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The purpose of this research is to conceptualize, define and measure resource orchestration capabilities of R&D teams pursuing advanced scientific research and technological innovation at public-funded R&D organizations in India.

A series of five mutually exclusive studies were designed over two years to develop and validate the ROCI scale within public research and development (R&D) organizations pursuing advanced scientific research and technological development in India. The first three studies address the refinement, reduction and rationalization of items for measuring the ROCI construct. The next study explores the factor structure underlying the ROCI construct whereas the subsequent one confirms the three-factor structure within empirical settings.

The resource orchestration capability towards innovation (ROCI) construct reflected through three sub-dimensions namely – adaptive structuring capability (ASC), synergistic leveraging capability (SLC) and decentralized decision-making capability (DDC), each loaded with their respective items can be used for capability measurement in public-funded R&D organizations.

R&D managers can use this ROCI scale to measure, monitor and improve the innovation-oriented resource orchestration capabilities of their R&D teams and help them improve their innovation performance.

This research contributes to the extant literature on resource orchestration for innovation management in three unique and original ways – theoretically-grounded conceptualization, empirical measurement and rigorous validation through multiple studies conducted in public-funded R&D organizations in India.

This paper aims to propose a conceptual framework for measuring, comparing or predicting the science commercialization capability of academic research-driven organizations. Drawing on extant literature on innovation commercialization, two influential predictors were explored and the nature of their influence was proposed.

Based on the theoretical analysis of relevant literature on science commercialization, this conceptual paper proposes a predictive framework along with two critical antecedents – patronage and parochialism. The analysis further reveals their sub-dimensions and provides insights into how patronage and parochialism can be measured within empirical settings. The study concludes with theoretical propositions about how these two constructs influence science commercialization.

The study reveals that patronage can positively influence science commercialization and be reflected through mentorship, specialized knowledge-sharing and providing decision-making support to academic innovators pursuing science commercialization. Alternatively, parochialism can positively influence science commercialization and be reflected through academic innovators’ perception, purpose and persistence of efforts toward science commercialization initiatives.

The study contributes to extant literature on science commercialization in three major ways – a conceptual predictive model, theoretically grounded antecedents and their corresponding influence on science commercialization.

This study aims to perceive research and development (R&D) knowledge management from a capability-based view, develops a theoretically grounded construct and empirically validates it within R&D organizational settings.

The paper presents a five-step multi-method research design consisting of a literature review, expert interviews and surveys to develop and validate the R&D knowledge management capability scale within R&D organizations.

R&D knowledge management capability construct emerges as a three-dimensional construct with dimensions – knowledge creation, communication and commercialization which can be measured through a parsimonious set of items, designed at team levels within R&D organizations.

R&D managers can use this R&D knowledge management capability scale to measure, compare and develop the knowledge management capabilities of their R&D teams.

The three dimensions of R&D knowledge management capabilities along with their measurement items are the unique contributions of this study to the knowledge-based view of the firm.

This conceptual paper aims to explain the unidirectional cross-level impact of five “organizational-level” factors on “team-level” innovation capability through two “team-level” mediating factors. This multivariate model consists of five organizational-level factors (higher-level) factors – leadership, culture, structure, networks and knowledge – and team-level (lower-level) factors – “innovation capability”, “team-level focus” and “team-level intensity” towards innovation. Understanding the top-down influence of higher-level factors on lower-level ones gives this study a cross-level and unidirectional nature.

A keyword-based approach was used to select “relevant” articles from major journals to collect evidences and develop a conceptual model. All factors in the conceptual model were chosen from the organizational- and the team-level literature. Theoretical background for each of the chosen “factors” has been presented under relevant headings.

First is the conceptualization of team-level mediators – intensity and focus – towards innovation. Second is the conceptualization of innovation capability as a team-level factor, characterized by two sub-dimensions: customer orientation and manifestation.

This conceptual paper does not contain any empirical data analysis. The authors have not considered individual-level factors like individual excellence, personalities, etc., which may impact team-level innovation. They are specifically looking at the top-down “unidirectional” cross-level impact of “higher-level” (organizational-level) factors on “lower-level” (team-level) factor, not the other way around.

Innovation-driven organizations can use this model to build long-term “innovation capabilities” by developing the right kind of “intensity” and “focus” of their R&D teams towards innovation. R&D teams can be encouraged to work closely with their “target” customers and manifest their innovation capabilities (to them) to ensure market success.

Top management can design organizational-level policies to improve their leadership, culture, structure, networks and knowledge to encourage better innovation. Future researchers who wish to study the “cross-level” influence of organizational-level factors on team-level innovation capability may find this paper useful.

This study’s original contributions include: first, the conceptualization of a multivariate “cross-level” model to understand team-level innovation capability. Second is proposing the mediating role of “team-level” factors like focus and intensity while building innovation capability. Third is conceptualizing innovation capability as a team-level construct, with sub-dimensions: customer orientation and manifestation.