Global Business and Social Technologies - Assignment Example

Global Business and Social Technologies Take Home Exam (School of Business IT and Logistics) Professor (Tutor) The Name of the School (University) The City and State Date Global Business and Social Technologies Take Home Exam (School of Business IT and Logistics) Question 1 It is no doubt that technology plays a dominant role in today’s society. From the personal to business contexts, technology is part of life. Technologies such as smartphones and computers are changing the way people accomplish different tasks. However, people have become over-dependent with technology or machines. Machines have undertaken the role of humans in numerous ways from avoiding face-to-face conversations to replacing human-to-human interactions. Clearly, there should be a line drawn as to what kinds of tasks we leave to machines, and what we should keep for humans. According to Turkel (2011) human develop new technologies and in turn they shape humans. Moreover, humans are changed because technology offers them substitutes or alternatives for connecting with each other directly or face-to-face. Professor Turkel argues that technology may be developed for social communication or interaction with people, but this perceived role transforms into something else. Technology takes up a different role that involves a replacement of face-to-face interaction into a virtual communication with no emotional connections (Turkel 2011). Parents may neglect their children while concentrating on technology while people may post apologies on social media rather than directly apologizing. Technologies such as text messaging, social media and email have replaced the face-to-face interaction, which is considered better in terms of emotional connection and development of negotiating skills (Gonzales 2014). The basic argument of Turkel is based on the way technologies are developed with a genuine and abstract purpose that has changed over time to provide a form of communication, interaction, and method of achieving tasks without the original or natural human emotions (Sarmento 2011). Technology enables people to be or feel there, without actually being there. Issues such as work are have now intruded on every minute of our lives, which is why today it is impossible to switch off the mobile phone. Employees and professionals fells that they need to offer instant feedback to customers no matter what time (Turner 2013). This is how the nature of communication in our lives has changed to the need for instant and real-time communication resulting in the lack of emotional and deeper connections. The discussion on using a baby seal robot is quite insightful to the whole debate on drawing a line as to what kinds of tasks we should leave to machines, and what we should keep for humans. According to Calo, et al. (2011) the baby seal is developed as a substitute for social interaction or communication with people, but this has substituted the human-robot interaction with human-cuddly pet interaction or human-human interaction. It is evident that having the elderly interact with robots such as the baby seal instead of their children or grandchildren tends to diminish the emotional range that such machines or technologies can offer. Nonetheless, in cases where people need special care or they are allergic animals that they may need to connect to, the baby seal robot can offer a low-risk alternative (Calo, et al. 2011). This means that it is not in all cases that the baby seal is considered to be devaluing the emotional connection when offered by machines rather than humans. References Calo, C. J., Hunt-Bull, N., Lewis, L., & Metzler, T. (2011). Ethical Implications of Using the Paro Robot. In 2011 AAAI Workshop (WS-2011-2012) (pp. 20-24). Gonzales, AL 2014, 'Text-based communication influences self-esteem more than face-to-face or cellphone communication', Computers in Human Behavior, vol. 39, pp. 197-203 Sarmento, A 2011, Sociological and Philosophical Aspects of Human Interaction with Technology : Advancing Concepts, IGI Global, Hershey PA. Turkle, S. (2012). Alone together: Why we expect more from technology and less from each other. Basic books. Turner, P 2013, How We Cope with Digital Technology, Morgan & Claypool Publishers, San Rafael, Calif. Question 2 The use of social media in the 21st century has created an unbelievable amount of data about the world society. According to Golbeck (2014), approximately half of the world’s population shares different kinds of data on social media sites such as Facebook. Nonetheless, the presence of this big data enables for data mining where mechanisms can be developed to extract actionable models or patterns that can be beneficial for companies, consumers, and users. In this light, Golbeck (2014) suggests three paths for the future of big data to ensure that users’ information is not inferred, but their online experience is enhanced. The best path to take in relation to future data for individuals is the development of mechanisms for computing such data where users can be warned or advised about what may be predicted from what they share as well as the ability to encrypt what they share so that it is worthless and invisible to social sites and third parties, but is accessible to the people the individual who shared information wants to see. To begin with, the identified path that individuals should take in relation to future data is not that simple. According to Oboler et al. (2012), professional computing and engineering bodies have significant codes of ethics such as the IEEE that commits its members to enhance the understanding of technology and consider its suitable application and possible consequences. These codes of ethics also expand to protecting and respecting the privacy of others. The main challenge is not a lack of ethical guidelines to development of social media platforms, but the application of these guidelines. According to Oboler et al. (2012), appropriate applications starts with understanding that social media platforms such as Facebook are a type of computational social science. Therefore, in the development of new social networking tools and improvement of existing social networks, both social and computer scientists should contribute to the discussion and development of more effective social media tools. Such development can significantly support the suggested path for enabling users encrypt what they share and warning or advisory mechanisms for activities conducted on social networking platforms (Gundecha & Liy 2012). Baden, et al. (2009), have already developed a model and mechanisms that can help online social network users dictate who may access their personal information or what they share. The model allows users to have total control of who can access their information making it invincible and worthless to social media providers or third party services. Moreover, the mechanisms also allows users to encrypt information and allows those that they would like to see the information to decrypt the information while remaining invisible and worthless to social media providers and third party services (Baden, et al. 2009). The main breakthrough of this development is that it was implemented on Facebook and illustrated a future path for future data. Therefore, users can then turn from being the product to consumers where their personal information is not used to pay social media companies (Fitzpatrick 2010). Overall, users currently lack privacy awareness that is a complex process, but development of these capabilities can reduce the complexity discourage companies or others from data mining of user’s information. References Baden, R, Bender, A, Spring, N, Bhattacharjee, B, & Starin, D 2009, 'Persona: An Online Social Network with User-Defined Privacy', COMPUTER COMMUNICATION REVIEW, vol. 39, no. 4, pp. 135-146. Fitzpatrick, J 2010, If You're Not Paying for It; You're the Product. Life Hacker. Available at < http://lifehacker.com/5697167/if-youre-not-paying-for-it-youre-the-product > [Accessed 21st Oct. 2015]. Golbeck, J 2014. The curly fry conundrum: Why social media “likes” say more than you might think. TED TALK. Available at: < https://www.ted.com/talks/jennifer_golbeck_the_curly_fry_conundrum_why_social_media_likes_say_more_than_you_might_think/transcript?language=en> [Accessed 21st Oct. 2015]. Gundecha, P & Liy, H 2012, Mining Social Media: A Brief Introduction. INFORMS. Oboler, A, Welsh, K, & Cruz, L 2012, ‘The dangers of big data: Social media as computational social science’ First Monday Online Journal, vol. 17, no. 7, http://firstmonday.org/ojs/index.php/fm/article/view/3993/3269/ Essay Topics Social Media Fail Event Today’s businesses are driven by social media marketing based on the huge access to global markets available on the internet. Nonetheless, being a new frontier, most businesses are caught up in social media fails where the intended strategies end up giving the unexpected or unwanted results or outcomes (Funk 2011). The following essay aims at analyzing the Sweden’s Pepsi Max social media fail. Pepsi’s subsidiary in Sweden began a social media campaign on Facebook to promote their energy drink brand Pepsi Max. The company rolled out the campaign just before the start of Sweden’s World Cup play-off that was in their second leg where Sweden was expected to face Portugal (Wright 2013). Most companies develop and implement their social media campaigns to coincide with important or relevant events such as illustrated in this case. The company developed a voodoo doll that featured Cristiano Ronaldo in the Portuguese national football team uniform being tortured or illustrating his defeat in numerous ways (Rocket Post, 2014). The doll made it clear that it meant to portray Ronaldo since the doll was designed with a jersey that had the number 7, which is the position Ronaldo plays in the Portuguese national football team. The doll was posted on Facebook through different adverts in form of pictures. One of the adverts was a picture of the doll tied up on its mouth, hands, and legs on a rail track with the caption “We’re going to pass over Portugal” (Drayton 2013). Another ad showed Ronaldo’s doll covered in needles lying on the ground while another showed the same doll lying with its head smashed or stifled by a Pepsi Max can. Following the adverts, Ronaldo fans who are Facebook users began developing different adverts to mock Pepsi Max adverts. Most fans of Ronaldo especially from his hometown Real Madrid found the adverts to be offensive, abusive, and inappropriate (Wright 2013). This led to the fans creating a group known as ““Nunca mais vou beber Pepsi” or in English “Never drink Pepsi again”. Within a single day, the group had accumulated over 100,000 likes (Wright 2013). Most of the group members posted their messages of disappointment and angers as well as their intention never to associate with the brand in any way. This was the trigger of Pepsi’s social media fail. The company had angered and disappointed Ronald’s fans by depicting him in insensitive and offensive manners as being tortured. The company did not achieve what it expected from the social media campaign as they got over 100,000 customer or potential customers angered with their brand (Rocket Post, 2014). As a result the whole Pepsi as a multinational brand realized they were getting bad press, which was not in line with their strategy or aims. The Sweden subsidiary that was responsible for the campaign was forced to pull down the adverts and apologize for its actions. In a statement issued on Facebook, the company indicated that they would never want or wish to put the spirit of competition in a bad or negative perspective and they regret if people were offended by the adverts (Wright 2013). The company also acknowledged that all adverts were pulled down immediately. The company also extended apologies to all those concerned. Even though the response was prompt, the damage had already been done as the company’s image was tainted just from several images posted on social media. Such a social media fail is accompanied by lessons that other companies can rely on while developing social media campaigns. One of the main lessons learned in Pepsi Max social media fail is how to ensure cultural inclusiveness in social media marketing. According to DiStaso & Bortree (2014), companies should develop Facebook campaigns while considering how they may be translated oversees or in different cultures. Pepsi Max had targeted the Swedish consumers because they were supporting their team against Portugal. This means that Pepsi Max expected their Swedish target consumers to take the adverts in a positive manner and offer them the encouragement to support their team. Nonetheless, social media is a global network, thus includes people with different beliefs, backgrounds, and customs. It is clear that Pepsi did not consider how the Portuguese Facebook users would react with an image of their star and celebrity being illustrated in an offensive manner. The creativity to develop a Ronaldo voodoo doll was in good faith, but lack of looking at all the angles failed to enable Pepsi realize that the campaign was not appropriate or would fail all together. Businesses should not be hasty to develop social media campaigns, but rather undertake all the necessary analysis to ensure that there minimal risk involved of failure (DiStaso & Bortree 2014). Another lesson is that social media campaigns should not be used to attack or target certain individuals especially celebrities. Most celebrities have global fans on social media and any post, picture, video, or campaign that may illustrate them in a bad way may be offensive to these fans. Overall, it is important to consider the cultural content and possible reactions of social media campaigns to avoid offending others while attempting to market products and services (Hurk, 2013). The company could have not launched the social media campaign given that they target one of Portuguese and the world’s best football players especially when the World Cup Qualifiers were occurring. A simple statement to offer the Sweden team morale should have been used as their campaign. Additionally, the method used to handle the social media fail was also not that effective. Nonetheless, there are numerous recommendations that such a company and others can use to recover from social media fails. Recovering a tainted brand or company image from a social media fail requires increased planning, transparency, and commitment to the social media community. After realizing that something has gone wrong or a social media campaign has backfired, the first step is to acknowledge the mistake immediately. According to LePage (2015), social media users anticipate transparency and speed from companies and it becomes more important when social media campaigns fail. When a social media blunder occurs even if it’s a typo or offensive post, the best thing to do is acknowledge that it occurred. Users who realize a social media mistake are always watching while those who have been offended start making complaints, sharing the mistake, and disassociating from the businesses social media community (LePage 2015). Therefore, the need for immediate acknowledgement is important to ensure that customers are not lost or rivals created in the event. This allows the company to control the conversation and avoid further damage. One of the main don’ts in social media fail responses is censoring negative feedback following a social media mistake. One example of such a scenario is Volkswagen’s social media post that asked their followers to share their views on what they wanted the company to achieve in 2012. The campaign resulted in increased negative feedback, which the company supposedly deleted especially the most offensive (Gray 2014). The company also went ahead to ignore the negative comments resulting in increased damage. Censoring negative feedback taints a company’s image as guilty while it angers users who took much effort to share their comments. Such negative feedback can help in shaping a business’ approach in the future, which would certainly rebuild the company’s image on social media (ROHN & BAUMANN 2015). The third step in handling a social media fail is apologizing especially when a company has posted or used insensitive or offending campaigns. Apologies go illustrate transparency by ensuring that those offended can actually feel or get a sense of genuine expression of regret from the company (Frativelli et al. 2015). The fourth step is indicating and being transparent with the corrective actions being undertaken to ensure a similar mistake does not occur. Even the simple step of saying that a business is reviewing their social media posting process and department is not bad. Most companies have to fire people who are behind social media failures, which is because they lack proper planning in terms of those who can access the official social media accounts of such businesses. Illustrating the steps being taken to avoid future social media blunders can help in reviving the company’s image (Charlesworth 2015). Furthermore, it is also important to reach out to community members. These are people who interact with the company regularly social media. For instance, a company can tag some of its close users in an apology or the positive message, which they can use to spread the message in a more effective manner. Such members of the social media community can come in handy in future cases of social media mistakes. In conclusion, it is important to ensure social media fails should serve as lessons. All companies should learn from their own mistakes and those of others. Moreover, the businesses should share their experiences of social media mistake with others to enable a trend or culture of ensuring appropriate and effective use of social media for marketing. Social media is a powerful, yet risky marketing and communication tool for today’s businesses. Increased caution and consideration is needed in the development and implementation of social media camp gains and communications. References Charlesworth, A 2015, An Introduction to Social Media Marketing, Routledge, London [England]. DiStaso, M & Bortree, D 2014, Ethical Practice of Social Media in Public Relations. London, Routledge. Frativelli, F, Negri, F, & Cori, E 2015, 'Social media communities of practice: Reputation at risk', International Journal of Management Cases, vol. 17, no. 4, pp. 102-119. Funk, T 2011, Social Media Playbook for Business: Reaching Your Online Community with Twitter, Facebook, Linkedin, and More. Santa Barbara: ABC-CLIO. Gray, R 2014, Great Brand Blunders: The Worst Marketing and Social Media Meltdowns of All Time ... and how to Avoid Your Own. London: Crimson. Hurk, A M 2013, Social Media Crisis Communications: Preparing for, Preventing, and Surviving a Public Relations #FAIL. Indianapolis: Que Publishing. LePage, E 2015, How to Come Back From a Social Media Fail. Hoot Suite. Available at < http://blog.hootsuite.com/how-to-come-back-from-a-social-media-fail/> [Accessed 21st Oct. 2015]. Rocket Post, 2014, Facebook Gone Wrong: 5 Fails Brands Can Learn From. Rocket Post. Available at [Accessed 21st Oct. 2015]. ROHN, U, & BAUMANN, S 2015, 'Media brands in social network sites: Problems German media companies have faced and lessons they have learned', Journal of Brand Strategy, vol. 4, no. 1, pp. 70-82. Wright, C 2013, Pepsi Forced To Apologise After Using Cristiano Ronaldo Voodoo Dolls In Ill-Judged Advert Campaign. Available at http://www.whoateallthepies.tv/photos/180057/pepsi-forced-to-apologise-after-using-cristiano-ronaldo-voodoo-dolls-in-ill-judged-advert-campaign.html [Accessed 21st Oct. 2015]. Essay 2 Social media and digital humanitarianism Digital humanitarianism is a recent development into how people can help in times of disaster from virtually anywhere in the world. Digital humanitarians share the same objectives as humanitarian workers and organizations (Meier 2015). They partner with such organizations to help in disaster relief efforts although not being physically present. One of the recent challenges is the aspect of social media. Social media has developed into a powerful global community with billions of users. When a disaster strikes people on social media either on their computers or mobile phones send, post, and share an enormous amount of information. This includes relying messages of current situations, risks, warnings, aftermaths, and relief. Since the beginning of digital humanitarianism, social media played an integral part for first responders. Relief people could easily identify or warn others of potential disasters through social media posts. Nonetheless, the enormous amount of data posted on social media during disasters makes it impossible to sieve in the important aspects. However, the emergence of crowdsourcing mechanisms has enabled the development of a new technology that allows all the information generated during a disaster to be sieved or developed into patterns or micro tasks that can help solve world problems. The following essay aims at discussing the manner in which this new technology can be used to solve real world problems. According to Meier (2015), the information overflow that happens when a disaster strikes can paralyze humanitarian response efforts. All kinds of gadgets such as phones, computers, and satellites produce a huge amount of information. However, most of the information is produced in social media. For instance, about 20 million tweets and 500,000 Instagram pictures were posted in the wake of Hurricane Sandy all relating to the disaster (International Federation of Red Cross and Red Crescent Societies 2013). Again, about 117 million tweets were also posted the day after Japan’s 2011 earthquake as well as over half a million tweeter accounts created in the same day (International Federation of Red Cross and Red Crescent Societies 2013). This is what can be called an information overflow or the increase of big “crises” data. The enormous overflow of information is on social media, which may be overwhelming for disaster response or humanitarians to use in their relief efforts is the main challenge in digital humanitarianism. Nonetheless, the development of crowdsourcing solutions or mechanisms presented the new technology to help solve world problems. According to Meier (2015), the people behind this technology are referred to as digital Jedis. These are teams of volunteers with the appropriate computer and technology skills needed to make sense of all the big data generated on social media during disasters. The new technology is also known as crowd mapping (Corcoran 2015). The main objective and purpose of the new crowd mapping technology is to transform the big data into rich data. This means that the new technologies are developed to sip through large volumes of data and make sense of it to help humanitarian agencies in their efforts for aid and relief. There are numerous applications and platforms that can be used to help the Digital Jedis map useful information from social media by breaking down larger systematic data into small, simply finalized micro tasks (Shelton et al. 2014). The new technologies can enable digital volunteers tag tweets or Facebook posts with situation-specific terms or pictures to classify the type or amount of damage visible and geo-tag images and posts that not automatically geo tagged. All these tasks can be effortlessly achieved by anyone anywhere once the information is made available. The first actual use of this technology was witnessed in 2010 following the Haiti earthquake disaster. Following the disaster, digital volunteers from Fletcher School at Tufts University developed a crisis map that pinpointed the damage and resulting aid needs across Haiti’s capital city, Port-au-Prince. The volunteers manually monitored social media activities on Facebook and Twitters as well as mainstream news to search for map-able and relevant reports from Haiti. Within a week, there were thousands of volunteers who did the same and enabled increased penetration of humanitarian aid and relief to specific and relevant locations in the city. The crisis maps even included the specific places where victims would get humanitarian aid and relief. According to Meier (2011), after ten day of the digital humanitarianism response, the head of FEMA, Fugute referred to crisis mapping as the most useful and detailed tools for the humanitarian community. The ability to sieve through huge amounts of data is an ingenious technology that allows social media to play an effective role in humanitarian response. According to International Federation of Red Cross and Red Crescent Societies (2013), the whole idea behind this new technology of crowd mapping is differentiating between a mystery and a puzzle. A mystery has no known outcome, thus gathering as much information as possible will not solve the problem but make it harder. However, a puzzle is based on a known result that necessitates a precise set of information to complete. In this case, humanitarian organizations must identify the relevant information they require for them to accomplish their efforts effectively. Such information would be damage causes, amount of survivors, accessibility, and what is needed. Such information is then passed to digital volunteers who can analyze social media posts or data and find posts, images, videos, and tweets that are relevant to this information. The information can then be analyzed and compiled to develop patterns or a set of simpler information needed to make a decision for humanitarian response. In 2012, the Digital Humanitarian Network was asked to sieve through social media within 12 hours to find pictures and videos relating to Typhoon Pablo’s aftermath in Philippines. The team sieved through 20,000 images and video and compiled a social media map that also produced a set of analytical graphs (Meier 2015). The information was handed to OCHA to make relevant decisions on their response strategies. Additionally, volunteers also analyzed 20,000 tweets in 10 hours during the Nepal floods in 2015, which was handed to the UN OCHA and was used to develop the official UN crisis map on Google (Corcoran 2015). Additionally, the same data was shared to Nepal authorities and humanitarian organizations such as the Nepalese army and Nepal Red Cross resulting in efficient and effective response to the disaster. Crowd mapping was also used in the Libyan war conflict to analyze relevant social media information from Twitter, You-Tube, Flicker, and Facebook. The 150 digital volunteers collected geo-referenced, analyzed, and verified large volumes of data (International Federation of Red Cross and Red Crescent Societies 2013). The result was a map that could identify potential conflict risk areas, health needs, relief needs, and accessibility of victims. Overall, the use of crowd mapping has illustrated an effective technology that is invaluable to humanitarian organizations. The crowd mapping enables increased collaboration between organizations that are tasked with offering relief to victims (Burns 2015). Moreover, the application of this technology has the capacity to sip through the same social media data and make predictions or areas of perceived vulnerability before disasters occur. Most humanitarian and non-profit organizations may not be able to sip through all the big data as well as offer aid and relief to victims in a disaster (Fielding 2014). Therefore, the most useful and important technology in relation to social media and digital humanitarianism is crown mapping. Social media users data can positive be used for good rather than data mining for marketing strategies of companies (Morabito 2015). Social media illustrates the development of a new digital society that share their experiences and emotions online (Thomas & McSharry 2015). Without a proper way of understanding information shared on social media, it would be impossible to address world problems. Additionally, crowd mapping is also capable of enabling humanitarian response to be efficient. Organizations can save through the ability to access vital information necessary to make cost-effective decisions (Taylor & Schroeder 2015). The main aim of crowd mapping is enabling strategic and effective decision making. Through the manipulation and categorization of data, organizations can effectively meet their goals and address world problems. In conclusion, the emergence of crowdsourcing mechanisms has enabled the development of a new technology that allows all the information generated during a disaster to be sieved or developed into patterns or micro tasks that can help solve world problems. Organizations have a better and invaluable resource in their decision making process, which is the vital information. References Burns, R 2015, 'Rethinking big data in digital humanitarianism: practices, epistemologies, and social relations', GeoJournal, vol. 80, no. 4, p. 477. Corcoran, L 2015, How data gathering has helped in Nepal. Irish Times. Available at: [Accessed 21st Oct. 2015]. Fadiya, SO, Saydam, S, & Zira, VV 2014, 'Advancing Big Data for Humanitarian Needs', Procedia Engineering, vol. 78, no. Humanitarian Technology: Science, Systems and Global Impact 2014, HumTech2014, pp. 88-95. Fielding, D 2014, 'The Dynamics of Humanitarian Aid Decisions', Oxford Bulletin of Economics & Statistics, vol. 76, no. 4, pp. 536-564. International Federation of Red Cross and Red Crescent Societies, 2013, Strengthening humanitarian information: the role of technology. World Disaster Report. Available at http://qcri.org.qa/app/media/2212 [Accessed 21st Oct. 2015]. Meier, P 2011, 'New information technologies and their impact on the humanitarian sector', International Review of the Red Cross, vol. 93, no. 884, pp. 1239-1263. Meier, P 2015, Digital Humanitarians : How Big Data Is Changing the Face of Humanitarian Response, CRC Press, Boca Raton, FL. Morabito, V 2015, Big Data and Analytics : Strategic and Organizational Impacts, Springer, Cham. Shelton, T, Poorthuis, A, Graham, M, & Zook, M 2014, 'Mapping the data shadows of Hurricane Sandy: Uncovering the sociospatial dimensions of ‘big data’', Geoforum, vol. 52, pp. 167-179. Taylor, L, & Schroeder, R 2015, 'Is bigger better? The emergence of big data as a tool for international development policy', GeoJournal, vol. 80, no. 4, p. 503. Thomas, R, & McSharry, P 2015, Big Data Revolution : What Farmers, Doctors and Insurance Agents Teach Us About Discovering Big Data Patterns, Wiley, Chichester. Read More