Moderating Effect of Environmental Turbulence on New Product Development Cycle Time in the Telecom Industry

INTRODUCTION

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The construct of teamwork quality along with its measures was investigated in empirical research conducted by Easley et al. (2003), Hoegl et al. (2004) and Hsu et al. (2012). With regards to high teamwork quality, team members often practice open communication regarding task materials (Hauptman and Hirji, 1996), activities, coordination (Adler, 1995; Faraj and Sproull, 2000) and contribute their knowledge (Seers, 1989). They also practice mutual support among them in discussions and individual tasks (Cooke and Szumal, 1994), lay down and sustain standards of great effort (Weingart, 1992) and encourage team cohesion (Gully et al., 1995). Therefore, different levels teamwork quality can have varying impacts on project performance (Hoegl and Gemuenden, 2001).

In this study, Hoegl and Gemuendens (2001) teamwork quality (TWQ) model was chosen as a basis for this study because it is one of the prominent models in teamwork and is regularly applied to explain the phenomenon. Six dimensions are shown in the following:

•	Communication
•	Coordination
•	Balance of Member Contributions
•	Mutual Support
•	Effort
•	Cohesion

There are a number of reasons to expect that group cohesion may also be an important antecedent of NPD cycle time. First, when group cohesion is high, there is a motivation to improve the performance of the team (Mullen and Copper, 1994) which positively a ffects the NPD cycle time. Second, a cohesive team also provides more opportunities for team members to interact with each other (Ehrhart and Naumann, 2004). The frequent interaction may allow them to observe each other’s team and improve the NPD processes. Based on the multidimensional model Carron et al. (1985) studied the relationship between group cohesion and performance. A direct relationship between specific dimensions of group cohesiveness and performance was found. Cohesion was indicated to be an antecedent of performance. In their meta analytic study, Beal et al. (2003) showed that cohesion wass related to team performance and NPD cycle time (effectiveness and efficiency). However, Mullen and Copper (1994), in their meta analytic study, revealed disagreements on the relationship between group cohesion and performance. They concluded that the relationship between cohesion and performance is significant but small.

Depending on the industry they compete in, firms need to continuously engage in new product development in order to remain competitive. New products or improved products are not sufficient for a competitive environment that is modern knowledge-based. New Product Development (NPD) must be complemented with the rapid introduction of new or significantly improved products in order to prevent obsolescence. The following sections address the definition of NPD and then introduce the construct of NPD cycle time including its measurement and reduction techniques.

The first new school of thought focuses on how to enhance the structured NPD process. Cooper and Kleinschmidt (1995) also agreed that a structured process should be abided by; however, they added that stages can be combined or even skipped. They emphasized that a NPD process should still encompass the structured approach; however, they did stress that the activities within each stage need not be fully executed prior to proceeding through a "gate". This first school of thought is referred to as the "flexible school of thought". Improvisation is the second school of thought. It is the extreme case of flexibility. In the "Improvisation school of thought", there are no structured frameworks that the NPD process follows. Due to frazzled structures, it causes NPD teams to improvise throughout the progression of each project. Moorman and Miner (1998), among others, believed that improvisation can have an affirmative effect on new product outcomes.

A new product development cycle time is critical because life cycles are shrinking and obsolescence is occurring more quickly than in the past while competition has intensified (Griffin, 1997). In today’s world economy, regardless of the industry, organizations are searching for new ways to compete more effectively and efficiently. In their efforts to do so, they are confronted with numerous competitive challenges. It is no longer sufficient to meet the traditional requirements of product cost, performance, quality and dependable delivery.

In order to be able to measure the actual steps of the development process, Griffin (1997) used project timing, which chronicle(s) the dates when various phases of development (begin). As mentioned already, Griffin (1997) measured NPD cycle time in terms of time-to-market, concept-to-customer and development time. Each one of the time variables begin with different stages of the NPD process, but the series of activities of interest end just before the product launch stage begins, which Kumar et al. (1994) called the production stage of the NPD process, for the purpose of treating time as an internal variable. The stages described here become easier to measure as the development process moves forward. The earliest stages are the most difficult to uncover. Stages 0 and 1 are usually estimates kept informally with marketing or planning groups. The transition from stage 0 to stage 1 is especially fuzzy (general uncertainties of start dates). Conversely, Stages 2, 3 and 4, are usually recorded in logbooks kept by design/development or manufacturing (Griffin, 1993, 1997). Now that the stages have been identified, the time variables are defined in Table 1.

The initial duration of a five product development phases are needed for every project. The first stage (Stage 0) is referred to as the concept generation stage. This is followed by Stage 1 which is the project evaluation where approval of product strategy and target market is sealed and the project is given a green light for specifications development. The actual times for the initiation of Stages of 0 and 1 are sometimes unsure as the idea may just be juggled around in marketing or development for some time without employment. The initial step of some projects may be listed down with clarity in memorandums bringing forward the idea or in case of a project conducted to satisfy competitor’s entry, the data the other product was publicized in the market. This is followed by Stage 2 where the first R and D money was spent on physical product development. Stage 3 is the manufacturing development where the documentation takes place concerning the development of the processes. This is followed by Stage 4 that concerns commercialization in this phase, the manufacturing production trials are initiated. The initial dates are procured easily from the time sheets of engineering and manufacturing as well as business memorandums.

Research concerning moderators of the market orientation-new product development has primarily concentrated on the moderating role of environmental conditions (Schweitzer et al., 2011). Three widely acknowledged factors that comprise environmental conditions are market turbulence, technological turbulence and competitive intensity (Aziz and Yassin, 2010; Schweitzer et al., 2011).

Table 1:	Phase timing variables
Source: Griffin (1993)

Previous studies showed that environmental conditions influence the internal market orientation and performance link (Kirca et al., 2005). These three environmental factors have important roles in determining the strategic orientation of afirm within the high tech division (Su et al., 2010). This study concentrates on effect of technological turbulence, competition turbulence, as well as market turbulence on:

•	Technological turbulence
•	Competition turbulence
•	Market turbulence

In the past several years, telecommunication workers have been tackling changes in the environment (Garrett and McDaniel, 2001). Complex work environments call for worker flexibility in adapting various client needs and adapting to the environment particularly in telecommunication organizations. According to a previous study, Environmental Turbulence (ET) refers to the individuals’ interaction with their environment in reaction to instability and dynamic changes in their internal or external environment or both that are influenced by the individuals/groups or organization’s attributes and that has the potential to eventually influence patient and nursing outcomes.

A case that established the impact of environmental turbulence on individual teamwork took place in the 1980s when ET was integrated into healthcare environment as part of the restructuring of patient care delivery system that came with a decrease in hospital funding (Tillman et al., 1997). Internal and external environmental factors in healthcare may be characterized by instantaneous and unpredictable changes that alter the patients, units and the resources’ characteristics (e.g., equipment, money and number of nurses). The internal environment refers to the forces operating external to the organization to which it is susceptible to (i.e., regulatory groups, personal issues, customers, suppliers and market and resource competition). Some environmental issues that complicate nurses’ work include missing information, lack of resources, missing medications and equipment, defective equipment and lack of communication and team work ingrained in the culture.

Furthermore, the internal environment was revealed to influence job satisfaction, which in turn was related to patient outcomes. Specifically, emotional exhaustion, which is a component of burnout (Garrett and McDaniel, 2001) has been linked to unsafe work environments. This condition is often an outcome of long-term involvement in emotionally draining situations and the ineffective handling of long-term stress. Nurses that have been in profession for a long time were found to be more susceptible to burnout and were at a greater risk of quitting (Ebright et al., 2004).

The external environment may develop turbulence in the form of the creation of countless rules, unrealistic mandates, or decreasing reimbursement or the combination of all. This turbulence may adversely affect the internal environment, which in turn may develop changes in the external environment. Additionally, the internal environment may also change and thus create perceived environmental uncertainty and add to the turbulence (Aiken et al., 2002).

It has been hypothesized that teamwork quality affects the new product development cycle time which itself has been linked to better organizational performance. The first theory upon which the framework is grounded is resource-based view founded by Wernerfelt (1984) and popularized by Barney (1991). The second theory is contingency theory, which explains the moderator variable in the framework. Based on this theory, it is proposed that performance is a condition to the relationship of an organization and its external environment (Duncan, 1972; Gresov, 1989; Weiss and Heide, 1993). The third one is internal market orientation theory founded by Lings and Greenley (2005), which explains the mediating influence of internal market orientation.

So, the present study aims to obtain the moderating effects of enviromental turbulence on new product development time in the telecom industry.