Which of the Following Strategies Can Help Businesses Foster Innovation?

INTRODUCTION

i To what extent is innovation compatible with strategy formalization in small firms? Researchers have led an indecisive debate over the claim and drawbacks of formalization pertaining to innovation strategy. On the one hand, formalization seems to hamper creativity and improvisation capabilities that are crucial to innovation (e.g., Chua, Roth & Lemoine, 2015; Miner, Bassoff & Moorman, 2001). On the other hand, strategy formalization may exist fundamental to innovation as it involves a general clarification of the firm's objectives, a ameliorate analysis of competitors, and a general contribution to organizational learning (eastward.thousand., Sirén & Kohtamäki, 2016; Vlaar, Van Den Bosch & Volberda, 2006). Recent studies take increasingly demonstrated that, despite criticism, strategy formalization in the form of strategic planning (or business plans) could have a generally positive affect on house performance, including in small firms (Burke, Fraser & Greene, 2010; Delmar & Shane, 2003). Nonetheless, innovation is notwithstanding propitious to face the advantages and disadvantages of strategy formalization (Vocal, Im, Van Der Bij & Song, 2011). Furthermore, SMEs' frailty maintains doubt over the possible implementation and bear upon of strategy formalization, even though some recent studies accept contended the possibility for such firms to take reward of formalization equally well (Dibrell, Craig & Neubaum, 2014; Song & Chen, 2014).

2 The purpose of this study is to enrich our understanding of strategy formalization in the innovation process. Our primal supposition is that the contend over the advantages of formalization may have been misleading in that we do not know the conditions nether which strategy formalization may be beneficial to innovation. In this research, we draw primarily on open innovation literature and argue that formalization is a means of benefiting from openness. Innovation scholars take demonstrated the importance for firms of capturing noesis and resource across their organizational boundaries to nurture their own innovation process (Chesbrough, 2003; Cousins, Lawson, Petersen & Handfield, 2011). This openness implies that external stakeholders are progressively involved in a network of relationships that the firm has to manage (Salter, Criscuolo & Ter Wal, 2014). In this regard, SMEs are concerned that increased openness will sometimes stretch already limited resources (Bianchi, Campodall'Orto, Frattini & Vercesi, 2010). Moreover, a key consequence of openness is that the influences, exchanges, and decisions involved become increasingly circuitous for the house, and firms must deal with this complexity while negotiating with stakeholders who get increasingly involved in the strategy procedure (Oberoi, Haon & Freitas, 2014).

3 In order to justify how formalization may help to leverage open innovation strategy, we combined open up innovation with a "socio-material" perspective equally a secondary theoretical groundwork. This perspective allows us to consider formalization as a technology: Organizational space includes both cloth and symbolic artifacts that are constitutive of collective action (Clegg & Kornberger, 2006). Plans, matrices, procedures, and reports are not socially inert simply are occasions for actors to collaborate, confront diverging views, and foster commonage thinking. In this view, formalization presents an opportunity to leverage the many implications of actors that open innovation entails. Information technology offers a technology to foster commonage thinking almost strategy and to simultaneously favor gathering. Because formalization is an opportunity to organize information flows, discuss with partners, and legitimate the choices of organization (Fernhaber & Patel, 2012; Sivadas & Dwyer, 2000), nosotros contend that strategy formalization might be of particular importance in the presence of open up innovation strategies.

4 Therefore, this paper explores the leveraging influence of formalization on open innovation strategies. More than precisely, nosotros investigate the possible positive interaction between openness and formalization on innovation performance. Using a unique information set of SMEs that were questioned on their strategy process, we explore the influence of formalization in 2 facets, namely process (referring to the efforts of description and articulation of strategy) and tools (which include common matrices, scenarios, methods, or competitive assay). Our empirical findings support the general contention of a moderating upshot of formalization. Consistent with the socio-material approach, the findings mean that even SMEs can take advantage of formalization in open innovation processes. Therefore, our study supports an increased legitimacy of conventional strategic tools to foster innovation.

5 The remainder of the paper is divided into four parts. The first part is dedicated to theoretical development, in which nosotros develop the rationale for blending open innovation and socio-material perspectives when studying formalization. The second part presents the data set and the descriptive statistics of the variables used. In the third function, nosotros particular the exploration, modeling strategy, and analysis of potential interactions between the variables of interests, earlier we depict conclusions from model testing. In the fourth part, we talk over the implications of our work in calorie-free of previous studies.

THEORETICAL Groundwork

INNOVATION IN SMES

vi Central to innovation is the search by firms for knowledge, particularly in the context of SMEs (Hervas-Oliver, Sempere-Ripoll & Borona-Moll, 2014). Innovation may be conceived as the outcome of a cosmos, absorption, and recombination of technological ideas (Katila & Ahuja, 2002). Accordingly, the literature has developed the argument that firms should rely on external cognition to introduce. In this vein, open innovation is a seductive term, coined by Chesbrough (2003), that enjoys some convergence in recent innovation studies. It refers to "the utilise of purposive inflows and outflows of noesis to accelerate internal innovation, and aggrandize the markets for external use of innovation, respectively" (Chesbrough, Vanhaverbeke & West, 2006: 1). The concept reflects the full general idea that innovation is distributed both within and outside the firms in terms of available ideas, embodied noesis, and know-how. Indeed, innovation had been viewed initially equally an internal process, involving a focus on resource allocation inside the boundaries of the firm. However, many studies have emphasized the role of external sources of knowledge to nurture the innovation process (east.g., Beers & Zand, 2014). In fact, firms may make their innovation open past undertaking a large fix of activities with external actors. Therefore, the focus on openness reflects a wider trend to consider the importance of relationships betwixt the firm and its environment (Laursen & Salter, 2006). The innovation project follows a funnel that is permeable in that some actors may go out whereas others may bring together. As such, the innovation process implies a web of complex relationships betwixt stakeholders (Dittrich & Duysters, 2007). To date, studies focusing on innovation openness accept been empirically successful, passing the test of replication (e.1000., Garriga, Von Krogh & Spaeth, 2013). Firms adopting open innovation strategies have more than chance of developing an innovation too as attaining college turnover as a result of that innovation.

7 Exactly what constitutes an open innovation do varies, according to the relevant authors. All the same, inter-organizational cooperation and involvement of external stakeholders are frequent indicators (e.one thousand., Laursen & Salter, 2014; Oberoi, et al., 2014). Both denote active behaviors to redirect external resources toward the firm's innovation process. Nonetheless, authors stress the differences betwixt minor and large firms. For small-scale firms, open up innovation strategies are motivated by dissimilar rationales than for large firms (Wynarczyk, Piperopoulos & McAdam, 2013). Small firms seldom expect for scale economies but rather seek to bargain with resource scarcity and uncertainty. The arrival of noesis is prevalent when SMEs' stakeholders get involved. In this logic, strategic alliances and relationships with external actors are crucial for SMEs. This echoes the general importance of contractual relationships, ties with stakeholders, alliances, and joint ventures (Han, et al., 2012). Furthermore, open innovation strategies exhibit specific challenges for SMEs. Indeed, they require that firms allocate attending that is intrinsically bounded (e.chiliad., Dahlander, O'Mahony & Gann, 2016). Profiting from openness, therefore, entails organizational requisites and constraints that only some firms can meet. Consistent with this argument, empirical findings tend to demonstrate that small firms are constrained in open up innovation strategies, while openness is as important for them equally information technology is for big firms (Spithoven, Vanhaverbeke & Roijakkers, 2013). Van De Vrande, De Jong, Vanhaverbeke, and De Rochemont (2009) prove that SMEs accept increased their action in open innovation with inbound open innovation being far more diffused than outbound open innovation.

STRATEGY FORMALIZATION As TECHNOLOGY

eight Practitioners and scholars have suggested a variety of tools and methods that the firms had to implement to increase the likelihood of innovation success. However, the role of these tools and procedures remains in question. This relates to the full general influence of formalization on organizational performance, which has given rise to a long-lasting fence. At a full general level, formalization refers to the employ of explicit rules, procedures, and behaviors (Sivadas & Dwyer, 2000; Vlaar, et al., 2006). For decades, researchers accept sought to determine whether it improved or impeded organizational performance, including innovation.

9 A classic, cardinal assumption is that formalization is likely to exhibit benefits likewise as drawbacks (Prajogo & McDermott, 2014; Vocal, et al., 2011). On the ane mitt, strategy formalization helps to deal with ambiguity in promoting consensus and legitimacy of strategic orientations (Abdallah & Langley, 2014; Grant, 2003). It also helps to make projects explicit and fosters deliberations within the firm (Sivadas & Dwyer, 2000). It thereby clarifies organizational processes (Song, et al., 2011) and acts as an integrative device (Ketokivi & Castañer, 2004). Consistent with this argument, some researchers have found that business organisation plans increased the performance and survival of new ventures (Burke, et al., 2010; Delmar & Shane, 2003). Dibrell, et al. (2014) fifty-fifty found a directly and positive issue of formal strategic planning on firm innovativeness.

10 On the other hand, post-obit Mintzberg (1994), researchers have underscored the potential negative effects of formalization on innovation. Considering innovation induces novelty, it might disharmonize with a strict compliance to organizational rules and procedures (Avadikyan, Llerena, Matt, Rozan & Wolff, 2001). As such, innovation might impede innovation because it forces teams working on new products to develop convergent thinking (Im, Montoya & Workman, 2013). Consistent with this statement, Song, et al. (2011) find that the number of new production development projects decreases every bit strategic planning increases, thus claiming a negative relationship betwixt strategy formalization and innovation. Furthermore, strategic planning is believed to develop an illusion of control among superlative direction teams, which is detrimental to risk assessment (Titus, Covin & Slevin, 2011).

11 To deal with these conflicting views, some scholars proposed to develop new approaches under the umbrella term "socio-materiality." A central tenet of socio-material approaches is to consider that organizational infinite includes textile and symbolic artifacts that are constitutive of collective activity (Clegg & Kornberger, 2006). In this regard, the socio-material perspective aims at providing a improve agreement of technologies in organizations (Orlikowski & Scott, 2008). Early studies considered technology in a narrow sense. Progressively, researchers widened the scope to cover technology every bit any means "designed by organizations to steer individuals and objects toward assigned goals" (Moisdon, 2006).

12 Through socio-textile lenses, direction tools and techniques are seen as technology to promote organizational functioning. They include technological substrate in the form of blueprints, strategic matrices, or written procedures. All the same, their use is continuously reconfigured by actors. Based on that rationale, socio-material scholars insist on the fact that artifacts are not separable from activity and discourse to sympathize practices (Cecez-Kecmanovic, Galliers, Henfridsson, Newell & Vidgen, 2014). Material artifacts and their utilize are so intertwined that a argue has arisen to determine whether the two are conceptually distinct (Balogun, Jacobs, Jarzabkowski, Mantere & Vaara, 2014). In any case, socio-cloth approaches abet that the social and the material are entangled to constitute an aggregation (Orlikowski & Scott, 2008).

thirteen Ane important contribution from the socio-material literature is that it explains how novelty is possible with technology. In the long term, technology and organizational routines transform each other. Sele and Grand (2016) emphasize that procedures generate opportunities by connecting organization members who may try to use and alter them. From this signal of view, routines can trigger innovation outcomes and are generative in nature. Engineering science influences practices, through technical substrate (in the grade of material artifacts) and through managerial philosophy. Technical substrate, organizational models, and managerial philosophy are not necessarily distinct but institute a theoretical "whole" (Labatut, Aggeri & Girard, 2012).

14 Building on this perspective, we depict two major conclusions. Starting time, we consider strategy formalization equally technology, which may be conceived as an entangled assemblage of technological substrate and managerial practice. Information technology thus embodies "strategic tools" in the form of matrices, checklists (Wright, Paroutis & Blettner, 2013), documents, blueprints, and reports. At the same time, it comprises endeavors to submit strategic choices to rules, procedures, and standards to make them explicit and controllable. Equally such, it includes non only "strategic planning" (Dibrell, et al., 2014) just also "concern planning" (Burke, et al., 2010) or "deliberate" strategy (Titus, et al., 2011). Therefore, it is possible to conceive strategy formalization both as a procedure and a set of artifacts.

15 Second, nosotros build on the potent assumption that the utilise of technology may be generative in nature. Strategy formalization does not contradict innovation because it creates opportunities, in the long run, for a cross-transformation of technology and routines. Therefore, the focus shifts to a better depiction of the conditions under which formalization may be beneficial to the firm.

OPENNESS AND FORMALIZATION

16 Considering formalization as a engineering in practise allows looking beyond the apparent tension between formalization and innovation. In item, it sheds light on the potential reinforcement of open innovation strategies. To this end, we emphasize two "roles" or "functions" that formalization may fulfill with respect to open up innovation strategies.

17 Integrative office. Firms relying on external sources of cognition demand internal capabilities to digest and organize incoming flows. To this end, they must align their internal processes to the external environment (Laursen & Salter, 2014). For many SMEs, this proves to be a substantial claiming due to scarcity of resource (Brunswicker & Vanhaverbeke, 2015). SMEs too face cumulative learning difficulties that involve entry barriers in new markets (D'Este, Iammarino, Savona & Von Tunzelmann, 2012) and, arguably, this combines with the lack of management procedures. Thus, these firms need tools to leverage open innovation. In this situation, formalization may act every bit a device to bring together disparate strategic visions. Formalization thus "affords" (Jarzabkowski & Compression, 2013) disciplined collective thinking. Matrices, strategic tools, or business concern plans do not solely invite ane to fill in blank cells in tables; they also indirectly promote contend and discourse about strategy. They provide opportunities for meetings and interaction whereby actors adjudicate different interests (Kaplan, 2011). Put differently, artifacts may exist considered as a "boundary object" providing a locus for negotiation (Yakura, 2002). Through this process, an organizational discourse is elaborated inseparably from the engineering science in utilize. Undoubtedly, technology also has constraints besides affordances (Faraj & Azad, 2012). However, both affordances and constraints of engineering are a relational attribute: Dissimilar people will perceive different uses and limitations of formalization. For that reason, firms might develop their own approach to formalization and be creative in an original fashion.

xviii Analytical function. One of the master limitations of open innovation strategy lies in attention shortcomings (Dahlander & Gann, 2010). Open innovation involves a higher number of partners and projects for the business firm to organize (Dittrich & Duysters, 2007). Because individuals tin but focus on a few tasks at whatsoever given moment, greater openness in the grade of numerous sources of knowledge becomes harder to assimilate. Moreover, external stakeholders in open innovation come up to gain partial influence over organizations' strategy though their interest (Oberoi, et al., 2014; Salter, et al., 2014). From this viewpoint, formalization represents an opportunity to deal with attending and cerebral limitations in open innovation settings. Documents, charts, meetings, and exchanges over strategy definition represent opportunities to analyze stakeholder expectations and make sense of their participation in the innovation process. Formalization thereby facilitates heterogeneous discourses and viewpoints together, just too fosters reflection that, in plow, results in artifacts and discourse. It may help to relax cognitive bias shortfalls and contribute to sense-making among managers (Vlaar, et al., 2006). As such, the attention of managers is fatigued to opportunities that would otherwise have gone unnoticed (Barnett, 2008). Therefore, strategy tools and artifacts provide discursive and cognitive resource that shape strategy work (Balogun, et al., 2014) and, in this mode, assist to implement practices for the structure of significant among the participants (Kaplan, 2011). Knowledge produced in this manner does non necessarily match the aforementioned requirements as that in science fields. Notwithstanding, practices with tools tend to promote legitimate knowledge reflecting stakeholders' views.

RESEARCH QUESTION

nineteen In a nutshell, the research question we address could be formulated in these terms: "Can we say that formalization improves the affect of open up innovation strategies?" From what nosotros have seen above, it follows that formalization could be specially suitable for firms that undertake open innovation strategies. In other words, a reasonable hypothesis is that strategy formalization improves the success of open up innovation strategies. In modeling terms, formalization may act as a positive moderator of the influence of openness on success. In this research, we propose to investigate this supposition through an explorative protocol. We build a serial of models derived from the general hypothesized model. Nosotros justify this option as follows: Both "openness" and "formalization" can exist understood in different ways. Therefore, nosotros detect it more relevant to make a main hypothesis a guideline and to explore the diverse dimensions of the constitutive variables of the model.

Figure 1

Relationships investigated in the written report

Formalization
Artifacts Practices
Tools Processes
Openness Innovation
Cooperation Likelihood
External stakeholders Intensity

Relationships investigated in the study

xx Figure 1 (above) depicts this research question, recalling the various facets of the concepts. Formalization is considered both under antiquity and organizational practice facets. Openness is noted in its two frequent forms, namely cooperation and external stakeholders' implication [ane]. In the next department, we describe in detail the method used to investigate possible answers.

METHOD

21 Our enquiry procedure relied on amassing two databases. The showtime 1 is the DIANE database, defended to financial information well-nigh French firms. As such, it presents official accounting data, especially fiscal statements, that firms are legally jump to declare every year. The 2d is the "Plan-PME" database, specifically created to conduct studies on SMEs' management practices. It was non congenital for the study, but it contains precise data on how firms undertake their strategy process. Likewise, the database embodies data on innovation that were calibrated on Community Innovation Survey studies to ensure comparability. The data were collected through a questionnaire survey that was completed by SMEs in the Rhône-Alpes region of France in 2012. At the time of writing, nosotros have gathered a sample of 555 observations. The region had publicly asked firms to participate in a study and it would provide them, in turn, with feedback on the results. The aim of the feedback was to serve as a a benchmarking device to assist SMEs decide areas in which they might improve. Thus, there were strong incentives to give sincere and non-biased responses. The only caveat was in relation to potential for bias through self-selection; completing the questionnaire was a precondition for accessing support from regional administration, in item gaining access to the results of the survey. Therefore, at that place was a hazard that respondents differed in their motivation and organizational attributes from those who chose non to respond to the questionnaire. To assess the possibility of a choice bias, nosotros drew 7000 SMEs randomly from the aforementioned region and performed mean tests on disinterestedness, income, and turnover. None of those tested led united states to reject the nil hypothesis, with no detectable difference in means between respondents and non- respondents. This suggested that self-choice bias was not an issue in our study.

VARIABLES

22 Innovation (new product). Our showtime dependent variable is the existence of a product innovation that can exist considered as new to the market. If a new product or service was developed during the iii previous years, it takes the value 1; if not, it takes the value 0. New production introduction is, indeed, ane of the most acknowledged measures of innovation (Spithoven, et al., 2013); it is the same as in CIS studies, which take products new to market as the core proxy for radical innovation activities. As noted above, nosotros focus here on this kind of innovation because it is the one for which the problem of multiple sources of knowledge arises (Laursen & Salter, 2006).

23 Turnover derived from innovation. Our 2nd alternative dependent variable is the amount of turnover that derives primarily from innovative activities, and is another widely best-selling measure of innovation functioning (Laursen & Salter, 2006). Early on works have used the percentage of turnover as the dependent variable. Even so, Klingebiel and Rammer (2014) notation that this variable may not reflect new product success but rather substitutive strategies in the firm. For that reason, nosotros use the log of the raw turnover derived from new product launches or production improvements fabricated by the firm during the terminal twelvemonth. As we shall run across, the fact that we cannot precisely distinguish between the furnishings of new products and the effects of production improvements led to specific treatment of our data likewise every bit a degree of caution in our analysis.

24 Formalization. As formalization encompasses both artifacts and procedures, we measured information technology in the following two ways:

25 Formalization procedure. This was measured through three five-point Likert scales ( "Nosotros plan the developments of our firm"; "We bank check if objectives are achieved"; and "Nosotros have a articulate and consistent view of what we want to undertake"). Factor assay indicates a i-dimensional construct whereas reliability appears acceptable (Cronbach's alpha = 0.69). It corresponds to the organization's "managerial philosophy" pertaining to formalization efforts.

26 Formalization tools. In parallel, we measured formalization through the number of strategic tools and documents that the firm used, including: (a) general data notes; (b) strategic planning; (c) strategic scoreboards; (d) scenario development and analysis; and (due east) decomposition and analysis co-ordinate to strategic business units. As a summative measure, information technology ranges from 0 to 5. These are part of the most usually used tools in strategic management (Wright, et al., 2013).

27 Openness represents the extent to which an arrangement seeks to integrate external cognition in its ain innovation procedure. This connection phenomenon with external actors, resources, and cognition is, by nature, multifaceted (Michelino, Lamberti, Cammarano & Caputo, 2015). In this study, we focus on 2 of the near agreed proxies for openness, namely inter-organizational relationships and external influences on decision making.

28 Inter-organizational relationships (IORs). IORs are a central feature of open innovation. Openness is enacted through contracts with partners and involvement in communities, including SMEs (Lee, Park, Yoon & Park, 2010). Nosotros measured IORs with the sum of different types of relationships formed during the three previous years, namely: (a) articulation ventures or brotherhood contracts; (b) franchising partnership; (c) integration in a cluster; (d) condign a member of a "pôle de competitivité"; and (eastward) vertical agreement with a supplier. The variable takes values between 0 and 5. Equally such, our measure out is akin to what Laursen and Salter (2006, 2014) telephone call the "external search breath," which reflects the number of split up channels of knowledge inflow.

29 External influences on decision making. The influence of external stakeholders on strategy is 1 distinctive feature of open up innovation (Oberoi, et al., 2014). It was assessed by the number of exterior sources of influence on strategic decision processes. The firms were asked if they were involved in strategic decisions involving: (a) banks; (b) consultants; (c) chartered accountants; (d) public organizations or associations; (eastward) suppliers or clients; and (f) pinnacle managers from other firms. The variable has values between 0 and 6.

thirty Control variables. In our analysis, we added the post-obit command variables. Industrial dummies have business relationship of sector differences. Employees (log) and turnover (log) represent the natural logarithm of employees and turnover and aim at controlling size effect, which is believed to matter in formalization studies (east.grand., Vocal, et al., 2011). Innovation expenses represent to the percentage of turnover dedicated to innovation activities, as shown in visitor statements. We also introduced control variables related to openness. A house may involve external stakeholders in noesis searching or decision making. When it does so, it is important to run across that internal stakeholders are also involved. If external connections increase in parallel to internal ones, and so perhaps they exercise not announce openness but rather a archetype evolution of the stakeholders' network. In other words, without command of internal participation and monitoring, the measure of openness can be spurious. Therefore, to reinforce the measure of openness, we introduced two other control variables. First, internal decisions is a variable reflecting the breadth of internal participation in decision making that includes: (a) all the members of a steering committee; (b) consultation of employees; and (c) interest of shareholders. The variable spans from 0 to 3. Second, and following the same logic, internal monitoring reflects firms' monitoring of: (a) internal resources; and (b) internal processes. This control variable is an integer from 0 to 2.

DESCRIPTIVE STATISTICS

31 Table 1 (beneath) presents an overview of the firm's sample by size and manufacture, while Table 2 displays the descriptive statistics. Product innovation (NwPdt) appears reasonably correlated with formalization variables likewise as openness proxies. These observations are consistent with a large torso of literature about innovation. The signs beingness positive for formalization, we conceptualize that our findings will resolve the dilemma of formalization influence in the direction of a positive effect. In parallel, nosotros observe a strong correlation between formalization measured as a process (FormalPcs) and as an output in the form of tools (FormalTool). It suggests that the 2 variables may be two facets of the same construct. Our purpose is not to aggregate them, however. We managed to examination our models using formalization variables separately, assessing solely their final consistence. Likewise, openness variables (IORs, ExtDecis) exhibit highly significant correlations between them, corroborating a convergence in underlying phenomena. Equally for formalization, nosotros do not demand to aggregate them as far as we utilise them separately in dissimilar models. Finally, we observe that product innovation appears at a charge per unit of 61 %; a percentage that, in CISs, tends to be associated with large firms, whereas small firms normally exhibit an approximate charge per unit closer to 50 % (e.k., Spithoven, et al., 2013). Our sample, therefore, could be slightly biased toward higher rates of innovation. The order of magnitude of product innovation likelihood, however, remains the aforementioned.

Tabular array ane

Frequencies of firms by sector and size in sample

Industry	Size			Total
	< x	10 to < 50	l +
Food industry	8 (iii.83 %)	eighteen (6.59 %)	three (4.11 %)	29 (5.23 %)
Clothing, leather	5 (2.39 %)	10 (3.66 %)	1 (1.37 %)	xvi (2.88 %)
Wood, paper	5 (2.39 %)	18 (vi.59 %)	3 (four.11 %)	26 (4.68 %)
Metallic products	24 (xi.48 %)	45 (sixteen.48 %)	20 (27.40 %)	89 (16.04 %)
Figurer, electronic, optical, electric equipment	iv (1.91 %)	10 (iii.66 %)	five (vi.85 %)	19 (3.42 %)
Machinery	12 (11.48 %)	20 (16.48 %)	x (27.forty %)	42 (vii.57 %)
Furniture, jewelry, repair	15 (vii.18 %)	23 (8.42 %)	four (5.48 %)	42 (7.57 %)
Electricity, gas, water	37 (17.70 %)	24 (viii.79 %)	6 (eight.22 %)	67 (12.07 %)
Waste matter	2 (0.96 %)	3 (one.10 %)	1 (1.37 %)	6 (1.08 %)
Construction, electricity, plumbing	7 (three.35 %)	14 (5.13 %)	3 (four.11 %)	24 (4.32 %)
Retail wholesale, repair	x (4.78 %)	5 (1.83 %)	ane (1.37 %)	16 (2.88 %)
Send	0	one (0.37 %)	1 (1.37 %)	1 (0.36 %)
Accommodation, food	0	1 (0.37 %)	ane (1.37 %)	1 (0.36 %)
Publishing, motion picture, dissemination	iv (1.91 %)	9 (three.thirty %)	2 (2.74 %)	fifteen (2.70 %)
Telecommunications, programming, information	xiv (6.lxx %)	16 (five.86 %)	4 (five.48 %)	34 (6.13 %)
Real estate, scientific activities, direction	39 (18.66 %)	36 (13.19 %)	3 (4.11 %)	78 (14.05 %)
Administrative activities, renting, employment	23 (11.00 %)	21 (7.69 %)	five (half-dozen.85 %)	49 (eight.83 %)
Total	208 (100 %)	273 (100 %)	73 (100 %)	555 (100 %)

Frequencies of firms by sector and size in sample

Table 2

Descriptive statistics and bivariate correlations

Descriptive statistics and bivariate correlations

MODELING STRATEGY AND RESULTS

32 Nosotros congenital our models following ii waves of analysis. In the first moving ridge, we took the likelihood of innovation as a dependent variable. In the second moving ridge, nosotros considered the corporeality of turnover that directly stems from innovation. The two variables are potential and alternative measures of innovation performance and are, arguably, convergent. The use of turnover seems more widespread in the literature. In our example, notwithstanding, some shortcomings in data availability—which we develop later—led us to behave analyses with the two dependent variables.

INNOVATION LIKELIHOOD

33 This assay was decomposed into two subsets. Starting time, we basically assessed the influence of formalization and openness on innovation products new to market place (NwPdt). In Tabular array 3 (below), Model ane is a logit model on product innovation with formalization process and formalization tools every bit explanatory variables. It may be considered as the base of operations model. To this model, we independently added openness variables. It exhibits a positive influence of formalization on NwPdt (β=0.29, p<0.05). Notwithstanding, the influence of formal tools appears to be non-significant. In particular, the influence of formalization tools seems to decrease when we integrate openness variables. In parallel, we observe a general simply marginal influence of IORs on innovation (β=0.23, p<0.05). This is consistent with theory in so far every bit IORs are considered one of the most important tools to develop innovation in open up innovation settings (Chesbrough, 2003). In dissimilarity, external involvement in determination making seemingly has no influence on innovation.

34 A second subset of logit models consists of focusing on possible interaction furnishings betwixt formalization and openness. To this end, interaction terms were added to the regressions. Nonetheless, it is now well documented that the interpretation of interaction coefficients can exist misleading in terms of probability (Hoetker, 2007). A researcher should interpret neither the sign nor the magnitude of an interaction coefficient to infer an interaction effect. In nonlinear models, the strength of interaction furnishings on probability varies with the level of variables. Interaction effects are marginal effects at various levels of an interaction variable (Wiersema & Bowen, 2009). Therefore, simply a general scanning of the interacted variable can display the values for which the interaction effect is significant. To deal with this issue, we adopted the following approach. First, we estimated a logit with interaction term resulting in Models 2 to 5 in Table three. Then, we computed the marginal furnishings of the interacted openness variable at unlike values of formalization variables. Next, we plotted the marginal effects with confidence intervals against interacted variables to go a graphical representation. Wherever it appeared that the confidence interval did not include zero, the interaction effect could be considered significant.

Table iii

Logistic regressions explaining product innovation (N=555)

	Model i	Model two	Model 3	Model four	Model five
FormalPcs	0.29* (0.14)	0.06 (0.22)	- 0.00 (0.36)	0.31* (0.15)	0.xxx* (0.xv)
FormalTool	0.06 (0.ten)	0.06 (0.10)	0.06 (0.x)	- 0.16 (0.18)	- 0.54* (0.26)
FormalPcs × IORs		0.17 (0.13)
FormalPcs × ExtDecis			0.07 (0.08)
FormalTool × IORs				0.14 (0.09)
FormalTool × ExtDecis					0.fourteen* (0.06)
IORs	0.23✝ (0.12)	- 0.39 (0.49)	0.23✝ (0.12)	0.04 (0.17)	0.22✝ (0.12)
ExtDecis	0.06 (0.08)	0.06 (0.08)	- 0.twenty (0.31)	0.07 (0.08)	- 0.11 (0.x)
Employees (log)	- 0.00 (0.00)	- 0.00 (0.00)	- 0.00 (0.00)	- 0.00 (0.00)	- 0.00 (0.00)
Turnover (log)	0.eleven (0.09)	0.11 (0.09)	0.xi (0.09)	0.xi (0.09)	0.eleven (0.09)
Innov. expenses	0.86*** (0.12)	0.86*** (0.13)	0.86*** (0.thirteen)	0.86*** (0.xiii)	0.86*** (0.13)
Internal decisions	- 0.11 (0.11)	- 0.11 (0.11)	- 0.11 (0.eleven)	- 0.11 (0.11)	- 0.10 (0.11)
Internal supervision	0.00 (0.24)	0.02 (0.24)	0.02 (0.24)	0.01 (0.24)	0.06 (0.24)
Industrial dummies	Yes	Aye	Yes	Yep	Aye
Intercept	- 1.48 (0.97)	- 0.72 (1.thirteen)	- 0.47 (1.50)	- one.40 (0.97)	- 0.83 (one.00)
AIC	675.00	675.29	676.24	674.68	670.61
BIC	791.95	796.57	797.52	795.96	791.89
Log likelihood	- 310.50	- 309.64	- 310.12	- 309.34	- 307.30

Logistic regressions explaining product innovation (N=555)

^***p < 0.001, ^**p < 0.01, ^*p < 0.05, ^✝p < 0.1

35 Following the procedure above, we tested the interaction effects for formalization and IORs through Models 2 and four presented in Table 3. Interaction terms do not appear to exist significant, which is a poor clue for detecting interactions. To assess potential interaction effects, nosotros must refer to the graph of marginal furnishings of IORs plotted with 95 % conviction intervals for different levels of formalization variables, as presented in Figure ii (below).

36 Opposite to interaction terms, plotted marginal effects betoken an interaction result that is perceptible for higher values of formalization procedure and for almost values of formalization tools. More precisely, the graphs show that interaction effects go positive and significant when the process formalization variable takes values in a higher place mean. In other words, for college values, formalization increases the influence of IORs on production innovation. A similar analysis applies, with sharper results, to the interaction of IORs with formalization tools. A meaning interaction upshot appears as soon as the house uses at least one strategy-formalization tool. This supports the being of a full general interaction issue between IORs and formalization tools.

Figure 2

Average marginal effects of IORs at various levels of formalization (process and tools)

Average marginal effects of external participation with 95 % CI Average marginal effects of external participation with 95 % CI
- .ane .1
- .05 .05
.1
0
- .05 .05 .fifteen
0
1 two iii 4 5 0123456
Formalization (process) Formalization (tools)

Average marginal furnishings of IORs at various levels of formalization (procedure and tools)

37 Finally, Models 3 and v aim to assess the potential interaction between external participation in decision making and formalization (Table 3). Below, Figure iii exhibits the boilerplate marginal effects of the external participation on the probability of innovation. The analysis of marginal effects of external participation provides mixed findings that, nonetheless, identify interaction effects. For lower levels of formalization procedure, the marginal effects are conspicuously not significant. However, the interaction effect becomes moderately significant for high values. Conclusions are sharper for the marginal effects of formalization: The interaction issue is clearly observable whenever the number of tools the firm uses is greater than 1.

Figure 3

Boilerplate marginal furnishings of external participation at different levels of formalization (process and tools)

Boilerplate marginal effects of IORs with 95 % CI Average marginal furnishings of IORs with 95 % CI
- .ii -.ane .one .2
0
- .1 .1 .two .iii
0
one two iii 4 5012345
Formalization (process) Formalization (tools)

Boilerplate marginal effects of external participation at different levels of formalization (process and tools)

INTENSITY OF INNOVATION TURNOVER

38 The second wave of assay took innovative turnover as the dependent variable. In our sample, the variable was however subject field to two significant caveats. First, the firms were asked to provide the turnover that resulted from products new to the market, products new to the firm simply, and improved products. It is worth noting that the different possibilities are non sectional. Available turnover is, therefore, an inclusive variable that includes radical but also more incremental innovations. In this research, nosotros focus on the former. Withal, there is no possibility of distinguishing the relative proportion that relates to each kind of innovation. Consequently, we used one supplementary control variable, namely the presence of a simply implemented product. This variable aims to control the touch on of incremental innovation on turnover. Moreover, the sample exhibits substantial missing data of the dependent variable; nosotros find innovative turnover in only 477 cases of a total of 555 original observations. We found no identifiable pattern to explicate why those values are missing, for they include observations of innovating and not-innovating firms simultaneously. In the same vein, t-tests on the variables show there is no significant difference betwixt missing observations and the remaining subsample. This suggests that the missing observations are random.

39 Our analysis relied on Tobit regressions. The dependent variable is indeed censored. Regardless of the missing data, we tin can observe the dependent variable only when there is an innovation. The observed zeros in turnover, therefore, mean that the variable is censored and does non reflect the intensity of the turnover. Because Tobit models take the censoring phenomenon into account, they tend to be common in innovation studies. As far as we interpret the model, based on the latent variable that is non always observed, interaction terms may be understood as in classic ordinary least squares regressions. In Table iv (below), Model 6 reflects the basic model with no interaction term. Nosotros detect that formalization process seems to have a meaning impact on innovation performance (β=36.90, p<0.05) while formalization tools take not. Model seven presents the interaction term between formalization process and IOR, and proves to exist neatly significant and positive (β=41.28, p<0.01). Model 8 corresponds to interaction betwixt formalization process and external participation. It is too significant and positive (β=17.22, p<0.05). Finally, Models ix and 10 show interaction effects taking tools with IOR and tools with external participation, respectively. Both interaction terms evidence to be positive but only moderately significant (β=18.02 and β=11.93, p<0.05). From the above results, we can conclude that formalization, both equally a process and a tool, increases the effectiveness of openness on innovation performance. As such, the findings are consequent with those obtained for the likelihood of innovation.

Table 4

Tobit models to explain innovative turnover (N=477)

	Model 6	Model seven	Model 8	Model 9	Model 10
FormalPcs	36.90* (15.28)	- 24.49 (24.34)	- 34.85 (38.07)	40.59** (xv.32)	39.79** (15.29)
FormalTool	13.78 (9.89)	16.08 (9.82)	14.25 (9.83)	- xvi.90 (17.67)	- 38.93 (26.43)
FormalPcs × IORs		41.28** (thirteen.15)
FormalPcs × ExtDecis			17.22* (8.46)
FormalTool × IORs				18.02* (viii.63)
FormalTool × ExtDecis					11.93* (five.55)
IORs	27.twenty* (11.76)	- 132.76* (52.33)	26.76* (11.69)	- 1.14 (17.91)	25.44* (11.74)
ExtDecis	6.36 (8.25)	7.18 (viii.14)	- 58.56✝ (32.82)	7.46 (eight.22)	- 9.44 (ten.96)
Improved product	xc.13*** (25.22)	93.29*** (24.97)	88.39*** (25.01)	91.34*** (25.07)	89.41*** (25.ten)
Employees (log)	0.38 (0.36)	0.37 (0.35)	0.39 (0.35)	0.42 (0.35)	0.45 (0.35)
Innov. expenses	lxx.76*** (13.23)	73.44*** (thirteen.xvi)	70.53*** (13.14)	71.25*** (13.xviii)	69.45*** (13.xix)
Internal decisions	- 4.51 (xi.75)	- 2.06 (eleven.66)	- 3.70 (11.66)	- 4.71 (11.70)	- 3.48 (11.71)
Internal supervision	- seven.87 (25.88)	- 5.06 (25.55)	- 2.36 (25.86)	- seven.38 (25.69)	- 3.18 (25.81)
Industrial dummies	Aye	Yeah	Yeah	Yes	Yes
Intercept	- 378.fifteen*** (83.63)	- 166.04 (103.61)	- 114.31 (150.91)	- 365.73*** (83.09)	- 322.54*** (86.21)
AIC	3189.66	3181.71	3187.56	3187.29	3187.02
BIC	3306.35	3302.57	3308.42	3308.15	3307.87
Log likelihood	- 1566.83	- 1561.85	- 1564.78	- 1564.64	- 1564.51
Left-censored	263	263	263	263	263
Uncensored	214	214	214	214	214

Tobit models to explain innovative turnover (N=477)

^***p < 0.001, ^**p < 0.01, ^*p < 0.05, ^✝p < 0.ane

Give-and-take

twoscore The purpose of this research was to deepen our understanding about the affect of strategy formalization on open up innovation strategies. To get beyond the conflicting views over the influence of formalization, we combined open up innovation and socio-material perspectives. In doing so, nosotros specifically considered the possibility for formalization to be a means of benefiting from openness in gild to innovate. Therefore, nosotros hypothesized that formalization could be a positive moderator of the acknowledged influence of openness on innovation success. Using a unique database of 555 SMEs, we investigated the effects of strategy formalization, open up innovation, and their interactions on product innovation. Analyzing the data, we dealt with several models that could be derived from our general hypothesis. This information analysis strategy was motivated, on the one hand, by debates over definition of some variables and, on the other manus, by limitations induced past data availability during our empirical investigations. In a nutshell, the multiple model design was commended past a search for robustness. Adjacent, we considered innovation success alternately as new production likelihood and as turnover derived from new products. Using the same logic, we considered innovation through its process and artifact dimensions. Furthermore, we used two unlike variables to measure openness: cooperation, and the implications of external stakeholders. Ultimately, the multiple models provided convergent findings. Overall, formalization positively moderates the influence of openness on innovation. While we concede that findings are merely moderately significant, they all show that open innovation strategies atomic number 82 to better outcomes when formalization is greater. The main outcome is more obvious for formalization considered in its process dimension than as a tool. Withal, the interaction effects have no perceivable differences across the facets of formalization. Consequently, our findings contribute to the extant research on four principal points.

41 First, our report underscores the positive influence of formalization in open innovation situations. To the best of our knowledge, this is the offset study to investigate how open innovation strategies interact with formalization. Prior research nurtured competing views on this topic; some researchers developed complex models that immune a negative influence of strategy formalization on innovation development, while having a generally positive part in organization functioning (e.grand., Vocal, et al., 2011). In parallel, a growing body of literature argued that formalization, despite its double-edged nature, could bring directly benefits to the organization (e.k., Dibrell, et al., 2014). The socio-material literature invites us to look beyond this argue by considering the generative facet of formalization and its potential role on innovation. Therefore, we contribute past specifying some of the conditions under which formalization benefits the open organization. In our study, nosotros adult the rationale whereby formalization could play a positive role. In open innovation strategies, the number of stakeholders poses specific challenges that formalization helps to cope with. Indeed, formalization may play both an integrative and an analytical function. The need to clarify, organize, negotiate with stakeholders on the project, and legitimate this project to partners' views tends to prove that the literature should now pay more than attention to firms' internal capabilities to leverage inbound openness. Our empirical approach confirms implications drawn from this view.

42 Second, and of particular importance, is that our findings were obtained in an SME setting. Until recently, researchers neglected open innovation in small firms (Spithoven, et al., 2013). Nonetheless, open innovation is recognized to be important for SMEs as well (Gassman, Enkel & Chesbrough, 2010; Van De Vrande, et al., 2009). Constraints on SMEs' capabilities explicate that open up innovation represents an opportunity to develop them. Simply, at the aforementioned time, it raises the question of availability of techniques and finite resources to take reward from openness. Our study yields interesting insights on this indicate: As the small firm adopts openness, formalization gains increased importance in innovating as well as increasing turnover from innovation activities. Furthermore, nosotros also annotation a modest direct outcome from the formalization process on innovation performance, whatsoever the openness of the firm. In this fashion, we prolong the studies of the bear on of strategy formalization in new ventures (Burke, et al., 2010; Delmar & Shane, 2003) and expand them toward innovation. As for the question of whether the tools we teach in business schools are useful to managers (Wright, et al., 2013), we would clearly answer "Yeah" in the context of open innovation.

43 3rd, nosotros see our study as providing incidental feedback to the socio-material literature. Our first goal was to build on socio-materiality to enlighten our strategy for data analysis. In doing so, we confirm empirically the stiff ties between the technical artifacts and organizational practices pertaining to formalization. Socio-material studies ostend the strong correlation between the two but remain controversial as to whether they are separable constructs. In our study, we provide an example in which the two facets may be distinguished. Nosotros identify each variable'due south proper influence by controlling for the other in the analyses. Therefore, we were able to care for each miracle separately during our empirical investigations. Future studies could develop a series of measures and investigate the relationships between them. Hitherto, in-depth example studies have been the exclusive enquiry method used past socio-textile approaches. However, our work suggests that quantitative methods may be more suitable to study socio-material variables, only the lack of consensus over the employ of the various theoretical models represents a limiting factor for now.

44 Fourth, our piece of work offers direct managerial implications. It points out the importance of formalization in open innovation contexts. Managers frequently consider business organization plans, reports, and meetings for plans as mainly fourth dimension consuming, and frequently rate more informal methods equally superior to formalized procedures. Thus, it is important that formalizing strategy is seen as cardinal for modest firms aiming to adopt openness. If managers plan to collaborate with other organizations or involve many actors in decision making, formalization becomes essential. Managers should, therefore, learn to condone the apparent drawbacks of formalization for innovation. Because the importance of formalization in bringing together actors and stimulating strategic thinking is a style of acknowledging an assertion that has been counterintuitive.

INTENSITY OF INNOVATION TURNOVER

45 Too the usual shortcomings, two limitations are noteworthy. In this enquiry, we deliberately focused on strategy formalization at the general level. However, it is too possible to consider strategy at the specific level of new product development (e.yard., Holahan, Sullivan & Markham, 2014). While the literature has explored formalization of processes dedicated to innovation, much remains to be learned about their link with open innovation. Another limitation is that we have not studied the antecedent of formalization. In this regard, our arroyo was consistent with the literature that has paid scant attention to the causes of strategic planning (Harris & Ogbonna, 2006). Future enquiry could advance the argument for the open up innovation approach past investigating how the demand for a network could trigger specific postures in initiating strategy formalization. More generally, nosotros strongly believe that hereafter research volition reveal more interesting ideas by focusing on management details and accessing microdata not present in conventional databases, thus avoiding the pitfall of because concepts as monolithic.

Notes

• [1]

  At this stage, the different proxies for innovation have not been presented because they were not central to theoretical evolution. They are detailed in the methodological part of the newspaper.

REFERENCES

• En ligne Abdallah, C., & Langley, A. (2014). The double edge of ambiguity in strategic planning. Journal of Management Studies, 51 (2), 235-264.
• Avadikyan, A., Llerena, P., Matt, Chiliad., Rozan, A., & Wolff, Southward. (2001). Organisational rules, codification and knowledge creation in inter-system cooperative agreements. Codification of Cognition, thirty (9), 1443-1458.
• En ligne Balogun, J., Jacobs, C., Jarzabkowski, P., Mantere, Due south., & Vaara, Eastward. (2014). Placing strategy soapbox in context: Sociomateriality, sensemaking and power. Periodical of Management Studies, 51 (2), 175-201.
• En ligne Barnett, M. L. (2008). An attention-based view of existent options reasoning. Academy of Direction Review, 33 (3), 606-628.
• En ligne Beers, C., & Zand, F. (2014). R&D cooperation, partner diversity, and innovation functioning: An empirical analysis. Periodical of Product Innovation Management, 31 (2), 292-312.
• En ligne Bianchi, 1000., Campodall'Orto, S., Frattini, F., & Vercesi, P. (2010). Enabling open innovation in small-scale and medium-sized enterprises: How to detect alternative applications for your technologies. R&D Management, 40 (4), 414-431.
• En ligne Brunswicker, S., & Vanhaverbeke, West. (2015). Open innovation in small and medium-sized enterprises (SMEs): External knowledge sourcing strategies and internal organizational facilitators. Periodical of Minor Business Management, 53 (4), 1241-1263.
• En ligne Burke, A., Fraser, S., & Greene, F. J. (2010). The multiple furnishings of business planning on new venture performance. Periodical of Management Studies, 47 (3), 391-415.
• En ligne Cecez-Kecmanovic, D., Galliers, R. D., Henfridsson, O., Newell, South., & Vidgen, R. (2014). The sociomateriality of information systems: Current status, future directions. MIS Quarterly, 38 (iii), 809- 830.
• Chesbrough, H. Westward. (2003), Open innovation: The new imperative for creating and profiting from engineering. Boston: Harvard Business organization Review Press.
• Chesbrough, H. Westward., Vanhaverbeke, W. & West, J.. (2006), Open innovation: Researching a new prototype. Oxford: Oxford University Press.
• En ligne Chua, R., Roth, Y., & Lemoine, J.-F. (2015). The impact of culture on creativity: How cultural tightness and cultural distance affect global innovation crowdsourcing work. Administrative Science Quarterly, threescore (two), 189-227.
• Clegg, S. R., & Kornberger, M. (Eds.). (2006). Infinite, organizations and management theory. Malmö: Liber & Copenhagen Business organisation School Printing.
• En ligne Cousins, P. D., Lawson, B., Petersen, K. J., & Handfield, R. B. (2011). Breakthrough scanning, supplier knowledge exchange, and new product evolution performance. Journal of Product Innovation Management, 28 (6), 930-942.
• En ligne Dahlander, L., & Gann, D. One thousand. (2010). How open is innovation? Inquiry Policy, 39 (six), 699-709.
• En ligne Dahlander, L., O'Mahony, Southward., & Gann, D.Chiliad. (2016). One foot in, one pes out: How does individuals' external search breadth affect innovation outcomes? Strategic Direction Journal, 37 (2), 280-302.
• En ligne Delmar, F., & Shane, South. (2003). Does business planning facilitate the development of new ventures? Strategic Management Journal, 24 (12), 1165-1185.
• En ligne D'Este, P., Iammarino, Southward., Savona, M. & Von Tunzelmann, N. (2012). What hampers innovation? Revealed barriers versus deterring barriers. Enquiry Policy, 41 (two), 482-488.
• En ligne Dibrell, C., Craig, J. B., & Neubaum, D.O. (2014). Linking the formal strategic planning process, planning flexibility, and innovativeness to firm performance. Journal of Business Research, 67 (9), 2000-2007.
• En ligne Dittrich, Grand., & Duysters, G. (2007). Networking equally a means to strategy alter: The case of open innovation in mobile telephony. Periodical of Product Innovation Management, 24 (6), 510-521.
• Faraj, S., & Azad, F. (2012). The Materiality of Technology: An Affordance Perspective. In P. Grand. Leonardi, B.A. Nardi, & J. Kallinikos (Eds), Materiality and organizing, Social Interaction in a Technological Globe (pp.237-258). Oxford, UK: Oxford University Press.
• En ligne Fernhaber, S. A., & Patel, P. C. (2012). How do immature firms manage product portfolio complication? The role of absorptive capacity and ambidexterity. Strategic Management Periodical, 33 (13), 1516-1539.
• En ligne Garriga, H., Von Krogh, 1000., & Spaeth, S. (2013). How constraints and cognition affect open innovation. Strategic Management Journal, 34 (9), 1134-1144.
• En ligne Gassman, O., Enkel, E., & Chesbrough, H. (2010). The future of open innovation. R&D Management, twoscore(iii), 213-221.
• En ligne Grant, R. M. (2003). Strategic planning in a turbulent environment: Show from the oil majors. Strategic Management Journal, 24 (6), 491-517.
• En ligne Han, K., Oh, W., Im, K.S., Oh, H., Pinsonneault, A., & Chang, R.M. (2012). Value cocreation and wealth spillover in open up innovation alliances. MIS Quarterly, 36 (1), 291-316.
• En ligne Harris, Fifty. C., & Ogbonna, E. (2006). Initiating strategic planning. Periodical of Business organization Research, 59 (1), 100-111.
• En ligne Hervas-Oliver, J.-50., Sempere-Ripoll, F., & Borona-Moll, C. (2014). Process innovation strategy in SMEs, organizational innovation and functioning: A misleading argue? Small Business Economic science, 43 (iv), 873-886.
• En ligne Hoetker, G. (2007). The use of logit and probit models in strategic management research: Critical issues. Strategic Direction Journal, 28 (four), 331-343.
• En ligne Holahan, P. J., Sullivan, Z. Z., & Markham, S.Thou. (2014). Production development as core competence: How formal product development practices differ for radical, more innovative, and incremental product innovations. Periodical of Product Innovation Management, 31 (two), 329-345.
• En ligne Im, S., Montoya, M. Chiliad., & Workman, J. P. (2013). Antecedents and consequences of creativity in production innovation teams antecedents and consequences of creativity in product innovation teams. Periodical of Product Innovation Management, xxx (ane), 170-185.
• En ligne Jarzabkowski, P. & Pinch, T. (2013). Sociomateriality is 'the New Blackness': Accomplishing repurposing, reinscripting and repairing in context. M@n@gement, 16 (5), 579-592.
• En ligne Kaplan, Sarah (2011). Strategy and powerpoint: an enquiry into the epistemic culture and machinery of strategy making. Organization Science 22 (2), 320- 346.
• En ligne Katila, R., & Ahuja, Chiliad. (2002). Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of Direction Journal, 45 (6), 1183-1194.
• Ketokivi, M., & Castañer, X. (2004). Strategic planning as an integrative device. Administrative Science Quarterly, 49 (three), 337-365.
• En ligne Klingebiel, R., & Rammer, C. (2014). Resources allocation strategy for innovation portfolio management. Strategic Direction Periodical, 35 (ii), 246-268.
• En ligne Labatut, J., Aggeri, F., & Girard, N. (2012). Subject area and alter: How technologies and organizational routines interact in new practise creation. Organization Studies, 33 (i), 39-69.
• En ligne Laursen, K., & Salter, A. J. (2006). Open for innovation: the function of openness in explaining innovation performance amid U.Thou. manufacturing firms. Strategic Management Journal, 27 (2), 131-150.
• En ligne Laursen, K., & Salter, A. J. (2014). The paradox of openness: Appropriability, external search and collaboration. Research Policy 43 (five), 867-878.
• En ligne Lee, S., Park, K., Yoon, B., & Park, J. (2010). Open innovation in SMEs: An intermediated network model. Research Policy, 39 (2), 290-300.
• En ligne Michelino, F., Lamberti, E., Cammarano, A., & Caputo, M. (2015). Measuring open innovation in the bio- pharmaceutical industry. Creativity & Innovation Management, 24 (i), 4-28.
• En ligne Miner, A.S., Bassoff, P., & Moorman, C. (2001). Organizational improvisation and learning: A field study. Administrative Science Quarterly, 46 (2), 304- 337.
• Mintzberg, H. (1994), Ascension and fall of strategic planning: Reconceiving the robes for planning, plans, planners (1st Ed.), New York, NY: Free Press.
• Moisdon, J.-C. (2006). Sur la largeur des mailles du filet: Savoirs incomplets et gouvernement des organisations [On the size of the mesh in the net: Incomplete noesis and organizational governance]. In: A. Hatchuel, E. Pezet, M. Starkey & O. Lenay (Eds.), Gouvernement, organization et gestion: Fifty'héritage de Michel Foucault [Governance, organization and management: The legacy of Michel Foucault] (pp. 135-146). Laval, Canada: Presses de l'Université de Laval.
• En ligne Oberoi, P., Haon, C., & Freitas, I.M.B. (2014). Organizing for open innovation: Incorporating the externality of control with multifariousness of contribution. One thousand@n@gement, 17 (3), 180-192.
• Orlikowski, W.J. & Scott, Southward.V. (2008) . Sociomateriality: Challenging the separation of technology, work and organization. The Academy of Management Register, ii (1), 433-474.
• En ligne Prajogo, D., & McDermott, C.M. (2014). Antecedents of service innovation in SMEs: Comparing the furnishings of external and internal factors. Journal of Small Concern Direction, 52 (3), 521-540.
• En ligne Salter, A., Criscuolo, P., & Ter Wal, A.Fifty.J. (2014). Coping with open innovation: Responding to the challenges of external engagement in R&D. California Management Review, 56 (2), 77-94.
• En ligne Sele, 1000., & G, Southward. (2016). Unpacking the dynamics of ecologies of routines: mediators and their generative effects in routine interactions. Organization Science, 27 (3), 722-738.
• En ligne Sirén, C., & Kohtamäki, Thou. (2016). Stretching strategic learning to the limit: The interaction betwixt strategic planning and learning. Journal of Business concern Research, 69 (2), 653-663.
• En ligne Sivadas, E., & Dwyer, F. R. (2000). An exam of organizational factors influencing new product success in internal and brotherhood-based processes. Journal of Marketing, 64 (1), 31-49.
• En ligne Song, G., & Chen, Y. (2014). Organizational attributes, marketplace growth, and product innovation. Journal of Product Innovation Direction, 31 (6), 1312-1329.
• En ligne Vocal, M., Im, S., Van Der Bij, H., & Song, Fifty. Z. (2011). Does strategic planning heighten or impede innovation and firm performance? Journal of Product Innovation Management, 28 (4), 503-520.
• En ligne Spithoven, A., Vanhaverbeke, Westward., & Roijakkers, N. (2013). Open innovation practices in SMEs and large enterprises. Pocket-size Business Economic science, 41 (3), 537-562.
• En ligne Titus, V. K., Jr., Covin, J. G., & Slevin, D. P. (2011). Aligning strategic processes in pursuit of firm growth. Periodical of Business Inquiry, 64 (5), 446- 453.
• En ligne Van De Vrande, Five., De Jong, J. P. J., Vanhaverbeke, W., & De Rochemont, M. (2009). Open up innovation in SMEs: Trends, motives and direction challenges. Technovation, 29 (half-dozen-7), 423-437.
• En ligne Vlaar, P., Van Den Bosch, F.A., & Volberda, H.Westward. (2006). Coping with bug of understanding in interorganizational relationships: Using formalization every bit a means to make sense. Organization Studies, 27 (11), 1617-1638.
• En ligne Wiersema, Chiliad. F., & Bowen, H.P. (2009). The use of limited dependent variable techniques in strategy research: Bug and methods. Strategic Management Journal, thirty (half-dozen), 679-692.
• En ligne Wright, R. P., Paroutis, Due south. E., & Blettner, D.P. (2013). How useful are the strategic tools we teach in business schools? Journal of Management Studies, l (i), 92-125.
• En ligne Wynarczyk, P., Piperopoulos, P., & McAdam, M. (2013). Open innovation in small and medium-sized enterprises: An overview. International Pocket-sized Business Journal, 31 (three), 240-255.
• En ligne Yakura, E. M. (2002). Charting time: timelines equally temporal boundary objects. Academy of Management Journal, 45 (5), 956-970.

claassentrier1945.blogspot.com

Source: https://www.cairn.info/revue-management-2017-3-page-266.htm

Share this post