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It is typical of public real estate benchmarking reports to show only highly aggregated benchmarks based on buildings’ floor areas. They hardly provide disaggregated benchmarks for usage clusters. The aim of this study is to show the caveats from highly aggregated benchmarking without consideration of cluster-specific characteristics.

Based on the parameters of the German facility management association 812 standards, cleaning costs and costs for the surfaces of seven hospitals have been collected and allocated to specific room clusters. Using these basic data, a calculation and simulation conducted with the aim of simulating facilities that are comparable in the sum of costs yet feature varying sub-clusters as cost drivers. In particular, during this simulation, area ratios were varied randomly and the average cleaning costs per cluster were held constant for all hospitals. Therefore, the costs per square meter in the clusters of all simulated hospitals are identical and the full costs only depend on the area ratios.

The simulation shows that highly aggregated cleaning costs lead to large spans, and thus, to misinterpretations in the field of action. In the case, the aggregate benchmark ranges from 40.6 to 66.5 EUR/m², although, for all hospitals the same costs per square meter had been used. Thus, the bias results only from varying the share of area across the clusters. This finding is caused by a well-known statistical problem: the Simpson’s paradoxon, which currently receives little attention in real estate benchmarking.

The results show, that the regular benchmarking with high aggregated data, often used in practice, cannot be recommended. The author consider using a detailed benchmarking as meaningful and purposeful. To be able to make a detailed benchmarking, it is essential to identify and collect the influencing factors. Only if all important factors, in this case, the clusters will be regarded in the benchmarking, a reasonable benchmarking and useful interpretation can be given. Using a simple benchmarking to get a rough overview is refused steadfastly.

The study highlights that a comparison with public benchmarking reports (operation costs) must be taken with great caution. The author has quantified the bias from the aggregated benchmarking and have shown, that the Simpson’s paradox fully explains the consequences.

This study aims to draw on the categorization theory to explore the mediating role of customer qualification skills in explaining how social media use in sales contributes to salespeople’s adaptive selling behaviors to achieve high sales performance in export selling. The study also integrates network effect theory and social linguistics theory to identify the specific social media platform (Facebook versus non-Facebook) and the characteristics of salespeople in terms of English language proficiency, which play a facilitating role in promoting the effectiveness of social media use in export sales.

The sampling frame of the research is a list of Chinese export salespersons obtained on the FOB Business Forum website. Survey data were obtained from 873 Chinese export salespeople. Partial least squares structural equation modeling was performed to analyze the data.

Social media use in sales is associated positively with customer qualification skills and adaptive selling behaviors. Moreover, the results revealed a partial mediating effect of customer qualification skills on the positive impact of social media use in sales on adaptive selling behaviors. The moderating effect analysis found that the positive association between social media use in sales and customer qualification skills was stronger in export salespeople who used Facebook and had mastered a high level of English language proficiency.

This study provides new findings, based on data collected from salespeople in Mainland China, that support the effectiveness of social media use in an export sales context. Moreover, the study advances prior research by showing that the effectiveness of social media use still depends on the type of social media used and the English language proficiency of the salespeople.

J-curve relationship analyses can provide valuable insights to information systems (IS) researchers. This paper aims to discuss moderated mediation in IS research and the related emergence of J-curve relationships.

Building on an illustrative study in the field of IS, the author Lays out three steps to combine moderation and J-curve analyses, with the goal of more fully understanding the underlying moderated mediation relationships. The paper proposes a new segmentation delta method to test for J-curve emergence, as part of this framework.

The paper shows, in the context of this study, the complementarity of moderation and J-curve analyses.

Currently, IS researchers rarely conduct moderation and J-curve analyses in a complementary way, even though there are software tools, and related methods, which allow them to do so in a relatively straightforward way.

The analyses were conducted with the software WarpPLS, a widely used tool that allows for moderated mediation and J-curve analyses, in a way that is fully compatible with the set of steps presented in this paper.

Evidence for adverse impact in applied, organizational settings can often depend on application of the “four-fifths rule.” We analyze the arithmetic four-fifths rule, its operationalization, and related statistical tests. We note that the rule has intuitive appeal and has arithmetic directness. On the other hand, the four-fifths rule contains many ambiguities because of the manner in which it is defined, as well as its use in practice. One purpose of this article is to discuss the arithmetic and statistical facets of the definition. A related purpose of this article is to demonstrate where the ambiguities (and possibly unintended consequences) with the four-fifths rule might arise when numerical interpretations are invoked. Implications for future research and academic dialogues are then noted.

This study aims to examine the impact of managerial use of motivating language on employee absenteeism, turnover intention, job satisfaction and job performance for employees from three nations: India, the USA and Vietnam.

Data is collected from 614 employees working in India, the USA and Vietnam. A variance-based partial least squares structural equation modeling technique is used to test the hypotheses. In addition, a statistical test is used to examine the statistical differences in the results across the three nations.

The findings are consistent with the motivating language theory, in that managerial use of motivating language can be an effective strategy in motivating employees. Specifically, motivating language is found to significantly decrease employee absenteeism and turnover intention, as well as significantly increase job satisfaction and performance across the three nations. The effect sizes indicate that, across all samples, motivating language has a medium effect for all employee outcomes, except absenteeism, which is shown to have a small effect size. Moreover, the results indicate that employees in different cultures perceive and interpret the leader’s use of motivating language in different ways. Whereas motivating language may receive greater success in promoting workers’ job performance in eastern cultures, it is also more effective in retaining employees in western cultures.

The study adds to the literature in three major ways. First, it provides evidence for two understudied relationships: motivating language and absenteeism and motivating language and turnover intention. Second, it assesses the generalizability of the motivating language theory by investigating data from India, the USA and Vietnam. Finally, this paper offers a statistical comparison of the three samples to analyze how the relationship between motivating language and worker outcomes differ among the three samples.

Gives the constructions of a general system on its object set and on its set of fundamental objects. Discusses some methodological implications of the constructions. Lists several examples to show that human sense organs are limited in the comprehension of the surrounding nature.

The purpose of this paper is to reveal factors that drive the adoption and use of unified communications and collaboration (UC&C) technology in organizations.

The authors used quantitative method to survey 296 employees from 50 different countries by conducting and international study. Partial least squares -method was used for the latent variables latent variable analysis

The authors found that unified theory of acceptance and use of technology constructs are mainly validated where results suggests that performance expectancy and social influence are the most influential drivers in employee acceptance and use of UC&C in organizations. Social presence, influence of peers and superiors are the main factors to take into consideration when implementation UC&C technology.

The study was not longitudinal in design, which should be addressed by a future study that includes multi-cultural dimensions with a longitudinal design

Awareness through education and training of employees needs to be given very particular attention in the future mobile implementations. Moreover, management and employee support is the critical component of the effective information security governance framework implementation. Finally, mobile strategy needs to go over very precise and detailed planning process to ensure the right technology acceptance by users.

The authors close the existing research gap by providing useful insights into organizations regarding their UC&C technology adoption and use factors

In this paper, the authors emphasize that COVID-19 pandemic is a serious pandemic as it continues to cause deaths and long-term health effects, followed by the most prolonged crisis in the 21st century and has disrupted supply chains globally. This study questions “can technological inputs such as big data analytics help to restore strength and resilience to supply chains post COVID-19 pandemic?”; toward which authors identified risks associated with purchasing and supply chain management by using a hypothetical model to achieve supply chain resilience through big data analytics.

The hypothetical model is tested by using the partial least squares structural equation modeling (PLS-SEM) technique on the primary data collected from the manufacturing industries.

It is found that big data analytics tools can be used to help to restore and to increase resilience to supply chains. Internal risk management capabilities were developed during the COVID-19 pandemic that increased the company's external risk management capabilities.

The findings provide valuable insights in ways to achieve improved competitive advantage and to build internal and external capabilities and competencies for developing more resilient and viable supply chains.

To the best of authors' knowledge, the model is unique and this work advances literature on supply chain resilience.

Various authors allege that the theory of group selection is inconsistent with methodological individualism, and therefore analysts must reject at least one of these principles. The present article argues for their compatibility. The meaning of methodological individualism is clarified, and the new version of group selection (articulated by Wilson & Sober, 1994, 1998) is explained. The two principles are then incorporated into a single methodological approach. Group selection affects the assumptions made about the kind of individuals who populate social scientific models, while methodological individualism requires models’ conclusions to follow from the actions and interactions of those individuals.

IT security compliance is critical to the organization’s success, and such compliance depends largely on IT leadership. Considering the prevalence of unconscious gender biases and stereotyping at the workplace and growing female leadership in IT, the authors examine how the internalization of stereotype beliefs, in the form of the employee’s gender, impacts the relationships between leadership characteristics and IT security compliance intentions.

A controlled experiment using eight different vignettes manipulating Chief Information Officer (CIO) gender (male/female), Information Technology (IT) expertise (low/high) and leadership style (transactional/transformational) was designed in Qualtrics. Data were gathered from MTurk workers from all over the US.

The findings suggest that both CIOs' and employees' gender play an important role in how IT leadership characteristics – perceived expertise and leadership style – influence the employees' intentions and reactance to comply with CIO security recommendations.

This study's findings enrich the security literature by examining the role of leadership styles on reactance and compliance intentions. They also provide important theoretical implications based on gender stereotype theory alone: First, the glass ceiling effects can be witnessed in how men and women employees demonstrate prejudice against women CIO leaders through their reliance on perceived quadratic CIO IT expertise in forming compliance intentions. Secondly, this study's findings related to gender role internalization show men and women have a prejudice against gender-incongruent roles wherein women employees are least resistive to transactional male CIOs, and men employees are less inclined to comply with transactional female CIOs confirm the findings related to gender internationalization from Hentschel et al. (2019).

This study highlights the significance of organizations and individuals actively promoting gender equality and fostering environments that recognize women's achievements. It also underscores the importance of educating men and women about the societal implications of stereotyping gender roles that go beyond the organizational setting. This research demonstrates that a continued effort is required to eradicate biases stemming from gender stereotypes and foster social inclusion. Such efforts can positively influence how upcoming IT leaders and employees internalize gender-related factors when shaping their identities.

This study shows that more work needs to be done to eliminate gender stereotype biases and promote social inclusion to positively impact how future IT leaders and employees shape their identities through internalization.

This study redefines the concept of “sticky floors” to explain how subordinates can hinder and undermine female leaders, thereby contributing to the glass ceiling effect. In addition, the study elucidates how gender roles shape employees' responses to different leadership styles through gender stereotyping and internalization.