مقاله انگلیسی رایگان در مورد ظرفیت های تیم توسعه دهنده محصول در نوآوری رادیکالی پروژه ها – امرالد 2017

 

مشخصات مقاله
انتشار مقاله سال 2017
تعداد صفحات مقاله انگلیسی 19 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه امرالد
نوع مقاله ISI
عنوان انگلیسی مقاله Dynamic capabilities of new product development teams in performing radical innovation projects
ترجمه عنوان مقاله ظرفیت های پویای تیم های توسعه دهنده محصول جدید در نوآوری رادیکالی پروژه ها
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مدیریت، مهندسی صنایع
گرایش های مرتبط مدیریت صنعتی، تولید صنعتی، استراتژی های توسعه صنعتی، مدیریت نوآوری و فناوری
مجله مجله بین المللی علوم نوآوری – International Journal of Innovation Science
دانشگاه Sripatum University Chonburi Campus – Thailand
کلمات کلیدی قابلیت های پویا، کارایی پروژه، اثربخشی پروژه، تیم توسعه محصول جدید
کلمات کلیدی انگلیسی Dynamic capabilities, Project efficiency, Project effectiveness, New product development team
کد محصول E7595
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بخشی از متن مقاله:
1. Introduction

Sustaining business competitiveness and strategic competence in turbulent business environments place great demand on the capabilities of new product development (NPD) teams. These capabilities, namely dynamic capabilities, refer to the ability of sensing, learning, integrating and coordinating the internal and external competencies of an organization to cope with rapidly changing environments (Pavlou and Sawy, 2011; Teece et al., 1997). Teams with dynamic capabilities can effectively observe, understand and interpret information on existing customers and competitors. Consequently, team members adjust current strategies and develop new ones which will support implementation of radical innovation projects. Dynamic capabilities are therefore essential elements for enhancing competitive advantage amid highly uncertain situations (Teece, 2007). Existing empirical studies have emphasized the importance of dynamic capabilities by focusing on the organization level. For example, Arthurs and Busenitz (2006) found that the dynamic capabilities of venture capital can improve financial performance. Similarly, Marcus and Anderson (2006) revealed that the dynamic capability of food retailers improves their businesses and social competence. More recently, Park and Kim (2013) found that the dynamic capabilities of high-tech companies lead to better NPD project performance. However, there are very few studies on dynamic capabilities at the team level. As a team, all members who are involved in an existing project play a vital role in achieving innovation projects (Rothaermel and Hess, 2007). Therefore, this study contributes to existing theory by examining the influence of an NPD team’s dynamic capabilities on project performance. Since NPD teams consist of members from a wide range of functional areas [e.g. research and development (R&D), marketing, quality control (QC), production], each individual has a different perspective, potential and specialization based upon their educational backgrounds and job characteristics. For instance, marketing personnel are responsible for seeking out market potentials and requirements, whereas R&D personnel are in charge of finding and implementing new technical and scientific breakthroughs (Brettel et al., 2011). As these two functions regularly encounter conflict because of different personalities, attitudes and work styles (Darawong, 2017), the success of innovation projects depends upon how well they complement each other during the NPD process. Dynamic capabilities can be a source of diverse resource in the decision-making system (Katila and Ahuja, 2002). Hence, it could be problematic for team managers to enhance dynamic capabilities of NPD teams whose characteristics are primarily cross-functional and complex-structured. The primary objective of this research is to fill the gap in previous NPD studies by examining the impact of dynamic capabilities at the team level and their effect on project performance. The structure of this study is as follows: Section 2 provides the details of two groups of key study variables of a conceptual model. Section 3 develops an argument of four hypotheses based on a literature review. Section 4 describes the methodology, including sample and research design. Section 5 explains the results of data analysis, including descriptive statistics, reliability and validity of the measurements, correlations between constructs and the results of the structural equation modeling (SEM) output. The last section discusses the results of this study and provides the implications, limitations and future research recommendations.