Abstract
Purpose: The overall purpose of this article is to provide an overview of studies related to the orchestration of dynamic capabilities. The specific goal is to identify the main paths for a future research agenda.
Methodology: A bibliometric study and content analysis on Dynamic Capability Orchestration, using software MaxQda, Bibliometrix, and VosViewer. The collected data resulted in a final sample of 54 articles, published from 2003 to 2021.
Results: The results identified four clusters that unfold into 15 research lines. The clusters are: (i) Studies on Business Ecosystems; (ii) Dynamic Capabilities and their Orchestration via Microfoundations; (iii) Internationalization; and (iv) Technology and Digitalization.
Conclusions: The analysis of the four clusters and the deepening of research paths showed a relationship between clusters, conceptual elements, and orchestration of capabilities, which are presented as a Dynamic Capability Orchestration Model, with an emphasis on the fields of strategy and innovation.
Contributions: The contributions to the studies of dynamic capability orchestration regard the presentation of research clusters that cover the field of study and show routes for future research. These clusters are linked to Business Ecosystems, Orchestration via Micro-foundations, Internationalization, and Technology and Digitalization. Within these groups, there are research flows that articulate referential concepts for creating research lines and new scientific propositions and hypotheses.
Keywords: Orchestration of dynamic capabilities. Dynamic capabilities. Asset orchestration. Systematic review.
Resumo
Objetivo: O objetivo geral deste trabalho é apresentar um panorama de pesquisas relacionadas à orquestração de capacidades dinámicas. Já o objetivo específico é identificar os principais caminhos para a realização de uma agenda para pesquisas futuras.
Metodologia: Estudo bibliométrico e análise de conteúdo sobre o tema Orquestração de Capacidades Dinámicas com a utilização dos softwares: MaxQda, Bibliometrix e VosViewer. Os dados coletados representam uma amostra final de 54 artigos no período de 2003 e 2021.
Resultados: Os resultados identificaram quatro clusters que se desdobram em 15 fluxos de pesquisa. Os clusters de pesquisa identificados são: (i) Estudos sobre Ecossistemas de Negocios, (ii) Capacidades Dinâmicas e sua Orquestração Via Microfundamentos; (iii) Internacionalização; e (iv) Tecnología e Digitalização.
Conclusões: A análise dos clusters e aprofundamento nos caminhos de pesquisa, mostrou que existe uma relação entre os clusters, elementos conceituais e orquestração de capacidades que são apresentados em formato de um Modelo de Orquestração de Capacidades Dinâmicas estressado no campo da estratégia e inovação.
Contribuções: Para os estudos de orquestração de capacidades dinâmicas, reside na apresentação de clusters de pesquisa que distribuem o campo de estudo e apresentam caminhos para pesquisas futuras. Estes clusters estão ligados a Ecossistemas de Negócios, Orquestração via Microfundamentos, Internacionalização e Tecnologia e Digitalização. Dentro destes clusters encontram-se fluxos de pesquisas que articulam conceitos referenciais para a criação de linhas de pesquisa e novas proposições e hipóteses científicas.
Palavras-chave: Orquestração de capacidades dinâmicas. Capacidades dinâmicas. Orquestração de ativos. Revisão sistemática.
Resumen
Objetivo: El presente trabajo tiene como propósito presentar una visión general de la literatura relacionada con la orquestación de capacidades dinámicas por intermedio de la identificación de los principales caminos evidenciados por la clusterización y los elementos conceptuales para la realización de una agenda para futuras investigaciones.
Metodología: Estudio bibliométrico y análisis de contenido sobre la orquestación temática de capacidades dinámicas con el uso de software: MaxQda, Bibliometrix y VosViewer. Como resultado se representa una muestra final de 54 artículos en el periodo 2003 y 2021.
Originalidad: Este estudio se basa en la comprensión de las diferentes formas de utilizar los microfundamentos a partir de la orquestación de capacidades dinámicas para los campos de la estrategia y la innovación.
Resultados: Se identificaron cuatro clusters como categorías de investigación, que se despliegan en 15 subcategorías. Así, son esos los flujos de investigación para proponer una agenda futura: (i) estudios sobre ecosistemas empresariales, (ii) capacidades dinámicas y su orquestación por microfundamentos; iii) internacionalización; y iv) tecnología y digitalización.
Conclusiones: El análisis de clusters y profundización en las rutas de investigación mostró que existe una relación entre la clusterización, elementos conceptuales y orquestación de capacidades que resultó en un modelo de orquestación de capacidades dinámicas para el campo de la estrategia y la innovación.
Contribuciones: El progreso se revela a través de grupos de investigación que distribuyen el campo de estudio en la presentación de nuevos caminos y preguntas para futuras líneas de investigación más allá del modelo teórico para los ecosistemas empresariales.
Palabras clave: Orquestación. Capacidades dinámicas. Orquestación de recursos. Orquestación de capacidades dinámicas. Análisis bibliométrica.
1 Introduction
The study on Orchestration is part of the seminal research field of Dynamic Capabilities (Teece, Pisano & Shuen, 1997; Helfat & Peteraf, 2015), described as an organization's ability to seek, integrate, build, and reconfigure internal and external competencies, in order to deal with dynamic environments, in constant and quick transformation (Shuen, Feiler & Teece, 2014). From this definition, dynamic capabilities gave rise to several studies that address their impacts on innovation, the types of capacities, their applications, consequences, and managerial processes (Teece et al., 1997; Agarwal & Selen, 2013; Helfat & Peteraf, 2015).
Among such studies, the research field on Orchestration of Dynamic Capabilities emerged, as the simultaneous search for exploiting and seizing opportunities requires agility and change of organizational processes (O'Reilly III & Tushman, 2011; Yoshikawa et al., 2020). It comprises the search, configuration, and change of groups of tangible and intangible assets, routines, and competencies to generate competitive advantage and increase organizational performance (Helfat & Peteraf, 2015). The orchestration process refers to the management of companies' capabilities via micro-foundations, to generate new capabilities and organizational agility within business ecosystems (Shuen et al., 2014).
The literature on Dynamic Capability Orchestration covers studies on business ecosystems that investigate the relationship between different ecosystems and capacity building (Pitelis & Teece, 2018; Linde et al., 2021). Micro-foundations have a key role in the strategic articulation for leveraging entrepreneurial resources and generating innovations, through new capabilities that enable reconfiguring business models of different types of firms (Sirmon & Hitt, 2009; Helfat & Peteraf, 2015; Brink, 2019).
Orchestration of Dynamic Capabilities also covers internationalization studies that address process internalization and capacity reconfiguration as catalysts for entrepreneurship and innovation (Shuen et al., 2014; Tasheva & Nielsen, 2020), in addition to exploring the dynamics of knowledge management in the matrix structures of meta-multinational firms (Lesserd, Teece & Leih, 2016). In the field of Information Technology and Digitalization, reconfiguring resources for building and adopting new technologies to improve firm performance is also addressed under the theoretical lens of Capacity Orchestration (Helfat & Raubitschek, 2018; Lee & Kim, 2021).
The academic production shows a large increase in the number of articles involving orchestration of dynamic capabilities, in parallel with the growth of this research topic (Hayter & Cahoy, 2018). Thus, the need to organize future research trends by aligning research agendas and suggestions for seminal papers becomes relevant. Based on this context, we defined the research question: "What is the current overview of research on orchestration of dynamic capabilities?", which led us to the general objective of the article - to survey the studies related to this topic, through a bibliometric study and content analysis. The specific objective was to identify the main paths for building an agenda for future research.
The research gap that the paper aimed to fill regards understanding the different ways of using the foundations of dynamic capability orchestration for studies on strategy and innovation (Helfat & Peteraf, 2015; Helfat & Raubitscheck, 2018; Linde et al., 2021). The field is maturing and has grown continuously over the past five years (Pitelis & Teece, 2018; Hayter & Cahoy, 2018; Rui & Bruyaka, 2021), requiring organization and systematization, so that researchers can explore new forms, under new theoretical lenses and methodological approaches (Tasheva & Nielsen, 2020).
The scientific contribution of this paper to the studies on orchestration of dynamic capabilities lies in presenting clusters that cover the field of study and show routes for future research. These clusters are linked to Business Ecosystems, Orchestration via microfoundations, Internationalization, and Technology and Digitalization. Within each cluster there are research flows that articulate referential concepts for the creation of research lines and new scientific propositions and hypotheses. Furthermore, we contribute to expand the literature on the topic, by synthesizing and explaining the concept, and showing the difference between Orchestration of Dynamic Capabilities and Asset Orchestration.
2.Theoretical background
2.1 Orchestration of dynamic capabilities
Orchestration of Dynamic Capabilities is the configuration, modification, and integration of groups of tangible and intangible assets, routines, and competencies, to generate competitive advantages aligned with organizations' goals (Helfat & Peteraf, 2015). Especially in continuously changing environments, coordination and reconfiguration of strategies and business models are essential for the effectiveness of innovation management and for increasing organizational performance. Orchestration takes place through the management of companies' capabilities via micro-foundations, for generating new capabilities and organizational agility within business ecosystems (Shuen et al., 2014).
2.1.1 Orchestration of assets x orchestration of dynamic capabilities
Regardless of the industry, companies seek to develop maturity in processes and improve the perception of strategic advantages. This is initially established through past experiences and anticipatory behavior, which can be perceived and articulated to capture, generate, and develop sustainable value for the organization (Pitelis & Teece, 2018). The impulse caused by innovation and rapid change creates needs for companies to orchestrate their resources, in order to achieve better outputs. Prior to the theory that addressed the term 'orchestration', Pitelis (2007) already mentioned the development resulting from past experiences that turned into proactive actions.
Studies on orchestration are recent in the literature. Teece (2007, 2014) pioneered this field by developing the topic, and fostered the interest of other researchers, like Helfat & Peteraf (2015), who addressed competitive advantages, and Shuen et al. (2014), who explored firm performance. The concept of orchestration is described by the ability to combine technology and resources to develop new products and processes, locally and globally, and is critical for creating strategic business competitiveness, especially in the digital age (Lessard et al., 2016). Additionally, proper asset orchestration leverages strategic and competitive positioning, and is considered effective only by promoting value creation (Lessard et al., 2016; Teece, Peteraf & Leih, 2016).
Since orchestration is similar to the behavior of a conductor in a leading position for achieving congruence (Nadler & Tushman, 1980), he/she is responsible for orchestrating the resources and assets that are core elements for creating new organizational processes and routines (Teece, 2007). According to Helfat et al. (2007), asset orchestration is the selection, configuration, change, and creation of tangible and intangible assets. It seeks the enhancement and adaptation of assets through innovation and organizational learning, and by acquiring resources (Helfat & Peteraf, 2015).
On the other hand, the orchestration theory, observed through the lens of dynamic capabilities, helps understanding several phenomena, including technology-based companies. However, the literature still does not show a consensus on the theory of dynamic capability orchestration. Pitelis and Teece (2018) present the concepts of asset orchestration, but these are insufficient to encompass all the nuances of the orchestration theory, as it is broader and includes dynamic capabilities and entrepreneurs' co gnitive competencies. The relevance of these competencies in the orchestration theory was shown by Sirmon and Hitt (2009) and Helfat and Peteraf (2015); however, none of these authors explained the construct "orchestration of dynamic capabilities" and its contribution to asset orchestration.
Next, we present a potential definition for orchestration of dynamic capabilities, based on the systematic reading of articles related to orchestration. Therefore, we understand that orchestration of dynamic capabilities involves the creation and co-creation of the decisionmaking context. Thus, it improves the selection, configuration, transformation, and development of capabilities and competencies, within their context, resulting in the generation and co-generation of markets and business ecosystems.
2.2 Micro-foundations in the orchestration process
Micro-foundations are based on managers/entrepreneurs' abilities to constantly orchestrate (identify, coordinate, and reconfigure) the opportunities that emerge from new technologies, consumer needs, market niches, and competitors (Helfat & Peteraf, 2015). Among the micro-foundations are decision makers' managerial and cognitive dynamic capacities, whose efficiency is especially necessary to achieve greater organizational agility (Lessard et al., 2016). Through these capacities it is possible to be agile when managing problems generated by the centralization-decentralization polarization in business ecosystems, which leads to ambidexterity (O'Reilly III & Tushman, 2011; Shuen et al., 2014).
According to O'Reilly III and Tushman (2011), organizational ambidexterity orchestrated via micro-foundations comprises a broad set of routines that include decentralization, differentiation, and integration, beyond the capacity of top managers to orchestrate the simultaneous balance between asset exploration and exploitation (Priyono, Idris, & Abdul Halim Lim, 2020). However, there are also other prominent fields in the universe of dynamic capability orchestration, such as Business Model Configuration (Pitelis & Teece, 2018; Symeonidou & Nicolau, 2018), Digital Ecosystems (Zhou et al., 2017; Helfat & Raubitschek, 2018), Knowledge Management (Rastogi, 2003; Symeonidou & Nicolau, 2018), and Innovation Capacity (Agarwal & Selen, 2013; Rui & Bruyaka, 2021), among others.
3Methodology
3.1Bibliometrics and content analysis
We conducted a bibliometric study and content analysis on the topic of Dynamic Capability Orchestration. The former is a conglomeration of statistical methods that enables investigating and organizing scientific publications on a given topic (Pritchard, 1969). It can be defined by three structures: concept mapping, presentation of theory relevance, and exploitation of existing methodologies in the literature (Thanuskodi, 2010). Knowledge is organized from scientific research, and contributes for identifying gaps that may foster new studies (Aria & Cuccurullo, 2017), while content analysis examines texts in qualitative studies (Bardin, 2016).
To carry out the research, we used three software - MaxQda, Bibliometrix, and VosViewer. MaxQda helped identify the categories of the four clusters, in the content analysis for reviewing and separating the texts. The Bibliometrix R Package software enabled the quantitative programming language to analyze and describe published studies. We chose the 2.0 version of R Studio Cloud, including the Biblioshiny extension, which allows treating data collected at the Scopus database in csv format, showing them in graphs and tables that helped the analysis of the considerable number of surveyed articles (Aria & Cuccurullo, 2017). And the VosViewer 1.6.16. software analyzed the bibliometric networks of the specific fields of study. Its use assisted in conducting graphical analyses, such as publications per year, network of authors per citation, most evident research areas, keyword networks, and cooperation networks, including authors, journals, and countries.
3.2Data collection and extraction
Data collection had four steps. The first comprised extracting data from the Scopus database, using the terms "dynamic capabilities" and "orchestration," through which we identified 196 articles published between 2003 and 2021. Then we applied filters, selecting the areas of Administration, Business, and Economics. This database has a huge number of articles, and is one of the most relevant in quotations of peer-reviewed articles (Aria & Cuccurullo, 2017). Figure 1 shows the stages of selection and systematization of the articles for the literature review.
The second step was to export the database to Microsoft Excel. We separated studies of greater relevance to meet the research objective, by topic, and read the articles' abstracts, which resulted in the exclusion of 30 papers, whose themes were not relevant for the study objective. The exclusion criteria considered themes related to "Information Technology", "Telephone Services", "Cloud Services", "Data Integration", and related topics, which were part of the Information Systems area and did not approach the theoretical lens of Dynamic Capability Orchestration.
With a final sample of 54 articles, the third stage addressed content analysis, using the MaxQda software, which enabled reading with criteria for tabulation in Microsoft Excel, emphasizing the most quoted articles for the content analysis (Bardin, 2016). In the fourth stage, in order to compose the results of the base systematization, we used the software Bibliometrix, in the Biblioshiny extension, and the VosViewer. To present an overview of the studies, we did the following analyses: statistical data and information, bibliographic coupling, historiographical citation analysis, thematic map, and research clusters.
4Bibliometric analysis
Bibliometric study is a method that uses quantitative and statistical data analysis to identify topics of relevance in the literature (Knopf, 2006). The increase in publications makes bibliometric studies relevant for showing highlights that enable analyses such as main journals, authors who carried out certain studies, number of publications per year and country, and, finally, presenting frameworks for future research (Thanuskodi, 2010). The set of publications is the starting point for a bibliometric study, and can be established by organizing the surveyed data, contributing to generate knowledge on the research topic (Knopf, 2006).
4.1 Data and statistical information
From the collected data, we reached a final sample of 54 articles. In this set, the papers were written by 160 authors, between 2003 and 2021. The average number of quotes in the articles, since 2003, is 34%, and per year is 5%. There are five articles with a single author, and 49 with several, which shows the relevance of studies with many authors, and less interest in single-author papers. Altogether, there were 270 keywords, which guided the development of this research. We got details on quotes, number of keywords, and single or joint authorship, through the Bibliometrix software. The topic on 'orchestration of dynamic capabilities' is recent in the literature. In 2007, Pitelis (2007) published the first paper, and as of 2019 researchers showed greater interest in the subjects that contain terms like managerial capacity, innovation, performance, and technology.
4.2Articles, journals, and authors who address the topic
We ranked the ten journals with the highest relevance of citations in studies on orchestration of dynamic capabilities. Such relevance is attested to by the metric called H index, estimated by the ratio between the number of quotations that the articles published in that journal received, during a certain period, and the number of journals in which they were quoted. Thus, Table 1 shows the H index of each journal. The bibliometric analysis established by the Biblioshiny software highlights three journals that reached 1,169 quotes, representing 66% of the total number of articles analyzed in the database.
There were two articles published in journal 1 - Strategic Management Journal. The first addresses managerial Cognitive Capabilities and the micro-foundations of dynamic capabilities, by Helfat and Peteraf (2015), and is the most quoted article in the base. The second analyzes managerial dynamic capabilities and the effects on firm performance (Sirmon & Hitt, 2009). Journal 2, California Management Review, features a study on organizational ambidexterity and how managers explore and exploit it (O'Reilly III & Tushman, 2011). Journal 3, Research Policy, presents a study addressing dynamic and integrative capabilities to profit from innovation, in digital platform-based ecosystems (Helfat & Raubitschek, 2018).
Table 2 shows the 10 most relevant articles and authors in studies on Dynamic Capability Orchestration. Their respective impacts are measured in terms of total quotes, which point to Helfat and Peteraf (2015) as the most influential, with almost twice as many quotes as the second author duo, O'Reilly III and Tushman (2011). The majority of the most influential articles address managerial capabilities and innovation.
4.3Bibliographic coupling
The co-citation cluster analysis stems from articles of impact in the scientific community, and provides a microscopic view of association networks. Nodes represent the authors, and networks symbolize the citations between the authors with higher visibility, represented by several co-citation networks (Grácio, 2016). Co-citation Analysis, on the other hand, measures the relationship between two or more articles, based on the number of publications in which they are quoted. We designed four clusters; in Cluster 1, Teece (1997) is the most relevant in citations, because he created the fundamentals of dynamic capabilities. Cluster 2 includes authors with recent citations. Cluster 3, although distant from Cluster 1, shows its relevance by the size of the connections. Cluster 4 is located between clusters 1 and 3, and has a lower frequency of co-citations, compared to the others, which we can check by the size of the nodes.
4.4Keyword analysis
Since keywords indicate an article's most relevant terms, regarding the research topics and fields, we carried out a keyword co-occurrence analysis, to understand the thematic structure of the field (Knopf, 2006; Thanuskodi, 2010). By analyzing the authors' keywords present in the 54 articles, through the VOSviewer software, and filtering terms specific to the articles' object of study, we developed a keyword network (Fig. 3), where the proximity and the gradient that connect the keywords show the frequency of their coexistence, while the size of the node represents the frequency of the term's occurrence.
The network suggests four clusters. The number of keywords in the clusters is distributed rather equally, with a certain uniformity of the topics. Cluster 1 covers terms related to business models, value creation and capture, and digital ecosystems; Cluster 2 presents terms related to orchestration, knowledge management, and dynamic and innovation capabilities. In Cluster 3 there are terms referring to managerial capabilities, asset orchestration, and multinational corporations; finally, in Cluster 4, the terms refer to technology and digitalization.
4.5 Analysis of historiographic quotes
The historiographic analysis allows a chronological view of the relevant quotations in face of the bibliographic data. The results presented in Figure 4, with authors and years, show in 2009 the initial development of studies that address orchestration. From the historiographical citations, we can notice the research development. The red colors, analyzed as warm, concentrate the largest cluster of citations between authors who develop the same research interest. Mazumder and Garg (2021) conducted studies quoting Zhou et al. (2017), who addressed topics on resource regrouping and organizing.
4.6 Thematic map
To show the internal (seen in density) and external (seen in centrality) strengths of authors' keyword associations, we drew a two-dimensional thematic map (Figure 5). We observe in it that the keywords present in the type A quadrant, whose internal and external associations are high, represent dominant topics in the literature. In our study, these are the topics related to performance and asset orchestration. Their relevance is linked to the purpose of dynamic capability orchestration.
On the other hand, quadrant D, whose internal and external associations are weaker, does not show any research topic, indicating greater cohesion and connection between the study approaches that cover the orchestration of dynamic capabilities. In quadrant C, internal associations are significant, but external are weaker, and the only topic in this cluster is firm performance. We observe that this research flow is isolated from other topics in the field, and may be more connected to other lines of research.
In quadrant B, where internal associations are weaker and external are high, we found the highest concentration of keywords, with emphasis on the topics of orchestration, resource orchestration, and dynamic capabilities. This configuration suggests that there is greater coherence in the study fields, although the correlations between the topics are weaker.
5Content analysis
We applied content analysis (Bardin, 2016) for examining the articles. By reading them, we selected excerpts, separated them into categories, and organized on a table. We used MaxQda software to ensure a better criterion for the articles' content analysis, and to enable our joint work. We identified four research categories that, from the perspective of this bibliometric analysis, we considered as Research Clusters. They are: (1) Studies on Business Ecosystems; (2) Dynamic Capabilities and their Orchestration via Micro-Foundations; (3) Internationalization; and (4) Technology and Digitalization.
In addition to the Research Clusters, Content Analysis showed subcategories with relevant incidence, which we named Research Flows. These are topics that appear within the context of each of the Research Clusters, and were divided in order to contribute with the process of systematization of the study field.
Figure 6 shows the Research Clusters and flows, extracted from the Content Analysis of the articles collected in the database. The dotted squares represent each of the Research Clusters identified, as well as their context. The arrows indicate the research paths pointed out by different researchers within each cluster, leading to the Research flows addressed.
5.1 Research categories surveyed: Research clusters and their research flows
We identified the research categories by crossing the data extracted from reading the articles and analyzing data from software VosViewer and MaxQda. This process took place by following the assumptions mentioned by LeCompte (2000): (i) data organization; (ii) search of repeated research items; (iii) creation of sets of items (categories and subcategories); (iv) creation of analysis patterns; and (v) creation of structures and visual models for understanding categories and subcategories, using software support. From this analysis, four research categories - Research Clusters -, and 15 subcategories - Research Flows - emerged (Figure 6).
5.1.1.Cluster 1: Studies on business ecosystems
Cluster 1 represents the category Business Ecosystem Studies. The topic Business Ecosystem was highly repeated, motivated by studies that aim to understand how innovation takes place through the process of orchestration in different ecosystems. Among these ecosystems are Entrepreneurial Ecosystem (Symeonidou & Nicolau, 2018; Linde et al., 2021), Digital Ecosystem (Helfat & Raubitschek, 2018), Innovation Ecosystem (Agarwal & Selen, 2013), and Industrial Ecosystem (Shuen et al., 2014). Within the Ecosystem context, this cluster covered the following Research Flows (subcategories): Business Model Configuration, Digital Ecosystems, Value Creation and Capture via Networking, and Multisided Platforms and the Role of Integrative Capabilities.
Studies of business model configuration seek to understand the creation of new business models from the perspective of dynamic capabilities, considering existing ecosystems and the exchange of information between companies and digital platforms, which allow shaping the strategic positioning of firms, through the creation of new capabilities and resources (Pitelis & Teece, 2018; Symeonidou & Nicolau, 2018). The phenomena of study in this flow include startups, MNEs, and SMEs (Symeonidou & Nicolau, 2018). Business models are the central axis for achieving competitive advantage through dynamic capabilities that can be adapted, according to market challenges.
The flow of Digital Ecosystems unfolds the digital transformation phenomenon that appears as a driving factor for companies' adjustment to new platforms, in a technological context (Zhou et al., 2017; Helfat & Raubitschek, 2018; Garbellano & Da Veiga, 2019; Yoshikawa et al., 2020; Mazumder & Garg, 2021). Industry 4.0 and the orchestration of dynamic capabilities in small and medium-sized enterprises in developed countries are determinants for knowledge exchange between the digital ecosystem and the entrepreneurial ecosystem (Garbellano & Da Veiga, 2019). On the other hand, the role of integrative capabilities is necessary for firms to absorb new technologies into their business environment and create value through innovation capabilities, environmental digitalization, and ability to detect market threats (Helfat & Raubitscheck, 2018; Mazumder & Garg, 2021). Information technology (IT), which provides the renewal of firm's resources and organizational agility, is a widely analyzed phenomenon in this path, within the context of developing economies (Ma et al., 2015; Zhou et al., 2017; Queiroz, et al., 2018).
Value creation and capture via networking is a research flow that covers value capture and innovation creation using networking and dynamic capabilities that are orchestrated in different ecosystems (Rui & Bruyaka, 2021). In turn, the flow 'Multisided Platforms and the Role of Integrative Capabilities' considers the role of integrative capacities for adopting platforms that can generate innovation and follow companies' digital transformation, providing them with competitive advantage (Helfat & Raubitscheck, 2018; Hermawati & Gunawan, 2020).
5.1.2.Cluster 2: Dynamic capabilities and their orchestration via micro-foundations
Cluster 2 represents Dynamic Capabilities and their Orchestration via MicroFoundations. The cluster emerged from the research flows Knowledge Management (Knowledge-based View), Resource Orchestration, Innovation Capacity, and Strategies for Achieving Competitive Advantage. Cluster 2 comprises studies that follow the microfoundations (sensing, seizing, and reconfiguring), in order to influence and relate concepts and variables from other theoretical foundations.
Knowledge-based View (KBV) proved to be a latent research subcategory, and addresses issues related to the foundations of Social Capital (SC), Human Capital (HC), and Intellectual Capital (IC), for understanding the orchestration of dynamic capabilities within companies (Rastogi, 2003; Symeonidou & Nicolau, 2018). These studies cover the Entrepreneurial Ecosystem and government relations, especially to check the relationship between SC, HC and IC variables with the micro-foundations of dynamic capabilities.
The Resource Orchestration research flow was a latent subcategory during the analyses. Since the foundations of dynamic capabilities are rooted in the Resource-Based View (RBV), the flow presented a number of studies highlighting the managerial implications of dynamic capabilities for renewing competencies that result in firm performance (Sirmon & Hitt, 2009). Studies on resource orchestration focus on understanding how dynamic capabilities can foster firms' organizational change across different industries and ecosystems (Shuen et al., 2014; Symeonidou & Nicolau, 2018). In this research flow, micro-foundations define resource orchestration and its role for business asset allocation.
The role of innovation as a capacity has also appeared as a research flow and was named as Innovation Capability (Agarwal & Selen, 2013; Helfat, & Raubitschek, 2018; Hermawati & Gunawan, 2020; Rui & Bruyaka, 2021). In most studies on orchestration of dynamic capabilities, innovation capacity is the result of the process and the relationship between the micro-foundations; it has also been identified as an integrative capability for reconfiguring firms' business model.
The research flow Strategies for Achieving Competitive Advantage includes the seminal text by Helfat and Peteraf (2015), showing that the orchestration of dynamic capabilities takes place through the micro-foundations adopted by top managers, which relate to their cognitive capacity for designing new strategies. Still in this flow, ecosystems are present in the studies by Brink (2019) and Linde et al. (2021), showing that companies' strategies use micro - foundations for exchanging knowledge with different ecosystems, and formulate paths for the creation of competitive advantage. This research flow is highly relevant in emerging markets that establish entrepreneurial and technological ecosystems to help firms improve their capabilities and achieve competitive advantages in the market through cooperation (Ma et al., 2015; Zhou et al., 2017; Queiroz et al., 2018).
5.1.3.Cluster 3: Internationalization
Cluster 3 focuses on the field of International Business. The categorical repetition of this Cluster was smaller than the others, and its Research Flows are linked to Multinationals, International New Ventures, Emerging Markets, and International Ambidexterity (Pitelis & Teece, 2018; Tasheva & Nielsen, 2020; Priyono et al., 2020; Rui & Bruyaka, 2021).
The Multinational Enterprise (MNE) research flow presents studies on process internalization using the orchestration of dynamic capabilities to generate business coopetition and foster entrepreneurship and Open Innovation practices (Shuen et al., 2014; Soebandrija, Aprillia & Ho, 2016; Pitelis & Teece, 2018). Additionally, Lesserd et al. (2016) address MNEs from the perspective of Meta-Multinationals, which are firms that orchestrate their assets and dynamic capabilities by concentrating their knowledge in headquarters and orchestrating their resources among the subsidiaries.
International New Ventures are startup companies that internationalize, and were identified as a research flow within the Internationalization Cluster, addressing these firms and their global dynamics by counting on the capabilities and resources they hold, besides highlighting the relationship between Social Capital, Human Capital, and Cognitive Capabilities (Ma et al., 2015; Tasheva & Nielsen, 2020). According to Ma et al. (2015), the role of technology and digitalization for International Ventures is investigated in emerging markets due to resource shortage and the need to articulate the micro-foundations for firm internationalization.
Emerging Markets are a trend in future studies on orchestration of dynamic capabilities, and was a subcategory mapped as a research flow (Ma et al., 2015; Zhou et al., 2017; Rui & Bruyaka, 2021). Studies on the Chinese market stood out in the database, through the analysis of cases that relate orchestration of dynamic capabilities to the creation of industry networking for business strategy formulation (Rui & Bruyaka, 2021), use of IT for orchestration of firm processes (Zhou et. al, 2017), and the adoption of new technology platforms for startups (Ma et al., 2015).
International Ambidexterity is a research flow that deepens exploitation and exploration, focusing on the organizational agility of small and medium-sized companies that try to enter the global market through innovation (Priyono et al., 2020). Here, the role of executives is crucial for companies that practice international ambidexterity, because it depends on cognitive capabilities that drive technology companies to explore their potentials and reconfigure their businesses to increase organizations' efficiency (O'Reilly III & Tushman, 2011).
5.1.4.Cluster 4: Technology and digitalization
Cluster 4 comprises Technology and Digitalization studies, focusing on research on digital platform ecosystems. This cluster became relevant recently in the business sphere, especially since the year 2019. The network interconnected to technology and digitization studies cover digital capabilities, information technology studies, and digital transformation (Helfat & Raubitschek, 2018; Queiroz et al., 2018).
Studies that include digital capabilities exploit capacity development in the market for value creation, through continuous process reconfiguration (Zhou et al., 2017). Accordingly, Yuan et al. (2018) address the increase of digital capacities in educational institutions and present ways to perceive new stages in the creation of new technologies.
Regarding information technology studies, Koufteros, Verghese, and Lucianetti (2014) addressed project monitoring systems using the diagnostics as an attribute for capturing a constructive technological capability. Other studies regard the use of resource reconfiguration in positive technology building for firm performance (Lee & Kim, 2021).
Research that approaches digital transformation shows the application of technology to adapt renewable and non-renewable energy facilities (Shuen et al., 2014; Brink, 2019). Digital transformation has driven companies to create digital platforms for promoting agility, unification, and systematization of processes (Helfat & Raubitschek, 2018; Mazumder & Garg, 2021).
6Directions for future research
6.1 Research agenda on orchestration of dynamic capabilities
After organizing the research field and systematically reading the articles in the database, the creation of Clusters and Research Flows provided the possibility of suggesting future research paths and defining questions that consolidate a Research Agenda, based on the most cited articles. Table 3 presents the 10 most quoted authors, who represent 82% of the database analyzed in the paper, including the main research questions on the phenomenon of Orchestration of Dynamic Capabilities, and suggestions for future research from each of the articles. We also present different types of analysis, methodological approaches, and supporting theories, in order to define paths for the advancement of this field.
Considering the recent increase in studies, the qualitative approach has prevailed and intends to create propositions to advance case studies and generate concepts and constructs that will serve as a basis for subsequent quantitative studies. In this regard, case studies, theoretical essays, and non-systematic literature reviews have led the qualitative research, while in quantitative research the main statistical methods used consist of regression techniques, and focus on Contingency Theory studies and the relationship between different types of Capital - Human, Intellectual and Social. We suggest studies with a mixed approach (Quali-Quanti), in order to test the propositions presented in the essays, reviews, and case studies.
7Conclusion
The paper's overall goal - to present an overview of research related to orchestration of dynamic capabilities - was fully achieved. The growth of studies on the topic occurred between 2017 and 2021, guided by the deepening of clusters' subjects. In addition, research paths are shown in Table 3, based on the analyses with the software and systematic readings, from which we extracted suggestions for future research and limitations of the main articles analyzed, thus meeting our paper's specific objective.
During the analysis, we presented the methods and theories used, simultaneously with thematic analyses of keywords and research groupings that bring scientific contributions. We intend to help researchers in their areas and flows that are currently being explored, with the potential for growth in the coming years. This academic contribution frames the field of Dynamic Capability Orchestration from the perspective of different phenomena and theoretical lenses, showing the advances that can contribute to the flow of studies, growth of the topic, and scientific gaps that researchers can address in the future.
The analysis of the clusters and their unfolding into research paths showed that there is a relationship between clusters, conceptual elements, and capability orchestration. Figure 7 suggests a model that consolidates, in practice, how the foundations of Dynamic Capability Orchestration have been addressed over time, in the field of strategy and innovation studies. The model is based on the bibliometric analyses carried out in this paper. The assets, resources, and capabilities of different business ecosystems are articulated by the micro-foundations, for renewing competencies and new capabilities within other ecosystems. Additionally, we inserted into the model factors like Internationalization and Digitalization to investigate the different contexts and relationship between the ecosystems.
We suggest that scientists address the research questions presented in Table 3, creating hypotheses and propositions that include the Research Clusters, to bring new contributions to the presented research flows and to the seminal articles examined in this paper. The limitation lies in the bibliometric method; due to its nature, it restricts the critical sense of articulation of the selected papers. To overcome this problem, we suggest carrying out meta-analyses and Systematic Literature Reviews, using the bibliometric technique together with a critical deepening of the articles found in databases. Future studies should explore the model suggested in this paper (Figure 7), by including new elements and identifying new theories and perspectives to advance the studies on Orchestration of Dynamic Capabilities in a multidisciplinary way.
Cite as - American Psychological Association (APA)
Noronha, M. E. S., Ferraro, D. M. J., & Silva, R. de S. V. (2022, Sept./Dec.). Bibliometric analysis on the orchestration of dynamic capabilities. International Journal of Innovation - IJI, Sâo Paulo, 10(4), 610-637. https://doi.org/10.5585/iji.vl0i4.21381.
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Abstract
Objetivo: O objetivo geral deste trabalho é apresentar um panorama de pesquisas relacionadas à orquestração de capacidades dinámicas. Já o objetivo específico é identificar os principais caminhos para a realização de uma agenda para pesquisas futuras. Metodologia: Estudo bibliométrico e análise de conteúdo sobre o tema Orquestração de Capacidades Dinámicas com a utilização dos softwares: MaxQda, Bibliometrix e VosViewer. Os dados coletados representam uma amostra final de 54 artigos no período de 2003 e 2021. Resultados: Os resultados identificaram quatro clusters que se desdobram em 15 fluxos de pesquisa. Os clusters de pesquisa identificados são: (i) Estudos sobre Ecossistemas de Negocios, (ii) Capacidades Dinâmicas e sua Orquestração Via Microfundamentos; (iii) Internacionalização; e (iv) Tecnología e Digitalização. Conclusões: A análise dos clusters e aprofundamento nos caminhos de pesquisa, mostrou que existe uma relação entre os clusters, elementos conceituais e orquestração de capacidades que são apresentados em formato de um Modelo de Orquestração de Capacidades Dinâmicas estressado no campo da estratégia e inovação. Contribuções: Para os estudos de orquestração de capacidades dinâmicas, reside na apresentação de clusters de pesquisa que distribuem o campo de estudo e apresentam caminhos para pesquisas futuras. Estes clusters estão ligados a Ecossistemas de Negócios, Orquestração via Microfundamentos, Internacionalização e Tecnologia e Digitalização. Dentro destes clusters encontram-se fluxos de pesquisas que articulam conceitos referenciais para a criação de linhas de pesquisa e novas proposições e hipóteses científicas.