Reputational intelligence: innovating brand management through social media data

Pages40-56
Date07 November 2019
Published date07 November 2019
DOIhttps://doi.org/10.1108/IMDS-03-2019-0145
AuthorAna-María Casado-Molina,Celia M.Q. Ramos,María-Mercedes Rojas-de-Gracia,José Ignacio Peláez Sánchez
Subject MatterInformation & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems
Reputational intelligence:
innovating brand management
through social media data
Ana-María Casado-Molina
Department of Economics and Business Administration,
University of Malaga, Malaga, Spain and
School of Management, Hospitality and Tourism,
University of Algarve, Faro, Portugal
Celia M.Q. Ramos
School of Management, Hospitality and Tourism,
University of Algarve, Faro, Portugal
María-Mercedes Rojas-de-Gracia
Department of Economics and Business Administration,
University of Malaga, Malaga, Spain, and
José Ignacio Peláez Sánchez
Department of Computer Sciences and Languages,
Higher Technical School of Computer Science,
University of Malaga, Malaga, Spain
Abstract
Purpose Companies are currently facing the challenge of understanding how their business is affected by
the large volume of opinions continually generated by their stakeholders in social media regarding their
intangible assets (experiences, emotions and attitudes). With this in mind, the purpose of this paper is to
present an innovative management model, named E2AB, to measure and analyse reputational intangibles
from digital ecosystems and their impacts on tangible assets.
Design/methodology/approach The methodology applied was big data and business intelligence
techniques. These methods were used in the computing process to obtain daily data from every asset
guarantees that the model is validated with robust data. This model has been corroborated using data from
the banking sector, specifically 402,383 net data inputs from the digital ecosystems.
Findings This study illustrates the existence of a holistic influence of intangible assets over tangible
assets. The findings demonstrate complex relationships between tangible and intangible assets, determined
not only by the type of variable but also by its valence and intensity.
Practical implications These findings may help chief communication officers and general managers a
better understanding of how intangible assets extracted from online usersopinions are related to their
organisations tangible assets plus a chance to find out about their impact and how to manage them for a
practical and agile decision making in real time.
Originality/value It is a pioneering work in establishing a model, which demonstrates transversal and
holistic relationships between relational intangible and tangible assets of firms from digital ecosystems, using
business intelligence techniques.
Keywords Business intelligence, Social media data, Reputational intelligence, Reputational model,
Intangible management, Customer perceptions
Paper type Research paper
Industrial Management & Data
Systems
Vol. 120 No. 1, 2020
pp. 40-56
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-03-2019-0145
Received 16 March 2019
Revised 28 June 2019
Accepted 9 October 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
This work was supported by the University of Malaga, through grant project (PPIT.UMA.B1.2017/05)
Diagnosis and Positioning of SMIs. This paper was also financed by National Funds provided by
FCT Foundation for Science and Technology through the CIEO project (UID/SOC/04020/2019) and
project CEFAGE (UID/ECO/04007/2019).
40
IMDS
120,1
Introduction
All organisations are interested in controlling their reputation, but this is becoming
increasingly difficult due to the big data expressed by society on social networks ( Ji et al.,
2017). It has already been stated in the literature on the subject that reputation, even though
it has much influence on the creation of value and economic benefits for organisations
(De Quevedo et al., 2005), is difficult to measure (Groenland, 2002). This is because it is
constructed from the perceptions that interest groups have of companies, based on the
experiences, emotions and attitudes that these provoke in their audiences (Fombrun and
Gardberg, 2003). Such perceptions are often transmitted and published verbally in various
online and offline media (Arbelo and Pérez, 2001).
Even when academic studies exist that define some measurements of reputation in online
contexts (Azzeh, 2017; Casimiro and Coelho, 2017; Dutot and Castellano, 2015), they do not
study how the perceptions of stakeholders extracted from the internet could influence the
business of organisations. These perceptions, which are very difficult to measure, are part of
the so-called intangible assets of companies, while their business is framed within their
tangible assets. From a management perspective, intangible assets are defined as the
intellectual capital that provides a company with a competitive advantage (Edvinsson and
Malone, 1997). Of particular importance among such assets is relational capital, this being
understood as the set of relationships that companies maintain with their stakeholders
(Bontis et al., 2000). This capital is extracted from the experiences, emotions and attitudes of
individuals in the context of the relations they maintain with organisations (Diefenbach,
2006). As for tangible assets, these basically comprise the economic resources that are a part
of the companys balance sheet (Garcia-Parra et al., 2007), the stock market price or the price
of shares being particularly important as both are relevant indicators of a companys value
(Ansotegui, 2010).
One important question is how could we measure the impact of relational intangibles
from digital ecosystems on the companiestangible assets? Due to the immediacy and the
large volumes of data handled in digital conversations, measurement tools should
incorporate not only data in real time but also offer robust and representative data.
Companies have often used online data simply to monitor their reputation in this context.
However, the way of integrating all this information and using it as a business performance
indicator remains an unresolved matter. This is precisely where the originality of this work
lies: the construction and validation of a model that analyses the relationship of intangible
assets with each other and with the stock market price. This is possible thanks to big data
and business intelligence techniques, which allow us to extract a large volume of qualitative
data from the internet and convert them into quantitative data that are integrated into the
proposed model.
Conceptual background
Models to manage the relational intangibles assets in digital environments
There is extensive literature on how to construct models to manage perceptions (Elshwikh,
2017; Ingenhoff and Buhmann, 2016; Money et al., 2010) and much research has been done
on reputation management (Eckert, 2017). Reputation models have identified the causes of
this in terms of the good or bad experiences of stakeholders with firms, and their
consequences in terms of favourable or unfavourable attitudes towards the brand, but
without considering the economic impact (Ponzi et al., 2011; Money et al., 2010). Other
authors have been content to establish relationships between intangibles and tangibles,
albeit without proposing a model (Brown et al., 2009; Gabbioneta et al., 2011; Stuebs and Sun,
2011; Wang et al., 2010). None of the studies discuss how these tangible and intangible
relational capital assets can influence each other, nor their holistic effect on the company as
a whole and on different business areas (Eckert, 2017; Ponzi et al., 2011).
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Reputational
intelligence

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