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This study aims to explore how libraries in the United Arab Emirates use technology to preserve and digitize cultural and historical documents. It examined how these institutions use different technology models to facilitate the dissemination of UAE’s cultural traditions, practices, historical experiences and expressions to the local and global populations interested in learning about the country.

This study relied heavily on a review of the relevant literature and case studies covering how UAE libraries use technology to preserve, document and share tangible and intangible cultural heritage. The methodology entailed gathering and synthesizing relevant information from scholarly journal articles, government and reputable institutional resources online and reports. Collectively, it led to a close analysis of the impact of technology on cultural preservation and an assessment of the specific technology models preferred for optimal outcomes in preserving and disseminating cultural heritage information of the UAE.

Multiple UAE libraries rely heavily on technology to collect, record, translate and store cultural heritage information, including releasing it to users when required. The National Archives of the United Arab Emirates, the Arabian Gulf Digital Archive, Mohammed Bin Rashid Library, the UAE National Library and Archives, New York University Abu Dhabi and Khalifa University of Science and Technology and Research libraries have leveraged different technological models and tools to make UAE’s cultural heritage information available and accessible globally. Artificial intelligence and machine learning algorithms, three-dimensional imaging and scanning, electronic archiving systems, document management systems and ICT storage systems have helped the UAE libraries to promote and disseminate the nation’s tangible and intangible cultural heritage.

By relying on scholarly and authoritative sources of information and evidence to draw conclusions, this study contributes to the existing literature by offering insights into the innovative strategies used by UAE libraries to leverage technology for cultural preservation and promotion. In underlining the value of digital approaches to safeguard tangible and intangible cultural heritage, the research highlights the instrumentalism of technology in preserving the UAE’s cultural heritage and identity.

Introduction: As the human population grows, consumer demand for digital services tailored to their specific needs also increases. To improve the financial performance of farms and meet the need for food of a growing population, farmers and agribusinesses have started incorporating distributed ledger technology into agricultural and farm management software. These developments in the agriculture sector may lead to realising sustainable development goals.

Purpose: Several researchers have done studies to explore the features and benefits of blockchain technology in the field of agriculture. There is a need to analyse the available literature to identify the use of this technology in agriculture and the scope of further research. This chapter will mainly focus on its publication trend, journal productivity and impact, prolific studies, and coherent themes.

Methodology: For a comprehensive review, bibliometric and content analysis of 71 open-access articles collected through a structured database of Mendeley is done. These articles were published during 2017–2021.

Findings: The execution of blockchain is continuously increasing in the agriculture sector, which has resulted in automation in supply chain management, land registrations, and crop insurance. The study revolves around supply chain management, digitisation of agriculture, and sustainable economic development. This study’s conclusions can help agriculturalists improve their understanding of blockchain implementation in agriculture. The study also gives directions for future research.

In prior literature, online endorsement system allowing the users to “like” or “dislike” shared information is found very useful in information filtering and trust elicitation in most social networks. This paper shows that such systems could fail in the context of investment communities due to several psychological biases.

This study develops a series of regression analyses to model the “like”/“dislike” voting process and whether or not such endorsement distinguishes between valuable information and noise. Trading simulations are also used to validate the practical implications of the findings.

The main findings of this research are twofold: (1) in the context of investment communities, online endorsement system fails to signify value-relevant information and (2) bullish information and “wisdom over the past event” information receive more “likes” and fewer “dislikes” on average, but they underperform in stock market price discovery.

This study demonstrates that biased endorsement may lead to the failure of the online endorsement system as information gatekeeper in investment communities. Two underlying mechanisms are proposed and tested. This study opens up new research opportunities to investigate the causes of biased endorsement in online environment and motivates the development of alternative information filtering systems.

This study aims to observe the coloring efficacy of graphite (G) and nano bentonite clay (BCNPs) on the adsorption of Basic Blue 5 dye from residual dye bath solution.

Some factors that affected the adsorption processes were examined and found to have significant impacts on the adsorption capacity such as the initial concentration of G and/or BCNPs (Co: 40–2,320 mg/L), adsorbent bath pH (4–9), shaking time (30–150 min.) and initial dye concentration (40–200 mg/L). The adsorption mechanism of dye by using G and/or BCNPs was studied using two different models (first-pseudo order and second-pseudo order diffusion models). The equilibrium adsorption data for the dye understudy was analyzed by using four different models (Langmuir, Freundlich, Temkin modle and Dubinin–Radushkevich) models.

It has been found that the adsorption kinetics follow rather a pseudo-first-order kinetic model with a determination coefficient (R²) of 0.99117 for G and 0.98665 for BCNPs. The results indicate that the Freundlich model provides the best correlation for G with capacities q_max = 2.33116535 mg/g and R² = 0.99588, while the Langmuir model provides the best correlation for BCNPs with R² = 0.99074. The adsorbent elaborated from BCNPs was found to be efficient and suitable for removing basic dyes rather than G from aqueous solutions due to its availability, good adsorption capability, as well as low-cost preparation.

There is no research limitation for this work. Basic Blue 5 dye graphite (G) and nano bentonite clay (BCNPs) were used.

This work has practical applications for the textile industry. It is concluded that using graphite and nano bentonite clay can be a possible alternative to adsorb residual dye from dye bath solution and can make the process greener.

Socially, it has a good impact on the ecosystem and global community because the residual dye does not contain any carcinogenic materials.

The work is original and contains value-added products for the textile industry and other confederate fields.

We conducted a systematic review to explore the potential for the application of blockchain technologies for supply chain resilience in a small-scale agri-food business context.

As part of the research methodology, scientific databases such as Web of Science, Google Scholar and Scopus were used to find relevant articles for this review.

The systematic review of articles (n = 57) found that the use of blockchain technology in the small-scale agri-food business sector can reduce the risk of food fraud by assuring the provenance of food products.

Only a few papers were directly from a small-scale agribusiness context. Key challenges that limit the implementation of blockchain and other distributed ledger technologies include concerns over the disclosure of proprietary information and trade secrets, incomplete or inaccurate information, economic and technical difficulties, low levels of trust in the technology, risk of human error and poor governance of process-related issues.

The application of blockchain technology ensures that the risks and costs associated with non-compliance, product recalls and product loss are reduced. Improved communication and information sharing can increase resilience and better support provenance claims and traceability. Better customer relationships can be built, increasing supply chain efficiency and resilience.

The increased availability and adoption of precision agriculture technologies has left researchers to grapple with how to best utilize the associated high-frequency large-volume of data. Since the wealth of information from precision equipment can easily be aggregated in real-time, this poses an interesting question of how aggregates of high-frequency data may complement, or substitute for, publicly released periodic reports from government agencies.

This study utilized advances in event study and yield projection methodologies to test whether simulated weekly harvest-time yields potentially drive futures price that are significantly different from the status quo. The study employs a two-step methodology to ascertain how corn futures price reactions and price levels would have evolved if market participants had access to weekly forecasted yields. The marginal effects of new information on futures price returns are first established by exploiting the variation between news in publicly available information and price returns. Given this relationship, the study then estimates the counterfactual evolution of corn futures price attributable to new information associated with simulated weekly forecasted yields.

The results show that the market for corn exhibits only semi-strong form efficiency, as the “news” provided by the monthly Crop Production and World Agricultural Supply and Demand Estimates reports is incorporated into prices in at most two days after the release. As expected, an increase in corn yields relative to what was publicly known elicits a futures price decrease. The counterfactual analysis suggests that if weekly harvest-time yields were available to market participants, the daily corn futures price will potentially be relatively volatile during the harvest period, but the final price at the end of the harvest season will be lower.

The study uses simulation to show the potential evolution of corn futures price if market participants had access to weekly harvest-time yields. In doing so, the study provides insights centered around the ongoing debate regarding the economic value of USDA reports in the presence of growing information availability within the private sector.

This paper empirically investigates the demand for pastured eggs in the United States and evaluates the welfare consequences of Japan's egg import tariff reductions for the US consumers.

Using household-level Nielsen Homescan panel data, a fixed-effects Heckman two-stage sample selection model is estimated.

The estimation results ascertain the importance of a set of household socioeconomic characteristics, which are found to influence both the purchase probabilities and the consumption amounts associated with pastured eggs. In addition, demand for pastured eggs is estimated to be inelastic, and pastured eggs are found to be a normal good, more specifically a luxury.

The dataset used in this study reflect purchases only for at-home consumption, lacking information on away-from-home purchases.

Building upon previous research, this study makes the following distinct contributions to the current literature. To the best of our knowledge, it constitutes the first study to empirically examine the demand for pastured eggs, using household-level panel data and an estimation model that not only allows for left-censoring but also controls for regional and time fixed effects. Second, the present study reflects a unique effort in analyzing the adverse welfare consequences of the increased egg prices in the United States brought by a reduction of Japanese import tariffs on US-supplied eggs, focusing specifically on pastured eggs.

The purpose of this paper is to analyse the current state of research on the integration of blockchain and building information modelling (BIM) in the Architecture, Engineering, Construction and Operations (AECO) industry as a means of identifying gaps between the existing paradigm and practical applications for determining future research directions and improving the industry. The study aims to provide clear guidance on areas that need attention for further research and funding and to draw academic attention to factors beyond the technical dimension.

A mixed-method systematic review is used, considering multiple literature types and using a sociotechnical perspective-based framework that covers three dimensions (technic, process and context) and three research elements (why, what and how). Data are retrieved and analysed from the Web of Science and Scopus databases for the 2017–2023 period.

While blockchain has the potential to address security, traceability and transparency and complement the system by integrating supporting applications, significant gaps still exist between these potentials and widespread industry adoption. Current limitations and further research needs are identified, including designing fully integrated prototypes, empirical research to identify operational processes, testing and analysing operational-level models or applications and developing and applying a technology acceptance model for the integration paradigm. Previous research lacks contextual settings, real-world tests or empirical investigations and is primarily conceptual.

This paper provides a comprehensive, critical systematic review of the integration of blockchain with BIM in the construction industry, using a sociotechnical perspective-based framework which can be applied in future reviews. The study provides insight into the current state and future opportunities for policymakers and practitioners in the AECO industry to prepare for the transition in this disruptive paradigm. It also provides a phased plan along with a clear direction for the transition to more advanced applications.

Building on the premise that the CEO position is complex and challenging, and drawing on research on upper echelons, executive job demands and emotions, this study explores how chief executive officers' (CEOs’) perceptions of job-associated difficulty can influence negative emotional displays and subsequently hamper firm innovation. Additionally, the authors explore how CEOs with higher levels of emotional intelligence might mitigate the influence of job demands on negative emotional displays.

The authors conducted a two-stage survey with a sample of CEOs and top management team members from 120 small- and medium-sized firms operating in multiple industries in Colombia.

The authors found that CEOs' perceptions of job demands are positively associated with CEOs' displays of negative emotions, which in turn are negatively associated with firm innovation. The authors also find that two dimensions of emotional intelligence (self-appraisal and regulation) weaken the influence of CEO perceptions of job demands on CEO negative emotional displays.

The authors advance a novel perspective on the challenges of leading organizations by explaining the emotional implications of the CEO position, underscoring their repercussions for important organizational outcomes such as innovation and suggesting potential ways CEOs can handle the emotional consequences of their position.