Business Intelligence for Bottleneck-Sensitive International

Market Entry Screening

Asif aIqbal1,* Shahid Mahmood2

1 School of International Languages, Zhengzhou University, Henan, China

2 School of Finance and Economics, Jiangsu University, Zhenjiang, China

Received: July 24, 2026 Revised: September 08, 2026 Accepted: October 04, 2026 ⋆ Corresponding author

ABSTRACT

An international expansion team must decide which candidate markets warrant costly commercial due diligence.

Regulation-only rankings can overlook the services and operating processes needed to conduct business. We develop

a reproducible business intelligence screen using the three published pillars of theWorld Bank’s Business Ready 2025

for 101 economies. The analysis compares a regulation-led shortlist with a noncompensatory weakest-pillar rule, tests

its sensitivity to shortlist capacity and alternative aggregation, and examines a mechanical one-pillar improvement

scenario. Public Services is the lowest pillar in 67 economies and Operational Efficiency in 31. Regulation exceeds

services by 12.36 points on average (95% bootstrap interval 10.52–14.12). The regulation-led and bottleneck-led top

20 share 11 economies, so nine due-diligence candidates change; their equal-weight and bottleneck-led counterparts

share 18. Raising the lowest pillar hypothetically by ten points increases the resulting minimum by 6.63 points

on average because another pillar may become binding. The output identifies markets requiring checks of service

delivery or operational execution before a site-selection decision. Its rankings are transparent decision rules applied

to official scores, not World Bank rankings, investment-return estimates, or evidence of causal reform effects.

Keywords: Business intelligence Business data analytics Market entry screening Decision support Operational

bottlenecks

1. INTRODUCTION

A market entry committee does not need a general statement

that one economy is “business friendly.” It needs to know

which operating condition could defeat a proposed investment.

A well-written commercial code offers little reassurance if

permits, utilities, registries, or administrative processes do

not deliver reliably. Conversely, a modest rule score need

not imply that the practical service interface is equally weak.

A one-number screen can hide the particular exposure that

managers must test on the ground.

The World Bank’s Business Ready 2025 (B-READY) reports

three scores for each of 101 economies: Regulatory Framework,

Public Services, and Operational Efficiency [1]. These

dimensions support a specific business data analytics question:

how many candidates in a capacity-limited market-entry

shortlist change when a committee shifts from a rules-led

score to an explicitly noncompensatory one? We answer that

question for the full published cross-section. We also quantify

within-economy gaps, identify the pillar that constrains each

profile, test the stability of an equal-weight summary, and

calculate a simple one-pillar improvement scenario.

This article does not introduce an official country league table.

Its ranks are sample-specific outputs of two decision rules

chosen to show the cost of an implicit assumption. A firm

might rationally accept compensation between dimensions