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Environmental pollution and corresponding adverse health impacts have now become a significant concern for the entire planet. In this regard, analysts and experts are continually formulating policies to reduce environmental pollution and improve natural ecological conditions. To aid in coping with the ecological predicament, a framework has been developed in the present study to inspect the adverse environmental impacts and related health issues of coal mining.

The parameters for this study have been identified through a review of the literature and finalized 23 critical parameters of air, water, land and soil, and noise related to coal mining by consultation with experts from industry and academia. Finally, the parameters have been categorized in accordance with the level of threat they pose to the environment by assigning weight using the Bradley–Terry model considering attitudinal data acquired by a questionnaire survey.

It is found that coal mining has a relatively higher impact on four attributes of “air pollution” (suspended particulate matter [SPM], respiratory particulate matter [RPM], sulfur dioxide [SO₂] and oxides of nitrogen [NO_x]), followed by “land and soil pollution” (deforestation and surface structure diversion), “noise pollution” (vehicle movement) and “water pollution” (water hardness, total solids (TSS/TDS) and iron content). It is also found that raising the air concentration of SPM and RPM results in increased respiratory and cardiopulmonary mortality. Therefore, reducing dust concentrations into the air generated during coal mining is recommended to reduce air pollution caused by coal mining, which will reduce contamination of water and land and soil.

The model built in this study is a hypothesized model that relied on the experts' opinions considering the parameters of coal production only. However, the parameters related to the usage of coal and its consequences have been excluded. Further, only industrial and academic experts were considered for this study; however, they excluded local people, coal mining personnel, policy authorities, etc. Therefore, the study findings might differ in real circumstances. The research can further be reproduced by considering the parameters related to the use of coal and its consequences, considering the opinions of the local people, coal mining personnel and policy authorities.

Categorizing the parameters according to the threat they pose to the environment due to coal mining can help the decision-maker develop an effective policy to reduce environmental pollution due to coal mining by considering the parameters on a priority basis. In addition, the results further help the decision-makers to assess the environmental impact of coal mining and take necessary action.

The study has developed a framework using the Bradley–Terry model to categorize the environmental parameters of coal mining to develop effective environmental policies, which are original and unique in nature.

Examines and compares wine attribute preferences within and between two different Spanish regions, Aragón and Navarra, by means of the weighted least squares approach for conjoint analysis. Uses three attributes in the conjoint design: price, origin and grape vintage year. Among these attributes, Navarra consumers assigned more importance to the origin of the wine, followed by price and grape vintage year. Aragón consumers also considered origin as the most important attribute, followed, in this case, by grape vintage year and price. Comparing the different attribute levels, consumers from Aragón preferred locally produced and cheaper wines, while consumers from Navarra preferred Rioja and more expensive wines. Identifies and characterizes four wine consumer segments. Describes how a market simulation experiment was designed to simulate market shares of three alternative wine profiles.

The purpose of this paper is to identify the factors influencing Indonesian students’ choice of university by estimating the trade-off students make in selecting a university.

Conjoint analysis was used to examine the relative importance and the part-worth scores of the attributes that influence students’ public university preferences in Indonesia.

High-school leavers in Indonesia trade off university preferences and view advice from family, friends, and/or teachers, reputation, and job prospects as important factors for selecting a public university. Two different preference-based segments of prospective students were identified from cluster analysis, and classified as either a “social networks-based decision” or a “rational decision” segment. A choice simulator was employed with three propositions, and the segments were found to have dissimilar preferences.

While this paper provides insights on higher-education consumer choice, more research is needed that includes samples from different types of higher-education institutions and fields of study.

A greater understanding of student choice can help to inform marketing practices and customize marketing strategies for each segment by providing important information to principal parties involved in making university choice decisions.

This paper demonstrates the relevance and value of conjoint analysis as an effective analytical tool for the identification of important choice criteria and its potential contribution to the development of more effective marketing strategies.

Ranked preference data arise when a set of judges rank, in order of their preference, a set of objects. Such data arise in preferential voting systems and market research surveys. Covariate data associated with the judges are also often recorded. Such covariate data should be used in conjunction with preference data when drawing inferences about judges.

To cluster a population of judges, the population is modeled as a collection of homogeneous groups. The Plackett-Luce model for ranked data is employed to model a judge's ranked preferences within a group. A mixture of Plackett- Luce models is employed to model the population of judges, where each component in the mixture represents a group of judges.

Mixture of experts models provide a framework in which covariates are included in mixture models. Covariates are included through the mixing proportions and the component density parameters. A mixture of experts model for ranked preference data is developed by combining a mixture of experts model and a mixture of Plackett-Luce models. Particular attention is given to the manner in which covariates enter the model. The mixing proportions and group specific parameters are potentially dependent on covariates. Model selection procedures are employed to choose optimal models.

Model parameters are estimated via the ‘EMM algorithm’, a hybrid of the expectation–maximization and the minorization–maximization algorithms. Examples are provided through a menu survey and through Irish election data. Results indicate mixture modeling using covariates is insightful when examining a population of judges who express preferences.

The purpose of this paper is to utilise market-oriented methodologies and simulation analysis to generate information regarding consumers’ attitudes, opinions and preferences towards novel β-glucan-enriched breads.

Focus Groups and In-depth interviews were used to generate consumer information on potentially suitable attributes that would maximise consumer acceptance. The approach involved the creation of a set of realistic product concepts from a combination of attribute levels and the presentation of these product concepts to consumers. A fractional factorial design generated an orthogonal array of 22 hypothetical products that were presented to consumers for rating while K-means cluster analysis was used to segment consumers into four specific consumer segments. The simulation analysis then identified β-glucan-enriched bread concepts targeted specifically at these four market segments.

The simulation analysis identified β-glucan-enriched bread concepts targeted specifically at these four market segments.

This research can assist manufacturers who wish to optimally design foods with novel ingredients and aid in the development of product concepts which maximise consumer acceptance and increase the likelihood of product success.

The purpose of this study is to utilise market-oriented methodologies to determine key attributes driving consumers' preferences for novel sustainably sourced seafood concepts, derived from a species of wild-caught fish unfamiliar to consumers and to explore new product concepts for various consumer clusters.

This study applied a mixed-method approach including five focus groups with 40 consumers and a single conjoint-based questionnaire administered to 300 seafood consumers in Ireland. The focus groups explored in-depth consumers' expectations, requirements and preferences and identified the key attributes that would influence acceptance of new seafood products. Full-profile conjoint analysis was used to model consumers' preferences for novel seafood product concepts that utilised a sustainably sourced species unfamiliar to the consumer.

Focus groups revealed that the most important attributes were brand, price, format, packaging, supplementary information and accompaniment. The conjoint simulation identified three consumer clusters. Product concepts containing a sustainably sourced fish species were identified according to the preferences of each consumer cluster.

This research highlighted a sustainability angle in new product development and identified a competitive advantage and market potential for boarfish (Capros aper), which is an underutilised Irish fish species. It used a market-oriented approach to explore the development of novel sustainably sourced value-added seafood product concepts. The study results provide small and medium seafood companies with original and unique insights for developing novel sustainably sourced fish products that increase consumer acceptance.

The purpose of this paper is to contribute to knowledge on the preferences of cheese consumers in Spain. The first step was to determine where and how frequently cheeses are purchased and consumed, along with different aspects relating to the recognition of cheeses certified by a denomination of origin (DO). The second step consisted in determining how consumer preferences are structured.

The methodology consisted of a survey of 412 consumers in the Castilla‐La Mancha Region who were buying food items for their homes. In order to process data related to the first step, a descriptive analysis was undertaken. For the second step, a conjoint analysis was carried out, with three types of attributes (price, certification and type).

The results show that cheese is a food which is present and also consumed within Spanish homes, while being bought in supermarkets at least once a week. Consumers value most the DO labels as a guarantee of quality and food safety. The cheese that is best known to consumers is the Manchego DO. Consumers prefer cheeses which are well‐priced, aged and, if possible, certified.

This paper analyses current consumer behaviour and, by means of conjoint analysis, identifies consumer preferences for cheeses in Spain. Internationally, conjoint analysis has rarely been used for cheeses, and this would appear to be the first time it has been applied in Spain.

This paper aims to use conjoint analysis to examine how Malaysian consumers make decisions regarding a consumer durable product – namely room air conditioners – under multi‐cue situations.

This study first assesses the impact of a priori perceived differences between brand names, country of manufacture, price, quality, technological advancement, and warranty on product evaluation. Second, the relative importance of the attributes as evaluative criteria is determined by performing part worth analysis. Six pertinent hypotheses are developed and tested. Conjoint analysis is used to develop product profiles that respondents could evaluate via a survey. This is followed by a market simulation to suggest marketing strategies for Malaysian and Japanese products (the latter dominate the Malaysian market).

The findings indicate the importance of capitalising upon consumer durables' intrinsic qualities, and the need to carefully consider the relationship between price and quality. Ways to take advantage of the strength of foreign brand names need to be understood and operationalised. The simulation exercise also indicates ways in which indigenous and external competitors could take advantage of market opportunities.

The study does place in a Malaysian context, and moreover used a convenience sampling approach. The need is demonstrable for more representative probabilistic sampling. While country of origin effects are understood, other criteria (i.e. design, assembly, and source) need to be considered in future studies.

It is felt that the approach utilised and the simulations developed can be applied in other geographic and cultural contexts and have implications for marketing strategies for branded consumer durable typologies.

The paper identifies and evaluates strategies for more effective competition in the Malaysian room air conditioner market. The use of conjoint analysis and market simulation provides a basis for competitive advantage in a tightly focused market sector.

The Flemish Examination Centre designed an intervention to establish a professional learning community on the topic of writing assessment. The purpose of this paper is to investigate the effects of this intervention and explain how this intervention succeeded in establishing a professional learning community.

A mixed method design was used to answer the research questions. Quantitative analysis of comparative judgement data provided insight into the effects of the intervention. More specifically was analysed whether examiners judged more in line after the intervention. Qualitative analysis of the conversations within the intervention served to examine how interdependent examiners behaved in the professionalisation exercises and to gain insight into how a professional learning community was established.

The analysis showed that the intervention of the Flemish Examination Centre facilitated the formation of a professional learning community. This was visible in the quantitative analysis. The qualitative analysis showed that highly interdependent activities were helpful in establishing the professional learning community.

This study shows that interactions of high interdependence are beneficial to facilitate professional learning communities.

This study shows that the assessment data can guide a well-thought out design of interventions to establish professional learning communities among assessors. Assessment data can be a guidance for supportive group constellations and discussions to improve assessment practices. The key in this regard lies in the level of interdependence that is created among participants.

Sustainability is a major challenge for India’s (Bharat’s) coal mining industry. The government has prioritized sustainable growth in the coal mining industry. It is putting forth multifaceted economic, environmental and social efforts to accomplish the Sustainable Development Goals (SDGs). This research aims to identify the factors for sustainable improvements in coal mining operations. Secondly, this study examines the intensity of causal relations among the factors. Thirdly, this study examines whether causal relations exist among the factors to be considered for sustainable improvement in coal mining operations. Lastly, the study aims to understand how the factors ensure sustainable improvement in coal mining operations.

An integrated three-phase methodology was applied to identify the critical factors related to coal mining and explore the contextual relationships among the identified factors. Fifteen critical factors were selected based on the Delphi technique. Subsequently, the fifteen factors were analyzed to determine the contextual and causal relationships using the total interpretive structural modelling (TISM) and DEMATEL methods.

The study identified “Extraction of Coal and Overburden” as the leading factor for sustainable improvement in coal mining operations, because it directly or indirectly influences the overall mining operation, environmental impact and resource utilization. Hence, strict control measures are necessary in “Extraction of Coal and Overburden” to ensure sustainable coal mining. Conversely, “Health Impact” is the lagging factor as it has very low or no impact on the system. Therefore, it requires fewer control mechanisms. Nevertheless, control measures for the remaining factors must be decided on a priority basis.

The proposed structural model can serve as a framework for enhancing sustainability in India’s (Bharat’s) coal mining operations. This framework can also be applied to other developing nations with similar sustainability concerns, providing valuable guidance for sustainable operations.

The current study highlights the significance of logical links and dependencies between several parameters essential to coal mining sustainability. Furthermore, it leads to the development of a well-defined control sequence that identifies the causal linkages between numerous components needed to achieve real progress towards sustainability.