Pertanika Journal of Science & Technology

TesisEl propósito de este trabajo de investigación fue determinar el grado de relación entre el clima organizacional y la satisfacción laboral en los trabajadores de la Asociación para el Desarrollo Empresarial en Apurímac, Andahuaylas. A fin de proporcionar al directivo de la institución, sugerencias de cambio, reforzamiento y/o de mejora. Para la realización de este estudio se determinó como muestra al total de la población, conformada por 30 trabajadores a quienes se les aplicó un cuestionario estructurado, tipo escala de Likert, para diagnosticar el clima organizacional, compuesto por 21 ítems correspondiente a 5 dimensiones, y para medir la satisfacción laboral, compuesto por 14 ítems correspondiente a 2 dimensiones, validados por tres expertos en la materia. El análisis de fiabilidad de los cuestionarios arroja un coeficiente de Alf a de Cronbach para la escala de clima organizacional y satisfacción laboral de 0.796 y 0.721 respectivamente confiables. La hipótesis principal señalaba que existía relación entre el clima organizacional y satisfacción laboral. La principal conclusión comprobó que hay relación entre las dos variable, es decir, existe relación significativa positiva entre el clima organizacional y satisfacción laboral. A nivel de las hipótesis específicas se comprobó las dimensiones de clima organizacional la estructura, autonomía, relaciones interpersonales, identidad se correlacionaron de forma significante y positiva con la satisfacción laboral. Sin embargo no se encontró relación entre la dimensión recompensa con la satisfacción laboral en la Asociación para el Desarrollo Empresarial el Apurímac

Telecommunication Systems

This book is based on both industrial and academic research efforts in which a number of recent advancements and rare insights into telecommunication systems are well presented. The volume is organized into four parts: "Telecommunication Protocol, Optimization, and Security Frameworks", "Next-Generation Optical Access Technologies", "Convergence of Wireless-Optical Networks" and "Advanced Relay and Antenna Systems for Smart Networks." Chapters within these parts are self-contained and cross-referenced to facilitate further study

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202

Emerging Technologies

This monograph investigates a multitude of emerging technologies including 3D printing, 5G, blockchain, and many more to assess their potential for use to further humanity’s shared goal of sustainable development. Through case studies detailing how these technologies are already being used at companies worldwide, author Sinan Küfeoğlu explores how emerging technologies can be used to enhance progress toward each of the seventeen United Nations Sustainable Development Goals and to guarantee economic growth even in the face of challenges such as climate change. To assemble this book, the author explored the business models of 650 companies in order to demonstrate how innovations can be converted into value to support sustainable development. To ensure practical application, only technologies currently on the market and in use actual companies were investigated. This volume will be of great use to academics, policymakers, innovators at the forefront of green business, and anyone else who is interested in novel and innovative business models and how they could help to achieve the Sustainable Development Goals. This is an open access book

Development of a real-time business intelligence (BI) framework based on hex-elementization of data points for accurate business decision-making

The desire to use business intelligence (BI) to enhance efficiency and effectiveness of business decisions is neither new nor revolutionary. The promise of BI is to provide the ability to capture interrelationship from data and information to guide action towards a business goal. Although BI has been around since the 1960s, businesses still cannot get competitive information in the form they want, when they want and how they want. Business decisions are already full of challenges. The challenges in business decision-making include the use of a vast amount of data, adopting new technologies, and making decisions on a real-time basis. To address these challenges, businesses spend valuable time and resources on data, technologies and business processes. Integration of data in decision-making is crucial for modern businesses. This research aims to propose and validate a framework for organic integration of data into business decision-making. This proposed framework enables efficient business decisions in real-time. The core of this research is to understand and modularise the pre-established set of data points into intelligent and granular “hex-elements” (stated simply, hex-element is a data point with six properties). These intelligent hex-elements build semi-automatic relationships using their six properties between the large volume and high-velocity data points in a dynamic, automated and integrated manner. The proposed business intelligence framework is called “Hex-Elementization” (or “Hex-E” for short). Evolution of technology presents ongoing challenges to BI. These challenges emanate from the challenging nature of the underlying new-age data characterised by large volume, high velocity and wide variety. Efficient and effective analysis of such data depends on the business context and the corresponding technical capabilities of the organisation. Technologies like Big Data, Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning (ML), play a key role in capitalising on the variety, volume and veracity of data. Extricating the “value” from data in its various forms, depth and scale require synchronizing technologies with analytics and business processes. Transforming data into useful and actionable intelligence is the discipline of data scientists. Data scientists and data analysts use sophisticated tools to crunch data into information which, in turn, are converted into intelligence. The transformation of data into information and its final consumption as actionable business intelligence is an end-to-end journey. This end-to-end transformation of data to intelligence is complex, time-consuming and resource-intensive. This research explores approaches to ease the challenges the of end-to-end transformation of data into intelligence. This research presents Hex-E as a simplified and semi-automated framework to integrate, unify, correlate and coalesce data (from diverse sources and disparate formats) into intelligence. Furthermore, this framework aims to unify data from diverse sources and disparate formats to help businesses make accurate and timely decisions