Evaluation of Strategic Opportunities and Resulting Business Models for SMEs

2021 ◽  
pp. 689-718
Author(s):  
Izabella V. Lokshina ◽  
Cees J. M. Lanting ◽  
Barbara Durkin
Keyword(s):  
Business Models ◽  
Management Practices ◽  
Environmental Indicators ◽  
Third Party ◽  
Easy Access ◽  
The Internet ◽  
Knowledge Based ◽  
Ubiquitous Sensing ◽  
Provision Of Services ◽  
And Control

This chapter focuses on ubiquitous sensing devices, enabled by Wireless Sensor Network (WSN) technologies, that cut across every area of modern day living, affecting individuals and businesses and offering the ability to measure and understand environmental indicators. The proliferation of these devices in a communicating-actuating network creates the internet of things (IoT). The IoT provides the tools to establish a major global data-driven ecosystem with its emphasis on Big Data. Currently, business models may focus on the provision of services, i.e., the internet of services (IoS). These models assume the presence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated. Different business models may support creating revenue and value for different types of customers. This chapter contributes to the literature by considering, innovatively, knowledge-based management practices, strategic opportunities and resulting business models for third-party data analysis services.

Evaluation of Strategic Opportunities and Resulting Business Models for SMEs

2020 ◽  
pp. 148-186 ◽  
Author(s):  
Izabella V. Lokshina ◽  
Cees J. M. Lanting ◽  
Barbara Durkin
Keyword(s):  
Business Models ◽  
Management Practices ◽  
Environmental Indicators ◽  
Third Party ◽  
Easy Access ◽  
The Internet ◽  
Knowledge Based ◽  
Ubiquitous Sensing ◽  
Provision Of Services ◽  
And Control

This chapter focuses on ubiquitous sensing devices, enabled by Wireless Sensor Network (WSN) technologies, that cut across every area of modern day living, affecting individuals and businesses and offering the ability to measure and understand environmental indicators. The proliferation of these devices in a communicating-actuating network creates the internet of things (IoT). The IoT provides the tools to establish a major global data-driven ecosystem with its emphasis on Big Data. Currently, business models may focus on the provision of services, i.e., the internet of services (IoS). These models assume the presence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated. Different business models may support creating revenue and value for different types of customers. This chapter contributes to the literature by considering, innovatively, knowledge-based management practices, strategic opportunities and resulting business models for third-party data analysis services.

The IoT- and Big Data-Driven Data Analysis Services

2018 ◽  
Vol 14 (4) ◽  
pp. 88-107 ◽  
Author(s):  
Izabella V. Lokshina ◽  
Barbara J. Durkin ◽  
Cees Lanting
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Business Models ◽  
Environmental Indicators ◽  
Third Party ◽  
Data Driven ◽  
Easy Access ◽  
The Internet ◽  
Ubiquitous Sensing ◽  
Provision Of Services

Ubiquitous sensing devices, enabled by wireless sensor network (WSN) technologies, cut across every area of modern day living, affecting individuals and businesses and offering the ability to measure and understand environmental indicators. The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT). The IoT provides the tools to establish a major global data-driven ecosystem with its emphasis on Big Data. Now business models may focus on the provision of services, i.e., the Internet of Services (IoS). These models assume the presence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated. Different business models may support potential opportunities to create revenue and value for various types of customers. This article contributes to the literature by considering, for the first time, business models, strategic implications and business opportunities for third-party data analysis services.

IoT- and Big Data-Driven Data Analysis Services for Third Parties, Strategic Implications and Business Opportunities

2018 ◽  
Vol 9 (3) ◽  
pp. 34-52 ◽  
Author(s):  
Izabella V. Lokshina ◽  
Cees J.M. Lanting ◽  
Barbara J. Durkin
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Business Models ◽  
Management Practices ◽  
Environmental Indicators ◽  
Third Party ◽  
Data Driven ◽  
Easy Access ◽  
Business Opportunities ◽  
Provision Of Services

This article describes ubiquitous sensing devices, enabled by wireless sensor network (WSN) technologies, now cut across every area of modern day living, affecting individuals and businesses and offering the ability to obtain and measure environmental indicators. Proliferation of these devices in a communicating-actuating network creates an Internet of Things (IoT). The IoT provides the tools to establish a major, global data-driven ecosystem that also enables Big Data techniques to be used. New business models may focus on the provision of services, i.e., the Internet of Services (IoS). These models assume the presence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated. Different business models may support opportunities to create revenue and value for various types of customers. This article contributes to the literature by considering, a first, knowledge-based management practices, business models, strategic implications and business opportunities for third-party data analysis services.

Data Analysis Services Related to the IoT and Big Data

Web Services ◽  
2019 ◽  
pp. 882-903
Author(s):  
Izabella V. Lokshina ◽  
Barbara J. Durkin ◽  
Cees J.M. Lanting
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Business Models ◽  
Third Party ◽  
Data Driven ◽  
Easy Access ◽  
Provision Of Services ◽  
And Control ◽  
Measurement And Control ◽  
The Internet Of Things

The Internet of Things (IoT) provides the tools for the development of a major, global data-driven ecosystem. When accessible to people and businesses, this information can make every area of life, including business, more data-driven. In this ecosystem, with its emphasis on Big Data, there has been a focus on building business models for the provision of services, the so-called Internet of Services (IoS). These models assume the existence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated by any party. Different business models may support opportunities that generate revenue and value for various types of customers. This paper contributes to the literature by considering business models and opportunities for third-party data analysis services and discusses access to information generated by third parties in relation to Big Data techniques and potential business opportunities.

Data Analysis Services Related to the IoT and Big Data

2017 ◽  
Vol 9 (2) ◽  
pp. 37-56 ◽  
Author(s):  
Izabella V. Lokshina ◽  
Barbara J. Durkin ◽  
Cees J.M. Lanting
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Business Models ◽  
Third Party ◽  
Data Driven ◽  
Easy Access ◽  
Provision Of Services ◽  
And Control ◽  
Measurement And Control ◽  
The Internet Of Things

The Internet of Things (IoT) provides the tools for the development of a major, global data-driven ecosystem. When accessible to people and businesses, this information can make every area of life, including business, more data-driven. In this ecosystem, with its emphasis on Big Data, there has been a focus on building business models for the provision of services, the so-called Internet of Services (IoS). These models assume the existence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated by any party. Different business models may support opportunities that generate revenue and value for various types of customers. This paper contributes to the literature by considering business models and opportunities for third-party data analysis services and discusses access to information generated by third parties in relation to Big Data techniques and potential business opportunities.

Internet of Things and Big Data-Driven Data Analysis Services for Third Parties

2019 ◽  
pp. 256-289 ◽  
Author(s):  
Izabella V. Lokshina ◽  
Barbara J. Durkin ◽  
Cees J. M. Lanting
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Business Models ◽  
Management Practices ◽  
Data Driven ◽  
The Internet ◽  
Knowledge Based ◽  
Provision Of Services ◽  
New Business

Ubiquitous sensing devices, enabled by wireless sensor network (WSN) technologies, cut across every area of modern day living, affecting individuals and businesses and offering the ability to measure and understand environmental indicators. The proliferation of these devices in a communicating-actuating network creates the internet of things (IoT). The IoT provides the tools to establish a major global data-driven ecosystem with its emphasis on big data. Now business models may focus on the provision of services (i.e., the internet of services [IoS]). These models assume the presence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated. Different business models may support creating revenue and value for different types of customers. This chapter contributes to the literature by considering, for the first time, knowledge-based management practices, business models, new ventures, and new business opportunities for third-party data analysis services.

scholarly journals Personalisation as Currency

2015 ◽  
Vol 4 (1) ◽  
pp. 17-28
Author(s):  
Renée Ridgway
Keyword(s):  
Communication Networks ◽  
Business Models ◽  
Third Party ◽  
The Internet ◽  
Information Superhighway ◽  
Abstract Logic ◽  
Digital Capitalism ◽  
Nature Of Information ◽  
Cyber Space ◽  
Do So

‘Cybercapitalism’, commonly termed ‘digital capitalism’, refers to the Internet, or ‘cyber- space’ and seeks to engage in business models within this territory in order to make financial profit. Cybercapitalism is structured by a highly intricate series of communication networks, which connect us through our participation on social platforms, but outside of these platforms how do we navigate and explore this information superhighway? We do so predominantly through search requests. Algorithms ostensibly know what we want before we even type them, as with Google’s ‘autocomplete’. Thus search is not merely an abstract logic but a lived practice that helps manage and sort the nature of information we seek as well as the direction of our queries. Nowadays it has become clear that users pay for such services with their data, which is increasingly the means to finance various corporations’ growth as they sell this data to third party advertisers. It is a transaction and in the exchange we get relevance. But is this really true? 

scholarly journals eResearch:  Ethics, Security, Design, and Control in Psychological Research on the Internet

2016 ◽  
Author(s):  
Brian A. Nosek ◽  
Mahzarin R. Banaji ◽  
Anthony G. Greenwald
Keyword(s):  
Data Storage ◽  
Psychological Research ◽  
Third Party ◽  
Laboratory Research ◽  
The Internet ◽  
Security Design ◽  
Confidential Data ◽  
Internet Study ◽  
Data Transmission Security ◽  
And Control

Differences between traditional laboratory research and Internet-based research require review of basic issues of research methodology. These differences have implications for research ethics (e.g., absence of researcher, potential exposure of confidential data and/or identity to a third-party, guaranteed debriefing) and security (e.g., confidentiality and anonymity, security of data transmission, security of data storage, and tracking subjects over time). We also review basic design issues a researcher should consider before implementing an Internet study, including the problem of subject self-selection and loss of experimental control on the Internet laboratory. An additional challenge for Internet-based research is the increased opportunity for subject misbehavior, intentional or otherwise. We discuss methods to detect and minimize these threats to the validity of Internet-based research.

Privacy Concerns for Ubiquitous Data Aggregation and Storage

2014 ◽  
Author(s):  
Jarrod M. Rifkind ◽  
Seymour E. Goodman
Keyword(s):  
World Bank ◽  
High Performance ◽  
Business Models ◽  
The United States ◽  
Third Party ◽  
The Internet ◽  
Public And Private ◽  
Personal Lives ◽  
The Public ◽  
The World

Information technology has drastically changed the ways in which individuals are accounted for and monitored in societies. Over the past two decades, the United States and other countries worldwide have seen a tremendous increase in the number of individuals with access to the Internet. Data collected by the World Bank shows that 17.5 of every 100 people in the world had access to the Internet in 2006, and this number increased to 23.2 in 2008, 29.5 in 2010, and 32.8 in 2011 (World Bank 2012). According to the latest Cisco traffic report, Internet traffic exceeded 30 exabytes (1018 bytes) per month in 2011 and is expected to reach a zettabyte (1021 bytes) per month by 2015 (Cisco Systems 2011). Activities on the Web are no longer limited to seemingly noncontroversial practices like e-mail. The sheer growth of the Internet as a medium for communication and information sharing as well as the development of large, high-performance data centers have made it easier and less expensive for companies and governments to aggregate large amounts of data generated by individuals. Today, many people’s personal lives can be pieced together relatively easily according to their search histories and the information that they provide on social networking websites such as Facebook and Twitter. Therefore, technological breakthroughs associated with computing raise important questions regarding information security and the role of privacy in society. As individuals begin using the Internet for e-commerce, e-government, and a variety of other services, data about their activities has been collected and stored by entities in both the public and private sectors. For the private sector, consumer activities on the Internet provide lucrative information about user spending habits that can then be used to generate targeted advertisements. Companies have developed business models that rely on the sale of such information to third-party entities, whether they are other companies or the federal government. As for the public sector, data collection occurs through any exchange a government may have with its citizens.

The Circuits of Capital

Inland Shift ◽  
2018 ◽  
Author(s):  
Juan D. De Lara
Keyword(s):  
Radio Frequency Identification ◽  
Business Models ◽  
Management Practices ◽  
New Technologies ◽  
Third Party ◽  
Added Value ◽  
Scientific Management ◽  
Just In Time ◽  
Production And Distribution ◽  
Labor Regimes

Global economic restructuring, especially the geographic expansion of commodity networks during the 1990s and 2000s, had a profound effect on logistics workers. This chapter examines how companies used new technologies and scientific management techniques to produce labor regimes that cut costs and added value to distribution practices. Some of these technologies included barcodes, radio-frequency identification (RFID), and computer tracking software. Retailers used such technologies to develop sophisticated inventory systems and point-of-sale (POS) information databases that allowed them to implement just-in-time (JIT) production and distribution business models. In addition to these technological systems, retailers and third-party logistics companies (3PLs) or subcontractors also developed new just-in-time management practices and labor regimes. Less time and more goods became the mantra for retailers, who embraced shorter commodity cycles, dispersed production, and flexible labor.

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