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A series of policies have been formulated to promote off-site construction (OSC) development. However, the effectiveness of these policies has yet to be fully explored. This study aims to explore the practical policy configurational conditions for achieving a high level of OSC development.

Data on policy configurational conditions and the OSC development level were collected from 28 provinces/municipalities in China using text mining. A mixed-method approach was used to conduct data analysis involving text analysis and qualitative comparative analysis (QCA). Text analysis was used to identify current policies with frequencies as independent variables and obtain the proportion of OSC projects in new construction projects as the dependent variable. QCA is employed to analyze the necessary and sufficient conditions of policy conditions for the high-level development of OSC by exploring the complex causal relationships between policy configurational conditions and the OSC development level.

Nine policies are obtained from the current policy framework for promoting OSC development using text analysis: industry supports, land policies, presale policies, reputation rewards, regulation controls, tax incentives, floor area rewards, financial subsidies, and loan subsidies. Four policy configurational conditions are identified that can achieve a high development level of OSC: three incentive-driven policy conditions with industry supports, presale policies, tax incentives, and floor area rewards as the core conditions, and one compulsory-driven policy conditions with land policies, financial supports, and loan supports as the core conditions using fuzzy set QCA. Moreover, our study found that a single policy cannot achieve a high level of OSC development as a necessary condition, and the policy configurational conditions that lead to high and nonhigh levels of OSC development are asymmetrical.

The study did not test the policy’s dynamic effects on the OSC development. A longitudinal study will be conducted to further identify the impact of policy on OSC implementation.

It provides policymakers with four practical policy configurational conditions to promote OSC development and guides policymakers to optimize effective policies considering the interaction effects of effective policies such as industry supports, presale policies, tax incentives, and floor area rewards instead of their net effects.

It contributes to the existing literature concerning the effects of policy on emerging technology (i.e. OSC) promotion by elucidating configurative effects rather than net effects. Meanwhile, it enriches the research on the antecedent conditions that affect the implementation of other emerging technologies in the architecture engineering and construction industry.

This study examines how dynamic capabilities (DCs) impact global value chain (GVC) upgrading and assesses the mediating role of innovation.

The study uses a quantitative research method. The data are collected using an online questionnaire administered to respondents working in Chinese automobile manufacturers in China and Laos. The data are analyzed using structural equation modeling (SEM) and related software.

The results show that DCs and innovation capabilities (ICs) positively affect GVC upgrading and that ICs plays a mediating role between DC and GVC upgrading. Dynamic capabilities evolution (CE) mediates the relationship between DCs, ICs and GVC upgrading. Finally, differences exist in the effects of the three dimensions of DCs on ICs and GVC upgrading.

Focusing on the absorption and transformation of knowledge, enterprises could experience a clear enhancement of IC and CE and be more likely to obtain higher marginal returns. The study provides insights for emerging market firms to gain higher added value in internationalization.

This study demonstrates that different dimensions of DCs have different effects on GVC upgrading. In terms of theory, the impact of IC is considered in terms of the mediating effect of CE on IC. Differences are highlighted concerning the impact of learning capability, integrating and coordinating capability and sensing capability on the mediated relationships.

The purpose of this paper is to explore a new eco-friendly green textile dyeing. Natural plant Buddleja officinalis is traditionally used as yellow pigment addition in rice. It is worth developing its application and dyeing performance in cotton fabric.

Buddleja officinalis dried flower was extracted with ethanol aqueous. The extraction conditions including ethanol concentration, material to liquor ratio, extract time and temperature were optimized. Then cotton fabrics were dyed with Buddleja officinalis extraction under conventional and ultrasonic conditions. The effects of dyeing time, bath ratio, pH value of dyeing bath, dyeing temperature and mordants on K/S values were studied and the resulting color strength obtained by conventional and ultrasonic dyeing were compared. The ultraviolet (UV) transmittance of Buddleja officinalis dyed cotton fabric was also evaluated.

The color strength of the fabric dyed with Buddleja officinalis under ultrasonic conditions was higher than that under conventional conditions. Alum, Fe and Cu as simultaneous mordants improved the K/S value of the dyed cotton fabrics. Both washing fastness and rubbing fastness were fairly good in all Buddleja officinalis dyed cotton fabrics, washing fastness = 3–4 and rubbing fastness = 4. What’s more, the dyed cotton fabrics showed lower transmittance values as compared to undyed cotton fabrics and indicated potential UV protection capability.

Buddleja officinalis can be a new natural dye source for the ultrasonic dyeing of cotton fabric.

It is for the first time that Buddleja officinalis is used as a natural dye in cotton fabric dyeing with less water and the dyeing using ultrasound has been found to have an obvious improvement in the color strength and color-fastness.

Viewing consumer confidence as a set of static factors has informed previous research and underpinned strategies used in recovering from food safety quality failures, but this approach has not delivered reliable and quick recovery from large-scale food safety scandals. The purpose of this paper is to examine extant models and the factors they are composed of, and suggest an extended model that has a better potential for consumer confidence. The paper focuses on food products where supply chains are visible, and use these features to group the findings.

In this study principal components and logit analyses are used to assess the role of 30 variables operating in a consumer confidence model constructed from several existing in the literature. This combined model considers emotional, cognitive, trust and sociodemographic factors. In total, 14 independent factors are identified. The authors examine the factors, and from these, the decision-making mechanisms before and after the Sanlu Infant Milk Formula (IMF) scandal of 2008.

The authors find that the factors considered by consumers are different for different IMF supply chains, and different again before and after the scandal. The authors develop the argument for an extension to the existing models, incorporating a dynamic consumer confidence system.

The paper uses a single survey after the focus event to establish “before” and “after” decision-making factors. Since the IMF scandal is recent and of very high profile, this is likely valid even if it carries memory bias effects. The study is directly applicable to food safety scandals in a Chinese context. Deductive reasoning extends our assertions to a wider context. They are logically validated but have not been formally tested.

Using this system as a framework a checklist for recovery from a similar food safety scandal is suggested. The authors also suggest more general use for use where supply chains features are visible to consumers.

Models for food safety consumer confidence recovery have previously focused on identifying models and the static factors they consist of. These do represent a reflection of how this phenomenon operates, but using the principals of this model nevertheless does not result in good recovery from extreme food safety failures. This paper contributes by extending these models to one that can be applied for better recovery.

The purpose of this paper is to explore a descriptive framework for a more structured and objective evaluation of the risk situation of textile and apparel, also to find the best set of methods or optimal scientific grounds for the safety evaluation of textile and apparel.

Risk analysis theory is used to analyze potential hazard of textile and apparel, weight is given to risk indicators using subjective and objective weighting method, respectively, grading standards of safe risk of textile and apparel is made. Finally a safety risk assessment model of textile and apparel based on support vector machine (SVM) is built, and empirical analysis is also made.

Quantitative and highly reliable evaluation of textile and apparel risks, relatively easy grading classification and simplicity in operating the evaluation process are the advantages that promote the application of risk assessment model based on SVM for textile and apparel, and empirical analysis showed considerably good applicability.

The research is useful to ensure safety textile and apparel in market, also contributing to the sustainable development of textile industries in future.

SVM as a risk assessment method provided safety evaluation to toxic and harmful substance and small parts in textile and apparel, which can be an effective tool to monitor textile and apparel safety.

As the global economy expands, it would seem to be in the interests of the major professional sport leagues of the US to move into new markets, especially China, one of the fastest growing and largest in the world. In order to sell effectively in this market, it is vital to gain an understanding of the potential fan base. To explore national differences in fandom, a survey was completed by sports fans in both China and the US to assess which sports participants followed and which media they used, to identify fan motives and their feelings about expansion. This study determined that there are clear differences between Chinese and Americans. While many of the Chinese were fans of American sports, they tended to follow individual athletes rather than teams and had relatively low fan identity but high levels of fan motivation. Motives also varied by country, with aesthetics and affiliation the primary motives among the Chinese sample. These distinctions can be utilised to create marketing strategies.

This research aimed to find out both direct and mediating relationships between the fear of COVID-19 (FC) and the usage of digital financial services (UDFS) via mediator financial anxiety (FA). It also attempted to ascertain the moderated effect of education of small and medium-sized enterprise (SME) owners (ESO), i.e. business degree holders (BDH) vs nonbusiness degree holders (NBDH), in the relationship between FC and the UDFS.

This research employed a simple random sampling technique. In total, 387 complete responses were collected from Pakistani SMEs. The complete analysis was performed using Statistical Package for the Social Sciences (SPSS) 23, AMOS 24, Process Marco 4.1, and Interaction 1.7.

According to the findings, FC leads to UDFS and FA mediates this relationship. Additionally, the findings show that the ESO between FC and UDFS was moderated. However, conditional analysis shows that BDH-SME owners strengthened the moderated relationship between FC and UDFS compared to NBDH-SME owners, who did not show any relationship.

Policymakers might use the study's findings to promote business education, which has been recognized as essential for making sound financial decisions. Finally, because the study is cross-sectional, the authors are unable to draw definitive generalizations.

The key novelty of this research work lies in the inclusion of FA as a mediator and the education of SME owners as a moderator in understanding the relationship between FC and the UDFS. This study illuminated the positive aspects of the COVID-19 epidemic based on the theory of emotional finance, risk avoidance theory and theories of emotion.

The purpose of this paper is to study the friction and wear properties of journal bearings under different working conditions.

Friction coefficient and wear losses of journal bearing under different working conditions have been determined by a bearing test rig. The worn surfaces of bearing were examined by scanning electron microscopy and laser three-dimensional micro-imaging profile measurements, and the tribological behavior and wear mechanisms were investigated.

The wear loss and friction coefficient of bearing under starting-stopping working condition is far greater than that of steady-state working conditions. In addition, the maximum wear loss under start-up and stop conditions is about 120 times of that under stable operating conditions. Under stable working conditions, the main wear forms of bearings are abrasive wear, under starting-stopping working conditions the main wear mechanisms of bearings are adhesion wear, abrasive wear and fatigue wear.

These research results have certain practical value for understanding the tribology behavior of journal bearings under different working conditions.

The study aims to identify Green Lean Six Sigma (GLSS) barriers in the context of Higher Education Institutions (HEIs) and prioritize them for executing the GLSS approach.

A systematic literature review (SLR) was used to identify a total of 14 barriers, which were then verified for greater relevance by the professional judgments of industrial personnel. Moreover, many removal measures strategies are also recommended in this study. Furthermore, this work also utilizes Gray Relational Analysis (GRA) to prioritize the identified GLSS barriers.

The study reveals that training and education, continuous assessment of SDG, organizational culture, resources and skills to facilitate implementation, and assessment of satisfaction and welfare of the employee are the most significant barriers to implementing this approach.

The present study provides an impetus for practitioners and managers to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers. In this case, the outcomes of this research, and in particular the GRA technique presented by this work, can be used by managers and professionals to rank the GLSS barriers and take appropriate action to eliminate them.

The ranking of GLSS barriers gives top officials of HEIs a very clear view to effectively and efficiently implementing GLSS initiatives. The outcomes also show training and education, sustainable development goals and organizational culture as critical barriers. The findings of this study provide an impetus for managers, policymakers and consultants to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers.

The GLSS barriers in HEIs may significantly affect the society. HEIs can lessen their environmental effect by using GLSS practices, which can support sustainability initiatives and foster social responsibility. Taking steps to reduce environmental effect can benefit society as a whole. GLSS techniques in HEIs can also result in increased operational effectiveness and cost savings, which can free up resources to be employed in other areas, like boosting student services and improving educational programs. However, failing to implement GLSS procedures in HEIs could have societal repercussions as well. As a result, it is critical for HEIs to identify and remove GLSS barriers in order to advance sustainability, social responsibility and operational effectiveness.

GLSS is a comprehensive methodology that facilitates the optimum utilization of resources, reduces waste and provides the pathway for sustainable development so, the novelty of this study stands in the inclusion of its barriers and HEIs to prioritize them for effective implementation.