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The value-creating role of firm capabilities: mapping relationships among absorptive capacity, ordinary capabilities, and performance.

Research related to capabilities in general, and dynamic capabilities in particular, is one of the most active areas of scholarship in management and has much promise as an area of study (Di Stefano et al, 2014; Helfat and Winter, 2011). Capabilities are developed from deeply embedded routines within the firm and have been singled out as the primary functions crucial for firm survival (Prahalad, 1993; Winter, 2000). The majority of research in this area focuses on two important classes of capabilities: dynamic capabilities and ordinary capabilities (Teece, 2014). Each type of capability is noted for its value-creating benefits; however, limited investigations examine how these classes of capabilities work together to create firm value and deliver performance returns.

To understand how capabilities are configured within the firm, the relationship between one type of firm-level dynamic capability, absorptive capacity, and ordinary capabilities is examined. Absorptive capacity (ACAP) is the capability of the firm to acquire, assimilate, transform, and exploit new knowledge toward commercial ends (Cohen and Levinthal, 1990; Zahra and George, 2002). Firms with refined knowledge management capabilities, such as ACAP, are better equipped to obtain and extract value from external knowledge resources (Argote, 1999), adapt to change, and enhance their competitive advantage. ACAP is noted to influence firm performance (Cohen and Levinthal, 1990; Todorova and Durisin, 2007; Zahra and George, 2002), as well as other firm outcomes including innovation (Huang et al, 2015; Leal-Rodriguez et al, 2014), corporate entrepreneurship (Garcia-Morales et al, 2014), market responsiveness (Chang et al, 2013), new products (George et al., 2001), product development (Stock et al., 2001), and financial outcomes (George et al., 2001). The nature of these findings suggests that ACAP is essential in creating firm value and altering firm outcomes, although, the means through which this value creation occurs remains less clear.

For the firm to successfully compete in a dynamic marketplace, the capability to understand the marketplace is necessary to ensure the firm remains in congruence with the environment. ACAP is a dynamic capability that enables the firm to obtain new, external knowledge, yet once the knowledge exists within the firm, internal capabilities are required to exploit the knowledge and create value. Without internal mechanisms (capabilities) to leverage new knowledge, the value of obtaining new insights is marginalized. Therefore, this study hypothesizes that knowledge entering the firm via ACAP is exploited via internal ordinary capabilities, and through ordinary capabilities, firm value is created and performance affected.

After hypothesizing a broad relationship between ACAP and ordinary capabilities, a finer-grained perspective is used to more closely examine the relationship between ACAP and three types of ordinary capabilities (i.e., customer, alignment, and operational). An analysis of data from a sample of firms in the software industry suggests that ordinary capabilities serve an intermediary role in the ACAP-performance relationship, and ACAP has a positive relationship with each type of ordinary capability (i.e., customer, alignment, and operational capabilities). Thus, results suggest that firms exploit new knowledge via ordinary capabilities.

The findings of this investigation offer several contributions to the existing research on firm capabilities. First, insights extend prior findings that ACAP is directly related to firm performance by demonstrating that value is created via ordinary capabilities. Second, this investigation offers new insight into the manner in which ACAP relates to ordinary capabilities by finding that ACAP has a positive relationship with each type of ordinary capability. Third, although several studies have examined various classes of capabilities, few studies simultaneously investigate how multiple classes of capabilities (i.e., dynamic and ordinary) are configured in relation to firm performance. Overall, the findings offer a more comprehensive understanding of capability value-creation, noting how firm-level capabilities work together to influence performance.


Capability-Based Perspective

A capability is a high-level routine, or collection of routines, that offers managers the ability to create commercial output (Winter, 2000). Capability-based research evolved from the resource-based perspective and acknowledges the need for firm resources to remain flexible given the ever-changing environment (Schreyogg and Kliesch-Eberl, 2007). That is, capability research seeks to understand how firms dynamically configure their resources for competitive advantage. Firm competitive advantage is primarily obtained via two classes of capabilities: dynamic capabilities and ordinary capabilities (Teece, 2014).

Ordinary capabilities exist to generate value that the firm delivers to its customers (Winter, 2003), thus representing the "value-creating engine" of the firm. Taking a latent action perspective (Di Stefano et al, 2014), researchers have argued that dynamic capabilities may be viewed as capabilities that allow the firm to shape and integrate ordinary capabilities, such that the firm's value-creating engine is constantly aligned with the dynamics of the competitive environment (Teece et al, 1997; Winter, 2000). Teece notes that dynamic capabilities, "... enable an enterprise to profitably build and renew resources and assets that lie both within and beyond its boundaries, reconfiguring them as needed to innovate and respond to (or bring) changes in the market and in the business environment more generally" (2014: 332). Given its capability to integrate, build, and reconfigure ordinary capabilities in response to environmental changes, ACAP has been deemed to be one such dynamic capability through which competitive advantage is obtained (Zahra and George, 2002).

Absorptive Capacity (ACAP)

Firms seek and use new knowledge to meet the changing demands of a dynamic environment. ACAP is the capability of the firm to acquire, assimilate, transform, and exploit new knowledge for commercial purposes (Cohen and Levinthal, 1990; Zahra and George, 2002). The acquisition component of ACAP acknowledges the firm's ability to actively scan the environment and obtain new, potentially valuable, knowledge (Liao et al, 2003). Once the knowledge is acquired, the firm assimilates (synthesizes and understands) the new knowledge (Zahra and George, 2002). The knowledge is then transformed and stored for future use, and the knowledge is ultimately exploited.

The components of ACAP collectively create value and are related to performance outcomes (Daspit and D'Souza, 2013); yet, the means through which new knowledge is exploited by the firm to achieve desired performance remains to be understood. Zahra and George (2002) hypothesize that exploitation should logically be embedded in routines that allow the firm to leverage existing capabilities. Hence, exploitation is suggested to represent the firm's ability to incorporate knowledge into its internal operations. Flatten et al. (2011) posit that exploitation refers to the firm's ability to improve and expand existing competencies and routines. In all, researchers generally acknowledge exploitation as a viable and necessary component of ACAP, yet a comprehensive explanation of how the exploitation of knowledge occurs is largely absent.

To this end, the current conceptualization of ACAP is extended to suggest that once knowledge is acquired, assimilated, and transformed, the exploitation of the knowledge occurs via a different class of capability. ACAP, a dynamic capability, is suggested to exploit new knowledge via the ordinary capabilities of the firm. This is in line with prior research (e.g., Flatten et al., 2011) suggesting that the exploitation of new knowledge is leveraged through changes made to the existing internal operations and systems associated with the ordinary capabilities of the firm.

The Exploitation Role of Ordinary Capabilities

The broad relationship between dynamic capabilities and ordinary capabilities is acknowledged in the strategic management literature (Di Stefano et al., 2014; Teece, 2014). Pavlou and El Sawy (2011) show that dynamic capabilities influence operational capabilities in the context of new product development, and Zahra et al. (2006) offer conceptual arguments to support the relationship between dynamic capabilities, ordinary capabilities, and firm performance. Zott (2003) uses dynamic modeling techniques to demonstrate how the cost and use of dynamic capabilities influence performance via operational routines (i.e., via ordinary capabilities). Broadly, research suggests an interconnectedness among dynamic capabilities, ordinary capabilities, and firm performance.

Given that ACAP is a type of dynamic capability, a similar interconnectedness is hypothesized to exist between ACAP, ordinary capabilities, and firm performance. Several scholarly studies offer evidence of statistically significant relationships between ACAP and firm performance (e.g., Liao et al, 2007; Schreyogg and Kliesch-Eberl, 2007; Fosfuri and Tribo, 2008; Volberda et al, 2010; Lewin et al, 2011). However, only a few investigations attempt to understand the means through which ACAP leverages knowledge for the benefit of the firm (see Tu et al, 2006). Kostopoulos et al. (2011) find that ACAP is not directly related to a firm's financial performance, but rather, that the firm's innovation capability mediates this relationship. These studies suggest a value-creating role for ordinary capabilities.

ACAP is responsible for enabling the firm to obtain new, external knowledge regarding market changes. However, simply having exposure to valuable external knowledge is not sufficient to ensure a competitive advantage; the firm must have internal capabilities that enable the synthesis and application of the knowledge to create value (Jansen et al, 2005). ACAP is a dynamic capability of the firm (Zahra and George, 2002), and Teece acknowledges that dynamic capabilities are "higher-level activities that can enable an enterprise to direct its ordinary activities toward high-payoff endeavors." (2014: 328) Thus, as new knowledge is obtained via the "higher-level activities" associated with absorptive capacity, the knowledge must then be leveraged via "ordinary activities" to leverage the benefit.

In summary, prior literature acknowledges a relationship between ACAP and firm performance. However, once new knowledge enters the firm, it does not directly alter firm performance. The new knowledge must first be leveraged into value-enhancing products and services, and it is through such exploitation of the new knowledge that firm performance is altered. Here, ordinary capabilities are posited to act as a transducer (2) that allows the firm to leverage the new knowledge that has been acquired, assimilated, and transformed by the firm's ACAP, thereby enabling the creation of products and services valued by the customer and influencing firm performance. Insights from capability literature are extended to suggest that new knowledge obtained via ACAP creates value through relationships with ordinary capabilities in the firm. Therefore, ordinary capabilities are hypothesized to have a mediating role in the relationship between ACAP and firm performance.

Hypothesis 1: Ordinary capabilities mediate the relationship between ACAP and firm performance.

Relationships between ACAP and Types of Ordinary Capabilities

Now that a broad relationship among ACAP, ordinary capabilities, and performance is established, a more detailed perspective is taken to understand the relationships between ACAP and each type of ordinary capability. Winter (2003) refers to ordinary capabilities as the capabilities governing "how we earn a living now" in the firm (Winter, 2003: 992) giving such capabilities a central role in the basic functions of the firm. To conceptualize the various types of ordinary capabilities within the firm, a review of capability literature was conducted, (3) and three general types of ordinary capabilities are acknowledged to exist: customer, alignment, and operational. These three types of ordinary capabilities are not specific to a functional area in the firm; rather, each exists at the firm-level and spans across functional areas. The hypothesized relationships between ACAP and each type of ordinary capability are developed below.

ACAP and customer capability. The customer capability represents the firm's ability to build customer relationships to (a) obtain knowledge from the firm's stakeholders and become aware of both current and future demand patterns (Treacy and Wiersema, 1993) and (b) respond in a timely manner to the customer, thereby realizing market demands (Hall, 1992, 1993; Kaplan and Norton, 2006; Roberts and Grover, 2012). Prior studies suggest a positive relationship between ACAP and the customer capability may exist. Welsch et al. (2001), for example, find that knowledge acquisition--one component of ACAP--is positively related to the firm's responsiveness and ability to adapt to changing consumer demands. Further, in an investigation of Taiwanese financial service companies, Chen and Ching (2004) find that the ACAP of a firm influences customer relationship management practices.

Prior insights are extended to suggest that knowledge acquired, assimilated, and transformed via the firm's ACAP affects the customer capability. ACAP influences the market responsiveness of the firm (Chang et al, 2013), which is an outcome affected by the customer capability. As new knowledge is obtained and understood, insights may be leveraged to enhance the firm's ability to respond to customers in an effective and expedited manner. Thus, given that knowledge acquired and utilized by a firm likely enhances the ability of the firm to anticipate and respond to customer needs, ACAP positively relates to the customer capability of the firm.

Hypothesis 2: ACAP is positively related to the customer capability.

ACAP and alignment capability. The alignment capability allows the firm to mobilize and combine knowledge (Lenz, 1980) to make continuous product and/or process improvements (Cakar and Erturk, 2010) that align the value creating engine with market needs. This capability offers the firm a logical, incremental pathway (Duncan, 1972) to align knowledge from existing customer or operational capabilities.

Weeks and Thomason (2011) examine the relationship between ACAP and firm improvement, and the authors demonstrate how the relationship improves by altering the configuration of human capital dedicated to ACAP. Measures of R&D are occasionally used as a proxy for ACAP (e.g., Lane and Lubatkin, 1998), and Li (2011) finds that investment in R&D is positively related to incremental innovative change. Prior studies support the existence of a relationship between ACAP and product/process adjustments (e.g., Liao et al, 2007). When firm-level change is necessary, the extent to which a firm acquires and leverages external knowledge likely enhances the capability of the firm to make incremental improvements and enhance capability alignment. Thus, the external knowledge acquisition and integration capabilities that create the firm's ACAP are exploited to alter the incremental changes specific to the alignment capability of the firm.

Hypothesis 3: ACAP is positively related to the alignment capability.

ACAP and operational capability. The operational capability is the firm's ability to allocate resources and share common processes in a cooperative manner (Kaplan and Norton, 2006; Crossan et al, 2009). This collection of routines allows a firm to respond to market demands by implementing customized practices that result in desired products or services. The operational capability is commonly embedded in value-creation activities associated with manufacturing, service, purchasing, sales, distribution, and similar activities.

Levinthal and March (1993) highlight the relationship between knowledge exploitation and firm efficiency, noting that through the use of new knowledge acquired, the firm can refine internal value-creating processes. Thus, the authors conceptually link ACAP with the operational capabilities of the firm. At a higher level of abstraction, Cepeda and Vera (2007) find support for the influence of dynamic capabilities on operational capabilities among information technology and communication industries in Spain. Furthermore, Tanriverdi (2005) examines new knowledge acquisition capabilities and suggests that such capabilities influence cross-unit synergies, a component of the firm's operational capability. Overall, operational efficiency is enhanced through the utilization of the firm's ACAP (Malhotra et al., 2005), which suggests a positive relationship between ACAP and the operational capability.

Hypothesis 4: ACAP is positively related to the operational capability.


Data Collection and Sample

Prior to the data collection for the main study, a panel of experts reviewed items in the survey instrument to ensure their applicability to both product and service-oriented firms. A key informant approach, in which top managers were identified, was used to collect data (Kumar et al, 1993), and data collection began with a pilot study. In the pilot study, the research team tested the updated instrument with a sample of top executives from firms in the software industry. After reviewing their responses, the research team made minor refinements to the survey instrument to ensure contextual appropriateness.

The research team obtained firm names and contact details from a dataset acquired from a leading industry database provider and collected data for the study using an Internet-based survey administered to top-level managers of firms in the software industry. The research design was crafted using Dillman's (1978, 2007) total design method for survey methodologies. All firm leaders were contacted via email, and following the deletion of undeliverable addresses and unsubscribe requests, a total of 3,926 unique firms were included in the survey. In all, 322 responses were received, yielding a response rate of 8.20%. Of the responses received, 151 responses were usable for the analysis. Nearly half of the firms (44.60%) reported to be fewer than ten years old with the average firm having 106.57 employees. Of respondents that reported their position, the majority were top managers or chief executives (90.0%) with others more closely identifying with other positions of leadership (e.g., chairman, founder). Approximately 72% of respondents had at least five years of professional experience in their current firm.

Common Method and Non-Response Biases

Prior to survey administration, proactive measures were included in the survey design to act as procedural controls of common method bias (Podsakoff et al., 2003). Additionally, the questionnaire included a marker variable to further minimize the presence of common method bias (Lindell and Whitney, 2001). Results of Harman's single factor test suggested that common method bias was not likely to confound the interpretation of results.

To examine non-response bias, early and late respondents were compared (Armstrong and Overton, 1977). Specifically, data from the earliest and latest 25 percent of respondents were examined for reported differences in performance, levels of ordinary capabilities, and levels of ACAP. No significant difference was found between respondents for any assessed value.


All measures were assessed using previously validated scales adapted to fit the context of this study. ACAP was measured using a scale developed by Jansen et al. (2005) and included assessments of the acquisition, assimilation, and transformation dimensions. Customer capabilities were measured using a scale adapted from Jayachandran et al. (2004), and alignment capabilities were measured using Liao et al.'s (2007) scale. For operational capabilities, a scale developed by Wu et al. (2010) was used. See Table 1 for an overview of constructs, dimensions, definitions, and sample items.

Because the sampled firms are primarily privately held entities, relative measures of performance were used (e.g., Garcia-Morales et al., 2014). This approach minimizes the hesitation of managers and reduces the likelihood of inaccurate data. Managers were asked to rate the net profit (as a percentage of sales) and the overall performance of the firm compared to other firms in the industry. As with other items in the questionnaire, responses to these items were provided on a Likert scale ranging from 1 (strongly disagree/worse than other firms) to 5 (strongly agree/much better than other firms).

Control Variables

To minimize the variance experienced by external factors, control variables were included. First, the size of a firm relates to how the firm utilizes knowledge and engages in innovation. Specifically, smaller firms are generally more innovative than larger firms (Nootebloom et al., 2007). Hence, firm size was measured as the number of employees in the firm for the most recent year end.

Second, research suggests that established firms--firms with more time to develop and refine capabilities--have an advantage over younger firms that are in the process of developing and refining capabilities related to knowledge processing and innovation (Nootebloom et al., 2007). Therefore, a control variable was included to account for the firm's age. Third, a measure of industry change was included to account for the variation of perceived environmental dynamism across firms (Li and Liu, 2014). Even though all firms sampled are from the software industry, firms may perceive the dynamism within the industry differently, and thus respond in accordance with their perception. To control for industry dynamism, respondents were asked to report the extent to which they perceived the technology in the industry was changing.


Measurement Models

Analyses were conducted using AMOS Version 21 and SPSS Version 22. Table 2 presents the means, standard deviations, intercorrelations, and coefficient alpha reliabilities for the study. A confirmatory analysis was conducted first to examine the higher-order constructs associated with Hypothesis 1. Namely, customer capability, alignment capability, and operational capability were modeled using a single latent factor of ordinary capability, and the latent factors of ACAP, ordinary capability, and performance were allowed to correlate. The higher-order model indicated proper fit (x2 [38, n = 151] = 59.98, p < 0.05; CFI = 0.96; RMSEA = 0.06; SRMR = 0.05), and all factor estimates were significant and greater than 0.50, with the exception of the acquisition factor, which was significant but loaded slightly below the recommended level (standardized estimate = 0.47).

A second measurement model was examined to assess the model fit for subsequent hypotheses (H2-H4). The second model included the latent variables of ACAP, customer capability, alignment capability, operational capability, and performance. The analysis indicated that this five-factor model fit the data well ([chi square] [34, n = 151] = 57.98, p < 0.01 ; CFI = 0.96; RMSEA = 0.07; SRMR = 0.04). Similar to the previous model, all items significantly loaded onto their respective factors, with the exception of the acquisition factor (standardized estimate = 0.47). Table 3 details the factor loadings, construct reliabilities, and average variances extracted for each construct.

Structural Models

Hypothesis 1 suggests ordinary capabilities mediate the relationship between absorptive capacity and firm performance. Thus, to examine the paths and structure of the higher-order relationships, a three-factor model, which included ACAP, a latent construct of ordinary capabilities, and performance, was used. To test for mediation, Baron and Kenny's (1986) three conditions for examining mediation were used with Brown's (1997) recommendations for testing mediation in a structural model. First, absorptive capacity was significantly related to the mediator of ordinary capabilities (p < 0.001; [gamma] = 0.91). Second, the mediator of ordinary capabilities was significantly related to firm performance (p < 0.001; [gamma] = 0.71). Last, the previously significant relationship between absorptive capacity and performance was no longer significant (p = 0.72; [gamma] = -0.11) when the additional relationships were added. The final structural mediation model is presented in Figure 1 and has an appropriate fit ([chi square] [99, n = 151] = 128.90, p < 0.05; CFI = 0.96; RMSEA = 0.05; SRMR = 0.05), thereby supporting Hypothesis 1.

Given the mediating role of ordinary capabilities, further analyses were conducted to assess the relationship between ACAP and each type of ordinary capability. To assess these relationships, a five-factor model was examined, which included ACAP, customer capability, alignment capability, operational capability, and firm performance. The fit indices suggest the structural model fit is appropriate ([chi square] [90, n = 151] = 124.54, p < 0.01; CFI = 0.96; RMSEA = 0.05; SRMR = 0.05). Hypothesis 2 states that ACAP positively relates to customer capability, and results suggest this relationship is positive and significant ([gamma] = 0.76; p < 0.001). The relationship between ACAP and alignment capability is positive and significant (y = 0.97; p < 0.001), thereby supporting Hypothesis 3. Last, Hypothesis 4 is supported, which suggests that ACAP positively relates to operational capability ([gamma] = 0.95; p < 0.001).

Furthermore, although not directly hypothesized but assumed in Hypothesis 1, the influence on firm performance was examined. The relationship between operational capability and firm performance is found to be partially significant ([beta] = 0.58; p < 0.06) while the alignment capability ([beta] = -0.02; p > 0.05) and customer capability ([beta] = 0.19; p > 0.05) do not significantly relate to firm performance. Thus, operational capability is the sole ordinary capability with a partially significant direct relationship to firm performance, which offers additional insight into the relationships between ordinary capabilities and performance. Figure 2 graphically displays these relationships.




Results of the study suggest that ACAP and ordinary capabilities are related, and more specifically, ordinary capabilities mediate the ACAP--performance relationship. These findings help to extend knowledge of firm capabilities, and the results offer evidence to support the transductive role of ordinary capabilities. Additionally, ACAP was found to positively relate to each type of ordinary capability: customer, alignment, and operational. This exploration of the relationship between two classes of capabilities (i.e., dynamic and operational) advances understanding of how firm capabilities work together to alter firm performance in the software industry.

Research Implications

Scholarly work (e.g., Zahra and George, 2002; Volberda et al., 2010) notes ACAP is positively related to firm outcomes, suggesting that ACAP creates value for the firm; however, the means through which value is created within the firm remains less clear. This study offers insight into the relationship between ACAP and ordinary capabilities, noting that ordinary capabilities are the value-creating capabilities through which knowledge is exploited. The conceptual development and empirical examination herein highlights the relationship between absorptive capacity and each type of ordinary capability and finds that ordinary capabilities mediate the relationship between ACAP and performance.

Second, this research extends the contributions in a parallel stream of organizational capability research by providing empirical support for the existence of a relationship between one type of dynamic capability (i.e., ACAP) and ordinary capabilities (Collis, 1994; Winter, 2000). Further, the findings (a) support a broader call to include the ordinary capabilities construct in research relating dynamic capabilities and firm performance and (b) supports prior research (e.g., Helfat and Peteraf, 2003; Martelo et al., 2013) that suggests dynamic capabilities may not have a direct relationship with firm performance, rather, other classes of firm capabilities may mediate the relationship.

Third, scholars have noted critical shortcomings in organizational capability research. Dosi et al. (2000) note that growth of the capability research stream has experienced developmental challenges with many studies conducted at a high level of abstraction. In addition, Kusunoki et al. (1998) note that prior research employs a construct-level operationalization of ordinary capabilities, and few studies examine ordinary capabilities as a multi-dimensional construct. This investigation represents an attempt to begin a scholarly dialogue that addresses such limitations of capability research. The study deploys a multi-dimensional operationalization of ordinary capabilities and finds a positive relationship between ACAP and each of the three ordinary capability dimensions.

Fourth, a more detailed analysis was conducted to examine relationships between ACAP and each type of ordinary capability. In this finer-grained analysis, only operational capabilities are found to directly relate to firm performance (neither alignment capabilities nor customer capabilities were significantly related to performance). Even though this relationship is partially significant (p < 0.10), the finding points to an interesting future area of research: examining the relationship among the types of ordinary capabilities, and how each relates to varied forms of firm outcomes. Given these and other insights, future studies are necessary to further investigate how ordinary capabilities work together, and with other classes of capabilities, to create value and influence performance.

Managerial Implications

While the findings of this study advance ACAP and capability-related scholarship, implications to advance the practice of management are also noted. For managers of firms in dynamic environments (similar to those of the software industry), investments to enhance the ACAP of the firm are likely to result in enhanced ordinary capabilities. As an example, managers may participate in professional organizations to obtain the latest information on industry trends and forecasted changes, have active bi-directional relationships with customers, and engage with stakeholders to enhance knowledge acquisition. Kindstrom et al. (2013) note that, given their unique access, front-line personnel should have appropriate training to recognize potentially valuable knowledge and opportunities when interacting directly with the customer. Further, once a firm obtains knowledge, the firm must come to understand the new knowledge (e.g., use cross-functional groups to filter and/or generate ideas) and subsequently store newly acquired knowledge (e.g., codification via repositories, such as knowledge databases and/or process manuals, or in tacit form via human capital networks).

For managers, recognizing the capabilities associated with obtaining new knowledge (e.g., absorptive capacity) and exploiting the value from the knowledge (e.g., ordinary capabilities) provides a framework for diagnosing and refining sources of competitive advantage. For example, Pugh and Dixon (2008) illustrate how Intel Service Solutions--the consulting division of Intel--used a knowledge harvest program wherein knowledge was systematically acquired, circulated to the various departments and units, and applied to create and promote future products and services. Using a similar harvest approach, managers may systematically identify areas where new knowledge is needed, acquire the new knowledge, and ensure the knowledge is shared with the appropriate functional units so the full value of the knowledge can be leveraged. A strategic approach, wherein knowledge is systematically leveraged, is likely to yield performance returns.

Limitations and Future Research

Although this study offers an enhanced understanding of how ACAP creates firm value, the investigation has limitations. First, the study consists of firms in the software industry. The software industry is highly dynamic and a context commonly used for the study of knowledge transfer and firm capabilities. While significant relationships are found between absorptive capacity and ordinary capabilities, future studies are encouraged to determine if the noted relationships manifest similarly beyond the software industry in, for example, industries that are less dynamic and more mature.

Second, this study is restricted by a limited variable bias, given that another class of capabilities (e.g., strategic capabilities) has been theoretically linked to those investigated in this study. The scope of this investigation was limited to two classes of capabilities--namely, dynamic capabilities (ACAP) and ordinary capabilities--owing to the prior claims that dynamic and ordinary capabilities are the primary classes of firm capabilities (Teece, 2014). Given Ortega's (2010) suggestion of the possibility of combinatorial influences among the three classes of firm capabilities, future efforts to operationalize the "metaphysical strategic insights" (Collis, 1994) of strategic capabilities will help extend this stream of research.

Third, the acquisition component of ACAP demonstrated a slightly lower-than-expected factor loading when evaluating the measurement models. While this was not uncommon given the sample size and model complexity, researchers are encouraged to examine the measurement approaches for assessing ACAP. This study utilized a measure derived from Jansen et al. (2005), yet other measurement scales exist (e.g., see the scale by Flatten et al., 2011). Future studies are encouraged to continue refining the measurement of ACAP and also consider including a more comprehensive operationalization of the exploitation component.

Finally, the research design presents inherent limitations. The data were collected at a single point in time; thus, claims that dynamic capabilities are causally related to ordinary capabilities or performance should be made cautiously. Findings from the study by Lisboa et al. (2011) suggest that an extension of the current hypothesized model may have an influence on current and future firm performance given their finding that exploitative capabilities relate to current performance while explorative capabilities influence future performance. Future longitudinal studies have the opportunity to explicate the recursive relationship between the various types of capabilities and performance. Lin and Wu (2014) find that dynamic learning capabilities (e.g., ACAP) mediate the relationship between valuable firm resources and performance. Hence, assessing capabilities using data from multiple time periods will provide an improved understanding of causal interrelatedness among these constructs and will shed light onto the knowledge processes internal to the firm.


Capability-related questions are central to, and among the most complex, in strategic management research (Helfat and Peteraf, 2009). Although capability-specific research has existed for some time, much remains to be understood about how capabilities of various classes work together. To this end, an attempt is made to understand how ACAP, a dynamic capability, exploits new knowledge and creates firm value. Empirical results demonstrate that ordinary capabilities act as transducers that convert new knowledge into value-creating options for the firm, thereby influencing firm performance. Introducing ordinary capabilities into the research conversation on ACAP offers an improved understanding of how the ACAP of a firm leverages new knowledge while offering insights on how firms renew or re-configure their value-creating processes.

Joshua J. Daspit

Assistant Professor of Management

Mississippi State University

Derrick E. D'Souza

Professor of Management

University of North Texas


Lisa A. Dicke

Professor, Department of Public Administration

University of North Texas


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(1) Acknowledgements: The authors wish to thank Divesh Ojha, Michael Breazeale, and Robert Moore for their insightful comments and suggestions on earlier versions of this manuscript. Additionally, Xueni (Judy) Dong is appreciated for research assistance. Editor Eric Harris and Assistant Editor Irene Robinson are thanked for their support during the review process, and the feedback received from two anonymous reviewers is also appreciated. Portions of this research were funded by the Department of Management at the University of North Texas College of Business.

(2) "Transducer" is a commonly used term in the scientific literature. It is derived from "transduction," which represents the process of converting one form of energy to another. Thus, in genetics, a virus can be viewed as the transducer that transfers DNA from one bacterium to another. In electro-mechanical systems, a motor represents a transducer that converts electrical energy from a source into mechanical energy (torque) at the point of use. It is important to note that in both cases transduction does not require physical contact between the source and the user. In the case of the current study, ordinary capabilities act as the transducer that converts the new knowledge into customer value that is ultimately reflected in the Firm's performance.

(3) To conduct the review of ordinary capabilities, a literature search was conducted to identify published capability frameworks from journals including: Academy of Management Journal; Academy of Management Perspectives; Academy of Management Review; Administrative Science Quarterly; Entrepreneurship, Theory & Practice; Family Business Review; International Journal of Management Reviews; Journal of Business Venturing; Journal of Engineering and Technology Management; Journal of Management; Journal of Management Studies; Long Range Planning; Research Policy; Strategic Entrepreneurship Journal; Strategic Management Journal; and Technovation.
Table 1 Constructs, Definitions, and Sample Items

Construct (with
definition)                Dimension (with definition and reliability)

Absorptive Capacity        Acquisition: The firm's capability to
A dynamic capability       identify and acquire external knowledge
that enables the firm to   (Zahra and George, 2002) ([alpha] = 0.77)
acquire, assimilate,
transform, and exploit     Assimilation; The firm's capability to
new knowledge for          analyze, process. interpret, and understand
commercial purposes        external knowledge (Zahra and George, 2002)
(Cohen and Levinthal,      ([alpha] = 0.81)
1990; Zahra and George,
2002)                      Transformation; The firm's capability to
                           combine existing knowledge with newly
                           acquired and assimilated knowledge (Zahra
                           and George, 2002) ([alpha] = 0.72)

Ordinary Capability        Customer Capability: The firm's capability
Lower-order capabilities   to satisfy customer needs through effective
that enable the            and quick responses (Jayachandran et al,
performance of basic       2004) ([alpha] = 0.77)
firm functions necessary
to accomplish core firm    Alignment Capability: The firm's capability
tasks (Teece, 2014)        to align procedures to achieve product and/
                           or process improvements (Cakar and Erturk,
                           2010; Liao et al, 2007) ([alpha] = 0.83)

                           Operational Capability: The firm's
                           capability to configure operational
                           resources by implementing customized and
                           shared practices (Kaplan and Norton, 2006;
                           Wu et al., 2010) ([alpha] = 0.85)

Construct (with
definition)                Sample Item

Absorptive Capacity        Our firm has frequent interactions with
A dynamic capability       other firms to acquire new knowledge
that enables the firm to   (Jansen et al., 2005)
acquire, assimilate,
transform, and exploit     We are quick to recognize shifts in our
new knowledge for          market (e.g., competition, regulation,
commercial purposes        demography) (Jansen et ai, 2005)
(Cohen and Levinthal,
1990; Zahra and George,
2002)                      Our employees record and store newly
                           acquired knowledge for future reference
                           (Jansen et al., 2005)

Ordinary Capability        When we find that customers would like us
Lower-order capabilities   to modify a product/service, the
that enable the            departments involved make concerted efforts
performance of basic       to do so (Jayachandran et al., 2004)
firm functions necessary
to accomplish core firm    We often try different procedures to speed
tasks (Teece, 2014)        up the realization of the firm's goals
                           (Liao et al., 2007)

                           Our operations process has been modified to
                           gain unique positions in the market (Wu et
                           al., 2010)

Table 2
Descriptive Statistics and Correlation Matrix

Construct           M        SD         1           2           3

1. Absorptive       3.67     0.54    0.84 (a)

2. Operational      3.76     0.61    0.53 **     0.85 (a)

3. Alignment        3.61     0.56    0.60 **     0.59 **     0.83 (a)

4. Customer         4.04     0.49    0.39 **     0.53 **     0.51 **

5. Performance      3.39     0.74    0.42 **     0.48 **     0.43 **

6. Firm age (b)     2.69     1.10   -0.05        0.02       -0.06

7. Number of      106.57   335.01   -0.01       -0.10        0.04

8. Industry         4.28     0.72    0.19 *      0.08        0.13

9. Marker           2.36     0.79   -0.23 **    -0.17 *     -0.15

Construct             4           5        6       7       8

1. Absorptive

2. Operational

3. Alignment

4. Customer        0.77 (a)

5. Performance     0.42 **     0.70 (a)

6. Firm age (b)   -0.09       -0.01

7. Number of       0.01        0.04       0.07

8. Industry        0.14        0.18 *     0.14   -0.04

9. Marker         -0.09       -0.13       0.01   -0.08   -0.02

Note: (a) Cronbach's correlational coefficient; (b) Firm age was
measured using clustered age groups; ** = p < 0.01; * = p <0.05

Table 3
Factor Loadings, Construct Reliabilities, and Average Variances

                     Absorptive    Customer    Alignment
                      Capacity    Capability   Capability

Acquisition             0.47

Assimilation            0.79

Transformation          0.75

Response Speed                       0.85

Response Expertise                   0.69

Product Alignment                                 0.78

Process Alignment                                 0.76



Net Profit


CR (a)                  0.72         0.75         0.75

AVE (a)                 0.47         0.60         0.60

                     Operational   Performance




Response Speed

Response Expertise

Product Alignment

Process Alignment

Cooperation             0.68

Customization           0.80

Net Profit                            0.68

Generalized                           0.79

CR (a)                  0.70          0.70

AVE (a)                 0.55          0.54

Note: (a) Construct reliability (CR); (b) Average variance extracted
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Date:Mar 22, 2016
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