Unraveling the determinants of SaaS performance: a dynamic capabilities perspective

Cloud computing has reshaped how organizations develop, deliver and consume software, giving rise to the Software-as-a-Service (SaaS) model (Terho et al., 2023). SaaS allows business customers to access applications hosted and managed by external providers on a subscription basis, reducing upfront investment, installation and maintenance while enabling scalability and timely upgrades (Brock and Kohli, 2023; Lu, 2025). Despite rapid growth and prominent success stories such as Salesforce, Adobe and Zoom, SaaS providers differ substantially in performance outcomes (Mero et al., 2022; Liu et al., 2023), raising the question of how organizational determinants are developed and deployed alongside technology-related resources.

Extant research on SaaS and cloud services has predominantly focused on technological and system-related issues. Prior studies examine cloud architecture, data management, security and storage (Senyo et al., 2018; Jagli et al., 2016), as well as website configuration and system quality (Ali et al., 2020; Jyoti and Efpraxia, 2023). While this literature has advanced understanding of the technical requirements for delivering SaaS solutions, it has paid comparatively less attention to organizational and relational factors that may also shape performance, particularly in business-to-business contexts where long-term relationships, trust and coordination are important (Jayasimha and Nargundkar, 2020). Prior SaaS research often focuses on technology drivers or examines organizational factors in isolation, offering limited insight into how these determinants work together as sensing, seizing and transforming to sustain performance (Rodrigues et al., 2021; Suoniemi et al., 2021).

Recent research has begun to recognize a broader set of non-technological determinants of SaaS performance, including market-facing routines, relationship and ecosystem coordination practices, legitimacy and compliance-related activities and business model design choices (Rodrigues et al., 2021; Manis and Madhavaram, 2023). These studies suggest that performance is shaped not by a single capability, but by a constellation of organizational factors that influence how providers engage customers, coordinate with partners and adapt their offerings. However, much of this recent work remains conceptual or survey-based, offering limited insight into how SaaS providers configure and prioritize multiple determinants as an integrated set of sensing, seizing and transforming activities and thus leaving underexplained how these mechanisms operate together in practice (Reimann et al., 2022; Terho et al., 2023). Accordingly, we examine how these determinants work together and map onto sensing, seizing and transforming to address this gap.

To address these limitations, this study draws on Dynamic Capabilities Theory (DCT; Teece et al., 1997) and the hierarchical view of dynamic capabilities (Leemann and Kanbach, 2022). DCT explains performance differences by emphasizing how firms sense opportunities, seize them through timely decisions and investments and transform resource configurations over time (Teece, 2018; Kump et al., 2019; Pitelis et al., 2024). We use DCT to guide how we interpret organizational and relational routines that underpin customer engagement, opportunity identification and commercialization in SaaS markets and we examine how these routines align with the three higher-order dimensions of dynamic capabilities, namely sensing, seizing and transforming, with exploration and exploitation specified as learning orientations. In this framing, business model innovation is interpreted as a firm-level expression of transforming, while the remaining determinants are treated as organizational mechanisms through which sensing, seizing and, at times, transforming are enacted in practice.

The empirical setting consists of small and medium-sized SaaS providers headquartered in South Korea. This context features advanced digital infrastructure, widespread SaaS adoption and demanding certification and security requirements, alongside intense competition and rapidly evolving customer expectations (Statista, 2025). While the analysis is grounded in this context, the study is theory-driven and aims to generate insights applicable to SaaS providers operating in comparable environments.

Guided by these considerations, this study addresses the following research questions:

This research makes three contributions. First, the study extends B2B marketing research by showing that SaaS performance is shaped not only by technology-related factors emphasized in prior studies but also by an interdependent set of organizational and relational determinants that jointly support sensing, seizing and transforming. Second, it strengthens the application of DCT by clarifying that the identified themes are not separate dynamic capabilities but organizational mechanisms through which SaaS providers enact sensing, seizing and transforming in practice. Third, while recent SaaS research has increasingly acknowledged non-technological and relational drivers of performance, this study shows more explicitly how customer-facing, relational, legitimacy-building and business model mechanisms are configured together in practice, thereby offering a more integrated explanation of SaaS performance beyond technology investments alone.

Capabilities exist at different levels within and across organizations (Zollo and Winter, 2002; Teece, 2018). Capabilities that enable firms to deploy existing resources in the present are referred to as ordinary or zero-order capabilities (Winter, 2003). These underpin higher-order capabilities, known as dynamic capabilities, that allow firms to build new capabilities and to create or reconfigure asset combinations in response to change (Zollo and Winter, 2002; Teece et al., 1997; Manis and Madhavaram, 2023). This study adopts DCT as the overarching lens to examine how such capabilities enhance the performance of SaaS providers.

Dynamic capabilities are defined as “the ability to integrate, build and reconfigure internal and external competencies to address a rapidly changing environment” (Teece et al., 1997, p. 516). Subsequent work emphasizes three core dimensions, namely sensing, seizing and transforming (Teece, 2018; Kump et al., 2019; Pitelis et al., 2024). A hierarchical view distinguishes between lower-order capabilities embedded in specific activities and higher-order, firm-level dynamic capabilities that reconfigure how these lower-order capabilities are combined over time (Zollo and Winter, 2002; Leemann and Kanbach, 2022). In this study, we treat sensing, seizing and transforming as the three core higher-order dimensions of dynamic capabilities, while the themes identified in the data are interpreted as organizational mechanisms through which these dimensions are enacted in SaaS markets. Business model innovation is discussed at the firm level, while marketing activities and website functionality and interactivity are reviewed through the lenses of adaptive marketing capabilities and website interactivity, respectively. We review established capability streams in more depth and use DCT to interpret the remaining determinants as organizational mechanisms observed in the data that operate mainly during SaaS commercialization and delivery, while exploration and exploitation are treated as learning orientations (March, 1991).

DCT also highlights the role of absorptive capacity as an important microfoundation. Absorptive capacity reflects the ability to recognize the value of external knowledge, assimilate it and apply it (Cohen and Levinthal, 1990; Zahra and George, 2002). It develops through routines for information sharing, collaboration and joint problem solving and helps explain how firms sense and seize opportunities through knowledge recognition and application (Lane et al., 2006). In the SaaS context, practices such as sharing usage data with customers, co-developing solutions with clients and working closely with partners strengthen absorptive capacity and operate most directly during commercialization and delivery, thereby primarily supporting seizing.

SaaS firms operate in highly dynamic markets where customer needs, technologies and competitive conditions change rapidly (Senyo et al., 2018; Rodrigues et al., 2021). These markets also involve significant concerns about data protection and reliability. Online security has become a key concern for B2B buyers and certifications such as ISO 27001 or regional cloud security schemes can be interpreted as part of a capability portfolio that converts regulatory requirements into market access and legitimacy for SaaS providers (Stephanow and Khajehmoogahi, 2017; Senyo et al., 2018; Singh, 2019). Table 1 summarizes key articles on dynamic capabilities and highlights the perspectives that inform this study.

Within this DCT perspective, prior research points to several capability areas that are particularly relevant for SaaS providers (Rodrigues et al., 2021; Mero et al., 2022; Terho et al., 2023). Adaptive marketing capabilities help firms anticipate market shifts, experiment and adjust strategies to meet changing demands (Day, 2011; Hunt and Madhavaram, 2020). These capabilities contribute primarily to sensing by enabling firms to monitor changing buyer needs and they provide inputs for seizing through timely refinement of value propositions (Day, 2011). Following March (1991), exploration and exploitation are treated as learning orientations that guide how firms refine existing offerings while experimenting with new opportunities under change. From a DCT perspective, exploration and exploitation learning orientations can inform how firms prioritize attention and adjust actions during sensing and seizing under change (Teece, 2018; Ho et al., 2020; Faroque et al., 2022).

Website functionality and interactivity enable SaaS providers to engage buyers and monitor feedback through digital interfaces, which we interpret primarily as supporting sensing (Barreda et al., 2016). Analytics and interactive tools embedded in SaaS websites support sensing by revealing patterns in traffic, behavior and usage signals (Kim et al., 2022). Relational capabilities such as partnerships and information sharing strengthen cooperation with customers and other actors in the ecosystem, which further enhances absorptive capacity and facilitates joint problem-solving (Dong et al., 2017; Yang et al., 2017). Although these routines can also contribute to sensing through ongoing knowledge recognition, we discuss them mainly in relation to seizing because they operate most directly during commercialization, delivery and relational coordination (Teece, 2018). Finally, business model innovation brings these organizational mechanisms together at the firm level and is conceptualized as a firm-level expression of transforming that reconfigures how sensing- and seizing-related routines are combined over time in SaaS markets (Schoemaker et al., 2018; Teece, 2018; Spieth et al., 2025).

From a dynamic capabilities perspective, firms need adaptive capabilities to align resources with environmental change (Teece, 2014; Coreynen et al., 2020). Adaptive marketing capabilities refer to the ability to sense market shifts, interpret customer feedback, experiment with new approaches and reconfigure marketing resources accordingly (Day, 2011; Hunt and Madhavaram, 2020). These capabilities support the sensing and seizing dimensions of dynamic capabilities by enabling firms to detect emerging needs, test solutions and respond in a timely manner.

In turbulent environments, SaaS providers depend on adaptive strategies that allow behavioral change and better strategic fit (Teece, 2014; AlQahtani et al., 2025). Adaptive marketing capabilities involve learning from market experiments, leveraging digital analytics and social media technologies to monitor trends and adjusting offerings in real time (Hunt and Madhavaram, 2020). Consistent with DCT, adaptive marketing capabilities can be viewed as operational capabilities that underpin responsiveness in turbulent markets. They provide important inputs for higher-order dynamic capability processes that reorganize and extend offerings over time.

Research suggests that combining exploitation-oriented refinement with exploration-oriented experimentation can support performance in dynamic environments (March, 1991; Farzaneh et al., 2022). Following March (1991), we treat exploration and exploitation as learning orientations rather than dynamic capabilities and focus on how firms balance refinement and experimentation in their learning routines. Exploitation enables SaaS firms to refine existing services, improve efficiency and deliver incremental innovations, while exploration involves acquiring new knowledge, experimenting with novel solutions and entering new markets (Farzaneh et al., 2022; Li et al., 2025). Consistent with this positioning, we do not frame the concurrent pursuit of exploration and exploitation as a dynamic capability in this study. Instead, it refers to a learning pattern in which SaaS providers refine what works while pursuing new opportunities, which may help interpret how firms update offerings and allocate attention across sensing- and seizing-related activities in dynamic markets (Teece, 2018; Ho et al., 2020; Faroque et al., 2022).

Website functionality and interactivity provide a digitally mediated interface that primarily supports sensing in B2B relationships (Kim et al., 2022). Interactivity is considered a valuable means of improving communication quality because it allows organizations to tailor and personalize interactions with both B2B and B2C customers (Murphy and Sashi, 2018; Valdez et al., 2018; Bozkurt et al., 2021). In the context of cloud computing, the website interactivity of SaaS providers differs from that of other online firms because it relies on both synchronous and asynchronous communication between buyers and sellers on cloud-based infrastructure (Xiao et al., 2020; Jyoti and Efpraxia, 2023).

Interactive websites enable B2B buyers to exchange information, ideas and usage data with SaaS providers (Kim et al., 2022). Analytics tools embedded in these websites support sensing by revealing patterns in traffic and behavior, while real-time communication and self-service features enable timely responses during delivery and use (Wang et al., 2020; Yuan et al., 2024). Website interactivity can enhance buyers’ trust in SaaS providers and strengthen long-term relationships, thereby contributing to performance (Kim et al., 2022). In this sense, website functionality and interactivity can be conceptualized as operational capabilities that primarily underpin sensing and aspects of absorptive capacity in digitally mediated B2B exchanges.

Business model innovation has been widely recognized as a critical driver of competitiveness and performance, particularly in volatile and technology-driven markets (Heider et al., 2021; Wardhana et al., 2023). In the SaaS context, business model innovation is a multifaceted, firm-level phenomenon encompassing changes in revenue structures, service delivery mechanisms and contractual arrangements. It operates at a higher, corporate level than specific marketing or relational routines and can be viewed as a firm-level expression of transforming that reconfigures how operational mechanisms are combined and monetized (Schoemaker et al., 2018; Teece, 2018; Baden-Fuller and Teece, 2020; Cruz-Sánchez et al., 2026).

Revenue model innovation captures the shift from one-off licensing toward recurring approaches such as subscription, freemium and usage-based models (Teece, 2014; Kowalkowski and Ulaga, 2024; Lu, 2025). These models reduce adoption barriers, align payments with realized value and promote long-term customer engagement (Suoniemi et al., 2021; Mero et al., 2022). The scalability of SaaS offerings is further enabled through standardized, cloud-hosted delivery that allows replication across geographies and customer segments while minimizing the need for costly customization (Senyo et al., 2018; Rodrigues et al., 2021). This scalability logic supports international expansion and broadens access to small and medium-sized enterprises that traditionally lacked IT resources. Additionally, performance-linked pricing aligns provider incentives with client outcomes, reduces buyer risk and embeds continuous learning around customer success, reinforcing value co-creation in B2B relationships (Keränen et al., 2023; Uvet et al., 2023).

These elements illustrate how business model innovation enables firms to sense opportunities, seize them through new value-capture logics and transform resource configurations in turbulent environments (Schoemaker et al., 2018; Spieth et al., 2025). In this study, business model innovation is interpreted as a firm-level expression of transforming because it reconfigures how organizational mechanisms are combined and redeployed to support sensing, seizing and longer-term adaptation in SaaS markets (Bruyaka et al., 2024; Cruz-Sánchez et al., 2026).

We adopted an exploratory multiple case study design, which is well suited for examining complex organizational phenomena in dynamic market settings (Siggelkow, 2007; Yin, 2017; Myers, 2019). Because SaaS remains a relatively new business model with limited theory development in B2B marketing, this design enables us to elaborate DCT through rich, contextualized insights rather than statistical generalization (Senyo et al., 2018).

In qualitative case research, sample adequacy is evaluated based on the richness and relevance of the empirical evidence and study purpose, rather than numerical representativeness (Guest et al., 2006; Boddy, 2016; Yin, 2017). Eisenhardt (1989) suggests that four to ten cases are often sufficient for theory building. Consistent with this logic, our final sample of ten cases was appropriate for the study’s exploratory and theory-elaborative purpose, as cross-case comparison showed that the final two interviews reinforced rather than altered the second-order thematic structure.

To investigate determinants of SaaS performance, we conducted ten interviews across ten small and medium-sized SaaS providers in South Korea, following purposive sampling logic (Easterby-Smith et al., 2021). Following Dess and Robinson (1984), we identified firms that informants perceived as outperforming key competitors, reflected in consistent accounts of revenue growth and strong customer retention. In line with prior work, we define SMEs as firms with fewer than 500 employees (Schwaeke et al., 2025). We focused on SMEs because resource constraints make organizational and relational capabilities especially salient. The sample includes one micro firm with about five employees, allowing observation of capability routines in very small organizations (Ricciardi et al., 2025). Firms were selected to meet three criteria. They operated primarily in B2B markets, reported sustained growth and customer retention over five years and had senior executives with direct knowledge of firm-level capability development and performance outcomes.

Between December 2021 and November 2025, we conducted 45–60 min interviews via phone and Zoom with senior executives in IT, marketing and strategy (Myers, 2019). The final analysis included 10 interviews across 10 SaaS providers. The final two interviews did not yield additional second-order themes and instead reinforced the existing thematic structure, providing further support for conceptual saturation for the study’s theory elaboration purpose (Guest et al., 2006; Yin, 2017). South Korea was selected because it combines advanced digital infrastructure, a dynamic IT sector and strong institutional support. In addition, SaaS providers in this setting face evolving certification and security requirements, intense competitive pressure, short technology cycles and rapidly shifting customer expectations, making it a suitable context for examining capability development under competitive and technology-intensive conditions (International Trade Administration, 2024; Statista, 2025).

We used a semi-structured interview protocol that allowed follow-up questions and clarification where needed (Yin, 2017). A consistent set of open-ended and probing questions was used across interviews to support comparability across cases (Eisenhardt, 1989). All interviews were recorded and transcribed verbatim. The protocol covered firm background, marketing activities, capability-related practices, innovations over the past five years, website functionality and interactivity, security certifications, B2B partnerships and information sharing. We also asked managers to describe how changes in customer needs, technologies and competitive conditions influenced their decisions and routines.

We analyzed the data using thematic analysis to identify patterns within and across cases (Braun and Clarke, 2006; Yin, 2017). The analysis combined inductive coding grounded in participants’ accounts with theory-guided interpretation informed by DCT (Teece et al., 1997; Teece, 2018). First, we read the transcripts repeatedly and manually generated initial codes grounded in managers’ descriptions of activities, routines and decisions linked to SaaS performance (Myers, 2019). We then organized these initial codes into candidate themes and examined how they align with sensing, seizing and transforming, consistent with DCT (Teece, 2018). These first-order codes captured concrete practices such as market sensing activities, customer feedback use, experimentation, website-based support routines, security practices and ecosystem collaboration. We iteratively reviewed and refined themes to ensure internal coherence and clear distinctions across cases (Braun and Clarke, 2006).

Second, we grouped related first-order codes into second-order themes through iterative comparison within and across cases and by moving between the data and relevant literature on dynamic capabilities, adaptive marketing capabilities and exploration and exploitation as learning orientations (March, 1991; Day, 2011; Hunt and Madhavaram, 2020; Teece, 2018). At this stage, DCT guided the development of second-order themes by clarifying whether the emerging patterns reflected sensing, seizing or transforming processes. We also interpreted how routines such as information sharing and partnering supported knowledge recognition, assimilation and application, which are closely associated with absorptive capacity (Cohen and Levinthal, 1990; Zahra and George, 2002).

Third, we integrated the second-order themes into aggregate dimensions aligned with our hierarchical framing of capabilities. Consistent with DCT, we aggregated the second-order themes into sensing-, seizing- and transforming-related dimensions and then applied the hierarchical view to distinguish firm-level from activity-level patterns (Teece, 2018; Leemann and Kanbach, 2022). Business model innovation was coded as a firm-level pattern associated with transforming, whereas the remaining dimensions were interpreted as organizational mechanisms through which firms primarily enact sensing and seizing in practice. This coding decision was guided by our theoretical framing and supported by cross-case evidence that business model innovation reflected firm-wide changes in value creation and capture, rather than activity-specific routines. Coding was iterative, involving refinement of category boundaries and systematic comparison of patterns across cases (Krippendorff, 2018; Yin, 2017). To enhance reliability, a senior researcher reviewed the coding structure against the transcripts and it was refined through discussion. Table 2 summarizes the coding structure and illustrates how the themes were derived and organized through iterative analysis.

Before presenting the findings, Table 3 reports the participating organizations and key informants. This provides an overview of the cases analyzed and establishes the basis for the thematic discussion that follows.

Thematic analysis was used to identify determinants of SaaS performance. First-order codes were derived from interview data by noting recurring patterns and managerial actions. These were then grouped into broader categories as second-order themes. Drawing on DCT as an interpretive lens, we organized the second-order themes into three aggregated themes that reflect sensing, seizing and transforming activities, treating exploration and exploitation as learning orientations within market-led customized innovation (March, 1991). As summarized in Table 2, the aggregated themes are:

• Sensing market signals and generating demand;

• Seizing opportunities through solution adaptation, legitimacy, and relational coordination; and

• Transforming through business model redesign. Interview quotes and examples demonstrate how each theme is grounded in the data.

1. Sensing Market Signals and Generating Demand

Marketing activities. All participating organizations emphasized the importance of digital marketing to SaaS performance. Most customers were acquired through company websites and online inquiries, supported by advertising, analytics and Search Engine Optimization (SEO). Several firms also pointed to content marketing, webinars and customer success stories as tools for building trust and retaining customers:

Alongside digital channels, some firms (A, B, D) still used offline events, forums, and advertising. Although digital approaches were viewed as more cost-effective, traditional marketing remained useful for trust-building, relationship development and reaching senior decision-makers:

These insights are consistent with prior research showing that marketing capabilities help firms sense market changes through web-based approaches while minimizing costs (Day, 2011). Company websites can reduce buyer search costs (Baden-Fuller and Teece, 2020) and web analytics can convert clickstream signals into actionable insights on traffic and visitor behavior (McGuirk, 2023). Reliance on cloud-based marketing also reflects efficiency and speed compared with traditional methods (Kannan, 2017). In line with Reimann et al. (2022) and Hunt and Madhavaram (2020), the findings suggest that adaptive marketing capabilities involve continuous market learning and timely adjustment to evolving B2B buyer needs. In this study, we interpret marketing activities as reflecting adaptive marketing capabilities. These routines support sensing by helping firms detect shifts in buyer needs and generate demand signals through both digital and offline channels.

Website functionality and interactivity. Firms (A, C, D, E, F, H) identified website functionality and interactivity as a driver of performance because it supported lead generation, monitoring of buyer engagement and ongoing outreach. Most firms used Google Analytics and Naver (for example, A, C, D, H), while others combined SEO, BI dashboards and marketing automation (E, F, J). These tools helped managers monitor visitor numbers, navigation paths and behavior patterns, enabling responses to shifts such as increasing mobile usage:

In addition, firms highlighted the role of website analytics and automation tools in enabling more timely, targeted outreach and in supporting rapid adjustments to market response:

These practices align with prior studies showing that web analytics and related tools improve website effectiveness by converting data into actionable insights (Yang et al., 2017; McGuirk, 2023). Managers also linked improved website traffic and more targeted outreach to sales growth and revenue outcomes, consistent with Winkler et al. (2020). In this study, we interpret website functionality and interactivity as reflecting website interactivity. These analytics-enabled and interactive features support sensing by monitoring buyer engagement and enabling timely, targeted responses to changes in market interest.

2 Seizing Opportunities through Solution Adaptation, Legitimacy, and Relational Coordination

Market-led customized innovation. Most organizations engaged in market-led customized innovation by gathering customer input, adapting solutions and developing new services. Firms described both exploratory and exploitative learning as they refined existing offerings while responding to emerging opportunities (March, 1991). They also reported operational adjustments to support delivery and performance outcomes, including process adjustments and service redesign.

In Company A, representatives frequently visited B2B buyers to capture opinions and requirements. The firm synthesized customer feedback to identify unmet needs and experimented with a new solution launch as a response to emerging opportunities, while also using these interactions to identify mobile applications as a priority for future performance. This illustrates how customer-led input supported exploitation of existing knowledge and exploration of new service opportunities:

Company C emphasized acting early on an anticipated market trend. This early action reflects exploratory learning that allowed the firm to position its service offering ahead of demand shifts and reduce uncertainty in solution direction:

Other firms highlighted exploitative improvement routines that strengthened efficiency and delivery reliability. These routines focused on standardizing workflows, removing redundancy and tightening implementation processes so that existing services could be delivered with greater consistency and lower cost:

Service redesign and service innovation were also visible through concrete initiatives that supported adoption and customer value. In these cases, firms adjusted service features and delivery processes t to improve usability and fit with customer operations, which facilitated adoption and strengthened perceived value:

Overall, these findings indicate that exploration, exploitation, service redesign and service innovation operate as complementary components of market-led customized innovation. Consistent with Birkinshaw et al. (2016) and Cenamor et al. (2019), managers described maintaining performance by refining what works while pursuing new opportunities. The evidence is used here to document concurrent learning orientations and operational adaptation, rather than to interpret this pattern as organizational ambidexterity as a dynamic capability. For instance, Company E emphasized efficiency-driven refinement, while Company A simultaneously experimented with new digital offerings:

Together, these examples make the concurrent pursuit of exploitation and exploration more concrete in the cases.

Security certifications. SaaS managers (A, C, G, H) emphasized that certifications were essential for market access and contract eligibility, particularly for public-sector buyers and international partners. Company A noted that overseas partners requested ISO certifications as a prerequisite for entering global markets, while Company C linked cloud service security certification to expansion into the South Korean public sector. Company G described certifications such as CSAP as functioning beyond technical labels by effectively serving as a license for participation in public procurement. In the Korean context, Company H added that ISMS and CSAP were prerequisites for government contracts and that the firm also holds ISO 27001 and ISO 27017:

Prior studies confirm that certifications are critical for SaaS performance (Stephanow and Khajehmoogahi, 2017), as they facilitate customer acquisition, retention and market entry (Singh, 2019; Kochhar and Khanna, 2020). To improve market penetration and achieve global reach, SaaS providers in South Korea increasingly need to adopt internationally recognized certifications such as ISO.

B2B partnerships. Partnerships were highlighted as essential for SaaS performance, encompassing both strategic alliances with partners and buyer trust and commitment. These relational capabilities facilitated collaboration, responsiveness and sustained competitiveness by enabling firms to coordinate complementary resources and capabilities.

On the strategic alliance side, firms emphasized collaborating with partners that provided complementary resources and capabilities to enhance coordination and performance. Such alliances allowed providers to focus on core solutions while leveraging partners for customer support, implementation or channel access, which improved service quality and reduced operating costs for resource-constrained SMEs (Day, 2011; O'Dwyer and Gilmore, 2018; Reimann et al., 2022):

On the buyer trust and commitment side, some providers reported that trust-based relationships strengthened performance. Trust improved communication and made it easier to understand customer needs and respond quickly, which supported referrals and reinforced relationship continuity over time. Company B and D described this dynamic as customers introducing the service to other potential buyers, consistent with prior work on relational governance and performance in B2B contexts (Dong et al., 2017; Paparoidamis et al., 2019; Yoon and Moon, 2019):

Information sharing. Positive relationships often enhanced buyer trust and facilitated information sharing between buyers and sellers. Firms reported sharing sensitive or proprietary information with B2B customers through mobile applications, online platforms and joint analysis activities, with these exchanges typically enabled by established relationships. This pattern is consistent with prior work suggesting that firms are more willing to exchange information or knowledge with trustworthy buyers when mutual benefits are clear (Yang et al., 2017). In our cases, customer-facing information sharing supported collaboration and service outcomes by improving coordination, clarifying requirements and accelerating problem-solving during delivery and ongoing use. These exchanges also strengthened absorptive capacity by enabling knowledge recognition, assimilation and application during delivery and post-adoption use (Cohen and Levinthal, 1990; Zahra and George, 2002; Lane et al., 2006):

Firms also described information sharing with partners and ecosystem actors through joint content creation, co-hosted events and access to shared databases. These partner-oriented exchanges reinforced relational coordination and helped firms act on opportunities by extending reach, strengthening engagement and improving responsiveness in implementation and commercialization. Consistent with Dong et al. (2017), the findings suggest that trusted relationships can sustain ongoing information exchange and build confidence in collaboration over time:

3 Transforming through Business Model Redesign

Business model innovation. All participating firms emphasized business model innovation as a key driver of performance. To address concerns about mixing units of analysis, we present business model innovation as a firm-level redesign of how value is created, delivered and captured and we report the recurring patterns that managers linked to performance outcomes. Three subcategories emerged: revenue model innovation, scalability logic and performance-based contracts.

Revenue model innovation reflected a shift from product-based sales to subscription, freemium and usage-based models (Kahn, 2018; Teece, 2018; Jabeen et al., 2023; Kowalkowski and Ulaga, 2024; Lu, 2025). Managers described this flexibility as allowing them to serve both smaller buyers with limited budgets and larger customers seeking advanced features, while supporting more predictable revenue streams and ongoing customer engagement:

Scalability logic enabled firms to broaden their customer base and international reach through packaged and standardized solutions (Mero et al., 2022; Dutta et al., 2025). Managers linked scalability to faster expansion with lower delivery risk by reducing reliance on costly customization and enabling entry into overseas markets without heavy local infrastructure:

Finally, performance-based contracts reflected outcome-driven agreements that aligned provider compensation with client results (Datta, 2020; Keränen et al., 2023; Uvet et al., 2023). By linking fees to measurable outcomes, managers described these contracts as strengthening longer-term relationships and reinforcing value co-creation by aligning incentives during implementation and post-adoption use:

Overall, the findings indicate that business model innovation extends beyond technical improvements to include flexible revenue design, scalable delivery and outcome-linked contracting (Foss and Saebi, 2017; Markfort et al., 2022; Spieth et al., 2025). Within the studied SMEs, managers described these choices as shaping commercialization and delivery logic in ways that supported adaptation and sustained performance.

This study identifies seven organizational determinants of SaaS performance and shows how they operate as an integrated set of sensing, seizing and transforming mechanisms. Drawing on DCT (Teece et al., 1997) and the hierarchical view of dynamic capabilities (Leemann and Kanbach, 2022), the findings extend prior work that has primarily emphasized technology-oriented drivers by showing that SaaS performance is supported by an interdependent set of organizational mechanisms enacted through sensing, seizing and transforming in practice. The findings both align with and extend recent SaaS and dynamic capabilities research. Consistent with prior studies, the results confirm that non-technological determinants such as customer engagement, relational coordination, legitimacy-related activities and business model design matter for SaaS performance. However, this study extends the literature by showing how these determinants are configured together as organizational mechanisms that jointly support sensing, seizing and transforming, rather than operating as isolated influences. In doing so, the study provides a more integrated explanation of how SaaS providers support performance in practice.

First, the study shows that SaaS performance is shaped not only by technology-related factors such as system quality or cloud architecture (Jagli et al., 2016; Ali et al., 2020), but also by a coordinated set of organizational and relational determinants, including marketing activities, website functionality and interactivity, customized innovation, certifications, partnerships, information sharing and business model innovation. This advances B2B marketing research by placing buyer engagement, partner coordination and legitimacy building at the center of the performance discussion in digital service markets.

Second, the study strengthens the application of DCT by explaining how firms build, integrate and reconfigure capabilities in response to market change. Marketing activities that reflect adaptive marketing capabilities support ongoing sensing and responding to evolving customer requirements. Website interactivity supports sensing by monitoring buyer engagement signals, while information sharing and B2B partnerships support seizing by enabling knowledge application and coordination with customers and complementary actors during adoption, delivery and refinement. Certifications do not operate only as compliance requirements. They function as a credibility and market-access mechanism that enables entry into regulated segments and public procurement contexts. Together, these determinants show how firms coordinate sensing- and seizing-related routines to respond to change and sustain performance. This interpretation is consistent with recent dynamic capability research that emphasizes sensing, seizing and transforming as the core dimensions of organizational adaptation (Kump et al., 2019; Pitelis et al., 2024). It extends this research by showing more explicitly how sensing is enacted through marketing activities and website functionality and interactivity, how seizing is supported by customized innovation, certifications, partnerships and information sharing and how transforming is expressed through business model innovation.

Third, consistent with the hierarchical view used in the study, the findings clarify the role of business model innovation relative to the other determinants. Business model innovation represents a firm-level expression of transforming because it redesigns how value is created, delivered and captured through revenue model innovation, scalability logic and performance-based contracts. Marketing activities, website functionality and interactivity, market-led customized innovation, security certifications, B2B partnerships and information sharing are interpreted as organizational mechanisms through which sensing, seizing, and, at times, transforming are enacted in practice. Within market-led customized innovation, firms combined exploration and exploitation as learning orientations (March, 1991) to refine existing services while experimenting with new features and delivery approaches. Together, these determinants show how firm-level transformation is supported by a broader set of coordinated organizational and relational mechanisms.

The findings also provide practical implications for managers in SaaS markets. Managers should look beyond technology-related investments and focus on capability development that supports sustained performance. These marketing activities require continuous customer feedback and internal coordination so that learning translates into service updates, onboarding improvements and clearer value propositions. Website interactivity should be managed as a channel for customer engagement and knowledge exchange with business buyers. This includes improving responsiveness, offering clearer pathways to product evaluation and providing credible information that supports decision-making.

Managers should also prioritize relationship building and coordination with partners. B2B partnerships and information sharing can improve implementation, integration and ongoing service delivery, especially for small and medium-sized providers with limited resources. Certification-related practices should be managed proactively as part of market strategy. In settings where procurement and compliance shape demand, certifications can strengthen legitimacy and expand access to enterprise and public-sector customers.

Finally, the study suggests that business model choices can be a direct lever for performance. Providers can use revenue model innovation, scalability logic and performance-based contracts to better align with customer outcomes and differentiate in competitive markets. Performance-based contracts, in particular, can strengthen trust and commitment when buyers require evidence of value and accountability. Overall, sustained SaaS performance depends on how firms coordinate sensing, seizing and transforming across these determinants.

This study has several limitations that also suggest directions for future research. First, our evidence is based on ten interviews with SME SaaS providers, including one micro firm with around five employees. This focus allows close observation of capability routines under resource constraints, but it may limit transferability to larger providers with more formalized structures and specialized functions. Future research could replicate the framework using a larger, more diverse set of firms, including enterprise-scale providers, to assess whether the same determinants operate similarly across size tiers. Second, the study examines firms headquartered in South Korea, which may limit transferability to other institutional and regional contexts. Comparative research across Western and Asian markets could clarify how institutional arrangements and cultural norms shape capability development and deployment.

Third, the study relies on qualitative case evidence, which provides depth but does not enable statistical inference about the strength of relationships among determinants and performance. Future research could test the proposed relationships using surveys or archival data and estimate effect sizes across broader samples. Fourth, the findings reflect a largely cross-sectional snapshot of capability deployment. Longitudinal designs could capture how adaptive marketing capabilities, exploration-exploitation learning orientations and business model innovation evolve over time as firms respond to ongoing digital transformation and market turbulence. Although AI did not emerge as a dominant determinant in the present interviews, future research could examine how AI-enabled capabilities influence SaaS performance and reshape sensing, seizing and transforming in this industry.