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Robust Optimization Approaches for Purchase Planning with Supplier Selection under Lead Time Uncertainty
No full textInternational audienceSupplier reliability is a critical issue for manufacturing companies. Delivery delays from suppliers create backlog and firefighting on the shop floors. To avoid disruption and hedge against supplier lead time uncertainty, companies rely on diversification, multi-sourcing, and safety lead times. In multi-sourcing, the buyer might order the same product (raw material) from different suppliers. The design of a robust and cost-efficient purchasing/ordering plan in multi-sourcing is a complex task which has a strong impact on the performance of the company. In this study, we investigate the use of robust optimization for the integrated lot-sizing and supplier selection problem under lead time uncertainty. More specifically, we use polyhedral budgeted uncertainty sets. The resulting model determines the ideal lot sizes to minimize the total costs taking into consideration suppliers’ reliability and prices. To solve this problem, a row and column generation approach is proposed. To alleviate scalability issues, we enhance the row and column generation through a robust counterpart formulation, and we propose an efficient fix-and-optimize approach. Our extensive computational experiments show that the fix-and-optimize approach yields good quality solutions within a reasonable amount of computational time. We provide insights into supplier diversification based on the risk profile of the decision-maker. One of the conclusions is that an extremely risk-averse decision-maker selects a single supplier, namely the most reliable one even if it does not offer the lowest price
How latecomers catch up to build an energy-saving industry : The case of the Chinese electric vehicle industry 1995–2018
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A maximum-flow network interdiction problem in an uncertain environment under information asymmetry condition: Application to smuggling goods
No full textInternational audienceWe study the interdiction of smuggling network that arranging the activities of the police in order to successfully interdict criminals in smuggling goods. This work contributes to the literature of maximum flow network interdiction problems by addressing asymmetric information, uncertain conditions, multi commodity, and with multiple sources (origins) and sinks (destinations). Information Asymmetry realistically occurs due to incomplete information of interdictor (police) and operator (smuggler) about each other's performance, which is adapted from the real-world condition. We propose two mixed-integer programming models by reformulating a Min–Max bi-level mathematical model. In the first model, the type of interdiction is discrete (zero and one), while in the second model, the interdiction is assumed continuous, meaning that the partial interdiction is possible. The asymmetry type of the smuggler's information towards the police have formulated through a linear function while the asymmetry of the police information to the smuggler is formulated using an uncertain parameter through a two-stage stochastic programming framework. To solve the first model, an innovative exact hybrid method is proposed combining of a Decomposition Method and Progressive Hedging Algorithm (DM-PHA). An augmented Karush-Kuhn-Tucker (KKT) method is also used to solve the second model. Several sensitivity analyses are then conducted, and the results demonstrate the applicability and effectiveness of the proposed models as well as the solving approach. It is also shown that the proposed models can be used as a suitable approach in uncertain environment and under asymmetric information to determine the optimal interdiction decisions of police to prevent further smuggling
Societal trust and Sukuk activity
No full textInternational audienceSukuk investments require investors and issuers to adhere to subtle moral and ethical standards beyond following mere profit maximization objectives. Investor trust manifested through the level of societal trust could be vital in the global Sukuk investment surge. This study investigates the relationship between the societal trust level and Sukuk activity. It employs a global sample of Sukuk issuances spanning over 2001–2019 and finds that a country’s societal trust level significantly and positively influences the amount of Sukuk issued. Moreover, this positive effect supersedes the negative effects of higher information asymmetry associated with equity-based Sukuk or Sukuk issued by risky firms. Ultimately, trust is both a deterrent and critical for Islamic finance success
COVID-19 containment measures and stock market returns: An international spatial econometrics investigation
No full textInternational audienceWe investigate the impact of governments’ social distancing measures against the novel coronavirus disease 2019 (COVID-19) as this was reflected on 45 major stock market indices. We find evidence of negative direct and indirect (spillover) effects for the initial period of containment measures (lockdown)
Antecedents of intention to adopt artificial intelligence services by consumers in personal financial investing
No full textInternational audienceAntecedents of intention to adopt artificial intelligence and robo-advisory services from the German private investors' perspective may guide future adoption behavior. This paper raises the question to what extent German investors' is willing to use robo-advisory services instead of a human advisor to manage their investments. The exploratory study identified the following constructs that impact the intention to use artificial intelligence to invest: perceived risk, perceived usefulness, perceived ease of use, social influences, and intention to use. Findings from this study can help inform marketers when developing strategies to foster awareness and the adoption of robo-advisors
Fixed and rolling batching for order picking from multiple carousels
No full textInternational audienceThe carousel is an important automated storage and retrieval system. Customer orders to be collected from carousels are grouped into batches and the orders of a batch are collected simultaneously. We study two batching methods for picking from multiple carousels: (i) fixed batching, where all orders belonging to a batch are collected before the next batch is started, and (ii) rolling batching, where each time an order belonging to the current batch is completed, it is immediately replaced by a new order. For these methods, the main decision is respectively to allocate orders to different batches and to define a sequence for adding orders into batches. With the objective of minimising the total completion time, we develop models for fixed and rolling batching. Thanks to our collaboration with the company KLS Logistic Systems, we use real data to test and prove the efficiency of our models. With comparison to current batching strategies of real companies and to benchmark heuristics, our models yield a considerable time saving. Our findings also indicate that an increase in order size favours the rolling batching over the fixed batching. The models developed in this paper have been implemented and are currently being used in practice
Serving the low-income consumer in a rich economy: Dollar General racks up sales
No full textInternational audiencePurpose The conceptualization of the Base of Pyramid (BOP) proposes that low-income markets can lead to profitable opportunities for businesses. The purpose of this study is to identify key success factors of a BOP business strategy based on a case study of the discount retailer, Dollar General, in the USA. Design/methodology/approach The research design used in this research is an in-depth case study of Dollar General in the USA. Qualitative methods are applied in both the primary and secondary data collection and during the follow-on data analysis of Dollar General. Findings Dollar General’s strategic profile is achieved through the combination of the following four actions which are tailored to compete effectively at the BOP in the USA: creating the neighborhood discounter, raising aspirational appeal, reducing service and eliminating internationalization. Research limitations/implications The case is specific to Dollar General in a US cultural context. Practical implications The case of Dollar General demonstrates how a discounter retailer should not only follow a low-cost strategy to compete at the BOP. Its ability to craft a distinctive strategy is coherent with meeting the logistical, rational and emotional needs of the low-income consumer in the USA. Social implications Many businesses have neglected rural areas of the USA as being unprofitable. The ability for businesses such as Dollar General to serve the BOP segment can foster the socio-economic well-being of communities. Originality/value The overwhelming body of the BOP literature is based on emerging markets. To the best of the authors’ knowledge, this is one of the few studies to investigate BOP business strategy in the USA
Corporate environmentalism and brand value: A natural resource-based perspective
No full textInternational audienceGiven ever-increasing engagement of firms in corporate environmentalism over the past few decades, a multitude of studies investigated the antecedents and consequences of corporate environmentalism. Extant studies exploring the consequences of corporate environmentalism predominantly measured its effects on firm performance. However, to the best of our knowledge, no study thus far has explored whether or not the key pro-environmental initiatives pertaining to corporate environmentalism carried out by industrial firms have any effect on market-based assets, namely, brand value. This study endeavored to address this gap in the literature. Drawing on natural resource-based view of the firm (NRBV), this study argued that industrial firms committed to corporate environmentalism reap rewards in the form of higher brand value. This study investigated three salient areas of corporate environmentalism, namely, environmental innovation, efficiency in using natural resources and emission reduction. The findings of this research demonstrate that industrial firms that outperform in environmental innovation, use fewer natural resources, and reduce emission have a higher brand value. Interestingly, while environmental innovation and efficiency in using natural resources contribute fairly equally to brand value, ability to reduce emissions contributes the least to brand value creation