Grassroots Design Meets Grassroots Innovation: Rural Design Orientation and Firm Performance
March 2024
Working Paper Number:
CES-24-17
Abstract
The study of grassroots design'applying structured, creative processes to the usability or aesthetics of a product without input from professional design consultancies'remains under investigated. If design comprises a mediation between people and technology whereby technologies are made more accessible or more likely to delight, then the process by which new grassroots inventions are transformed into innovations valued in markets cannot be fully understood. This paper uses U.S. data on the design orientation of respondents in the 2014 Rural Establishment Innovation Survey linked to longitudinal data on the same firms to examine the association between design, innovation, and employment and payroll growth. Findings from the research will inform questions to be investigated in the recently collected 2022 Annual Business Survey (ABS) that for the first time contains a Design module.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
analysis,
survey,
technology,
technological,
invention,
research,
innovation,
innovator,
development,
patent,
rural,
developed,
marketing,
innovative
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
National Science Foundation,
Center for Economic Studies,
Organization for Economic Cooperation and Development,
Longitudinal Business Database,
Department of Energy,
Department of Agriculture,
Regional Economic Information System,
Patent and Trademark Office,
Cornell Institute for Social and Economic Research,
Disclosure Review Board,
Federal Statistical Research Data Center,
National Center for Science and Engineering Statistics
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'Grassroots Design Meets Grassroots Innovation: Rural Design Orientation and Firm Performance' are listed below in order of similarity.
-
Working PaperAn Examination of the Informational Value of Self-Reported Innovation Questions
October 2022
Working Paper Number:
CES-22-46
Self-reported innovation measures provide an alternative means for examining the economic performance of firms or regions. While European researchers have been exploiting the data from the Community Innovation Survey for over two decades, uptake of US innovation data has been much slower. This paper uses a restricted innovation survey designed to differentiate incremental innovators from more far-ranging innovators and compares it to responses in the Annual Survey of Entrepreneurs (ASE) and the Business R&D and Innovation Survey (BRDIS) to examine the informational value of these positive innovation measures. The analysis begins by examining the association between the incremental innovation measure in the Rural Establishment Innovation Survey (REIS) and a measure of the inter-industry buying and selling complexity. A parallel analysis using BRDIS and ASE reveals such an association may vary among surveys, providing additional insight on the informational value of various innovation profiles available in self-reported innovation surveys.View Full Paper PDF
-
Working PaperThe Need to Account for Complex Sampling Features when Analyzing Establishment Survey Data: An Illustration using the 2013 Business Research and Development and Innovation Survey (BRDIS)
January 2017
Working Paper Number:
CES-17-62
The importance of correctly accounting for complex sampling features when generating finite population inferences based on complex sample survey data sets has now been clearly established in a variety of fields, including those in both statistical and non statistical domains. Unfortunately, recent studies of analytic error have suggested that many secondary analysts of survey data do not ultimately account for these sampling features when analyzing their data, for a variety of possible reasons (e.g., poor documentation, or a data producer may not provide the information in a publicuse data set). The research in this area has focused exclusively on analyses of household survey data, and individual respondents. No research to date has considered how analysts are approaching the data collected in establishment surveys, and whether published articles advancing science based on analyses of establishment behaviors and outcomes are correctly accounting for complex sampling features. This article presents alternative analyses of real data from the 2013 Business Research and Development and Innovation Survey (BRDIS), and shows that a failure to account for the complex design features of the sample underlying these data can lead to substantial differences in inferences about the target population of establishments for the BRDIS.View Full Paper PDF
-
Working PaperRegistered Report: Exploratory Analysis of Ownership Diversity and Innovation in the Annual Business Survey
March 2023
Working Paper Number:
CES-23-11
A lack of transparency in specification testing is a major contributor to the replicability crisis that has eroded the credibility of findings for informing policy. How diversity is associated with outcomes of interest is particularly susceptible to the production of nonreplicable findings given the very large number of alternative measures applied to several policy relevant attributes such as race, ethnicity, gender, or foreign-born status. The very large number of alternative measures substantially increases the probability of false discovery where nominally significant parameter estimates'selected through numerous though unreported specification tests'may not be representative of true associations in the population. The purpose of this registered report is to: 1) select a single measure of ownership diversity that satisfies explicit, requisite axioms; 2) split the Annual Business Survey (ABS) into an exploratory sample (35%) used in this analysis and a confirmatory sample (65%) that will be accessed only after the publication of this report; 3) regress self-reported new-to-market innovation on the diversity measure along with industry and firm-size controls; 4) pass through those variables meeting precision and magnitude criteria for hypothesis testing using the confirmatory sample; and 5) document the full set of hypotheses to be tested in the final analysis along with a discussion of the false discovery and family-wise error rate corrections to be applied. The discussion concludes with the added value of implementing split sample designs within the Federal Statistical Research Data Center system where access to data is strictly controlled.View Full Paper PDF
-
Working PaperINNOVATION OUTPUT CHOICES AND CHARACTERISTICS OF FIRMS IN THE U.S.
October 2014
Working Paper Number:
CES-14-42
This paper uses new business micro data from the Business Research and Development and Innovation Survey (BRDIS) for the years 2008-2011 to relate the discrete innovation choices made by U.S. companies to features of the company that have long been considered to be important correlates of innovation. We use multinomial logit to model those choices. Bloch and Lopez-Bassols (2009) used the Community Innovation Surveys (CIS) to classify companies according dual, technological or output-based innovation constructs. We found that for each of those constructs of innovation combinations considered, manufacturing and engaging in intellectual property transfer increase the odds of choosing innovation strategies that involve more than one type of categories (for example, both goods and services, or both tech and non-tech) and radical innovations, controlling form size, productivity, time and type of R&D. Company size and company productivity as well as time do not lean the choices in any particular direction. These associations are robust across the three multinomial choice models that we have considered. In contrast with other studies, we have been able to use companies that do and companies that do not innovate, and this has allowed to rule out to some extent selectivity bias.View Full Paper PDF
-
Working PaperA Portrait of U.S. Factoryless Goods Producers
October 2018
Working Paper Number:
CES-18-43
This paper evaluates the U.S. Census Bureau's most recent data collection efforts to classify business entities that engage in an extreme form of production fragmentation called 'factoryless' goods production. 'Factoryless' goods-producing entities outsource physical transformation activities while retaining ownership of the intellectual property and control of sales to customers. Responses to a special inquiry on the incidence of purchases of contract manufacturing services in combination with data on production inputs and outputs, intellectual property, and international trade is used to identify and document characteristics of 'factoryless' firms in the U.S. economy.View Full Paper PDF
-
Working PaperInvestigating the Effect of Innovation Activities of Firms on Innovation Performance: Does Firm Size Matter?
January 2025
Working Paper Number:
CES-25-04
Understanding the relationship between a firm's innovation activities and its performance has been of great interest to management scholars. While the literature on innovation activities is vast, there is a dearth of studies investigating the effect of key innovation activities of the firm on innovation outcomes in a single study, and whether their effects are dependent on the nature of firms, specifically firm size. Drawing from a longitudinal dataset from the Business Research & Development and Innovation Survey (BRDIS), and informed by contingency theory and resource orchestration theory, we examine the relationship between a firm's innovation activities - including its Research & Development (R&D) investment, securing patents, collaborative R&D, R&D toward new business areas, and grants for R&D - and its product innovation and process innovation. We also investigate whether these relationships are contingent on firm size. Consistent with contingency theory, we find a significant difference between large firms and small firms regarding how they enhance product innovation and process innovation. Large firms can improve product innovation by securing patents through applications and issuances, coupled with active participation in collaborative R&D efforts. Conversely, smaller firms concentrate their efforts on the number of patents applied for, directing R&D efforts toward new business areas, and often leveraging grants for R&D efforts. To achieve process innovation, a similar dichotomy emerges. Larger firms demonstrate a commitment to securing patents, engage in R&D efforts tailored to new business areas, and actively collaborate with external entities on R&D efforts. In contrast, smaller firms primarily focus on securing patents and channel their R&D efforts toward new business pursuits. This nuanced exploration highlights the varied strategies employed by large and small firms in navigating the intricate landscape of both product and process innovation. The results shed light on specific innovation activities as antecedents of innovation outcomes and demonstrate how the effectiveness of such assets is contingent upon firm size.View Full Paper PDF
-
Working PaperExploratory Report: Annual Business Survey Ownership Diversity and Its Association with Patenting and Venture Capital Success
October 2024
Working Paper Number:
CES-24-62
The Annual Business Survey (ABS) as the replacement for the Survey of Business Owners (SBO) serves as the principal data source for investigating business ownership of minorities, women, and immigrants. As a combination of SBO, the innovation questions formerly collected in the Business R&D and Innovation Survey (BRDIS), and an R&D module for microbusinesses with fewer than 10 employees, ABS opens new research opportunities investigating how ownership demographics are associated with innovation. One critical issue that ABS is uniquely able to investigate is the role that diversity among ownership teams plays in facilitating innovation or intermediate innovation outcomes in R&D-performing microbusinesses. Earlier research using ABS identified both demographic and disciplinary diversity as strong correlates to new-to-market innovation. This research investigates the extent to which the various forms of diversity also impact tangible innovation related intermediate outcomes such as the awarding of patents or securing venture capital financing for R&D. The other major difference with the earlier work is the focus on R&D-performing microbusinesses that are an essential input to radical innovation through the division of innovative labor. Evidence that disciplinary and/or demographic diversity affect the likelihood of receiving a patent or securing venture capital financing by small, high-tech start-ups may have implications for higher education, affirmative action, and immigration policy.View Full Paper PDF
-
Working PaperBusiness Dynamic Statistics of Innovative Firms
January 2017
Working Paper Number:
CES-17-72
A key driver of economic growth is the reallocation of resources from low to high productivity activities. Innovation plays an important role in this regard by introducing new products, services, and business methods that ultimately lead to increased productivity and rising living standards. Traditional measures of innovation, particularly those based on aggregate inputs, are increasingly unable to capture the breadth and depth of innovation in modern economies. In this paper, we describe an effort at the US Census Bureau, the Business Dynamics Statistics of Innovative Firms (BDS-IF) project, which aims to address these challenges by extending the Business Dynamics Statistics data to include new measures of innovative activity. The BDS-IF project will produce measures of firm, establishment, and employment flows by firm age, firm size, and industry for the subset of firms engaged in activities related to innovation. These activities include patenting and trademarking, the employment of STEM workers, and R&D expenditures. The exibility of the underlying data infrastructure allows this measurement agenda to be extended to include copyright activity, management practices, and high growth firms.View Full Paper PDF
-
Working PaperMeasuring U.S. Innovative Activity
March 2007
Working Paper Number:
CES-07-11
Innovation has long been credited as a leading source of economic strength and vitality in the United States because it leads to new goods and services and increases productivity, leading to better living standards. Better measures of innovative activities'activities including but not limited to innovation alone'could improve what we know about the sources of productivity and economic growth. The U.S. Census Bureau either currently collects, or has collected, data on some measures of innovative activities, such as the diffusion of innovations and technologies, human and organizational capital, entrepreneurship and other worker and firm characteristics, and the entry and exit of businesses, that research shows affect productivity and other measures of economic performance. But developing an understanding of how those effects work requires more than just measures of innovative activity. It also requires solid statistical information about core measures of the economy: that is, comprehensive coverage of all industries, including improved measures of output and sales and additional information on inputs and purchased materials at the micro (enterprise) level for the same economic unit over time (so the effects can be measured). Filling gaps in core data would allow us to rule out the possibility that a measure of innovative activity merely proxies for something that is omitted from or measured poorly in the core data, provide more information about innovative activities, and strengthen our ability to evaluate the performance of the entire economy. These gaps can be filled by better integrating existing data and by more structured collections of new data.View Full Paper PDF
