The analysis of road sequences’ gains, efficiency, and importance across solutions may help policy makers identify the key roadworks in potential plans. These strategies may further help compensate for the delays and inefficiencies inherent to Nepal’s capital infrastructure planning bureaucracy, by focusing policy makers’ attention on the roadworks most critical to success within an overall optimized portfolio.

# 5.5. Limitations

We must note certain limitations to our analysis. The most significant is that due to resource and data constraints, we present the accessibility gains as a simultaneous phenomenon instead of staggered over the provincial government’s 5-year road construction window. A deeper analysis would specify a yearly budgetary max within the overall budget max and stagger the solution roads across the time period, with gains appropriately discounted. Additionally, we employed flat per-kilometer road costs per geographic area due to lack of data, and to better align and compare with Nepali practitioners and academics (Shrestha, 2018); more specific road cost data would improve our method’s accuracy. Finally, this analysis treats population as spatially fixed, while in reality population is dynamic and new road construction can induce population movements; for example, in Nepal new markets often spring up at newly built roads heads. This could create additional unobserved objectives if the government speculatively selected roads to create new market hubs or connect underpopulated remote villages to reduce population outflows.

The complexity of the analysis routines described here places them effectively out of reach of even national government planning agencies in Nepal, let alone provincial or municipal ones. Thus government will need to employ universities and private sector companies with specialized expertise to replicate this analysis in new areas. Given that the studied investment planning exercise happens on a 5 year basis this seems a manageable extra expense. As stated above, care was taken to use free global or common national data sets to ease adoption and replication by other parties.

A further limitation is the difficulty of communicating our results to policy makers compared to traditional instruments. Welfare-based evaluation methods ease the cognitive burden on decision makers by measuring investment returns in terms of familiar NPR values or easily parsable rates of return. To compensate we have produced thorough explanatory visuals for our methods and results. Nevertheless, correctly interpreting a 3D bubble chart – itself a simplification of 6D results – of person-hours is inherently more challenging than a table of NPV or Internal Rate of Return (IRR) values. This erodes decision makers’ ability and willingness to use our results. Therefore real-world implementations will need to invest additional time and effort in correctly explaining results and guiding policy makers to use them appropriately.

# 5.6. Potential improvements and future research opportunities

Given the complexity of the multi-disciplinary analysis methods undertaken we employed a relatively straightforward series of inputs, metrics, and decision criteria for roads investment. Having proven the value of this work, we have several suggestions for enlarging its focus, improving its specificity, and aligning it better with traditional planning methods.

Additional georeferenced services would nuance the analysis, each one representing two (dry and monsoon season) additional objectives. For instance, the analysis could incorporate accessibility to schools, water points, agricultural extension services, or other important services, even at a village or household level. A variation on this theme is to differentiate qualitatively between services, for instance by separating hospitals from health posts or major from minor financial institutions and then re-running the analysis with each as an objective.

A more involved modification would involve calculating cumulative person-hours within service-specific constrained catchments that reflect travel time limits on the utility of services, both generally and for specific demographic groups. For instance, in an August 2018 interview RAP staff described how individuals might travel 8 hours for important health problems but never to bring produce to weekly markets and Nepalese women are typically warier of overnight travel (in excess of 4 hours one way). Accessibility indicators could also be calculated solely for target demographic groups (i.e. pregnant women to maternal health centers). Particularly ambitious would be replacing cumulative person-hours with more data intensive changes in gravity models of service access based on the quality (attractiveness) of services vs. the distance and size of reached populations.

Alternatively, the geospatial models could be adapted to provide inputs to a comprehensive cost-benefit analysis. While this paper has explored our methods as an alternative to CBA for planning remote rural roads, 41