Search results

The study aims to review state-of-art literature on supply chain resilience in SMEs in the context of the coronavirus (COVID-19) pandemic and provides a comprehensive view of insights gained, gaps identified and suggests potential areas of future research.

Using a thorough search strategy, 46 articles were found relevant for this study. Each of these articles was further reviewed, classified and analysed to highlight the development of literature in this field and identify the significant focal area of research in this domain.

The classification of studies indicates a growing number of articles in the last two years with a significant focus on multiple industries and survey-based research design. The study's findings suggest that literature on supply chain resilience in SMEs falls into four categories: supply chain resilience principle, impact of COVID-19 pandemic on SMEs, strategies for developing supply chain resilience and role of Industry 4.0 technologies in supply chain resilience. We also identified knowledge gaps and suggested directions for future research to catalyse studies at the interface of supply chain resilience, SMEs and COVID-19 pandemic.

The generalisability of this study can be limited to a specific population of online databases and selected time periods chosen for a particular period.

The study provides a structured literature review on studies published between 2012 and 2022 for the use of academicians and practitioners. Findings will be of great value for SMEs to improve their resilience during the uncertain business environment.

The purpose of this study is to discern the role of entrepreneurial leadership (EL) – a dynamic capability – in increasing supply chain performance (SCP), through building supply chain resilience (SCR). The study further suggests that the presence of supply chain orientation (SCO) within a firm will enhance the relationship between EL and SCR.

Dynamic capabilities view is used to develop the hypotheses and a survey method is used to collect data from manufacturing firms in Pakistan. The hypothesized model is tested using structural equation modeling (SEM).

The results in general confirm the hypothesized model. The findings suggest that SCR mediates the relationship between EL and SCP. The results also confirm that SCO moderates the relationship between EL and SCR.

This paper contributes by studying the pivotal role of EL in building SCR and sustaining a competitive advantage in an uncertain environment.

This study aims to examine the levels of stress and resilience in a sample of British Indian parents bringing up a child with autism.

A total of 52 British Indian parents took part in a survey that included measures of stress, resilience, support and child adaptive functioning. Results were compared to a sample of white British (n = 120) and Indian parents (n = 120).

The British Indian parents recorded higher levels of stress and less perceived social support than their white British counterparts. British Indian parents took longer to register concern about their child’s development and sought a diagnosis at a later age than the white British group. The delay in concern and diagnosis was similar to that found in the India group.

The research suggests that British Indian parents are disadvantaged in social support and mental well-being compared to white British parents and may face similar community pressures to parents bringing up a child in India.

This paper aims to investigate the difference between the impacts of indicators of trade barriers (TBs) on bankrupt enterprises (BEs), new enterprises (NEs) and other enterprises (OEs).

The paper has used a multiple-step approach. At the first stage, the initial data has been collected from interviews with 164 top managers of SMEs in West Azerbaijan in Iran during two periods of 2013–2015 and 2017–2019. At the second step, multiple correspondence analysis has been used to summarize the relationships between variables and construct indices for different groups of TBs. Finally, the generalized structural equation model method was used to examine the impact of export barriers.

The results showed that the political legal index is the main TBs for BEs and NEs, but it had a more significant impact on BEs; the financial index was the second major TBs factor for BEs, while OEs did not have a problem in performance index, and the financial index was classified as a minor obstacle for them. All indicators of marketing barriers (except production index) had a negative and significant effect on all enterprises; the most important TBs for NEs was the information index.

The results indicated that if enterprises have a strong financial system and function, they can lessen the impact of sanctions and keep themselves in the market.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

The objective of this study is to examine how formal and informal institutional environment influences managers’ fair value opinion shopping behaviour in the largest International Financial Reporting Standards adopter, China.

To test the hypotheses, I conduct a 2 × 2 between-subject randomised experiment since the inferences about cause and effect are important in this study. The between-subject experimental situations are manipulated on the basis of the financial condition of companies and boards’ oversight.

I find that managers are likely to seek favourable fair value opinions from external valuation professionals when they are under the weak boards’ oversight and high stress to meet the regulation target of the China Securities Regulatory Commission. These results are more pronounced for managers with higher both rent-seeking and favour-seeking guanxi orientations are more likely to engage in fair value opinion shopping.

Consistent with theoretical analysis of Balfoort et al. (2017), this study provides empirical evidence that guanxi influences the neutrality and faithful representation in fair value measurement in China. In addition, the findings extend Salzsieder’s study (2015) and reflect the context-embeddedness nature of accounting.