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Maintaining cooperation and avoiding opportunism is essential for a healthy venture capitalist (VC) – entrepreneur relationship. Therefore, the purpose of this paper is to explore the role of control and trust for developing a cooperative VC-entrepreneur relationship in an agency environment in the Indian context.

The study adopts a multiple case study approach to investigate ten VC-entrepreneur dyads. It uses data collected from both primary and secondary sources. Content analysis was used as the data treatment technique.

The empirical evidence indicates that VC-entrepreneur relationships emerging in the early stages suffer from low agency risks and use more of relational mechanisms to curb opportunism and develop cooperation while relationships at an advanced stage suffer from higher agency risks and employ more of control mechanisms to address it.

The findings can be utilized to enhance cooperation in VC-entrepreneur relationship by identifying the appropriate context to apply relational or control mechanisms, which would eventually lead to better performance of the venture.

This distinction results in the development of a theoretical model which shows how the dual governance mechanisms of control and trust interact with one another to affect confidence in partner cooperation as an entrepreneurial venture raises multiple rounds of venture capital across various stages. The data collected from Indian VC-entrepreneur dyads offers a rich description of the relationship dynamics across the Indian entrepreneurial ecosystem.

This article aims to explore the importance of trust and reputation in new ventures that are raising venture capital.

The article is based on an interview with founding partners of an eminent Indian venture capital firm, conducted by an independent interviewer.

Venture capitalists are moving from a more formal approach for investing to a more relational one. Other than traditional methods of selecting and protecting their investments, the venture capitalists are resorting to trustworthiness of entrepreneurs and reputation as vital deterrence mechanisms.

The findings can be utilized to reduce contracting costs and develop a more efficient venture capitalist‐entrepreneur relationship.

The article proposes new criteria which the entrepreneurs should be aware of before trying to raise venture finance.

The objective of this article is to highlight the important role played by an entrepreneur’s network in the survival and performance of new ventures.

The article is based on a case study of a new venture, where data were collected from various stakeholders through interviews.

Entrepreneurs can overcome their liability of newness, enhance their competitiveness and increase their firm’s value by utilizing their networks. The case study demonstrated in the study is a good example of how an entrepreneur utilized his strong ties and weak ties to establish and enhance the performance of his venture.

The findings can be utilized by entrepreneurs worldwide to reduce the mortality rate of their venture and enhance their performance.

The article demonstrates, through a case study, a unique business model of an entrepreneurial venture that leverages the power of networks to achieve superior performance.

EDMC represents extended dynamic matrix control, which can be applied to nonlinear process control. In this method, control inputs are determined based on a linear model that approximates the process and is updated during each sampling interval. Since nonlinear relation still exists between the prediction error and the control input, numerical (iterative) methods are used to solve the optimization problem defined in the method. For nonlinear processes with high variation and/or sign changes in their steady‐state gain, iterative methods do not converge properly to an acceptable solution for some desired outputs or external disturbances. To eliminate the problem, we augment the process with its steady‐state gain inverse (or pseudo inverse whenever required) such that the steady‐state gain for the new augmented system is constant or contains slow variations. In the case of unstable processes, the method may be applied after stabilizing the process using a proper state or output feedback. Effectiveness of the method has been examined using computer simulations of some benchmark processes. Some of the obtained results are presented in this paper.

Global virtual teams (GVTs) – composed of members in two or more countries who work together primarily using information and communication technologies – are increasingly prevalent in organizations today. There has been a burgeoning of research on this relatively new organizational unit, spanning various academic disciplines. In this chapter, we review and discuss the major developments in this area of research. Based on our review, we identify areas in need of future research, suggest research directions that have the potential to enhance theory development, and provide practical guidelines on managing and working in GVTs.

The purpose of this study is to monitor suspended particulate matter (SPM), PM2.5 and source apportionment study for the identification of possible sources during the year 2018–2019 at Raipur, India.

Source apportionment study was performed using a multivariate receptor model, positive matrix factorization (PMFv5.0) with a view to identify the various possible sources of particulate matter in the area. Back-trajectory analysis was also performed using NOAA-HYSPLIT model to understand the origin and trans-boundary movement of air mass over the sampling location.

Daily average SPM and PM2.5 aerosols mass concentration was found to be 377.19 ± 157.24 µg/m³ and 126.39 ± 37.77 µg/m³ respectively. SPM and PM2.5 mass concentrations showed distinct seasonal cycle; SPM – (Winter ; 377.19 ±157.25 µg/m?) > (Summer; 283.57 ±93.18 µg/m?) > (Monsoon; 33.20 ±16.32 µg/m?) and PM2.5 – (Winter; 126.39±37.77 µg/m³) > (Summer; 75.92±12.28 µg/m³). Source apportionment model (PMF) have been applied and identified five major sources contributing the pollution; steel production and industry (68%), vehicular and re-suspended road dust (10.1%), heavy oil combustion (10.1%), tire wear and brake wear/abrasion (8%) and crustal/Earth crust (3.7%). Industrial activities have been identified as major contributing factor for air quality degradation in the region.

Chemical characterization of aerosols and identification of possible sources will be helpful in abatement of pollution and framing mitigating strategies. It will also help in standardization of global climate model.

The findings provide valuable results to be considered for controlling air pollution in the region.