MANAGING (NON-)SUSTAINABLE INNOVATIONS How organizational structures influence firm’s (non-)sustainable innovation performance

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MANAGING (NON-)SUSTAINABLE INNOVATIONS

How organizational structures influence firm’s (non-)sustainable innovation

performance

by

Lianne Yvette Noteboom

s2221489

University of Groningen

Faculty of Economics and Business Strategic Innovation Management 1st_{supervisor: dr. T.L.J. Broekhuizen}

2nd_{supervisor: dr. W.G. Biemans}

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Preface

After two-and-a-half years of hard work, the moment is finally here. Handing in this thesis gives me a small sense of elation and joy, because I never thought I would get to this point. I have always been interested in how products are marketed and how this could be done more effectively. The real joy for me, however, is coming up with an idea and developing an actual product. This is why I decided to make the switch to Strategic Innovation Management after I finished the premaster. During the last few years I found out what I really wanted, which is going into sports innovation. But before we get ahead of ourselves,, I would first like to enjoy this moment.

To start, I would like to extend a special thanks to dr. Thijs Broekhuizen, who guided me throughout the research process with a lot of valuable feedback and support. Thanks to my second supervisor dr. W. G. Biemans for his time and effort. Also, I would like to thank all the participants that filled in the

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Abstract

Sustainable innovation is an emerging and fundamental force for change in business and society. By creating, improving and making environmental friendly products, firms try to stay ahead of the competitor. Structuring these innovation processes is a critical factor in arriving at successful innovations. In particular, the implementation of different structures such as functional and cross-functional have been found to positively influence the innovation performance of a firm for incremental and radical innovations respectively. This study establishes the link between organizational structures and innovation performance, measured as innovation output and the extent to which the incremental or radical (non-)sustainable innovations have contributed to the sales.

This research is based on a survey study of 82 firms. This study conducted an assessment of the impact of different kind of organizational structures (i.e. functional versus cross-functional) on different kinds of firms’ non-sustainable and sustainable innovation performance (i.e. number of incremental versus radical and the percentage of sales of incremental versus radical innovations). It is observed that most firms use similar structures for both their incremental and radical NPD processes. This study also found that firms, which use a cross-functional structure for both radical non-sustainable and radical sustainable innovations, perform better than firms that use a functional structure. Finally, the results indicated that the more radical and more sustainable the innovations become, the more a cross-functional structure is preferred.

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Table of content

1 | INTRODUCTION ... 4

2 | THEORETICAL FRAMEWORK ... 7

2.1 SUSTAINABLE DEVELOPMENT: A BROAD PERSPECTIVE ... 7

2.2 DEFINING SUSTAINABLE INNOVATION ... 7

2.3 THE LINK BETWEEN ORGANIZATIONAL STRUCTURE AND INNOVATION PERFORMANCE ... 10

2.4 THE LINK BETWEEN STRUCTURE AND SUSTAINABLE INNOVATION PERFORMANCE ... 12

2.5 RESEARCH MODEL ... 13 3 | METHODOLOGY ... 15 3.1 RESEARCH DESIGN ... 15 3.2 DATA COLLECTION ... 15 3.3 MEASURES ... 16 3.4 DATA ANALYSIS ... 19 4 | RESULTS ... 21 4.1 RESPONDENT CHARACTERISTICS ... 21

4.2 INDEPENDENT SAMPLES T-TEST: COMPARING MEANS ... 22

4.3 REGRESSION ANALYSIS: ESTIMATE RELATIONSHIPS AMONG VARIABLES ... 24

5 | DISCUSSION AND CONCLUSION ... 30

5.1 FINDINGS ... 30

5.2 THEORETICAL AND MANAGERIAL IMPLICATIONS ... 31

5.3 LIMITATIONS AND FUTURE RESEARCH ... 32

5.4 CONCLUSION ... 32

REFERENCE LIST ... 34

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1 | Introduction

If the world were stable there neither would be a need to change business operations and methods, nor to understand what has changed and what works well. However, firms operate in dynamic environments. Increasing competition, low market growth rates and saturatedmarkets make it much more difficult for businesses to continue to exist (Matzler & Hinterhuber, 1998). Due to this pressure it is crucial for their long-term survival and growth to create and/or improve products at any time (Ernst, 2002; Schumpeter, 1939). This process of creating new products is called the new product development (NPD) process. Due to this increased importance scholars have increasingly studied the NPD process within firms during the last decades (Brown & Eisenhardt, 1995; Cooper, 1999; Ernst, 2002). These studies show that the innovativeness of these products can vary between incremental and radical NPD processes (Dewar and Dutton, 1986; Tushman & Anderson, 1986). In addition, according to De Visser, De Weerd-Nederhof, Faems, Song, Van Looy, & Visscher (2010), the NPD process is a multidimensional phenomenon, encompassing development processes that focus on the improvement of existing products (incremental NPD processes) as well as processes that focus on the generation of new products (radical NPD processes).

Besides the importance of creating and improving new products, making these products and processes more sustainable is another relevant issue (Pujari, 2006). In recent years, sustainable-industries have emerged as an important segment of the European economy. This sector has an estimated turnover of around €227 billion, corresponding to 2.2% of EU GDP, and employs 3.4 million people directly. Businesses around the world have recognized this emerging industry and acknowledged the need to respond appropriately to sustainable development challenges (Sharma, 2000). This is mainly due to the growing pressure from internal and external stakeholders to consider the environmental and social impacts of their operations (Searcy & Elkhawas, 2012). For example, customers are becoming more aware of the pollution caused by the companies they buy their products from and base their purchasing on this issue (Arora & Gangopadhyay, 1995). Additionally, investors have become more critical in selecting partners for their investments. Grove & Janney (2011) showed that being involved in an environmental scandal was devastating for their company image. Also, in the literature there has been increasing awareness and attention dedicated to sustainable development (Banerjee, Lyer, & Kashyap, 2003).

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study focuses only on the environmental dimension. New products and processes that contribute to sustainable development are called sustainable innovations (Charter & Clark, 2007). Sustainable innovation or eco-innovation differs from regular innovation by the aim to decrease the negative impacts the product (good and/or service) or the process has on the environmental, social, and economical aspects (Hassi, Peck, Dewulf, & Wever, 2009). Sustainale innovation is a powerful instrument, combining reduced negative impact on the environment with a positive impact on the economy and society (European Commission, 2013). Being sustainable or making these products and processes sustainable has major advantages. For example, results indicate that leading Corporate Sustainability Performance (CSP) firms have higher levels of growth and have a higher return on equity than conventional firms (Artiach, Lee, Nelson, & Walker, 2010). The research by Murray & Ayuon (2010) showed that companies who are considered to be sustainable attract more and better future employees.

To become more sustainable, significant changes to the way materials and resources are used, re-used and managed are needed. For example, management instruments at firm-level such as eco-audits are important for sustainable innovations (Rennings, 2000). More qualified personnel is necessary as sustainable innovations need more research input and are more dependent on external sources (Horbach, 2013). In the literature, the way the new product development process is structured or managed has been recognized as one of the crucial factors in arriving at successful innovation (Cooper, 2003; de Visser et al., 2010). These structures are mostly divided into two types, namely functional and cross-functional structures. The functional structure deals with various specialized departments (research and development, manufacturing and marketing) working independently (Song et al., 1998), whereas the cross-functional structure deals with specialists of different departments that are brought together within a single team structure for particular NPD projects (Griffin, 1997).

Current literature on product innovations points to the relevance of adopting different structures for different innovations (Benner & Tushman, 2003; Song & Xie, 2000; de Visser et al., 2010). The study of De Visser et al. (2010) found evidence that the effectiveness of cross-functional structures is different for different kinds of NPD processes. They observed that, adopting a cross-functional structure—instead of a functional structure—in radical NPD processes has a significant positive impact on the radical innovation performance, while the implementation of a cross-functional structure in incremental NPD processes has a significant negative impact on incremental innovation performance.

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further research. This study tries to investigate how specific organizational structures may contribute to sustainable and non-sustainable incremental and radical innovation performance.

Research(question(

For the purpose of exploring how specific organizational structures influence the (non-)sustainable innovation performance, the following main research question is formulated:

“How does the organizational structure influence the (non-)sustainable innovation performance of a firm?” This study distinguishes between two types of structures: functional and cross-functional, and two types of innovation performance: the number of innovations (output measure) and the sales percentage of these incremental and radical innovations (relative sales success measure). Besides exploring the influence of organizational structures on sustainable innovation performance, also non-sustainable innovations are taken into account.

Outline(

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2 | Theoretical framework

2.1 Sustainable development: a broad perspective

Sustainable development is viewed as a crucial factor in overall business success (Searcy & Elkhawas, 2012). It has grown from being a movement focused on environmental concerns to a widely accepted framework that guides the decision making of individuals, corporations, society and governments to balance the concerns of ecological, economic, and social needs of the current and future generation (Varma, 2009). There are many definitions, but the most commonly cited definition of sustainable development comes from the WCED (1987) and states that sustainable development is “development that meets the needs of the present without compromising the ability of future generations to meet their own needs”. This definition clearly focuses on the social issues, such as human rights and working conditions (Steurer et al., 2005). However, this definition of sustainable development failed to clarify what exactly is supposed to be done by companies particularly with regards to generating new products. In recent years, it has become clear that in order to address the sustainable development challenge, companies need to balance financial, social and environmental performance. According to Elkington (1999) these dimensions belong to the “triple bottom line”, which aims to report on an organization’s economic, social and environmental impacts. The expression” triple bottom line” comprises out of the three elements people, planet and profit, where people belong to the social dimension, planet to the environmental dimension and profit to the economic dimension. Even though a sustainable organization strives to create value on all three dimensions, one weak dimension does not necessarily make the product or process unsustainable.

2.2 Defining sustainable innovation

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eco-(measured by the use of sustainable innovations) and economic performance eco-(measured by the percentage of sales contributed to sustainable innovation), and does not include the social aspect. The following definition of sustainable innovation will be used:

“Sustainable innovation is the process of developing new ideas, behavior, products and processes that contribute to a reduction of environmental impact, to ecologically specified sustainability targets, or achieving a more efficient and responsible use of natural resources” (European Commission, 2013; Rennings, 2000)

To achieve a better understanding of the concept of sustainable innovations, it is useful to categorize the types of innovations.

2.2.1 Categorization of (sustainable) innovations

Innovations have generally referred to the introduction of new or improved things (Schumpeter, 1939; Wijnberg, 2004). This level of improvement or innovativeness of products in relation to existing products is mostly classified in two broad categories: incremental changes and radical changes (Abernathy & Clark, 1985). According to Tushman & Smith (2002) the objective of incremental innovation is to improve existing products through conducting exploitative activities such as optimization, standardization and refinement. Incremental innovations are typically extensions to current product offerings or logical and relatively minor extensions to existing processes (Dewar & Dutton, 1986). With radical innovations, the objective is to generate wholly new products through explorative activities such as fundamental research, experimenting and prototyping. Radical product innovations involve the development or application of new technologies or ideas into markets that are either nonexistent or require dramatic behavior changes to existing markets.

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Weizacker, Lovins, & Lovins, 1997). Put differently, to achieve greater reductions in environmental impact, greater changes must occur. This eco-efficiency scale from low to high is in line with the scale from incremental to radical sustainable innovation.

Brezet (1997) proposed a model (figure 1) depicting four different levels of sustainable innovation, from low to high, with the primary focus on the environmental dimension; product improvement, product redesign, function innovation and system innovation. Each level potentially achieves greater eco-efficiency but takes more time to do so. In level 1, “product improvement”, the existing product is being improved with regards to pollution prevention and environmental care. For example reducting harmful substances in products, like unleaded petrol. At the “product redesign” (level 2) stays the concept the same, but parts of the product are developed further or replaced by others. Typical aims are increased reuse of spare parts and raw materials, or minimising the energy use at several stages in the product life cycle, for example jeans made from cannabis rather than cotton that needs a lot of clean water to grow or an energy saving bulb. In level 3, “functional innovation”, the desired function is fulfilled in a new way. For example the development of hybrid cars. Finally in level 4 new products and services arise requiring changes in the related infrastructure and organizations. For example, a changeover in agriculture to industry-based food production, or changes in organisation, transportation and abour based on information technology are typical. These four levels can also be related to incremental innovations and radical innovations. If a line were to be drawn between what this paper defines as incremental and radical, it would split levels 2 and 3. This again indicates a positive correlation between greater eco-efficiency improvements and how radical an innovation must be to achieve them. In this research the classification of Brezet’s (1997) model will be used.

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2.3 The link between organizational structure and innovation performance

According to numerous studies a firm can choose between two kinds of structures for the NPD process, namely a functional structure and a cross-functional structure (Griffin & Hauser, 1992; Song, Thieme, & Xie, 1998). At the functional structure various specialized departments (e.g. R&D, manufacturing and marketing) work independently, while at the cross-functional structure specialists of different departments are brought together within a single team structure for a particular NPD project (Griffin, 1997). Research on cross-functional integration in NPD projects appears to agree on R&D, marketing, and manufacturing as the three main contributors to the product innovation process (Hardaker, 1998). In other words, a cross-functional structure is sort of an overlay on the functional structure that creates temporary teams of organizational members. With this overlay as a basis, it appears from the literature that most of the advantages of cross-functional integration are derived from the creation of horizontal communication linkages not available in the classic (functional) structure. This lateral communication forces managers to maintain close contact with all organizational groups upon whose support they must rely for project success (Ford & Randolph, 1992). In addition, these team members with various specializations provide firms with a lot of different knowledge sources, which increases the probability of developing successful innovations (Balbontin, Yazdani, Cooper, & Souder, 1999). According to Ernst (2002), the advantage of a cross-functional team over a functional team is that cross-functional teams foster interdepartmental communication and cooperation, which in turn facilitate coordination. However, these multiple dimensions may create an atmosphere of ambiguity and conflict over areas such as resources, technical issues, salaries and promotion (Katz & Allen, 1985; Larson & Dobeli, 1987). This ambiguity results in power struggles as each side attempts to clarify and define its responsibility and accountability (Davis & Lawrence, 1978) (Larson & Dobeli, 1987). Besides there are costs associated with integration of the different departments, for example, through an increased frequency of meetings to facilitate information flows and joint decision-making (Song, Thieme, & Xie, The impact of crossfunctional joint involvement across product development stages: An exploratory study, 1998). In contrast, communication is less important for functional structures, because fewer conflicts will appear about resources. Also, it is not necessary to integrate different departments as a result of which costs are much lower (Song, Thieme, & Xie, The impact of crossfunctional joint involvement across product development stages: An exploratory study, 1998). The driving motive behind functional structures is most often efficiency and functional learning (Appelo, 2011), while it offers higher levels of specialization.

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should engage in different kinds of innovation activities (Tushman & Anderson, 1986; De Visser et al., 2010). In particular, activities such as optimization, standardization, and refinement (incremental innovations) are linked to incremental innovation performance, whereas activities such as fundamental research, experimentation, and search (radical innovations) are connected to radical innovation performance (Benner & Tushman, 2003).

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H1: Firms that apply a functional structure for their incremental non-sustainable innovations display significantly higher levels of incremental non-sustainable innovation performance than firms that apply a cross-functional structure

H2: Firms that apply a cross-functional structure for their radical non-sustainable innovations display significantly higher levels of radical non-sustainable innovation performance than firms that apply a functional structure

2.4 The link between structure and sustainable innovation performance

Sustainability in the context of new product development (NPD) is viewed as the organizational ability to continuously (re)generate new products, improve quality of work life and environment, achieve a high degree of system flexibility that allows for continuous change and development of human, technological and work processes, to improve business processes, image and outcomes (Docherty et al., 2002). Thus, at a basic level, meeting the increasing demands on NPD units to deliver improved products at a faster rate and pace create major tension with the emerging need to develop sustainable work systems. Radical sustainable innovations have the potential for market disruption. The more radical the innovation, the bigger the clash with its existing value system (Jacobs, 2007). Consequently, this leads to more friction with the customers, retailers, suppliers, complementors and other relevant parties. Therefore departments within the firm need to work together in order to achieve the required knowledge to facilitate the adoption and acceptance of the innovation. Results of the study by Smith (2008) confirm the importance of using cross-functional structures for radical sustainable innovations. They showed that for developing radical sustainable innovations, both R&D and Environmental Management were important departments. Communicating information, like getting wind of new legislation, between these departments is of great importance.

Incremental sustainable innovations are generally more complex than incremental non-sustainable innovations. Decreasing the negative impacts on the environment asks for more knowledge about these products and processes. For example, which environmentally friendly materials can be used to make products become more sustainable, how do processes work now and how product or processes can be redesigned to save energy? The study of Smith (2008) showed that for incremental sustainable innovations besides the marketing department, also R&D and Environmental Management were influential departments. Working together in cross-functional teams is important for success with both the incremental and radical sustainable innovations.

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necessary. In line with this research Horbach (2013) found evidence that sustainable innovations need more research input and more high-skilled employees than non-sustainable innovations. In cross-functional structures specialized employees are working together and therefore more knowledge is available. Because of this it is expected that both the incremental sustainable innovations and the radical sustainable innovations benefit more from cross-functional structures. Therefore this research hypothesizes that:

H3 Firms that apply a cross-functional structure for their incremental sustainable innovations display significantly higher level of incremental sustainable innovation performance than firms that apply a functional structure

H4 Firms that apply a cross-functional structure for their radical sustainable innovations display significantly higher level of radical sustainable innovation performance than firms that apply a functional structure

2.5 Research model

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Figure 2. Research model

Organizational structures Functional structure Cross-functional structure

H1: Incremental non-sustainable innovation performance Number of incremental non-sustainable innovations Sales percentage of incremental non-sustainable innovations

H2: Radical non-sustainable innovation performance Number of radical non-sustainable innovations

Sales percentage of radical non-sustainable innovations

H3: Incremental sustainable innovation performance Number of incremental sustainable innovations Sales percentage of incremental sustainable innovations

H4: Radical sustainable innovation performance Number of radical sustainable innovations Sales percentage of radical sustainable innovations

Control variables

Firm size, firm age, industry, NPD strategy and innovative culture

F** CF*

CF*

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3 | Methodology

3.1 Research design

The goal of this research is to investigate how organizational structures influence (non-)sustainable innovation performance in the Netherlands. Based on the literature, a research model (see chapter 2.5) has been created. This research model will be tested through statistical analysis. Since the goal of this research is to investigate “which” structure favors which (non-)sustainable innovation, a quantitative research approach is used. By executing a quantitative research, it is possible to approximate how much one variable is related to other variables.

3.2 Data collection

This study has approached firms that bring sustainable innovations to the market. The contact data was gathered through industry associations and companies’ websites. A starting point for the search for firms that could participate in the survey was the government-led initiative Green Deals (www.green-deals.nl). Green Deals is a cooperative partnership that helps firms to become more sustainable. It supports firms and associations by bringing parties together, by providing them with knowledge and by trying to change regulatory barriers. On their website, Green Deals published a list with the most sustainable industries in the Netherlands. Those industries associations keep member lists, which were used to distribute the survey. It is assumed that this is a representative sample of the environmentally innovative firms in the Netherlands. Besides the list with companies on the website of Green Deals, Dutch companies participating in eco-innovation projects from the European Commission and companies registered on the website of MVO Netherlands are used as well. Table 1 shows a list of industry associations from which members were e-mailed with a request to participate in the survey. In all, 695 companies were approached.

Table 1. Consulted industry associations

Industry association Website Federatie Technologie Branch www.fhi.nl

Dutch Material Handling www.dutchmaterialhandling.nl

Organisatie duurzame energie www.duurzameenergie.org

Federatie Nederlandse Levensmiddelen www.fnli.nl

Vereniging Leveranciers Milieutechniek www.vlm.fme.nl

Holland Health Tech www.hollandhealthtech

Foodvalley www.foodvalley.nl

Contactnet Duurzame Innovatie Noord-NL www.codin.nl

Lean & Green www.lean-green.nl

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European Commission www.eaci-projects.eu

MVO Nederland www.mvonederland.nl

This research collects survey data. Prior to the final survey, the suitability and understandability of the questionnaire were pre-tested by two staff members of a Dutch university and two product managers. The questionnaire was developed and run using Thesis Tools (www.thesistools.com), and distributed by email. The email included an explanation of the purpose of the study and the link to the questionnaire. Since the email and questionnaire have been sent to firms operating in the Netherlands, the questions of the survey and the email were translated to Dutch, to pursue a higher response rate. In addition, amongst all respondents that provided ad the end an email address three freshly baked apple pies were raffled to increase the response rate. Further, a follow-up email was sent after one week to the companies who did not fill in the questionnaire.

The questionnaire targeted managers with knowledge of sustainable innovations and organizational structures, and consisted of five parts: 1) general information of the firm and the respondent, 2) NPD strategy, 3) innovative climate, 4) questions related to sustainable innovations, and 5) questions related to organizational structures. Different scales and ratings were used in the questionnaire: these included Likert scale ratings, multiple choice, text entries and matrix questions. The questionnaire can be found in Appendix 1.

The dataset contains 113 out of 695 firms that were contacted to participate in the survey, representing an overall response rate of 16.3%. After the deletion of outliers and non-complete questionnaires, the dataset contained 82 firms. This was done to ensure that respondents filled in all relevant data on the used structures for their incremental and radical innovations, the number of innovations and the percentages of sales contributed to the innovations were missing. Independent samples t-test showed that the 31 firms, which were dropped, did not differ significantly from the 82 used firms in terms of mean averages for the main constructs.

3.3 Measures

3.3.1 Independent variables

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brought together. In particular, respondents were asked to indicate which NPD structure was most commonly used for which type of innovation.

3.3.2 Dependent variables

Following the study of De Visser et al., (2010) this study used innovation performance as a dependent variable, where innovation performance was measured as the percentage of sales created by the innovation in the past three years. In addition another measurement was included, namely the number of innovations. As mentioned earlier innovations can be classified in two broad categories: incremental innovations and radical innovations. In this research the classification of Brezet’s (1997) model will be used to typify sustainable innovations. To achieve greater reductions in environmental impact, greater changes must generally occur. Therefore companies must move from incremental sustainable innovations tot more radical forms (Von Weizacker, Lovins, & Lovins, 1997). This line of thinking brings the scale from low to high efficiency into alignment with the scale from incremental to radical eco-innovation. Incremental sustainable innovations include (1) product improvements and (2) product redesign. Radical innovations include (3) functional innovations and (4) system innovations.

Number(of(innovations(

Respondents were asked to indicate how many products their company produced for each type of innovation, for the years 2010 - 2012. The types of innovations are: (1) Incremental non-sustainable innovations, (2) incremental sustainable innovations, (3) radical non-sustainable innovations, and (4) radical sustainable innovations.

Percentage(of(sales(generated(

Respondents were asked to indicate for each type of innovation that has been introduced in the years 2010 - 2012 for what percentage it contributed to their total annual sales of 2012. An important side note is that the sum does generally not equal 100%, because of sales generated by products that exist longer than 3 years.

Reliability analysis indicated that none of the four performance variables (% of incremental (non-) sustainable innovations – number of incremental (non-)sustainable innovations and % radical (non-) sustainable – number of radical (non-)sustainable innovations) are related to each other and that they are distinctive variables. Therefore these two variables have to be analyzed separately for all hypotheses.

3.3.3 Control variables

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Age also impacts product innovation, although its impact is not straightforward (Pereira & Vence, 2012). A firm with a wide historical trajectory can have experience with or know-how of cases that favour a fast response to new opportunities or problems that arise. However, it could also have a dark side when routines control the activities of the business and therefore creating a barrier to new opportunities. In this research firm age is measured by the age of the firm in 2012.

A third control variable is NPD strategy. Result of previous studies showed that firms could differ in terms of the extent to which their NPD strategy is professionalized, and that professionalization of the NPD strategy can impact a firm’s innovation performance. In particular, respondents are asked to indicate on a seven-point Likert scale to what extent they applied the following five strategy-related NPD practices as identified by Cooper & Kleinsmidt (1995) and Cooper et al. (2004): (1) the role of NPD in achieving business goals is clearly articulated, (2) there is a formally stated NPD strategy, (3) there are clearly defined goals for all of the individual new products, (4) systematic portfolio management is in place, and (5) the project portfolios are aligned with the business strategy. The factor analysis showed that the five variables could be combined into one variable, since one component arises in the model. Reliability analysis indicated that the scale’s reliability is high (Cronbach’s α = .88). The construct professionalization of NPD strategy is calculated as the mean of the scores on these five items.

Organizational climate may also influence a firm’s innovation performance (de Visser et al., 2010). This study uses innovative climate that is characterized by intrapreneurship, risk-taking behaviour and mutual trust, and will stimulate innovation (Cooper et al., 2004; Ernst, 2002). Innovative climate was measured on a six-item scale adopted from Parry, Song, De Weerd-Nederhof, & Visscher (2009). This scale measures the degree in which employees are (1) emotionally involved in firms goals, (2) trust each other, (3) have conflicts, (4) have freedom to define their work, and have time to (5) develop and (6) support new ideas. Factor analysis of these six variables indicated that “high conflict” did not belong to the main construct. Therefore “high conflict” will be deleted from the grouped variable. After deleting high conflict reliability analysis indicated that the reliability of these five items is high (Cronbach’s α = .91).

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and (11) consultancy, research and other specialist services. If none was applicable, they could enter “other”.

3.4 Data analysis

To find evidence to reject or to accept the hypothesis all collected data was inserted into the statistical program SPSS 20. The data were analyzed using an independent samples t-test and via multiple regression. The independent samples t-test is used for analyzing whether the means of the dependent variables differ significantly between the different independent variables (functional versus cross-functional). In other words, comparing the means of the innovation performance across the two organizational structures. Multiple regression analysis is used to estimating caused relationships among variables. To be more precise, regression analysis helps to find how the value of the dependent variables changes when one of the independent variable or control variables varies, while the other variables remain fixed.

The regression analysis is performed in a hierarchal manner, meaning that firstly the independent variable is entered, which is presented in model 1 and secondly the control variables are entered in model 2. For this analysis, some variables had undertaken a log-transformation. This transformation was necessary to control for the skewed distribution of the variables firm size, firm age and innovative climate. The formula of the regression model used at this analysis can be found below. There are several unknown parameters denoted as β.

Y1i to Y8i = α0 + β1X1i + β2X2i + β3X3i + β4X4i + β5X5i + β6X6i + β7X7i + β8X8i + β9X9i + β10X10i + β11X11i + β12X12i +

β13X13i + β14X14i + β15X15i + β16X16i + ɛi

Y1i to Y8i = different dependent variables (e.g. number of incremental non-sustainable innovations, sales

percentages of incremental non-sustainable innovations, number of incremental sustainable innovations, sales percentages of incremental sustainable innovations, number of radical non-sustainable innovations, sales percentages of radical non-sustainable innovations, number of radical sustainable innovations and sales percentages of radical sustainable innovations)

α0 = constant, unstandardized B coefficient of base case χ1i = independent variable: organizational structure

χ2i = control variable: firm age

χ3i = control variable: firm size

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Validation(

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4 | Results

4.1 Respondent characteristics

The average size of firms was 4985 FTE, with a minimum of 1 FTE and a maximum of 370000 FTE. The average age of firms was 67 years with a minimum of 1 year and a maximum of 295 years. Total average annual sales in 2012 was €1.362.088,82. Concerning R&D expenditures, most of the companies (56.1%) spent more than €50.000 on R&D while 18.3% spent less than €1000 on R&D. Of 82 companies, 64 (78,0%) introduced at least one sustainable innovation between the years 2010 and 2012. About half of the sample (48.8%) introduced fewer than 5 sustainable innovations within these 3 years. 20.7% of firms has an Environmental Management System certificate while 25.6% of all firms in the sample had a chief sustainability officer or someone who is in charge of the corporation’s sustainability program. When looking at organizational structures, out of 82 firms 50 firms (61,0%) used both structures for all four types of innovations, 13 firms use only functional structures and 19 firms use only cross-functional structures.

Table 2 provides an overview of the frequencies and percentages of used structures for both the sustainable and non-sustainable incremental and radical NPD processes. This table indicates that for both the radical non-sustainable and radical sustainable NPD processes, cross-functional structures are much more common than functional structures. However, for the incremental NPD processes the results are more ambiguous. Structure use for incremental non-sustainable NPD processes is nearly equally divided: 33 functional structures and 32 cross-functional structures. The same applies to the sustainable incremental NPD processes, 28 firms uses functional structures and 39 uses cross-functional structures.

Table 2. Frequencies and percentages different type of innovations

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Table 3 and 4 show which kind of structures firms apply for their incremental and radical non-sustainable NPD processes (table 3) and incremental and radical sustainable NPD processes (table 4). Both tables illustrate that the majority of the responding firms apply a homogenous approach for structuring their NPD processes. In particular, 76,2% of the firms with sustainable NPD processes rely on a non-mixed structure, which means that for both their incremental and radical non-sustainable NPD processes firms use the same structure (functional – functional or cross-functional – cross-functional). An even higher percentage (85,8%) of firms rely on a non-mixed structure for their sustainable NPD processes. This means that the group of firms relying on a mixed structure is rather small, 23,8% for the non-sustainable NPD processes and 14,2% of the non-sustainable NPD processes.

Table 3. Combination of non-sustainable innovation structures

Incremental non-sustainable NPD processes

Radical non-sustainable NPD processes

Functional Cross-functional Functional 18 (28.6%) 14 (22.2%)

Cross-functional 1 (1.6%) 30 (47.6%)

Table 4. Combination of sustainable innovation structures

Incremental sustainable NPD processes

Radical sustainable NPD processes

Functional Cross-functional Functional 19 (30.2%) 8 (12.7%)

Cross-functional 1 (1.6%) 35 (55.6%)

4.2 Independent samples t-test: comparing means

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Table 5. Incremental non-sustainable innovations

Mean

Functional Cross-functional Mean difference t Sig.* (2-tailed) Number 9.75 (23.19) 2.00 (4.44) 7.75 1.85 .07*

Sales 14.63 (24.18) 9.14 (19.78) 5.49 .93 .36 *p < 0.1, **p < 0.05, ***p < 0.01, Standard Deviations are between brackets

Table 6 shows that firms using a cross-functional structure provide a higher number of radical non-sustainable innovations than firms using a functional structure (MD = 5.45). In other words, using a functional structure for the radical non-sustainable NPD process will results on average in 6 innovations less. Mean of the sales percentage of radical non-sustainable innovations is not significantly different (p > 0.1).

Hypotheses 2 stated that: “firms that apply a cross-functional structure for their radical non-sustainable innovations display significantly higher levels of radical non-sustainable innovation performance than firms that apply a functional structure”. Since only one dependent variable of the hypothesis is significant, hypothesis 2 is partially accepted.

Table 6. Radical non-sustainable innovations

Mean

Functional Cross-functional Mean difference t Sig.* (2-tailed) Number 0.55 (1.28) 6.00 (17.93) -5.45 -1.96 .06*

Sales 4.21 (8.21) 9.50 (21.50) -5.29 -1.33 .19 *p < 0.1, **p < 0.05, ***p < 0.01, Standard Deviations are between brackets

Results of the independent sample t-test on incremental sustainable innovations show that both the number and the sales percentage are not significant different across organizational structures (p > 0.1). Therefore hypothesis 3 “firms that apply a cross-functional structure for their incremental sustainable innovations display significantly higher level of incremental sustainable innovation performance than firms that apply a functional structure” is rejected.

Table 7. Incremental sustainable innovations

Mean

Functional Cross-functional Mean difference t Sig.* (2-tailed) Number 5.89 (18.74) 4.14 (7.34) 1.75 .51 .61

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structure. Firms that use a cross-functional structure for their radical sustainable NPD process will have a higher number of radical sustainable innovations ((MD = 3.447). A strong significant difference is found on the sales percentage of radical sustainable innovations between the functional and cross-functional structure (t = -3.758, p < 0.01). In other words, when firms use a cross-functional structure for their radical sustainable NPD process the percentage of sales will be much higher (MD = 18.901). Based on this analysis hypothesis 4 “firms that apply a cross-functional structure for their radical sustainable innovations display significantly higher level of radical sustainable innovation performance than firms that apply a functional structure”, is accepted.

Table 8. Radical sustainable innovations

Mean

Functional Cross-functional Mean difference t Sig.* (2-tailed) Number 0.67 (1.53) 4.11 (12.82) -3.45 -1.76 .09*

Sales 2.05 (6.03) 20.95 (31.71) -18.90 -3.76 .00*** *p < 0.1, **p < 0.05, ***p < 0.01, Standard Deviations are between brackets

4.3 Regression analysis: estimate relationships among variables

In this section, it will be investigated whether the dependent variables (innovation performance) can be explained by the organizational structure (functional versus cross-functional) while controlling for other variables (industry, age, size, innovative climate and NPD strategy). Since regression only allows for one dependent variable, each of the dependent variables had to be analyzed separately. The results of the regression analysis are summarized in table 9 - 16. The regression analysis is performed in a hierarchical manner, starting in model 1 with the independent variable and after, in the second model, the control variables are added.

Prior to conducting a multiple regression analysis it is necessary to check for multi-collinearity between the dependent variables. Multicollinearity issues arise when intercorrelations among the predictors are very high (Malhotra, 2010). Multicollinearity is high when the VIF-score exceeds 5 (i.e., when the tolerance is lower than 0.20). Multicollinearity can result in the exclusion of one or more of the independent variables from further analysis (Gravetter & Wallnau, 2000). All VIF-scores were less than 3, so no concern for multicollinearity exists. This provides support for the use of the regression analysis.

Incremental(non;sustainable(innovation(performance(

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number of incremental non-sustainable innovations, and both firm age and industry type “information and communication” are significant on a 10% level.

As both table 9 and 10 shows no relationship between the two measures of innovation performance and the organizational structure has been found, while controlling for the other variables, therefore hypothesis 1 is not confirmed.

Table 9. Regression results number of incremental non-sustainable innovations

Variables Model 1 B Model 2 B Organizational structure -7.96* -4.61

NPD strategy .11

Innovative climate (LOG) 20.58

Firm size (LOG) 13.28***

Firm age (LOG) -9.25*

Food, drinks & tobacco -8.70

Textile, fashion & shoes -22.18

Energy -6.85

Wholesale & retail -.28

Transport & storage 2.27

Information & communication -16.76*

Consultancy, research & other -4.03 *p < 0.1, **p < 0.05, ***p < 0.01

Table 10. Regression results sales percentage of incremental non-sustainable innovations

Variables Model 1 B Model 2 B Organizational structure -5.54 -4.49

NPD strategy 2.14

Firm size (LOG) 6.07

Firm age (LOG) -5.60

Food, drinks & tobacco 8.72

Energy -11.71

Wholesale & retail -9.45

Transport & storage -12.66

Information & communication -2.09

Radical(non;sustainable(innovation(performance(

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significant on a 5% level (p < 0.05) and both negative. A weak negative significance is found between the number of radical non-sustainable innovations and industry type “food, drinks and tobacco”, indicating that firms operating in this industry introduce fewer radical non-sustainable innovations.

Results in table 12 show no relationship between the organization structure and the sales percentage of radical non-sustainable innovations (p > 0.1). The only control variable that is significant related is industry type “information and communication (B = -15.0, p < 0.05). Since both table 11 and table 12 found no significant effect of the organizational structure on the number and the sales percentage, hypothesis 2 is rejected.

Table 11. Regression results number of radical non-sustainable innovations

Variables Model 1 B Model 2 B Organizational structure 5.70 .42

Firm size (LOG) 13.20***

Firm age (LOG) -9.77**

Food, drinks & tobacco -8.08*

Energy -2.97

Wholesale & retail 3.53

Information & communication -14.99**

Table 12. Regression results sales percentage of radical non-sustainable innovations

Variables Model 1 B Model 2 B Organizational structure 5.64 3.39

Firm age (LOG) -7.83

Energy .81

Information & communication 29.63**

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Incremental(sustainable(innovation(performance(

Table 13 shows that again firm size has a strong significant influence on the number of incremental sustainable innovations. Further when firms are elder they will have less incremental sustainable innovations (firm age: B = -8.4, p < 0.05) and results also show that industry type “information and communication” has a weak significant effect on the number of incremental sustainable innovations. In other words firms of this industry have on average less incremental sustainable innovations (B = -12.2). This time the sales percentage of incremental sustainable innovations is not significant influenced by the firm size. Instead a significant and positive effect has found between the industry type “food, drinks and tobacco” (B = 25.6, p < 0.05). This means that the percentage of sales for firm of this industry is much higher. Both table 13 and 14 show that innovation performance can not be explained by the organizational structured, while controlling for the other variables, therefore hypothesis 3 is rejected.

Table 13. Regression results number of incremental sustainable innovations

Variables Model 1 B Model 2 B Organizational structure -1.71 -3.62

Firm size (LOG) 10.41***

Firm age (LOG) -8.40**

Energy -4.23

Information & communication -12.24*

Consultancy, research & other 2.31 *p < 0.1, **p < 0.05, ***p < 0.01

Table 14. Regression results sales percentage of incremental sustainable innovations

Firm size (LOG) -.33

Firm age (LOG) 2.74

Food, drinks & tobacco 25.56***

Energy 5.19

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Radical(sustainable(innovation(performance(

Both the model of the number of radical sustainable innovations as a whole and the organizational structure are not related to the number of radical sustainable innovations (p > 0.1). There are also no control variables that have a significant influence on the number. In contrast the organizational structure has a significant influence on the sales percentage of radical sustainable innovations. Furthermore there are no other variables that are related to the sales percentage.

As table 16 shows in both model 1 and model 2 the sales percentage of radical sustainable innovations is positively influenced by the organizational structure. In other words when firms go from a functional to a cross-functional structure without the control variables their sales percentages increases with 20% and when control variables are added (model 2) it increases with 17%. Based on the results of table 15 and 16 the correlation partially support hypothesis 4.

Table 15. Regression results number of radical sustainable innovations

NPD strategy -.79

Firm size (LOG) 5.84***

Firm age (LOG) -6.85*

Energy -.27

Agriculture, forestry & fishery -4.76

Table 16. Regression results sales percentage of radical sustainable innovations

Variables Model 1 B Model 2 B Organizational structure 19.75** 16.55*

Innovative climate (LOG) -33.77

Firm age (LOG) -26.38***

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Energy -8.19

Agriculture, forestry & fishery -42.82**

Transport & storage -25.25

The results of both the independent samples t-test and the regression analysis are displayed in table 17.

Table 17. Results hypotheses

Type of analysis Partially accepted Fully accepted # %

H1 Firms that apply a functional structure for their incremental

non-sustainable innovations display significantly higher levels of

incremental non-sustainable innovation performance than firms that apply a cross-functional structure

T-test ✓ Regression

H2 Firms that apply a cross-functional structure for their radical

non-sustainable innovations display significantly higher levels of radical

non-sustainable innovation performance than firms that apply a functional structure

T-test ✓ Regression

H3 Firms that apply a cross-functional structure for their incremental

sustainable innovations display significantly higher level of

incremental sustainable innovation performance than firms that apply a functional structure

T-test Regression H4 Firms that apply a cross-functional structure for their radical

sustainable innovations display significantly higher level of radical

sustainable innovation performance than firms that apply a functional structure

T-test ✓

Regression ✓

Results seem to indicate that the more radical and the more sustainable the innovations become (moving from left to right in figure 3), the more cross-functional structure is preferred. Which in turn leads to higher innovation performance.

Figure 3 Organizational structures per type of innovation

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5 | Discussion and conclusion

5.1 Findings

This research aims to analyze the influence of organizational structures on non-sustainable and sustainable innovations performance. In other words: which organizational structure (functional or cross-functional) provides a higher number of innovations and/or a higher percentage of sales generated by these innovations, and do sustainable innovations favor a different structure than non-sustainable innovations? The main outcome of this study is that no strong and consist linkages are found between the organization structure and the firm’s innovation performance. Still specific linkages or mean differences exist.

Although literature has shown that firms differ in their chosen organizational form (Tushman & Anderson, 1986), the analyses showed that the use of different structures for different types of innovations is rather low. To be more precise, results of the data show that firms mainly apply a non-mixed structure (both types of innovations use the same organizaitonal structure) for both their non-sustainable NPD processes (76.2%) and their sustainable NPD processes (85.8%).

Non;sustainable(innovations(

De Visser et al. (2010) showed that the effectiveness of cross-functional structures is different among different kinds of NPD processes. In particular, organizations that rely on a cross-functional structure for their incremental NPD processes perform significantly lower on incremental innovation performance than organizations that apply a functional structure for their incremental NPD processes. The results of this study partly confirm this finding. The percentage of sales was not significantly higher, even though the second measure of innovation performance - number of innovations - has a significant influence on the incremental non-sustainable innovations. The results show that firms relying on a cross-functional structure on average produce 8 innovations less in the given period, than firms that rely on a functional structure. A reason why only the number of innovations is significant is that percentage of sales is determined on the market success of the innovations while the number of innovations is a pure output measure. The success measures differ. For example, external events (e.g., the financial crisis in 2008) may have impacted the market success of these innovations.

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Sustainable(innovations(

Results of the sustainable innovations are somewhat different. For the sustainable incremental NPD process neither a positive nor a negative effect was found for either the number of sustainable innovations and sales percentage. Since firms only have to minimize or reduce environmental damage and do not have to focus on the transformation of products or processes (radical innovations), they can possibly rely on less highly skilled employees or product knowledge for their incremental sustainable NPD processes. Still, cross-functional structures were used more often (58%) than functional structures for the incremental non-sustainable innovations. In contrast, radical sustainable innovations perform better in both number of innovations and percentage of sales, when using a cross-functional structure instead of a functional structure. This extends the results of De Visser et al. (2010) to the sustainable context. In addition, it became clear that firm age has a strong significant negative influence on the sales percentage of these innovations. A reason for this could be that older firms have a bigger portfolio than younger ones, which makes the influence of any new product on sales percentages relatively small. This in turn explains the negative number.

Finally, some additional conclusions could be drawn out of the results. The literature (Horbach, 2013) mentions that regions characterized by an energy-intensive industry structure might produce more radical sustainable innovations. This study did not find a relationship between the number of innovations and this particular industry. Secondly, it is remarkable that in contrast to earlier findings (De Visser et al. 2010) both the innovative climate and NPD strategy did not have a significant impact on innovation performance. Further, 78% of the respondents introduced at least one sustainable innovation between the years 2010 and 2012. However, still 20.7% of the responding firms have an Environmental Management System certificate and 25.6% had a chief sustainability officer. This number is relatively low compared to the importance of becoming sustainable.

All in all, although the literature (De Marchi 2012; Horbach 2013; Hassi et al., 2009) points to the fact that sustainable innovations differ from non-sustainable innovations, our results did not indicate a strong difference between the used structure for non-sustainable innovations and sustainable innovations. However, this study did find evidence that radical non-sustainable and sustainable innovations are preferred by cross-functional structures. The results also indicate that incremental sustainable innovations are more complex than non-sustainable incremental innovations, creating a stronger need for the use cross-functional teams for sustainable innovations (even for incremental innovations).

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and (2) the percentage of sales dedicated to this innovation. In a previous study (De Visser et al., 2010) innovation was only measured by the percentage of sales. The results indicate that the chosen innovation measure alters the outcome. Researchers should be explicit and explain why they choose for a certain innovation outcome measure.

This study provides managers with knowledge about the differences of managing sustainable innovations and non-sustainable innovations. It can help them increasing their sales percentage by choosing the right structure for the right innovation type. For example, using cross-functional structures for radical sustainable innovations gives more innovations and higher percentage of sales, but using cross-functional structures for incremental innovations gives the opposite result. Secondly, firm size (measured in FTE) had a positive influence on the number of all four types of innovations. If managers want to innovate more, it is expected that recruiting additional staff will provide more innovations.

5.3 Limitations and future research

The field of using different NPD structures for different sustainable innovations is relatively new. Therefore, the results are preliminary and come with several limitations. These limitations could be the starting point for further research. From a methodological perspective, this study is limited by sample size. In total, 82 responses were used. To check the generalizability of the findings, it would be good to test the same hypotheses in a larger sample.

Secondly, this study uses self-report data. The use of more objective data could strengthen the findings and make them less susceptible to social desirability. Further, the survey contains some very specific questions for respondents to answer, which may be difficult to answer accurately. For example, the number of developed product innovations in each category and what percentage of each type of innovation was contributed to the annual sales in 2012 could be backed up with more objective firm data.

Thirdly, the focus of this research was performed in the Netherlands. Previous studies indicated that the relationship between structures, product innovativeness, and project performance is influenced by the national culture in which the firm is embedded. In addition, the research by Song & Xie (2000) showed that nationality also influences the innovation outcome, number of innovation they produce. Therefore, further research should have a broader focus and conduct an international comparison of the impact of organizational structures on the sustainable innovation performance.

5.4 Conclusion

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