Search results

This study acknowledges the existing digital divide in India, particularly for marginalised populations, and highlights the need for exceptional attention to address their unique needs, challenges and demands. Although previous research and policies have primarily focused on physical access and internet skills, this study shifts the focus to the outcomes of internet use. By understanding how older adults in marginalised communities incorporate the internet into their daily routines, this study aims to contribute to the development of an operational framework that charts the disadvantages of the digital divide.

The study draws from Helsper’s (2015) internet outcomes framework to identify the outcomes that older adults can derive from being online. By using a qualitative approach, the study seeks to understand how educational and economic backgrounds influence internet usage among older adults and how this can promote advantageous internet use.

The findings indicate that highly educated individuals are more likely to experience positive outcomes across various societal domains than their less educated counterparts. However, it was observed that the highly educated participants also try to limit the impact of internet use on their personal lives by intentionally disconnecting from the internet whenever possible.

By offering programmes and interventions to encourage internet use and improve digital skills, as well as by enhancing digital accessibility and incentive systems, the government should go forward with its plan to close the outcomes gap in internet use among older adults. For policymakers, it turns the spotlight on creating an environment conducive to the digital inclusion of older adults, consistent with sociocultural structures.

This study contributes to understanding the nuanced dynamics of internet use among older adults, shedding light on the role of educational background and sociocultural factors in shaping internet outcomes. It highlights the need to consider qualitative approaches in digital inequality research to capture the complexities underlying the digital divide.

In response to the growing interest in Internet of Things (IoT) technology and its profound implications for businesses and individuals, this bibliometric study focuses on a critical yet understudied aspect, i.e. cybersecurity. As IoT adoption grows, so do concerns regarding user privacy and data security. This study aims to provide a comprehensive understanding of the current research in this vital area, shedding light on research trends, gaps and emerging themes.

The study conducted a bibliometric analysis and systematic review of literature spanning over two decades (2013–2023). Bibliometric analysis is conducted using Biblioshiny which is R-software-based advanced analytical tool. Further, VOSviewer is used to conduct network analysis. The study highlights the evolving landscape of IoT cybersecurity, emphasizing interdisciplinary intersections and the ethical dimensions of IoT technologies.

The study uncovers crucial concerns related to IoT adoption, emphasizing the urgent need for comprehensive cybersecurity protocols. It identifies emerging themes such as artificial intelligence and blockchain integration, indicating a shift toward interdisciplinary solutions. Furthermore, the research highlights ethical gaps in current IoT discussions, emphasizing the importance of responsible innovation.

Businesses can bolster their cybersecurity strategies, policymakers can craft informed regulations and researchers are encouraged to explore IoT’s ethical dimensions.

This study pioneers a nuanced analysis of IoT cybersecurity, filling a crucial gap in the existing business and management literature. By synthesizing a decade of scholarly work, it provides foundational insights for researchers, businesses and policymakers. The research not only informs academic discourse but also offers practical guidance for enhancing IoT security measures and fostering ethical innovation.

This research presents machine learning models for predicting international tourist arrivals in Indonesia during the COVID-19 pandemic using multisource Internet data.

To develop the prediction models, this research utilizes multisource Internet data from TripAdvisor travel forum and Google Trends. Temporal factors, posts and comments, search queries index and previous tourist arrivals records are set as predictors. Four sets of predictors and three distinct data compositions were utilized for training the machine learning models, namely artificial neural networks (ANNs), support vector regression (SVR) and random forest (RF). To evaluate the models, this research uses three accuracy metrics, namely root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE).

Prediction models trained using multisource Internet data predictors have better accuracy than those trained using single-source Internet data or other predictors. In addition, using more training sets that cover the phenomenon of interest, such as COVID-19, will enhance the prediction model's learning process and accuracy. The experiments show that the RF models have better prediction accuracy than the ANN and SVR models.

First, this study pioneers the practice of a multisource Internet data approach in predicting tourist arrivals amid the unprecedented COVID-19 pandemic. Second, the use of multisource Internet data to improve prediction performance is validated with real empirical data. Finally, this is one of the few papers to provide perspectives on the current dynamics of Indonesia's tourism demand.

Agriculture is one sector where the Internet of things (IoT) is expected to make a major impact. Yet, its adoption in the sector falls behind expectations. The purpose of this paper is to present the state-of-the-art of IoT in agriculture and investigate its slow adoption in the sector.

The authors have undertaken a systematic review and a synthesis of 1355 relevant publications over the last decade.

This literature review reveals that the “big three” barriers for the overall sector are cost, skills and standardization. The lack of connectivity and data governance are two key reasons why most of the proposed IoT solutions are standalone systems of limited scope, while the majority of commercial IoT efforts focus on practices in the protected indoor environment. Lastly, the analysis of past research along the five layers of the IoT system architecture reveals limited attention to barriers and solutions at the business layer, which represents a research opportunity for information systems scholars.

It is possible that some of relevant publications were missed in the literature search, although the search queries were kept as broad as possible to avoid the exclusion of any relevant work. Any publication written in any other language other than English was excluded from the review. Given the geographical distribution of the reviewed English publications (see section 4.1), it is highly likely that important works written by Chinese and European scholars in their native language were overlooked.

This study provides practical insights into the technical and organisational challenges on the ground. It is the hope that this literature review lays the groundwork for IS researchers who are well positioned to investigate technology adoption challenges in the relatively understudied agriculture sector.

To the best of the authors’ knowledge, this is the first comprehensive review of adoption barriers and solutions across all five layers of the IoT system architecture.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

Social commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).

In the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.

From 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.

The SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.

The authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.

The study aims to examine the conceptualization of online abuse (OA) and identifies theories, countries of research, top-cited articles, methodologies, antecedents, mediators, outcomes and moderators of OA and future research opportunities. Two research questions are addressed. How have the past studies on OA progressed regarding theories, context, characteristics and methodology? What future research opportunities can be done in this area?

This study systematically reviews, synthesizes and integrates OA literature using the well-recommended preferred reporting items for systematic reviews and meta-analyses (PRISMA) rules. The literature on OA was synthesized based on the Theory–Context–Characteristics–Methodologies (TCCM) framework given by Paul and Rosado-Serrano.

Through an examination of TCCM used in OA research, the review presents an all-inclusive and up-to-date overview of the research in this arena and sets a future research agenda to spur scholarly research. This systematic literature review has analyzed top-quality sample papers, published in the past decade. As a result, it contributes to a better understanding of this relationship by analyzing the different types of use and the value added to the shopping experience.

This study provides groundwork for researchers and promotes a deeper understanding of OA.

The study aims to present a systematic literature review (SLR) to understand the current status of research on social media usage among the bottom of the pyramid (BOP). The purpose of this study is to identify the research gaps in this domain and review future research agendas by using theory, context, characteristics and methods [TCCM] framework.

An SLR, keywords co-occurrence and TCCM analysis were used to analyse and synthesize insights from 44 studies gained from Web of Science and Scopus databases.

The findings suggest that the USA and India are popular contexts for studying BOP. The BOP population uses social media to gain utilitarian, hedonic and social values. Further, social media can help BOP explore “entrepreneurship” opportunities, value co-creation and bring innovations.

This study expands the intellectual boundaries of social media at BOP and suggests multidisciplinary research. Additionally, adopting novel theoretical lenses helped determine social media's impact on BOP.

This study aimed to examine the research hotspots and evolution paths in the field of health information behavior (HIB) in China and abroad, and conduct comparative analysis to better understand its development trajectory globally.

A keyword search of the relevant literature included in the China National Knowledge Infrastructure (CNKI) database and Web of Science (WoS) core collection database was conducted, using the visualized analysis tool CiteSpace V for bibliometric analyses.

The common research hotspots in China and abroad can be divided into related research on HIB, research on its influencing factors and health information research. Among these, health information-seeking behavior has been the focus of domestic and foreign scholars. From the subdivision perspective, the focus of Chinese and foreign research hotspots differs. In terms of evolutionary path, the initial stage of HIB research in China and abroad revolves around health information and health information-seeking behavior, followed by the influencing factors of HIB; however, the research breakthrough point is the reverse. Then, domestic and foreign research was conducted on different types of HIBs. Regarding the selection of research objects, Chinese and foreign research objects were increasingly diversified.

This study also has several limitations. First, the literature sample only selected the literature in the WoS and CNKI databases, and there may be many HIB-related works published in other databases. Therefore, future research should include other databases. Second, in terms of language, this study selected only Chinese and English literature, but in many countries, important research results on certain topics are usually published in native language, and future research should expand the language selection. Third, this study only conducted national and institutional collaboration network analysis, keyword co-occurrence analysis, cluster analysis and timeline chart analysis.

The implication of practice can be divided into the following three points. (1) Analyzing the domestic and foreign literature on HIB and identifying highly cooperative institutions and countries in the field of HIB can reveal the research situation of HIB and help researchers establish new research networks in the future. (2) Analyzing the research hotspots and evolutionary paths of HIB at home and abroad is helpful for quickly understanding the development context of this field and grasping the emerging research directions such as HIB of people in close contact with patients, health information exchange behavior, health information avoidance behavior and health information discontinuation behavior, which can help researchers to explore the future research direction in this field, so as to determine the topic and fill the research gap. (3) Combining the analysis of HIB-related research at home and abroad is helpful for professionals to understand the characteristics and rules of HIB of users, consumers and other groups to further optimize and improve health information services.

Comparing and summarizing the research status of HIB in China and globally, and presenting the findings visually, will help researchers better grasp the research overview and hotspot changes in this field, as well as provide a follow-up reference.

This study explores whether and how four main factors of short-branded video content (content matching, information relevance, storytelling and emotionality) facilitate consumer engagement (likes, comments and shares), as well as the moderating effect of the release time (morning, afternoon and evening) in such relationships.

This study uses Python to write programs to crawl relevant data information, such as consumer engagement and short video release time. It combines coding methods to empirically analyze the impact of short-branded video content characteristics on consumer engagement. A total of 10,240 Weibo short videos (total duration: 238.645 h) from 122 well-known brands are utilized as research objects.

Empirical results show that the content characteristics of short videos significantly affected consumer engagement. Furthermore, the release time of videos significantly moderated the relationship between the emotionality of short videos and consumer engagement. Content released in the morning enhanced the positive impact of warmth, excitement and joy on consumer engagement, compared to that released in the afternoon.

The findings provide new insights for the dissemination of products and brand culture through short videos. The authors suggest that enterprises that use brand videos consider content matching, information relevance, storytelling and emotionality in their design.

From a broader perspective, this study constructs a new method for comprehensively evaluating short-branded video content, based on four dimensions (content matching, information relevance, storytelling and emotionality) and explores the value of these dimensions for creating social media marketing success, such as via consumer engagement.