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A study is performed on the properties of jute-pineapple leaf fiber (PALF) blended yarn and 100% jute yarn. The jute-PALF blend ratios of two counts of yarn (5 and 7 lbs/spy) are 70:30 and 80:20 respectively. The physical properties of the blended yarns such as load at break, strain at break, tenacity at break, tensile modulus and quality ratio are tested and measured. It is observed from the test results that the physical properties of the blended yarns are better than those of the 100% jute yarn. The experimental results also show that the physical and structural properties of the blended yarn changes with the increase of PALF in the blend ratio. So the blending of PALF has a positive impact on yarn properties. Another study is done, in which it is found that surface appearance properties like color strength (K/S value) and whiteness, yellowness and brightness indices of the blended yarns are almost the same as those of the jute yarn due to the blending of jute-PALF. Therefore, the blending ratio does not cause any notable changes in the natural color of the jute yarn.

Doubling farming households’ income through occupational diversification to the non-farm sector has been advocated to be of paramount importance in an agrarian economy such as India. The purpose of this paper is to analyse the effects of non-farm activities on rural household incomes in four different Indian states by using a propensity score matching technique and developing an endogenous switching model.

The research is based on secondary data taken from four quinquennial rounds of employment and unemployment surveys conducted by the National Sample Survey Organization.

The matching results indicate a maximum monthly rise in per capita income of Rs. 60 in Gujarat and a minimum increase of Rs. 18 in Rajasthan among rural households employed in the non-farm sector as compared to the farm sector. The findings confirm that rural non-farm structural diversification cannot be viewed as a blueprint for increasing rural household incomes in different states. Further, it suggests the need to segmenting the different states on the basis of agricultural development for increasing rural incomes.

The study argues that Indian states with a strongly developed farm sector i.e. Gujarat and Punjab are not ideally suited to undergo structural changes in their economic pursuit. The estimates suggest that the transition of rural households from farm to non-farm-sector activities is a very weak strategy in agriculturally developed states of Gujarat and Punjab, whereas non-farm diversification becomes a pivotal strategy for increasing rural household incomes in less agriculturally developed states such as Rajasthan and Uttar Pradesh. A contrasting point that arises from these evidence is that although diversification to the non-farm sector leads to higher income, but the resultant figures are very scanty.

The present study contributes to the existing literature by providing evidence and policy implications on rural non-farm diversification in India and its impact on the rural household income. The study can help the policymakers in framing policies aiming at increasing the income of the rural household through the structural transition of the rural economy.

This study aims to explore factors that influence tourists’ visiting behaviors towards smart tourism destinations (STDs) by extending the theory of planned behavior.

Partial least squares structural equation modeling (PLS-SEM) technique is used to test the proposed hypotheses by analyzing 413 usable responses that are collected through personal interviews. Moreover, data are collected using structured interviews and analyzed by SmartPLS, 3.3.3.

This study results reveal that STD visit intentions significantly influence STD visiting behaviors among international and domestic tourists in Bangladesh. Moreover, the results show that e-attitude, resource efficiency norms and perceived environmental sustainability have significant impacts on STD visit intentions.

The study findings indicate that destinations’ electronic flowcharts of places, usage of low impact and biodegradable materials and history and culture presented in the forms of games and stories increase travelers’ motivation to visit STDs.

The study provides empirical evidence to support the importance of factors enhancing travelers’ STD visiting behaviors by integrating e-attitude, resource efficiency norms, perceived environmental sustainability and STD visit intentions.

研究人員藉著把計劃行為理論伸延開去,去探索是哪些因素影響著到訪智慧旅遊目的地的旅遊行為。

研究人員以偏最小平方法的結構方程模型 (PLS-SEM) 技術去測試其提出之假設,方法是透過分析取自個人訪談413個可用的回應。這些數據均以結構化訪談方式收集,繼而以 SmartPLS 3.3.3 來進行分析。

研究結果顯示,就於孟加拉的國際和國內旅客而言,到訪智慧旅遊目的地的目的,顯著地影響著智慧旅遊目的地的旅遊行為。研究結果亦顯示,到訪智慧旅遊目的地的目的和意願,會顯著地受電子態度、資源效率規範和感知環境可持續性所影響。

研究結果表明了目的地的處所電子流程圖、低影響和能進行生物降解材料的使用,以及以遊戲和故事形式展示的歷史和文化,均會提昇旅客到訪智慧旅遊目的地的動機。

研究人員透過結合電子態度、資源效率規範、感知環境可持續性和到訪智慧旅遊目的地的目的,給我們提供了經驗性證據,以確認增強及完善影響著旅客到訪智慧旅遊目的地的旅遊行為的因素至為重要。

Generative artificial intelligence (GenAI) is one of the most diffused AI technologies, capable of generating manifold forms of content, including music, text, images and synthetic data. The purpose of this study is to analyze the determinants that affect GenAI acceptance and its outcomes on both the explorative and exploitative forms of innovation.

The study employs a conceptual framework based on the technology-organization-environment (TOE) paradigm. Through Smart-PLS analysis, it examines empirical data retrieved from an online survey where 302 manufacturing companies took part.

It is found that GenAI has the potential to facilitate both exploratory and exploitative innovation, particularly via the moderating effect of environmental dynamism. Hence the adoption of GenAI has potential to improve organizational performance.

The study is the first empirical project to investigate factors that influence manufacturing firms' adoption of GenAI. As the first project to have integrated the TOE paradigm when examining the impact of environmental dynamism on exploratory and exploitative innovation, the study emphasizes the double innovation potential of GenAI in organizational performance improvement.