Knowledge exchanges for open innovation: the role of inter-organisational citizenship behaviours and organisational support

Naqshbandi, M. Muzamil; Tabche, Ibrahim; Said, Thuraya Farhana

doi:10.1080/14778238.2023.2185549

Cited by 9 publications

(1 citation statement)

References 89 publications

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“…R. Osorno and N. Medrano (2020) pointed out the challenges that open innovation platform design encounters are as follows: intellectual property management; costs and benefits to keep the stakeholders' interest; information structure; governance; quality assurance; and finally associated risks [15]. M, I, and T (2020) pointed out that both internal knowledge at the backers' level and at the OIPs' level have a positive impact on the outcomes of the initiatives [16]. In addition, there was no significant correlation between the shareholding ratio of senior executives, the company's total assets, and the company's growth.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Green Industry Innovation Efficiency Based on Three-Stage DEA Model: A Case Study of Chinese Information Technology Industry

Zhang

Wang

2023

Sustainability

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The information technology industry as a new engine driving China’s economy has made more and more contributions to Chinese sustainable development. At present, it has overtaken real estate as the new cradle of Chinese billionaires. The information technology industry not only has its own characteristics of high economic, social benefits, and small impact on the ecological environment, but also can enable the green development of the economy and society. So it is the core industry to support the realization of the “double carbon” goal. This paper evaluated the innovation efficiency of 80 enterprises in the software and information technology service from 2017 to 2018 by constructing a three-stage DEA model. It puts forward countermeasures, which points out the direction for the development of environmental protection and green low-carbon industry. Empirical results show that environmental variables have different effects on innovation efficiency. After excluding the influence of environmental and random factors, the increase in innovation efficiency, while generally significant, is not high. Low innovation efficiency is caused by both pure technical efficiency and scale efficiency, especially pure technical efficiency. Enterprises’ adjusted scale returns are mostly increasing; the innovation investment scale is not optimal. Regional differences of enterprise innovation exist; the East and Midwest have obvious polarization both in quantity and quality. These results quantify the effect of the factors affecting enterprise innovation efficiency and put forward policies and suggestions for promoting the development of China’s information technology industry accordingly.

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Section: Introductionmentioning

confidence: 99%