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Drawing upon a political economy approach, this article aims to analyze the transformations in the labor market within the context of contemporary capitalism, focusing on the phenomenon of financialization.

Financialization is defined as a distinct wealth pattern marked by a growing proportion of financial assets in capitalist wealth. Within financial markets, corporate performance is continuously assessed, in a process that disciplines management to achieve expected financial results, with consequences throughout corporate management.

We find that this phenomenon has implications for labor management, resulting in the intensification of labor processes and the adoption of insecure forms of employment, leading to the fractalization of work. These two mechanisms, added to the indebtedness of workers, constitute three elements for disciplining labor in contemporary capitalism.

We argue that these forms of discipline constitute a subsumption of labor to finance, resulting in an increase in labor exploitation. This formulation of the relationship between financialization and changes in the realm of labor also contributes to understanding the unrealizing potential of social free time in contemporary capitalism.

This study investigated whether job resources (i.e. strengths use support, career self-management and person–job [PJ] fit) moderate the relationship between perceived involvement in a career accident (PICA) and work engagement.

The study adopted a time-lagged design (N = 398; 69% male), and data were collected at two-point of measurements among Nigerian university academics.

Results of the present study indicated that employees with higher PICA scores reported low work engagement. Strength use support had significant direct positive main effects on employee work engagement and also produced a significant moderation effect between PICA and work engagement. Career self-management (CSM) was positively related to employee work engagement. The moderation effect of CSM on the relationship between PICA and work engagement was also significant. Results of the present study further indicated that P-J fit was related positively to work engagement and also moderated the negative relationship between PICA and work engagement.

Dearth of employment opportunities has led individuals to choose their career by chance, but empirical studies that validate this assertion are lacking. Few available studies on career accident were exclusively conducted in Western European contexts. The current study therefore deepens the understanding of career accident and work engagement in a neglected context such as Nigeria.

The aim of this study is, from the perspective of artisan entrepreneurship, to trace and analyse the artisan's profile in the sustainable development of low population density cross-border territories, using the quintuple helix innovation model.

Ten semi-structured interviews were conducted with cultural and traditional artisans to achieve the proposed objective using a qualitative approach. The artisans are from Northeast Portugal (Bragança, Miranda do Douro, Mogadouro, Vimioso and Vinhais) and Northern Spain (Province of Zamora). The interviews were conducted face-to-face between May and June 2022. The interviews were manually transcribed and subjected to content and lexical analyses using IRaMuTeQ software.

An artisan was identified as an enterprising individual whose marketed handicraft pieces transmit the values and teachings of his community. Innovation, technology, sustainability and circular economy in a family environment, where dedication, resilience, happiness and hard work transmit an identity that places the artisan and his artisan practice as the driving force for the enhancement and promotion of his territory, cultural heritage and identity.

This work is the first study to address and treat the issue of artisan entrepreneurship by analysing and defining the cultural-based and traditional artisan profile in a cross-border and low population density territorial context.

The purpose of this study was to establish the cause-effect relationship between determinants of trust in the buyer–supplier integration and the procurement performance of large manufacturing firms in Tanzania.

The study surveyed 52 firms from Temeke Municipality, Tanzania using questionnaire subjected to one procurement manager and one stores manager tallying a sample size of 104 respondents. Explanatory design was employed due to the presence of cause–effect relationship and the null hypotheses were tested using binary logistic regression technique at p values < 0.05 and ExpB > 1.

Mutual goals, geographical vicinity among partners, and supplier reliability are significant for the procurement performance of the manufacturing firms in Tanzania, whereas interpersonal and inter-organizational trusts and perceived buyers’ confidence are of no significant impact.

Buyer–supplier integration is a recently embraced and paramount practice for the manufacturing firms in Tanzania. Therefore, longitudinal study would further add value. The presence of the causality from the tested hypothesis appeals for the necessity of progress tracking.

Causality has been established, and a framework has been developed for the performance of large manufacturing firms using trust of buyer–supplier integration.

There shall be creation of more employment opportunities and timely availability of materials from large manufacturing firms in Tanzania.

Anchored on transaction cost economics and resource dependency theories, the study disclosed the root cause of procurement performance in the context of manufacturing firms in Tanzania whilst considering trust as a resource advantage of buyer–supplier integration.

The purpose of this study is to investigate artificial intelligence (AI) as enabler of future library services, with consideration to how prepared are librarians in African university libraries.

This study applied the interpretive content/document analysis of literature harvested from different databases of Scopus and Web of Science. AI could be used to perform daily routines in circulation, serial, reference and selective dissemination of information among others. It could also be applied to the provision of innovative services of recognition of library activities such as answering research quarries, cataloguing and classification of library materials and management of library system software of different databases within the library systems.

It could be deduced from the study that AI would continue to serve as a panacea to future library services irrespective of its geographical context. Due to the evolving nature of knowledge growth, AI having its roots in the field of engineering has been found useful to support future library services. The support accrued from library service delivery in the library profession has made librarians continue to interact with other intelligent machines that can demonstrate human behaviour even though they are not real human beings. The behaviour of machines and AI where human beings play a significant role has brought many renovations in the management of complex tasks of processing, communication, knowledge representation, decision making and suggestions, on potentials of diverse work operations.

The understanding that the present paper portrays in the context of future library services is that there is no way the AI could function without a human interaction perspective when drawing an analogy from computer science, information science and information systems fields of study.

The interest of users across their background would be strengthen if AI advances transformed the handling complex tasks of processing, communication, knowledge representation, decision-making and giving suggestions, among other things. The possibilities of diverse work operations from empirical evidence of studies consulted in recent times gave the authors the impetus to consider AI as the enabler of future library services.

The increasing demands from library patrons have prompted librarians to adapt their methods of delivering services. These emerging technologies have also brought about shifts in approaches to teaching and learning. Consequently, the recent surge in digital technology-driven service innovations has ushered in a fresh paradigm for education and research. In response to these changes, librarians are actively seeking novel and innovative technologies to enhance user experiences within their libraries. They serve as catalysts for introducing modern and advanced technologies, consistently adapting to contemporary tools that enhance their offerings.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.

The current paper aims at exploring negative aspects in reviews about Airbnb listings in Athens, Greece.

The aspect-based sentiment approach (ABSA), a subset of sentiment analysis, is used. The study analyzed 8,200 reviews, which had at least one negative aspect. Based on dependency parsing, noun phrases were extracted, and the underlying grammar relationships were used to identify aspect and sentiment terms.

The extracted aspect terms were classified into three broad categories, i.e. the location, the amenities and the host. To each of them the associated sentiment was assigned. Based on the results, Airbnb properties could focus on certain aspects related to negative sentiments in order to minimize negative reviews and increase customer satisfaction.

The study employs the ABSA, which offers more advantages in order to identify multiple conflicting sentiments in Airbnb comments, which is the limitation of the traditional sentiment analysis method.

The purpose of this study is to analyze the impact of teachers’ performance expectancy, teachers’ effort expectancy, teachers’ performance anxiety, teachers’ engagement, perceived student engagement, teachers’ digital competence, teachers’ normalization ease and perceived organizational support as predictors of teachers’ satisfaction with online teaching-learning, especially during a pandemic in the context of hospitality, tourism and travel education.

Conceptually, this study is grounded in the normalization process theory and examines teachers’ satisfaction by applying the unified theory of acceptance and use of technology model. To test the proposed model, 374 complete survey forms were received for data analysis from teachers engaged with higher education institutes offering courses in the field of hospitality, travel and tourism. Minor modifications were made to the survey instrument based on inputs received after a pilot study.

The model was tested using confirmatory factor analysis and structural equation modeling. Of the eight constructs predicting teachers’ satisfaction in the online teaching-learning environment, two constructs, that is, teachers’ effort expectancy and teachers’ digital competence, were found to have an insignificant relationship. This finding hints at the emergence of a “new normal.”

This study contributes to the literature by presenting and validating a theory-driven framework that accentuates the factors influencing online teaching during the outbreak of a pandemic. This study further extends the unified theory of acceptance and integrates it with the normalization process theory to test and validate the model in the unique context of hospitality education which is considered to be highly practice oriented.

The COVID-19 pandemic compelled educational institutions to shift to online learning modes. This is unprecedented for students and teachers of hospitality, travel and tourism, especially in a developing country like India, and it has brought with it a new set of challenges and opportunities. With the extension of the pandemic-induced lockdown in educational institutions, teachers – and other stakeholders – must adapt to this new normal of reliance on remote education.

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging behind other disciplines. This paper aims to provide a review of the current use of data analytics in project delivery encompassing both academic research and practice to accelerate current understanding and use this to formulate questions and goals for future research.

We propose to achieve the research aim through the creation of a systematic review of the status of data analytics in project delivery. Fusing the methodology of integrative literature review with a recently established practice to include both white and grey literature amounts to an approach tailored to the state of the domain. It serves to delineate a research agenda informed by current developments in both academic research and industrial practice.

The literature review reveals a dearth of work in both academic research and practice relating to data analytics in project delivery and characterises this situation as having “more gap than knowledge.” Some work does exist in the application of machine learning to predicting project delivery though this is restricted to disparate, single context studies that do not reach extendible findings on algorithm selection or key predictive characteristics. Grey literature addresses the potential benefits of data analytics in project delivery but in a manner reliant on “thought-experiments” and devoid of empirical examples.

Based on the review we articulate a research agenda to create knowledge fundamental to the effective use of data analytics in project delivery. This is structured around the functional framework devised by this investigation and highlights both organisational and data analytic challenges. Specifically, we express this structure in the form of an “onion-skin” model for conceptual structuring of data analytics in projects. We conclude with a discussion about if and how today’s project studies research community can respond to the totality of these challenges. This paper provides a blueprint for a bridge connecting data analytics and project management.

This study aims to test the mediating effect of psychological distress and bullying victimization on the relationship between alexithymia and fibromyalgia (FM) among school adolescents.

This study used cross-sectional, correlational design. Data was collected using self-administered questionnaire. The sample consisted of 1,000 school adolescents at Grade 9–12 who were recruited randomly using multistrategic sampling technique.

The analysis showed that alexithymia was a significant predictor of FM (odds ratio [OR] = 1.065). Psychological distress was also a significant predictor of FM; however, its mediating effect resulted in drop of OR to 1.041. The joined effect of bulling victimization and psychological distress found to be significant although OR dropped from 1.065 to 1.039.

The study highlights the significant role of school health nurses and mental health counselors to early detect and direct mental health interventions toward significant psychological problems among school adolescents.

I affirm this information has not been published or submitted for publication elsewhere. All authors approve the content of the manuscript and have contributed significantly to research involved/ the writing of the manuscript. The authors affirm their commitment to transfer copyright ownership to your journal if the manuscript is accepted for publication. The authors also affirm they will obtain any other copyright permission if deemed necessary within 30 days of acceptance for publication. All identifying information regarding the study participants has been omitted and this study was approved by the IRB at School of Nursing of the University of Jordan. The research conforms to the provisions of the Declaration of Helsinki in 1995 (as revised in Brazil, 2013). All participants gave informed consent for the research, and that their anonymity was preserved. None of the authors has financial or personal matters that may pose a conflict of interest.