Cloud platforms and Collaborative advantage: Knowledge creation and Learning in Dynamic Network Organizations
Abstract
Within the context of virtual
organization, Knowledge Management is subject to some drastic
transformations related to rapid
technological innovation such as cloud
computing platforms, increasing globalization, evolution of technological
capabilities, and analytical
developments of network approach. Research paper
study forms, functions and effectiveness of single-firm strategies with the key
players in its process-oriented working
environment. An ontological-based approach was used in order to
investigate relationship in three dimensions: knowledge
creation, learning and collaboration.
I gathering data from a literature review, from
online Google survey and from websites of four different companies which aims
to use cloud integration with Google platform. Results
show that trust and deep commitment developed through processes enhanced
transformation of co-operation into collaboration. As a future research I
purpose measure of innovative output of knowledge creation, learning and collaboration trough patents for technology other then
cloud computing platforms.
Keywords: Knowledge
creation; Collaboration; Learning; Dynamic network; Cloud platforms;
I. Introduction
The purpose of
paper is to understand more fully the forms, functions and effectiveness of
inter-firm strategies and how a group functions may focus on single-firm and
relationship with key players in its environment (Ancona & Caldwell, 1992).
The vast amount of literature offers an extremely diverse collection of
collaborative forms, where researchers given attention relate to business
concepts such as knowledge management, flexible or dynamic networking, agile
competition, business process redesign, new products or service design and
supply web. The aim describe Google platforms delivery of a product or service
to the customer or organization, through dynamic network which again uses
information and communication technology, vertical integration, and globalization
(Camarinha-Matos et al., 2003; Grimshaw and Kwok, 1998).
Main goals is to improve process-oriented working
environment for knowledge creation, learning and collaboration, and to deeper understanding
what a virtual organization form is and how it is organized trough
technologically intensive fields such as cloud computing platforms, data
mining, distributed file systems, and the Internet. Network approach
include non-equity strategic alliances, interfirm
relationships, network position, growth, and portfolios of collaborative
activities.
I attempted to map
out, or explain more fully triangulation which involving three-dimension ‘size
growth’, ‘relationship growth’, and ‘dynamic capability growth’ (Cohen & Manion, 2000)
by following methods of Gauvin (2005) which includes three phases: (1) establishing an
ontological model for knowledge
creation, learning and collaboration, (2) gathering the
meanings both from a literature review and from online survey and (3) the
analysis and comparison of findings. I assumed that direct network creates a positive externality, and that consumers
may value a product more if similar consumers or group
of economic agents use that product as well (Gawer, 2011; [1]). I study relation between Google and four different primarily technology-driven
companies: Agosto, Ezakus, Gigya, and ShareThis, which are part of the program
Google Certified Ad Networks. Main focus of this companies are driven by
businesses' needs to reduce costs and increase efficiency, expanded company
offerings, and improve competitive positions. In
terms of the dataset, I use qualitative
survey analysis, from Google website and from partners websites, for the exploration
of meanings and experiences, observed social interactions or communications
between two companies.
My results show that deeper levels of commitment and trust
developed through personal relationships enhanced transformation of
co-operation into collaboration. Learning as either gaining knowledge or
acquiring new competencies and skills, expanding individual’s experience from
past experience. Collaboration as a transfer of knowledge
between firms help to improve the efficiency,
effectiveness and productivity of internal processes [2].
I
organized my paper, in Chapter I introduction, Chapter II literatures review,
writing about knowledge creation, collaboration,
learning, dynamic network, creating
ontology map and relationship between different assets. In Chapter III, I
presented research method. In Chapter IV, I used case study method for four
different primarily technology-driven companies: Agosto, Ezakus, Gigya,
and ShareThis, explained integration of cloud computing technology in there structure,
inter-firm relationship, collaboration and experience which they gain through
the process. In Chapter V, I summered results. In Chapter VI, I write about
limitation and stated some future expectations.
II. Background
A move back towards the resource-based view (RBV)
in the beginning on 21st millennium, superior knowledge of
single-firm and corporate dynamic capabilities become
the ‘King’ between all biggest competitive advantages (Mowshowitz, 1986).
Following the RBV precept that ‘success breeds success’ when firms enjoy asset
mass efficiencies, organizational knowledge processes become the predominant
paradigm for the firm activities, where new principles such as multiplication and combination, integration,
sharing of knowledge (Pettigrew and
Evelyn, 2000) and adding value,
become firm’s strategic management capability, imperative to quickly
orchestrate and reconfigure externally sourced competences while leveraging
internal resources (Kungu, 2013) such as unique,
valuable, and portable new growth platform, know-how and
know-who, user communities and digital, social and mobile networks (Dierickx
& Cool, 1989; [3]; Shuen,
2008). Transaction costs economics
(Williamson, 1975; 1985) and Agency theory (Fama, 1980;
Jensen & Meckling, 1976), helps swing the strategic
management pendulum further away from the industry level, treating equity joint
ventures and minority equity investments as a single category (Pisano, 1989).
Inside the RBV
black box of the firm, the theory of Dynamic
Capabilities is a highly integrative theory of the firm ability to ‘integrate,
build, and reconfigure internal and external competences to address rapidly
changing environments (Pisano 1989; Amy Shuen, 2008; Teece [4]). In comparison with the earlier industrial
organization view (Bain, 1955; Porter, 1990) and the RBV (Wernerfelt, 1984), the dynamic capabilities view assigns a
prominent role to the entrepreneurial decision-makers in the strategy formulation
and implementation of sustainable competitive advantage. The dynamic capabilities view
(Bain, 1959) suggests that the firm needs to develop new
capabilities, change rapidly, search for new strategies, identify opportunities
and respond quickly to them (Jarvenpaa & Leidner, 1998), highly specialized and innovative process
capabilities and creating defensible positions against competitive forces. The
manner in which dynamic capabilities take form is shaped by the individuals who
bring internal assets such as positive values
and identities, social competencies, and commitment to learning that can
be leveraged from outside the firm that these persons somehow have access to (Weerawardena, 2007).
The important role
of played by networks as mechanisms has been explained by the Actor- Network
Theory of innovation. Theory involves processes of learning
that are knowledge and know-how based, and are instrumental in knowledge
creation, integration, configuration and utilization.
The Dynamic Stability Model was created as a framework to assist managers to
adapt their organizations to a turbulent
and changing world in a wide range of fields
including Business Strategy, Strategic Management, Knowledge Management,
Technology Management, Technology Strategy, Systems Thinking, Enterprise
Architecture or Enterprise Engineering and others [5]. The capacity of an organization to purposefully create,
extend, or modify its resource base was followed
with two types of strategies: ‘mass production’ and ‘invention’.
To deeper
understanding what a virtual organization is, how it is organized trough
technologically intensive fields, and to improve process-oriented environment,
I conduct future study in three
dimension: knowledge creation, learning and collaboration.
I attempted to map out, or explain more fully company triangulation and
inter-firm relationship with key players in its environment.
Knowladge creation
The relationship of firms with the
environment emerged with the systems theory Katz and Kahn (1970). Emery and Trist (1965) stated that organization structure should
be combined to create better external
environment needs and roles performed. Following Miles et al., (1986) and Powell (1990), Pateli (2009) stated: “On the one hand, knowledge
required to compete in emerging technology-based markets is becoming more
diverse as markets converge and industries collide. On the other hand, firms
are narrowing their knowledge base in an effort to specialize and create
incentives for learning and the dissemination of information, allowing ideas to
be translated into action quickly” (p. 1). Rapid technological innovation, increasing globalization, evolution
of technological capabilities, analytical developments of network approach and capability to
learn continuously creates on that way new dimensions of knowledge. To improve organizational performance and reduce costs, knowledge
management need to enabling individuals to create,
capture, use and share their collective knowledge to make optimal
decisions […] in real time’ (Smith and Farquhar, 2000). Jones
(2001) and Smith
(2001) proposed value proposition-based approach to knowledge management that creating a supportive environment such
as culture, technology, infrastructure, and measurement, where main steps in
implementing a change process are trough planning, design, implementation, and
scalability. The processes of knowledge management involve ‘knowledge
acquisition, creation, refinement, storage, transfer, sharing, and utilization’
(King, 2009).
In contrast to
knowledge creation, knowledge acquisition involves the search for, recognition
of, and assimilation of potentially valuable knowledge, often from outside the
organization (Huber, 1991).
Canary at.el. (2010) state that the company quickly became
focused on technological priorities such as “the need for innovation,
technology solutions, users, platforms, and course templates replaced
educational discourse”. ‘Acquisition’ illustrate firm's
ability to identify and acquire knowledge from
external sources in order to develop new
products (Huber, 1991). The best of joint ventures are, above all,
powerful strategic alliances that have these strategic, structural, and
operational characteristics: synergistic, strategic, separate management and
organization, tight operating linkages, beyond win-win, reciprocal
relationships (Morris 1998).
Most of the
literature assumes that, if large
firms as providers of knowledge with high absorptive capacities and high
R&D expenditures
are willing to modify attitudes
and approaches, they will able to engage constructively with local counterparts
(Tan, 2012). Certain firms may
appear as ‘technological gatekeepers’ while being strongly connected to
external sources of knowledge; and may be
crucial to transferring knowledge while being strongly connected to
external sources of knowledge; others are ‘active mutual exchangers’, i.e. characterized by the right balance
of absorption and diffusion of knowledge, while others still may appear to play
the role of ‘weak mutual exchangers’ with a balanced role of absorber (Lazaric at.el.,
2008). Some researchers such as Byosiere and
Luethge, (2004); Nonaka et al., (2000) and Rai (2001) proposes that ‘the internalization mode is
the process where explicit knowledge is embodied and internalized through
knowledge interpretation and is converted into tacit knowledge’ (p. 783).
Under all this
assumption I conceptual semantic ontology
model of knowledge creation, in which collaboration and learning objects are created, evaluated and used (See Figure 1).
Figure 1. Ontology model of Knowledge creation
Source:
Gauvin, M., et al. (2005).
According to the model main providers which orchestrate networks and
access external flows of knowledge by making significant investments in
searching, learning and diffusing knowledge could support local counterparts to much easily access
external flows of knowledge.
Collaboration
Collaboration development process was
principled on a specific, tentative model described as a cycle of mutual
learning, knowledge sharing, and open communication between members (Tuominen and Ericksson,
2005). To better
achieve common or compatible goals collaborative
network has focuses on the
structure, behavior, social capital and
devolving of dynamics networks (Camarinha and Afsarmanesh, 2005; 2008; DeSanctis, 1999). Hossain and Wigand (2004) defined virtual collaboration
as ‘refers to the use of
information and communication technologies for supporting the collective
interaction among multiple parties involved’. Typology concepts is divided into internal,
stable, dynamic and web-company, and focus into structure and process
perspective, blurred the boundaries of the firm in terms of scope and depth.
The structure perspective focuses on the building blocks of the virtual
organizations and its properties, while the process perspective focuses on
behavior and operation. By scope we mean the inclusion of a much larger
constituency of interests, from owned and affiliated subunits, to joint
ventures, strategic partnerships and networks, including political and social
institutions shared by similar firms. By depth I mean the flattening of
hierarchies and the breaking down of barriers between functions in order to
create the horizontal and vertical integration of knowledge.
Miles and Snow attribute three roles to the broker (architect, lead
operator, and caretaker) which performing in the life cycle of the
co-operation. The architect keep skills and resources around the world, lead
operator take advantage laid by manager-architects, and understand how
cross-cultural relationships are forged and maintained, and the caretaker is focus on
enhancement activity, and sharing information among firms. Firms in
technologically intensive fields rely on collaborative relationships to access,
survey, and exploit emerging technological opportunities. First, collaboration
raises entry barriers. Second, interfirm cooperation accelerates the rate of
technological innovation. Third, reliance on collaboration has potentially
transformative effects on all participants. Finally, collaboration may itself
become a dimension of competition (Augier, 1999).
Collaborative networks of Virtual enterprises is inductor of value
creation based on stable business networks or ‘virtual communities’, and represent
a promising paradigm for all knowledge-driven entities in the society [6]. In
contrast to equity inter-organizational relationship with direct minority
investments and joint ventures, non-equity alliances are based on contracts and
do not use ownership in the relationship. This form of relationship is used to
develop existing internal ventures or create a framework for joined business
development (Schildt, 2005).
Non-Equity Strategic Alliances are less costly and require less time to
terminate and can range from close working
relations with suppliers, outsourcing of activities or licensing of technology,
to large R&D consortia, industry clusters and innovation networks.
Under all this
assumption I follow conceptual semantic ontology
model of collaboration by Gauvin (2005), in which learning objects are created, evaluated and used (See Figure 2).
Figure 2. Ontology model of Collaboration
Source:
Gauvin, M., et al. (2005).
Strategic Learning
A key feature in organizations’ capacity for
learning from collaboration is a function of access to knowledge and possession
of capabilities for utilizing and building on such knowledge. The idea of transformation as a result of the learning process
is present in the most recent learning theories (Stenström, 2009). The RBV suggests
that firms in the same industry perform differently because they differ in
their resources and capabilities (Wernerfelt, 1984). Theories
such as Mezirow`s (1991) theory of transformative
learning, speak explicitly about transformation, while in other theories the
transformative dimension is an implicit one. For example, cognitive
constructivists describe learning as a process of conceptual change (Vosniadou,
1994), while socio-cultural theories see learning as changes in
the learner`s participation in a community of practice (Lave & Wenger, 1991; Wegner, 1998). Basically a process of
transformation: a change in the way in which people think and act (Stenström, 2009).
Schumpeter
[7] presented the business concept
of 'strategic learning cycles', new dynamic capabilities of virtual
organizations over time, and new roles
for designers as ‘broker’, ‘entrepreneur’ or ‘promoter’ (Miles, 1986;
Schumpeter,
1943;
Pümpin, 1995). The concept of explorative and exploitative
learning (March, 1999)
contrasts entrepreneurial search for new opportunities and solutions with
adaptive and more risk-averse learning that leverages existing knowledge.
Exploration activities include search, variation, risk taking, experimentation,
play, flexibility, discovery, or innovation, while exploitation activities
include refinement, choice, production, efficiency, selection, implementation,
and execution (March, 1991).
Companies are increasingly using corporate
venturing to learn from knowledge sources beyond the boundaries of the firm, driven by professional associations outside the
organization, where identified learning policies and learning needs are
function of new developments within the broader profession (Smith, at.el., 2006). Learning in these circumstances is a
complex, multi-level process, involving learning from and with partners under
conditions of uncertainty, learning about partners’ behavior and developing
routines and norms that can mitigate the risks of opportunism, and learning how
to distribute newly acquired knowledge across different projects and functions
(Smith, 2000).
Organizational members are increasingly being encouraged to co-construct their
own practice environments, not only from the mind-set of external authorities
or academic experts (Raelin, 2006), but
also from the feedback and taking action based on understanding and maintained
of interrelationships between processes, and examined and changed as needed (Jones, 2001).
Under all this
assumption I follow Gauvin (2005) conceptual semantic ontology
model of learning (See Figure 2).
Figure 3. Ontology model of Learning
Source:
Gauvin, M., et al. (2005).
The issues of trust, partner selection,
knowledge transfer through co-operative business ventures, complementarities
and synergies between partners have dominated the scientific discourse. Miles
and Snow, (1986) point out that information technology will ‘substitute
for lengthy trust building processes’ during the implementation of dynamic
networks. Paradoxically, the more virtual the organization, the more people
need to meet in person to establish trust in
their relationships. The more consumers trust you build, the more
trusted a brand is, and the more willing consumers are to share their data (Handy,
1995; Hydari,
2012; Morey, 2015).
In this chapter, I review literatures, create
ontology maps in order to study
interfirm relationships, network position, growth, and portfolios of knowladge
creation, collaboration and strategic learning.
IV. Research Methods
I use tentative model to illustrate the fact
that virtual organization and social networks as ‘loose coupling’ can in right
circumstances transform into virtual communities of practice, a joint
enterprise. I follows Ononiwu (2015) that the processes of learning and knowledge acquisition,
articulation, codification and capture will bring a virtual enterprise closer
toward true virtual governance if it use characteristics such as ‘transformation, personal
relationships, common vision, collaboration and trust’ as well as ‘learning
capacity, culture, team work and human capital’. I adopt Teece et
al. (1997) view that ‘the
firm’s ability to integrate, build, and reconfigure internal and external
competences’ could give a firm a more sustainable competitive advantage,
specialized assets and address to rapidly changing environments. I assume that
with the growth in IT capability, the knowledge-based view as the key to
competitive advantage, could create new firm forms of organizing, facilitating
market entry into market value, processing and transforming trough the time
social capabilities and relational dimensions (Dierickx & Cool, 1989).
I study
Google network portfolio diversity of collaborative activities in Google
Certified Ad Networks, gathering the meanings both from a literature review and
from online Google survey. I follow Denzin (2006) which identified data triangulation: involves
time, space, and persons and methodological triangulation: involves using more than one
method to gather data, such as interviews, observations, questionnaires, and
documents. I follow also Furlan
& Grandinetti (2011)
three-dimension framework: ‘size growth’, ‘relationship growth’, and ‘dynamic
capability growth’. In sampling procedure I intended to have four respondents
to cover each category from generic ontology model: knowledge creation, learning and collaboration.
My main goals was to improve work environment processes and to deeper understanding
how virtual organization is organized trough platform technology.
V. State of the art
In this paper I study state of Knowledge
Management with ontologies, researching wide variety of techniques and
technologies which has been developed and adapted as a cloud computing
platforms. In my example four different companies using cloud integration with
Google platform, driven by businesses' needs to reduce costs, increase
efficiency, expanding company offerings, and improving competitive positions,
as a follow:
Agosto
Finding the right cloud
partner is a journey. More than matching what you need, to what they do. Partnering involved in a project need to
uncover mutual interests and build the trust and respect. As Wenger et al (2002) state ‘trust building relationship, equal exchange and
foster collaboration meeting an objective’. The synergy effect
enables the organization to meeting the customer demands, as a results of
combining all the core competencies on diversified firms relative to
non-diversified firms. Using the full spectrum
of Google’s Cloud Platform tools, Agosto helped Fortune 100 organizations and
others to bring their products to market more quickly and cost-effectively.
They minimizes transactions costs through pricing, product design, and
marketing (Evans, 2013), organized
themselves to best leverage the benefits and to gain competitive advantage. As Andy Parkins, Vice President Agosto said: ‘Integration with Google
platform helping us to positively transform our business’ [8].
Ezakus
Ezakus
want to maximizes advertising investments by determining, in
real time, categories of users most receptive to banners, promotions and
branding campaigns. From a business perspective, advertisers wish to
learn everything about their audience. From a technical perspective, there are
multiple ways in which data can be captured inside the data management platform. Olivier
Gardinetti, CTO, Ezakus said: “As a leading data management platform in Europe,
day-to-day, we manage approximately six hundred million events. That could be
around fifty or sixty million people to process. This predictive knowledge
maximizes advertising investments by determining, in real time, categories of
users most receptive to banners, promotions and branding campaigns. Compute
Engine transforms and multiplies the service that we provide to our clients. We can better anticipate buying behavior of
Internet users”.
I assumed that in
order to reach the most profitable overall pricing the platform thus has to
have a solid knowledge of the indirect network effects on the one hand and
especially on their relative effects on the other hand (Dewenter, 2006b).
The demand of each group for membership depends both on the fee it is charged
and on the number of members from the other group. Networks result from the ‘linking
of different units’ forming an intimate connection versus hierarchical
structure (Koleva,, 2002).
Gigya
From another side, if you
want to know what people are talking about online, ask Gigya, the company’s
which integrates Facebook, Twitter, LinkedIn® and other social networking
features as a Software as a Service (SaaS) technology. Many businesses have built pricing strategies
that are as sophisticated as predictive models using traditional business
intelligence methods and platforms. Gigya vice president, Raviv Pavel said: “The Gigya team quickly
realized that its platform hosting solution was not ideal. They wanted to develop a competitive pricing model that
doesn’t charge customers for unused capacity and to provide a reliable,
flexible system with minimal downtime for customers.”
Predictive analytics
pricing models look at information like the path the customer took to purchase
as well as information about the customer to determine the customer’s actual needs group, value group and
decision analytics. Kortge et. al. (1994) calculate the customer`s
perceived value price range, using a combination of stage in the life cycle,
experience cost curves, and learning curves (p. 155). From my opinion, Google team viewed
learning as either gaining knowledge or acquiring new competencies and skills, expanding
individual’s experience from past experience with Ezakus. For Gigya team, they represented a learning curve for
migration from the previous chat platform,
where Pavel says the experience was rewarding: “We
found that BigQuery handles that structure quite easily without flattening the
data. There was a bit of a learning curve in the beginning, and perhaps we were
unclear on some of our requirements. We now simply building products faster.”
Once they figured out what they wanted though, things went pretty smoothly. As
Pavel said: “The big implementation task was migrating 30 million comments from
one system to another in about 10 days” [9]. Pavel conclude: “The
platform is highly effective and does exactly what it's supposed to do. We are
very happy with it.” The biggest point (to improve learning)
would be to have techniques to share learning.
ShareThis
The main problem for many companies arises
from the fact that data can be
extremely large and must be processed in real
time period. ShareThis drives traffic and
revenue to their sites from advertisers, which work with them to reach relevant
audiences with highly targeted messaging across mobile and web. The company gathers about a billion social
data points each day. With the old platform, setting up of queries might have
taken days, with new platform, it takes seconds: “We found that BigQuery
handles structure quite easily without flattening the data. Data science and
predictive analytics can help marketing pros know where to find the new revenue
opportunities and which product or service offerings are most likely to address
the market requirement. The goal is to leverage both internal and external data
- as well as structured and unstructured data - to gain competitive advantage
and make better decisions [2].
The most effective way for commercial Web
providers to develop profitable exchange relationships with online customers is
to earn their trust. Companies will be rewarded, willingness to disclose
personal information, and increased loyalty (Hoffman, 1999). Trust
is best achieved by allowing the balance of power to shift toward a more
cooperative interaction between an online business and its customers (Hoffman and Novak, 1997). As Ishika Paul, engineering at ShareThis said: “We’re
building the right products faster. Now marketing analysts can get the
information they need without engineering intervention” [10]. A more
consumer-oriented information privacy model will lead to commercially valuable
relationship exchanges with important benefits for consumers and companies
doing business on the Internet (Wang, 1998).
VI. The Results
I research collaboration
as a transfer of knowledge between firms or as working relationships among
actors. The development processes towards collaboration was described as a
developmental cycle of mutual learning, knowledge sharing, and open
communication between members. I used case study method of four different
companies which collaborated with Google in order to expands data capacity and
client base using Cloud Platform technology. The Google virtual
enterprise reduces the amount of vertical integration to a virtual integration
level which consists of the core competencies of the organization which manages
a series of collaborations and contracts with third parties. In all four cases
vertical integration is efficient solution to a transaction cost minimization
problem, where the costs of market exchange compare unfavorably with the costs
of controlling production hierarchically through ownership. In order to
understand choice of this companies, three crucial transactional issue Google used
as interorganizational strategies: knowing the partner’s preferences, exchange
and mutual gain, and discovering ways in which similarities or shared interests
can be exploited to maximize co-operative joint gains that accrue to both parties.
Results show that knowledge
management includes the creation and sustainment of communities of practice,
coping with behavioral and cultural aspects of people, creating trusted and
validated content (Smith and Farquhar, 2000). Using action learning, participants learn
and become competent practitioners as they work (Raelin,
2006). Managers who aim to develop new platform
business models or to create new platform companies need to have a vision what
problem will solve for consumers but also for other firms. Trust and deep commitment developed through
these processes enhanced the likelihood of the movement along the slide, i.e.,
the transformation of co-operation into collaboration (Ononiwu, 2015).
VI. Conclusion
In paper I used three approaches, knowledge creation, collaboration and learning, where
decision depends on size and position in ‘value-chain,’ technological level,
resource constraints, alliance expenses. I used concept of dynamic capabilities
in terms of organizational knowledge processes. In my example four different companies want to
reduce costs, increase efficiency, and expanding company offerings. They used
processes of learning and knowledge acquisition, articulation, codification and
capture to improve there own business, and to expand learning capacity,
culture, team work and human capital. Characteristics such as ‘transformation, personal
relationships, common vision, collaboration and trust’ was explained
trough the process of learning from and with
partners. Limitation of this study is in data collection, I used survey method
which conduct Google on its website, and it will be much better to create own
parameters, to size three dimension ‘firm growth’, ‘relationship growth’, and
‘dynamic capability growth’. I would purpose as a future research using of real
statistical data collected trough survey or interview. Also some other
technology than cloud computing platforms could be use to measure innovative
output trough patents, for knowladge creation, collaboration and strategic
learning.
VI. Citations
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