Journal of Managerial Issues -...

Journal of Managerial Issues Volume XXV Number 3 Fall 2013

Editor-in-Chief Bienvenido S. Cortes Assistant Editor Irene Robinson Consulting Editors Donald Baack, Stephen Horner, and Eric G. Harris

Founder and Editor-in-Chief 1989-2008 Charles C. Fischer

Editorial Policy

The Journal of Managerial Issues seeks to publish the highest quality empirical, theoretical, and methodological papers in business research. The overriding criterion for publication of a manuscript in the JMI is the knowledge readers will gain about the theory of organizations and the practice of management. The JMI is intended to foster research from a variety of business school and related disciplines. As such, the JMI is open to and encourages a wide range of emerging methods, conceptual approaches, and substantive problem areas within the domain of business behavior. Articles published are not necessarily the opinions of the JMI, the editors, or Pittsburg State University. Statements by authors appearing in the Journal are the exclusive responsibility of the authors themselves. Authors are allowed to express their opinions so as to encourage and stimulate a free flow of ideas. Each paper submitted to the JMI is processed as follows:

1. Receipt of the manuscript is acknowledged promptly by a letter from the Editor. An initial screening is made by the Editor to determine the suitability of the article. Key factors considered are the quality of the research methodology, the ability to communicate to university faculty and business leaders, and, most important, the potential contribution to the advancement of knowledge directly related to the theory of organizations and the practice of management.

2. Assuming the manuscript is suitable for consideration by the JMI, it is assigned to two (or more) “external” referees, according to its functional and methodological content. Manuscripts are “double-blind” reviewed by referees selected by the Editor.

3. Each referee provides a careful evaluation of the manuscript, makes a recommendation to the Editor, and supplies comments for the author.

4. The Editor appraises the reviews and makes a final decision regarding publication of the article. Every effort is made to obtain prompt reviews and make early decisions (about eight to ten weeks) regarding publication or suggested revision of the manuscript.

Circulation includes university faculty and administrators, collegiate and public libraries, business executives, and government managers.

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EDITORIAL REVIEW BOARD

Industry and Government Robert H. Bennett, III Farmers Exchange Bank Linda Boise, Legacy Health Systems Hubert D. Glover, PwCES John J. Hater, Federal Express Corp. Albert T. Olenzak, Sun Company David C. Parcell, Technical Associates, Inc.

University Accounting Thomas L. Albright, University of Alabama Arnold I. Barkman, Texas Christian University Karen M. Collins, Lehigh University Edward Douthett, Jr., George Mason University Timothy A. Farmer, University of Missouri -

St. Louis Timothy J. Fogarty, Case Western Reserve

University Mark E. Haskins, University of Virginia Robert Kee, University of Alabama Charles Krueger, University of Wisconsin,

Madison Kenneth Lambert, University of Memphis James A. Largay III, Lehigh University Claire Latham, Washington State University Janice E. Lawrence, University of Nebraska -

Lincoln Bruce Lubich, University of Maryland University

College Lawrence M. Metzger, Loyola University of

Chicago Mahmoud M. Nourayi, Loyola Marymount

University Eric Press, Temple University Walter A. Robbins, University of Alabama Finance Philip L. Cooley, Trinity University Kerry Cooper, Texas A&M University Thomas H. Eyssell, University of Missouri -

St. Louis Stephen Ferris, University of Missouri - Columbia George W. Gallinger, Arizona State University George G. Kaufman, Loyola University of

Chicago William A. Kracaw, Penn State University Suk Hun Lee, Loyola University of Chicago R. Charles Moyer, University of Louisville Edward D. Zychowicz, Hofstra University

Management

Behavioral Donald E. Baack, Pittsburg State University Mark Bolino, University of Oklahoma Amy Colbert, University of Notre Dame Debra R. Comer, Hofstra University Jennifer M. George, Rice University J. David Johnson, University of Kentucky James C. McElroy, Iowa State University Terence R. Mitchell, University of Washington Pamela L. Perrewe´, Florida State University Tina L. Robbins, Clemson University Bret L. Simmons, North Dakota State University Howard L. Smith, Boise State University Kenneth R. Thompson, DePaul University

International

Myria Watkins Allen, University of Arkansas Rajan Chandran, Temple University Meredith Downes, Illinois State University Stanley E. Fawcett, Brigham Young University Lee A. Graf, Illinois State University Bruce T. Lamont, Florida State University Jenice Prather-Kinsey, University of Missouri -

Columbia Kathleen A. Rehbein, Marquette University Malika Richards, Penn State University - Berks

Legal and Social Environment

Robert L. Holbrook, Jr., Ohio University Tammy Hunt, UNC-Wilmington Fred A. Jacobs, Georiga State University Paula Rechner, California State University -

Fresno S. S. Samuelson, Boston University Lee P. Stepina, Florida State University G. Stephen Taylor, Mississippi State University Lori L. Wadsworth, Brigham Young University

Human Resource Management

David Antonioni, University of Wisconsin -Madison

Thomas M. Begley, Northeastern University Wendy R. Boswell, Texas A&M University Joseph Broschak, University of Illinois -

Urbana-Champaign M. Ronald Buckley, University of Oklahoma Michael D. Crino, Clemson University

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Nancy E. Day, University of Missouri -

Kansas City Angelo S. DeNisi, Texas A&M University Helen I. Doerpinghaus, University of South

Carolina Gerald R. Ferris, Florida State University Dwight D. Frink, University of Mississippi Jeffrey H. Greenhaus, Drexel University Wayne A. Hochwarter, Florida State University Nancy Johnson, University of Kentucky K. Michele Kacmar, University of Alabama Tim Keaveny, Marquette University Brian S. Klaas, University of South Carolina Howard J. Klein, Ohio State University Douglas M. McCabe, Georgetown University Lawrence H. Peters, Texas Christian University Jason D. Shaw, University of Minnesota Scott A. Snell, Cornell University Patrick M. Wright, Cornell University

Production/Operations

Arnold Barnett, MIT Steve F. Bolander, University of New Hampshire Farzaneh Fazel, Illinois State University Lawrence D. Fredendall, Clemson University Hélène Giroux, HEC Montréal Loretta Hoover, University of Missouri -

Columbia Nancy Lea Hyer, Vanderbilt University Sang M. Lee, University of Nebraska - Lincoln Manoj Malhotra, University of South Carolina Robert E. Markland, University of South

Carolina Joseph S. Martinich, University of Missouri -

St. Louis Marc Schniederjans, University of Nebraska -

Lincoln

Strategy and Policy Allen C. Amason, University of Georgia Diana Bilimoria, Case Western Reserve

University Aaron Buchko, Bradley University Lowell W. Busenitz, University of Oklahoma Charles M. Byles, Virginia Commonwealth

University

William J. Donoher, Missouri State University Derrick D’Souza, University of North Texas Masoud Hemmasi, Illinois State University Charles W. L. Hill, University of Washington James J. Hoffman, Texas Tech University John A. Pearce II, Villanova University John F. Preble, University of Delaware Terrence C. Sebora, University of Nebraska -

Lincoln Chamu Sundaramurthy, San Diego State

University Ellen Weisbord, Pace University Management Information Systems John R. Carlson, Baylor University J. N. D. Gupta, University of Alabama -

Huntsville Jeffrey J. Johnson, Utah State University Anita Lee-Post, University of Kentucky -

Lexington David Paper, Utah State University Marion G. Sobol, Southern Methodist University Mohan Tanniru, University of Arizona Michael P. Thompson, Brigham Young

University Marketing Gerald Albaum, University of New Mexico Rolph E. Anderson, Drexel University J. Scott Armstrong, University of Pennsylvania Rosemary J. Avery, Cornell University Raymond Benton, Jr., Loyola University

Chicago James S. Boles, Georgia State University Isabella Cunningham, University of Texas at

Austin C. Anthony di Benedetto, Temple University Jule B. Gassenheimer, Rollins College Keun S. Lee, Hofstra University James H. Martin, John Carroll University J. Barry Mason, University of Alabama Ajay Menon, Colorado State University Paul Murphy, John Carroll University John Sherry Jr., University of Notre Dame R. Dale Wilson, Michigan State University

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The JMI in Brief

Volume XXV Number 3 Fall 2013 Venture Capital and Risk Management: Evidence from Initial Public Offerings ................... Charles E. Bamford and Edward B. Douthett, Jr.

This study analyzes a sample of initial public offerings (IPOs) to examine the sources of firm-specific risk associated with investment by venture capitalists. The results indicate that IPO backing by venture capitalists is associated with risk factors related to operating profit margins and ongoing sales generation, but not operational financing. The results also indicate that venture-backed IPOs are associated with greater reductions in firm-specific risk over the course of a year that includes the date of the IPO. In sum, the findings suggest venture capitalists are willing to accept higher levels of risk in those instances where they might have an advantage in terms of managerial skill or are able to reduce firm-specific risk subsequent to investment in order to maximize returns when they cash out. The study also makes use of proxies that are representative of the ex-ante nature of firm-specific risk at the time of a new issue.

Time to Regroup: Further Validation of a Fourth Equity Sensitivity Dimension .................... W. Randy Clark, Leigh Anne Clark, David A. Foote, and Amanda C. Hanna

For more than twenty-five years, researchers have believed that the equity sensitivity construct consists of three distinct groups of people (benevolents, equity sensitives, entitleds) based on individuals’ preferences for, or tolerance of, different states of equity. Recently, two studies using different measures and analyses (Davison and Bing, 2008; Clark et al., 2010) found that equity sensitivity yields a fourth group (indifferents) that has been masked by the use of previous measures and analyses. This significant shift in equity sensitivity research calls for replications and additional research to build consensus that a reformulation of the equity sensitivity construct is warranted. The current study primarily replicates the Clark et al. (2010) study using a slightly modified Triadic Measure of Equity Sensitivity (TMES) with a different sample of 332 working adults. Respondents indicated their preference to give or to get in a work setting on the TMES and evaluated the importance of intrinsic and extrinsic inputs and outcomes. Cluster analysis yielded four distinct categories of equity sensitivity response supporting the Clark et al. (2010) finding that four distinct categories of respondents exist. The study also found, as Clark et al. (2010) had, that entitleds and benevolents differ significantly in the importance they put on the extrinsic outcome of pay with entitleds viewing it as more important. This study’s findings also support the conclusion that it is not accurate to assume that benevolents are input-focused and entitleds are outcome-focused.

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Cultural Value Orientation: Measurement Invariance in a Multi-Country Sample ................

Suman Niranjan, Vishal Gupta, Banu A. Goktan, Yu-Ha Cheung, Gonca Gunay, Ashish Pareek

The use of Western-based theory and measures is widespread in international research in business and organizational studies. Contemporary research in international settings often uses four distinct values power distance, uncertainty avoidance, individualism, and masculinity to describe cultural orientation of individuals. This study empirically examines cross-national invariance of the four values using data collected from young adults in the United States, Hong Kong, India, and Turkey. Issues related to configural invariance and metric invariance are examined using paired comparisons of the United States with each of the other three countries. Structural equation modeling is used to analyze data. Findings reveal substantial problems with invariance across countries. Implications for research using culture theory at the individual level are discussed.

A Cross-National Analysis of Corporate Citizenship: Saudi Arabia vs. the

United States ...................................................................................................... Christopher J. Robertson, Jamal Al-Khatib, and Mazen Faris Rasheed

Although corporate citizenship has been a burgeoning theme in the corporate social responsibility literature, comparative studies of citizenship across cultures have been limited. The development of a deeper understanding of how diverse nations perceive citizenship principles from their own paradigms is important in the complex world of international business. This study develops and tests a survey instrument in the Kingdom of Saudi Arabia and the United States to assess perceptions of corporate citizenship principles. Results from a sample of 224 working adults (Saudi Arabia 108, USA 116) include the finding that, regardless of culture, citizenship principles are positively related to ethical business behavior. Significant differences across the two groups are identified such as the higher U.S. perception of citizenship principles related to Ethics, Stakeholders, and the Community at large. Both countries are found to have comparable beliefs related to consumer rights. Managerial implications and future research directions are also discussed.

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192 Understanding the Multi-Dimensional Nature of Absorptive Capacity .................................

Joshua J. Daspit and Derrick E. D’Souza

Numerous studies have examined absorptive capacity, yet the literature has remained generally noncumulative partially due to a limited understanding of the dimensionality of the construct. The capability-based perspective suggests that absorptive capacity is leveraged through multiple underlying capabilities. The objective of this study is to examine and hypothesize relationships among the capabilities to strengthen the theoretical foundation of research on absorptive capacity. An investigation of firms in the software industry was conducted, and the findings suggest firms convert knowledge using four distinct capabilities. The four-capability model of absorptive capacity is shown to be an appropriate operationalization, and empirical results confirm a positive relationship with firm performance. The theoretically anchored and empirically tested model of absorptive capacity offers a unifying conceptualization intended to provide a foundation for future studies and advance the progression of absorptive capacity-related studies.

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JOURNAL OF MANAGERIAL ISSUES Vol. XXV Number 3 Fall 2013

Understanding the Multi-Dimensional Nature of Absorptive Capacity1

Joshua J. Daspit Assistant Professor of Management

Mississippi State University

Derrick E. D’Souza Professor of Management

University of North Texas

Researchers note that firm competitiveness is enhanced by assembling and leveraging idiosyncratic configurations of resources and capabilities (Prahalad and Hamel, 1990; Sparrow, 2001; Van Gils and Zwart, 2004). Hence, the ability to acquire and transform knowledge to create these unique configurations is critical to firm success (Wiklund and Shepherd, 2003). Absorptive capacity represents a set of specific capabilities employed by the firm to achieve these unique configurations. Cohen and Levinthal (1990: 128) define absorptive capacity as the firm’s use of capabilities to “recognize the value of new, external information, assimilate it, and apply it to commercial ends.” Although the manner in which absorptive capacity influences competitive advantage is addressed in extant literature, much remains to be understood about the multidimensional nature of absorptive capacity.

While researchers have referenced the dimensionality of absorptive capacity, the body of research is fragmented and inconsistent, citing the construct as consisting of two (e.g., Zahra and George, 2002), three (e.g., Lichtenthaler, 2009), and/or four internal capabilities (e.g., Sun and Anderson, 2010). The inconsistency evidenced in the literature is indicative of researchers’ limited understanding of the knowledge conversion capabilities associated with absorptive capacity, which has stifled development in the field. Without knowing the precise capabilities associated with

1 Acknowledgements: The authors are grateful to the Department of Management at University of North Texas for partial funding in support of this project. The authors also appreciate suggestions and comments from Bienvenido S. Cortes, Editor, and two anonymous reviewers. Additionally the authors are thankful for the contributions of Divesh Ojha and Lisa Dicke.

JOURNAL OF MANAGERIAL ISSUES Vol. XXV Number 3 Fall 2013: 299-316

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MULTI-DIMENSIONAL NATURE OF ABSORPTIVE CAPACITY


absorptive capacity, and how the capabilities are inter-related, research investigating the antecedents of and other influences on absorptive capacity is hindered.

From a practitioner’s perspective, managers struggle with understanding how firm-level factors (e.g., social integration mechanisms) are used to enhance the firm’s ability to acquire and use new knowledge, and researchers are limited in offering recommendations given that a limited understanding exists of how the capabilities are related. Therefore, prior to offering insight specific to the influence of factors on absorptive capacity, researchers must first understand how the internal capabilities of the construct are leveraged. Studies that offer a better understanding of the capabilities associated with absorptive capacity will further consolidate and extend understanding of the absorptive capacity phenomenon. As a result of detailed investigations, managers will have a more defined blueprint of how to create firm value by leveraging the proper capabilities.

Scholars (e.g., Zahra and George, 2002; Volberda et al., 2010; Lewin et al., 2011) acknowledge that absorptive capacity is a dynamic capability2 consisting of underlying capabilities used to leverage knowledge resources. A similar capability perspective is adopted in this study to advance absorptive capacity research by hypothesizing a four-factor capability model and examining the relationships among the underlying capabilities. More specifically, the objectives of this investigation are to confirm that a four-capability specification of absorptive capacity is the most appropriate conceptualization, identify linkages among the capabilities associated with absorptive capacity, and demonstrate that absorptive capacity, as conceptualized, positively influences firm performance.

The investigation begins with an overview of absorptive capacity, which includes a description of the four primary capabilities: acquisition, assimilation, transformation, and exploitation. Following, relationships among the capabilities are hypothesized, and structural modeling is used to conduct an empirical examination. Results confirm that a four-capability model offers an appropriate operationalization of the absorptive capacity construct. Further, the findings suggest that positive relationships exist between the (1) acquisition and assimilation capabilities, (2) assimilation and transformation capabilities, and (3) transformation and exploitation capabilities. Finally, the construct, as specified, is positively related to firm performance. The results of the study offer a unified conceptualization of absorptive capacity with implications for researchers and managers.

LITERATURE REVIEW

Overview of the Absorptive Capacity Construct

Although not the first to conceptualize the idea, Cohen and Levinthal (1990) are credited with applying learning theory to sculpt absorptive capacity. Cohen and

2 Researchers (e.g., Eisenhardt and Martin, 2000; Winter, 2003; Teece, 2012) have described dynamic capabilities as unique and distinguishable capabilities that allow an organization to orchestrate changes (i.e., creation, integration, or reconfiguration) to the capabilities that allow it to conduct business activities.

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DASPIT AND D’SOUZA


Levinthal (1990) suggest a three-component model, yet subsequent studies vary in their operationalization of the construct. For example, some studies include state-based, unidimensional operationalizations using proxy measures.3 Although such operationalizations may be suitable in specific contexts, they fail to capture the richness of the multidimensional nature of the construct. Of studies that offer a multidimensional conceptualization of absorptive capacity, inconsistency remains on whether two (Zahra and George, 2002), three (Lichtenthaler, 2009), or four capabilities (Sun and Anderson, 2010; Flatten et al., 2011; Gebauer et al., 2012) appropriately conceptualize the model.

To determine the most appropriate conceptualization of absorptive capacity, reference to its theoretical foundations in organizational learning must be considered. Crossan et al. (1999) offer a framework of organization learning consisting of four distinct components (intuiting, interpreting, integrating, and institutionalizing), and the four capabilities of absorptive capacity are posited to convert knowledge in a similar manner. Furthermore, Sun and Anderson (2010) show the direct relationship between the capabilities of absorptive capacity and organizational learning suggesting that both consist of four distinct components. Additionally, Kale and Singh (2007) demonstrate that the alliance learning process (also a dynamic capability) consists of four underlying capabilities. Thus, given its theoretical relationship to organizational learning, absorptive capacity is proposed to similarly consist of four distinct capabilities. Below, details are offered on the unique characteristics of each capability prior to examining the relationships among the four capabilities.

Acquisition capability. This capability represents the firm’s ability to identify and acquire beneficial knowledge (Zahra and George, 2002). Hamel (1991) notes the potential to acquire new knowledge motivates the firm to engage in external relationships (e.g., inter-organizational collaborations, partnerships, etc.). When searching for knowledge, firms engage in “active listening” to scan the environment (Liao et al., 2003: 67), and this approach results in the acquisition of new knowledge from a diverse spectrum of sources (Fosfuri and Tribó, 2008). Once the new knowledge is identified and perceived to have value, it is transferred across the boundary of the firm.

Assimilation capability. The assimilation capability enables the absorption of newly captured knowledge (Daghfous, 2004). The notion of knowledge assimilation is rooted in the work of Piaget (1952) who identified learning processes as consisting of assimilation and accommodation. Assimilation facilitates an understanding of the new knowledge, determines whether the new knowledge fits with prior knowledge, and assesses whether the new knowledge must be altered to fit with existing knowledge structures in the firm (Lefkowitz and Lesser, 1988). In other words, assimilation represents the capability to analyze and understand new knowledge in the context of the firm (Jansen et al., 2005).

Transformation capability. The capability to transform allows the firm to modify, adapt, and combine new knowledge with internal knowledge (Fosfuri and Tribó,

3 Examples of proxy measures used in absorptive capacity include R&D investment (Stock et al., 2001), participation in research communities (Deeds, 2001), age (Allen et al., 2007), and external/internal knowledge acquisition (Liao et al., 2003).

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2008). After knowledge is internalized and understood, it must be combined with existing knowledge structures of the firm. Piaget (1952) suggests that accommodation (or transformation) is needed to alter current schemas and enable a proper fit with the new knowledge given that incompatibilities may exist between new and existing knowledge structures. Put differently, the transformation capability allows the firm to combine newly acquired and understood knowledge with existing knowledge (Lane et al., 2006).

Exploitation capability. Firms leveraging the exploitation capability create incremental change or refinement to the firm’s existing value-creating capabilities (March, 1991; Benner and Tushman, 2003). The result of such change may be reflected in the creation of new goods, processes, or organizational forms (Spender, 1996) thus resulting in enhanced competitive advantage and value generation for the firm (Cohen and Levinthal, 1990; Jansen et al., 2005; Fosfuri and Tribó, 2008).

Relationships among Absorptive Capacity Components

With respect to the relationships among the absorptive capacity capabilities, complementarity theory suggests that certain firm activities are mutually complementary and tend to be adopted simultaneously to enhance the synergistic value of each (Milgrom and Roberts, 1995). In essence, the sum of complementary practices is greater than the sum of individual parts. Applying these arguments to the absorptive capacity phenomenon, it is argued that firms develop underlying capabilities of absorptive capacity in a complementary manner. Without the acquisition capability, for example, the full value of other capabilities is limited. This is in line with Cohen and Levinthal’s (1990) initial conceptualization of absorptive capacity. Thus, prima facie, a conceptualization of absorptive capacity is adopted in which the four capabilities (i.e., acquisition, assimilation, transformation, and exploitation) work in a complementary manner to convert new knowledge acquired by the firm. Specifically, positive relationships are hypothesized to exist between the acquisition and assimilation capabilities, assimilation and transformation capabilities, and transformation and exploitation capabilities. In the following sections, hypothesized relationships are developed to conceptualize the relationships between the capabilities.

Acquisition and assimilation capabilities. The acquisition capability allows the firm to identify new knowledge, and once identified, the capability is further leveraged to transfer the knowledge across the firm boundary (Daft and Weick, 1984; Inkpen, 2002). To appropriately identify and internalize knowledge, firms develop the capability to acquire knowledge through interaction with other firms. During the process of developing and exploiting interorganizational relationships, the firm gains new insight on the external market conditions and new opportunities to serve customers. This additional insight, gained via the acquisition capability, is complementary to the knowledge assimilation capability given that as new relationships are formed and knowledge exchanged, the firm gains experience and additional insight that supports the understanding of new, external knowledge. Szulanski (1996) suggests that knowledge capture and knowledge interpretation are positively related, and therefore, a similar relationship is proposed to exist between the acquisition and assimilation capabilities.

Relationships among Absorptive Capacity Capabilities

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Hypothesis 1: The acquisition capability is positively related to the assimilation capability.

Assimilation and transformation capabilities. Researchers have examined the

relationship between the assimilation and transformation capabilities and suggest that a direct relationship exists (e.g., Todorova and Durisin, 2007). The firm leverages the assimilation capability to understand new knowledge and is likely to also realize the benefit of knowledge for future experience. In other words, the firm will also leverage the transformation capability because little value is created from understanding knowledge if it is not stored for later use. Additionally, Sun and Anderson (2010) suggest the assimilation and transformation capabilities of absorptive capacity are similar to the interpretation and integration capabilities of the organizational learning process whereby the interpretation and integration capabilities are directly related. Therefore, in line with the aforementioned research, a direct and positive relationship is proposed between the acquisition and transformation capabilities.

Hypothesis 2: The assimilation capability is positively related to the

transformation capability.

Transformation and exploitation capabilities. Zahra and George (2002) propose that the transformation and exploitation capabilities of absorptive capacity are closely related. Similarly, Volberda et al. (2010) suggest the two capabilities are related in their review of absorptive capacity, yet the manner in which they are related is not specified. The presence of knowledge-related communication is shown to directly influence knowledge exploitation (Li et al., 2011), which supports research by Sun and Anderson (2010) who offer a conceptualization in which the transformation capability is directly related to the exploitation capability. Similarly, the 4-I framework suggests a direct relationship between the integration and institutionalization of knowledge (Crossan et al., 1999). Overall, firms that accumulate knowledge by leveraging the transformation capability are likely to also engage the exploitation capability to extract the value from the accumulated knowledge; thus, the transformation and exploitation capabilities work together in a complementary manner. That is, a positive relationship exists between the transformation and exploitation capabilities.

Hypothesis 3: The transformation capability is positively related to the

exploitation capability.

METHOD

Measures

The instrument developed by Jansen et al. (2005) was adapted to measure absorptive capacity. This operationalization of absorptive capacity was used for several reasons. First, the scale operationalizes absorptive capacity based on a four-capability conceptualization, and the items offered are shown to best fit a four-factor model by the authors. Second, the scale was tested and found to be reliable (Jansen et al., 2005),

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and third, discriminant validity was found to be previously significant. Details of the scale content and reliabilities for the current study are presented in the Appendix.

Procedure

Data for this study were collected using a key informant approach (Kumar et al., 1993) with surveys administered to top managers of firms in the software industry. Given the focus of this study, senior business executives were selected to obtain unique perspectives on business-unit phenomena, and participants were asked to respond to questions in the survey based on the primary business unit of the firm. The data collection procedure used Dillman’s (1978) total design method and recommendations specific to online surveys (Dillman, 2007). Each executive received a series of email messages in line with the total design method technique: (1) a brief pre-notice letter, (2) a questionnaire mailing, (3) a thank you note, and (4) a replacement questionnaire. Additionally, two special contact notices were incorporated and an incentive was offered (Newby et al., 2003). Sample

The initial sample consisted of 5,085 unique firms from the software industry. After deleting undeliverable email addresses and unsubscribe requests, a total of 3,926 unique firms were included in the survey. A total of 1,287 participants viewed the message, and completed questionnaires were received from 152 respondents, yielding a response rate of 11.8 percent. The response rate obtained is within the anticipated range and in line with previous studies.4

Non-response bias was assessed by comparing early and late respondents (Armstrong and Overton, 1977) in terms of age and relative net profit. No significant differences existed for either variable. Furthermore, to proactively minimize common method bias, procedural controls were incorporated in the survey (Podsakoff et al., 2003). Following data collection, Harman’s single factor test was used to examine the presence of common method bias, and the results suggested common method bias was unlikely to confound the results.5 To further minimize the bias, a marker variable was included in the data analysis to eliminate the presence of unaccounted variance (Lindell and Whitney, 2001).

4 Similar studies that contained an online survey component yielded response rates of approximately 14 percent (e.g., Xiao and Dasgupta, 2009) and recent absorptive capacity studies achieved response rates between 10 and 20 percent (e.g., Khoja and Maranville, 2010; Flatten et al., 2011). 5 To test for common method bias, Harman’s single-factor test was used (Podsakoff et al., 2003). Results from the test concluded a total of 61.42 percent of the total variance was explained, and the largest factor was responsible for 26.62 percent of the variance; thus suggesting that common method bias is not likely to confound the interpretation of the results.

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Control Variables

Although larger firms are likely to contain more knowledge-based resources than smaller firms, they may be limited in flexibility needed for acquisition and assimilation; thus, in line with prior studies (e.g., Lane et al., 2001; Lichtenthaler, 2009) firm size was used as a control variable. Firm size was measured using the number of employees in the most recent year. Additionally, a firm’s age is shown to influence knowledge acquisition and exploitation given that older firms have enhanced social links and refined exploitation processes (e.g., Autio et al., 2000; Jansen et al., 2005). Hence, firm age was controlled and was measured as the number of years since the firm was established.

Confirmatory Factor Analysis

A confirmatory factor analysis was run using AMOS software version 19 and SPSS version 20, and the corresponding fit was assessed for each variable. Two items were removed from the measures for transformation to ensure proper fit, and items for all other dimensions remained. Descriptive statistics and correlations are presented in Table 1.

All factor loadings were above the 0.50 recommended value, and all were significant indicating convergent validity (Hair et al., 2006). To assess discriminant validity, covariances among constructs were fixed to 1.00, and the fit indices for the fixed (constrained) model were observed. A 2 difference test was conducted to determine whether a significant difference existed among the models, and the results were significant (p < 0.01) indicating that discriminant validity was present.

RESULTS

Following the confirmatory analysis, model fit was evaluated. The hypothesized

relationships yielded an appropriate proper overall model fit ( 2 [192, n = 152] = 274.50, p < 0.01; CFI = 0.91; RMSEA = 0.05; SRMR = 0.06; AIC = 490.50; BIC = 817.08). Given an acceptable model fit, the hypotheses were examined. Hypothesis 1 predicted a positive relationship between the acquisition and assimilation capabilities and was found to be significant (p < 0.01, standardized estimate = 0.40). Hypothesis 2 was significant (p < 0.01) and showed a positive relationship between the assimilation and transformation capabilities (standardized estimate = 0.83). Last, the relationship between the transformation and exploitation capabilities, Hypothesis 3, was supported and found to be positive as hypothesized (p < 0.01, standardized estimate = 0.96).

Overall, the findings support direct, positive relationships among the four capabilities of absorptive capacity. However, to further confirm the appropriateness of the findings, additional comparative analyses were conducted to examine the nature of the observed relationships. First, specification of the theorized model was assessed by using comparisons of alternative two- and three-factor models. Second, the hypothesized model was compared against more complex relationships, and last, the relationship between absorptive capacity and firm performance was examined.

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Tab

le 1

D

escr

ipti

ve S

tati

stic

s an

d C

orre

lati

on M

atri

x

Con

stru

ct

Mea

n S.

D.

1 2

3 4

5 6

7 8

1. A

cqui

sitio

n 3.

36

0.73

1.

00

2. A

ssim

ilatio

n 3.

82

0.73

0.

30**

1.

00

3. T

rans

form

atio

n 3.

90

0.59

0.

38**

0.

62**

1.

00

4. E

xplo

itatio

n 3.

83

0.51

0.

16

0.56

**

0.61

**

1.00

5. P

erfo

rman

ce

3.26

0.

80

0.12

0.

43**

0.

27**

0.

42**

1.

00

6. F

irm

age

4.

81

2.68

0.

12

0.16

0.

10

0.16

0.

13

1.00

7. E

mpl

oyee

s 10

6.57

41

8.77

0.

18

-0.1

9 -0

.06

-0.2

0*

0.05

-0

.16

1.00

8. M

arke

r 2.

36

0.88

-0

.12

-0.2

1**

-0.2

6**

-0.3

2**

-0.2

0*

-0.0

8 -0

.08

1.00

Not

e: *

* si

gnifi

cant

at p

0

.01;

* s

igni

fica

nt a

t p

0.0

5

306



Model specification. To assess whether the four-capability model most accurately represents absorptive capacity, two alternative models were examined. Specifically, a two-capability model (consisting of potential absorptive capacity and realized absorptive capacity) and a three-capability model (consisting of acquisition, a combined component of assimilation and transformation, and exploitation) were examined and compared with the four-capability model. All examined models included control and marker variables. Of the three models, the four-capability model displayed the best overall fit indices and the lowest values of AIC and BIC (two-factor model: 2 [194, n = 152] = 405.05, p < 0.01; CFI = 0.78; RMSEA = 0.09; SRMR = 0.08; AIC = 617.05; BIC = 937.58; three-factor model: 2 [193, n = 152] = 287.72, p < 0.01; CFI = 0.90; RMSEA = 0.06; SRMR = 0.06; AIC = 501.72; BIC = 825.28) suggesting the four-factor model best represents the data.

Model complexity. While support was found for a model of absorptive capacity consisting of four, directly-related capabilities, the literature contains examples of models that propose more complex relationships among the capabilities. For example, even though the Todorova and Durisin (2007) model suggests each capability should be acknowledged independently, the authors suggest the relationships among the components may be more complex. Specifically, the authors propose that additional relationships exist between the acquisition and transformation capabilities and between the assimilation and exploitation capabilities. To assess whether the proposed relationships existed, an empirical test of a more complex model was conducted, which included two additional relationships suggested in the literature. The fit indices for the more complex model suggested a proper fit ( 2 [191, n = 152] = 272.08, p < 0.01; CFI = 0.92; RMSEA = 0.05; SRMR = 0.06). However, the relationship between the acquisition and transformation capabilities was not significant (p = 0.37, standardized estimate = 0.08), and the relationship between the assimilation and exploitation capabilities was also not significant (p = 0.40, standardized estimate = -0.27) with all other relationships retaining significance (at the p < 0.01 level). When these additional insignificant relationships are removed from the complex model, the hypothesized four-component model emerges further supporting the proper specification of the model tested in this study.

Influence on performance. Since absorptive capacity is commonly believed to influence firm performance (e.g., Zahra and George, 2002; Todorova and Durisin, 2007, Brettel et al., 2011), an analysis was conducted to determine whether the four-capability conceptualization of absorptive capacity influences the performance of the firm. Two measures, ROA and net profit, were used to assess firm performance6 (Zott, 2003; Lichtenthaler, 2009). The model displayed proper overall fit ( 2 [238, n = 152] = 344.84, p < 0.01; CFI = 0.90; RMSEA = 0.06; SRMR = 0.07), and the relationship with performance was significant (p < 0.01; standardized estimate = 0.53). This

6 Because most of the firms surveyed were privately held, financial information was not readily available from secondary sources; therefore, the information was collected from respondents. A relative measure of performance was used to collect the data because of the reluctance by managers to provide other performance data (e.g., Wolff and Pett, 2006). Managers were presented with the question “How does your firm compare to other firms in your industry in terms of…” and asked to assess the ROA and net profit of their firm. Additional information is available in the Appendix.

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DISCUSSION

To advance absorptive capacity research, this study was designed to examine how firms use underlying capabilities to acquire, assimilate, transform, and exploit knowledge. Empirical testing confirmed the relationships among the four capabilities of absorptive capacity, and the results suggest that the four-component model of absorptive capacity as conceptualized is positively related to firm performance. The confirmation of a four-capability conceptualization of absorptive capacity is an important step forward for the field as it suggests knowledge is converted using a set of distinct yet related capabilities. The intent of this study is to move the field toward a unified and empirically supported view of the absorptive capacity phenomenon. Theoretical Implications

Researchers have employed various conceptualizations of absorptive capacity, which have contributed to a fragmented knowledge base and multiple, uncoordinated developmental pathways. The confirmation of parsimonious relationships among the capabilities of absorptive capacity is an important step forward for the field. First, the findings suggest that more complex models should be carefully reconsidered. Results from the model complexity analysis indicate that research suggesting overly complex models may be less representative of the true nature of absorptive capacity. The findings of this study present researchers with an empirically tested representation of how absorptive capacity leverages internal capabilities.

The findings of this study also suggest that the capabilities associated with absorptive capacity are related in a manner similar to the relationships found among organizational learning capabilities. For example, models of organizational learning (e.g., the 4-I framework described by Crossan et al., 1999) portray a configuration of capabilities wherein learning occurs via intuiting, interpreting, integrating, and institutionalizing. The relationships among the components of organizational learning are similar to the direct, positive relationships found among the capabilities of absorptive capacity. Furthermore, the theory of constructivist learning suggests that individuals also learn in a manner that is conceptually linear (Piaget, 1952). Given this, is it possible that the knowledge conversion capabilities of firms are similar to that of individual-level processes? With further examination, researchers may find that the differences between how firms and individuals convert knowledge is more similar than different. Additionally, the use of multi-level modeling methods will be useful for future researchers interested in further examining how knowledge conversion capabilities are manifested and leveraged at various levels in the firm.

Practical Implications

In addition to presenting valuable findings for researchers, the results also offer insights for managers by supporting an understanding of how one type of dynamic capability (i.e., absorptive capacity) is used to create value for the firm. Given the results, managers are encouraged to re-examine how knowledge is acquired by the firm and thereby improve knowledge codification and retention practices. Specifically,

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strategic-fit theory suggests the firm is likely to experience decline if it is unable to adapt to environmental changes. However, since environmental change tends to occur at a faster pace than most firms learn (Dilworth, 1998), the firm must selectively designate areas where change must occur and to which capabilities resources should be directed. Thus, the firm must actively and selectively engage in developing specified capabilities to support and optimize change in these designated areas.

This research supports the findings of Chandler and Lyon (2009) and encourages managers to fine-tune the acquisition capability to serve the needs of change initiatives. The low correlation between the acquisition and assimilation capabilities suggests that one way to enhance “through-put” of new knowledge in designated areas is to judiciously increase the amount and type of new knowledge acquired by the firm. Further, in line with the recommendations of Fletcher and Prashantham (2011), encouraging employees to be discriminating gatherers of knowledge and employing a community-of-practice that supports peer-to-peer interaction and knowledge sharing will further enhance the quantity, quality, and selectivity of the acquired knowledge.

A similar argument can be constructed at the firm level. Based on the work of Granovetter (1973), firms are encouraged to seek knowledge from weak links in their social network since new, innovative knowledge is more likely to come from such relationships. Therefore, managers seeking to enhance the acquisition capability may encourage employees to participate in professional organizations, trade associations, online communities, newsgroups, message boards, and similar environments where the exchange of knowledge is facilitated. Managers must also ensure that the acquired knowledge is later assimilated, transformed, and exploited via the respective capabilities. Nonaka (1994) notes that codified knowledge can be easily transferred within the organization. That is, if the assimilated knowledge is appropriately codified, there is a higher probability of successfully transforming the knowledge to meet the exploitative needs of the firm. Hence, it behooves managers to carefully codify acquired knowledge thereby enhancing eventual exploitation.

Limitations and Suggestions for Future Research

Although this study provides beneficial implications for both researchers and managers, it is not without limitations. While firms in the software industry were investigated in this study, the conceptualization should be replicated in other industries to determine the consistency of relationships across contexts. Building on the work of Chen and Hambrick (1995), researchers should explore differences in how the capabilities of absorptive capacity are configured in specific types of firms. For example, do firms in all industries leverage absorptive capacity capabilities in similar manner, or do firms in some industries operate differently? Also, does the size of the firm or the type of knowledge (explicit versus implicit) change the relationships among the absorptive capacity capabilities? Furthermore, the proposed operationalization of absorptive capacity may advance entrepreneurship research (Dutta and Crossan, 2005) by helping researchers conceptualize the relationship between entrepreneurial orientation (EO) and organizational learning as proposed by Kreiser (2011).

The internal reliabilities – measured using Cronbach’s – for two components were below the 0.70 level recommended by Nunnally (1978). Although Nunnally

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(1978) recommends 0.70 as a minimum level of reliability, other scholars have suggested that reliabilities in the range of 0.60 to 0.69 represent moderate reliability (Robinson et al., 1991). The transformation and exploitation capabilities of absorptive capacity were both in the moderate range as suggested by Robinson et al. (1991). This level of reliability suggests that results of the study should be appropriately interpreted, and it also provides evidence that further refinement of absorptive capacity measurement technique may be advantageous. Previous studies using this same scale (e.g., Jansen et al., 2005) report reliabilities only slightly above Nunnally’s (1978) recommended level (transformation, = 0.72; exploitation, = 0.71); thus future enhancement of the scale items will be beneficial to further support the development of absorptive capacity .

An additional limitation of the current study is the assumption that the appropriate social integration mechanisms exist in the firm to facilitate the exchange of knowledge among employees. This exchange of knowledge is vital to the firm’s absorptive capacity as it allows for the transfer of knowledge from the individual to firm level. The current study offers an empirically tested model of absorptive capacity capabilities, and researchers are encouraged to expand the model to understand how such factors influence absorptive capacity capabilities. For example, Zahra and George (2002) suggest social integration mechanisms influence the dimensions of absorptive capacity, yet empirical investigations of the influence are limited. Furthermore, Volberda et al. (2010) offer an integrative framework detailing numerous other influences on absorptive capacity (e.g., managerial antecedents, prior related knowledge, etc.).

Still other researchers have explored the relationship between organizational culture and absorptive capacity (Khoja and Maranville, 2010) and the influence of absorptive capacity as the firm adapts to technological obsolesce (Ahsan et al., 2010). Further examination could provide insights on the influence of such factors on the outcomes of absorptive capacity. As one example of research in this area, Brettel et al. (2011) found a curvilinear relationship between absorptive capacity and performance, which raises interesting questions about why absorptive capacity influences firm performance in this manner. Future researchers are encouraged to incorporate the findings of the current study with additional factors (e.g., industry competitiveness, social integration mechanisms, etc.) to understand how such factors influence the capabilities of absorptive capacity and how such influences impact the relationship between absorptive capacity and firm performance.

CONCLUSION

The central objective of this study was to understand the underlying capabilities of absorptive capacity. Specifically, the capabilities of absorptive capacity were analyzed and relationships were examined. The findings indicate that the firm leverages four distinct capabilities to acquire, assimilate, transform, and exploit new knowledge. The results of this study suggest that a more fine-grained approach is required if researchers are to understand the knowledge conversion capabilities embedded in the absorptive capacity of a firm. This theoretically anchored and empirically tested model of absorptive capacity offers a robust and unified conceptualization that has the

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potential to advance absorptive capacity beyond its current state and provide a foundation for further research in the field.

APPENDIX Survey Items

Absorptive Capacitya: The following questions address your firm’s adaptive abilities:

Acquisition ( = 0.77) AQ1 Our firm has frequent interactions with other firms to acquire new

knowledge. AQ2 Our employees regularly visit other firms in the industry. AQ3 We collect industry information through informal means (e.g., lunch

with industry friends, talks with trade partners). AQ4 (R) Our employees rarely meet with employees from peer firms. AQ5 Our firm periodically meets with customers or third parties to

acquire new knowledge. AQ6 Our employees regularly approach third parties such as accountants,

consultants, or tax consultants. Assimilation ( = 0.81)

AS1 We are quick to recognize shifts in our market (e.g., competition, regulation, demography).

AS2 New opportunities to serve our customers are quickly understood. AS3 We quickly analyze and interpret changing market demands.

Transformation ( = 0.63)

TR1 Our firm considers the consequences of changing market demands in terms of new products and services.

TR2 Our employees record and store newly acquired knowledge for future reference.

TR3 Our firm recognizes the usefulness of new external knowledge to existing knowledge.

TR4 (R)b Our employees rarely share practical experiences. TR5 (R)b It is difficult for our firm to grasp opportunities from new external

knowledge. TR6 Our firm periodically meets to discuss consequences of market

trends. Exploitation ( = 0.60)

EX1 We know how activities within our firm should be performed. EX2 (R) Customer complaints are ignored in our firm. EX3 Our firm has a clear division of job duties. EX4 We often seek to exploit new knowledge acquired by the firm. EX5 (R) Our firm has difficulty introducing new products and services.

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EX6 Our employees have a common language regarding our products and services.

Performance ( = 0.82): How does your firm compare to other firms in your industry in terms

of:

OPPERF1 ROA (return on assets) OPPERF2 Net profit (as a percentage of sales)

a Items adapted from Jansen et al. (2005); b Item removed during CFA; (R) = Reverse coded; Reliabilities reported are values achieved

in the current study; All items rated using a five-point Likert scale with anchors ranging from (1) strongly disagree to (5) strongly agree.

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