of two “modern” alternatives for handling missing data, full information maximum likelihood (FIML) and multiple imputation (MI). These techniques are currently considered to be the methodological “state of the art”, and generally provide more accurate parameter estimates than the traditional methods that are still common in published educational studies. The chapter begins with an overview of missing data theory, and provides brief descriptions of some traditional missing data techniques and their requisite assumptions. Detailed descriptions of FIML and MI are given, and the chapter concludes with an analytic example from a longitudinal study of depression.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

This paper proposes an evaluation model for prefabricated construction to guide a supply chain with controllable costs. Prefabricated construction is prevalent due to area limitations. Nevertheless, the development is limited by budget control and identifying the factors affecting cost. The degree of close collaboration in the supply chain is closely interconnected with cost performance that includes direct and indirect factors. This paper not only quantizes these factors but also distinguishes the degree of influence of various factors.

System dynamics is applied to simulate and analyze the construction cost factors through Vensim software. It can also clarify the relationship between cost and other influencing factors. The input data are collected from an Internet of Things (IoT)-enabled system under a Building Information Modeling (BIM) system and Hong Kong government reports.

Simulation results indicate that prefabricated construction cost is mainly influenced by government promotion degree (GPD), working pressure from on-site construction (WPOSC), prefab quality (PQ), load-bearing capacity per vehicle (LBPV) and mold quality (MQ). However, it is more sensitive toward GPD, which indicates that the government should take measures to promote this construction technology. On-site worker management is also essential for the assembly process and indirectly influences the construction cost.

This paper quantifies indirect influential factors to clarify the specific features for prefabricated construction. The investigated factors are limited.

The contractor can identify all factors and classify the levels of influence to make decisions under the supply chain system boundary.

The input data are collected from an IoT-enabled system under a BIM system and Hong Kong government reports. Thus, the relationship between construction cost influential factors can be investigated.

This paper quantifies indirect influencing factors and clarifies the specific features in prefabricated construction. The contractor could identify these factors to make decisions and classify the levels of influence under the supply chain system boundary.

This paper aims to investigate the distributed formation control problem for a multi-quadrotor unmanned aerial vehicle system without linear velocity feedbacks.

A nonlinear controller is proposed based on the orthogonal group SE(3) to obviate singularities and ambiguities of the traditional parameterized attitude representations. A cascade structure is applied in the distributed controller design. The inner loop is responsible for attitude control, and the outer loop is responsible for translational dynamics. To ensure a linear-velocity-free characteristic, some auxiliary variables are introduced to construct virtual signals in distributed controller design. The stability analysis of the proposed distributed control method by the Lyapunov function is provided as well.

A group of four quadrotors with constant reference linear velocity and a group of six quadrotors with varying reference linear velocity are adopted to verify the effectiveness of the proposed strategy.

This is a new innovation for multi-robot formation control method to improve assembly automation.

This paper proposes a class of estimators for population correlation coefficient when information about the population mean and population variance of one of the variables is not available but information about these parameters of another variable (auxiliary) is available, in two phase sampling and analyzes its properties. Optimum estimator in the class is identified with its variance formula. The estimators of the class involve unknown constants whose optimum values depend on unknown population parameters. In earlier research it has been shown that when these population parameters are replaced by their consistent estimates the resulting class of estimators has the same asymptotic variance as that of optimum estimator. An empirical study is carried out to demonstrate the performance of the constructed estimators.

For the survival and growth of an organization, it is important to understand the transition phases of different market scenarios. During the transition from one market scenario to another, effective strategic planning is needed to manage the performance of the organizations. The paper models different market scenarios leading to excellent and poor performance of the organizations. Policy experimentations have been conducted using system dynamics methodology. The results indicate that there is no quick fix to achieve the TQM maturity level. To sustain TQM maturity level, it is extremely important to handle the transition phases of different market scenarios effectively.

The production of sleeve grouting in prefabricated construction is routinely plagued by a variety of factors, and lack of mass data and complex environmental conditions over time make problems inevitable. Thus, a dynamic risk control system is a valuable support for the successful completion of the sleeve grouting process. This study aims to develop an entropy-based sleeve grouting risk dynamic control system.

First, static risk assessment was conducted through the structured interview survey using the entropy weight method, followed by a dynamic risk control technique, where indicators were simulated through system dynamics containing causal loop diagrams and stock-and-flow diagrams.

Finally, three types of risk control models, namely, “tortuous type”, “stable type” and “peak loop type”, were developed in the entropy-based sleeve grouting risk dynamic control system and simulated using system dynamics in a real case.

Compared to traditional sleeve grouting risk management, the developed system enabled dynamic control over time.

This paper aims to propose a system dynamics model of blockchain online community knowledge sharing, with the following goals: to reveal the internal mechanism of blockchain technology on community knowledge sharing; to show the impact of blockchain technology on knowledge sharing; and to promote knowledge sharing and the self-development of blockchain online communities.

Based on the core characteristic factors of blockchain technology, including incentive mechanism, trust mechanism, information protection mechanism, etc., a knowledge sharing analysis framework is established. Through the use of the Vensim PLE (Personal Learning Version) software, according to the steps of “putting forward a dynamic hypothesis”, “establishing a system dynamic equations”, and then “model testing” and “simulation”, the article analyzes in depth the process and extent of the impact of the above features on online community knowledge sharing.

The results show that the blockchain incentive mechanism, trust mechanism and information protection mechanism all contribute to promoting an increase in the number of community knowledge sharing users, as well as in the total amount of knowledge shared. The results also show that the token reward in the incentive mechanism has in fact a higher degree of influence than the trust and information protection mechanisms.

At present, no research on the internal mechanism of knowledge sharing in blockchain online communities has been carried out. This article plays a complementary role in research in this field, and offers significant guidance for promoting online community knowledge management and online community development.