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A contingency-based approach to service robot design: Role of robot capabilities and personalities
No full textInternational audienceThe rise of service robots is changing how products and services are delivered, significantly affecting customer outcomes. However, research has yet to specifically examine how the design of a service robot to specific service contexts influences customer engagement and value co-creation. Our study adopts a contingency perspective to investigate how the design of robot capabilities and personalities aligned with specific service contexts impacts customer engagement and value co-creation intentions. We tested this proposition through three experiments carried out in the banking and restaurant service contexts. Our findings revealed the effectiveness of carefully designed robotic capabilities and personalities within a service infrastructure depends on the specific service contexts. The study findings have important implications for service firms in designing service robots through managing robot capabilities and personalities to align with specific service contexts
Completing Projects on Time and Budget: A Study on the Analysis of Project Monitoring Practices Using Real Data
No full textInternational audienceThis article analyzes the relationship between project cost and time performance indicators and monitoring activities, namely, tracking frequency and regularity with real project data. The existing literature on project monitoring and control remains scant, mainly based on self-reported, simulation-based artificial data for a single project, and somewhat inconclusive. Data from 60 projects managed in Belgium between 2011 and 2019 with different project duration and sizes were first used to reveal associations of regular monitoring with project performance with linear probability models; then, to dissect nonlinear associations between monitoring frequency and project performance indicators using random effects models. Earned value management technique with performance indicators is adopted to assess the project performance. Empirical findings indicate that regularly tracked projects are less likely to be late. Tracking frequency displays a U-shaped association with the likelihood of late completion. Moreover, tracking frequency has inverted U-shaped relationships with cost performance and schedule performance indexes. Moving beyond the direct effects, this article is the first to analyze a nonlinear relationship between monitoring and project performance. Our results also validate prior studies' findings on regular and frequent tracking effects using real-life multiple-project data and assess the EVM metrics and their behavior in project management
Recession-proof marketing? Unraveling the impact of advertising efficiency on stock volatility
No full textInternational audienceThe current study examines how corporate advertising efficiency (estimated using data envelopment analysis) is impacted during economic recessions. The study then investigates how advertising efficiency affects stock price volatility in recession and non-recession times. Drawing on the resource-based view and contingency theory, this study utilizes generalized method of moments (GMM) estimation to analyze a sample of US listed firms. The findings reveal that advertising efficiency tends to decline during economic downturns. Moreover, the study demonstrates that firms with higher advertising efficiency experience more stable stock prices during normal economic conditions. However, an interesting observation emerges during recessions, as firms with strong advertising efficiency face higher stock price volatility. This suggests that while consumers are attracted to efficient advertisements, investors do not assign the same value to advertising spending during economic contractions. Importantly, these results are robust to endogeneity issues and various measurements of variables
Investing in cryptocurrency before and during the COVID-19 crisis: Hedge, diversifier or safe haven?
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Cyber resilience framework for online retail using explainable deep learning approaches and blockchain-based consensus protocol
No full textInternational audienceOnline retail platforms encounter numerous challenges, such as cyber-attacks, data breaches, device failures, and operational disruptions. These challenges have intensified in recent years, underscoring the importance of prioritizing resilience for businesses. Unfortunately, conventional cybersecurity methods have proven insufficient in thwarting sophisticated cybercrime tactics. This paper proposes a novel resilience strategy that leverages Explainable Deep Learning technologies and a Blockchain-based consensus protocol strategy. By combining these two approaches, our strategy enables rapid incident detection, explains the features and related vulnerabilities that are used, and enhances decision-making during cyber incidents. To validate the efficacy of our approach, we conducted experiments using NAB datasets, preprocessed and trained the data, and performed an experimental study on real online retail architectures. Our results demonstrate the effectiveness of the proposed framework in supporting business and operation continuity and creating more efficient cyber resilience strategies that will enhance decision-making capabilities
Quand la suppression vaut mieux que la réévaluation : le point d’ébullition de la colère dans les rencontres de service
No full textInternational audienceLes recherches sur la manière dont les évaluations cognitives de multiples signaux de défaillance d’un service se combinent pour générer la colère du client et le rôle des stratégies de régulation émotionnelle (suppression et réévaluation) dans l’atténuation de cette émotion sont encore rares. En utilisant une méthode expérimentale de vignettes d’une situation de défaillance de service auprès de 971 participants, nous montrons que les évaluations cognitives du blocage des objectifs, de la responsabilité d’autrui et du faible contrôle agissent conjointement, de manière indifférenciée, pour augmenter la colère de façon non linéaire. Nous démontrons également que la suppression émotionnelle est bénéfique pour faire face à la colère dans des situations où plusieurs signaux provoquent la colère. Inversement, la réévaluation est plus efficace lorsque les signaux déclencheurs de colère sont moins nombreux. Ce résultat remet en question le point de vue dominant selon lequel la réévaluation est préférable à la suppression pour faire face aux émotions négatives
Piling and Discounting Perishable Products: Optimal Replenishment and Discounting Policy for Perishable Products
No full textInternational audienceRetail stores often display large quantities of perishable products that they sell at full price over a given period and then at a discount until the end of the inventory cycle. We investigate this common practice by considering a product which is subject to continuous decay through time. The demand is a function of both the price of the product and the inventory level. The retailer may discount the product once during the cycle. Closed-form expressions were provided for the maximum discounting time and cycle time. The conditions under which an optimal discount policy exists were established. The results provide insights to decision-makers on how to design a markdown policy for perishable products
Flight to cryptos: Evidence on the use of cryptocurrencies in times of geopolitical tensions
No full textInternational audienceThis paper examines trading activity in cryptocurrencies in times of geopolitical crises. Cryptocurrencies represent speculative assets as well as payment methods. This combination of features is not present in securities like stocks and bonds. The empirical analysis is based on a sample of 93 events associated to potential limitations of a fiat currency circulation and considers five cryptos (Bitcoin, Ether, Ripple, Dash, and Tether). We find that trading in cryptocurrencies increases with events of geopolitical tensions. The increase in cryptocurrencies trading in times of crises can be motivated by different explanations (e.g., protecting savings as the domestic currency devaluates, making payments as the domestic financial system is no longer available, avoiding sanctions) which are difficult to disentangle. A more specific analysis concerning the EU sanctions established in 2022 on Russia shows that crypto trading slows down when crypto-related services (wallet, account or custody services) are explicitly included in EU financial sanctions packages. A warning about data limitations: the data set only includes trading activities conducted on centralized exchanges (CEXs) and does not include transactions conducted on decentralized exchanges (DEXs). Sanctions are supposed to be more effective on CEXs where the platform acts as a custodian for trader's asset. We also examine trading activity from the Ukranian Hrvynia to cryptocurrencies and find a strong increase in outflow from Hrvynia since the beginning of the conflict. This finding – which is not affected by donations of cryptos received by Ukraine from abroad – is consistent with the hypothesis that Ukrainians increasingly exchanged their domestic currency for cryptocurrencies
A risk-averse distributionally robust project scheduling model to address payment delays
No full textInternational audienceDelays in payments have become a common risk factor for industrial projects, especially in recent years, since the financial position of firms has been threatened by pandemics, wars, inflation, and major supply chain disruptions. These delays create a time lag between expenses and payments, potentially leading to cash shortages that can have significant negative effects on the project success. To address cash shortage issues, project contractors often explore alternative financing options. The amount of money the contractor needs to borrow and when the loan is taken out considerably affects the overall project cost. In this paper, we present a distributionally robust model for effective cash flow management that minimizes the financing cost by accurately estimating the amount and timing of the expenses and revenues throughout the project life cycle. For the proposed model, we develop a heuristic algorithm that solves the problem efficiently. The performance of the heuristic is compared to the best-known solutions generated within a time limit by an off-the-shelf exact solver. Our results show that our algorithm is very competitive and can generate better solutions in substantially less time
Simultaneous Pickup-and-Delivery Production-Routing Problem in closed-loop supply chain with remanufacturing and disassembly consideration
No full textInternational audienceIn a context of Closed-Loop Supply Chain, Production-Routing Problem with Pickup and Delivery is presented. In its basic form, Production-Routing Problem (PRP) attempts to solve jointly Dynamical Lot-Sizing and Inventory-Routing Problems. In this paper, a novel PRP model seeking to minimize the total cost of manufacturing, remanufacturing, disassembly, inventory, and routing by taking into account the remanufacturing and disassembly processes of End-of-Life returned products is provided. Novel hybrid heuristics based on Two-Phase Iterative and Relax-and-Fix heuristics were developed and outperform Branch-and-Cut algorithm for large size instances with a small vehicle capacity. Main insights derived from sensitivity analyses are (i) managers can use the model to trade off the cost saving resulting from the integration of forward and reverse flows, on the one hand, and any additional cost incurred by the organizational changes related to the integration, on the other hand, (ii) a high level of remanufacturing rate for returned products is not necessarily profitable, and managers should develop a return policy that leads to the appropriate level of remanufacturing rate, and (iii) investing in expanding the remanufacturing or the disassembly capacities can significantly reduce the total cost until a threshold level, beyond which any further investment is not beneficial