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This paper aims to investigate infant sensory patterns and their associations with previous perinatal loss, maternal-foetal attachment and postnatal maternal sensory patterns.

In a prospective cohort study, women with and without perinatal loss (N = 57) were recruited from an Australian public hospital. Participants were surveyed during pregnancy (maternal-foetal attachment, loss) and again postnatally (maternal/infant sensory patterns). Chi-square tests and logistic regression analyses controlling for previous perinatal loss were conducted with infant sensory patterns as outcome variables.

“More than typical” infant low registration was associated with poorer quality of maternal-foetal attachment. “More than typical” infant sensory seeking was associated with previous perinatal loss and higher levels of maternal sensory seeking. “More than typical” infant sensory sensitivity was linked with previous perinatal loss, poorer quality of maternal-foetal attachment and higher maternal low registration. “More than typical” infant sensory avoidance was associated with poorer quality of maternal-foetal attachment and higher levels of maternal sensory sensitivity.

To support more typical infant sensory patterns, results point to the potential benefit of occupational therapists supporting pregnant women with previous perinatal loss; facilitating favourable maternal-foetal attachment; and educating new mothers on how their sensory patterns impact on interactions with their infant. Sensory modulation strategies that consider the sensory patterns of both mother and infant may be beneficial to promote engagement in co-occupations.

These findings are the first to suggest that previous perinatal loss, poorer quality of maternal-foetal attachment and higher levels of maternal postnatal sensory patterns represent risk factors for infant sensory patterns that are “more than typical.”

Crop suitability analysis is vital for identifying a piece of land’s potential for sustainable crop production and aids in the formulation of an effective agricultural management plan. This study aims to conduct crop suitability analysis of prominent Kharif (rice and maize) and Rabi (potato and wheat) crops in Sirajganj district, a flood-prone area of Bangladesh, and recommend a suitable cropping pattern to mitigate the detrimental effects of flooding.

Various factors such as soil drainage, soil depth, soil moisture, soil texture, soil permeability, soil pH, erosion hazard, nutrient status and flooding risk were considered for this study. For all four crops, the weights of each factor were determined using the analytical hierarchy process approach, and the scores of each subfactor were assigned on the basis of favorable circumstances of crop cultivation. Using the weighted overlay analysis in the ArcGIS 10.3 environment, the crop suitability maps were generated and were divided into four suitable classes. Geographic information system integration of crop suitability for all the crops determined the suitable cropping pattern of the study area in Kharif and Rabi seasons.

A vast portion of the study area covering 64.80% of the total land is suitable for cultivating either rice or maize in Kharif season followed by either potato or wheat in Rabi season. Other suitable cropping pattern for Kharif and Rabi seasons found in the study area are rice-wheat, rice-wheat/potato, rice/maize-wheat and rice/maize-potato, which covers a little portion of the study area.

This research validates the suitable location of crop cultivation on the basis of flooding occurrences in the locality.

Three different pedagogical approaches grounded in three different definitional foundations of entrepreneurship have been compared in relation to their effects on students. They are: (1) “Idea and Artefact-Creation Pedagogy” (IACP), grounded in opportunity identification and creation, (2) “Value-Creation Pedagogy” (VaCP), grounded in value creation and (3) “Venture-Creation Pedagogy” (VeCP), grounded in organisation creation.

Data were collected at 35 different sites where education was deemed to be entrepreneurial and experiential. A quantitative, smartphone app-based data collection method was used alongside a qualitative interview approach. 10,953 short-survey responses were received from 1,048 participants. Responses were used to inform respondent selection and discussion topics, in 291 student and teacher interviews. Comparative analysis was then conducted.

The three approaches resulted in very different outcomes, both in magnitude and in kind. VaCP had strong effects on entrepreneurial competencies, on student motivation and on knowledge and skills acquisition. VeCP had weaker effects on knowledge and skills acquisition. IACP had weak effects on all outcomes probed for. Differences were attributed to variation in prevalence of certain emotional learning events and to variation in purpose as perceived by students.

VaCP could serve as an escape from the potential dilemma faced by many teachers in entrepreneurial education, of being caught between two limiting courses of action; a marginal VeCP approach and a fuzzy IACP one. This could prompt policymakers to reconsider established policies. However, further research in other contexts is needed, to corroborate the extent of differences between these three approaches.

Most impact studies in experiential entrepreneurial education focus only on organisation-creation-based education. This study contributes by investigating entrepreneurial education that is also grounded in two other definitional foundations. Allowance has been made for novel comparative conclusions.

The purpose of this paper is to examine how, and by whom, institutional logics are determined in the action of sustainable organisation. The authors analyse a supply chain network structure to understand how multiple stakeholders' perceptions of sustainability emerge into a dominant logic and diffuse across an organisational field.

Stakeholder network theory provides novel insights into emerging logics within a chocolate supply chain network. Semi-structured interviews with 35 decision-makers were analysed alongside 269 company documents to capture variations in emergent logics. The network was mapped to include 63 nodes and 366 edges to analyse power structure and mechanisms.

The socio-economic organising principles of sustainable organisation, their sources of power and their logics are identified. Economic and social logics are revealed, yet the dominance of economic logics creates risks to their coexistence. Logics are largely shaped in pre-competitive activities, and resource fitness to collaborative clusters limits access for non-commercial actors.

Powerful firms use network structures and collaborative and concurrent inter-organisational relationships to define and diffuse their conceptualisation of sustainability and restrict competing logics.

This novel study contributes to sustainable supply chain management (SSCM) through presenting the socio-economic logic as a new conceptual framework to understand the action of sustainable organisation. The identification of sophisticated mechanisms of power and hegemonic control in the network opens new research agendas.

This study investigated how organizations can maintain their supply chain (SC) resilience in situations where high-impact shocks cannot be absorbed and what capabilities are needed. The article is an empirical exploration of a socio-ecological view of resilience in the SC context.

The case under study in this article is that of Médecins sans Frontières (MSF) and MSF's reconfiguration of its supply management processes in response to the supply shocks during the coronavirus disease 2019 (COVID-19) pandemic. In total, 503 internal documents and ERP extractions from six databases from late 2019 to September 2020, 43 semi-structured interviews and a 3-round policy Delphi process were used to investigate this phenomenon.

The authors' results show that throughout the pandemic, MSF adapted its procurement and supply processes to cope with supply shortages at both the international and local levels of the SC. This was possible due to the organization's capacity to use its exploitation and exploration capabilities of the organization at the same time.

This research is based on the single in-depth case study of a medical aid organization. Further research should investigate this phenomenon in commercial companies with similar or different organizational structures.

This study constitutes a first attempt to empirically demonstrate that the four phases of the adaptive cycle put forth in the panarchy theory constitute a suitable representation of the reconfigurations that SCs follow in response to a high-impact shock. The study also adds to the growing body of knowledge on resilience by including ambidexterity as a mechanism to achieve resilience.

The performance of behavioral targeting (BT) mainly relies on the effectiveness of user classification since advertisers always want to target their advertisements to the most relevant users. In this paper, the authors frame the BT as a user classification problem and describe a machine learning–based approach for solving it.

To perform such a study, two major research questions are investigated: the first question is how to represent a user’s online behavior. A good representation strategy should be able to effectively classify users based on their online activities. The second question is how different representation strategies affect the targeting performance. The authors propose three user behavior representation methods and compare them empirically using the area under the receiver operating characteristic curve (AUC) as a performance measure.

The experimental results indicate that ad campaign effectiveness can be significantly improved by combining user search queries, clicked URLs and clicked ads as a user profile. In addition, the authors also explore the temporal aspect of user behavior history by investigating the effect of history length on targeting performance. The authors note that an improvement of approximately 6.5% in AUC is achieved when user history is extended from 1 day to 14 days, which is substantial in targeting performance.

This paper confirms the effectiveness of BT on user classification and provides a validation of BT for Internet advertising.

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.

Present for more than 20 years, 3D food printing (3DFP) technology has not experienced the same widespread adoption as its non-food counterparts. It is believed that relevant business models are crucial for its expansion. The purpose of this study is to identify the dominant prototypical business models and patterns in the 3DFP industry. The knowledge gained could be used to provide directions for business model innovation in this industry.

The authors established a business model framework and used it to analyse the identified 3DFP manufacturers. The authors qualitatively identified the market’s prototypical business models and used agglomerative hierarchical clustering to extract further patterns.

All identified 3DFP businesses use the prototypical business model of selling ownership of physical assets, with some variations. Low-cost 3D food printers for private usage and dedicated 3D food printers for small-scale food producers are the two primary patterns identified. Furthermore, several benefits of 3DFP technology are not being used, and the identified manufacturers are barely present in high-revenue markets, which prevents them from driving technological innovation forward.

The extracted patterns can be used by the companies within the 3DFP industry and even in other additive manufacturing segments to reflect upon, refine or renew their business model. Some directions for business model innovation in this industry are provided.

To the best of the authors’ knowledge, this is the first quantitative study to give an account of the current 3DFP business models and their possible evolution. This study also contributes to the business model patterns methodological development.