Search results

Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.

We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.

Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.

Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

This study focuses on anti-corruption disclosure (ACD) as a critical indicator of a bank’s commitment to combat corruption. It seeks to measure the level of ACD in banking companies. Emphasizing the pivotal role of board directors in ensuring corporate accountability and transparency, the study further explores the connection between board composition and ACD.

This study adopts automated content analysis (using keyword search) to measure the level of ACD in the annual reports of listed banks in Bangladesh. Drawing upon agency theory and resource-dependence theory, the study proposes that the collective monitoring and resources facilitated by a well-structured board (size, gender diversity and independence) significantly influence a bank’s commitment to combat corruption. The paper employs linear regression to examine the hypotheses. The reliability of the findings is further validated through the application of the Generalized Method of Moments (GMM) and Quantile Regression.

The results indicate a steady rise in ACD over the sample period (2014–2022). The analysis establishes that larger board sizes and a greater presence of female directors are positively associated with ACD. Notably, the study identifies a critical mass of at least three female directors for a significant positive relationship between gender diversity on the board and ACD. However, no significant relationship is observed between board independence and ACD.

The study sheds light on the current state of ACD within the banking companies of a least-developed country. The findings carry significant implications for regulators to gauge banks' dedication to anti-corruption efforts and make informed decisions on issuing guidance for enhanced ACD. These findings can also assist regulators in assessing the implications of board composition and formulating guidelines within the corporate governance code.

This study contributes to the literature on ACD in the context of a least-developed economy. Notably, the study fills a research gap by exploring ACD in the banking industry. A key aspect of this study is its exploration of the determinants of ACD, explicitly emphasizing how board composition is likely to influence ACD.

This study investigates the impact of corporate governance on FinTech disclosure levels in Jordanian conventional and Islamic banks. It aims to determine whether governance mechanisms affect disclosure practices in the FinTech sector, exploring the interplay between governance and transparency in financial innovations.

The research methodology entails a thorough analysis of data from all 15 Jordanian conventional and Islamic banks listed on the Amman Stock Exchange, covering the period from 2015 to 2022. This study uses manual content analysis using a custom FinTech Disclosure Index (FDI) and quantitative analysis with a two-way clustered error regression model.

The findings show that corporate governance mechanisms, particularly board size, board meetings and “Big4” audit firms, are crucial in enhancing FinTech disclosure across conventional and Islamic banks. However, Islamic banks consistently show higher disclosure levels than their conventional counterparts, attributed to their distinct governance structures that emphasize ethical governance and transparency. These results indicate an awareness among decision-makers about the importance of business model transformation toward FinTech.

This study pioneers the introduction of FDI, using it for a novel comparative analysis of FinTech disclosure levels between Islamic and conventional banks. By exploring how various governance structures influence FinTech disclosure, this research provides fresh insights into the interplay between corporate governance and financial technologies in the banking sector.

Learning from past construction accident reports is critical to reducing their occurrence. Digital technology provides feasibility for extracting risk factors from unstructured reports, but there are few related studies, and there is a limitation that textual contextual information cannot be considered during extraction, which tends to miss some important factors. Meanwhile, further analysis, assessment and control for the extracted factors are lacking. This paper aims to explore an integrated model that combines the advantages of multiple digital technologies to effectively solve the above problems.

A total of 1000 construction accident reports from Chinese government websites were used as the dataset of this paper. After text pre-processing, the risk factors related to accident causes were extracted using KeyBERT, and the accident texts were encoded into structured data. Tree-augmented naive (TAN) Bayes was used to learn the data and construct a visualized risk analysis network for construction accidents.

The use of KeyBERT successfully considered the textual contextual information, prompting the extracted risk factors to be more complete. The integrated TAN successfully further explored construction risk factors from multiple perspectives, including the identification of key risk factors, the coupling analysis of risk factors and the troubleshooting method of accident risk source. The area under curve (AUC) value of the model reaches up to 0.938 after 10-fold cross-validation, indicating good performance.

This paper presents a new machine-assisted integrated model for accident report mining and risk factor analysis, and the research findings can provide theoretical and practical support for accident safety management.

This paper aims to assess the impact of regulatory changes on corporate environmental disclosure practices in Europe. More specifically, the authors perform a difference-in-differences analysis to study the impact of the Paris agreement (United Nations Climate Change Conference, COP21) and of the French Law 2015-992 on energy transition for green growth.

The sample consists of the listed companies belonging to the Euro Stoxx 50 index, and they are analysed over the 2010–2019 time horizon by means of an expert validated environmental disclosure dictionary and difference-in-differences analysis.

The main results show that both regulatory interventions contributed to improving corporate environmental disclosure. The authors also show that firms belonging to the most polluting sectors tend to provide more information on environmental matters, likely in an attempt to divert stakeholders’ attention.

By analysing an under-investigated topic, the paper calls for significant efforts by regulators to find the most suitable solutions to induce firms to increase their levels of transparency on the impact of environmental risks and on how these risks are managed.

The increasing adoption of informatization in the architecture, engineering, and construction (AEC) industries has raised the competency requirements for AEC practitioners. However, existing research primarily focuses on the integration of emerging technologies in AEC education programs, with little attention to the development of informatization-related competencies. Therefore, this paper aims to explore the competency requirements in the information age of the AEC industry.

Taking a policy perspective, this study investigates the competency requirements within the context of AEC industry informatization. By employing a competency-based theoretical framework, content analysis is conducted on China's policy document, the Outline of the Development of Informatization in the Construction Industry.

The study identifies crucial emerging technologies in the AEC industry, such as building information modeling (BIM), Big Data, Internet of things, networking, and cloud computing, along with their application scenarios. It considers various market players, including survey and design institutes, construction companies, and general contracting enterprises. Comparative analysis reveals the technology application patterns of these market players, shedding light on their preferences and perspectives. Based on these findings, the study proposes recommendations for competency requirements in the AEC industry.

This study extends the competency-based theory to AEC education from a macro perspective. The findings enhance understanding of informatization by providing insights into the related technologies, their applications, and the market players utilizing them. Moreover, the study's results have significant implications for AEC education, particularly in the design of curriculum systems for emerging technology-related fields.

Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.

The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.

The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.

The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.

This paper aims to examine the association between perceived firm risk and two reporting mechanisms: risk disclosure and earnings smoothing in the UK context.

This study juxtaposes three competing views, the “null”, the “divergence” and the “convergence” hypotheses, and empirically investigates whether risk disclosure and earnings smoothing affect firm perceived risk for a sample of large UK firms with rich and poor information environments. This study also uses the global financial crisis as an external shock on overall risk in the economy to investigate when and how managers use these two reporting mechanisms to shape the firm perceived risk.

This paper documents that risk disclosures have no significant effect on investors’ risk perceptions, consistent with risk disclosures containing boilerplate and generic statements about firm risk. This paper also finds that earnings smoothing reduces investors’ risk perceptions, reflecting investors’ interpretations about future firm performance. Additional tests reveal that earnings smoothing is not associated with perceived firm risk for firms with rich information environments and expanded risk disclosures. Furthermore, reporting smooth earnings decreases perceived firm risk following the global financial crisis. These findings are robust to alternative specifications and measures of earnings smoothing as well as post-filing perceived firm risk.

This study does not distinguish between the garbling role and the informational role of earnings smoothing. The risk disclosure measurement used in this study, developed based on UK annual reports, may limit the generalizability of findings to other countries.

The findings suggest that managers should revise their risk disclosure strategies to provide in-depth details on firm risk. Investors might require information and thorough assessment to evaluate investment risks when firms provide generic risk disclosures and smoothed earnings by consulting sources like financial intermediaries. Regulators should keep an eye on firms reporting boilerplate risk disclosures and on how smoothing earnings impacts the firm perceived risk following economic turmoil, to guide interventions that promote market stability.

The findings provide new insights into when and how managers use their financial reporting discretion to make firms appear less risky and, therefore, influence investors’ risk perceptions.

The purpose of this transformative service research (TSR) is to apply, innovate on and extend the understanding of service-dominant logic (SDL) perspectives, sustainable service ecosystem design ideas, transformative value and meeting sustainable development goals (SDGs). This study explores these through volunteers’ lived experiences and their perceived health and well-being outcomes in the context of botanic gardens as health-care service settings.

A total of 3 UK botanic gardens and 84 volunteers between 22 and 87 years of age participated in this qualitative study. Volunteering stories were collected through emails, telephone exchanges, online and in-person interviews, free-flowing discussion and field observations. These were coded and analysed by using computer-assisted qualitative data analysis software, NVivo 14 Plus and Leximancer. Thematic analysis facilitated the mapping of well-being outcomes highlighting transformative value against existing health and well-being indices.

Insights extend knowledge into SDL, TSR and transformative value experienced by volunteers across three UK botanic garden service ecosystems. Environmental, organisational and personal factors, and physical, mental and social health outcomes are presented to emphasise transformative value experienced, especially in retiree volunteers. Theoretical contribution is in the form of empirical evidence to support and extend insights about transformative value and more so, significant epistemological change and meeting SDGs in botanic gardens. Results add to contemporary TSR on health-care-related well-being outcomes and ideas regarding sustainable service ecosystem design.

It is recommended that service research be extended across other botanic gardens, as well as other novel underexplored contexts for comparative studies of transformative value. Continued development and consideration of service designs as ongoing efforts to redefine and reimagine services marketing innovation for botanic gardens are recommended. Botanic gardens are complex service ecosystems worthy of rigorous service research to capture and measure the impact and outcome of ongoing work of the sector in advancing SDGs and having a transformative effect on individual and societal health and well-being.

This study highlights opportunities for greater area-based, coordinated, collaborative, multi-stakeholder services marketing partnerships for strategic sustainable service ecosystem design for the botanic gardens and health-care sectors. These sectors can make better use of service research and marketing to further innovate and co-develop health and well-being strategies, campaigns and opportunities to develop services to transform and influence positive health and well-being outcomes for people. Results reveal greater opportunities for collaborative partnership and services marketing’s role and practice for the ongoing vitality and viability of botanic gardens. Joint efforts would enable innovation on sustainable service ecosystem design, advancing SDGs and improving life on planet Earth.

Transformative value linked to newfound life experiences and meaning to life after retiring with a range of factors, and health and well-being outcomes were prominent. Social connections to the wider community were present, revealing links to a range of people who may not have traditionally had contact with botanic garden heritage and their strategic efforts. Therefore, it is services marketing opportunities for botanic gardens that hold one key to greater transformative value, sustainability and greater influence and impact on individual and societal health and well-being.

To the best of the author’s knowledge, this is the first TSR on botanic gardens as health-care service settings, resulting in a conceptual framework on transformative value and well-being outcomes in meeting SDGs. It extends insights on SDL, sustainable service ecosystem design and roles of marketing for the common good. Botanic gardens are unique research institutes, highly acclaimed for research, conservation, education and displays of special botanical collections, as well as providing health care, among other impactful SDG opportunities. This can be made more explicit through ecosystemic thinking, service research and integrated services marketing of botanic garden’ roles and contributions worldwide.