Developing Information Technology Standards

Last Updated: 19 Dec 2022
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Information technology (IT) plays an important role in economic growth, and social development, it is changing work and the world. Consider the invention of internet, the mobile phone, home wireless networks, computer algorithms that recognize faces, or self-driving vehicles. High speed internet connectivity has been available for decades, the distribution of high-speed internet connectivity to all over the world is still in the making. Technology for self-driving was recently implement but quickly removed of the market because one the car crashed and killed a passenger. Information technology (IT) standards are sets of specification for communication or performing actions that ensure that various technologies or products that implement certain specifications are compatible (e.g. David and Greenstein 1990; Lyytinen et al. 2008; Nicerson and zur Muehlen 2006; Weitzel et al. 2006).

IT standards are central to the integration of heterogeneous IS within organizations and thereby reduce the cost of managing IT infrastructure (Chen and Forman 2006). Both software development and the hardware involved in the IT industry include everything from computer systems, to the design, implementation, study and development of IT and management systems. The IT sector has emerged as a major global source of both growth and employment. Economies for the Information technology industry are high and unlike other common industries, the IT industry is knowledge-based.

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The rate of diffusion of technology has influenced many forces, including demand, cost, technology maturity, competitive pressures, societal acceptance, government policies and regulations, safety requirements, resistance by entrenched interests, and the interventions of entrepreneurs in creating and marketing products. Currently the widespread use of computers, is digital and online data. Moving services and data to computers and online is what is referred as digitization, this changed and affected lives. Majority of people now use retail services such as Amazon, navigation services in cars and smartphones and free video internet calls. Businesses have been revolutionized by new computer systems that capture, organize, optimize, and program business processes. Healthcare is also changing using new computer technologies that will enhance the efficiency and quality of health-care delivery.

Education has also been impacted by digitization, with an increase of students taking online courses that include video lectures, and instructors giving instructions and answering questions through online discussion boards. Digitizing has creating opportunity for some workers to work at home using video conferencing and online business processes. Most jobs today involve in some communication with IT systems, that most of the workforce are informed and trained to use all the systems. Employees as well will encounter problems with information technology, and everyone depends on the systems to work perfectly for any task to be completed.

American corporations have spent billions of dollars on digitalization operations and investing in large systems, such as supply chain management, customer relationship management and human resource management. These systems cost tens of thousands of dollars and it will take several years before they are implemented. The process of redesign and employee training, that includes on the job training will exceed the direct costs of IT hardware and software, to which has been described to benefit the organization over many years.

Artificial intelligence, also known as AI, refers to principals and applications of computer algorithms that attempt to imitate various aspect of human intelligence. A1 systems is based on a machine learning methods that is algorithms that gather their own decision making rules from training data by joining large data sets. For example, fraud detection strategies are now developed by machine learning algorithms that analyze millions of historical credit card transactions. Machine learning has increased in production of variety A1 subfields including computer vision, speech recognition, robot control, automated translation between languages, and automated decision making. Over decades A1 systems has produced a number of systems that include the following:

• Intelligent agents, such as Apple’s Siri, Google Now, Microsoft’s Cortana, and Amazon’s Echo. These A1 systems combine speech recognition, background knowledge about the user.

• Self-driving vehicles. Tesla in 2015 released software that allows its customers to put their automobile into self-driving mode on public highways. Uber has recently begun testing this type of cars on the streets of Pittsburg. This demonstrates that computer insight and control and in particular, computer vision and self-steering have reached an important beginning of practical reliability.

• A1 and robotic system that sense and act within the physical world. An example is Nest’s intelligent thermostat, which learns to customize individual buildings their occupants’ routine.

• A1 systems capable of answering many factual questions. IMB’s Watson system defeated the world Jeopardy champion in 2011. Wolfram|Alpha provides a similar broad-scope resource for answering diverse accurate questions.

Tremendous progress has been made in computers, especially in the areas of computer vision and speech recognition. Computer vision is used today in different application such as fingerprint recognition at safety barriers, high speed procession of handwritten address on letter by the U.S. Postal Service, reading of checks deposited at ATMs or via cell phone cameras, and recognition of faces in personal online photo albums.

Settling on a single IT standard may lead to reduced competition and higher prices for customers. (Fuentelsaz et al.2012; Lee and Mendelson 2007). Positive externalities from additional suppliers that join a technological development path support of a standards candidate under development. Direct supply-side network effects are positive externalities generated by the number of suppliers that support a standard of candidates, for example, learning effects, decreased technological uncertainty, the provision of complementary and enabling technologies, and increase legitimacy associated with a technological solution (Arthur 1989; Jacpbsspm amd Bergel 2204; Vam de Vem amd Garud 1989; Wade 1995; Zhao et al. 2011).

While high imitation costs may lead to better IT standards on average, they also lead to a prolonged diversity of standards, which has negative short term welfare effects. As the Bluetooth example illustrates, battles between competing standards candidates may be resolved based on suppliers’ decisions long before any significant competition in the end user market has occurred (Christ and Slowak 2009; Hagiu 2006; Hill 1997).

References:

Information Technology, A. and the U. S. W. (2017). Information Technology and the U.S. Workforce : Where Are We and Where Do We Go From Here? Washington, DC: National Academies Press.
Supply-side network effects and the development of information technology standards; Uotila, Juha; Keil, Thoma; Maula, Markku ; MIS Quarterly Vol. 41.4. pp. 1207-1226/December 2017 

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Developing Information Technology Standards. (2022, Dec 19). Retrieved from https://phdessay.com/developing-information-technology-standards/

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