Optimal Retail Location: Empirical Methodology and Application to Practice

Glaeser, Chloe Kim; Fisher, Marshall L.; Su, Xuanming

doi:10.2139/ssrn.2842064

Cited by 4 publications

(10 citation statements)

References 19 publications

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“…Recently, Fisher et al. () demonstrate the operational benefits due to increasing retail mobility in a Buy‐Online‐Pick‐Up‐In‐Store setting, in which customers pick up groceries from trucks that have flexible operating locations and hours. In the case study, they estimate that optimizing truck location configuration and schedule increases revenue by at least 42%.…”

Section: Smart‐city Om Research Opportunitiesmentioning

confidence: 99%

A Smart‐City Scope of Operations Management

Wei

Shen

2019

Production and Operations Management

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W e are entering an era of great expectations towards our cities. The vision of "smart city" has been pursued worldwide to transform urban habitats into superior efficiency, quality, and sustainability. This phenomenon prompts us to ponder what role the scholars in operations management (OM) can assume. In this essay, we express our initial thoughts on expanding OM to the smart-city scope. We review smart-city initiatives of governments, industry, national laboratories and academia. We argue that the smart-city movement will transition from the tech-oriented stage to the decision-oriented stage. Hence, a smart city can be perceived as a system scope within which planning and operational decisions are orchestrated at the urban scale, reflective of multi-dimensional needs, and adaptive to massive data and innovation. The benefits of studying smart-city OM are manifold and significant: contributing to deeper understanding of smart cities by providing advanced analytical frameworks, pushing OM knowledge boundaries (such as data-driven decision making), and empowering the OM community to deliver much broader impacts than before. We discuss several research opportunities to embody these thoughts, in the interconnected contexts of smart buildings, smart grid, smart mobility and new retail. These opportunities arise from the increasing integration of systems and business models at the urban scale.

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Section: Smart‐city Om Research Opportunitiesmentioning

confidence: 99%

A Smart‐City Scope of Operations Management

Wei

Shen

2019

Production and Operations Management

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“…The models we develop in this paper have predictive power better than other models suggested in the literature for similar contexts; for example, the (out-of-sample) mean absolute percent error of our predictive models is around 20%, which is less than that reported by Fisher et al (2016), for predicting sales at online websites.…”

Section: Introductionmentioning

confidence: 55%

“…Cui et al (2017) implement multiple machine learning methods to forecast daily sales for an online apparel retailer. Fisher et al (2016) propose a combined method to predict demand at potential locations, which utilizes both machine learning methods and econometric techniques.…”

Section: Machine Learning For Predicting Demand and Optimizing Decisi...mentioning

confidence: 99%

“…There is an increasing number of papers that consider the cannibalization effect among outlets of the same retailer (Fisher et al 2016, Nishida 2014, Pancras et al 2012. Pancras et al (2012) examines the impact of opening/closing an outlet on overall chain performance, but their demand model is more suitable for isolating locations that can be closed.…”

Section: Retail Site Decision Makingmentioning

confidence: 99%

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Predictive and Prescriptive Analytics for Location Selection of Add‐on Retail Products

Huang

Bergman

Gopal

2019

Production and Operations Management

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In this paper, we study an analytical approach to selecting expansion locations for retailers selling add‐on products whose demand is derived from the demand for a separate base product. Demand for the add‐on product is realized only as a supplement to the demand for the base product. In our context, either of the two products could be subject to spatial autocorrelation where demand at a given location is impacted by demand at other locations. Using data from an industrial partner selling add‐on products, we build predictive models for understanding the derived demand of the add‐on product and establish an optimization framework for automating expansion decisions to maximize expected sales. Interestingly, spatial autocorrelation and the complexity of the predictive model impact the complexity and the structure of the prescriptive optimization model. Our results indicate that the formulated models are highly effective in predicting add‐on‐product sales, and that using the optimization framework built on the predictive model can result in substantial increases in expected sales over baseline policies.

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“…Some of these are summarized as follows: Safian et al (2018) recommended a GIS-based decision-making approach in order to evaluate the sustainable business location for purpose-built offices in Malaysia. Fisher, Glaeser, and Su (2016) o offered an empirical methodology and application to decide the optimal retail location. Fraser, Chester, and Eisenman (2018) suggested a decision approach based on GIS to determine the strategic location of refuges for extreme heat events (or heat waves).…”

Section: Introductionmentioning

confidence: 99%

Contribution of small and medium enterprises to economic development and quality of life in Turkey

Erdin

Özkaya

2020

Heliyon

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All successful cities are the most developed and productive cities in their regions and countries in terms of economy and quality of life. In addition, it is observed that there are strong industries and enterprises in these regions and cities. Therefore, this study tries to evaluate the quality of life and the development of the industry together. The proposed method can be considered as a combination of operational research and GIS (Geographical Information System). The results of both approaches support each other. In addition, the innovative approaches of the sectors are evaluated by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Also, the article recommends SMEs (Small and Medium-Sized Enterprises) for sustainable economic growth. According to the results, the quality of life and socio-economic development has a very close relationship with the existence of investments and manufacturing companies. If the current development policy continues, the regions with low quality of life will continue to lag behind the other cities in terms of development. The study indicates that there are remarkable differences between eastern and western Turkey in terms of living standards and the contribution of SMEs to economic development.

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Optimal Retail Location: Empirical Methodology and Application to Practice

Cited by 4 publications

References 19 publications

A Smart‐City Scope of Operations Management

A Smart‐City Scope of Operations Management

Predictive and Prescriptive Analytics for Location Selection of Add‐on Retail Products

Contribution of small and medium enterprises to economic development and quality of life in Turkey

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