Big Data and Analytics for Competitive Advantage

2015 ◽  
pp. 3-22 ◽  
Author(s):  
Vincenzo Morabito
Keyword(s):  
Big Data ◽  
Competitive Advantage

Big data analytics as a roadmap towards green innovation, competitive advantage and environmental performance

2021 ◽  
pp. 128998
Author(s):  
Muhammad Waqas ◽  
Xue Honggang ◽  
Naveed Ahmad ◽  
Syed Abdul Rehman Khan ◽  
Muzzafar Iqbal
Keyword(s):  
Big Data ◽  
Competitive Advantage ◽  
Environmental Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Green Innovation

scholarly journals Artificial Intelligence Sebagai Penggerak Industri 4.0 dan Tantangannya Bagi Sektor Pemerintah dan Swasta

2019 ◽  
Vol 10 (1) ◽  
pp. 68
Author(s):  
Reza Yogaswara
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Big Data ◽  
Deep Learning ◽  
Internet Of Things ◽  
Competitive Advantage ◽  
Smart City ◽  
Chief Information Officer ◽  
Deep Learning Neural Network

Artificial Intelligence (AI) atau kecerdasan buatan menjadi penggerak revolusi industri 4.0 yang menjanjikan banyak kemudahan bagi sektor pemerintah maupun industri. Internet of Things (IoT) dan big data contohnya dimana AI dapat diimplementasikan, teknologi yang telah banyak diadopsi di era industri 4.0 ini mampu menghubungkan setiap perangkat, seseorang dapat mengotomatisasi semua perangkat tanpa harus berada di lokasi, lebih dari itu, saat ini telah banyak mesin yang dapat menginterprestasi suatu kondisi atau kejadian tertentu dengan bantuan AI, sebagaimana telah kamera cerdas pendeteksi kepadatan volume kendaraan di jalan raya menggunakan teknologi Deep Learning Neural Network, yang telah diimplementasikan pada beberapa Pemerintah Daerah Kabupaten dan Kota dalam mendukung program Smart City yang telah dicanangkan. Pada sektor industri, banyak juga dari mereka yang telah mengotomatisasi mesin produksi dan manufaktur menggunakan robot dan Artificial Intelligence, sehingga Industri 4.0 akan meningkatkan daya saing melalui perangkat cerdas, setiap entitas yang mampu menguasai teknologi ini disitulah keunggulan kompetitifnya (competitive advantage). Namun ditengah perkembangan industri 4.0 yang cukup masif pemerintah harus bergerak cepat dalam mengadopsi platform ini, jika tidak, mereka akan menurunkan efisiensi proses bisnis untuk menjaga stabilitas layanan publik. Oleh sebab itu diperlukan keilmuan dan pemahaman yang benar bagi pemerintah dalam menghadapai era Industri 4.0, dimana Chief Information Officer (CIO) dapat mengambil peranan penting dalam memberikan dukungan yang didasari atas keilmuan mereka terkait tren teknologi industri 4.0, khususnya AI yang telah banyak diadopsi di berbagai sektor.

scholarly journals Big Data using Cloud Computing - Opportunities for Small and Medium-sized Enterprises

2016 ◽  
Vol 4 (1) ◽  
pp. 129 ◽  
Author(s):  
Narasimha Rao Vajjhala ◽  
Ervin Ramollari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Fault Tolerance ◽  
Competitive Advantage ◽  
Computer Architecture ◽  
Financial Resources ◽  
Future Research ◽  
Current Trends ◽  
Low Performance ◽  
Research Frontiers

Big Data has been listed as one of the current and future research frontiers by Gartner. Large-sized companies are already investing on and leveraging big data. Small-sized and medium-sized enterprises (SMEs) can also leverage big data to gain a strategic competitive advantage but are often limited by the lack of adequate financial resources to invest on the technology and manpower. Several big data challenges still exist especially in computer architecture that is CPU-heavy but I/O poor. Cloud computing eliminates the need to maintain expensive computing hardware and software. Cloud computing resources and techniques can be leveraged to address the traditional problems associated with fault tolerance and low performance causing bottlenecks to using big data. SMEs can take advantage of cloud computing techniques to avail the advantages of big data without significant investments in technology and manpower. This paper explores the current trends in the area of big data using cloud resources and how SMEs can take advantage of these technological trends. The results of this study will benefit SMEs in identifying and exploring possible opportunities and also understanding the challenges in leveraging big data.

Big Data, Knowledge, and Business Intelligence

2018 ◽  
pp. 943-950
Author(s):  
G. Scott Erickson ◽  
Helen N. Rothberg
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Competitive Advantage ◽  
Intellectual Capital ◽  
Business Intelligence ◽  
Competitive Intelligence ◽  
Business Analytics ◽  
The Past ◽  
The People ◽  
Tools And Techniques

Knowledge management (KM), intellectual capital (IC), and competitive intelligence are distinct yet related fields that have endured and grown over the past two decades. KM and IC have always differentiated between the terms and concepts of data, information, knowledge, and wisdom/intelligence, suggesting value only comes from the more developed end of the range (knowledge and intelligence). But the advent of big data/business analytics has created new interest in the potential of data and information, by themselves, to create competitive advantage. This new attention provides opportunities for some exchange with more established theory. Big data gives direction for reinvigorating the more mature fields, providing new sources of inputs and new potential for analysis and use. Alternatively, big data/business analytics applications will undoubtedly run into common questions from KM/IC on appropriate tools and techniques for different environments, the best methods for handling the people issues of system adoption and use, and data/intelligence security.

Big-Data-Based Techniques for Predictive Intelligence

2019 ◽  
pp. 1-18
Author(s):  
Dharmpal Singh ◽  
Madhusmita Mishra ◽  
Sudipta Sahana
Keyword(s):  
Big Data ◽  
Competitive Advantage ◽  
Predictive Analytics ◽  
Unstructured Data ◽  
Security Issue ◽  
Operational Costs ◽  
Big Data Technologies ◽  
Ending Process ◽  
Big Data Technology

Big-data-analyzed finding patterns derive meaning and make decisions on data to produce responses to the world with intelligence. It is an emerging area used in business intelligence (BI) for competitive advantage to analyze the structured, semi-structured, and unstructured data stored in different formats. As the big data technology continues to evolve, businesses are turning to predictive intelligence to deepen the engagement to customers with optimization in processes to reduce the operational costs. Predictive intelligence uses sets of advanced technologies that enable organizations to use data stored in real time that move from a historical and descriptive view to a forward-looking perspective of data. The comparison and other security issue of this technology is covered in this book chapter. The combination of big data technology and predictive analytics is sometimes referred to as a never-ending process and has the possibility to deliver significant competitive advantage. This chapter provides an extensive review of literature on big data technologies and its usage in the predictive intelligence.

A Conceptual Model for Describing the Integration of Decision Aspect into Big Data

2022 ◽  
pp. 294-318
Author(s):  
Fatma Chiheb ◽  
Fatima Boumahdi ◽  
Hafida Bouarfa
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Competitive Advantage ◽  
Conceptual Model ◽  
Big Data Analytics ◽  
Decision Makers ◽  
Modern Business ◽  
Definition Of ◽  
A Company ◽  
Support Decision Making

Big Data is an important topic for discussion and research. It has gained this importance due to the meaningful value that could be extracted from these data. The application of Big Data in the modern business allows enterprises to take faster and smarter decisions, achieving a real competitive advantage. However, a lot of Big Data projects provide disappointing results that don't address the decision-makers' needs due to many reasons. The main reason for this failure can be summarized in neglecting the study of the decision-making aspect of these projects. In light of this challenge, this study proposes the integration of decision aspect into Big Data as a solution. Therefore, this article presents three main contributions: 1) Clarify the definition of Big Data; 2) Presents BD-Da model, a conceptual model describes the levels that should be considered to develop a Big Data project aiming to solve a problem that calls a decision; 3) Describes a particular, logical, requirements-like approach that explains how a company develops a Big Data analytics project to support decision-making.

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.

scholarly journals Decision Framework for Engaging Cloud-Based Big Data Analytics Vendors

2020 ◽  
Vol 22 (4) ◽  
pp. 60-74
Author(s):  
Emmanuel Wusuhon Yanibo Ayaburi ◽  
Michele Maasberg ◽  
Jaeung Lee
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Competitive Advantage ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Unique Contribution ◽  
Data Services ◽  
Business Environments ◽  
Digital Era ◽  
Service Oriented

Organizations face both opportunities and risks with big data analytics vendors, and the risks are now profound, as data has been likened to the oil of the digital era. The growing body of research at the nexus of big data analytics and cloud computing is examined from the economic perspective, based on agency theory (AT). A conceptual framework is developed for analyzing these opportunities and challenges regarding the use of big data analytics and cloud computing in e-business environments. This framework allows organizations to engage in contracts that target competitive parity with their service-oriented decision support system (SODSS) to achieve a competitive advantage related to their core business model. A unique contribution of this paper is its perspective on how to engage a vendor contractually to achieve this competitive advantage. The framework provides insights for a manager in selecting a vendor for cloud-based big data services.

Big Data, HRIS, and Competitive Advantage

2020 ◽  
Vol 2020 (1) ◽  
pp. 14552
Author(s):  
Victor Chen ◽  
Nolan Gaffney
Keyword(s):  
Big Data ◽  
Competitive Advantage

The use of social media by higher education institutions

2020 ◽  
Vol 65 (2) ◽  
pp. 30-42
Author(s):  
Jacek Maślankowski ◽  
Łukasz Brzezicki
Keyword(s):  
Higher Education ◽  
Social Media ◽  
Big Data ◽  
Competitive Advantage ◽  
Full Advantage ◽  
Higher Education Institutions ◽  
Marketing Activities ◽  
Use Of Social Media ◽  
Marketing Methods

Higher education institutions have been using, to an increasing extent, various marketing methods and tools, which are becoming a decisive factor in building their competitive advantage and achieving success. In order to initiate and maintain long-term relationships with their communities and to conduct other marketing activities, higher education institutions have been increasingly often using social media, which has enabled them to actively create their image. The aim of this study is to utilize big data methods and tools to measure the scale of the use of social media by the higher education sector. The research carried out in the first quarter of 2019 demonstrates that large higher education institutions, i.e. those with over 1696 students (according to the adopted classification), use social media to communicate current news to a larger extent than the smaller ones. A significantly smaller percentage of mediumsized higher education institutions (223-1695 students) and small ones (up to 222 students) have accounts in social media, thus failing to take full advantage of the potential of these media. Higher education institutions use social media mainly to promote events they organise.

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