Search results

This paper examines how evidence based management (EBM) can help managers build more flexible organizations. In the context of this article, we define the need to build for this capacity around the challenge of “ambidexterity”, or the need for companies to continue operations while also allowing for innovation. We present a framework to help managers create strategies that help them build ambidexterity in their organizations, whether they operate in highly regulated, compliance driven or un-regulated, non-compliance climates.

This paper identifies four organizational design strategies each of which represents a different leadership and organization consideration that may focus on how evidence based management practices are linked to competency building (i.e., exploitation), the need innovation, or an equal balance between the two (i.e., ambidexterity).

Our findings reveal that an organization’s use of data given these four strategic orientations reflect different uses of data (verifiability and codification concerns) and ways of embedding compliance and ambidexterity (exploitation vs. exploration) considerations.

These four strategies help managers expose biases in their current decision-making practices, and how they subsequently may affect lifecycle, change management, and data practice in ambidexterity development.

While EBM acknowledges the importance of utilizing evidence, it remains limited toward understanding how it might be used to build for ambidexterity in organizations.

The purpose of this paper is to bring up the concept of multi‐material electromagnetic band‐gap structure (EBGs) and develop a method for its fabrication. Meanwhile, its microwave properties were studied and compared with the traditional EBGs consisting of two kinds of material.

Stereolithography (SL) and gel casting were used to fabricate 3D multi‐material EBGs. Resin mold was designed and fabricated based on SL process, slurries loaded with 55vol per cent Al₂O₃ and 55vol per cent TiO₂, respectively, were prepared, and using gel casting, multilayer EBGs with diamond structure were fabricated. T/R method was used to obtain the characteristic parameter S₂₁ of the EBGs; meanwhile, characters of their band structure were studied based on plane wave expansion method.

The fabricated EBGs with a TiO₂‐resin‐air structure showed a band gap from 11.7 GHz to 16.0 GHz along <1, 1, 0> direction; the EBGs with a TiO₂‐resin‐Al₂O₃ structure showed a band gap from 11.4 GHz to 11.9 GHz along <1, 1, 0> direction. Both of them agreed well with the simulation result. Also, through the study of multi‐material EBGs' microwave properties, it could be seen that this structure was a good approach to adjust the band gap.

With the concept of multi‐material EBG structure brought up, multilayer 3D EBGs were designed and fabricated based on SL combined with gel casting. It could be seen that multi‐material EBGs was a good approach to adjust the band gap. Also, the fact that the testing result matched the simulation validates the feasibility of the process.

This paper aims to propose a framework for engaging tourists as citizen scientists in marine research. Justification for such a framework is driven by the increasing use of citizen science (CS) as a method for collecting data in various research projects. While the tenets of CS exist, few studies have demonstrated how these could be integrated to address the challenges and benefits of engaging tourists as scientists.

A systematic review focused on CS-based literature within environmental management, tourism and marine tourism revealed 18 models. Key themes, those repeatedly identified, were extracted. These were adapted to inform the proposed theoretical framework for engaging tourist scientists.

The key themes were clarified and incorporated into the framework to enhance the value of marine research by engaging tourists. Important features considered were the singularity and sporadic nature of tourist participation, training and engagement as well as the reliability of data collected by citizen scientists.

The framework informs the unique requirements of research in marine environments and the under-used potential of tourist scientists.

抽象

本文构建了一个吸引游客成为海洋研究的公民科学家的框架。越来越多的人使用公民科学(CS)作为在各种研究项目中收集数据的一种方法, 这证实了这种框架具有合理性。尽管 CS 的原则是存在的, 但很少有研究表明如何将这些原则整合起来, 以便在吸引游客成为科学家的过程中解决问题, 实现效益。

本文对环境管理, 旅游和海洋旅游领域基于 CS 的文献进行了系统的回顾, 发现了18 种模式。接下来, 提取出重复确定的关键主题。为了吸引旅游者成为科学家, 这些都根据所提出的理论框架作了调整。

为了通过吸引游客成为科学家来提高海洋研究的价值，本文明确关键主题并将其纳入框架。同时，本文考虑到了一些重要因素，包括游客参加, 培训和融入的奇异性和零星性，以及公民科学家收集的数据的可靠性

该框架反映出，海洋环境研究具有独特的要求，以及旅游者科学家的潜力尚未得到充分利用。

Resumen

Este artículo propone un marco de trabajo, para involucrar a los turistas como ciudadanos científicos en la investigación marina. La justificación de este marco, está impulsada por el uso creciente de la ciencia ciudadana (CS), como un método para recopilar datos en los proyectos de investigación. Si bien ya existen los principios de la CS, pocos estudios han demostrado cómo estos podrían integrarse para abordar los desafíos y beneficios de involucrar a los turistas como científicos.

Una revisión sistemática, centrada y basada en la literature sobre CS, y al mismo tiempo relacionada con la gestión ambiental, turismo y turismo marino, reveló 18 diferentes modelos. Se extrajeron los temas clave, identificados repetidamente. Estos fueron adaptados para fundamentar el marco teórico propuesto e involucrar a los científicos turísticos.

Se aclararon los temas claves y se incorporaron en el marco de trabajo, para aumentar el valor de la investigación marina, mediante la participación de los turistas. Las características consideradas importantes, fueron la singularidad y la naturaleza esporádica de la participación turística, la capacitación y el compromiso, así como la fiabilidad de los datos recopilados por los científicos ciudadanos.

El marco de análisis, expone los requisitos únicos de investigación en entornos marinos y el potencial infrautilizado de los científicos turísticos.

The purpose of this paper is to examine how psychological antecedents (i.e. consumer mindsets) and individual difference characteristics (i.e. moral identity) affect the intention to purchase Fair Trade products based on the triadic reciprocal causation model in social cognitive theory (Bandura, 1986). The primary factors that influence ethical consumption decisions in ethnic Chinese societies were explored by integrating the unique cultural environment of the Chinese.

The study effective sample comprised university students and professors. Structural equation modelling was used to test the hypotheses and indirect effects. Results showed that moral identity internalization had a mediating effect on the relationship between a collectivistic mindset and the intention to purchase Fair Trade products.

A high moral identity symbolization had a moderating effect on the relationship between a collectivistic mindset and the intention to purchase Fair Trade products. This demonstrated that the two dimensions of moral identity, internalization and symbolization, play different roles and have different functions in regards to the intention to purchase Fair Trade products.

Future studies are urged to examine this issue at a cultural level by performing a cross-cultural comparison and to integrate consumer heterogeneity for a deeper examination of the interaction between demographic factors and psychological traits on consumer behaviours regarding Fair Trade products.

This study indicates that moral identity internalization is the primary factor that influences ethical consumption decisions in Chinese societies. In terms of the moderating effect of moral identity symbolization, results showed that the higher an individual’s moral identity symbolization, the stronger the relationship between a collectivistic mindset and the intention to purchase Fair Trade products is. These results can serve as a reference for marketing communications and market segmentation policies in the business world.

Social networks have changed the communication patterns significantly. Information available from different social networking sites can be well utilized for the analysis of users opinion. Hence, the organizations would benefit through the development of a platform, which can analyze public sentiments in the social media about their products and services to provide a value addition in their business process. Over the last few years, deep learning is very popular in the areas of image classification, speech recognition, etc. However, research on the use of deep learning method in sentiment analysis is limited. It has been observed that in some cases the existing machine learning methods for sentiment analysis fail to extract some implicit aspects and might not be very useful. Therefore, we propose a deep learning approach for aspect extraction from text and analysis of users sentiment corresponding to the aspect. A seven layer deep convolutional neural network (CNN) is used to tag each aspect in the opinionated sentences. We have combined deep learning approach with a set of rule-based approach to improve the performance of aspect extraction method as well as sentiment scoring method. We have also tried to improve the existing rule-based approach of aspect extraction by aspect categorization with a predefined set of aspect categories using clustering method and compared our proposed method with some of the state-of-the-art methods. It has been observed that the overall accuracy of our proposed method is 0.87 while that of the other state-of-the-art methods like modified rule-based method and CNN are 0.75 and 0.80 respectively. The overall accuracy of our proposed method shows an increment of 7–12% from that of the state-of-the-art methods.