Personal and social predictors of use and non-use of fitness/diet app: Application of Random Forest algorithm

This study investigated the various groups of factors that predict individuals’ use and non-use of fitness and diet apps on smartphones. Unlike previous research on fitness and diet apps which have mainly studied individuals’ intentions to use the apps, this study focused on the prediction accuracy of various factors that lead people to use fitness and diet apps through analysis of data collected from users as well as non-users of these apps. To examine prediction accuracy, this study applied the Random Forest algorithm. According to the findings, prediction accuracy higher than that of 70 percent was observed for nine factors: age, annual income, education, perceived obesity, dieting efforts, number of smartphone apps currently used, daily time spent with smartphone apps, perceived benefits from exercise, and social influence. A major contribution of this study is its detection of those factors predicting actual behavioral decisions regarding use of fitness and diet apps, as opposed to future intentions..     

An Identification of Factors Motivating Individuals’ Use of Cloud-Based Services

The purpose of this study is to develop a better understanding of the factors motivating individuals who use cloud-based services despite the privacy and security risks associated with it. The authors developed a research model that incorporates the theory of planned behavior (TPB) and constructs from previous research to explain individuals’ intentions to use cloud-based services. Our analysis shows support for the relationships among predictor variables (attitude, subjective norm, perceived behavioral control, and information privacy) and the outcome variable (behavioral intention). Additionally, our analysis shows IT leadership and trust as moderating variables between the TPB predictor variables (attitude and perceived behavioral control), but not subjective norm. The results indicate that IT leadership support of cloud-based systems can have a positive effect on cloud adoption and individuals are likely to continue their use of cloud computing despite the privacy and security risks associated with it.     

Exploring Factors Affecting the Adoption of Internet of Things Services

The Internet of things (IoT) is seen as a potentially effective means of integrating multiple technologies to improve the quality of life. However, little attention has been paid to factors that may have a significant effect on a user’s intention to use the IoT services. This study applies the value-based adoption model to examine the influences of benefits (i.e. perceived usefulness and perceived enjoyment) and sacrifices (i.e. perceived privacy risk and perceived costs) on the user’s perceived value of and intention to use the IoT services. A structural equation modeling approach is applied to a survey of 489 IoT users, with results indicating that perceived usefulness and perceived enjoyment significantly affect behavioral intention through perceived value. Moreover, perceived privacy risk also plays a key factor in determining IoT adoption. The implications of this study are discussed.     

The effects of IT-related attributional style in voluntary technology training

IT training is firmly established as a key condition that influences successful technology adoption, yet little is known about factors that can affect voluntary training participation. We evaluate the predictive value of IT-related attributional style in relation to the intention to participate in voluntary training in the context of a mandatory enterprise resource planning system rollout. We find that individual IT-related attributional style is highly predictive of the intention to participate.     

Information technology adoption for sustainable development: green e-books as an example*

ABSTRACT

In recent years, due to increasing awareness of the need for environmental protection, there have been significant efforts to improve consumers’ acceptance of green information technology(IT) products for sustainable development. This study first investigated how knowledge about a green IT product (e-books) influences consumers’ planning processes by using the technology acceptance model and the theory of planned behavior. Data from 320 respondents were analyzed using structural equation modeling to examine the hypothesized relationships in the research model. Results show that perceived usefulness, attitudes, subjective norms, and perceived behavioral control have a significant and positive impact on the intention to purchase e-books. Results also show the moderating effect of consumers’ knowledge about the environmental friendliness of e-books on their intention to buy e-books. Finally, important implications of the findings are discussed, and directions for future research are also provided in this paper.     

Forecasting social CRM adoption in SMEs: A combined SEM-neural network method

The growth of social media usage questions the old-style idea of customer relationship management (CRM). Social CRM strategy is a novel version of CRM empowered by social media technology that offers a new way of managing relationships with customers effectively. This study aims to forecast the predictors of social CRM strategy adoption by small and medium enterprises (SMEs). The proposed model used in this study derived its theoretical support from IT/IS, marketing, and CRM literature. In the proposed Technology-Organization-Environment-Process (TOEP) adoption model, several hypotheses are developed which examine the role of Technological factors, such as Cost of Adoption, Relative Advantages, Complexity, and Compatibility; Organizational factors, such as IT/IS knowledge of employee, and Top management support; Environmental factors such as Competitive Pressure, and Customer Pressure; and Process factors such as Information Capture, Information Use, and Information Sharing; all having a positive relationship with social CRM adoption. This research applied a following two staged SEM-neural network method combining both structural equation modelling (SEM) and neural network analyses. The proposed hypothetical model is examined by using SEM on the collected data of SMEs in Kuala Lumpur, the central city of Malaysia. The SEM approach with a neural network method can be used to investigate the complicated relations involved in the adoption of social CRM. The study finds that compatibility, information capture, IT/IS knowledge of employee, top management support, information sharing, competitive pressure, cost, relative advantage, and customer pressure are the most important factors influencing social CRM adoption. Remarkably, the results of neural network analysis show that compatibility and information capture of social CRM are the most significant factors which affect SMEs' adoption of this form of customer relationship management. The outcomes of this research benefit executives' decision-making by identifying and ranking factors that enable them to discover how they can advance the usage of social CRM in their firms. Furthermore, the findings of this study can help the managers/owners of SMEs assign their resources, according to the ranking of social CRM adoption factors, when they are making plans to adopt social CRM. This study differs from previous studies as it proposes an innovative new approach to determine what influences the adoption of social CRM. By proposing the TOEP adoption model, additional information process factors advance the traditional TOE adoption model.     

Factors affecting the adoption of fertilizers by rice farmers in Côte d'Ivoire

This paper analyzed the factors that affect the adoption of chemical fertilizers by rice farmers in Côte d'Ivoire using a Tobit model. The results show that the major factors that positively influence farmers' use of fertilizers in rice fields are cultivation of lowlands, use of mechanization, farm size, land pressure and availability of non-farm income. Factors found to negatively affect the use of fertilizer in rice fields are the distance of the field to the village, distance of the village to the major market, and if the cultivator is a female. The paper concludes with strategies for targeting soil fertility interventions on farmers' rice fields.     

离散制造企业RFID实施框架研究*

为推进离散制造企业RFID系统的成功实施,提出了面向离散制造企业的RFID实施方法论框架。从应用领域、应用层次、产品生命周期三个维度分析了离散制造企业的RFID应用需求。以信息技术采纳理论为基础,构建了包括RFID技术采纳决策和RFID系统实施两个阶段的RFID实施过程框架,并对各阶段的实施步骤和实施方法进行了阐述。利用上述RFID实施框架在重庆某整车生产厂进行实际应用,验证了可行性。     

Mapping ICT use at home and telecommuting practices: A perspective from work/family border theory

This study draws on the work/family border theory to investigate the role of information communication technology (ICT) use at home in shaping the characteristics of work/family borders (i.e. flexibility and permeability) and consequently influencing individuals’ perceived work-family conflict, technostress, and level of telecommuting. Data were collected from a probability sample of 509 information workers in Hong Kong who were not self-employed. The results showed that the more that people used ICT to do their work at home, the greater they perceived their work/family borders flexible and permeable. Interestingly, low flexibility and high permeability, rather than the use of ICT at home, had much stronger influences on increasing, in particular, family-to-work conflict. As expected, work-to-family conflict was significantly and positively associated with technostress. Results also showed that the telecommuters tended to be older, had lower family incomes, used ICT frequently at home, and had a permeable boundary that allowed work to penetrate their home domain. The theoretical and practical implications are discussed.     

BIM adoption by public facility agencies: impacts on occupant value

ABSTRACT

Many governments have begun to demand that large public facility agencies adopt and implement building information modelling (BIM) in their business processes. Some have published BIM guides. Most of these are technical specifications that are useful at the project level, but they provide no support for the organization-level adoption effort. On the basis of a literature review, action research and case studies of five large UK government facility agencies, a BIM adoption impact map (BIM AIM) is proposed. It describes a set of possible relationships between the actions taken by public facility agencies, the intermediate outcomes of their actions and the eventual achievement of value for the occupants of the facilities they build. BIM AIM can be used by public facility agencies with a wide variety of construction project types to analyse and visualize the strengths, weaknesses and opportunities in their BIM adoption efforts, potentially enabling them to focus on social impacts and outcomes rather than on the technological or management actions that intermediate stakeholders promote.