247 lines
8.4 KiB
YAML
247 lines
8.4 KiB
YAML
abstract: 'Background The adoption of improved technologies is generally associated
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with better economic performance and development. Despite its desirable
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effects, the process of technology adoption can be quite slow and market
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failures and other frictions may impede adoption. Interventions in
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market processes may be necessary to promote the adoption of beneficial
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technologies. This review systematically identifies and summarizes the
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evidence on the effects of interventions that shape the incentives of
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firms to adopt new technologies. Following Foster and Rosenzweig,
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technology is defined as ``the relationship between inputs and
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outputs,{''''} and technology adoption as ``the use of new mappings
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between input and outputs and the corresponding allocations of inputs
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that exploit the new mappings.{''''} The review focuses on studies that
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include direct evidence on technology adoption, broadly defined, as an
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outcome. The term intervention refers broadly to sources of exogenous
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variation that shape firms'' incentives to adopt new technologies,
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including public policies, interventions carried out by private
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institutions (such as NGOs), experimental manipulations implemented by
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academic researchers trying to understand technology adoption, and
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natural experiments. Objective The objective of this review is to answer
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the following research questions: To what extent do interventions affect
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technology adoption in firms? To what extent does technology adoption
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affect profits, employment, productivity, and yields? Are these effects
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heterogeneous across sectors, firm size, countries, workers'' skill
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level, or workers'' gender? 1.2.3. Selection Criteria To be included,
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papers had to meet the inclusion criteria described in detail in Section
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3.1 which is grouped into four categories: (1) Participants, (2)
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Interventions, (3) Methodology, and (4) Outcomes. Regarding
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participants, our focus was on firms, and we omitted studies at the
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country or region level. In terms of interventions, we included studies
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that analyzed a source of exogenous variation in incentives for firms to
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adopt new technologies and estimated their effects. Thus, we left out
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studies that only looked at correlates of technology adoption, without a
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credible strategy to establish causality, and only included studies that
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used experimental or quasi-experimental methods. Regarding outcomes,
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papers were included only if they estimated effects of interventions
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(broadly defined) on technology adoption, although we also considered
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other firm outcomes as secondary outcomes in studies that reported them.
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Search Methods The first step in selecting the studies to be included in
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the systematic review was to identify a set of candidate papers. This
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set included both published and unpublished studies. To look for
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candidate papers, we implemented an electronic search and, in a
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subsequent step, a manual search. The electronic search involved running
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a keyword search on the most commonly used databases for published and
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unpublished academic studies in the broad topic area. The words and
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their Boolean combinations were carefully chosen (more details in
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Section 3.2). The selected papers were initially screened on title and
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abstract. If papers passed this screen, they were screened on full text.
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Those studies that met the stated criteria were then selected for
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analysis. The manual search component involved asking for references
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from experts and searching references cited by papers selected through
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the electronic search. These additional papers were screened based on
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title and abstract and the remaining were screened on full text.
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If they met the criteria they were added to the list of selected
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studies. Data Collection and Analysis For the selected studies, the
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relevant estimates of effects and their associated standard errors (SEs)
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were entered into an Excel spreadsheet along with other related
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information such as sample size, variable type, and duration for flow
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variables. Other information such as authors, year of publication, and
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country and/or region where the study was implemented was also included
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in the spreadsheet. Once the data were entered for each of the selected
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studies, the information on sample size, effect size and SE of the
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effect size was used to compute the standardized effect size for each
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study to make the results comparable across studies. For those studies
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for which relevant data were not reported, we contacted the authors by
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email and incorporated the information they provided. Forest plots were
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then generated and within-study pooled average treatment effects were
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computed by outcome variable. In addition, an assessment of reporting on
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potential biases was conducted including (1) reporting on key aspects of
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selection bias and confounding, (2) reporting on spillovers of
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interventions to comparison groups, (3) reporting of SEs, and (4)
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reporting on Hawthorne effects and the collection of retrospective data.
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Results The electronic and manual searches resulted in 42,462 candidate
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papers. Of these, 80 studies were ultimately selected for the review
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after screenings to apply the selection criteria. Relevant data were
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extracted for analysis from these 80 studies. Overall, 1108 regression
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coefficients across various interventions and outcomes were included in
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the analysis, representing a total of 4,762,755 firms. Even though the
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search methods included both high-income and developing countries, only
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1 of the 80 studies included in the analysis was in a high-income
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country, while the remaining 79 were in developing countries. We discuss
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the results in two parts, looking at firms in manufacturing and services
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separately from firms (i.e., farms) in agriculture. In each case, we
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consider both technology adoption and other firm outcomes. Authors''
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Conclusions Overall, our results suggest that some interventions led to
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positive impacts on technology adoption among firms across
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manufacturing, services, and agriculture sectors, but given the wide
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variation in the time periods, contexts, and study methodologies, the
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results are hard to generalize. The effects of these interventions on
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other firm performance measures such as farm yields, firm profits,
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productivity, and employment were mixed. Policy-makers must be careful
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in interpreting these results as a given intervention may not work
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equally well across contexts and may need to be adjusted to each
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specific regional context. There is great need for more research on the
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barriers to technology adoption by firms in developing countries and
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interventions that may help alleviate these obstacles. One major
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implication for researchers from our review is that there is a need to
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carefully measure technology adoption.'
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affiliation: 'Goicoechea, A (Corresponding Author), World Bank Grp, 1818 H St NW,
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Washington, DC 20433 USA.
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Alfaro-Serrano, David, Cornerstone Res, New York, NY USA.
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Balantrapu, Tanay; Goicoechea, Ana, World Bank Grp, 1818 H St NW, Washington, DC
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20433 USA.
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Chaurey, Ritam, Johns Hopkins Univ, SAIS, Washington, DC USA.
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Verhoogen, Eric, Columbia Univ, Dept Econ, New York, NY 10027 USA.
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Verhoogen, Eric, Columbia Univ, Sch Int \& Publ Affairs, New York, NY USA.'
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article-number: e1181
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author: Alfaro-Serrano, David and Balantrapu, Tanay and Chaurey, Ritam and Goicoechea,
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Ana and Verhoogen, Eric
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author-email: agoicoechea@worldbank.org
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author_list:
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- family: Alfaro-Serrano
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given: David
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- family: Balantrapu
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given: Tanay
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- family: Chaurey
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given: Ritam
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- family: Goicoechea
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given: Ana
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- family: Verhoogen
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given: Eric
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da: '2023-09-28'
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doi: 10.1002/cl2.1181
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eissn: 1891-1803
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files: []
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journal: CAMPBELL SYSTEMATIC REVIEWS
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keywords-plus: 'SUB-SAHARAN AFRICA; FEMALE ENTREPRENEURSHIP; TECHNICAL CHANGE; IMPACT;
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BUSINESS; FARMERS; PRODUCTIVITY; INFORMATION; SELECTION; MARKETS'
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language: English
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month: DEC
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number: '4'
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number-of-cited-references: '111'
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papis_id: 783c3aef691a2efcb8c11261b0b3baf2
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ref: Alfaroserrano2021interventionspromote
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researcherid-numbers: Pereira, Fernanda/AID-4926-2022
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tags:
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- review
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times-cited: '0'
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title: 'Interventions to promote technology adoption in firms: A systematic review'
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type: article
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unique-id: WOS:000731087200003
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usage-count-last-180-days: '2'
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usage-count-since-2013: '6'
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volume: '17'
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web-of-science-categories: Social Sciences, Interdisciplinary
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year: '2021'
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