Search results

Understanding consumer brand relationships from the perspective of the consumer has been a research topic for years. Despite this, there are still various ways in which the construct is interpreted. This paper aims to identify the most typical interpretation of brand relationships by consumers.

A four-study prototype analysis was conducted, in which a bottom-up approach was applied to identify lay people’s conceptualization of consumer brand relationships.

The prototype analysis generates a comprehensive list of features of consumer brand relationships that provide a nuanced understanding of the concept. The most typical characteristics of a brand relationship according to consumers are quality, bond, value and joy. Comparing this relationship prototype with existing literature shows that there may be a gap between theory and practice regarding the concept of brand relationship.

The prototypical conceptualization of brand relationships shows which aspects play a role in consumers' most common interpretation of the construct. This provides an opportunity to assess the validity of existing conceptualizations of brand relationships. Knowing which aspects are most relevant for consumers’ brand relationships allows brands to make adjustments as needed and improve at establishing and maintaining relationships with consumers.

The emerging business partner role of management accountants (MAs) results in an increased requirement of MAs to make business decisions. Frame dependence cognitive biases regularly influence decisions made in conditions of uncertainty, as is the case in business decision-making. Consequently, this study aims to examine susceptibility of MAs to frame dependence bias.

A survey was conducted among an international sample of practising MAs. The proportion of MAs influenced by framing bias was analysed and compared to findings in other populations. Logistic regression was then used to determine whether MAs who exhibit a higher preference for evidence-based (as opposed to intuitive) decision-making are more susceptible to framing bias.

Despite a comparatively high preference for evidence-based decision-making, the prevalence of framing bias among MAs is comparable to that of other populations. A higher preference for evidence-based decision-making was found to only be associated with higher susceptibility to endowment effect bias.

To the best of the authors’ knowledge, this is the first study to comprehensively examine framing bias for MAs as a group of decision-makers. Additionally, this study’s sample consists of practising MAs, and not only students.

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.

This paper aims to investigate the effectiveness of Language Enhancement Program (LEP) activities in enhancing the oral communication skills of English as a Foreign Language (EFL) students at King Khalid University.

A mixed-method study design was used. Simple random sampling techniques were adopted to recruit the study participants. For the survey, a total of 58 male students were recruited and for interviews, 20 male students were selected. The 58 participants were randomly divided into experimental and control groups. The traditional method was adopted to teach the control group, while LEP activities were conducted to teach the experimental group.

A post-test was conducted to examine the oral communication skills of the participants of the experimental group. The scores of both groups were analyzed using a t-test value at a significant level of 0.05. The content analysis method was adopted to assess the enhancement of the oral communication of the students enrolled in the LEP. The questionnaires and interview results showed that the LEP program has a central focus on improving students' oral communication skills.

It is limited to the EFL students at King Khalid University.

LEP is a good program and can be implemented in Saudi Universities.

Students can interact with one another through the LEP activities that promote their English proficiency as well as their personality characteristics.

The paper spells out the role of LEP activities in improving students' oral communication in English and students' opinions about LEP activities in enhancing their English language in different types of communicative contexts. Further, it suggests some pedagogical implications for overcoming the difficulties faced by EFL students in various communicative contexts.

Higher education institutions (HEIs) have a great responsibility to put education for sustainable development at the centre of their work. Curricula should therefore start to incorporate the sustainable development goals (SDGs) and key competencies in sustainability, and research should be carried out to determine effective learning methods for this. This study aims to explore the usefulness of problem-based learning (PBL) approaches to train biomedical students in sustainability and to provide some recommendations for the design and implementation of new PBL-SDG scenarios.

Two PBL-SDG scenarios were designed, implemented and evaluated for 110 students of human biology degree. Learning outcomes and student perceptions of this approach were analysed through questionnaires, student productions, non-participant observation and focus groups.

The results show that the PBL-SDG scenarios effectively addressed several SDGs and sustainability competencies in a transversal, collaborative and innovative manner. According to student perceptions, the elements that contributed most to the development of these competencies were emotional involvement with the scenario, reflection on their own actions, freedom to approach the problem and tutors who empowered them with their proposals.

The PBL-SDG approach presented in this study is an example of a pedagogical strategy that can help HEIs educate their learners as key change agents. The findings of this study provide evidence for this important aspect and give guidelines and strategies to successfully designing and implementing such methodologies in biomedical education.

This study aims to identify user perception of different qualities of optical character recognition (OCR) in texts. The purpose of this paper is to study the effect of different quality OCR on users' subjective perception through an interactive information retrieval task with a collection of one digitized historical Finnish newspaper.

This study is based on the simulated work task model used in interactive information retrieval. Thirty-two users made searches to an article collection of Finnish newspaper Uusi Suometar 1869–1918 which consists of ca. 1.45 million autosegmented articles. The article search database had two versions of each article with different quality OCR. Each user performed six pre-formulated and six self-formulated short queries and evaluated subjectively the top 10 results using a graded relevance scale of 0–3. Users were not informed about the OCR quality differences of the otherwise identical articles.

The main result of the study is that improved OCR quality affects subjective user perception of historical newspaper articles positively: higher relevance scores are given to better-quality texts.

To the best of the authors’ knowledge, this simulated interactive work task experiment is the first one showing empirically that users' subjective relevance assessments are affected by a change in the quality of an optically read text.

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

It has been demonstrated that AI-powered, data-driven tools’ usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy.

The authors introduce the results of a case study based on a large educational intervention at a fully online university. The views of the participants from degrees representing different knowledge areas and contexts of technology adoption (work, education and leisure) were explored after engaging in the analysis of the terms and conditions of use about privacy and data usage. After consultation, 27 course instructors (CIs) integrated the activity and worked with 823 students (702 of whom were complete and correct for analytical purposes).

The results of this study indicated that the intervention increased privacy-conscious online behaviour among most participants. Results were more contradictory when looking at the tools’ daily usage, with overall positive considerations around the tools being mostly needed or “indispensable”.

Though appliable only to the authors’ case study and not generalisable, the authors’ results show both the complexity of privacy views and the presence of forms of renunciation in the trade-off between data protection and the need of using a specific software into a personal and professional context.

This study provides an example of teaching and learning activities that supports the development of data literacy, with a focus on data privacy. Therefore, beyond the research findings, any educator can build over the authors’ proposal to produce materials and interventions aimed at developing awareness on data privacy issues.

Developing awareness, understanding and skills relating to data privacy is crucial to live in a society where digital technologies are used in any area of our personal and professional life. Well-informed citizens will be able to obscure, resist or claim for their rights whenever a violation of their privacy takes place. Also, they will be able to support (through adoption) better quality apps and platforms, instead of passively accepting what is evident or easy to use.

The authors specifically spot how students and educators, as part of a specific learning and cultural ecosystem, need tailored opportunities to keep on reflecting on their degrees of freedom and their possibilities to act regarding evolving data systems and their alternatives.