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Few studies have analysed how to actively manage strategic networks (SNs) to achieve individual and collective goals and create value. This paper aims to examine the influence of network management on the value created by SNs and the mediation role of resources and relationship quality.

The authors distributed a survey to 126 companies linked to SNs in the Brazilian information and communication technology sector. This study tested the hypothesized relationships using partial least squares structural equation modelling.

This study found that network management directly influences value creation. Furthermore, the exchange and combination of resources mediate the relationship between the two constructs. Surprisingly, the quality of the relationships does not mediate the relationship between management and the value created. However, it positively impacts the exchange and combination of complementary resources.

This study provides a new interpretation of the determinants of value creation in SNs. The results contribute to the theory by demonstrating that the relationship between network management and value creation is strengthened when the exchange and combination of resources between network participants occur. In turn, these are positively influenced by the quality of relationships established in the network, thus providing a new interpretation of the determinants of value creation in SNs.

The present study examined the psychometric properties of the EGame- flow scale in a Mexican sample, presenting evidence of construct validity (exploratory factor analysis and confirmatory factor analysis), reliability (Cronbach’s alpha and McDonald’s omega) and discriminant validity (mean variance extracted).

Participants: Of the 255 Mexican participants in the non-probabilistic sample who had previously interacted with the LOST logistics simulator, 166 (65%) were men and 89 (35%) were women; their ages ranged from 22 to 45. The statistical packages SPSS 25, JASP 0.16 and AMOS 23 facilitated the corresponding analyses. First, we calculated the means and standard deviations of the scale items. Next, we performed an exploratory factor analysis to examine the measurement model’s internal structure and a confirmatory factor analysis to confirm the structure proposed in the exploratory factor analysis. To analyze the internal structure of the measurement model so that the estimates were not affected by multivariate normality problems, we utilized the AMOS bootstrap method (with 500 repetitions, 95% CI), the maximum likelihood (MV) estimation method, and the fit indices: X2, p (chi-square and associated likelihood), Tucker–Lewis index (TLI), standardized statistical mean square residual (SRMR), comparative fit index (CFI) and root mean Square error approximation (RMSEA) with its confidence interval, the values of X2 with p < 0.001; TLI, CFI, AGFI = 0.95; RMSEA and SRMR = 0.08 (Byrne, 2016). Finally, we estimated the reliability of the measurement model with Cronbach’s alpha (a), McDonald’s omega (ω) coefficient and the mean variance extracted (VME).

An exploratory factor analysis with the MV method and obliminal rotation showed a good fit of the data to the model, which aligns with the significance of the Barlette sphericity test (X2 = 8443.2, p < 0.000) and the Kaiser–Meyer-Olkin (KMO) value of 0.94. The indices confirmed the fit of the data to the six-dimensional model for measuring the users' level of enjoyment of online games (X2 = 678.2 gl = 411, p = 0.000; SRMR = 0.05; TLI = 0.95, CFI = 0.95 and RMSEA = 0.05, IC 90% [0.04, 0.05]).

The self-reporting format of the scale increases the social desirability of the responses, but the sample only collects information from a specific geographic location, so these findings cannot extrapolate to populations with very marked cultural differences. Finally, the study did not measure other validity evidence, such as predictive and concurrent validity, which should be considered in future studies.

From a practical perspective, the study offers a measurement scale with fewer items and robust psychometric evidence that ensures the fit of the data to the EGame-flow measurement scale. Further research must continue to learn about the behavior of the EGame-flow scale in different samples that new evidence of psychometric properties continues to appear and that other factors associated with the users' gaming enjoyment experience are analyzed.

The value and originality of the study lie in the type of evidence of psychometric properties that the instrument has and particularly in the style of sample in which the study is carried out, in this case, in the context of Mexico, where there are not enough instruments that measure the flow experience of users.

The purpose of this study is to test whether equity theory (ET) – which posits that individuals compare their outcome/input ratio to the ratio of a “comparison other” and classify individuals as Benevolent, Equity Sensity, and Entitled – applies to the modern workplace of global virtual teams (GVT), where work is mostly intellectual, geographically dispersed and online, making individual effort nearly impossible to observe directly.

Using a sample of 1,343 GVTs comprised 6,347 individuals from 137 countries, this study tests three ET’s predictions in the GVT context: a negative, linear relationship between Benevolents’ perceptions of equity and job satisfaction in GVTs; an inverted U-shaped relationship between Equity Sensitives’ perceptions of equity and job satisfaction in GVTs; and a positive, linear relationship between Entitleds’ perceptions of equity and job satisfaction in GVTs.

Although the second prediction of ET is supported, the first and third have statistically significant opposite signs.

The research has important ramifications for management studies in explaining differences in organizational behavior in GVTs as opposed to traditional work settings.

The authors conclude that the main novelty with ET in GVTs is that GVTs are an environment stingy with satisfaction for “takers” (Entitleds) and generous in satisfaction for “givers” (Benevolents).

Madan Mohanka set up Tega Industries Ltd. in 1976 to manufacture abrasion-resistant rubber mill lining products used in the mining and mineral processing industries. In 2011, as part of its inorganic expansion strategy, Tega bought a company in Chile. However, post-acquisition, several managerial, legal and commercial problems crept up in its manufacturing facilities in Chile, leading to financial downturn in Tega's fortunes in 2016 and compelling it to planning a revival between 2016-19. However, political unrest and Covid 19 uncertainty has caused a dilemma related to further investments worth INR 1.25 billion. Management is contemplating the next steps.