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Convergence or Divergence: A Computational Text Analysis of Stakeholder Concerns on Manufacturing Upgrading in China
No full textInternational audienceStakeholder participation is essential to the reasonable design and smooth implementation of industrial policies. Discourse analysis can be employed as a valuable methodology to decode stakeholder (dis)agreements. Following stakeholder theory, we examine four stakeholder groups, namely the government, enterprises, media, and academia, to analyze the public focus of industrial upgrading in China. We adopt a computational text analysis approach (keyword frequency calculation, word collocation analysis, and theme identification) to understand the divergent and convergent stakeholders’ concerns toward manufacturing upgrading in China from 2015 to 2020, which is widely considered as a manufacturing upgrading policy formulation stage. Our results show that stakeholders mainly focus on innovation capability and digital transformation for China's manufacturing upgrading. There, industrial planning is the major issue for government and academia. Contradistinctively, enterprises’ main concern is servitization. Enterprise internationalization is more frequently mentioned than manufacturing upgrading in the media industry. Policymakers should engage in various tactics to make the policies endorsed by other stakeholders. Most importantly, the government should fully integrate the views of entrepreneurs in the policy initiation stage. We provide practical implications for the Chinese government to implement better the Made in China 2025 plan
The Emergence of Mythologies in Organisations: A process model
No full textInternational audienceResearch on organisational storytelling has shed light on different types of narratives. A specific story type, organisational myths, has caught the interest of some scholars in the field, but has not been theorised in any great detail. While it is rarely disputed that organisational members can and do develop emotional connections to myths and mythical stories in their social context, how and why these myths, or ‘sacred stories’, emerge in organisational settings has remained mostly unaddressed. Therefore, drawing upon a Jungian psychosocial approach, we propose a process model for the emergence of mythologised stories in organisations by situating members’ psychological dynamics within the social context in which they emerge. We propose that a conscious understanding of the conditions that lead to the emergence of mythologised stories in organisations can help clarify and deepen the relationship between different types of stories to support and sustain organisational change and development. The paper contributes to the existing literature on organisational storytelling and myths within organisational studies
Forecasting the price of oil: A cautionary note
No full textInternational audienceWe study the out-of-sample predictability of monthly crude oil prices using forecast combinations constructed from several individual predictor forecasts. Our empirical results indicate that combination forecasts of monthly average oil prices are more accurate than the no-change forecast with statistically significant reductions in mean square forecast errors (MSFE) and significant directional accuracy at every horizon up to 24 months, consistent with earlier evidence that forecast combinations greatly enhance the forecastability of oil prices. In contrast, we find no significant MSFE reductions or directional accuracy for forecasts of end-of-month oil prices at almost all horizons. Furthermore, we document that end-of-month forecasts when used to guide investment and hedging decisions of investors, statistically, do not deliver superior economic value to investors. Overall, the implication of our results is that the statistical and economic significance of forecasts of oil prices is heavily influenced by the construction of the underlying oil price series and provide a cautionary note on which oil price series to use in forecasting
Anticipated chilly climate for women: the development and validation of a measure
No full textInternational audiencePurpose This study develops a measure of anticipated chilly climate for women and provides initial evidence of its validity. Design/methodology/approach We draw on three studies. Study 1 consisted of three focus groups to gain deeper insights into the meaning of the concept for prospective female jobseekers and generate scale items. In Study 2, we pre-tested job post vignettes ( N = 203), refined the scale items and explored the factor structure ( N = 136). Study 3 aimed to determine the convergent and discriminant validity of the new scale ( N = 224) by testing its relationships with organisational attractiveness, person-organisation fit perceptions and gendered language. Findings The results show that the anticipated chilly climate is an important concept with implications for applicants’ career decision-making and career growth in the technology industry, where women tend to be underrepresented. Perceptions of anticipated chilly climate comprise expectations of devaluation, marginalisation and exclusion from the prospective employment. The masculine stereotypes embedded in the language of the job posts signalled a chilly climate for both genders, negatively affecting perceptions of fit and organisational attractiveness. Originality/value Most previous studies have focussed on the actual experiences of chilly climates in organisations. We extend this body of literature to anticipatory climates and draw on social identity threat theory and signalling theory to highlight that job applicants make inferences about the climate they expect to find based on job ads. Specifically, they may anticipate a chilly climate based on cues from job ads signalling masculine stereotypes. Whilst the literature has emphasised women’s perceptions of chilly climates within organisations, our results show that both genders anticipate chilly climates with detrimental consequences for both organisations and prospective job applications.This article develops and validates a scale that measures a climate for wome
Does corruption sand the wheels of sustainable development? Evidence through green innovation
No full textInternational audienceThis study investigates the impact of corruption on green innovation, as corruption may impede or foster green innovation in developing economies due to their weak governance systems. We develop a dataset of Chinese non‐financial firms listed between 2007 and 2020 and apply static and dynamic regression techniques. The results indicate a highly significant negative association between corruption and green innovation. This supports the notion that corruption culture reduces corporate legitimacy concerns ( institutional theory ), increases managerial rent‐seeking ( agency theory ), and hinders green innovation, thus impeding sustainable development and supporting the “ sand the wheels ” hypothesis. Our analysis also reveals that corruption's negative impact on green innovation is particularly significant for firms with lower media and analyst coverage, non‐state‐owned firms, and firms in heavy‐polluting industries. These results are robust to alternate proxies of green innovation and corruption as well as econometric specifications that account for endogeneity issues and industry, region, and time‐fixed effects
Explainable artificial intelligence in transport Logistics: Risk analysis for road accidents
No full textInternational audienceAutomobile traffic accidents represent a significant threat to global public safety, resulting in numerous injuries and fatalities annually. This paper introduces a comprehensive, explainable artificial intelligence (XAI) artifact design, integrating accident data for utilization by diverse stakeholders and decision-makers. It proposes responsible, explanatory, and interpretable models with a systems-level taxonomy categorizing aspects of driver-related behaviors associated with varying injury severity levels, thereby contributing theoretically to explainable analytics. In the initial phase, we employed various advanced techniques such as data missing at random (MAR) with Bayesian dynamic conditional imputation for addressing missing records, synthetic minority oversampling technique for data imbalance issues, and categorical boosting (CatBoost) combined with SHapley Additive exPlanations (SHAP) for determining and analyzing the importance and dependence of risk factors on injury severity. Additionally, exploratory feature analysis was conducted to uncover hidden spatiotemporal elements influencing traffic accidents and injury severity levels. We developed several predictive models in the second phase, including eXtreme Gradient Boosting (XGBoost), random forest (RF), deep neural networks (DNN), and fine-tuned parameters. Using the SHAP approach, we employed model-agnostic interpretation techniques to separate explanations from models. In the final phase, we provided an analysis and summary of the system-level taxonomy across feature categories. This involved classifying crash data into high-level causal factors using aggregate SHAP scores, illustrating how each risk factor contributes to different injury severity levels
Nonmarket Negotiations: Leveraging performance when negotiating with Governments, Influencers, Media, NGOs, Communities and other key stakeholders
No full textInternational audienceThis work highlights the primary effects of externalities on businesses, organizations, and teams. It then discusses the necessity for adapting and complementing traditional concepts, models, and theories of negotiation in this increasingly diverse and complex nonmarket arena. A third topic focuses on strategic negotiations with Governments, one of the most potent components among nonmarket forces. Finally, the work provides a list of practical recommendations for negotiators in the new era of externalities’ impacts and nonmarket prominence
Facebook’s Influence on Effectiveness of Digital Advertising among Malaysian Youth
No full textInternational audienceThe growth of advanced technology has contributed to the digital advertising industry as Facebook's users are easily connected, and purchasing behaviours will be developed with the content of the products promoted in digital advertising. The older generation prefers traditional advertising due to technology's security and privacy aspects, leading to fewer choices in purchasing products. This study aimed to identify the relationship between the influence of Facebook and the effectiveness of digital advertising among Malaysian youth in Klang Valley. It was anticipated that this research would provide helpful information to the public and assist researchers in the future based on the findings of this topic area. Data was collected using a Google Form and distributed via social media like WhatsApp. The targeted respondents are between 15 and 34 years old and are located in the Klang Valley area. Statistical Package for the Social Sciences (SPSS) version 27 system was used to determine digital advertising characteristics electronically. T-test and ANOVA tests were applied in this study to examine the demographic factors that affect the relationship between the variables, as different backgrounds influence the perspectives and behaviours of the users. The findings show that the independent variable, the influence of Facebook, has a strong correlation with the dependent variable, the effectiveness of digital advertising among Malaysian youth in Klang Valley (r= 0.770). Socio-demographic factors such as age and educational level had an effect on the relationship between the variables. The effectiveness of digital advertising is influenced by the number of likes, comments, and shares by Facebook users
Green drives greenbacks: The impact of sustainable innovation on corporate cash holdings in BRICS nations
No full textInternational audienceThis study delves into the impact of sustainable innovation on corporate liquidity, specifically examining its influence on cash holdings among companies listed in BRICS nations. The study also explores the impact of green innovation on cash holdings before and after COVID-spread. Utilizing the system GMM regression technique on data spanning 2010 to 2022, we scrutinize the relationship between green innovation and cash reserves. Our findings reveal a significant correlation, showcasing that companies actively engaged in sustainable practices maintain lower levels of cash. This suggests a tangible reduction in the necessity for large cash reserves among businesses prioritizing green innovation. Notably, this effect persists even in the post-COVID landscape, highlighting the resilience of sustainability efforts on financial strategies. The influence of green innovation on cash holdings remains robust with diverse firm-specific and macroeconomic variables. The implications underscore the dual benefits of sustainable innovation, contributing not only to environmental sustainability but also enhancing financial efficiency by minimizing excess cash holdings. This study accentuates the imperative of integrating sustainability considerations into financial decision-making, offering practical insights for firms seeking to align sustainability goals with effective financial management. It provides valuable insights for policymakers and investors interested in promoting and supporting green initiatives. This study contributes to the evolving discourse on sustainability and corporate finance by shedding light on a relatively unexplored aspect of the association between green innovation and financial strategies
Perceived Benefits of Plant-Based Diets
No full textInternational audienceUne transition globale vers des alimentations végétales pourrait considérablement atténuer l’impact négatif du système alimentaire actuel sur l’environnement, la santé et le bien-être animal. Alors que les campagnes d’informations sont devenues un outil privilégié des décideurs politiques et des spécialistes des sciences sociales pour inciter les consommateurs à adopter une alimentation plus durable, de nombreuses zones d’ombre demeurent quant aux connaissances de la population sur les avantages de l’adoption d’alimentations végétales. Dans ce travail, nous étudions les connaissances d’un échantillon représentatif de la population française ( N = 715) quant aux mérites relatifs des alimentations végétales vis-à-vis de l’environnement, la santé et le bien-être animal. Nous montrons que les Français ont en moyenne une bonne connaissance de l’impact environnemental relativement moindre des alimentations végétales (gaz à effet de serre, utilisation des sols) mais sous-estiment considérablement leurs bénéfices sur la santé. Nous constatons également que les Français sous-estiment considérablement la prévalence de l’élevage intensif et, par conséquent, les avantages d’adopter une alimentation végétale pour les animaux. Nos résultats montrent que la société est principalement divisée en deux groupes : les individus qui ont une opinion positive des alimentations végétales dans tous les domaines, et ceux qui y voient moins d’avantages tous les domaines. Nous discutons des implications de ces résultats pour les campagnes d’information visant à modifier les alimentations. JEL codes : Q10, Q1