A Study on the Effect of New Technologies on Supply Chain Coordination
Bibliographic record
Abstract
In this globalized economy, the fierce competition in the market, added to the increasingly exigences from customers demanding products with more added value and lower prices, force organizations to be always at the vanguard to maintain their positioning in the market. One critical ingredient for maintaining the competitive advantage is the acquisition and implementation of new technologies for achieving process and product enhancement. This is specially the case for high tech industries in sectors like aerospace, pharmaceutic and telecommunication, to name but a few. But investment in new technologies is a challenging decision due to their complexity for implementation and the cost involved. Therefore, it is of utmost importance to understand the effect of new technologies on the performance of the acquiring company and on its supply chain. Although the existence of an ample number of empirical studies in the current literature describing the relation between supply chain (SC) operation and new technologies acquisition, analytical research on this matter is quite scarce. In this thesis, our objective is to model and analyze the effect of new technologies on the SC members performance. We propose two main directions of research: (1) impact of technology transfer among SC members; and (2) impact of technology investment in the SC. In the first direction, we consider that an existing technology in the supply chain is transferred from its owner to a different member in the system. In the second direction, we assume that the new technology is independently acquired by an organization in the supply chain, i.e. obtained from a third-party or through internal R&D. Furthermore, we analyze the impact of new technologies on the performance of different system structures. On the first stream of research, we discuss the effect of technology transfer on a one-supplier one-manufacturer supply chain system involving technology transfer and market sharing. We consider the technology transfer decision to be made by the manufacturer, the key technology owner, as the decision affects its market share. It is proposed three models for analyzing the system performance: (i) a supply chain without technology transfer, (ii) a supply chain with technology transfer but without supplier’s market sharing, and (iii) a supply chain with technology transfer and supplier’s market sharing. Findings show that the optimal profit of the manufacturer in a supply chain with technology transfer and market sharing is typically greater than those without technology transfer or market sharing. The analysis also provides the conditions for the manufacturer to enhance technology transfer when the supplier’s market is open to the final products. On the second stream of research, we explore the impact of technology investment on supply chain coordination. We first investigate the optimal pricing and technology investment decisions in a system consisting of one manufacturer and two competing retailers. On one hand, the manufacturer is required to invest in new technologies in order to improve its performance. On the other hand, the retailers compete in the same market with different products. We determine the conditions at which the cost-revenue sharing contract and the two-part tariff contract are capable of coordinating the one-manufacturer two-retailer supply chain system. Lastly, we analyze a system consisting of multiple complementary suppliers and a single manufacturer. It is assumed that the suppliers are required to invest in new technologies in order to participate in the supply chain negotiations. While the manufacturer initially offers a wholesale price contract to the suppliers. We compare both the decentralized and centralized settings, and show that if the supply chain members decide to cooperate and coordinate the system, they could increase the overall expected profit by at least 1/3 compared to the non-cooperative scenario. We then find that although the cost-sharing contract is unable to coordinate the system, the cost-revenue sharing contract is capable of coordinating the multi-supplier and single-manufacturer supply chain. Moreover, we establish the conditions at which the cost-revenue sharing contract offers a win-win profit scenario to all parties of the negotiation and review how bargaining analysis can lead to the optimal negotiation ability of each member.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".