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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.

This paper aims to formulate a hedonic pricing model for Japanese rice wine, sake, via hierarchical Bayesian modeling estimated using an efficient Markov chain Monte Carlo (MCMC) method. Using the estimated model, the authors examine how producing regions, rice breeds and taste characteristics affect sake prices.

The datasets in the estimation consist of cross-sectional observations of 403 sake brands, which include sake prices, taste indicators, premium categories, rice breeds and regional dummy variables. Data were retrieved from Rakuten, Japan’s largest online shopping site. The authors used the Bayesian estimation of the hedonic pricing model and used an ancillarity–sufficiency interweaving strategy to improve the sampling efficiency of MCMC.

The estimation results indicate that Japanese consumers value sweeter sake more, and the price of sake reflects the cost of rice preprocessing only for the most-expensive category of sake. No distinctive differences were identified among rice breeds or producing regions in the hedonic pricing model.

To the best of the authors’ knowledge, this study is the first to estimate a hedonic pricing model of sake, despite the rich literature on alcoholic beverages. The findings may contribute new insights into consumer preference and proper pricing for sake breweries and distributors venturing into the e-commerce market.

This paper aims to analyse the effect of the investment duration, the overall market condition and the industry to which the investee firm belongs on exit returns realised by venture capital (VC) firms invested in Indian market, using hierarchical regression models.

The study examines the relationship that exist among the variables of interest by analysing all the 210 exits that happened in the Indian VC market over the period 2004–2017 by using analytical tools such as moving averages, hierarchical regressions and pooled ordinary least squares regression.

Exit return has an approximate U-shaped relationship with investment duration, and the turning point in the convex relationship happens around seven to eight years after investment. Returns are weakly related to the market condition, discarding the market timing hypothesis. Relationship patterns are found to be generally unvarying during the time period under study.

The results indicate VC funds in the Indian market tend to exit in a brief time span and gain substantial returns from the immediate exits beyond, which returns start dipping. This points to the illiquidity of the Indian VC market wherein the exits from “lemons” are quite tricky, which make them remain invested for longer durations and eroding the value substantially in the process. VC funds may make rational investment/exit decisions in the Indian market capitalising this knowledge.

This study empirically connects the value creating factors in a VC process to the established theories about the early stage investments and analyse the applicability and relevance of those theories in a market with high growth potential like India.

The main purpose of this study is to investigate the factors affecting e-trust perception of tourists using Web-based travel intermediaries (WBTIs). Cognitive and affective attitude components are believed to be important in assessing the e-trust perception of tourists. However, this paper aims to investigate if self-efficacy would be an important predictor for e-trust in the context of WBTIs.

The quantitative research method is used in this study. Data were collected by the survey method from the tourists who visited Istanbul/Turkey and made their bookings via Web-based travel intermediaries. Hierarchical linear regression analysis is used to investigate to which extent age/gender/years of usage, self-efficacy, cognitive and affective components are affecting tourists’ e-trust perception.

According to the study results, self-efficacy, the attitude components, in addition to the demographic variables, predict a significant amount of variance (45%) in e-trust for Web-based travel intermediaries. Besides attitude components, self-efficacy is put forward as significantly important in the perception of e-trust.

The novelty of the current study is that it uses hierarchical regression to test if self-efficacy would be an important predictor for e-trust while examining the effect of various predictive variables in sequential order. Therefore, the relative importance of this e-trust predictor can be evaluated based on how much it contributes to the prediction over and above other important antecedents of e-trust according to the literature. This study provides evidence that the social cognitive theory may be useful in understanding e-trust in online tourist behavior.

论网络旅游中介的网络信任的原因：调研伊斯坦布尔游客

本论文旨在调研影响网络旅游中介（WBTIs）的游客网络信任的各项因子。认知与态度因素是形成游客的网络信任的重要方面。然而, 本论文旨在研究是否自我效能感对于WBTIs的网络信任构成重要的影响因子。

本论文采用定量分析法。数据采用问卷形式采集, 样本人群为伊斯坦布尔/土耳其的游客, 他们通过网络旅游中介订购他们的旅程。本论文采用层次回归分析法来检测年龄/性别/使用年份, 自我效能感, 认知与态度因子, 在何种程度上影响旅游的网络信任感知。

研究结果表明, 自我效能感, 态度成分, 以及人口统计变量, 解释了WBTIs网络信任的45%变量方差。除了态度因子, 系我效能对于网络信任起到显著的促进作用。

本论文的特别之处在于其使用了层次回归分析法检测了是否自我效能感对于影响网络信任, 同时又检验了各种预测变量作用的大小层次。因此, 每个信任预测因子的作用大小可以根据其对预测方差的大小比较来判断。本论文提出社会认知理论对理解在线旅游行为的网络信任有着显著帮助。

The purpose of this paper is to provide a greater understanding of the general practitioner (GP)-patient relationship for academics and practitioners. A new model for dyadic professional relationships specifically designed for research into the doctor-patient relationship was developed and tested. Various conceptual models of trust and related constructs in the literature were considered and assessed for their relevance as were various related scales.

The model was designed and tested using purposefully designed scales measuring doctors’ trustworthiness, practice orientation performance and patient satisfaction. A quantitative survey used closed-ended questions and 372 patients responded from seven GP practices. The sample closely reflected the profile of the patients who responded to the DoH/NHS GP Patient Survey for England, 2010.

Hierarchical regression and partial least squares both accounted for 74 per cent of the variance in “overall patient satisfaction”, the dependent variable. Trust accounted for 39 per cent of the variance explained, with the other independent variables accounting for the other 35 per cent. ANOVA showed good model fit.

The findings on the factors which affect patient satisfaction and the doctor-patient relationship have direct implications for GPs and other health professionals. They are of particular relevance at a time of health reform and change.

The paper provides: a new model of the doctor-patient relationship and specifically designed scales to test it; a greater understanding of the effects of doctors’ trustworthiness, practice orientation and performance on patient satisfaction; and a new framework for examining the breadth and meaning of the doctor-patient relationship and the management of care from the patient’s viewpoint.

There is general agreement among researchers and practitioners that satisfaction is relative to competitive alternatives. Nonetheless, researchers and managers have not treated satisfaction as a relative construct. The result has been weak relationships between satisfaction and share of wallet in the literature, and challenges by managers as to whether satisfaction is a useful predictor of customer behavior and business outcomes. The purpose of this paper is to explore the best approach for linking satisfaction to share of wallet.

Using data from 79,543 consumers who provided 258,743 observations regarding the brands that they use (over 650 brands) covering 20 industries from 15 countries, various models such as the Wallet Allocation Rule (WAR), Zipf-AE, and Zipf-PM, truncated geometric model, generalization of the WAR and hierarchical regression models are compared to each other.

The results indicate that the relationship between satisfaction and share of wallet is primarily driven by the relative fulfillment customers perceive from the various brands that they use (as gauged by their relative ranked satisfaction level), and not the absolute level of satisfaction.

The findings provide practical insight into several easy-to-use approaches that researchers and managers can apply to improve the strength of the relationship between satisfaction and share of wallet.

This research provides support to the small number of studies that point to the superiority of using relative metrics, and encourages the adoption of relative satisfaction metrics by the academic community.

Although the use of data from different levels is very common in international marketing research, the practice of employing multi‐level analysis techniques is relatively new. The paper aims to provide an application of a specific case of multi‐level modelling – where the dependent variable is dichotomous, which is often the case in marketing research (e.g. whether a consumer buys the brand or not, whether he/she is aware of the brand or not, etc.)

A hierarchical generalized linear model is employed.

Since this is a technical paper, the authors would like to emphasize the process rather than the empirical findings. In summary, the paper: provides a brief theoretical overview of Hierarchical Linear Modeling and Hierarchical Generalized Linear Modeling; illustrates the application of the method using the domains of consumers within countries and a dichotomous dependent variable; focuses on interpretation of log‐odds results; and concludes with practical issues and research implications.

The main value of this research is to demonstrate how to employ multi‐level models when the dependent variable is dichotomous. Multi‐level techniques are quite new in international marketing research, although nested data structures are relatively common in our field. This is a technical paper that guides the researchers as to how to apply and interpret the results when modeling such data with a dichotomous dependent variable.

The purpose of this paper is to track changes in organizational and occupational stress in the Finnish police force during the police reform years. It also estimates the effects of organizational stressors on labor turnover intention (LTI).

The study is based on six distinct cross-sectional Police Personnel Surveys from 1999 to 2012. The surveys are not sample based, but have targeted the entire police force with good response rates. The study employs hierarchical logit models to predict LTI.

Police agencies can be depicted as hierarchical frontline organizations. Major reforms in such agencies can be expected to give rise to increased organizational conflicts and stress. The empirical findings of the paper fall in line with the theory. Organizational stress and LTI have been increasing in the Finnish police force during the police reform years. However, at the same time, personal and occupational stressors have actually been reducing in the police force. Turnover intention was observed to be a positive function of those particular organizational stressors that have increased the most over the reform years.

The data are cross-sectional. No direct causal conclusions can be drawn from the results of this study. A non-material violation of the linearity assumption was detected in two logit models.

Relying on Tops and Spelier's 2013 theory of police organizations as frontline organizations, the paper introduces a new theoretical construct – hierarchical frontline organization – and combines its theoretical ideas with comprehensive long-term data from the Finnish police force.

The importance of the performance of a firm and the essential role played by the management in their accomplishment has been discussed and recognised by many researchers from Drucker to Upper Echelon Theory. Nonetheless, currently, anybody has been able to determine the precious and reliable parameters which let the firm achieve required-level performance. The confusion around this objective is still sufficient and the controversial has being growing widely over time, being the findings achieved contradictory, insufficient, imprecise and unreliable. Regarding the demographical literature findings focus on the premises previous related to Upper Echelon Theory. The purpose of this paper is to go further and try to test how, not only the level, but also the diversity of constructs like top management teams (TMT)'s demographic characteristics influence the firm performance accomplished by the managers by applying a Hierarchical Linear Regression Model.

Based on primary data from two Spanish databases – SABI, CNMV – and secondary data, a sample size of 147 TMTs in large companies from 18 industries sector with headquarters in Spain over a four years period (2004-2007) were obtained. The analysis focused on the total TMT for each firm. To test the relationship between the company performance and the demographic constructs, a more recent methodology based on hierarchical linear models (HLMs) using a longitudinal dataset of multinational big firms with headquarters in Spain was applied.

After applying the statistical techniques the results show a partial confirmation of the hypotheses formulated in the theoretical model proposed. First, the analysis evidences that company size is both highly correlated with TMT size and their demographic variables in terms of diversity. Second, the HLM shows that TMT's education-level diversity has a negative and significant impact on corporate performance and no significant effects for functionality and education background diversity have been found. Based on the accomplished findings, organisations appear to be more concerned about the employee's education level rather than their education background. Moreover, the model further supports that companies seem to be more aware of industry experience diversity than functionality diversity, also confirming a greater influence of the more international experience diversity of TMT on corporate performance.

This study offers a significant contribution not only by specifying a three-level hierarchical regression models regarding diverse approaches to measure the performance variable as dependent variable but also by considering as predictors not only the level of the demographic variables but also their diversity. This knowledge is relevant for entrepreneurial purposes since it highlights the achievement of high performance. The results allow us to explain which constructs influence the achievement of firm performance. Thus, this knowledge could be relevant to the entrepreneurs to encourage the firm survival and growth. Furthermore, focused on an ambitious purpose, it reveals the parameters needed to achieve to get the optimums performance level. Hence, the present study contributes an attempt to advance the literature on TMT composition by applying multi-level theory given the nested structure of the data set. The paper is one of few studies which apply panel data to analyse the influences of TMT characteristics on corporate performance and one of the first focused on Spanish entrepreneurial context.