Factors Influencing Modern Timber Structure Building Development in China
Abstract
:1. Introduction
- (1)
- Identify the key influencing factors;
- (2)
- Quantify the complex connections among different influencing factors.
2. Literature Review
2.1. Stakeholders and Influencing Factors in MTS Building
- (1)
- The first priority was the government organization.
- (2)
- The second priority group was housing investors. Suppliers influenced changes in customer demands, improved information acquisition, and cultivated the learning ability of firms [34].
- (3)
- (4)
- Other important and identified target groups were foresters, housing designers, and builders [6].
2.2. Social Network Analysis
3. Methodology
3.1. Identification of Stakeholders and Influencing Factors
3.2. Determination of Influencing Factors’ Interrelations
- (1)
- Dependent relationship: direct connection exists between two influencing factors;
- (2)
- Independent relationship: no connection exists between two influencing factors;
- (3)
- Interdependent relationship: no direct connection exists between two influencing factors, but they have indirect connection through the network [39].
3.3. Visualization of Influencing Factor Network
3.4. Decipherment of Influencing Factor Network
3.4.1. Network Measures
- (1)
- Density is defined as the ratio of existing links in a network to the maximum number of links possible if all network participants are connected with each other [39]. The value of network density ranges from 0 to 1. The higher the density of the whole network, the more relational connections are within the network, and the closer the relationships between network nodes.
- (2)
- Cohesion is defined as the network complexity. This complexity is expressed by measuring the distance or the number of links to reach nodes within a network. The distance between nodes can be quantized by defining a reasonable the unit length, which is based on the shortest path [44]. The higher the cohesion, the more walks are required from each node to reach everyone else, and the higher degree of network complexity.
3.4.2. Node/Link Measures
- (1)
- The degree of nodes is defined as the immediate connectivity characteristic of a factor. “In-degree” and “out-degree” are, respectively, represented by the incoming relations (impacted by) and outcoming relations (impact to) [45]. The value and degree of nodes indicate the links between risk factor S#F※ and its adjacent factors all over the network. The degree of each node can be calculated by the weight sum of links. The higher the “in-degree” value, the heavier impact of the factor suffered from the others. Correspondingly, the higher the “out-degree” value, the greater impact of the factor to the others.
- (2)
- Betweenness centrality indicates the frequency of occurrence in which an assigned node/link is situated between the two other nodes/links. The node/link with a strong value of betweenness centrality has a high level of domination of the impact passing through it. Such a node/link acts as a mediator between different parts of the network, and feebleness at these key points may lead to global decomposition [40].
- (3)
- Status centrality shows the overall influence of a stakeholder issue on the whole network [27]. This measure calculates the number of direct successors and predecessors of this node, and all other nodes in the network link to the node via these direct near neighbors. Status centrality is further classified into in-status centrality and out-status centrality; they, respectively, represent the degree to which a factor is affected by others, and a factor can influence the others [39]. Out-state centrality is used as the result measure, because it is considered to have a larger influence level. The higher the out-status centrality value, the greater the influence factor.
- (4)
- Brokerage describes the role of a node in the network and its ability to connect different subgroups in a specific grouping situation [46]. After determining a grouping category, the five types of brokerage relationships (to include the number of times listed; coordinator, gatekeeper, representative, consultant, and liaison) in each node are counted. Nodes with high brokerage values need more attention, because they have key roles in extending communication impacts and promoting the overall network complexity.
3.5. Identification of the Critical Influencing Factors
4. Results
4.1. Data Collection Results
4.2. SNA Analysis Results
4.2.1. Network Level Results
4.2.2. Node and Link Level Results
5. Discussion
5.1. Critical Challenges and Obstacles during the Developmental Stage of MTS Building
5.2. Stakeholder Relationships
5.3. Countermeasures to MTS Building Development
5.3.1. Increase Policy Incentives and Support
5.3.2. Improve Technical Specification System
5.3.3. Enhance Publicity
5.3.4. Innovative Development Mode
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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No. | Influencing Factors | Stakeholders | Sources |
---|---|---|---|
S1F1 | Investment inclination | Developer | [6] |
S1F2 | Market positioning on MTS building | Interview | |
S1F3 | Development cost of MTS building | [47] | |
S1F4 | Comprehensive benefits of developing MTS building | Interview | |
S1F5 | Management experience and ability | Interview | |
S2F6 | Experience and ability on MTS building design | Designer | [6] |
S2F7 | Number of people engaged in MTS building design | Interview | |
S3F8 | Timber raw material acquisition | Prefabricated component manufacturer | Interview |
S3F9 | Production technology and operation process | [6] | |
S3F10 | Production innovation capacity | Interview | |
S3F11 | Number of suppliers | [26] | |
S3F12 | Logistics transportation technology | Interview | |
S4F13 | Experience and ability on MTS building Construction | Construction enterprise | [6] |
S4F14 | Number of technical professionals | Interview | |
S5F15 | Post-occupancy evaluation on MTS building | End user | Interview |
S6F16 | Promulgation of supportive policy | Government | [6] |
S6F17 | Technological specifications on MTS building | [39] | |
S7F18 | Research input on MTS building | Research institution | [6] |
S7F19 | Experience on MTS building research and development | [26] | |
S7F20 | Conversion rate of scientific research achievements | Interview | |
S8F21 | Understanding about MTS building | Public | [11] |
S8F22 | Acceptance and publicity on MTS building | [27] | |
S9F23 | Purchase tendency of MTS building | Media | [11] |
Rank | Factor ID | Out-Degree | Rank | Factor ID | Degree Difference |
---|---|---|---|---|---|
1 | S6F16 | 18 | 1 | S6F16 | 11 |
2 | S1F2 | 12 | 2 | S6F17 | 9 |
3 | S6F17 | 12 | 3 | S1F1 | 8 |
4 | S3F9 | 12 | 4 | S5F15 | 6 |
5 | S7F18 | 11 | 5 | S2F7 | 6 |
6 | S5F15 | 11 | 6 | S9F23 | 5 |
7 | S1F4 | 9 | 7 | S7F18 | 5 |
8 | S1F3 | 9 | 8 | S1F3 | 5 |
9 | S8F22 | 8 | 9 | S3F11 | 4 |
10 | S4F13 | 8 | 10 | S3F8 | 3 |
Rank | Factor ID | Node Betweenness Centrality | Link ID | Link Betweenness Centrality |
---|---|---|---|---|
1 | S1F3 | 17.468 | S1F1 → S1F2 | 23.386 |
2 | S1F2 | 12.489 | S1F3 → S6F16 | 19.869 |
3 | S6F16 | 11.792 | S1F2 → S1F5 | 17.315 |
4 | S3F9 | 8.186 | S1F3 → S7F18 | 16.888 |
5 | S7F18 | 5.152 | S3F11 → S1F3 | 16.662 |
6 | S1F4 | 4.780 | S6F16 → S3F8 | 15.964 |
7 | S5F15 | 4.303 | S4F14 → S1F3 | 14.304 |
8 | S4F13 | 3.678 | S1F5 → S5F15 | 13.095 |
9 | S8F21 | 3.549 | S1F4 → S6F16 | 12.499 |
10 | S2F6 | 2.931 | S8F21 → S6F16 | 11.804 |
Factor ID | Partition Value | Coordinator | Gatekeeper | Representative | Consultant | Liaison | Total |
---|---|---|---|---|---|---|---|
S1F3 | Developer | 3 | 25 | 9 | 0 | 49 | 86 |
S6F16 | Government | 0 | 4 | 8 | 3 | 53 | 68 |
S3F9 | Prefabricated component manufacturer | 3 | 14 | 18 | 0 | 32 | 67 |
S1F2 | Developer | 6 | 19 | 18 | 3 | 20 | 66 |
S1F4 | Developer | 0 | 8 | 7 | 1 | 28 | 44 |
S8F21 | Public | 0 | 5 | 1 | 0 | 35 | 41 |
S7F18 | Research institution | 1 | 5 | 14 | 1 | 18 | 39 |
S8F22 | Public | 0 | 2 | 1 | 0 | 30 | 33 |
S9F23 | Media | 0 | 0 | 2 | 0 | 27 | 29 |
S4F13 | Construction enterprise | 0 | 6 | 6 | 1 | 14 | 27 |
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Du, Q.; Zhang, R.; Cai, C.; Jin, L. Factors Influencing Modern Timber Structure Building Development in China. Sustainability 2021, 13, 7936. https://doi.org/10.3390/su13147936
Du Q, Zhang R, Cai C, Jin L. Factors Influencing Modern Timber Structure Building Development in China. Sustainability. 2021; 13(14):7936. https://doi.org/10.3390/su13147936
Chicago/Turabian StyleDu, Qiang, Runnan Zhang, Changlu Cai, and Liangwei Jin. 2021. "Factors Influencing Modern Timber Structure Building Development in China" Sustainability 13, no. 14: 7936. https://doi.org/10.3390/su13147936
APA StyleDu, Q., Zhang, R., Cai, C., & Jin, L. (2021). Factors Influencing Modern Timber Structure Building Development in China. Sustainability, 13(14), 7936. https://doi.org/10.3390/su13147936