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This study aims to investigate the influence of inventors’ abilities to acquire external knowledge, provide broad and professional knowledge and patenting output (i.e. different types of inventors) on the formation of structural holes.

The authors collected 59,798 patents applied for and granted in the USA by 33 of the largest firms worldwide in the pharmaceutical industry between 1975 and 2014. A random-effects tobit model was used to test the hypotheses.

The inventors’ ability to acquire external knowledge contributes to the formation of structural holes. While inventors’ ability to provide broad knowledge positively affects the formation of structural holes, their ability to provide professional knowledge works otherwise. In addition, key inventors and industrious inventors are more likely to form structural holes than talents.

The results identify individual factors that affect the formation of structural holes and improve the understanding of structural hole theory. This study is unique in that most scholars have studied the consequences of structural hole formation rather than their antecedents. Studies on the origin of structural holes neglect the effect of inventors’ knowledge abilities and patenting output. By addressing this gap, this study contributes to a more comprehensive theoretical understanding of structural holes. The results can guide managers in managing structural holes in accordance with inventors’ knowledge abilities and patenting outputs, which optimize the allocation of network resources.

The paper aims to reveal the intellectual structure of studies on artificial intelligence (AI) in the fields of tourism and hospitality. Evaluations regarding the intellectual structure have been made based on co-author, co-word and citation.

The study is exploratory in nature. The study, using bibliometric analysis, provides a Web of Sciences (WOS) overview. The data has been obtained from the WOS database by coding as “artificial intelligence” and “tourism” and “hospitality.” VOSviewer program has been used to obtain and analyze the data.

The findings of the research show that studies on the use of AI in tourism and hospitality have become very popular, especially in the last 4 years. The authors of the study are working in the tourism and hospitality fields and have a high h-index. Generally, in current AI studies in tourism, topics such as robot, automation, ChatGPT, technology adoption and mechanical learning are studied. It has also been determined that topics related to the future of destinations and literature reviews are also discussed.

Although this paper examines all studies identified as a result of filtering, the analysis is limited to 195 studies. However, due to the widespread use of AI in tourism-related studies recently, bibliometric analysis has been made with extensive filtering. As studies on the subject become more widespread in the coming years, it would be useful to repeat similar studies by filtering with more specific quotas.

There are a few similar studies on the subject in the field. However, these studies need to be repeated at certain periods. This paper contributes to monitoring the literature of AI studies, which are new to use in tourism and hospitality, and to the formation of a theoretical framework on the subject.

Three-dimensional (3D)printed skulls for neurosurgical training are increasingly being used due to the widespread access to 3D printing technology, their low cost and accuracy, as well as limitations and ethical concerns associated with using human cadavers. However, little is known about the risks of airborne particles or volatile organic compounds (VOCs) released while drilling into 3D-printed plastic models. The aim of this study is to assess the level of exposure to airborne contaminants while burr hole drilling.

3D-printed skull samples were produced using three different materials (polyethylene terephthalate glycol [PETG], white resin and Bone^STN) across three different 3D print processes (fused filament fabrication, stereolithography [SLA] and material jetting). A neurosurgeon performed extended burr hole drilling for 10 min on each sample. Spot measurements of particulate matter (PM2.5 and PM10) were recorded, and air samples were analysed for approximately 90 VOCs.

The particulate matter for PETG was found to be below the threshold value for respirable particles. However, the particulate matter for white resin and Bone^STN was found to be above the threshold value at PM10, which could be harmful for long periods of exposure without personal protective equipment (PPE). The VOC measurements for all materials were found to be below safety thresholds, and therefore not harmful.

To the best of the authors’ knowledge, this is the first study to evaluate the safety of 3D-printed materials for burr hole surgical drilling. It recommends PETG as a safe material requiring minimal respiratory control measures, whereas resin-based materials will require safety controls to deal with airborne particles.

The choice of crops to produce at a location depends to a large degree on the climate. As the climate changes and food demand evolves, farmers may need to produce a different mix of crops. This study assesses how much cropland may be subject to such upheavals at the global scale, and then focuses on China as a case study to examine how spatial heterogeneity informs different contexts for adaptation within a country.

A global agricultural economic model is linked to a cropland allocation algorithm to generate maps of cropland distribution under historical and future conditions. The mix of crops at each location is examined to determine whether it is likely to experience a major shift.

Two-thirds of rainfed cropland and half of irrigated cropland are likely to experience substantial upheaval of some kind.

This analysis helps establish a global context for the local changes that producers might face under future climate and socioeconomic changes. The scale of the challenge means that the agricultural sector needs to prepare for these widespread and diverse upheavals.

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 circular economy (CE) promotes the recovery of value from waste while also working towards achieving long-term environmentally sustainable goals. The goal of this research is to explore the challenges, opportunities, future scope and green practices that small and medium-sized firms (SMEs) face as they move from the linear economy to the CE.

Based on a structured questionnaire, a survey was conducted with representatives from 163 SMEs in India. The data were analysed using co-variance based structural equation modelling technique.

This research identifies various challenges, including consumer acceptability, worries about awareness, recyclability issues, financial constraints and the absence of a defined management plan for SMEs in adopting the CE. Further, strong management will, innovation, technical up-gradation, training of employees, employee motivation and appropriate guidelines are recognized as essential possibilities for CE implementation.

While there has been some work on CE, no studies have directly compared these efforts with the goal of shifting from a linear economy to a CE. Given the transient nature of many archives, it is critical that the efforts put into them and the opinions of those who work in them be recorded so that communities can benefit from a shared linear economy in making decisions about their own history.

The Covid-19 pandemic appears to have engendered heterogeneous effects on individuals’ labour market prospects. This paper focuses on two possible sources of a heterogeneous exposition to labour market risks associated with the pandemic outbreak: the routine task content of the job and the teleworkability. To evaluate whether these dimensions played a crucial role in amplifying employment and wage gaps among workers, we focus on the case of Italy, the first EU country hit by Covid-19.

Investigating the actual effect of the pandemic on workers employed in jobs with a different degree of teleworkability and routinization, using real microdata, is currently unfeasible. This is because longitudinal datasets collecting annual earnings and the detailed information about occupations needed to capture a job’s routine task content and teleworkability are not presently available. To simulate changes in the wage distribution for the year 2020, we have employed a static microsimulation model. This model is built on data from the Statistics on Income and Living Conditions (IT-SILC) survey, which has been enriched with administrative data and aligned with monthly observed labour market dynamics by industries and regions.

We measure the degree of job teleworkability and routinization with the teleworkability index (TWA) built by Sostero et al. (2020) and the routine-task-intensity index (RTI) developed by Cirillo et al. (2021), respectively. We find that RTI and TWA are negatively and positively associated with wages, respectively, and they are correlated with higher (respectively lower) risks of a large labour income drop due to the pandemic. Our evidence suggests that labour market risks related to the pandemic – and the associated new types of earnings inequality that may derive – are shaped by various factors (including TWA and RTI) instead of by a single dimension. However, differences in income drop risks for workers in jobs with varying degrees of teleworkability and routinization largely reduce when income support measures are considered, thus suggesting that the redistributive effect of the emergency measures implemented by the Italian government was rather effective.

No studies have so far investigated the effect of the pandemic on workers employed in jobs with a different degree of routinization and teleworkability in Italy. We thus investigate whether income drop risks in Italy in 2020 – before and after income support measures – differed among workers whose jobs are characterized by a different degree of RTI and TWA.

This study developed new measures of the routine and non-routine task contents of managerial, professional, technical, and clerical occupations from a workload perspective. Here, we present a comparative analysis of the workload structures of state and industrial sector employees.

Our method involves detailed descriptions of work processes and an element-wise time study. We collected and analysed data to obtain a workload structure that falls within three conceptual task categories: (i) non-routine analytic tasks, (ii) non-routine interactive tasks and (iii) routine cognitive tasks. A total of 2,312 state and industrial sector employees in Kazakhstan participated in the study. The data were collected using a proprietary web application that resembles a timesheet.

The study results are consistent with the general trend reported by previous studies: the higher the job level, the lower the occupation’s routine task content. In addition, the routine cognitive task contents of managerial, professional, technical, and clerical occupations in the industrial sector are higher than those in local governments. The work of women is also more routinary than that of men. Finally, vthe routine cognitive task contents of occupations in administrative units are higher than those of occupations in substantive units.

Our study sought to address the challenges of using the task-based approach associated with measuring tasks by introducing a new measurement framework. The main advantage of our task measures is a direct approach to assessing workloads consisting of routine tasks, which allows for an accurate estimation of potential staff reductions due to the automation of work processes.

The purpose of this paper is to scrutinise the effectiveness of four derivative exchanges’ enforcement efforts since 2007. These exchanges include the Commodity Exchange Inc. and ICE Futures US from the United States and ICE Futures Europe and the London Metal Exchange from the UK.

The paper examines 799 enforcement notices published by four exchanges through a behavioural science lens: HUMANS conceived by Hunt (2023) in Humanizing Rules: Bringing Behavioural Science to Ethics and Compliance.

The paper finds the effectiveness of the exchanges’ enforcement efforts to be a mixed picture as financial markets transition from the digital to artificial intelligence era. Humans remain a key cog in the wheel of market participants’ trading operations, albeit their roles have changed. Despite this, some elements of exchanges’ enforcement regimes have not kept pace with the move from floor to remote trading. However, in other respects, their efforts are or should be, effective, at least in behavioural terms.

The paper’s findings are arguably limited to exchanges based in Anglophone jurisdictions. The information published by the exchanges is variable, making “like-for-like” comparisons difficult in some areas.

The paper makes several recommendations that, if adopted, could help exchanges to increase the potency of their enforcement programmes.

A key aim of the paper is to shift the lens through which the debate concerning the efficacy of exchange-level oversight is conducted. Hitherto, a legal lens has been used, whereas this paper uses a behavioural lens.

The concept of banking reputation has gained significant attention due to its relevance in the banking industry. A strong reputation has become crucial for a bank’s success, as it affects trust, credibility and stakeholders' perceptions. However, understanding and managing reputation in the banking sector involves several challenges. This study aims to analyze the field of banking reputation research through bibliometric analysis.

It explores the evolution of research in this area, identifies key journals, articles and authors, examines the main research streams, and identifies research fronts and opportunities for future advancement.

The findings reveal that banking reputation research has evolved over time, with multiple perspectives and viewpoints. Key journals and authors in the field are identified, and leading research streams are highlighted. The study also uncovers the conceptual and intellectual structure of the research domain, providing insights into the complex and multidimensional nature of banking reputation. Furthermore, the study emphasizes the importance of corporate social responsibility, sustainability practices and gender diversity in shaping a bank’s reputation. These factors play a significant role in attracting and retaining customers, accessing financial markets and securing funding.

The results contribute to the existing body of knowledge and provide researchers and practitioners with valuable insights for further exploration.

The paper concludes by outlining potential avenues for future research in the field of banking reputation.