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Although studies have shown that electronic media exposure can negatively affect infants’ and young children’s language development, exposure to these forms of media is increasing in North America. To better understand the types of electronic media exposure and their potential effects, we utilized naturalistic daylong recordings collected in the homes of bilingual Spanish–English infants of Latinx descent (n = 37). The present study examines contextual aspects of electronic media exposure, and the effects of electronic media on two types of parent–infant social interactions associated with child language development: parentese (a style of infant-directed speech distinguished by its higher pitch, slower tempo, and exaggerated intonation) and parent–infant turn-taking. Using Language ENvironment Analysis (LENA), two daylong audio recordings were collected from each family. These recordings were manually annotated for electronic media type, directedness, language, parental support, parentese, and turn-taking. Our results showed that the infants in our study experienced exposure to many different forms of electronic media, in both English and Spanish, and that the programming was predominantly adult-directed rather than child-directed. While both parentese and turn-taking were reduced in the presence of electronic media, the strength of these effects was modulated by electronic media sources, demonstrating that various devices differentially affect parental language input. These results provide a glimpse into what types of media young bilingual Spanish–English learning infants are experiencing and can help researchers design language interventions that are inclusive and relevant for families from these populations.

This study offers an in-depth examination of Google Bard, an advanced artificial intelligence chatbot created by Google, focusing specifically on its potential impact on academic research. This discussion aims to comprehensively explore the features of Google Bard, highlighting its capabilities in data management, facilitating collaborative discussions, and enhancing accessibility to complex research. In addition to the aforementioned positive characteristics, we will also delve into the limitations and ethical considerations associated with this innovative device. The functionality of the system is constrained by the limitations imposed by its pre-established algorithms and training data. In addition, there are significant concerns regarding data privacy, potential biases in its responses stemming from its training data, and the wider societal implications associated with a heavy reliance on machine-generated content. Ensuring responsible and ethical utilization of Bard necessitates Google's provision of transparent communication regarding its development process. In light of the prominent functionalities demonstrated by Google Bard, it is imperative for researchers to engage in a rigorous examination of the information it presents, thereby safeguarding against the inadvertent propagation of misinformation or biased viewpoints. This will lay the groundwork for its effective integration into the academic research methodology.

This chapter sought to answer the following questions: (a) what does special education means for students with intellectual disability?, (b) what is being done, and (c) how do we maintain tradition? The answers, while complicated, suggest special education for students with intellectual disability historically and currently involves attention to what, how, and where, with the how being the key elements of special education for students with intellectual disability. This chapter discussed the what, how, and where for students with intellectual disability in a historical and current framework while also providing evidence-based practices for students with intellectual disability to implement to maintain the tradition of high-quality services.

Artificial intelligence and augmented reality are two key tools gaining importance in the digital era due to their wide range of applications in different fields and sectors. Industry 4.0 lays emphasis principally on the technology used to help the business remain competitive and sustainable. Sustainable development goals are another important objective of the UN which has laid responsibility for every business to support addressing the global challenges. Purpose: This chapter essentially aims to present the standpoint of artificial intelligence and augmented reality in meeting the sustainability perspective of organizations. Information about the study is gathered through secondary approaches, critically reviewing published literature, scientific reports, and statistical data accessible through business reports, and corporate websites. Further analyzed to present the perspectives of the authors in the study. Globally artificial intelligence market size is predicted to reach $190 billion by 2025, while the funding for startups doubled during the period 2011–2020 globally. The investment in artificial intelligence is going to reach $500 by 2024 resulting in substantial revenue returns. The augmented reality market size could reach $97 billion by 2028. Artificial intelligence today is increasingly used in many fields and is attracting multiple applications in many sectors such as manufacturing, retail, education, IT, and health care and has also contributed to sustainable development the same time by providing energy conservation options, optimization, and reduction of resources, minimizing wastage, offering timely assistance on maintenance schedules, practices which are enabling organizations to reach closer to sustainability and transformation.

Introduction: Amidst Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), turbulence is a vital component of an entrepreneurial landscape. VUCA world has set a new dynamic in the business environment and organisation’s settings. In such an environment, it is pertinent for entrepreneurs to exhibit creativity, innovative service behaviour, and performance.

Purpose: The study investigates whether creativity, innovative service behaviour, and performance of entrepreneurs are fostered through employee engagement practices in a highly volatile, uncertain, complex, and ambiguous environment.

Methodology: The methodology involves a systematic review and meta-synthesis. By identifying the major topics, a systematic literature review helped critically analyse and synthesise the literature.

Findings: According to the study, corporate entrepreneurial factors like (management reinforcement, reward/reinforcement, job autonomy/discretion, time attainability, and organisational boundaries) entrepreneurial potential, entrepreneurial orientation, human capital, self-efficacy beliefs lead to employee engagement, which, in turn, fosters creativity, innovative service behaviour, and performance among entrepreneurs in the VUCA world.

This chapter examines the influence of external public borrowing resources on economic progress in Tunisia. The study focuses on two stages: First, the influence is studied in a direct sense and then in an indirect sense, i.e., through a transmission channel of this influence. By applying the autoregressive distributed technique with staggered lags (ARDL), over a period ranging from 1986 to 2019, the results showed that the influence of external borrowing resources on growth seems to be unfavorable in the short term but positive in the long term, hence the importance of the empirical technique chosen. Second, three interaction variables were tested, namely total government expenditure, government investment expenditure, and the real effective exchange rate. The results obtained call for better attention to the channels identified to maximize the positive influence of external public debt on the country's economic progress.

Purpose: Different approaches have been applied to define and measure service quality as both a process and a performance-intensive presentation. The literature agreed that service quality assessments are essential in measuring performance, however they could only reach a partial consensus. Although the Servqual scale is the most widely known and used tool in measuring service quality, it has received various criticisms. This study presents the difficulties encountered in measuring service quality and an evaluation of the Servqual scale.

Methodology: The study provides a conceptual framework, examining the research on the subject in the literature and the criticisms of the Servqual scale. It is designed as a compilation/assessment to improve the perspectives of the interested parties by bringing together evaluations about the pros and cons of the most well-known service quality scale.

Findings: Measurement of service quality is a complex business. Although it has received various criticisms, the Servqual scale which enables the measurement of quality in the services sector is still the most frequently used measurement tool.

Practical Implications: The difficulty of defining the service and its quality, which arises from the characteristics of the services, does not eliminate the necessity of measuring the quality of the service. With this study, a conceptual framework has been provided on the subject, a collective evaluation has been made for the most widely used scale, and the ground has been prepared for improvement and development in the criticisms of the scale.

The supply chain is undergoing a significant digital transformation to adapt to the increasingly digitalized and globalized business environment. To remain competitive in this evolving market, businesses must seamlessly integrate digital technologies throughout the supply chain, spanning all stages from procurement to distribution. This chapter delves into models and methodologies critical to digital supply chain (DSC) transformation, with a focus on advanced techniques such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, and data analytics to boost the resilience and agility of supply chain operations. By leveraging practical examples and case studies, the chapter highlights the myriad enhancements digital transformation can introduce across diverse supply chain stages, including sourcing and after-sales service. Additionally, the chapter examines the complexities of cybersecurity, data integrity, and change management within the digital transformation framework, proposing strategies to address these challenges. The insights offered in this chapter will serve as a thorough guide for both practitioners and scholars in the supply chain field, equipping them to adeptly navigate the multifaceted arena of digital transformation.