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This study aims to highlight that security and flexibilities remain the main points of contention in the cordiality business. This research points to planning a framework that empowers hotel users to get to the room using a mobile access key. Advancing secured facilities, mobile phone “Near Field Communication” (NFC) innovation as the entrance device by carrying out an application containing an imitated mobile key for explicit verification access is used.

The proposed system is evaluated by triangulation of experimental, numerical and rational evaluation using partial least square structural equation modeling (PLS-SEM) with Malaysian hotel guests and employees.

The discoveries with the hypothesis supported validated that the suggested solution can eliminate physical cards, boost protection and encourage a contactless ecosystem. Theoretical, management and societal contributions are discussed here.

This experiment comes with the constraints that it was conducted in only two hotels and does not fully reflect the choices of a wider range of travellers. Secondly, the cost of existing NFC smart locks is still relatively high, and along with the development of technology, the price will decrease when supply exceeds demand.

To promote high-security attributes, NFC technology as the access system by implementing an application containing an emulated smart key for specific authentication access is used. The host-card emulation enables cost-effectiveness profit and initiating a defence system in the pandemic era.

To promote high-security attributes, NFC technology is used as the access system by implementing an application containing an emulated smart key for specific authentication access. The host-card emulation enables cost-effectiveness profit and initiating a defence system in the pandemic era.

The novelty of this study comes from the use of commonly available smartphone NFC features that are yet to be applied in the tourism ecosystem. The research provokes the applied concept of mobile smartkeys.

This study aims to investigate the effect of social influence and value-driven mobile marketing activities on consumers’ acceptance of mobile marketing offers.

The method used is survey questionnaire. A proposed model was tested by using structural model analysis and data gathered from 356 Mexico consumers and 346 US consumers.

The study shows the number of peers and providing information are the main predictor variables of consumer acceptance of mobile marketing offers in both countries. These results suggest that social value factors are important variables for explaining consumers’ responses to mobile marketing offers across two countries characterized by dissimilar macro-environmental conditions.

The study’s overall implication about standardization vs adaptation is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries. One limitation in this study is the use of a convenience sample of undergraduate college students. This study did not control for different types of mobile phones and the screen sizes of mobile phones.

The overall implication of standardization vs adaptation from the study results is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries.

Unlike previous studies where the emphasis is to explicate the effect of value-oriented mobile activity, this study examines the combined effect of social influence and value-driven mobile activities on acceptance of mobile marketing.

COVID-19 has occurred in more than 150 countries and causes a huge impact on the health of many people. The main purpose of this work is, COVID-19 has occurred in more than 150 countries and causes a huge impact on the health of many people. The COVID-19 diagnosis is required to detect at the beginning stage and special attention should be given to them. The fastest way to detect the COVID-19 infected patients is detecting through radiology and radiography images. The few early studies describe the particular abnormalities of the infected patients in the chest radiograms. Even though some of the challenges occur in concluding the viral infection traces in X-ray images, the convolutional neural network (CNN) can determine the patterns of data between the normal and infected X-rays that increase the detection rate. Therefore, the researchers are focusing on developing a deep learning-based detection model.

The main intention of this proposal is to develop the enhanced lung segmentation and classification of diagnosing the COVID-19. The main processes of the proposed model are image pre-processing, lung segmentation and deep classification. Initially, the image enhancement is performed by contrast enhancement and filtering approaches. Once the image is pre-processed, the optimal lung segmentation is done by the adaptive fuzzy-based region growing (AFRG) technique, in which the constant function for fusion is optimized by the modified deer hunting optimization algorithm (M-DHOA). Further, a well-performing deep learning algorithm termed adaptive CNN (A-CNN) is adopted for performing the classification, in which the hidden neurons are tuned by the proposed DHOA to enhance the detection accuracy. The simulation results illustrate that the proposed model has more possibilities to increase the COVID-19 testing methods on the publicly available data sets.

From the experimental analysis, the accuracy of the proposed M-DHOA–CNN was 5.84%, 5.23%, 6.25% and 8.33% superior to recurrent neural network, neural networks, support vector machine and K-nearest neighbor, respectively. Thus, the segmentation and classification performance of the developed COVID-19 diagnosis by AFRG and A-CNN has outperformed the existing techniques.

This paper adopts the latest optimization algorithm called M-DHOA to improve the performance of lung segmentation and classification in COVID-19 diagnosis using adaptive K-means with region growing fusion and A-CNN. To the best of the authors’ knowledge, this is the first work that uses M-DHOA for improved segmentation and classification steps for increasing the convergence rate of diagnosis.

This research investigates how consumers who are most active on Facebook during the day vs in the evening differ, differ in their ad consumption, and how advertising effects vary as a function of a key moderator: gender.

Using a survey of 281 people, the research identifies Facebook users who are more intensely using mobile social media during the day versus in the evening, and measures five Facebook mobile advertising outcomes: brand and product recall, clicking on ads, acting on ads and purchases.

The results show that women who are using social media more intensely during the day are more likely to use Facebook to seek information, hence, Facebook mobile ads tend to be more effective for these users compared to those in the evening.

This contributes to the literature by analyzing how the time of day affects social media behavior in relation to mobile advertising effectiveness, and broadening the scope of mobile advertising effectiveness research from other than just clicks on ads to include measures like brand and product recall.

By analyzing the effectiveness of mobile advertising on social media as a function of the time of day, advertisers can be more targeted in their media buys, and so better use their social media budgets, i.e. advertising is more effective for women who use social media (Facebook) more intensely during the day than for those who use social media more intensely in the evening as the former tend to seek more information than the latter.

This research extends media ecology theory by drawing on circadian rhythm research to provide a first demonstration of how the time of day relates to different uses of mobile social media, which in turn relate to social media mobile advertising consumption.

While research on social media advertising has been steadily increasing, little has been explored on how users consume ads when they engage with social media at different periods along the day. This paper extends media ecology theory by investigating time of day, drawing on the circadian rhythm literature, and how it relates to social media usage.

Even if digital financial services have a positive impact on financial inclusion, it creates a digital as well as gender divide within and across countries, creating regional disparity even within developing nations. Though pandemic has initiated digitalization of various services, there has been scanty research on whether digital transfer of income can improve digital financial inclusion in post-pandemic era, especially in developing countries. The purpose of the current study is to explain the regional disparity within developing countries from three regions East Asia Pacific, South Asia and Sub-Saharan Africa, using latest World Findex data, 2021.

The author takes an instrumental variable approach to run bivariate probit model to find the factors that motivate the users to make digital payments.

The study observes that electronic transfer of wages, government transfers and remittances can motivate individuals to make use of digital mode of transactions and mobile. The practice of formal saving and borrowings are the prerequisites. However, this mechanism holds good for East Asia Pacific and not for South Asia and Sub-Saharan Africa, which are poor in information and communication technology infrastructure. Women are lagging behind men, but digital transfer of wages motivate them to make digital transaction.

Digitalization of all government services and provision of affordable mobile network and internet services are necessary for regions like South Asia and Sub-Saharan Africa. In East Asia Pacific region, data protection, data governance and better regulatory framework are required. Higher female labor force participation with digital transfer of wages and empowerment with smartphones are key to reducing the Gender gap.

The current study corrects for the possible endogeneity issue, which the extant literature has not paid attention to, and provides region-specific and gender-specific policy recommendations for an improved digital inclusion.

The COVID-19 pandemic has significantly impacted global tourism, with international travel bearing the burden of restrictions. Domestic tourism has also faced substantial challenges. This paper aims to analyse the impact of the COVID-19 pandemic on domestic tourism in Spain, focusing on travel from Madrid (the country’s capital) to other tourist destinations.

Mobile phone data has been used to study the evolution of tourist trips over the summers of 2019, 2020 and 2021. Regression models are used to explain the number of visitors at destinations.

The pandemic not only caused a drastic drop in tourist flows but also disrupted the overall pattern of the domestic flow system. Winning destinations were typically areas in proximity to Madrid and less densely populated destinations, while urban destinations were major losers. The preferences of domestic tourists varied notably by income group, but the decrease in trip volumes showed only marginal differences.

The paper demonstrates the potential of mobile phone data analysis to study the uneven impact of external shocks, such as the COVID-19 pandemic, on tourist destinations. This approach considers spatial resilience heterogeneity within regions or provinces. By incorporating income information, the analysis introduces a social dimension to highly detailed spatial data, surpassing traditional studies conducted at the regional or national levels.

COVID-19大流行对全球旅游业产生了重大影响，国际旅行受到了限制的影响最为严重。国内旅游也面临着重大挑战。本文分析了COVID-19大流行对西班牙国内旅游的影响，重点关注从马德里（该国首都）到其他旅游目的地的旅行。

本研究使用移动电话数据研究了2019年、2020年和2021年夏季旅游出行的演变。采用回归模型解释了各目的地游客数量。

大流行不仅导致了旅游流量急剧下降，还扰乱了国内流动系统的总体模式。获胜的目的地通常是马德里附近的地区和人口较稀少的目的地，而城市目的地是主要的输家。国内游客的偏好在收入群体之间有明显差异，但旅行量的减少只显示出边际差异。

本文展示了使用移动电话数据分析研究外部冲击（如COVID-19大流行）对旅游目的地的不均匀影响的潜力。该方法考虑了区域或省份内的空间弹性异质性。通过整合收入信息，该分析为高度详细的空间数据引入了社会维度，超越了传统在区域或国家水平进行的研究。

Financial inclusion and digital finance go side by side and help enhance agricultural activities; however, the magnitude of digital financial services varies across countries. In line with this argument, this study aims to examine whether financial inclusion enhances agricultural participation and decompose the significance of the difference in determinants of agricultural participation between financially included – not financially included households and digital finance – no digital finance households.

This study uses Pakistan’s household integrated economic survey 2018/19 to test hypotheses. The logit model is used to examine the effect of financial inclusion on agriculture participation. Moreover, this study employs a nonlinear Fairlie Oaxaca Blinder technique to investigate the difference in determinants of agricultural participation.

This study reports that financial inclusion positively influences agricultural participation, meaning households may have access to financial services and participate in agricultural activities. The results suggest that the likelihood of participating in agriculture in households with mobiles and smartphones is higher. Moreover, household size, income, age, gender, education, urban, remittances from abroad, fertilizer, pesticides, wheat, cotton, sugarcane, fruits and vegetables are the significant determinants of agricultural participation. To distinguish the financially included – not financially included households’ gap, this study employs a nonlinear Fairlie Oaxaca Blinder decomposition and finds that differences in fertilizer explain the substantial gap in agricultural participation. Likewise, this study tests the digital finance – no digital finance gap and finds that the difference in fertilizer is a significant contributor, describing a considerable gap in agricultural participation.

Empirically identified that various factors cause agricultural participation including financial inclusion and digital finance. Regarding the research limitation, this study only considers a developing country to analyze the findings. However, for future research, scholars may consider some other countries to compare the results and identify their differences.

The accessibility of fertilizer can reduce the agricultural participation gap. However, increased income level, education and cotton and sugar production can also overcome the differences in agriculture participation between digital finance and no digital finance households.

This is the first study to decompose the difference in determinants of agricultural participation between financially and not financially included households.

Prior research has extensively examined how bringing technology from work into the non-work life domain creates conflict, yet the reverse pathway has rarely been studied. The purpose of this study is to bridge this gap and examine how the non-work use of smartphones in the workplace affects work–life conflict.

Drawing from three literature streams: technostress, work–life conflict and role boundary theory, the authors theorise on how limiting employees' ability to integrate the personal life domain into work, by means of technology use policy, contributes to stress and work–life conflict. To test this model, the authors employ a natural experiment in a company that changed its policy from fully restricting to open smartphone access for non-work purposes in the workplace. The insights gained from the experiment were explored further through qualitative interviews.

Work–life conflict declines when a ban on using smartphones for non-work purposes in the workplace is revoked. This study's results show that the relationship between smartphone use in the workplace and work–life conflict is mediated by sensed stress. Additionally, a post-hoc analysis reveals that work performance was unchanged when the smartphone ban was revoked.

First, this study advances the authors' understanding of how smartphone use policies in the workplace spill over to affect non-work life. Second, this work contributes to the technostress literature by revealing how, in specific situations, engagement with ICT can reduce distress and strain.

This study aims to estimate the quality-adjusted changes in residential mobile consumer prices by controlling for the changes in the relevant service characteristics and quality, in a case study on Hungary between 2015 and 2021; compare the results with changes measured by the traditionally calculated official telecommunications price index of the Statistical Office; and discuss separating the hedonic price changes from the effect of a specific government intervention that occurred in Hungary, namely, the significant reduction in the value added tax rate (VAT) levied on internet services.

Since the price of commercial mobile offers does not directly reflect the continuous improvements in service characteristics and functionalities over time, the price changes need to be adjusted for changes in quality. The authors use hedonic regression analysis to address this issue.

The results show significant hedonic price changes over the observed seven-year period of over 30%, which turns out to be primarily driven by the significant developments in the comprising service characteristics and not the VAT policy change.

This paper contributes to the literature on hedonic price analyses on complex telecommunications service plans and enhances this methodology by using weights and analysing the content-related features of the mobile packages.

This study aims to explore the factors influencing the bottom of the pyramid (BOP) consumers’ adoption and usage intention towards mobile payment (m-payment) to achieve financial inclusion and sustainable development goals.

A qualitative research design is used to explore the enablers and inhibitors that influence BOP consumers’ m-payment adoption and usage intention. To collect the qualitative responses, semi-structured in-depth interviews with BOP respondents were conducted. The thematic analysis using the text mining technique will be used to analyse qualitative data for exploring the predominant factors affecting m-payment adoption intention and usage.

The results suggested awareness, social influences and self-efficacy as crucial enablers and privacy and security risks and vulnerability concerns as crucial inhibitors towards m-payment adoption and usage.

As a novel contribution to the BOP, financial inclusion, sustainable development goals and m-payment literature, this study unfolds several unknown perceived benefits and perceived sacrifices that influence the BOP consumers’ m-payment adoption intention and usage. The study’s findings help the government and banks formulate and implement strategies to achieve financial inclusion among BOP consumers.