The effect of technological diversification on organizational performance: An empirical study of S&P 500 manufacturing firms

Technological Forecasting & Social Change 90 (2015) 575–586

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Technological Forecasting & Social Change

The effect of technological diversification on organizational performance: An empirical study of S&P 500 manufacturing firms Chinho Lin 1, Chia-Chi Chang ⁎ Department of Industrial and Information Management & Institute of Information Management, National Cheng Kung University, No. 1, University Road, Tainan City 701, Taiwan, ROC

a r t i c l e

i n f o

Article history: Received 9 May 2012 Received in revised form 13 February 2014 Accepted 14 February 2014 Available online 5 March 2014 Keywords: Technological diversity Absorptive capacity Environmental dynamism

a b s t r a c t Despite the increasing number of studies investigating technological portfolios of firms, the effects of technological diversification on performance remain unclear. This study is an attempt to revisit this topic, with a particular focus on large firms, which tend to have more capabilities to undertake diversified technological projects. In a sample of 165 S&P manufacturing firms with data taken into use in 2008, the results show that large firms can benefit from a diversified technological portfolio with regard to both financial and innovation performances. In addition, the relationship between technological diversity and firm performance is found to be strengthened by firms' internal and external contextual factors, namely absorptive capacity and environmental dynamism. Overall, this study not only proves the importance of technological diversity in large firms, but also provides evidence for the moderating effects of absorptive capacity and environmental dynamism. © 2014 Elsevier Inc. All rights reserved.

1. Introduction Technology has been evolving at an ever greater rate over the last few decades, and technological diversification is widely considered as a vehicle of organizational growth. Indeed, numerous technology management scholars have expounded on the benefits of technological diversification, which comes from an expansion in the number and variety of technologies that firm is able to utilize. This is because a broad technology base may provide a firm with more opportunities to combine and integrate the knowledge from different technological fields, and thus create innovative new products and services [1–4]. However, the development of technological diversification may raise the costs of coordination, integration, and communication efforts [5,6], and it may also prevent firms from creating the focus needed in any specific technology domain that it required

⁎ Corresponding author. Tel.: +886 9 37366857; fax: +886 6 2759451. E-mail addresses: [email protected] (C. Lin), [email protected] (C.-C. Chang). 1 Tel.: +886 6 2757575x53137; fax: +886 6 2759451.

http://dx.doi.org/10.1016/j.techfore.2014.02.014 0040-1625/© 2014 Elsevier Inc. All rights reserved.

to realize economies of scale [7]. In such situations, the related studies associated with the performance effects of technological diversification are still inconclusive [8,9]. More work is therefore needed to examine this issue. Despite, the doubts of some theorists, as noted above, the increasing complexity of technological innovations necessitates the pooling and integration of multiple kinds of knowledge [10], and shortening product life cycles as well as expanding numbers of technology options further intensify the demand for increasingly diversified technology portfolios. The merits of technological diversification may thus be more important than ever, particularly in technologically intensive industries. This suggests that the inconsistent findings of earlier studies may be due to their different research settings. In order to capture a clearer picture, in this study we restrict our attention to large size firms only. The size of a company is likely to affect its capability to undertake diversified technological projects, and small firms have many disadvantages in this respect, such as the shortage of resources and structural divisibility [11–13]. Furthermore, from a practical perspective, whether to diversify or not is also an important issue, and little conventional wisdom is available to

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guide the managers of large firms [14], also suggesting that further research is necessary. The first aim of this study is thus to reinvestigate the relationship between technological diversification and performance in large firms. This study further considers various organizational or environmental factors and their relationship with technological diversification. For example, Chiu et al. [15] found that the performance effect of technological diversification is influenced by a firm's complementary assets. Therefore, one possible reason for the inconclusive results of earlier studies is the fact that the contingency effect of organizational or environmental factor has been neglected. According to the resource-based view (RBV) of the firm, successful firms have a greater ability to identify, cultivate, and exploit the core competencies that are the roots of sustainable competitive advantages [16–18]. In other words, a firm's capabilities probably moderate the performance effect of technological diversification. However, among the various organizational capabilities, a firm's absorptive capacity is particularly important to the success of technology and knowledge integration. As pointed out by Pandza and Holt [19], through increased absorptive capacity a firm expands its knowledge base to improve its ability to assimilate and utilize information, and eventually to enhance its technological performance. This suggests that simply enlarging a firm's technological portfolio does not guarantee superior performance, and that much depends on a firm's ability to identify potentially fruitful technological opportunities, and then to explore and exploit its technological assets. The second aim of this study is thus to fill the gaps in the current technological diversification research with regard to absorptive capacity. In addition to the internal synergistic effect of a firm's absorptive capacity, the external environment may also accelerate or hinder the efficacy of technological diversification. For example, in a turbulent and rapidly changing environment, technology quickly becomes obsolete, thus making it difficult for firms to evaluate the utility of existing products or services. As Teece [20] suggests, firms operating in this context need to develop varied technological portfolios to sustain their superior performance. By contrast, firms operating in a relatively stable environment may have less need for a diversified technological portfolio. We thus have reason to believe that the relationship between technological diversification and firm performance is influenced by environmental circumstances. According to the prior literature, environmental dynamism serves as an important boundary condition for firm actions and the consequent outcomes [21,22]. The third aim of this work is thus to discover the contingency effect of environmental dynamism. These two contingency considerations not only arise in response to recent calls for more theoretical and empirical inquiries into the impact of technological diversification [7,23], but also because of their possible contributions to the situational efficacy of technological diversification, and in particular to the concept of contextual efficacy. Accordingly, the main contributions of this study are fourfold. First, as technological innovation increasingly plays a central role in modern business environment, investigating the relationship between technological diversification and firm performance deserves more theoretical and empirical efforts, and this subject may be especially important in large firms. As Granstrand et al. [24] and D'Este [25] suggest, the performance of large firms may be significantly improved by

increasing technological diversification. Compared to prior studies using unscreened samples, the present study focuses on S&P 500 manufacturing firms, which tend to be larger. This research setting can help to clarify and elaborate upon the benefits of technological diversification in a specific setting. Second, this study adopts a contingency perspective by exploring the moderating effects of absorptive capacity and environmental dynamism on the relationship between technological diversification and firm performance. These efforts can help to better comprehend the boundary conditions of when technological diversification improves firm performance, and are also based on the conventional wisdom that the benefits of a firm's technological choices are embedded in organizational/environmental contexts that cannot be ignored [26,27]. Third, in order to eliminate uncertainties and ambiguities concerning the robustness of the performance effect, in this study we not only explore the financial performance effect of technological diversification, but also simultaneously consider the innovation performance effect. These measures increase the internal validity of this study, and can provide more in-depth knowledge with regard to technological management. Fourth, the three hypotheses were tested on the data collected in 2008, the biggest economic downturn since the Great Depression. This further reinforces the notion that a diversified technological portfolio allows firms to hedge against economic uncertainties while maintaining sustainable advantages. The rest of the paper is organized as follows. The next section presents the theoretical background and develops the research hypotheses, while section three describes the sample and measures used in this work. The fourth section presents the empirical results, and the final section provides a discussion of the key findings and conclusions, as well as recommendations for further research. 2. Literature review and hypothesis development 2.1. Technological diversification As RBV theorists suggest, a firm's technological capabilities are defined as the roots of a firm's sustainable competitive advantage [28,29], and thus they are obviously of great importance in modern business. This further implies that how a firm constructs its technological portfolio is likely to be a determinant of its success. However, the literature related to the contribution of diversified or concentrated technological portfolios provides inconclusive results. Several evolutionary theorists have suggested that, with the prevailing trend of increasing complexity of products and processes over time, it is necessary for firms to invest in a variety of technology fields to complement their own competences (e.g. [30]). According to Hamel and Prahalad's [31] observations, there are many examples of once successful companies that failed because they were monotonous and unable to adapt to altering conditions. Technological diversification is therefore believed to benefit firms for several reasons. For example, due to shortening product life cycles and expanding technological possibilities, technological diversification provides firms with many different technological possibilities, which cannot only be used to enter different markets, but also to improve the functionality of existing products through integrating various technologies [3]. Empirical evidence from Nesta and Saviotti [32], Garcia-Vega

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[23], and Chiu et al. [15] confirms the positive effect of technological diversification on organizational outcomes. In short, as Quintana-García and Benavides-Velasco [9] suggest, building a diversified technological portfolio provides firms with more opportunities for combining and recombining their existing technological capabilities, and thus reduces the threats from an ever-changing environment. By contrast, the opposition argues that specialization enables firms to take advantage of the economies of scale that result from exploitation of existing technologies. The returns associated with specialization are also seen as more reliable, and can enable firms to secure a steady position in the marketplace by leveraging their technological capabilities. As Breschi et al. [2] suggest, specialization facilitates the transfer of knowledge between the core technologies of the firm, and thus more benefits accrue from its technological comparative advantages. Strategic theorists, such as Benner and Tushman [6], also point out the incompatibility of technological specialization and diversification. This implies that the first which focuses on technological diversification may fall into a diversification trap, and suffers from the high that can come from the integration of complex technological components [14]. However, empirical evidence with regard to the benefits or otherwise of technological diversification is still inconsistent. For this reason, some researchers believe that technological diversification is somewhat of a double-sword, and further propose that an inverted-U relationship exists between technological diversification and firm performance [7]. One possible reason for the conflicting findings in the literature could be that studies of technological diversification often ignore the potential effect of firm size, which may affect whether a firm has the ability or need to cope with diversified technological developments. The consideration of firm size carried out in the current study may thus provide a new angle from which to clarify the ambiguous effects of technological diversification. The influence of firm size on innovation activities has sparked a great deal of controversy and research; however our understanding of innovation and growth patterns in different-sized firms is not yet comprehensive. Some argue that smaller firms have more advantages in technological innovation because of their flexibility and lack of inertial constraints (e.g. [33]), whereas others suggest that larger firms are more effective in innovation because they have more resources and professional talents (e.g. [34]); namely, large and small firms have their respective advantages for technological development. Judging from the above, with regard to the ability to cope with diversified technological advancements, the firm size could be one of the most important contextual factors which govern the technological diversification performance. More specifically, in order to enhance the effectiveness of technological diversification, the firm has to be able to simultaneously manage multiple projects which often require considerable resources. Some characteristics of large-sized firms can be used to explain why large firms might gain more advantages from technological diversification. Firstly, the advantages of firm size become more marked because large firms have more physical, financial, manpower and technological resources to serve multiple purposes [35,36]. Secondly, large firms have more sophisticated management skills to help manage and accelerate the developments of its diversified technological portfolio. Thirdly, compared to small-sized firms,

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the horizons of large firms are less limited by managerial constraints [37], which may scale down assistance and support that can be given to each project and thus not result in expected functionality. In synthesizing the above-mentioned concepts into a coherent whole, the value of technological diversification is much more likely to be obtained by larger firms rather than smaller ones. Some observations and empirical studies further underpin the positive effect of increased technological diversification on organizational outcomes in large-sized firms. For example, by observing Samsung's performance in the smartphone sector in recent years, the propeller of its growth largely built on its diversified technological competences, such as semiconductor, optics, and house appliances. The synergy and complementarily of various technologies keep the company ahead of its rivals in the Android segment. Conversely, the failure of Kodak in the digit revolution may be one of the best known examples of how technological rigidity can bring a big company down. Moreover, based on a small sample of the 32 largest US and European electronic firms, Gambardella and Torrisi [38] find a positive relationship between technological diversification and corporate performance. In summary, based on the above literature review and discussion, the following hypothesis is proposed. Hypothesis 1. Among large firms, an increase in technological diversification is positively associated with its performance. 2.2. The contingency effects As mentioned above, although the benefits of technological diversification have been recognized in existing studies, there are no consistent findings in the literature, and one reason for this is the fact that the contingency factors have not been addressed. For example, Chiu et al. [15] find that the consideration of a firm's complementary assets can help to explain the relationship between technological diversification and firm performance. More specifically, no single perspective on a firm works at all times and in all situations. As Anthony et al. [39] suggest, an organization's specific way of doing business depends upon a number of conditions, reflecting the fact that an organization's structure and process are contingent on various internal and external factors. However, existing studies of technological diversification have not addressed the moderating role of internal absorptive capacity and external environmental dynamism. Therefore, in the following sections, this study addresses in more detail the contingency effects of absorptive capacity and environmental dynamism. 2.2.1. Absorptive capacity When a firm seeks to increase its technological diversification, managers may face a number of problems related to the growing complexity of its technology portfolio. As suggested by the organizational learning literature, how a firm identifies and manages its technological knowledge bases will be determined by its absorptive capacity [40,41], which is an organization's ability to recognize the value of external knowledge [16], to evaluate emerging technology [42], and to predict the future technological advances. As Zahra et al. [43] state, absorptive capacity is a set of organizational routines and processes by

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which firms acquire, assimilate, transform, and exploit knowledge to produce a dynamic organizational capability, which enables them to make sense of external knowledge, interpret and combine it with existing knowledge, and successfully exploit it commercially. In short, absorptive capacity is necessary to recognize and understand potentially valuable new technologies, and can help firms to identify more technological opportunities [44,45]. As Cohen and Levinthal [16] suggest, if a firm has a certain level of absorptive capacity then it will be able to take advantage of its pool of technological competence. Moreover, as pointed out by Lane et al. [46], absorptive capacity represents a firm's ability to manage knowledge and promote performance, and the amount of technological potential that the firm perceives is an increasing function of its absorptive capacity. In other words, if a firm has the requisite absorptive capacity, it can quickly comprehend the technological potential of a diversified technological portfolio, and then successfully exploit it, thus facilitating new product and process developments that improve profitability [47,48]. Based on the studies and reviews above, firms that have high absorptive capacity are more likely to benefit from a diversified technological portfolio and achieve better performance, and thus the following hypothesis is presented: Hypothesis 2. Among large firms, the relationship between a firm's technological diversification and performance can be positively moderated by its absorptive capacity. 2.2.2. Environmental dynamism In accordance with Hypothesis 2, the existence of certain organizational capabilities will influence the performance effect of technological diversification. Similarly, external environmental characteristics also affect the relationship between technological diversification and firm performance. For example, according to prior research, technological competences become obsolete more readily in some industries rather than others [49,50], and this is probably because of the different levels of environmental dynamism that apply in different contexts. Environmental dynamism is thus recognized as an important contextual factor in defining the boundary conditions limiting the advantages associated with firm-specific technological competences [51–53]. Environmental dynamism describes the rate and instability of environmental change [54], and previous research has decomposed it into the variance in the rate of technological change and market volatility across industries [55]. The former is related to the unpredictability in technology outcomes in an industry, while the latter is linked to the volatility in customer demand for certain products. That is to say, when the task environment becomes more dynamic and volatile, a particular technological solution may suffer from a significant depreciation in value. Conversely, according to Wiklund and Shepherd [56], environmental dynamism also opens new opportunities in markets for firms to grow. In this vein, environmental dynamism may intensify the importance of a diversified technological portfolio. As noted above, there are theoretical grounds for suggesting the importance of diversified technological competencies in a dynamic environment. More specifically, in a dynamic environment, a firm with a diversified technology portfolio can avoid the risk of core rigidity [57], while also

benefiting by taking advantage of the cross-fertilization effects from a combination of diversified technological competences [3,9]. For these reasons, a high level of environmental dynamism is more likely to induce the beneficial effects of a firm's diversified technological portfolio. Therefore, the following hypothesis is proposed: Hypothesis 3. Among large firms, the relationship between a firm's technological diversification and performance can be positively moderated by environmental dynamism. 3. Method 3.1. Data and sample To examine the proposed hypotheses, our research sample covers manufacturing firms in the 2008 Standard & Poor's (S&P) 500 index, a stock market index containing the 500 largest publicly listed firms in the United States, which has been widely adopted in prior studies related to issues in large-sized firms (e.g. [58]). In addition, the observation made in 2008, at which time a financial crisis spawned by the collapse of U.S. financial institutions, provides a distinct opportunity to examine the validity of a firm's adoption of a discretionary strategy; namely this economic downturn inevitably brought pressures on the performance and market values of most companies. In order to measure a firm's technological diversification and innovation performance, we use patent-application data, which has several advantages compared with other indicators, such as being available at the level of the firm, and providing detailed information on the technological content of a firm's innovation activities [7]. For this reason, based on the first three digits of SIC code, our sample included manufacturing firms in five patent-intensive industries: chemicals (12.72%), computers and telecommunications (31.12%), biotechnology and pharmaceuticals (18.79%), electricity and electronics (27.27%), and machinery (9.10%). The patent data were collected from the US Patent and Trademark Office (USPTO). In addition to the patent data, we also collected other firms' information and financial data from Compustat. After removing some firms with incomplete data, we obtained a sample of 165 firms. According to the sample analyzed, as shown in Table 1, the smallest firm (i.e. QLogic Corp.) in this study has over 1100 employees or assets of over 780 million US dollars. The average firm size is 43,234 employees and 29 billion US dollars. All above statistics are satisfied with the standard of the U.S. Census Bureau that a company must employ at least 500 workers to be classified as large. As a result, generalizations to the population of large-sized manufacturing firms in patent-intensive sectors should be made. 3.2. Variables and measures 3.2.1. Technological diversification Since the Herfindahl index [59] is a common measure for the degree of concentration in diversification studies [60,61], this study thus employed the modified Herfindahl index (1-Herfindahl index) as a measure of the degree of technological diversification. In line with Quintana-García and Benavides-Velasco [9], technological diversification is

2710 (Snap-on)

1622 (Waters) 1754 (Red Hat) 1475 (Intuitive Surgical) 780 (QLogic)

6000 (Harley-Davidson) 39,111 9.10%

3.2.3. Environmental dynamism The variable of environmental dynamism was measured in accordance with the recommendation of various prior studies [54,55,69]. We used industry-level sales and R&D information to measure the variations in both product and technology markets. More specifically, following Keats and Hitt [70] and Dean and Snell [71], we regressed industry sales over a moving window of five years (from t − 4 to t) preceding the focal year (t) on the year variable, then used the standard error of the regression coefficient related to a year variable, divided by the average value of the industry's sales, to produce a standardized index of product dynamism. Industry-level sales were the aggregated sales of all sample firms in the same industry. We then adopted the same procedure to evaluate technological dynamism. Finally, we standardized the two measures and combined them into a composite measure to represent the level of environmental dynamism. A higher value implies that the technological and industrial developments of an industry is more uncertain and volatile.

Unit: Millions US dollars.

152,983 (Caterpillar)

16,270

3.2.2. Absorptive capacity Absorptive capacity represents a firm's ability to value and assimilate information [16]. Examination of the relevant literature shows that absorptive capacity is a complex concept, and various different measures have been used to assess it, with no single one being superior to all others under all circumstances [45,64]. For example, Mowery and Oxley [65] and Keller [66] used the number of scientists and engineers working for a company to measure its absorptive capacity. However, the most widely used measure of absorptive capacity is R&D capacity [16,67], which usually provides the foundation for knowledge creation and subsequent exploitation [68]. This study therefore used a firm's R&D intensity (R&D/sales) as a proxy for absorptive capacity.

a

Machinery

579

expressed as follows: Technological diversification = 1-Herfindahl index = 1 – ∑ p2i , where Pi represents the proportion of a firm's patent iportfolio in technological field i. The technological portfolio of each firm was calculated using the three-digit USPTO classification (i.e. UPC), which distinguishes over 400 technology classes. In order to better capture technological diversification, based on method from previous studies [1], patents assigned to more than one technological field are treated as different applications. Moreover, since organizational memory is imperfect, and knowledge depreciates sharply and probably loses significant value within five years [62,63], this study only used the patents granted between 2004 and 2008. Consequently, the value of this measurement ranges from 0 to 1, with a higher value implying that a firm has a more diverse technological portfolio.

228,052 (Exxon Mobil) 26,5245 (AT&T) 111,148 (Pfizer) 797,769 (General Electric) 67,782 (Caterpillar) 46,480 27,803 23,661 31,340 5000 (Waters) 2380 (Akamai) 2100 (Intuitive Surgical) 1147 (QLogic) 26,722 56,364 33,716 43,409 12.72% 31.12% 18.79% 27.27% Chemicals Computers and telecommunications Biotechnology and pharmaceuticals Electricity and electronics

83,600 (Exxon Mobil) 433,362 (IBM) 103,700 (Johnson & Johnson) 301,000 (General Electric)

% of total sample Mean of total employees Max. of total employees Industry

Table 1 The descriptive characteristics of sample firms.

Min. of total employees

Mean of total assetsa Max. of total assetsa

Min. of total assetsa

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3.2.4. Performance Since the components of a firm's technological portfolio may influence performance in different ways and over different time periods, the traditional accounting-based performance indicators (e.g., ROA or EPS) may be problematic, since they can only reflect a firm's short-term profits. Therefore, instead of using accounting-based measures of firm performance, firm performance is measured by using Tobin's Q, defined as the ratio of a firm's market value to the book value of its assets [72,73]. The book value of the assets represents the total value

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of assets reported on a firm's balance sheet, while the market value is measured by adding the nominal value of outstanding debt to the market capitalization [74]. The outstanding debt is defined as the sum of total long term debt and debt in current liabilities. Tobin's Q has the advantage of capturing short-term performance and long-term prospects [75,76], and allows us to use a single indicator to simultaneously consider both shortand long-term performance effects. In addition to the financial-based performance, technological diversification also influences other firm performance indicators [9]. This is to say, the value of a diversified technological portfolio should be reflected not only in a firm's financial performance, but also in its innovation performance. This study thus used Levitas and Mcfadyen's [77] evaluation of patent value to assess innovation performance. We first counted the number of times each of a firm's patents, issued during the period 2004 to 2007, is cited in other patents in the years until 2008. As the prior literature suggests, a patent that gains more citations by subsequent patents is considered to be more important [78,79]. However, since certain classes of patents will demonstrate greater rates of patenting and technological advancement than others [80], we thus divided each patent's citation count by the mean patent citation count for all patents produced in the same technological class, categorized by the first set of UPC numbers. This was carried out to minimize bias across industries. We then added together each firm's standardized patent citation values for each year, which describe the patent flow created by the firm in that single year. Finally, we added to this yearly value the previous four years' flows to generate a stock of patent value. As Levitas and Mcfadyen [77] suggest, “the advantage of constructing patent value as a stock is that it provides us with a multiyear aggregate of patent value activity that reflects not only the signaling value of a current year's patents, but also the signaling value that remains from previous years.” Because this study's sample firms are from various industries, the performances among different industries are not completely uniform. In order to control for industrial differences, both financial and innovation performances were industry-adjusted by subtracting the industry mean (e.g., [81,82]). The threedigit standard industrial classification (SIC) code was used to determine which industry each firm belongs to. 3.2.5. Control variables Numerous factors beyond technological diversification may influence firm performance. Based on the relevant literature, this study added several control variables to the empirical models to reduce possible variances, since sample firms have various organizational technological characteristics. A total of five firm-level control variables are used, namely firm age, total asset, total number of employees, debt ratio, and prior performance. Firm age is measured as the number of years from the founding of the business until 2008. The natural logarithm of the total asset and total number of employees are used to control the possible effects of firm size. Debt ratio represents a firm's financial constraints, which influences both corporate behaviors and outcomes, and this is measured by the ratio of debt to total assets. ROAt − 1 is used to measure prior performance, and to control for its potential influence. Finally, in addition to the above firm-level control variables, because the sample firms came from five industries, we included four industry dummy variables to account for industrial factors.

Among these five industries, the machinery industry served as the latent dummy. 4. Results Table 2 presents the descriptive statistics and correlation matrix for all the variables in the analysis, and it can be seen that correlations among the independent variables are relatively modest. For all the models, the variance inflation factor was calculated to check for multicollinearity. A commonly used rule of thumb for multicollinearity is 10 or less [83,84], and the highest value across all models and variables was less than 3.373, indicating that the problem of multicollinearity is not significant among the independent and control variables. Linear ordinary least squares (OLS) regression was used to test the effect of technological diversification on firm performance. The results of the regression analyses for financial performance are shown in Table 3, while those for innovation performance are presented in Table 3. In Models 1a and 1b, we included nine control variables as the baseline model for both dependent variables. In Models 2a and 2b, the coefficient of technological diversification was positively related to both financial performance (β = 0.346; p b 0.001) and innovation performance (β = 0.320; p b 0.001), in support of Hypothesis 1. However, due to some inconsistencies in previous studies, we had to consider the potential effects of quadratic term. According to results for Models 3a and 3b, the inverted U-shaped relationship did not exist in our research context, further confirming the results of testing Hypothesis 1. Hypothesis 2 proposed a positive moderating effect of absorptive capacity, so that firms possessing higher absorptive capacity will see a stronger relationship between technological diversification and organizational performance. Both Models 4a and 4b indicate that technological diversification strongly interacts with absorptive capacity (Model 4a: β = 0.288; p b 0.001; Model 4b: β = 0.153; p b 0.05), i.e. both financial and innovation performances are enhanced when higher technological diversification is accomplished by higher absorptive capacity. Additional credibility regarding this interpretation is available through the increase in adjusted R2; the interaction term is included in both Model 4a (compared with Model 2a: ΔR2 = 0.129; p b 0.001) and 4b (compared with Model 2b: ΔR2 = 0.145; p b 0.001). Moreover, in order to better clarify the moderating effect of absorptive capacity on the performance effect of technological diversification, we followed the procedure suggested by Aiken and West [85] to create the figures. In Fig. 1a and b, the horizontal axes represent the extent of financial and innovation performances, and the vertical axes represent the level of technological diversification. The sample firms were split in two groups: high and low absorptive capacity. Fig. 1a and b show a strong positive relationship between technological diversification and performance when firms have a higher absorptive capacity, but a less positive relationship when the absorptive capacity is lower. Hypothesis 2 hence was supported. Hypothesis 3 assessed the positive moderating effect of environmental dynamism. As shown in Models 5a and 5b, the coefficients of the terms presenting the interaction effect between technological diversification and environmental dynamism are both positive and significant (Model 5a: β = 0.279; p b 0.001; Model 5b: β = 0.319; p b 0.001).

0.138 −0.042 0.435 0.066 −0.060 0.126 −0.188 0.124 −0.368 0.056 0.174 0.063 0.282 −0.303 0.067 0.798 0.137 0.002 0.235 −0.267 0.056 0.190 0.287 0.232 0.100 0.240 −0.296 0.128 0.212 0.009 0.050 0.262 −0.049 0.129 −0.179 0.037

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Moreover, compared to Models 2a and 2b, the inclusion of the direct and moderating effects of environmental dynamism in Models 5a and 5b significantly increase the explained variance of financial and innovation performances. Similarly, by adopting the same graphing method, Fig. 2a and b illustrate the moderating effect of environmental dynamism. The figures show that technological diversification has a stronger positive relationship with financial or innovation performance for firms operating in highly dynamic industries, while the relationship becomes weaker when industrial environment is relatively stable. The above results lend further support to Hypothesis 3. In order to confirm the stability of the results reported above, all the explanatory variables were considered in Models 6a and 6b to examine whether the directions of the coefficients have changed. Moreover, we replicated the aforementioned analyses with non-mean-centered dependent variables. The focal relationships continued to be statistically significant at the 95% confidence level. The experimental results confirm the robustness and reliability of this study. 5. Discussion

Bold means the significant correlation at the 0.05 level. a Both dependent variables were mean-centered by industry. b These variables were transformed by nature logarithm.

0.383 0.079 −0.015 0.010 −0.084 0.006 0.133 0.042 0.157 0.142 0.308 0.374 0.090 0.463

0.029 0.002 −0.076 0.037 −0.012 0.139 0.347 0.323 0.005 0.188 0.392 0.210 0.399

−0.201 −0.155 −0.191 −0.098 0.147 0.086 −0.051 0.087 −0.016 0.160 −0.211 0.024

−0.254 −0.315 −0.161 −0.345 0.053 0.021 −0.325 −0.059 −0.075 0.207 −0.045

−0.242 −0.124 0.055 0.088 −0.022 −0.023 −0.014 −0.116 0.129 −0.049

−0.153 −0.167 −0.203 −0.105 −0.106 0.078 −0.031 0.229 −0.054

9 8 5 4 3 2 1 S.D. Mean

−0.033 0.083 0.127 0.321 0.188 0.273 0.091 3.822 9.252 9.979 20.822 8.157 0.827 0.058 0.117

Variables

1 Tobin's Qa 2 Patent valuea 3 Chemicals 4 Computers and telecommunications 5 Biotechnology and pharmaceuticals 6 Electricity and electronics 7 Machinery 8 Firm ageb 9 Total assetb 10 Total employeesb 11 Debt ratio 12 Prior performance 13 Technological diversity 14 Absorptive capacity 15 Environmental dynamism

Table 2 Descriptive statistics and correlation matrix.

1.496 1.927 0.313 0.433 0.371 0.422 0.260 0.960 1.244 1.215 13.991 7.425 0.147 0.059 1.110

6

7

10

11

12

13

14

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Although there is a growing literature on technological diversification, knowledge on its influence is still incomplete, and the related studies also have inconclusive findings, most likely because not all firms have a need or capabilities to diversify their technological portfolios. For this reason, the main purpose of this study was to re-explore the influence of technological diversification on corporate performance in a particular setting, and it is hoped that the results will clarify which sectors can benefit most from a diversified technological portfolio. Based on a sample of large manufacturing firms, our findings provide strong evidence for the premise that a diversified technology portfolio positively and significantly affects firm performance. However, examining only the direct effect of technological diversification cannot provide a complete picture of this issue. Therefore, this study further considered the moderating effects of internal and external factors, which may contribute to theoretical advances in our understanding of technological diversification as well as shed new light on its situational merits. The empirical evidence reveals that both internal absorptive capacity and external environmental dynamism have positive moderating effects on the relationship between technological diversification and firm performance. Based on the findings, this study provides several original contributions to the study of technological management. First, this study provides empirical evidence that large manufacturing firms with a higher level of technological diversification are more likely to achieve higher corporate performance. Very few studies with similar aims are based on such research setting. This study has made a step further in the investigation of controlling for the confounding effect of firm size and this focus contributes to clarify the technological diversification–performance relationship. Such a finding would echo the Schumpeterian argument that R&D is more productive in large firms with greater resources and well-developed complementary activities to accommodate the increasing size of the technology projects. However, our findings do not negate the significance of technological diversification in small-sized firms, even though they have the constraint of resources and capabilities. In order to survive in an ever changing environment, smaller firms can leverage

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N = 165

Chemicals Computers and telecommunications Biotechnology and pharmaceuticals Electricity and electronics Firm age Total asset Total employees Debt ratio Prior performance Technological diversity (TD) Technological diversity2 Absorptive capacity (AC) Environment dynamism (ED) TD × AC TD × ED Adjusted R2 F F for ΔR2

All coefficients are standardized. ⁎ Is significant at the 0.05 level. ⁎⁎ Is significant at the 0.01 level. ⁎⁎⁎ Is significant at the 0.001 level. a Is significant at the 0.1 level.

Financial performance (Tobin's Q)

Innovation performance (patent value)

Model 1a

Model 2a

Model 3a

Model 4a

Model 5a

Model 6a

Model 1b

Model 2b

Model 3b

Model 4b

Model 5b

Model 6b

0.147 0.154 0.110 −0.002 0.036 −0.279⁎ 0.316⁎ 0.221⁎⁎ 0.340⁎⁎⁎

0.088 0.139 0.128 −0.027 −0.012 −0.290⁎

0.096 0.139 0.136 −0.010 −0.016 −0.325⁎⁎ 0.283⁎ 0.203⁎ 0.312⁎⁎⁎ 0.360⁎⁎⁎

0.106 0.038 0.091 −0.110 −0.030 −0.263⁎ 0.236⁎ 0.223⁎⁎ 0.340⁎⁎⁎ 0.322⁎⁎⁎

0.108 0.121 0.157a 0.008 −0.001 −0.323⁎⁎ 0.308⁎⁎ −0.161⁎ 0.249⁎⁎⁎ 0.180⁎

0.114 0.061 0.132 −0.569 −0.015 −0.300⁎⁎ 0.287⁎⁎ 0.174⁎ 0.271⁎⁎⁎ 0.204⁎⁎

0.006 0.027 −0.077 0.096 0.084 0.323⁎

−0.049 0.014 −0.061 0.073 0.039 0.313⁎

−0.029 −0.135 −0.171a −0.073 0.046 0.353⁎⁎

−0.040 −0.046 −0.040 0.091 0.035 0.277⁎

0.042 −0.015 0.165⁎

−0.027 −0.027 0.150⁎ 0.320⁎⁎⁎

−0.041 0.022 −0.060 0.094 0.038 0.267⁎ 0.039 −0.025 0.130a 0.279⁎⁎

−0.033 −0.147 −0.137 −0.029 0.047 0.315⁎⁎ 0.064 −0.013 0.134⁎ 0.173⁎

0.241a 0.208⁎⁎ 0.322⁎⁎⁎ 0.346⁎⁎⁎

0.028

0.184⁎

0.356 7.984⁎⁎⁎ 14.913⁎⁎⁎

0.279⁎⁎⁎ 0.410 9.705⁎⁎⁎ 22.890⁎⁎⁎

(Compared to Model 2a)

(Compared to Model 2a)

(Compared to Model 5a)

0.288⁎⁎⁎ 0.136 3.588⁎⁎⁎

0.239 5.690⁎⁎⁎

0.238 5.238⁎⁎⁎

−0.099 0.107 0.236⁎⁎ 0.208⁎⁎ 0.233⁎⁎⁎ 0.455 10.086⁎⁎⁎ 7.281⁎⁎

0.308⁎⁎⁎

0.025 0.041 0.187⁎⁎ 0.263⁎⁎⁎ 0.396⁎⁎⁎ 0.153⁎

0.125 3.335⁎⁎

0.212 5.015⁎⁎⁎

0.227 4.995⁎⁎⁎

0.356 7.983 18.133⁎⁎⁎ (Compared to Model 2b)

0.032 −0.076 0.094 0.175⁎

0.319⁎⁎⁎ 0.372 8.429⁎⁎⁎ 20.560⁎⁎⁎

0.309⁎⁎⁎ 0.161⁎ 0.084 0.268⁎⁎⁎ 0.438 9.475⁎⁎⁎ 9.827⁎⁎⁎

(Compared to Model 2b)

(Compared to Model 5b)

0.243⁎⁎

C. Lin, C.-C. Chang / Technological Forecasting & Social Change 90 (2015) 575–586

Table 3 Regression results.

C. Lin, C.-C. Chang / Technological Forecasting & Social Change 90 (2015) 575–586

Fig. 1. a. The moderating effect of absorptive capacity (financial performance). b. The moderating effect of absorptive capacity (innovation performance).

technological competences through alliances and informal networks to overcome challenges inherent in obtaining the desired technologies. Second, this study helps advance the importance of pursuing a broader technological scope by investigating its performance effect in the context of economic decline. More specifically, the conventional beliefs that are widely accepted in general can become controversial during the period of recession, so that it is the best of times to ascertain whether a firm's strategy is valid for all times. Our findings respond to the long-standing argument about the benefits of technological diversification. During recession, only those companies with diversified competences will thrive. From the above two arguments, the beneficial effect of technological diversification on firm performance in the large-sized manufacturing firms can also be observed worldwide. Samsung Electronics, the Korean manufacturing giant, is a typical case in the recent decade. By investigating Samsung's patent portfolio and performance in the 2000s, based on the first 3 digits of the UPC code, its patent classification increased from about 142 fields in 2001 to 189 fields in 2010; meanwhile its earnings per share accordingly rose from $15 in 2001 to $93 in 2010. The variety of products derived from the diversification of technological competencies also helped Samsung remain profitable during the 2008 financial crisis. More recently, according to the Worldwide

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Fig. 2. a. The moderating effect of environmental dynamism (financial performance). b. The moderating effect of environmental dynamism (innovation performance).

Intellectual Property Search's (WIPS) investigation, in order to gain footholds in the long-run, Samsung has spread its tentacles into various promising areas, such as solar cell, automobile battery, LED, bio-medicine and medical device. This case further confirms our findings that a firm's technological diversification not only affects firm performance but underpins the long-term growth opportunity of the business. Third, in terms of the contingency effect of absorptive capacity, our findings show that a firm's absorptive capacity has a positive moderating effect on the technological diversification-firm performance relationship. This finding reflects that a great level of absorptive capacity allows these large firms to harness the spillovers from pursuing their technological diversification, as well as to help relieve tension from multiple project implementations. The result also supports the argument that absorptive capacity is an important contingency factor that influences the subsequent exploitation of technological capabilities [48,75], thus indicating that absorptive capacity should be managed so that firms can derive the maximum benefits from their technological portfolio. Fourth, as Stock et al. [86] pointed out, large firms tend to be less responsive to environmental changes. In a dynamic environment, technological unpredictability and volatile customer demand can make specific technologies rapidly obsolete,

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and increase the demand for new technologies and products. Our finding demonstrates that a firm with a diversified technological portfolio can achieve better performance than one that focuses on a narrower technological field. This finding supports the argument that to sustain competitive advantages in a continually changing environment in which new knowledge emerges frequently, it is necessary for firms to invest in a variety of technologies to better serve the increasing complexity of products and production processes over time [7,30]. In addition to the risk-reducing effects of diversification, a firm with diversified technological competences is more capable of grasping the opportunities arising from environmental changes, and thus better able to achieve superior performance. The above findings not only enrich technology management literature but prove the belief that firms do not act in a vacuum. There are several practical implications that can be derived from these findings. First, the results show that technological diversification has a positive relationship with respect to performance in large firms. Managers in large firms should thus recognize that developing a broad technological portfolio is more likely to yield greater firm performance. The significance of technological diversification is particularly striking in technology-based industries, because there is often a mismatch between a firm's technological capabilities and its environmental conditions. However, as Quintana-García and Benavides-Velasco [9] suggest, diversifying a technological portfolio usually requires not only greater investment and patient support, but also information processing and integration mechanisms to ensure the integration of various technological solutions and projects. Second, managers should be aware that the relationship between technological diversification and firm performance can be intensified in specific contexts. The finding of the positive moderating effect of absorptive capacity further emphasizes that managers need to be aware of current and emerging technological developments. Absorptive capacity cannot only enhance knowledge acquisition and strategic variety, but also may homogenize incoming external knowledge, making it easier to combine with existing knowledge [87]. This also highlights the fact that efforts devoted to exploring external technological knowledge are helpful with regard to developing the potential of a firm's diversified technology pool, and worth continued investment. Furthermore, as environmental dynamism increases, firms are usually constrained by an imperfect and limited understanding of the environment within which they operate, and thus have difficulty in predicting the direction of technological change and identifying their technological capabilities. A diversified technology strategy allows firms to lower their commitment to specific technologies and to raise their adaptability to technology or market changes. Consequently, an increased understanding of the fit between technology strategy and environmental conditions is vitally important in an ever-changing environment. As with most studies, this work has some limitations, which provide some suggestions for future research. First, although our research demonstrates that technological diversification offers large firms an avenue through which to achieve better performance, and further clarifies some of the currently inconclusive results, this finding may not be generalizable to firms of all sizes. Future studies can be extended to consider

the performance effect of technological diversification on companies of different sizes, which may contribute to our understanding of this important issue. Second, the present study, along with many prior works on technology strategy, used patent information to assess technological diversification and innovation performance. However, this instrument does not capture every aspect of a firm's technology strategy and innovation performance. Some firms patent aggressively, while others intentionally avoid patenting and rely instead on trade secrets to protect their innovation or learning outcomes [88]. Likewise, patents serve different purposes in different industries, and have varied influences within them [89]. Additional research could employ other proxies, such as questionnaire surveys, to gain access to firms' innovation behaviors and performance. Finally, a firm's internal capabilities and external environment are multifaceted. Due to the scope of this study, we only examined the moderating effects of absorptive capacity and environmental dynamism. Future studies can further consider other contingency factors which may intensify, block, or confound the relationship between technological diversification and organizational outcomes. These limitations notwithstanding, we believe that these issues should continue drive research on technological diversification toward even better measures and more refined theory. Acknowledgments We are grateful to the editor and anonymous reviewers' valuable suggestions which greatly improved this article. Also, we thank Kuo-Yuan Lin for the research assistance, especially in data collection. References [1] N. Argyres, Capabilities, technological diversification and divisionalization, Strateg. Manage. J. 17 (1996) 395–410. [2] S. Breschi, F. Lissoni, F. Malerba, Knowledge-relatedness in firm technological diversification, Res. Policy 32 (2003) 69–87. [3] J. Suzuki, F. Kodama, Technological diversity of persistent innovators in Japan: two case studies of large Japanese firms, Res. Policy 33 (2004) 531–549. [4] C. Watanabe, J.Y. Hur, K. Matsumoto, Technological diversification and firm's techno-economic structure: an assessment of Canon's sustainable growth trajectory, Technol. Forecast. Soc. Chang. 72 (2005) 11–27. [5] O. Granstrand, Towards a theory of the technology-based firm, Res. Policy 27 (1998) 465–489. [6] M.J. Benner, M.L. Tushman, Exploitation, exploration and process management: the productivity dilemma revisited, Acad. Manage. Rev. 28 (2003) 238–256. [7] B. Leten, R. Belderbos, B. Von Looy, Technological diversification, coherence, and firm performance, J. Prod. Innov. Manage. 24 (2007) 567–579. [8] K. Gemba, F. Kodama, Diversification dynamics of the Japanese industry, Res. Policy 30 (2001) 1165–1184. [9] C. Quintana-García, C.A. Benavides-Velasco, Innovative competence, exploration and exploitation: the influence of technological diversification, Res. Policy 37 (2008) 492–507. [10] M. Subramaniam, M.A. Youndt, The influence of intellectual capital on the types of innovative capabilities, Acad. Manage. J. 48 (2005) 450–463. [11] A.O. Nielsen, Patenting, R&D and market structure: manufacturing firms in Denmark, Technol. Forecast. Soc. Chang. 66 (2001) 47–58. [12] K.H. Tsai, J.C. Wang, Does R&D performance decline with firm size? A re-examination in terms of elasticity, Res. Policy 34 (2005) 966–976. [13] C.C. Trumbach, D. Payne, A. Kongthon, Technology mining for small firms: knowledge prospecting for competitive advantage, Technol. Forecast. Soc. Chang. 73 (2006) 937–949.

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[87] B. Larrañeta, S.A. Zahra, J.L.G. González, Enriching strategic variety in new ventures through external knowledge, J. Bus. Ventur 27 (2012) 401–413. [88] S.W. Geiger, M. Makri, Exploration and exploitation innovation processes: the role of organizational slack in R&D intensive firms, J. High Technol. Manage. Res. 17 (2006) 97–108. [89] W.M. Cohen, R.R. Nelson, J.P. Walsh, Links and impacts: the influence of public research on industrial R&D, Manage. Sci. 48 (2002) 1–23. Chinho Lin is a Chair Professor of the Department of Industrial and Information Management & Institute of Information Management at National Cheng Kung University, Taiwan (ROC). He received his Ph.D. in business administration from the City University of New York. His works have been published in Information & Management, Decision Support Systems, Decision Sciences, European Journal of Operations Research, Omega, International Journal of Production Research, Journal of Operational Research Society, and other journals. His current research interests include knowledge management, supply chain management, quality and reliability management, and technology management. Chia-Chi Chang is a doctoral candidate at the Department of Industrial and Information Management & Institute of Information Management at National Cheng Kung University. She received MS in Public Health from National Yang-Ming University, Taiwan. Before joining the academic field, she served as a statistical analyst in Academia Sinica for two years. Her current research interests include industrial and technology management. She has published papers in Technovation, Industrial Management & Data Systems, and other journals.