The Effects of Internet Experience and Attitudes Toward Privacy and Security on Internet Purchasing

Using the Theory of Reasoned Action as the theoretical base, data collected through a semi-annual survey of web users was used to determine if beliefs about privacy and Internet security helped determine attitudes towards the Internet, which were thought to affect intent to make Internet purchases. Intent, in turn, was thought to affect actual purchasing behavior. Taking Internet experience into account, general support for the model was found, although security beliefs were stronger indicators of attitude than privacy beliefs

Critical review of the e-loyalty literature: a purchase-centred framework

Over the last few years, the concept of online loyalty has been examined extensively in the literature, and it remains a topic of constant inquiry for both academics and marketing managers. The tremendous development of the Internet for both marketing and e-commerce settings, in conjunction with the growing desire of consumers to purchase online, has promoted two main outcomes: (a) increasing numbers of Business-to-Customer companies running businesses online and (b) the development of a variety of different e-loyalty research models. However, current research lacks a systematic review of the literature that provides a general conceptual framework on e-loyalty, which would help managers to understand their customers better, to take advantage of industry-related factors, and to improve their service quality. The present study is an attempt to critically synthesize results from multiple empirical studies on e-loyalty. Our findings illustrate that 62 instruments for measuring e-loyalty are currently in use, influenced predominantly by Zeithaml et al. (J Marketing. 1996;60(2):31-46) and Oliver (1997; Satisfaction: a behavioral perspective on the consumer. New York: McGraw Hill). Additionally, we propose a new general conceptual framework, which leads to antecedents dividing e-loyalty on the basis of the action of purchase into pre-purchase, during-purchase and after-purchase factors. To conclude, a number of managerial implementations are suggested in order to help marketing managers increase their customers’ e-loyalty by making crucial changes in each purchase stage

Secure webs and buying intention: the moderating role of usability

El presente trabajo ha planteado un modelo conceptual a fin de mostrar como los antecedentes de la intención de compra se ven reforzados en contextos de Webs altamente usables. Específicamente, el trabajo analiza en profundidad el rol moderador de la usabilidad en la explicación de la conexión entre seguridad de una Web e intención de compra. Entre ambos extremos (seguridad e intención de compra), se han incluido diversas variables para explicar mejor su conexión. Para ello, ha sido diseñada una Web ficticia de ropa dirigida al segmento joven de clase media. A fin de alterar la usabilidad de la Web se han realizado dos tipos de manipulaciones: la velocidad y la facilidad de uso de la Web. Las dos Webs creadas (alta usabilidad y baja usabilidad) fueron visitadas por un total de 170 encuestados que fueron compensados con un USB valorado en 15 euros. Los resultados muestran que la seguridad percibida en la Web acarrea tres interesantes efectos (especialmente para la Web altamente usable): (i) mejora las actitudes agrado, (ii) reduce el nivel de riesgo percibido; (iii) aumenta la confianza. Los dos últimos efectos, a su vez, acaban aumentando la intención de compra.. Por último, se ha demostrado que la usabilidad, efectivamente, refuerza las relaciones consideradas en el modelo propuesto para explicar la intención de compra.A conceptual model has been proposed to show how buying intention antecedents are reinforced in highly usable contexts. Specifically, this paper deeply analyses the moderator role of system variables (usability) on explaining the relationship between Web security and buying intention. Between both extremes (security and buying intention), several relationships have also been stated to better explain this effect. An “ideal” fictitious Website was designed for a non existent clothing company directed at the segment of middle class consumers. In order to alter Web usability, two blocks of changes were made, one concerning Website speed and the other related to ease of use. Our experiment sample consisted of 170 respondents who participated in exchange for a pen-drive (USB) valued at 15 euros. The results show that improving website security has three interesting effects (especially in high usable contexts): (i) it improves pleasure attitudes, (ii) reduces the level of perceived risk and (iii) increases trust. Secondly, it has been found that to increase buying intention, two actions must be taken: (i) to diminish perceived risk and (ii) to improve users’ pleasure attitudes towards the Website. Finally, usability has been found to have a moderating role in all the relationships considered (reinforcing them)

Who Spends More Online? The Influence of Time, Usage Variety, and Privacy Concern on Online Spending

The paper tests the influence of adoption time, online time, usage variety, and privacy concern on online spending. Findings support the hypothesis that online time, adoption time, and usage variety, the three dimensions of Internet usage experience, have a positive and significant influence on the amount of money consumers spend online, and privacy concern has a negative and significant influence. The control variables included in the model are gender, age, education, and income. Gender, age, and education did not influence online spending. However, income has a significant effect on online spending. Theoretical and strategic implications and recommendations for future research are presented

A conceptual model of channel choice: measuring online and offline shopping value perceptions

This study tries to understand how consumers evaluate channels for their purchasing. Specifically, it develops a conceptual model that addresses consumer value perceptions of using the Internet versus the traditional (physical) channel. Previous research showed that perceptions of price, product quality, service quality and risk strongly influence perceived value and purchase intentions in the offline and online channel. Perceptions of online and offline buyers can be analyzed to see how value is constructed in both channels. This model enables comparisons between online and offline shoppers perceptions. As such, it is possible to determine the factors that encourage or prevent consumers to engage in online shopping.

The Importance of Transparency and Willingness to Share Personal Information

This study investigates the extent to which individuals are willing to share their sensitive personal information with companies. The study examines whether skepticism can influence willingness to share information. Additionally, it seeks to determine whether transparency can moderate the relationship between skepticism and willingness to share and whether 1) companies perceived motives, 2) individual’s prior privacy violations, 3) individuals’ propensity to take risks, and 4) individuals self-efficacy act as antecedents of skepticism. Partial Least Squares (PLS) regression is used to examine the relationships between all the factors. The findings indicate that skepticism does have a negative impact on willingness to share personal information and that transparency can reduce skepticis

User Perceptions of Smart Home IoT Privacy

Smart home Internet of Things (IoT) devices are rapidly increasing in popularity, with more households including Internet-connected devices that continuously monitor user activities. In this study, we conduct eleven semi-structured interviews with smart home owners, investigating their reasons for purchasing IoT devices, perceptions of smart home privacy risks, and actions taken to protect their privacy from those external to the home who create, manage, track, or regulate IoT devices and/or their data. We note several recurring themes. First, users' desires for convenience and connectedness dictate their privacy-related behaviors for dealing with external entities, such as device manufacturers, Internet Service Providers, governments, and advertisers. Second, user opinions about external entities collecting smart home data depend on perceived benefit from these entities. Third, users trust IoT device manufacturers to protect their privacy but do not verify that these protections are in place. Fourth, users are unaware of privacy risks from inference algorithms operating on data from non-audio/visual devices. These findings motivate several recommendations for device designers, researchers, and industry standards to better match device privacy features to the expectations and preferences of smart home owners.Comment: 20 pages, 1 tabl

An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection

The biological immune system (BIS) is characterized by networks of cells, tissues, and organs communicating and working in synchronization. It also has the ability to learn, recognize, and remember, thus providing the solid foundation for the development of Artificial Immune System (AIS). Since the emergence of AIS, it has proved itself as an area of computational intelligence. Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. These randomly generated detectors suffer from not been able to adequately cover the non-self space, which diminishes the detection performance of the V-Detectors algorithm. This research therefore proposed CSDE-V-Detectors which entail the use of the hybridization of Cuckoo Search (CS) and Differential Evolution (DE) in optimizing the random detectors of the V-Detectors. The DE is integrated with CS at the population initialization by distributing the population linearly. This linear distribution gives the population a unique, stable, and progressive distribution process. Thus, each individual detector is characteristically different from the other detectors. CSDE capabilities of global search, and use of L´evy flight facilitates the effectiveness of the detector set in the search space. In comparison with V-Detectors, cuckoo search, differential evolution, support vector machine, artificial neural network, na¨ıve bayes, and k-NN, experimental results demonstrates that CSDE-V-Detectors outperforms other algorithms with an average detection rate of 95:30% on all the datasets. This signifies that CSDE-V-Detectors can efficiently attain highest detection rates and lowest false alarm rates for anomaly detection. Thus, the optimization of the randomly detectors of V-Detectors algorithm with CSDE is proficient and suitable for anomaly detection tasks

Modelling and testing consumer trust dimensions in e-commerce

Prior research has found trust to play a significant role in shaping purchase intentions of a consumer. However there has been limited research where consumer trust dimensions have been empirically defined and tested. In this paper we empirically test a path model such that Internet vendors would have adequate solutions to increase trust. The path model presented in this paper measures the three main dimensions of trust, i.e. competence, integrity, and benevolence. And assesses the influence of overall trust of consumers. The paper also analyses how various sources of trust, i.e. consumer characteristics, firm characteristic, website infrastructure and interactions with consumers, influence dimensions of trust. The model is tested using 365 valid responses. Findings suggest that consumers with high overall trust demonstrate a higher intention to purchase online