Enabling Technologies and the Role of Private Firms: A Machine Learning Matching Analysis

2020 ◽  
Author(s):  
Jason M. Rathje ◽  
Riitta Katila
Keyword(s):  
Machine Learning ◽  
Public Sector ◽  
Technology Development ◽  
Private Firm ◽  
Private Firms ◽  
Strategic Decisions ◽  
Enabling Technology ◽  
Enabling Technologies ◽  
Technology Standard ◽  
Cooperative Agreements

Investments in enabling technologies—including the fifth-generation technology standard for broadband cellular networks (5G), artificial intelligence (AI), and light detection and ranging (LIDAR) technology—are important strategic decisions for firms. This paper asks how inventions that private firms developed with (versus without) public-sector partners differ in their enabling technology trajectory. Using a novel method of machine learning matching, we compare patented technologies generated from more than 30,000 public–private relationships with comparable technologies invented by private firms alone during a 21-year period. To measure the enabling potential of a technology, we introduce a new enabling technology index. The findings show that private-firm relationships with the public sector—in particular cooperative agreements and grants with mission agencies (National Aeronautics and Space Administration and Department of Defense)—are likely starting points for enabling technology trajectories. We thus put a spotlight on organizational arrangements that combine the breadth of exploration (agreements, grants) with deep exploitation in a particular domain (mission agency). A key contribution is a better understanding of the types of private-firm efforts that are associated with enabling technologies. We also challenge the common assumption that enabling technologies have their origins only in public-sector projects and show how private firms are involved. Our significant contribution is to show how private firms can change evolution of ecosystems through technology development.

scholarly journals Contribution of policy change on maize varietal development and yields in Kenya

2019 ◽  
Vol 9 (1) ◽  
pp. 4-21 ◽  
Author(s):  
Latha Nagarajan ◽  
Anwar Naseem ◽  
Carl Pray
Keyword(s):  
Public Sector ◽  
Intellectual Property ◽  
Policy Change ◽  
Private Firms ◽  
Content Type ◽  
Improved Varieties ◽  
The Public ◽  
Varietal Development ◽  
New Varieties ◽  
Maize Yields

Purpose Since the start of seed and other market reforms in the 1990s, the annual number of improved varietal releases for maize in Kenya has increased substantially. Prior to the reforms, private firms were restricted in introducing new varieties, could not protect their intellectual property and farmers had to rely exclusively on improved seeds developed and marketed by the public sector. Reforms have resulted in not only private firms entering the market and releasing improved varieties, but also an increase in varietal releases by the public sector. The purpose of this paper is to review some of the key policy reforms related to maize in Kenya, and their impacts on varietal development and yields. Design/methodology/approach The authors estimate a yield model that relates national maize yields to a number of input policy variables. The authors employ a two-stage least square regression, as one of the explanatory variables – the number of varietal releases – is likely endogenous with yield. The authors use policy variables such as public R&D, the number of plant breeder’s rights issued, and the years since private varieties have been introduced as instrument variables to estimate their influence new varietal releases directly, and then new varieties, inputs and other policies to measure their impact on yields. Findings The results show that policy changes such as the introduction of intellectual property rights had an important impact on the number of improved maize varieties released. However, the outcomes of the policy change such as the number of varieties and the share of area under improved varieties has no impact on increasing maize yields. The authors argue that this is because farmers continue to use older improved varieties because of the dominance of a parastatal in the maize, seed market and that newer improved varieties may not have the assumed yield advantage. Future policy and programs should be directed toward increasing the adoption of improved varieties rather than simply releasing them. Originality/value This paper provides evidence that while policy change may lead to new varietal development and release, its aggregate productivity impacts may be limited without additional reforms and intervention.

scholarly journals What Predicts Corruption?

2020 ◽  
Author(s):  
Emanuele Colonnelli ◽  
Jorge Gallego ◽  
Mounu Prem
Keyword(s):  
Machine Learning ◽  
Human Capital ◽  
Cost Effectiveness ◽  
Public Sector ◽  
Financial Development ◽  
Predictive Power ◽  
Public Spending ◽  
Learning Models ◽  
Micro Data ◽  
Machine Learning Models

The ability to predict corruption is crucial to policy. Using rich micro-data from Brazil, we show that multiple machine learning models display high levels of performance in predicting municipality-level corruption in public spending. We then quantify which individual municipality features and groups of similar characteristics have the highest predictive power. We find that measures of private sector activity, financial development, and human capital are the strongest predictors of corruption, while public sector and political features play a secondary role. Our findings have implications for the design and cost-effectiveness of various anti-corruption policies.

scholarly journals An Overview of LoRaWAN

2021 ◽  
Vol 19 ◽  
pp. 231-239
Author(s):  
Biswajit Paul
Keyword(s):  
System Architecture ◽  
Communication Protocol ◽  
Data Rate ◽  
Network Coverage ◽  
Enabling Technology ◽  
Long Distance ◽  
Ism Band ◽  
Enabling Technologies ◽  
Distance Communication

LoRa is an IoT enabling technology which is particularly suitable for low data rate applications. The technology can achieve extended network coverage while operating in unlicensed ISM band and falls into the category of Low­Power­Wide­Area­Networks (LPWANs) technologies. Among the non­cellular based LPWAN enabling technologies, LoRa has got remarkable attention due to its fast adoption by industries. LoRa through wireless modulation enables the end­nodes to establish long distance communication while LoRaWAN refers to the communication protocol and system architecture. In this paper, an overview of LoRaWAN is presented.

Zac Bercy Front du Parc: un lungo ed efficace processo di riqualificazione urbana

TERRITORIO ◽  
2009 ◽  
pp. 130-138
Author(s):  
Viviana di Martino
Keyword(s):  
Public Sector ◽  
Urban Planning ◽  
Urban Transformation ◽  
Strategic Decisions ◽  
The Public ◽  
Entire Process ◽  
Municipal Administration ◽  
History Of ◽  
The One

- An important urban transformation was achieved in Paris with the redevelopment of the Bercy quarter. It was characterised by farsightedness and an ability to monitor and manage on the part of the public sector operators who guided the entire operation. While on the one hand the Bercy case presents a series of ‘extraordinary' elements deriving from the particular history of the site, the continuity with which the municipal administration moved forward with its strategic decisions, its capacity to frame those strategies in a broader and more complex context and the ways in which the entire process was implemented certainly constitute important factors on which to reflect in the framework of a more general discussion on the effectiveness and potentials of large urban projects. This paper looks at the main stages of the transformation starting with the framing of the operation within the provisions of the main urban planning instruments and it seeks to highlight the most significant aspects of the intervention with a particular focus on the outcomes of the project implemented.

Private firm performance: do women directors matter?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahnoor Sattar ◽  
Pallab Kumar Biswas ◽  
Helen Roberts
Keyword(s):  
Firm Performance ◽  
Performance Measures ◽  
Small Firm ◽  
Gender Diversity ◽  
Private Firm ◽  
Private Firms ◽  
Women Directors ◽  
Content Type ◽  
Firm Profitability ◽  
Board Gender Diversity

Purpose This paper aims to examine the relationship between board gender diversity and private firm performance. Design/methodology/approach The authors test the association between board gender diversity and private firm performance by estimating pooled multivariate regressions using an unbalanced panel data set of 115,253 firm-year observations. Findings The authors find that younger, less busy and local women directors enhance private firm performance. Firms with 40% or more women directors report triple the economic benefits compared to boards with at least 20% women directors. Considering firm size, women directors significantly increase small firm profitability, and the effect is more pronounced for high-risk firms. Greater board gender diversity enhances small firm performance as the monitoring role of women directors benefits the firm even in the presence of busy men directors. Consistent with the agency theory framework, the authors find that women directors improve small firm profitability in the presence of agency costs. Research limitations/implications Due to the lack of availability of data about private firms, many factors are not directly observable. The analysis uses accounting-based performance measures that may be subject to managerial discretion. Nevertheless, the authors report highly significant results using cash-based performance measures that substantiate the overall findings. Practical implications The results of the present study point to the need for private firms to increase board gender diversity and consider women director busyness, age, nationality and firm size when making board director appointments. Originality/value This study adds to the scarce existent literature investigating private firms. The results contribute to the understanding of gender-diverse boards as well as the attributes of women directors that enhance private firm performance.

Big Data Models and the Public Sector

Web Services ◽  
2019 ◽  
pp. 105-126
Author(s):  
N. Nawin Sona
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Public Sector ◽  
Predictive Analytics ◽  
Data Types ◽  
The Public ◽  
Emerging Trends ◽  
Wide Range ◽  
Learning Data

This chapter aims to give an overview of the wide range of Big Data approaches and technologies today. The data features of Volume, Velocity, and Variety are examined against new database technologies. It explores the complexity of data types, methodologies of storage, access and computation, current and emerging trends of data analysis, and methods of extracting value from data. It aims to address the need for clarity regarding the future of RDBMS and the newer systems. And it highlights the methods in which Actionable Insights can be built into public sector domains, such as Machine Learning, Data Mining, Predictive Analytics and others.

3. Barriers to employment rights

2019 ◽  
pp. 46-82
Author(s):  
Stephen Taylor ◽  
Astra Emir
Keyword(s):  
Public Sector ◽  
Employment Law ◽  
Time Limit ◽  
Equal Protection ◽  
Private Firms ◽  
Continuous Service ◽  
Barriers To Employment ◽  
The Uk ◽  
Employment Rights

UK employment law does not give equal protection to everyone considered to be working for an employer. In fact, a substantial minority of people who work for private firms, companies and public sector organisations do not enjoy the protection of employment law in some significant respects. There are four types of situation that often deny people the opportunity to bring their claims to court: when a claimant is not considered to be an employee; when a claimant is not considered to be a worker; when a claimant (who is an employee) has not completed sufficient continuous service with their employer; and when a claimant is found not to be working legally in the UK. In addition, employment tribunals operate strict limits on how soon after someone is dismissed or suffers from an instance of unlawful discrimination they make a claim if they want it to be heard. For most tribunal jurisdictions this time limit is set at three months, meaning that after this period has passed a claim cannot be considered because it is ‘out of time’. In practice this rule can also act as a fifth type of barrier preventing people from accessing their employment rights. This chapter focuses on these five types of situations.

DataNaut Incorporated

2011 ◽  
pp. 94-106
Author(s):  
Nancy C. Shaw ◽  
Joan O’Reilly Fix
Keyword(s):  
Web Sites ◽  
Technology Development ◽  
New Technology ◽  
Business Case ◽  
Profit Sharing ◽  
High Tech ◽  
Strategic Decisions ◽  
American University ◽  
Capital Financing ◽  
Pro Forma

This case was written for the 8th annual Kogod School of Business Case Competition at American University. It discusses a small, locally run company that faced several strategic decisions at the end of 1999: marketing its new high-tech products, securing sufficient venture capital financing, and creating a profit-sharing plan for current and future employees. The case involves an actual corporation (although some of the employee names have been changed) and the issues that confronted the management team at the end of 1999. Thecae includes a complete description of the company’s products, a glossary of terms, a list of Web sites summarizing existing radio market research, detailed operating expenses and pro-forma financial statements (numbers have been altered for confidentiality). This case combines new technology development, HR decisions, marketing and finance, which makes it a true cross-disciplinary case that can be used in several different courses

Machine Learning-Based Design Concept Evaluation

2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Bradley Camburn ◽  
Yuejun He ◽  
Sujithra Raviselvam ◽  
Jianxi Luo ◽  
Kristin Wood
Keyword(s):  
Machine Learning ◽  
Technology Development ◽  
Empirical Evaluation ◽  
Learning Technologies ◽  
Design Concept ◽  
Third Party ◽  
Large Set ◽  
Design Concepts ◽  
Automated Method ◽  
Concept Evaluation

Abstract In order to develop novel solutions for complex systems and in increasingly competitive markets, it may be advantageous to generate large numbers of design concepts and then to identify the most novel and valuable ideas. However, it can be difficult to process, review, and assess thousands of design concepts. Based on this need, we develop and demonstrate an automated method for design concept assessment. In the method, machine learning technologies are first applied to extract ontological data from design concepts. Then, a filtering strategy and quantitative metrics are introduced that enable creativity rating based on the ontological data. This method is tested empirically. Design concepts are crowd-generated for a variety of actual industry design problems/opportunities. Over 4000 design concepts were generated by humans for assessment. Empirical evaluation assesses: (1) correspondence of the automated ratings with human creativity ratings; (2) whether concepts selected using the method are highly scored by another set of crowd raters; and finally (3) if high scoring designs have a positive correlation or relationship to industrial technology development. The method provides a possible avenue to rate design concepts deterministically. A highlight is that a subset of designs selected automatically out of a large set of candidates was scored higher than a subset selected by humans when evaluated by a set of third-party raters. The results hint at bias in human design concept selection and encourage further study in this topic.

scholarly journals Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence

2020 ◽  
Vol 3 (1) ◽  
pp. 61-87 ◽  
Author(s):  
Theodore Alexandrov
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Mass Spectrometry ◽  
Image Analysis ◽  
Imaging Mass Spectrometry ◽  
Rapid Evolution ◽  
Life Sciences ◽  
Imaging Data ◽  
Enabling Technology ◽  
Tissue Sections

Spatial metabolomics is an emerging field of omics research that has enabled localizing metabolites, lipids, and drugs in tissue sections, a feat considered impossible just two decades ago. Spatial metabolomics and its enabling technology—imaging mass spectrometry—generate big hyperspectral imaging data that have motivated the development of tailored computational methods at the intersection of computational metabolomics and image analysis. Experimental and computational developments have recently opened doors to applications of spatial metabolomics in life sciences and biomedicine. At the same time, these advances have coincided with a rapid evolution in machine learning, deep learning, and artificial intelligence, which are transforming our everyday life and promise to revolutionize biology and healthcare. Here, we introduce spatial metabolomics through the eyes of a computational scientist, review the outstanding challenges, provide a look into the future, and discuss opportunities granted by the ongoing convergence of human and artificial intelligence.

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