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To support the advancement of an underrepresented category of research in the field of entrepreneurial teams, this study proposes and tests a novel empirical model that connects two team emergent states, namely team entrepreneurial passion (TEP) and transactive memory systems (TMSs), and their influence on team performance.

The data were gathered using an online questionnaire distributed to undergraduate students who had formed entrepreneurial teams as part of a course assignment. Two methods were executed on the obtained data, namely partial least-square structural equation modelling (PLS-SEM) and necessary condition analysis (NCA).

The results uphold the hypothesised mediation role of TMSs between TEP and team performance. Of the two direct relations in the model, only the necessary conditions were present for the effect of TEP on TMSs.

The issue of the small sample size, a common feature in entrepreneurial team research, as discussed in the methodical section of the paper, is sidestepped with the use of PLS-SEM tools. Nonetheless, a larger sample size could have increased confidence in the results' validity. In addition, a longitudinal approach to data collection and analysis could have been used to augment that confidence further.

Three practical implications stem from the empirical findings. First, it lends support for implementing teaching approaches and task designs that are envisaged to improve team functioning in university classrooms. Making a business plan boosts students' desire to exploit the received knowledge and find a venture, so the teaching effort in entrepreneurship courses can have real-world consequences.

By testing the mediation model, new insights are made into the associations between team emerging states and, subsequently, team performance. In addition, this study responds to recent calls in the literature to incorporate NCA in an entrepreneurial setting.

This paper offers a definition of the core of information science, which encompasses most research in the field. The definition provides a unique identity for information science and positions it in the disciplinary universe.

After motivating the objective, a definition of the core and an explanation of its key aspects are provided. The definition is related to other definitions of information science before controversial discourse aspects are briefly addressed: discipline vs. field, science vs. humanities, library vs. information science and application vs. theory. Interdisciplinarity as an often-assumed foundation of information science is challenged.

Information science is concerned with how information is manifested across space and time. Information is manifested to facilitate and support the representation, access, documentation and preservation of ideas, activities, or practices, and to enable different types of interactions. Research and professional practice encompass the infrastructures – institutions and technology –and phenomena and practices around manifested information across space and time as its core contribution to the scholarly landscape. Information science collaborates with other disciplines to work on complex information problems that need multi- and interdisciplinary approaches to address them.

The paper argues that new information problems may change the core of the field, but throughout its existence, the discipline has remained quite stable in its central focus, yet proved to be highly adaptive to the tremendous changes in the forms, practices, institutions and technologies around and for manifested information.

The author examined effects of endorser type and message framing on visual attention and ad effectiveness in health ads, including the moderator of involvement. This paper aims to discuss this issue.

An experiment was conducted with a 2 (celebrity vs. expert) × 2 (positive vs. negative framing) between-subject factorial design. Eye-tracking measured visual attention and a questionnaire measured ad effectiveness and product involvement.

Experimental data from 78 responses showed no vampire effect in the health advertisements. Celebrity endorsement with negative message framing received more attention and had less ad recall than that with positive message framing. Negative and positive message framing attracted the same amount of attention and ad recall in the expert endorsement condition. High involvement participants paid more attention to the ad message with the expert than that with the celebrity, but ad recall was not significantly increased. Low involvement participants exhibited the same attention to the ad message with the expert and with the celebrity, but had greater recall of the ad message with the expert. Visual attention to the endorser was associated with ad attitude but not with ad recall. Ad attitude impacted behavioral intention.

Studies examining influences of celebrity and message framing on ad effectiveness have focused on the response to advertising stimuli, not the information process. The author provides empirical evidence of the viewers' information processing of endorsers and health messages, and its relationship with ad effectiveness. The study contributes to the literature by combining endorser and message framing in health ads to promote public health communication from the information processing perspective.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This study attempts to answer the question: “how are the two drivers, accountability focus and organizational learning, independently and interactively associated with public agencies’ proactive policy orientation?” The first driver is the multiple accountabilities that public agencies pursue: (1) bureaucratic, (2) legal, (3) professional and (4) political. The second driver is the organizational learning activities of public agencies: (1) socialization, (2) externalization, (3) combination and (4) internalization.

For data, 800 respondents from the public agencies in South Korea were surveyed.

The analysis provided several findings: (1) the discretionary accountabilities (professional and political) have a greater positive influence on the proactive policy orientation; (2) the conventional accountabilities (legal and bureaucratic) tend to have negative impacts on the proactive policy orientation and (3) among the four types of accountability, legal accountability can be more significantly complemented by organizational learning activities, which can enable both visionary and realistic administration in a balanced manner.

This study provides a unique insight on how organizational proactivity can be ensured through the interactions of organizational accountabilities and organizational learning.

The effect of dynamic capabilities on operational excellence and the moderating effect of environmental dynamism on the relationship between operational excellence and dynamic capabilities in the apparel industry in Sri Lanka were investigated while developing new psychometric scales to assess operational excellence and dynamic capacities constructs.

We followed the exploratory sequential research design with a mixed-method research approach, aligning with the pragmatic research philosophy. Thus, both qualitative and quantitative research methods were followed.

Dynamic capabilities positively affect operational excellence, and environmental dynamism moderates the relationship between operational excellence and dynamic capabilities in the apparel industry in Sri Lanka such that when a higher environmental dynamism exists, a weaker positive relationship exists between dynamic capabilities and operational excellence. The two main dimensions of the operational excellence construct are continuous improvement of sustainable operational performance and sustainable competitive advantages. It empirically confirmed that sensing, seizing and reconfiguring capabilities are the three main dimensions of the dynamic capabilities construct.

This study was limited to the apparel industry in Sri Lanka. This research phenomenon should be explored in other industrial sectors worldwide to generalize the findings. The practitioners in the apparel sector may improve the organizational dynamic capabilities to achieve operational excellence and keep a strong positive relationship between dynamic capabilities and operational excellence in a highly dynamic environment if they address out-of-family situations with out-of-the-box thinking.

We generated two new empirical findings: (1) dynamic capabilities positively affect operational excellence, and (2) environmental dynamism moderates the relationship between dynamic capabilities and operational excellence. Also, we introduced validated new scales for assessing operational excellence and dynamic capabilities.

This study aims to introduce a novel noise filter module designed for LiDAR simultaneous localization and mapping (SLAM) systems. The primary objective is to enhance pose estimation accuracy and improve the overall system performance in outdoor environments.

Distinct from traditional approaches, MCFilter emphasizes enhancing point cloud data quality at the pixel level. This framework hinges on two primary elements. First, the D-Tracker, a tracking algorithm, is grounded on multiresolution three-dimensional (3D) descriptors and adeptly maintains a balance between precision and efficiency. Second, the R-Filter introduces a pixel-level attribute named motion-correlation, which effectively identifies and removes dynamic points. Furthermore, designed as a modular component, MCFilter ensures seamless integration into existing LiDAR SLAM systems.

Based on rigorous testing with public data sets and real-world conditions, the MCFilter reported an increase in average accuracy of 12.39% and reduced processing time by 24.18%. These outcomes emphasize the method’s effectiveness in refining the performance of current LiDAR SLAM systems.

In this study, the authors present a novel 3D descriptor tracker designed for consistent feature point matching across successive frames. The authors also propose an innovative attribute to detect and eliminate noise points. Experimental results demonstrate that integrating this method into existing LiDAR SLAM systems yields state-of-the-art performance.

Drawing upon the theory of communication visibility, this research intends to investigate the direct effect of enterprise social media (ESM) usage on team members’ knowledge creation capability (KCC) and the mediating effects of psychological safety and team identification. In addition, it aims to untangle how the efficacy of ESM usage varies between pre- and post-COVID-19 periods.

Using two-wave survey data from 240 members nested within 60 teams, this study utilizes a multilevel approach to test the proposed hypotheses.

We discover that ESM usage enhances team members’ KCC. More importantly, the results show that psychological safety and team identification mediate the ESM–KCC linkage. Interestingly, we further find that the impacts of ESM usage on team members’ KCC, psychological safety, and team identification are stronger in the pre-COVID-19 period than those in the post-COVID-19 period.

This research sheds light on the ESM literature by unraveling the mechanisms of psychological safety and team identification underlying the linkage between ESM usage and team members’ KCC. Moreover, it advances our understanding of the differential efficacy of ESM usage in pre- and post-COVID-19 periods.

The gift-giving literature has documented several cases in which givers and recipients do not see eye-to-eye in gift-giving decisions. To help integrate this considerable segment of the gifting literature, this paper aims to develop a social norms-based framework for understanding and predicting giver-recipient asymmetries in gift selection.

Five experimental studies test the hypotheses. Participants in these studies evaluate gifts used in previous research, choose between gifts as either gift-givers or gift-recipients, and/or indicate their level of discomfort with choosing different kinds of gifts. The gifts vary in ways that allow the authors to test the social norms-based framework.

Gift-giving asymmetries tend to occur when one of the gifts under consideration is less descriptively, but not less injunctively, normative than the other. This theme holds for both asymmetries recorded in the gift-giving literature and novel ones. Indeed, the authors document new asymmetries in cases where the framework would expect asymmetries to occur and, providing critical support for the framework, the absence of asymmetries in cases where the framework would not expect asymmetries to emerge. Moreover, the authors explain these asymmetries, and lack thereof, using a mechanism that is novel to the literature on gift-giving mismatches: feelings of discomfort.

This research has multiple theoretical implications for the literatures studying gift-giving and social norms. A limitation of this work is that it left some (secondary) predictions of its model untested. Future research could test some of these predictions.

Billions of dollars are spent on gifts each year, making gift-giving a research topic of great practical importance. In addition, the research offers suggestions to consumers giving gifts, consumers receiving gifts, as well as marketers.

The research is original in that it creates a novel framework that predicts both the presence and absence of gift-giving asymmetries, introduces a psychological mechanism to the literature on giver-recipient gift choice asymmetries, and unifies many of the mismatches previously documented in this literature.

Drawing on the dynamic capability view, this study aims to examine the relationships between big data analytics capability (BDAC) and sustainable supply chain performance (SSCP) by exploring the mediating effects of knowledge development (KD) in terms of knowledge acquisition, information distribution, shared meaning and achieved memory.

Data were collected by questionnaire survey from 300 manufacturing organizations. Structural equation modeling was used to test the research hypotheses.

It was found that all the dimensions of KD were positively related to BDAC and SSCP. Although no direct association was established between BDAC and SSCP, the empirical findings indicated that all the dimensions of KD fully mediated the relationship between BDAC and SSCP. This highlights that organizations need to harness KD because developing BDAC alone may not be sufficient.

No previous research has explored how KD dimensions such as knowledge acquisition, information distribution, shared meaning and achieved memory mediate the relationship between BDAC and SSCP. This paper addresses this gap in the literature and contributes to the existing debate to better understand the conditions in which BDAC affects SSCP. Pointers for future research are also identified.