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The organic product market can be considered as an emerging market. Since the 1990s it has experienced rapid growth, and supermarket chains have become the sales channel with the largest market share and are the main driver for further growth. However, different supermarket retail groups have very different strategies concerning the marketing of organic products. The purpose of this paper is to gain insight into the different strategies of retailers who are active in the organic product market and to explain the drivers which may underlie them.

The strategies of the three most important Belgian retailers that market organic products, and in particular organic beef, are analyzed. Data were collected through interviews with the retailers' staff and through observations in retail outlets. Also, GfK‐household panel data which recorded all purchases of 3,000 Belgian households and a postal survey with 529 respondents were used as data sources.

The different strategies used by retailers to market organic foods are associated with the overall characteristics and marketing strategies of the retail groups. Some retail groups have clear “first mover” advantages from engaging in the organic product line, while for others an adaptive strategy is more appropriate.

The insights from this paper will help the understanding and facilitate the development of future strategies for organic and other high‐value or premium products, which will be of interest to researchers and stakeholders who are active in these markets.

The retail sector is not a single homogeneous block, but instead consists of retailers who pursue quite different strategies. This concept may have major implications for the future development of high‐value markets.

Existing relevant theories were applied to the adoption of the organic product line, a segment in the portfolio of retailers that is becoming more important. The empirical material collected sheds new light on the drivers behind retail strategies.

This study takes the position that the concept of fraud is socially constructed. Moreover, it asks why and how different understandings of fraud have emerged. Insights from the work of Lakoff and Johnson (1999, 2003; Lakoff, 2002, 2004, 2009) are used to analyze language revealing dominant worldviews and metaphors regarding fraud. The research method is a case study (Yin, 2014), and the analytical approach used parallels the one described in O’Dwyer (2004). The research setting is a report issued by the Financial Crisis Inquiry Commission, which provides a context to study different understandings of fraud due to the report’s divided nature. The analysis reveals three alternative worldviews, representing different assumptions about reality, that are at the root of the different understandings of fraud. These worldviews also lead to the usage of different conceptual metaphors which allow the commissioners to interpret facts in a manner that supports each worldview’s assumptions. The paper also concludes by providing a nuanced and critical examination of the results of the commission concerning its understanding of fraud.

Various approaches have been made to alter the vibration sensing properties of zinc oxide (ZnO) films to achieve high sensitivity. This paper aims to report the experimental study of the fabrication of precursor molar ratio concentration varied ZnO nanostructures grown on rigid substrates using the refresh hydrothermal method. The effect of these fabricated ZnO nanostructures-based vibration sensors was experimentally investigated using a vibration sensing setup.

ZnO nanostructures have been grown using low temperature assisted refresh hydrothermal method with different precursor molar concentrations 0.025 M (R1), 0.075 M (R2) and 0.125 M (R3). Poly 3,4-ethylenedioxythiophene polystyrene sulfonate, a p-type material is spun coated on the grown ZnO nanostructures. Structural analysis reveals the increased intensity of the (002) plane and better c-axis orientation of the R2 and R3 sample comparatively. Morphological examination shows the changes in the grown nanostructures upon increasing the precursor molar concentration. The optical band gap value decreases from 3.11 eV to 3.08 eV as the precursor molar concentration is increased. Photoconductivity study confirms the formation of a p-n junction with less turn-on voltage for all the fabricated devices. A less internal resistance of 0.37 kΩ was obtained from Nyquist analysis for R2 compared with the other two fabricated samples. Vibration testing experimentation showed an improved output voltage of the R2 sample (2.61 V at 9 Hz resonant frequency and 2.90 V for 1 g acceleration) comparatively. This also gave an increased sensitivity of 4.68 V/g confirming its better performance when compared to the other fabricated two samples.

Photoconductivity study confirms the formation of a p-n junction with less turn-on voltage for all the fabricated devices. A less internal resistance of 0.37 kΩ was calculated from the Nyquist plot. Vibration testing experimentation proves an increased sensitivity of 4.68 V/g confirming its better performance when compared to the other fabricated two samples.

Vibration testing experimentation proves an increased sensitivity of 4.68 V/g for R2 confirming its better performance when compared to the other fabricated two samples.

The purpose of this paper is to investigate practices of argumentation on Twitter discussions about climate change.

Conversational threads were collected from the Twitter API. Fundamental concepts from argumentation theory and linking practices were operationalised through a coding schema for content analysis. Tweets were analysed in the context of the discussions and coded according to their argumentative approach, interaction type and argumentation stage. Linked and embedded sources were analysed in order to find how they were used in arguments, the plausibility and soundness of the message, the consistency and trustworthiness of the linked source and its adequacy with the target audience.

Among the interactions between arguers, this study found five typical practices and several patterns involving the dynamics of the conversations, the strategy of the argumentation and the linking practices. Although the rhetorical approach was prominent, the agreement was rarely achieved. The arguers used a variety of sources to justify or support their positions, often embedding non-textual content. These linking practices, together with the strategy adopted and the topics discussed, suggest the involvement of a multiple audience engaged in discussing ad lib scientific artefacts, topics and outputs.

While Twitter has been the focus for many research papers, the conversational threads have been given little attention so far. With the Twitter API making conversations more accessible for research, this paper does not only give insight into multiple audience group argumentation dynamics but also provides a method to study the conversations from an argumentation theory perspective.

Increases in industrialisation in developing countries bring bout increases in the levels of industrial waste which have to be disposed of. Increasing the efficiency of such waste disposal processes can be achieved by effective quality control systems. The objectives of waste control systems are multiple but can broadly be considered to be environmental and economic. This article shows how goal programming can be successfully applied to the type of quality control problem in which the levels of inputs and process variables are fixed in order to meet a required specification of output which is expressed by multiple characteristics. The authors conclude that the success of the approach depends crucially on the efficiency of the necessary regression analysis.

This study aims to propose a learning pattern analysis method which can improve a predictive model’s performance, as well as discover hidden insights into micro-level learning pattern. Analyzing student’s learning patterns can help instructors understand how their course design or activities shape learning behaviors; depict students’ beliefs about learning and their motivation; and predict learning performance by analyzing individual students’ learning patterns. Although time-series analysis is one of the most feasible predictive methods for learning pattern analysis, literature-indicated current approaches cannot provide holistic insights about learning patterns for personalized intervention. This study identified at-risk students by micro-level learning pattern analysis and detected pattern types, especially at-risk patterns that existed in the case study. The connections among students’ learning patterns, corresponding self-regulated learning (SRL) strategies and learning performance were finally revealed.

The method used long short-term memory (LSTM)-encoder to process micro-level behavioral patterns for feature extraction and compression, thus the students’ behavior pattern information were saved into encoded series. The encoded time-series data were then used for pattern analysis and performance prediction. Time series clustering were performed to interpret the unique strength of proposed method.

Successful students showed consistent participation levels and balanced behavioral frequency distributions. The successful students also adjusted learning behaviors to meet with course requirements accordingly. The three at-risk patten types showed the low-engagement (R1) the low-interaction (R2) and the non-persistent characteristics (R3). Successful students showed more complete SRL strategies than failed students. Political Science had higher at-risk chances in all three at-risk types. Computer Science, Earth Science and Economics showed higher chances of having R3 students.

The study identified multiple learning patterns which can lead to the at-risk situation. However, more studies are needed to validate whether the same at-risk types can be found in other educational settings. In addition, this case study found the distributions of at-risk types were vary in different subjects. The relationship between subjects and at-risk types is worth further investigation.

This study found the proposed method can effectively extract micro-level behavioral information to generate better prediction outcomes and depict student’s SRL learning strategies in online learning. The authors confirm that the research in their work is original, and that all the data given in the paper are real and authentic. The study has not been submitted to peer review and not has been accepted for publishing in another journal.

This paper provides a further investigation into the application of Correspondence Analysis (CA) as outlined by Greenacre (1984, 1993), which is one technique for “quantifying qualitative data” in research on learning and teaching. It also builds on the utilisation of CA in the development of the emerging discipline of English as an International Language provided by Hassall and Ganesh (1996, 1999). This is accomplished by considering its application to the analysis of attitudinal data that positions the developing pedagogy of Teaching English as an International Language (TEIL) (see Hassall, 1996a & ff.) within the more established discipline of World Englishes (cf. Kachru, 1985, 1990). The multidimensional statistical technique Correspondence Analysis is used to provide an assessment of the interdependence of the rows and columns of a data matrix (primarily, a two-way contingency table). In this case, attitudinal data, produced at a number of international workshops which focused on the development of a justifiable pedagogy for Teaching English as an International Language (TEIL), are examined to provide a more complete picture of how these venues differed from each other with respect to the collective responses of the respondents. CA facilitates dimensionality reduction and provides graphical displays in low-dimensional spaces. In other words, it converts the rows and columns of a data matrix or contingency table into a series of points on a graph. The current study presents analyses of two different interpretations of this data.

The purpose of this application manuscript is to address assessing and evaluating the impact of leadership mentoring programs on collegiate mentors. Specifically, this paper addresses the nuanced considerations of creating appropriate program outcomes and associated objectives given the individualized nature of mentoring relationships. Additionally, the current paper discusses assessment and evaluation strategies to demonstrate impact of leadership mentoring on the collegiate mentor via a three-year program evaluation effort. By innovating leadership mentoring program practice, leadership educators can more soundly design and deliver leadership mentoring programs and more precisely measure and demonstrate impact.

Each year, millions of people around the world are affected by natural disasters. Following these disasters, many students from colleges and universities arrive to support the affected areas. These seamless leadership learning opportunities engage students by allowing them to implement the concepts they learned in a classroom. Humanitarian relief requires leadership and logistics to mobilize essential resources to aid vulnerable groups affected by these disasters. This qualitative study evaluates two separate relief projects that were hands-on, week- long service trips involving college students responding to two natural disasters in the United States of America. Using data collected from prompt-based journals, the researchers in this study sought to develop a deeper understanding of participant service experiences in relation to leadership education. Leadership education provides valuable reflection points for students and this manuscript outlines key themes from two unique service experiences. This project showcases these reflections and provides a potential qualitative assessment process for similar endeavors useful for both educators and researchers alike.

This study examines the construct of respect, its manifestations in teacher-student relationships, and it relationship to ethics of care and sustainable development. The study found that students place a high premium on being respected by their teachers and measure expressions of respect chiefly through the attention received through listening. Students’ perspectives on the quality of the schools’ leadership and the teaching and learning environment were found to be shaped by their assessments of the degree to which they feel respected. In a number bivariate correlations, the study found strong, positive correlations between the variable ‘listening’ and other variables that characterize the teacher-student relationship, in particular respect for teachers and principals and comfort with the teaching and learning environment.

The study makes the case that the act of showing respect is a critical component of the ethics of care and sustainable development. The study recommends that one strategy that teachers and educational administrators should adopt in seeking to strengthen teacher-student relationships, exert positive influence on students’ behaviours and academic performance, and thus ensure the sustainability of healthy social environments is to invest in the creation of organizational cultures and administrative systems and processes that create the avenues through which respect for students can be demonstrably seen.