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The challenges of using forecasting techniques in logistics

Quantitative forecasting techniques refers to the approaches of forecasting used for examining the future trends by analysing the historical data. These forecasting techniques are applied through static methods like time series forecasting and casual forecasting (Spedding & Chan, 2010). The casual forecasting is conducted using simple or multiple regression models. On the other hand, casual forecasting is executed through the use of autoregressive moving average models. In logistics, time series forecasting focuses on analyzing the change in business strategies over a period of time. This forecasting is done using moving average and exponential smoothing which uses mathematical formulas to identify the forthcoming claim of the consumers addressed (Dombi, et al., 2018).

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Maslow’s hierarchy of needs to understand the social characteristics of online customers

Maslow’s hierarchy of needs focuses on the basic requirement and demand for the individuals utilized by the marketers to identify the customer buying pattern (Yan, et al., 2016). The components of the theory or basic needs of the human being comprise:

  • psychological needs,
  • safety and security needs,
  • love and belonging need,
  • self-esteem and,
  • self-actualization needs.

Identifying buying behaviours

The burdens and necessities of diversified customer range have been distributed through the type of products which help the marketers to select a particular group of target consumers.

The feedback and the opinion of the customers are evaluated in a structured manner to deliver a product or service to accomplish a business goal (Karahanna, et al., 2018). Maslow’s hierarchy helps to identify the difference between the external environments that affect an individual’s behaviour, trait and attributes in choosing a brand. The psychological and social demand of the customers remain fulfilled effectively by evaluating the model and the price of the products remain aligned with the regular range as it covers the basic need of human being (Harrigan & Commons, 2015).

The values provided to the consumer for sales is considered as an important factor for the marketers in a marketing strategy (Li, et al., 2017). On the other hand, the sentimental judgment of the customers remains evaluated through the Maslow’s need of hierarchy to demonstrate a pattern in the buying behaviour (Bouzenita & Boulanouar, 2016).

Case example of the use of Maslow’s hierarchy of needs

Pharmeasy, an E-commerce website and application serving pharmacy products, medical equipment and booking of medical tests (Pharmeasy, 2019). Pharmeasy has been able to deliver medicines at low cost compared to the physical stores and meet the basic psychological needs of customers. Before, the start of online pharmacy stores, medicine or conducting the medical tests relied on the traditional stores and diagnostic centres. The firm has identified lack of proficiency for understanding the name of the medicines ordered. So, they have taken the approach of uploading a copy of the prescription to identify the medicines.

Pharmeasy had offered a 40% discount on the first five orders to its new users. This addressed the consumer buying behaviour based on the Maslow theory. These types of demands and needs are frequent in nature and customer retention has become more simplified through their quick delivery and pricing (Lee & Hanna, 2015). The queries and doubts of the customers also remain fulfilled and are often replied over social media platforms fulfilling the need of social characteristics of online consumers.


  • Bouzenita, A. & Boulanouar, A., 2016. Maslow’s hierarchy of needs: An Islamic critique. Intellectual Discourse, 1(24), pp. 25-28.
  • Gbededo, M. & Liyanage, K., 2018. Identification and alignment of the social aspects of sustainable manufacturing with the theory of motivation. Sustainability, 3(10), p. 852.
  • Harrigan, W. & Commons, M., 2015. Replacing Maslow’s needs hierarchy with an account based on stage and value. Behavioral Development Bulletin, 1(20), p. 24.
  • Indiatimes, 2018. e-commerce-players-brace-for-big-battle-over-online-pharma/. [Online] Available at:
  • Karahanna, E., Xu, S., Xu, Y. & Zhang, N., 2018. The needs–affordances–features perspective for the use of social media. Management Review, 2(26), pp. 298-310.
  • Lee, J. & Hanna, S., 2015. Savings goals and saving behavior from a perspective of Maslow’s hierarchy of needs. Journal of Financial Counseling and Planning, 2(26), pp. 14-18.
  • Li, Y., Zhang, H. & Huang, W., 2017. Gender differences in information quality of virtual communities: a study from an expectation-perception perspective. Personality and individual differences, 1(104), pp. 224-229.
  • Missimer, M., Robèrt, K. & Broman, G., 2017. A strategic approach to social sustainability–Part 1: exploring the social system. Journal of Cleaner Production, 1(140), pp. 32-41.
  • Pharmeasy, 2019. About Us. [Online] Available at: Us/ [Accessed 08 August 2019].
  • Yan, Z., Wang, T., Chen, Y. & Zhang, H., 2016. Knowledge sharing in online health communities: A social exchange theory perspective. Information & Management, 5(53), pp. 643-653.

Application of Marshallian economics as an online shopping strategy

Online shopping facilitates buying and selling of products and services beyond the geographical periphery. The array of interdependence and parameters that emerge from coalescence among consumer purchasing behaviour, economics and human behaviour lead to the emergence of the Marshallian economics model. The advantage of this model is that it provides an idea of a marketplace consumer behaviour (Omotoyinbo et al., 2017).

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Using Psychoanalytic theory and Pavlovian theory by online marketers

The Marshallian Economic was propounded by Alfred Marshall in order to propose the buying preferences of customers in the situation of product purchase (Biswas, 2012). Based on the gaps found in the Marshallian Economics, Psychoanalytic Theory and Pavlovian Theory of customer behaviour model were developed to fill them. The customers are given utmost preference in this economic model. Moreover, the model finds aggressive use in e-retailing services.

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Supply chain costs management models

Supply chain cost management is the task of controlling the operational cost in order to enhance the profit margin of a business. It involves all activities of logistics and supply chain such as stocking, distribution, processing, packaging, procurement, and handling (Silva, Gonçalves, & Leite, 2014). Supply chain cost management has become very crucial for businesses due to the intensifying market competition (Lai & Cheng, 2016).

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Quantitative and qualitative forecasting techniques in logistics management

Demand forecasting is defined as an approach used for analyzing future demand in comparison to the previous ones. The purpose of demand forecasting is to apply future planning and decision in the domain of finance, logistics, operation and sales. Companies use a qualitative method of forecasting to analyse and evaluate the opinion of experienced staff rather than focusing on numerical values (Dwyer, et al., 2012). These methods are used for predicting any short term or internal forecasting on the basis of summative feedback of departmental heads. On the other hand, quantitative forecasting technique deals with numerical data focus on projection of trends on the basis of historical figures of the business. This method of forecasting is consistent and useful for long term scenario planning of the company.

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The use of the Veblenian socio-psychological model for online marketing

Traditionally, consumer behaviour theories emerged from different psychological, anthropological and economic theories as marketers applied them to understand consumer wants. The Psychoanalytic theory classifies human psyche into three dimensions:

  1. Id,
  2. Ego, and
  3. Superego.
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Factors affecting the online buying behaviour of Millennials and Gen Z

The buying process goes through a series of steps, leading to a purchase decision (Ordun and Ordun, 2015). The series of steps that lead to either of the two outcomes is very important for marketers to understand to avoid negative outcomes. To understand these steps, marketers should first assess consumer buying behaviour (Sivakumar and Gunasekaran, 2017). Both millennials (25-39 years old) and Gen Z (4-24 years old) are socially aware and technology-savvy generations.

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