scholarly journals The Buy-Online-Pick-Up-in-Store Retailing Model: Optimization Strategies for In-Store Picking and Packing

Algorithms ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 350
Author(s):  
Nicola Ognibene Pietri ◽  
Xiaochen Chou ◽  
Dominic Loske ◽  
Matthias Klumpp ◽  
Roberto Montemanni
Keyword(s):  
Mathematical Model ◽  
Online Shopping ◽  
Cost Driver ◽  
Model Optimization ◽  
Real World Data ◽  
Effective Strategies ◽  
Digital Services ◽  
Brick And Mortar ◽  
Packing Process ◽  
Increasing Demand

Online shopping is growing fast due to the increasingly widespread use of digital services. During the COVID-19 pandemic, the desire for contactless shopping has further changed consumer behavior and accelerated the acceptance of online grocery purchases. Consequently, traditional brick-and-mortar retailers are developing omnichannel solutions such as click-and-collect services to fulfill the increasing demand. In this work, we consider the Buy-Online-Pick-up-in-Store concept, in which online orders are collected by employees of the conventional stores. As labor is a major cost driver, we apply and discuss different optimizing strategies in the picking and packing process based on real-world data from a German retailer. With comparison of different methods, we estimate the improvements in efficiency in terms of time spent during the picking process. Additionally, the time spent on the packing process can be further decreased by applying a mathematical model that guides the employees on how to organize the articles in different shopping bags during the picking process. In general, we put forward effective strategies for the Buy-Online-Pick-up-in-Store paradigm that can be easily implemented by stores with different topologies.

scholarly journals Life-Stage Modeling by Customer-Manifold Embedding

2017 ◽  
Author(s):  
Jing-Wen Yang ◽  
Yang Yu ◽  
Xiao-Peng Zhang
Keyword(s):  
Online Shopping ◽  
Life Stage ◽  
Customer Behavior ◽  
Behavior Patterns ◽  
Prediction System ◽  
Behavior Prediction ◽  
Real World Data ◽  
Manifold Embedding ◽  
Latent Space ◽  
Hidden Layer

A person experiences different stages throughout the life, causing dramatically varying behavior patterns. In applications such as online-shopping, it has been observed that customer behaviors are largely affected by their stages and are evolving over time. Although this phenomena has been recognized previously, very few studies tried to model the life-stage and make use of it. In this paper, we propose to discover a latent space, called customer-manifold, on which a position corresponds to a customer stage. The customer-manifold allows us to train a static prediction model that captures dynamic customer behavior patterns. We further embed the learned customer-manifold into a neural network model as a hidden layer output, resulting in an efficient and accurate customer behavior prediction system. We apply this system to online-shopping recommendation. Experiments in real world data show that taking customer-manifold into account can improve the performance of the recommender system. Moreover, visualization of the customer-manifold space may also be helpful to understand the evolutionary customer behaviors.

scholarly journals South African generation-X online shopper satisfaction and their repurchase intentions

2016 ◽  
Vol 13 (3) ◽  
pp. 371-379 ◽  
Author(s):  
Jobo Dubihlela ◽  
Difference Chauke
Keyword(s):  
Customer Satisfaction ◽  
South African ◽  
Social Exchange ◽  
Generation X ◽  
Online Shopping ◽  
Target Population ◽  
Jel Classification ◽  
Future Research ◽  
Repurchase Intentions ◽  
Brick And Mortar

The growth of online shopping channels gradually forces brick and mortar retailers to explore the importance of online shopping trends and online customer behavior. While maintaining customer satisfaction has been recognized as one of the essential factors for business survival and growth, this has not been sufficiently explored for online shopping platforms. Understanding what online constructs appeal to generation-X consumers is critical for organization that would want to pursue virtual business platforms. From a brief literature review in this study, it could be said that online customer satisfaction and its influences on online repurchase intentions in the South African retailing environment remain sparsely researched. Therefore, this study seeks to analyze the dimensions of online customer satisfaction and regress the online satisfaction dimensions on repurchase intentions of generation-X consumers. An attempt is made to apply the theory of planned behavior and social exchange in the adapted conceptual of the study. These theories are deemed to provide an appropriate theoretical grounding to this study. The target population was South African generation-X online consumers in Gauteng. A total of 377 questionnaires were received for data analysis. Implications of the research findings are discussed and limitations and future research directions are provided. Keywords: online shoppers, online customer satisfaction, repurchase intentions, generation-X consumers, South Africa. JEL Classification: M1, M30, M31, L10

scholarly journals Evaluation of Strategies to Reduce the Cost Impacts of Flight Delays on Total Network Costs

Aerospace ◽  
2020 ◽  
Vol 7 (11) ◽  
pp. 165
Author(s):  
Judith Rosenow ◽  
Philipp Michling ◽  
Michael Schultz ◽  
Jörn Schönberger
Keyword(s):  
Trajectory Optimization ◽  
Economic Cost ◽  
Cost Driver ◽  
Cost Index ◽  
Flight Delays ◽  
Cost Component ◽  
Effective Strategies ◽  
Network Costs ◽  
The Cost ◽  
Hub Airport

Competitive price pressure and economic cost pressure constantly force airlines to improve their optimization strategies. Besides predictable operational costs, delay costs are a significant cost driver for airlines. Especially reactionary delay costs can endanger the profitability of such a company. These time-dependent costs depend on the number of sensitive transfer passengers. This cost component is represented by the number of missed flights and the connectivity of onward flights, i.e., the offer of alternative flight connections. The airline has several options to compensate for reactionary delays, for example, by increasing cruising speeds, shortening turnaround times, rebookings and cancellations. The effects of these options on the cost balance of airline total operating costs have been examined in detail, considering a flight-specific number of transfer passengers. The results have been applied to a 24-h rotation schedule of a large German hub airport. We found, that the fast turnaround and increasing cruise speed are the most effective strategies to compensate for passenger-specific delay costs. The results could be used in a multi-criteria trajectory optimization to find a balance between environmentally-driven and cost-index-driven detours and speed adjustments.

Changing the face of retail: Where fashion meets technology

2016 ◽  
Author(s):  
Nadire Cavus ◽  
Rudo Muriel Munyavi
Keyword(s):  
Online Shopping ◽  
Online Marketing ◽  
Mobile Technologies ◽  
The Internet ◽  
Fashion Industry ◽  
Brick And Mortar ◽  
The Face ◽  
Similar Area ◽  
Fashion Designers ◽  
Technology Specialists

Prior to the introduction of mobile technologies and the internet, the manual system of going to a brick-and-mortar store to buy clothing was boring and tiresome as customers would spend hours moving from shop to shop trying to find the exact type of outfit they are looking for. The assimilation of technology in fashion designing and online marketing of clothing is marking an incredible venture in the fashion industry. Due to improved security features of online purchasing a lot of people now prefer buying clothing online since it saves time and online shopping provides variety at a click. This paper reviews several ways in which technology is transforming the fashion industry.  However this subject has not been researched in detail therefore there is a missing gap in the literature. We hope that this paper will fill the gap in the literature in order to review the role that technology is playing in the fashion industry. Information provided in this paper is beneficial to fashion designers, entrepreneurs in the fashion industry, information technology specialists as well as other researchers interested in a similar area of study.Keywords: Technology, fashion, virtual fitting room, wearable technology, virtual wardrobe.

scholarly journals Modelling and forecasting the spread tendency of the COVID-19 in China

2020 ◽  
Author(s):  
Deshun Sun ◽  
Li Duan ◽  
Jianyi Xiong ◽  
Daping Wang
Keyword(s):  
Mathematical Model ◽  
Removal Rate ◽  
High Accuracy ◽  
Error Rates ◽  
Peak Time ◽  
Model Data ◽  
Key Factors ◽  
Effective Strategies ◽  
Forecasting Error ◽  
Modelling And Forecasting

Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies to prevent the disease, an improved SEIR model was established. Parameters of our model were estimated based on collected data that issued by the National Health Commission of China (NHCC) from January 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors influencing the epidemic were explored through modulation of parameters, including the removal rate, the average number of the infected contacting the susceptible per day and the average number of the exposed contacting the susceptible per day. The correlation of the infected is 99.9% between established model data in this study and issued data by NHCC from January 10 to February 15. The correlation of the removed is 99.8%. The average forecasting error rates of the infected and the removed are 0.78% and 0.75%, respectively, from February 16 to March 3. The peak time of the epidemic forecast by our established model coincided with the issued data by NHCC. Therefore, our study established a mathematical model with high accuracy. The aforementioned parameters significantly affected the trend of epidemic, suggesting that the exposed and the infected population should be strictly isolated. If the removal rate increases to 0.12, the epidemic will come to an end on May 25. In conclusion, the proposed mathematical model accurately forecast the spread tendency of COVID-19 in China and the model can be applied for other countries with appropriate modifications.

PV Array Mathematical Model Optimization Based on Monitoring Data

2013 ◽  
Vol 376 ◽  
pp. 336-340 ◽  
Author(s):  
Qian Wen Zhong ◽  
Yang Xu ◽  
Jie Yang ◽  
Zhuo Meng
Keyword(s):  
Mathematical Model ◽  
Detection System ◽  
Monitoring Data ◽  
Model Optimization ◽  
Solar Panels ◽  
Photovoltaic Array ◽  
Pv Array ◽  
Photovoltaic Power ◽  
The Mathematical Model ◽  
Generating System

The type of Solar panels in photovoltaic power generating system is generally photovoltaic array. On the basis of the photovoltaic array mathematical model for engineering , using the mathematical software MATLAB Simulink tool to build a photovoltaic array simulation model and utilizing monitoring data acquired by the detection system-Sunny Sensor Box-for Donghua University photovoltaic power generating system, the mathematical model of the PV array for engineering is optimized and the optimization includes linear and natural exponential optimization. Furthermore, higher accuracy of the optimized models is validated.

scholarly journals When children express their preferences regarding sales channels

2014 ◽  
Vol 42 (11/12) ◽  
pp. 1018-1031 ◽  
Author(s):  
Jacques Boulay ◽  
Brigitte de Faultrier ◽  
Florence Feenstra ◽  
Laurent Muzellec
Keyword(s):  
Online Shopping ◽  
Dominant Role ◽  
Content Type ◽  
Product Availability ◽  
Sales Channels ◽  
Advantages And Disadvantages ◽  
Young Consumers ◽  
Brick And Mortar ◽  
Competitive Prices ◽  
Online Stores

Purpose – The purpose of this paper is to investigate the preferences of children under the age of 12 regarding sales channels: how young consumers perceive online vs offline shopping in terms of advantages and disadvantages. Within a cross channel perspective, it also analyses the connections they make between brick-and-mortar and online stores. Design/methodology/approach – Results are drawn from an exploratory and qualitative study based on a multi-category approach. In all, 62 children (34 girls and 28 boys) aged six to 12 years were interviewed about the advantages and disadvantages of each channel for shopping; how/where they would prefer to shop and why; and the links they make between a brand’s physical store and an online store. Findings – Traditional sales outlets are more popular with six to 12 year olds than online shopping. Physical stores offer variety and instant gratification. Products can be tried out and tested on-site, making the offline retail experience a fun activity. Conversely, children express a very negative perception of e-retailing, which they often consider to be dishonest, offering limited choice at higher prices. When shopping online, delivery time can be a deterrent. Last but not least, no cross-channel shopping perceptions were found. Practical implications – Several results from this study can inform marketing practices at retailers’ headquarters. Store assortment, product availability and store atmospherics are central to the success of offline shopping among six- to 12-year-old children. Retailers should find ways to transfer this relational approach to their online strategy. In the meantime, they must deliver the same basic promises as in stores: a wide choice and competitive prices, no shortage of products and no late delivery. Originality/value – This study adds to the existing body of knowledge on children’s consumer behaviour in three ways. First, it provides new insight into how children perceive not the internet per se but online shopping. Second, it confirms that stores still play a dominant role in shaping the image of a retail brand, from an early age. Third, it suggests that the cross-channel perspective may not apply to very young consumers.

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