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Social movements are made up of organized groups and individuals working together to accomplish shared objectives. Under what circumstances do active groups build and break their coalitions? Five conditions have been identified in the literature as influencing coalition formation: common identity, resources, organizational structure, historical connection, and institutional setting. Whereas coalition dynamics within a movement wave are best understood in terms of institutional opportunities and threats, further research is needed to determine how and to what extent these contextual elements influence coalitions. This chapter examines how threats posed by indiscriminate and selective repression affect the shape and structure of interorganizational coalitions during the 2019 Anti-Extradition Law Amendment Bill (Anti-ELAB) protests in Hong Kong. The analysis relies on an original political event dataset and an organization-event network dataset. These datasets were produced utilizing syntactic event coding techniques based on Telegram posts, which Hong Kong protesters used to distribute information, plan future actions, and crowdsource news. Furthermore, Telegram provides detailed information about state activities, event-level coalitions, and violent groups, which is difficult to access from other sources. This study investigates the coalition networks across the movement's four stages, each of which was marked by a particular type and degree of repression. The findings indicate that indiscriminate and selective repression have varied effects on coalition networks. A wide coalition disintegrates as a result of indiscriminate repression. Selective repression, however, leads to the formation of coalitions around activist groups targeted by repression.

The purpose of this research is to review empirical research on customer involvement in innovation and identify future research directions that can better connect this research with marketing strategy literatures and offer opportunities for further theoretical development.

We conduct a review of empirical articles published in eight leading marketing and innovation journals between 2001 and 2017.

The review shows that the literature on customer involvement in innovation is highly diverse and fragmented, lacking a common understanding of what constitutes customer involvement in innovation and its theoretical underpinnings. There exists a multitude of conceptualizations of customer involvement in innovation, which limits effective accumulation of domain knowledge. A large number of studies have taken the customer’s perspective to examine their motivation to participate and ability to contribute, whereas less research has been done from the firm’s perspective to understand how firms may effectively manage the well-recognized challenges of customer involvement as well as the implications of customer involvement for long-term innovation strategy and overall performance. Based on the review, we offer recommendations for future research.

We identify important questions for future research that are highly relevant for the practice of customer involvement in innovation.

We provide a systematic review of the rapidly growing empirical research on customer involvement in innovation. We evaluate key points of differences in the literature and offer a synthesis that helps identify opportunities for future research.

In conventional discourses on sustainability, the relationship between economics and ecology is central. A number of nations' economies benefited from responsible tourism following these conferences. By supporting local businesses and attractions, ‘green’ tourism helps communities achieve their natural and cultural objectives while also preserving their limited resources. In terms of sustainable travel, Kerala was an early leader. This study looks at RT initiatives in various stages, with an emphasis on green tourism's sustainable responsible travel practises. The green economic development bottom line method was used for this descriptive research. These results highlight the difficulties inherent with RT implementation. Our review of secondary data shows that the first rollout of RT was unsuccessful, but that subsequent stages showed great promise. In order to create sustainable tourism on a worldwide scale, the study also highlights the necessity for more research in other culturally distant places.

Machine learning (ML) has recently gained momentum as a method for measurement in strategy research. Yet, little guidance exists regarding how to appropriately apply the method for this purpose in our discipline. We address this by offering a guide to the application of ML in strategy research, with a particular emphasis on data handling practices that should improve our ability to accurately measure our constructs of interest using ML techniques. We offer a brief overview of ML methodologies that can be used for measurement before describing key challenges that exist when applying those methods for this purpose in strategy research (i.e., sample sizes, data noise, and construct complexity). We then outline a theory-driven approach to help scholars overcome these challenges and improve data handling and the subsequent application of ML techniques in strategy research. We demonstrate the efficacy of our approach by applying it to create a linguistic measure of CEOs' motivational needs in a sample of S&P 500 firms. We conclude by describing steps scholars can take after creating ML-based measures to continue to improve the application of ML in strategy research.

Technology offers great potential to gifted, talented, and creative (GCT) students, including students who are twice exceptional (i.e., students who are GCT as well as identified with a disability). However, little research exists regarding the use and evidence-base base of technologies for these populations. This chapter presents technology to support students who are GCT as well as students identified as twice exceptional, including assistive technology to support students in content area instruction. Although, an evidence-base is needed for using technology in education for GCT and twice-exceptional students, existing research supports using the Internet and Web 2.0 technologies with these students.