David Marius Gligor

This study investigates how Performative Artificial Intelligence (AI), an active form of AI that enacts phenomena, boundaries, and control, supports supply chains in building temporal resilience. Temporal resilience is examined through three main responses: adjusting, absorbing, and adopting. We further explore how the intensity of extreme event contexts, namely emergency and disruptive contexts, moderates these relationships. Using a mixed-methods design, the study draws on survey data from 252 U.S. business-to-business (B2B) organizations and qualitative insights from 53 structured interviews. The findings demonstrate that Performative AI contributes to all three temporal resilience responses, with the strength of most of these relationships influenced by the intensity of the extreme event context. This research primarily contributes to the supply chain literature by conceptualizing and empirically validating Performative AI as a resilience enabler in technologically mature B2B environments, and by extending temporal resilience theory to organizational and supply chain levels. The study also highlights the growing importance of AI for organizations and supply chains to respond effectively to disruptions, mitigating the impact on their time-based operations. •Introduces “Performative AI” as active AI that enacts actions and boundaries to enhance resilience.•Examines temporal resilience via adjusting, absorbing, and adapting in supply chains.•Uses mixed methods: survey data from 252 U.S. B2B firms and 53 structured interviews.•Finds Performative AI strengthens resilience, moderated by intensity of extreme events.•Extends resilience theory, positioning Performative AI as key to adaptive supply chains.

As tariffs rapidly emerge as a prominent yet potentially divisive topic in management education, there is a notable lack of literature assessing student views of tariffs, including antecedents and outcomes. This gap leaves management faculty under-equipped to help students critically process global trade dynamics, including trade conflicts. To fill this gap, we apply Social Identity Theory to compare U.S. business student and consumer survey data, evaluating the role of consumer ethnocentrism (CE) in shaping support for tariffs on the largest U.S. trading partners in Canada, Mexico, and China. Overall, CE levels are modest for both students and consumers, though statistically higher for consumers. Structural equation modeling (SEM) reveals that higher CE broadly correlates with stronger support for tariffs regardless of the trading partner. Nevertheless, tariff support is not correlated with willingness to pay for these tariffs. This disconnect signals a possible fundamental misunderstanding of tariffs as well as the larger concept of global trade. To bridge this gap, we describe a simple, effective, and flexible class exercise (“American Cars”) to pique students’ interest in the complexity of global supply chains, including tariffs and misconceptions about supposed “domestic” versus “foreign” goods. •While tariffs are prominent and divisive, limited pedagogical literature exists.•Limited differences in tariff views between U.S. students and consumers were found.•Consumer ethnocentrism is linked to support for tariffs on Canada, Mexico, and China.•Support for tariffs is not linked to a willingness to pay more for foreign goods.•We present an exercise to help students process the complexity of global trade.

This paper examines whether corporate ESG reporting genuinely reflects authentic sustainability commitments or serves as virtue signaling intended to secure legitimacy. To address this question, we employ a multi-study, multi-sample design that combines thematic, linguistic, and quantitative analyses of corporate sustainability communication. In Study 1, we map the thematic content of sustainability reports, revealing how firms emphasize environmental and social responsibility while often downplaying governance aspects. In Study 2, cluster analysis of the Corporate Knights Global 100 identifies three ESG signaling profiles, Environmental Stewards, Pragmatic Legitimizers, and Balanced Performers, highlighting heterogeneity in the ways firms frame their commitments. A comparative analysis of Fortune 500 companies demonstrates that authenticity and analytic tone do not differ significantly between sustainability exemplars and mainstream corporations, suggesting that sustainability reporting may be subject to homogenized rhetorical norms. In Study 3, a cluster analysis of Fortune 500 firms links ESG risk scores with financial variables, showing that large, high-asset firms often emphasize governance and environmental proxies as part of investor-oriented legitimacy strategies, whereas mid-sized firms adopt more balanced profiles. Collectively, the three studies demonstrate that while some firms integrate authentic sustainability commitments across ESG dimensions, others selectively emphasize measurable indicators, risking perceptions of greenwashing. By triangulating thematic, linguistic, and performance-based evidence, this paper advances understanding of how ESG communication simultaneously functions as a signaling device and a legitimacy-building mechanism, and it underscores the importance of distinguishing authentic engagement from virtue signaling in stakeholder evaluation.

PurposeThis study examines how medical quality indicators and transportation/logistics conditions jointly affect the probability of deceased-donor kidney discard. While previous research has focused on clinical factors, this research quantifies the added impact of distance, airport accessibility and temporal coordination on discard decisions.Design/methodology/approachWe analyzed a retrospective panel dataset of deceased-donor kidneys from UNOS Region 4 (2001-2021) using binary logistic regression and pooled logit models with year fixed effects and time-varying interactions. Medical variables, including kidney donor profile index (KDPI) and cold ischemia time, were combined with logistical variables, including donor-to-transplant center distance, airport category, time of day and day of week. We reported results with log-odds coefficients and average marginal effects for better managerial interpretability. Robustness checks addressed multicollinearity and extreme-value sensitivity.FindingsHigher KDPI and longer cold ischemia time significantly increase the probability of organ discard. Key logistics variables include donor-to-transplant distance and airport accessibility; organs from non-hub and small-hub airports have higher discard rates than those from large-hub airports, even after accounting for medical risk. Temporal controls reflect system-level shifts over the years, whereas time-of-day and weekday effects remain weak. Interaction analyses reveal that logistics burdens disproportionately impact marginal-quality organs.Originality/valueThe study conducts an integrated, multidisciplinary examination of clinical risk and transportation infrastructure for kidney discard within a single empirical framework. By translating coefficients into probability-scale AMEs, the research provides actionable insights for allocation design, transport planning and infrastructure prioritization. Findings extend healthcare supply-chain theory to a high-stakes, perishable-asset context, demonstrating that accessibility and coordination constraints significantly affect medical utilization outcomes.

Mediation analysis tests whether the effect of an independent variable on an outcome is transmitted through an intervening variable, offering insights into the mechanisms that shape complex relationships. It is widely applied in marketing research, and over time, several approaches have been developed to test mediation (e.g., Baron and Kenny’s method, the bootstrap, and the joint significance test). However, some applications contradict the principles of these methods, undermining both theory building and managerial decision-making. To our knowledge, this is the first systematic literature review of mediation analysis in marketing research. We evaluate current practices, identify common pitfalls, outline steps to avoid them, and assess the strengths and weaknesses of widely used approaches. Drawing on 2209 distinct studies identified within 1,870 articles across 20 leading journals (2013–2023), we employed a structured screening and coding process. Our results provide methodological guidance to improve rigor, transparency, and both theoretical and practical relevance of future mediation analyses in marketing research.

While AI use in supply chain (SC) management is widely acknowledged to render some SC jobs redundant, little is known about the influence of this dynamic on boundary-spanning employees (BSEs). With this in mind, we specifically evaluate the effects of AI-induced displacement of boundary-spanning roles, as links for critical tacit knowledge, on SC innovation. We adopt a three-stage mixed-method approach. First, we interviewed SC professionals. Second, we collect SC practitioner survey data and analyse it using structural equation modelling. Then, probe further via follow-up interviews in phase 3. We find that, in addition to influencing SC innovation, BSEs are instrumental in exchanging tacit knowledge with SC partners and ensuring trust in SC partners, revealing the complex relationship between AI-induced BSE displacement and interfirm trust. The study extends social network theory by showing that qualitative attributes of business ties are more important than quantitative attributes when sourcing external innovation. Our findings reinforce actor-network theory (ANT) by highlighting the role BSEs leveraging non-human 'actors' -like technology- play in interorganizational collaboration. The ensuing contributions emphasize the role of BSEs as part of a human-AI hybrid, providing insight into the need for an optimal human-AI balance in the SC to ensure continuing innovation.

Purpose
Disaster immunity capability has been demonstrated to benefit firms during supply chain disruptions. However, research on how supply chain digitalization provides data to assist firms in achieving immunity capability is lacking. Supply chain digitalization focuses on the application of digital technologies (e.g. the Internet of Things (IoT), artificial intelligence (AI) and blockchain) to optimize supply chain operations. This paper aims to answer the research question: How can supply chain digitalization contribute to organizational disaster immunity capability?

Design/methodology/approach
We propose a research model based on dynamic capabilities theory to address the research question by exploring relationships between supply chain digitalization, process integration, innovation speed and disaster immunity capabilities. Two empirical studies, a survey and a vignette-based experiment, provide empirical support using data collected from manufacturing and service companies to test the proposed model.

Findings
The results demonstrate that supply chain digitalization significantly enhances disaster immunity capability through the mediating effects of supply chain process integration and innovation speed.

Originality/value
This study contributes to existing literature by introducing supply chain process integration and innovation speed as mediating variables that explain how digitalization leads to disaster immunity capability. This paper provides practical, actionable insights for organizations to prepare for future disasters and make informed decisions.

Purpose
As organizations increasingly adopt interorganizational information systems, the subsequent impacts on organizational capabilities and the potential displacement of employees remain unclear. To address this gap, this study aims to evaluate the effects of such adoption on boundary-spanning employees who collaborate with supply chain partners.

Design/methodology/approach
We develop grounded theory via the Straussian approach with guided, semi-structured interviews with mid- to senior-level supply chain executives.

Findings
Interorganizational information systems cannot do the job alone. Such systems can automate some operational processes formerly performed by boundary spanners but also elevate strategic boundary-spanner responsibilities in knowledge exchange and trust building with supply chain partners. The combined interorganizational information systems-human solution enhances collaboration with supply chain partners, improving organizational knowledge management and agility capabilities while enhancing organizational performance and innovation.

Originality/Value
The theoretical framework highlights how the unique and complementary competencies of interorganizational information systems and boundary-spanning employees are best suited for collaborative activities to improve supply chain capabilities.

Organizations are increasingly applying artificial intelligence (AI) in interorganizational systems (IOS) to mitigate demand and supply disruptions. This shift towards AI to enhance supply chain agility capabilities automates some tasks previously undertaken by boundary-spanning employees who serve as critical informational and influential links with supply chain partners. Given limited related research, we investigate the impact of AI not only on the potential displacement of boundary-spanning employee roles but also on subsequent supply chain agility. Leveraging dynamic capabilities and social network theories, we first conducted interviews with supply chain executives to develop a practitioner survey. Following a mixed-methods approach, we next applied structural equation modeling to this survey data and then probed further via follow-up interviews. The results reveal that despite displacing some employees, the use of AI in IOS enhances the remaining operational and strategic roles of the boundary-spanning employees to enrich supply chain agility. The ensuing theoretical and managerial contributions emphasize the essential role of boundary-spanning employees as part of a hybrid human-AI solution, providing insight into the need for an optimal human/AI balance in the supply chain to cope with dynamic marketplaces.

As blockchain technology reshapes operations and supply chain management (OSCM), understanding its capability-driven adoption pathways is crucial for enhancing supply chain efficiency, resilience, and decision-making. This study applies Fuzzy-Set Qualitative Comparative Analysis (fsQCA) within the Technology-Organisation-Environment (TOE) framework to analyse data from supply chain managers with blockchain implementation experience. Our findings reveal three adoption pathways: (1) Dynamic Collaborators, who integrate blockchain through external collaboration and agility; (2) Resilient Specialists, who prioritise internal resilience over partnerships; and (3) Proficient Collaborators, who emphasise information sharing and agility without deep IT integration. These results highlight the causal complexity of blockchain adoption, demonstrating that firms follow multiple strategic configurations based on their capability portfolios. By uncovering scalable, context-specific adoption pathways, this study provides actionable insights for managers and policymakers, advancing both blockchain integration strategies and the broader OSCM literature.