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This study explores the challenge of cyber security threats that e-commerce technology and business are facing. Technology applications for e-commerce are attracting attention from both academia and industry. It has made what was not possible before for the business community and consumers. But it did not come all alone but has brought some challenges, and cyber security challenge is one of them. Cyber security concerns have many forms, but this study focuses on social engineering, denial of services, malware, and attacks on personal data. Firms worldwide spend a lot on addressing cybersecurity issues, which grow each year. However, it seems complicated to overcome the challenge because the attackers continuously search for new vulnerabilities in humans, organizations, and technology. This paper is based on the conceptual analysis of social engineering, denial of services, malware, and attacks on personal data. We argue that implementing modern technology for e-commerce and cybersecurity issues is a never-ending game of cat and mouse. To reduce risks, reliable technology is needed, training of employees and consumer is necessary for using the technology, and a strong policy and regulation is needed at the firm and governmental level.

This study investigates the impact of globalization (defined as phasing-out of the multifiber arrangements [MFA]/agreement on textile and clothing [ATC]) on working conditions of textile and apparel workers in general and female workers in particular in Pakistan. We found that the impact of the elimination of the MFA/ATC on workers of the textile and apparel sector is negative and statistically insignificant. The working conditions of workers in the textile and apparel sector are not different relative to other sectors. The working conditions of females deteriorated as a result of the phasing out of the MFA/ ATC in relation to the male working environment and compared with other industries. Our findings are robust in the sense that the direction of the impact remains the same and statistically significant even after performing sensitivity analysis. We also controlled for provincial heterogeneity, and the results showed minor correction in magnitude but remain negative and statistically significant. We also addressed treatment selection bias by performing propensity score analysis and found similar results.

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