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Book part
Publication date: 30 July 2018

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Marketing Management in Turkey
Type: Book
ISBN: 978-1-78714-558-0

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Article
Publication date: 15 May 2017

Khaldoon Al-Htaybat and Larissa von Alberti-Alhtaybat

The purpose of this paper is to investigate the phenomenon of Big Data and corporate reporting, and to determine the impact of Big Data and the current Big Data state of

Abstract

Purpose

The purpose of this paper is to investigate the phenomenon of Big Data and corporate reporting, and to determine the impact of Big Data and the current Big Data state of mind with regard to corporate reporting, what accountant and non-accountant participants’ perceptions are of the phenomenon, what the accountants’ role is and will be in this regard, and what opportunities and risks are associated with Big Data and corporate reporting. Furthermore, this study seeks to identify the inherent technological paradoxes of Big Data and corporate reporting.

Design/methodology/approach

The current study is qualitative in nature and assumes an interpretive stance, investigating participants’ perceptions of the phenomenon of Big Data and corporate reporting. To this end, interview data from 25 participants, video and text material, were analysed to enhance and triangulate findings. A four-fold sampling strategy was employed to ensure that any collected data would contribute to the findings. Data were analysed on the basis of open and selective coding stages. Data collection and analysis took place in two stages, in 2014 and in 2016.

Findings

Three topics, or categories, emerged from the data analysis, which have sufficient explanatory power to illustrate the phenomenon of Big Data and corporate reporting, namely the Big Data state of mind and corporate reporting, accountants’ role and future related to Big Data, and perceived opportunities and risks of Big Data. Features of a new approach to corporate reporting were identified and discussed. Furthermore, four paradoxes emerged to express inherent opposing positions of Big Data and corporate reporting, namely empowerment vs enslavement, fulfilling vs creating needs, reliability vs timeliness and simplicity vs complexity.

Originality/value

The original contribution of the study lies in the empirical investigation of the phenomenon of Big Data and corporate reporting as one of the most recent and praised developments in the accounting context. The dual communication flows of corporate reporting with Big Data is an important element of the findings, which can enhance the prospective financial statements significantly. Finally, technological paradoxes of Big Data and corporate reporting are discussed for the first time, two of which are based on the literature and the remaining two are inherent in the phenomenon of Big Data and corporate reporting.

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Accounting, Auditing & Accountability Journal, vol. 30 no. 4
Type: Research Article
ISSN: 0951-3574

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Article
Publication date: 1 June 1999

George K. Chacko

Gives an in depth view of the strategies pursued by the world’s leading chief executive officers in an attempt to provide guidance to new chief executives of today…

Abstract

Gives an in depth view of the strategies pursued by the world’s leading chief executive officers in an attempt to provide guidance to new chief executives of today. Considers the marketing strategies employed, together with the organizational structures used and looks at the universal concepts that can be applied to any product. Uses anecdotal evidence to formulate a number of theories which can be used to compare your company with the best in the world. Presents initial survival strategies and then looks at ways companies can broaden their boundaries through manipulation and choice. Covers a huge variety of case studies and examples together with a substantial question and answer section.

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Asia Pacific Journal of Marketing and Logistics, vol. 11 no. 2/3
Type: Research Article
ISSN: 1355-5855

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Article
Publication date: 1 June 2002

George K. Chacko

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade…

Abstract

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade Exchange for Auto Parts procurement by GM, Ford, Daimler‐Chrysler and Renault‐Nissan. Provides many case studies with regards to the adoption of technology and describes seven chief technology officer characteristics. Discusses common errors when companies invest in technology and considers the probabilities of success. Provides 175 questions and answers to reinforce the concepts introduced. States that this substantial journal is aimed primarily at the present and potential chief technology officer to assist their survival and success in national and international markets.

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Asia Pacific Journal of Marketing and Logistics, vol. 14 no. 2/3
Type: Research Article
ISSN: 1355-5855

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Book part
Publication date: 25 November 2019

Ryan Ziols

This chapter considers some of the limit points of contemporary relations between International Large-Scale Assessments, learning analytic platforms, and theories of mind

Abstract

This chapter considers some of the limit points of contemporary relations between International Large-Scale Assessments, learning analytic platforms, and theories of mind circulating in contemporary comparative and transnational educational policy discourses. First, aspects of the rise of Big Data and predictive analytics are historicized, with particular attention to how emergent notions of concepts like an intelligent educational economy paradoxically seem to offer unprecedented opportunities for personalizing education that increasingly rely on efforts to construct, universalize, and predict transnational benchmarks. Then, the chapter pursues how such efforts to universalize measures and predict changes have located the mind as a primary target for solving social problems through educational reform. More specifically, the emergence and circulation of the perceptron in the United States during the 1950s and 1960s is suggested as one example of how efforts to model the human mind as a neuro-dynamic learning system became entangled with efforts to produce universal, mobile, and adaptive neuro-dynamic learning systems targeting the transnational optimization of human minds.

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The Educational Intelligent Economy: Big Data, Artificial Intelligence, Machine Learning and the Internet of Things in Education
Type: Book
ISBN: 978-1-78754-853-4

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Article
Publication date: 26 October 2019

Islam Mohamed Hegazy

The purpose of this paper is the better understanding of the increasing relation between big data 2.0 and neuromarketing, particularly to influence election outcomes…

Abstract

Purpose

The purpose of this paper is the better understanding of the increasing relation between big data 2.0 and neuromarketing, particularly to influence election outcomes, along with a special aim to discuss some raised doubts about Trump’s presidential campaign 2016 and its ability to hijack American political consumers’ minds, and to direct their votes.

Design/methodology/approach

This paper combines deductive/inductive methodology to define the term of political neuromarketing 2.0 through a brief literature review of related concepts of big data 2.0, virtual identity and neuromarketing. It then applies a single qualitative case study by presenting the history and causes of online voter microtargeting in the USA, and analyzing the political neuromarketing 2.0 mechanisms adopted by Trump’s political campaign team in the 2016 presidential election.

Findings

Based on Trump’s political marketing mechanisms analysis, the paper believes that big data 2.0 and neuromarketing techniques played an unusual role in reading political consumers’ minds and helping the controversial candidate to meet one of the most unexpected victories in the presidential elections. Nevertheless, this paper argues that the ethics of using political neuromarketing 2.0 to sell candidates and its negative impacts on the quality of democracy are and will continue to be a subject of ongoing debates.

Originality/value

The marriage of big data 2.0 and political neuromarketing is a new interdisciplinary field of inquiry. This paper provides a useful introduction and further explanations for why and how Trump’s campaign defied initial loss predictions and attained victory during this election.

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Review of Economics and Political Science, vol. 6 no. 3
Type: Research Article
ISSN: 2356-9980

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Book part
Publication date: 24 May 2007

Frederic Carluer

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth

Abstract

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

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Managing Conflict in Economic Convergence of Regions in Greater Europe
Type: Book
ISBN: 978-1-84950-451-5

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Documents from the History of Economic Thought
Type: Book
ISBN: 978-0-7623-1423-2

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Article
Publication date: 7 May 2020

Eda Atasoy, Harun Bozna, Abdulvahap Sönmez, Ayşe Aydın Akkurt, Gamze Tuna Büyükköse and Mehmet Fırat

This study aims to investigate the futuristic visions of PhD students at Distance Education department of Anadolu University on the use of learning analytics (LA) and…

Abstract

Purpose

This study aims to investigate the futuristic visions of PhD students at Distance Education department of Anadolu University on the use of learning analytics (LA) and mobile technologies together.

Design/methodology/approach

This qualitative research study, designed in the single cross-section model, aimed to reveal futuristic visions of PhD students on the use of LA in mobile learning. In this respect, SCAMPER method, which is also known as a focused brainstorming technique, was used to collect data.

Findings

The findings of the study revealed that the use of LA in mobile can solve everyday problems ranging from health to education, enable personalized learning for each learner, offer a new type of evaluation and assessment and allow continuous feedback and feedforwards; yet this situation can also arise some ethical concerns since the big data collected can threaten the learners by interfering with their privacy, reaching their subconscious and manipulating them as well as the whole society by wars, mind games, political games, dictation and loss of humanity.

Research limitations/implications

The research is limited with the views of six participants. Also, the sample of the study is homogeneous in terms of their backgrounds – their age range, their departments as PhD students and their fields of expertise.

Practical implications

The positive perceptions of PhD students provide a ground for the active use of LA in mobile. Further, big data collected through LA can help educators and system makers to identify patterns which will enable tailored education for all. Also, use of LA in mobile learning may stimulate the development of a new education system including a new type of evaluation and assessment and continuous feedback and feedforwards.

Originality/value

The widespread use of mobile technologies opens new possibilities for LA in the future. The originality of this research comes from its focus on this critical point.

Details

Asian Association of Open Universities Journal, vol. 15 no. 2
Type: Research Article
ISSN: 1858-3431

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Article
Publication date: 3 January 2017

Rashid Mehmood, Royston Meriton, Gary Graham, Patrick Hennelly and Mukesh Kumar

The purpose of this paper is to advance knowledge of the transformative potential of big data on city-based transport models. The central question guiding this paper is…

Abstract

Purpose

The purpose of this paper is to advance knowledge of the transformative potential of big data on city-based transport models. The central question guiding this paper is: how could big data transform smart city transport operations? In answering this question the authors present initial results from a Markov study. However the authors also suggest caution in the transformation potential of big data and highlight the risks of city and organizational adoption. A theoretical framework is presented together with an associated scenario which guides the development of a Markov model.

Design/methodology/approach

A model with several scenarios is developed to explore a theoretical framework focussed on matching the transport demands (of people and freight mobility) with city transport service provision using big data. This model was designed to illustrate how sharing transport load (and capacity) in a smart city can improve efficiencies in meeting demand for city services.

Findings

This modelling study is an initial preliminary stage of the investigation in how big data could be used to redefine and enable new operational models. The study provides new understanding about load sharing and optimization in a smart city context. Basically the authors demonstrate how big data could be used to improve transport efficiency and lower externalities in a smart city. Further how improvement could take place by having a car free city environment, autonomous vehicles and shared resource capacity among providers.

Research limitations/implications

The research relied on a Markov model and the numerical solution of its steady state probabilities vector to illustrate the transformation of transport operations management (OM) in the future city context. More in depth analysis and more discrete modelling are clearly needed to assist in the implementation of big data initiatives and facilitate new innovations in OM. The work complements and extends that of Setia and Patel (2013), who theoretically link together information system design to operation absorptive capacity capabilities.

Practical implications

The study implies that transport operations would actually need to be re-organized so as to deal with lowering CO2 footprint. The logistic aspects could be seen as a move from individual firms optimizing their own transportation supply to a shared collaborative load and resourced system. Such ideas are radical changes driven by, or leading to more decentralized rather than having centralized transport solutions (Caplice, 2013).

Social implications

The growth of cities and urban areas in the twenty-first century has put more pressure on resources and conditions of urban life. This paper is an initial first step in building theory, knowledge and critical understanding of the social implications being posed by the growth in cities and the role that big data and smart cities could play in developing a resilient and sustainable transport city system.

Originality/value

Despite the importance of OM to big data implementation, for both practitioners and researchers, we have yet to see a systematic analysis of its implementation and its absorptive capacity contribution to building capabilities, at either city system or organizational levels. As such the Markov model makes a preliminary contribution to the literature integrating big data capabilities with OM capabilities and the resulting improvements in system absorptive capacity.

Details

International Journal of Operations & Production Management, vol. 37 no. 1
Type: Research Article
ISSN: 0144-3577

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