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The adoption of climate-smart agricultural practices (CSAPs) is important for sustaining Indian agriculture in the face of climate change. Despite considerable effort by both national and international agricultural organizations to promote CSAPs in India, adoption of these practices is low. This study aims to examine the elements that affect the likelihood and intensity of adoption of multiple CSAPs in Bihar, India.

The probability and intensity of adoption of CSAPs are analyzed using multivariate and ordered probit models, respectively.

The results show significant correlations between multiple CSAPs, indicating that their adoptions are interrelated, providing opportunities to exploit the complementarities. The results confirm that both the probability and intensity of adoption of CSAPs are affected by numerous factors, such as demographic characteristics, farm plot features, access to market, socio-economics, climate risks, access to extension services and training. Farmers who perceive high temperature as the major climate risk factor are more likely to adopt crop diversification and minimum tillage. Farmers are less likely to adopt site-specific nutrient management if faced with short winters; however, they are more likely to adopt minimum tillage in this case. Training on agricultural issues is found to have a positive impact on the likelihood and the intensity of CSAPs adoption.

The major policy recommendations coming from of our results are to strengthen local institutions (public extension services, etc.) and to provide more training on CSAPs.

By applying multivariate and ordered probit models, this paper provides some insights on the long-standing discussions on whether farmers adopt CSAPs in a piecemeal or in a composite way.

The purpose of the present study was the development of a methodology for translating predicted rates of decompression sickness (DCS), following tower escape from a sunken submarine, into predicted probability of survival, a more useful statistic for making operational decisions.

Predictions were made, using existing models, for the probabilities of a range of DCS symptoms following submarine tower escape. Subject matter expert estimates of the effect of these symptoms on a submariner’s ability to survive in benign weather conditions on the sea surface until rescued were combined with the likelihoods of the different symptoms occurring using standard probability theory. Plots were generated showing the dependence of predicted probability of survival following escape on the escape depth and the pressure within the stricken submarine.

Current advice on whether to attempt tower escape is based on avoiding rates of DCS above approximately 5%–10%. Consideration of predicted survival rates, based on subject matter expert opinion, suggests that the current advice might be considered as conservative in the distressed submarine scenario, as DCS rates of 10% are not anticipated to markedly affect survival rates.

According to the authors’ knowledge, this study represents the first attempt to quantify the effect of different DCS symptoms on the probability of survival in submarine tower escape.

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.

The quality of tourist accommodation establishments is a recurring theme in public strategies for planning and managing tourist destinations. The applying standards as a way to achieve quality. This strategy consists of legally regulating a series of minimum physical standards by using measureable parameters, as well as the desired characteristics or levels of amenities, which vary according to the type of provision required. The purpose of this study is to analyze the strengths and weaknesses of applying strategies that regulate standards for accommodations in coastal tourism areas in the Canary Islands (Spain).

The authors used an explanatory case study methodology. An “inter-case” comparison has been chosen, because the object of analysis (public policy applying tourism standards) has changed over time; furthermore, a content analysis approach was selected so that the subject of this research is the process of implementing this kind tourism policy. The result is a systematization of the process in stages.

Quantifiable criteria that exclusively consider the physical or operational parameters of a tourist establishment are no longer sufficient to provide quality service that meets the needs and expectations of customers. It is not enough to set standards for surface area parameters or essential amenities when organizing new tourist developments, but rather it is the qualitative aspect that must be addressed. At the same time, quality tourist accommodation establishment is not obtained merely by reducing density, which constitutes the significant standard.

This paper evidence is presented that may influence the quality of accommodation perceived by the client, which increases their level of satisfaction and, in turn, the degree of trust and, therefore, fidelity, understood as the future decision to repeat or not the tourist experience. There are also issues related to the approach that the quality of accommodation establishments has a direct effect on the visitor’s perception of the destination, which cannot be merely physical, mensurable in square metres.

The relationship between urban standards and quality is no longer linear. This determines that the regulated tourist accommodations (defined by sectoral regulations) it is common to set a required plot size in m2 based on the number of bed places offered by the establishment is no longer valid. Today, tourists rate accommodation establishments by the prestige of their brand or the diversity of services and experiences (entertainment, sensations, emotions, etc.) they provide. These experiences play such an important role in producing customer satisfaction and loyalty to a hotel that guests are willing to pay more for their stay, with the understanding that they will be able to experience certain emotions. It has been evidenced that the main reason for setting physical quality parameters that can be measured by a rating system for accommodation establishments, to provide a basic reference for customers, is no longer necessary, given the amount of easily accessible real-time information freely available through multiple independent channels based on the 2.0 paradigm, information technologies and communication, as well as applications and virtual platforms.

Applying this public strategy of classifying or rating tourist accommodations on a territorial scale has some strengths and weaknesses. However, it is not easy to find a comprehensive evaluation of the impact of such strategies because, among other issues, the public administration seems disinterested in measuring the consequences of their decisions, instead focussing on whether the formal legal requirements are being complied with. Moreover, whenever such assessments have been carried out, the discussion has been limited to the effectiveness of the implementation. This is why, beyond such purely mechanical responses, there are currently no studies or technical reports that specifically examine the positive or negative effects of such approaches. Evidently, these circumstances make any work analyzing this material relevant and timely. Likewise, the main reason for setting physical quality parameters that can be measured by a rating system for accommodation establishments, to provide a basic reference for customers, is no longer necessary, given the amount of easily accessible, real-time information freely available through multiple independent channels based on the 2.0 paradigm, information technologies and communication, as well as applications and virtual platforms.

The paper determines that the impact of the strategies of set a required plot size in square metres based on the number of bed places offered by the establishment is limited. Applying this public strategy of classifying or rating tourist accommodations on a territorial scale has some strengths and weaknesses. However, it is not easy to find a comprehensive evaluation of the impact of such strategies because, among other issues, the public administration seems disinterested in measuring the consequences of their decisions, instead focussing on whether the formal legal requirements are being complied with. Moreover, whenever such assessments have been carried out, the discussion has been limited to the effectiveness of the implementation. This is why, beyond such purely mechanical responses, there are currently no studies or technical reports that specifically examine the positive or negative effects of such approaches. Evidently, these circumstances make any work analyzing this material relevant and timely.

The purpose of the study is to analyse the occurrence and distribution of different tree species in Gilgit-Baltistan, Pakistan, as a baseline for further inventories, and estimate the biomass per species and plot. Furthermore, it aims to measure forest biodiversity using established formulae for tree species diversity index, richness, evenness and accumulative curve.

Field data were collected, including stratification of forest sample plots. Statistical analysis of the data was carried out, and locally appropriate allometric equations were applied for biomass estimation.

Representative circular 556 forest sample plots of 1,000 m² contained 13,135 trees belonging to nine tree species with a total aboveground biomass of 12,887 tonnes. Sixty-eight per cent of the trees were found between 2,600 and 3,400 masl; approximately 63 per cent had a diameter at breast height equal to 30 cm, and 45 per cent were less than 12 m in height. The Shannon diversity index was 1.82, and Simpson’s index of diversity was 0.813.

Rough terrain, long distances, harsh weather conditions and location of forest in steep narrow valleys presented challenges for the field crews, and meant that fieldwork took longer than planned.

Estimating biomass in Gilgit-Baltistan’s forests using locally developed allometric equations will provide transparency in estimates of forest reference levels, National Forest Monitoring System in Pakistan and devising Reducing Emissions from Deforestation and Forest Degradation national strategies and for effective implementation.

This paper presents the first detailed forest inventory carried out for the dry temperate and semi-arid cold region of Gilgit-Baltistan, Pakistan.

This study proposes a Bayesian approach to analyze structural breaks and examines whether structural changes have occurred, at the onset of civil war, with respect to economic development and population during the period from 1945 to 1999.

In the Bayesian logit regression changepoint model, parameters of covariates are allowed to shift individually, regime transitions can move back and forth, and the model is applicable to cross-sectional, time-series data.

Contrary to popular belief that the causal process of civil war changed with the end of the Cold War, the empirical analysis shows that the regression relationships between civil war and economic development, as well as between civil war and population, remain quite stable during the study period.

This is the first to develop a Bayesian logit regression changepoint model and to apply it to studies of economic development and civil war.

The purpose of this paper we present a case study where the Swedish planning support system Citylab is applied to a Chinese case in Changzhou's Tianning District.

China's planning system is a vertical system based on policy development on the national level, policies which are to be implemented on local level. There is a gap between the ambitious central policies and the implementations on local levels. China is now exporting its planning model to other developing countries which makes it urgent to show examples of other strategies including more horizontal planning involving the public. The planning system in Sweden is based on a much more horizontal process. Therefore, the authors try to learn from Sweden's vertical planning system in the urban development environment of China.

A key message for policy makers in China is that systems like Citylab can play an important role in developing practical and scalable examples of more sustainable city districts. The paper concludes that a barrier for local sustainability planning in China is still lack of effective communication between local actors including the public.

The authors exemplified Changzhou Tianning District's practical exploration, thus proving the adapted Citylab method's practical operability. Based on the common problems faced by eco-city development in developing countries, the method framework of Citylab is applicable to other developing countries, with strong room for deduction and development.

Over recent years, public relations (PR) research has diversified in themes and theories. As a result, PR presents itself today as a multi-paradigmatic discipline with competing ideas of progress that mainly circle around questions of ontology and epistemology, i.e. around defining appropriate object and knowledge in PR research.

This conceptual article highlights a third crucial question underlying the debate drawing on a narrative approach: The question of axiology, hence, the normative question how PR research shall develop to contribute to societal progress.

The article presents a model, which describes how normative visions of progress in different PR paradigms – functional, co-creational, social-reflective and critical-cultural – manifest in each distinct combinations of four narrative plots – tragedy, romance, comedy and satire.

These findings complement the current debate on disciplinary progress in PR research by fostering reflection and debate on paradigm development and cross-paradigmatic tensions and exchange from an explicit axiological perspective.