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This paper aims to investigate the cooperative governance mechanisms for personal information security, which can help enrich digital governance research and provide a reference for the formulation of protection policies for personal information security.

This paper constructs an evolutionary game model consisting of regulators, digital enterprises and consumers, which is combined with the simulation method to examine the influence of different factors on personal information protection and governance.

The results reveal seven stable equilibrium strategies for personal information security within the cooperative governance game system. The non-compliant processing of personal information by digital enterprises can damage the rights and interests of consumers. However, the combination of regulatory measures implemented by supervisory authorities and the rights protection measures enacted by consumers can effectively promote the self-regulation of digital enterprises. The reputation mechanism exerts a restricting effect on the opportunistic behaviour of the participants.

The authors focus on the regulation of digital enterprises and do not consider the involvement of malicious actors such as hackers, and the authors will continue to focus on the game when assessing the governance of malicious actors in subsequent research.

This study's results enhance digital governance research and offer a reference for developing policies that protect personal information security.

This paper builds an analytical framework for cooperative governance for personal information security, which helps to understand the decision-making behaviour and motivation of different subjects and to better address issues in the governance for personal information security.

This study aimed to examine the efficient market hypothesis (EMH) for the stock markets of 12 member countries of the Organization of Islamic Cooperation (OIC), such as Egypt, Indonesia, Jordan, Kuwait, Malaysia, Morocco, Pakistan, Saudi Arabia, Tunisia, Turkey and the United Arab Emirates (UAE), during the global financial crisis (GFC) and the COVID-19 (CV-19) epidemic. The objective was to classify the effects on individual indices.

The study employed the multifractal detrended fluctuation analysis (MF-DFA) on daily returns. After calculation and analysis, the data were then divided into two significant events: the GFC and the CV-19 pandemic. Additionally, the market deficiency measure (MDM) was utilized to assess and rank market efficiency.

The findings indicate that the average returns series exhibited persistent and non-persistent patterns during the GFC and the CV-19 pandemic, respectively. The study employed MF-DFA to analyze the sequence of normal returns. The results suggest that the average returns series displayed persistent and non-persistent patterns during the GFC and the CV-19 pandemic, respectively. Furthermore, all markets demonstrated efficiency during the two crisis periods, with Turkey and Tunisia exhibiting the highest and deepest levels of efficiency, respectively. The multifractal properties were influenced by long-range correlations and fat-tailed distributions, with the latter being the primary contributor. Moreover, the impact of the fat-tailed distribution on multifractality was found to be more pronounced for indices with lower market efficiency. In conclusion, this study categorizes indices with low market efficiency during both crisis periods, which subsequently affect the distribution of assets among shareholders in the stock markets of OIC member countries.

Multifractal patterns, especially the long memory property observed in stock markets, can assist investors in formulating profitable investment strategies. Additionally, this study will contribute to a better understanding of market trends during similar events should they occur in the future.

This research marks the initial effort to assess the impact of the GFC and the CV19 pandemic on the efficiency of stock markets in OIC countries. This undertaking is of paramount importance due to the potential destabilizing and harmful effects of these events on global financial markets and societal well-being. Furthermore, to the best of the authors’ knowledge, this study represents the first investigation utilizing the MFDFA method to analyze the primary stock markets of OIC countries, encompassing both the GFC and CV19 crises.

This study aims to uncover the main predictors of financial distress in the Gulf Cooperation Council (GCC) countries using a wide range of global factors and asset classes.

This study uses novel approaches that take into account extreme events as well as the nonlinear behavior of time series over various time intervals (i.e. short, medium and long term) and during boom and bust episodes. This study primarily uses the conditional value at risk (CoVaR), the quantile multivariate causality test and the partial wavelet coherence method. The data collection period ranges from March 2014 to September 2022.

US T-bills and gold are the primary factors that can increase financial stability in the GCC region, according to VaRs and CoVaRs. More proof of the predictive value of the oil, gold and wheat markets, as well as geopolitical tensions, uncertainty over US policy and volatility in the oil and US equities markets, is provided by the multivariate causality test. When low extreme quantiles or cross extreme quantiles are taken into account, these results are substantial and sturdy. Lastly, after adjusting for the effect of crude oil prices, this study’s wavelet coherence results indicate diminished long-run connections between the GCC stock market and the chosen global determinants.

Despite the implications of the author’s research for decision makers, there are some limitations mainly related to the selection of Morgan Stanley Capital International (MSCI) GCC ex-Saudi Arabia. Considering the economic importance of the Kingdom of Saudi Arabia (KSA) in the region, the author believes that it would be better to include this country in the data to obtain more robust results. In addition, there is evidence in the literature of the existence of heterogeneous responses to global shocks; some markets are more vulnerable than others. This is another limitation of this study, as this study considers the GCC as a bloc rather than each country individually. These limitations could open up further research opportunities.

These findings are important for investors seeking to manage their portfolios under extreme market conditions. They are also important for government policies aimed at mitigating the impact of external shocks.

This study aims to explore a new restaurant category’s development from birth to maturity, thereby explaining the rationale for category innovation strategies.

The authors conducted a qualitative case study analysis of the New Chinese-style Fusion Restaurant category’s development from birth to maturity. Thematic analysis was conducted on data collected from semi-structured interviews and textual information.

A new restaurant category’s maturation is determined by the formation of society’s shared knowledge about the category’s crucial attributes, which is an outcome of market participants’ category-related social practices. The authors develop a novel, four-stage framework for the socialized construction of this shared knowledge: a knowledge creation (KC), knowledge diffusion (KD), knowledge integration (KI) and knowledge structuralization (KS). This knowledge evolution along this KC–KD–KI–KS sequence can holistically describe the category maturation process. This framework can help understand the rationale for a restaurant category’s maturation by analyzing the interrelationships among market participants’ social practices, knowledge-related activities and market development.

This study explains how market participants’ knowledge-related activities facilitate a new restaurant category’s maturation. This can help restaurant managers cope with increasingly homogeneous competition by applying a category-innovation strategy.

This study extends product categorization research on restaurants by articulating a product category’s maturation process from a knowledge perspective.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

The purpose of this paper is to study the effect of temperature on Zn–Ni alloys in ChCl–Urea.

Based on cyclic voltammetry experiments, the deposition behavior and kinetics of the Zn–Ni alloy are studied. The nucleation process of the Zn–Ni alloy is studied in detail via chronoamperometry experiments. The effects of the deposition temperature on the microstructure, Ni content and phase composition of Zn–Ni alloy coatings are investigated via scanning electron microscopy and X-ray diffraction (XRD) combined with classical thermodynamics.

The results show that with increasing temperature, the reduction peak shifts toward a more positive electric potential, which is beneficial for the co-electric deposition process, and the diffusion coefficient is estimated. With increasing temperature, the nucleation process of the Zn–Ni alloy becomes a three-dimensional instantaneous nucleation, the typical kinetic parameters are determined using the standard 3D growth proliferation control model and the Gibbs free energy is estimated. The Zn–Ni alloy coatings are prepared via normal co-deposition. With increasing temperature, the degree of crystallinity increases, the coating gradually becomes uniform and compact and the XRD peak intensity increases.

The nucleation process of the Zn–Ni alloy at different temperatures is analyzed. The diffusion coefficient D and Gibbs free energy are calculated. The contribution of the three processes at different temperatures is analyzed. The effect of temperature on the morphology of the Zn–Ni alloy coatings is studied.

To understand the mechanisms underlying social media discontinuance behavior, this study explores factors affecting social media discontinuance behavior from the perspective of social cognitive theory (SCT).

Based on SCT, this study puts forward a theoretical model incorporating habit, excessive use and negative emotions to predict social media discontinuance behavior. The proposed research model was empirically tested with 465 responses collected from WeChat users in China via an online survey. WeChat is one of the most popular social media in China. However, WeChat also faces the challenges of reduced or terminated usage among its users. Partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data.

The research results in this study show that habit exerts a negative effect on social media discontinuance behavior, while exhaustion and regret have positive influences. In addition, habit positively affects excessive use, which further leads to negative emotions of social media exhaustion and regret. Moreover, gender moderates the relationship between habit and social media discontinuance behavior.

This study adds to the literature of information system (IS) use lifecycle by investigating user behavioral changes regarding a transition from habituated to excessive use and further to discontinuance behavior. This study also helps elucidate the complex role of habit by explaining social media discontinuance from the social cognitive view. Furthermore, this study advances the current understanding of gender difference in social media discontinuance in the Chinese context. The study also offers insights to practitioners on how to prevent individuals from discontinuing their use of social media.

The purpose of this study is to prepare a robust superhydrophobic coating on concrete substrate with remarkable chemical and mechanical durability through “all-covalent” strategy.

Amino-modified silica nano/micro-particles were prepared through two synthetic steps. “All-covalent” strategy was introduced to prepare a robust superhydrophobic coating on concrete surface via a “all-in-one” dispersion and a simple spraying method. The successful construction of the products was confirmed by Fourier transform infrared spectroscopy, water contact angles (WCA), X-ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM). The concrete protective properties were verified by solution immersion test, pull-off test and rapid chloride migration coefficient test. The mechanical durability was tested by falling sand impact.

Hierarchical structures combined with the low-surface-energy segments lead to typically superhydrophobic coating with a WCA of 156° and a sliding angle of 1.3°. The superhydrophobic coating prepared through “all-covalent” strategy not only improves chemical and mechanical durability but also achieves higher corrosion and wear resistance than the comparison sample prepared by physically blending strategy. More importantly, the robust superhydrophobic coating showed excellent adhesion and protective performance of concrete engineerings.

This new “all-covalent” superhydrophobic coating could be applied as a concrete protective layer with properties of self-cleaning, anti-graffiti, etc.

Introduction of both silica nanoparticles and silica microparticles to prepare a robust superhydrophobic coating on concrete surface through “all-covalent” strategy has not been systematically studied previously.

The purpose of this paper is to add expanded perlite (EP) immobilized microorganisms that replace part of the standard sand in mortar to improve the self-healing ability of mortar cracks and reduce the water absorption of mortar after healing.

Bacillus pseudofirmus spores were immobilized with EP particles as self-healing agents. The effects of adding self-healing agents on the compressive strength of mortar specimens were observed. The ability of mortar specimens to heal cracks was evaluated using crack microscopic observation and water absorption experiments. The filler at the cracks was microscopically analyzed by scanning electron microscope and X-ray diffraction experiments.

First, the internal curing effect of EP promotes the hydration of cement in mortar, which generates more amount and denser crystal structure of Ca(OH)2 at mortar cracks and improves the self-healing ability of mortar. Second, the self-healing ability of mortar improves with the increase of self-healing agent admixture. Adding a self-healing agent of high admixture makes the planar undulation of calcite crystal accumulation at mortar cracks more significant. Finally, the initial crack widths that can be completely healed by adding EP and self-healing agents to the mortar are 200 µm and 600 µm, respectively.

The innovation points of this study are as follows. (1) The mechanism of the internal curing effect of EP particles on the self-healing ability of mortar cracks was revealed by crack microscopic observation tests and microscopic experiments. (2) The effect of different self-healing agent amounts on the self-healing ability of mortar cracks has been studied. (3) The effects of EP particles and self-healing agents on healing different initial widths were elucidated by crack microscopic observation tests.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.