Explicating Factors explaining. Organizational Innovation and its Effects

Transcription

1 Explicating Factors explaining Organizational Innovation and its Effects KOSON SAPPRASERT 1 Abstract This paper shows how the firm s decision on organizational innovation and its superior performance subsequence can be explained by firm age and size and other determinants. The integrated firm-level dataset obtained from the Norwegian CIS 3 & 4 (Community Innovation Survey) and annual accounts is used to analyze this complex relationship with an emphasis to explicate the issue on a resistance to the change of organizational routines or structural inertia. This study finds that age and size have distinct impacts on the odds that the firm goes about reorganization and on the effects from doing it. Older and larger firms are found to be more inclined to make an attempt on organizational change; while, concerning the outcome, their smaller counterparts benefit more from such an attempt. The results further demonstrate that different types of organizational change do foster firm s performance where even greater effects can be led by persistency in organizational innovation as well as complementarity between organizational and technological innovation. In addition, it is evidence that past economic performance and innovation cost influence the firm s decision on organizational innovation. Version of Keywords: Organizational Innovation, Age & Size, Structural Inertia, Firm s Performance, Complementarity, Persistency, Perception. JEL Classification: L25, O21, O39. 1 Centre for Technology, Innovation and Culture (TIK), University of Oslo & Centre for Advanced Study (CAS) at the Norwegian Academy of Science and Letters, correspondence: koson.sapprasert@tik.uio.no The author thanks Jan Fagerberg, Bart Verspagen, Giovanni Dosi, Tommy Clausen, Glenn Carroll, Ed Steinmueller, Ben Martin, Martin Srholec, Magnus Gulbrandsen and Issanee Kamlang for very good advice. All usual caveats apply.

2 1. INTRODUCTION Recent decades have seen a remarkably increasing concern on innovation among interdisciplinary scholars (see Fagerberg, 2004; Fagerberg and Verspagen, 2006; Fagerberg et al., 2008), arguably with a predominance of the technological aspect. Despite the great importance of organizational innovations, e.g., driving a number of economies to forging ahead and catching up at different points in time (Bruland and Mowery, 2004), technological innovations such as in terms of new or significantly changed products and processes, for instance through but not limited to R&D (Research and Development), have hitherto received more attention and been taken into account in a vast number of analyses in the area as mainly owing to the availability of statistics. Taking advantage of a novel dataset obtained from an integration of the firm-level Norwegian CIS 3 & 4 (Community Innovation Survey) and annual accounts, this paper endeavors to investigate how firms make their decision upon and benefit from organizational innovation, defined as a non- or less-technological, customary and institutional way of change in how the firm organizes the works. Innovation of this sort is regarded to be of crucial importance to the firm s survival and competitiveness as it has been one of the major factors accompanying certain key technological innovations enabling the firm s development and economic success (Chandler, 1962; Nelson 1991). However, organizational innovation can be greatly constrained by many factors such as, in particular, firm age and size associated with a high resistance to the change of organizational routines in the firm (Nelson and Winter, 1982), i.e., organizational rigidity or, to put in Hannan and Freeman s (1984) term, structural inertia. The study takes accounts of these critical age and size factors and other determinants in analyzing their impact on: (i) the firm s decision on attempting organizational innovation; and (ii) the consequence on its performance. The paper is organized as follows. Section 2 gives some notes on organizational innovation. Section 3 provides theoretical background and puts forward hypotheses. In section 4 data and method used in this study are presented. Section 5 discusses empirical findings from the analysis. Section 6 makes final remarks and concludes the paper. 1

3 2. SOME NOTES ON ORGANISATIONAL INNOVATION More than half a century ago Schumpeter (1934, 1950) gives a broad notion of innovation as the introduction of new products, new processes, new sources of supply, new markets exploitation and new ways of organizing business. 2 This holds valid in a modern time still especially in a majority of industrialized countries in which their certain national systems of innovation are composed of and significantly fostered by all these essential innovative changes (Freeman, 1987, 1995). Both technological and nontechnological aspects of innovation are of complementary importance (Chandler, 1962; Nelson 1991). The effort to innovate technologically will meet only limited success unless accompanied by the change of organizational kind and vice versa as they are considerably interdependent (Freeman, 1995). Thus, organizational innovation shall never be neglected, the sort of innovation that has been, together with certain key technological innovations, helping to escalate the firm s performance and growth in many leading and catching-up countries (such as the US, Germany and Japan) from the first industrialization through different business cycles (Schumpeter, 1939) or, to use Freeman and Louca s (2001) label, techno-economic paradigm. 3 A number of more recent evidences confirm that organizational innovation is yet crucial in our epoch as it also complements a key technological driver like Information and Communication Technology (ICT) and these complementary changes lead to the superior performance and growth of the firm (Bresnahan et al., 2002; Brynjolfsson and Hitt, 2000, 2003; Brynjolfsson et al. 2002; Sapprasert, 2007). It is important to flag here that organizational innovation in this sense does not refer broadly to the adoption of whatever novelty into the organization like that defined in, for instance, Damanpour (1991) and Sorensen and Stuart (2000). By organizational innovation, it is considered in this study in a more restricted manner dealing specifically with the implementation of new or significant changes in the firm s structure and management methods, 4 what often termed by researchers in management/organizational 2 See a discussion in, e.g., Fagerberg (2003, 2004). 3 See a discussion especially in Bruland and Mowery (2004). 4 This is largely corresponding to the CIS4 s definition of organizational innovation. See below. 2

4 studies (Evan, 1966; Daft, 1978; Damanpour, 1987, 1991; Kimberly and Evanisko, 1981; Teece, 1980) as administrative innovation as opposed to technical innovation (because of considering organizational innovation as innovation of any sort in the organization), or what Edquist et al. (2001) refer to as organizational process innovation (vis-à-vis technological process innovation ). Put another way, organizational innovation concerned here denotes an innovative change in the organization in a customary and institutional manner that is non- or relatively less technological and related more to the organizational nature, structure, arrangements, practices, beliefs, rules and norms, rather than to the technical facet (see, e.g., Pettigrew and Fenton, 2000). 5 As argued above, compared to the technological aspect of innovation, organizational innovation has received much less attention in the area of innovation studies. For instance, if one looks at the recent studies on the scholar s contributions in this field (Fagerberg and Verspagen, 2006; Fagerberg et al., 2008), one may observe that most of prominent works have been focused more on the technological dimension, whereas minimal studies have taken into consideration the importance of organizational innovation. This is in large part due to the availability of statistics. While technological innovation is widely examined on the basis of, e.g., patent and R&D data, how can one really measure a relatively intangible change like organizational innovation? Fortunately enough, a very recent fruitful attempt by the CIS allows this paper to contribute to this neglected side of innovation studies. A unique dataset based mainly on the new CIS information is exploited in this study to scrutinize the complex relationships between the crucial determinants such as firm age & size and the rate of organizational innovation as well as its consequence on firm s performance (see below). 3. THEORETICAL BACKGROUND AND HYPOTHESES One central evolutionary principle: organizational routines intrinsically exist as the fundamental ways of doing things in the firm (Nelson and Winter, 1982). As time goes by, some best practices or prevailing routines in the firm may be found less effective or 5 See also a discussion on the organizational innovation studies in, e.g., Lam (2004) and Sapprasert (2008). 3

5 even no longer acceptable as becoming obsolete, especially compared to what its competitors possess (Dosi and Nelson, 1994). A revolution is thus crucial (Romanelli and Tushman, 1994), i.e., old routines need to be replaced by something new before the firm is driven out of business. To survive and remain competitive in the dynamics of innovation, the firm has to search for a better solution and/or make some beneficial change in particular when its performance falls below its aspiration level or a new window of opportunity starts to open (Cyert and March, 1963; Greve, 2003). This is clearly of great importance to all firms, but due to a considerable heterogeneity (Nelson and Winter, 1982), a wide range of firms with diverse characteristics differ in how they decide on attempting routine change and benefit from such an attempt. This firm-level study, in line with Becker et al. (2005), applies the concept of organizational routine in understanding organizational change with a special focus on how essential intrinsic factors, firm age and size among others, influence the firm s decision on organizational innovation and its consequential effects. 3.1 Age, Size, Organizational Innovation and Effects Inertia theory (Hannan and Freeman, 1984) indicates inter alia that age and size are associated with strong structural inertia, the force that hinders organizational change. Inertia increases monotonically with age because having lived longer makes the firm s working relationships more formalized, routines more standardized and structure more stabilized (Kelly and Amburgey, 1991). Size instigates inertia because being larger makes the firm more rigid and inflexible (Downs, 1967). Inertia arisen from these attributes in turn makes the firm resistant to change (Carroll and Hannan, 2000). It is indeed conceivable that age and size generate structural inertia, a vital source of resistance to change. Considering further however, when looking separately at the relationships between age and size and: (i) the firm s tendency to attempt organizational innovation; and (ii) the subsequent outcome on firm s performance, these two organizational factors, as in addition containing some other properties, may have different influences on these two distinct but related issues (see Figure 1). <INSERT FIGURE 1 ABOUT HERE> 4

6 First, size and age typically come with some features that may be conducive to organizational innovation attempt. As Kimberly and Evanisko (1981) argue, firm size not only necessitates but also facilitates the firm s innovative behavior. Compared with their smaller counterparts, big firms might be more inclined to make change to their organization as they are generally in a better position; having a higher financial status and more resources. Put another way, since larger firms have a greater capability to innovate (Schumpeter, 1950), they are probably more ready and likely to do so. 6 As a managerial decision is fundamental to ways of doing things in the firm (Witt, 1998; Knott, 2001), the head of elephants may then have a strong tendency to innovate, arguably, not only technologically but also organizationally (Kimberly and Evanisko, 1981; Damanpour, 1987). Further, the reverse vis-à-vis inertia theory goes for age effect on a decision on organizational innovation attempt. In contrast to typical young firms that would remain working out their immature routines, dealing with many basic business operational issues commonly come about during their early life (such as maintaining cash-flow, formalizing relationships and so on) or paying attention more on innovating new products or processes, old firms can be expected to be relatively unoccupied, stable and ready to make some change, and thus more likely to undertake organizational innovation after having well established main routines, learnt most of necessary operational elements and accumulated much information and knowledge sufficient to be able to make a sound decision on reorganization. So a decision maker who plays a role as the head of experienced and mature old men may choose to take a chance to change too. This line of reasoning suggests that, although organizational age and size are often seen to be associated with inertia which often blocks structural change completely (Hannan and Freeman, 1984, p. 155), this is not always the case as it also depends on type of change (e.g., core vs. periphery), environmental dynamics and other conditions (Hannan and Freeman, 1984). It is possible that the same forces that make organizations inert also make them malleable (Amburgey et al., 1993, p. 51). That is, 6 There is a large body of literature on the so-called Schumpeterian Hypotheses dealing with the issue on how firm size matters for innovation (See, e.g., Scherer, 1980; Kamien and Schwartz, 1975, 1982; Cohen and Levin, 1989 for reviews). One standard justification from this Schumpeterian tradition is that larger firms have a greater propensity to innovate due to their better access to financial resource. 5

7 there exist some additional properties with regard to age and size, as discussed above, that could be in favor of the attempt on organizational change in which they are hypothesized to have a stronger impact: H1: Firm age increases the probability of organizational innovation attempt H2: Firm size increases the probability of organizational innovation attempt Second, from Hannan and Freeman s (1984) inertia theory, it is far from determinate how age and size are related to the outcome of organizational change in particular in terms of the effects on firm s performance. This paper argues that the inertial properties resisting firms to change, as pointed out by Hannan and Freeman (1984) to greatly exist in large and old firms, do in fact matter more for the change outcome. Put another way, age and size may actually be more disadvantageous when it comes to the effects of organizational innovation on firm s performance. As having lived longer, old firms are said to have more standardized routines and rigid structure (Stinchcombe, 1965, Hannan and Freeman 1984). They may then be more reluctant to unlearn past routines, less able to transform their structure and as a result have a higher probability to get stuck in a competency trap (Levinthal and March, 1993) or remain path dependent (Arthur, 1994; David, 1994). Therefore, as managerial authority to deliberately change is often subject to limits in practice (Leibenstein, 1987), aged firms in general may not substantially benefit from carrying it out after necessary change has been strategically initiated, unlike youngsters those are commonly adaptive as being less committed to the past. Likewise, the effects of organizational change might decrease with size that is commonly associated with the distance between decision makers and practitioners. And this distance between hierarchical layers is likely to vary plans or commands laid out by the former, therefore diminishing or diverging the expected performance of certain undertaking (Beckmann, 1977). In a large but lean organizational structure however, there typically exist a number of links among each unit, i.e., complexity (Simon, 1962), which can also hamper success of change. In addition, larger firms are usually confronted with greater internal political forces often come about as organizational members usually tend to maintain the status quo and thus behave 6

8 against organizational innovation (Pfeffer, 1992). These conditions result in ossification and inflexibility that as a consequence make large firms less prospective to significantly benefit from organizational change attempt. In this sense, the study seeks to explicate Hannan and Freeman s (1984) inertia theory by arguing that size and age, though as discussed above increasing the odds of change attempt, hamper the effects of organizational innovation on firm s performance: H3: Firm age decreases the effects of organizational innovation on firm s performance H4: Firm size decreases the effects of organizational innovation on firm s performance 3.2 Persistency and Complementarity A process of creative accumulation is considerably fundamental to the success of innovative firms since what has been learnt or experienced in the past would be propitious to certain innovation to be undertaken (Schumpeter, 1950). Firms learn to change by changing (as in conformity with learning by doing, see, e.g., Arrow, 1962; Nelson and Winter, 1982; Dosi, 1988). And having changed results in acquaintance with change or even makes it become a modification routine (Nelson and Winter, 1982; Aldrich, 1999). Put differently, prior changes lead to more knowledge and competence, and persistency, though not widely in existence (Geroski et al., 1997; Malerba and Orsenigo, 1999; Cefis and Orsenigo, 2001; Cefis, 2003), has thus a crucial influence on innovation process and performance of the firm. As business environment keeps shifting, the innovative firm needs knowledge and competence past accumulated to constitute capabilities to deal with it (Winter 1987; Teece and Pisano, 1994). In addition, it can be said in particular in the relatively less technical aspect in line with Hannan and Freeman (1984) and Amburgey et al. (1993) that organizational change resets the organizational clock, or in other words; it makes the firm new again as having altered routines, structure, role and relations. The firm that has changed earlier may then have its clock reset and become young again. This implies correspondingly to the foregoing hypothesis (H3) that having had reorganization before leads to the firm greater benefit from the ongoing organizational innovation: 7

9 H5: Organizational innovation persistency increases the effects of organizational innovation on firm s performance Further, as argued above, technological and organizational innovation are complementary factors driving firm s performance. Successful firms have through time shown to manage to succeed by not merely innovating technologically. A steam engine alone could not bring about better performance and growth in a vast number of industrializing firms a few centuries back. Nor can firms in the present ICT era simply plug in computers and thereafter achieve product/service quality or efficiency gains (Bresnahan et al., 2002). Change in the organizational aspect is in point of fact not less crucial and has been conducted jointly with technological innovation through time by the firm in the pursuit of superior performance (Bruland and Mowery, 2004), i.e., only limited success can be met unless technological and organizational innovation are carried out in conjunction as they are complementarily important (Chandler, 1962; Nelson, 1991; Freeman, 1995). This compulsory recipe generating complementarity effect thus suggests hypothesizing as: H6: Technological and Organizational innovation jointly increase the effects of organizational innovation on firm s performance 3.3 Perception: Performance Feedback and Obstacles To understand why firms (not) innovate is also one important item in the evolutionary agenda (Nelson and Winter 1982, Fagerberg, 2003). Just as sunglasses are worn when the sunlight is noticed, so do firms change in response to a wide range of problems perceived (Cyert and March, 1963). Low performance is a major one that induces the firm to make necessary change especially when the aspiration level cannot be achieved on the basis of current capabilities (March and Shapira, 1992; Greve, 2003). The idea that past failure drives change is herein accordingly applied (Levinthal and March, 1981; Greve, 1998), i.e., reorganization is expectable due to a decline in growth since a decision maker or firm would be inclined to take risk after having perceived an unpleasant performance feedback. Thus, it is hypothesized that: 8

10 H7: A decline in growth increases the probability of organizational innovation attempt The firm is also deemed able to perceive obstacles existing either internally ( weaknesses ; see, e.g., Penrose, 1959) or externally ( threats ; see, e.g., Porter, 1980, 1985) when it comes to a decision on whether or not undertaking innovation (Cyert and March, 1963; Kline and Rosenberg, 1986). As Mohr (1969) points out, a propensity to innovate is determined by not only a variety of motivations, but also the strength of obstacles to innovation and resources available to overcome such obstacles. For instance, the firm would commonly perceive innovation as a costly activity (Sirilli and Evangelista, 1998; Galia and Legros, 2004). This is particularly linked to a view on resource essential especially when a strategic plan for achieving competitive advantage is decided upon (Wernerfelt, 1984; Barney, 1991), e.g., low level of resources such as funds and skilled workers may explain why the firm has a limited tendency to implement or invest in making change. 7 In addition, since the consequences of changing can be said to be generally less foreseeable than the consequences of not changing (Greve, 1998), perception of obstacles would accordingly lead to the firm reluctance to attempt reorganization: H8: Perception of obstacles decreases the probability of organizational innovation attempt 4. DATA AND RESEARCH METHODOLOGY A unique firm-level dataset from an integration of annual accounts ( ) and the latest two waves of CIS from Norway, namely CIS3 ( ) and CIS4 ( ) that embrace a noteworthy emphasis on organizational innovation is employed in this analysis. 8 The dataset contains nearly two thousand firms in manufacturing, service 7 This is also in line with the argument above that resources commonly more available in large firms correlate with the rate of innovation. 8 The representativeness of the two datasets (CIS3 & 4) is deemed well sufficient as the resulting merger has an overlap percentage of greater than 30 percent. 9

11 and other industries in which more than one third of firms are reported to be active in organizational innovation (see Table 1 and discussion below). To examine the determinants and effects of organizational innovation, the models are constructed as follows: ORG = SIZE + AGE + IND + PASTORG + PASTPERF + HAMPi (1) EFORG = SIZE + AGE + IND + PASTORG + INCOMP (2) ORG = A dummy for the presence of organizational innovation EFORG = Factor score for six types of effects of organizational innovation SIZE = Firm size in terms of number or employees (LogEmp) and turnover (LogTurn) AGE = Firm age (log value) IND = A dummy for industrial classifications (NACE) PASTORG = A dummy for past attempt on organizational change ( ) PASTPERF = Past performance in terms of profitability growth ( ) HAMPi = Hampering factors (value from 0-3) INCOMP = A dummy for joint contribution of technological and organizational innovation ( ) As only the firms attempted organizational innovation were allowed to answer the question in the CIS 4 on its effects that follows, the sample selection problem potentially comes about. The Heckman s (1979) two-step estimation thus seems most appropriate to be applied in order to correct possible selection bias (see, e.g., Zucker et al., 1998; Hall, 2002; Catozzella and Vivarelli, 2007), which may arise when it comes to an analysis of the effects of organizational innovation in the second stage (non-organizationally innovators excluded from the second-step regressions). 9 In this respect, the first equation explains whether, and the extent to which, firm size and age and other determinants have 9 Since the results show no sign of selection bias, the OLS estimation is also used in the second stage experiment. Three types of organizational innovations (ORGSYS, ORGSTR are ORGREL) are added in order to examine their potentially distinct impacts. See below. 10

12 impacts on the firm s decision to undertake organizational innovation while the second further examines how these factors affect the outcome of such undertaking. The variables of interest in this Heckman two-step procedure are organizational innovation, its effects, firm size, firm age and other relevant factors. First, organizational innovation (ORG) employed as a dependent variable in the selection equation (Stage 1) is obtained from the answers to the question in the CIS4 asking whether the firm has introduced organizational innovation defined as an implementation of new or significant change in firm s structure or management methods aiming at the improvement upon firm s use of knowledge, quality of goods or services, or work flows efficiency. The question asks whether or not this has been done in three respects which are: (i) new or significantly improved knowledge management system implemented to better use or exchange information, knowledge and skills within the firm (ORGSYS); (ii) major change to the organization of work within the firm, such as change in the management structure or integrating different departments or activities (ORGSTR); and (iii) new or significant change in the firm s relations with other firms or public institutions, such as through alliances, partnerships, outsourcing or sub-contracting (ORGREL). On the basis of these three proxies, a dependent variable ORG for Stage 1 (Probit) is constructed. ORG equals one if the firm has a positive answer for at least one of the foregoing three aspects of organizational innovation, and zero otherwise. The variable used to assess the impact of organizational innovation is then built on the subsequent question that inquires about various types of effects from such attempt. As mentioned above, only the firms that have carried out organizational innovation, i.e., having at least one positive answer to sub-questions in the preceding question (ORG = 1), shall also respond to this next question on its effects. This question asks the firm to rate (from 0 3) the importance of six types of organizational innovation s effects which are: (i) reduced response time to customer needs; (ii) improved quality of goods or services; (iii) reduced costs per unit output; (iv) improved employee satisfaction and/or reduced employee turnover; (v) increased enterprise s capacity; and (vi) higher enterprise s profitability. Factor scores (EFORG) for these six measures are calculated (see Table A.1 in the Appendix) and used as a dependent variable in the outcome equation (Stage 2) in 11

13 order to examine how the effects of organizational innovation are influenced by the explanatory factors discussed hereafter. Two variables of major concern namely firm size and age assumed to have distinct impacts on the firm s decision on organizational change attempt and the subsequent effects are taken into account in both equations. Research in organizational ecology (see, e.g., Hannan and Freeman, 1984; Carroll and Hannan, 2000) shows that both age and size should essentially be taken into consideration when analyzing structural inertia and organizational change. In doing so, as Penrose (1959) suggests, they shall be considered as separate determinants of innovation since aged firms are not necessarily large, and vice versa. 10 The study therefore applies this approach. Firm age (LogAge) is calculated using a log value of the period between the year the firm was established and the last year before entering the period concerned ( ). Firm size is measured on the basis of information on the number of employees (LogEmp) and firm s total turnover (LogTurn) in Having both of these proxies would be advantageous since they possibly explain firm size in different dimensions. That is, while LogEmp deemed to be more related to a scale of human resource might better depict a degree of complexity/hierarchy of the firm s structure, LogTurn represents size of firm in terms of financial capacity. A simple correlation test conducted shows that turnover does not necessarily strongly correlate with number of employees (see Appendix). Industrial classifications (IND) and past organizational change (PASTORG) dummies are also employed in both Stage 1 & 2. The former, as commonly applied, shows how industrial characteristics may affect the firm s propensity to innovate as well as the effects. The uses of the latter variable (PASTORG) are twofold. In the first stage, it implies how the presence of organizational change in the past triggers another attempt by the firm in the subsequent period ( ). Second, PASTORG is used in the outcome equation to further show whether and the extent to which prior and current changes together (organizational innovation persistency from ) increase the 10 See Table A.2 in the Appendix for a correlation test between firm age and size (in terms of both total turnover and number of employees). 12

14 effects of organizational innovation in the period concerned. 11 PASTORG has a value equal to one if the firm has during introduced change in at least one of the following types: corporate strategies; management techniques; and organizational structures. Further, two additional variables (PASTPERF & HAMP) hypothesized to influence the firm s decision to carry out organizational innovation (ORG) are included in the selection equation (Stage 1). PASTPERF is a measure for the recent change in firm s performance (that may induce the attempt on organizational innovation) in terms of profitability growth ( ). HAMP represents three types of hampering factors, which are high innovation cost, lack of funds and lack of qualified personnel. These three proxies are constructed using information obtained from the question that asks the firm to rate (from 0 3) the importance of different hampering factors. 12 Finally, a dummy for product and process innovations (INCOMP) in the current period ( ) is used as a measure for the joint contribution of technological and organizational innovation in the outcome equation (Stage 2). 13 This variable representing their complementarity effect on firm s performance equals one if the firm has introduced at least one innovation of this technical sort (product/process) during ANALYSIS First of all, a descriptive picture in Table 1 shows that more than one third of firms in the sample are organizational innovators (having introduced at least one type of organizational innovation), with a larger share of those considered to be large in terms of either total turnover or number of employees (supporting H1) whereas it is less clear-cut and yet to be further examined whether age monotonically increases the rate of 11 A dummy for past organizational change (PASTORG) is simply used as a measure for organizational innovation persistency because in the second stage all firms included have introduced at least one type of organizational innovation in the present period These three variables assumed to influence a decision to innovate are selected based on their relevance to innovation in the organizational aspect, significance in different models tested and results concerning uniqueness from a factor analysis (not reported here). 13 Since all uncensored firms in the second equation are organizational innovators, a technological innovation dummy shall be deemed an appropriate measure for complementarity. 13

15 organizational change (H2). The results from Table 1 also indicate that, with small exceptions in large and old firms, the likelihood of change varies negatively with its intensity. In other words, the greater the number of types of organizational innovation considered, the lower the percentage of organizational innovators. And for the three types taken accounts of, a change in the firm s structure (ORGSTR) appears to be most widely introduced, followed by changing in the firm s knowledge management systems (ORGSYS) and in the firm s external relations (ORGREL), respectively. <INSERT TABLE 1 ABOUT HERE> Table 2 continues with more descriptive evidence beyond organizational innovation in the present period ( ). It demonstrates that more firms in the previous period (more than fifty percent in ) had carried out organizational change and, more importantly that, as opposed to the prior innovation persistence studies in the technological aspect (see, e.g., Geroski et al., 1997; Cefis and Orsenigo, 2001), a relatively impressive number of Norwegian firms are persistent in organizational innovation (about 23 percent from ). However, the results show that technological innovation (product/process) is of greater concern of firms in the dataset (0.47 versus 0.35 percent of 1737 firms reported to be technologically and organizationally innovative, respectively). When comparing across sector, not surprisingly, more manufacturing firms engaged in technological innovation while more service firms are found to be active in organizational innovation. 14 Finally, despite no sharp effect from firm age, larger firms are reported to be more persistent in organizational innovation and highly innovative in both organizational and technological aspect (Kimberly and Evanisko, 1981; Damanpour, 1987). <INSERT TABLE 2 ABOUT HERE> 14 As usually argued in the literature on service innovation (see, e.g., Evangelista, 2000; Miles, 2004, Sapprasert, 2007), non-technological and intangible characteristics of services are very significant and relatively linked to the importance of organizational change. 14

16 Next is to discuss further several issues concerned on the basis of results from the econometric analysis (see Table 3). This shall be done in two steps (for selection and outcome equation). Starting with looking at the determinants of organizational innovation (Stage 1), the results thoroughly support H1 such that firm age remarkably increases the chance of reorganization attempt. The coefficient between firm age (LogAge) and the dummy for organizational innovation (ORG) is positive and statistically significant. Although H2 on the positive size effect on the change attempt is not confirmed in the econometric part, 15 the evidence in Table 3 corroborates the descriptive results by depicting fairly high significance in organizational innovation persistency. Firms those made prior change attempt ( ) are very likely to do it again in the subsequent period ( ). This can be seen from the significant positive coefficient between the dummy for organizational innovation in the previous and current period (PASTORG and ORG). H7 is also supported by the econometric results in this part. Table 3 illustrates the firm s behavior in relation to the past performance (Cyert and March, 1963; Greve, 1998). That the decision to attempt organizational innovation is likely to be induced by a decline in profitability growth ( ), or in other words; it is evidence that one way the firm solves the profit problem perceived is to go about reorganization. The coefficient between these two variables (PASTPERF and ORG) is negative and statistically significant. Nevertheless, only high innovation cost is found in supporting H8 to be what perceived by the Norwegian firms as the obstacle to organizational innovation (HAMP). 16 <INSERT TABLE 3 ABOUT HERE> Emphasis hereafter is placed on the effects of organizational innovation in the second stage of econometric analysis. Since no selection bias at all appears (insignificant 15 Firm size is however consistently reported to positively influence organizational innovation in the descriptive part. See Table 1 & This result is in contradiction with that from Veugelers and Cassiman (1999) using Belgian manufacturing firm data. They find that high innovation cost the firm perceives does not discourage innovation. 15

17 Mills ratio in all models considered), the results from both the Heckman s outcome equation (Stage 2) and OLS (Ordinary Least Square) estimations are reported and discussed (Table 3). First, H3 is not supported in both models. Despite a negative sign, firm age does not seem to have a significant impact on how well firms can benefit from organizational innovation. 17 However, the study finds in conformity with H4 (OLS model) that firm size in terms of both number of employees (LogEmp) and total turnover (LogTurn) decreases the extent to which reorganization affects firm s performance (EFORG). 18 This negative relationship can be seen from the coefficients between these variables in the OLS estimation. Further, the complementarity effect as hypothesized in H6 is confirmed in both models. The significant positive coefficients between the proxy for complementarity (INCOMP) and organizational innovation effects (EFORG) show that technological and organizational innovation play a complementary role in boosting firm s performance, i.e., a joint contribution between changes in both technological and organizational aspect is crucial and leads to a superior performance outcome (Chandler, 1962; Bruland and Mowery, 2004). Next, evidence from the Heckman s outcome equation supports H5 predicting a positive relationship between organizational innovation persistency (PASTORG) and its effect on firm s performance (EFORG). 19 The significant positive coefficient between these two variables implies that the firm can benefit more from organizational change by carrying it out more persistently. Finally, the OLS results show with no bias that, not surprisingly though, firm s performance shows significant sign of being fostered by different types of organizational innovation. That happens to be to a different extent. 20 The Norwegian firms received 17 Nonetheless in a detailed analysis (results not reported here), firm age is found to have a significant negative influence on one type of organizational innovation effect that is improved goods/services quality. 18 The sign remains, though insignificant, negative concerning the results from the Heckman s models. The coefficients for firm size and most types of organizational innovation effects are also confirmed to be significantly negative in a detailed OLS analysis (results not reported here). 19 The same sign is though maintained in the OLS estimation. 20 The results (not reported here) from a detailed analysis on different effects (6 types as dependent variables one at a time) from these three types of change also go along the similar line with the evidence discussed here using the factor scores (EFORG). 16

18 considerable benefit to a higher degree from change in the firm s structure (ORGSTR), knowledge management systems (ORGSYS) and external relations (ORGREL), respectively MAJOR FINDINGS AND CONCLUDING REMARKS Using a novel dataset based on an integration of the latest two waves of firm-level Norwegian CIS ( and ) and annual accounts, this paper endeavors to explicate the determinants of organizational innovation and its effects on firm s performance. The paper argues that organizational innovation is greatly constrained by many factors, in particular, firm age and size associated with a high resistance to the change of organizational routines (Nelson and Winter, 1982), the socalled structural inertia (Hannan and Freeman, 1984). Taking accounts of inter alia these two crucial factors, the study attempts to elucidate and extend the inertia theory by showing that size and age have distinct impacts on the firm s decision to carry out organizational innovation and on its performance outcome. Put another way, though it is widely accepted that firm size and age do instigate firm s inertia, it is also and even more important to know how such inertia differently matters for a decision on organizational innovation and its effects. In this respect, the Heckman s (1979) two-step estimation is applied since only organizational innovators, i.e., firms those have at all undertaken organizational innovation, are included in both selection model (that explains the firm s decision) and outcome model (that explains the effects of organizational innovation) whereas nonorganizational innovators are taken into consideration in the former but censored from the latter in which they have no information for (on the effects). This means that for the dataset used in this study containing nearly two thousand firms in manufacturing, service and other industries, about one third of these firms reported to be organizationally innovative are selectively included in the second-step analysis of the organizational innovation s effects. 21 In trying to explain this evidence, one may interpret this difference as a result of the difference in type of change (e.g., core versus periphery). See, for instance, Hannan and Freeman (1984). 17

19 The major findings shed light on the complex relationships between organizational innovation, its effects, firm age, firm size and other determinants. First, firm age, while having no significant influence on the effects of organizational innovation, 22 is a consistent factor explaining the attempt on doing it. The study finds that, compared to those younger, older firms tend to innovate more not only technologically, but also in the organizational aspect. In addition, there appears a sign of organizational innovation persistency of the Norwegian firms, i.e., firms those that attempted organizational change before (in the period ) are quite likely to do it again in the subsequent period ( ). The results also reveal the firm s behavior in relation to how the decision on organizational change is made. A decline in growth is one reason for that. The study finds this performance feedback influential when it comes to the firm s propensity to innovate organizationally. On the other hand, high cost of innovation is evident to be what the Norwegian firms perceive as an obstacle to organizational innovation. Although the descriptive picture illustrates that a greater percentage of large firms are organizational innovators, it is not very clear from the regression results how firm size matters for the decision on undertaking organizational innovation, as Cohen and Levin (1989, p. 1069) point out, the most notable feature of this considerable body of empirical research on the relationship between firm size and innovation is its inconclusiveness. However, the study finds that firm size does matter for the effects of organizational innovation undertaken, that is, due to less rigid structure and political forces, i.e., flexibility, smaller firms benefit more from organizational change. Furthermore, firms do well out of different types of change and the effects appear to be strengthened by organizational innovation persistency and complementarity between technological and organizational innovation, i.e., firms can better reap the fruits of reorganization by doing it more persistently and jointly with technological innovation Carroll and Hannan (2000) also find this age dependence yet a very complicated issue. 23 From all estimations carried out, industrial heterogeneity does not however appear to have any significant influences on the firm s decision on organizational change and its effects. 18

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