All work intensity is not created equal: Effort motives,job satisfaction and quit intentions at a grocery chain

Prior research has shown that the well-being of employees engaged in intensive work can vary with the discretion their jobs afford regarding how and when to carry out the work. This article explores a different avenue. It argues that well-being also varies with employees’ individual motives for working intensively. The article introduces self-determination theory to the domain of work intensity and focuses on two hypotheses. The first is whether intensive work driven by explicit or implicit incentives is more positively associated with an employee's job satisfaction than intensive work driven by job demands. The second is whether intensive work driven by intrinsic motives is more positively associated with job satisfaction than that driven by explicit or implicit incentives. In both these cases, the article also examines whether equivalent effects exist on (reduced) quit intentions. Original data from a major Greek grocery chain provide corroborative evidence that is robust to a rich set of covariates, including increasingly demanding adjustments for job discretion. The findings contribute to a more complete understanding of why differences in well-being exist among employees performing intensive work, with implications for workers and employers.     

Can investors time their exposure to private equity?

Private equity performance, both for buyouts and venture capital, has been highly cyclical: periods of high fundraising have been followed by periods of low performance. Despite this seemingly predictable variation, we find modest gains, at best, to pursuing realistic, investable strategies that time capital commitments to private equity. This occurs, in part, because investors can only time their commitments to funds; they cannot time when commitments are called or when investments are exited. There is a high degree of time-series correlation in net cash flows even across commitment strategies that allocate capital in a very different manner over time.     

Migration,Ethnicity and Solidarity: ‘Multinational Workers’ in the Former Soviet Union

We investigate migrant construction workers’ experiences in the Former Soviet Union, examining their attitudes to other ethno-national groups, unions and collective action. Industrial relations and migration studies view migrant workers’ hypermobility and diversity, under conditions of low union coverage and rising nationalism, as potentially obstructing consciousness-raising and mobilizing. Workers in our study faced union indifference, ethno-national segregation and discrimination. However, managerial abuses, informality and contestation from below led to spontaneous mobilization. Lack of institutional channels to solve these disputes drove workers’ further mobility. Complex mobility trajectories and collective action translated into increased awareness of collective interests and rejection of nationalist ideologies. The outcome is ‘multinational workers’ potentially resistant to nation-state politics and capital's logics but also aware of the value and usefulness of collective solidarities. Thus, previous arguments solely associating exit with individualistic attitudes, and post-socialist legacies with workers’ quiescence present only partial pictures.     

Information flows and crashes in dynamic social networks

We develop a dynamic model of information transmission and aggregation in social networks in which continued membership in the network is contingent on the accuracy of opinions. Agents have opinions about a state of the world and form links to others in a directed fashion probabilistically. Agents update their opinions by averaging those of their connections, weighted by how long their connections have been in the system. Agents survive or die based on how far their opinions are from the true state. In contrast to the results in the extant literature on DeGroot learning, we show through simulations that for some parameterizations the model cycles stochastically between periods of high connectivity, in which agents arrive at a consensus opinion close to the state, and periods of low connectivity, in which agents’ opinions are widely dispersed.

     

PITFALLS IN CROSS‐SECTION STUDIES WITH INTEGRATED REGRESSORS: A SURVEY AND NEW DEVELOPMENTS

In cross‐section studies, if the dependent variable is I(0) but the regressor is I(1), the true slope must be zero in the resulting “unbalanced regression.” A spuriously significant relationship may be found in large cross‐sections, however, if the integrated regressor is related to a stationary variable that enters the DGP but is omitted from the regression. The solution is to search for the related stationary variable, in some cases the first difference of the integrated regressor, in other cases, a categorical variable that can take on limited number of values which depend on the integrated variable. We present an extensive survey, new developments, and applications particularly in finance.     

Transmission of information within transnational social networks: a field experiment

Several studies have shown a relationship between the stocks of migrants and country-level investment in the home country; however the mechanism through which this relationship operates is still unexplored. We use a field experiment in which participants who are recent immigrants send information about risky decisions to others in their social network in their home country. The results demonstrate how this information influences decisions in the home country. We find that the advice given by family members and decisions made by friends significantly affects an individual’s risky decision-making.     

Learning patterns in early stage R&D projects: empirical evidence from the fibre raw material technology project in the Netherlands

Past research has reported that learning processes in early stage R&D are either chaotic, or absent. We challenge this finding by elaborating Van de Ven et al.’s trial‐and‐error learning model and explore an alternative conceptualization. We explored the combinations of positive and negative outcomes and action course continuation and modification. We use data gathered in an R&D setting of a 4‐years pre‐competitive knowledge generation project in the Dutch paper and board industry. Whereas the Van de Ven and Polley (1992) approach applied on our data also would lead us to conclude that ‘no learning’ would happen, our decomposed model identified three distinct learning patterns: (1) a virtuous pattern of positive outcomes resulting in continuations of action courses; (2) a vacuous pattern of negative outcomes resulting in modifications of action courses; and (3) a verification pattern of positive outcomes resulting in modifications of action courses. We observed the virtuous and verification patterns during the first 2 years and virtuous and vacuous learning in the second 2 years. These results might be useful for R&D managers since they provide insight into how an early stage R&D project can develop and where managers might intervene and adjust action courses.     

Advertising to the masses: the effects of crowding on the attention to place-based advertising

Advertising situated in environments where people congregate or pass through on their way to somewhere else benefit from being placed in such high traffic areas. However, these strategically placed ads also suffer from conditions of human crowding that prevents them from being noticed and processed. We undertake a study of place-based advertising in a shopping mall using facial recognition software to determine the effect of human density on the attention directed to advertising. We find that as human density increases, attention to advertising decreases, but only to a point where it begins to increase again. Our research also finds that human density plays a moderating role on the motivation to process advertising.