ICN Business School

This article sheds light on often overlooked organizational antecedents that build supply chain resilience by drawing on knowledge management theory and the resource-based view because of their focus on exploitation and exploration as capabilities related to organizational learning. It was examined whether the relationships between supply chain ecocentricity and supply chain exploitation and exploration practices enable supply chain resilience. It was also determined whether environmental uncertainty would affect the relationship between these enablers and resilience. Manufacturing companies operating in France were surveyed and variance-based structural equation modeling was used to analyze primary data from 405 completed questionnaires. Ecocentricity, driven mainly by secondary stakeholders, was found to influence supply chain resilience as well as the exploitation and exploration of resources and capabilities, confirming that they are enablers of supply chain resilience. Firms should be aware that secondary stakeholders cannot be neglected in the supply chain network, because they contribute to knowledge management and a better understanding of market contingencies and in turn improve supply chain resilience. The original contributions of this article are to demonstrate the relevance of the ecocentricity perspective and its role in helping achieve resilience in supply chains.

Groups and communities have been key topics in the information systems (IS) research agenda. While communities are assumed to emerge at the intersection of overlapping groups and their practices, prior research has mainly focused on their dynamics and evolution. This has resulted to limited empirical support regarding the emergence of communities. We address that lacuna by tracing the emergence of communities through the prism of resource mobilization theory. In doing so, we make use of a unique longitudinal dataset and incorporate Topic Modelling, Bipartite Network Analysis, and Community Detection. We show that new communities are formed at the intersection of overlapping groups and practices. In addition, we contribute to the IS literature by demonstrating that their emergence occurs due to resource mobilization that gives rise to a shared mindset. We also reveal that multiple resources are incorporated into the practices of an emerging community. By combining large datasets and innovative computational approaches, we help IS theory and practice to move away from traditional "what" questions towards the more insightful "how" ones. We discuss the theoretical and practical implications of our work and delineate an agenda for future research on the topic.

The assumption that generativity engenders unbounded growth has acquired an almost taken-for-granted position in information systems and management literature. Against this premise, we examine the relationship between generativity and user base growth in the context of a digital platform. To do this, we synthesize the literature on generativity into two views, social interaction (expansion of ecosystem boundaries) and product view (expansion of product boundaries), that jointly and individually relate to user base growth. Both views help us explain how opening a platform relates to the emergence and resolution of conflicting expectations in a platform ecosystem that result in new functions and expanded use. We adopt a panel vector autoregressive approach combining data from six large transaction platforms that engaged with open-source developer communities. We found that the dominant narrative of generativity engendering growth, although generally supported by our analysis, obscures the fact that the inverse is also true; that is, growth can lead to expansion of product boundaries (inverse generativity) and that generativity can be bounded; that is, growth can stabilize ecosystem boundaries (bounded generativity). Against this background, we propose an extended generativity theory that presents generativity and growth in an integrative view and raises awareness about the limitations of the “unbounded growth” claim. We conclude that there is value in separating the two views of generativity conceptually and analytically, along with their relationship to user base growth, and we call for research on the pathways through which generativity produces growth. History: Ola Henfridsson, Senior Editor; Robert Wayne Gregory, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.1209 .

We provide the first empirical study on the role of panic and stress related to the COVID-19 pandemic, including six uncertainties and the four most traded cryptocurrencies, on three green bond market volatilities. Based on daily data covering the period from January 1, 2020 to January 31, 2022, we combine Diebold and Yilmaz's (2012, 2014) time domain spillover approach and Ando et al.'s (2022) quantile regression framework to investigate the time-frequency spillover connectedness among markets and measure the direction and intensity of the net transmission effect under extreme negative and positive event conditions, and normal states. We further provide novel insights into the green finance literature by examining sensitivity to quantile analysis of the net transfer mechanism between green bonds, cryptocurrencies, and pandemic uncertainty. Regarding the network connectedness analysis, the results reveal strong net information spillover transmission among markets under the bearish market. In extremely negative event circumstances, the MSCI Euro green bond acts as the leading net shock receiver in the system, whereas COVID-19 fake news appears as the largest net shock contributor, followed by BTC. According to sensitivity to quantile analysis, the net dynamic shock transfer mechanism is time-varying and quantile-dependent. Overall, our work uncovers crucial implications for investors and policymakers.

We empirically examine the relationship between business regulation and total (i.e., formal and informal) entrepreneurship using a unique panel data set. We estimate separate regressions for opportunity-driven and necessity-driven nascent entrepreneurship as well as young business entrepreneurship based on two different estimation methods (pooled OLS and system GMM). Our results show that business regulation generally rather hinders entrepreneurship. If we additionally consider the development stage of countries, we find different results for high-income and lower-income countries: first, we surprisingly find that stricter employment protection legislation positively affects entrepreneurship in lower-income countries where the informal sector is larger. This might be because more rigid employment laws make waged employment less attractive to employers, who thus push employees into dependent or informal self-employment. Second, we find that stricter insolvency regulation hinders entrepreneurship only in high-income economies. In lower-income economies, where there are more unregistered businesses, insolvency laws might be more difficult to enforce, so entrepreneurship rates are less affected. Third, we find that government intervention in the form of high-quality governmental support programs stimulates opportunity nascent and young business entrepreneurship. This relationship is apparent only in high-income countries, where the formal sector is larger, as such programs typically address formal rather than informal entrepreneurs. Governmental support programs may thus reach the goal of facilitating entrepreneurship only in high-income economies.

Climate has traditionally played an important role in the development of countries, owing to its inherent relationship with agricultural output and pricing. This study explores one such association between the most well-known climate anomaly, the El Niño34 Southern Oscillation, and international commodity prices of agriculture and food indexes. This study addresses the potentially causal effect of El Niño34 on international agricultural and food stock prices. To do so, we develop a novel approach: the empirical mode decomposition variable-lag transfer entropy (EMD-VL transfer entropy) by combining the variable-lag transfer entropy framework and the empirical mode decomposition. The evidence reveals the following major results. First, climate shocks affect global agricultural stock prices in the short-term. Second, significant transfer entropy from El Niño34 to food index appeared at mid- and long-term business cycles. Third, unidirectional causal effect from climate shocks to agricultural and food stock prices is more intense in the short business cycle attesting to the impact of climate shocks on the food market, which is especially visible in the short-term horizon. Finally, our proposed method exceeds the traditional variable-lag transfer entropy by detecting such causal interplay at various business cycles, which is useful for investors and policymakers.

In this work, we address an optimized integrated maintenance strategy and spare parts management problem for wind turbine system, with an observable level of degradation. The purpose of the study consists in establishing an improved maintenance strategy integrating a spare parts policy, according random production of energy over a given period. The wind turbine system failure rate is being modeled as a function of the current operating mode. Therefore, an improved maintenance strategy, characterized by a switching between both perfect and imperfect preventive maintenance actions, is developed and optimized. Formally, our objective is realized by the optimization of a total cost integrating maintenance action and spare parts management over a finite planning horizon, with considering the impact of the production rate on wind turbine system failure rate. A numerical study is realized in order to proof the robustness of the analytical model developed.

In this paper, we present an integrated production-maintenance scheduling problem with economic and ecological considerations. The contribution of our study consists in developing a new analytical model which determines, an optimal sequence of production and maintenance minimizing earliness and tardiness penalty costs as well as harmful emissions (CO2) cost due to degradation of production system. This study addresses the problem of the single machine where the machine follows a failure law. Each time the machine's degradation rate reaches a predefined threshold (λthreshold), preventive maintenance (PM) is carried out throughout optimal periods. The maintenance strategy adopted makes it possible to define the age of preventive maintenance T* corresponding to a minimum total cost of preventive and corrective maintenance. We consider the result of this strategy as a strong constraint in order to determine an optimal integrated scheduling of production and maintenance. We provide illustrative numerical examples as well as sensitivity analysis to show the applicability of our approaches and provide.

We examine the directional predictability of energy stock returns on exchange rates and stock market in the E7 + 1 emerging market economies, which include India, China, Indonesia, South Korea, Turkey, Brazil, Mexico, and Russia, over the period 4 January 2000 to 31 May 2018. To achieve this, we carried out a cross‐quantile analysis in the static and dynamic frameworks, using the bi‐variate cross‐quantilogram (CQ) and the partial cross‐quantilogram (PCQ) approaches and a dynamic variant of such approaches. The predictability of the stock returns on the energy prices for WTI, Brent, OPEC, heating oil and natural gas is examined. Further relationships are also conditioned by using two measures of geopolitical risk, including the general geopolitical risk (GPRD), and the geopolitical risk threats (GPRD_Threat). The overall results highlight the importance of employing the PCQ approach in examining the predictability of different pairs of the energy prices, exchange rates and stock markets. They also indicate that controlling for GPRD and GPRD_Threat significantly improves the predictability of these variables. Policy implications of the empirical findings have been elaborated and discussed.

With the increasing prominence of digital media, retailers attempt to attract consumers to their websites by investing in sponsored search advertising. However, due to stiff competition among retailers, sponsored search advertising can be expensive. This paper develops a multi-period, dynamic programming model that provides a retailer with an optimal portfolio of generic and branded bids. We model two critical aspects of consumer search behavior: (i) the spillover effect of generic searches leading to branded search arrivals in subsequent periods and (ii) the memory effect that leads to a decline of consumer awareness of a brand over time. We find that the retailer can effectively shuffle his investments on generic and branded keywords depending on several consumer parameters, e.g., awareness level, brand retention and reservation price variances. We develop a bidding policy framework to highlight the shift in bid shares from generic to branded at different levels of consumer awareness. We find that harnessing the benefits of spillover from generic to branded keywords allows the retailer to save on generic bids at higher awareness and retention levels and lower variance in consumers’ reservation prices. Further, we extend our model to different consumer purchase situations/ product classifications, viz., Convenience, Shopping and Specialty purchasing. Our analysis suggests prevalence of generic bids for certain purchase/product situations, whereas branded bids remain salient in other situations.

In this study, we attempt to revisit how dependent the US stock market returns are on climate change related risks (CCRR). In this regard, we use a spillover and connectedness network analysis to assess the strength of the causal effect and transmission pathway of CCRR proxies (green index, carbon price, general and climate uncertainty) on US Small Minus Big (SMB) and High Minus Low (HML) factors. Statically, our findings reveal that the indexes of the clean energy and new energy innovation industry (green companies) and climate policy uncertainty are drivers of the transmission spillover network, especially in extreme market scenarios. Dynamically, CCRR proxies act as net contributors and/or net receipts of shock spillovers over time and across the quantiles of the joint distribution. We further find that the spillover connectedness network is very sensitive to market states and that the strength of the effects of CCRR proxies are more pronounced under bust and boom markets. Our findings are beneficial for environmental investors and policymakers responsible for portfolio diversification strategies.

Although the literature has documented the positive effects of empowerment strategies (empowerment to create and to select) for companies, the relative evaluation of these strategies as perceived by participants and nonparticipants has been neglected. Based on two qualitative studies ( N = 23), we show that participants engaged in empowerment campaigns value the empowerment to select (vs empowerment to create) more if they have low self-confidence and limited expertise relating to the requested task. In addition, we emphasize that the empowerment to create provides a richer overall experience for participants compared with the empowerment to select. Nonparticipants have a better evaluation of empowerment-to-create campaigns because of a stronger authenticity of the brands launching them and a more positive evaluation of participating consumers’ motivations. This research provides managerial recommendations for the successful deployment of empowerment strategies.

The current research explores the residential energy use and residential energy expenditure behavior, induced by ethnic diversity, income inequality and climate characteristics. In doing so, the authors use the data on United States from 1984Q1 to 2020Q4 and employ the recent multiple wavelet and quantile coherency methods. Based on the pairwise wavelet coherency results we find that as far as the coherence across the pairs-- residential energy use vs. ethnic tensions again residential energy use vs. socio economic conditions, and residential energy vs. GINI measure of inequality is concerned there are indications of strong coherence during the short and medium term. The coherencies get intensified during periods of 2001, 2009 and 2020. The direction of arrows was left ward oriented demonstrating that lack of energy expenditure or alternatively speaking energy poverty precedes ethnic crisis. In contrary there are strong pairs of negative correlation in the (0.95|0.95) quantiles for residential energy expenditure and the interaction term on heating and cooling. Such findings imply that conditions of buildings are major drivers on the energy expenditure across time scales. The findings on hand are in line with the COP 26 declarations and report practical implications apropos the achievement of sustainable development goals.

Research on hybrid organization (HO) has grown rapidly over recent decades, yet the conceptualization and research structure remain fragmented. In this paper, we employ a combination of bibliometric analysis and a structured review of recent influential articles to evaluate the domain of HO. As part of the bibliometric analysis, we analysed 676 documents containing 51,014 references by applying citation, co‐citation, and social network analysis (SNA) techniques. Based on our analysis, we identified the 108 most influential works shaping the domain and explored the linkages between them to uncover the intellectual structure of the domain. Specifically, we observed five different clusters that depicted the intellectual structure of the HO domain. Our result further clarified the overall centrality features of the HO research network. Further, the structured review resulted in the identification of six different themes: impact of organizational actors on HO, impact of the external environment on HO, hybridization process and organizational response, organizational structure and governance, organizational strategy, and organizational performance. Building on our results, we propose a framework and explicate the gaps for future HO research.

Cryptocurrency values have recently fallen substantially. Why? We examine the impact of attention on the Russia-Ukraine War, proxied by Google Trends, on cryptocurrencies (and equity) to measure the returns coherences. Using quantile cross-spectral analysis and daily data for February 24, 2022–June 21, 2022, we observe that co-movements between War attention and cryptocurrencies depends on investment horizon and market state. Under bearish and normal (bull) markets, War attention negatively (positively) affects all cryptocurrencies in the short term. Results are consistent with cryptocurrency investors responding to War attention by seeking liquidity, with recent price falls explained as sell-offs by large holders.

This study investigates the relationship between in-store social atmospherics (crowd and employees), satisfaction, and intention to revisit the store and word-of-mouth. We propose a conceptual framework based on the SOR model, considering crowd and employees as the stimuli, satisfaction as the internal response, and intention to revisit and word-of-mouth as the response. We conducted a quantitative study and surveyed 422 Abercrombie & Fitch store customers, and we used a regression method. The results show that social atmospherics positively impacts satisfaction, relational variables and satisfaction mediating effects. Our contribution is to confirm the relevance of the SOR, the positive relationships between store employees and crowd on satisfaction, and between satisfaction and intention to revisit, word-of-mouth, and the mediating role of satisfaction.