Disruptive technologies like the internet of things, big data analytics, blockchain, and artificial intelligence have transformed how businesses operate. Artificial intelligence (AI) is the most recent technological disruptor and has enormous marketing transformation potential. Practitioners all over the world are attempting to determine which AI solutions are best suited to their marketing needs. A systematic literature review, on the other hand, can highlight the importance of artificial intelligence (AI) in marketing and point the way for future research. The goal of this study is to provide a comprehensive review of AI in marketing by analysing extant literature published between 1982 and 2020 using bibliometric, conceptual, and intellectual network analysis. The performance of the scientific actors, such as the most relevant authors and sources, was identified through a comprehensive review of 1,584 papers. Furthermore, the conceptual and intellectual network was revealed through co-citation and co-occurrence analysis. The Louvain algorithm was used to cluster data and identify research sub-themes and future research directions in order to expand AI in marketing.

The high volatility and energy usage of rare earths have raised sustainable and financial concerns for environmentalists and sustainable investors. Therefore, this paper aims to investigate time-varying volatility transmission among rare earths elements, energy commodities, and sustainable financial markets. The sample covers global and major financial markets, i.e., US, China, and Australia. Using daily log returns from 2018 to 2022, the paper considers the dynamic Time Varying Parameter-Vector Autoregression (TVP-VAR) connectedness approach to gauge the time-varying features of volatility spillovers. The findings of total spillovers index reveal weak connectedness among markets during the sampled period. US and China rare earth markets were net volatility transmitters, whereas the Dow Jones Australia Sustainability Index (ASI), China Sustainability Index (CSI), Dow Jones Sustainability World Index (SWI), and MVIS Global Rare Earth Index (MVISGREI) were net recipients. Moreover, energy commodities i.e., WTI Crude Oil, Gasoline, and Natural Gas were net volatility transmitters, while ASI, CSI, and SWI were major volatility recipients. The weak financial contagion effect and connectedness across financial markets uncovers possible diversification opportunities. However, the US sustainable financial market is persistently not affected by these volatility spillovers. Policymakers need to establish strict regulations to protect sustainable financial markets in China and Australia.

This study investigates the co-movements between the Solactive Electric Vehicle and Future Mobility Index (EVFMI) and multiple rare earth elements (REEs). We applied a TVP-VAR model and bivariate wavelet coherence approach to capture co-movements both in the time and frequency domain considering short-, medium- and long-term investment horizons. Using daily returns from 1 June 2012 to 4 June 2021, the results of the TVP-VAR model show that individual REEs and the EVFMI have strong return connectedness and are heterogenous over time. The bivariate wavelet coherence approach reveals that Dysprosium, Neodymium, Praseodymium and Terbium returns have positive co-movement (in-phase) with the EVFMI in the medium-term and long-term. In contrast, Cerium, Europium, Lanthanum and Yttrium returns have negative co-movements (out-phase) with the EVFMI in the medium-term and long-term. We find strong positive co-movements between the MVIS Global Rare Earth/Strategic Metals Index (MVREMX) and EVFMI at multiple wavelet scales. Following the lead/lag relationship, Cerium, Europium and Lanthanum, Yttrium returns are leading the EVFMI, and Neodymium, Dysprosium, Praseodymium, Terbium and MVREMX returns are lagging to the EVFMI. This study, therefore, suggests heterogenous hedging and diversification properties of REEs over time and investment horizons. Specifically, Cerium, Europium, Lanthanum and Yttrium act as strong hedges in long-term investment horizons and Neodymium, Dysprosium, Praseodymium and Terbium are weak hedges or diversifiers in short-term investment horizons. These results may be of particular interest to investors and relevant to policymakers considering multiple investment horizons.

Workplace productivity is badly affected by many negative factors such as narcissism, and sadism. In addition, paranoia and antagonism play an important role in increasing workplace incivility. Through emotional intelligence, such negative behaviors could be addressed by managers and their junior colleagues. The current study aims to investigate the parallel mediating role of paranoia, antagonism, and emotional intelligence on the relationship between narcissism, sadism, and workplace incivility. A survey approach was used. Primary data was collected in PLS-SEM. The population of the study was all faculty members in higher education institutions in the Khyber Pakhtunkhwa (Pakistan) region. A measurement model and structural model were developed. The measurement model demonstrated that convergent and discriminant validities were established. The structural model's findings revealed that narcissism, antagonism, and emotional intelligence were not mediated between narcissism and workplace incivility. Similarly, emotional intelligence did not play any mediating role between sadism and workplace incivility. This implied that emotional intelligence has no role in decreasing or reducing workplace uncivil behavior.