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Writer's picturePhillip Williams

Journal Critique

Updated: Jul 31, 2020




Names of the authors: Ducange, Pietro and Pecori, Riccardo and Mezzina, Paolo

Title of article: A glimpse on big data analytics in the framework of marketing strategies

Title of journal: Soft Computing| volume= 22 | number= 1| pages= (325-342)

year= (2018) | publisher= (Springer)

Statement of the problem or issue discussed

a. the authors set out to provide an understanding of the main concepts and issues regarding social big data, as well as their features and technologies.

b. They focus on marketing, describing an operative methodology to get insights from social big data.

c. They outline some open issues and suggestions in order to encourage further research in the field.

The title

The title of this journal gives the reader the impression that it will provide a comprehensive overview of the concept of Big Date and how it is used particularly with in the marketing field, to this end the contents of the document does live up to the expectations of the title.

The abstract

After reading the abstract, one can get a clear sequence of the information discussed in the document and the order in which it is laid out. What is missing however is the fact that the authors included quite a number of illustrations to which mention should have been made in the abstract since it could prove useful for a researcher.

Purpose

The authors speak clearly and concisely to the purpose in paragraph 4 of a 7- paragraph introduction and states the intention of the 5 -section paper. The remainder of the introduction provides a backdrop against which the authors provide some clarity to key concepts and words used in the document.

The discussion

In the body of the document the authors provide an easy to read approach and were key to explain any new concepts and abreactions. Most of the discussion was relevant and pulled on relatable real-world case studies to support the points made however, the presentation of the table data could be considered overwhelming and may have been better represented in more of a summarized format.

Author’s bias and assumptions

The Authors presented the facts about Big data and relied on mostly supporting data that confirms to the benefits of big data. There were no deliberate attempts to highlight the demerits of the topic instead, the Authors aim was to educate the readers on the benefits and possible usage of the big date information. In my judgement the tone of the writers seems to be pro big data and to this end they can be criticized for not being completely value free and exhibiting confirmation bias in their approach. Additionally, the assumption is made that the reader is interested in understanding big data and its application for marketing and to this end the language caters to a reader with a fundamental background in marketing and or sales.

Major Conclusions.

What can be concluded is that social big data is no more a niche topic nowadays, but rather a proper phenomenon capable of radically changing the world and to promote a great variety of benefits:

1. increase of operating margin,

2. growth in the available jobs and working positions,

3. the growth in market figures,

4. the escalation of on-time decisions and saved time,

5. the boost in digitally generated data

6. customer experience-driven promotions

The authors concluded that current development is still far from a single centralized, holistic and rigorous platform having a few buttons through which a marketer can take relevant decisions for his future market strategies.

General Concussions

Overall the authors have demonstrated a clear and well though out writing structure. Their aim was to fill the gap in knowledge of big date and marketing and they have certainly provided valuable information. In between the writing they provided tables with references to the reference papers on big data however the placement of these tables proved distracting and overwhelming. It was difficult to identify referencing errors but the interpretation of the refences appeared to be accurate since 85% of the references revolved around big data and the benefits to be derived.

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