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To investigate whether additional information of the permanent news flow, especially reporting intensity, can help to increase transparency in housing markets, this study aims to examine the relationship between news coverage or news sentiment and residential real estate prices in Germany at a regional level.

Using methods in the field of natural language processing, in particular word embeddings and dictionary-based sentiment analyses, the authors derive five different sentiment measures from almost 320,000 news articles of two professional German real estate news providers. These sentiment indicators are used as covariates in a first difference fixed effects regression to investigate the relationship between news coverage or news sentiment and residential real estate prices.

The empirical results suggest that the ascertained news-based indicators have a significant positive relationship with residential real estate prices. It appears that the combination of news coverage and news sentiment proves to be a reliable indicator. Furthermore, the extracted sentiment measures lead residential real estate prices up to two quarters. Finally, the explanatory power increases when regressing on prices for condominiums compared with houses, implying that the indicators may rather reflect investor sentiment.

To the best of the authors’ knowledge, this is the first paper to extract both the news coverage and news sentiment from real estate-related news for regional German housing markets. The approach presented in this study to quantify additional qualitative data from texts is replicable and can be applied to many further research areas on real estate topics.

This paper aims to investigate customer attitude towards the use of emerging social media platforms (SMPs) for promotional activities by United Arab Emirates (UAE)-based Islamic banks, particularly, in the post-COVID-19 era. The key drivers of this research include analysing, anticipating and providing recommendations to reinvigorate the marketing and promotional strategies of the UAE Islamic banks to spark renewed customer interest.

This study is anticipatory and descriptive in nature. Primary data is used to understand customer perception towards the use of emerging social media marketing tools by the UAE-based Islamic banks. Reliability, factor analysis and multiple regression analysis are applied to understand customer attitude. While focusing on the current COVID-19 scenario, the need for innovative structure is envisaged to meet the post-COVID-19 needs.

The findings of this research highlight the significance of emerging SMPs such as WhatsApp, TikTok, Pinterest, Viber, Snapchat and their application as promotional tools to inspire the purchase intention of customers in this virtual age. The results of the study reveal these emerging SMPs are predicted to be used as the preferred promotional tools for Islamic banks.

This paper is limited to the UAE Islamic banks and to a specified set of SMPs as promotional tools. Nevertheless, its findings have important implications that can be extended and validated through studying the post-COVID-19 customer attitude towards other innovative promotional tools used by commercial banks in general and Islamic banks in particular, in the GCC and Middle East and North Africa (MENA) regions.

There is currently limited available research on the innovative social media marketing techniques and promotional strategies. This study is a novel attempt to examine the adoption of the emerging SMPs as promotional tools by the UAE Islamic banks. This paper extends value to the existing studies on the impact of the pandemic on the promotional activities of the UAE Islamic banking industry. Nonetheless, while regionally specific, it is valuable in its potential application to the Islamic banking sector in the entire GCC and MENA region in the post-COVID-19 era.

The internationalization of business has grown the production value chains and created performance challenges for industrial production. Industry 4.0, the digital transformation of industrial processes, promises to deliver performance improvements through smart functionalities. This study investigates how digital transformation translates to performance gain by adopting a systems perspective to drive smartness.

This study uses qualitative research to collect data on the lived experiences of digital transformation practitioners for theory development. It uses semi-structured interviews with industry experts and applies the Gioia methodology for analysis.

The study determined that enterprise smartness is an organizational capability developed by digital transformation, it is a function of integration and the enabler of organizational performance gains in the Industry 4.0 context. The study determined that performance gains are experienced in productivity, sustainability, safety and customer experience, which represents performance metrics for Industry 4.0.

This study contributes a model that inserts smartness in the linkage between digital transformation and organizational outcomes to the digital transformation and production management literature.

The study indicates that digital transformation programs should focus on developing smartness rather than technology implementations, which must be considered an enabling activity.

Existing studies recognized the positive impact of technology on performance in industrial production. The study addresses a missing link in the Industry 4.0 value creation process. It adopts a systems perspective to establish the role of smartness in translating technology use to performance outcomes. Smart capabilities have been the critical missing link in the literature on harnessing digital transformation in organizations. The study advances theory development by contributing an Industry 4.0 value model that establishes a link between digital technologies, smartness and organizational performance.