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How to enhance organizational creativity by analyzing new
knowledge sources to gain competitive advantage
Maria Mach-Król*
Katowice University of Economics, Bogucicka 3, 40-226 Katowice, Poland
Abstract
The main aim of the paper is to discuss the role of web data and big data analysis in achieving, and maintaining competitive
advantage by an organization. Any organization that wants to succeed must be able to make the most of massive influx of
information: to analyze it in almost real time, to process it and to make decisions on its basis. Thus, the paper is an attempt to
answer the question, how to effectively analyze business environment and information coming from it, in order to enhance
organizational creativity, and – in consequence – to achieve and to maintain competitive advantage. The main research findings
of the paper are several recommendations, elaborated by the author, how to efficiently analyze business environment to enhance
organizational creativity and establish a sustained competitive advantage. The research methods and techniques used to write the
paper encompassed method of critical analysis of literature, creative thinking, and an interpretive philosophy.
© 2016 The Authors. Published by ISCDBU Inc.
Selection and peer-review under responsibility of the Organizing Committee of ISCDBU.
Keywords: big data; web mining; organizational creativity; competitive advantage; business environment
1. Introduction and motivation
Modern enterprises often operate on global markets, in turbulent and uncertain business environment. They must
face competitive forces coming from other producers, from suppliers, and – above all – from new technologies,
products and services. Therefore competitive analysis of environment has been for long time of a great interest.
About 1990 Norbert Wiener introduced the notion of “knowledge society” (Breton, 2005), p. 47. In consequence,
knowledge has been perceived as an important asset of any organization, strictly connected with its innovativeness.
Amabile (1988, 1996), and others – see e.g. (Yao & Fan, 2015) – linked innovativeness and competitiveness with
organizational creativity: organization is the more competitive, the more it is creative. A precise definition of the
notion of creativity states that it is “the ability to produce work that is both novel (i.e. original, unexpected) and
appropriate (i.e. useful, adaptive concerning task and constraints)” (Sternberg, 1999). This applies of course also to
organizational creativity, with the addition, that it is commonly perceived as a team, dynamic activity, responding to
changing features of organization’s environment, a team process – see e.g. (Unsworth, 2001), (Andriopoulos &
Dawson, 2014).
While analyzing business environment in order to enhance organizational creativity, it is extremely important to
pay attention to technological and competitive environments. The former may give information on technological
changes and trends in industry, the latter concerns probable strategic movements of direct competitors. Conclusions
from both forms of analyzes affect organizational creativity, because its role is to generate ideas on e.g. new
© 2016 The Authors. Published by ISCDBU Inc.
Selection and peer-review under responsibility of the Organizing Committee of ISCDBU.
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products, services or business processes. If organizational creativity is put in the context of business environment
analysis, new ideas may better fit market challenges and trends.
On the other hand, nowadays data, information, and knowledge used to analyze different aspects of business
environment come from new sources, which can be – generally speaking – found in the web. These are e.g. web
pages, fan pages, but also zettabytes of data commonly known as big data. As sources change, so do analysis tools
and techniques.
The main aim of the paper is to discuss the role of web data and big data analysis in achieving, and maintaining
competitive advantage by an organization. The topic is important, as modern organizations operate in environments
characterized by turbulences, permanent changes, and above all by the constant influx of massive amounts of
information. Any organization that wants to succeed must be able to make the most of this information flow: to
analyze it in almost real time, to process it and to make decisions on its basis. It is a critical component of success.
Thus, the paper is an attempt to answer the question, how to effectively analyze business environment and
information coming from it, in order to enhance organizational creativity, and – in consequence – to achieve and to
maintain competitive advantage.
The paper is organized as follows. In section 2 innovations and organizational creativity as the sources of
competitive advantage are described. Section 3 is devoted to new sources of knowledge, mainly unstructured web
ones, and their role in acquiring knowledge on innovations in industry. Section 4 presents several recommendations,
elaborated by the author, how to efficiently analyze business environment to enhance organizational creativity and
establish a sustained competitive advantage. In section 5 related work is described. The last section is devoted to
conclusions, and future research directions.
The research methods and techniques used to write the paper encompassed: method of critical analysis of
literature, creative thinking, and an interpretive philosophy. The sources of information included literature from the
field of strategic management, computer science, and management information systems. Research reports and
expertise opinions from different research institutions were also used.
2. Innovations and organizational creativity as a source of competitive advantage
There are many definitions of competitive advantage, here we cite the one presented in (Campbell, et al., 2012) –
after (Peteraf & Barney, 2003), according to which a firm achieves a competitive advantage if it is able to create
more economic value, than the marginal (breakeven) competitor” (p. 377).
Although there can be many sources of competitive advantage, in the literature from both strategic management
and knowledge management, it is commonly accepted, that such assets as human capital, and precious knowledge of
employees may contribute to sustainable competitive advantage of the firm – see e.g. (Campbell, et al., 2012).
According to these authors, it may be assumed, that organizational creativity, being the effect of organization’s high
quality human capital, turns into organization’s sustainable competitive advantage.
Let us look at the sources listed by a consulting firm (Partners Creating Growth, 2013):
 Localization in global markets;
 Strategic alliances or acquisitions;
 Competitive actions;
 Customer clusters;
 Company-wide market orientation;
 Strategic fit between marketing and manufacturing;
 Implementation of strategy;
 Human capital;
 Employee engagement;
 Technological change (innovations);
 Business analytics;
 Production systems;
 Business processes;
 National export promotion.
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In the work cited the sources mentioned above are discussed in detail. It should be noted, that on the above list
human capital and innovations are almost listed together. It thus indicates, that organizational creativity, and
innovations linked with it constitute an important source of obtaining and maintaining advantage over firm’s
competitors. Research confirms this statement: e.g. in fig. 1 the role of creativity and innovativeness in gaining
competitive advantage is shown.
Fig. 1. Sources of competitive advantage. Based on (Grant, 2013), p. 156.
If by innovation we understand not only technological changes and improvements, but first of all their practical
applications, then the human factor is the essential element of the innovation process, because people create new
ideas – by analyzing internal and external environment – and thus the ideas may concur to organization’s
competitive advantage (Urbancová, 2013). Innovations would play this role, if e.g. (ibid., p. 84):
 New products help maintain market shares and improve profitability.
 Growth also by means of non-price factors (design, quality, individualization, etc.);
 Ability to substitute outdated products (shortening of product lifecycles);
 Innovation of processes that lead to production time shortening and speed up new product development in
comparison to competitors.
Depending on the source, there are “pull”, and “push” innovations (Brem, et al., 2016). The former are developed
and introduced in response to market’s needs, and this is why tracking trends and consumers’ requirements is so
important. The latter are independent from market’s needs, these are rather technological novelties, for which
market demand has to be created.
The same authors divide innovations also according to the scope of the change criterion. Incremental innovations
are implemented relatively quickly and with relatively low risk, these are e.g. new versions of previously known
products; radical innovations, in turn, are connected with key changes, but also with great risk.
Already Porter (1990) pointed out the fact that innovations may be and should be a way for obtaining competitive
advantage; his idea was then connected with the resource approach and with the approach stating, that creative
members of organization are responsible for its capabilities, while resources are equal to innovations (Brem, et al.,
2016), p. 139. It has to be noted, however, that innovations will the more result in competitive advantage, the more
they will be an effect of organization’s opening to ideas coming from competitive environment – see e.g. research
presented in (Reed, et al., 2012). Thus continuous monitoring of this environment and analysis of collected data is
extremely important.
Innovations are obviously dependent on creative ideas being generated in organization, that is, on organizational
creativity processes. This is why e.g. authors of (Im, et al., 2013) stress the role of (organizational) creativity in
obtaining competitive advantage, in this case of a product. Moreover they prove, that the creativity level of
organization enables to predict the results of implementing the given innovation.
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In fig. 2 a fragment of the model presented in (Im, et al., 2013) is shown. In the original version it concerns
competitive advantage in the product dimension, but in our opinion may be easily generalized. What is important,
the model shows the role of creativity and novelty (innovativeness), together with enterprise’s environment
characteristics, in obtaining of competitive advantage.
Fig. 2. Connection between selected aspects of organizational creativity, and competitive advantage in product dimension. Based on (Im, et al.,
2013), p. 173. NP – new product; MP – marketing program.
3. Web sources analysis in the process of acquiring knowledge about innovations in competitive environment
Web is nowadays one of the main sources of knowledge about competitors in industry – both in the aspect of
innovations, and in the aspect of strategic planning. It is the place, where enterprises maintain their official sites,
where they seek for employees, where they maintain the so-called fan pages, used to communicate with their
customers, and business partners. Thus the web is an important source of knowledge about industry, and hence the
growing popularity of web mining – using data mining techniques to automatically extract information and
knowledge from documents and web services – see (Kantardzic, 2011) p. 301; these documents may be in
structured, semi structured or unstructured form (Dubey & Namdeo, 2015). The web mining process is composed of
four tasks (Kantardzic, 2011):
1. Finding of relevant resources;
2. Choosing and preprocessing of information;
3. Generalizing with the use of data mining techniques;
4. Analysis of discovered information/knowledge.
Generally, depending on the web element being mined, the following web mining sub-genres may be
distinguished:
 Web content mining – mining of documents found in the web;
 Web structure mining – mining of linkages between documents in the web;
 Web usage mining – examining the ways users browse the web.
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As research has shown, data acquired from the web by its mining give significantly better results (in the context
of searching for innovations) than data/knowledge acquired from such sources, as e.g. patent databases, or scientific
publications (Gök, et al., 2015), p. 653. According to the authors cited, companies’ web pages constitute a very
valuable source of information, providing information on products, services, and even strategies. It is obvious, that
the most useful technique here is document mining, which in this case equals to web content mining. A sample
process of mining knowledge about innovations in the web is presented in fig. 3.
Fig. 3. The process of web content mining aimed at innovation exploring. (Gök, et al., 2015), p. 660.
The web content mining task is also strictly connected with text mining. As Kantardzic (2011) writes, even 80%
of information about a company may be contained in various text documents (p. 318), which in turn are the more
and more often available in textual form. Text mining and web mining are the more closer, the more knowledge may
be found in such sources as e.g. social media (Erl, et al., 2015), p. 196. The text mining and analyzing techniques
gain importance because blogs, Twitter, Facebook or discussion forums constitute a valuable source of
information/knowledge on consumers’ opinions. Even a new research domain is born, named opinion mining, or
more broadly – sentiment analysis.
The data coming from unstructured sources mentioned above – social networks – but also from e.g. web
clickstreams, shop videos, call center recordings, sensors, RFID, and other devices are generally characterized with
an adjective “big”. The authors of (Provost & Fawcett, 2013) introduce the notion of “data science” to describe the
way of analyzing big data. They define this notion as a set of rules regulating acquisition of information and
knowledge from data, and link it with data mining rules. Big data thus is for modern organizations both a natural
resource, digital inventory, and a more detailed insight into the past (Conway & Klabjan, 2013).
Russom (2011) suggests, that to efficiently analyze big data sources, organization should primarily use advanced
visualization tools, advanced analytics tools, text mining tools, or tools enabling to combine big data with data
warehouse.
Taking into consideration heterogeneous and unstructured nature of data and knowledge that form big data
sources, the artificial intelligence techniques gain great importance. These are primarily natural language processing
techniques aimed at analyzing blogs and forums; machine learning techniques; graph analysis techniques, and
similar ones (Lohr, 2012) (Elbattah, et al., 2013). Especially the graph analysis is a good choice in case of problems
that do not require processing of all available data.
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4. Recommendations for efficient analysis of new knowledge sources
As already said, modern competitive environment creates completely new challenges for organizations, such as
dynamics, turbulences or intermittency. Similar challenges concern also the analysis of this environment, because
the most important question nowadays is to track and to anticipate changes concerning innovations, technology or
services. At the same time research shows that innovativeness, and the creativity level of organization strongly
affect its ability to gain, and to maintain competitive advantage. Hence it is extremely important that modern
analysis of organization’s environment support organizational creativity. From such perspective, the
recommendations for effective analysis of competitive environment, based on new knowledge sources, may be
divided into three groups.
First, recommendations concerning analytical process itself. Here, attention should be first of all paid to:
 Dynamics of market features;
 Innovations;
 Current changes in the market (current trends);
 Anticipated changes.
Thus, emphasis should be put on modern methods of Competitive Intelligence, principally those concerning big
data analysis; and on modern methods/techniques of environment analysis, e.g. shadowing.
Second, recommendations concerning appropriate IT equipment. Keeping in mind challenges of modern
competitive environment analysis in the context of organizational creativity, we suggest the following IT solutions:
 IT solutions capable of accommodating environment’s dynamics, such as e.g. temporal databases, temporal
knowledge base systems, real time data warehouses;
 Advanced analytical business IT tools, e.g. Business Intelligence solutions, data mining solutions, intelligent
systems;
 IT solutions capable of analyzing new data types, as web data, big data – e.g. Hadoop, and other.
Third, recommendations concerning the choice of data sources. Formerly the typical sources for competitor
analysis were e.g. reports, patents, etc., but nowadays these sources are obviously insufficient, because of the pace
of changes on the markets, in competitors’ offerings, and in consumers’ expectations. Thus the good sources
nowadays are e.g.:
 Semantic Web;
 Social networks;
 Web forums;
 Opinion portals;
 Companies’ fan pages;
 Companies’ web pages.
These belong all to the broad category of big data. As already pointed out in Section 3, the specific nature of this
data (no structure, real-time influx, huge volume, etc.) needs new IT solutions capable of storing, processing, and
visualizing it. More detailed discussion on big data, and the ways to process it and analyze may be found e.g. in (Erl,
et al., 2015).
5. Related work
In (Lai, et al., 2015) a system called ISSWM is proposed to analyze social media. It combines search techniques
witch machine learning ones (e.g. k-NN, clustering). Anand, et al. (2015) present a system for intelligent
information mining from the web, using multi-agent technology. Such solution enables to dynamically adapt the
mined content to user’s needs, and to adjust its size.
Małyszko and Filipowska (2013) propose to build and develop sources for sentiment analysis, while Węckowski
(2013) presents a concept of a web crawler, which indexes web pages, taking into consideration their usability for
business analyses, and handles changes in these pages. There are also proposals to use techniques elaborated as part
of Semantic Web analysis (Bizer, et al., 2011), p. 58-59.
Combination of data on web traffic, and statistic and/or data mining tools may give new, valuable knowledge on
behaviors and behavioral patterns of huge number of users (Lazer, et al., 2009). (McKelvey, et al., 2012) present in
Maria Mach-Król/ Procedia - Social and Behavioral Sciences 00 (2016) 000–000
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turn an interactive cockpit for studying communication processes on Twitter. The tool is based on Truthy
architecture, initially built for tracking political discussions on this microblogging platform. It contains several
analytical components, as e.g. discussion visualization, detailed activity, sentiments, languages, and communication
channels metrics, etc. Its interface is equipped with filters, and searching/sorting tools, that allow for quick statistical
comparisons of attributes assigned to given Twitter users. An interesting survey on solutions for social media
analyzing can be found in (Cambria, et al., 2014).
(Dubey & Namdeo, 2015) propose web knowledge searching, based on ontologies, and on the concept of
Semantic Web, which means extending the web with standards for a web of data/information/knowledge that can be
easily processed by machines (Berners-Lee, et al., 2001).
6. Conclusions and future research directions
The paper focused on the problem of achieving and maintaining a sustainable competitive advantage, by
combining the analysis of modern knowledge sources (web and big data ones) with the questions of organization’s
innovativeness, and processes of organizational creativity. We have shown, that knowledge on innovations that can
be found in modern sources, affects creativity in organizations, which in turn affects their competitiveness.
We have discussed the role of web data and big data analysis in achieving, and maintaining competitive
advantage by an organization. The main research question of the paper was how to effectively analyze business
environment and information coming from it, in order to enhance organizational creativity, and – in consequence –
to achieve and to maintain competitive advantage. We have answered this question by formulating several
recommendations, concerning different analytical aspects, how to efficiently analyze business environment to
enhance organizational creativity and establish a sustained competitive advantage. Dividing the recommendations
into three groups gives interested organizations the possibility to fully adapt their analytical processes to the
challenges of modern business environment, to introduce the analytics which will buoy up organizational creativity,
and in consequence will contribute to their competitive advantage.
The planned future research directions concern checking practical analytical solutions. The research team plans to
create a hybrid analytical tool which would collect, filter, and analyze knowledge from the web in order to anticipate
innovations planned by competitors. This can be done e.g. by analyzing competences required in web job ads.
Acknowledgements
This paper has been supported by a grant: „Methodology for Computer Supported Organizational Creativity”
from National Science Centre in Poland, 2013/09B/HS4/00473.
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