Mean-Variance Analysis of Supply Chain Contracts

Institute of Textiles and Clothin

A new and efficient intelligent collaboration scheme for fashion design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance

Values of blockchain for risk-averse high-tech manufacturers under government’s carbon target environmental taxation policies

AbstractToday, high-tech industries such as consumer electronics commonly face government rules on carbon emissions. Among the rules, carbon emission tax as well as extended producer responsibility (EPR) tax are two important measures. Using blockchain, the policy makers can better determine the carbon target environmental taxation (CTET) policy with accurate information. In this paper, based on the mean-variance framework, we study the values of blockchain for risk-averse high-tech manufacturers who are under the government’s CTET policy. To be specific, the government first determines the optimal CTET policy. The high-tech manufacturer then reacts and determines its optimal production quantity. We analytically prove that the CTET policy simply relies on the setting of the optimal EPR tax. Then, in the absence of blockchain, we consider the case in which the government does not know the manufacturer’s degree of risk aversion for sure and then derive the expected value of using blockchain for the high-tech manufacturers. We study when it is wise for the high-tech manufacturer and the government to implement blockchain. To check for robustness, we consider in two extended models respectively the situations in which blockchain incurs non-trivial costs as well as having an alternative risk measure. We analytically show that most of the qualitative findings remain valid.</jats:p

Electronic Market Place for Returned Products in The Publishing Industry: A Simulation Analysis

In the publishing industry, the publishers supply products like the magazines, newspapers and books to the retailers. In order to encourage the retailers to order more, the publishers usually adopt a kind of buy-back return policies under which the retailers can return the unsold products for a partial refund. In the past, due to the lack of retail sales channel, most of the returned products were salvaged at a very low value. Now, with the advance of e-commerce, publishers can make use of Internet as an e-marketplace to sell those returned products to a completely different market – the World Wide Web. Since Internet offers a global open system, it breaks the geographical barrier and the demand for those “locally fade-out” goods can be very significant. In light of this, we study in this paper a two-echelon supply chain with one publisher and multiple retailers. Through the simulation analysis, we find that the impact of the e-marketplace can be substantial. Depending on the operations cost of the emarketplace and the size of the demand, the expected profit improvements for the publisher, the retailers and the overall supply chain vary. We identify the factors that can achieve the situation under which all parties\u27 profits are improved with the e-marketplace. Moreover, with a price dependent demand distribution for the e-marketplace, we can determine the optimal buy-back price and the optimal emarketplace selling price for the product. A real case of a local publisher has been chosen for simulation analysis and the managerial issues are discussed

Risk management for second-hand clothing imports in least developed countries: Legislations and perception of public-sector corruption

The second-hand clothing imports are very popular in the least developed countries (LDCs). The social health risk (SHR) associated with second-hand clothing products and the lack of relevant legislations in LDCs, however, bring substantial challenges. This article is therefore developed to explore the sterilization legislation design for second-hand clothing supply chains in LDCs. To address LDCs' different import requirements of fumigation, both the extended exporter responsibility (EER) legislation scheme and the extended importer responsibility (EIR) legislation scheme are considered. We also examine whether the perception of public-sector corruption in LDCs may affect the performance of sterilization legislation schemes. We compare the performance of sterilization legislation schemes under different public-sector corruption cases, different sterilization legislation structures, as well as market competition. Interestingly, our analyses show that the EER and EIR legislation schemes can achieve the same performance under a per unit SHR duty, no matter whether there is public-sector corruption or not. However, these two legislation schemes perform differently under the lump-sum SHR duty. Besides, with the presence of the public-sector corruption perception, the prospect of financial benefits from bribing the regulatory agency can induce the firm to choose a higher optimal sterilization level when the bribe is sufficiently small. These implications complement the extant knowledge on risk management of second-hand clothing in LDCs, and provide an important guidance regarding the design of sterilization legislations on second-hand clothing imports

Responsive supply in fashion mass customisation systems with consumer returns

Mass customisation systems have been well-established in the fashion industry. Some fashion brands offer the mass customisation system for their selected seasonal products, and allow unconditional returns and full refund for any unsatisfied customers. Motivated by the above mentioned observed industrial practice and based on the growing importance of responsive supply, we explore in this paper the value of quick response supply in fashion mass customisation systems with consumer returns. We focus on investigating how the consumer returns rate affects (i) the optimal inventory decision of the fashion brand, (ii) the achievability of Pareto improvement in implementing quick response supply, (iii) the respective values of quick response for the fashion brand, the fashion supplier and also the fashion supply chain, and (iv) the impact of quick response supply on the environment. We interestingly find that consumer returns enhance the value of quick response supply to the fashion supplier. Quick response supply is also found to be helpful in reducing the environmental cost under the fashion mass customisation system with consumer returns

Order picking optimization with order assignment and multiple workstations in KIVA warehouses

We consider the problem of allocating orders and racks to multiple stations and sequencing their interlinked processing flows at each station in the robot-assisted KIVA warehouse. The various decisions involved in the problem, which are closely associated and must be solved in real time, are often tackled separately for ease of treatment. However, exploiting the synergy between order assignment and picking station scheduling benefits picking efficiency. We develop a comprehensive mathematical model that takes the synergy into consideration to minimize the total number of rack visits. To solve this intractable problem, we develop an efficient algorithm based on simulated annealing and dynamic programming. Computational studies show that the proposed approach outperforms the rule-based policies used in practice in terms of solution quality. Moreover, the results reveal that ignoring the order assignment policy leads to considerable optimality gaps for real-world-sized instances