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Record W327040762

Strategies for SMEs after Global Recession

2011· article· en· W327040762 on OpenAlexaboutno aff
Durgesh Sharma, S. K. Garg, C. L. Sharma

Bibliographic record

VenueGlobal business and management research · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsRecessionDynamismBusinessChinaFinancial crisisGlobal recessionInternational tradeEconomyEconomicsGeography
DOInot available

Abstract

fetched live from OpenAlex

Introduction The impact of the sub- prime crisis along with a slowdown in mortgages has led to a significant lowering of growth estimates in USA. Since the United States dominates the global economy, this had led to slowing down of economies of all major countries. The recession has affected the world economy very badly. It had shoddily affected almost all economies of the world like USA, United Kingdom, Canada, Japan, Australia, China, and New Zealand. World's greatest banks suffered losses and thousands of people lost their jobs. Countries like Greece and Iceland have become completely bankrupt. Unsurprisingly, smaller and weaker companies have struggled the most in this hostile environment. Unlike large corporations, small and medium-sized enterprises (SMEs) have little flexibility to cope with plummeting demand, cancelled orders, scarcer financing and delayed payments. SMEs in Asia are no exception, despite their dynamism and rapidly improving economic outlook crisis management is their top priority. The fate of SMEs is particularly crucial since SMEs account for bulk of employment in many of the region's economies. They have been hit disproportionately hard by the global recession, particularly those companies, reliant on exports. The paper examine the how have value chains influenced the effect of the crisis on SMEs in Asia and what opportunities/threats has the crisis presented to SMEs internationally. The paper will be helpful to the SME managers to formulate strategies to fight recession. Contribution of SMEs in Asian Economy According to Asia-Pacific Economic Co-operation (APEC) forum, 95% of businesses in the Asia-Pacific region are SMEs, and they employ 60% of the workforce. In terms of value, the sector accounts for about 40-45 per cent of the manufacturing output. (APEC, 2010). In China about 42 million SMEs are in operation as of 2008, equivalent to 99% of the country's total enterprises and employing 75% of urban dwellers. They accounted for 60 % of GDP and 62.3% of exports in value terms (People's Daily Online, 2010). In Taiwan, according to the Ministry of Economic Affairs SMEs account for 98% of enterprises, 77% of employment and 17% of export sales. (MEA, Tiawan, 2010). In Hong Kong, they account for 98% of businesses and 48% of total employment (excluding civil service positions). In India too, the SMEs play a pivotal role in the overall development of country. It is estimated that in terms of value, the sector accounts for about 45 per cent of the manufacturing output and 40 per cent of the total exports of the country. The sector is estimated to employ about 59 million person in over 26 million units throughout the country. There are over 6000 products ranging from traditional to high-tech items, which are being manufactured by the SMEs in India. Indian SMEs constitute about 80% of the country's industrial enterprises and employing 70% of the workforce. (MSME, 2009) Importance of SMEs for Socio-economic Development Poverty is one of the major global problems. One in five people in the world lives in miserable poverty. About 50% of the world population survives on less than USD 2.00 a day. Poverty denies a person to make choice of alternative avenues for economic, social and cultural growth that can better his life. Poverty ensures that all principles of human rights are violated. Not only in Asia, but also across the world, the SME sector makes a tremendous contribution in reducing poverty. SMEs generate new jobs in the economy thus they contribute affirmatively to employment generation and poverty alleviation. Further, it is claimed that this additional employment comes with relatively low investments in capital compared to the large enterprises. Therefore, it has a lot of relevance for those economies that are characterized by surplus labor and paucity of capital. Major Recessions and Their Causes A recession is a decline in a country's gross domestic product (GDP) growth for two or more consecutive quarters of a year. …

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.136
GPT teacher head0.330
Teacher spread0.194 · 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 designTheoretical or conceptual
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

Citations8
Published2011
Admission routes1
Has abstractyes

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