Farmer’s age, technology adoption, and income: a case of the elderly-friendly technology in South Korea

( Jin Hwa Jung ),( Sae Bom Kim ) 한국농업경제학회 2017 農業經濟硏究 Vol.58 No.3

This paper analyzes the effect of farmers’ age on the adoption of new agricultural technology and farm household income for the case of elderly-friendly new technology. Considering the endoge-neity of technology adoption, a two-stage estimation method was applied. Empirical analysis was conducted using the survey data of 265 strawberry farmers in South Korea. The empirical results confirm the significant income effect of technology adoption of farmers, but no income effect of farmers’ age once controlled for technology adoption. Farmers’ age also does not reduce the proba-bility of adopting new technology when controlled for the differences in technology acceptability, whereas farmers’ technology acceptability significantly raises the probability of technology adoption. Put differently, it is not farmers’ age but their technology acceptability level that determines the adoption of new technology and subsequently farm household income, at least in the case of eld-erly-friendly technology. It thus suggests that, facing the rapidly aging rural sectors, measures need to be taken to promote the development of elderly-friendly technology and enhance farmers’ technol-ogy acceptability level so that they are apt enough to adopt newly developed technology. Further research is called for to investigate whether this age-technology acceptability-technology adoption nexus holds for non-elderly-friendly technology.

Farmer’s age, technology adoption, and income: a case of the elderly-friendly technology in South Korea

정진화,김새봄 한국농업경제학회 2017 農業經濟硏究 Vol.58 No.3

This paper analyzes the effect of farmers’ age on the adoption of new agricultural technology and farm household income for the case of elderly-friendly new technology. Considering the endoge-neity of technology adoption, a two-stage estimation method was applied. Empirical analysis was conducted using the survey data of 265 strawberry farmers in South Korea. The empirical results confirm the significant income effect of technology adoption of farmers, but no income effect of farmers’ age once controlled for technology adoption. Farmers’ age also does not reduce the proba-bility of adopting new technology when controlled for the differences in technology acceptability, whereas farmers’ technology acceptability significantly raises the probability of technology adoption. Put differently, it is not farmers’ age but their technology acceptability level that determines the adoption of new technology and subsequently farm household income, at least in the case of eld-erly-friendly technology. It thus suggests that, facing the rapidly aging rural sectors, measures need to be taken to promote the development of elderly-friendly technology and enhance farmers’ technol-ogy acceptability level so that they are apt enough to adopt newly developed technology. Further research is called for to investigate whether this age-technology acceptability-technology adoption nexus holds for non-elderly-friendly technology.

EXPLORING MILLENNIAL CONSUMERS’ PERCEPTIONS, ATTITUDES AND PURCHASE INTENTIONS TOWARDS LUXURY FASHION WEARABLE TECHNOLOGY (SMARTWATCHES)

Marta Blazquez Cano,Bethan Alexander,Karie Fung 글로벌지식마케팅경영학회 2018 Global Marketing Conference Vol.2018 No.07

Introduction Smartwatches are mini devices that are worn like standard watches, which allow installation and use of mobile apps enabling connectivity and interactivity (Chuah et al., 2016). Park et al. (2016) regard smartwatches as multi-category products and are considered to be the first commercialized wearable technology for consumers (Jung et al., 2016). Wearable technologies refer to high-tech devices that are integrated into clothing, accessories or the human body to provide personalized functions to users, regardless of the types of usage (Choi and Kim, 2016). Thus, the smartwatch is recognised as an important and pioneering sub-category of broader smart-fashion. Wearable technology has become more readily available and widespread in the market. A recent industry report (IDC, 2017) indicates that worldwide shipments of wearable devices are expected to increase by 132% from 102.4 million units to 237.5 million units between 2016 and 2021, driven by the proliferation of new and various types of smartwatches. In the past, high-tech and fashion were considered as two separate industries. However, recent years have witnessed a trend towards fashion and high-tech collaborations (Zimmermann, 2016). For example, “Herm?s Apple watch” and “Louis Vuitton Tambour Horizon” (O‟Connor, 2017). Millennial consumers are often perceived as the first high-tech generation. This young generation is increasingly attracted by the innovativeness of smartwatches (Shotter and Bradshaw, 2014). According to PwC (2016), millennials are more likely to use smartwatches than older generations. Gartner‟s (2017) research also highlights that millennials represent the largest user group of wearable technologies. Considering the increasing magnitude of millennials‟ interest in luxury wearables, this study takes factors affecting millennial consumers‟ new technology acceptance, and luxury consumption into account. Despite increasing attention from industry, scholarly research on wearable technology has been limited to technological uses. Extant studies are focused in the fields of information systems, computers in human behaviour (Chuah et al., 2016) or electronic textiles (Berzowska, 2005). They concentrate on how these devices might be utilized for healthcare and safety monitoring, fitness or biometric purposes (Choi & Kim, 2016). Academic research to date therefore tends to be more technology rather than consumer driven (Choi and Kim, 2016). As discussed, although the fashion and technology industries are converging (Zimmermann, 2016), most existing research into smartwatch adoption (Choi & Kim, 2016; Chuah et al., 2016; Kim & Shin, 2016) utilizes standard or fitness-centric smartwatches as the research objects. Researchers generally fail to see smartwatches as a hybrid of high-tech wearable and luxury products. The Technology Acceptance Model (TAM) (Davis, 1986) is a frequently cited model in predicting consumers‟ intentions to adopt an emerging technology. It depicts that perceived usefulness and perceived ease of use are two critical variables influencing users‟ beliefs, attitudes and intentions to embrace a new information system (Legris et al., 2003). An extension of TAM, TAM 2 (Venkatesh and Davis, 2000) denotes the influence of subjective norm on behavioural intentions. In this model, technology adoption is regarded as a process of social influence. TAM has been extensively applied to explain consumer acceptance of e-commerce (Pavlou, 2003), mobile payment (Schierz et al., 2010), smart glasses (Raushnabel and Ro, 2016), mobile learning systems (Park et al., 2012) and standard smartwatches launched by IT brands (Kim and Shin, 2015; Choi an Kim, 2016). Yet, despite considerable research on the application of TAM, studies incorporating TAM 2 to explain consumers‟ perceptions, attitudes and intentions towards using luxury fashion wearables is still scarce. While Choi and Kim (2016) provide a first step towards understanding consumers‟ perceptions of smartwatches, the authors consider only the functional (perceived usefulness and ease of use) and personal (need for uniqueness and vanity) variables. The influences of other factors like emotional and social factors are neglected. Within the context of consumer behaviour, watches are consumed primarily for aesthetic appeal, as well as providing a means for constructing one‟s self-identity. Thus, psychological and social motivations may also be considered as antecedents to luxury fashion smartwatch adoption. In addition, luxury fashion wearable technology products embrace both high-tech functionality and fashionable design. These smartwatches are marketed as luxurious accessories, rather than solely functional digital devices, as self-expressive use of them has become more commonplace (Mintel, 2016). Furthermore, millennial consumers generally consume luxury for social-oriented purposes (Eastman & Liu, 2012). Hence, values that drive millennial consumers‟ luxury consumption, along with factors proposed in TAM 2, are perceived to play a critical role in affecting the adoption of these smart accessories. The premise of this paper is based on Wiedmann et al.‟s (2007) model of luxury values, employing individual values (self-identity and perceived hedonism), social value (perceived conspicuousness) and functional values (perceived usefulness and perceived quality) to investigate the key factors affecting luxury fashion smartwatch adoption. The Theory of Reasoned Action (TRA) (Ajzen and Fishbein, 1975) provides a framework for understanding consciously intended consumer behaviour (Yousafzai et al., 2010). It posits that the impact of consumer attitudes and subjective norms on actual behaviour are mediated by behavioural intentions, which is considered the most powerful predictor of human behaviour (Ajzen and Fishbein, 2005). In TRA, the roles of personal and social factors in forming behavioural intentions are considered. This attitude-intention-behaviour association has been extensively validated in various contexts like ethical consumption (Paul et al., 2016), Green Information Technology (Mishra et al., 2014) and online banking (Yousafzai et al., 2010). Yet, nascent research exists on the attitude-intention link in luxury fashion smartwatch adoption. Purpose In order to address the research gaps elucidated, this study aims to examine the relationships between key value propositions of luxury fashion smartwatches, consumer attitudes and their purchase intentions, and to explore millennial consumers‟ overall perceptions of using these luxury wearable technologies. Specifically, this study critically reviews and links the theories of technology adoption and luxury consumer behaviour to investigate and explore consumer behaviour towards luxury fashion smartwatches in order to offer compelling academic and managerial implications. Design/Methodology/Approach A conceptual framework (see Figure 1) was developed grounded in luxury consumption, technology acceptance and consumer behaviour literature, from which 9 research hypotheses and 3 research questions ensued. The model posits that millennial consumers develop attitudes and purchase intentions towards luxury fashion smartwatches in 3 stages. In line with the tri-component attitude model (Fishbein and Ajzen, 1975), consumers learn about luxury fashion smartwatches at the first phase (cognition). The second phase (affective) involves the formation of consumers‟ attitudes towards using luxury fashion smartwatches. At the final phase (conation), consumers develop intentions to buy consistent with their overall evaluations. Drawing on the TRA, relationship between consumer attitudes and purchase behaviour in terms of learning, feeling and doing (Solomon et al., 2010) is depicted. To offer a detailed understanding, mixed methods were employed (Creswell, 2014). An online self-administrated questionnaire was conducted and 230 valid samples were collected. The sample profile were millennial consumers, born between 1980 and 2000 (Young and Hinesly, 2012), who have seen or tried any luxury fashion smartwatch. This study recognizes millennial consumers as the research subject because this generation is described as the next prominent consumers of global luxury and are the largest user group of wearable devices (Higgins et al., 2016; Gartners, 2017). The proposed hypotheses were tested using SPSS 23.0 and subject to 5- statistical tests: reliability, descriptive statistics, factor analysis, correlation analysis and multiple linear regression. In addition, two face-to-face semi-structured focus-group discussions with 10 participants were conducted aiming to better understand the millennial consumer perceptions of using luxury fashion smartwatches. Quantitative content analysis and thematic analysis were employed to produce a more organized and comprehensive summary of the qualitative data. << Insert Figure 1 about here >> Findings The findings indicate that functional, individual and social factors influence millennial consumers‟ adoption intention of luxury fashion smartwatches. Empirical results reveal that perceived hedonism and usefulness are the most important factors that motivate adoption intentions, followed by subjective norm and perceived conspicuousness, indicating luxury fashion smartwatches are perceived as both an IT device and luxury fashion accessory. Other factors that might affect adoption are also discussed. A positive association between attitudes towards using luxury fashion smartwatches and purchase intentions is identified. Implications This study addresses a scholarly research gap by examining factors affecting attitudes and intentions towards using luxury fashion smartwatches, from millennial consumers‟ perspectives. It also offers strategic recommendations for luxury fashion brands in launching and growing luxury wearable opportunities specifically aimed at millennial consumers – a substantial and strategic segment for luxury brands. Research limitations and directions for future research are further elucidated. Originality and Value Given extant research on luxury fashion smartwatches is limited, this study contributes to this unique research stream by exploring millennial consumers‟ perceptions towards using these new generation smartwatches. To the authors‟ knowledge, this study is the first to investigate the application of TAM 2 in examining luxury fashion smartwatch adoption, and subjective norms has been proven as one of the most important factors.

THE INFLUENCE OF SOCIO-DEMOGRAPHICS AND TECNOLOGY READINESS ON MOBILE DEVICE USE IN B2B DIGITAL SERVICES

Heli Hallikainen,Ari Alamaki,Tommi Laukkanen 글로벌지식마케팅경영학회 2016 Global Marketing Conference Vol.2016 No.7

This research was conducted in order to examine the effects of user socio-demographics and recently introduced streamlined technology readiness index TRI 2.0 (Parasuraman & Colby, 2015) on mobile device use in B2B digital services. Mobile adoption has been studied from a consumer perspective, but to the best of the authors’ knowledge, very few studies explore mobile use in B2B markets. Mobile marketing is becoming a strategic effort in companies, as digital services not only in B2C but also in B2B sector are getting increasingly mobile (Leeflang, Verhoef, Dahlstr?m & Freundt 2014). This raises an interest to better understand the characteristics of those mobile enthusiasts who primarily use B2B services via a mobile device rather than via a personal computer. The study tests hypotheses with a large data set of 2,306 business customers of which around 10 percent represent these innovative mobile enthusiasts. Technology readiness is an individual’s propensity to embrace and use new technologies for accomplishing goals in home life and at work (Parasuraman & Colby, 2015; Parasuraman, 2000). Parasuraman and Colby (2015) recently introduced an updated version of the original Technology Readiness Index (TRI 1.0) scale called TRI 2.0 to better match with the recent changes in the technology environment. At the same time they streamlined the scale to a compact 16-item version so that it is easier for researchers to adopt it as a part of research questionnaires. Likewise the original scale, TRI 2.0 consists of four dimensions: optimism, innovativeness, discomfort, and insecurity. Optimism and innovativeness are motivators of technology adoption while discomfort and insecurity are inhibitors of technology readiness, and these motivator and inhibitor feelings can exist simultaneously (Parasuraman & Colby, 2015). Optimism is a general positive view of technology containing a belief that technology offers individuals with increased control, flexibility and efficiency in their lives. Innovativeness refers to a tendency to be a pioneer and thought leader in adopting new technologies. Discomfort reflects a perception of being overwhelmed by technology and lacking control over it. Moreover, insecurity reflects distrust and general skepticism towards technology, and includes concerns about the potential harmful consequences of it. As individuals differ in their propensity to adopt new technologies (Rogers, 1995), the authors propose that technology readiness influences mobile device use of B2B customers: H1: Optimism has a positive effect on mobile device use of B2B digital services. H2: Innovativeness has a positive effect on mobile device use of B2B digital services. H3: Insecurity has a negative effect on mobile device use of B2B digital services. H4: Discomfort has a negative effect on mobile device use of B2B digital services. The earlier literature argues that socio-demographic factors such as gender (Venkatesh & Morris, 2000; Chong, Chan & Ooi, 2012), age (Venkatesh, Thong & Xu, 2012; Chong et al., 2012; Kongaut & Bohlin 2016), education (Agarwal & Prasad, 1999; Chong et al., 2012; Puspitasari & Ishii 2016) and occupation (Okazaki, 2006) influence technology adoption behavior in general, and mobile adoption in particular. For example, men are nearly twice as likely as women to adopt mobile banking, and age is a negative determinant (Laukkanen, 2016). Higher educated use mobile devices more for utilitarian purposes, while lower educated use mobile devices more for entertainment (Chong et al., 2012). Moreover, research suggests that occupational factors influence mobile use (Okazaki, 2006). The authors hypothesize: H5: Males are more likely than females to use mobile device for B2B digital services. H6: Age has a negative effect on the use mobile device for B2B digital services. H7: Customers with higher education level have a higher likelihood for using mobile device for B2B digital services than customers with lower education level. H8: Occupation has an effect on the use mobile device for B2B digital services. The study tests hypotheses with a data collected among B2B customers of four large Finnish companies, all representing different industry fields. The large sample (n=2306) consists of procurement decision-makers all experienced with using B2B digital services. The sample shows that over 90 percent of the B2B customers are still using a computer (laptop or desktop computer) as their primary access device for digital services in their work. The sample divides between females and males in proportion to 46 and 54 percent respectively. University degree represents a majority with 42 percent, while only 2,7 percent of the respondents have a comprehensive or elementary school education. Over half of the sample represent top management or middle management with 24,6 and 28,4 percent respectively, while 9 percent are entrepreneurs, 21,2 percent represent experts, and 16,7 percent are officials or employess. Mean age of the respondents is 51,6 years, ranging from 18 to 81 years. The study uses logistic regression analysis with backward stepwise method in which the dependent variable is a dichotomous binary variable indicating the respondent’s primary access device for B2B digital services with 0=computer and 1=mobile device. As for the independent variables, the study measures individual’s technology propensity with recently introduced 16-item TRI 2.0 scale from Parasuraman and Colby (2015) using a five-point Likert scale ranging from Strongly disagree=1 to Strongly agree=5. The authors used confirmatory factor analysis to verify the theory-driven factor structure of the TRI 2.0 scale, i.e. optimism, innovativeness, discomfort, and insecurity. The analysis show that the measurement model for the TRI 2.0 scale provides an adequate fit and standardized regression estimates for all measure items exceed 0.60 (p<0.001) except for one item in discomfort (β=0.516) and one item in insecurity (β=0.480). After removing these two items the model shows an excellent fit with χ2=478.033 (df=71; p<0.001), CFI=0.965, RMSEA=0.050. Moreover, discriminant validity is supported, as the square root of the average variance extracted (AVE) value of each construct is greater than the correlations between the constructs (Fornell & Larcker, 1981). In addition, composite reliability values vary from 0.726 to 0.852 supporting convergent validity of the TRI 2.0 factors (Table 1). Thereafter, the factor scores of the latent factors showing sufficient internal consistency were imputed to create composite measures. These composite measures were used as independent variables in the logistic regression model. With regards to socio-demographic variables, age is measured as a continuous variable, while gender, education, and occupation are categorical independent variables in the model. The results of the logistic regression analysis show that innovativeness, insecurity, age, and occupation are statistically significant predictors of mobile device use in B2B services, supporting hypotheses H2, H3, H6, H8. The stepwise analysis procedure removed optimism (p=0.860), education (p=0.789), gender (p=0.339), and discomfort (p=0.159) from the model as they proved to be non-significant predictors of mobile device use. The results indicate that occupation is the strongest predictor for mobile device use in B2B digital services so that the top management has the greatest likelihood as the odds ratios of middle management, experts, and officials/employees are 0.610, 0.282, and 0.178 respectively. This means that, for example, the odds of the top management using mobile device as their primary channel for B2B digital services are 1.64 (1/0.610) times greater than the odds of the middle management, and 5.62 (1/0.178) times greater than the odds of the officials/employees. Interestingly the β-value for the entrepreneurs is positive indicating that their likelihood for mobile device use is even greater than the likelihood of the top management. However, the p-value (0.913) indicates that the difference is not statistically significant. With regards to age of the B2B customer, the results indicate a negative relationship with mobile device use. The odds ratio [Exp(β)=0.979] claims that the odds of a B2B customer to use mobile device as the primary channel for digital services decrease by 2 percent for each additional year of age. Regarding the TRI 2.0 constructs, the results show that innovativeness is a highly significant positive predictor for mobile device use, while perceived insecurity has a negative effect (Table 2). Literature suggests that B2B customers increasingly use mobile devices but yet little is known about those individuals most enthusiastic in using B2B digital services via a mobile device. Thus, the current study attempts to better understand those mobile enthusiasts who among the first have adopted mobile devices as their primary method to access B2B digital services. The results suggest that occupation is the most significant predictor of mobile use among B2B customers, implying that top managers are among the most likely to adopt and use mobile device for business services. Moreover, younger B2B customers use mobile devices more eagerly as the results suggest the likelihood for mobile device use degreases by 2 percent with every added year of age. The results further imply that out of the four TRI 2.0 dimensions innovativeness and insecurity influence in the mobile device use of B2B customers, innovativeness positively and insecurity negatively as the theory proposes. Innovativeness represents individual’s tendency to be a pioneer and thought leader in terms of technology adoption, while insecurity stems from the general skepticism and distrust of technology. These results imply that B2B customers who mainly access B2B digital services via a mobile device are open minded towards the possibilities new technologies can provide for them. Moreover, it appears that those B2B customers still accessing digital services primarily via a computer are more skeptical than mobile users towards technology in general. Compared to the use of mobile devices for individual purposes, business related use is more functional in nature, and thus, mobile devices and technologies must be convenient to use, offer real benefits for example in forms of mobility and portability, and be reliable in order for B2B customers to use them. Interestingly, our results do not support the effects of generally positive attitudes towards technology reflecting optimism, or discomfort of using technologies to influence mobile use among B2B customers. In addition, there are organizational factors (e.g. voluntariness of use) that the authors omit in the current study. These may limit the findings. Mobility will be a key driver in the ongoing digital revolution of marketing and sales. Understanding online behavior of mobile enthusiasts assists B2B marketing and sales leaders to plan and implement more effective mobile marketing strategies. Rogers (1995) has shown that the majority will follow the early adopters, and the adaptation cycle has even shortened during the last years (Downes & Nunes, 2014). Thus, mobile devices are evidently becoming the primary method in accessing B2B digital services.

An Extended UTAUT2 model to Explain the Adoption of Virtual Reality Technology in Health Centers: An Empirical Study Based in Riyadh

Algahtani, Manar,Altameem, Abdullah,Baig, Abdul Rauf International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.3

The adoption of new technology in any organization will represent change, and such change needs user acceptance for its successful implementation. Saudi Arabian health centers are no exception; therefore, the current study will investigate the adoption of new technology, namely that of virtual reality (VR), within health centers in Saudi Arabia and specifically in Riyadh City. This study explores the current state of VR technology adoption, factors that influence such adoption, and the extent of this technology's efficiency when it is used for vaccinating children. The data were collected from two samples: workers in vaccination clinics who responded to a survey and a group of children who participated in the VR technology experiment. The current study proposed a model based on the unified theory of acceptance and use of technology 2 (UTAUT2), with the addition of two variables: personal innovativeness and satisfaction. The results indicated that the respondents' perceptions regarding the health centers' infrastructure in terms of adopting VR were moderate. Among the factors affecting VR adoption, satisfaction, personal innovativeness, and behavioral intention were identified as vastly influential factors. From the eight hypotheses, six were found to be supported, with their factors significantly influencing behavioral intention with regard to VR technology adoption. Besides, the experiment concerning the use of VR technology on children verified the technique's high efficiency in terms of providing pain management and fear removal. These findings support the continuity of VR technology use, expand its future application fields, and integrate this study into the literature on technology acceptance models for VR adoption, as limited studies have covered this topic; consequently, this will benefit future research in this field.

User Experience and the Multi-Stage Adoption of Mobile Apps

Kim, Ambrose,Kim, Kyoung-jae Korea Data Strategy Society 2014 Journal of information technology applications & m Vol.21 No.2

The adoption of technology has always been of interest to academicians and practitioners of the field of Management Information System. This is so because without proper and adequate adoption, technology-no matter how beneficial or advanced it may be-will be of little value to users. Numerous researches, such as the researches of the Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), had been conducted to understand the human nature in association with the adoption or rejection of technologies that have bombarded the users. The coming of smart technologies (i.e., smart phones and devices), however, seems to have fundamentally changed the environment for adoption. The ubiquity combined with mobility of technology, especially when it comes to mobile apps, seem to make the old PC era of two-stage-pre and post-adoption models obsolete. A new model of adoption that identifies the determinants of technology acceptance and continuance is needed for the smart age. To this end, this paper undertakes an empirical study, by analyzing 229 users of Social Networking Service (SNS) mobile apps, to identify the role of user experience on the multi-stage adoption of technology, and provides results that User Experience (UX) plays the crucial role of bridging the separate stages of pre and post adoption of technologies. The paper concludes by providing practical implications of the new model as it relates to mobile apps and technologies, and recommendations for further studies to get a better understanding of technology adoption in the smart age.

Analysis of Multi-Farmers’ Technology Adoption Behavior

He Liang,Zhujie Chu,Yanzhao Lyu,Weiyi Yang 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.5

Due to farmers’ limited knowledge and judgment ability, obvious herding behavior during the process of technology innovation adoption is a common phenomenon. In this light of thinking, this paper constructs game model and spread model of technology innovation adoption of multi-farmers and then develops the empirical analysis. The empirical analysis shows that exchange earnings is an important factor to determine whether herding behavior happens in the process of multi-farmers’ technology innovation adoption, and the exchange range and cost also have an effect on the farmers’ decision-making behavior adoption.

Adoption and Diffusion Speed of New Technology with Network Externality in a Two-level Supply Chain

Daeheon Choi(최대헌) 한국경영과학회 2013 韓國經營科學會誌 Vol.38 No.3

This paper develops a model to predict the adoption and level of usage of network technology in a two-level supply chain with buyer-supplier relationships. A firm’s adoption of a new technology depends not only on its own beliefs of the new technology’s costs and benefits, but also on the adoption decisions of other firms in the supply chain. A model first analyzes an individual supplier’s decision about a new technology adoption considering with multiple suppliers and buyers. Individual suppliers’ decisions are aggregated with a population model to project how new technology diffuses across the supply chain and examine the pattern of diffusion process. This study found that as more firms adopt in initial periods, the total amount of information to the potential adopters in the population increases, and then the number of firms persuaded by the information increases as the process moves up the distribution of adoption process. We consider three factors influencing the diffusion speed of the new technology in a supply chain network : mean benefits, cost sharing, and information provision. This study examines how such factors affect the reduction of threshold levels, which implies that reductions in threshold levels have an aggregate effect by accelerating the rate of adoption. In particular, we explore relationship factors available in practice in a buyer-supplier relationship and numerically examines how these relationship factors contribute to increase the diffusion speed of the technology in a two-level supply chain

User Experience and the Multi-Stage Adoption of Mobile Apps

Ambrose Kim,Kyoung-jae Kim 한국데이타베이스학회 2014 Journal of information technology applications & m Vol.21 No.2

The adoption of technology has always been of interest to academicians and practitioners of the field of Management Information System. This is so because without proper and adequate adoption, technology-no matter how beneficial or advanced it may be-will be of little value to users. Numerous researches, such as the researches of the Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), had been conducted to understand the human nature in association with the adoption or rejection of technologies that have bombarded the users. The coming of smart technologies (i.e., smart phones and devices), however, seems to have fundamentally changed the environment for adoption. The ubiquity combined with mobility of technology, especially when it comes to mobile apps, seem to make the old PC era of two-stage-pre and post-adoption models obsolete. A new model of adoption that identifies the determinants of technology acceptance and continuance is needed for the smart age. To this end, this paper undertakes an empirical study, by analyzing 229 users of Social Networking Service (SNS) mobile apps, to identify the role of user experience on the multi-stage adoption of technology, and provides results that User Experience (UX) plays the crucial role of bridging the separate stages of pre and post adoption of technologies. The paper concludes by providing practical implications of the new model as it relates to mobile apps and technologies, and recommendations for further studies to get a better understanding of technology adoption in the smart age.

Technology and Competitiveness: Assessing The Influence of Transaction Costs in The Adoption of Technology and Recommended Farm Practices for Rice

Agham C. Cuevas 한국무역연구원 2012 The International Academy of Global Business and T Vol.8 No.2

Modern rice technology plays an important role in enhancing agricultural productivity and improving competitiveness that translates to higher household farm income. However, despite the benefits that these technologies and recommended farming practices bring, the adoption rate by farmers has been low. Adoption literature identifies a variety of factors ranging from farm characteristics and farm household attributes to varietal characteristics and technology attributes. One particular stream of adoption studies explores the role that transaction cost plays in technology adoption. The paper explored the influence of transaction costs on the adoption of technology and recommended farm practices by rice farmers. The study suggests that aside from farm and household characteristics, transaction costs affect farmers’ decisions to adopt recommended rice technologies and farm practices. Reduction of transaction costs makes adopting recommended practices more attractive as it assures the farmer that the eventual increases in yield will result to higher level of market participation and therefore higher value of net surplus.