Adoption of Technology as a Response Strategy to Globalization: A Study of Manufacturing Firms in Kenya
Bibliographic record
Abstract
Globalization affects local and international firms in many ways. Studies have shown that factors in the internal as well as external environments of firms influence the rate to which globalization will affect them. On the local scene however, no known studies have been done on the response of manufacturing firms to counter globalization. In addition, since the concept of globalization is multidimensional and its influence is varied in nature, this study aimed at investigating how manufacturing firms in Kenya have responded to probable pressure from the forces of globalization in order to sharpen their competitiveness. Cross sectional survey design was adopted for the study. The population for the study was the 735 manufacturing firms in Kenya. The target population of the study were CEOs/MDs and their deputies from 545 manufacturing companies in Nairobi and Athi River. Stratified sampling technique was used to categorize the targeted manufacturing firms into sectors where purposive sampling technique was used to sample the respondents for the study. A total of 100 firms from the 14 sectors were targeted by the study out of which 80 responded giving a response rate of 80%. Questionnaire was used to collect primary data. Regression and correlation analysis was done to test the relationship between the study variables. The study found that 65% of the respondents agreed that continued global technological advancement has enabled management come up with innovations to respond to customer needs and economic and regulatory factors which have prompted outsourcing some operations, respectively. The results of the correlation analysis show that adoption of technology is statistically significant with a Pearson’s Correlation Coefficient of 0.683 and at a level of significance of 0.000. The study also found out that 67.5% of the respondents agreed that continued global technological advancement has enabled management come up with innovations to respond to customer needs and economic and regulatory factors which have prompted outsourcing some operations respectively. The null hypotheses that there is no significant relationship between globalization and competition was therefore reject. The study concluded that manufacturing firms in Kenya have adopted technology as response strategies to globalization. The study recommended that manufacturing firms should adopt the new changes in the market and to absorb into the technological trend. Thus, they should remain flexible and stay focused to the day to day changes of globalization strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".