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This study investigated the moderating effect of organizational knowledge management performance on the sharing and use of information encountered by serendipity within the organization.

The authors surveyed 274 medical librarians from the top 100 medical schools.

Individual information encountering predicted information encountering at work, which, in turn, predicted organizational sharing of encountered information. When the propensity to encounter information was high, then organizational knowledge management performance moderated the effect between organizational encountering and organizational sharing of information. Encountered information at work was only present when high organizational knowledge management performance was in place.

This finding helps information behavior researchers discover the transfer of behaviors from everyday life to organizational environments.

It shows the need for greater support for information encounterers at work and the role of knowledge management, which may enhance their contribution to the organizational objectives.

Information encountering involves finding information by chance. Studies on information encountering have not focused on work settings and if the individual propensity to encounter information translates to organizational settings. Also, the relationship between information encountering and organizational knowledge management has not been studied so far.

This study aims to improve the complexity of chaotic systems and the security accuracy of information encrypted transmission. Applying five-dimensional memristive Hopfield neural network (5D-HNN) to secure communication will greatly improve the confidentiality of signal transmission and greatly enhance the anticracking ability of the system.

Chaos masking: Chaos masking is the process of superimposing a message signal directly into a chaotic signal and masking the signal using the randomness of the chaotic output. Synchronous coupling: The coupled synchronization method first replicates the drive system to get the response system, and then adds the appropriate coupling term between the drive The synchronization error and the coupling term of the system will eventually converge to zero with time. The synchronization error and coupling term of the system will eventually converge to zero over time.

A 5D memristive neural network is obtained based on the original four-dimensional memristive neural network through the feedback control method. The system has five equations and contains infinite balance points. Compared with other systems, the 5D-HNN has rich dynamic behaviors, and the most unique feature is that it has multistable characteristics. First, its dissipation property, equilibrium point stability, bifurcation graph and Lyapunov exponent spectrum are analyzed to verify its chaotic state, and the system characteristics are more complex. Different dynamic characteristics can be obtained by adjusting the parameter k.

A new 5D memristive HNN is proposed and used in the secure communication

This chapter explores how state–business relations (SBR) in the Arab world influence public policy on industrial clusters and the resulting economic benefits from these clusters on innovation and productivity. The main SBR actors are identified as the state, big capitalists (or tycoons), and small and medium business managers and owners (entrepreneurs). The framework used here focuses on interactors' power relations. Such power relations are reflected in the ability/inability of the state to enforce its will with less consultation with and/or favorite treatment to nonstate actors. It is also reflected in the ability/inability of nonstate actors to act individually or organize in order to defend their interests and influence government policy formulation and implementation. Such power relations are reflected in the ability of nonstate actors to organize – especially entrepreneurs – and the level of favoritism provided by state officials to tycoons. The power dynamics in SBR lead to different SBR modes and different economic outcomes, one of which is the development of industrial clusters and how efficient they are in fostering innovation and productivity in Arab countries. This chapter suggests that the development of industrial clusters in the Arab world necessitates institutional reform, addressing the power relations governing SBR in the region. A more open political system allowing the independence and growth of broad-based business associations and curbing favoritism is necessary for realizing the benefits from implementing recommended policies, leading to cluster development and reaping the economic benefits from such development. Using statistical and regression analysis, empirical evidence supporting these arguments is provided.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

Globalization, along with its technological developments, has brought important changes and developments in all sectors and led to innovation and modernization. In the tourism industry, the concept of smart destination, derived from the concept of smart city, has become widespread to meet the changing needs of tourists. In this context, smart technologies have started to be used in destinations, but more than technology in destinations is needed in terms of sustainability. To ensure sustainability in tourism, these smart technologies must also be eco-friendly. Smart destinations and eco-friendly practices are important for the sustainable development of the tourism industry. The use of technology in destinations can increase sustainability and efficiency, while using eco-friendly practices can protect and preserve the natural environment. In this study, first of all, smart destinations and the characteristics of smart destinations are discussed. Then, smart tourism and related eco-friendly practices are argued. Following this, information about the future of smart destinations is given, and assumptions are mentioned. Afterward, problems and solutions are discussed. Finally, the study has been completed with the conclusion part. The findings of the study revealed that the concept of green especially comes to the fore in smart destinations, that there are studies to prevent all kinds of pollution (air, noise, etc.), and applications such as smart parking systems, smart lighting systems, augmented reality (AR), and virtual reality (VR) are given importance.

Economic policy uncertainty has increased around the world since the financial crisis of 2007–2008. While scholars have devoted a lot of time and energy to investigating the impact of economic policy uncertainty (EPU) on firm innovation, they have not reached consistent research conclusions. This study aimed to clarify the above research differences by exploring the impact of EPU on firms' relative exploitative innovation emphasis, so as to provide a more comprehensive and granular understanding of the relationship between EPU and firm innovation.

This study obtained 17,165 firm-year data points from 3,107 listed companies in China. It analyzed the above data with a fixed effects model. In addition, this study used an instrumental variables method to solve potential endogeneity problems.

Based on real options theory and contingency theory, the authors proposed and found that EPU has a significant positive effect on relative exploitative innovation emphasis. In addition, the authors proposed and found that this effect is more pronounced in industries with high technological uncertainty, low competitive intensity, and low state monopolization.

This study is the first to explore why firms prefer exploitative innovation over exploratory innovation from the perspective of EPU. In doing so, this study expands and enriches the EPU literature and the innovation literature. Furthermore, by introducing the moderating role of industry environment, this study deepens the authors' understanding of how complex interactions between industry and institutional environments work together to shape firm strategic choices, and especially firm innovation. Finally, the conclusions of this study have important practical implications for shareholders to take measures to balance exploitative innovation and exploratory innovation to achieve better development.

The purpose of this study is to examine the impact of country-level governance on sustainability performance, taking into account the effect of sustainable development goals (SDGs) and board characteristics.

This study uses panel data analysis using fixed effect models to investigate the influence of country-level governance on sustainability performance while considering the effect of SDGs and board characteristics. The sample comprises 8,273 firms across 41 countries during the period spanning from 2016 to 2021. The sample is divided into two categories based on the score of SDGs.

The findings of this study show that countries with high SDGs score have better overall country-level governance and board attributes which have a statistically significant positive impact on sustainability performance. However, for those countries with low SDGs, political stability shows a statistically insignificant and negative impact on sustainability performance, while government effectiveness indicates a statistically insignificant positive impact on sustainability performance.

This study contributes to the literature by providing empirical evidence on the relationship between country-level governance, SDGs, board characteristics and sustainability performance. The study also highlights the importance of considering the effect of SDGs on the relationship between country-level governance and sustainability performance. The findings of this study could be useful for policymakers and firms in improving their sustainability performance and contributing to sustainable development.

This study aimed to explore the spatial accessibility dynamics of urban parks and their driving forces from 1901 to 2010 in terms of the dynamic relationships between spatial morphology and road networks, taking Nanjing City as an example.

This study mapped and examined the spatiotemporal distribution of urban parks and road networks in four time points at Nanjing: the 1910s, 1930s, 1960s and 2010s, using the analysis methodology of spatial design network analysis, kernel density estimation and buffer analysis. Two approaches of spatial overlaying and data analysis were adopted to investigate the accessibility dynamics. The spatial overlaying compared the parks' layout and the road networks' core, subcore and noncore accessible areas; the data analysis clarified the average data on the city-wide and local scales of the road networks within the park buffer zone.

The analysis of the changing relationships between urban parks and the spatial morphology of road networks showed that the accessibility of urban parks has generally improved. This was influenced by six main factors: planning implementation, political policies, natural resources, historical heritage and cultural and economic levels.

The results provide a reference for achieving spatial equity, improving urban park accessibility and supporting sustainable urban park planning.

An increasing number of studies have explored the spatial accessibility of urban parks through the relationships between their spatial distribution and road networks. However, few studies have investigated the dynamic changes in accessibility over time. Discussing parks' accessibility over relatively long-time scales has practical, innovative and theoretical values; because it can reveal correlational laws and internal influences not apparent in short term and provide reference and implications for parks' spatial equity.

This study investigates how perceived political corruption, a generally overlooked corruption type, relates to firms' new product development (NPD) through perceived regulatory obstacles. It also examines firms' perceptions of business association support in this relationship, considering these associations' potential support for NPD.

This study conducted an empirical analysis of 1,663 firms in Turkey, a country noted for a history of legislative corruption, and in which there are strong business associations. Drawing the data from the World Bank's 2019 Enterprise Surveys Dataset, this study tested the hypotheses via the two-stage factor score regression method.

This study finds that perceived political corruption significantly relates to NPD negatively through perceived regulatory obstacles. It also finds that the perceived support of business associations to NPD is significantly greater when firms perceive regulatory obstacles but only slight political corruption.

As far as political corruption is concerned, this study reveals that corruption can also be the cause of regulatory obstacles, expanding the common view of corruption as a means of overcoming regulatory obstacles to NPD. In addition, it introduces the role of business associations in this relationship by revealing their support to NPD for different levels of perceived political corruption and regulatory obstacles.