However, studies that would have investigated the effect of formalization of the front-end phase, the creative and chaotic early part of the innovation process, are scare. Typically studies consider both front-end phase and development project phase simultaneously, thus averaging the totally different characteristics of these two phases. This article tested the association between front-end process formalization and perceived superiority of created product concepts. In addition, this article tested the classical contingency hypotheses whether the task uncertainty moderates this relationship.
The study is based on exploratory factor analysis and multiple regression analysis that are used to investigate 133 frontend cases collected from Finnish industrial companies. The results indicated, opposite to the existing theory, that front-end process formalization is associated with superior product concepts. In addition, market uncertainty positively moderates this association, i. e. the more market uncertainty is present the more positive is the association. Implications of results from theoretical and practical point of views are discussed. Introduction
The foundation for successful new product development is created in the front-end phase, which refers to the activities that take place before the formal development project phase (Koen et al. , 2001).
The overall structure and the main characteristics of the future product are all decided in the front-end phase, which then strongly affects subsequent new product development activities. Recent studies indicate that these early front-end activities represent the most troublesome phase of the innovation process, and at the same time one of the greatest opportunities to improve the verall innovation capability of a company (Reid and de Brentani, 2004; Herstatt et al. , 2004; Nobelius and Trygg, 2002; Kim and Wilemon, 2002; Cagan and Vogel, 2002).
The Essay on Operations Management Product Design Process
Chapter 3 Jaime MualimProduct design is the process of defining all of the product's characteristics, such as its appearance, the materials it is made of, its dimensions and tolerances, and its performance standards. Service design is the process of establishing all the characteristics of the service, including physical, sensual, and psychological benefits. There are four steps in product design: ...
The front-end phase nourishes the new product development project phase by producing new incremental and radical product concepts. The front-end phase results in a well-defined product concept, clear development requirements and a business plan aligned with the corporate strategy (Kim and Wilemon, 2002).
In addition, the front-end phase should result a decision on how the product concept will be developed further.
The decision could be to continue with an immediate development project or to put the concept ‘on hold’ to wait for more suitable timing, or even to kill the initiative. However, despite the recognized importance and great development potential of the front-end phase, e. g. compared to the development project phase, there has still been relatively little research on the best practices related to the front-end phase (Nobelius and Trygg, 2002; Kim and Wilemon, 2002; Koen et al. , 2001).
The theoretical discussion is still hindered by general level models, vague terminology and unclear definitions (Zhang and Doll, 2001; Koen et al. , 2001).
The front-end phase has a very strategic nature since important strategic decisions related to e. g. target markets, customer needs satisfaction, value propositions, expected product price and product costs, the main functionalities of products, and the predominately used technologies are all made at this stage (Bonner et al. , 2002; Smith and Reinertsen, 1998; Wheelwright and Clark, 1992).
These decisions embodied in a product concept define and guide the subsequent development activities later in the innovation process. An important activity in the front-end phase is to ensure that decisions and choices serve the best interests of the company and fulfill its long-term strategic objectives. However, strategic guidelines might be missing, misleading or too general to assure an efficient link between strategies and operative level activities, thus making decisions uncertain and unsystematic.
The Term Paper on Strategic Decision Analysis with Mrt Model
For the period of thirteen days of October 1962, the leaders of both sides spent every single moment to tackle the situation when there was a higher-than-ever probability of 100 million Americans, over 100 million Russians, and millions of Europeans being killed. Given the probability of calamity which Anatoly Gribkov - Soviet General and Army Chief of Operations - estimated that “Nuclear ...
Product concepts can become “moving targets” when there is no comprehensive strategy directing the innovation processes (Wheelwright and Clark, 1992).
Other familiar symptoms reflecting front-end failure are new product initiatives that are cancelled half-way through because they do not match the company’s strategy, and delayed top-priority new product initiatives that suffer from a lack of prioritization of assignments (Englund and Graham, 1999; Khurana and Rosenthal, 1997).
Furthermore, Khurana and Rosenthal (1997) have analyzed these front-end failures and found that they emerge because senior managers do not communicate their strategic level expectations, such as the product’s core benefits, choice of market segments, and pricing of products, to the development team. Strategic statements can also be too abstract without giving any direction to front-end activities (Smith and Reinertsen, 1998).
In general, firms seem to want more explicit links between strategy and the new product development process (Hertenstein and Platt, 2000).
Management’s ability to influence strategic choices in product development is naturally greatest at the beginning of the innovation process. However, the typical real involvement pattern shows that management gets heavily involved in the initiative after the design phase has already been completed when development problems have become visible and just when large financial commitment is actually needed (Smith and Reinertsen, 1998; McGrath, 1996; Wheelwright and Clark, 1992).
Unfortunately, the ability to influence the outcome then without considerable and costly redesign effort is low. Management should invest their time proactively to confirm that critical choices made in the front-end phase are strategically feasible from the company’s point of view (Smith and Reinertsen, 1998; McGrath, 1996; Wheelwright and Clark, 1992).
The above mentioned challenges related to front-end execution and management involvement relate to the interesting question of how management should actually control the front-end phase of the innovation process.
The Review on Motivation Effecting Innovation Management
Abstract: This paper discusses the meaning, value and role of innovation and the ways to manage it. The need, necessity and origin of innovations are briefly discussed and contours the different perspectives of the Innovation Management. The various processes of Innovation management are also highlighted drawing special attention towards the overall need of each process and factors affecting the ...
The term ‘management’ refers to individuals such as R&D (research and development) directors or technology directors, who are responsible (based on their organizational position) for assuring that new product development activities fulfill strategic objectives and serve the long-term development needs of the organization. The creative nature of the front-end phase makes it difficult to use a hard command type of control, but still certain controllability is needed to secure the effective use of resources and the achievement of the company’s long-term objectives.
Thus the critical question is how to control the front-end phase of the innovation process while simultaneously maintaining the innovativeness and assuring the company’s long-term objective achievement. However, contingency theorists and many others have acknowledged that the degree of task uncertainty influences the optimal way of organizing management processes (see e. g. Donaldson, 2001; Tidd et al. , 2001; Burns and Stalker, 1966).
Thus innovations including different degrees of task uncertainty, e. . incremental or radical product innovations, probably need different control approaches. This leads to another important question of how task uncertainty in incremental and radical innovations influences the applicability of different control mechanisms. The goal of finding appropriate means to balance control and creativity is not a new issue. There are several studies that have raised this important question in management literature in general (see e. g.
Marginson, 2002; Simons, 1995) and in the innovation and new product development (NPD) context (see e. g. Bonner et al. , 2002; Tatikonda and Rosenthal, 2000; Park, 1998; Brown and Eisenhardt, 1997; McGrath 1996).
One challenge of interpreting sometimes conflicting results of existing management control research in the NPD context, is due to the fact that these studies have investigated NPD projects as a whole, without considering the characteristics of different phases of projects, e. . differences between the front-end phase and the development project phase. As several studies have shown, the nature of these phases is totally different in terms of task characteristics and people involved (Kirsch, 2004; Koen et al. , 2001; Nixon, 1998; Zien and Buckler, 1997).
The Essay on The Project Management Process Groups
The Project Management Process Groups: A Case Study Learning Objectives o Describe the five project management (PM) process groups, the typical level of activity for each, and the interactions among them. o Understand how the project management process groups relate to the project management knowledge areas. o Discuss how organizations develop IT project management methodologies to meet their ...
The front-end phase shows characteristics of high uncertainty and ambiguity, while the development project phase shows characteristics more of formality and certainty.
Reasoning goes further by arguing that because of the different nature of the phases, they should be managed differently as well. This leads to the interesting notion of whether different control mechanisms are generally applicable in different phases of the innovation process. Research on management control of information system development projects give indications that types of management control and control mechanisms change when the initiative proceed from the idea stage towards commercialization (Kirsch, 2004; Choudhury and Sabherwal, 2003).
Results indicate that simple output based controls are preferred over behavior control at the beginning of projects (Choudhury and Sabherwal, 2003).
An other study revealed that informal control modes dominated over formal methods in the requirements definition phase of information system projects whereas formal methods were taken into use in the implementation phase (Kirsch, 2004).
It may be justifiable to wonder whether any type of control is appropriate i. e. has a positive effect on performance in the highly uncertain and even chaotic front-end phase.
Critical question from the practical point of view is whether there is a certain limit (measured in terms of uncertainty) where different types of control becomes ineffective. The importance of studying different phases of the innovation process separately has been discussed by Davila (2000), Olson et al. (1995), and Kirsch (2004).
The author’s own notion is that industrial companies are currently intensively developing systematic approaches to manage and control the front-end phase.
Qualitative studies indicated that many of those development interventions focused on creating some kind of stage-gate model (formalized process model) for the front-end phase. A formal process model is a key mechanism to control front-end activities, and is typically associated with creation of formal reporting channels, review and evaluation procedures, and decision gates. Current theoretical understanding is in line with stated concerns of practitioners, who were afraid of the possible influence a stage-gate process may have on innovativeness in the front-end phase.
The Term Paper on Controlling Processes
Multiple Choice 1. Which of the following is NOT a problem commonly found when monitoring? a) Organizations collect data that are easily gathered b) Gathered data are not the most important to reach the organization’s goals c) There is an undue emphasis on measuring objective output performance d) Inputs measurements are used as a proxy for output completion Answer: c Difficulty: Hard Response: ...
This article aims at helping to understand how management can control the front-end phase of the innovation process in a product innovation context. Process formalization as one type of management control mechanism is taken into closer investigation. Two research questions have been set for this paper: 1. How is front-end process formalization related to the front-end performance? 2. How does task uncertainty influence on the relationship between the process formalization and the front-end performance. Management control and front-end process formalization
Management control has been stated to be an important aspect of organizational design (Eisenhardt, 1985), fundamental management activity (Jaworski, 1988), critical activity for organizational success (Merchant, 1982), and also a central feature of all human organizations (Otley and Berry, 1980).
Merchant (1982) argues that control should especially be directed to strategically important areas in organizations such as NPD. The traditional 1970s and 80s view of control emphasized managerial actions as confirming that activities conform to existing strategic plans.
The present understanding of management control sees it as a function of divergent requirements between creativity and innovativeness, and intended goal achievement (Simons, 1995).
Simons discusses management control systems as “…the formal, information-based routines and procedures managers use to maintain or alter patterns in organizational activities” (Simons 1995, p. 5).
This definition covers both top-down induced and bottom-up emerged strategies. Simons emphasizes that the competitive pressure created by senior management is a catalyst for innovation and adaptation.
Thus traditional command type, top-down oriented control is no longer sufficient. In addition to the top-down information flows and commands that inform lower level employees about the organization’s intended strategies, there needs to be channels transferring information from the bottom of the hierarchy to the top. Through these channels the top management receives information about progress in achieving intended strategies and also information about threats and opportunities that may contain seeds of new emergent strategies. Simons, 1995) The theoretical control framework of this paper is based on Hales (1993) who separates four dimensions of control: 1) focus of control, 2) level of formality of control 3) level of interactiveness of control, and 4) locus of authority of exercising control. The first dimension, focus of control, categorizes management control by placing control practices in a chronological order based on the actual sequence when the control is implemented. This leads to the following categories of management control: input, process, output and value.
The Research paper on Business process management Case Study
1.How would you define “business process management”based on this video and text reading? How would you compare it to business process re-engineering, continuous improvement, and total quality management approaches? Answer: -Business Process Management is most often associated with the life cycle of a business process. The process life cycle spans identifying and improving processes that deliver ...
Input control occurs before the controlled activity. Instructions, materials, and the knowledge and skills of those carrying out the forthcoming work are the main objects of the control. Process control, in turn, is exercised during the activity focusing on work processes and technical work methods of the controlled employees. Output control takes place after the activity and focuses on outputs, material, information or financial results. Finally, value control influences the activities all the time by affecting the planning, implementation and evaluation of work activities.
Value control is a kind of meta control, which is based on the influence of beliefs and norms of the company. (Hales, 1993) Management control can also be classified in formal and informal ways of implementing control (the second dimension in Hales’ framework).
Jaworski (1988 p. 26), who studied control in marketing units, defines formal controls as “written, management-initiated mechanisms that influence the probability that employees or groups will behave in ways that support the stated [marketing] objectives”.
Informal controls, conversely, are “unwritten, typically worker-initiated mechanisms that influence the behavior of individuals or groups in [marketing] units”. Many of different control mechanisms can be applied either informally or formally. Management control can also be applied either in interactive/personal or bureaucratic/impersonal ways (the third dimension in Hales’ framework) (Hales, 1993; Bonner et al. , 2002; Simons, 1995; Fisher, 1995).
Interactive control means that managers have personal contact with the decision making activities of their subordinates (Simons, 1994).
Hales emphasizes that personal control manifests that control is exercised by one individual over others, whereas impersonal control is based on rules and regulations (Hales, 1993).
The locus of responsibility for implementing the control may also be possessed by different parties within the organization (fourth dimension).
The control may rest in the hands of individuals (self-control), a group of colleagues (mutual, peer or clan control) or a body which is separated from the work process itself (external control) (Hales, 1993).
The latter case refers to traditional top-down implemented control.
Organizational control has traditionally been based on the use of two means of control: output or process (action or behavior control) (see e. g. Ouchi, 1979; Merchant, 1982; Eisenhardt, 1985; Jaworski, 1988; Hales, 1993; Simons, 1994; Ramaswami, 1996; Abernathy and Brownell, 1997; Bonner et al. , 2002; Marginson, 2002).
The basic difference between these control types is that process control focuses on work procedures and processes during the controlled activity, whereas output control focuses on the end results of a certain activity after the event.
Merchant (1982) uses the term “action control” to mean different ways of controlling the actions that individuals in the organization are performing. According to Merchant, there are three basic types of action control: 1) behavioral constraints e. g. segregation of duties prohibiting improper activities; 2) action accountability including definitions of limits of appropriate behavior, monitoring activities, and rewarding or punishing deviations from the cceptable limits, and; 3) pre-action reviews in the form of direct supervision, formal planning reviews or expenditure approvals. In the case of complete process control, management holds employees responsible for following the established process guidelines and work instructions, and not responsible for the potential outcome of the specific activity (Jaworski, 1988).
Ouchi (1979) stated that behavioral control is appropriate in situations of high task programmability and low outcome measurability, and the outcome control in the opposite situation.
When task programmability is perfect and outcome measurability is high, the organization has the option to use either behavioral or outcome control. The organization then chooses the control mode which is the most cost efficient. Behavioral control is typically preferred over output control if the means-ends relationships are known, because of the real-time operating nature of behavioral controls which gives accurate control information during the activity (Ouchi and Maguire, 1975).
Eisenhardt (1985) states that an increase in task programmability, the possibility of behavior measurement, the cost of outcome measurement, and outcome uncertainty, lead to favor behavioral control. One critical precondition for the use of behavioral control is that the employees under control must really know what kind of behavior is expected from them (Merchant, 1982).
Process control and especially process formalization in the front-end means specifying procedures to be followed and monitoring that work activities are proceeding in accordance with the defined procedures.
Management aims at ensuring that those activities that are considered necessary and critical for the success are thoroughly accomplished. In addition, management arranges review and decision points during the processes and establishes reporting procedures in order to be kept informed about the progress of front-end initiatives. The effect of process formalization on front-end performance in the presence of high task uncertainty is hard to predict due to many conflicting findings.
The organization control literature states that critical pre-condition for process control and process formalization is that the appropriate work process leading to the desired end results needs to be known (Ouchi, 1977 (Ouchi uses the term knowledge of transformation process); Eisenhardt, 1985 (Eisenhardt uses the term task programmability)).
Thus routine, structured and independent tasks are suitable for instituting formal process control. This is also the essence of classical contingency theory and the distinction between mechanistic and organic structures (Burns and Stalker, 1966).
The increase in task uncertainty should cause reduction in formalization and an increase in decentralization (Donaldson, 2001).
Lawrence and Lorsch (1967) were among the first to link this causality into performance. They found that the situation (e. g. a research lab) where high task uncertainty was associated with low formality and low centralization led to higher performance. The front-end phase, being an experimental and even chaotic endeavor, is not so fertile ground for process control and its formalization based on the above arguments.
However, the widely referred new product development text books for practitioners give some indication that new product success may be, at least partly, dependent on existence and efficiency of the defined, formal front-end process model (see e. g. Cooper, 1998; Wheelwright and Clark, 1992).
The literature provides several process models to decrease fuzziness and increase systematic approach and manageability of the front-end phase (see e. g. Cagan and Vogel, 2002; Nobelius and Trygg, 2002; Koen et al. 2001; Cooper, 1998; Khurana and Rosenthal, 1998; McGrath, 1996).
The Stage-Gate model is one of the most linear and formal process models presented to manage the front-end phase. Copper (1998) has introduced a model for the front-end phase including three phases (idea generation, preliminary investigation and business case preparation) and three decision gates. An opposite process model, i. e. the non-linear and iterative process model, is a new concept development model developed by Koen et al. (2001).
The model consists of three key building blocks: a) five front-end elements, b) the engine which is fuelled by leadership and innovation culture, and which nourishes and gives power to the front-end elements, and c) external influencing factors such as organizational capabilities, business strategy, and the enabling science. The front-end elements or activities included in the model are opportunity identification, opportunity analysis, idea genesis, idea selection, and concept and technology development.
In addition to linearity, the level of formality can be used to categorize different process models. Khurana and Rosenthal (1998) state that the formal approach includes implementing an explicit and widely known process with clear decision making responsibilities and specific performance measures. A more informal method is the culture-driven approach, which aims to assure that important front-end issues, e. g. , strategic vision, technical feasibility, customer focus, schedule, and coordination are always on the minds of all key participants.
Decision making structure in the form of decision gates or review points is typically defined together with the front-end process model. Tatikonda and Rosenthal (2000) point out that periodic reviews are important especially for senior management providing a time and place for intervene and giving guidance regarding project decisions. The existence of specific review points decrease also the probability that senior management involves hands-on, i. e. too deeply, in operative decision making.
The right timing and existence of adequate information to make decisions in these review points are of importance (McGrath 1996).
The process model is also associated with definition of reporting hierarchy inside the organization. Simons (1995) discusses managers using monthly updates and exceptions reports as diagnostic control mechanisms. These reports are used to confirm that no unpleasant surprises emerge from the organization. Internal reporting is one of the basic functions that information systems are designed to do in organizations.
Recent research has criticized the current management approaches because they adopt one single, optimal model for the front-end without considering any contextual factors, e. g. differences between incremental and radical innovations. For example, the study of Nobelius and Trygg (2002) showed that front-end processes differ regarding performed activities and task sequences, as well as relative time duration and perceived importance of specific tasks. The findings indicate that the definition of the frontend process model, which is applicable for all kinds of pre-project phases, is questionable.
Buggie (2002) has presented strong criticism against stage-gate types of models stating that they are not NPD models at all, but more like general project management models which can be used only to control milestone achievement. The most crucial fault of this kind of model is that its decision gates focus on searching for ‘fatal flaws’ of new initiatives, thus especially excluding many radical ideas. However, there is also some evidence that a formal process in the front-end can lead to improved and faster decision making as well as to more successful products (Koen et al. 2001; Montoya-Weiss and O’Driscoll, 2000; Khurana and Rosenthal, 1998).
Naturally, the process formalization brings several advantages. Ability to focus, possibility for replication and learning, and improved coordination and integration are typical advantages associated with process formalization (Bonner et al. , 2002; Tatikonda and Rosenthal, 2000; Hertenstein and Platt, 2000).
Process formalization provides a sense of structure and clear sequence of activities reducing uncertainty regarding the work tasks.
Defined processes provide both motivation and sense of accomplishments as well as require employees continuously evaluate whether they are in the right track. In addition, formalization helps to achieve more efficient coordination and cross-functional communication and may enhance a feeling of collectiveness among the development group. (Tatikonda and Rosenthal, 2000) Hertenstein and Platt (2000) state that not only do formal models and documentation enable the replication of process but they also help management to monitor the process and to improve it when needed.
Process formalization enables both the management and employees to focus on the most critical development issues while implementing the predefined processes. However, the above mentioned authors do not make distinction between the front-end and development project phase in their studies. The existing studies have also identified several disadvantages of process formalization such as decreased innovativeness, increased corner cutting activities, negative attitudes among employees, excess bureaucracy, and decreased flexibility (Bonner et al. 2002; Tatikonda and Rosenthal, 2000; Hertenstein and Platt, 2000; Amabile, 1998; McGrath, 1996).
Amabile (1998) states that granting a choice over applied work processes fosters creativity by increasing employees’ sense of ownership and intrinsic motivation. Free choices regarding the process allow employees to maximally utilize their substance expertise and creative thinking skills. Ramaswami (1996) warns that excessive process formalization may actually lead to dysfunctional behavior among employees. Excessive formalism may also result inefficiency, inflexibility and heavy bureaucracy e. . when required approvals are acquired for operative level decisions (McGrath, 1996).
New product development process formalization has negatively been related to project performance (Bonner et al. , 2002; Abernethy and Brownell, 1997) Bonner et al. (2002) found that formal process control was negatively related to project performance. Process formalization led to delays, cost overruns, lower product performance, and lower team performance in projects ranging from incremental improvements to radical new products.
Again, the above mentioned authors investigated a development project as a whole without considering special characteristics of its phases. However, since the existing research gives somewhat conflicting results of the applicability of process formalization in terms of performance in a new product development project phase, it is believed that the front-end phase including even more uncertainty is not suitable for process formalization. The negative consequences of process formalization are more likely to overcome the potential advantages of formalization.
Thus the following hypotheses are created: • H1: Front-end process formalization is negatively associated with a superiority of product concept. • H2: The more market uncertainty, the more negative the association between process formalization and a superiority of product concept. • H3: The more technology uncertainty, the more negative the association between process formalization and a superiority of product concept. Research method The sample companies were derived from BlueBook database (TDC Hakemistot Oy Blue Book, http://yrityshaku. bluebook. i), which includes information of all the Finnish industrial companies. The sample companies were derived from the database by using two selection criteria: 1) companies have more than 50 employees, and 2) companies carry out product development activities. Different business units of 50 biggest Finnish companies (based on turnover figures in 2004) fulfilling the above criteria were also included in the research. In total, 888 companies (company in this context refers also to different business unit of 50 biggest Finnish companies) fulfilling these criteria were found from the database.
The questionnaire were sent to all these companies, i. e. , to the whole population in December 2005. The questionnaire was addressed to R&D Director, Research director, Technology director, CEO or R&D responsible person in each company. These titles were considered as key informants with a purpose to find a director/person who participates in controlling individual new product development initiatives in the front-end phase from management’s point of view. The respondents were requested to select the last completed front-end case and base their answers on that in order to avoid success bias.
The survey questionnaire was eight pages long and divided in two parts. The first part focused on the background information of the company. The second part focused on the example front-end case itself, which was a unit of analysis in this study. The questions covered different control mechanisms (independent variables), front-end performance measures (dependent variables) and also some contextual information regarding the front-end case. Before sending the questionnaire was tested both with academics and practitioners as suggested by Fowler (2002).
The mailing process included three separate contacts to the company representatives. First contact was a mail consisting of a cover letter emphasizing the importance of the survey, response instructions, the eight-page questionnaire, and a pre-paid return envelope. Three weeks after first mailing, second contact was taken by an e-mail to non-respondents as suggested by Dillman (2000).
The final third contact was taken by a phone to the randomly selected 50 non-respondents. Of these 888 companies, 137 returned the filled questionnaire, which leads to the response rate of 15. 8 %.
The response rate can be considered as acceptable in the light of the long eight-page questionnaire and the fact that the questionnaire was targeted towards the director level where the time resources are always scare. The final useable sample for statistical testing was 133. When a survey relies on the responses of a single informant, special attention should be paid that the informant is knowledgeable in survey domain (Campbell, 1955; John and Reve, 1982).
The great majority of respondents (91. 8 %) had one of these expected positions to whom the questionnaire was sent. The respondent had 5,7 years xperience (range: 0-30) in their position in average and 12,8 years experience (range: 0-40) in the organization in average.
Only 1. 56 % of data of used measurement items were missing, which indicates that the returned questionnaires were completed thoroughly. The missing values were visually inspected to find possible patterns of missing data. However, not such patterns were found. Mean substitution was used to replace missing values (Hair et al. , 1998).
The influence of mean substitution to final results was checked and found to be non-existing. The response rate in this study was 15. %, which gives a reason to study a possible response bias. One method to investigate the response bias is to compare early and late respondents of the survey. Armstrong and Overton (1977) have suggested that late respondents, who responded because of the increased stimulus, are relatively similar to non-respondents. Possible response bias was analyzed by testing a difference in turnover, number of employees and R&D intensity (% of turnover to R&D) between early (63 companies) and late (70 companies) respondents. No statistically significant differences were found between early and late respondent groups.
The results indicate that response-bias is not a problem in this study and the sample can be considered to be representative of the target population. Herman’s one-factor test was used to analyze common method variance (Podsakoff and Organ, 1986).
All the interested independent variables were entered in the factor analysis simultaneously. This resulted in 6 independent factors as expected. In addition, first general factor accounted only 23. 45 % of the covariance of independent variables. This gives some indication that common method variance is not a serious problem in this study.
Multitrait-multimehtod matrix analysis was done to assess convergent and discriminant validity of measurement constructs (Campbell and Fiske, 1959).
A good convergent validity exists if withinconstruct correlations are statistically significant. The inter-item correlations generally exceeded the threshold value . 30 (Hair et al. 1998) indicating a good convergent validity. A good discriminat validity requires that there is a small number of cross-construct correlations that exceed within-construct correlations. All the items with one exception loaded . 0 or lower to other than a primary factor in the factor analysis resulting in a good discrimnant validity. Analysis methods Two main statistical methods were used in this study. First, the exploratory factor analysis was applied to test validity and undimensionality of the created measurement constructs (Hair et al. , 1998).
Exploratory factor analysis was favored over confirmatory factor analysis, since the verified management control measurement constructs applied in the front-end context are scare. Further, Cronbach’s inter-item coefficient alpha was measured for ach factor to evaluate the reliability of the measurement construct. Second, a multiple regression analysis was used to test the created hypothesis (Hair et al. , 1998).
The appropriateness of empirical data (such as a normality of residuals) was tested to investigate that multiple linear regression analysis can be applied (Hair et al. , 1998; Cohen and Cohen, 2003).
Predictor value centering was used to overcome problems of multicolinearity while investigating the moderating effects of task uncertainty (Cohen and Cohen, 2003).
Measurement constructs This study applies existing, validated measurement constructs as much as possible.
However, there are not so many empirical quantitative studies that would have investigated management control in the front-end phase of the innovation process. Thus, the author needed to create new measurement constructs. Two principles for creating new measurement constructs were applied. First, the new measurement construct was based on modification of existing and validated measurement constructs from the other contexts, if the close proxy was found. Second, when the new measurement construct was created from the scratch, it was based on extensive literature analysis and tested with both academics and practitioners.
The measurement of the dependent variable and moderating variable “uncertainty” was based on the Likert scale from one to five (1 = strongly disagree, 5 = strongly agree).
Independent variables (other than “intrinsic task motivation” and “influence of strategic vision” constructs, where the Likert scale was used) were measured in the scale one to five asking respondents to judge the intensity to which extent different control mechanisms were used in a particular case (1 = not at all, 5 = used in a great extent).
Process formalization measurement construct was created based on the extensive literature review of different process control mechanisms used in new product development and front-end context. The first measure concerned the use of a reporting system informing the management about the progress of the front-end case. This kind of status reporting has been regarded as an important diagnostic control tool in the literature (Simons, 1995; Cleland and King, 1975).
The second item measured the extent to which the front-end case was executed in accordance with the defined process model.
The measure was derived from discussion emphasizing the importance of specifying the overall structure and procedures in new product development context (Bonner et al. , 2002; Ulrich and Eppinger, 2001; Hertenstein and Platt, 2000; Tatikonda and Rosenthal, 2000).
The third measure focused on the existence of specific evaluation gates during the front-end. These review points enable the management to consider the progress of the case and to make decisions about appropriate direction as well as continuing the case (Davila, 2000; Tatikonda and Rosenthal, 2000).
Finally, the fourth item measured used direct supervision over the procedures used by the front-end group. This measure was adopted and modified from Ramaswami (1996) but modified to the context of this study. The Cronbach’s inter-item coefficient alpha for this construct is . 79 indicating a good reliability. From the vast amount of different control mechanisms, the following six other control mechanisms were adapted to this study: input control, output based rewarding, influence of strategic vision, intrinsic task motivation of the development group, informal communication, and involvement in goal setting.
Since the primary focus in this study is on process formalization, these six constructs are introduced as covariates in the regression analysis. Much of the discussion of measuring product concept superiority (a dependent variable) is adopted from Cooper (1994), who studied over 1000 new products and their development process with the aim of finding drivers of successful product innovations. A product including unique attributes, superior price/performance characteristics, and high customer satisfaction has greater chances for success in the markets.
Measures for this product concept superiority construct were collected and modified based on variables used by Cooper (1994), Griffin and Page (1996) and Song and Montoya-Weiss (2001) who used these measures product development project context, and especially by Herstatt et al. (2004) and Kleinschmidt et al. (2005) who applied these measures in studying front-end performance. Product superiority construct is consisted of five measures, two of them dealing product’s comparative position to the competitors’ products, one concerning the potential competitive advantage created by the product, and two measures related to the impact on customers.
The variables were measured with a five point Likert scale. Overall, this measure is found to have a reasonable reliability (alpha = . 69).
Uncertainty was used both as a control variable and as a moderating variable in multiple linear regression analysis. Classical contingency theory considers uncertainty of being one of the main factors influencing optimal way of organizing work activities. There are two main factors defining uncertainty in the product innovation context: applied technology and aimed target market (Tidd et al. , 2001; Danneels and Kleinschmidt, 2001).
The more new technology the product includes or the more unfamiliar the target market is, the more uncertainty the development task includes. Thus the uncertainty measurement covered both market and technology dimensions. Garcia and Calantone (2002) emphasized that product innovativeness (the uncertainty that product includes) must be evaluated from two different perspectives: macro-level industry perspective and micro-level company perspective. First two measures both in market uncertainty and technology uncertainty constructs reflects this notion.
These measures were modified to fit the context of this study from Danneels and Kleinschmidt (2001) who used these measures in the market familiarity and technological familiarity measurement constructs. The third and fourth measures in both constructs relate to the discussion of whether the new products can rely on firm’s existing technological and marketing competencies or not. This is an important measure of uncertainty in this study since products with a closer fit to existing competences of the firm tend to be more successful in average.
