Building Acquisition Management Capability to Improve Firm Performance in Acquisitions

In the past two decades, the number of cross-border mergers and acquisitions in ASEAN has progressively expanded as the region has become a desired economic market for trade and investment. Therefore, this study aimed to identify the factors contributing to the success of acquisitions by corporations. It investigates the role of acquisition management capability with strategic integration and acquisition. The non-probability sampling strategy was used to collect information from 51 firms. With a five-point Likert scale, a systematic questionnaire was designed to test the latent variables by employing confirmatory factor analysis. The quantitative method of Structural Equation Modeling was used in the analysis. The results show that the structural model had a Goodness of Fit Index value that indicates all three latent variables and independent variables were valid. The findings indicate that acquisition management capability have a central role in advancing the overall integration of the acquiring firm in the ASEAN context.

Remote Patient Monitoring in Diabetes: How to Acquire, Manage, and Use All of The Data

The ability of patients and health care providers to use various forms of technology for general health has significantly increased in the past several years with the expansion of telehealth, digital applications, personal digital devices, smartphones, and other Internet-connected platforms and devices. For individuals with diabetes, this also includes connected blood glucose meters, continuous glucose monitoring devices, and insulin delivery systems. In this article, the authors outline several steps to facilitate the acquisition, management, and meaningful use of digital diabetes data that can enable successful implementation of both diabetes technology and telehealth services in primary care clinics.

The Dynamic Digital Twin: diagnosis, treatment, prediction and prevention of disease during the life course (Preprint)

UNSTRUCTURED A Digital Twin (DT), which is defined originally as a virtual representation of a physical asset, system or process, is a new concept in healthcare. DT in healthcare cannot be a single technology, but a domain adapted multi-modal modelling approach, which incorporates the acquisition, management, analysis, prediction, and interpretation of the data, aiming to improve medical decision making. However, there are many challenges and barriers that has to be overcome before a DT can be used in healthcare. In this viewpoint paper, we address these challenges, and envision a dynamic DT in healthcare for optimizing individual patient health care journeys. We describe how we can commit multiple domains to developing this DT. With our cross-domain definition of the DT, we aim to define future goals, trade-offs, and methods, which guide the development of the dynamic DT and the implementation strategies in healthcare.

Meteo-Hydrological Sensors within the Lake Maggiore Catchment: System Establishment, Functioning and Data Validation

Climate change and human activities have a strong impact on lakes and their catchments, so to understand ongoing processes it is fundamental to monitor environmental variables with a spatially well-distributed and high frequency network and efficiently share data. An effective sharing and interoperability of environmental information between technician and end-user fosters an in-depth knowledge of the territory and its critical environmental issues. In this paper, we present the approaches and the results obtained during the PITAGORA project (Interoperable Technological Platform for Acquisition, Management and Organization of Environmental data, related to the lake basin). PITAGORA was aimed at developing both instruments and data management, including pre-processing and quality control of raw data to ensure that data are findable, accessible, interoperable, and reusable (FAIR principles). The main results show that the developed instrumentation is low-cost, easily implementable and reliable, and can be applied to the measurement of diverse environmental parameters such as meteorological, hydrological, physico-chemical, and geological. The flexibility of the solutions proposed make our system adaptable to different monitoring purposes, research, management, and civil protection. The real time access to environmental information can improve management of a territory and ecosystems, safety of the population, and sustainable socio-economic development.

The effect of supply channel structures on remanufacturing, pricing, and acquisition management

This paper developed an acquisition management problem in a Closed-Loop Supply chain (CLSC) network. This study determines optimal selling prices of brand-new and remanufactured products, wholesale prices, and acquisition prices in various distribution and collection channel structures. It shows that determining the best structure is highly affected by the model’s parameters, as well as the decision-makers’ objectives. Moreover, precious managerial insights from five different viewpoints have been provided for decision-makers in order to benefit considerably from various situations of remanufacturing and acquisition activities, as well as manufacturing and distribution activities. Simulation approach is employed for analyzing the proposed solutions in different conditions.

The Swiss data cube, analysis ready data archive using earth observations of Switzerland

Since the opening of Earth Observation (EO) archives (USGS/NASA Landsat and EC/ESA Sentinels), large collections of EO data are freely available, offering scientists new possibilities to better understand and quantify environmental changes. Fully exploiting these satellite EO data will require new approaches for their acquisition, management, distribution, and analysis. Given rapid environmental changes and the emergence of big data, innovative solutions are needed to support policy frameworks and related actions toward sustainable development. Here we present the Swiss Data Cube (SDC), unleashing the information power of Big Earth Data for monitoring the environment, providing Analysis Ready Data over the geographic extent of Switzerland since 1984, which is updated on a daily basis. Based on a cloud-computing platform allowing to access, visualize and analyse optical (Sentinel-2; Landsat 5, 7, 8) and radar (Sentinel-1) imagery, the SDC minimizes the time and knowledge required for environmental analyses, by offering consistent calibrated and spatially co-registered satellite observations. SDC derived analysis ready data supports generation of environmental information, allowing to inform a variety of environmental policies with unprecedented timeliness and quality.

Innovation Resistance and Resource Allocation Strategy of Medical Information Digitalization

Healthcare industries are facing an enormous flow of medical records due to the progression of information technology and the trend of digital transformation. Thus, medical information digitalization is a huge digital dataset that can be utilized to benefit healthcare systems and patients. While many studies focus on the application of the digitalized medical information in the healthcare field, only a few mentioned its resistance. The theoretical background depicts a comprehensive overview of medical information digitalization and the barriers in previous literature. This study emphasized the interaction of medical information digitalization barriers and applies the importance-resistance analysis model (IRA) to identify the resistant factors overcoming strategy. It also clarifies the pathway to eliminating the innovation resistance and reveals the interaction of medical information digitalization barriers. The acquisition, management, and application of medical information digitalization are the key foundation of medical technology innovation, digital transformation, and the application of artificial intelligence. This work can reduce the limitation of a narrow healthcare context. This study helps healthcare industries to clarify and solve barriers and realizes the innovation and application of medical information digitalization. In the long term, the results provide a basis for the future development direction of medical information digitalization and affect the medical industry.

HydroLang: An Open-Source Web-Based Programming Framework for Hydrological Sciences

This paper presents HydroLang, an open-source and integrated community-driven computational web framework to support research and education in hydrology and water resources. HydroLang uses client-side web technologies and standards to perform different routines which aim towards the acquisition, management, transformation, analysis and visualization of hydrological datasets. HydroLang is comprised of four main high-cohesion low-coupling modules for: (1) retrieving, manipulating, and transforming raw hydrological data, (2) statistical operations, hydrological analysis, and creating models, (3) generating graphical and tabular data representations, and (4) mapping and geospatial data visualization. Two extensive case studies (i.e., evaluation of lumped models and development of a rainfall disaggregation model) have been presented to demonstrate the framework’s capabilities, portability, and interoperability. HydroLang’s unique modular architecture and open-source nature allow it to be easily tailored into any use case and web framework and promote iterative enhancements with community involvement to establish the comprehensive next-generation hydrological software toolkit.

AN INTRODUCTORY REVIEW ABOUT DEFENCE MANAGEMENT: A CONCEPTUAL FRAMEWORK

The concept of management refers to the process to plan, to organize, to staff, to direct and to control the activities in any organization for achieving the common goal in a very systematic manner. Further, the term management refers to both a method of science art to empower individuals and to make an institution more efficient and effective when compared to the state without the manager and the management. As a process of the institution, the management lies amidst the policy formation for and the actual control and command of the forces in the military sector. management covers elements like management of the resources of sector, management of the personnel in the field and acquisition management.

Patient Information Maintaining & Analyzing

Hospitals presently use a manual system for the management and maintenance of essential info. This system needs various paper forms, with knowledge stores unfold throughout the hospital management infrastructure. Usually, info (on forms) is incomplete or does not follow management standards. Forms are usually lost in transit between departments requiring a comprehensive auditing method to confirm that no important info is lost. Multiple copies of similar info exist within the hospital and should result in inconsistencies in knowledge in numerous knowledge stores. A significant part of the operation of any hospital involves the acquisition, management, and timely retrieval of nice volumes of knowledge. This info generally involves; patient personal info and case history, staff information and ward scheduling, scheduling programming, operating theatre scheduling, and numerous facilities waiting lists. All of this info should be managed in an economical and cost-wise fashion so that an institution's resources could also be effectively utilized. Patient info maintaining & Analyzing can automate the management of the hospital creating additional economic and the error free. It aims at standardizing data, consolidating data, reducing inconsistencies, and ensuring data integrity.