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Purpose: Previous research identified a measurement gap in the individual assessment of social misconduct in the workplace related to gender. This gap implies that women respond to comparable self-reported acts of bullying or sexual discrimination slightly more often than men with the self-labeling as “bullied” or “sexually discriminated and/or harassed.” This study tests this hypothesis for women and men in the scientific workplace and explores patterns of gender-related differences in self-reporting behavior.

Basic design: The hypotheses on the connection between gender and the threshold for self-labeling as having been bullied or sexually discriminated against were tested based on a sample from a large German research organization. The sample includes 5,831 responses on bullying and 6,987 on sexual discrimination (coverage of 24.5 resp. 29.4 percentage of all employees). Due to a large number of cases and the associated high statistical power, this sample for the first time allows a detailed analysis of the “gender-related measurement gap.” The research questions formulated in this study were addressed using two hierarchical regression models to predict the mean values of persons who self-labeled as having been bullied or sexually discriminated against. The status of the respondents as scientific or non-scientific employees was included as a control variable.

Results: According to a self-labeling approach, women reported both bullying and sexual discrimination more frequently. This difference between women and men disappeared for sexual discrimination when, in addition to the gender of a person, self-reported behavioral items were considered in the prediction of self-labeling. For bullying, the difference between the two genders remained even in this extended prediction. No statistically significant relationship was found between the frequency of self-reported items and the effect size of their interaction with gender for either bullying or sexual discrimination. When comparing bullying and sexual discrimination, it should be emphasized that, on average, women report experiencing a larger number of different behavioral items than men.

Interpretation and relevance: The results of the study support the current state of research. However, they also show how volatile the measurement instruments for bullying and sexual discrimination are. For example, the gender-related measurement gap is considerably influenced by single items in the Negative Acts Questionnaire and Sexual Experience Questionnaire. The results suggest that women are generally more likely than men to report having experienced bullying and sexual discrimination. While an unexplained “gender gap” in the understanding of bullying was found for bullying, this was not the case for sexual discrimination.

The purpose of this paper is to explore the career shocks that young, newly graduated entrepreneurs experience in the process of starting a business.

The study adopted a qualitative approach, drawing upon 25 semi-structured interviews with entrepreneurs who recently graduated from university (up to the age of 30) in different European countries.

The analysis identifies several career shocks that can confront entrepreneurs before and after starting a business and reveals how these shocks influence graduates’ decisions to become and continue to be an entrepreneur.

The study sheds light on the diverse nature of career shocks and the importance of integrating agency concepts and environmental influences in career research. It identifies important factors relevant for school-to-work transition research and complements work in entrepreneurship research on necessity and opportunity entrepreneurship, push and pull motives, and entrepreneurial intentions.

Organizations can use the findings to attract and retain young entrepreneurial employees, while higher education organizations can use the findings to better prepare students for a successful transition into entrepreneurship, whether in the corporate or independent form.

The paper integrates the concept of career shocks with literature on entrepreneurship and offers a categorization of career shocks in the pathway to entrepreneurship.

The growth of online communities and social media has led to a growing need for methods, concepts, and tools for researching online cultures. Particular attention should be paid to polarizing online discussion cultures and dynamics that increase inequality in online environments. Social media has enormous potential to create good, but in order to unlock its full potential, we also need to examine the mechanisms keeping these spaces monotonous, homogenous, and even hostile toward some groups. With this need in mind, I have developed the concept and theory of othering online discourse (OOD).

This chapter introduces and defines the concept of OOD and explains the key characteristics and different attributes of OOD in relation to other concepts that deal with disruptive and discriminatory behavior in online spaces. The attributes of OOD are demonstrated drawing on examples gathered from the Finnish Suomi24 (Finland24) forum.

A common understanding of what events to regard as production disturbances (PD) are essential for effective handling of PDs. Therefore, the purpose of this paper is to answer the two questions: how are individuals with production or maintenance management positions in industry classifying different PD factors? Which factors are being measured and registered as PDs in the companies monitoring systems?

A longitudinal approach using a repeated cross-sectional survey design was adopted. Empirical data were collected from 80 companies in 2001 using a paper-based questionnaire, and from 71 companies in 2014 using a web-based questionnaire.

A diverging view of 21 proposed PD factors is found between respondents in manufacturing industry, and there is also a lack of correspondence with existing literature. In particular, planned events are not classified and registered to the same extent as downtime losses. Moreover, the respondents are often prone to classify factors as PDs compared to what is actually registered. This diverging view has been consistent for over a decade, and hinders companies to develop systematic and effective strategies for handling of PDs.

There has been no in-depth investigation, especially not from a longitudinal perspective, of the personal interpretation of PDs from people who play a central role in achieving high reliability of production systems.

The key concern nowadays is smartphone addiction and user profiles. Following the risk and protective factors framework, the authors aim to characterize smartphone users according to two levels: (1) individual: referred to the use (i.e. boredom proneness, compulsive app downloading smartphone addiction) and (2) microsystem: referred to family and peers (i.e. family harmony and phubbing). Besides, the authors will derive useful managerial implications and strategies.

First, an extensive literature revision and in-depth interviews with experts were employed to identify the addiction-related variables at the individual and microsystem level. Second, information was collected from a sample of 275 Spanish smartphone users, and a K-means clustering algorithm was employed to classify smartphone users.

The proposed traffic lights schema identifies three users’ profiles (red, yellow and green) regarding their smartphone addiction and considering individual and microsystem critical variables.

This study proposes a practical and pioneer traffic lights schema to classify smartphone users and facilitate each cluster's strategies development.

一個大家現時頗關注的事項就是智慧型手機癮和用戶檔案。遵循著風險和保護因子框架,我們擬根據兩個層面,去描述智慧型手機使用者的特性:(一) 個人層面: 這是指手機的使用方面 (即是:無聊傾向、強制性應用程式的下載、智慧型手機癮), 以及(二)微系統層面:這是指家庭和同儕 (即是:家庭和諧和低頭族)。此外,我們也會探討從中得到管理方面的啟示和一些有用的策略。

我們首先進行廣泛的文獻回顧和深入訪問有關的專家,以確定在個人和微系統層面上與入迷成癮有關的變數。繼而從275名西班牙智慧型手機使用者中收集資料,然後以K均值聚類算法把智慧型手機使用者分類。

我們提出的紅綠燈圖表,就用戶的智慧型手機癮,並考慮了個人和微系統的關鍵變數,識別了三個用戶檔案(紅、黃、綠)。

本研究提出一個實用及有倡導性的紅綠燈圖表,把智慧型手機使用者分類,並促進每個群集戰略的制定。

This study aims to propose an innovative model that integrates variables and examines the influence of internet usage expertise, perceived risk and attitude toward information control on privacy concerns (PC) and, consequently, in consumers’ willingness to disclose personal information online. The authors also propose to test the mediation role of trust between PCs and willingness to disclose information. Trust is not a predictor of PC but a causal mechanism – considering that the focus is to understand consumers’ attitudes and behavior regarding the virtual environment (not context-specific) (Martin, 2018).

The authors developed a survey questionnaire based on the constructs that compose the proposed model to collect data from 864 respondents. The survey questionnaire included the following scales: internet usage expertise from Ohanian (1990); perceived risk, attitude toward information control, trust and willingness to disclose personal information online from Malhotra et al. (2004); and PC from Castañeda and Montoro (2007). All items were measured on a Likert seven-point scale (1 = totally disagree; 7 = totally agree). To obtain Westin’s attitudinal categories toward privacy, respondents answered Westin’s three-item privacy index. For data analysis, the authors applied covariance-based structural equation modeling.

First, the proposed model explains the drivers of consumers’ disposition to provide personal information at a level that surpasses specific contexts (Martin, 2018), bringing the analysis to consumers’ level and considering their general perceptions toward data privacy. Second, the findings provide inputs to propose a better definition of Westin’s attitudinal categories toward privacy, which used to be defined only by individuals’ information privacy perception. Consumers’ perceptions about their abilities in using the internet, the risks, their beliefs toward information control and trust also help to delimitate and distinguish the fundamentalists, the pragmatics and the unconcerned.

Some limitations weigh the theoretical and practical implications of this study. The sample size of pragmatic and unconcerned respondents was substantially smaller than that of fundamentalists. It might be explained by applying Westin’s self-report index to classify the groups according to their score regarding PCs. Most individuals affirm having a great concern for their data privacy but still provide online information for the benefit of personalization – known as the privacy paradox (Zeng et al., 2021). It leads to another limitation of this research, given the lack of measures that classify respondents by considering their actual behavior toward privacy.

PC emerges as an important predictor of consumer trust and willingness to disclose their data online, and trust also influences this disposition. Managers need to implement actions that effectively reduce consumers’ concerns about privacy and increase their trust in the company – e.g. adopting a clear and transparent policy on how the data collected is stored, treated, protected and used to benefit the consumer. Regarding the perception of risk, if managers convince consumers that the data collected on the internet is protected, they tend to be less concerned about privacy.

The results suggest different aspects influencing the willingness to disclose personal information online, including different responses considering consumers’ PCs. Through their policies and legislation, the authors understand that governments must be attentive to this aspect, establishing regulations that protect consumers’ data in the virtual environment. In addition to regulatory policies, education campaigns can be carried out for both consumers and managers to raise the discussion about privacy and the availability of information in the online environment, demonstrating the importance of protecting personal data to benefit the government, consumers and organizations.

Although there is increasing research on consumers’ privacy, studies have not considered their attitudinal classifications – high, moderate and low concern – as moderators of willingness to disclose information online. Researchers have also increased attention to the antecedents of PCs and disclosure of information but overlooked possible mechanisms that explain the relationship between them.

The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics.

A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model.

The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods.

This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.

Purpose: The study elaborates the contextual conditions of the academic workplace in which gender, age, and nationality considerably influence the likelihood of self-categorization as being affected by workplace bullying. Furthermore, the intersectionality of these sociodemographic characteristics is examined.

Basic Design: The hypotheses underlying the study were mainly derived from the social role, social identity, and cultural distance theory, as well as from role congruity and relative deprivation theory. A survey data set of a large German research organization, the Max Planck Society, was used. A total of 3,272 cases of researchers and 2,995 cases of non-scientific employees were included in the analyses performed. For both groups of employees, binary logistic regression equations were constructed. the outcome of each equation is the estimated percentage of individuals who reported themselves as having experienced bullying at work occasionally or more frequently in the 12 months prior to the survey. The predictors are the demographic and organization-specific characteristics (hierarchical position, scientific field, administrative unit) of the respondents and selected interaction terms. Using regression equations, hypothetically relevant conditional marginal means and differences in regression parameters were calculated and compared by means of t-tests.

Results: In particular, the gender-related hypotheses of the study could be completely or conditionally verified. Accordingly, female scientific and non-scientific employees showed a higher bullying vulnerability in (almost) all contexts of the academic workplace. An increased bullying vulnerability was also found for foreign researchers. However, the patterns found here contradicted those that were hypothesized. Concerning the effect of age analyzed for non-scientific personnel, especially the age group 45–59 years showed a higher bullying probability, with the gender gap in bullying vulnerability being greatest for the youngest and oldest age groups in the sample.

Interpre4tation and Relevance: The results of the study especially support the social identity theory regarding gender. In the sample studied, women in minority positions have a higher vulnerability to bullying in their work fields, which is not the case for men. However, the influence of nationality on bullying vulnerability is more complex. The study points to the further development of cultural distance theory, whose hypotheses are only partly able to explain the results. The evidence for social role theory is primarily seen in the interaction of gender with age and hierarchical level. Accordingly, female early career researchers and young women (and women in the oldest age group) on the non-scientific staff presumably experience a masculine workplace. Thus, the results of the study contradict the role congruity theory.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

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.