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Allocating budget optimally to marketing channels is an increasingly difficult venture. This difficulty is compounded by an increase in the number of marketing channels, a rise in siloed data between marketing technologies, and a decrease in individually identifiable data due to legislated privacy policies. The authors explore the rich attribution modeling literature and discuss the different model types and approaches previously used by practitioners and researchers. They also investigate the changing landscape of marketing attribution, discuss the advantages and disadvantages of different data handling approaches (i.e., aggregate vs. individualistic data), and present a research agenda for future attribution research.

The purpose of this paper is to simultaneously examine individual‐ and team‐level predictors of workplace victimization by applying two‐level modeling. Previous workplace victimization research has primarily been conducted on the individual level of analysis, which may be insufficient when assessing organizational‐ and team‐level predictors of workplace victimization. The authors examined the relationships between target personality (Big Five personality factors), perceived stressors, work climate, and perceived workplace victimization.

The research was conducted in organizations within the restaurant sector; the data were obtained using questionnaires completed by employees and supervisors (n=207) in 70 restaurants.

A model that included all variables fitted the data well. However, individual‐level perceived stressors was the only variable that was significantly related to workplace victimization. The facts that our model included team‐level climate factors and individual‐level personality traits, and both individual‐ and team‐level victimization showed good fit to the data, with only one specific variable in the model showing any significant relationship with bullying, may indicate that bullying is more a consequence of the total risk factors than related to specific factors, on an individual or team level. Hence, it is the additive effect of the factors that matters more than each individual factor.

Of practical relevance is that the paper provides evidence that both individual and team‐level factors are related to workplace victimization, indicating that bullying cannot be prevented by focusing on clearly defined risk factors either on team or individual levels. As a manager, one must work on all aspects of the social working environment, including the total vulnerability of one's employees and their respective levels of work stress.

From a methodological viewpoint, the paper demonstrates that an analysis of clustered individual‐level data, without the application of proper multilevel analysis, may lead to biased results.

Surveys in Europe show that immigration is more of a challenge than an opportunity for a significant number of people. However, little attention is given to attitudes toward immigration in the Middle East. This paper examines the effects of personal values and religiosity on the anti-immigration attitudes of citizens in the Middle East and North African countries.

Utilizing data from the World Values Survey, we analyze how personal values and religiosity affect anti-immigration attitudes in nine Middle Eastern countries. The data covers individual-level data of 9 MENA countries from the WVS Round 7 (2017–2022). Factor analysis is applied as a data reduction method. Afterward, an OLS regression analysis is conducted on the pooled data.

Anti-immigration attitudes increase with age, education, and religiosity. Personal values such as national pride, support for nationals, and belongingness to one’s country significantly affect anti-immigration attitudes. Furthermore, the importance of religion as a measure of religiosity was found to be positively associated with anti-immigration attitudes.

This paper contributes to underexplored literature by investigating how individual-level determinants, such as demographic indicators, personal values, and religious factors, shape anti-immigration attitudes in the MENA context, distinct from European dynamics.

The purpose of this paper is to provide a better understanding of how the interplay of individual-level resources and culture affects entrepreneurs’ propensity to adopt social value creation goals.

Using a sample of 12,685 entrepreneurs in 35 countries from the Global Entrepreneurship Monitor, it investigates the main effects of individual-level resources – measured as financial, human and social capital – on social value creation goals, as well as the moderating effects of the cultural context in which the respective entrepreneur is embedded, on the relationship between individual-level resources and social value creation goals.

Drawing on the resource-based perspective and Hofstede’s cultural values framework, the results offer empirical evidence that individual-level resources are relevant for predicting the extent to which entrepreneurs emphasise social goals for their business. Furthermore, culture influences the way entrepreneurs allocate their resources towards social value creation.

The study sheds new light on how entrepreneurs’ individual resources influence their willingness to create social value. Moreover, by focussing on the role of culture in the relationship between individual-level resources and social value creation goals, it contributes to social entrepreneurship literature, which has devoted little attention to the interplay of individual characteristics and culture.

In the age of digital media, customers have access to vast digital information sources, within and outside a company's direct control. Yet managers lack a metric to capture customers' cross-media exposure and its ramifications for individual customer journeys. To solve this issue, this article introduces media entropy as a new metric for assessing cross-media exposure on the individual customer level and illustrates its effect on consumers' purchase decisions.

Building on information and signalling theory, this study proposes the entropy of company-controlled and peer-driven media sources as a measure of cross-media exposure. A probit model analyses individual-level customer journey data across more than 25,000 digital and traditional media touchpoints.

Cross-media exposure, measured as the entropy of information sources in a customer journey, drives purchase decisions. The positive effect is particularly pronounced for (1) digital (online) versus traditional (offline) media environments, (2) customers who currently do not own the brand and (3) brands that customers perceive as weak.

The proposed metric of cross-media exposure can help managers understand customers' information structures in pre-purchase phases. Assessing the consequences of customers' cross-media exposure is especially relevant for service companies that seek to support customers' information search efforts. Marketing agencies, consultancies and platform providers also need actionable customer journey metrics, particularly in early stages of the journey.

Service managers and marketers can integrate the media entropy metric into their marketing dashboards and use it to steer their investments in different media types. Researchers can include the metric in empirical models to explore customers' omni-channel journeys.

The purpose of this paper is to examine the effect of work characteristics on members’ self‐efficacy and collective efficacy, and the subsequent effect on police officers’ performance.

A multilevel model is adopted to analyze quantitative data obtained by using 812 police officers and 54 chiefs of police stations in Taiwan as the research objects.

The authors found that work characteristics affected members’ self‐efficacy and collective efficacy, which further affected the individual‐ and group‐level performance and the contextual effect of social work characteristics (SWCs) and collective efficacy on self‐efficacy and individual performance. The authors also confirmed the cross‐level moderation of social characteristics on the relationship between motivational work characteristics (MWCs) and self‐efficacy, and between self‐efficacy and individual performance.

A limitation was the characteristics of the sample, which consisted of mostly first‐line uniformed police officers in Taiwan. From the perspective of managerial implications, it is felt that police organizations should beef up the training on police officers’ collective efficacy, such as building group spirit, improving members’ sense of responsibility, and building up trust with the organization.

The findings prove that the study of work design is particularly important for enhancing the management effectiveness of police organization, because it explains the causes of a number of organizational behaviors as well as a number of important results that influence the police organization (e.g. efficacy and performance).

The purpose of this paper is to explain prevalent earnings differentials in Gulf Cooperation Council’s (GCC’s) private sectors between skilled local and migrant labor and provide estimates of potential price distortions to underlie future market-based corrective policies that increase participation of locals in private employment.

The paper uses an individual-level data set on workers’ earnings and productivity-related characteristics to decompose estimated earnings differentials at the mean level and at various percentiles of the earnings distribution via well-established decomposition approaches.

Results show that the real earnings differential between locals and Asians decreases at higher earnings, while that between locals and non-GCC Arabs are relatively stable. Both are characterized by overpayment of locals, that is, self-inflicted by current nationalization policies. Higher earnings of Westerners are due to their superior productivity-related characteristics.

Due to the lack of official individual-level data on workers’ productivity-related characteristics, this paper is compelled to utilize an open-source primary data set. Despite the data set’s ability to reproduce officially published aggregates and produce sound econometric results, findings are not entirely proof against sampling bias.

The paper demonstrates that the failure of GCC’s nationalization policies is self-inflicted by the current quota system and by the lack of legislative frameworks that ensure equal pay for equal work. Effective nationalization ought to be market based, rather than by fiat.

The paper is the first to analyze GCC’s private earnings differentials at the individual level and provides micro-econometric evidence on existing price distortions.

The grounded theory method is more appropriate than just a grounded theory “approach,” for teasing out the detail of the level of analysis of constructs. Also, triangulation is important to this kind of research, but the methodological distinctions between qualitative and quantitative data and qualitative and quantitative analysis need to be made clear when mapping out a methodology. The contention here is that the qualitative analysis of quantitative data is more important than the quantitative analysis of qualitative data. Qualitative analysis in line with the full grounded theory method will generate explanations of how and why a construct is represented at various levels of analysis. In turn, such an explanation can illustrate whether the questionnaire instrument is representing the levels of analysis of the construct adequately or not.

Organization development is focused on implementing a planned process of positive humanistic change in organizations through the use of social science theory, action research, and data-based feedback methods. The role of personality in that change process, however, has historically been ignored or relegated to a limited set of interventions. The purpose of this chapter is to provide a conceptual overview of the linkages between personality and OD, discuss the current state of personality in the field including key trends in talent management, and offer a new multi-level framework for conceptualizing applications of personality for different types of OD efforts. The chapter concludes with implications for research and practice.

This paper aims to, considering the potential to generate additional revenue from cross-gamers, identify variables predicting predominant slot-players’ propensity to play table games, as well as predominant table-game players’ propensity to play slots (cross-game play). Casino marketers often promote cross-game play through game lessons and coupons for game trial.

Logistic regression analysis was performed on the player data provided by a destination hotel casino on the Las Vegas Strip. Furthermore, the authors described how to estimate propensity scores, the probability of cross-game play, at the individual level, using a logistic regression equation.

Comparisons of cross-gamers versus non cross-gamers indicated that the amount of play and gaming values of cross-gamers were much higher than those of slot-only players. The results of a logistic regression analysis show that a player’s cross-gaming propensity can be predicted using gaming-related behavioral data. More specifically, cross-gaming propensities were associated with the frequency and recency of casino trips, the amount of money won or lost in gaming, player values to the casino, the duration of play and the length of a customer–casino relationship.

It is recommended that future research apply the model tested herein to other samples and investigate other predictor variables to develop a better predictive model for cross-game play.

The findings and the model introduced herein could help casino marketers identify players with cross-gaming propensity and develop more targeted strategies for customer-relationship management and database marketing.

This study is the first attempt to estimate the cross-gaming propensity at the individual level and offers detailed guidance on how to use the propensity scores for targeting specific customers.