Value Creation through Collaborative Supply Chain: Holistic Performance Enhancement Road Map Value Creation through Collaborative Supply Chain: Holistic Performance Enhancement Road Map (original) (raw)
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B2B supply chain performance enhancement road map using data mining techniques
The 9th International …, 2010
Presently, modern B2B supply chain management (B2B-SCM) equipped with semi-automated data logging systems accumulate large volumes. However, each SC unit in B2B-SC still individually develops their performance. Besides, their linkages of performance attributes between SC units still lack vital information extraction to improve theirs. Therefore, this paper aims to propose an integrated framework between B2B supply chain (B2B-SC) performance evaluation systems and data mining techniques, developing relationship rules of collaborative performance attribute enhancement. The methodology is as follows. Firstly, B2B-SC performance evaluation questionnaires based on two levels able to characterize collaborative relation between two or more partners in their SC were gathered from the case study companies. The data set of relationships between enterprise and its direct customers of the case study companies in France was used for demonstration. Secondly, data cleaning and preparations for rule extraction were performed on the questionnaire database. The significance of attribute was calculated using attribute ranking algorithms by means of information gain based on ranker search. These results were used to choose the crucial attributes from each micro view. Thirdly, web graph analysis was performed on this data to confirm the strong attribute relationship. Next, association rule was deployed to extract performance attribute relationship rules grounded on support and confidence cross validation method. The quality of each recognized rule is tested and, from numerous rules, only those that are statistically very strong and contain vital information are selected. Last but not least, these rules are interpreted by domain experts and studied by domain engineers to build a collaborative performance attribute enhancement road map. Furthermore, the final rule set of extracted rules contains very interesting information relating to SCs and also point out the critical existing SC attribute improvement. Ultimately, companies in this SC are able to use this framework to design and adjust their units to conform with the exact customer needs.
Supply chain performance measurement and improvement system
Journal of Modelling in Management, 2018
Purpose: The purpose of this paper is to adopt a supply chain performance measurement (SCPM) framework as proposed by Dweiri and Khan (2012) to model a novel supply chain performance measurement indexing (SCPMI) system to measure and improve supply chain performance. Design/methodology/approach: The adopted SCPM framework developed by Dweiri and Khan (2012) is used to model a generic SCPMI framework aided by Analytic Hierarchy Process (AHP) method and inputs from industrial experts. To exemplify the applicability and efficiency of the generic SCPMI system, an automobile assembling company from an emerging economy was utilized. This SCMPI system is used to measure, improve and measure postimprovement supply chain performance (SCP) guided by DMAIC (Define, Measure, Analyze, Improve and Control) methodology. Findings: The study's initial measurement results showed an average SCP of the case company over a four month period as 82%. DMAIC methodology was utilized to identify inherent problems and proposed improvements. The post-improvement SCP measurement saw an improvement from an average of 82% to 83.82% over a four month period. Practical Implications: The proposed generic SCPMI framework aided by AHP-DMAIC has been successfully implemented in a case company. After implementation, managers and decision makers saw an improvement in their SCP. The proposed SCPMI system and results can be useful for benchmarking by manufacturing organizations for continuous SCP improvement. Originality: An original SCPMI framework proposed is general in nature and can be applied in any organization.
Embedding Attributes Towards the Supply Chain Performance Measurement
Cleaner Logistics and Supply Chain, 2023
Dependency on the Balanced Scorecard (BSC) and the Supply Chain Operations Reference (SCOR) model is inadequate in the context of sustainability, environment, and other multiple factors along with the changes in the market dynamics. As a result, performance evaluation through a holistic approach in the manufacturing industry is not comprehensive. Therefore, a Supply Chain Performance Measurement (SCPM) is required to assess the supply chain's effectiveness. This research formulates Integrated Supply Chain Performance Measurement (ISCPM) model through the supply chain performance attributes in the outlook of input-process-output considering the BSC and the SCOR model at three decisions levels with an application of quantitative techniques to bring synergic effect to all stakeholder issues. A gap analysis was performed through systematic literature reviews. The integrated supply chain performance measurement model incorporates ten supply chain performance measurement attributes supplier relationship management (SRM), internal supply chain management (ISCM), and customer relationship management (CRM). The model was then tested from the various sectors in the manufacturing industry of Bangladesh, through a simple random sampling. The ISCPM model furnishes stakeholders of the manufacturing supply chain with the appropriate strategies to review and appraise their performance toward fulfillment of the ultimate goals. This model is suggested to be implemented in manufacturing industries to improve their operational performance. The study contributes to academia developing the ISCPM model with ten performance measurement attributes that enrich the literature on SCPM. It also contributes to the industry for practitioners by bringing synergy into the framework and performance measurement attributes which eventually upgrade the prosperity of the manufacturing industry and eventually the society.
Presentation a New Algorithm for Performance Measurement of Supply Chain by Using FMADM Approach
2008
Supply chain management has become such a popular topic in modern business management and researches. It brings the revolutionary philosophy and approach to manage the business with the sustained competitiveness. However, the existing performance measurement theory fails to provide its necessary support in strategy development, decision making and performance improvement. The main goal of this paper is presentation of a new approach to supply chain performance measurement by use of FMADM (Fuzzy Multi Attribute Decision Making) method. For this goal, we extract the performance metrics based-on balanced scorecard (BSC) model. Afterward we present a three-step approach to measure the performance of the supply chain by FMADM method. In the process of supply chain performance measurement, many of our data are qualitative. Since the qualitative data are ambiguous we transform the qualitative terms into quantities terms by using the fuzzy collections. This includes identifying and prioritization the key factors in increasing competitiveness. The main framework of this method is outlined with some suggestions and a simple example Key word: Performance measurement • BSC model food supply chain • FMADM • fuzzy approach
Data Mining: A Tool to Increase Productivity in Supply Chain Management
Data Mining techniques are able to predict the future by analysing the past. Data Mining is able to sift through massive amounts of data and find hidden information and relationships. Data mining has had an important impact in supply chain management, data mining has made mass customisation and personalisation systems easier to implement, has also been used to detect supply chain fraud in e-procurement transactions, reduce the supply chain risk by analysing public data information and improve the financial performance of corporation by optimizing the use of supply chain data maintained in data centres. The article has the objective of introducing main data mining concepts and explains how these have been applied in supply chain management.
Supply Chain Management (SCM) has gained significance as one of the 21 st century manufacturing paradigms for improving organizational competitiveness. Supply chain ensures improved efficiency and effectiveness of not only product transfer, but also information sharing between the complex hierarchies of all the tiers. The literature on SCM that deals with strategies and technologies for effectively managing a supply chain is quite vast. In recent years, organizational performance measurement (PM) and metrics have received much attention from researchers and practitioners. Performance measurement and metrics have an important role to play in setting objectives, evaluating performance, and determining future courses of actions. Apart from the common criteria such as cost and quality, ten other performance measurements are defined, visibility, trust, innovativeness, delivery reliability, flexibility and responsiveness, resource utilization, cost, assets, technological capability, service and time to market, so total twelve criteria and fifty eight subcriteria are used to evaluate the performance in supply chain. So, for evaluating and selecting supplier a multi-attribute decision-making technique, an analytic hierarchy process (AHP), is used to make decision based on the priority of performance measures. This paper describes a decision framework for evaluating and selecting supplier performance in a supply chain. A case study from the automotive industry is used to demonstrate the AHP technique.
Management and Production Engineering Review, 2018
Performance measurement system in supply chain management (SCM) has been receiving increasing attention by business organizations as a way to evaluate efficiency in supply chain activities. Assessing the performance of supply chain uncovers the gap between planning and actual performance as to trace the potential problems thus ascertain necessary areas for improvement. This research aims to investigate the application of performance measurement system in SCM as well as exploring its relationship with organization's performance among Malaysian manufacturing firms. By utilizing the questionnaire method, respondents involved were requested to indicate the extent to which they use a number of 24 selected performance measures that are related to SCM. The results show that the majority of the observed manufacturing firms utilize specific performance measurement tools in evaluating the supply chain performance. The current performance measurement techniques, the Balanced Score Card is adopted by around a quarter of the total responding firms followed by Supply Chain Operations References Model-SCOR, which attracts total users of only a fifth of the total respondents. In particular, performance measures under customer service category recorded the highest number of usage followed by cost-based performance measures and operations management. The results of this investigation also unveil few major points that are important to be highlighted. Firstly, the obtained outcomes of this study bring to light the significant relationships between the utilization of supply chain performance measures under customer service, operations management and organizational performance. In addition, this study discovered a significant correlation between the size of the organization and the extent of use of supply chain performance measures and how these two variables positively correlated. Lastly, the findings also suggested that the performance measures for SCM has been playing a crucial role in enhancing the performance of the organizations and is increasingly operated as the firms grow in size. Based on the brief highlighted points listed above, it is not an exaggeration to say that this research contributes new information to the body of knowledge in performance measurement system in SCM and its associations with organizational performance.
Predictive collaborative performance system in B2B supply chain using neuro-fuzzy
Proceedings of the 9th …, 2010
Recently, contemporary B2B supply chain management (B2B-SCM) has been furnished with semiautomated data record systems to gather large quantities. Notwithstanding, most of companies and academic research groups have also concentrated on the results of the historical performance measurement interpretation and relied on the things, what have already happened. These has been rarely concerned the performance inclination. It has resulted in the lack of well-rounded performance planning improvement in the long term. Moreover, they have focused on the physical operation performance enhancement without concerning the collaborative performance among their partners. On the grounds of the fact that, this paper is to present a Neuro-fuzzy system approach to construct collaborative performance which has forward looking collaborative capabilities and its linguistic rules to make understanding how to put the collaborative performance directions in another time. The methodology is as follows. Firstly, B2B-SC performance evaluation questionnaires, with two levels were able to distinguish collaborative relation between two or more partners in their SC were congregated from the case study chains. The data set of relationships between enterprise and its direct clients of the case study companies in France was used for manifestation. Secondly, data cleaning and preparations before the proposed model construction. The multi attribute decision making, simple additive weighting, was employed to build the collaborative performance scoring model, as well. Thirdly, the pervious results were us e as the learning dataset to make up of the predictive collaborative performance system based on Neuro-fuzzy. Finally, the result deployment for collaborative performance guideline from model was validated by the domain experts in term of its real practical usage efficiency. The developed system enables managers to develop systematic manners to foresee future collaborative performance and recognize latent problems in their collaboration. The prognostic ability of the developed system is comparable with the decision of the manager in their collaboration. The comment on its usages and difficulties in its developed process are also discussed. Furthermore, the final predictive results and rules contain very interesting information relating to SC improvement in long runs.
2021
This study aims to identify effective indicators in the performance measurement of a firm using Balanced Scorecard (BSC) as well as weighting and ranking indicators by employing Fuzzy Analysis Network Process (FANP) and investigation on network mapping and the relationships between balanced scorecards with Fuzzy DEMATEL presenting strategies to improve performance of a firm. To assess the significance of the four perspectives: financial, customer, internal processes and learning and growth, about 28 indicators are identified, and after screening, 13 indicators are located as final BSC indicators. After examining the influencing of the main factors using fuzzy DEMATEL technique, internal processes dimension has the most impact and customer, and learning and growth and financial dimensions respectively are ranked as second to fourth priorities. Also using the Fuzzy ANP technique has examined weighting and ranking of dimension and performance measures indicators that dimension of customers has gained first rank and financial, internal processes and learning and growth are ranked as second to fourth respectively. .