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on Project, Program and Portfolio Management |
| By: | Spiros Bougheas; Pasquale Commendatore; Laura Gardini; Ingrid Kubin |
| Abstract: | We introduce a banking sector and heterogeneous agents in the Matsuyama et al. (2016) dynamic over-lapping generations neoclassical model with good and bad projects. The model captures the benefits and costs of an advanced banking system which can facilitate economic development when allocates resources to productive activities but can also hamper progress when invests in projects that do not contribute to capital formation. When the economy achieves higher stages of development it becomes prone to cycles. We show how the disparity of incomes across agents de-pends on changes in both the prices of the factors of production and the reallocation of agents across occupations. |
| Keywords: | banks, financial innovation, economic development, business cycles, income inequality |
| JEL: | E32 E44 G21 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10135&r=ppm |
| By: | Spiros Bougheas; Pasquale Commendatore; Laura Gardini; Ingrid Kubin |
| Abstract: | We introduce a banking sector and heterogeneous agents in the Matsuyama et al. (2016) dynamic over-lapping generations neoclassical model with good and bad projects. The model captures the benefits and costs of an advanced banking system which can facilitate economic development when allocates resources to productive activities but can also hamper progress when invests in projects that do not contribute to capital formation. When the economy achieves higher stages of development it becomes prone to cycles. We show how the disparity of incomes across agents depends on changes in both the prices of the factors of production and the reallocation of agents across occupations. |
| Keywords: | Banks, business cycles, Economic Development, Financial Innovation, Income Inequality |
| JEL: | E32 E44 G21 |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:nsr:niesrd:545&r=ppm |
| By: | Andrej Woerner; Sander Onderstal; Arthur Schram |
| Abstract: | For reward-based crowdfunding, we introduce the strategy-proof Generalized Moulin-Shenker mechanism (GMS) and compare its performance to the prevailing All-Or-Nothing mechanism (AON). Theoretically, GMS outperforms AON in equilibrium profit and funding success. We test these predictions experimentally, distinguishing between a sealed-bid and a dynamic version of GMS. We find that the dynamic GMS outperforms the sealed-bid GMS. It performs better than AON when the producer aims at maximizing funding success. For crowdfunding in practice, this implies that the current standard of financing projects could be improved upon by implementing a crowdfunding mechanism that is similar to the dynamic GMS. |
| Keywords: | crowdfunding, market design, strategy-proofness, laboratory experiment |
| JEL: | C92 D82 G29 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10081&r=ppm |
| By: | Nicoletta Berardi; Paul Seabright |
| Abstract: | This paper investigates an unexplored rationale for joint ownership of a production project. We model projects with autocorrelated productivity shocks as creating an option value of investing over time so that later investments benefit from the information revealed by the realization of earlier investments. However, internal and external interest groups may pressurize owners into paying out early revenues. Joint ownership provides a commitment mechanism against them, thereby enabling more efficient levels of investment. The Business Environment and Enterprises Performance survey data corroborate the model's prediction that organizations under interest group lobbying pressure are more likely to choose joint ownership. |
| Keywords: | Commitment Mechanism, Joint Ownership, Joint Venture, Lobbying, Interest Group |
| JEL: | D23 F21 G32 L14 L24 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:bfr:banfra:889&r=ppm |
| By: | Tauchert, Christoph |
| Abstract: | Artificial intelligence (AI) is fundamentally changing our society and economy. Companies are investing a great deal of money and time into building corresponding competences and developing prototypes with the aim of integrating AI into their products and services, as well as enriching and improving their internal business processes. This inevitably brings corporate and private users into contact with a new technology that functions fundamentally differently than traditional software. The possibility of using machine learning to generate precise models based on large amounts of data capable of recognizing patterns within that data holds great economic and social potential—for example, in task augmentation and automation, medical diagnostics, and the development of pharmaceutical drugs. At the same time, companies and users are facing new challenges that accompany the introduction of this technology. Businesses are struggling to manage and generate value from big data, and employees fear increasing automation. To better prepare society for the growing market penetration of AI-based information systems into everyday life, a deeper understanding of this technology in terms of organizational and individual use is needed. Motivated by the many new challenges and questions for theory and practice that arise from AI-based information systems, this dissertation addresses various research questions with regard to the use of such information systems from both user and organizational perspectives. A total of five studies were conducted and published: two from the perspective of organizations and three among users. The results of these studies contribute to the current state of research and provide a basis for future studies. In addition, the gained insights enable recommendations to be derived for companies wishing to integrate AI into their products, services, or business processes. The first research article (Research Paper A) investigated which factors and prerequisites influence the success of the introduction and adoption of AI. Using the technology–organization–environment framework, various factors in the categories of technology, organization, and environment were identified and validated through the analysis of expert interviews with managers experienced in the field of AI. The results show that factors related to data (especially availability and quality) and the management of AI projects (especially project management and use cases) have been added to the framework, but regulatory factors have also emerged, such as the uncertainty caused by the General Data Protection Regulation. The focus of Research Paper B is companies’ motivation to host data science competitions on online platforms and which factors influence their success. Extant research has shown that employees with new skills are needed to carry out AI projects and that many companies have problems recruiting such employees. Therefore, data science competitions could support the implementation of AI projects via crowdsourcing. The results of the study (expert interviews among data scientists) show that these competitions offer many advantages, such as exchanges and discussions with experienced data scientists and the use of state-of-the-art approaches. However, only a small part of the effort related to AI projects can be represented within the framework of such competitions. The studies in the other three research papers (Research Papers C, D, and E) examine AI-based information systems from a user perspective, with two studies examining user behavior and one focusing on the design of an AI-based IT artifact. Research Paper C analyses perceptions of AI-based advisory systems in terms of the advantages associated with their use. The results of the empirical study show that the greatest perceived benefit is the convenience such systems provide, as they are easy to access at any time and can immediately satisfy informational needs. Furthermore, this study examined the effectiveness of 11 different measures to increase trust in AI-based advisory systems. This showed a clear ranking of measures, with effectiveness decreasing from non-binding testing to providing additional information regarding how the system works to adding anthropomorphic features. The goal of Research Paper D was to investigate actual user behavior when interacting with AI-based advisory systems. Based on the theoretical foundations of task–technology fit and judge–advisor systems, an online experiment was conducted. The results show that, above all, perceived expertise and the ability to make efficient decisions through AI-based advisory systems influence whether users assess these systems as suitable for supporting certain tasks. In addition, the study provides initial indications that users might be more willing to follow the advice of AI-based systems than that of human advisors. Finally, Research Paper E designs and implements an IT artifact that uses machine learning techniques to support structured literature reviews. Following the approach of design science research, an artifact was iteratively developed that can automatically download research articles from various databases and analyze and group them according to their content using the word2vec algorithm, the latent Dirichlet allocation model, and agglomerative hierarchical cluster analysis. An evaluation of the artifact on a dataset of 308 publications shows that it can be a helpful tool to support literature reviews but that much manual effort is still required, especially with regard to the identification of common concepts in extant literature. |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:dar:wpaper:135700&r=ppm |
| By: | Zapata, Oscar |
| Abstract: | Energy transitions in Indigenous, Northern and remote communities in Canada promise benefits that go beyond reliable, clean and affordable energy services. The Federal and Provincial governments have committed funding to get remote communities off diesel, acknowledging energy transitions’ global and local benefits. Besides climate change mitigation, other benefits, including job creation, income generation, community ownership and local economic growth, are fundamental components of the value proposition of renewable energy projects. However, despite the promises, little evidence on the impacts of renewable energy on communities’ local conditions exists. This article looks at the relationship between renewable energy projects and community wellbeing in Canada. We construct a panel of Indigenous community wellbeing with Census data and information about renewable energy projects for the period 1981 – 2016, and find that renewable energy is associated with higher levels of wellbeing. Concretely, having access to renewable energy increases overall wellbeing by 1 to 5 points on the 0-100 wellbeing scale, depending on the component of the wellbeing index considered in the analysis. |
| Date: | 2022–11–22 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:tk59y&r=ppm |
| By: | Pollermann, Kim; Fynn, Lynn-Livia |
| Abstract: | Across the European Union, the so-called "Community-Led Local Development" (CLLD) is a well-established policy instrument. It began with LEADER in rural areas over 30 years ago and now comprises over 3000 Local Action Groups (LAGs) across the continent. LEADER is a place-based and participatory approach where a Local Action Group composed of stakeholders from local government, civil society and economy steers the implementation of its local development strategy. LAGs each have a budget at their disposal to support project implementation within the EU funding period (time for implementation is around five years). A set of LEADER principles describes the characteristics of LEADER: territorial approach, bottom-up, public-private partnerships, integrated and multi-sectoral approach, innovation, cooperation with other regions and networking. The aim of this contribution is to discuss different possibilities for policy design of LEADER implementation regarding different steering options. To examine the performance of LEADER, we utilise results from the 2014-2020 funding period, specifically data from 115 LAGs from four federal states in Germany. Main material was collected by three surveys using written questionnaires (mainly executed as online surveys: LAG member survey n=1999, LAG management survey n=114, survey of beneficiaries: n=1079). The results are related to single variables of LEADER implementation and their impact on the performance of LEADER. Due to complex relations of different aspects, we mainly elaborate findings on simplified output indicators. Regarding a suitable policy design, the results offer several insights: in the context of spatial delimitation, results show that a suitable region design/delimitation is not dependent on the population size of the various LEADER regions. To foster a higher share of innovative projects, it is adjuvant to establish a suitable staff capacity in LAG managements. This supports a policy recommendation to predefine minimum targets for staff capacity as a prior condition for funding the LAGs, as this shows be an important factor to support innovation and participation of local actors. |
| Keywords: | Community-Led Local Development (CLLD), LEADER, participation, rural development |
| JEL: | R58 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:esconf:267150&r=ppm |