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Seekers who visit professional virtual communities (PVCs) are usually motivated by knowledge-seeking, which is a complex cognitive process. How do seekers search for knowledge, and how is their search linked to prior knowledge or PVC situation factors? From the cognitive process and interactional psychology perspectives, this study investigated the three-way interactions between seekers’ expertise, task complexity, and perceptions of PVC features (i.e. knowledge quality and system quality) on knowledge-seeking strategies and resultant outcomes.

A field experiment was conducted with 119 seekers in a PVC using a 2 × 2 factorial design of seekers’ expertise (i.e. expert versus novice) and task complexity (i.e. low versus high).

The study reveals three significant insights: (1) For a high-complexity task, experts adopt an ask-directed searching strategy compared to novices, whereas novices adopt a browsing strategy; (2) For a high-complexity task, experts who perceive a high system quality are more likely than novices to adopt an ask-directed searching strategy; and (3) Task completion time and task quality are associated with the adoption of ask-directed searching strategies, whereas knowledge seekers’ satisfaction is more associated with the adoption of browsing strategy.

We draw on the perspectives of cognitive process and interactional psychology to explore potential two- and three-way interactions of seekers’ expertise, task complexity, and PVC features on the adoption of knowledge-seeking strategies in a PVC context. Our findings provide deep insights into seekers’ behavior in a PVC, given the popularity of the search for knowledge in PVCs.

Numerous design methods are available to facilitate digital innovation processes in user interface design. Nonetheless, little guidance exists on their appropriate selection within the design process based on specific situations. Consequently, design novices with limited design knowledge face challenges when determining suitable methods. Thus, this paper aims to support design novices by guiding the situational selection of design methods.

Our research approach includes two phases: i) we adopted a taxonomy development method to identify dimensions of design methods by reviewing 292 potential design methods and interviewing 15 experts; ii) we conducted focus groups with 25 design novices and applied fuzzy-set qualitative comparative analysis to describe the relations between the taxonomy's dimensions.

We developed a novel taxonomy that presents a comprehensive overview of design conditions and their associated design methods in innovation processes. Thus, the taxonomy enables design novices to navigate the complexities of design methods needed to design digital innovation. We also identify configurations of these conditions that support the situational selections of design methods in digital innovation processes of user interface design.

The study’s contribution to the literature lies in the identification of both similarities and differences among design methods, as well as the investigation of sufficient condition configurations within the digital innovation processes of user interface design. The taxonomy helps design novices to navigate the design space by providing an overview of design conditions and the associations between methods and these conditions. By using the developed taxonomy, design novices can narrow down their options when selecting design methods for their specific situations.

Wine producers and marketing professionals increasingly recognize the significance of online wine reviews. Emotions have long been acknowledged as influential in online review behaviors. However, considering the multisensory nature of the wine experience, consumers’ wine expertise also plays a substantial role. Hence, this study aims to examine the online review behaviors exhibited by wine consumers through the dual lens of wine expertise and emotionality.

Two studies were conducted to address the research question. Study 1 explored the relationship among expertise, emotionality and review behaviors using a panel data model, with a data set consisting of 4,600,922 reviews from Vivino.com. Study 2 used a multigroup structural equation modeling (SEM) analysis using data obtained from an online survey. Study 2 aimed to investigate the interactive impact of emotionality and expertise on online review intention mediated by customer engagement.

The findings from Study 1 demonstrated a positive correlation between emotionality and online wine reviews. In addition, expertise displayed a bell-shaped relationship with both emotionality and online wine reviews. Study 2, in turn, uncovered that novices and experts experienced a direct influence of emotionality on their review intentions. In contrast, for those classified as ordinary, the influence of emotionality on review intention occurred indirectly through the mediation of customer engagement.

This paper extends the current literature on online wine review by integrating the effect of emotion and expertise on online wine review behaviors, expanding the examination of Dunning–Kruger effect in the wine literature. It also adds value by introducing emotionality and the Evaluative Lexicon into the hospitality literature, extending the measurement of emotion from valence and extremity to a third dimension, emotionality, in hospitality and wine domains.

This study examines what constitutes competence and how a novice becoming a competent weaver is enabled by information literacy in the fabric-weavers’ workplace landscape.

Ethnography as a research design was employed using participant observation and semi-structured interviews as the data collection techniques.

Competence constitutes the demonstration of Kente knowledge and mentorship capability enabled by information literacy through access to the on-the-loom and off-the-loom information in the Kente-weaving landscape.

This study explains how the transition from a novice weaver to a competent weaver is underpinned by information literacy.

This is one of the first studies that contribute to the understanding of information literacy in the craft workplace. The study proposes a framework for weavers' information literacy practice.

The “experience is the best teacher” model assumes that acquiring expertise in a given domain reduces biases. Research in expert knowledge in investment decisions has shown better ability to produce improved results in asset selection or portfolio returns. Universities created student-managed investment funds (SMIFs) to train students in portfolio management as fiduciaries. However, analyses of the effectiveness of the SMIF as a medium for expert knowledge transfer have not been done.

The authors’ analyze an SMIF's structure against established models of expert knowledge transfer, using the voting patterns of the trustees of the fund from the recorded minutes of the fund's meetings to show the fund's structure and outcomes demonstrate effective knowledge transfer. Voter consensus between faculty and student trustees is one proxy the authors use for knowledge transfer.

Consensus between faculty and students was uniformly high across all recommendations. Chi-square tests were employed to test for independence between approval of recommendation and level of consensus, showing dependence in most cases. Analysis of sale returns over the 12-year sample period showed significantly better performance of asset sales over relevant benchmarks for both equity and fixed income portfolios.

Most analyses of SMIF structure concentrate on well-known issues with things like student turnover, summers or other structural issues. Performance is evaluated based on returns. This study looks at the SMIF as an expert knowledge transfer medium and examines expert/novice decision approval in terms of knowledge transfer.

Vlogging constitutes a potential advertising channel for branded products. This paper aims to investigate the role and antecedents of the learning value, i.e. substantive (vs nonsubstantive) information processing, in consumers’ purchase behavior online.

The authors used a mixed-methods approach including qualitative data from 25 interviews, and two quantitative studies (a field study on 4,560 members of a vlogging learning community and a replication survey on 118 participants in a different context).

The results highlight the predominant role played by perceived learning due to the characteristics of the online environment. The authors further identify the components of vlog tutorials’ learning value. The findings distinguish structured from destructured learning content depending on consumers’ level of expertise.

The findings recommend developing the learning value for consumers. Managers should provide micro learning unit tutorials for expert consumers and complete structured learning units for novices based on core and additional learning components.

In contrast with traditional entertainment videos, tutorials provide added learning value that affects purchase behaviors to a greater extent. The results present in learning components that are recommended when developing learning tutorials.

This research analyses challenges faced by users at various levels in planning and designing participatory simulation models of cities. It aims to identify issues that hinder experts from maximising the effectiveness of the SUMO tool. Additionally, evaluating current methods highlights their strengths and weaknesses, facilitating the use of participatory simulation advantages to address these issues. Finally, the presented case studies illustrate the diversity of user groups and emphasise the need for further development of blueprints.

In this research, action research was used to assess and improve a step-by-step guideline. The guideline's conceptual design is based on stakeholder analysis results from those involved in developing urban logistics scenarios and feedback from potential users. A two-round process of application and refinement was conducted to evaluate and enhance the guideline's initial version.

The guidelines still demand an advanced skill level in simulation modelling, rendering them less effective for the intended audience. However, they have proven beneficial in a simulation course for students, emphasising the importance of developing accurate conceptual models and the need for careful implementation.

This paper introduces a step-by-step guideline designed to tackle challenges in modelling urban logistics scenarios using SUMO simulation software. The guideline's effectiveness was tested and enhanced through experiments involving diverse groups of students, varying in their experience with simulation modelling. This approach demonstrates the guideline's applicability and adaptability across different skill levels.

Co-teaching is a foundational mentoring model used in teacher residency programs in urban classrooms throughout the United States of America. Beyond the basic understanding of co-teaching in categorizing classroom models, the purpose of this qualitative case study is to investigate the dialectical tensions manifested in mentored co-teaching activities through the lens of cultural-historical activity theory (CHAT).

Designed as a qualitative case study of 17 pairs of teaching-residents and mentor-teachers, the authors used thematic analysis to scrutinize archival interview data in an urban teacher residency program located in the largest megalopolis of the USA Northeast. The authors used CHAT-based concept coding to analyze the interview narratives from participants across different secondary school placements as they reflected on their co-teaching philosophy and the relationships they built.

The authors found that for teaching-residents and mentor-teachers to co-develop as co-teachers, they jointly must learn to resolve the dialectical tensions of unbalanced classroom ownership vs added co-working responsibilities, breaking from routine so that a partnership can grow. Furthermore, the findings suggest that the prefix co- should be understood as (1) shifts in thinking that transcend the status quo and (2) the orchestration of human capital to change norms.

This new understanding of the prefix co- allows teacher education programs to better mediate the dialectical tensions experienced by co-teachers in a mentored co-teaching activity, from individual teacher learning (e.g. a pair/dyad comprising one teaching-resident and one mentor-teacher) to collective co-learning across activity systems (e.g. partnership-based teacher education).

Historically, graduate education’s goal was to prepare academics; now most science, technology, engineering and/or mathematics (STEM) graduate students (GSs) go on to nonacademic careers. STEM GSs must be equipped for success regardless of career aspirations, which can be done by strengthening GSs’ professional identities. This study aims to explore an interdisciplinary partnership designed to strengthen STEM GS professional identity.

The STEM Partnership Project (SPP), asked STEM GSs to serve as disciplinary experts and teach STEM content to elementary teacher candidates (TCs) so the TCs could design and teach an elementary science lesson. GSs also enrolled in a one-credit course to support SPP participation and activities. Over five semesters, the authors collected data from 28 STEM GSs across different disciplines and degree programs in the form of course assignments, surveys and interviews.

The SPP supported the development of a professional identity by having GSs serve as and feel like experts; increasing GSs’ sense of belonging in their field; increasing GSs’ self-confidence that they could (learn to) teach a wide variety of audiences; and raising GSs’ awareness of their ability to serve others via their field.

The SPP’s outcomes were consistent across STEM disciplines, did not require GSs to take on large amounts of coursework, nor did it cost much beyond materials for the various lessons. Furthermore, the key components that strengthened GSs’ professional identities could be adapted for different contexts and institutions.

In recent years, data science has become a high-demand profession, thereby attracting transmuters (individuals who want to change their profession due to industry trends) to this field. The primary purpose of this paper is to guide transmuters in becoming data scientists.

An exploratory study was conducted to uncover the challenges faced by data scientists according to their educational backgrounds. An extensive set of responses from 31 countries was received.

The results reveal that skill requirements and tool usage vary significantly with educational background. However, regardless of differences in academic background, the data scientists surveyed spend more time analyzing data than operationalizing insight.

The collected data are available to support replication in various scenarios, for example, for use as a roadmap for those with an educational background in art-related disciplines. Additional empirical studies can also be conducted specific to geographical location.

The current work has categorized data scientists by their fields of study making it easier for universities and online academies to suggest required knowledge (courses) according to prospective students' educational background.

The conducted study suggests the required knowledge and skills for transmuters to acquire, based on their educational background, and reports a set of motivational factors attracting them to adopt the data science field.