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Why Are Inflation Forecasts Sticky ? Theory and Application to France and Germany
No full textInternational audienceThis paper proposes to adapt the model of pricing decisions developed by Alvarez, Lippi, and Paciello (2011) to the decision process of forecasters. The model features both a fixed cost of announcing a revised forecast and a fixed cost of updating the information set and adapting the forecast accordingly. Basically, the former fixed communication costs determine state dependence, which implies that the forecaster changes its forecast only when it is far enough from the optimal forecast, i.e., beyond a fixed threshold; the latter fixed information costs determine time dependence, which implies that the forecaster updates its information set only every other T periods, where T is optimally chosen. We show that survey data of inflation forecast updates as well as the last known monthly inflation rates can be used to estimate the threshold implied by the theoretical model. This threshold estimate is then crucial to uncover the optimal time between two information observations. French and German data suggest that the maximum optimal time to next observation is six months, while the observation cost is at most twice as large as the communication cost. the existence of both types of costs as well as an upper bound of the optimal time between two information observations. French and German data suggest that the maximum optimal time to next observation is six months, while the observation cost is at most twice as large as the communication cost
Surviving or solidarity? Crisis responses of small and medium‐sized enterprises during the Covid‐19 pandemic
No full textInternational audienceAbstract The Covid‐19 pandemic posed a serious threat to small and medium‐sized enterprises (SMEs). This explorative qualitative study of 100 SMEs from 20 industries and 21 countries investigates how entrepreneurs responded to the Covid‐19 pandemic and which cognitive frames guided their actions. Observed cognitive frames prioritize either business survival, conversion of business and stakeholder interest, or acceptance of conflicting social and financial goals. These cognitive frames influence the choice of crisis response without determining it. Four response patterns were found: weathering the storm, bricolage, solidarity and support, and social innovation. Strategic innovation creating access to new markets is the most successful response. The findings support a more encompassing definition of the concept of organizational resilience and shed light on motivations for acts of solidarity and social innovation as crisis responses
Digital-Free Tourism Intention: The Effects of Message Concreteness and Intervention
No full textInternational audienceDigital-free tourism is an emerging trend that limits tourists' access to information and communication technologies during vacations. However, how to motivate tourists to engage in digital-free tourism is not yet understood. Anchoring on Construal Level Theory and educational intervention, this study examines the effects of message concreteness and intervention type on tourists' intention to take digital-free tourism. Experimental data from 249 respondents showed that when factual intervention was provided, tourists were more likely to engage in digital-free tourism when they received abstract messages instead of concrete messages. Our findings can contribute to the design of promotional messages for digital-free tourism
Big Data Adoption in Project Management: Insights From French Organizations
No full textInternational audienceBig data have the potential to revolutionize the project management, but it is not clear how. Despite the growing interest, there is a paucity of exploratory research to assess the practice and the impact of big data tools and technologies on project management approaches and practices. To address this gap, in this article, we initially embrace the technological–organizational–environmental (TOE) framework as the research basis for the adoption process and conducts in-depth interviews with project managers from French organizations in different sectors. The synthesis of interviews reveals that many organizations are still in the early stage of the adoption process, mainly due to a lack of resources, especially expertise. Besides the factors of the three contexts of TOE, the project-level factors are also found to be critical for the adoption of big data in project management. Most of them adopted big data solutions to support them in the conception, definition, and execution phases of project management. Drawing on the findings, this article also provides guidelines to broaden the understanding of big data applications and their role in project management. Based on these results, we present a model with testable propositions and discuss insights that arise for organizations and project managers regarding how to apply big data tools and technologies to create value and overcome the related challenges
Optimal channel structure for a green supply chain with consumer green-awareness demand
No full textInternational audienceThis paper examines the optimal channel structure of a green supply chain consisting of one manufacturer and one retailer. The manufacturer, who is the Stackelberg leader, is responsible for green technology costs. Consumers prefer green products and therefore are green aware. We study four channel structures: a manufacturer’s dual-channel supply chain, a retailer’s dual-channel supply chain, a manufacturer-online and retailer-offline (hybrid I) structure, and a manufacturer-offline and retailer-online (hybrid II) structure. For each structure, we analytically investigate the impact of consumers’ green awareness and proportion of online and offline consumers on the level of green technology, profits, and retail prices. We also examine the effect on the optimal solutions of the manufacturer and retailer when they share the green cost. The results show that the manufacturer’s dual-channel supply chain performs the best in improving the greenness of products and its own profits. Concerning hybrid dual-channel supply chains, the manufacturer will always choose the channel with the majority of consumers to directly sell products through. The retailer, in most cases, also prefers to operate two channels simultaneously. In addition, regardless of the type of channel structure involved, consumers’ green awareness encourages the manufacturer to improve the greenness of its products; however, the proportion of online consumers has a positive effect on the greenness of products in the retailer-offline and manufacturer-online cases but a negative effect in the retailer-online and manufacturer-offline cases
Efficiency of multinational banks: Impacts of geographic and product loci
No full textInternational audienceThis paper explores geographic diversification strategies’ impact on multinational banks’ operational performance within the context of research on globalization and regionalization. We employ a sample of the 49 largest banks from 16 European countries from 2011 to 2018 and proxy operational performance by technical efficiency. We find the impact of geographic diversification on operational performance depends on the locus of geographic diversification—home-regional vs. inter-regional—and the interplay between geographic diversification and banks’ functional focus. More specifically, home-regional diversification together with a concentration on non-interest income-generating activities, including fee and commission and trading income, worsens performance, and diversification across regions alongside a focus on non-interest income-generating activities improves performance. Distinct product characteristics’ ability to facilitate different regional dispersions has important managerial implications for enhancing the success of geographic diversification strategies, a central but unresolved issue in global banking
Entrepreneurial responses to Covid‐19: The use of digital brand marketing events in the craft alcohol sector
No full textInternational audienceAbstract The wide‐ranging implications following the Covid‐19 pandemic have necessitated research into innovative entrepreneurial responses. The research study incorporates the concept of branded marketing events (BMEs) and considers their effectiveness in craft alcohol digital marketing. An exploratory qualitative study was conducted in Charlotte, North Carolina, and focused on the entrepreneurial responses of craft alcohol producers. Findings indicate that the inter‐relationships between the experiential components adapted to a digital environment enhance the engagement consumers experience with craft alcohol producers. The responses of craft alcohol producers to the impact of the Covid‐19 pandemic provide valuable insights into strategies employed during times when traditional sales and marketing activities face exceptional challenges
How uncertainty can determine corporate ESG performance?
No full textInternational audienceUsing Sino‐Securities Environmental, social, and governance (ESG) ratings data, we examine how environmental uncertainty affects the ESG performance of Chinese A‐share non‐financial listed firms from 2008 to 2020. Our findings show that environmental uncertainty harms corporate ESG performance. In particular, when environmental uncertainty increases, a firm's ESG score and ESG ratings decline due to factors such as financial constraints and industry competition. We argue that as the environmental risk premium rises, it increases the real options value of postponing sustainable investment for a firm. Consequently, the firms tend to cut down their ESG investment by weighing the long‐term benefits and short‐term direct costs. The value of real options changes with the investment opportunities available to the firms and the financing constraints and competitive pressure changes the size of investment opportunities. We argue that higher financing constraints and industry competition restrict available investment opportunities and dilute the negative impact of environmental uncertainty on corporate ESG performance. These results add to the existing literature investigating the impact of uncertainty on corporate ESG performance and offer insights to regulators and enterprise managers. These results are robust to alternate proxies of ESG performance and alternate regression techniques
Recycling of multi-source waste in an aggregate circular economy
No full textInternational audienceWe investigate how the relationship between capital accumulation and pollution is affected by the source of pollution: production or consumption. We are interested in polluting waste that cannot be naturally absorbed, but for which recycling efforts aim to avoid massive pollution accumulation with harmful consequences in the long run. Based on both environmental and social welfare perspectives, we determine how the interaction between growth and polluting waste accumulation is affected by the source of pollution, i.e., either consumption or production, and by the fact that recycling may or may not act as an income generator, i.e., either capital-improving or capital-neutral recycling efforts. Several new results are extracted regarding optimal recycling policy and the shape of the relationship between production and pollution. Beside the latter concern, we show both analytically and numerically that the optimal control of waste through recycling allows to reaching larger (resp., lower) consumption and capital stock levels under consumption-based waste compared to production-based waste while the latter permits to reach lower stocks of waste through lower recycling efforts
The formal rationality of artificial intelligence-based algorithms and the problem of bias
No full textInternational audienceThis paper presents a new perspective on the problem of bias in artificial intelligence (AI)-driven decision-making by examining the fundamental difference between AI and human rationality in making sense of data. Current research has focused primarily on software engineers’ bounded rationality and bias in the data fed to algorithms but has neglected the crucial role of algorithmic rationality in producing bias. Using a Weberian distinction between formal and substantive rationality, we inquire why AI-based algorithms lack the ability to display common sense in data interpretation, leading to flawed decisions. We first conduct a rigorous text analysis to uncover and exemplify contextual nuances within the sampled data. We then combine unsupervised and supervised learning, revealing that algorithmic decision-making characterizes and judges data categories mechanically as it operates through the formal rationality of mathematical optimization procedures. Next, using an AI tool, we demonstrate how formal rationality embedded in AI-based algorithms limits its capacity to perform adequately in complex contexts, thus leading to bias and poor decisions. Finally, we delineate the boundary conditions and limitations of leveraging formal rationality to automatize algorithmic decision-making. Our study provides a deeper understanding of the rationality-based causes of AI’s role in bias and poor decisions, even when data is generated in a largely bias-free context