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In this paper, the seismic behavior of the gusset plate moment connection (GPMC) exposed to the post-earthquake fire (PEF) is investigated.

For this purpose, for the sake of verification, first, a numerical model is built using ABAQUS software and then exposed to earthquakes and high temperatures. Afterward, the effects of a series of parameters, such as gusset plate thickness, gap width, steel grade, vertical load value and presence of the stiffeners, are evaluated on the behavior of the connection in the PEF conditions.

Based on the results obtained from the parametric study, all parameters effectively played a role against the seismic loads, although, when exposed to fire, it was found that the vertical load value and presence of the stiffener revealed a great contribution and the other parameters could not significantly affect the connection performance. Finally, to develop the modeling and further study the performance of the connection, the 4 and 8-story frames are subjected to 11 accelerograms and 3 different fire scenarios. The findings demonstrate that high temperatures impose rotations on the structure, such that the story drifts were changed compared to the post-earthquake drift values.

The obtained results can be used by engineers to design the GPMC for the combined action of earthquake and fire.

This paper researches a bidirectional volatility transmission effect between stocks and exchange rate markets in the six East European and Eurasian countries.

Research process involves creation of transitory and permanent volatilities via optimal component generalized autoregressive heteroscedasticity (CGARCH) model, while these volatilities are subsequently embedded in Markov switching model.

This study’s results indicate that bidirectional volatility transmission exists between the markets in the selected countries, whereas the effect from exchange rate to stocks is stronger than the other way around in both short-term and long-term. In particular, the authors find that long-term spillover effect from exchange rate to stocks is stronger than the short-term counterpart in all countries, which could suggest that flow-oriented model better explains the nexus between the markets than portfolio-balance approach. On the other hand, short-term volatility transfer from stock to exchange rate is stronger than its long-term equivalent.

This suggests that portfolio-balance theory also has a role in explaining the transmission effect from stock to exchange rate market, but a decisive fact is from which direction spillover effect is observed.

This paper is the first one that analyses the volatility nexus between stocks and exchange rate in short and long term in the four East European and two Eurasian countries.

Using data from a continuous and ongoing cross-sectional web survey on hospitalisation service experiences in two Italian regions, the authors used multilevel and multivariate logistic regression models to identify factors related to users' demographics, emotional and informative support, technical and physical aspects of the provision, influencing satisfaction and willingness-to-recommend, before and during a crisis.

The value-in-use, defined in terms of a positive or negative value given by the experience with services, can be evaluated by users and influenced by the context of provision. The authors tested whether and how the value-in-use of services changed in a context of crisis. This study is applied to the healthcare sector during the coronavirus disease 2019 (COVID-19) epidemic, by evaluating the impact of the pandemic on hospitalisation experience.

Overall, analyses of 8,712 questionnaires found a greater value after the pandemic spread. In a time of crisis, technical and informative aspects of care were found to be most valued by patients that may recognise the extraordinary professionalism of workers during the crisis.

This study empirically suggests that context can affect the evaluation of value-in-use by patients during unprecedented circumstances, producing additional value-in-context.

These findings imply that during critical periods where there is less scope for expressions of gratitude and appreciation towards front-line workers, user-reported data can be used for motivating professionals and increase resilience. These results reiterate the need to continue collecting and reporting the service users' voices, including as activity within plans for managing challenging situations.

The level of healthcare system distress, due to the COVID-19 epidemic, positively affects patients' propensity to recommend, which the authors suggest is driven by healthcare services' feelings of reverse compassion. These findings imply that during critical periods where there is less scope for expressions of gratitude and appreciation towards front-line workers, user-reported data can be used for motivating professionals and increase resilience, which can have positive social implications. These results reiterate the need to continue collecting and reporting the service users' voices, including as activity within plans for managing challenging situations.

Research based on the intersection of theoretical and empirical research regarding value-in-use, value-in-context and service quality measured through user experience is scarce, in particular in the healthcare sector. The authors' findings set the direction for future research on the influence of context on value creation and value creation's perception by users, on the concept of reverse compassion and on reverse compassion's impact on organisational well-being, particularly in times of crisis.

The purpose of this study is to define and investigate the governance requirements of supply chain finance (SCF).

A qualitative analysis of 849 news articles published in UK newspapers (2000–2022) using the Gioia method.

SCF governance relies on developing capacities for reflexive scrutiny at two stages: (1) prior to entering into an SCF relationship and (2) during its operation. Based on the notion of SCF as a complex adaptive system, we theorise SCF governance requirements as a dual-layered semipermeable boundary. The semipermeability of the two layers allows for a dynamic exchange between the SCF system and its environment. The first layer is the capacity to selectively enable or control the entry and access of certain actors and practices into the SCF system. The second layer is a capacity for ongoing scrutiny of the SCF operation and its development. Further, we identify five aspects of governance to be enabled, i.e. enhancing adaptability, building confidence, improving efficiency, advancing technology and promoting transparency; and four aspects to be controlled, i.e. preventing abuse of power, curbing fraud risk, constraining operational risk and restricting risky extensions to SCF practices.

Our dynamic framework can guide supply chain (SC) members in making decisions about whether to participate, or continue to operate, in an SCF relationship. Moreover, the findings have implications for policymakers and authorities who oversee entry/access and the involvement of SCF providers, particularly, fintech firms.

The study contributes to both the SC and governance literature by providing a systematic analysis of what SCF governance has to accomplish. Our novel contribution lies in its analysis of SCF governance based on a complex adaptive system approach, which expands the existing literature where SCF is described in rather static terms. More specifically, it suggests a need for a dynamic duality of SCF governance through the semipermeable boundary that selectively enables and controls certain SCF actors and practices.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

Our paper studies a central issue with a long history in economics: the relationship between population and economic growth. We analyze the joint dynamics of economic and demographic growth in 111 countries during the period 1960–2019.

Using the concept of economic regime, the paper introduces the notion of distance between the dynamical paths of different countries. Then, a minimal spanning tree (MST) and a hierarchical tree (HT) are constructed to detect groups of countries sharing similar dynamic performance.

The methodology confirms the existence of three country clubs, each of which exhibits a different dynamic behavior pattern. The analysis also shows that the clusters clearly differ with respect to the evolution of other fundamental variables not previously considered [gross domestic product (GDP) per capita, human capital and life expectancy, among others].

Our results indirectly suggest the existence of dynamic interdependence in the trajectories of economic growth and population change between countries. It also provides evidence against single-model approaches to explain the interdependence between demographic change and economic growth.

We introduce a methodology that allows for a model-free topological and hierarchical description of the interplay between economic growth and population.

While scholars have researched the impact of specific total quality management (TQM) aspects on innovation performance (INP), empirical evidence on how the former, as a composite construct, influences the latter is rare. To add, empirical evidence on the mechanism through which TQM passes to affect innovative behaviour (INB) and, then, INP is limited. Essentially, scholars have requested that future research look at the boundary conditions that support the adoption of TQM activities in businesses. Although the banking sector has experienced a number of transformations, there is still a need to raise the standard of service provided to bank customers. This research sheds more light on this subject.

This research tests the hypotheses in Ahinful et al.’s (2023) conceptual model using responses from 260 top- and middle-level bank managers by applying Smart PLS. Organisational support and team member exchange were used as potential control variables for the mediator, while slack resources and bank size were applied to the target endogenous latent construct. Mediation and moderation effects were estimated using the variance accounted for (VAF) and product indicator approaches, respectively. Sig. level was set at 5%.

This study found that TQM and INP had a positive and significant connection (ß = 0.303, p = 0.000), and INB partially mediated this connection (VAF = 40.92%). However, government regulation (GOV; ß = 0.055, p = 0.365), market dynamism (MKD; ß = 0.063, p = 0.434), competitive intensity (CMP; ß = 0.069, p = 0.297) and technological turbulence (TUR; ß = 0.011, p = 0.865) all failed to moderate the TQM–INB connection, although the expected positive directions of these moderation relationships were established.

This research provides empirical evidence on the TQM–INP connection, how this connection may be mediated and how the TQM–INB connection may be activated. It also sheds light on novel ways in which service quality in the banking sector may be improved. Upcoming research may explore other control variables in their research. Since the moderating relationships were unsupported, this avenue is open for further research, particularly in other banking settings across the globe.

Practical lessons for bank consultants, regulators, customers, employees and managers are deliberated.

This research is novel. It is the first to test the hypotheses in Ahinful et al.’s (2023) conceptual model. This study advances the theoretical frameworks and existing knowledge within the TQM, innovation and performance management fields.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

These implementations not only generate excessive voltage levels to enhance the quality of power but also include a detailed investigating of the various modulation methods and control schemes for multilevel inverter (MLI) topologies. Reduced harmonic modulation technology is used to produce 11-level output voltage with the production of renewable energy applications. The simulation is done in the MATLAB/Simulink for 11-level symmetric MLI and is correlated with the conventional inverter design.

This paper is focused on investigating the different types of asymmetric, symmetric and hybrid topologies and control methods used for the modular multilevel inverter (MMI) operation. Classical MLI configurations are affected by performance issues such as poor power quality, uneconomic structure and low efficiency.

The variations in both carrier and reference signals and their performance are analyzed for the proposed inverter topologies. The simulation result compares unipolar and bipolar pulse-width modulation (PWM) techniques with total harmonic distortion (THD) results. The solar-fed 11-level MMI is controlled using various modulation strategies, which are connected to marine emergency lighting loads. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by using SPARTAN 3A field programmable gate array (FPGA) board and the least harmonics are obtained by improving the power quality.

The simulation result compares unipolar and bipolar PWM techniques with THD results. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by a SPARTAN 3A field programmable gate array (FPGA) board, and the power quality is improved to achieve the lowest harmonics possible.