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Keynes’ Grandchildren and Easterlin’s Paradox. What Is Keeping Us from Reducing Our Working Hours?
(2019)
In 1930 Keynes famously predicted that 100 years later-i.e. in 2030-the “economic problem” would be solved and we would be living in an “age of leisure and of abundance” working only 3 h a day. In the same text, Keynes stated that there are absolute and relative needs (“in the sense that we feel them only if their satisfaction lifts us above, makes us feel superior to, our fellows”), but he thought that relative needs are of minor importance. Richard Easterlin’s work, on the other hand, suggests that relative needs are pervasive and that wellbeing depends much more on one’s relative income than Keynes once thought.
It will be argued in this text that Richard Easterlin’s findings, in spite of proving Keynes off the mark in his understatement of relative needs, strengthens the case for working time reductions: the larger the proportion of goods subject to the relative-income effect, the greater are the benefits of working fewer hours. Perhaps the main explanation for why we are still sticking to the 40-h work-week is that the Easterlin paradox has not been widely understood yet.
Thirty years ago, the Fourth King of Bhutan famously proclaimed that ―Gross National Happiness is more important than Gross National Product, thereby setting Bhutan on a holistic development path. Following this historic declaration, Bhutan developed a Gross National Happiness (GNH) Index and screening tool to evaluate all new policies, proclaiming that:
―Gross National Happiness measures the quality of a country in more holistic way [than GNP] and believes that the beneficial development of human society takes place when material and spiritual development occur side by side to complement and reinforce each other.
In July 2011, 68 nations joined Bhutan in co-sponsoring its UN General Assembly resolution on ―Happiness: Towards a Holistic Approach to Development.
Despite decades of empirical happiness research, there is still little evidence for the positive effect of economic growth on life satisfaction. This poses a major challenge to welfare economic theory and to normative conceptions of socio-economic development. This book endeavours to explain these findings and to make sense of their ethical implications.
While most of the existing literature on empirical happiness research is ultimately interested in understanding how to improve human lives and societal development, the ethical backdrop against which these findings are evaluated is rarely made explicit. In contrast to this, Professor Hirata focuses on the role happiness should play in an ethically founded conception of good development. Taking a development ethics perspective, this book proposes a nuanced conception of happiness that includes both its affective and its normative dimensions and embeds this in a comprehensive conception of good development.
The argument is that happiness should not be regarded as the only thing that determines a good life and that good development cannot sensibly be thought of as a matter of maximizing happiness. Happiness should rather be seen as an important indicator for the presence or absence of those concerns that really matter to people: the reasons that give rise to happiness. This book should be of interest to students and researchers of economics, psychology and development studies.
With the increasing size and complexity of embedded systems, the impact of software on energy consumption is becoming more important. Previous research focused mainly on energy optimization at the hardware level. However, little research has been carried out regarding energy optimization at the software design level. This paper focuses on the software design level and addresses the gap between software and hardware design for embedded systems. This is achieved by proposing a framework for software design patterns, which takes aspects of power consumption and time behavior of the hardware level into account. We evaluate the expressiveness of the framework by applying it to well-known and novel design patterns. Furthermore, we introduce a dimensionless numerical efficiency factor to make possible energy savings quantifiable.
Current challenges are a result of complex and multi-layered factors. They require systemic solutions: problems must be solved holistically by identifying interconnections between the different problems which are results of the same root cause. Social entrepreneurs are agents of change, their mission is to generate societal impact. I investigated how a social entrepreneurship think tank can be conceptualized to support systems change. Think tanks can conduct in-depth research to inform about the systems and share knowledge. Entrepreneurs can make strategic interventions based on the research findings. To create a framework of how social entrepreneurship think tanks can promote systems change I conducted 14 case studies. The framework is created based on the method of Theory of Change, it displays how different activities can contribute to succeeding in systems change. I outline eleven activities which include strategies in capacity building, research and collaboration with the other actors in the field. In the end, the framework is applied to the evolving case of a think tank founded in 2018.
The objective of this review is a global assessment of the economics of second‐generation biorefineries, with a focus on the use of food waste and agricultural residues for chemical production by applying biotechnological processes. Analyses are conducted on feedstock and product distribution, applied economic models, and profitability figures for the period 2013–2018. In a study of 163 articles on different biorefinery systems, the production of chemicals is identified as the second major product class, after bioenergy. Bagasse and straw are frequently analyzed second‐generation feedstocks. Based on the evaluation of 22 articles, second‐generation biorefineries producing chemicals by applying biotechnological processes proves to be economically feasible. On average, both the internal rate of return (IRR) and the return on investment (ROI) are 20% and the payback period (PP) is 6 years. The cost share of feedstock in biorefineries is between 0–50%. The price of the end product and the fermentation yields have the most impact on profitability. The processing of food waste that has industrial and municipal origins appears more economical than the processing of agricultural residues. Scientists, policy makers and entrepreneurs with an appropriate risk tolerance are advised to pay particular attention to municipal food waste and the potential economic production of carboxylic acids. For various economic issues related to biorefineries, dynamic‐deterministic models are recommended, which can be extended by a stochastic model. This review provides an initial overview of the economic feasibility of second‐generation biorefineries. Further techno‐economic analyses are required to produce statistically significant statements on key profitability figures. © 2020 The Authors. Biofuels, Bioproducts, and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.
Process modeling languages help to define and execute processes and workflows. The Business Process Model and Notation (BPMN) 2.0 is used for business processes in commercial areas such as banks, shops, production and supply industry. Due to its flexible notation, BPMN is increasingly being used in non-traditional business process domains like Internet of Things (IoT) and agriculture. However, BPMN does not fit well to scenarios taking place in environments featuring limited, delayed, intermittent or broken connectivity. Communication just exists for BPMN - characteristics of message transfers, their priorities and connectivity parameters are not part of the model. No backup mechanism for communication issues exists, resulting in error-prone and failing processes. This paper introduces resilient BPMN (rBPMN), a valid BPMN extension for process modeling in unreliable communication environments. The meta model addition of opportunistic message flows with Quality of Service (QoS) parameters and connectivity characteristics allows to verify and enhance process robustness at design time. Modeling of explicit or implicit, decision-based alternatives ensures optimal process operation even when connectivity issues occur. In case of no connectivity, locally moved functionality guarantees stable process operation. Evaluation using an agricultural slurry application showed significant robustness enhancements and prevented process failures due to communication issues.
This paper describes the development and test of a novel LiDAR based combine harvester steering system using a harvest scenario and sensor point cloud simulation together with an established simulation toolchain for embedded software development. For a realistic sensor behavior simulation, considering the harvesting environment and the sensor mounting position, a phenomenological approach was chosen to build a multilayer LiDAR model at system level in Gazebo and ROS. A software-in-the-loop simulation of the mechatronic steering system was assembled by interfacing the commercial AppBase framework for point cloud processing and feature detection algorithms together with a machine model and control functions implemented in MATLAB/ Simulink. A test of ECUs in a hardware-in-the-loop simulation and as well as HMI elements in a driver-in-the-loop simulation was achieved by using CAN hardware interfaces and a CANoe based restbus simulation.
This article proposes the concept of a simulation framework for environmental sensors with multilevel abstraction in agricultural scenarios. The implementation case study is a simulation of a grain-harvesting scenario enabled by LiDAR sensors. Environmental sensor models as well as kinematics and dynamic behavior of machines are based on the robotics simulator Gazebo. Models for powertrain, machine process aggregates and peripheral simulation components are implemented with the help of MATLAB/ Simulink and with the robotics middleware Robot Operating System (ROS). This article deals with the general concept of a multilevel simulation framework and in particular with sensor and environmental modeling.
This paper presents an optimized algorithm for estimating static and dynamic gait parameters. We use a marker- and contact-less motion capture system that identifies 20 joints of a person walking along a corridor.
Based on the proposed gait cycle detection basic metrics as walking frequency, step/stride length, and support phases are estimated automatically. Applying a rigid body model, we are capable to calculate static and dynamic gait stability metrics. We conclude with initial results of a clinical study evaluating orthopaedic technical support.