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A wetland is a place of tourist attraction, and tourism values play a key role in economic development. Among various services provided by a wetland, recreational services are increasingly valuable in the tourism sector. This paper aims to unfold the potential recreational values of the Dal Lake in Jammu and Kashmir, India.

The study uses individual travel cost methods (TCMs) and assesses its impact on regional development in terms of income and employment generation. A sample of 200 tourists is selected through an on-site survey on Dal Lake, and the demand for recreational visits and its value is estimated by employing the truncated Poisson regression model (TPRM) and un-truncated Poisson regression model (UTPRM). The consumers' surplus is estimated and tourists' benefit to visiting the wetland is explored.

On average, estimated consumers' surplus per visitor is Rs 6,250 (US$96.15) and Rs 25,000 (US$384.61) from respective models. The annual total recreational value of the lake is accounted for Rs 1713m (US$ 26m). This high consumer surplus (CS) and recreational values of the lake indicate large demand for its recreational facilities.

The study is based on primary data and thus, is original. The paper has implications for the policymakers to formulate sustainable management plans for the proper use of Dal Lake and tourism development.

According to Yubin et al. (2023), films serve as a medium for conveying visual representations of various elements such as landscapes, buildings, landmarks and monuments, which provide a contextual backdrop for the narrative. According to Vila et al. (2021), the number of global tourists visiting film locations exceeds 80 million. In addition, according to Yubin et al. (2023), the promotion of tourism is facilitated through the utilisation of films, which serve to create novel representations, counteract negative perceptions and enhance the portrayal of underdeveloped destinations. A significant number of individuals engage in the practise of visiting movie sets with the intention of re-experiencing the emotional impact of the film. The devaluation of film marketing has been observed. This method represents a highly indirect approach to enticing tourists. This chapter examines the comprehension of travellers' motivations and the perception of film-exposed locations in Bollywood films (Salnick, 2023). Film tourism provides a tailored and personalised experience for individuals. The difficulty in measuring this concept arises from factors such as the emotional responsiveness, personality traits, background and interpretive abilities of the viewers in relation to media images. According to Castro et al. (2023), the inclusion of a destination on a screen can serve as a means to enhance the diversity of a site's tourist offerings or mitigate the effects of seasonality by providing opportunities for experiential activities, showcasing notable landmarks or serving as a filming location. Film destinations have the potential to gain popularity and benefit from advertising and the perception of spectators.

This study aims to examine the relationship between the perceptions of local residents concerning political factors and support for tourism development in the Kashmir region.

Primary data have been collected (n = 650) from the residents of the top five tourist destinations (Pahalgam, Gulmarg, Srinagar, Sonamarg and Kokernag) through a pre-tested questionnaire by multistage sampling method. In presence of non-normal data, the partial least squares structural equation model is applied for analysis. The study is based on the theoretical framework of social exchange theory (SET) and institutional theory of political trust (ITPT).

Results suggest that trust in government, the perceived economic performance of government and level of power are negative determinants of support for tourism development, which nullifies SET for politically disturbed regions.

The results of this study are useful for the local government and tourism institutions in policy formation and fill the vast gap in tourism literature with a theoretical base. This study is also an addition to the existing literature on city tourism for the politically disturbed region.

The study aims to investigate the effect of four customer relationship management (CRM) dimensions, namely, customer orientation, customer relationship management organization, managing knowledge and CRM based technology, on customer satisfaction in the hospitality sector of Kashmir.

A survey instrument with a slight modification is adapted from literature and is exercised on the customers of three- and four-star hotels operating in Kashmir. A total of 176 responses received using systematic random sampling were subjected to exploratory factor and regression analyses to uncover the underlying relationships among dependent and independent variables.

The results revealed a significant and positive relationship between CRM dimensions, namely, customer orientation, managing knowledge and CRM organization on customer satisfaction. Though the results also indicate a significant positive effect of CRM-based technology on customer satisfaction, the magnitude of this effect is very weak. This suggests that hotel organizations use technology as a mere tool to store customer information only. Thus, CRM-based technology should be used by the hotels to analyze customer information and, subsequently, design customized products. This will unravel the full potential of the technology and lead to better customer satisfaction.

The findings of this study provide significant insights to the practitioners to understand the role of successfully implementing a CRM strategy. It reflects that establishing an effective CRM strategy helps managers in improving customer satisfaction and in maintaining a long-term relationship with customers to achieve the organizational goals. Thus, establishing an efficient and effective CRM strategy should be (one of) the key objectives for all hotel managers. Moreover, the hotels that successfully implement CRM strategy and manage customer knowledge properly will reap the rewards in terms of better customer loyalty and long-term sustainable profitability.

This study approaches the implementation of CRM strategy from a customer perspective with a specific focus on investigating the effect of four CRM dimensions on customer satisfaction in the hospitality sector. This will provide a novel impetus to the hotel managers to devise and manage a CRM strategy that leads to (better) customer satisfaction.

The purpose of this paper is to contribute to the nascent literature on the use of the internet in destination image formation by exploring India's online image through consumer queries posted on travel message boards.

The paper uses netnography, which is ethnography applied to the internet and is a qualitative method.

The paper finds that consumers are not only perceivers of destination image information but actively construct and share their own images via the internet. India is appreciated for its natural resources, culture, history and art but huge dissatisfaction is expressed for general and tourist infrastructure.

With consumers sharing both positive and negative aspects of a destination online, destination marketing organizations will increasingly find their “picture postcard” images being contested.

Traditionally internet based travel studies have focused on supply side sources. This paper illustrates that with the internet, consumers can and do easily share their complex images with other consumers.

The purpose of this study is to determine the contamination level in natural water resources because the tremendous development in the agriculture sector has increased the amount of contamination in natural water sources. Hence, the water is polluted and unsafe to drink.

Three types of sensor arrays were suggested: parallel, star and delta. The simulation of all types of sensor array was carried out to calculate the sensors’ impedance value, capacitance and inductance during their operation to determine the best sensor array. The contamination state was simulated by altering the electrical properties values of the environmental domain of the model to represent water contamination.

The simulation results show that all types of sensor array are sensitive to conductivity, σ, and permittivity, ɛ (i.e. contaminated water). Furthermore, a set of experiments was conducted to determine the relationship between the sensor’s impedance and the water’s nitrate and sulphate contamination. The performance of the system was observed where the sensors were tested, with the addition of distilled water with different concentrations of potassium nitrate and potassium sulphate. The sensitivity of the developed sensors was evaluated and the best sensor was selected.

Based on the outcomes of the experiments, the star sensor array has the highest sensitivity and can be used to measure nitrate and sulphate contaminations in water.

The star sensor array presented in this paper has the potential to be used as a useful low-cost tool for water source monitoring.

The dynamic yet volatile nature of tourism and travel industry in a competitive environment calls for enhanced marketing intelligence and analytics, especially for those entities with limited marketing budgets. The past decade has witnessed an increased use of user-generated content (UGC) analysis as a marketing tool to make better informed decisions. Likewise, textual data analysis of UGC has gained much attention among tourism and hospitality scholars. Nonetheless, most of the scholarly works have focused on the singular application of an existing method or technique rather than using a multi-method approach. The purpose of this study is to propose a novel Web analytics methodology to examine online reviews posted by tourists in real time and assist decision-makers tasked with marketing strategy and intelligence.

For illustration, the case of tourism campaign in India was undertaken. A total of 305,298 reviews were collected, and after filtering, 276,154 reviews were qualified for analysis using a string of models. Descriptive charts, sentiment analysis, clustering, topic modeling and machine learning algorithms for real-time classification were applied.

Using big data from TripAdvisor, a total of 145 tourist destinations were clustered based on tourists’ perceptions. Further exploration of each cluster through topic modeling was conducted, which revealed interesting insights into satisfiers and dissatisfiers of different clusters of destinations. The results supported the use of the proposed multi-method Web-analytics approach.

The proposed machine learning model demonstrated that it could provide real-time information on the sentiments in each incoming review about a destination. This information might be useful for taking timely action for improvisation or controlling a service situation.

In terms of Web-analytics and UGC, a comprehensive analytical model to perform an end-to-end understanding of tourist behavior patterns and offer the potential for real-time interpretation is rarely proposed. The current study not only proposes such a model but also offers empirical evidence for a successful application. It contributes to the literature by providing scholars interested in textual analytics a step-by-step guide to implement a multi-method approach.