Emerging trends around strategic flexibility: a systematic review supported by bibliometric techniques

In the rapidly changing external environment characterized by uncertainty, dynamism and technological change strategic flexibility (SF) has emerged as a key requirement for firms to obtain sustained competitive advantage and superior performance (Brozovic, 2018; Dai et al., 2018; Micevski et al., 2019). SF has been defined as an organizational capability (Bashir and Verma, 2019; Jiao et al., 2021) that companies need for surviving and thrive in turbulent business environments (Alamro et al., 2018; Hagen et al., 2019). Practitioners increasingly acknowledge that “under the changing conditions of a nascent or recently disrupted industry, a rigid plan can become a straitjacket for the flexibility and adaptation which may be required to succeed” ^[1]. Therefore, flexibility has become a key mechanism for successful transformation to face the changing environmental conditions and to take on ground-breaking new technologies ^[2].

In line with these developments in the business strategy and practice, academic interest in the field of SF has been growing in the recent years (Brozovic, 2018), resulting in a rapid evolution of the field (Bamel and Bamel, 2018). However, several tensions still exist in the extant literature on SF due to its multidimensional nature (Liao et al., 2019; Singh et al., 2015). Divergent theoretical perspectives and different conceptual underpinnings have been used to describe the SF concept, which has resulted in a broad and fragmented body of literature (Brozovic, 2018), with some researchers describing it as a “conceptual schizophrenia” (Herhausen et al., 2021, p. 437). To consolidate the literature, and potentially resolve the existing debates, Brozovic (2018) and Herhausen et al. (2021) recently published two literature reviews about SF. The first publication, which included articles published between 1978 and 2015, brought to light the interactions between the different constructs revolving around SF, classifying them as triggers, enablers, barriers, dimensions and outcomes of SF (Brozovic, 2018). The second publication, Herhausen et al. (2021) extended the work by Brozovic (2018) by focusing on the effect of the contingencies of SF to resolve the SF-performance relationship by means of a meta-review of quantitative contributions up to 2019.

While these publications are relevant and necessary to provide a broad understanding of the field from different angles, business leaders are continuing to seek new areas to develop and maintain SF (Nowak, 2022). Recently, disruptive changes in the area of digitalization have pushed firms to make their businesses strategically flexible (Nylén and Holmström, 2015) to innovate their business models in times of continuous change (Miroshnychenko et al., 2021). Therefore, SF is intertwined with recently topics (e.g. Matalamäki and Joensuu-Salo, 2022), thus making emerging synergies worth discovering to be further investigated by future research. Since 2015, articles published on SF have more than doubled, which corroborates the need to make a systematic evaluation of the recent literature. Accordingly, the aim of this article is to systematically review the SF literature with the help of a bibliographic analysis in order to unveil the state of the art of the recent literature on SF. We analyze the semantic structure of the literature, identify emerging trends and suggest new promising areas for future research on SF. To the best of our knowledge, this is the first literature review article on SF that uses a bibliometric approach to draw conclusions on the findings in the literature. While the two previous literature reviews of SF were based on the enablers-inhibitors-consequences framework, the bibliometric technique is based on connections of keywords to highlight trends and identify interconnections among topics.

In the remainder of the article, first, we discuss the multidimensionality of SF (Singh et al., 2015) by summarizing the various conceptualizations that exist in the literature. Then, we describe our data collection process and the bibliometric technique that was used to systematically analyze the literature. After that, to illustrate the primary emerging topics in the recent literature on SF, we discuss the three main clusters that emerged in the data, namely (1) SF as a dynamic capability (DC), (2) the role of knowledge management (KM) for SF and (3) the relationship between a firm SF and the external environment, which. We contrast these clusters with older literature on the topic and finally, drawing from our results, we offer reflections and suggestions on future avenues in research on SF, and contribute to an enhanced understanding of these main novel research streams and illustrate ways of exploring them further. In doing so, we contribute to an enhanced understanding of the main novel research streams in the literature on SF and illustrate ways of exploring them further. Moreover, to this purpose we have managed a Special Issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” that paves the way towards a clearer understanding of the relationship between SF and digitalization.

The concept of SF has emerged to describe a crucial capability underpinning the success of today’s organizations (Micevski et al., 2019). Despite the growth the field has witnessed in the literature in the recent years, there still exists a lack of consolidation and of common definitions within the scope of the SF literature (Herhausen et al., 2021). [Researchers, including Brozovic (2018), in their most recently published literature review articles, attempted to provide a common ground among the different definitions.] Brozovic (2018) provided an extensive overview of the definitions of SF to extrapolate its various dimensions, such as reactive, proactive, time aspect, strategic option and intentionality dimensions. Herhausen et al. (2021), on the other hand, leveraged five key definitions by Sanchez (1995), Volberda (1996), Hitt et al. (1998), Young-Ybarra and Wiersema (1999) and Grewal and Tansuhaj (2001) to identify product competition, organizational form, competitive landscape, strategic alliances and economic crisis, respectively, as key dimensions of SF. While the revelation of the key dimensions of SF contributes greatly to the SF research, it does not directly address the issue of a lack of a consolidated and widely accepted definition of SF, which has rendered the literature difficult to understand, as argued by these same researchers.

Therefore, prior to going into the details of the content of the literature review, in this research paper, we provide an overview of existing conceptualizations of SF to provide a more holistic definition of SF. We did this by mapping and coding, in a consolidated manner, the different definitions found in the literature analysis. Table 1 illustrates the key conceptualizations of SF, including SF as strategic adjustment, strategic options, dynamic capability and resource flexibility [which are used individually or in combination of two or, more rarely, three]. It is important to note the role of reactive and/or proactively dimension of SF, which emerged in the definitions, where the reactive ability includes the “responsiveness and adaptation to changes in the business environment” while the proactive dimension emphasizes, e.g. creating new markets, influencing the environment, changing game plans, acting on opportunities or simply “proacting” to changes in the business environment (Brozovic, 2018).

Considering the different angles through which SF can be explained, it becomes necessary to provide a holistic definition. Thus, for the purpose of this study, SF is defined an organization’s ability to change and adapt their use of organizational resources (Chen et al., 2017) by rapidly and effectively reconfiguring and reallocating its flexible resources and capabilities (Herhausen et al., 2021; Kamasak et al., 2019) to create and maintain alternative courses of action (Li et al., 2017; Liao et al., 2019) or diverse portfolios of strategic options (Chen et al., 2022; Yawson, 2020) that can be leveraged to act, either proactively or reactively (Miroshnychenko et al., 2021; Vihari, 2019; Yang and Gan, 2021), on identified environmental opportunities and/or threats (Brinckmann et al., 2019; Frare and Beuren, 2021).

Our first step was to search and collect articles that belong to the field of SF (McCain, 1990). To this purpose, in May 2022 we performed a wide search in the Web of Science (WoS) database, using the keyword “strategic flexib*” in the topic. Building on Rialti et al. (2019), we chose the WoS database because (1) it is considered as the database that includes most of the articles published in journals of good standing (i.e. all with impact factor), (2) it is the most up-to-date database concerning recently accepted articles (Marzi et al., 2018), (3) it provides less off-topic articles and (4) it does not include articles written in magazines or nonscientific journals (Caputo et al., 2018, 2021). This resulted in 717 entries that were then reduced to 508 after filtering on WoS categories (management, business and operations research management science). The number decreased to 505 after filtering on the language to include only articles written in English. Finally, the results were brought down to 436 after selecting only articles, reviews and early access articles as document type. After this first screening, we set two boundary conditions with the purpose of selecting the management-oriented articles on SF:

1. The article does not only mention SF, but specifically deals with it;

2. The article has a clear focus on SF, instead of other types of flexibility (e.g. manufacturing flexibility, supply chain flexibility). The decision to exclude other types of flexibilities was influenced by the point that SF is a multidimensional concept as earlier demonstrated, with researchers such as Singh et al. (2015) identifying supply chain flexibility, operations flexibility, and manufacturing flexibility as flexibility types that govern SF. Also, other researchers (e.g. Singh et al., 2015) single out SF as a higher order capability, this study thus focused only on SF to prevent any further complexities should other flexibility types be integrated into the research.

3. The article deals with management aspects associated to SF;

4. The article is published from 2015 onwards. There is a twofold motivation behind this condition: there has been a rapid increase in publications from 2015, as illustrated in Figure 1. 2015 also happens to be the same year up to which the highly cited literature review by Brozovic (2018) covers ^[3], as illustrated in Figure 1. Moreover, from the abstract reading, we noticed the emergence of new themes starting from 2015, such green practices (Yang et al., 2015; Perez-Valls et al., 2016) and big data (Rialti et al., 2020; Atkinson et al., 2022) that were not mentioned in Brozovic (2018) and Herhausen et al.’s (2021) literature reviews, which our study is able to capture.

After applying the first three conditions to the article abstracts, 225 articles remained, among which 117 were published from 2015 onwards. This sample was reduced to 108 after full article reading. To examine the emergence of new themes starting from 2015, we used the group of 108 articles published between 1991 and 2014 as a basis for comparison. Therefore, while the focus of this article is on more recent articles, which we will refer to as period 2 (i.e. 2015–2022), we will perform the bibliometric analysis also on the earlier studies, which we will refer to as Period 1 (i.e. 1991–2014). In other words, we use results derived from the more recent studies (period 1) in combination with evidence from earlier studies (period 2) to give a comparative standpoint. Figure 2 exhibits a diagram of the methodological protocol that we believe represents a balance between focusing more deeply on new articles that were not fully analyzed in prior reviews while, at the same time, not overlooking the less recent literature and taking previous evidence into account for proving contrast.

We proceeded by conducting a bibliometric analysis to trace the state of the art of the field of SF and identify the evolution of the field over time. Bibliometrics is “the mathematical and statistical analysis of bibliographic records” (Pritchard, 1969). It is used to establish intellectual linkages among different units of analysis, such as keywords in this case, to provide an overall picture of the trends and potential research opportunities. The primary advantage of bibliometric techniques is the quantitative accuracy it adds to the subjective evaluation of the literature such as narrative literature reviews which can be subjected to researcher bias and lack of rigor (Tranfield et al., 2003). Consequently, the bibliometric analysis guides the researcher to the most influential works through a mapping of the research field without subjective bias.

The specific bibliometric technique applied in this research was the co-occurrence of keywords, which reveals the most relevant research topics and the underlying conceptual structure of the field (Callon et al., 1983). The technique is based on counting the number of articles in which two keywords appeared together. To perform this analysis, the software VOSviewer version 1.6.14 was used to construct and display the bibliographic maps. Before importing the data set into the software, the completeness of information within the data was checked and the missing relevant information such as the publication year was added manually. Also, the keywords were refined and standardized, i.e. some authors used abbreviations or plural forms of the keywords.

In VOS Viewer, to perform the co-occurrence of keywords analyses, only the author keywords of the sampled articles were considered. As the co-occurrence of keywords looks at the content of the sampled articles, the relevant features of these articles were also mapped in a spreadsheet, namely the article purpose, definition/conceptualisation of SF, role of SF, specific methodology, context (country/industry under investigation, firm size), gaps leading to research, debates in the literature and the main results. The full list of articles with details about the methodology and the aim of the research is presented in  Appendix. Mapping these aspects supported the identified themes that characterized each cluster revealed in the maps and paved the way for identifying the gaps and research opportunities.

In the bibliographic map, the node size represents the weight, i.e. the number of articles in which a keyword appears. Thus, the larger the node size, the higher the number of articles in which the keyword appears. The line thickness represents the frequency of co-occurrence between two keywords. Hence, the thicker the line between two keywords, the higher the number of articles in which the two keywords appear together. In addition, the smaller the proximity between two nodes, the stronger their relationship, in terms of how many articles these two keywords appears in together, and with other keywords. Finally, the color of each node and keyword indicates the cluster to which they belong, with the same color of nodes and keywords belonging to the same cluster of related keywords.

Figure 3 exhibits the co-occurrence of keywords in the sampled articles published between 2015 and 2022 (i.e. Period 2). Out of 380 keywords, 41 keywords were selected that had at least 2 occurrences. For contrast, we also show the analysis of keywords in the sampled articles published between 1991 and 2014 (i.e. Period 1) (see Figure 4). In 2015–2022, three clusters emerged (red, blue and green) with each cluster representing the most frequently related keywords. The red cluster depicts the relationship between different DC and SF. The blue cluster illustrates different aspects of KM and SF. Finally, the green cluster focuses on the external push towards SF. The following paragraphs explain further these clusters, with emphasis on the emerging topics with respect to previous years of research in this domain.

The red cluster revolves around the keyword business model innovation (BMI), which only emerged in Period 2, DC and firm performance, which is the most prominent development in this cluster with respect to Period 1. The keyword DC was mentioned in Period 1 and Period 2. However, the distance between DC and SF is shorter in Period 2 compared to Period 1, which shows a stronger relationship between the keywords, indicating they have been used together in more articles in Period 2 compared to Period 1. Also, the line connecting DC and SF is thicker in Period 2, which indicates a higher frequency of co-occurrence between both keywords. Beyond the impact of SF on firm performance (Brozovic, 2018), there is a shift from DC to BMI as the primary focus of the research in this cluster with respect to the previous period, as indicated by its more central position.

The increase in thickness of the line connecting DC to SF and an increase in their proximity indicates a more frequent co-occurrence of the keywords, and a stronger relationship with other keywords. This bond is reflected in their overlapping interpretations (Hoeft, 2021). The term dynamic capability describes an organization’s ability to integrate, build and reconfigure its internal and external competencies, resource bases and organizational capabilities to deal with challenges in the business environment (Benitez et al., 2018; Chen et al., 2022; Spanuth et al., 2020).

Dynamic capabilities include three main capabilities: to sense and shape opportunities and threats, to seize opportunities and to sustain a competitive edge through enhancing, combining, protecting and when necessary, reconfiguring the firm’s intangible and tangible assets (Frare and Beuren, 2021; Kandemir and Acur, 2022; Spanuth et al., 2020). Considering that SF exhibits the three capabilities of sensing (Yang and Gan, 2021), seizing (Haarhaus and Liening, 2020) and reconfiguring (Spanuth et al., 2020), it has been identified as a prominent DC by various researchers in the field (Yang et al., 2015; Nwachukwu and Vu, 2020; Chen et al., 2022). Most of the different definitions of SF agree in considering it as a DC that enables a firm to reconfigure resources and act quickly to changing competitive conditions, thus achieving competitive advantage (e.g. Bamel and Bamel, 2018; Cui and Wu, 2016; Jia et al., 2022; Li and Wang, 2021; Yang et al., 2015; Yi et al., 2017) and making it a key conceptualization of SF as pointed in Table 1 above. This aligns with the literature review by Herhausen et al. (2021), according to which the perspective of understanding SF as a DC is one of the main perspectives in the definitions of SF. As a DC, SF depends both on the inherent flexibilities of resources available to a firm (resource flexibility) and on the firm’s flexibilities in applying those resources to alternative courses of action (coordination flexibility) (Li et al., 2017).

It can be observed that even though the resource-based view is in a different cluster (i.e. the green one) from DC in Period 1, they were connected to each other. In Period 2, however, they are not only in different clusters (green and red respectively) but are no longer linked to each other. A possible explanation derived from the articles in the sample could be that while firms gain competitive advantage from a resource base with unique characteristics (Bamel and Bamel, 2018; Spanuth et al., 2020; Yeniaras et al., 2020), such resources are static and cannot explain the inability of firm’s resources to adapt to the dynamic digital environment (Zhu et al., 2022). Thus, beyond a rare, valuable, perfectly inimitable, nonsubstitutable and flexible resource base, firms should develop DC to rebuild resource portfolios that contribute to sustainable competitive advantage, in response to the current turbulent business environment (Yang et al., 2020; Yang and Gan, 2021). Hence, considering that the resource-based view and the DC view are usually considered complementary (Bamel and Bamel, 2018), with the latter as an extension of the former, we can observe that they are diverging into somewhat different directions regarding their role in SF. The literature review by Brozovic (2018) proposed further exploration of the links between SF and DC as a route towards sustainable competitive advantage. As the volatility, uncertainty, complexity and ambiguity of the business environment continue to increase, it is important for firms to benefit from the synergistic effect of SF (as one type of DC), with other higher order capabilities, to increase their performance and competitiveness (Bamel and Dhir, 2019).

BMI has taken center stage, as evident by its central position in Period 2, as a route through which firms leverage SF to deliver more sustained competitive advantage (Gaertner and Schon, 2016; Liao et al., 2019; Xiao et al., 2021). Furthermore, the shift from new product development as a primary innovative capability in Period 1 (as evidenced by its close proximity to DC) to BMI in Period 2 further illustrates that researchers and practitioners are increasingly going beyond product or process innovation to consider the role of business models in innovation processes (Gärtner and Schön, 2016). Existing SF research has highlighted the association between BMI and SF (Zhang and Zhu, 2022), as firms are leveraging the DC of SF through resource flexibility and coordination flexibility to facilitate the BMI process (Miroshnychenko et al., 2021). BMI involves integrating all business model elements, the external environment and interfaces with customers and partners, in order to search for new ways of doing business and design new activity systems to create and capture value for its stakeholders (Yang et al., 2020). Resource and coordination flexibility thus allow firms to use more exploratory methods to efficiently and innovatively combine internal and external resources, processes and strategies to pursue novel business models (Xiao et al., 2021). Coordination flexibility can also help alleviate the organizational routine inertia, which helps firms break down institutionalized BMI processes and explore new alternatives (Liao et al., 2019). The association between BMI and resource flexibility, and BMI and coordination flexibility can also be seen by their connection in Period 2.

It is also worth noting that while some studies consider SF as an antecedent of BMI as illustrated above, others see SF as an outcome of BMI (Miroshnychenko et al., 2021; Vihari, 2019). For example (Clauss et al., 2022), identify temporary BMI as a means of increasing firms' SF to react to environmental changes. The researchers revealed this approach as an effective crisis response strategy for small and medium-sized enterprises (SMEs) who were particularly vulnerable to the Covid-19 pandemic. This could be a possible explanation to the emergence of SMEs as a novel keyword in Period 2 since all kinds of businesses are facing challenges to respond to rapid innovation in the dynamic environment” (Nassani and Aldakhil, 2021, p. 1). Thus, researchers and practitioners are recognizing SF as an imperative attribute for SMEs to survive and grow in a competitive context (Majid et al., 2021), despite their constraints (Ahmadi et al., 2020; Clauss et al., 2022). Associated to the topic of SMEs, we find another novel concept in the field of SF, emerging in Period 2, in the top right-hand corner of the figure, namely entrepreneurial bricolage. Entrepreneurial managers of new ventures or start-ups are often faced with the paradox wherein they need to establish competitive advantage but struggle to do so due to their newness, small size, lower organizational legitimacy and insufficient organizational resources (Yu and Wang, 2021). As evidenced by its emergence, entrepreneurial firms are increasingly leveraging entrepreneurial bricolage which entails “making do by applying combinations of resources at hand”, to give them a chance to make better use of available resources and take advantage of overlooked but unusual market opportunities to explore more potential market segments and customers despite their limited resources (Li and Wang, 2021, p. 2). Since SF as a DC involves the effective coordination of resources to generate various solutions to cope with external difficulties (Dewsnap et al., 2020), entrepreneurial firms are not only using SF to supplement the effect of using their resources at hand more creatively (Li and Wang, 2021), but entrepreneurial firms are also developing their SF to react to changing business conditions via entrepreneurial bricolage (Yu and Wang, 2021). Entrepreneurial bricolage enables managers to improve resource mobility in their organizations through reallocation of resources from projects that no longer meet the dynamic needs of the market to develop alternative options, thus increasing the firm’s SF to respond to unexpected changes.

In the blue cluster, KM emerges not only as the central keyword in Period 2 but also a novel keyword that was not present in Period 1. In the newer strategy literature, KM is portrayed as synergistic to SF because cross-functional exchange of knowledge helps organizations quickly understand the changing environment, allowing firms to plan organizational priorities and actions accordingly (Perez-Perez et al., 2019). Scholars have argued that KM is a key component in the development of DC (Gutierrez-Gutierrez et al., 2018). Consequently, in today’s increasingly dynamic environment, managing and transforming a firm’s knowledge stock is vital (Miroshnychenko et al., 2021). The blue cluster features several keywords that are related to aspects of knowledge such as big data, value creation and ambidexterity, emerging in Period 2, which suggests that management of organizational knowledge is increasingly being considered as a valuable resource for firms that support SF (Siahtiri et al., 2020; Zhao and Wang, 2020). KM has been defined in the literature as a set of activities, initiatives and strategies that companies use to generate, store, transfer and apply knowledge within and among organizations (Perez-Perez et al., 2019). It involves three processes, acquisition, conversion and application of new and existing knowledge (Rialti et al., 2020), as the role of the firm is not only to obtain knowledge, but also to exploit and develop knowledge to produce capabilities to respond to the changing environment, thus achieving a fit between the changing environment and SF (Zhao and Wang, 2020). Researchers increasingly regard firms as social communities “specializing in the speed and transfer of knowledge” (Jia et al., 2022), and thus are beginning to focus on knowledge search, defined as “the ability to capture multiple knowledge sources for innovation” (Jia et al., 2022, p. 785), embodying the process of knowledge acquisition. The researchers leverage this definition to distinguish between knowledge search and absorptive capacity where the latter instead stresses on knowledge conversion (e.g. the conversion from external knowledge to internal knowledge). This shift in focus from knowledge conversion to knowledge acquisition, especially in today’s knowledge-intensive environment (Matalamäki and Joensuu-Salo, 2022), can be seen in the decrease of attention of the keyword absorptive capacity considering its significantly smaller node size in Period 2 compared to its central position and relatively larger node size in Period 1. Also, the focus on knowledge acquisition stems from the fact that the more knowledge a firm can accumulate the stronger the capabilities it can develop (Zhao and Wang, 2020).

Knowledge acquisition can be based on big data. The novel keyword big data in Period 2 refers to a large amount of structured and unstructured data, available immediately everywhere and characterized by the 7 Vs: different volume, velocity, variety, veracity, value, variability and visualization (Gnizy, 2020; Rialti et al., 2020). With the demand of firms to obtain a sustainable competitive advantage in uncertain environments characterized by globalization, technological advancements, short product life cycles and fleeting customer requirements, the investment of firms on big data that provide knowledge-rich information is deepening all over the world (Gnizy, 2020; Wan and Liu, 2021). Indeed, the primary objective of big data is to gain new knowledge to establish competitive advantage (Rialti et al., 2020). Brozovic (2018) mentioned the need for a more inclusive understanding of what a business or product can do for a customer and why, by integrating internal resources, technology and the macro environment to increase market orientation and environmental scanning as enablers of SF. This article introduces big data as a tool to enhance SF by increasing a firm’s strategic options given that it “enables the extraction of hidden insights to uncover unforeseen patterns in customers' behaviors and feelings, assists in better knowing customer’s unique expectations and facilitates building a dynamic view of customers and thus exploring new opportunities to change firms' current marketing strategies” (Gnizy, 2020, p. 1225). Furthermore, the use of big data enables SF via the development of growth strategies, primarily product and service development and market penetration and market development strategies (Matalamäki and Joensuu-Salo, 2022).

Brozovic (2018) also called for further investigation into the proactive dimension of SF, though, e.g. creating new markets, influencing the environment, acting upon opportunities or simply pro-acting to changes in the business environment. Research on big data can be seen as a response to this call and consists of three analytic categories: a descriptive one which presents “what happened”, a predictive one which identifies “what is probable to happen,” and a prescriptive one which recommends “what should be done” (Gnizy, 2020). Big data provides input for short-, medium- and long-term choices that firms can leverage to become more proactive and flexible in selecting more effective strategies, with the aim of actively shaping their highly uncertain environments (Gnizy, 2020).

The map shows proximity between big data and ambidexterity indicating that they have frequently been mentioned together in literature. Researchers recognize that organizations that are ambidextrous are better able to leverage big data to thrive in a turbulent environment (Rialti et al., 2020) or, alternatively, big data allows for, e.g. ambidextrous product strategies. Ambidextrous organizations are those that can perform differing and often competing strategic acts at the same time (Ahmadi et al., 2020; Jiang et al., 2021; Majid et al., 2021) for example, quickly respond to market changes, whilst meeting and maintaining an adequate satisfaction level among their existing customers through their products and services (Rialti et al., 2020). Ambidexterity can be conceptualized as an organization’s ability to combine explorative and exploitative innovation, either through balancing them or combining them. Exploration aims at renewing knowledge by experimenting with novel, often disruptive innovation, whereas exploitation involves the refinement and extension of existing competencies, technologies and paradigms (Jiang et al., 2021). Big data has been shown in the literature to be integral to the pursuit of ambidexterity as the information provided by big data increases an organization’s ability to identify and exploit new opportunities emerging in the environment (Rialti et al., 2020). Research has shown that when organizations identify these new opportunities and embark on their exploitation, SF is triggered as the organizations engage in either committing resources to new courses of action, or stop or reverse existing resource commitments, as such, bringing all three variables together (big data, ambidexterity and SF). For instance, research shows that big data is an antecedent of SF and ambidexterity mediates this relationship (Rialti et al., 2020).

The literature also focuses on the role of ambidextrous leadership in managing big data (Jia et al., 2022; Jiang et al., 2021; Zhang and Zhu, 2022), which contributes to further explaining the close proximity between ambidexterity and big data on the map. By demonstrating “opening behaviors”, leaders encourage employees to seek opportunities from the ever-changing innovative environment and build an atmosphere conducive to explorative knowledge search and “closing behavior” where leaders focus on operational effectiveness and performance in line with exploitation (Jia et al., 2022). Also, the pertinent, fast and smart information that big data provides may help in exploring and exploiting previously neglected areas and trigger firms' search for change in their current strategies, thus increasing SF (Gnizy, 2020), especially if the information is directed to the right person within an organization who can take initiative and better identify and exploit opportunities (Rialti et al., 2020). Thus, big data has been identified as an ambidextrous managerial tool enabling innovation and operational efficiency (Gnizy, 2020).

Although the concept of ambidexterity is new in the context of SF, the two dimensions of ambidexterity exploitation and exploration (Benitez et al., 2018; Jiang et al., 2021) were featured already in Period 1, but as individual nodes. However, in Period 2, we find exploitation and exploration merged to form one node, representing the keyword ambidexterity, and this time in close connection to big data unlike exploitation and exploration which were in close connection to absorptive capacity in Period 1. This further strengthens our argument above that researchers are focusing more on knowledge acquisition compared to knowledge conversion.

The other novel keyword in this cluster, value creation, which is in close proximity to SF has been defined in the literature as a key element of BMI (Bashir and Verma, 2019; Liao et al., 2019; Xiao et al., 2021). Research shows that knowledge resources present a significant potential for value creation (Brinckmann et al., 2019), hence the connection between KM and value creation. Firms seek innovative ways to engage in market intelligence which enhances customer value creation processes through sourcing, tracking, storing and disseminating market information for greater awareness of business opportunities to serve customers (Yang et al., 2020). Firms with high SF can leverage their resource and coordination flexibility to reconfigure and recombine their existing resource base with new incoming information to create more value for customers (Yang et al., 2020). As such, firms are engaging in distal knowledge search to access diverse knowledge bases that can contribute to creativity and innovation (Siahtiri et al., 2020). One method that firms are using to access diverse knowledge is the social media strategic capability (SMSC) which has surfaced as a new digital capability that offers opportunities for firms to move beyond the traditional means of value creation (Zhang and Zhu, 2022). SMSC involves the acquisition of information from social media, and its integration within a firm’s knowledge base in alignment with its strategic directions (Zhang and Zhu, 2022). As such, the researchers argue that SMSC enables firms to draw from a wider range of information which increases firms' resource base and helps managers to extend their cognitive capabilities, overcoming potential sources of rigidity as they find innovative ways to recombine these extensive resources, which consequently positively influences firms' SF. Finally, firm competitiveness and competitive advantage which are closely connected to value creation, have all been identified in the literature as outcomes of SF (Bamel and Bamel, 2018), which enhance firm performance.

This cluster presents the “outside-in” perspective of SF by illustrating how SF interplays with the external environment, and the consequent influence on different forms of firm performance. In Period 1, competitive intensity features as the only external variable that provokes SF, but environmental dynamism and environmental uncertainty emerge in Period 2 as additional triggers. Rapid development in technologies, intense competition, increasing globalization, shortening product life cycles and the need for successful new products has fundamentally reshaped the external business environment, making it even more dynamic, complex and unpredictable (Brinckmann et al., 2019; Xiu et al., 2017; Ouakouak and Ammar, 2015). As a result, to stay competitive, firms need to develop SF to adapt (Alamro et al., 2018; Cheng and Krumwiede, 2017; Hoeft, 2021; Xiu et al., 2017). The literature that we analyzed tends to use the terms environmental dynamism and environmental uncertainty rather interchangeably, referring to them as the rate of change and the degree of instability and unpredictability in a firm’s external environment (Cheng and Krumwiede, 2017; Kamasak et al., 2017; Liao et al., 2019; Vihari, 2019; Zhang and Zhu, 2022) ^[4]. Competition, also referred to as competitive intensity, is defined as the degree of competition a firm faces from its competitors (Herhausen et al., 2021). Thus, as mentioned earlier, with the growing environmental dynamism, complexity, uncertainty and competitive intensity, businesses must develop SF that enables them to reorganize their internal resources and adapt their strategies in a way that can increase the likelihood of correct reactions to these emergent exogenous changes, as illustrated by the firms' responses to Covid-19 (Hoeft, 2021; Nowak, 2022).

Additionally, contingency theorists suggest that the success of firm strategies is derived from achieving a fit between firm strategy and the external environment, i.e. companies must strategically align their resources, capabilities and strategies with market changes (Wang and Lou, 2020). Strategic alignment, an emergent keyword in Period 2, is the linking of organizational structure, resources and strategies with the availing environment (Nassani and Aldakhil, 2021). Strategic alignment can reduce resource waste and enhance organizational capabilities during strategy reformulation in innovation processes, as it gives structure and clarity to the organization’s position within its surrounding market (Nassani and Aldakhil, 2021). Also, it allows for the more efficient use of resources. Strategic change is important given the dynamic nature of market competition making it almost impossible to have the “best” strategy in the long term without adjustments over time (Wang and Lou, 2020). Anwar and Hasnu (2017) point out that the current business environment demands a high level of managerial response through strategic change. It is worth highlighting that the keyword strategic change, though mentioned in both periods, appears to be closer in terms of proximity to SF in Period 2 than in Period 1. This indicates a growing relationship between the two keywords as they have started appearing together in more articles in Period 2 compared to the former period.

It is through this external push on SF that firms have identified social and political concerns about the negative environmental impact of their activities (Perez-Valls et al., 2016), and have consequently designed a proactive environmental strategy referred to as green management (Yang et al., 2015). The ongoing environmental degradation caused by development has triggered business leaders to advocate for more social and environmental responsibility via sustainable development, defined as the ability to meet the needs of the current generation without compromising the future generation (Vihari, 2019; Nwachukwu and Vu, 2020). The concept of green practices has emerged as a mechanism for alleviating the negative impact of firm activities on the environment (Jiao et al., 2021; Perez-Valls et al., 2016). The novelty of research on green practices is evidenced by its emergence on the map in Period 2. Green practices are product-related practices that focus on the design and development of more ecological products and process-related practices that highlight the development and implementation of manufacturing and operational processes in a way that reduce the impact on the environment (Jiao et al., 2021). The literature has reported inconsistent findings on the effect of green practices on financial performance. Some studies find a positive effect (Perez-Valls et al., 2016; Yang et al., 2015), whereas others reveal a negative effect (Jiao et al., 2021). Researchers have attributed these inconsistent results to the omission of some important moderators (Jiao et al., 2021). For instance, it is argued that firms with SF can strengthen the positive effect of the adoption of green practices on a firm’s financial performance (Gelhard and von Delft, 2016; Yang et al., 2015). The successful adoption of green practices requires firms to adjust their organizational structures and operational processes. As such, firms with SF are able to overcome organizational inertia and break down existing operational routines at low cost (Kamasak et al., 2017; Xiao et al., 2021), which allows them to benefit financially from the adoption of green practices. Moreover, when SF is high, firms are more sensitive to opportunities in the “green” market and can quickly reallocate resources to green practices adoption with the aim of developing green products that can better satisfy customer demands, thereby expanding market share and earning more profits (Gelhard and von Delft, 2016; Jiao et al., 2021).

Firm performance is a key measure used to evaluate the success or possibility of survival of an organization (Chan et al., 2017), as evidenced by its recurring relevance, indicative of its relatively large node size in Period 1 and Period 2. Firm performance is addressed in all three clusters: as firm performance in the red cluster, as competitive advantage, firm competitiveness and value creation in the blue cluster and as innovation performance and financial performance in the green cluster, which only emerge in Period 2, which goes to further accentuate its relevance. As earlier mentioned, some studies examining SF and firm performance report a positive relationship (Chan et al., 2017; Friedmann et al., 2018; Xiao et al., 2021), but other findings are only partially supportive, or even refute the relationship (Alamro et al., 2018; Ouakouak and Ammar, 2015). It has been argued that financial performance is a narrow indicator of organizational effectiveness and captures only part of a firm’s profitability, which fails to reflect performance as a multidimensional concept (Alamro et al., 2018; Chan et al., 2017). The meta-analysis of Herhausen et al. (2021) showed that SF has a negative direct effect on financial performance. However, the findings suggested that when the indirect positive effect of SF through innovation outcomes and market outcomes is considered, SF’s overall impact on financial outcomes is positive, as they outweigh the costs associated with SF. This is supported by the work of Xiao et al. (2021) who argue that that because of the nature of SF as an organizational resource, “having a positive impact on organizational performance requires implementation of innovative activities” (Xiao et al., 2021, p. 475). Accordingly, the positive relationship between SF and innovation performance has been shown by recent studies in the field (Chen et al., 2022; Nwachukwu and Vu, 2020).

The aim of this research was to systematically review the SF literature with the help of a bibliographic analysis in order to unveil the state of the art of the recent literature on SF. We analyzed the semantic structure of the literature and identified three emerging streams: SF as a DC, the role of KM for SF and the relationship between a firm SF and the external environment. This understanding of the prior literature obtained with the bibliographic analysis leads us to present several avenues for future research that put forward some of the potential interconnections between the stream of research on SF and diverse other topics.

Avenue 1. SF, BMI and other DCs. The red cluster in Period 2 showed the growing importance of SF as a dynamic capability (Chaudhary et al., 2022; Cui and Wu, 2016; Jia et al., 2022; Xiao et al., 2021; Yi et al., 2017). This conceptualization was put forward also before 2015, but what seems to be promising for future research to explore is the interrelationship of SF with other DC. The impact of other higher order DC in enhancing the SF of a firm is illustrated in our findings, which implies synergistic effect of DC in increasing the performance and competitiveness of firms (Bamel and Dhir, 2019). Furthermore, researchers have called for replicating studies on the relationship between DC and SF in developing and emerging countries (Anwar and Hasnu, 2017; Li et al., 2017). Finally, longitudinal studies would be important to better understand the causal relationships between different DC and SF (Yang and Gan, 2021; Yeniaras et al., 2020). In this cluster, we observed the emergence of BMI, seen as a DC, as an important antecedent of SF and consequently firm performance. This is a promising cross-fertilization of streams within the strategic management research that has been unveiled by this study. Miroshnychenko et al. (2021) revealed a nonsignificant link between SF and BMI. In future research, it would be important to clarify further the relationship between SF and BMI and the related mechanisms. For example, alliance reconfiguration capabilities and external stakeholder engagement capabilities could be further investigated as potential facilitators of business model transformation. Also, the role of temporary BMI could be further investigated (Clauss et al., 2022) in SF. Particular research attention was paid to the aspect of BMI in Period 2 considering its emergence as a “powerful means for a firm to anticipate and respond to environmental changes,” Vihari (2019). Researchers could examine further how these two capabilities interact to further enhance a firm’s performance.

Moreover, it would be intriguing to investigate the role of social media, and more broadly social movements, in value creation and BMI, which could influence SF and consequently firm performance (Zhang and Zhu, 2022). Furthermore, Miroshnychenko et al. (2021) have called for a more fine-grained investigation into the complex interplay between the different types of absorptive capacity (e.g. potential absorptive capacity and realized absorptive capacity) in relation to SF and BMI. Finally, BMI is more difficult to implement in established firms, which suggests examining whether entrepreneurial bricolage that has been studied mainly in new ventures, is effective also for incumbents (Yu and Wang, 2021).

Avenue 2. Digital technologies and SF/organizational agility. In the blue cluster, KM was recognized to have an influence on SF since the cross-functional exchange of knowledge helps organizations quickly understand the changing environment, allowing them to reorganize/restructure their resources as they plan organizational priorities and response actions accordingly (Perez-Perez et al., 2019). Nevertheless, with the growth of new technologies, there is a need to investigate how novel KM tools are shaping the field of SF. The speed at which knowledge gets obsolete is accelerating (Zhao and Wang, 2020), which makes firms to turn to big data to provide them with knowledge-rich information to facilitate and speed up their decision-making process (Wan and Liu, 2021).

However, despite the importance of big data and big data analytics in revolutionizing organizations' decision-making processes, most companies have struggled to successfully implement big data strategies (Matalamaki and Joensuu-Salo, 2022). Especially, literature has neglected to explore the organizational micro-mechanisms that can facilitate the transformation of these new tools into new organizational capacities, allowing a firm to react to new situations (Rialti et al., 2020). Accordingly, Rialti et al. (2020) and Wan and Liu (2021) call for investigation into the human element of big data analytics because organizational architectures are insufficient if the organizational members are not capable of managing the system complexity or are unable to relate to each other and share their knowledge. Gnizy (2020) calls for future research into different managerial capabilities (e.g. experience, creativity, intuition) that may influence the big data-strategy formation link that incorporates the dimension of SF.

Also, the commercial value of big data lies in its effective integration with other resources that lead to novel organizational capabilities (Wan and Liu, 2021). Understanding how big data can be combined with other digital technologies such as artificial intelligence and machine learning to reformulate strategies and business models (Matalamaki and Joensuu-Salo, 2022) seems a promising avenue for future research, which also represents a connection across topics in the red cluster. Along the same lines, more research that elaborates the understanding of what constitutes digitalization capabilities, and how these can influence an organization SF and consequently add value for customers is needed (Matalamaki and Joensuu-Salo, 2022). This aligns with the recent developments of the organizational and strategic literature towards examining the connection between digital transformation and strategic change. In particular, organizational agility (a firm’s capacity to effectively and efficiently transform its resources to create new value (Teece et al., 2016), organizational adaptability (learning by an experimental approach) and organizational ambidexterity (combining exploration and exploitation), together with SF, have been put forward as mechanisms and capabilities through which companies can benefit from and respond to digital transformation (Del Giudice et al., 2021; Reeves et al., 2015). The interplay between digital transformation and firm’s adaptive processes is intriguing in its complexity, thus deserving further attention. Before 2015, this interplay was not widely considered, whereas its emergence in more recent studies corroborates the increasing tendency of researchers to approach the topic of digital transformation without neglecting the strategic side of the phenomenon.

Third, this study examined how the relationship between GOPs adoption and firm performance is influenced by firm resources. Firm resources examined in this study included SF and organizational slack, both of which are at the firm level. Future research could examine the effect of other resources at the firm level. For example, big data analytics has been proven immensely useful in the field of operations management (Bag et al., 2021), and recent studies have demonstrated that it can promote green practices adoption and improve environmental performance.

Avenue 3. SF and sustainability. Finally, the green cluster dealt with the role of the external environmental in SF, with green practices emerging as a novel proactive environmental response strategy (Yang et al., 2015), revealing mixed impacts on financial performance. The studies of green practices in the literature so far have focused on a one sided relationship with SF, where SF is considered as either an antecedent (Gelhard and von Delft, 2016; Gorondutse et al., 2020; Nwachukwu and Vu, 2020; Yang et al., 2015) or moderating variable (Jiao et al., 2021; Kamasak et al., 2019; Perez-Valls et al., 2016; Vihari, 2019) in helping firms adopt green management practices and/or sustainability practices. Further research is therefore needed to investigate the potential impact of green practices on SF.

Green practices play a critical role in alleviating the negative impact of firm activities on the environment which has rendered the area of study very relevant as it has become a key factor contributing to firms' competitive advantage (Jiao et al., 2021). However, the studies in the green practices context so far have been very general in nature, with either green management practices treated as a general concept or only green operational practices identified as a particular green management practice. Also, green practices include a wide range of practices that can be classified based on the perspective of firm functional departments such as green operational practices, green procurement practices, green human resource practices, green information systems and green marketing practices (Jiao et al., 2021). Future research could therefore investigate the role of green practices across different organizational functions and their specific relationships with SF and firm performance. For example, the research conducted by Jiao et al. (2021) shows a negative effect of SF on the relationship between green operational practices and financial performance. The negative relationship is theorized to result from the view that SF emphasizes resource configuration and neglects efficiency, thus accentuating the maximum output from existing resources but undermining the efficiency of green operational practice adoption and thus negatively affecting financial performance.

Green practices fall within the environmental dimension of sustainability, a stream that has recently started exploring interactions with SF, but is still underexplored, thus leading to many fruitful avenues for future research (e.g. Kafetzopoulos, 2022; Nwachukwu and Vu, 2020). Research about sustainability has been gaining increasing importance due to the pressing need to pursue sustainability objectives set at the international level. This is due to the negative environmental impact of corporate development activities that pushed firms to now include green management practices and objectives in their strategies (Perez-Valls et al., 2016). Nowadays, firms endeavor to conduct green management activities as required by both business ethics and social responsibility (Yang et al., 2015). This presents an opportunity for managers to investigate how the incorporation of these green management practices influence their ability to respond to changes in the external environment, thus enhancing their SF and consequently their firm performance.

The current research on the relationship between SF and firm performance, including sustainability, appears to be complex with somewhat mixed results. Herhausen et al. (2021) thus call for further investigation using multidimensional conceptualizations and measures. Future studies could employ the multidimensional composition of SF, e.g. reactivity vs proactivity and internal vs external dimensions, which would contribute to clarify the multidimensional conceptualization of SF, to better capture the performance effects. In addition, studies should consider the role of the multidimensional environmental conditions, such as environmental dynamism, environmental uncertainty, demand uncertainty and competitive intensity.

In the broader context of SF, which was presented in this article, the articles included in the special issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” contribute to Avenue 2. Digital technologies and SF/organizational agility. Using a DC lens, Hutter et al. (2023) explores the agile transformation of an incumbent multinational firm, highlighting a set of activities in sensing, seizing and transforming required to succeed and stressing the role of an intermediate solution at a divisional level, to be subsequently scaled up at the organizational level. Brozovic et al. (2023) focus on how to achieve SF in the SME context, finding that a high strategic orientation, mainly in terms of entrepreneurial and market orientation, high innovation and digitalization capabilities, and changing leadership and organizational culture promote SF. Marchese et al. (2023), through a multicase study research based on the DC perspective, confirm that digital technologies seem to support adaptive organizations, not only SMEs, but also larger firms. Contrarily, Marrucci et al. (2023) investigate antecedents of Industry 4.0 implementation, finding that organizational agility and SF play a fundamental role. However, Dahms et al. (2023) and Qin (2023) provide an integrative view of the interplay between SF and digitalization that combines these two apparently conflicting views. On the one hand, Dahms et al. (2023) find that the interplay of organizational agility and digital capabilities contributes to superior innovation performance, but on the other hand, Qin (2023) empirically shows that a degree of flexibility is required for digital transformation that, in turn, increases flexibility. This gives an alternative perspective that puts forward a more sophisticated relationship where SF and digital technologies/digitalization may influence each other, which still deserves further investigation.

Moreover, related to the different constructs coming into play, a distinction between digital technologies and digitalization should be made, because digital technologies may contribute to be more adaptive, as suggested by Marchese et al. (2023), but then, in turn, being more flexible or agile could help taking advantage of digital technologies “to enable major business improvements to augment customer experience, streamline operations, or create new business models” (Warner and Wäger, 2019), which reflects digitalization.

Finally, two contributions are derived from the insights of the new business model (NBM) conference 2022: (1) Minà and Michelini (2023) discuss the role of strategic agility for implementing sustainable business models, proposing a framework that starts shedding more light on other potential avenues for future research presented above, namely BMI and sustainability, while (2) the article by Pusceddu et al. (2023) shows the role of SF to enhancing value creation through customer experience.

Figure 5 illustrates the substreams of research about SF that we established through the bibliometric method and the potential avenues for future research with some exemplary research questions. The figure also exhibits how the special issue builds on and contributes to the second future research avenue through various explorations on the relationship between digital technologies and SF/organizational agility. Moreover, two articles included in the special issue are the evolution of two contributions deriving from the NBM Conference 2022, and contribute to the first and third avenues for future research highlighted in this study.

Following Micevski et al. (2019) and Nowak’s (2022) call to identify key areas where SF can be developed and maintained within firms, this research set out to trace the development of research on SF, to identify novel areas in which the literature has developed lately and to suggest promising future areas of research around SF. We conducted a comprehensive and systematic literature review on SF and analyzed the collected data with bibliometric techniques which helped to reveal the emerging themes in the field. Thus, our findings are underpinned by a robust systematic literature review and bibliometric technique, including co-occurrence of keywords analysis that allowed for the mapping of the research field and revelation of the trends and potential opportunities for research.

Our review contributes to the theoretical understanding of SF by illustrating and explicating core topics that have persisted over time and form the underlying structure of the field. These theoretical underpinnings center around topics such as DC, environmental factors, knowledge aspects and firm performance. Secondly, as pointed out by Bamel and Bamel (2018), the field of SF is constantly evolving, which is apparent in Figure 1, showing a steady rise of published articles between 2015 and 2022, which necessitated a more recent literature review. This study also identified new, emerging and underdeveloped core topics in the field, which were presented as three research avenues in Chapter 5: SF, BMI and other DCs; SF and digital technologies; SF and sustainability. The recently published special issue mentioned in Section 6 focused on examining the relationship between digitalization and SF. While we hope that our article helps to take a step forward in understanding research on SF, a lot remains to be uncovered in the field of SF. Table 2 below provides a summary of the potential research areas for conducting further research in the field.

For practitioners, this study shows the relevance of SF by demonstrating its role in enabling businesses not only to adapt in today’s business environment, but also to survive and thrive amidst exogenous crisis, such as the Covid-19. Second, considering the complex and fragmented nature of the literature on SF, we bring structure into the field by offering insights into the specific resources and/or capabilities that companies can develop to take full advantage of the opportunities offered by SF. The proposed avenues for future research provide insights into different areas where practitioners can partner with academicians to investigate, and consequently implement in their organizations, depending on the results, to increase their SF which has been proven to be vital for businesses. Moreover, they can have a clearer idea about the meaning of SF and its relationship with some macro trends they are inevitably going to deal with or are already confronting with, namely digitalization and sustainability, when facing these new challenges, including reflections about SF is worth doing and helpful.

Despite these contributions, our study has some limitations. Our literature review included articles based on the keyword “strategic flexib*” in the topic. We recognize that limiting the research to this keyword could have exposed the research to the potential risk of omitting relevant articles that discussed similar issues but used different terminology such as “adaptability”, “strategic agility” or “dynamic capability.” However, considering the complexity of the field, we believe it was better to limit the keyword to the main focus of the study. Also, our study used only one database to conduct the study. We recognize that not using multiple databases to gather relevant material for the study may have left out some relevant articles that could have contributed to the study. Nevertheless, the selected database in this article is one of the most trusted databases and so we believe we have captured the most relevant literature in this field.

In conclusion, our study shows the importance of the SF field as a research area and illustrates novel and exciting themes that have recently emerged. We hope that this study has revealed innovative insights that will lead to further studies on SF with significant theoretical and empirical contributions.

Since submission of this article, the following author have updated their affiliation: Corinne Nkeng is at the Arise IIP, Kinshasa, Democratic Republic of Congo.

Erratum: It has come to the attention of the publisher that the article, Agostini, L., Nosella, A., Sarala, R. and Nkeng, C. (2024), “Emerging trends around strategic flexibility: a systematic review supported by bibliometric techniques”, Management Decision, Vol. 62 No. 13, pp. 46-92. https://doi.org/10.1108/MD-02-2023-0135, was compiled into the journal’s Open Access issue in error. The article is an editorial for the Special Issue titled “A strategic perspective on flexibility, agility and adaptability in the digital era”. The publisher sincerely apologises for the error and any inconvenience caused.

Table A1