Business’s accelerated globalization has weakened regulatory capacity of the law and scholars have been paid attention to fraud detection in recent years. In this study, we introduced Random Forest (RF) for financial fraud technique detection and detailed features selection, variables’ importance measurement, partial correlation analysis and Multidimensional analysis. The results show that a combination of eight variables has the highest accuracy. The ratio of debt to equity (DEQUTY) is the most important variable in the model. Moreover, we applied four statistic methodologies, including parametric and non-parametric models to construct detection models and concluded that Random Forest has the highest accuracy and the non-parametric models have higher accuracy than non-parametric models. However, Random Forest can improve the detection efficiency significantly and have an important practical implication.

Purpose: The study aims to examine the role of consumer psychological attitude, subjective norm, perceived behavior control and pro-environmental self-identity on green food purchase intention. Also, it examines the effect of ecological conscious consumers' behavior (ECCB) on green intention and behavior.Design/methodology/approach: The study has focused on the upper-middle-class segment of Karachi. The authors have used area sampling for collecting the data. Six recruited enumerators distributed 450 questionnaires in five areas of Karachi and received 423 filled-in questionnaires. The study has used the Smart PLS version for data analysis.Findings: The study found that biospheric egoistic and hedonic values affect attitudes toward green products, and altruistic values have no effect on attitude. Also, the authors did not find any association between attitude and green purchase intention, but found that attitude stimulates ECCB. Subjective norms and perceived behavior control strongly affect green purchase intention and ECCB. The results also suggest that pro-environment self-identity and ECCB are significant predictors of green purchase intention. The authors also found that green purchase intention stimulates green food behavior.Originality/value: The authors have taken a holistic approach by investigating 13relationships. The authors also examined the association between hedonic values and green purchase intentions, which in the past studies have contradictory results.

Marketers and advertisers ignore new technology and diverse marketing tactics when attempting to increase product exposure, customer engagement, customer behavior and buying intention in fashion accessory marketplaces in developing countries. This research sought to discover how the Augmented Reality (AR) experience influenced consumer behavior, buying intention and pleasure when purchasing a fashion item in developing countries. This study employs positivist ideas to investigate the connections between various factors, believing that reality is unwavering, stable, and static. Experiential marketing following stimulus exposure will gather cross-sectional data. The undertaken study has developed proper experimental design (within group) from business innovation models, for instance, uses and gratification and user experience models. User experience is disclosed by its four defining characteristics: hedonic quality (identification and simulation), aesthetic quality, and pragmatic quality. After encountering an enhanced user experience, users have a more favorable attitude about purchasing; in contrast, pleasure from using the application directly impacts buying intention. It was also shown that knowledge of AR apps impacts user experience and attitude. The novelty of this research is multifarious, for instance, the smart lab was used as a marketing technology to explore a virtual mirror of the Ray-Ban products. Secondly, the augmented reality experiential marketing activities have been developed by the developers as bearing in mind the four different aspects of the user experience—haptic, hedonic, aesthetic, and pragmatic. It should be functional, simple to learn and use, symmetrical, pleasant, and appealing, while fulfilling the unconscious emotional elements of a customer’s purchase. The research is the first known study in Pakistan to evaluate the influence of augmented reality on consumer proficiency and its consequent effects on attitude and satisfaction for fashion accessory brands. The research also advances the notion that application familiarity is the most important moderator between attitude and an augmented reality-enriched user experience, contradicting the prior studies, which focus on gender and age. This research has important theoretical implications for future researchers, who may wish to replicate the proposed final model in developed and developing countries’ fashion brands. This research also has imperative managerial implications for brand managers and marketing managers, who could include the recommendations of this study in their marketing strategies.

In today's world the data is considered as an extremely valued asset and its volume is increasing exponentially every day. This voluminous data is also known as Big Data. The Big Data can be described by 3Vs: the extreme Volume of data, the wide Variety of data types, and the Velocity required processing the data. Business companies across the globe, from multinationals to small and medium enterprises (SMEs), are discovering avenues to use this data for their business growth. In order to bring significant change in businesses growth the use of Big Data is foremost important. Nowadays, mostly business organization, small or big, wishes valuable and accurate information in decision-making process. Big data can help SMEs to anticipate their target audience and customer preferences and needs. Simply, there is a dire necessity for SMEs to seriously consider big data adoption. This study focusses on SMEs due to the fact that SMEs are backbone of any economy and have ability and flexibility for quicker adaptation to changes towards productivity. The big data holds different contentious issues such as; suitable computing infrastructure for storage, processing and producing functional information from it, and security and privacy issues. The objective of this study is to survey the main potentials & threats to Big Data and propose the best practices of Big Data usage in SMEs to improve their business process.