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Corporations with multiple national and international sites rely on telecommunication services such as public switched telephone network (PSTN) to deal with their customers and with vendors. Over the last few years, the cost of using PSTN for telecommunication has increased, thus adding considerable cost to business. The infrastructure of the internet is well placed now, and the continued growth of information technologies have made it cost effective to route voice calls over the internet, known as voice over internet protocol (VoIP). The purpose of this paper is to advance research, strategies and a predictive decision model that analyzes the cost of routing voice‐based traffic either via VoIP network or PSTN. This predictive decision model is based on the beta‐binomial distribution, and it computes the cost differential in tariff with respect to choice of routing the voice traffic between the VoIP network and the PSTN.

A call supported by the PSTN involves the establishment of an end‐to‐end circuit that is maintained for the duration of the call. A call supported by VoIP technology, by contrast, involves the transmission of many individual packets over an IP network. The cost of a VoIP call thus depends in part on the number and size of the packets that must be transmitted, i.e. the bandwidth required.

Great savings are realized when optimal number of calls would be routed through CCS vendors, as determined by the VoIP allocation model. The available bandwidth on the internet is capable of supporting VoIP at much cheaper rate than the expensive PSTN. Business could still buy into PSTN service if they require secured telecommunication services.

The paper tackles one of the most critical problems of minimizing the burden and costs of telecommunications by PSTN and VoIP.

This paper seeks to advance research and strategies that lead to a heightened awareness of the need to protect data from disclosure, to guarantee the authenticity of data and messages, and to protect systems from network‐based attacks.

The paper introduces the necessary mathematics of cryptography: integer and modular arithmetic, linear congruence, Euclidean and extended Euclidean algorithm, Fermat's theorem, and Elliptic curve.

The results indicate that encryption has expanded beyond confidentiality concerns to include techniques for message integrity checking, sender/receiver identity authentication, digital signatures, interactive proofs, and secure computation.

The results of this research show that all forms of e‐commerce activities such as online credit card processing, purchasing stocks, and banking data processing, if compromised, would lead to businesses losing billions of dollars in lost revenues as well as losing confidence in e‐commerce. In the last few years, it had been reported that organizations that store and maintain customers' private and confidential records were compromised on many occasions by hackers breaking into the data networks and stealing the records from the storage media.

This paper tackles one of the most critical problems of securing data networks. Security problems arise among other things to resource and workload sharing; complexity of interconnected networks; authentication of users; fast expandability of networks; threats to networks such as wiretapping and violations of the seven pillars of security: authentication, authorization, privacy, integrity, non‐repudiation, availability, and audit.

Artificial intelligence (AI) is a powerful and promising technology that can foster the performance, and competitiveness of micro, small and medium enterprises (MSMEs). However, the adoption of AI among MSMEs is still low and slow, especially in developing countries like Jordan. This study aims to explore the elements that influence the intention to adopt AI among MSMEs in Jordan and examines the roles of firm innovativeness and government support within the context.

The study develops a conceptual framework based on the integration of the technology acceptance model, the resource-based view, the uncertainty reduction theory and the communication privacy management. Using partial least squares structural equation modeling – through AMOS and R studio – and the importance–performance map analysis techniques, the responses of 471 MSME founders were analyzed.

The findings reveal that perceived usefulness, perceived ease of use and facilitating conditions are significant drivers of AI adoption, while perceived risks act as a barrier. AI autonomy positively influences both firm innovativeness and AI adoption intention. Firm innovativeness mediates the relationship between AI autonomy and AI adoption intention, and government support moderates the relationship between facilitating conditions and AI adoption intention.

The findings provide valuable insights for policy formulation and strategy development aimed at promoting AI adoption among MSMEs. They highlight the need to address perceived risks and enhance facilitating conditions and underscore the potential of AI autonomy and firm innovativeness as drivers of AI adoption. The study also emphasizes the role of government support in fostering a conducive environment for AI adoption.

As in many emerging nations, the AI adoption research for MSMEs in Jordan (which constitute 99.5% of businesses), is under-researched. In addition, the study adds value to the entrepreneurship literature and integrates four theories to explore other significant factors such as firm innovativeness and AI autonomy.

The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.

The study was carried out in a fivefold step. In the first step, the enablers of QWL were identified through an exhaustive literature survey, in the second step identified vital few components through Pareto analysis. Then the third step was followed by exploratory factor analysis (EFA) to further, to identify the precise components and validate the same using confirmatory factor analysis in fourth step. The final step included interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification analysis to model the validated components and determine the interrelationships and linkages.

Predominant QWL enablers of employees working in the garment industries are training and development, satisfaction in job, compensation and rewards, relation and co-operation, grievance handling, work environment, job nature, job security and facilities.

In this study, the interpretive structural model is designed based on the opinion of the experts who are working in the garment industry considering the responses from employees in garment sectors. The framework can be extended further to the other sectors.

In future, the researchers in QWL may develop a model to quantify the level of employees’ QWL who are working in different sectors. Enablers of QWL are essential, and based on this further statistical analysis can be carried out. This study will provide limelight to the researchers in choosing the valid and reliable set of enablers for the empirical studies. Organizations can get benefit by implementing the outcome of this research for the enhancement of the QWL of employees.

The study was carried out in 133 garment industries where 851 workers constituted the final valid responses that were considered for analysis. The outcomes from the study help administrators, policy and decision-takers in taking decisions to enhance QWL.