Effective Product Innovation Management for the
Homogeneous Product Industry
Master Thesis
by
DEWI TELEHALA
First Supervisor: Dr. Killian McCarthy
Second Supervisor: Dr. Florian Noseleit
University of Groningen
Faculty of Economics and Business
MSc BA Strategy & Innovation
ABSTRACT
This paper explores the impacts of the variables strategy and leadership, culture and climate, planning and selection, structure and performance, and communication and collaboration on the product innovation performance of firms. Research has shown that these five factors facilitate effective product innovation management in the high-technology industry. The aim of this research is to determine whether these findings also apply to a homogeneous product industry. This has never been investigated before and is interesting, because companies producing homogeneous products encounter difficulties differentiating themselves from their competitors. The study uses questionnaires as a data collection tool in order to perform statistical analyses. The results of this study will show that only communication and collaboration is a significant predictor of product innovation performance.
Key words: product innovation, homogeneous product, strategy and leadership, culture and
ACKNOWLEDGEMENTS
This research paper is the very last project in order to graduate for my MBA program Strategy and Innovation at the University of Groningen. Time has flown, and since this is my very last work as a student at the University of Groningen, I would like to grab this opportunity to thank some people that have been very helpful during the process of writing my master thesis. I have chosen for the subject product innovation in the homogeneous product industry,
because I was able to find me an internship at Hoomark BV with this topic. Within this company, I was given the opportunity to learn in real life what it is like to work at an
organization that manufactures a homogeneous product. It has been an interesting and fruitful experience for me, and I would like to thank Hoomark’s managing director Mr. Joost Bogers for giving me the opportunity to do an internship at Hoomark. In addition, many thanks to my supervisor at Hoomark Mr. Eric Hisken for providing me constructive feedback, helping me with questions and his guidance in the organization. Moreover, I would like to thank
Hoomark’s employees for their cooperation.
Additionally, I would like to thank my supervisor Dr. Killian McCarthy for his constructive feedback, and for always replying my messages and questions quick. His constructive feedback and positive thinking made the process of writing the master thesis a very nice learning experience. I would like to thank my second supervisor Dr. Florian Noseleit as well for being so helpful so that I can make my deadline in time.
Moreover, I owe my deepest gratitude to the most important people in my life. These are my parents and sister. They have always supported me and have the strongest believe in me. For this research, they have helped me a lot with finding companies to send my questionnaire to. My parents even spent a lot of time approaching people and firms to fill in my questionnaire during their well-deserved holiday in Indonesia. I appreciate it a lot. Thank you for your support and encouragement to always get out the best of me.
TABLE OF CONTENT
1. INTRODUCTION……….1
1.1. Initial Motive………1
1.2. Problem Statement and Research Question……….2
1.3. Structure Paper……….3
2. LITERATURE EVIEW………...4
2.1. Homogeneous Products………4
2.2. Product Innovation………...4
2.3. Homogeneous Products and Product Innovation……….5
2.4. Product Innovation Management……….7
2.5.Best Practice Model………..8
2.5.1. Strategy and Leadership………9
2.5.2. Culture and Climate………10
2.5.3. Planning and Selection………11
2.5.4. Structure and Performance………..12
2.5.5. Communication and Collaboration……….14
3. RESEARCH DESIGN………...……….15
3.1. Data………15
3.1.1. Sample Description……….15
3.1.2. Instruments and Data Collection.…..………..15
3.2. Variables………16
3.2.1. Independent Variables……….16
3.2.2. Dependent Variable………...17
3.3. Procedure of Data Analysis………17
3.4. Sample Descriptive………18
4. RESULTS………19
4.1. General Characteristics of the Sample………...……19
4.2. Descriptive Statistics………..19
4.3. Reliability Analysis………21
4.4. Correlations………21
4.5. One-Sample T-Test………23
4.6. ANOVA……….23
5. DISCUSSION………..26
5.1. Findings………...26
5.2. Limitations and Directions for Further Research…………...………30
5.3. Implications………31
6. CONCLUSION………33
REFERENCE………..34
APPENDIX 1: QUESTIONNAIRE………...38
APPENDIX 2: DESCRIPTIVE STATISTICS……….40
1. INTRODUCTION
1.1 Initial Motive
Research clearly emphasizes the importance to include innovation in the strategy of
organizations (Bowonder, Dambal, Kumar & Shirodkar, 2010; Cooper & Edgett, 2010). It is important for companies to be creative and innovative in order to survive, compete, grow and lead (Gumusluoğlu & Ilsev, 2009). Even though innovation can influence an organization’s performance positively, it is a very difficult process to manage (Cooper, 1999; Cormican & O’Sullivan, 2004; de Luca & Atuahene-Gima, 2007). The topic of innovation has been investigated in relation to all kinds of different aspects, however the area of focus of this particular research is on factors that facilitate successful product innovation management. This, in turn, can lead to the determination of effective strategies for the product innovation management. This topic has been tested before in the high-technology industry (Cormican & O’Sullivan, 2004), however has never been tested in a homogenous product industry.
Innovation is particularly important for firms producing homogeneous products, because innovation can act as a barrier to imitation. In addition, innovation could be a way out of price competition in this industry (Besanko, Dranove, Shanly & Schaefer, 2010).
Even though there are different types of innovations (Garcia & Calantone, 2002), this particular study only focuses on product innovation. Product innovation is outward-oriented and may result in product differentiation or an increase in product quality (Damanpour, 2010). According to Brown and Eisenhardt (1995), product innovation is an important topic for companies as it can be a source of competitive advantage. This is, because their research shows that product innovation is critical for a firm’s success, survival, and renewal. This is supported by research done by Katilan and Ahuja (2002) who argue that the introduction of new products are crucial for an organization to diversify, adapt, and reinvent themselves in changing markets and technical conditions. Because product innovation is such an important concept for organizations, companies should have clear strategies on how to effectively manage the product innovation processes (Cooper & Edgett, 2010).
A characteristic of homogeneous products is that in the eye of the consumer, these products are perceived as similar (Hwang, Mai & Yang, 2008). This is a disadvantage for firms as early research done by Porter (1980) already demonstrated the importance of product
manufacture a homogenous product are restricted by the fact that their consumers do not make a distinction between the goods.
1.2. Problem Statement and Research Question
The discussion above illustrates that product innovation is an important topic for firms as it strongly affects a firm’s performance (Cooper, 1999; Cormican & O’Sullivan, 2004; Gumusluoğlu & Ilsev, 2009). Even though companies with homogenous products face difficulties differentiating themselves from their competitors, product innovation remains an important topic (Arping & Lóránth, 2006; Boyaci & Ray, 2006; Hsu, 2009). Probably product innovation is even more important for such firms because product innovation can lead to product differentiation and/or an increase in product quality (Damanpour, 2010).
The aim of this research paper is to provide an answer to the following research question:
Which factors facilitate effective product innovation management in the homogeneous product industry? This particular research question guides the complete research report.
In order to provide an answer to this research question, a literature study was conducted first to determine what has already been written about this topic. Previous research shows that many different factors facilitate effective product innovation management (Jassawalla & Sashittal, 2002; Johanessen, Olsen, & Olaisen, 1999; Lau, Tang, & Yam, 2010; March-Chordà, Gunasekaran & Begoña, 2002). Nevertheless, the Best Practice Model developed by Cormican and O’Sullivan (2004) best summarizes the most important ones. Cormican and O’Sullivan (2004) argue in their research paper that strategy and leadership, culture and climate, planning and selection, structure and performance, and communication and collaboration facilitate successful product innovation management in a high-technology industry. The purpose of this study is to determine whether these factors also apply to an industry characterized by the production of homogeneous products. We have chosen to focus on all five factors and not only one or two, because this approach will allow us to provide a fair picture of the most relevant factors for successful product innovation management. We cannot focus only on one or two specific factors since successful product innovation is a combination of different factors together.
produce different products, all products have in common that they are homogeneous and therefore perceived as similar in the eye of the consumer. The data acquired by the
questionnaires allowed us to perform statistical analyses so that valuable conclusions could be drawn.
Furthermore, this particular research focuses on managers of firms that produce a
homogeneous product, because they are the ones that have the power to initiate change, and therefore have the power to influence the product innovation processes. In addition, they are responsible for product innovation management, and therefore can really benefit from the results of this study. The results of this research will show that only the variable
communication and collaboration is a significant predictor for product innovation
performance. Even though most respondents agree on the statements that have been provided in the questionnaire, no significant relationships can be found between strategy and
leadership, culture and climate, planning and selection, structure and performance, and the product innovation performance measure for this study.
1.3. Structure Paper
Regarding the structure of this research paper, there will be first a section that will discuss the literature review. The literature review includes some important definitions such as
homogeneous products, product innovation, and product innovation management. These definitions need to be explained first, because they play such an important role throughout this research. Moreover, there will be a discussion of the Best Practice Model and the five
2. LITERATURE REVIEW
For this part of the research paper, a literature study was conducted to determine what has already been written and investigated in relation to the topic of this study. First, a definition of homogeneous products and product innovation will be provided to understand what this paper is all about. In addition, there will be an explanation of the link between the two concepts to illustrate why it is so important to study both concepts in relation to each other. Furthermore, there will be a discussion of product innovation management, and the Best Practice Model with the five key factors that facilitate effective product innovation management.
2.1. Homogeneous Products
Early research done by Porter (1980) already suggested that companies should differentiate in their products to create barriers for new entrants. Product differentiation is important in order to create competitive advantage through product uniqueness in the market (Kamoto, 2009). Even though product differentiation is such an important aspect for competition, the focus of this research is on companies that produce and sell only a homogeneous product, which is the opposite of a differentiated product.
Homogeneous is defined as consisting of things or people that are all the same or all of the same type (Oxford advanced learner’s dictionary). Applying this to products, it means that the focus of this research is on products that are similar or of the same type perceived by
consumers. A characteristic of a homogeneous product is that consumers are indifferent between the goods. Consumers are not specifically buying a good because it has a certain brand. Rather, they will buy from the lowest-priced producers. In this case, price plays an important role (Hwang et al., 2008). In addition, besides being bounded by price, research has shown that firms competing in this specific industry have similar input factors and technology which results in roughly comparable marginal costs (Yang, 2002).
2.2. Product Innovation
decreases and innovation-inspired margin increases (Aaker, 2007). According to Garcia and Calantone (2002:112), the following definition of innovation best captures the real meaning of innovations from a general perspective. Innovation is “an iterative process initiated by the
perception of a new market and/or new service opportunity for a technology-based invention which leads to development, production, and marketing tasks striving for commercial success of the invention”. In this process, the creation of value is an important aspect. Companies
invest in innovations with the intention to make profit. Patterson (2009) argues that the main reason to start and maintain a business is to create an enterprise that generates high rates of returns through innovations. These high rates of returns are far greater than those that can be obtained through other, more commonly available, investment opportunities. This way, innovation includes business aspects beyond the more traditional concept of product development.
Research further categorizes innovation into product and process innovation. Whereas process innovation is about new elements that are introduced into the production and service
operation, product innovation, the focus of this research, includes the introduction of new products or services to meet an external user need (Damanpour, 2010; Walker, 2005). While process innovation is mainly oriented towards the efficiency or effectiveness of production and therefore may result in a decrease in production cost, product innovation is more output-oriented and may result in product differentiation or an increase in product quality
(Damanpour, 2010). Product innovation transforms business opportunities into tangible products and services (Cormican & O’Sullivan, 2004). In addition, it seems that product innovation has similar characteristics with technical innovation, because they both comprise the adoption of a novel idea for a product or service in the operating component that affects the technical system of an organization (Walker, 2005).
2.3. Homogeneous Products and Product Innovation
The focus of this particular research is on product innovation in the homogeneous product industry. An interesting characteristic of this particular industry is that consumers are
The reason why firms producing homogeneous products should innovate is that innovation implies differentiation (Damanpour, 2010). When a firm is able to differentiate from its competitors, it does not have to compete on price anymore. This is, because the firm offers a distinct product than its competitors. Consumers will only buy from a particular seller if that seller offers a higher consumer surplus than its competitors. Due to product innovation, a firm changes the perceived benefits of a product through innovations. A product innovative firm is striving for monopolistic competition rather than perfect competition, because it wants to make sure that higher prices can be asked. An advantage for a monopolist is higher profits. Under perfect competition, a company is not able to attain sustainable competitive advantage, and the long-term profitability is weak because a firm’s profit will converge to the
competitive level. If a company is able to ask higher prices, producer surplus increases as well. When both consumer and producer surpluses increase, the value creation of a firm will increase. Additionally, another advantage of product innovation is the acquisition of an early-mover advantage. This is, because the new innovative product has never been produced before (Besanko et al., 2010). To conclude, this discussion shows that innovation acts as a barrier to imitation and is a way out of price competition within this industry.
Furthermore, Boyaci and Ray (2006) argue that one way to improve customer satisfaction for a homogeneous product firms through innovation is to implement fast and/or reliable delivery. Nevertheless, because delivery times, delivery reliabilities, and prices are related to a firm’s capacity, the success of this product differentiation strategy is highly dependent on the capacity of the firm. Arping and Lóránth (2006) argue that because homogeneous products are perceived as similar among consumers, managers of firms could think of design
innovations in order to achieve still some differentiation with their products. A product design strategy is closely related to new product development strategy. Research argues that a good product design not only benefits the enterprise, but offers consumers knowledge regarding product operation as well, which could represent also excellent values of the enterprise identity (Hsu, 2009).
2.4. Product Innovation Management
According to Kärkkläinen and Elfvengren (2002), product innovation management includes managing all the people in the process involved to create successful and competitive product innovation, and to fulfill the company’s strategies. The long-term success of organizations depends on its ability to provide existing and new customers with a continuing stream of new products. Because there is such a strong link between product innovation and the overall success of the organization, it is very important that managers ensure that this process is properly managed. The problem, however, is that product innovation is very risky and expensive to manage, and often leads to low success rates so that many projects have to be ended midway in the development cycle (Cormican & O’Sullivan, 2004). In addition,
research shows that a high number of new product ideas fail commercially in the market place (Cooper, 1999; Cormican & O’Sullivan, 2004). Several factors that contribute to unsuccessful product innovation management include a lack of customer focus, lack of shared
understanding, poor portfolio management, and poor communication and knowledge transfer (Cormican & O’Sullivan, 2004). The marketing literature, however, argues that many failures in product innovation are due to inability to manage the relationships between market
knowledge, cross-functional collaboration, and knowledge integration mechanisms. Market knowledge includes the information firms have regarding their customers and competitors. In addition, cross-functional collaboration refers to the degree of cooperation and representation of the functional units in the product innovation process. These units include marketing, research and development (R&D), and others. Finally, the knowledge integration mechanisms comprise the formal processes and structure within the organization that ensure the capture, analysis, interpretation, and integration of the market and other types of knowledge (de Luca & Atuahene-Gima, 2007).
definition of goals and objectives, definition of strategic thrust, identification of attack and entry strategies, deployment decisions, and strategic product roadmap. Moreover, research performed by Cooper (1999) shows other important action items such as the overhaul of your process, the implementation of training etc. Even though there are many segmentations of the product innovation process, the process is broadly separated into three phases. These phases comprise discovery, development, and commercialization (Cooper, 2008; Durmuşoğlu & Barczak, 2011; Frishammar & Ylinenpää, 2007).
First, the discovery or ideation phase includes all kinds of activities that allow teams to create and evaluate new product opportunities and ideas. This is an important phase, because the discovery phase has to make sure that no large amount of resources is wasted on bad ideas. Therefore, the activities that comprise this particular phase entail the identification of market opportunities, collection, and analysis of customer requirements, generation of product or service ideas that link opportunities with customer needs, testing the concepts with customers, developments of a clear product description, creation of budget and schedules. In order to avoid delays and problems, technical and non-technical issues can also be specified in this particular phase. Second, the development phase entails the activities that are necessary to create a product. The product requirements and specifications collected in the discovery phase are now put together in a product. In addition, this phase includes the testing of the product. Finally, the last phase comprises the commercialization, formulation, execution, and
synchronization of the launch of the product. This phase is characterized by marketing efforts to convince consumers to buy the products (Durmuşoğlu & Barczak, 2011). This phase can also be called the launch phase (Cooper, 2008).
Even though often a separation is made between the three phases, it is also important to consider that there is a post-launch review. According to Cooper’s model (2008), a tough post-launch review should be implemented to determine accountability for results. This should foster a culture of continuous improvements.
2.5. Best Practice Model
include infrastructure and support systems. In addition, culture (Jassawalla & Sashittal, 2002; Johanessen et al., 1999), customer and supplier involvement seem to play an important role as well (Lau, Tang, & Yam, 2010).
From the literature review done on this particular subject, it can be concluded that there exist many different perspectives on the critical success factors for successful product innovation management. Nevertheless, research shows a lot of overlap. We think that the Best Practice Model developed by Cormican and Sullivan (2004) best shows a summary of the relevant factors for the product innovation processes. The Best Practice Model provides an overview of five key factors facilitating product innovation management. These factors include strategy and leadership, culture and climate, planning and selection, structure and performance, and communication and collaboration.
2.5.1. Strategy and Leadership
Early research done on product innovation shows that product strategy is a critical factor for enabling successful product innovation management (Cooper, 2000; Cooper & Edgett, 2010; Cooper & Kleinschmidt, 2007; Englund & Graham, 1999). When there is no product strategy, people do not know what is expected from them. Therefore, it is important that this is
communicated effectively to all the employees within the organization (Martensen &
Dahlgaard, 1999). If the product strategy is not clear, there is no direction, which in turn leads to poor results (Cooper, 2000). According to Cormican and Sullivan (2004), a product
strategy defines aims, objectives, and strategic areas of product innovation effort. This way, product innovation strategy facilitates team effort, permits delegation, determines how resources should be allocated, and helps the selection of projects.
Additionally, essential elements for successful product innovation management include that product strategy should be linked to the overall strategy of the company, and it should have a long-term commitment (Cooper & Edgett, 2010). Cooper and Edgett (2010) argue that the steps for developing your own product innovation strategy include the definition of goals and objectives, definition of strategic thrust, identification of attack and entry strategies,
deployment decisions, and strategic product roadmap.
function through product strategy are important as well. In addition, even though the Best Practice Model argues that strategies should be flexible enough to respond to changes in the environment, no justification for this argument can be found. Therefore, this particular dimension has been left out in the questionnaire.
Furthermore, even though all employees are very important in the processes of product innovation, leaders take a special role (Amabile, Schatzel, Moneta & Kramer, 2004; Cooper, 1999; Cooper & Kleinschmidt, 2007). Research has shown that leadership is one of the most important factors affecting innovation (Gumusluoğlu & Ilsev, 2009). This is, because leaders can affect the process of innovation in several ways. Leaders have the ability to help its employees to have higher levels of creativity at work, to establish a working environment that stimulates creativity, to create an organizational atmosphere that serves as a guiding principle for more creative processes, and to develop and maintain a system that provides rewards to creative performances. This way, leaders can influence organization’s characteristics such as culture, strategy, structure, rewards systems, or resources (Cormican & O’Sullivan, 2004). In addition, leaders can influence the marketing process of the innovative products at all levels of the organization. As will be discussed in the next section about the organizational culture, important characteristics of an innovative organization include being proactive, take risks, create commitment, and initiate change. Therefore, an important feature of leadership is that senior management is committed to risk taking (Cormican & O’Sullivan, 2004).
Because the literature confirms that strategy and leadership are crucial factors to facilitate successful product innovation management, for this research it is hypothesized that
H1: strategy and leadership are important determinants for successful product innovation management in firms with homogeneous products.
2.5.2. Culture and Climate
Schneider, Brief, and Guzzo (1996) argue in their article that culture and climate are linked to each other. Whereas organizational culture entails beliefs and values of the members of the organization, climate entails policies, practices, and rewards. Culture and climate are
interconnected, because policies, practices, and procedures (climate) change, when the values and beliefs (culture) of management change.
with bad habits or incompetence. Important features of an innovative organization include being proactive, take risk, create commitment, and initiate change (Cormican & O’Sullivan, 2004; Johanessen, et al., 1999). In order to have an appropriate culture for effective product innovation, an organization should stimulate a culture of openness and sharing. This is done through knowledge creation, knowledge transfer, and knowledge reuse. Important ways to stimulate these processes could be by motivating employees, or implement knowledge management activities in the day-to-day business processes, internal systems, and structures (Cormican & O’Sullivan, 2004).
Moreover, the results of the case study done by Cormican and O’Sullivan (2004) show that it is important that when mistakes are made, they should not be punished. This allows for better stimulation of creativity. In addition, the role of product champions and intrapreneurs also seem important. Product champion and intrapreneurs are crucial for the generation of new product ideas, the presentation, and promotion to influential stakeholders, and the introduction of the product innovation (Howell, 2005). Therefore, it is important than organizations permit the emergence of these significant players.
Because the literature confirms that culture and climate are crucial factors to facilitate successful product innovation management, for this research it is hypothesized that
H2: culture and climate are important determinants for successful product innovation management in firms with homogeneous products.
2.5.3. Planning and Selection
It is important that firms rationally plan their product innovation plan in advance to achieve new product development success (Cooper & Kleinschmidt, 2007; de Brentani, 2001). According to Cooper and Kleinschmidt (2007), important aspects of the planning and
selection process include up-front homework, and a sharp and clear product definition before the development of the product actually starts. Whereas up-front homework includes
all these factors have to make sure that the projects chosen fit the overall strategy and goal of the company (Cooper & Kleinschmidt, 2007)
Furthermore, besides that projects should be linked to the overall strategy and goal of the organization, they should also be linked to customers’ needs (de Brentani, 2001; Cooper, 1999). It is important that the voice of the consumer is build into all product innovations (Cormican & O’Sullivan, 2004). In addition, important to note is that the portfolio of products should be matched to the firm’s competencies and capabilities. Martensen and Dahlgaard (1999) argue that there are questions an organization has to ask itself first before making a product innovation strategy. These questions concern the organization’s capabilities, customer demand, and technological limitations.
Additionally, research by Cormican and O’Sullivan (2004) adds that important features of this particular category are that an effective product plan is consistently implemented, and the project and spending breakdown mirrors the organizations goals and measures. In addition, it is important that there is a right balance of projects, because success depends on finding synergies between the projects (Cooper, 1999). Therefore, Cormican and O’Sullivan (2004) argue that portfolio management techniques and methods should be incorporated in the selection process.
Because the literature confirms that planning and selection are crucial factors to facilitate successful product innovation management, for this research it is hypothesized that
H3: planning and selection are important determinants for successful product innovation management in firms with homogeneous products.
2.5.4. Structure and Performance
Cormican and O’Sullivan (2004) make a distinction between organic and mechanistic organizational structures in their research. Early research done by Damanpour (1991) shows that the adoption of innovation is easier when organizations have characteristics of an organic structure. An organic structure is characterized by being informal, flexible, open to risk-taking, and always searching for creative solutions while mechanistic structures are inherently more formalized, bureaucratic, inflexible, and standardized (Menguc & Auh, 2010). Cormican and O’Sullivan (2004) add to this that organic structures are decentralized whereas
mechanistic structures are centralized. From this, it can be inferred that in order to stimulate creativity in an organization, it is better to have a decentralized organic structure as
rich environment. Centralization, which is a feature of a mechanistic structure, does not stimulate people to challenge basic assumptions nor does it allow people think for themselves. Moreover, even though organizational structures can be classified under the degree of
formalization, centralization, and organizational size, looking at the degree to which an organization is formal or informal has been shown to be very relevant in the product innovation context (Damanpour, 1991).
Furthermore, making use of cross-functional teams can really benefit an organization (Bunduchi, 2009; Sethi, Smith & Park, 2001). According to Stehi, Smith and Park (2001), cross-functional teams consist of members from different functions such as marketing, engineering, research and development, manufacturing, and purchasing, working together. Cross-functional teams can be an advantage for organizations because they can lead to shorter development time and higher product innovativeness when they are managed properly. Increased speed of development and an increase in product innovativeness are important things as they influence process performance, project success, and organizational
performance. The main reason why cross-functional teams are so important is, because they stimulate creativity in new product development. This is due to the increase of information diversity when more people are involved. More information diversity allows greater problem-solving activity. This is especially important when an organization persuades a product innovation strategy for radical innovations (Bunduchi, 2009). Even though research shows that there are definitely some disadvantages of cross-functional teams since they can also influence a company’s performance in a negative way (Blindenbach-Driessen, 2009; Lovelace, Shapiro & Weingart, 2001), the purpose of this research is to only determine whether the companies in the sample of the homogenous product industry consider the use of cross-functional teams important in their product innovation management process.
Finally, research shows that individuals respond positively to incentives that reward
achievement and performance. For a company, rewards systems can be effective tools to align the interests of the employees to the interests of the organization. An important feature of this particular category is that team members’ rewards should be equitable (Cormican &
O’Sullivan, 2004).
H4: structure and performance are important determinants for successful product innovation management in firms with homogeneous products.
2.5.5. Communication and Collaboration
As discussed earlier in this paper, product innovation management entails managing all the people in the process involved to create successful and competitive product innovation, and to fulfill the company’s strategies (Kärkkläinen & Elfvengren, 2002). Because so many people are involved in the product innovation process, it is important that communication and collaboration are encouraged.
Cormican and O’Sullivan (2004) make in their article a distinction between internal and external communication. For internal communication to happen, gatekeepers play an
important role. Accordingly, a gatekeeper is a person that scans the organization’s boundaries and communicates this information to those people inside the organization. Further, the results of their studies show that face-to-face interaction is one of the most powerful tools for effective and productive communication. When virtual teams are however present, there is a lack of face-to-face meetings. One way to overcome this difficulty is the implementation of web technologies to support the communication process. More importantly, employees should have access to data of previous projects that concerns innovation to prevent making similar mistakes that have been made in the past.
Additionally, for external communication it is beneficial to integrate customers and suppliers in the product innovation process. Product co-development with customers and information sharing with suppliers seems to have a beneficial impact on the overall product performance, because the involvement of suppliers and consumers provides the opportunity to acquire external resources (Lau, et al., 2010). In addition, as already emphasized before in the paper, consumer needs are important and should be communicated to all so that everyone knows what is expected from them.
Because the literature confirms that communication and collaboration are crucial factors to facilitate successful product innovation management, for this research it is hypothesized that
3. RESEARCH DESIGN
This chapter will discuss the research design of this study and includes three different elements. First, there will be a discussion of the data. This section will provide a description of the sample, and a discussion of the instruments and data collection. Second, the most important variables for this study are discussed that are necessary to test the hypotheses. Third, there will be discussion of the data analysis procedures to illustrate what kind statistical analyses have been performed for this research. Finally, there will be a discussion of the sample descriptive.
3.1. Data
3.1.1. Sample Description
For this study, 130 companies which produce a homogeneous product have been approached with the question whether they could help to find at least five employees within their
company to fill in a questionnaire. Some examples of homogeneous products are paper, wrapping paper, tobacco, agricultural products such as potatoes, sugar, vegetables etc. Since our findings will be applicable to an industry that is characterized by the production of
homogeneous products, we did not limit our sample to a particular country. Rather, we limited the sample to manufacturing firms producing homogeneous products. Therefore, it does not matter in what country this company is situated and we have approached besides many Dutch firms, foreign firms as well.
There were 30 companies that filled in the questionnaire, which means we have a respondent rate of 24%. In total, we have been able to find 47 employees that were willing to fill in the questionnaire for this research on effective product innovation management in the
homogeneous product industry.
3.1.2. Instruments and Data Collection
Data was collected by the distribution of a questionnaire. The questionnaire is a combination of different models found in earlier research. Nevertheless, The Best Practice Model
developed by Cormican and Sullivan (2004) plays a special role. The results of their research show an overview of five key factors that facilitate successful product innovation
The questionnaire includes different statements which ask the respondents to fill in to what extent they agree or disagree with the statements. It is a 5-point Likert scale where 1 represents ‘strongly disagree’ and 5 represents ‘strongly agree’ (see Appendix 1). Even though the aim of the questionnaire is to test whether the five categories of strategy and leadership, culture and climate, planning and selection, structure and performance, and communication and collaboration are crucial for product innovation management in the homogeneous product industry, it was decided to leave those dimensions out of the questionnaire. This means that the questionnaires sent to respondents only state those sub-factors that facilitate these five categories. We aware that a disadvantage of this approach is that the structure of the questionnaire does not look very attractive. However, a main
advantage of this approach is that people do not specifically know what we are asking. We are afraid that if we did show the separate categories, the respondents may want to please us, and therefore won’t be able to provide an objective image.
Furthermore, we have made sure to state some statements in the questionnaire negatively. If all statements were stated in a positive way, there was a tendency that people filled in the survey without thinking about it. In order to get an objective representation, respondents should be forced to think first about the statements before filling in their answer. Thus, to force respondents to think about the statements first, negative statements have been put in place.
3.2. Variables
3.2.1. Independent Variables
In order to test the hypotheses, there are important variables that need to be tested. There are five independent variables in this study. These include:
1) strategy and leadership 2) culture and climate 3) planning and selection 4) structure and performance
5) communication and collaboration.
3.2.2. Dependent Variable
The value of the dependent variable depends on the five independent variables. The dependent variable that is used in this research is:
1) product innovation performance
To determine how the five independent factors affect the product innovation performance of a company, a recognized product innovation performance measure was chosen (Zhang, Di Benedetto & Hoenig, 2009; Zhang, Hoenig, Di Benedetto, Lancioni & Phatak, 2009) which was developed by Im, Nakata, Park and Ha (2003). This product innovation measure
determines the organization’s perception towards the market performance of the introduction of new products. The products concerns products that have been introduced less than three years ago and the respondents were asked to evaluate the contribution of these products. This should be done in relation to sales volume, profitability, and customer satisfaction relative to their competitors and their original objectives.
3.3. Procedure of Data Analysis
Several statistical analyses have been performed on the data acquired by the questionnaires. The aim is to provide an answer to the research question, and to determine to what extent the factors of strategy and leadership, culture and climate, planning and selection, structure and performance, and communication and collaboration are important for a homogeneous product industry. In order to determine whether there are significant impacts between the independent variables and the dependent variable, the procedures of data analysis are designed as follows: 1. Descriptive Statistics
With help of the mean, standard deviation, and mode we were able to see on what statements respondents agreed or disagreed. This allowed us to see whether respondents consider the statements in the questionnaire important for this industry or not.
2. Reliability Analysis
The reliability analysis was performed to investigate whether the values of the Cronbach’s alpha are satisfactory for constructing scales. This was done to check internal consistency and to determine whether the sub-factors in the questionnaire do really measure the scales.
3. Correlation Analysis
performed for the independent variables only to determine whether they all correlate. The correlation coefficients are relevant in order to determine the strength and direction of the relationships.
4. One-Sample T-Test and ANOVA
The one-sample T-test was performed in order to determine whether there are significant differences between the sample mean and those people that filled in the answer ‘neither agree nor disagree’. In addition, the ANOVA test was performed to report means.
5. Simple Regression Analysis
The simple regression analysis was an important analysis, because it showed whether the five independent variables in this study are significant predictors of the dependent variable or not.
3.4. Sample Descriptive
4. RESULTS
This chapter presents the results of the statistical analyses that were performed on the data acquired by the questionnaires. Before discussing the actual results of the analyses, there will be first a section about the general characteristics of the sample in this study. The other sections will show the results of the descriptive statistics, reliability analysis, correlations, one-sample t-test, ANOVA, and simple regression analysis.
4.1. General Characteristics of the Sample
Before discussing the results of the different analyses that have been performed, several important issues concerning the data such as missing values and normality, should be addressed first.
It is first important to check for missing data, because missing data affects your analyses. Even though we have been able to find 47 respondents willing to fill in the questionnaire for this study, one respondent had to be deleted from the sample. This is, because this respondent missed 26 questions out of 50. This means that more than 50% of the questionnaire was not filled in. Consequently, statistical analyses have been performed on a sample size of 46 respondents.
Additionally, there were 14 variables that showed only one case missing. Because this is such a low number, the missing values have been replaced with the mode. We replaced those values with the mode because we are working with ordinal data. Important to note is that the variables that missed one value were not due to the same respondent.
Furthermore, examining skewness and kurtosis values is a way to check normality. We have performed this analysis for the dependent variable to determine whether we are dealing with a normal distribution or not. It is important that you know the type of data you are working with, because there are different measurement instruments for different types of data. Appendix 2 shows an overview of skewness and kurtosis coefficients and standard errors. Since no variable has a skew index higher than 3 and no kurtosis index is higher than 10, it can be concluded that the data is univariate normally distributed.
4.2. Descriptive Statistics
A value of 1 means ‘strongly disagree’, 2 means ‘disagree’, 3 means ‘neither agree nor disagree’, 4 means ‘agree’, and 5 means ‘strongly agree’.
Moreover, looking at the five independent variables separately, it is interesting to note that the majority of respondents ‘totally disagree’ with the statement ‘failures and mistakes should not be tolerated and punished’ (sub-factor of culture and climate). The statements ‘the product innovation programme should have a short-term commitment’ (sub-factor strategy and leadership), ‘all team members should be mutually accountable’ (sub-factor structure and performance), and ‘team members’ rewards should be equitable’ (sub-factor structure and performance) show the highest frequency on the answer ‘neither agree nor disagree’. Table 1 was implemented to show what the valid percentages are for these five statements.
Table 1 Valid percentages on the five statements where the majority of respondents did not
agree or strongly agree on
From table 1, it can be seen what the rest of the respondents filled in for the four statements where the majority of respondents filled in the answer ‘neither agree nor disagree’. The table
Statement 1 2 3 4 5 Strategy and Leadership Culture and Climate Structure and Performance Structure and Performance Structure and Performance
The product innovation programme should have a short-term commitment
8.7% 21.7% 28.3% 26.1% 15.2%
Failures and mistakes should not be tolerated and punished
37.0 26.1 26.1 - 10.9
The company’s structure should be characterized by a centralized structure
15.2 - 41.3 32.6 10.9
All team members should be mutually accountable
8.7 - 39.1 39.1 13.0
Team members’ rewards should be equitable
indicates that the second highest percentage is on the answer ‘agree’ for the first three statements. However, the statement ‘all team members should be mutually accountable’ (sub-factor structure and performance) shows a percentage of 39% on both answers ‘neither agree nor disagree’ and ‘agree’.
4.3. Reliability Analysis
In order to determine the internal consistency of the statements that facilitate the variables used in this study, a reliability analysis was carried out.
Table 2 Reliability analysis of the scales
Scale Value N Mode M(SD) N
(items)
Cronbach’s alpha Product Innovation Performance
Strategy and Leadership Culture and Climate Planning and Selection Structure and Performance Communication and Collaboration 1-5 1-5 1-5 1-5 1-5 1-5 46 46 46 46 46 46 3/4* 4,11 3.56/3.89* 3.78 3.44/3.78* 4.00 3.3696(.72343) 3.7802(.49441) 3.9420(.44613) 3.9831(.47429) 3.7657(.50849) 3.9293(.47701) 6 9 9 9 9 8 .835 .699 .768 .774 .816 .739 *multiple modes
The results of table 1 indicate that the Cronbach’s alpha values of the product innovation performance, strategy and leadership, culture and climate, planning and selection, structure and performance, and communication and collaboration scales all have a value above .70. This is satisfactory which means that Cronbach’s alpha values show that the factors measure the same scale. Consequently, all the statements provided in the questionnaire do measure the dependent variable and five independent variables for this study. For this reason, statistical analyses can be performed on the six scales.
4.4. Correlations
strategy and leadership, culture and climate, planning and selection, structure and performance, and communication and collaboration. The results can be seen in table 3. Table 3 Correlation analyses of product innovation performance with the five independent
variables
Product Innovation Performance
N Sig. (2-tailed) Pearson Correlation Strategy and Leadership
Culture and Climate Planning and Selection Structure and Performance Communication and Collaboration
46 46 46 46 46 .478 .058 .102 .312 .025 .107 .282 .244 .152 .330* *correlation is significant at the 0.05 level (2-tailed)
The results of table 3 show that only one significant correlation can be found between the dependent variable, product innovation performance, and the independent variable, communication and collaboration. This correlation coefficient has a value of .330 with a significant level of 0.05. A correlation coefficient of .33 means that the strength of this relationship is moderate. In addition, this relationship is positive which means that when the value of communication and correlation increases (or decreases), the value of the product innovation performance will increase (or decrease) as well. This also happens the other way around.
coefficient has a value of .32, which is measured with a significance level of 0.05. Thus, there exist a moderate and positive relationship between the sub-factor and the dependent variable. Lastly, another Pearson correlation test was carried out in order to determine correlation coefficients between the five independent variables. These findings can be found in Appendix 3 as well. The tables in Appendix 3 indicate that many significant correlations exist between the independent variables with different significant levels. Interesting to note is that the scale communication and collaboration shows significant correlations with all other independent variables. In addition, no significant correlations can be found between the independent variables strategy and leadership and structure and performance.
4.5. One-Sample T-Test
The one-sample T-test was performed in order to determine the difference between the sample mean and the middle point in this study, represented in this case by the answer category ‘neither agree nor disagree’. The aim of this test is to investigate if the sample mean is significantly lower or higher than the middle point.
Table 4 One-sample t-test analyses of the five independent variables
M(SD) Mean
Difference
T-Value Strategy and Leadership
Culture and Climate Planning and Selection Structure and Performance Communication and Collaboration
3.9240(.44613) 3.7802(.49441) 3.9831(.47429) 3.7657(.50849) 3.9293(.47701) .94203 .78019 .98309 .76570 .92935 14.321*** 10.703*** 14.058*** 10.213*** 13.214*** *** significant at the 0.01 level
The results of the T-test indicate that the means of the answers for all the scales in the analysis are significantly higher than the middle point, as can be seen in table 3. This implies that the majority of the answers for the scales are ‘agree’ or ‘strongly agree’. This shows a very positive attitude of the participants in general for all the items in the scales. Next step is to check if these positive answers determine a positive effect on product innovation. This is what can be seen from the results in the regression analysis.
4.6. ANOVA
posthoc test could not perform. We assume that the reason for this is that the sample size is too small. In addition, for the first category there was only one respondent that filled in ‘disagree’ which means that no posthoc test can be performed. Although the ANOVA is not significant, it is interesting to note that the means for product innovation performance change when the answers differ. Respondents that ‘strongly agree’ have the highest mean for product innovation performance, whereas respondents that ‘strongly disagree’ have the lowest means. This implies that the respondents that strongly agreed with the five factors also have higher means for product innovation performance. Even though the differences between the means are not significant for the sample tested, this remains an interesting observation.
4.7. Simple Regression Analysis
According to Field (2009), for each predictor, your should have 10 or 15 cases of data to be able to perform a regression analysis. Since we have 46 cases, it is possible to perform a regression analysis for this research. A simple regression analysis was performed for the scale communication and collaboration, because this factor is the only factor that correlates with product innovation performance.
Table 5 Regression analysis of communication and collaboration and product innovation
performance Model B SE (B) β p 95% Confidence interval for B Lower bound Upper bound Constant Communication & Collaboration 1.406 .005 .854 .216 .33 .107 .033 -.316 .065 3.127 .935
The simple regression analysis having communication and collaboration as the main predictor of product innovation performance used a sample of 46 respondents. The beta (β)
analysis indicated that the predictor communication and collaboration explains 11% of the variance of product innovation performance (R2 = .109).
5. DISCUSSION
This part of the research paper will discuss some interesting findings that can be drawn from the literature study and the results of the statistical analyses performed in the previous chapter. In addition, there will be a discussion of the limitations and directions for further research, and implications of this study.
5.1. Findings
The five factors standing central throughout this research are based on previous research done on product innovation management in the high-technology industry. The purpose of this particular research is to determine whether the findings found in early research also apply to an industry that is characterized by the production of homogeneous products.
(1) The majority of the respondents agree on the statements that have been provided in the questionnaire.
First of all, important to note is that most people agree on the statements that have been provided in the literature. There was only one statement ‘failures and mistakes should not be tolerated and punished’ (sub-factor of culture and climate) where the majority of respondents totally disagreed. This finding is supported by the literature where Cormican and O’Sullivan (2004) argue that in order to stimulate creativity, mistakes should not be punished. Because all statements are based on findings from previous research, it can be concluded that people working in the homogeneous product industry, consider most sub-factors found in literature vital. However, this finding does not apply for ‘the product innovation programme should have a short-term commitment’ (sub-factor strategy and leadership), ‘the company’s structure should be characterized by a centralized structure’ (sub-factor structure and performance), ‘all team members should be mutually accountable’ (sub-factor structure and performance), and ‘team members’ rewards should be equitable’ (sub-factor structure and performance). These four sub-factors show the highest frequency on the answer ‘neither agree nor disagree’.
(2) Employees working in the homogeneous product industry indicate that the product innovation programme should have a short-term commitment, and the company’s structure should be characterized by a centralized structure. These findings contradict with results from previous research.
of the case study performed by Cormican and Sullivan (2004) shows that it is important that team members are mutually accountable, and that rewards should be equitable. Rewards are effective tools to align the interests of the employees to the interests of the organization, however there should no distinction be made between team members.
Furthermore, while most respondents agree that the product innovation programme should have a short-term commitment, the literature argues that it is important that the product innovation programme has a long-term commitment (Cooper & Edgett, 2010; Cormican & Sullivan, 2004). In addition, most people in the homogeneous product industry agree that the company’s structure should be characterized by a centralized structure, which contradicts with what can be found in the literature. Whereas Cormican and O’Sullivan (2004) argue that centralization does not stimulate people to challenge basic assumptions nor does it allow people to think for themselves and therefore does not stimulate creativity, the results of the questionnaire indicate that the respondents feel that a centralized structure is necessary for effective product innovation in a homogeneous product industry. Thus, the literature study does not show similar findings on all the sub-factors of this research.
Even though these are all noteworthy findings, this does not tell anything about relationships between the variables. The purpose of this study is to determine whether strategy and
leadership, culture and climate, planning and selection, structure and performance, and communication and collaboration are important determinants for successful product innovation management.
(3) Only the variable communication and collaboration has a significant correlation with the product innovation performance of a firm.
The correlations show some valuable results for interpretation. After performing a reliability analysis first, it was shown that scales could be made. This allowed us to determine the relationships between the dependent variable and the independent variables. Only
communication and collaboration show a significant correlation with the dependent variable, which means that only this variable has a linear relationship with product innovation
successful and competitive product innovation, it is important that communication and collaboration are encouraged. This is, because there are so many people involved in the product innovation processes.
Even though, the literature supports that communication and collaboration facilitate successful product innovation performance, this finding contradicts with the Best Practice Model developed by Cormican and O’Sullivan (2004). As discussed in chapter 2, the Best Practice Model argues that there are five key factors that facilitate effective product innovation management. However, this research shows that only communication and collaboration show a significant relationship with the product innovation performance of a company.
(4) The sub-factor ‘product strategy and performance measures should be clearly
communicated to all employees’ is the only sub-factor of communication and collaboration that significantly correlates with the product innovation performance.
Additionally, only one significant correlation can be found between the product innovation performance and the sub-factor ‘product strategy and performance measures should be clearly communicated to all employees’ of communication and collaboration. Therefore, if all
employees are aware of the product strategy and performance measure, you can expect that the product innovation performance of firms will improve. This finding corresponds with the results of the research performed by Cormican and O’Sullivan (2004). Because so many people are involved in the product innovation processes of firms, it is vital that everyone works towards the same goal and everyone knows how to get there. Therefore, for firms it is crucial that all employees are aware of the product strategy and how the performance is measured.
(5) Communication and collaboration correlate significantly with all other independent variables.
the other variables show significant relationships with each other (except strategy and leadership with structure and performance), they do not have the power to influence the product innovation performance of a firm. This is, because they do not significantly correlate with the product innovation performance of a firm. Nevertheless, it can be argued that these four factors still have an indirect relationship with product innovation performance. This is due to their relationship with the communication and collaboration variable.
(6) Product innovation performance tends to increase when respondents agree with the statements provided in the questionnaire.
Even though the ANOVA test did not show a significant correlation, it can be argued that the respondents that filled in ‘strongly agree’ score higher on product innovation performance compared to those respondents that filled in ‘strongly disagree’. This is a relevant observation, because this could mean that a company is successful in their product innovation if they agree that strategy and leadership, culture and climate, planning and selection, structure and
performance, and communication and collaboration are considered as important. This way, these five factors do affect the product innovation performance positively which corresponds with the Best Practice Model that argues that all five factors influence product innovation performance positively. Nevertheless, results have shown that the ANOVA is not significant which is assumed due to the low sample size.
(7) The variable communication and collaboration is the only significant predictor of product innovation performance.
Additionally, the simple regression analysis indicated that the predictor communication and collaboration explains 11% of the variance of product innovation performance. This is a relatively high percentage, which means that this predictor explains a lot from the difference in product innovation performance among companies. Therefore, companies with higher values of collaboration and communication register in general also higher levels of product innovation performance.
5.2. Limitations and Directions for Further Research
The main limitation of this particular research is that the sample size is quite small. The aim of this research was to have a large sample size so that findings can be generalized to a large population. Nevertheless, due to time constraint we were not able to gather more data. This is a bit disappointing, however the data that we were able to acquire allowed us to perform some valuable statistical analyses and therefore we were able to draw valuable conclusions. This is, because product innovation management has never been tested before in an industry
characterized by homogeneous products. Nevertheless, a suggestion for future research would be to have a much bigger sample size so that more and better statistical analyses can be performed such as the ANOVA. In addition, with a bigger sample, it is better possible to generalize your findings to a large population of course.
Additionally, another limitation is that the questionnaire has been filled in by companies that are situated in different countries. This way a country’s culture is not really taken into consideration and it is not known whether this variable would influence the results of this study. In addition, this particular research only focuses on five factors while other factors could have been included as well. A suggestion for further research would be to include other factors as well. This would be an extension of the results that have been found in this
particular research.
5.3. Implications
As discussed in the introduction already, this research paper particularly focuses on managers of firms that produce a homogeneous products. Therefore, there are some practical
implications for managers. Managers have the power to initiate change and therefore we would recommend that, based on the finding of this study, special emphasis should be placed on communication and collaboration. Factors that facilitate communication and collaboration include gatekeepers should be in place to continuously span the external environment, customers and suppliers should be involved in the product innovation process, alliances should be formed with other organizations for mutual benefit, communications among team members should be efficient and effective, communications between project teams should be efficient and effective, information on ideas generated, problems raised and project status should be accessible to everyone within the organization, user needs analyses should be undertaken and communicated to all, and product strategy and performance measures should be clearly communicated to all. It is important that managers stimulate the factors in order to improve communication and collaboration. Important to note though is that the results of this study show that you can expect that when product strategy and performance measures are clearly communicated to all, the product innovation performance will get better. Therefore, it is very important for managers to make sure that everyone within the company knows what the product strategy exactly entails and how product innovation performance is measured. This way, everyone knows what is expected from him or her and there is a clear focus.
Especially because so many people are involved in the product innovation processes, it is vital that everyone works towards the same goal and everyone knows how to get there.
strong relationships that exist between the variables. This is, because managers can use the other variables as some kind of tool to influence communication and collaboration.
Furthermore, a theoretical implication is that although research conducted in the past have turned out that there are five key factors that facilitate effective product innovation
management in the high-technology industry, this research shows that only effective
6. CONCLUSION
The purpose of this study is to provide an answer to the following research question: Which
factors facilitate effective product innovation management in the homogeneous product industry? After first conducting a literature study, it appeared that there are five key factors
facilitating successful product innovation management in the high-technology industry. Since this topic has never been investigated in the homogeneous product industry, we had to
determine whether the factors found in literature also apply to an industry characterized by the production of homogeneous products. The results of the statistical analyses show that only communication and collaboration is a predictor of product innovation performance. Even though this research shows that there exist no relationships between strategy and leadership, culture and climate, planning and selection, structure and the dependent variable, product innovation performance measure, it is shown that there are significant linear relationships between the five factors. Communication and collaboration show positive and moderate to strong significant relationships with the other four factors. This means that when
communication and collaboration improves, you can expect that strategy and leadership, culture and climate, planning and selection, structure and performance to improve as well. Moreover, because communication and collaboration affects the product innovation
performance, it could be perceived that there exist indirect relationship between strategy and leadership, culture and climate, planning and selection, structure and performance and the product innovation performance. However, communication and collaboration stand central in the relationship with the product innovation performance.
Moreover, the answer to the research question would be that only communication and
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