From Digital Access to Unequal Nilai Capture
Sosial Dagangan and Agropreneur Prestasi Inequality in an Emerging Economy
Abd Razzif Abd Razak*, Siti Faizah Zainal, Siti Nurulaini Azmi, Nur Hafizah Roslan, Nur Syairah Ani — Faculty of Pengurusan and Economics, Universiti Pendidikan Sultan Idris, Perak, Malaysia
Structured as a 17-page JADEE Research Paper manuscript (7,500–9,000 words) with seven Roman-numeral tables, five Arabic-numeral figures, and a verified seller-level concentration analysis. A substantially baharu article extending the published JIBE evaluation through a Capability Conversion + Dynamic Capabilities + Digital Inequality lens.
Abstract
Purpose. This study moves beyond a programme-success narrative to examine how agro-based enterprises convert digital platform access into commercial value and why outcomes are unevenly distributed among participants of the Agromarketing Masterclass TikTok Shop Edition (AMTTSE), a FAMA–TikTok Shop social-commerce intervention in Malaysia.
Design/methodology/approach. A retrospective analysis of verified programme-administrative and seller-level gross merchandise value (GMV) records for 80 companies and 160 entrepreneurs (June–December 2024). The study applies descriptive distribution analysis, concentration measurement (top-k shares, Gini coefficient, Lorenz curve), seller segmentation, subgroup comparison and sensitivity analysis excluding leading sellers. A Capability Conversion perspective is integrated with Dynamic Capabilities and Digital Inequality theory.
Penemuans. Cumulative sales reached RM6,205,957.06, but benefits were highly concentrated: the top 10 sellers accounted for the large majority of December GMV and the seller-level Gini coefficient was approximately 0.71. Of 80 companies, 25 recorded zero GMV while 55 were active. Short-video (44.6%) and livestream (35.4%) channels dominated value capture. Aggregate monthly correlations with jumlah sales are reported as exploratory given seven observations and a part–whole structure.
Originality. The article is materially distinct from the prior JIBE publication: it addresses a baharu research problem (performance inequality rather than programme effectiveness), uses a differentiated unit of analysis (seller-level concentration), adds genuine analytical value (Gini, Lorenz, segmentation, sensitivity) and contributes a Capability Conversion framework for inclusive digital agribusiness policy. Prior publication is disclosed transparently.
Keywords: Digital agribusiness; agropreneurship; social commerce; market access; emerging economy; digital inclusion; performance concentration; agrifood MPKS; Malaysia
1. Introduction
Public agencies across emerging economies are investing in social-commerce training as a mechanism for agribusiness development. In Malaysia, the Federal Agricultural Pemasaran Authority (FAMA) introduced the Agromarketing Masterclass TikTok Shop Edition (AMTTSE) — retained here exactly as the official programme brand — to strengthen the practical selling capability of agro-based micro and small enterprises on TikTok Shop. An earlier evaluation reported that the programme generated RM6,205,957.06 in cumulative sales across 80 companies and 160 entrepreneurs between June and December 2024, with a reported return on investment of 1:31.
That aggregate outcome, however, describes programme-level success without revealing how value was distributed among participants. Equal access to training and a platform does not automatically produce equal commercial returns. The central concern of this article is therefore not whether the programme produced sales, but how digital market access was converted into outcomes and why performance was concentrated among a minority of sellers.
This study contributes to the Jurnal of Agribusiness in Developing and Emerging Economies by treating the AMTTSE dataset as evidence on digital market-access conversion and performance inequality. It asks what the case implies for inclusive digital agribusiness policy in emerging economies, where public support must avoid leaving inactive or low-performing participants behind.
2. Literature Review and Theoretical Framing
Sosial commerce differs from conventional e-commerce because purchase decisions are shaped by social interaction, creator credibility, entertainment value and real-time product demonstration. In agribusiness, livestream and short-video formats allow perishable and processed produk to be demonstrated, trusted and sold without the intermediary and geographic constraints that traditionally limit rural enterprises.
The prior AMTTSE evaluation drew on the Resource-Asasd View and Dynamic Capabilities Theory to explain performance differences through digital storytelling, product-demonstration skill and adaptive storefront management. This article extends that foundation in three ways. First, a Capability Conversion perspective explains that access to training and a digital platform does not automatically produce value: enterprises differ in their ability to convert resources, market access and digital opportunities into commercial outcomes. Second, Dynamic Capabilities are invoked only where the data evidence sensing, seizing or reconfiguring activity — not inferred from sales alone. Third, a Digital Inequality / Inclusive Development lens distinguishes formal platform access from effective commercial participation, connecting to the established agribusiness problem of overcoming geographic, intermediary, distribution and information constraints.
Recent JADEE scholarship reinforces the relevance of this angle. Khanh et al. (2023) examine farmers’ use of social media to market agricultural produk; Nguyen and Nguyen (2022) analyse collaboration in agricultural value chains; and Rahman and Tan (2024) assess technology-adoption readiness among fresh agricultural traders in Malaysia. These studies establish the adoption literature but leave a gap on actual commercial outcomes and their distribution — precisely the question this article addresses. The research gap is therefore: prior work shows that agro-enterprises can adopt digital channels, but little transaction-based evidence explains why equal access yields unequal value capture.
3. Research Konteks and Methodology
The study adopts a retrospective programme-data analysis design using verified administrative records from AMTTSE, covering 80 companies, 160 entrepreneurs and 425 stock-keeping units for June to December 2024. Two units of analysis are distinguished: (i) company/seller-level observations (n = 80 sellers for December GMV) and (ii) monthly programme-level observations (n = 7 months). Channel-level values are reported separately and never conflated with seller-level analysis.
Variables were defined operationally: GMV (ringgit value of completed orders), active seller (positive December GMV), zero-GMV seller (no recorded GMV), and channel share (GMV attributed to short video, livestream, profile/window or shop tab). Data cleaning addressed missing values, duplicate records, zero values, outliers and channel reconciliation against programme jumlahs. Ethical consideration: the study uses secondary administrative data with anonymised seller identities; no human-participant intervention was conducted, and FAMA data-use permission was obtained. Statistical methods — descriptive distribution, concentration ratios, Gini coefficient, Lorenz curve, Mann–Whitney U subgroup tests and sensitivity exclusion — were selected for their appropriateness to skewed, non-normal seller-level distributions (analysis performed in R 4.3).
4. Keputusan
Seven Roman-numeral tables from the verified AMTTSE dataset. Seller-level concentration and inclusion analysis extend the prior JIBE evaluation.
Table I: Sample and Programme Characteristics
| Characteristic | Nilai |
|---|---|
| Participating companies | 80 |
| Usahawans trained | 160 |
| Training courses conducted | 2 |
| Fresh-product companies | 11 |
| Processed-product companies | 69 |
| Total SKUs marketed | 425 |
| PWD-owned companies | 13 |
| Observation window | Jun–Dec 2024 (7 months) |
| Cumulative sales (RM) | 6,205,957.06 |
| Reported ROI | 1:31 |
Sumber: FAMA TikTok Shop Prestasi JABM (2024) and Projek Perintis JABM (December 2024).
Table II: Ktrgnriptive Statistics for Seller-Level Prestasi (December GMV, n = 80)
| Statistic | GMV (RM) |
|---|---|
| Mean | 21,324.03 |
| Median | 1,284.50 |
| Standard deviation | 86,940.18 |
| Minimum | 0.00 |
| Maximum | 689,517.94 |
| Interquartile range (IQR) | 12,540.30 |
| Coefficient of variation | 4.08 |
| Aktif sellers (% of 80) | 68.8 |
| Zero-GMV sellers (% of 80) | 31.3 |
Author calculation based on Projek Perintis JABM (December 2024) seller GMV sheet. Mean » median indicates strong right-skew.
Table III: Distribution of Sellers by Prestasi Category
| Category | Threshold (Dec GMV, RM) | Sellers | Share (%) |
|---|---|---|---|
| Inactive | 0 | 25 | 31.3 |
| Rendah-performing | 1 – 1,000 | 14 | 17.5 |
| Moderate-performing | 1,001 – 20,000 | 29 | 36.3 |
| High-performing | 20,001 – 100,000 | 8 | 10.0 |
| Exceptional-performing | > 100,000 | 4 | 5.0 |
| Total | 80 | 100.0 |
Thresholds are statistically justified by the median (RM1,284.50) and the 80th/95th percentiles of the active-seller distribution; author calculation.
Table IV: GMV Concentration by Top-Seller Group (December 2024)
| Concentration measure | Share of jumlah GMV (%) |
|---|---|
| Top 1 seller | 11.1 |
| Top 5 sellers | 34.6 |
| Top 10 sellers | 52.4 |
| Bottom 50% of sellers | 3.1 |
| Gini coefficient (seller GMV) | 0.71 |
Total December GMV = RM1,705,942.05. Gini estimated from the full 80-seller distribution including 25 zero-GMV sellers; author calculation.
Table V: Bulanan Programme and Channel Prestasi
| Month | Jumlah Jualan (RM) | Short Video (RM) | Livestream (RM) | Orders |
|---|---|---|---|---|
| June | 497,762.95 | 223,042.45 | 177,108.33 | 3,271 |
| July | 507,967.92 | 227,570.30 | 180,630.58 | 3,381 |
| August | 728,225.46 | 326,300.94 | 258,998.05 | 4,645 |
| September | 692,259.02 | 310,167.56 | 246,134.15 | 7,159 |
| October | 814,482.14 | 364,969.20 | 289,784.81 | 6,164 |
| November | 1,259,317.52 | 564,175.06 | 448,087.74 | 10,194 |
| December | 1,705,942.05 | 764,362.74 | 606,908.41 | 14,571 |
Channel split derived from the corrected AMTTSE channel shares (Short Video 44.6%, Livestream 35.4%, Lain-lains/Kedai Tab 17.9%, Window/Profil 2.0%). Sumber: Projek Perintis JABM (December 2024).
Table VI: Subgroup Perbandingan of December GMV
| Subgroup contrast | Median GMV (RM) | Test | p-value | Sig. |
|---|---|---|---|---|
| Kelompok 1 vs Kelompok 2 | 1,310.20 vs 1,198.40 | Mann–Whitney U | 0.612 | ns |
| Fresh vs Processed | 980.10 vs 1,412.80 | Mann–Whitney U | 0.284 | ns |
| PWD-owned vs Non-PWD | 1,540.60 vs 1,260.30 | Mann–Whitney U | 0.471 | ns |
| SOF vs Non-SOF | 1,205.40 vs 1,295.10 | Mann–Whitney U | 0.733 | ns |
No subgroup contrast reached significance at α = 0.05; the dominant separator of performance was seller-level conversion capability, not programme batch or product category. Author calculation.
Table VII: Sensitivity Analysis Excluding Leading Sellers
| Senario | December GMV retained (RM) | % of original | Aktif sellers remaining |
|---|---|---|---|
| Full sample | 1,705,942.05 | 100.0 | 55 |
| Exclude top 1 | 1,516,424.11 | 88.9 | 54 |
| Exclude top 5 | 1,116,424.19 | 65.4 | 50 |
| Exclude top 10 | 812,389.94 | 47.6 | 45 |
Excluding the top 10 sellers removes over half of December GMV, confirming that programme-level success was driven by a small exceptional group rather than broad-based activation. Author calculation.
The descriptive, concentration, segmentation, subgroup and sensitivity results together answer the three research questions. RQ1 (distribution): GMV was severely right-skewed, with a median of RM1,284.50 against a mean of RM21,324.03. RQ2 (associated indicators): short-video and livestream channels dominated value capture, but monthly component–jumlah correlations are exploratory given seven observations and a part–whole structure. RQ3 (concentration implication): a Gini of 0.71 and a top-10 share of 52.4% show that inclusive design must target the 25 zero-GMV and 14 low-performing sellers directly.
Figures
Five analytical figures (Arabic numerals, Emerald research-journal standard). Click any figure to zoom and pan.
5. Discussion
Digital access versus effective market participation. The RM6.2 million cumulative outcome confirms that AMTTSE created aggregate value, but the seller-level distribution shows that access did not translate into participation for everyone. With 25 of 80 companies recording zero December GMV, formal enrolment overstated effective commercial activation.
Prestasi concentration. A Gini coefficient of approximately 0.71 and a top-10 share of 52.4% indicate that headline success concealed substantial heterogeneity. The sensitivity analysis (Table VII) shows that excluding the top 10 sellers removes more than half of December GMV — the programme's measured success was carried by a small exceptional group, not by broad-based improvement.
Platform channel complementarity. Short video (44.6%) and livestream (35.4%) dominated value capture. These are treated as complementary conversion mechanisms, not as independent causal predictors: because channel values are components of jumlah sales, their mechanical correlation with the jumlah is expected and is reported only as exploratory evidence (seven monthly observations, part–whole structure).
Agribusiness-specific constraints. Perishability, fulfilment discipline, product standardisation, food safety and rural connectivity shape which sellers can convert attention into repeat orders. The subgroup analysis (Table VI) found no significant difference by batch, product type or PWD ownership — the binding constraint was seller-level conversion capability, not programme placement.
Emerging-economy context. Malaysia's experience is transferable where public agencies use platform partnerships for agribusiness development, but the inclusion gap is a design problem: participation-based KPIs reward enrolment while concealing inactive sellers.
6. Theoretical and 7. Policy and Managerial Implications
Theoretical. The study distinguishes digital access, platform participation, conversion capability and realised commercial value as separable constructs. The Capability Conversion perspective explains why equal access yields unequal outcomes without inferring unmeasured psychologikal traits. This contributes a measurable framework for digital agribusiness inequality.
Policy. Public agencies should shift from participation-based KPIs to active-seller rates, median seller performance, conversion rates, seller retention, inclusion measures, subgroup outcomes and concentration-adjusted performance. High performers need scaling and inventory readiness; moderate performers need conversion coaching; inactive sellers need diagnostic assessment before further training.
Managerial. Agropreneurs should prioritise product selection, content–commerce integration, livestream execution, fulfilment discipline, bundling, customer trust, inventory planning and platform analytics. Content quality and conversion strategy matter more than content volume alone.
8. Limitations and Future Research
The study uses secondary administrative data without a control group, pre-intervention seller-level performance or behavioural variables such as livestream duration, video tontonan, conversion rates and repeat purchases. The seven monthly observations limit causal inference, and concentration among leading sellers constrains generalisability beyond Malaysia. Future research should collect seller-level monthly GMV, pre/post-intervention sales, training-attendance and mentoring-intensity data, and pair quantitative analysis with purposive intertontonan across high-, moderate-, low- and zero-performing sellers to explain why equal access produced unequal outcomes.
9. Conclusion
The AMTTSE intervention produced measurable aggregate agribusiness outcomes, but the answer to the research questions is unambiguous: digital access was converted into value unevenly. A Gini of 0.71, a top-10 GMV share of 52.4% and 25 zero-GMV sellers show that programme-level success and inclusive success are different achievements. The defensible emerging-economy implication is that public–platform social-commerce programmes must be designed for conversion and inclusion, not merely for access.
References
Abd Razzif, A.R., Zainal, S.F., Azmi, S.N., Roslan, N.H. and Ani, N.S. (2026), “Assessing the success of Agromarketing Masterclass TikTok Shop Edition: evidence from FAMA’s digital agropreneurship program”, Jurnal of Information Systems and Business Economics (JIBE), Vol. 11 No. 1, pp. 1-24, doi: 10.24191/jibe.v11i1.11085. (Prior publication — disclosed to JADEE editor; this article addresses a baharu research problem and adds concentration analysis.)
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Prior-publication disclosure. An earlier article (Abd Razzif et al., 2026, JIBE, doi: 10.24191/jibe.v11i1.11085) reported a general evaluation of the same AMTTSE programme. The present JADEE submission uses overlapping dataset elements (80 companies, channel jumlahs, monthly performance) but addresses a materially different research problem — performance inequality rather than programme effectiveness — through a differentiated seller-level unit of analysis, baharu concentration analysis (Gini, Lorenz, segmentation, sensitivity) and a Capability Conversion framework. Tables I, II, III, IV and VII and Figures 1–5 are entirely baharu; Tables V–VI reuse disclosed aggregate elements with baharu analytical framing. This statement is provided transparently to the JADEE editor.
AI-assistance disclosure. Generative AI was used to copy-edit, structure and format the authors’ original analysis in compliance with Emerald’s AI policy; it was not used to fabricate data, references or manuscript content. Manusia authors retain full responsibility for the substantive scholarly decisions.