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To address the shortcomings of existing academic user information needs identification methods, such as low efficiency and high subjectivity, this study aims to propose an automated method of identifying online academic user information needs.

This study’s method consists of two main parts: the first is the automatic classification of academic user information needs based on the bidirectional encoder representations from transformers (BERT) model. The second is the key content extraction of academic user information needs based on the improved MDERank key phrase extraction (KPE) algorithm. Finally, the applicability and effectiveness of the method are verified by an example of identifying the information needs of academic users in the field of materials science.

Experimental results show that the BERT-based information needs classification model achieved the highest weighted average F1 score of 91.61%. The improved MDERank KPE algorithm achieves the highest F1 score of 61%. The empirical analysis results reveal that the information needs of the categories “methods,” “experimental phenomena” and “experimental materials” are relatively high in the materials science field.

This study provides a solution for automated identification of academic user information needs. It helps online academic resource platforms to better understand their users’ information needs, which in turn facilitates the platform’s academic resource organization and services.

This study aims to focus on exploring the role of fear of missing out (FOMO) in the technology adoption context, whereby the bottom-of-the-pyramid (BOP) segment was studied to explore the factors responsible for the development of behavioural intentions (BI) to use unified payments interface (UPI), a disruptive technological phenomenon in the mobile payment systems field.

A mixed-method research approach involving both qualitative and quantitative methods was used. Initially, qualitative data obtained through interviews with UPI’s BOP users were subjected to thematic analysis, leading to the identification of eight factors and the construction of a conceptual model. Subsequently, 354 responses were gathered, and empirical analysis was conducted using structural equation modelling in AMOS 23.0.

Eight factors, including personal and social benefits, perceived security risk, socio-cultural influences, governmental influence, usability, psychological inertia, perceived value (PV) and FOMO, were discovered. The quantitative examination confirmed the validity of the conceptual model in the BOP context, explaining 51% of the variance in BI. FOMO and PV emerged as robust indicators of UPI adoption, with PV significantly regulating the impact of FOMO.

To the best of the author’s knowledge, this study is one of the first to explore what drives BOP users in an emerging economy to adopt UPI. The conceptual model it presents contributes to the advancement of technology adoption literature by incorporating FOMO alongside newly identified BOP-specific factors.

This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.

A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.

Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.

The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.

This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.

We present configurational theorising as a novel approach to developing middle-range theory in two steps: (1) we illustrate configurational theorising as a new form of supply chain inquiry by connecting its philosophical assumptions with a methodological execution, and (2) we generate new insights underpinning a middle-range theory for supply chain resilience.

We synthesise information from a range of sources and invoke ‘critical realism” to suggest a five-phase configurational theorising roadmap to develop middle-range theory. We demonstrate this roadmap to explain supply chain resilience by analysing qualitative data from 22 organisations within the Australian food supply chain.

Coopetition and supply chain collaboration are necessary causal conditions, but they need to combine with either supply chain agility or multi-sourcing strategy to build supply chain resilience. Asymmetrical analyses showed that the simultaneous absence of supply chain collaboration, supply chain agility and multi-sourcing results in low supply chain resilience, but coopetition was indifferent to low supply chain resilience. Similarly, high supply chain resilience is possible with the non-presence of supply chain agility and multi-sourcing.

The configurational middle-range theorising roadmap presented and empirically tested in this paper constitutes a substantial advancement to both theory and the methodological domain.

This is the first attempt at developing a middle-range theory for supply chains by explicitly drawing on configurational theorising.

This study explores the configurations of management control systems (MCSs) while taking into account entrepreneurial cognition styles (ECSs) in small and medium enterprises (SMEs). The objective is to understand the impact of ECS on deployment and identify the various modes of MCS configurations employed by SMEs. The authors draw on and synthesise two theoretical perspectives relating to cognition and management control packages to understand the associations between ECS and MCS employed by SMEs in managing their business. This study was conducted using a quantitative approach that utilises a questionnaire survey to collect cross-sectional data from 150 SMEs. The authors uncovered three cognitive styles: knowing (e.g. preciseness), planning (e.g. organising), and creativity (e.g. innovativeness). Furthermore, five configurations of MCS utilised by SMEs were identified: customer focus, performance monitoring, administrative focus, strategic focus, and development focus. By combining both analyses, the authors discovered three constellations of significant association between ECS and MCS characterised by Cluster 1’s cohesive integration approach, Cluster 2’s revealing strategic approach, and Cluster 3’s multifaceted exploration. The study is significant because it uncovers the complex relationship between ECS and MCS configurations, highlighting their interdependence within the institutional context. Using a cognitive view, the authors explore how the cognitive styles of entrepreneurs facilitated imprinting institutional context into MCS configurations. These insights enable us to envisage that ECS is not mutually exclusive but forms a continuum that provides more plausible explanations that relax the direct universal relationship between MCS configurations and contextual factors.

In the UK signposting services can be developed as enhanced support for people with health and social care needs or service diversion to help primary and urgent care services manage their workload. This review considers these two conflicting purposes.

The review used a realist approach, initial searches to identify theory; we then selected 22 publications and extracted programme theories, from which we developed questions from three viewpoints: the service user, the front-line service provider and the commissioner. A rich sample of studies were found from purposive searching. To optimise the applicability of synthesis findings predominantly UK studies were included.

Users value signposting service that understand their needs, suggest a range of options and summarise potential actions. People with complex health and social care needs generally require extended time/input from signposting services. Front-line providers require initial and ongoing training, support/supervision, good knowledge of available services/resources and the ability to match users to them and a flexible response. Commissioned signposting services in England are diverse making evaluation difficult.

Meaningful evaluation of signposting services requires greater clarity around roles and service expectations. Signposting services alone fulfil the needs of a small number of users due to the unreconciled tension between efficient (transactional) service provision and effective (relational) service provision. This is underpinned by competing narratives of whether signposting represents diversion of inappropriate demand from primary care and other urgent care services or improved quality of care through a joined-up response encompassing health, social care and community/voluntary services.

This study introduces diagrammatic morphology as a novel method for analysing the synergistic interactions within school mapping. It seeks to reshape the evaluation of school mapping typologies, focusing on the interconnectedness of learning activities, social interactions, and spatial configurations. Aims: (1) To develop the morphological evaluation procedures for school mapping. (2) To evaluate the Iranian Middle Schools' Interior Architecture (IMSIA) using the diagrammatic morphological method.

This qualitative study has been conducted in two steps: A review of the morphological method for school mapping evaluation. A case study analysis of fifty-five IMSIA samples.

The spatial typology of IMSIA were categorized into four distinct models. These models included ten distinct pattern categories within twenty-one different types. The case study evaluation identified three levels of synergistic complexity within the school mapping: primary, intermediate, and advanced. The advanced level displayed the strongest connection to pedagogies among the analysed models.

This research innovatively evaluates the synergistic context of schools based on the assemblage theory through an occupational analysis of the Iranian middle schools' interior architecture mapping diagrammatic morphological method.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

The purpose of this study is to empirically explore how firms configure centrifugal and centripetal forces in promoting breakthrough innovation (BI), thus improving their strategic performance (SP) in the artificial intelligence (AI) context.

This study applies the centrifugal and centripetal forces model to a survey sample of 285 Chinese AI firms. Fuzzy-set qualitative comparative analysis (fsQCA) and propensity score matching (PSM) are integrated to explore the configurational effects of three centrifugal forces—the autonomy of technical experts, knowledge search and alliance network—and two centripetal forces—strictness of organisational institutions (SOI) and human–human–AI collaboration (HHAC)—on BI, examining whether the configurations that enhance BI can further improve SP.

The results indicate that the strictness of innovation institutions (SII) and strictness of ethical institutions (SEI) are equally important for determining SOI. Three configurations can improve BI when SOI and HHAC are the core conditions; only one of three configurations can further improve SP significantly.

By introducing SOI composed of equally important levels of SII and SEI and HHAC, this research is one of the few empirical studies to explore the mechanisms behind the impact of centrifugal and centripetal forces on BI and SP, which may help researchers and managers address innovation challenges in the AI context.

The purpose of this paper is to examine the role of entrepreneurial passion, specifically venture obsession, in agentic relationships within entrepreneurial contexts. It aims to develop a new conceptualization of the role of the venture in these relationships and explore the negative impacts that can arise from the obsessive passion for the venture. The paper contributes to the literature by shedding light on the complexities of agency outside of large for-profit firms, unpacking components of self-interest in the agentic relationship and challenging the assumption that entrepreneurial passion is always beneficial for both the entrepreneur and the venture.

This paper employs theoretical framework development and conceptual mapping to explore the role of entrepreneurial passion, specifically venture obsession, in agentic relationships within entrepreneurial contexts. We conducted a comprehensive literature review and synthesis of existing research on agency theory, entrepreneurial passion and venture obsession. By integrating these insights, we developed a new conceptual framework that theorizes the negative impacts of venture obsession on agentic relationships and venture performance. This approach allows us to propose a nuanced model that highlights the complexities and potential maladaptive behaviors associated with obsessive passion in entrepreneurship.

Venture obsession can have detrimental outcomes, such as escalation of commitment and ignoring external feedback, due to the intense focus on protecting the venture at all costs.

The study highlights the impact of venture obsession on agentic relationships, emphasizing the balance between autonomy, competence and relatedness that entrepreneurs strive to maintain for their well-being. While previous research has explored the role of entrepreneurial passion and its effects on venture performance, this study extends the understanding by delving into the darker side of passion when it transforms into obsessive agency. By emphasizing the importance of maintaining a healthy balance in agentic relationships and considering the psychological well-being of entrepreneurs, this study adds nuance and depth to the existing knowledge on the subject.