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This study investigates the antecedents of supply chain resilience of small and medium-sized enterprises (SMEs) and the effects of government assistance and disruption intensity in long-term disruptions.

This study collected data from 626 SMEs in Australia in 2022 and analysed data using partial least squares structural equation modelling.

The study empirically confirms that digital capabilities, prior experience in disruptions, supplier proximity and relationships are antecedents of supply chain resilience of SMEs, with supply chain robustness as a mediator. It further confirms that SMEs' access to government assistance positively moderates the relationship between digital capabilities and supply chain robustness. The disruption intensity moderates the relationships between supplier proximity and supply chain robustness with supply chain resilience. Severe disruptions weaken the effects of prior disruption experiences and supplier relationships on supply chain resilience.

The findings inform SME practitioners of the importance of building supply chain robustness, leveraging their prior experience, supplier proximity and relationships and capabilities and flexibility for dynamic supply chain structures when disruptions are intense.

The novelty of our study is the use of the Contingent Resource-Based View to understand the effects of firm and supply chain-level antecedents on supply chain robustness and resilience, considering the contextual contingencies of disruption intensity and government assistance. The focus on long-term disruptions extends the conventional supply chain resilience studies on supply and demand disruptions of small scale. We also explore the firm-level effects of government assistance, which extends the commonly tested economic-level effects. Furthermore, we investigate supply chain robustness and resilience as different but connected constructs, deviating from common approaches. The finding that the relationship between digital capabilities and supply chain robustness, not the relationship between digital capabilities and supply chain resilience, becomes stronger with higher access to government support shows the importance of this approach to investigating specific effects.

Malicious attacks extremely traumatize knowledge networks due to increasing interdependence among knowledge elements. Therefore, exposing the damage of malicious attacks to knowledge networks has important theoretical and practical significance. Despite the insights being offered by the growing research stream, few studies discuss the diverse responses of knowledge networks’ robustness to different target-attacks, and the authors lack sufficient knowledge of which forms of malicious attacks constitute greater disaster when knowledge networks evolve to different stages. Given the irreversible consequences of malicious attacks on knowledge networks, this paper aims to examine the impacts of different malicious attacks on the robustness of knowledge networks.

On the basic of dividing malicious attacks into six forms, the authors incorporate two important aspects of robustness of knowledge networks – structure and function – in a research framework, and use maximal connected sub-graphs and network efficiency, respectively, to measure structural and functional robustness. Furthermore, the authors conceptualize knowledge as a multi-dimensional structure to reflect the heterogeneous nature of knowledge elements, and design the fundamental rules of simulation. NetLogo is used to simulate the features of knowledge networks and their changes of robustness as they face different malicious attacks.

First, knowledge networks gradually form more associative integrated structures with evolutionary progress. Second, various properties of knowledge elements play diverse roles in mitigating damage from malicious attacks. Recalculated-degree-based attacks cause greater damage than degree-based attacks, and structure of knowledge networks has higher resilience against ability than function. Third, structural robustness is mainly affected by the potential combinatorial value of high-degree knowledge elements, and the combinatorial potential of high-out-degree knowledge elements. Forth, the number of high in-degree knowledge elements with heterogeneous contents, and the inverted U-sharp effect contributed by high out-degree knowledge elements are the main influencers of functional robustness.

The authors use the frontier method to expose the detriments of malicious attacks both to structural and functional robustness in each evolutionary stage, and the authors reveal the relationship and effects of knowledge-based connections and knowledge combinatorial opportunities that contribute to maintaining them. Furthermore, the authors identify latent critical factors that may improve the structural and functional robustness of knowledge networks.

First, from the dynamic evolutionary perspective, the authors systematically examine structural and functional robustness to reveal the roles of the properties of knowledge element, and knowledge associations to maintain the robustness of knowledge networks. Second, the authors compare the damage of six forms of malicious attacks to identify the reasons for increased robustness vulnerability. Third, the authors construct the stock, power, expertise knowledge structure to overcome the difficulty of knowledge conceptualization. The results respond to multiple calls from different studies and extend the literature in multiple research domains.

The purpose of this study is to investigate the correlation between the price return of leading cryptocurrencies, including Bitcoin, Ethereum, Ripple, Litecoin, Monero, Stellar, Peercoin and Dash, and stock return of technology companies' indices that mainly operate on the blockchain platform and provide financial services, including alternative finance, democratized banking, future payments and digital communities.

This study employs a Bayesian asymmetric dynamic conditional correlation multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (BADCC-MGARCH) model with skewness and heavy tails on daily sample ranging from August 11, 2015, to February 10, 2020, to investigate the dynamic correlation between price return of several cryptocurrencies and stock return of the technology companies' indices that mainly operate on the blockchain platform. Data are collected from multiple sources. For parameter estimation and model comparison, the Markov chain Monte Carlo (MCMC) algorithm is employed. Besides, based on the expected Akaike information criterion (EAIC), Bayesian information criterion (BIC), deviance information criterion (DIC) and weighted Deviance Information Criterion (wDIC), the skewed-multivariate Generalized Error Distribution (mvGED) is selected as an optimal distribution for errors. Finally, some other tests are carried out to check the robustness of the results.

The study results indicate that blockchain-based technology companies' indices' return and price return of cryptocurrencies are positively correlated for most of the sampling period. Besides, the return price of newly invented and more advanced cryptocurrencies with unique characteristics, including Monero, Ripple, Dash, Stellar and Peercoin, positively correlates with the return of stock indices of blockchain-based technology companies for more than 93% of sampling days. The results are also robust to various sensitivity analyses.

The positive correlation between the price return of cryptocurrencies and the return of stock indices of blockchain-based technology companies can be due to the investors' sentiments toward blockchain technology as both cryptocurrencies and these companies are based on blockchain technology. It could also be due to the applicability of cryptocurrencies for these companies, as the price return of more advanced and capable cryptocurrencies with unique features has a positive correlation with the return of stock indices of blockchain-based technology companies for more days compared to the other cryptocurrencies, like Bitcoin, Litecoin and Ethereum, that may be regarded more as speculative assets.

The study results may show the positive role of cryptocurrencies in improving and developing technology companies that mainly operate on the blockchain platform and provide financial services and vice versa, suggesting that managers and regulators should pay more attention to the usefulness of cryptocurrencies and blockchains. This study also has important risk management and diversification implications for investors and companies investing in cryptocurrencies and these companies' stock. Besides, blockchain-based technology companies can add cryptocurrencies to their portfolio as hedgers or diversifiers based on their strategy.

This is the first study analyzing the connection between leading cryptocurrencies and technology companies that mainly operate on the blockchain platform and provide financial services by employing the Bayesian ssymmetric DCC-MGARCH model. The results also have important implications for investors, companies, regulators and researchers for future studies.

Vector autoregressions (VAR) combined with Minnesota-type priors are widely used for macroeconomic forecasting. The fact that strong but sensible priors can substantially improve forecast performance implies VAR forecasts are sensitive to prior hyperparameters. But the nature of this sensitivity is seldom investigated. We develop a general method based on Automatic Differentiation to systematically compute the sensitivities of forecasts – both points and intervals – with respect to any prior hyperparameters. In a forecasting exercise using US data, we find that forecasts are relatively sensitive to the strength of shrinkage for the VAR coefficients, but they are not much affected by the prior mean of the error covariance matrix or the strength of shrinkage for the intercepts.

By drawing on knowledge-based view, this paper aims to test causal model linking supply chain analytics, innovation, robustness capability and firm age. More specifically, the mediating role of supply chain innovation on supply chain analytics and robustness capability link and the moderating role of firm age.

Survey data were procured from companies operating in the United Arab Emirates using a simple random sampling technique. The obtained data were analyzed with variance-based structural equation modeling (PLS-SEM).

The findings from PLS-SEM revealed that supply chain innovation fully mediate supply chain analytics and robustness capability associations. Findings from multi-group analysis (MGA) denote that firm age did not moderate any of the paths of the research model. Suggesting that the associations are similar for old, mid-aged and younger firms.

This work demonstrates that supply chain analytic is valuable tool that can foster innovation and robustness in supply chain. This work is among the first to scrutinize the variation among old, mid-aged and younger firms in supply chain analytics research stream. The paper concludes with implications for theory and practice.

The purpose of this paper is to investigate if Jordanian banks using provision accounts as a technique to smooth income, manage capital ratio, signal future earning and test other determinants affecting provision accounts.

The study was conducted on all Jordanian listed banks, and it covers the period 2005-2014. Different models are applied to test the dependent variables (loan loss provision [LLP] accounts) and its effects on different explanatory variables by using several statistical techniques (e.g. multiple regression).

The results show that there is no conclusive evidence supports that Jordanian banks used provision to smooth income, manage capital ratio or engage in pro-cyclical behavior. However, a positive and significant effect between one year ahead change in earnings and loan loss allowance, indicating that banks may use provisions to signal future positive changes in earnings. In addition, the results show that loan-to-asset ratio and beginning loan loss allowance have positive effect on provision accounts.

The results of this study are useful in assisting the regulators (e.g. US Securities and Exchange Commission, central bank) in efforts toward improving the quality of the reported financial reporting in the banking industry and focus on LLP management motivations. This study gives shareholders further insight which enables them to better understand the actions of managers and thus increase their control over their investments. Additionally, auditors should be aware of different incentives for using LLP as a tool of earnings management to be able to detect eventual manipulation of accounting earnings.

Banking in is one of the most stringently regulated of sectors and, furthermore, has a major impact on other sectors and on economic growth in general. In view of such importance, this study focuses on the banking industry and contributes to the literature in several ways. First, it represents the first known study, to the best of author knowledge, which examines if Jordanian banks use LLP accounts as a tool to smooth income and/or to manage capital. Second, unlike most existing research, which usually studies one aspect of LLP, this study focuses on four main motivations influencing provision accounts in the banks of Jordan. Third, additional tests were carried out to check the robustness of results, for example, sensitivity analysis is used to examine the change of findings by repeating of tests after using different proxies. Fourth, as a difference from other studies, this study investigates the effects of global financial crisis of 2008 on income smoothing behavior of Jordanian banking sector. Fifth, this paper provides a timely contribution to the continuous debate of the effect of LLP on earnings management in a poorly exploited setting, emerging market context.

Credibility concerns regarding integrated reports can harm the intended decrease of information asymmetry between a firm and its investors. Therefore, it is crucial to examine whether voluntary third-party assurance enhances the credibility of integrated reports and, thus, decreases information asymmetry. Furthermore, this study aims to investigate the interaction effect between assurance quality and the disclosed connectivity of the capitals, a distinguishing feature of integrated reports.

Content analysis is performed of the 176 assurance statements included in the 269 integrated reports of Forbes Global 2000 firms disclosed from 2013 to 2015 and the 269 integrated reports themselves. Regression analyzes are applied to examine the associations between assurance, the disclosed connectivity of the capitals and information asymmetry.

The presence of an assurance statement in an integrated report significantly decreases information asymmetry. Surprisingly, assurance quality is not significantly associated with information asymmetry. However, an interaction analysis reveals that combining high assurance quality with high disclosed connectivity of the capitals allows a significant decrease in information asymmetry.

The paper demonstrates that the connectivity of the capitals of integrated reports and assurance quality are connected and together are associated with information asymmetry.

The results imply, both for report preparers and standard setters, that assurance quality is advantageous only when combined with disclosed connectivity of the capitals.

More information on non-financial information measured by the connectivity of the capitals of integrated reporting has an interaction effect together with assurance quality on information asymmetry.

This paper builds on a unique data set derived from the contents of integrated reports and accompanying assurance statements. Furthermore, it extends the integrated reporting literature by investigating the interaction between assurance quality and the disclosed connectivity of the capitals, which had not previously been examined in combination.

This study aims to analyse whether the presence of supply chain complexity (SCC) influences firms to improve their supply chain (SC) resilience and SC robustness capability. This study also examines an important paradox: whether investing in both exploitation and exploration practices is conflicting or complementary to enabling SC resilience and robustness in the presence of SCC.

The authors used a survey-based approach to collect 242 useful responses from SC professionals of Pakistani firms, an important emerging economy context. The data were analysed with covariance-based structural equation modelling to statistically validate the model.

The analysis reveals several key findings: the presence of SCC has a direct, positive influence on SC resilience and SC robustness; while exploitation practices only partially mediate the nexus between SCC and SC resilience, they fully mediate the relationship between SCC and SC robustness; while exploration practices partially mediate the nexus between SCC and SC resilience, they do not mediate the relationship between SCC and SC robustness and SCC has a significant influence on SC resilience and SC robustness sequentially through exploitation and exploration (i.e. one after the other).

These findings help to reconcile the exploitation versus exploration paradox in cultivating SC resilience and SC robustness in the presence of SCC. The findings assist SC managers in determining how to deploy their limited resources most effectively to enhance SC resilience and SC robustness while facing SCC.

The authors devise and empirically validate a unique framework that demonstrates how the presence of SCC works as a stimulus to build SC resilience and SC robustness.

This paper aims to unite firm- and country-level drivers of the disclosure of integrated reports. It creates a synopsis of voluntary disclosure, signaling, proprietary cost, legitimacy, stakeholder and institutional theory.

The empirical analyses build on a logistic regression model examining the disclosure decisions for integrated reports published between 2012 and 2016 by the 2,000 largest listed companies worldwide.

The results indicate that the disclosure of integrated reports by large listed companies is explained in parallel by multiple theories, operationalized by the firm-level characteristics of lower profitability, a higher market-to-book value, lower leverage, lower level of industry concentration and higher social performance. Additionally, the country-level characteristics of civil law setting and lower investor protection, lower power distance and lower masculinity coincide with the disclosure of integrated reports.

The inferences emphasize that a single theoretical framework cannot explain the decision to disclose an integrated report. Rather, a set of economic firm characteristics may lead to different disclosure decisions in different socio-economic and institutional environments.

This study aims to examine the relationship between board capital and firm performance in the Chinese tourism industry.

The study’s sample includes firms from the Chinese hotel, air transportation/travel and catering industries. This study explores the governance environment in tourism industries. This study estimates three dimensions of the board, including education, expertise and directors interlock. These dimensions are further grouped as human capital (i.e. education and expertise), social capital (interlocks) and board capital (sum of social and human capital). Ordinary least square regressions with multiple robustness tests are used to investigate the effect of board capital on firm value in Chinese listed tourism firms during 2005–2018.

This study finds that board capital positively impacts firm performance in its dimensions of human and social capital. This study also highlights the two important ownership contexts, namely, institutional investors and state-ownership, that shape the board capital-firm performance association in the Chinese tourism industry.

The findings suggest that board capital plays a significant role in corporate decisions. The results illustrate that higher board capital improves both governance mechanisms and resource provision roles of the board, resulting in higher firm value. The results further offer implications for managers and shareholders of tourism firms when electing directors as shareholders’ representatives.

The study has two important contributions. First, it extends the prior literature of firm value by considering the board’s human and social dimensions in the tourism sector. Second, contrary to prior research on board, this study takes three facets of board capital, education, expertise and interlocks that improve governance mechanisms and bring new resources in the shape of skills, knowledge and expertise.