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The purpose of this study is to investigate the key predictors and outcomes of task–technology fit (TTF) of facial recognition payment systems with the moderating role of cultural differences in the restaurant industry.

The survey responses were collected from 336 South Korean and 336 US restaurant customers.

The results revealed that function significantly affected TTF in both groups. Unique to the Korean sample, emotion was found to be a significant determinant of TTF, whereas convenience and social influence were key predictors of TTF only for the US sample. TTF had significant and positive effects on the three dimensions of behavioral intentions in both groups. The result of multi-group analysis showed that cultural differences moderated the effect of convenience on TTF and the effect of emotion on TTF.

The authors provided recommendations for restaurant operators and technology companies seeking to improve customer TTF and acceptance of facial recognition payment systems for the first time.

本研究旨在调查面部识别支付系统任务技术匹配（TTF）的关键前置因素和影响, 以文化差异为调节变量, 研究其在餐饮行业的应用。

我们收集了来自336名韩国和336名美国餐厅顾客的调查回答。

结果显示, 在两组中, 功能显著影响TTF。对于韩国样本来说, 情感被发现是TTF的重要决定因素, 而对于美国样本来说, 方便性和社会影响是TTF的关键预测因素。在两组中, TTF对行为意向的三个维度均产生了显著且积极的影响。多组分析结果显示, 文化差异在方便性对TTF的影响以及情感对TTF的影响中起到了调节作用。

我们首次为寻求改善顾客TTF和接受面部识别支付系统的餐厅经营者和技术公司提供了建议。

In the aftermath of disasters, humanitarian actors need to coordinate their activities based on accurate information about the disaster site, its surrounding environment, the victims and survivors and the supply of and demand for relief supplies. In this study, the authors examine the characteristics of radio frequency identification (RFID) technology and those of disaster relief operations to achieve information visibility and actor coordination for effective and efficient humanitarian relief operations.

Building on the contingent resource-based view (CRBV), the authors present a model of task-technology fit (TTF) that explains how the use of RFID can improve visibility and coordination. Survey data were collected from humanitarian practitioners in India, and partial least squares (PLS) analysis was used to analyze the model.

The characteristics of both RFID technology and disaster relief operations significantly influence TTF, and TTF predicts RFID usage in disaster relief operations, providing visibility and coordination. TTF is also a mediator between the characteristics of RFID technology and disaster relief operations and between visibility and coordination.

The many recent humanitarian disasters have demonstrated the critical importance of effective and efficient humanitarian supply chain and logistics strategies and operations in assisting disaster-affected populations. The active and appropriate use of technology, including RFID, can help make disaster response more effective and efficient.

Humanitarian actors value RFID technology because of its ability to improve the visibility and coordination of relief operations. This study brings a new perspective to the benefits of RFID technology and sheds light on its antecedents. The study thus expands the understanding of technology in humanitarian operations.

The purpose of this paper is to investigate the factors that influence college students’ smartphone use for academic purposes by identifying the task-technology fit (TTF) of smartphones. A research model is proposed to explain how TTF of smartphones affects college students’ perceived academic performance and smartphone use.

Online surveys were administered to college students at a South Korean university that has offered online academic services for more than five years, and 1,923 valid responses were analyzed. The study used partial least squares path modeling to evaluate the measurement model, and the bootstrapping technique to test the significance of the hypotheses.

The findings highlight that the TTF of smartphones has a direct influence on students’ perceptions of performance impact and an indirect influence on smartphone use through a precursor of utilization, such as attitude toward smartphone use, social norms and facilitating conditions.

Despite a reasonably large sample, a single cross-sectional survey has a likelihood of selection bias in the sample.

This study applies the TTF model to smartphone use among college students and suggests an effective way to motivate them to use mobile technologies for their academic activities.

The present study develops an empirical model to assess the adoption of smartphones and its effect on college students’ academic performance. Above all, the study identifies a causal relationship among TTF, precursor of utilization, smartphone use and a perceived impact on academic performance based on the development and validation of the TTF constructs of smartphones.

According to expectation–confirmation model (ECM) and task-technology fit (TTF) model, the purpose of this paper is to examine the role of TTF in students’ cloud-based e-learning continuance and evaluate whether TTF affects students’ perceived impact on learning of the cloud-based e-learning system within the educational institution.

Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 500 questionnaires were distributed in the campus, and 391 (78.2 percent) usable questionnaires were analyzed using structural equation modeling in this study.

This study’s results verified that both task characteristics and technology characteristics affected students’ perceived TTF, which significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, and these in turn directly or indirectly led to their continuance intention of the system and perceived impact on learning; essentially, the results strongly supported the research model integrating ECM and TTF model via positioning key constructs as the drivers with all hypothesized links being significant.

This study contributes to an understanding of the TTF in explaining students’ cloud-based e-learning continuance that is difficult to explain with only their utilitarian perception of the cloud-based e-learning system, and further places considerably more emphasis upon students’ perceived impact on learning greatly driven by their TTF in the system. Thus, this study’s empirical evidence on incorporating ECM and TTF model can shed light on the outcome for cloud-based e-learning continuance and enhance better understanding of a richer post-adoption model.

The purpose of this paper is to identify and examine the most important factors that could predict the Saudi customer’s continued intention towards adoption of mobile banking.

The proposed conceptual model was based on the technology acceptance model (TAM) and task-technology fit (TTF) model. This is also expanded by considering two additional factors: perceived privacy and perceived security. By using a self-administered questionnaire, the data were collected from a convenience sample of Saudi banking customers from different parts of Saudi Arabia.

The main results based on structural equation modelling analyses supported the impact of perceived privacy, perceived security, perceived usefulness and TTF on the customers’ continued intention to use mobile banking.

The moderation influence of the demographic factors (i.e. age, gender, income level, educational level) was not tested. The data were also collected using a self-report questionnaire; however, it would be more accurate to utilise more statistics from the bank database about the users of m-banking.

This study represents a worthy attempt to test such novel technology (m-banking) in the KSA where there is a scarcity of literature. A considerable theoretical contribution was also made by integrating the TTF model with the TAM in addition to consider privacy and security in one single model. Moreover, considering both perceived privacy and security in the current model creates an accurate picture about the adoption of m-banking especially as there are a limited number of m-banking studies that have considered privacy and security alongside the TTF model and TAM in the same model.

Using the extended task‐technology fit (TTF) model, the purpose of this paper is to examine the impact of intranet usage on middle managers' performance in the port industry.

The study was conducted on 357 middle managers from various organisations in the Malaysian port industry.

The structural equation modelling results indicate that TTF and usage significantly explains the variance on managers' performance. TTF is a predictor of perceived usefulness and usage but it does not predict user resistance. Perceived usefulness is a predictor of usage but it does not predict user resistance. User resistance does not predict managers' performance.

The study focuses only on the port industry in Malaysia and concentrates only on the management perspective of intranet usage.

The results provide insights on how the Malaysian port industry and other organisations of a similar structure could improve on their intranet adoption.

This study is perhaps one of the first to address the intranet adoption in the port industry using a comprehensive, extended TTF model (perceived usefulness, usage, user resistance) to investigate their influences on individual job performance.

Although the use of e-book readers has become increasingly widespread, there are few studies to evaluate e-book user behavior and satisfaction with commercial e-book stores, and even fewer approaches from the perspective of task-technology fit (TTF). In order to fill this gap, the purpose of this paper is to adopt the TTF theory to explore the factors that affect the behavior satisfaction of users of commercial e-book stores.

A survey was conducted to collect data from 183 e-book users. Data were collected from an online survey. The results were analyzed via the structural equation model.

The results show that functional service, mobility, convenience, and searching task are the important factors that influence users’ TTF behavior. Moreover, TTF may improve user satisfaction, flow, and scanpath. Finally, satisfaction was affected by TTF, scanpath, and flow factors. An analysis of the research explained 46 percent of the variance for the users’ TTF, and 59 percent of the variance for satisfaction of using the e-book store.

The research model modifies utility and performance from TTF theory in order to focus on individual flow, scanpath, and user satisfaction measurement because general e-book store users are not typically concerned about work performance issues for their leisure activities. These results provide a new perspective to e-book researchers and can help e-book store managers and designers in making policies and designing platforms.

This study's purpose is to propose an integrated model based on expectation-confirmation model (ECM), task-technology fit (TTF) model, and updated DeLone and McLean information system (IS) success model to examine whether quality factors and TTF as antecedents to physician beliefs can affect physicians' continuance intention of the cloud-based hospital information system (HIS) and performance impact.

Sample data for this study were collected from physicians at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 305 (61.0 percent) usable questionnaires were analyzed using structural equation modeling in this study.

This study verified that physicians' perceived information quality, system quality, general technical support service quality, and cloud storage service quality all positively caused their PU, confirmation, and perceived TTF in the cloud-based HIS, which together explained their satisfaction with the system, and subsequently led to their continuance intention of the system and performance impact.

First, IS-related and cloud-related quality factors are simultaneously taken into consideration within this study's research model, and empirical results reveal deep insights into quality evaluation in the field of physicians' cloud-based HIS continuance intention. Next, this study contributes to an understanding of TTF in explaining physicians' cloud-based HIS continuance intention that is difficult to explain with only their utilitarian perception of the system, and places emphasis upon physicians' perception of performance impact greatly driven by their perceived TTF and continuance intention of the system, thus the results can shed light on antecedents and outcome of physicians' cloud-based HIS continuance intention.

This study's purpose is to propose a hybrid model based on expectation-confirmation model (ECM) and technology acceptance model (TAM) to examine whether organizational users' perceived task-technology fit (TTF) in cloud enterprise resource planning (ERP) as an antecedent to user beliefs can directly and indirectly affect their continuance intention of cloud ERP and individual performance.

Sample data for this study were collected from end users of cloud ERP working in companies in Taiwan. A total of 500 questionnaires were distributed in the 50 sample companies, and 355 (71.0%) usable questionnaires were analyzed using structural equation modeling in this study.

This study showed that organizational users' perceived TTF contributed positively to their perceived usefulness, confirmation and perceived ease of use of cloud ERP, which in turn directly and indirectly led to their satisfaction with cloud ERP, continuance intention of cloud ERP and individual performance; that is, this study's findings strongly supported the research model integrating ECM, TAM and TTF model with all hypothesized links being significant.

This study contributes to an understanding of the TTF model in explaining organizational users' cloud ERP continuance intention that is difficult to explain with only their utilitarian perceptions of cloud ERP. Further, it is especially worth mentioning that this study places considerably more emphasis upon organizational users' individual performance greatly driven by their perceived TTF in cloud ERP and continuance intention of cloud ERP. Thus, this study's empirical evidence on incorporating ECM, TAM and TTF model can significantly enhance better understanding of the outcomes for cloud ERP continuance intention and shed light on the possible formulation of a richer post-adoption model.

To explore the impact of luxury hotel brands’ technologies on guests’ perceived value enhancement and its consequences, this study aims to examine how task–technology fit (TTF) and luxury–technology fit (LTF) affect luxury hotel guests’ perceived value enhancement, satisfaction and brand loyalty.

A scenario-based online survey was conducted with existing and potential luxury hotel guests. The relationships among TTF, LTF, value enhancement, satisfaction and loyalty were examined using partial least square structural equation modeling. Moreover, the respondents were asked their preferred service agent (human staff vs technology) in a luxury hotel to further understand luxury hotel guests’ perception toward technological services in a luxury hotel setting.

The results reveal that both TTF and LTF have significant impacts on the luxury hotel’s value enhancement, and the impacts of TTF and LTF on value enhancement are moderated by the guests’ technology optimism. The findings of this study suggest that the luxury hotel brands must consider the fit between the image of their brand and the technology to increase guests’ perceived value enhancement, satisfaction and loyalty.

Applying categorization theory, this study extended the concept of brand extension to technology implementation. The findings advance the current understanding of how technology affects luxury hotel consumers’ perceived value enhancement, and how consumers’ optimism influences the impacts of TTF and LTF on value enhancement.

By examining the effects of TTF and LTF on luxury hotel guests’ perceived value enhancement, this study would shed light on luxury hotel brands’ technology implementation strategies. By understanding how TTF and LTF affect consumers’ perceived value enhancement, luxury hotel brands will be able to better design their technology implementation plans.

Even though luxury hotel brands are well known for offering high-level and personalized services through interpersonal interactions between employees and consumers, they have been actively implementing a variety of technologies to enhance guest experience and satisfaction. This study investigates the role of technological innovations in a luxury hotel setting. Particularly, this study examines how technologies improve guests’ perceived value of a luxury hotel and lead to satisfaction and loyalty.