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In this paper, the authors explore the reasons for reluctance to use mobile banking with the help of the technology acceptance model (TAM) and modifications proposed by the literature that is particularly adequate for developing countries and mobile banking: the theory of trying (TT) and the concept of attitude strengths.

This study intends to shed more light on the acceptance of mobile banking in Ethiopia from the banking industry's perspective. To this end, the authors identify models used in the literature for explaining acceptance and fit them to a sample of Ethiopian bank customers. The authors' sample of 394 mobile banking subscribers does not include non-banked individuals, because the authors' main intention is to help banks understanding why banks' platforms are not used as desired.

The authors' findings suggest that attitude is the most significant factor determining acceptance, a multi-dimensional approach to attitude is more recommendable to understanding how mobile banking users shape users' attitude and combining TAM and TT is impactful and better explains the factors influencing attitude.

The authors' analysis suggests focusing on improving the attitude of users toward mobile banking since users' attitude is the integral component for acceptance decisions. In doing so, banks shall concentrate on making mobile banking services/platforms easy to use than promoting the usefulness of mobile banking, because the perception of ease of use has a more significant influence on attitude than usefulness.

Practical application of the authors' findings may guide future marketing decisions while individuals can elucidate where individuals stand on mobile banking.

In the current dynamic business environment, Internet of Things (IoT) is employed by a number of companies in the logistics industry to achieve intelligent sorting, network optimization, real-time tracking and simplifying last-mile service. Although logistics entities are trying to introduce IoT into their business areas, users' perception of this new technology is still limited. This paper aims to develop a research model for the factors influencing the user adoption of IoT technology in the logistics industry.

In this study, based on the major theories on the application of new technologies such as technology acceptance model (TAM), technology–organization–environment (TOE) and innovation diffusion theory (IDT), a new research model was established to identify factors affecting customers' behavioral intention (BI) to adopt IoT technology provided by logistics companies. In addition, the authors surveyed unspecified customers of Cainiao Logistics Network, which is in charge of the logistics operation of Alibaba Group, China's largest e-commerce company, and tested the causality between the latent variables presented in the model using the structural equation model (SEM).

This empirical study shows that the support system of a logistics company and users' innovative propensity significantly affect perceived ease of use (PEOU) and BI for logistics services to which IoT technology is applied. It also presents that users' perceived security and enjoyment significantly affect perceived usefulness (PU) and BI. In addition, it was possible to confirm that the causal structure between variables suggested by TAM that PEOU has a significant effect on PU and BI, and PU has a substantial effect on BI.

Logistics companies should expand and upgrade technical support systems so that customers can flexibly accept logistics services with IoT technology and make efforts to alleviate customers' concerns about personal information leakage. In addition, it is necessary to find customers with an inclusive attitude toward using new technologies, to induce them to become leading users of logistics devices with IoT technology and to find various ways to amplify their enjoyment. Through a strategic approach to these technical and individual factors, it will be possible to boost customers' intention to use IoT logistics services.

As far as the authors know, this paper is the first study to set significant factors that affect users' BI to use IoT technology-applied logistics services provided by logistics companies and empirically analyze the causal relationships between proposed latent variables.

This study investigates the acceptance of mobile phone technology in Tanzanian small- and medium-sized enterprises (SMEs) using the Technology Acceptance Model (TAM) with a special focus on service quality.

The conceptual framework was designed by extending the TAM with an additional construct, service quality, before testing a model in a survey of 155 respondents and analysing using Smart PLS 4.

Service quality was found to be among the significant factors in the acceptance of mobile phone technology among SME employees.

This implies that the higher the quality of service offered, the more employees accept and use mobile phone technology in their duties and improve the productivity of SMEs.

The aspects of quality of mobile phone technology usage such as call dropouts, network quality, speed, etc., must be improved significantly.

The Mobile Network Operators and Regulators must understand that employees are offered the most accurate and reliable mobile phone services for its usefulness to be realised.

The originality is a modified version of a TAM that accommodates service quality that has been tested in the Tanzanian context.

This paper aims to investigate the factors influencing chief executive officers’ (CEOs') intentions to implement cloud technology in Italian small and medium-sized enterprises (SMEs).

The study proposes a model that integrates the theoretical construct of the technology acceptance model (TAM) with a classification of perceived benefits and risks related to cloud computing. The study employs a structural equation modeling approach to analyze data gathered through a Likert scale-based survey.

The findings indicate that risk perception has a strong negative effect on the intention to introduce cloud technology in firms. This effect is partially offset by the perceived ease of use of the technology.

The study provides a new theoretical framework that integrates the TAM and a classification of perceived risks to provide a clear view of management's cognitive processes during technological change. Moreover, the results show the main factors influencing decisions regarding the implementation of cloud computing in firms in light of the perception of risks. Finally, this study provides interesting findings for cloud service providers (CSPs) about their customers' decision-making processes.

This research involves empirical evidence from the Tanzanian context to find out whether participation, trust and transparency have a significant impact on the acceptance of e-government systems.

The research employs a survey of 153 respondents followed by structural equation modelling-variance based (CB-SEM) analysis using PLS 4. The conceptual framework was developed by extending the technology acceptance model (TAM) with additional constructs before testing it in quantitative research.

Results of the model show that the perceived ease of use (PEU) had neither a significant relationship with behaviour intention nor with perceived transparency, while all the other relationships were found to be significant.

Among others, this research provides theoretical underpinnings to the area of acceptance of technologies as well as providing areas for future research and policy implications.

The study presents the relationships involving transparency, trust and participation in e-government systems by the citizens and how they can potentially influence intention to use e-government systems.

The regulatory authorities, mobile service operators and government can use this research to enhance decision-making and governance towards effective use of mobile phone technology in accessing government services.

This research delivers a refined, extended model of TAM that comprises extra constructs, namely, trust, transparency and participation. This model provides the basis for upcoming research in the area of technology acceptance, e-government and in behavioural science.

In this study, three models were empirically compared, the DeLone and McLean model, the Seddon model and the Modified Seddon model, by measuring the impact of a business intelligence system (BIS) in companies in Peru. After that, the mediators and dependent constructs were analysed to determine if they were behaving properly (a good level of variance explanation and significant relations with others constructs). The study used a sample of 104 users of the BIS, from companies in several important economic sectors, in a quasi-voluntary context and with six constructs: information quality, system quality, service quality, system dependence (system use), user satisfaction and perceived usefulness (individual impact).

To interpret the results, the authors used structural equations. The idea was to look for the best fit and explanations for the outcomes. The main difference in these models is that the DeLone and McLean model considers system dependence (system use) as a part of information system success, but in the Seddon model, it is a consequence of it.

The Seddon model seems to show the best fit and explanation for the outcomes. After that, a review of the system use construct was realised, because of its limited variance explained and the few significant relations with other constructs, to improve its explanation power in future research.

It is estimated that the sample includes more than 15 per cent of all the companies that use a BISs in Peru, so the size of the sample is adequate, but it is not entirely random and therefore limits the generalizability of outcomes. Besides that, a sample size that is bigger could be better for the sake of making a more detailed analysis, permitting the use of some items with less power, or the use of another statistical procedure for structural equations such as the Asymptotical Distribution Free, permitting a more detailed analysis (Hair et al., 2006).

Business intelligence (BI), one of the most important components of information systems (IS), is playing a very relevant role in business in this time of high competition, high amounts of data and new technology. Currently, companies feel pressured to respond quickly to change and complicated conditions in the market, needing to make the correct tactical, operational and strategic decisions (Chugh and Grandhi, 2013). BI is one of the most important drivers of the decade (Gartner, 2013). Big companies of IS are creating special units specialised in BI, helping companies become more efficient and effective in daily operations.

Mobile location-based service (m-LBS) seems like a new class of personalized service due to location positioning technologies. This work aims to investigate consumer readiness (RED) toward m-LBS based on integrating pull effect- and push effect-related factors into the technology acceptance model (TAM).

An online survey collected data from 423 participants, and the research framework was analyzed using structural equation modeling (SEM).

The results divulge that consumer RED is determined by TAM antecedents, including usefulness (USE) and ease of use (EOU). EOU motivates USE in m-LBS. Regarding pull effect-related factors, absorptive capacity (ABC) is the strongest positive factor influencing consumer RED to use m-LBS, followed by technology willingness (TWI) and innovativeness (INN). Moreover, INN, trust (TRU) and perceived risk (RIS) significantly influence USE and EOU.

This work endeavors to explicate customer RED toward m-LBS by incorporating some meaningful pull effect-related dimensions (i.e. ABC, TWI and INN) and pushing effect-related dimensions (i.e. RIS) into crucial antecedents rooted in TAM. Thus, the findings assist practitioners in developing marketing strategies by boosting pull effects and controlling push effects on customer engagement in m-LBS.

Service robotics, a branch of robotics that entails the development of robots able to assist humans in their environment, is of growing interest in the hospitality industry. Designing effective autonomous service robots, however, requires an understanding of Human–Robot Interaction (HRI), a relatively young discipline dedicated to understanding, designing, and evaluating robotic systems for use by or with humans. HRI has not yet received sufficient attention in hospitality robotic design, much like Human–Computer Interaction (HCI) in property management system design in the 1980s. This article proposes a set of introductory HRI guidelines with implementation standards for autonomous hospitality service robots.

A set of key user-centered HRI guidelines for hospitality service robots were extracted from 52 research articles. These are organized into service performance categories to provide more context for their application in hospitality settings.

Based on an extensive literature review, this article presents some HRI guidelines that may drive higher levels of acceptance of service robots in customer-facing situations. Deriving meaningful HRI guidelines requires an understanding of how customers evaluate service interactions with humans in hospitality settings and to what degree those will differ with service robots.

Robots are challenging assumptions on how hospitality businesses operate. They are being increasingly deployed by hotels and restaurants to boost productivity and maintain service levels. Effective HRI guidelines incorporate user requirements and expectations in the design specifications. Compilation of such information for designers of hospitality service robots will offer a clearer roadmap for them to follow.

Mobile shopping is the current trend for firms to conduct business, having great advantages over electronic shopping as well as traditional shopping. The purpose of this paper is to discuss not only the driving forces of mobile shopping behaviors from the theory of reasoned action (TRA) perspective, but also the additional promotion and barrier sides of the mobile business.

A structural equation modeling approach with latent constructs is applied on a self-administered survey data of 208 Vietnamese consumers to test the hypotheses.

The results of this study have proved the predictive power of TRA in exploring consumer behavior in the context of mobile shopping. Also, both promotion and barrier variables have significantly strong impacts on the intention to adopt mobile shopping.

Future studies would benefit from investigating other variables (e.g. specific aspects of trust and risk) and using actual behavior (e.g. online purchases).

Business managers should pay attention to both promotion and barrier factors to understand how and why Vietnamese consumers adopt mobile shopping.

This pioneering study adapts the TRA model with extended promotion and barrier variables to explain mobile shopping in the context of Vietnam.

This paper aims to examine students’ perception, views and opinions about the usage of mobile phones in an educational setting in a higher education institution located in Jamaica. The results of these findings were used to gain insights and to assist education policymakers in adopting most suitable approaches to integrating mobile technology in learning.

A survey approach was used for this study. A total of 145 students participated in the study using structured questionnaire design containing 14 questions.

The results indicated an overall positive student perception toward cell phones usage as a learning tool and integrating cell phones into learning activities. Students were keen on its usage as a social connectivity and collaborative tool, which they can use for flexible and personalized learning activities.

Less research has been done in Caribbean and developing countries in analyzing student perception toward using cell phones for learning purposes. This research provides insights in developing policies to assist with the integration of mobile phone technology in learning and how institutions can respond to the advent of advancing mobile technology.