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The purpose of this paper is to examine FaceReader as a tool to compare the olfactory preferences of two selected countries. This paper examines the olfactory preferences of customers in the bakery department of a grocery store in the Slovak and the Spanish market.

The aim of this study is to examine subconscious/unconscious preferences in the selection of aromas suitable for the bakery department in the Slovak and the Spanish market. In this case, it is not a classical qualitative sensory testing of the perception of fragrances. The aim is to identify the associations of scents related to the selected sales department through images of the selected aromas. A special platform is used to obtain subconscious/unconscious feedback, which allows online collection of implicit feedback using the software FaceReader 7.

The authors noticed the different moods of the two groups of respondents when they answered the question about what they associate with the smell of bakery products. The Spanish respondents were slightly pleasantly disposed, while the Slovak respondents were slightly unpleasantly disposed. The smell of bakery products evoked more memories and emotions in the Spanish respondents than in the Slovak respondents, which can be explained by the higher pleasant mood. The main contribution of this work lies in the new opportunities to obtain feedback that can be used in marketing research and that rely not only on explicit but also implicit data. The extension of the methodological apparatus to implicit feedback presupposes some form of control of the data collected by the questionnaire. The use of biometric tools can represent an efficient alternative in terms of time and money to the use of neuroimaging tools in the selection/research of aromas for specific stores/departments.

It must be noted that the sample is small, and adequate conclusions cannot be made about entire population. Based on empirical findings and pandemic-related limitations, the authors plan to conduct similar research with real aroma samples and with even larger sample of tested respondents, considering weather, season, olfactory sensitivity (anosmia, hyposmia and normosmia) and participant fatigue (beginning and end of the week).

Today, marketers are facing the greatest challenge of how to attract consumers’ attention. Every individual has a different perception of the shopping environment based on his own experience, beliefs and attitudes. This is why new marketing techniques and approaches are becoming increasingly popular in the marketing environment.

El objetivo de esta investigación es examinar FaceReader como una herramienta para comparar las preferencias olfativas entre dos países. Concretamente, examinamos las preferencias olfativas de los clientes en el departamento de panadería de un supermercado en el mercado eslovaco y español.

El objetivo de este estudio es examinar las preferencias subconscientes/inconscientes en la selección de aromas adecuados para el departamento de panadería en el mercado eslovaco y español. En este caso, no se trata de una prueba sensorial cualitativa clásica de la percepción de fragancias. El objetivo es identificar las asociaciones de olores relacionados con el departamento de ventas seleccionado a través de imágenes de los aromas seleccionados. Se utiliza una plataforma especial para obtener comentarios subconscientes/inconscientes, que permite la recopilación en línea de comentarios implícitos utilizando el software FaceReader 7.

Observamos diferentes estados de ánimo de los dos grupos de encuestados cuando respondieron a la pregunta sobre qué asociaban con el olor de los productos de panadería. Los encuestados españoles estaban ligeramente más predispuestos hacia aromas más agradables, mientras que los encuestados eslovacos estaban ligeramente más predispuestos hacia aromas menos agradables. El olor de los productos de panadería evocó más recuerdos y emociones en los encuestados españoles que en los eslovacos, lo que puede explicarse por el estado de ánimo. La principal contribución de este trabajo radica en las nuevas oportunidades para obtener comentarios que pueden ser utilizados en investigaciones de marketing y que no solo se basan en datos explícitos, sino también implícitos. La ampliación del aparato metodológico para obtener comentarios implícitos presupone algún tipo de control de los datos recopilados mediante el cuestionario. El uso de herramientas biométricas puede representar una alternativa eficiente en términos de tiempo y dinero al uso de herramientas de neuroimagen en la selección/investigación de aromas para tiendas/departamentos específicos.

Debe tenerse en cuenta que la muestra utilizada es pequeña y no se pueden extrapolar conclusiones para toda la población. Basándonos en los resultados empíricos y con las limitaciones relacionadas con la pandemia, planeamos realizar una investigación similar con muestras de aroma reales y con una muestra aún más grande de encuestados, considerando el clima, la temporada, la sensibilidad olfativa (anosmia, hiposmia, normosmia) y la fatiga de los participantes (inicio y fin de semana).

Hoy en día, los profesionales del marketing se enfrentan al gran desafío de cómo atraer la atención de los consumidores. Cada individuo tiene una percepción diferente del entorno de compra basada en su propia experiencia, creencias y actitudes. Es por eso que las nuevas técnicas y enfoques de marketing se están volviendo cada vez más populares en el entorno del marketing.

本文旨在探讨FaceReader在比较斯洛伐克和西班牙两个国家的顾客嗅觉偏好方面的效用。我们以斯洛伐克和西班牙市场一家食品杂货店的面点部门顾客为研究对象, 考察其嗅觉偏好。

本研究的目标是探讨在斯洛伐克和西班牙市场选择适合面点部门的香气时潜在的/无意识的偏好。与传统的定性感官测试不同, 我们旨在通过选定香气的图像识别与选定销售部门相关的气味的联想, 并通过FaceReader 7软件在线收集隐性反馈。

我们观察到两组受访者在回答关于面点产品气味联想时的心境差异。西班牙受访者略带愉悦, 而斯洛伐克受访者略带不悦。西班牙受访者对面点产品的气味引起的记忆和情感更为丰富, 这可能是由更高愉悦心境所解释的。该研究的主要贡献在于提供了在营销研究中利用反馈的新机会, 该反馈不仅依赖于明确的数据, 还依赖于隐性数据。将方法学工具扩展到隐性反馈的前提是以某种形式对问卷收集的数据进行控制。在为特定商店/部门选择/研究香气方面, 相对于使用神经影像工具在时间和金钱方面的花费, 生物测定工具的使用可以作为高效替代。

由于本研究的样本量较小, 因此不能对整个人口做出充分的结论。基于经验发现和受到大流行病限制, 我们计划进行类似研究, 使用真实的香气样本, 并考虑更大规模的受试者样本, 同时考虑到天气、季节、嗅觉敏感度（嗅觉缺失、嗅觉减退、正常嗅觉）和参与者疲劳程度（周初和周末）对受试者的影响。

当今, 营销人员面临着吸引消费者注意的最大挑战。每个个体根据其自身经验、信仰和态度对购物环境有着不同的感知。因此, 在营销环境中, 新的营销技术和方法变得越来越受欢迎。

The purpose of the study is to research the current state of fathers' involvement in childcare during parental leave and to assess attitudes of Russian population towards possible measures that can expand the use of parental leave by fathers in Russia.

The authors conducted a survey of Russian parents with children under the age of 18 months in 2022. The sample accounts for 1,000 people; the survey covered almost all Russian regions.

The authors found that the ideal workload of fathers is not expected to exceed a third of the total parental workload. Russian parents are not ready to admit dissatisfaction with the existing distribution of workload during parental leave. However, an egalitarian demand for greater involvement of fathers in parental responsibilities is forming, and an interest in transforming the parental leave policy is emerging.

The value of the study consists of assessing the effectiveness of measures that may have a beneficial effect on the use of parental leave by fathers, as well as identifying consequences of the possible introduction of mandatory parental leave for fathers.

This paper aims to identify how a public client’s use of control systems (process, output and social control) affect innovation possibilities in construction projects.

Semi-structured interviews about six infrastructure projects were conducted to identify respondents’ views on innovation possibilities. These possibilities were then analyzed from an organizational control perspective within principal–agent relationships between the Swedish Transport Administration (STA) and their contractors.

How the client uses control systems affects innovation possibilities. Relying on process control could negatively affect innovation opportunities, whereas output control could have a positive influence. In addition, social control seems to have a weak effect, as the STA appears not to use social control to facilitate joint innovation. Public clients must comply with the Public Procurement Act and, therefore, retain the requirements specified in the tendering documents. Much of the steering of the execution is connected to the ex ante phase (before signing the contract), which affects innovation possibilities in the design and execution phases for the contractor.

This study was conducted with only one client, thus limiting its generalizability. However, the findings provide an important stepping stone to further investigation into balancing control systems and creating innovation possibilities in a principal–agent relationship.

Although public procurement has increasingly been emphasized as a major potential source of innovation, studying how a public client’s use of organizational control systems affects innovation possibilities in the construction sector has received scant attention.

This paper aims to bridge the extended reality framework and the luxury hospitality literature by providing insights into how immersive technologies using artificial intelligence (AI) can shape luxury value and consumer differentiation.

The authors conducted three experimental studies comparing immersive AI versus traditional hospitality across luxury contexts (hotels, restaurants and spas). Study 1 investigates the effect of immersive AI (vs traditional hospitality) on customers’ behavioral intentions and the need for differentiation using virtual-assisted reality. Study 2 tests the underlying mechanism of the need for differentiation and luxury value in an augmented reality context. Study 3 provides additional support for the proposed underlying mechanism using virtual-assisted reality in luxury hospitality.

The findings reveal that immersive AI (vs traditional) luxury hospitality reduces customers’ behavioral intentions of using such services and perceived luxury value. Moreover, the findings indicate that the intention to use immersive AI (vs traditional) luxury hospitality services is contingent upon customers’ need for differentiation.

The findings have important theoretical and managerial implications for immersive technologies in luxury hospitality. They shed light on the dynamics between integrating immersive AI into luxury hospitality and its impact on customers’ differentiation motives and perceived luxury value. The findings reveal the detrimental effect of using immersive AI (vs traditional hospitality) within this context.

The objective of this study is to explore the impact of a government-supported initiative for operational security, specifically the establishment of the national security emergency industry demonstration base, on the profitability of local publicly traded companies. Additionally, the study investigates the significance of firms' blockchain strategies and technologies within this framework.

Using the differences-in-differences (DID) approach, this study evaluates the impact of China's national security emergency industry demonstration bases (2015–2022) on the profitability of local firms. Data from the China Research Data Service (CNRDS) platform and investor Q&As informed our analysis of firms' blockchain strategy and technology, underpinned by detailed data collection and a robust DID model.

Emergency industry demonstration bases have notably boosted enterprise profitability in both return on assets (ROA) and return on equity (ROE). Companies adopting blockchain strategies and operational technology see a clear rise in profitability over non-blockchain peers. Additionally, the technical operation of blockchain presents a more pronounced advantage than at the strategic level.

We introduced a new perspective, emphasizing the enhancement of corporate operational safety and financial performance through the pathway of emergency industry policies, driven by the collaboration between government and businesses. Furthermore, we delved into the potential application value of blockchain strategies and technologies in enhancing operational security and the emergency industry.

Cyberattacks are becoming increasingly widespread, and cybersecurity is therefore increasingly important. Although the technological aspects of cybersecurity are its best-known characteristics, the cybersecurity phenomenon goes beyond the detection of technological impacts, and encompasses all the dimensions of an organization. This study thus focusses on an additional set of organizational elements. The key elements of cybersecurity organizational readiness depicted here are cybersecurity awareness, cybersecurity culture and cybersecurity organizational resilience (OR). This study aims to qualitatively assess small and medium enterprises’ (SMEs) overall level of organizational cybersecurity readiness.

This study focused on conducting a cybersecurity organizational readiness assessment using a sample of 53 Italian SMEs from the information and communication technology sector. Informed mixed method research, this study was conducted consistent with the principles of the explanatory sequential mixed method design, and adopting a quanti-qualitative methodology. The quantitative data were collected through a questionnaire. Qualitative data were subsequently collected through semi-structured interviews.

Although many elements of the technical aspects of cybersecurity OR have yielded very encouraging results, there are still some areas that require improvement. These include those facets that constitute the foundation of cybersecurity awareness, and, thus, a cybersecurity culture. This result highlights that the areas in need of improvement are exactly those that are most important in fighting against cyber threats via organizational cybersecurity readiness.

Although the importance of SMEs is obvious, evidence of such organizations’ attitudes to cybersecurity are still limited. This research is an attempt to depict the organizational issue related to cybersecurity, i.e. overall cybersecurity organizational readiness.

This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.

We employed fuzzy techniques for order preference by similarity to the ideal solution (FTOPSIS), fuzzy analytical hierarchy process (FAHP), and failure mode effect analysis (FMEA) to determine the causes of defects. To determine the current defect cause identification procedures, time studies, checklists, and process flow charts were employed. The study focuses on the sewing department of a clothing industry in Addis Ababa, Ethiopia.

These techniques outperform conventional techniques and offer a better solution for challenging decision-making situations. Each lean waste’s FMEA criteria, such as severity, occurrence, and detectability, were examined. A pairwise comparison revealed that defect has a larger effect than other lean wastes. Defects were mostly caused by inadequate operator training. To minimize lean waste, prioritizing their causes is crucial.

The research focuses on a case company and the result could not be generalized for the whole industry.

The study used quantitative approaches to quantify and prioritize the causes of lean waste in the garment industry and provides insight for industrialists to focus on the waste causes to improve their quality performance.

The methodology of integrating FMEA with FAHP and FTOPSIS was the new contribution to have a better solution to decision variables by considering the severity, occurrence, and detectability of the causes of wastes. The data collection approach was based on experts’ focus group discussion to rate the main causes of defects which could provide optimal values of defect cause prioritization.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.