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With the uptake of prefabricated construction (PC) facing serious obstacles in China, networked innovation can break the technical constraints while also containing the risks in individual innovation. However, the construction community has paid little attention to PC innovation, especially networked innovation. This study aims to gain deep insights into what impacts the formation and dynamics of a prefabricated construction innovation network (PCIN). With the uptake of PC facing serious obstacles in China, networked innovation can break the technical constraints while also containing the risks in individual innovation.

The research design follows a sequential mixed methodology of qualitative and quantitative data collection and analysis. It first conceptualizes the PCIN based on the quadruple helix model and formulates a corresponding system dynamics model based on causality analysis. After validating the PCIN model using empirical data, simulations are carried out using Vensim PLE software. Finally, this study identifies key factors that promote the formation of PCIN in China through sensitivity analysis.

The results show that PC predicts a continuous increase in practice as of 2030. The tested drivers all positively influence the formation of the PCIN, with market demand and risk sharing having the greatest influence, followed by competitive pressure, profit government support, scientific and technological advancement and collaborative innovation strategy.

The study makes three major contributions. First, it provides a novel angle for a deeper understanding of the PC innovation. Second, it proposes a new approach for probing the formation and dynamics of the PCIN. Finally, it offers a theoretical reference for promoting the formation of innovation networks and the development of PC.

This study aims to present a state-of-the-art review of building information modelling (BIM) in the Swedish construction practice with a focus on wood construction. It focuses on examining the extent, maturity and actual practices of BIM in the Swedish wood construction industry, by analysing practitioners’ perspectives on the current state of BIM and its perceived benefits.

A qualitative approach was selected, given the study’s exploratory character. Initially, an extensive review was undertaken to examine the current state of BIM utilisation and its associated advantages within the construction industry. Subsequently, empirical data were acquired through semi-structured interviews featuring open-ended questions, aimed at comprehensively assessing the prevailing extent of BIM integration within the Swedish wood construction sector.

The research concluded that the wood construction industry in Sweden is shifting towards BIM on different levels, where in some cases, the level of implementation is still modest. It should be emphasised that the wood construction industry in Sweden is not realising the full potential of BIM. The industry is still using a combination of BIM and traditional methods, thus, limiting the benefits that full BIM implementation could offer the industry.

This study provided empirical evidence on the current perceptions and state of practice of the Swedish wood construction industry regarding BIM maturity.

This study aims to measure social enterprises’ (SEs’) social objectives under the United Nation’s 17 Sustainable Development Goals (SDGs) framework, and explore the impact of SEs’ social objectives on their choices of legal forms.

This study used semi-structured questionnaires followed up by field interviews and observations of the sampled SEs. The survey sample includes 80 participants of Social Entrepreneurs Stars Competition in Zhejiang Province of China. The authors conduct content analysis to measure the objectives of SEs. The authors also perform descriptive analysis, chi-square test and regression analysis on the data.

The findings confirm the theoretical discussions that SEs’ choices of legal forms reflect SEs’ strategies toward achieving social objectives. Similar to certain countries, some SEs in China register as nonprofit entities to concentrate on nonprofitable sustainability objectives, while others register as commercial enterprises or hybrid organizations to generate profits. However, some SEs focus on profitable non-sustainability issues and fail to prioritize social objectives over economic objectives. There are positive effects of social entrepreneurs’ background similarity and negative effects of social entrepreneurs’ educational level on their SEs’ choices to register as commercial enterprises.

Due to the small size and nonrepresentative sample this study is based on, the findings need be further tested by a larger sample. SEs in different service domains rely on different types of financial resources (Mair et al., 2012; Doherty et al., 2014). In future research, the model can be expanded to test the effects of service domains and types of financial sources on SEs’ choices of legal forms.

To encourage more societal resources being allocated toward achieving the United Nations’ SDGs, policymakers and SE certification programs are recommended to explicitly incorporate sustainability objectives into the evaluation standards and supportive policies for SEs. Social entrepreneurs who aim to balance the social and economic objectives in their business are suggested to target the population with whom they share similar community background. Training or consulting programs for social entrepreneurs are suggested to provide advice tailored to their socio-economic background and personal experiences.

To the best of the authors’ this study is the first quantitative analysis to identify factors that associate with SEs’ choice of legal forms in China. The authors developed new instruments to measure SEs’ social objectives and service targets, access to financial resources and social entrepreneurs’ social-economic backgrounds.

This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aims to provide some policy implications for corporate debt financing and further liberalization of the capital market in China.

Employing the exogenous event of Shanghai-Shenzhen-Hong Kong Stock Connect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturity structure. To validate the results, this study performed several robustness tests, including the parallel test, the placebo test, the Heckman two-stage regression and the propensity score matching.

This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on the debt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit. Channel tests show that capital market liberalization improves firms’ information environment and curbs self-interested management behavior.

This research provides empirical evidence for the consequences of capital market liberalization and enriches the literature on the determinants of corporate debt maturity structure. Further this study makes a reference for regulators and financial institutions to improve corporate financing through the governance role of capital market liberalization.

The purpose of this paper is to find out how absorptive capacity (AC), leadership capacity (LC) and government support (GS) affect small and medium enterprises (SMEs) innovation (product innovation [PDI], process innovation [PCI] and distribution channel innovation [DCI]), taking into consideration the role of innovation (PDI, PCI and DCI) on competitive advantage and SMEs performance and the moderating role of customer orientation (CO).

This study gives a theoretical model tested using structural equation modeling. The information used to test the hypotheses came from interviews with the top managers of Vietnam’s SMEs. The 633 survey respondents from the southern part of Vietnam were chosen for the study. The goal of the 47-item questionnaire is to look at how all variables relate to each other.

The results show that a firm’s LC has the most significant impact on innovation, followed by its AC and GS. According to the study, DCI does not lead to competitive advantage but improves SMEs’ performance. In addition, the study’s findings indicate that CO moderates the relationship between PDI – SMEs performance and DCI – SMEs performance.

The classification of only three types of innovation (PDI, PCI and DCI) restricted the applicability of the research to other kinds of innovation in SMEs. Second, only AC, LC and GS are identified in this study as external factors that influence business innovation. In this study, the authors have not studied different business industries; the authors recommend that the research in the back on SMEs should investigate their classification into distinct industry groups, including agricultural, forestry and marine products; industry and construction; and commerce and services.

This study shows the importance of innovation senior management for innovation in SMEs. This study found that innovation, especially continuous innovation, increased competitive advantage and SMEs performance. Companies that wish to innovate must have access to external resources and support. Moreover, enterprises must comprehend their consumers’ wants to achieve innovation and better SMEs’ performance.

This research significantly contributes to enterprise innovation and operational efficiency for the sustainable development of SMEs in Vietnam. It is expected to enhance employment opportunities, maintain social stability and expand Vietnam’s gross domestic product.

This study contributes to the growing knowledge of the indirect and direct effects, the mediating function of innovation (PDI, PCI and DCI) on competitive advantage and SMEs performance and the moderating effect of CO.

With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data visualization techniques to genealogical data is limited. This paper aims to fill this research gap by providing a systematic framework and process guidance for practitioners seeking to uncover hidden knowledge from genealogy.

Based on a literature review of genealogy's current knowledge reasoning research, the authors constructed an integrated framework for knowledge inference and visualization application using a knowledge graph. Additionally, the authors applied this framework in a case study using “Manchu Clan Genealogy” as the data source.

The case study shows that the proposed framework can effectively decompose and reconstruct genealogy. It demonstrates the reasoning, discovery, and web visualization application process of implicit information in genealogy. It enhances the effective utilization of Manchu genealogy resources by highlighting the intricate relationships among people, places, and time entities.

This study proposed a framework for genealogy knowledge reasoning and visual analysis utilizing a knowledge graph, including five dimensions: the target layer, the resource layer, the data layer, the inference layer, and the application layer. It helps to gather the scattered genealogy information and establish a data network with semantic correlations while establishing reasoning rules to enable inference discovery and visualization of hidden relationships.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This study aims to explore the role of social media visual posts (known as foodstagramming) on restaurant visit intention. Drawing on the heuristic–systematic model and normative focus theory, this research introduces a framework that assesses the effects of key foodstagramming attributes – vicarious expression, aesthetic appeal and post popularity – and the mediating roles of goal relevance and mimicking desire, in the process.

Structural equation modelling was performed to test the proposed model using a sample of tourists (n = 377) and residents (n = 341). Multi-group analysis was performed to compare the differences between these groups.

Results reveal that mimicking desire and goal relevance influence restaurant visit intention; however, mimicking desire has a stronger influence than goal relevance. Little difference was found between the tourist and the resident groups in the proposed relationships, except that vicarious expression positively influences mimicking desire in the tourist group but not in the resident group.

This study guides restauranteurs and social media influencers (foodstagrammers). It shows that consumers value the textual content and aesthetic appeal of photos over the popularity of a post. It also indicates that vicarious expression is more important for tourists than for residents.

This research advances social media marketing literature by proposing a new information processing framework. To the best of the authors’ knowledge, this study is one of the first studies to explore the impact of visual post attributes on individual decision-making behaviours through socially acceptable norms.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.

Prior research has proposed a number of scales measuring the customer experience (CX), which tend to conceptualize and operationalize CX differently, raising potential confusion among researchers (e.g. regarding which scale to use). Addressing this issue, this article conducts a systematic review to inventorize key CX scales and assess their theoretical rigor, with a focus on the identification of potential scale-related drawbacks or risks.

Drawing on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach, 104 CX scale development studies published between 1996 and 2024 are identified and analyzed in terms of their respective CX conceptualization, dimensionality, itemization, and adopted theoretical perspective to evaluate their theoretical rigor.

The findings reveal the existence of five main risks associated with the adoption of specific CX or related scales, including (1) defining experience with explicit reference to other extant constructs, (2) failure to accurately and comprehensively capture the experience, (3) experience-based tautology and theoretical indeterminacy, (4) experience-based composite constructs, and (5) lacking robustness of experience-based conceptual models. Based on these observations, recommendations are offered for scholars to improve the rigor of their adopted, refined, or proposed CX or related scales.

This article assesses the benefits and potential risks inherent in the adoption of particular CX scales, equipping researchers with a CX roadmap.