Mass Communication Project Topics

Effect of Social Media Communications on Students’ Buying Behaviour Towards Smartphones in Calabar

Effect of Social Media Communications on Students’ Buying Behaviour Towards Smartphones in Calabar

Effect of Social Media Communications on Students’ Buying Behaviour Towards Smartphones in Calabar

Chapter One 

Objective of the study

The main objective of this study is to examine the effect of social media communications on students’ buying behaviour towards smartphones in Calabar. Its specific objectives are to;

  1. assess the effect of Facebook on students’ buying behaviour towards smartphones in Calabar;
  2. determine the effect of YouTube on students’ buying behaviour towards smartphones in Calabar;
  3. examine the effect of WhatsApp on students’ buying behaviour towards smartphones in Calabar.




Theoretical framework

Rational choice theory

The centrality of the rational choice model in economic analysis means that it is important to be aware of its role and limits. There is a long tradition of research marshalling experimental and empirical evidence that is in conflict with the most basic rational choice model. And indeed the last decade has seen a growing movement that questions the model’s assumptions and seeks to incorporate insights from psychology, sociology and cognitive neuroscience into economic analysis. A main criticism of the most basic rational choice model is that real-world choices often appear to be highly situational or context-dependent. The way in which a choice is posed, the social context of the decision, the emotional state of the decision-maker, the addition of seemingly extraneous items to the choice set, and a host of other environmental factors appear to influence choice behavior. The existence of the marketing industry is testament to this, and many other examples are possible. To take a simple one, the presence of a tempting chocolate cake on the dessert menu might make you feel good about sharing an order of apple pie, when you might have ordered fruit if you hadn’t been tempted by the cake. Strictly speaking, there is little formal problem in allowing preferences to depend on context (it is even possible to incorporate cues and temptations). That being said, the strength of the rational choice model derives from the assumption that preferences are relatively stable and not too situation-dependent. This is the source of the theory’s empirical content, because it allows us to observe choices in one situation and then draw inferences about choices in related situations. Such inferences become problematic if preferences are highly sensitive to context. A further criticism of the rational choice model is that in reality, many choices are not considered. Rather they are based on intuitive reasoning, heuristics or 22 instinctive visceral desires. That people rely on intuition and heuristics is not surprising. Given that people have limited cognitive capacity, there is simply no way to reason through every decision. Arguably, instinctive judgement may often mimic preference maximization, particularly in familiar environments. When people rely on heuristic reasoning or intuition in unfamiliar situations, however, the result can be striking departures from the sort of behavior predicted by rational choice models. Particularly surprising behavior can result when people in unfamiliar situations are given inappropriate contextual clues. For instance, Ariely, Loewenstein and Prelec (2003, QJE) report an experiment in which they showed students in an MBA class six ordinary products (wine, chocolate, books, computer accessories). The items had an average retail price of about $70. Students were asked whether they would buy each good at an amount equal to the last two digits of their social security number. They were then asked to state their valuation for each good. In spite of the familiarity of the products, students’ reported valuations correlated significantly with the random final digits of their social security number. That is, it appears that the students had no firm valuation in mind and “anchored” their value to an essentially arbitrary suggestion (the social security number).2 Interestingly, Ariely, Loewenstein and Prelec go on to show that once people have fixed on a valuation, they respond to price changes, and other changes, in ways that are consistent with the rational choice model. The authors label this behavior “coherent arbitrariness.” A second example that has attracted much attention is the role of default choices. For instance, Madrian and Shea (2001, QJE) provide evidence that enrollment in employer-sponsored 401-K retirement plans (an extremely good deal for most workers by objective criteria) is highly sensitive to whether workers must “opt-in” or “opt-out” of the plan. Another example along these lines comes from organ donations. In the United States, people must “opt-in” to become a donor by signing up when they get their driver’s license. There is a dire shortage of organ donors relative to needy recipients. In Spain, people must “opt out” and the demand-supply situation is reversed. The behavior in these examples is hard to square happily with the most basic preference maximization approach. Once one tries to move away from optimization, however, modeling becomes a difficult challenge. That being said, there are models of decision-making that acknowledge people’s limited cognitive capacity. These models take a variety of forms: some assume that people make systematic “mistakes” or optimize only partially; others assume people used fixed learning rules, or “rules of thumb”. It is safe to say, however, that there is plenty of work left to be done in developing better “bounded rationality” models. In closing this section, it is worth emphasizing that despite the shortcomings of the rational choice model, it remains a remarkably powerful tool for policy analysis. To see why, imagine conducting a welfare analysis of alternative policies. Under the rational choice approach, one would begin by specifying the relevant preferences over economic outcomes (e.g. everyone likes to consume more, some people might not like inequality, and so on), then model the allocation of resources under alternative policies and finally compare policies by looking at preferences over the alternative outcomes. Many of the “objectionable” simplifying features of the rational choice model combine to make such an analysis feasible. By taking preferences over economic outcomes as the starting point, the approach abstracts from the idea that preferences might be influenced by contextual details, by the policies themselves, or by the political process. Moreover, rational choice approaches to policy evaluation typically assume people will act in a way that maximizes these preferences this is the justification for leaving choices in the hands of individuals whenever possible. Often, it is precisely these simplifications – that preferences are fundamental, focused on outcomes, and not too easily influenced by one’s environment and that people are generally to reason through choices and act according to their preferences – that allow economic analysis to yield sharp answers to a broad range of interesting public policy questions. The behavioral critiques we have just discussed put these features of the rational choice approach to policy evaluation into question. Of course institutions affect preferences and some people are willing to exchange worse economic outcomes for a sense of control. Preferences may even be affected by much smaller contextual details. Moreover, even if people have well-defined preferences, they may not act to maximize them. A crucial question then is whether an alternative model for example an extension of the rational choice framework that incorporates some of these realistic features  would be a better tool for policy analysis. Developing equally powerful alternatives is an important unresolved question for future generations of economists.





This chapter examines the various methods and procedures that will be adopted in carrying out this study.  These include the following: design of the Study, area of the study population of the Study, sample and sampling techniques, instrumentation, validation of the instrument, reliability of the instrument, method of data collection, method of data analysis and decision rule.

Design of the Study

The study adopted a descriptive survey research design in which questionnaire and other form of instrument for data collection was considered appropriate for data collection. This design was considered suitable for the study because of its ability to describe the behavior of a given group of people.

Area of the Study

The study was conducted in Calabar (also referred to as Callabar, Calabari, Calbari and Kalabar) is the capital of Cross River State, Nigeria. It was originally named Akwa Akpa, in the Efik language. The city is adjacent to the Calabar and Great Kwa rivers and creeks of the Cross River (from its inland delta). Calabar is often described as the tourism capital of Nigeria, especially due to several initiatives implemented during the administration of Donald Duke (1999–2007), which made the city the cleanest and most environmentally friendly city in Nigeria. Administratively, the city is divided into Calabar Municipal and Calabar South Local Government Areas. It has an area of 406 square kilometres (157 sq mi) and a population of 371,022 as at 2006 census.

Population of the Study

The population of the study consist all students of University of Calabar in Cross River State



This chapter presents the result and discussion of findings based on the following; answer to research question, test of hypotheses and discussion of findings.


This section presents the result of research questions and hypotheses used in the study. It started by answering the research questions and testing for the research hypotheses as follows.




It is important to ascertain that the objective of this study was on effect of social media communications on students’ buying behaviour towards smartphones in Calabar. In the preceding chapter, the relevant data collected for this study were presented, critically analyzed and appropriate interpretation given. In this chapter, certain recommendations made which in the opinion of the researcher will be of benefits in addressing the challenges of social media communications on students’ buying behaviour towards smartphones in Calabar


This study was on effect of social media communications on students’ buying behaviour towards smartphones in Calabar. Three objectives were raised which included: assess the effect of Facebook on students’ buying behaviour towards smartphones in Calabar, determine the effect of YouTube on students’ buying behaviour towards smartphones in Calabar and examine the effect of WhatsApp on students’ buying behaviour towards smartphones in Calabar. In line with these objectives, four research questions were formulated and answered. The total population for the study is 260 students of University of Calabar. The researcher used questionnaires as the instrument for the data collection. Descriptive Survey research design was adopted for this study.


The overall conclusion of the study is that social media drives consumers’ intention to buy. However, there is need to enhance the social media campaign so as to stimulate consumers’ interest using the correct social media variables. The study concludes that the most engaging social media variable is social media word of mouth. Viral communication on social networks circulates faster and are more believable than information generated by the company. In actual fact, the study concludes that company generated content negatively effect on student buying intention.


It is therefore recommended to companies in the mobile telephony industry to minimise their generated posts and promote user created posts and sponsored word of mouth marketing. The study also concludes that social media platforms in themselves do not drive intended purchase behaviour. Therefore, companies may run social media campaigns on any social platform.


  • Ajzen, I. (1975). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. 5978(91)90020-T
  •  Ajzen, I. and Fishbein. M. (1991). The theory of planned behaviour; Organisational Behaviour and Human Decision Processes. Journal of Theoretical and Applied Information Technology, 55(1), 33-54.
  • Alnsour, M., Ghannam, M. and Al-natour, R. (2018). Social media effect on purchase intention: Jordanian airline industry. Journal of Internet Banking and Commerce, 23(2), 3-17.
  •  Al-qasa, K., Isa, F. and Othman, S. (2013). Factors Affecting Intentions to Use Banking Services in Yemen. Journal of Internet Banking and Commerce, 18(2), 122-131.
  •  Bharucha, J. (2018). Social Media and Young Consumers Behavior. International Journal of Supply Chain Management, 7(6), 72-81.
  • Bruno, S. and Dariusz, D. (2013). The effect of social-media communication on consumer perceptions of brands. Journal of Economics and Management, 12(2), 1-21.
  • Campbell, C., Ludahn, N., and Zholnal, C. (2011). The differential effect of social media on consumer behavioral intention. Journal of Behavioural Studies, 14(2), 162-178.
  •  Collins, C. (2015). Business Research Methods, Principles and Practices. Lower Manhattan.
  • Diebes, H. and Iriqat, R. (2019). Social media as a strategic marketing communication tool in Palestinian mobile telecom companies – business to customers relationship perspective. International Review of Management and Marketing, 9(3), 31-40.
  • Econet Wireless (2020). Our social media activities. Available at: (Accessed: 03 March 2020).
  • Eqwubo, E. (2020). The effect of social media towards driving consumer intention in Ghana. International Journal of Business Administration and Economics, 4(2), 78-89.


WeCreativez WhatsApp Support
Our customer support team is here to answer your questions. Ask us anything!