Search results

Due to the uniqueness of individual construction projects, identifying the dominant risk factors is needed for risk mitigation in ongoing and future projects. This study aims to identify the dominant construction supply chain risk (CSCR) factors, based on studies conducted between 2002 and 2022.

The study adopts the preferred reporting items for systematic reviews and meta-analysis (PRISMA) procedure to identify, screen and select relevant articles in order to provide a bibliography and annotation of the prevalent risks in the supply chains. A descriptive analysis of the findings then follows.

The study’s findings have highlighted the three most prevalent risks in the construction supply chain (poor communication across project teams, changes in foreign currency rate, unfavorable climate conditions) as reported in literature, that project teams need to pay closer attention to and take proactive steps to mitigate.

Due to limitations imposed by the chosen research methodology, tools, time frame and article availability, the study was unable to examine all CSCR-related papers.

The results will serve as a useful roadmap for risk/supply chain managers in the construction industry to take strategically proactive steps towards allocating resources for CSCR mitigation efforts.

Context-specific research on the impact of social and cultural risks on the construction supply chain would be beneficial, due to emerging social network risk factors and the complex socio-cultural settings.

There is presently no study that has reviewed extant studies to identify and compile the dominant risk factors (DRFs) associated with the supply chain of construction projects for ranking in the supply chain risk management process.

This article aims to identify and review existing studies on the adoption and compliance of International Financial Reporting Standards (IFRS) in Africa.

The methodology involves a sole focus on studies conducted with an African sample, using a bibliometric method and data from the Web of Science (WoS) database. Visualizations from VOSViewer and Biblioshiny software are employed to identify the dominant authors, journals and countries contributing to research in the region.

The findings reveal existing collaborations among authors in the field. However, the study emphasizes the need for additional research to enhance the intellectual structure of the research domain, as the majority of related documents are concentrated within twenty articles with at least one citation.

The practical implications underscore the importance of collaboration in practice, emphasizing the need for cooperation among corporations, experts and regulatory agencies involved in IFRS adoption and compliance in Africa. By fostering collaborative efforts and knowledge-sharing among corporations, experts and regulatory agencies, practitioners can enhance their understanding, streamline implementation processes and improve compliance methods.

This review is one of the few to explicitly conduct a bibliometric review of IFRS adoption and compliance studies in Africa, providing a foundation for future research to determine the current direction of IFRS studies in this region.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

Extant literature in supply chain management tends to address a portion of the product flow to make food accessible to clients in need. The authors present a broader view of food insecurity and present nuances relevant to appreciate the complexities of dealing with this social problem.

The authors conducted an inductive study to reveal the deep meaning of the context as managers of nonprofit organizations (NPO) define and address food insecurity. The focus was on a delimited geographic area for capturing interactions among NPOs which have not been described previously.

This study describes the role of supply chains collaborating in unexpected ways in the not-for-profit context, leading to interesting insights for the conceptual development of service ecosystems. This is relevant because the solution for the food insecure stems from the orchestration of assistance provided by the many supply chains for social assistance.

The authors introduce two concepts: customer sharing and customer release. Customer sharing enables these supply chains behave like an ecosystem with no focal organization. Customer release is the opposite to customer retention, when the food insecure stops needing assistance.

The authors describe the use of customer-centric measures of success such improved health measured. The solution to food insecurity for an individual is likely to be the result of the orchestration of assistance provided by several supply chains.

The authors started asking who the client is and how the NPOs define food insecurity, leading to discussing contrasts between food access and utilization, between hunger relief and nourishment, between assistance and solution of the problem, and between supply chains and ecosystems.

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the authors address the role of position–practice relations and irresistible causal forces in this conduct.

The authors examine SID-making (SIDM) practices in four case organisations operating in highly competitive markets, conducting interviews with managers at various levels and analysing company documents. Drawing on strong structuration theory, the authors show how managerial decision makers draw upon their knowledge of organisational context when exercising agency in SIDs.

The authors provide insights into how SIDM behaviour, specifically agents’ conduct, is shaped by a combination of position–practice relations and the agents’ comprehension of their organisation’s context.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice. Particularly, the authors contribute to this literature by identifying irresistible causal forces and illuminating why actors might not resist in SIDM processes, despite having the potential to do so.

The main purpose of this article is to understand the motivations for Bhutanese students to study hospitality and tourism courses. The second objective is to analyse what countries are the preferred destinations for study abroad and visitation for students. This includes focussing on new course topic areas such as sustainability for business in hospitality and tourism courses.

A quantitative methodology approach was undertaken with two surveys administered to the first and second student intakes into the Bhutan Middle Management Hotel Program. Motivational and reasoned action theory form the basis of the theoretical framework to understand behavioural intentions regarding educational choices in hospitality and tourism courses.

The results of the surveys indicate that the main motivations to study hospitality and tourism are for attraction, career opportunities, status, broader benefits and aptitude. In addition, it was found that students studying hospitality and tourism in Bhutan are likely to stay in the sector for a long period of time thereby contributing to the economic and social development of Bhutan. Moreover, it was found that the United Nations Sustainable Development goals are increasingly being integrated into the tourism and hospitality sector, which is influencing students to study these topic areas.

The results of this study will help government and hospitality providers support educational training programs by focussing on new education topic areas. This study is limited to Bhutan.

The results of this study will help government and hospitality providers support educational training programs by focussing on new education topic areas such as sustainability for business management. This will enable hospitality and tourism providers in Bhutan to update their curriculum and to focus on emerging industry needs.

This is amongst the first studies on Bhutanese students motivations for studying hospitality and tourism. It will provide practical and policy advise about how to train workers in order to become less reliant on foreign training providers and the importance of integrating sustainability topics in course design.

Drawing on the theory of memory-dominant logic, this study aims to examine how the substantive staging of the servicescape, experience co-creation, experiential satisfaction and experience intensification affect experience memorability and hedonic well-being in the case of unmanned smart hotels.

An online survey was used, with the target respondents being hotel guests people aged 18 years and older who had been recent guests of the FlyZoo Hotel in Hangzhou, China. Data were collected online from 429 guests who had stayed in the hotel between April and June 2023. Data analysis was undertaken using structural equation modelling.

The results suggest that all the proposed four constructs are positive drivers of a memorable unmanned smart hotel experience. The relationship between the memorability of the hotel experience and hedonic well-being was found to be significant and positive.

Unmanned smart hotels should ensure that all smart technologies function effectively and dependably and offer highly personalised services to guests, allowing them to co-create their experiences. This will lead to the guest receiving a satisfying and memorable experience. To enable experience co-creation using smart technologies, unmanned smart hotels could provide short instructional videos for guests, as well as work closely with manufacturers and suppliers to ensure that smart technology systems are regularly updated.

This study investigates the antecedents and outcomes of a novel phenomenon and extends the concept of memorable tourism experiences to the context of unmanned smart hotels.

The academic library’s physical capacity and its service obligations to local users structured the traditional print collection. Largely freed of these constraints, the digital collection manager enjoys unprecedented freedoms but now contends with a collection susceptible to resource sprawl and scope ambiguity. This exploratory study aims to consider the possibility that intra-field social processes help to structure and routinize digital collection practice.

Lacking the constraints to which print collections are subject, electronic resource and digital library collections are more likely to reflect idiosyncratic institutional interests and therefore, to demonstrate significant variation. Evidence of homogeneity may suggest the influence of heretofore underexplored social structures. To determine the extent of such homogeneity, the author performed exploratory/descriptive content analyses on ten electronic resource collection development policies and six digital library collection development policies.

The data reveal among both the electronic resource and digital library collection policies significant uniformity. Content analyses demonstrate consistent themes (e.g. media, audience, selection priorities, etc.) and rhetoric. These findings lend support to the study’s central hypothesis regarding latent social structures. Analyses also reveal a set of unanticipated constraints unique to digital collection management.

Despite the breadth and maturity of literature addressing the Digital Turn in academic librarianship, relatively little attention has been paid to the social dimensions of collection management. This work represents an important corrective and suggests new theoretical approaches to the study of digital collection practice.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.

The study aims to provide a critical review of the extent to which digital technologies are likely to replace human labour, the exponential rise in the amount of work to be done and how far distinctively human skills are future-proofed and therefore likely to be in short supply. It reviews the evidence for a permanent switch to home and remote working enabled by emerging technologies. It assesses the business, digital and labour strategies of work organisations and the promise and challenges from a dominant trend towards a digitally enabled flexible labour model.

A critical review of 1020 plus case studies and the extant literature was carried out.

The relationship between emerging technologies and work is widely misunderstood, and there are major qualifiers to the idea of an overwhelming tsunami of technology drastically reducing headcounts globally. Distinctive human skills remain valuable, the amount of work to be done is increasing exponentially and automation is becoming more a coping than a labour replacement mechanism. Moves to a hybrid digitalised flexible labour model are promising but not if short-term, and if the challenges they represent are not managed well.

The main limitation is that we are making projections into the future, though we are drawing on a lot of different sources and evidence and past data projected into the future.

The problem is not labour displacement but large skills shortages that will slow down the speed of technology adoption. Skills development is vital, as is the taking of long-term perspectives towards the management of hybrid, flexible working based on human-machine interactions.

Organisations need to revitalise their training and development and labour management models. Governments and intermediary institutions need to manage transition states if the skills required to gain economic growth are to be available, and to ensure that large labour pools do not get bypassed from not having requisite skills.

The study offers a more subtle and complex perspective on the emerging evidence about the future of technology and work.