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Purpose

The article is Part I of a two-part series that investigates the limitations of conventional analysis of shopping centre investment performance and suggests how a time dependent period/regime framework can provide more accurate and reliable measures.

Design/methodology/approach

This article draws on theory, literature and advances in analytics to review conventional homothetic methods of analysing longitudinal shopping centre performance data. It introduces a holothetic approach that deploys linear/spline functions to identify inflection points that support the delineation of the 25-year study frame into a series of longer-term periods and more precise, shorter-term regimes.

Findings

The discussion demonstrates the pattern of shopping centre performance varies across the generally recognised five time periods in the study frame. The use of holothetic analytics can be used to stochastically decompose the periods into shorter regimes that exhibit different performance in terms of level and direction. This framework can be used to provide more accurate measures of shopping centre performance.

Research limitations/implications

This discussion and the following analytics use the retail component of the NPI, a US-only benchmark. We believe it introduces methods that can be extended to other geographic areas.

Practical implications

The research frames the argument that time matters; that agents should pay attention to market drivers of value and fundamentals that change over time and affect outcomes and decisions.

Social implications

The study supports the development of more accurate information regarding shopping centre performance.

Originality/value

This paper extends holothetic, time-based analysis to shopping centres, a property sector that has received limited attention in the literature.

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