{"title":"Industry 4.0 Challenges and Implementation Strategies: Benchmarked Results From Food and Beverage Manufacturing Industries in Tanzania","authors":"Ismail W. R. Taifa, Ikupa Mwakagamba","doi":"10.1002/eng2.70168","DOIUrl":null,"url":null,"abstract":"<p>The study assessed the challenges and strategies of Industry 4.0 (I4.0) in Tanzania's food and beverage manufacturing industries (FBMIs). Pertinent data were collected through a closed-ended questionnaire from 103 medium and large FBMIs. Data validity and reliability were tested using SPSS 23, where <i>p</i>-values < 0.05 for validity testing and Cronbach Alpha value of > 0.7 were determined for the reliability of the collected questionnaires. The normality of the data was tested using Kolmogorov–Smirnov and Shapiro–Wilk tests. The study found that employees were more informed about the benefits of adopting I4.0, with a mean score of 4.78. The prospect of I4.0 improving industry competitiveness on the international stage was ranked second in terms of awareness. Also, there was no significant difference in awareness levels for nine I4.0 technologies among the FBMIs. Most FBMIs had not fully established a roadmap for using I4.0 technologies. Findings showed that challenges have no significant differences, for example, for financial challenges (χ<sup>2</sup> = 1.121, <i>p</i> = 0.571 > 0.05), return on investment and cost–benefit analysis for implementing I4.0 technologies with (χ<sup>2</sup> = 0.027, <i>p</i> = 0.987 > 0.05), identifying and securing funds for implementing I4.0 technologies (with χ<sup>2</sup> = 1.918, <i>p</i> = 0.383 > 0.05), among others. Implementing I4.0-related technologies is high; the findings showed that the overall mean score was 3.75, corresponding to “level 4” on the five-point Likert awareness scale. Also, some challenges should be tackled to implement I4.0-related technologies smoothly. Consequently, such challenges can be addressed by implementing the proposed strategies. The study suggests that stakeholders must implement relevant technologies fully despite FBMIs' high I4.0 awareness. Lastly, the study proposed strategies for implementing I4.0 in the FBMIs, including embracing data-driven decision-making and training leaders and top management regarding the benefits of I4.0 implementation. Strategies should be supported by top management commitment and adequate budget allocation.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"7 5","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.70168","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering reports : open access","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/eng2.70168","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
The study assessed the challenges and strategies of Industry 4.0 (I4.0) in Tanzania's food and beverage manufacturing industries (FBMIs). Pertinent data were collected through a closed-ended questionnaire from 103 medium and large FBMIs. Data validity and reliability were tested using SPSS 23, where p-values < 0.05 for validity testing and Cronbach Alpha value of > 0.7 were determined for the reliability of the collected questionnaires. The normality of the data was tested using Kolmogorov–Smirnov and Shapiro–Wilk tests. The study found that employees were more informed about the benefits of adopting I4.0, with a mean score of 4.78. The prospect of I4.0 improving industry competitiveness on the international stage was ranked second in terms of awareness. Also, there was no significant difference in awareness levels for nine I4.0 technologies among the FBMIs. Most FBMIs had not fully established a roadmap for using I4.0 technologies. Findings showed that challenges have no significant differences, for example, for financial challenges (χ2 = 1.121, p = 0.571 > 0.05), return on investment and cost–benefit analysis for implementing I4.0 technologies with (χ2 = 0.027, p = 0.987 > 0.05), identifying and securing funds for implementing I4.0 technologies (with χ2 = 1.918, p = 0.383 > 0.05), among others. Implementing I4.0-related technologies is high; the findings showed that the overall mean score was 3.75, corresponding to “level 4” on the five-point Likert awareness scale. Also, some challenges should be tackled to implement I4.0-related technologies smoothly. Consequently, such challenges can be addressed by implementing the proposed strategies. The study suggests that stakeholders must implement relevant technologies fully despite FBMIs' high I4.0 awareness. Lastly, the study proposed strategies for implementing I4.0 in the FBMIs, including embracing data-driven decision-making and training leaders and top management regarding the benefits of I4.0 implementation. Strategies should be supported by top management commitment and adequate budget allocation.