FMCG industry is typically the products sold to customers at a low cost and will be completely consumed within 1 year. The nature of this industry is the short product life cycle, low profit margin, high competition and demand fluctuation. This section will present the case studies of P&G, Unilever and Coca-Cola respectively. Forecasting and new product introduction has always been the issues for many FMCG companies, P&G is no exception. To cope with this, P&G conducts a merchandise testing at the pilot stores to determine the customer’s response to new product before the launch. The result is that the forecast accuracy is improved because a demand planner has an additional source data to make a better decision. Moreover, products can be shipped to stores in-time then lost sales is minimal. – Unilever also feels that the competition in FMCG industry has significantly increased. They have to launch the new products on regular basis but the forecasting of new product is difficult. So they create a better classification of new products (base, relaunch, repack, new) using a regression model to identify potential forecast errors for each type of new product. – Coca-Cola doesn’t really have many stock keep units when compared with other companies in the same industry. However, products go to over 2.4 million delivery points through over 430 distribution centers. Managing transportation at this scale is the absolute challenge. In order to streamline the delivery, Coca-Cola implemented a vehicle routing software. The reason is that is the software vendor has a very good relationship with Coca-Cola’s legacy ERP software vendor. Moreover, the vendor has a solid connection with the university who can help to develop the algorithm that fits in with the business’ needs. The result is that transportation planners at each distribution center can use the new tool to reduce travelling time/distance on daily basis.
Lean manufacturing concept has been implemented widely in the automotive industry so the case studies about lean manufacturing is very readily available. Due to the increasing competition in the automobile industry, car manufacturers have to launch a new model to the market more frequently. This section will show you how BMW manages a long term planning, how Ford applies lean concept to the new product development and how Hyundai manages the production planning and control. – BMW uses a 12-year planning horizon and divides it into an annual period. After that, they will make an annual sales forecast for the whole planning horizon. After the demand is obtained, they divide sales into 8 market and then select the appropriate production sites for each market, considering overall capacity constraints and total cost. As you may notice, this kind of a long range planning has to be done strategically. – Ford calls its product development system as “work streams” which include the body development, engine development, prototyping and launch process . The cross-functional team are the experts and their roles are to identify key processes, people, technology necessary for the development of new prototype. Each work stream team is responsible to develop timeline of each process. Detailed plan is usually presented on A3 sized paper. They clearly identifying current issues they are facing with supporting data, drawings and pictures. On weekly basis, they organize a big group meeting of all work stream team to discuss the coordination issues. – Hyundai deploys a centralized planning system covering both production and sales activities across the facilities and functional areas. They develop a 6-month master production plan and a weekly and a daily production schedule for each month in advance. During a short term planning (less than one month), they pay much attention to the coordination between purchasing, production and sales. Providing a long term planning data to its suppliers help to stabilize production of its part makers a lot.
Life cycle of technology products is getting shorter and shorter every day. Unlike FMCG, the launch of a new product in the hi-tech industry requires the investment in research and development quite extensively. Then, a poor planning will result in a massive loss. This section will cover JIT and outsourcing by Apple Inc, Supply Chain Risk Management by Cisco System, Technology Roadmap by Intel, Supply Chain Network Model by HP, Mass Customization by Dell and Quality Management by Sam Sung. Steve Jobs invited the Tim Cook to help to improve Apple’s Supply Chain in 1998. Jobs told Cook that he visited many manufacturing companies in Japan and he would like Cook to implement the JIT system for Apple. Jobs believed that Apple’ supply chain was too complex then both of them reduced the number of product availability and created 4 products segment, reduced on hand inventory and moved the assembling activities to Asia so they could focus on developing the breathtaking products that people wanted to buy. – Cisco Systems would like to be the brand of customer choice so they implement a very comprehensive supply chain risk management program by applying basic risk mitigation strategies, establishing appropriate metrics, monitoring potential supply chain disruptions on 24/7 basis and activate an incident management team when the level of disruption is significant. – Intel ‘s new product development is done by the process called Technology Roadmap. Basically, it’s the shared expectations among Intel, its customers and suppliers for the future product lineup. The first step to prepare the roadmap is to identify the expectations among semiconductor companies and suppliers. Then they identify key technological requirements needed to fulfill the expectations. The final step is to propose the plan to a final meeting to discuss about the feasibility of project. Some concerning parties such as downstream firms may try to alter some aspects of the roadmap. Technology Roadmap allows Intel to share its vision to its ecosystem and to utilize new technology from its suppliers. – HP ‘s case study is pretty unique. They face with a basic question, where to produce, localize and distribute products. Its simple supply chain network model is presented below,
From this example, only 3 possible locations result in 5 different way to design the supply chain. In reality, HP has more production facilities than the example above so there are so many scenarios to work with. How should HP decide which kind of a supply chain network configuration they should take to reduce cost and increase service to customer? The answer is that they use the multi-echelon inventory model to solve the problem. – Dell is one of the classic supply chain case studies of all time. Many industries try to imitate Dell’s success. The key ingredients of Dell’s supply chain are the partnership with suppliers, part modularity, vendor managed inventory program, demand management and mass customization. Also, you can find the simplified process map of Dell’s order-to-cash process as below,
– Sam Sung has proven to be the force to be reckoned with in the hi-tech industry. The secret behind its supply chain success is the use of Six Sigma approach. They studied how General Electric (GE), DuPont and Honeywell implemented six sigma. After that, they have created their own implementation methodology called DMAEV (define, measure, analyze, enable, verify). They use the global level KPI to ensure that each player in the same supply chain is measured the same way. Also, they utilize SCOR Model as the standard process. Any process changes will be reflected through an advance planning system (APS).
The last industry covered here is the general merchandise retailing industry. The critical success factor of this industry is to understand the drivers of consumer demand. Four case studies will be presented, namely, 7-11, Tesco, Walmart, Amazon and Zappos. – 7/11 is another popular case study in supply chain management. The integration of information technology between stores and its distribution centers play the important role. Since the size of 7/11 store is pretty small, it’s crucial that a store manager knows what kind of products should be displayed on shelves to maximize the revenue. This is achieved through the monitoring of sales data every morning. Sales data enables the company to create the right product mix and the new products on regular basis. 7/11 also uses something called combined delivery system aka cross docking. The products are categorized by the temperature (frozen, chilled, room temperature and warm foods). Each truck routes to multiple stores during off-peak time to avoid the traffic congestion and reduce the problems with loading/unloading at stores. – Tesco is one of the prominent retail stores in Europe. Since UK is relatively small when compared with the United States, centralized control of distribution operations and warehouse makes it easier to manage. They use the bigger trucks (with special compartments for multi-temperature products) and make a less frequent delivery to reduce transportation cost. Definitely, they use a computerized systems and electronic data interchange to connect the stores and the central processing system. – Wal-Mart ‘s “Every Day Low Prices” is the strategy mentioned in many textbooks. The idea is to try not to make the promotions that make the demand plunges and surges aka bullwhip effect. Wal-Mart has less than 100 distribution centers in total and each one serves a particular market. To make a decision about new DC location, Walmart uses 2 main factors, namely, the demand in the proposed DC area and the outbound logistics cost from DC to stores. Cost of inbound logistics is not taken into account. There are 3 types of the replenishment process in Wal-Mart supply chain network as below,
In contrary to general belief, Wal-mart doesn’t use cross-docking that often. About 20% of orders are direct-to-store (for example, dog food products). Another 80% of orders are handled by both warehouse and cross dock system. Wal-Mart has one of the largest private fleet in the United States. The delivery is made 50% by common carriers and 50% by private fleet. Private fleet is used to perform the backhauls (picks up cargoes from vendors to replenish DCs + sends returned products to vendors). Short-hauls (less than one working day drive) is also done by the a private fleet. For long-hauls, the common carriers will be used. There are 2 main information system deployed by Wal-Mart. “Retail Link” is the communication system developed in-house to store data, share data and help with the shipment routing assignments. Another system is called “Inforem” for the automation of a replenishment process. Inforem was originally developed by IBM and has been modified extensively by Wal-Mart. Inforem uses various factors such as POS data, current stock level and so on to suggest the order quantity many times a week. Level of collaboration between Wal-Mart and vendors is different from one vendor to the other. Some vendors can participate in VMI program but the level of information sharing is also different. VMI program at Wal-Mart is not 100% on consignment basis. – Amazon has a very grand business strategy to “ offer customers low prices, convenience, and a wide selection of merchandise “. Due to the lack of actual store front, the locations of warehouse facilities are strategically important to the company. Amazon makes a facility locations decision based on the distance to demand areas and tax implications. With 170 million items of physical products in the virtual stores, the back end of order processing and fulfillment is a bit complicated. Anyway, a simplified version of the order-to-cash process are illustrated as below,
Upon receipt of the orders, Amazon assign the orders to an appropriate DC with the lowest outbound logistics cost. In Amazon’s warehouse, there are 5 types of storage areas. Library Prime Storage is the area dedicated for book/magazine. Case Flow Prime Storage is for the products with a broken case and high demand. Pallet Prime Storage is for the products with a full case and high demand. Random Storage is for the smaller items with a moderate demand and Reserve Storage will be used for the low demand/irregular shaped products. Amazon uses an propitiatory warehouse management system to make the putaway decision and order picking decision. After the orders are picked and packed, Amazon ships the orders using common carriers so they can obtain the economy of scale. Orders will arrive at UPS facility near a delivery point and UPS will perform the last mile delivery to customers. Amazon is known to use Sales and Operations Planning (S&OP) to handle the sales forecast. Anyway, this must be S&OP process at product family/category level. To compete with other online retailers, Zappos pays much attention to the way they provide the services to customers. In stead of focusing on the call center productivity, Zappos encourages its staff to spend times over the phone with customers as long as they can so they can fully understand the customer’s requirements. They also upgrade the delivery from 3 days to 1 day delivery in order to exceed customer expectation.
All case study demonstrates that supply chain management is truly the strategic initiatives, not merely a cost cutting technique. Leading companies have a very strong customer focus because almost all of initiatives are something to fill the needs of customers. Relationship management is the unsung hero in supply chain management. It’s the prerequisite to the success of every supply chain. And at the end of the day, it comes down to the quality of supply chain people who analyze, improve and control supply chain operations. – See more at: http://www.supplychainopz.com/2014/04/supply-chain-management-case-study.html#sthash.MrnrGsyY.dpuf
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Examining the response to covid-19 in logistics and supply chain processes: insights from a state-of-the-art literature review and case study analysis.
2.1. systematic literature review, 2.1.1. sample creation, 2.1.2. descriptive analyses, 2.1.3. paper classification.
2.1.5. interrelated aspects, 2.2. case study, 2.2.1. data collection.
2.2.3. analysis and summary, 3. results—systematic literature review, 3.1. descriptive statistics, 3.2. common classification fields, 3.2.1. macro theme, 3.2.2. industrial sector, 3.2.3. data collection method, 3.2.4. research method, 3.2.5. country, 3.3. cross-analyses, 3.3.1. macro theme vs. industrial sector, 3.3.2. research method vs. macro theme, 3.4. interrelated aspects, 4. results—case study, 4.1. company overview, 4.2. pre-covid-19 period, 4.3. covid-19 period, 4.4. post-covid-19 period, 4.5. analysis and summary.
5.1. answer to the research questions, 5.2. scientific and practical implications, 5.3. suggestions for future research directions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.
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Source | No. of Papers | Scimago Ranking |
---|---|---|
Sustainability (Switzerland) | 10 | Q1–Q2 |
International Journal of Logistics Management | 6 | Q1 |
Journal of Global Operations and Strategic Sourcing | 5 | Q2 |
Agricultural Systems | 5 | Q1 |
Benchmarking | 4 | Q1 |
International Journal of Production Research | 3 | Q1 |
Research Method | No. of Papers |
---|---|
ANOVA | 2 |
Contingency analysis and frequency analysis | 1 |
Cronbach’s alpha | 1 |
Descriptive statistics | 8 |
Econometric | 1 |
Hypothesis test | 5 |
Keyword analysis | 1 |
Logistic regression—R software | 1 |
Partial Least Square (PLS) | 1 |
PLS-SEM | 11 |
Random forest regression | 1 |
Regression | 3 |
SEM | 9 |
Descriptive statistics, bias and common method variance test, multiple regression analysis and mediation test | 1 |
Analysis with SPSS and Nvivo | 1 |
Best Worst Method | 1 |
Decision-Making Trial and Evaluation Laboratory (DEMATEL) | 1 |
DEMATEL—Maximum mean de-entropy (MMDE) | 1 |
Fuzzy | 10 |
ISM | 1 |
ISM-Bayesian network (BN) | 1 |
ISM-Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) | 1 |
Multi-Attribute Decision Making (MADM) | 1 |
Multi-Attribute Utility Theory (MAUT) | 1 |
Multi-Criteria Decision Methods (MCDM) | 6 |
SWOT analysis | 2 |
Total Interpretive Structural Modelling (TISM) + MICMAC analysis | 1 |
Case study | 7 |
Framework and case study | 1 |
Product design changes (PDC)—domain modelling | 1 |
Qualitative | 5 |
ABC analysis | 2 |
Poisson pseudo-maximum likelihood (PPML) | 1 |
Method of stochastic factor economic–mathematical analysis | 1 |
Discrete Event Simulation (DES) | 1 |
System dynamics approach | 1 |
Multi-period simulation | 1 |
Industrial Sector | No. of Papers |
---|---|
Logistics | 13 |
Manufacturing | 4 |
Food | 4 |
Automotive | 3 |
Agri-food | 3 |
Industrial Sector | No. of Papers |
---|---|
Logistics | 10 |
Food | 7 |
Agri-food | 6 |
Manufacturing | 6 |
Healthcare | 2 |
Electronic | 2 |
Industrial Sector | No. of Papers |
---|---|
Logistics | 9 |
Food | 3 |
Agri-food | 3 |
Manufacturing | 2 |
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Monferdini, L.; Bottani, E. Examining the Response to COVID-19 in Logistics and Supply Chain Processes: Insights from a State-of-the-Art Literature Review and Case Study Analysis. Appl. Sci. 2024 , 14 , 5317. https://doi.org/10.3390/app14125317
Monferdini L, Bottani E. Examining the Response to COVID-19 in Logistics and Supply Chain Processes: Insights from a State-of-the-Art Literature Review and Case Study Analysis. Applied Sciences . 2024; 14(12):5317. https://doi.org/10.3390/app14125317
Monferdini, Laura, and Eleonora Bottani. 2024. "Examining the Response to COVID-19 in Logistics and Supply Chain Processes: Insights from a State-of-the-Art Literature Review and Case Study Analysis" Applied Sciences 14, no. 12: 5317. https://doi.org/10.3390/app14125317
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In the era of Industry 5.0, characterized by the seamless collaboration between humans and machines, the integration of digital twin technology (DTT) and blockchain technology (BCT) is poised to revolutionize supply chain management. This research explores the impact of DTT and BCT on achieving sustainable and efficient supply chain operations. Digital twins, virtual replicas of physical systems, enable real-time analysis and simulations, enhancing decision-making and operational efficiency. Simultaneously, blockchain technology ensures transparency and security in supply chains by maintaining unchangeable transaction records. This paper delves into the advantages and challenges presented by these technologies, examining real-world case studies across various industries. The study reveals that the combination of DTT and BCT creates a symbiotic relationship, driving continuous monitoring and validation of supply chain processes. This integration aligns with global sustainability goals, emphasizing resource optimization and waste reduction. However, data privacy, scalability, and interoperability remain significant barriers. A comprehensive approach is advocated to overcome these challenges, emphasizing ethical and environmental norms. Furthermore, this research offers insights into the mediating role of sustainable supply chain management (SSCM) practices and dynamic capabilities in the relationship between Industry 5.0 technologies and operational resource utilization (ORU) performance. It highlights the need for a sophisticated strategy in implementing technology adoption initiatives. This study contributes to theoretical advancements in Industry 5.0 by elucidating the complex interactions between DTT, BCT, and SSCM, paving the way for future research. Additionally, it provides valuable policy implications, guiding policymakers to prioritize innovation, transparency, and sustainability in the industrial sector. Integrating DTT and BCT can reshape supply chain dynamics, fostering a future marked by efficiency, innovation, and environmental responsibility.
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Abid, N., Ceci, F., Ahmad, F., & Aftab, J. (2022). Financial development and green innovation, the ultimate solutions to an environmentally sustainable society: Evidence from leading economies. Journal of Cleaner Production, 369 , 133223.
Article Google Scholar
Ahmed, M., Shuai, C., Abbas, K., Rehman, F. U., & Khoso, W. M. (2022). Investigating health impacts of household air pollution on woman’s pregnancy and sterilization: Empirical evidence from Pakistan, India, and Bangladesh. Energy, 247 , 123562.
Akram, M. W., Yang, S., Hafeez, M., Kaium, M. A., Zahan, I., & Salahodjaev, R. (2023). Eco-innovation and environmental entrepreneurship: Steps towards business growth. Environmental Science and Pollution Research, 30 (23), 63427–63434.
Allal-Chérif, O., Guijarro-Garcia, M., & Ulrich, K. (2022). Fostering sustainable growth in aeronautics: Open social innovation, multifunctional team management, and collaborative governance. Technological Forecasting and Social Change, 174 , 121269.
Alzakri, S. (2023). Does financial stability inspire environmental innovation? Empirical insights from China. Journal of Cleaner Production, 416 , 137896.
Ashenafi, B. B., & Dong, Y. (2023). Financial sector development, trade and income inequality: Regional perspectives using evidence from macro and firm-specific data. Journal of Economic Studies, 50 (6), 1260–1280.
Awosusi, A. A., Adebayo, T. S., Kirikkaleli, D., Rjoub, H., & Altuntaş, M. (2023). Evaluating the determinants of load capacity factor in Japan: The impact of economic complexity and trade globalization. In Natural resources forum . Blackwell Publishing Ltd.
Bah, M., Ondoa, H. A., & Kpognon, K. D. (2021). Effects of governance quality on exports in Sub-Saharan Africa. International Economics, 167 , 1–14.
Bahl, M., Kriauciunas, A., & Brush, T. H. (2020). How do ownership type and knowledge transfer influence success of change? A study of transition economy firms. Global Strategy Journal, 10 (4), 861–884.
Banholzer, V. M. (2022). From “Industry 4.0” to “Society 5.0” and “Industry 5.0”: Value-and mission-oriented policies. Technological and Social Innovations–Aspects of Systemic Transformation. IKOM WP, 3 (2), 2022.
Google Scholar
Basu, S., Pereira, V., Sinha, P., Malik, A., & Moovendhan, V. (2022). Esoteric governance mechanism and collective brand equity creation in confederated organizations: Evidence from an emerging economy. Journal of Business Research, 149 , 217–230.
Battisti, E., Alfiero, S., Quaglia, R., & Yahiaoui, D. (2022). Financial performance and global start-ups: The impact of knowledge management practices. Journal of International Management, 28 (4), 100938.
Bertrand, O., Betschinger, M. A., & Brea-Solís, H. (2022). Export barriers for SMEs in emerging countries: A configurational approach. Journal of Business Research, 149 , 412–423.
Bigerna, S., Hagspiel, V., Kort, P. M., & Wen, X. (2023). How damaging are environmental policy targets in terms of welfare? European Journal of Operational Research, 311 (1), 354–372.
Birasnav, M., & Bienstock, J. (2019). Supply chain integration, advanced manufacturing technology, and strategic leadership: An empirical study. Computers & Industrial Engineering, 130 , 142–157.
Botín-Sanabria, D. M., Mihaita, A. S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., & Lozoya-Santos, J. D. J. (2022). Digital twin technology challenges and applications: A comprehensive review. Remote Sensing, 14 (6), 1335.
Bourcet, C. (2020). Empirical determinants of renewable energy deployment: A systematic literature review. Energy Economics, 85 , 104563.
Bramwell, A., Hepburn, N., & Wolfe, D. A. (2012). Growing innovation ecosystems: University-industry knowledge transfer and regional economic development in Canada. Final Report to the Social Sciences and Humanities Research Council of Canada, 62.
Braz, F. A., Fernandez, E. B., & VanHilst, M. (2008). Eliciting security requirements through misuse activities. In 2008 19th international workshop on database and expert systems applications (pp. 328–333). IEEE.
Chatterjee, S., Chaudhuri, R., Grandhi, B., & Galati, A. (2023). Evolution of strategy for global value creation in MNEs: Role of knowledge management, technology adoption, and financial investment. Journal of International Management, 29 (5), 101057.
Chen, Y., Ma, X., Ma, X., Shen, M., & Chen, J. (2023). Does green transformation trigger green premiums? Evidence from Chinese listed manufacturing firms. Journal of Cleaner Production, 407 , 136858.
D’amato, A., Henderson, S., & Florence, S. (2009). Corporate social responsibility and sustainable business. A Guide to Leadership tasks and functions , 102, CCL Press.
De Sousa, J., Disdier, A. C., & Gaigné, C. (2020). Export decision under risk. European Economic Review, 121 , 103342.
Duong, K. D., Huynh, T. N., Van Nguyen, D., & Le, H. T. P. (2022). How innovation and ownership concentration affect the financial sustainability of energy enterprises: Evidence from a transition economy. Heliyon , 8 (9).
Figueira, S., de Oliveira, R. T., Verreynne, M. L., Nguyen, T., Indulska, M., & Tanveer, A. (2023). Entrepreneurs: Gender and gendered institutions’ effects in open innovation. Industrial Marketing Management, 111 , 109–126.
Findlay, C. (2017). Participatory cultures, trust technologies and decentralisation: Innovation opportunities for record-keeping. Archives and Manuscripts, 45 (3), 176–190.
Gigauri, I., & Janjua, L. R. (2023). Digital and sustainable products to achieve sustainable business goals along the path to industry 5.0. In Digitalization, sustainable development, and industry 5.0: An organizational model for twin transitions (pp. 25–40). Emerald Publishing Limited.
Gökalp, E., Gökalp, M. O., Çoban, S., & Eren, P. E. (2018). Analysing opportunities and challenges of integrated blockchain technologies in healthcare. Information Systems: Research, Development, Applications, Education: 11th SIGSAND/PLAIS EuroSymposium 2018, Gdansk, Poland, September 20, 2018, Proceedings 11, 174–183.
Gong, Q., Ying, L., & Dai, J. (2023). Green finance and energy natural resources nexus with economic performance: A novel evidence from China. Resources Policy, 84 , 103765.
Han, J., Raghutla, C., Chittedi, K. R., Tan, Z., & Koondhar, M. A. (2022). How natural resources affect financial development? Fresh evidence from top-10 natural resource abundant countries. Resources Policy, 76 , 102647.
Hemdan, E. E. D., El-Shafai, W., & Sayed, A. (2023). Integrating digital twins with IoT-based blockchain: Concept, architecture, challenges, and future scope. Wireless Personal Communications, 131 (3), 2193–2216.
Hernández, V., Nieto, M. J., & Rodríguez, A. (2022). Home country institutions and exports of firms in transition economies: Does innovation matter? Long Range Planning, 55 (1), 102087.
Hosmer, L. T. (1995). Trust: The connecting link between organizational theory and philosophical ethics. Academy of Management Review, 20 (2), 379–403.
Hult, G. T. M., Hair, J. F., Jr., Proksch, D., Sarstedt, M., Pinkwart, A., & Ringle, C. M. (2018). Addressing endogeneity in international marketing applications of partial least squares structural equation modeling. Journal of International Marketing, 26 (3), 1–21.
Ingendahl, M., Schöne, T., Wänke, M., & Vogel, T. (2021). Fluency in the in-out effect: The role of structural mere exposure effects. Journal of Experimental Social Psychology, 92 , 104079.
Jianqiang, G. U., Umar, M., Soran, S., & Yue, X. G. (2020). Exacerbating effect of energy prices on resource curse: Can research and development be a mitigating factor? Resources Policy, 67 , 101689.
Jiglau, G., Hesselman, M., Dobbins, A., Grossmann, K., Guyet, R., Tirado Herrero, S., & Varo, A. (2024). Energy and the social contract: From “energy consumers” to “people with a right to energy.” Sustainable Development, 32 (1), 1321–1336.
Kelishomi, A. M., & Nisticò, R. (2022). Employment effects of economic sanctions in Iran. World Development, 151 , 105760.
Kirikkaleli, D., Addai, K., & Castanho, R. A. (2023). Energy productivity, financial stability, and environmental degradation in an Eastern European country: evidence from novel Fourier approaches. Heliyon , 9 (7).
Lee, S. M., Bazel-Shoham, O., Tarba, S. Y., & Shoham, A. (2022). The effect of economic freedom on board diversity. Journal of Business Research, 149 , 833–849.
Leng, J., Chen, Z., Huang, Z., Zhu, X., Su, H., Lin, Z., & Zhang, D. (2022). Secure blockchain middleware for decentralized iiot towards Industry 5.0: A review of architecture, enablers, challenges, and directions. Machines, 10 (10), 858.
Li, J., Jiang, Q., Dong, K., & Dong, X. (2022). Does the local electricity price affect labor demand? Evidence from China’s industrial enterprises. Environment, Development and Sustainability , 1–25.
Li, C., & Gong, K. (2023). Does the resource curse hypothesis hold in China? Evaluating the role of trade liberalisation and gross capital formation. Resources Policy, 86 , 103975.
Liang, S., Yu, R., Liu, Z., Wang, W., Wu, L., & Hu, X. (2023). An empirical study on the asset-light operation and corporate performance of China’s tourism listed companies. Heliyon , 9 (2).
Liu, C., Gao, M., Zhu, G., Zhang, C., Zhang, P., Chen, J., & Cai, W. (2021). Data driven eco-efficiency evaluation and optimization in industrial production. Energy, 224 , 120170.
Liu, H., Zhu, Q., Khoso, W. M., & Khoso, A. K. (2023). Spatial pattern and the development of green finance trends in China. Renewable Energy, 211 , 370–378.
Long, Y., Feng, T., Fan, Y., & Liu, L. (2023). Adopting blockchain technology to enhance green supply chain integration: The moderating role of organizational culture. Business Strategy and the Environment, 32 (6), 3326–3343.
Ma, L., Iqbal, N., Bouri, E., & Zhang, Y. (2023). How good is green finance for green innovation? Evidence from the Chinese high-carbon sector. Resources Policy, 85 , 104047.
Maddikunta, P. K. R., Pham, Q. V., Prabadevi, B., Deepa, N., Dev, K., Gadekallu, T. R.,..., & Liyanage, M. (2022). Industry 5.0: A survey on enabling technologies and potential applications. Journal of Industrial Information Integration , 26 , 100257.
Maghrabi, L. A. (2014). The threats of data security over the Cloud as perceived by experts and university students. In 2014 World Symposium on Computer Applications & Research (WSCAR) (pp. 1–6). IEEE.
Magnac, T., & Roux, S. (2021). Heterogeneity and wage inequalities over the life cycle. European Economic Review, 134 , 103715.
Makhdoom, Z. H., Gao, Y., Song, X., Khoso, W. M., & Baloch, Z. A. (2023). Linking environmental corporate social responsibility to firm performance: The role of partnership restructure. Environmental Science and Pollution Research, 30 (16), 48323–48338.
Mathivathanan, D., Govindan, K., & Haq, A. N. (2017). Exploring the impact of dynamic capabilities on sustainable supply chain firm’s performance using grey-analytical hierarchy process. Journal of Cleaner Production, 147 , 637–653.
Mele, G., Capaldo, G., Secundo, G., & Corvello, V. (2024). Revisiting the idea of knowledge-based dynamic capabilities for digital transformation. Journal of Knowledge Management, 28 (2), 532–563.
Milana, C., & Wu, H. X. (2012). Growth, institutions, and entrepreneurial finance in China: A survey. Strategic Change, 21 (3–4), 83–106.
Moslehpour, M., Chau, K. Y., Tu, Y. T., Nguyen, K. L., Barry, M., & Reddy, K. D. (2022). Impact of corporate sustainable practices, government initiative, technology usage, and organizational culture on automobile industry sustainable performance. Environmental Science and Pollution Research, 29 (55), 83907–83920.
Sahin, G., & Sahin, A. (2023). An empirical examination of asymmetry on exchange rate spread using the quantile autoregressive distributed lag (QARDL) Model. Journal of Risk and Financial Management, 16 (1), 38.
Seuring, S., Sarkis, J., Müller, M., & Rao, P. (2008). Sustainability and supply chain management–an introduction to the special issue. Journal of Cleaner Production, 16 (15), 1545–1551.
Sharkawy, M. H. D. (2020). Potential applications of collaborative intelligence technologies in manufacturing: Study of applicability of collaborative intelligence technologies in manufacturing small-and-medium enterprises, collaborative intelligence frameworks, application benefits and adoption barriers. Master’s thesis, ING – School of Industrial and Information Engineering.
Sharma, A., & Kumar Tiwari, M. (2023). Digital twin design and analytics for scaling up electric vehicle battery production using robots. International Journal of Production Research, 61 (24), 8512–8546.
Shaw, D., & Scully, J. (2023). The foundations of influencing policy and practice: How risk science discourse shaped government action during COVID‐19. Risk Analysis . Early Access
Shen, T., Chen, H. H., Zhao, D. H., & Qiao, S. (2022). Examining the impact of environment regulatory and resource endowment on technology innovation efficiency: From the microdata of Chinese renewable energy enterprises. Energy Reports, 8 , 3919–3929.
Singh, G., Rajesh, R., Daultani, Y., & Misra, S. C. (2023). Resilience and sustainability enhancements in food supply chains using digital twin technology: A grey causal modelling (GCM) approach. Computers & Industrial Engineering, 179 , 109172.
Su, C. W., Qin, M., Tao, R., & Umar, M. (2020). Does oil price really matter for the wage arrears in Russia? Energy, 208 , 118350.
Toh, Y., Jamaludin, A., Hung, W. L. D., & Chua, P. M. H. (2014). Ecological leadership: Going beyond system leadership for diffusing school-based innovations in the crucible of change for 21st century learning. The Asia-Pacific Education Researcher, 23 , 835–850.
Tosini, L. (2020). Study applying simulation to improve a real production process in the context of Industry 4.0 (Master’s thesis, Universitat Politècnica de Catalunya).
Turner, C. J., Ma, R., Chen, J., & Oyekan, J. (2021). Human in the Loop: Industry 4.0 technologies and scenarios for worker mediation of automated manufacturing. IEEE Access, 9 , 103950–103966.
Umar, M., Su, C. W., Rizvi, S. K. A., & Lobonţ, O. R. (2021). Driven by fundamentals or exploded by emotions: Detecting bubbles in oil prices. Energy, 231 , 120873.
Vachon, S., & Klassen, R. D. (2007). Supply chain management and environmental technologies: The role of integration. International Journal of Production Research, 45 (2), 401–423.
Varriale, V., Cammarano, A., Michelino, F., & Caputo, M. (2023). Industry 5.0 and triple bottom line approach in supply chain management: The state-of-the-art. Sustainability, 15 (7), 5712.
Verma, A., Bhattacharya, P., Madhani, N., Trivedi, C., Bhushan, B., Tanwar, S.,..., & Sharma, R. (2022). Blockchain for Industry 5.0: Vision, opportunities, key enablers, and future directions. IEEE Access , 10 , 69160-69199.
Wang, B., Zhao, J., Dong, K., & Jiang, Q. (2022). High-quality energy development in China: Comprehensive assessment and its impact on CO2 emissions. Energy Economics, 110 , 106027.
Xu, J., Ng, C. P., Sam, T. H., Vasudevan, A., Tee, P. K., Ng, A. H. H., & Hoo, W. C. (2023). Fiscal and tax policies, access to external financing and green innovation efficiency: An evaluation of Chinese listed firms. Sustainability, 15 (15), 11567.
Yin, X., Wang, S. X., Lu, Y., & Yan, J. (2023). Endogenous information acquisition and disclosure of private information in a duopoly. Economic Modelling, 126 , 106443.
Zhan, Z., Naqvi, B., Rizvi, S. K. A., & Cai, X. (2021). How exchange rate regimes are exacerbating or mitigating the resource curse? Resources Policy, 72 , 102122.
Zhang, Z., Bouri, E., Klein, T., & Jalkh, N. (2022). Geopolitical risk and the returns and volatility of global defense companies: A new race to arms? International Review of Financial Analysis, 83 , 102327.
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This work was supported by the 2023 Major Project on Philosophy and Social Sciences Research in Jiangsu Higher Education Institutions “A Research on the Digital Transformation Path of Jiangsu Manufacturing Enterprises under the Goal of Climbing Global Value Chains” (No. 2023SJZD018) and 2023 High-Level-Talent Research Project funded by Nanjing Vocational College of Information Technology “Research on the Theoretical Mechanism and Implementation Path of Digital Empowerment on Organizational Resilience of Enterprises Embedded in Global Value Chains” (No. YB20230601).
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Zhen, Z., Yao, Y. The Confluence of Digital Twin and Blockchan Technologies in Industry 5.0: Transforming Supply Chain Management for Innovation and Sustainability. J Knowl Econ (2024). https://doi.org/10.1007/s13132-024-02151-0
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Blockchain. While primarily associated with cryptocurrencies, blockchain, the distributed ledger technology, also ranks high on the list of technologies poised to bring improved visibility and transparency to supply chain processes. Because blockchain creates an immutable record of transactions, the technology is well situated to track the ...
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IBM supply chain management set out a bold vision to build its first cognitive supply chain. The aim was to have an agile supply chain that extensively uses data and AI to lower costs, exceed customer expectations, ruthlessly eliminate or automate non-value add work and exponentially improve the experience of supply chain colleagues.
Proceedings of the Joint International Conference: 10th Textile Conference and 4th Conference on Engineering and Entrepreneurship. Conference paper. Information Technology in Supply Chain Management. Case Study. Conference paper. First Online: 10 January 2024. pp 35-44. Cite this conference paper. Download book PDF.
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It shows that case study and survey are the most used methods, followed by literature review, conceptual study and other methods, such as Delphi, DEMATEL and ANFIS. ... This research contributes to the fields of the digital technology and supply chain management. The proposed framework, in particular the two-dimensional adoption levels of ...
A digital supply chain roadmap is a multiyear plan for supply chain technology investment to support business growth. The best roadmaps address the capability, talent and process implications of digital technology on both business and supply chain operating models. Strong collaboration across the end‑to‑end supply chain is key to build and ...
Previous studies distinguished two categories of IT use in supply chain management (SCM): internal and external IT use (Savitskie, 2007; Zhang et al., 2016b). Internal IT use is conceptualized as the implementation of IT throughout manufacturing processes to share information within the firm ( Savitskie, 2007 ; Zhang et al., 2016b ).
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This study attempts to prove the impact of information technology (IT) in supply chain management (SCM). The criteria include the applications of IT to get the high firm performance comprising marketing performance, financial performance, and customer satisfaction. The fuzzy DEMATEL method is applied to show out the interrelationships among all ...
In conclusion, Walmart's integrated supply chain has been a crucial factor in the company's global dominance and sustained competitive advantage. By strategically investing in technology and optimizing its supply chain, Walmart has managed to maintain its position as the world's largest retailer with over $572 billion in revenue in 2022.
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Click on the "View Library" button (arrow 1) in upper right corner of the Account Management screen. In the Library screen you see a list of available supply chain case studies; click " Import " to load a selected case study into your account; give the imported case a Name, and click " My Account " to go back to your Account ...
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Four case studies will be presented, namely, 7-11, Tesco, Walmart, Amazon and Zappos. - 7/11 is another popular case study in supply chain management. The integration of information technology between stores and its distribution centers play the important role. Since the size of 7/11 store is pretty small, it's crucial that a store manager ...
Supply Chain Management Software: Build the foundation, deliver the value As the days of slow, invisible supply chains that "worked behind the scenes" continue to fade in the rearview mirror, companies are improving their demand forecasting, gaining real-time visibility across their networks…
Supply Chain Management Review delivers the best industry content. Subscribe today and get full access to all of Supply Chain Management Review's exclusive content, email newsletters, premium resources and in-depth, comprehensive feature articles written by the industry's top experts on the subjects that matter most to supply chain professionals.
Abstract: The aim of this research study is to look for possible re-search opportunities to applying blockchain technology in supply chain management and logistics. In addition, accom-panying challenges to utilizing blockchain in supply chain management along with possible solutions are also provided. To fulfil the study objective, both ...
This article investigates the impact of the COVID-19 pandemic on logistics and supply chain processes through a two-phase analysis. First, a literature review maps the existing studies, published from 2021 to 2023 (101 papers), offering a view of the multiple challenges faced by supply chains during the pandemic emergency. The literature analysis makes use of descriptive statistics, thematic ...
In the era of Industry 5.0, characterized by the seamless collaboration between humans and machines, the integration of digital twin technology (DTT) and blockchain technology (BCT) is poised to revolutionize supply chain management. This research explores the impact of DTT and BCT on achieving sustainable and efficient supply chain operations. Digital twins, virtual replicas of physical ...
When you don't have eyes on your supply chain management, losses can happen without your knowledge. This is why technological innovations are providing more supply chain visibility improving the overall governance of e-commerce, manufacturing, and retail business.
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