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This article explores the effect of technological similarity in acquisitions on invention quantity and quality. In doing so, we confirm previous findings in the literature suggesting that technological similarity exhibits an inverted U-shaped relationship with innovative output and a negative relationship with average invention quality. However, we identify the nature of the technology as an important moderating factor for both relationships. We distinguish between two types of technologies, complex and discrete, and suggest that at high levels of technological similarity, invention quantity and average quality increase more in complex technology industries as compared to discrete technology industries. These effects are attributed to innovation cumulativeness and the interdependencies developed between patent rights in complex technology settings. A study of acquisition and patenting activity in two industries over a sixteen-year period provides empirical support to our claims.

Dynamic relationships between technologies and organizations are investigated through research on digital visualization technologies and their use in the construction sector. Theoretical work highlights mutual adaptation between technologies and organizations but does not explain instances of sustained, sudden, or increasing maladaptation. By focusing on the technological field, I draw attention to hierarchical structuring around inter-dependent levels of technology; technological priorities of diverse groups; power asymmetries and disjunctures between contexts of development and use. For complex technologies, such as digital technologies, I argue these field-level features explain why organizations peripheral to the field may experience difficulty using emerging technology.

In this paper, we seek to understand how changes in product architecture affect the innovation performance of firms in a complex product ecosystem. The canonical view in the literature is that changes in the technological dependencies between components, which define a product’s architecture, undermine the innovation efforts of incumbent firms because their product development efforts are built around existing architectures. We extend this prevailing view in arguing that component dependencies and changes in them affect firm innovation efforts via two principal mechanisms. First, component dependencies expand or constrain the choice set of firm component innovation efforts. From the perspective of any one component in a complex product (which we label the focal component), an increase in the flow of design information to the focal component from other (non-focal) components simultaneously increases the constraint on focal component firms in their choice of profitable R&D projects while decreasing the constraint on non-focal component firms. Second, asymmetries in component dependencies can confer disproportionate influence on some component firms in setting and dictating the trajectory of progress in the overall system. Increases in such asymmetric influence allow component firms to expand their innovation output. Using historical patenting data in the personal computer ecosystem, we develop fine-grained measures of interdependence between component technologies and changes in them over time. We find strong support for the empirical implications of our theory.

The impact of technology on the health and well-being of workers has been a topic of interest since computers and computerized technology were widely introduced in the 1980s. Of recent concern is the impact of rapid technological advances on individuals’ psychological well-being, especially due to advancements in mobile technology that have increased many workers’ accessibility and expected productivity. In this chapter we focus on the associations between occupational stress and technology, especially behavioral and psychological reactions. We discuss some key facilitators and barriers associated with users’ acceptance of and engagement with information and communication technology. We conclude with recommendations for ongoing research on managing occupational health and well-being in conjunction with technological advancements.

While it is widely recognized that firms in an era of technological ferment exist under conditions of significant uncertainty and ambiguity, little is known about the exact processes through which firms explore their ideas and resolve uncertainty. Arguing that our understanding of the era of ferment is much less developed than other aspects of the technology life cycle, we examine the micro-dynamics of technology-based entrepreneurial firms during this period. We focus on the role of purposeful experimentation as a key form of learning for start-ups firms in the era of ferment. Our approach contrasts with the prevailing view in the literature in which the era of ferment is characterized by extensive experimentation across firms, with each firm representing a single data point in an industry-level experiment. It also extends the learning literature by focusing on start-ups and taking the perspective that learning can encompass purposeful experimentation as well as local search and chaotic adaptation in the era of ferment. Building on the literature on experimental design, we propose a definition and taxonomy of purposeful experimentation. The taxonomy defines the experimental landscape as having three domains – technological, product and business model; and two dimensions – degree of simultaneity and degree of parameter manipulation. We examine this framework using data from a technology-based start-up and find evidence for purposeful experimentation as a key element of the firm’s learning strategy. We also highlight the organizational constraints and challenges that are associated with experimentation. Our findings emphasize the importance of entrepreneurial action, choice and internal experimentation processes.

The following is an introductory profile of the fastest growing firms over the three-year period of the study listed by corporate reputation ranking order. The business activities in which the firms are engaged are outlined to provide background information for the reader.

We review the literature on individual acceptance of technology to show how organizations can improve the effective use of human resource web-based technologies. Integrating and expanding several theoretical models of technology acceptance, we develop a perceptual model of employee self-service (ESS) acceptance and usage. Based on this model, we propose several key individual, technological, and organizational factors relevant to individual intentions to use ESS technology. We summarize these in several testable propositions and also discuss implications for organizational researchers and practitioners.

E-learning programs exist in a wide variety of formats. Without a framework for distinguishing between different e-learning programs, it is a challenge for researchers to compare their effectiveness or identify characteristics of e-learning that contribute to learning effectiveness. Based on general theories of learning, we develop a typology that compares e-learning programs in terms of the nature of the learning interactions they provide for learners in three dimensions: degree of interaction, learner control of interactions, and informational value of interactions. The typology dimensions apply to learner–instructor, learner–learner, and learner–instructional material interactions. We also discuss important theoretical implications of the typology. First, we show the utility of the typology for comparing the effectiveness of different e-learning programs. Second, we apply the typology dimensions to develop a theoretical framework for e-learning research that provides a foundation for examining factors that influence learning effectiveness in an e-learning program. The framework identifies e-learning program characteristics, learner characteristics, and contextual factors that impact learning effectiveness in different e-learning environments. It also shows how the typology dimensions align with learning goals to influence learning effectiveness.

The changing technological landscape has brought about new forms of groups and grouping that span across computing and communication devices, space, time, institutions, cultures, realities (physical, virtual, and augmented), and intelligence (natural and artificial intelligence). This chapter utilizes a series of publication and keyword analyses to identify trends in group and technology research in the fields of communication, management, and computer-supported cooperative work (CSCW) between 2008 and 2019. The results reveal prominent research areas, and recent shifts and emergent questions in the study of groups and technology, highlighting a complex entanglement of technology with collaborative social practices. The chapter concludes with a discussion of novel key areas and trends suggested by the analyses, with the goal of contributing toward a research agenda for future study of groups and technology.