Maturity models: identifying the state-of-the-art
and the scientific gaps from a bibliometric study

Thalita Laua Reis1 • Maria Augusta Siqueira Mathias1 •

Otavio Jose de Oliveira1

Received: 13 April 2016 / Published online: 23 November 2016
� Akadémiai Kiadó, Budapest, Hungary 2016

Abstract Maturity model has been increasingly approached by several researchers from

various research areas in order to develop models that could assess the strengths and weaknesses

of a system and/or a process, and to develop scripts for improvement. Additionally, they pursue

the development of a process with desirable goals, such as a set of resources or practices,

resulting in a more mature organization or system. This study provides an overview of the

maturity models’ literature and their main features while employing bibliometric analyses of

publications from 2004 through 2014 aiming to identify scientific gaps that would serve as

guides for future research. The analyses’ results reveal that maturity models are highly applied

in project management seeking for processes and/or systems improvement, and they can also be

described as adaptable models which could be used in various research areas, as can be seen in

the scientific gaps section. Therefore, the main contribution of this paper is to make the

evolution of this subject and its importance better known, thus encouraging the use of maturity

model in future researches, seeking the improvement of the current model.

Keywords Maturity model � Bibliometric analysis � Scientific gaps � Organizational

evaluation

Introduction

Organizations grow in a complex manner involving several evolutionary aspects, such as

organizational, technical, strategic, among others. They realize more and more the need to

assess their present situation, determine desirable future scenarios and verify possible and

profitable ways that will lead them towards this evolution (Marx et al. 2012).

Electronic supplementary material The online version of this article (doi:10.1007/s11192-016-2182-0)
contains supplementary material, which is available to authorized users.

& Otavio Jose de Oliveira
otaviodeoliveira@uol.com.br

1 São Paulo State University - UNESP, São Paulo, Brazil

123

Scientometrics (2017) 110:643–672
DOI 10.1007/s11192-016-2182-0

http://dx.doi.org/10.1007/s11192-016-2182-0
http://crossmark.crossref.org/dialog/?doi=10.1007/s11192-016-2182-0&domain=pdf
http://crossmark.crossref.org/dialog/?doi=10.1007/s11192-016-2182-0&domain=pdf


As the technology progress and the introduction of management systems provide sig-

nificant competitive benefits to organizations, they also need resources that support them to

achieve desired goals. Maturity model is a method that has been increasingly growing and

gaining notoriety, which determines the maturity levels based on the performances of the

companies’ process areas (Ngai et al. 2013).

The application and development of maturity models have increased in demand, since

they can be used for strengths’ and weaknesses’ analyses, developing improvement plans

and the company’s evaluation when compared to other organizations’ standards and best

practices (Pigosso et al. 2013).

In general, the term ‘maturity’ can be defined as ‘the state of being perfect, complete

and ready’, or more specifically as ‘a measure used to evaluate the resources of an

organization’. Hence, maturity implies an evolutionary process from an early stage towards

a desired scenario or, in other words, a final stage (Marx et al. 2012). Furthermore, Harmon

(2004) states that mature organizations do their business in a systematic way, while the

others only get their results through the heroic efforts of determined individuals, who

spontaneously create the approaches they intend to use.

Maturity models consist of several maturity levels reflecting the evolutionary path for a

given area or process, being widely used for continuous improvement and benchmarking.

With the help of the maturity models, organizations can assess their present situation and

determine a future desired scenario, considering a number of predefined items (Marx et al.

2012).

Fischer (2004) determined five organizational change triggers, namely: strategy, con-

trols, people, technology and process. They provide the components on which the

resources will be evaluated, as the organization then proceed to the second dimension of

the maturity model, during which the components formerly set will be evaluated at each

one of the maturity stages. As for the model developed by Fischer (2004), they are: siloed,

tactically integrated, process-driven, optimized enterprise, and intelligent operating

network.

The maturity model designed by Fischer (2004) is appropriate to all organizations

seeking to reach the maturity level in their businesses, since, through the evaluation of

those change triggers, the gaps between their current situation and the future desired

scenario are identified. By assessing those gaps at each level of the proposed model, the

organization may create action plans that would ultimately help eliminate those lacunas,

enabling the achievement of corporative goals.

Therefore, a maturity model contains essential elements and effective processes for one

or more areas and/or systems, describing an evolutionary path of improvement, and turning

premature processes into mature ones with improved quality and effectiveness (Garzás

et al. 2013). A maturity model can be seen as a guide to best practices and also as a process

assessment framework that could be employed step by step in an organization’s low-cost

evaluation process and planning improvement (Gorschek 2012).

Due to the benefits that the use of maturity model provides those organizations wishing

to achieve a future desirable situation, the model has been used in various areas of study,

covering areas of biological, human and exact sciences. Moreover, the implementation of

maturity models in the organizations allows a better decision-making process, enlightening

the managers as to their current processes’ and services’ status.

According to Liker and Morgan (2011) and León et al. (2011), maturity models have

been developed in order to assess the organizations’ competence, capacity level and

sophistication based on a relatively extensive set of criteria. Consequently, a maturity

644 Scientometrics (2017) 110:643–672

123



model could be analyzed as a structured dataset, which describes specific maturity aspects

of an organization.

Spanyi (2004) believes that, even though maturity models are well-intentioned, they are

mechanistic and do not capture the required attention from senior managers. The author

also states that many of those models fail in recognizing that the organization’s main

purpose to develop new management practices is to improve the corporate performance.

Thereafter, the majority of these models do not take explicitly into account two fun-

damental organizational realities: companies are complex, both considering their business

and their social systems, and, for them to achieve an exemplar business management

performance, their leaders must work as a team, in a collaborative way.

This article briefly presents maturity models and their main feature, and also a bib-

liometric analysis, which verifies the contribution of articles that have been published from

2004 to 2014 on maturity models, while identifying scientific gaps for research

advancement. Robinson et al. (2011) define scientific gaps as topics or areas where there is

a lack of information or a limited capacity to achieve an understanding. In the present

paper, there will be exposed the suggestions for future researches signalized both in the

studied articles and by the analyzed authors.

The paper also exhibits analyses of the most cited articles and authors on maturity

model, and, from these analyses, the scientific gaps will be identified in order to guide

researchers on future studies. Additionally, it would allow them to recognize the most

prominent authors so as to adopt them as references.

There are similar works in the extant literature, such as Souza and Gomes (2015),

however, it focused on the scientific production on project management concerning the

organizations’ most expressive maturity models. They investigated articles published from

2010 to 2014 from the Web of Science, the Scopus and the Scielo databases, and the data

analyses, such as the most influencing countries, the number of articles per country and the

grouping of the articles according to the maturity model, were executed through the Zotero
� software.

The bibliometric analysis provides an accurate and presumably objective method to

measure the contribution of an article for the advancement of knowledge, and is a fre-

quently used tool to analyze trends and performance on a particular subject (Yang et al.

2013). Thereupon, this bibliometric analysis is employed to better comprehend the evo-

lution in the studies on maturity models within the academic community, and to verify

their real efficiency in the business world.

This section exhibited an introduction to the paper, while the next one will be presenting

a brief theoretical framework on maturity model. Then, the research method is described

including the criteria adopted, the used databases and the tools employed in the analysis.

Next, the obtained results are described and analyzed, while the last section presents the

findings and proposals for future researches.

Theoretical framework

In an immature organization, processes are generally improvised by people who are in

direct contact with them, and, even though they had been specified, that does not mean the

guidelines will be strictly followed. In this type of organization managers are focused on

solving problems immediately, being informally known as firefighters, while deadlines and

budgets are routinely exceeded, since the planning is not based on actual estimates. An

Scientometrics (2017) 110:643–672 645

123



immature organization does not have an objective way to verify the quality of products or

solving problems, turning quality into something difficult to achieve (Paulk et al. 1993).

On the other hand, a mature organization possesses a broad process control enabling

their development management and maintenance. Managers communicate accurately with

staff and new workers about processes, and the activities are carried out according to the

plan. Processes are updated whenever necessary through pilot testing and cost-benefit

analysis seeking for improvements, besides, rules and responsibilities are clear to the entire

organization, especially those involved in the project. In a mature organization, managers

monitor the quality of products and processes, therefore, since deadlines and budgets are

based on historical data, the results of costs, functionality and quality can be usually

achieved (Paulk et al. 1993).

According to Schmietendorf et al. (2000), Poppendieck (2004) and Paulk et al. (1993),

maturity in an organization can be seen as an extension in which the worked process is

explicitly defined, very well managed, fully controlled and effective. Hence, their

respective models come to help organizations achieve the desired benefits.

Maturity model happens in development stages and involves the knowledge of the

capacity of the areas of process, wealth and consistency of the whole system (Randeree

et al. 2012). The maturity model is conceptualized through a set of elements that describes

the development of a particular area of interest and assists in describing a process that a

system may eventually develop in order to achieve a desirable goal, by means of a set of

resources or practices, resulting in a more mature organization (Pigosso et al. 2013).

Maturity models can be used for three main purposes: analysis of strengths and

weaknesses, development of a roadmap for future improvements and evaluation of the

company when compared to other organizations’ standards and best practices (Pigosso

et al. 2013). There are different classifications of maturity models concerning their

structures: (a) capability maturity models and (b) maturity matrix. However, there are also

variations of models adapted to the aforementioned ones.

After several unfulfilled promises regarding productivity and quality improvements, all

of which would be derived from the deployment of new technologies and software

methodologies in organizations, developers have identified that the real problem is the lack

of ability to manage software processes. Within various organizations, the budgeting and

planning of projects take place too late in the timeline, thus, the benefits that could be

achieved from new software methods or technologies are not possible due to the lack of

discipline in the planning stage (Paulk et al. 1993).

Paulk et al. (1993) had also stated that the Software Engineering Institute (SEI) started

the development of a process-maturity framework in November 1986 that would help

software developers improve their processes. In September 1987, SEI gave a brief

description of the process-maturity framework and, after a few more years of experience

with this method, it was implicated in the Capability Maturity Model (CMM).

The capability maturity model (CMM), which is illustrated in Fig. 1 (Jin et al. 2014),

consists of a five-stage structure of evolution, or capacity levels, or process maturity,

describing an evolutionary improvement path from an immature process to a mature one,

disciplining the process (Albu and Panzat 2010).

CMM is characterized by its comprehensive and complex architecture, because, unlike

maturity matrices, each maturity level on a CMM has its own process areas. It is a specific

maturity level that can only be achieved if the practices and objectives of all process areas

in a previous level are met (Jin et al. 2014).

An extension of the CMM with best practices, the Capability Maturity Model Integrated

(CMMI), is used in the areas of product and service development, service providers,

646 Scientometrics (2017) 110:643–672

123



management, product delivery, and acquisition of services and products. It provides the

organization with a guide for continuous improvement through the integration of inter-

organizational functions, focusing on objectives and priorities by orienting quality pro-

cesses and establishing a benchmark to evaluate the ongoing process.

The CMMI is represented by stages and continuous representation, wherein the first one

is similar to the CMM presenting five maturity stages, while the continuous representation

uses six capability levels to improve the process. Each level corresponds to a generic goal

and a series of practices, and each level is analyzed separately. Capacity levels focus on

increasing the ability to control, the performance and the organizations’ improvement in

specific process areas (Ngai et al. 2013).

A rapid growth in the development and use of maturity matrixes has been noticed in

management practices in industrial enterprises since 1990, approximately. These matrixes

were developed by academic researchers, people involved in industrial processes, such as

managers and consultants, who used the original Quality Management Maturity Grid

(QMMG) by Crosby as a reference (Maier et al. 2012).

The Crosby’s QMMG contains various maturity levels, usually from 3 to 6 levels (Stage

I—uncertainty; Stage II—awakening; Stage III—enlightenment; Stage IV—wisdom; Stage

V—certainty), forming an evolutionary pathway of resources, which is used as ground-

work to the maturity matrix illustrated in Fig. 2. For any given factor in a specific maturity

level, detailed descriptions are provided to serve as a basis for the measurement of

maturity. For inspecting the maturity level of each key factor, companies become aware of

their weaknesses and, consequently, may improve relevant activities (Crosby 1979; Jin

et al. 2014).

The main purpose of a maturity matrix is to measure and encode capabilities or typical

behaviors that reflect on best practices to effectively accomplish specific tasks and goals. A

maturity matrix usually includes several key aspects that give an overview of the area of

interest, in which the progress in each of the intermediate or transitional stages are

described and interpreted. Maturity matrixes have been successfully applied to evaluate

Fig. 1 Capability maturity model (Source Jin et al. 2014)

Scientometrics (2017) 110:643–672 647

123



strategic and operational capabilities in quality management, product development, com-

munication, data security and risk management organizations (Golev et al. 2015).

To develop maturity matrixes, Maier et al. (2012), suggest a script consisting of four

phases: planning, development, evaluation, and maintenance. For each phase, a number of

points and decision options are discussed. Progression through some phases can be an

iterative work and may have to be re-evaluated (Maier et al. 2012).

‘‘The decision points and their respective decision’s options for each one of the stages

suggested by Maier et al. (2012) are: at the first stage (planning): 1—specify audience, e.g.

users; 2—define objective, e.g. entities; 3—clarify scope, e.g. general or specific domain;

and 4—define success criteria, e.g. high-level and specific requirements.

The second stage (development) can be defined as: 1—select areas of processes

(components and theoretical framework); 2—select maturity levels; 3—formulate text cell,

e.g. type of formulation (prescriptive or descriptive), source of information (synthesize the

point of view of future users or comparison of other organizations’ practices), and

mechanism of formulation (inductively generated from descriptions of practices or

deducted from the subjacent logic); and 4—set delivery mechanism, e.g. focus on the

evaluation process or focus in the final results (Maier et al. 2012).

The decision points and their options at the third stage (evaluation) are: 1—validation,

i.e. correspondence between the author’s intent and the user understanding; and 2—veri-

fication, i.e. matching specific requirements. In terms of the fourth stage (maintenance),

they are: 1—check reference, if applicable; 2—keep results database, if applicable; and

3—document and communicate development process and results, specific to the public

(Maier et al. 2012)’’.

According to Maier et al. (2012), despite the existence of a script to be followed, there

can be variation of the points within the phases, although the phases are consistent and,

therefore, can be applied in various fields. Even though it is mainly targeted as a guide to

future developments of maturity matrices, the script can be used for evaluative purposes of

current observations. The script works as a warning to researchers and professionals to a

set of decisions that must be made when developing a maturity matrix (Maier et al. 2012).

Maier et al. (2012) affirm that the differentiation of the maturity matrixes models and

CMM is not a trivial task, because frameworks are improvements that complement each

other. Nevertheless, some points may differ in orientation, in the evaluation mode and in

Fig. 2 Maturity matrix (Source Jin et al. 2014)

648 Scientometrics (2017) 110:643–672

123



the model intention. With respect to orientation, while the CMM only applies to more

specific sectors, maturity matrix may be enforced at any company or sector, considering it

does not require a specific process for its execution.

Typically, the CMM is assessed by a Likert or binary scale based on questionnaires that

evaluate the process performance. The maturity matrix, in turn, is structured in a matrix

with maturity levels and key aspects of the process performance, creating a series of cells

which contains text describing the performance characteristics required at each level.

Maturity matrixes are less complex than the CMM, being used as a diagnostic or

improvement tool, while the CMM follows a formatted and internationally recognized

standard (Maier et al. 2012).

Schmietendorf et al. (2000) proposed the Performance Engineering Maturity Model

(PEMM), which is similar to the CMM, in order to determine the maturity of the Per-

formance Engineering (PE) process within the software development, and with the purpose

of evaluating PE processes and their integration. There were determined five level: Stage

I—uncoordinated practices; Stage II—consideration of PE sub process; Stage III—Entire

PE Process Definition; Stage IV—successfully integrated and proved PE process; and

Stage V—Optimized PE process.

The lean capability model, based on the continuous improvement (CI) maturity model,

has been proposed by Jorgensen et al. (2007), which illustrates a gradual but steady

development of CI through five maturity stages arising from the adoption of some

behaviors that, when integrated, provide organizational capabilities. Stage one consists of

behavioral activities, such as ‘‘firefighters’’, through the creation of systems, procedures

and organization processes. The development of CI becomes more structured and focused

on strategy, finally reaching stage five, where a solid learning about CI is obtained in the

organization.

The lean capability model has been elaborated based on experiments that the

researchers had with organizations and key people implementing lean in order to develop

lean capabilities and long-term sustainability. The collected data were sorted into five

maturity stages similar to the CI maturity model, namely: Stage I—Sporadic production

optimization; Stage II—Basic lean understanding and implementation; Stage III—Strategic

lean interventions; Stage IV—Proactive lean culture; and Stage V—Lean in the extended

manufacturing enterprise (EME) (Jorgensen et al. 2007).

There are distinct types of maturity models that, similarly to the aforementioned ones,

had been designed based on existent models, adapting them according to the organizations’

needs and goals.

Research methodology

To conduct the bibliometric analysis consistent with what was pre-established in this

article, a search for articles has been carried out on the Scopus and Web of Science

platforms, which are scientific multidisciplinary articles databases. They bring together a

wide range of journals from relevant publishers that provide a global access point to most

of the scientific literature published internationally, such as: Elsevier, Springer, Wiley-

Blackwell, Taylor & Francis, Stage, Emerald and others.

Articles published in journals are the dominant means for the disclosure of results in the

areas of natural sciences, engineering and biomedical research (Mongeon and Paul-Hus

2016), and so they had been chosen as the main database for this research. Bibliometric

Scientometrics (2017) 110:643–672 649

123



analyses use bibliographic data stored in electronic databases and the studies are carried

out under the premise that they encompass different databases, thus the need to properly

choose which ones will be used (Uriona-Maldonado et al. 2012).

The traditional method of bibliometric analysis is to conduct a research on the trending

topics of a particular field of study, mostly based on the publication date, the institute and

journal, author, country and subject of research, besides the frequency of the keywords,

among others. Bibliometric analysis is being increasingly applied to analyze the rela-

tionship among keywords, country, research institute and author (Zhuang et al. 2013).

For this bibliometric analysis, the subject to be examined was initially established, in

this case ‘‘maturity model’’, and, therefore, the database platforms to be used and the

search parameters are defined. This research will be using the Scopus and Web of Science

platforms and the following parameters: article tittle containing the term ‘‘maturity

model’’, data range from 2004 to 2014 and document type restricted to ‘‘article’’.

The aforementioned parameters were used as filters in both databases in order to increase

the accuracy of the results, and, after their application, 156 (one hundred fifty-six) documents

have been found in Scopus and 107 (one hundred-seven) documents in Web of Science.

Scopus platform is a large depository for revised summaries and literature citations

(scientific journals, books and conference proceedings), which provides a comprehensive

overview of research production in the world in science, technology, medicine, social

sciences and arts and humanities, enabling several intelligent features and tools to track,

analyze and visualize researches. It becomes even more global when it comes to resear-

ches, being an interdisciplinary and collaborative tool (Elsevier 2015).

The data extracted from the database platforms were assigned to various analyzes, such

as: the most cited articles and keywords, the number of publications of the most cited

authors, the H-index and the institution of the most cited authors, their citations’ quantity

and evolution (regarding a variety of subjects), their last published articles (topic: maturity

model), the impact factor (SJR) of the journal in which their last article on maturity model

has been published and their proposals for future research.

The evolution of the subject within the pre-established period was retrieved from the

Scopus platform, while, in determining the most cited keywords, it was necessary to export

all the keywords found in the studied articles in a format compatible with Excel, so they

could be properly treated and have their frequencies analyzed.

The most cited articles could be also identified from the platform by selecting the option

‘‘cited by’’, as well as those articles’ information, such as authors, journal, the journal’s

impact factor, publishing year, volume, issue, and how many times the article has been

cited in other publications.

Regarding the most cited authors, the following analyzes have been made by using the

authors’ names as filters in the Scopus database: number of publications, h-index, number

of citations in different themes, evolution of citations, and the last published article on

maturity model. The impact factor of the journal in which the author’s last article on

maturity model was published could be also retrieved within this platform.

For the identification of the scientific gaps, the latest articles published on maturity

model of the most cited authors were analyzed one at a time, when their future studies

proposals or research continuation have been observed.

Regarding the data obtained from the Web of Science platform (WoS), the following

analyses were conducted: the most cited articles, the most cited authors and their network.

The WoS platform also allows the identification of the most cited articles, however,

duplications with articles already identified in the Scopus platform were noticed. A further

investigation showed that all items presented in the WoS had been already exhibited in the

650 Scientometrics (2017) 110:643–672

123



Scopus database, thus, the later has been determined as the primary data source for this

study. The Sci2Tool computational tool was employed in the recognition of the most cited

authors on maturity model. Since this tool is only compatible with the WoS data format

though, that was the chosen database when creating the most cited authors’ network on

model maturity.

For the analysis of the most cited articles, a combination of data from both databases has

been carried out by checking whether the most cited articles in both bases corresponded

well, besides verifying the veracity of those articles being the ten (10) items with higher

citations on the subject.

The research was bounded by documents classified as ‘‘articles’’, because it allows the sci-

entific gaps on maturity model to be identified, as well as providing greater scientific reliability.

The domain on the characterization of maturity model publications and the identification of

scientific gaps are made possible based on the data obtained by means of the Scopus and Web

of Science databases. The various analyzes were allowed due to the transformation of the

collected data on relevant information to perform a consistent analysis of the ten (10) most

cited articles on maturity model, the ten (10) most used keywords, 10 (ten) most cited authors

and last article on maturity model published by each of the ten (10) most cited authors.

Thereby, it should be emphasized that the first three aforementioned analyzes enable the

knowledge on the development and characterization of publications on maturity model,

while the last one enables the identification of scientific gaps.

The bibliometric analysis of the collected data was performed by two software tools:

Microsoft Excel and Sci2Tool. Using Microsoft Excel spreadsheets, graphs and charts

based on information taken from both databases were obtained, in addition to enabling the

identification of the most cited keywords from the Scopus platform, while the Sci2Tool tool

allowed the identification of most cited authors as well as their network formation through

the data extraction in the Web of Science platform.

The last article on maturity model of each of the ten (10) most cited authors was given a

special attention in order to verify the authors’ proposals for future research, forming the set

of scientific gaps. Figure 3 shows the flow of steps performed for the bibliometric analysis.

The search has been restricted to the first ten most cited articles and the first ten most

cited authors, because, in doing so, the study’s relevance was guaranteed and it was possible

to perform a more thorough analysis of the articles and the most cited authors on the subject.

Had a greater amount of articles and authors been analyzed, it would have required a longer

search and, perhaps, the main objectives would not be reached, which is to identify the most

important articles and authors who effectively collaborate to the subject ‘‘maturity model’’

and to acknowledge scientific gaps. Therefore, the authors decided to scrutinize only 10

articles and 10 authors, which would end up providing a list of the top articles and authors

on maturity model that is considered satisfactory for this research.

Results and discussion

Analysis of the evolution of publications on maturity model, research areas
and most frequently used keywords

A sharp increase is observed in the number of published articles on maturity model,

considering that the study of articles published from 2004 until 2014 enables us to identify

the evolution of research on the subject, as shown in Fig. 4.

Scientometrics (2017) 110:643–672 651

123



Fig. 3 Steps flow to perform the bibliometric analysis

652 Scientometrics (2017) 110:643–672

123



An increase in the number of published articles on maturity model is shown in Fig. 4,

depicting that, from the end of 2007 to early 2009, there was a significant evolution, which

reappears at the end of 2011 and remains in progress until early 2014.

Figure 5 exhibits the areas that have been publishing articles on maturity model, and the

subject importance to the development of scientific knowledge can be identified through

the correlation among research areas and the amount of articles that have been published

on the subject in each of them.

Despite maturity model being employed in various areas of research, Fig. 5 highlights

its concentration in the exact sciences, especially in: computer science, engineering and

business, management and accounting.

In order to identify what are the topics that have been studied along with maturity

model, it was performed an analysis of the most used keywords in articles on the subject.

The keyword ‘‘maturity model’’ was removed from the analysis, since the goal is to

identify the keywords that have been addressed along with it.

The keywords ‘‘project management’’ and ‘‘performance’’ are the most used in articles

on maturity model, comprising approximately 1.30% of total keywords (see Online

Resource 1). Accounting for all the keywords identified in the articles on maturity model,

except the very keyword ‘‘maturity model’’, the total value of 460 was obtained (four

hundred and sixty), but many of them were employed only once.

The keyword ‘‘CMMI’’ or ‘‘Capability Maturity Model Integration’’ is approximately

1.09% of the total of the keywords used in the articles on maturity model, since CMMI is

an adaptation of the CMM model.

The most used keywords are ‘‘Project management’’ and ‘‘Performance’’, which rein-

forces the idea that maturity model is largely employed along with project management in

order to guarantee continuous improvement, thus seeking to achieve a desired performance.

Bibliometric analysis of the ten most cited articles on maturity model

Continuing with the analysis of the characterization of publications on the topic, the ten

(10) most cited articles on maturity model are tabulated as shown in Table 1, including

Fig. 4 Evolution of the publications on maturity model over the period of 2004–2014 according to the
Scopus database

Scientometrics (2017) 110:643–672 653

123



the article’s title, the authors, the journal to which it belongs, volume and edition, the

journal’s impact factor obtained from SCImago Journal Rank (SJR) in 2014, the year of

publication of the article, the amount and evolution of the quotations from the year

2004 until 2014.

The most cited article, ‘‘E-government maturity models: Extension of the Layne and

Lee model’’ by Andersen K.V. and Henriksen H.Z., proposes a reorientation of the gov-

ernment’s electronic program using maturity models focusing on applications for the

improvement of activities.

From Table 1 it is possible to extract Fig. 6 displaying citations’ evolution through the

years, identifying that between the years of 2007 and 2008 there was an intensification of

mentions of maturity model.

Table 2 is obtained from Table 1 by analyzing the articles’ respective years of publi-

cation and citations evolution in the established period (2004–2014). It can be noticed that,

even though one of the top 10 most cited articles had been published in 2004, its largest

citation period occurred in 2010, as well as it is clear that the articles started to be more

heavily quoted from 2009 on. This means that, although they have been published since

2004, the articles which make up the 10 most cited articles still impart strong scientific

collaborations to current researchers.

Among the ten (10) most cited articles, 3 (three) of them were published in the Journal

Government Information Quarterly, and other three (3) articles were published in journals

of the management area, namely: Information Systems Management, Industrial Manage-

ment and Data Systems, Supply Chain Management-An International Journal, as can be

seen in ‘‘Online Resource 2’’.

The analysis in Table 1, with respect to the titles of the most cited articles and the

journals they are published in, confirms what has been seen in ‘‘Online Resource 2’’

regarding the various research areas in which the subject is approached. Maturity model

can be adapted to many different situations and areas of study, since it will help achieve a

better performance.

Fig. 5 Research areas where articles were published on maturity model according to the Scopus database

654 Scientometrics (2017) 110:643–672

123



T
a
b
le

1
B

ib
li

o
m

et
ri

c
an

al
y

se
s

o
f

th
e

1
0

m
o

st
ci

te
d

ar
ti

cl
es

o
n

m
at

u
ri

ty
m

o
d

el
in

th
e

p
er

io
d

fr
o
m

2
0

0
4

to
2

0
1

4

T
it

le
A

u
th

o
rs

Jo
u

rn
al

F
I/

S
JR

(2
0

1
4
)

Y
ea

r
V

o
lu

m
e

E
d

it
io

n
T

o
ta

l
o

f
ci

ta
ti

o
n

s

E
-g

o
v
er

n
m

en
t

m
at

u
ri

ty
m

o
d

el
s:

ex
te

n
si

o
n

o
f

th
e

L
ay

n
e

an
d

L
ee

m
o

d
el

A
n

d
er

se
n

K
.V

.,
H

en
ri

k
se

n
H

.Z
.

G
o

v
er

n
m

en
t

In
fo

rm
at

io
n

Q
u

ar
te

rl
y

1
.2

0
3

2
0

0
6

2
3

2
1

9
2

T
h

e
d

ev
el

o
p

m
en

t
o

f
a

su
p

p
ly

ch
ai

n
m

an
ag

em
en

t
p

ro
ce

ss
m

at
u

ri
ty

m
o

d
el

u
si

n
g

th
e

co
n

ce
p

ts
o

f
b

u
si

n
es

s
p

ro
ce

ss
o
ri

en
ta

ti
o
n

L
o
ck

am
y
,

A
;

M
cC

o
rm

ac
k

,
K

S
u

p
p

ly
C

h
ai

n
M

an
ag

em
en

t-
an In

te
rn

at
io

n
al

Jo
u

rn
al

1
.9

3
1

2
0

0
4

9
3

–
4

1
0

8

A
m

at
u

ri
ty

m
o

d
el

fo
r

th
e

im
p

le
m

en
ta

ti
o
n

o
f

so
ft

w
ar

e
p

ro
ce

ss
im

p
ro

v
em

en
t:

an
em

p
ir

ic
al

st
u

d
y

N
ia

zi
M

.,
W

il
so

n
D

.,
Z

o
w

g
h

i
D

.

Jo
u

rn
al

o
f

S
y

st
em

s
an

d
S

o
ft

w
ar

e

1
.3

8
1

2
0

0
5

7
4

2
9

8

S
o

ft
w

ar
e

M
ai

n
te

n
an

ce
M

at
u

ri
ty

M
o

d
el

(S
M

m
m

):
th

e
so

ft
w

ar
e

m
ai

n
te

n
an

ce
p

ro
ce

ss
m

o
d

el

A
p

ri
l

A
.,

H
ay

es
J.

H
.,

A
b

ra
n

A
.,

D
u

m
k

e
R

.

Jo
u

rn
al

o
f

S
o

ft
w

ar
e

M
ai

n
te

n
an

ce
an

d
E

v
o

lu
ti

o
n

0
.7

9
4

2
0

0
5

1
7

3
5

3

Scientometrics (2017) 110:643–672 655

123



T
a
b
le

1
co

n
ti

n
u
ed

T
it

le
A

u
th

o
rs

Jo
u

rn
al

F
I/

S
JR

(2
0

1
4
)

Y
ea

r
V

o
lu

m
e

E
d

it
io

n
T

o
ta

l
o

f
ci

ta
ti

o
n

s

M
at

u
ri

ty
m

o
d

el
fo

r
IT

o
u

ts
o

u
rc

in
g

re
la

ti
o
n
sh

ip
s

G
o

tt
sc

h
al

k
P

.,
S

o
ll

i-
S

ae
th

er
H

.
In

d
u

st
ri

al
M

an
ag

em
en

t
an

d
D

at
a

S
y

st
em

s

0
.8

4
6

2
0

0
6

1
0

6
2

5
2

S
er

v
ic

e-
o

ri
en

te
d

ar
ch

it
ec

tu
re

:
m

y
th

s,
re

al
it

ie
s,

an
d

a
m

at
u

ri
ty

m
o

d
el

H
ir

sc
h

h
ei

m
,

R
u

d
y

;
W

el
k
e,

R
ic

h
ar

d
;

S
ch

w
ar

z,
A

n
d

re
w

M
IS

Q
u
ar

te
rl

y
E

x
ec

u
ti

v
e

1
.1

7
2

2
0

1
0

9
1

3
3

A
n

O
p

en
G

o
v

er
n

m
en

t
M

at
u

ri
ty

M
o

d
el

fo
r

so
ci

al
m

ed
ia

-b
as

ed
p

u
b

li
c

en
g

ag
em

en
t

L
ee

G
.,

K
w

ak
Y

.H
.

G
o

v
er

n
m

en
t

In
fo

rm
at

io
n

Q
u

ar
te

rl
y

1
.2

0
3

2
0

1
2

2
9

4
3

3

C
o

n
ce

p
ti

o
n

,
d

ev
el

o
p

m
en

t
an

d
im

p
le

m
en

ta
ti

o
n

o
f

an
e-

g
o

v
er

n
m

en
t

m
at

u
ri

ty
m

o
d

el
in

p
u

b
li

c
ag

en
ci

es

V
al

d
es

,
G

o
n

za
lo

;
S

o
la

r,
M

au
ri

ci
o

;
A

st
u

d
il

lo
,

H
er

n
an

;
Ir

ib
ar

re
n

,
M

ar
ce

lo
;

C
o
n
ch

a,
G

as
to

n
;

V
is

co
n
ti

,
M

ar
ce

ll
o

G
o

v
er

n
m

en
t

In
fo

rm
at

io
n

Q
u

ar
te

rl
y

1
.2

0
3

2
0

1
1

2
8

2
2

4

656 Scientometrics (2017) 110:643–672

123



T
a
b
le

1
co

n
ti

n
u
ed

T
it

le
A

u
th

o
rs

Jo
u

rn
al

F
I/

S
JR

(2
0

1
4
)

Y
ea

r
V

o
lu

m
e

E
d

it
io

n
T

o
ta

l
o

f
ci

ta
ti

o
n

s

A
P

A
C

S
m

at
u

ri
ty

m
o

d
el

:
a

sy
st

em
at

ic
m

et
a-

an
al

y
ti

c
re

v
ie

w
o

n
m

at
u
ra

ti
o
n

an
d

ev
o

lv
ab

il
it

y
o

f
P

A
C

S
in

th
e

h
o

sp
it

al
en

te
rp

ri
se

v
an

d
e

W
et

er
in

g
,

R
o

g
ie

r;
B

at
en

b
u
rg

,
R

o
n

al
d

In
te

rn
at

io
n

al
Jo

u
rn

al
o

f
M

ed
ic

al
In

fo
rm

at
ic

s

0
.8

0
3

2
0

0
9

7
8

2
2

3

T
h

e
p

ro
je

ct
m

an
ag

em
en

t
m

at
u

ri
ty

m
o

d
el

K
en

t
C

ra
w

fo
rd

J.
In

fo
rm

at
io

n
S

y
st

em
s

M
an

ag
em

en
t

0
.4

4
1

2
0

0
6

2
3

4
2

2

Scientometrics (2017) 110:643–672 657

123



Bibliometric analysis of the ten most cited authors on maturity model

After this previous analysis, information about the first authors who were most cited among

articles on maturity model from 2004 to 2014 were compiled in Table 3. Table 3 contains

the names of the most cited authors in descending order with respect to citations in articles

on maturity model and the institution to which they belong. Further information can be

extracted from these authors’ publications in various areas and research topics, such as: the

most used keywords by each one of them, h-index, number of publications and the number

of citations during the period of 2004–2014.

Regarding the evolution of citations over the years, it is being shown the evolution of

how many times the author was quoted in various subjects. Below it is the evolution of how

many times the author’s articles on maturity model have been cited and, therefore, it is

possible to check the impact of the aforementioned articles on the scientific community and

the general impact of this author. Figure 7 illustrates the network of authors and their most

cited co-authors in articles on maturity model. As a result of the network analysis, the

authors are placed in descending order, since the circle diameter and the color tone allow

this allocation. The larger the circle diameter and the more intense its hue, the greater the

number of author’s citations.

Table 3 shows how many times the authors have been cited for their work in general

and, immediately below, how many times they are cited for their work on ‘‘maturity

model’’. Therefore, Lackamy and McCormack together have produced articles on maturity

model that were cited 109 (one hundred and nine) times by other authors, which, in other

words, means that they have a huge impact on scientific research. However, when ana-

lyzing their citations in general they do not have such a high impact as their colleagues in

the group of the ten most cited authors.

Table 4 shows the relationship between the institutions the 10 most cited authors belong

to and the citations’ evolution of their articles on maturity model.

Considering the institutions with more citations on maturity model identified in Table 4,

which could also be checked out in ‘‘Online Resource 3’’, the ones presenting more than

100 cited articles are Samford University, at the Brock School of Business and DRK

Research, both from Birmingham, USA. The institutions exhibiting a range from 90 to 99

Fig. 6 Evolution of citations from 2004 to 2014 according to the Scopus database

658 Scientometrics (2017) 110:643–672

123



T
a
b
le

2
A

n
al

y
si

s
o

f
th

e
ci

ta
ti

o
n

s
ev

o
lu

ti
o

n
in

th
e

p
er

io
d

fr
o
m

2
0

0
4

to
2

0
1

4
w

it
h

th
e

ar
ti

cl
es

’
y

ea
r

o
f

p
u

b
li

ca
ti

o
n

C
it

at
io

n
s

ev
o

lu
ti

o
n

(2
0

0
4
–

2
0

1
4

)

T
it

le
Y

ea
r

o
f

p
u

b
li

ca
ti

o
n

2
0

0
4

2
0

0
5

2
0

0
6

2
0

0
7

2
0

0
8

2
0

0
9

2
0

1
0

2
0

1
1

2
0

1
2

2
0

1
3

2
0

1
4

E
-g

o
v
er

n
m

en
t

m
at

u
ri

ty
m

o
d

el
s:

ex
te

n
si

o
n

o
f

th
e

L
ay

n
e

an
d

L
ee

m
o
d

el
2

0
0

6
0

0
0

3
1

8
2

0
1

8
4
9

3
6

2
0

2
8

T
h
e

d
ev

el
o
p
m

en
t

o
f

a
su

p
p
ly

ch
ai

n
m

an
ag

em
en

t
p
ro

ce
ss

m
at

u
ri

ty
m

o
d
el

u
si

n
g

th
e

co
n

ce
p

ts
o

f
b

u
si

n
es

s
p

ro
ce

ss
o

ri
en

ta
ti

o
n

2
0

0
4

0
1

3
7

8
1

5
1
7

1
0

1
4

1
6

1
7

A
m

at
u

ri
ty

m
o
d

el
fo

r
th

e
im

p
le

m
en

ta
ti

o
n

o
f

so
ft

w
ar

e
p

ro
ce

ss
im

p
ro

v
em

en
t:

an
em

p
ir

ic
al

st
u

d
y

2
0

0
5

0
3

8
7

1
4

1
1

1
8

7
1

2
1

1
7

S
o
ft

w
ar

e
M

ai
n
te

n
an

ce
M

at
u
ri

ty
M

o
d
el

(S
M

m
m

):
th

e
so

ft
w

ar
e

m
ai

n
te

n
an

ce
p

ro
ce

ss
m

o
d

el
2

0
0

5
0

0
5

3
5

8
4

1
1

8
4

5

M
at

u
ri

ty
m

o
d

el
fo

r
IT

o
u

ts
o

u
rc

in
g

re
la

ti
o

n
sh

ip
s

2
0

0
6

0
0

1
4

5
1
8

7
4

5
6

2

S
er

v
ic

e-
o
ri

en
te

d
ar

ch
it

ec
tu

re
:

m
y
th

s,
re

al
it

ie
s,

an
d

a
m

at
u
ri

ty
m

o
d
el

2
0
1
0

0
0

0
0

0
0

3
1
0

8
5

8

A
n

O
p

en
G

o
v

er
n

m
en

t
M

at
u

ri
ty

M
o

d
el

fo
r

so
ci

al
m

ed
ia

-b
as

ed
p

u
b

li
c

en
g

ag
em

en
t

2
0

1
2

0
0

0
0

0
0

0
0

0
1

5
1
8

C
o

n
ce

p
ti

o
n

,
d

ev
el

o
p

m
en

t
an

d
im

p
le

m
en

ta
ti

o
n

o
f

an
e-

g
o

v
er

n
m

en
t

m
at

u
ri

ty
m

o
d
el

in
p
u
b
li

c
ag

en
ci

es
2

0
1

1
0

0
0

0
0

0
0

3
7

8
6

A
P

A
C

S
m

at
u
ri

ty
m

o
d
el

:
a

sy
st

em
at

ic
m

et
a-

an
al

y
ti

c
re

v
ie

w
o
n

m
at

u
ra

ti
o
n

an
d

ev
o

lv
ab

il
it

y
o

f
P

A
C

S
in

th
e

h
o

sp
it

al
en

te
rp

ri
se

2
0

0
9

0
0

0
0

0
0

2
8

4
5

4

T
h

e
p

ro
je

ct
m

an
ag

em
en

t
m

at
u

ri
ty

m
o

d
el

2
0

0
6

0
0

0
1

0
2

1
3

3
8

4

T
h
e

n
u
m

b
er

s
in

b
o
ld

re
p
re

se
n
t

th
e

h
ig

h
er

ci
ta

ti
o
n

v
al

u
e

fo
r

th
e

ar
ti

cl
e

b
et

w
ee

n
2
0
0
4

an
d

2
0
1
4

Scientometrics (2017) 110:643–672 659

123



T
a
b
le

3
M

o
st

ci
te

d
au

th
o

rs
o

n
m

at
u

ri
ty

m
o

d
el

M
o
st

ci
te

d
au

th
o

rs
A

ffi
li

at
io

n
M

o
st

u
se

d
k

ey
w

o
rd

s
h

-
in

d
ex

P
u

b
li

ca
ti

o
n

C
it

at
io

n
s

(C
)

M
at

u
ri

ty
m

o
d

el
ci

ta
ti

o
n
s

(M
.M

.C
)

E
v

o
lu

ti
o

n
o

f
ci

ta
ti

o
n

s

L
o
ck

am
y
,A

S
am

fo
rd

U
n
iv

,
B

ro
ck

S
ch

B
u
si

n
es

s,
B

ir
m

in
g
h
am

,
A

L

U
S

A

S
u
p
p
ly

C
h
ai

n

M
an

ag
em

en
t

1
0

2
8

5
3
6

1
0
9

C M
.M

.C
11

20
28

31
40

39
42

43
55

50
77

0
10

0

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
1

3
7

8
15

17
10

14
17

17
020

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

M
cC

o
rm

ac
k
,

K
.

D
R

K
R

es
ea

rc
h
,

B
ir

m
in

g
h
am

,

U
n
it

ed
S

ta
te

s

S
u
p
p
ly

C
h
ai

n

M
an

ag
em

en
t

1
0

2
1

5
6
1

1
0
9

C M
.M

.C
1

2
15

21
21

38
58

69
11

5
91

13
0

0
20

0

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
1

3
7

8
15

17
10

14
17

17
020

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

W
il

so
n
,

D
.

U
n
iv

er
si

ty
o
f

T
ec

h
n
o
lo

g
y

S
y
d
n
ey

,
F

ac
u
lt

y
o
f

In
fo

rm
at

io
n

T
ec

h
n
o
lo

g
y
,

S
y
d
n
ey

,
A

u
st

ra
li

a

S
o
ft

w
ar

e

p
ro

ce
ss

im
p
ro

v
em

en
t

(S
P

I)

9
3
3

5
6
1

9
8

C M
.M

.C
3

15
37

45
62

55
70

85
65

65
59

0
10

0

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
3

8
7

14
11

18
7

12
11

7
020

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

N
ia

zi
,

M
ah

m
o
o
d

K
.

K
in

g
F

ah
d

U
n
iv

er
si

ty
o
f

P
et

ro
le

u
m

an
d

M
in

er
al

s,

In
fo

rm
at

io
n

an
d

C
o
m

p
u
te

r

S
ci

en
ce

D
ep

ar
tm

en
t,

D
h
ah

ra
n
,

S
au

d
i

A
ra

b
ia

S
y
st

em
at

ic

li
te

ra
tu

re

re
v
ie

w

1
4

6
0

7
1
0

9
8

C M
.M

.C

0
3

8
7

14
11

18
7

12
11

7
020

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

1
10

13
25

48
58

86
88

12
1

13
0

13
0

0
20

0

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

660 Scientometrics (2017) 110:643–672

123



T
a
b
le

3
co

n
ti

n
u
ed

M
o
st

ci
te

d
au

th
o

rs
A

ffi
li

at
io

n
M

o
st

u
se

d
k

ey
w

o
rd

s
h

-
in

d
ex

P
u

b
li

ca
ti

o
n

C
it

at
io

n
s

(C
)

M
at

u
ri

ty
m

o
d

el
ci

ta
ti

o
n
s

(M
.M

.C
)

E
v

o
lu

ti
o

n
o

f
ci

ta
ti

o
n

s

Z
o
w

g
h
i,

D
id

ar

U
n
iv

er
si

ty
o
f

T
ec

h
n
o
lo

g
y

S
y
d
n
ey

,
R

es
ea

rc
h

C
en

te
r

fo
r

H
u
m

an
C

en
te

re
d

T
ec

h
n
o
lo

g
y

D
es

ig
n
,

S
y
d
n
ey

,
A

u
st

ra
li

a

N
o
n
-f

u
n
ct

io
n
al

re
q
u
ir

em
en

ts

(N
F

R
s)

1
2

8
3

6
9
6

9
8

C M
.M

.C
1

22
28

43
71

60
95

84
87

10
7

98

0
20

0

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
3

8
7

14
11

18
7

12
11

7
020

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

G
o
tt

sc
h
al

k
,

P
et

te
r

In
st

it
u
te

fo
r

L
ea

d
er

sh
ip

an
d

O
rg

an
iz

at
io

n
al

M
an

ag
em

en
t,

D
ep

ar
tm

en
t

o
f

L
ea

d
er

sh
ip

an
d

O
rg

an
iz

at
io

n
al

B
eh

av
io

u
r,

O
sl

o
,

N
o
rw

ay

K
n
o
w

le
d
g
e

m
an

ag
em

en
t

1
7

1
5
0

1
0
0
7

7
5

C M
.M

.C
15

30
46

88
12

8
14

0
12

2
98

12
9

11
2

99
0

20
0

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
1

4
10

26
9

6
8

7
2

2
050

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

L
ee

,

G
w

an
h
o
o

A
m

er
ic

an
U

n
iv

er
si

ty
,

K
o
g
o
d

S
ch

o
o
l

o
f

B
u
si

n
es

s,

W
as

h
in

g
to

n
,

U
n
it

ed
S

ta
te

s

P
ro

ce
ss

am
b
id

ex
te

ri
ty

2
9

4
3

5
6

C M
.M

.C
0

0
0

0
0

0
0

0
2

19
22

050

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
0

0
0

0
0

0
0

16
18

22
050

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

K
w

ak
,

Y
o
u
n
g

H
o
o
n

G
eo

rg
e

W
as

h
in

g
to

n

U
n
iv

er
si

ty
,

D
ep

ar
tm

en
t

o
f

D
ec

is
io

n
S

ci
en

ce
s,

W
as

h
in

g
to

n
,

U
n
it

ed
S

ta
te

s

P
ro

je
ct

m
an

ag
em

en
t

1
3

3
6

7
0
8

5
6

C M
.M

.C
6

17
18

16
36

44
80

94
97

13
6

16
4

0
20

0

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
0

0
0

0
0

0
0

16
18

22
050

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

Scientometrics (2017) 110:643–672 661

123



T
a
b
le

3
co

n
ti

n
u
ed

M
o
st

ci
te

d
au

th
o

rs
A

ffi
li

at
io

n
M

o
st

u
se

d
k

ey
w

o
rd

s
h

-
in

d
ex

P
u

b
li

ca
ti

o
n

C
it

at
io

n
s

(C
)

M
at

u
ri

ty
m

o
d

el
ci

ta
ti

o
n
s

(M
.M

.C
)

E
v

o
lu

ti
o

n
o

f
ci

ta
ti

o
n

s

S
o
ll

i-
S

æ
th

er
,

H
an

s

B
I

N
o
rw

eg
ia

n
B

u
si

n
es

s

S
ch

o
o
l,

O
sl

o
,

N
o
rw

ay

O
u
ts

o
u
rc

in
g

7
2
4

2
2
7

5
3

C M
.M

.C

 
0

0
8

19
25

52
34

17
29

23
20

0
10

0

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
0

1
4

5
18

7
4

5
7

2
020

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

P
ia

tt
in

i,

M
ar

io

U
n
iv

er
si

d
ad

d
e

C
as

ti
ll

a-
L

a

M
an

ch
a,

A
la

rc
o
s

R
es

ea
rc

h

G
ro

u
p
,

C
iu

d
ad

R
ea

l,
S

p
ai

n

S
o
ft

w
ar

e

p
ro

ce
ss

im
p
ro

v
em

en
t

(S
P

I)

2
5

5
8
7

3
0
0
3

3
9

C M
.M

.C
34

46
76

11
5

22
0

30
1

39
3

39
4

46
9

49
6

45
9

0
10

00

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

0
0

0
0

0
2

2
7

1
9

17

020

20
04

20
05

20
06

20
07

20
08

20
09

20
10

20
11

20
12

20
13

20
14

662 Scientometrics (2017) 110:643–672

123



cited articles are: University of Technology Sydney, at the Faculty of Information Tech-

nology in Sydney, Australia; King Fahd University of Petroleum and Minerals, at the

Information and Computer Science Department in Dhahran, Saudi Arabia; and University

of Technology Sydney, at the Research Center for Human Centered Technology Design in

Sydney, Australia.

Next, encompassing a scope from 70 to 80 cited articles, it is the Institute for Leadership

and Organizational Management, at the Department of Leadership and Organizational

Behaviour in Oslo, Norway. The American University, at the Kogod School of Business in

Washington, USA, the George Washington University, at the Department of Decision

Sciences, also in Washington, and the BI Norwegian Business School in Oslo, Norway,

presents an amount of 40–60 cited articles. Lastly, the Universidad de Castilla-La Mancha,

from the Alarcos Research Group in Ciudad Real, Spain, is ranked with less than 40 cited

articles on maturity model.

From the data collected to build the evolution of the citations on ‘‘maturity model’’, it

was observed that Piattini has three (3) articles on the subject, namely: ‘‘IQM3: Infor-

mation quality management maturity model’’ which was cited 24 (twenty-four) times,

‘‘MIS-PyME software measurement capability maturity model - Supporting the definition

of software measurement programs and capability determination’’ cited 8 (eight) times, and

‘‘A maturity model for the Spanish software industry based on ISO standards’’ cited 7

(seven) times, totaling 39 (thirty-nine) references on maturity model.

It can also be noticed, among the ten most cited authors, Piattini is the one with the least

amount of citations on the subject, whereas when analyzing in a general context he stands

out, since he has the largest number of citations when compared to the others.

Still from Table 3, the author with the highest impact on scientific research in a general

context, accounted for 3109 (three thousand, one hundred and nine) citations, exerts very

little impact when it comes to the subject of ‘‘maturity model’’, in this case 38 (thirty-eight)

citations.

The bibliometrical h-index was seen in Table 3, which measures the production of a

scientific researcher, wherein the index ‘‘h’’ stands for the number of articles having greater

Fig. 7 Network of the most cited authors on maturity model obtained through the Sci2Tool

Scientometrics (2017) 110:643–672 663

123



T
a
b
le

4
T

h
e

1
0

m
o
st

ci
te

d
au

th
o
rs

’
af

fi
li

at
io

n
s

an
d

th
e

ci
ta

ti
o
n
s

ev
o
lu

ti
o
n

o
f

th
ei

r
ar

ti
cl

es
o
n

m
at

u
ri

ty
m

o
d
el

A
ffi

li
at

io
n

M
at

u
ri

ty
m

o
d

el
ci

ta
ti

o
n

s
(M

.M
.C

)
2

0
0

4
2

0
0

5
2

0
0

6
2

0
0

7
2

0
0

8
2

0
0

9
2

0
1

0
2

0
1

1
2

0
1

2
2

0
1

3
2

0
1

4

S
am

fo
rd

U
n

iv
,

B
ro

ck
S

ch
B

u
si

n
es

s,
B

ir
m

in
g
h

am
,

A
L

U
S

A
1

0
9

0
1

3
7

8
1

5
1

7
1

0
1

4
1

7
1

7

D
R

K
R

es
ea

rc
h

,
B

ir
m

in
g
h

am
,

U
n

it
ed

S
ta

te
s

1
0

9
0

1
3

7
8

1
5

1
7

1
0

1
4

1
7

1
7

U
n

iv
er

si
ty

o
f

T
ec

h
n

o
lo

g
y

S
y

d
n

ey
,

F
ac

u
lt

y
o

f
In

fo
rm

at
io

n
T

ec
h

n
o
lo

g
y

,
S

y
d

n
ey

,
A

u
st

ra
li

a
9

8
0

3
8

7
1

4
1

1
1

8
7

1
2

1
1

7

K
in

g
F

ah
d

U
n
iv

er
si

ty
o
f

P
et

ro
le

u
m

an
d

M
in

er
al

s,
In

fo
rm

at
io

n
an

d
C

o
m

p
u

te
r

S
ci

en
ce

D
ep

ar
tm

en
t,

D
h

ah
ra

n
,

S
au

d
i

A
ra

b
ia

9
8

0
3

8
7

1
4

1
1

1
8

7
1

2
1

1
7

U
n

iv
er

si
ty

o
f

T
ec

h
n

o
lo

g
y

S
y

d
n

ey
,

R
es

ea
rc

h
C

en
te

r
fo

r
H

u
m

an
C

en
te

re
d

T
ec

h
n
o
lo

g
y

D
es

ig
n
,

S
y
d
n
ey

,
A

u
st

ra
li

a
9

8
0

3
8

7
1

4
1

1
1

8
7

1
2

1
1

7

In
st

it
u
te

fo
r

L
ea

d
er

sh
ip

an
d

O
rg

an
iz

at
io

n
al

M
an

ag
em

en
t,

D
ep

ar
tm

en
t

o
f

L
ea

d
er

sh
ip

an
d

O
rg

an
iz

at
io

n
al

B
eh

av
io

u
r,

O
sl

o
,

N
o

rw
ay

7
5

0
1

4
1

0
2

6
9

6
8

7
2

2

A
m

er
ic

an
U

n
iv

er
si

ty
,

K
o

g
o

d
S

ch
o
o

l
o

f
B

u
si

n
es

s,
W

as
h

in
g

to
n

,
U

n
it

ed
S

ta
te

s
5

6
0

0
0

0
0

0
0

0
1

6
1

8
2

2

G
eo

rg
e

W
as

h
in

g
to

n
U

n
iv

er
si

ty
,

D
ep

ar
tm

en
t

o
f

D
ec

is
io

n
S

ci
en

ce
s,

W
as

h
in

g
to

n
,

U
n

it
ed

S
ta

te
s

5
6

0
0

0
0

0
0

0
0

1
6

1
8

2
2

B
I

N
o
rw

eg
ia

n
B

u
si

n
es

s
S

ch
o
o
l,

O
sl

o
,

N
o
rw

ay
5

3
0

0
1

4
5

1
8

7
4

5
7

2

U
n
iv

er
si

d
ad

d
e

C
as

ti
ll

a-
L

a
M

an
ch

a,
A

la
rc

o
s

R
es

ea
rc

h
G

ro
u
p
,

C
iu

d
ad

R
ea

l,
S

p
ai

n
3

9
0

0
0

0
0

2
2

7
1

9
1

7

664 Scientometrics (2017) 110:643–672

123



than or equal to an ‘‘h’’ number of citations (HIRSCH, 2005). Thus, from the h-index an

author’s productivity can be quantified by showing the impact they have in a general

context on the scientific community. A connection between this indicator and the number

of the authors’ citations can be noticed, since those with the highest number of citations

showed higher h-index.

During the analysis of Table 3 it was found out that the 10 authors who have their most

cited work as articles on maturity model, turned out to be also prominent in the scientific

community in a variety of research subjects, and several of them possess a vast amount of

publications and citations. Thereby, the scientific research on maturity model that has been

done based on the articles developed by these authors are assumed as righteous and

reliable.

Identifying scientific gaps

Table 5 presents the scientific gaps in the most recent articles on maturity model written by

those most cited authors. Some of the most cited authors engaged in a joint effort for the

preparation of the most recent articles on maturity model.

(1) Lockamy and McCormack have written their last article on maturity model in 2004,

‘‘The development of the supply chain management process maturity model using

the concepts of business process orientation’’, published in the Supply Chain

Management journal. In it, they propose the use of the measurements obtained

through the supply chain maturity to improve the points where the maturity

measurements fall short.

The research conducted by Lockamy and McCormack presents the use of the maturity

model for the supply chain through a carefully evaluated table, which was well-grounded

in a prime theoretical reference, and suggests that the performance of the supply chain

obtained by SCOR (Supply Chain Operations Reference) is strongly related to the maturity

of the supply chain.

The research indicates that direct performance measures, such as cycle times and

inventory levels, are closely related to the supply chain maturity. All these connections

suggest that the measurements of the supply chain maturity can be used to improve those

points where the maturity measurements fall short.

Nevertheless, the measurement method of overall performance used in this research is

not enough, and further clarification is needed in future studies, as well as an investigation

of the supply chain maturity and financial measures.

(2) In their article, Wilson, Niazi and Zowghi identifies as scientific gap the need to

improve the implementation framework of maturity model that contains three

components: the SPI implementation plan (software process improvement), the SPI

implementation script and the SPI implementation model.

A maturity model for the SPI implementation (software process improvement) is pre-

sented, so it could help companies evaluate and improve their SPI implementation pro-

cesses. This research’s model is extracted from CMMI (capability maturity model

integrity), based on CSFs (critical success factors) and some critical barriers are identified

through a literature review and an empirical study.

To develop this model, experiences, opinions and the views of professionals were

analyzed in order to identify the factors that positively and negatively impact on the SPI

Scientometrics (2017) 110:643–672 665

123



T
a
b
le

5
T

h
e

sc
ie

n
ti

fi
c

g
ap

s
id

en
ti

fi
ed

in
th

e
re

ce
n
t

ar
ti

cl
es

o
n

m
at

u
ri

ty
m

o
d
el

o
f

th
e

m
o
st

ci
te

d
au

th
o
rs

A
u

th
o

r
C

o
-a

u
th

o
rs

L
as

t
p

ap
er

o
n

m
at

u
ri

ty
m

o
d

el
Y

ea
r

Jo
u

rn
al

/F
I

(S
JR

)
S

ci
en

ti
fi

c
g

ap

L
o

ck
am

y
,A

M
cC

o
rm

ac
k
,

K
.

(1
)

T
h

e
d

ev
el

o
p

m
en

t
o

f
a

su
p

p
ly

ch
ai

n
m

an
ag

em
en

t
p

ro
ce

ss
m

at
u

ri
ty

m
o

d
el

u
si

n
g

th
e

co
n

ce
p

ts
o

f
b

u
si

n
es

s
p

ro
ce

ss
o

ri
en

ta
ti

o
n

2
0

0
4

S
u

p
p

ly
C

h
ai

n
M

an
ag

em
en

t/
1

.9
3
1

T
h

e
au

th
o

rs
p

ro
p

o
se

th
e

u
se

o
f

th
e

m
ea

su
re

m
en

ts
o

b
ta

in
ed

th
ro

u
g

h
th

e
su

p
p

ly
ch

ai
n

m
at

u
ri

ty
to

im
p

ro
v
e

p
o

in
ts

w
h

er
e

th
e

m
at

u
ri

ty
m

ea
su

re
m

en
ts

fa
ll

sh
o

rt

M
cC

o
rm

ac
k
,

K
.

L
o

ck
am

y
,A

T
h

e
d

ev
el

o
p

m
en

t
o

f
a

su
p

p
ly

ch
ai

n
m

an
ag

em
en

t
p

ro
ce

ss
m

at
u

ri
ty

m
o

d
el

u
si

n
g

th
e

co
n

ce
p

ts
o

f
b

u
si

n
es

s
p

ro
ce

ss
o

ri
en

ta
ti

o
n

2
0

0
4

S
u

p
p

ly
C

h
ai

n
M

an
ag

em
en

t/
1

.9
3
1

a
T

h
e

au
th

o
rs

p
ro

p
o
se

th
e

u
se

o
f

th
e

m
ea

su
re

m
en

ts
o

b
ta

in
ed

th
ro

u
g

h
th

e
su

p
p

ly
ch

ai
n

m
at

u
ri

ty
to

im
p

ro
v
e

p
o

in
ts

w
h

er
e

th
e

m
at

u
ri

ty
m

ea
su

re
m

en
ts

fa
ll

sh
o

rt

W
il

so
n
,

D
.

N
ia

zi
,

M
.K

.,
Z

o
w

g
h

i,
D

.
(2

)
A

m
at

u
ri

ty
m

o
d

el
fo

r
th

e
im

p
le

m
en

ta
ti

o
n

o
f

so
ft

w
ar

e
p

ro
ce

ss
im

p
ro

v
em

en
t:

A
n

em
p

ir
ic

al
st

u
d

y

2
0

0
5

Jo
u

rn
al

o
f

S
y

st
em

s
an

d
S

o
ft

w
ar

e/
1

.3
8
1

T
h

e
re

co
m

m
en

d
at

io
n

is
to

im
p

ro
v
e

th
e

im
p

le
m

en
ta

ti
o

n
fr

am
ew

o
rk

co
n
ta

in
in

g
th

re
e

co
m

p
o
n
en

ts
:

im
p
le

m
en

ta
ti

o
n

p
la

n
o

f
th

e
S

P
I,

th
e

S
P

I
im

p
le

m
en

ta
ti

o
n

sc
ri

p
t

an
d

it
s

im
p

le
m

en
ta

ti
o

n
m

o
d

el
.

A
b

et
te

r
as

se
ss

m
en

t
m

o
d

el
ca

n
b

e
su

g
g
es

te
d

N
ia

zi
,

M
ah

m
o
o
d

K
.

W
il

so
n
,

D
.,

Z
o

w
g
h

i,
D

.
A

m
at

u
ri

ty
m

o
d
el

fo
r

th
e

im
p
le

m
en

ta
ti

o
n

o
f

so
ft

w
ar

e
p

ro
ce

ss
im

p
ro

v
em

en
t:

A
n

em
p

ir
ic

al
st

u
d

y

2
0

0
5

Jo
u

rn
al

o
f

S
y

st
em

s
an

d
S

o
ft

w
ar

e/
1

.3
8
1

a
T

h
e

re
co

m
m

en
d

at
io

n
is

to
im

p
ro

v
e

th
e

im
p

le
m

en
ta

ti
o

n
fr

am
ew

o
rk

co
n
ta

in
in

g
th

re
e

co
m

p
o
n
en

ts
:

im
p
le

m
en

ta
ti

o
n

p
la

n
o

f
th

e
S

P
I,

th
e

S
P

I
im

p
le

m
en

ta
ti

o
n

sc
ri

p
t

an
d

it
s

im
p

le
m

en
ta

ti
o

n
m

o
d

el
.

A
b

et
te

r
as

se
ss

m
en

t
m

o
d

el
ca

n
b

e
su

g
g
es

te
d

Z
o
w

g
h
i,

D
id

ar
N

ia
zi

,
M

.K
.,

W
il

so
n
,

D
A

m
at

u
ri

ty
m

o
d
el

fo
r

th
e

im
p
le

m
en

ta
ti

o
n

o
f

so
ft

w
ar

e
p

ro
ce

ss
im

p
ro

v
em

en
t:

an
em

p
ir

ic
al

st
u

d
y

2
0

0
5

Jo
u

rn
al

o
f

S
y

st
em

s
an

d
S

o
ft

w
ar

e/
1

.3
8
1

a
T

h
e

re
co

m
m

en
d

at
io

n
is

to
im

p
ro

v
e

th
e

im
p

le
m

en
ta

ti
o

n
fr

am
ew

o
rk

co
n
ta

in
in

g
th

re
e

co
m

p
o
n
en

ts
:

im
p
le

m
en

ta
ti

o
n

p
la

n
o

f
th

e
S

P
I,

th
e

S
P

I
im

p
le

m
en

ta
ti

o
n

sc
ri

p
t

an
d

it
s

im
p

le
m

en
ta

ti
o

n
m

o
d

el
.

A
b

et
te

r
as

se
ss

m
en

t
m

o
d

el
ca

n
b

e
su

g
g
es

te
d

G
o

tt
sc

h
al

k
,

P
et

te
r

–
(3

)
M

at
u

ri
ty

m
o

d
el

fo
r

em
ai

l
co

m
m

u
n

ic
at

io
n

in
k

n
o

w
le

d
g

e
o

rg
an

iz
at

io
n

s:
th

e
ca

se
o

f
p

o
li

ce
in

v
es

ti
g

at
io

n
s

2
0

0
8

In
te

rn
at

io
n

al
Jo

u
rn

al
o

f
L

aw
,

C
ri

m
e

an
d

Ju
st

ic
e/

0
.2

4
9

T
h

e
au

th
o

rs
su

g
g

es
t

an
em

p
ir

ic
al

st
u

d
y

in
o

rd
er

to
te

st
th

e
m

o
d
el

’s
p
ro

p
o
se

d
st

ag
es

,
ch

ec
k
in

g
th

e
p
er

fo
rm

an
ce

o
f

th
e

p
o

li
ce

in
v

es
ti

g
at

io
n

w
h

en
ad

o
p

ti
n

g
th

e
id

ea
l

m
ea

su
re

in
th

e
co

m
m

u
n

ic
at

io
n

v
ia

e-
m

ai
l

p
h

as
e

L
ee

,
G

w
an

h
o

o
K

w
ak

,
Y

.H
.

(4
)

A
n

O
p

en
G

o
v

er
n

m
en

t
M

at
u
ri

ty
M

o
d
el

fo
r

so
ci

al
m

ed
ia

-b
as

ed
p

u
b

li
c

en
g

ag
em

en
t

2
0

1
2

G
o

v
er

n
m

en
t

In
fo

rm
at

io
n

Q
u
ar

te
rl

y
/1

.2
0
3

A
s

a
fu

tu
re

w
o

rk
,

th
e

au
th

o
r

su
g

g
es

ts
th

at
th

e
m

o
d

el
is

ri
g

o
ro

u
sl

y
v

al
id

at
ed

th
ro

u
g

h
th

e
u

se
o

f
q

u
an

ti
ta

ti
v

e
em

p
ir

ic
al

d
at

a
an

d
in

co
rp

o
ra

te
th

e
p

u
b

li
c

p
er

sp
ec

ti
v

e
to

th
e

m
o

d
el

666 Scientometrics (2017) 110:643–672

123



T
a
b
le

5
co

n
ti

n
u
ed

A
u

th
o

r
C

o
-a

u
th

o
rs

L
as

t
p

ap
er

o
n

m
at

u
ri

ty
m

o
d

el
Y

ea
r

Jo
u

rn
al

/F
I

(S
JR

)
S

ci
en

ti
fi

c
g

ap

S
o

ll
i-

S
æ

th
er

,
H

an
s

G
o

tt
sc

h
al

k
,

P
.

(5
)

M
at

u
ri

ty
m

o
d

el
fo

r
IT

o
u

ts
o

u
rc

in
g

re
la

ti
o
n
sh

ip
s

2
0

0
6

In
d

u
st

ri
al

M
an

ag
em

en
t

an
d

D
at

a
S

y
st

em
s/

0
.8

4
6

S
ea

rc
h

ca
re

fu
ll

y
fo

r
o

th
er

ex
is

ti
n

g
p

h
as

es
in

an
IT

o
u

ts
o

u
rc

in
g

re
la

ti
o

n
sh

ip
,

d
ev

el
o

p
an

d
ex

p
la

in
th

e
im

p
o

rt
an

t
is

su
es

at
ea

ch
st

ag
e

an
d

cl
ar

if
y

th
e

th
eo

re
ti

ca
l

an
d

em
p
ir

ic
al

co
n

tr
ib

u
ti

o
n

s
th

at
m

ak
es

o
f

th
e

re
se

ar
ch

m
o
re

th
an

ju
st

a
sc

ie
n
ti

fi
c

co
n
tr

ib
u
ti

o
n

K
w

ak
,

Y
o

u
n

g
H

o
o

n
L

ee
,

G
.

A
n

O
p

en
G

o
v

er
n

m
en

t
M

at
u

ri
ty

M
o

d
el

fo
r

so
ci

al
m

ed
ia

-b
as

ed
p

u
b

li
c

en
g

ag
em

en
t

2
0

1
2

G
o

v
er

n
m

en
t

In
fo

rm
at

io
n

Q
u
ar

te
rl

y
/1

.2
0
3

a
A

s
a

fu
tu

re
w

o
rk

,
th

e
au

th
o

r
su

g
g
es

ts
th

at
th

e
m

o
d

el
is

ri
g

o
ro

u
sl

y
v

al
id

at
ed

th
ro

u
g

h
th

e
u

se
o

f
q

u
an

ti
ta

ti
v

e
em

p
ir

ic
al

d
at

a
an

d
in

co
rp

o
ra

te
th

e
p

u
b

li
c

p
er

sp
ec

ti
v

e
to

th
e

m
o

d
el

P
ia

tt
in

i,
M

ar
io

G
ar

zá
s,

J.
,

P
in

o
,

F
.

J.
,

F
er

n
án

d
ez

,
C

.M
.

(6
)

A
m

at
u

ri
ty

m
o
d

el
fo

r
th

e
S

p
an

is
h

so
ft

w
ar

e
in

d
u

st
ry

b
as

ed
o

n
IS

O
st

an
d
ar

d
s

2
0

1
3

C
o

m
p
u

te
r

S
ta

n
d

ar
d

s
an

d
In

te
rf

ac
es

/0
.7

4
4

E
n
h
an

ce
th

e
d
ev

el
o
p
m

en
t

o
f

an
o
rg

an
iz

at
io

n
al

m
at

u
ri

ty
m

o
d

el
fo

r
th

e
so

ft
w

ar
e

in
d

u
st

ry
in

S
p

ai
n

a
Id

en
ti

ca
l

sc
ie

n
ti

fi
c

g
ap

s,
si

n
ce

th
ey

re
fe

r
to

th
e

sa
m

e
ar

ti
cl

e

Scientometrics (2017) 110:643–672 667

123



implementation, however the authors of this study emphasize the need for improvement

and a better evaluation of the model.

The authors should review the model in the future based on feedback from different

practitioners and formulate a new version of it, then a case study will be conducted in order

to validate and test the model in a practical way. Based on both the maturity model and the

empirical study, the purpose is the structuring of an implementation framework consisting

of three components: implementation plan of the SPI, the SPI implementation script and its

implementation model. Theoretically, this paper presents only one component, namely the

SPI implementation script.

The implementation framework is in its early stages and needs to be improved, so that a

case study could be undertaken in order to test and validate it, as well as point out which

aspects need to be adjusted.

(3) Gottschalk wrote his last article on maturity model in 2008 on the International

Journal of Law, Crime and Justice under the title: ‘‘Maturity model for email

communication in knowledge organizations: The case of police investigations’’.

This article proposes a maturity model to the communication via email within a

work environment in order to help organizations focus on e-mail as a tool, so that the

benefits exceed costs and damages.

The model has four stages: person-technology, person–person, person-information and

person-application. The author suggests a future empirical study testing the stages pro-

posed in this model, checking the investigation performance while taking the appropriate

action in the communication via email phase, which could be stated as the work’s scientific

gap.

It is acknowledged the necessity to constantly check whether the stages or levels used in

maturity models are consistent with the process which the model is being prepared for, so

that an effective maturity model could be obtained.

(4) Lee and Kwak published their last article on maturity model in 2012 on the

Government Information Quarterly, with the title ‘‘An Open Government Maturity

Model for social media-based public engagement’’. The research suggests the

existence of different levels of maturity to achieve a government with greater public

engagement.

They propose that, when moving from one maturity level to the next one in an orderly

manner, governmental agencies can avoid unnecessary risks and systematically build its

open-government capabilities, enabling both public and private sectors to participate,

collaborate and innovate together.

The model, which was validated through a focus group and several field interviews, is

mostly based on the perspective of the governmental agency. Therefore, the author sug-

gests that in a future work the model be rigorously validated through the use of quantitative

empirical data, and incorporates the public perspective.

The maturity model developed by Lee and Kwak is based largely on the government’s

perspective, so future research should be based on the perspectives of the public. The

authors claim that there are situations where the existing linearity in the elaborated model

would not bring the expected practicality due to other factors that might influence it, such

as political, organizational and financial ones.

That way, some agencies will not use this model in its totality, requiring adjustments to

meet specific needs. Thus, it is necessary a reformulation of the model by examining how

668 Scientometrics (2017) 110:643–672

123



government agencies were able to manage certain existing tensions prior to their drafting,

and, finally, how to customize the maturity model for more specific conditions.

(5) Gottschalk was co-author of the last publication of Solli-Sæther on maturity model,

published in 2006 on the Industrial Management and Data System journal, under the

title ‘‘Maturity model for IT outsourcing relationships’’. This research presents a

maturity model for IT outsourcing based on organizational theories and practices,

identifying three stages of maturity: cost, resource and partnership.

The analyzed variables for each stage were: economic benefits, primary transactions,

contractual completeness, vendor behavior control, demarcation of labor, core competence

management, vendor resource exploitation, relationship exploitation, social exchange

exploitation, and stakeholder management.

According to Solli-Sæther, the research has several shortcomings that should be

addressed in future research, for example: carefully check out for other existing phases in

an IT outsourcing relationship, develop and explain the important issues at each stage and

clarify the theoretical and empirical contributions that make of the research more than only

a scientific contribution.

In order to validate the model stages, it is necessary to show that the transition occurs by

their means, that is, to empirically demonstrate that most relationships will evolve toward

cost-resources–partnership. A scientific gap is then identified: the necessity of measuring

the model’s reference variables, to which the authors suggest the use of the Guttman scale.

(6) Piattini was the latest to publish an article on maturity model, with the theme ‘‘The

maturity model for the Spanish software industry based on ISO standards’’. Piattini

has Garzas, Pino and Fernandez as co-authors and they identified the improvement

of the development of an organizational maturity model for the software industry in

Spain as a scientific gap.

This study presents the use and adaptation of some ISO models in the development of an

organizational maturity model for the software industry in Spain, in order to minimize the

deficiencies found in small software development companies by implementing models that

are most widely used in large organizations.

With the development of the project to build the model, an application was initially

performed in 16 Spanish companies belonging to AENOR (Spanish Association for

Standardization and Certification) to obtain certification. According to the author, by 2013

approximately 38 companies have already obtained levels 2 and 3 certifications and several

others were awaiting certification until the next year.

Arising from the need for an international ISO certification for process improvement in

the organizational maturity level, the model presented in this article has been created,

which evaluates software processes through maturity levels. The proposed model, based on

ISO standards, is specific to small Spanish companies in the software industry, aiming to

minimize the problems that occurred when process improvement models directed to large

companies were implemented, such as CMMI-DEV (Capability Maturity Model-Integra-

tion for Development).

The proposed model has the advantage of not being as expensive, neither as complex as

the CMMI-DEV. To elaborate the model known as software engineering maturity model,

AENOR has formed a group of researchers and professionals in software engineering to

develop and apply a maturity model consisting of three components: (a) evaluation of the

CMM, (b) the model of a software life cycle, and (c) audit process based on the standards

ISO/IEC 15504, ISO/IEC 12207:2008 e ISO/IEC 17021.

Scientometrics (2017) 110:643–672 669

123



For that reason, besides of fulfilling the scientific gap of enhancing the development of

an organizational maturity model for the software industry in Spain, this article also brings

a great incentive to researchers on maturity models, identifying how useful and effective

they can be. The proposed maturity model has been developed in Spain and, according to

the authors, it was well diffused across the region, thus it can be adapted to other regions

and/or other business sectors.

Conclusion

Through the bibliometric analysis on the topic ‘‘maturity model’’ it was possible to

characterize the importance of the subject in the decade 2004–2014. Considering the

research areas presented in the study, the subject has a comprehensive approach involving

the exact, human and biological sciences. Moreover, the maturity model is widely

employed in project management to promote continuous improvement, as well as being a

theme in progress that has been gaining relevance in the scientific community.

From the bibliometric analysis on maturity model, it has been also observed that new

models arise from formerly developed ones, acting as guides or examples to be followed,

which are then adapted in order to meet the requirement of a specific area, process or

system.

This paper presents a bibliometric analysis of the maturity model in a general manner,

not specifically analyzing an area for the application of the model. It also brings into light

the analysis of published articles during an extended period of time.

Authors who have been publishing on the subject have certain relevance in the scientific

community, since they have a great number of publications in various areas, in addition to

the remarkable amount of citations each one possesses. Therefore, the articles which have

been published on the subject have a desirable reliability.

Through the identification of the scientific gaps, a focus on continuous as well as

processes’ and systems’ improvement is noticed, in addition to other situations that may

need to achieve a desirable maturity. For this identification to be performed, the most

recent published article on maturity model of the most cited authors has been analyzed, and

it has been perceived that the publishing years are not close to the current date. This

occurrence supported the conclusion that these authors are often cited due to the relevance

of their published articles to the academic community, bringing theoretical collaborations

and new ideas of how to develop maturity models, while also demonstrating that they

could be applied to various sectors.

This article may also assist researchers in pursuing ideas for future studies on maturity

models, identifying which key points cannot be left incomplete in their research, as well as

serve to identify if their studies are on the right path to bringing scientific collaborations to

the academic community. Researchers wishing to deepen their knowledge on maturity

models will be aware of the most relevant articles and most distinguished authors on the

subject, making it easier the search for information.

As the main scientific contribution of this paper, the presentation of the theme of

maturity model, its applications and its increasing importance yet to be explored in the

scientific community could be enumerated, in the hope of encouraging further study and

research on the subject. Some of the authors who had previously worked with bibliometric

analyzes, namely Blagus et al. (2015), Rubem et al. (2015), Ellegaard and Wallin (2015),

among others, did not presented detailed tables with citations evolution graphics, as well as

tables identifying the articles’ scientific gaps.

670 Scientometrics (2017) 110:643–672

123



In relation to its main applied contribution is the identification and analysis of major

studies that have contributed significantly to the scientific research, allowing and

encouraging the subject adoption by various organizational sectors.

Due to the relatively novelty of the subject, a more intense analysis could not be

performed since it would probably lack information. Up to this moment, this article por-

trays the sole bibliometric analysis for the theme ‘‘maturity model’’.

Finally, a future deeper analysis on the subject is suggested, covering areas of study

separately or a bibliometric analysis on the topic related to a more specific model.

Acknowledgements We appreciate the permission given by Emerald Publisher for we use Figs. 1 and 2 in
our text.

References

Albu, E., & Panzar, C. (2010). A new tool for assessing maturity aligment: The enterprise maturity matrix.
Performance Improvement, 49(9), 35–47.

Blagus, R., Leskošek, B. L., & Stare, J. (2015). Comparison of bibliometric measures for assessing relative
importance of researchers. Scientometrics, 105(3), 1743–1762.

Crosby, P. B. (1979). Quality is free: The art of making quality certain. New York: McGrawHill Companies.
Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the

impact? Scientometrics, 105(3), 1809–1831.
Elsevier. (2015). http://www.elsevier.com/solutions/scopus. Accessed 03 Sept 2015.
Fischer, D. (2004). The business process maturity model: A practical approach for identifying opportunities

for optimization. Resource document. BPTrends. http://www.bptrends.com/bpt/wp-content/
publicationfiles/10-04%20ART%20BP%20Maturity%20Model%20-%20Fisher.pdf. Accessed 06
June 2016.

Garzás, J., et al. (2013). A maturity model for the Spanish software industry based on ISO standards.
Computer Standards and Interfaces, 35(6), 616–628.

Golev, A., Corder, G. D., & Giurco, D. P. (2015). Barriers to industrial symbiosis: Insights from the use of a
maturity grid. Journal of Industrial Ecology, 19(1), 141–153.

Gorschek, T. (2012). Introduction of a process maturity model for market-driven product management and
requirements engineering. Journal of Software: Evolution and Process, 24, 83–113.

Harmon, P. (2004). Evaluating an organization’s business process maturity. Business Process Trends
Newsletter, 2(3), 1–11.

Hirsch, J. E. (2005). An index to quantify an individual’s s scientific research output. Proceedings of the
National Academy of Sciences, 102(46), 16569–16572.

Jin, D., Chai, K., & Tan, K. (2014). New service development maturity model. Managing Service Quality:
An International Journal, 24(1), 86–116.

Jorgensen, F., et al. (2007). Lean maturity, lean sustainability. Advances in Production Management Sys-
tems, 246, 371–378.

León, H., et al. (2011). Lean product development research: Current state and future directions. Engineering
Management Journal, 23(1), 29–51.

Liker, J., & Morgan, J. (2011). lean product development as a system: A case study of body and stamping
development at Ford. Engineering Management Journal, 23(1), 16–28.

Maier, A. M., Moultrie, J., & Clarckson, P. J. (2012). Assessing organizational capabilities: Reviewing and
guiding the development of maturity grids. IEEE Transactions on Engineering Management, 59(1),
138–159.

Marx, F., Wortmann, F., & Mayer, J. H. (2012). A maturity model for management control systems five
evolutionary steps to guide development. Business and Information Systems Engineering, 4(4),
193–207.

Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative
analysis. Scientometrics, 106, 213–228.

Ngai, N. W. T., et al. (2013). Energy and utility management maturity model for sustainable manufacturing
process. International Journal of Production Economics, 146, 453–464.

Paulk, M. C., et al. (1993). Capability maturity model, version 1.1. IEEE Software, 10(4), 18–26.

Scientometrics (2017) 110:643–672 671

123

http://www.elsevier.com/solutions/scopus
http://www.bptrends.com/bpt/wp-content/publicationfiles/10-04%20ART%20BP%20Maturity%20Model%20-%20Fisher.pdf
http://www.bptrends.com/bpt/wp-content/publicationfiles/10-04%20ART%20BP%20Maturity%20Model%20-%20Fisher.pdf


Pigosso, D. C. A., Rozenfeld, H., & McAloone, T. C. (2013). Ecodesign maturity model: A management
framework to support ecodesign implementation into manufacturing companies. Journal of Cleaner
Production, 59, 160–173.

Poppendieck, M. (2004). The lean maturity measure assessment and implementation. Lecture Notes in
Computer Science, 3134, 3–18.

Randeree, K., Mahal, A., & Narwani, A. (2012). A business continuity management maturity model for the
UAE banking sector. Business Process Management Journal, 18(3), 472–492.

Robinson, K. A., Saldanha, I. J., & Mckoy, N. A. (2011) Frameworks for determining research gaps during
systematic reviews. Resource document. Agency for Healthcare Research and Quality (US). http://
www.ncbi.nlm.nih.gov/books/NBK62478/pdf/Bookshelf_NBK62478.pdf. Accessed 14 July 2016.

Rubem, A. P. S., Moura, A. L., & Mello, J. C. C. B. S. (2015). Comparative analysis of some individual
bibliometric indices when applied to groups of researchers. Scientometrics, 102(1), 1019–1035.

Schmietendorf, A., Scholz, A., & Rautenstrauch, C. (2000) Evaluating the performance engineering process.
WOSP2000: Second International Workshop on Software and Performance, doi:10.1145/350391.
350413.

Souza, T. F., & Gomes, C. F. S. (2015). Assessment of maturity in project management: A bibliometric
study of main models. Procedia Computer Science, 55, 92–101.

Spanyi, A. (2004) Beyond process maturity to process competence. Resource document. BPTrends. http://
www.bptrends.com/bpt/wp-content/publicationfiles/06-04%20ART%20Dev%20Business%
20Process%20Competence%20-%20Spanyi.pdf. Accessed 04 June 2016.

Uriona-Maldonado, M., Santos, R. N. M., & Varvakis, G. (2012). State of the art on the systems of
innovation research: A bibliometrics study up to 2009. Scientometrics, 91(3), 977–996.

Yang, L., et al. (2013). Global trends of solid waste research from 1997 to 2011 by using bibliometric
analysis. Scientometrics, 96, 133–146.

Zhuang, Y., et al. (2013). Global remote sensing research trends during 1991–2010: A bibliometric analysis.
Scientometrics, 96, 203–219.

672 Scientometrics (2017) 110:643–672

123

http://www.ncbi.nlm.nih.gov/books/NBK62478/pdf/Bookshelf_NBK62478.pdf
http://www.ncbi.nlm.nih.gov/books/NBK62478/pdf/Bookshelf_NBK62478.pdf
http://dx.doi.org/10.1145/350391.350413
http://dx.doi.org/10.1145/350391.350413
http://www.bptrends.com/bpt/wp-content/publicationfiles/06-04%20ART%20Dev%20Business%20Process%20Competence%20-%20Spanyi.pdf
http://www.bptrends.com/bpt/wp-content/publicationfiles/06-04%20ART%20Dev%20Business%20Process%20Competence%20-%20Spanyi.pdf
http://www.bptrends.com/bpt/wp-content/publicationfiles/06-04%20ART%20Dev%20Business%20Process%20Competence%20-%20Spanyi.pdf

	Maturity models: identifying the state-of-the-art and the scientific gaps from a bibliometric study
	Abstract
	Introduction
	Theoretical framework
	Research methodology
	Results and discussion
	Analysis of the evolution of publications on maturity model, research areas and most frequently used keywords
	Bibliometric analysis of the ten most cited articles on maturity model
	Bibliometric analysis of the ten most cited authors on maturity model
	Identifying scientific gaps

	Conclusion
	Acknowledgements
	References