Archive Ouverte INSA Rennes
Not a member yet
692 research outputs found
Sort by
A Dynamic Stochastic Integrated Climate–Economic Spatiotemporal Model for Agricultural Insurance Products
No full textInternational audienceWe propose a new methodology for area yield distribution modeling. We explore a variety of new hybrid data emulators for spatialtemporal statistical modeling of agricultural crop yields. The regression models explored leverage from a combination of model-generated and observed features incorporating climate/weather variables relating to temperature and precipitation over space and time and agricultural variables for farms such as crop allocations, crop types, land use, and crop rotation. This provides the modeling framework to achieve a hierarchical decomposition of the yield distribution at multiple spatial scales over time, allowing us to study both county- and individual farm-level information with suitably selected weighting functions that take into account farm size and crop type. A core component of our model framework is the climate model component that involves a spatialtemporal local approximate seasonal autoregressive integrated moving average Gaussian process (La-SARIMA-GP) model that is suitable for accurately studying local monthly temperatures and rainfalls. Upon construction of the crop yield model, we demonstrate that for practitioners, there is a clear incentive to consider such a model because it accommodates apportioning of the county yield information to the farms level. This is of significance for both individual and index-based agricultural crop insurance product design and for farm risk management. We demonstrate an application of our model in the insurance context of crop insurance risk pooling and insurance policy rating where we investigate the impact of different temporal and spatial interpolation methods on insurance loss ratios using a rating game
Artificial Intelligence Research in Management: A Computational Literature Review
No full textInternational audienceArtificial intelligence (AI) spring of the past decade created an increased interest into the topic in business as well as in academia. This resulted in an upward trend in academic publications, not only in computer science but also in management. This article presents a computational literature review with an abstract-based sampling approach to investigate the status of the management literature to take stock of academic research of the past two decades. We analyze 6324 papers from 1990 to 2020 published in five management-related domains and identify 41 distinct topics. We present the evolution of research pre and post AI spring, emerging topics as well as saturated areas. The findings show that the previously disjointed topic network structure is fully connected by early 2010s and the upward trend in management research starts in the period of 2014–2015. The results provide a comprehensive insight into the potential of AI in management versus underdeveloped areas, and presents, for management scholars and practitioners, suggestions about effective adoption of AI practices
How do organizations leverage social media to enhance marketing performance? Unveiling the power of social CRM capability and guanxi
No full textInternational audienceDrawing on information technology-enabled organizational capabilities theory, we argue that how and when social media use affects marketing performance depending on the mediating role of social customer relationship management (CRM) capability and the moderating role of guanxi. Using a sample of 194 Chinese agricultural firms, we employed a combination of complementary techniques: advanced analysis for composites–structural equation modeling (ADANCO-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). In ADANCO-SEM analysis, we empirically verify the full mediating role of social CRM capability in the association between social media use and marketing performance and identify the condition for this indirect effect (i.e., when the guanxi levels are high). Moreover, guanxi plays a dual moderating role—it exerts a substitution effect when social media is used to build social CRM capability, and it exerts a complementary effect when social CRM capability is leveraged to improve marketing performance. FsQCA analysis further reveals the different configurations of social media use, guanxi, and social CRM capability that can lead to high marketing performance in different firm sizes. The findings complement those from ADANCO-SEM analysis vis-à-vis the conditions for the formation of marketing performance. This study contributes to the emerging literature on the business value of social media by theoretically exploring and empirically validating the mechanisms and boundary conditions by which social media affects marketing performance
Sustainable group tourist trip planning: An adaptive large neighborhood search algorithm
No full textInternational audienceThe tourism industry is a key driver of economic growth and contributes to the achievement of sustainability goals. This paper presents a multi-objective group tourist planning problem that considers economic, environmental, and social dimensions simultaneously. The proposed model minimizes total cost and environmental impacts while maximizing the total collected prizes from tourists' interests. We introduce the lost profit opportunity for the cost of tours from an economic perspective for the first time. From an environmental perspective, the model minimizes both carbon emissions for transportation and the waste produced by tourists. Social satisfaction is addressed by considering tourists' preferences for visiting tourist sites and their interests in participating in group tours, maximizing total collected prizes. Uncertainties in travel time and prize values are addressed by using a fuzzy programming approach. A multi-objective adaptive large neighborhood search (ALNS) algorithm is developed to solve the proposed multi-objective group tourist planning problem, offering various removal, insertion, and local search heuristic procedures. Extensive analyses and computations are conducted to demonstrate the performance of the proposed multi-objective optimization model and the ALNS metaheuristic algorithm in solving large-scale instances. The results demonstrate the effectiveness of our approach in aiding tourism managers to make informed decisions that balance economic, environmental, and social objectives
Equilibrium anti-counterfeiting strategies with deceptive counterfeits: Proactive, reactive, or instantaneous?
No full textInternational audienceThis papers studies anti-counterfeiting strategies with deceptive counterfeits. We develop a model to study the interactive anti-counterfeiting and counterfeit hiding decisions between the genuine brand company and a deceptive counterfeiter. Facing deceptive counterfeits, the genuine brand company can choose to adopt a proactive, instantaneous, or reactive anti-counterfeit strategy. We first examine these strategies and then characterize the equilibrium outcomes. Surprisingly, we reveal that the genuine brand company does not necessarily benefit from heavier penalty and the counterfeiter is not necessarily worse off with more costly counterfeit hiding efforts. Interestingly, the counterfeiter’s hiding effort decreases with heavier penalty when the genuine brand company’s anti-counterfeit and the counterfeiter’s hiding decisions are sufficiently efficient. Besides, higher levels of counterfeit imitation or penetration can either hurt or benefit the genuine brand company. Whether the counterfeiter is better off with deeper counterfeit penetration depends on the status quo. Furthermore, the counterfeiter exerts fewer counterfeit hiding efforts when the genuine brand company exerts more anti-counterfeit efforts, while the anti-counterfeit effort increases with the counterfeit hiding effort, regardless of the anti-counterfeiting strategies. Finally, for decision makers and policy makers, we discuss the implications for anti-counterfeiting strategies in practice
Inégalités de revenu et de patrimoine : modèles, données et perspectives croisées
No full textInternational audienceBien que liées par l’étude d’un objet commun, les approches empiriques permettant de mesurer les inégalités de revenu et de patrimoine et les approches macroéconomiques semblent s’être développées de manière relativement disjointe. Dans cet article, nous revenons sur les origines et développements de ces deux littératures. Nous montrons comment leurs évolutions récentes ouvrent la possibilité d’un dialogue fructueux, et l’illustrons par les travaux d’Auray et al. [2022], qui étudient les facteurs explicatifs des inégalités de revenu et de patrimoine en France depuis 1984. A l’aide d’un modèle à agents hétérogènes et d’analyses contrefactuelles, ces travaux mettent en lumière le rôle clé de l’augmentation du pouvoir de marché des entreprises, des réformes du système socio-fiscal et des variations différenciées du prix des actifs sur la dynamique des inégalités
Dynamic dependence between quantum computing stocks and Bitcoin: Portfolio strategies for a new era of asset classes
No full textInternational audienceQuantum computing and digital currencies еmеrgеs as an еssеntial arеa of inquiry within thе rеalms of science, technology, and finance. A pivotal yеt lеss еxplorеd aspect of this area pеrtains to thе dеvеlopmеnt trajеctory of quantum computing rеsеarch in enhancing financial markets trading and as diversification portfolio instrument. This research investigates the different portfolio strategies and the dynamic dependence between quantum computing stocks and Bitcoin using daily data from August 11, 2010, to September 6, 2023. For this purpose, the paper utilises the Wavelet Local Multiple Correlation (WLMC), the Dynamic Conditional Correlation- Generalized AutoRegressive Conditional Heteroskedasticity (DCC-GARCH) methods, and portfolio optimisation implications. The results show a strong dependence on the time-scale domain, specifically after 2020. Thе timе еvolution of cumulativе rеturns for thе Minimum Variancе Portfolio (MVP), Minimum Corrеlation Portfolio (MCP), and Minimum Connеctеdnеss Portfolio (MCoP) еvidеnt that MVP еxhibits considеrably lowеr cumulativе rеturns compared to MCP and MCoP, given thе the significant invеstmеnt wеight of Bitcoin, IBM and NVDA markets. The findings are crucial for investors, policymakers, and regulators, providing a detailed understanding of the dynamic interplay between quantum computing stocks and Bitcoin and enabling more informed and strategic investment decisions
It is a match! The effect of regulatory fit on new products recommendations
No full textInternational audienceOnline retailers often recommend new products to consumers. The present study examined the influence of regulatory fit on consumers' click‐through intentions of new products recommended by online retailers. We proposed that regulatory fit resulting from aligning the product's regulatory focus and recommendation message's regulatory orientation positively influences click‐through intention of new product recommendations. In a laboratory study (Study 1), we found that regulatory fit increase consumers' click‐through behaviors of new product recommendations. Study 2 replicated the findings of Study 1 in a controlled online experiment and found support for regulatory fit—click‐through intentions relationship. Study 3 found that regulatory fit increases click‐through intentions for new products but not for existing products. Study 4 supported the mediating role of perceived efficacy and boundary condition of consumer innovativeness in the relationship between regulatory fit and click‐through intentions. This study contributes to the literature on new product adoption, regulatory focus, and product recommendation strategies. Furthermore, it helps online retailors develop effective recommendation strategies for new product recommendations
Role of IIoT as New Business Model Innovation in the Manufacturing Industry
No full textInternational audienceThe manufacturing Industry in Europe plays a significant role in economic growth and development. Given the increased role of technology in this sector, the Industrial Internet of Things (IIoT) is one of the technological advancements that improve the Business Model (BM) efficacy in various manufacturing industries. However, research into the role of IIoT as a BM in the manufacturing industry is limited despite its contribution to the success and performance of the firms. Therefore, this study explores the role that IIoT plays as a BM in various manufacturing industries. A survey was conducted utilizing open-ended questionnaires across 60 manufacturing firms in Europe including automotive suppliers, information and communication, machine and plant engineering, electrical engineering, and medical engineering. The findings indicate that IIoT as a BM has different levels of contribution across the manufacturing industry with glaring variations in terms of performance between information and communication firms as well as automotive. This study can act as a guideline for further research on the complex relationship between IIoT as a BM and firms’ performance to influence decision-making processes within the manufacturing industry. Given that this is a pre-study, the limitations, and recommendations for future research are highlighted
Airfreight forwarder’s shipment planning: Shipment consolidation and containerization
No full textInternational audienceThis study focuses on an airfreight forwarder's shipment planning problem, while considering shipment consolidation and containerization in the international supply chain. Items belonging to different shipments from supplier's manufacturing warehouses are consolidated and loaded into Unit Loading Devices (ULDs) at outbound logistics hubs and to inbound logistics hubs by air transportation, where items are unloaded from the ULDs and distributed to the corresponding retailers by parcel delivery. A three-dimensional multiple bin size bin packing problem is considered, where items are consolidated and orthogonally loaded into ULDs of heterogeneous irregular shapes, where each item has a required latest allowable delivery time. A mixed integer programming model is formulated for the problem, which aims to determine the optimal route planning and feasible packing scheme for the transported items. This study develops a biased random-key genetic algorithm combining a three-dimensional bin packing heuristic to solve the problem. A two-phase greedy heuristic with a chaotic system is designed for the generation of initial population. Additionally, a catastrophe operator and a self-adaptive neighborhood search are put forward to further improve the performance of the algorithm. A numerical experiment is given to demonstrate the feasibility of formulation and effectiveness of algorithm by comparing with ILOG CPLEX, and managerial insights are provided