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Building on resource dependence theory and the dynamic institution-based view, this paper examines the influence of government affiliations on firm product innovation in a dynamic institutional environment.

Using unique panel data of Chinese manufacturing firms covering a period of 12 years (1998–2009) with 2,564,547 firm-year observations, this study chooses the panel Tobit model with random effects to explore the influence of government affiliations on firm product innovation, followed by an analysis to test the moderation effects of dynamic institutional environments.

The study findings suggest that Chinese firms with higher-level government affiliations have a relatively high product innovation performance. It finds that this innovation stimulating effect is contingent on the dynamic nature of the institutional environment. To be specific, a high speed of institutional transition may depress the positive innovation effects of government affiliations, while a more synchronized transition speed of institutional components may enhance the positive innovation effects of firms' government affiliations.

This study adds to a better understanding of the drivers of product innovation in Chinese firms that are situated in environments that are characterized by institutional change, using and contributing to resource dependence theory and the dynamic institution-based view.

In recent years, especially after the COVID-19 pandemic, home textile production orders decreased significantly. This sudden drop in production has increased industry competition, making customer satisfaction more challenging. As a result, it has become imperative for the industry to deftly navigate such ongoing challenges.

This study examines textile production efficiency methodically. Customer requirements like quality, on-time delivery, better working conditions, cost-effectiveness and facility safety audits are understood first. Quality function deployment (QFD) turns client requirements into technical requirements. Prioritise and analyse risks using Monte Carlo simulation and Pareto charts. Consequently, experts and literature propose corrective measures, which are tested in a pilot run to see how they affect production.

QFD, define, measure, analyse, improve and control (DMAIC) and Monte Carlo simulation were used to reduce high-priority risks and meet client requirements in this study. The house of quality helped relate customers’ requirements and technical requirements. Monte Carlo simulation has also improved risk prioritisation by providing a flexible mathematical structure for identifying and managing the most important risks.

This study is novel in the way it applies this integrated approach to the understudied home textile sector. Unlike traditional DMAIC, this study introduces a novel matrix encompassing all defects. This study offers a data-driven approach to improve product quality, meet customer expectations and reduce prioritised risks in home textile manufacturing.

This study aimed to uncover the characteristics of both misinformation and refutations as well as the associations between different aspects of misinformation and corresponding ways of rebutting it.

Leveraging Hovland's persuasion theory as a research lens and taking data from two Chinese refutation platforms, we characterized the topics of COVID-19-related misinformation and refutations, misinformation communicator, persuasion strategies of misinformation, refutation communicators and refutation strategies based on content analysis. Then, logistic regressions were undertaken to examine how the characteristics of misinformation and refutation strategies interacted.

The investigation into the association between misinformation and refutations found that distinct refutation strategies are favored when debunking particular types of misinformation and by various kinds of refutation communicators. In addition, several patterns of persuasion strategies were identified.

This study had theoretical and practical implications. It emphasized how misinformation and refutations interacted from the perspective of Hovland's persuasion theory, extending the scope of the existing literature and expanding the classical theory to a new research scenario. In addition, several patterns of persuasion strategies used in misinformation and refutation were detected, which may contribute to the refutation practice and help people become immune to misinformation.

This research is among the first to analyze the relationships between misinformation and refutation strategies. Second, we investigated the persuasion strategies of misinformation and refutations, contributing to the concerning literature. Third, elaborating on Hovland’s persuasion theory, this study proposed a comprehensive framework for analyzing the misinformation and refutations in China during the COVID-19 pandemic.

This paper aims to demonstrate that, in line with the emerging trend of multifunctional yarn development, cotton yarn can effectively harness renewable solar energy to achieve photothermal conversion and thermochromism. This innovation not only maintains the comfort associated with natural fiber cotton yarn but also enhances its ultraviolet (UV) light resistance.

In this work, 4% zirconium carbide (ZrC) and thermochromic powder were adhered to cotton yarn through polyurethane (PU) by sizing coating method. After sizing, the two cotton yarns are twisted by ring spinning to obtain composite yarns with photothermal conversion and thermochromic functions.

The yarn obtained by cotton/6%PU/8% thermochromic dye single yarn and cotton/6%PU/4% ZrC single yarn composite is the best match. After 5 min of infrared light, the temperature of the composite yarn rose to the maximum, increasing by 36.1°C. The ΔE* value before and after irradiation of infrared lamp is 26.565, which proves that the thermochromic function is good. The yarn dryness unevenness was significantly reduced by 27.2%. The composite yarn has a UPF value of up to 89.22, and its performance characteristics remain stable after 100 minutes of washing.

The composite yarn’s photothermal conversion and thermochromism functions are mutually reinforcing. Using sunlight can simultaneously achieve heating and discoloration effects without consuming additional energy. The cotton yarn used in this application is versatile, and suitable for a wide range of uses including clothing, temperature visualization detection and other scenarios.

China has recently introduced a new audit law that aims to increase the scope of audit supervision and raise the standards for preventing risks in auditing national public projects. This paper presents a systematic research study on the causes of audit risks in national public projects and discusses the process by which these causes contribute to the emergence of such risks. Furthermore, the paper investigates the core risk sources in various types of national construction project audit. This paper aims to provide theoretical support for auditors of national construction projects in risk avoidance when conducting audits.

In this study, the authors carefully selected five national public audit projects from China and performed a comprehensive analysis of 85 relevant audit documentation. The textual analysis was conducted using Nvivo12 software, and the grounded theory approach was adopted for generalization purposes.

Based on the research results, the findings suggest that there are five key causes contributing to the audit risk of national construction projects: professional competence, risk awareness, management capacity, level of attention and deliberate fraud. The most critical factor identified is management capability, with 59.93% of the data supporting this view. This conclusion was based on an analysis of state-owned enterprises, administrative organs and public institutions. Building upon this, a framework titled “the mechanism of audit risk factors with management capability as the core” was constructed.

This paper employs qualitative analysis methods to examine national construction projects in China, contributing new literature to the theoretical study of audit risk management. The article also provides practical recommendations for auditors on how to mitigate audit risks and improve the quality of audit services in national project governance.

Consequence prediction is an emerging topic in safety management concerning the severity outcome of accidents. In practical applications, it is usually implemented through supervised learning methods; however, the evaluation of classification results remains a challenge. The previous studies mostly adopted simplex evaluation based on empirical and quantitative assessment strategies. This paper aims to shed new light on the comprehensive evaluation and comparison of diverse classification methods through visualization, clustering and ranking techniques.

An empirical study is conducted using 9 state-of-the-art classification methods on a real-world data set of 653 construction accidents in China for predicting the consequence with respect to 39 carefully featured factors and accident type. The proposed comprehensive evaluation enriches the interpretation of classification results from different perspectives. Furthermore, the critical factors leading to severe construction accidents are identified by analyzing the coefficients of a logistic regression model.

This paper identifies the critical factors that significantly influence the consequence of construction accidents, which include accident type (particularly collapse), improper accident reporting and handling (E21), inadequate supervision engineers (O41), no special safety department (O11), delayed or low-quality drawings (T11), unqualified contractor (C21), schedule pressure (C11), multi-level subcontracting (C22), lacking safety examination (S22), improper operation of mechanical equipment (R11) and improper construction procedure arrangement (T21). The prediction models and findings of critical factors help make safety intervention measures in a targeted way and enhance the experience of safety professionals in the construction industry.

The empirical study using some well-known classification methods for forecasting the consequences of construction accidents provides some evidence for the comprehensive evaluation of multiple classifiers. These techniques can be used jointly with other evaluation approaches for a comprehensive understanding of the classification algorithms. Despite the limitation of specific methods used in the study, the presented methodology can be configured with other classification methods and performance metrics and even applied to other decision-making problems such as clustering.

This study sheds new light on the comprehensive comparison and evaluation of classification results through visualization, clustering and ranking techniques using an empirical study of consequence prediction of construction accidents. The relevance of construction accident type is discussed with the severity of accidents. The critical factors influencing the accident consequence are identified for the sake of taking prevention measures for risk reduction. The proposed method can be applied to other decision-making tasks where the evaluation is involved as an important component.

The short/fast-food and perishable food supply chains (PFSC) have similar characteristics of lower lifespan and variable demand, leading to significant waste. However, the global population surge and increased health awareness make it impossible to continue wasting food because it is responsible for the loss of economy, resources, and biodiversity. A sustainable transition in short and PFSC is necessary; thus, addressing challenges is critical to explore the best strategy for redesigning PFSC.

An extensive literature review helped to identify 40 challenges, while a Delphi study highlighted 21 critical challenges. The fuzzy decision-making trial and evaluation laboratory method establishes a causal relationship between sustainable development (SD) challenges to help redesign PFSC.

From a strategic development perspective, frequent transportation disruption is the main critical challenge. Lack of supplier reliability is the most substantial cause of independence, with a causal value of 2.878. Overhead costs and lack of green maintenance strategies are part of the performance-oriented challenges. As it belongs to the driving zone, the second quadrant requires control while transforming PFSC for better sustainable development.

The study has several implications, such as lack of supplier reliability and frequent transportation disruption, which have the most robust causal value used as short-term strategy development. For short- and fast-food supply chains, it is necessary to study market and consumer behavior patterns to optimize inventory and customer service. Combating transportation disruption and supplier reliability challenges is vital in both PFSC and short and fast-food supply chains to reduce waste and promote sustainability.

The study’s findings are unique and put value toward the sustainable transition of PFSC by revealing critical challenges and their impact.

Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.

This study aims to examine the impact of geographical and business proximity between parent companies and affiliates on R&D investments in business groups. Furthermore, it compares the moderating effect of value chain participants’ bargaining power and the performance-aspiration gap.

This study uses data from 411 Chinese private manufacturing listed firms affiliated with business groups. This paper conducts regression analysis using Stata 16.0 software. Additionally, this paper employs combined random effects regression models, the 2SLS method and GMM method.

Geographical distance between focal affiliates and parent companies is negatively related to focal affiliates’ R&D. The higher the business proximity between focal affiliates and parent companies, the more R&D investments are made. Further research shows that with stronger bargaining power and a wider performance-aspiration gap, the negative relationship between geographical distance and R&D investment weakens.

This study contributes to the R&D investment literature by offering a novel perspective on why proximity influences affiliates’ R&D investments in Chinese business groups. This study enriches the proximity theory by introducing business proximity as a new dimension into the framework. Furthermore, this study highlights the boundary conditions of the proximity theory by ascertaining the moderating effects of bargaining power and the performance-aspiration gap.

This research complements the extant literature on poverty and inequality by assessing the role of “virtual social networks” and “internet access in schools” in mitigating the incidence of inequality on poverty.

Using secondary data, the focus of the study is on developing countries and the empirical evidence is based on Tobit regressions.

The study shows that inequality unconditionally increases poverty while “virtual social networks” and “internet access in schools” negatively moderate the effect of inequality on poverty. An extended analysis provides thresholds of “virtual social networks” and “internet access in schools” at which, the unconditional positive effect of inequality on poverty is completely dampened and above which, negative incidences on poverty are apparent. These attendant information technology thresholds are below average levels in the sampled countries.

The study complements that extant literature by assessing the role of virtual social networks and internet access in schools in mitigating the incidence of inequality on poverty in developing countries. Policy implications are discussed in the light of Sustainable Development Goals.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2023-0695