Innovation Efficiency Evaluation Based on a Two-Stage DEA Model With Shared-Input: A Case of Patent-Intensive Industry in China

Wang, Xiaoli; Liu, Yun; Chen, Lingdi

doi:10.1109/tem.2021.3068989

Cited by 25 publications

(13 citation statements)

References 71 publications

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“…where s ij is the score of sub-CIMP j related to CIMP i of a bank, s ij ∈ [1,5]; K is the number of experts participating in the evaluation; and s k ij is the score that the kth expert assesses sub-CIMP j related to CIMP i of a bank,…”

Section: ) Data Formulationmentioning

confidence: 99%

“…where c i is the development degree of CIMP i at a bank, c i ∈ [1,5]; s ij is the score of sub-CIMP j related to CIMP i at a bank, s ij ∈ [1,5]; J is the number of sub-CIMPs related to CIMP i; and w ij is the weight of sub-CIMP j related to CIMP i,…”

Section: Computing the Overall Evaluation Of Ic And Rankingmentioning

confidence: 99%

“…where ICI is the innovation capability index of a bank, ICI ∈ [1,5]; I is the number of CIMPs; c i is the development degree of CIMP i at a bank, c i ∈ [1,5]; and W i is the importance weight of CIMP i; W i ∈ [0; 1]. A ranking of the banks in a sample can then be created based on their IC.…”

Section: Computing the Overall Evaluation Of Ic And Rankingmentioning

confidence: 99%

“…For instance, Dozier and Montgomery [4] conducted an in-depth investigation of the evaluation process utilizing the grounded theory approach for blockchain technology innovation in banking. Wang et al [5] proposed an evaluation method using a twostage data envelopment analysis model for innovation efficiency of the patent-intensive industry. Koliouska et al [6] developed a multicriteria evaluation model for tourism enterprises in Greece through their websites that not only allows identification of the most successful practices, but also provides suggestions for service improvement or innovation taking advantage of the opportunities arising in the new era of technological innovation in the tourism sector.…”

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confidence: 99%

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Evaluating Innovation Capability in Banking Under Uncertainty

Ngo

Tansuchat

et al. 2024

IEEE Trans. Eng. Manage.

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The evaluation of innovation capability (IC) plays a key role in an age of keen competition driven by modern technologies, since it enables organizations to review their innovation management process and to adjust their corresponding innovation policies. Moreover, the IC evaluation is, in fact, a multicriteria process with high uncertainty, since the market environments and competitors' performance are both in a dynamic environment. Therefore, the evaluation of IC under uncertainty is vital to organizations. This study proposes a new integrated method for the evaluation of IC in banking organizations by combining the analytic hierarchy process (AHP) and the evidential reasoning (ER) approach in terms of the Dempster-Shafer theory of evidence. Three Vietnamese banks were used as a case study to demonstrate the applicability and validity of the proposed method. Experts in banking-related fields were invited to determine the relative importance weights of critical innovation management practices (CIMPs) and their sub-CIMPs using the AHP and to score the maturity levels of sub-CIMPs at the evaluated banks. The ER approach was then applied to generate aggregated assessments representing the ICs of banks that were finally used for their ranking in terms of IC.

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Section: ) Data Formulationmentioning

confidence: 99%

Section: Computing the Overall Evaluation Of Ic And Rankingmentioning

confidence: 99%

Section: Computing the Overall Evaluation Of Ic And Rankingmentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluating Innovation Capability in Banking Under Uncertainty

Ngo

Tansuchat

et al. 2024

IEEE Trans. Eng. Manage.

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“…The number of valid invention patents is more subject to human interference and takes longer to be granted. Wang et al [39] pointed out that even if a company's patent application is not approved, it still reflects that the company is actively carrying out scientific and technological research and development work, which will positively impact its later work. The number of patent applications better reflects the contribution of the research sector to the development sector, as it takes into account the portion of patents that are not granted but still have a significant economic and social effect.…”

Section: The Link Variablesmentioning

confidence: 99%

Measurement of Innovation Efficiency in China’s Electronics and Communication Equipment Manufacturing Industry-Based on Dynamic Network SBM Model

2022

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In recent years, China’s electronics and communication equipment manufacturing (ECEM) industry has overgrown, and the government should assess the innovation performance of the industry for its sustainable development. However, most previous studies on the innovation efficiency of the ECEM industry have ignored the link and carry-over variables. This paper uses the number of patent applications as a link variable to consider the stage of innovation activities. It divides the innovation activities of the electronics industry into two stages: technology development and results in transformation. To consider the dynamics of innovation activities, this paper uses capital stock as a period carry-over variable and evaluates the change of innovation efficiency over time. In this paper, the DNSBM model is used to measure the innovation efficiency of the ECEM industry in 26 Chinese provinces from 2013–2019. This model includes both stage link variables and period carry-over variables, thus allowing for overall efficiency and stage efficiency and period efficiency. The results show that the overall innovation efficiency values in the Chinese ECEM industry are low, there are considerable differences between the two-stage efficiency values in the east, central and western regions, and the overall efficiency values show a slow upward trend.

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Boundary spanning strategy and tacit knowledge recombination: Analysis of joint‐patent networks of patent‐intensive firms

Jiang

Zhang

2023

Manage Decis Econ

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This paper collects 103 sample firms' 2015 to 2019 data through data envelopment analysis to measure their technical innovation performance and social network analysis to build joint‐patent networks and explore knowledge‐creating alliance relationships. The article highlights how tacit knowledge recombination works as a mechanism of boundary spanning. It emphasizes the significance of strategic balancing networks' position to improve technical innovation performance and competitiveness of patent‐intensive (PI) firms. This research contributes to shedding additional light on the nature of the boundary‐spanning mechanism and PI firms' knowledge exchanges. Specifically, it examines how balancing boundaries spanning through joint‐patent networks can influence the processes of tacit knowledge transmission and recombination between knowledge‐based actors.

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Innovation Efficiency Evaluation Based on a Two-Stage DEA Model With Shared-Input: A Case of Patent-Intensive Industry in China

Cited by 25 publications

References 71 publications

Evaluating Innovation Capability in Banking Under Uncertainty

Evaluating Innovation Capability in Banking Under Uncertainty

Measurement of Innovation Efficiency in China’s Electronics and Communication Equipment Manufacturing Industry-Based on Dynamic Network SBM Model

Boundary spanning strategy and tacit knowledge recombination: Analysis of joint‐patent networks of patent‐intensive firms

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