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The purpose of this paper is to investigate the impact of factor-based trading strategies on pricing and volume.

The authors employ a regression discontinuity approach to identify abnormalities in volume or pricing around expected portfolio changes. In addition, the authors characterize more granular effects on pricing and volume as a result of portfolio re-classification through Fama and Macbeth (1973) regressions.

The authors find that firms which are predicted to transfer among the factor portfolios of Fama and French (1993) exhibit strong and statistically significant short-term variation in stock price and volume. Short-term returns around the cutoff values comprising SMB and HML tend to be temporarily high if the firm is predicted to move into a long component of a factor-mimicking portfolio, and temporarily low if moving into a short component. Similar results are apparent when examining movement in and out of the 25 size and book-to-market sorted test asset portfolios.

The use of portfolio strategies formulated on the basis of sorting procedures, while once upon a time a niche market in the portfolio management industry, is now ubiquitous. The results of this study raise interesting methodological questions about the pricing implications arising from these common methodologies.

This study makes a number of contributions. First, it contributes to the idea that the publication or dissemination of trading strategies or – more generally – common portfolio sorting methods, leads to effects on pricing and volume through commonly motivated trading pressure. In other words, recipe-like discoveries of advantageous trading strategies lead to a synthetic creation of demand. Second, by noting that a lot of factor-focused trading activity begins around July and August of each year, the study relates to existing literature which documents seasonal variation in stock returns and volume. The findings raise questions about what guides institutional investors’ portfolio allocation decisions and whether these are optimal in aggregate.

Adopting a feminist constructionist perspective, this article proposes an analysis of the micro-level processes and dynamics of interpersonal, gendered, business relationships between female entrepreneurs, therefore constituting an extension to network theory in the women's entrepreneurship research field.

The qualitative research builds on a single, longitudinal case study of a successful, 15-years long collaboration between two female entrepreneurs. Qualitative data were collected over two years, through formal and informal interviews with the entrepreneurs, observations and complementary documentation. The data analysis is based on a grounded theory and narrative approach.

The article proposes a thick narrative of the evolution of the dyadic business relationship, and reveals the power of gender role stereotypes in its progressive formation and development.

The article produces situated knowledge about female entrepreneurs and strong interpersonal business ties. The limitations relate to the specificity of the case analysed, representing the viewpoint of privileged, white, Western, educated and wealthy female entrepreneurs. It therefore does not account for the diversity of women's entrepreneurship.

The article enriches and extends social network theory in the women's entrepreneurship field through analysing how gender is done in discursive and social practices at the interpersonal level. The case also constitutes an illustration of social feminism in women's entrepreneurial practice, challenging dominant gender stereotypes.

Most research on the work conditions and family responsibilities associated with work-family conflict and other measures of mental health uses the individual employee as the unit of analysis. We argue that work conditions are both individual psychosocial assessments and objective characteristics of the proximal work environment, necessitating multilevel analyses of both individual- and team-level work conditions on mental health.

This study uses multilevel data on 748 high-tech professionals in 120 teams to investigate relationships between team- and individual-level job conditions, work-family conflict, and four mental health outcomes (job satisfaction, emotional exhaustion, perceived stress, and psychological distress).

We find that work-to-family conflict is socially patterned across teams, as are job satisfaction and emotional exhaustion. Team-level job conditions predict team-level outcomes, while individuals’ perceptions of their job conditions are better predictors of individuals’ work-to-family conflict and mental health. Work-to-family conflict operates as a partial mediator between job demands and mental health outcomes.

Our findings suggest that organizational leaders concerned about presenteeism, sickness absences, and productivity would do well to focus on changing job conditions in ways that reduce job demands and work-to-family conflict in order to promote employees’ mental health.

We show that both work-to-family conflict and job conditions can be fruitfully framed as team characteristics, shared appraisals held in common by team members. This challenges the framing of work-to-family conflict as a “private trouble” and provides support for work-to-family conflict as a structural mismatch grounded in the social and temporal organization of work.

In the past decade, library literature has witnessed a spate of studies documenting different aspects of Collaborative Virtual Reference Services (CVRS) and a significant amount of valuable information is spread across numerous individual reports. With the support of the Institute for Museum and Library Services, the authors of this chapter undertook a synergistic effort to examine these studies and identify the popular governance models as well as shared challenges and benefits. They conducted a supplementary survey of librarians with personal experience working in CVRS. The authors found that while collaborative structures are myriad, many utilize similar staffing and management strategies. Benefits of CVRS include shared staffing responsibilities, the extension of service hours, professional and community development, access to specialists, and mitigating the risks of a new service, while challenges include answering local questions, cultural differences, and software and technology problems. The literature on CVRS primarily focuses on single collaborations. While these in-depth examinations are valuable, they cannot provide a “big picture” of how libraries may work together to provide a service. As budgets shrink and ICT-facilitated connections grow, collaboration is an option to which many libraries are turning to for the provision of reference as well as other services. The quality of such collaborations may be improved by considering the lessons presented in this chapter, resulting in better service.

The purpose of this paper is to propose a research model in which coworker service sabotage influences hospitality employees’ service creativity via work engagement. It also aims to test the moderating effect of sensitivity to the interpersonal mistreatment of others (SIMO).

A time-lagged questionnaire study was performed in hotels in China. The hypotheses were tested via hierarchical multiple regression.

Coworker service sabotage is indirectly associated with hospitality employees’ service creativity via work engagement. The trait of SIMO buffers the harmful effect of coworker service sabotage.

Although our research design helps mitigate common method bias, it could still exist. Other coworker behaviors that might influence employees were not included in this research. The findings may also be biased due to the restricted sample from China.

Hospitality organizations should take measures to curb service sabotage. Organizations could also provide supportive resources to suppress the negative impacts of coworker service sabotage. Moreover, organizations should motivate those low in SIMO to care more about customers.

The research takes the lead in investigating the outcomes of service sabotage from a third-party perspective. Work engagement is identified as the mechanism for transmitting the impact of coworker service sabotage to employees. Moreover, a new moderator that attenuates the negative effects of coworker service sabotage is found.

The purpose of this chapter was to examine the implementation of a flexible work initiative that attempted to challenge two institutionalized precepts of contemporary white-collar workplaces: the gendered ideal worker norm, with its expectation of the primacy of paid work over family and personal life, and the assumption of managerial control over employees’ schedules and work location.

Using ethnographic and interview data, how the Results Only Work Environment (ROWE) was experienced by employees in four different teams within the Best Buy, Co., Inc. corporate headquarters was explored.

Comparing more and less successful implementation across teams, results suggested that collective institutional work is required for the emergence of new norms, expectations, and legitimated practices. Findings indicated that managers’ task-specific knowledge – their deep experience with the tasks that the team is charged with completing – is a structural condition that facilitates managers’ trust in employees and encourages team experimentation with new practices.

Data for this study was limited to one organization and four teams. Future research should include similar organizational change efforts in other organizations and in larger teams.

These findings may promote a better understanding, among researchers and practitioners, of the importance of manager knowledge and background and how this appears to be key to achieving institutional change.

This research is an example of an innovative approach to workplace flexibility and applies an institutional theory lens to investigate variation in the implementation of organizational change.

This literature review is on advanced computer analytics, which is a major trend in the field of Human Resource Management (HRM). The authors focus specifically on computer-assisted text analysis (CATA) because text data are a prevalent yet vastly underutilized data source in organizations. The authors gathered 341 articles that use, review, or promote CATA in the management literature. This review complements existing reviews in several ways including an emphasis on CATA in the management literature, a description of the types of software and their advantages, and a unique emphasis on findings in employment. This examination of CATA relative to employment is based on 66 studies (of the 341) that bear on measuring constructs potentially relevant to hiring decisions. The authors also briefly consider the broader machine learning literature using CATA outside management (e.g., data science) to derive relevant insights for management scholars. Finally, the authors discuss the main challenges when using CATA for employment, and provide recommendations on how to manage such challenges. In all, the authors hope to demystify and encourage the use of CATA in HRM scholarship.

Despite the pervasiveness of teen-targeted food advertising on social media, little is known about the persuasive elements (or power) found within those ads. This research study aims to engage with the concept of “visual style” to explore the range of visual techniques used in Instagram food marketing to teenagers.

A participatory study was conducted with 57 teenagers, who used a specially designed mobile app to capture images of the teen-targeted food marketing they encountered for seven days. A visual thematic analysis was used to assess and classify the advertisements that participants captured from Instagram and specifically tagged with “visual style”.

A total of 142 food advertisements from Instagram were tagged with visual style, and classified into five main styles: Bold Focus, Bespoke, Absurd, Everyday and Sensory.

This study contributes to an improved understanding about how the visual is used as a marketing technique to capture teenagers’ attention, contributing to the persuasive power of marketing messages.

Food marketing is a significant part of the young consumer’s marketplace, and this study provides new insight into the sophisticated nature of such marketing – revealing the visual styles used to capture the attention of its brand-aware audience.

Much of what we learn from empirical research is based on a specific empirical model(s) presented in the literature. However, the range of plausible models given the data is potentially larger, thus creating an additional source of uncertainty termed: model uncertainty. The purpose of this paper is to examine the effect of model uncertainty on empirical research in HRM and suggest potential solutions to deal with the same.

Using a sample of call center employees from India, the authors test the robustness of predictors of intention to leave based on the unfolding model proposed by Harman et.al. (2007). Methodologically, the authors use Bayesian Model Averaging (BMA) to identify the specific variables within the unfolding model that have a robust relationship with turnover intentions after accounting for model uncertainty.

The findings show that indeed model uncertainty can impact what we learn from empirical studies. More specifically, in the context of the sample, using four plausible model specifications, the authors show that the conclusions can vary depending on which model the authors choose to interpret. Furthermore, using BMA, the authors find that only two variables, job satisfaction and perceived organizational support, are model specification independent robust predictors of intention to leave.

The research has specific implications for the development of HR analytics and informs managers on which are the most robust elements affecting attrition.

While empirical research typically acknowledges and corrects for the presence of sampling uncertainty through p-values, rarely does it acknowledge the presence of model uncertainty (which variables to include in a model). To the best of the authors’ knowledge, it is the first study to show the effect and offer a solution to studying total uncertainty (sampling uncertainty + model uncertainty) on empirical research in HRM. The work should open more doors toward more studies evaluating the robustness of key HRM constructs in explaining important work-related outcomes.