15 research outputs found

    WHY DO PEOPLE REJECT TECHNOLOGIES โ€“ A LITERATURE-BASED DISCUSSION OF THE PHENOMENA โ€œRESISTANCE TO CHANGEโ€ IN INFORMATION SYSTEMS AND MANAGERIAL PSYCHOLOGY RESEARCH

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    In 2008, Ford et al. (2008) pointed out for management research, that โ€œit is time to expand our understanding of resistance to changeโ€. Since 1947, when Kurt Lewin discuss the first time the concept of resistance to change within his field theory, managerial psychology researchers have extended, criticized, modified and re-conceptualized the understanding of employeesโ€Ÿ responses to change initiatives. Also information systems research has identified resistance to change as major reason for IT project failures. However, as our analysis in this paper shows, there are a lot of opportunities for IS research to research resistance to IT-induced change. Using a literature review the paper discusses different concepts of resistance to change from managerial psychology and IS research in order to provide a better understanding of resistance to IT-induced change. The paper highlights implications from managerial psychology research to update the understanding of resistance to change in information systems research

    User Resistance Factor to UTM e-learning in Post- Implementation

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    E-learning stands for Electronic Learning. E-Learning systems are becoming mature technologies to support study method in the university. However, there are factors frequently cited as the major reason for the failure of E-Learning system in post implementation is โ€œUser Resistanceโ€. E-Learning implementation doesnโ€™t finish after the program run, instead the real test of the system starts when a user begins using the system. The main purpose of this study is to investigate the factors that influence user resistance in E-Learning post implementation stage. To achieve this objective, the quantitative method was conducted with 400 E-Learning end users. The result shows Resistance due to change, User Age, Cultural study method, User Expectations, Previous Bad Experience, Lack of Education, Training are the factors behind user resistance. Recommendations and guideline to avoid user resistance in E-Learning post implementation is also presented. The benefits and outcomes of this study shall aid university to overcome user resistance in post E-Learning implementation. Keywords: User resistance factor; E-Learning; Post Implementation; UTM E-Learnin

    A DECISION SUPPORT SYSTEM DESIGN TO OVERCOME RESISTANCE TOWARDS SUSTAINABLE INNOVATIONS

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    The concept of sustainability has been acknowledged as one of the central and most important issues of our time. However, technological innovations which provide a more sustainable way of living, for instance electric cars, are not always welcomed with open arms by consumers but often resisted at the beginning. As such, human resistance behavior can be explained as an interplay of different personality traits that favour the status quo. In this study, a decision support system design is introduced which bases on the concept of digital nudging that addresses innovation resistance on an individualโ€™s cognitive level by de-biasing innovation trial decision-making. An experimental pre-study is conducted to test the influence of different DSS modifications on the selection of electric cars in an online rental car booking scenario. First results show that DSS which set sustainable innovations as default option have a significantly positive effect on their trial probability while priming consumers towards electric car trial has no significant effect

    Overcoming Innovation Resistance beyond Status Quo Bias - A Decision Support System Approach (Research-in-Progress)

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    When innovative products and services are launched to the market, many consumers initially resist adopting them, even if the innovation is likely to enhance their life quality. Explanations for this behavior can also be found in specific personality traits and in general pitfalls of human decision-making. We believe that decision support systems (DSS) can help alleviate such innovation resistance. We propose a DSS design that addresses innovation resistance to complex innovations on an individualโ€™s cognitive level. An experimental study will be conducted to test the influence of different DSS modifications on the perception and selection of complex innovations. We aim to identify levers for reducing innovation resistance and to derive DSS design implications.

    User Acceptance of New Technology in Mandatory Adoption Scenario for Food Distribution in India

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    Ubiquitous utilization of information and communication technologies (ICTs) has led the governments of various countries to use ICTs in public administration and social welfare initiatives. Direct use of e-governance technology by citizens in developing countries is hindered by lack of training, education and infrastructure. This makes it inevitable to employ intermediary users who can bridge this gap between technology use and beneficiaries. Analyzing the technology adoption behavior of intermediaries could help policy makers and designers of e-governance technologies to create devices, processes and training programs that target the factors that inhibit as well as encourage the use of ICTs among technology users. We study the effect of technology characteristics and usersโ€™ internal traits on technology satisfaction of intermediaries who are mandated by the government to use android tablets in order to provide efficient services to end-users in the Indian food security supply chain. We further translate the results into tangible recommendations in context of infrastructure, usersโ€™ traits, business performance, and technology and policy design. The research model proposes that certain technology characteristics (screen design, technology relevance and terminology) and usersโ€™ internal traits (resistance to change, technology anxiety, trust in internet and result demonstrability) influence their technology satisfaction, either directly or indirectly through UTAUT constructs. Results indicated that resistance to change, technology anxiety, trust in internet, screen design and terminology had an impact on ICT usersโ€™ technology adoption behavior. Result demonstrability and technology relevance were found to have no effect on technology satisfaction in case of mandatory use

    Technology adoption in the public distribution system of Chhattisgarh, India: Analysis of factors that facilitate the transition to technology utilization in food distribution

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    Information and communication technologies in public administration and social welfare initiatives are increasingly being used by various countries with an intent to augment transparency and provide better services to citizens. However, lack of infrastructure, education, technology literacy, and training keeps a major proportion of target population deprived of the benefits of these initiatives in various developing countries. Hence services of technology intermediaries are utilized to bridge this gap between the benefits of e-government technologies and citizens. The public distribution system (PDS) is the biggest poverty alleviation program in India that aims to provide subsidized food grains and other essential commodities to below poverty line households through a network of fair price shops. Under the centralized online real-time electronic public distribution system, the state of Chhattisgarh implemented various technological and administrative reforms to empower end-beneficiaries of the PDS supply chain. Fair price shop salespersons, who are the users of implemented technologies, face various challenges in making this transition from manual transactions to automated transactions. These intermediaries play a critical role in successful implementation of any technology-based policy change. It is also essential to analyze their technology adoption behavior due to the mandatory nature of technology use in e-governance. This research attempts to analyze and understand the adoption of mandatory e-governance technologies from intermediary usersโ€™ perspective. The first study aimed to identify and prioritize challenges faced by technology users in mandatory technology adoption of point of sale devices that were implemented in fair price shops of Chhattisgarh to replace the paper-based commodity distribution system. Data collected from 170 fair price shops were analyzed using the quality management tools of list reduction, affinity diagram, and Pareto chart. The result of the list reduction technique established a final set of 33 challenges faced by fair price shop salespersons in adopting the mandated technology. This list of challenges was then organized and categorized into six priority areas that required improvement for easier technology adoption. A Pareto chart was then used to prioritize and identify the areas that required immediate attention. These priority areas, in order of their importance, included โ€œlack of infrastructure,โ€ โ€œdesign of device hardware,โ€ โ€œprocess design,โ€ โ€œsalespeopleโ€™ errors,โ€ โ€œgovernment support,โ€ and โ€œsoftware designโ€. Results of this study could help the government agencies to channelize their resources on areas that require immediate attention and to take into consideration the technology usersโ€™ perspective while expanding technology-based policy implementations. Improper device design, high maintenance costs, and poor network strength led to replacement of point of sale devices with tablets. Although improvement in the areas identified in previous study would enable an easier transition to technology use, there are various other driving factors that could influence the technology adoption by intermediary users. Therefore, the second study aimed to analyze the effect of technology characteristics and usersโ€™ internal traits on the technology adoption behavior of fair price salespersons. The need for this analysis is underscored by mandatory nature of technology adoption in e-governance. Data collected from 176 fair price shops from 167 villages of three districts of state of Chhattisgarh were analyzed using partial least square structural equation modeling. Technology satisfaction, rather than technology acceptance, is a more relevant outcome variable to study in mandatory adoption scenario. Therefore, the effect of various characteristics of implemented technology and usersโ€™ internal traits on technology satisfaction was modeled using an extension of the unified theory of acceptance and use of technology (UTAUT). The proposed model established that technology characteristics of โ€œscreen designโ€ and โ€œterminologyโ€ and usersโ€™ internal traits of โ€œresistance to change,โ€ โ€œtechnology anxiety,โ€ and โ€œtrust in internetโ€ influenced their technology satisfaction either directly or indirectly through UTAUT constructs performance expectancy, effort expectancy, social influence, and facilitating conditions. However, โ€œtechnology relevanceโ€ and โ€œresult demonstrabilityโ€ had no effect on technology satisfaction in a mandated-use environment

    Resistance to IT-induced Change - Theoretical Foundation and Empirical Evidence

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    In this PhD thesis the question โ€œWhy do people reject technologies?โ€ is investigated and a variety of theoretical founded and empirical evaluated answers are given. Too many IT implementation and organizational change projects in firms still fail as the underling Information Systems are inadequately used. The thesis evaluates the reasons for user resistance behavior including individual characteristics such as personality traits, process characteristics, technology characteristics, and characteristics of the change process. Moreover, it can be shown that user resistance is not only related to the observed usage behavior, but also in work- and process-related consequences. The results contribute not only to IT adoption and change management literature, but also to the literature on Human Resources Information Systems (HRIS) as the thesis investigates employeesโ€™ reactions to information systems in HR departments

    Creating an information systems security culture through an integrated model of employees compliance

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    Employeesโ€™ non-compliance with information systems security policies has been identified as a major threat to organizational data and information systems. This dissertation investigates the process underlying information systems security compliance in organizations with the focus on employees. The process model is complex, comprising many normative, attitudinal, psychological, environmental, and organizational factors. Therefore, the study of information security compliance requires a holistic assessment of all these factors. This dissertation seeks to achieve this objective by offering a comprehensive and integrated model of employee behavior especially focused towards information security compliance. The research framework is influenced by the Reciprocal Determinism Theory which explains individuals psycho-social functioning in terms of triadic reciprocal causation. Several theories explain the role of various factors forming the intellectual puzzle. These are: General Deterrence Theory, Social-Exchange Theory, Social Learning Theory, Expectation-Disconfirmation Theory, Rational Choice Theory, Cognitive Dissonance Theory, Reactance Theory, and Status-Quo Bias Theory. This dissertation makes several significant contributions to literature and to practitioners. Several new factors that influence compliance decisions by employees have been proposed, namely task dissonance, self-policing, word-of-mouth, and habit. For the first time, top management support has been examined as a multi-dimensional construct which provides a better understanding of the phenomenon. Also for the first time, this dissertation constructs a process model to examine the interactions between punishment severity and certainty and top management support and normative factors. It also investigates the interactions between normative and psychological factors, namely resistance and self-policing on information security compliance. This dissertation emphasizes that the practitioners should consider all the relevant factors in order to manage the information security compliance problem. Therefore, it is more useful to think in terms of establishing a security culture that embodies all the relevant factors prevalent in an organization. The dissertation is guided by positivist paradigm. Hypotheses are tested and validated using established quantitative approaches, namely data collection using survey and structural equation modeling. Major findings were derived and most of the dissertationโ€™s hypotheses were supported. The findings are discussed, and the conclusions, significant theoretical and practical implications of the findings, limitations, and recommendations for future research are presented

    Determinants of Intention to Use New Technology: An Investigation of Students in Higher Education

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    The federal government continues to monitor the cost of paper texts as an essential component of postsecondary education expenses. The Higher Education Act (HEA), which was initially passed in 1965, was created to buttress the educational resources of colleges and universities. Along with addressing the benefits of financial aid in postsecondary and higher education, the act referenced the projected financial burdens of paper texts. The last 2008 reauthorization suggested that colleges and universities develop plans to reduce the costs of college. Congress is currently working to reauthorize the legislation. Based on this information, the problem identified in this study explored how to use the results of the study to develop a framework that may be used by universities. This framework could be used to consider the success (or failure) of the intention to use e-texts in student learning, given how the cost of textbooks contributes to the perceived high cost of college attendance. The primary goal of the study was to evaluate studentsโ€™ perceptions of the usefulness of e-texts. The subordinate goal was to address the financial benefits of e-texts. In this study, the author has explored the perceived ease of use, perceived usefulness, and computer self-efficacy involved in the actual use of new technology such as textbooks in electronic format among undergraduate, postsecondary or university students. The main research questions for the study were: โ€œHow do the variables perceived ease of use, perceived usefulness, and computer self-efficacy impact the intention to use, which may be a predictor of actual use of new technology?โ€ and โ€œHow will the results of this study assist institutions of higher education in planning for the successful acceptance of new technologies, which may or may not be a predictor of actual use?โ€ The researcher used a Web-based survey and selected a sample of 5,600 undergraduate students from two universities. There were 482 complete responses to the survey. The context of the study included two traditional, land-based, universities. This was an exploratory, quantitative, qualitative research study. The research study measured the level of impact of perceived ease of use, perceived usefulness, and computer self-efficacy on the intention to use that may or may not lead to the actual use of new technology. The researcher investigated the topic and provided a framework for identifying factors that may lead to the intention to use new technology, which may determine the actual use of technology (i.e., technology acceptance). The higher levels of studentsโ€™ perceived ease of use, and perceived usefulness of the e-texts, the more apt the student is to choose an e-text as opposed to a paper text. The lower costs of e-texts in comparison to paper texts would be a positive predictor of financial benefits for the students that choose to use e-texts. The financial gains in the purchasing of e-texts could lead to a positive impact on the total of college and education costs. The author also concluded that the market for recreational reading continues to grow for e-texts usage. Academic use of e-texts still represents a lesser portion of the market place. This study contributed to the body of knowledge, profession, and overall literature in the field of study regarding intentions to use new technology, user acceptance research, and information systems. The results of the study have provided a framework for launching new technology within a postsecondary school environment

    Development of UX design guidelines by innovation adoption process based on prior experience

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๋ฏธ์ˆ ๋Œ€ํ•™ ๋””์ž์ธํ•™๋ถ€, 2017. 8. ์ •์˜์ฒ .๋ณธ ์—ฐ๊ตฌ๋Š” ์‚ฌ์šฉ์ž์˜ ์‹ค๋ฌผ๋งค์ฒด๋ฅผ ํ†ตํ•œ ์„ ํ–‰๊ฒฝํ—˜์„ ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค๋ฅผ ํ†ตํ•œ ๊ฐ€์ƒ ๊ฒฝํ—˜์œผ๋กœ ์ „ํ™˜ํ•˜๋Š”๋ฐ ์žˆ์–ด, ์‚ฌ์šฉ์ž์˜ ์ธ์ง€ ๋ถ€๋‹ด์„ ์™„ํ™”ํ•˜์—ฌ ์„œ๋น„์Šค ์ฑ„ํƒ๋ฅ ์„ ๋†’์ด๋ ค๋ฉด ์–ด๋–ป๊ฒŒ ๋””์ž์ธํ•ด์•ผ ํ•˜๋Š”์ง€์— ๋Œ€ํ•œ ๊ฒƒ์ด๋‹ค. ์ด์— ๋”ฐ๋ผ, ์ด๋ก ์  ๊ณ ์ฐฐ๊ณผ ์‚ฌ๋ก€์—ฐ๊ตฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ, ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •์˜ ๊ฐ ๋‹จ๊ณ„์—์„œ ๋ถ€์ •์  ์ธ์ง€์š”์ธ์— ๋Œ€ํ•œ ์กฐ์ ˆ ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ธ์ •์  ์ธ์ง€์š”์ธ๊ณผ ๊ด€๋ จ๋œ UX๋””์ž์ธ ๊ฐ€์ด๋“œ๋ผ์ธ์„ ๊ฐœ๋ฐœํ•˜๋Š” ๊ฒƒ์„ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ์ƒ๊ธฐ ์—ฐ๊ตฌ๋ชฉ์ ์„ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์Œ 3๊ฐ€์ง€ ์—ฐ๊ตฌ๋ฌธ์ œ๋ฅผ ์„ค์ •ํ•˜์˜€๋‹ค. 1. ์‚ฌ์šฉ์ž๊ฐ€ ์ƒˆ๋กœ์šด ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค๋ฅผ ์ฑ„ํƒํ•˜๊ธฐ๊นŒ์ง€ ์–ด๋–ค ๊ณผ์ •์„ ๊ฑฐ์น˜๋Š”๊ฐ€? 2. ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •์˜ ์ง„ํ–‰์„ ์ €ํ•ดํ•˜๋Š” ๋ถ€์ •์  ์š”์ธ์€ ๋ฌด์—‡์ด๋ฉฐ, ์ด์— ๋Œ€ํ•œ ์กฐ์ ˆ์ž‘์šฉ์„ ํ•˜๋Š” ๊ธ์ •์  ์š”์ธ์€ ๋ฌด์—‡์ธ๊ฐ€? 3. ๊ธ์ •์  ์š”์ธ์„ ๊ฐ•ํ™”ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์–ด๋–ป๊ฒŒ ๋””์ž์ธํ•ด์•ผ ํ•˜๋Š”๊ฐ€? ๋ณธ ์—ฐ๊ตฌ๋Š” ์„ ํ—˜์ ์œผ๋กœ ์ ‘๊ทผํ•ด์•ผ ํ•˜๋Š” ์ƒˆ๋กœ์šด ๊ฐ€์ƒ ๋งค์ฒด๋ฅผ ์–ด๋–ป๊ฒŒ ๋””์ž์ธํ•  ์ˆ˜ ์žˆ๋Š”๊ฐ€์— ๋Œ€ํ•œ ๊ฒƒ์ด๋ฏ€๋กœ, ์ „ํ†ต์ ์ธ ์˜คํ”„๋ผ์ธ ์ƒ๊ฑฐ๋ž˜ ์‹œ์Šคํ…œ์— ํŒจ๋Ÿฌ๋‹ค์ž„์˜ ๋ณ€ํ™”๋ฅผ ๊ฐ€์ ธ์˜ฌ ๊ฒƒ์ด๋ผ ๊ธฐ๋Œ€๋˜๋Š” ํ˜์‹  ๊ธฐ์ˆ ์ธ ๋ชจ๋ฐ”์ผ ๊ฒฐ์ œ ์„œ๋น„์Šค๋ฅผ ์—ฐ๊ตฌ๋Œ€์ƒ์œผ๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ์„ ํ–‰๊ฒฝํ—˜์ด ์œ ์‚ฌํ•˜๋‹ค๋Š” ์ „์ œ ํ•˜์— ๋น„๊ต๋ถ„์„์ด ๊ฐ€๋Šฅํ•˜๋ฏ€๋กœ, ์Šค๋งˆํŠธ ๋””๋ฐ”์ด์Šค๊ฐ€ ๋ณธ๊ฒฉ์ ์œผ๋กœ ๊ตญ๋‚ด์— ์ƒ์šฉํ™”๋œ 2010๋…„ ์ดํ›„๋ถ€ํ„ฐ 2017๋…„ ์ƒ๋ฐ˜๊ธฐ๊นŒ์ง€ ์˜คํ”„๋ผ์ธ ๊ฒฐ์ œ๋ฅผ ํ•ต์‹ฌ ๊ธฐ๋Šฅ์œผ๋กœ ํ•œ ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค๋ฅผ ์ง€์†์ ์œผ๋กœ ์ถœ์‹œ ๋ฐ ์šด์˜ํ•œ S์‚ฌ์™€ K์‚ฌ์˜ ๋ชจ๋ฐ”์ผ ๊ฒฐ์ œ ์„œ๋น„์Šค๋“ค์„ ์‚ฌ๋ก€๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ณผ์ •์œผ๋กœ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์ฒซ์งธ. ํ˜์‹ ์ฑ„ํƒ ๋ฐ ์ €ํ•ญ ์ด๋ก ๊ณผ UX๊ณผ์ •์— ๋Œ€ํ•œ ์ด๋ก ์  ๊ณ ์ฐฐ์„ ํ†ตํ•˜์—ฌ, ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค์˜ ํŠน์„ฑ์ด ๋ฐ˜์˜๋œ ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •์„ ์ •์˜ํ•˜๊ณ , ๊ฐ ๋‹จ๊ณ„ ๋ณ„ ๋ถ€์ •์ ใ†๊ธ์ •์  ์ธ์ง€์š”์ธ์„ ์ถ”์ถœํ–ˆ๋‹ค. ๋‘˜์งธ. ํ˜์‹  ์ฑ„ํƒ๊ณผ์ • ๋ณ„ ํŠน์„ฑ์— ๋”ฐ๋ผ ์„ ํ–‰์—ฐ๊ตฌ์— ์–ธ๊ธ‰๋œ ๋‹ค์–‘ํ•œ ์ธ์ง€์š”์ธ๋“ค์„ ์ƒํ˜ธ๊ด€๋ จ์„ฑ์„ ํ† ๋Œ€๋กœ ์žฌ๋ฐฐ์น˜ํ•˜์—ฌ ์—ฐ๊ตฌ๋ชจ๋ธ์„ ๊ตฌ์„ฑํ–ˆ๋‹ค. ์…‹์งธ. ์—ฐ๊ตฌ๋ชจ๋ธ์„ ํ† ๋Œ€๋กœ, ํ™•์žฅ๋‹จ๊ณ„์— ์ง„์ž…ํ•œ S์‚ฌ์˜ ๋ชจ๋ฐ”์ผ ๊ฒฐ์ œ ์„œ๋น„์Šค ์ „๊ฐœ๊ณผ์ •์„ ์‚ดํŽด ๋ณด๊ณ , ๊ฐ ๋‹จ๊ณ„ ๋ณ„ ์‹œ์‚ฌ์ ์„ ๋„์ถœํ–ˆ๋‹ค. ๋„ท์งธ. ์—ฐ๊ตฌ๋ชจ๋ธ์„ ํ† ๋Œ€๋กœ, ๋„์ž…๋‹จ๊ณ„์— ๋จธ๋ฌผ๋Ÿฌ ์žˆ๋Š” K์‚ฌ์˜ ๋ชจ๋ฐ”์ผ ๊ฒฐ์ œ ์„œ๋น„์Šค ์ „๊ฐœ๊ณผ์ •์„ ์‚ดํŽด ๋ณด๊ณ , ๊ฐ ์š”์†Œ ๋ณ„ ์‹œ์‚ฌ์ ์„ ๋„์ถœํ–ˆ๋‹ค. ๋‹ค์„ฏ์งธ. ์—ฐ๊ตฌ๋ชจ๋ธ์„ ํ† ๋Œ€๋กœ, S์‚ฌ์˜ ๋ชจ๋ฐ”์ผ ๊ฒฐ์ œ ์„œ๋น„์Šค์— ๋Œ€ํ•œ ์‚ฌ์šฉ์ž ๋ฐ˜์‘์„ ์‚ดํŽด ๋ณด๊ณ , ๊ฐ ๋‹จ๊ณ„ ๋ณ„ ์‹œ์‚ฌ์ ์„ ๋„์ถœํ–ˆ๋‹ค. ์ตœ์ข…์ ์œผ๋กœ ์ƒ๊ธฐ ๊ณผ์ •์„ ํ†ตํ•ด ์ถ”์ถœ๋œ ์‹œ์‚ฌ์ ์„ ํ† ๋Œ€๋กœ ํ˜์‹  ์ฑ„ํƒ๊ณผ์ • ๋ณ„ UX๋””์ž์ธ ๊ฐ€์ด๋“œ๋ผ์ธ์„ ์ œ์•ˆํ–ˆ๋‹ค. ๋ณธ ๊ฐ€์ด๋“œ๋ผ์ธ์€ ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค์˜ ๊ทผ๊ฐ„์„ ์ด๋ฃจ๋Š” ๊ฐœ๋…๊ณผ ์กฐ๊ฑด๊ณผ ์„œ๋น„์Šค ์ธ์ง€๋ถ€ํ„ฐ ์‹œ์žฅ ์ •์ฐฉ์— ์ด๋ฅด๊ธฐ๊นŒ์ง€๋ฅผ 4๋‹จ๊ณ„๋กœ ๊ตฌ๋ถ„ํ•œ ๊ธฐ๋Œ€ โ†’ ๋„์ž… โ†’ ์ ์šฉ โ†’ ํ™•์žฅ์˜ ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •์„ ํฌํ•จํ•˜์—ฌ ์ด 5๊ฐœ์˜ ์žฅ์œผ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ๊ฐœ๋…๊ณผ ์กฐ๊ฑด์€, ์‚ฌ์šฉ์ž๊ฐ€ ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค๋ฅผ ํ†ตํ•ด ์ง€์›๋ฐ›์„ ์ˆ˜ ์žˆ๋Š” ํ–‰๋™(Action)์— ๋Œ€ํ•œ ๋ช…ํ™•ํ•œ ๊ฐœ๋… ์ œ์‹œ์™€ ์‚ฌ์šฉ์ž์™€ ์„œ๋น„์Šค ๊ฐ„ ์‹ ๋ขฐ๊ด€๊ณ„ ํ˜•์„ฑ ๋ฐ ์œ ์ง€์— ๋Œ€ํ•œ ๊ฒƒ์œผ๋กœ, ์ „ ๋‹จ๊ณ„์—์„œ ์ง€์†์ ์œผ๋กœ ์ถ”๊ตฌ๋˜์–ด์•ผ ํ•  ์„œ๋น„์Šค์˜ ๊ถ๊ทน์  ๋ชฉ์ ๊ณผ ๊ฐ€์น˜์— ๋Œ€ํ•œ ์žฅ์ด๋‹ค. ๊ธฐ๋Œ€๋Š” ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •์˜ ์ฒซ ๋ฒˆ์งธ ๋‹จ๊ณ„๋กœ, ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค ์‚ฌ์šฉ๊ณผ ๊ด€๋ จ๋œ ์‹ค์ œ ์ƒํ™ฉ(Scene)์„ ๋ช…์‹œํ•˜์—ฌ ์‚ฌ์šฉ์ž๊ฐ€ ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค์— ๋Œ€ํ•œ ์„ ํ–‰๊ฐœ๋…์„ ํ˜•์„ฑํ•˜๋Š” ์žฅ์ด๋‹ค. ๋„์ž…์€ ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •์˜ ๋‘ ๋ฒˆ์งธ ๋‹จ๊ณ„๋กœ, ์‹ค์ œ ๋Œ€์ƒ(Real Object) ์‚ฌ์šฉ ์ƒํ™ฉ์„ ์•”์‹œํ•˜๋Š” ๋ฉ”ํƒ€ํฌ(Metaphor)์™€ ์ œ์Šค์ฒ˜(Gesture)๋กœ ์„ ํ–‰๊ฐœ๋…๊ณผ ๊ฐ€์ƒ๊ฒฝํ—˜์„ ๋งค๊ฐœํ•˜๋Š” ์žฅ์ด๋‹ค. ์ ์šฉ์€ ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •์˜ ์„ธ ๋ฒˆ์งธ ๋‹จ๊ณ„๋กœ, ๋ฐ˜๋ณต์  ์‚ฌ์šฉ์˜ ํšจ์ต์„ ๋†’์ด๊ธฐ ์œ„ํ•ด ๊ฐ€์ƒ๋งค์ฒด(Virtual Object)๋ฅผ ๋ณ„๋„ UI๋กœ ๋ถ„๋ฆฌํ•˜๊ณ , ํ•ต์‹ฌ ๊ธฐ๋Šฅ์„ ๊ณ ๋„ํ™”ํ•˜๋Š” ์žฅ์ด๋‹ค. ํ™•์žฅ์€ ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •์˜ ๋งˆ์ง€๋ง‰ ๋‹จ๊ณ„๋กœ, ํƒ€ ๋งค์ฒด ๋˜๋Š” ์„œ๋น„์Šค์™€์˜ ์—ฐ๊ณ„๋ฅผ ํ†ตํ•˜์—ฌ ์ˆœํ™˜์  ์ƒํƒœ๊ณ„๊ฐ€ ๊ตฌ์ถ•๋˜๋ฉด์„œ ์ ์ง„์ ์œผ๋กœ ์‚ฌ์šฉ์ž ๊ฒฝํ—˜์ด ํ™•์žฅ๋˜๋Š” ์žฅ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š”, ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค์˜ ๋ฐœ์ „๋‹จ๊ณ„๋ฅผ ๊ณ ๋ คํ•œ ํ˜์‹  ์ฑ„ํƒ๊ณผ์ •๊ณผ ๊ฐ ๋‹จ๊ณ„ ๋ณ„ ์ธ์ง€์š”์ธ์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ์ •๋ฆฌํ•œ ์ด๋ก ์  ์—ฐ๊ตฌ๋ชจ๋ธ์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ, ์‹ค์ œ ์‚ฌ๋ก€์— ๋Œ€ํ•œ UX๋ถ„์„์˜ ์‹œ์‚ฌ์ ์„ ํ† ๋Œ€๋กœ ๋งค์ฒด ์ „ํ™˜์— ๋”ฐ๋ฅธ ๊ตฌ์ฒด์ ์ธ ๊ฐ€์ด๋“œ๋ผ์ธ์„ ๊ฐœ๋ฐœํ•˜์—ฌ ์ œ์•ˆํ•˜์˜€๋‹ค๋Š”๋ฐ ์˜์˜๊ฐ€ ์žˆ๋‹ค. ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฌผ์ธ ํ˜์‹  ์ฑ„ํƒ๊ณผ์ • ๋ณ„ UX๋””์ž์ธ ๊ฐ€์ด๋“œ๋ผ์ธ์€ ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค์˜ ์ฃผ์š” ๋Œ€์ƒ์ด ์‹ค๋ฌผ ๋งค์ฒด์— ๊ธฐ๋ฐ˜ํ•˜๊ณ  ์žˆ์–ด ์‚ฌ์šฉ์ž์˜ ์„ ํ–‰๊ฒฝํ—˜์„ ๊ฐ€์ƒ๊ฒฝํ—˜์œผ๋กœ ์ „ํ™˜ํ•ด์•ผ ํ•˜๋Š” UX/์„œ๋น„์Šค๋ฅผ ๊ธฐํšํ•˜๋Š” ๋””์ž์ด๋„ˆ ๋˜๋Š” ๊ธฐํš์ž์—๊ฒŒ ์•„๋ž˜์™€ ๊ฐ™์ด ํ™œ์šฉ๋  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค. (1) ๋ชจ๋ฐ”์ผ ์„œ๋น„์Šค์˜ ์‹œ์žฅ ์ •์ฐฉ ์‹œ๊นŒ์ง€ ์žฅ๊ธฐ์  ๊ด€์ ์˜ ์šด์˜ ๊ณ„ํš์„ ์ˆ˜๋ฆฝํ•˜๊ฑฐ๋‚˜, (2) ํ˜์‹  ์ฑ„ํƒ๊ณผ์ • ๋ณ„๋กœ ์ค‘์š”ํ•˜๊ฒŒ ๊ณ ๋ คํ•ด์•ผ ํ•  ์š”์ธ์„ ํŒŒ์•…ํ•˜์—ฌ ์„œ๋น„์Šค ๋ฐฉํ–ฅ์„ฑ์„ ๊ฒ€ํ†  ๋ฐ ์กฐ์ •ํ•˜๊ฑฐ๋‚˜, (3) ์œ ๊ด€ ๋ถ€์„œ์™€ ๊ณตํ†ต์  ๊ด€์ ์„ ๊ฒฌ์ง€ํ•˜๊ธฐ ์œ„ํ•œ ๊ธฐ๋ฐ˜ ์ž๋ฃŒ๋กœ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.1.์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ 1 1.2 ์—ฐ๊ตฌ๋ชฉ์  13 1.3 ์—ฐ๊ตฌ๋Œ€์ƒ 14 1.4 ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 17 1.5 ์šฉ์–ด์ •์˜ 18 2.์ด๋ก ์  ๊ณ ์ฐฐ 23 2.1 ์ธ์ง€๊ณผ์ • 23 2.1.1 ํ˜์‹ ์ฑ„ํƒ 23 2.1.1 ํ˜์‹ ์ €ํ•ญ 33 2.1.2 UX ๊ณผ์ • 41 2.2 ์ธ์ง€์š”์ธ 52 2.2.1 ์ธ์ง€๊ณผ์ • ๋ณ„ ์ธ์ง€์š”์ธ 53 2.2.2 ์ธ์ง€์š”์ธ ๊ฐ„ ์ƒํ˜ธ์ž‘์šฉ 68 2.2.3 ๋ถ€์ •์ ใ†๊ธ์ •์  ์ธ์ง€์š”์ธ 72 3.์—ฐ๊ตฌ๋ชจ๋ธ ์ •์˜ 76 3.1 ์ง€์†์  ์˜ํ–ฅ 76 3.1.1 ๋ถˆํ™•์‹ค์„ฑ(Uncertainty) 77 3.1.2 ๋ถˆํŽธ๊ฐ (Discomfort) 78 3.1.3 ๊ธฐ๋Šฅ์  ๊ฐ€์น˜ (Functional Value) 78 3.1.4 ๋ธŒ๋žœ๋“œ ์‹ ๋ขฐ๋„ (Brand Credibility) 81 3.1.5 ์ œ์–ด ์šฉ์ด์„ฑ (Ease of Control) 86 3.1.6 ์ž๊ธฐ ํšจ๋Šฅ๊ฐ (Self-efficacy) 87 3.2 ๊ธฐ๋Œ€๋‹จ๊ณ„ (Anticipation) 91 3.2.1 ๋‘๋ ค์›€ (Fear) 91 3.2.2 ๋…ธ๋ ฅ ๊ธฐ๋Œ€ (Effort Expectancy) 92 3.2.3 ์‚ฌํšŒ์  ๊ฐ€์น˜ (Social Value) 93 3.2.4 ๊ด€์ฐฐ ๊ฐ€๋Šฅ์„ฑ (Observability) 96 3.2.5 ์ž๋ฐœ์  ์œ ํฌ์„ฑ (Voluntary Enjoyment) 99 3.3 ๋„์ž…๋‹จ๊ณ„ (Orientation) 100 3.3.1 ์ขŒ์ ˆ๊ฐ (Frustration) 101 3.3.2 ๋ณต์žก์„ฑ (Complexity) 103 3.3.3 ์พŒ๋ฝ์  ์œ ํฌ์„ฑ (Hedonic Enjoyment) 104 3.3.4 ์นœ์ˆ™ํ•จ (Familiarity) 106 3.3.5 ํ•™์Šต ์šฉ์ด์„ฑ (Ease of Learn) 112 3.4 ์ ์šฉ๋‹จ๊ณ„ (Incorporation) 114 3.4.1 ํ”ผ๋กœ๊ฐ (Fatigue) 114 3.4.2 ์‚ฌ์šฉ์šฉ์ด์„ฑ (Ease of Use) 115 3.4.3 ์‹ค์šฉ์  ๊ฐ€์น˜ (Pragmatic Value) 119 3.5 ํ™•์žฅ๋‹จ๊ณ„ (Extension) 121 3.5.1 ๋ถˆ๋งŒ (Discontent) 121 3.5.2 ์กฐ์ • ์šฉ์ด์„ฑ (Ease of Modify) 122 3.5.3 ํ‘œํ˜„์  ์œ ํฌ์„ฑ (Expressive Enjoyment) 123 3.5.4 ์ •์„œ์  ๊ฐ€์น˜ (Emotional Value) 125 3.6 ์—ฐ๊ตฌ๋ชจ๋ธ 126 4. ํ™•์žฅ๋‹จ๊ณ„์— ์ง„์ž…ํ•œ S์‚ฌ ์„œ๋น„์Šค์˜ UX๋ถ„์„ 128 4.1 ๊ฐœ๋… ๋ฐ ์กฐ๊ฑด 130 4.1.1 ์„œ๋น„์Šค๋ช… ๋ฐ ์•„์ด์ฝ˜ 131 4.1.2 ๋ธŒ๋žœ๋“œ ์š”์†Œ 136 4.2 ๊ธฐ๋Œ€๋‹จ๊ณ„ 137 4.2.1 ํ™๋ณด์ž๋ฃŒ ๋ฐ ๋ฉ”์‹œ์ง€ 138 4.2.2 ์•ฑ์Šคํ† ์–ด ํŽ˜์ด์ง€ 143 4.3 ๋„์ž…๋‹จ๊ณ„ 147 4.3.1 ์„œ๋น„์Šค ์•ˆ๋‚ด 147 4.3.2 ํ™ˆ ํ™”๋ฉด 151 4.3.3 ์ƒ์„ธํ™”๋ฉด 153 4.3.4 ๊ธฐ๋ŠฅํŠนํ™”ํ™”๋ฉด 155 4.3.5 ๋“ฑ๋ก ์ ˆ์ฐจ 169 4.3.6 ๊ด€๋ฆฌ 174 4.4 ์ ์šฉ๋‹จ๊ณ„ 177 4.4.1 ํ™ˆ ํ™”๋ฉด 178 4.4.2 ์ƒ์„ธํ™”๋ฉด 180 4.4.3 ๊ธฐ๋ŠฅํŠนํ™”ํ™”๋ฉด 181 4.4.4 ๋“ฑ๋ก์ ˆ์ฐจ 184 4.4.5 ๊ด€๋ฆฌ 185 4.5 ํ™•์žฅ๋‹จ๊ณ„ 186 4.5.1 ์„œ๋น„์Šค๋ช… ๋ฐ ์•„์ด์ฝ˜ 188 4.5.2 ํ™๋ณด์ž๋ฃŒ ๋ฐ ๋ฉ”์‹œ์ง€ 188 4.5.3 ํ™ˆ ํ™”๋ฉด 190 4.5.4 ์ƒ์„ธํ™”๋ฉด 192 4.5.5 ๊ธฐ๋ŠฅํŠนํ™”ํ™”๋ฉด 196 4.5.6 ๊ด€๋ฆฌ 198 5.๋„์ž…๋‹จ๊ณ„์— ๋จธ๋ฌธ K์‚ฌ์˜ ์„œ๋น„์Šค UX๋ถ„์„ 200 5.1 ๊ธฐ๋Œ€ 201 5.1.1 ์„œ๋น„์Šค๋ช… ๋ฐ ์•„์ด์ฝ˜ 201 5.1.2 ํ™๋ณด์ž๋ฃŒ ๋ฐ ๋ฉ”์‹œ์ง€ 204 5.1.3 ์•ฑ์Šคํ† ์–ด ํŽ˜์ด์ง€ 209 5.2 ๋„์ž… 210 5.2.1 ์ง„์ž…ํ™”๋ฉด 210 5.2.2 ํ™ˆํ™”๋ฉด 211 5.2.3 ์ƒ์„ธํ™”๋ฉด 214 5.2.4 ๊ธฐ๋ŠฅํŠนํ™”๋ชจ๋“œ 215 5.2.5 ๋“ฑ๋ก์ ˆ์ฐจ 218 6.์‚ฌ์šฉ์ž ๋ฐ˜์‘ UX๋ถ„์„ 220 6.1 ์ž๋ฃŒ์ˆ˜์ง‘ ๋ฐ ํ‘œ๋ณธ์˜ ํŠน์„ฑ 220 6.2 ๋ถ„์„๋ฐฉ๋ฒ• 222 6.3 ๋ถ„์„๊ฒฐ๊ณผ 223 6.3.1 ๊ธฐ๋Œ€๋‹จ๊ณ„ 223 6.3.2 ๋„์ž…๋‹จ๊ณ„ 224 6.3.3 ์ ์šฉ๋‹จ๊ณ„ 228 6.3.4 ํ™•์žฅ๋‹จ๊ณ„ 232 7.ํ˜์‹  ์ฑ„ํƒ๊ณผ์ • ๋ณ„ UX๋””์ž์ธ ๊ฐ€์ด๋“œ๋ผ์ธ 235 8.๊ฒฐ๋ก  ๋ฐ ์ œ์–ธ 257 ์ฐธ๊ณ  ๋ฌธํ—Œ 261 ๋ถ€ ๋ก 282 ๋ถ€๋ก ๏ผ‘ ๊ฐ€์ด๋“œ๋ผ์ธ ํ‰๊ฐ€ ์ž๋ฃŒ 282 ๋ถ€๋ก ๏ผ’ ์ธํ„ฐ๋ทฐ KT ์ „๋žต๊ธฐํš 293 ๋ถ€๋ก ๏ผ“ ์ธํ„ฐ๋ทฐ KT ๋งˆ์ผ€ํŒ… 307 ๋ถ€๋ก ๏ผ” ์ธํ„ฐ๋ทฐ KT ๊ธฐํš 318 ๋ถ€๋ก ๏ผ• ์ธํ„ฐ๋ทฐ CONAD UX 324 ๋ถ€๋ก ๏ผ– ์ธํ„ฐ๋ทฐ PXD UX 331 ๋ถ€๋ก ๏ผ— ์ธํ„ฐ๋ทฐ PXD UX 333 Abstract 338Docto
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