Research background: With growing evidence of consumer adoption of mobile shopping apps, there is a pivotal need for comprehending Internet-enabled consumer devices in mobile shopping behavior. Mobile shopping platform features and user technological readiness configure consumers? expectations and demands as regards mobile retailing adoption, leading to acceptance of mobile shopping apps and payment services. Purpose of the article: In this research, prior findings have been cumulated indicating that mobile social apps extend throughout consumer attitudes and behaviors by the widespread adoption of smartphones. We contribute to the literature by showing that cutting-edge technological developments associated with customer behavior in relation to mobile commerce apps have resulted in the rise of data-driven systems. Consumer behavioral intention and adoption intention in relation to mobile shopping apps/websites are developed on perceived risk and trust consequences. Methods: Throughout February and March 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was carried out, with search terms comprising ?mobile shopping app?, ?mobile commerce platform?, ?mobile payment service?, ?Internet-enabled consumer device?, ?consumer technological adoption?, and ?mobile shopping behavior?. As research published between 2018 and 2021 was analyzed, only 330 sources met the suitability criteria. By removing questionable or indeterminate findings (insubstantial/inconsequent data), results unconfirmed by replication, too imprecise content, or having quite similar titles, 66, chiefly empirical, sources were selected. A systematic review of recently published literature was carried out on technological adoption of mobile commerce apps by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. The Systematic Review Data Repository was used, a software program for the gathering, handling, and analysis of data for the systematic review. The quality of the academic articles was determined by harnessing the Mixed Method Appraisal Tool. Findings & value added: The consumer purchase decision?making process in mobile app-based marketing involves consumer engagement and willingness to adopt mobile commerce apps. Further advancements should clarify how technological-based consumer adoption of mobile shopping throughout social commerce can improve the payment for products and services.

The aim of this paper is to synthesize and analyze existing evidence on interconnected sensor networks and digital urban governance in data-driven smart sustainable cities. The research topic of this systematic review is whether and to what extent smart city governance can effectively integrate the Internet of Things (IoT), Artificial Intelligence of Things (AIoT), intelligent decision algorithms based on big data technologies, and cloud computing. This is relevant since smart cities place special emphasis on the involvement of citizens in decision-making processes and sustainable urban development. To investigate the work to date, search outcome management and systematic review screening procedures were handled by PRISMA and Shiny app flow design. A quantitative literature review was carried out in June 2024 for published original and review research between 2018 and 2024. For qualitative and quantitative data management and analysis in the research review process, data extraction tools, study screening, reference management software, evidence map visualization, machine learning classifiers, and reference management software were harnessed. Dimensions and VOSviewer were deployed to explore and visualize the bibliometric data.

Research background: Enterprise generative AI system-based worker behavior tracking and monitoring, socially responsible organizational practices, employee performance management satisfaction, and human resource management procedures, relationships, and outcomes develop on hiring and objective performance assessment algorithms in terms of human resource management activities, functions, processes, practices, policies, and productivity. Deep reinforcement and machine learning techniques, operational and analytical generative AI and cloud capabilities, and real-time anomalous behavior recognition systems further fintech development for credit and lending services, payment analytics processes, and risk assessment, monitoring, and mitigation. Generative AI tools can bolster predictive analytics by collaborative and interconnected sensor and machine data for tailored, seamless, and fine-tuned product, operational process, and organizational workflow development, efficiency, and innovation, driving agile transformative changes in digital twin industrial metaverse. Purpose of the article: We show that enterprise generative AI-driven schedule prediction tools, job search and algorithmic hiring systems, and synthetic training data can improve team selection, job performance and firing decisions, hiring decision processes, and workforce productivity in terms of prediction and decision-making by use of algorithmic management, system performance, and production process tracking tools. Blockchain-based fintech operations can shape cloud-based financial and digital banking services, quote-to-cash process automation, cash-settled crypto futures, digital loan decisioning, asset tokenization simulated transactions, transaction switching and routing operations, tailored peer-to-peer lending, and proactive credit line management. Collaborative unstructured enterprise data processing, infrastructure, and governance can develop on AI decision and behavior automation technology, retrieval augmented generation and development management systems, and real-time data descriptive and predictive analytics, driving productivity surges and competitive advantage in digital twin industrial metaverse. Methods: Reference and review management tools, together with evidence synthesis screening software, harnessed were Abstrackr, AMSTAR, ASReview Lab, CASP, Catchii, Citationchaser, DistillerSR, JBI SUMARI, Litstream, PICO Portal, and Rayyan. Findings & value added: The current state of the art is improved for theory on organizational issues and for policy making as deep learning-based generative AI tools and workplace monitoring systems can augment performance and productivity, gauge employee effectiveness, build resilient, satisfied, and engaged workforce, assess human capital, skill, and career development, drive employee and productivity expectations in relation to flexibility and stability, and shape turnover, retention, and loyalty. Cloud and account servicing technologies can be deployed in generative AI fintechs for embedded cryptocurrency trading, transaction monitoring and processing, digital asset transfers, payment screening, corporate and retail banking operations, and fraud prevention. Generative AI technologies can reshape jobs and reimagine meaningful work, involving creativity and innovation and adaptable and resilient sustained performance, providing valuable constructive feedback, optimizing workplace flexibility and psychological safety, and measuring and supporting autonomy and flexibility-based efficiency, performance, and productivity, while configuring demanding, engaging, and rewarding experiences by cloud and edge computing devices in digital twin industrial metaverse.

This research investigates the critical role of intercultural communication and cultural intelligence in global international organisations and their link to effective stakeholder engagement and Environmental, Social, and Governance (ESG) practices. There is still a scarcity of empirical research focusing on global governance institutions like the United Nations (UN), which was chosen as a case study. Such organisations are one-of-a-kind communicative spaces in which people from various cultural, linguistic, and professional backgrounds work together to achieve common international goals. However, despite the UN’s prominent role in enabling global collaboration, the mechanisms by which intercultural communication occurs and adapts in such circumstances are little understood. Focusing on the social and governance dimensions of ESG, this research brings new insights into the work of the United Nations (UN)’s multicultural teams, as well as into the cross-cultural projects at the heart of this organisation and how they align with the goal of preserving local cultures in achieving the Sustainable Development Goals (SDGs). The study’s findings confirm the critical role of intercultural communication in engaging internal and external stakeholders and reinforcing sustainable ESG practices in international institutions such as the UN. Moreover, the managerial implications of the research could be of relevance to other global organisations which operate across diverse cultural contexts, where understanding and managing these differences become essential for fostering trust, collaboration, and responsibility. The paper proposes a conceptual framework verified through corroborated semistructured interviews to illustrate how intercultural communication enhances inclusivity, tailors ESG strategies to cultural contexts, and improves organisational decision-making and accountability.