Search results

1 – 10 of over 4000
To view the access options for this content please click here
Book part
Publication date: 6 September 2019

Vivian M. Evangelista and Rommel G. Regis

Machine learning methods have recently gained attention in business applications. We will explore the suitability of machine learning methods, particularly support vector…

Abstract

Machine learning methods have recently gained attention in business applications. We will explore the suitability of machine learning methods, particularly support vector regression (SVR) and radial basis function (RBF) approximation, in forecasting company sales. We compare the one-step-ahead forecast accuracy of these machine learning methods with traditional statistical forecasting techniques such as moving average (MA), exponential smoothing, and linear and quadratic trend regression on quarterly sales data of 43 Fortune 500 companies. Moreover, we implement an additive seasonal adjustment procedure on the quarterly sales data of 28 of the Fortune 500 companies whose time series exhibited seasonality, referred to as the seasonal group. Furthermore, we prove a mathematical property of this seasonal adjustment procedure that is useful in interpreting the resulting time series model. Our results show that the Gaussian form of a moving RBF model, with or without seasonal adjustment, is a promising method for forecasting company sales. In particular, the moving RBF-Gaussian model with seasonal adjustment yields generally better mean absolute percentage error (MAPE) values than the other methods on the sales data of 28 companies in the seasonal group. In addition, it is competitive with single exponential smoothing and better than the other methods on the sales data of the other 15 companies in the non-seasonal group.

Details

Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78754-290-7

Keywords

To view the access options for this content please click here
Article
Publication date: 4 May 2012

Youngjin Bahng and Doris H. Kincade

The influence of weather on business activities and human behaviour has been explored in several fields (e.g. finance and psychology), but little research about weather…

Abstract

Purpose

The influence of weather on business activities and human behaviour has been explored in several fields (e.g. finance and psychology), but little research about weather and retail sales is found in the retail or fashion literature. The purpose of the study is to analyse the relationship between temperature, one aspect of weather, and retail sales of seasonal garments.

Design/methodology/approach

The researchers collected sales data from a retailer of branded women's business wear in the Seoul‐Kyunggi area in South Korea. Along with the sales data for seasonal basic styles, corresponding daily and weekly average temperature data were collected and evaluated. The analysis for the study was drawn using descriptive statistics including graphical evaluations, correlation analysis and paired samples t‐test. Interviews with the retailer's merchandisers were used to supplement interpretation of the statistical data.

Findings

Results of this study provide strong evidence that fluctuations in temperature can impact sales of seasonal garments. During sales periods when drastic temperature changes occurred, more seasonal garments were sold. However, the temperature changes from day to day or week to week did not affect the number of garments sold for the whole season. Of the seasonal garments expected to sell within the same season, the selling periods of each product category differed depending on type of fabric and design. For some seasonal garments, the actual sales dates were one week to two weeks in variance from the merchandisers' forecasts.

Research limitations/implications

Limitations in the sample (i.e. product category) and location of stores (i.e. geographic region) prevent the generalization of results to all seasonal garments or retailers. In spite of these limitations, this study can be a pilot study that supports the significant relationship between temperature and sales of seasonal basic products by quantifying the temperature effects on sales of particular products. Therefore, future studies are needed to establish generalized conclusions with a larger sample.

Originality/value

As little academic research is available about weather's effect on sales of garments, the present study contributes to the field of clothing and retail distribution by providing evidence of significant relationships between temperature and sales of seasonal clothing.

Details

International Journal of Retail & Distribution Management, vol. 40 no. 6
Type: Research Article
ISSN: 0959-0552

Keywords

To view the access options for this content please click here
Article
Publication date: 18 January 2021

Martin Hirche, Juliane Haensch and Larry Lockshin

Little research on the influence of external factors, such as weather and holiday periods, on retail sales on alcoholic beverages is available. This study aims to…

Abstract

Purpose

Little research on the influence of external factors, such as weather and holiday periods, on retail sales on alcoholic beverages is available. This study aims to investigate how weekly retail sales of different alcoholic beverages vary in association with daily maximum temperatures and annual federal holidays across selected US counties in the years 2013 to 2015. The research provides information, which can contribute to better sales forecasts.

Design/methodology/approach

Secondary data of weekly retail sales (volume) of alcoholic beverages from 37,346 stores in 651 counties in the USA are analysed. The data cover on average 21% of all existing US counties and 12% of the total US off-trade retail sales of alcoholic beverages in the period studied (Euromonitor, 2017). Additional data of federal holidays and meteorological data are collated for each county in the sample. Seasonal autoregressive integrated moving average models with exogenous regressors (SARIMAX) are applied to develop forecasting models and to investigate possible relationships and effects.

Findings

The results indicate that off-trade retail sales of beer, liquor, red and white wine are temperature sensitive throughout the year, while contrary to expectations rosé, sparkling and other wines are not. Sales sensitivities to temperature also differ by geography. In the warmest regions, liquor and white wine sales do not respond to temperature changes, as opposed to the coolest regions, where they are responsive. Public holidays, particularly Easter, Thanksgiving, Christmas and New Year holidays, represent a constant influencing factor on short-term sales increases for all investigated alcoholic beverage categories.

Originality/value

This is the first large-scale study of weather and holiday-related sales variations over time, across geographies and different alcoholic beverage categories. Seasonal and non-seasonal short-term sales variations are important for retailers and manufacturers alike. Accounting for expected changes in demand accommodates efficiencies along the supply chain and has implications for retail management, as well as adjusting marketing efforts in competing categories.

Details

International Journal of Wine Business Research, vol. 33 no. 3
Type: Research Article
ISSN: 1751-1062

Keywords

To view the access options for this content please click here
Article
Publication date: 1 September 2003

Kim Shyan Fam

The present study considers how clothing and shoe retailers in New Zealand, Portugal and Hungary manage promotion campaigns and looks at the objectives that are most…

Abstract

The present study considers how clothing and shoe retailers in New Zealand, Portugal and Hungary manage promotion campaigns and looks at the objectives that are most important to these retailers as well as the marketing activities that are undertaken to reach these objectives. Change‐of‐season sales are found to be the most frequently used sales type by the retailers studied and these sales are linked with objectives of moving a volume of stock and activities such as co‐ordination of media across all forms. Secondary sales types include Christmas and general sales, and these are linked with other promotional objectives and activities such as increasing profit and dollar sales, and stock management.

Details

Marketing Intelligence & Planning, vol. 21 no. 5
Type: Research Article
ISSN: 0263-4503

Keywords

To view the access options for this content please click here
Article
Publication date: 5 November 2018

Andy Newing, Graham Clarke and Martin Clarke

The purpose of this paper is to demonstrate that applied spatial modelling can inform the planning, delivery and evaluation of retail services, offering improvements over…

Abstract

Purpose

The purpose of this paper is to demonstrate that applied spatial modelling can inform the planning, delivery and evaluation of retail services, offering improvements over traditional retail impact assessment (RIA), especially within localities which experience seasonal fluctuations in demand.

Design/methodology/approach

The paper first describes a new theoretically informed tourist-based spatial interaction model (SIM) which has been custom-built and calibrated to capture the dynamics of the grocery sector in Cornwall, UK. It tests the power of the model to predict store performance for stores not used in the original calibration process, using client data for a new store development. The model is operationalised for the evaluation of various retail development schemes, demonstrating its contribution across a full suite of location decision making application areas.

Findings

The paper demonstrates that this highly disaggregate modelling framework can provide considerable insight into the local economic and social impacts of new store developments, rarely addressed in the retail location modelling literature.

Practical implications

Whilst SIMs have been widely used in retail location research by the private sector, the paper shows that such a model can have considerable value for public sector retail planning, a sector which seemed to have abandoned such models from the 1980s onwards, replacing them with often very limited and crude RIA.

Originality/value

The ability to review the forecasting capabilities of a model (termed post-investment review) are very rare in academic research. This paper offers new evidence that SIMs can support the RIA process.

Details

International Journal of Retail & Distribution Management, vol. 46 no. 11/12
Type: Research Article
ISSN: 0959-0552

Keywords

To view the access options for this content please click here
Article
Publication date: 8 February 2016

Patrik Appelqvist, Flora Babongo, Valérie Chavez-Demoulin, Ari-Pekka Hameri and Tapio Niemi

The purpose of this paper is to study how variations in weather affect demand and supply chain performance in sport goods. The study includes several brands differing in…

Abstract

Purpose

The purpose of this paper is to study how variations in weather affect demand and supply chain performance in sport goods. The study includes several brands differing in supply chain structure, product variety and seasonality.

Design/methodology/approach

Longitudinal data on supply chain transactions and customer weather conditions are analysed. The underlying hypothesis is that changes in weather affect demand, which in turn impacts supply chain performance.

Findings

In general, an increase in temperature in winter and spring decreases order volumes in resorts, while for larger customers in urban locations order volumes increase. Further, an increase in volumes of non-seasonal products reduces delays in deliveries, but for seasonal products the effect is opposite. In all, weather affects demand, lower volumes do not generally improve supply chain performance, but larger volumes can make it worse. The analysis shows that the dependence structure between demand and delay is time varying and is affected by weather conditions.

Research limitations/implications

The study concerns one country and leisure goods, which can limit its generalizability.

Practical/implications

Well-managed supply chains should prepare for demand fluctuations caused by weather changes. Weekly weather forecasts could be used when planning operations for product families to improve supply chain performance.

Originality/value

The study focuses on supply chain vulnerability in normal weather conditions while most of the existing research studies major events or catastrophes. The results open new opportunities for supply chain managers to reduce weather dependence and improve profitability.

Details

International Journal of Retail & Distribution Management, vol. 44 no. 2
Type: Research Article
ISSN: 0959-0552

Keywords

To view the access options for this content please click here
Case study
Publication date: 1 December 2010

Stephen J.J. McGuire, Ellen A. Drost, K. Kern Kwong, David Linnevers, Ryan Tash and Oxana Lavrova

A family business founded by Chinese immigrants grew into a $133 million toy and costume maker by exploiting seasonal niche segments in the highly competitive, global toy…

Abstract

A family business founded by Chinese immigrants grew into a $133 million toy and costume maker by exploiting seasonal niche segments in the highly competitive, global toy industry. Sales of traditional toys stagnated when replaced by game consoles and electronic toys. Unable to compete in high tech toys, MegaToys moved instead toward seasonal products. In 2007, brothers Peter and Charlie Woo were about to pitch what they hoped would be $63 million in Easter basket sales to Wal-Mart. If Wal-Mart took the full order, it would come to represent over half of MegaToys' revenue.

The company was faced with the dilemma of how to grow, and at what pace. Charlie Woo knew that MegaToys could continue to grow as long as it was able to satisfy Wal-Mart's demands. Peter Woo wondered if this was the smartest way to grow the business. “Growth is a good thing as long as you don't sell your shirt to get it,” he noted. Should MegaToys continue to increase its sales to Wal-Mart, or would dependence on Wal-Mart eventually threaten the firm's success? Were there other, untapped opportunities for MegaToys that were well aligned with its strengths, resources, and capabilities?

Details

The CASE Journal, vol. 7 no. 1
Type: Case Study
ISSN: 1544-9106

To view the access options for this content please click here
Article
Publication date: 1 November 2005

Geoff Buxey

The paper reports on the ramifications for production planning when monthly sales exhibit predictable seasonal highs and lows. The literature first acknowledged and dealt…

Abstract

Purpose

The paper reports on the ramifications for production planning when monthly sales exhibit predictable seasonal highs and lows. The literature first acknowledged and dealt with the (aggregate planning) problem 50 years ago. Nevertheless, there is neither evidence that industry has adopted any of the mathematical techniques that were subsequently developed, nor a convincing explanation as to why not. Hence this research sets out to discover the methods manufacturers use to cope with seasonal demand, and how germane the published algorithms really are.

Design/methodology/approach

Forty‐two case studies were compiled by interviewing senior managers and then conducting plant tours. No prior assumptions were made and the list of questions covered the gamut of production planning.

Findings

The main finding is that manufacturers select a straightforward production strategy, right from the outset, so the fundamental cost‐balancing format is not relevant. The majority pick a “chase” strategy, since most organizations subscribe to a “just in time” ethos. Whenever a different strategy is preferred the rationale springs from skilled labour considerations or binding facilities constraints. The chosen strategy serves as a road map for resources acquisitions, and the master production schedule is constructed directly. So, the complex issue of how to disaggregate an optimal aggregate plan never even arises. Managers do not seek perfect solutions, but strive to eliminate, or contain, the most significant marginal costs. The nature of the business determines the most appropriate tactics to employ.

Originality/value

These findings break the mould as far as orthodox aggregate planning is concerned and show why theory is at odds with practice, whilst reaffirming the importance of concepts such as “flexibility”, “integration”, and “just‐in‐time production”.

Details

International Journal of Operations & Production Management, vol. 25 no. 11
Type: Research Article
ISSN: 0144-3577

Keywords

To view the access options for this content please click here
Article
Publication date: 1 July 1993

Geoff Buxey

When sales vary significantly according to season, the manufacturermakes special provisions to integrate the acquisition of raw materialsand labour with an effective…

Abstract

When sales vary significantly according to season, the manufacturer makes special provisions to integrate the acquisition of raw materials and labour with an effective production schedule which satisfies customers′ requirements. The recommended procedure is called aggregate planning, and many algorithms produce a good definitive solution. However, they have been ignored by industry. The empirical research presented here looks at such planning in a sample of 20 Australian factories. It sheds some light on the acknowledged gap between theory and practice, and suggests that business strategy, the extent of the seasonal distortion, and the tactical remedies available, are all linked. Strategic and tactical considerations tend to bypass the aggregate planning step, and the problem is ultimately resolved at the master production schedule level.

Details

International Journal of Operations & Production Management, vol. 13 no. 7
Type: Research Article
ISSN: 0144-3577

Keywords

To view the access options for this content please click here
Article
Publication date: 11 July 2016

Nari Sivanandam Arunraj and Diane Ahrens

Weather is often referred as an uncontrollable factor, which influences customer’s buying decisions and causes the demand to move in any direction. Such a risk usually…

Abstract

Purpose

Weather is often referred as an uncontrollable factor, which influences customer’s buying decisions and causes the demand to move in any direction. Such a risk usually leads to loss to industries. However, only few research studies about weather and retail shopping are available in literature. The purpose of this paper is to develop a model and to analyze the relationship between weather and retail shopping behavior (i.e. store traffic and sales).

Design/methodology/approach

The data set for this research study is obtained from two food retail stores and a fashion retail store located in Lower Bavaria, Germany. All these three retail stores are in same geographical location. The weather data set was provided by a German weather service agency and is from a weather station nearer to the retail stores under study. The analysis for the study was drawn using multiple linear regression with autoregressive elements (MLR-AR). The estimated coefficients of weather variables using MLR-AR model represent corresponding weather impacts on the store traffic and the sales.

Findings

The snowfall has a significant effect on the store traffic and the sales in both food and fashion retail stores. In food retail store, the risk due to snowfall varies depending on the location of stores. There are also significant lagging effects of snowfall in the fashion retail store. However, the rainfall has a significant effect only on the store traffic in the food retail stores. In addition to these effects, the sales in the fashion retail store are highly affected by the temperature deviation.

Research limitations/implications

Limitations in availability of data for the weather variables and other demand influencing factors (e.g. promotion, tourism, online shopping, demography of customers, etc.) may reduce efficiency of the proposed MLR-AR model. In spite of these limitations, this study can be able to quantify the effects of weather variables on the store traffic and the sales.

Originality/value

This study contributes to the field of retail distribution by providing significant evidence of relationship between weather and retail business. Unlike previous studies, the proposed model tries to consider autocorrelation property, main and interaction effects between weather variables, temperature deviation and lagging effects of snowfall on the store traffic or the sales. The estimated weather impacts from this model can act as a reliable tool for retailers to explain the importance of different non-catastrophic weather events.

Details

International Journal of Retail & Distribution Management, vol. 44 no. 7
Type: Research Article
ISSN: 0959-0552

Keywords

1 – 10 of over 4000