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The relationship between variation in time perspectives and collaborative performance is scarcely explored, and even less is known about the respective mechanisms that lead to varying task performance. Thus, we aim to further the literature on time perspectives and collaborative performance, shedding light on the underlying behavioral patterns.

We report a quasi-experiment analyzing the impact of past, present and future orientation variation in dyads (N = 76) on their quantitative and qualitative performance when confronted with a simple incentivized creative task with constraints. Subsequently, we offer a qualitative analysis of comments given by the participants after the task on the collaboration.

Results indicate that a dyad's elevation of past orientation and diversity in future orientation negatively affect collaborative performance. At the same time, there is a positive effect of elevation of future orientation. The positive effect is driven by clear communication and agreement during the task, while the negative effect arises from work sharing and complementation.

This study provides insights for organizations on composing individuals regarding their temporal focus for collaborative tasks that should be executed rapidly and require creative solutions.

Our study distinguishes by considering the composition of past, present and future time perspectives in dyads and focuses on a creative task setting. Moreover, we explore the mechanisms in the dyads with a substantial elevation of/diversity in future orientation, leading to their stronger/weaker performance.

This study aims to answer the question of what characterizes organizations with future-potential, and with the help of a model introduced in this study, the authors propose what interventions can be identified and which improvements need to be made in traditional organizations so that they meet the requirements of future-potentiality.

A systematic literature review was conducted to identify management interventions. Citation and co-word analyses were also performed. Content analysis of 311 journal articles from the past five years was performed taking into account relevant keywords, and disciplinary narrowing was also applied. These articles were used to identify knowledge that could be used to suggest micro-, meso- and macro-level changes.

To develop the future potential of organizations, three organizational levels must be separated. The first is the micro level of relations between leaders and employees, where equity is a key value for future potentiality. It should be emphasized that not all employees’ organizational commitment is equally important for organizations with future potential, and leaders should strengthen their commitment according to individual needs and opportunities. The second is the meso level, where the decisive value is organizational moderation, and this suggests that a careful and restrained development is needed both in satisfying consumer needs and in innovation. The third is the macro level, where the defining value is responsibility and sustainability, which are necessary for achieving a state where the active development of national culture becomes possible.

Contrary to the authors’ expectations, it has been found that there are only a few studies dealing with change management for the purpose of achieving a future potential mode of organizational operation; thus, the results can be considered new and will contribute to the development of a cross-section of change management and future studies.

Integrating artificial intelligence and quantitative investment has given birth to various agricultural futures price prediction models suitable for nonlinear and non-stationary data. However, traditional models have limitations in testing the spatial transmission relationship in time series, and the actual prediction effect is restricted by the inability to obtain the prices of other variable factors in the future.

To explore the impact of spatiotemporal factors on agricultural prices and achieve the best prediction effect, the authors innovatively propose a price prediction method for China's soybean and palm oil futures prices. First, an improved Granger Causality Test was adopted to explore the spatial transmission relationship in the data; second, the Seasonal and Trend decomposition using Loess model (STL) was employed to decompose the price; then, the Apriori algorithm was applied to test the time spillover effect between data, and CRITIC was used to extract essential features; finally, the N-Beats model was selected as the prediction model for futures prices.

Using the Apriori and STL algorithms, the authors found a spillover effect in agricultural prices, and past trends and seasonal data will impact future prices. Using the improved Granger causality test method to analyze the unidirectional causality relationship between the prices, the authors obtained a spatial effect among the agricultural product prices. By comparison, the N-Beats model based on the spatiotemporal factors shows excellent prediction effects on different prices.

This paper addressed the problem that traditional models can only predict the current prices of different agricultural products on the same date, and traditional spatial models cannot test the characteristics of time series. This result is beneficial to the sustainable development of agriculture and provides necessary numerical and technical support to ensure national agricultural security.

The purpose of this study is to unfold the existing information channel in the higher moments of currency futures for different time horizons.

The authors use a quasi-Bayesian local likelihood approach within a time-varying parameter vector autoregression (TVP-VAR) framework and a dynamic connectedness measure to study the volatility, skewness and kurtosis of most traded currency futures.

The authors’ results suggest a time-varying presence of dynamic connectedness within higher moments of currency futures. Most spillovers pertain to shorter time horizons. The authors find that in net terms, CHF, EUR and JPY are the most important contributors to the system, while the authors emphasize that the role of being a transmitter or a receiver varies for pairwise interactions and time windows.

To the best of the authors’ knowledge, this is the first study that looks upon the connectivity vis-á-vis uncertainty, asymmetry and fat tails in currency futures within a dynamic Bayesian paradigm. The authors extend the current literature by proposing new insights into asset distributions.

Targeting at the inconsistent relationship between protean career orientation and turnover intentions, this study aims to uncover when and why such inconsistency occurs. It emphasized the mediating role of organizational identification and moderating effects of current organizational career growth and future organizational career growth prospect.

The authors conducted a three-wave time-lagged study over seven months, with a sample of 1,012 participants from various occupations.

The relationship of protean career orientation to turnover intentions via organizational identification was negative when current organizational career growth was high, and it was positive when current growth was low. Future organizational career growth prospect weakened organizational identification–turnover intentions relationship. Those two moderators jointly influenced the indirect relationship. For employees low in both states, the positive indirect relationship was the most significant.

By integrating social identity theory and social cognitive theory, this study provides a comprehensive understanding of protean career orientation–turnover intentions relationship. It also enriches studies on protean career orientation and organizational identification–turnover intentions relationship.

In recent years, there has been a growing trend of individuals willingly opting for employment positions that do not fully use their education, skills and abilities, a phenomenon known as voluntary overqualification. This study aims to investigate the factors that influence and the formation mechanism of this emerging phenomenon. Drawing upon social cognition theory, this study explores the relationship between work values and voluntary overqualification while also examining the mediating role of the future work self and the moderating role of perceived marketability.

This study used a longitudinal approach, collecting data through questionnaires administered at multiple time points. The sample consisted of 607 employees from various departments of five Chinese companies. Regression analysis using the PROCESS macro in SPSS was used to test the research hypotheses.

The results indicate a positive relationship between employees’ work values and voluntary overqualification. Furthermore, this relationship is mediated by the future work self. Additionally, perceived marketability plays a moderating intermediary role in the whole model.

This study contributes to the overqualification literature by introducing a novel type of overqualification and unveiling the mechanism by which work values influence voluntary overqualification. The findings provide insights for understanding and managing employees who are voluntarily overqualified.

This paper aims to investigate whether the establishment of commodity futures can effectively hedge systemic risk in the spot network, given the context of financialization in the commodity futures market.

Utilizing industry association data from the Chinese commodity market, the authors identify systemically important commodities based on their importance in the production process using multiple graph analysis methods. Then the authors analyze the effect of listing futures on the systemic risk in the spot market with the staggered difference-in-differences (DID) method.

The findings suggest that futures contracts help reduce systemic risks in the underlying spot network. Systemic risk for a commodity will decrease by approximately 5.7% with the introduction of each corresponding futures contract, since the hedging function of futures reduces the timing behavior of firms in the spot market. Establishing futures contracts for upstream commodities lowers systemic risks for downstream commodities. Energy commodities, such as crude oil and coal, have higher systemic importance, with the energy sector dominating systemic importance, while some chemical commodities also have considerable systemic importance. Meanwhile, the shortest transmission path for risk propagation is composed of the energy industry, chemical industry, agriculture/metal industry and final products.

The paper provides the following policy insights: (1) The role of futures contracts is still positive, and future contracts should be established upstream and at more systemically important nodes in the spot production chain. (2) More attention should be paid to the chemical industry chain, as some chemical commodities are systemically important but do not have corresponding futures contracts. (3) The risk source of the commodity spot market network is the energy industry, and therefore, energy-related commodities should continue to be closely monitored.

The purpose of this research is to examine the narratives of victims of abusive supervision. We explore the meaning or “lessons” victims derive from those experiences and how they shape the victims’ views of self, work and organization in relation to navigating their subsequent jobs.

We analyzed how appraisals of supervisory abuse transform victims’ narratives and their consequent work attitudes through sensemaking processes. Semi-structured interviews with the past victims of abusive supervision generated a four-stage model of how sensemaking shapes victims’ future work attitudes. Our interpretations were guided through narrative thematic analysis based on the constructionist approach.

Victims’ lessons learned are predominantly framed by their retrospective post-event appraisal of abuse (based on its severity) once individuals are no longer subject to abusive supervision. With greater distance from the abuse, victims can process the abuse and better understand the motivation of the abuser, enabling the process of causal attributions. These attributions further shape victims’ narratives and future work attitudes through a complex interplay of retrospective and prospective sensemaking mechanisms. The victims broadly reported proactive (with higher self-awareness and endurance) and reactive (self-protection, and emotional scars) lessons. A four-stage model was proposed based on our findings.

Abusive supervision remains a persistent issue experienced by many individuals at some point in their working life. However, little is known about how victims make sense of the event post-abuse and how this sense-making guides their future work behaviors. Understanding this phenomenon provides insight into how employees navigate through adversity and construct a more positive future. The contribution of this narrative inquiry is threefold. First, it explores how individual appraisals of supervisory abuse frame their (1) mechanisms of narrative construction; and (2) future work attitudes. Second, our findings demonstrate how narrative construction is a fluid process often informed by the process of retrospective and prospective sensemaking. Finally, our research suggests two broader categories of lessons that victims internalize and carry forward to their subsequent jobs.

This study aims to assess the effect of material internal control weaknesses (MICW) on the relationship between ownership structures and future-oriented disclosure.

A total number of 197 firms were assessed in this study during 2014–2021. Two measures were used for MICW. First, the number of existing MICW was assessed in independent auditors’ reports. In Iran, the maximum number of weaknesses is 13. Second, the scoring (0 or 1) method was used as a dummy variable, 1 for a firm with MICW and otherwise 0. Moreover, the scoring (0 or 1) method was used to measure the level of future-oriented disclosure of 13 indicators.

The findings showed that institutional ownership and managerial ownership have a significant positive effect on future-oriented disclosure, whereas the MICW have a significant negative effect on future-oriented disclosure. In addition, MICW played a moderator role in the relationship between ownership structures and future-oriented disclosure. The robustness checks confirmed the results.

As the studies conducted on future-oriented disclosure and the contributing factors are limited, and also the effect of MICW on future-oriented disclosure is not explored, the present findings can show the importance of the study, and fill the gap in this field. This study offers theoretical and practical implications to drive policymakers and managers to the effectiveness of internal control and future-oriented transparency.

Since crude oil is crucial to the nation's economic growth, crude oil futures are closely related to many other markets. Accurate forecasting can offer investors trustworthy guidance. Numerous studies have begun to consider creating new metrics from social networks to improve forecasting models in light of their rapid development. To improve the forecasting of crude oil futures, the authors suggest an integrated model that combines investor sentiment and attention.

This study first creates investor attention variables using Baidu search indices and investor sentiment variables for medium sulfur crude oil (SC) futures by collecting comments from financial forums. The authors feed the price series into the NeuralProphet model to generate a new feature set using the output subsequences and predicted values. Next, the authors use the CatBoost model to extract additional features from the new feature set and perform multi-step predictions. Finally, the authors explain the model using Shapley additive explanations (SHAP) values and examine the direction and magnitude of each variable's influence.

The authors conduct forecasting experiments for SC futures one, two and three days in advance to evaluate the effectiveness of the proposed model. The empirical results show that the model is a reliable and effective tool for predicting, and including investor sentiment and attention variables in the model enhances its predictive power.

The data analyzed in this paper span from 2018 through 2022, and the forecast objectives only apply to futures prices for those years. If the authors alter the sample data, the experimental process must be repeated, and the outcomes will differ. Additionally, because crude oil has financial characteristics, its price is influenced by various external circumstances, including global epidemics and adjustments in political and economic policies. Future studies could consider these factors in models to forecast crude oil futures price volatility.

In conclusion, the proposed integrated model provides effective multistep forecasts for SC futures, and the findings will offer crucial practical guidance for policymakers and investors. This study also considers other relevant markets, such as stocks and exchange rates, to increase the forecast precision of the model. Furthermore, the model proposed in this paper, which combines investor factors, confirms the predictive ability of investor sentiment. Regulators can utilize these findings to improve their ability to predict market risks based on changes in investor sentiment. Future research can improve predictive effectiveness by considering the inclusion of macro events and further model optimization. Additionally, this model can be adapted to forecast other financial markets, such as stock markets and other futures products.

The authors propose a novel integrated model that considers investor factors to enhance the accuracy of crude oil futures forecasting. This method can also be applied to other financial markets to improve their forecasting efficiency.