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A fast and effective heuristic for smoothing workloads on assembly lines: algorithm design and experimental analysis
No full textInternational audienceWorkload smoothing on assembly lines, which aims to evenly assign tasks to stations, supports workforce planning and resource optimization. In this paper, we study smoothing assembly lines and develop a problem-specific heuristic to efficiently solve large-sized instances. To build solutions, the algorithm uses a number of well-known priority rules for task assignment in conjunction with a probabilistic decision-making procedure for closing workstations. We conduct an experimental design for selecting the best performing priority rules and for tuning the probabilistic decision-making procedure. The efficiency of our algorithm is tested and demonstrated through an extensive experimental study
When bike-sharing crashed in China: a bumpy ride
No full textInternational audiencePurpose Buoyed by the desire to reduce carbon dioxide emissions and develop sustainable urban transportation, the dockless bike-sharing industry boomed in China during 2017–2018. To the surprise of the stakeholders, this industry dramatically ebbed in 2019. The dockless bike-sharing system deviated from a problem-solver to a troublemaker in a very short period. The oversupplied and excessively discarded shared bikes caused a big waste of resources and serious pollution to the environment. In this paper, the decision-making of the key players of the industry, i.e. business operators, investors, customers and government, is analyzed through the lens of the cognitive bias. This paper aims to illuminate the process of how this innovative transport solution turned to a disastrous ending, which caused damage to urban environment and financial loss to investors. Design/methodology/approach In this study, a qualitative analysis based on the rich secondary data sources is conducted. A rich amount of qualitative data including news reports, government policies, consulting reports and companies’ annual reports etc. were collected. Findings The study shows, in the product introduction period, the government, business operators, investors and consumers fell into the cognitive bias. They over focused on the positive side such as high-tech, eco-friendly, convenient image of the dockless bike-sharing solution. Thereby, the key stakeholders made irrational decisions in product adoption and management. This study moves toward increasing key stakeholders’ awareness of the imperative to reduce these biases when promoting eco-innovations. This study also recommends a prudent attitude with a rational and comprehensive thinking style in dealing with eco-innovation and the emerging sharing economy. Originality/value To solve the cognitive biases, this study recommends that people use rational decision-making style to examine and adopt the dockless bike-sharing solutions. Practical recommendations to tackle the existing recycling crisis of the dockless bike-sharing industry are also discussed
A measurement of affluence and poverty interdependence across countries: Evidence from the application of tail copula
No full textInternational audienceThis paper examines affluence and poverty interdependence across 185 countries and its evolution over 1969–2014. To estimate affluence and poverty interdependence and derive tail interdependences the tail copulae are applied to multivariate density function. The tail coefficients are estimated in the non‐parametric way as in Schmidt and Stadtmüller (2006). The estimates show, that poverty is less interdependent and continue to decrease, while affluence has asymptotically high global dependence, meaning a higher global dependence on and sensitivity to the well‐being of the affluent countries.The received results derive the pattern of the extreme interdependence and can help to identify poverty and affluence spill‐over across countries and regions and calculate the average sensitivity of a country to these phenomena on the global level and can potentially help in poverty reduction strategies within the Sustainable Development Goal by the United Nations
Adjusting to China competition: Evidence from Japanese plant-product-level data
No full textThis study examines how the product mixes of Japanese manufacturing plants have been impacted by the rise of China imports over the period 1997-2014, and the extent that plants' local embeddedness mitigate this causal relationship. We find evidence that China import competition induced both product downsizing and product exit within Japanese manufacturing plants. Moreover, we find that those negative e ects differ across plants according to various plant characteristics including the spatial organization of their parent firm. Finally, we show that both product survival and product sales are positively impacted by external agglomeration economies, but these e ects are strong for standalone plants only, and almost non-existent for plants aliated to spatially compact multi-unit firms
Retailing Competition for Substitutable Products in Greenness- and Price- Dependent Market
No full textInternational audienceWe consider two retailers that offer two substitutable products and compete in greennessand price-sensitive market. One retailer offers a product that is produced abroad and the other one offers a product that is produced locally. The local product is greener (releases less carbon emission) than abroad product. The demand function is decreasing in price and carbon emission’s level of product. Since the products are substitutable, the price and carbon emission level of each product affect the other product’s demand. The first retailer decides its product’s price and stock level. The second retailer decides its product’s greenness level, price and stock level. An analytical approach is used in order to solve the model. By using the Nash equilibrium, we find the best strategy for both retailers. We show how the market’s structures affect the strategy of each retailer
Factor‐augmented Bayesian cointegration models: a case‐study on the soybean crush spread
No full textInternational audienceWe investigate how vector auto-regressive models can be used to study the soybean crush spread. By crush spread we mean a time series marking the difference between a weighted combination of the value of soymeal and soyoil to the value of the original soybeans. Commodity industry practitioners often use fixed prescribed values for these weights, which do not take into account any time-varying effects or any financial-market-based dynamic features that can be discerned from futures price data. We address this issue by proposing an appropriate time series model with cointegration. Our model consists of an extension of a particular vector auto-regressive model that is used widely in econometrics. Our extensions are inspired by the problem at hand and allow for a time-varying covariance structure and a time-varying intercept to account for seasonality. To perform Bayesian inference we design an efficient Markov chain Monte Carlo algorithm, which is based on the approach of Koop and his co-workerss. Our investigations on prices obtained from futures contracts data confirmed that the added features in our model are useful in reliable statistical determination of the crush spread. Although the interest here is on the soybean crush spread, our approach is applicable also to other tradable spreads such as oil and energy-based crack and spark spreads
Understanding Heterogeneous Consumer Preferences in Chinese Milk Markets: A Latent Class Approach
No full textInternational audienceWe examine heterogeneous consumer preferences in Chinese milk markets. Using a discrete choice experiment, we examine how the brand, quality certification, traceability label and price influence consumers’ milk choices. We identify four consumer segments using a latent class model: price conscious (9.8%), balanced thinking (19.8%), health conscious (57.5%), and environment conscious (12.9%) consumers. These four segments have distinct preferences: price conscious consumers prefer green certification; balanced thinking consumers have the highest willingness to pay for traceability labels; health conscious consumers have strong brand awareness; and environment conscious consumers prefer organic certification and traceability labels and use price as a quality signal. Such diversity of consumer preference can be explained by four psychological factors: price consciousness, food safety concerns, health consciousness and environmental concerns
A complex networks based analysis of jump risk in equity returns: An evidence using intraday movements from Pakistan stock market
No full textInternational audienceWe employ a multi-stage methodology combining complex network analytics and financial risk modelling to unveil the correlation structures amongst the price jump risks of companies forming the KSE-100 index in Pakistan. We identify the most influential companies in terms of jump risk, and identify communities — clusters of companies with similar price movement characteristics or with highly correlated price jumps. We find that equities in Pakistan stock market experience jumps in different time periods that are correlated to varying degrees within and across industries resulting in 19 different communities, four of which are strongly connected. While Oil & Gas, Cement and Banking sectors exhibit a significant representation of firms in communities, the automobile industry, however, seems to play an important role in risk propagation. These results provide an interesting insight to investors and other stakeholders from an emerging market viewpoint identifying the major sectors driving the volatility of KSE-100 index
A classification and review of approaches and methods for modeling uncertainty in projects
No full textInternational audienceIn this paper, we created a classification for major sources of uncertainty in projects and categorized the studies in project scheduling literature with respect to the uncertainty source(s) they address. In addition, we investigated the approaches and methods to manage uncertainty, and studied the literature regarding these methods. Project management predominantly models the randomness in duration of activities; however, studies modeling the uncertainty due to other sources are scarce. We focused on these sources of uncertainty and highlighted the promising areas of research. The results presented in this paper will help researchers to identify the research gaps in modeling project uncertainty
Consumer adoption of pro-poor service innovations in subsistence marketplaces
No full textInternational audienceDespite some extant research on innovation adoption in subsistence marketplace contexts, little is known about subsistence consumers and how they evaluate so-called pro-poor innovations. This research identified six existing, empirically tested, and well-cited innovation adoption models and collected data on them within a subsistence context. Extending existing research, data was collected across two separate and distinct pro-poor services targeted at the subsistence segment, and structural models were compared based on mediating relationships. This research contributes to the subsistence marketplace literature by providing guidance about how antecedents within these models affect subsistence consumers' evaluations of pro-poor service innovations in this increasingly important context. The research provides novel practical and theoretical insights through the development of new, testable hypotheses in the area and explores the effect of service type and geographic area (urban versus rural)