Journal of Distribution Science (유통과학연구)

Korea Distribution Science Association (한국유통과학회)
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Effect of Information Sharing on Dimensions of Trust and Logistics Performance

  • Changjoon LEE (College of Business Administration, University of Ulsan) ;
  • Young-Kyou HA (Department of International Trade and Logistics, Chung-Ang University)
  • Received : 2024.02.26
  • Accepted : 2024.06.05
  • Published : 2024.06.30
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Abstract

Purpose: This study aims to empirically analyze the effect of information sharing on the two dimensions of trust and logistics performance in the relationship between firms in the supply chain. Research design, data and methodology: In this study, information sharing is a variable for information competency of the entire supply chain. Moreover, we classified trust into quantitative and qualitative trust and analyzed the two paths through which information sharing reaches logistics performance. To examine these correlations, we conducted a survey among professionals in supply chain-related departments in South Korea. Based on 350 completed questionnaires, we tested the hypotheses with structural equation modeling using SPSS 18.0 and AMOS 18.0. Results: We found that information sharing has a significant positive effect on trust and logistics performance, which is a typical index of supply chain performance. These results show that information itself is considered a partner to a firm's competencies in operating the supply chain and plays a major role in forming the other's competencies and trust for the present and future. Conclusions: As these competencies and trust consequentially affect logistics performance, supply chain managers must pay attention to the importance of information competency and consider ways of promoting it to improve logistics performance across the entire supply chain.

Keywords

1. Introduction

Information has played a critical role for a long time in supply chain operations. Since firms in the supply chain are also aware of this, they have been focusing their efforts into efficiently delivering information to ensure smooth operational performance of the hierarchical supply chain. Although traditional information sharing is an internal competency of the supply chain, it has only been effective for sharing superficial facts. However, as the external environment of supply chains is changing rapidly, which has a growing impact on the internal supply chain, there is a need for not only internal information sharing but also the information competency of all players in the supply chain (Fan et al., 2016).

Traditional research explains that accurate information sharing prevents the bullwhip effect and eliminates wasteful factors (Fransoo & Wouters, 2000). The bullwhip effect here means a supply chain phenomenon describing how small fluctuations in demand at the retail level can cause larger fluctuations in demand at the distributor and material supplier levels (Wang & Disney, 2016). However, merely preventing the bullwhip effect cannot fully address and explain the impact of rapidly changing external factors on the supply chain’s internal factors. For example, the need to launch new products due to changes in trends and technology, adjust production due to rapid changes in economic/policy factors, and responses to external factors such as trade wars, are domains that require information competency across the entire supply chain, such as information collection, interpretation, and prediction, rather than information delivery.

Previous studies on information sharing focused on accurately delivering the market demand to manufacturers based on the bullwhip effect (Lee et al., 1997; Wang & Disney, 2016). These studies not only led to the stable operation of the existing supply chain, but also produced meaningful results. However, this revealed many limitations in analyzing the rapidly changing internal and external environments of the supply chain, which is why there is now a need for new research analyzing how information sharing acts as the competency of the entire supply chain that can process and deliver information outside of itself.

Therefore, this study defined information sharing as encompassing the ability to collect, interpret, and predict information inside and outside the supply chain. We conducted research with the assumption that information sharing maximizes logistics performance. Specifically, information sharing, as defined in this study, is information competency across the entire supply chain, which affects cognitive and affective trust among the members. In other words, as more quality information is shared promptly with its consistency validated, supply chain members will have more quantitative and qualitative trust in one another.

These two dimensions of trust ultimately create synergy within the supply chain, thereby improving its overall logistics performance (Sahay, 2003).

This study not only emphasizes the importance of information sharing within the rapidly changing supply chain, but also redefines it and provides academic scalability and implications. Furthermore, by selecting trust (which had been used as a qualitative factor and independent variable in structural equations) as a key variable that connects quantitative and performance factors, a new role is provided for the structural equation path. In addition, resetting these traditional key variables will suggest academic scalability for future research. The results of this study are expected to provide practical implications for the government and firms seeking to produce the best results in the rapidly changing internal and external supply chain environment.

2. Literature Review

2.1. Information Sharing

Previous studies related to supply chain management (SCM) are usually conducted from two perspectives: the relationship between firms in the supply chain and the structure of the supply chain (Kitchot et al., 2021; Shukla et al., 2011). Information sharing is emerging as an important issue, which may be due to changes in the supply chain environment. In the past, only direct order information had been exchanged between firms in the form of orders. This not only led to delayed deliveries and excessive inventory accumulation, but also resulted in the bullwhip effect by distorting actual demand. However, supply chain management refers to a technique that manages information flow in addition to the overall flow of goods. In particular, the advancements in information technology are more easily integrating firms in the supply chain; Zhou and Benton (2007) argued that performing supply chain-related tasks, including information sharing in this environment, has a positive effect on performance improvement.

Specifically, Holland (1995) empirically analyzed that smooth information sharing reduces uncertainties in supply and demand within the supply chain, which may improve performance. Ouyang (2007) proved that information sharing between firms leads to a reduction in the bullwhip effect, which is a chronic and frequently appearing problem. Thus, to improve overall performance, it is essential to make strategic and proper use of information sharing. The term smart SCM can easily be found in recent studies related to supply chain management. Smart SCM refers to a business system that emphasizes automation, liberalization, and connectivity of the entire supply chain (Bhattacharyya et al., 2021). The core foundation of smart SCM is visibility and information sharing related to the inventories of finished products; the quantity of products currently being assembled is important in securing visibility.

2.2. Trust

Trust refers to honesty and goodwill toward the other party. Honesty here means believing that the other party will faithfully fulfill their promise, and goodwill means believing that the other party consistently has an interest in one's well-being (Kumar et al., 1995). In addition, Schurr and Ozanne (1985) described trust as believing the other party’s words, actions, and promises, and McKnight et al. (1998) described it as a belief formed based on interaction experiences in interpersonal relationships. Since this kind of trust is included in all relationships, including interpersonal relationships, it is generally explored in social sciences. In business administration, the role of trust is examined with a focus on the relationship between suppliers and buyers and between firms. Recently, trust has also been studied in many previous studies related to supply chain, which is because supply chain performance can be improved based on trust. Specifically, trust is necessary for the smooth collaboration between firms in the supply chain (Ballou et al., 2000), and the role of trust is also important to reduce transaction costs (Sako, 1991). In other words, the concept of trust can be a critical factor in efficiently building a supply chain.

As a multidimensional concept, trust can be divided into two dimensions depending on the research purpose: trust based on objective facts such as the other party’s ability (cognitive trust), and trust based on affective states such as good faith (affective trust) (Johnson & Grayson, 2005). Cognitive trust refers to trust generated by the other party’s ability, where ability indicates skill or competency. Furthermore, Lewis and Weigert (1985) defined cognitive trust as believing in others based on valid reasons, and Nyaga et al. (2010) defined it as the belief that others will perform their tasks effectively based on rational knowledge. Hence, the concept of cognitive trust appears frequently in studies that view trust as a logical choice. As cognitive trust is explored from a logical perspective, it often does not consider the affective aspect. Thus, cognitive trust can be described as trust with high rationality that is formed based on the other party’s expertise.

Affective trust, which is described as goodwill and care, refers to trust based on emotions generated in interpersonal relationships (Lewis & Weigert, 1985). It can be seen as an emotional bond with the other party, and is subjective as it is based on emotions or psychological states. Affective trust acts as a necessary element in the supply chain; Lawler (2001) claimed that it is useful in generating positive emotions by reducing uncertainties with the other party. It also plays a key role in reducing the bullwhip effect, which is one of the chronic problems that occurs in supply chains (de Almeida et al., 2017). Thus, based on previous studies, affective trust can be said to play a role in reducing risks within the supply chain and is an essential factor for smooth collaboration between firms.

2.3. Logistics Performance

Logistics refers to managing the movement of products from where they are produced to the end user. The U.S. Council of Logistics Management describes logistics as the control of the process from the source of raw materials supply to the consumer to meet consumer demand. Since logistics is one of the essential components of supply chains, many firms perceive its necessity and importance. Meanwhile, performance can be examined in terms of efficiency and effectiveness. Efficiency can be defined as the degree to which resources are used economically, and effectiveness can be defined as the degree to which the firm’s goals are achieved. Thus, combining these two concepts, logistics performance is a subset of corporate and organizational performance (Chow et al., 1994), and can be interpreted as a firm’s ability to manage all situations that arise while performing logistics-related tasks.

Measuring logistics performance is critical for firms in the supply chain because it is related to profitability and market share. In addition, it is possible to analyze the trade-off between logistics costs and customer services by measuring logistics performance, which is why it is necessary to continue measuring the performance of logistics-related activities. Meanwhile, logistics performance is also being studied as a multidimensional concept depending on research purpose. Stank et al. (2003) divided logistics performance into financial and non-financial, and Lacovou (1995) classified it into operational and strategic. In addition, Germain et al. (1996) examined logistics performance by dividing it into internal performance and performance compared to competition. As such, there are various forms of dimensions in measuring logistics performance depending on the research purpose. Based on previous studies, this study divides logistics performance into efficiency and effectiveness and measures each through total logistics cost, lead time, order completion rate, inventory turnover rate, and logistics operations ability (Harrison & New, 2002; Wang, 2018).

3. Hypotheses Setting

3.1. Information Sharing and Trust

Today, firms conduct constant research to achieve high quality, low delivery costs, and logistics service performance improvements. Information sharing is broadly related to these (Prajogo & Olhager, 2012). In other words, firms can not only reduce total logistics costs, but also deliver a higher value to end users through information sharing between firms in the supply chain. Thus, information sharing is a key factor in supply chain management and has a positive effect on firms that constitute the supply chain. In addition, the development of enterprise resource planning (ERP) and electronic data interchange (EDI) also proves the importance of information sharing (Smith et al., 2020). Information may be the most important yet difficult aspect to manage in a business environment. Several cases have revealed that firms that are highly capable of managing information can survive even in fierce competition. Accordingly, firms in the supply chain are striving to develop ERP, a tool that can promote productivity, and EDI, a tool that can increase the effectiveness of information exchange.

Meanwhile, this correlation between information sharing and trust has also been explored in several previous studies. Özer et al. (2018) empirically analyzed that it is possible to form a higher level of trust through information sharing. Khan et al. (2018) proved the correlation between information sharing and trust in service supply chain management in the United Arab Emirates, and Hassan Ibrahim and Allen (2012) revealed that the collaborative act of information sharing is necessary for building trust in the oil industry. Therefore, this study determined that information sharing will have a significant effect on the two dimensions of trust. Accordingly, the following hypotheses were established:

H1: Information sharing has a significant positive effect on cognitive trust.

H2: Information sharing has a significant positive effect on affective trust.

3.2. Trust and Logistics Performance

The definition of trust varies depending on the field and purpose of research. In psychology, trust is described as the act expected from the other party, whereas in business management, it is described as the belief in the other party. Trust is the most fundamental element in supply chain management, which is because it is useful in mitigating problems that may arise in relationships with other parties (Lawler, 2001). In other words, trust can play a role in reducing uncertainties in trade connections. In addition, Blau (2017) claimed that trust is a prerequisite to continuous mutual commitment, and Schurr and Ozanne (1985) argued that it is a prerequisite to a favorable attitude. Thus, these previous studies show that trust is an essential factor for building effective and efficient relationships with trading partners.

Correlations between trust and corporate performance have been explored from various perspectives. Glaveli et al. (2023) empirically analyzed that the formation of trust improves the quality of interaction and the performance of shipping companies. Ganesan (1994) claimed that trust can promote collaboration with trading partners and reduce legal issues that may arise in their relationships. Cambra-Fierro and Polo-Redondo (2008) revealed that trust is necessary as an antecedent for building a satisfactory relationship. Therefore, this study determined that building the two dimensions of trust will have a significant effect on logistics performance, which is a key indicator of supply chain performance. Accordingly, the following hypotheses were established:

H3: Cognitive trust has a significant positive effect on logistics performance.

H4: Affective trust has a significant positive effect on logistics performance.

Figure 1 presents these hypotheses in a diagram:

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Figure 1: Research model

4. Empirical Analysis

4.1. Data Collection

This study seeks to empirically analyze the effect of information sharing on the two dimensions of trust and logistics performance in the relationship between buyers and suppliers in the supply chain. Prior to distributing the questionnaire, the study’s validity was secured by seeking advice on the survey items from employees working in supply-chain-related jobs. Subsequently, the final survey items were selected, with all items measured on a 7-point Likert Scale. The survey was conducted for two months, from June 2023, targeting employees working in supply-chain-related jobs in South Korea, through a survey agency called Entrust Survey. A total of 4,200 copies of the questionnaire were distributed, and 350 completed copies were used for statistical analysis, excluding responses from dropouts and disqualified respondents.

The hypotheses were tested using structural equation modeling, which has the advantage of examining the structural relationships between variables that are simultaneously set according to the hypotheses. That is, even if there are complex relationships among several variables, they can be easily analyzed using structural equation modeling. The hypotheses were tested using SPSS 18.0 and AMOS 18.0.

4.2. Operational Definitions and Measurement of Variables

This study measured information sharing and the two dimensions of trust with four variables each. Moreover, the dependent variable, logistics performance, was measured with five variables. Table 1 shows the measurement items used in this study:

Table 1: Measurement Variables

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4.3. Sample Characteristics

The characteristics of the sample used in this study are shown in Table 2 below. Of the respondents, 30.6% had fewer than 5 years of experience in SCM-related departments, the largest group, and the most common industry was general machinery, followed by semiconductors and petrochemical products. Of the respondents, 90.0% reported total employees less than 5000 and 32.9% were doing business with more than 20 suppliers.

Table 2: Sample Characteristics

OTGHB7_2024_v22n6_123_5_t0002.png 이미지

4.4. Reliability and Validity Analysis

In social sciences, the reliability of measurement variables is commonly assessed using Cronbach's alpha, which is considered reliable when the value is at least 0.7 (Hair et al., 2010). The measurement variables used in this study generally showed high reliability. Next, this study examined the convergent and discriminant validity of each construct. The convergent validity of the measurement variables was verified using composite reliability (CR) and average variance extracted (AVE). The CR and AVE values were above the recommended threshold of 0.7 and 0.5, respectively (Hair et al., 2010). Table 3 presents the results of the confirmatory factor analysis:

Table 3: Results of Confirmatory Factor Analysis

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* p<0.05, ** p<0.01, *** p<0.001

The fit of the measurement model is shown in Table 4 below. It was found that the research model is acceptable as it meets most of the recommended criteria proposed by Hair et al. (2010). Subsequently, discriminant validity was examined, verifying that the concepts measured are indeed distinct from one another. The validation results indicate that the squared correlations between all factors were less than the AVE values, thereby confirming discriminant validity. Table 5 shows the results of the discriminant validity analysis:

Table 4: Measurement Model Fit

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Table 5: Results from Analyzing Discriminant Validity

OTGHB7_2024_v22n6_123_6_t0003.png 이미지

The diagonal represents the AVE of the respective latent variables, while the values below represent the squared correlation coefficient.

4.5. Hypotheses Testing

This study used maximum likelihood estimation to verify the causalities and correlations between information sharing, cognitive trust, affective trust, and logistics performance. The fit of the research model also met most of the recommended criteria proposed by Hair et al. (2010). The results show that information sharing has a significant positive effect on the two dimensions of trust. Moreover, both cognitive and affective trust were found to have a significant effect on logistics performance, which is the dependent variable. Table 6 shows the fit of the structural model, and Table 7 shows the results of hypotheses testing:

Table 6: Structural Model Fit

OTGHB7_2024_v22n6_123_6_t0004.png 이미지

Table 7: Hypotheses Testing Results

OTGHB7_2024_v22n6_123_7_t0001.png 이미지

* p<0.05, ** p<0.01, *** p<0.001

5. Conclusion

5.1. Discussion

This study selected information sharing as an antecedent for improving logistics performance and empirically analyzed the relationship between information sharing, trust, and logistics performance. The analysis results are summarized below.

First, this study emphasized the importance of information sharing by extending the meaning of information within the supply chain. Specifically, information sharing in this study refers to information competency across the entire supply chain. In addition, in future supply chain operations, the ability to collect, analyze, and predict the firm’s internal information, or information that is not superficial, is expected to be considered a comprehensive information competency and a critical element in evaluating and trusting the other’s abilities.

Other conclusions based on empirical analysis show that information sharing has a positive effect on the two dimensions of trust. Specifically, trust is divided into cognitive and affective trust, and information sharing has a positive effect on both. In this study, information sharing refers to information competency of the entire supply chain, which implies that perceiving the other party’s abilities leads to an increase in trust. Moreover, the other party’s dedication to information collection, analysis, and sharing makes firms perceive the other as a reliable partner, thereby having a positive effect on affective trust.

Finally, trust had a positive effect on logistics performance, which is consistent with the result of previous research showing that information sharing affects logistics performance (Yuan et al., 2019). This study extended previous studies and added quantitative and qualitative trust to information sharing and logistics performance, which proved to affect solidarity within the supply chain, ultimately leading to better performance. In other words, trusting each other eliminates opportunistic elements and promotes new attempts and bold decisions, creating a positive effect on the logistics performance of the entire supply chain.

5.2. Implications and Limitations

This study examined whether logistics performance can be improved by using information sharing, which is one of the key elements of supply chain operations, through which it provided the following academic and practical implications.

First, this study redefines the meaning of information sharing and emphasizes its necessity, thereby suggesting academic scalability for further research. Specifically, previous studies defined information sharing from the inventory management perspective, focusing on preventing the bullwhip effect. However, this study redefined information sharing by adding policies, know-how, and market trends necessary for supply chain operations. This extensive redefinition is necessary for research on supply chains that are rapidly changing and becoming more complex.

Second, the study’s redefinition of information sharing provides practical implications for firms operating a supply chain and considering its direction. Information sharing, defined in this study, refers to the information competency across the entire supply chain. This competency is essential for eliciting quantitative and qualitative trust within the supply chain to lead to performance, and its importance was emphasized in this study. In other words, interpretation and prediction will play a more crucial role than superficial information in the future. This study is significant as information competency across the entire supply chain will lead to trust among its members, enhancing logistics performance.

Third, this study examined the role of trust by dividing it into two dimensions rather than a single dimension. Many of the preceding studies that explored trust tended to see it as a single dimension. However, since the variable trust is a concept of a macroscopic dimension, it has been divided into two based on previous studies. And through this process, it is judged to be of academic significance as much as it was possible to clearly grasp the role of trust within the supply chain.

Finally, supply chain operations are recently changing from one that values corporate profits to a trust chain that attaches importance to the overall national interest and security between allies. In other words, there must be policy considerations of performance within the supply chain, not only at the corporate level, but also at the information level. This study emphasized that information sharing can affect supply chain performance, which creates policy implications.

However, this study has limitations in that the analysis was conducted using only ‘trust’ as a variable that connects information sharing and logistics performance. More in-depth research can be conducted by adding diverse variables and performance factors. Furthermore, by subdividing and reanalyzing information humanly, physically, and systematically, it will be possible to extend the research to the entire supply chain, in addition to logistics performance related to information sharing.

References

  1. Ballou, R. H., Gilbert, S. M., & Mukherjee, A. (2000). New managerial challenges from supply chain opportunities. Industrial Marketing Management, 29(1), 7-18. https://doi.org/10.1016/S0019-8501(99)00107-8
  2. Bhattacharyya, S. S., Maitra, D., & Deb, S. (2021). Study of adoption and absorption of emerging technologies for smart supply chain management: A dynamic capabilities perspective. International Journal of Applied Logistics, 11(2), 14-54. DOI: 10.4018/IJAL.2021070102
  3. Blau, B. M. (2017). Social trust and the liquidity of cross-listed securities. Journal of Business Research, 78, 155-171. https://doi.org/10.1016/j.jbusres.2017.05.009
  4. Cambra-Fierro, J. J., & Polo-Redondo, Y. (2008). Creating satisfaction in the demand-supply chain: The buyers' perspective. Supply Chain Management: An International Journal, 13(3), 211-224. https://doi.org/10.1108/13598540810871253
  5. Chen, S. J., Waseem, D., Xia, Z. R., Tran, K.T., Li, Y., & Yao J. (2021). To disclose or to falsify: The effects of cognitive trust and affective trust on customer cooperation in contact tracing. International Journal of Hospitality Management, 94, 102867. https://doi.org/10.1016/j.ijhm.2021.102867
  6. Chow, G., Heaver, T. D., & Henriksson, L. E. (1994). Logistics performance: Definition and measurement. International Journal of Physical Distribution & Logistics Management, 24(1), 17-28. https://doi.org/10.1108/09600039410055981
  7. de Almeida, M. M. K., Marins, F. A. S., Salgado, A. M. P., Santos, F. C. A., & da Silva, S. L. (2017). The importance of trust and collaboration between companies to mitigate the bullwhip effect in supply chain management. Acta Scientiarum Technology, 39(2), 201-210. Doi: 10.4025/actascitechnol.v39i2.29648
  8. Fan, H., Cheng, T. C. E., Li, G., & Lee, P. K. (2016). The effectiveness of supply chain risk information processing capability: An information processing perspective. IEEE Transactions on Engineering Management, 63(4), 414-425. DOI: 10.1109/TEM.2016.2598814
  9. Fransoo, J. C., & Wouters, M. J. F. (2000). Measuring the bullwhip effect in the supply chain. Supply Chain Management: An International Journal, 5(2), 78-89. https://doi.org/10.1108/13598540010319993
  10. Ganesan, S. (1994). Determinants of long-term orientation in buyer-seller relationships. Journal of Marketing, 58(2), 1-19. https://doi.org/10.1177/0022242994058002
  11. Germain, R., Droge, C., & Spears, N. (1996). The implications of just-in-time for logistics organization management and performance, Journal of Business Logistics, 17(2), 19-34.
  12. Glaveli, N., Papadimitriou, D., Karagiorgos, T., & Alexandris, K. (2023). Exploring the role of fitness instructor's interaction quality skills in building customer trust in the service provider and customer satisfaction, European Sport Management Quarterly, 23(3), 767-788. https://doi.org/10.1080/16184742.2021.1928256
  13. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. Prentice Hall, Englewood Cliffs, NJ.
  14. Harrison, A., & New, C. (2002). The role of coherent supply chain strategy and performance management in achieving competitive advantage: An international survey. Journal of the Operational Research Society, 53(3), 263-271. https://doi.org/10.1057/palgrave.jors.2601193
  15. Hassan Ibrahim, N., & Allen, D. (2012). Information sharing and trust during major incidents: Findings from the oil industry. Journal of the American Society for Information Science and Technology, 63(10), 1916-1928. https://doi.org/10.1002/asi.22676
  16. Holland, C. P. (1995). Cooperative supply chain management: The impact of interorganizational information systems. The Journal of Strategic Information Systems, 4(2), 117-133. https://doi.org/10.1016/0963-8687(95)80020-Q
  17. Johnson, D., & Grayson, K. (2005). Cognitive and affective trust in service relationships. Journal of Business Research, 58(4), 500-507. https://doi.org/10.1016/S0148-2963(03)00140-1
  18. Khan, M., Hussain, M., Papastathopoulos, A., & Manikas, I. (2018). Trust, information sharing and uncertainty: An empirical investigation into their impact on sustainability in service supply chains in the United Arab Emirates. Sustainable Development, 26(6), 870-878. https://doi.org/10.1002/sd.1856
  19. Kitchot, S., Siengthai, S., & Sukhotu, V. (2021). The mediating effects of HRM practices on the relationship between SCM and SMEs firm performance in Thailand. Supply Chain Management: An International Journal, 26(1), 87-101.
  20. Kumar, N., Scheer, L. K., & Steenkamp, J. B. E. M. (1995). The effects of supplier fairness on vulnerable resellers. Journal of Marketing Research, 32(1), 54-65. https://doi.org/10.1177/002224379503200107
  21. Lacovou, C. L., Benbasat, I., & Dexter, A. S. (1995). Electronic data interchange and small organizations: Adoption and impact of technology. MIS Quarterly, 19(4), 465-485. https://doi.org/10.2307/249629
  22. Lawler, E. J. (2001). An affect theory of social exchange. American Journal of Sociology, 107, 321-352. https://doi.org/10.1086/324071
  23. Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546-558. https://doi.org/10.1287/mnsc.43.4.546
  24. Lewis, J. D., & Weigert, A. (1985). Trust as a social reality. Social Forces, 63(4), 967-985. https://doi.org/10.1093/sf/63.4.967
  25. Li, S., & Lin, B. (2006). Accessing information sharing and information quality in supply chain management. Decision Support Systems, 42(3), 1641-1656. https://doi.org/10.1016/j.dss.2006.02.011
  26. McKnight, D. H., Cummiongs, L.L., & Chervany, N. L. (1998). Initial trust formation in new organizational relationships. Academy of Management Review, 23(3), 473-490. https://doi.org/10.5465/amr.1998.926622
  27. Nyaga, G. N., Whipple, J. M., & Lynch, D. F. (2010). Examining supply chain relationships: Do buyer and supplier perspectives on collaborative relationships differ? Journal of Operations Management, 28(2), 101-114. https://doi.org/10.1016/j.jom.2009.07.005
  28. Ouyang, Y. (2007). The effect of information sharing on supply chain stability and the bullwhip effect. European Journal of Operational Research, 182(3), 1107-1121. https://doi.org/10.1016/j.ejor.2006.09.037
  29. Ozer, O., Subramanian, U., & Wang, Y. (2018). "Information sharing, advice provision, or delegation: What leads to higher trust and trustworthiness? Management Science, 64(1), 474-493. https://doi.org/10.1287/mnsc.2016.2617
  30. Prajogo, D., & Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135(1), 514-522. https://doi.org/10.1016/j.ijpe.2011.09.001
  31. Sahay, B. S. (2003). Understanding trust in supply chain relationships. Industrial Management and Data Systems, 103(8), 553-563. https://doi.org/10.1108/02635570310497602
  32. Sako, M. (1991). The role of trust in Japanese buyer-supplier relationships. Ricerche Economiche, 23, 449-473.
  33. Schurr, P. H., & Ozanne, J. L. (1985). Influences on exchange processes: Buyers' preconceptions of a seller's trustworthiness and bargaining toughness. Journal of Consumer Research, 11(4), 939-953. https://doi.org/10.1086/209028
  34. Smith, J. R., Yost, J., & Lopez, H. (2020). Electronic data interchange and enterprise resource planning technology in supply chain contracts. Computers & Industrial Engineering, 142, 106330. https://doi.org/10.1016/j.cie.2020.106330
  35. Shukla, R. K., Garg, D., & Agarwal, A. (2011). Understanding of supply chain: A literature review. International Journal of Engineering Science and Technology, 3(3), 2059-2072.
  36. Stank, T. P., Goldsby, T. J., Vickery, S. K., & Savitskie, K. (2003). Logistics service performance: Estimating its influence on market share. Journal of Business Logistics, 24(1), 27-55. https://doi.org/10.1002/j.2158-1592.2003.tb00031.x
  37. Wang, M. (2018). Impacts of supply chain uncertainty and risk on the logistics performance. Asia Pacific Journal of Marketing and Logistics, 30(3), 689-704. https://doi.org/10.1108/APJML-04-2017-0065
  38. Wang, X., & Disney, S. M. (2016). The bullwhip effect: Progress, trends and directions. European Journal of Operational Research, 250(3), 691-701. https://doi.org/10.1016/j.ejor.2015.07.022
  39. Yuan, Y., Viet, N., & Behdani, B. (2019). The impact of information sharing on the performance of horizontal logistics collaboration: A simulation study in an agri-food supply chain. IFAC-PapersOnLine, 52(13), 2722-2727. https://doi.org/10.1016/j.ifacol.2019.11.619
  40. Zhou, H., & Benton Jr., W. C. (2007). Supply chain practice and information sharing. Journal of Operations Management, 25(6), 1348-1365. https://doi.org/10.1016/j.jom.2007.01.009