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Business to Consumer (B2C) – Definition

Cite this article as:"Business to Consumer (B2C) – Definition," in The Business Professor, updated September 24, 2019, last accessed June 5, 2020, https://thebusinessprofessor.com/lesson/business-to-consumer-b2c-definition/.


Business-to-Consumer (B2C) Definition

Business-to-consumer (B2C) refers to direct commerce activities between a business and its customers. It is a business model in which businesses sell their goods and services to their customers without the need for an intermediary. B2C companies are interested in selling their products and rendering their unique services directly to the end-users.

The term Business-to-consumer (B2C) became popular in the late 1990s. B2C also refers to internet transactions between a business and its customers. This is also called e-commerce, this type of commerce is done purely through the internet or electronic channels.

A Little More on What is Business-to-Consumer

In many industries and countries, many businesses operate using the business-to-consumer (B2C) model. This means that sales of goods and services are offered directly to customers who need them. This business or sales model was first used in 1979, Michael Aldrich was the first business owner to use the model to reach out to customers.

Examples of businesses that use the B2C model are bars, restaurants, cinemas, shopping malls and others. There are some businesses that engage the B2C model via the internet, these businesses sell their goods and services to their customers through the e-commerce channel.

It is important to state that B2C companies have a good customer relations management model in place. This will help them maintain good relationships with their customers and in the end drive sales growth and profit margin. At a certain period, B2C businesses experienced a decline in the interest of investors in the model which in turn created a reduction in investment and funding by venture capitalists. Despite this trying period, some B2C businesses survived and became reputable amongst other B2C businesses, examples of such businesses are Amazon and Priceline.

Reference for “Business-to-Consumer (B2C)”

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Academic research for “Business-to-Consumer (B2C)”

Key dimensions of businesstoconsumer web sites, Ranganathan, C., & Ganapathy, S. (2002). Key dimensions of business-to-consumer web sites. Information & Management39(6), 457-465. The rapid growth in the electronic commerce over the Internet has fuelled predictions and speculations about what makes a business-to-consumer (B2C) web site effective. Yet, there are very few empirical studies that examine this issue. We examined the key characteristics of a B2C web site as perceived by online consumers. Based on a questionnaire survey of 214 online shoppers, we empirically derived four key dimensions of B2C web sites: information contentdesignsecurity, and privacy. Though all these dimensions seem to have an impact on the online purchase intent of consumers, security and privacy were found to have greater effect on the purchase intent of consumers. The implications of the findings for online merchants are discussed.

The role of system trust in businesstoconsumer transactions, Pennington, R., Wilcox, H. D., & Grover, V. (2003). The role of system trust in business-to-consumer transactions. Journal of Management Information Systems20(3), 197-226. It has been argued that the buyer’s trust of the vendor is a critical precursor to a transactional relationship in an e-commerce environment. This study uses an experimental survey to test a model that includes a number of factors such as trust mechanisms, “system trust,” and vendor reputation. The results suggest that one trust mechanism, vendor guarantees, has a direct influence on system trust. Further, within e-commerce situations, system trust plays an important role in the nomological network by directly affecting trust in vendors and indirectly affecting attitudes and intentions to purchase. These results held in the case of both firms with and without an established reputation. The results demonstrate the importance of interventions such as self-reported vendor guarantees that affect system trust in enabling successful e-commerce outcomes.

Current technological impediments to businesstoconsumer electronic commerce, Rose, G., Khoo, H., & Straub, D. W. (1999). Current technological impediments to business-to-consumer electronic commerce. Communications of the AIS1(5es), 1.

Assessing service quality on the web: evidence from businesstoconsumer portals, Gounaris, S., & Dimitriadis, S. (2003). Assessing service quality on the web: evidence from business-to-consumer portals. Journal of Services Marketing17(5), 529-548. The article explores the quality dimensions that the visitors of national and foreign business‐to‐consumer portals use to assess the performance of their service offering. Based on the SERVQUAL model and previous research on Web site evaluation and quality, the paper identified three quality dimensions that proved to be stable across sites’ nationality and user profiles. Several implications are drawn from these results for both Web site marketers and future academic research.

The influence of relationship marketing tactics on customer’s loyalty in B2C relationship–the role of communication and personalization, Halimi, A. B., Chavosh, A., & Choshalyc, S. H. (2011). The influence of relationship marketing tactics on customer’s loyalty in B2C relationship–the role of communication and personalization. European Journal of Economics, Finance and Administrative Science, (31), 49-56. Relationship marketing develops marketing productivity and generates mutual values for both customer and company through growing marketing effectiveness. This study proposes a model to link key relationship marketing tactics to the customers’ relationship satisfaction and customer loyalty. This framework is evaluated from the customer perspective in a business-to-consumer (B2C) setting across the tour and travel industry in Singapore. The Model demonstrates that the customer’s loyalty is basically formed by the variables of communication and personalization. This study intends to evaluate the impact of personalization and communication on customer’s relationship satisfaction and then determines the impact of customer’s relationship satisfaction on customers’ loyalty. Meanwhile, in order to conduct this study, primary data has been collected by a properly designed questionnaire which was distributed among customers in 5 different tour and travel agency in Singapore and the secondary data has been collected through online data base such as Ebsco, Emerald and Science Direct. Afterwards, SPSS (17.0) tool has been used in order to evaluate the relationship between variables of the model. Accordingly, correlation analysis and regression results determined the relationship between the variables. Based on the results, there are significant relationships between personalization and communication as independent variables and customers’ relationship satisfaction as dependent variable. So, high level of communication and personalization increase the customers’ relationship satisfaction. Meanwhile, the results also show that there is significant relationship between customers’ relationship satisfaction on customers’ loyalty. Consequently, as customers’ relationship satisfaction increases, customers’ loyalty also enhances. Ultimately, personalization and communication increases the customer’s loyalty by enhancing customer’s relationship satisfaction.

Analysis and design of businesstoconsumer online auctions, Bapna, R., Goes, P., & Gupta, A. (2003). Analysis and design of business-to-consumer online auctions. Management Science49(1), 85-101. Business-to-consumer online auctions form an important element in the portfolio of mercantile processes that facilitate electronic commerce activity. Much of traditional auction theory has focused on analyzing single-item auctions in isolation from the market context in which they take place. We demonstrate the weakness of such approaches in online settings where a majority of auctions are multiunit in nature. Rather than pursuing a classical approach and assuming knowledge of the distribution of consumers’ valuations, we emphasize the largely ignored discrete and sequential nature of such auctions. We derive a general expression that characterizes the multiple equilibria that can arise in such auctions and segregate these into desirable and undesirable categories. Our analytical and empirical results, obtained by tracking real-world online auctions, indicate that bid increment is an important factor amongst the control factors that online auctioneers can manipulate and control. We show that consumer bidding strategies in such auctions are not uniform and that the level of bid increment chosen influences them. With a motive of providing concrete strategic directions to online auctioneers, we derive an absolute upper bound for the bid increment. Based on the theoretical upper bound we propose a heuristic decision rule for setting the bid increment. Empirical evidence lends support to the hypothesis that setting a bid increment higher than that suggested by the heuristic decision rule has a negative impact on the auctioneer’s revenue.

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