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There is a lack of understanding in the literature on the relation between parks and house price in relation to crime in Scandinavian context. This paper aims to investigate the effect of the amenity value of accessibility to parks on apartment prices with reference to crime rates in parks in Stockholm.

This paper analyses the effects of park proximity and crime in parks on apartment prices by using geographic information systems and hedonic modelling.

Findings show that the proximity of parks as an environmental amenity has an effect on apartment prices. The results also demonstrate that the impact of parks on apartment prices is different in the different segments of the apartment market in Stockholm. Moreover, various types of parks may differ in their impact, for instance, grass parks and park blocks are more desirable in Stockholm than landscape parks and neighbourhood parks. The effects of crimes in parks influence apartment prices negatively.

This paper provides a new methodology by using the shortest distance to a park as a main variable. The shortest distance to a park variable is considered a better choice than using park as an aggregate measure. To the best of the author’s knowledge, this is the first study that investigates the effect of specific park types, for instance, grass parks, neighbourhood parks, landscape parks and park blocks, in Stockholm housing market.

In light of the widely acknowledged significance of GHRM practices, this study improves comprehension pertaining to GHRM practices and employee workplace outcome relationships. Drawing on the conservation of resource (COR) theory, the association between GHRM practices and employee workplace outcomes, namely green commitment and thriving at work, was explored, with a specific focus on the mediating role of organizational pride.

A quantitative research design was adopted, and data was collected through a multistage sampling technique, yielding a sample of 255 employees working in six textile manufacturing organizations in Pakistan, all of which held the ISO 14001 certification. The model was tested using Partial Least Square Structural Equation Modeling (PLS-SEM).

The findings of this study reveal a significant link between GHRM practices and organizational pride. Moreover, organizational pride was found to mediate the relationship between GHRM practices and thriving at work while partially mediating the relationship between GHRM practices and green commitment.

The outcomes of this study have implications for organizations seeking to enhance sustainability and employee well-being by adopting GHRM practices. Specifically, fostering a sense of organizational pride can further enhance thriving at work and green commitment among employees.

The findings contribute to the existing literature by highlighting the positive impact of GHRM practices on employee workplace outcomes and the importance of organizational pride as a mediating mechanism.

Sharing and obtaining information over social media has enabled people to express their opinions regarding any event. Since the tweets regarding the Russia-Ukraine war were extensively publicized on social media, this study aims to analyse the temporal sentiments people express through tweets related to the war.

Relevant hashtag related to the Russia-Ukraine war was identified, and tweets were downloaded using Twitter API, which were later migrated to Orange Data mining software. Pre-processing techniques like transformation, tokenization, and filtering were applied to the extracted tweets. VADER (Valence Aware Dictionary for Sentiment Reasoning) sentiment analysis module of Orange software was used to categorize tweets into positive, negative and neutral ones based on the tweet polarity. For ascertaining the key and co-occurring terms and phrases in tweets and also to visualize the keyword clusters, VOSviewer, a data visualization software, was made use of.

An increase in the number of tweets is witnessed in the initial days, while a decline is observed over time. Most tweets are negative in nature, followed by positive and neutral ones. It is also ascertained that tweets from verified accounts are more impactful than unverified ones. russiaukrainewar, ukraine, russia, false, war, nato, zelensky and stoprussia are the dominant co-occurring keywords. Ukraine, Russia and Putin are the top hashtags for sentiment representation. India, the USA and the UK contribute the highest tweets.

The study tries to explore the public sentiments expressed over Twitter related to Russia-Ukraine war.