Dynamic Modeling and Simulation of How Information Sharing Influences Supply Chain Performance

Wang, Weibin; Chi, Renyong

doi:https://doi.org/10.1155/2021/2877467

Discrete Dynamics in Nature and Society

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Abstract Introduction Literature Review Conclusions Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

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Modeling the Complexity and Dynamics of Socioeconomic Systems

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Research Article | Open Access

Volume 2021 | Article ID 2877467 | https://doi.org/10.1155/2021/2877467

Dynamic Modeling and Simulation of How Information Sharing Influences Supply Chain Performance

Weibin Wang^1,2and Renyong Chi²

Academic Editor: Daqing Gong

Received22 Sept 2021

Revised11 Oct 2021

Accepted12 Oct 2021

Published31 Oct 2021

Abstract

With the growing intensity of cooperation, the partners in the manufacturing supply chain (SC) raise stricter requirements for information sharing (IS) within the SC, which has been an effective capability to improve the performance of manufacturing SC. To reveal the influence of IS on SC performance, this paper firstly carries out a theoretical analysis on the influencing factors of IS, SC integration and SC performance, and builds a theoretical model of the IS’s impacting on SC performance. Next, valid index data were obtained by investigating typical manufacturing enterprises in Yangtze River Delta region of China. Then, according to the dynamics system flow of IS influence on SC performance, the proposed theoretical model would be modeled from system dynamics and simulated by Vensim PLE software. The results show that IS among manufacturing SC nodes enhances the SC performance via SC integration; when SC integration is suitable for IS, SC performance will be improved as long as the IS amount is greater than zero; however, excessive IS would reduce the quality and weaken the amount of IS; overall, the degree of IS and SC integration are the key to better SC performance. This implies that how to improve IS among SC partners is a very important thing in manufacturing SC management. And, it also enlightens that enterprise managers should pay attention to establish a high-level trust relationship with SC partners, achieve high-quality IS with a wider range, and then promote the SC system more integrated to improve its operational performance.

1. Introduction

With the advancement of information technology (IT), network communication, and manufacturing technology, integration and competition are two defining trends of the global market. The fierce competition transforms the seller market into a buyer market and promotes the diversification of user needs. In response, manufacturers are updating their products faster and reducing the production cycles.

As consumers pursue better product/service quality, enterprises now have a smaller space for surviving on their own advantages. To cope with severe challenges, it is inevitable for enterprises to start strategic cooperation and complement each other’s advantages. As a result, the supply chain (SC) based on diverse cooperation relations becomes an effective mode of manufacturing management. The rise of SC management mode can help enterprises strengthen information communication with the nodes in the chain to establish a close partnership, so as to quickly optimize the allocation of resources and realize the purpose of high-quality and low-cost supply and demand services for meeting the diverse needs of customers. Especially, under the industrial revolution of “German Industry 4.0” and “Made in China 2025,” enhancing the communication and information sharing ability of SC system has become an effective means to improve the efficiency of manufacturing SC.

Information sharing (IS) is the basis of SC management [1]. In SC, the utility of IS is to mitigate bullwhip effect, information distortion, and information risks, thereby improving the SC operations [2]. Through IS, SC partners can get a whole picture of their diverse relations, realize long-term cooperation, and fully utilize their strengths. This will give full play to the competitive advantages of the entire SC [3].

Nevertheless, many enterprises are reluctant to share information because information, as a valuable competitive resource of enterprises, is easily affected by trust constraints, information circulation channels, limited knowledge sharing, and unreasonable benefit distribution between enterprises. The lack of effective IS among SC partners often hampers the operating efficiency of the SC [4]. Therefore, IS in SC has attracted much attention in recent years. IS has a significant positive impact on partnership in SC, so as to achieve good operation performance of SC [5]. The higher the degree of IS in SC, the higher the level of cooperation in SC, the higher the demand satisfaction rate, the lower the total cost of SC, and thus the higher the supply chain operation performance will be [6]. In general, most scholars believe that IS has a positive impact on SC performance [7, 8].

Concerning IS mechanism, the existing studies mainly consider the weakening of bullwhip effect in the SC. IS helps to reduce uncertainty and enhance trust between SC partners [9]. In a multiechelon SC, the IS between distributors and manufacturers can lower the inventory level and cost [10]. Sun and Ma [11] established a demand function model and found that IS greatly inhibits the bullwhip effect of products with highly autoregressive prices. To boost the overall synergy of the SC, effective IS needs to be realized in addition to the good partnership in the SC [12]. Some studies have shown that IS has a positive impact on SC performance, but the degree of the impact varies with assumptions, exogenous variables, and methods [13, 14]. How IS will improve SC performance is an issue worthy of further discussion.

The above analysis shows the importance to clarify the relationship between IS, SC features, and SC operation performance. To do it, the paper will first take manufacturers in China as objects to identify the factors and relations that affect SC partnership and IS. Specifically, a dynamic model was adopted to simulate the relationship between IS and SC performance. The research results guide enterprises to improve the SC performance by streamlining its relationship with IS.

2. Literature Review and Hypotheses

2.1. Factors Affecting IS in SC

In the existing research, the factors affecting IS in SC are summed up as partner trust, cooperation ability of partners, IS quality, completeness of IS contents (ISCC), market environment, government policies, etc. Without considering external macroscopic factors, this paper holds that IS in SC is mainly affected by ISCC, IS quality, and partner trust.

2.1.1. ISCC

IS refers to the mode by which an information owner communicates with stakeholders and works with them to jointly manage information resources for a specific purpose in a certain range and period [15].

Ovalle and Marquez [16] categorized IS into product information, customer demand information, exchange information, and inventory information. Li and Lin [17] classified IS contents to three levels: transaction information, operation information, and strategic information. Ye et al. [18] divided IS contents into production plan information, production capacity information, inventory information, and demand forecast information. Li et al. [19] believed that the information being shared is used for making production decisions. These studies differ in the understanding of IS contents in SC.

According to the normal relations in manufacturing SC, this paper considers the IS in SC as the information flows about human, material, financial, knowledge, and management between SC partners, supported by IT. In other words, the degree of IS can be measured by ISCC in the SC.

2.1.2. IS Quality

IS quality refers to the timeliness, necessity, and usefulness of IS in collaborative work [20]. The success of SC enterprises depends on the accuracy and timeliness of information provided by partners [21].

Monczka et al. [22] measured IS quality with accuracy, timeliness, adequacy, and reliability. Wiengarten et al. [23] identified four dimensions of IS quality: added value, accuracy, relevance, and timeliness. Ye et al. [24] summarized the aspects of IS quality as accuracy, adequacy, timeliness, integrity, and reliability. It is apparent that most scholars equate IS quality with information quality.

This paper argues that IS quality is mainly about the quality of information transmission, i.e., the undifferentiated transmission of information contents. Therefore, IS quality should be measured by the accuracy, timeliness, and reliability of information.

2.1.3. Partner Trust

Al-Hakim [25] suggested that the effective IS among organizations depends on trust and commitment, and IS quality hinges on the level of trust. Li [26] discovered that the trust and common vision among SC partners promote IS level and quality. Mao and Jiang [27] identified trust, channel power, supplier status, and personal relationship as the behavioral factors affecting IS. Liu and Wang [28] believed that mutual trust significantly promotes the IS between enterprises. Paul and McDaniel [29] echoed that collaboration largely depends on trust to promote the information and knowledge sharing in the whole team.

Smooth collaboration is crucial to the maintenance of a harmonious partnership. A better partnership leads to good information communication between partners, resulting in in-depth IS. In particular, trust and commitment are important metrics for the cooperative relationship between SC enterprises. Hence, this paper regards partnership, trust, and commitment as key promoters of IS degree.

What effect does these core factors of IS have on the operation of SC? Most studies believe that IS strategy among SC members is conducive to the improvement of the overall profit of SC, can save large costs, alleviate bullwhip effect, and improve SC performance [30, 31]. The specific value of IS to SC would be described below.

2.2. Impact of IS on SC Integration

2.2.1. SC Integration

Partnership-based integration of resources and relationship structure is the crux of value creation in SC management [32], and the key to the collaboration among SC partners [33]. SC integration means enterprises collaboratively improve their efficiency and utility by sharing information and allocating resources, trying to make proper decisions of products, services, funds, and management according to the SC relationship structure [34]. Mentzer et al. [35] treated SC integration as combining the processes of the entire SC and merging the relations based on both internal and external resources. Therefore, SC integration not only fuses the relations and collaboration resources among all SC partners but also synthetizes decision-making information to enhance the ability of decision makers.

The demand for IS promotes the integration of the SC system, which in turn accelerates the IS among partners. These two aspects promote each other, but from the perspective of mechanism, IS is the prerequisite for realizing SC integration. For example, Wang et al. [36] analyzed the collaborative development of service SC from the perspective of IS and established an effective sharing incentive model by integrating information flow resources and using IS platform. Wang and Zong [37] analyzed the IS among partners on LSSC and constructed a SC information platform for the aim of IS. Obviously, this indicates the logical relationship between the two dimensions of IS and SC integration.

2.2.2. IS and SC Integration

To improve technology and knowledge, enterprises need to model the relationship between IT capability and corporate performance by exchanging information with each other. The model facilitates the learning of advanced technical skills from each other and acquisition of knowledge and skills from the other parties [38]. From the perspective of industrial cluster, Chen et al. [39] discussed the IS and cooperative innovation among enterprises and concluded that IS brings cooperative innovation and enhances the corporate competitiveness, that is, IS promotes the cooperation between enterprises and suppliers. Therefore, this paper regards IS as a necessary and sufficient condition for SC integration.

2.2.3. Influencing of IS on SC Performance

SC performance covers the performance within an enterprise and that of corporate cooperation. It can be understood as the product/service quality generated from internal/external resources of the enterprise and the total value generated through corporate operation [40].

Chen et al. [41] defined the four objectives for the evaluation of manufacturing SC performance: cost, quality, delivery, and flexibility. Huang et al. [42] proposed that demand sharing improves SC efficiency by reducing inventory level and cost. Deng et al. [43] claimed that the IS among SC partners optimizes inventory management and minimizes supply error rate. Ji [44] demonstrated that IS affects the response time, delivery delay, lead time, inventory turnover, etc., making SC operation more coordinated. Therefore, IS has a clear impact on SC performance [45].

In short, the positive relationship between IS and SC performance is generally accepted. Namely, the higher the degree of IS, the higher the SC performance will be promoted [46]. However, it has also been found that IS is not always beneficial [47]. For example, Zhang and Chen [48] found that IS with uncertain demand did not increase the total revenue, but led to the reduction of the total revenue. Then, what are the rules of impact of IS on SC performance? To explore this issue in depth, we will carry out follow-up studies based on the hypothesis of positive relationship between the two dimensions.

3. Theoretical Model

IS demand is the premise to promote SC system integration, which, on the contrary, is the basis of IS. At the same time, the degree of IS determines the degree of SC integration.

Overall, IS in the SC affects SC performance indirectly via SC integration. Figure 1 shows our theoretical model for the indirect influence of IS on SC performance.

As shown in Figure 1, our model depicts the IS between SC partners in the SC environment, with SC integration and SC performance as the main variables. The causality between the main variables is as follows:(1)Partner trust in SC is the basic condition for implementing IS and the constraint of IS coverage and quality.(2)SC integration increases with the degree of IS between SC partners.(3)Information integration in SC aims to allocate resources effectively and maximize the resource value in SC through coordinated management of the complex supply-demand relationships. In return, the effective resource allocation and value maximization deepen the information integration in the SC.(4)High information integration improves SC performance. The better the performance, the greater the trust and dependence between SC partners.

4. Methodology

4.1. System Dynamics (SD) Theory

SD is a method for system simulation analysis based on feedback control theory, with the aim to solve dynamic problems of the complex system [49]. The possible solutions are searched for by analyzing the internal relationship between function structure and dynamic behavior of the system, using cybernetics, information theory, decision theory, and computer simulation [50]. SD theory was originally used to simulate the survival and inventory management for enterprises. Over the years, the theory has been gradually applied to project management, SC management, learning organization, and corporate strategy [51].

SD theory has both qualitative and quantitative aspects [52]. Qualitatively, the theory intends to analyze the problem and confirm the research goal and draw the causal feedbacks of the system. Quantitatively, the theory tries to establish a system dynamics model and reproduce the system behavior through simulation. In recent years, more and more attention has been paid to the application of SD modeling in SC management. This paper establishes a dynamic model for the complex relations between SC partners.

4.2. Questionnaire Design

Based on the literature review of [16–47] and three dimensions of Figure 1, we conclude the indicators of the factors in Figure 1, as shown in Table 1. So, our questionnaire was designed by analyzing the above influencing factors. Each item in the questionnaire was rated by the respondents against a Likert 5-point scale from very inconsistent to very consistent, according to the actual situation of their enterprises. The respondents are experts from 100 enterprises in the Yangtze River Delta. A total of 89 valid questionnaires were obtained. The reliability and validity analysis of the data is shown in Table 1.

The cumulative variance interpretation rate is greater than 60%, indicating that the extracted three factors can explain the included indicators. It shows that the setting of dimensions and indicators is reasonable. At the same time, reliability and validity tests on valid samples show that Cronbach’s alpha was 0.893, indicating the variables are highly reliable. In addition, the Kaiser–Meyer–Olkin (KMO) statistic was 0.853. Overall, the selected variables are proved reliable and valid.

5. Dynamic Simulation

5.1. Dynamic Modeling of System Flows

In order to explore the influence relationship between dimensions, this paper introduces the system dynamics method to construct the causal relationship of factors. Considering that the commonly used software in system dynamics modeling is Vensim_PLE and Anylogic, Anylogic is more used in discrete events, multiagent simulation, etc. However, Vensim_ PLE can be more widely used in the research field of informatization influencing factors, specifically reflected in the application of logistics informatization and enterprise informatization [53–55]. Venism has a friendly interface and clear system boundaries to simulate the causality between factors in a graphical manner. It can write the quantitative relationship between variables and parameters into the model in the form of equations. The SD model established on Venism can clearly illustrate the causality and support manual editing of equations, providing a desired tool for economic management research.

System dynamics model is an abstract description of the real situation. In order to grasp the main influence relationship of the system, it is assumed that the system is not affected by other external nonmajor factors. Based on the influencing factors in Figure 1 and their causality, a Venism-based model was constructed for IS effects on SC performance, which is as shown in Figure 2.

5.2. Variables and Equations

According to the causal relationship between factors and factor analysis, the main path equations between the influencing factors are as follows:(1)IS quantity = IS coverage × IS quality × partner trust × degree of SC integration(2)Degree of SC integration = 0.82 × SIN ((dynamic resource allocation) × (information decision) × (network partnership))(3)SC performance = Cost × consumer satisfaction × shared benefits × degree of SC integration

6. Results’ Analysis

6.1. IS Evolution

Figure 3 shows the effects of the three constituent variables of IS on IS amount.

As shown in Figure 3, the effect of IS gradually appeared with the growing partner trust, IS coverage, and IS quality, in the initial phase of IS. Soon, the partner trust surpassed the critical value, and IS amount rose steadily, despite the oscillations of IS coverage and IS quality. The oscillation range of IS coverage was similar to that of IS quality in a month. After 40 days, however, the gap between the two in the oscillation range gradually widened.

With the elapse of time, IS coverage expanded faster to the maximum than IS quality. This means a deep and wide IS contributes to IS quality. However, this is not always the case. Once the time extended beyond 100 days, IS coverage and IS quality started to fluctuate in opposite directions. Perhaps, an excessive IS hinders the improvement of IS quality. In other words, there should be a limit on IS coverage. Effective IS should be carried out within a reasonable sharing range.

Under a normal IS environment, IS amount and information diffusion in the SC reached the best state from 60 days to 80 days. However, IS amount declined deeply, once IS coverage expanded again.

6.2. Impact of IS on SC Performance

6.2.1. Impact of SC Integration on SC Performance

To judge whether IS amount is fully effective for SC performance, this paper chooses a specific SC integration level higher than the initial value as a reference to simulate SC performance (Figure 4).

As shown in Figure 4, SC performance continues to rise within the first 100 days, as long as IS amount is greater than zero. There are two implications of this trend: First, IS amount indeed promotes SC performance. Second, IS has a significant effect on SC performance, when SC integration level is suitable. That is, the best SC performance appears under the compatibility between SC integration and IS. If the SC is integrated excessively, i.e., surpassing the supporting need of IS, it would be difficult to optimize the SC performance.

6.2.2. Direct Influence of IS Amount on SC Performance

Figure 5 compares the indirect and direct effects of IS on SC performance, with and without mediator variable.

As shown in Figure 5, IS quantity, which changed rather stably, had a significant improving effect on SC performance. This shows that when the integration of the SC system is consistent with the amount of IS in the chain (i.e., the degree of IS); even if the degree of IS is no longer increased, the effectiveness of IS is still enough to promote the continuous improvement of SC performance, which further supports the conclusion in Figure 4. Thus, there is a positive correlation SC performance and IS amount. This correlation could be mediated by SC integration. SC performance can be improved most effectively by matching IS with SC integration.

7. Conclusions

This paper theoretically analyzes influencing factors of IS in SC, SC integration and SC performance, and proposes several hypotheses. On this basis, a dynamics model was constructed for the IS effects on SC performance, using a SD modeling software.

Through model simulation, it is confirmed that IS has a positive impact on SC performance, and IS could promote SC performance via SC integration. Note that, during the generation of SC performance, SC integration serves as a trigger of the IS’ promoting effect on SC performance. The higher the degree of SC integration, the greater the utility of IS. In other words, SC integration lays the basis and acts as a critical supporting condition for IS to promote SC performance. The positive effect of IS on SC performance persists, as long as the level of SC integration ensures the best utility of IS.

In addition, it should be noted that the relations among IS coverage, IS quality, and partner trust are not linear. When partner trust grows, the influence of the other two variables on IS amount was relatively consistent in the initial stage. Moreover, with the elapse of time, the coverage of IS expanded, while the quality of IS weakened. This means, when the trust is unlimited, completely open IS will lead to inefficient IS quality, which in turn reduces the effective IS amount. Therefore, it is important to carry out IS within a reasonable open range to achieve better SC performance.

The research also has some shortcomings. Due to the limitations of questionnaire survey, the amount of simulation data in this research is relatively small, and the simulation results of the overall system dynamics model should be further improved on the basis of large sample data. Moreover, the structure of the model is relatively linear, and the feedback relationship between different variables in the model should be adjusted to make the structure of the model closer to reality by considering the dynamic operation environment of SC.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest regarding the publication of this paper.

Acknowledgments

This research was supported by the Industry-University-Research Collaborative Education Project of the Ministry of Education (Grant no. 201801218003), the Social Science Planning Project of Zhejiang Province (Grant no. 17NDJC093YB), and the Key social science planning projects in Zhejiang Province (Grant no. 22HQZZ602Z).

References

Z. P. Chang and F. Jiang, “The analysis of the levels of information sharing in supply chain and its impact factors,” Industrial Engineering & Management, vol. 8, no. 2, pp. 22–24, 2003.
View at: Google Scholar
R. F. Zhou and W. Y. Su, “Study on supply chain partner characteristics, information sharing and enterprise operational performance,” Logistics technology, vol. 31, no. 11, pp. 356–359, 2012.
View at: Google Scholar
C. S. ReVelle and H. A. Eiselt, “Location analysis: a synthesis and survey,” European Journal of Operational Research, vol. 165, no. 1, pp. 1–19, 2005.
View at: Publisher Site | Google Scholar
G. M. Wei, L. G. Ren, J. J. Qin, and Y. M. Ma, “Research on demand information sharing strategies in low carbon dual-channel supply chain,” Operations Research and Management Science, vol. 28, no. 3, pp. 45–56, 2019.
View at: Google Scholar
H. Zhou, Y. Shou, X. Zhai, L. Li, C. Wood, and X. Wu, “Supply chain practice and information quality: a supply chain strategy study,” International Journal of Production Economics, vol. 147, pp. 624–633, 2014.
View at: Publisher Site | Google Scholar
S. H. Zhang and K. L. Cheung, “The impact of information sharing and advance order information on a supply chain with balanced ordering,” Production and Operations Management, vol. 20, no. 2, pp. 253–267, 2015.
View at: Google Scholar
H. Feng, L. Nie, and Y. L. Shi, “The interaction between supply chain governance mechanisms and supply chain performance: based on the mediating effects of information sharing and the moderating effects of information technology level,” Chinese Journal of Management Science, vol. 28, no. 2, pp. 104–114, 2020.
View at: Google Scholar
R. H. Zhou, “Empirical Study on the impact of enterprise information sharing level on supply Chain Performance--taking manufacturing enterprises as an example,” China Business and Trade, vol. 30, pp. 170–172, 2017.
View at: Google Scholar
R. K. Sue, “Factors affecting the level of trust and commitment in supply chain relationships: study of small-medium size enterprises (SMEs) in Taiwan,” Institute of International Management, Cheng-Gong University, Tainan, Taiwan, 2007, Master’s thesis.
View at: Google Scholar
Y. N. Wu and T. C. Edwin Cheng, “The impact of information sharing in a multiple-echelon supply chain,” International Journal of Production Economics, vol. 115, no. 1, pp. 1–11, 2008.
View at: Publisher Site | Google Scholar
Y. Q. Sun and Y. G. Ma, “Impact of information sharing on bullwhip effect--from the perspective of price sensitive demand function,” Systems Engineering, vol. 32, no. 1, p. 8, 2014.
View at: Google Scholar
Z. P. Zhai, Research on the Relationship between Supply Chain Partnership, Information Sharing and Supply Chain Performance, Capital University of Economics and Business, Beijing, China, 2018.
F. Ye, Y. N. Li, H. Zhang, and X. Y. Lei, “Relationship among influential factors and level of information sharing and enterprise performance in supply chains,” Chinese Journal of management, vol. 6, no. 6, pp. 743–750, 2009.
View at: Google Scholar
H. Zhou and W. C. Benton, “Supply chain practice and information sharing,” Journal of Operations Management, vol. 25, no. 6, pp. 1348–1365, 2007.
View at: Publisher Site | Google Scholar
K. Sun and R. H. Liu, “Inter-organizational information sharing strategy choice based on information processing theory,” Chinese Journal of Management, vol. 10, no. 2, pp. 293–298, 2013.
View at: Google Scholar
O. Rubiano Ovalle and A. Crespo Marquez, “The effectiveness of using e-collaboration tools in the supply chain: an assessment study with system dynamics,” Journal of Purchasing and Supply Management, vol. 9, no. 4, pp. 151–163, 2003.
View at: Publisher Site | Google Scholar
S. Li and B. Lin, “Accessing information sharing and information quality in supply chain management,” Decision Support Systems, vol. 42, no. 3, pp. 1641–1656, 2006.
View at: Publisher Site | Google Scholar
F. Ye, J. Zhang, and H. Lv, “Research on the impact of supplier opportunism on information sharing and operational performance,” Journal of Management Science, vol. 25, no. 2, pp. 51–60, 2012.
View at: Google Scholar
L. Li, J. Q. Lu, and J. H. Ji, “Trust in information sharing research,” Shanghai Management Science, vol. 37, no. 3, pp. 60–64, 2015.
View at: Google Scholar
M. S. Magyar, J. F. Edens, M. Epstein, P. G. Stiles, and N. G. Poythress, “Examining attitudes about and influences on research participation among forensic psychiatric inpatients,” Behavioral Sciences & the Law, vol. 30, no. 1, pp. 69–86, 2012.
View at: Publisher Site | Google Scholar
A. Y. L. Chong, B. Lin, K. B. Ooi, and M. Raman, “Factors affecting the adoption level of c-commerce: an empirical study,” Journal of Computer Information Systems, vol. 50, no. 2, pp. 13–22, 2009.
View at: Google Scholar
R. M. Monczka, K. J. Petersen, R. B. Handfield, and G. L. Ragatz, “Success factors in strategic supplier alliances: the buying company perspective,” Decision Sciences, vol. 29, no. 3, pp. 553–577, 1998.
View at: Publisher Site | Google Scholar
F. Wiengarten, P. Humphreys, G. Cao, B. Fynes, and A. McKittrick, “Collaborative supply chain practices and performance: exploring the key role of information quality,” Supply Chain Management: An International Journal, vol. 15, no. 6, pp. 463–473, 2010.
View at: Publisher Site | Google Scholar
F. Ye, H. Lv, and J. Wu, “An empirical study on the relationship among information system Alignment, information sharing and operational performance,” Industrial Engineering & Management, vol. 16, no. 5, pp. 9–15, 2011.
View at: Google Scholar
L. A. Hakim, “Trust and information quality: performance gap analysis,” International Journal of Information Quality, vol. 2, no. 4, pp. 359–372, 2011.
View at: Publisher Site | Google Scholar
Y. Li, “A study of problems arising in sharing and cornering information,” Journal of Beijing University of Posts and Telecommunications, vol. 8, no. 3, pp. 9–12, 2006.
View at: Google Scholar
W. J. Mao and L. Jiang, “On behavioral factors affecting the willingness to share information by retailers and suppliers,” Journal of Hebei University of economics and trade, vol. 29, no. 1, pp. 66–72, 2008.
View at: Google Scholar
G. Liu and L. Wang, “Research on fairness perception, relationship quality and R & D cooperative relationship value,” Science Research Management, vol. 35, no. 8, pp. 25–33, 2014.
View at: Google Scholar
D. L. Paul and R. R. McDaniel, “A field study of the effect of interpersonal trust on virtual collaborative relationship performance,” MIS Quarterly, vol. 28, no. 2, pp. 183–227, 2004.
View at: Publisher Site | Google Scholar
S. Srivathsan and M. Kamath, “Performance modeling of a two-echelon supply chain under different levels of upstream inventory information sharing,” Computers & Operations Research, vol. 77, pp. 210–225, 2017.
View at: Publisher Site | Google Scholar
M. Khan, M. Hussain, and H. M. Saber, “Information sharing in a sustainable supply chain,” International Journal of Production Economics, vol. 181, pp. 208–214, 2016.
View at: Publisher Site | Google Scholar
L. Horvath, “Collaboration: the key to value creation in supply chain management,” Supply Chain Management: An International Journal, vol. 6, no. 5, pp. 205–207, 2001.
View at: Publisher Site | Google Scholar
H. L. Lee and S. Whang, “Winning the last mile of E-commerce,” MIT Sloan Management Review, vol. 42, no. 4, pp. 54–62, 2001.
View at: Google Scholar
W. A. Pan, “Study on the effects of supply chain partnership to competitive advantage based on integration competence,” Science Research Management, vol. 27, no. 6, pp. 47–53, 2006.
View at: Google Scholar
J. T. Mentzer, W. DeWitt, J. S. Keebler et al., “Defining supply chain management,” Journal of Business Logistics, vol. 22, no. 2, pp. 1–25, 2001.
View at: Publisher Site | Google Scholar
H. C. Wang, X. F. Lin, and Y. Wang, “Research on incentive strategies for coordinated development of logistics service supply chain from the perspective of information sharing,” Modern Business Trade Industry, vol. 40, no. 6, pp. 39-40, 2019.
View at: Google Scholar
H. C. Wang and F. Zong, “Research on logistics service supply chain information platform based on B/S architecture,” Economic & Trade, vol. 40, no. 22, pp. 34–37, 2018.
View at: Google Scholar
Y. Q. Zhang, J. H. Chen, and H. Wang, “Research on the relationship between it capability, information sharing and supply chain integration,” Science and Technology Management Research, vol. 31, no. 22, pp. 180–184, 2011.
View at: Google Scholar
Y. Chen, W. C. Wang, J. H. Yang, and X. B. Dai, “Research of information sharing and cooperative innovation in industrial cluster,” System Engineering Theory-Practice & Practice, vol. 24, no. 8, pp. 54–57, 2004.
View at: Google Scholar
W. W. Hao, “Research on partnership, information sharing and their impact on supply chain performance,” Zhejiang Business University, Hangzhou, China, 2015, Master’s thesis.
View at: Google Scholar
F. Chen, Z. Drezner, J. K. Ryan, and D. Simchi-Levi, “Quantifying the bullwhip effect in a simple supply chain: the impact of forecasting, lead times, and information,” Management Science, vol. 46, no. 3, pp. 436–443, 2000.
View at: Publisher Site | Google Scholar
M. X. Huang, Q. Pan, C. X. Xing, J. J. Yang, and Y. M. Cheng, “Information sharing in tri-echelon supply chain,” Industrial Engineering, vol. 11, no. 3, pp. 6–9, 2008.
View at: Google Scholar
W. H. Deng, M. Yi, and G. N. Cai, “Game analysis on information sharing technology strategy of the members on supply chain,” Chinese Journal of Management Science, vol. 17, no. 4, pp. 103–108, 2009.
View at: Google Scholar
J. Z. Ji, “Research on performance evaluation indicators of information sharing in supply chain,” China Commerce and Trade, vol. 2010, no. 8, p. 78, 2010.
View at: Google Scholar
K. D. Lawrence, “The impact of forecasting model selection on the value of information sharing in a supply chain,” International Journal of Forecasting, vol. 19, no. 4, p. 765, 2003.
View at: Google Scholar
X. Zhao, B. Huo, B. B. Flynn, and J. H. Y. Yeung, “The impact of power and relationship commitment on the integration between manufacturers and customers in a supply chain,” Journal of Operations Management, vol. 26, no. 3, pp. 368–388, 2008.
View at: Publisher Site | Google Scholar
S. Q. Cai and J. Liang, “The relation between information sharing and supply chain coordination,” Chinese Journal of Management, vol. 4, no. 2, pp. 157–162, 2007.
View at: Google Scholar
Y. L. Zhang and J. Chen, “Study based on Stackelberg game about the information sharing coordination in supply chain,” Journal of Industrial Engineering and Engineering Management, vol. 18, no. 3, pp. 118–120, 2004.
View at: Google Scholar
Y. Feng, “System dynamics modeling for supply chain information sharing,” Physics Procedia, vol. 25, pp. 1463–1469, 2012.
View at: Publisher Site | Google Scholar
Q. F. Wang, System Dynamics, Tsinghua University Press, Beijing, China, 1994.
H. H. Wang and Z. X. Wu, “Dynamic simulation of inventory control system based on Vensim,” China Management Informationization, vol. 2014, no. 6, p. 45, 2014.
View at: Google Scholar
B. Zhang, Z. H. Yu, Q. Sun, S. Li, M. X. Huang, and L. Q. Wang, “The introduction to system dynamics and relating software,” Environment and Sustainable Development, vol. 35, no. 2, pp. 1–4, 2010.
View at: Google Scholar
W. Li and X. Gao, “Analysis of effect factors of logistics informationalization based on analytic hierarchy process,” Value Engineering, vol. 29, no. 17, p. 7, 2010.
View at: Google Scholar
X. D. Zhang, “Research on evaluation index system and system dynamics simulation of manufacturing informatization,” Tianjin University, Tianjin, China, 2007, Master’s thesis.
View at: Google Scholar
X. Hu, “Research on enterprise informatization driving mechanism and its mode selection,” China University of Mining and Technology, Xuzhou, China, 2013, Doctoral Dissertation.
View at: Google Scholar

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Copyright © 2021 Weibin Wang and Renyong Chi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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