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Due to high efficiency and low carbon of natural gas, the consumption of natural gas is increasing rapidly, and the prediction of natural gas consumption has become the focus. The purpose of this paper is to employ a prediction technique by combining grey prediction model and trigonometric residual modification for predicting average per capita natural gas consumption of households in China.

The GM(1,1) model is utilised to obtain the tendency term, then the generalised trigonometric model is used to catch the periodic phenomenon from the residual data of GM(1,1) model for improving predicting accuracy.

The case verified the view of Xie and Liu: “When the value of a is less, DGM model and GM(1,1) model can substitute each other.” The combination of the GM(1,1) and the trigonometric residual modification technique can observably improve the predicting accuracy of average per capita natural gas consumption of households in China. The mean absolute percentage errors of GM(1,1) model, DGM(1,1), unbiased grey forecasting model, and TGM model in ex post testing stage (from 2013 to 2015) are 32.5510, 33.5985, 36.9980, and 5.2996 per cent, respectively. The TGM model is suitable for the prediction of average per capita natural gas consumption of households in China.

According to the historical data of average per capita natural gas consumption of households in China, the authors construct GM(1,1) model, DGM(1,1) model, unbiased grey forecasting model, and GM(1,1) model with trigonometric residual modification. The accuracy of TGM is the best. TGM helps to improve the accuracy of GM(1,1).

This paper gives a successful practical application of grey model GM(1,1) with the trigonometric residual modification, where the cyclic variations exist in the residual series. The case demonstrates the effectiveness of trigonometric grey prediction model, which is helpful to understand the modeling mechanism of trigonometric grey prediction model.

The purpose of this paper is to provide a new recursive GM (1,1) model based on forgetting factor and apply it to the modern weapon and equipment system.

In order to distinguish the contribution of new and old data to the grey prediction model with new information, the authors add forgetting factor to the objective function. The purpose of the above is to realize the dynamic weighting of new and old modeling data, and to gradually forget the old information. Second, the recursive estimation algorithm of grey prediction model parameters is given, and the new information is added in real time to improve the prediction accuracy of the model.

It is shown that the recursive GM (1,1) model based on forgetting factor can achieve both high effectiveness and high efficiency.

The paper succeeds in proposing a recursive GM (1,1) model based on forgetting factor, which has high accuracy. The model is applied to the field of modern weapon and equipment system and the result the model is better than the GM(1,1) model. The experimental results show the effectiveness and the efficiency of the prosed method.

The aggregation of information from a group of decision experts for developing collective opinion is the important question in practice. The purpose of this paper is to provide a group decision-making method via ordered weighted aggregation (OWA) operator and grey incidence analysis.

In this study, OWA operator provides aggregation of attribute values to form an overall decision for each decision expert, and grey incidence model provides aggregation of decision experts’ evaluations to form overall score for each alternative. The example illustrates the procedure and practicability of the proposed model.

A new thought for multiple attribute group decision-making problems is given. The proposed method produces an overall desirability score for each alternative.

This is to obtain a more comprehensive and realistic solution to the given group decision-making problem. The proposed analysis method of group decision-making problems reveals vitality of grey systems theory.

This paper combines OWA operator and grey incidence analysis to obtain a novel and effective method for group decision making. It is suitable for group decision-making problems in which the attribute weights are completely unknown, expert weights are completely unknown.

The authors investigate when and why a subordinate's expressive suppression facilitates workplace creativity, building on the conservation of resources theory and considering the effect of the supervisor's expressive suppression and time pressure as boundary conditions.

Multisource data were collected from 132 teams in northwestern China, including 132 supervisors and 648 subordinates. Hierarchical regression analyses were used to test the effects.

The subordinate’s expressive suppression was positively related to their workplace creativity. Challenge time pressure was positively related to workplace creativity, and the subordinate’s expressive suppression was positively related to workplace creativity when challenge time pressure was lower and the supervisor's expressive suppression was higher. Hindrance time pressure was negatively related to workplace creativity, and a positive relationship between a subordinate's expressive suppression and workplace creativity was also found with less hindrance time pressure and greater expressive suppression by their supervisor.

By examining the role of the supervisor as a source of downward spillovers in various time pressure contexts, the study explains why a subordinate’s suppression facilitates workplace creativity from the conservation of resources perspective.

The increased interest among academicians to explore more about tax management behavior is evident in the literature on corporate tax avoidance. This paper aims to illustrate the multiple aspects that influence the tax avoidance behavior of corporations and its impacts through the systematic review method.

This study used “Tax Avoidance” OR “Tax Aggressiveness” OR “Tax Planning” as search strings to extract the relevant literature from the Scopus database. This study is a comprehensive analysis of existing literature on corporate tax avoidance behavior. Further, the keyword network analysis has been used to find out the most explored and dry research areas related to corporate tax avoidance behavior using VOSviewer software.

The study finds that taxation decision is an important managerial decision. Managers adopt tax avoidance tactics to boost postax profits to meet the shareholders’ expectations, particularly of risk-averse shareholders, and sometimes for their benefit also. With this, this study also finds that firms’ characteristics, political connections and corporate social responsibility activities also impact taxation decisions. In addition, the study identifies that tax-avoiding behavior has a contradictory impact on firm value, market growth and corporate transparency disclosure decisions.

The study assists the researchers by providing a brief overview of tax avoidance behavior, for corporates in understanding the implications of tax avoidance, and for policymakers to fix the taxation loopholes and bring necessary tax reforms.

This study adds to the existing literature by providing a thorough overview of theories, determinants and outcomes of corporate tax avoidance behavior.

Today, customers are generally perceived to be demanding higher quality and better performing products, in shorter and more predictable development cycle-times and at a lower cost. These market pressures drive firms to collaborate with possible partners in product development (PD) processes. However, the selection of a suitable partner for an effective PD is not an easy decision and is associated with complexity. The purpose of this paper is to propose an integrated multi-criteria decision-making (MCDM) approach to effectively evaluate PD partners.

The proposed evaluation procedure consists of several steps. First, based on a literature review and expert validation, the strategic main and sub-criteria of the PD partner selection process that companies consider the most important are identified. After constructing the evaluation criteria hierarchy, the criteria weights are calculated by applying the Analytic Hierarchy Process (AHP) method. The VIKOR (a compromise ranking) method is used to obtain the final partner ranking results. A case study is given to demonstrate the potential of the methodology. In the last part of the study, a sensitivity analysis is performed to determine the influence of criteria weights on the decision making process.

The PD partner evaluation model contains three main criteria, namely, partner, collaboration and PD-oriented criteria, with 13 sub-criteria. The market position, competency of the partner, compatibility, technical expertise and complementarity are found as the most considerable evaluation criteria for the ABC case company. Results of the sensitivity analysis from different cases demonstrate that the integrated AHP-VIKOR model is quite sensitive to the weights assigned to the evaluation criteria. This finding underlines the importance of forming a capable, qualified group of experts for the decision-making procedure. The results of the empirical study show that the proposed evaluation framework is practical for solving partner selection problems.

Partner selection is critical to the success of a collaborative PD process. The main contribution of this paper is the definition and development of an effective evaluation framework to guide managers for suitable PD partner selection. In our knowledge, there exists no study in the literature that combines the established AHP VIKOR model for PD partner selection problem. This study can be useful to researchers to better understand PD partner selection problem theoretically, as well as to organizations in designing better satisfying PD partner evaluation systems.

This study aims to reveal whether social capital has an effect on the housing price index in Turkey, which is a developing country. The research was carried out by using the data on the basis of 81 provinces of Turkey in a 12-year period covering the years 2007–2018.

The data were subjected to panel data regression analysis and the related models were tested using the Driscoll-Kraay (1998) Estimator.

According to the results of the analysis, it was understood that there is a negative and significant relationship between social capital (SC1) and the housing price index. The results were corroborated by susceptibility testing. As the level of social capital rises in the provinces in Turkey, the manipulative and opportunistic behavior tendencies of individual and corporate house sellers decrease. These results support the principal–agent theory and theory of moral hazard, which constitute the theoretical background of the study.

No study has been found in the literature on the effect of social capital on housing prices. This situation constitutes the main motivation source of the study and shows its originality.

The purpose of this paper is to explore the continuous identification of tangible and intangible strategic resources needed to achieve competitive advantages in uncertain times in Spanish wineries, highlighting the critical value of human capital.

By means of a case study of a Spanish Sherry winery theoretically based on the resource-based view (RBV) of the firm, the paper focuses on the influence of environmental uncertainty on firms’ strategic resources and the need for in-depth knowledge. Direct participation and experience in the business have allowed access to data for longitudinal exploratory analysis.

Human capital, especially managers’ knowledge and experience, has been the key to the survival and success of the company analysed, throughout its history.

The paper guides managers, especially in microenterprises and SMEs, on the inclusion among the firm’s strategic resources of a part of their own human capital that is generally not considered.

This paper contributes to the RBV and self-reflection theory by demonstrating the value of human capital in a small family business under extremely uncertain times.

This paper aims to examine how organizational practices such as climate for conflict management (CCM) and high involvement work practices (HIWPs) reduce the negative consequences of workplace bullying (WPB) on work-related depression (WRD).

Data were collected from 468 full-time employees working in the financial sector in Türkiye by applying a student-recruited sampling strategy. The aforesaid relationships were assessed using SPSS AMOS 29.

The results indicated that WPB leads to WRD; however, this effect is alleviated by employee perceptions of strong CCM and the administration of HIWPs in workplace settings.

Collecting data from a single source poses the risks of self-report data bias; however, in the future, data may be collected from multiple sources to lessen this potential threat. The study was a cross-sectional study, which makes it hard to make casual inferences; longitudinal data would be more beneficial to establish casual associations.

Business owners and managers can draw from the study results to create a work environment perceived by employees to be fair when dealing with conflicts and the negative vices of bullying in workplaces. Also, organizations may administer practices that empower employees’ confidence and competence to deal with negative persecution in organizations.

Few studies, if any, have focused on examining the moderating effect of CCM and HIWPs in the association between WPB and WRD. Drawing upon conservation of resources theory, the study stands out as it tests the moderating effect of CCM and HIWPs in the connection between WPB and WRD. The findings contribute to the few available studies tackling organizational factors relevant to alleviating the negative consequences of WPB in organizations.

Drawing on knowledge-based theory, contingency theory of leadership, social learning theory and resource-based view, this study aims to investigate the relationships among knowledge-oriented leadership (KOL), knowledge management capacity (KMC), innovation performance (IP) and organizational performance (OP).

The relationships were examined using the serial mediation model of Hayes (2013). Data were collected from the firms (N = 502) operating in technology development zones in Turkey. The sample size corresponds to 10% of total number of the firms. Within the scope of a policy called National Technology Move by public authority, Turkey has been making strong investments to produce original and advanced technology products. A significant portion of these investments is directed toward technology development zones. Therefore, research on this topic may be of interest in Turkey. It should also be noted that Turkey is a developing country and is one of the world’s 20 largest economies.

The findings show that KMC and IP serially mediate the effect of KOL on OP. In the light of the findings, KOL establishes the eligible conditions for the improvement of KMC. Enhanced KMC transforms into innovation, and as a result, OP increases. As a result, this research shows that Turkish firms under the leadership of knowledge-oriented leaders have high KMC, innovation performance and firm performance. These findings can serve as a valuable benchmark for future studies in developing countries.

The current research has several limitations. It was carried out on the firms operating in technology development zones in Turkey. Future researches can be conducted on the firms outside the technology development zones. Second, this research was carried out in Turkey. The study was conducted in a specific national context covering only Turkish firms. It is recommended that readers be cautious when generalizing the results to different contexts (e.g. other countries and industries). Future researches can be conducted on the firms located in technology development zones in different countries. This may allow the comparison of countries. Turkey is a developing country. For this reason, developing countries should be taken into consideration in the comparison between countries, not developed countries such as the USA and European countries. Third, this is a cross-sectional study. Therefore, it does not reveal the changes in research variables over time. Longitudinal data collection is recommended for future researches.

The research findings are turned into a slogan and the firms are recommended the following perspective: more innovation for strong performance; a strong KMC for innovation; and for all, a strong knowledge-oriented leadership.

KOL is a quite new research field. The current study makes a significant contribution to the literature by revealing the fact that KOL is effective in increasing OP. In addition, testing via the serial mediation model the relationships which put forward how KOL increases OP, this study sheds light on organizational outcomes of KOL. There is an important gap in the search for leadership characteristics that allow knowledge-intensive firms to improve their KMC, innovation and firm performance. Therefore, this research is an important step toward filling this gap.