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The purpose of the chapter was to examine the impact of customer care chatbots on customer satisfaction levels in the mobile telephony industry in Zimbabwe, with a special focus on the company Econet Wireless. This chapter shows the conceptual framework used. An online questionnaire was administered to a sample of 100 Econet Wireless subscribers who were selected using probability stratified random sampling from Zimbabwe’s 10 provinces. The research data were collected and analysed for correlation, and a multiple regression analysis was carried out to identify the relationship between customer satisfaction and the three customer service improvements brought in by the introduction of customer service chatbots. The study discovered that there is a positive relationship between customer satisfaction levels and each of the three customer service improvements brought in by customer service chatbots, namely customer service convenience, speed of response, and omnichannel strategies. This study thereby proves that the introduction of customer service chatbots in the mobile telephony industry in Zimbabwe can lead to an improvement in customer satisfaction levels. However, addressing service quality only as a determinant of customer satisfaction in isolation is not sufficient to fully improve customer satisfaction levels. Therefore, organisations that seek to improve their customer satisfaction should consider strategies that address all determinants of customer satisfaction, namely price, product quality, service quality, situational factors, and personal factors. This study contributes to the body of knowledge, particularly regarding the use of artificial intelligence (AI) for customer service in developing economies.

Purpose: The COVID-19 pandemic is the most severe threat we have faced since World War II. So far, there have been about 5 million recorded cases, with over 300,000 fatalities globally. The epidemic is also wreaking havoc on the corporate world. People are losing their jobs and money, and no one knows when normalcy will return. So, addressing the VUCA Leadership Strategies Model is important to get more insight into this topic.

Need for the Study: According to the International Labor Organization, the pandemic might cost 195 million jobs. Even when the immediate impacts wear off, the long-term economic impact will reverberate for years. All four volatile, unpredictable, complex, and ambiguous (VUCA) characteristics apply to the issues we confront due to the coronavirus.

Methodology: Changes caused by COVID-19 occur daily, and are unpredictable, dramatic, and quick. No one can predict precisely when the epidemic will end or when a treatment or immunisation will be available. The pandemic impacts many parts of society, including health care, business, the economy, and social life. There is no ‘best practice’ that enterprises may utilise to tackle the pandemic’s issues. The VUCA leadership strategy models will be discussed and compared in this research study.

Findings: In this moment of transition, leaders must adhere to their fundamental values, core purpose, and ambition for big, hairy, and audacious goals.

Practical Implications: In this chapter, VUCA leadership strategy models will be discussed in detail for pre- and post-pandemic scenarios and their impact on different sectors, which will be very important for researchers in the same field.

This chapter discusses what special education means for students with visual impairments (that is, those who are blind or have low vision) including what is being done and how traditions are maintained. More specifically, this chapter explores the importance of advancing values for the diverse population of students with visual impairments, focusing on cultivation of supportive, inclusive, and collaborative educational environments that continue to stand the test of time. This chapter highlights the increasing heterogeneity of this population of students and specific instructional strategies to support the cultural and linguistic diversity of learners with visual impairments in today's classrooms. This chapter also discusses the significance of promoting core concepts that are rooted in a traditional and specialized instructional framework for students who are visually impaired.

This performance autoethnography may or may not be interpreted as a continuation of a conversation regarding the experiences of those with devalued statuses in academic settings. The authors rely on “strange accounting” to consider their experiences in the academy from various standpoints: before and after promotion, before and after leaving academia. While reflecting on our past experiences, we introduce the concept of “everyday precariousness” as a way of explaining the normalization of instability, insecurity, and negative affect that is part of everyday life for those with devalued statuses in academic settings and beyond. Everyday precariousness is an embodied experience for those in vulnerable positions. Normalized exposure to risks, such as discrimination, harassment, bullying, or structural instability, produces an undercurrent of threat that permeates academic culture. Our stories of everyday precariousness span race, ethnicity, class, academic roles, and gender boundaries (among many others). Analyzing these experiences furthers previous work on the uses of strange accounting as well as the dynamics of status silencing. In the final analysis, unresisted and unabated, everyday precariousness and status silencing can lead to institutional failure and resonance disasters.

First-generation college students in the United States are a unique demographic that is often characterized by the institutions that serve them with a risk-laden and deficit-based model. However, our analysis of the transcripts of open-ended, semi-structured interviews with 22 “first-gen” respondents suggests they are actively deft, agentic, self-determining parties to processes of identity construction that are both externally imposed and potentially stigmatizing, as well as exemplars of survivance and determination. We deploy a grounded theory approach to an open-coding process, modeled after the extended case method, while viewing our data through a novel synthesis of the dual theoretical lenses of structural and radical/structural symbolic interactionism and intersectional/standpoint feminist traditions, in order to reveal the complex, unfolding, active strategies students used to make sense of their obstacles, successes, co-created identities, and distinctive institutional encounters. We find that contrary to the dictates of prevailing paradigms, identity-building among first-gens is an incremental and bidirectional process through which students actively perceive and engage existing power structures to persist and even thrive amid incredibly trying, challenging, distressing, and even traumatic circumstances. Our findings suggest that successful institutional interventional strategies designed to serve this functionally unique student population (and particularly those tailored to the COVID-moment) would do well to listen deeply to their voices, consider the secondary consequences of “protectionary” policies as potentially more harmful than helpful, and fundamentally, to reexamine the presumption that such students present just institutional risk and vulnerability, but also present a valuable addition to university environments, due to the unique perspective and broader scale of vision their experiences afford them.

The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based on 57,794 English-language tweets mined from Twitter from 1 April 2020 to 15 October 2020. Based on thematic and sentiment analysis, the study found that overall sentiments expressed on Twitter were negative. This chapter contributes to existing knowledge about the COVID-19 crisis and broadens the respondents’ understanding of the potential impacts of the crisis on the most vulnerable tourism and hospitality industry. This research emphasises the sustainable revival of the hospitality industry.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.