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The purpose of the study has been to fill the gap detected in the literature and to analyze whether the application of management of R&D in accordance with UNE 166002:2021 allows companies to obtain higher product innovation and better performance, specifically incremental and radical product innovations.

The population used in this study included Spanish manufacturing organizations that were active, had more than 50 employees according to the SABI. The information was collected through a structured questionnaire previously tested using a company specializing in the sector under the supervision of the authors. A total of 1,154 companies were randomly contacted in order to reach an acceptable number of 225 valid questionnaires. The data analysis has been carried out with structural equation methodology.

The results obtained with a sample of 225 companies show that the application of this standard for innovation management promotes the development of new products with incremental and radical changes, and improves business performance. It has also been found that incremental and radical product innovations mediate the relationship between this standard and performance.

Firstly, the survey is only addressed to the company's operations manager. Secondly, the sample used is cross-sectional, whereas innovation management implies a broad implementation process.

Managers must know that radical and incremental product innovation can improve the company's operational performance. And the most direct implication of this work is that, those companies that are committed to the development of innovations should seriously consider the application of the principles incorporated in Standard 166,002, as an instrument that improves the results of innovation in the organization. Since this SIMS promotes both types of innovations, it improves results directly and indirectly through these product innovations.

The existing literature indicates that no empirical study has focused on the benefits of this SIMSs for innovation and BP. This paper fills this gap detected in the literature and analyzes the results of the implementation of this standard on incremental and radical product innovations and business performance.

The paper aims to develop a useful tool that can reliably and accurately find the critical paths of high-rise buildings and provide optimal solutions considering the uncertainty based on Monte Carlo simulation (MCS) to enhance project implementation performance by assisting site workers and project managers in high-rise building engineering.

This research proposes an approach integrating the improved nondominated sorting genetic algorithm II (NSGA-II) considering uncertainty and delay scenarios simulated by MCS with the technique for order preference by similarity to an ideal solution.

The results demonstrate that the proposed approach is capable of generating optimal solutions, which can improve the construction performance of high-rise buildings and guide the implementation management for shortening building engineering project schedule and cost under the delay conditions.

In this study, only the construction data of the two floors was focused due to the project at the construction stage, and future work can analyze the whole construction stage of the high-rise building to examine the performance of the approach, and the multi-objective optimization (MOO) only considered two factors as objectives, where more objectives, such as schedule, cost and quality, can be expanded in future.

The approach proposed in this research can be successfully applied to the construction process of high-rise buildings, which can be a guidance basis for optimizing the performance of high-rise building construction.

The innovations and advantages derived from the proposed approach underline its capability to handle project construction scheduling optimization (CSO) problems with different performance objectives under uncertainty and delay conditions.

The research aims to explore the dynamic relationship between digital service innovation (DSI), artificial intelligence (AI) and business performance (BPer) in service-based models with a focus on how AI-enhanced insights from service use and customer feedback can strengthen business strategies. The aims are to show that DSI and AI are key to driving growth and efficiency in the digital economy and to underscore AI’s role in utilizing contextual data to improve decision-making and business outcomes.

The study uses general structural equation modeling to analyze Spanish manufacturing firms, focusing on medium-sized enterprises and including both business-to-business and business-to-consumer orientations. Data are drawn from the Iberian Balance Analysis System [Sistema de Análisis de Balances Ibéricos (SABI)] database, complemented by a Qualtrics survey to assess the integration of AI in decision-making processes. The methodology is designed to evaluate the interplay between DSI, AI and BPer, with the aim of identifying actionable insights for service-based business orientations.

The study clarifies the relationships between DSI, AI and BPer, providing new theoretical and empirical insights. The findings confirm DSI's direct positive impact on performance and suggest AI’s nuanced mediating role, emphasizing the need for strategic DSI-AI integration in manufacturing firms for enhanced performance.

The research explains the synergistic bond between DSI and AI in boosting BPer and discovering how by-product data can be transformed into strategic insights.

This study advises manufacturing sector leaders to integrate DSI and AI for enhanced performance and competitive advantage, emphasizing the value of high-quality, contextual data for AI learning and decision-making.

Researchers will observe that the study confirms the positive impact of DSI on BPer, while also highlighting the significant role of AI in enhancing this effect.

The purpose of this study is to get a clearer knowledge of the reasons for, approaches to and challenges associated with integrating sustainable development concerns into pipeline construction projects in New Zealand. To achieve this, this study delves deeply into sustainable construction to understand the reasons behind and incorporate sustainable development trials into their newly established product management and development procedure. As a result, this study looks at identifying key elements of sustainable construction practices and various interpretations of sustainability in the construction industry; offering a strategy for incorporating sustainable construction practices into the pipeline construction project in New Zealand; and benefits and difficulties that the construction industry encounters when implementing sustainable construction. Finally, a framework is developed to help in understanding the issues and potential solutions for integrating sustainable building methods into the pipeline construction project in New Zealand.

This study followed a four-step method (Figure 1), beginning with the identification of the data, continuing with the first screening of the data, determining eligibility and, finally, including the data. This data collection is being done to provide knowledge and direction for further research. Data were collected from various websites on the Web of Science and from Scopus databases. Additionally, data were gathered with the assistance of aggregator databases such as Scopus (scopus.com) and publishing databases such as Elsevier (sciencedirect.com), Inderscience, Taylor and Francis (tandfonline.com), Emerald Insight (emeraldinsight.com) and Google Scholar. These databases have been considered by a number of scholars to be reputable databases.

This research provided a thorough description of the key justifications for sustainable construction. This study demonstrated how the idea worked in practice by reviewing the literature on the relevance and analysis of sustainability in construction. This body of research identified crucial components of sustainable construction techniques and varied interpretations of sustainability in the construction industry. To better grasp the current application considerations in the construction sector, it also offered literature on sustainable construction methods. To determine the most effective strategy to make certain adjustments to the current construction processes, the literature also includes a wide range of sustainability-related topics in both developed and developing country contexts. This study also demonstrated the many perspectives and strategies for sustainable behaviors. Because the purpose of this study was to develop a strategy for implementing sustainable construction in New Zealand, it was of the utmost importance to shed light on the most well-known and prominent sustainable construction applications from across the world. The output of this aim provided the literature on construction practices to acquire insight into the ongoing conversations on sustainable practices and systems in the construction industry. This was done to obtain insight into the existing talks.

This research's contribution to the body of knowledge is demonstrated by the fact that this study has led to a better understanding of sustainable construction practices in the construction industry as well as the identification of the most significant challenges that businesses, organizations, educators and policymakers must face to improve their ability to put these strategies into practice. This research has provided a solid foundation for future research that aims to advance knowledge in this field by providing options for future research to evaluate the influence that the approach has had on enhancing the implementation of sustainable construction. Additionally, this study presents options for future research to evaluate the influence the approach has had on improving the implementation of sustainable construction. The successful completion of the research aim in the more traditional forms of higher education in the built environment can contribute to a better representation of new trends in the practice area associated with expanding and improving the construction industry sustainably.

In today’s digital era, talent recruitment can help address the growing shortage of skilled labor in the construction industry and promote sustainable growth. While existing research has explored the association between talent acquisition and local labor productivity or economic progress, the impact on construction growth deserves further study. This study aims to (1) explore the influence of talent recruitment on the growth of the construction industry and (2) analyze whether different regional characteristics shape the differential impact of talent acquisition on construction growth.

This research employs a quantitative approach, focusing on 35 major cities in China. A panel data regression model is utilized to analyze annual data from 2013 to 2018, considering variables like the construction talent recruitment index, value added in construction, gross regional product per capita and others. The study also examines regional heterogeneity and conducts robustness tests to validate the findings.

The results reveal a positive and significant correlation between talent recruitment and construction industry growth. This correlation is more pronounced in economically advanced and infrastructure-rich regions. The study also finds that factors like capital investment, educational attainment and housing prices significantly contribute to industry growth. Talent recruitment not only transforms local labor market dynamics but also drives demand for construction services, promoting industry growth through economies of scale.

This research constructs a new measurement for talent recruitment and provides new insights into the pivotal role of talent recruitment in the sustainable growth of the construction industry. It underscores the need for construction firms to tailor talent acquisition policies to their specific circumstances and regional developmental conditions. The findings offer practical guidance for driving regional growth within the sector, emphasizing the importance of talent recruitment as a key yet previously underappreciated factor in industry development.

The purpose of this study is to identify and assess new risks in construction projects that use 3D printing.

A mixed approach of both qualitative and quantitative methods was used. Literature review was conducted to extract 30 risks of 3D printing in construction. A survey was then developed to assess the probability and impact of these risks. In total, 37 respondents, who have experience and/or knowledge of 3D printing, completed the survey. The risk priority was calculated using a fuzzy logic approach. The main benefit of the proposed model is being able to use numerical and linguistic data in the risk assessment model.

The results show that the main risks, in terms of priority, are lack of codes and regulations for 3D printing in construction, delay in government approvals, shortage in labour skilled in 3D printed construction, lack of knowledge and information of 3D printed design concepts and changes in 3D construction codes and regulations.

This paper fills an identified gap in the literature related to 3D printing in construction and provides insights into the key risks affecting this disruptive technology.

Due to the influence of complex and intersecting factors, self-governed public open spaces (POSs) (managed by local communities) are subject to collective action dilemmas such as tragedy of the commons (overexploitation), free-riding, underinvestment and mismanagement. This review paper adopts a multi-dimensional and multi-tier social-ecological system (SES) framework proposed by McGinnis and Ostrom, drawing on collective action theory to explore the key institutional-social-ecological factors that impact POS self-governance.

In this paper, Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was utilized to systematically screen and review the relevant literature for the period from 2000 to 2023 in three databases: Web of Science, Scopus and Google Scholar. A total of 57 papers were chosen for in-depth analysis.

The literature review identified and categorized several variables associated with the self-organizing system of POS; consequently, an SES-based POS management framework was developed for the first time, consisting of 114 institutional-social-ecological sub-variables from different dimensions and three levels. Compared to ecological factors, among others, governance organizations, property-rights systems, socioeconomic attributes and actors' knowledge of SES have been commonly and primarily studied.

There is still room for the refinement of the conceptual SES-based POS collective action framework over the time (by adding in new factors), and indefinitely empirical research validating those identified factors is also worth to be undertaken, particularly testing how SES factors and interaction variables affect the POS quality (collective action).

The findings of this study can provide local policy insights and POS management strategies based on the identification of specific SES factors for relevant managers. Moreover, this research makes significant theoretical contributions to the integration of the SES framework and collective action theory with POS governance studies.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

Face is the most intuitive and representative feature at the individual level. Many studies show that beautiful faces help individuals and enterprises obtain economic benefits and form a high economic premium, but the discussion of their potential social value is insufficient. This study aims to focus on the impact of the personal characteristics of executives. It mainly analyzes the impact mechanism of CEO facial attractiveness on corporate social responsibility (CSR) decision-making, clarifying the social value of beauty from the perspective of CSR.

The authors use the regression model to analyze the panel data set, which was conducted by a sample of Chinese publicly listed firms from 2016 to 2018.

The study found that CEOs with high facial attractiveness are more active in fulfilling CSR, which can usually bring higher social benefits. CEOs with beautiful faces are prone to overconfidence, are optimistic about their ability and the future development of the enterprise and are more willing to increase their investment in CSR. CEO duality can positively regulate the positive correlation between a CEO’s facial attractiveness and CSR.

Based on the perspective of upper echelons theory, this paper explores the mechanism of CEO facial attractiveness on CSR. This study enriches the perspective of the upper echelon’s theoretical research and has essential enlightenment for CEO selection and training practice.