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The authors provide primary data on salt iodisation of processed foods in Germany, analyse reasons for food processors' use or non-use of iodisation and derive implications for public health.

Statistical evidence is presented on the use of iodised salt in bread and bakery products, meat and meat products and dairy products in the German grocery-retailing sector. Information is based on mobile data collection in a representative sample of grocery stores in four German cities. These data are analysed with logistic regression models. Additionally, an online survey of bakers and butchers is utilised to record and to explain the use of iodised salt in specialised food stores.

Salt was added in 69.3% of the 29,910 foods analysed in the market study. When salt was added, iodised salt was used in only 28.5% of the cases. According to the online survey, only 44% of the bakers and butchers used iodised salt, and the user share declined over time. Incomplete information from processors on the role of iodised salt for public health is contributing to the low and declining user share.

The authors combine different market research methods and elaborate that the recommendation by the German Federal Ministry of Food and Agriculture – “If salt, then iodised salt” – is implemented to a very limited extent by the food industry and specialised food stores. From the behaviour of food processors and their perceptions of salt iodisation, the authors gain new insights for policy and public health.

This study aims to explore whether early anti-social fire exposure (ASFE) is associated with how adults engage with fire and how they view fire.

An opportunistic sample (N = 326) was recruited. Participants completed an online survey exploring ASFE, fire use, strength of fire-beliefs and interest in/attitudes supportive of fire. Additionally, implicit fire bias was measured using the affect misattribution procedure (AMP).

Participants with ASFE engaged with more criminalised fire use as adults. They also scored higher on fire interest and general fire beliefs and showed an implicit dislike of fire stimuli, compared to non-exposed participants (although differences in fire use were not statistically significant when gender was accounted for). Males also had higher levels of fire interest, held stronger fire related beliefs and were more likely to have been exposed to ASFE during childhood. However, there were no gender differences in fire use or on the implicit task.

The findings have practical application, namely in relation to early intervention and rehabilitative approaches. However, a limitation is that participants’ cultural background were not accounted for. Additionally, we advise caution in interpreting the implicit results and call for further research.

The need for better early interventions for young people is highlighted, along with better screening which, currently, is unstandardised and inconsistent across the country (Foster, 2020). This demands a community-engagement approach.

This is the first study to explore type of early exposure to fire. It is also the first to adopt the AMP as a measure of implicit fire-bias.

In this article we explore the level of motivation held by students engaged in a specially designed leadership program - Emerging Leaders in Technology, Science and Mathematics (Elites). Elites was developed as part of a NSF S-STEM grant awarded to Radford University in 2014 that provides scholarships for meritorious students with financial need, which aligns with Involvement Theory (Astin, 1985). Elites was designed to incentivize student participation in high impact activities to develop their professional skills aligned with their degree program, in order to develop them into STEM leaders. Coupled with Proactive Advising (Schee, 2007, Varney, 2012), the Elites program overarching goal was to promote retention of these students at Radford University and in their STEM related disciplines. This paper presents the successes and challenges of the Elites program as measured by focus group interviews and evaluating the students’ motivation levels to engage in the Elites program that is framed on an academic motivational model: M.U.S.I.C. (Jones, 2009). The results suggest students were motivated to remain with the Elites program and perceived the Elites program as effective as they prepared for their futures as STEM leaders.

In present research, the authors conducted the massive literature review and collected the information, in regards to material handling system (MHS) to build a multi criteria MHS hierarchical module consists of ecological cum fiscal criteria. Moreover, similar literature review assisted the authors to resolve and eventually construct the effectual and robust approach. The purpose of this paper is to facilitate the managers for benchmarking the MHS alternatives operating under similar module via robust decision support system (DSS).

In present research, the proposed module dealt with ecological (subjective) and fiscal (objective) criteria, where subjective criteria associated with incompleteness, vagueness, imprecision, as well as inconsistency, solicited the discrete information in terms of Grey set via linguistic scale from experts panel. The objective information (capital) has been assigned by expert’s panel in terms of Grey set. To robustly evaluate and select the admirable MHS, three approaches named: degree of possibility, technique for order preference similar to ideal solution as well as Grey relational analysis fruitfully applied to connect and unite discrete information.

The performance evaluation of MHSs has been carried out under concert of individual fiscal criteria excluding ecological criteria in past researches. Moreover the previous developed DSS tackled sole approach under individual fiscal criteria. The authors found the broad applications of fuzzy sets except Grey set theory in the same context for measuring the performance of MHS alternatives. Aforesaid research gaps have been transformed into research objectives by incorporating the module for both fiscal cum ecological criteria. This research embraces a robust DSS, which has been explored to select the admirable MHS alternative.

An empirical case study has been carried out in order to demonstrate the legitimacy of holistic Grey-MCDM method, implemented over multi criteria MHS hierarchical module. Proposed DSS seems to be the best for organisations, which believe to appraise and select the MHS including fiscal as well as ecological criteria excluding individual fiscal criteria. Moreover, subjective cum objective or individual subjective or objective criteria can be extended with respect to varieties of MHSs.

The purpose of this paper is to explore the role of service flexibility in addressing consumer vulnerability for chronically-traumatized consumers within the funerary context.

Using phenomenological philosophy and a grounded approach, data was collected and analyzed through 12 depth interviews with funeral service providers, coupled with observations and photographs of three second-line funeral processionals.

Study results include the following three primary roles of service providers in supporting chronically-traumatized consumers: the role of service fluidity in addressing trauma, mitigating vulnerability via service providers as community members and alleviating suffering through compassionate service. Service flexibility and value co-creation efforts were executed through an expansive service ecosystem of vendors.

When consumers experience vulnerability that demands reliance upon service industries, service providers can intentionally implement fluidity and agility in service design, adopt understanding and altruistic practices, and operate with empathy and compassion to orchestrate mutually-beneficial service outcomes.

Rooted in transformative service research, providers are advised to consider modifying services to improve well-being and mitigate vulnerability for chronically-traumatized consumers via fluidity, community and compassion.

This study contributes originality to the body of service marketing literature by illustrating how service providers alleviate vulnerability for chronically-traumatized consumers through three adaptive service strategies.

Nanosensors have a wide range of applications because of their high sensitivity, selectivity and specificity. In the past decade, extensive and pervasive research related to nanosensors has led to significant progress in diverse fields, such as biomedicine, environmental monitoring and industrial process control. This led to better and more efficient detection and monitoring of physical and chemical properties at better resolution, opening new horizons in the development of novel technologies and applications for improved human health, environment protection, enhanced industrial processes, etc.

In this paper, the authors discuss the application of citation network analysis in the field of nanosensor research and development. Cluster analysis was carried out using papers published in the field of nanomaterial-based sensor research, and an in-depth analysis was carried out to identify significant clusters. The purpose of this study is to provide researchers to identify a pathway to the emerging areas in the field of nanosensor research. The authors have illustrated the knowledge base, knowledge domain and knowledge progression of nanosensor research using the citation analysis based on 3,636 Science Citation Index papers published during the period 2011 to 2021.

Among these papers, the bibliographic study identified 809 significant research publications, 11 clusters, 556 research sector keywords, 1,296 main authors, 139 referenced authors, 63 nations, 206 organizations and 42 journals. The authors have identified single quantum dot (QD)-based nanosensor for biological applications, carbon dot-based nanosensors, self-powered triboelectric nanogenerator-based nanosensor and genetically encoded nanosensor as the significant research hotspots that came to the fore in recent years. The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

This is a novel bibliometric analysis in the area of “nanomaterial based sensor,” which is carried out in CiteSpace software.

Hydraulic excavator cycle time and associated unit costs of excavation for given input estimating data, for machines operating in the UK construction industry, are predicted. Using multiple regression analysis, three variables are identified as accurate predictors of cycle time: machine weight, digging depth and machine swing angle. With a coefficient of determination (R2) of 0.88, a mean percentage error (MPE) of −5.49, and a mean absolute error (MAPE) of 3.67, the cycle time model is robust; this is further validated using chi‐square analysis and Pearson's correlation coefficient (on predicted and actual values of machine cycle time). An illustrative example of the model's application to determine machine productivity is given. The paper concludes with a spreadsheet model for calculating excavation costs (m3 and cost per h) which is able to deal with any combination of the three independent cycle time predictor variables and other estimator's input data.

This paper offers key methodological insights for scholars new to qualitative transformative service research (TSR).

The paper offers ten lessons on conducting qualitative TSR that the authors have gleaned, across more than 30 years (combined) of qualitative inquiries and engagement with other scholars conducting and publishing what may be now termed TSR.

The key lessons of conducting qualitative TSR work include: displaying ethics in conducting and presenting qualitative TSR; preparing for and understanding the research context; considering design, mechanics and technical elements; being participant-centric; co-creating meaning with participants; seeking/using diverse types of data; analyzing data in an iterative fashion, including/respecting multiple perspectives; presenting evidence in innovative ways; and looking inward at every stage of the research process.

The paper provides implications for addressing the vulnerability of both research participants and researchers with the aim of improving research methods that lead to improved service research and well-being outcomes.

Clearly, the complexity and importance of the social problems TSR scholars investigate – poverty, war, disaster recovery, inadequate healthcare – requires preparation for how to engage in transformative service research. Importantly, the paper fits with recent persistent calls within the broader literature of services marketing to: use service research and design to create “uplifting changes” within society and broaden the paradigmatic underpinnings of service research to include dynamic, process-oriented approaches, which capture the dynamic and relational aspects of service ecosystems.

Utilization of off‐highway vehicles forms an essential part of UK industry's efforts to augment the productivity of plant operations and reduce production costs. However, uninterrupted utilization of plant and equipment is requisite to reaping the maximum benefit of mechanization; one particular problem being plant breakdown duration and its impact upon process productivity. Predicting the duration of plant downtime would enable plant managers to develop suitable contingency plans to reduce the impact of downtime. This paper presents a stochastic mathematical modelling methodology (more specifically, probability density function of random numbers) which predicts the probable magnitude of ‘the next’ breakdown, in terms of duration for tracked hydraulic excavators. A random sample of 33 machines was obtained from opencast mining contractors, containing 1070 observations of machine breakdown duration. Utilization of the random numbers technique will engender improved maintenance practice by providing a practical methodology for planning, scheduling and controlling future plant resource requirements. The paper concludes with direction for future research which aims to: extend the model's application to cover other industrial settings and plant items; to predict the time at which breakdown will occur (vis‐à‐vis the duration of breakdown); and apply the random numbers modelling to individual machine compartments.