The Implications of Online Shopping for Sustainability Considering Different Stages of Consumer Decision-making Process
Every marketer urges to be ahead of the curve. To do so, research on consumers’ decision-making is a cornerstone and can be conceptualized in several forms, be those multidimensional scaling of the five stages of a consumer’s decision-making process or conjoint measurements that verbalize subjects of consumers when it comes to their purchasing reality. Such reality has changed throughout the years. Online shopping has not only transformed the dynamics of consumer flows at different timelines, scales, and shopping places, but has also tackled the problem of modelling shopping changes when considering multiple variables (Baker, 16). This change of style structures a new shopping orientation, which defines the individual’s attitude towards his/her shopping activity, encompassing the situation as the most decisive factor rather than his/her personality trait. Online shopping orientation has traditionally been rooted in retail shopping and accordingly transformed the e-commerce through its interactive feature of “convenience-oriented shopping” (Kim and LaRose, 1). This leads internet users to pursue their
shopping activities online, save time and contribute to an overall increasing shopping utility. Although conceptually distinct, consumers do not usually engage in such activity for any random product; instead, they mostly shop when making a choice in complexity (Hairong Li et al, 1).
Parallel to a consumer’s stages of decision making, the multi-functionality of online shopping can also be detailed by the marketing channels that include but are not limited to: information, negotiation, ordering, and payment. The volume and quality of information is crucial when consumers consider making final choices regarding their shopping activities. This introduces the
“channel accessibility” which can only be described as an efficient mixture of time and effort within the channel category (information, negotiation, etc.) or between different categories (Hairong Li et al, 1). Built upon a sustainability outlook between consumers and buyers, the ecommerce industry has matured and has improved its resource efficiency. This maturity aroused
a great interest among researchers and professionals to differentiate between the implications and opportunities, leading to a visible clutter, which in the process pressures profitability and indicates a need for innovation to make the business models more sustainable.
Sustainability basically refers to an enduring balance that grant humans to live, produce and work accordingly to the well-established norms, environmentally, socially, or economically wise. Its detailed interpretation lies upon its domains that include the material, economic and social domains that all embody the sustainability framework and its ties with e commerce (Patch,
1). It is more than clear now the need for brands to meet consumers’ thirst for favorable platforms that introduce timely deliveries and built-up trust, furnished by a relatively well-known intermediary. According to SustainAbility, an environmental think tank and consultancy, which
drives business impact and trends reports related to sustainability, Chinese e commerce in 2016 accounted 15% of total private consumption, compared to having 3% in 2010 (Annual Trends Report, SustainAbility). US is experiencing a similar trend as well, where total e-commerce sales for 2017 were estimated at $453.5 billion, an increase of 16 percent compared to 2016 (U.S Department of Commerce, 1). But, as e-commerce continues to bloom, so do the challenges across the supply chain, all of which can threaten the balance of the industry. From the business perspective, an important ring of this supply chain is undoubtedly packaging and delivery systems put in place. Retailers’ distribution centers and networks are still mostly geared towards
pre-digital store model, not designed to fulfill single-item orders to precise location set by the consumer within a shorter time frame. Given the fact that, online and traditional retailers have different supply chains to answer the consumer’s demand, each step of the search, purchase or return could be described differently.
To a traditional shopper, the shopping behavior including the above mentioned phases highlights visiting a brick-and-mortar store to accommodate each of the phases, while an online shopper or “cybernaut” performs all these steps online (Weideli, 3). According to Dimitri Weideli, a consumer behaviorist and his environmental analysis of online shopping, the carbon footprint of the buying process highly depends on the product, packaging, transportation, energy consumption and information flow (4). Having all this in mind, the “cybernaut” results on a lower environmental impact compared to the traditional shopper, as long as the later one halts the speedy delivery (Weideli, 5). Because of their centralized sub-services being delivery and transportation systems, online retailers tend to have a more controlled environmental impact and should always take into account additional insight such as urban density and compactness, item bundling and smart shipping containers so to develop a more tailored approach towards environment.
Beyond current chain implications, there is a different approach by individuals whose powerful utilitarian and hedonistic motivations define the regularity of one’s online cart use and boost the conversion rate of shopping-to-buying through online price promotions, the need of additional information, shopping items structure and pure entertainment. (Close and Kukar-Kinney, 1). Most of the decision-making process starts with problem recognition and search process. This lack of a good or service perceived by the consumer, develops a need or a want that he or she wishes to satisfy. To do that online, there are two dominant determinants of information: socio-cultural influences and website marketing application through commercials and promotions, so as to inform and grab the attention of the consumers upon the detailed attributes of the product (Wei, 113). To establish a trusting customer relationship, one compares products or services on factors that are deemed important from both external and/or internal by nature.
These inputs, motivational or psychological highlighted by perception, personality, attitude, emotions, product characteristics and situational factors, are used to evaluate the alternatives prior of making the decision (Wei, 113–114). As a final stage that brings out the output of shopping activities, we have two post-decision features: the ongoing purchase behavior and post-purchase interpretation (Wei, 114). If the latter is positive, the purchasing action will be repeated, thus drawing to the product embracement. The same process continues in a closed loop, which again causes the consumers to choose between their shopping options. All this is geared to help marketers better understand the process behind a purchase. To businesses, an uneducated online market audience highlighted by low search and selection costs mean low retention rates, an implication which they need to mitigate. Moreover, the search methods and the ranking of results are not always cleared out for the consumer to purchase something off-book or non-random and do determine the tendency of people to shop online.
In that sense, there is a higher costumer intention to shop online when purchasing commonplace and well-known products (Wei, 114). The decision
support system for online shopping is also highlighted by the consumer trust in intermediary B2C e-marketplaces. Lack of physical interactions with products (e.g. health-care, car, or car parts) makes it more difficult to assess them, which in the process causes a non-trusting relationship between the buyer and the seller. According to Nielsen, a global measurement, and data analytics company on providing an overview of consumers and markets, only 4% of car hire were purchased online in 2016 (Wei, 114). When to this is added an unknown third-party involvement that leads to complications in transaction, it creates an uncertainty to manage the perceived risks of online shopping.
In a comparative analysis with brick-and-mortal shopping behavior, there are evident reasons why a relatively large pool of consumers opts to shop there versus online. Benefits include compatibility with schedule, ease, and better pricing. Still, consumers are growing familiarity and comfort with online outlets, regardless their lack of immediacy and added delivery and pickup fees. Consumers consider the traditional shopping a well-established and fitting experience and want the same shopping basis structure with online shopping. To help realize their imaginations, a customer design system would be an immediate solution which could collect consumers’ public data, to provide them with objective options to specialize on their choices and be separated in their most prolific segments. This segmentation, structured by Nielsen to lay out the dynamics of the online retail landscape is grouped into several “shopping extremes”: technology adverse, non-planners and digital advocates among others (Total Consumer Report, 8). Consumers falling under the first category are characterized with low trust and non-technical
skills, having small online basket sizes and only shop online for products not found in stores, while the non-planners seek little shopping enjoyment from online retailers (Total Consumer Report, 8). The positive extreme of the latest group, the digital advocates are driven and proactive by the advantage and accessibility of online shopping, and usually have the highest index of the online purchase frequency (Total Consumer Report, 7).
In conclusion, by encompassing consumer behavior factors, we are presented with enough explanatory power for relationship quality between consumers and online sellers. A successful and long-term relationship in the online retailing context is a consequence of trust, and a well-educated shopping audience regarding online retail platforms, which mitigates the insecurity of online shopping environment associated by the detailed implications previously explained.
*References are to be provided upon readers’ requests.