Search results

The rapid development and high penetration of digitalization have triggered profound changes in the energy sector. The purpose of this study is to integrate the government digital transformation into the analysis framework and discuss its impact on urban energy efficiency and its realization mechanism.

Using the “Information Benefit Pilot City” (IBC) policy as a quasi-natural experiment, and drawing on data from 285 prefecture-level cities in China from 2008 to 2019, this paper discusses how digital government affects urban energy efficiency by using difference-in-differences (DID).

The results show that digital governance significantly improves energy efficiency, and this conclusion remains reliable even after a series of robustness tests, endogeneity processing and sensitivity analysis. Heterogeneity results show that resource-based, eastern, high economic development level and high urbanization rate city digital government construction are more conducive to improving energy efficiency. The mediating effect shows that the influence mechanism of digital government on energy efficiency mainly includes reducing carbon emission, promoting green technology innovation and attracting talents.

(1) From the perspective of government digital transformation, this study supplements the way to improve energy efficiency and also expands the social dividend of government governance transformation. (2) Through quasi-experimental analysis of IBC policy, this paper solves the problem of difficulty in quantifying the government's digital transformation indicators. (3) The impact heterogeneity and realization mechanism are further discussed and the specific ways of digital government's impact on energy efficiency are revealed.

The growing awareness of climate risks associated with food safety issues has drawn the attention of stakeholders urging the food industry to carry out a sustainable food safety management system (FSMS). This study aims to investigate whether the critical success factors (CSFs) of sustainable FSMS can contribute to achieving climate neutrality, and how the adoption of FSMS 4.0 supported by the Industry Revolution 4.0 (IR 4.0) technologies moderates the impact of the CSFs on achieving climate neutrality.

Survey data from 255 food production firms in China and Vietnam were utilised for the empirical analysis. The research hypotheses were examined using structural equations modelling (SEM) with route analysis and bootstrapping techniques.

The results show that top management support, human resource management, infrastructure and integration appear as the significant CSFs that directly impact food production firms in achieving climate neutrality. Moreover, the results demonstrate that the adoption of FSMS 4.0 integrated with the three components (ecosystems, quality standards and robustness) significantly moderates the impact of the CSFs on achieving climate neutrality with lower inputs in human resources, infrastructure investment, integration and external assistance, and higher inputs in strengthening food safety administration.

This study provides empirical findings that fill the research gap in understanding the relationship between climate neutrality and the CSFs of sustainable FSMS while considering the moderating effects of the FSMS 4.0 components. The results provide theoretical and practical insights into how the food production sector can utilise IR 4.0 to attain sustainable FSMS for achieving climate neutrality.

Based on the resource bricolage theory, we investigate the impact of proactive market orientation and responsive market orientation on firms’ disruptive green innovation. We also examine the impact of resource bricolage on disruptive green innovation and the mediating role of resource bricolage.

Quantitative data were collected from 232 firms in China. Structural equation modelling was used to test hypotheses.

The result show that proactive market orientation had positive effect on firm’s disruptive green innovation, whereas responsive market orientation had negative effect on firm’s disruptive green innovation. In addition, resource bricolage positively promotes firm’s disruptive green innovation. Resource bricolage played a mediating role between proactive market orientation and disruptive green innovation. Resource bricolage had a suppressing effect between responsive market orientation and disruptive green innovation.

This study makes up for the deficiency of the existing research on the relationship between market orientation and enterprise disruptive green innovation, improves the guidance mechanism of disruptive green innovation.

Stereolithography (SLA) additive manufacturing (AM) technique has enabled the production of inconspicuous and aesthetically pleasing orthodontics that are also hygienic. However, the staircase effect poses a challenge to the application of invisible orthodontics in the dental industry. The purpose of this study is to implement chemical postprocessing technique by using isopropyl alcohol as a solvent to overcome this challenge.

Fifteen experiments were conducted using a D-optimal design to investigate the effect of different concentrations and postprocessing times on the surface roughness, material removal rate (MRR), hardness and cost of SLA dental parts required for creating a clear customized aligner, and a container was constructed for chemical treatment of these parts made from photocurable resin.

The study revealed that the chemical postprocessing technique can significantly improve the surface roughness of dental SLA parts, but improper selection of concentration and time can lead to poor surface roughness. The optimal surface roughness was achieved with a concentration of 90 and a time of 37.5. Moreover, the dental part with the lowest concentration and time (60% and 15 min, respectively) had the lowest MRR and the highest hardness. The part with the highest concentration and time required the greatest budget allocation. Finally, the results of the multiobjective optimization analysis aligned with the experimental data.

This paper sheds light on a previously underestimated aspect, which is the pivotal role of chemical postprocessing in mitigating the adverse impact of stair case effect. This nuanced perspective contributes to the broader discourse on AM methodologies, establishing a novel pathway for advancing the capabilities of SLA in dental application.

Although researchers have long recognized the importance of participating organizations’ (POs) relational behavior for mega construction projects (MCPs) performance, relational behavior may not be executed by POs without effective leadership from project owners. However, little is known about the mechanisms linking owners’ leadership styles to POs’ relational behavior. This study draws on full range leadership theory and role theory to examine the relationships between owners’ leadership styles (i.e. transformational and transactional) and relational behavior. POs’ role orientations (i.e. normative and economic) are considered as potential mediators.

Data were collected from 175 managers deeply involved in MCPs. Hierarchical regression model and bootstrapping methods were performed on the data to examine the direct effects of owners’ leadership on POs’ relational behavior and the mediating effects of POs’ role orientations.

The results revealed that both owners’ transformational and transactional leadership positively affect POs’ relational behavior, despite the former being higher than the latter, and indirectly influence relational behavior via POs’ normative and economic role orientation, respectively.

This study provides a clear picture of how owners’ leadership can motivate POs’ relational behavior to achieve high-quality inter-organizational relationships in MCPs. The findings can guide owners’ top manager selection by prioritizing those with transformational leadership, which is beneficial to achieving high-level relational behavior of POs. The results also imply that owners should pay greater attention to cultivating POs’ normative role orientation by encouraging teamwork and open communication to enhance their implementation of relational behavior.

Unlike previous research focusing more on intra-organizational leader–follower relationship within one PO, this study is one of the first to empirically confirm owners’ leadership as a critical antecedent of POs’ relational behavior, thus enhancing the theoretical understanding of inter-organizational relationship management in MCPs. Based on role theory, this study considers a novel organizational psychology mechanism, i.e. POs’ role orientations, as the mediator to unravel how owners’ leadership affects POs’ relational behavior, which was rarely invoked in MCP leadership literature.

This study aims to analyze and discuss the impact of corporate social responsibility (CSR) on firms’ performance, as well as to examine the interplay between CSR and the economy, society and innovation.

This paper collects data from 420 manufacturing firms across various geographical regions in China. By using a structural equation model, the paper investigates the impact of CSR on enterprise innovation, customer management capability, market competitiveness (MC) and firm financial performance.

The findings demonstrate that CSR performance positively contributes to enhancing the level of enterprise innovation, as well as customer management capability and market competitiveness. Furthermore, it assists enterprises in improving market competitiveness and elevating customer management capabilities. Thus, CSR can have a positive effect on the firm financial performance.

The outcomes presented in this paper offer valuable evidence regarding the influence of implementing CSR on different aspects of enterprise performance and innovation. Moreover, it provides practical recommendations for enterprises seeking to transition towards low-carbon practices and upgrade their manufacturing industry.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

The utilisation of products with recycled content (PwRC) in construction projects has been identified as a targeted way to achieve sustainable management of construction and demolition waste resources. However, sustainable applications of these resources are subject to a wide array of factors that demand a thorough investigation. This study, therefore, explores the motivations, barriers and strategies for optimal PwRC uptake using a multiple-case study approach.

This study adopted an interpretive multiple-case study approach. The case studies were selected from recently completed construction projects including two infrastructure projects, one commercial project and one residential project. A series of semi-structured interviews were carried out to collect the data. For each case study, four participants were interviewed; these participants represented design, client, supply and building teams.

The study revealed the main barriers, motivations and opportunities for adoption of PwRC resources in four construction projects. These factors are believed to influence the utilisation of PwRC to varying extents and/or in diverse ways. The findings also suggest that there is a significant opportunity for stakeholders to adopt more sustainable waste management practices, and the use of institutional drivers can help achieve this goal.

The primary research contribution of the study lies in proposing three key research directions: investigating regulatory constraints impacting the use of PwRC, addressing supply chain challenges and enhancing quality assurance.

The research has a practical contribution to the industry through a suite of actionable strategies to increase the uptake of PwRC. The strategies are mostly focussed on stakeholders' education, the regulation that supports PwRC and project management planning. The two major motivations – referring to two of the three pillars of sustainability (economy and environment) – provide a basis for organisational changes to ensure achieving sustainability in construction activities.

The objectives of this research are to analyze the sociodemographic and personality profiles most related to good academic time management among 845 students from different faculties at the University de Barcelona (UB) and to identify the explanatory factors of effective academic time management.

Poor time management is a common behavior among university students and an explanatory factor for academic failure. A sociodemographic questionnaire, the Procrastination Assessment Scale-Student (PASS), the Academic Time Management (ATM), the Brief Symptom Inventory (BSI-18) and the Big Five Inventory-10 (BFI-10) were administered.

The results reveal that female students, education majors and those with high academic performance show better time management than the rest of the student body. Additionally, students who have better academic time management are also more neurotic, more open to experience, more responsible and less prone to procrastination. The factors established as explanatory of good academic time management are neuroticism, openness to experience and low procrastination.

The implications of the results for promoting academic time management in university studies through specific actions are discussed.

This study aims to provide a precise understanding of how corporate sustainability information is used in socially responsible investing (SRI). The study is motivated by the lack of a recognised body of knowledge on this issue. This study, therefore, collates and reviews relevant studies (67 studies) to provide guidance to investors interested in SRI and identify a research agenda for academics desiring to contribute to this area.

This study conducts a systemic literature review employing recognised key words and searching the Web of Science. HistCite is utilised to ensure important cited studies are not missed from the collection. The review was conducted from two perspectives: (1) sources of sustainability information and (2) how the information is used in SRI.

The review identifies five major sources of sustainability information, including corporate reports, ESG ratings, industry affiliation, news and private communication with firms. These sources of information play different roles in the cross section of SRI strategies (i.e. negative and positive screening, active ownership and integration). This study provides guidance on how to use this information in SRI and provides recommendations for future research on how analysts interact with the information, how different informational characteristics impact implementation, ways to improve data quality, improvements to analysis methods and where data use needs to be extended into new strategies.

This review contributes to the SRI literature by inventorying studies of an important, yet omitted aspect, namely, sustainability information. This work also enriches the literature on corporate sustainability information by investigating how this information can be used for a specific purpose, namely, SRI. Given the increasing interest in SRI, this review will provide much-needed guidance for a range of practitioners, including investors and regulators.