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This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

We consider a joint optimization problem of product platform design and scheduling on unrelated additive/subtractive hybrid machines, and seek to find efficient solution approaches to solve such problem.

We propose a mathematical formulation for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines, and develop a simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length to solve the problem.

The simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length (SAHH-osla) that we proposed can be quite efficient in solving the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

To the best of our knowledge, we are one of the first to consider both cost-related and time-related criteria for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

By using a wide range of macro and micro factors, this paper aims to provide a new assessment of the recent literature on inbound tourism demand models.

This study examines the determinants and spatial effects of inbound tourism using Hausman–Taylor and spatial econometric models.

Several important factors were identified, including local economic growth, openness to the outside world, regional size, geographic distance, foreign direct investment, level of innovation and average annual temperature. In addition, the study found strong cross-city competition effects on tourism resource endowment and hotel infrastructure.

Inbound tourism is a crucial link in achieving high-quality economic development. However, previous studies have mainly focused on the analysis of single influencing factors, ignoring the spatial spillover effects of factors.

This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

Based on the conservation of resource theory and the affective events theory, the study aims to explore the role of workplace incivility in predicting work engagement through emotional exhaustion and how psychological capital moderates this relationship.

Using the questionnaire survey with a sample of 278 restaurant employees in Ghana and through process macro analysis, the hypotheses were tested.

The results depict the mediating role of emotional exhaustion on the workplace incivility–engagement relationship. Also, the level of an individual’s psychological capital buffers the impact of workplace incivility on engagement through emotional exhaustion. When psychological capital is high, the negative effect of workplace incivility on work engagement through emotional exhaustion weakens.

The findings suggest that organizations, particularly those in developing economies in Africa, can derive immense benefit from giving psychological capital training to employees to help buffer the effects of incivility on engagement through emotional exhaustion.

With a focus on a developing economy in Africa, to the best of the author’s knowledge, this study is novel in exploring the mediating and moderating mechanisms of the incivility–engagement relationship.

This study’s aim is to introduce a high-performance sorbent for the removal of both anionic (Congo red; CR) and cationic (methylene blue; MB) dyes from aqueous solutions.

Sodium silicate is adopted as a substrate for GO and AgNPs with positive charge are used as modifiers. The synthesized nanocomposite is characterized by FTIR, FESEM, EDS, BET and XRD techniques. Then, some of the most effective parameters on the removal of CR and MB dyes such as solution pH, sorbent dose, adsorption equilibrium time, primary dye concentration and salt effect are optimized using the spectrophotometry technique.

The authors successfully achieved notable maximum adsorption capacities (Qmax) of CR and MB, which were 41.15 and 37.04 mg g⁻¹, respectively. The required equilibrium times for maximum efficiency of the developed sorbent were 10 and 15 min for CR and MB dyes, respectively. Adsorption equilibrium data present a good correlation with Langmuir isotherm, with a correlation coefficient of R2 = 0.9924 for CR and R2 = 0.9904 for MB, and kinetic studies prove that the dye adsorption process follows pseudo second-order models (CR R2 = 0.9986 and MB R2 = 0.9967).

The results showed that the proposed mechanism for the function of the developed sorbent in dye adsorption was based on physical and multilayer adsorption for both dyes onto the active sites of non-homogeneous sorbent.

The as-prepared nano-adsorbent has a high ability to remove both cationic and anionic dyes; moreover, to the high efficiency of the adsorbent, it has been tried to make its synthesis steps as simple as possible using inexpensive and available materials.

The objective of this paper is to develop a condition-based maintenance (CBM) scheme for pneumatic cylinders. The CBM scheme will detect two common types of air leaking failure modes and identify the leaky/faulty cylinder. The successful implementation of the proposed scheme will reduce energy consumption, scrap and rework, and time to repair.

Effective implementation of maintenance is important to reduce operation cost, improve productivity and enhance quality performance at the same time. Condition-based monitoring is an effective maintenance scheme where maintenance is triggered based on the condition of the equipment monitored either real time or at certain intervals. Pneumatic air systems are commonly used in many industries for packaging, sorting and powering air tools among others. A common failure mode of pneumatic cylinders is air leaks which is difficult to detect for complex systems with many connections. The proposed method consists of monitoring the stroke speed profile of the piston inside the pneumatic cylinder using hall effect sensors. Statistical features are extracted from the speed profiles and used to develop a fault detection machine learning model. The proposed method is demonstrated using a real-life case of tea packaging machines.

Based on the limited data collected, the ensemble machine learning algorithm resulted in 88.4% accuracy. The algorithm can detect failures as soon as they occur based on majority vote rule of three machine learning models.

Early air leak detection will improve quality of packaged tea bags and provide annual savings due to time to repair and energy waste reduction. The average annual estimated savings due to the implementation of the new CBM method is $229,200 with a payback period of less than two years.

To the best of the authors’ knowledge, this paper is the first in terms of proposing a CBM for pneumatic systems air leaks using piston speed. Majority, if not all, current detection methods rely on expensive equipment such as infrared or ultrasonic sensors. This paper also contributes to the research gap of economic justification of using CBM.

Attracting resources (financial and non-financial), supporters and the community’s attention to sports and physical activity has become essential for local sports associations (LSAs). Corporate social responsibility (CSR) initiatives are innovative and less imitable tools for strengthening relationships with customers (Lim et al., 2018), and there needs to be relevant research on CSR and the variables discussed in this study at the level of small sports organizations. Moreover, past research has focused on professional sports organizations in developed and non-Islamic countries. So, the following research questions are: What is the influence of CSR initiatives on the organizational reputation, brand equity and customer satisfaction of LSAs operating in the context of recreational sports, particularly in Islamic developing countries, and how does this relationship evolve within the framework of small sports organizations?

Participants (n = 290) consisted of all customers who used the services of LSAs in the Islamic Republic of Iran). This research seeks to measure the relationship between variables within a causal model based on structural equation modeling.

This study critically examines the connection between CSR, customer satisfaction, organizational reputation and brand equity in LSAs. This study presents a model that explores how CSR influences customer satisfaction, reputation and brand equity in LSAs in developing countries.

Consequently, customers are likely to feel more satisfied with LSAs that demonstrate a commitment to CSR, and this leads to evaluations of the organization’s reputation and brand equity, ultimately resulting in outcomes for them.

This research presents a comprehensive theoretical model that examines the relationship between CSR, customer satisfaction, reputation and brand equity of LSAs in developing Islamic countries. LSAs must understand and recognize customer interests in social issues and their response to various CSR programs.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

This study aims to investigate the most effective approach for governments and enterprises to combat desertification by considering the governance cycle. The focus is on understanding how the government can incentivize enterprises to actively engage in desertification combat efforts.

Both the government and the enterprise are treated as rational entities, making strategic choices for joint participation in combating desertification. Recognizing the dynamic nature of the desertification combat area, differential game models are employed to identify the optimal mode for combating desertification.

The findings underscore the significant influence of the governance cycle duration on the selection of desertification combat modes for government and enterprise. A cooperative mode is best suited to a short governance cycle, while an ecological subsidy mode is optimal for a longer cycle. Enhancing governance technology and shortening the governance cycle are conducive to combating desertification. Reducing taxes alone may not be an effective control strategy; rather, the government can better motivate enterprises by adopting tax rate policies aligned with the chosen governance mode.

This research contributes by elucidating the impact mechanism of the government cycle’s length on the desertification combat process. The results may offer valuable insights for governments in formulating strategies to encourage corporate participation in combating desertification and provide theoretical support for selecting optimal desertification combat modes.