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The purpose of this study is to estimate carbon mitigation impacts of project activities in a community forestry project in Andhra Pradesh, India. Measurement and quantification of carbon stocks, monitoring of these stocks over time and projections using models is necessary for assessing the climate change mitigation potential or impacts of all forest development and conservation projects.

In this study, multiple mitigation assessment methods and models were used to estimate the carbon mitigation impacts – PROCOMAP, TARAM and CATIE, by adopting a three-tier approach similar to Intergovernmental Panel on Climate Change (IPCC) Guidelines.

There are differences in mitigation potential estimates across models as well as across tiers. The study highlights the strength and weaknesses and/or limitations and advantages of adopting the different approaches and their applicability for estimating mitigation potential of a forestry project. The same could be adopted for a future Reducing Emissions from Deforestation and Forest Degradation (REDD) regime also, given countries may not have the necessary technical capacity and data needed during the post-2012 REDD scheme. While countries with advanced data, technical and research capabilities could use models or, in other words, adopt the Tier-3 approach, countries with data and technical limitations, as in India, could adopt a Tier-2 or Tier-1 approach to begin with.

The limitations and advantages of use of the multiple mitigation models is addressed.

This work would help understand use of three mitigation models by prospective students and researchers and also the data needs and limitations for use of these models.

The majority of the population in the Gulf Cooperation Council (GCC) lives in urban areas. In the year 2030, the percentage of the rural population is expected to be 14% in the Kingdom of Saudi Arabia, 11% in the United Arab Emirates, 10% in Oman, 9% in Bahrain, 1% in Qatar, and will remain 0% in Kuwait. Like many other countries, however, GCC countries continue to invest efforts and resources toward their national agendas aimed at sustainable development. In this context, smart villages are of special interest as, increasingly, they serve as the crossroads between urban living and rural life embracing history, culture, tradition, spiritual values, and human capital. The objective of this chapter is to explore actions taken toward the development of smart villages in the GCC countries, with a comparative overview on pertaining approaches and strategies; challenges related to the implementation of these actions are identified. It is demonstrated that despite GCCs’ tremendous efforts toward developing infrastructure in urban centers, more infrastructure investment is needed with regard to key issues related to developing remote areas – including their smart networks, digital facilities, and e-governance. It is also highlighted that more research is needed, especially on issues related to the transformation of villages into smart villages, including the need for holistic approaches, policies, and strategies toward smart villages.

Tropical wetland ecosystems are threatened by climate change but also play a key role in its mitigation and adaptation through management of land use and other drivers. Local-level assessments are needed to support evidence-based wetland management in the face of climate change. This study aims to examine the local communities’ knowledge and perception of climate change in Yala wetland, Kenya, and compare them with observed data on climate trends. Such comparisons are useful to inform context-specific climate change adaptation actions.

The study used a mixed methods approach that combined analysis of climate data with perceptions from the local community. Gridded data on temperature and rainfall for the period from 1981 to 2018 were compared with data on climate change perceptions from semi-structured questionnaires with 286 key informants and community members.

Majority of the respondents had observed changes in climate parameters – severe drought (88.5%), increased frequency of floods (86.0%) and irregular onset and termination of rains (90.9%) in the past 20 years. The perceptions corresponded with climate trends that showed a significant increasing trend in the short rains and the average maximum temperature, high incidence of very wet years and variability in onset and termination of rainfall between 1981 and 2018. Gender, age and education had little influence on knowledge and awareness of climate change, except for frequency of floods and self-reported understanding of climate change. The community perceived the wetland to be important for climate change adaptation, particularly the provision of resources such as grazing grounds during drought.

The study faced challenges of low sample size, use of gridded climate data and reproducibility in other contexts. The results of this study apply to local communities in a tropical wetland in Western Kenya, which has a bi-modal pattern of rainfall. The sample of the study was regional and may therefore not be representative of the whole of Kenya, which has diverse socioeconomic and ecological contexts. Potential problems have been identified with the use of gridded data (for example, regional biases in models), although their usefulness in data scarce contexts is well established. Moreover, the sample size has been found to be a less important factor in research of highly complex socio-ecological systems where there is an attempt to bridge natural and social sciences.

This study addresses the paucity of studies on climate change trends in papyrus wetlands of sub-Saharan Africa and the role of local knowledge and perceptions in influencing the management of such wetlands. Perceptions largely influence local stakeholders’ decisions, and a study that compares perceptions vs “reality” provides evidence for engagement with the stakeholders in managing these highly vulnerable ecosystems. The study showed that the local community’s perceptions corresponded with the climate record and that adaptation measures are already ongoing in the area.

This study presents a case for the understanding of community perceptions and knowledge of climate change in a tropical wetland under threat from climate change and land use change, to inform management under a changing climate.

The purpose of this study is to examine the role of ethnic similarity in the audit partner–client manager relationship and its impact on auditor selection and retention decisions.

The authors use name matching analysis to infer ethnicity of audit partners and client managers in the US nonprofit reporting environment. The authors examine the degree of ethnic similarity (co-ethnicity) between the two parties and model auditor selection and retention decisions as a function of co-ethnicity. The authors also model reporting attributes as a function of co-ethnicity.

The authors find that the ethnic similarity between the client manager and their external audit partner is a significant determinant of auditor-client alignment. Specifically, the authors find that clients are more likely to select and retain an audit partner who is ethnically similar to the client manager. The authors find that co-ethnicity is associated with a lowered propensity to issue a going concern opinion to a financially distressed client and an increased occurrence of underreporting of fundraising and administrative expenses.

Taken together, the evidence suggests that ethnic diversity (the opposite of co-ethnicity) in the auditor-client relationship is associated with higher audit quality. These findings are relevant to client managers, audit committees and public accounting firms as they make auditor selection and reporting decisions.

Prior studies have found that co-ethnicity influences the formation and future success of various business partnerships. The auditor-client relationship is a unique setting within the business environment where the two parties must balance their desire to maintain a close relationship with their need to maintain independence. The study is the first to examine the role of ethnicity in the auditor-client relationship.

The extant literature provides evidence that single CEOs are less risk-averse. Building on the theory of risk aversion, the authors argue that the risk aversion trait arising from CEO’s marital status partially explains capital allocation efficiency. The paper aims to examine the association between CEO marital status and capital allocation efficiency.

The primary sample includes 9,671 observations from 1,264 US firms. The authors apply multivariate regression and a series of endogeneity tests to examine the association between CEO marital status and capital allocation efficiency.

Single-CEO firms have higher capital allocation inefficiency than those with married CEOs. The findings continue to hold after a series of endogeneity tests such as propensity score matching, change analysis and instrumental variable regression analysis and are robust to alternative proxies for capital allocation inefficiency. The capital allocation inefficiency in single-CEO firms arises from overinvestment but not underinvestment, and corporate risk-taking channels the effect.

The study is limited to the effect of CEO marital status, not CEO marital quality.

The findings imply that besides information asymmetry and agency conflicts, CEO marital status should receive special attention for capital allocation efficiency. Also, marital status influences the CEOs’ commitment to the general good of society, affecting the potential conflict of interest with different stakeholders from inefficient capital allocation.

This study extends corporate finance literature on CEO marital status by providing novel evidence on the effect of single CEOs on capital allocation efficiency. The authors conclude that CEOs’ personality traits, such as marital status, matter in corporate policy choices.

This paper aims to provide a mathematical modeling and design of H-infinity controller for an autonomous vertical take-off and landing (VTOL) Quad Tiltrotor hybrid unmanned aerial vehicles (UAVs). The variation in the aerodynamics and model dynamics of these aerial vehicles due to its tilting rotors are the key issues and challenges, which attracts the attention of many researchers. They carry parametric uncertainties (such as non-linear friction force, backlash, etc.), which drives the designed controller based on the nominal model to instability or performance degradation. The controller needs to take these factors into consideration and still give good stability and performance. Hence, a robust H-infinity controller is proposed that can handle these uncertainties.

A unique VTOL Quad Tiltrotor hybrid UAV, which operates in three flight modes, is mathematically modeled using Newton–Euler equations of motion. The contribution of the model is its ability to combine high-speed level flight, VTOL and transition between these two phases. The transition involves the tilting of the proprotors from 90° to 0° and vice-versa in 15° intervals. A robust H-infinity control strategy is proposed, evaluated and analyzed through simulation to control the flight dynamics for different modes of operation.

The main contribution of this research is the mathematical modeling of three flight modes (vertical takeoff–forward, transition–cruise-back, transition-vertical landing) of operation by controlling the revolutions per minute and tilt angles, which are independent of each other. An autonomous flight control system using a robust H-infinity controller to stabilize the mode of transition is designed for the Quad Tiltrotor UAV in the presence of uncertainties, noise and disturbances using MATLAB/SIMULINK. This paper focused on improving the disturbance rejection properties of the proposed UAV by designing a robust H-infinity controller for position and orientation trajectory regulation in the presence of uncertainty. The simulation results show that the Tiltrotor achieves transition successfully with disturbances, noise and uncertainties being present.

A novel VTOL Quad Tiltrotor UAV mathematical model is developed with a special tilting rotor mechanism, which combines both aircraft and helicopter flight modes with the transition taking place in between phases using robust H-infinity controller for attitude, altitude and trajectory regulation in the presence of uncertainty.

We argue that uninformed subscribers to an initial public offering (IPO) of common stocks are exposed to greater ex ante risk of trading against informed traders in the secondary market because the advent of public trading conveys hitherto private information and thereby mitigates adverse selection. The going‐public firm underprices the new issue to compensate uninformed subscribers for this added secondary market adverse selection risk. We test this market liquidity‐based explanation by investigating the ex‐post consequences of ownership structure choice on the initial pricing and the secondary market liquidity of a sample of initial public offerings on the New York Stock Exchange (NYSE). Consistent with our argument, we find that initial underpricing varies directly with the ex post trading costs in the secondary market. Further, initial underpricing is related positively to the concentration of institutional shareholdings and negatively to the proportional equity ownership retained by the founding shareholders. Finally, the secondary market illiquidity of new issues is positively related to institutional ownership concentration and negatively to ownership retention and underwriter reputation. Thus, the evidence based on our NYSE sample supports the view that the entrepreneurs' choice of ownership structure affects both the initial pricing and the subsequent market liquidity of new issues.

The purpose of this paper is to give reviews on the platform modeling and design of a controller for autonomous vertical take-off and landing (VTOL) tilt rotor hybrid unmanned aerial vehicles (UAVs). Nowadays, UAVs have experienced remarkable progress and can be classified into two main types, i.e. fixed-wing UAVs and VTOL UAVs. The mathematical model of tilt rotor UAV is time variant, multivariable and non-linear in nature. Solving and understanding these plant models is very complex. Developing a control algorithm to improve the performance and stability of a UAV is a challenging task.

This paper gives a thorough description on modeling of VTOL tilt rotor UAV from first principle theory. The review of the design of both linear and non-linear control algorithms are explained in detail. The robust flight controller for the six degrees of freedom UAV has been designed using H-infinity optimization with loop shaping under external wind and aerodynamic disturbances.

This review will act as a basis for the future work on modeling and control of VTOL tilt rotor UAV by the researchers. The development of self-guided and fully autonomous UAVs would result in reducing the risk to human life. Civil applications include inspection of rescue teams, terrain, coasts, border patrol buildings, police and pipelines. The simulation results show that the controller achieves robust stability, good adaptability and robust performance.

The review articles on quadrotors/quadcopters, hybrid UAVs can be found in many literature, but there are comparatively a lesser amount of review articles on the detailed description of VTOL Tilt rotor UAV. In this paper modeling, platform design and control algorithms for the tilt rotor are presented. A robust H-infinity loop shaping controller in the presence of disturbances is designed for VTOL UAV.

The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.

This paper aims to empirically investigate the evidence of the transmission of monetary policy impulses to firm profitability via manufacturing firms’ short-term and long-term corporate financing decisions.

This study decomposes the receptiveness of firm profitability to monetary policy shock under circumstances of financial flexibility. Additionally, the study extends its scope to undertake a sector-wise analysis of manufacturing firms from 2008 to 2020. Generalized methods of moments (GMM) and quantile regression models are employed.

The profitability of firms in the chemical, food and machinery sector are positively impacted by short-term financing, whereas the metal sector is positively impacted. But during the tight monetary policy, short-term financing does not appear to be a significant parameter while explaining the firms’ profitability. Secondly, the profitability of firms in the consumer goods and metal sector is positively impacted by long-term financing. Therefore, debt financing of assets could be more appropriate to maximize profitability in these sectors.

Analyzing the transmission of monetary policy impulses to firm profitability by clustering firms with financial flexibility across six key manufacturing sectors makes the study unique.