Organizational Readiness Assessment for Open Source Software

Adoption

Lucía Méndez-Tapia

1,2

and Juan Pablo Carvallo

Universidad del Azuay (UDA), Av. 24 de Mayo 7-77 y Francisco Moscoso, Cuenca, Ecuador

Universitat Politècnica de Valencia (UPV), Camí de Vera, s/n, 46022 València, Spain

Keywords: Organizational Readiness Assessment, Open Source Software Adoption, Open Innovation.

Abstract: Open Source Software (OSS) is probably, the most iconic implementation of Open Innovation business

paradigm, due its capacity to concentrate both technical benefits and business advantages. Over time,

organizations face the OSS adoption challenge strengthening mainly its internal and technical elements.

However, the rapid changes on business dynamics, and the comprehensiveness and fast development of open

paradigms, show us that a new set of conditions must be satisfied to reach a successfully OSS adoption. These

conditions, considered as a critical success factors, involve a wide range of resources, capacities and skills,

both in internal and external scopes. Hence, although adopter organizations should be better prepared to face

the challenges related to collaborative innovation, they do not have a systematic approach to value its

readiness level to face the adoption challenges. In this context, the present research work proposes a model to

assess the organizational readiness, considering the adopter as part of a live business ecosystem, where the

relationships originated on co-development with developers’ communities, have mutual business impact at

strategic, tactic, and operative level.

1 INTRODUCTION

A successful adoption of Open Source Software

(OSS) brings a wide range of well-known technical

benefits like flexibility and dynamicity of solutions

(Ardagna et al., 2009), trustworthiness and quality

improvement (Lindman et al., 2009), short time-to-

market software delivery, lower development and

maintenance costs (Goldman and Gabriel, 2005).

Furthermore, from organizational perspective, there

are other kind of benefits, related for instance, with

business performance improvements (e.g. working

practices (Almeida and Cruz, 2012), job roles (Alexy

et al., 2013), ownership cost (Ardagna et al., 2009)),

value creation and value capture.

To achieve and sustain its benefits, all OSS

adoption initiatives demand the fulfillment of specific

requirements, mainly in terms of available support,

resources, capabilities and skills. Thus, before

initiating any incorporation of OSS it is crucial to

know if an adequate level of business readiness is

reached. As far as we know, there do not exist

structured approaches to assess organizational

https://orcid.org/0000-0001-6678-4774

readiness in the adoption of OSS, at least embracing

both external and internal ecosystems. This weakness

not only avoid organizations from reaching the

innovative benefits of OSS, but OSS adoption

projects do not materialize or do not reach their

objectives. In this context, we propose an assessment

model to help organizations to identify its current

readiness to face an OSS project. The develop of this

model is guided by three research questions (RQ):

RQ1 – Which are the main organizational

characteristics that can be considered as critical

success factor to support a successfully OSS

adoption?

RQ2 – How is it possible to organize these

characteristics into a generic assessment model?

RQ3 – How is it possible to suggest a way in

which OSS should be adopted, based on the

assessment model results?

In response to this, we propose the Organizational

Readiness Assessment Model for OSS Adoption to

estimate the preparation level of an organization to

take ad-vantage of OSS, and to suggest the way in

which OSS should be adopted. This model was

800

Méndez-Tapia, L. and Carvallo, J.

Organizational Readiness Assessment for Open Source Software Adoption.

DOI: 10.5220/0010497008000807

In Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 2, pages 800-807

ISBN: 978-989-758-509-8

applied on CEDIA, a non-profit entity in academic

sector, whose members are universities, community

colleges and high schools. CEDIA acts as technology

integrator and provide a portfolio of over 65 services

and programs intended to improve quality of

education and research.

The following sections are organized as follows:

Section 2 presents the related work; Section 3

describes the model; Section 4 shows the assessment

mechanism; Section 5 contains the results of

application case; finally, conclusions and work in

progress are presented.

2 BACKGROUND AND RELATED

WORK

This section briefly describes the main concepts

applied, and previous work in relation to our

proposal.

OSS refers to software that can be freely used,

modified and redistributed. The principles that drive

OSS (co-creation, openness, innovation, voluntary

association, self-organization), create a new

paradigm able to change not only the software

development but the social and economic value

creation. From this point of view, the OSS adoption

should be managed as a strategic business decision.

The way in which OSS is adopted by an

organization, is called adoption strategy. (López et

al., 2015) analysing empirical evidence, identifies and

model six ways of OSS adoption. Each of them

presents a particular set of characteristics which

depends in last instance, on how strong the interaction

with OSS Developer Community (OSS-DC) is, and

which business goals the adopter organizations hope

to achieves. These strategies are described below.

 Release: Organization releases personalized

software as OSS but does not care whether an

OSS-DC takes it up or forms around it. No

OSS-DC is involved. The organization does

not care OSS evolution for maintenance

 Acquisition: Organization use existing OSS

code without contributing to its OSS

project/community. The involvement with the

community is minimum after obtains the

software and its documentation. The

organization does not care OSS evolution for

maintenance.

 Integration: It involves the active

participation of an organization in an OSS

community (to share and co-create OSS) but

not necessarily leading or influencing it.

 Fork: Organization creates its own

independent version of the software that is

available from an existing OSS project or

community. The OSS-DC is forked too.

Organization continues the development of

OSS component (generally critical ones) and

OSS-DC evolves for its own account, to

achieve specific requirements.

 Takeover: Organization attracts an existent

OSS-DC to support its business activity. The

creation of its own OSS-DC pursues to ‘take

the control’ of critical software development.

 Initiative: Organization initiates an OSS

project and creates its own OSS-DC around it,

in order to ‘take the control’ of critical software

development.

Regarding technical issues, there is good set of

well-known contributions to OSS adoption in the

field of information and communication

technologies. This research work deals with the

business dimensions of OSS and Open Innovation

(OI). We conduct our proposal through OI

perspective, due to the fact that OSS is perhaps, the

most iconic form of OI implementation. In this sense,

the work of (Lopes et al., 2017) describes the

relationship among knowledge management,

sustainable innovations, and organizational

sustainability. (Rogo et al., 2014) propose a

methodology to assess the performance of OI

practices and improves the allocation of intellectual

capital resources into value creation process and high-

lights the importance of co-evolution between the

organization and its customers, competitors and

suppliers; here, Intellectual Capital refers to skills and

competences of staff, capabilities and knowledge

supported by organizational structure; and

environmental relationships with external

stakeholders. (Secundo, 2020) also emphasizes the

role of external stakeholders and its contribution in

sharing and transferring knowledge, across

technology-intensive organization boundaries with

OI. The cause and effects of agglomeration,

networks, and trust on OI culture, are integrated in a

model proposed by (Nestle et al., 2019), where the

need to extend the research on networks and

ecosystems is indicated.

In relation with OI assessment, based on a survey

among 223 Asian service firms, the work of (Cheng,

and Huizingh, 2014) proposes a comprehensive

measurement scale for OI that include a wide range

of activities, to indicate to what extent a firm has

implemented OI activities. This research work deals

with innovation performance and consider three

points of view: entrepreneurial, market, and resource.

Organizational Readiness Assessment for Open Source Software Adoption

801

This approach does not consider issues like

organizational culture, innovation stage, and lawful

knowledge.

Although there is a great variety of research work

that describes the relationship among some

organizational resources, capacities and skills, there

are no a model focused on evaluate the organization

as a whole, considering generic areas involved in an

OSS adoption project. Hence, we design a model that

supports the organizational assessment and suggest

the way in which OSS should be adopted.

3 CONSTRUCTIVE PROCESS

To take advantage of business benefits derived from

OSS, it is indispensable to fulfill a set of specific

requirements of OSS adoption strategies, and

consequently, it is essential that the organization

knows how ready it is to fulfill these requirements.

The internal structure of the organization keeps a

close relationship with the organizational

performance, facilitating or hindering the way in

which the individuals manage the complexity and

uncertainty derived from the activity with multiple

internal and external actors. In this context, the OSS

adoption implies establishing a non-trivial

relationship with multiple external stakeholders. The

specific association with one of them, the OSS

Developer Community, has particular complexity

(because has many connections) and uncertainty

(because the organization cannot exercise control nor

demand commitment, although this stakeholder

provides an important OSS component and/or its

support service).

For this reason, we propose the Organizational

Readiness Assessment Model, a support artifact which

final objective is to validate the organization’s

readiness to manage complex relationships and

uncertainties derived from the OSS adoption in an

organization that works according to open innovation

paradigm. It's important to highlight that because the

OSS adoption involves both technical and business

aspects, a global validation is required.

The constructive process that we use to develop

the model, is summarized in Fig. 1. The iterative

approach guides the application of four stages, which

are described below.

 Stage 1 – Identification. The first stage of the

constructive process consist on the review of

works in three main areas interrelated with

organizational OSS adoption: open innovation

(wide scope), IT management (medium scope),

and OSS adoption itself (short scope).

(Chesbrough, 2006), (Ven and Verelst, 2009),

(Spinellis and Giannikas, 2012), (Hogan and

Coote, 2014), (Cohen, and Levinthal, 1990),

(Branscomb and Auerswald, 2001), (López et

al., 2015), (RISCOSS, 2014) constitute the core

of support documentation from where we

identified a set of organizational issues for the

assessment.

 Stage 2 – Organization and Prioritization.

The issues identified in previous stage were

chronologically organized in past (experience

in OSS adoption), present (current resources,

capabilities, and skills), and future

(expectations about OSS projects). Issues in

present time were grouped into thematic

categories. In order to quantify the

organizational compliance of each issue, a

numeric scale was assigned, with scores

between 0 to 1. Initially, all categories have the

same weight in the model.

 Stage 3 – Decision Support. In this stage, we

stablish a relationship among resources,

capabilities and skills available in the

organization, and the requirements of OSS

adoption strategies identified in (López et al.,

2015). This relationship allows us to suggest a

specific OSS adoption strategy or strategies,

and identify the key issues that should be

improved to support OSS adequately.

 Stage 4 – Feedback. In this stage, the model

can be modified to incorporate enhances

suggested by strategic/tactic staff of the

assessed organizations, about: new issues,

intervals of scoring, weight of categories, and

so on.

As a result of applying these four stages, we

obtain a model to estimate, in a systematic way, the

level of readiness to face an OSS adoption project.

4 MODEL DESCRIPTION

The model constructed in previous section contains

nine categories, as shown in Fig. 2. In this section, we

describe briefly each of them. When the organization

has completed the assessment, the next step is to

know how to carry out the adoption process. To

contribute to identify the most suitable path to adopt

OSS, we work with the proposal of (López et al.,

2015), which describes six ways in which the

organizations usually adopt OSS.

ICEIS 2021 - 23rd International Conference on Enterprise Information Systems

802

Figure 1: Constructive Process.

4.1 Section A: OSS Experience

This section aims to identify the kind of knowledge

and learned lessons obtained by the organization from

previous OSS works. This experience brings to the

organization a valuable support in practical issues of

OSS adoption.

A1 Organization’s OSS Experience: it refers to

the main feature of previous organizational

experience with OSS, from no existence, to existence

of high complex experience.

A2 Staff’s OSS Experience: it assesses the main

previous OSS experience that the staff has had

outside the organization, from no existence to

existence of high complex experience.

A3 Organization’s Previous Related

Knowledge in the Organization: The work of

(Cohen, and Levinthal, 1990) argues that prior related

knowledge enables the organization to assimilate and

use new outside knowledge, and has a reinforcing

effect. This knowledge should be structured. The

innovation projects require both commonality

knowledge (which improves the communication

among staff of diverse areas), and individual

knowledge (which maintains the diversity).

(Steinmacher et al., 2015) identifies the lack of

previous knowledge as an incoming barrier faced by

newcomers. Thus, the prior related knowledge in the

organization is estimated in the range from

inexistence on OSS domain or related fields, to

existence of knowledge identified and available.

Figure 2: Model Structure.

4.2 Section B: Stakeholder

Management

It identifies if the organization has a structured and

systematic management of stakeholders, which bring

support the relationships involved in OSS adoption.

The organization should manage a minimum schema

that allows it to identify, classify and prioritize the

stakeholders according to the importance level that

they have.

B1 Stakeholder Relationship Management: it

refers to the existence of defined process to manage

the organizational relationships with its external

stakeholders.

B2 Stakeholder Prioritization Criteria: it refers

to the existence of a defined criteria to assign a

prelation order in which the stakeholders are managed

and its satisfaction is monitored.

4.3 Section C: Internal Support

Assurance

This issue evaluates the support level that the

organization can bring to OSS adoption, from the

perspective of open innovation. This issue has a

critical role because identifies the responsibilities and

commitments that the organization must met in order

to give viability and sustainability to OSS initiative.

C1 Business-IT Alignment: This issue asks for

the alignment of Information Technologies issues to

business, i.e., to what extent the IT operations support

the business goals, business strategy and mission.

C2 Strategic Commitment for OSS: It is the

strategic commitment that can obtain an OSS project,

through initiative sponsoring and basic requirements

(i.e. budget, resources project management support,

business process management support), valued using

three possible responses, from the no offering of

strategic commitment to OSS, to refer that this

commitment is feasible. This resource commitment

(financial, material, logistic, etc.), contributes to

avoid or reduce delays. (Spinellis and Giannikas,

2012).

C3 OSS Technical Skills: they are the technical

skills required for OSS adoption (i.e. crowdsourcing,

collaborative teams, agile development).

C4 Technical Support for OSS: It is the internal

technical support available to OSS (it refers to staff

effort, hardware and communications resources).

(Spinellis and Giannikas, 2012) show that

“organizations in fields with a high IT-usage intensity

could be more likely to adopt OSS”. This issue

indicates the availability of support.

Organizational Readiness Assessment for Open Source Software Adoption

803

C5 Learning Capacity (LC): Known as the “the

capacity to develop knowledge” (Hult et al., 2001), or

“the organizational potential to use available

knowledge within the organization and to continually

renew that knowledge” (Prieto and Revilla, 2003), the

ultimate impact of Learning Capacity (LC) is to

improve the organizational innovation and

performance. The present assessment seeks the

organization’s expert criteria to identify the LC level

(high, medium, or low) that can support the learning

required by OSS adoption. It is assumed that in every

organization has at least individual learning capacity.

C6 Absorptive Capacity (AC): The Absorptive

Capacity (AC) (proposed by (Cohen, and Levinthal,

1990), and reformulated by (Zahra and George, 2002)

is considered as the set of routines and processes by

which organizations systematically identify, acquire,

assimilate, transform, and exploit knowledge; in turn,

this knowledge impact the levels of organizational

innovation and performance. According to (Cohen,

and Levinthal, 1990), previous to AC, the internal

Research and Development (R&D) should be

developed to generate Prior Related Knowledge that

allows the assimilation of the external knowledge.

Part of AC is the facility to adopt technologies,

referred by (Spinellis and Giannikas, 2012) as the use

of technologies, the obtainment of advantage of its

use, and the general adoption experience. In this

context, the present assessment seeks the

organization’s expert criteria to identify the AC level.

C7 Human Talent: it refers to the innovation-

driven approach (i.e. the existence and application of

innovation processes, policies and systems) present or

not in hu-man talent management. This variable has

three sub-components: a) staff conformation, b) staff

operation, and c) innovator’s role. The first two are

referred to the support that the human talent

management offers to the innovation process. The last

one is referred to the existence of innovation role(s)

clearly defined and focused on monitoring the

environment, sourcing knowledge, and

communicating the knowledge (to their organization

and across their organization) (Cohen, and Levinthal,

1990), (Huang et al., 2017).

C8 Disseminative Capacity (DC): As part of the

knowledge transfer process, the Disseminative

Capacity is referred by (Tang et al, 2010) as “the

ability of knowledge holders to efficiently,

effectively, and convincingly frame knowledge in a

way that other people can understand accurately and

put into practice”. In the present assessment, DC is

valued both internal level (among individuals and

groups) and external level (between the organization

and its stakeholders).

C9 Open Innovation Process Management:

OSS developing practices as agile end-user and

volunteer driven, have a marked difference with

traditional software development processes (Spinellis

and Giannikas, 2012) because, among other factors,

OSS is a way of open innovation (Chesbrough, 2003),

and as such, its adoption requires flexibility not only

at software development level but at business level.

The business importance of open innovation process

management is treated in (Lendel et al., 2015), and

organizational issues required by OSS (for instance,

process reengineering, leadership role in ecosystems)

are identified in (Appleyard and Chesbrough, 2017).

4.4 Section D: Organizational Culture

The organizational culture comprehends norms,

systems, symbols, language, assumptions, beliefs,

habits, collective behaviour patterns, and

assumptions. All of them shape and characterize the

organization, and are able to facilitate and promote

the innovation. In this sense, (Hogan and Coote,

2014) show that values, norms and artifacts steer

innovative behaviours, and these in turn impact on

organizational performance.

From works of (Hogan and Coote, 2014), (Cohen,

and Levinthal, 1990), (Branscomb and Auerswald,

2001), a set of elements from the innovation-oriented

organizational culture was selected to be evaluated.

D1 Valuation of Organizational Performance:

The value that the organization attributes to success,

high and innovative performance, challenging goals,

motivates staff and improves the innovative solutions

and in general terms, helps to develop a proactive

behaviour.

D2 Agreement to Openness and Flexibility: An

organization opened to new ideas and new

approaches to solve problems, facilitates the

generation of creative solutions, the discovering of

new paths to achieve these solutions, and decreases

the resistance to changes.

D3 Organizational Tolerance to Risk: All

innovations have a certain uncertainty level, because

their potential impact (at organizational and

environmental level) can be positive or not. In this

scenario, the “willingness to engage in and encourage

behaviours and activities with uncertain outcomes”

(Chapman and Hewitt-Dundas, 2017), referred as risk

tolerance, is one of the influential factors to undertake

an innovation project.

ICEIS 2021 - 23rd International Conference on Enterprise Information Systems

804

4.5 Section E: Open Innovation Level

Thus, guided by the Open Innovation Paradigm

(Chesbrough, 2006), (Chesbrough, 2003), the open

innovation stage is estimated in general terms, through

the following axis: Innovation Process Management,

Intellectual Property Management, Technology

Management, External Stakeholder Management,

Market Knowledge Management, Customer Offering

Planning, Value Added Management

4.6 Section F: External Support

Assurance

This section identifies the source of specialized

support level to OSS adoption that the organization

can obtain from third parties. This refers to potential

support provided by other division, business unit, or

area of the own corporation.

4.7 Section G: Lawful Knowledge

This appraisement aims to identify the level of

organizational knowledge about legal and regulatory

issues related to open source. This is integrated by

three components: licensing knowledge, IP and

G1 Licensing Knowledge: It is the

organizational knowledge about OSS licensing,

valued using four alternative responses, from no

knowledge, to high level of knowledge.

G2 IP and Copyright Knowledge: It is the

organizational knowledge about Intellectual Property

regulations, valued through four alternative

responses, from no knowledge, to a high level of

knowledge.

G3 IP Policies: this component is referred to the

existence of protection terms for the organizational

knowledge, and has develop of correspondent IP

policies. There are three possible responses, from the

no existence of protection terms or IP policies, to the

existence, diffusion and application of this policies.

4.8 Section H: Response to General

Environmental Factors

The environment has influence in how the

organization operates. There are external factors that

can impact on open innovation initiatives (OSS in

particular) either promoting them or restricting them.

The management of these factors is assessed from the

point of view of the value network to which the

organization pertains, and from the perspective of the

organization.

4.9 Section I: Expectations about OSS

Adoption

This section is oriented to identify the role that the

company has planned for OSS, in relation with the

customer offering, the Internal Development Team,

and the link with OSS Developer Community. These

issues are described below.

I1 OSS Inclusion in Customer Offering: The

inclusion of an OSS component as part of the

customer offering (unlike using it internally) involves

issues like customer relationship, image, incomings,

and market, among others. The specific role planned

for OSS as part of customer offering gives a general

idea of the organization's awareness of resources to

invest in the OSS adoption.

4.10 Suggestion of OSS Adoption

Strategy

As we introduce in Background Section, the work of

(López et al., 2015) shows six OSS adoption

strategies. Due to the main external stakeholder in

them is the OSS-DC, they were organized into three

groups, according to the interaction level between the

organization and the OSS-DC. Hence, we define three

interaction levels: Low-none, where organization has

a minimal relationship with OSS-DC, or no exist

relationship at all (Release, Acquisition, and

Integration); Medium, where organization has a

limited relationship with OSS-DC, through sending

patches, requirement specifications, performance

reports, and so on (Fork); and High, where

organization has strong and permanent relationship

with OSS-DC through co-development (Takeover,

and Initiative).

5 APPLICATION CASE: CEDIA

5.1 General Description

A questionnaire was developed as assessment

mechanism, based on the schema presented in Section

4. This questionnaire contains 40 closed polytomic

questions derived from issues at level 2, and uses a

Likert Scale of 3, 4, 6 or 9 points (where the points

for a question are not overlapped). These questions

are exhaustive (includes all possible responses) and

mutually exclusive (it is not possible the co-existence

of two or more responses for each issue). Only one

question includes the possibility of an open response:

the case of OSS experience, where the interviewed

Organizational Readiness Assessment for Open Source Software Adoption

805

can respond with a description of its particular OSS

adoption way.

CEDIA was selected according to the following

criteria: a. To have experience in OSS adoption

projects; b. To include OSS as part of customer

offering; c. To have (or have had) some relationship

with OSS-DC. After selecting the organization, the

following criteria were stablished to identify the most

suitable executive profile to response the

questionnaire: a. To have experience as Technology,

Innovation, and Business Management; b. To have

decision-making facilities (in terms of resource

assignment) over OSS related projects; and c. To have

software engineering background (desirable),

specifically in requirements management, and system

integration, areas. The responses were given by a high

executive of CEDIA.

The following subsections describe each issue to

be assessed.

As we see in Fig. 3, CEDIA has a high compliance

level in most categories, and an average compliance

of 84.4%. In the following paragraphs, we present the

main findings.

About previous staff experience on OSS adoption.

Although the staff reports an experience quantified of

37.91% (considered low level), it does not affect the

subsequent performance in OSS projects.

According with the obtained scores, and applying

the suggestion schema proposed in Subsection 4.10,

we found that CEDIA is ready to carry forward OSS

adoption strategies that involves low and med

relationships with OSS-DC.

In the case of strategies with high involvement

with developer’s community, it is important to

reinforce the capacities and skills related to

environmental interaction (improving the process to

manage relationship with OSS-DC, and the criteria to

prioritize internal-external requirements). The lack of

knowledge and confidence in its environment, may be

one of the reasons why CEDIA has a medium level of

risk tolerance (Section D – Organizational Culture)

and a medium level of development of its value

network (Section H – Response to General

Environmental Factors).

5.2 Threads to Validity

The validation of a proposal using a single case,

might introduce bias (either by excluding important

elements or by over valuate others) that makes

difficult to generalize its conclusions. To reduce this

threat, we place special attention on selecting the

organization where perform the application case.

Figure 3: CEDIA Assessment Results.

This organization satisfy the following additional

criteria: a) representativeness: has a common cases of

OSS adoption b) truthfulness: we have free access to

historical and current information about OSS

initiatives.

6 CONCLUSIONS AND WORK IN

PROGRESS

In this paper, we present a model to assess the

organizational readiness for Open Source Software,

from open innovation business perspective. In

response to the research questions (RQ) stablished in

Section 1, the following results were obtained. RQ1:

A meaningful set of skills, capacities and resources

related with OSS adoption in Open Innovation

environment were identified. RQ2: we organize the

results from RQ1 into 9 categories grouped in 3-time

instances (past, present and future) that integrate the

structure of the Organizational Readiness Assessment

Model. RQ3: After our model application, an OSS

adoption strategy(ies) can be suggested, mapping the

estimated level of organizational readiness, with the

business requirements of OSS adoption strategies.

The main benefits of our proposal are: a) establish

a solid and systematic criterion to identify

organizational issues involved in OSS adoption; b)

organize these issues in categories that can facilitate

the strategic user assessment; c) suggest a type of

OSS adoption strategy, according to organizational

readiness; and d) identify aspects that should be

improved in organizations, mainly in terms of

Business-IT alignment.

Other important benefit of our proposal resides in

the fact that it can be used with minor adjustments in

any organization, independently of its nature or

industry to which pertains. Accordingly, the proposed

ICEIS 2021 - 23rd International Conference on Enterprise Information Systems

806

method constitutes a decision-making tool that helps

adopters to take advantage of OSS benefits.

We continue to specific work on two issues: a. to

identify the synapsis between organizational

readiness and its correspondent OSS adoption

strategies, in order to disaggregate these connections

to goal, risk, and cost level; and b. to apply the model

in other representative organizations, once the model

structured has been improved using current feedback.

REFERENCES

Ardagna, C., Branzi, M., Daminai, E., El Ioini, N., Frati, F.

2009. Assurance Evaluation for OSS Adoption in a

Telco Context. In: IFIP. AICT 299, pp. 363

Lindman, J., Juutilainen, J., Rossi, M.: Beyond the Business

Model - Incentives for organizations to publish

software source code. 2009. In: IFIP. AICT 299, pp. 47-

-56

Goldman, R., Gabriel, R. P.: Innovation happens elsewhere

- Open source as business strategy. 2005. Morgan

Kaufmann.

Almeida, F., Cruz, J.: Open Source Unified

Communications - The New Paradigm to Cut Costs and

Extend Productivity. 2012. In: OSDOC'12, ACM

Communications.

Alexy, O., Henkel, J., Wallin, M.: From closed to open -

Job role changes individual predispositions and the

adoption of commercial open source software

development. 2013. Research Policy. vol 42 pp. 1325--

1340

Lopes, C., Scavarda, A., Hofmeister L., Tavares, A., Roehe,

G.: An analysis of the interplay between organizational

sustainability, knowledge management, and open

innovation. 2017. Journal of Cleaner Production 142,

476-488

Rogo, F., Cricelli, L., Grimaldi, M.: Assessing the

performance of open innovation practices: A case study

of a community of innovation. 2014. Technology in

Society 38, 60-80

Secundo, G., Del Vecchio, P., Simeone, L., Schiuma, G.:

Creativity and stakeholders' engagement in open

innovation: Design for knowledge translation in

technology-intensive enterprises. 2020. Journal of

Business Research. Vol 119. 272-282

Nestle, V., Täube, F., Heidenreich, S., Bogers, M.:

Establishing open innovation culture in cluster

initiatives: The role of trust and information

asymmetry. 2019. Technological Forecasting & Social

Change 146, 563–57

Cheng, C. and Huizingh, E.: When Is Open Innovation

Beneficial? The Role of Strategic Orientation. 2014.

Product Development & Management Association

1(6):1235–1253

Chesbrough, H. W.: Open Business Models – How to thrive

in the new innovation land-scape. 2006. Harvard

Business School Press.

Ven, K., Verelst, J.: The Importance of External Support in

the Adoption of Open Source Server Software. 2009. In

Open Source Ecosystems: Diverse Communities

Interacting. pp. 116-128

Spinellis D., Giannikas, V.: Organizational adoption of

open source software. 2012. The Journal of Systems

and Software 85. pp. 666– 682. Elsevier.

Hogan, S., Coote, L.: Organizational culture, innovation,

and performance: A test of Schein’s model. 2014.

Journal of Business Research. Vol 67 pp. 1609-1621

Cohen, W. M., Levinthal, D. A. Absorptive capacity: a new

perspective on learning and innovation. 1990. In

Administrative Science Quarterly, 35 pp. 128–152

Branscomb, M. and Auerswald, P. Taking Technical Risks.

2001. The MIT Press.

López, L., Costal, D., Ayala, C., Franch, X., Annosi, M.,

Glott, R., Haaland, R.: Adoption of OSS components: a

goal-oriented approach. 2015. Data & Knowledge

Engineering Vol 99. Pp. 17–38.

RISCOSS. An Overview of the RISCOSS Decision Support

Platform, Methodology and Architecture. (2014).

http://www.riscoss.eu/

Steinmacher, I., Graciotto Silva, M.A., Gerosa, M.A.,

Redmiles, D.: A systematic literature review on the

barriers faced by newcomers to open source software

projects. 2015. Information and Software Technology

59, pp. 67–85

Hult G. T. M., Ketchen D. J., Reus T. H.: Organizational

Learning Capacity and Internal Customer Orientation

Within Strategic Sourcing Units. 2001. Journal of

Quality Management. 6: pp.173-192

Prieto, I., Revilla, E.: How learning capacity influences on

organizational performance: an empirical evidence.

2003. In 5th International Conference of Organizational

Learning and Knowledge.

Zahra, S. A., George, G. Absorptive capacity: a review,

reconceptualization, and extension. 2002. Acad.

Manage. Rev. 27 (2) pp. 185–203

Huang, M., Bhattacherjee, A., Wong, Ch.: Gatekeepers’

innovative use of IT: An absorptive capacity model at

the unit level. 2017. Information and Management.

Article in Press. Elsevier.

Tang, F., Mu, J., MacLachlan, D.: Disseminative capacity,

organizational structure and knowledge transfer. 2010.

Expert Systems with Applications, 37, pp. 1586–1593.

Elsevier.

Chesbrough, H. W.: Open Innovation – The New

Imperative for Creating and Profiting from Technology.

2003. Harvard Business School Press.

Lendel, V., Hittmár, Š., Siantová, E., Latka, M.: Proposal

of the evaluation system of the level of the innovation

processes management in company. 2015. Procedia

Economics and Finance 34 pp. 417 – 422

Appleyard, M., Chesbrough, H.: The Dynamics of Open

Strategy: From Adoption to Re-version. 2017. Long

Range Planning, vol 50, 50, pp. 310-321

Chapman, G., Hewitt-Dundas, N.: The effect of public

support on senior manager attitudes to innovation.

2017. Technovation. Elsevier.

Organizational Readiness Assessment for Open Source Software Adoption

807