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The purpose of this paper is to investigate the empirical relevance of attribute framing in the financial marketplace.

Incorporating a sample of German initial public offerings (IPOs) from 2010 to 2019, the author uses quantitative methods, including regression models and tests for the equality of means, to analyze whether unsophisticated investors are susceptible to attribute framing and whether this susceptibility reflects irrational behavior.

Unsophisticated investors, who are typically retail investors, are susceptible to attribute framing. They are likely to subscribe to IPOs whose attribute “market valuation” is framed in a positive way, that is, IPOs with low offer prices. As low-priced IPOs are overvalued and underperform in the secondary market relative to high-priced IPOs, the susceptibility to attribute framing reflects irrational behavior. The findings are robust to controlling for sentiment.

Since this paper includes a relatively small sample from a single stock market, future research might employ alternative approaches.

When issuers and underwriters are able to exploit retail investors through attribute framing, the participation of these investors in the financial marketplace may finally decrease. Therefore, the financial literacy of retail investors needs to be improved.

This paper is the first to provide empirical evidence of attribute framing in a financial markets context. While most previous research on IPO offer prices focuses on US stocks, this paper is the first to incorporate German stocks.

This study aims to investigate a systematic approach to the production and use of additively manufactured injection mould inserts in product development (PD) processes. For this purpose, an evaluation of the additive tooling design method (ATDM) is performed.

The evaluation of the ATDM is conducted within student workshops, where students develop products and validate them using AT-prototypes. The evaluation process includes the analysis of work results as well as the use of questionnaires and participant observation.

This study shows that the ATDM can be successfully used to assist in producing and using AT mould inserts to produce valid AT prototypes. As a reference for the implementation of AT in industrial PD, extracts from the work of the student project groups and suitable process parameters for prototype production are presented.

This paper presents the application and evaluation of a method to support AT in PD that has not yet been scientifically evaluated.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

Despite the increasing role of the data warehouse as a supportive decision-making tool in today's business world, academic research for measuring its effectiveness has been lacking. This paucity of academic interest stimulated us to evaluate data warehousing effectiveness in the organizational context of Jordanian banks.

This paper develops a theoretical model specific to the data warehouse system domain that builds on the DeLone and McLean model. The model is empirically tested by means of structural equation modelling applying the partial least squares approach and using data collected in a survey questionnaire from 127 respondents at Jordanian banks.

Empirical data analysis supported that data quality, system quality, user satisfaction, individual benefits and organizational benefits have made strong contributions to data warehousing effectiveness in our organizational data context.

The results provide a better understanding of the data warehouse effectiveness and its importance in enabling the Jordanian banks to be competitive.

This study is indeed one of the first empirical attempts to measure data warehouse system effectiveness and the first of its kind in an emerging country such as Jordan.