Competitive advantage and dynamic capability in small and medium‑sized enterprises: a systematic literature review and future research directions

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Cleomar Marcos Fabrizio¹ · Fabíola Kaczam¹ · Gilnei Luiz de Moura¹ · Luciana Santos Costa Vieira da Silva² · Wesley Vieira da Silva³ ·

Claudimar Pereira da Veiga⁴

Received: 2 April 2020 / Accepted: 3 March 2021

Abstract

Competitive advantage is a significant concept both in studies of strategic management and in the practice of organizations. The dynamic reality of the market and competitors’ innovation capacity make it difficult for companies to achieve their goals and maintain sustainable competitive performance. In small and medium- sized enterprises (SMEs), this difficulty is often compounded by a scarcity of strategic resources, which can considerably decrease their competitive advantage sources.

In the present study, we discovered, through a systematic literature review (n = 70), a conceptual typology, with identification of five classes, categorized as (i) methodological procedures, (ii) organizational environment, (iii) organizational performance, (iv) resources/profile and (v) organizational research which were used to capture notions around dynamic capabilities and competitive advantage for SMEs. Likewise, as a result, a diverse selection of three clusters was found to show the positive influence (direct and indirect) of dynamic capabilities on competitive advantage and that performance variables mediate the impact on innovation capacity. Given this, we have answered two research questions related to the (i) discovery of state of the art and (ii) future research directions on Dynamic Capabilities and Competitive Advan- tage for SMEs.

Keywords Competitive Advantage · Dynamic Capabilities · Small and Medium- sized Enterprises

* Claudimar Pereira da Veiga [email protected]

1 Federal University of Santa Maria—UFSM, Rio Grande do Sul, Brazil

2 Municipal University Center of São José—USJ, Santa Catarina, Brazil

3 Federal University of Alagoas, UFAL, Alagoas, Brazil

4 Federal University of Parana, UFPR, Paraná, Brazil

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JEL Classification M13 · M21

1 Introduction

In the literature, studies in the field of strategy provide managers with a deep understanding of how to achieve superior company performance, especially when companies are oriented towards entrepreneurship and advocate the moderating role of pas- sion for work in the relationship between entrepreneurial orientation and company performance in dynamic environments, in the search for a competitive advantage (Adomako et al. 2016; Michaelis et al. 2020). Competitive advantage remains a significant concept, both in strategic management studies and in the practice of organizations in the market. On the other hand, market participants’ dynamic and innovative reality makes it difficult for companies to achieve their goals and maintain sustainable competitive performance (Porter 1980; Yadav et al. 2017; Dong et al.

2019).

In small and medium-sized enterprises (SMEs), this difficulty can still often be exacerbated by a scarcity of strategic resources, which can considerably decrease their sources of competitive advantage (Porter 1980; Dess and Davis 1984; Por- ter 1991; Barney and Hansen 1994; Stonehouse and Snowdon 2007; Švárová and Vrchota 2014; Yadav et al. 2017; Dong et al. 2019). Due to their small size, SMEs are often characterized as isolated companies with limited resources (Tang 2011;

Pinho and Prange 2016) or are classified based on the number of employees and rev- enues (Montoro-Sanchez et al. 2018).

One of the main difficulties for SMEs is deciding their investments and their competitive advantages (Rao et al. 2019; Khan et al. 2017). In this sense, sources of competitive advantage take on particular significance for SMEs regarding organizational decision-making. In terms of their capabilities and strategic assets, SMEs’

competitive advantages are based on their level of entrepreneurship, their simple capital structures, and their dynamism sources. In other words, the relationship between SMEs’ resources and capabilities is influenced by strategic assets relating to organizational flexibility—a significant source of competitive advantage for small businesses, with their competitive attributes discussed in terms of dynamic capabilities (Yu 2001; Mudalige 2015).

Several studies in the literature show that dynamic capabilities (Teece et al. 1997) are essential for SMEs in order to make better capacity decisions, which should be a focal point for any strategic analysis (Hatum et al. 2010; Pisano 2017). Dynamic capabilities can help SMEs to examine the environment, understand the market, and create and seize opportunities (Eikelenboom and Jong 2018; Muhic and Bengtsson 2019). In this context, Rashidirad and Salimian (2020) state that it is necessary to understand the different ways in which SME managers and decision-makers per- ceive the value of dynamic capabilities, which influence the extent to which they support and invest in the development and deployment of these resources for the benefit of their businesses. Therefore, understanding the key elements of their capabilities (and those that can be developed) can give SMEs a competitive advantage over market rivals.

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Dynamic capabilities are understood as "ultimate" organizational capabilities that lead to long-term performance, rather than merely a subset of resources, as suggested by Teece et al. (1997). Wang and Ahmed (2007) determined the three main factors that make up dynamic capabilities, namely: (i) adaptive capacity, (ii) absorptive capacity, and (iii) innovative capacity. For these authors, adaptive capacity is the company’s ability to adapt promptly through the flexibility of their resources and the alignment of resources and training with environmental changes. Thus, the focus of adaptive capacity is to align internal organizational factors with external environmental factors. Absorption capacity highlights the importance of considering external knowledge, combining this with internal knowledge, and absorbing it for internal use. The capabilities for innovation is a crucial factor for SMEs. It links the innovation inherent in a company and the associated advantages in terms of new products and markets.

In the context presented, the systemic approach to innovation has been widely used in recent decades (Turner et al. 2017; Saunila 2019; Mortazavi et al. 2020).

In the market, innovation is highlighted as being an "engine" for economic growth, generating competitiveness and jobs, not only in high-tech industries but in all sectors (Rametsteiner and Weiss 2006; Xiong et al. 2020).

The concept of innovation has undergone transformation over time, together with evolution of the concept itself (Louçã 2014). Thus, the emphasis that was ini- tially placed on isolated innovative acts, carried out by individual inventors or by large companies, shifted to the complex social mechanisms underlying production of new products and the introduction of new production processes. Thus, the terms

"innovation processes" or "innovation activities" came to be used to indicate that the traditional distinctions between discovery, invention and diffusion no longer made sense (Marques and Abrunhosa 2005). Countless observations show that innovation processes result from development of the dynamic capabilities that companies need to obtain in order to innovate or improve performance (McKelvie and Davidsson 2009).

Despite countless observations that dynamic capabilities are at the root of competitive advantage, we still have limited knowledge about how access to company- based resources and changes in these factors affect the development of dynamic resources. It is important to note that changes in resource bases have a more influ- ential role in the development of dynamic capabilities than resource stock variables measured at an earlier stage of company development. This provides empirical support for the notion of treating a company as having a dynamic flow of resources rather than static stock (McKelvie and Davidsson 2009).

According to Barney and Hesterly (2012), competitive advantage can be seen as a company’s entrepreneurial capacity to generate greater economic value than its rivals, that is, to distinguish itself from its competitors. Various resources and

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capabilities can create and sustain a competitive advantage and can affect business performance. Shepherd, Haynie, and Patzelt (2013) have stated that entrepreneurship mostly implies searching for new products and services, representing a mecha- nism by which organizations adapt, rejuvenate and grow. On the other hand, these actions can lead a company to underperform when these procedures are not adopted in dynamic environments.

Based on the concepts of competitive advantage and dynamic capabilities, and the importance of understanding the performance of SMEs, we are faced with the following research question: What is the state of the art in terms of research into dynamic capabilities and competitive advantage for SMEs? This question then leads to the following secondary question: What are the directions for future research into dynamic capabilities and competitive advantage for SMEs?

This question is motivated by considering that the universe of SME’s activities is vast; that is, from very dynamic to little dynamic sectors and is highly dependent on the institutional environment in which they operate, which would influence the formation of strategies for obtaining performance. The study by D2014rnevich and Kriauciunas (2011) shows that ordinary capacities can contribute to obtain dynamic capacities and, consequently, competitive advantage. The various works in the literature on competitive advantage and dynamic capabilities are comprehensive (Zott 2003; Drnevich and Kriauciunas 2011; Makkonen et al. 2014) but still lack guidance for SMEs.

The rest of the article is structured as follows: Sect. 2 presents the methodological procedures; Sect. 3 presents a discussion of the results; and Sect. 4 presents the final considerations and directions for future research.

2 Methodological procedures

The SLR process allows for (i) identification, (ii) mapping and (iii) analysis of relevant research, in order to evaluate a specific aspect of the research topic and create opportunities for new discussions of the findings presented in traditional reviews (Tranfield et al. 2003; Kitchenham 2004; Biolchini et al. 2007; Zahoor et al. 2020;

Kraus et al. 2020). Based on these authors, for this study, the SLR process was com- posed of three stages: (i) planning the SLR, (ii) conducting the SLR, and (iii) dissemination of the knowledge.

2.1 First step: planning the SLR

This stage was based on the guidance of experts and the theme central to the research corpus selection process, involving a textual analysis to determine the key search terms to be used (Aarts 2014). Firstly, having defined the strings in order to guarantee the originality of this study, we conducted a search of the Scopus and Web of Science databases. Articles and review studies were selected, without a lan- guage or time limitation, based on the recommendations of Almeida and Goulart (2017), in order to minimize any selection bias. The Scopus and Web of Science

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Core Collection databases were eligible due to their wide coverage of scientific literature (Chadegani et al. 2013; Chersan et al. 2020). Table 1 presents the strings and number of articles resulting from our search of reviews.

Our database search identified the following key areas/factors (see Table 1):

15 studies including narrative reviews combined with empirical tests and an SLR with a focus on dynamic capabilities and external sources of learning for SMEs (Bierly and Daly 2007); dynamic capabilities as mediators of sustainable operations in the manufacturing industry (De Guimarães et al. 2019); effects of organizational absorption capacity in the relationship between information technology and business performance in SMEs (Francalanci and Morabito 2008);

*Data exportation/collection was carried out on August 14th, 2020

"dynamic capacity*" OR "adaptive capacity*" OR "absorptive capacity*" OR "innovation capacity*"))) AND ("small and medium-sized enterprise*" OR "small and medium-sized firm*" OR "small and medium-sized business*" OR

"small and medium enterprise*"

OR "small and medium firm*" OR

"small and medium business*"

OR "SME" OR "SMES") AND (LIMIT-TO (DOCTYPE, "re")) Web of Science TS = ("competitive advantage"

AND ("dynamic capability*" OR

"adaptive capability*" OR "absorptive capability*" OR "innovation capability*" OR "dynamic capacity*" OR "adaptive capacity*" OR

"absorptive capacity*" OR "innovation capacity*"))

Refined by: TOPIC: ("small and medium-sized enterprise*" OR

"small and medium-sized firm*"

OR "small and medium-sized business*" OR "small and medium enterprise*" OR "small and medium firm*" OR "small and medium business*" OR "SME"

OR "SMES") AND DOCUMENT TYPES: (REVIEW)

Timespan: All years. Indexes: SCI- EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, ESCI

5

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confidence in the acquisition of knowledge by SMEs, and the conversion of knowledge into results (Geneste and Galvin 2015); facilitators and barriers in the development of innovation projects in SMEs (Sánchez et al. 2017); SLRs on innovation management (Savino et al. 2015); resource-based theory reviews (Kozlenkova et al. 2013); business strategies to obtain a competitive advantage (Li et al. 2006); technological and organizational innovation for small business growth (Macpherson et al. 2004); SLRs on the influence of strategic alliances on the development of dynamic capabilities (Mamédio et al. 2019); long-term performance of firms (Martynov and Shafti 2016); the Agile Wheel Reference Model (AWRM) (Meredith and Francis 2000); SLRs on internal capabilities and eco-innovation in manufacturing companies (Salim et al. 2018); SLRs on design management as a dynamic capability (Santos et al. 2018); and SLRs on dynamic capabilities, innovation capabilities, entrepreneurial capabilities, and financial and strategic performance (Vu 2020).

It was then possible to proceed to the phase in which the SLR was to be conducted, since we did not find systematic literature reviews addressing the direct relationship between dynamic capacity and competitive advantage in SMEs.

Thus, the present study represents a significant contribution to the literature on SMEs and considers the important role of these ventures in emerging economies (Gherghina et al. 2020).

2.2 Second step: conducting the SLR

The second step was to conduct a broad and impartial search (Tranfield et al.

2003; Kitchenham 2004; Biolchini et al. 2007; Zahoor et al. 2020). The search strategy consisted of finding publications with the help of Boolean operators and keywords related to the themes of competitive advantage and dynamic capacity, with a focus on SMEs. Table 2 shows the strings and the results obtained from the databases used.

After the data collection step, the selection process for the textual corpus was initiated, as shown in Fig. 1. The first step consisted of removing duplicates using RStudio software (RStudio Team 2020). In this stage, from a sample of 455, we identified 430 exclusive studies in the area.

When checking the existence of string terms in the article title, abstract or keyword fields, in the second step, for "Part I", we selected 380 studies. From these studies, we analyzed "Part II" and obtained 365, among which we verified

"Part III" and selected 90 studies. In this phase, we used Microsoft® Excel software to prepare the data, considering the existence of the string terms in at least one of the fields (article title, abstract or keyword fields), and (mainly in "Part II" and "Part III") we observed the presence of at least one of the terms.

In the third and final stage of the selection process, we evaluated the articles’

adherence to the theme. After reading the abstracts of the 90 studies, we defined a textual corpus of 70 articles (see articles in annex A).

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2.3 Third step: knowledge dissemination

Dissemination of the knowledge includes presentation and discussion of the results and conclusions of the study. In this stage, we used RStudio, Gephi and IRA- MUTEQ software (Bastian et al. 2009; Perianes-Rodriguez et al. 2016; RStudio Team 2020; Souza et al. 2018). RStudio enabled us to extract descriptive information from the textual corpus. We extracted the bibliographic coupling network with the aid of the Gephi software, and we produced word clouds and the typology using the IRAMUTEQ software.

*Data exportation/collection was carried out on August 14th, 2020

"dynamic capacity*" OR "adaptive capacity*" OR "absorptive capacity*" OR "innovation capacity*"))) AND ("small and medium-sized enterprise*" OR "small and medium-sized firm*" OR "small and medium-sized business*" OR

"small and medium enterprise*"

OR "small and medium firm*" OR

"small and medium business*"

OR "SME" OR "SMES") AND (LIMIT-TO ( DOCTYPE, "ar") OR LIMIT-TO ( DOCTYPE, "re")) Web of Science TS = ("competitive advantage"

AND ( "dynamic capability*" OR

"adaptive capability*" OR "absorptive capability*" OR "innovation capability*" OR "dynamic capacity*" OR "adaptive capacity*" OR

"absorptive capacity*" OR "innovation capacity*"))

Refined by: TOPIC: ("small and medium-sized enterprise*" OR

"small and medium-sized firm*"

OR "small and medium-sized business*" OR "small and medium enterprise*" OR "small and medium firm*" OR "small and medium business*" OR "SME"

OR "SMES") AND DOCUMENT TYPES: (ARTICLE OR REVIEW) Timespan: All years. Indexes: SCI-

EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, ESCI

100

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3 Presentation and analysis of the results

In this section, we present a descriptive analysis of the textual corpus, an analysis of bibliographic coupling and the word clouds, the typology and proposals for future research.

Fig. 1 Selection process for the textual corpus

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3.1 Textual corpus descriptive analysis

Figure 2 shows the distribution of the 70 articles in the textual corpus according to their year of publication. The average number of citations in the study period (2003 to August 2020) was 9.23 per article (published by 125 authors and co-authors).

Regarding the number of publications, there was a growth trend, mainly between 2015 and 2019, an interval in which the increase was 300%.

Sulistyo and Siyamtinah’s (2016) study stood out, entitled "Innovation capability of SMEs through entrepreneurship, marketing capability, relational capital and empowerment". The authors suggested that development of team empowerment, the company’s relational capital, and marketing and entrepreneurial capacities can improve innovation capacity, enhancing organizational performance. This study was published in the Asia Pacific Management Review, where it received 23 citations.

Although 2019 also included a large number of publications, the total number of citations was low compared to previous years. According to Glänzel (2003), the quote window can reveal a temporal dependency, which means that the number of citations can become significant three to five years after publication of the study.

The continuous increase in the number of publications reflects wide debate on issues involving competitive advantage, due to its importance for the survival of SMEs, which have a positive impact on local economic development through job creation, poverty reduction and economic growth. (Gherghina et al. 2020).

3.2 Bibliographic coupling analysis

Bibliographic coupling analysis (BCA) identifies groups of documents that share references. Kessler (1963) and Boyack and Klavans (2010) found that if articles are linked bibliographically when different authors cite one or more articles in common, there will be an implicit relationship between them. For Jarneving (2007), while the co-citation technique allows past approaches to be observed, bibliographic coupling is related to the mapping of research fronts. Thus, the

Fig. 2 Annual distribution of the textual corpus. Source: research data

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coupling is established through references made to the authors of the researched documents, while their strength is determined by the amount of overlap in their bibliographies.

Bibliographic coupling measures the proximity between two articles, comparing the references and, from there, demonstrating that the greater the number of shared references, the greater the similarity between them, which can be thematic, theoretical, methodological, other similarities or a shared particularity, as evidenced by Soós (2014). For this analysis, we used Gephi software, and the parameters defined were as follows: "bibliographic coupling" for the types of analysis; "Documents" for the unit of analysis; and "total count" as a counting option. The same weight was attributed to links between the documents. It is worth mentioning that the analyzed data consisted of 50 linked articles extracted from 70 articles in the textual corpus, a configuration which aimed to optimize the network view.

Egghe and Rousseau (2002) and Zhao and Strotmann (2008) showed that the intensity of bibliographic coupling of two articles depends on the number of references they share: the greater the number of references, the stronger the connection between them. Figure 3 shows the network of linked documents, distributed among three clusters, where each point represents one of the articles that make up the corpus of the investigation.

In Cluster 1, the authors with the greatest strength in terms of coupling (that is, those with the most references in common with the other authors) were Ferreira and Coelho (2020), whose work entitled ’’Dynamic capabilities, innovation and branding capabilities and their impact on competitive advantage and SMEs’ performance in Portugal: the moderating effects of entrepreneurial orientation’’ was published in the International Journal of Innovation Science, with the objective of investigating the impact of prospecting and exploitation capabilities on competitive advantage and performance, taking into account the mediating role of innovation capacities and the moderating role of organizational learning capacity in the proposed relationships.

This research showed that dynamic capacities positively influence (direct and indirect) on competitive advantage and that performance variables mediate the impact on innovation capacity for business expansion both for the national and international market. According to Haapanen et al. (2018), concerning SMEs’ internationalization, directing financial resources to marketing and R&D functions is necessary;

however, developing dynamic capabilities and competitive advantage also involves specific skills, processes, and routines related to management marketing and Com- pany R&D.

Peng and Lin (2019) find a positive relationship between international network relationships, dynamic internationalization capacity, and global performance.

Besides, the absorption capacity moderates the relationship between the international network and international exploration. Frank et al. (2017) call attention that the dynamic capacities that enhance the search, flexibility, and learning gain importance with environmental dynamism. However, in hostile environments, it is also necessary to recognize opportunities and identify possible threats by competitors to increase business survival chances.

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In Cluster 2, the work that stood out the most in terms of the sharing of reference terms was developed by Zhang and Hartley (2018), entitled "Guanxi,¹ IT systems, and innovation capability: The moderating role of proactiveness". It was published in the Journal of Business Research, and the aim of the study was to explore how organizations can use two resources: (1) guanxi with customers, distributors, suppli- ers and government officials; and (2) IT systems to improve the performance of their new products and innovation resources. The results of this research suggest that IT systems and guanxi are resources that can help SMEs in China to develop a competitive advantage; these features contribute in different ways. Investing in IT systems

Fig. 3 Bibliographic coupling network (BCA). Source: research data; estimated by Gephi

1 Guanxi is a Chinese concept, defined as a close and comprehensive interpersonal relationship based on high-quality social interactions and mutual exchange of mutual benefits (Fu et al. 2013; Ou et al. 2014).

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increases the capacity for innovation, which, in turn, improves the performance of the new product. Secondly, SMEs need to cultivate more proactivity. Thirdly, guanxi can be used to directly improve the new product’s performance to increase the competitive differential in the market.

Maintaining competitiveness in the market requires companies to assess which strategic determinants give them an advantage over their competitors. In this perspective, Rua et al. (2018) and França and Rua (2018) highlight the importance of competitive strategies in SMEs’ performance, based on integrating entrepreneurial orientation and intangible resources absorptive capacity. Mennens et al. (2018) extend the absorptive capacity analysis and find that employee collaboration and the research’s breadth can enhance it.

In Cluster 3, the work to be highlighted (in terms of overlapping its bibliographic references with other authors in the same cluster) was prepared by Wen- dra et al. (2019) and was entitled "Exploring dynamic capabilities, intellectual capital and innovation performance relationship: Evidence from garment manufacturing [firms]". This article was published in the magazine Business: Theory and Practice, and the results obtained in this work show that dynamic capabilities can directly stimulate innovation performance through intellectual capital in the clothing industry.

According to Ferreira et al. (2019), dynamic capabilities indirectly affect performance and competitiveness through strategic guidance, innovation, and managerial capacity. Strategic orientation significantly influences competitiveness and performance, while managerial capabilities can reinforce dynamic capabilities on innovation capabilities. Adeniran et al. (2016) draw attention to the support of Information and Communication Technologies (ICT) in association with dynamic capabilities (detection, absorption, adaptive, innovative, network, and integrative) to generate long-term returns for SMEs. Dewi et al. (2020) highlight the importance of adaptive capacity to make innovation a competitive advantage regarding the transformations imposed by technological advances.

Wu et al (2020) contributes to the study of the relationship between dynamic capacities and competitive advantage to the extent that he notes the positive effect of a cohesive network on the potential absorption capacity and carried out through the moderating effect of learning orientation. Although the coupling network had a low density, it had a clustering index that was considered "high" since its value was around 0.75594, meaning that the network was not interconnected in general, but there was a high degree of connectivity within each cluster. This is also confirmed by the relationship developed by Watts and Strogatz (1998), who determined small worldwide networks to be those where the average cluster coefficient (CC) was greater than the network density (D) (which was confirmed in the results achieved, where the CC of 0.75594 was greater than the network density of 0.380). Another important measure analyzed was the measure of centrality of intermediation, as this explains how much an author can establish bridges with other works and thus be able to disseminate the study of themes to other researchers.

According to Zupic and Čater (2014), BCA is the most appropriate analytical tool to capture the evolutionary and contemporary patterns of a specific research domain. Unlike traditional co-citation references, the network nodes in BCA are

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articles identified through the use of co-citation classification methods, which facilitate analysis and visualization of the relationships between different research topics. The work that presented the greatest intermediation centrality was developed by Wendra et al. (2019), with an intermediation centrality equal to 143,074. This study therefore presented itself as having the most connections, both within Cluster 3 (to which it belonged) and with the rest of the network (Clusters 1 and 2).

3.3 Word cloud analysis

In Fig. 4, we present a detailed evaluation of the articles in the textual corpus. The 512 most frequent terms were extracted from the abstracts, categorized according to the research objective, the methodology that was applied in each work and the main results, built from the word incidence matrix (where the size of the terms is propor- tional to their occurrence).

In Fig. 4, it has been possible to show that the studies focus on "innovation" and

"performance", corroborating (as highlighted) the word cloud, which suggests that organizational innovation promotes greater performance and, consequently, greater competitive advantage. A recurrence of the two words "innovation" and "performance" can be seen in several studies of the textual corpus. An example of this is the work described by Ardyan et al. (2017), entitled "Green innovation capability as driver of sustainable competitive advantages and SMEs’ marketing performance", whose objective was to test the capacity of green innovation factors that lead to sustainable competitive advantage and performance in terms of marketing in small and medium-sized enterprises.

In terms of the methodology used in the evaluated works of the textual corpus, the word cloud highlighted the number of occurrences, as follows: "questionnaire",

"quantitative research" and the technique of "structural equation modeling". In the case of the term "questionnaire", 44 occurrences were found among evaluated studies which used this type of collection method (using structured questionnaires). In relation to the term "quantitative research", we obtained a frequency of occurrence equal to 39, which refers to the fact that most studies use statistical tools, in addition to a strong theoretical and methodological apparatus.

Another highlight concerns the term "structural equation modeling", since a total of 32 occurrences was verified, with this technique being used in a recurrent way in

Objecve Methodology Results

Fig. 4 Most frequent words in abstracts. Source: research data; estimated by RStudio

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the empirical works of the corpus seeking to identify causal relationships between the constructs researched in this SLR. Proof of this is provided by the study developed by Rua (2019), entitled "Absorptive capabilities and competitive advantage:

The linkage", which aimed to analyze the influence of absorption capacities on competitive advantage in small and medium-sized Portuguese companies, and which made intensive use of this type of quantitative relational modeling.

Regarding the word cloud of the results of the articles in the corpus, it was noticed that the most prominent terms were "innovation" and "performance" (with a frequency of 93 occurrences), in addition to the term "resource" (whose frequency of occurrence was equal to 39), which suggests that such occurrences stem from the

"resource-based view" theory, which is the basis for understanding dynamic capabilities. The study described by Chang, Chen and Lin (2014), entitled "Determinants of absorptive capacity: contrasting manufacturing vs services enterprises", focused on exploring the determinants and consequent absorption capacity of resource and performance capacity in Taiwan’s manufacturing and service industries. In this analysis, we highlighted the Zipf Law (1949), which analyzes the frequency and distribution of words contained in a text, making it possible to map and create occurrence ranking, highlighting the most cited words (leaving the researcher to interpret the context).

3.4 Proposed typology

Supported by the definition provided by the Cambridge Advanced Learner’s Dic- tionary and Thesaurus (2020), which is reaffirmed by Loo (2020), we understand typology as a systematic categorization of words, which considers meaning and context in addition to the lexical field and frequency of occurrence. The organization of a text allows us to interpret the most relevant words associated with the areas of knowledge related to the research topics in question, in order to provide insights for the strengthening of SMEs.

The typology was extracted using Reinert’s descending hierarchical classification (DHC) method, estimated by the IRAMUTEQ software. In this analysis, 70 abstracts of articles from the textual corpus were considered, comprising 333 text segments, of which 296 were classified (equivalent to 88.89%). The retention must be at least 70% of the text segments for the DHC analysis to be considered statisti- cally significant (Camargo and Justo 2013).

Regarding categorization, we obtained a total of five classes, which were renamed from the content analysis: Class 1 included 54 text segments (18.24%); Class 2 contained 48 text segments (16.22%); Class 3 included 72 text segments (24.32%);

Class 4 contained 74 text segments (25%); and Class 5 included a total of 48 text segments (16.22%), as shown in Fig. 5.

To improve our exploration of the content in detail, we created tables, one for each class and their respective words. We only considered words with a minimum frequency equal to 10, and we estimated the chi-square (χ²) non-parametric hypoth- esis test, where we identified words in which the chi-square statistic was greater than 3.80.

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(χ² > 3.80) or, alternatively, had a probability value less than 5% (p value < 0.05), eliminating the rest of the words that did not meet these criteria. We emphasize that the value of p < 0.05 portrays a level of significance in terms of the association between words and classes (Reinert 1990). The words comprising Class 1 (Meth- odological Procedures) are presented in Table 3.

Class 1 stood out because of its relationship with the other four classes, as can be seen in Fig. 5 (typology classes), which shows a pattern in relation to methodological procedures. Of the 70 articles analyzed, 57 (representing 81.43% of the total) were quantitative studies; 42 articles made their data collections through survey- based research, supported by statistical metrics such as the following: (i) descriptive statistics; (ii) the Q technique; (iii) exploratory factor analysis; (iii) confirmatory factor analysis; and (iv) modeling of structural equations (with and without multi- group evaluation) (Chang 2012; Ferreira and Coelho 2017, 2020; França and Rua 2018; Hyvonen and Tuominen 2006; Jundahuadong and Chemsripong 2020; Kerd- pitak et al. 2019) and others. This shows that there is a need to carry out qualitative studies to carry out analyses that complement the results found by the quantitative studies.

Table 4 shows the words comprising Class 2, which highlights the work developed by Chen and Hatzakis (2008), where the authors reinforced the importance of promoting a culture of knowledge management in order to sustain a competitive advantage. However, the authors Rafailidis et al. (2017) found that it is not enough to manage knowledge and culture; it is also necessary to consider the development of the company’s quality competences in terms of searching out products, services

Number of texts: 70 (abstracts) Number of text segments: 333 Acceptance: 88.89%

Fig. 5 Typology classes. Source: data research Table 3 Class 1—

Methodological Procedures

Source: data research

Word Frequency χ² p value

Model 33 38.52 0.0000000

Survey 27 33.51 0.0000000

Structural 19 69.07 0.0000000

Equation 16 75.8 0.0000000

Questionnaire 14 44.85 0.0000000

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and market innovation. The authors also suggested that SMEs pay attention to the balance between maintaining quality and adaptability to changes resulting from technological advances.

The organizational environment is an essential element in performance, as it makes it possible to generate the necessary conditions to develop the skills essential to obtain a competitive advantage. Makkonen et al. (2014) emphasize that to get performance in the organizational environment, and the company must promote exploratory activities to change its resource base and improve communication to explore opportunities and know how to keep up with threats.

Table 5 presents Class 3, with words that portray organizational performance.

In this table, together with articles from the textual corpus, the work developed by Susanti and Arief (2015) is highlighted, providing details of the relationship between dynamic capabilities, competitive advantage and organizational performance. According to the aforementioned authors, the influence of dynamic capabilities on performance is seen indirectly and is only effective if it results in a competitive advantage. Development of this set of capacities (i.e., (i) strategic

Table 4 Class 2—

Organizational Environment Word Frequency χ² p value

Knowledge 42 47.12 0.0000000

Process 26 10.38 0.0012727

Management 24 1 + 6.86 0.0000402

Environment 22 4.26 0.0390642

Technology 22 7.1 0.0077059

Source 19 32.93 0.0000000

Managerial 17 4.83 0.0279432

Organizational 17 12.63 0.0003800

Innovative 15 16.02 0.0000626

Learn 13 8.97 0.0027451

Organizational Performance Word Frequency χ² p value

Performance 80 60.7 0.0000000

Capability 65 15.91 0.0000664

Relationship 30 6.55 0.0104696

Manufacture 26 17.24 0.0000329

Strategy 24 6.56 0.0104054

Capital 20 10.96 0.0009286

Service 15 4.28 0.0384532

Entrepreneurship 14 12.75 0.0003563

Flexibility 5 8.56 0.0034278

Infrastructure 4 5.66 0.0173878

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capacities, (ii) innovation capacities, (iii) management capacities and (iv) adaptive capacities) makes it possible to obtain a competitive advantage, which will influence the company’s performance. Besides, organizational performance is also dependent on ordinary resources such as relationships, infrastructure, capital, manufacturing so that dynamic capabilities can be obtained.

Table 6 presents the words comprising Class 4, where it is possible to highlight the work described by Konsti-Laakso et al. (2012). In this research, business networks should were highlighted as a facilitator in the development of innovation capacity in SMEs. The network formation process involves motivation, which, in turn, is linked to the company’s profile (objectives and expectations). When considering the impact on innovation potential, the authors highlighted several management roles which can act to minimize the distances (geographic, cultural and functional) of the network as different resources are needed.

Table 7 shows the words in Class 5 that portray organizational research. There is a close relationship between research, development, innovation and competitive

Dynamic 20 28.6 0.0000001

Ability 16 8.81 0.0029966

Entrepreneur 13 14.19 0.0001655

Competitiveness 12 4.17 0.0411698

Value 12 7.41 0.0064805

Intangible 11 5.32 0.0210957

Organizational Research

Word Frequency χ² p value

Innovation 97 4.44 0.0351595

Firm 82 9.4 0.0021664

Research 63 8.99 0.0027113

Paper 50 25.05 0.0000006

Development 33 8.01 0.0046534

Strategic 25 5.01 0.0252454

Literature 20 18.02 0.0000219

Implication 19 19.82 0.0000085

Practice 14 18.12 0.0000208

Evidence 5 7.18 0.0073883

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advantage. In general, the scope of everything that is discussed in organizational terms in the previous classes depends on research, which justifies its name.

In the context presented, when considering the diversity of sectors of activity of SMEs involved in the studies that make up the corpus in question (the service sector, food, sport, and technology, among others), continuous research becomes even more necessary as the particularities make it challenging to generalize the results (Car- raresi et al. 2015; Kerdpitak et al. 2019; Wynarczyk 2013). In this sense, it is necessary to consider that organizational research can be directed towards innovation and the improvement of internal processes without the purpose of innovating, but that both efforts can lead to greater performance. Forsman and Ratanen (2011) state that the capacity for innovation in SMEs is more due to its organizational characteristics than just the external environment.

It is essential to consider that studies on SMEs need to incorporate the sector in which they operate. This will direct to what type of resources efforts will be most important: ordinary or dynamic. Then, and not least, it’s necessary to identify the types of capabilities needed to improve the company’s performance; and, in this case, it is also necessary to know which performances the company needs to improve or pay attention to (financial, organizational, product/service performance), so that in the end, it is possible to identify the type of competitive advantage that the company can obtain.

3.5 Future research directions

The results of this SLR indicate areas (both those presented in the articles of the textual corpus and the authors’ insights) which may lead to the development of future research into thematic dynamic capacity and competitive advantage in small and medium-sized companies, considering different approaches which can contribute both practically and academically to companies’ organizational routines. In this context, this review indicates seven directions for future research:

i. SMEs increasingly participate in business in the context of globalization, whether through IT or expanding business in emerging markets. Thus, it is suggested that studies be carried out on how to develop and execute dynamic capabilities in different environments, mainly in emerging markets (compared to already established or developed markets). Dewi et al. (2020) suggest, for example, studying the adaptive capacity of companies in order to have a clearer idea of how to innovate in the midst of market turbulence. In this perspective, Takahashi et al. (2017) also suggest studying how environmental turbulence can impact on dynamic capabilities.

ii. Considering the sector of activity of SMEs is essential to identify the types of capabilities that companies need to develop, as not every company needs to innovate, but all companies need to improve their performance to become competitive. For this, it is necessary to recognize the necessary competencies within the performance of each sector.

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interfere with the use of different dynamic capabilities (Medeiros et al. 2020).

v. Studies should focus on analyzing which different dynamic capabilities can be identified in SMEs that are able to improve performance through innovation, compared to those that do not seek to innovate.

vi. In view of the scope existing in types of dynamic capabilities and also in types of innovation, it is suggested that a study be conducted to identify whether there are specific capacities that lead to certain types of innovation.

vii. Based on the textual corpus, it has also been observed that studies need to provide information on what types of dynamic capabilities can promote competitive advantage. It is suggested that tangible and intangible resources supporting these capacities be analyzed and related to companies from the perspective of orientation towards the market, the customer and the company.

In this article, a widely accepted methodology in the management arena was used to carry out an SLR (proposed by Tranfield et al. 2003; Kitchenham 2004; Biolchini et al. 2007; and Zahoor et al. 2020). The guidelines detailed in this research were followed in a systematic and consistent manner. The main limitation of this study is that only two databases were used. Relevant articles in the area may not have been captured by our searches. For the development of new works, it is suggested that studies from other databases be incorporated, testing new protocols in different con- textual areas that can be studied and applied individually.

4 Final considerations

The purpose of this SLR was to present a typology about dynamic capabilities and competitive advantage for SMEs. Our analysis identified five classes used to capture notions around the theme. We also identified the diverse selection of three clusters, indicating that dynamic capabilities positively influence, direct and indirect, on competitive advantage and that performance variables mediate the impact on innovation capacity. In this context, we sought to answer two research questions as a basis for future efforts to assess the various ways in which SMEs integrate competitive advantage and dynamic capabilities in their strategies.

Answers to the surveys made a unique contribution to the analysis of the literature on SMEs. A small business is not necessarily an obstacle to obtaining a competitive advantage and superior performance. In this scenario, dynamic capabilities’ continuous development is the decisive factor, combined with a balance between maintaining quality and adaptability to changes resulting from technological advances.

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In the proposed typology, with regard to the theoretical perspective, Class 1 showed methods commonly used involving the research topics in question. In addition, from the proposed set of future research, we realized the importance of the relationship between theory and practice, reinforcing the perspective presented in Class 5. With regard to the practical implications, when analyzing Classes 2 and 3 of the typology, we identified elements that facilitate development of dynamic capabilities, such as managing organizational culture and knowledge (intellectual capital), with a focus on quality and innovation, starting from definition of the company profile, based on objectives and expectations and (considering the availability of resources) establishing an adequate business network based on the analyzed corpus. When considering the heterogeneity of the corpus in relation to the sectors of application, objectives, methods of analysis and research contributions, we can conclude that the proposed typology provided a means of standardization, highlighting elements that positively impact on the organizational structure of SMEs.

Among the aspects that can be considered differential in relation to other reviews identified in the corpus, we have highlighted the robustness and scope of the research. The study by Rafailidis and Tselekidis (2009) relied on random choice of the references that made up the review, and there was no protocol adop- tion or definition of a priori selection criteria for articles. In addition, the narrative review presented by the authors found an association between a distinct set of dynamic capabilities and innovation: change management capability, absorptive capability, human resources management capability, organizational learning capability and market-customer-oriented capability. The study by Olea et al.

(2016) only considered absorptive capacity, and although there was a practical application, construction of the theoretical model was also based on a traditional narrative review.

Another issue that can be pointed out from the studied corpus includes using survey-type collection methods, limiting a more longitudinal analysis of the phe- nomena. Concerning SMEs, it is important to verify whether companies make more social or environmental innovations, affecting direct efforts to obtain a competitive advantage. It is also essential to consider how dynamic capabilities can contribute to future actions, determining SMEs’ adaptability to changes in the environment.

Besides, SMEs must align their competencies with organizational strategies when making adaptive responses, which will also be influenced by their capacity to identify and predict scenarios, as they can find themselves, especially SMEs in emerging countries, in an environment characterized by a high degree of instability and changeability, but also a great many opportunities.

According to Zott (2003), it is necessary to take into account that relevant performance attributes of dynamic capabilities need to be considered, such as: the development of dynamic capabilities, the importance of imitation as an alternative resource for learning and improvement, the cost of capacity development dynamics and their learning in this process. Finally, this study is useful because it can help future empirical studies, both quantitative and qualitative. For example, qualitative studies could use this work to define analysis categories, and quantitative studies could use the aspects observed here to devise testable hypotheses.

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