The current research aims to expose the value of Instagram's features and content and investigate how cognitive functions mediate the relationship between Instagram's content-related elements (informative material, user-generated content, augmented reality content, entertainment, trustworthiness, sociability) and consumer affection and behavior. This study employed a random sample strategy and gathered 292 responses. The tool AMOS 22 (Analysis of a Moment Structure) examined the data efficiently. Results show that all Instagram content marketing elements affect cognitive engagement, where augmented reality content has rated the highest effect, then user-generated content, trustworthiness, informative material, entertainment, and sociability, consequently. Then cognitive engagement affects affection and behavior.

During the innovation era and in the highly competitive environment, big data capabilities (BDCs) play a pivotal role in shaping competitive dynamics; the influence of these technologies on small and medium-sized enterprises (SMEs) operating in the retail sector is critically significant. This study is specifically focused on the retail industry, with a particular emphasis on how BDCs impact the project success, business continuity, and sustainability of SMEs within this industry. Our theoretical model was tested using a survey of 300 operations managers working in SMEs in the retail sector in the Middle East. PLS-SEM was conducted to analyze our collected data. Our results reveal that BDCs enhance project success and promote sustainability practices. The findings also reveal that BDCs have no impact on business continuity. By shedding light on the nuanced impact of BDCs on SMEs in the retail sector, this study contributes valuable insights to the existing literature, offering a deeper understanding of how these technological capabilities can drive success and sustainability in a highly competitive market environment.

This study aims to examine the indirect impact of supply chain management (SCM) in its three dimensions (relationship with suppliers, relationship with intermediaries and distributors, relationship with customers) on the competitive advantage (CA) in its five dimensions (Cost, Quality, Delivery Time, flexibility, and Creativity commitment) with the presence of information technology (IT) as a mediator. Furthermore, 250 questionnaires were distributed in Halawani Industrial Company. The questionnaires analyzed were 226. The Statistical Package for Social Sciences (SPSS) was used to test the hypotheses. The results of the partial analysis show that both relationships with the suppliers and customers contributed to the impact on IT, while the relationship with intermediaries and distributors did not contribute to the impact, but it was supportive of SCM to indirectly influence CA. The most important result of the study was the necessity to evaluate the fundamental competencies; periodically then continuously in order to alter the imperative assets which are the pillars of core competencies including the requirements and conditions regarding strategic thinking and leadership competencies. Also, the study provides an inventory of knowledge about the reality of SCM and its role in achieving CA through IT, which contributes to enriching the library in overall and Jordanian in specific in this subject.

Customer focus strategy has shifted the way the businesses shape their customer satisfaction. Service oriented companies in general have been given a great emphasis and a significance care to both customer satisfaction and customer delight lately. However, the management decision of what to offer to gain customer happiness is still a challenge issue. To test such issue, this study develops and tests a set of new factors which shapes both customer satisfaction and delight within the UAE setting. The factors include perceived service value, perceived service quality, perceived price fairness in addition to perceived service recovery. Data were collected through survey using a structured questionnaire distributed to 420 customers over all 28 branches of Etisalat Company in Dubai. 350 valid questionnaires were analyzed using factor analysis along with correlation and regression. The results of the study indicate that perceived service value, perceived service quality, perceived price fairness and perceived service recovery could be considered as the critical success factors that can be used to shape and measure customer satisfaction and delight. The findings can be used as guidelines to retain customers and to enhance the business value especially when organizations service providers focusing more on what customer perceive rather than focusing on what to offer from products and/or services. Moreover, some managerial implications and a set of theoretical recommendations are suggested in the final part of this study.

Loyalty programs are widely used by organizations as a structured customer relationship management (CRM) tool to build and extend customer-supplier relationship. Although a large number of benefits are offered through them to both companies and consumers, loyalty programs face a set of planning and implementation pitfalls. Scholars or practitioners rarely discuss such pitfalls. Thus, this paper intends to add further values to the current literature by exploring/investigating the main loyalty scheme pitfalls, both theoretically and practically. The study explores a set of loyalty program planning problems and some of the execution’s drawbacks, including clear aim need, loyalty program design, budgeting and experienced employee involvement. In addition to loyalty programs benefits and rewards offered, loyalty programs target customer selection problems using loyalty program promotional tools. For the study, 161 managers and employees who were involved in loyalty program planning and execution were surveyed. Smart-PLS was used to test the developed model and hypotheses. The study found that all studied loyalty program elements identified affected their planning and implementation. However, some of these elements where seen important to be considered when planning loyalty schemes, such schemes’ benefits and rewards offered were still not planned properly and did not meet customer needs or even expectations and, in most cases, the loyalty programs’ aims were not clear to all their stakeholders. The paper also provides additional discussion about additional issues of loyalty schemes planning and execution problems and proposes a set of solutions and recommendations, which might highlight some of the future venues with this regard.

Smart contracts offer automation for various decentralized applications but suffer from vulnerabilities that cause financial losses. Detecting vulnerabilities is critical to safeguarding decentralized applications before deployment. Automatic detection is more efficient than manual auditing of large codebases. Machine learning (ML) has emerged as a suitable technique for vulnerability detection. However, a systematic literature review (SLR) of ML models is lacking, making it difficult to identify research gaps. No published systematic review exists for ML approaches to smart contract vulnerability detection. This research focuses on ML-driven detection mechanisms from various databases. 46 studies were selected and reviewed based on keywords. The contributions address three research questions: vulnerability identification, machine learning model approaches, and data sources. In addition to highlighting gaps that require further investigation, the drawbacks of machine learning are discussed. This study lays the groundwork for improving ML solutions by mapping technical challenges and future directions.

This study aims to examine the complex dynamics of short video marketing, social sharing, and consumer engagement specifically within the tourism sector in Jordan. The study used AMOS software for analysis, gathering data from a total of 468 participants, including both internal and external tourists. The results emphasize the significant impact of short video marketing in stimulating social sharing behaviors among travelers, prompting them to share their experiences on various social platforms, thus expanding the reach of tourism-related content. Moreover, the research reveals the mutual relationship between social sharing and consumer engagement, indicating that sharing behaviors play a crucial role in increasing levels of engagement among tourists. The novelty of this research resides in its concentrated investigation of these associations within the unique context of the Jordanian tourism sector. The study's significance lies in its ability to expand comprehension of digital marketing dynamics in the tourism industry, providing practical insights for marketers seeking to improve brand visibility and engagement in digital spaces. This study enhances the current knowledge base by employing a quantitative approach, establishes a basis for future research endeavors, and offers valuable insights for marketers aiming to maximize the effectiveness of digital marketing strategies.

In the dynamic realm of facility management in the UAE, this study investigates the uptake of digital facility management systems among managers operating locally. The study aims to uncover the influential factors affecting technology acceptance within this sector. Its primary objective is to identify and understand the determinants that impact the adoption of these systems, utilizing a structured framework to analyze influential factors and their implications. The initial phase involves a systematic review to reveal trends in integrating digital technologies, focusing specifically on digital twin technology. Subsequently, quantitative surveys are conducted with 407 facility managers, guided by the UTAUT framework, employing statistical analyses to pinpoint key factors. Notably, Effort Expectancy and Performance Expectancy emerge as significant influencers, particularly influenced by the managerial level. This study provides detailed insights into the nuanced factors that drive acceptance, emphasizing the crucial role of constructs like Performance Expectancy and Effort Expectancy moderated by managerial level, shaping Behavioral Intention and Use Behavior. These findings offer practical implications for devising strategies to encourage the adoption of Digital Facility Management Systems in the UAE, laying the groundwork for future research and industry advancements.

This research focuses on the consumer cyborg's engagement with social media, online shopping, and tourism activities. The objective is to explore the effect of narcissism, social media addiction, and self-esteem on online shopping and tourism addiction. The survey involved 221 participants chosen through the convenient sampling method. The data was processed using exploratory and confirmatory factor analysis and structural equation models. The findings of this study indicate that narcissism significantly influences social media addiction and self-esteem. Besides, social media addiction has a considerable effect on self-esteem. In addition, self-esteem significantly impacts both online shopping addiction and tourism addiction. These findings provide new insights into cyborg marketing and consumer addiction theory.

The practical application of business data analytics in human resource (HR) management activities is still limited and underutilized. The primary reason for this is the requirement for more analytical skills, which can be acquired through data literacy. These skills are necessary to ensure obtaining the potential benefits of human resource analytics linked to desired positive employee outcomes, such as fostering innovative behavior. To address this issue, this quantitative study has been conducted to delve into the prospective moderating role of data literacy in the interaction between human resource analytics and employees’ innovative behavior. The core objective of this study is to examine whether human resource professionals’ data literacy level significantly impacts the correlation between human resource analytics and the inclination of employees towards innovative behavior. A sample of 250 HR specialists from large companies in Jordan has been used to address this inquiry. A correlational-predictive design has been used in this study. Regression analysis using the SPSS macro-PROCESS software has been utilized to address the study hypotheses. The study reveals a positive connection between HR analytics and employees’ innovative behavior. Moreover, it uncovers a noteworthy moderating influence of data literacy on this association. These findings suggest that heightened data analysis proficiency among HR professionals amplifies the potential benefits derived from analytics, thereby enhancing employees’ innovative capabilities. As a result, the research suggests that companies upgrade their technical infrastructure for HR functions and concurrently utilize data analytics for informed HR decisions. Further, these insights do serve as necessary inputs in understanding HR analytics and their implications for prudent business strategy. In view of this dynamic nature of HR analytics, the contributions made by the study are immensely valuable; hence, further exploration is needed to fill in gaps within existing knowledge.