Effective Strategies for Communicating and Managing Communication in a Project Team

Projects are temporary endeavors that require a series of tasks to be completed. A project manager and their team execute these tasks. However, one of the biggest challenges that the project manager and the team will face is how to communicate effectively throughout the project. Communication is one of the most critical factors in a project’s success, as without a proper communication plan and communication management strategies, a project can go downhill quickly. Also, communication is important in a business, but what makes it a crucial factor for projects is that they face deadlines and budget constraints. This paper will look at the communication process and the models that affect project environments, and it will recommend effective strategies for communicating and managing communication within project teams to aid in project success.

Blockchain Technology Concept for Improving Supply Chain Traceability in the Ivory Market

Supply chain traceability is gaining momentum as a means to gain visibility across the supply chain. In order to curb poaching in wildlife sector and harvesting of resources such as ivory, there is need to introduce full proof technologies. This article proposes use of blockchain in tracing the supply chain of ivory and other wildlife products, from source to destination. The article is based on literature review on wildlife practices. Ivory trade participants were identified and mapped into a blockchain model using blockchain modeling techniques. The proposed blockchain approach allows transaction recording as blocks and visibility to relevant participants.

Effective Strategies for Communicating and Managing Communication in a Project Team – My Perspective

Projects are temporary endeavors that require a series of tasks to be completed. A project manager and their team execute these tasks. However, one of the biggest challenges that the project manager and the team will face is how to communicate effectively throughout the project. Communication is one of the most critical factors in a project’s success, as without a proper communication plan and communication management strategies, a project can go downhill quickly. Also, communication is important in a business, but what makes it a crucial factor for projects is that they face deadlines and budget constraints. This paper will look at the communication process and the models that affect project environments, and it will recommend effective strategies for communicating and managing communication within project teams to aid in project success.

Multiple Criteria DEA-Based Ranking Approach With the Transformation of Decision-Making Units

Though various ranking methods in the data envelopment analysis (DEA) context have emerged since the conventional DEA was introduced, none of them has not been accepted as a universal or a superior method for ranking decision-making units (DMUs). The DEA-based ranking methods show some shortcomings as the numbers of inputs and outputs for DMUs increase. To overcome such shortcomings, this paper proposes a two-step procedure of ranking DMUs more effectively and consistently. In the first step, the multi-objective programming (MOP) is applied for the multiple criteria DEA to transform the original DMUs into the new simpler DMUs with two inputs and a single output, regardless of the numbers of inputs and outputs that the original DMUs use and produce. With the transformed DMUs, some conventional DEA based-methods for ranking DMUs are applied in the second step. A numerical example demonstrates the efficient performance of the proposed method.

How Statistical Analysis Tools can be Used to Effectively Plan and Execute a Strategic Plan for an Organization

However, pre-existing literature does not show how these variables, their concepts, and models help in strategic planning, which has resulted in a research gap. Thus, this study addresses the most current variables, their concepts, and models within operations and project management. With a design-science-investigate strategy, we approve a valuable growth reveal for reasonable and hypothetical application. Thus, we create a suitable assessment model to fill the research void, as well as to contribute to the engineering field by improving the project success rates and helping with team communication.

How Statistical Analysis Tools Can Be Used to Effectively Plan and Execute a Strategic Plan for an Organization

However, pre-existing literature does not show how these variables, their concepts, and models help in strategic planning, which has resulted in a research gap. Thus, this study addresses the most current variables, their concepts, and models within operations and project management. With a design-science-investigate strategy, we approve a valuable growth reveal for reasonable and hypothetical application. Thus, we create a suitable assessment model to fill the research void, as well as to contribute to the engineering field by improving the project success rates and helping with team communication.

Multiple Criteria DEA-Based Ranking Approach With the Transformation of Decision-Making Units

Though various ranking methods in the data envelopment analysis (DEA) context have emerged since the conventional DEA was introduced, none of them has not been accepted as a universal or a superior method for ranking decision-making units (DMUs). The DEA-based ranking methods show some shortcomings as the numbers of inputs and outputs for DMUs increase. To overcome such shortcomings, this paper proposes a two-step procedure of ranking DMUs more effectively and consistently. In the first step, the multi-objective programming (MOP) is applied for the multiple criteria DEA to transform the original DMUs into the new simpler DMUs with two inputs and a single output, regardless of the numbers of inputs and outputs that the original DMUs use and produce. With the transformed DMUs, some conventional DEA based-methods for ranking DMUs are applied in the second step. A numerical example demonstrates the efficient performance of the proposed method.

Muscle Fatigue Analysis During Welding Tasks Using sEMG and Recurrence Quantification Analysis

The main goal of this study was to detect muscle fatigue and to identify muscles vulnerable to musculoskeletal disorders by evaluating muscle activation of subjects during welding tasks. In this study, six subjects performed two different welding tasks for a total of three hours. Surface electromyography (sEMG) was used to record the muscle activation of sixteen different muscles. Recurrence Quantification Analysis (RQA) was then used to analyze the EMG data. In addition, a subjective fatigue assessment was conducted to draw comparisons with the RQA results. According to the RQA results, twelve of the tested muscles experienced fatigue by showing significant difference in RQA values (p-value < 0.05) between the first and last 10 minutes of the experiment. Moreover, time-to-fatigue results obtained from RQA and subjective analysis were closely correlated for seven muscle groups. This study showed that RQA can be used in ergonomic studies for evaluating muscle activation during construction tasks.

An Analysis for the Use of Simulation Modeling in Reducing Patient Waiting Time in Emergency Departments (EDs) in Hospitals

The emergency department (ED) plays crucial role in providing 24-hour healthcare services to the ill with speed, accuracy, and sympathy. ED faces the problem of patient waiting time, which leads to patient dissatisfaction and patient crowding. This paper presents a systematic literature review of simulation of ED in healthcare systems from 1970 to 2013. The objectives of this review are to highlight the importance and role of simulation studies to solve the problem of patient waiting time faced by the ED. It also discusses how simulation can be better applied as a tool to solve these problems. The authors found that these simulation studies focus important insights into ED problems, but they also had some limitations that should be addressed.

Application of Multiple Regression and Artificial Neural Networks as Tools for Estimating Duration and Life Cycle Cost of Projects

Project managers face complex challenges when planning project stages because contract durations and project costs are difficult to predict accurately. The purpose of this study is to investigate statistical tools and concepts that can be integrated in the second phase of the project life cycle: the planning stage. Furthermore, this study aims to compare the accuracy of multiple regression and artificial neural network models, as well as the application of simulation in construction models used in predicting project duration and cost. This paper will also discuss the industry's current estimation methods, the use of statistical approaches, simulation, and the relationship between the application statistical tools and project success. Thus, this review identifies the trending statistical tools used by scholars to develop regression and neural models to solve the complexity of cost and duration estimation. The findings indicate that although the industry needs more accurate predictions and estimating tools, and regardless of the investigations and advancements made with integrating statistical tools, implementing these statistical approaches is faced with barriers.