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This commentary argues that social marketing and the application of behavioural sciences to policy constitute two converging paths towards better policies. It highlights points of convergence and divergence between both disciplines and the potential benefits of further embedding social marketing principles and methods within the recent trend of applying behavioural sciences to policy.

The commentary relies on a review of the behavioural sciences and social marketing literatures and on an analysis of institutional reports reviewing cases of behaviourally informed policies.

Behavioural sciences are increasingly informing policies to promote societal well-being. Social marketing has seldom been explicitly considered as being part of this phenomenon, although it is de facto. Both disciplines share similar end-goals, inform similar policy applications and are rooted in behavioural analysis. They diverge in their theoretical frameworks, their relative emphasis on behaviour change and the span of interventions they generate. Several benefits of embedding social marketing principles and methods within the current way of applying behavioural sciences to policy are identified.

Scholars applying behavioural sciences to policy are encouraged, when appropriate, to use the insights and methods from social marketing. Social marketing can engage in a dialogue with behavioural sciences to explore how to pilot the convergence of both approaches in practice.

The novelty of this contribution lies in providing the first comparison of the application of behavioural sciences to policy with social marketing, and in using the policy-making cycle framework to map the contributions and complementarities of both disciplines.

This study aims to investigate the effect of smoking on the income of workers in the Brazilian labor market.

Using data from the 2019 National Health Survey (PNS), we initially address the sample selection bias concerning labor market participation by using the Heckman (1979) method. Subsequently, the decomposition of income between smokers and nonsmokers is analyzed, both on average and across the earnings distribution by employing the procedure of Firpo, Fortin, and Lemieux (2009) - FFL decomposition. Ñopo (2008) technique is also used to obtain more robust estimates.

Overall, the findings indicate an income penalty for smokers in the Brazilian labor market across both the average and all quantiles of the income distribution. Notably, the most significant differentials and income penalties against smokers are observed in the lower quantiles of the distribution. Conversely, in the higher quantiles, there is a tendency toward a smaller magnitude of this gap, with limited evidence of an income penalty associated with this habit.

This study presents an important limitation, which refers to a restriction of the PNS (2019), which does not provide information about some subjective factors that also tend to influence the levels of labor income, such as the level of effort and specific ability of each worker, whether smokers or not, something that could also, in some way, be related to some latent individual predisposition that would influence the choice of smoking.

The relevance of the present study is clear in identifying the heterogeneity of the income gap in favor of nonsmokers, as in the lower quantiles there was a greater magnitude of differentials against smokers and a greater incidence of unexplained penalties in the income of these workers, while in the higher quantiles, there was low magnitude of the differentials and little evidence that there is a penalty in earnings since the worker is a smoker.

The purpose of this study is to evaluate whether the perceptions of cleanliness and organization of the point of sale, hygiene and training of those who serve the public (service) and healthiness of the products, constitute a base for the perception of the quality of food sold in the street. Studies about development of street food trade have gained relevance in academic debate because of its social and economic significance. Usually, aspects related to sanitary issues are presented, and the factors that influence consumer perception regarding quality of food consumed are less explored. This was the focus of this work. The relationships among possible predecessors – attendance, cleanliness, organization and healthiness – were tested, all acting together, influencing the variable perception of product quality. Competitive models were tested because of theoretical divergences regarding the relationship between quality and healthiness, not yet totally clear in the literature.

A quantitative survey was carried out in the city of Diadema (SP, Brazil), getting 603 respondents, with data and theoretical models analyzed by structural equation modeling.

Results indicated that organization variable is not significant regarding perception of product quality, while attendance and healthiness directly affect this perception. On the other hand, cleanliness influences perceived healthiness and this, in turn, reinforces perception of product quality.

The focus of street food traders should be on clerk cleanliness and politeness (characteristics related to the service) that end up influencing the perception that the consumer develops regarding healthiness (characteristic related to product quality).

Usually research studies on this theme include only aspects related to sanitary and safety issues, and those which focus on consumer perception of food quality cover conventional outlets such as bars and restaurants. There are few ones performed as in this study that analyze street food consumer behavior regarding his/her perception of quality, cleanliness, care received, among others.

Our study aims to evaluate the impact of infrastructure and public investment on private investment in machinery and equipment in Brazil from 1947 to 2017. The contribution of our article to the existing literature lies in providing a more comprehensive understanding of the presence or absence of the crowding effect in the Brazilian economy by leveraging an extensive historical database. Our central argument posits that the recent decline in private capital accumulation over the last few decades can be attributed to shifts in economic policies – moving from a developmentalist orientation to nondevelopmental guidance since the early 1990s, which is reflected in the diminished levels of public investment and infrastructure since the 1980s.

We conducted a series of econometric regressions utilizing the autoregressive distributed lag (ARDL) model as our chosen econometric methodology.

Employing two different variables to measure public investment and infrastructure, our results – robust across various specifications – have substantiated the existence of a crowding-in effect in Brazil over the examined period. Thus, we have empirical evidence indicating that the state has influenced private capital accumulation in the Brazilian economy over the past decades.

Our article contributes to the existing literature by offering a more comprehensive understanding of the crowding effect in the Brazilian economy, utilizing an extensive historical database.

This study aims to perform a benefit segmentation and then a classification of visitors that travel to the Rocha Department in Uruguay from the capital city of Montevideo during the summer months.

A convenience sample was obtained with an online survey. A total of 290 cases were usable for subsequent data analysis. The following statistical techniques were used: hierarchical cluster analysis, K-means cluster analysis, machine learning, support vector machines, random forest and logistic regression.

Visitors that travel to the Rocha Department from Montevideo can be classified into four distinct clusters. Clusters are labelled as “entertainment seekers”, “Rocha followers”, “relax and activities seekers” and “active tourists”. The support vector machine model achieved the best classification results.

Implications for destination marketers who cater to young visitors are discussed. Destination marketers should determine an optimal level of resource allocation and destination management activities that compare both present costs and discounted potential future income of the different target markets. Surveying non-residents was not possible. Future work should sample tourists from abroad.

The combination of market segmentation of Rocha Department’s visitors from the city of Montevideo and classification of sampled individuals training various machine learning classifiers would allow Rocha’s destination marketers determine the belonging of an unsampled individual into one of the already obtained four clusters, enhancing marketing promotion for targeted offers.

Prolonged exposure to daily stressors can have long-term detrimental implications for overall mental health. For asylum seekers in European Union transit or destination countries, navigating life in reception centres can represent a significant burden. The purpose of this study was to explore post-migration stressors during residency in reception centres, and to formulate recommendations for adequate service provision in Belgium.

Research was conducted in two reception centres in Belgium. A total of 41 in-depth interviews were carried out with asylum seeker residents (n = 29) and staff (n = 12). Purposive recruitment was used for asylum seekers (for variation in length of centre residency and family status) and staff (variation in job profiles). Interviews were conducted in English, French or with a translator in Arabic or Dari. Interviews were audio-recorded, transcribed verbatim and manually coded using thematic analysis.

Asylum seekers face significant constraints with regard to their living conditions, including total absence of privacy, overcrowding and unhygienic conditions. These act as continuous and prolonged exposure to daily stressors. Several barriers to accessing activities or integration opportunities prevent meaningful occupation, contribute towards eroded autonomy and isolation of asylum seeker residents. Inadequate capacity and resources for the provision of psychosocial support in reception centres leads to a sense of abandonment and worthlessness.

Analysis indicates that structural and practical challenges to adequately support asylum seekers are rooted in policy failures necessary for appropriate resourcing and prioritization of preventative measures. Such deliberate decisions contribute towards state deterrence strategies, eroding both individual well-being and manufacturing a crisis in the systems of support for asylum seekers.

This paper empirically addresses the effect of coercive, normative and mimetic pressures on sustainability results, focussing on the three dimensions of the triple bottom line approach: environmental, economic and social. The mediating role of compliance, analyser or proactive corporate strategies towards sustainability is also considered.

The hypotheses developed in this study were tested using data from a sample of private companies from two industries: manufacture of chemicals and chemical products, and manufacture of basic metals.

The results confirm the role played by institutional pressures for sustainability in explaining the involvement of organisations in economic, social and environmental aspects. The mediating effect of corporate strategy is also confirmed, although only for environmental aspects.

Research into sustainability development is evolving rapidly; however, few studies have explored its diffusion amongst organisations from a triple bottom line perspective by considering the role of different current external pressures, the corporate strategy and the diverse results.

本研究擬對強制壓力、規範壓力和模仿壓力對可持續性成果的影響進行實證研究。研究的焦點放在三重底線法的三個層面上,即是環境層面、經濟層面和社會層面。研究人員亦探討尋求可持續性的承諾、分析儀和積極主動的公司戰略的中介作用。

研究人員測試其建立的各項假設; 使用的數據取自兩個企業的私人公司的樣本,它們是製造化學品和化學產品的企業,以及製造基本金屬的企業。

研究結果確認了尋求可持續性所帶來的制度壓力,在解說企業於經濟、社會和環境三方面的參與上所扮演的角色。研究結果亦確認了公司戰略的中介作用,唯這只見於環境的層面上。

探討可持續性發展的學術研究發展迅速,唯當中較少從三個基本的角度去探討可持續性發展在組織內的傳播; 本研究考慮了目前各種外來壓力、公司戰略和不同的結果所扮演的角色,以彌補這研究差距。

Roadmapping has been used as an approach to support market, product and technology-integrated planning, resulting in a document commonly known as a roadmap. Despite the gains made in relation to the technique, recent studies indicate that most users leave or have difficulties in sustaining the process (i.e. maintaining the updated roadmaps). This paper aims to present a framework for continuous roadmap updating that incorporates principles from agile management fields.

The framework was developed through action research in a manufacturing firm in the construction industry.

The results demonstrate a positive impact on the degree of continuous information monitoring, roadmap credibility and use of the roadmap during innovation strategy decisions.

The key contribution of this framework is the demonstration of a new strategy for carrying out the maps in which information is internalized by the organization itself, using agile teams, without commissioned specialists and as part of the work standards.

Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are limited to 140 characters. This led users to create their own novel syntax in tweets to express more in lesser words. Free writing style, use of URLs, markup syntax, inappropriate punctuations, ungrammatical structures, abbreviations etc. makes it harder to mine useful information from them. For each tweet, we can get an explicit time stamp, the name of the user, the social network the user belongs to, or even the GPS coordinates if the tweet is created with a GPS-enabled mobile device. With these features, Twitter is, in nature, a good resource for detecting and analyzing the real time events happening around the world. By using the speed and coverage of Twitter, we can detect events, a sequence of important keywords being talked, in a timely manner which can be used in different applications like natural calamity relief support, earthquake relief support, product launches, suspicious activity detection etc. The keyword detection process from Twitter can be seen as a two step process: detection of keyword in the raw text form (words as posted by the users) and keyword normalization process (reforming the users’ unstructured words in the complete meaningful English language words). In this paper a keyword detection technique based upon the graph, spanning tree and Page Rank algorithm is proposed. A text normalization technique based upon hybrid approach using Levenshtein distance, demetaphone algorithm and dictionary mapping is proposed to work upon the unstructured keywords as produced by the proposed keyword detector. The proposed normalization technique is validated using the standard lexnorm 1.2 dataset. The proposed system is used to detect the keywords from Twiter text being posted at real time. The detected and normalized keywords are further validated from the search engine results at later time for detection of events.