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Drawing from legitimacy and institutional entrepreneurship theory, this study assesses the naming patterns of entrepreneurial firms in the US biotechnology industry.

The authors use a mixed-methods design of content analysis and regression to analyze a sample of 441 entrepreneurial biotechnology firms, for which data were obtained from Net Advantage. The authors track changes to the proportion of firms with naming attributes, such as name length and type of name. The authors also examine variability in those characteristics during the industry's evolution, comparing freestanding to acquired start-ups.

Start-ups select names that are longer, more descriptive, begin with rare sounds or hard plosives and have stronger discipline- or technology-specific links during nascent years of the industry. As the industry evolves, entrepreneurs are more likely to select names that are shorter, more abstract, begin with hard plosives and have stronger industry-specific links. The naming patterns of freestanding and acquired companies differ, and companies that conform to industry pressures tend to remain independent.

Unlike extant studies that assess established industries, the current study identifies shifting trends in the naming patterns of entrepreneurial firms in an emerging industry. By focusing on start-ups, the authors expand research on organizational naming practices, which focuses traditionally on name choices and name change patterns of incumbents. By using marketing and linguistics methods when analyzing organizational name attributes, naming patterns in these attributes are identified, including name length, name type, starting letter of the name and link to the industry.

Container shipping is generally considered a global business. This truth may not hold from a single-company perspective. The companies’ physical operation networks show that container carriers operate differently and follow different paths in their internationalisation development. Additionally, the degree of internationalisation, measured on the basis of sea-oriented operations, differs from that measured according to land-oriented front-end marketing and sales activities. The purpose of this study is to further examine the internationalisation patterns of shipping lines.

An examination of the front-end activities and the structures of leading container-shipping companies is conducted. The sales office networks of the sector’s 20 largest companies worldwide (by twenty-foot equivalent unit capacity) are analysed as key indicators. The numbers of sales offices are measured by analysing the websites of the sample (20 companies), as well as annual reports and other publicly available data sources.

The findings show that not all shipping companies are international, by virtue of the industry. While it is difficult to observe differences in the overall patterns of the sales networks at a macro level, some companies differ in their activities. The data set also shows that market share and total capacity are not necessarily good indicators of a carrier’s worldwide presence.

This research is based on secondary data. Other important transactional and market-oriented considerations should be examined before drawing conclusions about the internationalisation of container-shipping companies and of the industry.

This paper contributes to the relevant existing research, particularly by adding its view on the demand-oriented criteria as suggested by Dunning and Lundan (2008).

The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.

This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.

This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.

This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.

This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

This study aims to explore the connection between demographic traits and the choice of attraction patterns among international repeat tourists.

The study employed a questionnaire survey to collect data from 1550 international repeat tourists who visited Tanzania between November 2022 and July 2023. Convenient sampling was employed as tourists were selected from the three international airports of Tanzania, namely Kilimanjaro International Airport, Julius Nyerere International Airport, and Abeid Aman Karume International Airport. A multinomial logistic regression model was used to examine the impact of socio-demographic characteristics on the selection of attraction patterns among international repeat tourists.

The study revealed that demographic factors, including age, marital status, income level, occupation, and education level, exhibit statistically significant correlations with preferences for distinct attraction patterns. This significance was established through a p-value of less than 0.05 for all the aforementioned variables.

This study is primarily focused on international repeat tourists, thereby limiting insights into the preferences of domestic tourists. To better inform strategies aimed at attracting a larger domestic tourist base, future research may prioritize the investigation of choice of attractions patterns among domestic tourists in relation to their demographic characteristics.

This study contributes to the nuanced understanding of international tourist behavior by unraveling the extent to which demographic traits impact tourists’ choices of attraction patterns, thereby providing insights crucial for effective marketing strategies, improved visitor experiences, and sustainable tourism development strategies.

While previous studies focused mainly on East Asia to Europe or United States trade routes, in recent years, trade among South-East Asian countries has increased notably. The price of transporting a container is not fixed and can fluctuate heavily over the course of a week. Besides, extant literature only identified seasonality patterns in the container freight market, but did not explore route-varying seasonality patterns. Hence, this study analyses container freight seasonality patterns of the six South-East Asian routes of the South-East Asian Freight Index (SEAFI) and the index itself and forecasts them.

Data of the composite SEAFI and six routes are collected from the Shanghai Shipping Exchange (SSE) including 167 weekly observations from 2016 to 2019. The SEAFI and individual route data reflect spot rates from the Shanghai Port to South-East Asia base ports. The authors analyse seasonality patterns using polar plots. For forecasting, the study utilize two univariate models, autoregressive integrated moving average (ARIMA) and seasonal autoregressive neural network (SNNAR). For both models, the authors compare forecasting results of original level and log-transformed data.

This study finds that the seasonality patterns of the six South-East Asian container trade routes are identical in an overall but exhibits unique characteristics. ARIMA models perform better than SNNAR models for one-week ahead test-sample forecasting. The SNNAR models offer better performance for 4-week ahead forecasting for two selected routes only.

Major industry players such as shipping lines, shippers, ship-owners and others should take into account the route-level seasonality patterns in their decision-making. Forecast analysts can consider using the original level data without log transformation in their analysis. The authors suggest using ARIMA models in one-step and four-step ahead forecasting for majority of the routes. The SNNAR models are recommended for multi-step forecasting for Shanghai to Vietnam and Shanghai to Thailand routes only.

This study analyses a new shipping index, that is, the SEAFI and its underlying six routes. The authors analyze the seasonality pattern of container freight rate data using polar plot and perform forecasting using ARIMA and SNNAR models. Moreover, the authors experiment forecasting performance of log-transformed and non-transformed series.

Educational design patterns offer practical strategies that can be shared and adapted to address problems in teaching and learning. This article explores how educational design patterns for connected learning at scale at an Australian university may be adapted to a Vietnamese higher education context.

12 educational design patterns that address the challenges of active learning and large teaching team management are discussed. The authors then critically reflect on their cross-cultural adaptation for the higher education context, from an Australian to a Vietnamese university.

Transitioning from passive to active learning strategies and effectively leading large teaching teams present similar challenges across our contexts. Educational design patterns, when dynamically adapted, may assist educators to teach skills that are critical for work and the future. Higher education institutions globally could enhance their practices by incorporating international best practice approaches to educational design.

The Connected Learning at Scale (CLaS) educational design patterns explored in this article offer solution-oriented strategies that promote a more active learning experience. This paper identifies adaptations for educators, especially those in Vietnamese higher education that respect traditional structures, cultural nuances and resource limitations in implementation.

Whilst educational design patterns are well-researched in the Western contexts, few studies analyse design patterns in an Asian, and in particular the Vietnamese context. More research is needed in the cross-cultural adaptation of educational design patterns that joins practice and theory.

This paper aims to investigate the relationships amongst career patterns, neutrality of the state civil apparatus, and organizational performance of the local government in South Konawe District, Southeast Sulawesi Province in Indonesia.

Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the relationships between variables through direct and indirect influence testing.

The findings reveal that career patterns influence neutrality and organizational performance. Neutrality of the state civil apparatus in politics mediates career patterns and local government organizational performance. The findings indicate that, first, promotions most significantly influence the organization’s neutrality and performance. Second, demotions have the least influence on the organization’s robustness and performance.

This paper is among the first to examine the relationships amongst career patterns, neutrality, and organizational performance. Recommendations are provided to improve neutrality and organizational performance, that is, the need to increase promotions and reduce demotions.

In this paper, the authors suggest that Central Americans can use entrepreneurship to solve economic uncertainty in their home country and that entrepreneurship can contribute to reducing the number of undocumented migrants to the USA.

The authors first illustrate the context of Central American illegal migration to the USA from a transitional entrepreneurship perspective, the authors address the economic drivers of illegal migration from Central America, which results in marginalization in the USA. Second, the authors build a theoretical model that suggests that Central Americans can improve their entrepreneurial abilities through the entrepreneurial cognitive adjustment mechanism.

Central Americans at risk of illegally migrating to the USA have high entrepreneurial aptitudes. Entrepreneurship can help them avoid the economic uncertainty that drives Central Americans to illegally migrate to the USA and become part of a marginalized community of undocumented immigrants. This conceptual paper introduces an entrepreneurial cognitive adjustment mechanism as a tool for Central Americans to reshape their personalities and increase their entrepreneurial abilities in their home countries. In particular, entrepreneurial intentions reshape the personality characteristics of individuals (in terms of high agreeableness and openness to experiences, as well as low neuroticism) through the entrepreneurial cognitive adjustment mechanism, which consists of reflective action in sensemaking, cognitive frameworks in pattern recognition and coping in positive affect.

This paper studies Central Americans at risk of illegal migration using the lens of transitional entrepreneurship, which advances the understanding of the antecedents to marginalized immigrant communities in the USA and suggests a possible solution for this phenomenon. Besides, the authors build a cognitive mechanism to facilitate the transitional process starting from entrepreneurial intention to reshaping individuals' personality, which further opens individuals' minds to entrepreneurial opportunities. Since entrepreneurial intention applies the same way to all entrepreneurs, the authors' aim of constructing the entrepreneurial intention unfolding process will go beyond transitional entrepreneurship and contribute to intention-action knowledge generation (Donaldson et al., 2021). Moreover, the conceptual study contributes to public policy such that international and local agencies can better utilize resources and implement long-term solutions to the drivers of illegal migration from Central America to the USA.

Fingerprints and blood samples are important for the identification of individuals and criminals. The present study aims to identify the predominant fingerprint patterns and the association between the fingerprint patterns and ABO–Rh blood groups in Omani population.

A cross-sectional study was conducted on 200 Omani individuals aged 18 years (104 males and 96 females). The imprints of all right and left-hand fingers were taken, and the types of the fingerprints were determined using a standard protocol. The blood group of all the subjects was recorded. Chi-square test was performed to identify the association between the fingerprint patterns and the ABO and Rh blood groups.

The loop fingerprint pattern was the most common in Omani subjects (49.4%), followed by whorl (44.9%) and arch (5.7%) pattern. A significant association (p < 0.001) was found between gender and fingerprint pattern. The loop was the highest occurring pattern in the females (54.6%), while the whorl was more in males (50.0%). The whorl pattern was the most common in the AB+ and O− groups. The loop was a predominant pattern in the A+, A−, B+, B− and O+ groups. The Chi-square test also revealed a significant correlation between different fingerprint patterns and blood groups of the subjects (p < 0.001).

The present study is an outcome of undergraduate student's research project thesis for the Doctor of Medicine (MD) program. The results of the present study may help in creating a data bank for biometrics, which can be useful for diagnosing associated diseases and also help in identification of individuals.

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.