Essay: Voice Recognition's Impact On Peppers Broadbeach In Tourism (70 Characters)

The solution should be in the context of the selected organization in the industry mentioned below. You are allowed to select an organization in the industry mentioned below to demonstrate the requirements of this assignment. 

Demonstrate a creative and sustainable use of digital innovation in the ICT domain 
Identify implications for business model/business processes in the digital space 
Demonstrate an understanding of theoretical and practical issues in the integration of the latest developments in ICT and the digital space 
Ddemonstrate an understanding of diverse user stakeholder needs, organising and leading innovative initiatives, and the impact of interpersonal communication
Identify and explore contemporary challenges for the implementation of such innovation in a business environment.

Over the last decade, technology has been playing an important role in the tourism industry by helping improve customer experience and services, enhancing the operational experience, and helping reduce costs (Aldebert et al. 2011 p.1207). Both businesses and customers usually benefit from improved guest service systems, reservations, and communication. Through technology, the tourism industry has been able to replace human labor which is very expensive with technological labor hence helping in the reduction of labor costs and in the avoidance of issues with customer service. With the invention of artificial intelligence, voice recognition is currently helping in the transformation of the tourism industry by stealth. For example, Amazon Alexa, Windows Cortana, Google Now, and Apple Siri are leading in assisting consumers search without having to type and tapping into the preferences of users, previous search history, and geographical location, with the use of artificial intelligence algorithms for voice recognition and search (Canbek & Mutlu 2016 p.595). Therefore, the essay seeks to analyze the impact of technology trends in the voice recognition context in the tourism industry based on the case of Peppers Broadbeach Company.

Organizational Overview

Peppers Broadbeach soars high above Broadbeach’s premier dining and shopping precinct and offers an exclusive and chic haven for tourists who are looking for relaxation, sophistication, and luxury (Dedekorkut-Howes & Bosman 2015 p.72). At only an easy one hour drive south of Brisbane and only thirty-five minutes drive north of Gold Coast airport, Peppers Broadbeach consists of two towers which are architecturally impressive, each designed to reflect surfside surroundings and the beach. Peppers Broadbeach offers a perfect setting in the indulgence of life’s finer things and boasts of a luxury Gold Coast accommodation and a wide range of guest services choice.

Technology is advancing every day at a fast pace hence changing the way Peppers Broadbeach carry out its business activities. Some of the technology trends are leading to significant improvements thus changing how the organization plans its staff requirement, infrastructure, management structure and building (Cameron & Quinn 2011 p.6). The existing and latest technologies used in the organization include Wi-Fi infrastructure overhauls, digital conference facilities, mobile communication, and automation, near field communication (NFC) Robots and infrared sensors, internet on tap and media feedbacks.

The Wi-Fi overhauls have enabled the organization’s guests to connect effectively without interruptions hence attracting potential customers who can do their online business while still in the organization. In the past, the organization used to charge exorbitant rates and, therefore, customers who are technology savvy stayed in the organization for a very short time. The organization also has digital conference technologies such as Audio-visual, VoIP, real-time local services and internet local television. The mobile and automated communication have facilitated the effective online booking of Peppers Broadbeach with customers now being able to process payment for services in the comfort of their home.

The heavy reliance on search engines by Peppers Broadbeach makes the company susceptible to major changes in search and new trends thereby affecting their website’s traffic which in turn hikes revenue. Currently, voice recognition and search have been the main search trends which are highly driven by the availability and access to mobile devices which Peppers Broadbeach players must adapt to in order to increase the company’s revenue. Law et al. (2014 p.740) states that the voice recognition and search trends have assisted in the provision of new opportunities for all tourist companies as well as punishing the brands which never acknowledge the opportunities fast enough.

Existing Technology Analysis and Trends (Issues) in the Peppers Broadbeach

The mobile device growth in the tourism industry remains significant although it is less ascendant (Litvin et al. 2008 p.463). Aiming to tap into new clients who are allowed by the mobile device’s ubiquity, Peppers Broadbeach optimizes voice recognition for users who interact with the company’s website mainly through mobile platforms, which have poor internet speeds. The company has integrated lightweight mobile pages that can be cached on their servers and usually load fast hence creating the best experiences for users of mobile devices.

Peppers Broadband clients are using voice recognition and search more than ever due to its convenience, reliability, speed, ease, and interaction with mobile devices in handsfree mode. According to Gretzel et al. (2006 p.120) tech giants are aggressively battling for the command of the human voice, with the eyeball battle almost evolving to a possible final form. Voice recognition has enabled Peppers Broadbeach clients to change from typing to search queries which are conversational, longer, and natural.

Problem Statement

Voice recognition differs from the human comprehension of speech and, therefore, voice recognition lacks the redundancy and grammatical structure which humans use in the prediction of unspoken words since the words lack an arbitral sequence (Calder & Young 2005 p.61). Additionally, how humans ‘usually’ say things with the use of idioms and word mix makes it complicated to interact with voice recognition and search. Body language, including body movements and facial expressions, lack in the voice recognition and search hence making clients’ experiences feel unnatural. Moreover, noise makes it hard for the voice recognition technology to predict accurately what the person is trying to say and may lead to many unsuccessful attempts. Finally, spoken language can never be equal to written language as it is faster and more sophisticated due to channel variability and continuous speech (Zumalt 2005 p.182).

The availability and use of voice recognition for Peppers Broadbeach have enabled users to be increasingly aware of the reliability of the new voice artificial intelligence, therefore, expecting accurate and smarter responses. The aspect has changed the dynamics of voice recognition and searches in the company. Forstall et al. (2010 p.240) argues that in order to the client experience and solutions,  website contents have been optimized to follow a tone which is conversational, for longer searches characterized of voice searches, and for the offering of responses to clients’ queries.

Voice recognition describes the company’s website content and offers feedback from various search engines, in addition to the online texts and images which describe its web content. Local searches also emerge from voice recognition, which are searches confined within Peppers Broadbeach Company. Voice recognition has also enabled disabled clients to have easy access to the company’s services. For example, a client who has lost both arms can search and locate the services of Peppers Broadband. Furthermore, the illiterate have also been factored in as voice recognition foregoes the need for typing.

Business Model Canvas in Peppers Broadbeach

According to Osterwalder and Pigneur (2011 p.1) business model describes the rationale of how different organizations can create, deliver and capture the values of their internal and external stakeholders. Business model canvas is defined as a tool to describe, analyze and design business models through different elements which encompass four key areas including financial viability, customers, infrastructure, and offerings.

The scope of Voice Recognition in the Peppers Broadbeach Company

Customer Segments

According to Chan (2008 p.1) customer segmentation involves division of customers into groups basing on characteristics which are common thus the organization can be able to market each group effectively and appropriately. The types of customer segments that exist are niche market, mass market, diversified, segmented and multi-sided platform or market. The customer segments for voice recognition technology in Peppers Broadbeach are multi-sided platforms and for the technology to function a variety of stakeholders are required such as guests and management.

Alignment of the Business Model and Value Proposition

Value prepositions are used to create value for the customer segment by addressing the satisfying needs and problem. Furthermore, value propositions are thought to be innovative with the disruptive offer and therefore can add market offers with additional attributes and features. In the tourist industry in general, the values can be performance, customization, newness, cost reduction, price, usability, and prices. The value for voice recognition in Peppers Broadbeach includes performance, newness, accessibility, usability, and convenience. The greatest value for guest is accessibility to voice recognition services which are user-friendly, convenient and available. The greatest value for the management is to enhance customer satisfaction by using voice recognition to provide fast and accurate services to the guests. For the organization, the greatest value is to improve the profile of the company by effectively increasing its performance and market share. Therefore, through the assessment of all the values, it can be concluded that the main value of voice recognition is to satisfy customer needs than performance.

Conclusion

Voice recognition technology is ideal for the success of the organization as it will be fast and effective and also enhance customer satisfaction which is the ultimate goal of the organization. Ananth et al. (2010 p.1) argues that companies which adhere to the latest technology retain existing customers and attracts others; the voice recognition technology will boost company profile to the outside world. Despite the technology being up to date in terms of technology, the organization should also consider adopting the technology which is trending in the industry. Apart from voice recognition, the organization should adopt other technologies like smart room keys and infrared scanners. The smart key technology is a technology that allows the guest to unlock their doors by swiping their smartphones or tablets across a keyless pad on the door (Pesonen and Horster 2012 p.15). The technology will build customers’ confidence as they should not worry about picking up keys while the staff working at the front office will have little issues with new keys in case guests lose their keys. Furthermore, the organization should implement infrared scanners which minimize disruptions relating to housekeeping (Rees and Pellika 2010 p. 1). Instead of staff waking up guests during the cleaning process with phone calls and knocks, they should adopt infrared scanners that can be able to detect the body heat within the room and tell the staff who are cleaning that they should come back later. 

References

Aldebert, B., Dang, R. J., & Longhi, C. (2011). Innovation in the tourism industry: The case of Tourism@. Tourism management, 32(5), 1204-1213. France: University of Toulouse

Ananth, A. and Ramesh, R. and Prabaharan, B. (2010): Service quality gap analysis in private sector bank - a customer perspective. Published in: Indian Journal of Commerce and Management Studies , Vol. II, No. I (1. January 2011): pp. 245-252.

Calder, A. J., & Young, A. W. (2005). Understanding the recognition of facial identity and facial expression. Nature Reviews Neuroscience, 6(8), 641.

Cameron, K. S., & Quinn, R. E. (2011). Diagnosing and changing organizational culture: Based on the competing values framework. John Wiley & Sons. U.S: PB printing

Canbek, N. G., & Mutlu, M. E. (2016). On the track of artificial intelligence: Learning with intelligent personal assistants. Journal of Human Sciences, 13(1), 592-601.

Chan, C.C.H., 2008. Intelligent value-based customer segmentation method for campaign management: A case study of automobile retailer. Expert systems with applications, 34(4), pp.2754-2762.

Dedekorkut-Howes, A., & Bosman, C. (2015). The Gold Coast: Australia’s playground?. Cities, 42, 70-84.

Forstall, S.J., Melton, D.D., Sullivan, J.W. and Adler, D.B., Apple Inc, 2010. Immediate search feedback. U.S. Patent 7,788,248.

Gretzel, U., Fesenmaier, D. R., Formica, S., & O’Leary, J. T. (2006). Searching for the future: Challenges faced by destination marketing organizations. Journal of Travel Research, 45(2), 116-126.

Law, R., Buhalis, D., & Cobanoglu, C. (2014). Progress on information and communication technologies in hospitality and tourism. International Journal of Contemporary Hospitality Management, 26(5), 727-750.

Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism management, 29(3), 458-468.

Osterwalder, A. and Pigneur, Y., 2011. Aligning profit and purpose through business model innovation. Responsible management practices for the 21st century, pp.61-75.

Osterwalder, A., Pigneur, Y., Bernarda, G. and Smith, A., 2014. Value proposition design: How to create products and services customers want. John Wiley s& Sons.

Pesonen, J. and Horster, E., 2012. Near field communication technology in tourism. Tourism Management Perspectives, 4, pp.11-18.

Rees, W.G. and Pellika, P., 2010. Principles of remote sensing. Remote Sensing of Glaciers. London. Taylor & Francis Group

Zumalt, J. R. (2005). Voice recognition technology: Has it come of age?. America: Information technology and libraries, 24(4), 180-185.