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University–industry collaborations are an important driver of innovation that highlights the benefits of collaborative processes across organizational boundaries. However, like in most collaborative processes, many challenges remain when trying to manage the process of knowledge sharing and interaction in university–industry partnerships. In this chapter, the authors specifically investigate how leadership as a managerial dimension facilitates collaboration within university–industry joint laboratories. The authors present an explorative and inductive case study of eight joint laboratories set up by Telecom Italia within five major Italian universities. The results show that the laboratory directors play a crucial role in providing a dynamic and socially active working environment, which is enabled through a process of sensemaking and sensegiving. The authors, moreover, find that this process plays a crucial role by shaping effective communication channels that facilitate knowledge sharing and transfer of information. The authors find that this process ultimately acts as a mediator between charismatic leadership on the individual level and distributed leadership on the collective level.

The recent emergence of Chinese digital platform firms, whose size rivals that of the US platform giants, has attracted much popular interest. Given the size and increasing technical sophistication of these firms, there has been increasing interest in whether they have developed sufficient capacities and resources to become global-class competitors for the reigning US platform giants. The authors assembled a database of all overseas operations of the Chinese platform firms. Nine of them have foreign operations, with Tencent and Alibaba being the most important offshore investors. The authors describe the globalization patterns of these firms and analyze the strengths and obstacles to their globalization. Their globalization has proceeded on a number of vectors: first, these firms, with a few exceptions, when they have global strategies, have largely invested in firms with useful technology or content. One common strategy has been to follow Chinese customers abroad. Second, Chinese firms have made equity investments in a number of foreign Internet firms. And yet, in nearly all foreign markets, Chinese websites and apps still trail the US firms in market share and salience. Finally, Chinese investments are concentrated in proximate countries. Chinese platform firms, while having some state-of-the-art technologies, have a far smaller foreign presence than their US competitors do. Finally, the authors consider the implications of their research for discussions of whether emerging nation multinational firms require new theories for explaining their globalization.

Purpose: Green computing is a way of using the computer resource in an eco-friendly while maintaining and decreasing the harmful environmental impact. Minimising toxic materials and reducing energy usage can also be used to recycle the product.

Need for the Study: The motivation of the study is to use green computing resources to decrease carbon emissions and their adverse effect on the environment.

Methodology: The study uses a qualitative method of collecting resources and data to address the opportunities, challenges, and future trends in green computing for Sustainable Future Technologies. The study focusses on multiple kinds of cloud computing services collected and executed into single remote servers. The service demand processor offers these services to the client per their needs. The simultaneous requests to access the cloud services, processing and expertly managing these requests by the processors are discussed and analysed.

Findings: The findings suggest that green computing is an upcoming and most promising area. The number of resources employed for green computing can be beneficial for lowering E-waste so that computing can be environmentally friendly and self-sustainable.

Practical Implications: Green computing applies across all industries and service sectors like healthcare, entertainment, tourism, and education. The convergence of technologies like Cloud Computing, AI, and Internet of Things (IoT) is greatly impacting Green Supply Chain Management (GSCM) market.

This chapter seeks to quantify the effects of geographic access to community health centers on the likelihood of an individual having a regular source of health care.

Utilizing survey and center location data, the analysis employs bivariate cross-tabulation with chi-square and multinominal logistic regression to quantify the relationship between variables.

While individuals living in close spatial proximity to community health centers were more likely to identify a community health center as a regular source of care as compared with those without proximal access, the effect of community health center access on the identification of any source of regular health care was generally insignificant or negative, except for populations with a chronic medical condition.

While these findings support current literature suggesting that spatial proximity to care is insufficient to transform at-risk populations into regular primary care users, it is important to note that it is possible that individuals prefer to access primary care services outside of their immediate neighborhoods, potentially mediating the observed effect of proximity to care on the likelihood of having a regular source of care. Also, because this analysis is based on cross-sectional survey data, it is impossible to make a causal argument about the relationship between variables. Only the observed association can be asserted and used to inform future studies.

Existing research supports a positive association between community health center utilization and measures of health for social groups traditionally facing barriers to care, but few studies isolate the effect of center availability and health, particularly when considering those living in the catchment area but are not regular users. Due to the complexity and prevalence of barriers to health care for vulnerable and at-risk populations, these findings suggest that improving geographic access to primary health care does not guarantee positive outcomes for target groups. The magnitude of social disadvantage on vulnerable and at-risk populations can have a devastating effect on health care outcomes that is not easily overcome by social programs.