Innovation projects performance: Analyzing the impact of organizational characteristics

Cobo-Benita, Jose Ramon; Rodríguez-Segura, Enrique; Ortiz‐Marcos, Isabel

doi:10.1016/j.jbusres.2015.10.107

Cited by 26 publications

(16 citation statements)

References 27 publications

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“…In general, the regressions by firm size performed well with organizational innovation. The probability of a process or product innovation conditional on organizational innovation increases in a nearly linear fashion from small firms to large firms which is in concordance with Hypothesis one as well as Gallego, Rubalcaba, and Hipp (2012) and Cobo-Benita et al (2016). Moreover, the effects of organizational innovation are more pronounced for process innovation relative to product innovation.…”

Section: Discussionsupporting

confidence: 85%

“…Sapprasert & Clausen (2012) and Gallego et al (2012) show that small firms with flexible structures can benefit more from organizational innovation and lead more technical innovations. On the other hand, Cobo-Benita et al (2016) and Ganter & Hecker (2013) demonstrate that organizational innovation contributes more to technical innovation when the firm size is large. However due to the lack of available data, no empirical research study has formally established the link between organizational innovation and firm size to technical innovation.…”

Section: Organizational Innovation and Firm Sizementioning

confidence: 99%

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ORGANISATIONAL CHANGE IN THE INNOVATING FIRM: SIZE, R&D AND SECTOR EFFECTS

Cozzarin

Dimitrov

Koo

2019

Int. J. Innov. Mgt.

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This study investigates whether organisational innovation has positive impacts on small and medium enterprises, using three waves of the South Korean innovation survey. While correcting for endogeneity, we find that the probability of achieving a process or product innovation conditional on organisational innovation increases in a linear fashion from small to large firms. Moreover, the effects of organisational innovation are more pronounced for process innovation relative to product innovation. We show that R&D performers who implement an organisational innovation have a greater probability of introducing a new product or process. We also show that larger R&D performing firms benefit more from organisational innovation than smaller firms. Finally, we find evidence that high-tech industries benefit more from organisational innovation, in accordance with one of our hypotheses.

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Section: Discussionsupporting

confidence: 85%

Section: Organizational Innovation and Firm Sizementioning

confidence: 99%

ORGANISATIONAL CHANGE IN THE INNOVATING FIRM: SIZE, R&D AND SECTOR EFFECTS

Cozzarin

Dimitrov

Koo

2019

Int. J. Innov. Mgt.

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“…Within the extant literature, some scholars examine the influence of single conditions on knowledge transfer (e.g., Abrams, Cross, Lesser, & Levin, 2003;Ambos & Ambos, 2009;Minbaeva & Michailova, 2004;Simonin, 1999), whilst others investigate the influence of multiple conditions (e.g., Lawson & Potter, 2012;Miller et al, 2016). Whilst previous studies have applied fsQCA to the analysis of organizational (Cobo-Benita, Rodríguez-Segura, Ortiz-Marcos, & Ballesteros-Sánchez, 2016;Fiss, 2007;Mikalef, Boura, Lekakos, & Krogstie, 2019;Mikalef, Pateli, Batenburg, & Wetering, 2015) knowledge (Hughes, Cesinger, Cheng, Schuessler, & Kraus, 2017) and relationship (Karatzas, Johnson, & Bastl, 2016;Zaefarian, Thiesbrummel, Henneberg, & Naudé, 2017) characteristics, limited research has incorporated these factor types to the configurational analysis of knowledge transfer success. Despite a number of reviews (Al-Salti & Hackney, 2011;Cummings & Teng, 2003;Van Wijk et al, 2008), consensus surrounding key constituents of inter-organizational knowledge transfer, and their interrelations, remains absent.…”

Section: Combinations Of Conditionsmentioning

confidence: 99%

Recipes for success: Conditions for knowledge transfer across open innovation ecosystems

Bacon

Williams

Davies

2019

International Journal of Information Management

108

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Open innovation ecosystems involve the transfer of knowledge between multiple stakeholders to contribute toward product and service innovation, and to an extent, have superseded network-level approaches to co-creation. Effective management of the knowledge and information transferred between ecosystem partners is crucial for the process of open innovation. However, to date, limited research has focused on ascertaining the conditions required for knowledge transfer success, particularly where the context involves collaboration between diverse organizational actors. Correspondingly, this study extends existing knowledge by presenting an exploration of conditions for knowledge transfer success between ecosystem partners. Semi-structured interviews were conducted with thirty key stakeholders in order to acquire their perceptions of the presence of specific conditions within their ecosystem partnerships. Empirical data were analyzed using a fuzzy-set Qualitative Comparative Analysis approach, resulting in the production of success recipes from multinational, small and medium-sized enterprise, and academic institution perspectives. Results indicate that combinations of knowledge, relationship, and organizational characteristics contribute to knowledge transfer success. However, these combinations are found to be dependent on the type of ecosystem partnership involved. Theoretical and practical implications of the study are presented, along with acknowledged limitations and suggestions for further work.

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“…(Pellegrino & Savona, 2017). Cobo-Benita et al (2016) stated that a combination of large firm size, cooperation with international partners and organizational innovation, is a sufficient condition for success in innovation performance. b.…”

Section: Governmental Focusmentioning

confidence: 99%

Prioritizing Innovation Factors by Using Analytic Network Process

Taşel¹,

Bayarçelik²,

Apak³

2019

Beykoz Akademi Dergisi

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The emergence and development of the fourth industrial revolution affects production systems. This new revolution also has an impact on logistics, which has a direct relationship with production. Organizations give importance on innovation, technological change and product differentiation to compete with their rivals. Innovativeness creates better understanding of customer needs and wants, catch up their rivals and become more proactive in seeking the market opportunities for organizations. Therefore, improving logistics services using innovations can help improving strong customer relationships, derive barriers to competition, increase customer loyalty, change costs and conduct market activities more effectively. In this context, the objective of this study is to prioritize the innovation factors in logistics industry using a pairwise comprehensive method named Analytic Network Process (ANP). This model is proposed to define a ranking between selected criteria for innovation based decisions. This methodology demonstrates, which criteria has the most important role in the innovation processes.

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Innovation projects performance: Analyzing the impact of organizational characteristics

Cited by 26 publications

References 27 publications

ORGANISATIONAL CHANGE IN THE INNOVATING FIRM: SIZE, R&D AND SECTOR EFFECTS

ORGANISATIONAL CHANGE IN THE INNOVATING FIRM: SIZE, R&D AND SECTOR EFFECTS

Recipes for success: Conditions for knowledge transfer across open innovation ecosystems

Prioritizing Innovation Factors by Using Analytic Network Process

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