Old and Small Factories Left Behind in Ethiopia’s Waste Technology Race, Survey Finds

In the rapidly industrializing outskirts of Addis Ababa, a quiet divide is emerging between the factories that can afford modern waste management technology and those that cannot. A new survey of 303 manufacturing firms in Shaggar city, Ethiopia, has identified precisely which companies are being left out of the transition to cleaner industrial production, and the results challenge several assumptions about how environmental technology spreads through developing economies. The study, published in Discover Global Society, found that nearly 80 percent of surveyed firms reported access to modern waste management technology, but the remaining fifth were overwhelmingly small, older, or financially struggling businesses.

Shaggar city is an ideal laboratory for this kind of investigation. Established in 2022 from the former Oromia Special Zone Surrounding Finfinne, the city encircles Addis Ababa across roughly 160,893 hectares and is home to an estimated 2.1 million people. Its industrial landscape spans food and beverage processing, textiles, chemicals, leather goods, metalworking, and construction materials, with industrial zones concentrated in subcities such as Gelan, Melka Nonno, Koye Feche, and Gefersa Guje. These are the areas that have historically borne the brunt of industrial waste mismanagement, and the city’s ambition to become a model smart city built on urban agriculture and environmental sustainability makes the question of technology access especially urgent.

The scale of the underlying problem extends far beyond one Ethiopian city. Across sub-Saharan Africa, annual waste generation is projected to rise from 174 million tons in 2016 to 269 million tons by 2030, a trajectory that dramatically exceeds existing collection capacity. Population growth, urbanization, and industrialization are straining municipal systems throughout the region, and uncollected waste accumulates fastest in low-income neighborhoods. Poorly managed solid and liquid industrial waste threatens soil and water resources, contributes to greenhouse gas emissions, and imposes disease burdens that fall disproportionately on the urban poor, making the question of which firms adopt modern treatment technology a matter of public health as much as industrial policy.

To untangle the factors driving adoption, researcher Urgessa Tilahun Bekabil of Oromia State University surveyed a stratified random sample of 303 registered manufacturing firms drawn from ten of the city’s twelve subcity administrations. Firms were stratified by size into small-scale operations with fewer than 50 employees, medium-scale firms with 50 to 99 employees, and large firms with 100 or more. Structured questionnaires were administered to managers, owners, or designated environmental officers by five trained enumerators, and the instrument was piloted with 30 firms before full deployment. The analysis employed logistic regression, a statistical technique that models the probability of a binary outcome, in this case whether a firm has access to modern waste management technology or not, as a function of firm characteristics, environmental practices, financial conditions, and policy variables.

The statistical foundations of the model proved sound. Variance inflation factors, which measure how much multicollinearity among predictors inflates the uncertainty of coefficient estimates, never exceeded 2.1 and averaged just 1.41, well below the conventional threshold of 10. A link test confirmed correct model specification, with the squared prediction term statistically insignificant at p equals 0.562. The overall model was highly significant, with a likelihood ratio chi-square of 106.926 and a pseudo R-squared of 0.351, meaning the included variables explain roughly 35 percent of the variation in the log odds of technology access, a respectable figure for a binary outcome in a developing country setting.

Several determinants stood out with strong statistical significance. Firm age carried a negative coefficient of 0.098, indicating that each additional year of firm age reduces the log odds of accessing modern waste technology, a pattern the author attributes to organizational inertia and lock-in to legacy production systems. Firm size showed the opposite effect: medium-sized firms had significantly greater log odds of access than small firms, with a coefficient of 1.439, and large firms showed an even stronger effect at 2.379. The bivariate data reinforced this gradient, with 51 of the 61 firms lacking access, or 83.6 percent, being small-scale operations. Operating at a deficit also mattered significantly, with deficit firms showing a coefficient of minus 1.437 relative to surplus firms, consistent with the pecking order theory of finance, which holds that financially distressed firms cannot fund discretionary investments such as environmental equipment.

Environmental practices emerged as powerful predictors as well. Firms possessing a solid waste disposal facility showed a positive coefficient of 1.115, while participation in wastewater treatment produced the strongest multivariate effect at 1.533. The descriptive statistics were striking: among the 181 firms that treat their wastewater, 92.8 percent also had access to modern waste management technology, compared with only 60.7 percent of non-treating firms. This pattern suggests what the author calls environmental management complementarities, the idea that firms investing in one component of environmental infrastructure tend to build the technical knowledge and organizational capacity that make further adoption easier. Wastewater treatment in particular demands sophisticated process control, and firms that master it appear better positioned to absorb additional waste technologies.

Perhaps the most counterintuitive finding concerns environmental protection costs, which showed a significant negative association with technology access, with a coefficient of minus 0.123. Rather than signaling environmental commitment, high compliance spending appears to crowd out technology investment. Firms already paying heavily for nontechnological compliance methods, such as manual sorting, contractor disposal, or remediation, may simply lack the resources or motivation to fund capital-intensive advanced equipment. This substitution effect carries an important policy lesson: regulations that merely raise compliance costs may paradoxically delay the technological upgrades that would ultimately reduce pollution, whereas well-designed instruments should channel spending toward structured, lasting investment.

Equally telling were the variables that failed to reach significance. Access to credit, government incentives, innovation practices, and research and development spending all showed no statistically significant relationship with technology access in the multivariate model, despite theoretical expectations and some supportive bivariate patterns. The author interprets these null results as evidence that the current design, targeting, and disbursement of these policy instruments are ineffective in this setting, a finding with direct implications for the Shaggar City Administration, the Oromia Investment and Industry Bureau, and the Environmental Protection Authority, all of which are advised to review how support programs actually reach firms.

The policy recommendations flow directly from the evidence. Because small, older, and deficit-operating firms are systematically excluded, the study calls for differentiated adoption programs featuring subsidized technology packages, technical assistance, and phased compliance schedules tailored to smaller and more entrenched establishments. Concessional green credit lines, loan-guarantee schemes, and shared treatment facilities that allow clusters of small firms to spread fixed costs could address the financial barriers the data reveal. Requiring solid waste disposal facilities as a condition of industrial licensing, and prioritizing wastewater treatment capacity as a low-cost entry point before larger capital outlays, offers firms a practical sequencing strategy. The author also notes the study’s limitations and future directions: longitudinal data would reveal how access evolves over time, in-depth interviews could explain why incentives go unused, and comparative analyses across other Ethiopian cities and industrial zones would test whether these patterns generalize. For a young city aspiring to smart, sustainable industry, the message is clear that closing the technology gap requires deliberately designed support for the firms least able to help themselves.

Subject of Research: Determinants of manufacturing firms' access to modern waste management technology in Shaggar city, Ethiopia

Article Title: Factors affecting manufacturing firms’ access to modern waste management technology in Shaggar city, Ethiopia

Article References: Bekabil, U. T. (2026). Factors affecting manufacturing firms’ access to modern waste management technology in Shaggar city, Ethiopia. Discover Global Society, 4(1), Article 244. https://doi.org/10.1007/s44282-026-00611-3

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00611-3

Keywords: waste management technology, manufacturing firms, Ethiopia, Shaggar city, logistic regression, technology adoption, environmental management, firm size, wastewater treatment, Porter hypothesis, industrial pollution, policy instruments