scholarly journals INTEGRATING BIG DATA INTO DECISION-MAKING IN REAL ESTATE INDUSTRY

2020 ◽  
Vol Vol. 36 (No. 2) ◽  
pp. 25-33
Author(s):  
Beyza Ali ◽  
Nikolai Siniak
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Real Estate ◽  
Value Creation ◽  
Business Models ◽  
New Technologies ◽  
Smart Devices ◽  
Data Generation ◽  
Real Estate Industry ◽  
Business World

With the developments in technology everything we use became smarter which resulted in an outbreak in data generation, which in turn demanded innovations in technology. The new technologies did not only affect the social life but also changed the dynamics in the way businesses are conducted. Compared to before, today people have platforms where they can state their opinions publicly. As positive opinions can increase the reliability of a product, person, brand or etc. negative opinions can decrease the reliability. The increase in the use of such platforms and smart devices resulted in an unprecedented increase in data generation. Hereby a new phenomenon, called Big Data, emerged. In parallel with these developments, business world came to a point where traditional business models and strategies run short to challenge the requirements of clients. At this point it is important to realize that the only way to stay in the game is to accept the paper the meaning and the importance of the Big Data phenomena is discussed through its effect on value-creation and decision-making. The process of integrating Big -making processes is investigated with an emphasis on the importance of value-creation from Big Data. As a result of the conducted literature review, success factors for a successful integration process are suggested. One of the industries that has mostly affected from the emergence of Big Data is real estate industry. A case study on the owner occupation rates in Europe was conducted using the annual report for 2019 of European Mortgage Federation (EMF) with the aim to point out to the advantages of using Big Data and analysis over the traditional methods and to emphasize the significance of adopting data analytics technologies.

Global brain-reflective accounting practices

2019 ◽  
Vol 20 (6) ◽  
pp. 733-762 ◽  
Author(s):  
Khaldoon Al-Htaybat ◽  
Khaled Hutaibat ◽  
Larissa von Alberti-Alhtaybat
Keyword(s):  
Sustainable Development ◽  
Big Data ◽  
Intellectual Capital ◽  
Value Creation ◽  
Data Analytics ◽  
Business Models ◽  
New Technologies ◽  
Big Data Analytics ◽  
Content Type ◽  
Global Brain

Purpose The purpose of this paper is to explore the intersection of accounting practices and new technologies in the age of agility as a form of intellectual capital, through sharing the conceptualization and real implications of accounting and accountability ideas in exploring and deploying new technologies, such as big data analytics, blockchain and augmented accounting practices and expounding how they constitute new forms of intellectual capital to support value creation and realise Sustainable Development Goals (SDGs). Design/methodology/approach The adopted methodology is cyber-ethnography, which investigates online practices through observation and discourse analysis, reflecting on new business models and practices, and how accounting relates to these developments. The global brain sets the conceptual context, which reflects the distributed network intelligence that is created through the internet. Findings The main findings focus on various developments of accounting practice that reflect, utilise or support digital companies and new technologies, including augmentation, big data analytics and blockchain technology, as new forms of intellectual capital, that is knowledge and skills within organisations, that have the potential to support value creation and realise SDGs. These relate to and originate from the global brain, which constitutes the umbrella of tech-related intellectual capital. Originality/value This paper determines new developments in accounting practices in relation to new technologies, due to the continuous expansion and influence of the intelligence of the collective network, the global brain, as forms of intellectual capital, contributing to value creation, sustainable development and the realisation of SDGs.

scholarly journals Transformation of the real estate and construction industry: empirical findings from Germany

2020 ◽  
Vol 90 (7) ◽  
pp. 975-1019 ◽  
Author(s):  
Andreas Pfnür ◽  
Benjamin Wagner
Keyword(s):  
Real Estate ◽  
Construction Industry ◽  
Value Creation ◽  
Business Models ◽  
Service Providers ◽  
Adaptation Strategies ◽  
Real Estate Industry ◽  
The Real ◽  
The Real Estate ◽  
The Impact

Abstract The German real estate and construction industry is facing a transformation, triggered by fundamental changes in technology, the economy and society. The purpose of this paper is to explore how these changes exert pressure to adapt on existing business models, while also offering opportunities for their further development. A model that attributes the transformation of the real estate industry to megatrends, specific structural change drivers, business models and the interaction of the groups of players in the value creation system is developed. The model is tested empirically by a survey. Structural equation modelling is used to measure the impact of various determinants of transformation and the relevance of adaptation strategies to the different groups of players. As a result, the study explains three impact mechanisms of the transformation in the real estate industry. The transformation originates from the occupiers, who need more flexible space and are focusing on holistic solutions that are not provided by the real estate industry. Service providers are striving to increase the efficiency of their traditional processes, rather than evolving new business models or services. The investors recognise the increasing importance of the occupiers but they are rarely pursuing the resulting strategies. Property developers recognise these requirements: their adaptation strategies most strongly question their previous business. For practitioners, the results point out the opportunities and risks of transformation and help to illustrate the need for change. For academicians, the results indicate a way to explain and measure the transformation of a value creation system.

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.

IoT-Based Big Data

2017 ◽  
Vol 13 (1) ◽  
pp. 28-47 ◽  
Author(s):  
M. Mazhar Rathore ◽  
Anand Paul ◽  
Awais Ahmad ◽  
Gwanggil Jeon
Keyword(s):  
Decision Making ◽  
Big Data ◽  
City Planning ◽  
Water System ◽  
Planning System ◽  
Data Generation ◽  
Next Generation ◽  
Smart Systems ◽  
Tier 1 ◽  
Iot Devices

Recently, a rapid growth in the population in urban regions demands the provision of services and infrastructure. These needs can be come up wit the use of Internet of Things (IoT) devices, such as sensors, actuators, smartphones and smart systems. This leans to building Smart City towards the next generation Super City planning. However, as thousands of IoT devices are interconnecting and communicating with each other over the Internet to establish smart systems, a huge amount of data, termed as Big Data, is being generated. It is a challenging task to integrate IoT services and to process Big Data in an efficient way when aimed at decision making for future Super City. Therefore, to meet such requirements, this paper presents an IoT-based system for next generation Super City planning using Big Data Analytics. Authors have proposed a complete system that includes various types of IoT-based smart systems like smart home, vehicular networking, weather and water system, smart parking, and surveillance objects, etc., for dada generation. An architecture is proposed that includes four tiers/layers i.e., 1) Bottom Tier-1, 2) Intermediate Tier-1, 3) Intermediate Tier 2, and 4) Top Tier that handle data generation and collections, communication, data administration and processing, and data interpretation, respectively. The system implementation model is presented from the generation and collection of data to the decision making. The proposed system is implemented using Hadoop ecosystem with MapReduce programming. The throughput and processing time results show that the proposed Super City planning system is more efficient and scalable.

Big Data Myth

2019 ◽  
pp. 223-237
Author(s):  
Agata Mardosz-Grabowska
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Qualitative Data ◽  
New Technologies ◽  
Marketing Management ◽  
Individual Experience ◽  
Decision Making Process

Organizations are expected to act rationally; however, mythical thinking is often present among their members. It refers also to myths related to technology. New inventions and technologies are often mythologized in organizations. People do not understand how new technologies work and usually overestimate their possibilities. Also, myths are useful in dealing with ambivalent feelings, such as fears and hopes. The text focuses on the so-called “big data myth” and its impact on the decision-making process in modern marketing management. Mythical thinking related to big data in organizations has been observed both by scholars and practitioners. The aim of the chapter is to discuss the foundation of the myth, its components, and its impact on the decision-making process. Among others, a presence of a “big data myth” may be manifested by over-reliance on data, neglecting biases in the process of data analysis, and undermining the role of other factors, including intuition and individual experience of marketing professionals or qualitative data.

Big Data and Data Analytics Research

Web Services ◽  
2019 ◽  
pp. 2161-2171
Author(s):  
Miltiadis D. Lytras ◽  
Vijay Raghavan ◽  
Ernesto Damiani
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analytics ◽  
Business Models ◽  
Internet Technology ◽  
Cognitive Computing ◽  
New Paradigm ◽  
Web Science ◽  
New Business ◽  
Value Propositions

The Big Data and Data Analytics is a brand new paradigm, for the integration of Internet Technology in the human and machine context. For the first time in the history of the human mankind we are able to transforming raw data that are massively produced by humans and machines in to knowledge and wisdom capable of supporting smart decision making, innovative services, new business models, innovation, and entrepreneurship. For the Web Science research, this is a new methodological and technological spectrum of advanced methods, frameworks and functionalities never experienced in the past. At the same moment communities out of web science need to realize the potential of this new paradigm with the support of new sound business models and a critical shift in the perception of decision making. In this short visioning article, the authors are analyzing the main aspects of Big Data and Data Analytics Research and they provide their own metaphor for the next years. A number of research directions are outlined as well as a new roadmap towards the evolution of Big Data to Smart Decisions and Cognitive Computing. The authors do hope that the readers would like to react and to propose their own value propositions for the domain initiating a scientific dialogue beyond self-fulfilled expectations.

Machine Learning for Industrial IoT Systems

2021 ◽  
pp. 336-358
Author(s):  
Mona Bakri Hassan ◽  
Elmustafa Sayed Ali Ahmed ◽  
Rashid A. Saeed
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Operations Management ◽  
Industrial Applications ◽  
Smart Devices ◽  
Iot Applications ◽  
Industrial Iot ◽  
Effective Decision ◽  
Effective Decision Making

The use of AI algorithms in the IoT enhances the ability to analyse big data and various platforms for a number of IoT applications, including industrial applications. AI provides unique solutions in support of managing each of the different types of data for the IoT in terms of identification, classification, and decision making. In industrial IoT (IIoT), sensors, and other intelligence can be added to new or existing plants in order to monitor exterior parameters like energy consumption and other industrial parameters levels. In addition, smart devices designed as factory robots, specialized decision-making systems, and other online auxiliary systems are used in the industries IoT. Industrial IoT systems need smart operations management methods. The use of machine learning achieves methods that analyse big data developed for decision-making purposes. Machine learning drives efficient and effective decision making, particularly in the field of data flow and real-time analytics associated with advanced industrial computing networks.

scholarly journals Smart Manufacturing Systems and Applied Industrial Technologies for a Sustainable Industry: A Systematic Literature Review

2020 ◽  
Vol 10 (8) ◽  
pp. 2897
Author(s):  
Raffaele Cioffi ◽  
Marta Travaglioni ◽  
Giuseppina Piscitelli ◽  
Antonella Petrillo ◽  
Adele Parmentola
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Circular Economy ◽  
Manufacturing Systems ◽  
Business Models ◽  
New Technologies ◽  
Smart Manufacturing ◽  
Smart Devices ◽  
Digital Innovation ◽  
Smart Manufacturing Systems

Smart manufacturing is considered as a new paradigm that makes work smarter and more connected, bringing speed and flexibility through the introduction of digital innovation. Today, digital innovation is closely linked to the “sustainability” of companies. Digital innovation and sustainability are two inseparable principles that are based on the concept of circular economy. Digital innovation enables a circular economy model, promoting the use of solutions like digital platforms, smart devices, and artificial intelligence that help to optimize resources. Thus, the purpose of the research is to present a systematic literature review on what enabling technologies can promote new circular business models. A total of 31 articles were included in the study. Our results showed that realization of the circular economy involved two main changes: (i) managerial changes and (ii) legislative changes. Furthermore, the creation of the circular economy can certainly be facilitated by innovation, especially through the introduction of new technologies and through the introduction of digital innovations.

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