Ordinary Capabilities 1 Capability Configuration in Software Industry ...

Ordinary Capabilities 1 Capability Configuration in Software Industry SMEs: The CAO Model of Ordinary Capabilities* Joshua J. Daspit1 Mississippi State University Derrick E. D’Souza University of North Texas -----------------------------------------------Ordinary capabilities contribute to firm core competencies and are prominent drivers of firm performance. However, our understanding of ordinary capabilities, and how they are leveraged to advance performance in SMEs, remains unclear. We review prior literature and introduce the Customer-Alignment-Operational (CAO) model of ordinary capabilities, which identifies three types of ordinary capabilities: customer, alignment, and operational capabilities. Using data collected from software industry SMEs, we find that CAO capabilities are configured in previously undiscovered ways to enhance firm performance. The findings advance our understanding of ordinary capability types and offer insight into how ordinary capabilities are configured to generate firm value. -----------------------------------------------* The authors wish to thank Jim Chrisman for his feedback and contribution to the study. Divesh Ojha, Nolan Gaffney, William Carter, and Lisa Dicke are acknowledged for their insightful comments and suggestions on earlier versions of this manuscript. We are also grateful to Daniel T. Holt and Staci M. Zavattaro for conversations that improved the quality of the study. Additionally, Xueni (Judy) Dong is appreciated for research assistance. Portions of this research were funded by the Department of Management at the University of North Texas. 1

Address correspondence to: Joshua J. Daspit, Department of Management and Information Systems, Mississippi State University, P. O. Box 9581, Mississippi State, MS 39762. Tel: 662-325-2769. Email: [email protected].

Publication forthcoming in Journal of Small Business Management

Ordinary Capabilities 2 Capability Configuration in Software Industry SMEs: The CAO Model of Ordinary Capabilities Abstract Ordinary capabilities contribute to firm core competencies and are prominent drivers of firm performance. However, our understanding of ordinary capabilities, and how they are leveraged to advance performance in SMEs, remains unclear. We review prior literature and introduce the Customer-Alignment-Operational (CAO) model of ordinary capabilities, which identifies three types of ordinary capabilities: customer, alignment, and operational capabilities. Using data collected from software industry SMEs, we find that CAO capabilities are configured in previously undiscovered ways to enhance firm performance. The findings advance our understanding of ordinary capability types and offer insight into how ordinary capabilities are configured to generate firm value. Keywords: Ordinary capabilities; configuration; software industry; SMEs Introduction Small and medium-sized enterprises (SMEs) typically experience limited economies of scale, possess fewer resources, have limited experience (Notebloom 1994), and are often portrayed as competitively disadvantaged when compared to larger firms. SMEs, however, are better able to commercialize emergent technologies, thereby demonstrating that smaller firms are able to develop idiosyncratic core competencies and obtain competitive advantage (Bower and Christensen 1995; Walsh, Kirchhoff, and Newbert 2002). Core competencies result from the creative integration of firm capability and competency bundles1 to deliver inimitable strategic value (Hafeez, Zhang, and Malak 2002; Marino 1996; Prahalad and Hamel 1990; Walsh, Boylan, McDermott, & Paulson 2005). Despite the fundamental role in supporting the development of core competencies, what we know about the types of firm capabilities and how they interdependently create value has remained limited.

According to Marcus and Anderson (2006: 22), “Capabilities represent the system’s separate components, while competencies represent its realized wholes. Capabilities suggest potential, while competencies connote achieved proficiencies.” Further, capabilities are rooted in firm processes and routines, while competencies tend to be centered on technical expertise (Marino, 1996; Walsh et al., 2005). 1

Ordinary Capabilities 3 Prahalad (1993: 45) describes capabilities as the primary firm functions that are “prerequisites to being a business” and are “crucial for [firm] survival.” Capabilities, developed from deeply embedded firm routines (Pandza, Polajnar, Buchmeister, and Thorpe 2003), enable value creation by transforming inputs into outputs (Wu, Melnyk, and Swink 2012). Interestingly, though, not all value created by the firm occurs through a single type of organizational capability. Researchers generally agree that three categories of capabilities exist to create value within the firm: ordinary capabilities, dynamic capabilities, and strategic (higher-order) capabilities (Collis 1994; Winter 2003). In this conceptualization, ordinary capabilities represent the most fundamental of the three capabilities, and evidence exists that ordinary capabilities are closely related to firm performance (Schreyögg and Kliesch-Eberl 2007; Zahra, Sapienza, and Davidsson, 2006). This study focuses on the ordinary capabilities of the firm. Management scholars suggest that ordinary capabilities are composed of several different types of capabilities (Ulrich and Lake 1990; Hall 1992, 1993; Day 1994), yet uncertainty exists regarding the types of ordinary capabilities and how they work together to create value for the firm (Helfat and Peteraf 2003; Wang and Ahmed 2007). For example, how many types of ordinary capabilities exist within the firm? Furthermore, if multiple ordinary capabilities exist, how do these capabilities work together to create firm value? To this end, our study seeks to (a) identify the types of ordinary capabilities and (b) examine how the types of ordinary capabilities are complementarily configured to drive performance in SMEs. In doing so, we offer a more detailed understanding of how these capabilities are leveraged by SMEs, and we further a research agenda that extends our understanding of how ordinary capabilities work together to influence SME performance. This study makes several contributions to capability scholarship. First, while the majority of capability research is conducted largely at a theoretical level, and given the call for more

Ordinary Capabilities 4 empirical work that advances capability research (Giudici and Reinmoeller 2012), we conduct an empirical investigation of capabilities. Although other empirical studies of capabilities are few, we build on these prior contributions (for example, Newbert, Kirchoff, and Walsh 2007; Walsh et al. 2002, 2005) and offer a theoretically developed, and empirically tested, configuration of ordinary capabilities. Specifically, we add to the growing body of work on ordinary capabilities by introducing a three-component conceptualization of ordinary capabilities that we label the Customer-Alignment-Operational (CAO) model of ordinary capabilities. Second, ordinary capabilities have been found to be a source of competitive heterogeneity for SMEs. However, Jacobides and Winter (2012) suggest that numerous challenges remain regarding capability research, including understanding why capability differences exist between firms, and how capabilities are structured and evolve within the firm. The findings of this study offer empirical insight into the configuration of ordinary capabilities and provide a foundation for future comparison of how capabilities differ within SMEs. Specifically, we find a unique configuration of ordinary capabilities in software industry SMEs, which highlights the need for future research aimed at developing a more nuanced understanding how firm capabilities are configured to support the core competencies of a firm. In what follows, we begin with a review of prior research on ordinary capabilities. We highlight work that has focused on understanding the components of the ordinary capabilities construct. We synthesize prior research and develop a three-component conceptualization of ordinary capabilities. Then, using a sample of SMEs in the software industry, we seek empirical support for the configuration. Further, we hypothesize and empirically examine the relationships among each of the ordinary capabilities. The results suggest that these capabilities are uniquely configured to create value for SMEs in the software industry, and when so configured, are positively related to firm performance.

Ordinary Capabilities 5 Ordinary Capabilities Capability-Based Perspective According to Penrose (1959), the firm is more than an administrative unit; rather, the firm is a collection of productive resources, and when appropriately combined and exploited, these resources provide distinct advantages (Barney 1991; Penrose 1959; Wernerfelt 1984). Resources, which are stocks of inputs available to the firm for conversion into products or services (Amit and Schoemaker 1993), are uniquely combined and leveraged via the firm’s capabilities. Hence, a capability-centric perspective of the firm positions capabilities as the central organizational phenomenon (the “engine” of the firm) from where competitive advantage emanates (Bartmess and Cerny 1993). Viewed through a capability lens, the firm consists of resources configured through organizational processes, associated relationships, and governance structures that support ordinary capabilities, thereby creating value and extracting economic rent (Amit and Shoemaker 1993; Andersen 1997; Madhok 1997). Capabilities develop partly from learning, firm resources, and organizational histories, and capabilities are what the organization has the potential to accomplish rather than what it currently produces (Marcus and Anderson 2006; Teece 2014). Thus, we employ a capability-based perspective to understand how SMEs leverage ordinary capabilities and influence performance. Determining the Types of Ordinary Capabilities: A Review of the Literature We adopt Winter’s (2000: 983) broad definition of an organizational capability as, “…a high-level routine (or collection of routines) that, together with its implementing input flows, confers upon an organization’s management a set of decision options for producing significant outputs of a particular type.” Within the universe of firm capabilities, ordinary capabilities are defined as capabilities that enable the performance of basic firm functions needed to carry out

Ordinary Capabilities 6 planned tasks (Teece 2014). Ordinary capabilities represent the “how we earn a living now” capabilities of a firm (Winter 2003: 992); that is, ordinary capabilities are embodied in the value creating engine of the firm. Despite the vast literature on firm capabilities, few studies offer specific, multi-dimensional conceptualizations of ordinary capabilities, and of those that do, the conceptualizations often are inconsistently modeled. Further, various synonyms and descriptions are used to identify types of ordinary capabilities in the literature. Therefore, to ensure a comprehensive acknowledgement of capabilities, an examination of the literature was conducted to identify contributions that addressed the ordinary capabilities of the firm. We began the literature review with an assessment of ordinary capability frameworks found in high-quality journals, since such outlets arguably have the greatest impact on academic research (Judge, Cable, Colbert, and Rynes 2007). To ensure the list included journals from relevant subject areas within business, the 2015 Academic Journal Guide from the Association of Business Schools was used given its categorization of journals across 22 business-related subject areas. Using this guide, journals from the following subject areas were reviewed given their relevance to the topic: entrepreneurship and small business; general management; innovation, and strategy. Each area was examined, and all relevant journals with an impact factor of 2.0 or greater from each subject area were included in the literature review search. To assess the journal impact factor, the 2014 ISI Web of Knowledge Journal Citation Report® published by Thomson Reuters was referenced. The final list of journals searched included (by subject area): Entrepreneurship, Theory & Practice, Journal of Business Venturing, Strategic Entrepreneurship Journal, Family Business Review (entrepreneurship and small business); Research Policy, Technovation, Journal of Engineering and Technology Management (innovation); Academy of Management Journal, Academy of Management Review, Administrative Science Quarterly, Journal of Management,

Ordinary Capabilities 7 Journal of Management Studies, Academy of Management Perspectives, International Journal of Management Reviews (general management); Strategic Management Journal, and Long Range Planning (strategy). Given the broad scope of terms used to describe ordinary capabilities, we conducted a search in the Business Source Complete (EBSCO) database (journal websites were used when necessary) using the most commonly used synonyms2 found in the literature. The searches were not date restricted, and a total of 1,512 articles were identified. Each article was reviewed by the research team for its relevance in offering a unique framework of ordinary capabilities, and 16 articles were found to contain relevant frameworks that specified dimensions of ordinary capabilities. To ensure the list was representative of the developments in the literature, the authors also identified other works (from journals or books) that were cited in the literature and relevant to the study, including contributions from Journal of Small Business Management. An additional 15 contributions were discovered, yielding a total of 31 relevant conceptualizations ordinary capability components examined. CAO Model of Ordinary Capabilities Characterizations of ordinary capabilities were compared across the identified studies to examine commonalities and differences. Table 1 provides a summary of our review and synthesis. Based on the review, it was found that the conceptualizations generally referred to three broad categories of ordinary capabilities: customer capability, alignment capability, and operational capability. Given the three identified types, we refer to this model as the Customer-AlignmentOperational (CAO) Model of Ordinary Capabilities. The emergence and characterization of each ordinary capability is discussed below.

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Terms applied in the search string include: core capability, organizational capability, firm capability, ordinary capability, zero-order capability, core competency, organizational competency, firm competency, ordinary competency, zero-order competency, capability, and capabilities.

Ordinary Capabilities 8 -----------------------------------------Insert Table 1 about here -----------------------------------------Customer capability. Researchers agree that the ability to understand the market, and to address customer3 demands in ways that result in a strong and lasting relationship, holds value creation potential for the firm. These capabilities have been referred to as client-management capabilities (Ethiraj et al. 2005) or customer support capabilities (Grant 1996) that are intended, according to Treacy and Wiersema (1993), to build “intimacy” with the firm’s customers. Others have viewed the outcome of exercising this capability as the development of strong relationships with customers (Hall 1992, 1993; Zhao, Song, and Storm 2013) that, in turn, enhance the quality of information acquired from the customer (Lenz, 1980). Across studies, it was noted that authors consistently stressed the importance of understanding customer needs (Kaplan and Norton 1996; Meyer and Utterback 1993), managing customer relationships (Coyne 1986; Grant 1996; Tyler 2001), and hence, the importance of maintaining a high level of customer response expertise (Amit and Shoemaker 1993). Researchers also generally identified customer response speed as a component of customer capability (that is, the speed at which the firm responds to external changes) (Crossan, Rouse, Fry, and Killing 2009; Danneels 2002; Lerner and Almor 2002; Ulrich and Smallwood 2004). The ability to respond quickly, and with precision, is one way in which the firm is able to unlock value. We label this customer-centric ordinary capability as the customer capability of the firm. Alignment capability. The second ordinary capability identified in our review relates to the capability of the firm to create value through alignment. The alignment capability is defined as the

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The term “customer” is used herein to represent any significant stakeholder of the firm.

Ordinary Capabilities 9 firm’s ability to mobilize and combine knowledge (Lenz 1980) for the purpose of continuously making product and/or process improvements (Ҫakar and Ertürk 2010) that aid in the alignment of the firm’s value creating engine with market needs. The nature of the environment drives the firm to constantly adjust its strategic posture and requires a capability to develop a knowledge base and engage in knowledge management practices (Kaplan and Norton 1996). Capability researchers have referenced this type of capability using numerous terms including a learning capability (Kaplan and Norton 1996; Lado and Wilson 1994), R&D capability (Chen 2012), spanning capability (Day 1994), or integrative capability (Wang, Lo, and Yang 2004) to name a few. Recognizing that ordinary capabilities are responsible for such continuous change, we suggest that the “learning” or “adaptation” capability, referred to by these researchers, is more accurately represented as the firm’s ability to use knowledge for the purpose of making process/product changes such that the firm is optimally aligned with market demands. Amit and Shoemaker (1993) suggest this is the ability to repeatedly make product and process innovations. We suggest that these incremental changes are a manifestation of an underlying alignment capability of the firm. The alignment capability referred to herein seldom results in radical outcomes that are entirely unpredictable. Indeed, the alterations typically follow an evolutionary path of logical incrementalism as suggested by Duncan (1972). This does not entirely exclude unpredictable or revolutionary innovations from occurring as such innovations are possible; however, the alignment capability allows the firm to consistently offer customers desired products and/or services (Treacy and Wiersema 1993). Such alignment capabilities enable the firm to facilitate a progressive, but largely path-dependent, evolutionary trajectory. Day (1994) describes this type of capability as essential in integrating external and internal elements. In other words, the alignment capability is noted as a distinct type of ordinary capability given its role in producing continuous incremental

Ordinary Capabilities 10 changes to the value creation process of the firm so as to facilitate alignment between the firm and the demands of the market. Operational capability. Last, it was generally noted that a third type of ordinary capability was consistently referenced in the capability frameworks examined. This third type of capability was noted by Day (1994) as an “inside-out” capability that manifests in the firm’s ability to produce a product and/or service (Acar 1993; McGee and Peterson 2000) and in efficiencies that accrue from cross-functional synergies (Crossan et al. 2009; Yam, Lo, Tang, and Lau 2011). Kay (1996) expands on this notion by referring to cross-unit synergies as resulting from an architecture of implicit (and sometimes explicit) relationships between units of a firm. Further, the implementation of internal business processes, as noted by Kaplan and Norton (1996), and the knowledge, skills, and expertise of the firm’s employees at the functional level (Davies and Brady 2000; Hall 1992, 1993), are central to operational capabilities. We expand on Wu, Melnyk, and Flynn’s (2010) definition that the operational capability utilizes internal resources to generate functional outcomes consistent with desired results. In other words, the operational capability is the means through which knowledge is exploited into a usable (and in some cases tangible) form. Given that this capability is characterized by operational-level routines and activities that manifest within the various functional areas of the firm, we label it the operational capability of the firm. Hypotheses Relationships among Ordinary Capabilities We next seek to explore how the CAO capabilities are configured to create value for the firm. At the broadest level, the relationship between ordinary capabilities and performance is well established (Wu et al. 2012). For example, Zahra et al. (2006) suggest a relationship exists between ordinary capabilities and performance, and Schreyögg and Kliesch-Eberl (2007) state that “[ordinary] capabilities are bound to performance” (p. 915), emphasizing the relationship between

Ordinary Capabilities 11 ordinary capabilities and firm success. Even going back to the early work of Penrose (1959) and others, a broad relationship between firm capabilities and performance is noted. Although a general relationship between ordinary capabilities and firm performance exists; however, it is not clear how the three noted ordinary capabilities work together to achieve desired performance. In other words, how are ordinary capabilities configured within firms to create value? Given the insights from previous literature, we accept the existence of the relationship at the construct level and investigate nuanced relationships among the capability types and firm performance within SMEs. To address this issue, we employ a process perspective and build on the tenets of complementarity theory, which suggests that organizational activities can be designed to complement one another synergistically (Milgrom and Roberts 1995). Complementarity theory has been used to describe the cumulative benefit received from the integration of multiple ordinary capabilities. For example, Cassiman and Veugelers (2006) note that capabilities can offer superadditive (or synergistic) value. Other research on the complementarity of capabilities (Grewal and Slotegraff 2007), co-specialization (Teece 1988), and interconnected assets (Dierickx and Cool 1989) further supports this argument. Implied in these claims is the notion that firm success is not only a function of the unique characteristics of each ordinary capability, as argued in prior research, but is largely a function of the alignment among the ordinary capabilities. Accordingly, we suggest that ordinary capabilities are purposefully aligned to maximize firm value creation, and we next hypothesize the relationships among the CAO capabilities and note the configurational relationship with firm performance. Customer capability and alignment capability. When customer preferences change, the firm with a superior customer capability is more easily able to detect changes in customer needs than the firm with a less refined customer capability. Once the knowledge of a changing customer preference is obtained, the knowledge becomes potentially valuable to the firm. Before the firm is

Ordinary Capabilities 12 able to exploit the new knowledge and deliver an updated product and/or service, however, the firm may need to expand beyond its existing knowledge structures for an appropriate solution. That is, the firm may need to make internal changes prior to exploiting the new opportunity detected via the customer capability. To this end, the firm exercises its alignment capability to deliver the required change (Crossan et al. 2009; Day 1994). The changes made via the alignment capability are those related to product changes and/or process revisions. New customer preferences may dictate, for example, that the firm delivers a product with new attributes, and such changes may require alterations within the firm prior to deployment. The ability to rapidly and accurately isolate and understand changes in customer demand patterns, and to then make appropriate changes to the firm’s value proposition is critical. Thus, we posit that given the changing nature of the environment, refined customer and alignment capabilities are critical to success given that a strongly coupled relationship between the customer capability and alignment capability allows the firm to acquire necessary knowledge and make internal adjustments to meet changing demands. Hypothesis 1: The customer capability is positively related to the alignment capability. Alignment capability and operational capability. The flow and processing of knowledge across the firm in pursuit of functional outcomes, embodied in the implementation of value creating practices, is characterized as the operational capability of the firm (Kaplan and Norton 1996; Koufteros, Voderembse, and Doll 2002; Wu et al. 2010). When change to the output of the value creation process is warranted, the firm must leverage its alignment capability to alter the existing value creation process for the purpose of offering an appropriate output that maximizes rents (Liao, Fei, and Chen 2007). Calantone, Cavusgil, and Zhao (2002) studied change activities in a cross-section of firms in manufacturing and service industries and found that a refined alignment-type capability is

Ordinary Capabilities 13 associated with higher levels of firm outcomes. However, we suggest the resulting (product or process) changes alone do not directly influence firm outcomes; rather, once the firm alters products and/or processes, the firm then leverages the operational capability to extract value from the recent changes, and for this to occur, the firm’s alignment capability must act in concert with its operational capability. Hence, we support Zawislak, Alves, Tello-Gamarra, Barbieux, and Reichert’s (2012) suggestion that change in the firm’s operational capability is closely associated with the firm’s alignment capability, given that new knowledge leveraged by the alignment capability is then internally exploited via the operational capability to create functional outcomes. Hypothesis 2: The alignment capability is positively related to the operational capability. Mediating role of the alignment capability. Given the aforementioned relationships, we suggest the alignment capability maintains an integral role in enabling the firm to remain in sync with customer demands. Through a refined customer capability, the firm sustains close relationships with external stakeholders, and via such relationships, new knowledge regarding changes in customer preferences is obtained. Once the new knowledge is obtained by the firm, the knowledge is not directly implemented via firm operations; rather, the knowledge is first used to realign the firm by changing current products and/or processes. Finally, once changes are instituted, the firm is then able to extract value from the knowledge via the firm’s operational capability. The changes made to firm products and/or processes are leveraged via the alignment capability and functional outcomes are pursued by the operational capability. The alignment capability exists to ensure the firm remains in sync with changing customer preferences. In the absence of the alignment capability, changes in demand patterns may be recognized by the firm, yet the firm may not be able to extract the full value of the knowledge given its inability to support internal change and leverage the operational capability. Thus, in most instances, change in demand patterns triggers the search for and implementation of organizational

Ordinary Capabilities 14 realignment, and the subsequent leveraging of recently aligned operational capabilities deliver a new variant of customer value. Given the central role of the alignment capability in this transformation process, and the implied sequential linkage among the three ordinary capabilities, we posit that the relationship between the customer capability and operational capability is mediated by the alignment capability. Hypothesis 3: The alignment capability mediates the relationship between the customer capability and the operational capability. Relationship with firm performance. Noting the role of ordinary capabilities within the firm, prior studies confirm that ordinary capabilities have positive effects on firm performance (for example, Drnevich and Kriauciunas 2011). The firm is better able to survive, grow, and earn a profit when ordinary capabilities are abundant (Wang and Ang, 2004). Extending this understanding, we suggest that while ordinary capabilities collectively influence performance, a closer examination at the configuration of ordinary capabilities highlights how ordinary capabilities work together to drive firm performance. Specifically, the customer capability allows the firm to obtain new knowledge from outside the boundary of the firm, and the alignment capability enables the firm to create process or product/service revisions relevant in the context of the new knowledge acquired. However, in the absence of an operational capability, having knowledge from customers or having an altered process does not directly capture rents. Hence, while the customer capability and the alignment capability are integral to the firm’s ability to leverage value from input, the operational capability allows the firm to capture value; thus, the operational capability is directly associated with performance. We, therefore, extend prior work that acknowledges a broad relationship between ordinary capabilities and performance by suggesting that ordinary capabilities work together in a unique configuration to affect firm performance. More precisely, we suggest that the operational

Ordinary Capabilities 15 capability is the capability through which value from the customer capability and alignment capability is realized. In other words, it is via the operational capability that value is created, and the resulting value creation influences firm performance. Hypothesis 4: The operational capability is positively related to performance. Method Data Collection and Sample Data were collected using a key informant approach (Kumar, Stern, and Anderson 1993) beginning with a two-phased pilot study. In the first phase of the pilot study, the items and constructs were reviewed by a panel of experts. Each reviewer was asked to examine the items and confirm the questions were appropriate for both product and service-oriented firms. In the second phase, the instrument was tested using a sample of senior executives. Data collected from the executives were evaluated and minor refinements were incorporated in the instrument where needed. Following the pilot study, electronic surveys were administered to senior-level managers at firms in the software industry. The data collection procedure was based on Dillman’s (1978, 2007) total design method, which recommends making four contacts with survey participants through: (1) a brief pre-notice letter, (2) a questionnaire mailing, (3) a thank you note, and (4) a replacement questionnaire. Dillman also suggests an additional special contact be made with participants following the final contact to improve response rate. Thus, each executive was sent email messages in line with this technique, and two special contact notices were incorporated into the data collection procedure. The initial sample included 5,085 unique firms. After deleting undeliverable addresses and unsubscribe requests from firms, a total of 3,926 unique firms were included in the survey. In total, 322 responses were returned yielding a response rate of 8.20 percent. Responses with more than

Ordinary Capabilities 16 50 percent of data missing were deleted. Remaining missing data were examined and determined to be missing completely at random (MCAR); thus, estimated mean imputation was used to replace missing values when appropriate. Only firms with fewer than 500 employees were included in this study, which is in line with the Small Business Administration’s definition of SMEs and in line with previous studies (for example, Lu and Beamish 2001). Any firm not reporting the number of employees was also removed from the analysis, leaving a total of 97 responses from SMEs in the software industry. Similar sample sizes are found in industry-restricted, survey-based studies (for example, Gillis, McEwan, Crook, and Michael 2011). Nearly half of the firms surveyed (48.50 percent) reported to be fewer than 10 years old. Additionally, 24.70 percent of the firms had fewer than 10 employees and 49.50 percent of the firms had fewer than 20 employees. Further, 93.80 percent of the respondents reported to be the top manager of the firm, and 57.70 percent of the respondents reported to have been with the current firm for fewer than 10 years. Non-response Bias A test of non-response bias was conducted using a comparison of demographic and financial data. The number of employees was used as a measure of the size of the firm, and net profits was used to measure revenue. A t-test revealed no significant difference for number of employees or for net revenue, suggesting no significant differences among respondents and nonrespondents (Armstrong and Overton 1977). Common Method Variance To minimize the potential effects of common method variance, Podsakoff, MacKenzie, Lee, and Podsakoff (2003) recommend including procedural controls in the questionnaire design. Hence, prior to administering the survey, procedural controls were instituted to minimize the likelihood of common method variance. Furthermore, following data collection, statistical

Ordinary Capabilities 17 remedies were used to assess the presence of common method variance. First, Harman’s singlefactor test was conducted and results indicated no single factor accounted for a majority of the variance (largest factor accounted for 32.23 percent of the variance). Additionally, a marker variable (that is, a variable that is unrelated to the examined phenomena) was included in the structural model to address unaccounted variance resulting from bias (Lindell and Whitney 2001). The measure consisted of an item adapted from a scale used by Menguc and Auh (2010) to assess personal affect. Independent Variables Customer capability. Customer capability was measured using a scale adapted from a previously validated instrument created by Jayachandran, Hewen, and Kaufman (2004). The operationalization of customer capability in this study includes two dimensions: customer response speed and customer response expertise. Together the dimensions reflect the underlying characteristics of customer capability (that is, the capability to respond to changing customer needs quickly and appropriately). A total of five items measured customer capability. Alignment capability. Alignment capability was measured using a previously validated scale adapted from Liao et al. (2007). This scale contains two dimensions appropriate for the current study: product alignment and process alignment. A total of nine adapted items measured alignment capability. Operational capability. Operational capability was measured by using two dimensions of a scale developed by Wu et al. (2010): operational responsiveness and operational customization. A total of six items were adapted and used to measure operational capability. A list of items is available in the Appendix.

Ordinary Capabilities 18 Dependent Variable Performance. Performance was measured using a reported value of net profit (Zott 2003). Given the majority of firms in the study are privately held, data was collected directly from firm respondents, and a relative measure was requested given the reluctance of managers to disclose detailed performance data. Respondents were asked how the firm compares to others in the industry in terms of net profit. Control Variables The size of the firm may have an influence on the development of capabilities since larger firms have greater stocks of resources and could have more refined capabilities (Gulati 1999). Hence, we controlled for firm size in the study by measuring the number of employees. In addition, we controlled for the age of the firm given the temporal effect on development, granting younger firms a disadvantage to older firms (for example, Zaheer and Bell 2005). Additionally, age is believed to be to influence the success of SMEs (Mohan-Neil 1995; Withers, Drnevich, and Marino 2011). Firm age was assessed using a range of measures from 1 (less than 5 years) to 7 (greater than 50 years). Furthermore, SMEs are likely to experience variable rates of growth depending on the life cycle, and SME growth is shown to effect operating expenses, turnover, and financial ratios (McMahon 2001). Thus, a measure of sales growth was used to control for growth variation and was measured as the firm’s sales growth relative to competitors. Results Structural modeling was determined to be an appropriate methodological technique given the ability to simultaneously estimate multiple associations, incorporate latent and observed constructs, and account for random measurement error of latent constructs (Medsker, Williams, and Holahan 1994). A two-step procedure was used to analyze the data, which included an assessment of the measurement model followed by an assessment of the path relationships using

Ordinary Capabilities 19 structural equation modeling techniques (Anderson and Gerbing 1988). The results from both steps are reported below following suggestions from Shook, Ketchen, Hult, and Kacmar (2004). The means, standard deviations, and correlations are presented in Table 2. -----------------------------------------Insert Table 2 Here -----------------------------------------Measurement Model An assessment of the measurement model was first performed to ensure that latent constructs were properly specified (Hair, Black, Babin, Anderson, and Tatham 2006). To assess specification, the latent constructs and respective measures were analyzed and model fit examined. The modification indices and expected parameter change values were evaluated. Measurement items not significantly loading on the intended factor (p < 0.05) and with a factor loading above 0.50 were eliminated (Byrne 2010). The remaining items all loaded significantly on the intended constructs and yielded factor loadings ranging from 0.55 to 0.98. The constructs were subsequently evaluated for internal reliability using Cronbach’s alpha, and all measures were above Nunnally’s (1978) recommended level of 0.70: customer capability (α = 0.80), alignment capability (α = 0.82), and operational capability (α = 0.85). A confirmatory analysis was then conducted wherein the latent variables were allowed to correlate with one another. Three latent constructs were specified, which represented the types of ordinary capabilities noted in the study. The results of the measurement model indicate that a threefactor latent model provided an appropriate fit of the data (χ2 [161, n = 97] = 219.96, p < 0.01; CFI = 0.92; RMSEA = 0.06; SRMR = 0.07). To examine whether the constructs measured were statistically different, the covariances among constructs were fixed to 1.00, and the fit indices for the fixed (constrained) model were

Ordinary Capabilities 20 observed. Subsequently, the covariances among the constructs were freely estimated, and the fit indices of the free model were recorded. The details of the fit indices for both models are presented in Table 3. A χ2 difference test was then performed to determine whether a significant difference existed between the free and constrained model. The χ2 difference test resulted in a significance value of p < 0.001, thus indicating that the constrained model was not a better fit. Because the free model was accepted, the presence of discriminant validity was verified due to the observed differences, which suggests the items discriminantly load on the intended factor. -----------------------------------------Insert Table 3 Here -----------------------------------------Structural Model Following the confirmatory analyses, the overall fit indices of the hypothesized model were analyzed, and the measures indicated proper fit (χ2 [250, n = 97] = 310.07, p < 0.01; CFI = 0.92; RMSEA = 0.05; SRMR = 0.07). Given proper fit, the hypotheses were then examined. Hypothesis 1 was supported (p < 0.001; γ = 0.56), which suggests the customer capability has a positive and significant relationship with the alignment capability. The relationship between the alignment capability and the operational capability was confirmed (p < 0.001; γ = 0.82), thereby supporting Hypothesis 2. Additionally, Hypothesis 4 was supported (p < 0.05; β = 0.26), which suggests the operational capability is significantly and positively related to firm performance. To test the mediating relationship in Hypothesis 3, a structural model consisting of the three latent capability constructs was examined (control and marker variables included) and was properly specified (χ2 [231, n = 97] = 296.47, p < 0.01; CFI = 0.91; RMSEA = 0.05; SRMR = 0.07). Baron and Kenny’s (1986) three conditions for testing mediation were followed using Brown’s (1997) recommendations for examining mediation within a structural model. First, the

Ordinary Capabilities 21 exogenous variable of customer capability was significantly related to the mediator of alignment capability (p < 0.01; γ = 0.54). Second, the mediator of alignment capability was significantly related to the endogenous variable of operational capability (p < 0.001; γ = 0.80). Third, the previously significant relationship between the exogenous and endogenous variables (customer capability and operational capability, respectively) was no longer significant (p = 0.85; γ = 0.04) when the other relationships were included. Therefore, the results suggest the alignment capability fully mediates the relationship between the customer capability and operational capability, thereby supporting Hypothesis 3. The final structural model, inclusive of the relationship with performance, is presented in Figure 1. -----------------------------------------Insert Figure 1 Here -----------------------------------------Discussion Research on ordinary capabilities has largely been conducted at a high level of abstraction, addressing broad influences on firm-level outcomes (for example, Ambrosini and Bowman 2009; Chen 2012; McEvily and Marcus 2005). Wang and Ahmed (2007) suggest a better understanding of how the firm uses capabilities to achieve competitive advantage is warranted, and to this end, the central research objectives of this study were to (a) identify the types of ordinary capabilities and (b) examine how these types of ordinary capabilities work together to drive performance in SMEs. Using data from a sample of SMEs in the software industry, we offer a three-component conceptualization of ordinary capabilities and empirically examine the configuration among these ordinary capabilities and their relationship to firm performance. Our findings confirm that a three-factor model appropriately represents the ordinary capabilities within the firm. Further, extending previous studies that note the influence of

Ordinary Capabilities 22 capabilities on firm performance (for example, McGee and Peterson 2000, Wang and Ang 2004), our findings offer insight into how the three types of ordinary capabilities work interdependently to create firm value. Research exists that recognizes the critical role of the customer in affecting firm performance (for example, Ethiraj et al. 2005; Kaplan and Norton 1996) and the consequential mandate of the firm to use a customer capability to service such demands. Additionally, ample evidence notes the contribution of firm-level operational capabilities in delivering value (for example, Graves and Thomas 2008; Yu 2001). Our findings are consistent with prior research in confirming the appropriateness of acknowledging these two capabilities while highlighting the integral role of the alignment capability. Extending the work of Drnevich and Kriauciunas (2011), who find that environmental dynamism has a moderating effect on the relationship between ordinary capabilities and relative firm performance, we underscore the importance of the alignment capability within the dynamic software industry. Industry-level effects have notable influences on firm capabilities, and our findings highlight the importance of the alignment capability within this context as it allows the firm to remain in sync with environmental changes. Our findings confirm Teece’s (2014: 331) insight that “When the firm’s output is tuned to what the market desires, strong ordinary capabilities may be sufficient for competitive advantage…”, which highlights the importance of alignment. In all, we find that the CAO capabilities are configured by SMEs in previously undiscovered ways to deliver firm performance. These findings have the potential to advance research on ordinary capabilities and provide valuable insights for researchers and practitioners. Implications for Researchers Although researchers have acknowledged the importance of ordinary capabilities and the critical role of capabilities in supporting the development of firm core competencies (Hafeez et al. 2002; Prahalad and Hamel 1990), the lack of understanding surrounding these capabilities has

Ordinary Capabilities 23 hindered the progress of the field. The CAO model developed in this study reflects an attempt to address this research gap at the foundational level by first articulating a synthesized dimensionality of the ordinary capabilities of SMEs. Our framework offers a parsimonious, yet inclusive, configuration of ordinary capabilities and tests hypothesized relationships among the capabilities and the resulting influence on firm performance. In doing so, we answer the call to extend SMEspecific studies (for example, Wright, Liu, Buck, and Filatotchev 2008) by elucidating a conceptualization of capabilities that focuses on SMEs. In addition, we complement the work of Winter (2003), Collis (1994), Teece, Pisano, and Shuen (1997) and others by addressing their calls for theoretical and empirical extensions of existing capability theory. Ordinary capability configuration in the software industry. The resulting configuration of ordinary capabilities among SMEs in the software industry offers unique insight into how the CAO capabilities are leveraged within this context. One interesting finding of this study is the presence of a mediated relationship that exists among the ordinary capabilities. The empirical support suggests that the alignment capability fully mediates the relationship between the customer and operational capabilities; thus, the alignment capability is integral to ensuring the firm is able to deliver functional outcomes (via the operational capability) by aligning internal processes and products with customer demands (understood via the customer capability). This vital role of the alignment capability is similar to the role of the “linking mechanism” noted by Di Stefano, Peteraf, and Verona (2014). The industry context of this study (that is, software industry) is rapidly changing. Competition and uncertainty are high and the half-life of new products is low. In such a context, the firm is driven to leverage its alignment capability to remain in sync with the rapidly changing environmental demands. Hambrick and Crozier (1986) predict a sub-optimal alignment between customer demand patterns and the firm’s value proposition in high-growth environments. They argue that in such

Ordinary Capabilities 24 environments, rapidly changing organizational offerings or market demand characteristics (or both) make it impractical for the firm to successfully optimize alignment with its markets. Hence, in their view, firms in high-growth contexts choose to be internally focused, and often do not actively seek market alignment. Our finding, in one such high-growth industry, offers empirical evidence to suggest that this may not always be true. We found significant direct relationships among the customer capability, alignment capability, and operational capability, suggesting that firms in the software industry seek and gain adequate alignment to influence firm performance. The role of industry and the search for a typology of ordinary capabilities. Our study also raises several additional theoretical questions. For example, are our findings specific to firms in dynamic industries like the software industry? Should we expect different results if the sample of firms use for this study came from more stable industries? That is, if the industry is stable, would we find a significant relationship between the customer capability and operational capability, but not necessarily between the alignment capability and operations capability, given the expected lower demand for innovation? Economic theory suggests that an industry will stabilize as it matures. This stability is reflected in the narrowing of spread in buyer needs, supplier offerings, and new products/services development. Typically, in such environments, supply tends to exceed demand, price-based valuepropositions are more likely to be used by firms, and the cost of the production/delivery rises in prominence as a determinant of firm performance. Consequently, in stable industries, of the type illustrated above, matching customer needs with operational excellence is paramount. Firms in stable industries improve success by nurturing strong alignment between the customer and operational capabilities, yet the rate of change among the customer and operational capabilities is less.

Ordinary Capabilities 25 We suggest that in stable industries, the role of the alignment capability will continue to be significant. The relationship, however, may not be as strong as that found in firms operating in dynamic industries. We also suggest that in the case of stable industries, the relationship between the customer capability and operational capability may become more significant given the lower rate of change that occurs within the industry and, thus, the attenuated necessity for leveraging the alignment capability. Additional empirical research is warranted to confirm the extent to which this logic holds. We encourage further research in this area because industry-moderated differences raise the possibility that a typology of unique industry-dependent combinations of the three ordinary capabilities remains to be discovered. Given the above, is it possible that insights on the moderating effect of industry on the relationship between the customer capability, alignment capability, and operational capability explain phenomenon like first-mover advantage? Could such insights also aid scholars in discovering how firms alter ordinary capabilities as the industry matures? By identifying, operationalizing, and empirically confirming the existence of three types of ordinary capabilities, we have taken the first step toward clearing a pathway for further research in this and related areas. A call to move beyond ordinary capabilities. Our conceptualization and configuration of ordinary capabilities can be used to expand research in management-related areas of study and beyond. Although not explicitly examined in this investigation, the approach used herein may be applied to other types of capabilities to understand, for example, what capabilities constitute firmlevel dynamic capabilities, and how the types of dynamic capabilities are configured to create value. Furthermore, research suggests that dynamic capabilities influence performance (Todorova and Durisin 2007; Volberda, Foss, and Lyles 2010; Zahra and George 2002), yet researchers are not certain how the dynamic capability value creation process occurs. Using the CAO Model of

Ordinary Capabilities 26 Ordinary Capabilities, researchers can extend Pavlou and El Sawy’s (2011) general model of multiple capability types to more specifically conceptualize the relationships between dynamic capabilities and performance. Specifically, ordinary capabilities may be the missing link to understand how dynamic capabilities create value and drive performance. An extension of Liao, Welsch, and Stoica’s (2003) work on absorptive capacity and SME outcomes is likely a fertile starting ground for this conceptual expansion given that absorptive capacity is one type of dynamic capability. And even further, a recent meta-analysis conducted by Saeed, Yousafzai, and Engelen (2014) examines the influence of entrepreneurial orientation on firm performance; however, the means through which entrepreneurial orientation drives performance remains unanswered. Integration of the CAO Model of Ordinary Capabilities may offer insight into how the entrepreneurial orientation influences value creation via ordinary capabilities to alter performance. In other words, the components of ordinary capabilities as identified herein have broad potential for offering insight into the value creation process for SMEs and beyond. Implications for Managers The CAO conceptualization is useful to managers as they strive to orchestrate financial and non-financial investments to optimize the complementarity of ordinary capabilities. For example, the results of this study suggest that the alignment capability is fundamental to enhancing firm performance in a dynamic industry, and software-like SMEs will benefit from maintaining a viable alignment capability. Although the ordinary capability of alignment is not responsible for discontinuous technological changes in the industry, the alignment capability is essential as it enables the firm to make incremental changes to products and processes to remain in alignment with ever-changing demands. While the finding in itself is not surprising, our investigation suggests that the alignment capability must be designed to play a complementary role with two other types of ordinary capabilities for the firm to be successful. Thus, managers should be

Ordinary Capabilities 27 conscious of the firm’s ability to engage in incremental product and process change given the centrality of alignment to the success of firms within this context. If the alignment capability suffers from a lack of resources, including effects resulting from a culture not supportive of continuous incremental change, the performance and overall health of the firm is likely to be affected. Furthermore, given the synergistic relationships noted among ordinary capabilities, managers are encouraged to ensure that each type of ordinary capability has the necessary resources to optimally perform. For example, to enhance the operational capability of the firm, managers are encouraged to focus on customized internal systems and operational responsiveness. Additionally, managers interested in refining the customer capability are encouraged to focus efforts on firm’s ability to response with speed and precision in relationships with customers and other stakeholders. Examining firm-customer networks, sources of knowledge acquisition, and internal knowledge processes are all beneficial for enhancing the firm’s customer capability. In all, the CAO Model of Ordinary Capabilities offers managers a precise articulation of how value is created within the firm and highlights one foundation that supports the creation of firm core capabilities. Limitations The study provides an empirically tested configuration of ordinary capabilities. Although the results have potentially beneficial implications for both researchers and managers, all findings should be acknowledged within the scope of the study’s limitations. First, the investigation was conducted within the context of a single industry and among SMEs. Given the exploratory nature of this study, the dynamic software industry was intentionally selected for this study because it was expected to catalyze the development of prominent capabilities in resident firms. We expect

Ordinary Capabilities 28 that the variation in study variables would be less in a more mature industry where ordinary capability alignments are believed to be less intense. Second, the results of the study confirm that ordinary capabilities (specifically operational capabilities) are directly related to firm performance. Firm performance was measured using a relative measure of performance self-reported by top managers and further confirmed with additional post hoc analyses to substantiate robustness. Participants were asked to provide relative assessments of firm performance because managers of privately-held firms are known to be less willing to offer detailed financial information. While the use of more objective measures would be more desirable, data on these measures are not always available for privately-held firms. Furthermore, even though primary data collection techniques are common in capability-related studies, we acknowledge the potential limitations of response bias noted by Clougherty and Moliterno (2010) and have attempted to incorporate appropriate measures to mitigate the influence of such biases. Third, ordinary capabilities are responsible for supporting the day-to-day business functions of the firm. Accordingly, this conceptualization of ordinary CAO capabilities is limited to understanding the role of incremental changes that occur within the firm via the alignment capability. Larger scale changes that necessitate a reconfiguration of capabilities are leveraged through dynamic capabilities (Eisenhardt and Martin 2000; Teece, et al. 1997), and such changes are beyond the scope of the current study. Future opportunities lie, however, in understanding how dynamic capabilities influence (and reconfigure) ordinary capabilities in pursuit of more substantial changes to the firm. Fourth, the dynamic nature of the capability creation process is another area for scholars to continue research. As Helfat and Winter (2011) suggest, investigating capabilities is often difficult given that some form of change is always occurring in the firm, and deciphering where the change

Ordinary Capabilities 29 occurs and to what extent is challenging. This study is limited in that a cross-sectional design is used to examine relationships among capabilities at a single point in time rather than assessing the causal nature of capability development and the respective influence on firm performance. The findings of relationships, however, offer a suitable springboard for future longitudinal research. Now that we better understand the relationships among ordinary capabilities, and how performance relates to the noted configuration of ordinary capabilities, a next step in this line of investigation is to understand how ordinary capabilities evolve over time. Al-Aali and Teece (2013) suggest that a firm may survive temporarily with strong ordinary capabilities and weak dynamic capabilities, yet when rapid change occurs in the environment, dynamic capabilities become necessary to maintain evolutionary fitness (Eisenhardt and Martin 2000; Teece, et al. 1997). Future researchers are encouraged to elucidate a more detailed understanding of how the dimensions of ordinary and dynamic capabilities work together to influence firm performance. Conclusion Ordinary capabilities are viewed as prominent drivers of firm performance and vital to SME success (Bartmess and Cerny 1993; Prahalad and Hamel 1990; Sparrow 2001; Van Gils and Zwart 2004; Withers et al. 2011). Yet, research on ordinary capabilities has largely been conducted at a high level of abstraction. In this study, we propose and empirically test the CAO Model of Ordinary Capabilities to explain how ordinary capabilities create value for SMEs. Our conceptualization extends prior research and offers a configuration of ordinary capabilities that has the potential to enhance future capability-oriented research and better understand how SMEs achieve competitive advantage. References *Acar, A. C. (1993). The impact of key internal factors on firm performance: An empirical study of small Turkish firms. Journal of Small Business Management, 31(4): 86-92.

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Ordinary Capabilities 39 Table 1 Review of Ordinary Capability Conceptualizations: Existing Conceptualizations Aligned with Proposed Types of Ordinary Capabilities

Authors offering multi-dimensional capability frameworks*

Proposed types of ordinary capabilities Customer capability

Alignment capability

Operational capability

Lenz (1980)

Knowledge acquisition

New knowledge creation

Knowledge-technique for value creation

Coyne (1986)

Positional and regulatory capabilities

N/A

Functional and cultural capabilities

Ulrich and Lake (1990)

Strategic capability; Organizational capability

Technological capability; organizational capability

Financial capability; Organizational capability

Lado, Boyd, and Wright (1992)

Output-based competencies

Transformation-based competencies

Resource-based competencies

Hall (1992, 1993)

Positional and regulatory capabilities

N/A

Functional and cultural capabilities

Acar (1993)

Marketing competency; Management competency

Production competency; Management competency

Production competency; Management competency

Amit and Schoemaker (1993)

Highly-reliable service; Market-trend responsiveness Customer needs understanding capability

Repeated process or product innovation; Short product development cycle Product technology capability

Manufacturing flexibility

Treacy and Wiersema (1993)

Customer intimacy

Product leadership

Manufacturing capability; Distribution channel capability Operational excellence

Day (1994)

Outside-in capability

Spanning capability

Inside-out capability

Lado and Wilson (1994)

Output-based competencies

Innovation and entrepreneurial competencies; Organizational learning

Input-based competencies; Managerial competencies; Ability to convert input into output

Grant (1996)

Customer support capability

New product development capability

Quality management capability

Kaplan and Norton (1996)

Relationship with customers and shareholders

Organizational learning

Internal business process

Kay (1996)

Architecture; Reputation

Innovation

Architecture

Davies and Brady (2000)

N/A

Strategic capability

Functional capability; Project capability

Meyer and Utterback (1993)

* Contributions listed chronologically.

Ordinary Capabilities 40 Table 1 (continued) Review of Ordinary Capability Conceptualizations: Existing Conceptualizations Aligned with Proposed Types of Ordinary Capabilities

Authors offering multi-dimensional capability frameworks*

Proposed types of ordinary capabilities Customer capability

Alignment capability

Operational capability

McGee and Peterson (2000)

Service image; Control of retailing programs

N/A

Action ability

Tyler (2001)

Relationship management

Information management

Systemic interdependencies

Yu (2001)

External capabilities

N/A

Internal capabilities

Lerner and Almor (2002)

Proactiveness

Entrepreneurial skills; Previous experience

Venture resources

De Carolis (2003)

Marketing competencies; Regulatory competencies

N/A

Technological competencies

Ulrich and Smallwood (2004)

Coherent brand identify; Customer connectivity

Organizational learning; Innovation

Speed; Execution; Efficiency

Wang and Ang (2004)

Quality

Innovation

Cost leadership

Wang, Lo, and Yang (2004)

Marketing competencies

Integrative competencies

Technological competencies

Ethiraj, Kale, Krishnan, and Singh (2005) Graves and Thomas (2008)

Client-management capability

N/A

Project-management capability

Antonio, Richard, and Tang (2009)

Customer service

Product innovativeness

Low price; Product quality; Delivery; Flexibility

Crossan, Rouse, Fry, and Killing (2009)

Speed and agility of delivery to customers

Innovation

Cross-unit synergy; Productivity

Yam, Lo, Tang, and Lau (2011)

Marketing capability

Strategic planning capability; R&D capability

Chen (2012)

Marketing capability

R&D capability

Organizing capability; Manufacturing capability; Resources allocation capability Operational capability

Zhao, Song, and Storm (2013)

Marketing capability; Market-linking capability

Service design capability

N/A

Network relationships; Marketing capabilities

* Contributions listed chronologically.

Production capabilities

Ordinary Capabilities 41

Table 2 Descriptive Statistics and Correlation Matrix

Construct

Mean

S. D.

1

2

3

4

5

6

1. Customer capability

4.04

0.53

1.00

2. Operational capability

3.76

0.61

0.33**

1.00

3. Alignment capability

3.54

0.64

0.44**

0.58**

1.00

4. Performance

3.30

0.94

0.25*

0.35**

0.36**

1.00

5. Firm age

2.64

1.20

-0.05

0.07

-0.08

-0.03

1.00

6. Number of employees

42.93

65.82

0.00

0.07

0.10

0.16

0.19

1.00

7. Sales growth

3.30

1.01

0.19

0.37**

0.42**

0.51**

-0.25*

0.12

1.00

8. Marker

2.49

1.17

-0.04

-0.01

-0.08

-0.10

0.00

-0.13

0.02

Note: ** significant at p ≤ 0.01; * significant at p ≤ 0.05; Firm age was measured using clustered age groups

7

8

1.00

Ordinary Capabilities 42

Table 3 Test of Discriminant Validity

Free model

Constrained model

χ2

219.96

266.46

df

161

164

p-value

< 0.01

< 0.001

CFI

0.92

0.86

RMSEA

0.06

0.08

SRMR

0.07

0.24

Ordinary Capabilities 43 Figure 1 Structural Model: The CAO Model of Ordinary Capabilities

ε1

ε2

ε3

ACPROD1

ACPROD2

ACPROD3

ε4 ACPROD4

ε5 ACPROD5

ε6 ACPROC1

CCEXP1

δ2

CCEXP2

δ3

CCEXP3

ε9

ε8

ACPROC2

ACPROC3

ACPROC4

Process Alignment

Product Alignment

δ1

ε7

ε16

Response Expertise

δ4

CCSPD1

δ5

CCSPD2

Customer capability

0.56***

Alignment capability

0.82***

0.26*

Operational capability

Response Speed

Customization

OCCUST1

ε10

Notes: (1) Standardized regression weight indicated near respective path. (2) *** = p < 0.001; ** = p < 0.01; * = p < 0.05 (3) Control and marker variables excluded from graphical model.

OCCUST2

OCCUST3

ε11

ε12

Responsiveness

OCCUST4

ε13

OCRESP1

OCRESP2

ε14

ε15

Firm Performance

Ordinary Capabilities 44 Appendix Measurement Items Customer Capability1 Response Speed 1. When we identify a new customer need, we are quick to respond to it. 2. When we find that customers would like us to modify a product/service, the departments involved make concerted efforts to do so. Response Expertise 1. We can easily satisfy new needs of customers. 2. We can satisfy needs of our customers better than our competitors can. 3. We have a reputation for effectively meeting the demands of our customers. Alignment Capability2 Product Alignment 1. Our firm often develops new products/services that are well accepted by the market. 2. A majority of our firm’s profits are generated by new products/services. 3. The new products/services developed by our firm arouse imitation from competitors. 4. Our firm can launch new products/services faster than our competitors. 5. Our firm has better R&D capabilities for new products/services compared to our competitors. Process Alignment 1. We often try different procedures to speed up the realization of the firm’s goals. 2. Our firm can acquire new skills or equipment to improve operations or processes. 3. Our firm has the flexibility to meet the changing demands of customers. 4. New process/service procedures employed by our firm arouse imitation from competitors. Operational Capability3 Customization 1. Our resources are used in ways that differentiate us from our competitors. 2. Our operations capabilities are modified to better serve customer needs. 3. Our planning system has been modified to better serve the needs of our customers. 4. Our operations process has been modified to gain unique positions in the market. Responsiveness 1. We can adjust operational processes for unexpected variations in inputs. 2. We can adjust operational processes for unexpected variations in labor requirements. 1

Adapted from Jayachandran et al. (2004) Adapted from Liao et al. (2007) 3 Adapted from Wu et al. (2010) 2