Search results

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

This paper argues that when incumbent firms counter disruptive threats head-on, they may fail to develop the required new skills. This paper aims to propose an adjacent strategy which proved useful to Fujifilm to counter disruption of its core business of manufacturing photographic film.

The study uses an inductive methodology. Based on a detailed case study of Fujifilm, the study proposes two frameworks: for the conditions under which an adjacent strategy is likely to be fruitful and how firms can make the strategy work in their organizations.

The study finds that an adjacent strategy can be useful to firms under specific circumstances. Not only will the strategy help to counter decline in the core business, but it will also open up new avenues of growth. The success of the strategy requires significant efforts in aligning the leadership and the organization, however.

The frameworks proposed in the study can be useful to incumbent firms in many industries as they battle new disruptive business models and players.

The study’s key argument that incumbent firms can leverage skills from their core business is novel. The study also proposes frameworks that can help firms decide whether an adjacent strategy is appropriate for them and how they can implement it.

This study aims at understanding how higher education institutions (HEIs) can contribute to sustainable development, by designing their programmes for bringing about a transformative impact on communities and students, and also to examine what alternative pedagogical approaches could be used for that. In the past decades, HEIs have increasingly created social innovation (SI) programmes, as a way to achieve United Nations Sustainable Development Goals. These community-oriented and field-based programmes are difficult to ally with conventional classroom education. This study explores how these programmes could integrate the participatory approach and what would be the benefits. It also investigates the effectiveness of the experiential learning approach for teaching sustainability.

A case study method is used to document SI projects initiated by an HEI programme in rural India.

It was found that the participatory approach contributes to empowering communities and also benefits the students in terms of academic, professional and personal growth. Empirical findings show that experiential learning is an efficient method to teach sustainability. Ultimately, both pedagogical approaches are found to be mutually beneficial.

This study fills a gap in the literature, by providing empirical evidence on how HEI can implement innovative educational strategies such as participatory approach and experiential learning in their programmes towards teaching sustainability. A conceptual model for HEI interested in developing similar programmes is also proposed. To the best of the authors’ knowledge, this study is one of the first studies focusing on the context of Indian HEI.

Religious tourism is one of the oldest and fastest-growing segments. This study analyzes religious tourism through the pilgrimage of Muslims to the holy city of Mecca and has the following objectives: (1) establish the motivational dimensions of religious tourism; (2) identify the motivational dimensions that predict the satisfaction of religious tourism and (3) determine the motivational dimensions that predict return, recommend and say positive things about religious tourism applied to the pilgrimage to a sacred city.

The sample consisted of Muslim pilgrims who had visited Mecca. The sample was collected in Bahrain, a country located on the Persian Gulf, where most of its population is Muslim. A total of 380 valid questionnaires were obtained online. For the data analysis, factorial analysis and the multiple regression method enter were performed.

The results show that religious motivations are more important when visiting a sacred city than secular ones. Three motivational dimensions were found: religious, social and cultural and shopping. The three dimensions found have a significant relationship with satisfaction and loyalty. Likewise, it was found that the religious motivational dimension is the factor that most predicts satisfaction and loyalty in the behavior of religious visits to a sacred city.

The main limitation of the present study was the temporality in which the sample was taken because the demand may vary at another time of the year and therefore vary its results.

The authors of the study recommend that holy cities increase the religious motivations of these travelers by periodically researching their needs and organizing services to suit their desired spiritual experience. Also, to improve the social and cultural part, travel agencies and tourist companies to Mecca should promote social and cultural motivation among travelers in an appropriate way by providing service packages that involve visits to cultural and social sites such as museums and cultural centers.

This research will serve as a management guide for public institutions and private companies to develop more efficient planning in religious destinations and sacred cities.

This study is the first to analyze the construct of motivations in the pilgrimage to the city of Mecca, to then establish what the main motivations are that predict satisfaction and loyalty in a religious city. Thus, its results provide important information for tourist destination managers and tourism service providers.

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

This study aims to enhance the knowledge by offering perspectives from an emerging market by reviewing the existing literature on food tourism. This study applies a multimethod analysis, providing insights into the advancement of food tourism in India, the contributions, critical findings and emerging research themes.

The study adopted a multimethod analysis using descriptive, narrative and bibliometric analysis using VOSviewer to analyze research papers published on food tourism in India shortlisted from Scopus and Google Scholar.

Future research should focus on gauging the potential of food tourism in different regions of the country, applying theoretical frameworks that have not been used. “Culinary Diversity and Heritage,” “Sustainable and Responsible Food Tourism,” “Consumer Behavior and Food Tourism Experiences,” “Rural Development and Economic Impact,” “Technology and Digitalization,” “Stakeholder Collaboration,” “Food Safety and Hygiene” and “Policy and Regulation” were the identified future research themes. These findings are significant for emerging economies across the globe.

This study summarized the progress of food tourism research in India, the contributions and emerging themes, supplementing the need to study food tourism in India. This study contributed methodologically to the literature by adopting a multimethod review combining descriptive, narrative and bibliometric analysis. Finally, by proposing ideas and constructs for future research, this study provides directions for future food tourism research from an emerging market’s perspective.

Findings will assist managers and stakeholders in comprehending the factors influencing tourists, destination marketing and branding, aiding in effective planning and executing food tourism strategies to promote destinations. The identified themes and keywords can help academicians and researchers dwell upon the emerging research themes in food tourism.

To the best of the author’s knowledge, this is the first study analyzing food tourism research in India adopting a multimethod analysis. The study provides an in-depth analysis applying descriptive, narrative and bibliometric analysis, highlighting the critical trends and research themes. A framework for future studies was also proposed.

该研究旨在通过回顾有关美食旅游的现有文献, 提供来自新兴市场的观点, 从而强化现有的知识。本研究采用多方法分析, 深入了解印度美食旅游的发展、贡献、重要发现和新兴研究主题。

该研究采用了多种方法分析, 使用 VOSviewer 进行描述性、叙述性和文献计量分析, 以分析从 Scopus 和谷歌学术搜索中入围的关于印度美食旅游的研究论文。

未来的研究应侧重于衡量该国不同地区美食旅游的潜力, 应用尚未使用的理论框架。 “烹饪多样性和传统”、“可持续和负责任的美食旅游”、“消费者行为和美食旅游体验”、“农村发展和经济影响”、“技术和数字化”、“利益相关者协作”、“食品安全和卫生”, “政策与法规”是确定的未来研究主题。这些发现对全球新兴经济体具有重要意义。

本研究总结了印度美食旅游研究的进展、贡献和新兴主题, 补充了研究印度美食旅游的必要性。本研究采用结合描述性、叙述性和文献计量分析的多方法回顾, 在方法论上为文献做出了贡献。最后, 通过提出未来研究的思路和结构, 本研究从新兴市场的角度为未来的美食旅游研究提供了方向。

调查结果将帮助管理者和利益相关者理解影响游客、目的地营销和品牌的因素, 帮助有效规划和执行食品旅游战略以促进目的地。 确定的主题和关键词可以帮助院士和研究人员深入研究食品旅游中新兴的研究主题。

El estudio tiene como objetivo mejorar el conocimiento al ofrecer perspectivas de un mercado emergente mediante la revisión de la literatura existente sobre turismo gastronómico. Este estudio aplica un análisis de múltiples métodos, que proporciona información sobre el avance del turismo gastronómico en la India, las contribuciones, los hallazgos críticos y los temas de investigación emergentes.

El estudio adoptó un análisis multimétodo mediante un análisis descriptivo, narrativo y bibliométrico utilizando VOSviewer para analizar los artículos de investigación publicados sobre el turismo gastronómico en la India preseleccionados de Scopus y Google Scholar.

La investigación futura debería centrarse en calibrar el potencial del turismo gastronómico en las distintas regiones del país, aplicando marcos teóricos que no se han utilizado. “Diversidad culinaria y patrimonio”, “Turismo gastronómico sostenible y responsable”, “Comportamiento del consumidor y experiencias de turismo gastronómico”, “Desarrollo rural e impacto económico”, “Tecnología y digitalización”, “Colaboración de las partes interesadas”, “Seguridad e higiene alimentaria”, “Política y regulación” fueron los temas de investigación futura identificados. Estos hallazgos son significativos para las economías emergentes de todo el mundo.

Este estudio resumió el progreso de la investigación sobre turismo alimentario en la India, las contribuciones y los temas emergentes, complementando la necesidad de estudiar el turismo alimentario en la India. Este estudio contribuyó metodológicamente a la bibliografía al adoptar una revisión multimétodo que combina el análisis descriptivo, narrativo y bibliométrico. Por último, al proponer ideas y constructos para futuras investigaciones, este estudio proporciona orientaciones para futuras investigaciones sobre el turismo gastronómico desde la perspectiva de un mercado emergente.

Los resultados ayudarán a los gestores y a las partes interesadas a comprender los factores que influyen en los turistas, el marketing de los destinos y la creación de marcas, contribuyendo a una planificación y ejecución eficaces de las estrategias de turismo gastronómico para promocionar los destinos. Los temas y palabras clave identificados pueden ayudar a los académicos e investigadores a profundizar en los temas de investigación emergentes en el turismo gastronómico.

Se trata del primer estudio que analiza la investigación sobre turismo gastronómico en la India adoptando un análisis multimétodo. El estudio proporciona un análisis en profundidad aplicando un análisis descriptivo, narrativo y bibliométrico, destacando las tendencias críticas y los temas de investigación. También se propone un marco para futuros estudios.