scholarly journals APPLICATION AND PLATFORM DESIGN OF GEOSPATIAL BIG DATA

2021 ◽  
Vol XLIII-B4-2021 ◽  
pp. 293-300
Author(s):  
H. Li ◽  
W. Huang ◽  
Z. Zha ◽  
J. Yang
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Resource Sharing ◽  
Data Science ◽  
Geographic Information ◽  
Management Decision ◽  
Functional Requirements ◽  
Comprehensive Service ◽  
Data Platform ◽  
The Impact

Abstract. With the wide application of Big Data, Artificial Intelligence and Internet of Things in geographic information technology and industry, geospatial big data arises at the historic moment. In addition to the traditional "5V" characteristics of big data, which are Volume, Velocity, Variety, Veracity and Valuable, geospatial big data also has the characteristics of "Location Attribute". At present, the study of geospatial big data are mainly concentrated in: knowledge mining and discovery of geospatial data, Spatiotemporal big data mining, the impact of geospatial big data on visualization, social perception and smart city, geospatial big data services for government decision-making support four aspects. Based on the connotation and extension of geospatial big data, this paper comprehensively defines geospatial big data comprehensively. The application of geospatial big data in location visualization, industrial thematic geographic information comprehensive service and geographic data science and knowledge service is introduced in detail. Furthermore, the key technologies and design indicators of the National Geospatial Big Data Platform are elaborated from the perspectives of infrastructure, functional requirements and non-functional requirements, and the design and application of the National Geospatial Public Service Big Data Platform are illustrated. The challenges and opportunities of geospatial big data are discussed from the perspectives of open resource sharing, management decision support and data security. Finally, the development trend and direction of geospatial big data are summarized and prospected, so as to build a high-quality geospatial big data platform and play a greater role in social public application services and administrative management decision-making.

scholarly journals Data Analytics in Banking and Financial Services

2019 ◽  
Vol 8 (S1) ◽  
pp. 67-69
Author(s):  
S. Palaniammal ◽  
V. S. Thangamani
Keyword(s):  
Decision Making ◽  
Developing Countries ◽  
Big Data ◽  
Financial Services ◽  
Data Analytics ◽  
Data Science ◽  
Banking Industry ◽  
Rapid Development ◽  
Banking Services ◽  
The Impact

In Journal of Banking and Finance [1] we are living in the era of the big data. The rapid development of scientific and data technology over the past decade has brought not only new and sophisticated analytical tools into Financial and Banking services, but also introduced the power of data science application in everyday strategic and operational management. Data analytics and science developments have been particularly valuable to financial organizations that heavily depend on financial information in their decision making processes. The article presents the research that focuses on the impact of the data and technology trends on decision making, particularly in Finance and Banking services. It covers an overview of the benefits associated with the decision analytics and the use of big data by financial organizations. The aim of the research is to highlight the areas of impact where the big data trends are creating disruptive changes to the way the Finance and banking industry traditionally operates. For example, we can see rapid changes to organisation structures, approach to competition and customer as well as the recognition of the importance of data analytics in strategic and tactical decision making. Investment in data analytics is no longer considered a luxury, but necessity, especially for the financial organizations in developing countries. Technology and data science are both forcing and enabling the financial and banking industry to respond to transformative demands and adapt to rapidly changing market conditions in order to survive and thrive in highly competitive global environment. Financial companies operating in developing countries must develop strong understanding of data-related trends and impacts as well as opportunities. This knowledge should not only be utilized for survival efforts, but also seen as the opportunity to engage at global level through innovation, flexibility, and early adoption of data science benefits. The paper also recommends further studies in related areas, which would provide additional value and awareness to the organizations that are considering their participation in the global data and analytical trends.

Evolution of e-participation in Greek local government

2021 ◽  
pp. 1-15
Author(s):  
Constantina Costopoulou ◽  
Maria Ntaliani ◽  
Filotheos Ntalianis
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Local Government ◽  
Local Governments ◽  
Local Community ◽  
New Technologies ◽  
Mobile Apps ◽  
Digital Technologies ◽  
Decision Making Processes ◽  
The Impact

Local governments are increasingly developing electronic participation initiatives, expecting citizen involvement in local community affairs. Our objective was to assess e-participation and the extent of its change in local government in Greece. Using content analysis for 325 Greek municipal websites, we assessed e-participation status in 2017 and 2018 and examined the impact of change between these years. The assessment regards two consecutive years since the adoption of digital technologies by municipalities has been rapid. The main findings show that Greek local governments have made significant small- to medium-scale changes, in order to engage citizens and local societies electronically. We conclude that the integration of advanced digital technologies in municipalities remains underdeveloped. We propose that Greek municipalities need to consider incorporating new technologies, such as mobile apps, social media and big data, as well as e-decision making processes, in order to eliminate those obstacles that hinder citizen engagement in local government. Moreover, the COVID-19 outbreak has highlighted the need for enhancing e-participation and policymakers’ coordination through advanced digital technologies.

scholarly journals Manager perceptions of big data reliability in hotel revenue management decision making

2019 ◽  
Vol 36 (1) ◽  
pp. 25-39 ◽  
Author(s):  
David Egan ◽  
Natalie Claire Haynes
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Revenue Management ◽  
Management Decision ◽  
Local Market ◽  
Data Systems ◽  
Local Data ◽  
Content Type ◽  
User Input ◽  
Management Decision Making

PurposeThe purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing decisions.Design/methodology/approachA three-stage iterative thematic analysis technique based on the approaches of Braun and Clarke (2006) and Nowell et al. (2017) and using different research instruments to collect and analyse qualitative data at each stage was used to develop an explanatory framework.FindingsWhilst big data-driven automated revenue systems are technically capable of making pricing and inventory decisions without user input, the findings here show that the reality is that managers still interact with every stage of the revenue and pricing process from data collection to the implementation of price changes. They believe that their personal insights are as valid as big data in increasing the reliability of the decision-making process. This is driven primarily by a lack of trust on the behalf of managers in the ability of the big data systems to understand and interpret local market and customer dynamics.Practical implicationsThe less a manager believes in the ability of those systems to interpret these data, the more they perceive gut instinct to increase the reliability of their decision making and the less they conduct an analysis of the statistical data provided by the systems. This provides a clear message that there appears to be a need for automated revenue systems to be flexible enough for managers to import the local data, information and knowledge that they believe leads to revenue growth.Originality/valueThere is currently little research explicitly investigating the role of big data in decision making within hotel revenue management and certainly even less focussing on decision making at property level and the perceptions of managers of the value of big data in increasing the reliability of revenue and pricing decision making.

scholarly journals Data Science & Engineering into Food Science: A novel Big Data Platform for Low Molecular Weight Gelators’ Behavioral Analysis

2020 ◽  
Vol 20 (2) ◽  
pp. e08
Author(s):  
Verónica Cuello ◽  
Gonzalo Zarza ◽  
Maria Corradini ◽  
Michael Rogers
Keyword(s):  
Molecular Weight ◽  
Big Data ◽  
Data Science ◽  
Data Entry ◽  
Science Research ◽  
Food Science ◽  
Redundant Data ◽  
Data Platform ◽  
Assembly Behavior ◽  
Low Molecular Weight Gelators

The objective of this article is to introduce a comprehensiveend-to-end solution aimed at enabling the applicationof state-of-the-art Data Science and Analyticmethodologies to a food science related problem. Theproblem refers to the automation of load, homogenization,complex processing and real-time accessibility tolow molecular-weight gelators (LMWGs) data to gaininsights into their assembly behavior, i.e. whether agel can be mixed with an appropriate solvent or not.Most of the work within the field of Colloidal andFood Science in relation to LMWGs have centered onidentifying adequate solvents that can generate stablegels and evaluating how the LMWG characteristics canaffect gelation. As a result, extensive databases havebeen methodically and manually registered, storingresults from different laboratory experiments. Thecomplexity of those databases, and the errors causedby manual data entry, can interfere with the analysisand visualization of relations and patterns, limiting theutility of the experimental work.Due to the above mentioned, we have proposed ascalable and flexible Big Data solution to enable theunification, homogenization and availability of the datathrough the application of tools and methodologies.This approach contributes to optimize data acquisitionduring LMWG research and reduce redundant data processingand analysis, while also enabling researchersto explore a wider range of testing conditions and pushforward the frontier in Food Science research.

Application of Statistical Analysis Tools and Concepts to Big Data and Predictive Analytics to New Product Development

2020 ◽  
Vol 3 (1) ◽  
pp. 17-35
Author(s):  
Brian J. Galli
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Product Development ◽  
Competitive Advantage ◽  
New Product Development ◽  
New Product ◽  
Big Data Analysis ◽  
Life Cycles ◽  
The Impact

In today's fiercely competitive environment, most companies face the pressure of shorter product life cycles. Therefore, if companies want to maintain a competitive advantage in the market, they need to keep innovating and developing new products. If not, then they will face difficulties in developing and expanding markets and may go out of business. New product development is the key content of enterprise research and development, and it is also one of the strategic cores for enterprise survival and development. The success of new product development plays a decisive role both in the development of the company and in maintaining a competitive advantage in the industry. Since the beginning of the 21st century, with the continuous innovation and development of Internet technology, the era of big data has arrived. In the era of big data, enterprises' decision-making for new product development no longer solely relies on the experience of decision-makers; it is based on the results of big data analysis for more accurate and effective decisions. In this thesis, the case analysis is mainly carried out with Company A as an example. Also, it mainly introduces the decision made by Company A in the actual operation of new product development, which is based on the results of big data analysis from decision-making to decision-making innovation. The choice of decision-making is described in detail. Through the introduction of the case, the impact of big data on the decision-making process for new product development was explored. In the era of big data, it provides a new theoretical approach to new product development decision-making.

The influence of big data analytics management capabilities on supply chain preparedness, alertness and agility

2019 ◽  
Vol 32 (2) ◽  
pp. 297-318 ◽  
Author(s):  
Santanu Mandal
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Investment Decision ◽  
Big Data Analytics ◽  
Content Type ◽  
Investment Decision Making ◽  
Management Capabilities ◽  
The Impact

Purpose The importance of big data analytics (BDA) on the development of supply chain (SC) resilience is not clearly understood. To address this, the purpose of this paper is to explore the impact of BDA management capabilities, namely, BDA planning, BDA investment decision making, BDA coordination and BDA control on SC resilience dimensions, namely, SC preparedness, SC alertness and SC agility. Design/methodology/approach The study relied on perceptual measures to test the proposed associations. Using extant measures, the scales for all the constructs were contextualized based on expert feedback. Using online survey, 249 complete responses were collected and were analyzed using partial least squares in SmartPLS 2.0.M3. The study targeted professionals with sufficient experience in analytics in different industry sectors for survey participation. Findings Results indicate BDA planning, BDA coordination and BDA control are critical enablers of SC preparedness, SC alertness and SC agility. BDA investment decision making did not have any prominent influence on any of the SC resilience dimensions. Originality/value The study is important as it addresses the contribution of BDA capabilities on the development of SC resilience, an important gap in the extant literature.

Loyalty card adoption in SME retailers: the impact upon marketing management

2015 ◽  
Vol 49 (3/4) ◽  
pp. 467-490 ◽  
Author(s):  
Karise Hutchinson ◽  
Lisa Victoria Donnell ◽  
Audrey Gilmore ◽  
Andrea Reid
Keyword(s):  
Decision Making ◽  
Current Knowledge ◽  
Marketing Management ◽  
Management Decision ◽  
Adoption Process ◽  
Longitudinal Case Study ◽  
Content Type ◽  
Management Decision Making ◽  
The Impact ◽  
Loyalty Card

Purpose – The purpose of this paper is to understand how small to medium-sized enterprise (SME) retailers adopt and implement a loyalty card programme as a marketing management decision-making tool. Design/methodology/approach – A qualitative and longitudinal case study research design is adopted. Data were collected from multiple sources, incorporating semi-structured interviews and analysis of company documents and observation within a retail SME. Findings – The findings presented focus on the loyalty card adoption process to reflect both the organisational issues and impact upon marketing management decision-making. Research limitations/implications – This research is restricted to one region within the UK, investigating loyalty card adoption within a specific industry sector. Practical implications – SME retailers operate in an industry environment whereby there is a competitive demand for loyalty card programmes. SME retailers need to carefully consider how to match the firm’s characteristics with customer relationship management (CRM) operational requirements as highlighted in this case. Originality/value – The evidence presented extends current knowledge of retail loyalty card programmes beyond the context of large organisations to encompass SMEs. The study also illustrates the value of a structured, formal CRM system to help SME retailers compete in a complex, competitive and omni-channel marketplace, adding new insights into the retail literature.

Research on the Application of Big Data in the Environmental Decision-Making of the Government

2014 ◽  
Vol 685 ◽  
pp. 524-527
Author(s):  
Yan Ju Zhu
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Video Compression ◽  
Computer Processing ◽  
Environmental Data ◽  
Environmental Decision Making ◽  
Management Platform ◽  
Data Platform ◽  
The Government ◽  
Environmental Decision

The article mainly researches on the application of big data in the environment decision-making of the government. Through the integration of the technology of Internet, video compression, computer processing, we pose the model of the government environmental data platform. The platform includes the environmental data acquisition platform, the environmental decision-making platform and the environmental management platform.

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