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The purpose of this study was to uncover the impact of social media in supporting environmental conservation (EC) in protected areas.

The study has employed both quantitative and qualitative approaches of a cross-sectional type with simple random and purposive sampling were followed. Primary and secondary data sources were also entertained. A total of 146 observations were used in the analysis. A multiple linear regression analysis was used to measure the impact of social media.

The result revealed user-generated content and ease of language were significant in explaining EC. Environmental activism and social media usage shall be enhanced with environmental concerns (EnvCs) and objectives.

This is s an original research that tried to address the impact social media on EC and its dimensions in Lake Tana Biosphere Reserve. Unlike the research studies so far, this research attempted to uncover the impact of each social media element's impact on each EC dimensions. Besides, the impact of social media element is also assessed on EC as a construct in general. Thus, it will be helpful for policy makers, government and destination management organizations and other stakeholders to identify the areas which should be promoted and areas that need intervention.

“Fake news” or misinformation sharing using social media sites into public discourse or politics has increased dramatically, over the last few years, especially in the current COVID-19 pandemic causing concern. However, this phenomenon is inadequately researched. This study examines fake news sharing with the lens of stimulus-organism-response (SOR) theory, uses and gratification theory (UGT) and big five personality traits (BFPT) theory to understand the motivations for sharing fake news and the personality traits that do so. The stimuli in the model comprise gratifications (pass time, entertainment, socialization, information sharing and information seeking) and personality traits (agreeableness, conscientiousness, extraversion, openness and neuroticism). The feeling of authenticating or instantly sharing news is the organism leading to sharing fake news, which forms the response in the study.

The conceptual model was tested by the data collected from a sample of 221 social media users in India. The data were analyzed with partial least squares structural equation modeling to determine the effects of UGT and personality traits on fake news sharing. The moderating role of the platform WhatsApp or Facebook was studied.

The results suggest that pass time, information sharing and socialization gratifications lead to instant sharing news on social media platforms. Individuals who exhibit extraversion, neuroticism and openness share news on social media platforms instantly. In contrast, agreeableness and conscientiousness personality traits lead to authentication news before sharing on the social media platform.

This study contributes to social media literature by identifying the user gratifications and personality traits that lead to sharing fake news on social media platforms. Furthermore, the study also sheds light on the moderating influence of the choice of the social media platform for fake news sharing.

This paper examines the influence of facilitators and barriers on employees’ preference to work in a hybrid model. The study uses the theoretical lens of stimulus-organism-response (SOR) and dual factor theory (DFT). It examines the influence of health consciousness (stimulus), facilitators (e.g. work flexibility, work–life balance and team building) (organism) and barriers (e.g. pandemic and travel stressor and role overload [organism] on employees’ preference to work in a hybrid model) (response). Further, it tests the moderating influence of organizational culture.

A questionnaire survey was conducted among employees in India, Sri Lanka and Germany, obtaining 281 usable questionnaires. Structural equation modeling (SEM) using Warp PLS 7.0 was used as the analytical technique to examine the model fit and test hypotheses.

The findings reveal that health consciousness is essential in enhancing facilitators and motivating employees to prefer a hybrid working model. The study’s findings also prove the positive influence of work flexibility, work–life balance and team building as facilitators. The results suggest that pandemic and travel stressors inhibit employees’ preference for working in a hybrid model.

The study is based on a cross-sectional research design to generalise the findings. Future researchers can utilize longitudinal design to decipher the variation in response over time. The study has developed a model combining SOR with DFT; the authors suggest that future researchers use other theories in combination with SOR, like self-determination theory (SDT), to decipher the influence of intrinsic and extrinsic motivation of employees in the context of the hybrid working model.

This study identifies the need for open communication with the employees to overcome their concerns regarding the hybrid working model. The study also suggests that human resource (HR) managers need to prioritize the task that needs to be accomplished from the office versus working from home. The authors recommend various measures, like water cooler breaks and a buddy system, to motivate employees to work in a hybrid model.

This study is among the first studies focused on the hybrid working model. The current study adds to the limited literature on the facilitators and barriers of working in a hybrid work model.

The paper aims to find the preferences of different tourist type. Since, COVID-19 pandemic has brought the international hospitality industry to a standstill, there are some early signs of recovery. For this industry’s long-term recovery, the tourists’ changing preferences need to be analyzed. Moreover, with different types of tourists, a more nuanced and in-depth study is required to analyze the preferences of each tourist type.

The research focuses on the changing preferences of the tourist by comparatively analyzing the pre-COVID-19 and current COVID-19 phase. The study extracted online data from TripAdvisor and identified themes by applying Latent Dirichlet Allocation (LDA).

The study’s findings confirmed the change in preferences of the different types of tourists during the COVID-19 pandemic by performing thematic analysis. New themes emerged in the pandemic phase, providing more insights into tourists’ changing preferences in the current COVID-19 phase. The study also found that specific dominant themes in the pre-COVID-19 phase were replaced by new themes in the current COVID-19 phase.

To the best of the authors’ knowledge, this study is the first to compare the pre-COVID-19 and current COVID-19 phase themes to decipher the new themes that managers of the hotels should consider to win back tourists’ confidence during the pandemic. The unraveling of changing preferences of the different tourist types in the current COVID-19 pandemic is the novel contribution of the study.

在 COVID-19 大流行期间改变游客对酒店业的偏好

COVID-19 大流行使国际酒店业陷入停顿。虽然有一些复苏的早期迹象, 但对于这个行业的长期复苏, 还需要分析游客不断变化的偏好。此外, 针对不同类型的游客, 需要进行更细致和深入的研究来分析每种游客类型的偏好。

该研究通过比较分析 COVID-19 之前和当前 COVID-19 阶段, 重点关注游客不断变化的偏好。该研究从 TripAdvisor 提取在线数据, 并通过应用隐含狄利克雷分布 (LDA) 确定主题。

该研究的调查结果通过进行主题分析证实了不同类型游客在 COVID-19 大流行期间偏好的变化。大流行阶段出现了新主题, 为游客在当前 COVID-19 阶段不断变化的偏好提供了更多见解。该研究还发现, COVID-19之前阶段的特定主导主题被当前 COVID-19 阶段的新主题所取代。

该研究首次比较了 COVID-19 之前和当前 COVID-19 阶段的主题, 从而为酒店管理者在大流行期间赢回游客的信心提供了应该考虑的新主题。研究发现在当前的 COVID-19 大流行中不同游客类型的偏好的变化是该研究的新贡献。

Massive open online courses (MOOCs) are among the most recent e-learning initiatives to gain widespread acceptance among universities. However, despite MOOCs' “much-documented” benefits, many questions are being raised late regarding the long-term sustainability of the open online teaching e-learning model. With high dropout rates in MOOCs courses, recent research has focused on the challenges limiting MOOCs’ growth. But most of the research is directed toward students’ perspectives, leaving the instructors’ perspective. One of the most important aspects of instructors’ perspective is the motivation for MOOCs' development and delivery.

The present study collected the data from 25 MOOC developers of Indian origin. To prioritize or rank the motivational factor behind developing a MOOC, a fuzzy-analytical hierarchical process (F-AHP) technique was applied to the data set. The primary motivational factors considered for the study were professional development, altruism, personal development, institutional development, intrigue, monetary benefits and peer influence.

The results showed that professional development and personal development are two prime motives that drive MOOCs development. Monetary benefits and peer influence were the least important factors among all the factors considered for the study.

Previous studies have identified and modeled the motivational factors that contribute toward developing MOOCs. However, there was little knowledge about the hierarchy among the motivating factors. The present study fills this gap by establishing the ranking of motivational factors responsible for MOOCs development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0205.

Gig workers form the backbone of any crowdsourcing platform where they showcase their talent and choose a job of their choice and freedom. The study explores the role of information quality (IQ) and social-mediated dialogue (SMD) in evaluating gig worker engagement and productivity on crowdsourcing platforms. The authors also propose to understand how gig worker productivity could be improved under the moderating effect of game elements.

A conceptual model was developed and empirically tested by integrating media richness theory and dialogic public relation theory. Data were collected from gig workers that are involved in crowdsourcing activities for the past three years. An overall sample of 346 gig workers contributing to at least one of the crowdsourcing platforms was collected. The authors tested the hypotheses using Warp PLS 7.0. Warp PLS 7.0 uses partial least square (PLS) structured equation modeling (SEM) and has been used widely to test path analytical models.

Results reveal that the information quality plays an essential role in the SMD, thereby fostering gig workers' productivity and engagement, which could be improved in the presence of game elements due to their nature of supporting rewards. However, engagement in the platform leading to improved productivity was not supported.

The study lays practical foundations for crowdsourcing platforms as it sets the importance of both IQ and dialogic communication channels. The two-way communication between gig workers and the platforms via accurate, timely, valuable and reliable information forms the key to the task's success. The introduction of the right game element will help to achieve better engagement and productivity.

This study also offers a new dimension to media richness theory and dialogic public relation theory in crowdsourcing platforms. The results would help platform designers and gig employers understand gig workers' quality and performance in a platform economy. The study uniquely positions itself in the area of crowdsourcing platforms by using game elements.

The high rate of internet penetration has led to the proliferation of social media (SM) use, even at the workplace, including academia. This research attempts to develop a topology and thereby determine the dominant use motive for faculty’s use of SM.

In this two-part study, a two-stage research design has been adopted for topology development based on the application of Uses and Gratifications Theory. In the second part, the Technology Acceptance Model is applied to discern the dominant motive for SM use in academia.

The work is able to develop a seven-item topology, conforming to the basic three use motives, namely, hedonic, utilitarian and social. The work shows faculty attach more value to the instrumental utility of SM, while the hedonic function is also significant.

Discerning dominant motive implies that SM use at the workplace should not be banned, rather effective regulated use will instil the faculty to enhance work outcomes. The conceptualisation of topology for SM use in academia at the workplace can aid in designing an effective organisation policy, and design of an internal SM platform.

The study is unique towards topology development for academic faculty and has many important implications for management and academia, especially towards policy design for SM use at the workplace.

The healthcare sector in India is witnessing phenomenal growth, such that by the year 2022, it will be a market worth trillions of INR. Increase in income levels, awareness regarding personal health, the occurrence of lifestyle diseases, better insurance policies, low-cost healthcare services, and the emergence of newer technologies like telemedicine are driving this sector to new heights. Abundant quantities of healthcare data are being accumulated each day, which is difficult to analyze using traditional statistical and analytical tools, calling for the application of Big Data Analytics in the healthcare sector. Through provision of evidence-based decision-making and actions across healthcare networks, Big Data Analytics equips the sector with the ability to analyze a wide variety of data. Big Data Analytics includes both predictive and descriptive analytics. At present, about half of the healthcare organizations have adopted an analytical approach to decision-making, while a quarter of these firms are experienced in its application. This implies the lack of understanding prevalent in healthcare sector toward the value and the managerial, economic, and strategic impact of Big Data Analytics. In this context, this chapter on “Predictive Analytics in Healthcare” discusses sources, areas of application, possible future areas, advantages and limitations of the application of predictive Big Data Analytics in healthcare.