Tag Archives: technology

The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games

This is an excerpt from one of my latest empirical papers.

How to Cite: Camilleri, A.C. & Camilleri, M.A. (2019). The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games at Home and at School. 13th Annual International Technology, Education and Development Conference. Valencia, Spain (10-13 March, 2019). International Academy of Technology, Education and Development (IATED). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3339163


gamesThis contribution has explored the primary school’s grade three students’ attitudes toward educational games. It relied on the technology acceptance model to investigate the students’ perceived usefulness and ease of use of the schools’ games ([10], [12], [44]). Moreover, the researchers have also included the measuring items that explored the students’ perceived enjoyment ([19]) as they investigated whether they experienced normative pressures to play the educational games ([10], [14], [20]). The findings from the Wilcoxon test reported that the students played the school games at home, more than they did at school. They indicated that the school’s games were easy to play. This study reported that the students recognized that the school’s games were useful and relevant as they were learning from them. Moreover, they indicated that the school’s educational games held their attention since they found them enjoyable and fun.

The vast majority of the children played the educational games, both at home and at school. The findings in this study are consistent with the argument that digital natives are increasingly immersing themselves in digital technologies ([45]), including educational games ([1], [3]). However, the results have shown that there was no significant relationship between the perceived ease of the gameplay and the children’s enjoyment in them. Furthermore, the stepwise regression analysis revealed that there was no significant relationship between the normative expectations and the children’s engagement with the educational games; although it was evident (from the descriptive statistics) that the parents were encouraging their children to play the games at home and at school.

This research relied on previously tried and tested measures that were drawn from the educational technology literature in order to explore the hypothesized relationships. There is common tendency in academic literature to treat the validity and reliability of quantitative measures from highly cited empirical papers as given. In this case, the survey items in this study were designed and adapted for the primary school children who were in grade 3, in a small European state. Future studies may use different sampling frames, research designs and methodologies to explore this topic. To the best of our knowledge, there is no other empirical study that has validated the technology acceptance model within a primary school setting. Further work is needed to replicate the findings of this research in a similar context.

REFERENCES (this is a full list of references that appeared in the bibliography section of the paper)

 
[1] J. Bourgonjon, M. Valcke, R. Soetaert, and T. Schellens, “Students’ perceptions about the use of educational games in the classroom,” Computers & Education, vol. 54, no. 4, pp. 1145-1156, 2010.

[2] S. Bennett, K. Maton, and L. Kervin, “The ‘digital natives’ debate: A critical review of the evidence,” British Journal of Educational Technology, vol. 39, no. 5, pp. 775-786, 2008.

[3] M. Prensky, “Digital natives, digital immigrants part 1,” On the horizon, vol. 9, no. 5, pp. 1-6, 2001.

[4] W. Nadeem, D. Andreini, J. Salo, and T. Laukkanen, “Engaging consumers online through websites and social media: A gender study of Italian Generation Y clothing consumers.” International Journal of Information Management, vol. 35, no. 4, pp. 432- 442, 2015.

[5] H.J. So, H. Choi, W.Y. Lim, and Y. Xiong, “Little experience with ICT: Are they really the Net Generation student-teachers?”, Computers & Education, vol. 59, no. 4, pp. 1234- 1245, 2012.

[6] J.M. Twenge, “The evidence for generation me and against generation we.” Emerging Adulthood 1, no. 1, pp. 11-16, 2013.

[7] D. Oblinger, and J. Oblinger, “Is it age or IT: First steps toward understanding the net generation,” Educating the Net Generation, 2(1-2), 20, 2015.

[8] N. Howe, and W. Strauss, “Millennials go to college: Strategies for a new generation on campus,” American Association of Collegiate Registrars and Admissions Officers (AACRAO), 2003.

[9] K. Gregor, T. Judd, B. Dalgarno, and J. Waycott, “Beyond natives and immigrants: exploring types of net generation students,” Journal of Computer Assisted Learning, vol. 26, no. 5, pp.332-343, 2010.

[10] T. Teo, “Modelling technology acceptance in education: A study of pre-service teachers,” Computers & Education 52, no. 2 (2009): 302-312, 2009.

[11] M. Fishbein, and I. Ajzen, “Belief, attitude, intention and behavior: An introduction to theory and research,” 1975.

[12] F.D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, pp. 319-340, 1989.

[13] F.D. Davis, R.P. Bagozzi, and P.R. Warshaw, “User acceptance of computer technology: a comparison of two theoretical models,” Management Science, vol. 35, no. 8, pp. 982- 1003, 1989.

[14] I. Ajzen, “The theory of planned behavior,” Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179-211, 1991.

[15] V. Venkatesh, M.G. Morris, G.B. Davis, and F.D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Quarterly, pp. 425-478, 2003.

[16] V. Venkatesh, J.Y.L. Thong, and X. Xu, “Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology,” MIS Quarterly, pp. 157-178, 2012.

[17] S.Y. Park. “An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning,” Educational Technology & Society, vol. 12, no. 3, pp. 150-162, 2009.

[18] P. Legris, J. Ingham, and P. Collerette, “Why do people use information technology? A critical review of the technology acceptance model,” Information & Management, vol. 40, no. 3, pp. 191-204, 2003.

[19] H. Nysveen, P.E. Pedersen, and H. Thorbjørnsen, “Intentions to use mobile services: Antecedents and cross-service comparisons,” Journal of the Academy of Marketing Science, vol. 33, no. 3, pp. 330-346, 2005.

[20] L.M. Maruping, B. Hillol, V. Venkatesh, and S.A. Brown, “Going beyond intention Integrating behavioral expectation into the unified theory of acceptance and use of technology,” Journal of the Association for Information Science and Technology, vol. 68, no. 3, pp. 623-637, 2017.

[21] V. Venkatesh, and M.G. Morris, “Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior.” MIS Quarterly, pp. 115-139, 2000.

[22] M.A. Camilleri and A. Camilleri, “The Students’ Perceptions of Digital Game-Based Learning,” In M. Pivec and J. Grundler, 11th European Conference on Games Based Learning (October). Proceedings, University of Applied Sciences, Graz, Austria, pp 56- 62, 2017.

[23] T. Teo, and M. Zhou, “Explaining the intention to use technology among university students: a structural equation modeling approach,” Journal of Computing in Higher Education, vol. 26, no. 2, pp. 124-142, 2014.

[24] T. Doleck, P. Bazelais, and D.J. Lemay, “Examining the antecedents of social networking sites use among CEGEP students,” Education and Information Technologies, vol. 22, no. 5, pp. 2103-2123, 2017.

[25] B. Wu, and X. Chen, “Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model,” Computers in Human Behavior, vol. 67, pp. 221-232, 2017.

[26] C.T. Chang, J. Hajiyev, and C.R. Su, “Examining the students’ behavioral intention to use e-learning in Azerbaijan? The general extended technology acceptance model for elearning approach,” Computers & Education, vol. 111, pp. 128-143, 2017.

[27] I. Arpaci, K. Kilicer, and S. Bardakci, “Effects of security and privacy concerns on educational use of cloud services,” Computers in Human Behavior, vol. 45, pp. 93-98,
2015.

[28] A.F. Agudo-Peregrina, Á. Hernández-García, and F.J. Pascual-Miguel, “Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning,” Computers in Human Behavior, vol. 34,
pp. 301-314, 2014.

[29] F. Paraskeva, H. Bouta, and A. Papagianni. “Individual characteristics and computer self-efficacy in secondary education teachers to integrate technology in educational practice,” Computers & Education, vol. 50, no. 3, pp. 1084-1091, 2008.

[30] D.R. Compeau, and C.A. Higgins, “Computer self-efficacy: Development of a measure and initial test,” MIS Quarterly, pp. 189-211, 1995.

[31] S.A. Nikou, and A.A. Economides, “The impact of paper-based, computer-based and mobile-based self-assessment on students’ science motivation and achievement,” Computers in Human Behavior, vol. 55, pp. 1241-1248, 2016.

[32] L.A. Annetta, J. Minogue, S.Y. Holmes, and M.T. Cheng, “Investigating the impact of video games on high school students’ engagement and learning about genetics,” Computers & Education, vol. 53, no. 1, pp. 74-85, 2009.

[33] E.W.T. Ngai, J. K. L. Poon, and Y.H.C. Chan, “Empirical examination of the adoption of WebCT using TAM,” Computers & Education, vol. 48, no. 2, pp. 250-267, 2007.

[34] T.Teo, and C. Beng Lee, “Explaining the intention to use technology among student teachers: An application of the Theory of Planned Behavior (TPB),” Campus-Wide Information Systems, vol. 27, no. 2, pp. 60-67, 2010.

[35] T. Teo, and C. Beng Lee, C. Sing Chai, and S.L. Wong, “Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM),” Computers & Education, vol. 53, no. 3, pp. 1000-1009, 2009.

[36] J.Y.L. Thong, W. Hong, and K.Y. Tam, “Understanding user acceptance of digital libraries: what are the roles of interface characteristics, organizational context, and individual differences?” International journal of human-computer studies, vol. 57, no. 3, pp. 215-242, 2002.

[37] M.A. Camilleri, and A.C. Camilleri, “Digital learning resources and ubiquitous technologies in education,” Technology, Knowledge and Learning, vol. 22, no. 1, pp. 65- 82, 2017.

[38] D.Y. Lee, and M.R. Lehto, “User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model.” Computers & Education, vol. 61, pp. 193-208, 2013.

[39] T. Teo, and P. Van Schalk, “Understanding technology acceptance in pre-service teachers: A structural-equation modeling approach,” The Asia-Pacific Education Researcher, vol. 18, no. 1, pp. 47-66, 2009.

[40] C. Smarkola, “Technology acceptance predictors among student teachers and experienced classroom teachers,” Journal of Educational Computing Research, vol. 37, no. 1, pp. 65-82, 2007.

[41] M.A. Camilleri, and A.C. Camilleri, “Measuring The Educators’ Behavioural Intention, Perceived Use And Ease Of Use Of Mobile Technologies,” In Wood, G. (Ed) Reconnecting management research with the disciplines: Shaping the research agenda for the social sciences (University of Warwick, September). British Academy of Management, UK, 2017.

[42] M. Turner, B. Kitchenham, P. Brereton, S. Charters, and D. Budgen, “Does the technology acceptance model predict actual use? A systematic literature review,” Information and Software Technology, vol. 52, no. 5, pp. 463-479, 2010.

[43] R.P. Bagozzi, and Y. Youjae, “On the evaluation of structural equation models,” Journal of the Academy of Marketing Science, vol. 16, no. 1, pp.74-94, 1988.

[44] M.A. Camilleri, and A.C. Camilleri, “The Technology Acceptance of Mobile Applications in Education,” In Sánchez, I.A. and Isaias, P. (Eds) 13th International Conference on Mobile Learning (Budapest, 11th April). pp41-48. International Association for Development of the Information Society, 2017.

[45] A. Colbert, N. Yee, and G. George, “The digital workforce and the workplace of the future,” Academy of Management Journal, vol. 59, no. 3, pp. 731-739, 2016.

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Filed under digital games, digital media, Education

Data-Driven Marketing Technologies and Disruptive Innovations

The latest disruptive technologies are supporting  the  marketing mix elements as they can improve the businesses’ interactive engagement with prospective customers, and enhance their personalization of services. They  may also provide secure pricing options.

Many firms are evolving from their passive, rigid, and product-centric state to a more flexible, dynamic, and customer-centric environment. Technology is enabling data-driven companies to monitor and detect any changes in consumer sentiment. Savvy technology giants including Facebook, Amazon, Microsoft and Google are capturing (and analyzing) the online and mobile activity of prospective customers. Their analytics captures the consumers’ interactions with brands and companies through digital media. Big data is enabling them to target and re-target individu­als and online communities with instantaneous pricing and access options, across multiple channels (via web-site activity, mobile,video, social media, e-commerce, among others). 

Mobile tracking technologies are being utilized by big technology conglomerates as they gather information on the consumer behaviours, including their shopping habits, lifestyle preferences , et cetera. Businesses have learnt how to take advantage of on-demand, real-time information from sensors, radio frequency identification and other location tracking devices to better understand their marketing environments at a more granular level (Storey and Song, 2017). This way business could come up with personalised products and services, that are demanded by individual customers. From a business perspective, it is important to acquire this data, quickly, and in high velocities.

Many businesses are already benefiting of the programmatic advertising environment; where buyers and sellers of digital advertising connect online to exchange available inventory (Busch,2016; Stevens et al., 2016).  The challenge for tomorrow’s businesses is to recognize the value of smart technologies as effective tools that can help them analyse their marketing environment; that comprise their customers as well as their competitors.

The predictive-analytical tools can examine different scenarios as they can anticipate what will happen, when it will happen, and can explain why it happens. These technologies can monetise data by identifying revenue generating opportunities and cost savings.

Other innovations, including; blockchain’s distributed ledger technologies are improving data privacy. This technology involves the verification and the secure recording of transactions among an interconnected set of users. Blockchain tracks the ownership of assets before, during, and after any online transaction. Therefore, this technology could be used by different businesses to facilitate their transactions with marketplace stakeholders, including; suppliers, intermediaries, and consumers across borders. The block chain will probably be more convenient than other payment options, in terms of time and money. Therefore, blockchain’s ledger technology can possibly lead to better customer service levels and operational efficiencies for businesses.

The smart tourism technologies, including big data analytics are shifting how organisations collect, analyze and utilise and distribute data. A thorough literature review suggests that the crunching of big data analytics is generating meaningful insights and supporting tourism marketers in their decision making. Moreover,other technologies, including the programmatic advertising and block chain are helping them to improve their financial and strategic performance, whilst minimizing costs. Table 1 illustrates how smart tourism businesses are capturing, analysing and distributing data.

Table 1. Data-driven approaches for smart tourism

(Camilleri, 2018)

Emerging Trends and Future Research

Tomorrow’s tourism businesses will be serving customers from geographically-diverse regions. There will be more travellers from emerging markets and developing economies. The tourism service providers will have to cater to different demographics, including senior citizens and individuals with special needs; as the populations are getting older in many countries.

Therefore,  smart technologies can be used to anticipate the discerned consumers’ requirements. For instance, the use of programmatic advertising will probably increase the individuals’ intuitive shopping experiences and can tap into the individuals’ discretionary purchases.

It is very likely, that the third-party retailers will continue to form part of the distribution mix. However, many service providers will be using their direct channels to reach out to their targeted customers. 

The sales of products will continue to rely on mobile devices with increased consumer interactions through speech and voice recognition software. The service providers may possibly rely on artificial intelligence and other forms of cognitive learning capabilities, like machine learning and deep learning.

The businesses’ distributive systems could interface with virtual reality software to help online intermediaries to merchandise their products in captivating customer experiences. Many online prospects may use blockchain’s secure technology to purchase tourism products, in the foreseeable future.

This contribution calls for further empirical research that could explore smart tourism innovations for individuals and organisations, including; mobile social networking, mobile visualisation, personalization and behavioural modelling for mobile apps, programmatic advertising, blockchain, AI, and the internet of things, among other areas.

References

Busch, O. (2016), “The programmatic advertising principle”, In Programmatic Advertising (pp. 3-15). Springer, Cham, Switzerland.

Camilleri, M.A. (2018) Data-Driven Marketing and Disruptive Technologies. Working Paper 08/2018, Department of Corporate Communication, University of Malta. 

Stevens, A., Rau, A., and McIntyre, M. (2016), “Integrated campaign planning in a programmatic world”, In Programmatic Advertising (pp. 193-210), Springer, Cham, Switzerland. 

Storey, V. C., and Song, I. Y. (2017), “Big data technologies and Management: What conceptual modeling can do?”, Data and Knowledge Engineering, Vol. 108, pp. 50-67.

 

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Filed under Analytics, Big Data, blockchain, Business, digital media, Marketing

RESEARCH: The Small Business Owner-Managers’ Attitudes toward Digital Media

An Excerpt from my latest paper: Camilleri, M.A. (2018). The SMEs’ Technology Acceptance of Digital Media for Stakeholder Engagement. Journal of Small Business and Enterprise Development (Forthcoming).


small-businesses-social-media

This contribution sheds light on the SME owner-managers’ attitudes toward the pace of technological innovation, perceived use and ease of use of digital media; as they communicate and interact with interested stakeholders online. It also explored their stance on responsible entrepreneurship, specifically on commercial, ethical and social responsibilities, as well as on their willingness to support other responsible stakeholders.

This empirical study and its theoretical underpinnings contribute to an improved understanding as to why today’s SMEs are expected to communicate with stakeholders through digital media. At the same time, it raises awareness of responsible entrepreneurial initiatives that could be promoted through digital media, including; corporate websites, social media and blogs, among others.

Generally, the results reported that there were high mean scores and low standard deviations, particularly when the participants were expected to indicate their attitudes on their commercial and ethical responsibilities. The nature of the SMEs’ CSR activities is usually integrated into their company culture, often implicitly in habits and routines that are inspired by highly motivated owner-managers; rather than explicitly in job descriptions or formalized procedures (Jenkins, 2006). The factor analysis indicated that the SME owner-managers were increasingly perceiving the usefulness of digital media to engage with marketplace stakeholders, including; consumers, suppliers and other businesses, as they promoted their responsible entrepreneurship behaviors.

The communications on their businesses’ social responsibility and environmentally-sound practices also served them well to engage with other interested groups; including; human resources, shareholders and investors, among others. This finding mirrors Baumann Pauly et al.’s (2013) argumentation as these authors remarked that each business decision on economic, social, and environmental aspects must take into account all stakeholders. Notwithstanding, the businesses and their marketers need to possess relevant knowledge on their stakeholders, as this will impact on the effectiveness of their CSR communication (Morsing and Schultz, 2006; Vorvoreanu, 2009).

The value of their communications lies in their ability to open-up lines of dialogue through stories and ideas that reflect their stakeholders’ interests (Fieseler and Fleck, 2013; Moreno and Capriotti, 2009). For these reasons, companies cannot afford to overstate or misrepresent their CSR communications. Their online communication with stakeholders could foster positive behaviors or compel remedial actions, and will pay off in terms of corporate reputation, customer loyalty and market standing (Tantalo and Priem, 2016; Du et al, 2010).

This study suggests that the SME owner-managers were recognizing that they had to keep up with the pace of technological innovation. Yet there were a few participants, particularly the older ones, who were still apprehensive toward the use of digital media. Eventually, these respondents should realize that it is in their interest to forge relationships with key stakeholders (Lamberton and Stephen, 2016; Taiminen and Karjaluoto, 2015; Rauniar et al., 2014; Uhlaner et al., 2004). This research posits that the owner-managers or their members of staff should possess relevant digital skills and competences to communicate online with interested parties.

Likewise, Baumann Pauly et al., (2013) also recommended that the managers must be trained, and that their CSR activities must be evaluated. These findings are in line with other contributions (Spence and Perrini, 2011; Perrini et al., 2007) that have theoretically or anecdotally challenged the business case perspective for societal engagement (Penwar et al., 2017; Baden and Harwood 2013; Brammer et al. 2012).

The regression analysis has identified and analyzed the determinants which explain the rationale behind the SME owner-managers’ utilization of digital media for stakeholder engagement and for the promotion of responsible entrepreneurship. It reported that the respondents’ technology acceptance depended on their perceived “use” and “ease of use” of digital media; and on their willingness to communicate online on their commercial, ethical and social responsibilities.

The results from the regression analysis reported positive and significant relationships between the SMEs’ online stakeholder engagement and the pace of technological innovation; and between the SMEs’ online engagement and the owner-managers’ perceived usefulness of digital media. This study indicated that the pace of technological innovation, the owner-managers’ perceived ease of use of the digital media, as well as their commercial responsibility were significant antecedents for their businesses’ online communication of their responsible behaviors. Arguably, the use of technology is facilitated when individuals will perceive its usefulness and its ease of use (Davis, 1989).

In fact, the findings from this research have specified that the owner-managers’ intention was to use digital media to communicate about their responsible entrepreneurship. They also indicated their desire to use this innovation to engage with stakeholders on other topics, including commercial and ethical issues. This is in stark contrast with Penwar et al.’s (2017) findings, as the authors contended that the SME owner-managers’ perceptions on social engagement did not hold the same virility when compared to the context of their larger counterparts. These authors argued that the tangible benefits of CSR engagement had no effect on SMEs. In a similar vein, Baumann Pauly et al.’s (2013) study reported that the larger businesses were more effective than SMEs in their CSR communications.

However, the findings from this study’s second, third and fourth regression
equations indicated that the small and micro businesses were using digital media to improve their stakeholder engagement and to communicate about their responsible entrepreneurship issues.

Implications and Conclusions

SME managers and executives are in a position to enhance the effectiveness of their businesses’ communication efforts. This study has identified and analyzed the SME owner-managers’ attitudes toward the utilization of digital media for the communication of commercial, ethical and social responsibility issues.

Previous academic research has paid limited attention to the technology acceptance of digital media among small businesses, albeit a few exceptions (Taiminen and Karjaluoto, 2015; Baumann Pauly, Wickert, Spence and Scherer, 2013; Durkin et al., 2013; Taylor and Murphy, 2004). In this case, the research findings indicated that digital technologies and applications were perceived as useful by the SME owner-managers. This implies that the utilization of digital media can be viewed as a critical success factor that may lead to an improved engagement with stakeholders.

Several SMEs are already communicating about their responsible entrepreneurship through conventional and interactive media, including; social media, review sites, blogs, et cetera. These savvy businesses are leveraging their communications as they utilize digital media outlets (e.g., The Guardian Sustainability Blog, CSRwire, Triple Pundit and The CSR Blog in Forbes among others) to improve their reach, frequency and impact of their message.

In addition, there are instances where consumers themselves, out of their own volition are becoming ambassadors of trustworthy businesses on digital media (Du et al., 2010). Whilst other stakeholders may perceive these businesses’ posturing behaviors and greenwashing (Camilleri, 2017; Vorvoreanu, 2009).

A thorough literature review suggested that the positive word-of-mouth publicity through digital media may lead to strategic and financial benefits (Camilleri, 2017; Taiminen and Karjaluoto, 2015; Durkin et al., 2013). Therefore, businesses, including SMEs, are increasingly joining conversations in social media networks and online review sites. These sites are being used by millions of users every day. Indeed, there is potential for SMEs to engage with their prospects and web visitors in real-time.

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Filed under Business, Corporate Social Responsibility, digital media, Marketing, Small Business, SMEs, Stakeholder Engagement

Tourism Futures: Targeting Customers in the Digital Age

This is an excerpt from: Camilleri’s latest book on Travel Marketing (2018)

How to Cite: Camilleri, M. A. (2018). Market Segmentation, Targeting and Positioning. In Travel Marketing, Tourism Economics and the Airline Product (Chapter 4, pp. 69-83). Springer, Cham, Switzerland.

The advances in technology have enabled many businesses to reach their potential customers by using digital and mobile applications.

Google, Facebook, Ebay and Amazon, among others are dominating digital marketing; and are pushing the entire field of advertising to new levels. The use of personal info, web-browsing, search history, geographic location, apps and eCommerce transactions have gone mainstream. For example, Google has begun using transaction records to prove that its ads are working, and are pushing people to make more online purchases. This allowed the technology giant to determine the effectiveness of its digital ad campaigns and to verify their conversion rates.

All individuals leave a “digital trail” of data as they move about in the virtual and physical worlds. This phenomenon is called, “data exhaust”. Initially, this term that was used to describe how Amazon.com has used predictive analytics as it suggested items to its customers. However, pre­dictive analytics cannot determine when and why individuals may decide to change their habitual behaviours, as the possibility of “one off” events must never be discounted. Yet, a firm with sufficient scarce resources could be in a position to exploit big data and analytics to improve its businesses operations.

For instance, Deloitte Consulting have developed a mobile app that has enabled Delta Airlines’ executives to quickly query their operations. For instance, when users touch an airport on a map, the system brings up additional data at their disposal. Executives could also drill further down to obtain granular information on staffing requirements. and customer service levels, as they identify and predict problems in their airline operations.

Nevertheless, business intelligence and predictive analytics could possibly raise a number of concerns. Many customers may be wary of giving their data to the businesses and their stakeholders. Very often, the technological advances anticipate legislation, and its deployment. These contingent issues could advance economic and privacy concerns that regulators will find themselves hard-pressed to ignore. Some academics argue that the digital market and its manipulation may be pushing the limits of consumer protection law. Evidently, society has built up a set of rules that are aimed to protect personal information. Another contentious issue is figuring out the value of data and its worth in monetary terms. In the past, companies could have struggled to determine the value of their business; including patents, trade secrets and other intellectual property.

Targeted Segmentation through Mobile Devices

The mobile is an effective channel to reach out to many users. Portable devices, including smart phones and tablets are surely increasing the productivities and efficiencies of individuals as well as organisations. This has led to the growth of mobile applications (apps). As a result, the market for advertising on mobile is still escalating at a fast pace. Moreover, there are niche areas as new applications are being developed for many purposes on different mobile platforms.

Recent advances in mobile communication and geo-positioning technologies have presented marketers with a new way how to target consumers. Location-targeted mobile advertising involves the provision of ad messages to mobile data subscribers. This digital technology allows marketers to deliver native ads and coupons that are customised to individual consumers’ tastes, geographic location and the time of day. Given the ubiquity of mobile devices, location-targeted mobile advertising are increasingly offering tremendous marketing benefits.

In addition, many businesses are commonly utilising applications, including browser cookies that track consumers through their mobile devices, as they move out and about. Very often, when internet users leave the sites they visited, the products or services they viewed will be shown to them again in retargeted advertisements, across different websites. Several companies are using browsing session data combined with the consumers’ purchase history to deliver “suitable” items that consumers like. There are also tourism businesses who are personalising their offerings as they collect, classify and use large data volumes on the consumers’ behaviours. As more consumers carry smartphones with them, they may be easily targeted with compelling offers that instantaneously pop-up on their mobile screens.

Furthermore, consumers are continuously using social networks which are indicating their geo-location, as they use mobile apps. This same data can be used to identify where people tend to gather. This information is valuable to brands as they seek to improve their consumer engagement and marketing efforts. Therefore, businesses are using mobile devices and networks to capture important consumer data. For instance, smart phones and tablets interact with networks and convey information on their users’ digital behaviours and physical movements to network providers and ISPs. These devices have become interactive through the proliferation of technologies, including; near-field communication (NFC). Basically, embedded chips in the customers’ mobile phones are exchanging data with the retailers’ items possessing such NFC tags. The latest iPhone, Android and Microsoft smartphones have already incorporated NFC ca­pabilities. The growth of such data-driven, digital technologies is surely adding value to the customer-centric marketing. The latest developments in analytics are enabling businesses to provide a deeper personalisation of content as they use socio-demographic and geo-data that new mobile technologies are capable of gathering.

For example, mobile service companies are partnering with local cinemas, in response to the location-targeted mobile advertising; as cinema-goers may inquire about movie information, and could book tickets, and select their seats through their mobile app. These consumers who are physically situated within a given geographic proximity of the participating cinemas may receive location-targeted mobile ads. The cinemas’ ads will inform prospects what movies they are playing and could explain how to purchase tickets through their smart phone. The consumers may also call the cinemas’ hotlines to get more information from a customer service representative. Besides location-targeted advertising, the mobile companies can also promote movie ticket sales via mobile ads that are targeted to individuals, according to their behaviour (not by location). Therefore, companies may direct their mobile-ad messages to those consumers who had previously responded to previous mobile ads (and to others who had already purchased movie tickets, in the past months). Moreover, the cinema companies can also promote movies via Facebook Messenger Ads if they logged in the companies’ websites, via their Facebook account. Mobile users may also receive instant message ads via pop-up windows whenever they log into the corporate site of their service provider.

It is envisaged that such data points will only increase in the foreseeable future, as the multi-billion dollar advertising monopolies are being built on big data and analytics that are helping businesses personalise immersive ads as they target individual customers. The use of credit card transactions is also complementing geo-targeting and Google Maps, with ads; as the physical purchases are increasingly demanding personalisation, fulfillment and convenience. There may be consumers and employees alike who out of their own volition, are willing to give up their data for value. Therefore, the businesses need to reassure them through concise disclosures on how they will use personal data. They should clarify the purpose of maintaining their consumer data, as they are expected to provide simple user controls to opt in and out of different levels of data sharing. This way, they could establish a trust-worthy relationship with customers and prospects.

Companies are already personalising their shopping experience based on the user situation and history. Tomorrow’s tourism businesses are expected to customise the user experiences of their mobile applications and web interfaces, according to the specific needs of each segment. Big data and analytics capabilities are increasingly allowing businesses to fully leverage their rich data from a range of new digital touchpoints and to turn them into high impact interactions. Those businesses that are able to reorient their marketing and product-development efforts around digital customer segments and behaviours will be in a position to tap into the hyper-growth that mobile, social media and the wearables markets are currently experiencing.

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Filed under Airlines, Analytics, Big Data, digital media, Education, Hospitality, ICT, Marketing, tourism, Travel

Tourism and Technology: What the future holds for travel distribution?

mobile.pngThe development of digital media technologies, particularly the internet and social media are offering a wide range of possibilities to the travel industry. These latest technological advances have enabled many travel businesses, including airlines and hotels to manage their distribution channels in a more efficient and economical way.

With the changing landscape of travel e-commerce and the ubiquity of IT solutions which gather, store, and analyse data in a variety of ways; airlines have improved their ability to monitor their performance across channels. Very often, they are in a position to quickly adjust offers. Their prices are usually based on a variety of situations and circumstances, as they optimise communications and transactions.

By using big data and analytics on their customer behaviours, many travel businesses are taking advantage of channel-based distribution. Hence, the distribution networks have come a long way from the ticket counter. Evidently, travel and tourism businesses are leveraging themselves with data-driven marketing, as they seek new customers and prospects. For example, they may increase their profitability from high-yield customers as they are using elaborated pricing and revenue management systems. The travel distribution is evolving from its current passive, rigid, and technology-centric state to a more flexible, dynamic, and passenger-centric environment which we call ‘Active Distribution’.

Any changes in the tourism distributive systems may be stimulated by external macro factors such as politics and trade, global and national economies, technological innovations and access to them, et cetera. The airline industry could also be effected by increased competition from low-cost carriers, merger and acquisitions, and fuel costs, among other issues. However, the commercial future of the tourism industry may also be influenced by other factors, including travel distribution.

Tourism businesses can possibly become even more effective in how they sell their products and services, particularly if they deliver positive customer experiences. Tourists perceive value in customer-centric businesses. Most probably, in future, there will be significant improvements in terms of technologically enhanced customer services.

Tomorrow’s businesses will be serving passengers from geographically-diverse regions.  There will be more travellers from emerging markets and developing economies. The travel distribution systems will have to cater for senior citizens, as there are aging populations in many countries.

The distributive channels must be designed to accommodate a divergent nature of users. Tourism service providers and their intermediaries have to provide engaging, intuitive shopping experiences that tap into the traveller’s discretionary purchases.

The businesses will need to embrace new technologies and flexible distribution processes, as outmoded distribution components will be replaced. It is envisaged that the distributive systems will be increasingly relying on mobile devices as these technologies enable consumer interaction with speech and voice recognition software.

The tourism businesses will leverage themselves with artificial intelligence which could facilitate dynamic pricing as well as personalisation of services.

The distributive  systems could interface with virtual  reality software to help businesses merchandise their products in captivating customer experiences.

The third-party retailers will continue to form part of the distribution mix. However, many service providers will be using their direct channels to reach their targeted customers.

There will probably be fewer market intermediaries and online travel agencies will see significant declines.

It is very likely, that airlines will not have to pre-file volumes of defined fares through third-parties as they may not rely on inventory buckets to manage their selling capacity. The airlines must recognise the need to invest in new internal selling systems. Today’s passenger service systems lack the flexibility that airlines require. They are not adequate enough to serve  the airlines’ flexible and dynamic sales environments. These systems could be replaced with modular retailing platforms. Full Retailing Platforms (FRPs) will allows airlines to take back the control they require to be better retailers through any distribution channel (IATA, 2016).

However, Google, the multinational technology company, could be playing a much larger role in travel distribution. The technology giant could participate in, and possibly disrupt the tourism industry if it becomes an online travel agency. whether through acquisition or by launching a product of its own. In fact, its travel product, Google Flights is increasing in popularity among travellers.

Moreover, there have been recent developments in online payment facilities. Undoubtedly, there will further improvements in this area, as well. Payment providers like M-Pesa, Alipay, and PayPal will probably become more important.

In the foreseeable future, the travel marketplace will surely introduce new technologies and capabilities as multiple venture capital firms are increasingly investing in disruptive innovation.

There may be new businesses which could penetrate the market, including private air service operators who could provide “on-demand” airline services; alternatively, technology companies could develop or acquire their meta-search engines or online travel agencies.

Undoubtedly, the travel and tourism businesses need to find ways that intentionally overturn decades of outdated, distribution practices. The distribution community can choose to innovate and disrupt, or allow others to be leading innovators.

 

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