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This paper aims to investigate the multifaced aspects and consequences of the EU Carbon Border Adjustment Mechanism (CBAM) from an Australia-China Relationship perspective.

This paper leverages the SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis to examine both the internal and external factors that affect Australia and China in the context of the CBAM. In addition, we employ the PEST (Political, Economic, Social and Technological) framework to identify effective strategies for Australia-China cooperation following the implementation of the CBAM.

Our analysis reveals numerous mutual interests and opportunities for bilateral collaboration, despite challenges and threats, positioning the CBAM as a potentially significant catalyst for joint initiatives.

This paper proposes 10 potential areas for Australia and China cooperation from the political economic social and technological PEST dimensions.

This paper makes a pioneering attempt to explore potential strategies, both individually, and together, that Australia and China can adopt to manage the impact and consequence of CBAM.

The purpose of this study is to examine Bitcoin's price behavior across market conditions, focusing on the influence of Bitcoin's historical prices, news sentiment and market indicators like oil prices, gold and the S&P index. The authors also assess the stability of Bitcoin-inclusive hedging portfolios under different market conditions, for example, bearish, bullish and moderate market states.

This study uses the Quantile Autoregressive Distributed Lag model to explore the effects of different factors on Bitcoin's prices across various market situations. This method allows for a detailed analysis of historical trends, investor expectations and external market influences on Bitcoin's price movements and systematic stability.

Key findings reveal historical prices and investor expectations significantly influence Bitcoin in all market scenarios, with news sentiment exhibiting substantial volatility. This study indicates that oil prices have minimal impacts on Bitcoin, whereas gold is a stabilizing asset in bear markets, with the S&P index influencing short-term fluctuations. At the same time, Bitcoin's volatility varies with market conditions, proving more efficient as a hedging tool in bear and stable markets than in bull ones.

This study highlights the intrinsic correlation between Bitcoin's prices, news sentiment and financial market indicators, enhancing understanding of Bitcoin's market dynamics. The authors demonstrate Bitcoin's weak direct correlation with commodities like oil, the stabilizing role of gold in crypto portfolios and the stock market's indirect effect on Bitcoin prices. By examining these factors' impacts across various market conditions, the findings offer strategies for investors to improve hedging and portfolio management in cryptocurrency markets.

The paper aims to analyze the potential of artificial intelligence (AI) in enhancing marketing capabilities for Indian fast-moving consumer goods (FMCG) firms, with appropriate emphasis on dynamic capabilities (DC). By integrating AI into their operations, companies can enhance diverse marketing practices, leading to improved efficiency and effectiveness. In addition, the study offers valuable insights and guidance for effectively implementing AI in marketing strategies.

In-depth interviews of 26 seasoned professionals from various positions in the Indian FMCG sector were conducted for the study. A systematic approach of coding that includes open, axial and selective coding was made to recognize the themes that represent AI-enabled marketing practices. This approach ensured that the themes were precisely identified and comprehensively analyzed. Interviews followed by a rigorous coding process provide valuable insights into the practical implementation of AI-enabled marketing practices for the Indian FMCG industry.

The study’s results underscore the importance of AI in enhancing marketing practices for FMCG firms, particularly in four critical areas: personalization, consumer engagement, marketing automation and strategic goals. By adopting AI in these areas, Indian FMCG firms can significantly enhance their marketing capabilities, increasing efficiency, effectiveness and gaining a competitive advantage.

The study uses qualitative data analysis to explain how DC through AI technologies can enhance digital marketing practices for Indian FMCG organizations. Furthermore, the study provides valuable insights into how AI technologies can improve marketing capabilities and emphasizes the importance of DC. The study also proposes a framework for AI-enabled Marketing 4.0 that can guide FMCG firms seeking to leverage AI technologies to enhance their marketing practices.

This study outlines the potential for enhancing marketing practices by adapting AI in the Marketing 4.0 environment for Indian FMCG companies, highlighting the importance of DC in achieving this goal.

The COVID-19 pandemic has brought unprecedented challenges to businesses worldwide, compelling them to swiftly adapt their strategies to the evolving landscape. This study explores the relationships between uncertainty shocks (i.e. COVID-19), strategic responses, and performance outcomes, with a specific focus on general and green strategic responses.

Drawing from a sample of sustainability-oriented exporters in different industries, we examine the impact of these responses on market, financial, and operation performance by gathering data from 212 managers in Vietnam – an emerging country, and then applying PLS-SEM for analysis.

Our findings reveal that sustainability-oriented exporters have exhibited adaptability by adopting general and green strategic responses in the face of the pandemic’s disruptions. Green strategic responses positively influence market, financial, and operational performance, underscoring the strategic significance of integrating sustainability considerations. However, while general strategic responses show alignment with uncertainty risks, they just impact operational performance, but do not significantly influence market and financial outcomes.

Future research should consider diversifying the sample to encompass a wider range of firm types and geographical locations to enhance the external validity of the results. In addition, the study does not extensively explore the mechanisms that mediate or moderate the relationships between uncertainty shocks, strategic responses, and performance outcomes.

The study’s implications guide practitioners toward agile responses that balance adaptability, sustainability, and performance. This study provides timely insights for sustainability-oriented firms, managers, policymakers, and researchers aiming to navigate disruptions effectively and sustainably.

These findings contribute to the fields of strategic management and sustainability by emphasizing the complexities of strategic responses during uncertainty shocks, and disruptions and the pivotal role of sustainability-driven strategies in enhancing performance.

This paper aims to clarify the relationship between digital transformation and labor structure from the perspectives of microenterprise business strategies and factor allocation efficiency. It attempts to address the gap in existing research by explaining the impact of digital transformation on multidimensional workforce structures and the positive effects of this structural adjustment on labor allocation efficiency. In addition, the study further explores the economic ramifications of digital transformation, clarifying the correlation between changes in labor force structure and enterprise human resource allocation, thus enhancing the employment mobility effects of digital innovation at the enterprise level.

In contrast to prior research, our approach uses text analytics to assess the internal labor structure, incorporating labor skill, position and age into the analytical framework. This approach yields a more comprehensive data set, shedding light on variations in multidimensional employment structures.

The paper asserts that digital transformation significantly influences labor structure changes, evidenced by increased proportions of high-skilled, non-routine and younger laborers, as well as decreased shares of low-skilled, routine and older-age workers. Furthermore, it captures internal labor structure impacts, influenced by enterprise size, ownership, industry density and regional digitization levels. Mechanism analysis indicates moderation of digital transformation effects on labor structure by innovative tasks, labor productivity and management shareholding.

The paper reveals the specific impact of corporate digital transformation on workforce structure, enriching the employment mobility effects of digital innovation at the enterprise level and providing theoretical support for the formulation and implementation of relevant policies.

First, this paper delves into the impact of digital transformation on the internal labor structure from a microlevel perspective, elucidating its mechanisms. Second, in contrast to prior research, it uses text analytics to assess the internal labor structure, incorporating labor skill, position and age into the analytical framework. This approach yields a more comprehensive data set, shedding light on variations in multidimensional employment structures. Lastly, the study investigates the economic ramifications of shifts in employment structures. The findings of this study furnish novel empirical evidence for the debate regarding whether digital transformation can indeed enhance labor allocation efficiency.

This study aims to examine how auditors' perfectionism types and time budget pressure (TBP) influence fraud detection in Egypt.

We utilize a mixed-methods approach, combining questionnaires with an experimental case study in a within-subjects quasi-experimental design. Based on Almost Perfect Scale-Revised (APS-R), perfectionism traits were categorized using cluster analysis into adaptive, maladaptive, and non-perfectionism. Auditors from Egyptian firms performed fraud-related tasks with TBP manipulated.

Auditors' perfectionism types significantly influence fraud detection capabilities. Adaptive perfectionists demonstrated higher relevance in identifying fraud factors and excelled in accurately assessing fraud risks and audit procedures planning. Conversely, maladaptive perfectionists identified more but less relevant factors. TBP notably impacted maladaptive and non-perfectionist auditors' planning quality, unlike adaptive perfectionists, who showed resilience.

Findings provide insights to audit firms to bolster audit quality through team formations and task assignments, harnessing the strengths of adaptive and maladaptive perfectionists. Regulatory entities are positioned to integrate safeguards that recognize auditor capabilities and vulnerabilities, particularly under TBP. Considering psychological assessments in auditor selection and development assures alignment of traits with audit tasks, enhancing audit quality.

This study breaks new ground in the effects of auditor perfectionism on fraud detection, considering situational factors like TBP in emerging markets. Through a mixed-methods approach and cluster analysis, it reveals how different perfectionism traits influence audit effectiveness, offering insights not previously considered in auditing literature and suggesting practical applications for enhancing fraud detection in similar contexts.

The purpose of this paper is to investigate the likelihood of firm exit, focusing on firm- and sector-specific factors and other potential constraints that may lead to exit.

The authors address the main research question by using hazard-cox and probit models on plant level data for the period 1998–1999 to 2012–2013, drawn from the Annual Survey of Industries collected by the Central Statistical Organisation.

The authors find that probability of exit reduces with improved firm performance. Urban firms, proprietary firms and smaller firms are more likely to exit as compared with their respective counterparts. The findings are robust to alternate measures of performance, alternate specifications and different methods.

Studies of entry and exit rates at a point in time are useful in examining the turnover of establishments. But to understand the establishment survival, the authors must also examine the probability of firm exit and the possible determinants that aid exit. There are institutional factors that prevent easy exit of firms from an industry. It would be worthwhile to see how the exit rate will be impacted if these barriers ceased to exist. In this study, the authors construct a model of exit, which would help us to predict firm exit.

This study aims to measure the degree of volatility comovement between stock market liquidity and informational efficiency across Asia, Europe, North-South America, Africa, and the Pacific Ocean over three decades. In particular, the authors analyze the extent of the time-varying nexus between different aspects of stock market liquidity and multifractal scaling properties of the stock return series across various regions and diversified market conditions. This study further investigates several factors altering the degree of dynamic conditional correlations (DCCs) between the efficiency and liquidity of the domestic stock markets.

The study measures five aspects of stock market liquidity – tightness, depth, breadth, immediacy, and adjusted immediacy. The authors evaluate the multifractal scaling properties of the stock return series to measure the level of stock market efficiency across the regions and diversified market conditions. The study uses the dynamic conditional correlation-multivariate generalized autoregressive conditional heteroscedasticity framework to quantify the degree of volatility comovement between liquidity and efficiency over the period.

The study finds the presence of stronger volatility comovement between inefficiency and illiquidity due to the price impact characteristics of the stock markets irrespective of different regions and diversified market conditions. The extent of time-variation increased following the shock periods, indicating the significant role of the financial crisis in increasing the volatility comovement between inefficiency and illiquidity. The highest degree of time-varying correlation is observed in the developed stock markets of Northwestern and Northern Europe compared to the regional and emerging counterparts. On the other hand, weak DCCs are observed in the emerging stock markets of Europe.

The output of the present study assists investors in identifying diversification opportunities across the regions. Additionally, the study has significant implications for market regulators, aiding in predicting future troughs and peaks. The prediction, in turn, helps formulate capital market development plans during dynamic economic situations.

The retail investment landscape in the UK has drastically changed. Understanding owners’ responses to this structural change is critical to gain insight into protecting investment performance. This paper identifies and evaluates the tactics and strategies being adopted.

This paper employs a mixed methods research approach, using data collected from semi-structured interviews with professionals involved in the retail investment process. This is supplemented by secondary market data analysis.

The paper assesses the practical responses made by retail property owners/managers, structured around emerging sub-themes. Actions include mitigating short-term risks through greater use of temporary tenants/licensees and independent retailers, preparing generic “white box” retail space to capture remaining tenant demand, exploiting the tenant mix to provide “the retail experience,” and applying new technologies and processes in a sector where systematic risk remains high. A new framework for retail asset management has been developed.

This study contributes to the retail asset management literature and understanding of the way the contemporary retail landscape is shaping investment management behaviour.

The developed framework provides guidance to real estate managers developing a retail real estate management strategy and will help them recognise tactics to better support the evolving retailing market.

The new framework adds new insights to understanding the process for managing retail assets and the actions necessary for asset managers to address economic/functional obsolescence and sustain asset investment values.

This paper aims to propose a framework to assess the readiness of Brazilian small and medium service companies to use Industry 4.0 technologies to improve the efficiency of processes, reinforcing the idea that evaluating and planning the implementation is as important as the use, without the need for big investments.

The paper presents two applications on the readiness level of small and medium enterprises, with support from researchers and stakeholders. The literature seems to focus more on the maturity level than on providing a sequence of operational steps or decision support. It would lead to better implementation of I4.0 technologies in assessing the company’s readiness level to adopt them.

The authors analyze the relevant case studies in Brazilian small and medium service enterprises based on the proposed framework to investigate the main challenges and hardships for Industry 4.0 readiness in the current scenario and outline directions to increase their readiness for adopting key Industry 4.0 technologies. Moreover, the case studies consolidate a fundamental advantage to small and medium enterprise service: a guided implementation provides more knowledge about products, processes and I4.0 technologies, even in unsuccessful case studies.

The need was identified when studying market trends with the digital transformation provided by Industry 4.0 technologies and, in parallel, the difficulties of small and medium service companies in adapting to this new scenario. Through the proposed framework, an action plan can be drawn up with well-defined objectives, goals and activities so that the service enterprises can increase their Industry 4.0 readiness level within three months.

A relevant aspect is that this study is based on feedback from stakeholders and managers, which makes the analyses and conclusions from empirical points of view without relevant theoretical knowledge of the relationship between I4.0 technologies. Therefore, the proposed framework made it possible to diagnose the organization’s external and internal environments, allowing the ideal condition and the current situation of the companies to be compared, as argued in the Industry 4.0 readiness literature review.