2,808 research outputs found

    Supply chain contracting coordination for fresh products with fresh-keeping effort

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    Purpose โ€“ Fresh product loss rates in supply chain operations are particularly high due to the nature of perishable products. This paper aims to maximize profit through the contract between retailer and supplier. The optimized prices for the retailer and the supplier, taking the fresh-keeping effort into consideration, are derived. Design/methodology/approach โ€“ To address this issue, we consider a two-echelon supply chain consisting of a retailer and a supplier (i.e., wholesaler) for two scenarios: centralized and decentralized decision-making. We start from investigating the optimal decision in the centralized supply chain and then comparing the results with those of the decentralized decision. Meanwhile, a fresh-keeping cost-sharing contract and a fresh-keeping cost- and revenue-sharing contract are designed. Numerical examples are provided, and managerial insights are discussed at end. Findings โ€“ The results show that (a) the centralized decision is more profitable than the decentralized decision; (b) a fresh product supply chain can only be coordinated through a fresh-keeping cost- and revenue-sharing contract; (c) the optimal retail price, wholesale price and fresh-keeping effort can all be achieved; (d) the profit of a fresh product supply chain is positively related to consumersโ€™ sensitivity to freshness and negatively correlated with their sensitivity to price. Originality/value โ€“ Few studies have considered fresh-keeping effort as a decision variable in the modelling of supply chain. In this paper, a mathematical model for the fresh-keeping effort and for price decisions in a supply chain is developed. In particular, fresh-keeping cost sharing contract and revenue-sharing contract are examined simultaneously in the study of the supply chain coordination problem

    Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software

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    Recent years have seen great successes of revenue management, notably in the airline, hotel, and car rental business. Currently, an increasing number of industries, including manufacturers and retailers, are exploring ways to adopt similar concepts. Software companies are taking an active role in promoting the broadening range of applications. Also technological advances, including smart shelves and radio frequency identification (RFID), are removing many of the barriers to extended revenue management. The rapid developments in Supply Chain Planning and Revenue Management software solutions, scientific models, and industry applications have created a complex picture, which appears not yet to be well understood. It is not evident which scientific models fit which industry applications and which aspects are still missing. The relation between available software solutions and applications as well as scientific models appears equally unclear. The goal of this paper is to help overcome this confusion. To this end, we structure and review three dimensions, namely applications, models, and software. Subsequently, we relate these dimensions to each other and highlight commonalities and discrepancies. This comparison also provides a basis for identifying future research needs.Manufacturing;Revenue Management;Software;Advanced Planning Systems;Demand Fulfillment

    Evaluating Food Commodity Procurement Strategies

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    We use a case study approach to determine the primary factors affecting food manufacturers' commodity procurement decisions, as well as to examine the strategic nature of commodity procurement departments. The research fills a gap in both the commodity and procurement literature. A large literature exists on commodity marketing; however, very little exists on the topic of commodity procurement. Existing procurement literature tends to focus on non-commodity products rather than commodity products. The results suggest a model for the strategic role of commodity procurement departments within food manufacturers. The initial procurement strategy must be supply maintenance, which once accomplished, allows the commodity procurement department to progress to a profit-focused strategy, which is generally cost-based. Finally, the role of the commodity procurement department can expand by offering additional services to customers, such as designing promotional programs.Marketing,

    INTEGRATING AND ASSESSING EXISTING AGRIBUSINESS COURSEWORK INTO A NEW UNDERGRADUATE INTERNATIONAL AGRIBUSINESS MANAGEMENT CONCENTRATION

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    The purpose of this paper is to use Cal Poly's example of the design and assessment of a new agribusiness concentration as a means to develop a process by which subsequent change can be managed within the context of coordinating change with the ongoing curriculum and employment needs of a department's students.Teaching, Agribusiness, International, Assessment, Teaching/Communication/Extension/Profession, A100, A220, Q130, Q170,

    Optimization strategies for the integrated management of perishable supply chains: A literature review

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    Purpose: The main purpose of this article is to systematically review the papers published in the period 2005-2020 about the integration of production, inventory and distribution activities in perishable supply chains. Design/methodology/approach: The proposed research methodology is based on several steps. First, database and keywords are selected, with the aim to search and collect the main papers, dealing with the integration of production, inventory, distribution activities in perishable supply chains. Then, a bibliometric analysis is carried out, to detect: the main publishing sources, the chronological distribution, the most used keywords, the featured authors, about the selected papers. A five-dimension classification framework is proposed to carry out a content analysis, where the papers of the literature review are classified and discussed, according to: supply chain structure, objective, perishability type, solution approach, approach validation. Findings: Interest in the application of optimization models for integrated decision-making along perishable supply chains is strongly growing. Integrating multiple stages of the supply chain into a single framework is complex, especially when referring to perishable products. The vast majority of the problems addressed are then NP-Hard. Only a limited quantity of the selected papers aims to solve real-life case studies. There is a need for further research, which is capable of modeling and quantitatively improving existing supply chains. The potentials of Industry 4.0 are currently little explored. Originality/value: Based on the analysis of the papers published, this article outlines the current state of the art on the optimization strategies for the integrated management of perishable supply chains, which are very complex to be managed. Research trends and gaps are discussed, future challenges are presentedPeer Reviewe

    ํŒ๋งค์ด‰์ง„์„ ๋„์ž…ํ•œ ์ˆ˜์š” ๋ถˆํ™•์‹ค์„ฑ ์žฌ๊ณ ๊ด€๋ฆฌ ๋ชจํ˜•

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์‚ฐ์—…๊ณตํ•™๊ณผ, 2020. 8. ๋ฌธ์ผ๊ฒฝ.As the globalization of markets accelerates competition among companies, sales promotion, which refers to short-term incentives promoting sales of products or services, plays a prominent role. Although there are various types of sales promotions, such as price reduction, buy-x-get-y-free, and trade-in program, the common purpose is to induce the purchase of customers by offering benefits. This successful strategy has caught the attention of researchers, including operations management and supply chain management. Thus, various studies have been conducted to examine strategies for ongoing operations and to demonstrate the effects of the sales promotion, which are based on the strategic level. However, research at the tactical or operational level has been conducted insufficiently. This dissertation examines the inventory models considering (i) markdown sale, (ii) buy one get one free (BOGO), and (iii) trade-in program. First, the newsvendor model is considered. By introducing the decision variable, which represents the start time of markdown sale, the retailer can obtain the optimal combination of the start time of a markdown sale and an order quantity. Under certain conditions in a decentralized system, however, the start time of a markdown sale where the retailer obtains the highest profit is the least profitable for the manufacturer. To avoid irrational ordering behavior by a retailer against a manufacturer, a revenue-sharing contract is proposed. Second, the mobile application, ``My Own Refrigerator'', is considered in the inventory model. It enables customers to store BOGO products in their virtual storage for later use. That is, customers can drop by the store to pick up the extra freebies in the future. The promotion involves a high degree of uncertainty regarding the revisiting date because customers who buy the product do not need to take both products on the day of purchase. To deal with this uncertainty, we propose a robust multiperiod inventory model by addressing the approximation of a multistage stochastic optimization model. Third, the trade-in program is considered. It is one of the sales promotions that companies collect used old-generation products from customers and provide them with new-generation products at a discount price. It also helps to acquire the additional products which are required for the refurbishment service. A multiperiod stochastic inventory model based on the closed-loop supply chain system is proposed by incorporating the trade-in program and refurbishment service simultaneously. The stochastic optimization model is approximated to the robust counterpart, which features a deterministic second-order cone program.์‹œ์žฅ์˜ ์„ธ๊ณ„ํ™”์— ๋”ฐ๋ฅธ ๊ธฐ์—… ๊ฐ„์˜ ๊ฒฝ์Ÿ์ด ๊ฐ€์†ํ™”๋จ์— ๋”ฐ๋ผ, ๋‹จ๊ธฐ ์ธ์„ผํ‹ฐ๋ธŒ๋ฅผ ํ†ตํ•ด ๊ณ ๊ฐ์˜ ์ œํ’ˆ ๋˜๋Š” ์„œ๋น„์Šค ๊ตฌ๋งค๋ฅผ ์œ ๋„ํ•˜๋Š” ํŒ๋งค์ด‰์ง„์˜ ์—ญํ• ์ด ์ค‘์š”ํ•ด์กŒ๋‹ค. ๊ฐ€๊ฒฉ ์ธํ•˜, ํ–‰์‚ฌ์ƒํ’ˆ ์ฆ์ •, ํŠธ๋ ˆ์ด๋“œ์ธํ”„๋กœ๊ทธ๋žจ๊ณผ ๊ฐ™์€ ๋‹ค์–‘ํ•œ ์œ ํ˜•์˜ ํŒ๋งค์ด‰์ง„ ์ „๋žต์ด ์กด์žฌํ•˜์ง€๋งŒ, ๊ณตํ†ต๋œ ์ฃผ์š” ๋ชฉ์ ์€ ๊ธฐ์—…์ด ๊ณ ๊ฐ์—๊ฒŒ ํ˜œํƒ์„ ์ œ๊ณตํ•˜์—ฌ ๊ณ ๊ฐ์˜ ์ˆ˜์š”๋ฅผ ์ฆ๋Œ€์‹œํ‚ค๋Š” ๊ฒƒ์ด๋‹ค. ํŒ๋งค์ด‰์ง„์˜ ์„ฑ๊ณต์ ์ธ ์ „๋žต์€ ๊ฒฝ์˜๊ณผํ•™ ๋˜๋Š” ๊ณต๊ธ‰๋ง๊ด€๋ฆฌ ๋ถ„์•ผ๋ฅผ ํฌํ•จํ•œ ๊ด€๋ จ ํ•™๊ณ„์˜ ๊ด€์‹ฌ์„ ์ด๋Œ์—ˆ๋‹ค. ์ง€์†์ ์ธ ์šด์˜์„ ์œ„ํ•œ ์ „๋žต์„ ๊ฒ€ํ† ํ•˜๊ณ  ์ „๋žต์  ์ˆ˜์ค€ ๊ณ„ํš์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” ํŒ๋งค ์ด‰์ง„์˜ ํšจ๊ณผ๋ฅผ ์ž…์ฆํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ˆ˜ํ–‰๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์šด์˜ ์ˆ˜์ค€์˜ ์†Œ๋งค์—…์ฒด ์ž…์žฅ์—์„œ์˜ ์—ฐ๊ตฌ๋Š” ๋ฏธํกํ•œ ์‹ค์ •์ด๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” (i) ๋งˆํฌ ๋‹ค์šด (ii) buy one get one free (BOGO), ๋ฐ (iii) ํŠธ๋ ˆ์ด๋“œ์ธํ”„๋กœ๊ทธ๋žจ์„ ๊ณ ๋ คํ•œ ์žฌ๊ณ ๊ด€๋ฆฌ๋ชจํ˜•์„ ๋‹ค๋ฃฌ๋‹ค. ๋จผ์ €, ์‹ ๋ฌธ๊ฐ€ํŒ์› ๋ชจํ˜•์— ๋งˆํฌ ๋‹ค์šด ์‹œ์ž‘ ์‹œ์ ์„ ๋‚˜ํƒ€๋‚ด๋Š” ๊ฒฐ์ • ๋ณ€์ˆ˜๋ฅผ ๋„์ž…ํ•˜์—ฌ ์ตœ์ ์˜ ๋งˆํฌ ๋‹ค์šด ์‹œ์ž‘ ์‹œ์ ๊ณผ ์ฃผ๋ฌธ๋Ÿ‰์˜ ์กฐํ•ฉ์„ ์ œ๊ณตํ•˜๋Š” ๋ชจํ˜•์„ ์ œ์•ˆํ•œ๋‹ค. ๋ถ„์‚ฐ ์‹œ์Šคํ…œ์˜ ํŠน์ • ์กฐ๊ฑด์—์„œ๋Š” ์†Œ๋งค์—…์ž๊ฐ€ ๊ฐ€์žฅ ๋†’์€ ์ด์ต์„ ์–ป๋Š” ์‹œ์ ์ด ์ œ์กฐ์—…์ž์—๊ฒŒ ๋‚ฎ์€ ์ˆ˜์ต์„ฑ์„ ์•ผ๊ธฐํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ์ œ์กฐ์—…์ž์— ๋Œ€ํ•œ ์†Œ๋งค์—…์ž์˜ ๋น„ํ•ฉ๋ฆฌ์  ์ฃผ๋ฌธ์„ ๋ง‰๊ธฐ ์œ„ํ•œ ์ด์ต๋ถ„๋ฐฐ๊ณ„์•ฝ์„ ์ œ์•ˆํ•œ๋‹ค. ์ด์ต๋ถ„๋ฐฐ๊ณ„์•ฝ์„ ํ†ตํ•œ ์ค‘์•™์ง‘๊ถŒํ™” ์‹œ์Šคํ…œ์€ ๋ถ„์‚ฐ ์‹œ์Šคํ…œ์—์„œ ์–ป์€ ์ด์ต์— ๋น„ํ•ด ์†Œ๋งค์—…์ž์™€ ์ œ์กฐ์—…์ž์˜ ์ด์ต์„ ํ–ฅ์ƒ์‹œํ‚ด์„ ์ˆ˜์น˜์‹คํ—˜์„ ํ†ตํ•ด ํ™•์ธํ•˜์˜€๋‹ค. ๋‘˜์งธ, ๋ชจ๋ฐ”์ผ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜ ``๋‚˜๋งŒ์˜ ๋ƒ‰์žฅ๊ณ ''๋ฅผ ๊ณ ๋ คํ•œ ์žฌ๊ณ ๋ชจํ˜•์„ ๊ณ ๋ คํ•œ๋‹ค. ์ด ์•ฑ์„ ํ†ตํ•ด BOGO ํ–‰์‚ฌ์ œํ’ˆ์„ ๊ตฌ๋งคํ•œ ๊ณ ๊ฐ์€ ์ฆ์ •ํ’ˆ์„ ๊ตฌ๋งค ๋‹น์ผ ๋‚  ๊ฐ€์ ธ๊ฐ€์ง€ ์•Š๊ณ  ๋ฏธ๋ž˜์— ์žฌ๋ฐฉ๋ฌธํ•˜์—ฌ ์ˆ˜๋ นํ•  ์ˆ˜ ์žˆ๋Š” ํ˜œํƒ์„ ๋ฐ›๋Š”๋‹ค. ํ•˜์ง€๋งŒ ์†Œ๋งค์—…์ž ์ž…์žฅ์—์„œ๋Š” ๊ณ ๊ฐ์ด ์ฆ์ •ํ’ˆ์„ ์–ธ์ œ ์ˆ˜๋ นํ•ด ๊ฐˆ ์ง€์— ๋Œ€ํ•œ ๋ถˆํ™•์‹ค์„ฑ์ด ์กด์žฌํ•˜๋ฉฐ ์ด๋Š” ๊ธฐ์กด์˜ ์žฌ๊ณ ๊ด€๋ฆฌ ์šด์˜๋ฐฉ์‹์—๋Š” ํ•œ๊ณ„์ ์ด ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ณ ๊ฐ์˜ ์žฌ๋ฐฉ๋ฌธ์— ๋Œ€ํ•œ ๋ถˆํ™•์‹ค์„ฑ์„ ๊ณ ๋ คํ•œ ๋ณต์ˆ˜๊ธฐ๊ฐ„ ์ถ”๊ณ„๊ณ„ํš ์žฌ๊ณ ๋ชจํ˜•์„ ์ˆ˜๋ฆฝํ•˜๋ฉฐ ์ด๋ฅผ ํšจ์œจ์ ์œผ๋กœ ๊ณ„์‚ฐํ•˜๊ธฐ ์œ„ํ•œ ๊ฐ•๊ฑด์ตœ์ ํ™” ๋ชจํ˜•์œผ๋กœ ๊ทผ์‚ฌํ™”ํ•˜์˜€๋‹ค. ์…‹์งธ, ๋ฆฌํผ์„œ๋น„์Šค์™€ ํŠธ๋ ˆ์ด๋“œ์ธํ”„๋กœ๊ทธ๋žจ์„ ๊ณ ๋ คํ•œ ํํšŒ๋กœ ๊ณต๊ธ‰๋ง ์‹œ์Šคํ…œ ๊ธฐ๋ฐ˜์˜ ๋ณต์ˆ˜๊ธฐ๊ฐ„ ์žฌ๊ณ ๊ด€๋ฆฌ๋ชจํ˜•์„ ์ œ์•ˆํ•œ๋‹ค. ์‹ ์„ธ๋Œ€ ์ œํ’ˆ, ๋ฆฌํผ์„œ๋น„์Šค ๋ฐ ํŠธ๋ ˆ์ด๋“œ์ธํ”„๋กœ๊ทธ๋žจ์— ๋Œ€ํ•œ ์„ธ ๊ฐ€์ง€ ์œ ํ˜•์˜ ๋ถˆํ™•์‹คํ•œ ์ˆ˜์š”์— ๋Œ€ํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ฐ˜์˜ํ•จ์— ๋”ฐ๋ผ ๋ณต์ˆ˜๊ธฐ๊ฐ„ ์ถ”๊ณ„๊ณ„ํš ์žฌ๊ณ ๋ชจํ˜•์ด ์ˆ˜๋ฆฝ๋œ๋‹ค. ๋ณต์ˆ˜๊ธฐ๊ฐ„ ์ถ”๊ณ„๊ณ„ํš ์žฌ๊ณ ๋ชจํ˜•์˜ ๊ณ„์‚ฐ์ด ์–ด๋ ต๋‹ค๋Š” ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ ์ž ๊ฐ•๊ฑด์ตœ์ ํ™” ๋ชจํ˜•์œผ๋กœ ๊ทผ์‚ฌํ™”ํ•˜์˜€๋‹ค.Chapter 1 Introduction 1 1.1 Sales promotion 1 1.2 Inventory management 3 1.3 Research motivations 6 1.4 Research contents and contributions 8 1.5 Outline of the dissertation 10 Chapter 2 Optimal Start Time of a Markdown Sale Under a Two-Echelon Inventory System 11 2.1 Introduction and literature review 11 2.2 Problem description 17 2.3 Analysis of the decentralized system 21 2.3.1 Newsvendor model for a retailer 21 2.3.2 Solution procedure for an optimal combination of the start time of the markdown sale and the order quantity 25 2.3.3 Profi t function of a manufacturer 25 2.3.4 Numerical experiments of the decentralized system 27 2.4 Analysis of a centralized system 35 2.4.1 Revenue-sharing contract 35 2.4.2 Numerical experiments of the centralized system 38 2.5 Summary 40 2.5.1 Managerial insights 41 Chapter 3 Robust Multiperiod Inventory Model with a New Type of Buy One Get One Promotion: "My Own Refrigerator" 43 3.1 Introduction and literature review 43 3.2 Problem description 51 3.2.1 Demand modeling 52 3.2.2 Sequences of the ordering decision 54 3.3 Mathematical formulation of the IMMOR 56 3.3.1 Mathematical formulation of the IMMOR under the deterministic demand 58 3.3.2 Mathematical formulation of the IMMOR under the stochastic demand 58 3.3.3 Distributionally robust optimization approach for the IMMOR 60 3.4 Computational experiments 76 3.4.1 Experiment 1: tractability of the RIMMOR 77 3.4.2 Experiment 2: robustness of the RIMMOR 78 3.4.3 Experiment 3: e ect of duration of the expiry date under the different customers' revisiting propensities 78 3.5 Summary 83 3.5.1 Managerial insights 83 Chapter 4 Robust Multiperiod Inventory Model Considering Refurbishment Service and Trade-in Program 85 4.1 Introduction 85 4.2 Literature review 91 4.2.1 Effects of the trade-in program and strategic-level decisions for the trade-in program 91 4.2.2 Inventory or lot-sizing model in a closed-loop supply chain system 94 4.2.3 Distinctive features of this research 97 4.3 Problem description 100 4.3.1 Demand modeling 103 4.3.2 Decision of the inventory manager 105 4.4 Mathematical formulation 108 4.4.1 Mathematical formulation of the IMRSTIP under the deterministic demand model 108 4.4.2 Mathematical formulation of the IMRSTIP under the stochastic demand model 110 4.4.3 Distributionally robust optimization approach for the IMRSTIP 111 4.5 Computational experiments 125 4.5.1 Demand process 125 4.5.2 Experiment 1: tractability of the RIMRSTIP 128 4.5.3 Experiment 2: approximation error from the expected value given perfect information 129 4.5.4 Experiment 3: protection against realized uncertain factors 130 4.5.5 Experiment 4: di erences between modeling demands from VARMA and ARMA 131 4.5.6 Experiments 5 and 6: comparisons of backlogged refurbishment service with or without trade-in program 133 4.6 Summary 136 Chapter 5 Conclusions 138 5.1 Summary 138 5.2 Future research 140 Bibliography 142 Chapter A 160 A.1 160 A.2 163 A.3 163 A.4 164 A.5 165 A.6 166 Chapter B 168 B.1 168 B.2 171 B.3 172 Chapter C 174 C.1 174 C.2 174 ๊ตญ๋ฌธ์ดˆ๋ก 179Docto

    Minimizing food waste in grocery store operations: literature review and research agenda

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    Research on grocery waste in food retailing has recently attracted particular interest. Investigations in this area are relevant to address the problems of wasted resources and ethical concerns, as well as economic aspects from the retailerโ€™s perspective. Reasons for food waste in retail are already well-studied empirically, and based on this, proposals for reduction are discussed. However, comprehensive approaches for preventing food waste in store operations using analytics and modeling methods are scarce. No work has yet systematized related research in this domain. As a result, there is neither any up-to-date literature review nor any agenda for future research. We contribute with the first structured literature review of analytics and modeling methods dealing with food waste prevention in retail store operations. This work identifies cross-cutting store-related planning areas to mitigate food waste, namely (1) assortment and shelf space planning, (2) replenishment policies, and (3) dynamic pricing policies. We introduce a common classification scheme of literature with regard to the depth of food waste integration and the characteristics of these planning problems. This builds our foundation to review analytics and modeling approaches. Current literature considers food waste mainly as a side effect in costing and often ignores product age dependent demand by customers. Furthermore, approaches are not integrated across planning areas. Future lines of research point to the most promising open questions in this field

    Competitive Multi-period Pricing with Fixed Inventories

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    This paper studies the problem of multi-period pricing for perishable products in a competitive (oligopolistic) market. We study non cooperative Nash equilibrium policies for sellers. At the beginning of the time horizon, the total inventories are given and additional production is not an available option. The analysis for periodic production-review models, where production decisions can be made at the end of each period at some production cost after incurring holding or backorder costs, does not extend to this model. Using results from game theory and variational inequalities we study the existence and uniqueness of equilibrium policies. We also study convergence results for an algorithm that computes the equilibrium policies. The model in this paper can be used in a number of application areas including the airline, service and retail industries. We illustrate our results through some numerical examples.Singapore-MIT Alliance (SMA
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