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The persistence and virality of conspiracy theories online have raised significant concerns. This study revisits Rogers’ Diffusion of Innovations theory to examine the spread of conspiracy theories on social media, specifically focusing on how factors influencing their diffusion evolve over time.

The study analyzes over 1.18 million COVID-19-related tweets using a combination of natural language processing, social network analysis and machine learning techniques. It explores the dynamic roles of novelty, content negativity, influencers, echo chamber members and social bots in the diffusion of conspiracy theories.

The results indicate that novelty, influencers, echo chamber members and social bots are positively associated with the spread of conspiracy theories. The initial dissemination of conspiracy theories is primarily driven by content novelty and influencer involvement. Over time, the perpetuation of these theories becomes increasingly influenced by content negativity and the involvement of echo chamber members and social bots. Social bots serve as important connectors within echo chambers and their removal significantly reduces network cohesion.

The findings provide practical guidance for social media platforms and policymakers in monitoring diffusion patterns and applying targeted interventions.

This study introduces a time-sensitive approach to understanding the spread of conspiracy theories on social media. By identifying the key drivers at different stages of the diffusion process, this study offers valuable insights for developing effective strategies to counteract the proliferation of conspiracy theories at various points in their lifecycle.

Enhancing total factor productivity through digital transformation is a crucial pathway for the high-quality development of manufacturing enterprises. This research aims to investigate the impact mechanisms of manufacturing enterprises’ total factor productivity in the context of digital transformation.

Using the data from 536 Chinese listed manufacturing enterprises from 2018 to 2021, this research divides digital transformation into two dimensions (i.e. digital transformation breadth and digital transformation depth) and examines their impacts on total factor productivity as well as the mediation effects of innovation capability and reconfiguration capacity.

It is found that digital transformation breadth, digital transformation depth and their interaction can positively affect manufacturing enterprises’ total factor productivity. The innovation capability and reconfiguration capacity of manufacturing enterprises act as mediators between digital transformation breadth and total factor productivity, as well as between digital transformation depth and total factor productivity.

This study is one of the first attempts to investigate the impact mechanisms of manufacturing enterprises’ total factor productivity from the perspective of digital transformation breadth and depth.

This study aims to evaluate the effects of the downhole environment and auxiliary rubber bellows on the contact mechanical characteristics and sealing performance of rubber-bellows mechanical seals (RBMS) in electric submersible pumps (ESPs), considering the elastic support of the rubber bellows, multi-field coupling effect and actual operating conditions.

A thermal-fluid-solid multi-field coupling numerical model for RBMS in ESPs is developed using the finite element analysis and influence coefficient method. Based on the contact mechanical characteristics of RBMS, the interactions of multiple physical fields between the sealing rings and lubricating oil are accounted for to assess the liquid lubrication state and sealing performance of RBMS in ESPs.

The findings indicate the anti-leakage effects of rubber bellows, the transition of lubrication state of the sealing end face and the evolution law of sealing performance with environmental pressure, axial compression amount and contact widths of rubber bellows.

This study innovatively proposes a multi-field numerical research method to reveal the impact of the downhole environment and rubber bellows on RBMS in ESPs. These findings contribute to a more comprehensive understanding of the sealing mechanism of RBMS and optimize the sealing design for ESPs in high-pressure environments.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0369/

Based on the Sociometer Theory, this study aims to develop a comprehensive framework explaining how and when negative workplace gossip triggers distinct responses, including employee silence and compulsory citizenship behavior (CCB).

Two scenario-based experiments and a field survey were conducted to examine hypotheses. Study 1 (N = 149) manipulated workplace negative gossip and assessed the mediating effects of state self-esteem. Study 2 (N = 217) manipulated workplace negative gossip and consideration of future consequences (CFC) to verify the stability of the mediating mechanism and test the moderating effect of CFC. Study 3 (N = 321) tested the whole research model.

The findings indicate that negative workplace gossip decreases state self-esteem, resulting in silence among employees with low levels of CFC, while inducing CCB through state self-esteem among employees with high levels of CFC.

This study not only extends the research of negative workplace gossip by exploring its multifaceted impact on employee responses but also highlights the role of personality traits in shaping individuals’ response strategies.

This article aims to delve into the connections between DNA, cultural intelligence (CQ) and knowledge dynamics (KD) as native ingredients of the global mindset of multicultural managers and leaders. Cognitive science and knowledge management researchers show that business process decision-making is not entirely rational, based on explicit knowledge. They depend on the dynamics of rational, emotional and spiritual knowledge fields and on the capacity to integrate those dynamics into cultural intelligence. Most business process management studies show that managerial competencies depend on native and educational components. The literature usually addresses the developing process of those competencies through educational programs and leaves a knowledge gap concerning their native ingredients.

We designed an integrated research approach containing a critical literature review, supported by a bibliometric analysis using VOSviewer and a quantitative analysis derived from questionnaires and their statistical processing using SPSS, version 28. Based on VOSviewer variant 1.6.20, the bibliometric approach is used to understand the intricate correlation between DNA, CQ and KD, while the quantitative analysis is rooted in a questionnaire’s results from a sample of 101 managers with cross-cultural experience.

The analysis reveals that DNA diversity can play a notable role as a vector and predictor of CQ and KD. The results demonstrate the connection between geo-genetic diversity, CQ and the ability to be effective in multicultural business environments. Furthermore, the study highlights the impact of DNA on knowledge dynamics, revealing how geo-genetic variations impact the transfer and transformation of knowledge within sociocultural contexts—with implications for organizational behavior and cross-cultural and multicultural management.

This study may encounter limitations in establishing a direct and unique causal relationship between DNA, cultural intelligence and knowledge dynamics, as the complex interplay of various factors, such as individual experiences, social environment and education, could influence the interpretations of the findings. Additionally, generalizing the results across diverse populations would be challenging due to the potential ethnic and geographic variations in genetic and cultural contexts (Alexander et al., 2021). Also, for future research, we could reverse the process and measure a self-reported CQ before the DNA test in order to avoid any potential cultural bias or extended perception. Business process management within a multicultural environment is strongly nonlinear and more complex models should be developed to reveal the inner correlations between main constructs.

This research extends beyond academia into practical domains such as organizational behavior, cross-cultural and multicultural leadership, and sustainable business processes. Acknowledging the role of genetic diversity in these phenomena encourages further inquiry, prompting scholars and practitioners to investigate the organization’s concrete ways to increase creativity and innovation, adaptability and resilience toward successful navigation in the international business environment based on diversity, inclusion and global mindset.

Comprehending the genetic underpinnings of cultural intelligence and knowledge dynamics has potential implications for various fields, such as education, cross-cultural communication and even policy-making. By acknowledging and harnessing the influence of genetic diversity in these domains, we aim to create more inclusive and opportunity-rich environments that foster intercultural learning and cooperation. We also aim to generate more sustainable business approaches based on flexibility, continuous learning and cultural adaptation.

Previous literature mainly concentrated on environmental and individual factors acting on CQ and KD; however, this study is focused on uncovering DNA’s influence on these concepts and topics. The originality of this study lies in challenging conventional views on CQ and KD by introducing genetic factors to understand individual differences. Recognizing the impact of diverse genetic roots on CQ and KD, this paper emphasizes values like respect for the culture and historical background, understanding others' values, diversity and inclusion, and learning and agilely adapting. These vectors are the foundation for modern business processes in multicultural environments.

This study aims to investigate factors that drive or deter audit firms (AFs) from disclosing audit quality (AQ) information to stakeholders in Iran. Furthermore, information items that should be contained in their disclosures are examined.

The study followed an interpretive approach. In this regard, 21 semi-structured and face-to-face interviews were conducted to explore the viewpoints of audit partners and investment managers. Interviewees were selected by snowball sampling method. The transcripts of audio records were prepared, and a thematic perspective was applied to evaluate transcriptions.

Participants’ interpretations indicate that certain factors, such as signaling to stakeholders, active audit committees and investor demand, promote transparency among Iranian AFs. Nonetheless, this inclination is deterred by some concerns, including poor AQ, lack of financial resources, lack of legal enforcement, fear of raising stakeholders’ expectations, inactive professional associations and contextual factors which should be addressed. Interviewees believe five items should be contained in AFs’ disclosures to enhance transparency.

This study contributes to recognizing factors explaining AFs’ behavior in the context of an Islamic country. Furthermore, the type of disclosure that should be contained can provide good insight for standard setters or oversight bodies.

The semi-structured interviews shed light on the contextual factors that influence transparency within the accountancy profession, either enabling or hindering it. Additionally, it is crucial to consider each country’s unique characteristics when determining the disclosure items in transparency reports.

The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

Environmental, social and governance (ESG) scores are compelling for firm strategy and performance. Thus, this study aims to explore ESG scores’ predictive roles on global firms’ diversity scores.

A total of 1,114 global firm-year data from the Thomson Reuters Eikon database was analyzed using machine learning algorithms like rpart, support vector machine, partykit and evtree.

The results reveal a positive association between diversity, resulting in greater comprehensiveness and relevance. Broadly speaking, the two factors with the most significant values for calculating the overall diversity scores of businesses are ESG scores and social scores. ESG scores and environmental scores are the most effective predictors for the diversity pillar and people development scores. In contrast, community and social scores are the most important predictor factors for the inclusion scores.

The research is particularly pertinent to managers and investors considering ESG issues while making decisions. The results indicate that leaders and practitioners should prioritize ESG elements and diversity problems to enhance performance.

This study introduces the heritage city risk dimension of the urban rail transit (URT) projects. It aims to identify the risk factors affecting URT projects within the unique context of heritage-rich cities, exploring their interrelation and evaluating critical factors.

The research adopts a multi-case exploratory study to identify the unique challenges faced by URT projects in heritage-rich environments, followed by a comprehensive risk assessment framework integrating Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), Analytic Network Process (ANP) and Risk Interaction Network (RIN) analysis to assess identified risks in the context of Kathmandu Valley. Additionally, a risk response action is simulated using RIN analysis.

About 16 risk factors were identified from the case studies and evaluated using the proposed risk assessment methodology. The study reveals a highly interconnected risk environment, with heritage impact-related factors exerting the strongest causative influence on cost and social engagement factors. Community opposition (R8) shows the highest betweenness centrality, indicating its central position in risk propagation across the network. Cost-related risk, social demand contingency (R2) ranked as the most critical. Simulations of a targeted risk avoidance strategy showed that addressing only three key high-betweenness centrality factors (R5, R8 and R15) reduced overall risk interactions by 46%, simplifying the risk network, reducing project complexity and improving manageability.

The findings emphasize that project managers, urban planners and policymakers should integrate heritage preservation concerns when planning and executing URT projects in heritage-rich cities. Moreover, the research highlights that effective community engagement serves as a key strategy for reducing risk propagation and plays a crucial role in overall project risk management.

The study contributes to the underexplored context of URT projects in heritage-rich cities, providing a comprehensive risk management framework for identifying and assessing project risks intersecting with urban development imperatives and heritage conservation objectives.

In social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.

We collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.

Official media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.

This study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.