The applications of social media in sports marketing

n the era of big data, sports consumer's activities in social media become valuable assets to sports marketers. In this paper, the authors review extant literature regarding how to effectively use social media to promote sports as well as how to effectively analyze social media data to support business decisions. Methods: The literature review method. Results: Our findings suggest that sports marketers can use social media to achieve the following goals, such as facilitating marketing communication campaigns, adding values to sports products and services, creating a two-way communication between sports brands and consumers, supporting sports sponsorship program, and forging brand communities. As to how to effectively analyze social media data to support business decisions, extent literature suggests that sports marketers to undertake traffic and engagement analysis on their social media sites as well as to conduct sentiment analysis to probe customer's opinions. These insights can support various aspects of business decisions, such as marketing communication management, consumer's voice probing, and sales predictions. Conclusion: Social media are ubiquitous in the sports marketing and consumption practices. In the era of big data, these ＂footprints＂ can now be effectively analyzed to generate insights to support business decisions. Recommendations to both the sports marketing practices and research are also addressed

Towards a conceptualization of casual protest participation: Parsing a case from the Save Roşia Montană campaign

There is currently an empirical gap in the literature on protest participation in liberal democracies which has overwhelmingly focused on Western Europe and North America at the expense of Eastern Europe. To contribute to closing that gap, this article reviews findings from a multi-method field study conducted at FânFest, the environmental protest festival designed to boost participation in Save Roşia Montană, the most prominent environmental campaign in Romania. By contrast to its Western counterparts, Romania has seen markedly lower levels of involvement in voluntary organizations that are a key setting for mobilization into collective action. Concurrently, experience with participation in physical protests is limited amongst Romanians. Specifically, the article probes recent indications that social network sites provide new impetus to protest participation as an instrumental means of mobilization. Dwelling on a distinction between experienced and newcomers to protest, results indicate that social network site usage may make possible the casual participation of individuals with prior protest experience who are not activists in a voluntary organization. Whilst this finding may signal a new participatory mode hinging on digitally networked communication which is beginning to be theorized, it confounds expectations pertaining to a net contribution of social network site usage to the participation of newcomers to protest

Digital literacy in religious studies

This article considers the relevance of the concept of ‘digital literacy’ within the context of the discipline of religious studies in higher education and reflects on its potential impact on notions of ‘graduateness’. It contemplates how digital technology can be integrated most effectively in learning design and reflects on the skills students need to be equipped with to recognise the challenges and opportunities of digital technology and understand its impact and role within the study of religions

To take or not to take the laptop or tablet to classes, that is the question

In recent decades, so-called mobile learning or m-learning has become a new paradigm in education as a consequence of technological advances and the widespread use of mobile devices to access information and for communication. In this context, this paper analyzes different profiles depending on students’ preferences for taking mobile devices (specifically tablets and/or laptops) to economics classes at the University of Seville (Spain). A survey-based field study of a sample of 412 students and the application of bivariate probit models show a low level of mobile device integration in teaching (devices taken to class by only 29.8% of respondents) with a slight predominance of laptops. The results also show differences between users of the two types of devices. Students who take their laptops to class usually live at home with their family, have already used them in pre-university levels, and are concerned about recharging their devices in class. However, although users who take their tablets to class also live with their parents, they are much more active on social network sites and more concerned about the quality of the internet connection. These findings enable the design of strategies to encourage students to attend class with their own mobile devices

Predicting the intention to use social media among medical students in the United Arab Emirates: A machine learning approach

Aim: The volume of research being conducted on the acceptance of social media platforms is rising. But the factors influencing the acceptance for academic reasons are still not properly identified. This study's goal is two-fold. Initially, by including Technology Acceptance Model (TAM) and external variables, analyze the students' intention to use social media networks. Secondly, to employ Machine Learning (ML) algorithms and Partial Least Squares-Structural Equation Modeling (PLS-SEM) to verify the proposed theoretical model. Methods: The focus of this research is to create a conceptual model by supplementing TAM with a subjective norm to assess students' adoption of social media in the classroom. Students currently at one private university in the United Arab Emirates (UAE) provided a sum of 627 acceptable questionnaire surveys out of 700 distributed corresponding to 89.6%. The collected data were evaluated using ML and PLS-SEM. Results: According to the research findings, students' intention to utilize social media networks for learning is significantly predicted by “subjective norms, perceived usefulness, and perceived ease of use”. These findings illustrated how crucial it is for students to feel capable and secure using social networks in their academic work. For validation using machine learning classifiers, the results showed that J48 (a decision tree) typically outperformed other classifiers. Conclusion: According to the empirical findings, "subjective norm," "perceived usefulness and ease of use" all significantly increase students' intention to use social networks for learning. These results were in line with earlier research on social network acceptability. Lawmakers and managers of social media platforms in education must therefore concentrate on those factors that are crucial to promoting education and enhancing students' capacity for developing and implementing successful social media applications. Conflicts of interest: None declared

Predicting the intention to use social media among medical students in the United Arab Emirates: A machine learning approach

Aim: The volume of research being conducted on the acceptance of social media platforms is rising. But the factors influencing the acceptance for academic reasons are still not properly identified. This study's goal is two-fold. Initially, by including Technology Acceptance Model (TAM) and external variables, analyze the students' intention to use social media networks. Secondly, to employ Machine Learning (ML) algorithms and Partial Least Squares-Structural Equation Modeling (PLS-SEM) to verify the proposed theoretical model. Methods: The focus of this research is to create a conceptual model by supplementing TAM with a subjective norm to assess students' adoption of social media in the classroom. Students currently at one private university in the United Arab Emirates (UAE) provided a sum of 627 acceptable questionnaire surveys out of 700 distributed corresponding to 89.6%. The collected data were evaluated using ML and PLS-SEM. Results: According to the research findings, students' intention to utilize social media networks for learning is significantly predicted by “subjective norms, perceived usefulness, and perceived ease of use”. These findings illustrated how crucial it is for students to feel capable and secure using social networks in their academic work. For validation using machine learning classifiers, the results showed that J48 (a decision tree) typically outperformed other classifiers. Conclusion: According to the empirical findings, "subjective norm," "perceived usefulness and ease of use" all significantly increase students' intention to use social networks for learning. These results were in line with earlier research on social network acceptability. Lawmakers and managers of social media platforms in education must therefore concentrate on those factors that are crucial to promoting education and enhancing students' capacity for developing and implementing successful social media applications

Building an innovation discontinuance model : the case of twitter

This dissertation seeks to extend Everett Rogers’s Diffusion of Innovations theory by examining social media users’ post-adoption behavior. Despite the rapid growth of social networking sites (SNSs), the rate of user discontinuance is staggering. Keeping users active and engaged has always been a crucial issue for SNSs. Prior diffusion research has largely focused on innovation adoption, whereas innovation discontinuance is overlooked. However, innovation discontinuance is a vital facet of the diffusion process. In the real world, only a few innovations become institutionalized while most end up being fads that most users discontinue quickly. While early studies approached discontinuance as a one-time, complete abandonment of an innovation, this study extends the concept by examining two types of discontinuance: intermittent and permanent. Intermittent discontinuers are users who leave an innovation for a break but resume the use at a later time; permanent discontinuers are those who have no intentions to return. This study takes a mixed-methods approach—combining a user survey with computational analyses of “big data” drawn from Twitter—to explore the differences between intermittent and permanent discontinuers in three dimensions: (1) their distinctive characteristics (demographic, behavioral, and psychographic), (2) reasons for discontinuance, and (3) decision processes. The concept of intermittent discontinuance leads to the development of a new post-adoption decision-making model, which accounts for discontinuers’ planned and unplanned readoption behavior. This cyclical, multi-stage model also provides a systematic framework to compare the behavior and cognitive reasoning between intermittent and permanent discontinuers at each phase of the post-adoption cycle. While prior studies employed both qualitative and quantitative research methods to examine discontinuance, few came up with clear and reliable ways to measure the timeframe of discontinuance and users’ reasons for discontinuance. To address the arbitrariness of determining what length of inactivity constitutes intermittent and permanent discontinuance, this study introduces a mathematical approach based on an innovation’s life cycle and its user base. To examine users’ reasons for discontinuance, this study refines and expands Rogers and Shoemaker’s replacement-disenchantment typology—by factors and by discontinuance typologies. While Rogers conceptualized the innovation-diffusion process as an uncertainty reduction process, this study suggests that post-adoption decision-making process is a disturbance-coping mechanism—a temporal settlement of the constant interplay between an innovation’s utilitarian performance and social media exhaustion. Intermittent discontinuance usually occurs due to information overloads. Permanent discontinuance tends to occur due to perceived innovation shortcomings and innovation replacement. This dissertation provides theoretical insights into the temporal instability of an innovation, and why and how an innovation is discarded or discredited. The findings contribute to an adequate comprehension of the entire innovation diffusion process, which also helps SNS providers develop tailor-made retention solutions to re-engage SNS users.Journalis

The Impact of Subjective and Objective Experience on Mobile Banking Usage: An Analytical Approach

This paper aims to investigate mobile banking (MB) usage through the theoretical lens of UTAUT model with its four pillars. The research model will be tested via a hybrid neural networks-based structural equation modeling (SEM-NN) to reveal significant factors. Universal structural modeling (USM) will be then utilized to find the hidden paths and nonlinearity in our research model. To the best of our knowledge, this is the first study to examine the role of subjective and objective experience on MB usage using a multi-analytical approach. Neural network (NN) and USM can identify the most significant determinants and hidden interaction effects, respectively. Thus, both techniques would help to complement SEM and increase our understanding of the influential factors on MB usage. Preliminary results are presented and discussed. Potential contribution and conclusion are communicated to both academia and industry

Social media and public policy

Introduction: Government and public service delivery is taking place in a changed world. A significant level of social, economic and political activity is now happening on the internet.As people buy and sell goods, search for information, browse the web and share their day–to–day experiences with colleagues, friends and family through social networks, they produce an enormous amount of data.The use of this data to develop insights is growing rapidly. In the private sector it is being used to enhance decision making, understand customer behaviour, improve operational efficiency and identify new markets.The new information environment also obliges government to develop new capabilities to understand the information available and to compete for attention and influence within it.Part of the challenge in embracing the digital age is that, in the midst of rapid change, it’s very difficult to know where to place your bets. We do not yet know exactly what access to large volumes of social data will mean for our society. It certainly will not present a panacea for long–standing social problems; but it can add another dimension to our understanding of them.This report considers whether social media data can improve the quality and timeliness of the evidence base that informs public policy. Can the myriad of human connections and interactions on the web provide insight to enable government to develop better policy, understand its subsequent impact and inform the many different organisations that deliver public services?The report is based on an evaluation of available literature and interviews with 25 experts from a number of disciplines. Given that developments in this field are at such an early stage, it aims to provide helpful signposts rather than definitive answers