| Title |
Absorptive capacity, technological innovation, and product life cycle: a system dynamics model
|
|---|---|
| Published in |
SpringerPlus, September 2016
|
| DOI | 10.1186/s40064-016-3328-5 |
| Pubmed ID | |
| Authors |
Bo Zou, Feng Guo, Jinyu Guo |
| Abstract |
While past research has recognized the importance of the dynamic nature of absorptive capacity, there is limited knowledge on how to generate a fair and comprehensive analytical framework. Based on interviews with 24 Chinese firms, this study develops a system-dynamics model that incorporates an important feedback loop among absorptive capacity, technological innovation, and product life cycle (PLC). The simulation results reveal that (1) PLC affects the dynamic process of absorptive capacity; (2) the absorptive capacity of a firm peaks in the growth stage of PLC, and (3) the market demand at different PLC stages is the main driving force in firms' technological innovations. This study also explores a sensitivity simulation using the variables of (1) time spent in founding an external knowledge network, (2) research and development period, and (3) knowledge diversity. The sensitivity simulation results show that the changes of these three variables have a greater impact on absorptive capacity and technological innovation during growth and maturity stages than in the introduction and declining stages of PLC. We provide suggestions on how firms can adjust management policies to improve their absorptive capacity and technological innovation performance during different PLC stages. |
Mendeley readers
The data shown below were compiled from readership statistics for 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 1 | <1% |
| Unknown | 163 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 30 | 18% |
| Student > Master | 22 | 13% |
| Lecturer | 21 | 13% |
| Student > Doctoral Student | 17 | 10% |
| Researcher | 9 | 5% |
| Other | 20 | 12% |
| Unknown | 45 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 58 | 35% |
| Engineering | 16 | 10% |
| Social Sciences | 11 | 7% |
| Economics, Econometrics and Finance | 9 | 5% |
| Computer Science | 6 | 4% |
| Other | 15 | 9% |
| Unknown | 49 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 October 2016.
All research outputs
#18,475,157
of 22,893,031 outputs
Outputs from SpringerPlus
#1,261
of 1,850 outputs
Outputs of similar age
#245,224
of 322,701 outputs
Outputs of similar age from SpringerPlus
#114
of 160 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,850 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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We're also able to compare this research output to 160 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.