Search results

The purpose of this paper is to investigate the use contexts of personal computing devices in multiple steps and conducts an in-depth analysis for the use context of smartphones. The determinants of use context changes of smartphones are investigated using the technology-to-performance chain model.

In steps 1 and 2, a diary study method and 2014-2015 Korea media panel research data provided by the Korea Information Society Development Institute are used. Correspondence analysis, χ² independence tests, and standardized residual analyses were conducted. In step 3, this study develops and validates a framework for use context changes using a survey method and structural equation modeling.

The results show that the use context of personal computing devices is represented differently and is clearly defined depending on the device used. Furthermore, the use context of smartphones has changed significantly because of the rapid growth of smartphone users and diverse usage patterns of smartphones. The research model results show that users expand the scope and frequency of smartphone use when they experience improved performance in everyday tasks and feel that smartphone content and functions could support everyday tasks better.

This study presents novel early stage research and presents empirical evidence and propositions in both exploratory and confirmatory ways. The main contribution of this study is to provide guidelines and general implications for other empirical studies on the use contexts of devices or information technology services.

In mobile platforms, an increasing number of third-party developers (developers) create new ideas and enhance their expertise through knowledge sharing on the developers’ community. Notwithstanding the importance of the sharing and its uniqueness on the mobile platform contexts, the motivational factors of sharing their knowledge on the community have been underinvestigated. Therefore, this paper aims to provide a comprehensive framework to enhance the knowledge sharing in the mobile platform context.

Based on the theory of reasoned action, this paper incorporated intrinsic and internalized extrinsic motivations with two unique features of platform environments: platform open policies and coopetitive relationships. To test, an online survey was distributed to four developer communities in Korea, two Android and two iOS communities.

The results show that a platform pursuing higher openness causes the developers to find higher social pressure for information sharing. The coopetitive relationship with other developers in the same platform takes dissimilar roles; reciprocity significantly increases subjective norm, while rivalry does attitude. Self-efficacy and self-development stimulate knowledge sharing. Furthermore, multilevel analysis to capture the difference between two leading mobile platforms indicates no path difference but, interestingly, shows significant mean difference between the two platforms regarding perceived openness and rivalry.

With this paper, the authors fulfill the need to understand the knowledge-sharing intention of developers in the context of mobile platforms where developers can be potential competitors or cooperators and where two platforms offer different policies and developmental environments.

This chapter examines a popular online trend—photo-sharing—in an understudied region, the League of Arab States. In contrast to online information from official bodies, anyone with Internet access can view and create destination photos. This study first searched for destination photos on Flickr.com, a popular photo-sharing website, from 22 Arab countries, and then content analyzed 589 Muslim and travel photos. The key results included Egypt with the most destination photos and Saudi Arabia with the most Muslim images. Common Muslim images were mosques and women with headscarves. This chapter shows that Flickr photos represent Arab images and are possible destination recommendations.

In recent years, scholarly focus has shifted towards exploring the applications of disruptive technologies in professional services. These studies emphasise the need for further research in this domain. This research aims to comprehensively review the existing literature on the uses of blockchain, artificial intelligence (AI) and machine learning (ML) algorithms in professional services such as higher education, healthcare, financial securities firms and smart energy consulting. The rapid innovation and advancement in technology have led to substantial improvements in work efficiency and productivity. As industries transition towards sustainability and digitalisation, the role of energy-efficient systems becomes important in shaping smart factory designs and in further implementations. The uses of AI and other disruptive technologies for business operations not only boost production efficiency but also enhance customer satisfaction. Central to this transformation are strategies like deep learning and data/text mining, which facilitate the shift from conventional manufacturing practices to smart manufacturing. Apart from smart energy systems, the fields of higher education, healthcare and financial securities are witnessing a surge in the applications of AI, ML algorithms and blockchain technology and their contributions in emerging service economy. This study undertakes a comprehensive investigation into various factors associated with the application of disruptive technologies, evaluating their impact on the operational efficiency of professional service firms (PSFs). Through this research, we aim to identify gaps in the current literature and will suggest the directions for future research.

This study aims to examine consumer perception during COVID-19 and identifies cruise industry marketing strategies to fill a gap in crisis management and product pricing literature.

This study developed and validated two-factor measurement scales (vaccine perception and protective behavior), which predicted cruise intents well. This study revealed how geo-regional factors affect consumer psychology through spatial analysis.

This study recommended pricing 7-day cruises at $1,464 (the most preferred length). The results also showed that future price hikes would not affect demand and that coastal marketing would help retain customers.

This study contributed to the business, hospitality and tourism literature by identifying two new and unique factors (vaccine perception and protective behaviors), which were found to affect consumers’ intention to travel by cruise significantly. The result provided a better understanding of cruise tourists’ pricing preferences and the methods utilized could easily be applied to other cruise markets or tourism entities.

The use of volunteers is one of the approaches to capacity building, preparedness and the response of the health system in disasters. Appropriate management of volunteers during disasters and emergencies is essential. This study aimed to explain the challenges of volunteer management in the Pandemic COVID-19 in Iran.

Qualitative research was conducted using the content analysis based on the Graneheim method. The participants' selection was done based on purposeful sampling and theoretical sampling until data saturation. Direct field observation and 26 interviews were applied to collect data.

Four categories and 15 sub-categories emerged to describe the challenges of volunteer management during the COVID-19 crisis including policymaking barriers (including legal barriers, insurance and support coverage and risk governance), managerial barriers (including planning, coordinating and organizing, training and awareness, command and leadership and information management and documentation), socio-cultural barriers (personal safety attitude and culture, attitudes and expectations of the community and perspectives on volunteers) and executive-operational barriers (monitoring and evaluation, cost and needs assessment).

It is essential to increase managers', officials' and volunteers' perceptions of COVID19 risk through education and information. Preparing a database for volunteers' information, including non-governmental organization and governmental organization volunteers, planning for needs assessment, establishing a mechanism for recruiting volunteers and using their capacities and appropriate organizing, tracking and monitoring of volunteers can be among effective strategies.

The purpose of this paper is to examine the effect of green coffee extract on anthropometric index and lipid profile, fasting blood sugar, chemerin and malondialdehyde on subjects with metabolic syndrome.

A randomized, double-blind, placebo-controlled clinical trial was conducted in Sheikh Al Raise Clinic from September 2016 to March 2017. The participants were randomly divided into green coffee group and placebo group. Green coffee group (n = 24) received green coffee extract (GCE), while placebo group (n = 24) took cellulose as a placebo, two capsules (400 mg) two times each day for eight weeks. The anthropometric index and lipid profile, fasting blood sugar, chemerin and malondialdehyde were measured at the beginning of the study and after eight weeks of treatment with GCE. Blood samples were collected before and after eight weeks of supplementation.

Significant weight loss, from 84.80 ± 2.12 kg to 80.94 ± 2.10 kg (ptime = 0.030, pGC = 0.007), as well as decreases in body mass index (ptime = 0.034, pGC = 0.006) were detected in the green coffee group after eight weeks. Also, the green coffee group has significant lower (pgroup = 0.029, ptime = 0.013) malondialdehyde (MDA) compared to the placebo group, and there was a significant difference between two groups at the insulin level and homeostatic model assessment of insulin resistance (HOMA-IR) (ptime = 0.001, pgroup = 0.048), (ptime = 0.012, pgroup = 0.007). However, there was no significant difference in lipid profile, fasting blood sugar and serum chemerin between two groups after eight weeks of supplementation.

This paper showed the statistical difference in body weight, malondialdehyde, insulin and insulin resistance after eight weeks of treatment. GCE might be associated to reduction in the carbohydrate absorption and the enhancement of lipid metabolism.

Redistributive policies aim to reduce income disparities and improve social equity. This study investigates whether redistributive effects that successfully diminish objective income inequality also effectively alter people’s perceptions of inequality.

Utilizing data from the 2018 China Household Income Survey (CHIP), comprising 56,167 individuals, this study applies ordered probability regression (Oprobit) and ordinary least squares (OLS) for analysis. To address potential biases in estimates, we employed the generalized propensity score matching (GPSM) method to estimate the treatment effect of transfer income on perceptions of inequality.

The results indicate that while China’s redistribution policies effectively reduce income disparities, they do not improve perceptions of inequality. Individuals exhibit biased attitudes toward redistributive policies. Specifically, perceptions of inequality are insensitive to the overall redistributive effect; the relationship is negative among the poor but positive among the rich. This contradictory pattern may be attributed to perceived income losses among the rich and gains among the poor.

The findings have important implications for policy development. Redistribution policies should not only aim to mitigate income disparities but also address and improve people’s perceptions of inequality.

Existing literature has largely overlooked the impact of redistribution on perceived income inequality. This study represents an early effort to explore whether redistributive policies that reduce income inequality also influence people’s perceptions of inequality.