The Role of Big Data Analytics in the Relationship among the Collaboration Types, Supply Chain Management and Market Performance of Thai Manufacturing Firms

The current study is carried out to explore role of big data analytics in the relationship among the collaboration types, supply chain management and market performance of Thai manufacturing firms. It has been revealed through literature review that collaboration among the firms is more than just coordination. It is referred as inter-firm interaction with key focus on strategies. This type of collaboration can be witnessed in two different ways, which include STRC and SYSCL [1] . The concepts of STRC and SYSCL have not been recognized separately in literature as they create difference influences on the performance of firm. The study has employed the SEM-PLS to analyze the data. The study broached an argument that the system collaboration includes coordination, sharing of information, and activities management for planning and forecasting of demand. The next level of inter-firm interaction is the STRC. In this advanced level, achievements are more than just SYSCL. The level with which the partners in supply chain plan different business activities with the shared vision to improve the performance of each other is referred as STRC

Research and innovation in network and traffic management systems in Europe

Adequate research and innovation (R&I) is paramount for the seamless testing, adoption and integration of network and traffic management systems. This report provides a comprehensive analysis of R&I initiatives in Europe in this field. The assessment follows the methodology developed by the European Commission’s Transport Research and Innovation Monitoring and Information System (TRIMIS). The report critically addresses research by thematic area and technologies, highlighting recent developments and future needs.JRC.C.4-Sustainable Transpor

Research and innovation in smart mobility and services in Europe: An assessment based on the Transport Research and Innovation Monitoring and Information System (TRIMIS)

For smart mobility to be cost-efficient and ready for future needs, adequate research and innovation (R&I) in this field is necessary. This report provides a comprehensive analysis of R&I in smart mobility and services in Europe. The assessment follows the methodology developed by the European Commission’s Transport Research and Innovation Monitoring and Information System (TRIMIS). The report critically assesses research by thematic area and technologies, highlighting recent developments and future needs.JRC.C.4-Sustainable Transpor

A big-data analytics method for capturing visitor activities and flows: the case of an island country

© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Understanding how people move from one location to another is important both for smart city planners and destination managers. Big-data generated on social media sites have created opportunities for developing evidence-based insights that can be useful for decision-makers. While previous studies have introduced observational data analysis methods for social media data, there remains a need for method development—specifically for capturing people’s movement flows and behavioural details. This paper reports a study outlining a new analytical method, to explore people’s activities, behavioural, and movement details for people monitoring and planning purposes. Our method utilises online geotagged content uploaded by users from various locations. The effectiveness of the proposed method, which combines content capturing, processing and predicting algorithms, is demonstrated through a case study of the Fiji Islands. The results show good performance compared to other relevant methods and show applicability to national decisions and policies

A double-edged sword: Use of computer algebra systems in first-year Engineering Mathematics and Mechanics courses

Many secondary-level mathematics students have experience with graphical calculators from high school. For the purposes of this paper we define graphical calculators as those able to perform rudimentary symbolic manipulation and solve complicated equations requiring very modest user knowledge. The use of more advanced computer algebra systems e.g. Maple, Mathematica, Mathcad, Matlab/MuPad is becoming more prevalent in tertiary-level courses. This paper explores our students’ experience using one such system (MuPad) in first-year tertiary Engineering Mathematics and Mechanics courses. The effectiveness of graphical calculators and computer algebra systems in mathematical pedagogy has been investigated by a multitude of educational researchers (e.g. Ravaglia et al. 1998). Most of these studies found very small or no correlation between student use of graphical calculators or exposure to computer algebra systems with future achievement in mathematics courses (Buteau et al. 2010). In this paper we focus instead on students’ attitude towards a more advanced standalone computer algebra system (MuPad), and whether students’ inclination to use the system is indicative of their mathematical understanding. Paper describing some preliminary research into use of computer algebra systems for teaching engineering mathematics

Phenomenological Assessment of Integrative Medicine Decision-making and the Utility of Predictive and Prescriptive Analytics Tools

The U.S. Healthcare system is struggling to manage the burden of chronic disease, racial and socio-economic disparities, and the debilitating impact of the current global pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). More patients need alternatives to allopathic or “Western” medicine focused on fighting disease with mechanism, pharmaceuticals, and invasive measures. They are seeking Integrative Medicine which focuses on health and healing, emphasizing the centrality of the patient-physician relationship. In addition to providing the best conventional care, IM focuses on preventive maintenance, wellness, improved behaviors, and a holistic care plan. This qualitative research assessed whether predictive and prescriptive analytics (artificial intelligence tools that predict patient outcomes and recommend treatments, interventions, and medications) supports the decision-making processes of IM practitioners who treat patients suffering from chronic pain. PPA was used in a few U.S. hospitals but was not widely available for IM practitioners at the time of this research. Phenomenological interviews showed doctors benefit from technology that aggregates data, providing a clear patient snapshot. PPA exposed historical information that doctors often miss. However, current systems lacked the design to manage individualized, holistic care focused on the mind, body, and spirit. Using the Future-Focused Task-Technology Fit theory, the research suggested PPA could actually do more harm than good in its current state. Future technology must be patient-focused and designed with a better understanding of the IM task and group characteristics (e.g., the unique way providers practice medicine) to reduce algorithm aversion and increase adoption. In the ideal future state, PPA will surface healthcare Big Data from multiple sources, support communication and collaboration across the patient’s support system and community of care, and track the various objective and subjective factors contributing to the path to wellness

Methods for Using Manpower to Assess USAF Strategic Risk

With limited personnel resource funding availability, senior US Air Force (USAF) decision makers struggle to base enterprise resource allocation from rigorous analytical traceability. There are over 240 career fields in the USAF spanning 12 enterprises. Each enterprise develops annual risk assessments by distinctive core capabilities. A core capability (e.g. Research and Development) is an enabling function necessary for the USAF to perform its mission as part of the Department of Defense (DOD). Assessing risk at the core capability is a good start to assessing risk, but is still not comprehensiveness enough. One of the twelve enterprises has linked its task structure to Program Element Codes (PECs). Planners and programmers use amount of funding per PEC to assess tasks needed to address a desired capability. For the first time, a linkage between core functions, core capabilities, PECs, tasks and manpower has been developed. We now can provide an objective nomenclatured way to compute personnel risk. All resources planned are not programmed (i.e. resource allocated and budgeted); the delta between the two translate into capability gaps and a level of strategic risk. A USAF career field risk demonstration is performed using normal, sigmoid and Euclidean-norm functions. Understanding potential personnel shortfalls at the career field level should better inform core capability analysis, and thus increase credibility and defensibility of strategic risk assessment