Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 10Innovation and Socioeconomic DevelopmentGlobal trade, sustainability, and social impactInternational Business and FDI

The DOI matches its Crossref record; 81 of the 83 references it cites were found in a registry or an index; none of the 32 sources its claims cite is checked for support yet.

Remote (Dis)engagement: Shifting Corporate Risk to the ‘Bottom of the Pyramid’

Open access
Roll, Kate, Dolan, Catherine, Rajak, Dinah·2021·Development and Change
DOI 10.1111/dech.12669
Open this paper in CoChat — free accountOpen PDF

Abstract

Untapped markets are often deemed institutional voids, terra incognita ripe with economic possibility. The conversion of institutional voids into viable markets has become the ambition of many corporations today, which view marginal and under‐served areas such as urban slums as opportunities to achieve the dual aims of market growth and poverty reduction, particularly through ‘bottom of the pyramid’ (BoP) programmes. This article examines how firms manage institutional voids and the consequences of these approaches for workers through a case study of a BoP ‘route to market’ programme designed by a global food manufacturer in Kibera, Africa's largest slum, located in Nairobi. Instead of engaging with Kibera by upgrading informal markets or generating formal employment, the corporation focused on harnessing existing informal systems through composite arrangements of NGOs, social networks and informal enterprises, a strategy the authors term ‘remote (dis)engagement’. The article describes the logics and outcome of this strategy of formal engagement with informal markets, concluding that the BoP business model depends on ‘gig practices’ of flexibility, irregular work and insecurity to realize the much‐heralded ‘fortune at the bottom of the pyramid’.

Overview

CoChat Summary

TL;DR

The article examines Project Insansa, a bottom-of-the-pyramid “route to market” programme run by a global food manufacturer in Kibera, Nairobi, showing how the firm uses NGOs, wholesalers and sellers’ social networks to enter an “institutional void” while shifting physical, financial and social risks onto informal sellers. It argues that this strategy of “remote (dis)engagement” produces adverse incorporation and low-tech gig work rather than formal employment or meaningful market inclusion.

Key findings

  • Food Co. did not build formal distribution infrastructure or upgrade informal markets; it leveraged existing informal systems, initially through an NGO partner and later through wholesalers and field officers. After the NGO was dropped, recruitment shifted toward men with established distribution businesses, and the programme, which began with a focus on female empowerment, no longer focuses on gender.
  • Sellers are framed as independent “entrepreneurs” or “micro-entrepreneurs,” lack contracts and employee status, are paid on commission, and are excluded from formal benefits and protections. They assume risks for security and access, income and credit, and social protection. The programme has over 700 sellers and accounts for approximately one-tenth of Food Co.’s regional sales; sellers earn approximately US$0.15 per sale, and in 2015–17 earned on average US$55 per month or US$1.90 per day, compared with the lowest urban national minimum wage of 13,572.90 Kenyan shillings or US$126.40 per month.
  • The programme became more formalized and professionalized, with “super sellers” making up 25 per cent of participants but generating 66 per cent of sales. The authors conclude that the BoP business model depends on “gig practices” of flexibility, irregular work and insecurity, and that “there is no Project Insansa without precarity.”
  • Rather than inclusion on secure terms, the paper characterizes sellers’ incorporation as “adverse incorporation”: they are included in the market on disadvantageous terms, with possibilities for security and accumulation circumscribed by the programme’s design.

Methods

  • The authors conducted a three-year interdisciplinary case study of Project Insansa, including seven site visits, participant observation of the selling process, and briefings by local managers.
  • Phase I consisted of semi-structured interviews with 73 sellers (42 male and 31 female), field officers, programme managers in Kenya, NGO partners, and Food Co. members involved in the programme’s inception. Phase II, in April 2015, involved 16 photo elicitation interviews, with respondents evenly distributed by gender and between rural and urban sites.
  • Additional interviews were carried out with key managers at a sister BoP programme established by Food Co. in a different country. Interviews with micro-entrepreneurs were conducted in Kiswahili or a local language, while interviews with employees and associates at Insansa and Food Co. were conducted in English.

Limitations

  • The paper does not include a dedicated limitations section.
  • Limitations evident from the text include the single-case design focused on one MNC’s BoP programme in Kibera, which limits generalizability.
  • The study relies on interviews, participant observation and company/NGO/manager accounts; the paper also notes that Food Co. does not collect data on security incidents experienced by sellers, viewing security as something workers manage as independent contractors.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1111/dech.12669

Cites

81 of 81 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 Valid · 1 Not valid · 24 Not checked · 104 Own results and interpretations

57 more claims

Create a free account to see all 129 claims and to verify the 19 references still open.

See all claims — free account
  • It may state two separate claims as one. 61
  • Probably not a substantial claim. 11

Create a free account to see these claims.

Create a free account to see these assumptions.

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

2 of 2

Citations

Cites

Research works printed but not linked: 15

  1. Cant C., 2020, Riding for Deliveroo: Resistance in the New Economy
  2. 10.2307/j.ctvgs09h2 · DOI
  3. Hagen E., 2017, Making All Voices Count Research Report
  4. Hart S., 2005, Developing Native Capability: What Multinational Corporations Can Learn from the Base of the Pyramid, Stanford Innovation Review, 3, 28
  5. Johnson M., 2010, Where is your White Space?, Harvard Business Review
  6. Jones R., 2020, In this Sprawling City within a City, Fighting Coronavirus Requires Solidarity, National Geographic
  7. Kar S., 2018, Financializing Poverty: Labor and Risk in Indian Microfinance. South Asia in Motion
  8. Karanja M., 2010, Myth Shattered: Kibera Numbers Fail to Add Up, Nation
  9. Meagher K., 2016, Capitalist Redux: The Scramble for Africa's Workers, Review of African Political Economy
  10. Owino H., 2020, Into their own Hands: Kibera, Kenya's Largest Slum, Tames COVID‐19, Pulitzer Center
  11. Parsons A.W., 2010, Megaslumming: A Journey through Sub‐Saharan Africa's Largest Shantytown
  12. Roever S., 2019, Six out of 10 People Have Informal Jobs, and Pay with their Safety, Apolitical
  13. Simanis E., 2008, The BOP Protocol: Toward the Next Generation BOP Strategy
  14. Warah R., 2010, How Numbers Game Turned Kibera into “the Biggest Slum in Africa, Nation
  15. WFP and UN‐Habitat, 2020, Impact of Covid‐19 on Livelihoods, Food Security & Nutrition in East Africa, Urban Forum

Cited by

See all 10

Related

See all

Metadata

Authors
Roll, K., Dolan, C., & Rajak, D.
ORCID
Venue
Development and Change
Publisher
Wiley
Published
2021-06-29
Volume
52
Issue
4
Pages
878-901
ISSN
  • 0012-155X (ISSN-L)
  • 1467-7660
DOI
10.1111/dech.12669
OpenAlex
W3164892602
Cited by
10
References
83
Citations by year
2026: 2 · 2025: 3 · 2024: 3 · 2023: 2
FWCI
1.15
Type
journal article
Language
en
Open access
Licence
Locations
  • Development and Change (publishedVersion, cc-by-nc-nd)
  • SOAS Research Online (SOAS University of London) (acceptedVersion)
  • SOAS Research Online (SOAS University of London) (submittedVersion, cc-by)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion, cc-by-nc-nd)
  • Sussex Research Online (University of Sussex) (submittedVersion, cc-by-nc-nd)
Topics
  • Social Sciences › Business, Management and Accounting › Business and International Management › Innovation and Socioeconomic Development
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Global trade, sustainability, and social impact
  • Social Sciences › Business, Management and Accounting › Strategy and Management › International Business and FDI
Keywords
bottom of the pyramid, institutional voids, urban slums, informal markets, gig economy, informal employment, poverty reduction, Kibera, informal enterprises, NGO partnerships, social networks, food manufacturing

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-11-14, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-11-14 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.