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Robust maritime disruption management with a combination of speedup, skip, and port swap strategies
No full textInternational audienceA large volume of global transportation is carried out annually by liner shipping companies and it includes a large portion of global trade. Accordingly, due to the countless number of these voyages, precise planning in this field is vital to prevent severe loss. One of the noticeable issues that occur during the voyage can be natural or human disruption which is interpreted as a “delay” in the liner shipping services. Therefore, there is a need to reschedule the pre-established plan to compensate for the delays and reduce the costs including the penalties and exceeding fuel consumption. In this paper, a novel recovery model is proposed for container ship problems. This mixed-integer programming model with the use of speedup, skip, and swap ports strategies not only attempts to mitigate the dire financial consequence of the disruption but also reduces the carbon footprint. Furthermore, to ensure customer satisfaction, the alternative transshipment decision for the skipped ports cargo is considered in the model. The nonlinear model is linearized through the exact techniques, then solved in CPLEX software. As a result, the primary deterministic model could act as a “wait-and-see” solution to reduce disruption losses by up to 66% using simultaneous recovery strategies of speedup, skip and swap. However, a robust optimization approach is proposed owing to the uncertainty in delay time, type, severity, and point of disruption. This approach enables the model to face a wide variety of disruptions (that are predicted under different scenarios each of which is associated with an occurrence probability) and recommends an augmented schedule that guarantees to be feasible, optimal, and resistant. The robust model is applied in a real case from the maritime industry, and the value of robustness is reported. The results demonstrate the superiority of this model compared with others
Close encounters with the virtual kind: Defining a human-virtual agent coexistence framework
No full textInternational audienceVirtual agent research has evolved into a substantial body of work, albeit one with a fragmented structure and overlapping, and at times inconsistent, definitions and results. The current paper presents a computational literature review of 1865 academic journal publications and conference proceedings from 1995 to 2022 using Latent Dirichlet Allocation to understand the publication trends in the field, its intellectual structure, and how topics within virtual agent research have evolved and relate to each other. Our results point to a model of 16 topics as best representing the current state of the research landscape. We present descriptions of these topics, as well as topic dynamics and networks, in order to provide a clear picture of the current state of the field. We then organise these topics into a Human-Virtual Agent Coexistence Framework, identifying current trends and opportunities for future research
Animal Behavior in Capital markets: Herding formation dynamics, trading volume, and the role of COVID-19 pandemic
No full textInternational audienceThis paper provides new evidence on herding behavior. Using daily frequency data for 336 US listed firms over a five-year period, we investigate three important elements of financial herding behavior. First, trading volume, representing market interest, as a significant variable in capital markets apart from stock prices. Second, herding dynamics since herding formation is a dynamic process. Third, the reaction of possible financial herding to exogenous events-threats, as we use the pandemic event in order to investigate a market under stress. Even though the benchmark herding model used does not provide evidence of herding behavior, our results verify the significance of the above herding elements. We also find that trading volume and positive changes in trading volume result in increased cross-sectional absolute deviation (CSAD). Most importantly, we find that herding behavior is evident during the COVID-19 pandemic confirming that investors tend to herd during major crisis periods
The Effectiveness of AI in Marketing "Spotify Wrapped": How it Affects Indonesian Customer's Engagement
No full textInternational audienceWith the rise of Industry 4.0, everything has become more digitalized. Many companies have started implementing technologies in their digital marketing activities to enhance productivity. Spotify is one of the companies that used AI in their digital marketing campaign called “Spotify Wrapped” from 2016 until today. With the rise of the digital campaign, many consumers were interested in the campaign and the application. There are 3 topics that will be discussed related to how Spotify Wrapped does its marketing, the impact of the campaign on user engagement, and the way Spotify Wrapped could succeed. The data will be gathered in quantitative ways through a survey which will become the primary data. A literature study from a related journal has also been conducted to gain secondary data. The final outcome from this study has found that users participate actively and passively in this marketing strategy. In order to understand the link between dependent and independent factors and the usage of AI in Spotify Wrapped and how it impacts users' engagement with the application, the analyzed data were also utilized to support the hypotheses that were developed. It also demonstrates that one of the factors influencing users' decisions to continue using the Spotify app is Spotify Wrapped. The research is constrained by the fact that it can only include 100 Indonesian respondents who have used or are presently using the Spotify app. This study looks at consumer behavior, particularly how consumers respond to personalized content and other digital marketing tools. This report also examines and offers advice on how a company might use artificial intelligence to grow its business
Guest editorial: Artificial intelligence as an enabler for entrepreneurs: an integrative perspective and future research directions
No full textInternational audienc
Resource Mobility and Market Performance
No full textInternational audienceWe derive a feedback equilibrium of an infinite-horizon dynamic Cournot game where production requires exploitation of a renewable mobile resource, such as migratory fish, wildlife, and groundwater. We study how a small increase in the resource mobility parameter (starting from a position of no resource mobility) impacts on the equilibrium and the associated consumer’s surplus, firms’ profits and social welfare. We show that consumer’s surplus and social welfare increase in the short run but decrease in the long run, while firms’ profits may either increase or decrease in the short run, depending on initial conditions, and increase in the long run. Over the entire planning horizon, both the discounted consumer’s surplus and the discounted social welfare decrease, whereas the discounted profits increase. This result remains valid also in the presence of a per unit tax on extracti
Tracing environmental sustainability footprints in cross‐border M&A activity
No full textInternational audienceThis study documents the first large‐scale empirical evidence on the effects of differences in countries' environmental sustainability (ES) on cross‐border merger and acquisition (M&A) activity. Using 34,088 cross‐border mergers across 44 countries, we find that greater ES differences between acquirer and target countries stimulate the intensity of cross‐border mergers. The acquirer firms experience higher cumulative abnormal returns around merger announcements and pay higher merger premiums. Consistent with the pollution haven hypothesis, results on value effect are more pronounced for M&A deals in highly polluting industries such as petroleum, transportation and mining. The results are robust to a battery of robustness tests
A decentralized production–distribution scheduling problem: Solution and analysis
No full textInternational audienceIn modern production–distribution supply chains, decentralization has increased significantly, due to increasing production network efficiency. This study investigates a production scheduling and vehicle routing problem in a make-to-order context under a decentralized decision-making structure. Specifically, two different decision makers hierarchically decide the production and distribution schedules to minimize their incurred costs and we formulate the problem as a bi-level mixed-integer optimization model as a static Stackelberg game between manufacturer and distributor. At the upper level, the manufacturer decides its best scheduling under a flexible job-shop manufacturing system, and at the lower level, the distributor decides its distribution scheduling (routing) which influences the upper-level decisions. The model derives the best production–distribution scheduling scheme, with the objective of minimizing the cost of the manufacturer (leader) at the lowest possible cost for the distributor (follower). As the lower level represents a mixed-integer programming problem, it is challenging to solve the resulting bi-level model. Therefore, we extend an efficient decomposition algorithm based on Duplication Method and Column Generation. Finally, to discuss the decentralization value, the results of the presented bi-level model are compared with those of the centralized approach
Alternative governmental carbon policies on populations of green and non-green supply chains in a competitive market
No full textInternational audienceAs a severe challenge to governments, air pollution threatens many lives annually. This paper develops an evolutionary game theory model for supply chains (SCs) to encourage firms to reduce carbon emissions. A government dictates three carbon policies: carbon cap, carbon tax, and cap and trade. We construct six scenarios according to the carbon regulations and SC functions (i.e., centralized versus decentralized ones). First, the profit function of SCs that are the input of the game matrix is formulated, and optimal final prices and quantities of products are obtained. Then, an evolutionary game-theoretic model is formulated to analyze the behavior of populations by obtaining the evolutionary stable strategy under each scenario. In addition, three models of government intervention are presented, considering the cost associated with environmental pollution and government net revenue. Finally, a case study of motorcycle production dissects the results. The findings demonstrate that cap and trade can be introduced as an incentive policy since it encourages SCs to adopt green strategies and improves their profit. A carbon tax policy also succeeds in pressuring SCs to apply green strategies. However, a carbon cap policy fails in forcing SCs to adopt green strategies. Finally, it is concluded that decentralized supply chains (DSCs) handle high tax rates better than centralized supply chains (CSCs)
The horizontal and vertical coordination of policy mixes for industrial upgrading in China: an ambidexterity perspective
No full textInternational audienceThe established literature demonstrates the critical role of the policy mix in the formulation and implementation of government policies for industrial upgrading. However, existing studies mainly examine the policy mix from either a horizontal or a vertical coordination perspective; very few examine both dimensions. To gain further insights, the current study involves an analysis of how China’s central government manages horizontal and vertical coordination to pursue upgrading in manufacturing industries on the basis of an ambidextrous policy mix perspective and a thorough examination of both the external attributes (i.e., policy level) and content (i.e., policy instruments and themes) of policy documents. This analysis reveals several viable policy implications in relation to China’s manufacturing transformation. In particular, it finds that China’s policy mix for achieving manufacturing upgrading is highly coordinated on both horizontal and vertical dimensions. Governments at all levels apply the same set of policy instruments; environmental instruments are the most frequently used, followed by supply- and demand-side instruments. The core policy topics within the manufacturing upgrading structure include innovation, industrial transformation, industrial agglomeration, demonstration projects and service-oriented manufacturing. Therefore, this study establishes recommendations for future policies, which should focus on reinforcing guidance regarding national policies, encouraging local governments to apply innovative policy tools and increasing the use of demand-side policy instruments