Understanding the economic effects of abnormal weather to mitigate the risk of business failures

Bertrand, Jean‐Louis; Parnaudeau, Miia

doi:10.1016/j.jbusres.2017.09.016

Cited by 25 publications

(15 citation statements)

References 62 publications

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“…The study confirmed that consumers' seasonal clothing demands are not dependent on calendar changes and holiday sales events, but the temperature change effects on seasonal clothing sales. Our findings are consistent with other prior findings, which found that temperature changes affect clothing sales (Agnew and Palutikof, 1999;Bahng and Kincade, 2012;Bertrand et al, 2015;Bertrand and Parnaudeau, 2019;Martinez-de-Albeniz and Belkaid, 2019;Badorf and Hoberg, 2020). Clothing retailers endeavour to adopt a new operational model to respond to external changes such as the weather.…”

Section: Discussionsupporting

confidence: 91%

“…summer dresses) in spring and summer and decreases sales of the clothing items (i.e. winter jackets) in fall and winter (Bertrand et al, 2015;Bertrand and Parnaudeau, 2019;Martinez-de-Albeniz and Belkaid, 2019). However, the significance of temperature change impacts consumers' buying behaviour, while the maximum temperature is insignificant in clothing sales (Arunraj and Ahrens, 2016).…”

Section: Discussionmentioning

confidence: 99%

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The effect of anomalous weather on the seasonal clothing market in New York

2021

Meteorological Applications

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The occurrences of losing the merchandising calendar for seasonal clothes have become more frequent due to anomalous weather changes. In order to develop accurate sales forecasts for clothing retailers, weather changes should be incorporated. The purpose of the study was to find the timing of consumers' seasonal clothing demands and the relationship between the timing of consumers' searches for seasonal clothes and temperature changes. Specifically, drawing upon the United States' seasonal clothing demand from winter jacket Google Trends (GT) and air temperature data from empirical evidence, the study provided a methodology to discover the time lag for seasonal clothing demand timing based on temperature changes. Using the past five years (2014-2019) of GT and temperature data for the US state of New York, abnormal weather due to a significant El Niño year (2015-2016) and a weak La Niña year (2017-2018) was analysed. It suggested that consumers' search activities start when the temperature decreased rapidly continuously for at least six days. Furthermore, a plausible index was employed to determine the timing of peak demand with cumulative sums (CUSUMs). Based on the CUSUMs of air temperature for 18 days, consumers started to search for winter jackets at about 118-128 CUSUMs for a La Niña year, 217-248 CUSUMs for an El Niño year and 281 CUSUMs for a normal year. The results give a guideline to meet consumers' seasonal needs in a timely manner.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

The effect of anomalous weather on the seasonal clothing market in New York

2021

Meteorological Applications

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“…Weather factors impacted consumers' seasonal clothing throughout the season. The results were supported by previous studies [1,3,4,6,7,22,32]. What are the important predictors, and how the predictors interact with consumers' seasonal clothing searches?…”

Section: When Do Consumers Search For Seasonal Clothes?supporting

confidence: 83%

“…Temperature leading to clothing sales up to a certain period of a season Researchers have long recognized that clothing sale depends on unique aspects of clothing, including trend, quality, and price, and is related to the interaction of several weather situations. While the objectives of studies are various, and the results of studies are inconsistent, numerous studies investigated the impact of temperature changes on clothing sales [1,2,3,4,6,7,22]. Warmer temperature increases sales of the clothing item (i.e., dress) in Spring and Summer and decreases clothing items (i.e., winter jacket) in fall and winter [6,7,22].…”

Section: Introductionmentioning

confidence: 99%

New Normal Weather Breaks a Traditional Clothing Retail Calendar

2021

Preprint

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Background: Clothing businesses have complained of sluggish sales because of new normal weather, an increased variation of temperature and precipitation and the higher occurrence of extreme weather events. Traditionally, the business runs tied to calendar dates or retailing events, and the previous year's sales draw up a sales plan. This study questioned whether the sales planning method of the clothing business is valid and reliable for today. Results: Using weather observation data and Google Trends for the past 11 years, consumers' responses to weather changes were analyzed through the decision tree to learn about consumer insights. The month is the most significant predictor of seasonal clothing demand during a season, and consumers' responses to weather vary from month to month. Minimum temperature and maximum temperature were significant predictors in a particular month. Conclusions: Our results have important managerial implications. Rapid weather changes affect consumers’ demand. Clothing retailers can apply the predictive model to quickly respond to unexpected weather changes, prepare products with rapidly increasing demand not to miss sales opportunities, and adjust quantities and prices for products with sharp declines in demand.

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“…Hedging can be practically important to businesses with offshore operations in multiple regions and countries for reducing risks and improving performances (Chowdhry and Howe, 1999; Pantzalis et al , 2001; Vestring et al , 2005). The use of hedging is also studied in business risk management because of geopolitical events and climate change (Anderson and Dekker, 2009; Bertrand and Parnaudeau, 2017). Businesses can use both operational and financial hedging in enterprise risk management (Sadgrove, 2015; Zhao and Huchzermeier, 2017; Goel and Tanrısever, 2017; Park et al , 2017).…”

Section: Introductionmentioning

confidence: 99%

Application of stochastic linear programming in managerial accounting

Choi

2020

IJAIM

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Purpose This paper aims to focus on applications of stochastic linear programming (SLP) to managerial accounting issues by providing a theoretical foundation and practical examples. SLP models may have more implications – and broader ones – in industry practice than deterministic linear programming (DLP) models do. Design/methodology/approach This paper introduces both DLP and SLP methods. In addition, continuous and discrete SLP models are explained. Applications are demonstrated using practical examples and simulations. Findings This research work extends the current knowledge of SLP, especially concerning managerial accounting issues. Through numerical examples, SLP demonstrates its great ability of hedging against all scenarios. Originality/value This study serves as an addition to building a cumulative tradition of research on SLP in managerial accounting. Only a few SLP studies in managerial accounting have focused on the development of such an instrument. Thus, the measurement scales in this research can be used as the starting point for further refining the instrument of optimization in managerial accounting.

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Understanding the economic effects of abnormal weather to mitigate the risk of business failures

Cited by 25 publications

References 62 publications

The effect of anomalous weather on the seasonal clothing market in New York

The effect of anomalous weather on the seasonal clothing market in New York

New Normal Weather Breaks a Traditional Clothing Retail Calendar

Application of stochastic linear programming in managerial accounting

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