Improve Supply Chain Performance Research Articles

Risk Management for Improving Supply Chain Performance of Sugarcane Agroindustry

The purposes of this paper are to evaluate sugarcane supply chain performance, identify supply chain risks, and define mitigation to improve the performance. Supply chains were modeled through a Supply Chain Operation Reference (SCOR) and Fuzzy-Analytic Hierarchy Process (AHP) to evaluate the performance. This paper modeled fuzzy-House of Risk (HOR) to identify and assess supply chain risk. Expert judgment for supply chain risk assessment was aggregated using an Ordered Weighted Average (OWA) model. The supply chain performance of farmers was found to be average, while that of sugar mill was at below average. Our model succeeded in identifying and assessing 15 risk agents for farmer, seven risk agents for sugar mills, and four risk agents for distributors which had to be mitigated. This work offers meaningful guidance for decision-makers to compose strategies to mitigate risk and enhance performance of sugarcane agroindustry supply chains.

Contract Design in a Supply Chain With Product Recall and Demand Uncertainty

The product recall is becoming a challenging issue in supply chain management, and both suppliers and manufacturers are motivated to exert recall efforts to improve supply chain performance. Considering a supply chain composed of one supplier and one manufacturer with product recalls and demand uncertainty, we investigate the contract design by integrating the revenue sharing contract with three cost sharing policies, namely, fixed-rate cost sharing (Contract F), linear cost sharing (Contract L), and threshold-based cost sharing (Contract T), to coordinate the production quantity and recall efforts. Results show that cost sharing could improve the product recall probability and supply chain profits, but only Contract T can coordinate the supply chain in both production quantity and recall efforts. Moreover, the cost sharing rate in Contract T first decreases and then increases as the recall cost increases. When the recall cost is small (large), Contract T (Contract F) is optimal for the manufacturer. In contrast to our intuition, we find Contract L could overmotivate supply chain members to exert a recall effort that is greater than the first-best when the cost coefficient of recall efforts is large enough. However, demand uncertainty will mitigate the impact of product recalls on motivating recall efforts.

Digitalization for Sustainable Agri-Food Systems: Potential, Status, and Risks for the MENA Region

Digital technologies offer a potential solution to improve sustainability—economic, social, and environmental—of agri-food systems around the globe. While developed countries have led the innovation and adoption of digital agriculture, the potential impact in developing countries—including in the Middle East and North Africa (MENA) region—is massive. This article synthesizes existing evidence to review the potential and current contribution of digital technologies to the agri-food sectors in MENA. Digital agriculture shows promise in addressing the key challenges facing the agri-food sector across MENA countries. Improvements in primary production, supply chain and logistics performance, and optimized use of scarce natural resources (notably agricultural water) could be notable, if digital technologies can be implemented as envisioned. Available evidence shows that adoption of digital agriculture is at early stages, generally led by high-value agricultural production targeting domestic markets in Gulf countries and export markets in Mashreq countries. Economic sustainability appears the strongest force for current adoption, with less focus on social or environmental sustainability. Public policies should not only foster the adoption of digital technologies in MENA but also ensure equity of access, transparency of use, data protections, and labor protections. Policymakers should move beyond traditional, production-centric views to deliver also on social and environmental sustainability.

Multi-party coordination in sustainable supply chain under consumer green awareness

Abstract The rapid growth of the green market in recent years has motivated manufacturing companies to operate carbon abatement schemes for better sustainability. This paper investigates sustainability coordination among three major supply chain parties in the context of consumer green awareness by applying a Stackelberg game model. Instead of considering the manufacturer as the only party to operate carbon management schemes, this paper examines a model in which both the supplier and the manufacturer embark on green investment under make-to-order production. Meanwhile, the retailer considers the influence of green consumers on the demand rate and determines the order quantity for the manufacturer. This paper analyses the sustainability and profitability performance of the supply chain under centralised and decentralised scenarios, and applies the quantity discount and cost-sharing contracts to improve supply chain performance. It is shown that greener markets are more profitable and Pareto improvement can be achieved for all parties under a quantity discount contract. High investment cost hinders the company from achieving a higher emission reduction level. Further, increased consumer green awareness can motivate companies to achieve a higher emission reduction level, but not always lead to improved total carbon emission reductions resulting from the increase in product demand caused by green awareness. It also shows the importance of involving suppliers in green investment, due to their high carbon emission during the component production processes. The findings of this research provide theoretical support for supply chain parties to achieve better coordination in balancing profitability and carbon abatement.

Price and capacity strategies in the express delivery supply chain: advanced payment, penalty or time insurance contracts

In the Business to Consumer (B2C) environment, it is important to alleviate the mismatch between delivery capacity and demand in the express delivery supply chain. To do this, we propose three contracts to improve supply chain performance: the advanced payment contract, penalty contract, and time insurance contract. To assess these contracts, we considered the supply chain of one e-retailer and one express delivery provider. We discussed which contract is better for the supply chain partners when the three contracts can coordinate the supply chain. We found that when its unit cost of delayed orders is lower, the e-retailer will choose the advance payment contract among three contracts. When its unit cost of delayed orders is medium, the e-retailer will opt for the time insurance contract. When its unit cost of delayed orders is high, the e-retailer will not choose the advanced payment contract. In this case, whether the e-retailer chooses the time insurance contract and penalty contract depends on the value of wholesale price.

Trade Credit and Revenue Sharing of Supply Chain with a Risk-Averse Retailer

In this paper, we develop three supply chain game models, i.e., the basic model, the single trade credit model, and the trade credit and revenue sharing collaboration model. Conditional value-at-risk (CVaR) criterion is used as the measure of risk assessment in these models. We analyze the optimal decisions in the centralized and decentralized situations, respectively, and verify that single trade credit cannot coordinate the supply chain. However, the collaboration contract can coordinate the supply chain. Furthermore, this paper explores the influence of risk-aversion factor, trade credit period, revenue sharing coefficient, and other parameters on the optimal decisions and studies the feasible range of Pareto improvement in the collaborative model. In numerical experiments, the results show that the decisions and profits of both the manufacturer and the retailer reply on the degree of the risk aversion, the trade credit period, and the revenue sharing coefficient. The collaborative contract effectively improves supply chain performance and achieves a ‘win-win’ situation for the supply chain members. In addition, we also consider two extensions for our research. One extension shows that the collaborative contract of trade credit and buyback can also coordinate the supply chain in a certain range. The other extension considers the optimal decision of a risk-averse manufacturer with CVaR.

Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation.

Supply chain resilience (SCRes) and performance have become increasingly important in the wake of the recent supply chain disruptions caused by subsequent pandemics and crisis. Besides, the context of digitalization, integration, and globalization of the supply chain has raised an increasing awareness of advanced information processing techniques such as Artificial Intelligence (AI) in building SCRes and improving supply chain performance (SCP). The present study investigates the direct and indirect effects of AI, SCRes, and SCP under a context of dynamism and uncertainty of the supply chain. In doing so, we have conceptualized the use of AI in the supply chain on the organizational information processing theory (OIPT). The developed framework was evaluated using a structural equation modeling (SEM) approach. Survey data was collected from 279 firms representing different sizes, operating in various sectors, and countries. Our findings suggest that while AI has a direct impact on SCP in the short-term, it is recommended to exploit its information processing capabilities to build SCRes for long-lasting SCP. This study is among the first to provide empirical evidence on maximizing the benefits of AI capabilities to generate sustained SCP. The study could be further extended using a longitudinal investigation to explore more facets of the phenomenon.

Supply Chain Management Practices and Supply Chain Performance in the Manufacturing Industries of Bangladesh

Purpose: The paper aims to examine the association between supply chain management practices (SCMP) and supply chain performance (SCP) in the manufacturing industries of Bangladesh. SCMP was classified as strategic supplier partnership (SSP), customer relationship (CR), information sharing level (IS), information quality level (IQ), and postponement (POS). 
 Methods: It is a quantitative research based on a survey questionnaire. Supply chain management practices were measured by items adapted from Li, Nathan, and Rao (2006), while supply chain performance was measured by using key supply chain performance indicators suggested by Ambe (2013). Using convenience sampling technique, data were collected from 203 executives involved in supply chain activities working in different manufacturing organizations in two major cities of Bangladesh (Dhaka and Chittagong). Descriptive statistics, bivariate correlation, and regression analysis were used to analyze the data. 
 Results: Results demonstrated a positive correlation between supply chain management practices and supply chain performance (r=0.67**). However, strategic supplier partnership, customer relationship, and postponement are more strongly related to improving supply chain performance than information sharing level and information quality level. 
 Implications: A significant implication of the study is that manufacturing organizations should develop supply chain management capabilities to improve supply chain performance and they should begin with developing their level of information sharing and level of information quality.
 Limitations: The use of the convenience sampling technique limits the generalizability of the findings. The small sample size (n=203) also warrant caution in interpreting the results.

Enhancement Operations Management in Supply Chain based on Intelligent Support Techniques: A Case study.

The onset of the information technology revolution, economic globalization, and high customer expectations have all contributed to significant developments in businesses supply chain management (SCM). Due to the plethora of data generated throughout the entire supply chain has transformed how SCM analysis is conducted. Also, Retailers, in particular face the challenge of managing SC effectively to meet customer demands while reducing costs. Herein, we suggest an approach to optimize SCM using retail analysis techniques. As one of the most well-known artificial intelligences (AI) approaches and machine learning (ML) applications in SCM are the main goals of this study. By constructing conceptual framework, data analytics, ML, and optimization techniques are integrated to generate Intelligent Support Techniques (ISTs) for analyzing SC data and identify opportunities for improvement. We apply retail analysis techniques such as demand forecasting, inventory management, and assortment planning to optimize supply chain operations. The efficiency of our ISTs verified through employing it in a real-world case study of a large retail chain. Our results show that the suggested ISTs can lead to significant improvements in supply chain performance, including increased sales, reduced inventory costs, and improved customer satisfaction.

Performance Evaluation of Enterprise Supply Chain Management Based on the Discrete Hopfield Neural Network.

In order to make up for the shortcomings of current performance evaluation methods, this paper proposes a new method of enterprise performance evaluation, discusses the construction principle of the evaluation index, and proposes a method of enterprise supply chain overall performance evaluation based on the discrete Hopfield neural network (DHNN) algorithm. Enterprise supply chain (SC) is an important way for enterprises to conduct business with other strategic partners in the market, and the improvement of SC performance is an important way to improve the core competitiveness of enterprises, so it is of great value to study the performance evaluation and index design of the enterprise SC. This method calculates the level value of the overall performance of the SC. This level value is a value between 0 and 1. The higher the value, the higher the overall performance level of the SC. Therefore, when evaluating the overall performance of the SC, appropriate index weights must be selected according to the characteristics of the industry, which helps to objectively evaluate the overall performance of the SC.

Balanced Scorecard approach in deducing supply chain performance

Supply chain management showcases a major role in enhancing organizational efficiency and effectiveness. A proficient supply chain can lead to abridged costs, augmented market shares, improved transactions and sustainable customer relationships. Nevertheless, designing a supply chain alone may be inadequate in bettering the overall performance of an organization which can only be improved through evaluation. For deducing supply chain performance, the Balanced Scorecard (BSC) is an appropriate tool, apart from Supply Chain Operations Reference models (SCOR), Analytic Hierarchy Process (AHP), Data Envelopment Analysis (DEA) and Heuristic techniques based models. Modern firms face inabilities in measuring their real performance against the demanded performance. Real performance is often greater or lesser than the demanded performance which leads to uncertain and delicate supply chains. Accounting for this ambiguity and improving supply chain performance using Balanced Scorecard model is the emphasis of this research effort, by providing an approach to inspect value creation from four standpoints such as financial, customer, internal business process, learning and growth. In this paper, the drag factors which affects the above four standpoints have been explored and removed, to mend the supply chain for better profits.

Integrated production-distribution scheduling with energy considerations for efficient food supply chains

Abstract Quantitative approaches for the integration of production and distribution planning are attracting the interest of scholars and companies in recent years. They can significantly improve supply chain performance and sustainability. In this paper, we propose an optimization model for the integrated scheduling of production and distribution activities, with reference to a real-life company in the food sector. The model takes into consideration changeover times and perishability, and aims to jointly minimize energy, storage and distribution costs. Its applicability is shown through a set of computational experiments, carried out on instances generated from historical data. Two different rescheduling strategies, where the first one reproduces the current behaviour of the firm, are compared. The results show that the current practices of the company can be improved and the model is a valid tool for supporting operational business decisions.

Machine Learning and Statistics: A Study for assessing innovative Demand Forecasting Models

Besides increasing dynamics in market demands, companies strive to avoid short-term changes in their supply chain planning. Therefore, an essential lever to improve supply chain performance is the optimization of the demand forecast. In this regard, artificial intelligence is a widely adopted technique in Industry 4.0 that is associated with high expectations. Against this background, six different forecasting models from statistics and machine learning were evaluated in respect to forecast quality and effort for implementation. The results underline the potential of innovative forecasting models as well as the necessity for an intensive and application-specific evaluation of the advantages and disadvantages of the available approaches.

<i>K</i>-means clustering combined with principal component analysis for material profiling in automotive supply chains

At a time where available data is rapidly increasing in both volume and variety, descriptive data mining (DM) can be an important tool to support meaningful decision-making processes in dynamic supply chain (SC) contexts. Up until now, however, scarce attention has been given to the application of DM techniques in the field of inventory management. Here, we take advantage of descriptive DM to detect and grasp important patterns among several features that coexist in a real-world automotive SC. Principal component analysis (PCA) is employed to analyse and understand the interrelations between ten quantitative and dependent variables in a multi-item/multi-supplier environment. Afterwards, the principal component scores are characterised via a K-means clustering, allowing us to classify the samples into four clusters and to derive different profiles for the multiple inventory items. This work provides evidence that descriptive DM contributes to find interesting feature-patterns, resulting in the identification of important risk profiles that may effectively leverage inventory management for improved SC performance. [Received: 5 April 2019; Revised: 1 December 2019; Revised: 22 January 2020; Accepted: 21 April 2020]

The Effect of Organizational Culture and Supplier Integration to Supply Chain Performance

This study aims to investigate the influence of four types of organizational cultures and supplier integration to supply chain performance. The methodology of this research is an explanatory study by testing two hypotheses. The data’s were collected from a convenience samples of 171 manufacturing companies of total 850 companies in Kepulauan Riau Province being represented by manager in supply chain management divisions. Data’s were collected using questionnaire and technical data analysis using SEM (Structural Equation Model). The result of this study found that: (1) Group Culture and Rational Culture affect Supply Chain Performance positively and significantly but Development Culture and Hierarchical Culture are not significant; (2) Supplier Integration affects Supply Chain Performance positively and significantly. The managerial implication of this research is as a guidance for decision maker in the company or manager in the supply chain management to implement suitable organizational culture and consider the supplier integration as a strategic to improve Supply Chain Performance.

Two-stage pricing strategies of a dual-channel supply chain considering public green preference

In view of the mushroom growth of e-commerce and green production, some enterprises have shifted to provide environment friendly products and made full use of the online sales channel to enhance competitiveness. This paper investigates a dynamic pricing strategy and greening issues for a two-stage dual-channel supply chain containing a manufacturer and a retailer. Furthermore, we discuss pricing and green strategies for members under decentralized and centralized decision scenario. In decentralized decision scenario, two decision strategies are studied and compared. To improve supply chain performance, a cost-sharing contract is proposed. We find the market demand is concave by selling price and the market demand reaches the largest value when selling price equals to reference price. This result shows that the manufacturer should strategically decide the current selling price with respect to the price in the previous period. Sensitivity of consumers to the greening levels, the basic selling price and the greening levels have a positive influence on the performance of the supply chain. Moreover, the products in the centralized decision enjoy higher greening levels than that in decentralized decision scenario. In this study, we contribute to explore the effect of reference price in a dual-channel supply chain management and suggest a two-stage decision strategies to improve supply chain performance with a contract. The limitations and potential future directions are also provided to conclude the study.

The impact of information technology usage on supply chain resilience and performance: An ambidexterous view

Scholars and practitioners have recognized the importance of supply chain (SC) resilience. However, it remains unclear how to build SC resilience and whether SC resilience can enhance firm performance and bring values to customers. By analyzing data collected from 206 manufacturers in China, this study empirically examines how firms implement different information technology (IT) patterns (exploitative versus explorative) with SC partners to achieve supplier and customer resilience from information processing theory, and examines the performance implications of these two dimensions of SC resilience. In addition, this study also investigates how IT ambidexterity reconciles the paradox between IT exploitation and IT exploration in enhancing SC resilience. The results show that both supplier and customer resilience could improve SC performance. To achieve the two aspects of SC resilience, only explorative use of IT with suppliers and customers have significant effects. The results also show that the ambidextrous use of IT on the customer side takes effect. The exploitative and explorative use of IT complement each other to improve customer resilience. The findings of this study contribute to IT and SC resilience literature.

Supply Chain Performance Analysis With Data Envelopment Analysis in TBBM PT. Pertamina Boyolali

PT. PERTAMINA TBBM Boyolali is a supplier of fuel oil in the form of premium, pertamax and diesel. The company should distribute fuel products using tank cars with operating areas covering Boyolali, Surakarta, Karanganyar, Sukoharjo, Sragen, Klaten, Wonogiri, Ngawi, Pacitan, Magetan, Ungaran, Semarang, Salatiga, Purwodadi, and Blora. An efficient supply chain is needed to provide the right products and services, with the specifications needed, in the right place and to the right customers. This article aims to find out and analyze the efficiency that occurs at operational TBBM Pertamina Boyolali and to find out the variables that most influence supply chain performance to be analyzed and improved so that improvements in supply chain performance can be more focus and optimal. The Decision-Making Units (DMUs) stated in this article are the period of supply chain activities from January 2018 to November 2018 at TBBM Pertamina Boyolali, the number of DMU is 11 DMUs. Supply Chain Operation Reference (SCOR) method with responsiveness, flexibility, and reliability attributes is used to measure Supply chain performance. To analyze supply chains efficiency, this article applies input-oriented DEA CCR (Charnes, Cooper, and Rhodes) model which considers linear relationships in its input and output. Data Envelopment Analysis (DEA) is a strong tool for measuring the efficiency of the DMUs and does not need to normalize indicator values that have different dimensions. The software used for processing data in this article is Banxia Frontier Analyst 4.2. This article provides suggestions for improving cash-to-cash cycle time, lead time, and flexibility for more efficient fuel distribution.

MULTIGROUP ANALYSIS IN SUPPLY CHAIN PERFORMANCE

This study aims to examine differences in private and government third-party logistics companies in Indonesia in terms of improving supply chain performance. In this research, supply chain performance testing is influenced by collaboration, radical innovation, and incremental innovation. The sample used is the third-party logistics industry in West Java and DKI Jakarta, totaling 100, which is divided into private third-party logistic companies and government-owned third-party logistics companies. The results showed that there are differences in the effects of collaboration. There is supply chain performance where there are differences in the influence of collaboration and radical innovation on supply chain performance between private companies and government. There is no difference in the influence of collaboration and incremental innovation on supply chain performance between private companies and the government. The findings of this study indicate that radical and incremental innovation acts as a partial mediation on the effect of collaboration on supply chain performance in private and government companies.

Improvement of Supply Chain Performance on PT Surya Toto Indonesia Tbk

Improvement of Supply Chain Performance on PT Surya Toto Indonesia Tbk