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Record W3183862084 · doi:10.29173/aar116

Analysis of the Boiler and Heat Exchanger Manufacturing Industry in the US Using Porter's Five Forces Framework

2021· article· en· W3183862084 on OpenAlexaffvenue
Jerry Chik

Bibliographic record

VenueAlberta Academic Review · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Development and Digital Transformation
Canadian institutionsNorthwestern Polytechnic
Fundersnot available
KeywordsProfitability indexIndustrial organizationBusinessCompetition (biology)GlobalizationBarriers to entryCommerceMarket structureEconomicsMarket economyFinance

Abstract

fetched live from OpenAlex

As global trade expands and technological progress is being made in developing countries, manufacturers of boilers and heat exchangers in the United States (US) are facing increasing import competition while industry profitability is competed away from industry rivals, market entrants, as well as by the growing number of available choices for buyers, and by suppliers with larger clientele and differentiated products and services. The forces that influence profitability in this industry is an essential part of strategic planning for any boiler and heat exchanger manufacturer that aims to control competition risk and optimize profitability. This research aims to break down and analyze the influences that industry manufacturers, market entrants, purchasers, component and raw material suppliers, foreign imports, technological advances, government policies, industry organizations, and future trends have on the profitability of industry players. While it was found that the level of competition in the industry is moderate, rapid advances in technology, increasingly stringent government policies on emission standards and boiler and heat exchanger efficiencies, as well as growing import competition may catalyze industry competition in the near future. The use of Porter’s five forces in this analysis suggests the need to consider the significance of technology and the challenges posed by imports through increasing globalization, as these factors could substantially change and disrupt the industry by reducing barriers to entry and by raising the threat of substitutes. As a result, the boiler and heat exchanger manufacturing landscape in the US could become much more competitive, which in turn, could diminish returns for industry operators. This could also change the structure of the industry with the inception of industry players that offer differentiated products and services. The question for industry groups and policy-makers is to what extent should these five forces be influenced, since the degree of support for or of counteraction to these forces will guide the future competitiveness and marketization of the boiler and heat exchanger manufacturing industry in the US.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.270
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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