Antecedents dari Brand Equity pada Hotel Santika di Bsd Tangerang

This study refers to previous studies, by kevin kam Fung So and Ceridwyn King (2009). The background of this research was to prove the management approaches that brand equity as the key assets for hotel industries and provide brand manger hotel to evaluate brand equity as an outcome brand strategies. The objectives of this research was : (a) the positive effect of company's presented brand to brand awareness, (b) the positive effect of company's presented brand to brand meaning, (c) the positive effect of external brand communications to brand awarenessm, (d) the positive effect of external brand communications to brand meaning, (e) the positive effect of customer experience with company to brand meaning, (f) the positive effect of brand awareness to brand equity, (g) the positive effect of brand meaning to brandequity. The design of this research applies a survey toward unit of analysis on the hotel and to interview the customers for testing hypothesis. Meanwhile the required data consist of six variables; company presented brand, external brand communications, customer experience with company, brand awareness, brand meaning, and brand equity. The aggregate numbers of customer being respondent of the study are 150. Data analysis used in this research wasconsists of Structural Equation Method by LISRELL 8.7 as software. The result of this research conclude that variable of company's presented brand had effect to brand awareness, company's presented brand had effect to brand meaning, external brand communications had effect to brand awareness, external brand communications had effect to brand meaning, customer experience with company had effect to brand meaning, brand mening had effect to brand equity, and brand awareness had effect to brand equity

Digital twins: a survey on enabling technologies, challenges, trends and future prospects

Digital Twin (DT) is an emerging technology surrounded by many promises, and potentials to reshape the future of industries and society overall. A DT is a system-of-systems which goes far beyond the traditional computer-based simulations and analysis. It is a replication of all the elements, processes, dynamics, and firmware of a physical system into a digital counterpart. The two systems (physical and digital) exist side by side, sharing all the inputs and operations using real-time data communications and information transfer. With the incorporation of Internet of Things (IoT), Artificial Intelligence (AI), 3D models, next generation mobile communications (5G/6G), Augmented Reality (AR), Virtual Reality (VR), distributed computing, Transfer Learning (TL), and electronic sensors, the digital/virtual counterpart of the real-world system is able to provide seamless monitoring, analysis, evaluation and predictions. The DT offers a platform for the testing and analysing of complex systems, which would be impossible in traditional simulations and modular evaluations. However, the development of this technology faces many challenges including the complexities in effective communication and data accumulation, data unavailability to train Machine Learning (ML) models, lack of processing power to support high fidelity twins, the high need for interdisciplinary collaboration, and the absence of standardized development methodologies and validation measures. Being in the early stages of development, DTs lack sufficient documentation. In this context, this survey paper aims to cover the important aspects in realization of the technology. The key enabling technologies, challenges and prospects of DTs are highlighted. The paper provides a deep insight into the technology, lists design goals and objectives, highlights design challenges and limitations across industries, discusses research and commercial developments, provides its applications and use cases, offers case studies in industry, infrastructure and healthcare, lists main service providers and stakeholders, and covers developments to date, as well as viable research dimensions for future developments in DTs

Defining and Measuring High Technology in Georgia

This report defines and measures the high technology sector in Georgia

IPO Ready? Illuminating the Dark Box of Private Equity

The use of public equity data can help combat the challenges private equity funds currently face regarding data availability. The goal is to create a model to provide guidance to both investors and entrepreneurs in the decision-making process. The data gathered would provide insight on how close a private company is to a successful Initial Public Offering (IPO). The idea is that a model, showing the average financial metrics of companies within certain industries during an IPO, can provide new perceptiveness as to how the private company is performing

Ready for Tomorrow: Demand-Side Emerging Skills for the 21st Century

As part of the Ready for the Job demand-side skill assessment, the Heldrich Center explored emerging work skills that will affect New Jersey's workforce in the next three to five years. The Heldrich Center identified five specific areas likely to generate new skill demands: biotechnology, security, e-learning, e-commerce, and food/agribusiness. This report explores the study's findings and offers recommendations for improving education and training in New Jersey

Evaluating the quality of project planning: a model and field results

Faulty planning will result in project failure, whereas high-quality project planning increases the project's chances of success. The paper reports on the successful development and implementation of a model aimed at evaluating the quality of project planning. The model is based on both the abilities required of the project manager and the organizational support required for a proper project management infrastructure. The model was validated and applied by 282 project managers in nine organizations, where strong and weak planning processes were identified and analysed