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This study aims to develop an integrative framework for strategic intelligence (SI) tailored to guide companies navigating systemic disruptions within global supply chains, identifying key determinants for its effective deployment. Current literature on management systems addresses SI components individually, hindering a precise definition and implementation strategy. This systematic review aims to fill these gaps by establishing a conceptual model of SI capability, emphasizing the interdependence of its dimensions.

Following the Joanna Briggs Institute (JBI) mixed-method analysis approach and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, this systematic review synthesizes empirical studies, conceptual papers, mathematical models and literature reviews on SI capability dimensions. It adopts a flexible approach to explore SI within supply chain resilience during systemic crises.

The study enhances and broadens the field of dynamic capabilities (DCs) by advancing knowledge on SI as a dynamic capability inducing resilience within supply chains facing systemic risks. Additionally, it synthesizes and offers perspective on a rapidly expanding body of literature from the past three years, identifying emerging trends and gaps.

This research focused on three capacities: Supply Chain Visibility (SCV), Environmental Dynamism (ED) and Timely Seizing and Detection-Making (TSDM). While other dynamic capabilities may enhance SC resilience (SCR), this study emphasized the analytical and decision-making dimensions critical for improving SCR.

This systematic literature review introduces a novel conceptual framework, providing a foundation for empirical investigations. By offering an integrated theoretical perspective, the study proposes actionable research propositions and insights into SI’s strategic role in crisis management within supply chains.

This paper investigates whether resilience capabilities influence manufacturing performance dimensions. Specifically, it empirically analyses how supply chain agility, alertness, adaptability and preparedness affect manufacturing firms’ operational and sustainable (economic, social and environmental) performance aspects.

The paper employed a deductive approach and an explanatory design. It gathered survey data from 285 managers in 5,329 Ghanaian manufacturing firms and analysed it using structural equation modelling.

The study found resilience capabilities comprising agility, alertness and adaptability to significantly and positively predict changes in manufacturing firms’ sustainable (environmental, economic and social) and operational performance. However, the preparedness capability positively impacts the firms’ operational and environmental performance, not economic and social.

This paper is restricted to Ghana’s manufacturing industry. Underpinned by the dynamic capabilities theory and extensive empirical reviews, the model was developed with four resilient capabilities and four manufacturing performance dimensions.

The study highlights the relevance of resilience in today’s highly disruptive manufacturing environment for achieving sustainable and operational performance. It encourages manufacturing firms to prioritise heavy investments in alertness, adaptability and agile capabilities to overcome supply chain disruptions and enhance sustainable and operational excellence. It also offers significant insights for policymakers, managers and industry players to advance resilience capabilities and swiftly detect and recover from emerging disturbances in manufacturing supply chains, leading to higher performance.

The study contributes to resource conservation and a more sustainable future by projecting resilient capabilities in today’s disruptive environments. The shift towards SCR can influence public attitudes and opinions toward manufacturing and contribute to firms’ sustainability goals.

This study is the first to investigate the linkages between resilient capabilities and performance aspects simultaneously in less developed economies like Ghana. In these economies, manufacturing supply chains often face varying risks that continue to disrupt their operations and sustainability goals.

This paper aims to explore the hierarchy of motivations behind Chinese young wine consumers’ wine-purchasing behavior.

This study used a random and snowball sampling technique to collect data from Chinese young wine consumers. Ultimately, 840 participants were included, representing diverse geographic regions across China. The gathered data was analyzed to explore wine customer behavior using SPSS and AMOS.

The hierarchical structure of motivations guiding young consumers’ wine consumption becomes apparent when analyzed across ascending levels: from considerations of health benefits and emotional assessments to social interactions and status symbols. These factors wield significant influence over the purchase of wines among Chinese young wine consumers. Moreover, these consumption motivations notably impact consumption behavior by mediating through consumption intentions.

This study integrates the theory of planned behavior with Maslow’s hierarchy of needs, systematically identifying four primary motivations that hierarchically influence wine consumption among Chinese young wine consumers. It empirically validates the relationships between motivations, intentions and behaviors, underscoring intentions as a mediating factor linking motivations and behaviors.

The emergence of blockchain technology has the potential to bring about transformative changes in various industries, with supply chain management being a prominent domain of application. This study investigates the strategic performance benefits of using blockchain-enabled traceability systems for improving supply chain quality management.

The present study employed structural equation modelling to analyse data obtained from 200 practitioners working in Indian pharmaceutical companies.

The results reflect that blockchain-enabled traceability systems have a positive impact on multi-tier quality governance (MQG); supply chain process alignment and coordination (SPAC) and quality centric collaboration (QCC); all of which are the facets of supply chain quality management. Furthermore, when examining the impact of blockchain-enabled traceability systems on firm quality performance and economic performance, the mediation role of SPAC and QCC was confirmed, whereas the mediation role of MQG could not be established.

The study’s empirical insights offer practical guidance for pharmaceutical manufacturers, regulators and other industry participants seeking to harness the potential of blockchain technology for creating resilient and transparent supply chains that uphold product quality and safety standards.

These findings underscore the significance of blockchain-enabled traceability systems in revolutionizing supply chain quality management practices to achieve superior strategic performance in the pharmaceutical sector.

In the face of frequent supply chain disruptions, this study aims to identify the relationships between human capital (HC), digital supply chain practice (DSCP) and supply chain robustness and resilience (i.e. SCRO and SCRE).

To examine the proposed conceptual model based on the resource-based view and organizational information processing theory, an empirical study was conducted using a sample of Chinese manufacturers. Hierarchical regression is applied to understand the direct effect, mediating effect and moderating effect among HC, DSCP, SCRO, SCRE and digital culture.

The results reveal that HC positively influences digital maturity and supply chain resilience. DSCP positively affects both SCRO and SCRE. However, HC does not significantly influence the adoption of digital tools, and only employees’ capital has a positive relationship with SCRO. In addition, the moderating effect of digital culture on the relationship between HC and DSCP was examined.

As an early exploration of the relationships among HC, DSCP, SCRO and SCRE, this study enriches the literature by offering new insights and responding to the call for more empirical research and theoretical application. It emphasizes the importance of HC and DSCP as strategic resources and highlights the need for a digital culture to implement DSCP.

The increasing complexity and globalization of supply chains raise risks such as human rights abuses and environmental damage while affecting their supply chain performance (SCP), which prompted a study on supply chain due diligence (SCDD) practices. This study examines the impact of SCDD practices on the SCP. It examines if and how these relationships can be influenced by factors such as organizational culture and trust.

A conceptual model and hypotheses based on institutional theory were developed. The survey instrument captures organizations' perceptions of SCDD practices and related key performance indicators for SCP. The study collects data from 329 supply chain and logistics managers in Indian manufacturing and logistics organizations, and the hypotheses are validated using a structural equation model.

Results indicate that SCDD practices positively influence SCP. Trust and organizational culture strengthened SCDD–SCP relationships.

The study explores how organizations perceive and implement due diligence in their supply chains, highlighting areas for improvement. This understanding could help organizations enhance their supply chain management strategies, leading to better risk management, cost reduction, avoiding penalties and improved overall performance.

The main contribution of the study is to examine organizations' perceptions of SCDDA implementation and then identify its effects on supply chain performance. This is done considering trust and organizational culture as moderating factors.

This research examines the influence of the digital voice of consumers (DVoC) on the resilience of supply chains (SCR) within the renewable energy sector. The main goal is to identify and highlight the crucial aspects that enable the examination of this impact.

A comprehensive literature analysis was performed utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach to ascertain pertinent factors. This research utilizes a comprehensive methodology that merges interpretive structural modeling (ISM) with Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis to assess the discovered variables.

The study identified 16 factors that contribute to both DVoC and SCR. Key influential factors include top management support, collaboration, feedback influence and flexibility. These factors play a significant role in enhancing SCR by facilitating better adaptation and response to disruptions.

The study is confined to the renewable energy sector and may lack generalizability to other businesses without additional validation. Subsequent studies ought to investigate the implementation of these findings across various industrial contexts to enhance comprehension of DVoC’s influence on SCR.

This study presents a new integrated framework for comprehending the function of DVoC in improving SCR. It presents significant practical consequences for stakeholders in the renewable energy sector, such as researchers, regulators, manufacturers and consumers, highlighting the necessity for a resilient and flexible supply chain.

It is found that previous studies only focus on how digital transformation contributes to individual firms’ green innovation performance while ignoring the important role that it plays in the spillover and diffusion of green innovations among peer firms. Therefore, this study aims to investigate the influence of focal firms’ digital transformation on the spillover of green innovation among peer firms in heavily polluting industries mediated by environmental, social and governance (ESG) performance and agency conflict. Further, this study is also expected to explore the effects of digital transformation’s green innovation spillover.

This study chooses 6,438 A-share heavily polluting listed firms in the stock exchanges based in Shanghai and Shenzhen in China during 2010–2020 as samples and tests the hypothesis with ordinary least squares (OLS) regression. Results prove to be robust to a battery of robustness analyses the authors performed to take care of endogeneity.

The results show that the focal firm’s digital transformation may trigger their peer firms’ green innovation spillover and prompt them to engage in green innovation activities actively. The mechanism test shows that peer firms’ ESG performance and agency conflict mediate the influence path between digital transformation and peer firms’ green innovation spillover. Finally, among heavily polluting firms with high industry competition and large scale, digital transformation’s green innovation spillover effects are more significant in conventional energy-based source control, end-of-pipe treatment and substantive green innovation.

This study is possible to provide a potential driving mechanism of green innovation spillovers. The findings lay a sound foundation for future research, providing important theoretical support and practical insights for digital transformation to empower heavily polluting industries to achieve green transformation and low-carbon development.

Recommendation systems are a fundamental tool for hotels to adopt a differentiating competitive strategy. The main purpose of this work is to use machine learning techniques to treat imbalanced data sets, not applied until now in the tourism field. These techniques have allowed the authors to analyse the influence of imbalance data on hotel recommendation models and how this phenomenon affects client dissatisfaction.

An opinion survey was conducted among hotel customers of different categories in 120 different countries. A total of 135.102 surveys were collected over eleven quarters. A longitudinal design was conducted during this period. A binary logistic model was applied using the function generalized lineal model (GLM).

Through the analysis of a representative amount of data, the authors empirically demonstrate that the imbalance phenomenon is systematically present in hotel recommendation surveys. In addition, the authors show that the imbalance exists independently of the period in which the survey is done, which means that it is intrinsic to recommendation surveys on this topic. The authors demonstrate the improvement of recommendation systems highlighting the presence of imbalance data and consequences for marketing strategies.

The main contribution of the current work is to apply to the tourism sector the framework for imbalanced data, typically used in the machine learning, improving predictive models.

The research frontier concerning the relationship between Industry 4.0 (I4.0) and supply chain performance (SCP) in manufacturing is currently lacking in a comprehensive examination. This study examines the relationship between I4.0 adoption and SCP. Additionally, the study examines the mediating effects of supply chain traceability (SCT), supply chain visibility (SCV) and supply chain resilience (SCR), both individually and sequentially.

The data were garnered from 510 managers of manufacturing firms, and PLS-SEM was applied to examine the sequential mediation effect of SCT, SCV and SCR between I4.0 and SCP.

Results indicate a statistically significant direct relationship between I4.0 adoption and SCP. Furthermore, SCT mediates the impact of I4.0 on SCP. Similarly, results showed that SCV mediates the impact of I4.0 on SCP and SCR mediates the impact of I4.0 on SCP. Moreover, the relation between I4.0 adoption and SCP is substantially influenced by the sequential effects of SCT, SCV and SCR. The study provides novel empirical evidence by investigating the sequential mediation roles of SCT, SCV and SCR between I4.0 adoption and SCP through the lens of the resource-based view (RBV) perspective.

Policymakers must prioritize the promotion of I4.0 integration to strengthen the performance of manufacturing supply chains (SC). This can be achieved by improving traceability, visibility and resilience within these SCs.

The originality of this study lies in its use of the sequential mediation effect of SCT, SCV and SCR between I4.0 and SCP under the theoretical lens of RBV.