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The current study aims to examine if the internal marketing and employees’ personal traits can predict their green innovative behavior at the workplace.

A survey was conducted with 683 frontline employees working in four- and five-star hotels in Serbia. Zero-order bivariate correlations among variables and linear multiple regression were conducted to predict green innovative behavior based on internal marketing, personality traits and psychological capital. Binary genetic algorithms were used to segregate the subset of predictors that would be most suitable to describe variance in the outcome.

The results showed that internal communication, incentive and reward systems, work support, work environment, openness and creative self-efficacy were the most important predictors of almost all the phases of green innovative behavior.

The research showed that a multidimensional approach in analyzing green innovative behavior is necessary as some factors can be significant or not so significant predictors. Acknowledging that innovation is a multistage process, entailing distinct activities and requiring varied individual behaviors to accomplish each task, amplifies the importance of this inquiry. Employees’ personal characteristics have direct impact on green innovative behavior in hospitality. Further, the results gave an insight into the possible mix of elements of internal marketing that can be used for boosting employees’ green innovative behavior in hospitality. This is important as implementing effective internal marketing practices empowers organizations to motivate employees to invest discretionary efforts.

本研究旨在探讨内部营销和员工个人特质是否能预测他们在工作场所的绿色创新行为。

在塞尔维亚的四星和五星级酒店中, 对683名一线员工进行了调查。在变量之间进行了零阶双变量相关性和线性多元回归, 以预测基于内部营销、个性特质和心理资本的绿色创新行为。使用二元遗传算法(GAs)将适用于描述结果变异性的预测子集进行分离。

结果显示, 内部沟通、激励和奖励制度、工作支持、工作环境、开放性和创造力自效能是几乎所有绿色创新行为阶段的最重要的预测因素。

研究表明, 分析绿色创新行为需要采用多维度的方法, 因为某些因素可能是更或更少决定性的预测因素。承认创新是一个多阶段的过程, 涉及到不同的活动, 并要求采用不同的个体行为来完成每个任务, 这加强了对这一调查的重要性。员工的个人特征直接影响了酒店业的绿色创新行为。此外, 结果揭示了可以用于促进酒店业员工绿色创新行为的内部营销元素可能的混合。这是重要的, 因为实施有效的内部营销实践使组织能够激励员工投入可自由支配的努力。

El presente estudio examina si el marketing interno y los rasgos de personalidad de los empleados pueden predecir su comportamiento innovador ecológico en el lugar de trabajo.

Se realizó una encuesta a 683 empleados de primera línea que trabajan en hoteles de cuatro y cinco estrellas en Serbia. Se llevaron a cabo correlaciones bivariadas de orden cero y regresiones lineales múltiples (LM) para predecir el comportamiento innovador ecológico en función del marketing interno, los rasgos de personalidad y el capital psicológico. Se utilizaron algoritmos genéticos binarios (AGs) para segregar el subconjunto de predictores más adecuado para describir la variabilidad en el resultado.

Los resultados mostraron que la comunicación interna, los sistemas de incentivos y recompensas, el apoyo en el trabajo, el entorno laboral, la apertura y la autoeficacia creativa eran los predictores más importantes en casi todas las fases del comportamiento innovador ecológico.

La investigación demostró que es necesario un enfoque multidimensional para analizar el comportamiento innovador ecológico, ya que algunos factores pueden o no ser predictores significativos. Reconocer que la innovación es un proceso de múltiples etapas, que implica actividades distintas y requiere comportamientos individuales variados para realizar cada tarea, amplifica la importancia de esta investigación. Las características personales de los empleados influyen directamente en el comportamiento innovador ecológico en la industria hotelera. Además, los resultados ofrecen una visión de la posible combinación de elementos de marketing interno que se pueden utilizar para impulsar el comportamiento innovador ecológico de los empleados en la hotelería. Esto es importante ya que la implementación de prácticas eficaces de marketing interno permite a las organizaciones motivar a los empleados para que inviertan esfuerzos discrecionales.

The starting premise of the case study is to describe the ongoing interventions and experiences within the observed public marketplaces' organization. The objective of the research is to examine specified aspects of social and economic perspectives and the role of marketplaces in changing the local surroundings and economy of the Serbian capital and its largest city – Belgrade.

Multiple methods of analysis, such as archival investigation, participants' observation and semi-structured interviews were conducted. To inspect the research questions, the case implemented qualitative research that sampled 21 employees in the examined public company which manages all the analyzed urban marketplaces.

This case study will describe the city-sponsored organization, the Public Utility Company (PUC), that sustains marketplaces and the implications of that city sponsorship. Additionally, the outcomes describe the social and economic impact of marketplaces in placemaking around the region.

The most imperative implications of the manuscript are twofold: (1) the research results have shown that the potential of the city marketplaces can be increased through the support of the PUC and the city government; (2) as one of the first empirical projects about the social organization of the marketplaces in this part of Europe, the findings provide an overview of the contemporary market processes, and market outcomes. This study can affect other future research to explore similar aspects of the markets' organization.

This research can encourage comparable future examinations to explore other components of the market, varying in the regional diversities on one hand, and the manifold prospects for the community development with fewer benefits, on the other.

The study analyzes all the local markets in the selected urban area. This is the first empirical research on the social perspective and the role of marketplaces in the process of changing the modern society and economy in Belgrade. Moreover, it may contribute to future analysis in the field of social perspective and economic directions in future strategies of city planning.

Novi Sad, as the second largest city in Serbia, is nominated for the European Capital of Culture for 2021. In addition, the city has a rich traditional gastronomic resource base, belonging to over 16 nationalities living in the Vojvodina area (Autonomous Province of Serbia). This study aims to analyze the impact of Instagram, on the choice of catering facility and type of food, and to discover the extent to which it creates confidence to gastronomic consumers and the brand of the product or service.

The study presents a survey, which involves sharing survey questionnaires and gathering information from research participants. The sample of the survey included only the local population during 2019 year, on a random sample of 155 participants.

Of the total number of respondents, the highest percentage of them follow Instagram posts related to gastronomic objects, compared to other social networks. The results of this study undoubtedly show that consumers have great confidence in this social network and that it creates a certain brand and attitude on the basis of which consumers will choose a catering facility or food.

The process of interviewing people in gastronomy, regarding the impact of social networks on brand, attitude and consumer confidence, can provide an excellent insight into the current situation as well as influence changes that would contribute to better business of restaurant facilities in Serbia.

Doing survey research is much more significant in the field of tourism and gastronomy, as these are industries that are primarily the human sector. The personal attitude of the direct users of the services in the restaurant facilities can contribute to the overall picture of the state of gastronomy in this area.

The study contributes to the development of contemporary gastronomy, which is on the rise compared to many other branches of the economy in Serbia. Researching the impact of service providers, through social networks, on consumers is a way of reaching out to learn about the level of service quality and customer satisfaction achieved, as well as creating loyal consumers and better position in the market.

During the pandemic, two types of fear were identified that occur significantly in all groups or profiles of people. The aim of this paper is to determine which of the two types of fears exist in certain psychological groups, and which of the fears strongly influence the decision to travel.

The VALS 2 method and standardized questionnaire were used for the segmentation of the tourist market or for the determination of the psychographic profiles of the consumers, and three additional questions were joined to it as they were vital for the research of the type of fear and its impact on the decision for traveling. When the reliability of the questionnaire and the validity of the sample were determined, the data were further processed using a computer program package IMB AMOS SPSS 21.00, and then, based on the theoretical suppositions and hypotheses, the SEM structural model was created.

The paper indicates the existence of established types of fears in humans, when it comes to pandemics and similar crisis situations. People are most afraid of infection during travel, and lack of funds and job loss during the critical period of the pandemic. The research conducted confirms that all groups of people, who are determined by the psychological technique VALS 2, react with a certain dose of fear and make decisions under the pressure of fears.

The research had limitations in terms of contact with people and conducting live surveys. The measures during the pandemic, which were carried out by the state, included social distance and limited movement of people.

The work can contribute to the community, along with similar research. The results of the research will be available, and it will be possible to see the behavior of people during crisis situations, and the impact of fears on making decisions, both travel decisions and decisions related to other areas of life.

The paper provides research results on a large sample of respondents, and can serve as a basis for further research in the field of tourism, psychology and similar fields. It is crucial to consider the type of fears, and the strength of the impact of these fears on the decision to travel, during crisis situations.

The purpose of this study was to develop flexible sensors for detection of different concentrations of bacteria, such as Pseudomonas aeruginosa and Staphylococcus aureus, in saline.

The sensors were fabricated using ink-jet printing technology and they consist of a pair of silver interdigitated electrodes printed on mechanically flexible substrates – foil and paper. In house measurement setup for testing and characterization of sensors has been developed. Structural, electrical and mechanical properties of flexible sensors have been determined and compared.

The characteristics of sensor – the resonant frequency as a function of different concentrations of each bacteria – are presented. The obtained results demonstrate different resonant frequencies for each dilution of Pseudomonas aeruginosa and Staphylococcus aureus in physiological saline.

Both sensors showed accurate measurements of bacterial count, which can be achieved with detection of resonant frequency, and this is reflective of the number of bacterial cells within a sample.

The findings suggest that the newly developed method based on measuring resonant frequency corresponds well with bacterial cell count, thus establishing a new proof-of-concept that such method can have significant applications in bacterial cell counting that are economic and easily maintained.

Fast, cost-effective, accurate and non-invasive method for detection of different bacteria from saline was developed.

For the first time, comparison between performances of flexible sensors on foil and paper for bacteria detection is demonstrated. Almost linear dependence between shift of resonant frequency of developed sensors and concentration of bacteria has been obtained.

Higher education institutions (HEI) are acknowledged as a key driver for the development of sustainable societies, so much so that some profess education for sustainable development to be the most fundamental of the United Nation’s (UN) 17 sustainable development goals (SDGs). This chapter provides an overview of the chapters in the book: Higher Education for the SDGs, divided into two themes, namely (i) Research from the Global North and Global South and (ii) Rethinking curriculum.

To overcome the shortcomings of traditional industry classification systems such as the Standard Industrial Classification Standard Industrial Classification, North American Industry Classification System North American Industry Classification System, and Global Industry Classification Standard Global Industry Classification Standard, the authors explore industry classifications using machine learning methods as an application of interpretable artificial intelligence (AI).

The authors propose a text-based industry classification combined with a machine learning technique by extracting distinguishable features from business descriptions in financial reports. The proposed method can reduce the dimensions of word vectors to avoid the curse of dimensionality when measuring the similarities of firms.

Using the proposed method, the sample firms form clusters of distinctive industries, thus overcoming the limitations of existing classifications. The method also clarifies industry boundaries based on lower-dimensional information. The graphical closeness between industries can reflect the industry-level relationship as well as the closeness between individual firms.

The authors’ work contributes to the industry classification literature by empirically investigating the effectiveness of machine learning methods. The text mining method resolves issues concerning the timeliness of traditional industry classifications by capturing new information in annual reports. In addition, the authors’ approach can solve the computing concerns of high dimensionality.

This study investigates the effectiveness of microfinance-backed entrepreneurship as a mechanism for the holistic empowerment of women.

This study employs a mixed-method research-design consisting of quasi-experimental design (quantitative approach) involving women, both entrepreneurs (132) and non-entrepreneurs (238), as well as in-depth semi-structured interviews (qualitative approach).

Quantitative analysis revealed that female entrepreneurs are better off than female non-entrepreneurs in terms of economic, social, political and psychological indicators of empowerment. However, relatively lesser impact was found in terms of political, and to an even smaller extent, social empowerment of women. Analysis of in-depth interviews corroborated these findings confirming that entrepreneurship serves as an effective tool for the holistic empowerment of women. However, non-entrepreneurs also exhibit social empowerment.

Given the restricted geographical ambit of the study, prudence ought to be exercised in drawing inferences applied to alternate contexts. That the vast majority of questionnaire respondents are illiterate presented a notable impediment in the process of collection of accurate responses.

Microfinance intervention ought to be specifically directed to cultivating entrepreneurship among women; in particular, to achieve the full benefits of empowerment, women availing microfinance ought to exert full control over their own business ventures.

In analyzing holistic empowerment through microfinance supported businesses set up by women, the study adds to the existing literature on women entrepreneurship and empowerment.

The COVID-19 pandemic has generated a crisis that has hit the European economy and the currently existing systems. To cope with the crisis, Europe has started an investment aiming the energy transition and crisis. Portugal, Spain and Greece have received the approval of their National Recovery Plans from the European Commission, with a definition of spending up to 2026 through the European Union (EU) Next Generation Found. The study investigates whether the Green Deal policies are relaunched by the plans financed and whether the pandemic has changed and conditioned the priorities of the energy transaction. The study uses the lens of corporate social responsability (CSR) and relapse measurable across the Sustainable Development Goals (SDGs).

The Green Deal policies supported by new European investments in the three countries were analyzed through a content analysis (CA) technique to investigate the associated practical and theoretical elements.

The energy theme has a relevance compared to other issues in the investment plans envisaged in Greece, Portugal and Spain. The analysis highlights energy efficiency, sustainable energy and reduction of consumption among the main themes. Energetically, sustainable building plays a central role. The study highlights the relationship between Green Deal policies, CSR, SDGs and management tools adopted.

The study strengthens the relationship between the Green Deal, CSR and SDGs by identifying policies that have already been implemented and theoretical and practical gaps on which politicians and scholars will have to investigate and support in the process of development and continuity of the identified pillars.

With recent advances in additive manufacturing (AM), polymer-based three-dimensional (3D) printers are available for relatively low cost and have found their way even in domestic and educational uses. However, the optimum conditions for processing and post-processing of different materials are yet to be determined. The purpose of this paper is to examine the effects of printing temperature, pattern and annealing conditions on tensile strength and modulus of samples printed with polylactic acid (PLA).

This study focuses on fused deposition modelling according to ISO/ASTM 52900 material extrusion AM. To print parts with maximum mechanical properties, the printing variables must be optimised. To determine the printing and annealing condition on physical and mechanical properties of PLA-based parts, dogbone-shaped tensile samples were printed at four different nozzle temperatures and five different filling patterns embedded in a 3D printing software. The samples were further annealed at three different temperatures for three different time intervals. The mechanical properties were evaluated and the changes in mechanical properties were analysed with the help of rheometrical measurements.

The results showed that printing condition has a significant influence on final properties, for example, the strain at break value increases with increasing nozzle temperature from 34 to 56 MPa, which is close to the value of the injected sample, namely, 65 MPa. While tensile strength increases with printing temperature, the annealing process has negative effects on the mechanical properties of samples.

The authors observed that traditional findings in polymer science, for example, the relationship between processing and annealing temperature, must be re-evaluated when applied in 3D printing because of major differences in processing conditions resulting from the layer-by-layer manufacturing.