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This study aims to examine psychological mechanisms underlying tacit knowledge-sharing behaviours. The personality trait of conscientiousness is tested in relation to knowledge sharing, and the effect of eagerness and subjective norm on the intention to share is measured in the context of local and multinational knowledge-intensive enterprises in Croatia.

The quantitative study was conducted on a sample of 288 employees of small and medium-sized companies working on knowledge-intensive tasks. The purposive sampling technique and a survey strategy were used in the study. Organizational affiliation, as it was presumed that these individuals possess a higher degree of tacit knowledge. The data collection was conducted in October 2019. Respondents worked in science and technology companies in Croatia on assignments involving information technology, electronics, petrochemicals, medicine and biochemistry. Statistical product and service solutions analysis of a moment structures software was used to perform confirmatory factor analysis and structural equation modelling.

The findings suggest that the personality trait of conscientiousness has a positive impact on tacit knowledge sharing behaviour. An attitude of eagerness and subjective norm were also confirmed as predictors of tacit knowledge sharing behaviour. Furthermore, conscientiousness influences the eagerness to share knowledge. A significant association between subjective norm and conscientiousness was also established. Finally, the mediating effects were identified, indicating that subjective norm and eagerness mediate the relationship between conscientiousness and tacit knowledge sharing.

Explaining the relationship between personality and attitude in the context of knowledge sharing will result in a better understanding of factors that should be nurtured within individuals. Accordingly, distinct management initiatives are to be developed to suit these factors. Furthermore, to intensify the knowledge exchange when working on knowledge-intensive tasks of significant economic value, organizations tailor a more particularistic application to suit the individual in the domain of leadership, staffing decisions, work organization and incentive systems.

This study provides an in-depth analysis and theoretical understanding of factors salient for knowledge-sharing behaviour. The authors provide an overview of how knowledge sharing evolves during social interaction through intensive problem-solving sessions and teamwork. The authors render the explanation on how the personality trait of conscientiousness, conjoint with the attitude of eagerness to share know-how in the expert surrounding, is conducive to the generation of tacit knowledge sharing. Underpinning this study are employees’ psychological motives and internal drives to communicate individual cognitive capital outweighing the potential negative consequences, such as losing the competitive advantage over the colleagues.

Using the conservation of resources (COR) theory, the present study aims to examine the role of participative leadership in frontline service employees (FLEs)’ service recovery performance. The present study also tests FLEs’ role breadth self-efficacy (RBSE) as a theoretically relevant mediator and FLE trait mindfulness as an important moderator.

Data were collected using time-lagged (three rounds, two weeks apart) from two sources (193 FLEs and 772 customers, who experienced a service failure). Structural equation modeling (Mplus, 8.6) was employed to analyze the data.

The results revealed that participative leadership was positively associated with FLEs service recovery performance, both directly and indirectly, via RBSE. The results also showed that FLE trait mindfulness moderated the link of participative leadership with RBSE and the indirect association of participative leadership with service recovery performance, via RBSE.

This study suggests that organizational leaders who exhibit participative leadership behavior are valuable for organizations. By demonstrating such behaviors, they boost FLEs' RBSE, which in turn improves their service recovery performance.

The present work makes important contributions to the literature on service recovery performance by foregrounding two important yet overlooked antecedents (participative leadership and RBSE) of FLE service recovery performance. The present work also contributes to the nascent literature on the antecedents and outcomes of RBSE in service contexts.

This paper aims to empirically examine the structural relationship between innovation types, transformational leadership (TL), knowledge sharing (KS) and marketing performance (MP) in small- and medium-sized enterprise (SME) service firms. The paper further investigates the extent to which TL and KS influence the relationship between innovation and MP and how such an effect could be managed for SME development.

Cross-sectional survey data are collected from 437 from SME service firms of an emerging economy with a fast-growing service sector. The quantitative methodologies were used in which partial least squares structural equation modeling with bootstrap procedures was adopted to test the hypotheses.

The findings suggest that Innovations have a significant effect on MP, TL has a moderating effect on the relationship and whiles KS mediates between innovation and MP. The study’s results indicate that these effects are robust in the firm’s marketplace.

This study calls for future testing of the current framework in other economies and SME sectors such as manufacturing, which makes findings contextual.

For SME to remain competitive, this study deepens the effect of innovation on performance and as such managers/owners should consider the vital role of TL and KS as a predictor of the relationship between innovation and MP.

The findings emphasize the critical role of KS and TL in the relationship between innovation types and MP SMEs in an emerging economy.

This current study contributes to the literature by assessing a valid model that describes concurrently the relationships between innovation types, TL, KS and MP. This is the first empirical study to focus on SME MP in relation to types of innovation, TL and KS in an emerging economy.

This paper describes the organic geochemical characteristics and their roles on barium enrichment in the No. 2 Coal from Huanglong Jurassic Coalfield, China. A total of 18 bench samples were taken from Huangling Mine 2. The average content of barium (3701 mg/kg) was about 23 times higher than that of common world coals. Terrestrial higher plants were the main coal-forming parent material. Relying on the parameters of OEP, Pr/Ph and so on, there is little correlation between organic geochemical characteristics and barium enrichment. Therefore, organic material has little influence on the process of coal-forming and the enrichment of barium.

What remains uncertain with corporate universities is the contribution they provide to their organizations, particularly when considered from the perspective of managers. Managers are important stakeholders, as they may participate in carrying out the mission and policies that govern the corporate university and participate in the programs offered. Organizations would benefit from knowing more about the perceptions of managers. The purpose of this paper is to study managers’ perceptions of the accountability of two corporate university programs in China and its relationship with the managers’ overall involvement in corporate university programs and their commitment to the organization.

The study was conducted in two state-owned organizations in China, a country in which many organizations have adopted corporate universities. A mixed-method approach was used to carry out the study.

The results showed that there was a moderate relationship between the managers’ perceptions of the accountability of corporate university programs, based on two management development programs and managers’ involvement in corporate university programs and their commitment to the organization. The results also showed a low relationship between managers’ involvement in their corporate university programs and commitment to the organization.

The findings provide implications for managing corporate universities in China and enhancing the accountability of these initiatives. The study serves as a basis for future studies involving corporate universities and on the accountability of and involvement in training.

The purpose of this study is to determine the effect of loneliness and alienation in the workplace on the intention of leaving employment and whether emotional exhaustion has a mediating role in this effect.

The hypotheses generated within the framework of the study model were evaluated by using the data set obtained from 402 survey participants working at nine shopping malls in the Central and Eastern Black Sea regions of Turkey and statistical analysis programs. In this context, the confirmatory factor analysis (CFA) was used to determine the validity of the scale and the structural equation modeling (SEM) was used to test the research hypotheses.

The study reveals that loneliness and alienation in the workplace have an effect on the intention of leaving employment and that this effect is fully mediated by emotional exhaustion. Whether this full mediating role determined by the SEM is meaningful or not was evaluated by Bootstrap analysis and the results revealed that the effect is meaningful.

Developing effective communication channels that will prevent the employee from feeling isolated at work and eliminating the pressure and inadequate physical working conditions created by unrealistic sales targets are recommended. In addition, it is thought that if employees are included in decision-making processes and have sufficient autonomy related to the job, work alienation can be prevented.

This research is important in terms of evaluating shopping centers, which are accepted as the symbol of consumption today, not only with their economic aspects but also with their employees. In this context, the research has revealed that shopping mall employees want to leave their jobs due to emotional exhaustion caused by loneliness and alienation at work.

This study examines the impact of network embeddedness (NE) on innovation performance in small- and medium-sized enterprises (SMEs), and analyses absorptive capacity as mediator and openness as moderator.

Data were collected from 209 employees of SMEs using a convenient sampling technique. Partial least squares structural equation modeling in SmartPLS was used to analyze the various constructs.

The results exhibit a positive and significant relationship in NE and absorptive capacity. Also, this study found a positive and significant relationship in absorptive capacity and innovation performance. Moreover, absorptive capacity has a positive and significant mediation role in the relationship between NE and innovation performance. Also, openness positively moderated the relationship of NE and absorptive capacity.

SMEs should try to implement the functions of NE, such as interaction with other firms in higher frequency, developing trust among all parties, clear alliance among the partners to enhance innovation performance. Similarly, SMEs should focus on absorptive capacity and openness to enrich innovation performance.

This study adds in the current literature of the chosen constructs and empirically contributes the effects in the manufacturing industry of Jiangsu Province, China.

As social network sites (SNS) have increasingly become one of the most important channels for communication, the related privacy issues gain more and more attention in both industry and academic research fields. This study aims to connect the antecedents of information privacy disclosure on SNS.

Based on exchange theory, this study tries to investigate the decision-making process for information privacy disclosure on SNS. Factors from both user’s and website’s perspectives are taken into account in the proposed model.

The results suggest that an individual’s perceived benefits will increase their willingness to disclose information privacy on SNS, but perceived risks decrease this kind of willingness. The authors also find social network size, personal innovativeness and incentive provision positively affect people’s perceived benefits.

Moreover, privacy invasion experience enhances perceived personal risks, but website reputation helps to reduce perceived risks.

In the context of exploring and implementing China's new urbanization, green eco-city have become a transformation model for urban development. Sharpening green buildings in the construction industry can significantly influence and determine China's economic growth trends, as well as the growth and overall development of its national economy. However, current green eco-city still lack appropriate standards and scientific theoretical basis to determine the target star program of green buildings. To fully implement the green building standards, establish and improve a sound technical standard system for the construction of green building demonstration areas, this study considers the spatial layout of green buildings as the core, adopts a plot potential evaluation method for evaluating a few green building plots, and utilizes four factors in verifying plots with great star potential. The study also establishes a system to calculate the star proportion of green buildings and applies the system in calculating the green building ratio of GM New District. Results indicate that the system can quantitatively analyze a plot potential, calculate the star proportion of green buildings scientifically and rationally, and provide some references for the construction of eco-city and the preparation of special planning for green buildings. The system construction is conducive to provide technical support for the construction of green eco-city. The improved system can be applied in the green building demonstration areas in China, and will be a reference model of constructing green building demonstration areas in the country.

The time series forecasting is an essential methodology which can be used for analysing time series data in order to extract meaningful statistics based on the information obtained from past and present. These modelling approaches are particularly complicated when the available resources are limited as well as anomalous. The purpose of this paper is to propose a new hybrid forecasting approach based on unbiased GM(1,1) and artificial neural network (UBGM_BPNN) to forecast time series patterns to predict future behaviours. The empirical investigation was conducted by using daily share prices in Colombo Stock Exchange, Sri Lanka.

The methodology of this study is running under three main phases as follows. In the first phase, traditional grey operational mechanisms, namely, GM(1,1), unbiased GM(1,1) and nonlinear grey Bernoulli model, are used. In the second phase, the new proposed hybrid approach, namely, UBGM_BPNN was implemented successfully for forecasting short-term predictions under high volatility. In the last stage, to pick out the most suitable model for forecasting with a limited number of observations, three model-accuracy standards were employed. They are mean absolute deviation, mean absolute percentage error and root-mean-square error.

The empirical results disclosed that the UNBG_BPNN model gives the minimum error accuracies in both training and testing stages. Furthermore, results indicated that UNBG_BPNN affords the best simulation result than other selected models.

The authors strongly believe that this study will provide significant contributions to domestic and international policy makers as well as government to open up a new direction to develop investments in the future.

The new proposed UBGM_BPNN hybrid forecasting methodology is better to handle incomplete, noisy, and uncertain data in both model building and ex post testing stages.