Purpose This paper aims to examine travelers` behavioral intention of traveling in the period of coronavirus by employing the theory of planned behavior. The framework incorporates attitude, subjective norms, perceived behavioral control and a very crucial construct, i.e. perceived risk, as per the current critical scenario of COVID-19. Design/methodology/approach Data was collected using a survey instrument on the internet by posting the questionnaire link over social network web pages of online traveling websites. The data was analyzed using structural equations modeling with AMOS 22.0 and SPSS software, and the proposed hypotheses were statistically tested. The sample under consideration constitutes 417 responses. Findings Empirical findings suggest that attitude, perceived behavioral control and perceived risk are significant for predicting behavioral intention while subjective norms do not. And these variables explained about 35 percent of the variance in behavioral intention of traveling in the period of coronavirus. Research limitations/implications This study can benefit travelers, tourism and hospitality industry, governments, aviation industry and other relevant organizations as this paper offers the latest updates and essential information regarding traveler`s intention of traveling in the period of coronavirus. The study mainly focuses on India, so the generalizations of results to other countries are unwanted. Originality/value The primary value of this paper is that it tested the theory of planned behavior by incorporating perceived risk in the context of COVID-19. To the best of authors’ knowledge, in Indian context, there is no study which has tested the TPB by adding perceived risk in explaining the Indian citizens’ behavioral intention of traveling in the period of Coronavirus.

PurposeThis study examines the economic crisis caused by coronavirus on the global tourism industry in general and the Indian tourism industry in particular. This paper highlights the strategies that tourism companies should implement in times of crisis to reduce the negative impact. It also discovers the business opportunities which can be offered amid this deadly pandemic.Design/methodology/approachThe study is based on a systematic literature review. The literature has been explored by utilizing the keywords “economic crises,” “coronavirus,” “Indian tourism industry,” “Global tourism industry” on the three most popular databases namely Scopus, Web of Science and Google Scholar. In this study, statistics, current events, published research papers and a synthesis of news transmitted by various media sources were used to assess the economic crisis caused by coronavirus.FindingsThe obtained findings demonstrate that coronavirus severely affected the economy of the world and India. The pandemic has hit the economies that are dependent on tourism the worst. These countries are expected to bear the brunt of the crisis's consequences for longer than other economies. This coronavirus outbreak indicates that the tourism industry was unprepared to deal with such a pandemic, which affected and crippled the economy.Research limitations/implicationsThis study demonstrates economic crisis, management strategies and business opportunities during any crisis, chaos and disaster, in addition to its academic contribution to the existing body of the literature. Policymakers and industry practitioners might be offered suggestions based on the findings of current study to design futuristic strategies for better economic crisis management. The data given in this study is timely because taking an exact idea of tourism losses through the data is difficult, as the data changes as quickly as the virus spreads.Originality/valueThis paper forms its originality by concentrating on the aspects of economic crisis, strategies to mitigate the negative impact of coronavirus on the tourism economy and detailing the business opportunities which these crises can offer. This paper provides an evaluation of the current status of the tourism economy of the world and India as well.

PurposeThis study used an integrated framework that incorporates the technology acceptance model (TAM) (Davis, 1989), the theory of planned behavior (TPB) (Ajzen, 1991) and trust to examine factors that mainly influence consumers' intention towards the use of smart technologies in tourism and hospitality (T&H) industry. The Internet of things (IoT), artificial intelligence (AI), virtual reality systems, augmented reality systems, etc. are the Smart 4.0 technologies generally used in T&H industry these days.Design/methodology/approachConvenience sampling approach was employed in this study. Data were collected over the Internet using a survey instrument by posting the questionnaire link on social network web pages of travel agencies from November 10, 2021, to December 30, 2021. In the opening statement of the questionnaire, we have explained about the Smart 4.0 technologies so that every respondent could understand what we mean by Smart 4.0 technologies.FindingsThe findings show that conjoining the TAM and the TPB with trust resulted in a robust model for explaining customers' intention toward using smart technologies in the T&H industry.Research limitations/implicationsSmart technologies have become one of the most profitable e-commerce applications. This study examines and integrates the various advantages of smart technologies for the consumers in T&H industry, as well as providing insight into the intentions of Indian consumers. Hence, this study gives significant information to IT companies, online travel agencies, tour operators, travel agents, T&H planners and other stakeholders on Indian consumers' behavioral intentions (BIs).Originality/valueThis study tested the utility of the extended model in predicting consumers' intention towards the use of smart technologies in T&H industry. As far as the authors' knowledge is concerned, this is the first study that predicted intention of Indian consumers towards the use of smart technologies in T&H industry by integrating TAM, TPB and trust.

PurposeIn 2019, Generation Z (Gen Z) accounted for 32% of the world population, as per the report by Bloomberg, Gen Z in India is world's largest with 472 million people, still there is very limited research conducted to explain their intention to visit heritage sites. This paper aims to report the findings of an empirical research focussing on Gen Z Indians' intention to visit heritage sites by applying theory of planned behaviour (TPB) with two additional constructs, i.e. environmental concern (EC) and environmental friendly activities (EFA).Design/methodology/approachAs a fundamental theoretical framework, the TPB model is used. Data consists of responses of 434 Gen Z Indians which were collected through online questionnaires. Using structural equation modelling (SEM) technique, the measurement and structural model were tested with the help of AMOS 22 and SPSS 25 software.FindingsThe results of SEM indicate that the hypothesized relationships between attitude (AT), subjective norms (SN), EC, EFA and intention to visit heritage sites were all supported. However, perceived behavioural control (PBC) did not influence intention.Research limitations/implicationsThe study's findings have substantial practical implications for organizations/travel companies that primarily deal in heritage sites. The findings of this study contribute to the body of knowledge about intention to visit heritage sites. As the study focuses mostly on Gene Z Indians, it is difficult to extrapolate the findings to other countries.Originality/valueThis paper will help the researchers and practitioners to understand the Gen Z Indians' intention of visiting heritage sites. To the best of the authors' knowledge, this is the first study that predicts intention of Gen Z Indians to visit heritage sites.

One new ceramide (=long‐chain base linked to a fatty acid via an amide bond), tanacetamide D (1), was isolated from Tanacetum artemisioides. Besides this, the two known constituents 5‐demethylnobiletin (2) and 5‐hydroxy‐3,6,7,8,3′,4′‐hexamethoxyflavone (3) were isolated for the first time from this species. The structure elucidation of the isolated compounds were based primarily on 2D‐NMR techniques including correlation spectroscopy (COSY), heteronuclear multiple‐quantum coherence (HMQC), heteronuclear multiple‐bond correlation (HMBC), and nuclear Overhauser effect spectroscopy (NOESY) experiments.