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The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is general market-wide sentiments, while the second is biased approaches toward specific assets.

To achieve the goal, the authors conducted a multi-step analysis of stock returns and constructed complex sentiment indices that reflect the optimism or pessimism of stock market participants. The authors used panel regression with fixed effects and a sample of the US stock market to improve the explanatory power of the three-factor models.

The analysis showed that both market-level and stock-level sentiments have significant contributions, although they are not equal. The impact of stock-level sentiments is more profound than market-level sentiments, suggesting that neglecting the stock-level sentiment proxies in asset valuation models may lead to severe deficiencies.

In contrast to previous studies, the authors propose that investor sentiments should be measured using a multi-level factor approach rather than a single-factor approach. The authors identified two distinct levels of investor sentiment: general market-wide sentiments and individual stock-specific sentiments.

The authors compare sentiment level with sentiment shock from different angles to determine which measure better captures the relationship between sentiment and stock returns.

This paper examines the relationship between investor sentiment and contemporaneous stock returns. It also proposes a model of systems science to explain the empirical findings.

The authors find that sentiment shock has a higher explanatory power on stock returns than sentiment itself, and sentiment shock beta exhibits a much higher statistical significance than sentiment beta. Compared with sentiment level, sentiment shock has a more robust linkage to the market factors and the sentiment shock is more responsive to stock returns.

This is the first study to compare sentiment level and sentiment shock. It concludes that sentiment shock is a better indicator of the relationship between investor sentiment and contemporary stock returns.

Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

Purpose of This Chapter: This research aims to study the need for more age of qualified talent. The evolving corporate needs, education, and curriculum require urgent reform. Current university methods do not align with corporate demands due to outdated content and ineffective pedagogy.

Design / Methodology / Approach: Drawing on established research, this study delves into 7 prominent training strategies across 14 sectors. A survey of 53 HR professionals and managers forms the basis for employing the non-linear best–worst method (BWM) and the Fuzzy BWM to discern the most effective training and development (T&D) modules. This comprehensive methodology ensures a nuanced analysis of T&D practices and insights for businesses seeking to align with Industry 5.0 demands.

Findings: On-the-job training emerges as the most impactful method, followed by case studies, interactive group learning, and more. These methods enhance employee skills in Industry 5.0.

Research Limitations: Limited by a small sample, future research should expand participant diversity for robustness.

Practical Implications: The study holds significance for bridging the skill gap between academic institutions and Industry 5.0. Aligning strategies with industry needs reduces skill disparities, fuels growth, and addresses employability. The study’s impact extends to society, lowering unemployment and shaping a resilient, adaptable workforce for Industry 5.0.

Originality: This innovative research examines decision-making for implementing T&D strategies in the emergence of Industry 5.0, aligning with a human-centric approach to business transformation.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

The inflammatory potential of diet may play a role in the regulation of low-grade chronic inflammation derived from obesity. This study aims to investigate the relationship between the dietary inflammatory index (DII) and anthropometric indicators of adiposity among Turkish adults.

The study sample consisted of 833 young adults (mean age = 23 ± 5.2 years). The inflammatory potential of the diet was evaluated with a DII. Data on dietary intake were collected by a single 24-h dietary recall, and DII was estimated from 25 dietary components. Also, the Mediterranean diet (Med-Diet) adherence screener was applied using the 14-item assessment tool.

The proinflammatory diet was statistically associated with young (p < 0.001), singles (p < 0.001), high school degree (p = 0.011), students (p < 0.001), not working or unemployed (p < 0.001), eating outside (p = 0.016) and lower adherence to a Med-Diet (p = 0.027). There was a statistically significant positive relationship between the DII score and body weight (BW), waist circumference and waist-to-height ratio (WHtR) (r = 0.107; p = 0.002, r = 0.092; p = 0.008, r = 0.115; p = 0.001, respectively). Besides, there was a statistically significant negative relationship between MED score and BW, WHtR and neck circumference (r = −0.101; p = 0.004, r = −0.084; p = 0.016, r = −0.175; p = 0.000, respectively).

To the best of the authors’ knowledge, this was the first Turkish study to assess the association between the anthropometric indicators of obesity and DII or adherence to Med-Diet in young adults. Lower DII scores and higher adherence to Med-Diet are related to the better status of anthropometric indicators of adiposity.

This study aims to systematically review the health risk assessment of the concentration of heavy metals in Pistacia species globally.

The authors systematically searched PubMed, Science Direct, Scopus and Google Scholar to identify all articles published between 1 January 2002 and 20 August 2022. A total of 33 studies met the authors’ inclusion criteria, and their data were extracted. Additionally, the potential risk to human health was assessed by calculating the target hazard quotient and hazard index for both child and adult consumers.

The estimated daily intake for heavy metals in the included studies ranged from 9.72 × 10^–9 to 7.35 (mg/day) in the following order: zinc (Zn) > mercury (Hg) > iron (Fe) > lead (Pb) > copper (Cu) > aluminum (Al) > nickel (Ni) > chromium (Cr) > manganese (Mn) > cadmium (Cd) > arsenic (As) > selenium (Se) > cobalt (Co). Among the studies that investigated heavy metals in Pistacia species around the world, the non-carcinogenic risk for all species of Pistacia was determined to be less than 1, except for Pb and Hg in Pistacia lentiscus.

The soil near the industrial area contained excessive amounts of heavy metals, which led to the transfer of heavy metals to plants. Owing to the insufficiency of the number of studies that examined heavy metals in Pistacia species, further monitoring and investigations were recommended.

Acknowledging the significance of perceived organizational support (POS) for employees’ performance, this study aims to examine the underlying mechanism of task performance in a COVID-19 pandemic-induced blended working (TPBW) environment and the role of perceived usefulness of digitalization (PUDBW) in the process.

Survey data collected from 204 managers of Indian public sector undertakings pursuing blended working for the first time were analyzed using structural equation modelling. A qualitative study on 31 such managers was also performed.

Although employees perceived an improvement in POS, PUDBW and TPBW (during the COVID pandemic) in comparison to the pre-COVID time when traditional work design was operational, yet the improvement in task performance was not directly influenced by POS. POS had a positive effect on PUDBW, which in turn positively affected TPBW. PUD acted as a mediator. A negative moderation effect of POS on the relationship between PUDBW and TPBW was found.

Findings of the study may help organizations and policymakers to focus on key enablers, such as organizational support and relevant digital initiatives, for ensuring better task performance by their employees during a blended working environment, even in difficult times as the COVID-19 pandemic.

This study, for the first time, examined the proposed relationships in a new work setting of blended working and explained the underlying mediation and moderation mechanisms in their relationships.

Starting from the status quo, the paper outlines perspectives and challenges for the connection and interlinking of digitised and digital archival data. The following topics are addressed: Where are fields of action and what are the means of archives? Which functional and technical requirements are to be considered, and what is the role of portal infrastructures linking together various different institutions?

Considering needs of users and general framework conditions, the paper examines new approaches emerging in Germany. It outlines recent projects and considerations aiming to improve services and visibility of archives within the national data infrastructure in Germany.

Cross-connections are no new phenomenon, but change their appearance significantly in a digital context. In this respect, both smaller and bigger archives profit from participation in larger digital networks. Furthermore, archives need to keep in mind to reflect the quality of their digital (meta)data regularly and to offer or join systems that functionally and technically support cross-connection and interlinking of data.

The paper endeavours to show the importance of digital cross-connections and the role of portal infrastructures for visibility, online-distribution and use of digital archival metadata and data.

Living walls (LWs), vegetated walls with an integrated growth layer behind, are being increasingly incorporated in buildings. Examining plant characteristics’ comparative impacts on LWs’ energy efficiency-related thermal behavior was aimed, considering that studies on their relative effects are limited. LWs of varying leaf albedo, leaf transmittance and leaf area index (LAI) were studied for Antalya, Turkey for typical days of four seasons.

Dynamic simulations run by Envi-met were used to assess the plant characteristics’ influence on seasonal and orientation-based heat fluxes. After model calibration, a sensitivity analysis was conducted through 112 simulations. The minimum, mean and maximum values were investigated for each plant characteristic. Energy need (regardless of orientation), temperature and heat flux results were compared among different scenarios, including a building without LW, to evaluate energy efficiency and variables’ impacts.

LWs reduced annual energy consumption in Antalya, despite increasing energy needs in winter. South and west facades were particularly advantageous for energy efficiency. The impacts of leaf albedo and transmittance were more significant (44–46%) than LAI (10%) in determining LWs’ effectiveness. The changes in plant characteristics changed the energy needs up to ca 1%.

This study can potentially contribute to generating guiding principles for architects considering LW use in their designs in hot-humid climates.

The plant characteristics’ relative impacts on energy efficiency, which cannot be easily determined by experimental studies, were examined using parametric simulation results regarding three plant characteristics.