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Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

Employees play an essential role in interactive innovation activities in Open Innovation Communities (OICs). Nevertheless, the factors influencing employees' innovation behavior in OICs have not been studied in depth. This study selects personality traits and social network characteristics to explain why and how these two factors affect employees' innovation behavior in OICs.

Three regression models were constructed to test the relationship between personality traits, social network characteristics, and interactive innovation behaviors. The authors examined how employees' personality traits (Big Five personality traits) influence employees' innovative behavior (initiating and supporting innovation) directly in OICs and explored whether social network characteristics (social group) mediate the relationship between employees' personality traits and employees' innovation behavior.

Using empirical data on 162 employees from Salesforce's IdeaExchange, the authors found that extraversion and openness to experience have significant positive effects on employees' interactive innovation behaviors, while conscientiousness has a significant negative effect on employees' interactive innovation behaviors in OICs. Furthermore, the mediation effect test results indicated that social network characteristics have a mediating effect on the relationship between extraversion and innovative behavior, and between openness and innovative behavior.

This study analyzes how personality traits influence innovation behavior in an open innovation environment, thus enriching research related to the factors influencing interactive innovation behavior. Meanwhile, the study integrates personality, social network, and innovative behavior research streams and clearly explains the relationship between the three variables. The research findings assist firms in selecting suitable employees to participate in interactive innovation behaviors in OICs.

To authenticate the existence and principles of the adhesion recovery phenomenon under water pollution conditions, an innovative circumferential rail–wheel adhesion test rig was used. The study conducted extensive tests on the adhesion characteristics under large sliding conditions.

Experiments were conducted to investigate the influence of speed, axle load and slip on adhesion recovery. Based on the experimental results, the adhesion recovery transition function was re-fitted.

The study reveals that the adhesion recovery phenomenon truly exists under water conditions. The adhesion coefficient shows an increasing trend with the growth of the slip ratio. Moreover, at the current speed and axle load levels, the adhesion recovery is directly proportional to the square of the slip ratio and inversely proportional to the axle load.

The phenomenon of adhesion recovery and the formulated equations in this study can serve as an experimental and theoretical foundation for the design of braking and anti-skid control algorithms for trains.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2023-0379/

This paper aims to examine the influence of big data (BD) on human resource management (HRM). It defines how these data can be a useful tool in the decision-making process of companies’ human resources to obtain a sustainable competitive advantage.

This paper emphasizes the need to develop a holistic approach to emphasize these relations. Starting from these observations, the document proposes empirical research employing Eurostat data to test the benefits of BD in HRM decisions that optimize the relationship between training, productivity, and well-being.

The findings estimate HRM decisions and their impact in a broader macroeconomic and microeconomic perspective.

BD research is emerging as a crucial discipline in human resources. To overcome this problem, the paper develops an analysis of the literature on cleaner production and sustainability context; it creates a conceptual framework to clarify whether the existing studies consider the growing intensity of BD on human resources.

Meaningful feedback at work signals effective performance management. Drawing on a new perspective of the conservation of resources (COR) theory, this paper aims to examine the mediating effect of relational energy in the relationship between supervisor developmental feedback and subordinates' task performance with the moderating role of learning demands.

Data from 230 supervisor-subordinate dyads were collected at two time points of four enterprises in China.

The results support the proposed mediation effect that supervisor developmental feedback positively predicts subordinates' task performance via boosting subordinates' relational energy. Furthermore, the results highlighted the moderating role of learning demands in the relationship between supervisor developmental feedback and subordinates' relational energy. The moderated–mediated relationship for subordinates' task performance was also supported.

Drawing on COR theory, this paper contributes to a complete understanding of how supervisor developmental feedback may support or build employees' relational energy, facilitating task performance and further exploring learning demands as a boundary condition of this indirect relationship.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

Integrating transaction costs economics and task-technology fit theory, this study distinguishes two categories of social media–enabled interactions, namely task-related interactions and tie-related interactions, and explores the match between these two and firms' use of contracts in achieving safeguarding and coordinating purposes in interfirm governance.

Two studies were conducted to test the hypotheses. In Study 1, this study collaborated with a professional market research firm and collected responses from Chinese manufacturing firms in a survey. In Study 2, this study designed a scenario-based experiment and collected 239 participants from the Credamo platform.

This study categorized social media–enabled interactions into task-related interactions and tie-related interactions and conducted two studies to reveal that the safeguarding purpose of contract specificity is amplified by tie-related interactions, whereas the coordinating purpose of contract specificity is strengthened by task-related interactions.

This study assumes that firms permit and encourage the use of social media. However, some firms might prohibit the use of social media due to risk issues, or their partners may be prohibited from using social media.

Given that social media–enabled interactions have joint effects with contracts in achieving safeguarding and coordinating purposes, a firm's employees should match their goals with an appropriate type of social media–enabled interactions.

This study enriches the interfirm governance literature by uncovering the roles of these two types of interactions in matching contract specificity to achieve safeguarding and coordinating purposes, which provides actionable insights for managers in governing interfirm relationships.