Environmental demands and the emergence of social structure: Technological dynamism and interorganizational network forms

This study investigates the origins of variation in the structures of global interorganizational networks across industries. We combine empirical analyses of existing interorganizational networks with an agent-based simulation model of network emergence. Our insights are twofold. First, we find that differences in technological dynamism across industries and the concomitant demands for value creation engender variation in firms ’ collaborative behaviors. Specifically, firms in technologically dynamic industries on average pursue more open networks, which foster access to new and diverse resources that help sustain continuous innovation. By contrast, firms in technologically stable industries on average pursue more closed networks, which foster reliable collaboration and help preserve existing resources. Second, we show that because of the observed cross-industry differences in firms ’ collaborative behaviors, the emergent industry-wide networks take on distinct global forms. Technologically stable industries feature clan networks, characterized by low global connectedness and medium-to-strong community structures. Technologically dynamic industries, by contrast, feature community networks, characterized by high connectedness and medium community structures. Convention networks, which feature high global connectedness and weak community structures, wer

Learning horizon and optimal alliance formation

We develop a theoretical Bayesian learning model to examine how a firm’s learning horizon, defined as the maximum distance in a network of alliances across which the firm learns from other firms, conditions its optimal number of direct alliance partners under technological uncertainty. We compare theoretical optima for a ‘close’ learning horizon, where a firm learns only from direct alliance partners, and a ‘distant’ learning horizon, where a firm learns both from direct and indirect alliance partners. Our theory implies that in high tech industries, a distant learning horizon allows a firm to substitute indirect for direct partners, while in low tech industries indirect partners complement direct partners. Moreover, in high tech industries, optimal alliance formation is less sensitive to changes in structural model parameters when a firm’s learning horizon is distant rather than close. Our contribution lies in offering a formal theory of the role of indirect partners in optimal alliance portfolio design that generates normative propositions amenable to future empirical refutation

Friends and Foes: The Dynamics of Dual Social Structures

This paper investigates the evolutionary dynamics of a dual social structure encompassing collaboration and conflict among corporate actors. We apply and advance structural balance theory to examine the formation of balanced and unbalanced dyadic and triadic structures, and to explore how these dynamics aggregate to shape the emergence of a global network. Our findings are threefold. First, we find that existing collaborative or conflictual relationships between two companies engender future relationships of the same type, but crowd out relationships of the different type. This results in (a) an increased likelihood of the formation of balanced (uniplex) relationships that combine multiple ties of either collaboration or conflict, and (b) a reduced likelihood of the formation of unbalanced (multiplex) relationships that combine collaboration and conflict between the same two firms. Second, we find that network formation is driven not by a pull toward balanced triads, but rather by a pull away from unbalanced triads. Third, we find that the observed micro-level dynamics of dyads and triads affect the structural segregation of the global network into two separate collaborative and conflictual segments of firms. Our empirical analyses used data on strategic partnerships and patent infringement and antitrust lawsuits in biotechnology and pharmaceuticals from 1996 to 2006

The effect of 2 different premilking stimulation regimens, with and without a latency period, on teat tissue condition and milking performance in Holstein dairy cows

ABSTRACT: The objectives of this study were to assess the effect of 2 different premilking stimulation regimens, with and without a latency period between tactile stimulation and the attachment of the milking unit, on the teat tissue condition and milking performance of dairy cows. In a randomized controlled crossover study, 145 Holstein cows milked 3 times daily were assigned to treatment (TRT) or control (CON) groups. Premilking udder preparation for the TRT group consisted of the application of a latency period resulting in a preparation lag time of 90 s. The only difference in the premilking udder preparation of the CON group was the absence of latency period; the milking unit was attached immediately after completion of the tactile stimulation. The average duration of total tactile stimulation in TRT and CON group was 8 ± 2 and 9 ± 2 s, respectively. The study lasted for 14 d and was split into 2 periods, each consisting of a 2-d adjustment period followed by 5 d of data collection. We assessed machine milking-induced short-term changes to the teat tissue by palpation and visual inspection postmilking. Electronic on-farm milk meters were used to assess milking characteristics (milk yield [kg/milking session], machine-on time [s], 2-min milk yield [kg], and duration of low milk flow rate [s]). Generalized linear mixed models were used to analyze the effect of treatment on the outcome variables. The odds of machine milking-induced short-term changes to the teat tissue were lower for cows that received a 90-s preparation lag time (TRT cows) compared with cows in the CON group (odds ratio [95% confidence interval; 95% CI] = 0.13 [0.08–0.20]). The least squares means (95% CI) values of cows in the TRT and CON groups were 15.4 (14.9–15.9) and 15.3 (14.8–15.8) kg, respectively, for milk yield, and 246 (239–253) and 253 (247–260) s for machine-on time. The 2-min milk yield was higher for the TRT compared with CON group cows at all the parity levels. The 2-min milk yields of animals in lactation 1, 2, and ≥3 were 5.7, 5.7, and 6.5 kg, respectively, in the TRT group and 4.6, 5.0, and 5.9 kg in the CON group. The TRT cows spent less time in low milk flow rate compared with CON cows at all parity levels. The durations of low milk flow rate of cows in lactation 1, 2, and ≥3 in the TRT group were 19, 17 and 13 s, respectively, and those in the CON group were 31, 22, and 15 s. In this study, cows that received a latency period, and thus were subjected to a 90-s preparation lag time had lower odds of exhibiting short-term changes to the teat tissue after machine milking, shorter machine-on time, higher 2-min milk yields, and lower durations of low milk flow rates. We conclude that consideration of latency period leading to a 90-s preparation lag time in the premilking stimulation regimen facilitated cows' milk-ejection reflex. This latency period can alleviate the adverse effects of vacuum-induced forces on teat tissue during machine milking, improve udder health, and promote animal well-being

Achieving Effective Remote Working During the COVID‐19 Pandemic: A Work Design Perspective

Existing knowledge on remote working can be questioned in an extraordinary pandemic context. We conducted a mixed-methods investigation to explore the challenges experienced by remote workers at this time, as well as what virtual work characteristics and individual differences affect these challenges. In Study 1, from semi-structured interviews with Chinese employees working from home in the early days of the pandemic, we identified four key remote work challenges (work-home interference, ineffective communication, procrastination, and loneliness), as well as four virtual work characteristics that affected the experience of these challenges (social support, job autonomy, monitoring, and workload) and one key individual difference factor (workers’ self-discipline). In Study 2, using survey data from 522 employees working at home during the pandemic, we found that virtual work characteristics linked to worker's performance and well-being via the experienced challenges. Specifically, social support was positively correlated with lower levels of all remote working challenges; job autonomy negatively related to loneliness; workload and monitoring both linked to higher work-home interference; and workload additionally linked to lower procrastination. Self-discipline was a significant moderator of several of these relationships. We discuss the implications of our research for the pandemic and beyond