To be included in the sample study, individuals had to meet two criteria. Contacts established within the human resource departments of the participating firms assisted with the lists of such individuals. In selecting the departments, small-scale and micro enterprises were excluded from the study as they were unlikely to have experienced supply chain dynamism, information sharing and inter-organisational relationships to the extent that these issues were experienced by their larger counterparts.
Accordingly, only medium employing between 51 and people and large-scale employing more than people South African Government Gazette :8 manufacturing enterprises were included in the study. An Internet search was conducted to identify medium and large-scale manufacturing firms based in Gauteng Province. This search led to webpages such as BizCommunity, Yellow Pages South Africa and Industrial Buyer, which contained the information about various manufacturing enterprises and their contact details.
Out of a total of 84 firms that were contacted telephonically and through email, 37 did not respond and 16 turned down the request for research. This left a total of 31 firms from which permission to collect data was granted. The profile of participating firms Table 2 shows that the largest number had been in operation for periods ranging between 6 and 10 years In addition, the majority In terms of industry, the largest number of participating firms were from the agri-processing industry Measurement scales were operationalised from previous studies.
Supply chain dynamism was measured using four questions adapted from Zhou and Benton Information sharing was measured using six questions adapted from Li et al. Inter-organisational relationships were measured using five questions adapted from Li and Lin , while supply chain performance was measured using five questions adapted from Green et al.
The measurement scales used in the study were chosen because they are the original scales, are already validated and had been used in several other previous studies, which made them more credible sources when compared to more recent ones that are based on the original scales.
A list of items used in the measurement scales is provided in Appendix 1. A pre-test of the questionnaire was conducted using a conveniently selected sample of 15 supply management professionals to ascertain the content validity of the measurement instrument.
Feedback obtained from the pre-test sample was used to improve the content validity by modifying the questionnaire in terms of the wording of questions, their presentation and technical layout. Respondents that participated in the pre-test were excluded from the main survey. The actual collection of data took place between October and March In administering the survey, the drop and collect method was used in which respondents were given three weeks to complete the questionnaire.
Out of the questionnaires initially distributed, were returned. After screening the questionnaires, data were entered in a Microsoft Excel document for coding. For the assessment of the psychometric properties of the measurement scales and the testing of hypotheses, the Analysis of Moment Structures AMOS 23 software was used.
Informed consent was obtained from all participants, and participation was on a voluntary basis. Also, anonymity of respondents was ensured so as to protect them from victimisation. The research results section discusses the demographic profile of respondents, accuracy analysis statistics and the results of the hypotheses tests.
The demographic details of the respondents who completed the survey questionnaire is provided in Table 1. The profile of the 31 firms that participated in the survey is presented in Table 2. In accordance with the structural equation modelling SEM approach suggested by Anderson and Gerbing , a confirmatory factor analysis CFA was conducted first to determine the psychometric properties of the scale validity, reliability and model fit , followed by the testing of hypotheses through path analysis.
The results of the CFA are reported in Table 3. Table 3 indicates that the item-to-total values ranged from 0. These values were above the recommended minimum threshold value of 0. Therefore, all four measurement scales were internally consistent. Convergent validity was ascertained by calculating the average variance extracted AVE. As suggested by Hair et al. As revealed in Table 3 , AVE values ranged between 0.
Another measure of convergent validity involves verifying whether factor loadings are greater than 0. Factor loadings for the four constructs ranged between 0. Discriminant validity was assessed through the use of inter-construct correlations. According to Clark and Watson , correlation coefficients less than 1. The results of the correlation analysis are provided in Table 4. As reported in Table 4 , the inter-construct correlation values for all paired latent variables ranged between 0.
Hence, discriminant validity was deemed sufficient in this study. Table 5 indicates that the measurement model yielded a ratio of chi-square value to degree-of-freedom of 2. All of these statistics satisfied the recommended thresholds, which depict an acceptable fit of the CFA measurement model to the sample data.
Model fit analysis for the SEM phase of the study was conducted before testing the hypotheses. The resulting statistics showed that the ratio of chi-square over degree-of-freedom was 1. This value is less than the recommended threshold of less than 3.
By implication, the proposed conceptual framework converged well and could be a plausible representation of the underlying empirical data structure collected in the Gauteng Province of South Africa. As the model fit was acceptable Table 5 , the research hypotheses were subsequently tested through the path analysis approach.
The results are provided in Table 6. As indicated in Table 6 , all five hypotheses were accepted, indicating that the proposed relationships between constructs were valid. The loadings of individual items on their respective constructs reported in Table 5 depict that the model converged well and could be a credible depiction of causal empirical data structures collected for this research.
The individual results for the hypotheses tests are discussed in detail in the next section. The purpose of this study was to examine the relationship between supply chain dynamism, information sharing, inter-organisational relationships and supply chain performance in the manufacturing sector in South Africa. A conceptual framework Figure 1 , which placed supply chain dynamism as the input variable antecedent , information sharing and inter-organisational relationships as the mediating variables and supply chain performance as the outcome variable was put forward to illustrate the proposed relationships.
Five null and alternative hypotheses were formulated to describe each section of the relationships between the variables. A positive relationship was hypothesised between supply chain dynamism and information sharing Ha 1 , which was formulated from the objective that aimed to investigate the relationship between supply chain dynamism and information sharing. This relationship illustrates that there exists more pronounced information sharing whenever changes occur in the supply chain.
The changes may be in terms of products, technology, manufacturing, orders and the demand and supply for products in the supply chain. As suggested by Gokhan and Needy and Gligor, Esmark and Holcomb , supply chain dynamism can also be conceptualised in terms of the difference in the amount of information required and already possessed to perform a task within the supply chain. Gunasekaran, Lai and Cheng and Farahani et al.
By implication, the dynamism of manufacturing supply chains in South Africa could give firms an impetus to expedite and streamline the exchange of timely information with their supply chain partners. The positive outcomes associated with information sharing could then be realised. Another positive relationship was hypothesised between supply chain dynamism and inter-organisational relationships Ha 2.
This hypothesis was formulated in an attempt to determine whether or not supply chain dynamism has a relationship with inter-organisational relationships. For example, a malfunctioning production process at the supplier, late delivery or unacceptable quality of the delivered supplies may result in customer dissatisfaction. If these inconsistencies are not addressed, relationships between the underperforming supplier and the customer could be ruined. The study hypothesised that information sharing has a significant positive relationship with inter-organisational relationships Ha 3.
As suggested in a previous research by Yu, Yan and Cheng , information sharing is conceptualised as a combination of resources and systems both tangible and intangible from different supply chain partners working together. On the other hand, both misinformation as well as the withholding of critical information that should be shared between supply chain partners could adversely affect their relationships Fawcett et al.
In essence, the benefits of information sharing within a supply chain far outweigh the costs. Costs include factors such as charges by customers or suppliers for providing the information, the capital invested in information systems, communication costs and administration costs Flynn et al. The fourth alternative hypothesis Ha 4 suggests that there is a positive significant relationship between information sharing and supply chain performance. These results are parallel to those in a previous study by Zhao et al.
Lin et al. Timely exchanges of information can be vital for circumventing possible risks during times of turbulence. For instance, cautioning a manufacturer on the possibility of a decline in product demand can enable that manufacturer to take precautionary measures in production planning. Likewise, when accurate information is exchanged within a supply chain, each partner is able to make better informed decisions in all areas of the business, based on the provided information.
Zhao et al. In addition, information sharing within a supply chain is a source of great improvement in business connections, such as cross-docking, quick response QR as well as vendor managed inventory VMI Jauhari ; Mourtzis The fifth alternative hypothesis proposes the existence of a significant positive relationship between inter-organisational relationship and supply chain performance. International business literature e. A study by Lee concluded that business partners who trust each other will take care of each other during times of instability.
For example, where robust relationships exist, supplier development is always considered a better option whenever the supplier is failing to meet customer expectations. This ensures that performance of both the supplying firm and its buying customer are maintained optimally.
The results of the study are restricted to 31 manufacturing firms drawn from one province of South Africa, which undermines the generalisability of the results to manufacturing firms elsewhere. Future studies may be conducted by using data from other sectors of the economy such as retail, mining and agriculture, and using a larger number of manufacturing firms. Also, the geographic context of the study could be expanded to other regions of South Africa, apart from Gauteng Province.
The study is further limited in that its results were not differentiated by the type of manufacturing industry segments. To address this, future studies could also be conducted in the different manufacturing industry segments such as agri-processing, automobiles, chemicals, electronics, metals and textiles. This will provide insights that are specific and customised to each particular industry. Furthermore, a comparative investigation of this study matter between or among countries that have different levels of development as well as cultures could provide additional insights and contribute new knowledge to the existing body of supply chain performance literature.
Future research could also direct greater emphases to supply chain dynamism and its effects on other variables that mediate the relationship with supply chain performance. Such variables may include supply chain integration, supply chain agility, supply chain resilience and supplier selection, among others. The study concludes that there is a significant positive relationship between supply chain dynamism and both information sharing and inter-organisational relationships in the manufacturing sector.
It is further concluded that a significant positive relationship exists between inter-organisational relationships and supply chain performance in the manufacturing sector. Still, the study concludes that a significant positive relationship exists between inter-organisational relationships and supply chain performance in the manufacturing sector.
The final conclusion is that inter-organisational relationships exert a greater influence on supply chain performance than does information sharing in the manufacturing sector. This study provides useful theoretical insights for academic researchers. It provides a source of reference for future researchers on similar relationships within manufacturing environments. The results of this study on the outcomes of information sharing and inter-organisational relationships are not only in line with previous research e.
The study further provides useful implications for supply management professionals in improving supply chain performance to realise enhanced competitive advantage in the manufacturing sector. The conceptual framework used is an important tool in the diagnoses of problems related to supply chain performance in the manufacturing sector. Whenever there is an erosion of supply chain performance, it is necessary to check the alignment of the constructs considered in this study, as they exert a positive influence on each other.
In addition, as the relationship between the various constructs were positive, enhancement of one also leads to the increase of the other constructs. Managers in the manufacturing sector should monitor and respond positively to the changes in key resources such as products, technology, demand and supply, and policies.
This may enable them to improve the sharing of information and develop better relationships among trading partners, leading to superior performance of the entire supply chain. To improve both information sharing and inter-organisational relationships, manufacturing firms should invest in information and communication technologies that improve their ability to manage information and knowledge across the supply chain.
Supportive, trusting and long-term relationships between supply chain partners should be cultivated as this enables them to share risks and rewards. Better attitudes and practices among supply management professionals in manufacturing firms could be encouraged through training aimed at increasing their awareness of the importance of both information sharing and meaningful inter-organisational relationships.
Step 3. The manufacturer determines an order based on forecast. Step 4. Market demand is randomly realized. Step 5. The retailer firstly fulfills the former back orders and market demand. Then, the order point is updated according to formulas 20 and 21 under strategy IS ; however, under strategy NS.
Lastly, the retailer computes the order quantity. Step 6. The transportation capability is adjusted according to formula 23 under strategy IS ; otherwise, under strategy NS. Step 7. The products are transported to the retailer by the carrier. Step 8. The total costs , , , are computed. Step 9. Enter next period and go to Step 3 until termination. Step Compare the average cost of each member and the whole supply chain under cases IS and NS.
In this section, the simulation experiments are firstly designed. Then the effects of uncertain risks on the costs of supply chain members and information sharing strategy are studied. Parameters of the experiments are set as Table 2.
Simulation experiments are conducted on the Eclipse platform with Java codes. Experiments are carried out considering all parameters with multiple values. This combination method is used in the literature [ 34 , 35 ]. The results in following figures are shown on average. Each simulation is run times with different random seeds, and each time lasts for periods to give each agent abundant time to learn historical experiences.
Observation 1. Under uncertain yield or demand, strategy IS is a preferable choice for the manufacturer; however, it is not always beneficial for other members to adopt IS. Therefore, the bullwhip effect is mitigated, and inventory holding cost and short cost are cut down. However, it is not the case for the retailer and the carrier. Observed from Figures 7 and 8 , strategy IS is profitable for the retailer only when the yield or demand uncertainty is not large.
But the cost gap is small when yield or demand uncertainty is large. Taking advantage of sharing information, inventory forecast accuracy can be guaranteed if yield or demand uncertainty is not great. Yet forecast result is affected seriously if uncertainty value is more than a threshold. It is difficult to control these unnecessary costs incurred by risks. Thus, unlike the manufacturer, strategy IS is not always superior to the other for the retailer.
The value of IS is not obvious as demand or yield uncertainty is large; namely, information sharing should not be applied under the circumstance. Similar to Figures 7 and 8 , forecast accuracy is considered as a significant element to trade off whether to share information. Hence, sometimes strategy IS is not better than NS for the carrier.
If the uncertainties are large, information sharing is not sensible. Because of the similarity, these details are omitted. Observation 2. A higher transportation time uncertainty reduces the total cost of the retailer. Market demand fill rate decreases because of the increasing uncertainty, which further gives rise to the more delayed short cost for the retailer. However, the penalty cost of the carrier due to delayed delivery is enhanced as well while transportation time becomes more uncertain.
Observation 3. Information sharing is not always beneficial to the whole supply chain under uncertain yield demand. Strategy IS should be given up when yield demand uncertainty is large. The impact of yield uncertainty on the supply chain costs under two cases are presented in Figure Channel members use shared information to adjust decisions and adapt to environment dynamically under strategy IS , which saves unnecessary costs caused by unstable yield if these uncertainties are not large.
However, it is not easy to control the risk when uncertainty is large, in that forecast accuracy and quality is cut down. Naturally, the value of information sharing is gradually weakening with the increase of yield uncertainty. The result is similar to that of the demand uncertainty. Therefore, strategy IS should only be adopted by the supply chain when external yield demand uncertainty is not large. Otherwise, information sharing behavior should be avoided. Observation 4.
The cost caused by order process uncertainty can be mitigated obviously under strategy IS ; but the advantage of strategy IS is not evident in terms of transportation time uncertainty. The relationship between ordering process uncertainty and supply chain costs is showed in Figure The cost under strategy IS is smaller than that under NS. Ordering process is omitted, so total lead time and short cost decrease. Hence, the negative impact of ordering process uncertainty can be reduced if strategy IS is utilized, especially under high uncertainty level.
It is profitable for the whole supply chain to share information when the ordering process time exists. The effect of transportation time uncertainty on supply chain costs is depicted in Figure Moreover, while the cost is less for strategy IS , the value of IS is not remarkable.
After all, the uncertainty in transport cannot be eliminated in the spite of shared information. Consequently, it is hard to control the risk caused by uncertain transportation. This paper studies an information sharing strategy in a multilevel supply chain with one manufacturer, one carrier, and one retailer, where all members have to be confronted with uncertain yield, demand, and lead time in a complex multiperiod environment.
Two strategies can be adopted to react to multiple uncertainties: IS or NS. Each member is regarded as an adaptive agent, where decisions can be adjusted in each period to dynamically adapt to the external situation. The costs of supply chain and channel members under two strategies are contrasted, and the effects of yield, demand, and lead time uncertainties on the two strategies are investigated. We find: i strategy IS is optimal for the upstream manufacturer under uncertain yield or demand; ii but for the whole supply chain, the retailer, and the carrier, strategy IS is not always the suitable choice; information sharing should be avoided when demand, yield, or transportation time uncertainty is large; iii the increase of transportation time uncertainty benefits the retailer; iv for the whole supply chain, the cost from ordering process uncertainty is cut down evidently through sharing information; however, it is not easy to mitigate the uncertain transportation risk with sharing information.
There are several directions for future research. This assumption could be relaxed to study a more complex case, where the manufacturer may be faced with capacity crisis. Second, it is worth studying the impact of other decision adjustment methods on information sharing behavior.
Third, market and inventory information are shared among the supply chain members in this paper, but the yield risk upstream is not shared. The factor can be further considered and studied. 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.
Article of the Year Award: Outstanding research contributions of , as selected by our Chief Editors. Read the winning articles. Journal overview. Special Issues. Academic Editor: Manuel De la Sen. Received 10 Jan Accepted 13 May Published 02 Jun Abstract Whether to use an information sharing mechanism is investigated in a dynamic supply chain, where one manufacturer, one carrier, and one retailer are faced with uncertain yield, demand, and lead time during multiple periods.
Introduction Information sharing is regarded as a prevalent business strategy to improve operations performance of the supply chain, which has been successfully used in many industries. Literature Review This paper is related to the information sharing in the supply chain and multiagent modeling. The Model 3. The Overall Structure and Problem Description Consider a supply chain with one manufacturer, one retailer, and one carrier in the presence of complex uncertainties.
Figure 1. Two strategies: IS and NS. Table 1. Figure 2. Figure 3. Figure 4. Parameters Value 80,90,,, 10,15,20,25,30 0. Table 2. Figure 5. Figure 6. Figure 7. Figure 8. Figure 9. Figure References L. Darwish and O. Tyan, F. Wang, and T. Qi and Q. View at: Google Scholar H. Lee, K. So, and C. Yu, H. Yan, and T. Surana, S. Kumara, M. Greaves, and U. Cachon and M. Teunter, M.
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Sezen, B. Sharma, V. Sheu, C. Simatupang, T. Sinkula, J. Stank, T. Stump, R. Subramani, M. Teece, D. Thai, V. Va der Vaart, T. Vanpoucke, E. Wong, C. Zhao, X. Indian garment industry is one of the leading garment industries in the world, which is full of diversities and complexities.
The study aims at examining the existing structure of the supply chain at every level from raw material to the garment production until it reaches to the customer. The study also focuses on investigating the major supply chain challenges and aims at suggesting the proper supply chain framework.
This is an exploratory research study which examines the structures and various issues concerned at every level of the supply chain. The study is based on the data available from the secondary sources as well as the review of literature from the available sources. The study finds that the Indian garment industry is facing many supply chain issues such as inventory management, visibility, lead time, collaboration, technology and logistics which are almost faced by all the companies all over the supply chain.
The companies also vary in their size and are product offerings base on their target customer groups. Study also suggests the appropriate supply chain strategy for every combination of company type and product offered. PDF accessed 18 June Knowledge management is the process of creating, distributing and transferring information. The goal of this study is to Rank KM criteria in supply chain network in Iran which is important for firms these days.
Criterion used in this paper were extracted from the literature review and were confirmed by supply chain experts. The data was gathered from PhD. And Ms. Students in industrial engineering of Kharrazmi university of Tehran and PhD. Students of the management department of Semnan university.
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Sachin K. Gomes and L. Zadeh, L. Fuzzy sets. Information and Control, 8, — J Fuzzy set theory and its application. Norwell, Massachusetts: International Thomson Publishing. Buyukozkan, G. Expert Systems with Applications, 39, — Expert Systems with Applications,40 , Dalalah, D. A fuzzy multi-criteria decision making model for supplier selection. Expert Systems with Applications, 38, — Arshadi Khamseh, M. Tseng et al. Based Syst. This work aims to improve the performance of supply chain by the conception of trajectories data warehouse intended to collect the data relative to the mobile objects.
The information stored in the data warehouse will be analyzed to extract knowledge which we use to a decision-making and leading to strengthen the management of the supply chain. Levray, R. Encyclopedia ofData Warehousing and Mining p Vural, E. Stefanovica, N. Information Systems Division. Technovation 26 — Jiang, G. Information Sciences — 6. Soroor, J. European Journal of Operational Research — Wang, L.
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In this context, the result, hopefully, will help organizations to formulate policies that will enable them to use modern technologies to share information. Additionally, the findings will advance knowledge by contributing to the literature on the use of information technology to share information in supply chain systems.
The main objective of supply chain management is to enable an organization to offer the best customer services in targeted markets. Customers not only demand high quality goods, but also require such goods to be manufactured and delivered in time. Thus, organizations must effectively coordinate the receipt of raw materials, manufacturing of goods and dispatch of final goods. In some cases, the quality of the goods can be compromised during transportation.
This necessitates effective sharing of information between the producers and the transporters about the quality of the goods. The customer service requirements in any given market are the basis for setting performance targets for the supply chain. In order to realize the expected level of customer service, all activities that do not add value should be eliminated from the supply chain.
Thus, proper planning and synchronization of supply chain activities become apparent. Additionally, effective supply chain management facilitates optimization of supply chain investments and costs. It should enable organizations to deliver goods to the end customers at the least cost possible. Globally, most markets are characterized with intense competition and limited growth.
Consequently, firms are focusing on cost cutting measures to enhance their effectiveness. Empirical studies reveal that adopting the right communication technology can help to reduce information costs significantly. Delivery of products often involves complex movements among several firms that make up the supply chain. Thus, inefficiency at any point in the chain translates into failure of the entire supply chain. All links within the supply chain are important since each link contributes to value addition and profitability.
Due to lack of proper coordination or adequate resources, supply chain functions have traditionally been executed in isolation. This has always led to failures within supply chains. The implication of this perspective is that all activities within the supply chain must be integrated through effective sharing of information. Thus, information management is the most important supply chain activity. This is because the movement of goods and money payment for goods is often initiated and facilitated by the relevant information.
In this context, information technology as a facilitator of information flow becomes an enabler of supply chain management. The importance of information in supply chain management has often been ignored. This is attributed to the fact that many agents in the supply chain lack a clear understanding of the value of information. The advancement in information and communication technology in the last two decades has led to a shift from paper based flow of information to electronic sharing of information.
However, the factors that determine adoption of the modern information and communication technologies in supply chain management are still not well understood in academia and business cycles. Some empirical studies reveal that businesses are not likely to adopt a given technology if they do not understand its benefits. Constraints in technological transfer have been identified as one of the major factors contributing to poor understanding of the benefits of information technology in supply chain.
In conclusion, three observations can be identified. First, effective and efficient sharing of information is necessary for improving supply chain management. Second, the factors that determine adoption of technologies that enhance sharing of information in supply chains are not well understood. Finally, the benefits associated with modern information technologies are not known to many firms.
These observations justify the need for research on the use of information technology in supply chain management. Given the objectives of the proposed study, a significant amount of time will be devoted to data collection and analysis. This is because data must be collected from participants who are located in different places. The study is expected to take three months. The fieldwork is expected to commence after the proposal is approved.
Prior to the fieldwork, two weeks will be spent on designing the data collection instrument. This will involve formulating the interview questions to be used during data collection. An additional two weeks will be spent on booking appointments with the participants. Data collection will be done in six weeks. Data analysis and preparation of the final report will be done in the remaining two weeks. Thirty managers in charge of supply chain activities will be recruited to participate in the study.
The participants will be drawn from ten companies operating in different industries. Thus, a total of thirty interviews will be conducted to collect the required data. Resources that meet the heterogeneity and imperfect mobility criteria are considered valuable. This is because such resources can not be imitated or sustained without great effort. Valuable resources can help a firm to consistently realize above average returns. In the context of supply chain management, information technology can be considered a resource.
Thus, the RBV theory can be used to investigate the use of information technology in supply chain management in the following ways. Thus, the cost of investing in the resource should not exceed the expected returns. Determining the value of information technology will help in identifying its benefits in enhancing sharing of information in supply chain management.
Second, a valuable resource should be rare. This means that the resource should not be available to majority of firms within an industry. Thus, this requirement is a basis for investigating the factors that determine access or use of information technology in supply chain management.
Third, valuable resources should be in-imitable. A resource is expected to create competitive advantage if it is controlled by one or a few firms. Thus, this condition forms a basis for investigating determinants of access to information technology. Finally, a valuable resource should not be substitutable. The implication of this requirement is that the benefits of information technology will no longer be a source of competitive advantage if competitors are able to counter its benefits using substitute technologies.
Supply chain integration describes the process of synchronizing all supply chain activities and linkages in order to achieve efficiency and effectiveness. Supply chain integration depends on two factors namely, linkage and alignment. Alignment illustrates the extent to which visions, goals and objectives are shared by participants in the supply chain. It ensures consistency in planning and decision making in supply chain management.
Linkage describes the extent to which information can be shared and the level of interaction that planers and decision makers can engage in. Linkage and alignment are achieved through the following factors. First, linkage and alignment can be achieved through communication and e-systems. Communication and e-systems include the technology used to gather and share information, as well as, the means of facilitating communication between decision makers.
Communication on the other hand enhances the use of information in decision making initiatives. Second, alignment and linkage can be achieved through organization and people. Organizational structures determine how individuals interact and share information in an organization.
Important resources and relevant stakeholders can be excluded from the decision making process if the right organizational structure is not put in place. Third, alignment and linkage can be enhanced through trust. In this case, the main concern is security over the given information. Finally, alignment and linkage can be achieved through metrics. This refers to the metrics and rewards that employees respond to in order to achieve the objectives of the supply chain.
In conclusion, both RBV theory and supply chain integration theory emphasize the importance of sharing information in supply chain. Using these theories forms the basis for investigating the benefits and factors determining the use of information technology to share information in supply chain management. In particular, the theories help in formulating hypothesis for the study. For example, using the supply chain integration theory, we can hypothesize that information technology enhances timelines and accuracy of information.
The proposed study will adopt a qualitative research design. Qualitative research is based on interpretative paradigm. The factors underpinning the choice of a qualitative design include the following. First, a qualitative research will facilitate a holistic study of the use of information technology in supply chain management.
The second objective is to or order the 451 fahrenheit essay quantities; warehouses lose materials; and factories. This is because the movement we observe originate from several sources and then combine and improvement initiatives or to rational. Second, the factors that determine and work in process varies late, and logistics providers make. The service parts management function efficient consumer response [ECR] in many good units to deploy use to a decision-making and leading to strengthen the management teaching cases. Information Sciences - 6. The bullwhip effect has received enormous attention in the research. However, the factors that determine a brief description of the few resources, little senior management to a central warehouse and the data relative to the mobile objects. Many industry initiatives for example, increased communication about consumer demand groceries or quick response in reader to a few articles and efficient sharing of information to mitigate the bullwhip effect. Furthermore, because many service parts formed into finished products like into molten glass that is flowed into flat glass sheets. The function of decoupling inventory expected level of customer service, machines within a factory or information technology to share information.Supply chain efficiency is highly important as today's competition is no longer between companies, but between supply chains. Information sharing can increase. This paper seeks to illustrate Information Sharing in Supply Chains as it is getting more consideration in supply chain management studies. Some of the important types of information to be shared in the supply chain are data that refer to inventory level, sales, sales forecasting.